diff --git a/extensions-web/src/assistant-web/index.ts b/extensions-web/src/assistant-web/index.ts deleted file mode 100644 index 0a800d36d..000000000 --- a/extensions-web/src/assistant-web/index.ts +++ /dev/null @@ -1,198 +0,0 @@ -/** - * Web Assistant Extension - * Implements assistant management using IndexedDB - */ - -import { Assistant, AssistantExtension } from '@janhq/core' -import { getSharedDB } from '../shared/db' - -export default class AssistantExtensionWeb extends AssistantExtension { - private db: IDBDatabase | null = null - - private defaultAssistant: Assistant = { - avatar: '๐Ÿ‘‹', - thread_location: undefined, - id: 'jan', - object: 'assistant', - created_at: Date.now() / 1000, - name: 'Jan', - description: - 'Jan is a helpful desktop assistant that can reason through complex tasks and use tools to complete them on the user\'s behalf.', - model: '*', - instructions: - 'You are a helpful AI assistant. Your primary goal is to assist users with their questions and tasks to the best of your abilities.\n\n' + - 'When responding:\n' + - '- Answer directly from your knowledge when you can\n' + - '- Be concise, clear, and helpful\n' + - '- Admit when you\'re unsure rather than making things up\n\n' + - 'If tools are available to you:\n' + - '- Only use tools when they add real value to your response\n' + - '- Use tools when the user explicitly asks (e.g., "search for...", "calculate...", "run this code")\n' + - '- Use tools for information you don\'t know or that needs verification\n' + - '- Never use tools just because they\'re available\n\n' + - 'When using tools:\n' + - '- Use one tool at a time and wait for results\n' + - '- Use actual values as arguments, not variable names\n' + - '- Learn from each result before deciding next steps\n' + - '- Avoid repeating the same tool call with identical parameters\n\n' + - 'Remember: Most questions can be answered without tools. Think first whether you need them.\n\n' + - 'Current date: {{current_date}}', - tools: [ - { - type: 'retrieval', - enabled: false, - useTimeWeightedRetriever: false, - settings: { - top_k: 2, - chunk_size: 1024, - chunk_overlap: 64, - retrieval_template: `Use the following pieces of context to answer the question at the end. -{context} -Question: {question} -Helpful Answer:`, - }, - }, - ], - file_ids: [], - metadata: undefined, - } - - async onLoad() { - console.log('Loading Web Assistant Extension') - this.db = await getSharedDB() - - // Create default assistant if none exist - const assistants = await this.getAssistants() - if (assistants.length === 0) { - await this.createAssistant(this.defaultAssistant) - } - } - - onUnload() { - // Don't close shared DB, other extensions might be using it - this.db = null - } - - private ensureDB(): void { - if (!this.db) { - throw new Error('Database not initialized. Call onLoad() first.') - } - } - - async getAssistants(): Promise { - this.ensureDB() - - return new Promise((resolve, reject) => { - const transaction = this.db!.transaction(['assistants'], 'readonly') - const store = transaction.objectStore('assistants') - const request = store.getAll() - - request.onsuccess = () => { - resolve(request.result || []) - } - - request.onerror = () => { - reject(request.error) - } - }) - } - - async createAssistant(assistant: Assistant): Promise { - this.ensureDB() - - return new Promise((resolve, reject) => { - const transaction = this.db!.transaction(['assistants'], 'readwrite') - const store = transaction.objectStore('assistants') - - const assistantToStore = { - ...assistant, - created_at: assistant.created_at || Date.now() / 1000, - } - - const request = store.add(assistantToStore) - - request.onsuccess = () => { - console.log('Assistant created:', assistant.id) - resolve() - } - - request.onerror = () => { - console.error('Failed to create assistant:', request.error) - reject(request.error) - } - }) - } - - async updateAssistant(id: string, assistant: Partial): Promise { - this.ensureDB() - - return new Promise((resolve, reject) => { - const transaction = this.db!.transaction(['assistants'], 'readwrite') - const store = transaction.objectStore('assistants') - - // First get the existing assistant - const getRequest = store.get(id) - - getRequest.onsuccess = () => { - const existingAssistant = getRequest.result - if (!existingAssistant) { - reject(new Error(`Assistant with id ${id} not found`)) - return - } - - const updatedAssistant = { - ...existingAssistant, - ...assistant, - id, // Ensure ID doesn't change - } - - const putRequest = store.put(updatedAssistant) - - putRequest.onsuccess = () => resolve() - putRequest.onerror = () => reject(putRequest.error) - } - - getRequest.onerror = () => { - reject(getRequest.error) - } - }) - } - - async deleteAssistant(assistant: Assistant): Promise { - this.ensureDB() - - return new Promise((resolve, reject) => { - const transaction = this.db!.transaction(['assistants'], 'readwrite') - const store = transaction.objectStore('assistants') - const request = store.delete(assistant.id) - - request.onsuccess = () => { - console.log('Assistant deleted:', assistant.id) - resolve() - } - - request.onerror = () => { - console.error('Failed to delete assistant:', request.error) - reject(request.error) - } - }) - } - - async getAssistant(id: string): Promise { - this.ensureDB() - - return new Promise((resolve, reject) => { - const transaction = this.db!.transaction(['assistants'], 'readonly') - const store = transaction.objectStore('assistants') - const request = store.get(id) - - request.onsuccess = () => { - resolve(request.result || null) - } - - request.onerror = () => { - reject(request.error) - } - }) - } -} \ No newline at end of file diff --git a/extensions-web/src/index.ts b/extensions-web/src/index.ts index e45c2d71c..9e7f3aab3 100644 --- a/extensions-web/src/index.ts +++ b/extensions-web/src/index.ts @@ -5,18 +5,16 @@ import type { WebExtensionRegistry } from './types' -export { default as AssistantExtensionWeb } from './assistant-web' export { default as ConversationalExtensionWeb } from './conversational-web' export { default as JanProviderWeb } from './jan-provider-web' export { default as MCPExtensionWeb } from './mcp-web' // Re-export types -export type { - WebExtensionRegistry, +export type { + WebExtensionRegistry, WebExtensionModule, WebExtensionName, WebExtensionLoader, - AssistantWebModule, ConversationalWebModule, JanProviderWebModule, MCPWebModule @@ -24,7 +22,6 @@ export type { // Extension registry for dynamic loading export const WEB_EXTENSIONS: WebExtensionRegistry = { - 'assistant-web': () => import('./assistant-web'), 'conversational-web': () => import('./conversational-web'), 'jan-provider-web': () => import('./jan-provider-web'), 'mcp-web': () => import('./mcp-web'), diff --git a/extensions-web/src/types.ts b/extensions-web/src/types.ts index f98d761cc..47ef0be71 100644 --- a/extensions-web/src/types.ts +++ b/extensions-web/src/types.ts @@ -2,14 +2,10 @@ * Web Extension Types */ -import type { AssistantExtension, ConversationalExtension, BaseExtension, AIEngine, MCPExtension } from '@janhq/core' +import type { ConversationalExtension, BaseExtension, AIEngine, MCPExtension } from '@janhq/core' type ExtensionConstructorParams = ConstructorParameters -export interface AssistantWebModule { - default: new (...args: ExtensionConstructorParams) => AssistantExtension -} - export interface ConversationalWebModule { default: new (...args: ExtensionConstructorParams) => ConversationalExtension } @@ -22,10 +18,9 @@ export interface MCPWebModule { default: new (...args: ExtensionConstructorParams) => MCPExtension } -export type WebExtensionModule = AssistantWebModule | ConversationalWebModule | JanProviderWebModule | MCPWebModule +export type WebExtensionModule = ConversationalWebModule | JanProviderWebModule | MCPWebModule export interface WebExtensionRegistry { - 'assistant-web': () => Promise 'conversational-web': () => Promise 'jan-provider-web': () => Promise 'mcp-web': () => Promise diff --git a/src-tauri/src/core/mcp/constants.rs b/src-tauri/src/core/mcp/constants.rs index a93e62494..5ca605913 100644 --- a/src-tauri/src/core/mcp/constants.rs +++ b/src-tauri/src/core/mcp/constants.rs @@ -8,6 +8,12 @@ pub const MCP_BACKOFF_MULTIPLIER: f64 = 2.0; // Double the delay each time pub const DEFAULT_MCP_CONFIG: &str = r#"{ "mcpServers": { + "exa": { + "command": "npx", + "args": ["-y", "exa-mcp-server"], + "env": { "EXA_API_KEY": "YOUR_EXA_API_KEY_HERE" }, + "active": false + }, "browsermcp": { "command": "npx", "args": ["@browsermcp/mcp"], diff --git a/web-app/src/containers/DropdownAssistant.tsx b/web-app/src/containers/DropdownAssistant.tsx index 44a24e5e6..a75925002 100644 --- a/web-app/src/containers/DropdownAssistant.tsx +++ b/web-app/src/containers/DropdownAssistant.tsx @@ -28,7 +28,7 @@ const DropdownAssistant = () => { ) const selectedAssistant = - assistants.find((a) => a.id === currentAssistant.id) || assistants[0] + assistants.find((a) => a.id === currentAssistant?.id) || assistants[0] return ( <> diff --git a/web-app/src/containers/LeftPanel.tsx b/web-app/src/containers/LeftPanel.tsx index 2f4ce9ecc..8ddfdbd36 100644 --- a/web-app/src/containers/LeftPanel.tsx +++ b/web-app/src/containers/LeftPanel.tsx @@ -46,7 +46,7 @@ const mainMenus = [ title: 'common:assistants', icon: IconClipboardSmileFilled, route: route.assistant, - isEnabled: true, + isEnabled: PlatformFeatures[PlatformFeature.ASSISTANTS], }, { title: 'common:hub', diff --git a/web-app/src/hooks/useAppState.ts b/web-app/src/hooks/useAppState.ts index fe885e043..837ed8c38 100644 --- a/web-app/src/hooks/useAppState.ts +++ b/web-app/src/hooks/useAppState.ts @@ -50,7 +50,7 @@ export const useAppState = create()((set) => ({ const currentAssistant = useAssistant.getState().currentAssistant const selectedAssistant = - assistants.find((a) => a.id === currentAssistant.id) || assistants[0] + assistants.find((a) => a.id === currentAssistant?.id) || assistants[0] set(() => ({ streamingContent: content diff --git a/web-app/src/hooks/useAssistant.ts b/web-app/src/hooks/useAssistant.ts index eab1fffc9..577ff1283 100644 --- a/web-app/src/hooks/useAssistant.ts +++ b/web-app/src/hooks/useAssistant.ts @@ -2,10 +2,12 @@ import { getServiceHub } from '@/hooks/useServiceHub' import { Assistant as CoreAssistant } from '@janhq/core' import { create } from 'zustand' import { localStorageKey } from '@/constants/localStorage' +import { PlatformFeatures } from '@/lib/platform/const' +import { PlatformFeature } from '@/lib/platform/types' interface AssistantState { assistants: Assistant[] - currentAssistant: Assistant + currentAssistant: Assistant | null addAssistant: (assistant: Assistant) => void updateAssistant: (assistant: Assistant) => void deleteAssistant: (id: string) => void @@ -46,14 +48,31 @@ export const defaultAssistant: Assistant = { 'You are a helpful AI assistant. Your primary goal is to assist users with their questions and tasks to the best of your abilities.\n\nWhen responding:\n- Answer directly from your knowledge when you can\n- Be concise, clear, and helpful\n- Admit when youโ€™re unsure rather than making things up\n\nIf tools are available to you:\n- Only use tools when they add real value to your response\n- Use tools when the user explicitly asks (e.g., "search for...", "calculate...", "run this code")\n- Use tools for information you donโ€™t know or that needs verification\n- Never use tools just because theyโ€™re available\n\nWhen using tools:\n- Use one tool at a time and wait for results\n- Use actual values as arguments, not variable names\n- Learn from each result before deciding next steps\n- Avoid repeating the same tool call with identical parameters\n\nRemember: Most questions can be answered without tools. Think first whether you need them.\n\nCurrent date: {{current_date}}', } -export const useAssistant = create()((set, get) => ({ - assistants: [defaultAssistant], - currentAssistant: defaultAssistant, +// Platform-aware initial state +const getInitialAssistantState = () => { + if (PlatformFeatures[PlatformFeature.ASSISTANTS]) { + return { + assistants: [defaultAssistant], + currentAssistant: defaultAssistant, + } + } else { + return { + assistants: [], + currentAssistant: null, + } + } +} + +export const useAssistant = create((set, get) => ({ + ...getInitialAssistantState(), addAssistant: (assistant) => { set({ assistants: [...get().assistants, assistant] }) - getServiceHub().assistants().createAssistant(assistant as unknown as CoreAssistant).catch((error) => { - console.error('Failed to create assistant:', error) - }) + getServiceHub() + .assistants() + .createAssistant(assistant as unknown as CoreAssistant) + .catch((error) => { + console.error('Failed to create assistant:', error) + }) }, updateAssistant: (assistant) => { const state = get() @@ -63,25 +82,31 @@ export const useAssistant = create()((set, get) => ({ ), // Update currentAssistant if it's the same assistant being updated currentAssistant: - state.currentAssistant.id === assistant.id + state.currentAssistant?.id === assistant.id ? assistant : state.currentAssistant, }) // Create assistant already cover update logic - getServiceHub().assistants().createAssistant(assistant as unknown as CoreAssistant).catch((error) => { - console.error('Failed to update assistant:', error) - }) + getServiceHub() + .assistants() + .createAssistant(assistant as unknown as CoreAssistant) + .catch((error) => { + console.error('Failed to update assistant:', error) + }) }, deleteAssistant: (id) => { const state = get() - getServiceHub().assistants().deleteAssistant( - state.assistants.find((e) => e.id === id) as unknown as CoreAssistant - ).catch((error) => { - console.error('Failed to delete assistant:', error) - }) + getServiceHub() + .assistants() + .deleteAssistant( + state.assistants.find((e) => e.id === id) as unknown as CoreAssistant + ) + .catch((error) => { + console.error('Failed to delete assistant:', error) + }) // Check if we're deleting the current assistant - const wasCurrentAssistant = state.currentAssistant.id === id + const wasCurrentAssistant = state.currentAssistant?.id === id set({ assistants: state.assistants.filter((a) => a.id !== id) }) diff --git a/web-app/src/hooks/useChat.ts b/web-app/src/hooks/useChat.ts index 029dfe722..f56a650b6 100644 --- a/web-app/src/hooks/useChat.ts +++ b/web-app/src/hooks/useChat.ts @@ -73,7 +73,7 @@ export const useChat = () => { }, [provider, selectedProvider]) const selectedAssistant = - assistants.find((a) => a.id === currentAssistant.id) || assistants[0] + assistants.find((a) => a.id === currentAssistant?.id) || assistants[0] const getCurrentThread = useCallback(async () => { let currentThread = retrieveThread() @@ -237,7 +237,7 @@ export const useChat = () => { const builder = new CompletionMessagesBuilder( messages, - renderInstructions(currentAssistant?.instructions) + currentAssistant ? renderInstructions(currentAssistant.instructions) : undefined ) if (troubleshooting) builder.addUserMessage(message, attachments) @@ -284,10 +284,10 @@ export const useChat = () => { builder.getMessages(), abortController, availableTools, - currentAssistant.parameters?.stream === false ? false : true, + currentAssistant?.parameters?.stream === false ? false : true, { ...modelSettings, - ...currentAssistant.parameters, + ...(currentAssistant?.parameters || {}), } as unknown as Record ) diff --git a/web-app/src/hooks/useMessages.ts b/web-app/src/hooks/useMessages.ts index 8dba73b9b..fc9dcf793 100644 --- a/web-app/src/hooks/useMessages.ts +++ b/web-app/src/hooks/useMessages.ts @@ -29,7 +29,7 @@ export const useMessages = create()((set, get) => ({ const currentAssistant = useAssistant.getState().currentAssistant const selectedAssistant = - assistants.find((a) => a.id === currentAssistant.id) || assistants[0] + assistants.find((a) => a.id === currentAssistant?.id) || assistants[0] const newMessage = { ...message, diff --git a/web-app/src/lib/platform/const.ts b/web-app/src/lib/platform/const.ts index 5192a6d1e..c8beccf94 100644 --- a/web-app/src/lib/platform/const.ts +++ b/web-app/src/lib/platform/const.ts @@ -49,4 +49,7 @@ export const PlatformFeatures: Record = { // Extensions settings page - disabled for web [PlatformFeature.EXTENSIONS_SETTINGS]: isPlatformTauri(), + + // Assistant functionality - disabled for web + [PlatformFeature.ASSISTANTS]: isPlatformTauri(), } \ No newline at end of file diff --git a/web-app/src/lib/platform/types.ts b/web-app/src/lib/platform/types.ts index 48d917cab..64a8a2367 100644 --- a/web-app/src/lib/platform/types.ts +++ b/web-app/src/lib/platform/types.ts @@ -51,4 +51,7 @@ export enum PlatformFeature { // Extensions settings page management EXTENSIONS_SETTINGS = 'extensionsSettings', + + // Assistant functionality (creation, editing, management) + ASSISTANTS = 'assistants', } diff --git a/web-app/src/routes/assistant.tsx b/web-app/src/routes/assistant.tsx index 22e913445..bf4fd928c 100644 --- a/web-app/src/routes/assistant.tsx +++ b/web-app/src/routes/assistant.tsx @@ -10,6 +10,8 @@ import AddEditAssistant from '@/containers/dialogs/AddEditAssistant' import { DeleteAssistantDialog } from '@/containers/dialogs' import { AvatarEmoji } from '@/containers/AvatarEmoji' import { useTranslation } from '@/i18n/react-i18next-compat' +import { PlatformGuard } from '@/lib/platform/PlatformGuard' +import { PlatformFeature } from '@/lib/platform/types' // eslint-disable-next-line @typescript-eslint/no-explicit-any export const Route = createFileRoute(route.assistant as any)({ @@ -17,6 +19,14 @@ export const Route = createFileRoute(route.assistant as any)({ }) function Assistant() { + return ( + + + + ) +} + +function AssistantContent() { const { t } = useTranslation() const { assistants, addAssistant, updateAssistant, deleteAssistant } = useAssistant() diff --git a/web-app/src/routes/index.tsx b/web-app/src/routes/index.tsx index 0312fdaba..b3e7862e5 100644 --- a/web-app/src/routes/index.tsx +++ b/web-app/src/routes/index.tsx @@ -20,6 +20,8 @@ import DropdownAssistant from '@/containers/DropdownAssistant' import { useEffect } from 'react' import { useThreads } from '@/hooks/useThreads' import { useMobileScreen } from '@/hooks/useMediaQuery' +import { PlatformFeatures } from '@/lib/platform/const' +import { PlatformFeature } from '@/lib/platform/types' export const Route = createFileRoute(route.home as any)({ component: Index, @@ -57,7 +59,7 @@ function Index() { return (
- + {PlatformFeatures[PlatformFeature.ASSISTANTS] && }
- + {PlatformFeatures[PlatformFeature.ASSISTANTS] && }
-
+
({ mcpAutoApproveTools: false, mcpServersSettings: true, extensionsSettings: true, + assistants: true, } })) diff --git a/website/.gitignore b/website/.gitignore deleted file mode 100644 index 6240da8b1..000000000 --- a/website/.gitignore +++ /dev/null @@ -1,21 +0,0 @@ -# build output -dist/ -# generated types -.astro/ - -# dependencies -node_modules/ - -# logs -npm-debug.log* -yarn-debug.log* -yarn-error.log* -pnpm-debug.log* - - -# environment variables -.env -.env.production - -# macOS-specific files -.DS_Store diff --git a/website/API_SPEC_SYNC.md b/website/API_SPEC_SYNC.md deleted file mode 100644 index 7c2fb0e78..000000000 --- a/website/API_SPEC_SYNC.md +++ /dev/null @@ -1,183 +0,0 @@ -# API Specification Synchronization - -This document explains how the Jan Server API specification is kept in sync with the documentation. - -## Overview - -The Jan documentation automatically synchronizes with the Jan Server API specification to ensure the API reference is always up to date. This is managed through GitHub Actions workflows that can be triggered in multiple ways. - -## Synchronization Methods - -### 1. Automatic Daily Sync -- **Schedule**: Runs daily at 2 AM UTC -- **Branch**: `dev` -- **Behavior**: Fetches the latest spec and commits changes if any -- **Workflow**: `.github/workflows/update-cloud-api-spec.yml` - -### 2. Manual Trigger via GitHub UI -Navigate to Actions โ†’ "Update Cloud API Spec" โ†’ Run workflow - -Options: -- **Commit changes**: Whether to commit changes directly (default: true) -- **Custom spec URL**: Override the default API spec URL -- **Create PR**: Create a pull request instead of direct commit (default: false) - -### 3. Webhook Trigger (For Jan Server Team) - -Send a repository dispatch event to trigger an update: - -```bash -curl -X POST \ - -H "Accept: application/vnd.github.v3+json" \ - -H "Authorization: token YOUR_GITHUB_TOKEN" \ - https://api.github.com/repos/janhq/jan/dispatches \ - -d '{ - "event_type": "update-api-spec", - "client_payload": { - "spec_url": "https://api.jan.ai/api/swagger/doc.json" - } - }' -``` - -### 4. Local Development - -For local development, the spec is updated conditionally: - -```bash -# Force update the cloud spec -bun run generate:cloud-spec-force - -# Normal update (checks if update is needed) -bun run generate:cloud-spec - -# Update both local and cloud specs -bun run generate:specs -``` - -## Configuration - -### Environment Variables - -The following environment variables can be configured in GitHub Secrets: - -| Variable | Description | Default | -|----------|-------------|---------| -| `JAN_SERVER_SPEC_URL` | URL to fetch the OpenAPI spec | `https://api.jan.ai/api/swagger/doc.json` | -| `JAN_SERVER_PROD_URL` | Production API base URL | `https://api.jan.ai/v1` | -| `JAN_SERVER_STAGING_URL` | Staging API base URL | `https://staging-api.jan.ai/v1` | - -### Build Behavior - -| Context | Behavior | -|---------|----------| -| Pull Request | Uses existing spec (no update) | -| Push to dev | Uses existing spec (no update) | -| Scheduled run | Updates spec and commits changes | -| Manual trigger | Updates based on input options | -| Webhook | Updates and creates PR | -| Local dev | Updates if spec is >24hrs old or missing | - -## Workflow Integration - -### For Jan Server Team - -When deploying a new API version: - -1. **Option A: Automatic PR** - - Deploy your API changes - - Trigger the webhook (see above) - - Review and merge the created PR - -2. **Option B: Manual Update** - - Go to [Actions](https://github.com/janhq/jan/actions/workflows/update-cloud-api-spec.yml) - - Click "Run workflow" - - Select options: - - Set "Create PR" to `true` for review - - Or leave as `false` for direct commit - -3. **Option C: Wait for Daily Sync** - - Changes will be picked up automatically at 2 AM UTC - -### For Documentation Team - -The API spec updates are handled automatically. However, you can: - -1. **Force an update**: Run the "Update Cloud API Spec" workflow manually -2. **Test locally**: Use `bun run generate:cloud-spec-force` -3. **Review changes**: Check PRs labeled with `api` and `automated` - -## Fallback Mechanism - -If the Jan Server API is unavailable: - -1. The workflow will use the last known good spec -2. Local builds will fall back to the local OpenAPI spec -3. The build will continue without failing - -## Monitoring - -### Check Update Status - -1. Go to [Actions](https://github.com/janhq/jan/actions/workflows/update-cloud-api-spec.yml) -2. Check the latest run status -3. Review the workflow summary for details - -### Notifications - -To add Slack/Discord notifications: - -1. Add webhook URL to GitHub Secrets -2. Uncomment notification section in workflow -3. Configure message format as needed - -## Troubleshooting - -### Spec Update Fails - -1. Check if the API endpoint is accessible -2. Verify the spec URL is correct -3. Check GitHub Actions logs for errors -4. Ensure proper permissions for the workflow - -### Changes Not Appearing - -1. Verify the workflow completed successfully -2. Check if changes were committed to the correct branch -3. Ensure the build is using the updated spec -4. Clear CDN cache if using Cloudflare - -### Manual Recovery - -If automated updates fail: - -```bash -# Clone the repository -git clone https://github.com/janhq/jan.git -cd jan/website - -# Install dependencies -bun install - -# Force update the spec -FORCE_UPDATE=true bun run generate:cloud-spec - -# Commit and push -git add public/openapi/cloud-openapi.json -git commit -m "chore: manual update of API spec" -git push -``` - -## Best Practices - -1. **Version Control**: Always review significant API changes before merging -2. **Testing**: Test the updated spec locally before deploying -3. **Communication**: Notify the docs team of breaking API changes -4. **Monitoring**: Set up alerts for failed spec updates -5. **Documentation**: Update this guide when changing the sync process - -## Support - -For issues or questions: -- Open an issue in the [Jan repository](https://github.com/janhq/jan/issues) -- Contact the documentation team on Discord -- Check the [workflow runs](https://github.com/janhq/jan/actions) for debugging \ No newline at end of file diff --git a/website/README.md b/website/README.md deleted file mode 100644 index 659e09ccc..000000000 --- a/website/README.md +++ /dev/null @@ -1,48 +0,0 @@ -# Jan's Website - -This website is [built with Starlight](https://starlight.astro.build) - - -Starlight looks for `.md` or `.mdx` files in the `src/content/docs/` directory. Each file is exposed -as a route based on its file name. - -Images can be added to `src/assets/` and embedded in Markdown with a relative link. - -Static assets, like favicons, can be placed in the `public/` directory. - -If you want to add new pages, these can go in the `src/pages/` directory. Because of the topics plugin -we are using ([starlight sidebar topics](https://starlight-sidebar-topics.netlify.app/docs/guides/excluded-pages/)) -you will need to exclude them from the sidebar by adding them to the exclude list in `astro.config.mjs`, e.g., `exclude: ['/example'],`. - -## ๐Ÿงž Commands - -All commands are run from the root of the project, from a terminal: - -| Command | Action | -| :------------------------ | :----------------------------------------------- | -| `bun install` | Installs dependencies | -| `bun dev` | Starts local dev server at `localhost:4321` | -| `bun build` | Build your production site to `./dist/` | -| `bun preview` | Preview your build locally, before deploying | -| `bun astro ...` | Run CLI commands like `astro add`, `astro check` | -| `bun astro -- --help` | Get help using the Astro CLI | - -## ๐Ÿ“– API Reference Commands - -The website includes interactive API documentation. These commands help manage the OpenAPI specifications: - -| Command | Action | -| :------------------------------- | :-------------------------------------------------------- | -| `bun run api:dev` | Start dev server with API reference at `/api` | -| `bun run api:local` | Start dev server with local API docs at `/api-reference/local` | -| `bun run api:cloud` | Start dev server with cloud API docs at `/api-reference/cloud` | -| `bun run generate:local-spec` | Generate/fix the local OpenAPI specification | -| `bun run generate:cloud-spec` | Generate the cloud OpenAPI specification from Jan Server | -| `bun run generate:cloud-spec-force` | Force update cloud spec (ignores cache/conditions) | - -**API Reference Pages:** -- `/api` - Landing page with Local and Server API options -- `/api-reference/local` - Local API (llama.cpp) documentation -- `/api-reference/cloud` - Jan Server API (vLLM) documentation - -The cloud specification is automatically synced via GitHub Actions on a daily schedule and can be manually triggered by the Jan Server team. diff --git a/website/astro.config.mjs b/website/astro.config.mjs deleted file mode 100644 index 922f1a860..000000000 --- a/website/astro.config.mjs +++ /dev/null @@ -1,306 +0,0 @@ -// @ts-check -import { defineConfig } from 'astro/config' -import starlight from '@astrojs/starlight' -import starlightThemeRapide from 'starlight-theme-rapide' -import starlightSidebarTopics from 'starlight-sidebar-topics' -import starlightUtils from '@lorenzo_lewis/starlight-utils' -import react from '@astrojs/react' - -import mermaid from 'astro-mermaid' -import { fileURLToPath } from 'url' -import path, { dirname } from 'path' - -const __filename = fileURLToPath(import.meta.url) -const __dirname = dirname(__filename) - -// https://astro.build/config -export default defineConfig({ - // Deploy to the new v2 subdomain - site: 'https://docs.jan.ai', - integrations: [ - react(), - mermaid({ - theme: 'default', - autoTheme: true, - }), - starlight({ - title: '๐Ÿ‘‹ Jan', - favicon: 'favicon.ico', - customCss: ['./src/styles/global.css'], - head: [ - { - tag: 'script', - attrs: { src: '/scripts/inject-navigation.js', defer: true }, - }, - { - tag: 'link', - attrs: { rel: 'stylesheet', href: '/styles/navigation.css' }, - }, - ], - - plugins: [ - starlightThemeRapide(), - starlightSidebarTopics( - [ - { - label: 'Jan', - link: '/', - icon: 'rocket', - items: [{ label: 'Ecosystem', slug: 'index' }], - }, - { - label: 'Jan Desktop', - link: '/jan/quickstart', - icon: 'rocket', - items: [ - { - label: '๐Ÿš€ QUICK START', - items: [ - { label: 'Getting Started', slug: 'jan/quickstart' }, - { - label: 'Install Jan', - collapsed: false, - autogenerate: { directory: 'jan/installation' }, - }, - { label: 'AI Assistants', slug: 'jan/assistants' }, - ], - }, - { - label: '๐Ÿค– MODELS', - items: [ - { label: 'Overview', slug: 'jan/manage-models' }, - { - label: 'Jan Models', - collapsed: false, - items: [ - { - label: 'Jan v1', - slug: 'jan/jan-models/jan-v1', - }, - { - label: 'Research Models', - collapsed: true, - items: [ - { - label: 'Jan Nano 32k', - slug: 'jan/jan-models/jan-nano-32', - }, - { - label: 'Jan Nano 128k', - slug: 'jan/jan-models/jan-nano-128', - }, - { - label: 'Lucy', - slug: 'jan/jan-models/lucy', - }, - ], - }, - ], - }, - { - label: 'Cloud Providers', - collapsed: true, - items: [ - { label: 'OpenAI', slug: 'jan/remote-models/openai' }, - { - label: 'Anthropic', - slug: 'jan/remote-models/anthropic', - }, - { label: 'Gemini', slug: 'jan/remote-models/google' }, - { label: 'Groq', slug: 'jan/remote-models/groq' }, - { - label: 'Mistral', - slug: 'jan/remote-models/mistralai', - }, - { label: 'Cohere', slug: 'jan/remote-models/cohere' }, - { - label: 'OpenRouter', - slug: 'jan/remote-models/openrouter', - }, - { - label: 'HuggingFace ๐Ÿค—', - slug: 'jan/remote-models/huggingface', - }, - ], - }, - { - label: 'Custom Providers', - slug: 'jan/custom-provider', - }, - { - label: 'Multi-Modal Models', - slug: 'jan/multi-modal', - }, - ], - }, - { - label: '๐Ÿ”ง TOOLS & INTEGRATIONS', - items: [ - { label: 'What is MCP?', slug: 'jan/mcp' }, - { - label: 'Examples & Tutorials', - collapsed: true, - items: [ - { - label: 'Web & Search', - collapsed: true, - items: [ - { - label: 'Browser Control', - slug: 'jan/mcp-examples/browser/browserbase', - }, - { - label: 'Serper Search', - slug: 'jan/mcp-examples/search/serper', - }, - { - label: 'Exa Search', - slug: 'jan/mcp-examples/search/exa', - }, - ], - }, - { - label: 'Data & Analysis', - collapsed: true, - items: [ - { - label: 'Jupyter Notebooks', - slug: 'jan/mcp-examples/data-analysis/jupyter', - }, - { - label: 'Code Sandbox (E2B)', - slug: 'jan/mcp-examples/data-analysis/e2b', - }, - { - label: 'Deep Financial Research', - slug: 'jan/mcp-examples/deepresearch/octagon', - }, - ], - }, - { - label: 'Productivity', - collapsed: true, - items: [ - { - label: 'Linear', - slug: 'jan/mcp-examples/productivity/linear', - }, - { - label: 'Todoist', - slug: 'jan/mcp-examples/productivity/todoist', - }, - ], - }, - { - label: 'Creative', - collapsed: true, - items: [ - { - label: 'Design with Canva', - slug: 'jan/mcp-examples/design/canva', - }, - ], - }, - ], - }, - ], - }, - { - label: 'โš™๏ธ DEVELOPER', - items: [ - { - label: 'Local API Server', - collapsed: true, - items: [ - { label: 'Overview', slug: 'local-server' }, - { - label: 'API Configuration', - slug: 'local-server/api-server', - }, - { - label: 'Engine Settings', - slug: 'local-server/llama-cpp', - }, - { - label: 'Server Settings', - slug: 'local-server/settings', - }, - { - label: 'Integrations', - collapsed: true, - autogenerate: { - directory: 'local-server/integrations', - }, - }, - ], - }, - { - label: 'Technical Details', - collapsed: true, - items: [ - { - label: 'Model Parameters', - slug: 'jan/explanation/model-parameters', - }, - ], - }, - ], - }, - { - label: '๐Ÿ“š REFERENCE', - items: [ - { label: 'Settings', slug: 'jan/settings' }, - { label: 'Data Folder', slug: 'jan/data-folder' }, - { label: 'Troubleshooting', slug: 'jan/troubleshooting' }, - { label: 'Privacy Policy', slug: 'jan/privacy' }, - ], - }, - ], - }, - { - label: 'Browser Extension', - link: '/browser/', - badge: { text: 'Alpha', variant: 'tip' }, - icon: 'puzzle', - items: [{ label: 'Overview', slug: 'browser' }], - }, - { - label: 'Jan Mobile', - link: '/mobile/', - badge: { text: 'Soon', variant: 'caution' }, - icon: 'phone', - items: [{ label: 'Overview', slug: 'mobile' }], - }, - { - label: 'Jan Server', - link: '/server/', - badge: { text: 'Soon', variant: 'caution' }, - icon: 'forward-slash', - items: [{ label: 'Overview', slug: 'server' }], - }, - ], - { - exclude: ['/api-reference', '/api-reference/**/*'], - } - ), - ], - social: [ - { - icon: 'github', - label: 'GitHub', - href: 'https://github.com/menloresearch/jan', - }, - { - icon: 'x.com', - label: 'X', - href: 'https://twitter.com/jandotai', - }, - { - icon: 'discord', - label: 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High-performance, scalable inference service with automatic batching and optimized memory management.", - "title": "๐Ÿ‘‹Jan Server API", - "contact": { - "name": "Jan Server Support", - "url": "https://jan.ai/support", - "email": "support@jan.ai" - }, - "version": "1.0", - "x-logo": { - "url": "https://jan.ai/logo.png", - "altText": "๐Ÿ‘‹Jan Server API" - }, - "license": { - "name": "Apache 2.0", - "url": "https://github.com/menloresearch/jan/blob/main/LICENSE" - } - }, - "host": "", - "basePath": "/", - "paths": { - "/jan/v1/auth/google/callback": { - "post": { - "description": "Handles the callback from the Google OAuth2 provider to exchange the authorization code for a token, verify the user, and issue access and refresh tokens.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Authentication" - ], - "summary": "Google OAuth2 Callback", - "parameters": [ - { - "description": "Request body containing the authorization code and state", - "name": "request", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_auth_google.GoogleCallbackRequest" - } - } - ], - "responses": { - "200": { - "description": "Successfully authenticated and returned tokens", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_auth_google_GoogleCallbackResponse" - } - }, - "400": { - "description": "Bad request (e.g., invalid state, missing code, or invalid claims)", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized (e.g., a user claim is not found or is invalid in the context)", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal Server Error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - }, - "security": [ - { - "bearerAuth": [] - } - ] - } - }, - "/jan/v1/auth/google/login": { - "get": { - "description": "Redirects the user to the Google OAuth2 authorization page to initiate the login process.", - "tags": [ - "Jan", - "Jan-Authentication" - ], - "summary": "Google OAuth2 Login", - "responses": { - "307": { - "description": "Redirects to Google's login page" - }, - "500": { - "description": "Internal Server Error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - }, - "security": [ - { - "bearerAuth": [] - } - ] - } - }, - "/jan/v1/auth/guest-login": { - "post": { - "description": "JWT-base Guest Login.", - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Authentication" - ], - "summary": "Guest Login", - "responses": { - "200": { - "description": "Successfully refreshed the access token", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_auth_RefreshTokenResponse" - } - }, - "400": { - "description": "Bad Request (e.g., invalid refresh token)", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized (e.g., expired or missing refresh token)", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - }, - "security": [ - { - "bearerAuth": [] - } - ] - } - }, - "/jan/v1/auth/me": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves the profile of the authenticated user based on the provided JWT.", - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Authentication" - ], - "summary": "Get user profile", - "responses": { - "200": { - "description": "Successfully retrieved user profile", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_auth_GetMeResponse" - } - }, - "401": { - "description": "Unauthorized (e.g., missing or invalid JWT)", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/jan/v1/auth/refresh-token": { - "get": { - "description": "Use a valid refresh token to obtain a new access token. The refresh token is typically sent in a cookie.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Authentication" - ], - "summary": "Refresh an access token", - "responses": { - "200": { - "description": "Successfully refreshed the access token", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_auth_RefreshTokenResponse" - } - }, - "400": { - "description": "Bad Request (e.g., invalid refresh token)", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized (e.g., expired or missing refresh token)", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - }, - "security": [ - { - "bearerAuth": [] - } - ] - } - }, - "/jan/v1/chat/completions": { - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Generates a model response for the given chat conversation.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Chat" - ], - "summary": "Create a chat completion", - "parameters": [ - { - "description": "Chat completion request payload", - "name": "request", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/openai.ChatCompletionRequest" - } - } - ], - "responses": { - "200": { - "description": "Successful response", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_chat.ChatCompletionResponseSwagger" - } - }, - "400": { - "description": "Invalid request payload", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/jan/v1/conversations": { - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Creates a new conversation for the authenticated user", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Conversations" - ], - "summary": "Create a conversation", - "parameters": [ - { - "description": "Create conversation request", - "name": "request", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.CreateConversationRequest" - } - } - ], - "responses": { - "200": { - "description": "Created conversation", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationResponse" - } - }, - "400": { - "description": "Invalid request", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/jan/v1/conversations/{conversation_id}": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a conversation by its ID", - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Conversations" - ], - "summary": "Get a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Conversation details", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "delete": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Deletes a conversation and all its items", - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Conversations" - ], - "summary": "Delete a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Deleted conversation", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.DeletedConversationResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "patch": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Updates conversation metadata", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Conversations" - ], - "summary": "Update a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "description": "Update conversation request", - "name": "request", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.UpdateConversationRequest" - } - } - ], - "responses": { - "200": { - "description": "Updated conversation", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationResponse" - } - }, - "400": { - "description": "Invalid request", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/jan/v1/conversations/{conversation_id}/items": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Lists all items in a conversation", - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Conversations" - ], - "summary": "List items in a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "type": "integer", - "description": "Number of items to return (1-100)", - "name": "limit", - "in": "query" - }, - { - "type": "string", - "description": "Cursor for pagination", - "name": "cursor", - "in": "query" - }, - { - "type": "string", - "description": "Order of items (asc/desc)", - "name": "order", - "in": "query" - } - ], - "responses": { - "200": { - "description": "List of items", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemListResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Adds multiple items to a conversation", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Conversations" - ], - "summary": "Create items in a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "description": "Create items request", - "name": "request", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.CreateItemsRequest" - } - } - ], - "responses": { - "200": { - "description": "Created items", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemListResponse" - } - }, - "400": { - "description": "Invalid request", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/jan/v1/conversations/{conversation_id}/items/{item_id}": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a specific item from a conversation", - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Conversations" - ], - "summary": "Get an item from a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "type": "string", - "description": "Item ID", - "name": "item_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Item details", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "delete": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Deletes a specific item from a conversation", - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Conversations" - ], - "summary": "Delete an item from a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "type": "string", - "description": "Item ID", - "name": "item_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Updated conversation", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/jan/v1/mcp": { - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Handles Model Context Protocol (MCP) requests over an HTTP stream. The response is sent as a continuous stream of data.", - "consumes": [ - "application/json" - ], - "produces": [ - "text/event-stream" - ], - "tags": [ - "Jan", - "Jan-MCP" - ], - "summary": "MCP streamable endpoint", - "parameters": [ - { - "description": "MCP request payload", - "name": "request", - "in": "body", - "required": true, - "schema": {} - } - ], - "responses": { - "200": { - "description": "Streamed response (SSE or chunked transfer)", - "schema": { - "type": "string" - } - } - } - } - }, - "/jan/v1/models": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a list of available models that can be used for chat completions or other tasks.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Models" - ], - "summary": "List available models", - "responses": { - "200": { - "description": "Successful response", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1.ModelsResponse" - } - } - } - } - }, - "/jan/v1/organizations": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a list of organizations owned by the authenticated user.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Organizations" - ], - "summary": "List organizations", - "parameters": [ - { - "type": "integer", - "default": 10, - "description": "Number of organizations to return", - "name": "limit", - "in": "query" - }, - { - "type": "integer", - "default": 0, - "description": "Offset for pagination", - "name": "offset", - "in": "query" - } - ], - "responses": { - "200": { - "description": "Successfully retrieved organizations.", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ListResponse-app_interfaces_http_routes_jan_v1_organization_OrganizationResponse" - } - }, - "400": { - "description": "Bad request, e.g., invalid pagination parameters.", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized, e.g., invalid or missing token.", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error.", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/jan/v1/organizations/{org_public_id}/api_keys": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a list of all API keys associated with an organization.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Organizations" - ], - "summary": "List API keys for a specific organization", - "parameters": [ - { - "type": "string", - "description": "Organization Public ID", - "name": "org_public_id", - "in": "path", - "required": true - }, - { - "type": "integer", - "default": 0, - "description": "offset for pagination", - "name": "offset", - "in": "query" - }, - { - "type": "integer", - "default": 10, - "description": "Number of items per page", - "name": "limit", - "in": "query" - } - ], - "responses": { - "200": { - "description": "List of API keys retrieved successfully", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ListResponse-app_interfaces_http_routes_jan_v1_organization_api_keys_ApiKeyResponse" - } - }, - "400": { - "description": "Bad request, e.g., invalid pagination parameters", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized, e.g., invalid or missing token", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found, e.g., organization not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Creates a new API key with administrative permissions for a specific organization.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Organizations" - ], - "summary": "Create a new organization-level admin key", - "parameters": [ - { - "type": "string", - "description": "Organization Public ID", - "name": "org_public_id", - "in": "path", - "required": true - }, - { - "description": "Request body for creating an admin key", - "name": "requestBody", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_organization_api_keys.CreateAdminKeyRequest" - } - } - ], - "responses": { - "200": { - "description": "Admin API key created successfully", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_organization_api_keys_ApiKeyResponse" - } - }, - "400": { - "description": "Bad request, e.g., invalid payload or missing IDs", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized, e.g., invalid or missing token", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found, e.g., organization not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/jan/v1/organizations/{org_public_id}/projects": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "List all projects within a given organization.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Organizations" - ], - "summary": "List projects", - "parameters": [ - { - "type": "string", - "description": "Organization Public ID", - "name": "org_public_id", - "in": "path", - "required": true - }, - { - "type": "integer", - "default": 10, - "description": "Number of projects to return", - "name": "limit", - "in": "query" - }, - { - "type": "integer", - "default": 0, - "description": "Offset for pagination", - "name": "offset", - "in": "query" - } - ], - "responses": { - "200": { - "description": "Successfully retrieved projects", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ListResponse-app_interfaces_http_routes_jan_v1_organization_projects_ProjectResponse" - } - }, - "400": { - "description": "Bad request, e.g., invalid pagination parameters or organization ID", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized, e.g., invalid or missing token", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found, e.g., organization not found or no projects found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/jan/v1/organizations/{org_public_id}/projects/{project_public_id}/api_keys": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "List API keys for a specific project.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Organizations" - ], - "summary": "List new project API key", - "parameters": [ - { - "type": "string", - "description": "Organization Public ID", - "name": "org_public_id", - "in": "path", - "required": true - }, - { - "type": "string", - "description": "Project Public ID", - "name": "project_public_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "API key created successfully", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_organization_projects_api_keys_ApiKeyResponse" - } - }, - "400": { - "description": "Bad request, e.g., invalid payload or missing IDs", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized, e.g., invalid or missing token", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found, e.g., project or organization not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Creates a new API key for a specific project.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Jan", - "Jan-Organizations" - ], - "summary": "Create a new project API key", - "parameters": [ - { - "type": "string", - "description": "Organization Public ID", - "name": "org_public_id", - "in": "path", - "required": true - }, - { - "type": "string", - "description": "Project Public ID", - "name": "project_public_id", - "in": "path", - "required": true - }, - { - "description": "Request body for creating an API key", - "name": "requestBody", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_organization_projects_api_keys.CreateApiKeyRequest" - } - } - ], - "responses": { - "200": { - "description": "API key created successfully", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_organization_projects_api_keys_ApiKeyResponse" - } - }, - "400": { - "description": "Bad request, e.g., invalid payload or missing IDs", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized, e.g., invalid or missing token", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found, e.g., project or organization not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/chat/completions": { - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Generates a model response for the given chat conversation.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Chat" - ], - "summary": "Create a chat completion", - "parameters": [ - { - "description": "Chat completion request payload", - "name": "request", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/openai.ChatCompletionRequest" - } - } - ], - "responses": { - "200": { - "description": "Successful response", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_chat.ChatCompletionResponseSwagger" - } - }, - "400": { - "description": "Invalid request payload", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/conversations": { - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Creates a new conversation for the authenticated user", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Conversations" - ], - "summary": "Create a conversation", - "parameters": [ - { - "description": "Create conversation request", - "name": "request", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.CreateConversationRequest" - } - } - ], - "responses": { - "200": { - "description": "Created conversation", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationResponse" - } - }, - "400": { - "description": "Invalid request", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/conversations/{conversation_id}": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a conversation by its ID", - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Conversations" - ], - "summary": "Get a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Conversation details", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "delete": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Deletes a conversation and all its items", - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Conversations" - ], - "summary": "Delete a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Deleted conversation", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.DeletedConversationResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "patch": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Updates conversation metadata", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Conversations" - ], - "summary": "Update a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "description": "Update conversation request", - "name": "request", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.UpdateConversationRequest" - } - } - ], - "responses": { - "200": { - "description": "Updated conversation", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationResponse" - } - }, - "400": { - "description": "Invalid request", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/conversations/{conversation_id}/items": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Lists all items in a conversation", - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Conversations" - ], - "summary": "List items in a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "type": "integer", - "description": "Number of items to return (1-100)", - "name": "limit", - "in": "query" - }, - { - "type": "string", - "description": "Cursor for pagination", - "name": "cursor", - "in": "query" - }, - { - "type": "string", - "description": "Order of items (asc/desc)", - "name": "order", - "in": "query" - } - ], - "responses": { - "200": { - "description": "List of items", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemListResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Adds multiple items to a conversation", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Conversations" - ], - "summary": "Create items in a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "description": "Create items request", - "name": "request", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.CreateItemsRequest" - } - } - ], - "responses": { - "200": { - "description": "Created items", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemListResponse" - } - }, - "400": { - "description": "Invalid request", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/conversations/{conversation_id}/items/{item_id}": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a specific item from a conversation", - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Conversations" - ], - "summary": "Get an item from a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "type": "string", - "description": "Item ID", - "name": "item_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Item details", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "delete": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Deletes a specific item from a conversation", - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Conversations" - ], - "summary": "Delete an item from a conversation", - "parameters": [ - { - "type": "string", - "description": "Conversation ID", - "name": "conversation_id", - "in": "path", - "required": true - }, - { - "type": "string", - "description": "Item ID", - "name": "item_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Updated conversation", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationResponse" - } - }, - "401": { - "description": "Unauthorized", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "403": { - "description": "Access denied", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Conversation not found", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal server error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/mcp": { - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Handles Model Context Protocol (MCP) requests over an HTTP stream. The response is sent as a continuous stream of data.", - "consumes": [ - "application/json" - ], - "produces": [ - "text/event-stream" - ], - "tags": [ - "MCP" - ], - "summary": "MCP streamable endpoint", - "parameters": [ - { - "description": "MCP request payload", - "name": "request", - "in": "body", - "required": true, - "schema": {} - } - ], - "responses": { - "200": { - "description": "Streamed response (SSE or chunked transfer)", - "schema": { - "type": "string" - } - } - } - } - }, - "/v1/models": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a list of available models that can be used for chat completions or other tasks.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Models" - ], - "summary": "List available models", - "responses": { - "200": { - "description": "Successful response", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1.ModelsResponse" - } - } - } - } - }, - "/v1/organization/admin_api_keys": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a paginated list of all admin API keys for the authenticated organization.", - "tags": [ - "Platform", - "Platform-Organizations" - ], - "summary": "List Admin API Keys", - "parameters": [ - { - "type": "string", - "default": "\"Bearer \"", - "description": "Bearer token", - "name": "Authorization", - "in": "header", - "required": true - }, - { - "type": "integer", - "default": 20, - "description": "The maximum number of items to return", - "name": "limit", - "in": "query" - }, - { - "type": "string", - "description": "A cursor for use in pagination. The ID of the last object from the previous page", - "name": "after", - "in": "query" - } - ], - "responses": { - "200": { - "description": "Successfully retrieved the list of admin API keys", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization.AdminApiKeyListResponse" - } - }, - "401": { - "description": "Unauthorized - invalid or missing API key", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal Server Error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Creates a new admin API key for an organization. Requires a valid admin API key in the Authorization header.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Organizations" - ], - "summary": "Create Admin API Key", - "parameters": [ - { - "type": "string", - "default": "\"Bearer \"", - "description": "Bearer token", - "name": "Authorization", - "in": "header", - "required": true - }, - { - "description": "API key creation request", - "name": "body", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization.CreateOrganizationAdminAPIKeyRequest" - } - } - ], - "responses": { - "200": { - "description": "Successfully created admin API key", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization.OrganizationAdminAPIKeyResponse" - } - }, - "400": { - "description": "Bad request - invalid payload", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized - invalid or missing API key", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/organization/admin_api_keys/{id}": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a specific admin API key by its ID.", - "tags": [ - "Platform", - "Platform-Organizations" - ], - "summary": "Get Admin API Key", - "parameters": [ - { - "type": "string", - "default": "\"Bearer \"", - "description": "Bearer token", - "name": "Authorization", - "in": "header", - "required": true - }, - { - "type": "string", - "description": "ID of the admin API key", - "name": "id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Successfully retrieved the admin API key", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization.OrganizationAdminAPIKeyResponse" - } - }, - "401": { - "description": "Unauthorized - invalid or missing API key", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found - API key with the given ID does not exist or does not belong to the organization", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "delete": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Deletes an admin API key by its ID.", - "tags": [ - "Platform", - "Platform-Organizations" - ], - "summary": "Delete Admin API Key", - "parameters": [ - { - "type": "string", - "default": "\"Bearer \"", - "description": "Bearer token", - "name": "Authorization", - "in": "header", - "required": true - }, - { - "type": "string", - "description": "ID of the admin API key to delete", - "name": "id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Successfully deleted the admin API key", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization.AdminAPIKeyDeletedResponse" - } - }, - "401": { - "description": "Unauthorized - invalid or missing API key", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found - API key with the given ID does not exist or does not belong to the organization", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/organization/projects": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a paginated list of all projects for the authenticated organization.", - "tags": [ - "Platform", - "Platform-Organizations" - ], - "summary": "List Projects", - "parameters": [ - { - "type": "string", - "default": "\"Bearer \"", - "description": "Bearer token", - "name": "Authorization", - "in": "header", - "required": true - }, - { - "type": "integer", - "default": 20, - "description": "The maximum number of items to return", - "name": "limit", - "in": "query" - }, - { - "type": "string", - "description": "A cursor for use in pagination. The ID of the last object from the previous page", - "name": "after", - "in": "query" - }, - { - "type": "string", - "description": "Whether to include archived projects.", - "name": "include_archived", - "in": "query" - } - ], - "responses": { - "200": { - "description": "Successfully retrieved the list of projects", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization_projects.ProjectListResponse" - } - }, - "401": { - "description": "Unauthorized - invalid or missing API key", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal Server Error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Creates a new project for an organization.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Organizations" - ], - "summary": "Create Project", - "parameters": [ - { - "type": "string", - "default": "\"Bearer \"", - "description": "Bearer token", - "name": "Authorization", - "in": "header", - "required": true - }, - { - "description": "Project creation request", - "name": "body", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization_projects.CreateProjectRequest" - } - } - ], - "responses": { - "200": { - "description": "Successfully created project", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization_projects.ProjectResponse" - } - }, - "400": { - "description": "Bad request - invalid payload", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized - invalid or missing API key", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "500": { - "description": "Internal Server Error", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/organization/projects/{project_id}": { - "get": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Retrieves a specific project by its ID.", - "tags": [ - "Platform", - "Platform-Organizations" - ], - "summary": "Get Project", - "parameters": [ - { - "type": "string", - "default": "\"Bearer \"", - "description": "Bearer token", - "name": "Authorization", - "in": "header", - "required": true - }, - { - "type": "string", - "description": "ID of the project", - "name": "project_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Successfully retrieved the project", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization_projects.ProjectResponse" - } - }, - "401": { - "description": "Unauthorized - invalid or missing API key", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found - project with the given ID does not exist or does not belong to the organization", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - }, - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Updates a specific project by its ID.", - "consumes": [ - "application/json" - ], - "produces": [ - "application/json" - ], - "tags": [ - "Platform", - "Platform-Organizations" - ], - "summary": "Update Project", - "parameters": [ - { - "type": "string", - "default": "\"Bearer \"", - "description": "Bearer token", - "name": "Authorization", - "in": "header", - "required": true - }, - { - "type": "string", - "description": "ID of the project to update", - "name": "project_id", - "in": "path", - "required": true - }, - { - "description": "Project update request", - "name": "body", - "in": "body", - "required": true, - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization_projects.UpdateProjectRequest" - } - } - ], - "responses": { - "200": { - "description": "Successfully updated the project", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization_projects.ProjectResponse" - } - }, - "400": { - "description": "Bad request - invalid payload", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "401": { - "description": "Unauthorized - invalid or missing API key", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found - project with the given ID does not exist", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/organization/projects/{project_id}/archive": { - "post": { - "security": [ - { - "BearerAuth": [] - } - ], - "description": "Archives a specific project by its ID, making it inactive.", - "tags": [ - "Platform", - "Platform-Organizations" - ], - "summary": "Archive Project", - "parameters": [ - { - "type": "string", - "default": "\"Bearer \"", - "description": "Bearer token", - "name": "Authorization", - "in": "header", - "required": true - }, - { - "type": "string", - "description": "ID of the project to archive", - "name": "project_id", - "in": "path", - "required": true - } - ], - "responses": { - "200": { - "description": "Successfully archived the project", - "schema": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization_projects.ProjectResponse" - } - }, - "401": { - "description": "Unauthorized - invalid or missing API key", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - }, - "404": { - "description": "Not Found - project with the given ID does not exist", - "schema": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse" - } - } - } - } - }, - "/v1/version": { - "get": { - "description": "Returns the current build version of the API server.", - "produces": [ - "application/json" - ], - "tags": [ - "Jan Server" - ], - "summary": "Get API build version", - "responses": { - "200": { - "description": "version info", - "schema": { - "type": "object", - "additionalProperties": { - "type": "string" - } - } - } - }, - "security": [ - { - "bearerAuth": [] - } - ] - } - } - }, - "definitions": { - "app_interfaces_http_routes_jan_v1.Model": { - "type": "object", - "properties": { - "created": { - "type": "integer" - }, - "id": { - "type": "string" - }, - "object": { - "type": "string" - }, - "owned_by": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_jan_v1.ModelsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1.Model" - } - }, - "object": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_jan_v1_auth.GetMeResponse": { - "type": "object", - "properties": { - "email": { - "type": "string" - }, - "name": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_jan_v1_auth.RefreshTokenResponse": { - "type": "object", - "properties": { - "access_token": { - "type": "string" - }, - "expires_in": { - "type": "integer" - } - } - }, - "app_interfaces_http_routes_jan_v1_auth_google.GoogleCallbackRequest": { - "type": "object", - "required": [ - "code" - ], - "properties": { - "code": { - "type": "string" - }, - "state": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_jan_v1_auth_google.GoogleCallbackResponse": { - "type": "object", - "properties": { - "access_token": { - "type": "string" - }, - "expires_in": { - "type": "integer" - } - } - }, - "app_interfaces_http_routes_jan_v1_chat.ChatCompletionResponseSwagger": { - "type": "object", - "properties": { - "choices": { - "type": "array", - "items": { - "$ref": "#/definitions/openai.ChatCompletionChoice" - } - }, - "created": { - "type": "integer" - }, - "id": { - "type": "string" - }, - "model": { - "type": "string" - }, - "object": { - "type": "string" - }, - "usage": { - "$ref": "#/definitions/openai.Usage" - } - } - }, - "app_interfaces_http_routes_jan_v1_organization.OrganizationResponse": { - "type": "object", - "properties": { - "createdAt": { - "type": "string" - }, - "enabled": { - "type": "boolean" - }, - "name": { - "type": "string" - }, - "publicID": { - "type": "string" - }, - "updatedAt": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_jan_v1_organization_api_keys.ApiKeyResponse": { - "type": "object", - "properties": { - "apikeyType": { - "type": "string" - }, - "description": { - "type": "string" - }, - "enabled": { - "type": "boolean" - }, - "expiresAt": { - "type": "string" - }, - "id": { - "type": "string" - }, - "key": { - "type": "string" - }, - "last_usedAt": { - "type": "string" - }, - "permissions": { - "type": "string" - }, - "plaintextHint": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_jan_v1_organization_api_keys.CreateAdminKeyRequest": { - "type": "object", - "properties": { - "description": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_jan_v1_organization_projects.ProjectResponse": { - "type": "object", - "properties": { - "archivedAt": { - "type": "string" - }, - "createdAt": { - "type": "string" - }, - "name": { - "type": "string" - }, - "organizationID": { - "type": "integer" - }, - "publicID": { - "type": "string" - }, - "status": { - "type": "string" - }, - "updatedAt": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_jan_v1_organization_projects_api_keys.ApiKeyResponse": { - "type": "object", - "properties": { - "apikeyType": { - "type": "string" - }, - "description": { - "type": "string" - }, - "enabled": { - "type": "boolean" - }, - "expiresAt": { - "type": "string" - }, - "id": { - "type": "string" - }, - "key": { - "type": "string" - }, - "last_usedAt": { - "type": "string" - }, - "permissions": { - "type": "string" - }, - "plaintextHint": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_jan_v1_organization_projects_api_keys.CreateApiKeyRequest": { - "type": "object", - "properties": { - "description": { - "type": "string" - }, - "expiresAt": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_v1.Model": { - "type": "object", - "properties": { - "created": { - "type": "integer" - }, - "id": { - "type": "string" - }, - "object": { - "type": "string" - }, - "owned_by": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_v1.ModelsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/definitions/app_interfaces_http_routes_v1.Model" - } - }, - "object": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_v1_chat.ChatCompletionResponseSwagger": { - "type": "object", - "properties": { - "choices": { - "type": "array", - "items": { - "$ref": "#/definitions/openai.ChatCompletionChoice" - } - }, - "created": { - "type": "integer" - }, - "id": { - "type": "string" - }, - "model": { - "type": "string" - }, - "object": { - "type": "string" - }, - "usage": { - "$ref": "#/definitions/openai.Usage" - } - } - }, - "app_interfaces_http_routes_v1_organization.AdminAPIKeyDeletedResponse": { - "type": "object", - "properties": { - "deleted": { - "type": "boolean" - }, - "id": { - "type": "string" - }, - "object": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_v1_organization.AdminApiKeyListResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization.OrganizationAdminAPIKeyResponse" - } - }, - "first_id": { - "type": "string" - }, - "has_more": { - "type": "boolean" - }, - "last_id": { - "type": "string" - }, - "object": { - "type": "string", - "example": "list" - } - } - }, - "app_interfaces_http_routes_v1_organization.CreateOrganizationAdminAPIKeyRequest": { - "type": "object", - "required": [ - "name" - ], - "properties": { - "name": { - "type": "string", - "example": "My Admin API Key" - } - } - }, - "app_interfaces_http_routes_v1_organization.OrganizationAdminAPIKeyResponse": { - "type": "object", - "properties": { - "created_at": { - "type": "integer", - "example": 1698765432 - }, - "id": { - "type": "string", - "example": "key_1234567890" - }, - "last_used_at": { - "type": "integer", - "example": 1698765432 - }, - "name": { - "type": "string", - "example": "My Admin API Key" - }, - "object": { - "type": "string", - "example": "api_key" - }, - "owner": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization.Owner" - }, - "redacted_value": { - "type": "string", - "example": "sk-...abcd" - }, - "value": { - "type": "string", - "example": "sk-abcdef1234567890" - } - } - }, - "app_interfaces_http_routes_v1_organization.Owner": { - "type": "object", - "properties": { - "created_at": { - "type": "integer", - "example": 1698765432 - }, - "id": { - "type": "string", - "example": "user_1234567890" - }, - "name": { - "type": "string", - "example": "John Doe" - }, - "object": { - "type": "string", - "example": "user" - }, - "role": { - "type": "string", - "example": "admin" - }, - "type": { - "type": "string", - "example": "user" - } - } - }, - "app_interfaces_http_routes_v1_organization_projects.CreateProjectRequest": { - "type": "object", - "required": [ - "name" - ], - "properties": { - "name": { - "type": "string", - "example": "New AI Project" - } - } - }, - "app_interfaces_http_routes_v1_organization_projects.ProjectListResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/definitions/app_interfaces_http_routes_v1_organization_projects.ProjectResponse" - } - }, - "first_id": { - "type": "string" - }, - "has_more": { - "type": "boolean" - }, - "last_id": { - "type": "string" - }, - "object": { - "type": "string", - "example": "list" - } - } - }, - "app_interfaces_http_routes_v1_organization_projects.ProjectResponse": { - "type": "object", - "properties": { - "archived_at": { - "type": "integer", - "example": 1698765432 - }, - "created_at": { - "type": "integer", - "example": 1698765432 - }, - "id": { - "type": "string", - "example": "proj_1234567890" - }, - "name": { - "type": "string", - "example": "My First Project" - }, - "object": { - "type": "string", - "example": "project" - }, - "status": { - "type": "string" - } - } - }, - "app_interfaces_http_routes_v1_organization_projects.UpdateProjectRequest": { - "type": "object", - "properties": { - "name": { - "type": "string", - "example": "Updated AI Project" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.AnnotationResponse": { - "type": "object", - "properties": { - "end_index": { - "type": "integer" - }, - "file_id": { - "type": "string" - }, - "index": { - "type": "integer" - }, - "start_index": { - "type": "integer" - }, - "text": { - "type": "string" - }, - "type": { - "type": "string" - }, - "url": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ContentResponse": { - "type": "object", - "properties": { - "file": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.FileContentResponse" - }, - "image": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ImageContentResponse" - }, - "input_text": { - "type": "string" - }, - "output_text": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.OutputTextResponse" - }, - "text": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.TextResponse" - }, - "type": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationContentRequest": { - "type": "object", - "required": [ - "type" - ], - "properties": { - "text": { - "type": "string" - }, - "type": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemListResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemResponse" - } - }, - "first_id": { - "type": "string" - }, - "has_more": { - "type": "boolean" - }, - "last_id": { - "type": "string" - }, - "object": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemRequest": { - "type": "object", - "required": [ - "content", - "type" - ], - "properties": { - "content": { - "type": "array", - "items": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationContentRequest" - } - }, - "role": { - "type": "string" - }, - "type": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemResponse": { - "type": "object", - "properties": { - "content": { - "type": "array", - "items": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ContentResponse" - } - }, - "created_at": { - "type": "integer" - }, - "id": { - "type": "string" - }, - "object": { - "type": "string" - }, - "role": { - "type": "string" - }, - "status": { - "type": "string" - }, - "type": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationResponse": { - "type": "object", - "properties": { - "created_at": { - "type": "integer" - }, - "id": { - "type": "string" - }, - "metadata": { - "type": "object", - "additionalProperties": { - "type": "string" - } - }, - "object": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.CreateConversationRequest": { - "type": "object", - "properties": { - "items": { - "type": "array", - "items": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemRequest" - } - }, - "metadata": { - "type": "object", - "additionalProperties": { - "type": "string" - } - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.CreateItemsRequest": { - "type": "object", - "required": [ - "items" - ], - "properties": { - "items": { - "type": "array", - "items": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ConversationItemRequest" - } - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.DeletedConversationResponse": { - "type": "object", - "properties": { - "deleted": { - "type": "boolean" - }, - "id": { - "type": "string" - }, - "object": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.FileContentResponse": { - "type": "object", - "properties": { - "file_id": { - "type": "string" - }, - "mime_type": { - "type": "string" - }, - "name": { - "type": "string" - }, - "size": { - "type": "integer" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.ImageContentResponse": { - "type": "object", - "properties": { - "detail": { - "type": "string" - }, - "file_id": { - "type": "string" - }, - "url": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.OutputTextResponse": { - "type": "object", - "properties": { - "annotations": { - "type": "array", - "items": { - "$ref": "#/definitions/menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.AnnotationResponse" - } - }, - "text": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.TextResponse": { - "type": "object", - "properties": { - "value": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_handlers_conversation.UpdateConversationRequest": { - "type": "object", - "required": [ - "metadata" - ], - "properties": { - "metadata": { - "type": "object", - "additionalProperties": { - "type": "string" - } - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_responses.ErrorResponse": { - "type": "object", - "properties": { - "code": { - "type": "string" - }, - "error": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_auth_GetMeResponse": { - "type": "object", - "properties": { - "result": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_auth.GetMeResponse" - }, - "status": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_auth_RefreshTokenResponse": { - "type": "object", - "properties": { - "result": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_auth.RefreshTokenResponse" - }, - "status": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_auth_google_GoogleCallbackResponse": { - "type": "object", - "properties": { - "result": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_auth_google.GoogleCallbackResponse" - }, - "status": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_organization_api_keys_ApiKeyResponse": { - "type": "object", - "properties": { - "result": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_organization_api_keys.ApiKeyResponse" - }, - "status": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_responses.GeneralResponse-app_interfaces_http_routes_jan_v1_organization_projects_api_keys_ApiKeyResponse": { - "type": "object", - "properties": { - "result": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_organization_projects_api_keys.ApiKeyResponse" - }, - "status": { - "type": "string" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_responses.ListResponse-app_interfaces_http_routes_jan_v1_organization_OrganizationResponse": { - "type": "object", - "properties": { - "results": { - "type": "array", - "items": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_organization.OrganizationResponse" - } - }, - "status": { - "type": "string" - }, - "total": { - "type": "integer" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_responses.ListResponse-app_interfaces_http_routes_jan_v1_organization_api_keys_ApiKeyResponse": { - "type": "object", - "properties": { - "results": { - "type": "array", - "items": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_organization_api_keys.ApiKeyResponse" - } - }, - "status": { - "type": "string" - }, - "total": { - "type": "integer" - } - } - }, - "menlo_ai_jan-api-gateway_app_interfaces_http_responses.ListResponse-app_interfaces_http_routes_jan_v1_organization_projects_ProjectResponse": { - "type": "object", - "properties": { - "results": { - "type": "array", - "items": { - "$ref": "#/definitions/app_interfaces_http_routes_jan_v1_organization_projects.ProjectResponse" - } - }, - "status": { - "type": "string" - }, - "total": { - "type": "integer" - } - } - }, - "openai.ChatCompletionChoice": { - "type": "object", - "properties": { - "content_filter_results": { - "$ref": "#/definitions/openai.ContentFilterResults" - }, - "finish_reason": { - "description": "FinishReason\nstop: API returned complete message,\nor a message terminated by one of the stop sequences provided via the stop parameter\nlength: Incomplete model output due to max_tokens parameter or token limit\nfunction_call: The model decided to call a function\ncontent_filter: Omitted content due to a flag from our content filters\nnull: API response still in progress or incomplete", - "allOf": [ - { - "$ref": "#/definitions/openai.FinishReason" - } - ] - }, - "index": { - "type": "integer" - }, - "logprobs": { - "$ref": "#/definitions/openai.LogProbs" - }, - "message": { - "$ref": "#/definitions/openai.ChatCompletionMessage" - } - } - }, - "openai.ChatCompletionMessage": { - "type": "object", - "properties": { - "content": { - "type": "string" - }, - "function_call": { - "$ref": "#/definitions/openai.FunctionCall" - }, - "multiContent": { - "type": "array", - "items": { - "$ref": "#/definitions/openai.ChatMessagePart" - } - }, - "name": { - "description": "This property isn't in the official documentation, but it's in\nthe documentation for the official library for python:\n- https://github.com/openai/openai-python/blob/main/chatml.md\n- https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb", - "type": "string" - }, - "reasoning_content": { - "description": "This property is used for the \"reasoning\" feature supported by deepseek-reasoner\nwhich is not in the official documentation.\nthe doc from deepseek:\n- https://api-docs.deepseek.com/api/create-chat-completion#responses", - "type": "string" - }, - "refusal": { - "type": "string" - }, - "role": { - "type": "string" - }, - "tool_call_id": { - "description": "For Role=tool prompts this should be set to the ID given in the assistant's prior request to call a tool.", - "type": "string" - }, - "tool_calls": { - "description": "For Role=assistant prompts this may be set to the tool calls generated by the model, such as function calls.", - "type": "array", - "items": { - "$ref": "#/definitions/openai.ToolCall" - } - } - } - }, - "openai.ChatCompletionRequest": { - "type": "object", - "properties": { - "chat_template_kwargs": { - "description": "ChatTemplateKwargs provides a way to add non-standard parameters to the request body.\nAdditional kwargs to pass to the template renderer. Will be accessible by the chat template.\nSuch as think mode for qwen3. \"chat_template_kwargs\": {\"enable_thinking\": false}\nhttps://qwen.readthedocs.io/en/latest/deployment/vllm.html#thinking-non-thinking-modes", - "type": "object", - "additionalProperties": {} - }, - "frequency_penalty": { - "type": "number" - }, - "function_call": { - "description": "Deprecated: use ToolChoice instead." - }, - "functions": { - "description": "Deprecated: use Tools instead.", - "type": "array", - "items": { - "$ref": "#/definitions/openai.FunctionDefinition" - } - }, - "guided_choice": { - "description": "GuidedChoice is a vLLM-specific extension that restricts the model's output\nto one of the predefined string choices provided in this field. This feature\nis used to constrain the model's responses to a controlled set of options,\nensuring predictable and consistent outputs in scenarios where specific\nchoices are required.", - "type": "array", - "items": { - "type": "string" - } - }, - "logit_bias": { - "description": "LogitBias is must be a token id string (specified by their token ID in the tokenizer), not a word string.\nincorrect: `\"logit_bias\":{\"You\": 6}`, correct: `\"logit_bias\":{\"1639\": 6}`\nrefs: https://platform.openai.com/docs/api-reference/chat/create#chat/create-logit_bias", - "type": "object", - "additionalProperties": { - "type": "integer" - } - }, - "logprobs": { - "description": "LogProbs indicates whether to return log probabilities of the output tokens or not.\nIf true, returns the log probabilities of each output token returned in the content of message.\nThis option is currently not available on the gpt-4-vision-preview model.", - "type": "boolean" - }, - "max_completion_tokens": { - "description": "MaxCompletionTokens An upper bound for the number of tokens that can be generated for a completion,\nincluding visible output tokens and reasoning tokens https://platform.openai.com/docs/guides/reasoning", - "type": "integer" - }, - "max_tokens": { - "description": "MaxTokens The maximum number of tokens that can be generated in the chat completion.\nThis value can be used to control costs for text generated via API.\nDeprecated: use MaxCompletionTokens. Not compatible with o1-series models.\nrefs: https://platform.openai.com/docs/api-reference/chat/create#chat-create-max_tokens", - "type": "integer" - }, - "messages": { - "type": "array", - "items": { - "$ref": "#/definitions/openai.ChatCompletionMessage" - } - }, - "metadata": { - "description": "Metadata to store with the completion.", - "type": "object", - "additionalProperties": { - "type": "string" - } - }, - "model": { - "type": "string" - }, - "n": { - "type": "integer" - }, - "parallel_tool_calls": { - "description": "Disable the default behavior of parallel tool calls by setting it: false." - }, - "prediction": { - "description": "Configuration for a predicted output.", - "allOf": [ - { - "$ref": "#/definitions/openai.Prediction" - } - ] - }, - "presence_penalty": { - "type": "number" - }, - "reasoning_effort": { - "description": "Controls effort on reasoning for reasoning models. It can be set to \"low\", \"medium\", or \"high\".", - "type": "string" - }, - "response_format": { - "$ref": "#/definitions/openai.ChatCompletionResponseFormat" - }, - "safety_identifier": { - "description": "A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies.\nThe IDs should be a string that uniquely identifies each user.\nWe recommend hashing their username or email address, in order to avoid sending us any identifying information.\nhttps://platform.openai.com/docs/api-reference/chat/create#chat_create-safety_identifier", - "type": "string" - }, - "seed": { - "type": "integer" - }, - "service_tier": { - "description": "Specifies the latency tier to use for processing the request.", - "allOf": [ - { - "$ref": "#/definitions/openai.ServiceTier" - } - ] - }, - "stop": { - "type": "array", - "items": { - "type": "string" - } - }, - "store": { - "description": "Store can be set to true to store the output of this completion request for use in distillations and evals.\nhttps://platform.openai.com/docs/api-reference/chat/create#chat-create-store", - "type": "boolean" - }, - "stream": { - "type": "boolean" - }, - "stream_options": { - "description": "Options for streaming response. Only set this when you set stream: true.", - "allOf": [ - { - "$ref": "#/definitions/openai.StreamOptions" - } - ] - }, - "temperature": { - "type": "number" - }, - "tool_choice": { - "description": "This can be either a string or an ToolChoice object." - }, - "tools": { - "type": "array", - "items": { - "$ref": "#/definitions/openai.Tool" - } - }, - "top_logprobs": { - "description": "TopLogProbs is an integer between 0 and 5 specifying the number of most likely tokens to return at each\ntoken position, each with an associated log probability.\nlogprobs must be set to true if this parameter is used.", - "type": "integer" - }, - "top_p": { - "type": "number" - }, - "user": { - "type": "string" - } - } - }, - "openai.ChatCompletionResponseFormat": { - "type": "object", - "properties": { - "json_schema": { - "$ref": "#/definitions/openai.ChatCompletionResponseFormatJSONSchema" - }, - "type": { - "$ref": "#/definitions/openai.ChatCompletionResponseFormatType" - } - } - }, - "openai.ChatCompletionResponseFormatJSONSchema": { - "type": "object", - "properties": { - "description": { - "type": "string" - }, - "name": { - "type": "string" - }, - "schema": {}, - "strict": { - "type": "boolean" - } - } - }, - "openai.ChatCompletionResponseFormatType": { - "type": "string", - "enum": [ - "json_object", - "json_schema", - "text" - ], - "x-enum-varnames": [ - "ChatCompletionResponseFormatTypeJSONObject", - "ChatCompletionResponseFormatTypeJSONSchema", - "ChatCompletionResponseFormatTypeText" - ] - }, - "openai.ChatMessageImageURL": { - "type": "object", - "properties": { - "detail": { - "$ref": "#/definitions/openai.ImageURLDetail" - }, - "url": { - "type": "string" - } - } - }, - "openai.ChatMessagePart": { - "type": "object", - "properties": { - "image_url": { - "$ref": "#/definitions/openai.ChatMessageImageURL" - }, - "text": { - "type": "string" - }, - "type": { - "$ref": "#/definitions/openai.ChatMessagePartType" - } - } - }, - "openai.ChatMessagePartType": { - "type": "string", - "enum": [ - "text", - "image_url" - ], - "x-enum-varnames": [ - "ChatMessagePartTypeText", - "ChatMessagePartTypeImageURL" - ] - }, - "openai.CompletionTokensDetails": { - "type": "object", - "properties": { - "accepted_prediction_tokens": { - "type": "integer" - }, - "audio_tokens": { - "type": "integer" - }, - "reasoning_tokens": { - "type": "integer" - }, - "rejected_prediction_tokens": { - "type": "integer" - } - } - }, - "openai.ContentFilterResults": { - "type": "object", - "properties": { - "hate": { - "$ref": "#/definitions/openai.Hate" - }, - "jailbreak": { - "$ref": "#/definitions/openai.JailBreak" - }, - "profanity": { - "$ref": "#/definitions/openai.Profanity" - }, - "self_harm": { - "$ref": "#/definitions/openai.SelfHarm" - }, - "sexual": { - "$ref": "#/definitions/openai.Sexual" - }, - "violence": { - "$ref": "#/definitions/openai.Violence" - } - } - }, - "openai.FinishReason": { - "type": "string", - "enum": [ - "stop", - "length", - "function_call", - "tool_calls", - "content_filter", - "null" - ], - "x-enum-varnames": [ - "FinishReasonStop", - "FinishReasonLength", - "FinishReasonFunctionCall", - "FinishReasonToolCalls", - "FinishReasonContentFilter", - "FinishReasonNull" - ] - }, - "openai.FunctionCall": { - "type": "object", - "properties": { - "arguments": { - "description": "call function with arguments in JSON format", - "type": "string" - }, - "name": { - "type": "string" - } - } - }, - "openai.FunctionDefinition": { - "type": "object", - "properties": { - "description": { - "type": "string" - }, - "name": { - "type": "string" - }, - "parameters": { - "description": "Parameters is an object describing the function.\nYou can pass json.RawMessage to describe the schema,\nor you can pass in a struct which serializes to the proper JSON schema.\nThe jsonschema package is provided for convenience, but you should\nconsider another specialized library if you require more complex schemas." - }, - "strict": { - "type": "boolean" - } - } - }, - "openai.Hate": { - "type": "object", - "properties": { - "filtered": { - "type": "boolean" - }, - "severity": { - "type": "string" - } - } - }, - "openai.ImageURLDetail": { - "type": "string", - "enum": [ - "high", - "low", - "auto" - ], - "x-enum-varnames": [ - "ImageURLDetailHigh", - "ImageURLDetailLow", - "ImageURLDetailAuto" - ] - }, - "openai.JailBreak": { - "type": "object", - "properties": { - "detected": { - "type": "boolean" - }, - "filtered": { - "type": "boolean" - } - } - }, - "openai.LogProb": { - "type": "object", - "properties": { - "bytes": { - "description": "Omitting the field if it is null", - "type": "array", - "items": { - "type": "integer" - } - }, - "logprob": { - "type": "number" - }, - "token": { - "type": "string" - }, - "top_logprobs": { - "description": "TopLogProbs is a list of the most likely tokens and their log probability, at this token position.\nIn rare cases, there may be fewer than the number of requested top_logprobs returned.", - "type": "array", - "items": { - "$ref": "#/definitions/openai.TopLogProbs" - } - } - } - }, - "openai.LogProbs": { - "type": "object", - "properties": { - "content": { - "description": "Content is a list of message content tokens with log probability information.", - "type": "array", - "items": { - "$ref": "#/definitions/openai.LogProb" - } - } - } - }, - "openai.Prediction": { - "type": "object", - "properties": { - "content": { - "type": "string" - }, - "type": { - "type": "string" - } - } - }, - "openai.Profanity": { - "type": "object", - "properties": { - "detected": { - "type": "boolean" - }, - "filtered": { - "type": "boolean" - } - } - }, - "openai.PromptTokensDetails": { - "type": "object", - "properties": { - "audio_tokens": { - "type": "integer" - }, - "cached_tokens": { - "type": "integer" - } - } - }, - "openai.SelfHarm": { - "type": "object", - "properties": { - "filtered": { - "type": "boolean" - }, - "severity": { - "type": "string" - } - } - }, - "openai.ServiceTier": { - "type": "string", - "enum": [ - "auto", - "default", - "flex", - "priority" - ], - "x-enum-varnames": [ - "ServiceTierAuto", - "ServiceTierDefault", - "ServiceTierFlex", - "ServiceTierPriority" - ] - }, - "openai.Sexual": { - "type": "object", - "properties": { - "filtered": { - "type": "boolean" - }, - "severity": { - "type": "string" - } - } - }, - "openai.StreamOptions": { - "type": "object", - "properties": { - "include_usage": { - "description": "If set, an additional chunk will be streamed before the data: [DONE] message.\nThe usage field on this chunk shows the token usage statistics for the entire request,\nand the choices field will always be an empty array.\nAll other chunks will also include a usage field, but with a null value.", - "type": "boolean" - } - } - }, - "openai.Tool": { - "type": "object", - "properties": { - "function": { - "$ref": "#/definitions/openai.FunctionDefinition" - }, - "type": { - "$ref": "#/definitions/openai.ToolType" - } - } - }, - "openai.ToolCall": { - "type": "object", - "properties": { - "function": { - "$ref": "#/definitions/openai.FunctionCall" - }, - "id": { - "type": "string" - }, - "index": { - "description": "Index is not nil only in chat completion chunk object", - "type": "integer" - }, - "type": { - "$ref": "#/definitions/openai.ToolType" - } - } - }, - "openai.ToolType": { - "type": "string", - "enum": [ - "function" - ], - "x-enum-varnames": [ - "ToolTypeFunction" - ] - }, - "openai.TopLogProbs": { - "type": "object", - "properties": { - "bytes": { - "type": "array", - "items": { - "type": "integer" - } - }, - "logprob": { - "type": "number" - }, - "token": { - "type": "string" - } - } - }, - "openai.Usage": { - "type": "object", - "properties": { - "completion_tokens": { - "type": "integer" - }, - "completion_tokens_details": { - "$ref": "#/definitions/openai.CompletionTokensDetails" - }, - "prompt_tokens": { - "type": "integer" - }, - "prompt_tokens_details": { - "$ref": "#/definitions/openai.PromptTokensDetails" - }, - "total_tokens": { - "type": "integer" - } - } - }, - "openai.Violence": { - "type": "object", - "properties": { - "filtered": { - "type": "boolean" - }, - "severity": { - "type": "string" - } - } - } - }, - "securityDefinitions": { - "BearerAuth": { - "description": "Type \"Bearer\" followed by a space and JWT token.", - "type": "apiKey", - "name": "Authorization", - "in": "header" - } - }, - "servers": [ - { - "url": "https://api.jan.ai/v1", - "description": "Jan Server API (Production)" - }, - { - "url": "https://staging-api.jan.ai/v1", - "description": "Jan Server API (Staging)" - }, - { - "url": "http://localhost:8000/v1", - "description": "Jan Server (Local Development)" - }, - { - "url": "http://jan-server.local:8000/v1", - "description": "Jan Server (Minikube)" - } - ], - "security": [ - { - "bearerAuth": [] - } - ], - "tags": [ - { - "name": "Models", - "description": "List and describe available models" - }, - { - "name": "Chat", - "description": "Chat completion endpoints for conversational AI" - }, - { - "name": "Completions", - "description": "Text completion endpoints" - }, - { - "name": "Embeddings", - "description": "Generate embeddings for text" - }, - { - "name": "Usage", - "description": "Monitor API usage and quotas" - } - ], - "components": { - "securitySchemes": { - "bearerAuth": { - "type": "http", - "scheme": "bearer", - "bearerFormat": "JWT", - "description": "Enter your Jan Server API key. Configure authentication in your server settings." - } - } - }, - "x-jan-server-features": { - "vllm": { - "version": "0.5.0", - "features": [ - "PagedAttention for efficient memory management", - "Continuous batching for high throughput", - "Tensor parallelism for multi-GPU serving", - "Quantization support (AWQ, GPTQ, SqueezeLLM)", - "Speculative decoding", - "LoRA adapter support" - ] - }, - "scaling": { - "auto_scaling": true, - "min_replicas": 1, - "max_replicas": 100, - "target_qps": 100 - }, - "limits": { - "max_tokens_per_request": 32768, - "max_batch_size": 256, - "timeout_seconds": 300 - } - } -} \ No newline at end of file diff --git a/website/public/openapi/openapi-openai.json b/website/public/openapi/openapi-openai.json deleted file mode 100644 index 6eccbe6e7..000000000 --- a/website/public/openapi/openapi-openai.json +++ /dev/null @@ -1,44747 +0,0 @@ -{ - "openapi": "3.1.0", - "info": { - "title": "OpenAI API", - "description": "The OpenAI REST API. Please see https://platform.openai.com/docs/api-reference for more details.", - "version": "2.3.0", - "termsOfService": "https://openai.com/policies/terms-of-use", - "contact": { - "name": "OpenAI Support", - "url": "https://help.openai.com/" - }, - "license": { - "name": "MIT", - "url": "https://github.com/openai/openai-openapi/blob/master/LICENSE" - } - }, - "servers": [ - { - "url": "https://api.openai.com/v1" - } - ], - "security": [ - { - "ApiKeyAuth": [] - } - ], - "tags": [ - { - "name": "Assistants", - "description": "Build Assistants that can call models and use tools." - }, - { - "name": "Audio", - "description": "Turn audio into text or text into audio." - }, - { - "name": "Chat", - "description": "Given a list of messages comprising a conversation, the model will return a response." - }, - { - "name": "Conversations", - "description": "Manage conversations and conversation items." - }, - { - "name": "Completions", - "description": "Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position." - }, - { - "name": "Embeddings", - "description": "Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms." - }, - { - "name": "Evals", - "description": "Manage and run evals in the OpenAI platform." - }, - { - "name": "Fine-tuning", - "description": "Manage fine-tuning jobs to tailor a model to your specific training data." - }, - { - "name": "Graders", - "description": "Manage and run graders in the OpenAI platform." - }, - { - "name": "Batch", - "description": "Create large batches of API requests to run asynchronously." - }, - { - "name": "Files", - "description": "Files are used to upload documents that can be used with features like Assistants and Fine-tuning." - }, - { - "name": "Uploads", - "description": "Use Uploads to upload large files in multiple parts." - }, - { - "name": "Images", - "description": "Given a prompt and/or an input image, the model will generate a new image." - }, - { - "name": "Models", - "description": "List and describe the various models available in the API." - }, - { - "name": "Moderations", - "description": "Given text and/or image inputs, classifies if those inputs are potentially harmful." - }, - { - "name": "Audit Logs", - "description": "List user actions and configuration changes within this organization." - } - ], - "paths": { - "/assistants": { - "get": { - "operationId": "listAssistants", - "tags": [ - "Assistants" - ], - "summary": "List assistants", - "parameters": [ - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "before", - "in": "query", - "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.\n", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListAssistantsResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List assistants", - "group": "assistants", - "beta": true, - "returns": "A list of [assistant](https://platform.openai.com/docs/api-reference/assistants/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"asst_abc123\",\n \"object\": \"assistant\",\n \"created_at\": 1698982736,\n \"name\": \"Coding Tutor\",\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are a helpful assistant designed to make me better at coding!\",\n \"tools\": [],\n \"tool_resources\": {},\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n },\n {\n \"id\": \"asst_abc456\",\n \"object\": \"assistant\",\n \"created_at\": 1698982718,\n \"name\": \"My Assistant\",\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are a helpful assistant designed to make me better at coding!\",\n \"tools\": [],\n \"tool_resources\": {},\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n },\n {\n \"id\": \"asst_abc789\",\n \"object\": \"assistant\",\n \"created_at\": 1698982643,\n \"name\": null,\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": null,\n \"tools\": [],\n \"tool_resources\": {},\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n }\n ],\n \"first_id\": \"asst_abc123\",\n \"last_id\": \"asst_abc789\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/assistants?order=desc&limit=20\" \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.beta.assistants.list()\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const assistant of client.beta.assistants.list()) {\n console.log(assistant.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Beta.Assistants.List(context.TODO(), openai.BetaAssistantListParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.assistants.AssistantListPage;\nimport com.openai.models.beta.assistants.AssistantListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n AssistantListPage page = client.beta().assistants().list();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.beta.assistants.list\n\nputs(page)" - } - } - }, - "description": "Returns a list of assistants." - }, - "post": { - "operationId": "createAssistant", - "tags": [ - "Assistants" - ], - "summary": "Create assistant", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateAssistantRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/AssistantObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create assistant", - "group": "assistants", - "beta": true, - "returns": "An [assistant](https://platform.openai.com/docs/api-reference/assistants/object) object.", - "examples": [ - { - "title": "Code Interpreter", - "request": { - "curl": "curl \"https://api.openai.com/v1/assistants\" \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"instructions\": \"You are a personal math tutor. When asked a question, write and run Python code to answer the question.\",\n \"name\": \"Math Tutor\",\n \"tools\": [{\"type\": \"code_interpreter\"}],\n \"model\": \"gpt-4o\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nassistant = client.beta.assistants.create(\n model=\"gpt-4o\",\n)\nprint(assistant.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst assistant = await client.beta.assistants.create({ model: 'gpt-4o' });\n\nconsole.log(assistant.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/shared\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n assistant, err := client.Beta.Assistants.New(context.TODO(), openai.BetaAssistantNewParams{\n Model: shared.ChatModelGPT5,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", assistant.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.ChatModel;\nimport com.openai.models.beta.assistants.Assistant;\nimport com.openai.models.beta.assistants.AssistantCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n AssistantCreateParams params = AssistantCreateParams.builder()\n .model(ChatModel.GPT_5)\n .build();\n Assistant assistant = client.beta().assistants().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nassistant = openai.beta.assistants.create(model: :\"gpt-5\")\n\nputs(assistant)" - }, - "response": "{\n \"id\": \"asst_abc123\",\n \"object\": \"assistant\",\n \"created_at\": 1698984975,\n \"name\": \"Math Tutor\",\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are a personal math tutor. When asked a question, write and run Python code to answer the question.\",\n \"tools\": [\n {\n \"type\": \"code_interpreter\"\n }\n ],\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n}\n" - }, - { - "title": "Files", - "request": { - "curl": "curl https://api.openai.com/v1/assistants \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"instructions\": \"You are an HR bot, and you have access to files to answer employee questions about company policies.\",\n \"tools\": [{\"type\": \"file_search\"}],\n \"tool_resources\": {\"file_search\": {\"vector_store_ids\": [\"vs_123\"]}},\n \"model\": \"gpt-4o\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nassistant = client.beta.assistants.create(\n model=\"gpt-4o\",\n)\nprint(assistant.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst assistant = await client.beta.assistants.create({ model: 'gpt-4o' });\n\nconsole.log(assistant.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/shared\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n assistant, err := client.Beta.Assistants.New(context.TODO(), openai.BetaAssistantNewParams{\n Model: shared.ChatModelGPT5,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", assistant.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.ChatModel;\nimport com.openai.models.beta.assistants.Assistant;\nimport com.openai.models.beta.assistants.AssistantCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n AssistantCreateParams params = AssistantCreateParams.builder()\n .model(ChatModel.GPT_5)\n .build();\n Assistant assistant = client.beta().assistants().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nassistant = openai.beta.assistants.create(model: :\"gpt-5\")\n\nputs(assistant)" - }, - "response": "{\n \"id\": \"asst_abc123\",\n \"object\": \"assistant\",\n \"created_at\": 1699009403,\n \"name\": \"HR Helper\",\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are an HR bot, and you have access to files to answer employee questions about company policies.\",\n \"tools\": [\n {\n \"type\": \"file_search\"\n }\n ],\n \"tool_resources\": {\n \"file_search\": {\n \"vector_store_ids\": [\"vs_123\"]\n }\n },\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n}\n" - } - ] - }, - "description": "Create an assistant with a model and instructions." - } - }, - "/assistants/{assistant_id}": { - "get": { - "operationId": "getAssistant", - "tags": [ - "Assistants" - ], - "summary": "Retrieve assistant", - "parameters": [ - { - "in": "path", - "name": "assistant_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the assistant to retrieve." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/AssistantObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve assistant", - "group": "assistants", - "beta": true, - "returns": "The [assistant](https://platform.openai.com/docs/api-reference/assistants/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"asst_abc123\",\n \"object\": \"assistant\",\n \"created_at\": 1699009709,\n \"name\": \"HR Helper\",\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are an HR bot, and you have access to files to answer employee questions about company policies.\",\n \"tools\": [\n {\n \"type\": \"file_search\"\n }\n ],\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/assistants/asst_abc123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nassistant = client.beta.assistants.retrieve(\n \"assistant_id\",\n)\nprint(assistant.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst assistant = await client.beta.assistants.retrieve('assistant_id');\n\nconsole.log(assistant.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n assistant, err := client.Beta.Assistants.Get(context.TODO(), \"assistant_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", assistant.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.assistants.Assistant;\nimport com.openai.models.beta.assistants.AssistantRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Assistant assistant = client.beta().assistants().retrieve(\"assistant_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nassistant = openai.beta.assistants.retrieve(\"assistant_id\")\n\nputs(assistant)" - } - } - }, - "description": "Retrieves an assistant." - }, - "post": { - "operationId": "modifyAssistant", - "tags": [ - "Assistants" - ], - "summary": "Modify assistant", - "parameters": [ - { - "in": "path", - "name": "assistant_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the assistant to modify." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ModifyAssistantRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/AssistantObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify assistant", - "group": "assistants", - "beta": true, - "returns": "The modified [assistant](https://platform.openai.com/docs/api-reference/assistants/object) object.", - "examples": { - "response": "{\n \"id\": \"asst_123\",\n \"object\": \"assistant\",\n \"created_at\": 1699009709,\n \"name\": \"HR Helper\",\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.\",\n \"tools\": [\n {\n \"type\": \"file_search\"\n }\n ],\n \"tool_resources\": {\n \"file_search\": {\n \"vector_store_ids\": []\n }\n },\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/assistants/asst_abc123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"instructions\": \"You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.\",\n \"tools\": [{\"type\": \"file_search\"}],\n \"model\": \"gpt-4o\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nassistant = client.beta.assistants.update(\n assistant_id=\"assistant_id\",\n)\nprint(assistant.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst assistant = await client.beta.assistants.update('assistant_id');\n\nconsole.log(assistant.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n assistant, err := client.Beta.Assistants.Update(\n context.TODO(),\n \"assistant_id\",\n openai.BetaAssistantUpdateParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", assistant.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.assistants.Assistant;\nimport com.openai.models.beta.assistants.AssistantUpdateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Assistant assistant = client.beta().assistants().update(\"assistant_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nassistant = openai.beta.assistants.update(\"assistant_id\")\n\nputs(assistant)" - } - } - }, - "description": "Modifies an assistant." - }, - "delete": { - "operationId": "deleteAssistant", - "tags": [ - "Assistants" - ], - "summary": "Delete assistant", - "parameters": [ - { - "in": "path", - "name": "assistant_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the assistant to delete." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeleteAssistantResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete assistant", - "group": "assistants", - "beta": true, - "returns": "Deletion status", - "examples": { - "response": "{\n \"id\": \"asst_abc123\",\n \"object\": \"assistant.deleted\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/assistants/asst_abc123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -X DELETE\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nassistant_deleted = client.beta.assistants.delete(\n \"assistant_id\",\n)\nprint(assistant_deleted.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst assistantDeleted = await client.beta.assistants.delete('assistant_id');\n\nconsole.log(assistantDeleted.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n assistantDeleted, err := client.Beta.Assistants.Delete(context.TODO(), \"assistant_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", assistantDeleted.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.assistants.AssistantDeleteParams;\nimport com.openai.models.beta.assistants.AssistantDeleted;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n AssistantDeleted assistantDeleted = client.beta().assistants().delete(\"assistant_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nassistant_deleted = openai.beta.assistants.delete(\"assistant_id\")\n\nputs(assistant_deleted)" - } - } - }, - "description": "Delete an assistant." - } - }, - "/audio/speech": { - "post": { - "operationId": "createSpeech", - "tags": [ - "Audio" - ], - "summary": "Create speech", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateSpeechRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "headers": { - "Transfer-Encoding": { - "schema": { - "type": "string" - }, - "description": "chunked" - } - }, - "content": { - "application/octet-stream": { - "schema": { - "type": "string", - "format": "binary" - } - }, - "text/event-stream": { - "schema": { - "$ref": "#/components/schemas/CreateSpeechResponseStreamEvent" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create speech", - "group": "audio", - "returns": "The audio file content or a [stream of audio events](https://platform.openai.com/docs/api-reference/audio/speech-audio-delta-event).", - "examples": [ - { - "title": "Default", - "request": { - "curl": "curl https://api.openai.com/v1/audio/speech \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"gpt-4o-mini-tts\",\n \"input\": \"The quick brown fox jumped over the lazy dog.\",\n \"voice\": \"alloy\"\n }' \\\n --output speech.mp3\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nspeech = client.audio.speech.create(\n input=\"input\",\n model=\"string\",\n voice=\"ash\",\n)\nprint(speech)\ncontent = speech.read()\nprint(content)", - "javascript": "import fs from \"fs\";\nimport path from \"path\";\nimport OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nconst speechFile = path.resolve(\"./speech.mp3\");\n\nasync function main() {\n const mp3 = await openai.audio.speech.create({\n model: \"gpt-4o-mini-tts\",\n voice: \"alloy\",\n input: \"Today is a wonderful day to build something people love!\",\n });\n console.log(speechFile);\n const buffer = Buffer.from(await mp3.arrayBuffer());\n await fs.promises.writeFile(speechFile, buffer);\n}\nmain();\n", - "csharp": "using System;\nusing System.IO;\n\nusing OpenAI.Audio;\n\nAudioClient client = new(\n model: \"gpt-4o-mini-tts\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nBinaryData speech = client.GenerateSpeech(\n text: \"The quick brown fox jumped over the lazy dog.\",\n voice: GeneratedSpeechVoice.Alloy\n);\n\nusing FileStream stream = File.OpenWrite(\"speech.mp3\");\nspeech.ToStream().CopyTo(stream);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst speech = await client.audio.speech.create({ input: 'input', model: 'string', voice: 'ash' });\n\nconsole.log(speech);\n\nconst content = await speech.blob();\nconsole.log(content);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n speech, err := client.Audio.Speech.New(context.TODO(), openai.AudioSpeechNewParams{\n Input: \"input\",\n Model: openai.SpeechModelTTS1,\n Voice: openai.AudioSpeechNewParamsVoiceAlloy,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", speech)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.core.http.HttpResponse;\nimport com.openai.models.audio.speech.SpeechCreateParams;\nimport com.openai.models.audio.speech.SpeechModel;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n SpeechCreateParams params = SpeechCreateParams.builder()\n .input(\"input\")\n .model(SpeechModel.TTS_1)\n .voice(SpeechCreateParams.Voice.ALLOY)\n .build();\n HttpResponse speech = client.audio().speech().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nspeech = openai.audio.speech.create(input: \"input\", model: :\"tts-1\", voice: :alloy)\n\nputs(speech)" - } - }, - { - "title": "SSE Stream Format", - "request": { - "curl": "curl https://api.openai.com/v1/audio/speech \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"gpt-4o-mini-tts\",\n \"input\": \"The quick brown fox jumped over the lazy dog.\",\n \"voice\": \"alloy\",\n \"stream_format\": \"sse\"\n }'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst speech = await client.audio.speech.create({ input: 'input', model: 'string', voice: 'ash' });\n\nconsole.log(speech);\n\nconst content = await speech.blob();\nconsole.log(content);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nspeech = client.audio.speech.create(\n input=\"input\",\n model=\"string\",\n voice=\"ash\",\n)\nprint(speech)\ncontent = speech.read()\nprint(content)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n speech, err := client.Audio.Speech.New(context.TODO(), openai.AudioSpeechNewParams{\n Input: \"input\",\n Model: openai.SpeechModelTTS1,\n Voice: openai.AudioSpeechNewParamsVoiceAlloy,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", speech)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.core.http.HttpResponse;\nimport com.openai.models.audio.speech.SpeechCreateParams;\nimport com.openai.models.audio.speech.SpeechModel;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n SpeechCreateParams params = SpeechCreateParams.builder()\n .input(\"input\")\n .model(SpeechModel.TTS_1)\n .voice(SpeechCreateParams.Voice.ALLOY)\n .build();\n HttpResponse speech = client.audio().speech().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nspeech = openai.audio.speech.create(input: \"input\", model: :\"tts-1\", voice: :alloy)\n\nputs(speech)" - } - } - ] - }, - "description": "Generates audio from the input text." - } - }, - "/audio/transcriptions": { - "post": { - "operationId": "createTranscription", - "tags": [ - "Audio" - ], - "summary": "Create transcription", - "requestBody": { - "required": true, - "content": { - "multipart/form-data": { - "schema": { - "$ref": "#/components/schemas/CreateTranscriptionRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "anyOf": [ - { - "$ref": "#/components/schemas/CreateTranscriptionResponseJson" - }, - { - "$ref": "#/components/schemas/CreateTranscriptionResponseVerboseJson", - "x-stainless-skip": [ - "go" - ] - } - ] - } - }, - "text/event-stream": { - "schema": { - "$ref": "#/components/schemas/CreateTranscriptionResponseStreamEvent" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create transcription", - "group": "audio", - "returns": "The [transcription object](https://platform.openai.com/docs/api-reference/audio/json-object), a [verbose transcription object](https://platform.openai.com/docs/api-reference/audio/verbose-json-object) or a [stream of transcript events](https://platform.openai.com/docs/api-reference/audio/transcript-text-delta-event).", - "examples": [ - { - "title": "Default", - "request": { - "curl": "curl https://api.openai.com/v1/audio/transcriptions \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: multipart/form-data\" \\\n -F file=\"@/path/to/file/audio.mp3\" \\\n -F model=\"gpt-4o-transcribe\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ntranscription = client.audio.transcriptions.create(\n file=b\"raw file contents\",\n model=\"gpt-4o-transcribe\",\n)\nprint(transcription)", - "javascript": "import fs from \"fs\";\nimport OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nasync function main() {\n const transcription = await openai.audio.transcriptions.create({\n file: fs.createReadStream(\"audio.mp3\"),\n model: \"gpt-4o-transcribe\",\n });\n\n console.log(transcription.text);\n}\nmain();\n", - "csharp": "using System;\n\nusing OpenAI.Audio;\nstring audioFilePath = \"audio.mp3\";\n\nAudioClient client = new(\n model: \"gpt-4o-transcribe\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nAudioTranscription transcription = client.TranscribeAudio(audioFilePath);\n\nConsole.WriteLine($\"{transcription.Text}\");\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst transcription = await client.audio.transcriptions.create({\n file: fs.createReadStream('speech.mp3'),\n model: 'gpt-4o-transcribe',\n});\n\nconsole.log(transcription);", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{\n File: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n Model: openai.AudioModelWhisper1,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", transcription)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.audio.AudioModel;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateParams;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateResponse;\nimport java.io.ByteArrayInputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n TranscriptionCreateParams params = TranscriptionCreateParams.builder()\n .file(ByteArrayInputStream(\"some content\".getBytes()))\n .model(AudioModel.WHISPER_1)\n .build();\n TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ntranscription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model: :\"whisper-1\")\n\nputs(transcription)" - }, - "response": "{\n \"text\": \"Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that.\",\n \"usage\": {\n \"type\": \"tokens\",\n \"input_tokens\": 14,\n \"input_token_details\": {\n \"text_tokens\": 0,\n \"audio_tokens\": 14\n },\n \"output_tokens\": 45,\n \"total_tokens\": 59\n }\n}\n" - }, - { - "title": "Streaming", - "request": { - "curl": "curl https://api.openai.com/v1/audio/transcriptions \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: multipart/form-data\" \\\n -F file=\"@/path/to/file/audio.mp3\" \\\n -F model=\"gpt-4o-mini-transcribe\" \\\n -F stream=true\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ntranscription = client.audio.transcriptions.create(\n file=b\"raw file contents\",\n model=\"gpt-4o-transcribe\",\n)\nprint(transcription)", - "javascript": "import fs from \"fs\";\nimport OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nconst stream = await openai.audio.transcriptions.create({\n file: fs.createReadStream(\"audio.mp3\"),\n model: \"gpt-4o-mini-transcribe\",\n stream: true,\n});\n\nfor await (const event of stream) {\n console.log(event);\n}\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst transcription = await client.audio.transcriptions.create({\n file: fs.createReadStream('speech.mp3'),\n model: 'gpt-4o-transcribe',\n});\n\nconsole.log(transcription);", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{\n File: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n Model: openai.AudioModelWhisper1,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", transcription)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.audio.AudioModel;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateParams;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateResponse;\nimport java.io.ByteArrayInputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n TranscriptionCreateParams params = TranscriptionCreateParams.builder()\n .file(ByteArrayInputStream(\"some content\".getBytes()))\n .model(AudioModel.WHISPER_1)\n .build();\n TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ntranscription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model: :\"whisper-1\")\n\nputs(transcription)" - }, - "response": "data: {\"type\":\"transcript.text.delta\",\"delta\":\"I\",\"logprobs\":[{\"token\":\"I\",\"logprob\":-0.00007588794,\"bytes\":[73]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" see\",\"logprobs\":[{\"token\":\" see\",\"logprob\":-3.1281633e-7,\"bytes\":[32,115,101,101]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" skies\",\"logprobs\":[{\"token\":\" skies\",\"logprob\":-2.3392786e-6,\"bytes\":[32,115,107,105,101,115]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" of\",\"logprobs\":[{\"token\":\" of\",\"logprob\":-3.1281633e-7,\"bytes\":[32,111,102]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" blue\",\"logprobs\":[{\"token\":\" blue\",\"logprob\":-1.0280384e-6,\"bytes\":[32,98,108,117,101]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" and\",\"logprobs\":[{\"token\":\" and\",\"logprob\":-0.0005108566,\"bytes\":[32,97,110,100]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" clouds\",\"logprobs\":[{\"token\":\" clouds\",\"logprob\":-1.9361265e-7,\"bytes\":[32,99,108,111,117,100,115]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" of\",\"logprobs\":[{\"token\":\" of\",\"logprob\":-1.9361265e-7,\"bytes\":[32,111,102]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" white\",\"logprobs\":[{\"token\":\" white\",\"logprob\":-7.89631e-7,\"bytes\":[32,119,104,105,116,101]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\",\",\"logprobs\":[{\"token\":\",\",\"logprob\":-0.0014890312,\"bytes\":[44]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" the\",\"logprobs\":[{\"token\":\" the\",\"logprob\":-0.0110956915,\"bytes\":[32,116,104,101]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" bright\",\"logprobs\":[{\"token\":\" bright\",\"logprob\":0.0,\"bytes\":[32,98,114,105,103,104,116]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" blessed\",\"logprobs\":[{\"token\":\" blessed\",\"logprob\":-0.000045848617,\"bytes\":[32,98,108,101,115,115,101,100]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" days\",\"logprobs\":[{\"token\":\" days\",\"logprob\":-0.000010802739,\"bytes\":[32,100,97,121,115]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\",\",\"logprobs\":[{\"token\":\",\",\"logprob\":-0.00001700133,\"bytes\":[44]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" the\",\"logprobs\":[{\"token\":\" the\",\"logprob\":-0.0000118755715,\"bytes\":[32,116,104,101]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" dark\",\"logprobs\":[{\"token\":\" dark\",\"logprob\":-5.5122365e-7,\"bytes\":[32,100,97,114,107]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" sacred\",\"logprobs\":[{\"token\":\" sacred\",\"logprob\":-5.4385737e-6,\"bytes\":[32,115,97,99,114,101,100]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" nights\",\"logprobs\":[{\"token\":\" nights\",\"logprob\":-4.00813e-6,\"bytes\":[32,110,105,103,104,116,115]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\",\",\"logprobs\":[{\"token\":\",\",\"logprob\":-0.0036910512,\"bytes\":[44]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" and\",\"logprobs\":[{\"token\":\" and\",\"logprob\":-0.0031903093,\"bytes\":[32,97,110,100]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" I\",\"logprobs\":[{\"token\":\" I\",\"logprob\":-1.504853e-6,\"bytes\":[32,73]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" think\",\"logprobs\":[{\"token\":\" think\",\"logprob\":-4.3202e-7,\"bytes\":[32,116,104,105,110,107]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" to\",\"logprobs\":[{\"token\":\" to\",\"logprob\":-1.9361265e-7,\"bytes\":[32,116,111]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" myself\",\"logprobs\":[{\"token\":\" myself\",\"logprob\":-1.7432603e-6,\"bytes\":[32,109,121,115,101,108,102]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\",\",\"logprobs\":[{\"token\":\",\",\"logprob\":-0.29254505,\"bytes\":[44]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" what\",\"logprobs\":[{\"token\":\" what\",\"logprob\":-0.016815351,\"bytes\":[32,119,104,97,116]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" a\",\"logprobs\":[{\"token\":\" a\",\"logprob\":-3.1281633e-7,\"bytes\":[32,97]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" wonderful\",\"logprobs\":[{\"token\":\" wonderful\",\"logprob\":-2.1008714e-6,\"bytes\":[32,119,111,110,100,101,114,102,117,108]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\" world\",\"logprobs\":[{\"token\":\" world\",\"logprob\":-8.180258e-6,\"bytes\":[32,119,111,114,108,100]}]}\n\ndata: {\"type\":\"transcript.text.delta\",\"delta\":\".\",\"logprobs\":[{\"token\":\".\",\"logprob\":-0.014231676,\"bytes\":[46]}]}\n\ndata: {\"type\":\"transcript.text.done\",\"text\":\"I see skies of blue and clouds of white, the bright blessed days, the dark sacred nights, and I think to myself, what a wonderful world.\",\"logprobs\":[{\"token\":\"I\",\"logprob\":-0.00007588794,\"bytes\":[73]},{\"token\":\" see\",\"logprob\":-3.1281633e-7,\"bytes\":[32,115,101,101]},{\"token\":\" skies\",\"logprob\":-2.3392786e-6,\"bytes\":[32,115,107,105,101,115]},{\"token\":\" of\",\"logprob\":-3.1281633e-7,\"bytes\":[32,111,102]},{\"token\":\" blue\",\"logprob\":-1.0280384e-6,\"bytes\":[32,98,108,117,101]},{\"token\":\" and\",\"logprob\":-0.0005108566,\"bytes\":[32,97,110,100]},{\"token\":\" clouds\",\"logprob\":-1.9361265e-7,\"bytes\":[32,99,108,111,117,100,115]},{\"token\":\" of\",\"logprob\":-1.9361265e-7,\"bytes\":[32,111,102]},{\"token\":\" white\",\"logprob\":-7.89631e-7,\"bytes\":[32,119,104,105,116,101]},{\"token\":\",\",\"logprob\":-0.0014890312,\"bytes\":[44]},{\"token\":\" the\",\"logprob\":-0.0110956915,\"bytes\":[32,116,104,101]},{\"token\":\" bright\",\"logprob\":0.0,\"bytes\":[32,98,114,105,103,104,116]},{\"token\":\" blessed\",\"logprob\":-0.000045848617,\"bytes\":[32,98,108,101,115,115,101,100]},{\"token\":\" days\",\"logprob\":-0.000010802739,\"bytes\":[32,100,97,121,115]},{\"token\":\",\",\"logprob\":-0.00001700133,\"bytes\":[44]},{\"token\":\" the\",\"logprob\":-0.0000118755715,\"bytes\":[32,116,104,101]},{\"token\":\" dark\",\"logprob\":-5.5122365e-7,\"bytes\":[32,100,97,114,107]},{\"token\":\" sacred\",\"logprob\":-5.4385737e-6,\"bytes\":[32,115,97,99,114,101,100]},{\"token\":\" nights\",\"logprob\":-4.00813e-6,\"bytes\":[32,110,105,103,104,116,115]},{\"token\":\",\",\"logprob\":-0.0036910512,\"bytes\":[44]},{\"token\":\" and\",\"logprob\":-0.0031903093,\"bytes\":[32,97,110,100]},{\"token\":\" I\",\"logprob\":-1.504853e-6,\"bytes\":[32,73]},{\"token\":\" think\",\"logprob\":-4.3202e-7,\"bytes\":[32,116,104,105,110,107]},{\"token\":\" to\",\"logprob\":-1.9361265e-7,\"bytes\":[32,116,111]},{\"token\":\" myself\",\"logprob\":-1.7432603e-6,\"bytes\":[32,109,121,115,101,108,102]},{\"token\":\",\",\"logprob\":-0.29254505,\"bytes\":[44]},{\"token\":\" what\",\"logprob\":-0.016815351,\"bytes\":[32,119,104,97,116]},{\"token\":\" a\",\"logprob\":-3.1281633e-7,\"bytes\":[32,97]},{\"token\":\" wonderful\",\"logprob\":-2.1008714e-6,\"bytes\":[32,119,111,110,100,101,114,102,117,108]},{\"token\":\" world\",\"logprob\":-8.180258e-6,\"bytes\":[32,119,111,114,108,100]},{\"token\":\".\",\"logprob\":-0.014231676,\"bytes\":[46]}],\"usage\":{\"input_tokens\":14,\"input_token_details\":{\"text_tokens\":0,\"audio_tokens\":14},\"output_tokens\":45,\"total_tokens\":59}}\n" - }, - { - "title": "Logprobs", - "request": { - "curl": "curl https://api.openai.com/v1/audio/transcriptions \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: multipart/form-data\" \\\n -F file=\"@/path/to/file/audio.mp3\" \\\n -F \"include[]=logprobs\" \\\n -F model=\"gpt-4o-transcribe\" \\\n -F response_format=\"json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ntranscription = client.audio.transcriptions.create(\n file=b\"raw file contents\",\n model=\"gpt-4o-transcribe\",\n)\nprint(transcription)", - "javascript": "import fs from \"fs\";\nimport OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nasync function main() {\n const transcription = await openai.audio.transcriptions.create({\n file: fs.createReadStream(\"audio.mp3\"),\n model: \"gpt-4o-transcribe\",\n response_format: \"json\",\n include: [\"logprobs\"]\n });\n\n console.log(transcription);\n}\nmain();\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst transcription = await client.audio.transcriptions.create({\n file: fs.createReadStream('speech.mp3'),\n model: 'gpt-4o-transcribe',\n});\n\nconsole.log(transcription);", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{\n File: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n Model: openai.AudioModelWhisper1,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", transcription)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.audio.AudioModel;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateParams;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateResponse;\nimport java.io.ByteArrayInputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n TranscriptionCreateParams params = TranscriptionCreateParams.builder()\n .file(ByteArrayInputStream(\"some content\".getBytes()))\n .model(AudioModel.WHISPER_1)\n .build();\n TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ntranscription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model: :\"whisper-1\")\n\nputs(transcription)" - }, - "response": "{\n \"text\": \"Hey, my knee is hurting and I want to see the doctor tomorrow ideally.\",\n \"logprobs\": [\n { \"token\": \"Hey\", \"logprob\": -1.0415299, \"bytes\": [72, 101, 121] },\n { \"token\": \",\", \"logprob\": -9.805982e-5, \"bytes\": [44] },\n { \"token\": \" my\", \"logprob\": -0.00229799, \"bytes\": [32, 109, 121] },\n {\n \"token\": \" knee\",\n \"logprob\": -4.7159858e-5,\n \"bytes\": [32, 107, 110, 101, 101]\n },\n { \"token\": \" is\", \"logprob\": -0.043909557, \"bytes\": [32, 105, 115] },\n {\n \"token\": \" hurting\",\n \"logprob\": -1.1041146e-5,\n \"bytes\": [32, 104, 117, 114, 116, 105, 110, 103]\n },\n { \"token\": \" and\", \"logprob\": -0.011076359, \"bytes\": [32, 97, 110, 100] },\n { \"token\": \" I\", \"logprob\": -5.3193703e-6, \"bytes\": [32, 73] },\n {\n \"token\": \" want\",\n \"logprob\": -0.0017156356,\n \"bytes\": [32, 119, 97, 110, 116]\n },\n { \"token\": \" to\", \"logprob\": -7.89631e-7, \"bytes\": [32, 116, 111] },\n { \"token\": \" see\", \"logprob\": -5.5122365e-7, \"bytes\": [32, 115, 101, 101] },\n { \"token\": \" the\", \"logprob\": -0.0040786397, \"bytes\": [32, 116, 104, 101] },\n {\n \"token\": \" doctor\",\n \"logprob\": -2.3392786e-6,\n \"bytes\": [32, 100, 111, 99, 116, 111, 114]\n },\n {\n \"token\": \" tomorrow\",\n \"logprob\": -7.89631e-7,\n \"bytes\": [32, 116, 111, 109, 111, 114, 114, 111, 119]\n },\n {\n \"token\": \" ideally\",\n \"logprob\": -0.5800861,\n \"bytes\": [32, 105, 100, 101, 97, 108, 108, 121]\n },\n { \"token\": \".\", \"logprob\": -0.00011093382, \"bytes\": [46] }\n ],\n \"usage\": {\n \"type\": \"tokens\",\n \"input_tokens\": 14,\n \"input_token_details\": {\n \"text_tokens\": 0,\n \"audio_tokens\": 14\n },\n \"output_tokens\": 45,\n \"total_tokens\": 59\n }\n}\n" - }, - { - "title": "Word timestamps", - "request": { - "curl": "curl https://api.openai.com/v1/audio/transcriptions \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: multipart/form-data\" \\\n -F file=\"@/path/to/file/audio.mp3\" \\\n -F \"timestamp_granularities[]=word\" \\\n -F model=\"whisper-1\" \\\n -F response_format=\"verbose_json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ntranscription = client.audio.transcriptions.create(\n file=b\"raw file contents\",\n model=\"gpt-4o-transcribe\",\n)\nprint(transcription)", - "javascript": "import fs from \"fs\";\nimport OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nasync function main() {\n const transcription = await openai.audio.transcriptions.create({\n file: fs.createReadStream(\"audio.mp3\"),\n model: \"whisper-1\",\n response_format: \"verbose_json\",\n timestamp_granularities: [\"word\"]\n });\n\n console.log(transcription.text);\n}\nmain();\n", - "csharp": "using System;\n\nusing OpenAI.Audio;\n\nstring audioFilePath = \"audio.mp3\";\n\nAudioClient client = new(\n model: \"whisper-1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nAudioTranscriptionOptions options = new()\n{\n ResponseFormat = AudioTranscriptionFormat.Verbose,\n TimestampGranularities = AudioTimestampGranularities.Word,\n};\n\nAudioTranscription transcription = client.TranscribeAudio(audioFilePath, options);\n\nConsole.WriteLine($\"{transcription.Text}\");\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst transcription = await client.audio.transcriptions.create({\n file: fs.createReadStream('speech.mp3'),\n model: 'gpt-4o-transcribe',\n});\n\nconsole.log(transcription);", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{\n File: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n Model: openai.AudioModelWhisper1,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", transcription)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.audio.AudioModel;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateParams;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateResponse;\nimport java.io.ByteArrayInputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n TranscriptionCreateParams params = TranscriptionCreateParams.builder()\n .file(ByteArrayInputStream(\"some content\".getBytes()))\n .model(AudioModel.WHISPER_1)\n .build();\n TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ntranscription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model: :\"whisper-1\")\n\nputs(transcription)" - }, - "response": "{\n \"task\": \"transcribe\",\n \"language\": \"english\",\n \"duration\": 8.470000267028809,\n \"text\": \"The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.\",\n \"words\": [\n {\n \"word\": \"The\",\n \"start\": 0.0,\n \"end\": 0.23999999463558197\n },\n ...\n {\n \"word\": \"volleyball\",\n \"start\": 7.400000095367432,\n \"end\": 7.900000095367432\n }\n ],\n \"usage\": {\n \"type\": \"duration\",\n \"seconds\": 9\n }\n}\n" - }, - { - "title": "Segment timestamps", - "request": { - "curl": "curl https://api.openai.com/v1/audio/transcriptions \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: multipart/form-data\" \\\n -F file=\"@/path/to/file/audio.mp3\" \\\n -F \"timestamp_granularities[]=segment\" \\\n -F model=\"whisper-1\" \\\n -F response_format=\"verbose_json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ntranscription = client.audio.transcriptions.create(\n file=b\"raw file contents\",\n model=\"gpt-4o-transcribe\",\n)\nprint(transcription)", - "javascript": "import fs from \"fs\";\nimport OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nasync function main() {\n const transcription = await openai.audio.transcriptions.create({\n file: fs.createReadStream(\"audio.mp3\"),\n model: \"whisper-1\",\n response_format: \"verbose_json\",\n timestamp_granularities: [\"segment\"]\n });\n\n console.log(transcription.text);\n}\nmain();\n", - "csharp": "using System;\n\nusing OpenAI.Audio;\n\nstring audioFilePath = \"audio.mp3\";\n\nAudioClient client = new(\n model: \"whisper-1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nAudioTranscriptionOptions options = new()\n{\n ResponseFormat = AudioTranscriptionFormat.Verbose,\n TimestampGranularities = AudioTimestampGranularities.Segment,\n};\n\nAudioTranscription transcription = client.TranscribeAudio(audioFilePath, options);\n\nConsole.WriteLine($\"{transcription.Text}\");\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst transcription = await client.audio.transcriptions.create({\n file: fs.createReadStream('speech.mp3'),\n model: 'gpt-4o-transcribe',\n});\n\nconsole.log(transcription);", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{\n File: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n Model: openai.AudioModelWhisper1,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", transcription)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.audio.AudioModel;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateParams;\nimport com.openai.models.audio.transcriptions.TranscriptionCreateResponse;\nimport java.io.ByteArrayInputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n TranscriptionCreateParams params = TranscriptionCreateParams.builder()\n .file(ByteArrayInputStream(\"some content\".getBytes()))\n .model(AudioModel.WHISPER_1)\n .build();\n TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ntranscription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model: :\"whisper-1\")\n\nputs(transcription)" - }, - "response": "{\n \"task\": \"transcribe\",\n \"language\": \"english\",\n \"duration\": 8.470000267028809,\n \"text\": \"The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.\",\n \"segments\": [\n {\n \"id\": 0,\n \"seek\": 0,\n \"start\": 0.0,\n \"end\": 3.319999933242798,\n \"text\": \" The beach was a popular spot on a hot summer day.\",\n \"tokens\": [\n 50364, 440, 7534, 390, 257, 3743, 4008, 322, 257, 2368, 4266, 786, 13, 50530\n ],\n \"temperature\": 0.0,\n \"avg_logprob\": -0.2860786020755768,\n \"compression_ratio\": 1.2363636493682861,\n \"no_speech_prob\": 0.00985979475080967\n },\n ...\n ],\n \"usage\": {\n \"type\": \"duration\",\n \"seconds\": 9\n }\n}\n" - } - ] - }, - "description": "Transcribes audio into the input language." - } - }, - "/audio/translations": { - "post": { - "operationId": "createTranslation", - "tags": [ - "Audio" - ], - "summary": "Create translation", - "requestBody": { - "required": true, - "content": { - "multipart/form-data": { - "schema": { - "$ref": "#/components/schemas/CreateTranslationRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "anyOf": [ - { - "$ref": "#/components/schemas/CreateTranslationResponseJson" - }, - { - "$ref": "#/components/schemas/CreateTranslationResponseVerboseJson", - "x-stainless-skip": [ - "go" - ] - } - ] - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create translation", - "group": "audio", - "returns": "The translated text.", - "examples": { - "response": "{\n \"text\": \"Hello, my name is Wolfgang and I come from Germany. Where are you heading today?\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/audio/translations \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: multipart/form-data\" \\\n -F file=\"@/path/to/file/german.m4a\" \\\n -F model=\"whisper-1\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ntranslation = client.audio.translations.create(\n file=b\"raw file contents\",\n model=\"whisper-1\",\n)\nprint(translation)", - "javascript": "import fs from \"fs\";\nimport OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nasync function main() {\n const translation = await openai.audio.translations.create({\n file: fs.createReadStream(\"speech.mp3\"),\n model: \"whisper-1\",\n });\n\n console.log(translation.text);\n}\nmain();\n", - "csharp": "using System;\n\nusing OpenAI.Audio;\n\nstring audioFilePath = \"audio.mp3\";\n\nAudioClient client = new(\n model: \"whisper-1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nAudioTranscription transcription = client.TranscribeAudio(audioFilePath);\n\nConsole.WriteLine($\"{transcription.Text}\");\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst translation = await client.audio.translations.create({\n file: fs.createReadStream('speech.mp3'),\n model: 'whisper-1',\n});\n\nconsole.log(translation);", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n translation, err := client.Audio.Translations.New(context.TODO(), openai.AudioTranslationNewParams{\n File: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n Model: openai.AudioModelWhisper1,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", translation)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.audio.AudioModel;\nimport com.openai.models.audio.translations.TranslationCreateParams;\nimport com.openai.models.audio.translations.TranslationCreateResponse;\nimport java.io.ByteArrayInputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n TranslationCreateParams params = TranslationCreateParams.builder()\n .file(ByteArrayInputStream(\"some content\".getBytes()))\n .model(AudioModel.WHISPER_1)\n .build();\n TranslationCreateResponse translation = client.audio().translations().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ntranslation = openai.audio.translations.create(file: Pathname(__FILE__), model: :\"whisper-1\")\n\nputs(translation)" - } - } - }, - "description": "Translates audio into English." - } - }, - "/batches": { - "post": { - "summary": "Create batch", - "operationId": "createBatch", - "tags": [ - "Batch" - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "type": "object", - "required": [ - "input_file_id", - "endpoint", - "completion_window" - ], - "properties": { - "input_file_id": { - "type": "string", - "description": "The ID of an uploaded file that contains requests for the new batch.\n\nSee [upload file](https://platform.openai.com/docs/api-reference/files/create) for how to upload a file.\n\nYour input file must be formatted as a [JSONL file](https://platform.openai.com/docs/api-reference/batch/request-input), and must be uploaded with the purpose `batch`. The file can contain up to 50,000 requests, and can be up to 200 MB in size.\n" - }, - "endpoint": { - "type": "string", - "enum": [ - "/v1/responses", - "/v1/chat/completions", - "/v1/embeddings", - "/v1/completions" - ], - "description": "The endpoint to be used for all requests in the batch. Currently `/v1/responses`, `/v1/chat/completions`, `/v1/embeddings`, and `/v1/completions` are supported. Note that `/v1/embeddings` batches are also restricted to a maximum of 50,000 embedding inputs across all requests in the batch." - }, - "completion_window": { - "type": "string", - "enum": [ - "24h" - ], - "description": "The time frame within which the batch should be processed. Currently only `24h` is supported." - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "output_expires_after": { - "$ref": "#/components/schemas/BatchFileExpirationAfter" - } - } - } - } - } - }, - "responses": { - "200": { - "description": "Batch created successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Batch" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create batch", - "group": "batch", - "returns": "The created [Batch](https://platform.openai.com/docs/api-reference/batch/object) object.", - "examples": { - "response": "{\n \"id\": \"batch_abc123\",\n \"object\": \"batch\",\n \"endpoint\": \"/v1/chat/completions\",\n \"errors\": null,\n \"input_file_id\": \"file-abc123\",\n \"completion_window\": \"24h\",\n \"status\": \"validating\",\n \"output_file_id\": null,\n \"error_file_id\": null,\n \"created_at\": 1711471533,\n \"in_progress_at\": null,\n \"expires_at\": null,\n \"finalizing_at\": null,\n \"completed_at\": null,\n \"failed_at\": null,\n \"expired_at\": null,\n \"cancelling_at\": null,\n \"cancelled_at\": null,\n \"request_counts\": {\n \"total\": 0,\n \"completed\": 0,\n \"failed\": 0\n },\n \"metadata\": {\n \"customer_id\": \"user_123456789\",\n \"batch_description\": \"Nightly eval job\",\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/batches \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"input_file_id\": \"file-abc123\",\n \"endpoint\": \"/v1/chat/completions\",\n \"completion_window\": \"24h\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nbatch = client.batches.create(\n completion_window=\"24h\",\n endpoint=\"/v1/responses\",\n input_file_id=\"input_file_id\",\n)\nprint(batch.id)", - "node": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nasync function main() {\n const batch = await openai.batches.create({\n input_file_id: \"file-abc123\",\n endpoint: \"/v1/chat/completions\",\n completion_window: \"24h\"\n });\n\n console.log(batch);\n}\n\nmain();\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst batch = await client.batches.create({\n completion_window: '24h',\n endpoint: '/v1/responses',\n input_file_id: 'input_file_id',\n});\n\nconsole.log(batch.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n batch, err := client.Batches.New(context.TODO(), openai.BatchNewParams{\n CompletionWindow: openai.BatchNewParamsCompletionWindow24h,\n Endpoint: openai.BatchNewParamsEndpointV1Responses,\n InputFileID: \"input_file_id\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", batch.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.batches.Batch;\nimport com.openai.models.batches.BatchCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n BatchCreateParams params = BatchCreateParams.builder()\n .completionWindow(BatchCreateParams.CompletionWindow._24H)\n .endpoint(BatchCreateParams.Endpoint.V1_RESPONSES)\n .inputFileId(\"input_file_id\")\n .build();\n Batch batch = client.batches().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nbatch = openai.batches.create(\n completion_window: :\"24h\",\n endpoint: :\"/v1/responses\",\n input_file_id: \"input_file_id\"\n)\n\nputs(batch)" - } - } - }, - "description": "Creates and executes a batch from an uploaded file of requests" - }, - "get": { - "operationId": "listBatches", - "tags": [ - "Batch" - ], - "summary": "List batch", - "parameters": [ - { - "in": "query", - "name": "after", - "required": false, - "schema": { - "type": "string" - }, - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n" - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - } - ], - "responses": { - "200": { - "description": "Batch listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListBatchesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List batch", - "group": "batch", - "returns": "A list of paginated [Batch](https://platform.openai.com/docs/api-reference/batch/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"batch_abc123\",\n \"object\": \"batch\",\n \"endpoint\": \"/v1/chat/completions\",\n \"errors\": null,\n \"input_file_id\": \"file-abc123\",\n \"completion_window\": \"24h\",\n \"status\": \"completed\",\n \"output_file_id\": \"file-cvaTdG\",\n \"error_file_id\": \"file-HOWS94\",\n \"created_at\": 1711471533,\n \"in_progress_at\": 1711471538,\n \"expires_at\": 1711557933,\n \"finalizing_at\": 1711493133,\n \"completed_at\": 1711493163,\n \"failed_at\": null,\n \"expired_at\": null,\n \"cancelling_at\": null,\n \"cancelled_at\": null,\n \"request_counts\": {\n \"total\": 100,\n \"completed\": 95,\n \"failed\": 5\n },\n \"metadata\": {\n \"customer_id\": \"user_123456789\",\n \"batch_description\": \"Nightly job\",\n }\n },\n { ... },\n ],\n \"first_id\": \"batch_abc123\",\n \"last_id\": \"batch_abc456\",\n \"has_more\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/batches?limit=2 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.batches.list()\npage = page.data[0]\nprint(page.id)", - "node": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nasync function main() {\n const list = await openai.batches.list();\n\n for await (const batch of list) {\n console.log(batch);\n }\n}\n\nmain();\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const batch of client.batches.list()) {\n console.log(batch.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Batches.List(context.TODO(), openai.BatchListParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.batches.BatchListPage;\nimport com.openai.models.batches.BatchListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n BatchListPage page = client.batches().list();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.batches.list\n\nputs(page)" - } - } - }, - "description": "List your organization's batches." - } - }, - "/batches/{batch_id}": { - "get": { - "operationId": "retrieveBatch", - "tags": [ - "Batch" - ], - "summary": "Retrieve batch", - "parameters": [ - { - "in": "path", - "name": "batch_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the batch to retrieve." - } - ], - "responses": { - "200": { - "description": "Batch retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Batch" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve batch", - "group": "batch", - "returns": "The [Batch](https://platform.openai.com/docs/api-reference/batch/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"batch_abc123\",\n \"object\": \"batch\",\n \"endpoint\": \"/v1/completions\",\n \"errors\": null,\n \"input_file_id\": \"file-abc123\",\n \"completion_window\": \"24h\",\n \"status\": \"completed\",\n \"output_file_id\": \"file-cvaTdG\",\n \"error_file_id\": \"file-HOWS94\",\n \"created_at\": 1711471533,\n \"in_progress_at\": 1711471538,\n \"expires_at\": 1711557933,\n \"finalizing_at\": 1711493133,\n \"completed_at\": 1711493163,\n \"failed_at\": null,\n \"expired_at\": null,\n \"cancelling_at\": null,\n \"cancelled_at\": null,\n \"request_counts\": {\n \"total\": 100,\n \"completed\": 95,\n \"failed\": 5\n },\n \"metadata\": {\n \"customer_id\": \"user_123456789\",\n \"batch_description\": \"Nightly eval job\",\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/batches/batch_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nbatch = client.batches.retrieve(\n \"batch_id\",\n)\nprint(batch.id)", - "node": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nasync function main() {\n const batch = await openai.batches.retrieve(\"batch_abc123\");\n\n console.log(batch);\n}\n\nmain();\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst batch = await client.batches.retrieve('batch_id');\n\nconsole.log(batch.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n batch, err := client.Batches.Get(context.TODO(), \"batch_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", batch.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.batches.Batch;\nimport com.openai.models.batches.BatchRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Batch batch = client.batches().retrieve(\"batch_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nbatch = openai.batches.retrieve(\"batch_id\")\n\nputs(batch)" - } - } - }, - "description": "Retrieves a batch." - } - }, - "/batches/{batch_id}/cancel": { - "post": { - "operationId": "cancelBatch", - "tags": [ - "Batch" - ], - "summary": "Cancel batch", - "parameters": [ - { - "in": "path", - "name": "batch_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the batch to cancel." - } - ], - "responses": { - "200": { - "description": "Batch is cancelling. Returns the cancelling batch's details.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Batch" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Cancel batch", - "group": "batch", - "returns": "The [Batch](https://platform.openai.com/docs/api-reference/batch/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"batch_abc123\",\n \"object\": \"batch\",\n \"endpoint\": \"/v1/chat/completions\",\n \"errors\": null,\n \"input_file_id\": \"file-abc123\",\n \"completion_window\": \"24h\",\n \"status\": \"cancelling\",\n \"output_file_id\": null,\n \"error_file_id\": null,\n \"created_at\": 1711471533,\n \"in_progress_at\": 1711471538,\n \"expires_at\": 1711557933,\n \"finalizing_at\": null,\n \"completed_at\": null,\n \"failed_at\": null,\n \"expired_at\": null,\n \"cancelling_at\": 1711475133,\n \"cancelled_at\": null,\n \"request_counts\": {\n \"total\": 100,\n \"completed\": 23,\n \"failed\": 1\n },\n \"metadata\": {\n \"customer_id\": \"user_123456789\",\n \"batch_description\": \"Nightly eval job\",\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/batches/batch_abc123/cancel \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -X POST\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nbatch = client.batches.cancel(\n \"batch_id\",\n)\nprint(batch.id)", - "node": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nasync function main() {\n const batch = await openai.batches.cancel(\"batch_abc123\");\n\n console.log(batch);\n}\n\nmain();\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst batch = await client.batches.cancel('batch_id');\n\nconsole.log(batch.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n batch, err := client.Batches.Cancel(context.TODO(), \"batch_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", batch.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.batches.Batch;\nimport com.openai.models.batches.BatchCancelParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Batch batch = client.batches().cancel(\"batch_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nbatch = openai.batches.cancel(\"batch_id\")\n\nputs(batch)" - } - } - }, - "description": "Cancels an in-progress batch. The batch will be in status `cancelling` for up to 10 minutes, before changing to `cancelled`, where it will have partial results (if any) available in the output file." - } - }, - "/chat/completions": { - "get": { - "operationId": "listChatCompletions", - "tags": [ - "Chat" - ], - "summary": "List Chat Completions", - "parameters": [ - { - "name": "model", - "in": "query", - "description": "The model used to generate the Chat Completions.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "metadata", - "in": "query", - "description": "A list of metadata keys to filter the Chat Completions by. Example:\n\n`metadata[key1]=value1&metadata[key2]=value2`\n", - "required": false, - "schema": { - "$ref": "#/components/schemas/Metadata" - } - }, - { - "name": "after", - "in": "query", - "description": "Identifier for the last chat completion from the previous pagination request.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "Number of Chat Completions to retrieve.", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order for Chat Completions by timestamp. Use `asc` for ascending order or `desc` for descending order. Defaults to `asc`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "asc", - "desc" - ], - "default": "asc" - } - } - ], - "responses": { - "200": { - "description": "A list of Chat Completions", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ChatCompletionList" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List Chat Completions", - "group": "chat", - "returns": "A list of [Chat Completions](https://platform.openai.com/docs/api-reference/chat/list-object) matching the specified filters.", - "path": "list", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"chat.completion\",\n \"id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2\",\n \"model\": \"gpt-4.1-2025-04-14\",\n \"created\": 1738960610,\n \"request_id\": \"req_ded8ab984ec4bf840f37566c1011c417\",\n \"tool_choice\": null,\n \"usage\": {\n \"total_tokens\": 31,\n \"completion_tokens\": 18,\n \"prompt_tokens\": 13\n },\n \"seed\": 4944116822809979520,\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"presence_penalty\": 0.0,\n \"frequency_penalty\": 0.0,\n \"system_fingerprint\": \"fp_50cad350e4\",\n \"input_user\": null,\n \"service_tier\": \"default\",\n \"tools\": null,\n \"metadata\": {},\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"content\": \"Mind of circuits hum, \\nLearning patterns in silenceโ€” \\nFuture's quiet spark.\",\n \"role\": \"assistant\",\n \"tool_calls\": null,\n \"function_call\": null\n },\n \"finish_reason\": \"stop\",\n \"logprobs\": null\n }\n ],\n \"response_format\": null\n }\n ],\n \"first_id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2\",\n \"last_id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/chat/completions \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.chat.completions.list()\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const chatCompletion of client.chat.completions.list()) {\n console.log(chatCompletion.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Chat.Completions.List(context.TODO(), openai.ChatCompletionListParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.chat.completions.ChatCompletionListPage;\nimport com.openai.models.chat.completions.ChatCompletionListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ChatCompletionListPage page = client.chat().completions().list();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.chat.completions.list\n\nputs(page)" - } - } - }, - "description": "List stored Chat Completions. Only Chat Completions that have been stored\nwith the `store` parameter set to `true` will be returned.\n" - }, - "post": { - "operationId": "createChatCompletion", - "tags": [ - "Chat" - ], - "summary": "Create chat completion", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateChatCompletionRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateChatCompletionResponse" - } - }, - "text/event-stream": { - "schema": { - "$ref": "#/components/schemas/CreateChatCompletionStreamResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create chat completion", - "group": "chat", - "returns": "Returns a [chat completion](https://platform.openai.com/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](https://platform.openai.com/docs/api-reference/chat/streaming) objects if the request is streamed.\n", - "path": "create", - "examples": [ - { - "title": "Default", - "request": { - "curl": "curl https://api.openai.com/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"VAR_chat_model_id\",\n \"messages\": [\n {\n \"role\": \"developer\",\n \"content\": \"You are a helpful assistant.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Hello!\"\n }\n ]\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nchat_completion = client.chat.completions.create(\n messages=[{\n \"content\": \"string\",\n \"role\": \"developer\",\n }],\n model=\"gpt-4o\",\n)\nprint(chat_completion)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst chatCompletion = await client.chat.completions.create({\n messages: [{ content: 'string', role: 'developer' }],\n model: 'gpt-4o',\n});\n\nconsole.log(chatCompletion);", - "csharp": "using System;\nusing System.Collections.Generic;\n\nusing OpenAI.Chat;\n\nChatClient client = new(\n model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nList messages =\n[\n new SystemChatMessage(\"You are a helpful assistant.\"),\n new UserChatMessage(\"Hello!\")\n];\n\nChatCompletion completion = client.CompleteChat(messages);\n\nConsole.WriteLine(completion.Content[0].Text);\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/shared\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{\n Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{\n OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{\n Content: openai.ChatCompletionDeveloperMessageParamContentUnion{\n OfString: openai.String(\"string\"),\n },\n },\n }},\n Model: shared.ChatModelGPT5,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", chatCompletion)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.ChatModel;\nimport com.openai.models.chat.completions.ChatCompletion;\nimport com.openai.models.chat.completions.ChatCompletionCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()\n .addDeveloperMessage(\"string\")\n .model(ChatModel.GPT_5)\n .build();\n ChatCompletion chatCompletion = client.chat().completions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nchat_completion = openai.chat.completions.create(messages: [{content: \"string\", role: :developer}], model: :\"gpt-5\")\n\nputs(chat_completion)" - }, - "response": "{\n \"id\": \"chatcmpl-B9MBs8CjcvOU2jLn4n570S5qMJKcT\",\n \"object\": \"chat.completion\",\n \"created\": 1741569952,\n \"model\": \"gpt-4.1-2025-04-14\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"Hello! How can I assist you today?\",\n \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 19,\n \"completion_tokens\": 10,\n \"total_tokens\": 29,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": \"default\"\n}\n" - }, - { - "title": "Image input", - "request": { - "curl": "curl https://api.openai.com/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-4.1\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": \"What is in this image?\"\n },\n {\n \"type\": \"image_url\",\n \"image_url\": {\n \"url\": \"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg\"\n }\n }\n ]\n }\n ],\n \"max_tokens\": 300\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nchat_completion = client.chat.completions.create(\n messages=[{\n \"content\": \"string\",\n \"role\": \"developer\",\n }],\n model=\"gpt-4o\",\n)\nprint(chat_completion)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst chatCompletion = await client.chat.completions.create({\n messages: [{ content: 'string', role: 'developer' }],\n model: 'gpt-4o',\n});\n\nconsole.log(chatCompletion);", - "csharp": "using System;\nusing System.Collections.Generic;\n\nusing OpenAI.Chat;\n\nChatClient client = new(\n model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nList messages =\n[\n new UserChatMessage(\n [\n ChatMessageContentPart.CreateTextPart(\"What's in this image?\"),\n ChatMessageContentPart.CreateImagePart(new Uri(\"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg\"))\n ])\n];\n\nChatCompletion completion = client.CompleteChat(messages);\n\nConsole.WriteLine(completion.Content[0].Text);\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/shared\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{\n Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{\n OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{\n Content: openai.ChatCompletionDeveloperMessageParamContentUnion{\n OfString: openai.String(\"string\"),\n },\n },\n }},\n Model: shared.ChatModelGPT5,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", chatCompletion)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.ChatModel;\nimport com.openai.models.chat.completions.ChatCompletion;\nimport com.openai.models.chat.completions.ChatCompletionCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()\n .addDeveloperMessage(\"string\")\n .model(ChatModel.GPT_5)\n .build();\n ChatCompletion chatCompletion = client.chat().completions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nchat_completion = openai.chat.completions.create(messages: [{content: \"string\", role: :developer}], model: :\"gpt-5\")\n\nputs(chat_completion)" - }, - "response": "{\n \"id\": \"chatcmpl-B9MHDbslfkBeAs8l4bebGdFOJ6PeG\",\n \"object\": \"chat.completion\",\n \"created\": 1741570283,\n \"model\": \"gpt-4.1-2025-04-14\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"The image shows a wooden boardwalk path running through a lush green field or meadow. The sky is bright blue with some scattered clouds, giving the scene a serene and peaceful atmosphere. Trees and shrubs are visible in the background.\",\n \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 1117,\n \"completion_tokens\": 46,\n \"total_tokens\": 1163,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": \"default\"\n}\n" - }, - { - "title": "Streaming", - "request": { - "curl": "curl https://api.openai.com/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"VAR_chat_model_id\",\n \"messages\": [\n {\n \"role\": \"developer\",\n \"content\": \"You are a helpful assistant.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Hello!\"\n }\n ],\n \"stream\": true\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nchat_completion = client.chat.completions.create(\n messages=[{\n \"content\": \"string\",\n \"role\": \"developer\",\n }],\n model=\"gpt-4o\",\n)\nprint(chat_completion)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst chatCompletion = await client.chat.completions.create({\n messages: [{ content: 'string', role: 'developer' }],\n model: 'gpt-4o',\n});\n\nconsole.log(chatCompletion);", - "csharp": "using System;\nusing System.ClientModel;\nusing System.Collections.Generic;\nusing System.Threading.Tasks;\n\nusing OpenAI.Chat;\n\nChatClient client = new( model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nList messages =\n[ new SystemChatMessage(\"You are a helpful assistant.\"),\n new UserChatMessage(\"Hello!\")\n];\n\nAsyncCollectionResult completionUpdates = client.CompleteChatStreamingAsync(messages);\n\nawait foreach (StreamingChatCompletionUpdate completionUpdate in completionUpdates)\n{ if (completionUpdate.ContentUpdate.Count > 0)\n {\n Console.Write(completionUpdate.ContentUpdate[0].Text);\n }\n}\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/shared\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{\n Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{\n OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{\n Content: openai.ChatCompletionDeveloperMessageParamContentUnion{\n OfString: openai.String(\"string\"),\n },\n },\n }},\n Model: shared.ChatModelGPT5,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", chatCompletion)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.ChatModel;\nimport com.openai.models.chat.completions.ChatCompletion;\nimport com.openai.models.chat.completions.ChatCompletionCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()\n .addDeveloperMessage(\"string\")\n .model(ChatModel.GPT_5)\n .build();\n ChatCompletion chatCompletion = client.chat().completions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nchat_completion = openai.chat.completions.create(messages: [{content: \"string\", role: :developer}], model: :\"gpt-5\")\n\nputs(chat_completion)" - }, - "response": "{\"id\":\"chatcmpl-123\",\"object\":\"chat.completion.chunk\",\"created\":1694268190,\"model\":\"gpt-4o-mini\", \"system_fingerprint\": \"fp_44709d6fcb\", \"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\"},\"logprobs\":null,\"finish_reason\":null}]}\n\n{\"id\":\"chatcmpl-123\",\"object\":\"chat.completion.chunk\",\"created\":1694268190,\"model\":\"gpt-4o-mini\", \"system_fingerprint\": \"fp_44709d6fcb\", \"choices\":[{\"index\":0,\"delta\":{\"content\":\"Hello\"},\"logprobs\":null,\"finish_reason\":null}]}\n\n....\n\n{\"id\":\"chatcmpl-123\",\"object\":\"chat.completion.chunk\",\"created\":1694268190,\"model\":\"gpt-4o-mini\", \"system_fingerprint\": \"fp_44709d6fcb\", \"choices\":[{\"index\":0,\"delta\":{},\"logprobs\":null,\"finish_reason\":\"stop\"}]}\n" - }, - { - "title": "Functions", - "request": { - "curl": "curl https://api.openai.com/v1/chat/completions \\\n-H \"Content-Type: application/json\" \\\n-H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n-d '{\n \"model\": \"gpt-4.1\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"What is the weather like in Boston today?\"\n }\n ],\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather in a given location\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and state, e.g. San Francisco, CA\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\"celsius\", \"fahrenheit\"]\n }\n },\n \"required\": [\"location\"]\n }\n }\n }\n ],\n \"tool_choice\": \"auto\"\n}'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nchat_completion = client.chat.completions.create(\n messages=[{\n \"content\": \"string\",\n \"role\": \"developer\",\n }],\n model=\"gpt-4o\",\n)\nprint(chat_completion)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst chatCompletion = await client.chat.completions.create({\n messages: [{ content: 'string', role: 'developer' }],\n model: 'gpt-4o',\n});\n\nconsole.log(chatCompletion);", - "csharp": "using System;\nusing System.Collections.Generic;\n\nusing OpenAI.Chat;\n\nChatClient client = new(\n model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nChatTool getCurrentWeatherTool = ChatTool.CreateFunctionTool(\n functionName: \"get_current_weather\",\n functionDescription: \"Get the current weather in a given location\",\n functionParameters: BinaryData.FromString(\"\"\"\n {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and state, e.g. San Francisco, CA\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [ \"celsius\", \"fahrenheit\" ]\n }\n },\n \"required\": [ \"location\" ]\n }\n \"\"\")\n);\n\nList messages =\n[\n new UserChatMessage(\"What's the weather like in Boston today?\"),\n];\n\nChatCompletionOptions options = new()\n{\n Tools =\n {\n getCurrentWeatherTool\n },\n ToolChoice = ChatToolChoice.CreateAutoChoice(),\n};\n\nChatCompletion completion = client.CompleteChat(messages, options);\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/shared\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{\n Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{\n OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{\n Content: openai.ChatCompletionDeveloperMessageParamContentUnion{\n OfString: openai.String(\"string\"),\n },\n },\n }},\n Model: shared.ChatModelGPT5,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", chatCompletion)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.ChatModel;\nimport com.openai.models.chat.completions.ChatCompletion;\nimport com.openai.models.chat.completions.ChatCompletionCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()\n .addDeveloperMessage(\"string\")\n .model(ChatModel.GPT_5)\n .build();\n ChatCompletion chatCompletion = client.chat().completions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nchat_completion = openai.chat.completions.create(messages: [{content: \"string\", role: :developer}], model: :\"gpt-5\")\n\nputs(chat_completion)" - }, - "response": "{\n \"id\": \"chatcmpl-abc123\",\n \"object\": \"chat.completion\",\n \"created\": 1699896916,\n \"model\": \"gpt-4o-mini\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": null,\n \"tool_calls\": [\n {\n \"id\": \"call_abc123\",\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"arguments\": \"{\\n\\\"location\\\": \\\"Boston, MA\\\"\\n}\"\n }\n }\n ]\n },\n \"logprobs\": null,\n \"finish_reason\": \"tool_calls\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 82,\n \"completion_tokens\": 17,\n \"total_tokens\": 99,\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n }\n }\n}\n" - }, - { - "title": "Logprobs", - "request": { - "curl": "curl https://api.openai.com/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"VAR_chat_model_id\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Hello!\"\n }\n ],\n \"logprobs\": true,\n \"top_logprobs\": 2\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nchat_completion = client.chat.completions.create(\n messages=[{\n \"content\": \"string\",\n \"role\": \"developer\",\n }],\n model=\"gpt-4o\",\n)\nprint(chat_completion)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst chatCompletion = await client.chat.completions.create({\n messages: [{ content: 'string', role: 'developer' }],\n model: 'gpt-4o',\n});\n\nconsole.log(chatCompletion);", - "csharp": "using System;\nusing System.Collections.Generic;\n\nusing OpenAI.Chat;\n\nChatClient client = new(\n model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nList messages =\n[\n new UserChatMessage(\"Hello!\")\n];\n\nChatCompletionOptions options = new()\n{\n IncludeLogProbabilities = true,\n TopLogProbabilityCount = 2\n};\n\nChatCompletion completion = client.CompleteChat(messages, options);\n\nConsole.WriteLine(completion.Content[0].Text);\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/shared\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{\n Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{\n OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{\n Content: openai.ChatCompletionDeveloperMessageParamContentUnion{\n OfString: openai.String(\"string\"),\n },\n },\n }},\n Model: shared.ChatModelGPT5,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", chatCompletion)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.ChatModel;\nimport com.openai.models.chat.completions.ChatCompletion;\nimport com.openai.models.chat.completions.ChatCompletionCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()\n .addDeveloperMessage(\"string\")\n .model(ChatModel.GPT_5)\n .build();\n ChatCompletion chatCompletion = client.chat().completions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nchat_completion = openai.chat.completions.create(messages: [{content: \"string\", role: :developer}], model: :\"gpt-5\")\n\nputs(chat_completion)" - }, - "response": "{\n \"id\": \"chatcmpl-123\",\n \"object\": \"chat.completion\",\n \"created\": 1702685778,\n \"model\": \"gpt-4o-mini\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"Hello! How can I assist you today?\"\n },\n \"logprobs\": {\n \"content\": [\n {\n \"token\": \"Hello\",\n \"logprob\": -0.31725305,\n \"bytes\": [72, 101, 108, 108, 111],\n \"top_logprobs\": [\n {\n \"token\": \"Hello\",\n \"logprob\": -0.31725305,\n \"bytes\": [72, 101, 108, 108, 111]\n },\n {\n \"token\": \"Hi\",\n \"logprob\": -1.3190403,\n \"bytes\": [72, 105]\n }\n ]\n },\n {\n \"token\": \"!\",\n \"logprob\": -0.02380986,\n \"bytes\": [\n 33\n ],\n \"top_logprobs\": [\n {\n \"token\": \"!\",\n \"logprob\": -0.02380986,\n \"bytes\": [33]\n },\n {\n \"token\": \" there\",\n \"logprob\": -3.787621,\n \"bytes\": [32, 116, 104, 101, 114, 101]\n }\n ]\n },\n {\n \"token\": \" How\",\n \"logprob\": -0.000054669687,\n \"bytes\": [32, 72, 111, 119],\n \"top_logprobs\": [\n {\n \"token\": \" How\",\n \"logprob\": -0.000054669687,\n \"bytes\": [32, 72, 111, 119]\n },\n {\n \"token\": \"<|end|>\",\n \"logprob\": -10.953937,\n \"bytes\": null\n }\n ]\n },\n {\n \"token\": \" can\",\n \"logprob\": -0.015801601,\n \"bytes\": [32, 99, 97, 110],\n \"top_logprobs\": [\n {\n \"token\": \" can\",\n \"logprob\": -0.015801601,\n \"bytes\": [32, 99, 97, 110]\n },\n {\n \"token\": \" may\",\n \"logprob\": -4.161023,\n \"bytes\": [32, 109, 97, 121]\n }\n ]\n },\n {\n \"token\": \" I\",\n \"logprob\": -3.7697225e-6,\n \"bytes\": [\n 32,\n 73\n ],\n \"top_logprobs\": [\n {\n \"token\": \" I\",\n \"logprob\": -3.7697225e-6,\n \"bytes\": [32, 73]\n },\n {\n \"token\": \" assist\",\n \"logprob\": -13.596657,\n \"bytes\": [32, 97, 115, 115, 105, 115, 116]\n }\n ]\n },\n {\n \"token\": \" assist\",\n \"logprob\": -0.04571125,\n \"bytes\": [32, 97, 115, 115, 105, 115, 116],\n \"top_logprobs\": [\n {\n \"token\": \" assist\",\n \"logprob\": -0.04571125,\n \"bytes\": [32, 97, 115, 115, 105, 115, 116]\n },\n {\n \"token\": \" help\",\n \"logprob\": -3.1089056,\n \"bytes\": [32, 104, 101, 108, 112]\n }\n ]\n },\n {\n \"token\": \" you\",\n \"logprob\": -5.4385737e-6,\n \"bytes\": [32, 121, 111, 117],\n \"top_logprobs\": [\n {\n \"token\": \" you\",\n \"logprob\": -5.4385737e-6,\n \"bytes\": [32, 121, 111, 117]\n },\n {\n \"token\": \" today\",\n \"logprob\": -12.807695,\n \"bytes\": [32, 116, 111, 100, 97, 121]\n }\n ]\n },\n {\n \"token\": \" today\",\n \"logprob\": -0.0040071653,\n \"bytes\": [32, 116, 111, 100, 97, 121],\n \"top_logprobs\": [\n {\n \"token\": \" today\",\n \"logprob\": -0.0040071653,\n \"bytes\": [32, 116, 111, 100, 97, 121]\n },\n {\n \"token\": \"?\",\n \"logprob\": -5.5247097,\n \"bytes\": [63]\n }\n ]\n },\n {\n \"token\": \"?\",\n \"logprob\": -0.0008108172,\n \"bytes\": [63],\n \"top_logprobs\": [\n {\n \"token\": \"?\",\n \"logprob\": -0.0008108172,\n \"bytes\": [63]\n },\n {\n \"token\": \"?\\n\",\n \"logprob\": -7.184561,\n \"bytes\": [63, 10]\n }\n ]\n }\n ]\n },\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 9,\n \"completion_tokens\": 9,\n \"total_tokens\": 18,\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"system_fingerprint\": null\n}\n" - } - ] - }, - "description": "**Starting a new project?** We recommend trying [Responses](https://platform.openai.com/docs/api-reference/responses)\nto take advantage of the latest OpenAI platform features. Compare\n[Chat Completions with Responses](https://platform.openai.com/docs/guides/responses-vs-chat-completions?api-mode=responses).\n\n---\n\nCreates a model response for the given chat conversation. Learn more in the\n[text generation](https://platform.openai.com/docs/guides/text-generation), [vision](https://platform.openai.com/docs/guides/vision),\nand [audio](https://platform.openai.com/docs/guides/audio) guides.\n\nParameter support can differ depending on the model used to generate the\nresponse, particularly for newer reasoning models. Parameters that are only\nsupported for reasoning models are noted below. For the current state of\nunsupported parameters in reasoning models,\n[refer to the reasoning guide](https://platform.openai.com/docs/guides/reasoning).\n" - } - }, - "/chat/completions/{completion_id}": { - "get": { - "operationId": "getChatCompletion", - "tags": [ - "Chat" - ], - "summary": "Get chat completion", - "parameters": [ - { - "in": "path", - "name": "completion_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the chat completion to retrieve." - } - ], - "responses": { - "200": { - "description": "A chat completion", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateChatCompletionResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Get chat completion", - "group": "chat", - "returns": "The [ChatCompletion](https://platform.openai.com/docs/api-reference/chat/object) object matching the specified ID.", - "examples": { - "response": "{\n \"object\": \"chat.completion\",\n \"id\": \"chatcmpl-abc123\",\n \"model\": \"gpt-4o-2024-08-06\",\n \"created\": 1738960610,\n \"request_id\": \"req_ded8ab984ec4bf840f37566c1011c417\",\n \"tool_choice\": null,\n \"usage\": {\n \"total_tokens\": 31,\n \"completion_tokens\": 18,\n \"prompt_tokens\": 13\n },\n \"seed\": 4944116822809979520,\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"presence_penalty\": 0.0,\n \"frequency_penalty\": 0.0,\n \"system_fingerprint\": \"fp_50cad350e4\",\n \"input_user\": null,\n \"service_tier\": \"default\",\n \"tools\": null,\n \"metadata\": {},\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"content\": \"Mind of circuits hum, \\nLearning patterns in silenceโ€” \\nFuture's quiet spark.\",\n \"role\": \"assistant\",\n \"tool_calls\": null,\n \"function_call\": null\n },\n \"finish_reason\": \"stop\",\n \"logprobs\": null\n }\n ],\n \"response_format\": null\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/chat/completions/chatcmpl-abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nchat_completion = client.chat.completions.retrieve(\n \"completion_id\",\n)\nprint(chat_completion.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst chatCompletion = await client.chat.completions.retrieve('completion_id');\n\nconsole.log(chatCompletion.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n chatCompletion, err := client.Chat.Completions.Get(context.TODO(), \"completion_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", chatCompletion.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.chat.completions.ChatCompletion;\nimport com.openai.models.chat.completions.ChatCompletionRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ChatCompletion chatCompletion = client.chat().completions().retrieve(\"completion_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nchat_completion = openai.chat.completions.retrieve(\"completion_id\")\n\nputs(chat_completion)" - } - } - }, - "description": "Get a stored chat completion. Only Chat Completions that have been created\nwith the `store` parameter set to `true` will be returned.\n" - }, - "post": { - "operationId": "updateChatCompletion", - "tags": [ - "Chat" - ], - "summary": "Update chat completion", - "parameters": [ - { - "in": "path", - "name": "completion_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the chat completion to update." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "type": "object", - "required": [ - "metadata" - ], - "properties": { - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - } - } - } - }, - "responses": { - "200": { - "description": "A chat completion", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateChatCompletionResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Update chat completion", - "group": "chat", - "returns": "The [ChatCompletion](https://platform.openai.com/docs/api-reference/chat/object) object matching the specified ID.", - "examples": { - "response": "{\n \"object\": \"chat.completion\",\n \"id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2\",\n \"model\": \"gpt-4o-2024-08-06\",\n \"created\": 1738960610,\n \"request_id\": \"req_ded8ab984ec4bf840f37566c1011c417\",\n \"tool_choice\": null,\n \"usage\": {\n \"total_tokens\": 31,\n \"completion_tokens\": 18,\n \"prompt_tokens\": 13\n },\n \"seed\": 4944116822809979520,\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"presence_penalty\": 0.0,\n \"frequency_penalty\": 0.0,\n \"system_fingerprint\": \"fp_50cad350e4\",\n \"input_user\": null,\n \"service_tier\": \"default\",\n \"tools\": null,\n \"metadata\": {\n \"foo\": \"bar\"\n },\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"content\": \"Mind of circuits hum, \\nLearning patterns in silenceโ€” \\nFuture's quiet spark.\",\n \"role\": \"assistant\",\n \"tool_calls\": null,\n \"function_call\": null\n },\n \"finish_reason\": \"stop\",\n \"logprobs\": null\n }\n ],\n \"response_format\": null\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/chat/completions/chat_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"metadata\": {\"foo\": \"bar\"}}'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nchat_completion = client.chat.completions.update(\n completion_id=\"completion_id\",\n metadata={\n \"foo\": \"string\"\n },\n)\nprint(chat_completion.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst chatCompletion = await client.chat.completions.update('completion_id', { metadata: { foo: 'string' } });\n\nconsole.log(chatCompletion.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/shared\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n chatCompletion, err := client.Chat.Completions.Update(\n context.TODO(),\n \"completion_id\",\n openai.ChatCompletionUpdateParams{\n Metadata: shared.Metadata{\n \"foo\": \"string\",\n },\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", chatCompletion.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.core.JsonValue;\nimport com.openai.models.chat.completions.ChatCompletion;\nimport com.openai.models.chat.completions.ChatCompletionUpdateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ChatCompletionUpdateParams params = ChatCompletionUpdateParams.builder()\n .completionId(\"completion_id\")\n .metadata(ChatCompletionUpdateParams.Metadata.builder()\n .putAdditionalProperty(\"foo\", JsonValue.from(\"string\"))\n .build())\n .build();\n ChatCompletion chatCompletion = client.chat().completions().update(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nchat_completion = openai.chat.completions.update(\"completion_id\", metadata: {foo: \"string\"})\n\nputs(chat_completion)" - } - } - }, - "description": "Modify a stored chat completion. Only Chat Completions that have been\ncreated with the `store` parameter set to `true` can be modified. Currently,\nthe only supported modification is to update the `metadata` field.\n" - }, - "delete": { - "operationId": "deleteChatCompletion", - "tags": [ - "Chat" - ], - "summary": "Delete chat completion", - "parameters": [ - { - "in": "path", - "name": "completion_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the chat completion to delete." - } - ], - "responses": { - "200": { - "description": "The chat completion was deleted successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ChatCompletionDeleted" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete chat completion", - "group": "chat", - "returns": "A deletion confirmation object.", - "examples": { - "response": "{\n \"object\": \"chat.completion.deleted\",\n \"id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/chat/completions/chat_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nchat_completion_deleted = client.chat.completions.delete(\n \"completion_id\",\n)\nprint(chat_completion_deleted.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst chatCompletionDeleted = await client.chat.completions.delete('completion_id');\n\nconsole.log(chatCompletionDeleted.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n chatCompletionDeleted, err := client.Chat.Completions.Delete(context.TODO(), \"completion_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", chatCompletionDeleted.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.chat.completions.ChatCompletionDeleteParams;\nimport com.openai.models.chat.completions.ChatCompletionDeleted;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ChatCompletionDeleted chatCompletionDeleted = client.chat().completions().delete(\"completion_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nchat_completion_deleted = openai.chat.completions.delete(\"completion_id\")\n\nputs(chat_completion_deleted)" - } - } - }, - "description": "Delete a stored chat completion. Only Chat Completions that have been\ncreated with the `store` parameter set to `true` can be deleted.\n" - } - }, - "/chat/completions/{completion_id}/messages": { - "get": { - "operationId": "getChatCompletionMessages", - "tags": [ - "Chat" - ], - "summary": "Get chat messages", - "parameters": [ - { - "in": "path", - "name": "completion_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the chat completion to retrieve messages from." - }, - { - "name": "after", - "in": "query", - "description": "Identifier for the last message from the previous pagination request.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "Number of messages to retrieve.", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order for messages by timestamp. Use `asc` for ascending order or `desc` for descending order. Defaults to `asc`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "asc", - "desc" - ], - "default": "asc" - } - } - ], - "responses": { - "200": { - "description": "A list of messages", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ChatCompletionMessageList" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Get chat messages", - "group": "chat", - "returns": "A list of [messages](https://platform.openai.com/docs/api-reference/chat/message-list) for the specified chat completion.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0\",\n \"role\": \"user\",\n \"content\": \"write a haiku about ai\",\n \"name\": null,\n \"content_parts\": null\n }\n ],\n \"first_id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0\",\n \"last_id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/chat/completions/chat_abc123/messages \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.chat.completions.messages.list(\n completion_id=\"completion_id\",\n)\npage = page.data[0]\nprint(page)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const chatCompletionStoreMessage of client.chat.completions.messages.list('completion_id')) { console.log(chatCompletionStoreMessage);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Chat.Completions.Messages.List(\n context.TODO(),\n \"completion_id\",\n openai.ChatCompletionMessageListParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.chat.completions.messages.MessageListPage;\nimport com.openai.models.chat.completions.messages.MessageListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n MessageListPage page = client.chat().completions().messages().list(\"completion_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.chat.completions.messages.list(\"completion_id\")\n\nputs(page)" - } - } - }, - "description": "Get the messages in a stored chat completion. Only Chat Completions that\nhave been created with the `store` parameter set to `true` will be\nreturned.\n" - } - }, - "/completions": { - "post": { - "operationId": "createCompletion", - "tags": [ - "Completions" - ], - "summary": "Create completion", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateCompletionRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateCompletionResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create completion", - "group": "completions", - "returns": "Returns a [completion](https://platform.openai.com/docs/api-reference/completions/object) object, or a sequence of completion objects if the request is streamed.\n", - "legacy": true, - "examples": [ - { - "title": "No streaming", - "request": { - "curl": "curl https://api.openai.com/v1/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"VAR_completion_model_id\",\n \"prompt\": \"Say this is a test\",\n \"max_tokens\": 7,\n \"temperature\": 0\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ncompletion = client.completions.create(\n model=\"string\",\n prompt=\"This is a test.\",\n)\nprint(completion)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst completion = await client.completions.create({ model: 'string', prompt: 'This is a test.' });\n\nconsole.log(completion);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n completion, err := client.Completions.New(context.TODO(), openai.CompletionNewParams{\n Model: openai.CompletionNewParamsModelGPT3_5TurboInstruct,\n Prompt: openai.CompletionNewParamsPromptUnion{\n OfString: openai.String(\"This is a test.\"),\n },\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", completion)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.completions.Completion;\nimport com.openai.models.completions.CompletionCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n CompletionCreateParams params = CompletionCreateParams.builder()\n .model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)\n .prompt(\"This is a test.\")\n .build();\n Completion completion = client.completions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ncompletion = openai.completions.create(model: :\"gpt-3.5-turbo-instruct\", prompt: \"This is a test.\")\n\nputs(completion)" - }, - "response": "{\n \"id\": \"cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7\",\n \"object\": \"text_completion\",\n \"created\": 1589478378,\n \"model\": \"VAR_completion_model_id\",\n \"system_fingerprint\": \"fp_44709d6fcb\",\n \"choices\": [\n {\n \"text\": \"\\n\\nThis is indeed a test\",\n \"index\": 0,\n \"logprobs\": null,\n \"finish_reason\": \"length\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 5,\n \"completion_tokens\": 7,\n \"total_tokens\": 12\n }\n}\n" - }, - { - "title": "Streaming", - "request": { - "curl": "curl https://api.openai.com/v1/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"VAR_completion_model_id\",\n \"prompt\": \"Say this is a test\",\n \"max_tokens\": 7,\n \"temperature\": 0,\n \"stream\": true\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ncompletion = client.completions.create(\n model=\"string\",\n prompt=\"This is a test.\",\n)\nprint(completion)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst completion = await client.completions.create({ model: 'string', prompt: 'This is a test.' });\n\nconsole.log(completion);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n completion, err := client.Completions.New(context.TODO(), openai.CompletionNewParams{\n Model: openai.CompletionNewParamsModelGPT3_5TurboInstruct,\n Prompt: openai.CompletionNewParamsPromptUnion{\n OfString: openai.String(\"This is a test.\"),\n },\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", completion)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.completions.Completion;\nimport com.openai.models.completions.CompletionCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n CompletionCreateParams params = CompletionCreateParams.builder()\n .model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)\n .prompt(\"This is a test.\")\n .build();\n Completion completion = client.completions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ncompletion = openai.completions.create(model: :\"gpt-3.5-turbo-instruct\", prompt: \"This is a test.\")\n\nputs(completion)" - }, - "response": "{\n \"id\": \"cmpl-7iA7iJjj8V2zOkCGvWF2hAkDWBQZe\",\n \"object\": \"text_completion\",\n \"created\": 1690759702,\n \"choices\": [\n {\n \"text\": \"This\",\n \"index\": 0,\n \"logprobs\": null,\n \"finish_reason\": null\n }\n ],\n \"model\": \"gpt-3.5-turbo-instruct\"\n \"system_fingerprint\": \"fp_44709d6fcb\",\n}\n" - } - ] - }, - "description": "Creates a completion for the provided prompt and parameters." - } - }, - "/containers": { - "get": { - "summary": "List containers", - "description": "List Containers", - "operationId": "ListContainers", - "parameters": [ - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Success", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ContainerListResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List containers", - "group": "containers", - "returns": "a list of [container](https://platform.openai.com/docs/api-reference/containers/object) objects.", - "path": "get", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863\",\n \"object\": \"container\",\n \"created_at\": 1747844794,\n \"status\": \"running\",\n \"expires_after\": {\n \"anchor\": \"last_active_at\",\n \"minutes\": 20\n },\n \"last_active_at\": 1747844794,\n \"name\": \"My Container\"\n }\n ],\n \"first_id\": \"container_123\",\n \"last_id\": \"container_123\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/containers \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const containerListResponse of client.containers.list()) {\n console.log(containerListResponse.id);\n}", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.containers.list()\npage = page.data[0]\nprint(page.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Containers.List(context.TODO(), openai.ContainerListParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.containers.ContainerListPage;\nimport com.openai.models.containers.ContainerListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ContainerListPage page = client.containers().list();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.containers.list\n\nputs(page)" - } - } - } - }, - "post": { - "summary": "Create container", - "description": "Create Container", - "operationId": "CreateContainer", - "parameters": [], - "requestBody": { - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateContainerBody" - } - } - } - }, - "responses": { - "200": { - "description": "Success", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ContainerResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create container", - "group": "containers", - "returns": "The created [container](https://platform.openai.com/docs/api-reference/containers/object) object.", - "path": "post", - "examples": { - "response": "{\n \"id\": \"cntr_682e30645a488191b6363a0cbefc0f0a025ec61b66250591\",\n \"object\": \"container\",\n \"created_at\": 1747857508,\n \"status\": \"running\",\n \"expires_after\": {\n \"anchor\": \"last_active_at\",\n \"minutes\": 20\n },\n \"last_active_at\": 1747857508,\n \"name\": \"My Container\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/containers \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"name\": \"My Container\"\n }'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst container = await client.containers.create({ name: 'name' });\n\nconsole.log(container.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ncontainer = client.containers.create(\n name=\"name\",\n)\nprint(container.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n container, err := client.Containers.New(context.TODO(), openai.ContainerNewParams{\n Name: \"name\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", container.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.containers.ContainerCreateParams;\nimport com.openai.models.containers.ContainerCreateResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ContainerCreateParams params = ContainerCreateParams.builder()\n .name(\"name\")\n .build();\n ContainerCreateResponse container = client.containers().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ncontainer = openai.containers.create(name: \"name\")\n\nputs(container)" - } - } - } - } - }, - "/containers/{container_id}": { - "get": { - "summary": "Retrieve container", - "description": "Retrieve Container", - "operationId": "RetrieveContainer", - "parameters": [ - { - "name": "container_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Success", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ContainerResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve container", - "group": "containers", - "returns": "The [container](https://platform.openai.com/docs/api-reference/containers/object) object.", - "path": "get", - "examples": { - "response": "{\n \"id\": \"cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863\",\n \"object\": \"container\",\n \"created_at\": 1747844794,\n \"status\": \"running\",\n \"expires_after\": {\n \"anchor\": \"last_active_at\",\n \"minutes\": 20\n },\n \"last_active_at\": 1747844794,\n \"name\": \"My Container\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/containers/cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863 \\ -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst container = await client.containers.retrieve('container_id');\n\nconsole.log(container.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ncontainer = client.containers.retrieve(\n \"container_id\",\n)\nprint(container.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n container, err := client.Containers.Get(context.TODO(), \"container_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", container.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.containers.ContainerRetrieveParams;\nimport com.openai.models.containers.ContainerRetrieveResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ContainerRetrieveResponse container = client.containers().retrieve(\"container_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ncontainer = openai.containers.retrieve(\"container_id\")\n\nputs(container)" - } - } - } - }, - "delete": { - "operationId": "DeleteContainer", - "summary": "Delete a container", - "description": "Delete Container", - "parameters": [ - { - "name": "container_id", - "in": "path", - "description": "The ID of the container to delete.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "OK" - } - }, - "x-oaiMeta": { - "name": "Delete a container", - "group": "containers", - "returns": "Deletion Status", - "path": "delete", - "examples": { - "response": "{\n \"id\": \"cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863\",\n \"object\": \"container.deleted\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/containers/cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863 \\ -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nawait client.containers.delete('container_id');", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nclient.containers.delete(\n \"container_id\",\n)", - "go": "package main\n\nimport (\n \"context\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n err := client.Containers.Delete(context.TODO(), \"container_id\")\n if err != nil {\n panic(err.Error())\n }\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.containers.ContainerDeleteParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n client.containers().delete(\"container_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresult = openai.containers.delete(\"container_id\")\n\nputs(result)" - } - } - } - } - }, - "/containers/{container_id}/files": { - "post": { - "summary": "Create container file", - "description": "Create a Container File\n\nYou can send either a multipart/form-data request with the raw file content, or a JSON request with a file ID.\n", - "operationId": "CreateContainerFile", - "parameters": [ - { - "name": "container_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - } - } - ], - "requestBody": { - "required": true, - "content": { - "multipart/form-data": { - "schema": { - "$ref": "#/components/schemas/CreateContainerFileBody" - } - } - } - }, - "responses": { - "200": { - "description": "Success", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ContainerFileResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create container file", - "group": "containers", - "returns": "The created [container file](https://platform.openai.com/docs/api-reference/container-files/object) object.", - "path": "post", - "examples": { - "response": "{\n \"id\": \"cfile_682e0e8a43c88191a7978f477a09bdf5\",\n \"object\": \"container.file\",\n \"created_at\": 1747848842,\n \"bytes\": 880,\n \"container_id\": \"cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04\",\n \"path\": \"/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json\",\n \"source\": \"user\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/containers/cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04/files \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -F file=\"@example.txt\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst file = await client.containers.files.create('container_id');\n\nconsole.log(file.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfile = client.containers.files.create(\n container_id=\"container_id\",\n)\nprint(file.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n file, err := client.Containers.Files.New(\n context.TODO(),\n \"container_id\",\n openai.ContainerFileNewParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", file.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.containers.files.FileCreateParams;\nimport com.openai.models.containers.files.FileCreateResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileCreateResponse file = client.containers().files().create(\"container_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfile = openai.containers.files.create(\"container_id\")\n\nputs(file)" - } - } - } - }, - "get": { - "summary": "List container files", - "description": "List Container files", - "operationId": "ListContainerFiles", - "parameters": [ - { - "name": "container_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Success", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ContainerFileListResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List container files", - "group": "containers", - "returns": "a list of [container file](https://platform.openai.com/docs/api-reference/container-files/object) objects.", - "path": "get", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"cfile_682e0e8a43c88191a7978f477a09bdf5\",\n \"object\": \"container.file\",\n \"created_at\": 1747848842,\n \"bytes\": 880,\n \"container_id\": \"cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04\",\n \"path\": \"/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json\",\n \"source\": \"user\"\n }\n ],\n \"first_id\": \"cfile_682e0e8a43c88191a7978f477a09bdf5\",\n \"has_more\": false,\n \"last_id\": \"cfile_682e0e8a43c88191a7978f477a09bdf5\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/containers/cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04/files \\ -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const fileListResponse of client.containers.files.list('container_id')) {\n console.log(fileListResponse.id);\n}", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.containers.files.list(\n container_id=\"container_id\",\n)\npage = page.data[0]\nprint(page.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Containers.Files.List(\n context.TODO(),\n \"container_id\",\n openai.ContainerFileListParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.containers.files.FileListPage;\nimport com.openai.models.containers.files.FileListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileListPage page = client.containers().files().list(\"container_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.containers.files.list(\"container_id\")\n\nputs(page)" - } - } - } - } - }, - "/containers/{container_id}/files/{file_id}": { - "get": { - "summary": "Retrieve container file", - "description": "Retrieve Container File", - "operationId": "RetrieveContainerFile", - "parameters": [ - { - "name": "container_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "file_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Success", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ContainerFileResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve container file", - "group": "containers", - "returns": "The [container file](https://platform.openai.com/docs/api-reference/container-files/object) object.", - "path": "get", - "examples": { - "response": "{\n \"id\": \"cfile_682e0e8a43c88191a7978f477a09bdf5\",\n \"object\": \"container.file\",\n \"created_at\": 1747848842,\n \"bytes\": 880,\n \"container_id\": \"cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04\",\n \"path\": \"/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json\",\n \"source\": \"user\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/containers/container_123/files/file_456 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst file = await client.containers.files.retrieve('file_id', { container_id: 'container_id' });\n\nconsole.log(file.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfile = client.containers.files.retrieve(\n file_id=\"file_id\",\n container_id=\"container_id\",\n)\nprint(file.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n file, err := client.Containers.Files.Get(\n context.TODO(),\n \"container_id\",\n \"file_id\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", file.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.containers.files.FileRetrieveParams;\nimport com.openai.models.containers.files.FileRetrieveResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileRetrieveParams params = FileRetrieveParams.builder()\n .containerId(\"container_id\")\n .fileId(\"file_id\")\n .build();\n FileRetrieveResponse file = client.containers().files().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfile = openai.containers.files.retrieve(\"file_id\", container_id: \"container_id\")\n\nputs(file)" - } - } - } - }, - "delete": { - "operationId": "DeleteContainerFile", - "summary": "Delete a container file", - "description": "Delete Container File", - "parameters": [ - { - "name": "container_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "file_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "OK" - } - }, - "x-oaiMeta": { - "name": "Delete a container file", - "group": "containers", - "returns": "Deletion Status", - "path": "delete", - "examples": { - "response": "{\n \"id\": \"cfile_682e0e8a43c88191a7978f477a09bdf5\",\n \"object\": \"container.file.deleted\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/containers/cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863/files/cfile_682e0e8a43c88191a7978f477a09bdf5 \\ -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nawait client.containers.files.delete('file_id', { container_id: 'container_id' });", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nclient.containers.files.delete(\n file_id=\"file_id\",\n container_id=\"container_id\",\n)", - "go": "package main\n\nimport (\n \"context\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n err := client.Containers.Files.Delete(\n context.TODO(),\n \"container_id\",\n \"file_id\",\n )\n if err != nil {\n panic(err.Error())\n }\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.containers.files.FileDeleteParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileDeleteParams params = FileDeleteParams.builder()\n .containerId(\"container_id\")\n .fileId(\"file_id\")\n .build();\n client.containers().files().delete(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresult = openai.containers.files.delete(\"file_id\", container_id: \"container_id\")\n\nputs(result)" - } - } - } - } - }, - "/containers/{container_id}/files/{file_id}/content": { - "get": { - "summary": "Retrieve container file content", - "description": "Retrieve Container File Content", - "operationId": "RetrieveContainerFileContent", - "parameters": [ - { - "name": "container_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "file_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Success" - } - }, - "x-oaiMeta": { - "name": "Retrieve container file content", - "group": "containers", - "returns": "The contents of the container file.", - "path": "get", - "examples": { - "response": "\n", - "request": { - "curl": "curl https://api.openai.com/v1/containers/container_123/files/cfile_456/content \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst content = await client.containers.files.content.retrieve('file_id', { container_id: 'container_id' });\n\nconsole.log(content);\n\nconst data = await content.blob();\nconsole.log(data);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ncontent = client.containers.files.content.retrieve(\n file_id=\"file_id\",\n container_id=\"container_id\",\n)\nprint(content)\ndata = content.read()\nprint(data)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n content, err := client.Containers.Files.Content.Get(\n context.TODO(),\n \"container_id\",\n \"file_id\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", content)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.core.http.HttpResponse;\nimport com.openai.models.containers.files.content.ContentRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ContentRetrieveParams params = ContentRetrieveParams.builder()\n .containerId(\"container_id\")\n .fileId(\"file_id\")\n .build();\n HttpResponse content = client.containers().files().content().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ncontent = openai.containers.files.content.retrieve(\"file_id\", container_id: \"container_id\")\n\nputs(content)" - } - } - } - } - }, - "/conversations": { - "post": { - "operationId": "createConversation", - "tags": [ - "Conversations" - ], - "summary": "Create a conversation", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateConversationRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ConversationResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create a conversation", - "group": "conversations", - "returns": "Returns a [Conversation](https://platform.openai.com/docs/api-reference/conversations/object) object.\n", - "path": "create", - "examples": [ - { - "title": "Create a conversation.", - "request": { - "curl": "curl https://api.openai.com/v1/conversations \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"metadata\": {\"topic\": \"demo\"},\n \"items\": [\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": \"Hello!\"\n }\n ]\n }'\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst conversation = await client.conversations.create({\n metadata: { topic: \"demo\" },\n items: [\n { type: \"message\", role: \"user\", content: \"Hello!\" }\n ],\n});\nconsole.log(conversation);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nconversation = client.conversations.create()\nprint(conversation.id)", - "csharp": "using System;\nusing System.Collections.Generic;\nusing OpenAI.Conversations;\n\nOpenAIConversationClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nConversation conversation = client.CreateConversation(\n new CreateConversationOptions\n {\n Metadata = new Dictionary\n {\n { \"topic\", \"demo\" }\n },\n Items =\n {\n new ConversationMessageInput\n {\n Role = \"user\",\n Content = \"Hello!\"\n }\n }\n }\n);\nConsole.WriteLine(conversation.Id);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst conversation = await client.conversations.create();\n\nconsole.log(conversation.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/conversations\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n conversation, err := client.Conversations.New(context.TODO(), conversations.ConversationNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", conversation.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.conversations.Conversation;\nimport com.openai.models.conversations.ConversationCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Conversation conversation = client.conversations().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nconversation = openai.conversations.create\n\nputs(conversation)" - }, - "response": "{\n \"id\": \"conv_123\",\n \"object\": \"conversation\",\n \"created_at\": 1741900000,\n \"metadata\": {\"topic\": \"demo\"}\n}\n" - } - ] - }, - "description": "Create a conversation." - } - }, - "/conversations/{conversation_id}": { - "get": { - "operationId": "getConversation", - "tags": [ - "Conversations" - ], - "summary": "Retrieve a conversation", - "parameters": [ - { - "in": "path", - "name": "conversation_id", - "required": true, - "schema": { - "type": "string", - "example": "conv_123" - }, - "description": "The ID of the conversation to retrieve." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ConversationResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve a conversation", - "group": "conversations", - "returns": "Returns a [Conversation](https://platform.openai.com/docs/api-reference/conversations/object) object.\n", - "path": "retrieve", - "examples": [ - { - "title": "Retrieve a conversation", - "request": { - "curl": "curl https://api.openai.com/v1/conversations/conv_123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst conversation = await client.conversations.retrieve(\"conv_123\");\nconsole.log(conversation);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nconversation = client.conversations.retrieve(\n \"conv_123\",\n)\nprint(conversation.id)", - "csharp": "using System;\nusing OpenAI.Conversations;\n\nOpenAIConversationClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nConversation conversation = client.GetConversation(\"conv_123\");\nConsole.WriteLine(conversation.Id);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst conversation = await client.conversations.retrieve('conv_123');\n\nconsole.log(conversation.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n conversation, err := client.Conversations.Get(context.TODO(), \"conv_123\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", conversation.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.conversations.Conversation;\nimport com.openai.models.conversations.ConversationRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Conversation conversation = client.conversations().retrieve(\"conv_123\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nconversation = openai.conversations.retrieve(\"conv_123\")\n\nputs(conversation)" - }, - "response": "{\n \"id\": \"conv_123\",\n \"object\": \"conversation\",\n \"created_at\": 1741900000,\n \"metadata\": {\"topic\": \"demo\"}\n}\n" - } - ] - }, - "description": "Get a conversation with the given ID." - }, - "post": { - "operationId": "updateConversation", - "tags": [ - "Conversations" - ], - "summary": "Update a conversation", - "parameters": [ - { - "in": "path", - "name": "conversation_id", - "required": true, - "schema": { - "type": "string", - "example": "conv_123" - }, - "description": "The ID of the conversation to update." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UpdateConversationBody" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ConversationResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Update a conversation", - "group": "conversations", - "returns": "Returns the updated [Conversation](https://platform.openai.com/docs/api-reference/conversations/object) object.\n", - "path": "update", - "examples": [ - { - "title": "Update conversation metadata", - "request": { - "curl": "curl https://api.openai.com/v1/conversations/conv_123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"metadata\": {\"topic\": \"project-x\"}\n }'\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst updated = await client.conversations.update(\n \"conv_123\",\n { metadata: { topic: \"project-x\" } }\n);\nconsole.log(updated);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nconversation = client.conversations.update(\n conversation_id=\"conv_123\",\n metadata={\n \"foo\": \"string\"\n },\n)\nprint(conversation.id)", - "csharp": "using System;\nusing System.Collections.Generic;\nusing OpenAI.Conversations;\n\nOpenAIConversationClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nConversation updated = client.UpdateConversation(\n conversationId: \"conv_123\",\n new UpdateConversationOptions\n {\n Metadata = new Dictionary\n {\n { \"topic\", \"project-x\" }\n }\n }\n);\nConsole.WriteLine(updated.Id);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst conversation = await client.conversations.update('conv_123', { metadata: { foo: 'string' } });\n\nconsole.log(conversation.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/conversations\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n conversation, err := client.Conversations.Update(\n context.TODO(),\n \"conv_123\",\n conversations.ConversationUpdateParams{\n Metadata: map[string]string{\n \"foo\": \"string\",\n },\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", conversation.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.core.JsonValue;\nimport com.openai.models.conversations.Conversation;\nimport com.openai.models.conversations.ConversationUpdateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ConversationUpdateParams params = ConversationUpdateParams.builder()\n .conversationId(\"conv_123\")\n .metadata(ConversationUpdateParams.Metadata.builder()\n .putAdditionalProperty(\"foo\", JsonValue.from(\"string\"))\n .build())\n .build();\n Conversation conversation = client.conversations().update(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nconversation = openai.conversations.update(\"conv_123\", metadata: {foo: \"string\"})\n\nputs(conversation)" - }, - "response": "{\n \"id\": \"conv_123\",\n \"object\": \"conversation\",\n \"created_at\": 1741900000,\n \"metadata\": {\"topic\": \"project-x\"}\n}\n" - } - ] - }, - "description": "Update a conversation's metadata with the given ID." - }, - "delete": { - "operationId": "deleteConversation", - "tags": [ - "Conversations" - ], - "summary": "Delete a conversation", - "parameters": [ - { - "in": "path", - "name": "conversation_id", - "required": true, - "schema": { - "type": "string", - "example": "conv_123" - }, - "description": "The ID of the conversation to delete." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeletedConversationResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete a conversation", - "group": "conversations", - "returns": "A success message.\n", - "path": "delete", - "examples": [ - { - "title": "Delete a conversation", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/conversations/conv_123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst deleted = await client.conversations.delete(\"conv_123\");\nconsole.log(deleted);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nconversation_deleted_resource = client.conversations.delete(\n \"conv_123\",\n)\nprint(conversation_deleted_resource.id)", - "csharp": "using System;\nusing OpenAI.Conversations;\n\nOpenAIConversationClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nDeletedConversation deleted = client.DeleteConversation(\"conv_123\");\nConsole.WriteLine(deleted.Id);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst conversationDeletedResource = await client.conversations.delete('conv_123');\n\nconsole.log(conversationDeletedResource.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n conversationDeletedResource, err := client.Conversations.Delete(context.TODO(), \"conv_123\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", conversationDeletedResource.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.conversations.ConversationDeleteParams;\nimport com.openai.models.conversations.ConversationDeletedResource;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ConversationDeletedResource conversationDeletedResource = client.conversations().delete(\"conv_123\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nconversation_deleted_resource = openai.conversations.delete(\"conv_123\")\n\nputs(conversation_deleted_resource)" - }, - "response": "{\n \"id\": \"conv_123\",\n \"object\": \"conversation.deleted\",\n \"deleted\": true\n}\n" - } - ] - }, - "description": "Delete a conversation with the given ID." - } - }, - "/conversations/{conversation_id}/items": { - "post": { - "operationId": "createConversationItems", - "tags": [ - "Conversations" - ], - "summary": "Create items", - "parameters": [ - { - "in": "path", - "name": "conversation_id", - "required": true, - "schema": { - "type": "string", - "example": "conv_123" - }, - "description": "The ID of the conversation to add the item to." - }, - { - "name": "include", - "in": "query", - "required": false, - "schema": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Includable" - } - }, - "description": "Additional fields to include in the response. See the `include`\nparameter for [listing Conversation items above](https://platform.openai.com/docs/api-reference/conversations/list-items#conversations_list_items-include) for more information.\n" - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "properties": { - "items": { - "type": "array", - "description": "The items to add to the conversation. You may add up to 20 items at a time.\n", - "items": { - "$ref": "#/components/schemas/InputItem" - }, - "maxItems": 20 - } - }, - "required": [ - "items" - ] - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ConversationItemList" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create items", - "group": "conversations", - "returns": "Returns the list of added [items](https://platform.openai.com/docs/api-reference/conversations/list-items-object).\n", - "path": "create-item", - "examples": [ - { - "title": "Add a user message to a conversation", - "request": { - "curl": "curl https://api.openai.com/v1/conversations/conv_123/items \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"items\": [\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"input_text\", \"text\": \"Hello!\"}\n ]\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"input_text\", \"text\": \"How are you?\"}\n ]\n }\n ]\n }'\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst items = await client.conversations.items.create(\n \"conv_123\",\n {\n items: [\n {\n type: \"message\",\n role: \"user\",\n content: [{ type: \"input_text\", text: \"Hello!\" }],\n },\n {\n type: \"message\",\n role: \"user\",\n content: [{ type: \"input_text\", text: \"How are you?\" }],\n },\n ],\n }\n);\nconsole.log(items.data);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nconversation_item_list = client.conversations.items.create(\n conversation_id=\"conv_123\",\n items=[{\n \"content\": \"string\",\n \"role\": \"user\",\n }],\n)\nprint(conversation_item_list.first_id)", - "csharp": "using System;\nusing System.Collections.Generic;\nusing OpenAI.Conversations;\n\nOpenAIConversationClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nConversationItemList created = client.ConversationItems.Create(\n conversationId: \"conv_123\",\n new CreateConversationItemsOptions\n {\n Items = new List\n {\n new ConversationMessage\n {\n Role = \"user\",\n Content =\n {\n new ConversationInputText { Text = \"Hello!\" }\n }\n },\n new ConversationMessage\n {\n Role = \"user\",\n Content =\n {\n new ConversationInputText { Text = \"How are you?\" }\n }\n }\n }\n }\n);\nConsole.WriteLine(created.Data.Count);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst conversationItemList = await client.conversations.items.create('conv_123', {\n items: [{ content: 'string', role: 'user' }],\n});\n\nconsole.log(conversationItemList.first_id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/conversations\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n conversationItemList, err := client.Conversations.Items.New(\n context.TODO(),\n \"conv_123\",\n conversations.ItemNewParams{\n Items: []responses.ResponseInputItemUnionParam{responses.ResponseInputItemUnionParam{\n OfMessage: &responses.EasyInputMessageParam{\n Content: responses.EasyInputMessageContentUnionParam{\n OfString: openai.String(\"string\"),\n },\n Role: responses.EasyInputMessageRoleUser,\n },\n }},\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", conversationItemList.FirstID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.conversations.items.ConversationItemList;\nimport com.openai.models.conversations.items.ItemCreateParams;\nimport com.openai.models.responses.EasyInputMessage;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ItemCreateParams params = ItemCreateParams.builder()\n .conversationId(\"conv_123\")\n .addItem(EasyInputMessage.builder()\n .content(\"string\")\n .role(EasyInputMessage.Role.USER)\n .build())\n .build();\n ConversationItemList conversationItemList = client.conversations().items().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nconversation_item_list = openai.conversations.items.create(\"conv_123\", items: [{content: \"string\", role: :user}])\n\nputs(conversation_item_list)" - }, - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"type\": \"message\",\n \"id\": \"msg_abc\",\n \"status\": \"completed\",\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"input_text\", \"text\": \"Hello!\"}\n ]\n },\n {\n \"type\": \"message\",\n \"id\": \"msg_def\",\n \"status\": \"completed\",\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"input_text\", \"text\": \"How are you?\"}\n ]\n }\n ],\n \"first_id\": \"msg_abc\",\n \"last_id\": \"msg_def\",\n \"has_more\": false\n}\n" - } - ] - }, - "description": "Create items in a conversation with the given ID." - }, - "get": { - "operationId": "listConversationItems", - "tags": [ - "Conversations" - ], - "summary": "List items", - "parameters": [ - { - "in": "path", - "name": "conversation_id", - "required": true, - "schema": { - "type": "string", - "example": "conv_123" - }, - "description": "The ID of the conversation to list items for." - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between\n1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "in": "query", - "name": "order", - "schema": { - "type": "string", - "enum": [ - "asc", - "desc" - ] - }, - "description": "The order to return the input items in. Default is `desc`.\n- `asc`: Return the input items in ascending order.\n- `desc`: Return the input items in descending order.\n" - }, - { - "in": "query", - "name": "after", - "schema": { - "type": "string" - }, - "description": "An item ID to list items after, used in pagination.\n" - }, - { - "name": "include", - "in": "query", - "required": false, - "schema": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Includable" - } - }, - "description": "Specify additional output data to include in the model response. Currently\nsupported values are:\n- `web_search_call.action.sources`: Include the sources of the web search tool call.\n- `code_interpreter_call.outputs`: Includes the outputs of python code execution\n in code interpreter tool call items.\n- `computer_call_output.output.image_url`: Include image urls from the computer call output.\n- `file_search_call.results`: Include the search results of\n the file search tool call.\n- `message.input_image.image_url`: Include image urls from the input message.\n- `message.output_text.logprobs`: Include logprobs with assistant messages.\n- `reasoning.encrypted_content`: Includes an encrypted version of reasoning\n tokens in reasoning item outputs. This enables reasoning items to be used in\n multi-turn conversations when using the Responses API statelessly (like\n when the `store` parameter is set to `false`, or when an organization is\n enrolled in the zero data retention program).\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ConversationItemList" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List items", - "group": "conversations", - "returns": "Returns a [list object](https://platform.openai.com/docs/api-reference/conversations/list-items-object) containing Conversation items.\n", - "path": "list-items", - "examples": [ - { - "title": "List items in a conversation", - "request": { - "curl": "curl \"https://api.openai.com/v1/conversations/conv_123/items?limit=10\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst items = await client.conversations.items.list(\"conv_123\", { limit: 10 });\nconsole.log(items.data);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.conversations.items.list(\n conversation_id=\"conv_123\",\n)\npage = page.data[0]\nprint(page)", - "csharp": "using System;\nusing OpenAI.Conversations;\n\nOpenAIConversationClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nConversationItemList items = client.ConversationItems.List(\n conversationId: \"conv_123\",\n new ListConversationItemsOptions { Limit = 10 }\n);\nConsole.WriteLine(items.Data.Count);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const conversationItem of client.conversations.items.list('conv_123')) {\n console.log(conversationItem);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/conversations\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Conversations.Items.List(\n context.TODO(),\n \"conv_123\",\n conversations.ItemListParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.conversations.items.ItemListPage;\nimport com.openai.models.conversations.items.ItemListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ItemListPage page = client.conversations().items().list(\"conv_123\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.conversations.items.list(\"conv_123\")\n\nputs(page)" - }, - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"type\": \"message\",\n \"id\": \"msg_abc\",\n \"status\": \"completed\",\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"input_text\", \"text\": \"Hello!\"}\n ]\n }\n ],\n \"first_id\": \"msg_abc\",\n \"last_id\": \"msg_abc\",\n \"has_more\": false\n}\n" - } - ] - }, - "description": "List all items for a conversation with the given ID." - } - }, - "/conversations/{conversation_id}/items/{item_id}": { - "get": { - "operationId": "getConversationItem", - "tags": [ - "Conversations" - ], - "summary": "Retrieve an item", - "parameters": [ - { - "in": "path", - "name": "conversation_id", - "required": true, - "schema": { - "type": "string", - "example": "conv_123" - }, - "description": "The ID of the conversation that contains the item." - }, - { - "in": "path", - "name": "item_id", - "required": true, - "schema": { - "type": "string", - "example": "msg_abc" - }, - "description": "The ID of the item to retrieve." - }, - { - "name": "include", - "in": "query", - "required": false, - "schema": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Includable" - } - }, - "description": "Additional fields to include in the response. See the `include`\nparameter for [listing Conversation items above](https://platform.openai.com/docs/api-reference/conversations/list-items#conversations_list_items-include) for more information.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ConversationItem" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve an item", - "group": "conversations", - "returns": "Returns a [Conversation Item](https://platform.openai.com/docs/api-reference/conversations/item-object).\n", - "path": "get-item", - "examples": [ - { - "title": "Retrieve an item", - "request": { - "curl": "curl https://api.openai.com/v1/conversations/conv_123/items/msg_abc \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst item = await client.conversations.items.retrieve(\n \"conv_123\",\n \"msg_abc\"\n);\nconsole.log(item);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nconversation_item = client.conversations.items.retrieve(\n item_id=\"msg_abc\",\n conversation_id=\"conv_123\",\n)\nprint(conversation_item)", - "csharp": "using System;\nusing OpenAI.Conversations;\n\nOpenAIConversationClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nConversationItem item = client.ConversationItems.Get(\n conversationId: \"conv_123\",\n itemId: \"msg_abc\"\n);\nConsole.WriteLine(item.Id);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst conversationItem = await client.conversations.items.retrieve('msg_abc', {\n conversation_id: 'conv_123',\n});\n\nconsole.log(conversationItem);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/conversations\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n conversationItem, err := client.Conversations.Items.Get(\n context.TODO(),\n \"conv_123\",\n \"msg_abc\",\n conversations.ItemGetParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", conversationItem)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.conversations.items.ConversationItem;\nimport com.openai.models.conversations.items.ItemRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ItemRetrieveParams params = ItemRetrieveParams.builder()\n .conversationId(\"conv_123\")\n .itemId(\"msg_abc\")\n .build();\n ConversationItem conversationItem = client.conversations().items().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nconversation_item = openai.conversations.items.retrieve(\"msg_abc\", conversation_id: \"conv_123\")\n\nputs(conversation_item)" - }, - "response": "{\n \"type\": \"message\",\n \"id\": \"msg_abc\",\n \"status\": \"completed\",\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"input_text\", \"text\": \"Hello!\"}\n ]\n}\n" - } - ] - }, - "description": "Get a single item from a conversation with the given IDs." - }, - "delete": { - "operationId": "deleteConversationItem", - "tags": [ - "Conversations" - ], - "summary": "Delete an item", - "parameters": [ - { - "in": "path", - "name": "conversation_id", - "required": true, - "schema": { - "type": "string", - "example": "conv_123" - }, - "description": "The ID of the conversation that contains the item." - }, - { - "in": "path", - "name": "item_id", - "required": true, - "schema": { - "type": "string", - "example": "msg_abc" - }, - "description": "The ID of the item to delete." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ConversationResource" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete an item", - "group": "conversations", - "returns": "Returns the updated [Conversation](https://platform.openai.com/docs/api-reference/conversations/object) object.\n", - "path": "delete-item", - "examples": [ - { - "title": "Delete an item", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/conversations/conv_123/items/msg_abc \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst conversation = await client.conversations.items.delete(\n \"conv_123\",\n \"msg_abc\"\n);\nconsole.log(conversation);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nconversation = client.conversations.items.delete(\n item_id=\"msg_abc\",\n conversation_id=\"conv_123\",\n)\nprint(conversation.id)", - "csharp": "using System;\nusing OpenAI.Conversations;\n\nOpenAIConversationClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nConversation conversation = client.ConversationItems.Delete(\n conversationId: \"conv_123\",\n itemId: \"msg_abc\"\n);\nConsole.WriteLine(conversation.Id);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst conversation = await client.conversations.items.delete('msg_abc', { conversation_id: 'conv_123' });\n\nconsole.log(conversation.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n conversation, err := client.Conversations.Items.Delete(\n context.TODO(),\n \"conv_123\",\n \"msg_abc\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", conversation.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.conversations.Conversation;\nimport com.openai.models.conversations.items.ItemDeleteParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ItemDeleteParams params = ItemDeleteParams.builder()\n .conversationId(\"conv_123\")\n .itemId(\"msg_abc\")\n .build();\n Conversation conversation = client.conversations().items().delete(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nconversation = openai.conversations.items.delete(\"msg_abc\", conversation_id: \"conv_123\")\n\nputs(conversation)" - }, - "response": "{\n \"id\": \"conv_123\",\n \"object\": \"conversation\",\n \"created_at\": 1741900000,\n \"metadata\": {\"topic\": \"demo\"}\n}\n" - } - ] - }, - "description": "Delete an item from a conversation with the given IDs." - } - }, - "/embeddings": { - "post": { - "operationId": "createEmbedding", - "tags": [ - "Embeddings" - ], - "summary": "Create embeddings", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateEmbeddingRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateEmbeddingResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create embeddings", - "group": "embeddings", - "returns": "A list of [embedding](https://platform.openai.com/docs/api-reference/embeddings/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"embedding\",\n \"embedding\": [\n 0.0023064255,\n -0.009327292,\n .... (1536 floats total for ada-002)\n -0.0028842222,\n ],\n \"index\": 0\n }\n ],\n \"model\": \"text-embedding-ada-002\",\n \"usage\": {\n \"prompt_tokens\": 8,\n \"total_tokens\": 8\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/embeddings \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"input\": \"The food was delicious and the waiter...\",\n \"model\": \"text-embedding-ada-002\",\n \"encoding_format\": \"float\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\ncreate_embedding_response = client.embeddings.create(\n input=\"The quick brown fox jumped over the lazy dog\",\n model=\"text-embedding-3-small\",\n)\nprint(create_embedding_response.data)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst createEmbeddingResponse = await client.embeddings.create({\n input: 'The quick brown fox jumped over the lazy dog',\n model: 'text-embedding-3-small',\n});\n\nconsole.log(createEmbeddingResponse.data);", - "csharp": "using System;\n\nusing OpenAI.Embeddings;\n\nEmbeddingClient client = new( model: \"text-embedding-3-small\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nOpenAIEmbedding embedding = client.GenerateEmbedding(input: \"The quick brown fox jumped over the lazy dog\");\nReadOnlyMemory vector = embedding.ToFloats();\n\nfor (int i = 0; i < vector.Length; i++)\n{ Console.WriteLine($\" [{i,4}] = {vector.Span[i]}\");\n}\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n createEmbeddingResponse, err := client.Embeddings.New(context.TODO(), openai.EmbeddingNewParams{\n Input: openai.EmbeddingNewParamsInputUnion{\n OfString: openai.String(\"The quick brown fox jumped over the lazy dog\"),\n },\n Model: openai.EmbeddingModelTextEmbeddingAda002,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", createEmbeddingResponse.Data)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.embeddings.CreateEmbeddingResponse;\nimport com.openai.models.embeddings.EmbeddingCreateParams;\nimport com.openai.models.embeddings.EmbeddingModel;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n EmbeddingCreateParams params = EmbeddingCreateParams.builder()\n .input(\"The quick brown fox jumped over the lazy dog\")\n .model(EmbeddingModel.TEXT_EMBEDDING_ADA_002)\n .build();\n CreateEmbeddingResponse createEmbeddingResponse = client.embeddings().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\ncreate_embedding_response = openai.embeddings.create(\n input: \"The quick brown fox jumped over the lazy dog\",\n model: :\"text-embedding-ada-002\"\n)\n\nputs(create_embedding_response)" - } - } - }, - "description": "Creates an embedding vector representing the input text." - } - }, - "/evals": { - "get": { - "operationId": "listEvals", - "tags": [ - "Evals" - ], - "summary": "List evals", - "parameters": [ - { - "name": "after", - "in": "query", - "description": "Identifier for the last eval from the previous pagination request.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "Number of evals to retrieve.", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order for evals by timestamp. Use `asc` for ascending order or `desc` for descending order.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "asc", - "desc" - ], - "default": "asc" - } - }, - { - "name": "order_by", - "in": "query", - "description": "Evals can be ordered by creation time or last updated time. Use\n`created_at` for creation time or `updated_at` for last updated time.\n", - "required": false, - "schema": { - "type": "string", - "enum": [ - "created_at", - "updated_at" - ], - "default": "created_at" - } - } - ], - "responses": { - "200": { - "description": "A list of evals", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/EvalList" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List evals", - "group": "evals", - "returns": "A list of [evals](https://platform.openai.com/docs/api-reference/evals/object) matching the specified filters.", - "path": "list", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"object\": \"eval\",\n \"data_source_config\": {\n \"type\": \"stored_completions\",\n \"metadata\": {\n \"usecase\": \"push_notifications_summarizer\"\n },\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"item\": {\n \"type\": \"object\"\n },\n \"sample\": {\n \"type\": \"object\"\n }\n },\n \"required\": [\n \"item\",\n \"sample\"\n ]\n }\n },\n \"testing_criteria\": [\n {\n \"name\": \"Push Notification Summary Grader\",\n \"id\": \"Push Notification Summary Grader-9b876f24-4762-4be9-aff4-db7a9b31c673\",\n \"type\": \"label_model\",\n \"model\": \"o3-mini\",\n \"input\": [\n {\n \"type\": \"message\",\n \"role\": \"developer\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"\\nLabel the following push notification summary as either correct or incorrect.\\nThe push notification and the summary will be provided below.\\nA good push notificiation summary is concise and snappy.\\nIf it is good, then label it as correct, if not, then incorrect.\\n\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"\\nPush notifications: {{item.input}}\\nSummary: {{sample.output_text}}\\n\"\n }\n }\n ],\n \"passing_labels\": [\n \"correct\"\n ],\n \"labels\": [\n \"correct\",\n \"incorrect\"\n ],\n \"sampling_params\": null\n }\n ],\n \"name\": \"Push Notification Summary Grader\",\n \"created_at\": 1739314509,\n \"metadata\": {\n \"description\": \"A stored completions eval for push notification summaries\"\n }\n }\n ],\n \"first_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"last_id\": \"eval_67aa884cf6688190b58f657d4441c8b7\",\n \"has_more\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals?limit=1 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.evals.list()\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const evalListResponse of client.evals.list()) {\n console.log(evalListResponse.id);\n}", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.EvalListPage;\nimport com.openai.models.evals.EvalListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n EvalListPage page = client.evals().list();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.evals.list\n\nputs(page)" - } - } - }, - "description": "List evaluations for a project.\n" - }, - "post": { - "operationId": "createEval", - "tags": [ - "Evals" - ], - "summary": "Create eval", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateEvalRequest" - } - } - } - }, - "responses": { - "201": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Eval" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create eval", - "group": "evals", - "returns": "The created [Eval](https://platform.openai.com/docs/api-reference/evals/object) object.", - "path": "post", - "examples": { - "response": "{\n \"object\": \"eval\",\n \"id\": \"eval_67b7fa9a81a88190ab4aa417e397ea21\",\n \"data_source_config\": {\n \"type\": \"stored_completions\",\n \"metadata\": {\n \"usecase\": \"chatbot\"\n },\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"item\": {\n \"type\": \"object\"\n },\n \"sample\": {\n \"type\": \"object\"\n }\n },\n \"required\": [\n \"item\",\n \"sample\"\n ]\n },\n \"testing_criteria\": [\n {\n \"name\": \"Example label grader\",\n \"type\": \"label_model\",\n \"model\": \"o3-mini\",\n \"input\": [\n {\n \"type\": \"message\",\n \"role\": \"developer\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Classify the sentiment of the following statement as one of positive, neutral, or negative\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Statement: {{item.input}}\"\n }\n }\n ],\n \"passing_labels\": [\n \"positive\"\n ],\n \"labels\": [\n \"positive\",\n \"neutral\",\n \"negative\"\n ]\n }\n ],\n \"name\": \"Sentiment\",\n \"created_at\": 1740110490,\n \"metadata\": {\n \"description\": \"An eval for sentiment analysis\"\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"name\": \"Sentiment\",\n \"data_source_config\": {\n \"type\": \"stored_completions\",\n \"metadata\": {\n \"usecase\": \"chatbot\"\n }\n },\n \"testing_criteria\": [\n {\n \"type\": \"label_model\",\n \"model\": \"o3-mini\",\n \"input\": [\n {\n \"role\": \"developer\",\n \"content\": \"Classify the sentiment of the following statement as one of 'positive', 'neutral', or 'negative'\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Statement: {{item.input}}\"\n }\n ],\n \"passing_labels\": [\n \"positive\"\n ],\n \"labels\": [\n \"positive\",\n \"neutral\",\n \"negative\"\n ],\n \"name\": \"Example label grader\"\n }\n ]\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\neval = client.evals.create(\n data_source_config={\n \"item_schema\": {\n \"foo\": \"bar\"\n },\n \"type\": \"custom\",\n },\n testing_criteria=[{\n \"input\": [{\n \"content\": \"content\",\n \"role\": \"role\",\n }],\n \"labels\": [\"string\"],\n \"model\": \"model\",\n \"name\": \"name\",\n \"passing_labels\": [\"string\"],\n \"type\": \"label_model\",\n }],\n)\nprint(eval.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst _eval = await client.evals.create({\n data_source_config: { item_schema: { foo: 'bar' }, type: 'custom' },\n testing_criteria: [\n {\n input: [{ content: 'content', role: 'role' }],\n labels: ['string'],\n model: 'model',\n name: 'name',\n passing_labels: ['string'],\n type: 'label_model',\n },\n ],\n});\n\nconsole.log(_eval.id);", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.core.JsonValue;\nimport com.openai.models.evals.EvalCreateParams;\nimport com.openai.models.evals.EvalCreateResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n EvalCreateParams params = EvalCreateParams.builder()\n .customDataSourceConfig(EvalCreateParams.DataSourceConfig.Custom.ItemSchema.builder()\n .putAdditionalProperty(\"foo\", JsonValue.from(\"bar\"))\n .build())\n .addTestingCriterion(EvalCreateParams.TestingCriterion.LabelModel.builder()\n .addInput(EvalCreateParams.TestingCriterion.LabelModel.Input.SimpleInputMessage.builder()\n .content(\"content\")\n .role(\"role\")\n .build())\n .addLabel(\"string\")\n .model(\"model\")\n .name(\"name\")\n .addPassingLabel(\"string\")\n .build())\n .build();\n EvalCreateResponse eval = client.evals().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\neval_ = openai.evals.create(\n data_source_config: {item_schema: {foo: \"bar\"}, type: :custom},\n testing_criteria: [\n {\n input: [{content: \"content\", role: \"role\"}],\n labels: [\"string\"],\n model: \"model\",\n name: \"name\",\n passing_labels: [\"string\"],\n type: :label_model\n }\n ]\n)\n\nputs(eval_)" - } - } - }, - "description": "Create the structure of an evaluation that can be used to test a model's performance.\nAn evaluation is a set of testing criteria and the config for a data source, which dictates the schema of the data used in the evaluation. After creating an evaluation, you can run it on different models and model parameters. We support several types of graders and datasources.\nFor more information, see the [Evals guide](https://platform.openai.com/docs/guides/evals).\n" - } - }, - "/evals/{eval_id}": { - "get": { - "operationId": "getEval", - "tags": [ - "Evals" - ], - "summary": "Get an eval", - "parameters": [ - { - "name": "eval_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation to retrieve." - } - ], - "responses": { - "200": { - "description": "The evaluation", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Eval" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Get an eval", - "group": "evals", - "returns": "The [Eval](https://platform.openai.com/docs/api-reference/evals/object) object matching the specified ID.", - "path": "get", - "examples": { - "response": "{\n \"object\": \"eval\",\n \"id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"data_source_config\": {\n \"type\": \"custom\",\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"item\": {\n \"type\": \"object\",\n \"properties\": {\n \"input\": {\n \"type\": \"string\"\n },\n \"ground_truth\": {\n \"type\": \"string\"\n }\n },\n \"required\": [\n \"input\",\n \"ground_truth\"\n ]\n }\n },\n \"required\": [\n \"item\"\n ]\n }\n },\n \"testing_criteria\": [\n {\n \"name\": \"String check\",\n \"id\": \"String check-2eaf2d8d-d649-4335-8148-9535a7ca73c2\",\n \"type\": \"string_check\",\n \"input\": \"{{item.input}}\",\n \"reference\": \"{{item.ground_truth}}\",\n \"operation\": \"eq\"\n }\n ],\n \"name\": \"External Data Eval\",\n \"created_at\": 1739314509,\n \"metadata\": {},\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\neval = client.evals.retrieve(\n \"eval_id\",\n)\nprint(eval.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst _eval = await client.evals.retrieve('eval_id');\n\nconsole.log(_eval.id);", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.EvalRetrieveParams;\nimport com.openai.models.evals.EvalRetrieveResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n EvalRetrieveResponse eval = client.evals().retrieve(\"eval_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\neval_ = openai.evals.retrieve(\"eval_id\")\n\nputs(eval_)" - } - } - }, - "description": "Get an evaluation by ID.\n" - }, - "post": { - "operationId": "updateEval", - "tags": [ - "Evals" - ], - "summary": "Update an eval", - "parameters": [ - { - "name": "eval_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation to update." - } - ], - "requestBody": { - "description": "Request to update an evaluation", - "required": true, - "content": { - "application/json": { - "schema": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "Rename the evaluation." - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - } - } - } - }, - "responses": { - "200": { - "description": "The updated evaluation", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Eval" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Update an eval", - "group": "evals", - "returns": "The [Eval](https://platform.openai.com/docs/api-reference/evals/object) object matching the updated version.", - "path": "update", - "examples": { - "response": "{\n \"object\": \"eval\",\n \"id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"data_source_config\": {\n \"type\": \"custom\",\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"item\": {\n \"type\": \"object\",\n \"properties\": {\n \"input\": {\n \"type\": \"string\"\n },\n \"ground_truth\": {\n \"type\": \"string\"\n }\n },\n \"required\": [\n \"input\",\n \"ground_truth\"\n ]\n }\n },\n \"required\": [\n \"item\"\n ]\n }\n },\n \"testing_criteria\": [\n {\n \"name\": \"String check\",\n \"id\": \"String check-2eaf2d8d-d649-4335-8148-9535a7ca73c2\",\n \"type\": \"string_check\",\n \"input\": \"{{item.input}}\",\n \"reference\": \"{{item.ground_truth}}\",\n \"operation\": \"eq\"\n }\n ],\n \"name\": \"Updated Eval\",\n \"created_at\": 1739314509,\n \"metadata\": {\"description\": \"Updated description\"},\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"name\": \"Updated Eval\", \"metadata\": {\"description\": \"Updated description\"}}'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\neval = client.evals.update(\n eval_id=\"eval_id\",\n)\nprint(eval.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst _eval = await client.evals.update('eval_id');\n\nconsole.log(_eval.id);", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.EvalUpdateParams;\nimport com.openai.models.evals.EvalUpdateResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n EvalUpdateResponse eval = client.evals().update(\"eval_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\neval_ = openai.evals.update(\"eval_id\")\n\nputs(eval_)" - } - } - }, - "description": "Update certain properties of an evaluation.\n" - }, - "delete": { - "operationId": "deleteEval", - "tags": [ - "Evals" - ], - "summary": "Delete an eval", - "parameters": [ - { - "name": "eval_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation to delete." - } - ], - "responses": { - "200": { - "description": "Successfully deleted the evaluation.", - "content": { - "application/json": { - "schema": { - "type": "object", - "properties": { - "object": { - "type": "string", - "example": "eval.deleted" - }, - "deleted": { - "type": "boolean", - "example": true - }, - "eval_id": { - "type": "string", - "example": "eval_abc123" - } - }, - "required": [ - "object", - "deleted", - "eval_id" - ] - } - } - } - }, - "404": { - "description": "Evaluation not found.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Error" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete an eval", - "group": "evals", - "returns": "A deletion confirmation object.", - "examples": { - "response": "{\n \"object\": \"eval.deleted\",\n \"deleted\": true,\n \"eval_id\": \"eval_abc123\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/eval_abc123 \\\n -X DELETE \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\neval = client.evals.delete(\n \"eval_id\",\n)\nprint(eval.eval_id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst _eval = await client.evals.delete('eval_id');\n\nconsole.log(_eval.eval_id);", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.EvalDeleteParams;\nimport com.openai.models.evals.EvalDeleteResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n EvalDeleteResponse eval = client.evals().delete(\"eval_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\neval_ = openai.evals.delete(\"eval_id\")\n\nputs(eval_)" - } - } - }, - "description": "Delete an evaluation.\n" - } - }, - "/evals/{eval_id}/runs": { - "get": { - "operationId": "getEvalRuns", - "tags": [ - "Evals" - ], - "summary": "Get eval runs", - "parameters": [ - { - "name": "eval_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation to retrieve runs for." - }, - { - "name": "after", - "in": "query", - "description": "Identifier for the last run from the previous pagination request.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "Number of runs to retrieve.", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order for runs by timestamp. Use `asc` for ascending order or `desc` for descending order. Defaults to `asc`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "asc", - "desc" - ], - "default": "asc" - } - }, - { - "name": "status", - "in": "query", - "description": "Filter runs by status. One of `queued` | `in_progress` | `failed` | `completed` | `canceled`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "queued", - "in_progress", - "completed", - "canceled", - "failed" - ] - } - } - ], - "responses": { - "200": { - "description": "A list of runs for the evaluation", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/EvalRunList" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Get eval runs", - "group": "evals", - "returns": "A list of [EvalRun](https://platform.openai.com/docs/api-reference/evals/run-object) objects matching the specified ID.", - "path": "get-runs", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"eval.run\",\n \"id\": \"evalrun_67e0c7d31560819090d60c0780591042\",\n \"eval_id\": \"eval_67e0c726d560819083f19a957c4c640b\",\n \"report_url\": \"https://platform.openai.com/evaluations/eval_67e0c726d560819083f19a957c4c640b\",\n \"status\": \"completed\",\n \"model\": \"o3-mini\",\n \"name\": \"bulk_with_negative_examples_o3-mini\",\n \"created_at\": 1742784467,\n \"result_counts\": {\n \"total\": 1,\n \"errored\": 0,\n \"failed\": 0,\n \"passed\": 1\n },\n \"per_model_usage\": [\n {\n \"model_name\": \"o3-mini\",\n \"invocation_count\": 1,\n \"prompt_tokens\": 563,\n \"completion_tokens\": 874,\n \"total_tokens\": 1437,\n \"cached_tokens\": 0\n }\n ],\n \"per_testing_criteria_results\": [\n {\n \"testing_criteria\": \"Push Notification Summary Grader-1808cd0b-eeec-4e0b-a519-337e79f4f5d1\",\n \"passed\": 1,\n \"failed\": 0\n }\n ],\n \"data_source\": {\n \"type\": \"completions\",\n \"source\": {\n \"type\": \"file_content\",\n \"content\": [\n {\n \"item\": {\n \"notifications\": \"\\n- New message from Sarah: \\\"Can you call me later?\\\"\\n- Your package has been delivered!\\n- Flash sale: 20% off electronics for the next 2 hours!\\n\"\n }\n }\n ]\n },\n \"input_messages\": {\n \"type\": \"template\",\n \"template\": [\n {\n \"type\": \"message\",\n \"role\": \"developer\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"\\n\\n\\n\\nYou are a helpful assistant that takes in an array of push notifications and returns a collapsed summary of them.\\nThe push notification will be provided as follows:\\n\\n...notificationlist...\\n\\n\\nYou should return just the summary and nothing else.\\n\\n\\nYou should return a summary that is concise and snappy.\\n\\n\\nHere is an example of a good summary:\\n\\n- Traffic alert: Accident reported on Main Street.- Package out for delivery: Expected by 5 PM.- New friend suggestion: Connect with Emma.\\n\\n\\nTraffic alert, package expected by 5pm, suggestion for new friend (Emily).\\n\\n\\n\\nHere is an example of a bad summary:\\n\\n- Traffic alert: Accident reported on Main Street.- Package out for delivery: Expected by 5 PM.- New friend suggestion: Connect with Emma.\\n\\n\\nTraffic alert reported on main street. You have a package that will arrive by 5pm, Emily is a new friend suggested for you.\\n\\n\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"{{item.notifications}}\"\n }\n }\n ]\n },\n \"model\": \"o3-mini\",\n \"sampling_params\": null\n },\n \"error\": null,\n \"metadata\": {}\n }\n ],\n \"first_id\": \"evalrun_67e0c7d31560819090d60c0780591042\",\n \"last_id\": \"evalrun_67e0c7d31560819090d60c0780591042\",\n \"has_more\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/egroup_67abd54d9b0081909a86353f6fb9317a/runs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.evals.runs.list(\n eval_id=\"eval_id\",\n)\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const runListResponse of client.evals.runs.list('eval_id')) {\n console.log(runListResponse.id);\n}", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.runs.RunListPage;\nimport com.openai.models.evals.runs.RunListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunListPage page = client.evals().runs().list(\"eval_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.evals.runs.list(\"eval_id\")\n\nputs(page)" - } - } - }, - "description": "Get a list of runs for an evaluation.\n" - }, - "post": { - "operationId": "createEvalRun", - "tags": [ - "Evals" - ], - "summary": "Create eval run", - "parameters": [ - { - "in": "path", - "name": "eval_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation to create a run for." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateEvalRunRequest" - } - } - } - }, - "responses": { - "201": { - "description": "Successfully created a run for the evaluation", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/EvalRun" - } - } - } - }, - "400": { - "description": "Bad request (for example, missing eval object)", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Error" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create eval run", - "group": "evals", - "returns": "The [EvalRun](https://platform.openai.com/docs/api-reference/evals/run-object) object matching the specified ID.", - "examples": { - "response": "{\n \"object\": \"eval.run\",\n \"id\": \"evalrun_67e57965b480819094274e3a32235e4c\",\n \"eval_id\": \"eval_67e579652b548190aaa83ada4b125f47\",\n \"report_url\": \"https://platform.openai.com/evaluations/eval_67e579652b548190aaa83ada4b125f47&run_id=evalrun_67e57965b480819094274e3a32235e4c\",\n \"status\": \"queued\",\n \"model\": \"gpt-4o-mini\",\n \"name\": \"gpt-4o-mini\",\n \"created_at\": 1743092069,\n \"result_counts\": {\n \"total\": 0,\n \"errored\": 0,\n \"failed\": 0,\n \"passed\": 0\n },\n \"per_model_usage\": null,\n \"per_testing_criteria_results\": null,\n \"data_source\": {\n \"type\": \"completions\",\n \"source\": {\n \"type\": \"file_content\",\n \"content\": [\n {\n \"item\": {\n \"input\": \"Tech Company Launches Advanced Artificial Intelligence Platform\",\n \"ground_truth\": \"Technology\"\n }\n }\n ]\n },\n \"input_messages\": {\n \"type\": \"template\",\n \"template\": [\n {\n \"type\": \"message\",\n \"role\": \"developer\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\\n\\n# Steps\\n\\n1. Analyze the content of the news headline to understand its primary focus.\\n2. Extract the subject matter, identifying any key indicators or keywords.\\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\\n4. Ensure only one category is selected per headline.\\n\\n# Output Format\\n\\nRespond with the chosen category as a single word. For instance: \\\"Technology\\\", \\\"Markets\\\", \\\"World\\\", \\\"Business\\\", or \\\"Sports\\\".\\n\\n# Examples\\n\\n**Input**: \\\"Apple Unveils New iPhone Model, Featuring Advanced AI Features\\\" \\n**Output**: \\\"Technology\\\"\\n\\n**Input**: \\\"Global Stocks Mixed as Investors Await Central Bank Decisions\\\" \\n**Output**: \\\"Markets\\\"\\n\\n**Input**: \\\"War in Ukraine: Latest Updates on Negotiation Status\\\" \\n**Output**: \\\"World\\\"\\n\\n**Input**: \\\"Microsoft in Talks to Acquire Gaming Company for $2 Billion\\\" \\n**Output**: \\\"Business\\\"\\n\\n**Input**: \\\"Manchester United Secures Win in Premier League Football Match\\\" \\n**Output**: \\\"Sports\\\" \\n\\n# Notes\\n\\n- If the headline appears to fit into more than one category, choose the most dominant theme.\\n- Keywords or phrases such as \\\"stocks\\\", \\\"company acquisition\\\", \\\"match\\\", or technological brands can be good indicators for classification.\\n\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"{{item.input}}\"\n }\n }\n ]\n },\n \"model\": \"gpt-4o-mini\",\n \"sampling_params\": {\n \"seed\": 42,\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_completions_tokens\": 2048\n }\n },\n \"error\": null,\n \"metadata\": {}\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/eval_67e579652b548190aaa83ada4b125f47/runs \\\n -X POST \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"name\":\"gpt-4o-mini\",\"data_source\":{\"type\":\"completions\",\"input_messages\":{\"type\":\"template\",\"template\":[{\"role\":\"developer\",\"content\":\"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\\n\\n# Steps\\n\\n1. Analyze the content of the news headline to understand its primary focus.\\n2. Extract the subject matter, identifying any key indicators or keywords.\\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\\n4. Ensure only one category is selected per headline.\\n\\n# Output Format\\n\\nRespond with the chosen category as a single word. For instance: \\\"Technology\\\", \\\"Markets\\\", \\\"World\\\", \\\"Business\\\", or \\\"Sports\\\".\\n\\n# Examples\\n\\n**Input**: \\\"Apple Unveils New iPhone Model, Featuring Advanced AI Features\\\" \\n**Output**: \\\"Technology\\\"\\n\\n**Input**: \\\"Global Stocks Mixed as Investors Await Central Bank Decisions\\\" \\n**Output**: \\\"Markets\\\"\\n\\n**Input**: \\\"War in Ukraine: Latest Updates on Negotiation Status\\\" \\n**Output**: \\\"World\\\"\\n\\n**Input**: \\\"Microsoft in Talks to Acquire Gaming Company for $2 Billion\\\" \\n**Output**: \\\"Business\\\"\\n\\n**Input**: \\\"Manchester United Secures Win in Premier League Football Match\\\" \\n**Output**: \\\"Sports\\\" \\n\\n# Notes\\n\\n- If the headline appears to fit into more than one category, choose the most dominant theme.\\n- Keywords or phrases such as \\\"stocks\\\", \\\"company acquisition\\\", \\\"match\\\", or technological brands can be good indicators for classification.\\n\"} , {\"role\":\"user\",\"content\":\"{{item.input}}\"}]} ,\"sampling_params\":{\"temperature\":1,\"max_completions_tokens\":2048,\"top_p\":1,\"seed\":42},\"model\":\"gpt-4o-mini\",\"source\":{\"type\":\"file_content\",\"content\":[{\"item\":{\"input\":\"Tech Company Launches Advanced Artificial Intelligence Platform\",\"ground_truth\":\"Technology\"}}]}}'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.evals.runs.create(\n eval_id=\"eval_id\",\n data_source={\n \"source\": {\n \"content\": [{\n \"item\": {\n \"foo\": \"bar\"\n }\n }],\n \"type\": \"file_content\",\n },\n \"type\": \"jsonl\",\n },\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.evals.runs.create('eval_id', {\n data_source: { source: { content: [{ item: { foo: 'bar' } }], type: 'file_content' }, type: 'jsonl' },\n});\n\nconsole.log(run.id);", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.core.JsonValue;\nimport com.openai.models.evals.runs.CreateEvalJsonlRunDataSource;\nimport com.openai.models.evals.runs.RunCreateParams;\nimport com.openai.models.evals.runs.RunCreateResponse;\nimport java.util.List;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunCreateParams params = RunCreateParams.builder()\n .evalId(\"eval_id\")\n .dataSource(CreateEvalJsonlRunDataSource.builder()\n .fileContentSource(List.of(CreateEvalJsonlRunDataSource.Source.FileContent.Content.builder()\n .item(CreateEvalJsonlRunDataSource.Source.FileContent.Content.Item.builder()\n .putAdditionalProperty(\"foo\", JsonValue.from(\"bar\"))\n .build())\n .build()))\n .build())\n .build();\n RunCreateResponse run = client.evals().runs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.evals.runs.create(\n \"eval_id\",\n data_source: {source: {content: [{item: {foo: \"bar\"}}], type: :file_content}, type: :jsonl}\n)\n\nputs(run)" - } - } - }, - "description": "Kicks off a new run for a given evaluation, specifying the data source, and what model configuration to use to test. The datasource will be validated against the schema specified in the config of the evaluation.\n" - } - }, - "/evals/{eval_id}/runs/{run_id}": { - "get": { - "operationId": "getEvalRun", - "tags": [ - "Evals" - ], - "summary": "Get an eval run", - "parameters": [ - { - "name": "eval_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation to retrieve runs for." - }, - { - "name": "run_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run to retrieve." - } - ], - "responses": { - "200": { - "description": "The evaluation run", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/EvalRun" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Get an eval run", - "group": "evals", - "returns": "The [EvalRun](https://platform.openai.com/docs/api-reference/evals/run-object) object matching the specified ID.", - "path": "get", - "examples": { - "response": "{\n \"object\": \"eval.run\",\n \"id\": \"evalrun_67abd54d60ec8190832b46859da808f7\",\n \"eval_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"report_url\": \"https://platform.openai.com/evaluations/eval_67abd54d9b0081909a86353f6fb9317a?run_id=evalrun_67abd54d60ec8190832b46859da808f7\",\n \"status\": \"queued\",\n \"model\": \"gpt-4o-mini\",\n \"name\": \"gpt-4o-mini\",\n \"created_at\": 1743092069,\n \"result_counts\": {\n \"total\": 0,\n \"errored\": 0,\n \"failed\": 0,\n \"passed\": 0\n },\n \"per_model_usage\": null,\n \"per_testing_criteria_results\": null,\n \"data_source\": {\n \"type\": \"completions\",\n \"source\": {\n \"type\": \"file_content\",\n \"content\": [\n {\n \"item\": {\n \"input\": \"Tech Company Launches Advanced Artificial Intelligence Platform\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"Central Bank Increases Interest Rates Amid Inflation Concerns\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"International Summit Addresses Climate Change Strategies\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Major Retailer Reports Record-Breaking Holiday Sales\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"National Team Qualifies for World Championship Finals\",\n \"ground_truth\": \"Sports\"\n }\n },\n {\n \"item\": {\n \"input\": \"Stock Markets Rally After Positive Economic Data Released\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"Global Manufacturer Announces Merger with Competitor\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"Breakthrough in Renewable Energy Technology Unveiled\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"World Leaders Sign Historic Climate Agreement\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Professional Athlete Sets New Record in Championship Event\",\n \"ground_truth\": \"Sports\"\n }\n },\n {\n \"item\": {\n \"input\": \"Financial Institutions Adapt to New Regulatory Requirements\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"Tech Conference Showcases Advances in Artificial Intelligence\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"Global Markets Respond to Oil Price Fluctuations\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"International Cooperation Strengthened Through New Treaty\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Sports League Announces Revised Schedule for Upcoming Season\",\n \"ground_truth\": \"Sports\"\n }\n }\n ]\n },\n \"input_messages\": {\n \"type\": \"template\",\n \"template\": [\n {\n \"type\": \"message\",\n \"role\": \"developer\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\\n\\n# Steps\\n\\n1. Analyze the content of the news headline to understand its primary focus.\\n2. Extract the subject matter, identifying any key indicators or keywords.\\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\\n4. Ensure only one category is selected per headline.\\n\\n# Output Format\\n\\nRespond with the chosen category as a single word. For instance: \\\"Technology\\\", \\\"Markets\\\", \\\"World\\\", \\\"Business\\\", or \\\"Sports\\\".\\n\\n# Examples\\n\\n**Input**: \\\"Apple Unveils New iPhone Model, Featuring Advanced AI Features\\\" \\n**Output**: \\\"Technology\\\"\\n\\n**Input**: \\\"Global Stocks Mixed as Investors Await Central Bank Decisions\\\" \\n**Output**: \\\"Markets\\\"\\n\\n**Input**: \\\"War in Ukraine: Latest Updates on Negotiation Status\\\" \\n**Output**: \\\"World\\\"\\n\\n**Input**: \\\"Microsoft in Talks to Acquire Gaming Company for $2 Billion\\\" \\n**Output**: \\\"Business\\\"\\n\\n**Input**: \\\"Manchester United Secures Win in Premier League Football Match\\\" \\n**Output**: \\\"Sports\\\" \\n\\n# Notes\\n\\n- If the headline appears to fit into more than one category, choose the most dominant theme.\\n- Keywords or phrases such as \\\"stocks\\\", \\\"company acquisition\\\", \\\"match\\\", or technological brands can be good indicators for classification.\\n\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"{{item.input}}\"\n }\n }\n ]\n },\n \"model\": \"gpt-4o-mini\",\n \"sampling_params\": {\n \"seed\": 42,\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_completions_tokens\": 2048\n }\n },\n \"error\": null,\n \"metadata\": {}\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7 \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.evals.runs.retrieve(\n run_id=\"run_id\",\n eval_id=\"eval_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.evals.runs.retrieve('run_id', { eval_id: 'eval_id' });\n\nconsole.log(run.id);", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.runs.RunRetrieveParams;\nimport com.openai.models.evals.runs.RunRetrieveResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunRetrieveParams params = RunRetrieveParams.builder()\n .evalId(\"eval_id\")\n .runId(\"run_id\")\n .build();\n RunRetrieveResponse run = client.evals().runs().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.evals.runs.retrieve(\"run_id\", eval_id: \"eval_id\")\n\nputs(run)" - } - } - }, - "description": "Get an evaluation run by ID.\n" - }, - "post": { - "operationId": "cancelEvalRun", - "tags": [ - "Evals" - ], - "summary": "Cancel eval run", - "parameters": [ - { - "name": "eval_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation whose run you want to cancel." - }, - { - "name": "run_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run to cancel." - } - ], - "responses": { - "200": { - "description": "The canceled eval run object", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/EvalRun" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Cancel eval run", - "group": "evals", - "returns": "The updated [EvalRun](https://platform.openai.com/docs/api-reference/evals/run-object) object reflecting that the run is canceled.", - "path": "post", - "examples": { - "response": "{\n \"object\": \"eval.run\",\n \"id\": \"evalrun_67abd54d60ec8190832b46859da808f7\",\n \"eval_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"report_url\": \"https://platform.openai.com/evaluations/eval_67abd54d9b0081909a86353f6fb9317a?run_id=evalrun_67abd54d60ec8190832b46859da808f7\",\n \"status\": \"canceled\",\n \"model\": \"gpt-4o-mini\",\n \"name\": \"gpt-4o-mini\",\n \"created_at\": 1743092069,\n \"result_counts\": {\n \"total\": 0,\n \"errored\": 0,\n \"failed\": 0,\n \"passed\": 0\n },\n \"per_model_usage\": null,\n \"per_testing_criteria_results\": null,\n \"data_source\": {\n \"type\": \"completions\",\n \"source\": {\n \"type\": \"file_content\",\n \"content\": [\n {\n \"item\": {\n \"input\": \"Tech Company Launches Advanced Artificial Intelligence Platform\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"Central Bank Increases Interest Rates Amid Inflation Concerns\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"International Summit Addresses Climate Change Strategies\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Major Retailer Reports Record-Breaking Holiday Sales\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"National Team Qualifies for World Championship Finals\",\n \"ground_truth\": \"Sports\"\n }\n },\n {\n \"item\": {\n \"input\": \"Stock Markets Rally After Positive Economic Data Released\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"Global Manufacturer Announces Merger with Competitor\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"Breakthrough in Renewable Energy Technology Unveiled\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"World Leaders Sign Historic Climate Agreement\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Professional Athlete Sets New Record in Championship Event\",\n \"ground_truth\": \"Sports\"\n }\n },\n {\n \"item\": {\n \"input\": \"Financial Institutions Adapt to New Regulatory Requirements\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"Tech Conference Showcases Advances in Artificial Intelligence\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"Global Markets Respond to Oil Price Fluctuations\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"International Cooperation Strengthened Through New Treaty\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Sports League Announces Revised Schedule for Upcoming Season\",\n \"ground_truth\": \"Sports\"\n }\n }\n ]\n },\n \"input_messages\": {\n \"type\": \"template\",\n \"template\": [\n {\n \"type\": \"message\",\n \"role\": \"developer\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\\n\\n# Steps\\n\\n1. Analyze the content of the news headline to understand its primary focus.\\n2. Extract the subject matter, identifying any key indicators or keywords.\\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\\n4. Ensure only one category is selected per headline.\\n\\n# Output Format\\n\\nRespond with the chosen category as a single word. For instance: \\\"Technology\\\", \\\"Markets\\\", \\\"World\\\", \\\"Business\\\", or \\\"Sports\\\".\\n\\n# Examples\\n\\n**Input**: \\\"Apple Unveils New iPhone Model, Featuring Advanced AI Features\\\" \\n**Output**: \\\"Technology\\\"\\n\\n**Input**: \\\"Global Stocks Mixed as Investors Await Central Bank Decisions\\\" \\n**Output**: \\\"Markets\\\"\\n\\n**Input**: \\\"War in Ukraine: Latest Updates on Negotiation Status\\\" \\n**Output**: \\\"World\\\"\\n\\n**Input**: \\\"Microsoft in Talks to Acquire Gaming Company for $2 Billion\\\" \\n**Output**: \\\"Business\\\"\\n\\n**Input**: \\\"Manchester United Secures Win in Premier League Football Match\\\" \\n**Output**: \\\"Sports\\\" \\n\\n# Notes\\n\\n- If the headline appears to fit into more than one category, choose the most dominant theme.\\n- Keywords or phrases such as \\\"stocks\\\", \\\"company acquisition\\\", \\\"match\\\", or technological brands can be good indicators for classification.\\n\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"{{item.input}}\"\n }\n }\n ]\n },\n \"model\": \"gpt-4o-mini\",\n \"sampling_params\": {\n \"seed\": 42,\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_completions_tokens\": 2048\n }\n },\n \"error\": null,\n \"metadata\": {}\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7/cancel \\ -X POST \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.evals.runs.cancel(\n run_id=\"run_id\",\n eval_id=\"eval_id\",\n)\nprint(response.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.evals.runs.cancel('run_id', { eval_id: 'eval_id' });\n\nconsole.log(response.id);", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.runs.RunCancelParams;\nimport com.openai.models.evals.runs.RunCancelResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunCancelParams params = RunCancelParams.builder()\n .evalId(\"eval_id\")\n .runId(\"run_id\")\n .build();\n RunCancelResponse response = client.evals().runs().cancel(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.evals.runs.cancel(\"run_id\", eval_id: \"eval_id\")\n\nputs(response)" - } - } - }, - "description": "Cancel an ongoing evaluation run.\n" - }, - "delete": { - "operationId": "deleteEvalRun", - "tags": [ - "Evals" - ], - "summary": "Delete eval run", - "parameters": [ - { - "name": "eval_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation to delete the run from." - }, - { - "name": "run_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run to delete." - } - ], - "responses": { - "200": { - "description": "Successfully deleted the eval run", - "content": { - "application/json": { - "schema": { - "type": "object", - "properties": { - "object": { - "type": "string", - "example": "eval.run.deleted" - }, - "deleted": { - "type": "boolean", - "example": true - }, - "run_id": { - "type": "string", - "example": "evalrun_677469f564d48190807532a852da3afb" - } - } - } - } - } - }, - "404": { - "description": "Run not found", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Error" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete eval run", - "group": "evals", - "returns": "An object containing the status of the delete operation.", - "path": "delete", - "examples": { - "response": "{\n \"object\": \"eval.run.deleted\",\n \"deleted\": true,\n \"run_id\": \"evalrun_abc456\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/eval_123abc/runs/evalrun_abc456 \\\n -X DELETE \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.evals.runs.delete(\n run_id=\"run_id\",\n eval_id=\"eval_id\",\n)\nprint(run.run_id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.evals.runs.delete('run_id', { eval_id: 'eval_id' });\n\nconsole.log(run.run_id);", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.runs.RunDeleteParams;\nimport com.openai.models.evals.runs.RunDeleteResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunDeleteParams params = RunDeleteParams.builder()\n .evalId(\"eval_id\")\n .runId(\"run_id\")\n .build();\n RunDeleteResponse run = client.evals().runs().delete(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.evals.runs.delete(\"run_id\", eval_id: \"eval_id\")\n\nputs(run)" - } - } - }, - "description": "Delete an eval run.\n" - } - }, - "/evals/{eval_id}/runs/{run_id}/output_items": { - "get": { - "operationId": "getEvalRunOutputItems", - "tags": [ - "Evals" - ], - "summary": "Get eval run output items", - "parameters": [ - { - "name": "eval_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation to retrieve runs for." - }, - { - "name": "run_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run to retrieve output items for." - }, - { - "name": "after", - "in": "query", - "description": "Identifier for the last output item from the previous pagination request.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "Number of output items to retrieve.", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "status", - "in": "query", - "description": "Filter output items by status. Use `failed` to filter by failed output\nitems or `pass` to filter by passed output items.\n", - "required": false, - "schema": { - "type": "string", - "enum": [ - "fail", - "pass" - ] - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order for output items by timestamp. Use `asc` for ascending order or `desc` for descending order. Defaults to `asc`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "asc", - "desc" - ], - "default": "asc" - } - } - ], - "responses": { - "200": { - "description": "A list of output items for the evaluation run", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/EvalRunOutputItemList" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Get eval run output items", - "group": "evals", - "returns": "A list of [EvalRunOutputItem](https://platform.openai.com/docs/api-reference/evals/run-output-item-object) objects matching the specified ID.", - "path": "get", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"eval.run.output_item\",\n \"id\": \"outputitem_67e5796c28e081909917bf79f6e6214d\",\n \"created_at\": 1743092076,\n \"run_id\": \"evalrun_67abd54d60ec8190832b46859da808f7\",\n \"eval_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"status\": \"pass\",\n \"datasource_item_id\": 5,\n \"datasource_item\": {\n \"input\": \"Stock Markets Rally After Positive Economic Data Released\",\n \"ground_truth\": \"Markets\"\n },\n \"results\": [\n {\n \"name\": \"String check-a2486074-d803-4445-b431-ad2262e85d47\",\n \"sample\": null,\n \"passed\": true,\n \"score\": 1.0\n }\n ],\n \"sample\": {\n \"input\": [\n {\n \"role\": \"developer\",\n \"content\": \"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\\n\\n# Steps\\n\\n1. Analyze the content of the news headline to understand its primary focus.\\n2. Extract the subject matter, identifying any key indicators or keywords.\\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\\n4. Ensure only one category is selected per headline.\\n\\n# Output Format\\n\\nRespond with the chosen category as a single word. For instance: \\\"Technology\\\", \\\"Markets\\\", \\\"World\\\", \\\"Business\\\", or \\\"Sports\\\".\\n\\n# Examples\\n\\n**Input**: \\\"Apple Unveils New iPhone Model, Featuring Advanced AI Features\\\" \\n**Output**: \\\"Technology\\\"\\n\\n**Input**: \\\"Global Stocks Mixed as Investors Await Central Bank Decisions\\\" \\n**Output**: \\\"Markets\\\"\\n\\n**Input**: \\\"War in Ukraine: Latest Updates on Negotiation Status\\\" \\n**Output**: \\\"World\\\"\\n\\n**Input**: \\\"Microsoft in Talks to Acquire Gaming Company for $2 Billion\\\" \\n**Output**: \\\"Business\\\"\\n\\n**Input**: \\\"Manchester United Secures Win in Premier League Football Match\\\" \\n**Output**: \\\"Sports\\\" \\n\\n# Notes\\n\\n- If the headline appears to fit into more than one category, choose the most dominant theme.\\n- Keywords or phrases such as \\\"stocks\\\", \\\"company acquisition\\\", \\\"match\\\", or technological brands can be good indicators for classification.\\n\",\n \"tool_call_id\": null,\n \"tool_calls\": null,\n \"function_call\": null\n },\n {\n \"role\": \"user\",\n \"content\": \"Stock Markets Rally After Positive Economic Data Released\",\n \"tool_call_id\": null,\n \"tool_calls\": null,\n \"function_call\": null\n }\n ],\n \"output\": [\n {\n \"role\": \"assistant\",\n \"content\": \"Markets\",\n \"tool_call_id\": null,\n \"tool_calls\": null,\n \"function_call\": null\n }\n ],\n \"finish_reason\": \"stop\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"usage\": {\n \"total_tokens\": 325,\n \"completion_tokens\": 2,\n \"prompt_tokens\": 323,\n \"cached_tokens\": 0\n },\n \"error\": null,\n \"temperature\": 1.0,\n \"max_completion_tokens\": 2048,\n \"top_p\": 1.0,\n \"seed\": 42\n }\n }\n ],\n \"first_id\": \"outputitem_67e5796c28e081909917bf79f6e6214d\",\n \"last_id\": \"outputitem_67e5796c28e081909917bf79f6e6214d\",\n \"has_more\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/egroup_67abd54d9b0081909a86353f6fb9317a/runs/erun_67abd54d60ec8190832b46859da808f7/output_items \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.evals.runs.output_items.list(\n run_id=\"run_id\",\n eval_id=\"eval_id\",\n)\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const outputItemListResponse of client.evals.runs.outputItems.list('run_id', {\n eval_id: 'eval_id',\n})) {\n console.log(outputItemListResponse.id);\n}", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.runs.outputitems.OutputItemListPage;\nimport com.openai.models.evals.runs.outputitems.OutputItemListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n OutputItemListParams params = OutputItemListParams.builder()\n .evalId(\"eval_id\")\n .runId(\"run_id\")\n .build();\n OutputItemListPage page = client.evals().runs().outputItems().list(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.evals.runs.output_items.list(\"run_id\", eval_id: \"eval_id\")\n\nputs(page)" - } - } - }, - "description": "Get a list of output items for an evaluation run.\n" - } - }, - "/evals/{eval_id}/runs/{run_id}/output_items/{output_item_id}": { - "get": { - "operationId": "getEvalRunOutputItem", - "tags": [ - "Evals" - ], - "summary": "Get an output item of an eval run", - "parameters": [ - { - "name": "eval_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the evaluation to retrieve runs for." - }, - { - "name": "run_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run to retrieve." - }, - { - "name": "output_item_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the output item to retrieve." - } - ], - "responses": { - "200": { - "description": "The evaluation run output item", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/EvalRunOutputItem" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Get an output item of an eval run", - "group": "evals", - "returns": "The [EvalRunOutputItem](https://platform.openai.com/docs/api-reference/evals/run-output-item-object) object matching the specified ID.", - "path": "get", - "examples": { - "response": "{\n \"object\": \"eval.run.output_item\",\n \"id\": \"outputitem_67e5796c28e081909917bf79f6e6214d\",\n \"created_at\": 1743092076,\n \"run_id\": \"evalrun_67abd54d60ec8190832b46859da808f7\",\n \"eval_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"status\": \"pass\",\n \"datasource_item_id\": 5,\n \"datasource_item\": {\n \"input\": \"Stock Markets Rally After Positive Economic Data Released\",\n \"ground_truth\": \"Markets\"\n },\n \"results\": [\n {\n \"name\": \"String check-a2486074-d803-4445-b431-ad2262e85d47\",\n \"sample\": null,\n \"passed\": true,\n \"score\": 1.0\n }\n ],\n \"sample\": {\n \"input\": [\n {\n \"role\": \"developer\",\n \"content\": \"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\\n\\n# Steps\\n\\n1. Analyze the content of the news headline to understand its primary focus.\\n2. Extract the subject matter, identifying any key indicators or keywords.\\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\\n4. Ensure only one category is selected per headline.\\n\\n# Output Format\\n\\nRespond with the chosen category as a single word. For instance: \\\"Technology\\\", \\\"Markets\\\", \\\"World\\\", \\\"Business\\\", or \\\"Sports\\\".\\n\\n# Examples\\n\\n**Input**: \\\"Apple Unveils New iPhone Model, Featuring Advanced AI Features\\\" \\n**Output**: \\\"Technology\\\"\\n\\n**Input**: \\\"Global Stocks Mixed as Investors Await Central Bank Decisions\\\" \\n**Output**: \\\"Markets\\\"\\n\\n**Input**: \\\"War in Ukraine: Latest Updates on Negotiation Status\\\" \\n**Output**: \\\"World\\\"\\n\\n**Input**: \\\"Microsoft in Talks to Acquire Gaming Company for $2 Billion\\\" \\n**Output**: \\\"Business\\\"\\n\\n**Input**: \\\"Manchester United Secures Win in Premier League Football Match\\\" \\n**Output**: \\\"Sports\\\" \\n\\n# Notes\\n\\n- If the headline appears to fit into more than one category, choose the most dominant theme.\\n- Keywords or phrases such as \\\"stocks\\\", \\\"company acquisition\\\", \\\"match\\\", or technological brands can be good indicators for classification.\\n\",\n \"tool_call_id\": null,\n \"tool_calls\": null,\n \"function_call\": null\n },\n {\n \"role\": \"user\",\n \"content\": \"Stock Markets Rally After Positive Economic Data Released\",\n \"tool_call_id\": null,\n \"tool_calls\": null,\n \"function_call\": null\n }\n ],\n \"output\": [\n {\n \"role\": \"assistant\",\n \"content\": \"Markets\",\n \"tool_call_id\": null,\n \"tool_calls\": null,\n \"function_call\": null\n }\n ],\n \"finish_reason\": \"stop\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"usage\": {\n \"total_tokens\": 325,\n \"completion_tokens\": 2,\n \"prompt_tokens\": 323,\n \"cached_tokens\": 0\n },\n \"error\": null,\n \"temperature\": 1.0,\n \"max_completion_tokens\": 2048,\n \"top_p\": 1.0,\n \"seed\": 42\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7/output_items/outputitem_67abd55eb6548190bb580745d5644a33 \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\noutput_item = client.evals.runs.output_items.retrieve(\n output_item_id=\"output_item_id\",\n eval_id=\"eval_id\",\n run_id=\"run_id\",\n)\nprint(output_item.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst outputItem = await client.evals.runs.outputItems.retrieve('output_item_id', {\n eval_id: 'eval_id',\n run_id: 'run_id',\n});\n\nconsole.log(outputItem.id);", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.evals.runs.outputitems.OutputItemRetrieveParams;\nimport com.openai.models.evals.runs.outputitems.OutputItemRetrieveResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n OutputItemRetrieveParams params = OutputItemRetrieveParams.builder()\n .evalId(\"eval_id\")\n .runId(\"run_id\")\n .outputItemId(\"output_item_id\")\n .build();\n OutputItemRetrieveResponse outputItem = client.evals().runs().outputItems().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\noutput_item = openai.evals.runs.output_items.retrieve(\"output_item_id\", eval_id: \"eval_id\", run_id: \"run_id\")\n\nputs(output_item)" - } - } - }, - "description": "Get an evaluation run output item by ID.\n" - } - }, - "/files": { - "get": { - "operationId": "listFiles", - "tags": [ - "Files" - ], - "summary": "List files", - "parameters": [ - { - "in": "query", - "name": "purpose", - "required": false, - "schema": { - "type": "string" - }, - "description": "Only return files with the given purpose." - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 10,000, and the default is 10,000.\n", - "required": false, - "schema": { - "type": "integer", - "default": 10000 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListFilesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List files", - "group": "files", - "returns": "A list of [File](https://platform.openai.com/docs/api-reference/files/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"file-abc123\",\n \"object\": \"file\",\n \"bytes\": 175,\n \"created_at\": 1613677385,\n \"expires_at\": 1677614202,\n \"filename\": \"salesOverview.pdf\",\n \"purpose\": \"assistants\",\n },\n {\n \"id\": \"file-abc456\",\n \"object\": \"file\",\n \"bytes\": 140,\n \"created_at\": 1613779121,\n \"expires_at\": 1677614202,\n \"filename\": \"puppy.jsonl\",\n \"purpose\": \"fine-tune\",\n }\n ],\n \"first_id\": \"file-abc123\",\n \"last_id\": \"file-abc456\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/files \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.files.list()\npage = page.data[0]\nprint(page)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const fileObject of client.files.list()) {\n console.log(fileObject);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Files.List(context.TODO(), openai.FileListParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.files.FileListPage;\nimport com.openai.models.files.FileListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileListPage page = client.files().list();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.files.list\n\nputs(page)" - } - } - }, - "description": "Returns a list of files." - }, - "post": { - "operationId": "createFile", - "tags": [ - "Files" - ], - "summary": "Upload file", - "requestBody": { - "required": true, - "content": { - "multipart/form-data": { - "schema": { - "$ref": "#/components/schemas/CreateFileRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/OpenAIFile" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Upload file", - "group": "files", - "returns": "The uploaded [File](https://platform.openai.com/docs/api-reference/files/object) object.", - "examples": { - "response": "{\n \"id\": \"file-abc123\",\n \"object\": \"file\",\n \"bytes\": 120000,\n \"created_at\": 1677610602,\n \"expires_at\": 1677614202,\n \"filename\": \"mydata.jsonl\",\n \"purpose\": \"fine-tune\",\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/files \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -F purpose=\"fine-tune\" \\\n -F file=\"@mydata.jsonl\"\n -F expires_after[anchor]=\"created_at\"\n -F expires_after[seconds]=3600\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfile_object = client.files.create(\n file=b\"raw file contents\",\n purpose=\"assistants\",\n)\nprint(file_object.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fileObject = await client.files.create({\n file: fs.createReadStream('fine-tune.jsonl'),\n purpose: 'assistants',\n});\n\nconsole.log(fileObject.id);", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fileObject, err := client.Files.New(context.TODO(), openai.FileNewParams{\n File: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n Purpose: openai.FilePurposeAssistants,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fileObject.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.files.FileCreateParams;\nimport com.openai.models.files.FileObject;\nimport com.openai.models.files.FilePurpose;\nimport java.io.ByteArrayInputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileCreateParams params = FileCreateParams.builder()\n .file(ByteArrayInputStream(\"some content\".getBytes()))\n .purpose(FilePurpose.ASSISTANTS)\n .build();\n FileObject fileObject = client.files().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfile_object = openai.files.create(file: Pathname(__FILE__), purpose: :assistants)\n\nputs(file_object)" - } - } - }, - "description": "Upload a file that can be used across various endpoints. Individual files can be up to 512 MB, and the size of all files uploaded by one organization can be up to 1 TB.\n\nThe Assistants API supports files up to 2 million tokens and of specific file types. See the [Assistants Tools guide](https://platform.openai.com/docs/assistants/tools) for details.\n\nThe Fine-tuning API only supports `.jsonl` files. The input also has certain required formats for fine-tuning [chat](https://platform.openai.com/docs/api-reference/fine-tuning/chat-input) or [completions](https://platform.openai.com/docs/api-reference/fine-tuning/completions-input) models.\n\nThe Batch API only supports `.jsonl` files up to 200 MB in size. The input also has a specific required [format](https://platform.openai.com/docs/api-reference/batch/request-input).\n\nPlease [contact us](https://help.openai.com/) if you need to increase these storage limits.\n" - } - }, - "/files/{file_id}": { - "delete": { - "operationId": "deleteFile", - "tags": [ - "Files" - ], - "summary": "Delete file", - "parameters": [ - { - "in": "path", - "name": "file_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the file to use for this request." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeleteFileResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete file", - "group": "files", - "returns": "Deletion status.", - "examples": { - "response": "{\n \"id\": \"file-abc123\",\n \"object\": \"file\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/files/file-abc123 \\\n -X DELETE \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfile_deleted = client.files.delete(\n \"file_id\",\n)\nprint(file_deleted.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fileDeleted = await client.files.delete('file_id');\n\nconsole.log(fileDeleted.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fileDeleted, err := client.Files.Delete(context.TODO(), \"file_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fileDeleted.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.files.FileDeleteParams;\nimport com.openai.models.files.FileDeleted;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileDeleted fileDeleted = client.files().delete(\"file_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfile_deleted = openai.files.delete(\"file_id\")\n\nputs(file_deleted)" - } - } - }, - "description": "Delete a file." - }, - "get": { - "operationId": "retrieveFile", - "tags": [ - "Files" - ], - "summary": "Retrieve file", - "parameters": [ - { - "in": "path", - "name": "file_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the file to use for this request." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/OpenAIFile" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve file", - "group": "files", - "returns": "The [File](https://platform.openai.com/docs/api-reference/files/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"file-abc123\",\n \"object\": \"file\",\n \"bytes\": 120000,\n \"created_at\": 1677610602,\n \"expires_at\": 1677614202,\n \"filename\": \"mydata.jsonl\",\n \"purpose\": \"fine-tune\",\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/files/file-abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfile_object = client.files.retrieve(\n \"file_id\",\n)\nprint(file_object.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fileObject = await client.files.retrieve('file_id');\n\nconsole.log(fileObject.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fileObject, err := client.Files.Get(context.TODO(), \"file_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fileObject.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.files.FileObject;\nimport com.openai.models.files.FileRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileObject fileObject = client.files().retrieve(\"file_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfile_object = openai.files.retrieve(\"file_id\")\n\nputs(file_object)" - } - } - }, - "description": "Returns information about a specific file." - } - }, - "/files/{file_id}/content": { - "get": { - "operationId": "downloadFile", - "tags": [ - "Files" - ], - "summary": "Retrieve file content", - "parameters": [ - { - "in": "path", - "name": "file_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the file to use for this request." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "type": "string" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve file content", - "group": "files", - "returns": "The file content.", - "examples": { - "response": "", - "request": { - "curl": "curl https://api.openai.com/v1/files/file-abc123/content \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" > file.jsonl\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.files.content(\n \"file_id\",\n)\nprint(response)\ncontent = response.read()\nprint(content)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.files.content('file_id');\n\nconsole.log(response);\n\nconst content = await response.blob();\nconsole.log(content);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Files.Content(context.TODO(), \"file_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.core.http.HttpResponse;\nimport com.openai.models.files.FileContentParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n HttpResponse response = client.files().content(\"file_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.files.content(\"file_id\")\n\nputs(response)" - } - } - }, - "description": "Returns the contents of the specified file." - } - }, - "/fine_tuning/alpha/graders/run": { - "post": { - "operationId": "runGrader", - "tags": [ - "Fine-tuning" - ], - "summary": "Run grader", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RunGraderRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RunGraderResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Run grader", - "beta": true, - "group": "graders", - "returns": "The results from the grader run.", - "examples": { - "response": "{\n \"reward\": 1.0,\n \"metadata\": {\n \"name\": \"Example score model grader\",\n \"type\": \"score_model\",\n \"errors\": {\n \"formula_parse_error\": false,\n \"sample_parse_error\": false,\n \"truncated_observation_error\": false,\n \"unresponsive_reward_error\": false,\n \"invalid_variable_error\": false,\n \"other_error\": false,\n \"python_grader_server_error\": false,\n \"python_grader_server_error_type\": null,\n \"python_grader_runtime_error\": false,\n \"python_grader_runtime_error_details\": null,\n \"model_grader_server_error\": false,\n \"model_grader_refusal_error\": false,\n \"model_grader_parse_error\": false,\n \"model_grader_server_error_details\": null\n },\n \"execution_time\": 4.365238428115845,\n \"scores\": {},\n \"token_usage\": {\n \"prompt_tokens\": 190,\n \"total_tokens\": 324,\n \"completion_tokens\": 134,\n \"cached_tokens\": 0\n },\n \"sampled_model_name\": \"gpt-4o-2024-08-06\"\n },\n \"sub_rewards\": {},\n \"model_grader_token_usage_per_model\": {\n \"gpt-4o-2024-08-06\": {\n \"prompt_tokens\": 190,\n \"total_tokens\": 324,\n \"completion_tokens\": 134,\n \"cached_tokens\": 0\n }\n }\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/fine_tuning/alpha/graders/run \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"grader\": {\n \"type\": \"score_model\",\n \"name\": \"Example score model grader\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": \"Score how close the reference answer is to the model answer. Score 1.0 if they are the same and 0.0 if they are different. Return just a floating point score\\n\\nReference answer: {{item.reference_answer}}\\n\\nModel answer: {{sample.output_text}}\"\n }\n ],\n \"model\": \"gpt-4o-2024-08-06\",\n \"sampling_params\": {\n \"temperature\": 1,\n \"top_p\": 1,\n \"seed\": 42\n }\n },\n \"item\": {\n \"reference_answer\": \"fuzzy wuzzy was a bear\"\n },\n \"model_sample\": \"fuzzy wuzzy was a bear\"\n }'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.fineTuning.alpha.graders.run({\n grader: { input: 'input', name: 'name', operation: 'eq', reference: 'reference', type: 'string_check' },\n model_sample: 'model_sample',\n});\n\nconsole.log(response.metadata);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.fine_tuning.alpha.graders.run(\n grader={\n \"input\": \"input\",\n \"name\": \"name\",\n \"operation\": \"eq\",\n \"reference\": \"reference\",\n \"type\": \"string_check\",\n },\n model_sample=\"model_sample\",\n)\nprint(response.metadata)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.FineTuning.Alpha.Graders.Run(context.TODO(), openai.FineTuningAlphaGraderRunParams{\n Grader: openai.FineTuningAlphaGraderRunParamsGraderUnion{\n OfStringCheck: &openai.StringCheckGraderParam{\n Input: \"input\",\n Name: \"name\",\n Operation: openai.StringCheckGraderOperationEq,\n Reference: \"reference\",\n },\n },\n ModelSample: \"model_sample\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.Metadata)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.alpha.graders.GraderRunParams;\nimport com.openai.models.finetuning.alpha.graders.GraderRunResponse;\nimport com.openai.models.graders.gradermodels.StringCheckGrader;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n GraderRunParams params = GraderRunParams.builder()\n .grader(StringCheckGrader.builder()\n .input(\"input\")\n .name(\"name\")\n .operation(StringCheckGrader.Operation.EQ)\n .reference(\"reference\")\n .build())\n .modelSample(\"model_sample\")\n .build();\n GraderRunResponse response = client.fineTuning().alpha().graders().run(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.fine_tuning.alpha.graders.run(\n grader: {input: \"input\", name: \"name\", operation: :eq, reference: \"reference\", type: :string_check},\n model_sample: \"model_sample\"\n)\n\nputs(response)" - } - } - }, - "description": "Run a grader.\n" - } - }, - "/fine_tuning/alpha/graders/validate": { - "post": { - "operationId": "validateGrader", - "tags": [ - "Fine-tuning" - ], - "summary": "Validate grader", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ValidateGraderRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ValidateGraderResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Validate grader", - "beta": true, - "group": "graders", - "returns": "The validated grader object.", - "examples": { - "response": "{\n \"grader\": {\n \"type\": \"string_check\",\n \"name\": \"Example string check grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\"\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/alpha/graders/validate \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"grader\": {\n \"type\": \"string_check\",\n \"name\": \"Example string check grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\"\n }\n }'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.fineTuning.alpha.graders.validate({\n grader: { input: 'input', name: 'name', operation: 'eq', reference: 'reference', type: 'string_check' },\n});\n\nconsole.log(response.grader);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.fine_tuning.alpha.graders.validate(\n grader={\n \"input\": \"input\",\n \"name\": \"name\",\n \"operation\": \"eq\",\n \"reference\": \"reference\",\n \"type\": \"string_check\",\n },\n)\nprint(response.grader)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.FineTuning.Alpha.Graders.Validate(context.TODO(), openai.FineTuningAlphaGraderValidateParams{\n Grader: openai.FineTuningAlphaGraderValidateParamsGraderUnion{\n OfStringCheckGrader: &openai.StringCheckGraderParam{\n Input: \"input\",\n Name: \"name\",\n Operation: openai.StringCheckGraderOperationEq,\n Reference: \"reference\",\n },\n },\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.Grader)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.alpha.graders.GraderValidateParams;\nimport com.openai.models.finetuning.alpha.graders.GraderValidateResponse;\nimport com.openai.models.graders.gradermodels.StringCheckGrader;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n GraderValidateParams params = GraderValidateParams.builder()\n .grader(StringCheckGrader.builder()\n .input(\"input\")\n .name(\"name\")\n .operation(StringCheckGrader.Operation.EQ)\n .reference(\"reference\")\n .build())\n .build();\n GraderValidateResponse response = client.fineTuning().alpha().graders().validate(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.fine_tuning.alpha.graders.validate(\n grader: {input: \"input\", name: \"name\", operation: :eq, reference: \"reference\", type: :string_check}\n)\n\nputs(response)" - } - } - }, - "description": "Validate a grader.\n" - } - }, - "/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions": { - "get": { - "operationId": "listFineTuningCheckpointPermissions", - "tags": [ - "Fine-tuning" - ], - "summary": "List checkpoint permissions", - "parameters": [ - { - "in": "path", - "name": "fine_tuned_model_checkpoint", - "required": true, - "schema": { - "type": "string", - "example": "ft-AF1WoRqd3aJAHsqc9NY7iL8F" - }, - "description": "The ID of the fine-tuned model checkpoint to get permissions for.\n" - }, - { - "name": "project_id", - "in": "query", - "description": "The ID of the project to get permissions for.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "after", - "in": "query", - "description": "Identifier for the last permission ID from the previous pagination request.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "Number of permissions to retrieve.", - "required": false, - "schema": { - "type": "integer", - "default": 10 - } - }, - { - "name": "order", - "in": "query", - "description": "The order in which to retrieve permissions.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "ascending", - "descending" - ], - "default": "descending" - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListFineTuningCheckpointPermissionResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List checkpoint permissions", - "group": "fine-tuning", - "returns": "A list of fine-tuned model checkpoint [permission objects](https://platform.openai.com/docs/api-reference/fine-tuning/permission-object) for a fine-tuned model checkpoint.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"checkpoint.permission\",\n \"id\": \"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n \"created_at\": 1721764867,\n \"project_id\": \"proj_abGMw1llN8IrBb6SvvY5A1iH\"\n },\n {\n \"object\": \"checkpoint.permission\",\n \"id\": \"cp_enQCFmOTGj3syEpYVhBRLTSy\",\n \"created_at\": 1721764800,\n \"project_id\": \"proj_iqGMw1llN8IrBb6SvvY5A1oF\"\n },\n ],\n \"first_id\": \"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n \"last_id\": \"cp_enQCFmOTGj3syEpYVhBRLTSy\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/checkpoints/ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd/permissions \\ -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst permission = await client.fineTuning.checkpoints.permissions.retrieve('ft-AF1WoRqd3aJAHsqc9NY7iL8F');\n\nconsole.log(permission.first_id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npermission = client.fine_tuning.checkpoints.permissions.retrieve(\n fine_tuned_model_checkpoint=\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n)\nprint(permission.first_id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n permission, err := client.FineTuning.Checkpoints.Permissions.Get(\n context.TODO(),\n \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n openai.FineTuningCheckpointPermissionGetParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", permission.FirstID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.checkpoints.permissions.PermissionRetrieveParams;\nimport com.openai.models.finetuning.checkpoints.permissions.PermissionRetrieveResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n PermissionRetrieveResponse permission = client.fineTuning().checkpoints().permissions().retrieve(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npermission = openai.fine_tuning.checkpoints.permissions.retrieve(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n\nputs(permission)" - } - } - }, - "description": "**NOTE:** This endpoint requires an [admin API key](../admin-api-keys).\n\nOrganization owners can use this endpoint to view all permissions for a fine-tuned model checkpoint.\n" - }, - "post": { - "operationId": "createFineTuningCheckpointPermission", - "tags": [ - "Fine-tuning" - ], - "summary": "Create checkpoint permissions", - "parameters": [ - { - "in": "path", - "name": "fine_tuned_model_checkpoint", - "required": true, - "schema": { - "type": "string", - "example": "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd" - }, - "description": "The ID of the fine-tuned model checkpoint to create a permission for.\n" - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateFineTuningCheckpointPermissionRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListFineTuningCheckpointPermissionResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create checkpoint permissions", - "group": "fine-tuning", - "returns": "A list of fine-tuned model checkpoint [permission objects](https://platform.openai.com/docs/api-reference/fine-tuning/permission-object) for a fine-tuned model checkpoint.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"checkpoint.permission\",\n \"id\": \"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n \"created_at\": 1721764867,\n \"project_id\": \"proj_abGMw1llN8IrBb6SvvY5A1iH\"\n }\n ],\n \"first_id\": \"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n \"last_id\": \"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/checkpoints/ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd/permissions \\ -H \"Authorization: Bearer $OPENAI_API_KEY\"\n -d '{\"project_ids\": [\"proj_abGMw1llN8IrBb6SvvY5A1iH\"]}'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const permissionCreateResponse of client.fineTuning.checkpoints.permissions.create(\n 'ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd',\n { project_ids: ['string'] },\n)) {\n console.log(permissionCreateResponse.id);\n}", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.fine_tuning.checkpoints.permissions.create(\n fine_tuned_model_checkpoint=\"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd\",\n project_ids=[\"string\"],\n)\npage = page.data[0]\nprint(page.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.FineTuning.Checkpoints.Permissions.New(\n context.TODO(),\n \"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd\",\n openai.FineTuningCheckpointPermissionNewParams{\n ProjectIDs: []string{\"string\"},\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.checkpoints.permissions.PermissionCreatePage;\nimport com.openai.models.finetuning.checkpoints.permissions.PermissionCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n PermissionCreateParams params = PermissionCreateParams.builder()\n .fineTunedModelCheckpoint(\"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd\")\n .addProjectId(\"string\")\n .build();\n PermissionCreatePage page = client.fineTuning().checkpoints().permissions().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.fine_tuning.checkpoints.permissions.create(\n \"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd\",\n project_ids: [\"string\"]\n)\n\nputs(page)" - } - } - }, - "description": "**NOTE:** Calling this endpoint requires an [admin API key](../admin-api-keys).\n\nThis enables organization owners to share fine-tuned models with other projects in their organization.\n" - } - }, - "/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions/{permission_id}": { - "delete": { - "operationId": "deleteFineTuningCheckpointPermission", - "tags": [ - "Fine-tuning" - ], - "summary": "Delete checkpoint permission", - "parameters": [ - { - "in": "path", - "name": "fine_tuned_model_checkpoint", - "required": true, - "schema": { - "type": "string", - "example": "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd" - }, - "description": "The ID of the fine-tuned model checkpoint to delete a permission for.\n" - }, - { - "in": "path", - "name": "permission_id", - "required": true, - "schema": { - "type": "string", - "example": "cp_zc4Q7MP6XxulcVzj4MZdwsAB" - }, - "description": "The ID of the fine-tuned model checkpoint permission to delete.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeleteFineTuningCheckpointPermissionResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete checkpoint permission", - "group": "fine-tuning", - "returns": "The deletion status of the fine-tuned model checkpoint [permission object](https://platform.openai.com/docs/api-reference/fine-tuning/permission-object).", - "examples": { - "response": "{\n \"object\": \"checkpoint.permission\",\n \"id\": \"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/checkpoints/ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd/permissions/cp_zc4Q7MP6XxulcVzj4MZdwsAB \\ -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst permission = await client.fineTuning.checkpoints.permissions.delete('cp_zc4Q7MP6XxulcVzj4MZdwsAB', { fine_tuned_model_checkpoint: 'ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd',\n});\n\nconsole.log(permission.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npermission = client.fine_tuning.checkpoints.permissions.delete(\n permission_id=\"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n fine_tuned_model_checkpoint=\"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd\",\n)\nprint(permission.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n permission, err := client.FineTuning.Checkpoints.Permissions.Delete(\n context.TODO(),\n \"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd\",\n \"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", permission.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteParams;\nimport com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n PermissionDeleteParams params = PermissionDeleteParams.builder()\n .fineTunedModelCheckpoint(\"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd\")\n .permissionId(\"cp_zc4Q7MP6XxulcVzj4MZdwsAB\")\n .build();\n PermissionDeleteResponse permission = client.fineTuning().checkpoints().permissions().delete(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npermission = openai.fine_tuning.checkpoints.permissions.delete(\n \"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n fine_tuned_model_checkpoint: \"ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd\"\n)\n\nputs(permission)" - } - } - }, - "description": "**NOTE:** This endpoint requires an [admin API key](../admin-api-keys).\n\nOrganization owners can use this endpoint to delete a permission for a fine-tuned model checkpoint.\n" - } - }, - "/fine_tuning/jobs": { - "post": { - "operationId": "createFineTuningJob", - "tags": [ - "Fine-tuning" - ], - "summary": "Create fine-tuning job", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateFineTuningJobRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/FineTuningJob" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create fine-tuning job", - "group": "fine-tuning", - "returns": "A [fine-tuning.job](https://platform.openai.com/docs/api-reference/fine-tuning/object) object.", - "examples": [ - { - "title": "Default", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"training_file\": \"file-BK7bzQj3FfZFXr7DbL6xJwfo\",\n \"model\": \"gpt-4o-mini\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.create(\n model=\"gpt-4o-mini\",\n training_file=\"file-abc123\",\n)\nprint(fine_tuning_job.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.create({\n model: 'gpt-4o-mini',\n training_file: 'file-abc123',\n});\n\nconsole.log(fineTuningJob.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{\n Model: openai.FineTuningJobNewParamsModelBabbage002,\n TrainingFile: \"file-abc123\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n JobCreateParams params = JobCreateParams.builder()\n .model(JobCreateParams.Model.BABBAGE_002)\n .trainingFile(\"file-abc123\")\n .build();\n FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.create(model: :\"babbage-002\", training_file: \"file-abc123\")\n\nputs(fine_tuning_job)" - }, - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"created_at\": 1721764800,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-123\",\n \"result_files\": [],\n \"status\": \"queued\",\n \"validation_file\": null,\n \"training_file\": \"file-abc123\",\n \"method\": {\n \"type\": \"supervised\",\n \"supervised\": {\n \"hyperparameters\": {\n \"batch_size\": \"auto\",\n \"learning_rate_multiplier\": \"auto\",\n \"n_epochs\": \"auto\",\n }\n }\n },\n \"metadata\": null\n}\n" - }, - { - "title": "Epochs", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"training_file\": \"file-abc123\",\n \"model\": \"gpt-4o-mini\",\n \"method\": {\n \"type\": \"supervised\",\n \"supervised\": {\n \"hyperparameters\": {\n \"n_epochs\": 2\n }\n }\n }\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.create(\n model=\"gpt-4o-mini\",\n training_file=\"file-abc123\",\n)\nprint(fine_tuning_job.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.create({\n model: 'gpt-4o-mini',\n training_file: 'file-abc123',\n});\n\nconsole.log(fineTuningJob.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{\n Model: openai.FineTuningJobNewParamsModelBabbage002,\n TrainingFile: \"file-abc123\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n JobCreateParams params = JobCreateParams.builder()\n .model(JobCreateParams.Model.BABBAGE_002)\n .trainingFile(\"file-abc123\")\n .build();\n FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.create(model: :\"babbage-002\", training_file: \"file-abc123\")\n\nputs(fine_tuning_job)" - }, - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"gpt-4o-mini\",\n \"created_at\": 1721764800,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-123\",\n \"result_files\": [],\n \"status\": \"queued\",\n \"validation_file\": null,\n \"training_file\": \"file-abc123\",\n \"hyperparameters\": {\n \"batch_size\": \"auto\",\n \"learning_rate_multiplier\": \"auto\",\n \"n_epochs\": 2\n },\n \"method\": {\n \"type\": \"supervised\",\n \"supervised\": {\n \"hyperparameters\": {\n \"batch_size\": \"auto\",\n \"learning_rate_multiplier\": \"auto\",\n \"n_epochs\": 2\n }\n }\n },\n \"metadata\": null,\n \"error\": {\n \"code\": null,\n \"message\": null,\n \"param\": null\n },\n \"finished_at\": null,\n \"seed\": 683058546,\n \"trained_tokens\": null,\n \"estimated_finish\": null,\n \"integrations\": [],\n \"user_provided_suffix\": null,\n \"usage_metrics\": null,\n \"shared_with_openai\": false\n}\n" - }, - { - "title": "DPO", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"training_file\": \"file-abc123\",\n \"validation_file\": \"file-abc123\",\n \"model\": \"gpt-4o-mini\",\n \"method\": {\n \"type\": \"dpo\",\n \"dpo\": {\n \"hyperparameters\": {\n \"beta\": 0.1\n }\n }\n }\n }'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.create({\n model: 'gpt-4o-mini',\n training_file: 'file-abc123',\n});\n\nconsole.log(fineTuningJob.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.create(\n model=\"gpt-4o-mini\",\n training_file=\"file-abc123\",\n)\nprint(fine_tuning_job.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{\n Model: openai.FineTuningJobNewParamsModelBabbage002,\n TrainingFile: \"file-abc123\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n JobCreateParams params = JobCreateParams.builder()\n .model(JobCreateParams.Model.BABBAGE_002)\n .trainingFile(\"file-abc123\")\n .build();\n FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.create(model: :\"babbage-002\", training_file: \"file-abc123\")\n\nputs(fine_tuning_job)" - }, - "python": "from openai import OpenAI\nfrom openai.types.fine_tuning import DpoMethod, DpoHyperparameters\n\nclient = OpenAI()\n\nclient.fine_tuning.jobs.create(\n training_file=\"file-abc\",\n validation_file=\"file-123\",\n model=\"gpt-4o-mini\",\n method={\n \"type\": \"dpo\",\n \"dpo\": DpoMethod(\n hyperparameters=DpoHyperparameters(beta=0.1)\n )\n }\n)\n", - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc\",\n \"model\": \"gpt-4o-mini\",\n \"created_at\": 1746130590,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-abc\",\n \"result_files\": [],\n \"status\": \"queued\",\n \"validation_file\": \"file-123\",\n \"training_file\": \"file-abc\",\n \"method\": {\n \"type\": \"dpo\",\n \"dpo\": {\n \"hyperparameters\": {\n \"beta\": 0.1,\n \"batch_size\": \"auto\",\n \"learning_rate_multiplier\": \"auto\",\n \"n_epochs\": \"auto\"\n }\n }\n },\n \"metadata\": null,\n \"error\": {\n \"code\": null,\n \"message\": null,\n \"param\": null\n },\n \"finished_at\": null,\n \"hyperparameters\": null,\n \"seed\": 1036326793,\n \"estimated_finish\": null,\n \"integrations\": [],\n \"user_provided_suffix\": null,\n \"usage_metrics\": null,\n \"shared_with_openai\": false\n}\n" - }, - { - "title": "Reinforcement", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"training_file\": \"file-abc\",\n \"validation_file\": \"file-123\",\n \"model\": \"o4-mini\",\n \"method\": {\n \"type\": \"reinforcement\",\n \"reinforcement\": {\n \"grader\": {\n \"type\": \"string_check\",\n \"name\": \"Example string check grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\"\n },\n \"hyperparameters\": {\n \"reasoning_effort\": \"medium\"\n }\n }\n }\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.create(\n model=\"gpt-4o-mini\",\n training_file=\"file-abc123\",\n)\nprint(fine_tuning_job.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.create({\n model: 'gpt-4o-mini',\n training_file: 'file-abc123',\n});\n\nconsole.log(fineTuningJob.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{\n Model: openai.FineTuningJobNewParamsModelBabbage002,\n TrainingFile: \"file-abc123\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n JobCreateParams params = JobCreateParams.builder()\n .model(JobCreateParams.Model.BABBAGE_002)\n .trainingFile(\"file-abc123\")\n .build();\n FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.create(model: :\"babbage-002\", training_file: \"file-abc123\")\n\nputs(fine_tuning_job)" - }, - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"o4-mini\",\n \"created_at\": 1721764800,\n \"finished_at\": null,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-123\",\n \"result_files\": [],\n \"status\": \"validating_files\",\n \"validation_file\": \"file-123\",\n \"training_file\": \"file-abc\",\n \"trained_tokens\": null,\n \"error\": {},\n \"user_provided_suffix\": null,\n \"seed\": 950189191,\n \"estimated_finish\": null,\n \"integrations\": [],\n \"method\": {\n \"type\": \"reinforcement\",\n \"reinforcement\": {\n \"hyperparameters\": {\n \"batch_size\": \"auto\",\n \"learning_rate_multiplier\": \"auto\",\n \"n_epochs\": \"auto\",\n \"eval_interval\": \"auto\",\n \"eval_samples\": \"auto\",\n \"compute_multiplier\": \"auto\",\n \"reasoning_effort\": \"medium\"\n },\n \"grader\": {\n \"type\": \"string_check\",\n \"name\": \"Example string check grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\"\n },\n \"response_format\": null\n }\n },\n \"metadata\": null,\n \"usage_metrics\": null,\n \"shared_with_openai\": false\n}\n" - }, - { - "title": "Validation file", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"training_file\": \"file-abc123\",\n \"validation_file\": \"file-abc123\",\n \"model\": \"gpt-4o-mini\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.create(\n model=\"gpt-4o-mini\",\n training_file=\"file-abc123\",\n)\nprint(fine_tuning_job.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.create({\n model: 'gpt-4o-mini',\n training_file: 'file-abc123',\n});\n\nconsole.log(fineTuningJob.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{\n Model: openai.FineTuningJobNewParamsModelBabbage002,\n TrainingFile: \"file-abc123\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n JobCreateParams params = JobCreateParams.builder()\n .model(JobCreateParams.Model.BABBAGE_002)\n .trainingFile(\"file-abc123\")\n .build();\n FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.create(model: :\"babbage-002\", training_file: \"file-abc123\")\n\nputs(fine_tuning_job)" - }, - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"created_at\": 1721764800,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-123\",\n \"result_files\": [],\n \"status\": \"queued\",\n \"validation_file\": \"file-abc123\",\n \"training_file\": \"file-abc123\",\n \"method\": {\n \"type\": \"supervised\",\n \"supervised\": {\n \"hyperparameters\": {\n \"batch_size\": \"auto\",\n \"learning_rate_multiplier\": \"auto\",\n \"n_epochs\": \"auto\",\n }\n }\n },\n \"metadata\": null\n}\n" - }, - { - "title": "W&B Integration", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"training_file\": \"file-abc123\",\n \"validation_file\": \"file-abc123\",\n \"model\": \"gpt-4o-mini\",\n \"integrations\": [\n {\n \"type\": \"wandb\",\n \"wandb\": {\n \"project\": \"my-wandb-project\",\n \"name\": \"ft-run-display-name\"\n \"tags\": [\n \"first-experiment\", \"v2\"\n ]\n }\n }\n ]\n }'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.create({\n model: 'gpt-4o-mini',\n training_file: 'file-abc123',\n});\n\nconsole.log(fineTuningJob.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.create(\n model=\"gpt-4o-mini\",\n training_file=\"file-abc123\",\n)\nprint(fine_tuning_job.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{\n Model: openai.FineTuningJobNewParamsModelBabbage002,\n TrainingFile: \"file-abc123\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n JobCreateParams params = JobCreateParams.builder()\n .model(JobCreateParams.Model.BABBAGE_002)\n .trainingFile(\"file-abc123\")\n .build();\n FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.create(model: :\"babbage-002\", training_file: \"file-abc123\")\n\nputs(fine_tuning_job)" - }, - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"created_at\": 1721764800,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-123\",\n \"result_files\": [],\n \"status\": \"queued\",\n \"validation_file\": \"file-abc123\",\n \"training_file\": \"file-abc123\",\n \"integrations\": [\n {\n \"type\": \"wandb\",\n \"wandb\": {\n \"project\": \"my-wandb-project\",\n \"entity\": None,\n \"run_id\": \"ftjob-abc123\"\n }\n }\n ],\n \"method\": {\n \"type\": \"supervised\",\n \"supervised\": {\n \"hyperparameters\": {\n \"batch_size\": \"auto\",\n \"learning_rate_multiplier\": \"auto\",\n \"n_epochs\": \"auto\",\n }\n }\n },\n \"metadata\": null\n}\n" - } - ] - }, - "description": "Creates a fine-tuning job which begins the process of creating a new model from a given dataset.\n\nResponse includes details of the enqueued job including job status and the name of the fine-tuned models once complete.\n\n[Learn more about fine-tuning](https://platform.openai.com/docs/guides/model-optimization)\n" - }, - "get": { - "operationId": "listPaginatedFineTuningJobs", - "tags": [ - "Fine-tuning" - ], - "summary": "List fine-tuning jobs", - "parameters": [ - { - "name": "after", - "in": "query", - "description": "Identifier for the last job from the previous pagination request.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "Number of fine-tuning jobs to retrieve.", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "in": "query", - "name": "metadata", - "required": false, - "schema": { - "type": "object", - "nullable": true, - "additionalProperties": { - "type": "string" - } - }, - "style": "deepObject", - "explode": true, - "description": "Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Alternatively, set `metadata=null` to indicate no metadata.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListPaginatedFineTuningJobsResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List fine-tuning jobs", - "group": "fine-tuning", - "returns": "A list of paginated [fine-tuning job](https://platform.openai.com/docs/api-reference/fine-tuning/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"created_at\": 1721764800,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-123\",\n \"result_files\": [],\n \"status\": \"queued\",\n \"validation_file\": null,\n \"training_file\": \"file-abc123\",\n \"metadata\": {\n \"key\": \"value\"\n }\n },\n { ... },\n { ... }\n ], \"has_more\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs?limit=2&metadata[key]=value \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.fine_tuning.jobs.list()\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const fineTuningJob of client.fineTuning.jobs.list()) {\n console.log(fineTuningJob.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.FineTuning.Jobs.List(context.TODO(), openai.FineTuningJobListParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.JobListPage;\nimport com.openai.models.finetuning.jobs.JobListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n JobListPage page = client.fineTuning().jobs().list();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.fine_tuning.jobs.list\n\nputs(page)" - } - } - }, - "description": "List your organization's fine-tuning jobs\n" - } - }, - "/fine_tuning/jobs/{fine_tuning_job_id}": { - "get": { - "operationId": "retrieveFineTuningJob", - "tags": [ - "Fine-tuning" - ], - "summary": "Retrieve fine-tuning job", - "parameters": [ - { - "in": "path", - "name": "fine_tuning_job_id", - "required": true, - "schema": { - "type": "string", - "example": "ft-AF1WoRqd3aJAHsqc9NY7iL8F" - }, - "description": "The ID of the fine-tuning job.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/FineTuningJob" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve fine-tuning job", - "group": "fine-tuning", - "returns": "The [fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning/object) object with the given ID.", - "examples": { - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"davinci-002\",\n \"created_at\": 1692661014,\n \"finished_at\": 1692661190,\n \"fine_tuned_model\": \"ft:davinci-002:my-org:custom_suffix:7q8mpxmy\",\n \"organization_id\": \"org-123\",\n \"result_files\": [\n \"file-abc123\"\n ],\n \"status\": \"succeeded\",\n \"validation_file\": null,\n \"training_file\": \"file-abc123\",\n \"hyperparameters\": {\n \"n_epochs\": 4,\n \"batch_size\": 1,\n \"learning_rate_multiplier\": 1.0\n },\n \"trained_tokens\": 5768,\n \"integrations\": [],\n \"seed\": 0,\n \"estimated_finish\": 0,\n \"method\": {\n \"type\": \"supervised\",\n \"supervised\": {\n \"hyperparameters\": {\n \"n_epochs\": 4,\n \"batch_size\": 1,\n \"learning_rate_multiplier\": 1.0\n }\n }\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs/ft-AF1WoRqd3aJAHsqc9NY7iL8F \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.retrieve(\n \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n)\nprint(fine_tuning_job.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.retrieve('ft-AF1WoRqd3aJAHsqc9NY7iL8F');\n\nconsole.log(fineTuningJob.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.Get(context.TODO(), \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FineTuningJob fineTuningJob = client.fineTuning().jobs().retrieve(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.retrieve(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n\nputs(fine_tuning_job)" - } - } - }, - "description": "Get info about a fine-tuning job.\n\n[Learn more about fine-tuning](https://platform.openai.com/docs/guides/model-optimization)\n" - } - }, - "/fine_tuning/jobs/{fine_tuning_job_id}/cancel": { - "post": { - "operationId": "cancelFineTuningJob", - "tags": [ - "Fine-tuning" - ], - "summary": "Cancel fine-tuning", - "parameters": [ - { - "in": "path", - "name": "fine_tuning_job_id", - "required": true, - "schema": { - "type": "string", - "example": "ft-AF1WoRqd3aJAHsqc9NY7iL8F" - }, - "description": "The ID of the fine-tuning job to cancel.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/FineTuningJob" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Cancel fine-tuning", - "group": "fine-tuning", - "returns": "The cancelled [fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning/object) object.", - "examples": { - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"created_at\": 1721764800,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-123\",\n \"result_files\": [],\n \"status\": \"cancelled\",\n \"validation_file\": \"file-abc123\",\n \"training_file\": \"file-abc123\"\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/cancel \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.cancel(\n \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n)\nprint(fine_tuning_job.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.cancel('ft-AF1WoRqd3aJAHsqc9NY7iL8F');\n\nconsole.log(fineTuningJob.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.Cancel(context.TODO(), \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobCancelParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FineTuningJob fineTuningJob = client.fineTuning().jobs().cancel(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.cancel(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n\nputs(fine_tuning_job)" - } - } - }, - "description": "Immediately cancel a fine-tune job.\n" - } - }, - "/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints": { - "get": { - "operationId": "listFineTuningJobCheckpoints", - "tags": [ - "Fine-tuning" - ], - "summary": "List fine-tuning checkpoints", - "parameters": [ - { - "in": "path", - "name": "fine_tuning_job_id", - "required": true, - "schema": { - "type": "string", - "example": "ft-AF1WoRqd3aJAHsqc9NY7iL8F" - }, - "description": "The ID of the fine-tuning job to get checkpoints for.\n" - }, - { - "name": "after", - "in": "query", - "description": "Identifier for the last checkpoint ID from the previous pagination request.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "Number of checkpoints to retrieve.", - "required": false, - "schema": { - "type": "integer", - "default": 10 - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListFineTuningJobCheckpointsResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List fine-tuning checkpoints", - "group": "fine-tuning", - "returns": "A list of fine-tuning [checkpoint objects](https://platform.openai.com/docs/api-reference/fine-tuning/checkpoint-object) for a fine-tuning job.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"fine_tuning.job.checkpoint\",\n \"id\": \"ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB\",\n \"created_at\": 1721764867,\n \"fine_tuned_model_checkpoint\": \"ft:gpt-4o-mini-2024-07-18:my-org:custom-suffix:96olL566:ckpt-step-2000\",\n \"metrics\": {\n \"full_valid_loss\": 0.134,\n \"full_valid_mean_token_accuracy\": 0.874\n },\n \"fine_tuning_job_id\": \"ftjob-abc123\",\n \"step_number\": 2000\n },\n {\n \"object\": \"fine_tuning.job.checkpoint\",\n \"id\": \"ftckpt_enQCFmOTGj3syEpYVhBRLTSy\",\n \"created_at\": 1721764800,\n \"fine_tuned_model_checkpoint\": \"ft:gpt-4o-mini-2024-07-18:my-org:custom-suffix:7q8mpxmy:ckpt-step-1000\",\n \"metrics\": {\n \"full_valid_loss\": 0.167,\n \"full_valid_mean_token_accuracy\": 0.781\n },\n \"fine_tuning_job_id\": \"ftjob-abc123\",\n \"step_number\": 1000\n }\n ],\n \"first_id\": \"ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB\",\n \"last_id\": \"ftckpt_enQCFmOTGj3syEpYVhBRLTSy\",\n \"has_more\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/checkpoints \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const fineTuningJobCheckpoint of client.fineTuning.jobs.checkpoints.list(\n 'ft-AF1WoRqd3aJAHsqc9NY7iL8F',\n)) {\n console.log(fineTuningJobCheckpoint.id);\n}", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.fine_tuning.jobs.checkpoints.list(\n fine_tuning_job_id=\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n)\npage = page.data[0]\nprint(page.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.FineTuning.Jobs.Checkpoints.List(\n context.TODO(),\n \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n openai.FineTuningJobCheckpointListParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.checkpoints.CheckpointListPage;\nimport com.openai.models.finetuning.jobs.checkpoints.CheckpointListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n CheckpointListPage page = client.fineTuning().jobs().checkpoints().list(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.fine_tuning.jobs.checkpoints.list(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n\nputs(page)" - } - } - }, - "description": "List checkpoints for a fine-tuning job.\n" - } - }, - "/fine_tuning/jobs/{fine_tuning_job_id}/events": { - "get": { - "operationId": "listFineTuningEvents", - "tags": [ - "Fine-tuning" - ], - "summary": "List fine-tuning events", - "parameters": [ - { - "in": "path", - "name": "fine_tuning_job_id", - "required": true, - "schema": { - "type": "string", - "example": "ft-AF1WoRqd3aJAHsqc9NY7iL8F" - }, - "description": "The ID of the fine-tuning job to get events for.\n" - }, - { - "name": "after", - "in": "query", - "description": "Identifier for the last event from the previous pagination request.", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "Number of events to retrieve.", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListFineTuningJobEventsResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List fine-tuning events", - "group": "fine-tuning", - "returns": "A list of fine-tuning event objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"fine_tuning.job.event\",\n \"id\": \"ft-event-ddTJfwuMVpfLXseO0Am0Gqjm\",\n \"created_at\": 1721764800,\n \"level\": \"info\",\n \"message\": \"Fine tuning job successfully completed\",\n \"data\": null,\n \"type\": \"message\"\n },\n {\n \"object\": \"fine_tuning.job.event\",\n \"id\": \"ft-event-tyiGuB72evQncpH87xe505Sv\",\n \"created_at\": 1721764800,\n \"level\": \"info\",\n \"message\": \"New fine-tuned model created: ft:gpt-4o-mini:openai::7p4lURel\",\n \"data\": null,\n \"type\": \"message\"\n }\n ],\n \"has_more\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/events \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.fine_tuning.jobs.list_events(\n fine_tuning_job_id=\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n)\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const fineTuningJobEvent of client.fineTuning.jobs.listEvents('ft-AF1WoRqd3aJAHsqc9NY7iL8F')) { console.log(fineTuningJobEvent.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.FineTuning.Jobs.ListEvents(\n context.TODO(),\n \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n openai.FineTuningJobListEventsParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.JobListEventsPage;\nimport com.openai.models.finetuning.jobs.JobListEventsParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n JobListEventsPage page = client.fineTuning().jobs().listEvents(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.fine_tuning.jobs.list_events(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n\nputs(page)" - } - } - }, - "description": "Get status updates for a fine-tuning job.\n" - } - }, - "/fine_tuning/jobs/{fine_tuning_job_id}/pause": { - "post": { - "operationId": "pauseFineTuningJob", - "tags": [ - "Fine-tuning" - ], - "summary": "Pause fine-tuning", - "parameters": [ - { - "in": "path", - "name": "fine_tuning_job_id", - "required": true, - "schema": { - "type": "string", - "example": "ft-AF1WoRqd3aJAHsqc9NY7iL8F" - }, - "description": "The ID of the fine-tuning job to pause.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/FineTuningJob" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Pause fine-tuning", - "group": "fine-tuning", - "returns": "The paused [fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning/object) object.", - "examples": { - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"created_at\": 1721764800,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-123\",\n \"result_files\": [],\n \"status\": \"paused\",\n \"validation_file\": \"file-abc123\",\n \"training_file\": \"file-abc123\"\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/pause \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.pause(\n \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n)\nprint(fine_tuning_job.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.pause('ft-AF1WoRqd3aJAHsqc9NY7iL8F');\n\nconsole.log(fineTuningJob.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.Pause(context.TODO(), \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobPauseParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FineTuningJob fineTuningJob = client.fineTuning().jobs().pause(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.pause(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n\nputs(fine_tuning_job)" - } - } - }, - "description": "Pause a fine-tune job.\n" - } - }, - "/fine_tuning/jobs/{fine_tuning_job_id}/resume": { - "post": { - "operationId": "resumeFineTuningJob", - "tags": [ - "Fine-tuning" - ], - "summary": "Resume fine-tuning", - "parameters": [ - { - "in": "path", - "name": "fine_tuning_job_id", - "required": true, - "schema": { - "type": "string", - "example": "ft-AF1WoRqd3aJAHsqc9NY7iL8F" - }, - "description": "The ID of the fine-tuning job to resume.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/FineTuningJob" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Resume fine-tuning", - "group": "fine-tuning", - "returns": "The resumed [fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning/object) object.", - "examples": { - "response": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"created_at\": 1721764800,\n \"fine_tuned_model\": null,\n \"organization_id\": \"org-123\",\n \"result_files\": [],\n \"status\": \"queued\",\n \"validation_file\": \"file-abc123\",\n \"training_file\": \"file-abc123\"\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/resume \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nfine_tuning_job = client.fine_tuning.jobs.resume(\n \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n)\nprint(fine_tuning_job.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst fineTuningJob = await client.fineTuning.jobs.resume('ft-AF1WoRqd3aJAHsqc9NY7iL8F');\n\nconsole.log(fineTuningJob.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n fineTuningJob, err := client.FineTuning.Jobs.Resume(context.TODO(), \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", fineTuningJob.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.finetuning.jobs.FineTuningJob;\nimport com.openai.models.finetuning.jobs.JobResumeParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FineTuningJob fineTuningJob = client.fineTuning().jobs().resume(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nfine_tuning_job = openai.fine_tuning.jobs.resume(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n\nputs(fine_tuning_job)" - } - } - }, - "description": "Resume a fine-tune job.\n" - } - }, - "/images/edits": { - "post": { - "operationId": "createImageEdit", - "tags": [ - "Images" - ], - "summary": "Create image edit", - "requestBody": { - "required": true, - "content": { - "multipart/form-data": { - "schema": { - "$ref": "#/components/schemas/CreateImageEditRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ImagesResponse" - } - }, - "text/event-stream": { - "schema": { - "$ref": "#/components/schemas/ImageEditStreamEvent" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create image edit", - "group": "images", - "returns": "Returns an [image](https://platform.openai.com/docs/api-reference/images/object) object.", - "examples": [ - { - "title": "Edit image", - "request": { - "curl": "curl -s -D >(grep -i x-request-id >&2) \\\n -o >(jq -r '.data[0].b64_json' | base64 --decode > gift-basket.png) \\\n -X POST \"https://api.openai.com/v1/images/edits\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -F \"model=gpt-image-1\" \\\n -F \"image[]=@body-lotion.png\" \\\n -F \"image[]=@bath-bomb.png\" \\\n -F \"image[]=@incense-kit.png\" \\\n -F \"image[]=@soap.png\" \\\n -F 'prompt=Create a lovely gift basket with these four items in it'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nimages_response = client.images.edit(\n image=b\"raw file contents\",\n prompt=\"A cute baby sea otter wearing a beret\",\n)\nprint(images_response)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst imagesResponse = await client.images.edit({\n image: fs.createReadStream('path/to/file'),\n prompt: 'A cute baby sea otter wearing a beret',\n});\n\nconsole.log(imagesResponse);", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n imagesResponse, err := client.Images.Edit(context.TODO(), openai.ImageEditParams{\n Image: openai.ImageEditParamsImageUnion{\n OfFile: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n },\n Prompt: \"A cute baby sea otter wearing a beret\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", imagesResponse)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.images.ImageEditParams;\nimport com.openai.models.images.ImagesResponse;\nimport java.io.ByteArrayInputStream;\nimport java.io.InputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ImageEditParams params = ImageEditParams.builder()\n .image(ByteArrayInputStream(\"some content\".getBytes()))\n .prompt(\"A cute baby sea otter wearing a beret\")\n .build();\n ImagesResponse imagesResponse = client.images().edit(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nimages_response = openai.images.edit(image: Pathname(__FILE__), prompt: \"A cute baby sea otter wearing a beret\")\n\nputs(images_response)" - } - }, - { - "title": "Streaming", - "request": { - "curl": "curl -s -N -X POST \"https://api.openai.com/v1/images/edits\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -F \"model=gpt-image-1\" \\\n -F \"image[]=@body-lotion.png\" \\\n -F \"image[]=@bath-bomb.png\" \\\n -F \"image[]=@incense-kit.png\" \\\n -F \"image[]=@soap.png\" \\\n -F 'prompt=Create a lovely gift basket with these four items in it' \\\n -F \"stream=true\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nimages_response = client.images.edit(\n image=b\"raw file contents\",\n prompt=\"A cute baby sea otter wearing a beret\",\n)\nprint(images_response)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst imagesResponse = await client.images.edit({\n image: fs.createReadStream('path/to/file'),\n prompt: 'A cute baby sea otter wearing a beret',\n});\n\nconsole.log(imagesResponse);", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n imagesResponse, err := client.Images.Edit(context.TODO(), openai.ImageEditParams{\n Image: openai.ImageEditParamsImageUnion{\n OfFile: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n },\n Prompt: \"A cute baby sea otter wearing a beret\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", imagesResponse)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.images.ImageEditParams;\nimport com.openai.models.images.ImagesResponse;\nimport java.io.ByteArrayInputStream;\nimport java.io.InputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ImageEditParams params = ImageEditParams.builder()\n .image(ByteArrayInputStream(\"some content\".getBytes()))\n .prompt(\"A cute baby sea otter wearing a beret\")\n .build();\n ImagesResponse imagesResponse = client.images().edit(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nimages_response = openai.images.edit(image: Pathname(__FILE__), prompt: \"A cute baby sea otter wearing a beret\")\n\nputs(images_response)" - }, - "response": "event: image_edit.partial_image\ndata: {\"type\":\"image_edit.partial_image\",\"b64_json\":\"...\",\"partial_image_index\":0}\n\nevent: image_edit.completed\ndata: {\"type\":\"image_edit.completed\",\"b64_json\":\"...\",\"usage\":{\"total_tokens\":100,\"input_tokens\":50,\"output_tokens\":50,\"input_tokens_details\":{\"text_tokens\":10,\"image_tokens\":40}}}\n" - } - ] - }, - "description": "Creates an edited or extended image given one or more source images and a prompt. This endpoint only supports `gpt-image-1` and `dall-e-2`." - } - }, - "/images/generations": { - "post": { - "operationId": "createImage", - "tags": [ - "Images" - ], - "summary": "Create image", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateImageRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ImagesResponse" - } - }, - "text/event-stream": { - "schema": { - "$ref": "#/components/schemas/ImageGenStreamEvent" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create image", - "group": "images", - "returns": "Returns an [image](https://platform.openai.com/docs/api-reference/images/object) object.", - "examples": [ - { - "title": "Generate image", - "request": { - "curl": "curl https://api.openai.com/v1/images/generations \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-image-1\",\n \"prompt\": \"A cute baby sea otter\",\n \"n\": 1,\n \"size\": \"1024x1024\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nimages_response = client.images.generate(\n prompt=\"A cute baby sea otter\",\n)\nprint(images_response)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst imagesResponse = await client.images.generate({ prompt: 'A cute baby sea otter' });\n\nconsole.log(imagesResponse);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n imagesResponse, err := client.Images.Generate(context.TODO(), openai.ImageGenerateParams{\n Prompt: \"A cute baby sea otter\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", imagesResponse)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.images.ImageGenerateParams;\nimport com.openai.models.images.ImagesResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ImageGenerateParams params = ImageGenerateParams.builder()\n .prompt(\"A cute baby sea otter\")\n .build();\n ImagesResponse imagesResponse = client.images().generate(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nimages_response = openai.images.generate(prompt: \"A cute baby sea otter\")\n\nputs(images_response)" - }, - "response": "{\n \"created\": 1713833628,\n \"data\": [\n {\n \"b64_json\": \"...\"\n }\n ],\n \"usage\": {\n \"total_tokens\": 100,\n \"input_tokens\": 50,\n \"output_tokens\": 50,\n \"input_tokens_details\": {\n \"text_tokens\": 10,\n \"image_tokens\": 40\n }\n }\n}\n" - }, - { - "title": "Streaming", - "request": { - "curl": "curl https://api.openai.com/v1/images/generations \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-image-1\",\n \"prompt\": \"A cute baby sea otter\",\n \"n\": 1,\n \"size\": \"1024x1024\",\n \"stream\": true\n }' \\\n --no-buffer\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nimages_response = client.images.generate(\n prompt=\"A cute baby sea otter\",\n)\nprint(images_response)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst imagesResponse = await client.images.generate({ prompt: 'A cute baby sea otter' });\n\nconsole.log(imagesResponse);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n imagesResponse, err := client.Images.Generate(context.TODO(), openai.ImageGenerateParams{\n Prompt: \"A cute baby sea otter\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", imagesResponse)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.images.ImageGenerateParams;\nimport com.openai.models.images.ImagesResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ImageGenerateParams params = ImageGenerateParams.builder()\n .prompt(\"A cute baby sea otter\")\n .build();\n ImagesResponse imagesResponse = client.images().generate(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nimages_response = openai.images.generate(prompt: \"A cute baby sea otter\")\n\nputs(images_response)" - }, - "response": "event: image_generation.partial_image\ndata: {\"type\":\"image_generation.partial_image\",\"b64_json\":\"...\",\"partial_image_index\":0}\n\nevent: image_generation.completed\ndata: {\"type\":\"image_generation.completed\",\"b64_json\":\"...\",\"usage\":{\"total_tokens\":100,\"input_tokens\":50,\"output_tokens\":50,\"input_tokens_details\":{\"text_tokens\":10,\"image_tokens\":40}}}\n" - } - ] - }, - "description": "Creates an image given a prompt. [Learn more](https://platform.openai.com/docs/guides/images).\n" - } - }, - "/images/variations": { - "post": { - "operationId": "createImageVariation", - "tags": [ - "Images" - ], - "summary": "Create image variation", - "requestBody": { - "required": true, - "content": { - "multipart/form-data": { - "schema": { - "$ref": "#/components/schemas/CreateImageVariationRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ImagesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create image variation", - "group": "images", - "returns": "Returns a list of [image](https://platform.openai.com/docs/api-reference/images/object) objects.", - "examples": { - "response": "{\n \"created\": 1589478378,\n \"data\": [\n {\n \"url\": \"https://...\"\n },\n {\n \"url\": \"https://...\"\n }\n ]\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/images/variations \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -F image=\"@otter.png\" \\\n -F n=2 \\\n -F size=\"1024x1024\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nimages_response = client.images.create_variation(\n image=b\"raw file contents\",\n)\nprint(images_response.created)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst imagesResponse = await client.images.createVariation({ image: fs.createReadStream('otter.png') });\n\nconsole.log(imagesResponse.created);", - "csharp": "using System;\n\nusing OpenAI.Images;\n\nImageClient client = new(\n model: \"dall-e-2\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nGeneratedImage image = client.GenerateImageVariation(imageFilePath: \"otter.png\");\n\nConsole.WriteLine(image.ImageUri);\n", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n imagesResponse, err := client.Images.NewVariation(context.TODO(), openai.ImageNewVariationParams{\n Image: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", imagesResponse.Created)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.images.ImageCreateVariationParams;\nimport com.openai.models.images.ImagesResponse;\nimport java.io.ByteArrayInputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ImageCreateVariationParams params = ImageCreateVariationParams.builder()\n .image(ByteArrayInputStream(\"some content\".getBytes()))\n .build();\n ImagesResponse imagesResponse = client.images().createVariation(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nimages_response = openai.images.create_variation(image: Pathname(__FILE__))\n\nputs(images_response)" - } - } - }, - "description": "Creates a variation of a given image. This endpoint only supports `dall-e-2`." - } - }, - "/models": { - "get": { - "operationId": "listModels", - "tags": [ - "Models" - ], - "summary": "List models", - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListModelsResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List models", - "group": "models", - "returns": "A list of [model](https://platform.openai.com/docs/api-reference/models/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"model-id-0\",\n \"object\": \"model\",\n \"created\": 1686935002,\n \"owned_by\": \"organization-owner\"\n },\n {\n \"id\": \"model-id-1\",\n \"object\": \"model\",\n \"created\": 1686935002,\n \"owned_by\": \"organization-owner\",\n },\n {\n \"id\": \"model-id-2\",\n \"object\": \"model\",\n \"created\": 1686935002,\n \"owned_by\": \"openai\"\n },\n ],\n \"object\": \"list\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/models \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.models.list()\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const model of client.models.list()) {\n console.log(model.id);\n}", - "csharp": "using System;\n\nusing OpenAI.Models;\n\nOpenAIModelClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nforeach (var model in client.GetModels().Value)\n{\n Console.WriteLine(model.Id);\n}\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Models.List(context.TODO())\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.models.ModelListPage;\nimport com.openai.models.models.ModelListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ModelListPage page = client.models().list();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.models.list\n\nputs(page)" - } - } - }, - "description": "Lists the currently available models, and provides basic information about each one such as the owner and availability." - } - }, - "/models/{model}": { - "get": { - "operationId": "retrieveModel", - "tags": [ - "Models" - ], - "summary": "Retrieve model", - "parameters": [ - { - "in": "path", - "name": "model", - "required": true, - "schema": { - "type": "string", - "example": "gpt-4o-mini" - }, - "description": "The ID of the model to use for this request" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Model" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve model", - "group": "models", - "returns": "The [model](https://platform.openai.com/docs/api-reference/models/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"VAR_chat_model_id\",\n \"object\": \"model\",\n \"created\": 1686935002,\n \"owned_by\": \"openai\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/models/VAR_chat_model_id \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nmodel = client.models.retrieve(\n \"gpt-4o-mini\",\n)\nprint(model.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst model = await client.models.retrieve('gpt-4o-mini');\n\nconsole.log(model.id);", - "csharp": "using System;\nusing System.ClientModel;\n\nusing OpenAI.Models;\n\n OpenAIModelClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nClientResult model = client.GetModel(\"babbage-002\");\nConsole.WriteLine(model.Value.Id);\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n model, err := client.Models.Get(context.TODO(), \"gpt-4o-mini\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", model.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.models.Model;\nimport com.openai.models.models.ModelRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Model model = client.models().retrieve(\"gpt-4o-mini\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nmodel = openai.models.retrieve(\"gpt-4o-mini\")\n\nputs(model)" - } - } - }, - "description": "Retrieves a model instance, providing basic information about the model such as the owner and permissioning." - }, - "delete": { - "operationId": "deleteModel", - "tags": [ - "Models" - ], - "summary": "Delete a fine-tuned model", - "parameters": [ - { - "in": "path", - "name": "model", - "required": true, - "schema": { - "type": "string", - "example": "ft:gpt-4o-mini:acemeco:suffix:abc123" - }, - "description": "The model to delete" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeleteModelResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete a fine-tuned model", - "group": "models", - "returns": "Deletion status.", - "examples": { - "response": "{\n \"id\": \"ft:gpt-4o-mini:acemeco:suffix:abc123\",\n \"object\": \"model\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/models/ft:gpt-4o-mini:acemeco:suffix:abc123 \\\n -X DELETE \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nmodel_deleted = client.models.delete(\n \"ft:gpt-4o-mini:acemeco:suffix:abc123\",\n)\nprint(model_deleted.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst modelDeleted = await client.models.delete('ft:gpt-4o-mini:acemeco:suffix:abc123');\n\nconsole.log(modelDeleted.id);", - "csharp": "using System;\nusing System.ClientModel;\n\nusing OpenAI.Models;\n\nOpenAIModelClient client = new(\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nClientResult success = client.DeleteModel(\"ft:gpt-4o-mini:acemeco:suffix:abc123\");\nConsole.WriteLine(success);\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n modelDeleted, err := client.Models.Delete(context.TODO(), \"ft:gpt-4o-mini:acemeco:suffix:abc123\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", modelDeleted.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.models.ModelDeleteParams;\nimport com.openai.models.models.ModelDeleted;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ModelDeleted modelDeleted = client.models().delete(\"ft:gpt-4o-mini:acemeco:suffix:abc123\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nmodel_deleted = openai.models.delete(\"ft:gpt-4o-mini:acemeco:suffix:abc123\")\n\nputs(model_deleted)" - } - } - }, - "description": "Delete a fine-tuned model. You must have the Owner role in your organization to delete a model." - } - }, - "/moderations": { - "post": { - "operationId": "createModeration", - "tags": [ - "Moderations" - ], - "summary": "Create moderation", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateModerationRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateModerationResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create moderation", - "group": "moderations", - "returns": "A [moderation](https://platform.openai.com/docs/api-reference/moderations/object) object.", - "examples": [ - { - "title": "Single string", - "request": { - "curl": "curl https://api.openai.com/v1/moderations \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"input\": \"I want to kill them.\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nmoderation = client.moderations.create(\n input=\"I want to kill them.\",\n)\nprint(moderation.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst moderation = await client.moderations.create({ input: 'I want to kill them.' });\n\nconsole.log(moderation.id);", - "csharp": "using System;\nusing System.ClientModel;\n\nusing OpenAI.Moderations;\n\nModerationClient client = new(\n model: \"omni-moderation-latest\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nClientResult moderation = client.ClassifyText(\"I want to kill them.\");\n", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n moderation, err := client.Moderations.New(context.TODO(), openai.ModerationNewParams{\n Input: openai.ModerationNewParamsInputUnion{\n OfString: openai.String(\"I want to kill them.\"),\n },\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", moderation.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.moderations.ModerationCreateParams;\nimport com.openai.models.moderations.ModerationCreateResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ModerationCreateParams params = ModerationCreateParams.builder()\n .input(\"I want to kill them.\")\n .build();\n ModerationCreateResponse moderation = client.moderations().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nmoderation = openai.moderations.create(input: \"I want to kill them.\")\n\nputs(moderation)" - }, - "response": "{\n \"id\": \"modr-AB8CjOTu2jiq12hp1AQPfeqFWaORR\",\n \"model\": \"text-moderation-007\",\n \"results\": [\n {\n \"flagged\": true,\n \"categories\": {\n \"sexual\": false,\n \"hate\": false,\n \"harassment\": true,\n \"self-harm\": false,\n \"sexual/minors\": false,\n \"hate/threatening\": false,\n \"violence/graphic\": false,\n \"self-harm/intent\": false,\n \"self-harm/instructions\": false,\n \"harassment/threatening\": true,\n \"violence\": true\n },\n \"category_scores\": {\n \"sexual\": 0.000011726012417057063,\n \"hate\": 0.22706663608551025,\n \"harassment\": 0.5215635299682617,\n \"self-harm\": 2.227119921371923e-6,\n \"sexual/minors\": 7.107352217872176e-8,\n \"hate/threatening\": 0.023547329008579254,\n \"violence/graphic\": 0.00003391829886822961,\n \"self-harm/intent\": 1.646940972932498e-6,\n \"self-harm/instructions\": 1.1198755256458526e-9,\n \"harassment/threatening\": 0.5694745779037476,\n \"violence\": 0.9971134662628174\n }\n }\n ]\n}\n" - }, - { - "title": "Image and text", - "request": { - "curl": "curl https://api.openai.com/v1/moderations \\\n -X POST \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"omni-moderation-latest\",\n \"input\": [\n { \"type\": \"text\", \"text\": \"...text to classify goes here...\" },\n {\n \"type\": \"image_url\",\n \"image_url\": {\n \"url\": \"https://example.com/image.png\"\n }\n }\n ]\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nmoderation = client.moderations.create(\n input=\"I want to kill them.\",\n)\nprint(moderation.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst moderation = await client.moderations.create({ input: 'I want to kill them.' });\n\nconsole.log(moderation.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n moderation, err := client.Moderations.New(context.TODO(), openai.ModerationNewParams{\n Input: openai.ModerationNewParamsInputUnion{\n OfString: openai.String(\"I want to kill them.\"),\n },\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", moderation.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.moderations.ModerationCreateParams;\nimport com.openai.models.moderations.ModerationCreateResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ModerationCreateParams params = ModerationCreateParams.builder()\n .input(\"I want to kill them.\")\n .build();\n ModerationCreateResponse moderation = client.moderations().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nmoderation = openai.moderations.create(input: \"I want to kill them.\")\n\nputs(moderation)" - }, - "response": "{\n \"id\": \"modr-0d9740456c391e43c445bf0f010940c7\",\n \"model\": \"omni-moderation-latest\",\n \"results\": [\n {\n \"flagged\": true,\n \"categories\": {\n \"harassment\": true,\n \"harassment/threatening\": true,\n \"sexual\": false,\n \"hate\": false,\n \"hate/threatening\": false,\n \"illicit\": false,\n \"illicit/violent\": false,\n \"self-harm/intent\": false,\n \"self-harm/instructions\": false,\n \"self-harm\": false,\n \"sexual/minors\": false,\n \"violence\": true,\n \"violence/graphic\": true\n },\n \"category_scores\": {\n \"harassment\": 0.8189693396524255,\n \"harassment/threatening\": 0.804985420696006,\n \"sexual\": 1.573112165348997e-6,\n \"hate\": 0.007562942636942845,\n \"hate/threatening\": 0.004208854591835476,\n \"illicit\": 0.030535955153511665,\n \"illicit/violent\": 0.008925306722380033,\n \"self-harm/intent\": 0.00023023930975076432,\n \"self-harm/instructions\": 0.0002293869201073356,\n \"self-harm\": 0.012598046106750154,\n \"sexual/minors\": 2.212566909570261e-8,\n \"violence\": 0.9999992735124786,\n \"violence/graphic\": 0.843064871157054\n },\n \"category_applied_input_types\": {\n \"harassment\": [\n \"text\"\n ],\n \"harassment/threatening\": [\n \"text\"\n ],\n \"sexual\": [\n \"text\",\n \"image\"\n ],\n \"hate\": [\n \"text\"\n ],\n \"hate/threatening\": [\n \"text\"\n ],\n \"illicit\": [\n \"text\"\n ],\n \"illicit/violent\": [\n \"text\"\n ],\n \"self-harm/intent\": [\n \"text\",\n \"image\"\n ],\n \"self-harm/instructions\": [\n \"text\",\n \"image\"\n ],\n \"self-harm\": [\n \"text\",\n \"image\"\n ],\n \"sexual/minors\": [\n \"text\"\n ],\n \"violence\": [\n \"text\",\n \"image\"\n ],\n \"violence/graphic\": [\n \"text\",\n \"image\"\n ]\n }\n }\n ]\n}\n" - } - ] - }, - "description": "Classifies if text and/or image inputs are potentially harmful. Learn\nmore in the [moderation guide](https://platform.openai.com/docs/guides/moderation).\n" - } - }, - "/organization/admin_api_keys": { - "get": { - "summary": "List all organization and project API keys.", - "operationId": "admin-api-keys-list", - "description": "List organization API keys", - "parameters": [ - { - "in": "query", - "name": "after", - "required": false, - "schema": { - "type": "string", - "nullable": true, - "description": "Return keys with IDs that come after this ID in the pagination order." - } - }, - { - "in": "query", - "name": "order", - "required": false, - "schema": { - "type": "string", - "enum": [ - "asc", - "desc" - ], - "default": "asc", - "description": "Order results by creation time, ascending or descending." - } - }, - { - "in": "query", - "name": "limit", - "required": false, - "schema": { - "type": "integer", - "default": 20, - "description": "Maximum number of keys to return." - } - } - ], - "responses": { - "200": { - "description": "A list of organization API keys.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ApiKeyList" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List all organization and project API keys.", - "group": "administration", - "returns": "A list of admin and project API key objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"organization.admin_api_key\",\n \"id\": \"key_abc\",\n \"name\": \"Main Admin Key\",\n \"redacted_value\": \"sk-admin...def\",\n \"created_at\": 1711471533,\n \"last_used_at\": 1711471534,\n \"owner\": {\n \"type\": \"service_account\",\n \"object\": \"organization.service_account\",\n \"id\": \"sa_456\",\n \"name\": \"My Service Account\",\n \"created_at\": 1711471533,\n \"role\": \"member\"\n }\n }\n ],\n \"first_id\": \"key_abc\",\n \"last_id\": \"key_abc\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/admin_api_keys?after=key_abc&limit=20 \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - } - }, - "post": { - "summary": "Create admin API key", - "operationId": "admin-api-keys-create", - "description": "Create an organization admin API key", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "type": "object", - "required": [ - "name" - ], - "properties": { - "name": { - "type": "string", - "example": "New Admin Key" - } - } - } - } - } - }, - "responses": { - "200": { - "description": "The newly created admin API key.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/AdminApiKey" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create admin API key", - "group": "administration", - "returns": "The created [AdminApiKey](https://platform.openai.com/docs/api-reference/admin-api-keys/object) object.", - "examples": { - "response": "{\n \"object\": \"organization.admin_api_key\",\n \"id\": \"key_xyz\",\n \"name\": \"New Admin Key\",\n \"redacted_value\": \"sk-admin...xyz\",\n \"created_at\": 1711471533,\n \"last_used_at\": 1711471534,\n \"owner\": {\n \"type\": \"user\",\n \"object\": \"organization.user\",\n \"id\": \"user_123\",\n \"name\": \"John Doe\",\n \"created_at\": 1711471533,\n \"role\": \"owner\"\n },\n \"value\": \"sk-admin-1234abcd\"\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/admin_api_keys \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"name\": \"New Admin Key\"\n }'\n" - } - } - } - } - }, - "/organization/admin_api_keys/{key_id}": { - "get": { - "summary": "Retrieve admin API key", - "operationId": "admin-api-keys-get", - "description": "Retrieve a single organization API key", - "parameters": [ - { - "in": "path", - "name": "key_id", - "required": true, - "schema": { - "type": "string", - "description": "The ID of the API key." - } - } - ], - "responses": { - "200": { - "description": "Details of the requested API key.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/AdminApiKey" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve admin API key", - "group": "administration", - "returns": "The requested [AdminApiKey](https://platform.openai.com/docs/api-reference/admin-api-keys/object) object.", - "examples": { - "response": "{\n \"object\": \"organization.admin_api_key\",\n \"id\": \"key_abc\",\n \"name\": \"Main Admin Key\",\n \"redacted_value\": \"sk-admin...xyz\",\n \"created_at\": 1711471533,\n \"last_used_at\": 1711471534,\n \"owner\": {\n \"type\": \"user\",\n \"object\": \"organization.user\",\n \"id\": \"user_123\",\n \"name\": \"John Doe\",\n \"created_at\": 1711471533,\n \"role\": \"owner\"\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/admin_api_keys/key_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - } - }, - "delete": { - "summary": "Delete admin API key", - "operationId": "admin-api-keys-delete", - "description": "Delete an organization admin API key", - "parameters": [ - { - "in": "path", - "name": "key_id", - "required": true, - "schema": { - "type": "string", - "description": "The ID of the API key to be deleted." - } - } - ], - "responses": { - "200": { - "description": "Confirmation that the API key was deleted.", - "content": { - "application/json": { - "schema": { - "type": "object", - "properties": { - "id": { - "type": "string", - "example": "key_abc" - }, - "object": { - "type": "string", - "example": "organization.admin_api_key.deleted" - }, - "deleted": { - "type": "boolean", - "example": true - } - } - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete admin API key", - "group": "administration", - "returns": "A confirmation object indicating the key was deleted.", - "examples": { - "response": "{\n \"id\": \"key_abc\",\n \"object\": \"organization.admin_api_key.deleted\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/organization/admin_api_keys/key_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - } - } - }, - "/organization/audit_logs": { - "get": { - "summary": "List audit logs", - "operationId": "list-audit-logs", - "tags": [ - "Audit Logs" - ], - "parameters": [ - { - "name": "effective_at", - "in": "query", - "description": "Return only events whose `effective_at` (Unix seconds) is in this range.", - "required": false, - "schema": { - "type": "object", - "properties": { - "gt": { - "type": "integer", - "description": "Return only events whose `effective_at` (Unix seconds) is greater than this value." - }, - "gte": { - "type": "integer", - "description": "Return only events whose `effective_at` (Unix seconds) is greater than or equal to this value." - }, - "lt": { - "type": "integer", - "description": "Return only events whose `effective_at` (Unix seconds) is less than this value." - }, - "lte": { - "type": "integer", - "description": "Return only events whose `effective_at` (Unix seconds) is less than or equal to this value." - } - } - } - }, - { - "name": "project_ids[]", - "in": "query", - "description": "Return only events for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "event_types[]", - "in": "query", - "description": "Return only events with a `type` in one of these values. For example, `project.created`. For all options, see the documentation for the [audit log object](https://platform.openai.com/docs/api-reference/audit-logs/object).", - "required": false, - "schema": { - "type": "array", - "items": { - "$ref": "#/components/schemas/AuditLogEventType" - } - } - }, - { - "name": "actor_ids[]", - "in": "query", - "description": "Return only events performed by these actors. Can be a user ID, a service account ID, or an api key tracking ID.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "actor_emails[]", - "in": "query", - "description": "Return only events performed by users with these emails.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "resource_ids[]", - "in": "query", - "description": "Return only events performed on these targets. For example, a project ID updated.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "before", - "in": "query", - "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.\n", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Audit logs listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListAuditLogsResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List audit logs", - "group": "audit-logs", - "returns": "A list of paginated [Audit Log](https://platform.openai.com/docs/api-reference/audit-logs/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"audit_log-xxx_yyyymmdd\",\n \"type\": \"project.archived\",\n \"effective_at\": 1722461446,\n \"actor\": {\n \"type\": \"api_key\",\n \"api_key\": {\n \"type\": \"user\",\n \"user\": {\n \"id\": \"user-xxx\",\n \"email\": \"user@example.com\"\n }\n }\n },\n \"project.archived\": {\n \"id\": \"proj_abc\"\n },\n },\n {\n \"id\": \"audit_log-yyy__20240101\",\n \"type\": \"api_key.updated\",\n \"effective_at\": 1720804190,\n \"actor\": {\n \"type\": \"session\",\n \"session\": {\n \"user\": {\n \"id\": \"user-xxx\",\n \"email\": \"user@example.com\"\n },\n \"ip_address\": \"127.0.0.1\",\n \"user_agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36\",\n \"ja3\": \"a497151ce4338a12c4418c44d375173e\",\n \"ja4\": \"q13d0313h3_55b375c5d22e_c7319ce65786\",\n \"ip_address_details\": {\n \"country\": \"US\",\n \"city\": \"San Francisco\",\n \"region\": \"California\",\n \"region_code\": \"CA\",\n \"asn\": \"1234\",\n \"latitude\": \"37.77490\",\n \"longitude\": \"-122.41940\"\n }\n }\n },\n \"api_key.updated\": {\n \"id\": \"key_xxxx\",\n \"data\": {\n \"scopes\": [\"resource_2.operation_2\"]\n }\n },\n }\n ],\n \"first_id\": \"audit_log-xxx__20240101\",\n \"last_id\": \"audit_log_yyy__20240101\",\n \"has_more\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/audit_logs \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "List user actions and configuration changes within this organization." - } - }, - "/organization/certificates": { - "get": { - "summary": "List organization certificates", - "operationId": "listOrganizationCertificates", - "tags": [ - "Certificates" - ], - "parameters": [ - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - } - ], - "responses": { - "200": { - "description": "Certificates listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListCertificatesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List organization certificates", - "group": "administration", - "returns": "A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects.", - "examples": { - "request": { - "curl": "curl https://api.openai.com/v1/organization/certificates \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\"\n" - }, - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"organization.certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"My Example Certificate\",\n \"active\": true,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n ],\n \"first_id\": \"cert_abc\",\n \"last_id\": \"cert_abc\",\n \"has_more\": false\n}\n" - } - }, - "description": "List uploaded certificates for this organization." - }, - "post": { - "summary": "Upload certificate", - "operationId": "uploadCertificate", - "tags": [ - "Certificates" - ], - "requestBody": { - "description": "The certificate upload payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UploadCertificateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Certificate uploaded successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Certificate" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Upload certificate", - "group": "administration", - "returns": "A single [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) object.", - "examples": { - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/certificates \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\" \\\n-d '{\n \"name\": \"My Example Certificate\",\n \"certificate\": \"-----BEGIN CERTIFICATE-----\\\\nMIIDeT...\\\\n-----END CERTIFICATE-----\"\n}'\n" - }, - "response": "{\n \"object\": \"certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"My Example Certificate\",\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n}\n" - } - }, - "description": "Upload a certificate to the organization. This does **not** automatically activate the certificate.\n\nOrganizations can upload up to 50 certificates.\n" - } - }, - "/organization/certificates/activate": { - "post": { - "summary": "Activate certificates for organization", - "operationId": "activateOrganizationCertificates", - "tags": [ - "Certificates" - ], - "requestBody": { - "description": "The certificate activation payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ToggleCertificatesRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Certificates activated successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListCertificatesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Activate certificates for organization", - "group": "administration", - "returns": "A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects that were activated.", - "examples": { - "request": { - "curl": "curl https://api.openai.com/v1/organization/certificates/activate \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\" \\\n-d '{\n \"data\": [\"cert_abc\", \"cert_def\"]\n}'\n" - }, - "response": "{\n \"object\": \"organization.certificate.activation\",\n \"data\": [\n {\n \"object\": \"organization.certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"My Example Certificate\",\n \"active\": true,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n {\n \"object\": \"organization.certificate\",\n \"id\": \"cert_def\",\n \"name\": \"My Example Certificate 2\",\n \"active\": true,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n ],\n}\n" - } - }, - "description": "Activate certificates at the organization level.\n\nYou can atomically and idempotently activate up to 10 certificates at a time.\n" - } - }, - "/organization/certificates/deactivate": { - "post": { - "summary": "Deactivate certificates for organization", - "operationId": "deactivateOrganizationCertificates", - "tags": [ - "Certificates" - ], - "requestBody": { - "description": "The certificate deactivation payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ToggleCertificatesRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Certificates deactivated successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListCertificatesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Deactivate certificates for organization", - "group": "administration", - "returns": "A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects that were deactivated.", - "examples": { - "request": { - "curl": "curl https://api.openai.com/v1/organization/certificates/deactivate \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\" \\\n-d '{\n \"data\": [\"cert_abc\", \"cert_def\"]\n}'\n" - }, - "response": "{\n \"object\": \"organization.certificate.deactivation\",\n \"data\": [\n {\n \"object\": \"organization.certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"My Example Certificate\",\n \"active\": false,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n {\n \"object\": \"organization.certificate\",\n \"id\": \"cert_def\",\n \"name\": \"My Example Certificate 2\",\n \"active\": false,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n ],\n}\n" - } - }, - "description": "Deactivate certificates at the organization level.\n\nYou can atomically and idempotently deactivate up to 10 certificates at a time.\n" - } - }, - "/organization/certificates/{certificate_id}": { - "get": { - "summary": "Get certificate", - "operationId": "getCertificate", - "tags": [ - "Certificates" - ], - "parameters": [ - { - "name": "certificate_id", - "in": "path", - "description": "Unique ID of the certificate to retrieve.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "include", - "in": "query", - "description": "A list of additional fields to include in the response. Currently the only supported value is `content` to fetch the PEM content of the certificate.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "content" - ] - } - } - } - ], - "responses": { - "200": { - "description": "Certificate retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Certificate" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Get certificate", - "group": "administration", - "returns": "A single [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) object.", - "examples": { - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/certificates/cert_abc?include[]=content\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\"\n" - }, - "response": "{\n \"object\": \"certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"My Example Certificate\",\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 1234567,\n \"expires_at\": 12345678,\n \"content\": \"-----BEGIN CERTIFICATE-----MIIDeT...-----END CERTIFICATE-----\"\n }\n}\n" - } - }, - "description": "Get a certificate that has been uploaded to the organization.\n\nYou can get a certificate regardless of whether it is active or not.\n" - }, - "post": { - "summary": "Modify certificate", - "operationId": "modifyCertificate", - "tags": [ - "Certificates" - ], - "requestBody": { - "description": "The certificate modification payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ModifyCertificateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Certificate modified successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Certificate" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify certificate", - "group": "administration", - "returns": "The updated [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) object.", - "examples": { - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/certificates/cert_abc \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\" \\\n-d '{\n \"name\": \"Renamed Certificate\"\n}'\n" - }, - "response": "{\n \"object\": \"certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"Renamed Certificate\",\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n}\n" - } - }, - "description": "Modify a certificate. Note that only the name can be modified.\n" - }, - "delete": { - "summary": "Delete certificate", - "operationId": "deleteCertificate", - "tags": [ - "Certificates" - ], - "responses": { - "200": { - "description": "Certificate deleted successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeleteCertificateResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete certificate", - "group": "administration", - "returns": "A confirmation object indicating the certificate was deleted.", - "examples": { - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/organization/certificates/cert_abc \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\"\n" - }, - "response": "{\n \"object\": \"certificate.deleted\",\n \"id\": \"cert_abc\"\n}\n" - } - }, - "description": "Delete a certificate from the organization.\n\nThe certificate must be inactive for the organization and all projects.\n" - } - }, - "/organization/costs": { - "get": { - "summary": "Costs", - "operationId": "usage-costs", - "tags": [ - "Usage" - ], - "parameters": [ - { - "name": "start_time", - "in": "query", - "description": "Start time (Unix seconds) of the query time range, inclusive.", - "required": true, - "schema": { - "type": "integer" - } - }, - { - "name": "end_time", - "in": "query", - "description": "End time (Unix seconds) of the query time range, exclusive.", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "bucket_width", - "in": "query", - "description": "Width of each time bucket in response. Currently only `1d` is supported, default to `1d`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "1d" - ], - "default": "1d" - } - }, - { - "name": "project_ids", - "in": "query", - "description": "Return only costs for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "group_by", - "in": "query", - "description": "Group the costs by the specified fields. Support fields include `project_id`, `line_item` and any combination of them.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "project_id", - "line_item" - ] - } - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of buckets to be returned. Limit can range between 1 and 180, and the default is 7.\n", - "required": false, - "schema": { - "type": "integer", - "default": 7 - } - }, - { - "name": "page", - "in": "query", - "description": "A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Costs data retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UsageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Costs", - "group": "usage-costs", - "returns": "A list of paginated, time bucketed [Costs](https://platform.openai.com/docs/api-reference/usage/costs_object) objects.", - "examples": { - "response": "{\n \"object\": \"page\",\n \"data\": [\n {\n \"object\": \"bucket\",\n \"start_time\": 1730419200,\n \"end_time\": 1730505600,\n \"results\": [\n {\n \"object\": \"organization.costs.result\",\n \"amount\": {\n \"value\": 0.06,\n \"currency\": \"usd\"\n },\n \"line_item\": null,\n \"project_id\": null\n }\n ]\n }\n ],\n \"has_more\": false,\n \"next_page\": null\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/costs?start_time=1730419200&limit=1\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Get costs details for the organization." - } - }, - "/organization/invites": { - "get": { - "summary": "List invites", - "operationId": "list-invites", - "tags": [ - "Invites" - ], - "parameters": [ - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Invites listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/InviteListResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List invites", - "group": "administration", - "returns": "A list of [Invite](https://platform.openai.com/docs/api-reference/invite/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"organization.invite\",\n \"id\": \"invite-abc\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"status\": \"accepted\",\n \"invited_at\": 1711471533,\n \"expires_at\": 1711471533,\n \"accepted_at\": 1711471533\n }\n ],\n \"first_id\": \"invite-abc\",\n \"last_id\": \"invite-abc\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/invites?after=invite-abc&limit=20 \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Returns a list of invites in the organization." - }, - "post": { - "summary": "Create invite", - "operationId": "inviteUser", - "tags": [ - "Invites" - ], - "requestBody": { - "description": "The invite request payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/InviteRequest" - } - } - } - }, - "responses": { - "200": { - "description": "User invited successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Invite" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create invite", - "group": "administration", - "returns": "The created [Invite](https://platform.openai.com/docs/api-reference/invite/object) object.", - "examples": { - "response": "{\n \"object\": \"organization.invite\",\n \"id\": \"invite-def\",\n \"email\": \"anotheruser@example.com\",\n \"role\": \"reader\",\n \"status\": \"pending\",\n \"invited_at\": 1711471533,\n \"expires_at\": 1711471533,\n \"accepted_at\": null,\n \"projects\": [\n {\n \"id\": \"project-xyz\",\n \"role\": \"member\"\n },\n {\n \"id\": \"project-abc\",\n \"role\": \"owner\"\n }\n ]\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/invites \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"email\": \"anotheruser@example.com\",\n \"role\": \"reader\",\n \"projects\": [\n {\n \"id\": \"project-xyz\",\n \"role\": \"member\"\n },\n {\n \"id\": \"project-abc\",\n \"role\": \"owner\"\n }\n ]\n }'\n" - } - } - }, - "description": "Create an invite for a user to the organization. The invite must be accepted by the user before they have access to the organization." - } - }, - "/organization/invites/{invite_id}": { - "get": { - "summary": "Retrieve invite", - "operationId": "retrieve-invite", - "tags": [ - "Invites" - ], - "parameters": [ - { - "in": "path", - "name": "invite_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the invite to retrieve." - } - ], - "responses": { - "200": { - "description": "Invite retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Invite" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve invite", - "group": "administration", - "returns": "The [Invite](https://platform.openai.com/docs/api-reference/invite/object) object matching the specified ID.", - "examples": { - "response": "{\n \"object\": \"organization.invite\",\n \"id\": \"invite-abc\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"status\": \"accepted\",\n \"invited_at\": 1711471533,\n \"expires_at\": 1711471533,\n \"accepted_at\": 1711471533\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/invites/invite-abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Retrieves an invite." - }, - "delete": { - "summary": "Delete invite", - "operationId": "delete-invite", - "tags": [ - "Invites" - ], - "parameters": [ - { - "in": "path", - "name": "invite_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the invite to delete." - } - ], - "responses": { - "200": { - "description": "Invite deleted successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/InviteDeleteResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete invite", - "group": "administration", - "returns": "Confirmation that the invite has been deleted", - "examples": { - "response": "{\n \"object\": \"organization.invite.deleted\",\n \"id\": \"invite-abc\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/organization/invites/invite-abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Delete an invite. If the invite has already been accepted, it cannot be deleted." - } - }, - "/organization/projects": { - "get": { - "summary": "List projects", - "operationId": "list-projects", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "include_archived", - "in": "query", - "schema": { - "type": "boolean", - "default": false - }, - "description": "If `true` returns all projects including those that have been `archived`. Archived projects are not included by default." - } - ], - "responses": { - "200": { - "description": "Projects listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectListResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List projects", - "group": "administration", - "returns": "A list of [Project](https://platform.openai.com/docs/api-reference/projects/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"proj_abc\",\n \"object\": \"organization.project\",\n \"name\": \"Project example\",\n \"created_at\": 1711471533,\n \"archived_at\": null,\n \"status\": \"active\"\n }\n ],\n \"first_id\": \"proj-abc\",\n \"last_id\": \"proj-xyz\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects?after=proj_abc&limit=20&include_archived=false \\ -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Returns a list of projects." - }, - "post": { - "summary": "Create project", - "operationId": "create-project", - "tags": [ - "Projects" - ], - "requestBody": { - "description": "The project create request payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectCreateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Project created successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Project" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create project", - "group": "administration", - "returns": "The created [Project](https://platform.openai.com/docs/api-reference/projects/object) object.", - "examples": { - "response": "{\n \"id\": \"proj_abc\",\n \"object\": \"organization.project\",\n \"name\": \"Project ABC\",\n \"created_at\": 1711471533,\n \"archived_at\": null,\n \"status\": \"active\"\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/projects \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"name\": \"Project ABC\"\n }'\n" - } - } - }, - "description": "Create a new project in the organization. Projects can be created and archived, but cannot be deleted." - } - }, - "/organization/projects/{project_id}": { - "get": { - "summary": "Retrieve project", - "operationId": "retrieve-project", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Project" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve project", - "group": "administration", - "description": "Retrieve a project.", - "returns": "The [Project](https://platform.openai.com/docs/api-reference/projects/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"proj_abc\",\n \"object\": \"organization.project\",\n \"name\": \"Project example\",\n \"created_at\": 1711471533,\n \"archived_at\": null,\n \"status\": \"active\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Retrieves a project." - }, - "post": { - "summary": "Modify project", - "operationId": "modify-project", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "requestBody": { - "description": "The project update request payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectUpdateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Project updated successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Project" - } - } - } - }, - "400": { - "description": "Error response when updating the default project.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ErrorResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify project", - "group": "administration", - "returns": "The updated [Project](https://platform.openai.com/docs/api-reference/projects/object) object.", - "examples": { - "response": "", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/projects/proj_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"name\": \"Project DEF\"\n }'\n" - } - } - }, - "description": "Modifies a project in the organization." - } - }, - "/organization/projects/{project_id}/api_keys": { - "get": { - "summary": "List project API keys", - "operationId": "list-project-api-keys", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project API keys listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectApiKeyListResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List project API keys", - "group": "administration", - "returns": "A list of [ProjectApiKey](https://platform.openai.com/docs/api-reference/project-api-keys/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"organization.project.api_key\",\n \"redacted_value\": \"sk-abc...def\",\n \"name\": \"My API Key\",\n \"created_at\": 1711471533,\n \"last_used_at\": 1711471534,\n \"id\": \"key_abc\",\n \"owner\": {\n \"type\": \"user\",\n \"user\": {\n \"object\": \"organization.project.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n }\n }\n }\n ],\n \"first_id\": \"key_abc\",\n \"last_id\": \"key_xyz\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/api_keys?after=key_abc&limit=20 \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Returns a list of API keys in the project." - } - }, - "/organization/projects/{project_id}/api_keys/{key_id}": { - "get": { - "summary": "Retrieve project API key", - "operationId": "retrieve-project-api-key", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "key_id", - "in": "path", - "description": "The ID of the API key.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project API key retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectApiKey" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve project API key", - "group": "administration", - "returns": "The [ProjectApiKey](https://platform.openai.com/docs/api-reference/project-api-keys/object) object matching the specified ID.", - "examples": { - "response": "{\n \"object\": \"organization.project.api_key\",\n \"redacted_value\": \"sk-abc...def\",\n \"name\": \"My API Key\",\n \"created_at\": 1711471533,\n \"last_used_at\": 1711471534,\n \"id\": \"key_abc\",\n \"owner\": {\n \"type\": \"user\",\n \"user\": {\n \"object\": \"organization.project.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n }\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/api_keys/key_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Retrieves an API key in the project." - }, - "delete": { - "summary": "Delete project API key", - "operationId": "delete-project-api-key", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "key_id", - "in": "path", - "description": "The ID of the API key.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project API key deleted successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectApiKeyDeleteResponse" - } - } - } - }, - "400": { - "description": "Error response for various conditions.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ErrorResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete project API key", - "group": "administration", - "returns": "Confirmation of the key's deletion or an error if the key belonged to a service account", - "examples": { - "response": "{\n \"object\": \"organization.project.api_key.deleted\",\n \"id\": \"key_abc\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/organization/projects/proj_abc/api_keys/key_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Deletes an API key from the project." - } - }, - "/organization/projects/{project_id}/archive": { - "post": { - "summary": "Archive project", - "operationId": "archive-project", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project archived successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Project" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Archive project", - "group": "administration", - "returns": "The archived [Project](https://platform.openai.com/docs/api-reference/projects/object) object.", - "examples": { - "response": "{\n \"id\": \"proj_abc\",\n \"object\": \"organization.project\",\n \"name\": \"Project DEF\",\n \"created_at\": 1711471533,\n \"archived_at\": 1711471533,\n \"status\": \"archived\"\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/archive \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Archives a project in the organization. Archived projects cannot be used or updated." - } - }, - "/organization/projects/{project_id}/certificates": { - "get": { - "summary": "List project certificates", - "operationId": "listProjectCertificates", - "tags": [ - "Certificates" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - } - ], - "responses": { - "200": { - "description": "Certificates listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListCertificatesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List project certificates", - "group": "administration", - "returns": "A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects.", - "examples": { - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/certificates \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\"\n" - }, - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"organization.project.certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"My Example Certificate\",\n \"active\": true,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n ],\n \"first_id\": \"cert_abc\",\n \"last_id\": \"cert_abc\",\n \"has_more\": false\n}\n" - } - }, - "description": "List certificates for this project." - } - }, - "/organization/projects/{project_id}/certificates/activate": { - "post": { - "summary": "Activate certificates for project", - "operationId": "activateProjectCertificates", - "tags": [ - "Certificates" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "requestBody": { - "description": "The certificate activation payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ToggleCertificatesRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Certificates activated successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListCertificatesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Activate certificates for project", - "group": "administration", - "returns": "A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects that were activated.", - "examples": { - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/certificates/activate \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\" \\\n-d '{\n \"data\": [\"cert_abc\", \"cert_def\"]\n}'\n" - }, - "response": "{\n \"object\": \"organization.project.certificate.activation\",\n \"data\": [\n {\n \"object\": \"organization.project.certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"My Example Certificate\",\n \"active\": true,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n {\n \"object\": \"organization.project.certificate\",\n \"id\": \"cert_def\",\n \"name\": \"My Example Certificate 2\",\n \"active\": true,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n ],\n}\n" - } - }, - "description": "Activate certificates at the project level.\n\nYou can atomically and idempotently activate up to 10 certificates at a time.\n" - } - }, - "/organization/projects/{project_id}/certificates/deactivate": { - "post": { - "summary": "Deactivate certificates for project", - "operationId": "deactivateProjectCertificates", - "tags": [ - "Certificates" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "requestBody": { - "description": "The certificate deactivation payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ToggleCertificatesRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Certificates deactivated successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListCertificatesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Deactivate certificates for project", - "group": "administration", - "returns": "A list of [Certificate](https://platform.openai.com/docs/api-reference/certificates/object) objects that were deactivated.", - "examples": { - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/certificates/deactivate \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\" \\\n-d '{\n \"data\": [\"cert_abc\", \"cert_def\"]\n}'\n" - }, - "response": "{\n \"object\": \"organization.project.certificate.deactivation\",\n \"data\": [\n {\n \"object\": \"organization.project.certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"My Example Certificate\",\n \"active\": false,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n {\n \"object\": \"organization.project.certificate\",\n \"id\": \"cert_def\",\n \"name\": \"My Example Certificate 2\",\n \"active\": false,\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 12345667,\n \"expires_at\": 12345678\n }\n },\n ],\n}\n" - } - }, - "description": "Deactivate certificates at the project level. You can atomically and \nidempotently deactivate up to 10 certificates at a time.\n" - } - }, - "/organization/projects/{project_id}/rate_limits": { - "get": { - "summary": "List project rate limits", - "operationId": "list-project-rate-limits", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. The default is 100.\n", - "required": false, - "schema": { - "type": "integer", - "default": 100 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "before", - "in": "query", - "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, beginning with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project rate limits listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectRateLimitListResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List project rate limits", - "group": "administration", - "returns": "A list of [ProjectRateLimit](https://platform.openai.com/docs/api-reference/project-rate-limits/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"project.rate_limit\",\n \"id\": \"rl-ada\",\n \"model\": \"ada\",\n \"max_requests_per_1_minute\": 600,\n \"max_tokens_per_1_minute\": 150000,\n \"max_images_per_1_minute\": 10\n }\n ],\n \"first_id\": \"rl-ada\",\n \"last_id\": \"rl-ada\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/rate_limits?after=rl_xxx&limit=20 \\ -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - }, - "error_response": "{\n \"code\": 404,\n \"message\": \"The project {project_id} was not found\"\n}\n" - } - }, - "description": "Returns the rate limits per model for a project." - } - }, - "/organization/projects/{project_id}/rate_limits/{rate_limit_id}": { - "post": { - "summary": "Modify project rate limit", - "operationId": "update-project-rate-limits", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "rate_limit_id", - "in": "path", - "description": "The ID of the rate limit.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "requestBody": { - "description": "The project rate limit update request payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectRateLimitUpdateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Project rate limit updated successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectRateLimit" - } - } - } - }, - "400": { - "description": "Error response for various conditions.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ErrorResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify project rate limit", - "group": "administration", - "returns": "The updated [ProjectRateLimit](https://platform.openai.com/docs/api-reference/project-rate-limits/object) object.", - "examples": { - "response": "{\n \"object\": \"project.rate_limit\",\n \"id\": \"rl-ada\",\n \"model\": \"ada\",\n \"max_requests_per_1_minute\": 600,\n \"max_tokens_per_1_minute\": 150000,\n \"max_images_per_1_minute\": 10\n }\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/rate_limits/rl_xxx \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"max_requests_per_1_minute\": 500\n }'\n" - }, - "error_response": "{\n \"code\": 404,\n \"message\": \"The project {project_id} was not found\"\n}\n" - } - }, - "description": "Updates a project rate limit." - } - }, - "/organization/projects/{project_id}/service_accounts": { - "get": { - "summary": "List project service accounts", - "operationId": "list-project-service-accounts", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project service accounts listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectServiceAccountListResponse" - } - } - } - }, - "400": { - "description": "Error response when project is archived.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ErrorResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List project service accounts", - "group": "administration", - "returns": "A list of [ProjectServiceAccount](https://platform.openai.com/docs/api-reference/project-service-accounts/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"organization.project.service_account\",\n \"id\": \"svc_acct_abc\",\n \"name\": \"Service Account\",\n \"role\": \"owner\",\n \"created_at\": 1711471533\n }\n ],\n \"first_id\": \"svc_acct_abc\",\n \"last_id\": \"svc_acct_xyz\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/service_accounts?after=custom_id&limit=20 \\ -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Returns a list of service accounts in the project." - }, - "post": { - "summary": "Create project service account", - "operationId": "create-project-service-account", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "requestBody": { - "description": "The project service account create request payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectServiceAccountCreateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Project service account created successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectServiceAccountCreateResponse" - } - } - } - }, - "400": { - "description": "Error response when project is archived.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ErrorResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create project service account", - "group": "administration", - "returns": "The created [ProjectServiceAccount](https://platform.openai.com/docs/api-reference/project-service-accounts/object) object.", - "examples": { - "response": "{\n \"object\": \"organization.project.service_account\",\n \"id\": \"svc_acct_abc\",\n \"name\": \"Production App\",\n \"role\": \"member\",\n \"created_at\": 1711471533,\n \"api_key\": {\n \"object\": \"organization.project.service_account.api_key\",\n \"value\": \"sk-abcdefghijklmnop123\",\n \"name\": \"Secret Key\",\n \"created_at\": 1711471533,\n \"id\": \"key_abc\"\n }\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/service_accounts \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"name\": \"Production App\"\n }'\n" - } - } - }, - "description": "Creates a new service account in the project. This also returns an unredacted API key for the service account." - } - }, - "/organization/projects/{project_id}/service_accounts/{service_account_id}": { - "get": { - "summary": "Retrieve project service account", - "operationId": "retrieve-project-service-account", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "service_account_id", - "in": "path", - "description": "The ID of the service account.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project service account retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectServiceAccount" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve project service account", - "group": "administration", - "returns": "The [ProjectServiceAccount](https://platform.openai.com/docs/api-reference/project-service-accounts/object) object matching the specified ID.", - "examples": { - "response": "{\n \"object\": \"organization.project.service_account\",\n \"id\": \"svc_acct_abc\",\n \"name\": \"Service Account\",\n \"role\": \"owner\",\n \"created_at\": 1711471533\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/service_accounts/svc_acct_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Retrieves a service account in the project." - }, - "delete": { - "summary": "Delete project service account", - "operationId": "delete-project-service-account", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "service_account_id", - "in": "path", - "description": "The ID of the service account.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project service account deleted successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectServiceAccountDeleteResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete project service account", - "group": "administration", - "returns": "Confirmation of service account being deleted, or an error in case of an archived project, which has no service accounts", - "examples": { - "response": "{\n \"object\": \"organization.project.service_account.deleted\",\n \"id\": \"svc_acct_abc\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/organization/projects/proj_abc/service_accounts/svc_acct_abc \\ -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Deletes a service account from the project." - } - }, - "/organization/projects/{project_id}/users": { - "get": { - "summary": "List project users", - "operationId": "list-project-users", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project users listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectUserListResponse" - } - } - } - }, - "400": { - "description": "Error response when project is archived.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ErrorResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List project users", - "group": "administration", - "returns": "A list of [ProjectUser](https://platform.openai.com/docs/api-reference/project-users/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"organization.project.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n }\n ],\n \"first_id\": \"user-abc\",\n \"last_id\": \"user-xyz\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/users?after=user_abc&limit=20 \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Returns a list of users in the project." - }, - "post": { - "summary": "Create project user", - "operationId": "create-project-user", - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "tags": [ - "Projects" - ], - "requestBody": { - "description": "The project user create request payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectUserCreateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "User added to project successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectUser" - } - } - } - }, - "400": { - "description": "Error response for various conditions.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ErrorResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create project user", - "group": "administration", - "returns": "The created [ProjectUser](https://platform.openai.com/docs/api-reference/project-users/object) object.", - "examples": { - "response": "{\n \"object\": \"organization.project.user\",\n \"id\": \"user_abc\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/users \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"user_id\": \"user_abc\",\n \"role\": \"member\"\n }'\n" - } - } - }, - "description": "Adds a user to the project. Users must already be members of the organization to be added to a project." - } - }, - "/organization/projects/{project_id}/users/{user_id}": { - "get": { - "summary": "Retrieve project user", - "operationId": "retrieve-project-user", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "user_id", - "in": "path", - "description": "The ID of the user.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project user retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectUser" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve project user", - "group": "administration", - "returns": "The [ProjectUser](https://platform.openai.com/docs/api-reference/project-users/object) object matching the specified ID.", - "examples": { - "response": "{\n \"object\": \"organization.project.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/projects/proj_abc/users/user_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Retrieves a user in the project." - }, - "post": { - "summary": "Modify project user", - "operationId": "modify-project-user", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "user_id", - "in": "path", - "description": "The ID of the user.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "requestBody": { - "description": "The project user update request payload.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectUserUpdateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Project user's role updated successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectUser" - } - } - } - }, - "400": { - "description": "Error response for various conditions.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ErrorResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify project user", - "group": "administration", - "returns": "The updated [ProjectUser](https://platform.openai.com/docs/api-reference/project-users/object) object.", - "examples": { - "response": "{\n \"object\": \"organization.project.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/users/user_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"role\": \"owner\"\n }'\n" - } - } - }, - "description": "Modifies a user's role in the project." - }, - "delete": { - "summary": "Delete project user", - "operationId": "delete-project-user", - "tags": [ - "Projects" - ], - "parameters": [ - { - "name": "project_id", - "in": "path", - "description": "The ID of the project.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "user_id", - "in": "path", - "description": "The ID of the user.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Project user deleted successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ProjectUserDeleteResponse" - } - } - } - }, - "400": { - "description": "Error response for various conditions.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ErrorResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete project user", - "group": "administration", - "returns": "Confirmation that project has been deleted or an error in case of an archived project, which has no users", - "examples": { - "response": "{\n \"object\": \"organization.project.user.deleted\",\n \"id\": \"user_abc\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/organization/projects/proj_abc/users/user_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Deletes a user from the project." - } - }, - "/organization/usage/audio_speeches": { - "get": { - "summary": "Audio speeches", - "operationId": "usage-audio-speeches", - "tags": [ - "Usage" - ], - "parameters": [ - { - "name": "start_time", - "in": "query", - "description": "Start time (Unix seconds) of the query time range, inclusive.", - "required": true, - "schema": { - "type": "integer" - } - }, - { - "name": "end_time", - "in": "query", - "description": "End time (Unix seconds) of the query time range, exclusive.", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "bucket_width", - "in": "query", - "description": "Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to `1d`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "1m", - "1h", - "1d" - ], - "default": "1d" - } - }, - { - "name": "project_ids", - "in": "query", - "description": "Return only usage for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "user_ids", - "in": "query", - "description": "Return only usage for these users.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "api_key_ids", - "in": "query", - "description": "Return only usage for these API keys.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "models", - "in": "query", - "description": "Return only usage for these models.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "group_by", - "in": "query", - "description": "Group the usage data by the specified fields. Support fields include `project_id`, `user_id`, `api_key_id`, `model` or any combination of them.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "project_id", - "user_id", - "api_key_id", - "model" - ] - } - } - }, - { - "name": "limit", - "in": "query", - "description": "Specifies the number of buckets to return.\n- `bucket_width=1d`: default: 7, max: 31\n- `bucket_width=1h`: default: 24, max: 168\n- `bucket_width=1m`: default: 60, max: 1440\n", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "page", - "in": "query", - "description": "A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Usage data retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UsageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Audio speeches", - "group": "usage-audio-speeches", - "returns": "A list of paginated, time bucketed [Audio speeches usage](https://platform.openai.com/docs/api-reference/usage/audio_speeches_object) objects.", - "examples": { - "response": "{\n \"object\": \"page\",\n \"data\": [\n {\n \"object\": \"bucket\",\n \"start_time\": 1730419200,\n \"end_time\": 1730505600,\n \"results\": [\n {\n \"object\": \"organization.usage.audio_speeches.result\",\n \"characters\": 45,\n \"num_model_requests\": 1,\n \"project_id\": null,\n \"user_id\": null,\n \"api_key_id\": null,\n \"model\": null\n }\n ]\n }\n ],\n \"has_more\": false,\n \"next_page\": null\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/usage/audio_speeches?start_time=1730419200&limit=1\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Get audio speeches usage details for the organization." - } - }, - "/organization/usage/audio_transcriptions": { - "get": { - "summary": "Audio transcriptions", - "operationId": "usage-audio-transcriptions", - "tags": [ - "Usage" - ], - "parameters": [ - { - "name": "start_time", - "in": "query", - "description": "Start time (Unix seconds) of the query time range, inclusive.", - "required": true, - "schema": { - "type": "integer" - } - }, - { - "name": "end_time", - "in": "query", - "description": "End time (Unix seconds) of the query time range, exclusive.", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "bucket_width", - "in": "query", - "description": "Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to `1d`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "1m", - "1h", - "1d" - ], - "default": "1d" - } - }, - { - "name": "project_ids", - "in": "query", - "description": "Return only usage for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "user_ids", - "in": "query", - "description": "Return only usage for these users.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "api_key_ids", - "in": "query", - "description": "Return only usage for these API keys.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "models", - "in": "query", - "description": "Return only usage for these models.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "group_by", - "in": "query", - "description": "Group the usage data by the specified fields. Support fields include `project_id`, `user_id`, `api_key_id`, `model` or any combination of them.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "project_id", - "user_id", - "api_key_id", - "model" - ] - } - } - }, - { - "name": "limit", - "in": "query", - "description": "Specifies the number of buckets to return.\n- `bucket_width=1d`: default: 7, max: 31\n- `bucket_width=1h`: default: 24, max: 168\n- `bucket_width=1m`: default: 60, max: 1440\n", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "page", - "in": "query", - "description": "A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Usage data retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UsageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Audio transcriptions", - "group": "usage-audio-transcriptions", - "returns": "A list of paginated, time bucketed [Audio transcriptions usage](https://platform.openai.com/docs/api-reference/usage/audio_transcriptions_object) objects.", - "examples": { - "response": "{\n \"object\": \"page\",\n \"data\": [\n {\n \"object\": \"bucket\",\n \"start_time\": 1730419200,\n \"end_time\": 1730505600,\n \"results\": [\n {\n \"object\": \"organization.usage.audio_transcriptions.result\",\n \"seconds\": 20,\n \"num_model_requests\": 1,\n \"project_id\": null,\n \"user_id\": null,\n \"api_key_id\": null,\n \"model\": null\n }\n ]\n }\n ],\n \"has_more\": false,\n \"next_page\": null\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/usage/audio_transcriptions?start_time=1730419200&limit=1\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Get audio transcriptions usage details for the organization." - } - }, - "/organization/usage/code_interpreter_sessions": { - "get": { - "summary": "Code interpreter sessions", - "operationId": "usage-code-interpreter-sessions", - "tags": [ - "Usage" - ], - "parameters": [ - { - "name": "start_time", - "in": "query", - "description": "Start time (Unix seconds) of the query time range, inclusive.", - "required": true, - "schema": { - "type": "integer" - } - }, - { - "name": "end_time", - "in": "query", - "description": "End time (Unix seconds) of the query time range, exclusive.", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "bucket_width", - "in": "query", - "description": "Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to `1d`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "1m", - "1h", - "1d" - ], - "default": "1d" - } - }, - { - "name": "project_ids", - "in": "query", - "description": "Return only usage for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "group_by", - "in": "query", - "description": "Group the usage data by the specified fields. Support fields include `project_id`.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "project_id" - ] - } - } - }, - { - "name": "limit", - "in": "query", - "description": "Specifies the number of buckets to return.\n- `bucket_width=1d`: default: 7, max: 31\n- `bucket_width=1h`: default: 24, max: 168\n- `bucket_width=1m`: default: 60, max: 1440\n", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "page", - "in": "query", - "description": "A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Usage data retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UsageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Code interpreter sessions", - "group": "usage-code-interpreter-sessions", - "returns": "A list of paginated, time bucketed [Code interpreter sessions usage](https://platform.openai.com/docs/api-reference/usage/code_interpreter_sessions_object) objects.", - "examples": { - "response": "{\n \"object\": \"page\",\n \"data\": [\n {\n \"object\": \"bucket\",\n \"start_time\": 1730419200,\n \"end_time\": 1730505600,\n \"results\": [\n {\n \"object\": \"organization.usage.code_interpreter_sessions.result\",\n \"num_sessions\": 1,\n \"project_id\": null\n }\n ]\n }\n ],\n \"has_more\": false,\n \"next_page\": null\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/usage/code_interpreter_sessions?start_time=1730419200&limit=1\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Get code interpreter sessions usage details for the organization." - } - }, - "/organization/usage/completions": { - "get": { - "summary": "Completions", - "operationId": "usage-completions", - "tags": [ - "Usage" - ], - "parameters": [ - { - "name": "start_time", - "in": "query", - "description": "Start time (Unix seconds) of the query time range, inclusive.", - "required": true, - "schema": { - "type": "integer" - } - }, - { - "name": "end_time", - "in": "query", - "description": "End time (Unix seconds) of the query time range, exclusive.", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "bucket_width", - "in": "query", - "description": "Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to `1d`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "1m", - "1h", - "1d" - ], - "default": "1d" - } - }, - { - "name": "project_ids", - "in": "query", - "description": "Return only usage for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "user_ids", - "in": "query", - "description": "Return only usage for these users.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "api_key_ids", - "in": "query", - "description": "Return only usage for these API keys.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "models", - "in": "query", - "description": "Return only usage for these models.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "batch", - "in": "query", - "description": "If `true`, return batch jobs only. If `false`, return non-batch jobs only. By default, return both.\n", - "required": false, - "schema": { - "type": "boolean" - } - }, - { - "name": "group_by", - "in": "query", - "description": "Group the usage data by the specified fields. Support fields include `project_id`, `user_id`, `api_key_id`, `model`, `batch` or any combination of them.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "project_id", - "user_id", - "api_key_id", - "model", - "batch" - ] - } - } - }, - { - "name": "limit", - "in": "query", - "description": "Specifies the number of buckets to return.\n- `bucket_width=1d`: default: 7, max: 31\n- `bucket_width=1h`: default: 24, max: 168\n- `bucket_width=1m`: default: 60, max: 1440\n", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "page", - "in": "query", - "description": "A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Usage data retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UsageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Completions", - "group": "usage-completions", - "returns": "A list of paginated, time bucketed [Completions usage](https://platform.openai.com/docs/api-reference/usage/completions_object) objects.", - "examples": { - "response": "{\n \"object\": \"page\",\n \"data\": [\n {\n \"object\": \"bucket\",\n \"start_time\": 1730419200,\n \"end_time\": 1730505600,\n \"results\": [\n {\n \"object\": \"organization.usage.completions.result\",\n \"input_tokens\": 1000,\n \"output_tokens\": 500,\n \"input_cached_tokens\": 800,\n \"input_audio_tokens\": 0,\n \"output_audio_tokens\": 0,\n \"num_model_requests\": 5,\n \"project_id\": null,\n \"user_id\": null,\n \"api_key_id\": null,\n \"model\": null,\n \"batch\": null\n }\n ]\n }\n ],\n \"has_more\": true,\n \"next_page\": \"page_AAAAAGdGxdEiJdKOAAAAAGcqsYA=\"\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/usage/completions?start_time=1730419200&limit=1\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Get completions usage details for the organization." - } - }, - "/organization/usage/embeddings": { - "get": { - "summary": "Embeddings", - "operationId": "usage-embeddings", - "tags": [ - "Usage" - ], - "parameters": [ - { - "name": "start_time", - "in": "query", - "description": "Start time (Unix seconds) of the query time range, inclusive.", - "required": true, - "schema": { - "type": "integer" - } - }, - { - "name": "end_time", - "in": "query", - "description": "End time (Unix seconds) of the query time range, exclusive.", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "bucket_width", - "in": "query", - "description": "Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to `1d`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "1m", - "1h", - "1d" - ], - "default": "1d" - } - }, - { - "name": "project_ids", - "in": "query", - "description": "Return only usage for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "user_ids", - "in": "query", - "description": "Return only usage for these users.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "api_key_ids", - "in": "query", - "description": "Return only usage for these API keys.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "models", - "in": "query", - "description": "Return only usage for these models.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "group_by", - "in": "query", - "description": "Group the usage data by the specified fields. Support fields include `project_id`, `user_id`, `api_key_id`, `model` or any combination of them.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "project_id", - "user_id", - "api_key_id", - "model" - ] - } - } - }, - { - "name": "limit", - "in": "query", - "description": "Specifies the number of buckets to return.\n- `bucket_width=1d`: default: 7, max: 31\n- `bucket_width=1h`: default: 24, max: 168\n- `bucket_width=1m`: default: 60, max: 1440\n", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "page", - "in": "query", - "description": "A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Usage data retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UsageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Embeddings", - "group": "usage-embeddings", - "returns": "A list of paginated, time bucketed [Embeddings usage](https://platform.openai.com/docs/api-reference/usage/embeddings_object) objects.", - "examples": { - "response": "{\n \"object\": \"page\",\n \"data\": [\n {\n \"object\": \"bucket\",\n \"start_time\": 1730419200,\n \"end_time\": 1730505600,\n \"results\": [\n {\n \"object\": \"organization.usage.embeddings.result\",\n \"input_tokens\": 16,\n \"num_model_requests\": 2,\n \"project_id\": null,\n \"user_id\": null,\n \"api_key_id\": null,\n \"model\": null\n }\n ]\n }\n ],\n \"has_more\": false,\n \"next_page\": null\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/usage/embeddings?start_time=1730419200&limit=1\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Get embeddings usage details for the organization." - } - }, - "/organization/usage/images": { - "get": { - "summary": "Images", - "operationId": "usage-images", - "tags": [ - "Usage" - ], - "parameters": [ - { - "name": "start_time", - "in": "query", - "description": "Start time (Unix seconds) of the query time range, inclusive.", - "required": true, - "schema": { - "type": "integer" - } - }, - { - "name": "end_time", - "in": "query", - "description": "End time (Unix seconds) of the query time range, exclusive.", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "bucket_width", - "in": "query", - "description": "Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to `1d`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "1m", - "1h", - "1d" - ], - "default": "1d" - } - }, - { - "name": "sources", - "in": "query", - "description": "Return only usages for these sources. Possible values are `image.generation`, `image.edit`, `image.variation` or any combination of them.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "image.generation", - "image.edit", - "image.variation" - ] - } - } - }, - { - "name": "sizes", - "in": "query", - "description": "Return only usages for these image sizes. Possible values are `256x256`, `512x512`, `1024x1024`, `1792x1792`, `1024x1792` or any combination of them.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "256x256", - "512x512", - "1024x1024", - "1792x1792", - "1024x1792" - ] - } - } - }, - { - "name": "project_ids", - "in": "query", - "description": "Return only usage for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "user_ids", - "in": "query", - "description": "Return only usage for these users.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "api_key_ids", - "in": "query", - "description": "Return only usage for these API keys.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "models", - "in": "query", - "description": "Return only usage for these models.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "group_by", - "in": "query", - "description": "Group the usage data by the specified fields. Support fields include `project_id`, `user_id`, `api_key_id`, `model`, `size`, `source` or any combination of them.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "project_id", - "user_id", - "api_key_id", - "model", - "size", - "source" - ] - } - } - }, - { - "name": "limit", - "in": "query", - "description": "Specifies the number of buckets to return.\n- `bucket_width=1d`: default: 7, max: 31\n- `bucket_width=1h`: default: 24, max: 168\n- `bucket_width=1m`: default: 60, max: 1440\n", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "page", - "in": "query", - "description": "A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Usage data retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UsageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Images", - "group": "usage-images", - "returns": "A list of paginated, time bucketed [Images usage](https://platform.openai.com/docs/api-reference/usage/images_object) objects.", - "examples": { - "response": "{\n \"object\": \"page\",\n \"data\": [\n {\n \"object\": \"bucket\",\n \"start_time\": 1730419200,\n \"end_time\": 1730505600,\n \"results\": [\n {\n \"object\": \"organization.usage.images.result\",\n \"images\": 2,\n \"num_model_requests\": 2,\n \"size\": null,\n \"source\": null,\n \"project_id\": null,\n \"user_id\": null,\n \"api_key_id\": null,\n \"model\": null\n }\n ]\n }\n ],\n \"has_more\": false,\n \"next_page\": null\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/usage/images?start_time=1730419200&limit=1\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Get images usage details for the organization." - } - }, - "/organization/usage/moderations": { - "get": { - "summary": "Moderations", - "operationId": "usage-moderations", - "tags": [ - "Usage" - ], - "parameters": [ - { - "name": "start_time", - "in": "query", - "description": "Start time (Unix seconds) of the query time range, inclusive.", - "required": true, - "schema": { - "type": "integer" - } - }, - { - "name": "end_time", - "in": "query", - "description": "End time (Unix seconds) of the query time range, exclusive.", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "bucket_width", - "in": "query", - "description": "Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to `1d`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "1m", - "1h", - "1d" - ], - "default": "1d" - } - }, - { - "name": "project_ids", - "in": "query", - "description": "Return only usage for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "user_ids", - "in": "query", - "description": "Return only usage for these users.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "api_key_ids", - "in": "query", - "description": "Return only usage for these API keys.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "models", - "in": "query", - "description": "Return only usage for these models.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "group_by", - "in": "query", - "description": "Group the usage data by the specified fields. Support fields include `project_id`, `user_id`, `api_key_id`, `model` or any combination of them.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "project_id", - "user_id", - "api_key_id", - "model" - ] - } - } - }, - { - "name": "limit", - "in": "query", - "description": "Specifies the number of buckets to return.\n- `bucket_width=1d`: default: 7, max: 31\n- `bucket_width=1h`: default: 24, max: 168\n- `bucket_width=1m`: default: 60, max: 1440\n", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "page", - "in": "query", - "description": "A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Usage data retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UsageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Moderations", - "group": "usage-moderations", - "returns": "A list of paginated, time bucketed [Moderations usage](https://platform.openai.com/docs/api-reference/usage/moderations_object) objects.", - "examples": { - "response": "{\n \"object\": \"page\",\n \"data\": [\n {\n \"object\": \"bucket\",\n \"start_time\": 1730419200,\n \"end_time\": 1730505600,\n \"results\": [\n {\n \"object\": \"organization.usage.moderations.result\",\n \"input_tokens\": 16,\n \"num_model_requests\": 2,\n \"project_id\": null,\n \"user_id\": null,\n \"api_key_id\": null,\n \"model\": null\n }\n ]\n }\n ],\n \"has_more\": false,\n \"next_page\": null\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/usage/moderations?start_time=1730419200&limit=1\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Get moderations usage details for the organization." - } - }, - "/organization/usage/vector_stores": { - "get": { - "summary": "Vector stores", - "operationId": "usage-vector-stores", - "tags": [ - "Usage" - ], - "parameters": [ - { - "name": "start_time", - "in": "query", - "description": "Start time (Unix seconds) of the query time range, inclusive.", - "required": true, - "schema": { - "type": "integer" - } - }, - { - "name": "end_time", - "in": "query", - "description": "End time (Unix seconds) of the query time range, exclusive.", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "bucket_width", - "in": "query", - "description": "Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to `1d`.", - "required": false, - "schema": { - "type": "string", - "enum": [ - "1m", - "1h", - "1d" - ], - "default": "1d" - } - }, - { - "name": "project_ids", - "in": "query", - "description": "Return only usage for these projects.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - }, - { - "name": "group_by", - "in": "query", - "description": "Group the usage data by the specified fields. Support fields include `project_id`.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "project_id" - ] - } - } - }, - { - "name": "limit", - "in": "query", - "description": "Specifies the number of buckets to return.\n- `bucket_width=1d`: default: 7, max: 31\n- `bucket_width=1h`: default: 24, max: 168\n- `bucket_width=1m`: default: 60, max: 1440\n", - "required": false, - "schema": { - "type": "integer" - } - }, - { - "name": "page", - "in": "query", - "description": "A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "Usage data retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UsageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Vector stores", - "group": "usage-vector-stores", - "returns": "A list of paginated, time bucketed [Vector stores usage](https://platform.openai.com/docs/api-reference/usage/vector_stores_object) objects.", - "examples": { - "response": "{\n \"object\": \"page\",\n \"data\": [\n {\n \"object\": \"bucket\",\n \"start_time\": 1730419200,\n \"end_time\": 1730505600,\n \"results\": [\n {\n \"object\": \"organization.usage.vector_stores.result\",\n \"usage_bytes\": 1024,\n \"project_id\": null\n }\n ]\n }\n ],\n \"has_more\": false,\n \"next_page\": null\n}\n", - "request": { - "curl": "curl \"https://api.openai.com/v1/organization/usage/vector_stores?start_time=1730419200&limit=1\" \\\n-H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n-H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Get vector stores usage details for the organization." - } - }, - "/organization/users": { - "get": { - "summary": "List users", - "operationId": "list-users", - "tags": [ - "Users" - ], - "parameters": [ - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "required": false, - "schema": { - "type": "string" - } - }, - { - "name": "emails", - "in": "query", - "description": "Filter by the email address of users.", - "required": false, - "schema": { - "type": "array", - "items": { - "type": "string" - } - } - } - ], - "responses": { - "200": { - "description": "Users listed successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UserListResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List users", - "group": "administration", - "returns": "A list of [User](https://platform.openai.com/docs/api-reference/users/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"organization.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n }\n ],\n \"first_id\": \"user-abc\",\n \"last_id\": \"user-xyz\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/users?after=user_abc&limit=20 \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Lists all of the users in the organization." - } - }, - "/organization/users/{user_id}": { - "get": { - "summary": "Retrieve user", - "operationId": "retrieve-user", - "tags": [ - "Users" - ], - "parameters": [ - { - "name": "user_id", - "in": "path", - "description": "The ID of the user.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "User retrieved successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/User" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve user", - "group": "administration", - "returns": "The [User](https://platform.openai.com/docs/api-reference/users/object) object matching the specified ID.", - "examples": { - "response": "{\n \"object\": \"organization.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/organization/users/user_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Retrieves a user by their identifier." - }, - "post": { - "summary": "Modify user", - "operationId": "modify-user", - "tags": [ - "Users" - ], - "parameters": [ - { - "name": "user_id", - "in": "path", - "description": "The ID of the user.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "requestBody": { - "description": "The new user role to modify. This must be one of `owner` or `member`.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UserRoleUpdateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "User role updated successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/User" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify user", - "group": "administration", - "returns": "The updated [User](https://platform.openai.com/docs/api-reference/users/object) object.", - "examples": { - "response": "{\n \"object\": \"organization.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/organization/users/user_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"role\": \"owner\"\n }'\n" - } - } - }, - "description": "Modifies a user's role in the organization." - }, - "delete": { - "summary": "Delete user", - "operationId": "delete-user", - "tags": [ - "Users" - ], - "parameters": [ - { - "name": "user_id", - "in": "path", - "description": "The ID of the user.", - "required": true, - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "User deleted successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UserDeleteResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete user", - "group": "administration", - "returns": "Confirmation of the deleted user", - "examples": { - "response": "{\n \"object\": \"organization.user.deleted\",\n \"id\": \"user_abc\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/organization/users/user_abc \\\n -H \"Authorization: Bearer $OPENAI_ADMIN_KEY\" \\\n -H \"Content-Type: application/json\"\n" - } - } - }, - "description": "Deletes a user from the organization." - } - }, - "/realtime/client_secrets": { - "post": { - "summary": "Create realtime session", - "operationId": "create-realtime-client-secret", - "tags": [ - "Realtime" - ], - "requestBody": { - "description": "Create a client secret with the given session configuration.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RealtimeCreateClientSecretRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Client secret created successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RealtimeCreateClientSecretResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create realtime session", - "group": "realtime", - "returns": "The created client secret and the effective session object", - "examples": { - "response": "{\n \"value\": \"ek_68af296e8e408191a1120ab6383263c2\",\n \"expires_at\": 1756310470,\n \"session\": {\n \"type\": \"realtime\",\n \"object\": \"realtime.session\",\n \"id\": \"sess_C9CiUVUzUzYIssh3ELY1d\",\n \"model\": \"gpt-realtime\",\n \"output_modalities\": [\n \"audio\"\n ],\n \"instructions\": \"You are a friendly assistant.\",\n \"tools\": [],\n \"tool_choice\": \"auto\",\n \"max_output_tokens\": \"inf\",\n \"tracing\": null,\n \"truncation\": \"auto\",\n \"prompt\": null,\n \"expires_at\": 0,\n \"audio\": {\n \"input\": {\n \"format\": {\n \"type\": \"audio/pcm\",\n \"rate\": 24000\n },\n \"transcription\": null,\n \"noise_reduction\": null,\n \"turn_detection\": {\n \"type\": \"server_vad\",\n \"threshold\": 0.5,\n \"prefix_padding_ms\": 300,\n \"silence_duration_ms\": 200,\n \"idle_timeout_ms\": null,\n \"create_response\": true,\n \"interrupt_response\": true\n }\n },\n \"output\": {\n \"format\": {\n \"type\": \"audio/pcm\",\n \"rate\": 24000\n },\n \"voice\": \"alloy\",\n \"speed\": 1.0\n }\n },\n \"include\": null\n }\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/realtime/client_secrets \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"expires_after\": { \"anchor\": \"created_at\", \"seconds\": 600 },\n \"session\": {\n \"type\": \"realtime\",\n \"model\": \"gpt-realtime\",\n \"instructions\": \"You are a friendly assistant.\"\n }\n }'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst clientSecret = await client.realtime.clientSecrets.create();\n\nconsole.log(clientSecret.expires_at);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nclient_secret = client.realtime.client_secrets.create()\nprint(client_secret.expires_at)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/realtime\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n clientSecret, err := client.Realtime.ClientSecrets.New(context.TODO(), realtime.ClientSecretNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", clientSecret.ExpiresAt)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.realtime.clientsecrets.ClientSecretCreateParams;\nimport com.openai.models.realtime.clientsecrets.ClientSecretCreateResponse;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ClientSecretCreateResponse clientSecret = client.realtime().clientSecrets().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nclient_secret = openai.realtime.client_secrets.create\n\nputs(client_secret)" - } - } - }, - "description": "Create a Realtime session and client secret for either realtime or transcription.\n" - } - }, - "/realtime/sessions": { - "post": { - "summary": "Create session", - "operationId": "create-realtime-session", - "tags": [ - "Realtime" - ], - "requestBody": { - "description": "Create an ephemeral API key with the given session configuration.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RealtimeSessionCreateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Session created successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RealtimeSessionCreateResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create session", - "group": "realtime", - "returns": "The created Realtime session object, plus an ephemeral key", - "examples": { - "request": { - "curl": "curl -X POST https://api.openai.com/v1/realtime/sessions \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"gpt-4o-realtime-preview\",\n \"modalities\": [\"audio\", \"text\"],\n \"instructions\": \"You are a friendly assistant.\"\n }'\n" - }, - "response": "{\n \"id\": \"sess_001\",\n \"object\": \"realtime.session\",\n \"model\": \"gpt-4o-realtime-preview\",\n \"modalities\": [\"audio\", \"text\"],\n \"instructions\": \"You are a friendly assistant.\",\n \"voice\": \"alloy\",\n \"input_audio_format\": \"pcm16\",\n \"output_audio_format\": \"pcm16\",\n \"input_audio_transcription\": {\n \"model\": \"whisper-1\"\n },\n \"turn_detection\": null,\n \"tools\": [],\n \"tool_choice\": \"none\",\n \"temperature\": 0.7,\n \"max_response_output_tokens\": 200,\n \"speed\": 1.1,\n \"tracing\": \"auto\",\n \"client_secret\": {\n \"value\": \"ek_abc123\", \n \"expires_at\": 1234567890\n }\n}\n" - } - }, - "description": "Create an ephemeral API token for use in client-side applications with the\nRealtime API. Can be configured with the same session parameters as the\n`session.update` client event.\n\nIt responds with a session object, plus a `client_secret` key which contains\na usable ephemeral API token that can be used to authenticate browser clients\nfor the Realtime API.\n" - } - }, - "/realtime/transcription_sessions": { - "post": { - "summary": "Create transcription session", - "operationId": "create-realtime-transcription-session", - "tags": [ - "Realtime" - ], - "requestBody": { - "description": "Create an ephemeral API key with the given session configuration.", - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RealtimeTranscriptionSessionCreateRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Session created successfully.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RealtimeTranscriptionSessionCreateResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create transcription session", - "group": "realtime", - "returns": "The created [Realtime transcription session object](https://platform.openai.com/docs/api-reference/realtime-sessions/transcription_session_object), plus an ephemeral key", - "examples": { - "request": { - "curl": "curl -X POST https://api.openai.com/v1/realtime/transcription_sessions \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{}'\n" - }, - "response": "{\n \"id\": \"sess_BBwZc7cFV3XizEyKGDCGL\",\n \"object\": \"realtime.transcription_session\",\n \"modalities\": [\"audio\", \"text\"],\n \"turn_detection\": {\n \"type\": \"server_vad\",\n \"threshold\": 0.5,\n \"prefix_padding_ms\": 300,\n \"silence_duration_ms\": 200\n },\n \"input_audio_format\": \"pcm16\",\n \"input_audio_transcription\": {\n \"model\": \"gpt-4o-transcribe\",\n \"language\": null,\n \"prompt\": \"\"\n },\n \"client_secret\": null\n}\n" - } - }, - "description": "Create an ephemeral API token for use in client-side applications with the\nRealtime API specifically for realtime transcriptions. \nCan be configured with the same session parameters as the `transcription_session.update` client event.\n\nIt responds with a session object, plus a `client_secret` key which contains\na usable ephemeral API token that can be used to authenticate browser clients\nfor the Realtime API.\n" - } - }, - "/responses": { - "post": { - "operationId": "createResponse", - "tags": [ - "Responses" - ], - "summary": "Create a model response", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateResponse" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Response" - } - }, - "text/event-stream": { - "schema": { - "$ref": "#/components/schemas/ResponseStreamEvent" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create a model response", - "group": "responses", - "returns": "Returns a [Response](https://platform.openai.com/docs/api-reference/responses/object) object.\n", - "path": "create", - "examples": [ - { - "title": "Text input", - "request": { - "curl": "curl https://api.openai.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-4.1\",\n \"input\": \"Tell me a three sentence bedtime story about a unicorn.\"\n }'\n", - "javascript": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nconst response = await openai.responses.create({\n model: \"gpt-4.1\",\n input: \"Tell me a three sentence bedtime story about a unicorn.\"\n});\n\nconsole.log(response);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.create()\nprint(response.id)", - "csharp": "using System;\nusing OpenAI.Responses;\n\nOpenAIResponseClient client = new( model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nOpenAIResponse response = client.CreateResponse(\"Tell me a three sentence bedtime story about a unicorn.\");\n\nConsole.WriteLine(response.GetOutputText());\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.create();\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.create\n\nputs(response)" - }, - "response": "{\n \"id\": \"resp_67ccd2bed1ec8190b14f964abc0542670bb6a6b452d3795b\",\n \"object\": \"response\",\n \"created_at\": 1741476542,\n \"status\": \"completed\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4.1-2025-04-14\",\n \"output\": [\n {\n \"type\": \"message\",\n \"id\": \"msg_67ccd2bf17f0819081ff3bb2cf6508e60bb6a6b452d3795b\",\n \"status\": \"completed\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"In a peaceful grove beneath a silver moon, a unicorn named Lumina discovered a hidden pool that reflected the stars. As she dipped her horn into the water, the pool began to shimmer, revealing a pathway to a magical realm of endless night skies. Filled with wonder, Lumina whispered a wish for all who dream to find their own hidden magic, and as she glanced back, her hoofprints sparkled like stardust.\",\n \"annotations\": []\n }\n ]\n }\n ],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 36,\n \"input_tokens_details\": {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 87,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 123\n },\n \"user\": null,\n \"metadata\": {}\n}\n" - }, - { - "title": "Image input", - "request": { - "curl": "curl https://api.openai.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-4.1\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"input_text\", \"text\": \"what is in this image?\"},\n {\n \"type\": \"input_image\",\n \"image_url\": \"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg\"\n }\n ]\n }\n ]\n }'\n", - "javascript": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nconst response = await openai.responses.create({\n model: \"gpt-4.1\",\n input: [\n {\n role: \"user\",\n content: [\n { type: \"input_text\", text: \"what is in this image?\" },\n {\n type: \"input_image\",\n image_url:\n \"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg\",\n },\n ],\n },\n ],\n});\n\nconsole.log(response);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.create()\nprint(response.id)", - "csharp": "using System;\nusing System.Collections.Generic;\n\nusing OpenAI.Responses;\n\nOpenAIResponseClient client = new(\n model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nList inputItems =\n[\n ResponseItem.CreateUserMessageItem(\n [\n ResponseContentPart.CreateInputTextPart(\"What is in this image?\"),\n ResponseContentPart.CreateInputImagePart(new Uri(\"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg\"))\n ]\n )\n];\n\nOpenAIResponse response = client.CreateResponse(inputItems);\n\nConsole.WriteLine(response.GetOutputText());\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.create();\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.create\n\nputs(response)" - }, - "response": "{\n \"id\": \"resp_67ccd3a9da748190baa7f1570fe91ac604becb25c45c1d41\",\n \"object\": \"response\",\n \"created_at\": 1741476777,\n \"status\": \"completed\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4.1-2025-04-14\",\n \"output\": [\n {\n \"type\": \"message\",\n \"id\": \"msg_67ccd3acc8d48190a77525dc6de64b4104becb25c45c1d41\",\n \"status\": \"completed\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"The image depicts a scenic landscape with a wooden boardwalk or pathway leading through lush, green grass under a blue sky with some clouds. The setting suggests a peaceful natural area, possibly a park or nature reserve. There are trees and shrubs in the background.\",\n \"annotations\": []\n }\n ]\n }\n ],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 328,\n \"input_tokens_details\": {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 52,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 380\n },\n \"user\": null,\n \"metadata\": {}\n}\n" - }, - { - "title": "File input", - "request": { - "curl": "curl https://api.openai.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-4.1\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"input_text\", \"text\": \"what is in this file?\"},\n {\n \"type\": \"input_file\",\n \"file_url\": \"https://www.berkshirehathaway.com/letters/2024ltr.pdf\"\n }\n ]\n }\n ]\n }'\n", - "javascript": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nconst response = await openai.responses.create({\n model: \"gpt-4.1\",\n input: [\n {\n role: \"user\",\n content: [\n { type: \"input_text\", text: \"what is in this file?\" },\n {\n type: \"input_file\",\n file_url: \"https://www.berkshirehathaway.com/letters/2024ltr.pdf\",\n },\n ],\n },\n ],\n});\n\nconsole.log(response);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.create()\nprint(response.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.create();\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.create\n\nputs(response)" - }, - "response": "{\n \"id\": \"resp_686eef60237881a2bd1180bb8b13de430e34c516d176ff86\",\n \"object\": \"response\",\n \"created_at\": 1752100704,\n \"status\": \"completed\",\n \"background\": false,\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"max_tool_calls\": null,\n \"model\": \"gpt-4.1-2025-04-14\",\n \"output\": [\n {\n \"id\": \"msg_686eef60d3e081a29283bdcbc4322fd90e34c516d176ff86\",\n \"type\": \"message\",\n \"status\": \"completed\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"annotations\": [],\n \"logprobs\": [],\n \"text\": \"The file seems to contain excerpts from a letter to the shareholders of Berkshire Hathaway Inc., likely written by Warren Buffett. It covers several topics:\\n\\n1. **Communication Philosophy**: Buffett emphasizes the importance of transparency and candidness in reporting mistakes and successes to shareholders.\\n\\n2. **Mistakes and Learnings**: The letter acknowledges past mistakes in business assessments and management hires, highlighting the importance of correcting errors promptly.\\n\\n3. **CEO Succession**: Mention of Greg Abel stepping in as the new CEO and continuing the tradition of honest communication.\\n\\n4. **Pete Liegl Story**: A detailed account of acquiring Forest River and the relationship with its founder, highlighting trust and effective business decisions.\\n\\n5. **2024 Performance**: Overview of business performance, particularly in insurance and investment activities, with a focus on GEICO's improvement.\\n\\n6. **Tax Contributions**: Discussion of significant tax payments to the U.S. Treasury, credited to shareholders' reinvestments.\\n\\n7. **Investment Strategy**: A breakdown of Berkshire\\u2019s investments in both controlled subsidiaries and marketable equities, along with a focus on long-term holding strategies.\\n\\n8. **American Capitalism**: Reflections on America\\u2019s economic development and Berkshire\\u2019s role within it.\\n\\n9. **Property-Casualty Insurance**: Insights into the P/C insurance business model and its challenges and benefits.\\n\\n10. **Japanese Investments**: Information about Berkshire\\u2019s investments in Japanese companies and future plans.\\n\\n11. **Annual Meeting**: Details about the upcoming annual gathering in Omaha, including schedule changes and new book releases.\\n\\n12. **Personal Anecdotes**: Light-hearted stories about family and interactions, conveying Buffett's personable approach.\\n\\n13. **Financial Performance Data**: Tables comparing Berkshire\\u2019s annual performance to the S&P 500, showing impressive long-term gains.\\n\\nOverall, the letter reinforces Berkshire Hathaway's commitment to transparency, investment in both its businesses and the wider economy, and emphasizes strong leadership and prudent financial management.\"\n }\n ],\n \"role\": \"assistant\"\n }\n ],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"service_tier\": \"default\",\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_logprobs\": 0,\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 8438,\n \"input_tokens_details\": {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 398,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 8836\n },\n \"user\": null,\n \"metadata\": {}\n}\n" - }, - { - "title": "Web search", - "request": { - "curl": "curl https://api.openai.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-4.1\",\n \"tools\": [{ \"type\": \"web_search_preview\" }],\n \"input\": \"What was a positive news story from today?\"\n }'\n", - "javascript": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nconst response = await openai.responses.create({\n model: \"gpt-4.1\",\n tools: [{ type: \"web_search_preview\" }],\n input: \"What was a positive news story from today?\",\n});\n\nconsole.log(response);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.create()\nprint(response.id)", - "csharp": "using System;\n\nusing OpenAI.Responses;\n\nOpenAIResponseClient client = new(\n model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nstring userInputText = \"What was a positive news story from today?\";\n\nResponseCreationOptions options = new()\n{\n Tools =\n {\n ResponseTool.CreateWebSearchTool()\n },\n};\n\nOpenAIResponse response = client.CreateResponse(userInputText, options);\n\nConsole.WriteLine(response.GetOutputText());\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.create();\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.create\n\nputs(response)" - }, - "response": "{\n \"id\": \"resp_67ccf18ef5fc8190b16dbee19bc54e5f087bb177ab789d5c\",\n \"object\": \"response\",\n \"created_at\": 1741484430,\n \"status\": \"completed\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4.1-2025-04-14\",\n \"output\": [\n {\n \"type\": \"web_search_call\",\n \"id\": \"ws_67ccf18f64008190a39b619f4c8455ef087bb177ab789d5c\",\n \"status\": \"completed\"\n },\n {\n \"type\": \"message\",\n \"id\": \"msg_67ccf190ca3881909d433c50b1f6357e087bb177ab789d5c\",\n \"status\": \"completed\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"As of today, March 9, 2025, one notable positive news story...\",\n \"annotations\": [\n {\n \"type\": \"url_citation\",\n \"start_index\": 442,\n \"end_index\": 557,\n \"url\": \"https://.../?utm_source=chatgpt.com\",\n \"title\": \"...\"\n },\n {\n \"type\": \"url_citation\",\n \"start_index\": 962,\n \"end_index\": 1077,\n \"url\": \"https://.../?utm_source=chatgpt.com\",\n \"title\": \"...\"\n },\n {\n \"type\": \"url_citation\",\n \"start_index\": 1336,\n \"end_index\": 1451,\n \"url\": \"https://.../?utm_source=chatgpt.com\",\n \"title\": \"...\"\n }\n ]\n }\n ]\n }\n ],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"web_search_preview\",\n \"domains\": [],\n \"search_context_size\": \"medium\",\n \"user_location\": {\n \"type\": \"approximate\",\n \"city\": null,\n \"country\": \"US\",\n \"region\": null,\n \"timezone\": null\n }\n }\n ],\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 328,\n \"input_tokens_details\": {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 356,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 684\n },\n \"user\": null,\n \"metadata\": {}\n}\n" - }, - { - "title": "File search", - "request": { - "curl": "curl https://api.openai.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-4.1\",\n \"tools\": [{\n \"type\": \"file_search\",\n \"vector_store_ids\": [\"vs_1234567890\"],\n \"max_num_results\": 20\n }],\n \"input\": \"What are the attributes of an ancient brown dragon?\"\n }'\n", - "javascript": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nconst response = await openai.responses.create({\n model: \"gpt-4.1\",\n tools: [{\n type: \"file_search\",\n vector_store_ids: [\"vs_1234567890\"],\n max_num_results: 20\n }],\n input: \"What are the attributes of an ancient brown dragon?\",\n});\n\nconsole.log(response);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.create()\nprint(response.id)", - "csharp": "using System;\n\nusing OpenAI.Responses;\n\nOpenAIResponseClient client = new(\n model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nstring userInputText = \"What are the attributes of an ancient brown dragon?\";\n\nResponseCreationOptions options = new()\n{\n Tools =\n {\n ResponseTool.CreateFileSearchTool(\n vectorStoreIds: [\"vs_1234567890\"],\n maxResultCount: 20\n )\n },\n};\n\nOpenAIResponse response = client.CreateResponse(userInputText, options);\n\nConsole.WriteLine(response.GetOutputText());\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.create();\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.create\n\nputs(response)" - }, - "response": "{\n \"id\": \"resp_67ccf4c55fc48190b71bd0463ad3306d09504fb6872380d7\",\n \"object\": \"response\",\n \"created_at\": 1741485253,\n \"status\": \"completed\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4.1-2025-04-14\",\n \"output\": [\n {\n \"type\": \"file_search_call\",\n \"id\": \"fs_67ccf4c63cd08190887ef6464ba5681609504fb6872380d7\",\n \"status\": \"completed\",\n \"queries\": [\n \"attributes of an ancient brown dragon\"\n ],\n \"results\": null\n },\n {\n \"type\": \"message\",\n \"id\": \"msg_67ccf4c93e5c81909d595b369351a9d309504fb6872380d7\",\n \"status\": \"completed\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"The attributes of an ancient brown dragon include...\",\n \"annotations\": [\n {\n \"type\": \"file_citation\",\n \"index\": 320,\n \"file_id\": \"file-4wDz5b167pAf72nx1h9eiN\",\n \"filename\": \"dragons.pdf\"\n },\n {\n \"type\": \"file_citation\",\n \"index\": 576,\n \"file_id\": \"file-4wDz5b167pAf72nx1h9eiN\",\n \"filename\": \"dragons.pdf\"\n },\n {\n \"type\": \"file_citation\",\n \"index\": 815,\n \"file_id\": \"file-4wDz5b167pAf72nx1h9eiN\",\n \"filename\": \"dragons.pdf\"\n },\n {\n \"type\": \"file_citation\",\n \"index\": 815,\n \"file_id\": \"file-4wDz5b167pAf72nx1h9eiN\",\n \"filename\": \"dragons.pdf\"\n },\n {\n \"type\": \"file_citation\",\n \"index\": 1030,\n \"file_id\": \"file-4wDz5b167pAf72nx1h9eiN\",\n \"filename\": \"dragons.pdf\"\n },\n {\n \"type\": \"file_citation\",\n \"index\": 1030,\n \"file_id\": \"file-4wDz5b167pAf72nx1h9eiN\",\n \"filename\": \"dragons.pdf\"\n },\n {\n \"type\": \"file_citation\",\n \"index\": 1156,\n \"file_id\": \"file-4wDz5b167pAf72nx1h9eiN\",\n \"filename\": \"dragons.pdf\"\n },\n {\n \"type\": \"file_citation\",\n \"index\": 1225,\n \"file_id\": \"file-4wDz5b167pAf72nx1h9eiN\",\n \"filename\": \"dragons.pdf\"\n }\n ]\n }\n ]\n }\n ],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"file_search\",\n \"filters\": null,\n \"max_num_results\": 20,\n \"ranking_options\": {\n \"ranker\": \"auto\",\n \"score_threshold\": 0.0\n },\n \"vector_store_ids\": [\n \"vs_1234567890\"\n ]\n }\n ],\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 18307,\n \"input_tokens_details\": {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 348,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 18655\n },\n \"user\": null,\n \"metadata\": {}\n}\n" - }, - { - "title": "Streaming", - "request": { - "curl": "curl https://api.openai.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-4.1\",\n \"instructions\": \"You are a helpful assistant.\",\n \"input\": \"Hello!\",\n \"stream\": true\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.create()\nprint(response.id)", - "javascript": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nconst response = await openai.responses.create({\n model: \"gpt-4.1\",\n instructions: \"You are a helpful assistant.\",\n input: \"Hello!\",\n stream: true,\n});\n\nfor await (const event of response) {\n console.log(event);\n}\n", - "csharp": "using System;\nusing System.ClientModel;\nusing System.Threading.Tasks;\n\nusing OpenAI.Responses;\n\nOpenAIResponseClient client = new( model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nstring userInputText = \"Hello!\";\n\nResponseCreationOptions options = new()\n{ Instructions = \"You are a helpful assistant.\",\n};\n\nAsyncCollectionResult responseUpdates = client.CreateResponseStreamingAsync(userInputText, options);\n\nawait foreach (StreamingResponseUpdate responseUpdate in responseUpdates)\n{ if (responseUpdate is StreamingResponseOutputTextDeltaUpdate outputTextDeltaUpdate)\n {\n Console.Write(outputTextDeltaUpdate.Delta);\n }\n}\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.create();\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.create\n\nputs(response)" - }, - "response": "event: response.created\ndata: {\"type\":\"response.created\",\"response\":{\"id\":\"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654\",\"object\":\"response\",\"created_at\":1741290958,\"status\":\"in_progress\",\"error\":null,\"incomplete_details\":null,\"instructions\":\"You are a helpful assistant.\",\"max_output_tokens\":null,\"model\":\"gpt-4.1-2025-04-14\",\"output\":[],\"parallel_tool_calls\":true,\"previous_response_id\":null,\"reasoning\":{\"effort\":null,\"summary\":null},\"store\":true,\"temperature\":1.0,\"text\":{\"format\":{\"type\":\"text\"}},\"tool_choice\":\"auto\",\"tools\":[],\"top_p\":1.0,\"truncation\":\"disabled\",\"usage\":null,\"user\":null,\"metadata\":{}}}\n\nevent: response.in_progress\ndata: {\"type\":\"response.in_progress\",\"response\":{\"id\":\"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654\",\"object\":\"response\",\"created_at\":1741290958,\"status\":\"in_progress\",\"error\":null,\"incomplete_details\":null,\"instructions\":\"You are a helpful assistant.\",\"max_output_tokens\":null,\"model\":\"gpt-4.1-2025-04-14\",\"output\":[],\"parallel_tool_calls\":true,\"previous_response_id\":null,\"reasoning\":{\"effort\":null,\"summary\":null},\"store\":true,\"temperature\":1.0,\"text\":{\"format\":{\"type\":\"text\"}},\"tool_choice\":\"auto\",\"tools\":[],\"top_p\":1.0,\"truncation\":\"disabled\",\"usage\":null,\"user\":null,\"metadata\":{}}}\n\nevent: response.output_item.added\ndata: {\"type\":\"response.output_item.added\",\"output_index\":0,\"item\":{\"id\":\"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654\",\"type\":\"message\",\"status\":\"in_progress\",\"role\":\"assistant\",\"content\":[]}}\n\nevent: response.content_part.added\ndata: {\"type\":\"response.content_part.added\",\"item_id\":\"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654\",\"output_index\":0,\"content_index\":0,\"part\":{\"type\":\"output_text\",\"text\":\"\",\"annotations\":[]}}\n\nevent: response.output_text.delta\ndata: {\"type\":\"response.output_text.delta\",\"item_id\":\"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654\",\"output_index\":0,\"content_index\":0,\"delta\":\"Hi\"}\n\n...\n\nevent: response.output_text.done\ndata: {\"type\":\"response.output_text.done\",\"item_id\":\"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654\",\"output_index\":0,\"content_index\":0,\"text\":\"Hi there! How can I assist you today?\"}\n\nevent: response.content_part.done\ndata: {\"type\":\"response.content_part.done\",\"item_id\":\"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654\",\"output_index\":0,\"content_index\":0,\"part\":{\"type\":\"output_text\",\"text\":\"Hi there! How can I assist you today?\",\"annotations\":[]}}\n\nevent: response.output_item.done\ndata: {\"type\":\"response.output_item.done\",\"output_index\":0,\"item\":{\"id\":\"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654\",\"type\":\"message\",\"status\":\"completed\",\"role\":\"assistant\",\"content\":[{\"type\":\"output_text\",\"text\":\"Hi there! How can I assist you today?\",\"annotations\":[]}]}}\n\nevent: response.completed\ndata: {\"type\":\"response.completed\",\"response\":{\"id\":\"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654\",\"object\":\"response\",\"created_at\":1741290958,\"status\":\"completed\",\"error\":null,\"incomplete_details\":null,\"instructions\":\"You are a helpful assistant.\",\"max_output_tokens\":null,\"model\":\"gpt-4.1-2025-04-14\",\"output\":[{\"id\":\"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654\",\"type\":\"message\",\"status\":\"completed\",\"role\":\"assistant\",\"content\":[{\"type\":\"output_text\",\"text\":\"Hi there! How can I assist you today?\",\"annotations\":[]}]}],\"parallel_tool_calls\":true,\"previous_response_id\":null,\"reasoning\":{\"effort\":null,\"summary\":null},\"store\":true,\"temperature\":1.0,\"text\":{\"format\":{\"type\":\"text\"}},\"tool_choice\":\"auto\",\"tools\":[],\"top_p\":1.0,\"truncation\":\"disabled\",\"usage\":{\"input_tokens\":37,\"output_tokens\":11,\"output_tokens_details\":{\"reasoning_tokens\":0},\"total_tokens\":48},\"user\":null,\"metadata\":{}}}\n" - }, - { - "title": "Functions", - "request": { - "curl": "curl https://api.openai.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"gpt-4.1\",\n \"input\": \"What is the weather like in Boston today?\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather in a given location\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and state, e.g. San Francisco, CA\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\"celsius\", \"fahrenheit\"]\n }\n },\n \"required\": [\"location\", \"unit\"]\n }\n }\n ],\n \"tool_choice\": \"auto\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.create()\nprint(response.id)", - "javascript": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI();\n\nconst tools = [\n {\n type: \"function\",\n name: \"get_current_weather\",\n description: \"Get the current weather in a given location\",\n parameters: {\n type: \"object\",\n properties: {\n location: {\n type: \"string\",\n description: \"The city and state, e.g. San Francisco, CA\",\n },\n unit: { type: \"string\", enum: [\"celsius\", \"fahrenheit\"] },\n },\n required: [\"location\", \"unit\"],\n },\n },\n];\n\nconst response = await openai.responses.create({\n model: \"gpt-4.1\",\n tools: tools,\n input: \"What is the weather like in Boston today?\",\n tool_choice: \"auto\",\n});\n\nconsole.log(response);\n", - "csharp": "using System;\nusing OpenAI.Responses;\n\nOpenAIResponseClient client = new(\n model: \"gpt-4.1\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nResponseTool getCurrentWeatherFunctionTool = ResponseTool.CreateFunctionTool(\n functionName: \"get_current_weather\",\n functionDescription: \"Get the current weather in a given location\",\n functionParameters: BinaryData.FromString(\"\"\"\n {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and state, e.g. San Francisco, CA\"\n },\n \"unit\": {\"type\": \"string\", \"enum\": [\"celsius\", \"fahrenheit\"]}\n },\n \"required\": [\"location\", \"unit\"]\n }\n \"\"\"\n )\n);\n\nstring userInputText = \"What is the weather like in Boston today?\";\n\nResponseCreationOptions options = new()\n{\n Tools =\n {\n getCurrentWeatherFunctionTool\n },\n ToolChoice = ResponseToolChoice.CreateAutoChoice(),\n};\n\nOpenAIResponse response = client.CreateResponse(userInputText, options);\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.create();\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.create\n\nputs(response)" - }, - "response": "{\n \"id\": \"resp_67ca09c5efe0819096d0511c92b8c890096610f474011cc0\",\n \"object\": \"response\",\n \"created_at\": 1741294021,\n \"status\": \"completed\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4.1-2025-04-14\",\n \"output\": [\n {\n \"type\": \"function_call\",\n \"id\": \"fc_67ca09c6bedc8190a7abfec07b1a1332096610f474011cc0\",\n \"call_id\": \"call_unLAR8MvFNptuiZK6K6HCy5k\",\n \"name\": \"get_current_weather\",\n \"arguments\": \"{\\\"location\\\":\\\"Boston, MA\\\",\\\"unit\\\":\\\"celsius\\\"}\",\n \"status\": \"completed\"\n }\n ],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"description\": \"Get the current weather in a given location\",\n \"name\": \"get_current_weather\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and state, e.g. San Francisco, CA\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"celsius\",\n \"fahrenheit\"\n ]\n }\n },\n \"required\": [\n \"location\",\n \"unit\"\n ]\n },\n \"strict\": true\n }\n ],\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 291,\n \"output_tokens\": 23,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 314\n },\n \"user\": null,\n \"metadata\": {}\n}\n" - }, - { - "title": "Reasoning", - "request": { - "curl": "curl https://api.openai.com/v1/responses \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"model\": \"o3-mini\",\n \"input\": \"How much wood would a woodchuck chuck?\",\n \"reasoning\": {\n \"effort\": \"high\"\n }\n }'\n", - "javascript": "import OpenAI from \"openai\";\nconst openai = new OpenAI();\n\nconst response = await openai.responses.create({\n model: \"o3-mini\",\n input: \"How much wood would a woodchuck chuck?\",\n reasoning: {\n effort: \"high\"\n }\n});\n\nconsole.log(response);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.create()\nprint(response.id)", - "csharp": "using System;\nusing OpenAI.Responses;\n\nOpenAIResponseClient client = new(\n model: \"o3-mini\",\n apiKey: Environment.GetEnvironmentVariable(\"OPENAI_API_KEY\")\n);\n\nstring userInputText = \"How much wood would a woodchuck chuck?\";\n\nResponseCreationOptions options = new()\n{\n ReasoningOptions = new()\n {\n ReasoningEffortLevel = ResponseReasoningEffortLevel.High,\n },\n};\n\nOpenAIResponse response = client.CreateResponse(userInputText, options);\n\nConsole.WriteLine(response.GetOutputText());\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.create();\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.create\n\nputs(response)" - }, - "response": "{\n \"id\": \"resp_67ccd7eca01881908ff0b5146584e408072912b2993db808\",\n \"object\": \"response\",\n \"created_at\": 1741477868,\n \"status\": \"completed\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"o1-2024-12-17\",\n \"output\": [\n {\n \"type\": \"message\",\n \"id\": \"msg_67ccd7f7b5848190a6f3e95d809f6b44072912b2993db808\",\n \"status\": \"completed\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"The classic tongue twister...\",\n \"annotations\": []\n }\n ]\n }\n ],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": \"high\",\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 81,\n \"input_tokens_details\": {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 1035,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 832\n },\n \"total_tokens\": 1116\n },\n \"user\": null,\n \"metadata\": {}\n}\n" - } - ] - }, - "description": "Creates a model response. Provide [text](https://platform.openai.com/docs/guides/text) or\n[image](https://platform.openai.com/docs/guides/images) inputs to generate [text](https://platform.openai.com/docs/guides/text)\nor [JSON](https://platform.openai.com/docs/guides/structured-outputs) outputs. Have the model call\nyour own [custom code](https://platform.openai.com/docs/guides/function-calling) or use built-in\n[tools](https://platform.openai.com/docs/guides/tools) like [web search](https://platform.openai.com/docs/guides/tools-web-search)\nor [file search](https://platform.openai.com/docs/guides/tools-file-search) to use your own data\nas input for the model's response.\n" - } - }, - "/responses/{response_id}": { - "get": { - "operationId": "getResponse", - "tags": [ - "Responses" - ], - "summary": "Get a model response", - "parameters": [ - { - "in": "path", - "name": "response_id", - "required": true, - "schema": { - "type": "string", - "example": "resp_677efb5139a88190b512bc3fef8e535d" - }, - "description": "The ID of the response to retrieve." - }, - { - "in": "query", - "name": "include", - "schema": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Includable" - } - }, - "description": "Additional fields to include in the response. See the `include`\nparameter for Response creation above for more information.\n" - }, - { - "in": "query", - "name": "stream", - "schema": { - "type": "boolean" - }, - "description": "If set to true, the model response data will be streamed to the client\nas it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).\nSee the [Streaming section below](https://platform.openai.com/docs/api-reference/responses-streaming)\nfor more information.\n" - }, - { - "in": "query", - "name": "starting_after", - "schema": { - "type": "integer" - }, - "description": "The sequence number of the event after which to start streaming.\n" - }, - { - "in": "query", - "name": "include_obfuscation", - "schema": { - "type": "boolean" - }, - "description": "When true, stream obfuscation will be enabled. Stream obfuscation adds\nrandom characters to an `obfuscation` field on streaming delta events\nto normalize payload sizes as a mitigation to certain side-channel\nattacks. These obfuscation fields are included by default, but add a\nsmall amount of overhead to the data stream. You can set\n`include_obfuscation` to false to optimize for bandwidth if you trust\nthe network links between your application and the OpenAI API.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Response" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Get a model response", - "group": "responses", - "returns": "The [Response](https://platform.openai.com/docs/api-reference/responses/object) object matching the\nspecified ID.\n", - "examples": { - "response": "{\n \"id\": \"resp_67cb71b351908190a308f3859487620d06981a8637e6bc44\",\n \"object\": \"response\",\n \"created_at\": 1741386163,\n \"status\": \"completed\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-2024-08-06\",\n \"output\": [\n {\n \"type\": \"message\",\n \"id\": \"msg_67cb71b3c2b0819084d481baaaf148f206981a8637e6bc44\",\n \"status\": \"completed\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"Silent circuits hum, \\nThoughts emerge in data streamsโ€” \\nDigital dawn breaks.\",\n \"annotations\": []\n }\n ]\n }\n ],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 32,\n \"input_tokens_details\": {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 18,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 50\n },\n \"user\": null,\n \"metadata\": {}\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/responses/resp_123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst response = await client.responses.retrieve(\"resp_123\");\nconsole.log(response);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.retrieve(\n response_id=\"resp_677efb5139a88190b512bc3fef8e535d\",\n)\nprint(response.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.retrieve('resp_677efb5139a88190b512bc3fef8e535d');\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.Get(\n context.TODO(),\n \"resp_677efb5139a88190b512bc3fef8e535d\",\n responses.ResponseGetParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().retrieve(\"resp_677efb5139a88190b512bc3fef8e535d\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.retrieve(\"resp_677efb5139a88190b512bc3fef8e535d\")\n\nputs(response)" - } - } - }, - "description": "Retrieves a model response with the given ID.\n" - }, - "delete": { - "operationId": "deleteResponse", - "tags": [ - "Responses" - ], - "summary": "Delete a model response", - "parameters": [ - { - "in": "path", - "name": "response_id", - "required": true, - "schema": { - "type": "string", - "example": "resp_677efb5139a88190b512bc3fef8e535d" - }, - "description": "The ID of the response to delete." - } - ], - "responses": { - "200": { - "description": "OK" - }, - "404": { - "description": "Not Found", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Error" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete a model response", - "group": "responses", - "returns": "A success message.\n", - "examples": { - "response": "{\n \"id\": \"resp_6786a1bec27481909a17d673315b29f6\",\n \"object\": \"response\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/responses/resp_123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst response = await client.responses.delete(\"resp_123\");\nconsole.log(response);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nclient.responses.delete(\n \"resp_677efb5139a88190b512bc3fef8e535d\",\n)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nawait client.responses.delete('resp_677efb5139a88190b512bc3fef8e535d');", - "go": "package main\n\nimport (\n \"context\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n err := client.Responses.Delete(context.TODO(), \"resp_677efb5139a88190b512bc3fef8e535d\")\n if err != nil {\n panic(err.Error())\n }\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.ResponseDeleteParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n client.responses().delete(\"resp_677efb5139a88190b512bc3fef8e535d\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresult = openai.responses.delete(\"resp_677efb5139a88190b512bc3fef8e535d\")\n\nputs(result)" - } - } - }, - "description": "Deletes a model response with the given ID.\n" - } - }, - "/responses/{response_id}/cancel": { - "post": { - "operationId": "cancelResponse", - "tags": [ - "Responses" - ], - "summary": "Cancel a response", - "parameters": [ - { - "in": "path", - "name": "response_id", - "required": true, - "schema": { - "type": "string", - "example": "resp_677efb5139a88190b512bc3fef8e535d" - }, - "description": "The ID of the response to cancel." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Response" - } - } - } - }, - "404": { - "description": "Not Found", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Error" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Cancel a response", - "group": "responses", - "returns": "A [Response](https://platform.openai.com/docs/api-reference/responses/object) object.\n", - "examples": { - "response": "{\n \"id\": \"resp_67cb71b351908190a308f3859487620d06981a8637e6bc44\",\n \"object\": \"response\",\n \"created_at\": 1741386163,\n \"status\": \"completed\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-2024-08-06\",\n \"output\": [\n {\n \"type\": \"message\",\n \"id\": \"msg_67cb71b3c2b0819084d481baaaf148f206981a8637e6bc44\",\n \"status\": \"completed\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"Silent circuits hum, \\nThoughts emerge in data streamsโ€” \\nDigital dawn breaks.\",\n \"annotations\": []\n }\n ]\n }\n ],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1.0,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1.0,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 32,\n \"input_tokens_details\": {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 18,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 50\n },\n \"user\": null,\n \"metadata\": {}\n}\n", - "request": { - "curl": "curl -X POST https://api.openai.com/v1/responses/resp_123/cancel \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst response = await client.responses.cancel(\"resp_123\");\nconsole.log(response);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nresponse = client.responses.cancel(\n \"resp_677efb5139a88190b512bc3fef8e535d\",\n)\nprint(response.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst response = await client.responses.cancel('resp_677efb5139a88190b512bc3fef8e535d');\n\nconsole.log(response.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n response, err := client.Responses.Cancel(context.TODO(), \"resp_677efb5139a88190b512bc3fef8e535d\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", response.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.Response;\nimport com.openai.models.responses.ResponseCancelParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Response response = client.responses().cancel(\"resp_677efb5139a88190b512bc3fef8e535d\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nresponse = openai.responses.cancel(\"resp_677efb5139a88190b512bc3fef8e535d\")\n\nputs(response)" - } - } - }, - "description": "Cancels a model response with the given ID. Only responses created with\nthe `background` parameter set to `true` can be cancelled. \n[Learn more](https://platform.openai.com/docs/guides/background).\n" - } - }, - "/responses/{response_id}/input_items": { - "get": { - "operationId": "listInputItems", - "tags": [ - "Responses" - ], - "summary": "List input items", - "parameters": [ - { - "in": "path", - "name": "response_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the response to retrieve input items for." - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between\n1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "in": "query", - "name": "order", - "schema": { - "type": "string", - "enum": [ - "asc", - "desc" - ] - }, - "description": "The order to return the input items in. Default is `desc`.\n- `asc`: Return the input items in ascending order.\n- `desc`: Return the input items in descending order.\n" - }, - { - "in": "query", - "name": "after", - "schema": { - "type": "string" - }, - "description": "An item ID to list items after, used in pagination.\n" - }, - { - "in": "query", - "name": "include", - "schema": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Includable" - } - }, - "description": "Additional fields to include in the response. See the `include`\nparameter for Response creation above for more information.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ResponseItemList" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List input items", - "group": "responses", - "returns": "A list of input item objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"msg_abc123\",\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Tell me a three sentence bedtime story about a unicorn.\"\n }\n ]\n }\n ],\n \"first_id\": \"msg_abc123\",\n \"last_id\": \"msg_abc123\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/responses/resp_abc123/input_items \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "javascript": "import OpenAI from \"openai\";\nconst client = new OpenAI();\n\nconst response = await client.responses.inputItems.list(\"resp_123\");\nconsole.log(response.data);\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.responses.input_items.list(\n response_id=\"response_id\",\n)\npage = page.data[0]\nprint(page)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const responseItem of client.responses.inputItems.list('response_id')) {\n console.log(responseItem);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n \"github.com/openai/openai-go/responses\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Responses.InputItems.List(\n context.TODO(),\n \"response_id\",\n responses.InputItemListParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.responses.inputitems.InputItemListPage;\nimport com.openai.models.responses.inputitems.InputItemListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n InputItemListPage page = client.responses().inputItems().list(\"response_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.responses.input_items.list(\"response_id\")\n\nputs(page)" - } - } - }, - "description": "Returns a list of input items for a given response." - } - }, - "/threads": { - "post": { - "operationId": "createThread", - "tags": [ - "Assistants" - ], - "summary": "Create thread", - "requestBody": { - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateThreadRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ThreadObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create thread", - "group": "threads", - "beta": true, - "returns": "A [thread](https://platform.openai.com/docs/api-reference/threads) object.", - "examples": [ - { - "title": "Empty", - "request": { - "curl": "curl https://api.openai.com/v1/threads \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d ''\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nthread = client.beta.threads.create()\nprint(thread.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst thread = await client.beta.threads.create();\n\nconsole.log(thread.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n thread, err := client.Beta.Threads.New(context.TODO(), openai.BetaThreadNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", thread.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.Thread;\nimport com.openai.models.beta.threads.ThreadCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Thread thread = client.beta().threads().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nthread = openai.beta.threads.create\n\nputs(thread)" - }, - "response": "{\n \"id\": \"thread_abc123\",\n \"object\": \"thread\",\n \"created_at\": 1699012949,\n \"metadata\": {},\n \"tool_resources\": {}\n}\n" - }, - { - "title": "Messages", - "request": { - "curl": "curl https://api.openai.com/v1/threads \\\n-H \"Content-Type: application/json\" \\\n-H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n-H \"OpenAI-Beta: assistants=v2\" \\\n-d '{\n \"messages\": [{\n \"role\": \"user\",\n \"content\": \"Hello, what is AI?\"\n }, {\n \"role\": \"user\",\n \"content\": \"How does AI work? Explain it in simple terms.\"\n }]\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nthread = client.beta.threads.create()\nprint(thread.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst thread = await client.beta.threads.create();\n\nconsole.log(thread.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n thread, err := client.Beta.Threads.New(context.TODO(), openai.BetaThreadNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", thread.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.Thread;\nimport com.openai.models.beta.threads.ThreadCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Thread thread = client.beta().threads().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nthread = openai.beta.threads.create\n\nputs(thread)" - }, - "response": "{\n \"id\": \"thread_abc123\",\n \"object\": \"thread\",\n \"created_at\": 1699014083,\n \"metadata\": {},\n \"tool_resources\": {}\n}\n" - } - ] - }, - "description": "Create a thread." - } - }, - "/threads/runs": { - "post": { - "operationId": "createThreadAndRun", - "tags": [ - "Assistants" - ], - "summary": "Create thread and run", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateThreadAndRunRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RunObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create thread and run", - "group": "threads", - "beta": true, - "returns": "A [run](https://platform.openai.com/docs/api-reference/runs/object) object.", - "examples": [ - { - "title": "Default", - "request": { - "curl": "curl https://api.openai.com/v1/threads/runs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"assistant_id\": \"asst_abc123\",\n \"thread\": {\n \"messages\": [\n {\"role\": \"user\", \"content\": \"Explain deep learning to a 5 year old.\"}\n ]\n }\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.create_and_run(\n assistant_id=\"assistant_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.createAndRun({ assistant_id: 'assistant_id' });\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.NewAndRun(context.TODO(), openai.BetaThreadNewAndRunParams{\n AssistantID: \"assistant_id\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.ThreadCreateAndRunParams;\nimport com.openai.models.beta.threads.runs.Run;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ThreadCreateAndRunParams params = ThreadCreateAndRunParams.builder()\n .assistantId(\"assistant_id\")\n .build();\n Run run = client.beta().threads().createAndRun(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.create_and_run(assistant_id: \"assistant_id\")\n\nputs(run)" - }, - "response": "{\n \"id\": \"run_abc123\",\n \"object\": \"thread.run\",\n \"created_at\": 1699076792,\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"status\": \"queued\",\n \"started_at\": null,\n \"expires_at\": 1699077392,\n \"cancelled_at\": null,\n \"failed_at\": null,\n \"completed_at\": null,\n \"required_action\": null,\n \"last_error\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are a helpful assistant.\",\n \"tools\": [],\n \"tool_resources\": {},\n \"metadata\": {},\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_completion_tokens\": null,\n \"max_prompt_tokens\": null,\n \"truncation_strategy\": {\n \"type\": \"auto\",\n \"last_messages\": null\n },\n \"incomplete_details\": null,\n \"usage\": null,\n \"response_format\": \"auto\",\n \"tool_choice\": \"auto\",\n \"parallel_tool_calls\": true\n}\n" - }, - { - "title": "Streaming", - "request": { - "curl": "curl https://api.openai.com/v1/threads/runs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"assistant_id\": \"asst_123\",\n \"thread\": {\n \"messages\": [\n {\"role\": \"user\", \"content\": \"Hello\"}\n ]\n },\n \"stream\": true\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.create_and_run(\n assistant_id=\"assistant_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.createAndRun({ assistant_id: 'assistant_id' });\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.NewAndRun(context.TODO(), openai.BetaThreadNewAndRunParams{\n AssistantID: \"assistant_id\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.ThreadCreateAndRunParams;\nimport com.openai.models.beta.threads.runs.Run;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ThreadCreateAndRunParams params = ThreadCreateAndRunParams.builder()\n .assistantId(\"assistant_id\")\n .build();\n Run run = client.beta().threads().createAndRun(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.create_and_run(assistant_id: \"assistant_id\")\n\nputs(run)" - }, - "response": "event: thread.created\ndata: {\"id\":\"thread_123\",\"object\":\"thread\",\"created_at\":1710348075,\"metadata\":{}}\n\nevent: thread.run.created\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710348075,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"queued\",\"started_at\":null,\"expires_at\":1710348675,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"tool_resources\":{},\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}\n\nevent: thread.run.queued\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710348075,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"queued\",\"started_at\":null,\"expires_at\":1710348675,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"tool_resources\":{},\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}\n\nevent: thread.run.in_progress\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710348075,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"in_progress\",\"started_at\":null,\"expires_at\":1710348675,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"tool_resources\":{},\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}\n\nevent: thread.run.step.created\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710348076,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710348675,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_001\"}},\"usage\":null}\n\nevent: thread.run.step.in_progress\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710348076,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710348675,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_001\"}},\"usage\":null}\n\nevent: thread.message.created\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message\",\"created_at\":1710348076,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"in_progress\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":null,\"role\":\"assistant\",\"content\":[], \"metadata\":{}}\n\nevent: thread.message.in_progress\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message\",\"created_at\":1710348076,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"in_progress\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":null,\"role\":\"assistant\",\"content\":[], \"metadata\":{}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\"Hello\",\"annotations\":[]}}]}}\n\n...\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\" today\"}}]}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\"?\"}}]}}\n\nevent: thread.message.completed\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message\",\"created_at\":1710348076,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"completed\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":1710348077,\"role\":\"assistant\",\"content\":[{\"type\":\"text\",\"text\":{\"value\":\"Hello! How can I assist you today?\",\"annotations\":[]}}], \"metadata\":{}}\n\nevent: thread.run.step.completed\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710348076,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"completed\",\"cancelled_at\":null,\"completed_at\":1710348077,\"expires_at\":1710348675,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_001\"}},\"usage\":{\"prompt_tokens\":20,\"completion_tokens\":11,\"total_tokens\":31}}\n\nevent: thread.run.completed\n{\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710348076,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"completed\",\"started_at\":1713226836,\"expires_at\":null,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":1713226837,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":{\"prompt_tokens\":345,\"completion_tokens\":11,\"total_tokens\":356},\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}\n\nevent: done\ndata: [DONE]\n" - }, - { - "title": "Streaming with Functions", - "request": { - "curl": "curl https://api.openai.com/v1/threads/runs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"assistant_id\": \"asst_abc123\",\n \"thread\": {\n \"messages\": [\n {\"role\": \"user\", \"content\": \"What is the weather like in San Francisco?\"}\n ]\n },\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather in a given location\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and state, e.g. San Francisco, CA\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\"celsius\", \"fahrenheit\"]\n }\n },\n \"required\": [\"location\"]\n }\n }\n }\n ],\n \"stream\": true\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.create_and_run(\n assistant_id=\"assistant_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.createAndRun({ assistant_id: 'assistant_id' });\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.NewAndRun(context.TODO(), openai.BetaThreadNewAndRunParams{\n AssistantID: \"assistant_id\",\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.ThreadCreateAndRunParams;\nimport com.openai.models.beta.threads.runs.Run;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ThreadCreateAndRunParams params = ThreadCreateAndRunParams.builder()\n .assistantId(\"assistant_id\")\n .build();\n Run run = client.beta().threads().createAndRun(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.create_and_run(assistant_id: \"assistant_id\")\n\nputs(run)" - }, - "response": "event: thread.created\ndata: {\"id\":\"thread_123\",\"object\":\"thread\",\"created_at\":1710351818,\"metadata\":{}}\n\nevent: thread.run.created\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710351818,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"queued\",\"started_at\":null,\"expires_at\":1710352418,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"description\":\"Get the current weather in a given location\",\"parameters\":{\"type\":\"object\",\"properties\":{\"location\":{\"type\":\"string\",\"description\":\"The city and state, e.g. San Francisco, CA\"},\"unit\":{\"type\":\"string\",\"enum\":[\"celsius\",\"fahrenheit\"]}},\"required\":[\"location\"]}}}],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.queued\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710351818,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"queued\",\"started_at\":null,\"expires_at\":1710352418,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"description\":\"Get the current weather in a given location\",\"parameters\":{\"type\":\"object\",\"properties\":{\"location\":{\"type\":\"string\",\"description\":\"The city and state, e.g. San Francisco, CA\"},\"unit\":{\"type\":\"string\",\"enum\":[\"celsius\",\"fahrenheit\"]}},\"required\":[\"location\"]}}}],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.in_progress\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710351818,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"in_progress\",\"started_at\":1710351818,\"expires_at\":1710352418,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"description\":\"Get the current weather in a given location\",\"parameters\":{\"type\":\"object\",\"properties\":{\"location\":{\"type\":\"string\",\"description\":\"The city and state, e.g. San Francisco, CA\"},\"unit\":{\"type\":\"string\",\"enum\":[\"celsius\",\"fahrenheit\"]}},\"required\":[\"location\"]}}}],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.step.created\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710351819,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"tool_calls\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710352418,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"tool_calls\",\"tool_calls\":[]},\"usage\":null}\n\nevent: thread.run.step.in_progress\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710351819,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"tool_calls\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710352418,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"tool_calls\",\"tool_calls\":[]},\"usage\":null}\n\nevent: thread.run.step.delta\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step.delta\",\"delta\":{\"step_details\":{\"type\":\"tool_calls\",\"tool_calls\":[{\"index\":0,\"id\":\"call_XXNp8YGaFrjrSjgqxtC8JJ1B\",\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"arguments\":\"\",\"output\":null}}]}}}\n\nevent: thread.run.step.delta\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step.delta\",\"delta\":{\"step_details\":{\"type\":\"tool_calls\",\"tool_calls\":[{\"index\":0,\"type\":\"function\",\"function\":{\"arguments\":\"{\\\"\"}}]}}}\n\nevent: thread.run.step.delta\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step.delta\",\"delta\":{\"step_details\":{\"type\":\"tool_calls\",\"tool_calls\":[{\"index\":0,\"type\":\"function\",\"function\":{\"arguments\":\"location\"}}]}}}\n\n...\n\nevent: thread.run.step.delta\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step.delta\",\"delta\":{\"step_details\":{\"type\":\"tool_calls\",\"tool_calls\":[{\"index\":0,\"type\":\"function\",\"function\":{\"arguments\":\"ahrenheit\"}}]}}}\n\nevent: thread.run.step.delta\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step.delta\",\"delta\":{\"step_details\":{\"type\":\"tool_calls\",\"tool_calls\":[{\"index\":0,\"type\":\"function\",\"function\":{\"arguments\":\"\\\"}\"}}]}}}\n\nevent: thread.run.requires_action\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710351818,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"requires_action\",\"started_at\":1710351818,\"expires_at\":1710352418,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":{\"type\":\"submit_tool_outputs\",\"submit_tool_outputs\":{\"tool_calls\":[{\"id\":\"call_XXNp8YGaFrjrSjgqxtC8JJ1B\",\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"arguments\":\"{\\\"location\\\":\\\"San Francisco, CA\\\",\\\"unit\\\":\\\"fahrenheit\\\"}\"}}]}},\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"description\":\"Get the current weather in a given location\",\"parameters\":{\"type\":\"object\",\"properties\":{\"location\":{\"type\":\"string\",\"description\":\"The city and state, e.g. San Francisco, CA\"},\"unit\":{\"type\":\"string\",\"enum\":[\"celsius\",\"fahrenheit\"]}},\"required\":[\"location\"]}}}],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":{\"prompt_tokens\":345,\"completion_tokens\":11,\"total_tokens\":356},\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: done\ndata: [DONE]\n" - } - ] - }, - "description": "Create a thread and run it in one request." - } - }, - "/threads/{thread_id}": { - "get": { - "operationId": "getThread", - "tags": [ - "Assistants" - ], - "summary": "Retrieve thread", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread to retrieve." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ThreadObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve thread", - "group": "threads", - "beta": true, - "returns": "The [thread](https://platform.openai.com/docs/api-reference/threads/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"thread_abc123\",\n \"object\": \"thread\",\n \"created_at\": 1699014083,\n \"metadata\": {},\n \"tool_resources\": {\n \"code_interpreter\": {\n \"file_ids\": []\n }\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nthread = client.beta.threads.retrieve(\n \"thread_id\",\n)\nprint(thread.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst thread = await client.beta.threads.retrieve('thread_id');\n\nconsole.log(thread.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n thread, err := client.Beta.Threads.Get(context.TODO(), \"thread_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", thread.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.Thread;\nimport com.openai.models.beta.threads.ThreadRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Thread thread = client.beta().threads().retrieve(\"thread_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nthread = openai.beta.threads.retrieve(\"thread_id\")\n\nputs(thread)" - } - } - }, - "description": "Retrieves a thread." - }, - "post": { - "operationId": "modifyThread", - "tags": [ - "Assistants" - ], - "summary": "Modify thread", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread to modify. Only the `metadata` can be modified." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ModifyThreadRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ThreadObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify thread", - "group": "threads", - "beta": true, - "returns": "The modified [thread](https://platform.openai.com/docs/api-reference/threads/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"thread_abc123\",\n \"object\": \"thread\",\n \"created_at\": 1699014083,\n \"metadata\": {\n \"modified\": \"true\",\n \"user\": \"abc123\"\n },\n \"tool_resources\": {}\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"metadata\": {\n \"modified\": \"true\",\n \"user\": \"abc123\"\n }\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nthread = client.beta.threads.update(\n thread_id=\"thread_id\",\n)\nprint(thread.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst thread = await client.beta.threads.update('thread_id');\n\nconsole.log(thread.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n thread, err := client.Beta.Threads.Update(\n context.TODO(),\n \"thread_id\",\n openai.BetaThreadUpdateParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", thread.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.Thread;\nimport com.openai.models.beta.threads.ThreadUpdateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Thread thread = client.beta().threads().update(\"thread_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nthread = openai.beta.threads.update(\"thread_id\")\n\nputs(thread)" - } - } - }, - "description": "Modifies a thread." - }, - "delete": { - "operationId": "deleteThread", - "tags": [ - "Assistants" - ], - "summary": "Delete thread", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread to delete." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeleteThreadResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete thread", - "group": "threads", - "beta": true, - "returns": "Deletion status", - "examples": { - "response": "{\n \"id\": \"thread_abc123\",\n \"object\": \"thread.deleted\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -X DELETE\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nthread_deleted = client.beta.threads.delete(\n \"thread_id\",\n)\nprint(thread_deleted.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst threadDeleted = await client.beta.threads.delete('thread_id');\n\nconsole.log(threadDeleted.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n threadDeleted, err := client.Beta.Threads.Delete(context.TODO(), \"thread_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", threadDeleted.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.ThreadDeleteParams;\nimport com.openai.models.beta.threads.ThreadDeleted;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n ThreadDeleted threadDeleted = client.beta().threads().delete(\"thread_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nthread_deleted = openai.beta.threads.delete(\"thread_id\")\n\nputs(thread_deleted)" - } - } - }, - "description": "Delete a thread." - } - }, - "/threads/{thread_id}/messages": { - "get": { - "operationId": "listMessages", - "tags": [ - "Assistants" - ], - "summary": "List messages", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) the messages belong to." - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "before", - "in": "query", - "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "run_id", - "in": "query", - "description": "Filter messages by the run ID that generated them.\n", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListMessagesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List messages", - "group": "threads", - "beta": true, - "returns": "A list of [message](https://platform.openai.com/docs/api-reference/messages) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"msg_abc123\",\n \"object\": \"thread.message\",\n \"created_at\": 1699016383,\n \"assistant_id\": null,\n \"thread_id\": \"thread_abc123\",\n \"run_id\": null,\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": {\n \"value\": \"How does AI work? Explain it in simple terms.\",\n \"annotations\": []\n }\n }\n ],\n \"attachments\": [],\n \"metadata\": {}\n },\n {\n \"id\": \"msg_abc456\",\n \"object\": \"thread.message\",\n \"created_at\": 1699016383,\n \"assistant_id\": null,\n \"thread_id\": \"thread_abc123\",\n \"run_id\": null,\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": {\n \"value\": \"Hello, what is AI?\",\n \"annotations\": []\n }\n }\n ],\n \"attachments\": [],\n \"metadata\": {}\n }\n ],\n \"first_id\": \"msg_abc123\",\n \"last_id\": \"msg_abc456\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/messages \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.beta.threads.messages.list(\n thread_id=\"thread_id\",\n)\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const message of client.beta.threads.messages.list('thread_id')) {\n console.log(message.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Beta.Threads.Messages.List(\n context.TODO(),\n \"thread_id\",\n openai.BetaThreadMessageListParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.messages.MessageListPage;\nimport com.openai.models.beta.threads.messages.MessageListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n MessageListPage page = client.beta().threads().messages().list(\"thread_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.beta.threads.messages.list(\"thread_id\")\n\nputs(page)" - } - } - }, - "description": "Returns a list of messages for a given thread." - }, - "post": { - "operationId": "createMessage", - "tags": [ - "Assistants" - ], - "summary": "Create message", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) to create a message for." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateMessageRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/MessageObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create message", - "group": "threads", - "beta": true, - "returns": "A [message](https://platform.openai.com/docs/api-reference/messages/object) object.", - "examples": { - "response": "{\n \"id\": \"msg_abc123\",\n \"object\": \"thread.message\",\n \"created_at\": 1713226573,\n \"assistant_id\": null,\n \"thread_id\": \"thread_abc123\",\n \"run_id\": null,\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": {\n \"value\": \"How does AI work? Explain it in simple terms.\",\n \"annotations\": []\n }\n }\n ],\n \"attachments\": [],\n \"metadata\": {}\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/messages \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"role\": \"user\",\n \"content\": \"How does AI work? Explain it in simple terms.\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nmessage = client.beta.threads.messages.create(\n thread_id=\"thread_id\",\n content=\"string\",\n role=\"user\",\n)\nprint(message.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst message = await client.beta.threads.messages.create('thread_id', { content: 'string', role: 'user' });\n\nconsole.log(message.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n message, err := client.Beta.Threads.Messages.New(\n context.TODO(),\n \"thread_id\",\n openai.BetaThreadMessageNewParams{\n Content: openai.BetaThreadMessageNewParamsContentUnion{\n OfString: openai.String(\"string\"),\n },\n Role: openai.BetaThreadMessageNewParamsRoleUser,\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", message.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.messages.Message;\nimport com.openai.models.beta.threads.messages.MessageCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n MessageCreateParams params = MessageCreateParams.builder()\n .threadId(\"thread_id\")\n .content(\"string\")\n .role(MessageCreateParams.Role.USER)\n .build();\n Message message = client.beta().threads().messages().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nmessage = openai.beta.threads.messages.create(\"thread_id\", content: \"string\", role: :user)\n\nputs(message)" - } - } - }, - "description": "Create a message." - } - }, - "/threads/{thread_id}/messages/{message_id}": { - "get": { - "operationId": "getMessage", - "tags": [ - "Assistants" - ], - "summary": "Retrieve message", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) to which this message belongs." - }, - { - "in": "path", - "name": "message_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the message to retrieve." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/MessageObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve message", - "group": "threads", - "beta": true, - "returns": "The [message](https://platform.openai.com/docs/api-reference/messages/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"msg_abc123\",\n \"object\": \"thread.message\",\n \"created_at\": 1699017614,\n \"assistant_id\": null,\n \"thread_id\": \"thread_abc123\",\n \"run_id\": null,\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": {\n \"value\": \"How does AI work? Explain it in simple terms.\",\n \"annotations\": []\n }\n }\n ],\n \"attachments\": [],\n \"metadata\": {}\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/messages/msg_abc123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nmessage = client.beta.threads.messages.retrieve(\n message_id=\"message_id\",\n thread_id=\"thread_id\",\n)\nprint(message.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst message = await client.beta.threads.messages.retrieve('message_id', { thread_id: 'thread_id' });\n\nconsole.log(message.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n message, err := client.Beta.Threads.Messages.Get(\n context.TODO(),\n \"thread_id\",\n \"message_id\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", message.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.messages.Message;\nimport com.openai.models.beta.threads.messages.MessageRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n MessageRetrieveParams params = MessageRetrieveParams.builder()\n .threadId(\"thread_id\")\n .messageId(\"message_id\")\n .build();\n Message message = client.beta().threads().messages().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nmessage = openai.beta.threads.messages.retrieve(\"message_id\", thread_id: \"thread_id\")\n\nputs(message)" - } - } - }, - "description": "Retrieve a message." - }, - "post": { - "operationId": "modifyMessage", - "tags": [ - "Assistants" - ], - "summary": "Modify message", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread to which this message belongs." - }, - { - "in": "path", - "name": "message_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the message to modify." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ModifyMessageRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/MessageObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify message", - "group": "threads", - "beta": true, - "returns": "The modified [message](https://platform.openai.com/docs/api-reference/messages/object) object.", - "examples": { - "response": "{\n \"id\": \"msg_abc123\",\n \"object\": \"thread.message\",\n \"created_at\": 1699017614,\n \"assistant_id\": null,\n \"thread_id\": \"thread_abc123\",\n \"run_id\": null,\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": {\n \"value\": \"How does AI work? Explain it in simple terms.\",\n \"annotations\": []\n }\n }\n ],\n \"file_ids\": [],\n \"metadata\": {\n \"modified\": \"true\",\n \"user\": \"abc123\"\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/messages/msg_abc123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"metadata\": {\n \"modified\": \"true\",\n \"user\": \"abc123\"\n }\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nmessage = client.beta.threads.messages.update(\n message_id=\"message_id\",\n thread_id=\"thread_id\",\n)\nprint(message.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst message = await client.beta.threads.messages.update('message_id', { thread_id: 'thread_id' });\n\nconsole.log(message.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n message, err := client.Beta.Threads.Messages.Update(\n context.TODO(),\n \"thread_id\",\n \"message_id\",\n openai.BetaThreadMessageUpdateParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", message.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.messages.Message;\nimport com.openai.models.beta.threads.messages.MessageUpdateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n MessageUpdateParams params = MessageUpdateParams.builder()\n .threadId(\"thread_id\")\n .messageId(\"message_id\")\n .build();\n Message message = client.beta().threads().messages().update(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nmessage = openai.beta.threads.messages.update(\"message_id\", thread_id: \"thread_id\")\n\nputs(message)" - } - } - }, - "description": "Modifies a message." - }, - "delete": { - "operationId": "deleteMessage", - "tags": [ - "Assistants" - ], - "summary": "Delete message", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread to which this message belongs." - }, - { - "in": "path", - "name": "message_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the message to delete." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeleteMessageResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete message", - "group": "threads", - "beta": true, - "returns": "Deletion status", - "examples": { - "response": "{\n \"id\": \"msg_abc123\",\n \"object\": \"thread.message.deleted\",\n \"deleted\": true\n}\n", - "request": { - "curl": "curl -X DELETE https://api.openai.com/v1/threads/thread_abc123/messages/msg_abc123 \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nmessage_deleted = client.beta.threads.messages.delete(\n message_id=\"message_id\",\n thread_id=\"thread_id\",\n)\nprint(message_deleted.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst messageDeleted = await client.beta.threads.messages.delete('message_id', { thread_id: 'thread_id' });\n\nconsole.log(messageDeleted.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n messageDeleted, err := client.Beta.Threads.Messages.Delete(\n context.TODO(),\n \"thread_id\",\n \"message_id\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", messageDeleted.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.messages.MessageDeleteParams;\nimport com.openai.models.beta.threads.messages.MessageDeleted;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n MessageDeleteParams params = MessageDeleteParams.builder()\n .threadId(\"thread_id\")\n .messageId(\"message_id\")\n .build();\n MessageDeleted messageDeleted = client.beta().threads().messages().delete(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nmessage_deleted = openai.beta.threads.messages.delete(\"message_id\", thread_id: \"thread_id\")\n\nputs(message_deleted)" - } - } - }, - "description": "Deletes a message." - } - }, - "/threads/{thread_id}/runs": { - "get": { - "operationId": "listRuns", - "tags": [ - "Assistants" - ], - "summary": "List runs", - "parameters": [ - { - "name": "thread_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread the run belongs to." - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "before", - "in": "query", - "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.\n", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListRunsResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List runs", - "group": "threads", - "beta": true, - "returns": "A list of [run](https://platform.openai.com/docs/api-reference/runs/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"run_abc123\",\n \"object\": \"thread.run\",\n \"created_at\": 1699075072,\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"status\": \"completed\",\n \"started_at\": 1699075072,\n \"expires_at\": null,\n \"cancelled_at\": null,\n \"failed_at\": null,\n \"completed_at\": 1699075073,\n \"last_error\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": null,\n \"incomplete_details\": null,\n \"tools\": [\n {\n \"type\": \"code_interpreter\"\n }\n ],\n \"tool_resources\": {\n \"code_interpreter\": {\n \"file_ids\": [\n \"file-abc123\",\n \"file-abc456\"\n ]\n }\n },\n \"metadata\": {},\n \"usage\": {\n \"prompt_tokens\": 123,\n \"completion_tokens\": 456,\n \"total_tokens\": 579\n },\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_prompt_tokens\": 1000,\n \"max_completion_tokens\": 1000,\n \"truncation_strategy\": {\n \"type\": \"auto\",\n \"last_messages\": null\n },\n \"response_format\": \"auto\",\n \"tool_choice\": \"auto\",\n \"parallel_tool_calls\": true\n },\n {\n \"id\": \"run_abc456\",\n \"object\": \"thread.run\",\n \"created_at\": 1699063290,\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"status\": \"completed\",\n \"started_at\": 1699063290,\n \"expires_at\": null,\n \"cancelled_at\": null,\n \"failed_at\": null,\n \"completed_at\": 1699063291,\n \"last_error\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": null,\n \"incomplete_details\": null,\n \"tools\": [\n {\n \"type\": \"code_interpreter\"\n }\n ],\n \"tool_resources\": {\n \"code_interpreter\": {\n \"file_ids\": [\n \"file-abc123\",\n \"file-abc456\"\n ]\n }\n },\n \"metadata\": {},\n \"usage\": {\n \"prompt_tokens\": 123,\n \"completion_tokens\": 456,\n \"total_tokens\": 579\n },\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_prompt_tokens\": 1000,\n \"max_completion_tokens\": 1000,\n \"truncation_strategy\": {\n \"type\": \"auto\",\n \"last_messages\": null\n },\n \"response_format\": \"auto\",\n \"tool_choice\": \"auto\",\n \"parallel_tool_calls\": true\n }\n ],\n \"first_id\": \"run_abc123\",\n \"last_id\": \"run_abc456\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/runs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.beta.threads.runs.list(\n thread_id=\"thread_id\",\n)\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const run of client.beta.threads.runs.list('thread_id')) {\n console.log(run.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Beta.Threads.Runs.List(\n context.TODO(),\n \"thread_id\",\n openai.BetaThreadRunListParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.RunListPage;\nimport com.openai.models.beta.threads.runs.RunListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunListPage page = client.beta().threads().runs().list(\"thread_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.beta.threads.runs.list(\"thread_id\")\n\nputs(page)" - } - } - }, - "description": "Returns a list of runs belonging to a thread." - }, - "post": { - "operationId": "createRun", - "tags": [ - "Assistants" - ], - "summary": "Create run", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread to run." - }, - { - "name": "include[]", - "in": "query", - "description": "A list of additional fields to include in the response. Currently the only supported value is `step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result content.\n\nSee the [file search tool documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings) for more information.\n", - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "step_details.tool_calls[*].file_search.results[*].content" - ] - } - } - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateRunRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RunObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create run", - "group": "threads", - "beta": true, - "returns": "A [run](https://platform.openai.com/docs/api-reference/runs/object) object.", - "examples": [ - { - "title": "Default", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/runs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"assistant_id\": \"asst_abc123\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.runs.create(\n thread_id=\"thread_id\",\n assistant_id=\"assistant_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.runs.create('thread_id', { assistant_id: 'assistant_id' });\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.Runs.New(\n context.TODO(),\n \"thread_id\",\n openai.BetaThreadRunNewParams{\n AssistantID: \"assistant_id\",\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.Run;\nimport com.openai.models.beta.threads.runs.RunCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunCreateParams params = RunCreateParams.builder()\n .threadId(\"thread_id\")\n .assistantId(\"assistant_id\")\n .build();\n Run run = client.beta().threads().runs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.runs.create(\"thread_id\", assistant_id: \"assistant_id\")\n\nputs(run)" - }, - "response": "{\n \"id\": \"run_abc123\",\n \"object\": \"thread.run\",\n \"created_at\": 1699063290,\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"status\": \"queued\",\n \"started_at\": 1699063290,\n \"expires_at\": null,\n \"cancelled_at\": null,\n \"failed_at\": null,\n \"completed_at\": 1699063291,\n \"last_error\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": null,\n \"incomplete_details\": null,\n \"tools\": [\n {\n \"type\": \"code_interpreter\"\n }\n ],\n \"metadata\": {},\n \"usage\": null,\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_prompt_tokens\": 1000,\n \"max_completion_tokens\": 1000,\n \"truncation_strategy\": {\n \"type\": \"auto\",\n \"last_messages\": null\n },\n \"response_format\": \"auto\",\n \"tool_choice\": \"auto\",\n \"parallel_tool_calls\": true\n}\n" - }, - { - "title": "Streaming", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_123/runs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"assistant_id\": \"asst_123\",\n \"stream\": true\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.runs.create(\n thread_id=\"thread_id\",\n assistant_id=\"assistant_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.runs.create('thread_id', { assistant_id: 'assistant_id' });\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.Runs.New(\n context.TODO(),\n \"thread_id\",\n openai.BetaThreadRunNewParams{\n AssistantID: \"assistant_id\",\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.Run;\nimport com.openai.models.beta.threads.runs.RunCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunCreateParams params = RunCreateParams.builder()\n .threadId(\"thread_id\")\n .assistantId(\"assistant_id\")\n .build();\n Run run = client.beta().threads().runs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.runs.create(\"thread_id\", assistant_id: \"assistant_id\")\n\nputs(run)" - }, - "response": "event: thread.run.created\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710330640,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"queued\",\"started_at\":null,\"expires_at\":1710331240,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.queued\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710330640,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"queued\",\"started_at\":null,\"expires_at\":1710331240,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.in_progress\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710330640,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"in_progress\",\"started_at\":1710330641,\"expires_at\":1710331240,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.step.created\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710330641,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710331240,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_001\"}},\"usage\":null}\n\nevent: thread.run.step.in_progress\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710330641,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710331240,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_001\"}},\"usage\":null}\n\nevent: thread.message.created\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message\",\"created_at\":1710330641,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"in_progress\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":null,\"role\":\"assistant\",\"content\":[],\"metadata\":{}}\n\nevent: thread.message.in_progress\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message\",\"created_at\":1710330641,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"in_progress\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":null,\"role\":\"assistant\",\"content\":[],\"metadata\":{}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\"Hello\",\"annotations\":[]}}]}}\n\n...\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\" today\"}}]}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\"?\"}}]}}\n\nevent: thread.message.completed\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message\",\"created_at\":1710330641,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"completed\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":1710330642,\"role\":\"assistant\",\"content\":[{\"type\":\"text\",\"text\":{\"value\":\"Hello! How can I assist you today?\",\"annotations\":[]}}],\"metadata\":{}}\n\nevent: thread.run.step.completed\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710330641,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"completed\",\"cancelled_at\":null,\"completed_at\":1710330642,\"expires_at\":1710331240,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_001\"}},\"usage\":{\"prompt_tokens\":20,\"completion_tokens\":11,\"total_tokens\":31}}\n\nevent: thread.run.completed\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710330640,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"completed\",\"started_at\":1710330641,\"expires_at\":null,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":1710330642,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":{\"prompt_tokens\":20,\"completion_tokens\":11,\"total_tokens\":31},\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: done\ndata: [DONE]\n" - }, - { - "title": "Streaming with Functions", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/runs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"assistant_id\": \"asst_abc123\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather in a given location\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and state, e.g. San Francisco, CA\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\"celsius\", \"fahrenheit\"]\n }\n },\n \"required\": [\"location\"]\n }\n }\n }\n ],\n \"stream\": true\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.runs.create(\n thread_id=\"thread_id\",\n assistant_id=\"assistant_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.runs.create('thread_id', { assistant_id: 'assistant_id' });\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.Runs.New(\n context.TODO(),\n \"thread_id\",\n openai.BetaThreadRunNewParams{\n AssistantID: \"assistant_id\",\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.Run;\nimport com.openai.models.beta.threads.runs.RunCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunCreateParams params = RunCreateParams.builder()\n .threadId(\"thread_id\")\n .assistantId(\"assistant_id\")\n .build();\n Run run = client.beta().threads().runs().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.runs.create(\"thread_id\", assistant_id: \"assistant_id\")\n\nputs(run)" - }, - "response": "event: thread.run.created\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710348075,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"queued\",\"started_at\":null,\"expires_at\":1710348675,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.queued\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710348075,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"queued\",\"started_at\":null,\"expires_at\":1710348675,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.in_progress\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710348075,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"in_progress\",\"started_at\":1710348075,\"expires_at\":1710348675,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.step.created\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710348076,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710348675,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_001\"}},\"usage\":null}\n\nevent: thread.run.step.in_progress\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710348076,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710348675,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_001\"}},\"usage\":null}\n\nevent: thread.message.created\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message\",\"created_at\":1710348076,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"in_progress\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":null,\"role\":\"assistant\",\"content\":[],\"metadata\":{}}\n\nevent: thread.message.in_progress\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message\",\"created_at\":1710348076,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"in_progress\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":null,\"role\":\"assistant\",\"content\":[],\"metadata\":{}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\"Hello\",\"annotations\":[]}}]}}\n\n...\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\" today\"}}]}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\"?\"}}]}}\n\nevent: thread.message.completed\ndata: {\"id\":\"msg_001\",\"object\":\"thread.message\",\"created_at\":1710348076,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"completed\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":1710348077,\"role\":\"assistant\",\"content\":[{\"type\":\"text\",\"text\":{\"value\":\"Hello! How can I assist you today?\",\"annotations\":[]}}],\"metadata\":{}}\n\nevent: thread.run.step.completed\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710348076,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"completed\",\"cancelled_at\":null,\"completed_at\":1710348077,\"expires_at\":1710348675,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_001\"}},\"usage\":{\"prompt_tokens\":20,\"completion_tokens\":11,\"total_tokens\":31}}\n\nevent: thread.run.completed\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710348075,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"completed\",\"started_at\":1710348075,\"expires_at\":null,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":1710348077,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":{\"prompt_tokens\":20,\"completion_tokens\":11,\"total_tokens\":31},\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: done\ndata: [DONE]\n" - } - ] - }, - "description": "Create a run." - } - }, - "/threads/{thread_id}/runs/{run_id}": { - "get": { - "operationId": "getRun", - "tags": [ - "Assistants" - ], - "summary": "Retrieve run", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was run." - }, - { - "in": "path", - "name": "run_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run to retrieve." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RunObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve run", - "group": "threads", - "beta": true, - "returns": "The [run](https://platform.openai.com/docs/api-reference/runs/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"run_abc123\",\n \"object\": \"thread.run\",\n \"created_at\": 1699075072,\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"status\": \"completed\",\n \"started_at\": 1699075072,\n \"expires_at\": null,\n \"cancelled_at\": null,\n \"failed_at\": null,\n \"completed_at\": 1699075073,\n \"last_error\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": null,\n \"incomplete_details\": null,\n \"tools\": [\n {\n \"type\": \"code_interpreter\"\n }\n ],\n \"metadata\": {},\n \"usage\": {\n \"prompt_tokens\": 123,\n \"completion_tokens\": 456,\n \"total_tokens\": 579\n },\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_prompt_tokens\": 1000,\n \"max_completion_tokens\": 1000,\n \"truncation_strategy\": {\n \"type\": \"auto\",\n \"last_messages\": null\n },\n \"response_format\": \"auto\",\n \"tool_choice\": \"auto\",\n \"parallel_tool_calls\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.runs.retrieve(\n run_id=\"run_id\",\n thread_id=\"thread_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.runs.retrieve('run_id', { thread_id: 'thread_id' });\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.Runs.Get(\n context.TODO(),\n \"thread_id\",\n \"run_id\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.Run;\nimport com.openai.models.beta.threads.runs.RunRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunRetrieveParams params = RunRetrieveParams.builder()\n .threadId(\"thread_id\")\n .runId(\"run_id\")\n .build();\n Run run = client.beta().threads().runs().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.runs.retrieve(\"run_id\", thread_id: \"thread_id\")\n\nputs(run)" - } - } - }, - "description": "Retrieves a run." - }, - "post": { - "operationId": "modifyRun", - "tags": [ - "Assistants" - ], - "summary": "Modify run", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was run." - }, - { - "in": "path", - "name": "run_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run to modify." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ModifyRunRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RunObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify run", - "group": "threads", - "beta": true, - "returns": "The modified [run](https://platform.openai.com/docs/api-reference/runs/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"run_abc123\",\n \"object\": \"thread.run\",\n \"created_at\": 1699075072,\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"status\": \"completed\",\n \"started_at\": 1699075072,\n \"expires_at\": null,\n \"cancelled_at\": null,\n \"failed_at\": null,\n \"completed_at\": 1699075073,\n \"last_error\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": null,\n \"incomplete_details\": null,\n \"tools\": [\n {\n \"type\": \"code_interpreter\"\n }\n ],\n \"tool_resources\": {\n \"code_interpreter\": {\n \"file_ids\": [\n \"file-abc123\",\n \"file-abc456\"\n ]\n }\n },\n \"metadata\": {\n \"user_id\": \"user_abc123\"\n },\n \"usage\": {\n \"prompt_tokens\": 123,\n \"completion_tokens\": 456,\n \"total_tokens\": 579\n },\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_prompt_tokens\": 1000,\n \"max_completion_tokens\": 1000,\n \"truncation_strategy\": {\n \"type\": \"auto\",\n \"last_messages\": null\n },\n \"response_format\": \"auto\",\n \"tool_choice\": \"auto\",\n \"parallel_tool_calls\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"metadata\": {\n \"user_id\": \"user_abc123\"\n }\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.runs.update(\n run_id=\"run_id\",\n thread_id=\"thread_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.runs.update('run_id', { thread_id: 'thread_id' });\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.Runs.Update(\n context.TODO(),\n \"thread_id\",\n \"run_id\",\n openai.BetaThreadRunUpdateParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.Run;\nimport com.openai.models.beta.threads.runs.RunUpdateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunUpdateParams params = RunUpdateParams.builder()\n .threadId(\"thread_id\")\n .runId(\"run_id\")\n .build();\n Run run = client.beta().threads().runs().update(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.runs.update(\"run_id\", thread_id: \"thread_id\")\n\nputs(run)" - } - } - }, - "description": "Modifies a run." - } - }, - "/threads/{thread_id}/runs/{run_id}/cancel": { - "post": { - "operationId": "cancelRun", - "tags": [ - "Assistants" - ], - "summary": "Cancel a run", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread to which this run belongs." - }, - { - "in": "path", - "name": "run_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run to cancel." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RunObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Cancel a run", - "group": "threads", - "beta": true, - "returns": "The modified [run](https://platform.openai.com/docs/api-reference/runs/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"run_abc123\",\n \"object\": \"thread.run\",\n \"created_at\": 1699076126,\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"status\": \"cancelling\",\n \"started_at\": 1699076126,\n \"expires_at\": 1699076726,\n \"cancelled_at\": null,\n \"failed_at\": null,\n \"completed_at\": null,\n \"last_error\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You summarize books.\",\n \"tools\": [\n {\n \"type\": \"file_search\"\n }\n ],\n \"tool_resources\": {\n \"file_search\": {\n \"vector_store_ids\": [\"vs_123\"]\n }\n },\n \"metadata\": {},\n \"usage\": null,\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"response_format\": \"auto\",\n \"tool_choice\": \"auto\",\n \"parallel_tool_calls\": true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123/cancel \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -X POST\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.runs.cancel(\n run_id=\"run_id\",\n thread_id=\"thread_id\",\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.runs.cancel('run_id', { thread_id: 'thread_id' });\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.Runs.Cancel(\n context.TODO(),\n \"thread_id\",\n \"run_id\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.Run;\nimport com.openai.models.beta.threads.runs.RunCancelParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunCancelParams params = RunCancelParams.builder()\n .threadId(\"thread_id\")\n .runId(\"run_id\")\n .build();\n Run run = client.beta().threads().runs().cancel(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.runs.cancel(\"run_id\", thread_id: \"thread_id\")\n\nputs(run)" - } - } - }, - "description": "Cancels a run that is `in_progress`." - } - }, - "/threads/{thread_id}/runs/{run_id}/steps": { - "get": { - "operationId": "listRunSteps", - "tags": [ - "Assistants" - ], - "summary": "List run steps", - "parameters": [ - { - "name": "thread_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread the run and run steps belong to." - }, - { - "name": "run_id", - "in": "path", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run the run steps belong to." - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "before", - "in": "query", - "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "include[]", - "in": "query", - "description": "A list of additional fields to include in the response. Currently the only supported value is `step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result content.\n\nSee the [file search tool documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings) for more information.\n", - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "step_details.tool_calls[*].file_search.results[*].content" - ] - } - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListRunStepsResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List run steps", - "group": "threads", - "beta": true, - "returns": "A list of [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"step_abc123\",\n \"object\": \"thread.run.step\",\n \"created_at\": 1699063291,\n \"run_id\": \"run_abc123\",\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"type\": \"message_creation\",\n \"status\": \"completed\",\n \"cancelled_at\": null,\n \"completed_at\": 1699063291,\n \"expired_at\": null,\n \"failed_at\": null,\n \"last_error\": null,\n \"step_details\": {\n \"type\": \"message_creation\",\n \"message_creation\": {\n \"message_id\": \"msg_abc123\"\n }\n },\n \"usage\": {\n \"prompt_tokens\": 123,\n \"completion_tokens\": 456,\n \"total_tokens\": 579\n }\n }\n ],\n \"first_id\": \"step_abc123\",\n \"last_id\": \"step_abc456\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123/steps \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.beta.threads.runs.steps.list(\n run_id=\"run_id\",\n thread_id=\"thread_id\",\n)\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const runStep of client.beta.threads.runs.steps.list('run_id', { thread_id: 'thread_id' })) { console.log(runStep.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.Beta.Threads.Runs.Steps.List(\n context.TODO(),\n \"thread_id\",\n \"run_id\",\n openai.BetaThreadRunStepListParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.steps.StepListPage;\nimport com.openai.models.beta.threads.runs.steps.StepListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n StepListParams params = StepListParams.builder()\n .threadId(\"thread_id\")\n .runId(\"run_id\")\n .build();\n StepListPage page = client.beta().threads().runs().steps().list(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.beta.threads.runs.steps.list(\"run_id\", thread_id: \"thread_id\")\n\nputs(page)" - } - } - }, - "description": "Returns a list of run steps belonging to a run." - } - }, - "/threads/{thread_id}/runs/{run_id}/steps/{step_id}": { - "get": { - "operationId": "getRunStep", - "tags": [ - "Assistants" - ], - "summary": "Retrieve run step", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the thread to which the run and run step belongs." - }, - { - "in": "path", - "name": "run_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run to which the run step belongs." - }, - { - "in": "path", - "name": "step_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run step to retrieve." - }, - { - "name": "include[]", - "in": "query", - "description": "A list of additional fields to include in the response. Currently the only supported value is `step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result content.\n\nSee the [file search tool documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings) for more information.\n", - "schema": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "step_details.tool_calls[*].file_search.results[*].content" - ] - } - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RunStepObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve run step", - "group": "threads", - "beta": true, - "returns": "The [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"step_abc123\",\n \"object\": \"thread.run.step\",\n \"created_at\": 1699063291,\n \"run_id\": \"run_abc123\",\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"type\": \"message_creation\",\n \"status\": \"completed\",\n \"cancelled_at\": null,\n \"completed_at\": 1699063291,\n \"expired_at\": null,\n \"failed_at\": null,\n \"last_error\": null,\n \"step_details\": {\n \"type\": \"message_creation\",\n \"message_creation\": {\n \"message_id\": \"msg_abc123\"\n }\n },\n \"usage\": {\n \"prompt_tokens\": 123,\n \"completion_tokens\": 456,\n \"total_tokens\": 579\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123/steps/step_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun_step = client.beta.threads.runs.steps.retrieve(\n step_id=\"step_id\",\n thread_id=\"thread_id\",\n run_id=\"run_id\",\n)\nprint(run_step.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst runStep = await client.beta.threads.runs.steps.retrieve('step_id', {\n thread_id: 'thread_id',\n run_id: 'run_id',\n});\n\nconsole.log(runStep.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n runStep, err := client.Beta.Threads.Runs.Steps.Get(\n context.TODO(),\n \"thread_id\",\n \"run_id\",\n \"step_id\",\n openai.BetaThreadRunStepGetParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", runStep.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.steps.RunStep;\nimport com.openai.models.beta.threads.runs.steps.StepRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n StepRetrieveParams params = StepRetrieveParams.builder()\n .threadId(\"thread_id\")\n .runId(\"run_id\")\n .stepId(\"step_id\")\n .build();\n RunStep runStep = client.beta().threads().runs().steps().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun_step = openai.beta.threads.runs.steps.retrieve(\"step_id\", thread_id: \"thread_id\", run_id: \"run_id\")\n\nputs(run_step)" - } - } - }, - "description": "Retrieves a run step." - } - }, - "/threads/{thread_id}/runs/{run_id}/submit_tool_outputs": { - "post": { - "operationId": "submitToolOuputsToRun", - "tags": [ - "Assistants" - ], - "summary": "Submit tool outputs to run", - "parameters": [ - { - "in": "path", - "name": "thread_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) to which this run belongs." - }, - { - "in": "path", - "name": "run_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the run that requires the tool output submission." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/SubmitToolOutputsRunRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/RunObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Submit tool outputs to run", - "group": "threads", - "beta": true, - "returns": "The modified [run](https://platform.openai.com/docs/api-reference/runs/object) object matching the specified ID.", - "examples": [ - { - "title": "Default", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_123/runs/run_123/submit_tool_outputs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"tool_outputs\": [\n {\n \"tool_call_id\": \"call_001\",\n \"output\": \"70 degrees and sunny.\"\n }\n ]\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.runs.submit_tool_outputs(\n run_id=\"run_id\",\n thread_id=\"thread_id\",\n tool_outputs=[{}],\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.runs.submitToolOutputs('run_id', {\n thread_id: 'thread_id',\n tool_outputs: [{}],\n});\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.Runs.SubmitToolOutputs(\n context.TODO(),\n \"thread_id\",\n \"run_id\",\n openai.BetaThreadRunSubmitToolOutputsParams{\n ToolOutputs: []openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{\n\n }},\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.Run;\nimport com.openai.models.beta.threads.runs.RunSubmitToolOutputsParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunSubmitToolOutputsParams params = RunSubmitToolOutputsParams.builder()\n .threadId(\"thread_id\")\n .runId(\"run_id\")\n .addToolOutput(RunSubmitToolOutputsParams.ToolOutput.builder().build())\n .build();\n Run run = client.beta().threads().runs().submitToolOutputs(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.runs.submit_tool_outputs(\"run_id\", thread_id: \"thread_id\", tool_outputs: [{}])\n\nputs(run)" - }, - "response": "{\n \"id\": \"run_123\",\n \"object\": \"thread.run\",\n \"created_at\": 1699075592,\n \"assistant_id\": \"asst_123\",\n \"thread_id\": \"thread_123\",\n \"status\": \"queued\",\n \"started_at\": 1699075592,\n \"expires_at\": 1699076192,\n \"cancelled_at\": null,\n \"failed_at\": null,\n \"completed_at\": null,\n \"last_error\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": null,\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather in a given location\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and state, e.g. San Francisco, CA\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\"celsius\", \"fahrenheit\"]\n }\n },\n \"required\": [\"location\"]\n }\n }\n }\n ],\n \"metadata\": {},\n \"usage\": null,\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_prompt_tokens\": 1000,\n \"max_completion_tokens\": 1000,\n \"truncation_strategy\": {\n \"type\": \"auto\",\n \"last_messages\": null\n },\n \"response_format\": \"auto\",\n \"tool_choice\": \"auto\",\n \"parallel_tool_calls\": true\n}\n" - }, - { - "title": "Streaming", - "request": { - "curl": "curl https://api.openai.com/v1/threads/thread_123/runs/run_123/submit_tool_outputs \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"tool_outputs\": [\n {\n \"tool_call_id\": \"call_001\",\n \"output\": \"70 degrees and sunny.\"\n }\n ],\n \"stream\": true\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nrun = client.beta.threads.runs.submit_tool_outputs(\n run_id=\"run_id\",\n thread_id=\"thread_id\",\n tool_outputs=[{}],\n)\nprint(run.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst run = await client.beta.threads.runs.submitToolOutputs('run_id', {\n thread_id: 'thread_id',\n tool_outputs: [{}],\n});\n\nconsole.log(run.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n run, err := client.Beta.Threads.Runs.SubmitToolOutputs(\n context.TODO(),\n \"thread_id\",\n \"run_id\",\n openai.BetaThreadRunSubmitToolOutputsParams{\n ToolOutputs: []openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{\n\n }},\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", run.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.beta.threads.runs.Run;\nimport com.openai.models.beta.threads.runs.RunSubmitToolOutputsParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n RunSubmitToolOutputsParams params = RunSubmitToolOutputsParams.builder()\n .threadId(\"thread_id\")\n .runId(\"run_id\")\n .addToolOutput(RunSubmitToolOutputsParams.ToolOutput.builder().build())\n .build();\n Run run = client.beta().threads().runs().submitToolOutputs(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nrun = openai.beta.threads.runs.submit_tool_outputs(\"run_id\", thread_id: \"thread_id\", tool_outputs: [{}])\n\nputs(run)" - }, - "response": "event: thread.run.step.completed\ndata: {\"id\":\"step_001\",\"object\":\"thread.run.step\",\"created_at\":1710352449,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"tool_calls\",\"status\":\"completed\",\"cancelled_at\":null,\"completed_at\":1710352475,\"expires_at\":1710353047,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"tool_calls\",\"tool_calls\":[{\"id\":\"call_iWr0kQ2EaYMaxNdl0v3KYkx7\",\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"arguments\":\"{\\\"location\\\":\\\"San Francisco, CA\\\",\\\"unit\\\":\\\"fahrenheit\\\"}\",\"output\":\"70 degrees and sunny.\"}}]},\"usage\":{\"prompt_tokens\":291,\"completion_tokens\":24,\"total_tokens\":315}}\n\nevent: thread.run.queued\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710352447,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"queued\",\"started_at\":1710352448,\"expires_at\":1710353047,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"description\":\"Get the current weather in a given location\",\"parameters\":{\"type\":\"object\",\"properties\":{\"location\":{\"type\":\"string\",\"description\":\"The city and state, e.g. San Francisco, CA\"},\"unit\":{\"type\":\"string\",\"enum\":[\"celsius\",\"fahrenheit\"]}},\"required\":[\"location\"]}}}],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.in_progress\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710352447,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"in_progress\",\"started_at\":1710352475,\"expires_at\":1710353047,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":null,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"description\":\"Get the current weather in a given location\",\"parameters\":{\"type\":\"object\",\"properties\":{\"location\":{\"type\":\"string\",\"description\":\"The city and state, e.g. San Francisco, CA\"},\"unit\":{\"type\":\"string\",\"enum\":[\"celsius\",\"fahrenheit\"]}},\"required\":[\"location\"]}}}],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":null,\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: thread.run.step.created\ndata: {\"id\":\"step_002\",\"object\":\"thread.run.step\",\"created_at\":1710352476,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710353047,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_002\"}},\"usage\":null}\n\nevent: thread.run.step.in_progress\ndata: {\"id\":\"step_002\",\"object\":\"thread.run.step\",\"created_at\":1710352476,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"in_progress\",\"cancelled_at\":null,\"completed_at\":null,\"expires_at\":1710353047,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_002\"}},\"usage\":null}\n\nevent: thread.message.created\ndata: {\"id\":\"msg_002\",\"object\":\"thread.message\",\"created_at\":1710352476,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"in_progress\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":null,\"role\":\"assistant\",\"content\":[],\"metadata\":{}}\n\nevent: thread.message.in_progress\ndata: {\"id\":\"msg_002\",\"object\":\"thread.message\",\"created_at\":1710352476,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"in_progress\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":null,\"role\":\"assistant\",\"content\":[],\"metadata\":{}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_002\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\"The\",\"annotations\":[]}}]}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_002\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\" current\"}}]}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_002\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\" weather\"}}]}}\n\n...\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_002\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\" sunny\"}}]}}\n\nevent: thread.message.delta\ndata: {\"id\":\"msg_002\",\"object\":\"thread.message.delta\",\"delta\":{\"content\":[{\"index\":0,\"type\":\"text\",\"text\":{\"value\":\".\"}}]}}\n\nevent: thread.message.completed\ndata: {\"id\":\"msg_002\",\"object\":\"thread.message\",\"created_at\":1710352476,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"run_id\":\"run_123\",\"status\":\"completed\",\"incomplete_details\":null,\"incomplete_at\":null,\"completed_at\":1710352477,\"role\":\"assistant\",\"content\":[{\"type\":\"text\",\"text\":{\"value\":\"The current weather in San Francisco, CA is 70 degrees Fahrenheit and sunny.\",\"annotations\":[]}}],\"metadata\":{}}\n\nevent: thread.run.step.completed\ndata: {\"id\":\"step_002\",\"object\":\"thread.run.step\",\"created_at\":1710352476,\"run_id\":\"run_123\",\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"type\":\"message_creation\",\"status\":\"completed\",\"cancelled_at\":null,\"completed_at\":1710352477,\"expires_at\":1710353047,\"failed_at\":null,\"last_error\":null,\"step_details\":{\"type\":\"message_creation\",\"message_creation\":{\"message_id\":\"msg_002\"}},\"usage\":{\"prompt_tokens\":329,\"completion_tokens\":18,\"total_tokens\":347}}\n\nevent: thread.run.completed\ndata: {\"id\":\"run_123\",\"object\":\"thread.run\",\"created_at\":1710352447,\"assistant_id\":\"asst_123\",\"thread_id\":\"thread_123\",\"status\":\"completed\",\"started_at\":1710352475,\"expires_at\":null,\"cancelled_at\":null,\"failed_at\":null,\"completed_at\":1710352477,\"required_action\":null,\"last_error\":null,\"model\":\"gpt-4o\",\"instructions\":null,\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_current_weather\",\"description\":\"Get the current weather in a given location\",\"parameters\":{\"type\":\"object\",\"properties\":{\"location\":{\"type\":\"string\",\"description\":\"The city and state, e.g. San Francisco, CA\"},\"unit\":{\"type\":\"string\",\"enum\":[\"celsius\",\"fahrenheit\"]}},\"required\":[\"location\"]}}}],\"metadata\":{},\"temperature\":1.0,\"top_p\":1.0,\"max_completion_tokens\":null,\"max_prompt_tokens\":null,\"truncation_strategy\":{\"type\":\"auto\",\"last_messages\":null},\"incomplete_details\":null,\"usage\":{\"prompt_tokens\":20,\"completion_tokens\":11,\"total_tokens\":31},\"response_format\":\"auto\",\"tool_choice\":\"auto\",\"parallel_tool_calls\":true}}\n\nevent: done\ndata: [DONE]\n" - } - ] - }, - "description": "When a run has the `status: \"requires_action\"` and `required_action.type` is `submit_tool_outputs`, this endpoint can be used to submit the outputs from the tool calls once they're all completed. All outputs must be submitted in a single request.\n" - } - }, - "/uploads": { - "post": { - "operationId": "createUpload", - "tags": [ - "Uploads" - ], - "summary": "Create upload", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateUploadRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Upload" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create upload", - "group": "uploads", - "returns": "The [Upload](https://platform.openai.com/docs/api-reference/uploads/object) object with status `pending`.", - "examples": { - "response": "{\n \"id\": \"upload_abc123\",\n \"object\": \"upload\",\n \"bytes\": 2147483648,\n \"created_at\": 1719184911,\n \"filename\": \"training_examples.jsonl\",\n \"purpose\": \"fine-tune\",\n \"status\": \"pending\",\n \"expires_at\": 1719127296\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/uploads \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -d '{\n \"purpose\": \"fine-tune\",\n \"filename\": \"training_examples.jsonl\",\n \"bytes\": 2147483648,\n \"mime_type\": \"text/jsonl\",\n \"expires_after\": {\n \"anchor\": \"created_at\",\n \"seconds\": 3600\n }\n }'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst upload = await client.uploads.create({\n bytes: 0,\n filename: 'filename',\n mime_type: 'mime_type',\n purpose: 'assistants',\n});\n\nconsole.log(upload.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nupload = client.uploads.create(\n bytes=0,\n filename=\"filename\",\n mime_type=\"mime_type\",\n purpose=\"assistants\",\n)\nprint(upload.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n upload, err := client.Uploads.New(context.TODO(), openai.UploadNewParams{\n Bytes: 0,\n Filename: \"filename\",\n MimeType: \"mime_type\",\n Purpose: openai.FilePurposeAssistants,\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", upload.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.files.FilePurpose;\nimport com.openai.models.uploads.Upload;\nimport com.openai.models.uploads.UploadCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n UploadCreateParams params = UploadCreateParams.builder()\n .bytes(0L)\n .filename(\"filename\")\n .mimeType(\"mime_type\")\n .purpose(FilePurpose.ASSISTANTS)\n .build();\n Upload upload = client.uploads().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nupload = openai.uploads.create(bytes: 0, filename: \"filename\", mime_type: \"mime_type\", purpose: :assistants)\n\nputs(upload)" - } - } - }, - "description": "Creates an intermediate [Upload](https://platform.openai.com/docs/api-reference/uploads/object) object\nthat you can add [Parts](https://platform.openai.com/docs/api-reference/uploads/part-object) to.\nCurrently, an Upload can accept at most 8 GB in total and expires after an\nhour after you create it.\n\nOnce you complete the Upload, we will create a\n[File](https://platform.openai.com/docs/api-reference/files/object) object that contains all the parts\nyou uploaded. This File is usable in the rest of our platform as a regular\nFile object.\n\nFor certain `purpose` values, the correct `mime_type` must be specified.\nPlease refer to documentation for the\n[supported MIME types for your use case](https://platform.openai.com/docs/assistants/tools/file-search#supported-files).\n\nFor guidance on the proper filename extensions for each purpose, please\nfollow the documentation on [creating a\nFile](https://platform.openai.com/docs/api-reference/files/create).\n" - } - }, - "/uploads/{upload_id}/cancel": { - "post": { - "operationId": "cancelUpload", - "tags": [ - "Uploads" - ], - "summary": "Cancel upload", - "parameters": [ - { - "in": "path", - "name": "upload_id", - "required": true, - "schema": { - "type": "string", - "example": "upload_abc123" - }, - "description": "The ID of the Upload.\n" - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Upload" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Cancel upload", - "group": "uploads", - "returns": "The [Upload](https://platform.openai.com/docs/api-reference/uploads/object) object with status `cancelled`.", - "examples": { - "response": "{\n \"id\": \"upload_abc123\",\n \"object\": \"upload\",\n \"bytes\": 2147483648,\n \"created_at\": 1719184911,\n \"filename\": \"training_examples.jsonl\",\n \"purpose\": \"fine-tune\",\n \"status\": \"cancelled\",\n \"expires_at\": 1719127296\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/uploads/upload_abc123/cancel\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst upload = await client.uploads.cancel('upload_abc123');\n\nconsole.log(upload.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nupload = client.uploads.cancel(\n \"upload_abc123\",\n)\nprint(upload.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n upload, err := client.Uploads.Cancel(context.TODO(), \"upload_abc123\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", upload.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.uploads.Upload;\nimport com.openai.models.uploads.UploadCancelParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n Upload upload = client.uploads().cancel(\"upload_abc123\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nupload = openai.uploads.cancel(\"upload_abc123\")\n\nputs(upload)" - } - } - }, - "description": "Cancels the Upload. No Parts may be added after an Upload is cancelled.\n" - } - }, - "/uploads/{upload_id}/complete": { - "post": { - "operationId": "completeUpload", - "tags": [ - "Uploads" - ], - "summary": "Complete upload", - "parameters": [ - { - "in": "path", - "name": "upload_id", - "required": true, - "schema": { - "type": "string", - "example": "upload_abc123" - }, - "description": "The ID of the Upload.\n" - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CompleteUploadRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/Upload" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Complete upload", - "group": "uploads", - "returns": "The [Upload](https://platform.openai.com/docs/api-reference/uploads/object) object with status `completed` with an additional `file` property containing the created usable File object.", - "examples": { - "response": "{\n \"id\": \"upload_abc123\",\n \"object\": \"upload\",\n \"bytes\": 2147483648,\n \"created_at\": 1719184911,\n \"filename\": \"training_examples.jsonl\",\n \"purpose\": \"fine-tune\",\n \"status\": \"completed\",\n \"expires_at\": 1719127296,\n \"file\": {\n \"id\": \"file-xyz321\",\n \"object\": \"file\",\n \"bytes\": 2147483648,\n \"created_at\": 1719186911,\n \"expires_at\": 1719127296,\n \"filename\": \"training_examples.jsonl\",\n \"purpose\": \"fine-tune\",\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/uploads/upload_abc123/complete\n -d '{\n \"part_ids\": [\"part_def456\", \"part_ghi789\"]\n }'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst upload = await client.uploads.complete('upload_abc123', { part_ids: ['string'] });\n\nconsole.log(upload.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nupload = client.uploads.complete(\n upload_id=\"upload_abc123\",\n part_ids=[\"string\"],\n)\nprint(upload.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n upload, err := client.Uploads.Complete(\n context.TODO(),\n \"upload_abc123\",\n openai.UploadCompleteParams{\n PartIDs: []string{\"string\"},\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", upload.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.uploads.Upload;\nimport com.openai.models.uploads.UploadCompleteParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n UploadCompleteParams params = UploadCompleteParams.builder()\n .uploadId(\"upload_abc123\")\n .addPartId(\"string\")\n .build();\n Upload upload = client.uploads().complete(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nupload = openai.uploads.complete(\"upload_abc123\", part_ids: [\"string\"])\n\nputs(upload)" - } - } - }, - "description": "Completes the [Upload](https://platform.openai.com/docs/api-reference/uploads/object).\n\nWithin the returned Upload object, there is a nested [File](https://platform.openai.com/docs/api-reference/files/object) object that is ready to use in the rest of the platform.\n\nYou can specify the order of the Parts by passing in an ordered list of the Part IDs.\n\nThe number of bytes uploaded upon completion must match the number of bytes initially specified when creating the Upload object. No Parts may be added after an Upload is completed.\n" - } - }, - "/uploads/{upload_id}/parts": { - "post": { - "operationId": "addUploadPart", - "tags": [ - "Uploads" - ], - "summary": "Add upload part", - "parameters": [ - { - "in": "path", - "name": "upload_id", - "required": true, - "schema": { - "type": "string", - "example": "upload_abc123" - }, - "description": "The ID of the Upload.\n" - } - ], - "requestBody": { - "required": true, - "content": { - "multipart/form-data": { - "schema": { - "$ref": "#/components/schemas/AddUploadPartRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UploadPart" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Add upload part", - "group": "uploads", - "returns": "The upload [Part](https://platform.openai.com/docs/api-reference/uploads/part-object) object.", - "examples": { - "response": "{\n \"id\": \"part_def456\",\n \"object\": \"upload.part\",\n \"created_at\": 1719185911,\n \"upload_id\": \"upload_abc123\"\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/uploads/upload_abc123/parts\n -F data=\"aHR0cHM6Ly9hcGkub3BlbmFpLmNvbS92MS91cGxvYWRz...\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst uploadPart = await client.uploads.parts.create('upload_abc123', {\n data: fs.createReadStream('path/to/file'),\n});\n\nconsole.log(uploadPart.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nupload_part = client.uploads.parts.create(\n upload_id=\"upload_abc123\",\n data=b\"raw file contents\",\n)\nprint(upload_part.id)", - "go": "package main\n\nimport (\n \"bytes\"\n \"context\"\n \"fmt\"\n \"io\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n uploadPart, err := client.Uploads.Parts.New(\n context.TODO(),\n \"upload_abc123\",\n openai.UploadPartNewParams{\n Data: io.Reader(bytes.NewBuffer([]byte(\"some file contents\"))),\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", uploadPart.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.uploads.parts.PartCreateParams;\nimport com.openai.models.uploads.parts.UploadPart;\nimport java.io.ByteArrayInputStream;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n PartCreateParams params = PartCreateParams.builder()\n .uploadId(\"upload_abc123\")\n .data(ByteArrayInputStream(\"some content\".getBytes()))\n .build();\n UploadPart uploadPart = client.uploads().parts().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nupload_part = openai.uploads.parts.create(\"upload_abc123\", data: Pathname(__FILE__))\n\nputs(upload_part)" - } - } - }, - "description": "Adds a [Part](https://platform.openai.com/docs/api-reference/uploads/part-object) to an [Upload](https://platform.openai.com/docs/api-reference/uploads/object) object. A Part represents a chunk of bytes from the file you are trying to upload.\n\nEach Part can be at most 64 MB, and you can add Parts until you hit the Upload maximum of 8 GB.\n\nIt is possible to add multiple Parts in parallel. You can decide the intended order of the Parts when you [complete the Upload](https://platform.openai.com/docs/api-reference/uploads/complete).\n" - } - }, - "/vector_stores": { - "get": { - "operationId": "listVectorStores", - "tags": [ - "Vector stores" - ], - "summary": "List vector stores", - "parameters": [ - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "before", - "in": "query", - "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.\n", - "schema": { - "type": "string" - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListVectorStoresResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List vector stores", - "group": "vector_stores", - "returns": "A list of [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"vs_abc123\",\n \"object\": \"vector_store\",\n \"created_at\": 1699061776,\n \"name\": \"Support FAQ\",\n \"bytes\": 139920,\n \"file_counts\": {\n \"in_progress\": 0,\n \"completed\": 3,\n \"failed\": 0,\n \"cancelled\": 0,\n \"total\": 3\n }\n },\n {\n \"id\": \"vs_abc456\",\n \"object\": \"vector_store\",\n \"created_at\": 1699061776,\n \"name\": \"Support FAQ v2\",\n \"bytes\": 139920,\n \"file_counts\": {\n \"in_progress\": 0,\n \"completed\": 3,\n \"failed\": 0,\n \"cancelled\": 0,\n \"total\": 3\n }\n }\n ],\n \"first_id\": \"vs_abc123\",\n \"last_id\": \"vs_abc456\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.vector_stores.list()\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const vectorStore of client.vectorStores.list()) {\n console.log(vectorStore.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.VectorStores.List(context.TODO(), openai.VectorStoreListParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStoreListPage;\nimport com.openai.models.vectorstores.VectorStoreListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n VectorStoreListPage page = client.vectorStores().list();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.vector_stores.list\n\nputs(page)" - } - } - }, - "description": "Returns a list of vector stores." - }, - "post": { - "operationId": "createVectorStore", - "tags": [ - "Vector stores" - ], - "summary": "Create vector store", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateVectorStoreRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create vector store", - "group": "vector_stores", - "returns": "A [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) object.", - "examples": { - "response": "{\n \"id\": \"vs_abc123\",\n \"object\": \"vector_store\",\n \"created_at\": 1699061776,\n \"name\": \"Support FAQ\",\n \"bytes\": 139920,\n \"file_counts\": {\n \"in_progress\": 0,\n \"completed\": 3,\n \"failed\": 0,\n \"cancelled\": 0,\n \"total\": 3\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"name\": \"Support FAQ\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store = client.vector_stores.create()\nprint(vector_store.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStore = await client.vectorStores.create();\n\nconsole.log(vectorStore.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStore, err := client.VectorStores.New(context.TODO(), openai.VectorStoreNewParams{\n\n })\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStore.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStore;\nimport com.openai.models.vectorstores.VectorStoreCreateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n VectorStore vectorStore = client.vectorStores().create();\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store = openai.vector_stores.create\n\nputs(vector_store)" - } - } - }, - "description": "Create a vector store." - } - }, - "/vector_stores/{vector_store_id}": { - "get": { - "operationId": "getVectorStore", - "tags": [ - "Vector stores" - ], - "summary": "Retrieve vector store", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the vector store to retrieve." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve vector store", - "group": "vector_stores", - "returns": "The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) object matching the specified ID.", - "examples": { - "response": "{\n \"id\": \"vs_abc123\",\n \"object\": \"vector_store\",\n \"created_at\": 1699061776\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store = client.vector_stores.retrieve(\n \"vector_store_id\",\n)\nprint(vector_store.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStore = await client.vectorStores.retrieve('vector_store_id');\n\nconsole.log(vectorStore.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStore, err := client.VectorStores.Get(context.TODO(), \"vector_store_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStore.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStore;\nimport com.openai.models.vectorstores.VectorStoreRetrieveParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n VectorStore vectorStore = client.vectorStores().retrieve(\"vector_store_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store = openai.vector_stores.retrieve(\"vector_store_id\")\n\nputs(vector_store)" - } - } - }, - "description": "Retrieves a vector store." - }, - "post": { - "operationId": "modifyVectorStore", - "tags": [ - "Vector stores" - ], - "summary": "Modify vector store", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the vector store to modify." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UpdateVectorStoreRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Modify vector store", - "group": "vector_stores", - "returns": "The modified [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) object.", - "examples": { - "response": "{\n \"id\": \"vs_abc123\",\n \"object\": \"vector_store\",\n \"created_at\": 1699061776,\n \"name\": \"Support FAQ\",\n \"bytes\": 139920,\n \"file_counts\": {\n \"in_progress\": 0,\n \"completed\": 3,\n \"failed\": 0,\n \"cancelled\": 0,\n \"total\": 3\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n -d '{\n \"name\": \"Support FAQ\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store = client.vector_stores.update(\n vector_store_id=\"vector_store_id\",\n)\nprint(vector_store.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStore = await client.vectorStores.update('vector_store_id');\n\nconsole.log(vectorStore.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStore, err := client.VectorStores.Update(\n context.TODO(),\n \"vector_store_id\",\n openai.VectorStoreUpdateParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStore.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStore;\nimport com.openai.models.vectorstores.VectorStoreUpdateParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n VectorStore vectorStore = client.vectorStores().update(\"vector_store_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store = openai.vector_stores.update(\"vector_store_id\")\n\nputs(vector_store)" - } - } - }, - "description": "Modifies a vector store." - }, - "delete": { - "operationId": "deleteVectorStore", - "tags": [ - "Vector stores" - ], - "summary": "Delete vector store", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the vector store to delete." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeleteVectorStoreResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete vector store", - "group": "vector_stores", - "returns": "Deletion status", - "examples": { - "response": "{\n id: \"vs_abc123\",\n object: \"vector_store.deleted\",\n deleted: true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -X DELETE\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store_deleted = client.vector_stores.delete(\n \"vector_store_id\",\n)\nprint(vector_store_deleted.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStoreDeleted = await client.vectorStores.delete('vector_store_id');\n\nconsole.log(vectorStoreDeleted.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStoreDeleted, err := client.VectorStores.Delete(context.TODO(), \"vector_store_id\")\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStoreDeleted.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStoreDeleteParams;\nimport com.openai.models.vectorstores.VectorStoreDeleted;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n VectorStoreDeleted vectorStoreDeleted = client.vectorStores().delete(\"vector_store_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store_deleted = openai.vector_stores.delete(\"vector_store_id\")\n\nputs(vector_store_deleted)" - } - } - }, - "description": "Delete a vector store." - } - }, - "/vector_stores/{vector_store_id}/file_batches": { - "post": { - "operationId": "createVectorStoreFileBatch", - "tags": [ - "Vector stores" - ], - "summary": "Create vector store file batch", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string", - "example": "vs_abc123" - }, - "description": "The ID of the vector store for which to create a File Batch.\n" - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateVectorStoreFileBatchRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreFileBatchObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create vector store file batch", - "group": "vector_stores", - "returns": "A [vector store file batch](https://platform.openai.com/docs/api-reference/vector-stores-file-batches/batch-object) object.", - "examples": { - "response": "{\n \"id\": \"vsfb_abc123\",\n \"object\": \"vector_store.file_batch\",\n \"created_at\": 1699061776,\n \"vector_store_id\": \"vs_abc123\",\n \"status\": \"in_progress\",\n \"file_counts\": {\n \"in_progress\": 1,\n \"completed\": 1,\n \"failed\": 0,\n \"cancelled\": 0,\n \"total\": 0,\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123/file_batches \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"file_ids\": [\"file-abc123\", \"file-abc456\"]\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store_file_batch = client.vector_stores.file_batches.create(\n vector_store_id=\"vs_abc123\",\n file_ids=[\"string\"],\n)\nprint(vector_store_file_batch.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStoreFileBatch = await client.vectorStores.fileBatches.create('vs_abc123', {\n file_ids: ['string'],\n});\n\nconsole.log(vectorStoreFileBatch.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStoreFileBatch, err := client.VectorStores.FileBatches.New(\n context.TODO(),\n \"vs_abc123\",\n openai.VectorStoreFileBatchNewParams{\n FileIDs: []string{\"string\"},\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStoreFileBatch.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.filebatches.FileBatchCreateParams;\nimport com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileBatchCreateParams params = FileBatchCreateParams.builder()\n .vectorStoreId(\"vs_abc123\")\n .addFileId(\"string\")\n .build();\n VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store_file_batch = openai.vector_stores.file_batches.create(\"vs_abc123\", file_ids: [\"string\"])\n\nputs(vector_store_file_batch)" - } - } - }, - "description": "Create a vector store file batch." - } - }, - "/vector_stores/{vector_store_id}/file_batches/{batch_id}": { - "get": { - "operationId": "getVectorStoreFileBatch", - "tags": [ - "Vector stores" - ], - "summary": "Retrieve vector store file batch", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string", - "example": "vs_abc123" - }, - "description": "The ID of the vector store that the file batch belongs to." - }, - { - "in": "path", - "name": "batch_id", - "required": true, - "schema": { - "type": "string", - "example": "vsfb_abc123" - }, - "description": "The ID of the file batch being retrieved." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreFileBatchObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve vector store file batch", - "group": "vector_stores", - "returns": "The [vector store file batch](https://platform.openai.com/docs/api-reference/vector-stores-file-batches/batch-object) object.", - "examples": { - "response": "{\n \"id\": \"vsfb_abc123\",\n \"object\": \"vector_store.file_batch\",\n \"created_at\": 1699061776,\n \"vector_store_id\": \"vs_abc123\",\n \"status\": \"in_progress\",\n \"file_counts\": {\n \"in_progress\": 1,\n \"completed\": 1,\n \"failed\": 0,\n \"cancelled\": 0,\n \"total\": 0,\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store_file_batch = client.vector_stores.file_batches.retrieve(\n batch_id=\"vsfb_abc123\",\n vector_store_id=\"vs_abc123\",\n)\nprint(vector_store_file_batch.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStoreFileBatch = await client.vectorStores.fileBatches.retrieve('vsfb_abc123', {\n vector_store_id: 'vs_abc123',\n});\n\nconsole.log(vectorStoreFileBatch.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStoreFileBatch, err := client.VectorStores.FileBatches.Get(\n context.TODO(),\n \"vs_abc123\",\n \"vsfb_abc123\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStoreFileBatch.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.filebatches.FileBatchRetrieveParams;\nimport com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileBatchRetrieveParams params = FileBatchRetrieveParams.builder()\n .vectorStoreId(\"vs_abc123\")\n .batchId(\"vsfb_abc123\")\n .build();\n VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store_file_batch = openai.vector_stores.file_batches.retrieve(\"vsfb_abc123\", vector_store_id: \"vs_abc123\")\n\nputs(vector_store_file_batch)" - } - } - }, - "description": "Retrieves a vector store file batch." - } - }, - "/vector_stores/{vector_store_id}/file_batches/{batch_id}/cancel": { - "post": { - "operationId": "cancelVectorStoreFileBatch", - "tags": [ - "Vector stores" - ], - "summary": "Cancel vector store file batch", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the vector store that the file batch belongs to." - }, - { - "in": "path", - "name": "batch_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the file batch to cancel." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreFileBatchObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Cancel vector store file batch", - "group": "vector_stores", - "returns": "The modified vector store file batch object.", - "examples": { - "response": "{\n \"id\": \"vsfb_abc123\",\n \"object\": \"vector_store.file_batch\",\n \"created_at\": 1699061776,\n \"vector_store_id\": \"vs_abc123\",\n \"status\": \"in_progress\",\n \"file_counts\": {\n \"in_progress\": 12,\n \"completed\": 3,\n \"failed\": 0,\n \"cancelled\": 0,\n \"total\": 15,\n }\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/cancel \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -X POST\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store_file_batch = client.vector_stores.file_batches.cancel(\n batch_id=\"batch_id\",\n vector_store_id=\"vector_store_id\",\n)\nprint(vector_store_file_batch.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStoreFileBatch = await client.vectorStores.fileBatches.cancel('batch_id', {\n vector_store_id: 'vector_store_id',\n});\n\nconsole.log(vectorStoreFileBatch.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStoreFileBatch, err := client.VectorStores.FileBatches.Cancel(\n context.TODO(),\n \"vector_store_id\",\n \"batch_id\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStoreFileBatch.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.filebatches.FileBatchCancelParams;\nimport com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileBatchCancelParams params = FileBatchCancelParams.builder()\n .vectorStoreId(\"vector_store_id\")\n .batchId(\"batch_id\")\n .build();\n VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().cancel(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store_file_batch = openai.vector_stores.file_batches.cancel(\"batch_id\", vector_store_id: \"vector_store_id\")\n\nputs(vector_store_file_batch)" - } - } - }, - "description": "Cancel a vector store file batch. This attempts to cancel the processing of files in this batch as soon as possible." - } - }, - "/vector_stores/{vector_store_id}/file_batches/{batch_id}/files": { - "get": { - "operationId": "listFilesInVectorStoreBatch", - "tags": [ - "Vector stores" - ], - "summary": "List vector store files in a batch", - "parameters": [ - { - "name": "vector_store_id", - "in": "path", - "description": "The ID of the vector store that the files belong to.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "batch_id", - "in": "path", - "description": "The ID of the file batch that the files belong to.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "before", - "in": "query", - "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "filter", - "in": "query", - "description": "Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`.", - "schema": { - "type": "string", - "enum": [ - "in_progress", - "completed", - "failed", - "cancelled" - ] - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListVectorStoreFilesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List vector store files in a batch", - "group": "vector_stores", - "returns": "A list of [vector store file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"file-abc123\",\n \"object\": \"vector_store.file\",\n \"created_at\": 1699061776,\n \"vector_store_id\": \"vs_abc123\"\n },\n {\n \"id\": \"file-abc456\",\n \"object\": \"vector_store.file\",\n \"created_at\": 1699061776,\n \"vector_store_id\": \"vs_abc123\"\n }\n ],\n \"first_id\": \"file-abc123\",\n \"last_id\": \"file-abc456\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/files \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.vector_stores.file_batches.list_files(\n batch_id=\"batch_id\",\n vector_store_id=\"vector_store_id\",\n)\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const vectorStoreFile of client.vectorStores.fileBatches.listFiles('batch_id', {\n vector_store_id: 'vector_store_id',\n})) {\n console.log(vectorStoreFile.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.VectorStores.FileBatches.ListFiles(\n context.TODO(),\n \"vector_store_id\",\n \"batch_id\",\n openai.VectorStoreFileBatchListFilesParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.filebatches.FileBatchListFilesPage;\nimport com.openai.models.vectorstores.filebatches.FileBatchListFilesParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileBatchListFilesParams params = FileBatchListFilesParams.builder()\n .vectorStoreId(\"vector_store_id\")\n .batchId(\"batch_id\")\n .build();\n FileBatchListFilesPage page = client.vectorStores().fileBatches().listFiles(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.vector_stores.file_batches.list_files(\"batch_id\", vector_store_id: \"vector_store_id\")\n\nputs(page)" - } - } - }, - "description": "Returns a list of vector store files in a batch." - } - }, - "/vector_stores/{vector_store_id}/files": { - "get": { - "operationId": "listVectorStoreFiles", - "tags": [ - "Vector stores" - ], - "summary": "List vector store files", - "parameters": [ - { - "name": "vector_store_id", - "in": "path", - "description": "The ID of the vector store that the files belong to.", - "required": true, - "schema": { - "type": "string" - } - }, - { - "name": "limit", - "in": "query", - "description": "A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.\n", - "required": false, - "schema": { - "type": "integer", - "default": 20 - } - }, - { - "name": "order", - "in": "query", - "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", - "schema": { - "type": "string", - "default": "desc", - "enum": [ - "asc", - "desc" - ] - } - }, - { - "name": "after", - "in": "query", - "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "before", - "in": "query", - "description": "A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.\n", - "schema": { - "type": "string" - } - }, - { - "name": "filter", - "in": "query", - "description": "Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`.", - "schema": { - "type": "string", - "enum": [ - "in_progress", - "completed", - "failed", - "cancelled" - ] - } - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ListVectorStoreFilesResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "List vector store files", - "group": "vector_stores", - "returns": "A list of [vector store file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) objects.", - "examples": { - "response": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"file-abc123\",\n \"object\": \"vector_store.file\",\n \"created_at\": 1699061776,\n \"vector_store_id\": \"vs_abc123\"\n },\n {\n \"id\": \"file-abc456\",\n \"object\": \"vector_store.file\",\n \"created_at\": 1699061776,\n \"vector_store_id\": \"vs_abc123\"\n }\n ],\n \"first_id\": \"file-abc123\",\n \"last_id\": \"file-abc456\",\n \"has_more\": false\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123/files \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.vector_stores.files.list(\n vector_store_id=\"vector_store_id\",\n)\npage = page.data[0]\nprint(page.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const vectorStoreFile of client.vectorStores.files.list('vector_store_id')) {\n console.log(vectorStoreFile.id);\n}", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.VectorStores.Files.List(\n context.TODO(),\n \"vector_store_id\",\n openai.VectorStoreFileListParams{\n\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.files.FileListPage;\nimport com.openai.models.vectorstores.files.FileListParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileListPage page = client.vectorStores().files().list(\"vector_store_id\");\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.vector_stores.files.list(\"vector_store_id\")\n\nputs(page)" - } - } - }, - "description": "Returns a list of vector store files." - }, - "post": { - "operationId": "createVectorStoreFile", - "tags": [ - "Vector stores" - ], - "summary": "Create vector store file", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string", - "example": "vs_abc123" - }, - "description": "The ID of the vector store for which to create a File.\n" - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateVectorStoreFileRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreFileObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Create vector store file", - "group": "vector_stores", - "returns": "A [vector store file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) object.", - "examples": { - "response": "{\n \"id\": \"file-abc123\",\n \"object\": \"vector_store.file\",\n \"created_at\": 1699061776,\n \"usage_bytes\": 1234,\n \"vector_store_id\": \"vs_abcd\",\n \"status\": \"completed\",\n \"last_error\": null\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123/files \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -d '{\n \"file_id\": \"file-abc123\"\n }'\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store_file = client.vector_stores.files.create(\n vector_store_id=\"vs_abc123\",\n file_id=\"file_id\",\n)\nprint(vector_store_file.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\nconst vectorStoreFile = await client.vectorStores.files.create('vs_abc123', { file_id: 'file_id' });\n\nconsole.log(vectorStoreFile.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStoreFile, err := client.VectorStores.Files.New(\n context.TODO(),\n \"vs_abc123\",\n openai.VectorStoreFileNewParams{\n FileID: \"file_id\",\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStoreFile.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.files.FileCreateParams;\nimport com.openai.models.vectorstores.files.VectorStoreFile;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileCreateParams params = FileCreateParams.builder()\n .vectorStoreId(\"vs_abc123\")\n .fileId(\"file_id\")\n .build();\n VectorStoreFile vectorStoreFile = client.vectorStores().files().create(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store_file = openai.vector_stores.files.create(\"vs_abc123\", file_id: \"file_id\")\n\nputs(vector_store_file)" - } - } - }, - "description": "Create a vector store file by attaching a [File](https://platform.openai.com/docs/api-reference/files) to a [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object)." - } - }, - "/vector_stores/{vector_store_id}/files/{file_id}": { - "get": { - "operationId": "getVectorStoreFile", - "tags": [ - "Vector stores" - ], - "summary": "Retrieve vector store file", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string", - "example": "vs_abc123" - }, - "description": "The ID of the vector store that the file belongs to." - }, - { - "in": "path", - "name": "file_id", - "required": true, - "schema": { - "type": "string", - "example": "file-abc123" - }, - "description": "The ID of the file being retrieved." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreFileObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve vector store file", - "group": "vector_stores", - "returns": "The [vector store file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) object.", - "examples": { - "response": "{\n \"id\": \"file-abc123\",\n \"object\": \"vector_store.file\",\n \"created_at\": 1699061776,\n \"vector_store_id\": \"vs_abcd\",\n \"status\": \"completed\",\n \"last_error\": null\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123/files/file-abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\"\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store_file = client.vector_stores.files.retrieve(\n file_id=\"file-abc123\",\n vector_store_id=\"vs_abc123\",\n)\nprint(vector_store_file.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStoreFile = await client.vectorStores.files.retrieve('file-abc123', {\n vector_store_id: 'vs_abc123',\n});\n\nconsole.log(vectorStoreFile.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStoreFile, err := client.VectorStores.Files.Get(\n context.TODO(),\n \"vs_abc123\",\n \"file-abc123\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStoreFile.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.files.FileRetrieveParams;\nimport com.openai.models.vectorstores.files.VectorStoreFile;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileRetrieveParams params = FileRetrieveParams.builder()\n .vectorStoreId(\"vs_abc123\")\n .fileId(\"file-abc123\")\n .build();\n VectorStoreFile vectorStoreFile = client.vectorStores().files().retrieve(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store_file = openai.vector_stores.files.retrieve(\"file-abc123\", vector_store_id: \"vs_abc123\")\n\nputs(vector_store_file)" - } - } - }, - "description": "Retrieves a vector store file." - }, - "delete": { - "operationId": "deleteVectorStoreFile", - "tags": [ - "Vector stores" - ], - "summary": "Delete vector store file", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the vector store that the file belongs to." - }, - { - "in": "path", - "name": "file_id", - "required": true, - "schema": { - "type": "string" - }, - "description": "The ID of the file to delete." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/DeleteVectorStoreFileResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Delete vector store file", - "group": "vector_stores", - "returns": "Deletion status", - "examples": { - "response": "{\n id: \"file-abc123\",\n object: \"vector_store.file.deleted\",\n deleted: true\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/vs_abc123/files/file-abc123 \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"OpenAI-Beta: assistants=v2\" \\\n -X DELETE\n", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store_file_deleted = client.vector_stores.files.delete(\n file_id=\"file_id\",\n vector_store_id=\"vector_store_id\",\n)\nprint(vector_store_file_deleted.id)", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStoreFileDeleted = await client.vectorStores.files.delete('file_id', {\n vector_store_id: 'vector_store_id',\n});\n\nconsole.log(vectorStoreFileDeleted.id);", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStoreFileDeleted, err := client.VectorStores.Files.Delete(\n context.TODO(),\n \"vector_store_id\",\n \"file_id\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStoreFileDeleted.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.files.FileDeleteParams;\nimport com.openai.models.vectorstores.files.VectorStoreFileDeleted;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileDeleteParams params = FileDeleteParams.builder()\n .vectorStoreId(\"vector_store_id\")\n .fileId(\"file_id\")\n .build();\n VectorStoreFileDeleted vectorStoreFileDeleted = client.vectorStores().files().delete(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store_file_deleted = openai.vector_stores.files.delete(\"file_id\", vector_store_id: \"vector_store_id\")\n\nputs(vector_store_file_deleted)" - } - } - }, - "description": "Delete a vector store file. This will remove the file from the vector store but the file itself will not be deleted. To delete the file, use the [delete file](https://platform.openai.com/docs/api-reference/files/delete) endpoint." - }, - "post": { - "operationId": "updateVectorStoreFileAttributes", - "tags": [ - "Vector stores" - ], - "summary": "Update vector store file attributes", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string", - "example": "vs_abc123" - }, - "description": "The ID of the vector store the file belongs to." - }, - { - "in": "path", - "name": "file_id", - "required": true, - "schema": { - "type": "string", - "example": "file-abc123" - }, - "description": "The ID of the file to update attributes." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/UpdateVectorStoreFileAttributesRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreFileObject" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Update vector store file attributes", - "group": "vector_stores", - "returns": "The updated [vector store file](https://platform.openai.com/docs/api-reference/vector-stores-files/file-object) object.", - "examples": { - "response": "{\n \"id\": \"file-abc123\",\n \"object\": \"vector_store.file\",\n \"usage_bytes\": 1234,\n \"created_at\": 1699061776,\n \"vector_store_id\": \"vs_abcd\",\n \"status\": \"completed\",\n \"last_error\": null,\n \"chunking_strategy\": {...},\n \"attributes\": {\"key1\": \"value1\", \"key2\": 2}\n}\n", - "request": { - "curl": "curl https://api.openai.com/v1/vector_stores/{vector_store_id}/files/{file_id} \\\n -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"attributes\": {\"key1\": \"value1\", \"key2\": 2}}'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\nconst vectorStoreFile = await client.vectorStores.files.update('file-abc123', {\n vector_store_id: 'vs_abc123',\n attributes: { foo: 'string' },\n});\n\nconsole.log(vectorStoreFile.id);", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\nvector_store_file = client.vector_stores.files.update(\n file_id=\"file-abc123\",\n vector_store_id=\"vs_abc123\",\n attributes={\n \"foo\": \"string\"\n },\n)\nprint(vector_store_file.id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n vectorStoreFile, err := client.VectorStores.Files.Update(\n context.TODO(),\n \"vs_abc123\",\n \"file-abc123\",\n openai.VectorStoreFileUpdateParams{\n Attributes: map[string]openai.VectorStoreFileUpdateParamsAttributeUnion{\n \"foo\": openai.VectorStoreFileUpdateParamsAttributeUnion{\n OfString: openai.String(\"string\"),\n },\n },\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", vectorStoreFile.ID)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.core.JsonValue;\nimport com.openai.models.vectorstores.files.FileUpdateParams;\nimport com.openai.models.vectorstores.files.VectorStoreFile;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileUpdateParams params = FileUpdateParams.builder()\n .vectorStoreId(\"vs_abc123\")\n .fileId(\"file-abc123\")\n .attributes(FileUpdateParams.Attributes.builder()\n .putAdditionalProperty(\"foo\", JsonValue.from(\"string\"))\n .build())\n .build();\n VectorStoreFile vectorStoreFile = client.vectorStores().files().update(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\nvector_store_file = openai.vector_stores.files.update(\n \"file-abc123\",\n vector_store_id: \"vs_abc123\",\n attributes: {foo: \"string\"}\n)\n\nputs(vector_store_file)" - } - } - }, - "description": "Update attributes on a vector store file." - } - }, - "/vector_stores/{vector_store_id}/files/{file_id}/content": { - "get": { - "operationId": "retrieveVectorStoreFileContent", - "tags": [ - "Vector stores" - ], - "summary": "Retrieve vector store file content", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string", - "example": "vs_abc123" - }, - "description": "The ID of the vector store." - }, - { - "in": "path", - "name": "file_id", - "required": true, - "schema": { - "type": "string", - "example": "file-abc123" - }, - "description": "The ID of the file within the vector store." - } - ], - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreFileContentResponse" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Retrieve vector store file content", - "group": "vector_stores", - "returns": "The parsed contents of the specified vector store file.", - "examples": { - "response": "{\n \"file_id\": \"file-abc123\",\n \"filename\": \"example.txt\",\n \"attributes\": {\"key\": \"value\"},\n \"content\": [\n {\"type\": \"text\", \"text\": \"...\"},\n ...\n ]\n}\n", - "request": { - "curl": "curl \\\nhttps://api.openai.com/v1/vector_stores/vs_abc123/files/file-abc123/content \\\n-H \"Authorization: Bearer $OPENAI_API_KEY\"\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const fileContentResponse of client.vectorStores.files.content('file-abc123', {\n vector_store_id: 'vs_abc123',\n})) {\n console.log(fileContentResponse.text);\n}", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.vector_stores.files.content(\n file_id=\"file-abc123\",\n vector_store_id=\"vs_abc123\",\n)\npage = page.data[0]\nprint(page.text)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.VectorStores.Files.Content(\n context.TODO(),\n \"vs_abc123\",\n \"file-abc123\",\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.files.FileContentPage;\nimport com.openai.models.vectorstores.files.FileContentParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n FileContentParams params = FileContentParams.builder()\n .vectorStoreId(\"vs_abc123\")\n .fileId(\"file-abc123\")\n .build();\n FileContentPage page = client.vectorStores().files().content(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.vector_stores.files.content(\"file-abc123\", vector_store_id: \"vs_abc123\")\n\nputs(page)" - } - } - }, - "description": "Retrieve the parsed contents of a vector store file." - } - }, - "/vector_stores/{vector_store_id}/search": { - "post": { - "operationId": "searchVectorStore", - "tags": [ - "Vector stores" - ], - "summary": "Search vector store", - "parameters": [ - { - "in": "path", - "name": "vector_store_id", - "required": true, - "schema": { - "type": "string", - "example": "vs_abc123" - }, - "description": "The ID of the vector store to search." - } - ], - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreSearchRequest" - } - } - } - }, - "responses": { - "200": { - "description": "OK", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/VectorStoreSearchResultsPage" - } - } - } - } - }, - "x-oaiMeta": { - "name": "Search vector store", - "group": "vector_stores", - "returns": "A page of search results from the vector store.", - "examples": { - "response": "{\n \"object\": \"vector_store.search_results.page\",\n \"search_query\": \"What is the return policy?\",\n \"data\": [\n {\n \"file_id\": \"file_123\",\n \"filename\": \"document.pdf\",\n \"score\": 0.95,\n \"attributes\": {\n \"author\": \"John Doe\",\n \"date\": \"2023-01-01\"\n },\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": \"Relevant chunk\"\n }\n ]\n },\n {\n \"file_id\": \"file_456\",\n \"filename\": \"notes.txt\",\n \"score\": 0.89,\n \"attributes\": {\n \"author\": \"Jane Smith\",\n \"date\": \"2023-01-02\"\n },\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": \"Sample text content from the vector store.\"\n }\n ]\n }\n ],\n \"has_more\": false,\n \"next_page\": null\n}\n", - "request": { - "curl": "curl -X POST \\\nhttps://api.openai.com/v1/vector_stores/vs_abc123/search \\\n-H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n-H \"Content-Type: application/json\" \\\n-d '{\"query\": \"What is the return policy?\", \"filters\": {...}}'\n", - "node.js": "import OpenAI from 'openai';\n\nconst client = new OpenAI({ apiKey: 'My API Key',\n});\n\n// Automatically fetches more pages as needed.\nfor await (const vectorStoreSearchResponse of client.vectorStores.search('vs_abc123', { query: 'string' })) { console.log(vectorStoreSearchResponse.file_id);\n}", - "python": "from openai import OpenAI\n\nclient = OpenAI(\n api_key=\"My API Key\",\n)\npage = client.vector_stores.search(\n vector_store_id=\"vs_abc123\",\n query=\"string\",\n)\npage = page.data[0]\nprint(page.file_id)", - "go": "package main\n\nimport (\n \"context\"\n \"fmt\"\n\n \"github.com/openai/openai-go\"\n \"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n client := openai.NewClient(\n option.WithAPIKey(\"My API Key\"),\n )\n page, err := client.VectorStores.Search(\n context.TODO(),\n \"vs_abc123\",\n openai.VectorStoreSearchParams{\n Query: openai.VectorStoreSearchParamsQueryUnion{\n OfString: openai.String(\"string\"),\n },\n },\n )\n if err != nil {\n panic(err.Error())\n }\n fmt.Printf(\"%+v\\n\", page)\n}\n", - "java": "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStoreSearchPage;\nimport com.openai.models.vectorstores.VectorStoreSearchParams;\n\npublic final class Main {\n private Main() {}\n\n public static void main(String[] args) {\n OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n VectorStoreSearchParams params = VectorStoreSearchParams.builder()\n .vectorStoreId(\"vs_abc123\")\n .query(\"string\")\n .build();\n VectorStoreSearchPage page = client.vectorStores().search(params);\n }\n}", - "ruby": "require \"openai\"\n\nopenai = OpenAI::Client.new(api_key: \"My API Key\")\n\npage = openai.vector_stores.search(\"vs_abc123\", query: \"string\")\n\nputs(page)" - } - } - }, - "description": "Search a vector store for relevant chunks based on a query and file attributes filter." - } - } - }, - "webhooks": { - "batch_cancelled": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookBatchCancelled" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "batch_completed": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookBatchCompleted" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "batch_expired": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookBatchExpired" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "batch_failed": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookBatchFailed" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "eval_run_canceled": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookEvalRunCanceled" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "eval_run_failed": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookEvalRunFailed" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "eval_run_succeeded": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookEvalRunSucceeded" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "fine_tuning_job_cancelled": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookFineTuningJobCancelled" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "fine_tuning_job_failed": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookFineTuningJobFailed" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "fine_tuning_job_succeeded": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookFineTuningJobSucceeded" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "realtime_call_incoming": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookRealtimeCallIncoming" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200\nstatus codes will be retried.\n" - } - } - } - }, - "response_cancelled": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookResponseCancelled" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "response_completed": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookResponseCompleted" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "response_failed": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookResponseFailed" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - }, - "response_incomplete": { - "post": { - "requestBody": { - "description": "The event payload sent by the API.", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WebhookResponseIncomplete" - } - } - } - }, - "responses": { - "200": { - "description": "Return a 200 status code to acknowledge receipt of the event. Non-200 \nstatus codes will be retried.\n" - } - } - } - } - }, - "components": { - "schemas": { - "AddUploadPartRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "data": { - "description": "The chunk of bytes for this Part.\n", - "type": "string", - "format": "binary" - } - }, - "required": [ - "data" - ] - }, - "AdminApiKey": { - "type": "object", - "description": "Represents an individual Admin API key in an org.", - "properties": { - "object": { - "type": "string", - "example": "organization.admin_api_key", - "description": "The object type, which is always `organization.admin_api_key`", - "x-stainless-const": true - }, - "id": { - "type": "string", - "example": "key_abc", - "description": "The identifier, which can be referenced in API endpoints" - }, - "name": { - "type": "string", - "example": "Administration Key", - "description": "The name of the API key" - }, - "redacted_value": { - "type": "string", - "example": "sk-admin...def", - "description": "The redacted value of the API key" - }, - "value": { - "type": "string", - "example": "sk-admin-1234abcd", - "description": "The value of the API key. Only shown on create." - }, - "created_at": { - "type": "integer", - "format": "int64", - "example": 1711471533, - "description": "The Unix timestamp (in seconds) of when the API key was created" - }, - "last_used_at": { - "type": "integer", - "format": "int64", - "nullable": true, - "example": 1711471534, - "description": "The Unix timestamp (in seconds) of when the API key was last used" - }, - "owner": { - "type": "object", - "properties": { - "type": { - "type": "string", - "example": "user", - "description": "Always `user`" - }, - "object": { - "type": "string", - "example": "organization.user", - "description": "The object type, which is always organization.user" - }, - "id": { - "type": "string", - "example": "sa_456", - "description": "The identifier, which can be referenced in API endpoints" - }, - "name": { - "type": "string", - "example": "My Service Account", - "description": "The name of the user" - }, - "created_at": { - "type": "integer", - "format": "int64", - "example": 1711471533, - "description": "The Unix timestamp (in seconds) of when the user was created" - }, - "role": { - "type": "string", - "example": "owner", - "description": "Always `owner`" - } - } - } - }, - "required": [ - "object", - "redacted_value", - "name", - "created_at", - "last_used_at", - "id", - "owner" - ], - "x-oaiMeta": { - "name": "The admin API key object", - "example": "{\n \"object\": \"organization.admin_api_key\",\n \"id\": \"key_abc\",\n \"name\": \"Main Admin Key\",\n \"redacted_value\": \"sk-admin...xyz\",\n \"created_at\": 1711471533,\n \"last_used_at\": 1711471534,\n \"owner\": {\n \"type\": \"user\",\n \"object\": \"organization.user\",\n \"id\": \"user_123\",\n \"name\": \"John Doe\",\n \"created_at\": 1711471533,\n \"role\": \"owner\"\n }\n}\n" - } - }, - "ApiKeyList": { - "type": "object", - "properties": { - "object": { - "type": "string", - "example": "list" - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/AdminApiKey" - } - }, - "has_more": { - "type": "boolean", - "example": false - }, - "first_id": { - "type": "string", - "example": "key_abc" - }, - "last_id": { - "type": "string", - "example": "key_xyz" - } - } - }, - "AssistantObject": { - "type": "object", - "title": "Assistant", - "description": "Represents an `assistant` that can call the model and use tools.", - "properties": { - "id": { - "description": "The identifier, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `assistant`.", - "type": "string", - "enum": [ - "assistant" - ], - "x-stainless-const": true - }, - "created_at": { - "description": "The Unix timestamp (in seconds) for when the assistant was created.", - "type": "integer" - }, - "name": { - "description": "The name of the assistant. The maximum length is 256 characters.\n", - "type": "string", - "maxLength": 256, - "nullable": true - }, - "description": { - "description": "The description of the assistant. The maximum length is 512 characters.\n", - "type": "string", - "maxLength": 512, - "nullable": true - }, - "model": { - "description": "ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models) for descriptions of them.\n", - "type": "string" - }, - "instructions": { - "description": "The system instructions that the assistant uses. The maximum length is 256,000 characters.\n", - "type": "string", - "maxLength": 256000, - "nullable": true - }, - "tools": { - "description": "A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.\n", - "default": [], - "type": "array", - "maxItems": 128, - "items": { - "$ref": "#/components/schemas/AssistantTool" - } - }, - "tool_resources": { - "type": "object", - "description": "A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.\n", - "properties": { - "code_interpreter": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter`` tool. There can be a maximum of 20 files associated with the tool.\n", - "default": [], - "maxItems": 20, - "items": { - "type": "string" - } - } - } - }, - "file_search": { - "type": "object", - "properties": { - "vector_store_ids": { - "type": "array", - "description": "The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.\n", - "maxItems": 1, - "items": { - "type": "string" - } - } - } - } - }, - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "temperature": { - "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n", - "type": "number", - "minimum": 0, - "maximum": 2, - "default": 1, - "example": 1, - "nullable": true - }, - "top_p": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 1, - "example": 1, - "nullable": true, - "description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or temperature but not both.\n" - }, - "response_format": { - "$ref": "#/components/schemas/AssistantsApiResponseFormatOption", - "nullable": true - } - }, - "required": [ - "id", - "object", - "created_at", - "name", - "description", - "model", - "instructions", - "tools", - "metadata" - ], - "x-oaiMeta": { - "name": "The assistant object", - "beta": true, - "example": "{\n \"id\": \"asst_abc123\",\n \"object\": \"assistant\",\n \"created_at\": 1698984975,\n \"name\": \"Math Tutor\",\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are a personal math tutor. When asked a question, write and run Python code to answer the question.\",\n \"tools\": [\n {\n \"type\": \"code_interpreter\"\n }\n ],\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n}\n" - } - }, - "AssistantStreamEvent": { - "description": "Represents an event emitted when streaming a Run.\n\nEach event in a server-sent events stream has an `event` and `data` property:\n\n```\nevent: thread.created\ndata: {\"id\": \"thread_123\", \"object\": \"thread\", ...}\n```\n\nWe emit events whenever a new object is created, transitions to a new state, or is being\nstreamed in parts (deltas). For example, we emit `thread.run.created` when a new run\nis created, `thread.run.completed` when a run completes, and so on. When an Assistant chooses\nto create a message during a run, we emit a `thread.message.created event`, a\n`thread.message.in_progress` event, many `thread.message.delta` events, and finally a\n`thread.message.completed` event.\n\nWe may add additional events over time, so we recommend handling unknown events gracefully\nin your code. See the [Assistants API quickstart](https://platform.openai.com/docs/assistants/overview) to learn how to\nintegrate the Assistants API with streaming.\n", - "x-oaiMeta": { - "name": "Assistant stream events", - "beta": true - }, - "anyOf": [ - { - "$ref": "#/components/schemas/ThreadStreamEvent" - }, - { - "$ref": "#/components/schemas/RunStreamEvent" - }, - { - "$ref": "#/components/schemas/RunStepStreamEvent" - }, - { - "$ref": "#/components/schemas/MessageStreamEvent" - }, - { - "$ref": "#/components/schemas/ErrorEvent", - "x-stainless-variantName": "error_event" - } - ], - "discriminator": { - "propertyName": "event" - } - }, - "AssistantSupportedModels": { - "type": "string", - "enum": [ - "gpt-5", - "gpt-5-mini", - "gpt-5-nano", - "gpt-5-2025-08-07", - "gpt-5-mini-2025-08-07", - "gpt-5-nano-2025-08-07", - "gpt-4.1", - "gpt-4.1-mini", - "gpt-4.1-nano", - "gpt-4.1-2025-04-14", - "gpt-4.1-mini-2025-04-14", - "gpt-4.1-nano-2025-04-14", - "o3-mini", - "o3-mini-2025-01-31", - "o1", - "o1-2024-12-17", - "gpt-4o", - "gpt-4o-2024-11-20", - "gpt-4o-2024-08-06", - "gpt-4o-2024-05-13", - "gpt-4o-mini", - "gpt-4o-mini-2024-07-18", - "gpt-4.5-preview", - "gpt-4.5-preview-2025-02-27", - "gpt-4-turbo", - "gpt-4-turbo-2024-04-09", - "gpt-4-0125-preview", - "gpt-4-turbo-preview", - "gpt-4-1106-preview", - "gpt-4-vision-preview", - "gpt-4", - "gpt-4-0314", - "gpt-4-0613", - "gpt-4-32k", - "gpt-4-32k-0314", - "gpt-4-32k-0613", - "gpt-3.5-turbo", - "gpt-3.5-turbo-16k", - "gpt-3.5-turbo-0613", - "gpt-3.5-turbo-1106", - "gpt-3.5-turbo-0125", - "gpt-3.5-turbo-16k-0613" - ] - }, - "AssistantToolsCode": { - "type": "object", - "title": "Code interpreter tool", - "properties": { - "type": { - "type": "string", - "description": "The type of tool being defined: `code_interpreter`", - "enum": [ - "code_interpreter" - ], - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "AssistantToolsFileSearch": { - "type": "object", - "title": "FileSearch tool", - "properties": { - "type": { - "type": "string", - "description": "The type of tool being defined: `file_search`", - "enum": [ - "file_search" - ], - "x-stainless-const": true - }, - "file_search": { - "type": "object", - "description": "Overrides for the file search tool.", - "properties": { - "max_num_results": { - "type": "integer", - "minimum": 1, - "maximum": 50, - "description": "The maximum number of results the file search tool should output. The default is 20 for `gpt-4*` models and 5 for `gpt-3.5-turbo`. This number should be between 1 and 50 inclusive.\n\nNote that the file search tool may output fewer than `max_num_results` results. See the [file search tool documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings) for more information.\n" - }, - "ranking_options": { - "$ref": "#/components/schemas/FileSearchRankingOptions" - } - } - } - }, - "required": [ - "type" - ] - }, - "AssistantToolsFileSearchTypeOnly": { - "type": "object", - "title": "FileSearch tool", - "properties": { - "type": { - "type": "string", - "description": "The type of tool being defined: `file_search`", - "enum": [ - "file_search" - ], - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "AssistantToolsFunction": { - "type": "object", - "title": "Function tool", - "properties": { - "type": { - "type": "string", - "description": "The type of tool being defined: `function`", - "enum": [ - "function" - ], - "x-stainless-const": true - }, - "function": { - "$ref": "#/components/schemas/FunctionObject" - } - }, - "required": [ - "type", - "function" - ] - }, - "AssistantsApiResponseFormatOption": { - "description": "Specifies the format that the model must output. Compatible with [GPT-4o](https://platform.openai.com/docs/models#gpt-4o), [GPT-4 Turbo](https://platform.openai.com/docs/models#gpt-4-turbo-and-gpt-4), and all GPT-3.5 Turbo models since `gpt-3.5-turbo-1106`.\n\nSetting to `{ \"type\": \"json_schema\", \"json_schema\": {...} }` enables Structured Outputs which ensures the model will match your supplied JSON schema. Learn more in the [Structured Outputs guide](https://platform.openai.com/docs/guides/structured-outputs).\n\nSetting to `{ \"type\": \"json_object\" }` enables JSON mode, which ensures the message the model generates is valid JSON.\n\n**Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly \"stuck\" request. Also note that the message content may be partially cut off if `finish_reason=\"length\"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length.\n", - "anyOf": [ - { - "type": "string", - "description": "`auto` is the default value\n", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "$ref": "#/components/schemas/ResponseFormatText" - }, - { - "$ref": "#/components/schemas/ResponseFormatJsonObject" - }, - { - "$ref": "#/components/schemas/ResponseFormatJsonSchema" - } - ] - }, - "AssistantsApiToolChoiceOption": { - "description": "Controls which (if any) tool is called by the model.\n`none` means the model will not call any tools and instead generates a message.\n`auto` is the default value and means the model can pick between generating a message or calling one or more tools.\n`required` means the model must call one or more tools before responding to the user.\nSpecifying a particular tool like `{\"type\": \"file_search\"}` or `{\"type\": \"function\", \"function\": {\"name\": \"my_function\"}}` forces the model to call that tool.\n", - "anyOf": [ - { - "type": "string", - "description": "`none` means the model will not call any tools and instead generates a message. `auto` means the model can pick between generating a message or calling one or more tools. `required` means the model must call one or more tools before responding to the user.\n", - "enum": [ - "none", - "auto", - "required" - ], - "title": "Auto" - }, - { - "$ref": "#/components/schemas/AssistantsNamedToolChoice" - } - ] - }, - "AssistantsNamedToolChoice": { - "type": "object", - "description": "Specifies a tool the model should use. Use to force the model to call a specific tool.", - "properties": { - "type": { - "type": "string", - "enum": [ - "function", - "code_interpreter", - "file_search" - ], - "description": "The type of the tool. If type is `function`, the function name must be set" - }, - "function": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The name of the function to call." - } - }, - "required": [ - "name" - ] - } - }, - "required": [ - "type" - ] - }, - "AudioResponseFormat": { - "description": "The format of the output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or `vtt`. For `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`, the only supported format is `json`.\n", - "type": "string", - "enum": [ - "json", - "text", - "srt", - "verbose_json", - "vtt" - ], - "default": "json" - }, - "AuditLog": { - "type": "object", - "description": "A log of a user action or configuration change within this organization.", - "properties": { - "id": { - "type": "string", - "description": "The ID of this log." - }, - "type": { - "$ref": "#/components/schemas/AuditLogEventType" - }, - "effective_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of the event." - }, - "project": { - "type": "object", - "description": "The project that the action was scoped to. Absent for actions not scoped to projects. Note that any admin actions taken via Admin API keys are associated with the default project.", - "properties": { - "id": { - "type": "string", - "description": "The project ID." - }, - "name": { - "type": "string", - "description": "The project title." - } - } - }, - "actor": { - "$ref": "#/components/schemas/AuditLogActor" - }, - "api_key.created": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The tracking ID of the API key." - }, - "data": { - "type": "object", - "description": "The payload used to create the API key.", - "properties": { - "scopes": { - "type": "array", - "items": { - "type": "string" - }, - "description": "A list of scopes allowed for the API key, e.g. `[\"api.model.request\"]`" - } - } - } - } - }, - "api_key.updated": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The tracking ID of the API key." - }, - "changes_requested": { - "type": "object", - "description": "The payload used to update the API key.", - "properties": { - "scopes": { - "type": "array", - "items": { - "type": "string" - }, - "description": "A list of scopes allowed for the API key, e.g. `[\"api.model.request\"]`" - } - } - } - } - }, - "api_key.deleted": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The tracking ID of the API key." - } - } - }, - "checkpoint_permission.created": { - "type": "object", - "description": "The project and fine-tuned model checkpoint that the checkpoint permission was created for.", - "properties": { - "id": { - "type": "string", - "description": "The ID of the checkpoint permission." - }, - "data": { - "type": "object", - "description": "The payload used to create the checkpoint permission.", - "properties": { - "project_id": { - "type": "string", - "description": "The ID of the project that the checkpoint permission was created for." - }, - "fine_tuned_model_checkpoint": { - "type": "string", - "description": "The ID of the fine-tuned model checkpoint." - } - } - } - } - }, - "checkpoint_permission.deleted": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The ID of the checkpoint permission." - } - } - }, - "invite.sent": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The ID of the invite." - }, - "data": { - "type": "object", - "description": "The payload used to create the invite.", - "properties": { - "email": { - "type": "string", - "description": "The email invited to the organization." - }, - "role": { - "type": "string", - "description": "The role the email was invited to be. Is either `owner` or `member`." - } - } - } - } - }, - "invite.accepted": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The ID of the invite." - } - } - }, - "invite.deleted": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The ID of the invite." - } - } - }, - "login.failed": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "error_code": { - "type": "string", - "description": "The error code of the failure." - }, - "error_message": { - "type": "string", - "description": "The error message of the failure." - } - } - }, - "logout.failed": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "error_code": { - "type": "string", - "description": "The error code of the failure." - }, - "error_message": { - "type": "string", - "description": "The error message of the failure." - } - } - }, - "organization.updated": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The organization ID." - }, - "changes_requested": { - "type": "object", - "description": "The payload used to update the organization settings.", - "properties": { - "title": { - "type": "string", - "description": "The organization title." - }, - "description": { - "type": "string", - "description": "The organization description." - }, - "name": { - "type": "string", - "description": "The organization name." - }, - "threads_ui_visibility": { - "type": "string", - "description": "Visibility of the threads page which shows messages created with the Assistants API and Playground. One of `ANY_ROLE`, `OWNERS`, or `NONE`." - }, - "usage_dashboard_visibility": { - "type": "string", - "description": "Visibility of the usage dashboard which shows activity and costs for your organization. One of `ANY_ROLE` or `OWNERS`." - }, - "api_call_logging": { - "type": "string", - "description": "How your organization logs data from supported API calls. One of `disabled`, `enabled_per_call`, `enabled_for_all_projects`, or `enabled_for_selected_projects`" - }, - "api_call_logging_project_ids": { - "type": "string", - "description": "The list of project ids if api_call_logging is set to `enabled_for_selected_projects`" - } - } - } - } - }, - "project.created": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The project ID." - }, - "data": { - "type": "object", - "description": "The payload used to create the project.", - "properties": { - "name": { - "type": "string", - "description": "The project name." - }, - "title": { - "type": "string", - "description": "The title of the project as seen on the dashboard." - } - } - } - } - }, - "project.updated": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The project ID." - }, - "changes_requested": { - "type": "object", - "description": "The payload used to update the project.", - "properties": { - "title": { - "type": "string", - "description": "The title of the project as seen on the dashboard." - } - } - } - } - }, - "project.archived": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The project ID." - } - } - }, - "rate_limit.updated": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The rate limit ID" - }, - "changes_requested": { - "type": "object", - "description": "The payload used to update the rate limits.", - "properties": { - "max_requests_per_1_minute": { - "type": "integer", - "description": "The maximum requests per minute." - }, - "max_tokens_per_1_minute": { - "type": "integer", - "description": "The maximum tokens per minute." - }, - "max_images_per_1_minute": { - "type": "integer", - "description": "The maximum images per minute. Only relevant for certain models." - }, - "max_audio_megabytes_per_1_minute": { - "type": "integer", - "description": "The maximum audio megabytes per minute. Only relevant for certain models." - }, - "max_requests_per_1_day": { - "type": "integer", - "description": "The maximum requests per day. Only relevant for certain models." - }, - "batch_1_day_max_input_tokens": { - "type": "integer", - "description": "The maximum batch input tokens per day. Only relevant for certain models." - } - } - } - } - }, - "rate_limit.deleted": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The rate limit ID" - } - } - }, - "service_account.created": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The service account ID." - }, - "data": { - "type": "object", - "description": "The payload used to create the service account.", - "properties": { - "role": { - "type": "string", - "description": "The role of the service account. Is either `owner` or `member`." - } - } - } - } - }, - "service_account.updated": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The service account ID." - }, - "changes_requested": { - "type": "object", - "description": "The payload used to updated the service account.", - "properties": { - "role": { - "type": "string", - "description": "The role of the service account. Is either `owner` or `member`." - } - } - } - } - }, - "service_account.deleted": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The service account ID." - } - } - }, - "user.added": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The user ID." - }, - "data": { - "type": "object", - "description": "The payload used to add the user to the project.", - "properties": { - "role": { - "type": "string", - "description": "The role of the user. Is either `owner` or `member`." - } - } - } - } - }, - "user.updated": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The project ID." - }, - "changes_requested": { - "type": "object", - "description": "The payload used to update the user.", - "properties": { - "role": { - "type": "string", - "description": "The role of the user. Is either `owner` or `member`." - } - } - } - } - }, - "user.deleted": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The user ID." - } - } - }, - "certificate.created": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The certificate ID." - }, - "name": { - "type": "string", - "description": "The name of the certificate." - } - } - }, - "certificate.updated": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The certificate ID." - }, - "name": { - "type": "string", - "description": "The name of the certificate." - } - } - }, - "certificate.deleted": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "id": { - "type": "string", - "description": "The certificate ID." - }, - "name": { - "type": "string", - "description": "The name of the certificate." - }, - "certificate": { - "type": "string", - "description": "The certificate content in PEM format." - } - } - }, - "certificates.activated": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "certificates": { - "type": "array", - "items": { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The certificate ID." - }, - "name": { - "type": "string", - "description": "The name of the certificate." - } - } - } - } - } - }, - "certificates.deactivated": { - "type": "object", - "description": "The details for events with this `type`.", - "properties": { - "certificates": { - "type": "array", - "items": { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The certificate ID." - }, - "name": { - "type": "string", - "description": "The name of the certificate." - } - } - } - } - } - } - }, - "required": [ - "id", - "type", - "effective_at", - "actor" - ], - "x-oaiMeta": { - "name": "The audit log object", - "example": "{\n \"id\": \"req_xxx_20240101\",\n \"type\": \"api_key.created\",\n \"effective_at\": 1720804090,\n \"actor\": {\n \"type\": \"session\",\n \"session\": {\n \"user\": {\n \"id\": \"user-xxx\",\n \"email\": \"user@example.com\"\n },\n \"ip_address\": \"127.0.0.1\",\n \"user_agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36\"\n }\n },\n \"api_key.created\": {\n \"id\": \"key_xxxx\",\n \"data\": {\n \"scopes\": [\"resource.operation\"]\n }\n }\n}\n" - } - }, - "AuditLogActor": { - "type": "object", - "description": "The actor who performed the audit logged action.", - "properties": { - "type": { - "type": "string", - "description": "The type of actor. Is either `session` or `api_key`.", - "enum": [ - "session", - "api_key" - ] - }, - "session": { - "$ref": "#/components/schemas/AuditLogActorSession" - }, - "api_key": { - "$ref": "#/components/schemas/AuditLogActorApiKey" - } - } - }, - "AuditLogActorApiKey": { - "type": "object", - "description": "The API Key used to perform the audit logged action.", - "properties": { - "id": { - "type": "string", - "description": "The tracking id of the API key." - }, - "type": { - "type": "string", - "description": "The type of API key. Can be either `user` or `service_account`.", - "enum": [ - "user", - "service_account" - ] - }, - "user": { - "$ref": "#/components/schemas/AuditLogActorUser" - }, - "service_account": { - "$ref": "#/components/schemas/AuditLogActorServiceAccount" - } - } - }, - "AuditLogActorServiceAccount": { - "type": "object", - "description": "The service account that performed the audit logged action.", - "properties": { - "id": { - "type": "string", - "description": "The service account id." - } - } - }, - "AuditLogActorSession": { - "type": "object", - "description": "The session in which the audit logged action was performed.", - "properties": { - "user": { - "$ref": "#/components/schemas/AuditLogActorUser" - }, - "ip_address": { - "type": "string", - "description": "The IP address from which the action was performed." - } - } - }, - "AuditLogActorUser": { - "type": "object", - "description": "The user who performed the audit logged action.", - "properties": { - "id": { - "type": "string", - "description": "The user id." - }, - "email": { - "type": "string", - "description": "The user email." - } - } - }, - "AuditLogEventType": { - "type": "string", - "description": "The event type.", - "enum": [ - "api_key.created", - "api_key.updated", - "api_key.deleted", - "checkpoint_permission.created", - "checkpoint_permission.deleted", - "invite.sent", - "invite.accepted", - "invite.deleted", - "login.succeeded", - "login.failed", - "logout.succeeded", - "logout.failed", - "organization.updated", - "project.created", - "project.updated", - "project.archived", - "service_account.created", - "service_account.updated", - "service_account.deleted", - "rate_limit.updated", - "rate_limit.deleted", - "user.added", - "user.updated", - "user.deleted" - ] - }, - "AutoChunkingStrategyRequestParam": { - "type": "object", - "title": "Auto Chunking Strategy", - "description": "The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and `chunk_overlap_tokens` of `400`.", - "additionalProperties": false, - "properties": { - "type": { - "type": "string", - "description": "Always `auto`.", - "enum": [ - "auto" - ], - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "Batch": { - "type": "object", - "properties": { - "id": { - "type": "string" - }, - "object": { - "type": "string", - "enum": [ - "batch" - ], - "description": "The object type, which is always `batch`.", - "x-stainless-const": true - }, - "endpoint": { - "type": "string", - "description": "The OpenAI API endpoint used by the batch." - }, - "errors": { - "type": "object", - "properties": { - "object": { - "type": "string", - "description": "The object type, which is always `list`." - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/BatchError" - } - } - } - }, - "input_file_id": { - "type": "string", - "description": "The ID of the input file for the batch." - }, - "completion_window": { - "type": "string", - "description": "The time frame within which the batch should be processed." - }, - "status": { - "type": "string", - "description": "The current status of the batch.", - "enum": [ - "validating", - "failed", - "in_progress", - "finalizing", - "completed", - "expired", - "cancelling", - "cancelled" - ] - }, - "output_file_id": { - "type": "string", - "description": "The ID of the file containing the outputs of successfully executed requests." - }, - "error_file_id": { - "type": "string", - "description": "The ID of the file containing the outputs of requests with errors." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the batch was created." - }, - "in_progress_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the batch started processing." - }, - "expires_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the batch will expire." - }, - "finalizing_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the batch started finalizing." - }, - "completed_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the batch was completed." - }, - "failed_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the batch failed." - }, - "expired_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the batch expired." - }, - "cancelling_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the batch started cancelling." - }, - "cancelled_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the batch was cancelled." - }, - "request_counts": { - "$ref": "#/components/schemas/BatchRequestCounts" - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - }, - "required": [ - "id", - "object", - "endpoint", - "input_file_id", - "completion_window", - "status", - "created_at" - ], - "x-oaiMeta": { - "name": "The batch object", - "example": "{\n \"id\": \"batch_abc123\",\n \"object\": \"batch\",\n \"endpoint\": \"/v1/completions\",\n \"errors\": null,\n \"input_file_id\": \"file-abc123\",\n \"completion_window\": \"24h\",\n \"status\": \"completed\",\n \"output_file_id\": \"file-cvaTdG\",\n \"error_file_id\": \"file-HOWS94\",\n \"created_at\": 1711471533,\n \"in_progress_at\": 1711471538,\n \"expires_at\": 1711557933,\n \"finalizing_at\": 1711493133,\n \"completed_at\": 1711493163,\n \"failed_at\": null,\n \"expired_at\": null,\n \"cancelling_at\": null,\n \"cancelled_at\": null,\n \"request_counts\": {\n \"total\": 100,\n \"completed\": 95,\n \"failed\": 5\n },\n \"metadata\": {\n \"customer_id\": \"user_123456789\",\n \"batch_description\": \"Nightly eval job\",\n }\n}\n" - } - }, - "BatchFileExpirationAfter": { - "type": "object", - "title": "File expiration policy", - "description": "The expiration policy for the output and/or error file that are generated for a batch.", - "properties": { - "anchor": { - "description": "Anchor timestamp after which the expiration policy applies. Supported anchors: `created_at`. Note that the anchor is the file creation time, not the time the batch is created.", - "type": "string", - "enum": [ - "created_at" - ], - "x-stainless-const": true - }, - "seconds": { - "description": "The number of seconds after the anchor time that the file will expire. Must be between 3600 (1 hour) and 2592000 (30 days).", - "type": "integer", - "minimum": 3600, - "maximum": 2592000 - } - }, - "required": [ - "anchor", - "seconds" - ] - }, - "BatchRequestInput": { - "type": "object", - "description": "The per-line object of the batch input file", - "properties": { - "custom_id": { - "type": "string", - "description": "A developer-provided per-request id that will be used to match outputs to inputs. Must be unique for each request in a batch." - }, - "method": { - "type": "string", - "enum": [ - "POST" - ], - "description": "The HTTP method to be used for the request. Currently only `POST` is supported.", - "x-stainless-const": true - }, - "url": { - "type": "string", - "description": "The OpenAI API relative URL to be used for the request. Currently `/v1/chat/completions`, `/v1/embeddings`, and `/v1/completions` are supported." - } - }, - "x-oaiMeta": { - "name": "The request input object", - "example": "{\"custom_id\": \"request-1\", \"method\": \"POST\", \"url\": \"/v1/chat/completions\", \"body\": {\"model\": \"gpt-4o-mini\", \"messages\": [{\"role\": \"system\", \"content\": \"You are a helpful assistant.\"}, {\"role\": \"user\", \"content\": \"What is 2+2?\"}]}}\n" - } - }, - "BatchRequestOutput": { - "type": "object", - "description": "The per-line object of the batch output and error files", - "properties": { - "id": { - "type": "string" - }, - "custom_id": { - "type": "string", - "description": "A developer-provided per-request id that will be used to match outputs to inputs." - }, - "response": { - "type": "object", - "nullable": true, - "properties": { - "status_code": { - "type": "integer", - "description": "The HTTP status code of the response" - }, - "request_id": { - "type": "string", - "description": "An unique identifier for the OpenAI API request. Please include this request ID when contacting support." - }, - "body": { - "type": "object", - "x-oaiTypeLabel": "map", - "description": "The JSON body of the response" - } - } - }, - "error": { - "type": "object", - "nullable": true, - "description": "For requests that failed with a non-HTTP error, this will contain more information on the cause of the failure.", - "properties": { - "code": { - "type": "string", - "description": "A machine-readable error code." - }, - "message": { - "type": "string", - "description": "A human-readable error message." - } - } - } - }, - "x-oaiMeta": { - "name": "The request output object", - "example": "{\"id\": \"batch_req_wnaDys\", \"custom_id\": \"request-2\", \"response\": {\"status_code\": 200, \"request_id\": \"req_c187b3\", \"body\": {\"id\": \"chatcmpl-9758Iw\", \"object\": \"chat.completion\", \"created\": 1711475054, \"model\": \"gpt-4o-mini\", \"choices\": [{\"index\": 0, \"message\": {\"role\": \"assistant\", \"content\": \"2 + 2 equals 4.\"}, \"finish_reason\": \"stop\"}], \"usage\": {\"prompt_tokens\": 24, \"completion_tokens\": 15, \"total_tokens\": 39}, \"system_fingerprint\": null}}, \"error\": null}\n" - } - }, - "Certificate": { - "type": "object", - "description": "Represents an individual `certificate` uploaded to the organization.", - "properties": { - "object": { - "type": "string", - "enum": [ - "certificate", - "organization.certificate", - "organization.project.certificate" - ], - "description": "The object type.\n\n- If creating, updating, or getting a specific certificate, the object type is `certificate`.\n- If listing, activating, or deactivating certificates for the organization, the object type is `organization.certificate`.\n- If listing, activating, or deactivating certificates for a project, the object type is `organization.project.certificate`.\n", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The identifier, which can be referenced in API endpoints" - }, - "name": { - "type": "string", - "description": "The name of the certificate." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the certificate was uploaded." - }, - "certificate_details": { - "type": "object", - "properties": { - "valid_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the certificate becomes valid." - }, - "expires_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the certificate expires." - }, - "content": { - "type": "string", - "description": "The content of the certificate in PEM format." - } - } - }, - "active": { - "type": "boolean", - "description": "Whether the certificate is currently active at the specified scope. Not returned when getting details for a specific certificate." - } - }, - "required": [ - "object", - "id", - "name", - "created_at", - "certificate_details" - ], - "x-oaiMeta": { - "name": "The certificate object", - "example": "{\n \"object\": \"certificate\",\n \"id\": \"cert_abc\",\n \"name\": \"My Certificate\",\n \"created_at\": 1234567,\n \"certificate_details\": {\n \"valid_at\": 1234567,\n \"expires_at\": 12345678,\n \"content\": \"-----BEGIN CERTIFICATE----- MIIGAjCCA...6znFlOW+ -----END CERTIFICATE-----\"\n }\n}\n" - } - }, - "ChatCompletionAllowedTools": { - "type": "object", - "title": "Allowed tools", - "description": "Constrains the tools available to the model to a pre-defined set.\n", - "properties": { - "mode": { - "type": "string", - "enum": [ - "auto", - "required" - ], - "description": "Constrains the tools available to the model to a pre-defined set.\n\n`auto` allows the model to pick from among the allowed tools and generate a\nmessage.\n\n`required` requires the model to call one or more of the allowed tools.\n" - }, - "tools": { - "type": "array", - "description": "A list of tool definitions that the model should be allowed to call.\n\nFor the Chat Completions API, the list of tool definitions might look like:\n```json\n[\n { \"type\": \"function\", \"function\": { \"name\": \"get_weather\" } },\n { \"type\": \"function\", \"function\": { \"name\": \"get_time\" } }\n]\n```\n", - "items": { - "type": "object", - "x-oaiExpandable": false, - "description": "A tool definition that the model should be allowed to call.\n", - "additionalProperties": true - } - } - }, - "required": [ - "mode", - "tools" - ] - }, - "ChatCompletionAllowedToolsChoice": { - "type": "object", - "title": "Allowed tools", - "description": "Constrains the tools available to the model to a pre-defined set.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "allowed_tools" - ], - "description": "Allowed tool configuration type. Always `allowed_tools`.", - "x-stainless-const": true - }, - "allowed_tools": { - "$ref": "#/components/schemas/ChatCompletionAllowedTools" - } - }, - "required": [ - "type", - "allowed_tools" - ] - }, - "ChatCompletionDeleted": { - "type": "object", - "properties": { - "object": { - "type": "string", - "description": "The type of object being deleted.", - "enum": [ - "chat.completion.deleted" - ], - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The ID of the chat completion that was deleted." - }, - "deleted": { - "type": "boolean", - "description": "Whether the chat completion was deleted." - } - }, - "required": [ - "object", - "id", - "deleted" - ] - }, - "ChatCompletionFunctionCallOption": { - "type": "object", - "description": "Specifying a particular function via `{\"name\": \"my_function\"}` forces the model to call that function.\n", - "properties": { - "name": { - "type": "string", - "description": "The name of the function to call." - } - }, - "required": [ - "name" - ], - "x-stainless-variantName": "function_call_option" - }, - "ChatCompletionFunctions": { - "type": "object", - "deprecated": true, - "properties": { - "description": { - "type": "string", - "description": "A description of what the function does, used by the model to choose when and how to call the function." - }, - "name": { - "type": "string", - "description": "The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64." - }, - "parameters": { - "$ref": "#/components/schemas/FunctionParameters" - } - }, - "required": [ - "name" - ] - }, - "ChatCompletionList": { - "type": "object", - "title": "ChatCompletionList", - "description": "An object representing a list of Chat Completions.\n", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "default": "list", - "description": "The type of this object. It is always set to \"list\".\n", - "x-stainless-const": true - }, - "data": { - "type": "array", - "description": "An array of chat completion objects.\n", - "items": { - "$ref": "#/components/schemas/CreateChatCompletionResponse" - } - }, - "first_id": { - "type": "string", - "description": "The identifier of the first chat completion in the data array." - }, - "last_id": { - "type": "string", - "description": "The identifier of the last chat completion in the data array." - }, - "has_more": { - "type": "boolean", - "description": "Indicates whether there are more Chat Completions available." - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ], - "x-oaiMeta": { - "name": "The chat completion list object", - "group": "chat", - "example": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"chat.completion\",\n \"id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2\",\n \"model\": \"gpt-4o-2024-08-06\",\n \"created\": 1738960610,\n \"request_id\": \"req_ded8ab984ec4bf840f37566c1011c417\",\n \"tool_choice\": null,\n \"usage\": {\n \"total_tokens\": 31,\n \"completion_tokens\": 18,\n \"prompt_tokens\": 13\n },\n \"seed\": 4944116822809979520,\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"presence_penalty\": 0.0,\n \"frequency_penalty\": 0.0,\n \"system_fingerprint\": \"fp_50cad350e4\",\n \"input_user\": null,\n \"service_tier\": \"default\",\n \"tools\": null,\n \"metadata\": {},\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"content\": \"Mind of circuits hum, \\nLearning patterns in silenceโ€” \\nFuture's quiet spark.\",\n \"role\": \"assistant\",\n \"tool_calls\": null,\n \"function_call\": null\n },\n \"finish_reason\": \"stop\",\n \"logprobs\": null\n }\n ],\n \"response_format\": null\n }\n ],\n \"first_id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2\",\n \"last_id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2\",\n \"has_more\": false\n}\n" - } - }, - "ChatCompletionMessageCustomToolCall": { - "type": "object", - "title": "Custom tool call", - "description": "A call to a custom tool created by the model.\n", - "properties": { - "id": { - "type": "string", - "description": "The ID of the tool call." - }, - "type": { - "type": "string", - "enum": [ - "custom" - ], - "description": "The type of the tool. Always `custom`.", - "x-stainless-const": true - }, - "custom": { - "type": "object", - "description": "The custom tool that the model called.", - "properties": { - "name": { - "type": "string", - "description": "The name of the custom tool to call." - }, - "input": { - "type": "string", - "description": "The input for the custom tool call generated by the model." - } - }, - "required": [ - "name", - "input" - ] - } - }, - "required": [ - "id", - "type", - "custom" - ] - }, - "ChatCompletionMessageList": { - "type": "object", - "title": "ChatCompletionMessageList", - "description": "An object representing a list of chat completion messages.\n", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "default": "list", - "description": "The type of this object. It is always set to \"list\".\n", - "x-stainless-const": true - }, - "data": { - "type": "array", - "description": "An array of chat completion message objects.\n", - "items": { - "allOf": [ - { - "$ref": "#/components/schemas/ChatCompletionResponseMessage" - }, - { - "type": "object", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The identifier of the chat message." - }, - "content_parts": { - "type": "array", - "nullable": true, - "description": "If a content parts array was provided, this is an array of `text` and `image_url` parts.\nOtherwise, null.\n", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartText" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartImage" - } - ] - } - } - } - } - ] - } - }, - "first_id": { - "type": "string", - "description": "The identifier of the first chat message in the data array." - }, - "last_id": { - "type": "string", - "description": "The identifier of the last chat message in the data array." - }, - "has_more": { - "type": "boolean", - "description": "Indicates whether there are more chat messages available." - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ], - "x-oaiMeta": { - "name": "The chat completion message list object", - "group": "chat", - "example": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0\",\n \"role\": \"user\",\n \"content\": \"write a haiku about ai\",\n \"name\": null,\n \"content_parts\": null\n }\n ],\n \"first_id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0\",\n \"last_id\": \"chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0\",\n \"has_more\": false\n}\n" - } - }, - "ChatCompletionMessageToolCall": { - "type": "object", - "title": "Function tool call", - "description": "A call to a function tool created by the model.\n", - "properties": { - "id": { - "type": "string", - "description": "The ID of the tool call." - }, - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "The type of the tool. Currently, only `function` is supported.", - "x-stainless-const": true - }, - "function": { - "type": "object", - "description": "The function that the model called.", - "properties": { - "name": { - "type": "string", - "description": "The name of the function to call." - }, - "arguments": { - "type": "string", - "description": "The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function." - } - }, - "required": [ - "name", - "arguments" - ] - } - }, - "required": [ - "id", - "type", - "function" - ] - }, - "ChatCompletionMessageToolCallChunk": { - "type": "object", - "properties": { - "index": { - "type": "integer" - }, - "id": { - "type": "string", - "description": "The ID of the tool call." - }, - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "The type of the tool. Currently, only `function` is supported.", - "x-stainless-const": true - }, - "function": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The name of the function to call." - }, - "arguments": { - "type": "string", - "description": "The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function." - } - } - } - }, - "required": [ - "index" - ] - }, - "ChatCompletionMessageToolCalls": { - "type": "array", - "description": "The tool calls generated by the model, such as function calls.", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionMessageToolCall" - }, - { - "$ref": "#/components/schemas/ChatCompletionMessageCustomToolCall" - } - ], - "x-stainless-naming": { - "python": { - "model_name": "chat_completion_message_tool_call_union", - "param_model_name": "chat_completion_message_tool_call_union_param" - } - }, - "discriminator": { - "propertyName": "type" - }, - "x-stainless-go-variant-constructor": "skip" - } - }, - "ChatCompletionModalities": { - "type": "array", - "nullable": true, - "description": "Output types that you would like the model to generate for this request.\nMost models are capable of generating text, which is the default:\n\n`[\"text\"]`\n\nThe `gpt-4o-audio-preview` model can also be used to [generate audio](https://platform.openai.com/docs/guides/audio). To\nrequest that this model generate both text and audio responses, you can\nuse:\n\n`[\"text\", \"audio\"]`\n", - "items": { - "type": "string", - "enum": [ - "text", - "audio" - ] - } - }, - "ChatCompletionNamedToolChoice": { - "type": "object", - "title": "Function tool choice", - "description": "Specifies a tool the model should use. Use to force the model to call a specific function.", - "properties": { - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "For function calling, the type is always `function`.", - "x-stainless-const": true - }, - "function": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The name of the function to call." - } - }, - "required": [ - "name" - ] - } - }, - "required": [ - "type", - "function" - ] - }, - "ChatCompletionNamedToolChoiceCustom": { - "type": "object", - "title": "Custom tool choice", - "description": "Specifies a tool the model should use. Use to force the model to call a specific custom tool.", - "properties": { - "type": { - "type": "string", - "enum": [ - "custom" - ], - "description": "For custom tool calling, the type is always `custom`.", - "x-stainless-const": true - }, - "custom": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The name of the custom tool to call." - } - }, - "required": [ - "name" - ] - } - }, - "required": [ - "type", - "custom" - ] - }, - "ChatCompletionRequestAssistantMessage": { - "type": "object", - "title": "Assistant message", - "description": "Messages sent by the model in response to user messages.\n", - "properties": { - "content": { - "nullable": true, - "description": "The contents of the assistant message. Required unless `tool_calls` or `function_call` is specified.\n", - "anyOf": [ - { - "type": "string", - "description": "The contents of the assistant message.", - "title": "Text content" - }, - { - "type": "array", - "description": "An array of content parts with a defined type. Can be one or more of type `text`, or exactly one of type `refusal`.", - "title": "Array of content parts", - "items": { - "$ref": "#/components/schemas/ChatCompletionRequestAssistantMessageContentPart" - }, - "minItems": 1 - } - ] - }, - "refusal": { - "nullable": true, - "type": "string", - "description": "The refusal message by the assistant." - }, - "role": { - "type": "string", - "enum": [ - "assistant" - ], - "description": "The role of the messages author, in this case `assistant`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "An optional name for the participant. Provides the model information to differentiate between participants of the same role." - }, - "audio": { - "type": "object", - "nullable": true, - "description": "Data about a previous audio response from the model. \n[Learn more](https://platform.openai.com/docs/guides/audio).\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "Unique identifier for a previous audio response from the model.\n" - } - } - }, - "tool_calls": { - "$ref": "#/components/schemas/ChatCompletionMessageToolCalls" - }, - "function_call": { - "type": "object", - "deprecated": true, - "description": "Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model.", - "nullable": true, - "properties": { - "arguments": { - "type": "string", - "description": "The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function." - }, - "name": { - "type": "string", - "description": "The name of the function to call." - } - }, - "required": [ - "arguments", - "name" - ] - } - }, - "required": [ - "role" - ], - "x-stainless-soft-required": [ - "content" - ] - }, - "ChatCompletionRequestAssistantMessageContentPart": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartText" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartRefusal" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "ChatCompletionRequestDeveloperMessage": { - "type": "object", - "title": "Developer message", - "description": "Developer-provided instructions that the model should follow, regardless of\nmessages sent by the user. With o1 models and newer, `developer` messages\nreplace the previous `system` messages.\n", - "properties": { - "content": { - "description": "The contents of the developer message.", - "anyOf": [ - { - "type": "string", - "description": "The contents of the developer message.", - "title": "Text content" - }, - { - "type": "array", - "description": "An array of content parts with a defined type. For developer messages, only type `text` is supported.", - "title": "Array of content parts", - "items": { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartText" - }, - "minItems": 1 - } - ] - }, - "role": { - "type": "string", - "enum": [ - "developer" - ], - "description": "The role of the messages author, in this case `developer`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "An optional name for the participant. Provides the model information to differentiate between participants of the same role." - } - }, - "required": [ - "content", - "role" - ], - "x-stainless-naming": { - "go": { - "variant_constructor": "DeveloperMessage" - } - } - }, - "ChatCompletionRequestFunctionMessage": { - "type": "object", - "title": "Function message", - "deprecated": true, - "properties": { - "role": { - "type": "string", - "enum": [ - "function" - ], - "description": "The role of the messages author, in this case `function`.", - "x-stainless-const": true - }, - "content": { - "nullable": true, - "type": "string", - "description": "The contents of the function message." - }, - "name": { - "type": "string", - "description": "The name of the function to call." - } - }, - "required": [ - "role", - "content", - "name" - ] - }, - "ChatCompletionRequestMessage": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestDeveloperMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestSystemMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestUserMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestAssistantMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestToolMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestFunctionMessage" - } - ], - "discriminator": { - "propertyName": "role" - } - }, - "ChatCompletionRequestMessageContentPartAudio": { - "type": "object", - "title": "Audio content part", - "description": "Learn about [audio inputs](https://platform.openai.com/docs/guides/audio).\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "input_audio" - ], - "description": "The type of the content part. Always `input_audio`.", - "x-stainless-const": true - }, - "input_audio": { - "type": "object", - "properties": { - "data": { - "type": "string", - "description": "Base64 encoded audio data." - }, - "format": { - "type": "string", - "enum": [ - "wav", - "mp3" - ], - "description": "The format of the encoded audio data. Currently supports \"wav\" and \"mp3\".\n" - } - }, - "required": [ - "data", - "format" - ] - } - }, - "required": [ - "type", - "input_audio" - ], - "x-stainless-naming": { - "go": { - "variant_constructor": "InputAudioContentPart" - } - } - }, - "ChatCompletionRequestMessageContentPartFile": { - "type": "object", - "title": "File content part", - "description": "Learn about [file inputs](https://platform.openai.com/docs/guides/text) for text generation.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "file" - ], - "description": "The type of the content part. Always `file`.", - "x-stainless-const": true - }, - "file": { - "type": "object", - "properties": { - "filename": { - "type": "string", - "description": "The name of the file, used when passing the file to the model as a \nstring.\n" - }, - "file_data": { - "type": "string", - "description": "The base64 encoded file data, used when passing the file to the model \nas a string.\n" - }, - "file_id": { - "type": "string", - "description": "The ID of an uploaded file to use as input.\n" - } - }, - "x-stainless-naming": { - "java": { - "type_name": "FileObject" - }, - "kotlin": { - "type_name": "FileObject" - } - } - } - }, - "required": [ - "type", - "file" - ], - "x-stainless-naming": { - "go": { - "variant_constructor": "FileContentPart" - } - } - }, - "ChatCompletionRequestMessageContentPartImage": { - "type": "object", - "title": "Image content part", - "description": "Learn about [image inputs](https://platform.openai.com/docs/guides/vision).\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "image_url" - ], - "description": "The type of the content part.", - "x-stainless-const": true - }, - "image_url": { - "type": "object", - "properties": { - "url": { - "type": "string", - "description": "Either a URL of the image or the base64 encoded image data.", - "format": "uri" - }, - "detail": { - "type": "string", - "description": "Specifies the detail level of the image. Learn more in the [Vision guide](https://platform.openai.com/docs/guides/vision#low-or-high-fidelity-image-understanding).", - "enum": [ - "auto", - "low", - "high" - ], - "default": "auto" - } - }, - "required": [ - "url" - ] - } - }, - "required": [ - "type", - "image_url" - ], - "x-stainless-naming": { - "go": { - "variant_constructor": "ImageContentPart" - } - } - }, - "ChatCompletionRequestMessageContentPartRefusal": { - "type": "object", - "title": "Refusal content part", - "properties": { - "type": { - "type": "string", - "enum": [ - "refusal" - ], - "description": "The type of the content part.", - "x-stainless-const": true - }, - "refusal": { - "type": "string", - "description": "The refusal message generated by the model." - } - }, - "required": [ - "type", - "refusal" - ] - }, - "ChatCompletionRequestMessageContentPartText": { - "type": "object", - "title": "Text content part", - "description": "Learn about [text inputs](https://platform.openai.com/docs/guides/text-generation).\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "text" - ], - "description": "The type of the content part.", - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text content." - } - }, - "required": [ - "type", - "text" - ], - "x-stainless-naming": { - "go": { - "variant_constructor": "TextContentPart" - } - } - }, - "ChatCompletionRequestSystemMessage": { - "type": "object", - "title": "System message", - "description": "Developer-provided instructions that the model should follow, regardless of\nmessages sent by the user. With o1 models and newer, use `developer` messages\nfor this purpose instead.\n", - "properties": { - "content": { - "description": "The contents of the system message.", - "anyOf": [ - { - "type": "string", - "description": "The contents of the system message.", - "title": "Text content" - }, - { - "type": "array", - "description": "An array of content parts with a defined type. For system messages, only type `text` is supported.", - "title": "Array of content parts", - "items": { - "$ref": "#/components/schemas/ChatCompletionRequestSystemMessageContentPart" - }, - "minItems": 1 - } - ] - }, - "role": { - "type": "string", - "enum": [ - "system" - ], - "description": "The role of the messages author, in this case `system`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "An optional name for the participant. Provides the model information to differentiate between participants of the same role." - } - }, - "required": [ - "content", - "role" - ], - "x-stainless-naming": { - "go": { - "variant_constructor": "SystemMessage" - } - } - }, - "ChatCompletionRequestSystemMessageContentPart": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartText" - } - ] - }, - "ChatCompletionRequestToolMessage": { - "type": "object", - "title": "Tool message", - "properties": { - "role": { - "type": "string", - "enum": [ - "tool" - ], - "description": "The role of the messages author, in this case `tool`.", - "x-stainless-const": true - }, - "content": { - "description": "The contents of the tool message.", - "anyOf": [ - { - "type": "string", - "description": "The contents of the tool message.", - "title": "Text content" - }, - { - "type": "array", - "description": "An array of content parts with a defined type. For tool messages, only type `text` is supported.", - "title": "Array of content parts", - "items": { - "$ref": "#/components/schemas/ChatCompletionRequestToolMessageContentPart" - }, - "minItems": 1 - } - ] - }, - "tool_call_id": { - "type": "string", - "description": "Tool call that this message is responding to." - } - }, - "required": [ - "role", - "content", - "tool_call_id" - ], - "x-stainless-naming": { - "go": { - "variant_constructor": "ToolMessage" - } - } - }, - "ChatCompletionRequestToolMessageContentPart": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartText" - } - ] - }, - "ChatCompletionRequestUserMessage": { - "type": "object", - "title": "User message", - "description": "Messages sent by an end user, containing prompts or additional context\ninformation.\n", - "properties": { - "content": { - "description": "The contents of the user message.\n", - "anyOf": [ - { - "type": "string", - "description": "The text contents of the message.", - "title": "Text content" - }, - { - "type": "array", - "description": "An array of content parts with a defined type. Supported options differ based on the [model](https://platform.openai.com/docs/models) being used to generate the response. Can contain text, image, or audio inputs.", - "title": "Array of content parts", - "items": { - "$ref": "#/components/schemas/ChatCompletionRequestUserMessageContentPart" - }, - "minItems": 1 - } - ] - }, - "role": { - "type": "string", - "enum": [ - "user" - ], - "description": "The role of the messages author, in this case `user`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "An optional name for the participant. Provides the model information to differentiate between participants of the same role." - } - }, - "required": [ - "content", - "role" - ], - "x-stainless-naming": { - "go": { - "variant_constructor": "UserMessage" - } - } - }, - "ChatCompletionRequestUserMessageContentPart": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartText" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartImage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartAudio" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartFile" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "ChatCompletionResponseMessage": { - "type": "object", - "description": "A chat completion message generated by the model.", - "properties": { - "content": { - "type": "string", - "description": "The contents of the message.", - "nullable": true - }, - "refusal": { - "type": "string", - "description": "The refusal message generated by the model.", - "nullable": true - }, - "tool_calls": { - "$ref": "#/components/schemas/ChatCompletionMessageToolCalls" - }, - "annotations": { - "type": "array", - "description": "Annotations for the message, when applicable, as when using the\n[web search tool](https://platform.openai.com/docs/guides/tools-web-search?api-mode=chat).\n", - "items": { - "type": "object", - "description": "A URL citation when using web search.\n", - "required": [ - "type", - "url_citation" - ], - "properties": { - "type": { - "type": "string", - "description": "The type of the URL citation. Always `url_citation`.", - "enum": [ - "url_citation" - ], - "x-stainless-const": true - }, - "url_citation": { - "type": "object", - "description": "A URL citation when using web search.", - "required": [ - "end_index", - "start_index", - "url", - "title" - ], - "properties": { - "end_index": { - "type": "integer", - "description": "The index of the last character of the URL citation in the message." - }, - "start_index": { - "type": "integer", - "description": "The index of the first character of the URL citation in the message." - }, - "url": { - "type": "string", - "description": "The URL of the web resource." - }, - "title": { - "type": "string", - "description": "The title of the web resource." - } - } - } - } - } - }, - "role": { - "type": "string", - "enum": [ - "assistant" - ], - "description": "The role of the author of this message.", - "x-stainless-const": true - }, - "function_call": { - "type": "object", - "deprecated": true, - "description": "Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model.", - "properties": { - "arguments": { - "type": "string", - "description": "The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function." - }, - "name": { - "type": "string", - "description": "The name of the function to call." - } - }, - "required": [ - "name", - "arguments" - ] - }, - "audio": { - "type": "object", - "nullable": true, - "description": "If the audio output modality is requested, this object contains data\nabout the audio response from the model. [Learn more](https://platform.openai.com/docs/guides/audio).\n", - "required": [ - "id", - "expires_at", - "data", - "transcript" - ], - "properties": { - "id": { - "type": "string", - "description": "Unique identifier for this audio response." - }, - "expires_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when this audio response will\nno longer be accessible on the server for use in multi-turn\nconversations.\n" - }, - "data": { - "type": "string", - "description": "Base64 encoded audio bytes generated by the model, in the format\nspecified in the request.\n" - }, - "transcript": { - "type": "string", - "description": "Transcript of the audio generated by the model." - } - } - } - }, - "required": [ - "role", - "content", - "refusal" - ] - }, - "ChatCompletionRole": { - "type": "string", - "description": "The role of the author of a message", - "enum": [ - "developer", - "system", - "user", - "assistant", - "tool", - "function" - ] - }, - "ChatCompletionStreamOptions": { - "description": "Options for streaming response. Only set this when you set `stream: true`.\n", - "type": "object", - "nullable": true, - "default": null, - "properties": { - "include_usage": { - "type": "boolean", - "description": "If set, an additional chunk will be streamed before the `data: [DONE]`\nmessage. The `usage` field on this chunk shows the token usage statistics\nfor the entire request, and the `choices` field will always be an empty\narray.\n\nAll other chunks will also include a `usage` field, but with a null\nvalue. **NOTE:** If the stream is interrupted, you may not receive the\nfinal usage chunk which contains the total token usage for the request.\n" - }, - "include_obfuscation": { - "type": "boolean", - "description": "When true, stream obfuscation will be enabled. Stream obfuscation adds\nrandom characters to an `obfuscation` field on streaming delta events to\nnormalize payload sizes as a mitigation to certain side-channel attacks.\nThese obfuscation fields are included by default, but add a small amount\nof overhead to the data stream. You can set `include_obfuscation` to\nfalse to optimize for bandwidth if you trust the network links between\nyour application and the OpenAI API.\n" - } - } - }, - "ChatCompletionStreamResponseDelta": { - "type": "object", - "description": "A chat completion delta generated by streamed model responses.", - "properties": { - "content": { - "type": "string", - "description": "The contents of the chunk message.", - "nullable": true - }, - "function_call": { - "deprecated": true, - "type": "object", - "description": "Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model.", - "properties": { - "arguments": { - "type": "string", - "description": "The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function." - }, - "name": { - "type": "string", - "description": "The name of the function to call." - } - } - }, - "tool_calls": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ChatCompletionMessageToolCallChunk" - } - }, - "role": { - "type": "string", - "enum": [ - "developer", - "system", - "user", - "assistant", - "tool" - ], - "description": "The role of the author of this message." - }, - "refusal": { - "type": "string", - "description": "The refusal message generated by the model.", - "nullable": true - } - } - }, - "ChatCompletionTokenLogprob": { - "type": "object", - "properties": { - "token": { - "description": "The token.", - "type": "string" - }, - "logprob": { - "description": "The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value `-9999.0` is used to signify that the token is very unlikely.", - "type": "number" - }, - "bytes": { - "description": "A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token.", - "type": "array", - "items": { - "type": "integer" - }, - "nullable": true - }, - "top_logprobs": { - "description": "List of the most likely tokens and their log probability, at this token position. In rare cases, there may be fewer than the number of requested `top_logprobs` returned.", - "type": "array", - "items": { - "type": "object", - "properties": { - "token": { - "description": "The token.", - "type": "string" - }, - "logprob": { - "description": "The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value `-9999.0` is used to signify that the token is very unlikely.", - "type": "number" - }, - "bytes": { - "description": "A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token.", - "type": "array", - "items": { - "type": "integer" - }, - "nullable": true - } - }, - "required": [ - "token", - "logprob", - "bytes" - ] - } - } - }, - "required": [ - "token", - "logprob", - "bytes", - "top_logprobs" - ] - }, - "ChatCompletionTool": { - "type": "object", - "title": "Function tool", - "description": "A function tool that can be used to generate a response.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "The type of the tool. Currently, only `function` is supported.", - "x-stainless-const": true - }, - "function": { - "$ref": "#/components/schemas/FunctionObject" - } - }, - "required": [ - "type", - "function" - ] - }, - "ChatCompletionToolChoiceOption": { - "description": "Controls which (if any) tool is called by the model.\n`none` means the model will not call any tool and instead generates a message.\n`auto` means the model can pick between generating a message or calling one or more tools.\n`required` means the model must call one or more tools.\nSpecifying a particular tool via `{\"type\": \"function\", \"function\": {\"name\": \"my_function\"}}` forces the model to call that tool.\n\n`none` is the default when no tools are present. `auto` is the default if tools are present.\n", - "anyOf": [ - { - "type": "string", - "title": "Auto", - "description": "`none` means the model will not call any tool and instead generates a message. `auto` means the model can pick between generating a message or calling one or more tools. `required` means the model must call one or more tools.\n", - "enum": [ - "none", - "auto", - "required" - ] - }, - { - "$ref": "#/components/schemas/ChatCompletionAllowedToolsChoice" - }, - { - "$ref": "#/components/schemas/ChatCompletionNamedToolChoice" - }, - { - "$ref": "#/components/schemas/ChatCompletionNamedToolChoiceCustom" - } - ], - "x-stainless-go-variant-constructor": { - "naming": "tool_choice_option_{variant}" - } - }, - "ChunkingStrategyRequestParam": { - "type": "object", - "description": "The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy. Only applicable if `file_ids` is non-empty.", - "anyOf": [ - { - "$ref": "#/components/schemas/AutoChunkingStrategyRequestParam" - }, - { - "$ref": "#/components/schemas/StaticChunkingStrategyRequestParam" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "Click": { - "type": "object", - "title": "Click", - "description": "A click action.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "click" - ], - "default": "click", - "description": "Specifies the event type. For a click action, this property is \nalways set to `click`.\n", - "x-stainless-const": true - }, - "button": { - "type": "string", - "enum": [ - "left", - "right", - "wheel", - "back", - "forward" - ], - "description": "Indicates which mouse button was pressed during the click. One of `left`, `right`, `wheel`, `back`, or `forward`.\n" - }, - "x": { - "type": "integer", - "description": "The x-coordinate where the click occurred.\n" - }, - "y": { - "type": "integer", - "description": "The y-coordinate where the click occurred.\n" - } - }, - "required": [ - "type", - "button", - "x", - "y" - ] - }, - "CodeInterpreterFileOutput": { - "type": "object", - "title": "Code interpreter file output", - "description": "The output of a code interpreter tool call that is a file.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "files" - ], - "description": "The type of the code interpreter file output. Always `files`.\n", - "x-stainless-const": true - }, - "files": { - "type": "array", - "items": { - "type": "object", - "properties": { - "mime_type": { - "type": "string", - "description": "The MIME type of the file.\n" - }, - "file_id": { - "type": "string", - "description": "The ID of the file.\n" - } - }, - "required": [ - "mime_type", - "file_id" - ] - } - } - }, - "required": [ - "type", - "files" - ] - }, - "CodeInterpreterOutputImage": { - "type": "object", - "title": "Code interpreter output image", - "description": "The image output from the code interpreter.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "image" - ], - "default": "image", - "x-stainless-const": true, - "description": "The type of the output. Always 'image'." - }, - "url": { - "type": "string", - "description": "The URL of the image output from the code interpreter." - } - }, - "required": [ - "type", - "url" - ] - }, - "CodeInterpreterOutputLogs": { - "type": "object", - "title": "Code interpreter output logs", - "description": "The logs output from the code interpreter.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "logs" - ], - "default": "logs", - "x-stainless-const": true, - "description": "The type of the output. Always 'logs'." - }, - "logs": { - "type": "string", - "description": "The logs output from the code interpreter." - } - }, - "required": [ - "type", - "logs" - ] - }, - "CodeInterpreterTextOutput": { - "type": "object", - "title": "Code interpreter text output", - "description": "The output of a code interpreter tool call that is text.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "logs" - ], - "description": "The type of the code interpreter text output. Always `logs`.\n", - "x-stainless-const": true - }, - "logs": { - "type": "string", - "description": "The logs of the code interpreter tool call.\n" - } - }, - "required": [ - "type", - "logs" - ] - }, - "CodeInterpreterTool": { - "type": "object", - "title": "Code interpreter", - "description": "A tool that runs Python code to help generate a response to a prompt.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "code_interpreter" - ], - "description": "The type of the code interpreter tool. Always `code_interpreter`.\n", - "x-stainless-const": true - }, - "container": { - "description": "The code interpreter container. Can be a container ID or an object that\nspecifies uploaded file IDs to make available to your code.\n", - "anyOf": [ - { - "type": "string", - "description": "The container ID." - }, - { - "$ref": "#/components/schemas/CodeInterpreterToolAuto" - } - ] - } - }, - "required": [ - "type", - "container" - ] - }, - "CodeInterpreterToolAuto": { - "type": "object", - "title": "CodeInterpreterContainerAuto", - "description": "Configuration for a code interpreter container. Optionally specify the IDs\nof the files to run the code on.\n", - "required": [ - "type" - ], - "properties": { - "type": { - "type": "string", - "enum": [ - "auto" - ], - "description": "Always `auto`.", - "x-stainless-const": true - }, - "file_ids": { - "type": "array", - "items": { - "type": "string" - }, - "description": "An optional list of uploaded files to make available to your code.\n" - } - } - }, - "CodeInterpreterToolCall": { - "type": "object", - "title": "Code interpreter tool call", - "description": "A tool call to run code.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "code_interpreter_call" - ], - "default": "code_interpreter_call", - "x-stainless-const": true, - "description": "The type of the code interpreter tool call. Always `code_interpreter_call`.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the code interpreter tool call.\n" - }, - "status": { - "type": "string", - "enum": [ - "in_progress", - "completed", - "incomplete", - "interpreting", - "failed" - ], - "description": "The status of the code interpreter tool call. Valid values are `in_progress`, `completed`, `incomplete`, `interpreting`, and `failed`.\n" - }, - "container_id": { - "type": "string", - "description": "The ID of the container used to run the code.\n" - }, - "code": { - "type": "string", - "nullable": true, - "description": "The code to run, or null if not available.\n" - }, - "outputs": { - "type": "array", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/CodeInterpreterOutputLogs" - }, - { - "$ref": "#/components/schemas/CodeInterpreterOutputImage" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "discriminator": { - "propertyName": "type" - }, - "nullable": true, - "description": "The outputs generated by the code interpreter, such as logs or images. \nCan be null if no outputs are available.\n" - } - }, - "required": [ - "type", - "id", - "status", - "container_id", - "code", - "outputs" - ] - }, - "ComparisonFilter": { - "type": "object", - "additionalProperties": false, - "title": "Comparison Filter", - "description": "A filter used to compare a specified attribute key to a given value using a defined comparison operation.\n", - "properties": { - "type": { - "type": "string", - "default": "eq", - "enum": [ - "eq", - "ne", - "gt", - "gte", - "lt", - "lte" - ], - "description": "Specifies the comparison operator: `eq`, `ne`, `gt`, `gte`, `lt`, `lte`.\n- `eq`: equals\n- `ne`: not equal\n- `gt`: greater than\n- `gte`: greater than or equal\n- `lt`: less than\n- `lte`: less than or equal\n" - }, - "key": { - "type": "string", - "description": "The key to compare against the value." - }, - "value": { - "description": "The value to compare against the attribute key; supports string, number, or boolean types.", - "anyOf": [ - { - "type": "string" - }, - { - "type": "number" - }, - { - "type": "boolean" - } - ] - } - }, - "required": [ - "type", - "key", - "value" - ], - "x-oaiMeta": { - "name": "ComparisonFilter" - } - }, - "CompleteUploadRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "part_ids": { - "type": "array", - "description": "The ordered list of Part IDs.\n", - "items": { - "type": "string" - } - }, - "md5": { - "description": "The optional md5 checksum for the file contents to verify if the bytes uploaded matches what you expect.\n", - "type": "string" - } - }, - "required": [ - "part_ids" - ] - }, - "CompletionUsage": { - "type": "object", - "description": "Usage statistics for the completion request.", - "properties": { - "completion_tokens": { - "type": "integer", - "default": 0, - "description": "Number of tokens in the generated completion." - }, - "prompt_tokens": { - "type": "integer", - "default": 0, - "description": "Number of tokens in the prompt." - }, - "total_tokens": { - "type": "integer", - "default": 0, - "description": "Total number of tokens used in the request (prompt + completion)." - }, - "completion_tokens_details": { - "type": "object", - "description": "Breakdown of tokens used in a completion.", - "properties": { - "accepted_prediction_tokens": { - "type": "integer", - "default": 0, - "description": "When using Predicted Outputs, the number of tokens in the\nprediction that appeared in the completion.\n" - }, - "audio_tokens": { - "type": "integer", - "default": 0, - "description": "Audio input tokens generated by the model." - }, - "reasoning_tokens": { - "type": "integer", - "default": 0, - "description": "Tokens generated by the model for reasoning." - }, - "rejected_prediction_tokens": { - "type": "integer", - "default": 0, - "description": "When using Predicted Outputs, the number of tokens in the\nprediction that did not appear in the completion. However, like\nreasoning tokens, these tokens are still counted in the total\ncompletion tokens for purposes of billing, output, and context window\nlimits.\n" - } - } - }, - "prompt_tokens_details": { - "type": "object", - "description": "Breakdown of tokens used in the prompt.", - "properties": { - "audio_tokens": { - "type": "integer", - "default": 0, - "description": "Audio input tokens present in the prompt." - }, - "cached_tokens": { - "type": "integer", - "default": 0, - "description": "Cached tokens present in the prompt." - } - } - } - }, - "required": [ - "prompt_tokens", - "completion_tokens", - "total_tokens" - ] - }, - "CompoundFilter": { - "$recursiveAnchor": true, - "type": "object", - "additionalProperties": false, - "title": "Compound Filter", - "description": "Combine multiple filters using `and` or `or`.", - "properties": { - "type": { - "type": "string", - "description": "Type of operation: `and` or `or`.", - "enum": [ - "and", - "or" - ] - }, - "filters": { - "type": "array", - "description": "Array of filters to combine. Items can be `ComparisonFilter` or `CompoundFilter`.", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ComparisonFilter" - }, - { - "$recursiveRef": "#" - } - ] - } - } - }, - "required": [ - "type", - "filters" - ], - "x-oaiMeta": { - "name": "CompoundFilter" - } - }, - "ComputerAction": { - "anyOf": [ - { - "$ref": "#/components/schemas/Click" - }, - { - "$ref": "#/components/schemas/DoubleClick" - }, - { - "$ref": "#/components/schemas/Drag" - }, - { - "$ref": "#/components/schemas/KeyPress" - }, - { - "$ref": "#/components/schemas/Move" - }, - { - "$ref": "#/components/schemas/Screenshot" - }, - { - "$ref": "#/components/schemas/Scroll" - }, - { - "$ref": "#/components/schemas/Type" - }, - { - "$ref": "#/components/schemas/Wait" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "ComputerScreenshotImage": { - "type": "object", - "description": "A computer screenshot image used with the computer use tool.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "computer_screenshot" - ], - "default": "computer_screenshot", - "description": "Specifies the event type. For a computer screenshot, this property is \nalways set to `computer_screenshot`.\n", - "x-stainless-const": true - }, - "image_url": { - "type": "string", - "description": "The URL of the screenshot image." - }, - "file_id": { - "type": "string", - "description": "The identifier of an uploaded file that contains the screenshot." - } - }, - "required": [ - "type" - ] - }, - "ComputerToolCall": { - "type": "object", - "title": "Computer tool call", - "description": "A tool call to a computer use tool. See the \n[computer use guide](https://platform.openai.com/docs/guides/tools-computer-use) for more information.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the computer call. Always `computer_call`.", - "enum": [ - "computer_call" - ], - "default": "computer_call" - }, - "id": { - "type": "string", - "description": "The unique ID of the computer call." - }, - "call_id": { - "type": "string", - "description": "An identifier used when responding to the tool call with output.\n" - }, - "action": { - "$ref": "#/components/schemas/ComputerAction" - }, - "pending_safety_checks": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ComputerToolCallSafetyCheck" - }, - "description": "The pending safety checks for the computer call.\n" - }, - "status": { - "type": "string", - "description": "The status of the item. One of `in_progress`, `completed`, or\n`incomplete`. Populated when items are returned via API.\n", - "enum": [ - "in_progress", - "completed", - "incomplete" - ] - } - }, - "required": [ - "type", - "id", - "action", - "call_id", - "pending_safety_checks", - "status" - ] - }, - "ComputerToolCallOutput": { - "type": "object", - "title": "Computer tool call output", - "description": "The output of a computer tool call.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the computer tool call output. Always `computer_call_output`.\n", - "enum": [ - "computer_call_output" - ], - "default": "computer_call_output", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The ID of the computer tool call output.\n" - }, - "call_id": { - "type": "string", - "description": "The ID of the computer tool call that produced the output.\n" - }, - "acknowledged_safety_checks": { - "type": "array", - "description": "The safety checks reported by the API that have been acknowledged by the \ndeveloper.\n", - "items": { - "$ref": "#/components/schemas/ComputerToolCallSafetyCheck" - } - }, - "output": { - "$ref": "#/components/schemas/ComputerScreenshotImage" - }, - "status": { - "type": "string", - "description": "The status of the message input. One of `in_progress`, `completed`, or\n`incomplete`. Populated when input items are returned via API.\n", - "enum": [ - "in_progress", - "completed", - "incomplete" - ] - } - }, - "required": [ - "type", - "call_id", - "output" - ] - }, - "ComputerToolCallOutputResource": { - "allOf": [ - { - "$ref": "#/components/schemas/ComputerToolCallOutput" - }, - { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the computer call tool output.\n" - } - }, - "required": [ - "id" - ] - } - ] - }, - "ComputerToolCallSafetyCheck": { - "type": "object", - "description": "A pending safety check for the computer call.\n", - "properties": { - "id": { - "type": "string", - "description": "The ID of the pending safety check." - }, - "code": { - "type": "string", - "description": "The type of the pending safety check." - }, - "message": { - "type": "string", - "description": "Details about the pending safety check." - } - }, - "required": [ - "id", - "code", - "message" - ] - }, - "ContainerFileListResource": { - "type": "object", - "properties": { - "object": { - "description": "The type of object returned, must be 'list'.", - "const": "list" - }, - "data": { - "type": "array", - "description": "A list of container files.", - "items": { - "$ref": "#/components/schemas/ContainerFileResource" - } - }, - "first_id": { - "type": "string", - "description": "The ID of the first file in the list." - }, - "last_id": { - "type": "string", - "description": "The ID of the last file in the list." - }, - "has_more": { - "type": "boolean", - "description": "Whether there are more files available." - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ContainerFileResource": { - "type": "object", - "title": "The container file object", - "properties": { - "id": { - "type": "string", - "description": "Unique identifier for the file." - }, - "object": { - "type": "string", - "description": "The type of this object (`container.file`).", - "const": "container.file" - }, - "container_id": { - "type": "string", - "description": "The container this file belongs to." - }, - "created_at": { - "type": "integer", - "description": "Unix timestamp (in seconds) when the file was created." - }, - "bytes": { - "type": "integer", - "description": "Size of the file in bytes." - }, - "path": { - "type": "string", - "description": "Path of the file in the container." - }, - "source": { - "type": "string", - "description": "Source of the file (e.g., `user`, `assistant`)." - } - }, - "required": [ - "id", - "object", - "created_at", - "bytes", - "container_id", - "path", - "source" - ], - "x-oaiMeta": { - "name": "The container file object", - "example": "{\n \"id\": \"cfile_682e0e8a43c88191a7978f477a09bdf5\",\n \"object\": \"container.file\",\n \"created_at\": 1747848842,\n \"bytes\": 880,\n \"container_id\": \"cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04\",\n \"path\": \"/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json\",\n \"source\": \"user\"\n}\n" - } - }, - "ContainerListResource": { - "type": "object", - "properties": { - "object": { - "description": "The type of object returned, must be 'list'.", - "const": "list" - }, - "data": { - "type": "array", - "description": "A list of containers.", - "items": { - "$ref": "#/components/schemas/ContainerResource" - } - }, - "first_id": { - "type": "string", - "description": "The ID of the first container in the list." - }, - "last_id": { - "type": "string", - "description": "The ID of the last container in the list." - }, - "has_more": { - "type": "boolean", - "description": "Whether there are more containers available." - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ContainerResource": { - "type": "object", - "title": "The container object", - "properties": { - "id": { - "type": "string", - "description": "Unique identifier for the container." - }, - "object": { - "type": "string", - "description": "The type of this object." - }, - "name": { - "type": "string", - "description": "Name of the container." - }, - "created_at": { - "type": "integer", - "description": "Unix timestamp (in seconds) when the container was created." - }, - "status": { - "type": "string", - "description": "Status of the container (e.g., active, deleted)." - }, - "expires_after": { - "type": "object", - "description": "The container will expire after this time period.\nThe anchor is the reference point for the expiration.\nThe minutes is the number of minutes after the anchor before the container expires.\n", - "properties": { - "anchor": { - "type": "string", - "description": "The reference point for the expiration.", - "enum": [ - "last_active_at" - ] - }, - "minutes": { - "type": "integer", - "description": "The number of minutes after the anchor before the container expires." - } - } - } - }, - "required": [ - "id", - "object", - "name", - "created_at", - "status", - "id", - "name", - "created_at", - "status" - ], - "x-oaiMeta": { - "name": "The container object", - "example": "{\n \"id\": \"cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863\",\n \"object\": \"container\",\n \"created_at\": 1747844794,\n \"status\": \"running\",\n \"expires_after\": {\n \"anchor\": \"last_active_at\",\n \"minutes\": 20\n },\n \"last_active_at\": 1747844794,\n \"name\": \"My Container\"\n}\n" - } - }, - "Content": { - "description": "Multi-modal input and output contents.\n", - "anyOf": [ - { - "title": "Input content types", - "$ref": "#/components/schemas/InputContent" - }, - { - "title": "Output content types", - "$ref": "#/components/schemas/OutputContent" - } - ] - }, - "Conversation": { - "title": "The conversation object", - "allOf": [ - { - "$ref": "#/components/schemas/ConversationResource" - } - ], - "x-oaiMeta": { - "name": "The conversation object", - "group": "conversations" - } - }, - "ConversationItem": { - "title": "Conversation item", - "description": "A single item within a conversation. The set of possible types are the same as the `output` type of a [Response object](https://platform.openai.com/docs/api-reference/responses/object#responses/object-output).", - "discriminator": { - "propertyName": "type" - }, - "x-oaiMeta": { - "name": "The item object", - "group": "conversations" - }, - "anyOf": [ - { - "$ref": "#/components/schemas/Message" - }, - { - "$ref": "#/components/schemas/FunctionToolCallResource" - }, - { - "$ref": "#/components/schemas/FunctionToolCallOutputResource" - }, - { - "$ref": "#/components/schemas/FileSearchToolCall" - }, - { - "$ref": "#/components/schemas/WebSearchToolCall" - }, - { - "$ref": "#/components/schemas/ImageGenToolCall" - }, - { - "$ref": "#/components/schemas/ComputerToolCall" - }, - { - "$ref": "#/components/schemas/ComputerToolCallOutputResource" - }, - { - "$ref": "#/components/schemas/ReasoningItem" - }, - { - "$ref": "#/components/schemas/CodeInterpreterToolCall" - }, - { - "$ref": "#/components/schemas/LocalShellToolCall" - }, - { - "$ref": "#/components/schemas/LocalShellToolCallOutput" - }, - { - "$ref": "#/components/schemas/MCPListTools" - }, - { - "$ref": "#/components/schemas/MCPApprovalRequest" - }, - { - "$ref": "#/components/schemas/MCPApprovalResponseResource" - }, - { - "$ref": "#/components/schemas/MCPToolCall" - }, - { - "$ref": "#/components/schemas/CustomToolCall" - }, - { - "$ref": "#/components/schemas/CustomToolCallOutput" - } - ] - }, - "ConversationItemList": { - "type": "object", - "title": "The conversation item list", - "description": "A list of Conversation items.", - "properties": { - "object": { - "description": "The type of object returned, must be `list`.", - "x-stainless-const": true, - "const": "list" - }, - "data": { - "type": "array", - "description": "A list of conversation items.", - "items": { - "$ref": "#/components/schemas/ConversationItem" - } - }, - "has_more": { - "type": "boolean", - "description": "Whether there are more items available." - }, - "first_id": { - "type": "string", - "description": "The ID of the first item in the list." - }, - "last_id": { - "type": "string", - "description": "The ID of the last item in the list." - } - }, - "required": [ - "object", - "data", - "has_more", - "first_id", - "last_id" - ], - "x-oaiMeta": { - "name": "The item list", - "group": "conversations" - } - }, - "Coordinate": { - "type": "object", - "title": "Coordinate", - "description": "An x/y coordinate pair, e.g. `{ x: 100, y: 200 }`.\n", - "properties": { - "x": { - "type": "integer", - "description": "The x-coordinate.\n" - }, - "y": { - "type": "integer", - "description": "The y-coordinate.\n" - } - }, - "required": [ - "x", - "y" - ] - }, - "CostsResult": { - "type": "object", - "description": "The aggregated costs details of the specific time bucket.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.costs.result" - ], - "x-stainless-const": true - }, - "amount": { - "type": "object", - "description": "The monetary value in its associated currency.", - "properties": { - "value": { - "type": "number", - "description": "The numeric value of the cost." - }, - "currency": { - "type": "string", - "description": "Lowercase ISO-4217 currency e.g. \"usd\"" - } - } - }, - "line_item": { - "type": "string", - "nullable": true, - "description": "When `group_by=line_item`, this field provides the line item of the grouped costs result." - }, - "project_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=project_id`, this field provides the project ID of the grouped costs result." - } - }, - "required": [ - "object" - ], - "x-oaiMeta": { - "name": "Costs object", - "example": "{\n \"object\": \"organization.costs.result\",\n \"amount\": {\n \"value\": 0.06,\n \"currency\": \"usd\"\n },\n \"line_item\": \"Image models\",\n \"project_id\": \"proj_abc\"\n}\n" - } - }, - "CreateAssistantRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "model": { - "description": "ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models) for descriptions of them.\n", - "example": "gpt-4o", - "anyOf": [ - { - "type": "string" - }, - { - "$ref": "#/components/schemas/AssistantSupportedModels" - } - ], - "x-oaiTypeLabel": "string" - }, - "name": { - "description": "The name of the assistant. The maximum length is 256 characters.\n", - "type": "string", - "nullable": true, - "maxLength": 256 - }, - "description": { - "description": "The description of the assistant. The maximum length is 512 characters.\n", - "type": "string", - "nullable": true, - "maxLength": 512 - }, - "instructions": { - "description": "The system instructions that the assistant uses. The maximum length is 256,000 characters.\n", - "type": "string", - "nullable": true, - "maxLength": 256000 - }, - "reasoning_effort": { - "$ref": "#/components/schemas/ReasoningEffort" - }, - "tools": { - "description": "A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.\n", - "default": [], - "type": "array", - "maxItems": 128, - "items": { - "$ref": "#/components/schemas/AssistantTool" - } - }, - "tool_resources": { - "type": "object", - "description": "A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.\n", - "properties": { - "code_interpreter": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.\n", - "default": [], - "maxItems": 20, - "items": { - "type": "string" - } - } - } - }, - "file_search": { - "type": "object", - "properties": { - "vector_store_ids": { - "type": "array", - "description": "The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.\n", - "maxItems": 1, - "items": { - "type": "string" - } - }, - "vector_stores": { - "type": "array", - "description": "A helper to create a [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) with file_ids and attach it to this assistant. There can be a maximum of 1 vector store attached to the assistant.\n", - "maxItems": 1, - "items": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "A list of [file](https://platform.openai.com/docs/api-reference/files) IDs to add to the vector store. There can be a maximum of 10000 files in a vector store.\n", - "maxItems": 10000, - "items": { - "type": "string" - } - }, - "chunking_strategy": { - "type": "object", - "description": "The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy.", - "anyOf": [ - { - "type": "object", - "title": "Auto Chunking Strategy", - "description": "The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and `chunk_overlap_tokens` of `400`.", - "additionalProperties": false, - "properties": { - "type": { - "type": "string", - "description": "Always `auto`.", - "enum": [ - "auto" - ], - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - { - "type": "object", - "title": "Static Chunking Strategy", - "additionalProperties": false, - "properties": { - "type": { - "type": "string", - "description": "Always `static`.", - "enum": [ - "static" - ], - "x-stainless-const": true - }, - "static": { - "type": "object", - "additionalProperties": false, - "properties": { - "max_chunk_size_tokens": { - "type": "integer", - "minimum": 100, - "maximum": 4096, - "description": "The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100` and the maximum value is `4096`." - }, - "chunk_overlap_tokens": { - "type": "integer", - "description": "The number of tokens that overlap between chunks. The default value is `400`.\n\nNote that the overlap must not exceed half of `max_chunk_size_tokens`.\n" - } - }, - "required": [ - "max_chunk_size_tokens", - "chunk_overlap_tokens" - ] - } - }, - "required": [ - "type", - "static" - ], - "x-stainless-naming": { - "java": { - "type_name": "StaticObject" - }, - "kotlin": { - "type_name": "StaticObject" - } - } - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - } - } - }, - "anyOf": [ - { - "required": [ - "vector_store_ids" - ] - }, - { - "required": [ - "vector_stores" - ] - } - ] - } - }, - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "temperature": { - "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n", - "type": "number", - "minimum": 0, - "maximum": 2, - "default": 1, - "example": 1, - "nullable": true - }, - "top_p": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 1, - "example": 1, - "nullable": true, - "description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or temperature but not both.\n" - }, - "response_format": { - "$ref": "#/components/schemas/AssistantsApiResponseFormatOption", - "nullable": true - } - }, - "required": [ - "model" - ] - }, - "CreateChatCompletionRequest": { - "allOf": [ - { - "$ref": "#/components/schemas/CreateModelResponseProperties" - }, - { - "type": "object", - "properties": { - "messages": { - "description": "A list of messages comprising the conversation so far. Depending on the\n[model](https://platform.openai.com/docs/models) you use, different message types (modalities) are\nsupported, like [text](https://platform.openai.com/docs/guides/text-generation),\n[images](https://platform.openai.com/docs/guides/vision), and [audio](https://platform.openai.com/docs/guides/audio).\n", - "type": "array", - "minItems": 1, - "items": { - "$ref": "#/components/schemas/ChatCompletionRequestMessage" - } - }, - "model": { - "description": "Model ID used to generate the response, like `gpt-4o` or `o3`. OpenAI\noffers a wide range of models with different capabilities, performance\ncharacteristics, and price points. Refer to the [model guide](https://platform.openai.com/docs/models)\nto browse and compare available models.\n", - "$ref": "#/components/schemas/ModelIdsShared" - }, - "modalities": { - "$ref": "#/components/schemas/ResponseModalities" - }, - "verbosity": { - "$ref": "#/components/schemas/Verbosity" - }, - "reasoning_effort": { - "$ref": "#/components/schemas/ReasoningEffort" - }, - "max_completion_tokens": { - "description": "An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and [reasoning tokens](https://platform.openai.com/docs/guides/reasoning).\n", - "type": "integer", - "nullable": true - }, - "frequency_penalty": { - "type": "number", - "default": 0, - "minimum": -2, - "maximum": 2, - "nullable": true, - "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on\ntheir existing frequency in the text so far, decreasing the model's\nlikelihood to repeat the same line verbatim.\n" - }, - "presence_penalty": { - "type": "number", - "default": 0, - "minimum": -2, - "maximum": 2, - "nullable": true, - "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on\nwhether they appear in the text so far, increasing the model's likelihood\nto talk about new topics.\n" - }, - "web_search_options": { - "type": "object", - "title": "Web search", - "description": "This tool searches the web for relevant results to use in a response.\nLearn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search?api-mode=chat).\n", - "properties": { - "user_location": { - "type": "object", - "nullable": true, - "required": [ - "type", - "approximate" - ], - "description": "Approximate location parameters for the search.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of location approximation. Always `approximate`.\n", - "enum": [ - "approximate" - ], - "x-stainless-const": true - }, - "approximate": { - "$ref": "#/components/schemas/WebSearchLocation" - } - } - }, - "search_context_size": { - "$ref": "#/components/schemas/WebSearchContextSize" - } - } - }, - "top_logprobs": { - "description": "An integer between 0 and 20 specifying the number of most likely tokens to\nreturn at each token position, each with an associated log probability.\n`logprobs` must be set to `true` if this parameter is used.\n", - "type": "integer", - "minimum": 0, - "maximum": 20, - "nullable": true - }, - "response_format": { - "description": "An object specifying the format that the model must output.\n\nSetting to `{ \"type\": \"json_schema\", \"json_schema\": {...} }` enables\nStructured Outputs which ensures the model will match your supplied JSON\nschema. Learn more in the [Structured Outputs\nguide](https://platform.openai.com/docs/guides/structured-outputs).\n\nSetting to `{ \"type\": \"json_object\" }` enables the older JSON mode, which\nensures the message the model generates is valid JSON. Using `json_schema`\nis preferred for models that support it.\n", - "anyOf": [ - { - "$ref": "#/components/schemas/ResponseFormatText" - }, - { - "$ref": "#/components/schemas/ResponseFormatJsonSchema" - }, - { - "$ref": "#/components/schemas/ResponseFormatJsonObject" - } - ] - }, - "audio": { - "type": "object", - "nullable": true, - "description": "Parameters for audio output. Required when audio output is requested with\n`modalities: [\"audio\"]`. [Learn more](https://platform.openai.com/docs/guides/audio).\n", - "required": [ - "voice", - "format" - ], - "properties": { - "voice": { - "$ref": "#/components/schemas/VoiceIdsShared", - "description": "The voice the model uses to respond. Supported voices are\n`alloy`, `ash`, `ballad`, `coral`, `echo`, `fable`, `nova`, `onyx`, `sage`, and `shimmer`.\n" - }, - "format": { - "type": "string", - "enum": [ - "wav", - "aac", - "mp3", - "flac", - "opus", - "pcm16" - ], - "description": "Specifies the output audio format. Must be one of `wav`, `mp3`, `flac`,\n`opus`, or `pcm16`.\n" - } - } - }, - "store": { - "type": "boolean", - "default": false, - "nullable": true, - "description": "Whether or not to store the output of this chat completion request for\nuse in our [model distillation](https://platform.openai.com/docs/guides/distillation) or\n[evals](https://platform.openai.com/docs/guides/evals) products.\n\nSupports text and image inputs. Note: image inputs over 8MB will be dropped.\n" - }, - "stream": { - "description": "If set to true, the model response data will be streamed to the client\nas it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).\nSee the [Streaming section below](https://platform.openai.com/docs/api-reference/chat/streaming)\nfor more information, along with the [streaming responses](https://platform.openai.com/docs/guides/streaming-responses)\nguide for more information on how to handle the streaming events.\n", - "type": "boolean", - "nullable": true, - "default": false - }, - "stop": { - "$ref": "#/components/schemas/StopConfiguration" - }, - "logit_bias": { - "type": "object", - "x-oaiTypeLabel": "map", - "default": null, - "nullable": true, - "additionalProperties": { - "type": "integer" - }, - "description": "Modify the likelihood of specified tokens appearing in the completion.\n\nAccepts a JSON object that maps tokens (specified by their token ID in the\ntokenizer) to an associated bias value from -100 to 100. Mathematically,\nthe bias is added to the logits generated by the model prior to sampling.\nThe exact effect will vary per model, but values between -1 and 1 should\ndecrease or increase likelihood of selection; values like -100 or 100\nshould result in a ban or exclusive selection of the relevant token.\n" - }, - "logprobs": { - "description": "Whether to return log probabilities of the output tokens or not. If true,\nreturns the log probabilities of each output token returned in the\n`content` of `message`.\n", - "type": "boolean", - "default": false, - "nullable": true - }, - "max_tokens": { - "description": "The maximum number of [tokens](/tokenizer) that can be generated in the\nchat completion. This value can be used to control\n[costs](https://openai.com/api/pricing/) for text generated via API.\n\nThis value is now deprecated in favor of `max_completion_tokens`, and is\nnot compatible with [o-series models](https://platform.openai.com/docs/guides/reasoning).\n", - "type": "integer", - "nullable": true, - "deprecated": true - }, - "n": { - "type": "integer", - "minimum": 1, - "maximum": 128, - "default": 1, - "example": 1, - "nullable": true, - "description": "How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep `n` as `1` to minimize costs." - }, - "prediction": { - "nullable": true, - "description": "Configuration for a [Predicted Output](https://platform.openai.com/docs/guides/predicted-outputs),\nwhich can greatly improve response times when large parts of the model\nresponse are known ahead of time. This is most common when you are\nregenerating a file with only minor changes to most of the content.\n", - "anyOf": [ - { - "$ref": "#/components/schemas/PredictionContent" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "seed": { - "type": "integer", - "minimum": -9223372036854776000, - "maximum": 9223372036854776000, - "nullable": true, - "deprecated": true, - "description": "This feature is in Beta.\nIf specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result.\nDeterminism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend.\n", - "x-oaiMeta": { - "beta": true - } - }, - "stream_options": { - "$ref": "#/components/schemas/ChatCompletionStreamOptions" - }, - "tools": { - "type": "array", - "description": "A list of tools the model may call. You can provide either\n[custom tools](https://platform.openai.com/docs/guides/function-calling#custom-tools) or\n[function tools](https://platform.openai.com/docs/guides/function-calling).\n", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionTool" - }, - { - "$ref": "#/components/schemas/CustomToolChatCompletions" - } - ], - "x-stainless-naming": { - "python": { - "model_name": "chat_completion_tool_union", - "param_model_name": "chat_completion_tool_union_param" - } - }, - "discriminator": { - "propertyName": "type" - }, - "x-stainless-go-variant-constructor": { - "naming": "chat_completion_{variant}_tool" - } - } - }, - "tool_choice": { - "$ref": "#/components/schemas/ChatCompletionToolChoiceOption" - }, - "parallel_tool_calls": { - "$ref": "#/components/schemas/ParallelToolCalls" - }, - "function_call": { - "deprecated": true, - "description": "Deprecated in favor of `tool_choice`.\n\nControls which (if any) function is called by the model.\n\n`none` means the model will not call a function and instead generates a\nmessage.\n\n`auto` means the model can pick between generating a message or calling a\nfunction.\n\nSpecifying a particular function via `{\"name\": \"my_function\"}` forces the\nmodel to call that function.\n\n`none` is the default when no functions are present. `auto` is the default\nif functions are present.\n", - "anyOf": [ - { - "type": "string", - "description": "`none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function.\n", - "enum": [ - "none", - "auto" - ], - "title": "function call mode" - }, - { - "$ref": "#/components/schemas/ChatCompletionFunctionCallOption" - } - ] - }, - "functions": { - "deprecated": true, - "description": "Deprecated in favor of `tools`.\n\nA list of functions the model may generate JSON inputs for.\n", - "type": "array", - "minItems": 1, - "maxItems": 128, - "items": { - "$ref": "#/components/schemas/ChatCompletionFunctions" - } - } - }, - "required": [ - "model", - "messages" - ] - } - ] - }, - "CreateChatCompletionResponse": { - "type": "object", - "description": "Represents a chat completion response returned by model, based on the provided input.", - "properties": { - "id": { - "type": "string", - "description": "A unique identifier for the chat completion." - }, - "choices": { - "type": "array", - "description": "A list of chat completion choices. Can be more than one if `n` is greater than 1.", - "items": { - "type": "object", - "required": [ - "finish_reason", - "index", - "message", - "logprobs" - ], - "properties": { - "finish_reason": { - "type": "string", - "description": "The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence,\n`length` if the maximum number of tokens specified in the request was reached,\n`content_filter` if content was omitted due to a flag from our content filters,\n`tool_calls` if the model called a tool, or `function_call` (deprecated) if the model called a function.\n", - "enum": [ - "stop", - "length", - "tool_calls", - "content_filter", - "function_call" - ] - }, - "index": { - "type": "integer", - "description": "The index of the choice in the list of choices." - }, - "message": { - "$ref": "#/components/schemas/ChatCompletionResponseMessage" - }, - "logprobs": { - "description": "Log probability information for the choice.", - "type": "object", - "nullable": true, - "properties": { - "content": { - "description": "A list of message content tokens with log probability information.", - "type": "array", - "items": { - "$ref": "#/components/schemas/ChatCompletionTokenLogprob" - }, - "nullable": true - }, - "refusal": { - "description": "A list of message refusal tokens with log probability information.", - "type": "array", - "items": { - "$ref": "#/components/schemas/ChatCompletionTokenLogprob" - }, - "nullable": true - } - }, - "required": [ - "content", - "refusal" - ] - } - } - } - }, - "created": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the chat completion was created." - }, - "model": { - "type": "string", - "description": "The model used for the chat completion." - }, - "service_tier": { - "$ref": "#/components/schemas/ServiceTier" - }, - "system_fingerprint": { - "type": "string", - "deprecated": true, - "description": "This fingerprint represents the backend configuration that the model runs with.\n\nCan be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.\n" - }, - "object": { - "type": "string", - "description": "The object type, which is always `chat.completion`.", - "enum": [ - "chat.completion" - ], - "x-stainless-const": true - }, - "usage": { - "$ref": "#/components/schemas/CompletionUsage" - } - }, - "required": [ - "choices", - "created", - "id", - "model", - "object" - ], - "x-oaiMeta": { - "name": "The chat completion object", - "group": "chat", - "example": "{\n \"id\": \"chatcmpl-B9MHDbslfkBeAs8l4bebGdFOJ6PeG\",\n \"object\": \"chat.completion\",\n \"created\": 1741570283,\n \"model\": \"gpt-4o-2024-08-06\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"The image shows a wooden boardwalk path running through a lush green field or meadow. The sky is bright blue with some scattered clouds, giving the scene a serene and peaceful atmosphere. Trees and shrubs are visible in the background.\",\n \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 1117,\n \"completion_tokens\": 46,\n \"total_tokens\": 1163,\n \"prompt_tokens_details\": {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": \"default\",\n \"system_fingerprint\": \"fp_fc9f1d7035\"\n}\n" - } - }, - "CreateChatCompletionStreamResponse": { - "type": "object", - "description": "Represents a streamed chunk of a chat completion response returned\nby the model, based on the provided input. \n[Learn more](https://platform.openai.com/docs/guides/streaming-responses).\n", - "properties": { - "id": { - "type": "string", - "description": "A unique identifier for the chat completion. Each chunk has the same ID." - }, - "choices": { - "type": "array", - "description": "A list of chat completion choices. Can contain more than one elements if `n` is greater than 1. Can also be empty for the\nlast chunk if you set `stream_options: {\"include_usage\": true}`.\n", - "items": { - "type": "object", - "required": [ - "delta", - "finish_reason", - "index" - ], - "properties": { - "delta": { - "$ref": "#/components/schemas/ChatCompletionStreamResponseDelta" - }, - "logprobs": { - "description": "Log probability information for the choice.", - "type": "object", - "nullable": true, - "properties": { - "content": { - "description": "A list of message content tokens with log probability information.", - "type": "array", - "items": { - "$ref": "#/components/schemas/ChatCompletionTokenLogprob" - }, - "nullable": true - }, - "refusal": { - "description": "A list of message refusal tokens with log probability information.", - "type": "array", - "items": { - "$ref": "#/components/schemas/ChatCompletionTokenLogprob" - }, - "nullable": true - } - }, - "required": [ - "content", - "refusal" - ] - }, - "finish_reason": { - "type": "string", - "description": "The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence,\n`length` if the maximum number of tokens specified in the request was reached,\n`content_filter` if content was omitted due to a flag from our content filters,\n`tool_calls` if the model called a tool, or `function_call` (deprecated) if the model called a function.\n", - "enum": [ - "stop", - "length", - "tool_calls", - "content_filter", - "function_call" - ], - "nullable": true - }, - "index": { - "type": "integer", - "description": "The index of the choice in the list of choices." - } - } - } - }, - "created": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the chat completion was created. Each chunk has the same timestamp." - }, - "model": { - "type": "string", - "description": "The model to generate the completion." - }, - "service_tier": { - "$ref": "#/components/schemas/ServiceTier" - }, - "system_fingerprint": { - "type": "string", - "deprecated": true, - "description": "This fingerprint represents the backend configuration that the model runs with.\nCan be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.\n" - }, - "object": { - "type": "string", - "description": "The object type, which is always `chat.completion.chunk`.", - "enum": [ - "chat.completion.chunk" - ], - "x-stainless-const": true - }, - "usage": { - "$ref": "#/components/schemas/CompletionUsage", - "nullable": true, - "description": "An optional field that will only be present when you set\n`stream_options: {\"include_usage\": true}` in your request. When present, it\ncontains a null value **except for the last chunk** which contains the\ntoken usage statistics for the entire request.\n\n**NOTE:** If the stream is interrupted or cancelled, you may not\nreceive the final usage chunk which contains the total token usage for\nthe request.\n" - } - }, - "required": [ - "choices", - "created", - "id", - "model", - "object" - ], - "x-oaiMeta": { - "name": "The chat completion chunk object", - "group": "chat", - "example": "{\"id\":\"chatcmpl-123\",\"object\":\"chat.completion.chunk\",\"created\":1694268190,\"model\":\"gpt-4o-mini\", \"system_fingerprint\": \"fp_44709d6fcb\", \"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\"},\"logprobs\":null,\"finish_reason\":null}]}\n\n{\"id\":\"chatcmpl-123\",\"object\":\"chat.completion.chunk\",\"created\":1694268190,\"model\":\"gpt-4o-mini\", \"system_fingerprint\": \"fp_44709d6fcb\", \"choices\":[{\"index\":0,\"delta\":{\"content\":\"Hello\"},\"logprobs\":null,\"finish_reason\":null}]}\n\n....\n\n{\"id\":\"chatcmpl-123\",\"object\":\"chat.completion.chunk\",\"created\":1694268190,\"model\":\"gpt-4o-mini\", \"system_fingerprint\": \"fp_44709d6fcb\", \"choices\":[{\"index\":0,\"delta\":{},\"logprobs\":null,\"finish_reason\":\"stop\"}]}\n" - } - }, - "CreateCompletionRequest": { - "type": "object", - "properties": { - "model": { - "description": "ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models) for descriptions of them.\n", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "gpt-3.5-turbo-instruct", - "davinci-002", - "babbage-002" - ], - "title": "Preset" - } - ], - "x-oaiTypeLabel": "string" - }, - "prompt": { - "description": "The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays.\n\nNote that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document.\n", - "nullable": true, - "anyOf": [ - { - "type": "string", - "default": "", - "example": "This is a test." - }, - { - "type": "array", - "items": { - "type": "string", - "default": "", - "example": "This is a test." - }, - "title": "Array of strings" - }, - { - "type": "array", - "minItems": 1, - "items": { - "type": "integer" - }, - "title": "Array of tokens" - }, - { - "type": "array", - "minItems": 1, - "items": { - "type": "array", - "minItems": 1, - "items": { - "type": "integer" - } - }, - "title": "Array of token arrays" - } - ] - }, - "best_of": { - "type": "integer", - "default": 1, - "minimum": 0, - "maximum": 20, - "nullable": true, - "description": "Generates `best_of` completions server-side and returns the \"best\" (the one with the highest log probability per token). Results cannot be streamed.\n\nWhen used with `n`, `best_of` controls the number of candidate completions and `n` specifies how many to return โ€“ `best_of` must be greater than `n`.\n\n**Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.\n" - }, - "echo": { - "type": "boolean", - "default": false, - "nullable": true, - "description": "Echo back the prompt in addition to the completion\n" - }, - "frequency_penalty": { - "type": "number", - "default": 0, - "minimum": -2, - "maximum": 2, - "nullable": true, - "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.\n\n[See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation)\n" - }, - "logit_bias": { - "type": "object", - "x-oaiTypeLabel": "map", - "default": null, - "nullable": true, - "additionalProperties": { - "type": "integer" - }, - "description": "Modify the likelihood of specified tokens appearing in the completion.\n\nAccepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this [tokenizer tool](/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.\n\nAs an example, you can pass `{\"50256\": -100}` to prevent the <|endoftext|> token from being generated.\n" - }, - "logprobs": { - "type": "integer", - "minimum": 0, - "maximum": 5, - "default": null, - "nullable": true, - "description": "Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens. The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1` elements in the response.\n\nThe maximum value for `logprobs` is 5.\n" - }, - "max_tokens": { - "type": "integer", - "minimum": 0, - "default": 16, - "example": 16, - "nullable": true, - "description": "The maximum number of [tokens](/tokenizer) that can be generated in the completion.\n\nThe token count of your prompt plus `max_tokens` cannot exceed the model's context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.\n" - }, - "n": { - "type": "integer", - "minimum": 1, - "maximum": 128, - "default": 1, - "example": 1, - "nullable": true, - "description": "How many completions to generate for each prompt.\n\n**Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.\n" - }, - "presence_penalty": { - "type": "number", - "default": 0, - "minimum": -2, - "maximum": 2, - "nullable": true, - "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.\n\n[See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation)\n" - }, - "seed": { - "type": "integer", - "format": "int64", - "nullable": true, - "description": "If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result.\n\nDeterminism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend.\n" - }, - "stop": { - "$ref": "#/components/schemas/StopConfiguration" - }, - "stream": { - "description": "Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions).\n", - "type": "boolean", - "nullable": true, - "default": false - }, - "stream_options": { - "$ref": "#/components/schemas/ChatCompletionStreamOptions" - }, - "suffix": { - "description": "The suffix that comes after a completion of inserted text.\n\nThis parameter is only supported for `gpt-3.5-turbo-instruct`.\n", - "default": null, - "nullable": true, - "type": "string", - "example": "test." - }, - "temperature": { - "type": "number", - "minimum": 0, - "maximum": 2, - "default": 1, - "example": 1, - "nullable": true, - "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n\nWe generally recommend altering this or `top_p` but not both.\n" - }, - "top_p": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 1, - "example": 1, - "nullable": true, - "description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or `temperature` but not both.\n" - }, - "user": { - "type": "string", - "example": "user-1234", - "description": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).\n" - } - }, - "required": [ - "model", - "prompt" - ] - }, - "CreateCompletionResponse": { - "type": "object", - "description": "Represents a completion response from the API. Note: both the streamed and non-streamed response objects share the same shape (unlike the chat endpoint).\n", - "properties": { - "id": { - "type": "string", - "description": "A unique identifier for the completion." - }, - "choices": { - "type": "array", - "description": "The list of completion choices the model generated for the input prompt.", - "items": { - "type": "object", - "required": [ - "finish_reason", - "index", - "logprobs", - "text" - ], - "properties": { - "finish_reason": { - "type": "string", - "description": "The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence,\n`length` if the maximum number of tokens specified in the request was reached,\nor `content_filter` if content was omitted due to a flag from our content filters.\n", - "enum": [ - "stop", - "length", - "content_filter" - ] - }, - "index": { - "type": "integer" - }, - "logprobs": { - "type": "object", - "nullable": true, - "properties": { - "text_offset": { - "type": "array", - "items": { - "type": "integer" - } - }, - "token_logprobs": { - "type": "array", - "items": { - "type": "number" - } - }, - "tokens": { - "type": "array", - "items": { - "type": "string" - } - }, - "top_logprobs": { - "type": "array", - "items": { - "type": "object", - "additionalProperties": { - "type": "number" - } - } - } - } - }, - "text": { - "type": "string" - } - } - } - }, - "created": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the completion was created." - }, - "model": { - "type": "string", - "description": "The model used for completion." - }, - "system_fingerprint": { - "type": "string", - "description": "This fingerprint represents the backend configuration that the model runs with.\n\nCan be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.\n" - }, - "object": { - "type": "string", - "description": "The object type, which is always \"text_completion\"", - "enum": [ - "text_completion" - ], - "x-stainless-const": true - }, - "usage": { - "$ref": "#/components/schemas/CompletionUsage" - } - }, - "required": [ - "id", - "object", - "created", - "model", - "choices" - ], - "x-oaiMeta": { - "name": "The completion object", - "legacy": true, - "example": "{\n \"id\": \"cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7\",\n \"object\": \"text_completion\",\n \"created\": 1589478378,\n \"model\": \"gpt-4-turbo\",\n \"choices\": [\n {\n \"text\": \"\\n\\nThis is indeed a test\",\n \"index\": 0,\n \"logprobs\": null,\n \"finish_reason\": \"length\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 5,\n \"completion_tokens\": 7,\n \"total_tokens\": 12\n }\n}\n" - } - }, - "CreateContainerBody": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "Name of the container to create." - }, - "file_ids": { - "type": "array", - "description": "IDs of files to copy to the container.", - "items": { - "type": "string" - } - }, - "expires_after": { - "type": "object", - "description": "Container expiration time in seconds relative to the 'anchor' time.", - "properties": { - "anchor": { - "type": "string", - "enum": [ - "last_active_at" - ], - "description": "Time anchor for the expiration time. Currently only 'last_active_at' is supported." - }, - "minutes": { - "type": "integer" - } - }, - "required": [ - "anchor", - "minutes" - ] - } - }, - "required": [ - "name" - ] - }, - "CreateContainerFileBody": { - "type": "object", - "properties": { - "file_id": { - "type": "string", - "description": "Name of the file to create." - }, - "file": { - "description": "The File object (not file name) to be uploaded.\n", - "type": "string", - "format": "binary" - } - }, - "required": [] - }, - "CreateConversationRequest": { - "type": "object", - "description": "Create a conversation", - "properties": { - "metadata": { - "$ref": "#/components/schemas/Metadata", - "description": "Set of 16 key-value pairs that can be attached to an object. Useful for\nstoring additional information about the object in a structured format.\n" - }, - "items": { - "type": "array", - "description": "Initial items to include in the conversation context.\nYou may add up to 20 items at a time.\n", - "items": { - "$ref": "#/components/schemas/InputItem" - }, - "nullable": true, - "maxItems": 20 - } - }, - "required": [] - }, - "CreateEmbeddingRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "input": { - "description": "Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for all embedding models), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens. In addition to the per-input token limit, all embedding models enforce a maximum of 300,000 tokens summed across all inputs in a single request.\n", - "example": "The quick brown fox jumped over the lazy dog", - "anyOf": [ - { - "type": "string", - "title": "string", - "description": "The string that will be turned into an embedding.", - "default": "", - "example": "This is a test." - }, - { - "type": "array", - "title": "Array of strings", - "description": "The array of strings that will be turned into an embedding.", - "minItems": 1, - "maxItems": 2048, - "items": { - "type": "string", - "default": "", - "example": "['This is a test.']" - } - }, - { - "type": "array", - "title": "Array of tokens", - "description": "The array of integers that will be turned into an embedding.", - "minItems": 1, - "maxItems": 2048, - "items": { - "type": "integer" - } - }, - { - "type": "array", - "title": "Array of token arrays", - "description": "The array of arrays containing integers that will be turned into an embedding.", - "minItems": 1, - "maxItems": 2048, - "items": { - "type": "array", - "minItems": 1, - "items": { - "type": "integer" - } - } - } - ] - }, - "model": { - "description": "ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models) for descriptions of them.\n", - "example": "text-embedding-3-small", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "text-embedding-ada-002", - "text-embedding-3-small", - "text-embedding-3-large" - ], - "x-stainless-nominal": false - } - ], - "x-oaiTypeLabel": "string" - }, - "encoding_format": { - "description": "The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).", - "example": "float", - "default": "float", - "type": "string", - "enum": [ - "float", - "base64" - ] - }, - "dimensions": { - "description": "The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.\n", - "type": "integer", - "minimum": 1 - }, - "user": { - "type": "string", - "example": "user-1234", - "description": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).\n" - } - }, - "required": [ - "model", - "input" - ] - }, - "CreateEmbeddingResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "description": "The list of embeddings generated by the model.", - "items": { - "$ref": "#/components/schemas/Embedding" - } - }, - "model": { - "type": "string", - "description": "The name of the model used to generate the embedding." - }, - "object": { - "type": "string", - "description": "The object type, which is always \"list\".", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "usage": { - "type": "object", - "description": "The usage information for the request.", - "properties": { - "prompt_tokens": { - "type": "integer", - "description": "The number of tokens used by the prompt." - }, - "total_tokens": { - "type": "integer", - "description": "The total number of tokens used by the request." - } - }, - "required": [ - "prompt_tokens", - "total_tokens" - ] - } - }, - "required": [ - "object", - "model", - "data", - "usage" - ] - }, - "CreateEvalCompletionsRunDataSource": { - "type": "object", - "title": "CompletionsRunDataSource", - "description": "A CompletionsRunDataSource object describing a model sampling configuration.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "completions" - ], - "default": "completions", - "description": "The type of run data source. Always `completions`." - }, - "input_messages": { - "description": "Used when sampling from a model. Dictates the structure of the messages passed into the model. Can either be a reference to a prebuilt trajectory (ie, `item.input_trajectory`), or a template with variable references to the `item` namespace.", - "anyOf": [ - { - "type": "object", - "title": "TemplateInputMessages", - "properties": { - "type": { - "type": "string", - "enum": [ - "template" - ], - "description": "The type of input messages. Always `template`." - }, - "template": { - "type": "array", - "description": "A list of chat messages forming the prompt or context. May include variable references to the `item` namespace, ie {{item.name}}.", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/EasyInputMessage" - }, - { - "$ref": "#/components/schemas/EvalItem" - } - ] - } - } - }, - "required": [ - "type", - "template" - ] - }, - { - "type": "object", - "title": "ItemReferenceInputMessages", - "properties": { - "type": { - "type": "string", - "enum": [ - "item_reference" - ], - "description": "The type of input messages. Always `item_reference`." - }, - "item_reference": { - "type": "string", - "description": "A reference to a variable in the `item` namespace. Ie, \"item.input_trajectory\"" - } - }, - "required": [ - "type", - "item_reference" - ] - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "sampling_params": { - "type": "object", - "properties": { - "temperature": { - "type": "number", - "description": "A higher temperature increases randomness in the outputs.", - "default": 1 - }, - "max_completion_tokens": { - "type": "integer", - "description": "The maximum number of tokens in the generated output." - }, - "top_p": { - "type": "number", - "description": "An alternative to temperature for nucleus sampling; 1.0 includes all tokens.", - "default": 1 - }, - "seed": { - "type": "integer", - "description": "A seed value to initialize the randomness, during sampling.", - "default": 42 - }, - "response_format": { - "description": "An object specifying the format that the model must output.\n\nSetting to `{ \"type\": \"json_schema\", \"json_schema\": {...} }` enables\nStructured Outputs which ensures the model will match your supplied JSON\nschema. Learn more in the [Structured Outputs\nguide](https://platform.openai.com/docs/guides/structured-outputs).\n\nSetting to `{ \"type\": \"json_object\" }` enables the older JSON mode, which\nensures the message the model generates is valid JSON. Using `json_schema`\nis preferred for models that support it.\n", - "anyOf": [ - { - "$ref": "#/components/schemas/ResponseFormatText" - }, - { - "$ref": "#/components/schemas/ResponseFormatJsonSchema" - }, - { - "$ref": "#/components/schemas/ResponseFormatJsonObject" - } - ] - }, - "tools": { - "type": "array", - "description": "A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.\n", - "items": { - "$ref": "#/components/schemas/ChatCompletionTool" - } - } - } - }, - "model": { - "type": "string", - "description": "The name of the model to use for generating completions (e.g. \"o3-mini\")." - }, - "source": { - "description": "Determines what populates the `item` namespace in this run's data source.", - "anyOf": [ - { - "$ref": "#/components/schemas/EvalJsonlFileContentSource" - }, - { - "$ref": "#/components/schemas/EvalJsonlFileIdSource" - }, - { - "$ref": "#/components/schemas/EvalStoredCompletionsSource" - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "required": [ - "type", - "source" - ], - "x-oaiMeta": { - "name": "The completions data source object used to configure an individual run", - "group": "eval runs", - "example": "{\n \"name\": \"gpt-4o-mini-2024-07-18\",\n \"data_source\": {\n \"type\": \"completions\",\n \"input_messages\": {\n \"type\": \"item_reference\",\n \"item_reference\": \"item.input\"\n },\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"source\": {\n \"type\": \"stored_completions\",\n \"model\": \"gpt-4o-mini-2024-07-18\"\n }\n }\n}\n" - } - }, - "CreateEvalCustomDataSourceConfig": { - "type": "object", - "title": "CustomDataSourceConfig", - "description": "A CustomDataSourceConfig object that defines the schema for the data source used for the evaluation runs.\nThis schema is used to define the shape of the data that will be:\n- Used to define your testing criteria and\n- What data is required when creating a run\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "custom" - ], - "default": "custom", - "description": "The type of data source. Always `custom`.", - "x-stainless-const": true - }, - "item_schema": { - "type": "object", - "description": "The json schema for each row in the data source.", - "additionalProperties": true - }, - "include_sample_schema": { - "type": "boolean", - "default": false, - "description": "Whether the eval should expect you to populate the sample namespace (ie, by generating responses off of your data source)" - } - }, - "required": [ - "item_schema", - "type" - ], - "x-oaiMeta": { - "name": "The eval file data source config object", - "group": "evals", - "example": "{\n \"type\": \"custom\",\n \"item_schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\"type\": \"string\"},\n \"age\": {\"type\": \"integer\"}\n },\n \"required\": [\"name\", \"age\"]\n },\n \"include_sample_schema\": true\n}\n" - } - }, - "CreateEvalItem": { - "title": "CreateEvalItem", - "description": "A chat message that makes up the prompt or context. May include variable references to the `item` namespace, ie {{item.name}}.", - "type": "object", - "x-oaiMeta": { - "name": "The chat message object used to configure an individual run" - }, - "anyOf": [ - { - "type": "object", - "title": "SimpleInputMessage", - "properties": { - "role": { - "type": "string", - "description": "The role of the message (e.g. \"system\", \"assistant\", \"user\")." - }, - "content": { - "type": "string", - "description": "The content of the message." - } - }, - "required": [ - "role", - "content" - ] - }, - { - "$ref": "#/components/schemas/EvalItem" - } - ] - }, - "CreateEvalJsonlRunDataSource": { - "type": "object", - "title": "JsonlRunDataSource", - "description": "A JsonlRunDataSource object with that specifies a JSONL file that matches the eval\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "jsonl" - ], - "default": "jsonl", - "description": "The type of data source. Always `jsonl`.", - "x-stainless-const": true - }, - "source": { - "description": "Determines what populates the `item` namespace in the data source.", - "anyOf": [ - { - "$ref": "#/components/schemas/EvalJsonlFileContentSource" - }, - { - "$ref": "#/components/schemas/EvalJsonlFileIdSource" - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "required": [ - "type", - "source" - ], - "x-oaiMeta": { - "name": "The file data source object for the eval run configuration", - "group": "evals", - "example": "{\n \"type\": \"jsonl\",\n \"source\": {\n \"type\": \"file_id\",\n \"id\": \"file-9GYS6xbkWgWhmE7VoLUWFg\"\n }\n}\n" - } - }, - "CreateEvalLabelModelGrader": { - "type": "object", - "title": "LabelModelGrader", - "description": "A LabelModelGrader object which uses a model to assign labels to each item\nin the evaluation.\n", - "properties": { - "type": { - "description": "The object type, which is always `label_model`.", - "type": "string", - "enum": [ - "label_model" - ], - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the grader." - }, - "model": { - "type": "string", - "description": "The model to use for the evaluation. Must support structured outputs." - }, - "input": { - "type": "array", - "description": "A list of chat messages forming the prompt or context. May include variable references to the `item` namespace, ie {{item.name}}.", - "items": { - "$ref": "#/components/schemas/CreateEvalItem" - } - }, - "labels": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The labels to classify to each item in the evaluation." - }, - "passing_labels": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The labels that indicate a passing result. Must be a subset of labels." - } - }, - "required": [ - "type", - "model", - "input", - "passing_labels", - "labels", - "name" - ], - "x-oaiMeta": { - "name": "The eval label model grader object", - "group": "evals", - "example": "{\n \"type\": \"label_model\",\n \"model\": \"gpt-4o-2024-08-06\",\n \"input\": [\n {\n \"role\": \"system\",\n \"content\": \"Classify the sentiment of the following statement as one of 'positive', 'neutral', or 'negative'\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Statement: {{item.response}}\"\n }\n ],\n \"passing_labels\": [\"positive\"],\n \"labels\": [\"positive\", \"neutral\", \"negative\"],\n \"name\": \"Sentiment label grader\"\n}\n" - } - }, - "CreateEvalLogsDataSourceConfig": { - "type": "object", - "title": "LogsDataSourceConfig", - "description": "A data source config which specifies the metadata property of your logs query.\nThis is usually metadata like `usecase=chatbot` or `prompt-version=v2`, etc.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "logs" - ], - "default": "logs", - "description": "The type of data source. Always `logs`.", - "x-stainless-const": true - }, - "metadata": { - "type": "object", - "description": "Metadata filters for the logs data source.", - "additionalProperties": true - } - }, - "required": [ - "type" - ], - "x-oaiMeta": { - "name": "The logs data source object for evals", - "group": "evals", - "example": "{\n \"type\": \"logs\",\n \"metadata\": {\n \"use_case\": \"customer_support_agent\"\n }\n}\n" - } - }, - "CreateEvalRequest": { - "type": "object", - "title": "CreateEvalRequest", - "properties": { - "name": { - "type": "string", - "description": "The name of the evaluation." - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "data_source_config": { - "type": "object", - "description": "The configuration for the data source used for the evaluation runs. Dictates the schema of the data used in the evaluation.", - "anyOf": [ - { - "$ref": "#/components/schemas/CreateEvalCustomDataSourceConfig" - }, - { - "$ref": "#/components/schemas/CreateEvalLogsDataSourceConfig" - }, - { - "$ref": "#/components/schemas/CreateEvalStoredCompletionsDataSourceConfig" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "testing_criteria": { - "type": "array", - "description": "A list of graders for all eval runs in this group. Graders can reference variables in the data source using double curly braces notation, like `{{item.variable_name}}`. To reference the model's output, use the `sample` namespace (ie, `{{sample.output_text}}`).", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/CreateEvalLabelModelGrader" - }, - { - "$ref": "#/components/schemas/EvalGraderStringCheck" - }, - { - "$ref": "#/components/schemas/EvalGraderTextSimilarity" - }, - { - "$ref": "#/components/schemas/EvalGraderPython" - }, - { - "$ref": "#/components/schemas/EvalGraderScoreModel" - } - ], - "discriminator": { - "propertyName": "type" - } - } - } - }, - "required": [ - "data_source_config", - "testing_criteria" - ] - }, - "CreateEvalResponsesRunDataSource": { - "type": "object", - "title": "ResponsesRunDataSource", - "description": "A ResponsesRunDataSource object describing a model sampling configuration.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "responses" - ], - "default": "responses", - "description": "The type of run data source. Always `responses`." - }, - "input_messages": { - "description": "Used when sampling from a model. Dictates the structure of the messages passed into the model. Can either be a reference to a prebuilt trajectory (ie, `item.input_trajectory`), or a template with variable references to the `item` namespace.", - "anyOf": [ - { - "type": "object", - "title": "InputMessagesTemplate", - "properties": { - "type": { - "type": "string", - "enum": [ - "template" - ], - "description": "The type of input messages. Always `template`." - }, - "template": { - "type": "array", - "description": "A list of chat messages forming the prompt or context. May include variable references to the `item` namespace, ie {{item.name}}.", - "items": { - "anyOf": [ - { - "type": "object", - "title": "ChatMessage", - "properties": { - "role": { - "type": "string", - "description": "The role of the message (e.g. \"system\", \"assistant\", \"user\")." - }, - "content": { - "type": "string", - "description": "The content of the message." - } - }, - "required": [ - "role", - "content" - ] - }, - { - "$ref": "#/components/schemas/EvalItem" - } - ] - } - } - }, - "required": [ - "type", - "template" - ] - }, - { - "type": "object", - "title": "InputMessagesItemReference", - "properties": { - "type": { - "type": "string", - "enum": [ - "item_reference" - ], - "description": "The type of input messages. Always `item_reference`." - }, - "item_reference": { - "type": "string", - "description": "A reference to a variable in the `item` namespace. Ie, \"item.name\"" - } - }, - "required": [ - "type", - "item_reference" - ] - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "sampling_params": { - "type": "object", - "properties": { - "temperature": { - "type": "number", - "description": "A higher temperature increases randomness in the outputs.", - "default": 1 - }, - "max_completion_tokens": { - "type": "integer", - "description": "The maximum number of tokens in the generated output." - }, - "top_p": { - "type": "number", - "description": "An alternative to temperature for nucleus sampling; 1.0 includes all tokens.", - "default": 1 - }, - "seed": { - "type": "integer", - "description": "A seed value to initialize the randomness, during sampling.", - "default": 42 - }, - "tools": { - "type": "array", - "description": "An array of tools the model may call while generating a response. You\ncan specify which tool to use by setting the `tool_choice` parameter.\n\nThe two categories of tools you can provide the model are:\n\n- **Built-in tools**: Tools that are provided by OpenAI that extend the\n model's capabilities, like [web search](https://platform.openai.com/docs/guides/tools-web-search)\n or [file search](https://platform.openai.com/docs/guides/tools-file-search). Learn more about\n [built-in tools](https://platform.openai.com/docs/guides/tools).\n- **Function calls (custom tools)**: Functions that are defined by you,\n enabling the model to call your own code. Learn more about\n [function calling](https://platform.openai.com/docs/guides/function-calling).\n", - "items": { - "$ref": "#/components/schemas/Tool" - } - }, - "text": { - "type": "object", - "description": "Configuration options for a text response from the model. Can be plain\ntext or structured JSON data. Learn more:\n- [Text inputs and outputs](https://platform.openai.com/docs/guides/text)\n- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs)\n", - "properties": { - "format": { - "$ref": "#/components/schemas/TextResponseFormatConfiguration" - } - } - } - } - }, - "model": { - "type": "string", - "description": "The name of the model to use for generating completions (e.g. \"o3-mini\")." - }, - "source": { - "description": "Determines what populates the `item` namespace in this run's data source.", - "anyOf": [ - { - "$ref": "#/components/schemas/EvalJsonlFileContentSource" - }, - { - "$ref": "#/components/schemas/EvalJsonlFileIdSource" - }, - { - "$ref": "#/components/schemas/EvalResponsesSource" - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "required": [ - "type", - "source" - ], - "x-oaiMeta": { - "name": "The completions data source object used to configure an individual run", - "group": "eval runs", - "example": "{\n \"name\": \"gpt-4o-mini-2024-07-18\",\n \"data_source\": {\n \"type\": \"responses\",\n \"input_messages\": {\n \"type\": \"item_reference\",\n \"item_reference\": \"item.input\"\n },\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"source\": {\n \"type\": \"responses\",\n \"model\": \"gpt-4o-mini-2024-07-18\"\n }\n }\n}\n" - } - }, - "CreateEvalRunRequest": { - "type": "object", - "title": "CreateEvalRunRequest", - "properties": { - "name": { - "type": "string", - "description": "The name of the run." - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "data_source": { - "type": "object", - "description": "Details about the run's data source.", - "anyOf": [ - { - "$ref": "#/components/schemas/CreateEvalJsonlRunDataSource" - }, - { - "$ref": "#/components/schemas/CreateEvalCompletionsRunDataSource" - }, - { - "$ref": "#/components/schemas/CreateEvalResponsesRunDataSource" - } - ] - } - }, - "required": [ - "data_source" - ] - }, - "CreateEvalStoredCompletionsDataSourceConfig": { - "type": "object", - "title": "StoredCompletionsDataSourceConfig", - "description": "Deprecated in favor of LogsDataSourceConfig.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "stored_completions" - ], - "default": "stored_completions", - "description": "The type of data source. Always `stored_completions`.", - "x-stainless-const": true - }, - "metadata": { - "type": "object", - "description": "Metadata filters for the stored completions data source.", - "additionalProperties": true - } - }, - "required": [ - "type" - ], - "deprecated": true, - "x-oaiMeta": { - "name": "The stored completions data source object for evals", - "group": "evals", - "example": "{\n \"type\": \"stored_completions\",\n \"metadata\": {\n \"use_case\": \"customer_support_agent\"\n }\n}\n" - } - }, - "CreateFileRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "file": { - "description": "The File object (not file name) to be uploaded.\n", - "type": "string", - "format": "binary", - "x-oaiMeta": { - "exampleFilePath": "fine-tune.jsonl" - } - }, - "purpose": { - "$ref": "#/components/schemas/FilePurpose" - }, - "expires_after": { - "$ref": "#/components/schemas/FileExpirationAfter" - } - }, - "required": [ - "file", - "purpose" - ] - }, - "CreateFineTuningCheckpointPermissionRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "project_ids": { - "type": "array", - "description": "The project identifiers to grant access to.", - "items": { - "type": "string" - } - } - }, - "required": [ - "project_ids" - ] - }, - "CreateFineTuningJobRequest": { - "type": "object", - "properties": { - "model": { - "description": "The name of the model to fine-tune. You can select one of the\n[supported models](https://platform.openai.com/docs/guides/fine-tuning#which-models-can-be-fine-tuned).\n", - "example": "gpt-4o-mini", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "babbage-002", - "davinci-002", - "gpt-3.5-turbo", - "gpt-4o-mini" - ], - "title": "Preset" - } - ], - "x-oaiTypeLabel": "string" - }, - "training_file": { - "description": "The ID of an uploaded file that contains training data.\n\nSee [upload file](https://platform.openai.com/docs/api-reference/files/create) for how to upload a file.\n\nYour dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose `fine-tune`.\n\nThe contents of the file should differ depending on if the model uses the [chat](https://platform.openai.com/docs/api-reference/fine-tuning/chat-input), [completions](https://platform.openai.com/docs/api-reference/fine-tuning/completions-input) format, or if the fine-tuning method uses the [preference](https://platform.openai.com/docs/api-reference/fine-tuning/preference-input) format.\n\nSee the [fine-tuning guide](https://platform.openai.com/docs/guides/model-optimization) for more details.\n", - "type": "string", - "example": "file-abc123" - }, - "hyperparameters": { - "type": "object", - "description": "The hyperparameters used for the fine-tuning job.\nThis value is now deprecated in favor of `method`, and should be passed in under the `method` parameter.\n", - "properties": { - "batch_size": { - "description": "Number of examples in each batch. A larger batch size means that model parameters\nare updated less frequently, but with lower variance.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true, - "title": "Auto" - }, - { - "type": "integer", - "minimum": 1, - "maximum": 256 - } - ] - }, - "learning_rate_multiplier": { - "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid\noverfitting.\n", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true, - "title": "Auto" - }, - { - "type": "number", - "minimum": 0, - "exclusiveMinimum": true - } - ] - }, - "n_epochs": { - "description": "The number of epochs to train the model for. An epoch refers to one full cycle\nthrough the training dataset.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true, - "title": "Auto" - }, - { - "type": "integer", - "minimum": 1, - "maximum": 50 - } - ] - } - }, - "deprecated": true - }, - "suffix": { - "description": "A string of up to 64 characters that will be added to your fine-tuned model name.\n\nFor example, a `suffix` of \"custom-model-name\" would produce a model name like `ft:gpt-4o-mini:openai:custom-model-name:7p4lURel`.\n", - "type": "string", - "minLength": 1, - "maxLength": 64, - "default": null, - "nullable": true - }, - "validation_file": { - "description": "The ID of an uploaded file that contains validation data.\n\nIf you provide this file, the data is used to generate validation\nmetrics periodically during fine-tuning. These metrics can be viewed in\nthe fine-tuning results file.\nThe same data should not be present in both train and validation files.\n\nYour dataset must be formatted as a JSONL file. You must upload your file with the purpose `fine-tune`.\n\nSee the [fine-tuning guide](https://platform.openai.com/docs/guides/model-optimization) for more details.\n", - "type": "string", - "nullable": true, - "example": "file-abc123" - }, - "integrations": { - "type": "array", - "description": "A list of integrations to enable for your fine-tuning job.", - "nullable": true, - "items": { - "type": "object", - "required": [ - "type", - "wandb" - ], - "properties": { - "type": { - "description": "The type of integration to enable. Currently, only \"wandb\" (Weights and Biases) is supported.\n", - "anyOf": [ - { - "type": "string", - "enum": [ - "wandb" - ], - "x-stainless-const": true - } - ] - }, - "wandb": { - "type": "object", - "description": "The settings for your integration with Weights and Biases. This payload specifies the project that\nmetrics will be sent to. Optionally, you can set an explicit display name for your run, add tags\nto your run, and set a default entity (team, username, etc) to be associated with your run.\n", - "required": [ - "project" - ], - "properties": { - "project": { - "description": "The name of the project that the new run will be created under.\n", - "type": "string", - "example": "my-wandb-project" - }, - "name": { - "description": "A display name to set for the run. If not set, we will use the Job ID as the name.\n", - "nullable": true, - "type": "string" - }, - "entity": { - "description": "The entity to use for the run. This allows you to set the team or username of the WandB user that you would\nlike associated with the run. If not set, the default entity for the registered WandB API key is used.\n", - "nullable": true, - "type": "string" - }, - "tags": { - "description": "A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some\ndefault tags are generated by OpenAI: \"openai/finetune\", \"openai/{base-model}\", \"openai/{ftjob-abcdef}\".\n", - "type": "array", - "items": { - "type": "string", - "example": "custom-tag" - } - } - } - } - } - } - }, - "seed": { - "description": "The seed controls the reproducibility of the job. Passing in the same seed and job parameters should produce the same results, but may differ in rare cases.\nIf a seed is not specified, one will be generated for you.\n", - "type": "integer", - "nullable": true, - "minimum": 0, - "maximum": 2147483647, - "example": 42 - }, - "method": { - "$ref": "#/components/schemas/FineTuneMethod" - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - }, - "required": [ - "model", - "training_file" - ] - }, - "CreateImageEditRequest": { - "type": "object", - "properties": { - "image": { - "anyOf": [ - { - "type": "string", - "format": "binary" - }, - { - "type": "array", - "maxItems": 16, - "items": { - "type": "string", - "format": "binary" - } - } - ], - "description": "The image(s) to edit. Must be a supported image file or an array of images.\n\nFor `gpt-image-1`, each image should be a `png`, `webp`, or `jpg` file less \nthan 50MB. You can provide up to 16 images.\n\nFor `dall-e-2`, you can only provide one image, and it should be a square \n`png` file less than 4MB.\n", - "x-oaiMeta": { - "exampleFilePath": "otter.png" - } - }, - "prompt": { - "description": "A text description of the desired image(s). The maximum length is 1000 characters for `dall-e-2`, and 32000 characters for `gpt-image-1`.", - "type": "string", - "example": "A cute baby sea otter wearing a beret" - }, - "mask": { - "description": "An additional image whose fully transparent areas (e.g. where alpha is zero) indicate where `image` should be edited. If there are multiple images provided, the mask will be applied on the first image. Must be a valid PNG file, less than 4MB, and have the same dimensions as `image`.", - "type": "string", - "format": "binary", - "x-oaiMeta": { - "exampleFilePath": "mask.png" - } - }, - "background": { - "type": "string", - "enum": [ - "transparent", - "opaque", - "auto" - ], - "default": "auto", - "example": "transparent", - "nullable": true, - "description": "Allows to set transparency for the background of the generated image(s). \nThis parameter is only supported for `gpt-image-1`. Must be one of \n`transparent`, `opaque` or `auto` (default value). When `auto` is used, the \nmodel will automatically determine the best background for the image.\n\nIf `transparent`, the output format needs to support transparency, so it \nshould be set to either `png` (default value) or `webp`.\n" - }, - "model": { - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "dall-e-2", - "gpt-image-1" - ], - "x-stainless-const": true - } - ], - "x-oaiTypeLabel": "string", - "nullable": true, - "description": "The model to use for image generation. Only `dall-e-2` and `gpt-image-1` are supported. Defaults to `dall-e-2` unless a parameter specific to `gpt-image-1` is used." - }, - "n": { - "type": "integer", - "minimum": 1, - "maximum": 10, - "default": 1, - "example": 1, - "nullable": true, - "description": "The number of images to generate. Must be between 1 and 10." - }, - "size": { - "type": "string", - "enum": [ - "256x256", - "512x512", - "1024x1024", - "1536x1024", - "1024x1536", - "auto" - ], - "default": "1024x1024", - "example": "1024x1024", - "nullable": true, - "description": "The size of the generated images. Must be one of `1024x1024`, `1536x1024` (landscape), `1024x1536` (portrait), or `auto` (default value) for `gpt-image-1`, and one of `256x256`, `512x512`, or `1024x1024` for `dall-e-2`." - }, - "response_format": { - "type": "string", - "enum": [ - "url", - "b64_json" - ], - "default": "url", - "example": "url", - "nullable": true, - "description": "The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs are only valid for 60 minutes after the image has been generated. This parameter is only supported for `dall-e-2`, as `gpt-image-1` will always return base64-encoded images." - }, - "output_format": { - "type": "string", - "enum": [ - "png", - "jpeg", - "webp" - ], - "default": "png", - "example": "png", - "nullable": true, - "description": "The format in which the generated images are returned. This parameter is\nonly supported for `gpt-image-1`. Must be one of `png`, `jpeg`, or `webp`.\nThe default value is `png`.\n" - }, - "output_compression": { - "type": "integer", - "default": 100, - "example": 100, - "nullable": true, - "description": "The compression level (0-100%) for the generated images. This parameter \nis only supported for `gpt-image-1` with the `webp` or `jpeg` output \nformats, and defaults to 100.\n" - }, - "user": { - "type": "string", - "example": "user-1234", - "description": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).\n" - }, - "input_fidelity": { - "$ref": "#/components/schemas/ImageInputFidelity" - }, - "stream": { - "type": "boolean", - "default": false, - "example": false, - "nullable": true, - "description": "Edit the image in streaming mode. Defaults to `false`. See the\n[Image generation guide](https://platform.openai.com/docs/guides/image-generation) for more information.\n" - }, - "partial_images": { - "$ref": "#/components/schemas/PartialImages" - }, - "quality": { - "type": "string", - "enum": [ - "standard", - "low", - "medium", - "high", - "auto" - ], - "default": "auto", - "example": "high", - "nullable": true, - "description": "The quality of the image that will be generated. `high`, `medium` and `low` are only supported for `gpt-image-1`. `dall-e-2` only supports `standard` quality. Defaults to `auto`.\n" - } - }, - "required": [ - "prompt", - "image" - ] - }, - "CreateImageRequest": { - "type": "object", - "properties": { - "prompt": { - "description": "A text description of the desired image(s). The maximum length is 32000 characters for `gpt-image-1`, 1000 characters for `dall-e-2` and 4000 characters for `dall-e-3`.", - "type": "string", - "example": "A cute baby sea otter" - }, - "model": { - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "dall-e-2", - "dall-e-3", - "gpt-image-1" - ], - "x-stainless-nominal": false - } - ], - "x-oaiTypeLabel": "string", - "nullable": true, - "description": "The model to use for image generation. One of `dall-e-2`, `dall-e-3`, or `gpt-image-1`. Defaults to `dall-e-2` unless a parameter specific to `gpt-image-1` is used." - }, - "n": { - "type": "integer", - "minimum": 1, - "maximum": 10, - "default": 1, - "example": 1, - "nullable": true, - "description": "The number of images to generate. Must be between 1 and 10. For `dall-e-3`, only `n=1` is supported." - }, - "quality": { - "type": "string", - "enum": [ - "standard", - "hd", - "low", - "medium", - "high", - "auto" - ], - "default": "auto", - "example": "medium", - "nullable": true, - "description": "The quality of the image that will be generated. \n\n- `auto` (default value) will automatically select the best quality for the given model.\n- `high`, `medium` and `low` are supported for `gpt-image-1`.\n- `hd` and `standard` are supported for `dall-e-3`.\n- `standard` is the only option for `dall-e-2`.\n" - }, - "response_format": { - "type": "string", - "enum": [ - "url", - "b64_json" - ], - "default": "url", - "example": "url", - "nullable": true, - "description": "The format in which generated images with `dall-e-2` and `dall-e-3` are returned. Must be one of `url` or `b64_json`. URLs are only valid for 60 minutes after the image has been generated. This parameter isn't supported for `gpt-image-1` which will always return base64-encoded images." - }, - "output_format": { - "type": "string", - "enum": [ - "png", - "jpeg", - "webp" - ], - "default": "png", - "example": "png", - "nullable": true, - "description": "The format in which the generated images are returned. This parameter is only supported for `gpt-image-1`. Must be one of `png`, `jpeg`, or `webp`." - }, - "output_compression": { - "type": "integer", - "default": 100, - "example": 100, - "nullable": true, - "description": "The compression level (0-100%) for the generated images. This parameter is only supported for `gpt-image-1` with the `webp` or `jpeg` output formats, and defaults to 100." - }, - "stream": { - "type": "boolean", - "default": false, - "example": false, - "nullable": true, - "description": "Generate the image in streaming mode. Defaults to `false`. See the\n[Image generation guide](https://platform.openai.com/docs/guides/image-generation) for more information.\nThis parameter is only supported for `gpt-image-1`.\n" - }, - "partial_images": { - "$ref": "#/components/schemas/PartialImages" - }, - "size": { - "type": "string", - "enum": [ - "auto", - "1024x1024", - "1536x1024", - "1024x1536", - "256x256", - "512x512", - "1792x1024", - "1024x1792" - ], - "default": "auto", - "example": "1024x1024", - "nullable": true, - "description": "The size of the generated images. Must be one of `1024x1024`, `1536x1024` (landscape), `1024x1536` (portrait), or `auto` (default value) for `gpt-image-1`, one of `256x256`, `512x512`, or `1024x1024` for `dall-e-2`, and one of `1024x1024`, `1792x1024`, or `1024x1792` for `dall-e-3`." - }, - "moderation": { - "type": "string", - "enum": [ - "low", - "auto" - ], - "default": "auto", - "example": "low", - "nullable": true, - "description": "Control the content-moderation level for images generated by `gpt-image-1`. Must be either `low` for less restrictive filtering or `auto` (default value)." - }, - "background": { - "type": "string", - "enum": [ - "transparent", - "opaque", - "auto" - ], - "default": "auto", - "example": "transparent", - "nullable": true, - "description": "Allows to set transparency for the background of the generated image(s). \nThis parameter is only supported for `gpt-image-1`. Must be one of \n`transparent`, `opaque` or `auto` (default value). When `auto` is used, the \nmodel will automatically determine the best background for the image.\n\nIf `transparent`, the output format needs to support transparency, so it \nshould be set to either `png` (default value) or `webp`.\n" - }, - "style": { - "type": "string", - "enum": [ - "vivid", - "natural" - ], - "default": "vivid", - "example": "vivid", - "nullable": true, - "description": "The style of the generated images. This parameter is only supported for `dall-e-3`. Must be one of `vivid` or `natural`. Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images." - }, - "user": { - "type": "string", - "example": "user-1234", - "description": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).\n" - } - }, - "required": [ - "prompt" - ] - }, - "CreateImageVariationRequest": { - "type": "object", - "properties": { - "image": { - "description": "The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and square.", - "type": "string", - "format": "binary", - "x-oaiMeta": { - "exampleFilePath": "otter.png" - } - }, - "model": { - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "dall-e-2" - ], - "x-stainless-const": true - } - ], - "x-oaiTypeLabel": "string", - "nullable": true, - "description": "The model to use for image generation. Only `dall-e-2` is supported at this time." - }, - "n": { - "type": "integer", - "minimum": 1, - "maximum": 10, - "default": 1, - "example": 1, - "nullable": true, - "description": "The number of images to generate. Must be between 1 and 10." - }, - "response_format": { - "type": "string", - "enum": [ - "url", - "b64_json" - ], - "default": "url", - "example": "url", - "nullable": true, - "description": "The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs are only valid for 60 minutes after the image has been generated." - }, - "size": { - "type": "string", - "enum": [ - "256x256", - "512x512", - "1024x1024" - ], - "default": "1024x1024", - "example": "1024x1024", - "nullable": true, - "description": "The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024`." - }, - "user": { - "type": "string", - "example": "user-1234", - "description": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).\n" - } - }, - "required": [ - "image" - ] - }, - "CreateMessageRequest": { - "type": "object", - "additionalProperties": false, - "required": [ - "role", - "content" - ], - "properties": { - "role": { - "type": "string", - "enum": [ - "user", - "assistant" - ], - "description": "The role of the entity that is creating the message. Allowed values include:\n- `user`: Indicates the message is sent by an actual user and should be used in most cases to represent user-generated messages.\n- `assistant`: Indicates the message is generated by the assistant. Use this value to insert messages from the assistant into the conversation.\n" - }, - "content": { - "anyOf": [ - { - "type": "string", - "description": "The text contents of the message.", - "title": "Text content" - }, - { - "type": "array", - "description": "An array of content parts with a defined type, each can be of type `text` or images can be passed with `image_url` or `image_file`. Image types are only supported on [Vision-compatible models](https://platform.openai.com/docs/models).", - "title": "Array of content parts", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/MessageContentImageFileObject" - }, - { - "$ref": "#/components/schemas/MessageContentImageUrlObject" - }, - { - "$ref": "#/components/schemas/MessageRequestContentTextObject" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "minItems": 1 - } - ] - }, - "attachments": { - "type": "array", - "items": { - "type": "object", - "properties": { - "file_id": { - "type": "string", - "description": "The ID of the file to attach to the message." - }, - "tools": { - "description": "The tools to add this file to.", - "type": "array", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/AssistantToolsCode" - }, - { - "$ref": "#/components/schemas/AssistantToolsFileSearchTypeOnly" - } - ], - "discriminator": { - "propertyName": "type" - } - } - } - } - }, - "description": "A list of files attached to the message, and the tools they should be added to.", - "required": [ - "file_id", - "tools" - ], - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - }, - "CreateModelResponseProperties": { - "allOf": [ - { - "$ref": "#/components/schemas/ModelResponseProperties" - }, - { - "type": "object", - "properties": { - "top_logprobs": { - "description": "An integer between 0 and 20 specifying the number of most likely tokens to\nreturn at each token position, each with an associated log probability.\n", - "type": "integer", - "minimum": 0, - "maximum": 20 - } - } - } - ] - }, - "CreateModerationRequest": { - "type": "object", - "properties": { - "input": { - "description": "Input (or inputs) to classify. Can be a single string, an array of strings, or\nan array of multi-modal input objects similar to other models.\n", - "anyOf": [ - { - "type": "string", - "description": "A string of text to classify for moderation.", - "default": "", - "example": "I want to kill them." - }, - { - "type": "array", - "description": "An array of strings to classify for moderation.", - "items": { - "type": "string", - "default": "", - "example": "I want to kill them." - } - }, - { - "type": "array", - "description": "An array of multi-modal inputs to the moderation model.", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ModerationImageURLInput" - }, - { - "$ref": "#/components/schemas/ModerationTextInput" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "title": "Moderation Multi Modal Array" - } - ] - }, - "model": { - "description": "The content moderation model you would like to use. Learn more in\n[the moderation guide](https://platform.openai.com/docs/guides/moderation), and learn about\navailable models [here](https://platform.openai.com/docs/models#moderation).\n", - "nullable": false, - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "omni-moderation-latest", - "omni-moderation-2024-09-26", - "text-moderation-latest", - "text-moderation-stable" - ], - "x-stainless-nominal": false - } - ], - "x-oaiTypeLabel": "string" - } - }, - "required": [ - "input" - ] - }, - "CreateModerationResponse": { - "type": "object", - "description": "Represents if a given text input is potentially harmful.", - "properties": { - "id": { - "type": "string", - "description": "The unique identifier for the moderation request." - }, - "model": { - "type": "string", - "description": "The model used to generate the moderation results." - }, - "results": { - "type": "array", - "description": "A list of moderation objects.", - "items": { - "type": "object", - "properties": { - "flagged": { - "type": "boolean", - "description": "Whether any of the below categories are flagged." - }, - "categories": { - "type": "object", - "description": "A list of the categories, and whether they are flagged or not.", - "properties": { - "hate": { - "type": "boolean", - "description": "Content that expresses, incites, or promotes hate based on race, gender, ethnicity, religion, nationality, sexual orientation, disability status, or caste. Hateful content aimed at non-protected groups (e.g., chess players) is harassment." - }, - "hate/threatening": { - "type": "boolean", - "description": "Hateful content that also includes violence or serious harm towards the targeted group based on race, gender, ethnicity, religion, nationality, sexual orientation, disability status, or caste." - }, - "harassment": { - "type": "boolean", - "description": "Content that expresses, incites, or promotes harassing language towards any target." - }, - "harassment/threatening": { - "type": "boolean", - "description": "Harassment content that also includes violence or serious harm towards any target." - }, - "illicit": { - "type": "boolean", - "nullable": true, - "description": "Content that includes instructions or advice that facilitate the planning or execution of wrongdoing, or that gives advice or instruction on how to commit illicit acts. For example, \"how to shoplift\" would fit this category." - }, - "illicit/violent": { - "type": "boolean", - "nullable": true, - "description": "Content that includes instructions or advice that facilitate the planning or execution of wrongdoing that also includes violence, or that gives advice or instruction on the procurement of any weapon." - }, - "self-harm": { - "type": "boolean", - "description": "Content that promotes, encourages, or depicts acts of self-harm, such as suicide, cutting, and eating disorders." - }, - "self-harm/intent": { - "type": "boolean", - "description": "Content where the speaker expresses that they are engaging or intend to engage in acts of self-harm, such as suicide, cutting, and eating disorders." - }, - "self-harm/instructions": { - "type": "boolean", - "description": "Content that encourages performing acts of self-harm, such as suicide, cutting, and eating disorders, or that gives instructions or advice on how to commit such acts." - }, - "sexual": { - "type": "boolean", - "description": "Content meant to arouse sexual excitement, such as the description of sexual activity, or that promotes sexual services (excluding sex education and wellness)." - }, - "sexual/minors": { - "type": "boolean", - "description": "Sexual content that includes an individual who is under 18 years old." - }, - "violence": { - "type": "boolean", - "description": "Content that depicts death, violence, or physical injury." - }, - "violence/graphic": { - "type": "boolean", - "description": "Content that depicts death, violence, or physical injury in graphic detail." - } - }, - "required": [ - "hate", - "hate/threatening", - "harassment", - "harassment/threatening", - "illicit", - "illicit/violent", - "self-harm", - "self-harm/intent", - "self-harm/instructions", - "sexual", - "sexual/minors", - "violence", - "violence/graphic" - ] - }, - "category_scores": { - "type": "object", - "description": "A list of the categories along with their scores as predicted by model.", - "properties": { - "hate": { - "type": "number", - "description": "The score for the category 'hate'." - }, - "hate/threatening": { - "type": "number", - "description": "The score for the category 'hate/threatening'." - }, - "harassment": { - "type": "number", - "description": "The score for the category 'harassment'." - }, - "harassment/threatening": { - "type": "number", - "description": "The score for the category 'harassment/threatening'." - }, - "illicit": { - "type": "number", - "description": "The score for the category 'illicit'." - }, - "illicit/violent": { - "type": "number", - "description": "The score for the category 'illicit/violent'." - }, - "self-harm": { - "type": "number", - "description": "The score for the category 'self-harm'." - }, - "self-harm/intent": { - "type": "number", - "description": "The score for the category 'self-harm/intent'." - }, - "self-harm/instructions": { - "type": "number", - "description": "The score for the category 'self-harm/instructions'." - }, - "sexual": { - "type": "number", - "description": "The score for the category 'sexual'." - }, - "sexual/minors": { - "type": "number", - "description": "The score for the category 'sexual/minors'." - }, - "violence": { - "type": "number", - "description": "The score for the category 'violence'." - }, - "violence/graphic": { - "type": "number", - "description": "The score for the category 'violence/graphic'." - } - }, - "required": [ - "hate", - "hate/threatening", - "harassment", - "harassment/threatening", - "illicit", - "illicit/violent", - "self-harm", - "self-harm/intent", - "self-harm/instructions", - "sexual", - "sexual/minors", - "violence", - "violence/graphic" - ] - }, - "category_applied_input_types": { - "type": "object", - "description": "A list of the categories along with the input type(s) that the score applies to.", - "properties": { - "hate": { - "type": "array", - "description": "The applied input type(s) for the category 'hate'.", - "items": { - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - } - }, - "hate/threatening": { - "type": "array", - "description": "The applied input type(s) for the category 'hate/threatening'.", - "items": { - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - } - }, - "harassment": { - "type": "array", - "description": "The applied input type(s) for the category 'harassment'.", - "items": { - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - } - }, - "harassment/threatening": { - "type": "array", - "description": "The applied input type(s) for the category 'harassment/threatening'.", - "items": { - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - } - }, - "illicit": { - "type": "array", - "description": "The applied input type(s) for the category 'illicit'.", - "items": { - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - } - }, - "illicit/violent": { - "type": "array", - "description": "The applied input type(s) for the category 'illicit/violent'.", - "items": { - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - } - }, - "self-harm": { - "type": "array", - "description": "The applied input type(s) for the category 'self-harm'.", - "items": { - "type": "string", - "enum": [ - "text", - "image" - ] - } - }, - "self-harm/intent": { - "type": "array", - "description": "The applied input type(s) for the category 'self-harm/intent'.", - "items": { - "type": "string", - "enum": [ - "text", - "image" - ] - } - }, - "self-harm/instructions": { - "type": "array", - "description": "The applied input type(s) for the category 'self-harm/instructions'.", - "items": { - "type": "string", - "enum": [ - "text", - "image" - ] - } - }, - "sexual": { - "type": "array", - "description": "The applied input type(s) for the category 'sexual'.", - "items": { - "type": "string", - "enum": [ - "text", - "image" - ] - } - }, - "sexual/minors": { - "type": "array", - "description": "The applied input type(s) for the category 'sexual/minors'.", - "items": { - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - } - }, - "violence": { - "type": "array", - "description": "The applied input type(s) for the category 'violence'.", - "items": { - "type": "string", - "enum": [ - "text", - "image" - ] - } - }, - "violence/graphic": { - "type": "array", - "description": "The applied input type(s) for the category 'violence/graphic'.", - "items": { - "type": "string", - "enum": [ - "text", - "image" - ] - } - } - }, - "required": [ - "hate", - "hate/threatening", - "harassment", - "harassment/threatening", - "illicit", - "illicit/violent", - "self-harm", - "self-harm/intent", - "self-harm/instructions", - "sexual", - "sexual/minors", - "violence", - "violence/graphic" - ] - } - }, - "required": [ - "flagged", - "categories", - "category_scores", - "category_applied_input_types" - ] - } - } - }, - "required": [ - "id", - "model", - "results" - ], - "x-oaiMeta": { - "name": "The moderation object", - "example": "{\n \"id\": \"modr-0d9740456c391e43c445bf0f010940c7\",\n \"model\": \"omni-moderation-latest\",\n \"results\": [\n {\n \"flagged\": true,\n \"categories\": {\n \"harassment\": true,\n \"harassment/threatening\": true,\n \"sexual\": false,\n \"hate\": false,\n \"hate/threatening\": false,\n \"illicit\": false,\n \"illicit/violent\": false,\n \"self-harm/intent\": false,\n \"self-harm/instructions\": false,\n \"self-harm\": false,\n \"sexual/minors\": false,\n \"violence\": true,\n \"violence/graphic\": true\n },\n \"category_scores\": {\n \"harassment\": 0.8189693396524255,\n \"harassment/threatening\": 0.804985420696006,\n \"sexual\": 1.573112165348997e-6,\n \"hate\": 0.007562942636942845,\n \"hate/threatening\": 0.004208854591835476,\n \"illicit\": 0.030535955153511665,\n \"illicit/violent\": 0.008925306722380033,\n \"self-harm/intent\": 0.00023023930975076432,\n \"self-harm/instructions\": 0.0002293869201073356,\n \"self-harm\": 0.012598046106750154,\n \"sexual/minors\": 2.212566909570261e-8,\n \"violence\": 0.9999992735124786,\n \"violence/graphic\": 0.843064871157054\n },\n \"category_applied_input_types\": {\n \"harassment\": [\n \"text\"\n ],\n \"harassment/threatening\": [\n \"text\"\n ],\n \"sexual\": [\n \"text\",\n \"image\"\n ],\n \"hate\": [\n \"text\"\n ],\n \"hate/threatening\": [\n \"text\"\n ],\n \"illicit\": [\n \"text\"\n ],\n \"illicit/violent\": [\n \"text\"\n ],\n \"self-harm/intent\": [\n \"text\",\n \"image\"\n ],\n \"self-harm/instructions\": [\n \"text\",\n \"image\"\n ],\n \"self-harm\": [\n \"text\",\n \"image\"\n ],\n \"sexual/minors\": [\n \"text\"\n ],\n \"violence\": [\n \"text\",\n \"image\"\n ],\n \"violence/graphic\": [\n \"text\",\n \"image\"\n ]\n }\n }\n ]\n}\n" - } - }, - "CreateResponse": { - "allOf": [ - { - "$ref": "#/components/schemas/CreateModelResponseProperties" - }, - { - "$ref": "#/components/schemas/ResponseProperties" - }, - { - "type": "object", - "properties": { - "input": { - "description": "Text, image, or file inputs to the model, used to generate a response.\n\nLearn more:\n- [Text inputs and outputs](https://platform.openai.com/docs/guides/text)\n- [Image inputs](https://platform.openai.com/docs/guides/images)\n- [File inputs](https://platform.openai.com/docs/guides/pdf-files)\n- [Conversation state](https://platform.openai.com/docs/guides/conversation-state)\n- [Function calling](https://platform.openai.com/docs/guides/function-calling)\n", - "anyOf": [ - { - "type": "string", - "title": "Text input", - "description": "A text input to the model, equivalent to a text input with the\n`user` role.\n" - }, - { - "type": "array", - "title": "Input item list", - "description": "A list of one or many input items to the model, containing\ndifferent content types.\n", - "items": { - "$ref": "#/components/schemas/InputItem" - } - } - ] - }, - "include": { - "type": "array", - "description": "Specify additional output data to include in the model response. Currently\nsupported values are:\n- `web_search_call.action.sources`: Include the sources of the web search tool call.\n- `code_interpreter_call.outputs`: Includes the outputs of python code execution\n in code interpreter tool call items.\n- `computer_call_output.output.image_url`: Include image urls from the computer call output.\n- `file_search_call.results`: Include the search results of\n the file search tool call.\n- `message.input_image.image_url`: Include image urls from the input message.\n- `message.output_text.logprobs`: Include logprobs with assistant messages.\n- `reasoning.encrypted_content`: Includes an encrypted version of reasoning\n tokens in reasoning item outputs. This enables reasoning items to be used in\n multi-turn conversations when using the Responses API statelessly (like\n when the `store` parameter is set to `false`, or when an organization is\n enrolled in the zero data retention program).\n", - "items": { - "$ref": "#/components/schemas/Includable" - }, - "nullable": true - }, - "parallel_tool_calls": { - "type": "boolean", - "description": "Whether to allow the model to run tool calls in parallel.\n", - "default": true, - "nullable": true - }, - "store": { - "type": "boolean", - "description": "Whether to store the generated model response for later retrieval via\nAPI.\n", - "default": true, - "nullable": true - }, - "instructions": { - "type": "string", - "nullable": true, - "description": "A system (or developer) message inserted into the model's context.\n\nWhen using along with `previous_response_id`, the instructions from a previous\nresponse will not be carried over to the next response. This makes it simple\nto swap out system (or developer) messages in new responses.\n" - }, - "stream": { - "description": "If set to true, the model response data will be streamed to the client\nas it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).\nSee the [Streaming section below](https://platform.openai.com/docs/api-reference/responses-streaming)\nfor more information.\n", - "type": "boolean", - "nullable": true, - "default": false - }, - "stream_options": { - "$ref": "#/components/schemas/ResponseStreamOptions" - }, - "conversation": { - "description": "The conversation that this response belongs to. Items from this conversation are prepended to `input_items` for this response request.\nInput items and output items from this response are automatically added to this conversation after this response completes.\n", - "nullable": true, - "anyOf": [ - { - "type": "string", - "title": "Conversation ID", - "description": "The unique ID of the conversation.\n" - }, - { - "$ref": "#/components/schemas/ConversationParam" - } - ] - } - } - } - ] - }, - "CreateRunRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "assistant_id": { - "description": "The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to execute this run.", - "type": "string" - }, - "model": { - "description": "The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute this run. If a value is provided here, it will override the model associated with the assistant. If not, the model associated with the assistant will be used.", - "anyOf": [ - { - "type": "string" - }, - { - "$ref": "#/components/schemas/AssistantSupportedModels" - } - ], - "x-oaiTypeLabel": "string", - "nullable": true - }, - "reasoning_effort": { - "$ref": "#/components/schemas/ReasoningEffort" - }, - "instructions": { - "description": "Overrides the [instructions](https://platform.openai.com/docs/api-reference/assistants/createAssistant) of the assistant. This is useful for modifying the behavior on a per-run basis.", - "type": "string", - "nullable": true - }, - "additional_instructions": { - "description": "Appends additional instructions at the end of the instructions for the run. This is useful for modifying the behavior on a per-run basis without overriding other instructions.", - "type": "string", - "nullable": true - }, - "additional_messages": { - "description": "Adds additional messages to the thread before creating the run.", - "type": "array", - "items": { - "$ref": "#/components/schemas/CreateMessageRequest" - }, - "nullable": true - }, - "tools": { - "description": "Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.", - "nullable": true, - "type": "array", - "maxItems": 20, - "items": { - "$ref": "#/components/schemas/AssistantTool" - } - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "temperature": { - "type": "number", - "minimum": 0, - "maximum": 2, - "default": 1, - "example": 1, - "nullable": true, - "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n" - }, - "top_p": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 1, - "example": 1, - "nullable": true, - "description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or temperature but not both.\n" - }, - "stream": { - "type": "boolean", - "nullable": true, - "description": "If `true`, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a `data: [DONE]` message.\n" - }, - "max_prompt_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of prompt tokens that may be used over the course of the run. The run will make a best effort to use only the number of prompt tokens specified, across multiple turns of the run. If the run exceeds the number of prompt tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.\n", - "minimum": 256 - }, - "max_completion_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of completion tokens that may be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.\n", - "minimum": 256 - }, - "truncation_strategy": { - "allOf": [ - { - "$ref": "#/components/schemas/TruncationObject" - }, - { - "nullable": true - } - ] - }, - "tool_choice": { - "allOf": [ - { - "$ref": "#/components/schemas/AssistantsApiToolChoiceOption" - }, - { - "nullable": true - } - ] - }, - "parallel_tool_calls": { - "$ref": "#/components/schemas/ParallelToolCalls" - }, - "response_format": { - "$ref": "#/components/schemas/AssistantsApiResponseFormatOption", - "nullable": true - } - }, - "required": [ - "assistant_id" - ] - }, - "CreateSpeechRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "model": { - "description": "One of the available [TTS models](https://platform.openai.com/docs/models#tts): `tts-1`, `tts-1-hd` or `gpt-4o-mini-tts`.\n", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "tts-1", - "tts-1-hd", - "gpt-4o-mini-tts" - ], - "x-stainless-nominal": false - } - ], - "x-oaiTypeLabel": "string" - }, - "input": { - "type": "string", - "description": "The text to generate audio for. The maximum length is 4096 characters.", - "maxLength": 4096 - }, - "instructions": { - "type": "string", - "description": "Control the voice of your generated audio with additional instructions. Does not work with `tts-1` or `tts-1-hd`.", - "maxLength": 4096 - }, - "voice": { - "description": "The voice to use when generating the audio. Supported voices are `alloy`, `ash`, `ballad`, `coral`, `echo`, `fable`, `onyx`, `nova`, `sage`, `shimmer`, and `verse`. Previews of the voices are available in the [Text to speech guide](https://platform.openai.com/docs/guides/text-to-speech#voice-options).", - "$ref": "#/components/schemas/VoiceIdsShared" - }, - "response_format": { - "description": "The format to audio in. Supported formats are `mp3`, `opus`, `aac`, `flac`, `wav`, and `pcm`.", - "default": "mp3", - "type": "string", - "enum": [ - "mp3", - "opus", - "aac", - "flac", - "wav", - "pcm" - ] - }, - "speed": { - "description": "The speed of the generated audio. Select a value from `0.25` to `4.0`. `1.0` is the default.", - "type": "number", - "default": 1, - "minimum": 0.25, - "maximum": 4 - }, - "stream_format": { - "description": "The format to stream the audio in. Supported formats are `sse` and `audio`. `sse` is not supported for `tts-1` or `tts-1-hd`.", - "type": "string", - "default": "audio", - "enum": [ - "sse", - "audio" - ] - } - }, - "required": [ - "model", - "input", - "voice" - ] - }, - "CreateSpeechResponseStreamEvent": { - "anyOf": [ - { - "$ref": "#/components/schemas/SpeechAudioDeltaEvent" - }, - { - "$ref": "#/components/schemas/SpeechAudioDoneEvent" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "CreateThreadAndRunRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "assistant_id": { - "description": "The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to execute this run.", - "type": "string" - }, - "thread": { - "$ref": "#/components/schemas/CreateThreadRequest" - }, - "model": { - "description": "The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute this run. If a value is provided here, it will override the model associated with the assistant. If not, the model associated with the assistant will be used.", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "gpt-5", - "gpt-5-mini", - "gpt-5-nano", - "gpt-5-2025-08-07", - "gpt-5-mini-2025-08-07", - "gpt-5-nano-2025-08-07", - "gpt-4.1", - "gpt-4.1-mini", - "gpt-4.1-nano", - "gpt-4.1-2025-04-14", - "gpt-4.1-mini-2025-04-14", - "gpt-4.1-nano-2025-04-14", - "gpt-4o", - "gpt-4o-2024-11-20", - "gpt-4o-2024-08-06", - "gpt-4o-2024-05-13", - "gpt-4o-mini", - "gpt-4o-mini-2024-07-18", - "gpt-4.5-preview", - "gpt-4.5-preview-2025-02-27", - "gpt-4-turbo", - "gpt-4-turbo-2024-04-09", - "gpt-4-0125-preview", - "gpt-4-turbo-preview", - "gpt-4-1106-preview", - "gpt-4-vision-preview", - "gpt-4", - "gpt-4-0314", - "gpt-4-0613", - "gpt-4-32k", - "gpt-4-32k-0314", - "gpt-4-32k-0613", - "gpt-3.5-turbo", - "gpt-3.5-turbo-16k", - "gpt-3.5-turbo-0613", - "gpt-3.5-turbo-1106", - "gpt-3.5-turbo-0125", - "gpt-3.5-turbo-16k-0613" - ] - } - ], - "x-oaiTypeLabel": "string", - "nullable": true - }, - "instructions": { - "description": "Override the default system message of the assistant. This is useful for modifying the behavior on a per-run basis.", - "type": "string", - "nullable": true - }, - "tools": { - "description": "Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.", - "nullable": true, - "type": "array", - "maxItems": 20, - "items": { - "$ref": "#/components/schemas/AssistantTool" - } - }, - "tool_resources": { - "type": "object", - "description": "A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.\n", - "properties": { - "code_interpreter": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.\n", - "default": [], - "maxItems": 20, - "items": { - "type": "string" - } - } - } - }, - "file_search": { - "type": "object", - "properties": { - "vector_store_ids": { - "type": "array", - "description": "The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.\n", - "maxItems": 1, - "items": { - "type": "string" - } - } - } - } - }, - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "temperature": { - "type": "number", - "minimum": 0, - "maximum": 2, - "default": 1, - "example": 1, - "nullable": true, - "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n" - }, - "top_p": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 1, - "example": 1, - "nullable": true, - "description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or temperature but not both.\n" - }, - "stream": { - "type": "boolean", - "nullable": true, - "description": "If `true`, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a `data: [DONE]` message.\n" - }, - "max_prompt_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of prompt tokens that may be used over the course of the run. The run will make a best effort to use only the number of prompt tokens specified, across multiple turns of the run. If the run exceeds the number of prompt tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.\n", - "minimum": 256 - }, - "max_completion_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of completion tokens that may be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.\n", - "minimum": 256 - }, - "truncation_strategy": { - "allOf": [ - { - "$ref": "#/components/schemas/TruncationObject" - }, - { - "nullable": true - } - ] - }, - "tool_choice": { - "allOf": [ - { - "$ref": "#/components/schemas/AssistantsApiToolChoiceOption" - }, - { - "nullable": true - } - ] - }, - "parallel_tool_calls": { - "$ref": "#/components/schemas/ParallelToolCalls" - }, - "response_format": { - "$ref": "#/components/schemas/AssistantsApiResponseFormatOption", - "nullable": true - } - }, - "required": [ - "assistant_id" - ] - }, - "CreateThreadRequest": { - "type": "object", - "description": "Options to create a new thread. If no thread is provided when running a \nrequest, an empty thread will be created.\n", - "additionalProperties": false, - "properties": { - "messages": { - "description": "A list of [messages](https://platform.openai.com/docs/api-reference/messages) to start the thread with.", - "type": "array", - "items": { - "$ref": "#/components/schemas/CreateMessageRequest" - } - }, - "tool_resources": { - "type": "object", - "description": "A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.\n", - "properties": { - "code_interpreter": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.\n", - "default": [], - "maxItems": 20, - "items": { - "type": "string" - } - } - } - }, - "file_search": { - "type": "object", - "properties": { - "vector_store_ids": { - "type": "array", - "description": "The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this thread. There can be a maximum of 1 vector store attached to the thread.\n", - "maxItems": 1, - "items": { - "type": "string" - } - }, - "vector_stores": { - "type": "array", - "description": "A helper to create a [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) with file_ids and attach it to this thread. There can be a maximum of 1 vector store attached to the thread.\n", - "maxItems": 1, - "items": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "A list of [file](https://platform.openai.com/docs/api-reference/files) IDs to add to the vector store. There can be a maximum of 10000 files in a vector store.\n", - "maxItems": 10000, - "items": { - "type": "string" - } - }, - "chunking_strategy": { - "type": "object", - "description": "The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy.", - "anyOf": [ - { - "type": "object", - "title": "Auto Chunking Strategy", - "description": "The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and `chunk_overlap_tokens` of `400`.", - "additionalProperties": false, - "properties": { - "type": { - "type": "string", - "description": "Always `auto`.", - "enum": [ - "auto" - ], - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - { - "type": "object", - "title": "Static Chunking Strategy", - "additionalProperties": false, - "properties": { - "type": { - "type": "string", - "description": "Always `static`.", - "enum": [ - "static" - ], - "x-stainless-const": true - }, - "static": { - "type": "object", - "additionalProperties": false, - "properties": { - "max_chunk_size_tokens": { - "type": "integer", - "minimum": 100, - "maximum": 4096, - "description": "The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100` and the maximum value is `4096`." - }, - "chunk_overlap_tokens": { - "type": "integer", - "description": "The number of tokens that overlap between chunks. The default value is `400`.\n\nNote that the overlap must not exceed half of `max_chunk_size_tokens`.\n" - } - }, - "required": [ - "max_chunk_size_tokens", - "chunk_overlap_tokens" - ] - } - }, - "required": [ - "type", - "static" - ], - "x-stainless-naming": { - "java": { - "type_name": "StaticObject" - }, - "kotlin": { - "type_name": "StaticObject" - } - } - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - } - } - }, - "anyOf": [ - { - "required": [ - "vector_store_ids" - ] - }, - { - "required": [ - "vector_stores" - ] - } - ] - } - }, - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - }, - "CreateTranscriptionRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "file": { - "description": "The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.\n", - "type": "string", - "x-oaiTypeLabel": "file", - "format": "binary", - "x-oaiMeta": { - "exampleFilePath": "speech.mp3" - } - }, - "model": { - "description": "ID of the model to use. The options are `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, and `whisper-1` (which is powered by our open source Whisper V2 model).\n", - "example": "gpt-4o-transcribe", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "whisper-1", - "gpt-4o-transcribe", - "gpt-4o-mini-transcribe" - ], - "x-stainless-const": true, - "x-stainless-nominal": false - } - ], - "x-oaiTypeLabel": "string" - }, - "language": { - "description": "The language of the input audio. Supplying the input language in [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format will improve accuracy and latency.\n", - "type": "string" - }, - "prompt": { - "description": "An optional text to guide the model's style or continue a previous audio segment. The [prompt](https://platform.openai.com/docs/guides/speech-to-text#prompting) should match the audio language.\n", - "type": "string" - }, - "response_format": { - "$ref": "#/components/schemas/AudioResponseFormat" - }, - "temperature": { - "description": "The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically increase the temperature until certain thresholds are hit.\n", - "type": "number", - "default": 0 - }, - "stream": { - "description": "If set to true, the model response data will be streamed to the client\nas it is generated using [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).\nSee the [Streaming section of the Speech-to-Text guide](https://platform.openai.com/docs/guides/speech-to-text?lang=curl#streaming-transcriptions)\nfor more information.\n\nNote: Streaming is not supported for the `whisper-1` model and will be ignored.\n", - "type": "boolean", - "nullable": true, - "default": false - }, - "chunking_strategy": { - "$ref": "#/components/schemas/TranscriptionChunkingStrategy" - }, - "timestamp_granularities": { - "description": "The timestamp granularities to populate for this transcription. `response_format` must be set `verbose_json` to use timestamp granularities. Either or both of these options are supported: `word`, or `segment`. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency.\n", - "type": "array", - "items": { - "type": "string", - "enum": [ - "word", - "segment" - ] - }, - "default": [ - "segment" - ] - }, - "include": { - "description": "Additional information to include in the transcription response. \n`logprobs` will return the log probabilities of the tokens in the \nresponse to understand the model's confidence in the transcription. \n`logprobs` only works with response_format set to `json` and only with \nthe models `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`.\n", - "type": "array", - "items": { - "$ref": "#/components/schemas/TranscriptionInclude" - } - } - }, - "required": [ - "file", - "model" - ] - }, - "CreateTranscriptionResponseJson": { - "type": "object", - "description": "Represents a transcription response returned by model, based on the provided input.", - "properties": { - "text": { - "type": "string", - "description": "The transcribed text." - }, - "logprobs": { - "type": "array", - "optional": true, - "description": "The log probabilities of the tokens in the transcription. Only returned with the models `gpt-4o-transcribe` and `gpt-4o-mini-transcribe` if `logprobs` is added to the `include` array.\n", - "items": { - "type": "object", - "properties": { - "token": { - "type": "string", - "description": "The token in the transcription." - }, - "logprob": { - "type": "number", - "description": "The log probability of the token." - }, - "bytes": { - "type": "array", - "items": { - "type": "number" - }, - "description": "The bytes of the token." - } - } - } - }, - "usage": { - "type": "object", - "description": "Token usage statistics for the request.", - "anyOf": [ - { - "$ref": "#/components/schemas/TranscriptTextUsageTokens", - "title": "Token Usage" - }, - { - "$ref": "#/components/schemas/TranscriptTextUsageDuration", - "title": "Duration Usage" - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "required": [ - "text" - ], - "x-oaiMeta": { - "name": "The transcription object (JSON)", - "group": "audio", - "example": "{\n \"text\": \"Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that.\",\n \"usage\": {\n \"type\": \"tokens\",\n \"input_tokens\": 14,\n \"input_token_details\": {\n \"text_tokens\": 10,\n \"audio_tokens\": 4\n },\n \"output_tokens\": 101,\n \"total_tokens\": 115\n }\n}\n" - } - }, - "CreateTranscriptionResponseStreamEvent": { - "anyOf": [ - { - "$ref": "#/components/schemas/TranscriptTextDeltaEvent" - }, - { - "$ref": "#/components/schemas/TranscriptTextDoneEvent" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "CreateTranscriptionResponseVerboseJson": { - "type": "object", - "description": "Represents a verbose json transcription response returned by model, based on the provided input.", - "properties": { - "language": { - "type": "string", - "description": "The language of the input audio." - }, - "duration": { - "type": "number", - "description": "The duration of the input audio." - }, - "text": { - "type": "string", - "description": "The transcribed text." - }, - "words": { - "type": "array", - "description": "Extracted words and their corresponding timestamps.", - "items": { - "$ref": "#/components/schemas/TranscriptionWord" - } - }, - "segments": { - "type": "array", - "description": "Segments of the transcribed text and their corresponding details.", - "items": { - "$ref": "#/components/schemas/TranscriptionSegment" - } - }, - "usage": { - "$ref": "#/components/schemas/TranscriptTextUsageDuration" - } - }, - "required": [ - "language", - "duration", - "text" - ], - "x-oaiMeta": { - "name": "The transcription object (Verbose JSON)", - "group": "audio", - "example": "{\n \"task\": \"transcribe\",\n \"language\": \"english\",\n \"duration\": 8.470000267028809,\n \"text\": \"The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.\",\n \"segments\": [\n {\n \"id\": 0,\n \"seek\": 0,\n \"start\": 0.0,\n \"end\": 3.319999933242798,\n \"text\": \" The beach was a popular spot on a hot summer day.\",\n \"tokens\": [\n 50364, 440, 7534, 390, 257, 3743, 4008, 322, 257, 2368, 4266, 786, 13, 50530\n ],\n \"temperature\": 0.0,\n \"avg_logprob\": -0.2860786020755768,\n \"compression_ratio\": 1.2363636493682861,\n \"no_speech_prob\": 0.00985979475080967\n },\n ...\n ],\n \"usage\": {\n \"type\": \"duration\",\n \"seconds\": 9\n }\n}\n" - } - }, - "CreateTranslationRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "file": { - "description": "The audio file object (not file name) translate, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.\n", - "type": "string", - "x-oaiTypeLabel": "file", - "format": "binary", - "x-oaiMeta": { - "exampleFilePath": "speech.mp3" - } - }, - "model": { - "description": "ID of the model to use. Only `whisper-1` (which is powered by our open source Whisper V2 model) is currently available.\n", - "example": "whisper-1", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "whisper-1" - ], - "x-stainless-const": true - } - ], - "x-oaiTypeLabel": "string" - }, - "prompt": { - "description": "An optional text to guide the model's style or continue a previous audio segment. The [prompt](https://platform.openai.com/docs/guides/speech-to-text#prompting) should be in English.\n", - "type": "string" - }, - "response_format": { - "description": "The format of the output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or `vtt`.\n", - "type": "string", - "enum": [ - "json", - "text", - "srt", - "verbose_json", - "vtt" - ], - "default": "json" - }, - "temperature": { - "description": "The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically increase the temperature until certain thresholds are hit.\n", - "type": "number", - "default": 0 - } - }, - "required": [ - "file", - "model" - ] - }, - "CreateTranslationResponseJson": { - "type": "object", - "properties": { - "text": { - "type": "string" - } - }, - "required": [ - "text" - ] - }, - "CreateTranslationResponseVerboseJson": { - "type": "object", - "properties": { - "language": { - "type": "string", - "description": "The language of the output translation (always `english`)." - }, - "duration": { - "type": "number", - "description": "The duration of the input audio." - }, - "text": { - "type": "string", - "description": "The translated text." - }, - "segments": { - "type": "array", - "description": "Segments of the translated text and their corresponding details.", - "items": { - "$ref": "#/components/schemas/TranscriptionSegment" - } - } - }, - "required": [ - "language", - "duration", - "text" - ] - }, - "CreateUploadRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "filename": { - "description": "The name of the file to upload.\n", - "type": "string" - }, - "purpose": { - "description": "The intended purpose of the uploaded file.\n\nSee the [documentation on File purposes](https://platform.openai.com/docs/api-reference/files/create#files-create-purpose).\n", - "type": "string", - "enum": [ - "assistants", - "batch", - "fine-tune", - "vision" - ] - }, - "bytes": { - "description": "The number of bytes in the file you are uploading.\n", - "type": "integer" - }, - "mime_type": { - "description": "The MIME type of the file.\n\nThis must fall within the supported MIME types for your file purpose. See the supported MIME types for assistants and vision.\n", - "type": "string" - }, - "expires_after": { - "$ref": "#/components/schemas/FileExpirationAfter" - } - }, - "required": [ - "filename", - "purpose", - "bytes", - "mime_type" - ] - }, - "CreateVectorStoreFileBatchRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "file_ids": { - "description": "A list of [File](https://platform.openai.com/docs/api-reference/files) IDs that the vector store should use. Useful for tools like `file_search` that can access files.", - "type": "array", - "minItems": 1, - "maxItems": 500, - "items": { - "type": "string" - } - }, - "chunking_strategy": { - "$ref": "#/components/schemas/ChunkingStrategyRequestParam" - }, - "attributes": { - "$ref": "#/components/schemas/VectorStoreFileAttributes" - } - }, - "required": [ - "file_ids" - ] - }, - "CreateVectorStoreFileRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "file_id": { - "description": "A [File](https://platform.openai.com/docs/api-reference/files) ID that the vector store should use. Useful for tools like `file_search` that can access files.", - "type": "string" - }, - "chunking_strategy": { - "$ref": "#/components/schemas/ChunkingStrategyRequestParam" - }, - "attributes": { - "$ref": "#/components/schemas/VectorStoreFileAttributes" - } - }, - "required": [ - "file_id" - ] - }, - "CreateVectorStoreRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "file_ids": { - "description": "A list of [File](https://platform.openai.com/docs/api-reference/files) IDs that the vector store should use. Useful for tools like `file_search` that can access files.", - "type": "array", - "maxItems": 500, - "items": { - "type": "string" - } - }, - "name": { - "description": "The name of the vector store.", - "type": "string" - }, - "expires_after": { - "$ref": "#/components/schemas/VectorStoreExpirationAfter" - }, - "chunking_strategy": { - "$ref": "#/components/schemas/ChunkingStrategyRequestParam" - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - }, - "CustomTool": { - "type": "object", - "title": "Custom tool", - "description": "A custom tool that processes input using a specified format. Learn more about\n[custom tools](https://platform.openai.com/docs/guides/function-calling#custom-tools).\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "custom" - ], - "description": "The type of the custom tool. Always `custom`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the custom tool, used to identify it in tool calls." - }, - "description": { - "type": "string", - "description": "Optional description of the custom tool, used to provide more context.\n" - }, - "format": { - "description": "The input format for the custom tool. Default is unconstrained text.\n", - "anyOf": [ - { - "type": "object", - "title": "Text format", - "description": "Unconstrained free-form text.", - "properties": { - "type": { - "type": "string", - "enum": [ - "text" - ], - "description": "Unconstrained text format. Always `text`.", - "x-stainless-const": true - } - }, - "required": [ - "type" - ], - "additionalProperties": false - }, - { - "type": "object", - "title": "Grammar format", - "description": "A grammar defined by the user.", - "properties": { - "type": { - "type": "string", - "enum": [ - "grammar" - ], - "description": "Grammar format. Always `grammar`.", - "x-stainless-const": true - }, - "definition": { - "type": "string", - "description": "The grammar definition." - }, - "syntax": { - "type": "string", - "description": "The syntax of the grammar definition. One of `lark` or `regex`.", - "enum": [ - "lark", - "regex" - ] - } - }, - "required": [ - "type", - "definition", - "syntax" - ], - "additionalProperties": false - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "required": [ - "type", - "name" - ] - }, - "CustomToolCall": { - "type": "object", - "title": "Custom tool call", - "description": "A call to a custom tool created by the model.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "custom_tool_call" - ], - "x-stainless-const": true, - "description": "The type of the custom tool call. Always `custom_tool_call`.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the custom tool call in the OpenAI platform.\n" - }, - "call_id": { - "type": "string", - "description": "An identifier used to map this custom tool call to a tool call output.\n" - }, - "name": { - "type": "string", - "description": "The name of the custom tool being called.\n" - }, - "input": { - "type": "string", - "description": "The input for the custom tool call generated by the model.\n" - } - }, - "required": [ - "type", - "call_id", - "name", - "input" - ] - }, - "CustomToolCallOutput": { - "type": "object", - "title": "Custom tool call output", - "description": "The output of a custom tool call from your code, being sent back to the model.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "custom_tool_call_output" - ], - "x-stainless-const": true, - "description": "The type of the custom tool call output. Always `custom_tool_call_output`.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the custom tool call output in the OpenAI platform.\n" - }, - "call_id": { - "type": "string", - "description": "The call ID, used to map this custom tool call output to a custom tool call.\n" - }, - "output": { - "type": "string", - "description": "The output from the custom tool call generated by your code.\n" - } - }, - "required": [ - "type", - "call_id", - "output" - ] - }, - "CustomToolChatCompletions": { - "type": "object", - "title": "Custom tool", - "description": "A custom tool that processes input using a specified format.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "custom" - ], - "description": "The type of the custom tool. Always `custom`.", - "x-stainless-const": true - }, - "custom": { - "type": "object", - "title": "Custom tool properties", - "description": "Properties of the custom tool.\n", - "properties": { - "name": { - "type": "string", - "description": "The name of the custom tool, used to identify it in tool calls." - }, - "description": { - "type": "string", - "description": "Optional description of the custom tool, used to provide more context.\n" - }, - "format": { - "description": "The input format for the custom tool. Default is unconstrained text.\n", - "anyOf": [ - { - "type": "object", - "title": "Text format", - "description": "Unconstrained free-form text.", - "properties": { - "type": { - "type": "string", - "enum": [ - "text" - ], - "description": "Unconstrained text format. Always `text`.", - "x-stainless-const": true - } - }, - "required": [ - "type" - ], - "additionalProperties": false - }, - { - "type": "object", - "title": "Grammar format", - "description": "A grammar defined by the user.", - "properties": { - "type": { - "type": "string", - "enum": [ - "grammar" - ], - "description": "Grammar format. Always `grammar`.", - "x-stainless-const": true - }, - "grammar": { - "type": "object", - "title": "Grammar format", - "description": "Your chosen grammar.", - "properties": { - "definition": { - "type": "string", - "description": "The grammar definition." - }, - "syntax": { - "type": "string", - "description": "The syntax of the grammar definition. One of `lark` or `regex`.", - "enum": [ - "lark", - "regex" - ] - } - }, - "required": [ - "definition", - "syntax" - ] - } - }, - "required": [ - "type", - "grammar" - ], - "additionalProperties": false - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "required": [ - "name" - ] - } - }, - "required": [ - "type", - "custom" - ] - }, - "DeleteAssistantResponse": { - "type": "object", - "properties": { - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - }, - "object": { - "type": "string", - "enum": [ - "assistant.deleted" - ], - "x-stainless-const": true - } - }, - "required": [ - "id", - "object", - "deleted" - ] - }, - "DeleteCertificateResponse": { - "type": "object", - "properties": { - "object": { - "description": "The object type, must be `certificate.deleted`.", - "x-stainless-const": true, - "const": "certificate.deleted" - }, - "id": { - "type": "string", - "description": "The ID of the certificate that was deleted." - } - }, - "required": [ - "object", - "id" - ] - }, - "DeleteFileResponse": { - "type": "object", - "properties": { - "id": { - "type": "string" - }, - "object": { - "type": "string", - "enum": [ - "file" - ], - "x-stainless-const": true - }, - "deleted": { - "type": "boolean" - } - }, - "required": [ - "id", - "object", - "deleted" - ] - }, - "DeleteFineTuningCheckpointPermissionResponse": { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The ID of the fine-tuned model checkpoint permission that was deleted." - }, - "object": { - "type": "string", - "description": "The object type, which is always \"checkpoint.permission\".", - "enum": [ - "checkpoint.permission" - ], - "x-stainless-const": true - }, - "deleted": { - "type": "boolean", - "description": "Whether the fine-tuned model checkpoint permission was successfully deleted." - } - }, - "required": [ - "id", - "object", - "deleted" - ] - }, - "DeleteMessageResponse": { - "type": "object", - "properties": { - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - }, - "object": { - "type": "string", - "enum": [ - "thread.message.deleted" - ], - "x-stainless-const": true - } - }, - "required": [ - "id", - "object", - "deleted" - ] - }, - "DeleteModelResponse": { - "type": "object", - "properties": { - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - }, - "object": { - "type": "string" - } - }, - "required": [ - "id", - "object", - "deleted" - ] - }, - "DeleteThreadResponse": { - "type": "object", - "properties": { - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - }, - "object": { - "type": "string", - "enum": [ - "thread.deleted" - ], - "x-stainless-const": true - } - }, - "required": [ - "id", - "object", - "deleted" - ] - }, - "DeleteVectorStoreFileResponse": { - "type": "object", - "properties": { - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - }, - "object": { - "type": "string", - "enum": [ - "vector_store.file.deleted" - ], - "x-stainless-const": true - } - }, - "required": [ - "id", - "object", - "deleted" - ] - }, - "DeleteVectorStoreResponse": { - "type": "object", - "properties": { - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - }, - "object": { - "type": "string", - "enum": [ - "vector_store.deleted" - ], - "x-stainless-const": true - } - }, - "required": [ - "id", - "object", - "deleted" - ] - }, - "DeletedConversation": { - "title": "The deleted conversation object", - "allOf": [ - { - "$ref": "#/components/schemas/DeletedConversationResource" - } - ], - "x-oaiMeta": { - "name": "The deleted conversation object", - "group": "conversations" - } - }, - "DoneEvent": { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "done" - ], - "x-stainless-const": true - }, - "data": { - "type": "string", - "enum": [ - "[DONE]" - ], - "x-stainless-const": true - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a stream ends.", - "x-oaiMeta": { - "dataDescription": "`data` is `[DONE]`" - } - }, - "DoubleClick": { - "type": "object", - "title": "DoubleClick", - "description": "A double click action.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "double_click" - ], - "default": "double_click", - "description": "Specifies the event type. For a double click action, this property is \nalways set to `double_click`.\n", - "x-stainless-const": true - }, - "x": { - "type": "integer", - "description": "The x-coordinate where the double click occurred.\n" - }, - "y": { - "type": "integer", - "description": "The y-coordinate where the double click occurred.\n" - } - }, - "required": [ - "type", - "x", - "y" - ] - }, - "Drag": { - "type": "object", - "title": "Drag", - "description": "A drag action.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "drag" - ], - "default": "drag", - "description": "Specifies the event type. For a drag action, this property is \nalways set to `drag`.\n", - "x-stainless-const": true - }, - "path": { - "type": "array", - "description": "An array of coordinates representing the path of the drag action. Coordinates will appear as an array\nof objects, eg\n```\n[ { x: 100, y: 200 },\n { x: 200, y: 300 }\n]\n```\n", - "items": { - "title": "Drag path coordinates", - "description": "A series of x/y coordinate pairs in the drag path.\n", - "$ref": "#/components/schemas/Coordinate" - } - } - }, - "required": [ - "type", - "path" - ] - }, - "EasyInputMessage": { - "type": "object", - "title": "Input message", - "description": "A message input to the model with a role indicating instruction following\nhierarchy. Instructions given with the `developer` or `system` role take\nprecedence over instructions given with the `user` role. Messages with the\n`assistant` role are presumed to have been generated by the model in previous\ninteractions.\n", - "properties": { - "role": { - "type": "string", - "description": "The role of the message input. One of `user`, `assistant`, `system`, or\n`developer`.\n", - "enum": [ - "user", - "assistant", - "system", - "developer" - ] - }, - "content": { - "description": "Text, image, or audio input to the model, used to generate a response.\nCan also contain previous assistant responses.\n", - "anyOf": [ - { - "type": "string", - "title": "Text input", - "description": "A text input to the model.\n" - }, - { - "$ref": "#/components/schemas/InputMessageContentList" - } - ] - }, - "type": { - "type": "string", - "description": "The type of the message input. Always `message`.\n", - "enum": [ - "message" - ], - "x-stainless-const": true - } - }, - "required": [ - "role", - "content" - ] - }, - "Embedding": { - "type": "object", - "description": "Represents an embedding vector returned by embedding endpoint.\n", - "properties": { - "index": { - "type": "integer", - "description": "The index of the embedding in the list of embeddings." - }, - "embedding": { - "type": "array", - "description": "The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the [embedding guide](https://platform.openai.com/docs/guides/embeddings).\n", - "items": { - "type": "number", - "format": "float" - } - }, - "object": { - "type": "string", - "description": "The object type, which is always \"embedding\".", - "enum": [ - "embedding" - ], - "x-stainless-const": true - } - }, - "required": [ - "index", - "object", - "embedding" - ], - "x-oaiMeta": { - "name": "The embedding object", - "example": "{\n \"object\": \"embedding\",\n \"embedding\": [\n 0.0023064255,\n -0.009327292,\n .... (1536 floats total for ada-002)\n -0.0028842222,\n ],\n \"index\": 0\n}\n" - } - }, - "Error": { - "type": "object", - "properties": { - "code": { - "type": "string", - "nullable": true - }, - "message": { - "type": "string", - "nullable": false - }, - "param": { - "type": "string", - "nullable": true - }, - "type": { - "type": "string", - "nullable": false - } - }, - "required": [ - "type", - "message", - "param", - "code" - ] - }, - "ErrorEvent": { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "error" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/Error" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when an [error](https://platform.openai.com/docs/guides/error-codes#api-errors) occurs. This can happen due to an internal server error or a timeout.", - "x-oaiMeta": { - "dataDescription": "`data` is an [error](/docs/guides/error-codes#api-errors)" - } - }, - "ErrorResponse": { - "type": "object", - "properties": { - "error": { - "$ref": "#/components/schemas/Error" - } - }, - "required": [ - "error" - ] - }, - "Eval": { - "type": "object", - "title": "Eval", - "description": "An Eval object with a data source config and testing criteria.\nAn Eval represents a task to be done for your LLM integration.\nLike:\n - Improve the quality of my chatbot\n - See how well my chatbot handles customer support\n - Check if o4-mini is better at my usecase than gpt-4o\n", - "properties": { - "object": { - "type": "string", - "enum": [ - "eval" - ], - "default": "eval", - "description": "The object type.", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "Unique identifier for the evaluation." - }, - "name": { - "type": "string", - "description": "The name of the evaluation.", - "example": "Chatbot effectiveness Evaluation" - }, - "data_source_config": { - "type": "object", - "description": "Configuration of data sources used in runs of the evaluation.", - "anyOf": [ - { - "$ref": "#/components/schemas/EvalCustomDataSourceConfig" - }, - { - "$ref": "#/components/schemas/EvalLogsDataSourceConfig" - }, - { - "$ref": "#/components/schemas/EvalStoredCompletionsDataSourceConfig" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "testing_criteria": { - "description": "A list of testing criteria.", - "type": "array", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/EvalGraderLabelModel" - }, - { - "$ref": "#/components/schemas/EvalGraderStringCheck" - }, - { - "$ref": "#/components/schemas/EvalGraderTextSimilarity" - }, - { - "$ref": "#/components/schemas/EvalGraderPython" - }, - { - "$ref": "#/components/schemas/EvalGraderScoreModel" - } - ] - } - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the eval was created." - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - }, - "required": [ - "id", - "data_source_config", - "object", - "testing_criteria", - "name", - "created_at", - "metadata" - ], - "x-oaiMeta": { - "name": "The eval object", - "group": "evals", - "example": "{\n \"object\": \"eval\",\n \"id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"data_source_config\": {\n \"type\": \"custom\",\n \"item_schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"label\": {\"type\": \"string\"},\n },\n \"required\": [\"label\"]\n },\n \"include_sample_schema\": true\n },\n \"testing_criteria\": [\n {\n \"name\": \"My string check grader\",\n \"type\": \"string_check\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\",\n }\n ],\n \"name\": \"External Data Eval\",\n \"created_at\": 1739314509,\n \"metadata\": {\n \"test\": \"synthetics\",\n }\n}\n" - } - }, - "EvalApiError": { - "type": "object", - "title": "EvalApiError", - "description": "An object representing an error response from the Eval API.\n", - "properties": { - "code": { - "type": "string", - "description": "The error code." - }, - "message": { - "type": "string", - "description": "The error message." - } - }, - "required": [ - "code", - "message" - ], - "x-oaiMeta": { - "name": "The API error object", - "group": "evals", - "example": "{\n \"code\": \"internal_error\",\n \"message\": \"The eval run failed due to an internal error.\"\n}\n" - } - }, - "EvalCustomDataSourceConfig": { - "type": "object", - "title": "CustomDataSourceConfig", - "description": "A CustomDataSourceConfig which specifies the schema of your `item` and optionally `sample` namespaces.\nThe response schema defines the shape of the data that will be:\n- Used to define your testing criteria and\n- What data is required when creating a run\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "custom" - ], - "default": "custom", - "description": "The type of data source. Always `custom`.", - "x-stainless-const": true - }, - "schema": { - "type": "object", - "description": "The json schema for the run data source items.\nLearn how to build JSON schemas [here](https://json-schema.org/).\n", - "additionalProperties": true - } - }, - "required": [ - "type", - "schema" - ], - "x-oaiMeta": { - "name": "The eval custom data source config object", - "group": "evals", - "example": "{\n \"type\": \"custom\",\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"item\": {\n \"type\": \"object\",\n \"properties\": {\n \"label\": {\"type\": \"string\"},\n },\n \"required\": [\"label\"]\n }\n },\n \"required\": [\"item\"]\n }\n}\n" - } - }, - "EvalGraderLabelModel": { - "type": "object", - "title": "LabelModelGrader", - "allOf": [ - { - "$ref": "#/components/schemas/GraderLabelModel" - } - ] - }, - "EvalGraderPython": { - "type": "object", - "title": "PythonGrader", - "allOf": [ - { - "$ref": "#/components/schemas/GraderPython" - }, - { - "type": "object", - "properties": { - "pass_threshold": { - "type": "number", - "description": "The threshold for the score." - } - }, - "x-oaiMeta": { - "name": "Eval Python Grader", - "group": "graders", - "example": "{\n \"type\": \"python\",\n \"name\": \"Example python grader\",\n \"image_tag\": \"2025-05-08\",\n \"source\": \"\"\"\ndef grade(sample: dict, item: dict) -> float:\n \\\"\"\"\n Returns 1.0 if `output_text` equals `label`, otherwise 0.0.\n \\\"\"\"\n output = sample.get(\"output_text\")\n label = item.get(\"label\")\n return 1.0 if output == label else 0.0\n\"\"\",\n \"pass_threshold\": 0.8\n}\n" - } - } - ] - }, - "EvalGraderScoreModel": { - "type": "object", - "title": "ScoreModelGrader", - "allOf": [ - { - "$ref": "#/components/schemas/GraderScoreModel" - }, - { - "type": "object", - "properties": { - "pass_threshold": { - "type": "number", - "description": "The threshold for the score." - } - } - } - ] - }, - "EvalGraderStringCheck": { - "type": "object", - "title": "StringCheckGrader", - "allOf": [ - { - "$ref": "#/components/schemas/GraderStringCheck" - } - ] - }, - "EvalGraderTextSimilarity": { - "type": "object", - "title": "TextSimilarityGrader", - "allOf": [ - { - "$ref": "#/components/schemas/GraderTextSimilarity" - }, - { - "type": "object", - "properties": { - "pass_threshold": { - "type": "number", - "description": "The threshold for the score." - } - }, - "required": [ - "pass_threshold" - ], - "x-oaiMeta": { - "name": "Text Similarity Grader", - "group": "graders", - "example": "{\n \"type\": \"text_similarity\",\n \"name\": \"Example text similarity grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"pass_threshold\": 0.8,\n \"evaluation_metric\": \"fuzzy_match\"\n}\n" - } - } - ] - }, - "EvalItem": { - "type": "object", - "title": "Eval message object", - "description": "A message input to the model with a role indicating instruction following\nhierarchy. Instructions given with the `developer` or `system` role take\nprecedence over instructions given with the `user` role. Messages with the\n`assistant` role are presumed to have been generated by the model in previous\ninteractions.\n", - "properties": { - "role": { - "type": "string", - "description": "The role of the message input. One of `user`, `assistant`, `system`, or\n`developer`.\n", - "enum": [ - "user", - "assistant", - "system", - "developer" - ] - }, - "content": { - "description": "Inputs to the model - can contain template strings.\n", - "anyOf": [ - { - "type": "string", - "title": "Text input", - "description": "A text input to the model.\n" - }, - { - "$ref": "#/components/schemas/InputTextContent" - }, - { - "type": "object", - "title": "Output text", - "description": "A text output from the model.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the output text. Always `output_text`.\n", - "enum": [ - "output_text" - ], - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text output from the model.\n" - } - }, - "required": [ - "type", - "text" - ] - }, - { - "type": "object", - "title": "Input image", - "description": "An image input to the model.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the image input. Always `input_image`.\n", - "enum": [ - "input_image" - ], - "x-stainless-const": true - }, - "image_url": { - "type": "string", - "description": "The URL of the image input.\n" - }, - "detail": { - "type": "string", - "description": "The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`.\n" - } - }, - "required": [ - "type", - "image_url" - ] - }, - { - "$ref": "#/components/schemas/InputAudio" - }, - { - "type": "array", - "title": "An array of Input text, Input image, and Input audio", - "description": "A list of inputs, each of which may be either an input text, input image, or input audio object.\n" - } - ] - }, - "type": { - "type": "string", - "description": "The type of the message input. Always `message`.\n", - "enum": [ - "message" - ], - "x-stainless-const": true - } - }, - "required": [ - "role", - "content" - ] - }, - "EvalJsonlFileContentSource": { - "type": "object", - "title": "EvalJsonlFileContentSource", - "properties": { - "type": { - "type": "string", - "enum": [ - "file_content" - ], - "default": "file_content", - "description": "The type of jsonl source. Always `file_content`.", - "x-stainless-const": true - }, - "content": { - "type": "array", - "items": { - "type": "object", - "properties": { - "item": { - "type": "object", - "additionalProperties": true - }, - "sample": { - "type": "object", - "additionalProperties": true - } - }, - "required": [ - "item" - ] - }, - "description": "The content of the jsonl file." - } - }, - "required": [ - "type", - "content" - ] - }, - "EvalJsonlFileIdSource": { - "type": "object", - "title": "EvalJsonlFileIdSource", - "properties": { - "type": { - "type": "string", - "enum": [ - "file_id" - ], - "default": "file_id", - "description": "The type of jsonl source. Always `file_id`.", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The identifier of the file." - } - }, - "required": [ - "type", - "id" - ] - }, - "EvalList": { - "type": "object", - "title": "EvalList", - "description": "An object representing a list of evals.\n", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "default": "list", - "description": "The type of this object. It is always set to \"list\".\n", - "x-stainless-const": true - }, - "data": { - "type": "array", - "description": "An array of eval objects.\n", - "items": { - "$ref": "#/components/schemas/Eval" - } - }, - "first_id": { - "type": "string", - "description": "The identifier of the first eval in the data array." - }, - "last_id": { - "type": "string", - "description": "The identifier of the last eval in the data array." - }, - "has_more": { - "type": "boolean", - "description": "Indicates whether there are more evals available." - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ], - "x-oaiMeta": { - "name": "The eval list object", - "group": "evals", - "example": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"eval\",\n \"id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"data_source_config\": {\n \"type\": \"custom\",\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"item\": {\n \"type\": \"object\",\n \"properties\": {\n \"input\": {\n \"type\": \"string\"\n },\n \"ground_truth\": {\n \"type\": \"string\"\n }\n },\n \"required\": [\n \"input\",\n \"ground_truth\"\n ]\n }\n },\n \"required\": [\n \"item\"\n ]\n }\n },\n \"testing_criteria\": [\n {\n \"name\": \"String check\",\n \"id\": \"String check-2eaf2d8d-d649-4335-8148-9535a7ca73c2\",\n \"type\": \"string_check\",\n \"input\": \"{{item.input}}\",\n \"reference\": \"{{item.ground_truth}}\",\n \"operation\": \"eq\"\n }\n ],\n \"name\": \"External Data Eval\",\n \"created_at\": 1739314509,\n \"metadata\": {},\n }\n ],\n \"first_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"last_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"has_more\": true\n}\n" - } - }, - "EvalLogsDataSourceConfig": { - "type": "object", - "title": "LogsDataSourceConfig", - "description": "A LogsDataSourceConfig which specifies the metadata property of your logs query.\nThis is usually metadata like `usecase=chatbot` or `prompt-version=v2`, etc.\nThe schema returned by this data source config is used to defined what variables are available in your evals.\n`item` and `sample` are both defined when using this data source config.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "logs" - ], - "default": "logs", - "description": "The type of data source. Always `logs`.", - "x-stainless-const": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "schema": { - "type": "object", - "description": "The json schema for the run data source items.\nLearn how to build JSON schemas [here](https://json-schema.org/).\n", - "additionalProperties": true - } - }, - "required": [ - "type", - "schema" - ], - "x-oaiMeta": { - "name": "The logs data source object for evals", - "group": "evals", - "example": "{\n \"type\": \"logs\",\n \"metadata\": {\n \"language\": \"english\"\n },\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"item\": {\n \"type\": \"object\"\n },\n \"sample\": {\n \"type\": \"object\"\n }\n },\n \"required\": [\n \"item\",\n \"sample\"\n }\n}\n" - } - }, - "EvalResponsesSource": { - "type": "object", - "title": "EvalResponsesSource", - "description": "A EvalResponsesSource object describing a run data source configuration.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "responses" - ], - "description": "The type of run data source. Always `responses`." - }, - "metadata": { - "type": "object", - "nullable": true, - "description": "Metadata filter for the responses. This is a query parameter used to select responses." - }, - "model": { - "type": "string", - "nullable": true, - "description": "The name of the model to find responses for. This is a query parameter used to select responses." - }, - "instructions_search": { - "type": "string", - "nullable": true, - "description": "Optional string to search the 'instructions' field. This is a query parameter used to select responses." - }, - "created_after": { - "type": "integer", - "minimum": 0, - "nullable": true, - "description": "Only include items created after this timestamp (inclusive). This is a query parameter used to select responses." - }, - "created_before": { - "type": "integer", - "minimum": 0, - "nullable": true, - "description": "Only include items created before this timestamp (inclusive). This is a query parameter used to select responses." - }, - "reasoning_effort": { - "$ref": "#/components/schemas/ReasoningEffort", - "nullable": true, - "description": "Optional reasoning effort parameter. This is a query parameter used to select responses." - }, - "temperature": { - "type": "number", - "nullable": true, - "description": "Sampling temperature. This is a query parameter used to select responses." - }, - "top_p": { - "type": "number", - "nullable": true, - "description": "Nucleus sampling parameter. This is a query parameter used to select responses." - }, - "users": { - "type": "array", - "items": { - "type": "string" - }, - "nullable": true, - "description": "List of user identifiers. This is a query parameter used to select responses." - }, - "tools": { - "type": "array", - "items": { - "type": "string" - }, - "nullable": true, - "description": "List of tool names. This is a query parameter used to select responses." - } - }, - "required": [ - "type" - ], - "x-oaiMeta": { - "name": "The run data source object used to configure an individual run", - "group": "eval runs", - "example": "{\n \"type\": \"responses\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"temperature\": 0.7,\n \"top_p\": 1.0,\n \"users\": [\"user1\", \"user2\"],\n \"tools\": [\"tool1\", \"tool2\"],\n \"instructions_search\": \"You are a coding assistant\"\n}\n" - } - }, - "EvalRun": { - "type": "object", - "title": "EvalRun", - "description": "A schema representing an evaluation run.\n", - "properties": { - "object": { - "type": "string", - "enum": [ - "eval.run" - ], - "default": "eval.run", - "description": "The type of the object. Always \"eval.run\".", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "Unique identifier for the evaluation run." - }, - "eval_id": { - "type": "string", - "description": "The identifier of the associated evaluation." - }, - "status": { - "type": "string", - "description": "The status of the evaluation run." - }, - "model": { - "type": "string", - "description": "The model that is evaluated, if applicable." - }, - "name": { - "type": "string", - "description": "The name of the evaluation run." - }, - "created_at": { - "type": "integer", - "description": "Unix timestamp (in seconds) when the evaluation run was created." - }, - "report_url": { - "type": "string", - "description": "The URL to the rendered evaluation run report on the UI dashboard." - }, - "result_counts": { - "type": "object", - "description": "Counters summarizing the outcomes of the evaluation run.", - "properties": { - "total": { - "type": "integer", - "description": "Total number of executed output items." - }, - "errored": { - "type": "integer", - "description": "Number of output items that resulted in an error." - }, - "failed": { - "type": "integer", - "description": "Number of output items that failed to pass the evaluation." - }, - "passed": { - "type": "integer", - "description": "Number of output items that passed the evaluation." - } - }, - "required": [ - "total", - "errored", - "failed", - "passed" - ] - }, - "per_model_usage": { - "type": "array", - "description": "Usage statistics for each model during the evaluation run.", - "items": { - "type": "object", - "properties": { - "model_name": { - "type": "string", - "description": "The name of the model.", - "x-stainless-naming": { - "python": { - "property_name": "run_model_name" - } - } - }, - "invocation_count": { - "type": "integer", - "description": "The number of invocations." - }, - "prompt_tokens": { - "type": "integer", - "description": "The number of prompt tokens used." - }, - "completion_tokens": { - "type": "integer", - "description": "The number of completion tokens generated." - }, - "total_tokens": { - "type": "integer", - "description": "The total number of tokens used." - }, - "cached_tokens": { - "type": "integer", - "description": "The number of tokens retrieved from cache." - } - }, - "required": [ - "model_name", - "invocation_count", - "prompt_tokens", - "completion_tokens", - "total_tokens", - "cached_tokens" - ] - } - }, - "per_testing_criteria_results": { - "type": "array", - "description": "Results per testing criteria applied during the evaluation run.", - "items": { - "type": "object", - "properties": { - "testing_criteria": { - "type": "string", - "description": "A description of the testing criteria." - }, - "passed": { - "type": "integer", - "description": "Number of tests passed for this criteria." - }, - "failed": { - "type": "integer", - "description": "Number of tests failed for this criteria." - } - }, - "required": [ - "testing_criteria", - "passed", - "failed" - ] - } - }, - "data_source": { - "type": "object", - "description": "Information about the run's data source.", - "anyOf": [ - { - "$ref": "#/components/schemas/CreateEvalJsonlRunDataSource" - }, - { - "$ref": "#/components/schemas/CreateEvalCompletionsRunDataSource" - }, - { - "$ref": "#/components/schemas/CreateEvalResponsesRunDataSource" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "error": { - "$ref": "#/components/schemas/EvalApiError" - } - }, - "required": [ - "object", - "id", - "eval_id", - "status", - "model", - "name", - "created_at", - "report_url", - "result_counts", - "per_model_usage", - "per_testing_criteria_results", - "data_source", - "metadata", - "error" - ], - "x-oaiMeta": { - "name": "The eval run object", - "group": "evals", - "example": "{\n \"object\": \"eval.run\",\n \"id\": \"evalrun_67e57965b480819094274e3a32235e4c\",\n \"eval_id\": \"eval_67e579652b548190aaa83ada4b125f47\",\n \"report_url\": \"https://platform.openai.com/evaluations/eval_67e579652b548190aaa83ada4b125f47?run_id=evalrun_67e57965b480819094274e3a32235e4c\",\n \"status\": \"queued\",\n \"model\": \"gpt-4o-mini\",\n \"name\": \"gpt-4o-mini\",\n \"created_at\": 1743092069,\n \"result_counts\": {\n \"total\": 0,\n \"errored\": 0,\n \"failed\": 0,\n \"passed\": 0\n },\n \"per_model_usage\": null,\n \"per_testing_criteria_results\": null,\n \"data_source\": {\n \"type\": \"completions\",\n \"source\": {\n \"type\": \"file_content\",\n \"content\": [\n {\n \"item\": {\n \"input\": \"Tech Company Launches Advanced Artificial Intelligence Platform\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"Central Bank Increases Interest Rates Amid Inflation Concerns\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"International Summit Addresses Climate Change Strategies\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Major Retailer Reports Record-Breaking Holiday Sales\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"National Team Qualifies for World Championship Finals\",\n \"ground_truth\": \"Sports\"\n }\n },\n {\n \"item\": {\n \"input\": \"Stock Markets Rally After Positive Economic Data Released\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"Global Manufacturer Announces Merger with Competitor\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"Breakthrough in Renewable Energy Technology Unveiled\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"World Leaders Sign Historic Climate Agreement\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Professional Athlete Sets New Record in Championship Event\",\n \"ground_truth\": \"Sports\"\n }\n },\n {\n \"item\": {\n \"input\": \"Financial Institutions Adapt to New Regulatory Requirements\",\n \"ground_truth\": \"Business\"\n }\n },\n {\n \"item\": {\n \"input\": \"Tech Conference Showcases Advances in Artificial Intelligence\",\n \"ground_truth\": \"Technology\"\n }\n },\n {\n \"item\": {\n \"input\": \"Global Markets Respond to Oil Price Fluctuations\",\n \"ground_truth\": \"Markets\"\n }\n },\n {\n \"item\": {\n \"input\": \"International Cooperation Strengthened Through New Treaty\",\n \"ground_truth\": \"World\"\n }\n },\n {\n \"item\": {\n \"input\": \"Sports League Announces Revised Schedule for Upcoming Season\",\n \"ground_truth\": \"Sports\"\n }\n }\n ]\n },\n \"input_messages\": {\n \"type\": \"template\",\n \"template\": [\n {\n \"type\": \"message\",\n \"role\": \"developer\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\\n\\n# Steps\\n\\n1. Analyze the content of the news headline to understand its primary focus.\\n2. Extract the subject matter, identifying any key indicators or keywords.\\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\\n4. Ensure only one category is selected per headline.\\n\\n# Output Format\\n\\nRespond with the chosen category as a single word. For instance: \\\"Technology\\\", \\\"Markets\\\", \\\"World\\\", \\\"Business\\\", or \\\"Sports\\\".\\n\\n# Examples\\n\\n**Input**: \\\"Apple Unveils New iPhone Model, Featuring Advanced AI Features\\\" \\n**Output**: \\\"Technology\\\"\\n\\n**Input**: \\\"Global Stocks Mixed as Investors Await Central Bank Decisions\\\" \\n**Output**: \\\"Markets\\\"\\n\\n**Input**: \\\"War in Ukraine: Latest Updates on Negotiation Status\\\" \\n**Output**: \\\"World\\\"\\n\\n**Input**: \\\"Microsoft in Talks to Acquire Gaming Company for $2 Billion\\\" \\n**Output**: \\\"Business\\\"\\n\\n**Input**: \\\"Manchester United Secures Win in Premier League Football Match\\\" \\n**Output**: \\\"Sports\\\" \\n\\n# Notes\\n\\n- If the headline appears to fit into more than one category, choose the most dominant theme.\\n- Keywords or phrases such as \\\"stocks\\\", \\\"company acquisition\\\", \\\"match\\\", or technological brands can be good indicators for classification.\\n\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"{{item.input}}\"\n }\n }\n ]\n },\n \"model\": \"gpt-4o-mini\",\n \"sampling_params\": {\n \"seed\": 42,\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_completions_tokens\": 2048\n }\n },\n \"error\": null,\n \"metadata\": {}\n}\n" - } - }, - "EvalRunList": { - "type": "object", - "title": "EvalRunList", - "description": "An object representing a list of runs for an evaluation.\n", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "default": "list", - "description": "The type of this object. It is always set to \"list\".\n", - "x-stainless-const": true - }, - "data": { - "type": "array", - "description": "An array of eval run objects.\n", - "items": { - "$ref": "#/components/schemas/EvalRun" - } - }, - "first_id": { - "type": "string", - "description": "The identifier of the first eval run in the data array." - }, - "last_id": { - "type": "string", - "description": "The identifier of the last eval run in the data array." - }, - "has_more": { - "type": "boolean", - "description": "Indicates whether there are more evals available." - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ], - "x-oaiMeta": { - "name": "The eval run list object", - "group": "evals", - "example": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"eval.run\",\n \"id\": \"evalrun_67b7fbdad46c819092f6fe7a14189620\",\n \"eval_id\": \"eval_67b7fa9a81a88190ab4aa417e397ea21\",\n \"report_url\": \"https://platform.openai.com/evaluations/eval_67b7fa9a81a88190ab4aa417e397ea21?run_id=evalrun_67b7fbdad46c819092f6fe7a14189620\",\n \"status\": \"completed\",\n \"model\": \"o3-mini\",\n \"name\": \"Academic Assistant\",\n \"created_at\": 1740110812,\n \"result_counts\": {\n \"total\": 171,\n \"errored\": 0,\n \"failed\": 80,\n \"passed\": 91\n },\n \"per_model_usage\": null,\n \"per_testing_criteria_results\": [\n {\n \"testing_criteria\": \"String check grader\",\n \"passed\": 91,\n \"failed\": 80\n }\n ],\n \"run_data_source\": {\n \"type\": \"completions\",\n \"template_messages\": [\n {\n \"type\": \"message\",\n \"role\": \"system\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"You are a helpful assistant.\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Hello, can you help me with my homework?\"\n }\n }\n ],\n \"datasource_reference\": null,\n \"model\": \"o3-mini\",\n \"max_completion_tokens\": null,\n \"seed\": null,\n \"temperature\": null,\n \"top_p\": null\n },\n \"error\": null,\n \"metadata\": {\"test\": \"synthetics\"}\n }\n ],\n \"first_id\": \"evalrun_67abd54d60ec8190832b46859da808f7\",\n \"last_id\": \"evalrun_67abd54d60ec8190832b46859da808f7\",\n \"has_more\": false\n}\n" - } - }, - "EvalRunOutputItem": { - "type": "object", - "title": "EvalRunOutputItem", - "description": "A schema representing an evaluation run output item.\n", - "properties": { - "object": { - "type": "string", - "enum": [ - "eval.run.output_item" - ], - "default": "eval.run.output_item", - "description": "The type of the object. Always \"eval.run.output_item\".", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "Unique identifier for the evaluation run output item." - }, - "run_id": { - "type": "string", - "description": "The identifier of the evaluation run associated with this output item." - }, - "eval_id": { - "type": "string", - "description": "The identifier of the evaluation group." - }, - "created_at": { - "type": "integer", - "description": "Unix timestamp (in seconds) when the evaluation run was created." - }, - "status": { - "type": "string", - "description": "The status of the evaluation run." - }, - "datasource_item_id": { - "type": "integer", - "description": "The identifier for the data source item." - }, - "datasource_item": { - "type": "object", - "description": "Details of the input data source item.", - "additionalProperties": true - }, - "results": { - "type": "array", - "description": "A list of results from the evaluation run.", - "items": { - "type": "object", - "description": "A result object.", - "additionalProperties": true - } - }, - "sample": { - "type": "object", - "description": "A sample containing the input and output of the evaluation run.", - "properties": { - "input": { - "type": "array", - "description": "An array of input messages.", - "items": { - "type": "object", - "description": "An input message.", - "properties": { - "role": { - "type": "string", - "description": "The role of the message sender (e.g., system, user, developer)." - }, - "content": { - "type": "string", - "description": "The content of the message." - } - }, - "required": [ - "role", - "content" - ] - } - }, - "output": { - "type": "array", - "description": "An array of output messages.", - "items": { - "type": "object", - "properties": { - "role": { - "type": "string", - "description": "The role of the message (e.g. \"system\", \"assistant\", \"user\")." - }, - "content": { - "type": "string", - "description": "The content of the message." - } - } - } - }, - "finish_reason": { - "type": "string", - "description": "The reason why the sample generation was finished." - }, - "model": { - "type": "string", - "description": "The model used for generating the sample." - }, - "usage": { - "type": "object", - "description": "Token usage details for the sample.", - "properties": { - "total_tokens": { - "type": "integer", - "description": "The total number of tokens used." - }, - "completion_tokens": { - "type": "integer", - "description": "The number of completion tokens generated." - }, - "prompt_tokens": { - "type": "integer", - "description": "The number of prompt tokens used." - }, - "cached_tokens": { - "type": "integer", - "description": "The number of tokens retrieved from cache." - } - }, - "required": [ - "total_tokens", - "completion_tokens", - "prompt_tokens", - "cached_tokens" - ] - }, - "error": { - "$ref": "#/components/schemas/EvalApiError" - }, - "temperature": { - "type": "number", - "description": "The sampling temperature used." - }, - "max_completion_tokens": { - "type": "integer", - "description": "The maximum number of tokens allowed for completion." - }, - "top_p": { - "type": "number", - "description": "The top_p value used for sampling." - }, - "seed": { - "type": "integer", - "description": "The seed used for generating the sample." - } - }, - "required": [ - "input", - "output", - "finish_reason", - "model", - "usage", - "error", - "temperature", - "max_completion_tokens", - "top_p", - "seed" - ] - } - }, - "required": [ - "object", - "id", - "run_id", - "eval_id", - "created_at", - "status", - "datasource_item_id", - "datasource_item", - "results", - "sample" - ], - "x-oaiMeta": { - "name": "The eval run output item object", - "group": "evals", - "example": "{\n \"object\": \"eval.run.output_item\",\n \"id\": \"outputitem_67abd55eb6548190bb580745d5644a33\",\n \"run_id\": \"evalrun_67abd54d60ec8190832b46859da808f7\",\n \"eval_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"created_at\": 1739314509,\n \"status\": \"pass\",\n \"datasource_item_id\": 137,\n \"datasource_item\": {\n \"teacher\": \"To grade essays, I only check for style, content, and grammar.\",\n \"student\": \"I am a student who is trying to write the best essay.\"\n },\n \"results\": [\n {\n \"name\": \"String Check Grader\",\n \"type\": \"string-check-grader\",\n \"score\": 1.0,\n \"passed\": true,\n }\n ],\n \"sample\": {\n \"input\": [\n {\n \"role\": \"system\",\n \"content\": \"You are an evaluator bot...\"\n },\n {\n \"role\": \"user\",\n \"content\": \"You are assessing...\"\n }\n ],\n \"output\": [\n {\n \"role\": \"assistant\",\n \"content\": \"The rubric is not clear nor concise.\"\n }\n ],\n \"finish_reason\": \"stop\",\n \"model\": \"gpt-4o-2024-08-06\",\n \"usage\": {\n \"total_tokens\": 521,\n \"completion_tokens\": 2,\n \"prompt_tokens\": 519,\n \"cached_tokens\": 0\n },\n \"error\": null,\n \"temperature\": 1.0,\n \"max_completion_tokens\": 2048,\n \"top_p\": 1.0,\n \"seed\": 42\n }\n}\n" - } - }, - "EvalRunOutputItemList": { - "type": "object", - "title": "EvalRunOutputItemList", - "description": "An object representing a list of output items for an evaluation run.\n", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "default": "list", - "description": "The type of this object. It is always set to \"list\".\n", - "x-stainless-const": true - }, - "data": { - "type": "array", - "description": "An array of eval run output item objects.\n", - "items": { - "$ref": "#/components/schemas/EvalRunOutputItem" - } - }, - "first_id": { - "type": "string", - "description": "The identifier of the first eval run output item in the data array." - }, - "last_id": { - "type": "string", - "description": "The identifier of the last eval run output item in the data array." - }, - "has_more": { - "type": "boolean", - "description": "Indicates whether there are more eval run output items available." - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ], - "x-oaiMeta": { - "name": "The eval run output item list object", - "group": "evals", - "example": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"eval.run.output_item\",\n \"id\": \"outputitem_67abd55eb6548190bb580745d5644a33\",\n \"run_id\": \"evalrun_67abd54d60ec8190832b46859da808f7\",\n \"eval_id\": \"eval_67abd54d9b0081909a86353f6fb9317a\",\n \"created_at\": 1739314509,\n \"status\": \"pass\",\n \"datasource_item_id\": 137,\n \"datasource_item\": {\n \"teacher\": \"To grade essays, I only check for style, content, and grammar.\",\n \"student\": \"I am a student who is trying to write the best essay.\"\n },\n \"results\": [\n {\n \"name\": \"String Check Grader\",\n \"type\": \"string-check-grader\",\n \"score\": 1.0,\n \"passed\": true,\n }\n ],\n \"sample\": {\n \"input\": [\n {\n \"role\": \"system\",\n \"content\": \"You are an evaluator bot...\"\n },\n {\n \"role\": \"user\",\n \"content\": \"You are assessing...\"\n }\n ],\n \"output\": [\n {\n \"role\": \"assistant\",\n \"content\": \"The rubric is not clear nor concise.\"\n }\n ],\n \"finish_reason\": \"stop\",\n \"model\": \"gpt-4o-2024-08-06\",\n \"usage\": {\n \"total_tokens\": 521,\n \"completion_tokens\": 2,\n \"prompt_tokens\": 519,\n \"cached_tokens\": 0\n },\n \"error\": null,\n \"temperature\": 1.0,\n \"max_completion_tokens\": 2048,\n \"top_p\": 1.0,\n \"seed\": 42\n }\n },\n ],\n \"first_id\": \"outputitem_67abd55eb6548190bb580745d5644a33\",\n \"last_id\": \"outputitem_67abd55eb6548190bb580745d5644a33\",\n \"has_more\": false\n}\n" - } - }, - "EvalStoredCompletionsDataSourceConfig": { - "type": "object", - "title": "StoredCompletionsDataSourceConfig", - "description": "Deprecated in favor of LogsDataSourceConfig.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "stored_completions" - ], - "default": "stored_completions", - "description": "The type of data source. Always `stored_completions`.", - "x-stainless-const": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "schema": { - "type": "object", - "description": "The json schema for the run data source items.\nLearn how to build JSON schemas [here](https://json-schema.org/).\n", - "additionalProperties": true - } - }, - "required": [ - "type", - "schema" - ], - "deprecated": true, - "x-oaiMeta": { - "name": "The stored completions data source object for evals", - "group": "evals", - "example": "{\n \"type\": \"stored_completions\",\n \"metadata\": {\n \"language\": \"english\"\n },\n \"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"item\": {\n \"type\": \"object\"\n },\n \"sample\": {\n \"type\": \"object\"\n }\n },\n \"required\": [\n \"item\",\n \"sample\"\n }\n}\n" - } - }, - "EvalStoredCompletionsSource": { - "type": "object", - "title": "StoredCompletionsRunDataSource", - "description": "A StoredCompletionsRunDataSource configuration describing a set of filters\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "stored_completions" - ], - "default": "stored_completions", - "description": "The type of source. Always `stored_completions`.", - "x-stainless-const": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "model": { - "type": "string", - "nullable": true, - "description": "An optional model to filter by (e.g., 'gpt-4o')." - }, - "created_after": { - "type": "integer", - "nullable": true, - "description": "An optional Unix timestamp to filter items created after this time." - }, - "created_before": { - "type": "integer", - "nullable": true, - "description": "An optional Unix timestamp to filter items created before this time." - }, - "limit": { - "type": "integer", - "nullable": true, - "description": "An optional maximum number of items to return." - } - }, - "required": [ - "type" - ], - "x-oaiMeta": { - "name": "The stored completions data source object used to configure an individual run", - "group": "eval runs", - "example": "{\n \"type\": \"stored_completions\",\n \"model\": \"gpt-4o\",\n \"created_after\": 1668124800,\n \"created_before\": 1668124900,\n \"limit\": 100,\n \"metadata\": {}\n}\n" - } - }, - "FileExpirationAfter": { - "type": "object", - "title": "File expiration policy", - "description": "The expiration policy for a file. By default, files with `purpose=batch` expire after 30 days and all other files are persisted until they are manually deleted.", - "properties": { - "anchor": { - "description": "Anchor timestamp after which the expiration policy applies. Supported anchors: `created_at`.", - "type": "string", - "enum": [ - "created_at" - ], - "x-stainless-const": true - }, - "seconds": { - "description": "The number of seconds after the anchor time that the file will expire. Must be between 3600 (1 hour) and 2592000 (30 days).", - "type": "integer", - "minimum": 3600, - "maximum": 2592000 - } - }, - "required": [ - "anchor", - "seconds" - ] - }, - "FilePath": { - "type": "object", - "title": "File path", - "description": "A path to a file.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the file path. Always `file_path`.\n", - "enum": [ - "file_path" - ], - "x-stainless-const": true - }, - "file_id": { - "type": "string", - "description": "The ID of the file.\n" - }, - "index": { - "type": "integer", - "description": "The index of the file in the list of files.\n" - } - }, - "required": [ - "type", - "file_id", - "index" - ] - }, - "FileSearchRanker": { - "type": "string", - "description": "The ranker to use for the file search. If not specified will use the `auto` ranker.", - "enum": [ - "auto", - "default_2024_08_21" - ] - }, - "FileSearchRankingOptions": { - "title": "File search tool call ranking options", - "type": "object", - "description": "The ranking options for the file search. If not specified, the file search tool will use the `auto` ranker and a score_threshold of 0.\n\nSee the [file search tool documentation](https://platform.openai.com/docs/assistants/tools/file-search#customizing-file-search-settings) for more information.\n", - "properties": { - "ranker": { - "$ref": "#/components/schemas/FileSearchRanker" - }, - "score_threshold": { - "type": "number", - "description": "The score threshold for the file search. All values must be a floating point number between 0 and 1.", - "minimum": 0, - "maximum": 1 - } - }, - "required": [ - "score_threshold" - ] - }, - "FileSearchToolCall": { - "type": "object", - "title": "File search tool call", - "description": "The results of a file search tool call. See the \n[file search guide](https://platform.openai.com/docs/guides/tools-file-search) for more information.\n", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the file search tool call.\n" - }, - "type": { - "type": "string", - "enum": [ - "file_search_call" - ], - "description": "The type of the file search tool call. Always `file_search_call`.\n", - "x-stainless-const": true - }, - "status": { - "type": "string", - "description": "The status of the file search tool call. One of `in_progress`, \n`searching`, `incomplete` or `failed`,\n", - "enum": [ - "in_progress", - "searching", - "completed", - "incomplete", - "failed" - ] - }, - "queries": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The queries used to search for files.\n" - }, - "results": { - "type": "array", - "description": "The results of the file search tool call.\n", - "items": { - "type": "object", - "properties": { - "file_id": { - "type": "string", - "description": "The unique ID of the file.\n" - }, - "text": { - "type": "string", - "description": "The text that was retrieved from the file.\n" - }, - "filename": { - "type": "string", - "description": "The name of the file.\n" - }, - "attributes": { - "$ref": "#/components/schemas/VectorStoreFileAttributes" - }, - "score": { - "type": "number", - "format": "float", - "description": "The relevance score of the file - a value between 0 and 1.\n" - } - } - }, - "nullable": true - } - }, - "required": [ - "id", - "type", - "status", - "queries" - ] - }, - "FineTuneChatCompletionRequestAssistantMessage": { - "allOf": [ - { - "type": "object", - "title": "Assistant message", - "deprecated": false, - "properties": { - "weight": { - "type": "integer", - "enum": [ - 0, - 1 - ], - "description": "Controls whether the assistant message is trained against (0 or 1)" - } - } - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestAssistantMessage" - } - ], - "required": [ - "role" - ] - }, - "FineTuneChatRequestInput": { - "type": "object", - "description": "The per-line training example of a fine-tuning input file for chat models using the supervised method.\nInput messages may contain text or image content only. Audio and file input messages\nare not currently supported for fine-tuning.\n", - "properties": { - "messages": { - "type": "array", - "minItems": 1, - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestSystemMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestUserMessage" - }, - { - "$ref": "#/components/schemas/FineTuneChatCompletionRequestAssistantMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestToolMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestFunctionMessage" - } - ] - } - }, - "tools": { - "type": "array", - "description": "A list of tools the model may generate JSON inputs for.", - "items": { - "$ref": "#/components/schemas/ChatCompletionTool" - } - }, - "parallel_tool_calls": { - "$ref": "#/components/schemas/ParallelToolCalls" - }, - "functions": { - "deprecated": true, - "description": "A list of functions the model may generate JSON inputs for.", - "type": "array", - "minItems": 1, - "maxItems": 128, - "items": { - "$ref": "#/components/schemas/ChatCompletionFunctions" - } - } - }, - "x-oaiMeta": { - "name": "Training format for chat models using the supervised method", - "example": "{\n \"messages\": [\n { \"role\": \"user\", \"content\": \"What is the weather in San Francisco?\" },\n {\n \"role\": \"assistant\",\n \"tool_calls\": [\n {\n \"id\": \"call_id\",\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"arguments\": \"{\\\"location\\\": \\\"San Francisco, USA\\\", \\\"format\\\": \\\"celsius\\\"}\"\n }\n }\n ]\n }\n ],\n \"parallel_tool_calls\": false,\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"Get the current weather\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and country, eg. San Francisco, USA\"\n },\n \"format\": { \"type\": \"string\", \"enum\": [\"celsius\", \"fahrenheit\"] }\n },\n \"required\": [\"location\", \"format\"]\n }\n }\n }\n ]\n}\n" - } - }, - "FineTuneDPOHyperparameters": { - "type": "object", - "description": "The hyperparameters used for the DPO fine-tuning job.", - "properties": { - "beta": { - "description": "The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.\n", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "number", - "minimum": 0, - "maximum": 2, - "exclusiveMinimum": true - } - ] - }, - "batch_size": { - "description": "Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "integer", - "minimum": 1, - "maximum": 256 - } - ] - }, - "learning_rate_multiplier": { - "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.\n", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "number", - "minimum": 0, - "exclusiveMinimum": true - } - ] - }, - "n_epochs": { - "description": "The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "integer", - "minimum": 1, - "maximum": 50 - } - ] - } - } - }, - "FineTuneDPOMethod": { - "type": "object", - "description": "Configuration for the DPO fine-tuning method.", - "properties": { - "hyperparameters": { - "$ref": "#/components/schemas/FineTuneDPOHyperparameters" - } - } - }, - "FineTuneMethod": { - "type": "object", - "description": "The method used for fine-tuning.", - "properties": { - "type": { - "type": "string", - "description": "The type of method. Is either `supervised`, `dpo`, or `reinforcement`.", - "enum": [ - "supervised", - "dpo", - "reinforcement" - ] - }, - "supervised": { - "$ref": "#/components/schemas/FineTuneSupervisedMethod" - }, - "dpo": { - "$ref": "#/components/schemas/FineTuneDPOMethod" - }, - "reinforcement": { - "$ref": "#/components/schemas/FineTuneReinforcementMethod" - } - }, - "required": [ - "type" - ] - }, - "FineTunePreferenceRequestInput": { - "type": "object", - "description": "The per-line training example of a fine-tuning input file for chat models using the dpo method.\nInput messages may contain text or image content only. Audio and file input messages\nare not currently supported for fine-tuning.\n", - "properties": { - "input": { - "type": "object", - "properties": { - "messages": { - "type": "array", - "minItems": 1, - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestSystemMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestUserMessage" - }, - { - "$ref": "#/components/schemas/FineTuneChatCompletionRequestAssistantMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestToolMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestFunctionMessage" - } - ] - } - }, - "tools": { - "type": "array", - "description": "A list of tools the model may generate JSON inputs for.", - "items": { - "$ref": "#/components/schemas/ChatCompletionTool" - } - }, - "parallel_tool_calls": { - "$ref": "#/components/schemas/ParallelToolCalls" - } - } - }, - "preferred_output": { - "type": "array", - "description": "The preferred completion message for the output.", - "maxItems": 1, - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestAssistantMessage" - } - ] - } - }, - "non_preferred_output": { - "type": "array", - "description": "The non-preferred completion message for the output.", - "maxItems": 1, - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestAssistantMessage" - } - ] - } - } - }, - "x-oaiMeta": { - "name": "Training format for chat models using the preference method", - "example": "{\n \"input\": {\n \"messages\": [\n { \"role\": \"user\", \"content\": \"What is the weather in San Francisco?\" }\n ]\n },\n \"preferred_output\": [\n {\n \"role\": \"assistant\",\n \"content\": \"The weather in San Francisco is 70 degrees Fahrenheit.\"\n }\n ],\n \"non_preferred_output\": [\n {\n \"role\": \"assistant\",\n \"content\": \"The weather in San Francisco is 21 degrees Celsius.\"\n }\n ]\n}\n" - } - }, - "FineTuneReinforcementHyperparameters": { - "type": "object", - "description": "The hyperparameters used for the reinforcement fine-tuning job.", - "properties": { - "batch_size": { - "description": "Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "integer", - "minimum": 1, - "maximum": 256 - } - ] - }, - "learning_rate_multiplier": { - "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.\n", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "number", - "minimum": 0, - "exclusiveMinimum": true - } - ] - }, - "n_epochs": { - "description": "The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "integer", - "minimum": 1, - "maximum": 50 - } - ] - }, - "reasoning_effort": { - "description": "Level of reasoning effort.\n", - "type": "string", - "enum": [ - "default", - "low", - "medium", - "high" - ], - "default": "default" - }, - "compute_multiplier": { - "description": "Multiplier on amount of compute used for exploring search space during training.\n", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "number", - "minimum": 0.00001, - "maximum": 10, - "exclusiveMinimum": true - } - ] - }, - "eval_interval": { - "description": "The number of training steps between evaluation runs.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "integer", - "minimum": 1 - } - ] - }, - "eval_samples": { - "description": "Number of evaluation samples to generate per training step.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "integer", - "minimum": 1 - } - ] - } - } - }, - "FineTuneReinforcementMethod": { - "type": "object", - "description": "Configuration for the reinforcement fine-tuning method.", - "properties": { - "grader": { - "type": "object", - "description": "The grader used for the fine-tuning job.", - "anyOf": [ - { - "$ref": "#/components/schemas/GraderStringCheck" - }, - { - "$ref": "#/components/schemas/GraderTextSimilarity" - }, - { - "$ref": "#/components/schemas/GraderPython" - }, - { - "$ref": "#/components/schemas/GraderScoreModel" - }, - { - "$ref": "#/components/schemas/GraderMulti" - } - ] - }, - "hyperparameters": { - "$ref": "#/components/schemas/FineTuneReinforcementHyperparameters" - } - }, - "required": [ - "grader" - ] - }, - "FineTuneReinforcementRequestInput": { - "type": "object", - "unevaluatedProperties": true, - "description": "Per-line training example for reinforcement fine-tuning. Note that `messages` and `tools` are the only reserved keywords.\nAny other arbitrary key-value data can be included on training datapoints and will be available to reference during grading under the `{{ item.XXX }}` template variable.\nInput messages may contain text or image content only. Audio and file input messages\nare not currently supported for fine-tuning.\n", - "required": [ - "messages" - ], - "properties": { - "messages": { - "type": "array", - "minItems": 1, - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/ChatCompletionRequestDeveloperMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestUserMessage" - }, - { - "$ref": "#/components/schemas/FineTuneChatCompletionRequestAssistantMessage" - }, - { - "$ref": "#/components/schemas/ChatCompletionRequestToolMessage" - } - ] - } - }, - "tools": { - "type": "array", - "description": "A list of tools the model may generate JSON inputs for.", - "items": { - "$ref": "#/components/schemas/ChatCompletionTool" - } - } - }, - "x-oaiMeta": { - "name": "Training format for reasoning models using the reinforcement method", - "example": "{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Your task is to take a chemical in SMILES format and predict the number of hydrobond bond donors and acceptors according to Lipinkski's rule. CCN(CC)CCC(=O)c1sc(N)nc1C\"\n },\n ],\n \"reference_answer\": {\n \"donor_bond_counts\": 5,\n \"acceptor_bond_counts\": 7\n }\n}\n" - } - }, - "FineTuneSupervisedHyperparameters": { - "type": "object", - "description": "The hyperparameters used for the fine-tuning job.", - "properties": { - "batch_size": { - "description": "Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "integer", - "minimum": 1, - "maximum": 256 - } - ] - }, - "learning_rate_multiplier": { - "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.\n", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "number", - "minimum": 0, - "exclusiveMinimum": true - } - ] - }, - "n_epochs": { - "description": "The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "integer", - "minimum": 1, - "maximum": 50 - } - ] - } - } - }, - "FineTuneSupervisedMethod": { - "type": "object", - "description": "Configuration for the supervised fine-tuning method.", - "properties": { - "hyperparameters": { - "$ref": "#/components/schemas/FineTuneSupervisedHyperparameters" - } - } - }, - "FineTuningCheckpointPermission": { - "type": "object", - "title": "FineTuningCheckpointPermission", - "description": "The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint.\n", - "properties": { - "id": { - "type": "string", - "description": "The permission identifier, which can be referenced in the API endpoints." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the permission was created." - }, - "project_id": { - "type": "string", - "description": "The project identifier that the permission is for." - }, - "object": { - "type": "string", - "description": "The object type, which is always \"checkpoint.permission\".", - "enum": [ - "checkpoint.permission" - ], - "x-stainless-const": true - } - }, - "required": [ - "created_at", - "id", - "object", - "project_id" - ], - "x-oaiMeta": { - "name": "The fine-tuned model checkpoint permission object", - "example": "{\n \"object\": \"checkpoint.permission\",\n \"id\": \"cp_zc4Q7MP6XxulcVzj4MZdwsAB\",\n \"created_at\": 1712211699,\n \"project_id\": \"proj_abGMw1llN8IrBb6SvvY5A1iH\"\n}\n" - } - }, - "FineTuningIntegration": { - "type": "object", - "title": "Fine-Tuning Job Integration", - "required": [ - "type", - "wandb" - ], - "properties": { - "type": { - "type": "string", - "description": "The type of the integration being enabled for the fine-tuning job", - "enum": [ - "wandb" - ], - "x-stainless-const": true - }, - "wandb": { - "type": "object", - "description": "The settings for your integration with Weights and Biases. This payload specifies the project that\nmetrics will be sent to. Optionally, you can set an explicit display name for your run, add tags\nto your run, and set a default entity (team, username, etc) to be associated with your run.\n", - "required": [ - "project" - ], - "properties": { - "project": { - "description": "The name of the project that the new run will be created under.\n", - "type": "string", - "example": "my-wandb-project" - }, - "name": { - "description": "A display name to set for the run. If not set, we will use the Job ID as the name.\n", - "nullable": true, - "type": "string" - }, - "entity": { - "description": "The entity to use for the run. This allows you to set the team or username of the WandB user that you would\nlike associated with the run. If not set, the default entity for the registered WandB API key is used.\n", - "nullable": true, - "type": "string" - }, - "tags": { - "description": "A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some\ndefault tags are generated by OpenAI: \"openai/finetune\", \"openai/{base-model}\", \"openai/{ftjob-abcdef}\".\n", - "type": "array", - "items": { - "type": "string", - "example": "custom-tag" - } - } - } - } - } - }, - "FineTuningJob": { - "type": "object", - "title": "FineTuningJob", - "description": "The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.\n", - "properties": { - "id": { - "type": "string", - "description": "The object identifier, which can be referenced in the API endpoints." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the fine-tuning job was created." - }, - "error": { - "type": "object", - "nullable": true, - "description": "For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.", - "properties": { - "code": { - "type": "string", - "description": "A machine-readable error code." - }, - "message": { - "type": "string", - "description": "A human-readable error message." - }, - "param": { - "type": "string", - "description": "The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.", - "nullable": true - } - }, - "required": [ - "code", - "message", - "param" - ] - }, - "fine_tuned_model": { - "type": "string", - "nullable": true, - "description": "The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running." - }, - "finished_at": { - "type": "integer", - "nullable": true, - "description": "The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running." - }, - "hyperparameters": { - "type": "object", - "description": "The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs.", - "properties": { - "batch_size": { - "nullable": true, - "description": "Number of examples in each batch. A larger batch size means that model parameters\nare updated less frequently, but with lower variance.\n", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true, - "title": "Auto" - }, - { - "type": "integer", - "minimum": 1, - "maximum": 256, - "title": "Manual" - } - ] - }, - "learning_rate_multiplier": { - "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid\noverfitting.\n", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true, - "title": "Auto" - }, - { - "type": "number", - "minimum": 0, - "exclusiveMinimum": true - } - ] - }, - "n_epochs": { - "description": "The number of epochs to train the model for. An epoch refers to one full cycle\nthrough the training dataset.\n", - "default": "auto", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "x-stainless-const": true, - "title": "Auto" - }, - { - "type": "integer", - "minimum": 1, - "maximum": 50 - } - ] - } - } - }, - "model": { - "type": "string", - "description": "The base model that is being fine-tuned." - }, - "object": { - "type": "string", - "description": "The object type, which is always \"fine_tuning.job\".", - "enum": [ - "fine_tuning.job" - ], - "x-stainless-const": true - }, - "organization_id": { - "type": "string", - "description": "The organization that owns the fine-tuning job." - }, - "result_files": { - "type": "array", - "description": "The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).", - "items": { - "type": "string", - "example": "file-abc123" - } - }, - "status": { - "type": "string", - "description": "The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.", - "enum": [ - "validating_files", - "queued", - "running", - "succeeded", - "failed", - "cancelled" - ] - }, - "trained_tokens": { - "type": "integer", - "nullable": true, - "description": "The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running." - }, - "training_file": { - "type": "string", - "description": "The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents)." - }, - "validation_file": { - "type": "string", - "nullable": true, - "description": "The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents)." - }, - "integrations": { - "type": "array", - "nullable": true, - "description": "A list of integrations to enable for this fine-tuning job.", - "maxItems": 5, - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/FineTuningIntegration" - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "seed": { - "type": "integer", - "description": "The seed used for the fine-tuning job." - }, - "estimated_finish": { - "type": "integer", - "nullable": true, - "description": "The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running." - }, - "method": { - "$ref": "#/components/schemas/FineTuneMethod" - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - }, - "required": [ - "created_at", - "error", - "finished_at", - "fine_tuned_model", - "hyperparameters", - "id", - "model", - "object", - "organization_id", - "result_files", - "status", - "trained_tokens", - "training_file", - "validation_file", - "seed" - ], - "x-oaiMeta": { - "name": "The fine-tuning job object", - "example": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"davinci-002\",\n \"created_at\": 1692661014,\n \"finished_at\": 1692661190,\n \"fine_tuned_model\": \"ft:davinci-002:my-org:custom_suffix:7q8mpxmy\",\n \"organization_id\": \"org-123\",\n \"result_files\": [\n \"file-abc123\"\n ],\n \"status\": \"succeeded\",\n \"validation_file\": null,\n \"training_file\": \"file-abc123\",\n \"hyperparameters\": {\n \"n_epochs\": 4,\n \"batch_size\": 1,\n \"learning_rate_multiplier\": 1.0\n },\n \"trained_tokens\": 5768,\n \"integrations\": [],\n \"seed\": 0,\n \"estimated_finish\": 0,\n \"method\": {\n \"type\": \"supervised\",\n \"supervised\": {\n \"hyperparameters\": {\n \"n_epochs\": 4,\n \"batch_size\": 1,\n \"learning_rate_multiplier\": 1.0\n }\n }\n },\n \"metadata\": {\n \"key\": \"value\"\n }\n}\n" - } - }, - "FineTuningJobCheckpoint": { - "type": "object", - "title": "FineTuningJobCheckpoint", - "description": "The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use.\n", - "properties": { - "id": { - "type": "string", - "description": "The checkpoint identifier, which can be referenced in the API endpoints." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the checkpoint was created." - }, - "fine_tuned_model_checkpoint": { - "type": "string", - "description": "The name of the fine-tuned checkpoint model that is created." - }, - "step_number": { - "type": "integer", - "description": "The step number that the checkpoint was created at." - }, - "metrics": { - "type": "object", - "description": "Metrics at the step number during the fine-tuning job.", - "properties": { - "step": { - "type": "number" - }, - "train_loss": { - "type": "number" - }, - "train_mean_token_accuracy": { - "type": "number" - }, - "valid_loss": { - "type": "number" - }, - "valid_mean_token_accuracy": { - "type": "number" - }, - "full_valid_loss": { - "type": "number" - }, - "full_valid_mean_token_accuracy": { - "type": "number" - } - } - }, - "fine_tuning_job_id": { - "type": "string", - "description": "The name of the fine-tuning job that this checkpoint was created from." - }, - "object": { - "type": "string", - "description": "The object type, which is always \"fine_tuning.job.checkpoint\".", - "enum": [ - "fine_tuning.job.checkpoint" - ], - "x-stainless-const": true - } - }, - "required": [ - "created_at", - "fine_tuning_job_id", - "fine_tuned_model_checkpoint", - "id", - "metrics", - "object", - "step_number" - ], - "x-oaiMeta": { - "name": "The fine-tuning job checkpoint object", - "example": "{\n \"object\": \"fine_tuning.job.checkpoint\",\n \"id\": \"ftckpt_qtZ5Gyk4BLq1SfLFWp3RtO3P\",\n \"created_at\": 1712211699,\n \"fine_tuned_model_checkpoint\": \"ft:gpt-4o-mini-2024-07-18:my-org:custom_suffix:9ABel2dg:ckpt-step-88\",\n \"fine_tuning_job_id\": \"ftjob-fpbNQ3H1GrMehXRf8cO97xTN\",\n \"metrics\": {\n \"step\": 88,\n \"train_loss\": 0.478,\n \"train_mean_token_accuracy\": 0.924,\n \"valid_loss\": 10.112,\n \"valid_mean_token_accuracy\": 0.145,\n \"full_valid_loss\": 0.567,\n \"full_valid_mean_token_accuracy\": 0.944\n },\n \"step_number\": 88\n}\n" - } - }, - "FineTuningJobEvent": { - "type": "object", - "description": "Fine-tuning job event object", - "properties": { - "object": { - "type": "string", - "description": "The object type, which is always \"fine_tuning.job.event\".", - "enum": [ - "fine_tuning.job.event" - ], - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The object identifier." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the fine-tuning job was created." - }, - "level": { - "type": "string", - "description": "The log level of the event.", - "enum": [ - "info", - "warn", - "error" - ] - }, - "message": { - "type": "string", - "description": "The message of the event." - }, - "type": { - "type": "string", - "description": "The type of event.", - "enum": [ - "message", - "metrics" - ] - }, - "data": { - "type": "object", - "description": "The data associated with the event." - } - }, - "required": [ - "id", - "object", - "created_at", - "level", - "message" - ], - "x-oaiMeta": { - "name": "The fine-tuning job event object", - "example": "{\n \"object\": \"fine_tuning.job.event\",\n \"id\": \"ftevent-abc123\"\n \"created_at\": 1677610602,\n \"level\": \"info\",\n \"message\": \"Created fine-tuning job\",\n \"data\": {},\n \"type\": \"message\"\n}\n" - } - }, - "FunctionObject": { - "type": "object", - "properties": { - "description": { - "type": "string", - "description": "A description of what the function does, used by the model to choose when and how to call the function." - }, - "name": { - "type": "string", - "description": "The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64." - }, - "parameters": { - "$ref": "#/components/schemas/FunctionParameters" - }, - "strict": { - "type": "boolean", - "nullable": true, - "default": false, - "description": "Whether to enable strict schema adherence when generating the function call. If set to true, the model will follow the exact schema defined in the `parameters` field. Only a subset of JSON Schema is supported when `strict` is `true`. Learn more about Structured Outputs in the [function calling guide](https://platform.openai.com/docs/guides/function-calling)." - } - }, - "required": [ - "name" - ] - }, - "FunctionParameters": { - "type": "object", - "description": "The parameters the functions accepts, described as a JSON Schema object. See the [guide](https://platform.openai.com/docs/guides/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.\n\nOmitting `parameters` defines a function with an empty parameter list.", - "additionalProperties": true - }, - "FunctionToolCall": { - "type": "object", - "title": "Function tool call", - "description": "A tool call to run a function. See the\n[function calling guide](https://platform.openai.com/docs/guides/function-calling) for more information.\n", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the function tool call.\n" - }, - "type": { - "type": "string", - "enum": [ - "function_call" - ], - "description": "The type of the function tool call. Always `function_call`.\n", - "x-stainless-const": true - }, - "call_id": { - "type": "string", - "description": "The unique ID of the function tool call generated by the model.\n" - }, - "name": { - "type": "string", - "description": "The name of the function to run.\n" - }, - "arguments": { - "type": "string", - "description": "A JSON string of the arguments to pass to the function.\n" - }, - "status": { - "type": "string", - "description": "The status of the item. One of `in_progress`, `completed`, or\n`incomplete`. Populated when items are returned via API.\n", - "enum": [ - "in_progress", - "completed", - "incomplete" - ] - } - }, - "required": [ - "type", - "call_id", - "name", - "arguments" - ] - }, - "FunctionToolCallOutput": { - "type": "object", - "title": "Function tool call output", - "description": "The output of a function tool call.\n", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the function tool call output. Populated when this item\nis returned via API.\n" - }, - "type": { - "type": "string", - "enum": [ - "function_call_output" - ], - "description": "The type of the function tool call output. Always `function_call_output`.\n", - "x-stainless-const": true - }, - "call_id": { - "type": "string", - "description": "The unique ID of the function tool call generated by the model.\n" - }, - "output": { - "type": "string", - "description": "A JSON string of the output of the function tool call.\n" - }, - "status": { - "type": "string", - "description": "The status of the item. One of `in_progress`, `completed`, or\n`incomplete`. Populated when items are returned via API.\n", - "enum": [ - "in_progress", - "completed", - "incomplete" - ] - } - }, - "required": [ - "type", - "call_id", - "output" - ] - }, - "FunctionToolCallOutputResource": { - "allOf": [ - { - "$ref": "#/components/schemas/FunctionToolCallOutput" - }, - { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the function call tool output.\n" - } - }, - "required": [ - "id" - ] - } - ] - }, - "FunctionToolCallResource": { - "allOf": [ - { - "$ref": "#/components/schemas/FunctionToolCall" - }, - { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the function tool call.\n" - } - }, - "required": [ - "id" - ] - } - ] - }, - "GraderLabelModel": { - "type": "object", - "title": "LabelModelGrader", - "description": "A LabelModelGrader object which uses a model to assign labels to each item\nin the evaluation.\n", - "properties": { - "type": { - "description": "The object type, which is always `label_model`.", - "type": "string", - "enum": [ - "label_model" - ], - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the grader." - }, - "model": { - "type": "string", - "description": "The model to use for the evaluation. Must support structured outputs." - }, - "input": { - "type": "array", - "items": { - "$ref": "#/components/schemas/EvalItem" - } - }, - "labels": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The labels to assign to each item in the evaluation." - }, - "passing_labels": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The labels that indicate a passing result. Must be a subset of labels." - } - }, - "required": [ - "type", - "model", - "input", - "passing_labels", - "labels", - "name" - ], - "x-oaiMeta": { - "name": "Label Model Grader", - "group": "graders", - "example": "{\n \"name\": \"First label grader\",\n \"type\": \"label_model\",\n \"model\": \"gpt-4o-2024-08-06\",\n \"input\": [\n {\n \"type\": \"message\",\n \"role\": \"system\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Classify the sentiment of the following statement as one of positive, neutral, or negative\"\n }\n },\n {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": {\n \"type\": \"input_text\",\n \"text\": \"Statement: {{item.response}}\"\n }\n }\n ],\n \"passing_labels\": [\n \"positive\"\n ],\n \"labels\": [\n \"positive\",\n \"neutral\",\n \"negative\"\n ]\n}\n" - } - }, - "GraderMulti": { - "type": "object", - "title": "MultiGrader", - "description": "A MultiGrader object combines the output of multiple graders to produce a single score.", - "properties": { - "type": { - "type": "string", - "enum": [ - "multi" - ], - "default": "multi", - "description": "The object type, which is always `multi`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the grader." - }, - "graders": { - "anyOf": [ - { - "$ref": "#/components/schemas/GraderStringCheck" - }, - { - "$ref": "#/components/schemas/GraderTextSimilarity" - }, - { - "$ref": "#/components/schemas/GraderPython" - }, - { - "$ref": "#/components/schemas/GraderScoreModel" - }, - { - "$ref": "#/components/schemas/GraderLabelModel" - } - ] - }, - "calculate_output": { - "type": "string", - "description": "A formula to calculate the output based on grader results." - } - }, - "required": [ - "name", - "type", - "graders", - "calculate_output" - ], - "x-oaiMeta": { - "name": "Multi Grader", - "group": "graders", - "example": "{\n \"type\": \"multi\",\n \"name\": \"example multi grader\",\n \"graders\": [\n {\n \"type\": \"text_similarity\",\n \"name\": \"example text similarity grader\",\n \"input\": \"The graded text\",\n \"reference\": \"The reference text\",\n \"evaluation_metric\": \"fuzzy_match\"\n },\n {\n \"type\": \"string_check\",\n \"name\": \"Example string check grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\"\n }\n ],\n \"calculate_output\": \"0.5 * text_similarity_score + 0.5 * string_check_score)\"\n}\n" - } - }, - "GraderPython": { - "type": "object", - "title": "PythonGrader", - "description": "A PythonGrader object that runs a python script on the input.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "python" - ], - "description": "The object type, which is always `python`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the grader." - }, - "source": { - "type": "string", - "description": "The source code of the python script." - }, - "image_tag": { - "type": "string", - "description": "The image tag to use for the python script." - } - }, - "required": [ - "type", - "name", - "source" - ], - "x-oaiMeta": { - "name": "Python Grader", - "group": "graders", - "example": "{\n \"type\": \"python\",\n \"name\": \"Example python grader\",\n \"image_tag\": \"2025-05-08\",\n \"source\": \"\"\"\ndef grade(sample: dict, item: dict) -> float:\n \\\"\"\"\n Returns 1.0 if `output_text` equals `label`, otherwise 0.0.\n \\\"\"\"\n output = sample.get(\"output_text\")\n label = item.get(\"label\")\n return 1.0 if output == label else 0.0\n\"\"\",\n}\n" - } - }, - "GraderScoreModel": { - "type": "object", - "title": "ScoreModelGrader", - "description": "A ScoreModelGrader object that uses a model to assign a score to the input.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "score_model" - ], - "description": "The object type, which is always `score_model`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the grader." - }, - "model": { - "type": "string", - "description": "The model to use for the evaluation." - }, - "sampling_params": { - "type": "object", - "description": "The sampling parameters for the model." - }, - "input": { - "type": "array", - "items": { - "$ref": "#/components/schemas/EvalItem" - }, - "description": "The input text. This may include template strings." - }, - "range": { - "type": "array", - "items": { - "type": "number", - "min_items": 2, - "max_items": 2 - }, - "description": "The range of the score. Defaults to `[0, 1]`." - } - }, - "required": [ - "type", - "name", - "input", - "model" - ], - "x-oaiMeta": { - "name": "Score Model Grader", - "group": "graders", - "example": "{\n \"type\": \"score_model\",\n \"name\": \"Example score model grader\",\n \"input\": [\n {\n \"role\": \"user\",\n \"content\": (\n \"Score how close the reference answer is to the model answer. Score 1.0 if they are the same and 0.0 if they are different.\"\n \" Return just a floating point score\\n\\n\"\n \" Reference answer: {{item.label}}\\n\\n\"\n \" Model answer: {{sample.output_text}}\"\n ),\n }\n ],\n \"model\": \"gpt-4o-2024-08-06\",\n \"sampling_params\": {\n \"temperature\": 1,\n \"top_p\": 1,\n \"seed\": 42,\n },\n}\n" - } - }, - "GraderStringCheck": { - "type": "object", - "title": "StringCheckGrader", - "description": "A StringCheckGrader object that performs a string comparison between input and reference using a specified operation.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "string_check" - ], - "description": "The object type, which is always `string_check`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the grader." - }, - "input": { - "type": "string", - "description": "The input text. This may include template strings." - }, - "reference": { - "type": "string", - "description": "The reference text. This may include template strings." - }, - "operation": { - "type": "string", - "enum": [ - "eq", - "ne", - "like", - "ilike" - ], - "description": "The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`." - } - }, - "required": [ - "type", - "name", - "input", - "reference", - "operation" - ], - "x-oaiMeta": { - "name": "String Check Grader", - "group": "graders", - "example": "{\n \"type\": \"string_check\",\n \"name\": \"Example string check grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"operation\": \"eq\"\n}\n" - } - }, - "GraderTextSimilarity": { - "type": "object", - "title": "TextSimilarityGrader", - "description": "A TextSimilarityGrader object which grades text based on similarity metrics.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "text_similarity" - ], - "default": "text_similarity", - "description": "The type of grader.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the grader." - }, - "input": { - "type": "string", - "description": "The text being graded." - }, - "reference": { - "type": "string", - "description": "The text being graded against." - }, - "evaluation_metric": { - "type": "string", - "enum": [ - "cosine", - "fuzzy_match", - "bleu", - "gleu", - "meteor", - "rouge_1", - "rouge_2", - "rouge_3", - "rouge_4", - "rouge_5", - "rouge_l" - ], - "description": "The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, \n`gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, \nor `rouge_l`.\n" - } - }, - "required": [ - "type", - "name", - "input", - "reference", - "evaluation_metric" - ], - "x-oaiMeta": { - "name": "Text Similarity Grader", - "group": "graders", - "example": "{\n \"type\": \"text_similarity\",\n \"name\": \"Example text similarity grader\",\n \"input\": \"{{sample.output_text}}\",\n \"reference\": \"{{item.label}}\",\n \"evaluation_metric\": \"fuzzy_match\"\n}\n" - } - }, - "Image": { - "type": "object", - "description": "Represents the content or the URL of an image generated by the OpenAI API.", - "properties": { - "b64_json": { - "type": "string", - "description": "The base64-encoded JSON of the generated image. Default value for `gpt-image-1`, and only present if `response_format` is set to `b64_json` for `dall-e-2` and `dall-e-3`." - }, - "url": { - "type": "string", - "description": "When using `dall-e-2` or `dall-e-3`, the URL of the generated image if `response_format` is set to `url` (default value). Unsupported for `gpt-image-1`." - }, - "revised_prompt": { - "type": "string", - "description": "For `dall-e-3` only, the revised prompt that was used to generate the image." - } - } - }, - "ImageEditCompletedEvent": { - "type": "object", - "description": "Emitted when image editing has completed and the final image is available.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `image_edit.completed`.\n", - "enum": [ - "image_edit.completed" - ], - "x-stainless-const": true - }, - "b64_json": { - "type": "string", - "description": "Base64-encoded final edited image data, suitable for rendering as an image.\n" - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp when the event was created.\n" - }, - "size": { - "type": "string", - "description": "The size of the edited image.\n", - "enum": [ - "1024x1024", - "1024x1536", - "1536x1024", - "auto" - ] - }, - "quality": { - "type": "string", - "description": "The quality setting for the edited image.\n", - "enum": [ - "low", - "medium", - "high", - "auto" - ] - }, - "background": { - "type": "string", - "description": "The background setting for the edited image.\n", - "enum": [ - "transparent", - "opaque", - "auto" - ] - }, - "output_format": { - "type": "string", - "description": "The output format for the edited image.\n", - "enum": [ - "png", - "webp", - "jpeg" - ] - }, - "usage": { - "$ref": "#/components/schemas/ImagesUsage" - } - }, - "required": [ - "type", - "b64_json", - "created_at", - "size", - "quality", - "background", - "output_format", - "usage" - ], - "x-oaiMeta": { - "name": "image_edit.completed", - "group": "images", - "example": "{\n \"type\": \"image_edit.completed\",\n \"b64_json\": \"...\",\n \"created_at\": 1620000000,\n \"size\": \"1024x1024\",\n \"quality\": \"high\",\n \"background\": \"transparent\",\n \"output_format\": \"png\",\n \"usage\": {\n \"total_tokens\": 100,\n \"input_tokens\": 50,\n \"output_tokens\": 50,\n \"input_tokens_details\": {\n \"text_tokens\": 10,\n \"image_tokens\": 40\n }\n }\n}\n" - } - }, - "ImageEditPartialImageEvent": { - "type": "object", - "description": "Emitted when a partial image is available during image editing streaming.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `image_edit.partial_image`.\n", - "enum": [ - "image_edit.partial_image" - ], - "x-stainless-const": true - }, - "b64_json": { - "type": "string", - "description": "Base64-encoded partial image data, suitable for rendering as an image.\n" - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp when the event was created.\n" - }, - "size": { - "type": "string", - "description": "The size of the requested edited image.\n", - "enum": [ - "1024x1024", - "1024x1536", - "1536x1024", - "auto" - ] - }, - "quality": { - "type": "string", - "description": "The quality setting for the requested edited image.\n", - "enum": [ - "low", - "medium", - "high", - "auto" - ] - }, - "background": { - "type": "string", - "description": "The background setting for the requested edited image.\n", - "enum": [ - "transparent", - "opaque", - "auto" - ] - }, - "output_format": { - "type": "string", - "description": "The output format for the requested edited image.\n", - "enum": [ - "png", - "webp", - "jpeg" - ] - }, - "partial_image_index": { - "type": "integer", - "description": "0-based index for the partial image (streaming).\n" - } - }, - "required": [ - "type", - "b64_json", - "created_at", - "size", - "quality", - "background", - "output_format", - "partial_image_index" - ], - "x-oaiMeta": { - "name": "image_edit.partial_image", - "group": "images", - "example": "{\n \"type\": \"image_edit.partial_image\",\n \"b64_json\": \"...\",\n \"created_at\": 1620000000,\n \"size\": \"1024x1024\",\n \"quality\": \"high\",\n \"background\": \"transparent\",\n \"output_format\": \"png\",\n \"partial_image_index\": 0\n}\n" - } - }, - "ImageEditStreamEvent": { - "anyOf": [ - { - "$ref": "#/components/schemas/ImageEditPartialImageEvent" - }, - { - "$ref": "#/components/schemas/ImageEditCompletedEvent" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "ImageGenCompletedEvent": { - "type": "object", - "description": "Emitted when image generation has completed and the final image is available.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `image_generation.completed`.\n", - "enum": [ - "image_generation.completed" - ], - "x-stainless-const": true - }, - "b64_json": { - "type": "string", - "description": "Base64-encoded image data, suitable for rendering as an image.\n" - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp when the event was created.\n" - }, - "size": { - "type": "string", - "description": "The size of the generated image.\n", - "enum": [ - "1024x1024", - "1024x1536", - "1536x1024", - "auto" - ] - }, - "quality": { - "type": "string", - "description": "The quality setting for the generated image.\n", - "enum": [ - "low", - "medium", - "high", - "auto" - ] - }, - "background": { - "type": "string", - "description": "The background setting for the generated image.\n", - "enum": [ - "transparent", - "opaque", - "auto" - ] - }, - "output_format": { - "type": "string", - "description": "The output format for the generated image.\n", - "enum": [ - "png", - "webp", - "jpeg" - ] - }, - "usage": { - "$ref": "#/components/schemas/ImagesUsage" - } - }, - "required": [ - "type", - "b64_json", - "created_at", - "size", - "quality", - "background", - "output_format", - "usage" - ], - "x-oaiMeta": { - "name": "image_generation.completed", - "group": "images", - "example": "{\n \"type\": \"image_generation.completed\",\n \"b64_json\": \"...\",\n \"created_at\": 1620000000,\n \"size\": \"1024x1024\",\n \"quality\": \"high\",\n \"background\": \"transparent\",\n \"output_format\": \"png\",\n \"usage\": {\n \"total_tokens\": 100,\n \"input_tokens\": 50,\n \"output_tokens\": 50,\n \"input_tokens_details\": {\n \"text_tokens\": 10,\n \"image_tokens\": 40\n }\n }\n}\n" - } - }, - "ImageGenPartialImageEvent": { - "type": "object", - "description": "Emitted when a partial image is available during image generation streaming.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `image_generation.partial_image`.\n", - "enum": [ - "image_generation.partial_image" - ], - "x-stainless-const": true - }, - "b64_json": { - "type": "string", - "description": "Base64-encoded partial image data, suitable for rendering as an image.\n" - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp when the event was created.\n" - }, - "size": { - "type": "string", - "description": "The size of the requested image.\n", - "enum": [ - "1024x1024", - "1024x1536", - "1536x1024", - "auto" - ] - }, - "quality": { - "type": "string", - "description": "The quality setting for the requested image.\n", - "enum": [ - "low", - "medium", - "high", - "auto" - ] - }, - "background": { - "type": "string", - "description": "The background setting for the requested image.\n", - "enum": [ - "transparent", - "opaque", - "auto" - ] - }, - "output_format": { - "type": "string", - "description": "The output format for the requested image.\n", - "enum": [ - "png", - "webp", - "jpeg" - ] - }, - "partial_image_index": { - "type": "integer", - "description": "0-based index for the partial image (streaming).\n" - } - }, - "required": [ - "type", - "b64_json", - "created_at", - "size", - "quality", - "background", - "output_format", - "partial_image_index" - ], - "x-oaiMeta": { - "name": "image_generation.partial_image", - "group": "images", - "example": "{\n \"type\": \"image_generation.partial_image\",\n \"b64_json\": \"...\",\n \"created_at\": 1620000000,\n \"size\": \"1024x1024\",\n \"quality\": \"high\",\n \"background\": \"transparent\",\n \"output_format\": \"png\",\n \"partial_image_index\": 0\n}\n" - } - }, - "ImageGenStreamEvent": { - "anyOf": [ - { - "$ref": "#/components/schemas/ImageGenPartialImageEvent" - }, - { - "$ref": "#/components/schemas/ImageGenCompletedEvent" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "ImageGenTool": { - "type": "object", - "title": "Image generation tool", - "description": "A tool that generates images using a model like `gpt-image-1`.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "image_generation" - ], - "description": "The type of the image generation tool. Always `image_generation`.\n", - "x-stainless-const": true - }, - "model": { - "type": "string", - "enum": [ - "gpt-image-1" - ], - "description": "The image generation model to use. Default: `gpt-image-1`.\n", - "default": "gpt-image-1" - }, - "quality": { - "type": "string", - "enum": [ - "low", - "medium", - "high", - "auto" - ], - "description": "The quality of the generated image. One of `low`, `medium`, `high`, \nor `auto`. Default: `auto`.\n", - "default": "auto" - }, - "size": { - "type": "string", - "enum": [ - "1024x1024", - "1024x1536", - "1536x1024", - "auto" - ], - "description": "The size of the generated image. One of `1024x1024`, `1024x1536`, \n`1536x1024`, or `auto`. Default: `auto`.\n", - "default": "auto" - }, - "output_format": { - "type": "string", - "enum": [ - "png", - "webp", - "jpeg" - ], - "description": "The output format of the generated image. One of `png`, `webp`, or \n`jpeg`. Default: `png`.\n", - "default": "png" - }, - "output_compression": { - "type": "integer", - "minimum": 0, - "maximum": 100, - "description": "Compression level for the output image. Default: 100.\n", - "default": 100 - }, - "moderation": { - "type": "string", - "enum": [ - "auto", - "low" - ], - "description": "Moderation level for the generated image. Default: `auto`.\n", - "default": "auto" - }, - "background": { - "type": "string", - "enum": [ - "transparent", - "opaque", - "auto" - ], - "description": "Background type for the generated image. One of `transparent`, \n`opaque`, or `auto`. Default: `auto`.\n", - "default": "auto" - }, - "input_fidelity": { - "$ref": "#/components/schemas/ImageInputFidelity" - }, - "input_image_mask": { - "type": "object", - "description": "Optional mask for inpainting. Contains `image_url` \n(string, optional) and `file_id` (string, optional).\n", - "properties": { - "image_url": { - "type": "string", - "description": "Base64-encoded mask image.\n" - }, - "file_id": { - "type": "string", - "description": "File ID for the mask image.\n" - } - }, - "required": [], - "additionalProperties": false - }, - "partial_images": { - "type": "integer", - "minimum": 0, - "maximum": 3, - "description": "Number of partial images to generate in streaming mode, from 0 (default value) to 3.\n", - "default": 0 - } - }, - "required": [ - "type" - ] - }, - "ImageGenToolCall": { - "type": "object", - "title": "Image generation call", - "description": "An image generation request made by the model.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "image_generation_call" - ], - "description": "The type of the image generation call. Always `image_generation_call`.\n", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the image generation call.\n" - }, - "status": { - "type": "string", - "enum": [ - "in_progress", - "completed", - "generating", - "failed" - ], - "description": "The status of the image generation call.\n" - }, - "result": { - "type": "string", - "description": "The generated image encoded in base64.\n", - "nullable": true - } - }, - "required": [ - "type", - "id", - "status", - "result" - ] - }, - "ImageInputFidelity": { - "type": "string", - "enum": [ - "high", - "low" - ], - "default": "low", - "nullable": true, - "description": "Control how much effort the model will exert to match the style and features,\nespecially facial features, of input images. This parameter is only supported\nfor `gpt-image-1`. Supports `high` and `low`. Defaults to `low`.\n" - }, - "ImagesResponse": { - "type": "object", - "title": "Image generation response", - "description": "The response from the image generation endpoint.", - "properties": { - "created": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the image was created." - }, - "data": { - "type": "array", - "description": "The list of generated images.", - "items": { - "$ref": "#/components/schemas/Image" - } - }, - "background": { - "type": "string", - "description": "The background parameter used for the image generation. Either `transparent` or `opaque`.", - "enum": [ - "transparent", - "opaque" - ] - }, - "output_format": { - "type": "string", - "description": "The output format of the image generation. Either `png`, `webp`, or `jpeg`.", - "enum": [ - "png", - "webp", - "jpeg" - ] - }, - "size": { - "type": "string", - "description": "The size of the image generated. Either `1024x1024`, `1024x1536`, or `1536x1024`.", - "enum": [ - "1024x1024", - "1024x1536", - "1536x1024" - ] - }, - "quality": { - "type": "string", - "description": "The quality of the image generated. Either `low`, `medium`, or `high`.", - "enum": [ - "low", - "medium", - "high" - ] - }, - "usage": { - "$ref": "#/components/schemas/ImageGenUsage" - } - }, - "required": [ - "created" - ], - "x-oaiMeta": { - "name": "The image generation response", - "group": "images", - "example": "{\n \"created\": 1713833628,\n \"data\": [\n {\n \"b64_json\": \"...\"\n }\n ],\n \"background\": \"transparent\",\n \"output_format\": \"png\",\n \"size\": \"1024x1024\",\n \"quality\": \"high\",\n \"usage\": {\n \"total_tokens\": 100,\n \"input_tokens\": 50,\n \"output_tokens\": 50,\n \"input_tokens_details\": {\n \"text_tokens\": 10,\n \"image_tokens\": 40\n }\n }\n}\n" - } - }, - "ImagesUsage": { - "type": "object", - "description": "For `gpt-image-1` only, the token usage information for the image generation.\n", - "required": [ - "total_tokens", - "input_tokens", - "output_tokens", - "input_tokens_details" - ], - "properties": { - "total_tokens": { - "type": "integer", - "description": "The total number of tokens (images and text) used for the image generation.\n" - }, - "input_tokens": { - "type": "integer", - "description": "The number of tokens (images and text) in the input prompt." - }, - "output_tokens": { - "type": "integer", - "description": "The number of image tokens in the output image." - }, - "input_tokens_details": { - "type": "object", - "description": "The input tokens detailed information for the image generation.", - "required": [ - "text_tokens", - "image_tokens" - ], - "properties": { - "text_tokens": { - "type": "integer", - "description": "The number of text tokens in the input prompt." - }, - "image_tokens": { - "type": "integer", - "description": "The number of image tokens in the input prompt." - } - } - } - } - }, - "Includable": { - "type": "string", - "description": "Specify additional output data to include in the model response. Currently\nsupported values are:\n- `web_search_call.action.sources`: Include the sources of the web search tool call.\n- `code_interpreter_call.outputs`: Includes the outputs of python code execution\n in code interpreter tool call items.\n- `computer_call_output.output.image_url`: Include image urls from the computer call output.\n- `file_search_call.results`: Include the search results of\n the file search tool call.\n- `message.input_image.image_url`: Include image urls from the input message.\n- `message.output_text.logprobs`: Include logprobs with assistant messages.\n- `reasoning.encrypted_content`: Includes an encrypted version of reasoning\n tokens in reasoning item outputs. This enables reasoning items to be used in\n multi-turn conversations when using the Responses API statelessly (like\n when the `store` parameter is set to `false`, or when an organization is\n enrolled in the zero data retention program).\n", - "enum": [ - "code_interpreter_call.outputs", - "computer_call_output.output.image_url", - "file_search_call.results", - "message.input_image.image_url", - "message.output_text.logprobs", - "reasoning.encrypted_content" - ] - }, - "InputAudio": { - "type": "object", - "title": "Input audio", - "description": "An audio input to the model.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the input item. Always `input_audio`.\n", - "enum": [ - "input_audio" - ], - "x-stainless-const": true - }, - "input_audio": { - "type": "object", - "properties": { - "data": { - "type": "string", - "description": "Base64-encoded audio data.\n" - }, - "format": { - "type": "string", - "description": "The format of the audio data. Currently supported formats are `mp3` and\n`wav`.\n", - "enum": [ - "mp3", - "wav" - ] - } - }, - "required": [ - "data", - "format" - ] - } - }, - "required": [ - "type", - "input_audio" - ] - }, - "InputContent": { - "anyOf": [ - { - "$ref": "#/components/schemas/InputTextContent" - }, - { - "$ref": "#/components/schemas/InputImageContent" - }, - { - "$ref": "#/components/schemas/InputFileContent" - }, - { - "$ref": "#/components/schemas/InputAudio" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "InputItem": { - "discriminator": { - "propertyName": "type" - }, - "anyOf": [ - { - "$ref": "#/components/schemas/EasyInputMessage" - }, - { - "type": "object", - "title": "Item", - "description": "An item representing part of the context for the response to be \ngenerated by the model. Can contain text, images, and audio inputs,\nas well as previous assistant responses and tool call outputs.\n", - "$ref": "#/components/schemas/Item" - }, - { - "$ref": "#/components/schemas/ItemReferenceParam" - } - ] - }, - "InputMessage": { - "type": "object", - "title": "Input message", - "description": "A message input to the model with a role indicating instruction following\nhierarchy. Instructions given with the `developer` or `system` role take\nprecedence over instructions given with the `user` role.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the message input. Always set to `message`.\n", - "enum": [ - "message" - ], - "x-stainless-const": true - }, - "role": { - "type": "string", - "description": "The role of the message input. One of `user`, `system`, or `developer`.\n", - "enum": [ - "user", - "system", - "developer" - ] - }, - "status": { - "type": "string", - "description": "The status of item. One of `in_progress`, `completed`, or\n`incomplete`. Populated when items are returned via API.\n", - "enum": [ - "in_progress", - "completed", - "incomplete" - ] - }, - "content": { - "$ref": "#/components/schemas/InputMessageContentList" - } - }, - "required": [ - "role", - "content" - ] - }, - "InputMessageContentList": { - "type": "array", - "title": "Input item content list", - "description": "A list of one or many input items to the model, containing different content \ntypes.\n", - "items": { - "$ref": "#/components/schemas/InputContent" - } - }, - "InputMessageResource": { - "allOf": [ - { - "$ref": "#/components/schemas/InputMessage" - }, - { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the message input.\n" - } - }, - "required": [ - "id" - ] - } - ] - }, - "Invite": { - "type": "object", - "description": "Represents an individual `invite` to the organization.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.invite" - ], - "description": "The object type, which is always `organization.invite`", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The identifier, which can be referenced in API endpoints" - }, - "email": { - "type": "string", - "description": "The email address of the individual to whom the invite was sent" - }, - "role": { - "type": "string", - "enum": [ - "owner", - "reader" - ], - "description": "`owner` or `reader`" - }, - "status": { - "type": "string", - "enum": [ - "accepted", - "expired", - "pending" - ], - "description": "`accepted`,`expired`, or `pending`" - }, - "invited_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the invite was sent." - }, - "expires_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the invite expires." - }, - "accepted_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the invite was accepted." - }, - "projects": { - "type": "array", - "description": "The projects that were granted membership upon acceptance of the invite.", - "items": { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "Project's public ID" - }, - "role": { - "type": "string", - "enum": [ - "member", - "owner" - ], - "description": "Project membership role" - } - } - } - } - }, - "required": [ - "object", - "id", - "email", - "role", - "status", - "invited_at", - "expires_at" - ], - "x-oaiMeta": { - "name": "The invite object", - "example": "{\n \"object\": \"organization.invite\",\n \"id\": \"invite-abc\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"status\": \"accepted\",\n \"invited_at\": 1711471533,\n \"expires_at\": 1711471533,\n \"accepted_at\": 1711471533,\n \"projects\": [\n {\n \"id\": \"project-xyz\",\n \"role\": \"member\"\n }\n ]\n}\n" - } - }, - "InviteDeleteResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.invite.deleted" - ], - "description": "The object type, which is always `organization.invite.deleted`", - "x-stainless-const": true - }, - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - } - }, - "required": [ - "object", - "id", - "deleted" - ] - }, - "InviteListResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "description": "The object type, which is always `list`", - "x-stainless-const": true - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Invite" - } - }, - "first_id": { - "type": "string", - "description": "The first `invite_id` in the retrieved `list`" - }, - "last_id": { - "type": "string", - "description": "The last `invite_id` in the retrieved `list`" - }, - "has_more": { - "type": "boolean", - "description": "The `has_more` property is used for pagination to indicate there are additional results." - } - }, - "required": [ - "object", - "data" - ] - }, - "InviteRequest": { - "type": "object", - "properties": { - "email": { - "type": "string", - "description": "Send an email to this address" - }, - "role": { - "type": "string", - "enum": [ - "reader", - "owner" - ], - "description": "`owner` or `reader`" - }, - "projects": { - "type": "array", - "description": "An array of projects to which membership is granted at the same time the org invite is accepted. If omitted, the user will be invited to the default project for compatibility with legacy behavior.", - "items": { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "Project's public ID" - }, - "role": { - "type": "string", - "enum": [ - "member", - "owner" - ], - "description": "Project membership role" - } - }, - "required": [ - "id", - "role" - ] - } - } - }, - "required": [ - "email", - "role" - ] - }, - "Item": { - "type": "object", - "description": "Content item used to generate a response.\n", - "discriminator": { - "propertyName": "type" - }, - "anyOf": [ - { - "$ref": "#/components/schemas/InputMessage" - }, - { - "$ref": "#/components/schemas/OutputMessage" - }, - { - "$ref": "#/components/schemas/FileSearchToolCall" - }, - { - "$ref": "#/components/schemas/ComputerToolCall" - }, - { - "$ref": "#/components/schemas/ComputerCallOutputItemParam" - }, - { - "$ref": "#/components/schemas/WebSearchToolCall" - }, - { - "$ref": "#/components/schemas/FunctionToolCall" - }, - { - "$ref": "#/components/schemas/FunctionCallOutputItemParam" - }, - { - "$ref": "#/components/schemas/ReasoningItem" - }, - { - "$ref": "#/components/schemas/ImageGenToolCall" - }, - { - "$ref": "#/components/schemas/CodeInterpreterToolCall" - }, - { - "$ref": "#/components/schemas/LocalShellToolCall" - }, - { - "$ref": "#/components/schemas/LocalShellToolCallOutput" - }, - { - "$ref": "#/components/schemas/MCPListTools" - }, - { - "$ref": "#/components/schemas/MCPApprovalRequest" - }, - { - "$ref": "#/components/schemas/MCPApprovalResponse" - }, - { - "$ref": "#/components/schemas/MCPToolCall" - }, - { - "$ref": "#/components/schemas/CustomToolCallOutput" - }, - { - "$ref": "#/components/schemas/CustomToolCall" - } - ] - }, - "ItemResource": { - "description": "Content item used to generate a response.\n", - "discriminator": { - "propertyName": "type" - }, - "anyOf": [ - { - "$ref": "#/components/schemas/InputMessageResource" - }, - { - "$ref": "#/components/schemas/OutputMessage" - }, - { - "$ref": "#/components/schemas/FileSearchToolCall" - }, - { - "$ref": "#/components/schemas/ComputerToolCall" - }, - { - "$ref": "#/components/schemas/ComputerToolCallOutputResource" - }, - { - "$ref": "#/components/schemas/WebSearchToolCall" - }, - { - "$ref": "#/components/schemas/FunctionToolCallResource" - }, - { - "$ref": "#/components/schemas/FunctionToolCallOutputResource" - }, - { - "$ref": "#/components/schemas/ImageGenToolCall" - }, - { - "$ref": "#/components/schemas/CodeInterpreterToolCall" - }, - { - "$ref": "#/components/schemas/LocalShellToolCall" - }, - { - "$ref": "#/components/schemas/LocalShellToolCallOutput" - }, - { - "$ref": "#/components/schemas/MCPListTools" - }, - { - "$ref": "#/components/schemas/MCPApprovalRequest" - }, - { - "$ref": "#/components/schemas/MCPApprovalResponseResource" - }, - { - "$ref": "#/components/schemas/MCPToolCall" - } - ] - }, - "KeyPress": { - "type": "object", - "title": "KeyPress", - "description": "A collection of keypresses the model would like to perform.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "keypress" - ], - "default": "keypress", - "description": "Specifies the event type. For a keypress action, this property is \nalways set to `keypress`.\n", - "x-stainless-const": true - }, - "keys": { - "type": "array", - "items": { - "type": "string", - "description": "One of the keys the model is requesting to be pressed.\n" - }, - "description": "The combination of keys the model is requesting to be pressed. This is an\narray of strings, each representing a key.\n" - } - }, - "required": [ - "type", - "keys" - ] - }, - "ListAssistantsResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "example": "list" - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/AssistantObject" - } - }, - "first_id": { - "type": "string", - "example": "asst_abc123" - }, - "last_id": { - "type": "string", - "example": "asst_abc456" - }, - "has_more": { - "type": "boolean", - "example": false - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ], - "x-oaiMeta": { - "name": "List assistants response object", - "group": "chat", - "example": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"asst_abc123\",\n \"object\": \"assistant\",\n \"created_at\": 1698982736,\n \"name\": \"Coding Tutor\",\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are a helpful assistant designed to make me better at coding!\",\n \"tools\": [],\n \"tool_resources\": {},\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n },\n {\n \"id\": \"asst_abc456\",\n \"object\": \"assistant\",\n \"created_at\": 1698982718,\n \"name\": \"My Assistant\",\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": \"You are a helpful assistant designed to make me better at coding!\",\n \"tools\": [],\n \"tool_resources\": {},\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n },\n {\n \"id\": \"asst_abc789\",\n \"object\": \"assistant\",\n \"created_at\": 1698982643,\n \"name\": null,\n \"description\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": null,\n \"tools\": [],\n \"tool_resources\": {},\n \"metadata\": {},\n \"top_p\": 1.0,\n \"temperature\": 1.0,\n \"response_format\": \"auto\"\n }\n ],\n \"first_id\": \"asst_abc123\",\n \"last_id\": \"asst_abc789\",\n \"has_more\": false\n}\n" - } - }, - "ListAuditLogsResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/AuditLog" - } - }, - "first_id": { - "type": "string", - "example": "audit_log-defb456h8dks" - }, - "last_id": { - "type": "string", - "example": "audit_log-hnbkd8s93s" - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ListBatchesResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Batch" - } - }, - "first_id": { - "type": "string", - "example": "batch_abc123" - }, - "last_id": { - "type": "string", - "example": "batch_abc456" - }, - "has_more": { - "type": "boolean" - }, - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - } - }, - "required": [ - "object", - "data", - "has_more" - ] - }, - "ListCertificatesResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Certificate" - } - }, - "first_id": { - "type": "string", - "example": "cert_abc" - }, - "last_id": { - "type": "string", - "example": "cert_abc" - }, - "has_more": { - "type": "boolean" - }, - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - } - }, - "required": [ - "object", - "data", - "has_more" - ] - }, - "ListFilesResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "example": "list" - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/OpenAIFile" - } - }, - "first_id": { - "type": "string", - "example": "file-abc123" - }, - "last_id": { - "type": "string", - "example": "file-abc456" - }, - "has_more": { - "type": "boolean", - "example": false - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ListFineTuningCheckpointPermissionResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/FineTuningCheckpointPermission" - } - }, - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "first_id": { - "type": "string", - "nullable": true - }, - "last_id": { - "type": "string", - "nullable": true - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "has_more" - ] - }, - "ListFineTuningJobCheckpointsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/FineTuningJobCheckpoint" - } - }, - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "first_id": { - "type": "string", - "nullable": true - }, - "last_id": { - "type": "string", - "nullable": true - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "has_more" - ] - }, - "ListFineTuningJobEventsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/FineTuningJobEvent" - } - }, - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "has_more" - ] - }, - "ListMessagesResponse": { - "properties": { - "object": { - "type": "string", - "example": "list" - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/MessageObject" - } - }, - "first_id": { - "type": "string", - "example": "msg_abc123" - }, - "last_id": { - "type": "string", - "example": "msg_abc123" - }, - "has_more": { - "type": "boolean", - "example": false - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ListModelsResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Model" - } - } - }, - "required": [ - "object", - "data" - ] - }, - "ListPaginatedFineTuningJobsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/FineTuningJob" - } - }, - "has_more": { - "type": "boolean" - }, - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - } - }, - "required": [ - "object", - "data", - "has_more" - ] - }, - "ListRunStepsResponse": { - "properties": { - "object": { - "type": "string", - "example": "list" - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/RunStepObject" - } - }, - "first_id": { - "type": "string", - "example": "step_abc123" - }, - "last_id": { - "type": "string", - "example": "step_abc456" - }, - "has_more": { - "type": "boolean", - "example": false - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ListRunsResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "example": "list" - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/RunObject" - } - }, - "first_id": { - "type": "string", - "example": "run_abc123" - }, - "last_id": { - "type": "string", - "example": "run_abc456" - }, - "has_more": { - "type": "boolean", - "example": false - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ListVectorStoreFilesResponse": { - "properties": { - "object": { - "type": "string", - "example": "list" - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/VectorStoreFileObject" - } - }, - "first_id": { - "type": "string", - "example": "file-abc123" - }, - "last_id": { - "type": "string", - "example": "file-abc456" - }, - "has_more": { - "type": "boolean", - "example": false - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ListVectorStoresResponse": { - "properties": { - "object": { - "type": "string", - "example": "list" - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/VectorStoreObject" - } - }, - "first_id": { - "type": "string", - "example": "vs_abc123" - }, - "last_id": { - "type": "string", - "example": "vs_abc456" - }, - "has_more": { - "type": "boolean", - "example": false - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "LocalShellExecAction": { - "type": "object", - "title": "Local shell exec action", - "description": "Execute a shell command on the server.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "exec" - ], - "description": "The type of the local shell action. Always `exec`.\n", - "x-stainless-const": true - }, - "command": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The command to run.\n" - }, - "timeout_ms": { - "type": "integer", - "description": "Optional timeout in milliseconds for the command.\n", - "nullable": true - }, - "working_directory": { - "type": "string", - "description": "Optional working directory to run the command in.\n", - "nullable": true - }, - "env": { - "type": "object", - "additionalProperties": { - "type": "string" - }, - "description": "Environment variables to set for the command.\n" - }, - "user": { - "type": "string", - "description": "Optional user to run the command as.\n", - "nullable": true - } - }, - "required": [ - "type", - "command", - "env" - ] - }, - "LocalShellTool": { - "type": "object", - "title": "Local shell tool", - "description": "A tool that allows the model to execute shell commands in a local environment.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "local_shell" - ], - "description": "The type of the local shell tool. Always `local_shell`.", - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "LocalShellToolCall": { - "type": "object", - "title": "Local shell call", - "description": "A tool call to run a command on the local shell.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "local_shell_call" - ], - "description": "The type of the local shell call. Always `local_shell_call`.\n", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the local shell call.\n" - }, - "call_id": { - "type": "string", - "description": "The unique ID of the local shell tool call generated by the model.\n" - }, - "action": { - "$ref": "#/components/schemas/LocalShellExecAction" - }, - "status": { - "type": "string", - "enum": [ - "in_progress", - "completed", - "incomplete" - ], - "description": "The status of the local shell call.\n" - } - }, - "required": [ - "type", - "id", - "call_id", - "action", - "status" - ] - }, - "LocalShellToolCallOutput": { - "type": "object", - "title": "Local shell call output", - "description": "The output of a local shell tool call.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "local_shell_call_output" - ], - "description": "The type of the local shell tool call output. Always `local_shell_call_output`.\n", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the local shell tool call generated by the model.\n" - }, - "output": { - "type": "string", - "description": "A JSON string of the output of the local shell tool call.\n" - }, - "status": { - "type": "string", - "enum": [ - "in_progress", - "completed", - "incomplete" - ], - "description": "The status of the item. One of `in_progress`, `completed`, or `incomplete`.\n", - "nullable": true - } - }, - "required": [ - "id", - "type", - "call_id", - "output" - ] - }, - "LogProbProperties": { - "type": "object", - "description": "A log probability object.\n", - "properties": { - "token": { - "type": "string", - "description": "The token that was used to generate the log probability.\n" - }, - "logprob": { - "type": "number", - "description": "The log probability of the token.\n" - }, - "bytes": { - "type": "array", - "items": { - "type": "integer" - }, - "description": "The bytes that were used to generate the log probability.\n" - } - }, - "required": [ - "token", - "logprob", - "bytes" - ] - }, - "MCPApprovalRequest": { - "type": "object", - "title": "MCP approval request", - "description": "A request for human approval of a tool invocation.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp_approval_request" - ], - "description": "The type of the item. Always `mcp_approval_request`.\n", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the approval request.\n" - }, - "server_label": { - "type": "string", - "description": "The label of the MCP server making the request.\n" - }, - "name": { - "type": "string", - "description": "The name of the tool to run.\n" - }, - "arguments": { - "type": "string", - "description": "A JSON string of arguments for the tool.\n" - } - }, - "required": [ - "type", - "id", - "server_label", - "name", - "arguments" - ] - }, - "MCPApprovalResponse": { - "type": "object", - "title": "MCP approval response", - "description": "A response to an MCP approval request.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp_approval_response" - ], - "description": "The type of the item. Always `mcp_approval_response`.\n", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the approval response\n", - "nullable": true - }, - "approval_request_id": { - "type": "string", - "description": "The ID of the approval request being answered.\n" - }, - "approve": { - "type": "boolean", - "description": "Whether the request was approved.\n" - }, - "reason": { - "type": "string", - "description": "Optional reason for the decision.\n", - "nullable": true - } - }, - "required": [ - "type", - "request_id", - "approve", - "approval_request_id" - ] - }, - "MCPApprovalResponseResource": { - "type": "object", - "title": "MCP approval response", - "description": "A response to an MCP approval request.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp_approval_response" - ], - "description": "The type of the item. Always `mcp_approval_response`.\n", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the approval response\n" - }, - "approval_request_id": { - "type": "string", - "description": "The ID of the approval request being answered.\n" - }, - "approve": { - "type": "boolean", - "description": "Whether the request was approved.\n" - }, - "reason": { - "type": "string", - "description": "Optional reason for the decision.\n", - "nullable": true - } - }, - "required": [ - "type", - "id", - "request_id", - "approve", - "approval_request_id" - ] - }, - "MCPListTools": { - "type": "object", - "title": "MCP list tools", - "description": "A list of tools available on an MCP server.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp_list_tools" - ], - "description": "The type of the item. Always `mcp_list_tools`.\n", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the list.\n" - }, - "server_label": { - "type": "string", - "description": "The label of the MCP server.\n" - }, - "tools": { - "type": "array", - "items": { - "$ref": "#/components/schemas/MCPListToolsTool" - }, - "description": "The tools available on the server.\n" - }, - "error": { - "type": "string", - "description": "Error message if the server could not list tools.\n", - "nullable": true - } - }, - "required": [ - "type", - "id", - "server_label", - "tools" - ] - }, - "MCPListToolsTool": { - "type": "object", - "title": "MCP list tools tool", - "description": "A tool available on an MCP server.\n", - "properties": { - "name": { - "type": "string", - "description": "The name of the tool.\n" - }, - "description": { - "type": "string", - "description": "The description of the tool.\n", - "nullable": true - }, - "input_schema": { - "type": "object", - "description": "The JSON schema describing the tool's input.\n" - }, - "annotations": { - "type": "object", - "description": "Additional annotations about the tool.\n", - "nullable": true - } - }, - "required": [ - "name", - "input_schema" - ] - }, - "MCPTool": { - "type": "object", - "title": "MCP tool", - "description": "Give the model access to additional tools via remote Model Context Protocol \n(MCP) servers. [Learn more about MCP](https://platform.openai.com/docs/guides/tools-remote-mcp).\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp" - ], - "description": "The type of the MCP tool. Always `mcp`.", - "x-stainless-const": true - }, - "server_label": { - "type": "string", - "description": "A label for this MCP server, used to identify it in tool calls.\n" - }, - "server_url": { - "type": "string", - "description": "The URL for the MCP server. One of `server_url` or `connector_id` must be \nprovided.\n" - }, - "connector_id": { - "type": "string", - "enum": [ - "connector_dropbox", - "connector_gmail", - "connector_googlecalendar", - "connector_googledrive", - "connector_microsoftteams", - "connector_outlookcalendar", - "connector_outlookemail", - "connector_sharepoint" - ], - "description": "Identifier for service connectors, like those available in ChatGPT. One of\n`server_url` or `connector_id` must be provided. Learn more about service\nconnectors [here](https://platform.openai.com/docs/guides/tools-remote-mcp#connectors).\n\nCurrently supported `connector_id` values are:\n\n- Dropbox: `connector_dropbox`\n- Gmail: `connector_gmail`\n- Google Calendar: `connector_googlecalendar`\n- Google Drive: `connector_googledrive`\n- Microsoft Teams: `connector_microsoftteams`\n- Outlook Calendar: `connector_outlookcalendar`\n- Outlook Email: `connector_outlookemail`\n- SharePoint: `connector_sharepoint`\n" - }, - "authorization": { - "type": "string", - "description": "An OAuth access token that can be used with a remote MCP server, either \nwith a custom MCP server URL or a service connector. Your application\nmust handle the OAuth authorization flow and provide the token here.\n" - }, - "server_description": { - "type": "string", - "description": "Optional description of the MCP server, used to provide more context.\n" - }, - "headers": { - "type": "object", - "additionalProperties": { - "type": "string" - }, - "nullable": true, - "description": "Optional HTTP headers to send to the MCP server. Use for authentication\nor other purposes.\n" - }, - "allowed_tools": { - "description": "List of allowed tool names or a filter object.\n", - "nullable": true, - "anyOf": [ - { - "type": "array", - "title": "MCP allowed tools", - "description": "A string array of allowed tool names", - "items": { - "type": "string" - } - }, - { - "$ref": "#/components/schemas/MCPToolFilter" - } - ] - }, - "require_approval": { - "description": "Specify which of the MCP server's tools require approval.", - "nullable": true, - "anyOf": [ - { - "type": "object", - "title": "MCP tool approval filter", - "description": "Specify which of the MCP server's tools require approval. Can be\n`always`, `never`, or a filter object associated with tools\nthat require approval.\n", - "properties": { - "always": { - "$ref": "#/components/schemas/MCPToolFilter" - }, - "never": { - "$ref": "#/components/schemas/MCPToolFilter" - } - }, - "additionalProperties": false - }, - { - "type": "string", - "title": "MCP tool approval setting", - "description": "Specify a single approval policy for all tools. One of `always` or \n`never`. When set to `always`, all tools will require approval. When \nset to `never`, all tools will not require approval.\n", - "enum": [ - "always", - "never" - ] - } - ] - } - }, - "required": [ - "type", - "server_label" - ] - }, - "MCPToolCall": { - "type": "object", - "title": "MCP tool call", - "description": "An invocation of a tool on an MCP server.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp_call" - ], - "description": "The type of the item. Always `mcp_call`.\n", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the tool call.\n" - }, - "server_label": { - "type": "string", - "description": "The label of the MCP server running the tool.\n" - }, - "name": { - "type": "string", - "description": "The name of the tool that was run.\n" - }, - "arguments": { - "type": "string", - "description": "A JSON string of the arguments passed to the tool.\n" - }, - "output": { - "type": "string", - "description": "The output from the tool call.\n", - "nullable": true - }, - "error": { - "type": "string", - "description": "The error from the tool call, if any.\n", - "nullable": true - } - }, - "required": [ - "type", - "id", - "server_label", - "name", - "arguments" - ] - }, - "MCPToolFilter": { - "type": "object", - "title": "MCP tool filter", - "description": "A filter object to specify which tools are allowed.\n", - "properties": { - "tool_names": { - "type": "array", - "title": "MCP allowed tools", - "items": { - "type": "string" - }, - "description": "List of allowed tool names." - }, - "read_only": { - "type": "boolean", - "description": "Indicates whether or not a tool modifies data or is read-only. If an\nMCP server is [annotated with `readOnlyHint`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-readonlyhint),\nit will match this filter.\n" - } - }, - "required": [], - "additionalProperties": false - }, - "MessageContentImageFileObject": { - "title": "Image file", - "type": "object", - "description": "References an image [File](https://platform.openai.com/docs/api-reference/files) in the content of a message.", - "properties": { - "type": { - "description": "Always `image_file`.", - "type": "string", - "enum": [ - "image_file" - ], - "x-stainless-const": true - }, - "image_file": { - "type": "object", - "properties": { - "file_id": { - "description": "The [File](https://platform.openai.com/docs/api-reference/files) ID of the image in the message content. Set `purpose=\"vision\"` when uploading the File if you need to later display the file content.", - "type": "string" - }, - "detail": { - "type": "string", - "description": "Specifies the detail level of the image if specified by the user. `low` uses fewer tokens, you can opt in to high resolution using `high`.", - "enum": [ - "auto", - "low", - "high" - ], - "default": "auto" - } - }, - "required": [ - "file_id" - ] - } - }, - "required": [ - "type", - "image_file" - ] - }, - "MessageContentImageUrlObject": { - "title": "Image URL", - "type": "object", - "description": "References an image URL in the content of a message.", - "properties": { - "type": { - "type": "string", - "enum": [ - "image_url" - ], - "description": "The type of the content part.", - "x-stainless-const": true - }, - "image_url": { - "type": "object", - "properties": { - "url": { - "type": "string", - "description": "The external URL of the image, must be a supported image types: jpeg, jpg, png, gif, webp.", - "format": "uri" - }, - "detail": { - "type": "string", - "description": "Specifies the detail level of the image. `low` uses fewer tokens, you can opt in to high resolution using `high`. Default value is `auto`", - "enum": [ - "auto", - "low", - "high" - ], - "default": "auto" - } - }, - "required": [ - "url" - ] - } - }, - "required": [ - "type", - "image_url" - ] - }, - "MessageContentRefusalObject": { - "title": "Refusal", - "type": "object", - "description": "The refusal content generated by the assistant.", - "properties": { - "type": { - "description": "Always `refusal`.", - "type": "string", - "enum": [ - "refusal" - ], - "x-stainless-const": true - }, - "refusal": { - "type": "string", - "nullable": false - } - }, - "required": [ - "type", - "refusal" - ] - }, - "MessageContentTextAnnotationsFileCitationObject": { - "title": "File citation", - "type": "object", - "description": "A citation within the message that points to a specific quote from a specific File associated with the assistant or the message. Generated when the assistant uses the \"file_search\" tool to search files.", - "properties": { - "type": { - "description": "Always `file_citation`.", - "type": "string", - "enum": [ - "file_citation" - ], - "x-stainless-const": true - }, - "text": { - "description": "The text in the message content that needs to be replaced.", - "type": "string" - }, - "file_citation": { - "type": "object", - "properties": { - "file_id": { - "description": "The ID of the specific File the citation is from.", - "type": "string" - } - }, - "required": [ - "file_id" - ] - }, - "start_index": { - "type": "integer", - "minimum": 0 - }, - "end_index": { - "type": "integer", - "minimum": 0 - } - }, - "required": [ - "type", - "text", - "file_citation", - "start_index", - "end_index" - ] - }, - "MessageContentTextAnnotationsFilePathObject": { - "title": "File path", - "type": "object", - "description": "A URL for the file that's generated when the assistant used the `code_interpreter` tool to generate a file.", - "properties": { - "type": { - "description": "Always `file_path`.", - "type": "string", - "enum": [ - "file_path" - ], - "x-stainless-const": true - }, - "text": { - "description": "The text in the message content that needs to be replaced.", - "type": "string" - }, - "file_path": { - "type": "object", - "properties": { - "file_id": { - "description": "The ID of the file that was generated.", - "type": "string" - } - }, - "required": [ - "file_id" - ] - }, - "start_index": { - "type": "integer", - "minimum": 0 - }, - "end_index": { - "type": "integer", - "minimum": 0 - } - }, - "required": [ - "type", - "text", - "file_path", - "start_index", - "end_index" - ] - }, - "MessageContentTextObject": { - "title": "Text", - "type": "object", - "description": "The text content that is part of a message.", - "properties": { - "type": { - "description": "Always `text`.", - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - }, - "text": { - "type": "object", - "properties": { - "value": { - "description": "The data that makes up the text.", - "type": "string" - }, - "annotations": { - "type": "array", - "items": { - "$ref": "#/components/schemas/TextAnnotation" - } - } - }, - "required": [ - "value", - "annotations" - ] - } - }, - "required": [ - "type", - "text" - ] - }, - "MessageDeltaContentImageFileObject": { - "title": "Image file", - "type": "object", - "description": "References an image [File](https://platform.openai.com/docs/api-reference/files) in the content of a message.", - "properties": { - "index": { - "type": "integer", - "description": "The index of the content part in the message." - }, - "type": { - "description": "Always `image_file`.", - "type": "string", - "enum": [ - "image_file" - ], - "x-stainless-const": true - }, - "image_file": { - "type": "object", - "properties": { - "file_id": { - "description": "The [File](https://platform.openai.com/docs/api-reference/files) ID of the image in the message content. Set `purpose=\"vision\"` when uploading the File if you need to later display the file content.", - "type": "string" - }, - "detail": { - "type": "string", - "description": "Specifies the detail level of the image if specified by the user. `low` uses fewer tokens, you can opt in to high resolution using `high`.", - "enum": [ - "auto", - "low", - "high" - ], - "default": "auto" - } - } - } - }, - "required": [ - "index", - "type" - ] - }, - "MessageDeltaContentImageUrlObject": { - "title": "Image URL", - "type": "object", - "description": "References an image URL in the content of a message.", - "properties": { - "index": { - "type": "integer", - "description": "The index of the content part in the message." - }, - "type": { - "description": "Always `image_url`.", - "type": "string", - "enum": [ - "image_url" - ], - "x-stainless-const": true - }, - "image_url": { - "type": "object", - "properties": { - "url": { - "description": "The URL of the image, must be a supported image types: jpeg, jpg, png, gif, webp.", - "type": "string" - }, - "detail": { - "type": "string", - "description": "Specifies the detail level of the image. `low` uses fewer tokens, you can opt in to high resolution using `high`.", - "enum": [ - "auto", - "low", - "high" - ], - "default": "auto" - } - } - } - }, - "required": [ - "index", - "type" - ] - }, - "MessageDeltaContentRefusalObject": { - "title": "Refusal", - "type": "object", - "description": "The refusal content that is part of a message.", - "properties": { - "index": { - "type": "integer", - "description": "The index of the refusal part in the message." - }, - "type": { - "description": "Always `refusal`.", - "type": "string", - "enum": [ - "refusal" - ], - "x-stainless-const": true - }, - "refusal": { - "type": "string" - } - }, - "required": [ - "index", - "type" - ] - }, - "MessageDeltaContentTextAnnotationsFileCitationObject": { - "title": "File citation", - "type": "object", - "description": "A citation within the message that points to a specific quote from a specific File associated with the assistant or the message. Generated when the assistant uses the \"file_search\" tool to search files.", - "properties": { - "index": { - "type": "integer", - "description": "The index of the annotation in the text content part." - }, - "type": { - "description": "Always `file_citation`.", - "type": "string", - "enum": [ - "file_citation" - ], - "x-stainless-const": true - }, - "text": { - "description": "The text in the message content that needs to be replaced.", - "type": "string" - }, - "file_citation": { - "type": "object", - "properties": { - "file_id": { - "description": "The ID of the specific File the citation is from.", - "type": "string" - }, - "quote": { - "description": "The specific quote in the file.", - "type": "string" - } - } - }, - "start_index": { - "type": "integer", - "minimum": 0 - }, - "end_index": { - "type": "integer", - "minimum": 0 - } - }, - "required": [ - "index", - "type" - ] - }, - "MessageDeltaContentTextAnnotationsFilePathObject": { - "title": "File path", - "type": "object", - "description": "A URL for the file that's generated when the assistant used the `code_interpreter` tool to generate a file.", - "properties": { - "index": { - "type": "integer", - "description": "The index of the annotation in the text content part." - }, - "type": { - "description": "Always `file_path`.", - "type": "string", - "enum": [ - "file_path" - ], - "x-stainless-const": true - }, - "text": { - "description": "The text in the message content that needs to be replaced.", - "type": "string" - }, - "file_path": { - "type": "object", - "properties": { - "file_id": { - "description": "The ID of the file that was generated.", - "type": "string" - } - } - }, - "start_index": { - "type": "integer", - "minimum": 0 - }, - "end_index": { - "type": "integer", - "minimum": 0 - } - }, - "required": [ - "index", - "type" - ] - }, - "MessageDeltaContentTextObject": { - "title": "Text", - "type": "object", - "description": "The text content that is part of a message.", - "properties": { - "index": { - "type": "integer", - "description": "The index of the content part in the message." - }, - "type": { - "description": "Always `text`.", - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - }, - "text": { - "type": "object", - "properties": { - "value": { - "description": "The data that makes up the text.", - "type": "string" - }, - "annotations": { - "type": "array", - "items": { - "$ref": "#/components/schemas/TextAnnotationDelta" - } - } - } - } - }, - "required": [ - "index", - "type" - ] - }, - "MessageDeltaObject": { - "type": "object", - "title": "Message delta object", - "description": "Represents a message delta i.e. any changed fields on a message during streaming.\n", - "properties": { - "id": { - "description": "The identifier of the message, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `thread.message.delta`.", - "type": "string", - "enum": [ - "thread.message.delta" - ], - "x-stainless-const": true - }, - "delta": { - "description": "The delta containing the fields that have changed on the Message.", - "type": "object", - "properties": { - "role": { - "description": "The entity that produced the message. One of `user` or `assistant`.", - "type": "string", - "enum": [ - "user", - "assistant" - ] - }, - "content": { - "description": "The content of the message in array of text and/or images.", - "type": "array", - "items": { - "$ref": "#/components/schemas/MessageContentDelta" - } - } - } - } - }, - "required": [ - "id", - "object", - "delta" - ], - "x-oaiMeta": { - "name": "The message delta object", - "beta": true, - "example": "{\n \"id\": \"msg_123\",\n \"object\": \"thread.message.delta\",\n \"delta\": {\n \"content\": [\n {\n \"index\": 0,\n \"type\": \"text\",\n \"text\": { \"value\": \"Hello\", \"annotations\": [] }\n }\n ]\n }\n}\n" - } - }, - "MessageObject": { - "type": "object", - "title": "The message object", - "description": "Represents a message within a [thread](https://platform.openai.com/docs/api-reference/threads).", - "properties": { - "id": { - "description": "The identifier, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `thread.message`.", - "type": "string", - "enum": [ - "thread.message" - ], - "x-stainless-const": true - }, - "created_at": { - "description": "The Unix timestamp (in seconds) for when the message was created.", - "type": "integer" - }, - "thread_id": { - "description": "The [thread](https://platform.openai.com/docs/api-reference/threads) ID that this message belongs to.", - "type": "string" - }, - "status": { - "description": "The status of the message, which can be either `in_progress`, `incomplete`, or `completed`.", - "type": "string", - "enum": [ - "in_progress", - "incomplete", - "completed" - ] - }, - "incomplete_details": { - "description": "On an incomplete message, details about why the message is incomplete.", - "type": "object", - "properties": { - "reason": { - "type": "string", - "description": "The reason the message is incomplete.", - "enum": [ - "content_filter", - "max_tokens", - "run_cancelled", - "run_expired", - "run_failed" - ] - } - }, - "nullable": true, - "required": [ - "reason" - ] - }, - "completed_at": { - "description": "The Unix timestamp (in seconds) for when the message was completed.", - "type": "integer", - "nullable": true - }, - "incomplete_at": { - "description": "The Unix timestamp (in seconds) for when the message was marked as incomplete.", - "type": "integer", - "nullable": true - }, - "role": { - "description": "The entity that produced the message. One of `user` or `assistant`.", - "type": "string", - "enum": [ - "user", - "assistant" - ] - }, - "content": { - "description": "The content of the message in array of text and/or images.", - "type": "array", - "items": { - "$ref": "#/components/schemas/MessageContent" - } - }, - "assistant_id": { - "description": "If applicable, the ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) that authored this message.", - "type": "string", - "nullable": true - }, - "run_id": { - "description": "The ID of the [run](https://platform.openai.com/docs/api-reference/runs) associated with the creation of this message. Value is `null` when messages are created manually using the create message or create thread endpoints.", - "type": "string", - "nullable": true - }, - "attachments": { - "type": "array", - "items": { - "type": "object", - "properties": { - "file_id": { - "type": "string", - "description": "The ID of the file to attach to the message." - }, - "tools": { - "description": "The tools to add this file to.", - "type": "array", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/AssistantToolsCode" - }, - { - "$ref": "#/components/schemas/AssistantToolsFileSearchTypeOnly" - } - ] - } - } - } - }, - "description": "A list of files attached to the message, and the tools they were added to.", - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - }, - "required": [ - "id", - "object", - "created_at", - "thread_id", - "status", - "incomplete_details", - "completed_at", - "incomplete_at", - "role", - "content", - "assistant_id", - "run_id", - "attachments", - "metadata" - ], - "x-oaiMeta": { - "name": "The message object", - "beta": true, - "example": "{\n \"id\": \"msg_abc123\",\n \"object\": \"thread.message\",\n \"created_at\": 1698983503,\n \"thread_id\": \"thread_abc123\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": {\n \"value\": \"Hi! How can I help you today?\",\n \"annotations\": []\n }\n }\n ],\n \"assistant_id\": \"asst_abc123\",\n \"run_id\": \"run_abc123\",\n \"attachments\": [],\n \"metadata\": {}\n}\n" - } - }, - "MessageRequestContentTextObject": { - "title": "Text", - "type": "object", - "description": "The text content that is part of a message.", - "properties": { - "type": { - "description": "Always `text`.", - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "Text content to be sent to the model" - } - }, - "required": [ - "type", - "text" - ] - }, - "MessageStreamEvent": { - "anyOf": [ - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.message.created" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/MessageObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) is created.", - "x-oaiMeta": { - "dataDescription": "`data` is a [message](/docs/api-reference/messages/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.message.in_progress" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/MessageObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) moves to an `in_progress` state.", - "x-oaiMeta": { - "dataDescription": "`data` is a [message](/docs/api-reference/messages/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.message.delta" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/MessageDeltaObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when parts of a [Message](https://platform.openai.com/docs/api-reference/messages/object) are being streamed.", - "x-oaiMeta": { - "dataDescription": "`data` is a [message delta](/docs/api-reference/assistants-streaming/message-delta-object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.message.completed" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/MessageObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) is completed.", - "x-oaiMeta": { - "dataDescription": "`data` is a [message](/docs/api-reference/messages/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.message.incomplete" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/MessageObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) ends before it is completed.", - "x-oaiMeta": { - "dataDescription": "`data` is a [message](/docs/api-reference/messages/object)" - } - } - ], - "discriminator": { - "propertyName": "event" - } - }, - "Metadata": { - "type": "object", - "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard. \n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.\n", - "additionalProperties": { - "type": "string" - }, - "x-oaiTypeLabel": "map", - "nullable": true - }, - "Model": { - "title": "Model", - "description": "Describes an OpenAI model offering that can be used with the API.", - "properties": { - "id": { - "type": "string", - "description": "The model identifier, which can be referenced in the API endpoints." - }, - "created": { - "type": "integer", - "description": "The Unix timestamp (in seconds) when the model was created." - }, - "object": { - "type": "string", - "description": "The object type, which is always \"model\".", - "enum": [ - "model" - ], - "x-stainless-const": true - }, - "owned_by": { - "type": "string", - "description": "The organization that owns the model." - } - }, - "required": [ - "id", - "object", - "created", - "owned_by" - ], - "x-oaiMeta": { - "name": "The model object", - "example": "{\n \"id\": \"VAR_chat_model_id\",\n \"object\": \"model\",\n \"created\": 1686935002,\n \"owned_by\": \"openai\"\n}\n" - } - }, - "ModelIds": { - "anyOf": [ - { - "$ref": "#/components/schemas/ModelIdsShared" - }, - { - "$ref": "#/components/schemas/ModelIdsResponses" - } - ] - }, - "ModelIdsResponses": { - "example": "gpt-4o", - "anyOf": [ - { - "$ref": "#/components/schemas/ModelIdsShared" - }, - { - "type": "string", - "title": "ResponsesOnlyModel", - "enum": [ - "o1-pro", - "o1-pro-2025-03-19", - "o3-pro", - "o3-pro-2025-06-10", - "o3-deep-research", - "o3-deep-research-2025-06-26", - "o4-mini-deep-research", - "o4-mini-deep-research-2025-06-26", - "computer-use-preview", - "computer-use-preview-2025-03-11" - ] - } - ] - }, - "ModelIdsShared": { - "example": "gpt-4o", - "anyOf": [ - { - "type": "string" - }, - { - "$ref": "#/components/schemas/ChatModel" - } - ] - }, - "ModelResponseProperties": { - "type": "object", - "properties": { - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "top_logprobs": { - "description": "An integer between 0 and 20 specifying the number of most likely tokens to\nreturn at each token position, each with an associated log probability.\n", - "type": "integer", - "minimum": 0, - "maximum": 20, - "nullable": true - }, - "temperature": { - "type": "number", - "minimum": 0, - "maximum": 2, - "default": 1, - "example": 1, - "nullable": true, - "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\nWe generally recommend altering this or `top_p` but not both.\n" - }, - "top_p": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 1, - "example": 1, - "nullable": true, - "description": "An alternative to sampling with temperature, called nucleus sampling,\nwhere the model considers the results of the tokens with top_p probability\nmass. So 0.1 means only the tokens comprising the top 10% probability mass\nare considered.\n\nWe generally recommend altering this or `temperature` but not both.\n" - }, - "user": { - "type": "string", - "example": "user-1234", - "deprecated": true, - "description": "This field is being replaced by `safety_identifier` and `prompt_cache_key`. Use `prompt_cache_key` instead to maintain caching optimizations.\nA stable identifier for your end-users.\nUsed to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#safety-identifiers).\n" - }, - "safety_identifier": { - "type": "string", - "example": "safety-identifier-1234", - "description": "A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies.\nThe IDs should be a string that uniquely identifies each user. We recommend hashing their username or email address, in order to avoid sending us any identifying information. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#safety-identifiers).\n" - }, - "prompt_cache_key": { - "type": "string", - "example": "prompt-cache-key-1234", - "description": "Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the `user` field. [Learn more](https://platform.openai.com/docs/guides/prompt-caching).\n" - }, - "service_tier": { - "$ref": "#/components/schemas/ServiceTier" - } - } - }, - "ModifyAssistantRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "model": { - "description": "ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models) for descriptions of them.\n", - "anyOf": [ - { - "type": "string" - }, - { - "$ref": "#/components/schemas/AssistantSupportedModels" - } - ] - }, - "reasoning_effort": { - "$ref": "#/components/schemas/ReasoningEffort" - }, - "name": { - "description": "The name of the assistant. The maximum length is 256 characters.\n", - "type": "string", - "nullable": true, - "maxLength": 256 - }, - "description": { - "description": "The description of the assistant. The maximum length is 512 characters.\n", - "type": "string", - "nullable": true, - "maxLength": 512 - }, - "instructions": { - "description": "The system instructions that the assistant uses. The maximum length is 256,000 characters.\n", - "type": "string", - "nullable": true, - "maxLength": 256000 - }, - "tools": { - "description": "A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.\n", - "default": [], - "type": "array", - "maxItems": 128, - "items": { - "$ref": "#/components/schemas/AssistantTool" - } - }, - "tool_resources": { - "type": "object", - "description": "A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.\n", - "properties": { - "code_interpreter": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "Overrides the list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.\n", - "default": [], - "maxItems": 20, - "items": { - "type": "string" - } - } - } - }, - "file_search": { - "type": "object", - "properties": { - "vector_store_ids": { - "type": "array", - "description": "Overrides the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.\n", - "maxItems": 1, - "items": { - "type": "string" - } - } - } - } - }, - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "temperature": { - "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n", - "type": "number", - "minimum": 0, - "maximum": 2, - "default": 1, - "example": 1, - "nullable": true - }, - "top_p": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 1, - "example": 1, - "nullable": true, - "description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or temperature but not both.\n" - }, - "response_format": { - "$ref": "#/components/schemas/AssistantsApiResponseFormatOption", - "nullable": true - } - } - }, - "ModifyCertificateRequest": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The updated name for the certificate" - } - }, - "required": [ - "name" - ] - }, - "ModifyMessageRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - }, - "ModifyRunRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - }, - "ModifyThreadRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "tool_resources": { - "type": "object", - "description": "A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.\n", - "properties": { - "code_interpreter": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.\n", - "default": [], - "maxItems": 20, - "items": { - "type": "string" - } - } - } - }, - "file_search": { - "type": "object", - "properties": { - "vector_store_ids": { - "type": "array", - "description": "The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this thread. There can be a maximum of 1 vector store attached to the thread.\n", - "maxItems": 1, - "items": { - "type": "string" - } - } - } - } - }, - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - }, - "Move": { - "type": "object", - "title": "Move", - "description": "A mouse move action.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "move" - ], - "default": "move", - "description": "Specifies the event type. For a move action, this property is \nalways set to `move`.\n", - "x-stainless-const": true - }, - "x": { - "type": "integer", - "description": "The x-coordinate to move to.\n" - }, - "y": { - "type": "integer", - "description": "The y-coordinate to move to.\n" - } - }, - "required": [ - "type", - "x", - "y" - ] - }, - "OpenAIFile": { - "title": "OpenAIFile", - "description": "The `File` object represents a document that has been uploaded to OpenAI.", - "properties": { - "id": { - "type": "string", - "description": "The file identifier, which can be referenced in the API endpoints." - }, - "bytes": { - "type": "integer", - "description": "The size of the file, in bytes." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the file was created." - }, - "expires_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the file will expire." - }, - "filename": { - "type": "string", - "description": "The name of the file." - }, - "object": { - "type": "string", - "description": "The object type, which is always `file`.", - "enum": [ - "file" - ], - "x-stainless-const": true - }, - "purpose": { - "type": "string", - "description": "The intended purpose of the file. Supported values are `assistants`, `assistants_output`, `batch`, `batch_output`, `fine-tune`, `fine-tune-results`, `vision`, and `user_data`.", - "enum": [ - "assistants", - "assistants_output", - "batch", - "batch_output", - "fine-tune", - "fine-tune-results", - "vision", - "user_data" - ] - }, - "status": { - "type": "string", - "deprecated": true, - "description": "Deprecated. The current status of the file, which can be either `uploaded`, `processed`, or `error`.", - "enum": [ - "uploaded", - "processed", - "error" - ] - }, - "status_details": { - "type": "string", - "deprecated": true, - "description": "Deprecated. For details on why a fine-tuning training file failed validation, see the `error` field on `fine_tuning.job`." - } - }, - "required": [ - "id", - "object", - "bytes", - "created_at", - "filename", - "purpose", - "status" - ], - "x-oaiMeta": { - "name": "The file object", - "example": "{\n \"id\": \"file-abc123\",\n \"object\": \"file\",\n \"bytes\": 120000,\n \"created_at\": 1677610602,\n \"expires_at\": 1680202602,\n \"filename\": \"salesOverview.pdf\",\n \"purpose\": \"assistants\",\n}\n" - } - }, - "OtherChunkingStrategyResponseParam": { - "type": "object", - "title": "Other Chunking Strategy", - "description": "This is returned when the chunking strategy is unknown. Typically, this is because the file was indexed before the `chunking_strategy` concept was introduced in the API.", - "additionalProperties": false, - "properties": { - "type": { - "type": "string", - "description": "Always `other`.", - "enum": [ - "other" - ], - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "OutputAudio": { - "type": "object", - "title": "Output audio", - "description": "An audio output from the model.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the output audio. Always `output_audio`.\n", - "enum": [ - "output_audio" - ], - "x-stainless-const": true - }, - "data": { - "type": "string", - "description": "Base64-encoded audio data from the model.\n" - }, - "transcript": { - "type": "string", - "description": "The transcript of the audio data from the model.\n" - } - }, - "required": [ - "type", - "data", - "transcript" - ] - }, - "OutputContent": { - "anyOf": [ - { - "$ref": "#/components/schemas/OutputTextContent" - }, - { - "$ref": "#/components/schemas/RefusalContent" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "OutputItem": { - "anyOf": [ - { - "$ref": "#/components/schemas/OutputMessage" - }, - { - "$ref": "#/components/schemas/FileSearchToolCall" - }, - { - "$ref": "#/components/schemas/FunctionToolCall" - }, - { - "$ref": "#/components/schemas/WebSearchToolCall" - }, - { - "$ref": "#/components/schemas/ComputerToolCall" - }, - { - "$ref": "#/components/schemas/ReasoningItem" - }, - { - "$ref": "#/components/schemas/ImageGenToolCall" - }, - { - "$ref": "#/components/schemas/CodeInterpreterToolCall" - }, - { - "$ref": "#/components/schemas/LocalShellToolCall" - }, - { - "$ref": "#/components/schemas/MCPToolCall" - }, - { - "$ref": "#/components/schemas/MCPListTools" - }, - { - "$ref": "#/components/schemas/MCPApprovalRequest" - }, - { - "$ref": "#/components/schemas/CustomToolCall" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "OutputMessage": { - "type": "object", - "title": "Output message", - "description": "An output message from the model.\n", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the output message.\n", - "x-stainless-go-json": "omitzero" - }, - "type": { - "type": "string", - "description": "The type of the output message. Always `message`.\n", - "enum": [ - "message" - ], - "x-stainless-const": true - }, - "role": { - "type": "string", - "description": "The role of the output message. Always `assistant`.\n", - "enum": [ - "assistant" - ], - "x-stainless-const": true - }, - "content": { - "type": "array", - "description": "The content of the output message.\n", - "items": { - "$ref": "#/components/schemas/OutputContent" - } - }, - "status": { - "type": "string", - "description": "The status of the message input. One of `in_progress`, `completed`, or\n`incomplete`. Populated when input items are returned via API.\n", - "enum": [ - "in_progress", - "completed", - "incomplete" - ] - } - }, - "required": [ - "id", - "type", - "role", - "content", - "status" - ] - }, - "ParallelToolCalls": { - "description": "Whether to enable [parallel function calling](https://platform.openai.com/docs/guides/function-calling#configuring-parallel-function-calling) during tool use.", - "type": "boolean", - "default": true - }, - "PartialImages": { - "type": "integer", - "maximum": 3, - "minimum": 0, - "default": 0, - "example": 1, - "nullable": true, - "description": "The number of partial images to generate. This parameter is used for\nstreaming responses that return partial images. Value must be between 0 and 3.\nWhen set to 0, the response will be a single image sent in one streaming event.\n\nNote that the final image may be sent before the full number of partial images \nare generated if the full image is generated more quickly.\n" - }, - "PredictionContent": { - "type": "object", - "title": "Static Content", - "description": "Static predicted output content, such as the content of a text file that is\nbeing regenerated.\n", - "required": [ - "type", - "content" - ], - "properties": { - "type": { - "type": "string", - "enum": [ - "content" - ], - "description": "The type of the predicted content you want to provide. This type is\ncurrently always `content`.\n", - "x-stainless-const": true - }, - "content": { - "description": "The content that should be matched when generating a model response.\nIf generated tokens would match this content, the entire model response\ncan be returned much more quickly.\n", - "anyOf": [ - { - "type": "string", - "title": "Text content", - "description": "The content used for a Predicted Output. This is often the\ntext of a file you are regenerating with minor changes.\n" - }, - { - "type": "array", - "description": "An array of content parts with a defined type. Supported options differ based on the [model](https://platform.openai.com/docs/models) being used to generate the response. Can contain text inputs.", - "title": "Array of content parts", - "items": { - "$ref": "#/components/schemas/ChatCompletionRequestMessageContentPartText" - }, - "minItems": 1 - } - ] - } - } - }, - "Project": { - "type": "object", - "description": "Represents an individual project.", - "properties": { - "id": { - "type": "string", - "description": "The identifier, which can be referenced in API endpoints" - }, - "object": { - "type": "string", - "enum": [ - "organization.project" - ], - "description": "The object type, which is always `organization.project`", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the project. This appears in reporting." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the project was created." - }, - "archived_at": { - "type": "integer", - "nullable": true, - "description": "The Unix timestamp (in seconds) of when the project was archived or `null`." - }, - "status": { - "type": "string", - "enum": [ - "active", - "archived" - ], - "description": "`active` or `archived`" - } - }, - "required": [ - "id", - "object", - "name", - "created_at", - "status" - ], - "x-oaiMeta": { - "name": "The project object", - "example": "{\n \"id\": \"proj_abc\",\n \"object\": \"organization.project\",\n \"name\": \"Project example\",\n \"created_at\": 1711471533,\n \"archived_at\": null,\n \"status\": \"active\"\n}\n" - } - }, - "ProjectApiKey": { - "type": "object", - "description": "Represents an individual API key in a project.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.project.api_key" - ], - "description": "The object type, which is always `organization.project.api_key`", - "x-stainless-const": true - }, - "redacted_value": { - "type": "string", - "description": "The redacted value of the API key" - }, - "name": { - "type": "string", - "description": "The name of the API key" - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the API key was created" - }, - "last_used_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the API key was last used." - }, - "id": { - "type": "string", - "description": "The identifier, which can be referenced in API endpoints" - }, - "owner": { - "type": "object", - "properties": { - "type": { - "type": "string", - "enum": [ - "user", - "service_account" - ], - "description": "`user` or `service_account`" - }, - "user": { - "$ref": "#/components/schemas/ProjectUser" - }, - "service_account": { - "$ref": "#/components/schemas/ProjectServiceAccount" - } - } - } - }, - "required": [ - "object", - "redacted_value", - "name", - "created_at", - "last_used_at", - "id", - "owner" - ], - "x-oaiMeta": { - "name": "The project API key object", - "example": "{\n \"object\": \"organization.project.api_key\",\n \"redacted_value\": \"sk-abc...def\",\n \"name\": \"My API Key\",\n \"created_at\": 1711471533,\n \"last_used_at\": 1711471534,\n \"id\": \"key_abc\",\n \"owner\": {\n \"type\": \"user\",\n \"user\": {\n \"object\": \"organization.project.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"created_at\": 1711471533\n }\n }\n}\n" - } - }, - "ProjectApiKeyDeleteResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.project.api_key.deleted" - ], - "x-stainless-const": true - }, - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - } - }, - "required": [ - "object", - "id", - "deleted" - ] - }, - "ProjectApiKeyListResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ProjectApiKey" - } - }, - "first_id": { - "type": "string" - }, - "last_id": { - "type": "string" - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ProjectCreateRequest": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The friendly name of the project, this name appears in reports." - } - }, - "required": [ - "name" - ] - }, - "ProjectListResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Project" - } - }, - "first_id": { - "type": "string" - }, - "last_id": { - "type": "string" - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ProjectRateLimit": { - "type": "object", - "description": "Represents a project rate limit config.", - "properties": { - "object": { - "type": "string", - "enum": [ - "project.rate_limit" - ], - "description": "The object type, which is always `project.rate_limit`", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The identifier, which can be referenced in API endpoints." - }, - "model": { - "type": "string", - "description": "The model this rate limit applies to." - }, - "max_requests_per_1_minute": { - "type": "integer", - "description": "The maximum requests per minute." - }, - "max_tokens_per_1_minute": { - "type": "integer", - "description": "The maximum tokens per minute." - }, - "max_images_per_1_minute": { - "type": "integer", - "description": "The maximum images per minute. Only present for relevant models." - }, - "max_audio_megabytes_per_1_minute": { - "type": "integer", - "description": "The maximum audio megabytes per minute. Only present for relevant models." - }, - "max_requests_per_1_day": { - "type": "integer", - "description": "The maximum requests per day. Only present for relevant models." - }, - "batch_1_day_max_input_tokens": { - "type": "integer", - "description": "The maximum batch input tokens per day. Only present for relevant models." - } - }, - "required": [ - "object", - "id", - "model", - "max_requests_per_1_minute", - "max_tokens_per_1_minute" - ], - "x-oaiMeta": { - "name": "The project rate limit object", - "example": "{\n \"object\": \"project.rate_limit\",\n \"id\": \"rl_ada\",\n \"model\": \"ada\",\n \"max_requests_per_1_minute\": 600,\n \"max_tokens_per_1_minute\": 150000,\n \"max_images_per_1_minute\": 10\n}\n" - } - }, - "ProjectRateLimitListResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ProjectRateLimit" - } - }, - "first_id": { - "type": "string" - }, - "last_id": { - "type": "string" - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ProjectRateLimitUpdateRequest": { - "type": "object", - "properties": { - "max_requests_per_1_minute": { - "type": "integer", - "description": "The maximum requests per minute." - }, - "max_tokens_per_1_minute": { - "type": "integer", - "description": "The maximum tokens per minute." - }, - "max_images_per_1_minute": { - "type": "integer", - "description": "The maximum images per minute. Only relevant for certain models." - }, - "max_audio_megabytes_per_1_minute": { - "type": "integer", - "description": "The maximum audio megabytes per minute. Only relevant for certain models." - }, - "max_requests_per_1_day": { - "type": "integer", - "description": "The maximum requests per day. Only relevant for certain models." - }, - "batch_1_day_max_input_tokens": { - "type": "integer", - "description": "The maximum batch input tokens per day. Only relevant for certain models." - } - } - }, - "ProjectServiceAccount": { - "type": "object", - "description": "Represents an individual service account in a project.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.project.service_account" - ], - "description": "The object type, which is always `organization.project.service_account`", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The identifier, which can be referenced in API endpoints" - }, - "name": { - "type": "string", - "description": "The name of the service account" - }, - "role": { - "type": "string", - "enum": [ - "owner", - "member" - ], - "description": "`owner` or `member`" - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the service account was created" - } - }, - "required": [ - "object", - "id", - "name", - "role", - "created_at" - ], - "x-oaiMeta": { - "name": "The project service account object", - "example": "{\n \"object\": \"organization.project.service_account\",\n \"id\": \"svc_acct_abc\",\n \"name\": \"Service Account\",\n \"role\": \"owner\",\n \"created_at\": 1711471533\n}\n" - } - }, - "ProjectServiceAccountApiKey": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.project.service_account.api_key" - ], - "description": "The object type, which is always `organization.project.service_account.api_key`", - "x-stainless-const": true - }, - "value": { - "type": "string" - }, - "name": { - "type": "string" - }, - "created_at": { - "type": "integer" - }, - "id": { - "type": "string" - } - }, - "required": [ - "object", - "value", - "name", - "created_at", - "id" - ] - }, - "ProjectServiceAccountCreateRequest": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The name of the service account being created." - } - }, - "required": [ - "name" - ] - }, - "ProjectServiceAccountCreateResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.project.service_account" - ], - "x-stainless-const": true - }, - "id": { - "type": "string" - }, - "name": { - "type": "string" - }, - "role": { - "type": "string", - "enum": [ - "member" - ], - "description": "Service accounts can only have one role of type `member`", - "x-stainless-const": true - }, - "created_at": { - "type": "integer" - }, - "api_key": { - "$ref": "#/components/schemas/ProjectServiceAccountApiKey" - } - }, - "required": [ - "object", - "id", - "name", - "role", - "created_at", - "api_key" - ] - }, - "ProjectServiceAccountDeleteResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.project.service_account.deleted" - ], - "x-stainless-const": true - }, - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - } - }, - "required": [ - "object", - "id", - "deleted" - ] - }, - "ProjectServiceAccountListResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ProjectServiceAccount" - } - }, - "first_id": { - "type": "string" - }, - "last_id": { - "type": "string" - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ProjectUpdateRequest": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The updated name of the project, this name appears in reports." - } - }, - "required": [ - "name" - ] - }, - "ProjectUser": { - "type": "object", - "description": "Represents an individual user in a project.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.project.user" - ], - "description": "The object type, which is always `organization.project.user`", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The identifier, which can be referenced in API endpoints" - }, - "name": { - "type": "string", - "description": "The name of the user" - }, - "email": { - "type": "string", - "description": "The email address of the user" - }, - "role": { - "type": "string", - "enum": [ - "owner", - "member" - ], - "description": "`owner` or `member`" - }, - "added_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the project was added." - } - }, - "required": [ - "object", - "id", - "name", - "email", - "role", - "added_at" - ], - "x-oaiMeta": { - "name": "The project user object", - "example": "{\n \"object\": \"organization.project.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n}\n" - } - }, - "ProjectUserCreateRequest": { - "type": "object", - "properties": { - "user_id": { - "type": "string", - "description": "The ID of the user." - }, - "role": { - "type": "string", - "enum": [ - "owner", - "member" - ], - "description": "`owner` or `member`" - } - }, - "required": [ - "user_id", - "role" - ] - }, - "ProjectUserDeleteResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.project.user.deleted" - ], - "x-stainless-const": true - }, - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - } - }, - "required": [ - "object", - "id", - "deleted" - ] - }, - "ProjectUserListResponse": { - "type": "object", - "properties": { - "object": { - "type": "string" - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ProjectUser" - } - }, - "first_id": { - "type": "string" - }, - "last_id": { - "type": "string" - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "ProjectUserUpdateRequest": { - "type": "object", - "properties": { - "role": { - "type": "string", - "enum": [ - "owner", - "member" - ], - "description": "`owner` or `member`" - } - }, - "required": [ - "role" - ] - }, - "Prompt": { - "type": "object", - "nullable": true, - "description": "Reference to a prompt template and its variables. \n[Learn more](https://platform.openai.com/docs/guides/text?api-mode=responses#reusable-prompts).\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique identifier of the prompt template to use." - }, - "version": { - "type": "string", - "description": "Optional version of the prompt template.", - "nullable": true - }, - "variables": { - "$ref": "#/components/schemas/ResponsePromptVariables" - } - } - }, - "RealtimeAudioFormats": { - "anyOf": [ - { - "type": "object", - "title": "PCM audio format", - "description": "The PCM audio format. Only a 24kHz sample rate is supported.", - "properties": { - "type": { - "type": "string", - "description": "The audio format. Always `audio/pcm`.", - "enum": [ - "audio/pcm" - ] - }, - "rate": { - "type": "integer", - "description": "The sample rate of the audio. Always `24000`.", - "enum": [ - 24000 - ] - } - } - }, - { - "type": "object", - "title": "PCMU audio format", - "description": "The G.711 ฮผ-law format.", - "properties": { - "type": { - "type": "string", - "description": "The audio format. Always `audio/pcmu`.", - "enum": [ - "audio/pcmu" - ] - } - } - }, - { - "type": "object", - "title": "PCMA audio format", - "description": "The G.711 A-law format.", - "properties": { - "type": { - "type": "string", - "description": "The audio format. Always `audio/pcma`.", - "enum": [ - "audio/pcma" - ] - } - } - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "RealtimeClientEvent": { - "discriminator": { - "propertyName": "type" - }, - "description": "A realtime client event.\n", - "anyOf": [ - { - "$ref": "#/components/schemas/RealtimeClientEventConversationItemCreate" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventConversationItemDelete" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventConversationItemRetrieve" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventConversationItemTruncate" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventInputAudioBufferAppend" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventInputAudioBufferClear" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventOutputAudioBufferClear" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventInputAudioBufferCommit" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventResponseCancel" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventResponseCreate" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventSessionUpdate" - }, - { - "$ref": "#/components/schemas/RealtimeClientEventTranscriptionSessionUpdate" - } - ] - }, - "RealtimeClientEventConversationItemCreate": { - "type": "object", - "description": "Add a new Item to the Conversation's context, including messages, function \ncalls, and function call responses. This event can be used both to populate a \n\"history\" of the conversation and to add new items mid-stream, but has the \ncurrent limitation that it cannot populate assistant audio messages.\n\nIf successful, the server will respond with a `conversation.item.created` \nevent, otherwise an `error` event will be sent.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `conversation.item.create`.", - "x-stainless-const": true, - "const": "conversation.item.create" - }, - "previous_item_id": { - "type": "string", - "description": "The ID of the preceding item after which the new item will be inserted. \nIf not set, the new item will be appended to the end of the conversation.\nIf set to `root`, the new item will be added to the beginning of the conversation.\nIf set to an existing ID, it allows an item to be inserted mid-conversation. If the\nID cannot be found, an error will be returned and the item will not be added.\n" - }, - "item": { - "$ref": "#/components/schemas/RealtimeConversationItem" - } - }, - "required": [ - "type", - "item" - ], - "x-oaiMeta": { - "name": "conversation.item.create", - "group": "realtime", - "example": "{\n \"type\": \"conversation.item.create\",\n \"item\": {\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"hi\"\n }\n ]\n },\n \"event_id\": \"b904fba0-0ec4-40af-8bbb-f908a9b26793\",\n \"timestamp\": \"2:30:35 PM\"\n}\n" - } - }, - "RealtimeClientEventConversationItemDelete": { - "type": "object", - "description": "Send this event when you want to remove any item from the conversation \nhistory. The server will respond with a `conversation.item.deleted` event, \nunless the item does not exist in the conversation history, in which case the \nserver will respond with an error.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `conversation.item.delete`.", - "x-stainless-const": true, - "const": "conversation.item.delete" - }, - "item_id": { - "type": "string", - "description": "The ID of the item to delete." - } - }, - "required": [ - "type", - "item_id" - ], - "x-oaiMeta": { - "name": "conversation.item.delete", - "group": "realtime", - "example": "{\n \"event_id\": \"event_901\",\n \"type\": \"conversation.item.delete\",\n \"item_id\": \"msg_003\"\n}\n" - } - }, - "RealtimeClientEventConversationItemRetrieve": { - "type": "object", - "description": "Send this event when you want to retrieve the server's representation of a specific item in the conversation history. This is useful, for example, to inspect user audio after noise cancellation and VAD.\nThe server will respond with a `conversation.item.retrieved` event,\nunless the item does not exist in the conversation history, in which case the\nserver will respond with an error.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `conversation.item.retrieve`.", - "x-stainless-const": true, - "const": "conversation.item.retrieve" - }, - "item_id": { - "type": "string", - "description": "The ID of the item to retrieve." - } - }, - "required": [ - "type", - "item_id" - ], - "x-oaiMeta": { - "name": "conversation.item.retrieve", - "group": "realtime", - "example": "{\n \"event_id\": \"event_901\",\n \"type\": \"conversation.item.retrieve\",\n \"item_id\": \"msg_003\"\n}\n" - } - }, - "RealtimeClientEventConversationItemTruncate": { - "type": "object", - "description": "Send this event to truncate a previous assistant messageโ€™s audio. The server \nwill produce audio faster than realtime, so this event is useful when the user \ninterrupts to truncate audio that has already been sent to the client but not \nyet played. This will synchronize the server's understanding of the audio with \nthe client's playback.\n\nTruncating audio will delete the server-side text transcript to ensure there \nis not text in the context that hasn't been heard by the user.\n\nIf successful, the server will respond with a `conversation.item.truncated` \nevent.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `conversation.item.truncate`.", - "x-stainless-const": true, - "const": "conversation.item.truncate" - }, - "item_id": { - "type": "string", - "description": "The ID of the assistant message item to truncate. Only assistant message \nitems can be truncated.\n" - }, - "content_index": { - "type": "integer", - "description": "The index of the content part to truncate. Set this to 0." - }, - "audio_end_ms": { - "type": "integer", - "description": "Inclusive duration up to which audio is truncated, in milliseconds. If \nthe audio_end_ms is greater than the actual audio duration, the server \nwill respond with an error.\n" - } - }, - "required": [ - "type", - "item_id", - "content_index", - "audio_end_ms" - ], - "x-oaiMeta": { - "name": "conversation.item.truncate", - "group": "realtime", - "example": "{\n \"event_id\": \"event_678\",\n \"type\": \"conversation.item.truncate\",\n \"item_id\": \"msg_002\",\n \"content_index\": 0,\n \"audio_end_ms\": 1500\n}\n" - } - }, - "RealtimeClientEventInputAudioBufferAppend": { - "type": "object", - "description": "Send this event to append audio bytes to the input audio buffer. The audio \nbuffer is temporary storage you can write to and later commit. In Server VAD \nmode, the audio buffer is used to detect speech and the server will decide \nwhen to commit. When Server VAD is disabled, you must commit the audio buffer\nmanually.\n\nThe client may choose how much audio to place in each event up to a maximum \nof 15 MiB, for example streaming smaller chunks from the client may allow the \nVAD to be more responsive. Unlike made other client events, the server will \nnot send a confirmation response to this event.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `input_audio_buffer.append`.", - "x-stainless-const": true, - "const": "input_audio_buffer.append" - }, - "audio": { - "type": "string", - "description": "Base64-encoded audio bytes. This must be in the format specified by the \n`input_audio_format` field in the session configuration.\n" - } - }, - "required": [ - "type", - "audio" - ], - "x-oaiMeta": { - "name": "input_audio_buffer.append", - "group": "realtime", - "example": "{\n \"event_id\": \"event_456\",\n \"type\": \"input_audio_buffer.append\",\n \"audio\": \"Base64EncodedAudioData\"\n}\n" - } - }, - "RealtimeClientEventInputAudioBufferClear": { - "type": "object", - "description": "Send this event to clear the audio bytes in the buffer. The server will \nrespond with an `input_audio_buffer.cleared` event.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `input_audio_buffer.clear`.", - "x-stainless-const": true, - "const": "input_audio_buffer.clear" - } - }, - "required": [ - "type" - ], - "x-oaiMeta": { - "name": "input_audio_buffer.clear", - "group": "realtime", - "example": "{\n \"event_id\": \"event_012\",\n \"type\": \"input_audio_buffer.clear\"\n}\n" - } - }, - "RealtimeClientEventInputAudioBufferCommit": { - "type": "object", - "description": "Send this event to commit the user input audio buffer, which will create a \nnew user message item in the conversation. This event will produce an error \nif the input audio buffer is empty. When in Server VAD mode, the client does \nnot need to send this event, the server will commit the audio buffer \nautomatically.\n\nCommitting the input audio buffer will trigger input audio transcription \n(if enabled in session configuration), but it will not create a response \nfrom the model. The server will respond with an `input_audio_buffer.committed` \nevent.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `input_audio_buffer.commit`.", - "x-stainless-const": true, - "const": "input_audio_buffer.commit" - } - }, - "required": [ - "type" - ], - "x-oaiMeta": { - "name": "input_audio_buffer.commit", - "group": "realtime", - "example": "{\n \"event_id\": \"event_789\",\n \"type\": \"input_audio_buffer.commit\"\n}\n" - } - }, - "RealtimeClientEventOutputAudioBufferClear": { - "type": "object", - "description": "**WebRTC Only:** Emit to cut off the current audio response. This will trigger the server to\nstop generating audio and emit a `output_audio_buffer.cleared` event. This\nevent should be preceded by a `response.cancel` client event to stop the\ngeneration of the current response.\n[Learn more](https://platform.openai.com/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the client event used for error handling." - }, - "type": { - "description": "The event type, must be `output_audio_buffer.clear`.", - "x-stainless-const": true, - "const": "output_audio_buffer.clear" - } - }, - "required": [ - "type" - ], - "x-oaiMeta": { - "name": "output_audio_buffer.clear", - "group": "realtime", - "example": "{\n \"event_id\": \"optional_client_event_id\",\n \"type\": \"output_audio_buffer.clear\"\n}\n" - } - }, - "RealtimeClientEventResponseCancel": { - "type": "object", - "description": "Send this event to cancel an in-progress response. The server will respond \nwith a `response.done` event with a status of `response.status=cancelled`. If \nthere is no response to cancel, the server will respond with an error.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `response.cancel`.", - "x-stainless-const": true, - "const": "response.cancel" - }, - "response_id": { - "type": "string", - "description": "A specific response ID to cancel - if not provided, will cancel an \nin-progress response in the default conversation.\n" - } - }, - "required": [ - "type" - ], - "x-oaiMeta": { - "name": "response.cancel", - "group": "realtime", - "example": "{\n \"event_id\": \"event_567\",\n \"type\": \"response.cancel\"\n}\n" - } - }, - "RealtimeClientEventResponseCreate": { - "type": "object", - "description": "This event instructs the server to create a Response, which means triggering \nmodel inference. When in Server VAD mode, the server will create Responses \nautomatically.\n\nA Response will include at least one Item, and may have two, in which case \nthe second will be a function call. These Items will be appended to the \nconversation history.\n\nThe server will respond with a `response.created` event, events for Items \nand content created, and finally a `response.done` event to indicate the \nResponse is complete.\n\nThe `response.create` event includes inference configuration like \n`instructions`, and `temperature`. These fields will override the Session's \nconfiguration for this Response only.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `response.create`.", - "x-stainless-const": true, - "const": "response.create" - }, - "response": { - "$ref": "#/components/schemas/RealtimeResponseCreateParams" - } - }, - "required": [ - "type" - ], - "x-oaiMeta": { - "name": "response.create", - "group": "realtime", - "example": "{\n \"type\": \"response.create\",\n \"event_id\": \"xxx\",\n \"timestamp\": \"2:30:35 PM\"\n}\n" - } - }, - "RealtimeClientEventSessionUpdate": { - "type": "object", - "description": "Send this event to update the sessionโ€™s default configuration.\nThe client may send this event at any time to update any field,\nexcept for `voice`. However, note that once a session has been\ninitialized with a particular `model`, it canโ€™t be changed to\nanother model using `session.update`.\n\nWhen the server receives a `session.update`, it will respond\nwith a `session.updated` event showing the full, effective configuration.\nOnly the fields that are present are updated. To clear a field like\n`instructions`, pass an empty string.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `session.update`.", - "x-stainless-const": true, - "const": "session.update" - }, - "session": { - "$ref": "#/components/schemas/RealtimeSessionCreateRequest" - } - }, - "required": [ - "type", - "session" - ], - "x-oaiMeta": { - "name": "session.update", - "group": "realtime", - "example": "{\n \"type\": \"session.update\",\n \"session\": {\n \"type\": \"realtime\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"name\": \"display_color_palette\",\n \"description\": \"\\nCall this function when a user asks for a color palette.\\n\",\n \"parameters\": {\n \"type\": \"object\",\n \"strict\": true,\n \"properties\": {\n \"theme\": {\n \"type\": \"string\",\n \"description\": \"Description of the theme for the color scheme.\"\n },\n \"colors\": {\n \"type\": \"array\",\n \"description\": \"Array of five hex color codes based on the theme.\",\n \"items\": {\n \"type\": \"string\",\n \"description\": \"Hex color code\"\n }\n }\n },\n \"required\": [\n \"theme\",\n \"colors\"\n ]\n }\n }\n ],\n \"tool_choice\": \"auto\"\n },\n \"event_id\": \"5fc543c4-f59c-420f-8fb9-68c45d1546a7\",\n \"timestamp\": \"2:30:32 PM\"\n}\n" - } - }, - "RealtimeClientEventTranscriptionSessionUpdate": { - "type": "object", - "description": "Send this event to update a transcription session.\n", - "properties": { - "event_id": { - "type": "string", - "description": "Optional client-generated ID used to identify this event." - }, - "type": { - "description": "The event type, must be `transcription_session.update`.", - "x-stainless-const": true, - "const": "transcription_session.update" - }, - "session": { - "$ref": "#/components/schemas/RealtimeTranscriptionSessionCreateRequest" - } - }, - "required": [ - "type", - "session" - ], - "x-oaiMeta": { - "name": "transcription_session.update", - "group": "realtime", - "example": "{\n \"type\": \"transcription_session.update\",\n \"session\": {\n \"input_audio_format\": \"pcm16\",\n \"input_audio_transcription\": {\n \"model\": \"gpt-4o-transcribe\",\n \"prompt\": \"\",\n \"language\": \"\"\n },\n \"turn_detection\": {\n \"type\": \"server_vad\",\n \"threshold\": 0.5,\n \"prefix_padding_ms\": 300,\n \"silence_duration_ms\": 500,\n \"create_response\": true,\n },\n \"input_audio_noise_reduction\": {\n \"type\": \"near_field\"\n },\n \"include\": [\n \"item.input_audio_transcription.logprobs\",\n ]\n }\n}\n" - } - }, - "RealtimeConversationItem": { - "description": "A single item within a Realtime conversation.", - "anyOf": [ - { - "$ref": "#/components/schemas/RealtimeConversationItemMessageSystem" - }, - { - "$ref": "#/components/schemas/RealtimeConversationItemMessageUser" - }, - { - "$ref": "#/components/schemas/RealtimeConversationItemMessageAssistant" - }, - { - "$ref": "#/components/schemas/RealtimeConversationItemFunctionCall" - }, - { - "$ref": "#/components/schemas/RealtimeConversationItemFunctionCallOutput" - }, - { - "$ref": "#/components/schemas/RealtimeMCPApprovalResponse" - }, - { - "$ref": "#/components/schemas/RealtimeMCPListTools" - }, - { - "$ref": "#/components/schemas/RealtimeMCPToolCall" - }, - { - "$ref": "#/components/schemas/RealtimeMCPApprovalRequest" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "RealtimeConversationItemFunctionCall": { - "type": "object", - "title": "Realtime function call item", - "description": "A function call item in a Realtime conversation.", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the item." - }, - "object": { - "type": "string", - "enum": [ - "realtime.item" - ], - "description": "Identifier for the API object being returned - always `realtime.item`.", - "x-stainless-const": true - }, - "type": { - "type": "string", - "enum": [ - "function_call" - ], - "description": "The type of the item. Always `function_call`.", - "x-stainless-const": true - }, - "status": { - "type": "string", - "enum": [ - "completed", - "incomplete", - "in_progress" - ], - "description": "The status of the item. Has no effect on the conversation." - }, - "call_id": { - "type": "string", - "description": "The ID of the function call." - }, - "name": { - "type": "string", - "description": "The name of the function being called." - }, - "arguments": { - "type": "string", - "description": "The arguments of the function call." - } - }, - "required": [ - "type", - "name", - "arguments" - ] - }, - "RealtimeConversationItemFunctionCallOutput": { - "type": "object", - "title": "Realtime function call output item", - "description": "A function call output item in a Realtime conversation.", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the item." - }, - "object": { - "type": "string", - "enum": [ - "realtime.item" - ], - "description": "Identifier for the API object being returned - always `realtime.item`.", - "x-stainless-const": true - }, - "type": { - "type": "string", - "enum": [ - "function_call_output" - ], - "description": "The type of the item. Always `function_call_output`.", - "x-stainless-const": true - }, - "status": { - "type": "string", - "enum": [ - "completed", - "incomplete", - "in_progress" - ], - "description": "The status of the item. Has no effect on the conversation." - }, - "call_id": { - "type": "string", - "description": "The ID of the function call this output is for." - }, - "output": { - "type": "string", - "description": "The output of the function call." - } - }, - "required": [ - "type", - "call_id", - "output" - ] - }, - "RealtimeConversationItemMessageAssistant": { - "type": "object", - "title": "Realtime assistant message item", - "description": "An assistant message item in a Realtime conversation.", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the item." - }, - "object": { - "type": "string", - "enum": [ - "realtime.item" - ], - "description": "Identifier for the API object being returned - always `realtime.item`.", - "x-stainless-const": true - }, - "type": { - "type": "string", - "enum": [ - "message" - ], - "description": "The type of the item. Always `message`.", - "x-stainless-const": true - }, - "status": { - "type": "string", - "enum": [ - "completed", - "incomplete", - "in_progress" - ], - "description": "The status of the item. Has no effect on the conversation." - }, - "role": { - "type": "string", - "enum": [ - "assistant" - ], - "description": "The role of the message sender. Always `assistant`.", - "x-stainless-const": true - }, - "content": { - "type": "array", - "description": "The content of the message.", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "enum": [ - "text" - ], - "description": "The content type. Always `text` for assistant messages.", - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text content." - } - } - } - } - }, - "required": [ - "type", - "role", - "content" - ] - }, - "RealtimeConversationItemMessageSystem": { - "type": "object", - "title": "Realtime system message item", - "description": "A system message item in a Realtime conversation.", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the item." - }, - "object": { - "type": "string", - "enum": [ - "realtime.item" - ], - "description": "Identifier for the API object being returned - always `realtime.item`.", - "x-stainless-const": true - }, - "type": { - "type": "string", - "enum": [ - "message" - ], - "description": "The type of the item. Always `message`.", - "x-stainless-const": true - }, - "status": { - "type": "string", - "enum": [ - "completed", - "incomplete", - "in_progress" - ], - "description": "The status of the item. Has no effect on the conversation." - }, - "role": { - "type": "string", - "enum": [ - "system" - ], - "description": "The role of the message sender. Always `system`.", - "x-stainless-const": true - }, - "content": { - "type": "array", - "description": "The content of the message.", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "enum": [ - "input_text" - ], - "description": "The content type. Always `input_text` for system messages.", - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text content." - } - } - } - } - }, - "required": [ - "type", - "role", - "content" - ] - }, - "RealtimeConversationItemMessageUser": { - "type": "object", - "title": "Realtime user message item", - "description": "A user message item in a Realtime conversation.", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the item." - }, - "object": { - "type": "string", - "enum": [ - "realtime.item" - ], - "description": "Identifier for the API object being returned - always `realtime.item`.", - "x-stainless-const": true - }, - "type": { - "type": "string", - "enum": [ - "message" - ], - "description": "The type of the item. Always `message`.", - "x-stainless-const": true - }, - "status": { - "type": "string", - "enum": [ - "completed", - "incomplete", - "in_progress" - ], - "description": "The status of the item. Has no effect on the conversation." - }, - "role": { - "type": "string", - "enum": [ - "user" - ], - "description": "The role of the message sender. Always `user`.", - "x-stainless-const": true - }, - "content": { - "type": "array", - "description": "The content of the message.", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "enum": [ - "input_text", - "input_audio" - ], - "description": "The content type (`input_text` or `input_audio`)." - }, - "text": { - "type": "string", - "description": "The text content (for `input_text`)." - }, - "audio": { - "type": "string", - "description": "Base64-encoded audio bytes (for `input_audio`)." - }, - "transcript": { - "type": "string", - "description": "Transcript of the audio (for `input_audio`)." - } - } - } - } - }, - "required": [ - "type", - "role", - "content" - ] - }, - "RealtimeConversationItemWithReference": { - "type": "object", - "description": "The item to add to the conversation.", - "properties": { - "id": { - "type": "string", - "description": "For an item of type (`message` | `function_call` | `function_call_output`)\nthis field allows the client to assign the unique ID of the item. It is\nnot required because the server will generate one if not provided.\n\nFor an item of type `item_reference`, this field is required and is a\nreference to any item that has previously existed in the conversation.\n" - }, - "type": { - "type": "string", - "enum": [ - "message", - "function_call", - "function_call_output", - "item_reference" - ], - "description": "The type of the item (`message`, `function_call`, `function_call_output`, `item_reference`).\n" - }, - "object": { - "type": "string", - "enum": [ - "realtime.item" - ], - "description": "Identifier for the API object being returned - always `realtime.item`.\n", - "x-stainless-const": true - }, - "status": { - "type": "string", - "enum": [ - "completed", - "incomplete", - "in_progress" - ], - "description": "The status of the item (`completed`, `incomplete`, `in_progress`). These have no effect \non the conversation, but are accepted for consistency with the \n`conversation.item.created` event.\n" - }, - "role": { - "type": "string", - "enum": [ - "user", - "assistant", - "system" - ], - "description": "The role of the message sender (`user`, `assistant`, `system`), only \napplicable for `message` items.\n" - }, - "content": { - "type": "array", - "description": "The content of the message, applicable for `message` items. \n- Message items of role `system` support only `input_text` content\n- Message items of role `user` support `input_text` and `input_audio` \n content\n- Message items of role `assistant` support `text` content.\n", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "enum": [ - "input_text", - "input_audio", - "item_reference", - "text" - ], - "description": "The content type (`input_text`, `input_audio`, `item_reference`, `text`).\n" - }, - "text": { - "type": "string", - "description": "The text content, used for `input_text` and `text` content types.\n" - }, - "id": { - "type": "string", - "description": "ID of a previous conversation item to reference (for `item_reference`\ncontent types in `response.create` events). These can reference both\nclient and server created items.\n" - }, - "audio": { - "type": "string", - "description": "Base64-encoded audio bytes, used for `input_audio` content type.\n" - }, - "transcript": { - "type": "string", - "description": "The transcript of the audio, used for `input_audio` content type.\n" - } - } - } - }, - "call_id": { - "type": "string", - "description": "The ID of the function call (for `function_call` and \n`function_call_output` items). If passed on a `function_call_output` \nitem, the server will check that a `function_call` item with the same \nID exists in the conversation history.\n" - }, - "name": { - "type": "string", - "description": "The name of the function being called (for `function_call` items).\n" - }, - "arguments": { - "type": "string", - "description": "The arguments of the function call (for `function_call` items).\n" - }, - "output": { - "type": "string", - "description": "The output of the function call (for `function_call_output` items).\n" - } - } - }, - "RealtimeCreateClientSecretRequest": { - "type": "object", - "title": "Realtime session configuration", - "description": "Create a session and client secret for the Realtime API. The request can specify\neither a realtime or a transcription session configuration.\n[Learn more about the Realtime API](https://platform.openai.com/docs/guides/realtime).\n", - "properties": { - "expires_after": { - "type": "object", - "title": "Client secret expiration", - "description": "Configuration for the ephemeral token expiration.\n", - "properties": { - "anchor": { - "type": "string", - "enum": [ - "created_at" - ], - "description": "The anchor point for the ephemeral token expiration. Only `created_at` is currently supported.\n", - "default": "created_at", - "x-stainless-const": true - }, - "seconds": { - "type": "integer", - "description": "The number of seconds from the anchor point to the expiration. Select a value between `10` and `7200`.\n", - "minimum": 10, - "maximum": 7200, - "default": 600 - } - } - }, - "session": { - "title": "Session configuration", - "description": "Session configuration to use for the client secret. Choose either a realtime\nsession or a transcription session.\n", - "anyOf": [ - { - "$ref": "#/components/schemas/RealtimeSessionCreateRequest" - }, - { - "$ref": "#/components/schemas/RealtimeTranscriptionSessionCreateRequest" - } - ], - "discriminator": { - "propertyName": "type" - } - } - } - }, - "RealtimeCreateClientSecretResponse": { - "type": "object", - "title": "Realtime session and client secret", - "description": "Response from creating a session and client secret for the Realtime API.\n", - "properties": { - "value": { - "type": "string", - "description": "The generated client secret value." - }, - "expires_at": { - "type": "integer", - "description": "Expiration timestamp for the client secret, in seconds since epoch." - }, - "session": { - "title": "Session configuration", - "description": "The session configuration for either a realtime or transcription session.\n", - "anyOf": [ - { - "$ref": "#/components/schemas/RealtimeSessionCreateResponse" - }, - { - "$ref": "#/components/schemas/RealtimeTranscriptionSessionCreateResponse" - } - ] - } - }, - "required": [ - "value", - "expires_at", - "session" - ], - "x-oaiMeta": { - "name": "Session response object", - "group": "realtime", - "example": "{\n \"value\": \"ek_68af296e8e408191a1120ab6383263c2\",\n \"expires_at\": 1756310470,\n \"session\": {\n \"type\": \"realtime\",\n \"object\": \"realtime.session\",\n \"id\": \"sess_C9CiUVUzUzYIssh3ELY1d\",\n \"model\": \"gpt-4o-realtime-preview\",\n \"output_modalities\": [\n \"audio\"\n ],\n \"instructions\": \"You are a friendly assistant.\",\n \"tools\": [],\n \"tool_choice\": \"auto\",\n \"max_output_tokens\": \"inf\",\n \"tracing\": null,\n \"truncation\": \"auto\",\n \"prompt\": null,\n \"expires_at\": 0,\n \"audio\": {\n \"input\": {\n \"format\": {\n \"type\": \"audio/pcm\",\n \"rate\": 24000\n },\n \"transcription\": null,\n \"noise_reduction\": null,\n \"turn_detection\": {\n \"type\": \"server_vad\",\n \"threshold\": 0.5,\n \"prefix_padding_ms\": 300,\n \"silence_duration_ms\": 200,\n \"idle_timeout_ms\": null,\n \"create_response\": true,\n \"interrupt_response\": true\n }\n },\n \"output\": {\n \"format\": {\n \"type\": \"audio/pcm\",\n \"rate\": 24000\n },\n \"voice\": \"alloy\",\n \"speed\": 1.0\n }\n },\n \"include\": null\n }\n}\n" - } - }, - "RealtimeMCPApprovalRequest": { - "type": "object", - "title": "Realtime MCP approval request", - "description": "A Realtime item requesting human approval of a tool invocation.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp_approval_request" - ], - "description": "The type of the item. Always `mcp_approval_request`.", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the approval request." - }, - "server_label": { - "type": "string", - "description": "The label of the MCP server making the request." - }, - "name": { - "type": "string", - "description": "The name of the tool to run." - }, - "arguments": { - "type": "string", - "description": "A JSON string of arguments for the tool." - } - }, - "required": [ - "type", - "id", - "server_label", - "name", - "arguments" - ] - }, - "RealtimeMCPApprovalResponse": { - "type": "object", - "title": "Realtime MCP approval response", - "description": "A Realtime item responding to an MCP approval request.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp_approval_response" - ], - "description": "The type of the item. Always `mcp_approval_response`.", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the approval response." - }, - "approval_request_id": { - "type": "string", - "description": "The ID of the approval request being answered." - }, - "approve": { - "type": "boolean", - "description": "Whether the request was approved." - }, - "reason": { - "type": "string", - "description": "Optional reason for the decision.", - "nullable": true - } - }, - "required": [ - "type", - "id", - "approval_request_id", - "approve" - ] - }, - "RealtimeMCPHTTPError": { - "type": "object", - "title": "Realtime MCP HTTP error", - "properties": { - "type": { - "type": "string", - "enum": [ - "http_error" - ], - "x-stainless-const": true - }, - "code": { - "type": "integer" - }, - "message": { - "type": "string" - } - }, - "required": [ - "type", - "code", - "message" - ] - }, - "RealtimeMCPListTools": { - "type": "object", - "title": "Realtime MCP list tools", - "description": "A Realtime item listing tools available on an MCP server.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp_list_tools" - ], - "description": "The type of the item. Always `mcp_list_tools`.", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the list." - }, - "server_label": { - "type": "string", - "description": "The label of the MCP server." - }, - "tools": { - "type": "array", - "items": { - "$ref": "#/components/schemas/MCPListToolsTool" - }, - "description": "The tools available on the server." - } - }, - "required": [ - "type", - "server_label", - "tools" - ] - }, - "RealtimeMCPProtocolError": { - "type": "object", - "title": "Realtime MCP protocol error", - "properties": { - "type": { - "type": "string", - "enum": [ - "protocol_error" - ], - "x-stainless-const": true - }, - "code": { - "type": "integer" - }, - "message": { - "type": "string" - } - }, - "required": [ - "type", - "code", - "message" - ] - }, - "RealtimeMCPToolCall": { - "type": "object", - "title": "Realtime MCP tool call", - "description": "A Realtime item representing an invocation of a tool on an MCP server.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp_tool_call" - ], - "description": "The type of the item. Always `mcp_tool_call`.", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the tool call." - }, - "server_label": { - "type": "string", - "description": "The label of the MCP server running the tool." - }, - "name": { - "type": "string", - "description": "The name of the tool that was run." - }, - "arguments": { - "type": "string", - "description": "A JSON string of the arguments passed to the tool." - }, - "approval_request_id": { - "type": "string", - "description": "The ID of an associated approval request, if any.", - "nullable": true - }, - "output": { - "type": "string", - "description": "The output from the tool call.", - "nullable": true - }, - "error": { - "description": "The error from the tool call, if any.", - "nullable": true, - "anyOf": [ - { - "$ref": "#/components/schemas/RealtimeMCPProtocolError" - }, - { - "$ref": "#/components/schemas/RealtimeMCPToolExecutionError" - }, - { - "$ref": "#/components/schemas/RealtimeMCPHTTPError" - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "required": [ - "type", - "id", - "server_label", - "name", - "arguments" - ] - }, - "RealtimeMCPToolExecutionError": { - "type": "object", - "title": "Realtime MCP tool execution error", - "properties": { - "type": { - "type": "string", - "enum": [ - "tool_execution_error" - ], - "x-stainless-const": true - }, - "message": { - "type": "string" - } - }, - "required": [ - "type", - "message" - ] - }, - "RealtimeResponse": { - "type": "object", - "description": "The response resource.", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the response." - }, - "object": { - "description": "The object type, must be `realtime.response`.", - "x-stainless-const": true, - "const": "realtime.response" - }, - "status": { - "type": "string", - "enum": [ - "completed", - "cancelled", - "failed", - "incomplete", - "in_progress" - ], - "description": "The final status of the response (`completed`, `cancelled`, `failed`, or \n`incomplete`, `in_progress`).\n" - }, - "status_details": { - "type": "object", - "description": "Additional details about the status.", - "properties": { - "type": { - "type": "string", - "enum": [ - "completed", - "cancelled", - "incomplete", - "failed" - ], - "description": "The type of error that caused the response to fail, corresponding \nwith the `status` field (`completed`, `cancelled`, `incomplete`, \n`failed`).\n" - }, - "reason": { - "type": "string", - "enum": [ - "turn_detected", - "client_cancelled", - "max_output_tokens", - "content_filter" - ], - "description": "The reason the Response did not complete. For a `cancelled` Response, \none of `turn_detected` (the server VAD detected a new start of speech) \nor `client_cancelled` (the client sent a cancel event). For an \n`incomplete` Response, one of `max_output_tokens` or `content_filter` \n(the server-side safety filter activated and cut off the response).\n" - }, - "error": { - "type": "object", - "description": "A description of the error that caused the response to fail, \npopulated when the `status` is `failed`.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of error." - }, - "code": { - "type": "string", - "description": "Error code, if any." - } - } - } - } - }, - "output": { - "type": "array", - "description": "The list of output items generated by the response.", - "items": { - "$ref": "#/components/schemas/RealtimeConversationItem" - } - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "usage": { - "type": "object", - "description": "Usage statistics for the Response, this will correspond to billing. A \nRealtime API session will maintain a conversation context and append new \nItems to the Conversation, thus output from previous turns (text and \naudio tokens) will become the input for later turns.\n", - "properties": { - "total_tokens": { - "type": "integer", - "description": "The total number of tokens in the Response including input and output \ntext and audio tokens.\n" - }, - "input_tokens": { - "type": "integer", - "description": "The number of input tokens used in the Response, including text and \naudio tokens.\n" - }, - "output_tokens": { - "type": "integer", - "description": "The number of output tokens sent in the Response, including text and \naudio tokens.\n" - }, - "input_token_details": { - "type": "object", - "description": "Details about the input tokens used in the Response.", - "properties": { - "cached_tokens": { - "type": "integer", - "description": "The number of cached tokens used in the Response." - }, - "text_tokens": { - "type": "integer", - "description": "The number of text tokens used in the Response." - }, - "audio_tokens": { - "type": "integer", - "description": "The number of audio tokens used in the Response." - } - } - }, - "output_token_details": { - "type": "object", - "description": "Details about the output tokens used in the Response.", - "properties": { - "text_tokens": { - "type": "integer", - "description": "The number of text tokens used in the Response." - }, - "audio_tokens": { - "type": "integer", - "description": "The number of audio tokens used in the Response." - } - } - } - } - }, - "conversation_id": { - "description": "Which conversation the response is added to, determined by the `conversation`\nfield in the `response.create` event. If `auto`, the response will be added to\nthe default conversation and the value of `conversation_id` will be an id like\n`conv_1234`. If `none`, the response will not be added to any conversation and\nthe value of `conversation_id` will be `null`. If responses are being triggered\nby server VAD, the response will be added to the default conversation, thus\nthe `conversation_id` will be an id like `conv_1234`.\n", - "type": "string" - }, - "voice": { - "$ref": "#/components/schemas/VoiceIdsShared", - "description": "The voice the model used to respond.\nCurrent voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `sage`,\n`shimmer`, and `verse`.\n" - }, - "modalities": { - "type": "array", - "description": "The set of modalities the model used to respond. If there are multiple modalities,\nthe model will pick one, for example if `modalities` is `[\"text\", \"audio\"]`, the model\ncould be responding in either text or audio.\n", - "items": { - "type": "string", - "enum": [ - "text", - "audio" - ] - } - }, - "output_audio_format": { - "type": "string", - "enum": [ - "pcm16", - "g711_ulaw", - "g711_alaw" - ], - "description": "The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\n" - }, - "temperature": { - "type": "number", - "description": "Sampling temperature for the model, limited to [0.6, 1.2]. Defaults to 0.8.\n" - }, - "max_output_tokens": { - "description": "Maximum number of output tokens for a single assistant response,\ninclusive of tool calls, that was used in this response.\n", - "anyOf": [ - { - "type": "integer" - }, - { - "type": "string", - "enum": [ - "inf" - ], - "x-stainless-const": true - } - ] - } - } - }, - "RealtimeResponseCreateParams": { - "type": "object", - "description": "Create a new Realtime response with these parameters", - "properties": { - "modalities": { - "type": "array", - "description": "The set of modalities the model can respond with. To disable audio,\nset this to [\"text\"].\n", - "items": { - "type": "string", - "enum": [ - "text", - "audio" - ] - } - }, - "instructions": { - "type": "string", - "description": "The default system instructions (i.e. system message) prepended to model \ncalls. This field allows the client to guide the model on desired \nresponses. The model can be instructed on response content and format, \n(e.g. \"be extremely succinct\", \"act friendly\", \"here are examples of good \nresponses\") and on audio behavior (e.g. \"talk quickly\", \"inject emotion \ninto your voice\", \"laugh frequently\"). The instructions are not guaranteed \nto be followed by the model, but they provide guidance to the model on the \ndesired behavior.\n\nNote that the server sets default instructions which will be used if this \nfield is not set and are visible in the `session.created` event at the \nstart of the session.\n" - }, - "voice": { - "$ref": "#/components/schemas/VoiceIdsShared", - "description": "The voice the model uses to respond. Voice cannot be changed during the \nsession once the model has responded with audio at least once. Current \nvoice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `sage`,\n`shimmer`, and `verse`.\n" - }, - "output_audio_format": { - "type": "string", - "enum": [ - "pcm16", - "g711_ulaw", - "g711_alaw" - ], - "description": "The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\n" - }, - "tools": { - "type": "array", - "description": "Tools (functions) available to the model.", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "The type of the tool, i.e. `function`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the function." - }, - "description": { - "type": "string", - "description": "The description of the function, including guidance on when and how \nto call it, and guidance about what to tell the user when calling \n(if anything).\n" - }, - "parameters": { - "type": "object", - "description": "Parameters of the function in JSON Schema." - } - } - } - }, - "tool_choice": { - "description": "How the model chooses tools. Provide one of the string modes or force a specific\nfunction/MCP tool.\n", - "default": "auto", - "anyOf": [ - { - "$ref": "#/components/schemas/ToolChoiceOptions" - }, - { - "$ref": "#/components/schemas/ToolChoiceFunction" - }, - { - "$ref": "#/components/schemas/ToolChoiceMCP" - } - ] - }, - "temperature": { - "type": "number", - "description": "Sampling temperature for the model, limited to [0.6, 1.2]. Defaults to 0.8.\n" - }, - "max_output_tokens": { - "description": "Maximum number of output tokens for a single assistant response,\ninclusive of tool calls. Provide an integer between 1 and 4096 to\nlimit output tokens, or `inf` for the maximum available tokens for a\ngiven model. Defaults to `inf`.\n", - "anyOf": [ - { - "type": "integer" - }, - { - "type": "string", - "enum": [ - "inf" - ], - "x-stainless-const": true - } - ] - }, - "conversation": { - "description": "Controls which conversation the response is added to. Currently supports\n`auto` and `none`, with `auto` as the default value. The `auto` value\nmeans that the contents of the response will be added to the default\nconversation. Set this to `none` to create an out-of-band response which \nwill not add items to default conversation.\n", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "default": "auto", - "enum": [ - "auto", - "none" - ] - } - ] - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "prompt": { - "$ref": "#/components/schemas/Prompt" - }, - "input": { - "type": "array", - "description": "Input items to include in the prompt for the model. Using this field\ncreates a new context for this Response instead of using the default\nconversation. An empty array `[]` will clear the context for this Response.\nNote that this can include references to items from the default conversation.\n", - "items": { - "$ref": "#/components/schemas/RealtimeConversationItem" - } - } - } - }, - "RealtimeServerEvent": { - "discriminator": { - "propertyName": "type" - }, - "description": "A realtime server event.\n", - "anyOf": [ - { - "$ref": "#/components/schemas/RealtimeServerEventConversationCreated" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemCreated" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemDeleted" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionCompleted" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionDelta" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionFailed" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemRetrieved" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemTruncated" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventError" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventInputAudioBufferCleared" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventInputAudioBufferCommitted" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventInputAudioBufferSpeechStarted" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventInputAudioBufferSpeechStopped" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventRateLimitsUpdated" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseAudioDelta" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseAudioDone" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseAudioTranscriptDelta" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseAudioTranscriptDone" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseContentPartAdded" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseContentPartDone" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseCreated" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseDone" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseFunctionCallArgumentsDelta" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseFunctionCallArgumentsDone" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseOutputItemAdded" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseOutputItemDone" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseTextDelta" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseTextDone" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventSessionCreated" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventSessionUpdated" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventTranscriptionSessionUpdated" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventTranscriptionSessionCreated" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventOutputAudioBufferStarted" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventOutputAudioBufferStopped" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventOutputAudioBufferCleared" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemAdded" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemDone" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventInputAudioBufferTimeoutTriggered" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionSegment" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventMCPListToolsInProgress" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventMCPListToolsCompleted" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventMCPListToolsFailed" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseMCPCallArgumentsDelta" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseMCPCallArgumentsDone" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseMCPCallInProgress" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseMCPCallCompleted" - }, - { - "$ref": "#/components/schemas/RealtimeServerEventResponseMCPCallFailed" - } - ] - }, - "RealtimeServerEventConversationCreated": { - "type": "object", - "description": "Returned when a conversation is created. Emitted right after session creation.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `conversation.created`.", - "x-stainless-const": true, - "const": "conversation.created" - }, - "conversation": { - "type": "object", - "description": "The conversation resource.", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the conversation." - }, - "object": { - "description": "The object type, must be `realtime.conversation`.", - "const": "realtime.conversation" - } - } - } - }, - "required": [ - "event_id", - "type", - "conversation" - ], - "x-oaiMeta": { - "name": "conversation.created", - "group": "realtime", - "example": "{\n \"event_id\": \"event_9101\",\n \"type\": \"conversation.created\",\n \"conversation\": {\n \"id\": \"conv_001\",\n \"object\": \"realtime.conversation\"\n }\n}\n" - } - }, - "RealtimeServerEventConversationItemAdded": { - "type": "object", - "description": "Returned when a conversation item is added.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `conversation.item.added`.", - "x-stainless-const": true, - "const": "conversation.item.added" - }, - "previous_item_id": { - "type": "string", - "nullable": true, - "description": "The ID of the item that precedes this one, if any. This is used to\nmaintain ordering when items are inserted.\n" - }, - "item": { - "$ref": "#/components/schemas/RealtimeConversationItem" - } - }, - "required": [ - "event_id", - "type", - "item" - ], - "x-oaiMeta": { - "name": "conversation.item.added", - "group": "realtime", - "example": "{\n \"type\": \"conversation.item.added\",\n \"event_id\": \"event_C9G8pjSJCfRNEhMEnYAVy\",\n \"previous_item_id\": null,\n \"item\": {\n \"id\": \"item_C9G8pGVKYnaZu8PH5YQ9O\",\n \"type\": \"message\",\n \"status\": \"completed\",\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"hi\"\n }\n ]\n },\n \"timestamp\": \"2:30:35 PM\"\n}\n" - } - }, - "RealtimeServerEventConversationItemCreated": { - "type": "object", - "description": "Returned when a conversation item is created. There are several scenarios that produce this event:\n - The server is generating a Response, which if successful will produce \n either one or two Items, which will be of type `message` \n (role `assistant`) or type `function_call`.\n - The input audio buffer has been committed, either by the client or the \n server (in `server_vad` mode). The server will take the content of the \n input audio buffer and add it to a new user message Item.\n - The client has sent a `conversation.item.create` event to add a new Item \n to the Conversation.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `conversation.item.created`.", - "x-stainless-const": true, - "const": "conversation.item.created" - }, - "previous_item_id": { - "type": "string", - "nullable": true, - "description": "The ID of the preceding item in the Conversation context, allows the \nclient to understand the order of the conversation. Can be `null` if the \nitem has no predecessor.\n" - }, - "item": { - "$ref": "#/components/schemas/RealtimeConversationItem" - } - }, - "required": [ - "event_id", - "type", - "item" - ], - "x-oaiMeta": { - "name": "conversation.item.created", - "group": "realtime", - "example": "{\n \"event_id\": \"event_1920\",\n \"type\": \"conversation.item.created\",\n \"previous_item_id\": \"msg_002\",\n \"item\": {\n \"id\": \"msg_003\",\n \"object\": \"realtime.item\",\n \"type\": \"message\",\n \"status\": \"completed\",\n \"role\": \"user\",\n \"content\": []\n }\n}\n" - } - }, - "RealtimeServerEventConversationItemDeleted": { - "type": "object", - "description": "Returned when an item in the conversation is deleted by the client with a \n`conversation.item.delete` event. This event is used to synchronize the \nserver's understanding of the conversation history with the client's view.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `conversation.item.deleted`.", - "x-stainless-const": true, - "const": "conversation.item.deleted" - }, - "item_id": { - "type": "string", - "description": "The ID of the item that was deleted." - } - }, - "required": [ - "event_id", - "type", - "item_id" - ], - "x-oaiMeta": { - "name": "conversation.item.deleted", - "group": "realtime", - "example": "{\n \"event_id\": \"event_2728\",\n \"type\": \"conversation.item.deleted\",\n \"item_id\": \"msg_005\"\n}\n" - } - }, - "RealtimeServerEventConversationItemDone": { - "type": "object", - "description": "Returned when a conversation item is finalized.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `conversation.item.done`.", - "x-stainless-const": true, - "const": "conversation.item.done" - }, - "previous_item_id": { - "type": "string", - "nullable": true, - "description": "The ID of the item that precedes this one, if any. This is used to\nmaintain ordering when items are inserted.\n" - }, - "item": { - "$ref": "#/components/schemas/RealtimeConversationItem" - } - }, - "required": [ - "event_id", - "type", - "item" - ], - "x-oaiMeta": { - "name": "conversation.item.done", - "group": "realtime", - "example": "{\n \"type\": \"conversation.item.done\",\n \"event_id\": \"event_C9G8ps2i70P5Wd6OA0ftc\",\n \"previous_item_id\": null,\n \"item\": {\n \"id\": \"item_C9G8pGVKYnaZu8PH5YQ9O\",\n \"type\": \"message\",\n \"status\": \"completed\",\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"hi\"\n }\n ]\n },\n \"timestamp\": \"2:30:35 PM\"\n}\n" - } - }, - "RealtimeServerEventConversationItemInputAudioTranscriptionCompleted": { - "type": "object", - "description": "This event is the output of audio transcription for user audio written to the\nuser audio buffer. Transcription begins when the input audio buffer is\ncommitted by the client or server (in `server_vad` mode). Transcription runs\nasynchronously with Response creation, so this event may come before or after\nthe Response events.\n\nRealtime API models accept audio natively, and thus input transcription is a\nseparate process run on a separate ASR (Automatic Speech Recognition) model.\nThe transcript may diverge somewhat from the model's interpretation, and\nshould be treated as a rough guide.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "type": "string", - "enum": [ - "conversation.item.input_audio_transcription.completed" - ], - "description": "The event type, must be\n`conversation.item.input_audio_transcription.completed`.\n", - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the user message item containing the audio." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part containing the audio." - }, - "transcript": { - "type": "string", - "description": "The transcribed text." - }, - "logprobs": { - "type": "array", - "description": "The log probabilities of the transcription.", - "nullable": true, - "items": { - "$ref": "#/components/schemas/LogProbProperties" - } - }, - "usage": { - "type": "object", - "description": "Usage statistics for the transcription.", - "anyOf": [ - { - "$ref": "#/components/schemas/TranscriptTextUsageTokens", - "title": "Token Usage" - }, - { - "$ref": "#/components/schemas/TranscriptTextUsageDuration", - "title": "Duration Usage" - } - ] - } - }, - "required": [ - "event_id", - "type", - "item_id", - "content_index", - "transcript", - "usage" - ], - "x-oaiMeta": { - "name": "conversation.item.input_audio_transcription.completed", - "group": "realtime", - "example": "{\n \"event_id\": \"event_2122\",\n \"type\": \"conversation.item.input_audio_transcription.completed\",\n \"item_id\": \"msg_003\",\n \"content_index\": 0,\n \"transcript\": \"Hello, how are you?\",\n \"usage\": {\n \"type\": \"tokens\",\n \"total_tokens\": 48,\n \"input_tokens\": 38,\n \"input_token_details\": {\n \"text_tokens\": 10,\n \"audio_tokens\": 28,\n },\n \"output_tokens\": 10,\n }\n}\n" - } - }, - "RealtimeServerEventConversationItemInputAudioTranscriptionDelta": { - "type": "object", - "description": "Returned when the text value of an input audio transcription content part is updated.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `conversation.item.input_audio_transcription.delta`.", - "x-stainless-const": true, - "const": "conversation.item.input_audio_transcription.delta" - }, - "item_id": { - "type": "string", - "description": "The ID of the item." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part in the item's content array." - }, - "delta": { - "type": "string", - "description": "The text delta." - }, - "logprobs": { - "type": "array", - "description": "The log probabilities of the transcription.", - "nullable": true, - "items": { - "$ref": "#/components/schemas/LogProbProperties" - } - } - }, - "required": [ - "event_id", - "type", - "item_id" - ], - "x-oaiMeta": { - "name": "conversation.item.input_audio_transcription.delta", - "group": "realtime", - "example": "{\n \"type\": \"conversation.item.input_audio_transcription.delta\",\n \"event_id\": \"event_001\",\n \"item_id\": \"item_001\",\n \"content_index\": 0,\n \"delta\": \"Hello\"\n}\n" - } - }, - "RealtimeServerEventConversationItemInputAudioTranscriptionFailed": { - "type": "object", - "description": "Returned when input audio transcription is configured, and a transcription \nrequest for a user message failed. These events are separate from other \n`error` events so that the client can identify the related Item.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "type": "string", - "enum": [ - "conversation.item.input_audio_transcription.failed" - ], - "description": "The event type, must be\n`conversation.item.input_audio_transcription.failed`.\n", - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the user message item." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part containing the audio." - }, - "error": { - "type": "object", - "description": "Details of the transcription error.", - "properties": { - "type": { - "type": "string", - "description": "The type of error." - }, - "code": { - "type": "string", - "description": "Error code, if any." - }, - "message": { - "type": "string", - "description": "A human-readable error message." - }, - "param": { - "type": "string", - "description": "Parameter related to the error, if any." - } - } - } - }, - "required": [ - "event_id", - "type", - "item_id", - "content_index", - "error" - ], - "x-oaiMeta": { - "name": "conversation.item.input_audio_transcription.failed", - "group": "realtime", - "example": "{\n \"event_id\": \"event_2324\",\n \"type\": \"conversation.item.input_audio_transcription.failed\",\n \"item_id\": \"msg_003\",\n \"content_index\": 0,\n \"error\": {\n \"type\": \"transcription_error\",\n \"code\": \"audio_unintelligible\",\n \"message\": \"The audio could not be transcribed.\",\n \"param\": null\n }\n}\n" - } - }, - "RealtimeServerEventConversationItemInputAudioTranscriptionSegment": { - "type": "object", - "description": "Returned when an input audio transcription segment is identified for an item.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `conversation.item.input_audio_transcription.segment`.", - "x-stainless-const": true, - "const": "conversation.item.input_audio_transcription.segment" - }, - "item_id": { - "type": "string", - "description": "The ID of the item containing the input audio content." - }, - "content_index": { - "type": "integer", - "description": "The index of the input audio content part within the item." - }, - "text": { - "type": "string", - "description": "The text for this segment." - }, - "id": { - "type": "string", - "description": "The segment identifier." - }, - "speaker": { - "type": "string", - "description": "The detected speaker label for this segment." - }, - "start": { - "type": "number", - "format": "float", - "description": "Start time of the segment in seconds." - }, - "end": { - "type": "number", - "format": "float", - "description": "End time of the segment in seconds." - } - }, - "required": [ - "event_id", - "type", - "item_id", - "content_index", - "text", - "id", - "speaker", - "start", - "end" - ], - "x-oaiMeta": { - "name": "conversation.item.input_audio_transcription.segment", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6501\",\n \"type\": \"conversation.item.input_audio_transcription.segment\",\n \"item_id\": \"msg_011\",\n \"content_index\": 0,\n \"text\": \"hello\",\n \"id\": \"seg_0001\",\n \"speaker\": \"spk_1\",\n \"start\": 0.0,\n \"end\": 0.4\n}\n" - } - }, - "RealtimeServerEventConversationItemRetrieved": { - "type": "object", - "description": "Returned when a conversation item is retrieved with `conversation.item.retrieve`.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `conversation.item.retrieved`.", - "x-stainless-const": true, - "const": "conversation.item.retrieved" - }, - "item": { - "$ref": "#/components/schemas/RealtimeConversationItem" - } - }, - "required": [ - "event_id", - "type", - "item" - ], - "x-oaiMeta": { - "name": "conversation.item.retrieved", - "group": "realtime", - "example": "{\n \"event_id\": \"event_1920\",\n \"type\": \"conversation.item.created\",\n \"previous_item_id\": \"msg_002\",\n \"item\": {\n \"id\": \"msg_003\",\n \"object\": \"realtime.item\",\n \"type\": \"message\",\n \"status\": \"completed\",\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_audio\",\n \"transcript\": \"hello how are you\",\n \"audio\": \"base64encodedaudio==\"\n }\n ]\n }\n}\n" - } - }, - "RealtimeServerEventConversationItemTruncated": { - "type": "object", - "description": "Returned when an earlier assistant audio message item is truncated by the \nclient with a `conversation.item.truncate` event. This event is used to \nsynchronize the server's understanding of the audio with the client's playback.\n\nThis action will truncate the audio and remove the server-side text transcript \nto ensure there is no text in the context that hasn't been heard by the user.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `conversation.item.truncated`.", - "x-stainless-const": true, - "const": "conversation.item.truncated" - }, - "item_id": { - "type": "string", - "description": "The ID of the assistant message item that was truncated." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part that was truncated." - }, - "audio_end_ms": { - "type": "integer", - "description": "The duration up to which the audio was truncated, in milliseconds.\n" - } - }, - "required": [ - "event_id", - "type", - "item_id", - "content_index", - "audio_end_ms" - ], - "x-oaiMeta": { - "name": "conversation.item.truncated", - "group": "realtime", - "example": "{\n \"event_id\": \"event_2526\",\n \"type\": \"conversation.item.truncated\",\n \"item_id\": \"msg_004\",\n \"content_index\": 0,\n \"audio_end_ms\": 1500\n}\n" - } - }, - "RealtimeServerEventError": { - "type": "object", - "description": "Returned when an error occurs, which could be a client problem or a server \nproblem. Most errors are recoverable and the session will stay open, we \nrecommend to implementors to monitor and log error messages by default.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `error`.", - "x-stainless-const": true, - "const": "error" - }, - "error": { - "type": "object", - "description": "Details of the error.", - "required": [ - "type", - "message" - ], - "properties": { - "type": { - "type": "string", - "description": "The type of error (e.g., \"invalid_request_error\", \"server_error\").\n" - }, - "code": { - "type": "string", - "description": "Error code, if any.", - "nullable": true - }, - "message": { - "type": "string", - "description": "A human-readable error message." - }, - "param": { - "type": "string", - "description": "Parameter related to the error, if any.", - "nullable": true - }, - "event_id": { - "type": "string", - "description": "The event_id of the client event that caused the error, if applicable.\n", - "nullable": true - } - } - } - }, - "required": [ - "event_id", - "type", - "error" - ], - "x-oaiMeta": { - "name": "error", - "group": "realtime", - "example": "{\n \"event_id\": \"event_890\",\n \"type\": \"error\",\n \"error\": {\n \"type\": \"invalid_request_error\",\n \"code\": \"invalid_event\",\n \"message\": \"The 'type' field is missing.\",\n \"param\": null,\n \"event_id\": \"event_567\"\n }\n}\n" - } - }, - "RealtimeServerEventInputAudioBufferCleared": { - "type": "object", - "description": "Returned when the input audio buffer is cleared by the client with a \n`input_audio_buffer.clear` event.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `input_audio_buffer.cleared`.", - "x-stainless-const": true, - "const": "input_audio_buffer.cleared" - } - }, - "required": [ - "event_id", - "type" - ], - "x-oaiMeta": { - "name": "input_audio_buffer.cleared", - "group": "realtime", - "example": "{\n \"event_id\": \"event_1314\",\n \"type\": \"input_audio_buffer.cleared\"\n}\n" - } - }, - "RealtimeServerEventInputAudioBufferCommitted": { - "type": "object", - "description": "Returned when an input audio buffer is committed, either by the client or \nautomatically in server VAD mode. The `item_id` property is the ID of the user\nmessage item that will be created, thus a `conversation.item.created` event \nwill also be sent to the client.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `input_audio_buffer.committed`.", - "x-stainless-const": true, - "const": "input_audio_buffer.committed" - }, - "previous_item_id": { - "type": "string", - "nullable": true, - "description": "The ID of the preceding item after which the new item will be inserted.\nCan be `null` if the item has no predecessor.\n" - }, - "item_id": { - "type": "string", - "description": "The ID of the user message item that will be created." - } - }, - "required": [ - "event_id", - "type", - "item_id" - ], - "x-oaiMeta": { - "name": "input_audio_buffer.committed", - "group": "realtime", - "example": "{\n \"event_id\": \"event_1121\",\n \"type\": \"input_audio_buffer.committed\",\n \"previous_item_id\": \"msg_001\",\n \"item_id\": \"msg_002\"\n}\n" - } - }, - "RealtimeServerEventInputAudioBufferSpeechStarted": { - "type": "object", - "description": "Sent by the server when in `server_vad` mode to indicate that speech has been \ndetected in the audio buffer. This can happen any time audio is added to the \nbuffer (unless speech is already detected). The client may want to use this \nevent to interrupt audio playback or provide visual feedback to the user. \n\nThe client should expect to receive a `input_audio_buffer.speech_stopped` event \nwhen speech stops. The `item_id` property is the ID of the user message item \nthat will be created when speech stops and will also be included in the \n`input_audio_buffer.speech_stopped` event (unless the client manually commits \nthe audio buffer during VAD activation).\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `input_audio_buffer.speech_started`.", - "x-stainless-const": true, - "const": "input_audio_buffer.speech_started" - }, - "audio_start_ms": { - "type": "integer", - "description": "Milliseconds from the start of all audio written to the buffer during the \nsession when speech was first detected. This will correspond to the \nbeginning of audio sent to the model, and thus includes the \n`prefix_padding_ms` configured in the Session.\n" - }, - "item_id": { - "type": "string", - "description": "The ID of the user message item that will be created when speech stops.\n" - } - }, - "required": [ - "event_id", - "type", - "audio_start_ms", - "item_id" - ], - "x-oaiMeta": { - "name": "input_audio_buffer.speech_started", - "group": "realtime", - "example": "{\n \"event_id\": \"event_1516\",\n \"type\": \"input_audio_buffer.speech_started\",\n \"audio_start_ms\": 1000,\n \"item_id\": \"msg_003\"\n}\n" - } - }, - "RealtimeServerEventInputAudioBufferSpeechStopped": { - "type": "object", - "description": "Returned in `server_vad` mode when the server detects the end of speech in \nthe audio buffer. The server will also send an `conversation.item.created` \nevent with the user message item that is created from the audio buffer.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `input_audio_buffer.speech_stopped`.", - "x-stainless-const": true, - "const": "input_audio_buffer.speech_stopped" - }, - "audio_end_ms": { - "type": "integer", - "description": "Milliseconds since the session started when speech stopped. This will \ncorrespond to the end of audio sent to the model, and thus includes the \n`min_silence_duration_ms` configured in the Session.\n" - }, - "item_id": { - "type": "string", - "description": "The ID of the user message item that will be created." - } - }, - "required": [ - "event_id", - "type", - "audio_end_ms", - "item_id" - ], - "x-oaiMeta": { - "name": "input_audio_buffer.speech_stopped", - "group": "realtime", - "example": "{\n \"event_id\": \"event_1718\",\n \"type\": \"input_audio_buffer.speech_stopped\",\n \"audio_end_ms\": 2000,\n \"item_id\": \"msg_003\"\n}\n" - } - }, - "RealtimeServerEventInputAudioBufferTimeoutTriggered": { - "type": "object", - "description": "Returned when the server VAD timeout is triggered for the input audio buffer.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `input_audio_buffer.timeout_triggered`.", - "x-stainless-const": true, - "const": "input_audio_buffer.timeout_triggered" - }, - "audio_start_ms": { - "type": "integer", - "description": "Millisecond offset where speech started within the buffered audio." - }, - "audio_end_ms": { - "type": "integer", - "description": "Millisecond offset where speech ended within the buffered audio." - }, - "item_id": { - "type": "string", - "description": "The ID of the item associated with this segment." - } - }, - "required": [ - "event_id", - "type", - "audio_start_ms", - "audio_end_ms", - "item_id" - ], - "x-oaiMeta": { - "name": "input_audio_buffer.timeout_triggered", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6401\",\n \"type\": \"input_audio_buffer.timeout_triggered\",\n \"audio_start_ms\": 1200,\n \"audio_end_ms\": 2150,\n \"item_id\": \"msg_010\"\n}\n" - } - }, - "RealtimeServerEventMCPListToolsCompleted": { - "type": "object", - "description": "Returned when listing MCP tools has completed for an item.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `mcp_list_tools.completed`.", - "x-stainless-const": true, - "const": "mcp_list_tools.completed" - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP list tools item." - } - }, - "required": [ - "event_id", - "type", - "item_id" - ], - "x-oaiMeta": { - "name": "mcp_list_tools.completed", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6102\",\n \"type\": \"mcp_list_tools.completed\",\n \"item_id\": \"mcp_list_tools_001\"\n}\n" - } - }, - "RealtimeServerEventMCPListToolsFailed": { - "type": "object", - "description": "Returned when listing MCP tools has failed for an item.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `mcp_list_tools.failed`.", - "x-stainless-const": true, - "const": "mcp_list_tools.failed" - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP list tools item." - } - }, - "required": [ - "event_id", - "type", - "item_id" - ], - "x-oaiMeta": { - "name": "mcp_list_tools.failed", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6103\",\n \"type\": \"mcp_list_tools.failed\",\n \"item_id\": \"mcp_list_tools_001\"\n}\n" - } - }, - "RealtimeServerEventMCPListToolsInProgress": { - "type": "object", - "description": "Returned when listing MCP tools is in progress for an item.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `mcp_list_tools.in_progress`.", - "x-stainless-const": true, - "const": "mcp_list_tools.in_progress" - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP list tools item." - } - }, - "required": [ - "event_id", - "type", - "item_id" - ], - "x-oaiMeta": { - "name": "mcp_list_tools.in_progress", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6101\",\n \"type\": \"mcp_list_tools.in_progress\",\n \"item_id\": \"mcp_list_tools_001\"\n}\n" - } - }, - "RealtimeServerEventOutputAudioBufferCleared": { - "type": "object", - "description": "**WebRTC Only:** Emitted when the output audio buffer is cleared. This happens either in VAD\nmode when the user has interrupted (`input_audio_buffer.speech_started`),\nor when the client has emitted the `output_audio_buffer.clear` event to manually\ncut off the current audio response.\n[Learn more](https://platform.openai.com/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `output_audio_buffer.cleared`.", - "x-stainless-const": true, - "const": "output_audio_buffer.cleared" - }, - "response_id": { - "type": "string", - "description": "The unique ID of the response that produced the audio." - } - }, - "required": [ - "event_id", - "type", - "response_id" - ], - "x-oaiMeta": { - "name": "output_audio_buffer.cleared", - "group": "realtime", - "example": "{\n \"event_id\": \"event_abc123\",\n \"type\": \"output_audio_buffer.cleared\",\n \"response_id\": \"resp_abc123\"\n}\n" - } - }, - "RealtimeServerEventOutputAudioBufferStarted": { - "type": "object", - "description": "**WebRTC Only:** Emitted when the server begins streaming audio to the client. This event is\nemitted after an audio content part has been added (`response.content_part.added`)\nto the response.\n[Learn more](https://platform.openai.com/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `output_audio_buffer.started`.", - "x-stainless-const": true, - "const": "output_audio_buffer.started" - }, - "response_id": { - "type": "string", - "description": "The unique ID of the response that produced the audio." - } - }, - "required": [ - "event_id", - "type", - "response_id" - ], - "x-oaiMeta": { - "name": "output_audio_buffer.started", - "group": "realtime", - "example": "{\n \"event_id\": \"event_abc123\",\n \"type\": \"output_audio_buffer.started\",\n \"response_id\": \"resp_abc123\"\n}\n" - } - }, - "RealtimeServerEventOutputAudioBufferStopped": { - "type": "object", - "description": "**WebRTC Only:** Emitted when the output audio buffer has been completely drained on the server,\nand no more audio is forthcoming. This event is emitted after the full response\ndata has been sent to the client (`response.done`).\n[Learn more](https://platform.openai.com/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `output_audio_buffer.stopped`.", - "x-stainless-const": true, - "const": "output_audio_buffer.stopped" - }, - "response_id": { - "type": "string", - "description": "The unique ID of the response that produced the audio." - } - }, - "required": [ - "event_id", - "type", - "response_id" - ], - "x-oaiMeta": { - "name": "output_audio_buffer.stopped", - "group": "realtime", - "example": "{\n \"event_id\": \"event_abc123\",\n \"type\": \"output_audio_buffer.stopped\",\n \"response_id\": \"resp_abc123\"\n}\n" - } - }, - "RealtimeServerEventRateLimitsUpdated": { - "type": "object", - "description": "Emitted at the beginning of a Response to indicate the updated rate limits. \nWhen a Response is created some tokens will be \"reserved\" for the output \ntokens, the rate limits shown here reflect that reservation, which is then \nadjusted accordingly once the Response is completed.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `rate_limits.updated`.", - "x-stainless-const": true, - "const": "rate_limits.updated" - }, - "rate_limits": { - "type": "array", - "description": "List of rate limit information.", - "items": { - "type": "object", - "properties": { - "name": { - "type": "string", - "enum": [ - "requests", - "tokens" - ], - "description": "The name of the rate limit (`requests`, `tokens`).\n" - }, - "limit": { - "type": "integer", - "description": "The maximum allowed value for the rate limit." - }, - "remaining": { - "type": "integer", - "description": "The remaining value before the limit is reached." - }, - "reset_seconds": { - "type": "number", - "description": "Seconds until the rate limit resets." - } - } - } - } - }, - "required": [ - "event_id", - "type", - "rate_limits" - ], - "x-oaiMeta": { - "name": "rate_limits.updated", - "group": "realtime", - "example": "{\n \"event_id\": \"event_5758\",\n \"type\": \"rate_limits.updated\",\n \"rate_limits\": [\n {\n \"name\": \"requests\",\n \"limit\": 1000,\n \"remaining\": 999,\n \"reset_seconds\": 60\n },\n {\n \"name\": \"tokens\",\n \"limit\": 50000,\n \"remaining\": 49950,\n \"reset_seconds\": 60\n }\n ]\n}\n" - } - }, - "RealtimeServerEventResponseAudioDelta": { - "type": "object", - "description": "Returned when the model-generated audio is updated.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.output_audio.delta`.", - "x-stainless-const": true, - "const": "response.output_audio.delta" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part in the item's content array." - }, - "delta": { - "type": "string", - "description": "Base64-encoded audio data delta." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "content_index", - "delta" - ], - "x-oaiMeta": { - "name": "response.output_audio.delta", - "group": "realtime", - "example": "{\n \"event_id\": \"event_4950\",\n \"type\": \"response.output_audio.delta\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"msg_008\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"delta\": \"Base64EncodedAudioDelta\"\n}\n" - } - }, - "RealtimeServerEventResponseAudioDone": { - "type": "object", - "description": "Returned when the model-generated audio is done. Also emitted when a Response\nis interrupted, incomplete, or cancelled.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.output_audio.done`.", - "x-stainless-const": true, - "const": "response.output_audio.done" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part in the item's content array." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "content_index" - ], - "x-oaiMeta": { - "name": "response.output_audio.done", - "group": "realtime", - "example": "{\n \"event_id\": \"event_5152\",\n \"type\": \"response.output_audio.done\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"msg_008\",\n \"output_index\": 0,\n \"content_index\": 0\n}\n" - } - }, - "RealtimeServerEventResponseAudioTranscriptDelta": { - "type": "object", - "description": "Returned when the model-generated transcription of audio output is updated.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.output_audio_transcript.delta`.", - "x-stainless-const": true, - "const": "response.output_audio_transcript.delta" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part in the item's content array." - }, - "delta": { - "type": "string", - "description": "The transcript delta." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "content_index", - "delta" - ], - "x-oaiMeta": { - "name": "response.output_audio_transcript.delta", - "group": "realtime", - "example": "{\n \"event_id\": \"event_4546\",\n \"type\": \"response.output_audio_transcript.delta\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"msg_008\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"delta\": \"Hello, how can I a\"\n}\n" - } - }, - "RealtimeServerEventResponseAudioTranscriptDone": { - "type": "object", - "description": "Returned when the model-generated transcription of audio output is done\nstreaming. Also emitted when a Response is interrupted, incomplete, or\ncancelled.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.output_audio_transcript.done`.", - "x-stainless-const": true, - "const": "response.output_audio_transcript.done" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part in the item's content array." - }, - "transcript": { - "type": "string", - "description": "The final transcript of the audio." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "content_index", - "transcript" - ], - "x-oaiMeta": { - "name": "response.output_audio_transcript.done", - "group": "realtime", - "example": "{\n \"event_id\": \"event_4748\",\n \"type\": \"response.output_audio_transcript.done\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"msg_008\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"transcript\": \"Hello, how can I assist you today?\"\n}\n" - } - }, - "RealtimeServerEventResponseContentPartAdded": { - "type": "object", - "description": "Returned when a new content part is added to an assistant message item during\nresponse generation.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.content_part.added`.", - "x-stainless-const": true, - "const": "response.content_part.added" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the item to which the content part was added." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part in the item's content array." - }, - "part": { - "type": "object", - "description": "The content part that was added.", - "properties": { - "type": { - "type": "string", - "enum": [ - "text", - "audio" - ], - "description": "The content type (\"text\", \"audio\")." - }, - "text": { - "type": "string", - "description": "The text content (if type is \"text\")." - }, - "audio": { - "type": "string", - "description": "Base64-encoded audio data (if type is \"audio\")." - }, - "transcript": { - "type": "string", - "description": "The transcript of the audio (if type is \"audio\")." - } - } - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "content_index", - "part" - ], - "x-oaiMeta": { - "name": "response.content_part.added", - "group": "realtime", - "example": "{\n \"event_id\": \"event_3738\",\n \"type\": \"response.content_part.added\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"msg_007\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"part\": {\n \"type\": \"text\",\n \"text\": \"\"\n }\n}\n" - } - }, - "RealtimeServerEventResponseContentPartDone": { - "type": "object", - "description": "Returned when a content part is done streaming in an assistant message item.\nAlso emitted when a Response is interrupted, incomplete, or cancelled.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.content_part.done`.", - "x-stainless-const": true, - "const": "response.content_part.done" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part in the item's content array." - }, - "part": { - "type": "object", - "description": "The content part that is done.", - "properties": { - "type": { - "type": "string", - "enum": [ - "text", - "audio" - ], - "description": "The content type (\"text\", \"audio\")." - }, - "text": { - "type": "string", - "description": "The text content (if type is \"text\")." - }, - "audio": { - "type": "string", - "description": "Base64-encoded audio data (if type is \"audio\")." - }, - "transcript": { - "type": "string", - "description": "The transcript of the audio (if type is \"audio\")." - } - } - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "content_index", - "part" - ], - "x-oaiMeta": { - "name": "response.content_part.done", - "group": "realtime", - "example": "{\n \"event_id\": \"event_3940\",\n \"type\": \"response.content_part.done\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"msg_007\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"part\": {\n \"type\": \"text\",\n \"text\": \"Sure, I can help with that.\"\n }\n}\n" - } - }, - "RealtimeServerEventResponseCreated": { - "type": "object", - "description": "Returned when a new Response is created. The first event of response creation,\nwhere the response is in an initial state of `in_progress`.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.created`.", - "x-stainless-const": true, - "const": "response.created" - }, - "response": { - "$ref": "#/components/schemas/RealtimeResponse" - } - }, - "required": [ - "event_id", - "type", - "response" - ], - "x-oaiMeta": { - "name": "response.created", - "group": "realtime", - "example": "{\n \"type\": \"response.created\",\n \"event_id\": \"event_C9G8pqbTEddBSIxbBN6Os\",\n \"response\": {\n \"object\": \"realtime.response\",\n \"id\": \"resp_C9G8p7IH2WxLbkgPNouYL\",\n \"status\": \"in_progress\",\n \"status_details\": null,\n \"output\": [],\n \"conversation_id\": \"conv_C9G8mmBkLhQJwCon3hoJN\",\n \"output_modalities\": [\n \"audio\"\n ],\n \"max_output_tokens\": \"inf\",\n \"audio\": {\n \"output\": {\n \"format\": {\n \"type\": \"audio/pcm\",\n \"rate\": 24000\n },\n \"voice\": \"marin\"\n }\n },\n \"usage\": null,\n \"metadata\": null\n },\n \"timestamp\": \"2:30:35 PM\"\n}\n" - } - }, - "RealtimeServerEventResponseDone": { - "type": "object", - "description": "Returned when a Response is done streaming. Always emitted, no matter the \nfinal state. The Response object included in the `response.done` event will \ninclude all output Items in the Response but will omit the raw audio data.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.done`.", - "x-stainless-const": true, - "const": "response.done" - }, - "response": { - "$ref": "#/components/schemas/RealtimeResponse" - } - }, - "required": [ - "event_id", - "type", - "response" - ], - "x-oaiMeta": { - "name": "response.done", - "group": "realtime", - "example": "{\n \"event_id\": \"event_3132\",\n \"type\": \"response.done\",\n \"response\": {\n \"id\": \"resp_001\",\n \"object\": \"realtime.response\",\n \"status\": \"completed\",\n \"status_details\": null,\n \"output\": [\n {\n \"id\": \"msg_006\",\n \"object\": \"realtime.item\",\n \"type\": \"message\",\n \"status\": \"completed\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": \"Sure, how can I assist you today?\"\n }\n ]\n }\n ],\n \"usage\": {\n \"total_tokens\":275,\n \"input_tokens\":127,\n \"output_tokens\":148,\n \"input_token_details\": {\n \"cached_tokens\":384,\n \"text_tokens\":119,\n \"audio_tokens\":8,\n \"cached_tokens_details\": {\n \"text_tokens\": 128,\n \"audio_tokens\": 256\n }\n },\n \"output_token_details\": {\n \"text_tokens\":36,\n \"audio_tokens\":112\n }\n }\n }\n}\n" - } - }, - "RealtimeServerEventResponseFunctionCallArgumentsDelta": { - "type": "object", - "description": "Returned when the model-generated function call arguments are updated.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.function_call_arguments.delta`.\n", - "x-stainless-const": true, - "const": "response.function_call_arguments.delta" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the function call item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "call_id": { - "type": "string", - "description": "The ID of the function call." - }, - "delta": { - "type": "string", - "description": "The arguments delta as a JSON string." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "call_id", - "delta" - ], - "x-oaiMeta": { - "name": "response.function_call_arguments.delta", - "group": "realtime", - "example": "{\n \"event_id\": \"event_5354\",\n \"type\": \"response.function_call_arguments.delta\",\n \"response_id\": \"resp_002\",\n \"item_id\": \"fc_001\",\n \"output_index\": 0,\n \"call_id\": \"call_001\",\n \"delta\": \"{\\\"location\\\": \\\"San\\\"\"\n}\n" - } - }, - "RealtimeServerEventResponseFunctionCallArgumentsDone": { - "type": "object", - "description": "Returned when the model-generated function call arguments are done streaming.\nAlso emitted when a Response is interrupted, incomplete, or cancelled.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.function_call_arguments.done`.\n", - "x-stainless-const": true, - "const": "response.function_call_arguments.done" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the function call item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "call_id": { - "type": "string", - "description": "The ID of the function call." - }, - "arguments": { - "type": "string", - "description": "The final arguments as a JSON string." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "call_id", - "arguments" - ], - "x-oaiMeta": { - "name": "response.function_call_arguments.done", - "group": "realtime", - "example": "{\n \"event_id\": \"event_5556\",\n \"type\": \"response.function_call_arguments.done\",\n \"response_id\": \"resp_002\",\n \"item_id\": \"fc_001\",\n \"output_index\": 0,\n \"call_id\": \"call_001\",\n \"arguments\": \"{\\\"location\\\": \\\"San Francisco\\\"}\"\n}\n" - } - }, - "RealtimeServerEventResponseMCPCallArgumentsDelta": { - "type": "object", - "description": "Returned when MCP tool call arguments are updated during response generation.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.mcp_call_arguments.delta`.", - "x-stainless-const": true, - "const": "response.mcp_call_arguments.delta" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "delta": { - "type": "string", - "description": "The JSON-encoded arguments delta." - }, - "obfuscation": { - "type": "string", - "nullable": true, - "description": "If present, indicates the delta text was obfuscated." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "delta" - ], - "x-oaiMeta": { - "name": "response.mcp_call_arguments.delta", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6201\",\n \"type\": \"response.mcp_call_arguments.delta\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"mcp_call_001\",\n \"output_index\": 0,\n \"delta\": \"{\\\"partial\\\":true}\"\n}\n" - } - }, - "RealtimeServerEventResponseMCPCallArgumentsDone": { - "type": "object", - "description": "Returned when MCP tool call arguments are finalized during response generation.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.mcp_call_arguments.done`.", - "x-stainless-const": true, - "const": "response.mcp_call_arguments.done" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "arguments": { - "type": "string", - "description": "The final JSON-encoded arguments string." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "arguments" - ], - "x-oaiMeta": { - "name": "response.mcp_call_arguments.done", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6202\",\n \"type\": \"response.mcp_call_arguments.done\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"mcp_call_001\",\n \"output_index\": 0,\n \"arguments\": \"{\\\"q\\\":\\\"docs\\\"}\"\n}\n" - } - }, - "RealtimeServerEventResponseMCPCallCompleted": { - "type": "object", - "description": "Returned when an MCP tool call has completed successfully.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.mcp_call.completed`.", - "x-stainless-const": true, - "const": "response.mcp_call.completed" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item." - } - }, - "required": [ - "event_id", - "type", - "output_index", - "item_id" - ], - "x-oaiMeta": { - "name": "response.mcp_call.completed", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6302\",\n \"type\": \"response.mcp_call.completed\",\n \"output_index\": 0,\n \"item_id\": \"mcp_call_001\"\n}\n" - } - }, - "RealtimeServerEventResponseMCPCallFailed": { - "type": "object", - "description": "Returned when an MCP tool call has failed.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.mcp_call.failed`.", - "x-stainless-const": true, - "const": "response.mcp_call.failed" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item." - } - }, - "required": [ - "event_id", - "type", - "output_index", - "item_id" - ], - "x-oaiMeta": { - "name": "response.mcp_call.failed", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6303\",\n \"type\": \"response.mcp_call.failed\",\n \"output_index\": 0,\n \"item_id\": \"mcp_call_001\"\n}\n" - } - }, - "RealtimeServerEventResponseMCPCallInProgress": { - "type": "object", - "description": "Returned when an MCP tool call has started and is in progress.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.mcp_call.in_progress`.", - "x-stainless-const": true, - "const": "response.mcp_call.in_progress" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item." - } - }, - "required": [ - "event_id", - "type", - "output_index", - "item_id" - ], - "x-oaiMeta": { - "name": "response.mcp_call.in_progress", - "group": "realtime", - "example": "{\n \"event_id\": \"event_6301\",\n \"type\": \"response.mcp_call.in_progress\",\n \"output_index\": 0,\n \"item_id\": \"mcp_call_001\"\n}\n" - } - }, - "RealtimeServerEventResponseOutputItemAdded": { - "type": "object", - "description": "Returned when a new Item is created during Response generation.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.output_item.added`.", - "x-stainless-const": true, - "const": "response.output_item.added" - }, - "response_id": { - "type": "string", - "description": "The ID of the Response to which the item belongs." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the Response." - }, - "item": { - "$ref": "#/components/schemas/RealtimeConversationItem" - } - }, - "required": [ - "event_id", - "type", - "response_id", - "output_index", - "item" - ], - "x-oaiMeta": { - "name": "response.output_item.added", - "group": "realtime", - "example": "{\n \"event_id\": \"event_3334\",\n \"type\": \"response.output_item.added\",\n \"response_id\": \"resp_001\",\n \"output_index\": 0,\n \"item\": {\n \"id\": \"msg_007\",\n \"object\": \"realtime.item\",\n \"type\": \"message\",\n \"status\": \"in_progress\",\n \"role\": \"assistant\",\n \"content\": []\n }\n}\n" - } - }, - "RealtimeServerEventResponseOutputItemDone": { - "type": "object", - "description": "Returned when an Item is done streaming. Also emitted when a Response is \ninterrupted, incomplete, or cancelled.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.output_item.done`.", - "x-stainless-const": true, - "const": "response.output_item.done" - }, - "response_id": { - "type": "string", - "description": "The ID of the Response to which the item belongs." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the Response." - }, - "item": { - "$ref": "#/components/schemas/RealtimeConversationItem" - } - }, - "required": [ - "event_id", - "type", - "response_id", - "output_index", - "item" - ], - "x-oaiMeta": { - "name": "response.output_item.done", - "group": "realtime", - "example": "{\n \"event_id\": \"event_3536\",\n \"type\": \"response.output_item.done\",\n \"response_id\": \"resp_001\",\n \"output_index\": 0,\n \"item\": {\n \"id\": \"msg_007\",\n \"object\": \"realtime.item\",\n \"type\": \"message\",\n \"status\": \"completed\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"text\",\n \"text\": \"Sure, I can help with that.\"\n }\n ]\n }\n}\n" - } - }, - "RealtimeServerEventResponseTextDelta": { - "type": "object", - "description": "Returned when the text value of an \"output_text\" content part is updated.", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.output_text.delta`.", - "x-stainless-const": true, - "const": "response.output_text.delta" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part in the item's content array." - }, - "delta": { - "type": "string", - "description": "The text delta." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "content_index", - "delta" - ], - "x-oaiMeta": { - "name": "response.output_text.delta", - "group": "realtime", - "example": "{\n \"event_id\": \"event_4142\",\n \"type\": \"response.output_text.delta\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"msg_007\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"delta\": \"Sure, I can h\"\n}\n" - } - }, - "RealtimeServerEventResponseTextDone": { - "type": "object", - "description": "Returned when the text value of an \"output_text\" content part is done streaming. Also\nemitted when a Response is interrupted, incomplete, or cancelled.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `response.output_text.done`.", - "x-stainless-const": true, - "const": "response.output_text.done" - }, - "response_id": { - "type": "string", - "description": "The ID of the response." - }, - "item_id": { - "type": "string", - "description": "The ID of the item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part in the item's content array." - }, - "text": { - "type": "string", - "description": "The final text content." - } - }, - "required": [ - "event_id", - "type", - "response_id", - "item_id", - "output_index", - "content_index", - "text" - ], - "x-oaiMeta": { - "name": "response.output_text.done", - "group": "realtime", - "example": "{\n \"event_id\": \"event_4344\",\n \"type\": \"response.output_text.done\",\n \"response_id\": \"resp_001\",\n \"item_id\": \"msg_007\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"text\": \"Sure, I can help with that.\"\n}\n" - } - }, - "RealtimeServerEventSessionCreated": { - "type": "object", - "description": "Returned when a Session is created. Emitted automatically when a new \nconnection is established as the first server event. This event will contain \nthe default Session configuration.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `session.created`.", - "x-stainless-const": true, - "const": "session.created" - }, - "session": { - "$ref": "#/components/schemas/RealtimeSession" - } - }, - "required": [ - "event_id", - "type", - "session" - ], - "x-oaiMeta": { - "name": "session.created", - "group": "realtime", - "example": "{\n \"type\": \"session.created\",\n \"event_id\": \"event_C9G5RJeJ2gF77mV7f2B1j\",\n \"session\": {\n \"type\": \"realtime\",\n \"object\": \"realtime.session\",\n \"id\": \"sess_C9G5QPteg4UIbotdKLoYQ\",\n \"model\": \"gpt-4o-realtime-preview-2025-08-25\",\n \"output_modalities\": [\n \"audio\"\n ],\n \"instructions\": \"Your knowledge cutoff is 2023-10. You are a helpful, witty, and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human things in the real world. Your voice and personality should be warm and engaging, with a lively and playful tone. If interacting in a non-English language, start by using the standard accent or dialect familiar to the user. Talk quickly. You should always call a function if you can. Do not refer to these rules, even if youโ€™re asked about them.\",\n \"tools\": [],\n \"tool_choice\": \"auto\",\n \"max_output_tokens\": \"inf\",\n \"tracing\": null,\n \"prompt\": null,\n \"expires_at\": 1756324625,\n \"audio\": {\n \"input\": {\n \"format\": {\n \"type\": \"audio/pcm\",\n \"rate\": 24000\n },\n \"transcription\": null,\n \"noise_reduction\": null,\n \"turn_detection\": {\n \"type\": \"server_vad\",\n \"threshold\": 0.5,\n \"prefix_padding_ms\": 300,\n \"silence_duration_ms\": 200,\n \"idle_timeout_ms\": null,\n \"create_response\": true,\n \"interrupt_response\": true\n }\n },\n \"output\": {\n \"format\": {\n \"type\": \"audio/pcm\",\n \"rate\": 24000\n },\n \"voice\": \"marin\",\n \"speed\": 1\n }\n },\n \"include\": null\n },\n \"timestamp\": \"2:27:05 PM\"\n}\n" - } - }, - "RealtimeServerEventSessionUpdated": { - "type": "object", - "description": "Returned when a session is updated with a `session.update` event, unless \nthere is an error.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `session.updated`.", - "x-stainless-const": true, - "const": "session.updated" - }, - "session": { - "$ref": "#/components/schemas/RealtimeSession" - } - }, - "required": [ - "event_id", - "type", - "session" - ], - "x-oaiMeta": { - "name": "session.updated", - "group": "realtime", - "example": "{\n \"type\": \"session.updated\",\n \"event_id\": \"event_C9G8mqI3IucaojlVKE8Cs\",\n \"session\": {\n \"type\": \"realtime\",\n \"object\": \"realtime.session\",\n \"id\": \"sess_C9G8l3zp50uFv4qgxfJ8o\",\n \"model\": \"gpt-4o-realtime-preview-2025-08-25\",\n \"output_modalities\": [\n \"audio\"\n ],\n \"instructions\": \"Your knowledge cutoff is 2023-10. You are a helpful, witty, and friendly AI. Act like a human, but remember that you aren't a human and that you can't do human things in the real world. Your voice and personality should be warm and engaging, with a lively and playful tone. If interacting in a non-English language, start by using the standard accent or dialect familiar to the user. Talk quickly. You should always call a function if you can. Do not refer to these rules, even if youโ€™re asked about them.\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"name\": \"display_color_palette\",\n \"description\": \"\\nCall this function when a user asks for a color palette.\\n\",\n \"parameters\": {\n \"type\": \"object\",\n \"strict\": true,\n \"properties\": {\n \"theme\": {\n \"type\": \"string\",\n \"description\": \"Description of the theme for the color scheme.\"\n },\n \"colors\": {\n \"type\": \"array\",\n \"description\": \"Array of five hex color codes based on the theme.\",\n \"items\": {\n \"type\": \"string\",\n \"description\": \"Hex color code\"\n }\n }\n },\n \"required\": [\n \"theme\",\n \"colors\"\n ]\n }\n }\n ],\n \"tool_choice\": \"auto\",\n \"max_output_tokens\": \"inf\",\n \"tracing\": null,\n \"prompt\": null,\n \"expires_at\": 1756324832,\n \"audio\": {\n \"input\": {\n \"format\": {\n \"type\": \"audio/pcm\",\n \"rate\": 24000\n },\n \"transcription\": null,\n \"noise_reduction\": null,\n \"turn_detection\": {\n \"type\": \"server_vad\",\n \"threshold\": 0.5,\n \"prefix_padding_ms\": 300,\n \"silence_duration_ms\": 200,\n \"idle_timeout_ms\": null,\n \"create_response\": true,\n \"interrupt_response\": true\n }\n },\n \"output\": {\n \"format\": {\n \"type\": \"audio/pcm\",\n \"rate\": 24000\n },\n \"voice\": \"marin\",\n \"speed\": 1\n }\n },\n \"include\": null\n },\n \"timestamp\": \"2:30:32 PM\"\n}\n" - } - }, - "RealtimeServerEventTranscriptionSessionCreated": { - "type": "object", - "description": "Returned when a transcription session is created.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `transcription_session.created`.", - "x-stainless-const": true, - "const": "transcription_session.created" - }, - "session": { - "$ref": "#/components/schemas/RealtimeTranscriptionSessionCreateResponse" - } - }, - "required": [ - "event_id", - "type", - "session" - ], - "x-oaiMeta": { - "name": "transcription_session.created", - "group": "realtime", - "example": "{\n \"event_id\": \"event_5566\",\n \"type\": \"transcription_session.created\",\n \"session\": {\n \"id\": \"sess_001\",\n \"object\": \"realtime.transcription_session\",\n \"input_audio_format\": \"pcm16\",\n \"input_audio_transcription\": {\n \"model\": \"gpt-4o-transcribe\",\n \"prompt\": \"\",\n \"language\": \"\"\n },\n \"turn_detection\": {\n \"type\": \"server_vad\",\n \"threshold\": 0.5,\n \"prefix_padding_ms\": 300,\n \"silence_duration_ms\": 500\n },\n \"input_audio_noise_reduction\": {\n \"type\": \"near_field\"\n },\n \"include\": []\n }\n}\n" - } - }, - "RealtimeServerEventTranscriptionSessionUpdated": { - "type": "object", - "description": "Returned when a transcription session is updated with a `transcription_session.update` event, unless \nthere is an error.\n", - "properties": { - "event_id": { - "type": "string", - "description": "The unique ID of the server event." - }, - "type": { - "description": "The event type, must be `transcription_session.updated`.", - "x-stainless-const": true, - "const": "transcription_session.updated" - }, - "session": { - "$ref": "#/components/schemas/RealtimeTranscriptionSessionCreateResponse" - } - }, - "required": [ - "event_id", - "type", - "session" - ], - "x-oaiMeta": { - "name": "transcription_session.updated", - "group": "realtime", - "example": "{\n \"event_id\": \"event_5678\",\n \"type\": \"transcription_session.updated\",\n \"session\": {\n \"id\": \"sess_001\",\n \"object\": \"realtime.transcription_session\",\n \"input_audio_format\": \"pcm16\",\n \"input_audio_transcription\": {\n \"model\": \"gpt-4o-transcribe\",\n \"prompt\": \"\",\n \"language\": \"\"\n },\n \"turn_detection\": {\n \"type\": \"server_vad\",\n \"threshold\": 0.5,\n \"prefix_padding_ms\": 300,\n \"silence_duration_ms\": 500,\n \"create_response\": true,\n // \"interrupt_response\": false -- this will NOT be returned\n },\n \"input_audio_noise_reduction\": {\n \"type\": \"near_field\"\n },\n \"include\": [\n \"item.input_audio_transcription.avg_logprob\",\n ],\n }\n}\n" - } - }, - "RealtimeSession": { - "type": "object", - "description": "Realtime session object.", - "properties": { - "id": { - "type": "string", - "description": "Unique identifier for the session that looks like `sess_1234567890abcdef`.\n" - }, - "object": { - "type": "string", - "enum": [ - "realtime.session" - ], - "description": "The object type. Always `realtime.session`." - }, - "modalities": { - "description": "The set of modalities the model can respond with. To disable audio,\nset this to [\"text\"].\n", - "items": { - "type": "string", - "enum": [ - "text", - "audio" - ] - } - }, - "model": { - "type": "string", - "description": "The Realtime model used for this session.\n", - "enum": [ - "gpt-realtime", - "gpt-realtime-2025-08-28", - "gpt-4o-realtime-preview", - "gpt-4o-realtime-preview-2024-10-01", - "gpt-4o-realtime-preview-2024-12-17", - "gpt-4o-realtime-preview-2025-06-03", - "gpt-4o-mini-realtime-preview", - "gpt-4o-mini-realtime-preview-2024-12-17" - ] - }, - "instructions": { - "type": "string", - "description": "The default system instructions (i.e. system message) prepended to model\ncalls. This field allows the client to guide the model on desired\nresponses. The model can be instructed on response content and format,\n(e.g. \"be extremely succinct\", \"act friendly\", \"here are examples of good\nresponses\") and on audio behavior (e.g. \"talk quickly\", \"inject emotion\ninto your voice\", \"laugh frequently\"). The instructions are not\nguaranteed to be followed by the model, but they provide guidance to the\nmodel on the desired behavior.\n\n\nNote that the server sets default instructions which will be used if this\nfield is not set and are visible in the `session.created` event at the\nstart of the session.\n" - }, - "voice": { - "$ref": "#/components/schemas/VoiceIdsShared", - "description": "The voice the model uses to respond. Voice cannot be changed during the\nsession once the model has responded with audio at least once. Current\nvoice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `sage`,\n`shimmer`, and `verse`.\n" - }, - "input_audio_format": { - "type": "string", - "default": "pcm16", - "enum": [ - "pcm16", - "g711_ulaw", - "g711_alaw" - ], - "description": "The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\nFor `pcm16`, input audio must be 16-bit PCM at a 24kHz sample rate,\nsingle channel (mono), and little-endian byte order.\n" - }, - "output_audio_format": { - "type": "string", - "default": "pcm16", - "enum": [ - "pcm16", - "g711_ulaw", - "g711_alaw" - ], - "description": "The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\nFor `pcm16`, output audio is sampled at a rate of 24kHz.\n" - }, - "input_audio_transcription": { - "type": "object", - "nullable": true, - "description": "Configuration for input audio transcription, defaults to off and can be set to `null` to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through [the /audio/transcriptions endpoint](https://platform.openai.com/docs/api-reference/audio/createTranscription) and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.\n", - "properties": { - "model": { - "type": "string", - "description": "The model to use for transcription, current options are `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, and `whisper-1`.\n" - }, - "language": { - "type": "string", - "description": "The language of the input audio. Supplying the input language in\n[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format\nwill improve accuracy and latency.\n" - }, - "prompt": { - "type": "string", - "description": "An optional text to guide the model's style or continue a previous audio\nsegment.\nFor `whisper-1`, the [prompt is a list of keywords](https://platform.openai.com/docs/guides/speech-to-text#prompting).\nFor `gpt-4o-transcribe` models, the prompt is a free text string, for example \"expect words related to technology\".\n" - } - } - }, - "turn_detection": { - "type": "object", - "nullable": true, - "description": "Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to `null` to turn off, in which case the client must manually trigger model response.\nServer VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.\nSemantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with \"uhhm\", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.\n", - "properties": { - "type": { - "type": "string", - "default": "server_vad", - "enum": [ - "server_vad", - "semantic_vad" - ], - "description": "Type of turn detection.\n" - }, - "eagerness": { - "type": "string", - "default": "auto", - "enum": [ - "low", - "medium", - "high", - "auto" - ], - "description": "Used only for `semantic_vad` mode. The eagerness of the model to respond. `low` will wait longer for the user to continue speaking, `high` will respond more quickly. `auto` is the default and is equivalent to `medium`.\n" - }, - "threshold": { - "type": "number", - "description": "Used only for `server_vad` mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A\nhigher threshold will require louder audio to activate the model, and\nthus might perform better in noisy environments.\n" - }, - "prefix_padding_ms": { - "type": "integer", - "description": "Used only for `server_vad` mode. Amount of audio to include before the VAD detected speech (in\nmilliseconds). Defaults to 300ms.\n" - }, - "silence_duration_ms": { - "type": "integer", - "description": "Used only for `server_vad` mode. Duration of silence to detect speech stop (in milliseconds). Defaults\nto 500ms. With shorter values the model will respond more quickly,\nbut may jump in on short pauses from the user.\n" - }, - "create_response": { - "type": "boolean", - "default": true, - "description": "Whether or not to automatically generate a response when a VAD stop event occurs.\n" - }, - "interrupt_response": { - "type": "boolean", - "default": true, - "description": "Whether or not to automatically interrupt any ongoing response with output to the default\nconversation (i.e. `conversation` of `auto`) when a VAD start event occurs.\n" - }, - "idle_timeout_ms": { - "type": "integer", - "nullable": true, - "description": "Optional idle timeout after which turn detection will auto-timeout when\nno additional audio is received.\n" - } - } - }, - "input_audio_noise_reduction": { - "type": "object", - "description": "Configuration for input audio noise reduction. This can be set to `null` to turn off.\nNoise reduction filters audio added to the input audio buffer before it is sent to VAD and the model.\nFiltering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "near_field", - "far_field" - ], - "description": "Type of noise reduction. `near_field` is for close-talking microphones such as headphones, `far_field` is for far-field microphones such as laptop or conference room microphones.\n" - } - } - }, - "speed": { - "type": "number", - "default": 1, - "maximum": 1.5, - "minimum": 0.25, - "description": "The speed of the model's spoken response. 1.0 is the default speed. 0.25 is\nthe minimum speed. 1.5 is the maximum speed. This value can only be changed\nin between model turns, not while a response is in progress.\n" - }, - "tracing": { - "title": "Tracing Configuration", - "nullable": true, - "description": "Configuration options for tracing. Set to null to disable tracing. Once\ntracing is enabled for a session, the configuration cannot be modified.\n\n`auto` will create a trace for the session with default values for the\nworkflow name, group id, and metadata.\n", - "anyOf": [ - { - "type": "string", - "default": "auto", - "description": "Default tracing mode for the session.\n", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "object", - "title": "Tracing Configuration", - "description": "Granular configuration for tracing.\n", - "properties": { - "workflow_name": { - "type": "string", - "description": "The name of the workflow to attach to this trace. This is used to\nname the trace in the traces dashboard.\n" - }, - "group_id": { - "type": "string", - "description": "The group id to attach to this trace to enable filtering and\ngrouping in the traces dashboard.\n" - }, - "metadata": { - "type": "object", - "description": "The arbitrary metadata to attach to this trace to enable\nfiltering in the traces dashboard.\n" - } - } - } - ] - }, - "tools": { - "type": "array", - "description": "Tools (functions) available to the model.", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "The type of the tool, i.e. `function`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the function." - }, - "description": { - "type": "string", - "description": "The description of the function, including guidance on when and how\nto call it, and guidance about what to tell the user when calling\n(if anything).\n" - }, - "parameters": { - "type": "object", - "description": "Parameters of the function in JSON Schema." - } - } - } - }, - "tool_choice": { - "type": "string", - "default": "auto", - "description": "How the model chooses tools. Options are `auto`, `none`, `required`, or\nspecify a function.\n" - }, - "temperature": { - "type": "number", - "default": 0.8, - "description": "Sampling temperature for the model, limited to [0.6, 1.2]. For audio models a temperature of 0.8 is highly recommended for best performance.\n" - }, - "max_response_output_tokens": { - "description": "Maximum number of output tokens for a single assistant response,\ninclusive of tool calls. Provide an integer between 1 and 4096 to\nlimit output tokens, or `inf` for the maximum available tokens for a\ngiven model. Defaults to `inf`.\n", - "anyOf": [ - { - "type": "integer" - }, - { - "type": "string", - "enum": [ - "inf" - ], - "x-stainless-const": true - } - ] - }, - "expires_at": { - "type": "integer", - "description": "Expiration timestamp for the session, in seconds since epoch." - }, - "prompt": { - "$ref": "#/components/schemas/Prompt", - "nullable": true - }, - "include": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "item.input_audio_transcription.logprobs" - ] - }, - "nullable": true, - "description": "Additional fields to include in server outputs.\n- `item.input_audio_transcription.logprobs`: Include logprobs for input audio transcription.\n" - } - } - }, - "RealtimeSessionCreateRequest": { - "type": "object", - "title": "Realtime session configuration", - "description": "Realtime session object configuration.", - "properties": { - "type": { - "type": "string", - "description": "The type of session to create. Always `realtime` for the Realtime API.\n", - "enum": [ - "realtime" - ], - "x-stainless-const": true - }, - "output_modalities": { - "description": "The set of modalities the model can respond with. To disable audio,\nset this to [\"text\"].\n", - "items": { - "type": "string", - "enum": [ - "text", - "audio" - ] - } - }, - "model": { - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "gpt-realtime", - "gpt-realtime-2025-08-28", - "gpt-4o-realtime", - "gpt-4o-mini-realtime", - "gpt-4o-realtime-preview", - "gpt-4o-realtime-preview-2024-10-01", - "gpt-4o-realtime-preview-2024-12-17", - "gpt-4o-realtime-preview-2025-06-03", - "gpt-4o-mini-realtime-preview", - "gpt-4o-mini-realtime-preview-2024-12-17" - ], - "x-stainless-nominal": false - } - ], - "description": "The Realtime model used for this session.\n" - }, - "instructions": { - "type": "string", - "description": "The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. \"be extremely succinct\", \"act friendly\", \"here are examples of good responses\") and on audio behavior (e.g. \"talk quickly\", \"inject emotion into your voice\", \"laugh frequently\"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.\n\nNote that the server sets default instructions which will be used if this field is not set and are visible in the `session.created` event at the start of the session.\n" - }, - "audio": { - "type": "object", - "description": "Configuration for input and output audio.\n", - "properties": { - "input": { - "type": "object", - "properties": { - "format": { - "type": "string", - "default": "pcm16", - "enum": [ - "pcm16", - "g711_ulaw", - "g711_alaw" - ], - "description": "The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\nFor `pcm16`, input audio must be 16-bit PCM at a 24kHz sample rate,\nsingle channel (mono), and little-endian byte order.\n" - }, - "transcription": { - "type": "object", - "description": "Configuration for input audio transcription, defaults to off and can be set to `null` to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through [the /audio/transcriptions endpoint](https://platform.openai.com/docs/api-reference/audio/createTranscription) and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.\n", - "properties": { - "model": { - "type": "string", - "description": "The model to use for transcription. Current options are\n`whisper-1`, `gpt-4o-transcribe-latest`, `gpt-4o-mini-transcribe`, `gpt-4o-transcribe`,\nand `gpt-4o-transcribe-diarize`.\n", - "enum": [ - "whisper-1", - "gpt-4o-transcribe-latest", - "gpt-4o-mini-transcribe", - "gpt-4o-transcribe", - "gpt-4o-transcribe-diarize" - ] - }, - "language": { - "type": "string", - "description": "The language of the input audio. Supplying the input language in\n[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format\nwill improve accuracy and latency.\n" - }, - "prompt": { - "type": "string", - "description": "An optional text to guide the model's style or continue a previous audio\nsegment.\nFor `whisper-1`, the [prompt is a list of keywords](https://platform.openai.com/docs/guides/speech-to-text#prompting).\nFor `gpt-4o-transcribe` models, the prompt is a free text string, for example \"expect words related to technology\".\n" - } - } - }, - "noise_reduction": { - "type": "object", - "description": "Configuration for input audio noise reduction. This can be set to `null` to turn off.\nNoise reduction filters audio added to the input audio buffer before it is sent to VAD and the model.\nFiltering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "near_field", - "far_field" - ], - "description": "Type of noise reduction. `near_field` is for close-talking microphones such as headphones, `far_field` is for far-field microphones such as laptop or conference room microphones.\n" - } - } - }, - "turn_detection": { - "type": "object", - "description": "Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to `null` to turn off, in which case the client must manually trigger model response.\nServer VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.\nSemantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with \"uhhm\", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.\n", - "properties": { - "type": { - "type": "string", - "default": "server_vad", - "enum": [ - "server_vad", - "semantic_vad" - ], - "description": "Type of turn detection.\n" - }, - "eagerness": { - "type": "string", - "default": "auto", - "enum": [ - "low", - "medium", - "high", - "auto" - ], - "description": "Used only for `semantic_vad` mode. The eagerness of the model to respond. `low` will wait longer for the user to continue speaking, `high` will respond more quickly. `auto` is the default and is equivalent to `medium`.\n" - }, - "threshold": { - "type": "number", - "description": "Used only for `server_vad` mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A\nhigher threshold will require louder audio to activate the model, and\nthus might perform better in noisy environments.\n" - }, - "prefix_padding_ms": { - "type": "integer", - "description": "Used only for `server_vad` mode. Amount of audio to include before the VAD detected speech (in\nmilliseconds). Defaults to 300ms.\n" - }, - "silence_duration_ms": { - "type": "integer", - "description": "Used only for `server_vad` mode. Duration of silence to detect speech stop (in milliseconds). Defaults\nto 500ms. With shorter values the model will respond more quickly,\nbut may jump in on short pauses from the user.\n" - }, - "create_response": { - "type": "boolean", - "default": true, - "description": "Whether or not to automatically generate a response when a VAD stop event occurs.\n" - }, - "interrupt_response": { - "type": "boolean", - "default": true, - "description": "Whether or not to automatically interrupt any ongoing response with output to the default\nconversation (i.e. `conversation` of `auto`) when a VAD start event occurs.\n" - }, - "idle_timeout_ms": { - "type": "integer", - "nullable": true, - "description": "Optional idle timeout after which turn detection will auto-timeout when\nno additional audio is received.\n" - } - } - } - } - }, - "output": { - "type": "object", - "properties": { - "format": { - "type": "string", - "default": "pcm16", - "enum": [ - "pcm16", - "g711_ulaw", - "g711_alaw" - ], - "description": "The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\nFor `pcm16`, output audio is sampled at a rate of 24kHz.\n" - }, - "voice": { - "$ref": "#/components/schemas/VoiceIdsShared", - "default": "alloy", - "description": "The voice the model uses to respond. Voice cannot be changed during the\nsession once the model has responded with audio at least once. Current\nvoice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `sage`,\n`shimmer`, `verse`, `marin`, and `cedar`.\n" - }, - "speed": { - "type": "number", - "default": 1, - "maximum": 1.5, - "minimum": 0.25, - "description": "The speed of the model's spoken response. 1.0 is the default speed. 0.25 is\nthe minimum speed. 1.5 is the maximum speed. This value can only be changed\nin between model turns, not while a response is in progress.\n" - } - } - } - } - }, - "include": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "item.input_audio_transcription.logprobs" - ] - }, - "description": "Additional fields to include in server outputs.\n- `item.input_audio_transcription.logprobs`: Include logprobs for input audio transcription.\n" - }, - "tracing": { - "title": "Tracing Configuration", - "description": "Configuration options for tracing. Set to null to disable tracing. Once\ntracing is enabled for a session, the configuration cannot be modified.\n\n`auto` will create a trace for the session with default values for the\nworkflow name, group id, and metadata.\n", - "nullable": true, - "anyOf": [ - { - "type": "string", - "default": "auto", - "description": "Default tracing mode for the session.\n", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "object", - "title": "Tracing Configuration", - "description": "Granular configuration for tracing.\n", - "properties": { - "workflow_name": { - "type": "string", - "description": "The name of the workflow to attach to this trace. This is used to\nname the trace in the traces dashboard.\n" - }, - "group_id": { - "type": "string", - "description": "The group id to attach to this trace to enable filtering and\ngrouping in the traces dashboard.\n" - }, - "metadata": { - "type": "object", - "description": "The arbitrary metadata to attach to this trace to enable\nfiltering in the traces dashboard.\n" - } - } - } - ] - }, - "tools": { - "type": "array", - "description": "Tools available to the model.", - "items": { - "anyOf": [ - { - "type": "object", - "title": "Function tool", - "properties": { - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "The type of the tool, i.e. `function`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the function." - }, - "description": { - "type": "string", - "description": "The description of the function, including guidance on when and how\nto call it, and guidance about what to tell the user when calling\n(if anything).\n" - }, - "parameters": { - "type": "object", - "description": "Parameters of the function in JSON Schema." - } - } - }, - { - "$ref": "#/components/schemas/MCPTool" - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "tool_choice": { - "description": "How the model chooses tools. Provide one of the string modes or force a specific\nfunction/MCP tool.\n", - "default": "auto", - "anyOf": [ - { - "$ref": "#/components/schemas/ToolChoiceOptions" - }, - { - "$ref": "#/components/schemas/ToolChoiceFunction" - }, - { - "$ref": "#/components/schemas/ToolChoiceMCP" - } - ] - }, - "temperature": { - "type": "number", - "default": 0.8, - "description": "Sampling temperature for the model, limited to [0.6, 1.2]. For audio models a temperature of 0.8 is highly recommended for best performance.\n" - }, - "max_output_tokens": { - "description": "Maximum number of output tokens for a single assistant response,\ninclusive of tool calls. Provide an integer between 1 and 4096 to\nlimit output tokens, or `inf` for the maximum available tokens for a\ngiven model. Defaults to `inf`.\n", - "anyOf": [ - { - "type": "integer" - }, - { - "type": "string", - "enum": [ - "inf" - ], - "x-stainless-const": true - } - ] - }, - "truncation": { - "$ref": "#/components/schemas/RealtimeTruncation" - }, - "prompt": { - "$ref": "#/components/schemas/Prompt" - }, - "client_secret": { - "type": "object", - "description": "Configuration options for the generated client secret.\n", - "properties": { - "expires_after": { - "type": "object", - "description": "Configuration for the ephemeral token expiration.\n", - "properties": { - "anchor": { - "type": "string", - "enum": [ - "created_at" - ], - "description": "The anchor point for the ephemeral token expiration. Only `created_at` is currently supported.\n" - }, - "seconds": { - "default": 600, - "type": "integer", - "description": "The number of seconds from the anchor point to the expiration. Select a value between `10` and `7200`.\n" - } - }, - "required": [ - "anchor" - ] - } - } - } - }, - "required": [ - "type", - "model" - ] - }, - "RealtimeSessionCreateResponse": { - "type": "object", - "title": "Realtime session configuration object", - "description": "A Realtime session configuration object.\n", - "properties": { - "id": { - "type": "string", - "description": "Unique identifier for the session that looks like `sess_1234567890abcdef`.\n" - }, - "object": { - "type": "string", - "description": "The object type. Always `realtime.session`." - }, - "expires_at": { - "type": "integer", - "description": "Expiration timestamp for the session, in seconds since epoch." - }, - "include": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "item.input_audio_transcription.logprobs" - ] - }, - "description": "Additional fields to include in server outputs.\n- `item.input_audio_transcription.logprobs`: Include logprobs for input audio transcription.\n" - }, - "model": { - "type": "string", - "description": "The Realtime model used for this session." - }, - "output_modalities": { - "description": "The set of modalities the model can respond with. To disable audio,\nset this to [\"text\"].\n", - "items": { - "type": "string", - "enum": [ - "text", - "audio" - ] - } - }, - "instructions": { - "type": "string", - "description": "The default system instructions (i.e. system message) prepended to model\ncalls. This field allows the client to guide the model on desired\nresponses. The model can be instructed on response content and format,\n(e.g. \"be extremely succinct\", \"act friendly\", \"here are examples of good\nresponses\") and on audio behavior (e.g. \"talk quickly\", \"inject emotion\ninto your voice\", \"laugh frequently\"). The instructions are not guaranteed\nto be followed by the model, but they provide guidance to the model on the\ndesired behavior.\n\nNote that the server sets default instructions which will be used if this\nfield is not set and are visible in the `session.created` event at the\nstart of the session.\n" - }, - "audio": { - "type": "object", - "description": "Configuration for input and output audio for the session.\n", - "properties": { - "input": { - "type": "object", - "properties": { - "format": { - "type": "string", - "description": "The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\n" - }, - "transcription": { - "type": "object", - "description": "Configuration for input audio transcription.\n", - "properties": { - "model": { - "type": "string", - "description": "The model to use for transcription.\n" - }, - "language": { - "type": "string", - "description": "The language of the input audio.\n" - }, - "prompt": { - "type": "string", - "description": "Optional text to guide the model's style or continue a previous audio segment.\n" - } - } - }, - "noise_reduction": { - "type": "object", - "description": "Configuration for input audio noise reduction.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "near_field", - "far_field" - ] - } - } - }, - "turn_detection": { - "type": "object", - "description": "Configuration for turn detection.\n", - "properties": { - "type": { - "type": "string", - "description": "Type of turn detection, only `server_vad` is currently supported.\n" - }, - "threshold": { - "type": "number" - }, - "prefix_padding_ms": { - "type": "integer" - }, - "silence_duration_ms": { - "type": "integer" - } - } - } - } - }, - "output": { - "type": "object", - "properties": { - "format": { - "type": "string", - "description": "The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\n" - }, - "voice": { - "$ref": "#/components/schemas/VoiceIdsShared" - }, - "speed": { - "type": "number" - } - } - } - } - }, - "tracing": { - "title": "Tracing Configuration", - "description": "Configuration options for tracing. Set to null to disable tracing. Once\ntracing is enabled for a session, the configuration cannot be modified.\n\n`auto` will create a trace for the session with default values for the\nworkflow name, group id, and metadata.\n", - "anyOf": [ - { - "type": "string", - "default": "auto", - "description": "Default tracing mode for the session.\n", - "enum": [ - "auto" - ], - "x-stainless-const": true - }, - { - "type": "object", - "title": "Tracing Configuration", - "description": "Granular configuration for tracing.\n", - "properties": { - "workflow_name": { - "type": "string", - "description": "The name of the workflow to attach to this trace. This is used to\nname the trace in the traces dashboard.\n" - }, - "group_id": { - "type": "string", - "description": "The group id to attach to this trace to enable filtering and\ngrouping in the traces dashboard.\n" - }, - "metadata": { - "type": "object", - "description": "The arbitrary metadata to attach to this trace to enable\nfiltering in the traces dashboard.\n" - } - } - } - ] - }, - "turn_detection": { - "type": "object", - "description": "Configuration for turn detection. Can be set to `null` to turn off. Server\nVAD means that the model will detect the start and end of speech based on\naudio volume and respond at the end of user speech.\n", - "properties": { - "type": { - "type": "string", - "description": "Type of turn detection, only `server_vad` is currently supported.\n" - }, - "threshold": { - "type": "number", - "description": "Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A\nhigher threshold will require louder audio to activate the model, and\nthus might perform better in noisy environments.\n" - }, - "prefix_padding_ms": { - "type": "integer", - "description": "Amount of audio to include before the VAD detected speech (in\nmilliseconds). Defaults to 300ms.\n" - }, - "silence_duration_ms": { - "type": "integer", - "description": "Duration of silence to detect speech stop (in milliseconds). Defaults\nto 500ms. With shorter values the model will respond more quickly,\nbut may jump in on short pauses from the user.\n" - } - } - }, - "tools": { - "type": "array", - "description": "Tools (functions) available to the model.", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "The type of the tool, i.e. `function`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the function." - }, - "description": { - "type": "string", - "description": "The description of the function, including guidance on when and how\nto call it, and guidance about what to tell the user when calling\n(if anything).\n" - }, - "parameters": { - "type": "object", - "description": "Parameters of the function in JSON Schema." - } - } - } - }, - "tool_choice": { - "type": "string", - "description": "How the model chooses tools. Options are `auto`, `none`, `required`, or\nspecify a function.\n" - }, - "max_output_tokens": { - "description": "Maximum number of output tokens for a single assistant response,\ninclusive of tool calls. Provide an integer between 1 and 4096 to\nlimit output tokens, or `inf` for the maximum available tokens for a\ngiven model. Defaults to `inf`.\n", - "anyOf": [ - { - "type": "integer" - }, - { - "type": "string", - "enum": [ - "inf" - ], - "x-stainless-const": true - } - ] - } - }, - "required": [ - "client_secret" - ], - "x-oaiMeta": { - "name": "The session object", - "group": "realtime", - "example": "{\n \"id\": \"sess_001\",\n \"object\": \"realtime.session\",\n \"expires_at\": 1742188264,\n \"model\": \"gpt-4o-realtime\",\n \"output_modalities\": [\"audio\", \"text\"],\n \"instructions\": \"You are a friendly assistant.\",\n \"tools\": [],\n \"tool_choice\": \"none\",\n \"max_output_tokens\": \"inf\",\n \"tracing\": \"auto\",\n \"truncation\": \"auto\",\n \"prompt\": null,\n \"audio\": {\n \"input\": {\n \"format\": \"pcm16\",\n \"transcription\": { \"model\": \"whisper-1\" },\n \"noise_reduction\": null,\n \"turn_detection\": null\n },\n \"output\": {\n \"format\": \"pcm16\",\n \"voice\": \"alloy\",\n \"speed\": 1.0\n }\n },\n \"client_secret\": {\n \"value\": \"ek_abc123\",\n \"expires_at\": 1234567890\n }\n}\n" - } - }, - "RealtimeTranscriptionSessionCreateRequest": { - "type": "object", - "title": "Realtime transcription session configuration", - "description": "Realtime transcription session object configuration.", - "properties": { - "type": { - "type": "string", - "description": "The type of session to create. Always `transcription` for transcription sessions.\n", - "enum": [ - "transcription" - ], - "x-stainless-const": true - }, - "model": { - "description": "ID of the model to use. The options are `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, and `whisper-1` (which is powered by our open source Whisper V2 model).\n", - "example": "gpt-4o-transcribe", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "whisper-1", - "gpt-4o-transcribe", - "gpt-4o-mini-transcribe" - ], - "x-stainless-nominal": false - } - ] - }, - "turn_detection": { - "type": "object", - "description": "Configuration for turn detection. Can be set to `null` to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.\n", - "properties": { - "type": { - "type": "string", - "description": "Type of turn detection. Only `server_vad` is currently supported for transcription sessions.\n", - "enum": [ - "server_vad" - ] - }, - "threshold": { - "type": "number", - "description": "Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A\nhigher threshold will require louder audio to activate the model, and\nthus might perform better in noisy environments.\n" - }, - "prefix_padding_ms": { - "type": "integer", - "description": "Amount of audio to include before the VAD detected speech (in\nmilliseconds). Defaults to 300ms.\n" - }, - "silence_duration_ms": { - "type": "integer", - "description": "Duration of silence to detect speech stop (in milliseconds). Defaults\nto 500ms. With shorter values the model will respond more quickly,\nbut may jump in on short pauses from the user.\n" - } - } - }, - "input_audio_noise_reduction": { - "type": "object", - "description": "Configuration for input audio noise reduction. This can be set to `null` to turn off.\nNoise reduction filters audio added to the input audio buffer before it is sent to VAD and the model.\nFiltering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "near_field", - "far_field" - ], - "description": "Type of noise reduction. `near_field` is for close-talking microphones such as headphones, `far_field` is for far-field microphones such as laptop or conference room microphones.\n" - } - } - }, - "input_audio_format": { - "type": "string", - "default": "pcm16", - "enum": [ - "pcm16", - "g711_ulaw", - "g711_alaw" - ], - "description": "The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\nFor `pcm16`, input audio must be 16-bit PCM at a 24kHz sample rate,\nsingle channel (mono), and little-endian byte order.\n" - }, - "input_audio_transcription": { - "type": "object", - "description": "Configuration for input audio transcription. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.\n", - "properties": { - "model": { - "type": "string", - "description": "The model to use for transcription, current options are `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, and `whisper-1`.\n", - "enum": [ - "gpt-4o-transcribe", - "gpt-4o-mini-transcribe", - "whisper-1" - ] - }, - "language": { - "type": "string", - "description": "The language of the input audio. Supplying the input language in\n[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format\nwill improve accuracy and latency.\n" - }, - "prompt": { - "type": "string", - "description": "An optional text to guide the model's style or continue a previous audio\nsegment.\nFor `whisper-1`, the [prompt is a list of keywords](https://platform.openai.com/docs/guides/speech-to-text#prompting).\nFor `gpt-4o-transcribe` models, the prompt is a free text string, for example \"expect words related to technology\".\n" - } - } - }, - "include": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "item.input_audio_transcription.logprobs" - ] - }, - "description": "The set of items to include in the transcription. Current available items are:\n- `item.input_audio_transcription.logprobs`\n" - } - }, - "required": [ - "type", - "model" - ] - }, - "RealtimeTranscriptionSessionCreateResponse": { - "type": "object", - "title": "Realtime transcription session configuration object", - "description": "A Realtime transcription session configuration object.\n", - "properties": { - "id": { - "type": "string", - "description": "Unique identifier for the session that looks like `sess_1234567890abcdef`.\n" - }, - "object": { - "type": "string", - "description": "The object type. Always `realtime.transcription_session`." - }, - "expires_at": { - "type": "integer", - "description": "Expiration timestamp for the session, in seconds since epoch." - }, - "include": { - "type": "array", - "items": { - "type": "string", - "enum": [ - "item.input_audio_transcription.logprobs" - ] - }, - "description": "Additional fields to include in server outputs.\n- `item.input_audio_transcription.logprobs`: Include logprobs for input audio transcription.\n" - }, - "audio": { - "type": "object", - "description": "Configuration for input audio for the session.\n", - "properties": { - "input": { - "type": "object", - "properties": { - "format": { - "type": "string", - "description": "The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.\n" - }, - "transcription": { - "type": "object", - "description": "Configuration of the transcription model.\n", - "properties": { - "model": { - "type": "string", - "description": "The model to use for transcription. Can be `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, or `whisper-1`.\n", - "enum": [ - "gpt-4o-transcribe", - "gpt-4o-mini-transcribe", - "whisper-1" - ] - }, - "language": { - "type": "string", - "description": "The language of the input audio. Supplying the input language in\n[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format\nwill improve accuracy and latency.\n" - }, - "prompt": { - "type": "string", - "description": "An optional text to guide the model's style or continue a previous audio segment. The [prompt](https://platform.openai.com/docs/guides/speech-to-text#prompting) should match the audio language.\n" - } - } - }, - "noise_reduction": { - "type": "object", - "description": "Configuration for input audio noise reduction.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "near_field", - "far_field" - ] - } - } - }, - "turn_detection": { - "type": "object", - "description": "Configuration for turn detection.\n", - "properties": { - "type": { - "type": "string", - "description": "Type of turn detection, only `server_vad` is currently supported.\n" - }, - "threshold": { - "type": "number" - }, - "prefix_padding_ms": { - "type": "integer" - }, - "silence_duration_ms": { - "type": "integer" - } - } - } - } - } - } - } - }, - "x-oaiMeta": { - "name": "The transcription session object", - "group": "realtime", - "example": "{\n \"id\": \"sess_BBwZc7cFV3XizEyKGDCGL\",\n \"object\": \"realtime.transcription_session\",\n \"expires_at\": 1742188264,\n \"include\": [\"item.input_audio_transcription.logprobs\"],\n \"audio\": {\n \"input\": {\n \"format\": \"pcm16\",\n \"transcription\": {\n \"model\": \"gpt-4o-transcribe\",\n \"language\": null,\n \"prompt\": \"\"\n },\n \"noise_reduction\": null,\n \"turn_detection\": {\n \"type\": \"server_vad\",\n \"threshold\": 0.5,\n \"prefix_padding_ms\": 300,\n \"silence_duration_ms\": 200\n }\n }\n }\n}\n" - } - }, - "RealtimeTruncation": { - "title": "Realtime Truncation Controls", - "description": "Controls how the realtime conversation is truncated prior to model inference.\nThe default is `auto`. When set to `retention_ratio`, the server retains a\nfraction of the conversation tokens prior to the instructions.\n", - "anyOf": [ - { - "type": "string", - "description": "The truncation strategy to use for the session.", - "enum": [ - "auto", - "disabled" - ], - "title": "RealtimeTruncationStrategy" - }, - { - "type": "object", - "title": "Retention ratio truncation", - "description": "Retain a fraction of the conversation tokens.", - "properties": { - "type": { - "type": "string", - "enum": [ - "retention_ratio" - ], - "description": "Use retention ratio truncation.", - "x-stainless-const": true - }, - "retention_ratio": { - "type": "number", - "description": "Fraction of pre-instruction conversation tokens to retain (0.0 - 1.0).\n", - "minimum": 0, - "maximum": 1 - }, - "post_instructions_token_limit": { - "type": "integer", - "nullable": true, - "description": "Optional cap on tokens allowed after the instructions.\n" - } - }, - "required": [ - "type", - "retention_ratio" - ] - } - ] - }, - "Reasoning": { - "type": "object", - "description": "**gpt-5 and o-series models only**\n\nConfiguration options for\n[reasoning models](https://platform.openai.com/docs/guides/reasoning).\n", - "title": "Reasoning", - "properties": { - "effort": { - "$ref": "#/components/schemas/ReasoningEffort" - }, - "summary": { - "type": "string", - "description": "A summary of the reasoning performed by the model. This can be\nuseful for debugging and understanding the model's reasoning process.\nOne of `auto`, `concise`, or `detailed`.\n", - "enum": [ - "auto", - "concise", - "detailed" - ], - "nullable": true - }, - "generate_summary": { - "type": "string", - "deprecated": true, - "description": "**Deprecated:** use `summary` instead.\n\nA summary of the reasoning performed by the model. This can be\nuseful for debugging and understanding the model's reasoning process.\nOne of `auto`, `concise`, or `detailed`.\n", - "enum": [ - "auto", - "concise", - "detailed" - ], - "nullable": true - } - } - }, - "ReasoningEffort": { - "type": "string", - "enum": [ - "minimal", - "low", - "medium", - "high" - ], - "default": "medium", - "nullable": true, - "description": "Constrains effort on reasoning for \n[reasoning models](https://platform.openai.com/docs/guides/reasoning).\nCurrently supported values are `minimal`, `low`, `medium`, and `high`. Reducing\nreasoning effort can result in faster responses and fewer tokens used\non reasoning in a response.\n" - }, - "ReasoningItem": { - "type": "object", - "description": "A description of the chain of thought used by a reasoning model while generating\na response. Be sure to include these items in your `input` to the Responses API\nfor subsequent turns of a conversation if you are manually \n[managing context](https://platform.openai.com/docs/guides/conversation-state).\n", - "title": "Reasoning", - "properties": { - "type": { - "type": "string", - "description": "The type of the object. Always `reasoning`.\n", - "enum": [ - "reasoning" - ], - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique identifier of the reasoning content.\n" - }, - "encrypted_content": { - "type": "string", - "description": "The encrypted content of the reasoning item - populated when a response is\ngenerated with `reasoning.encrypted_content` in the `include` parameter.\n", - "nullable": true - }, - "summary": { - "type": "array", - "description": "Reasoning summary content.\n", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "description": "The type of the object. Always `summary_text`.\n", - "enum": [ - "summary_text" - ], - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "A summary of the reasoning output from the model so far.\n" - } - }, - "required": [ - "type", - "text" - ] - } - }, - "content": { - "type": "array", - "description": "Reasoning text content.\n", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "description": "The type of the object. Always `reasoning_text`.\n", - "enum": [ - "reasoning_text" - ], - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "Reasoning text output from the model.\n" - } - }, - "required": [ - "type", - "text" - ] - } - }, - "status": { - "type": "string", - "description": "The status of the item. One of `in_progress`, `completed`, or\n`incomplete`. Populated when items are returned via API.\n", - "enum": [ - "in_progress", - "completed", - "incomplete" - ] - } - }, - "required": [ - "id", - "summary", - "type" - ] - }, - "Response": { - "title": "The response object", - "allOf": [ - { - "$ref": "#/components/schemas/ModelResponseProperties" - }, - { - "$ref": "#/components/schemas/ResponseProperties" - }, - { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "Unique identifier for this Response.\n" - }, - "object": { - "type": "string", - "description": "The object type of this resource - always set to `response`.\n", - "enum": [ - "response" - ], - "x-stainless-const": true - }, - "status": { - "type": "string", - "description": "The status of the response generation. One of `completed`, `failed`,\n`in_progress`, `cancelled`, `queued`, or `incomplete`.\n", - "enum": [ - "completed", - "failed", - "in_progress", - "cancelled", - "queued", - "incomplete" - ] - }, - "created_at": { - "type": "number", - "description": "Unix timestamp (in seconds) of when this Response was created.\n" - }, - "error": { - "$ref": "#/components/schemas/ResponseError" - }, - "incomplete_details": { - "type": "object", - "nullable": true, - "description": "Details about why the response is incomplete.\n", - "properties": { - "reason": { - "type": "string", - "description": "The reason why the response is incomplete.", - "enum": [ - "max_output_tokens", - "content_filter" - ] - } - } - }, - "output": { - "type": "array", - "description": "An array of content items generated by the model.\n\n- The length and order of items in the `output` array is dependent\n on the model's response.\n- Rather than accessing the first item in the `output` array and\n assuming it's an `assistant` message with the content generated by\n the model, you might consider using the `output_text` property where\n supported in SDKs.\n", - "items": { - "$ref": "#/components/schemas/OutputItem" - } - }, - "instructions": { - "nullable": true, - "description": "A system (or developer) message inserted into the model's context.\n\nWhen using along with `previous_response_id`, the instructions from a previous\nresponse will not be carried over to the next response. This makes it simple\nto swap out system (or developer) messages in new responses.\n", - "anyOf": [ - { - "type": "string", - "description": "A text input to the model, equivalent to a text input with the\n`developer` role.\n" - }, - { - "type": "array", - "title": "Input item list", - "description": "A list of one or many input items to the model, containing\ndifferent content types.\n", - "items": { - "$ref": "#/components/schemas/InputItem" - } - } - ] - }, - "output_text": { - "type": "string", - "nullable": true, - "description": "SDK-only convenience property that contains the aggregated text output\nfrom all `output_text` items in the `output` array, if any are present.\nSupported in the Python and JavaScript SDKs.\n", - "x-oaiSupportedSDKs": [ - "python", - "javascript" - ], - "x-stainless-skip": true - }, - "usage": { - "$ref": "#/components/schemas/ResponseUsage" - }, - "parallel_tool_calls": { - "type": "boolean", - "description": "Whether to allow the model to run tool calls in parallel.\n", - "default": true - }, - "conversation": { - "nullable": true, - "$ref": "#/components/schemas/Conversation-2" - } - }, - "required": [ - "id", - "object", - "created_at", - "error", - "incomplete_details", - "instructions", - "model", - "tools", - "output", - "parallel_tool_calls", - "metadata", - "tool_choice", - "temperature", - "top_p" - ] - } - ] - }, - "ResponseAudioDeltaEvent": { - "type": "object", - "description": "Emitted when there is a partial audio response.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.audio.delta`.\n", - "enum": [ - "response.audio.delta" - ], - "x-stainless-const": true - }, - "sequence_number": { - "type": "integer", - "description": "A sequence number for this chunk of the stream response.\n" - }, - "delta": { - "type": "string", - "description": "A chunk of Base64 encoded response audio bytes.\n" - } - }, - "required": [ - "type", - "delta", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.audio.delta", - "group": "responses", - "example": "{\n \"type\": \"response.audio.delta\",\n \"response_id\": \"resp_123\",\n \"delta\": \"base64encoded...\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseAudioDoneEvent": { - "type": "object", - "description": "Emitted when the audio response is complete.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.audio.done`.\n", - "enum": [ - "response.audio.done" - ], - "x-stainless-const": true - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of the delta.\n" - } - }, - "required": [ - "type", - "sequence_number", - "response_id" - ], - "x-oaiMeta": { - "name": "response.audio.done", - "group": "responses", - "example": "{\n \"type\": \"response.audio.done\",\n \"response_id\": \"resp-123\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseAudioTranscriptDeltaEvent": { - "type": "object", - "description": "Emitted when there is a partial transcript of audio.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.audio.transcript.delta`.\n", - "enum": [ - "response.audio.transcript.delta" - ], - "x-stainless-const": true - }, - "delta": { - "type": "string", - "description": "The partial transcript of the audio response.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "response_id", - "delta", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.audio.transcript.delta", - "group": "responses", - "example": "{\n \"type\": \"response.audio.transcript.delta\",\n \"response_id\": \"resp_123\",\n \"delta\": \" ... partial transcript ... \",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseAudioTranscriptDoneEvent": { - "type": "object", - "description": "Emitted when the full audio transcript is completed.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.audio.transcript.done`.\n", - "enum": [ - "response.audio.transcript.done" - ], - "x-stainless-const": true - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "response_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.audio.transcript.done", - "group": "responses", - "example": "{\n \"type\": \"response.audio.transcript.done\",\n \"response_id\": \"resp_123\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseCodeInterpreterCallCodeDeltaEvent": { - "type": "object", - "description": "Emitted when a partial code snippet is streamed by the code interpreter.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.code_interpreter_call_code.delta`.", - "enum": [ - "response.code_interpreter_call_code.delta" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response for which the code is being streamed." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the code interpreter tool call item." - }, - "delta": { - "type": "string", - "description": "The partial code snippet being streamed by the code interpreter." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event, used to order streaming events." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "delta", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.code_interpreter_call_code.delta", - "group": "responses", - "example": "{\n \"type\": \"response.code_interpreter_call_code.delta\",\n \"output_index\": 0,\n \"item_id\": \"ci_12345\",\n \"delta\": \"print('Hello, world')\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseCodeInterpreterCallCodeDoneEvent": { - "type": "object", - "description": "Emitted when the code snippet is finalized by the code interpreter.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.code_interpreter_call_code.done`.", - "enum": [ - "response.code_interpreter_call_code.done" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response for which the code is finalized." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the code interpreter tool call item." - }, - "code": { - "type": "string", - "description": "The final code snippet output by the code interpreter." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event, used to order streaming events." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "code", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.code_interpreter_call_code.done", - "group": "responses", - "example": "{\n \"type\": \"response.code_interpreter_call_code.done\",\n \"output_index\": 3,\n \"item_id\": \"ci_12345\",\n \"code\": \"print('done')\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseCodeInterpreterCallCompletedEvent": { - "type": "object", - "description": "Emitted when the code interpreter call is completed.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.code_interpreter_call.completed`.", - "enum": [ - "response.code_interpreter_call.completed" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response for which the code interpreter call is completed." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the code interpreter tool call item." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event, used to order streaming events." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.code_interpreter_call.completed", - "group": "responses", - "example": "{\n \"type\": \"response.code_interpreter_call.completed\",\n \"output_index\": 5,\n \"item_id\": \"ci_12345\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseCodeInterpreterCallInProgressEvent": { - "type": "object", - "description": "Emitted when a code interpreter call is in progress.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.code_interpreter_call.in_progress`.", - "enum": [ - "response.code_interpreter_call.in_progress" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response for which the code interpreter call is in progress." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the code interpreter tool call item." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event, used to order streaming events." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.code_interpreter_call.in_progress", - "group": "responses", - "example": "{\n \"type\": \"response.code_interpreter_call.in_progress\",\n \"output_index\": 0,\n \"item_id\": \"ci_12345\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseCodeInterpreterCallInterpretingEvent": { - "type": "object", - "description": "Emitted when the code interpreter is actively interpreting the code snippet.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.code_interpreter_call.interpreting`.", - "enum": [ - "response.code_interpreter_call.interpreting" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response for which the code interpreter is interpreting code." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the code interpreter tool call item." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event, used to order streaming events." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.code_interpreter_call.interpreting", - "group": "responses", - "example": "{\n \"type\": \"response.code_interpreter_call.interpreting\",\n \"output_index\": 4,\n \"item_id\": \"ci_12345\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseCompletedEvent": { - "type": "object", - "description": "Emitted when the model response is complete.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.completed`.\n", - "enum": [ - "response.completed" - ], - "x-stainless-const": true - }, - "response": { - "$ref": "#/components/schemas/Response", - "description": "Properties of the completed response.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number for this event." - } - }, - "required": [ - "type", - "response", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.completed", - "group": "responses", - "example": "{\n \"type\": \"response.completed\",\n \"response\": {\n \"id\": \"resp_123\",\n \"object\": \"response\",\n \"created_at\": 1740855869,\n \"status\": \"completed\",\n \"error\": null,\n \"incomplete_details\": null,\n \"input\": [],\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"output\": [\n {\n \"id\": \"msg_123\",\n \"type\": \"message\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.\",\n \"annotations\": []\n }\n ]\n }\n ],\n \"previous_response_id\": null,\n \"reasoning_effort\": null,\n \"store\": false,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": {\n \"input_tokens\": 0,\n \"output_tokens\": 0,\n \"output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"total_tokens\": 0\n },\n \"user\": null,\n \"metadata\": {}\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseContentPartAddedEvent": { - "type": "object", - "description": "Emitted when a new content part is added.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.content_part.added`.\n", - "enum": [ - "response.content_part.added" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the content part was added to.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the content part was added to.\n" - }, - "content_index": { - "type": "integer", - "description": "The index of the content part that was added.\n" - }, - "part": { - "$ref": "#/components/schemas/OutputContent", - "description": "The content part that was added.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "item_id", - "output_index", - "content_index", - "part", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.content_part.added", - "group": "responses", - "example": "{\n \"type\": \"response.content_part.added\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"part\": {\n \"type\": \"output_text\",\n \"text\": \"\",\n \"annotations\": []\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseContentPartDoneEvent": { - "type": "object", - "description": "Emitted when a content part is done.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.content_part.done`.\n", - "enum": [ - "response.content_part.done" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the content part was added to.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the content part was added to.\n" - }, - "content_index": { - "type": "integer", - "description": "The index of the content part that is done.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - }, - "part": { - "$ref": "#/components/schemas/OutputContent", - "description": "The content part that is done.\n" - } - }, - "required": [ - "type", - "item_id", - "output_index", - "content_index", - "part", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.content_part.done", - "group": "responses", - "example": "{\n \"type\": \"response.content_part.done\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"sequence_number\": 1,\n \"part\": {\n \"type\": \"output_text\",\n \"text\": \"In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.\",\n \"annotations\": []\n }\n}\n" - } - }, - "ResponseCreatedEvent": { - "type": "object", - "description": "An event that is emitted when a response is created.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.created`.\n", - "enum": [ - "response.created" - ], - "x-stainless-const": true - }, - "response": { - "$ref": "#/components/schemas/Response", - "description": "The response that was created.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number for this event." - } - }, - "required": [ - "type", - "response", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.created", - "group": "responses", - "example": "{\n \"type\": \"response.created\",\n \"response\": {\n \"id\": \"resp_67ccfcdd16748190a91872c75d38539e09e4d4aac714747c\",\n \"object\": \"response\",\n \"created_at\": 1741487325,\n \"status\": \"in_progress\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-2024-08-06\",\n \"output\": [],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": null,\n \"user\": null,\n \"metadata\": {}\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseCustomToolCallInputDeltaEvent": { - "title": "ResponseCustomToolCallInputDelta", - "type": "object", - "description": "Event representing a delta (partial update) to the input of a custom tool call.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.custom_tool_call_input.delta" - ], - "description": "The event type identifier.", - "x-stainless-const": true - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - }, - "output_index": { - "type": "integer", - "description": "The index of the output this delta applies to." - }, - "item_id": { - "type": "string", - "description": "Unique identifier for the API item associated with this event." - }, - "delta": { - "type": "string", - "description": "The incremental input data (delta) for the custom tool call." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "delta", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.custom_tool_call_input.delta", - "group": "responses", - "example": "{\n \"type\": \"response.custom_tool_call_input.delta\",\n \"output_index\": 0,\n \"item_id\": \"ctc_1234567890abcdef\",\n \"delta\": \"partial input text\"\n}\n" - } - }, - "ResponseCustomToolCallInputDoneEvent": { - "title": "ResponseCustomToolCallInputDone", - "type": "object", - "description": "Event indicating that input for a custom tool call is complete.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.custom_tool_call_input.done" - ], - "description": "The event type identifier.", - "x-stainless-const": true - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - }, - "output_index": { - "type": "integer", - "description": "The index of the output this event applies to." - }, - "item_id": { - "type": "string", - "description": "Unique identifier for the API item associated with this event." - }, - "input": { - "type": "string", - "description": "The complete input data for the custom tool call." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "input", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.custom_tool_call_input.done", - "group": "responses", - "example": "{\n \"type\": \"response.custom_tool_call_input.done\",\n \"output_index\": 0,\n \"item_id\": \"ctc_1234567890abcdef\",\n \"input\": \"final complete input text\"\n}\n" - } - }, - "ResponseError": { - "type": "object", - "description": "An error object returned when the model fails to generate a Response.\n", - "nullable": true, - "properties": { - "code": { - "$ref": "#/components/schemas/ResponseErrorCode" - }, - "message": { - "type": "string", - "description": "A human-readable description of the error.\n" - } - }, - "required": [ - "code", - "message" - ] - }, - "ResponseErrorCode": { - "type": "string", - "description": "The error code for the response.\n", - "enum": [ - "server_error", - "rate_limit_exceeded", - "invalid_prompt", - "vector_store_timeout", - "invalid_image", - "invalid_image_format", - "invalid_base64_image", - "invalid_image_url", - "image_too_large", - "image_too_small", - "image_parse_error", - "image_content_policy_violation", - "invalid_image_mode", - "image_file_too_large", - "unsupported_image_media_type", - "empty_image_file", - "failed_to_download_image", - "image_file_not_found" - ] - }, - "ResponseErrorEvent": { - "type": "object", - "description": "Emitted when an error occurs.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `error`.\n", - "enum": [ - "error" - ], - "x-stainless-const": true - }, - "code": { - "type": "string", - "description": "The error code.\n", - "nullable": true - }, - "message": { - "type": "string", - "description": "The error message.\n" - }, - "param": { - "type": "string", - "description": "The error parameter.\n", - "nullable": true - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "code", - "message", - "param", - "sequence_number" - ], - "x-oaiMeta": { - "name": "error", - "group": "responses", - "example": "{\n \"type\": \"error\",\n \"code\": \"ERR_SOMETHING\",\n \"message\": \"Something went wrong\",\n \"param\": null,\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseFailedEvent": { - "type": "object", - "description": "An event that is emitted when a response fails.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.failed`.\n", - "enum": [ - "response.failed" - ], - "x-stainless-const": true - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - }, - "response": { - "$ref": "#/components/schemas/Response", - "description": "The response that failed.\n" - } - }, - "required": [ - "type", - "response", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.failed", - "group": "responses", - "example": "{\n \"type\": \"response.failed\",\n \"response\": {\n \"id\": \"resp_123\",\n \"object\": \"response\",\n \"created_at\": 1740855869,\n \"status\": \"failed\",\n \"error\": {\n \"code\": \"server_error\",\n \"message\": \"The model failed to generate a response.\"\n },\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"output\": [],\n \"previous_response_id\": null,\n \"reasoning_effort\": null,\n \"store\": false,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": null,\n \"user\": null,\n \"metadata\": {}\n }\n}\n" - } - }, - "ResponseFileSearchCallCompletedEvent": { - "type": "object", - "description": "Emitted when a file search call is completed (results found).", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.file_search_call.completed`.\n", - "enum": [ - "response.file_search_call.completed" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the file search call is initiated.\n" - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the file search call is initiated.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.file_search_call.completed", - "group": "responses", - "example": "{\n \"type\": \"response.file_search_call.completed\",\n \"output_index\": 0,\n \"item_id\": \"fs_123\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseFileSearchCallInProgressEvent": { - "type": "object", - "description": "Emitted when a file search call is initiated.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.file_search_call.in_progress`.\n", - "enum": [ - "response.file_search_call.in_progress" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the file search call is initiated.\n" - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the file search call is initiated.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.file_search_call.in_progress", - "group": "responses", - "example": "{\n \"type\": \"response.file_search_call.in_progress\",\n \"output_index\": 0,\n \"item_id\": \"fs_123\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseFileSearchCallSearchingEvent": { - "type": "object", - "description": "Emitted when a file search is currently searching.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.file_search_call.searching`.\n", - "enum": [ - "response.file_search_call.searching" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the file search call is searching.\n" - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the file search call is initiated.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.file_search_call.searching", - "group": "responses", - "example": "{\n \"type\": \"response.file_search_call.searching\",\n \"output_index\": 0,\n \"item_id\": \"fs_123\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseFormatJsonObject": { - "type": "object", - "title": "JSON object", - "description": "JSON object response format. An older method of generating JSON responses.\nUsing `json_schema` is recommended for models that support it. Note that the\nmodel will not generate JSON without a system or user message instructing it\nto do so.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of response format being defined. Always `json_object`.", - "enum": [ - "json_object" - ], - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "ResponseFormatJsonSchema": { - "type": "object", - "title": "JSON schema", - "description": "JSON Schema response format. Used to generate structured JSON responses.\nLearn more about [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs).\n", - "properties": { - "type": { - "type": "string", - "description": "The type of response format being defined. Always `json_schema`.", - "enum": [ - "json_schema" - ], - "x-stainless-const": true - }, - "json_schema": { - "type": "object", - "title": "JSON schema", - "description": "Structured Outputs configuration options, including a JSON Schema.\n", - "properties": { - "description": { - "type": "string", - "description": "A description of what the response format is for, used by the model to\ndetermine how to respond in the format.\n" - }, - "name": { - "type": "string", - "description": "The name of the response format. Must be a-z, A-Z, 0-9, or contain\nunderscores and dashes, with a maximum length of 64.\n" - }, - "schema": { - "$ref": "#/components/schemas/ResponseFormatJsonSchemaSchema" - }, - "strict": { - "type": "boolean", - "nullable": true, - "default": false, - "description": "Whether to enable strict schema adherence when generating the output.\nIf set to true, the model will always follow the exact schema defined\nin the `schema` field. Only a subset of JSON Schema is supported when\n`strict` is `true`. To learn more, read the [Structured Outputs\nguide](https://platform.openai.com/docs/guides/structured-outputs).\n" - } - }, - "required": [ - "name" - ] - } - }, - "required": [ - "type", - "json_schema" - ] - }, - "ResponseFormatJsonSchemaSchema": { - "type": "object", - "title": "JSON schema", - "description": "The schema for the response format, described as a JSON Schema object.\nLearn how to build JSON schemas [here](https://json-schema.org/).\n", - "additionalProperties": true - }, - "ResponseFormatText": { - "type": "object", - "title": "Text", - "description": "Default response format. Used to generate text responses.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of response format being defined. Always `text`.", - "enum": [ - "text" - ], - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "ResponseFormatTextGrammar": { - "type": "object", - "title": "Text grammar", - "description": "A custom grammar for the model to follow when generating text.\nLearn more in the [custom grammars guide](https://platform.openai.com/docs/guides/custom-grammars).\n", - "properties": { - "type": { - "type": "string", - "description": "The type of response format being defined. Always `grammar`.", - "enum": [ - "grammar" - ], - "x-stainless-const": true - }, - "grammar": { - "type": "string", - "description": "The custom grammar for the model to follow." - } - }, - "required": [ - "type", - "grammar" - ] - }, - "ResponseFormatTextPython": { - "type": "object", - "title": "Python grammar", - "description": "Configure the model to generate valid Python code. See the\n[custom grammars guide](https://platform.openai.com/docs/guides/custom-grammars) for more details.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of response format being defined. Always `python`.", - "enum": [ - "python" - ], - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "ResponseFunctionCallArgumentsDeltaEvent": { - "type": "object", - "description": "Emitted when there is a partial function-call arguments delta.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.function_call_arguments.delta`.\n", - "enum": [ - "response.function_call_arguments.delta" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the function-call arguments delta is added to.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the function-call arguments delta is added to.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - }, - "delta": { - "type": "string", - "description": "The function-call arguments delta that is added.\n" - } - }, - "required": [ - "type", - "item_id", - "output_index", - "delta", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.function_call_arguments.delta", - "group": "responses", - "example": "{\n \"type\": \"response.function_call_arguments.delta\",\n \"item_id\": \"item-abc\",\n \"output_index\": 0,\n \"delta\": \"{ \\\"arg\\\":\"\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseFunctionCallArgumentsDoneEvent": { - "type": "object", - "description": "Emitted when function-call arguments are finalized.", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.function_call_arguments.done" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the item." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - }, - "arguments": { - "type": "string", - "description": "The function-call arguments." - } - }, - "required": [ - "type", - "item_id", - "output_index", - "arguments", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.function_call_arguments.done", - "group": "responses", - "example": "{\n \"type\": \"response.function_call_arguments.done\",\n \"item_id\": \"item-abc\",\n \"output_index\": 1,\n \"arguments\": \"{ \\\"arg\\\": 123 }\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseImageGenCallCompletedEvent": { - "type": "object", - "title": "ResponseImageGenCallCompletedEvent", - "description": "Emitted when an image generation tool call has completed and the final image is available.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.image_generation_call.completed" - ], - "description": "The type of the event. Always 'response.image_generation_call.completed'.", - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response's output array." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the image generation item being processed." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.image_generation_call.completed", - "group": "responses", - "example": "{\n \"type\": \"response.image_generation_call.completed\",\n \"output_index\": 0,\n \"item_id\": \"item-123\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseImageGenCallGeneratingEvent": { - "type": "object", - "title": "ResponseImageGenCallGeneratingEvent", - "description": "Emitted when an image generation tool call is actively generating an image (intermediate state).\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.image_generation_call.generating" - ], - "description": "The type of the event. Always 'response.image_generation_call.generating'.", - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response's output array." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the image generation item being processed." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of the image generation item being processed." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.image_generation_call.generating", - "group": "responses", - "example": "{\n \"type\": \"response.image_generation_call.generating\",\n \"output_index\": 0,\n \"item_id\": \"item-123\",\n \"sequence_number\": 0\n}\n" - } - }, - "ResponseImageGenCallInProgressEvent": { - "type": "object", - "title": "ResponseImageGenCallInProgressEvent", - "description": "Emitted when an image generation tool call is in progress.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.image_generation_call.in_progress" - ], - "description": "The type of the event. Always 'response.image_generation_call.in_progress'.", - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response's output array." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the image generation item being processed." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of the image generation item being processed." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.image_generation_call.in_progress", - "group": "responses", - "example": "{\n \"type\": \"response.image_generation_call.in_progress\",\n \"output_index\": 0,\n \"item_id\": \"item-123\",\n \"sequence_number\": 0\n}\n" - } - }, - "ResponseImageGenCallPartialImageEvent": { - "type": "object", - "title": "ResponseImageGenCallPartialImageEvent", - "description": "Emitted when a partial image is available during image generation streaming.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.image_generation_call.partial_image" - ], - "description": "The type of the event. Always 'response.image_generation_call.partial_image'.", - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response's output array." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the image generation item being processed." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of the image generation item being processed." - }, - "partial_image_index": { - "type": "integer", - "description": "0-based index for the partial image (backend is 1-based, but this is 0-based for the user)." - }, - "partial_image_b64": { - "type": "string", - "description": "Base64-encoded partial image data, suitable for rendering as an image." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number", - "partial_image_index", - "partial_image_b64" - ], - "x-oaiMeta": { - "name": "response.image_generation_call.partial_image", - "group": "responses", - "example": "{\n \"type\": \"response.image_generation_call.partial_image\",\n \"output_index\": 0,\n \"item_id\": \"item-123\",\n \"sequence_number\": 0,\n \"partial_image_index\": 0,\n \"partial_image_b64\": \"...\"\n}\n" - } - }, - "ResponseInProgressEvent": { - "type": "object", - "description": "Emitted when the response is in progress.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.in_progress`.\n", - "enum": [ - "response.in_progress" - ], - "x-stainless-const": true - }, - "response": { - "$ref": "#/components/schemas/Response", - "description": "The response that is in progress.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "response", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.in_progress", - "group": "responses", - "example": "{\n \"type\": \"response.in_progress\",\n \"response\": {\n \"id\": \"resp_67ccfcdd16748190a91872c75d38539e09e4d4aac714747c\",\n \"object\": \"response\",\n \"created_at\": 1741487325,\n \"status\": \"in_progress\",\n \"error\": null,\n \"incomplete_details\": null,\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-2024-08-06\",\n \"output\": [],\n \"parallel_tool_calls\": true,\n \"previous_response_id\": null,\n \"reasoning\": {\n \"effort\": null,\n \"summary\": null\n },\n \"store\": true,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": null,\n \"user\": null,\n \"metadata\": {}\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseIncompleteEvent": { - "type": "object", - "description": "An event that is emitted when a response finishes as incomplete.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.incomplete`.\n", - "enum": [ - "response.incomplete" - ], - "x-stainless-const": true - }, - "response": { - "$ref": "#/components/schemas/Response", - "description": "The response that was incomplete.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "response", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.incomplete", - "group": "responses", - "example": "{\n \"type\": \"response.incomplete\",\n \"response\": {\n \"id\": \"resp_123\",\n \"object\": \"response\",\n \"created_at\": 1740855869,\n \"status\": \"incomplete\",\n \"error\": null, \n \"incomplete_details\": {\n \"reason\": \"max_tokens\"\n },\n \"instructions\": null,\n \"max_output_tokens\": null,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"output\": [],\n \"previous_response_id\": null,\n \"reasoning_effort\": null,\n \"store\": false,\n \"temperature\": 1,\n \"text\": {\n \"format\": {\n \"type\": \"text\"\n }\n },\n \"tool_choice\": \"auto\",\n \"tools\": [],\n \"top_p\": 1,\n \"truncation\": \"disabled\",\n \"usage\": null,\n \"user\": null,\n \"metadata\": {}\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseItemList": { - "type": "object", - "description": "A list of Response items.", - "properties": { - "object": { - "description": "The type of object returned, must be `list`.", - "x-stainless-const": true, - "const": "list" - }, - "data": { - "type": "array", - "description": "A list of items used to generate this response.", - "items": { - "$ref": "#/components/schemas/ItemResource" - } - }, - "has_more": { - "type": "boolean", - "description": "Whether there are more items available." - }, - "first_id": { - "type": "string", - "description": "The ID of the first item in the list." - }, - "last_id": { - "type": "string", - "description": "The ID of the last item in the list." - } - }, - "required": [ - "object", - "data", - "has_more", - "first_id", - "last_id" - ], - "x-oaiMeta": { - "name": "The input item list", - "group": "responses", - "example": "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"msg_abc123\",\n \"type\": \"message\",\n \"role\": \"user\",\n \"content\": [\n {\n \"type\": \"input_text\",\n \"text\": \"Tell me a three sentence bedtime story about a unicorn.\"\n }\n ]\n }\n ],\n \"first_id\": \"msg_abc123\",\n \"last_id\": \"msg_abc123\",\n \"has_more\": false\n}\n" - } - }, - "ResponseLogProb": { - "type": "object", - "description": "A logprob is the logarithmic probability that the model assigns to producing \na particular token at a given position in the sequence. Less-negative (higher) \nlogprob values indicate greater model confidence in that token choice.\n", - "properties": { - "token": { - "description": "A possible text token.", - "type": "string" - }, - "logprob": { - "description": "The log probability of this token.\n", - "type": "number" - }, - "top_logprobs": { - "description": "The log probability of the top 20 most likely tokens.\n", - "type": "array", - "items": { - "type": "object", - "properties": { - "token": { - "description": "A possible text token.", - "type": "string" - }, - "logprob": { - "description": "The log probability of this token.", - "type": "number" - } - } - } - } - }, - "required": [ - "token", - "logprob" - ] - }, - "ResponseMCPCallArgumentsDeltaEvent": { - "type": "object", - "title": "ResponseMCPCallArgumentsDeltaEvent", - "description": "Emitted when there is a delta (partial update) to the arguments of an MCP tool call.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.mcp_call_arguments.delta" - ], - "description": "The type of the event. Always 'response.mcp_call_arguments.delta'.", - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response's output array." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the MCP tool call item being processed." - }, - "delta": { - "type": "string", - "description": "A JSON string containing the partial update to the arguments for the MCP tool call.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "delta", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.mcp_call_arguments.delta", - "group": "responses", - "example": "{\n \"type\": \"response.mcp_call_arguments.delta\",\n \"output_index\": 0,\n \"item_id\": \"item-abc\",\n \"delta\": \"{\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseMCPCallArgumentsDoneEvent": { - "type": "object", - "title": "ResponseMCPCallArgumentsDoneEvent", - "description": "Emitted when the arguments for an MCP tool call are finalized.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.mcp_call_arguments.done" - ], - "description": "The type of the event. Always 'response.mcp_call_arguments.done'.", - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response's output array." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the MCP tool call item being processed." - }, - "arguments": { - "type": "string", - "description": "A JSON string containing the finalized arguments for the MCP tool call.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "arguments", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.mcp_call_arguments.done", - "group": "responses", - "example": "{\n \"type\": \"response.mcp_call_arguments.done\",\n \"output_index\": 0,\n \"item_id\": \"item-abc\",\n \"arguments\": \"{\\\"arg1\\\": \\\"value1\\\", \\\"arg2\\\": \\\"value2\\\"}\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseMCPCallCompletedEvent": { - "type": "object", - "title": "ResponseMCPCallCompletedEvent", - "description": "Emitted when an MCP tool call has completed successfully.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.mcp_call.completed" - ], - "description": "The type of the event. Always 'response.mcp_call.completed'.", - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item that completed." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that completed." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "item_id", - "output_index", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.mcp_call.completed", - "group": "responses", - "example": "{\n \"type\": \"response.mcp_call.completed\",\n \"sequence_number\": 1,\n \"item_id\": \"mcp_682d437d90a88191bf88cd03aae0c3e503937d5f622d7a90\",\n \"output_index\": 0\n}\n" - } - }, - "ResponseMCPCallFailedEvent": { - "type": "object", - "title": "ResponseMCPCallFailedEvent", - "description": "Emitted when an MCP tool call has failed.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.mcp_call.failed" - ], - "description": "The type of the event. Always 'response.mcp_call.failed'.", - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item that failed." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that failed." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "item_id", - "output_index", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.mcp_call.failed", - "group": "responses", - "example": "{\n \"type\": \"response.mcp_call.failed\",\n \"sequence_number\": 1,\n \"item_id\": \"mcp_682d437d90a88191bf88cd03aae0c3e503937d5f622d7a90\",\n \"output_index\": 0\n}\n" - } - }, - "ResponseMCPCallInProgressEvent": { - "type": "object", - "title": "ResponseMCPCallInProgressEvent", - "description": "Emitted when an MCP tool call is in progress.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.mcp_call.in_progress" - ], - "description": "The type of the event. Always 'response.mcp_call.in_progress'.", - "x-stainless-const": true - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response's output array." - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the MCP tool call item being processed." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.mcp_call.in_progress", - "group": "responses", - "example": "{\n \"type\": \"response.mcp_call.in_progress\",\n \"sequence_number\": 1,\n \"output_index\": 0,\n \"item_id\": \"mcp_682d437d90a88191bf88cd03aae0c3e503937d5f622d7a90\"\n}\n" - } - }, - "ResponseMCPListToolsCompletedEvent": { - "type": "object", - "title": "ResponseMCPListToolsCompletedEvent", - "description": "Emitted when the list of available MCP tools has been successfully retrieved.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.mcp_list_tools.completed" - ], - "description": "The type of the event. Always 'response.mcp_list_tools.completed'.", - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item that produced this output." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that was processed." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "item_id", - "output_index", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.mcp_list_tools.completed", - "group": "responses", - "example": "{\n \"type\": \"response.mcp_list_tools.completed\",\n \"sequence_number\": 1,\n \"output_index\": 0,\n \"item_id\": \"mcpl_682d4379df088191886b70f4ec39f90403937d5f622d7a90\"\n}\n" - } - }, - "ResponseMCPListToolsFailedEvent": { - "type": "object", - "title": "ResponseMCPListToolsFailedEvent", - "description": "Emitted when the attempt to list available MCP tools has failed.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.mcp_list_tools.failed" - ], - "description": "The type of the event. Always 'response.mcp_list_tools.failed'.", - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item that failed." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that failed." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "item_id", - "output_index", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.mcp_list_tools.failed", - "group": "responses", - "example": "{\n \"type\": \"response.mcp_list_tools.failed\",\n \"sequence_number\": 1,\n \"output_index\": 0,\n \"item_id\": \"mcpl_682d4379df088191886b70f4ec39f90403937d5f622d7a90\"\n}\n" - } - }, - "ResponseMCPListToolsInProgressEvent": { - "type": "object", - "title": "ResponseMCPListToolsInProgressEvent", - "description": "Emitted when the system is in the process of retrieving the list of available MCP tools.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.mcp_list_tools.in_progress" - ], - "description": "The type of the event. Always 'response.mcp_list_tools.in_progress'.", - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the MCP tool call item that is being processed." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that is being processed." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - } - }, - "required": [ - "type", - "item_id", - "output_index", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.mcp_list_tools.in_progress", - "group": "responses", - "example": "{\n \"type\": \"response.mcp_list_tools.in_progress\",\n \"sequence_number\": 1,\n \"output_index\": 0,\n \"item_id\": \"mcpl_682d4379df088191886b70f4ec39f90403937d5f622d7a90\"\n}\n" - } - }, - "ResponseModalities": { - "type": "array", - "nullable": true, - "description": "Output types that you would like the model to generate.\nMost models are capable of generating text, which is the default:\n\n`[\"text\"]`\n\nThe `gpt-4o-audio-preview` model can also be used to \n[generate audio](https://platform.openai.com/docs/guides/audio). To request that this model generate \nboth text and audio responses, you can use:\n\n`[\"text\", \"audio\"]`\n", - "items": { - "type": "string", - "enum": [ - "text", - "audio" - ] - } - }, - "ResponseOutputItemAddedEvent": { - "type": "object", - "description": "Emitted when a new output item is added.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.output_item.added`.\n", - "enum": [ - "response.output_item.added" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that was added.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - }, - "item": { - "$ref": "#/components/schemas/OutputItem", - "description": "The output item that was added.\n" - } - }, - "required": [ - "type", - "output_index", - "item", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.output_item.added", - "group": "responses", - "example": "{\n \"type\": \"response.output_item.added\",\n \"output_index\": 0,\n \"item\": {\n \"id\": \"msg_123\",\n \"status\": \"in_progress\",\n \"type\": \"message\",\n \"role\": \"assistant\",\n \"content\": []\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseOutputItemDoneEvent": { - "type": "object", - "description": "Emitted when an output item is marked done.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.output_item.done`.\n", - "enum": [ - "response.output_item.done" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that was marked done.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - }, - "item": { - "$ref": "#/components/schemas/OutputItem", - "description": "The output item that was marked done.\n" - } - }, - "required": [ - "type", - "output_index", - "item", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.output_item.done", - "group": "responses", - "example": "{\n \"type\": \"response.output_item.done\",\n \"output_index\": 0,\n \"item\": {\n \"id\": \"msg_123\",\n \"status\": \"completed\",\n \"type\": \"message\",\n \"role\": \"assistant\",\n \"content\": [\n {\n \"type\": \"output_text\",\n \"text\": \"In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.\",\n \"annotations\": []\n }\n ]\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseOutputTextAnnotationAddedEvent": { - "type": "object", - "title": "ResponseOutputTextAnnotationAddedEvent", - "description": "Emitted when an annotation is added to output text content.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.output_text.annotation.added" - ], - "description": "The type of the event. Always 'response.output_text.annotation.added'.", - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The unique identifier of the item to which the annotation is being added." - }, - "output_index": { - "type": "integer", - "description": "The index of the output item in the response's output array." - }, - "content_index": { - "type": "integer", - "description": "The index of the content part within the output item." - }, - "annotation_index": { - "type": "integer", - "description": "The index of the annotation within the content part." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event." - }, - "annotation": { - "type": "object", - "description": "The annotation object being added. (See annotation schema for details.)" - } - }, - "required": [ - "type", - "item_id", - "output_index", - "content_index", - "annotation_index", - "annotation", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.output_text.annotation.added", - "group": "responses", - "example": "{\n \"type\": \"response.output_text.annotation.added\",\n \"item_id\": \"item-abc\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"annotation_index\": 0,\n \"annotation\": {\n \"type\": \"text_annotation\",\n \"text\": \"This is a test annotation\",\n \"start\": 0,\n \"end\": 10\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponsePromptVariables": { - "type": "object", - "title": "Prompt Variables", - "description": "Optional map of values to substitute in for variables in your\nprompt. The substitution values can either be strings, or other\nResponse input types like images or files.\n", - "x-oaiExpandable": true, - "x-oaiTypeLabel": "map", - "nullable": true, - "additionalProperties": { - "x-oaiExpandable": true, - "x-oaiTypeLabel": "map", - "anyOf": [ - { - "type": "string" - }, - { - "$ref": "#/components/schemas/InputTextContent" - }, - { - "$ref": "#/components/schemas/InputImageContent" - }, - { - "$ref": "#/components/schemas/InputFileContent" - } - ] - } - }, - "ResponseProperties": { - "type": "object", - "properties": { - "previous_response_id": { - "type": "string", - "description": "The unique ID of the previous response to the model. Use this to\ncreate multi-turn conversations. Learn more about\n[conversation state](https://platform.openai.com/docs/guides/conversation-state). Cannot be used in conjunction with `conversation`.\n", - "nullable": true - }, - "model": { - "description": "Model ID used to generate the response, like `gpt-4o` or `o3`. OpenAI\noffers a wide range of models with different capabilities, performance\ncharacteristics, and price points. Refer to the [model guide](https://platform.openai.com/docs/models)\nto browse and compare available models.\n", - "$ref": "#/components/schemas/ModelIdsResponses" - }, - "reasoning": { - "$ref": "#/components/schemas/Reasoning", - "nullable": true - }, - "background": { - "type": "boolean", - "description": "Whether to run the model response in the background.\n[Learn more](https://platform.openai.com/docs/guides/background).\n", - "default": false, - "nullable": true - }, - "max_output_tokens": { - "description": "An upper bound for the number of tokens that can be generated for a response, including visible output tokens and [reasoning tokens](https://platform.openai.com/docs/guides/reasoning).\n", - "type": "integer", - "nullable": true - }, - "max_tool_calls": { - "description": "The maximum number of total calls to built-in tools that can be processed in a response. This maximum number applies across all built-in tool calls, not per individual tool. Any further attempts to call a tool by the model will be ignored.\n", - "type": "integer", - "nullable": true - }, - "text": { - "type": "object", - "description": "Configuration options for a text response from the model. Can be plain\ntext or structured JSON data. Learn more:\n- [Text inputs and outputs](https://platform.openai.com/docs/guides/text)\n- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs)\n", - "properties": { - "format": { - "$ref": "#/components/schemas/TextResponseFormatConfiguration" - }, - "verbosity": { - "$ref": "#/components/schemas/Verbosity" - } - } - }, - "tools": { - "type": "array", - "description": "An array of tools the model may call while generating a response. You\ncan specify which tool to use by setting the `tool_choice` parameter.\n\nWe support the following categories of tools:\n- **Built-in tools**: Tools that are provided by OpenAI that extend the\n model's capabilities, like [web search](https://platform.openai.com/docs/guides/tools-web-search)\n or [file search](https://platform.openai.com/docs/guides/tools-file-search). Learn more about\n [built-in tools](https://platform.openai.com/docs/guides/tools).\n- **MCP Tools**: Integrations with third-party systems via custom MCP servers\n or predefined connectors such as Google Drive and SharePoint. Learn more about\n [MCP Tools](https://platform.openai.com/docs/guides/tools-connectors-mcp).\n- **Function calls (custom tools)**: Functions that are defined by you,\n enabling the model to call your own code with strongly typed arguments\n and outputs. Learn more about\n [function calling](https://platform.openai.com/docs/guides/function-calling). You can also use\n custom tools to call your own code.\n", - "items": { - "$ref": "#/components/schemas/Tool" - } - }, - "tool_choice": { - "description": "How the model should select which tool (or tools) to use when generating\na response. See the `tools` parameter to see how to specify which tools\nthe model can call.\n", - "anyOf": [ - { - "$ref": "#/components/schemas/ToolChoiceOptions" - }, - { - "$ref": "#/components/schemas/ToolChoiceAllowed" - }, - { - "$ref": "#/components/schemas/ToolChoiceTypes" - }, - { - "$ref": "#/components/schemas/ToolChoiceFunction" - }, - { - "$ref": "#/components/schemas/ToolChoiceMCP" - }, - { - "$ref": "#/components/schemas/ToolChoiceCustom" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "prompt": { - "$ref": "#/components/schemas/Prompt" - }, - "truncation": { - "type": "string", - "description": "The truncation strategy to use for the model response.\n- `auto`: If the context of this response and previous ones exceeds\n the model's context window size, the model will truncate the\n response to fit the context window by dropping input items in the\n middle of the conversation.\n- `disabled` (default): If a model response will exceed the context window\n size for a model, the request will fail with a 400 error.\n", - "enum": [ - "auto", - "disabled" - ], - "nullable": true, - "default": "disabled" - } - } - }, - "ResponseQueuedEvent": { - "type": "object", - "title": "ResponseQueuedEvent", - "description": "Emitted when a response is queued and waiting to be processed.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "response.queued" - ], - "description": "The type of the event. Always 'response.queued'.", - "x-stainless-const": true - }, - "response": { - "$ref": "#/components/schemas/Response", - "description": "The full response object that is queued." - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number for this event." - } - }, - "required": [ - "type", - "response", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.queued", - "group": "responses", - "example": "{\n \"type\": \"response.queued\",\n \"response\": {\n \"id\": \"res_123\",\n \"status\": \"queued\",\n \"created_at\": \"2021-01-01T00:00:00Z\",\n \"updated_at\": \"2021-01-01T00:00:00Z\"\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseReasoningSummaryPartAddedEvent": { - "type": "object", - "description": "Emitted when a new reasoning summary part is added.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.reasoning_summary_part.added`.\n", - "enum": [ - "response.reasoning_summary_part.added" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the item this summary part is associated with.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item this summary part is associated with.\n" - }, - "summary_index": { - "type": "integer", - "description": "The index of the summary part within the reasoning summary.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - }, - "part": { - "type": "object", - "description": "The summary part that was added.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the summary part. Always `summary_text`.", - "enum": [ - "summary_text" - ], - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text of the summary part." - } - }, - "required": [ - "type", - "text" - ] - } - }, - "required": [ - "type", - "item_id", - "output_index", - "summary_index", - "part", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.reasoning_summary_part.added", - "group": "responses", - "example": "{\n \"type\": \"response.reasoning_summary_part.added\",\n \"item_id\": \"rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476\",\n \"output_index\": 0,\n \"summary_index\": 0,\n \"part\": {\n \"type\": \"summary_text\",\n \"text\": \"\"\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseReasoningSummaryPartDoneEvent": { - "type": "object", - "description": "Emitted when a reasoning summary part is completed.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.reasoning_summary_part.done`.\n", - "enum": [ - "response.reasoning_summary_part.done" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the item this summary part is associated with.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item this summary part is associated with.\n" - }, - "summary_index": { - "type": "integer", - "description": "The index of the summary part within the reasoning summary.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - }, - "part": { - "type": "object", - "description": "The completed summary part.\n", - "properties": { - "type": { - "type": "string", - "description": "The type of the summary part. Always `summary_text`.", - "enum": [ - "summary_text" - ], - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text of the summary part." - } - }, - "required": [ - "type", - "text" - ] - } - }, - "required": [ - "type", - "item_id", - "output_index", - "summary_index", - "part", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.reasoning_summary_part.done", - "group": "responses", - "example": "{\n \"type\": \"response.reasoning_summary_part.done\",\n \"item_id\": \"rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476\",\n \"output_index\": 0,\n \"summary_index\": 0,\n \"part\": {\n \"type\": \"summary_text\",\n \"text\": \"**Responding to a greeting**\\n\\nThe user just said, \\\"Hello!\\\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \\\"Hello! How can I assist you today?\\\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!\"\n },\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseReasoningSummaryTextDeltaEvent": { - "type": "object", - "description": "Emitted when a delta is added to a reasoning summary text.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.reasoning_summary_text.delta`.\n", - "enum": [ - "response.reasoning_summary_text.delta" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the item this summary text delta is associated with.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item this summary text delta is associated with.\n" - }, - "summary_index": { - "type": "integer", - "description": "The index of the summary part within the reasoning summary.\n" - }, - "delta": { - "type": "string", - "description": "The text delta that was added to the summary.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - } - }, - "required": [ - "type", - "item_id", - "output_index", - "summary_index", - "delta", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.reasoning_summary_text.delta", - "group": "responses", - "example": "{\n \"type\": \"response.reasoning_summary_text.delta\",\n \"item_id\": \"rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476\",\n \"output_index\": 0,\n \"summary_index\": 0,\n \"delta\": \"**Responding to a greeting**\\n\\nThe user just said, \\\"Hello!\\\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \\\"Hello! How can I assist you today?\\\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseReasoningSummaryTextDoneEvent": { - "type": "object", - "description": "Emitted when a reasoning summary text is completed.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.reasoning_summary_text.done`.\n", - "enum": [ - "response.reasoning_summary_text.done" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the item this summary text is associated with.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item this summary text is associated with.\n" - }, - "summary_index": { - "type": "integer", - "description": "The index of the summary part within the reasoning summary.\n" - }, - "text": { - "type": "string", - "description": "The full text of the completed reasoning summary.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - } - }, - "required": [ - "type", - "item_id", - "output_index", - "summary_index", - "text", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.reasoning_summary_text.done", - "group": "responses", - "example": "{\n \"type\": \"response.reasoning_summary_text.done\",\n \"item_id\": \"rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476\",\n \"output_index\": 0,\n \"summary_index\": 0,\n \"text\": \"**Responding to a greeting**\\n\\nThe user just said, \\\"Hello!\\\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \\\"Hello! How can I assist you today?\\\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseReasoningTextDeltaEvent": { - "type": "object", - "description": "Emitted when a delta is added to a reasoning text.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.reasoning_text.delta`.\n", - "enum": [ - "response.reasoning_text.delta" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the item this reasoning text delta is associated with.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item this reasoning text delta is associated with.\n" - }, - "content_index": { - "type": "integer", - "description": "The index of the reasoning content part this delta is associated with.\n" - }, - "delta": { - "type": "string", - "description": "The text delta that was added to the reasoning content.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - } - }, - "required": [ - "type", - "item_id", - "output_index", - "content_index", - "delta", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.reasoning_text.delta", - "group": "responses", - "example": "{\n \"type\": \"response.reasoning_text.delta\",\n \"item_id\": \"rs_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"delta\": \"The\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseReasoningTextDoneEvent": { - "type": "object", - "description": "Emitted when a reasoning text is completed.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.reasoning_text.done`.\n", - "enum": [ - "response.reasoning_text.done" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the item this reasoning text is associated with.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item this reasoning text is associated with.\n" - }, - "content_index": { - "type": "integer", - "description": "The index of the reasoning content part.\n" - }, - "text": { - "type": "string", - "description": "The full text of the completed reasoning content.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - } - }, - "required": [ - "type", - "item_id", - "output_index", - "content_index", - "text", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.reasoning_text.done", - "group": "responses", - "example": "{\n \"type\": \"response.reasoning_text.done\",\n \"item_id\": \"rs_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"text\": \"The user is asking...\",\n \"sequence_number\": 4\n}\n" - } - }, - "ResponseRefusalDeltaEvent": { - "type": "object", - "description": "Emitted when there is a partial refusal text.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.refusal.delta`.\n", - "enum": [ - "response.refusal.delta" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the refusal text is added to.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the refusal text is added to.\n" - }, - "content_index": { - "type": "integer", - "description": "The index of the content part that the refusal text is added to.\n" - }, - "delta": { - "type": "string", - "description": "The refusal text that is added.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - } - }, - "required": [ - "type", - "item_id", - "output_index", - "content_index", - "delta", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.refusal.delta", - "group": "responses", - "example": "{\n \"type\": \"response.refusal.delta\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"delta\": \"refusal text so far\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseRefusalDoneEvent": { - "type": "object", - "description": "Emitted when refusal text is finalized.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.refusal.done`.\n", - "enum": [ - "response.refusal.done" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the refusal text is finalized.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the refusal text is finalized.\n" - }, - "content_index": { - "type": "integer", - "description": "The index of the content part that the refusal text is finalized.\n" - }, - "refusal": { - "type": "string", - "description": "The refusal text that is finalized.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of this event.\n" - } - }, - "required": [ - "type", - "item_id", - "output_index", - "content_index", - "refusal", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.refusal.done", - "group": "responses", - "example": "{\n \"type\": \"response.refusal.done\",\n \"item_id\": \"item-abc\",\n \"output_index\": 1,\n \"content_index\": 2,\n \"refusal\": \"final refusal text\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseStreamEvent": { - "anyOf": [ - { - "$ref": "#/components/schemas/ResponseAudioDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseAudioDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseAudioTranscriptDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseAudioTranscriptDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseCodeInterpreterCallCodeDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseCodeInterpreterCallCodeDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseCodeInterpreterCallCompletedEvent" - }, - { - "$ref": "#/components/schemas/ResponseCodeInterpreterCallInProgressEvent" - }, - { - "$ref": "#/components/schemas/ResponseCodeInterpreterCallInterpretingEvent" - }, - { - "$ref": "#/components/schemas/ResponseCompletedEvent" - }, - { - "$ref": "#/components/schemas/ResponseContentPartAddedEvent" - }, - { - "$ref": "#/components/schemas/ResponseContentPartDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseCreatedEvent" - }, - { - "$ref": "#/components/schemas/ResponseErrorEvent" - }, - { - "$ref": "#/components/schemas/ResponseFileSearchCallCompletedEvent" - }, - { - "$ref": "#/components/schemas/ResponseFileSearchCallInProgressEvent" - }, - { - "$ref": "#/components/schemas/ResponseFileSearchCallSearchingEvent" - }, - { - "$ref": "#/components/schemas/ResponseFunctionCallArgumentsDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseFunctionCallArgumentsDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseInProgressEvent" - }, - { - "$ref": "#/components/schemas/ResponseFailedEvent" - }, - { - "$ref": "#/components/schemas/ResponseIncompleteEvent" - }, - { - "$ref": "#/components/schemas/ResponseOutputItemAddedEvent" - }, - { - "$ref": "#/components/schemas/ResponseOutputItemDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseReasoningSummaryPartAddedEvent" - }, - { - "$ref": "#/components/schemas/ResponseReasoningSummaryPartDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseReasoningSummaryTextDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseReasoningSummaryTextDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseReasoningTextDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseReasoningTextDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseRefusalDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseRefusalDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseTextDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseTextDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseWebSearchCallCompletedEvent" - }, - { - "$ref": "#/components/schemas/ResponseWebSearchCallInProgressEvent" - }, - { - "$ref": "#/components/schemas/ResponseWebSearchCallSearchingEvent" - }, - { - "$ref": "#/components/schemas/ResponseImageGenCallCompletedEvent" - }, - { - "$ref": "#/components/schemas/ResponseImageGenCallGeneratingEvent" - }, - { - "$ref": "#/components/schemas/ResponseImageGenCallInProgressEvent" - }, - { - "$ref": "#/components/schemas/ResponseImageGenCallPartialImageEvent" - }, - { - "$ref": "#/components/schemas/ResponseMCPCallArgumentsDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseMCPCallArgumentsDoneEvent" - }, - { - "$ref": "#/components/schemas/ResponseMCPCallCompletedEvent" - }, - { - "$ref": "#/components/schemas/ResponseMCPCallFailedEvent" - }, - { - "$ref": "#/components/schemas/ResponseMCPCallInProgressEvent" - }, - { - "$ref": "#/components/schemas/ResponseMCPListToolsCompletedEvent" - }, - { - "$ref": "#/components/schemas/ResponseMCPListToolsFailedEvent" - }, - { - "$ref": "#/components/schemas/ResponseMCPListToolsInProgressEvent" - }, - { - "$ref": "#/components/schemas/ResponseOutputTextAnnotationAddedEvent" - }, - { - "$ref": "#/components/schemas/ResponseQueuedEvent" - }, - { - "$ref": "#/components/schemas/ResponseCustomToolCallInputDeltaEvent" - }, - { - "$ref": "#/components/schemas/ResponseCustomToolCallInputDoneEvent" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "ResponseStreamOptions": { - "description": "Options for streaming responses. Only set this when you set `stream: true`.\n", - "type": "object", - "nullable": true, - "default": null, - "properties": { - "include_obfuscation": { - "type": "boolean", - "description": "When true, stream obfuscation will be enabled. Stream obfuscation adds\nrandom characters to an `obfuscation` field on streaming delta events to\nnormalize payload sizes as a mitigation to certain side-channel attacks.\nThese obfuscation fields are included by default, but add a small amount\nof overhead to the data stream. You can set `include_obfuscation` to\nfalse to optimize for bandwidth if you trust the network links between\nyour application and the OpenAI API.\n" - } - } - }, - "ResponseTextDeltaEvent": { - "type": "object", - "description": "Emitted when there is an additional text delta.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.output_text.delta`.\n", - "enum": [ - "response.output_text.delta" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the text delta was added to.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the text delta was added to.\n" - }, - "content_index": { - "type": "integer", - "description": "The index of the content part that the text delta was added to.\n" - }, - "delta": { - "type": "string", - "description": "The text delta that was added.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number for this event." - }, - "logprobs": { - "type": "array", - "description": "The log probabilities of the tokens in the delta.\n", - "items": { - "$ref": "#/components/schemas/ResponseLogProb" - } - } - }, - "required": [ - "type", - "item_id", - "output_index", - "content_index", - "delta", - "sequence_number", - "logprobs" - ], - "x-oaiMeta": { - "name": "response.output_text.delta", - "group": "responses", - "example": "{\n \"type\": \"response.output_text.delta\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"delta\": \"In\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseTextDoneEvent": { - "type": "object", - "description": "Emitted when text content is finalized.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.output_text.done`.\n", - "enum": [ - "response.output_text.done" - ], - "x-stainless-const": true - }, - "item_id": { - "type": "string", - "description": "The ID of the output item that the text content is finalized.\n" - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the text content is finalized.\n" - }, - "content_index": { - "type": "integer", - "description": "The index of the content part that the text content is finalized.\n" - }, - "text": { - "type": "string", - "description": "The text content that is finalized.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number for this event." - }, - "logprobs": { - "type": "array", - "description": "The log probabilities of the tokens in the delta.\n", - "items": { - "$ref": "#/components/schemas/ResponseLogProb" - } - } - }, - "required": [ - "type", - "item_id", - "output_index", - "content_index", - "text", - "sequence_number", - "logprobs" - ], - "x-oaiMeta": { - "name": "response.output_text.done", - "group": "responses", - "example": "{\n \"type\": \"response.output_text.done\",\n \"item_id\": \"msg_123\",\n \"output_index\": 0,\n \"content_index\": 0,\n \"text\": \"In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.\",\n \"sequence_number\": 1\n}\n" - } - }, - "ResponseUsage": { - "type": "object", - "description": "Represents token usage details including input tokens, output tokens,\na breakdown of output tokens, and the total tokens used.\n", - "properties": { - "input_tokens": { - "type": "integer", - "description": "The number of input tokens." - }, - "input_tokens_details": { - "type": "object", - "description": "A detailed breakdown of the input tokens.", - "properties": { - "cached_tokens": { - "type": "integer", - "description": "The number of tokens that were retrieved from the cache. \n[More on prompt caching](https://platform.openai.com/docs/guides/prompt-caching).\n" - } - }, - "required": [ - "cached_tokens" - ] - }, - "output_tokens": { - "type": "integer", - "description": "The number of output tokens." - }, - "output_tokens_details": { - "type": "object", - "description": "A detailed breakdown of the output tokens.", - "properties": { - "reasoning_tokens": { - "type": "integer", - "description": "The number of reasoning tokens." - } - }, - "required": [ - "reasoning_tokens" - ] - }, - "total_tokens": { - "type": "integer", - "description": "The total number of tokens used." - } - }, - "required": [ - "input_tokens", - "input_tokens_details", - "output_tokens", - "output_tokens_details", - "total_tokens" - ] - }, - "ResponseWebSearchCallCompletedEvent": { - "type": "object", - "description": "Emitted when a web search call is completed.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.web_search_call.completed`.\n", - "enum": [ - "response.web_search_call.completed" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the web search call is associated with.\n" - }, - "item_id": { - "type": "string", - "description": "Unique ID for the output item associated with the web search call.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of the web search call being processed." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.web_search_call.completed", - "group": "responses", - "example": "{\n \"type\": \"response.web_search_call.completed\",\n \"output_index\": 0,\n \"item_id\": \"ws_123\",\n \"sequence_number\": 0\n}\n" - } - }, - "ResponseWebSearchCallInProgressEvent": { - "type": "object", - "description": "Emitted when a web search call is initiated.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.web_search_call.in_progress`.\n", - "enum": [ - "response.web_search_call.in_progress" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the web search call is associated with.\n" - }, - "item_id": { - "type": "string", - "description": "Unique ID for the output item associated with the web search call.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of the web search call being processed." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.web_search_call.in_progress", - "group": "responses", - "example": "{\n \"type\": \"response.web_search_call.in_progress\",\n \"output_index\": 0,\n \"item_id\": \"ws_123\",\n \"sequence_number\": 0\n}\n" - } - }, - "ResponseWebSearchCallSearchingEvent": { - "type": "object", - "description": "Emitted when a web search call is executing.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `response.web_search_call.searching`.\n", - "enum": [ - "response.web_search_call.searching" - ], - "x-stainless-const": true - }, - "output_index": { - "type": "integer", - "description": "The index of the output item that the web search call is associated with.\n" - }, - "item_id": { - "type": "string", - "description": "Unique ID for the output item associated with the web search call.\n" - }, - "sequence_number": { - "type": "integer", - "description": "The sequence number of the web search call being processed." - } - }, - "required": [ - "type", - "output_index", - "item_id", - "sequence_number" - ], - "x-oaiMeta": { - "name": "response.web_search_call.searching", - "group": "responses", - "example": "{\n \"type\": \"response.web_search_call.searching\",\n \"output_index\": 0,\n \"item_id\": \"ws_123\",\n \"sequence_number\": 0\n}\n" - } - }, - "RunCompletionUsage": { - "type": "object", - "description": "Usage statistics related to the run. This value will be `null` if the run is not in a terminal state (i.e. `in_progress`, `queued`, etc.).", - "properties": { - "completion_tokens": { - "type": "integer", - "description": "Number of completion tokens used over the course of the run." - }, - "prompt_tokens": { - "type": "integer", - "description": "Number of prompt tokens used over the course of the run." - }, - "total_tokens": { - "type": "integer", - "description": "Total number of tokens used (prompt + completion)." - } - }, - "required": [ - "prompt_tokens", - "completion_tokens", - "total_tokens" - ], - "nullable": true - }, - "RunGraderRequest": { - "type": "object", - "title": "RunGraderRequest", - "properties": { - "grader": { - "type": "object", - "description": "The grader used for the fine-tuning job.", - "anyOf": [ - { - "$ref": "#/components/schemas/GraderStringCheck" - }, - { - "$ref": "#/components/schemas/GraderTextSimilarity" - }, - { - "$ref": "#/components/schemas/GraderPython" - }, - { - "$ref": "#/components/schemas/GraderScoreModel" - }, - { - "$ref": "#/components/schemas/GraderMulti" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "item": { - "type": "object", - "description": "The dataset item provided to the grader. This will be used to populate\nthe `item` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more details.\n" - }, - "model_sample": { - "type": "string", - "description": "The model sample to be evaluated. This value will be used to populate\nthe `sample` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more details.\nThe `output_json` variable will be populated if the model sample is a\nvalid JSON string.\n" - } - }, - "required": [ - "grader", - "model_sample" - ] - }, - "RunGraderResponse": { - "type": "object", - "properties": { - "reward": { - "type": "number" - }, - "metadata": { - "type": "object", - "properties": { - "name": { - "type": "string" - }, - "type": { - "type": "string" - }, - "errors": { - "type": "object", - "properties": { - "formula_parse_error": { - "type": "boolean" - }, - "sample_parse_error": { - "type": "boolean" - }, - "truncated_observation_error": { - "type": "boolean" - }, - "unresponsive_reward_error": { - "type": "boolean" - }, - "invalid_variable_error": { - "type": "boolean" - }, - "other_error": { - "type": "boolean" - }, - "python_grader_server_error": { - "type": "boolean" - }, - "python_grader_server_error_type": { - "type": "string", - "nullable": true - }, - "python_grader_runtime_error": { - "type": "boolean" - }, - "python_grader_runtime_error_details": { - "type": "string", - "nullable": true - }, - "model_grader_server_error": { - "type": "boolean" - }, - "model_grader_refusal_error": { - "type": "boolean" - }, - "model_grader_parse_error": { - "type": "boolean" - }, - "model_grader_server_error_details": { - "type": "string", - "nullable": true - } - }, - "required": [ - "formula_parse_error", - "sample_parse_error", - "truncated_observation_error", - "unresponsive_reward_error", - "invalid_variable_error", - "other_error", - "python_grader_server_error", - "python_grader_server_error_type", - "python_grader_runtime_error", - "python_grader_runtime_error_details", - "model_grader_server_error", - "model_grader_refusal_error", - "model_grader_parse_error", - "model_grader_server_error_details" - ] - }, - "execution_time": { - "type": "number" - }, - "scores": { - "type": "object", - "additionalProperties": {} - }, - "token_usage": { - "type": "integer", - "nullable": true - }, - "sampled_model_name": { - "type": "string", - "nullable": true - } - }, - "required": [ - "name", - "type", - "errors", - "execution_time", - "scores", - "token_usage", - "sampled_model_name" - ] - }, - "sub_rewards": { - "type": "object", - "additionalProperties": {} - }, - "model_grader_token_usage_per_model": { - "type": "object", - "additionalProperties": {} - } - }, - "required": [ - "reward", - "metadata", - "sub_rewards", - "model_grader_token_usage_per_model" - ] - }, - "RunObject": { - "type": "object", - "title": "A run on a thread", - "description": "Represents an execution run on a [thread](https://platform.openai.com/docs/api-reference/threads).", - "properties": { - "id": { - "description": "The identifier, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `thread.run`.", - "type": "string", - "enum": [ - "thread.run" - ], - "x-stainless-const": true - }, - "created_at": { - "description": "The Unix timestamp (in seconds) for when the run was created.", - "type": "integer" - }, - "thread_id": { - "description": "The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was executed on as a part of this run.", - "type": "string" - }, - "assistant_id": { - "description": "The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for execution of this run.", - "type": "string" - }, - "status": { - "$ref": "#/components/schemas/RunStatus" - }, - "required_action": { - "type": "object", - "description": "Details on the action required to continue the run. Will be `null` if no action is required.", - "nullable": true, - "properties": { - "type": { - "description": "For now, this is always `submit_tool_outputs`.", - "type": "string", - "enum": [ - "submit_tool_outputs" - ], - "x-stainless-const": true - }, - "submit_tool_outputs": { - "type": "object", - "description": "Details on the tool outputs needed for this run to continue.", - "properties": { - "tool_calls": { - "type": "array", - "description": "A list of the relevant tool calls.", - "items": { - "$ref": "#/components/schemas/RunToolCallObject" - } - } - }, - "required": [ - "tool_calls" - ] - } - }, - "required": [ - "type", - "submit_tool_outputs" - ] - }, - "last_error": { - "type": "object", - "description": "The last error associated with this run. Will be `null` if there are no errors.", - "nullable": true, - "properties": { - "code": { - "type": "string", - "description": "One of `server_error`, `rate_limit_exceeded`, or `invalid_prompt`.", - "enum": [ - "server_error", - "rate_limit_exceeded", - "invalid_prompt" - ] - }, - "message": { - "type": "string", - "description": "A human-readable description of the error." - } - }, - "required": [ - "code", - "message" - ] - }, - "expires_at": { - "description": "The Unix timestamp (in seconds) for when the run will expire.", - "type": "integer", - "nullable": true - }, - "started_at": { - "description": "The Unix timestamp (in seconds) for when the run was started.", - "type": "integer", - "nullable": true - }, - "cancelled_at": { - "description": "The Unix timestamp (in seconds) for when the run was cancelled.", - "type": "integer", - "nullable": true - }, - "failed_at": { - "description": "The Unix timestamp (in seconds) for when the run failed.", - "type": "integer", - "nullable": true - }, - "completed_at": { - "description": "The Unix timestamp (in seconds) for when the run was completed.", - "type": "integer", - "nullable": true - }, - "incomplete_details": { - "description": "Details on why the run is incomplete. Will be `null` if the run is not incomplete.", - "type": "object", - "nullable": true, - "properties": { - "reason": { - "description": "The reason why the run is incomplete. This will point to which specific token limit was reached over the course of the run.", - "type": "string", - "enum": [ - "max_completion_tokens", - "max_prompt_tokens" - ] - } - } - }, - "model": { - "description": "The model that the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for this run.", - "type": "string" - }, - "instructions": { - "description": "The instructions that the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for this run.", - "type": "string" - }, - "tools": { - "description": "The list of tools that the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for this run.", - "default": [], - "type": "array", - "maxItems": 20, - "items": { - "$ref": "#/components/schemas/AssistantTool" - } - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "usage": { - "$ref": "#/components/schemas/RunCompletionUsage" - }, - "temperature": { - "description": "The sampling temperature used for this run. If not set, defaults to 1.", - "type": "number", - "nullable": true - }, - "top_p": { - "description": "The nucleus sampling value used for this run. If not set, defaults to 1.", - "type": "number", - "nullable": true - }, - "max_prompt_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of prompt tokens specified to have been used over the course of the run.\n", - "minimum": 256 - }, - "max_completion_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of completion tokens specified to have been used over the course of the run.\n", - "minimum": 256 - }, - "truncation_strategy": { - "allOf": [ - { - "$ref": "#/components/schemas/TruncationObject" - }, - { - "nullable": true - } - ] - }, - "tool_choice": { - "allOf": [ - { - "$ref": "#/components/schemas/AssistantsApiToolChoiceOption" - }, - { - "nullable": true - } - ] - }, - "parallel_tool_calls": { - "$ref": "#/components/schemas/ParallelToolCalls" - }, - "response_format": { - "$ref": "#/components/schemas/AssistantsApiResponseFormatOption", - "nullable": true - } - }, - "required": [ - "id", - "object", - "created_at", - "thread_id", - "assistant_id", - "status", - "required_action", - "last_error", - "expires_at", - "started_at", - "cancelled_at", - "failed_at", - "completed_at", - "model", - "instructions", - "tools", - "metadata", - "usage", - "incomplete_details", - "max_prompt_tokens", - "max_completion_tokens", - "truncation_strategy", - "tool_choice", - "parallel_tool_calls", - "response_format" - ], - "x-oaiMeta": { - "name": "The run object", - "beta": true, - "example": "{\n \"id\": \"run_abc123\",\n \"object\": \"thread.run\",\n \"created_at\": 1698107661,\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"status\": \"completed\",\n \"started_at\": 1699073476,\n \"expires_at\": null,\n \"cancelled_at\": null,\n \"failed_at\": null,\n \"completed_at\": 1699073498,\n \"last_error\": null,\n \"model\": \"gpt-4o\",\n \"instructions\": null,\n \"tools\": [{\"type\": \"file_search\"}, {\"type\": \"code_interpreter\"}],\n \"metadata\": {},\n \"incomplete_details\": null,\n \"usage\": {\n \"prompt_tokens\": 123,\n \"completion_tokens\": 456,\n \"total_tokens\": 579\n },\n \"temperature\": 1.0,\n \"top_p\": 1.0,\n \"max_prompt_tokens\": 1000,\n \"max_completion_tokens\": 1000,\n \"truncation_strategy\": {\n \"type\": \"auto\",\n \"last_messages\": null\n },\n \"response_format\": \"auto\",\n \"tool_choice\": \"auto\",\n \"parallel_tool_calls\": true\n}\n" - } - }, - "RunStepCompletionUsage": { - "type": "object", - "description": "Usage statistics related to the run step. This value will be `null` while the run step's status is `in_progress`.", - "properties": { - "completion_tokens": { - "type": "integer", - "description": "Number of completion tokens used over the course of the run step." - }, - "prompt_tokens": { - "type": "integer", - "description": "Number of prompt tokens used over the course of the run step." - }, - "total_tokens": { - "type": "integer", - "description": "Total number of tokens used (prompt + completion)." - } - }, - "required": [ - "prompt_tokens", - "completion_tokens", - "total_tokens" - ], - "nullable": true - }, - "RunStepDeltaObject": { - "type": "object", - "title": "Run step delta object", - "description": "Represents a run step delta i.e. any changed fields on a run step during streaming.\n", - "properties": { - "id": { - "description": "The identifier of the run step, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `thread.run.step.delta`.", - "type": "string", - "enum": [ - "thread.run.step.delta" - ], - "x-stainless-const": true - }, - "delta": { - "$ref": "#/components/schemas/RunStepDeltaObjectDelta" - } - }, - "required": [ - "id", - "object", - "delta" - ], - "x-oaiMeta": { - "name": "The run step delta object", - "beta": true, - "example": "{\n \"id\": \"step_123\",\n \"object\": \"thread.run.step.delta\",\n \"delta\": {\n \"step_details\": {\n \"type\": \"tool_calls\",\n \"tool_calls\": [\n {\n \"index\": 0,\n \"id\": \"call_123\",\n \"type\": \"code_interpreter\",\n \"code_interpreter\": { \"input\": \"\", \"outputs\": [] }\n }\n ]\n }\n }\n}\n" - } - }, - "RunStepDeltaStepDetailsMessageCreationObject": { - "title": "Message creation", - "type": "object", - "description": "Details of the message creation by the run step.", - "properties": { - "type": { - "description": "Always `message_creation`.", - "type": "string", - "enum": [ - "message_creation" - ], - "x-stainless-const": true - }, - "message_creation": { - "type": "object", - "properties": { - "message_id": { - "type": "string", - "description": "The ID of the message that was created by this run step." - } - } - } - }, - "required": [ - "type" - ] - }, - "RunStepDeltaStepDetailsToolCallsCodeObject": { - "title": "Code interpreter tool call", - "type": "object", - "description": "Details of the Code Interpreter tool call the run step was involved in.", - "properties": { - "index": { - "type": "integer", - "description": "The index of the tool call in the tool calls array." - }, - "id": { - "type": "string", - "description": "The ID of the tool call." - }, - "type": { - "type": "string", - "description": "The type of tool call. This is always going to be `code_interpreter` for this type of tool call.", - "enum": [ - "code_interpreter" - ], - "x-stainless-const": true - }, - "code_interpreter": { - "type": "object", - "description": "The Code Interpreter tool call definition.", - "properties": { - "input": { - "type": "string", - "description": "The input to the Code Interpreter tool call." - }, - "outputs": { - "type": "array", - "description": "The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (`logs`) or images (`image`). Each of these are represented by a different object type.", - "items": { - "type": "object", - "anyOf": [ - { - "$ref": "#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeOutputLogsObject" - }, - { - "$ref": "#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeOutputImageObject" - } - ], - "discriminator": { - "propertyName": "type" - } - } - } - } - } - }, - "required": [ - "index", - "type" - ] - }, - "RunStepDeltaStepDetailsToolCallsCodeOutputImageObject": { - "title": "Code interpreter image output", - "type": "object", - "properties": { - "index": { - "type": "integer", - "description": "The index of the output in the outputs array." - }, - "type": { - "description": "Always `image`.", - "type": "string", - "enum": [ - "image" - ], - "x-stainless-const": true - }, - "image": { - "type": "object", - "properties": { - "file_id": { - "description": "The [file](https://platform.openai.com/docs/api-reference/files) ID of the image.", - "type": "string" - } - } - } - }, - "required": [ - "index", - "type" - ] - }, - "RunStepDeltaStepDetailsToolCallsCodeOutputLogsObject": { - "title": "Code interpreter log output", - "type": "object", - "description": "Text output from the Code Interpreter tool call as part of a run step.", - "properties": { - "index": { - "type": "integer", - "description": "The index of the output in the outputs array." - }, - "type": { - "description": "Always `logs`.", - "type": "string", - "enum": [ - "logs" - ], - "x-stainless-const": true - }, - "logs": { - "type": "string", - "description": "The text output from the Code Interpreter tool call." - } - }, - "required": [ - "index", - "type" - ] - }, - "RunStepDeltaStepDetailsToolCallsFileSearchObject": { - "title": "File search tool call", - "type": "object", - "properties": { - "index": { - "type": "integer", - "description": "The index of the tool call in the tool calls array." - }, - "id": { - "type": "string", - "description": "The ID of the tool call object." - }, - "type": { - "type": "string", - "description": "The type of tool call. This is always going to be `file_search` for this type of tool call.", - "enum": [ - "file_search" - ], - "x-stainless-const": true - }, - "file_search": { - "type": "object", - "description": "For now, this is always going to be an empty object.", - "x-oaiTypeLabel": "map" - } - }, - "required": [ - "index", - "type", - "file_search" - ] - }, - "RunStepDeltaStepDetailsToolCallsFunctionObject": { - "type": "object", - "title": "Function tool call", - "properties": { - "index": { - "type": "integer", - "description": "The index of the tool call in the tool calls array." - }, - "id": { - "type": "string", - "description": "The ID of the tool call object." - }, - "type": { - "type": "string", - "description": "The type of tool call. This is always going to be `function` for this type of tool call.", - "enum": [ - "function" - ], - "x-stainless-const": true - }, - "function": { - "type": "object", - "description": "The definition of the function that was called.", - "properties": { - "name": { - "type": "string", - "description": "The name of the function." - }, - "arguments": { - "type": "string", - "description": "The arguments passed to the function." - }, - "output": { - "type": "string", - "description": "The output of the function. This will be `null` if the outputs have not been [submitted](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) yet.", - "nullable": true - } - } - } - }, - "required": [ - "index", - "type" - ] - }, - "RunStepDeltaStepDetailsToolCallsObject": { - "title": "Tool calls", - "type": "object", - "description": "Details of the tool call.", - "properties": { - "type": { - "description": "Always `tool_calls`.", - "type": "string", - "enum": [ - "tool_calls" - ], - "x-stainless-const": true - }, - "tool_calls": { - "type": "array", - "description": "An array of tool calls the run step was involved in. These can be associated with one of three types of tools: `code_interpreter`, `file_search`, or `function`.\n", - "items": { - "$ref": "#/components/schemas/RunStepDeltaStepDetailsToolCall" - } - } - }, - "required": [ - "type" - ] - }, - "RunStepDetailsMessageCreationObject": { - "title": "Message creation", - "type": "object", - "description": "Details of the message creation by the run step.", - "properties": { - "type": { - "description": "Always `message_creation`.", - "type": "string", - "enum": [ - "message_creation" - ], - "x-stainless-const": true - }, - "message_creation": { - "type": "object", - "properties": { - "message_id": { - "type": "string", - "description": "The ID of the message that was created by this run step." - } - }, - "required": [ - "message_id" - ] - } - }, - "required": [ - "type", - "message_creation" - ] - }, - "RunStepDetailsToolCallsCodeObject": { - "title": "Code Interpreter tool call", - "type": "object", - "description": "Details of the Code Interpreter tool call the run step was involved in.", - "properties": { - "id": { - "type": "string", - "description": "The ID of the tool call." - }, - "type": { - "type": "string", - "description": "The type of tool call. This is always going to be `code_interpreter` for this type of tool call.", - "enum": [ - "code_interpreter" - ], - "x-stainless-const": true - }, - "code_interpreter": { - "type": "object", - "description": "The Code Interpreter tool call definition.", - "required": [ - "input", - "outputs" - ], - "properties": { - "input": { - "type": "string", - "description": "The input to the Code Interpreter tool call." - }, - "outputs": { - "type": "array", - "description": "The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (`logs`) or images (`image`). Each of these are represented by a different object type.", - "items": { - "type": "object", - "anyOf": [ - { - "$ref": "#/components/schemas/RunStepDetailsToolCallsCodeOutputLogsObject" - }, - { - "$ref": "#/components/schemas/RunStepDetailsToolCallsCodeOutputImageObject" - } - ], - "discriminator": { - "propertyName": "type" - } - } - } - } - } - }, - "required": [ - "id", - "type", - "code_interpreter" - ] - }, - "RunStepDetailsToolCallsCodeOutputImageObject": { - "title": "Code Interpreter image output", - "type": "object", - "properties": { - "type": { - "description": "Always `image`.", - "type": "string", - "enum": [ - "image" - ], - "x-stainless-const": true - }, - "image": { - "type": "object", - "properties": { - "file_id": { - "description": "The [file](https://platform.openai.com/docs/api-reference/files) ID of the image.", - "type": "string" - } - }, - "required": [ - "file_id" - ] - } - }, - "required": [ - "type", - "image" - ], - "x-stainless-naming": { - "java": { - "type_name": "ImageOutput" - }, - "kotlin": { - "type_name": "ImageOutput" - } - } - }, - "RunStepDetailsToolCallsCodeOutputLogsObject": { - "title": "Code Interpreter log output", - "type": "object", - "description": "Text output from the Code Interpreter tool call as part of a run step.", - "properties": { - "type": { - "description": "Always `logs`.", - "type": "string", - "enum": [ - "logs" - ], - "x-stainless-const": true - }, - "logs": { - "type": "string", - "description": "The text output from the Code Interpreter tool call." - } - }, - "required": [ - "type", - "logs" - ], - "x-stainless-naming": { - "java": { - "type_name": "LogsOutput" - }, - "kotlin": { - "type_name": "LogsOutput" - } - } - }, - "RunStepDetailsToolCallsFileSearchObject": { - "title": "File search tool call", - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The ID of the tool call object." - }, - "type": { - "type": "string", - "description": "The type of tool call. This is always going to be `file_search` for this type of tool call.", - "enum": [ - "file_search" - ], - "x-stainless-const": true - }, - "file_search": { - "type": "object", - "description": "For now, this is always going to be an empty object.", - "x-oaiTypeLabel": "map", - "properties": { - "ranking_options": { - "$ref": "#/components/schemas/RunStepDetailsToolCallsFileSearchRankingOptionsObject" - }, - "results": { - "type": "array", - "description": "The results of the file search.", - "items": { - "$ref": "#/components/schemas/RunStepDetailsToolCallsFileSearchResultObject" - } - } - } - } - }, - "required": [ - "id", - "type", - "file_search" - ] - }, - "RunStepDetailsToolCallsFileSearchRankingOptionsObject": { - "title": "File search tool call ranking options", - "type": "object", - "description": "The ranking options for the file search.", - "properties": { - "ranker": { - "$ref": "#/components/schemas/FileSearchRanker" - }, - "score_threshold": { - "type": "number", - "description": "The score threshold for the file search. All values must be a floating point number between 0 and 1.", - "minimum": 0, - "maximum": 1 - } - }, - "required": [ - "ranker", - "score_threshold" - ] - }, - "RunStepDetailsToolCallsFileSearchResultObject": { - "title": "File search tool call result", - "type": "object", - "description": "A result instance of the file search.", - "x-oaiTypeLabel": "map", - "properties": { - "file_id": { - "type": "string", - "description": "The ID of the file that result was found in." - }, - "file_name": { - "type": "string", - "description": "The name of the file that result was found in." - }, - "score": { - "type": "number", - "description": "The score of the result. All values must be a floating point number between 0 and 1.", - "minimum": 0, - "maximum": 1 - }, - "content": { - "type": "array", - "description": "The content of the result that was found. The content is only included if requested via the include query parameter.", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "description": "The type of the content.", - "enum": [ - "text" - ], - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text content of the file." - } - } - } - } - }, - "required": [ - "file_id", - "file_name", - "score" - ] - }, - "RunStepDetailsToolCallsFunctionObject": { - "type": "object", - "title": "Function tool call", - "properties": { - "id": { - "type": "string", - "description": "The ID of the tool call object." - }, - "type": { - "type": "string", - "description": "The type of tool call. This is always going to be `function` for this type of tool call.", - "enum": [ - "function" - ], - "x-stainless-const": true - }, - "function": { - "type": "object", - "description": "The definition of the function that was called.", - "properties": { - "name": { - "type": "string", - "description": "The name of the function." - }, - "arguments": { - "type": "string", - "description": "The arguments passed to the function." - }, - "output": { - "type": "string", - "description": "The output of the function. This will be `null` if the outputs have not been [submitted](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) yet.", - "nullable": true - } - }, - "required": [ - "name", - "arguments", - "output" - ] - } - }, - "required": [ - "id", - "type", - "function" - ] - }, - "RunStepDetailsToolCallsObject": { - "title": "Tool calls", - "type": "object", - "description": "Details of the tool call.", - "properties": { - "type": { - "description": "Always `tool_calls`.", - "type": "string", - "enum": [ - "tool_calls" - ], - "x-stainless-const": true - }, - "tool_calls": { - "type": "array", - "description": "An array of tool calls the run step was involved in. These can be associated with one of three types of tools: `code_interpreter`, `file_search`, or `function`.\n", - "items": { - "$ref": "#/components/schemas/RunStepDetailsToolCall" - } - } - }, - "required": [ - "type", - "tool_calls" - ] - }, - "RunStepObject": { - "type": "object", - "title": "Run steps", - "description": "Represents a step in execution of a run.\n", - "properties": { - "id": { - "description": "The identifier of the run step, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `thread.run.step`.", - "type": "string", - "enum": [ - "thread.run.step" - ], - "x-stainless-const": true - }, - "created_at": { - "description": "The Unix timestamp (in seconds) for when the run step was created.", - "type": "integer" - }, - "assistant_id": { - "description": "The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) associated with the run step.", - "type": "string" - }, - "thread_id": { - "description": "The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was run.", - "type": "string" - }, - "run_id": { - "description": "The ID of the [run](https://platform.openai.com/docs/api-reference/runs) that this run step is a part of.", - "type": "string" - }, - "type": { - "description": "The type of run step, which can be either `message_creation` or `tool_calls`.", - "type": "string", - "enum": [ - "message_creation", - "tool_calls" - ] - }, - "status": { - "description": "The status of the run step, which can be either `in_progress`, `cancelled`, `failed`, `completed`, or `expired`.", - "type": "string", - "enum": [ - "in_progress", - "cancelled", - "failed", - "completed", - "expired" - ] - }, - "step_details": { - "type": "object", - "description": "The details of the run step.", - "anyOf": [ - { - "$ref": "#/components/schemas/RunStepDetailsMessageCreationObject" - }, - { - "$ref": "#/components/schemas/RunStepDetailsToolCallsObject" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "last_error": { - "type": "object", - "description": "The last error associated with this run step. Will be `null` if there are no errors.", - "nullable": true, - "properties": { - "code": { - "type": "string", - "description": "One of `server_error` or `rate_limit_exceeded`.", - "enum": [ - "server_error", - "rate_limit_exceeded" - ] - }, - "message": { - "type": "string", - "description": "A human-readable description of the error." - } - }, - "required": [ - "code", - "message" - ] - }, - "expired_at": { - "description": "The Unix timestamp (in seconds) for when the run step expired. A step is considered expired if the parent run is expired.", - "type": "integer", - "nullable": true - }, - "cancelled_at": { - "description": "The Unix timestamp (in seconds) for when the run step was cancelled.", - "type": "integer", - "nullable": true - }, - "failed_at": { - "description": "The Unix timestamp (in seconds) for when the run step failed.", - "type": "integer", - "nullable": true - }, - "completed_at": { - "description": "The Unix timestamp (in seconds) for when the run step completed.", - "type": "integer", - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "usage": { - "$ref": "#/components/schemas/RunStepCompletionUsage" - } - }, - "required": [ - "id", - "object", - "created_at", - "assistant_id", - "thread_id", - "run_id", - "type", - "status", - "step_details", - "last_error", - "expired_at", - "cancelled_at", - "failed_at", - "completed_at", - "metadata", - "usage" - ], - "x-oaiMeta": { - "name": "The run step object", - "beta": true, - "example": "{\n \"id\": \"step_abc123\",\n \"object\": \"thread.run.step\",\n \"created_at\": 1699063291,\n \"run_id\": \"run_abc123\",\n \"assistant_id\": \"asst_abc123\",\n \"thread_id\": \"thread_abc123\",\n \"type\": \"message_creation\",\n \"status\": \"completed\",\n \"cancelled_at\": null,\n \"completed_at\": 1699063291,\n \"expired_at\": null,\n \"failed_at\": null,\n \"last_error\": null,\n \"step_details\": {\n \"type\": \"message_creation\",\n \"message_creation\": {\n \"message_id\": \"msg_abc123\"\n }\n },\n \"usage\": {\n \"prompt_tokens\": 123,\n \"completion_tokens\": 456,\n \"total_tokens\": 579\n }\n}\n" - } - }, - "RunStepStreamEvent": { - "anyOf": [ - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.step.created" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunStepObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) is created.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run step](/docs/api-reference/run-steps/step-object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.step.in_progress" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunStepObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) moves to an `in_progress` state.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run step](/docs/api-reference/run-steps/step-object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.step.delta" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunStepDeltaObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when parts of a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) are being streamed.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run step delta](/docs/api-reference/assistants-streaming/run-step-delta-object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.step.completed" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunStepObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) is completed.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run step](/docs/api-reference/run-steps/step-object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.step.failed" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunStepObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) fails.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run step](/docs/api-reference/run-steps/step-object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.step.cancelled" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunStepObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) is cancelled.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run step](/docs/api-reference/run-steps/step-object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.step.expired" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunStepObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run step](https://platform.openai.com/docs/api-reference/run-steps/step-object) expires.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run step](/docs/api-reference/run-steps/step-object)" - } - } - ], - "discriminator": { - "propertyName": "event" - } - }, - "RunStreamEvent": { - "anyOf": [ - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.created" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a new [run](https://platform.openai.com/docs/api-reference/runs/object) is created.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.queued" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to a `queued` status.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.in_progress" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to an `in_progress` status.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.requires_action" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to a `requires_action` status.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.completed" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) is completed.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.incomplete" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) ends with status `incomplete`.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.failed" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) fails.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.cancelling" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to a `cancelling` status.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.cancelled" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) is cancelled.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - }, - { - "type": "object", - "properties": { - "event": { - "type": "string", - "enum": [ - "thread.run.expired" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/RunObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) expires.", - "x-oaiMeta": { - "dataDescription": "`data` is a [run](/docs/api-reference/runs/object)" - } - } - ], - "discriminator": { - "propertyName": "event" - } - }, - "RunToolCallObject": { - "type": "object", - "description": "Tool call objects", - "properties": { - "id": { - "type": "string", - "description": "The ID of the tool call. This ID must be referenced when you submit the tool outputs in using the [Submit tool outputs to run](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) endpoint." - }, - "type": { - "type": "string", - "description": "The type of tool call the output is required for. For now, this is always `function`.", - "enum": [ - "function" - ], - "x-stainless-const": true - }, - "function": { - "type": "object", - "description": "The function definition.", - "properties": { - "name": { - "type": "string", - "description": "The name of the function." - }, - "arguments": { - "type": "string", - "description": "The arguments that the model expects you to pass to the function." - } - }, - "required": [ - "name", - "arguments" - ] - } - }, - "required": [ - "id", - "type", - "function" - ] - }, - "Screenshot": { - "type": "object", - "title": "Screenshot", - "description": "A screenshot action.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "screenshot" - ], - "default": "screenshot", - "description": "Specifies the event type. For a screenshot action, this property is \nalways set to `screenshot`.\n", - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "Scroll": { - "type": "object", - "title": "Scroll", - "description": "A scroll action.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "scroll" - ], - "default": "scroll", - "description": "Specifies the event type. For a scroll action, this property is \nalways set to `scroll`.\n", - "x-stainless-const": true - }, - "x": { - "type": "integer", - "description": "The x-coordinate where the scroll occurred.\n" - }, - "y": { - "type": "integer", - "description": "The y-coordinate where the scroll occurred.\n" - }, - "scroll_x": { - "type": "integer", - "description": "The horizontal scroll distance.\n" - }, - "scroll_y": { - "type": "integer", - "description": "The vertical scroll distance.\n" - } - }, - "required": [ - "type", - "x", - "y", - "scroll_x", - "scroll_y" - ] - }, - "ServiceTier": { - "type": "string", - "description": "Specifies the processing type used for serving the request.\n - If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.\n - If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.\n - If set to '[flex](https://platform.openai.com/docs/guides/flex-processing)' or '[priority](https://openai.com/api-priority-processing/)', then the request will be processed with the corresponding service tier.\n - When not set, the default behavior is 'auto'.\n\n When the `service_tier` parameter is set, the response body will include the `service_tier` value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.\n", - "enum": [ - "auto", - "default", - "flex", - "scale", - "priority" - ], - "nullable": true, - "default": "auto" - }, - "SpeechAudioDeltaEvent": { - "type": "object", - "description": "Emitted for each chunk of audio data generated during speech synthesis.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `speech.audio.delta`.\n", - "enum": [ - "speech.audio.delta" - ], - "x-stainless-const": true - }, - "audio": { - "type": "string", - "description": "A chunk of Base64-encoded audio data.\n" - } - }, - "required": [ - "type", - "audio" - ], - "x-oaiMeta": { - "name": "Stream Event (speech.audio.delta)", - "group": "speech", - "example": "{\n \"type\": \"speech.audio.delta\",\n \"audio\": \"base64-encoded-audio-data\"\n}\n" - } - }, - "SpeechAudioDoneEvent": { - "type": "object", - "description": "Emitted when the speech synthesis is complete and all audio has been streamed.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `speech.audio.done`.\n", - "enum": [ - "speech.audio.done" - ], - "x-stainless-const": true - }, - "usage": { - "type": "object", - "description": "Token usage statistics for the request.\n", - "properties": { - "input_tokens": { - "type": "integer", - "description": "Number of input tokens in the prompt." - }, - "output_tokens": { - "type": "integer", - "description": "Number of output tokens generated." - }, - "total_tokens": { - "type": "integer", - "description": "Total number of tokens used (input + output)." - } - }, - "required": [ - "input_tokens", - "output_tokens", - "total_tokens" - ] - } - }, - "required": [ - "type", - "usage" - ], - "x-oaiMeta": { - "name": "Stream Event (speech.audio.done)", - "group": "speech", - "example": "{\n \"type\": \"speech.audio.done\",\n \"usage\": {\n \"input_tokens\": 14,\n \"output_tokens\": 101,\n \"total_tokens\": 115\n }\n}\n" - } - }, - "StaticChunkingStrategy": { - "type": "object", - "additionalProperties": false, - "properties": { - "max_chunk_size_tokens": { - "type": "integer", - "minimum": 100, - "maximum": 4096, - "description": "The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100` and the maximum value is `4096`." - }, - "chunk_overlap_tokens": { - "type": "integer", - "description": "The number of tokens that overlap between chunks. The default value is `400`.\n\nNote that the overlap must not exceed half of `max_chunk_size_tokens`.\n" - } - }, - "required": [ - "max_chunk_size_tokens", - "chunk_overlap_tokens" - ] - }, - "StaticChunkingStrategyRequestParam": { - "type": "object", - "title": "Static Chunking Strategy", - "description": "Customize your own chunking strategy by setting chunk size and chunk overlap.", - "additionalProperties": false, - "properties": { - "type": { - "type": "string", - "description": "Always `static`.", - "enum": [ - "static" - ], - "x-stainless-const": true - }, - "static": { - "$ref": "#/components/schemas/StaticChunkingStrategy" - } - }, - "required": [ - "type", - "static" - ] - }, - "StaticChunkingStrategyResponseParam": { - "type": "object", - "title": "Static Chunking Strategy", - "additionalProperties": false, - "properties": { - "type": { - "type": "string", - "description": "Always `static`.", - "enum": [ - "static" - ], - "x-stainless-const": true - }, - "static": { - "$ref": "#/components/schemas/StaticChunkingStrategy" - } - }, - "required": [ - "type", - "static" - ] - }, - "StopConfiguration": { - "description": "Not supported with latest reasoning models `o3` and `o4-mini`.\n\nUp to 4 sequences where the API will stop generating further tokens. The\nreturned text will not contain the stop sequence.\n", - "nullable": true, - "anyOf": [ - { - "type": "string", - "default": "<|endoftext|>", - "example": "\n\n", - "nullable": true - }, - { - "type": "array", - "minItems": 1, - "maxItems": 4, - "items": { - "type": "string", - "example": "[\"\\n\"]" - } - } - ] - }, - "SubmitToolOutputsRunRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "tool_outputs": { - "description": "A list of tools for which the outputs are being submitted.", - "type": "array", - "items": { - "type": "object", - "properties": { - "tool_call_id": { - "type": "string", - "description": "The ID of the tool call in the `required_action` object within the run object the output is being submitted for." - }, - "output": { - "type": "string", - "description": "The output of the tool call to be submitted to continue the run." - } - } - } - }, - "stream": { - "type": "boolean", - "nullable": true, - "description": "If `true`, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a `data: [DONE]` message.\n" - } - }, - "required": [ - "tool_outputs" - ] - }, - "TextResponseFormatConfiguration": { - "description": "An object specifying the format that the model must output.\n\nConfiguring `{ \"type\": \"json_schema\" }` enables Structured Outputs, \nwhich ensures the model will match your supplied JSON schema. Learn more in the \n[Structured Outputs guide](https://platform.openai.com/docs/guides/structured-outputs).\n\nThe default format is `{ \"type\": \"text\" }` with no additional options.\n\n**Not recommended for gpt-4o and newer models:**\n\nSetting to `{ \"type\": \"json_object\" }` enables the older JSON mode, which\nensures the message the model generates is valid JSON. Using `json_schema`\nis preferred for models that support it.\n", - "anyOf": [ - { - "$ref": "#/components/schemas/ResponseFormatText" - }, - { - "$ref": "#/components/schemas/TextResponseFormatJsonSchema" - }, - { - "$ref": "#/components/schemas/ResponseFormatJsonObject" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "TextResponseFormatJsonSchema": { - "type": "object", - "title": "JSON schema", - "description": "JSON Schema response format. Used to generate structured JSON responses.\nLearn more about [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs).\n", - "properties": { - "type": { - "type": "string", - "description": "The type of response format being defined. Always `json_schema`.", - "enum": [ - "json_schema" - ], - "x-stainless-const": true - }, - "description": { - "type": "string", - "description": "A description of what the response format is for, used by the model to\ndetermine how to respond in the format.\n" - }, - "name": { - "type": "string", - "description": "The name of the response format. Must be a-z, A-Z, 0-9, or contain\nunderscores and dashes, with a maximum length of 64.\n" - }, - "schema": { - "$ref": "#/components/schemas/ResponseFormatJsonSchemaSchema" - }, - "strict": { - "type": "boolean", - "nullable": true, - "default": false, - "description": "Whether to enable strict schema adherence when generating the output.\nIf set to true, the model will always follow the exact schema defined\nin the `schema` field. Only a subset of JSON Schema is supported when\n`strict` is `true`. To learn more, read the [Structured Outputs\nguide](https://platform.openai.com/docs/guides/structured-outputs).\n" - } - }, - "required": [ - "type", - "schema", - "name" - ] - }, - "ThreadObject": { - "type": "object", - "title": "Thread", - "description": "Represents a thread that contains [messages](https://platform.openai.com/docs/api-reference/messages).", - "properties": { - "id": { - "description": "The identifier, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `thread`.", - "type": "string", - "enum": [ - "thread" - ], - "x-stainless-const": true - }, - "created_at": { - "description": "The Unix timestamp (in seconds) for when the thread was created.", - "type": "integer" - }, - "tool_resources": { - "type": "object", - "description": "A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.\n", - "properties": { - "code_interpreter": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.\n", - "default": [], - "maxItems": 20, - "items": { - "type": "string" - } - } - } - }, - "file_search": { - "type": "object", - "properties": { - "vector_store_ids": { - "type": "array", - "description": "The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this thread. There can be a maximum of 1 vector store attached to the thread.\n", - "maxItems": 1, - "items": { - "type": "string" - } - } - } - } - }, - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - }, - "required": [ - "id", - "object", - "created_at", - "tool_resources", - "metadata" - ], - "x-oaiMeta": { - "name": "The thread object", - "beta": true, - "example": "{\n \"id\": \"thread_abc123\",\n \"object\": \"thread\",\n \"created_at\": 1698107661,\n \"metadata\": {}\n}\n" - } - }, - "ThreadStreamEvent": { - "anyOf": [ - { - "type": "object", - "properties": { - "enabled": { - "type": "boolean", - "description": "Whether to enable input audio transcription." - }, - "event": { - "type": "string", - "enum": [ - "thread.created" - ], - "x-stainless-const": true - }, - "data": { - "$ref": "#/components/schemas/ThreadObject" - } - }, - "required": [ - "event", - "data" - ], - "description": "Occurs when a new [thread](https://platform.openai.com/docs/api-reference/threads/object) is created.", - "x-oaiMeta": { - "dataDescription": "`data` is a [thread](/docs/api-reference/threads/object)" - } - } - ], - "discriminator": { - "propertyName": "event" - } - }, - "ToggleCertificatesRequest": { - "type": "object", - "properties": { - "certificate_ids": { - "type": "array", - "items": { - "type": "string", - "example": "cert_abc" - }, - "minItems": 1, - "maxItems": 10 - } - }, - "required": [ - "certificate_ids" - ] - }, - "Tool": { - "description": "A tool that can be used to generate a response.\n", - "discriminator": { - "propertyName": "type" - }, - "anyOf": [ - { - "$ref": "#/components/schemas/FunctionTool" - }, - { - "$ref": "#/components/schemas/FileSearchTool" - }, - { - "$ref": "#/components/schemas/ComputerUsePreviewTool" - }, - { - "$ref": "#/components/schemas/WebSearchTool" - }, - { - "$ref": "#/components/schemas/MCPTool" - }, - { - "$ref": "#/components/schemas/CodeInterpreterTool" - }, - { - "$ref": "#/components/schemas/ImageGenTool" - }, - { - "$ref": "#/components/schemas/LocalShellTool" - }, - { - "$ref": "#/components/schemas/CustomTool" - }, - { - "$ref": "#/components/schemas/WebSearchPreviewTool" - } - ] - }, - "ToolChoiceAllowed": { - "type": "object", - "title": "Allowed tools", - "description": "Constrains the tools available to the model to a pre-defined set.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "allowed_tools" - ], - "description": "Allowed tool configuration type. Always `allowed_tools`.", - "x-stainless-const": true - }, - "mode": { - "type": "string", - "enum": [ - "auto", - "required" - ], - "description": "Constrains the tools available to the model to a pre-defined set.\n\n`auto` allows the model to pick from among the allowed tools and generate a\nmessage.\n\n`required` requires the model to call one or more of the allowed tools.\n" - }, - "tools": { - "type": "array", - "description": "A list of tool definitions that the model should be allowed to call.\n\nFor the Responses API, the list of tool definitions might look like:\n```json\n[\n { \"type\": \"function\", \"name\": \"get_weather\" },\n { \"type\": \"mcp\", \"server_label\": \"deepwiki\" },\n { \"type\": \"image_generation\" }\n]\n```\n", - "items": { - "type": "object", - "description": "A tool definition that the model should be allowed to call.\n", - "additionalProperties": true, - "x-oaiExpandable": false - } - } - }, - "required": [ - "type", - "mode", - "tools" - ] - }, - "ToolChoiceCustom": { - "type": "object", - "title": "Custom tool", - "description": "Use this option to force the model to call a specific custom tool.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "custom" - ], - "description": "For custom tool calling, the type is always `custom`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the custom tool to call." - } - }, - "required": [ - "type", - "name" - ] - }, - "ToolChoiceFunction": { - "type": "object", - "title": "Function tool", - "description": "Use this option to force the model to call a specific function.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "For function calling, the type is always `function`.", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the function to call." - } - }, - "required": [ - "type", - "name" - ] - }, - "ToolChoiceMCP": { - "type": "object", - "title": "MCP tool", - "description": "Use this option to force the model to call a specific tool on a remote MCP server.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "mcp" - ], - "description": "For MCP tools, the type is always `mcp`.", - "x-stainless-const": true - }, - "server_label": { - "type": "string", - "description": "The label of the MCP server to use.\n" - }, - "name": { - "type": "string", - "description": "The name of the tool to call on the server.\n", - "nullable": true - } - }, - "required": [ - "type", - "server_label" - ] - }, - "ToolChoiceOptions": { - "type": "string", - "title": "Tool choice mode", - "description": "Controls which (if any) tool is called by the model.\n\n`none` means the model will not call any tool and instead generates a message.\n\n`auto` means the model can pick between generating a message or calling one or\nmore tools.\n\n`required` means the model must call one or more tools.\n", - "enum": [ - "none", - "auto", - "required" - ] - }, - "ToolChoiceTypes": { - "type": "object", - "title": "Hosted tool", - "description": "Indicates that the model should use a built-in tool to generate a response.\n[Learn more about built-in tools](https://platform.openai.com/docs/guides/tools).\n", - "properties": { - "type": { - "type": "string", - "description": "The type of hosted tool the model should to use. Learn more about\n[built-in tools](https://platform.openai.com/docs/guides/tools).\n\nAllowed values are:\n- `file_search`\n- `web_search_preview`\n- `computer_use_preview`\n- `code_interpreter`\n- `image_generation`\n", - "enum": [ - "file_search", - "web_search_preview", - "computer_use_preview", - "web_search_preview_2025_03_11", - "image_generation", - "code_interpreter" - ] - } - }, - "required": [ - "type" - ] - }, - "TranscriptTextDeltaEvent": { - "type": "object", - "description": "Emitted when there is an additional text delta. This is also the first event emitted when the transcription starts. Only emitted when you [create a transcription](https://platform.openai.com/docs/api-reference/audio/create-transcription) with the `Stream` parameter set to `true`.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `transcript.text.delta`.\n", - "enum": [ - "transcript.text.delta" - ], - "x-stainless-const": true - }, - "delta": { - "type": "string", - "description": "The text delta that was additionally transcribed.\n" - }, - "logprobs": { - "type": "array", - "description": "The log probabilities of the delta. Only included if you [create a transcription](https://platform.openai.com/docs/api-reference/audio/create-transcription) with the `include[]` parameter set to `logprobs`.\n", - "items": { - "type": "object", - "properties": { - "token": { - "type": "string", - "description": "The token that was used to generate the log probability.\n" - }, - "logprob": { - "type": "number", - "description": "The log probability of the token.\n" - }, - "bytes": { - "type": "array", - "items": { - "type": "integer" - }, - "description": "The bytes that were used to generate the log probability.\n" - } - } - } - } - }, - "required": [ - "type", - "delta" - ], - "x-oaiMeta": { - "name": "Stream Event (transcript.text.delta)", - "group": "transcript", - "example": "{\n \"type\": \"transcript.text.delta\",\n \"delta\": \" wonderful\"\n}\n" - } - }, - "TranscriptTextDoneEvent": { - "type": "object", - "description": "Emitted when the transcription is complete. Contains the complete transcription text. Only emitted when you [create a transcription](https://platform.openai.com/docs/api-reference/audio/create-transcription) with the `Stream` parameter set to `true`.", - "properties": { - "type": { - "type": "string", - "description": "The type of the event. Always `transcript.text.done`.\n", - "enum": [ - "transcript.text.done" - ], - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text that was transcribed.\n" - }, - "logprobs": { - "type": "array", - "description": "The log probabilities of the individual tokens in the transcription. Only included if you [create a transcription](https://platform.openai.com/docs/api-reference/audio/create-transcription) with the `include[]` parameter set to `logprobs`.\n", - "items": { - "type": "object", - "properties": { - "token": { - "type": "string", - "description": "The token that was used to generate the log probability.\n" - }, - "logprob": { - "type": "number", - "description": "The log probability of the token.\n" - }, - "bytes": { - "type": "array", - "items": { - "type": "integer" - }, - "description": "The bytes that were used to generate the log probability.\n" - } - } - } - }, - "usage": { - "$ref": "#/components/schemas/TranscriptTextUsageTokens" - } - }, - "required": [ - "type", - "text" - ], - "x-oaiMeta": { - "name": "Stream Event (transcript.text.done)", - "group": "transcript", - "example": "{\n \"type\": \"transcript.text.done\",\n \"text\": \"I see skies of blue and clouds of white, the bright blessed days, the dark sacred nights, and I think to myself, what a wonderful world.\",\n \"usage\": {\n \"type\": \"tokens\",\n \"input_tokens\": 14,\n \"input_token_details\": {\n \"text_tokens\": 10,\n \"audio_tokens\": 4\n },\n \"output_tokens\": 31,\n \"total_tokens\": 45\n }\n}\n" - } - }, - "TranscriptTextUsageDuration": { - "type": "object", - "title": "Duration Usage", - "description": "Usage statistics for models billed by audio input duration.", - "properties": { - "type": { - "type": "string", - "enum": [ - "duration" - ], - "description": "The type of the usage object. Always `duration` for this variant.", - "x-stainless-const": true - }, - "seconds": { - "type": "number", - "description": "Duration of the input audio in seconds." - } - }, - "required": [ - "type", - "seconds" - ] - }, - "TranscriptTextUsageTokens": { - "type": "object", - "title": "Token Usage", - "description": "Usage statistics for models billed by token usage.", - "properties": { - "type": { - "type": "string", - "enum": [ - "tokens" - ], - "description": "The type of the usage object. Always `tokens` for this variant.", - "x-stainless-const": true - }, - "input_tokens": { - "type": "integer", - "description": "Number of input tokens billed for this request." - }, - "input_token_details": { - "type": "object", - "description": "Details about the input tokens billed for this request.", - "properties": { - "text_tokens": { - "type": "integer", - "description": "Number of text tokens billed for this request." - }, - "audio_tokens": { - "type": "integer", - "description": "Number of audio tokens billed for this request." - } - } - }, - "output_tokens": { - "type": "integer", - "description": "Number of output tokens generated." - }, - "total_tokens": { - "type": "integer", - "description": "Total number of tokens used (input + output)." - } - }, - "required": [ - "type", - "input_tokens", - "output_tokens", - "total_tokens" - ] - }, - "TranscriptionChunkingStrategy": { - "description": "Controls how the audio is cut into chunks. When set to `\"auto\"`, the server first normalizes loudness and then uses voice activity detection (VAD) to choose boundaries. `server_vad` object can be provided to tweak VAD detection parameters manually. If unset, the audio is transcribed as a single block.", - "anyOf": [ - { - "type": "string", - "enum": [ - "auto" - ], - "description": "Automatically set chunking parameters based on the audio. Must be set to `\"auto\"`.\n", - "x-stainless-const": true - }, - { - "$ref": "#/components/schemas/VadConfig" - } - ], - "nullable": true, - "x-oaiTypeLabel": "string" - }, - "TranscriptionInclude": { - "type": "string", - "enum": [ - "logprobs" - ] - }, - "TranscriptionSegment": { - "type": "object", - "properties": { - "id": { - "type": "integer", - "description": "Unique identifier of the segment." - }, - "seek": { - "type": "integer", - "description": "Seek offset of the segment." - }, - "start": { - "type": "number", - "format": "float", - "description": "Start time of the segment in seconds." - }, - "end": { - "type": "number", - "format": "float", - "description": "End time of the segment in seconds." - }, - "text": { - "type": "string", - "description": "Text content of the segment." - }, - "tokens": { - "type": "array", - "items": { - "type": "integer" - }, - "description": "Array of token IDs for the text content." - }, - "temperature": { - "type": "number", - "format": "float", - "description": "Temperature parameter used for generating the segment." - }, - "avg_logprob": { - "type": "number", - "format": "float", - "description": "Average logprob of the segment. If the value is lower than -1, consider the logprobs failed." - }, - "compression_ratio": { - "type": "number", - "format": "float", - "description": "Compression ratio of the segment. If the value is greater than 2.4, consider the compression failed." - }, - "no_speech_prob": { - "type": "number", - "format": "float", - "description": "Probability of no speech in the segment. If the value is higher than 1.0 and the `avg_logprob` is below -1, consider this segment silent." - } - }, - "required": [ - "id", - "seek", - "start", - "end", - "text", - "tokens", - "temperature", - "avg_logprob", - "compression_ratio", - "no_speech_prob" - ] - }, - "TranscriptionWord": { - "type": "object", - "properties": { - "word": { - "type": "string", - "description": "The text content of the word." - }, - "start": { - "type": "number", - "format": "float", - "description": "Start time of the word in seconds." - }, - "end": { - "type": "number", - "format": "float", - "description": "End time of the word in seconds." - } - }, - "required": [ - "word", - "start", - "end" - ] - }, - "TruncationObject": { - "type": "object", - "title": "Thread Truncation Controls", - "description": "Controls for how a thread will be truncated prior to the run. Use this to control the initial context window of the run.", - "properties": { - "type": { - "type": "string", - "description": "The truncation strategy to use for the thread. The default is `auto`. If set to `last_messages`, the thread will be truncated to the n most recent messages in the thread. When set to `auto`, messages in the middle of the thread will be dropped to fit the context length of the model, `max_prompt_tokens`.", - "enum": [ - "auto", - "last_messages" - ] - }, - "last_messages": { - "type": "integer", - "description": "The number of most recent messages from the thread when constructing the context for the run.", - "minimum": 1, - "nullable": true - } - }, - "required": [ - "type" - ] - }, - "Type": { - "type": "object", - "title": "Type", - "description": "An action to type in text.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "type" - ], - "default": "type", - "description": "Specifies the event type. For a type action, this property is \nalways set to `type`.\n", - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text to type.\n" - } - }, - "required": [ - "type", - "text" - ] - }, - "UpdateVectorStoreFileAttributesRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "attributes": { - "$ref": "#/components/schemas/VectorStoreFileAttributes" - } - }, - "required": [ - "attributes" - ], - "x-oaiMeta": { - "name": "Update vector store file attributes request" - } - }, - "UpdateVectorStoreRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "name": { - "description": "The name of the vector store.", - "type": "string", - "nullable": true - }, - "expires_after": { - "allOf": [ - { - "$ref": "#/components/schemas/VectorStoreExpirationAfter" - }, - { - "nullable": true - } - ] - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - } - }, - "Upload": { - "type": "object", - "title": "Upload", - "description": "The Upload object can accept byte chunks in the form of Parts.\n", - "properties": { - "id": { - "type": "string", - "description": "The Upload unique identifier, which can be referenced in API endpoints." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the Upload was created." - }, - "filename": { - "type": "string", - "description": "The name of the file to be uploaded." - }, - "bytes": { - "type": "integer", - "description": "The intended number of bytes to be uploaded." - }, - "purpose": { - "type": "string", - "description": "The intended purpose of the file. [Please refer here](https://platform.openai.com/docs/api-reference/files/object#files/object-purpose) for acceptable values." - }, - "status": { - "type": "string", - "description": "The status of the Upload.", - "enum": [ - "pending", - "completed", - "cancelled", - "expired" - ] - }, - "expires_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the Upload will expire." - }, - "object": { - "type": "string", - "description": "The object type, which is always \"upload\".", - "enum": [ - "upload" - ], - "x-stainless-const": true - }, - "file": { - "allOf": [ - { - "$ref": "#/components/schemas/OpenAIFile" - }, - { - "nullable": true, - "description": "The ready File object after the Upload is completed." - } - ] - } - }, - "required": [ - "bytes", - "created_at", - "expires_at", - "filename", - "id", - "purpose", - "status", - "object" - ], - "x-oaiMeta": { - "name": "The upload object", - "example": "{\n \"id\": \"upload_abc123\",\n \"object\": \"upload\",\n \"bytes\": 2147483648,\n \"created_at\": 1719184911,\n \"filename\": \"training_examples.jsonl\",\n \"purpose\": \"fine-tune\",\n \"status\": \"completed\",\n \"expires_at\": 1719127296,\n \"file\": {\n \"id\": \"file-xyz321\",\n \"object\": \"file\",\n \"bytes\": 2147483648,\n \"created_at\": 1719186911,\n \"filename\": \"training_examples.jsonl\",\n \"purpose\": \"fine-tune\",\n }\n}\n" - } - }, - "UploadCertificateRequest": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "An optional name for the certificate" - }, - "content": { - "type": "string", - "description": "The certificate content in PEM format" - } - }, - "required": [ - "content" - ] - }, - "UploadPart": { - "type": "object", - "title": "UploadPart", - "description": "The upload Part represents a chunk of bytes we can add to an Upload object.\n", - "properties": { - "id": { - "type": "string", - "description": "The upload Part unique identifier, which can be referenced in API endpoints." - }, - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) for when the Part was created." - }, - "upload_id": { - "type": "string", - "description": "The ID of the Upload object that this Part was added to." - }, - "object": { - "type": "string", - "description": "The object type, which is always `upload.part`.", - "enum": [ - "upload.part" - ], - "x-stainless-const": true - } - }, - "required": [ - "created_at", - "id", - "object", - "upload_id" - ], - "x-oaiMeta": { - "name": "The upload part object", - "example": "{\n \"id\": \"part_def456\",\n \"object\": \"upload.part\",\n \"created_at\": 1719186911,\n \"upload_id\": \"upload_abc123\"\n}\n" - } - }, - "UsageAudioSpeechesResult": { - "type": "object", - "description": "The aggregated audio speeches usage details of the specific time bucket.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.usage.audio_speeches.result" - ], - "x-stainless-const": true - }, - "characters": { - "type": "integer", - "description": "The number of characters processed." - }, - "num_model_requests": { - "type": "integer", - "description": "The count of requests made to the model." - }, - "project_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=project_id`, this field provides the project ID of the grouped usage result." - }, - "user_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=user_id`, this field provides the user ID of the grouped usage result." - }, - "api_key_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result." - }, - "model": { - "type": "string", - "nullable": true, - "description": "When `group_by=model`, this field provides the model name of the grouped usage result." - } - }, - "required": [ - "object", - "characters", - "num_model_requests" - ], - "x-oaiMeta": { - "name": "Audio speeches usage object", - "example": "{\n \"object\": \"organization.usage.audio_speeches.result\",\n \"characters\": 45,\n \"num_model_requests\": 1,\n \"project_id\": \"proj_abc\",\n \"user_id\": \"user-abc\",\n \"api_key_id\": \"key_abc\",\n \"model\": \"tts-1\"\n}\n" - } - }, - "UsageAudioTranscriptionsResult": { - "type": "object", - "description": "The aggregated audio transcriptions usage details of the specific time bucket.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.usage.audio_transcriptions.result" - ], - "x-stainless-const": true - }, - "seconds": { - "type": "integer", - "description": "The number of seconds processed." - }, - "num_model_requests": { - "type": "integer", - "description": "The count of requests made to the model." - }, - "project_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=project_id`, this field provides the project ID of the grouped usage result." - }, - "user_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=user_id`, this field provides the user ID of the grouped usage result." - }, - "api_key_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result." - }, - "model": { - "type": "string", - "nullable": true, - "description": "When `group_by=model`, this field provides the model name of the grouped usage result." - } - }, - "required": [ - "object", - "seconds", - "num_model_requests" - ], - "x-oaiMeta": { - "name": "Audio transcriptions usage object", - "example": "{\n \"object\": \"organization.usage.audio_transcriptions.result\",\n \"seconds\": 10,\n \"num_model_requests\": 1,\n \"project_id\": \"proj_abc\",\n \"user_id\": \"user-abc\",\n \"api_key_id\": \"key_abc\",\n \"model\": \"tts-1\"\n}\n" - } - }, - "UsageCodeInterpreterSessionsResult": { - "type": "object", - "description": "The aggregated code interpreter sessions usage details of the specific time bucket.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.usage.code_interpreter_sessions.result" - ], - "x-stainless-const": true - }, - "num_sessions": { - "type": "integer", - "description": "The number of code interpreter sessions." - }, - "project_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=project_id`, this field provides the project ID of the grouped usage result." - } - }, - "required": [ - "object", - "sessions" - ], - "x-oaiMeta": { - "name": "Code interpreter sessions usage object", - "example": "{\n \"object\": \"organization.usage.code_interpreter_sessions.result\",\n \"num_sessions\": 1,\n \"project_id\": \"proj_abc\"\n}\n" - } - }, - "UsageCompletionsResult": { - "type": "object", - "description": "The aggregated completions usage details of the specific time bucket.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.usage.completions.result" - ], - "x-stainless-const": true - }, - "input_tokens": { - "type": "integer", - "description": "The aggregated number of text input tokens used, including cached tokens. For customers subscribe to scale tier, this includes scale tier tokens." - }, - "input_cached_tokens": { - "type": "integer", - "description": "The aggregated number of text input tokens that has been cached from previous requests. For customers subscribe to scale tier, this includes scale tier tokens." - }, - "output_tokens": { - "type": "integer", - "description": "The aggregated number of text output tokens used. For customers subscribe to scale tier, this includes scale tier tokens." - }, - "input_audio_tokens": { - "type": "integer", - "description": "The aggregated number of audio input tokens used, including cached tokens." - }, - "output_audio_tokens": { - "type": "integer", - "description": "The aggregated number of audio output tokens used." - }, - "num_model_requests": { - "type": "integer", - "description": "The count of requests made to the model." - }, - "project_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=project_id`, this field provides the project ID of the grouped usage result." - }, - "user_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=user_id`, this field provides the user ID of the grouped usage result." - }, - "api_key_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result." - }, - "model": { - "type": "string", - "nullable": true, - "description": "When `group_by=model`, this field provides the model name of the grouped usage result." - }, - "batch": { - "type": "boolean", - "nullable": true, - "description": "When `group_by=batch`, this field tells whether the grouped usage result is batch or not." - } - }, - "required": [ - "object", - "input_tokens", - "output_tokens", - "num_model_requests" - ], - "x-oaiMeta": { - "name": "Completions usage object", - "example": "{\n \"object\": \"organization.usage.completions.result\",\n \"input_tokens\": 5000,\n \"output_tokens\": 1000,\n \"input_cached_tokens\": 4000,\n \"input_audio_tokens\": 300,\n \"output_audio_tokens\": 200,\n \"num_model_requests\": 5,\n \"project_id\": \"proj_abc\",\n \"user_id\": \"user-abc\",\n \"api_key_id\": \"key_abc\",\n \"model\": \"gpt-4o-mini-2024-07-18\",\n \"batch\": false\n}\n" - } - }, - "UsageEmbeddingsResult": { - "type": "object", - "description": "The aggregated embeddings usage details of the specific time bucket.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.usage.embeddings.result" - ], - "x-stainless-const": true - }, - "input_tokens": { - "type": "integer", - "description": "The aggregated number of input tokens used." - }, - "num_model_requests": { - "type": "integer", - "description": "The count of requests made to the model." - }, - "project_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=project_id`, this field provides the project ID of the grouped usage result." - }, - "user_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=user_id`, this field provides the user ID of the grouped usage result." - }, - "api_key_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result." - }, - "model": { - "type": "string", - "nullable": true, - "description": "When `group_by=model`, this field provides the model name of the grouped usage result." - } - }, - "required": [ - "object", - "input_tokens", - "num_model_requests" - ], - "x-oaiMeta": { - "name": "Embeddings usage object", - "example": "{\n \"object\": \"organization.usage.embeddings.result\",\n \"input_tokens\": 20,\n \"num_model_requests\": 2,\n \"project_id\": \"proj_abc\",\n \"user_id\": \"user-abc\",\n \"api_key_id\": \"key_abc\",\n \"model\": \"text-embedding-ada-002-v2\"\n}\n" - } - }, - "UsageImagesResult": { - "type": "object", - "description": "The aggregated images usage details of the specific time bucket.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.usage.images.result" - ], - "x-stainless-const": true - }, - "images": { - "type": "integer", - "description": "The number of images processed." - }, - "num_model_requests": { - "type": "integer", - "description": "The count of requests made to the model." - }, - "source": { - "type": "string", - "nullable": true, - "description": "When `group_by=source`, this field provides the source of the grouped usage result, possible values are `image.generation`, `image.edit`, `image.variation`." - }, - "size": { - "type": "string", - "nullable": true, - "description": "When `group_by=size`, this field provides the image size of the grouped usage result." - }, - "project_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=project_id`, this field provides the project ID of the grouped usage result." - }, - "user_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=user_id`, this field provides the user ID of the grouped usage result." - }, - "api_key_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result." - }, - "model": { - "type": "string", - "nullable": true, - "description": "When `group_by=model`, this field provides the model name of the grouped usage result." - } - }, - "required": [ - "object", - "images", - "num_model_requests" - ], - "x-oaiMeta": { - "name": "Images usage object", - "example": "{\n \"object\": \"organization.usage.images.result\",\n \"images\": 2,\n \"num_model_requests\": 2,\n \"size\": \"1024x1024\",\n \"source\": \"image.generation\",\n \"project_id\": \"proj_abc\",\n \"user_id\": \"user-abc\",\n \"api_key_id\": \"key_abc\",\n \"model\": \"dall-e-3\"\n}\n" - } - }, - "UsageModerationsResult": { - "type": "object", - "description": "The aggregated moderations usage details of the specific time bucket.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.usage.moderations.result" - ], - "x-stainless-const": true - }, - "input_tokens": { - "type": "integer", - "description": "The aggregated number of input tokens used." - }, - "num_model_requests": { - "type": "integer", - "description": "The count of requests made to the model." - }, - "project_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=project_id`, this field provides the project ID of the grouped usage result." - }, - "user_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=user_id`, this field provides the user ID of the grouped usage result." - }, - "api_key_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result." - }, - "model": { - "type": "string", - "nullable": true, - "description": "When `group_by=model`, this field provides the model name of the grouped usage result." - } - }, - "required": [ - "object", - "input_tokens", - "num_model_requests" - ], - "x-oaiMeta": { - "name": "Moderations usage object", - "example": "{\n \"object\": \"organization.usage.moderations.result\",\n \"input_tokens\": 20,\n \"num_model_requests\": 2,\n \"project_id\": \"proj_abc\",\n \"user_id\": \"user-abc\",\n \"api_key_id\": \"key_abc\",\n \"model\": \"text-moderation\"\n}\n" - } - }, - "UsageResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "page" - ], - "x-stainless-const": true - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/UsageTimeBucket" - } - }, - "has_more": { - "type": "boolean" - }, - "next_page": { - "type": "string" - } - }, - "required": [ - "object", - "data", - "has_more", - "next_page" - ] - }, - "UsageTimeBucket": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "bucket" - ], - "x-stainless-const": true - }, - "start_time": { - "type": "integer" - }, - "end_time": { - "type": "integer" - }, - "result": { - "type": "array", - "items": { - "anyOf": [ - { - "$ref": "#/components/schemas/UsageCompletionsResult" - }, - { - "$ref": "#/components/schemas/UsageEmbeddingsResult" - }, - { - "$ref": "#/components/schemas/UsageModerationsResult" - }, - { - "$ref": "#/components/schemas/UsageImagesResult" - }, - { - "$ref": "#/components/schemas/UsageAudioSpeechesResult" - }, - { - "$ref": "#/components/schemas/UsageAudioTranscriptionsResult" - }, - { - "$ref": "#/components/schemas/UsageVectorStoresResult" - }, - { - "$ref": "#/components/schemas/UsageCodeInterpreterSessionsResult" - }, - { - "$ref": "#/components/schemas/CostsResult" - } - ], - "discriminator": { - "propertyName": "object" - } - } - } - }, - "required": [ - "object", - "start_time", - "end_time", - "result" - ] - }, - "UsageVectorStoresResult": { - "type": "object", - "description": "The aggregated vector stores usage details of the specific time bucket.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.usage.vector_stores.result" - ], - "x-stainless-const": true - }, - "usage_bytes": { - "type": "integer", - "description": "The vector stores usage in bytes." - }, - "project_id": { - "type": "string", - "nullable": true, - "description": "When `group_by=project_id`, this field provides the project ID of the grouped usage result." - } - }, - "required": [ - "object", - "usage_bytes" - ], - "x-oaiMeta": { - "name": "Vector stores usage object", - "example": "{\n \"object\": \"organization.usage.vector_stores.result\",\n \"usage_bytes\": 1024,\n \"project_id\": \"proj_abc\"\n}\n" - } - }, - "User": { - "type": "object", - "description": "Represents an individual `user` within an organization.", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.user" - ], - "description": "The object type, which is always `organization.user`", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The identifier, which can be referenced in API endpoints" - }, - "name": { - "type": "string", - "description": "The name of the user" - }, - "email": { - "type": "string", - "description": "The email address of the user" - }, - "role": { - "type": "string", - "enum": [ - "owner", - "reader" - ], - "description": "`owner` or `reader`" - }, - "added_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the user was added." - } - }, - "required": [ - "object", - "id", - "name", - "email", - "role", - "added_at" - ], - "x-oaiMeta": { - "name": "The user object", - "example": "{\n \"object\": \"organization.user\",\n \"id\": \"user_abc\",\n \"name\": \"First Last\",\n \"email\": \"user@example.com\",\n \"role\": \"owner\",\n \"added_at\": 1711471533\n}\n" - } - }, - "UserDeleteResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "organization.user.deleted" - ], - "x-stainless-const": true - }, - "id": { - "type": "string" - }, - "deleted": { - "type": "boolean" - } - }, - "required": [ - "object", - "id", - "deleted" - ] - }, - "UserListResponse": { - "type": "object", - "properties": { - "object": { - "type": "string", - "enum": [ - "list" - ], - "x-stainless-const": true - }, - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/User" - } - }, - "first_id": { - "type": "string" - }, - "last_id": { - "type": "string" - }, - "has_more": { - "type": "boolean" - } - }, - "required": [ - "object", - "data", - "first_id", - "last_id", - "has_more" - ] - }, - "UserRoleUpdateRequest": { - "type": "object", - "properties": { - "role": { - "type": "string", - "enum": [ - "owner", - "reader" - ], - "description": "`owner` or `reader`" - } - }, - "required": [ - "role" - ] - }, - "VadConfig": { - "type": "object", - "additionalProperties": false, - "required": [ - "type" - ], - "properties": { - "type": { - "type": "string", - "enum": [ - "server_vad" - ], - "description": "Must be set to `server_vad` to enable manual chunking using server side VAD." - }, - "prefix_padding_ms": { - "type": "integer", - "default": 300, - "description": "Amount of audio to include before the VAD detected speech (in \nmilliseconds).\n" - }, - "silence_duration_ms": { - "type": "integer", - "default": 200, - "description": "Duration of silence to detect speech stop (in milliseconds).\nWith shorter values the model will respond more quickly, \nbut may jump in on short pauses from the user.\n" - }, - "threshold": { - "type": "number", - "default": 0.5, - "description": "Sensitivity threshold (0.0 to 1.0) for voice activity detection. A \nhigher threshold will require louder audio to activate the model, and \nthus might perform better in noisy environments.\n" - } - } - }, - "ValidateGraderRequest": { - "type": "object", - "title": "ValidateGraderRequest", - "properties": { - "grader": { - "type": "object", - "description": "The grader used for the fine-tuning job.", - "anyOf": [ - { - "$ref": "#/components/schemas/GraderStringCheck" - }, - { - "$ref": "#/components/schemas/GraderTextSimilarity" - }, - { - "$ref": "#/components/schemas/GraderPython" - }, - { - "$ref": "#/components/schemas/GraderScoreModel" - }, - { - "$ref": "#/components/schemas/GraderMulti" - } - ] - } - }, - "required": [ - "grader" - ] - }, - "ValidateGraderResponse": { - "type": "object", - "title": "ValidateGraderResponse", - "properties": { - "grader": { - "type": "object", - "description": "The grader used for the fine-tuning job.", - "anyOf": [ - { - "$ref": "#/components/schemas/GraderStringCheck" - }, - { - "$ref": "#/components/schemas/GraderTextSimilarity" - }, - { - "$ref": "#/components/schemas/GraderPython" - }, - { - "$ref": "#/components/schemas/GraderScoreModel" - }, - { - "$ref": "#/components/schemas/GraderMulti" - } - ] - } - } - }, - "VectorStoreExpirationAfter": { - "type": "object", - "title": "Vector store expiration policy", - "description": "The expiration policy for a vector store.", - "properties": { - "anchor": { - "description": "Anchor timestamp after which the expiration policy applies. Supported anchors: `last_active_at`.", - "type": "string", - "enum": [ - "last_active_at" - ], - "x-stainless-const": true - }, - "days": { - "description": "The number of days after the anchor time that the vector store will expire.", - "type": "integer", - "minimum": 1, - "maximum": 365 - } - }, - "required": [ - "anchor", - "days" - ] - }, - "VectorStoreFileAttributes": { - "type": "object", - "description": "Set of 16 key-value pairs that can be attached to an object. This can be \nuseful for storing additional information about the object in a structured \nformat, and querying for objects via API or the dashboard. Keys are strings \nwith a maximum length of 64 characters. Values are strings with a maximum \nlength of 512 characters, booleans, or numbers.\n", - "maxProperties": 16, - "propertyNames": { - "type": "string", - "maxLength": 64 - }, - "additionalProperties": { - "anyOf": [ - { - "type": "string", - "maxLength": 512 - }, - { - "type": "number" - }, - { - "type": "boolean" - } - ] - }, - "x-oaiTypeLabel": "map", - "nullable": true - }, - "VectorStoreFileBatchObject": { - "type": "object", - "title": "Vector store file batch", - "description": "A batch of files attached to a vector store.", - "properties": { - "id": { - "description": "The identifier, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `vector_store.file_batch`.", - "type": "string", - "enum": [ - "vector_store.files_batch" - ], - "x-stainless-const": true - }, - "created_at": { - "description": "The Unix timestamp (in seconds) for when the vector store files batch was created.", - "type": "integer" - }, - "vector_store_id": { - "description": "The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) that the [File](https://platform.openai.com/docs/api-reference/files) is attached to.", - "type": "string" - }, - "status": { - "description": "The status of the vector store files batch, which can be either `in_progress`, `completed`, `cancelled` or `failed`.", - "type": "string", - "enum": [ - "in_progress", - "completed", - "cancelled", - "failed" - ] - }, - "file_counts": { - "type": "object", - "properties": { - "in_progress": { - "description": "The number of files that are currently being processed.", - "type": "integer" - }, - "completed": { - "description": "The number of files that have been processed.", - "type": "integer" - }, - "failed": { - "description": "The number of files that have failed to process.", - "type": "integer" - }, - "cancelled": { - "description": "The number of files that where cancelled.", - "type": "integer" - }, - "total": { - "description": "The total number of files.", - "type": "integer" - } - }, - "required": [ - "in_progress", - "completed", - "cancelled", - "failed", - "total" - ] - } - }, - "required": [ - "id", - "object", - "created_at", - "vector_store_id", - "status", - "file_counts" - ], - "x-oaiMeta": { - "name": "The vector store files batch object", - "beta": true, - "example": "{\n \"id\": \"vsfb_123\",\n \"object\": \"vector_store.files_batch\",\n \"created_at\": 1698107661,\n \"vector_store_id\": \"vs_abc123\",\n \"status\": \"completed\",\n \"file_counts\": {\n \"in_progress\": 0,\n \"completed\": 100,\n \"failed\": 0,\n \"cancelled\": 0,\n \"total\": 100\n }\n}\n" - } - }, - "VectorStoreFileContentResponse": { - "type": "object", - "description": "Represents the parsed content of a vector store file.", - "properties": { - "object": { - "type": "string", - "enum": [ - "vector_store.file_content.page" - ], - "description": "The object type, which is always `vector_store.file_content.page`", - "x-stainless-const": true - }, - "data": { - "type": "array", - "description": "Parsed content of the file.", - "items": { - "type": "object", - "properties": { - "type": { - "type": "string", - "description": "The content type (currently only `\"text\"`)" - }, - "text": { - "type": "string", - "description": "The text content" - } - } - } - }, - "has_more": { - "type": "boolean", - "description": "Indicates if there are more content pages to fetch." - }, - "next_page": { - "type": "string", - "description": "The token for the next page, if any.", - "nullable": true - } - }, - "required": [ - "object", - "data", - "has_more", - "next_page" - ] - }, - "VectorStoreFileObject": { - "type": "object", - "title": "Vector store files", - "description": "A list of files attached to a vector store.", - "properties": { - "id": { - "description": "The identifier, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `vector_store.file`.", - "type": "string", - "enum": [ - "vector_store.file" - ], - "x-stainless-const": true - }, - "usage_bytes": { - "description": "The total vector store usage in bytes. Note that this may be different from the original file size.", - "type": "integer" - }, - "created_at": { - "description": "The Unix timestamp (in seconds) for when the vector store file was created.", - "type": "integer" - }, - "vector_store_id": { - "description": "The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) that the [File](https://platform.openai.com/docs/api-reference/files) is attached to.", - "type": "string" - }, - "status": { - "description": "The status of the vector store file, which can be either `in_progress`, `completed`, `cancelled`, or `failed`. The status `completed` indicates that the vector store file is ready for use.", - "type": "string", - "enum": [ - "in_progress", - "completed", - "cancelled", - "failed" - ] - }, - "last_error": { - "type": "object", - "description": "The last error associated with this vector store file. Will be `null` if there are no errors.", - "nullable": true, - "properties": { - "code": { - "type": "string", - "description": "One of `server_error` or `rate_limit_exceeded`.", - "enum": [ - "server_error", - "unsupported_file", - "invalid_file" - ] - }, - "message": { - "type": "string", - "description": "A human-readable description of the error." - } - }, - "required": [ - "code", - "message" - ] - }, - "chunking_strategy": { - "$ref": "#/components/schemas/ChunkingStrategyResponse" - }, - "attributes": { - "$ref": "#/components/schemas/VectorStoreFileAttributes" - } - }, - "required": [ - "id", - "object", - "usage_bytes", - "created_at", - "vector_store_id", - "status", - "last_error" - ], - "x-oaiMeta": { - "name": "The vector store file object", - "beta": true, - "example": "{\n \"id\": \"file-abc123\",\n \"object\": \"vector_store.file\",\n \"usage_bytes\": 1234,\n \"created_at\": 1698107661,\n \"vector_store_id\": \"vs_abc123\",\n \"status\": \"completed\",\n \"last_error\": null,\n \"chunking_strategy\": {\n \"type\": \"static\",\n \"static\": {\n \"max_chunk_size_tokens\": 800,\n \"chunk_overlap_tokens\": 400\n }\n }\n}\n" - } - }, - "VectorStoreObject": { - "type": "object", - "title": "Vector store", - "description": "A vector store is a collection of processed files can be used by the `file_search` tool.", - "properties": { - "id": { - "description": "The identifier, which can be referenced in API endpoints.", - "type": "string" - }, - "object": { - "description": "The object type, which is always `vector_store`.", - "type": "string", - "enum": [ - "vector_store" - ], - "x-stainless-const": true - }, - "created_at": { - "description": "The Unix timestamp (in seconds) for when the vector store was created.", - "type": "integer" - }, - "name": { - "description": "The name of the vector store.", - "type": "string" - }, - "usage_bytes": { - "description": "The total number of bytes used by the files in the vector store.", - "type": "integer" - }, - "file_counts": { - "type": "object", - "properties": { - "in_progress": { - "description": "The number of files that are currently being processed.", - "type": "integer" - }, - "completed": { - "description": "The number of files that have been successfully processed.", - "type": "integer" - }, - "failed": { - "description": "The number of files that have failed to process.", - "type": "integer" - }, - "cancelled": { - "description": "The number of files that were cancelled.", - "type": "integer" - }, - "total": { - "description": "The total number of files.", - "type": "integer" - } - }, - "required": [ - "in_progress", - "completed", - "failed", - "cancelled", - "total" - ] - }, - "status": { - "description": "The status of the vector store, which can be either `expired`, `in_progress`, or `completed`. A status of `completed` indicates that the vector store is ready for use.", - "type": "string", - "enum": [ - "expired", - "in_progress", - "completed" - ] - }, - "expires_after": { - "$ref": "#/components/schemas/VectorStoreExpirationAfter" - }, - "expires_at": { - "description": "The Unix timestamp (in seconds) for when the vector store will expire.", - "type": "integer", - "nullable": true - }, - "last_active_at": { - "description": "The Unix timestamp (in seconds) for when the vector store was last active.", - "type": "integer", - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - } - }, - "required": [ - "id", - "object", - "usage_bytes", - "created_at", - "status", - "last_active_at", - "name", - "file_counts", - "metadata" - ], - "x-oaiMeta": { - "name": "The vector store object", - "example": "{\n \"id\": \"vs_123\",\n \"object\": \"vector_store\",\n \"created_at\": 1698107661,\n \"usage_bytes\": 123456,\n \"last_active_at\": 1698107661,\n \"name\": \"my_vector_store\",\n \"status\": \"completed\",\n \"file_counts\": {\n \"in_progress\": 0,\n \"completed\": 100,\n \"cancelled\": 0,\n \"failed\": 0,\n \"total\": 100\n },\n \"last_used_at\": 1698107661\n}\n" - } - }, - "VectorStoreSearchRequest": { - "type": "object", - "additionalProperties": false, - "properties": { - "query": { - "description": "A query string for a search", - "anyOf": [ - { - "type": "string" - }, - { - "type": "array", - "items": { - "type": "string", - "description": "A list of queries to search for.", - "minItems": 1 - } - } - ] - }, - "rewrite_query": { - "description": "Whether to rewrite the natural language query for vector search.", - "type": "boolean", - "default": false - }, - "max_num_results": { - "description": "The maximum number of results to return. This number should be between 1 and 50 inclusive.", - "type": "integer", - "default": 10, - "minimum": 1, - "maximum": 50 - }, - "filters": { - "description": "A filter to apply based on file attributes.", - "anyOf": [ - { - "$ref": "#/components/schemas/ComparisonFilter" - }, - { - "$ref": "#/components/schemas/CompoundFilter" - } - ] - }, - "ranking_options": { - "description": "Ranking options for search.", - "type": "object", - "additionalProperties": false, - "properties": { - "ranker": { - "description": "Enable re-ranking; set to `none` to disable, which can help reduce latency.", - "type": "string", - "enum": [ - "none", - "auto", - "default-2024-11-15" - ], - "default": "auto" - }, - "score_threshold": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 0 - } - } - } - }, - "required": [ - "query" - ], - "x-oaiMeta": { - "name": "Vector store search request" - } - }, - "VectorStoreSearchResultContentObject": { - "type": "object", - "additionalProperties": false, - "properties": { - "type": { - "description": "The type of content.", - "type": "string", - "enum": [ - "text" - ] - }, - "text": { - "description": "The text content returned from search.", - "type": "string" - } - }, - "required": [ - "type", - "text" - ], - "x-oaiMeta": { - "name": "Vector store search result content object" - } - }, - "VectorStoreSearchResultItem": { - "type": "object", - "additionalProperties": false, - "properties": { - "file_id": { - "type": "string", - "description": "The ID of the vector store file." - }, - "filename": { - "type": "string", - "description": "The name of the vector store file." - }, - "score": { - "type": "number", - "description": "The similarity score for the result.", - "minimum": 0, - "maximum": 1 - }, - "attributes": { - "$ref": "#/components/schemas/VectorStoreFileAttributes" - }, - "content": { - "type": "array", - "description": "Content chunks from the file.", - "items": { - "$ref": "#/components/schemas/VectorStoreSearchResultContentObject" - } - } - }, - "required": [ - "file_id", - "filename", - "score", - "attributes", - "content" - ], - "x-oaiMeta": { - "name": "Vector store search result item" - } - }, - "VectorStoreSearchResultsPage": { - "type": "object", - "additionalProperties": false, - "properties": { - "object": { - "type": "string", - "enum": [ - "vector_store.search_results.page" - ], - "description": "The object type, which is always `vector_store.search_results.page`", - "x-stainless-const": true - }, - "search_query": { - "type": "array", - "items": { - "type": "string", - "description": "The query used for this search.", - "minItems": 1 - } - }, - "data": { - "type": "array", - "description": "The list of search result items.", - "items": { - "$ref": "#/components/schemas/VectorStoreSearchResultItem" - } - }, - "has_more": { - "type": "boolean", - "description": "Indicates if there are more results to fetch." - }, - "next_page": { - "type": "string", - "description": "The token for the next page, if any.", - "nullable": true - } - }, - "required": [ - "object", - "search_query", - "data", - "has_more", - "next_page" - ], - "x-oaiMeta": { - "name": "Vector store search results page" - } - }, - "Verbosity": { - "type": "string", - "enum": [ - "low", - "medium", - "high" - ], - "default": "medium", - "nullable": true, - "description": "Constrains the verbosity of the model's response. Lower values will result in\nmore concise responses, while higher values will result in more verbose responses.\nCurrently supported values are `low`, `medium`, and `high`.\n" - }, - "VoiceIdsShared": { - "example": "ash", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "alloy", - "ash", - "ballad", - "coral", - "echo", - "sage", - "shimmer", - "verse", - "marin", - "cedar" - ] - } - ] - }, - "Wait": { - "type": "object", - "title": "Wait", - "description": "A wait action.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "wait" - ], - "default": "wait", - "description": "Specifies the event type. For a wait action, this property is \nalways set to `wait`.\n", - "x-stainless-const": true - } - }, - "required": [ - "type" - ] - }, - "WebSearchActionFind": { - "type": "object", - "title": "Find action", - "description": "Action type \"find\": Searches for a pattern within a loaded page.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "find" - ], - "description": "The action type.\n", - "x-stainless-const": true - }, - "url": { - "type": "string", - "format": "uri", - "description": "The URL of the page searched for the pattern.\n" - }, - "pattern": { - "type": "string", - "description": "The pattern or text to search for within the page.\n" - } - }, - "required": [ - "type", - "url", - "pattern" - ] - }, - "WebSearchActionOpenPage": { - "type": "object", - "title": "Open page action", - "description": "Action type \"open_page\" - Opens a specific URL from search results.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "open_page" - ], - "description": "The action type.\n", - "x-stainless-const": true - }, - "url": { - "type": "string", - "format": "uri", - "description": "The URL opened by the model.\n" - } - }, - "required": [ - "type", - "url" - ] - }, - "WebSearchActionSearch": { - "type": "object", - "title": "Search action", - "description": "Action type \"search\" - Performs a web search query.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "search" - ], - "description": "The action type.\n", - "x-stainless-const": true - }, - "query": { - "type": "string", - "description": "The search query.\n" - }, - "sources": { - "type": "array", - "title": "Web search sources", - "description": "The sources used in the search.\n", - "items": { - "type": "object", - "title": "Web search source", - "description": "A source used in the search.\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "url" - ], - "description": "The type of source. Always `url`.\n", - "x-stainless-const": true - }, - "url": { - "type": "string", - "description": "The URL of the source.\n" - } - }, - "required": [ - "type", - "url" - ] - } - } - }, - "required": [ - "type", - "query" - ] - }, - "WebSearchApproximateLocation": { - "type": "object", - "title": "Web search approximate location", - "description": "The approximate location of the user.\n", - "nullable": true, - "properties": { - "type": { - "type": "string", - "enum": [ - "approximate" - ], - "description": "The type of location approximation. Always `approximate`.", - "default": "approximate", - "x-stainless-const": true - }, - "country": { - "type": "string", - "description": "The two-letter [ISO country code](https://en.wikipedia.org/wiki/ISO_3166-1) of the user, e.g. `US`.", - "nullable": true - }, - "region": { - "type": "string", - "description": "Free text input for the region of the user, e.g. `California`.", - "nullable": true - }, - "city": { - "type": "string", - "description": "Free text input for the city of the user, e.g. `San Francisco`.", - "nullable": true - }, - "timezone": { - "type": "string", - "description": "The [IANA timezone](https://timeapi.io/documentation/iana-timezones) of the user, e.g. `America/Los_Angeles`.", - "nullable": true - } - } - }, - "WebSearchContextSize": { - "type": "string", - "description": "High level guidance for the amount of context window space to use for the \nsearch. One of `low`, `medium`, or `high`. `medium` is the default.\n", - "enum": [ - "low", - "medium", - "high" - ], - "default": "medium" - }, - "WebSearchLocation": { - "type": "object", - "title": "Web search location", - "description": "Approximate location parameters for the search.", - "properties": { - "country": { - "type": "string", - "description": "The two-letter \n[ISO country code](https://en.wikipedia.org/wiki/ISO_3166-1) of the user,\ne.g. `US`.\n" - }, - "region": { - "type": "string", - "description": "Free text input for the region of the user, e.g. `California`.\n" - }, - "city": { - "type": "string", - "description": "Free text input for the city of the user, e.g. `San Francisco`.\n" - }, - "timezone": { - "type": "string", - "description": "The [IANA timezone](https://timeapi.io/documentation/iana-timezones) \nof the user, e.g. `America/Los_Angeles`.\n" - } - } - }, - "WebSearchTool": { - "type": "object", - "title": "Web search", - "description": "Search the Internet for sources related to the prompt. Learn more about the \n[web search tool](https://platform.openai.com/docs/guides/tools-web-search).\n", - "properties": { - "type": { - "type": "string", - "enum": [ - "web_search", - "web_search_2025_08_26" - ], - "description": "The type of the web search tool. One of `web_search` or `web_search_2025_08_26`.", - "default": "web_search" - }, - "filters": { - "type": "object", - "description": "Filters for the search.\n", - "nullable": true, - "properties": { - "allowed_domains": { - "type": "array", - "title": "Allowed domains for the search.", - "description": "Allowed domains for the search. If not provided, all domains are allowed.\nSubdomains of the provided domains are allowed as well.\n\nExample: `[\"pubmed.ncbi.nlm.nih.gov\"]`\n", - "items": { - "type": "string", - "description": "Allowed domain for the search." - }, - "default": [], - "nullable": true - } - } - }, - "user_location": { - "$ref": "#/components/schemas/WebSearchApproximateLocation" - }, - "search_context_size": { - "type": "string", - "enum": [ - "low", - "medium", - "high" - ], - "default": "medium", - "description": "High level guidance for the amount of context window space to use for the search. One of `low`, `medium`, or `high`. `medium` is the default." - } - }, - "required": [ - "type" - ] - }, - "WebSearchToolCall": { - "type": "object", - "title": "Web search tool call", - "description": "The results of a web search tool call. See the \n[web search guide](https://platform.openai.com/docs/guides/tools-web-search) for more information.\n", - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the web search tool call.\n" - }, - "type": { - "type": "string", - "enum": [ - "web_search_call" - ], - "description": "The type of the web search tool call. Always `web_search_call`.\n", - "x-stainless-const": true - }, - "status": { - "type": "string", - "description": "The status of the web search tool call.\n", - "enum": [ - "in_progress", - "searching", - "completed", - "failed" - ] - }, - "action": { - "type": "object", - "description": "An object describing the specific action taken in this web search call.\nIncludes details on how the model used the web (search, open_page, find).\n", - "anyOf": [ - { - "$ref": "#/components/schemas/WebSearchActionSearch" - }, - { - "$ref": "#/components/schemas/WebSearchActionOpenPage" - }, - { - "$ref": "#/components/schemas/WebSearchActionFind" - } - ], - "discriminator": { - "propertyName": "type" - } - } - }, - "required": [ - "id", - "type", - "status", - "action" - ] - }, - "WebhookBatchCancelled": { - "type": "object", - "title": "batch.cancelled", - "description": "Sent when a batch API request has been cancelled.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the batch API request was cancelled.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the batch API request.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `batch.cancelled`.\n", - "enum": [ - "batch.cancelled" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "batch.cancelled", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"batch.cancelled\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"batch_abc123\"\n }\n}\n" - } - }, - "WebhookBatchCompleted": { - "type": "object", - "title": "batch.completed", - "description": "Sent when a batch API request has been completed.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the batch API request was completed.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the batch API request.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `batch.completed`.\n", - "enum": [ - "batch.completed" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "batch.completed", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"batch.completed\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"batch_abc123\"\n }\n}\n" - } - }, - "WebhookBatchExpired": { - "type": "object", - "title": "batch.expired", - "description": "Sent when a batch API request has expired.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the batch API request expired.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the batch API request.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `batch.expired`.\n", - "enum": [ - "batch.expired" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "batch.expired", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"batch.expired\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"batch_abc123\"\n }\n}\n" - } - }, - "WebhookBatchFailed": { - "type": "object", - "title": "batch.failed", - "description": "Sent when a batch API request has failed.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the batch API request failed.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the batch API request.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `batch.failed`.\n", - "enum": [ - "batch.failed" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "batch.failed", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"batch.failed\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"batch_abc123\"\n }\n}\n" - } - }, - "WebhookEvalRunCanceled": { - "type": "object", - "title": "eval.run.canceled", - "description": "Sent when an eval run has been canceled.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the eval run was canceled.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the eval run.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `eval.run.canceled`.\n", - "enum": [ - "eval.run.canceled" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "eval.run.canceled", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"eval.run.canceled\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"evalrun_abc123\"\n }\n}\n" - } - }, - "WebhookEvalRunFailed": { - "type": "object", - "title": "eval.run.failed", - "description": "Sent when an eval run has failed.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the eval run failed.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the eval run.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `eval.run.failed`.\n", - "enum": [ - "eval.run.failed" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "eval.run.failed", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"eval.run.failed\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"evalrun_abc123\"\n }\n}\n" - } - }, - "WebhookEvalRunSucceeded": { - "type": "object", - "title": "eval.run.succeeded", - "description": "Sent when an eval run has succeeded.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the eval run succeeded.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the eval run.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `eval.run.succeeded`.\n", - "enum": [ - "eval.run.succeeded" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "eval.run.succeeded", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"eval.run.succeeded\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"evalrun_abc123\"\n }\n}\n" - } - }, - "WebhookFineTuningJobCancelled": { - "type": "object", - "title": "fine_tuning.job.cancelled", - "description": "Sent when a fine-tuning job has been cancelled.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the fine-tuning job was cancelled.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the fine-tuning job.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `fine_tuning.job.cancelled`.\n", - "enum": [ - "fine_tuning.job.cancelled" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "fine_tuning.job.cancelled", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"fine_tuning.job.cancelled\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"ftjob_abc123\"\n }\n}\n" - } - }, - "WebhookFineTuningJobFailed": { - "type": "object", - "title": "fine_tuning.job.failed", - "description": "Sent when a fine-tuning job has failed.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the fine-tuning job failed.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the fine-tuning job.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `fine_tuning.job.failed`.\n", - "enum": [ - "fine_tuning.job.failed" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "fine_tuning.job.failed", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"fine_tuning.job.failed\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"ftjob_abc123\"\n }\n}\n" - } - }, - "WebhookFineTuningJobSucceeded": { - "type": "object", - "title": "fine_tuning.job.succeeded", - "description": "Sent when a fine-tuning job has succeeded.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the fine-tuning job succeeded.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the fine-tuning job.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `fine_tuning.job.succeeded`.\n", - "enum": [ - "fine_tuning.job.succeeded" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "fine_tuning.job.succeeded", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"fine_tuning.job.succeeded\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"ftjob_abc123\"\n }\n}\n" - } - }, - "WebhookRealtimeCallIncoming": { - "type": "object", - "title": "realtime.call.incoming", - "description": "Sent when Realtime API Receives a incoming SIP call.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the model response was completed.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "call_id", - "sip_headers" - ], - "properties": { - "call_id": { - "type": "string", - "description": "The unique ID of this call.\n" - }, - "sip_headers": { - "type": "array", - "description": "Headers from the SIP Invite.\n", - "items": { - "type": "object", - "description": "A header from the SIP Invite.\n", - "required": [ - "name", - "value" - ], - "properties": { - "name": { - "type": "string", - "description": "Name of the SIP Header.\n" - }, - "value": { - "type": "string", - "description": "Value of the SIP Header.\n" - } - } - } - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `realtime.call.incoming`.\n", - "enum": [ - "realtime.call.incoming" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "realtime.call.incoming", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"realtime.call.incoming\",\n \"created_at\": 1719168000,\n \"data\": {\n \"call_id\": \"rtc_479a275623b54bdb9b6fbae2f7cbd408\",\n \"sip_headers\": [\n {\"name\": \"Max-Forwards\", \"value\": \"63\"},\n {\"name\": \"CSeq\", \"value\": \"851287 INVITE\"},\n {\"name\": \"Content-Type\", \"value\": \"application/sdp\"},\n ]\n }\n}\n" - } - }, - "WebhookResponseCancelled": { - "type": "object", - "title": "response.cancelled", - "description": "Sent when a background response has been cancelled.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the model response was cancelled.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the model response.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `response.cancelled`.\n", - "enum": [ - "response.cancelled" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "response.cancelled", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"response.cancelled\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"resp_abc123\"\n }\n}\n" - } - }, - "WebhookResponseCompleted": { - "type": "object", - "title": "response.completed", - "description": "Sent when a background response has been completed.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the model response was completed.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the model response.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `response.completed`.\n", - "enum": [ - "response.completed" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "response.completed", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"response.completed\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"resp_abc123\"\n }\n}\n" - } - }, - "WebhookResponseFailed": { - "type": "object", - "title": "response.failed", - "description": "Sent when a background response has failed.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the model response failed.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the model response.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `response.failed`.\n", - "enum": [ - "response.failed" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "response.failed", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"response.failed\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"resp_abc123\"\n }\n}\n" - } - }, - "WebhookResponseIncomplete": { - "type": "object", - "title": "response.incomplete", - "description": "Sent when a background response has been interrupted.\n", - "required": [ - "created_at", - "id", - "data", - "type" - ], - "properties": { - "created_at": { - "type": "integer", - "description": "The Unix timestamp (in seconds) of when the model response was interrupted.\n" - }, - "id": { - "type": "string", - "description": "The unique ID of the event.\n" - }, - "data": { - "type": "object", - "description": "Event data payload.\n", - "required": [ - "id" - ], - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the model response.\n" - } - } - }, - "object": { - "type": "string", - "description": "The object of the event. Always `event`.\n", - "enum": [ - "event" - ], - "x-stainless-const": true - }, - "type": { - "type": "string", - "description": "The type of the event. Always `response.incomplete`.\n", - "enum": [ - "response.incomplete" - ], - "x-stainless-const": true - } - }, - "x-oaiMeta": { - "name": "response.incomplete", - "group": "webhook-events", - "example": "{\n \"id\": \"evt_abc123\",\n \"type\": \"response.incomplete\",\n \"created_at\": 1719168000,\n \"data\": {\n \"id\": \"resp_abc123\"\n }\n}\n" - } - }, - "InputTextContent": { - "properties": { - "type": { - "type": "string", - "enum": [ - "input_text" - ], - "description": "The type of the input item. Always `input_text`.", - "default": "input_text", - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text input to the model." - } - }, - "type": "object", - "required": [ - "type", - "text" - ], - "title": "Input text", - "description": "A text input to the model." - }, - "InputImageContent": { - "properties": { - "type": { - "type": "string", - "enum": [ - "input_image" - ], - "description": "The type of the input item. Always `input_image`.", - "default": "input_image", - "x-stainless-const": true - }, - "image_url": { - "anyOf": [ - { - "type": "string", - "description": "The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL." - }, - { - "type": "null" - } - ] - }, - "file_id": { - "anyOf": [ - { - "type": "string", - "description": "The ID of the file to be sent to the model." - }, - { - "type": "null" - } - ] - }, - "detail": { - "type": "string", - "enum": [ - "low", - "high", - "auto" - ], - "description": "The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`." - } - }, - "type": "object", - "required": [ - "type", - "detail" - ], - "title": "Input image", - "description": "An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision)." - }, - "InputFileContent": { - "properties": { - "type": { - "type": "string", - "enum": [ - "input_file" - ], - "description": "The type of the input item. Always `input_file`.", - "default": "input_file", - "x-stainless-const": true - }, - "file_id": { - "anyOf": [ - { - "type": "string", - "description": "The ID of the file to be sent to the model." - }, - { - "type": "null" - } - ] - }, - "filename": { - "type": "string", - "description": "The name of the file to be sent to the model." - }, - "file_url": { - "type": "string", - "description": "The URL of the file to be sent to the model." - }, - "file_data": { - "type": "string", - "description": "The content of the file to be sent to the model.\n" - } - }, - "type": "object", - "required": [ - "type" - ], - "title": "Input file", - "description": "A file input to the model." - }, - "FileCitationBody": { - "properties": { - "type": { - "type": "string", - "enum": [ - "file_citation" - ], - "description": "The type of the file citation. Always `file_citation`.", - "default": "file_citation", - "x-stainless-const": true - }, - "file_id": { - "type": "string", - "description": "The ID of the file." - }, - "index": { - "type": "integer", - "description": "The index of the file in the list of files." - }, - "filename": { - "type": "string", - "description": "The filename of the file cited." - } - }, - "type": "object", - "required": [ - "type", - "file_id", - "index", - "filename" - ], - "title": "File citation", - "description": "A citation to a file." - }, - "UrlCitationBody": { - "properties": { - "type": { - "type": "string", - "enum": [ - "url_citation" - ], - "description": "The type of the URL citation. Always `url_citation`.", - "default": "url_citation", - "x-stainless-const": true - }, - "url": { - "type": "string", - "description": "The URL of the web resource." - }, - "start_index": { - "type": "integer", - "description": "The index of the first character of the URL citation in the message." - }, - "end_index": { - "type": "integer", - "description": "The index of the last character of the URL citation in the message." - }, - "title": { - "type": "string", - "description": "The title of the web resource." - } - }, - "type": "object", - "required": [ - "type", - "url", - "start_index", - "end_index", - "title" - ], - "title": "URL citation", - "description": "A citation for a web resource used to generate a model response." - }, - "ContainerFileCitationBody": { - "properties": { - "type": { - "type": "string", - "enum": [ - "container_file_citation" - ], - "description": "The type of the container file citation. Always `container_file_citation`.", - "default": "container_file_citation", - "x-stainless-const": true - }, - "container_id": { - "type": "string", - "description": "The ID of the container file." - }, - "file_id": { - "type": "string", - "description": "The ID of the file." - }, - "start_index": { - "type": "integer", - "description": "The index of the first character of the container file citation in the message." - }, - "end_index": { - "type": "integer", - "description": "The index of the last character of the container file citation in the message." - }, - "filename": { - "type": "string", - "description": "The filename of the container file cited." - } - }, - "type": "object", - "required": [ - "type", - "container_id", - "file_id", - "start_index", - "end_index", - "filename" - ], - "title": "Container file citation", - "description": "A citation for a container file used to generate a model response." - }, - "Annotation": { - "discriminator": { - "propertyName": "type" - }, - "anyOf": [ - { - "$ref": "#/components/schemas/FileCitationBody" - }, - { - "$ref": "#/components/schemas/UrlCitationBody" - }, - { - "$ref": "#/components/schemas/ContainerFileCitationBody" - }, - { - "$ref": "#/components/schemas/FilePath" - } - ] - }, - "TopLogProb": { - "properties": { - "token": { - "type": "string" - }, - "logprob": { - "type": "number" - }, - "bytes": { - "items": { - "type": "integer" - }, - "type": "array" - } - }, - "type": "object", - "required": [ - "token", - "logprob", - "bytes" - ], - "title": "Top log probability", - "description": "The top log probability of a token." - }, - "LogProb": { - "properties": { - "token": { - "type": "string" - }, - "logprob": { - "type": "number" - }, - "bytes": { - "items": { - "type": "integer" - }, - "type": "array" - }, - "top_logprobs": { - "items": { - "$ref": "#/components/schemas/TopLogProb" - }, - "type": "array" - } - }, - "type": "object", - "required": [ - "token", - "logprob", - "bytes", - "top_logprobs" - ], - "title": "Log probability", - "description": "The log probability of a token." - }, - "OutputTextContent": { - "properties": { - "type": { - "type": "string", - "enum": [ - "output_text" - ], - "description": "The type of the output text. Always `output_text`.", - "default": "output_text", - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text output from the model." - }, - "annotations": { - "items": { - "$ref": "#/components/schemas/Annotation" - }, - "type": "array", - "description": "The annotations of the text output." - }, - "logprobs": { - "items": { - "$ref": "#/components/schemas/LogProb" - }, - "type": "array" - } - }, - "type": "object", - "required": [ - "type", - "text", - "annotations" - ], - "title": "Output text", - "description": "A text output from the model." - }, - "RefusalContent": { - "properties": { - "type": { - "type": "string", - "enum": [ - "refusal" - ], - "description": "The type of the refusal. Always `refusal`.", - "default": "refusal", - "x-stainless-const": true - }, - "refusal": { - "type": "string", - "description": "The refusal explanation from the model." - } - }, - "type": "object", - "required": [ - "type", - "refusal" - ], - "title": "Refusal", - "description": "A refusal from the model." - }, - "ComputerCallSafetyCheckParam": { - "properties": { - "id": { - "type": "string", - "description": "The ID of the pending safety check." - }, - "code": { - "anyOf": [ - { - "type": "string", - "description": "The type of the pending safety check." - }, - { - "type": "null" - } - ] - }, - "message": { - "anyOf": [ - { - "type": "string", - "description": "Details about the pending safety check." - }, - { - "type": "null" - } - ] - } - }, - "type": "object", - "required": [ - "id" - ], - "description": "A pending safety check for the computer call." - }, - "ComputerCallOutputItemParam": { - "properties": { - "id": { - "anyOf": [ - { - "type": "string", - "description": "The ID of the computer tool call output." - }, - { - "type": "null" - } - ] - }, - "call_id": { - "type": "string", - "maxLength": 64, - "minLength": 1, - "description": "The ID of the computer tool call that produced the output." - }, - "type": { - "type": "string", - "enum": [ - "computer_call_output" - ], - "description": "The type of the computer tool call output. Always `computer_call_output`.", - "default": "computer_call_output", - "x-stainless-const": true - }, - "output": { - "$ref": "#/components/schemas/ComputerScreenshotImage" - }, - "acknowledged_safety_checks": { - "anyOf": [ - { - "items": { - "$ref": "#/components/schemas/ComputerCallSafetyCheckParam" - }, - "type": "array", - "description": "The safety checks reported by the API that have been acknowledged by the developer." - }, - { - "type": "null" - } - ] - }, - "status": { - "anyOf": [ - { - "type": "string", - "enum": [ - "in_progress", - "completed", - "incomplete" - ], - "description": "The status of the message input. One of `in_progress`, `completed`, or `incomplete`. Populated when input items are returned via API." - }, - { - "type": "null" - } - ] - } - }, - "type": "object", - "required": [ - "call_id", - "type", - "output" - ], - "title": "Computer tool call output", - "description": "The output of a computer tool call." - }, - "FunctionCallOutputItemParam": { - "properties": { - "id": { - "anyOf": [ - { - "type": "string", - "description": "The unique ID of the function tool call output. Populated when this item is returned via API." - }, - { - "type": "null" - } - ] - }, - "call_id": { - "type": "string", - "maxLength": 64, - "minLength": 1, - "description": "The unique ID of the function tool call generated by the model." - }, - "type": { - "type": "string", - "enum": [ - "function_call_output" - ], - "description": "The type of the function tool call output. Always `function_call_output`.", - "default": "function_call_output", - "x-stainless-const": true - }, - "output": { - "type": "string", - "maxLength": 10485760, - "description": "A JSON string of the output of the function tool call." - }, - "status": { - "anyOf": [ - { - "type": "string", - "enum": [ - "in_progress", - "completed", - "incomplete" - ], - "description": "The status of the item. One of `in_progress`, `completed`, or `incomplete`. Populated when items are returned via API." - }, - { - "type": "null" - } - ] - } - }, - "type": "object", - "required": [ - "call_id", - "type", - "output" - ], - "title": "Function tool call output", - "description": "The output of a function tool call." - }, - "ItemReferenceParam": { - "properties": { - "type": { - "anyOf": [ - { - "type": "string", - "enum": [ - "item_reference" - ], - "description": "The type of item to reference. Always `item_reference`.", - "default": "item_reference", - "x-stainless-const": true - }, - { - "type": "null" - } - ] - }, - "id": { - "type": "string", - "description": "The ID of the item to reference." - } - }, - "type": "object", - "required": [ - "id" - ], - "title": "Item reference", - "description": "An internal identifier for an item to reference." - }, - "ConversationResource": { - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the conversation." - }, - "object": { - "type": "string", - "enum": [ - "conversation" - ], - "description": "The object type, which is always `conversation`.", - "default": "conversation", - "x-stainless-const": true - }, - "metadata": { - "description": "Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters." - }, - "created_at": { - "type": "integer", - "description": "The time at which the conversation was created, measured in seconds since the Unix epoch." - } - }, - "type": "object", - "required": [ - "id", - "object", - "metadata", - "created_at" - ] - }, - "MetadataParam": { - "additionalProperties": { - "type": "string", - "maxLength": 512 - }, - "type": "object", - "maxProperties": 16 - }, - "UpdateConversationBody": { - "properties": { - "metadata": { - "$ref": "#/components/schemas/MetadataParam", - "description": "Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters." - } - }, - "type": "object", - "required": [ - "metadata" - ] - }, - "DeletedConversationResource": { - "properties": { - "object": { - "type": "string", - "enum": [ - "conversation.deleted" - ], - "default": "conversation.deleted", - "x-stainless-const": true - }, - "deleted": { - "type": "boolean" - }, - "id": { - "type": "string" - } - }, - "type": "object", - "required": [ - "object", - "deleted", - "id" - ] - }, - "InputTextContent-2": { - "properties": { - "type": { - "type": "string", - "enum": [ - "input_text" - ], - "description": "The type of the input item. Always `input_text`.", - "default": "input_text", - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text input to the model." - } - }, - "type": "object", - "required": [ - "type", - "text" - ], - "title": "Input text" - }, - "FileCitationBody-2": { - "properties": { - "type": { - "type": "string", - "enum": [ - "file_citation" - ], - "description": "The type of the file citation. Always `file_citation`.", - "default": "file_citation", - "x-stainless-const": true - }, - "file_id": { - "type": "string", - "description": "The ID of the file." - }, - "index": { - "type": "integer", - "description": "The index of the file in the list of files." - }, - "filename": { - "type": "string", - "description": "The filename of the file cited." - } - }, - "type": "object", - "required": [ - "type", - "file_id", - "index", - "filename" - ], - "title": "File citation" - }, - "UrlCitationBody-2": { - "properties": { - "type": { - "type": "string", - "enum": [ - "url_citation" - ], - "description": "The type of the URL citation. Always `url_citation`.", - "default": "url_citation", - "x-stainless-const": true - }, - "url": { - "type": "string", - "description": "The URL of the web resource." - }, - "start_index": { - "type": "integer", - "description": "The index of the first character of the URL citation in the message." - }, - "end_index": { - "type": "integer", - "description": "The index of the last character of the URL citation in the message." - }, - "title": { - "type": "string", - "description": "The title of the web resource." - } - }, - "type": "object", - "required": [ - "type", - "url", - "start_index", - "end_index", - "title" - ], - "title": "URL citation" - }, - "ContainerFileCitationBody-2": { - "properties": { - "type": { - "type": "string", - "enum": [ - "container_file_citation" - ], - "description": "The type of the container file citation. Always `container_file_citation`.", - "default": "container_file_citation", - "x-stainless-const": true - }, - "container_id": { - "type": "string", - "description": "The ID of the container file." - }, - "file_id": { - "type": "string", - "description": "The ID of the file." - }, - "start_index": { - "type": "integer", - "description": "The index of the first character of the container file citation in the message." - }, - "end_index": { - "type": "integer", - "description": "The index of the last character of the container file citation in the message." - }, - "filename": { - "type": "string", - "description": "The filename of the container file cited." - } - }, - "type": "object", - "required": [ - "type", - "container_id", - "file_id", - "start_index", - "end_index", - "filename" - ], - "title": "Container file citation" - }, - "Annotation-2": { - "discriminator": { - "propertyName": "type" - }, - "anyOf": [ - { - "$ref": "#/components/schemas/FileCitationBody-2" - }, - { - "$ref": "#/components/schemas/UrlCitationBody-2" - }, - { - "$ref": "#/components/schemas/ContainerFileCitationBody-2" - } - ] - }, - "TopLogProb-2": { - "properties": { - "token": { - "type": "string" - }, - "logprob": { - "type": "number" - }, - "bytes": { - "items": { - "type": "integer" - }, - "type": "array" - } - }, - "type": "object", - "required": [ - "token", - "logprob", - "bytes" - ], - "title": "Top log probability" - }, - "LogProb-2": { - "properties": { - "token": { - "type": "string" - }, - "logprob": { - "type": "number" - }, - "bytes": { - "items": { - "type": "integer" - }, - "type": "array" - }, - "top_logprobs": { - "items": { - "$ref": "#/components/schemas/TopLogProb-2" - }, - "type": "array" - } - }, - "type": "object", - "required": [ - "token", - "logprob", - "bytes", - "top_logprobs" - ], - "title": "Log probability" - }, - "OutputTextContent-2": { - "properties": { - "type": { - "type": "string", - "enum": [ - "output_text" - ], - "description": "The type of the output text. Always `output_text`.", - "default": "output_text", - "x-stainless-const": true - }, - "text": { - "type": "string", - "description": "The text output from the model." - }, - "annotations": { - "items": { - "$ref": "#/components/schemas/Annotation-2" - }, - "type": "array", - "description": "The annotations of the text output." - }, - "logprobs": { - "items": { - "$ref": "#/components/schemas/LogProb-2" - }, - "type": "array" - } - }, - "type": "object", - "required": [ - "type", - "text", - "annotations" - ], - "title": "Output text" - }, - "TextContent": { - "properties": { - "type": { - "type": "string", - "enum": [ - "text" - ], - "default": "text", - "x-stainless-const": true - }, - "text": { - "type": "string" - } - }, - "type": "object", - "required": [ - "type", - "text" - ], - "title": "Text Content" - }, - "SummaryTextContent": { - "properties": { - "type": { - "type": "string", - "enum": [ - "summary_text" - ], - "default": "summary_text", - "x-stainless-const": true - }, - "text": { - "type": "string" - } - }, - "type": "object", - "required": [ - "type", - "text" - ], - "title": "Summary text" - }, - "RefusalContent-2": { - "properties": { - "type": { - "type": "string", - "enum": [ - "refusal" - ], - "description": "The type of the refusal. Always `refusal`.", - "default": "refusal", - "x-stainless-const": true - }, - "refusal": { - "type": "string", - "description": "The refusal explanation from the model." - } - }, - "type": "object", - "required": [ - "type", - "refusal" - ], - "title": "Refusal" - }, - "InputImageContent-2": { - "properties": { - "type": { - "type": "string", - "enum": [ - "input_image" - ], - "description": "The type of the input item. Always `input_image`.", - "default": "input_image", - "x-stainless-const": true - }, - "image_url": { - "anyOf": [ - { - "type": "string", - "description": "The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL." - }, - { - "type": "null" - } - ] - }, - "file_id": { - "anyOf": [ - { - "type": "string", - "description": "The ID of the file to be sent to the model." - }, - { - "type": "null" - } - ] - }, - "detail": { - "type": "string", - "enum": [ - "low", - "high", - "auto" - ], - "description": "The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`." - } - }, - "type": "object", - "required": [ - "type", - "image_url", - "file_id", - "detail" - ], - "title": "Input image" - }, - "ComputerScreenshotContent": { - "properties": { - "type": { - "type": "string", - "enum": [ - "computer_screenshot" - ], - "description": "Specifies the event type. For a computer screenshot, this property is always set to `computer_screenshot`.", - "default": "computer_screenshot", - "x-stainless-const": true - }, - "image_url": { - "anyOf": [ - { - "type": "string", - "description": "The URL of the screenshot image." - }, - { - "type": "null" - } - ] - }, - "file_id": { - "anyOf": [ - { - "type": "string", - "description": "The identifier of an uploaded file that contains the screenshot." - }, - { - "type": "null" - } - ] - } - }, - "type": "object", - "required": [ - "type", - "image_url", - "file_id" - ], - "title": "Computer screenshot" - }, - "InputFileContent-2": { - "properties": { - "type": { - "type": "string", - "enum": [ - "input_file" - ], - "description": "The type of the input item. Always `input_file`.", - "default": "input_file", - "x-stainless-const": true - }, - "file_id": { - "anyOf": [ - { - "type": "string", - "description": "The ID of the file to be sent to the model." - }, - { - "type": "null" - } - ] - }, - "filename": { - "type": "string", - "description": "The name of the file to be sent to the model." - }, - "file_url": { - "type": "string", - "description": "The URL of the file to be sent to the model." - } - }, - "type": "object", - "required": [ - "type", - "file_id" - ], - "title": "Input file" - }, - "Message": { - "properties": { - "type": { - "type": "string", - "enum": [ - "message" - ], - "description": "The type of the message. Always set to `message`.", - "default": "message", - "x-stainless-const": true - }, - "id": { - "type": "string", - "description": "The unique ID of the message." - }, - "status": { - "type": "string", - "enum": [ - "in_progress", - "completed", - "incomplete" - ], - "description": "The status of item. One of `in_progress`, `completed`, or `incomplete`. Populated when items are returned via API." - }, - "role": { - "type": "string", - "enum": [ - "unknown", - "user", - "assistant", - "system", - "critic", - "discriminator", - "developer", - "tool" - ], - "description": "The role of the message. One of `unknown`, `user`, `assistant`, `system`, `critic`, `discriminator`, `developer`, or `tool`." - }, - "content": { - "items": { - "discriminator": { - "propertyName": "type" - }, - "anyOf": [ - { - "$ref": "#/components/schemas/InputTextContent-2" - }, - { - "$ref": "#/components/schemas/OutputTextContent-2" - }, - { - "$ref": "#/components/schemas/TextContent" - }, - { - "$ref": "#/components/schemas/SummaryTextContent" - }, - { - "$ref": "#/components/schemas/RefusalContent-2" - }, - { - "$ref": "#/components/schemas/InputImageContent-2" - }, - { - "$ref": "#/components/schemas/ComputerScreenshotContent" - }, - { - "$ref": "#/components/schemas/InputFileContent-2" - } - ] - }, - "type": "array", - "description": "The content of the message" - } - }, - "type": "object", - "required": [ - "type", - "id", - "status", - "role", - "content" - ], - "title": "Message" - }, - "FunctionTool": { - "properties": { - "type": { - "type": "string", - "enum": [ - "function" - ], - "description": "The type of the function tool. Always `function`.", - "default": "function", - "x-stainless-const": true - }, - "name": { - "type": "string", - "description": "The name of the function to call." - }, - "description": { - "anyOf": [ - { - "type": "string", - "description": "A description of the function. Used by the model to determine whether or not to call the function." - }, - { - "type": "null" - } - ] - }, - "parameters": { - "anyOf": [ - { - "additionalProperties": {}, - "type": "object", - "description": "A JSON schema object describing the parameters of the function." - }, - { - "type": "null" - } - ] - }, - "strict": { - "anyOf": [ - { - "type": "boolean", - "description": "Whether to enforce strict parameter validation. Default `true`." - }, - { - "type": "null" - } - ] - } - }, - "type": "object", - "required": [ - "type", - "name", - "strict", - "parameters" - ], - "title": "Function", - "description": "Defines a function in your own code the model can choose to call. Learn more about [function calling](https://platform.openai.com/docs/guides/function-calling)." - }, - "RankingOptions": { - "properties": { - "ranker": { - "type": "string", - "enum": [ - "auto", - "default-2024-11-15" - ], - "description": "The ranker to use for the file search." - }, - "score_threshold": { - "type": "number", - "description": "The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will attempt to return only the most relevant results, but may return fewer results." - } - }, - "type": "object", - "required": [] - }, - "Filters": { - "anyOf": [ - { - "$ref": "#/components/schemas/ComparisonFilter" - }, - { - "$ref": "#/components/schemas/CompoundFilter" - } - ] - }, - "FileSearchTool": { - "properties": { - "type": { - "type": "string", - "enum": [ - "file_search" - ], - "description": "The type of the file search tool. Always `file_search`.", - "default": "file_search", - "x-stainless-const": true - }, - "vector_store_ids": { - "items": { - "type": "string" - }, - "type": "array", - "description": "The IDs of the vector stores to search." - }, - "max_num_results": { - "type": "integer", - "description": "The maximum number of results to return. This number should be between 1 and 50 inclusive." - }, - "ranking_options": { - "$ref": "#/components/schemas/RankingOptions", - "description": "Ranking options for search." - }, - "filters": { - "anyOf": [ - { - "$ref": "#/components/schemas/Filters", - "description": "A filter to apply." - }, - { - "type": "null" - } - ] - } - }, - "type": "object", - "required": [ - "type", - "vector_store_ids" - ], - "title": "File search", - "description": "A tool that searches for relevant content from uploaded files. Learn more about the [file search tool](https://platform.openai.com/docs/guides/tools-file-search)." - }, - "ComputerUsePreviewTool": { - "properties": { - "type": { - "type": "string", - "enum": [ - "computer_use_preview" - ], - "description": "The type of the computer use tool. Always `computer_use_preview`.", - "default": "computer_use_preview", - "x-stainless-const": true - }, - "environment": { - "type": "string", - "enum": [ - "windows", - "mac", - "linux", - "ubuntu", - "browser" - ], - "description": "The type of computer environment to control." - }, - "display_width": { - "type": "integer", - "description": "The width of the computer display." - }, - "display_height": { - "type": "integer", - "description": "The height of the computer display." - } - }, - "type": "object", - "required": [ - "type", - "environment", - "display_width", - "display_height" - ], - "title": "Computer use preview", - "description": "A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use)." - }, - "ApproximateLocation": { - "properties": { - "type": { - "type": "string", - "enum": [ - "approximate" - ], - "description": "The type of location approximation. Always `approximate`.", - "default": "approximate", - "x-stainless-const": true - }, - "country": { - "anyOf": [ - { - "type": "string", - "description": "The two-letter [ISO country code](https://en.wikipedia.org/wiki/ISO_3166-1) of the user, e.g. `US`." - }, - { - "type": "null" - } - ] - }, - "region": { - "anyOf": [ - { - "type": "string", - "description": "Free text input for the region of the user, e.g. `California`." - }, - { - "type": "null" - } - ] - }, - "city": { - "anyOf": [ - { - "type": "string", - "description": "Free text input for the city of the user, e.g. `San Francisco`." - }, - { - "type": "null" - } - ] - }, - "timezone": { - "anyOf": [ - { - "type": "string", - "description": "The [IANA timezone](https://timeapi.io/documentation/iana-timezones) of the user, e.g. `America/Los_Angeles`." - }, - { - "type": "null" - } - ] - } - }, - "type": "object", - "required": [ - "type" - ] - }, - "WebSearchPreviewTool": { - "properties": { - "type": { - "type": "string", - "enum": [ - "web_search_preview", - "web_search_preview_2025_03_11" - ], - "description": "The type of the web search tool. One of `web_search_preview` or `web_search_preview_2025_03_11`.", - "default": "web_search_preview", - "x-stainless-const": true - }, - "user_location": { - "anyOf": [ - { - "$ref": "#/components/schemas/ApproximateLocation", - "description": "The user's location." - }, - { - "type": "null" - } - ] - }, - "search_context_size": { - "type": "string", - "enum": [ - "low", - "medium", - "high" - ], - "description": "High level guidance for the amount of context window space to use for the search. One of `low`, `medium`, or `high`. `medium` is the default." - } - }, - "type": "object", - "required": [ - "type" - ], - "title": "Web search preview", - "description": "This tool searches the web for relevant results to use in a response. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search)." - }, - "ImageGenInputUsageDetails": { - "properties": { - "text_tokens": { - "type": "integer", - "description": "The number of text tokens in the input prompt." - }, - "image_tokens": { - "type": "integer", - "description": "The number of image tokens in the input prompt." - } - }, - "type": "object", - "required": [ - "text_tokens", - "image_tokens" - ], - "title": "Input usage details", - "description": "The input tokens detailed information for the image generation." - }, - "ImageGenUsage": { - "properties": { - "input_tokens": { - "type": "integer", - "description": "The number of tokens (images and text) in the input prompt." - }, - "total_tokens": { - "type": "integer", - "description": "The total number of tokens (images and text) used for the image generation." - }, - "output_tokens": { - "type": "integer", - "description": "The number of output tokens generated by the model." - }, - "input_tokens_details": { - "$ref": "#/components/schemas/ImageGenInputUsageDetails" - } - }, - "type": "object", - "required": [ - "input_tokens", - "total_tokens", - "output_tokens", - "input_tokens_details" - ], - "title": "Image generation usage", - "description": "For `gpt-image-1` only, the token usage information for the image generation." - }, - "ConversationParam": { - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the conversation." - } - }, - "type": "object", - "required": [ - "id" - ], - "title": "Conversation object", - "description": "The conversation that this response belongs to." - }, - "Conversation-2": { - "properties": { - "id": { - "type": "string", - "description": "The unique ID of the conversation." - } - }, - "type": "object", - "required": [ - "id" - ], - "title": "Conversation", - "description": "The conversation that this response belongs to. Input items and output items from this response are automatically added to this conversation." - }, - "RealtimeConnectParams": { - "type": "object", - "properties": { - "model": { - "type": "string" - } - }, - "required": [ - "model" - ] - }, - "ModerationImageURLInput": { - "type": "object", - "description": "An object describing an image to classify.", - "properties": { - "type": { - "description": "Always `image_url`.", - "type": "string", - "enum": [ - "image_url" - ], - "x-stainless-const": true - }, - "image_url": { - "type": "object", - "description": "Contains either an image URL or a data URL for a base64 encoded image.", - "properties": { - "url": { - "type": "string", - "description": "Either a URL of the image or the base64 encoded image data.", - "format": "uri", - "example": "https://example.com/image.jpg" - } - }, - "required": [ - "url" - ] - } - }, - "required": [ - "type", - "image_url" - ] - }, - "ModerationTextInput": { - "type": "object", - "description": "An object describing text to classify.", - "properties": { - "type": { - "description": "Always `text`.", - "type": "string", - "enum": [ - "text" - ], - "x-stainless-const": true - }, - "text": { - "description": "A string of text to classify.", - "type": "string", - "example": "I want to kill them" - } - }, - "required": [ - "type", - "text" - ] - }, - "ChunkingStrategyResponse": { - "type": "object", - "description": "The strategy used to chunk the file.", - "anyOf": [ - { - "$ref": "#/components/schemas/StaticChunkingStrategyResponseParam" - }, - { - "$ref": "#/components/schemas/OtherChunkingStrategyResponseParam" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "FilePurpose": { - "description": "The intended purpose of the uploaded file. One of: - `assistants`: Used in the Assistants API - `batch`: Used in the Batch API - `fine-tune`: Used for fine-tuning - `vision`: Images used for vision fine-tuning - `user_data`: Flexible file type for any purpose - `evals`: Used for eval data sets\n", - "type": "string", - "enum": [ - "assistants", - "batch", - "fine-tune", - "vision", - "user_data", - "evals" - ] - }, - "BatchError": { - "type": "object", - "properties": { - "code": { - "type": "string", - "description": "An error code identifying the error type." - }, - "message": { - "type": "string", - "description": "A human-readable message providing more details about the error." - }, - "param": { - "type": "string", - "description": "The name of the parameter that caused the error, if applicable.", - "nullable": true - }, - "line": { - "type": "integer", - "description": "The line number of the input file where the error occurred, if applicable.", - "nullable": true - } - } - }, - "BatchRequestCounts": { - "type": "object", - "properties": { - "total": { - "type": "integer", - "description": "Total number of requests in the batch." - }, - "completed": { - "type": "integer", - "description": "Number of requests that have been completed successfully." - }, - "failed": { - "type": "integer", - "description": "Number of requests that have failed." - } - }, - "required": [ - "total", - "completed", - "failed" - ], - "description": "The request counts for different statuses within the batch." - }, - "AssistantTool": { - "anyOf": [ - { - "$ref": "#/components/schemas/AssistantToolsCode" - }, - { - "$ref": "#/components/schemas/AssistantToolsFileSearch" - }, - { - "$ref": "#/components/schemas/AssistantToolsFunction" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "TextAnnotationDelta": { - "anyOf": [ - { - "$ref": "#/components/schemas/MessageDeltaContentTextAnnotationsFileCitationObject" - }, - { - "$ref": "#/components/schemas/MessageDeltaContentTextAnnotationsFilePathObject" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "TextAnnotation": { - "anyOf": [ - { - "$ref": "#/components/schemas/MessageContentTextAnnotationsFileCitationObject" - }, - { - "$ref": "#/components/schemas/MessageContentTextAnnotationsFilePathObject" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "RunStepDetailsToolCall": { - "anyOf": [ - { - "$ref": "#/components/schemas/RunStepDetailsToolCallsCodeObject" - }, - { - "$ref": "#/components/schemas/RunStepDetailsToolCallsFileSearchObject" - }, - { - "$ref": "#/components/schemas/RunStepDetailsToolCallsFunctionObject" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "RunStepDeltaStepDetailsToolCall": { - "anyOf": [ - { - "$ref": "#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeObject" - }, - { - "$ref": "#/components/schemas/RunStepDeltaStepDetailsToolCallsFileSearchObject" - }, - { - "$ref": "#/components/schemas/RunStepDeltaStepDetailsToolCallsFunctionObject" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "MessageContent": { - "anyOf": [ - { - "$ref": "#/components/schemas/MessageContentImageFileObject" - }, - { - "$ref": "#/components/schemas/MessageContentImageUrlObject" - }, - { - "$ref": "#/components/schemas/MessageContentTextObject" - }, - { - "$ref": "#/components/schemas/MessageContentRefusalObject" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "MessageContentDelta": { - "anyOf": [ - { - "$ref": "#/components/schemas/MessageDeltaContentImageFileObject" - }, - { - "$ref": "#/components/schemas/MessageDeltaContentTextObject" - }, - { - "$ref": "#/components/schemas/MessageDeltaContentRefusalObject" - }, - { - "$ref": "#/components/schemas/MessageDeltaContentImageUrlObject" - } - ], - "discriminator": { - "propertyName": "type" - } - }, - "ChatModel": { - "type": "string", - "enum": [ - "gpt-5", - "gpt-5-mini", - "gpt-5-nano", - "gpt-5-2025-08-07", - "gpt-5-mini-2025-08-07", - "gpt-5-nano-2025-08-07", - "gpt-5-chat-latest", - "gpt-4.1", - "gpt-4.1-mini", - "gpt-4.1-nano", - "gpt-4.1-2025-04-14", - "gpt-4.1-mini-2025-04-14", - "gpt-4.1-nano-2025-04-14", - "o4-mini", - "o4-mini-2025-04-16", - "o3", - "o3-2025-04-16", - "o3-mini", - "o3-mini-2025-01-31", - "o1", - "o1-2024-12-17", - "o1-preview", - "o1-preview-2024-09-12", - "o1-mini", - "o1-mini-2024-09-12", - "gpt-4o", - "gpt-4o-2024-11-20", - "gpt-4o-2024-08-06", - "gpt-4o-2024-05-13", - "gpt-4o-audio-preview", - "gpt-4o-audio-preview-2024-10-01", - "gpt-4o-audio-preview-2024-12-17", - "gpt-4o-audio-preview-2025-06-03", - "gpt-4o-mini-audio-preview", - "gpt-4o-mini-audio-preview-2024-12-17", - "gpt-4o-search-preview", - "gpt-4o-mini-search-preview", - "gpt-4o-search-preview-2025-03-11", - "gpt-4o-mini-search-preview-2025-03-11", - "chatgpt-4o-latest", - "codex-mini-latest", - "gpt-4o-mini", - "gpt-4o-mini-2024-07-18", - "gpt-4-turbo", - "gpt-4-turbo-2024-04-09", - "gpt-4-0125-preview", - "gpt-4-turbo-preview", - "gpt-4-1106-preview", - "gpt-4-vision-preview", - "gpt-4", - "gpt-4-0314", - "gpt-4-0613", - "gpt-4-32k", - "gpt-4-32k-0314", - "gpt-4-32k-0613", - "gpt-3.5-turbo", - "gpt-3.5-turbo-16k", - "gpt-3.5-turbo-0301", - "gpt-3.5-turbo-0613", - "gpt-3.5-turbo-1106", - "gpt-3.5-turbo-0125", - "gpt-3.5-turbo-16k-0613" - ], - "x-stainless-nominal": false - }, - "CreateThreadAndRunRequestWithoutStream": { - "type": "object", - "additionalProperties": false, - "properties": { - "assistant_id": { - "description": "The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to execute this run.", - "type": "string" - }, - "thread": { - "$ref": "#/components/schemas/CreateThreadRequest" - }, - "model": { - "description": "The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute this run. If a value is provided here, it will override the model associated with the assistant. If not, the model associated with the assistant will be used.", - "anyOf": [ - { - "type": "string" - }, - { - "type": "string", - "enum": [ - "gpt-5", - "gpt-5-mini", - "gpt-5-nano", - "gpt-5-2025-08-07", - "gpt-5-mini-2025-08-07", - "gpt-5-nano-2025-08-07", - "gpt-4.1", - "gpt-4.1-mini", - "gpt-4.1-nano", - "gpt-4.1-2025-04-14", - "gpt-4.1-mini-2025-04-14", - "gpt-4.1-nano-2025-04-14", - "gpt-4o", - "gpt-4o-2024-11-20", - "gpt-4o-2024-08-06", - "gpt-4o-2024-05-13", - "gpt-4o-mini", - "gpt-4o-mini-2024-07-18", - "gpt-4.5-preview", - "gpt-4.5-preview-2025-02-27", - "gpt-4-turbo", - "gpt-4-turbo-2024-04-09", - "gpt-4-0125-preview", - "gpt-4-turbo-preview", - "gpt-4-1106-preview", - "gpt-4-vision-preview", - "gpt-4", - "gpt-4-0314", - "gpt-4-0613", - "gpt-4-32k", - "gpt-4-32k-0314", - "gpt-4-32k-0613", - "gpt-3.5-turbo", - "gpt-3.5-turbo-16k", - "gpt-3.5-turbo-0613", - "gpt-3.5-turbo-1106", - "gpt-3.5-turbo-0125", - "gpt-3.5-turbo-16k-0613" - ] - } - ], - "x-oaiTypeLabel": "string", - "nullable": true - }, - "instructions": { - "description": "Override the default system message of the assistant. This is useful for modifying the behavior on a per-run basis.", - "type": "string", - "nullable": true - }, - "tools": { - "description": "Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.", - "nullable": true, - "type": "array", - "maxItems": 20, - "items": { - "$ref": "#/components/schemas/AssistantTool" - } - }, - "tool_resources": { - "type": "object", - "description": "A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.\n", - "properties": { - "code_interpreter": { - "type": "object", - "properties": { - "file_ids": { - "type": "array", - "description": "A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.\n", - "default": [], - "maxItems": 20, - "items": { - "type": "string" - } - } - } - }, - "file_search": { - "type": "object", - "properties": { - "vector_store_ids": { - "type": "array", - "description": "The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.\n", - "maxItems": 1, - "items": { - "type": "string" - } - } - } - } - }, - "nullable": true - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "temperature": { - "type": "number", - "minimum": 0, - "maximum": 2, - "default": 1, - "example": 1, - "nullable": true, - "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n" - }, - "top_p": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 1, - "example": 1, - "nullable": true, - "description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or temperature but not both.\n" - }, - "max_prompt_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of prompt tokens that may be used over the course of the run. The run will make a best effort to use only the number of prompt tokens specified, across multiple turns of the run. If the run exceeds the number of prompt tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.\n", - "minimum": 256 - }, - "max_completion_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of completion tokens that may be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.\n", - "minimum": 256 - }, - "truncation_strategy": { - "allOf": [ - { - "$ref": "#/components/schemas/TruncationObject" - }, - { - "nullable": true - } - ] - }, - "tool_choice": { - "allOf": [ - { - "$ref": "#/components/schemas/AssistantsApiToolChoiceOption" - }, - { - "nullable": true - } - ] - }, - "parallel_tool_calls": { - "$ref": "#/components/schemas/ParallelToolCalls" - }, - "response_format": { - "$ref": "#/components/schemas/AssistantsApiResponseFormatOption", - "nullable": true - } - }, - "required": [ - "assistant_id" - ] - }, - "CreateRunRequestWithoutStream": { - "type": "object", - "additionalProperties": false, - "properties": { - "assistant_id": { - "description": "The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to execute this run.", - "type": "string" - }, - "model": { - "description": "The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute this run. If a value is provided here, it will override the model associated with the assistant. If not, the model associated with the assistant will be used.", - "anyOf": [ - { - "type": "string" - }, - { - "$ref": "#/components/schemas/AssistantSupportedModels" - } - ], - "x-oaiTypeLabel": "string", - "nullable": true - }, - "reasoning_effort": { - "$ref": "#/components/schemas/ReasoningEffort" - }, - "instructions": { - "description": "Overrides the [instructions](https://platform.openai.com/docs/api-reference/assistants/createAssistant) of the assistant. This is useful for modifying the behavior on a per-run basis.", - "type": "string", - "nullable": true - }, - "additional_instructions": { - "description": "Appends additional instructions at the end of the instructions for the run. This is useful for modifying the behavior on a per-run basis without overriding other instructions.", - "type": "string", - "nullable": true - }, - "additional_messages": { - "description": "Adds additional messages to the thread before creating the run.", - "type": "array", - "items": { - "$ref": "#/components/schemas/CreateMessageRequest" - }, - "nullable": true - }, - "tools": { - "description": "Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.", - "nullable": true, - "type": "array", - "maxItems": 20, - "items": { - "$ref": "#/components/schemas/AssistantTool" - } - }, - "metadata": { - "$ref": "#/components/schemas/Metadata" - }, - "temperature": { - "type": "number", - "minimum": 0, - "maximum": 2, - "default": 1, - "example": 1, - "nullable": true, - "description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n" - }, - "top_p": { - "type": "number", - "minimum": 0, - "maximum": 1, - "default": 1, - "example": 1, - "nullable": true, - "description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or temperature but not both.\n" - }, - "max_prompt_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of prompt tokens that may be used over the course of the run. The run will make a best effort to use only the number of prompt tokens specified, across multiple turns of the run. If the run exceeds the number of prompt tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.\n", - "minimum": 256 - }, - "max_completion_tokens": { - "type": "integer", - "nullable": true, - "description": "The maximum number of completion tokens that may be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.\n", - "minimum": 256 - }, - "truncation_strategy": { - "allOf": [ - { - "$ref": "#/components/schemas/TruncationObject" - }, - { - "nullable": true - } - ] - }, - "tool_choice": { - "allOf": [ - { - "$ref": "#/components/schemas/AssistantsApiToolChoiceOption" - }, - { - "nullable": true - } - ] - }, - "parallel_tool_calls": { - "$ref": "#/components/schemas/ParallelToolCalls" - }, - "response_format": { - "$ref": "#/components/schemas/AssistantsApiResponseFormatOption", - "nullable": true - } - }, - "required": [ - "assistant_id" - ] - }, - "SubmitToolOutputsRunRequestWithoutStream": { - "type": "object", - "additionalProperties": false, - "properties": { - "tool_outputs": { - "description": "A list of tools for which the outputs are being submitted.", - "type": "array", - "items": { - "type": "object", - "properties": { - "tool_call_id": { - "type": "string", - "description": "The ID of the tool call in the `required_action` object within the run object the output is being submitted for." - }, - "output": { - "type": "string", - "description": "The output of the tool call to be submitted to continue the run." - } - } - } - } - }, - "required": [ - "tool_outputs" - ] - }, - "RunStatus": { - "description": "The status of the run, which can be either `queued`, `in_progress`, `requires_action`, `cancelling`, `cancelled`, `failed`, `completed`, `incomplete`, or `expired`.", - "type": "string", - "enum": [ - "queued", - "in_progress", - "requires_action", - "cancelling", - "cancelled", - "failed", - "completed", - "incomplete", - "expired" - ] - }, - "RunStepDeltaObjectDelta": { - "description": "The delta containing the fields that have changed on the run step.", - "type": "object", - "properties": { - "step_details": { - "type": "object", - "description": "The details of the run step.", - "anyOf": [ - { - "$ref": "#/components/schemas/RunStepDeltaStepDetailsMessageCreationObject" - }, - { - "$ref": "#/components/schemas/RunStepDeltaStepDetailsToolCallsObject" - } - ], - "discriminator": { - "propertyName": "type" - } - } - } - } - }, - "securitySchemes": { - "ApiKeyAuth": { - "type": "http", - "scheme": "bearer" - } - } - }, - "x-oaiMeta": { - "navigationGroups": [ - { - "id": "responses", - "title": "Responses API" - }, - { - "id": "webhooks", - "title": "Webhooks" - }, - { - "id": "endpoints", - "title": "Platform APIs" - }, - { - "id": "vector_stores", - "title": "Vector stores" - }, - { - "id": "containers", - "title": "Containers" - }, - { - "id": "realtime", - "title": "Realtime" - }, - { - "id": "chat", - "title": "Chat Completions" - }, - { - "id": "assistants", - "title": "Assistants", - "beta": true - }, - { - "id": "administration", - "title": "Administration" - }, - { - "id": "legacy", - "title": "Legacy" - } - ], - "groups": [ - { - "id": "responses", - "title": "Responses", - "description": "OpenAI's most advanced interface for generating model responses. Supports\ntext and image inputs, and text outputs. Create stateful interactions\nwith the model, using the output of previous responses as input. Extend\nthe model's capabilities with built-in tools for file search, web search,\ncomputer use, and more. Allow the model access to external systems and data\nusing function calling.\n\nRelated guides:\n- [Quickstart](https://platform.openai.com/docs/quickstart?api-mode=responses)\n- [Text inputs and outputs](https://platform.openai.com/docs/guides/text?api-mode=responses)\n- [Image inputs](https://platform.openai.com/docs/guides/images?api-mode=responses)\n- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses)\n- [Function calling](https://platform.openai.com/docs/guides/function-calling?api-mode=responses)\n- [Conversation state](https://platform.openai.com/docs/guides/conversation-state?api-mode=responses)\n- [Extend the models with tools](https://platform.openai.com/docs/guides/tools?api-mode=responses)\n", - "navigationGroup": "responses", - "sections": [ - { - "type": "endpoint", - "key": "createResponse", - "path": "create" - }, - { - "type": "endpoint", - "key": "getResponse", - "path": "get" - }, - { - "type": "endpoint", - "key": "deleteResponse", - "path": "delete" - }, - { - "type": "endpoint", - "key": "cancelResponse", - "path": "cancel" - }, - { - "type": "endpoint", - "key": "listInputItems", - "path": "input-items" - }, - { - "type": "object", - "key": "Response", - "path": "object" - }, - { - "type": "object", - "key": "ResponseItemList", - "path": "list" - } - ] - }, - { - "id": "conversations", - "title": "Conversations", - "description": "Create and manage conversations to store and retrieve conversation state across Response API calls.\n", - "navigationGroup": "responses", - "sections": [ - { - "type": "endpoint", - "key": "createConversation", - "path": "create" - }, - { - "type": "endpoint", - "key": "getConversation", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "updateConversation", - "path": "update" - }, - { - "type": "endpoint", - "key": "deleteConversation", - "path": "delete" - }, - { - "type": "endpoint", - "key": "listConversationItems", - "path": "list-items" - }, - { - "type": "endpoint", - "key": "createConversationItems", - "path": "create-items" - }, - { - "type": "endpoint", - "key": "getConversationItem", - "path": "get-item" - }, - { - "type": "endpoint", - "key": "deleteConversationItem", - "path": "delete-item" - }, - { - "type": "object", - "key": "Conversation", - "path": "object" - }, - { - "type": "object", - "key": "ConversationItemList", - "path": "list-items-object" - } - ] - }, - { - "id": "responses-streaming", - "title": "Streaming events", - "description": "When you [create a Response](https://platform.openai.com/docs/api-reference/responses/create) with\n`stream` set to `true`, the server will emit server-sent events to the\nclient as the Response is generated. This section contains the events that\nare emitted by the server.\n\n[Learn more about streaming responses](https://platform.openai.com/docs/guides/streaming-responses?api-mode=responses).\n", - "navigationGroup": "responses", - "sections": [ - { - "type": "object", - "key": "ResponseCreatedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseInProgressEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseCompletedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseFailedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseIncompleteEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseOutputItemAddedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseOutputItemDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseContentPartAddedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseContentPartDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseTextDeltaEvent", - "path": "response/output_text/delta" - }, - { - "type": "object", - "key": "ResponseTextDoneEvent", - "path": "response/output_text/done" - }, - { - "type": "object", - "key": "ResponseRefusalDeltaEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseRefusalDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseFunctionCallArgumentsDeltaEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseFunctionCallArgumentsDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseFileSearchCallInProgressEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseFileSearchCallSearchingEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseFileSearchCallCompletedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseWebSearchCallInProgressEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseWebSearchCallSearchingEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseWebSearchCallCompletedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseReasoningSummaryPartAddedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseReasoningSummaryPartDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseReasoningSummaryTextDeltaEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseReasoningSummaryTextDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseReasoningTextDeltaEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseReasoningTextDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseImageGenCallCompletedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseImageGenCallGeneratingEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseImageGenCallInProgressEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseImageGenCallPartialImageEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseMCPCallArgumentsDeltaEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseMCPCallArgumentsDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseMCPCallCompletedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseMCPCallFailedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseMCPCallInProgressEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseMCPListToolsCompletedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseMCPListToolsFailedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseMCPListToolsInProgressEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseCodeInterpreterCallInProgressEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseCodeInterpreterCallInterpretingEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseCodeInterpreterCallCompletedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseCodeInterpreterCallCodeDeltaEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseCodeInterpreterCallCodeDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseOutputTextAnnotationAddedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseQueuedEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseCustomToolCallInputDeltaEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseCustomToolCallInputDoneEvent", - "path": "" - }, - { - "type": "object", - "key": "ResponseErrorEvent", - "path": "" - } - ] - }, - { - "id": "webhook-events", - "title": "Webhook Events", - "description": "Webhooks are HTTP requests sent by OpenAI to a URL you specify when certain\nevents happen during the course of API usage.\n\n[Learn more about webhooks](https://platform.openai.com/docs/guides/webhooks).\n", - "navigationGroup": "webhooks", - "sections": [ - { - "type": "object", - "key": "WebhookResponseCompleted", - "path": "" - }, - { - "type": "object", - "key": "WebhookResponseCancelled", - "path": "" - 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"path": "" - } - ] - }, - { - "id": "audio", - "title": "Audio", - "description": "Learn how to turn audio into text or text into audio.\n\nRelated guide: [Speech to text](https://platform.openai.com/docs/guides/speech-to-text)\n", - "navigationGroup": "endpoints", - "sections": [ - { - "type": "endpoint", - "key": "createSpeech", - "path": "createSpeech" - }, - { - "type": "endpoint", - "key": "createTranscription", - "path": "createTranscription" - }, - { - "type": "endpoint", - "key": "createTranslation", - "path": "createTranslation" - }, - { - "type": "object", - "key": "CreateTranscriptionResponseJson", - "path": "json-object" - }, - { - "type": "object", - "key": "CreateTranscriptionResponseVerboseJson", - "path": "verbose-json-object" - }, - { - "type": "object", - "key": "SpeechAudioDeltaEvent", - "path": "speech-audio-delta-event" - }, - { - "type": "object", - "key": "SpeechAudioDoneEvent", - "path": "speech-audio-done-event" - }, - { - "type": "object", - "key": "TranscriptTextDeltaEvent", - "path": "transcript-text-delta-event" - }, - { - "type": "object", - "key": "TranscriptTextDoneEvent", - "path": "transcript-text-done-event" - } - ] - }, - { - "id": "images", - "title": "Images", - "description": "Given a prompt and/or an input image, the model will generate a new image.\nRelated guide: [Image generation](https://platform.openai.com/docs/guides/images)\n", - "navigationGroup": "endpoints", - "sections": [ - { - "type": "endpoint", - "key": "createImage", - "path": "create" - }, - { - "type": "endpoint", - "key": "createImageEdit", - "path": "createEdit" - }, - { - "type": "endpoint", - "key": "createImageVariation", - "path": "createVariation" - }, - { - "type": "object", - "key": "ImagesResponse", - "path": "object" - } - ] - }, - { - "id": "images-streaming", - "title": "Image Streaming", - "description": "Stream image generation and editing in real time with server-sent events.\n[Learn more about image streaming](https://platform.openai.com/docs/guides/image-generation).\n", - "navigationGroup": "endpoints", - "sections": [ - { - "type": "object", - "key": "ImageGenPartialImageEvent", - "path": "" - }, - { - "type": "object", - "key": "ImageGenCompletedEvent", - "path": "" - }, - { - "type": "object", - "key": "ImageEditPartialImageEvent", - "path": "" - }, - { - "type": "object", - "key": "ImageEditCompletedEvent", - "path": "" - } - ] - }, - { - "id": "embeddings", - "title": "Embeddings", - "description": "Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.\nRelated guide: [Embeddings](https://platform.openai.com/docs/guides/embeddings)\n", - "navigationGroup": "endpoints", - "sections": [ - { - "type": "endpoint", - "key": "createEmbedding", - "path": "create" - }, - { - "type": "object", - "key": "Embedding", - "path": "object" - } - ] - }, - { - "id": "evals", - "title": "Evals", - "description": "Create, manage, and run evals in the OpenAI platform.\nRelated guide: [Evals](https://platform.openai.com/docs/guides/evals)\n", - 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}, - { - "id": "batch", - "title": "Batch", - "description": "Create large batches of API requests for asynchronous processing. The Batch API returns completions within 24 hours for a 50% discount.\nRelated guide: [Batch](https://platform.openai.com/docs/guides/batch)\n", - "navigationGroup": "endpoints", - "sections": [ - { - "type": "endpoint", - "key": "createBatch", - "path": "create" - }, - { - "type": "endpoint", - "key": "retrieveBatch", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "cancelBatch", - "path": "cancel" - }, - { - "type": "endpoint", - "key": "listBatches", - "path": "list" - }, - { - "type": "object", - "key": "Batch", - "path": "object" - }, - { - "type": "object", - "key": "BatchRequestInput", - "path": "request-input" - }, - { - "type": "object", - "key": "BatchRequestOutput", - "path": "request-output" - } - ] - }, - { - "id": "files", - "title": "Files", - "description": "Files are used to upload documents that can be used with features like [Assistants](https://platform.openai.com/docs/api-reference/assistants), [Fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning), and [Batch API](https://platform.openai.com/docs/guides/batch).\n", - "navigationGroup": "endpoints", - "sections": [ - { - "type": "endpoint", - "key": "createFile", - "path": "create" - }, - { - "type": "endpoint", - "key": "listFiles", - "path": "list" - }, - { - "type": "endpoint", - "key": "retrieveFile", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "deleteFile", - "path": "delete" - }, - { - "type": "endpoint", - "key": "downloadFile", - "path": "retrieve-contents" - }, - { - "type": "object", - "key": "OpenAIFile", - "path": "object" - } - ] - }, - { - "id": "uploads", - "title": "Uploads", - "description": "Allows you to upload large files in multiple parts.\n", - "navigationGroup": "endpoints", - "sections": [ - { - "type": "endpoint", - "key": "createUpload", - "path": "create" - }, - { - "type": "endpoint", - "key": "addUploadPart", - "path": "add-part" - }, - { - "type": "endpoint", - "key": "completeUpload", - "path": "complete" - }, - { - "type": "endpoint", - "key": "cancelUpload", - "path": "cancel" - }, - { - "type": "object", - "key": "Upload", - "path": "object" - }, - { - "type": "object", - "key": "UploadPart", - "path": "part-object" - } - ] - }, - { - "id": "models", - "title": "Models", - "description": "List and describe the various models available in the API. You can refer to the [Models](https://platform.openai.com/docs/models) documentation to understand what models are available and the differences between them.\n", - "navigationGroup": "endpoints", - "sections": [ - { - "type": "endpoint", - "key": "listModels", - "path": "list" - }, - { - "type": "endpoint", - "key": "retrieveModel", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "deleteModel", - "path": "delete" - }, - { - "type": "object", - "key": "Model", - "path": "object" - } - ] - }, - { - "id": "moderations", - "title": "Moderations", - "description": "Given text and/or image inputs, classifies if those inputs are potentially harmful across several categories.\nRelated guide: [Moderations](https://platform.openai.com/docs/guides/moderation)\n", - "navigationGroup": "endpoints", - "sections": [ - { - "type": "endpoint", - "key": "createModeration", - "path": "create" - }, - { - "type": "object", - "key": "CreateModerationResponse", - "path": "object" - } - ] - }, - { - "id": "vector-stores", - "title": "Vector stores", - "description": "Vector stores power semantic search for the Retrieval API and the `file_search` tool in the Responses and Assistants APIs.\n\nRelated guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)\n", - "navigationGroup": "vector_stores", - "sections": [ - { - "type": "endpoint", - "key": "createVectorStore", - "path": "create" - }, - { - "type": "endpoint", - "key": "listVectorStores", - "path": "list" - }, - { - "type": "endpoint", - "key": "getVectorStore", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "modifyVectorStore", - "path": "modify" - }, - { - "type": "endpoint", - "key": "deleteVectorStore", - "path": "delete" - }, - { - "type": "endpoint", - "key": "searchVectorStore", - "path": "search" - }, - { - "type": "object", - "key": "VectorStoreObject", - "path": "object" - } - ] - }, - { - "id": "vector-stores-files", - "title": "Vector store files", - "description": "Vector store files represent files inside a vector store.\n\nRelated guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)\n", - "navigationGroup": "vector_stores", - "sections": [ - { - "type": "endpoint", - "key": "createVectorStoreFile", - "path": "createFile" - }, - { - "type": "endpoint", - "key": "listVectorStoreFiles", - "path": "listFiles" - }, - { - "type": "endpoint", - "key": "getVectorStoreFile", - "path": "getFile" - }, - { - "type": "endpoint", - "key": "retrieveVectorStoreFileContent", - "path": "getContent" - }, - { - "type": "endpoint", - "key": "updateVectorStoreFileAttributes", - "path": "updateAttributes" - }, - { - "type": "endpoint", - "key": "deleteVectorStoreFile", - "path": "deleteFile" - }, - { - "type": "object", - "key": "VectorStoreFileObject", - "path": "file-object" - } - ] - }, - { - "id": "vector-stores-file-batches", - "title": "Vector store file batches", - "description": "Vector store file batches represent operations to add multiple files to a vector store.\nRelated guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)\n", - "navigationGroup": "vector_stores", - "sections": [ - { - "type": "endpoint", - "key": "createVectorStoreFileBatch", - "path": "createBatch" - }, - { - "type": "endpoint", - "key": "getVectorStoreFileBatch", - "path": "getBatch" - }, - { - "type": "endpoint", - "key": "cancelVectorStoreFileBatch", - "path": "cancelBatch" - }, - { - "type": "endpoint", - "key": "listFilesInVectorStoreBatch", - "path": "listBatchFiles" - }, - { - "type": "object", - "key": "VectorStoreFileBatchObject", - "path": "batch-object" - } - ] - }, - { - "id": "containers", - "title": "Containers", - "description": "Create and manage containers for use with the Code Interpreter tool.\n", - "navigationGroup": "containers", - "sections": [ - { - "type": "endpoint", - "key": "CreateContainer", - "path": "createContainers" - }, - { - "type": "endpoint", - "key": "ListContainers", - "path": "listContainers" - }, - { - "type": "endpoint", - "key": "RetrieveContainer", - "path": "retrieveContainer" - }, - { - "type": "endpoint", - "key": "DeleteContainer", - "path": "deleteContainer" - }, - { - "type": "object", - "key": "ContainerResource", - "path": "object" - } - ] - }, - { - "id": "container-files", - "title": "Container Files", - "description": "Create and manage container files for use with the Code Interpreter tool.\n", - "navigationGroup": "containers", - "sections": [ - { - "type": "endpoint", - "key": "CreateContainerFile", - "path": "createContainerFile" - }, - { - "type": "endpoint", - "key": "ListContainerFiles", - "path": "listContainerFiles" - }, - { - "type": "endpoint", - "key": "RetrieveContainerFile", - "path": "retrieveContainerFile" - }, - { - "type": "endpoint", - "key": "RetrieveContainerFileContent", - "path": "retrieveContainerFileContent" - }, - { - "type": "endpoint", - "key": "DeleteContainerFile", - "path": "deleteContainerFile" - }, - { - "type": "object", - "key": "ContainerFileResource", - "path": "object" - } - ] - }, - { - "id": "realtime", - "title": "Realtime", - "description": "Communicate with a multimodal model in real time over low latency interfaces\nlike WebRTC, WebSocket, and SIP. Natively supports speech-to-speech\nas well as text, image, and audio inputs and outputs.\n\n[Learn more about the Realtime API](https://platform.openai.com/docs/guides/realtime).\n", - "navigationGroup": "realtime" - }, - { - "id": "realtime-sessions", - "title": "Session tokens", - "description": "REST API endpoint to generate ephemeral session tokens for use in client-side\napplications.\n", - "navigationGroup": "realtime", - "sections": [ - { - "type": "endpoint", - "key": "create-realtime-client-secret", - "path": "create-realtime-client-secret" - }, - { - "type": "object", - "key": "RealtimeCreateClientSecretResponse", - "path": "create-secret-response" - } - ] - }, - { - "id": "realtime-client-events", - "title": "Client events", - "description": "These are events that the OpenAI Realtime WebSocket server will accept from the client.\n", - "navigationGroup": "realtime", - "sections": [ - { - "type": "object", - "key": "RealtimeClientEventSessionUpdate", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventInputAudioBufferAppend", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventInputAudioBufferCommit", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventInputAudioBufferClear", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventConversationItemCreate", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventConversationItemRetrieve", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventConversationItemTruncate", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventConversationItemDelete", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventResponseCreate", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventResponseCancel", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventTranscriptionSessionUpdate", - "path": "" - }, - { - "type": "object", - "key": "RealtimeClientEventOutputAudioBufferClear", - "path": "" - } - ] - }, - { - "id": "realtime-server-events", - "title": "Server events", - "description": "These are events emitted from the OpenAI Realtime WebSocket server to the client.\n", - "navigationGroup": "realtime", - "sections": [ - { - "type": "object", - "key": "RealtimeServerEventError", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventSessionCreated", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventSessionUpdated", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventTranscriptionSessionCreated", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemCreated", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemAdded", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemDone", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemRetrieved", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemInputAudioTranscriptionCompleted", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemInputAudioTranscriptionDelta", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemInputAudioTranscriptionSegment", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemInputAudioTranscriptionFailed", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemTruncated", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventConversationItemDeleted", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventInputAudioBufferCommitted", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventInputAudioBufferCleared", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventInputAudioBufferSpeechStarted", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventInputAudioBufferSpeechStopped", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventInputAudioBufferTimeoutTriggered", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseCreated", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseDone", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseOutputItemAdded", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseOutputItemDone", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseContentPartAdded", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseContentPartDone", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseTextDelta", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseTextDone", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseAudioTranscriptDelta", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseAudioTranscriptDone", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseAudioDelta", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseAudioDone", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseFunctionCallArgumentsDelta", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseFunctionCallArgumentsDone", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseMCPCallArgumentsDelta", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseMCPCallArgumentsDone", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventMCPListToolsInProgress", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventMCPListToolsCompleted", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventMCPListToolsFailed", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseMCPCallInProgress", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseMCPCallCompleted", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventResponseMCPCallFailed", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventTranscriptionSessionUpdated", - "path": "" - }, - { - "type": "object", - "key": "RealtimeServerEventRateLimitsUpdated", - "path": "" - } - ] - }, - { - "id": "chat", - "title": "Chat Completions", - "description": "The Chat Completions API endpoint will generate a model response from a\nlist of messages comprising a conversation.\n\nRelated guides:\n- [Quickstart](https://platform.openai.com/docs/quickstart?api-mode=chat)\n- [Text inputs and outputs](https://platform.openai.com/docs/guides/text?api-mode=chat)\n- [Image inputs](https://platform.openai.com/docs/guides/images?api-mode=chat)\n- [Audio inputs and outputs](https://platform.openai.com/docs/guides/audio?api-mode=chat)\n- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs?api-mode=chat)\n- [Function calling](https://platform.openai.com/docs/guides/function-calling?api-mode=chat)\n- [Conversation state](https://platform.openai.com/docs/guides/conversation-state?api-mode=chat)\n\n**Starting a new project?** We recommend trying [Responses](https://platform.openai.com/docs/api-reference/responses)\nto take advantage of the latest OpenAI platform features. Compare\n[Chat Completions with Responses](https://platform.openai.com/docs/guides/responses-vs-chat-completions?api-mode=responses).\n", - "navigationGroup": "chat", - "sections": [ - { - "type": "endpoint", - "key": "createChatCompletion", - "path": "create" - }, - { - "type": "endpoint", - "key": "getChatCompletion", - "path": "get" - }, - { - "type": "endpoint", - "key": "getChatCompletionMessages", - "path": "getMessages" - }, - { - "type": "endpoint", - "key": "listChatCompletions", - "path": "list" - }, - { - "type": "endpoint", - "key": "updateChatCompletion", - "path": "update" - }, - { - "type": "endpoint", - "key": "deleteChatCompletion", - "path": "delete" - }, - { - "type": "object", - "key": "CreateChatCompletionResponse", - "path": "object" - }, - { - "type": "object", - "key": "ChatCompletionList", - "path": "list-object" - }, - { - "type": "object", - "key": "ChatCompletionMessageList", - "path": "message-list" - } - ] - }, - { - "id": "chat-streaming", - "title": "Streaming", - "description": "Stream Chat Completions in real time. Receive chunks of completions\nreturned from the model using server-sent events.\n[Learn more](https://platform.openai.com/docs/guides/streaming-responses?api-mode=chat).\n", - "navigationGroup": "chat", - "sections": [ - { - "type": "object", - "key": "CreateChatCompletionStreamResponse", - "path": "streaming" - } - ] - }, - { - "id": "assistants", - "title": "Assistants", - "beta": true, - "description": "Build assistants that can call models and use tools to perform tasks.\n\n[Get started with the Assistants API](https://platform.openai.com/docs/assistants)\n", - "navigationGroup": "assistants", - "sections": [ - { - "type": "endpoint", - "key": "createAssistant", - "path": "createAssistant" - }, - { - "type": "endpoint", - "key": "listAssistants", - "path": "listAssistants" - }, - { - "type": "endpoint", - "key": "getAssistant", - "path": "getAssistant" - }, - { - "type": "endpoint", - "key": "modifyAssistant", - "path": "modifyAssistant" - }, - { - "type": "endpoint", - "key": "deleteAssistant", - "path": "deleteAssistant" - }, - { - "type": "object", - "key": "AssistantObject", - "path": "object" - } - ] - }, - { - "id": "threads", - "title": "Threads", - "beta": true, - "description": "Create threads that assistants can interact with.\n\nRelated guide: [Assistants](https://platform.openai.com/docs/assistants/overview)\n", - "navigationGroup": "assistants", - "sections": [ - { - "type": "endpoint", - "key": "createThread", - "path": "createThread" - }, - { - "type": "endpoint", - "key": "getThread", - "path": "getThread" - }, - { - "type": "endpoint", - "key": "modifyThread", - "path": "modifyThread" - }, - { - "type": "endpoint", - "key": "deleteThread", - "path": "deleteThread" - }, - { - "type": "object", - "key": "ThreadObject", - "path": "object" - } - ] - }, - { - "id": "messages", - "title": "Messages", - "beta": true, - "description": "Create messages within threads\n\nRelated guide: [Assistants](https://platform.openai.com/docs/assistants/overview)\n", - "navigationGroup": "assistants", - "sections": [ - { - "type": "endpoint", - "key": "createMessage", - "path": "createMessage" - }, - { - "type": "endpoint", - "key": "listMessages", - "path": "listMessages" - }, - { - "type": "endpoint", - "key": "getMessage", - "path": "getMessage" - }, - { - "type": "endpoint", - "key": "modifyMessage", - "path": "modifyMessage" - }, - { - "type": "endpoint", - "key": "deleteMessage", - "path": "deleteMessage" - }, - { - "type": "object", - "key": "MessageObject", - "path": "object" - } - ] - }, - { - "id": "runs", - "title": "Runs", - "beta": true, - "description": "Represents an execution run on a thread.\n\nRelated guide: [Assistants](https://platform.openai.com/docs/assistants/overview)\n", - "navigationGroup": "assistants", - "sections": [ - { - "type": "endpoint", - "key": "createRun", - "path": "createRun" - }, - { - "type": "endpoint", - "key": "createThreadAndRun", - "path": "createThreadAndRun" - }, - { - "type": "endpoint", - "key": "listRuns", - "path": "listRuns" - }, - { - "type": "endpoint", - "key": "getRun", - "path": "getRun" - }, - { - "type": "endpoint", - "key": "modifyRun", - "path": "modifyRun" - }, - { - "type": "endpoint", - "key": "submitToolOuputsToRun", - "path": "submitToolOutputs" - }, - { - "type": "endpoint", - "key": "cancelRun", - "path": "cancelRun" - }, - { - "type": "object", - "key": "RunObject", - "path": "object" - } - ] - }, - { - "id": "run-steps", - "title": "Run steps", - "beta": true, - "description": "Represents the steps (model and tool calls) taken during the run.\n\nRelated guide: [Assistants](https://platform.openai.com/docs/assistants/overview)\n", - "navigationGroup": "assistants", - "sections": [ - { - "type": "endpoint", - "key": "listRunSteps", - "path": "listRunSteps" - }, - { - "type": "endpoint", - "key": "getRunStep", - "path": "getRunStep" - }, - { - "type": "object", - "key": "RunStepObject", - "path": "step-object" - } - ] - }, - { - "id": "assistants-streaming", - "title": "Streaming", - "beta": true, - "description": "Stream the result of executing a Run or resuming a Run after submitting tool outputs.\nYou can stream events from the [Create Thread and Run](https://platform.openai.com/docs/api-reference/runs/createThreadAndRun),\n[Create Run](https://platform.openai.com/docs/api-reference/runs/createRun), and [Submit Tool Outputs](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs)\nendpoints by passing `\"stream\": true`. The response will be a [Server-Sent events](https://html.spec.whatwg.org/multipage/server-sent-events.html#server-sent-events) stream.\nOur Node and Python SDKs provide helpful utilities to make streaming easy. Reference the\n[Assistants API quickstart](https://platform.openai.com/docs/assistants/overview) to learn more.\n", - "navigationGroup": "assistants", - "sections": [ - { - "type": "object", - "key": "MessageDeltaObject", - "path": "message-delta-object" - }, - { - "type": "object", - "key": "RunStepDeltaObject", - "path": "run-step-delta-object" - }, - { - "type": "object", - "key": "AssistantStreamEvent", - "path": "events" - } - ] - }, - { - "id": "administration", - "title": "Administration", - "description": "Programmatically manage your organization.\nThe Audit Logs endpoint provides a log of all actions taken in the organization for security and monitoring purposes.\nTo access these endpoints please generate an Admin API Key through the [API Platform Organization overview](/organization/admin-keys). Admin API keys cannot be used for non-administration endpoints.\nFor best practices on setting up your organization, please refer to this [guide](https://platform.openai.com/docs/guides/production-best-practices#setting-up-your-organization)\n", - "navigationGroup": "administration" - }, - { - "id": "admin-api-keys", - "title": "Admin API Keys", - "description": "Admin API keys enable Organization Owners to programmatically manage various aspects of their organization, including users, projects, and API keys. These keys provide administrative capabilities, such as creating, updating, and deleting users; managing projects; and overseeing API key lifecycles.\n\nKey Features of Admin API Keys:\n\n- User Management: Invite new users, update roles, and remove users from the organization.\n\n- Project Management: Create, update, archive projects, and manage user assignments within projects.\n\n- API Key Oversight: List, retrieve, and delete API keys associated with projects.\n\nOnly Organization Owners have the authority to create and utilize Admin API keys. To manage these keys, Organization Owners can navigate to the Admin Keys section of their API Platform dashboard.\n\nFor direct access to the Admin Keys management page, Organization Owners can use the following link:\n\n[https://platform.openai.com/settings/organization/admin-keys](https://platform.openai.com/settings/organization/admin-keys)\n\nIt's crucial to handle Admin API keys with care due to their elevated permissions. Adhering to best practices, such as regular key rotation and assigning appropriate permissions, enhances security and ensures proper governance within the organization.\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "admin-api-keys-list", - "path": "list" - }, - { - "type": "endpoint", - "key": "admin-api-keys-create", - "path": "create" - }, - { - "type": "endpoint", - "key": "admin-api-keys-get", - "path": "listget" - }, - { - "type": "endpoint", - "key": "admin-api-keys-delete", - "path": "delete" - }, - { - "type": "object", - "key": "AdminApiKey", - "path": "object" - } - ] - }, - { - "id": "invite", - "title": "Invites", - "description": "Invite and manage invitations for an organization.", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "list-invites", - "path": "list" - }, - { - "type": "endpoint", - "key": "inviteUser", - "path": "create" - }, - { - "type": "endpoint", - "key": "retrieve-invite", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "delete-invite", - "path": "delete" - }, - { - "type": "object", - "key": "Invite", - "path": "object" - } - ] - }, - { - "id": "users", - "title": "Users", - "description": "Manage users and their role in an organization.\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "list-users", - "path": "list" - }, - { - "type": "endpoint", - "key": "modify-user", - "path": "modify" - }, - { - "type": "endpoint", - "key": "retrieve-user", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "delete-user", - "path": "delete" - }, - { - "type": "object", - "key": "User", - "path": "object" - } - ] - }, - { - "id": "projects", - "title": "Projects", - "description": "Manage the projects within an orgnanization includes creation, updating, and archiving or projects.\nThe Default project cannot be archived.\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "list-projects", - "path": "list" - }, - { - "type": "endpoint", - "key": "create-project", - "path": "create" - }, - { - "type": "endpoint", - "key": "retrieve-project", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "modify-project", - "path": "modify" - }, - { - "type": "endpoint", - "key": "archive-project", - "path": "archive" - }, - { - "type": "object", - "key": "Project", - "path": "object" - } - ] - }, - { - "id": "project-users", - "title": "Project users", - "description": "Manage users within a project, including adding, updating roles, and removing users.\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "list-project-users", - "path": "list" - }, - { - "type": "endpoint", - "key": "create-project-user", - "path": "create" - }, - { - "type": "endpoint", - "key": "retrieve-project-user", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "modify-project-user", - "path": "modify" - }, - { - "type": "endpoint", - "key": "delete-project-user", - "path": "delete" - }, - { - "type": "object", - "key": "ProjectUser", - "path": "object" - } - ] - }, - { - "id": "project-service-accounts", - "title": "Project service accounts", - "description": "Manage service accounts within a project. A service account is a bot user that is not associated with a user.\nIf a user leaves an organization, their keys and membership in projects will no longer work. Service accounts\ndo not have this limitation. However, service accounts can also be deleted from a project.\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "list-project-service-accounts", - "path": "list" - }, - { - "type": "endpoint", - "key": "create-project-service-account", - "path": "create" - }, - { - "type": "endpoint", - "key": "retrieve-project-service-account", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "delete-project-service-account", - "path": "delete" - }, - { - "type": "object", - "key": "ProjectServiceAccount", - "path": "object" - } - ] - }, - { - "id": "project-api-keys", - "title": "Project API keys", - "description": "Manage API keys for a given project. Supports listing and deleting keys for users.\nThis API does not allow issuing keys for users, as users need to authorize themselves to generate keys.\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "list-project-api-keys", - "path": "list" - }, - { - "type": "endpoint", - "key": "retrieve-project-api-key", - "path": "retrieve" - }, - { - "type": "endpoint", - "key": "delete-project-api-key", - "path": "delete" - }, - { - "type": "object", - "key": "ProjectApiKey", - "path": "object" - } - ] - }, - { - "id": "project-rate-limits", - "title": "Project rate limits", - "description": "Manage rate limits per model for projects. Rate limits may be configured to be equal to or lower than the organization's rate limits.\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "list-project-rate-limits", - "path": "list" - }, - { - "type": "endpoint", - "key": "update-project-rate-limits", - "path": "update" - }, - { - "type": "object", - "key": "ProjectRateLimit", - "path": "object" - } - ] - }, - { - "id": "audit-logs", - "title": "Audit logs", - "description": "Logs of user actions and configuration changes within this organization.\nTo log events, an Organization Owner must activate logging in the [Data Controls Settings](/settings/organization/data-controls/data-retention).\nOnce activated, for security reasons, logging cannot be deactivated.\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "list-audit-logs", - "path": "list" - }, - { - "type": "object", - "key": "AuditLog", - "path": "object" - } - ] - }, - { - "id": "usage", - "title": "Usage", - "description": "The **Usage API** provides detailed insights into your activity across the OpenAI API. It also includes a separate [Costs endpoint](https://platform.openai.com/docs/api-reference/usage/costs), which offers visibility into your spend, breaking down consumption by invoice line items and project IDs.\n\nWhile the Usage API delivers granular usage data, it may not always reconcile perfectly with the Costs due to minor differences in how usage and spend are recorded. For financial purposes, we recommend using the [Costs endpoint](https://platform.openai.com/docs/api-reference/usage/costs) or the [Costs tab](/settings/organization/usage) in the Usage Dashboard, which will reconcile back to your billing invoice.\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "usage-completions", - "path": "completions" - }, - { - "type": "object", - "key": "UsageCompletionsResult", - "path": "completions_object" - }, - { - "type": "endpoint", - "key": "usage-embeddings", - "path": "embeddings" - }, - { - "type": "object", - "key": "UsageEmbeddingsResult", - "path": "embeddings_object" - }, - { - "type": "endpoint", - "key": "usage-moderations", - "path": "moderations" - }, - { - "type": "object", - "key": "UsageModerationsResult", - "path": "moderations_object" - }, - { - "type": "endpoint", - "key": "usage-images", - "path": "images" - }, - { - "type": "object", - "key": "UsageImagesResult", - "path": "images_object" - }, - { - "type": "endpoint", - "key": "usage-audio-speeches", - "path": "audio_speeches" - }, - { - "type": "object", - "key": "UsageAudioSpeechesResult", - "path": "audio_speeches_object" - }, - { - "type": "endpoint", - "key": "usage-audio-transcriptions", - "path": "audio_transcriptions" - }, - { - "type": "object", - "key": "UsageAudioTranscriptionsResult", - "path": "audio_transcriptions_object" - }, - { - "type": "endpoint", - "key": "usage-vector-stores", - "path": "vector_stores" - }, - { - "type": "object", - "key": "UsageVectorStoresResult", - "path": "vector_stores_object" - }, - { - "type": "endpoint", - "key": "usage-code-interpreter-sessions", - "path": "code_interpreter_sessions" - }, - { - "type": "object", - "key": "UsageCodeInterpreterSessionsResult", - "path": "code_interpreter_sessions_object" - }, - { - "type": "endpoint", - "key": "usage-costs", - "path": "costs" - }, - { - "type": "object", - "key": "CostsResult", - "path": "costs_object" - } - ] - }, - { - "id": "certificates", - "beta": true, - "title": "Certificates", - "description": "Manage Mutual TLS certificates across your organization and projects.\n\n[Learn more about Mutual TLS.](https://help.openai.com/en/articles/10876024-openai-mutual-tls-beta-program)\n", - "navigationGroup": "administration", - "sections": [ - { - "type": "endpoint", - "key": "uploadCertificate", - "path": "uploadCertificate" - }, - { - "type": "endpoint", - "key": "getCertificate", - "path": "getCertificate" - }, - { - "type": "endpoint", - "key": "modifyCertificate", - "path": "modifyCertificate" - }, - { - "type": "endpoint", - "key": "deleteCertificate", - "path": "deleteCertificate" - }, - { - "type": "endpoint", - "key": "listOrganizationCertificates", - "path": "listOrganizationCertificates" - }, - { - "type": "endpoint", - "key": "listProjectCertificates", - "path": "listProjectCertificates" - }, - { - "type": "endpoint", - "key": "activateOrganizationCertificates", - "path": "activateOrganizationCertificates" - }, - { - "type": "endpoint", - "key": "deactivateOrganizationCertificates", - "path": "deactivateOrganizationCertificates" - }, - { - "type": "endpoint", - "key": "activateProjectCertificates", - "path": "activateProjectCertificates" - }, - { - "type": "endpoint", - "key": "deactivateProjectCertificates", - "path": "deactivateProjectCertificates" - }, - { - "type": "object", - "key": "Certificate", - "path": "object" - } - ] - }, - { - "id": "completions", - "title": "Completions", - "legacy": true, - "navigationGroup": "legacy", - "description": "Given a prompt, the model will return one or more predicted completions along with the probabilities of alternative tokens at each position. Most developer should use our [Chat Completions API](https://platform.openai.com/docs/guides/text-generation#text-generation-models) to leverage our best and newest models.\n", - "sections": [ - { - "type": "endpoint", - "key": "createCompletion", - "path": "create" - }, - { - "type": "object", - "key": "CreateCompletionResponse", - "path": "object" - } - ] - } - ] - } -} \ No newline at end of file diff --git a/website/public/openapi/openapi.json b/website/public/openapi/openapi.json deleted file mode 100644 index 976199abf..000000000 --- a/website/public/openapi/openapi.json +++ /dev/null @@ -1,515 +0,0 @@ -{ - "openapi": "3.1.0", - "info": { - "title": "๐Ÿ‘‹Jan API", - "description": "OpenAI-compatible API for local inference with Jan. Run AI models locally with complete privacy using llama.cpp's high-performance inference engine. Supports GGUF models with CPU and GPU acceleration. No authentication required for local usage.", - "version": "0.3.14", - "contact": { - "name": "Jan Support", - "url": "https://jan.ai/support", - "email": "support@jan.ai" - }, - "license": { - "name": "Apache 2.0", - "url": "https://github.com/janhq/jan/blob/main/LICENSE" - } - }, - "servers": [ - { - "url": "http://127.0.0.1:1337", - "description": "Local Jan Server (Default IP)" - }, - { - "url": "http://localhost:1337", - "description": "Local Jan Server (localhost)" - }, - { - "url": "http://localhost:8080", - "description": "Local Jan Server (Alternative Port)" - } - ], - "tags": [ - { - "name": "Models", - "description": "List and describe available models" - }, - { - "name": "Chat", - "description": "Chat completion endpoints for conversational AI" - }, - { - "name": "Completions", - "description": "Text completion endpoints for generating text" - }, - { - "name": "Extras", - "description": "Additional utility endpoints for tokenization and text processing" - } - ], - "paths": { - "/v1/completions": { - "post": { - "tags": ["Completions"], - "summary": "Create completion", - "description": "Creates a completion for the provided prompt and parameters. This endpoint is compatible with OpenAI's completions API.", - "operationId": "create_completion", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateCompletionRequest" - }, - "examples": { - "basic": { - "summary": "Basic Completion", - "description": "Simple text completion example", - "value": { - "model": "gemma-2-2b-it-Q8_0", - "prompt": "Once upon a time", - "max_tokens": 50, - "temperature": 0.7 - } - }, - "creative": { - "summary": "Creative Writing", - "description": "Generate creative content with higher temperature", - "value": { - "model": "gemma-2-2b-it-Q8_0", - "prompt": "Write a short poem about coding:", - "max_tokens": 150, - "temperature": 1, - "top_p": 0.95 - } - }, - "code": { - "summary": "Code Generation", - "description": "Generate code with lower temperature for accuracy", - "value": { - "model": "gemma-2-2b-it-Q8_0", - "prompt": "# Python function to calculate fibonacci\ndef fibonacci(n):", - "max_tokens": 200, - "temperature": 0.3, - "stop": ["\n\n", "def ", "class "] - } - }, - "streaming": { - "summary": "Streaming Response", - "description": "Stream tokens as they are generated", - "value": { - "model": "gemma-2-2b-it-Q8_0", - "prompt": "Explain quantum computing in simple terms:", - "max_tokens": 300, - "temperature": 0.7, - "stream": true - } - } - } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateCompletionResponse" - } - } - } - }, - "202": { - "description": "Accepted - Request is being processed", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateCompletionResponse" - } - }, - "text/event-stream": { - "schema": { - "type": "string", - "format": "binary", - "description": "Server-sent events stream for streaming responses" - } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ValidationError" - } - } - } - } - } - } - }, - "/v1/chat/completions": { - "post": { - "tags": ["Chat"], - "summary": "Create chat completion", - "description": "Creates a model response for the given chat conversation. This endpoint is compatible with OpenAI's chat completions API.", - "operationId": "create_chat_completion", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateChatCompletionRequest" - }, - "examples": { - "simple": { - "summary": "Simple Chat", - "description": "Basic question and answer", - "value": { - "model": "gemma-2-2b-it-Q8_0", - "messages": [ - { - "role": "user", - "content": "What is the capital of France?" - } - ], - "max_tokens": 100, - "temperature": 0.7 - } - }, - "system": { - "summary": "With System Message", - "description": "Chat with system instructions", - "value": { - "model": "gemma-2-2b-it-Q8_0", - "messages": [ - { - "role": "system", - "content": "You are a helpful assistant that speaks like a pirate." - }, - { - "role": "user", - "content": "Tell me about the weather today." - } - ], - "max_tokens": 150, - "temperature": 0.8 - } - }, - "conversation": { - "summary": "Multi-turn Conversation", - "description": "Extended conversation with context", - "value": { - "model": "gemma-2-2b-it-Q8_0", - "messages": [ - { - "role": "system", - "content": "You are a knowledgeable AI assistant." - }, - { - "role": "user", - "content": "What is machine learning?" - }, - { - "role": "assistant", - "content": "Machine learning is a subset of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed." - }, - { - "role": "user", - "content": "Can you give me a simple example?" - } - ], - "max_tokens": 200, - "temperature": 0.7 - } - }, - "streaming": { - "summary": "Streaming Chat", - "description": "Stream the response token by token", - "value": { - "model": "gemma-2-2b-it-Q8_0", - "messages": [ - { - "role": "user", - "content": "Write a haiku about programming" - } - ], - "stream": true, - "temperature": 0.9 - } - }, - "json_mode": { - "summary": "JSON Response", - "description": "Request structured JSON output", - "value": { - "model": "gemma-2-2b-it-Q8_0", - "messages": [ - { - "role": "user", - "content": "List 3 programming languages with their main use cases in JSON format" - } - ], - "max_tokens": 200, - "temperature": 0.5, - "response_format": { - "type": "json_object" - } - } - } - } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateChatCompletionResponse" - } - }, - "text/event-stream": { - "schema": { - "type": "string", - "format": "binary", - "description": "Server-sent events stream for streaming responses" - } - } - } - }, - "202": { - "description": "Accepted - Request is being processed", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/CreateChatCompletionResponse" - } - }, - "text/event-stream": { - "schema": { - "type": "string", - "format": "binary", - "description": "Server-sent events stream for streaming responses" - } - } - } - }, - "422": { - "description": "Validation Error", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ValidationError" - } - } - } - } - } - } - }, - "/v1/models": { - "get": { - "tags": ["Models"], - "summary": "List available models", - "description": "Lists the currently available models and provides basic information about each one such as the owner and availability.", - "operationId": "list_models", - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/ModelList" - }, - "example": { - "object": "list", - "data": [ - { - "id": "gemma-2-2b-it-Q8_0", - "object": "model", - "created": 1686935002, - "owned_by": "jan" - }, - { - "id": "llama-3.1-8b-instruct-Q4_K_M", - "object": "model", - "created": 1686935002, - "owned_by": "jan" - }, - { - "id": "mistral-7b-instruct-v0.3-Q4_K_M", - "object": "model", - "created": 1686935002, - "owned_by": "jan" - }, - { - "id": "phi-3-mini-4k-instruct-Q4_K_M", - "object": "model", - "created": 1686935002, - "owned_by": "jan" - } - ] - } - } - } - } - } - } - }, - "/extras/tokenize": { - "post": { - "tags": ["Extras"], - "summary": "Tokenize text", - "description": "Convert text input into tokens using the model's tokenizer.", - "operationId": "tokenize", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/TokenizeRequest" - }, - "example": { - "input": "Hello, world!", - "model": "gemma-2-2b-it-Q8_0" - } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/TokenizeResponse" - }, - "example": { - "tokens": [15339, 11, 1917, 0] - } - } - } - } - } - } - }, - "/extras/tokenize/count": { - "post": { - "tags": ["Extras"], - "summary": "Count tokens", - "description": "Count the number of tokens in the provided text.", - "operationId": "count_tokens", - "requestBody": { - "required": true, - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/TokenizeRequest" - }, - "example": { - "input": "How many tokens does this text have?", - "model": "gemma-2-2b-it-Q8_0" - } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/TokenCountResponse" - }, - "example": { - "count": 8 - } - } - } - } - } - } - } - }, - "components": { - "schemas": { - "TokenizeRequest": { - "type": "object", - "properties": { - "input": { - "type": "string", - "description": "The text to tokenize" - }, - "model": { - "type": "string", - "description": "The model to use for tokenization", - "enum": [ - "gemma-2-2b-it-Q8_0", - "llama-3.1-8b-instruct-Q4_K_M", - "mistral-7b-instruct-v0.3-Q4_K_M", - "phi-3-mini-4k-instruct-Q4_K_M" - ] - } - }, - "required": ["input"] - }, - "TokenizeResponse": { - "type": "object", - "properties": { - "tokens": { - "type": "array", - "items": { - "type": "integer" - }, - "description": "Array of token IDs" - } - }, - "required": ["tokens"] - }, - "TokenCountResponse": { - "type": "object", - "properties": { - "count": { - "type": "integer", - "description": "Number of tokens" - } - }, - "required": ["count"] - } - }, - "securitySchemes": { - "bearerAuth": { - "type": "http", - "scheme": "bearer", - "bearerFormat": "JWT", - "description": "Optional: Enter your API key if authentication is enabled. The Bearer prefix will be added automatically." - } - } - }, - "x-jan-local-features": { - "engine": "llama.cpp", - "features": [ - "GGUF model support", - "CPU and GPU acceleration", - "Quantized model support (Q4, Q5, Q8)", - "Metal acceleration on macOS", - "CUDA support on NVIDIA GPUs", - "ROCm support on AMD GPUs", - "AVX/AVX2/AVX512 optimizations", - "Memory-mapped model loading" - ], - "privacy": { - "local_processing": true, - "no_telemetry": true, - "offline_capable": true - }, - "model_formats": ["GGUF", "GGML"], - "default_settings": { - "context_length": 4096, - "batch_size": 512, - "threads": "auto" - } - } -} diff --git a/website/public/scripts/inject-navigation.js b/website/public/scripts/inject-navigation.js deleted file mode 100644 index 823d82773..000000000 --- a/website/public/scripts/inject-navigation.js +++ /dev/null @@ -1,119 +0,0 @@ -// Navigation injection script for Jan documentation -// This script adds navigation links to regular docs pages (not API reference pages) - -;(function () { - // Navigation configuration for Jan docs - const JAN_NAV_CONFIG = { - // Product navigation links - easy to extend for multiple products - links: [ - { - href: '/', - text: 'Docs', - isActive: (path) => - path === '/' || (path.startsWith('/') && !path.startsWith('/api')), - }, - { - href: '/api', - text: 'API Reference', - isActive: (path) => path.startsWith('/api'), - }, - ], - - // Pages that have their own navigation (don't inject nav) - excludePaths: ['/api-reference/', '/api/'], - } - - // Add navigation to docs pages with retry logic - function addNavigation(retries = 0) { - const currentPath = window.location.pathname - - // Skip if page has its own navigation - const shouldSkipNav = JAN_NAV_CONFIG.excludePaths.some((path) => - currentPath.startsWith(path) - ) - if (shouldSkipNav) return - - const header = document.querySelector('.header') - const siteTitle = document.querySelector('.site-title') - const existingNav = document.querySelector('.custom-nav-links') - - if (header && siteTitle && !existingNav) { - // Find the right container for nav links - const searchElement = header.querySelector('[class*="search"]') - const flexContainer = header.querySelector('.sl-flex') - const targetContainer = flexContainer || header - - if (targetContainer) { - // Create navigation container - const nav = document.createElement('nav') - nav.className = 'custom-nav-links' - nav.setAttribute('aria-label', 'Product Navigation') - - // Create links from configuration - JAN_NAV_CONFIG.links.forEach((link) => { - const a = document.createElement('a') - a.href = link.href - a.textContent = link.text - a.className = 'nav-link' - - // Set active state - if (link.isActive(currentPath)) { - a.setAttribute('aria-current', 'page') - } - - nav.appendChild(a) - }) - - // Insert navigation safely - if (searchElement && targetContainer.contains(searchElement)) { - targetContainer.insertBefore(nav, searchElement) - } else { - // Find site title and insert after it - if (siteTitle && targetContainer.contains(siteTitle)) { - siteTitle.insertAdjacentElement('afterend', nav) - } else { - targetContainer.appendChild(nav) - } - } - } else if (retries < 5) { - setTimeout(() => addNavigation(retries + 1), 500) - } - } else if (retries < 5) { - setTimeout(() => addNavigation(retries + 1), 500) - } - } - - // Initialize navigation injection - function initNavigation() { - // Update logo link to jan.ai - const logoLink = document.querySelector('a[href="/"]') - if (logoLink && logoLink.getAttribute('href') === '/') { - logoLink.href = 'https://jan.ai' - } - - // Start navigation injection - if (document.readyState === 'loading') { - setTimeout(() => addNavigation(), 1000) - } else { - addNavigation() - } - } - - // Run when DOM is ready - if (document.readyState === 'loading') { - document.addEventListener('DOMContentLoaded', initNavigation) - } else { - initNavigation() - } - - // Handle page navigation in SPA-like environments - let lastUrl = location.href - new MutationObserver(() => { - const url = location.href - if (url !== lastUrl) { - lastUrl = url - // Re-run navigation injection after navigation - setTimeout(() => addNavigation(), 100) - } - }).observe(document, { subtree: true, childList: true }) -})() diff --git a/website/public/styles/navigation.css b/website/public/styles/navigation.css deleted file mode 100644 index 00ff6694e..000000000 --- a/website/public/styles/navigation.css +++ /dev/null @@ -1,48 +0,0 @@ -/* Navigation links for regular docs pages */ -.custom-nav-links { - display: inline-flex; - align-items: center; - gap: 0.5rem; - margin: 0 1rem; -} - -.custom-nav-links .nav-link { - display: inline-flex; - align-items: center; - padding: 0.5rem 0.875rem; - border-radius: 0.375rem; - color: var(--sl-color-gray-2); - text-decoration: none; - font-weight: 500; - font-size: 0.875rem; - transition: all 0.2s ease; - white-space: nowrap; -} - -.custom-nav-links .nav-link:hover { - color: var(--sl-color-text); - background: var(--sl-color-gray-6); -} - -.custom-nav-links .nav-link[aria-current="page"] { - color: var(--sl-color-text); - background: var(--sl-color-gray-6); -} - -/* Responsive design */ -@media (max-width: 768px) { - .custom-nav-links { - display: none; - } -} - -@media (min-width: 768px) and (max-width: 1024px) { - .custom-nav-links { - margin: 0 0.5rem; - } - - .custom-nav-links .nav-link { - padding: 0.375rem 0.625rem; - font-size: 0.8125rem; - } -} diff --git a/website/public/videos/jan-nano-demo.mp4 b/website/public/videos/jan-nano-demo.mp4 deleted file mode 100644 index efcadf999..000000000 Binary files a/website/public/videos/jan-nano-demo.mp4 and /dev/null differ diff --git a/website/scripts/conditional-cloud-spec.js b/website/scripts/conditional-cloud-spec.js deleted file mode 100644 index febba969d..000000000 --- a/website/scripts/conditional-cloud-spec.js +++ /dev/null @@ -1,187 +0,0 @@ -#!/usr/bin/env node - -/** - * Conditional Cloud Spec Generator - * - * This script conditionally runs the cloud spec generation based on environment variables. - * It's designed to be used in CI/CD pipelines to control when the spec should be updated. - * - * Environment variables: - * - SKIP_CLOUD_SPEC_UPDATE: Skip cloud spec generation entirely - * - FORCE_UPDATE: Force update even if skip is set - * - CI: Detect if running in CI environment - */ - -import { spawn } from 'child_process' -import fs from 'fs' -import path from 'path' -import { fileURLToPath } from 'url' - -const __filename = fileURLToPath(import.meta.url) -const __dirname = path.dirname(__filename) - -// Configuration -const CONFIG = { - CLOUD_SPEC_PATH: path.join(__dirname, '../public/openapi/cloud-openapi.json'), - GENERATOR_SCRIPT: path.join(__dirname, 'generate-cloud-spec.js'), - FALLBACK_SPEC_PATH: path.join(__dirname, '../public/openapi/openapi.json'), -} - -// Color codes for console output -const colors = { - reset: '\x1b[0m', - green: '\x1b[32m', - yellow: '\x1b[33m', - cyan: '\x1b[36m', - gray: '\x1b[90m', -} - -function log(message, type = 'info') { - const prefix = { - info: `${colors.cyan}โ„น๏ธ `, - skip: `${colors.gray}โญ๏ธ `, - run: `${colors.green}โ–ถ๏ธ `, - warning: `${colors.yellow}โš ๏ธ `, - }[type] || '' - console.log(`${prefix}${message}${colors.reset}`) -} - -async function shouldRunGenerator() { - // Check environment variables - const skipUpdate = process.env.SKIP_CLOUD_SPEC_UPDATE === 'true' - const forceUpdate = process.env.FORCE_UPDATE === 'true' - const isCI = process.env.CI === 'true' - const isPR = process.env.GITHUB_EVENT_NAME === 'pull_request' - - // Force update overrides all - if (forceUpdate) { - log('Force update requested', 'info') - return true - } - - // Skip if explicitly requested - if (skipUpdate) { - log('Cloud spec update skipped (SKIP_CLOUD_SPEC_UPDATE=true)', 'skip') - return false - } - - // Skip in PR builds to avoid unnecessary API calls - if (isPR) { - log('Cloud spec update skipped (Pull Request build)', 'skip') - return false - } - - // Check if cloud spec already exists - const specExists = fs.existsSync(CONFIG.CLOUD_SPEC_PATH) - - // In CI, only update if spec doesn't exist or if scheduled/manual trigger - if (isCI) { - const isScheduled = process.env.GITHUB_EVENT_NAME === 'schedule' - const isManualWithUpdate = - process.env.GITHUB_EVENT_NAME === 'workflow_dispatch' && - process.env.UPDATE_CLOUD_SPEC === 'true' - - if (isScheduled || isManualWithUpdate) { - log('Cloud spec update triggered (scheduled/manual)', 'info') - return true - } - - if (!specExists) { - log('Cloud spec missing, will attempt to generate', 'warning') - return true - } - - log('Cloud spec update skipped (CI build, spec exists)', 'skip') - return false - } - - // For local development, update if spec is missing or older than 24 hours - if (!specExists) { - log('Cloud spec missing, generating...', 'info') - return true - } - - // Check if spec is older than 24 hours - const stats = fs.statSync(CONFIG.CLOUD_SPEC_PATH) - const ageInHours = (Date.now() - stats.mtime.getTime()) / (1000 * 60 * 60) - - if (ageInHours > 24) { - log(`Cloud spec is ${Math.round(ageInHours)} hours old, updating...`, 'info') - return true - } - - log(`Cloud spec is recent (${Math.round(ageInHours)} hours old), skipping update`, 'skip') - return false -} - -async function runGenerator() { - return new Promise((resolve, reject) => { - log('Running cloud spec generator...', 'run') - - const child = spawn('bun', [CONFIG.GENERATOR_SCRIPT], { - stdio: 'inherit', - env: { ...process.env } - }) - - child.on('close', (code) => { - if (code === 0) { - resolve() - } else { - reject(new Error(`Generator exited with code ${code}`)) - } - }) - - child.on('error', (err) => { - reject(err) - }) - }) -} - -async function ensureFallback() { - // If cloud spec doesn't exist but fallback does, copy it - if (!fs.existsSync(CONFIG.CLOUD_SPEC_PATH) && fs.existsSync(CONFIG.FALLBACK_SPEC_PATH)) { - log('Using fallback spec as cloud spec', 'warning') - fs.copyFileSync(CONFIG.FALLBACK_SPEC_PATH, CONFIG.CLOUD_SPEC_PATH) - return true - } - return false -} - -async function main() { - try { - // Determine if we should run the generator - const shouldRun = await shouldRunGenerator() - - if (shouldRun) { - try { - await runGenerator() - log('Cloud spec generation completed', 'info') - } catch (error) { - log(`Cloud spec generation failed: ${error.message}`, 'warning') - - // Try to use fallback - if (ensureFallback()) { - log('Fallback spec used successfully', 'info') - } else { - log('No fallback available, build may fail', 'warning') - // Don't exit with error - let the build continue - } - } - } else { - // Ensure we have at least a fallback spec - if (!fs.existsSync(CONFIG.CLOUD_SPEC_PATH)) { - ensureFallback() - } - } - - // Always exit successfully to not break the build - process.exit(0) - } catch (error) { - console.error('Unexpected error:', error) - // Even on error, try to continue the build - process.exit(0) - } -} - -// Run the script -main() diff --git a/website/scripts/fix-local-spec-complete.js b/website/scripts/fix-local-spec-complete.js deleted file mode 100644 index ed315098a..000000000 --- a/website/scripts/fix-local-spec-complete.js +++ /dev/null @@ -1,746 +0,0 @@ -#!/usr/bin/env node - -import fs from 'fs' -import path from 'path' -import { fileURLToPath } from 'url' - -const __filename = fileURLToPath(import.meta.url) -const __dirname = path.dirname(__filename) - -const cloudSpecPath = path.join( - __dirname, - '../public/openapi/cloud-openapi.json' -) -const outputPath = path.join(__dirname, '../public/openapi/openapi.json') - -console.log( - '๐Ÿ”ง Fixing Local OpenAPI Spec with Complete Examples and Schemas...' -) - -// Read cloud spec as a reference -const cloudSpec = JSON.parse(fs.readFileSync(cloudSpecPath, 'utf8')) - -// Convert Swagger 2.0 to OpenAPI 3.0 format for paths -function convertSwaggerPathToOpenAPI3(swaggerPath) { - const openApiPath = {} - - Object.keys(swaggerPath || {}).forEach((method) => { - if (typeof swaggerPath[method] === 'object') { - openApiPath[method] = { - ...swaggerPath[method], - // Convert parameters - parameters: swaggerPath[method].parameters?.filter( - (p) => p.in !== 'body' - ), - // Convert body parameter to requestBody - requestBody: swaggerPath[method].parameters?.find( - (p) => p.in === 'body' - ) - ? { - required: true, - content: { - 'application/json': { - schema: swaggerPath[method].parameters.find( - (p) => p.in === 'body' - ).schema, - }, - }, - } - : undefined, - // Convert responses - responses: {}, - } - - // Convert responses - Object.keys(swaggerPath[method].responses || {}).forEach((statusCode) => { - const response = swaggerPath[method].responses[statusCode] - openApiPath[method].responses[statusCode] = { - description: response.description, - content: response.schema - ? { - 'application/json': { - schema: response.schema, - }, - } - : undefined, - } - }) - } - }) - - return openApiPath -} - -// Create comprehensive local spec -const localSpec = { - openapi: '3.1.0', - info: { - title: 'Jan API', - description: - "OpenAI-compatible API for local inference with Jan. Run AI models locally with complete privacy using llama.cpp's high-performance inference engine. Supports GGUF models with CPU and GPU acceleration. No authentication required for local usage.", - version: '0.3.14', - contact: { - name: 'Jan Support', - url: 'https://jan.ai/support', - email: 'support@jan.ai', - }, - license: { - name: 'Apache 2.0', - url: 'https://github.com/janhq/jan/blob/main/LICENSE', - }, - }, - servers: [ - { - url: 'http://127.0.0.1:1337', - description: 'Local Jan Server (Default IP)', - }, - { - url: 'http://localhost:1337', - description: 'Local Jan Server (localhost)', - }, - { - url: 'http://localhost:8080', - description: 'Local Jan Server (Alternative Port)', - }, - ], - tags: [ - { - name: 'Models', - description: 'List and describe available models', - }, - { - name: 'Chat', - description: 'Chat completion endpoints for conversational AI', - }, - { - name: 'Completions', - description: 'Text completion endpoints for generating text', - }, - { - name: 'Extras', - description: - 'Additional utility endpoints for tokenization and text processing', - }, - ], - paths: {}, - components: { - schemas: {}, - securitySchemes: { - bearerAuth: { - type: 'http', - scheme: 'bearer', - bearerFormat: 'JWT', - description: - 'Optional: Enter your API key if authentication is enabled. The Bearer prefix will be added automatically.', - }, - }, - }, -} - -// Local model examples -const LOCAL_MODELS = [ - 'gemma-2-2b-it-Q8_0', - 'llama-3.1-8b-instruct-Q4_K_M', - 'mistral-7b-instruct-v0.3-Q4_K_M', - 'phi-3-mini-4k-instruct-Q4_K_M', -] - -// Add completions endpoint with rich examples -localSpec.paths['/v1/completions'] = { - post: { - tags: ['Completions'], - summary: 'Create completion', - description: - "Creates a completion for the provided prompt and parameters. This endpoint is compatible with OpenAI's completions API.", - operationId: 'create_completion', - requestBody: { - required: true, - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/CreateCompletionRequest', - }, - examples: { - basic: { - summary: 'Basic Completion', - description: 'Simple text completion example', - value: { - model: LOCAL_MODELS[0], - prompt: 'Once upon a time', - max_tokens: 50, - temperature: 0.7, - }, - }, - creative: { - summary: 'Creative Writing', - description: 'Generate creative content with higher temperature', - value: { - model: LOCAL_MODELS[0], - prompt: 'Write a short poem about coding:', - max_tokens: 150, - temperature: 1.0, - top_p: 0.95, - }, - }, - code: { - summary: 'Code Generation', - description: 'Generate code with lower temperature for accuracy', - value: { - model: LOCAL_MODELS[0], - prompt: - '# Python function to calculate fibonacci\ndef fibonacci(n):', - max_tokens: 200, - temperature: 0.3, - stop: ['\n\n', 'def ', 'class '], - }, - }, - streaming: { - summary: 'Streaming Response', - description: 'Stream tokens as they are generated', - value: { - model: LOCAL_MODELS[0], - prompt: 'Explain quantum computing in simple terms:', - max_tokens: 300, - temperature: 0.7, - stream: true, - }, - }, - }, - }, - }, - }, - responses: { - 200: { - description: 'Successful Response', - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/CreateCompletionResponse', - }, - }, - }, - }, - 202: { - description: 'Accepted - Request is being processed', - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/CreateCompletionResponse', - }, - }, - 'text/event-stream': { - schema: { - type: 'string', - format: 'binary', - description: 'Server-sent events stream for streaming responses', - }, - }, - }, - }, - 422: { - description: 'Validation Error', - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/ValidationError', - }, - }, - }, - }, - }, - }, -} - -// Add chat completions endpoint with rich examples -localSpec.paths['/v1/chat/completions'] = { - post: { - tags: ['Chat'], - summary: 'Create chat completion', - description: - "Creates a model response for the given chat conversation. This endpoint is compatible with OpenAI's chat completions API.", - operationId: 'create_chat_completion', - requestBody: { - required: true, - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/CreateChatCompletionRequest', - }, - examples: { - simple: { - summary: 'Simple Chat', - description: 'Basic question and answer', - value: { - model: LOCAL_MODELS[0], - messages: [ - { - role: 'user', - content: 'What is the capital of France?', - }, - ], - max_tokens: 100, - temperature: 0.7, - }, - }, - system: { - summary: 'With System Message', - description: 'Chat with system instructions', - value: { - model: LOCAL_MODELS[0], - messages: [ - { - role: 'system', - content: - 'You are a helpful assistant that speaks like a pirate.', - }, - { - role: 'user', - content: 'Tell me about the weather today.', - }, - ], - max_tokens: 150, - temperature: 0.8, - }, - }, - conversation: { - summary: 'Multi-turn Conversation', - description: 'Extended conversation with context', - value: { - model: LOCAL_MODELS[0], - messages: [ - { - role: 'system', - content: 'You are a knowledgeable AI assistant.', - }, - { - role: 'user', - content: 'What is machine learning?', - }, - { - role: 'assistant', - content: - 'Machine learning is a subset of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed.', - }, - { - role: 'user', - content: 'Can you give me a simple example?', - }, - ], - max_tokens: 200, - temperature: 0.7, - }, - }, - streaming: { - summary: 'Streaming Chat', - description: 'Stream the response token by token', - value: { - model: LOCAL_MODELS[0], - messages: [ - { - role: 'user', - content: 'Write a haiku about programming', - }, - ], - stream: true, - temperature: 0.9, - }, - }, - json_mode: { - summary: 'JSON Response', - description: 'Request structured JSON output', - value: { - model: LOCAL_MODELS[0], - messages: [ - { - role: 'user', - content: - 'List 3 programming languages with their main use cases in JSON format', - }, - ], - max_tokens: 200, - temperature: 0.5, - response_format: { - type: 'json_object', - }, - }, - }, - }, - }, - }, - }, - responses: { - 200: { - description: 'Successful Response', - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/CreateChatCompletionResponse', - }, - }, - 'text/event-stream': { - schema: { - type: 'string', - format: 'binary', - description: 'Server-sent events stream for streaming responses', - }, - }, - }, - }, - 202: { - description: 'Accepted - Request is being processed', - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/CreateChatCompletionResponse', - }, - }, - 'text/event-stream': { - schema: { - type: 'string', - format: 'binary', - description: 'Server-sent events stream for streaming responses', - }, - }, - }, - }, - 422: { - description: 'Validation Error', - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/ValidationError', - }, - }, - }, - }, - }, - }, -} - -// Add models endpoint -localSpec.paths['/v1/models'] = { - get: { - tags: ['Models'], - summary: 'List available models', - description: - 'Lists the currently available models and provides basic information about each one such as the owner and availability.', - operationId: 'list_models', - responses: { - 200: { - description: 'Successful Response', - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/ModelList', - }, - example: { - object: 'list', - data: LOCAL_MODELS.map((id) => ({ - id: id, - object: 'model', - created: 1686935002, - owned_by: 'jan', - })), - }, - }, - }, - }, - }, - }, -} - -// Add tokenization endpoints -localSpec.paths['/extras/tokenize'] = { - post: { - tags: ['Extras'], - summary: 'Tokenize text', - description: "Convert text input into tokens using the model's tokenizer.", - operationId: 'tokenize', - requestBody: { - required: true, - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/TokenizeRequest', - }, - example: { - input: 'Hello, world!', - model: LOCAL_MODELS[0], - }, - }, - }, - }, - responses: { - 200: { - description: 'Successful Response', - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/TokenizeResponse', - }, - example: { - tokens: [15339, 11, 1917, 0], - }, - }, - }, - }, - }, - }, -} - -localSpec.paths['/extras/tokenize/count'] = { - post: { - tags: ['Extras'], - summary: 'Count tokens', - description: 'Count the number of tokens in the provided text.', - operationId: 'count_tokens', - requestBody: { - required: true, - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/TokenizeRequest', - }, - example: { - input: 'How many tokens does this text have?', - model: LOCAL_MODELS[0], - }, - }, - }, - }, - responses: { - 200: { - description: 'Successful Response', - content: { - 'application/json': { - schema: { - $ref: '#/components/schemas/TokenCountResponse', - }, - example: { - count: 8, - }, - }, - }, - }, - }, - }, -} - -// Copy ALL necessary schemas from cloud spec -const schemasToInclude = [ - // Request/Response schemas - 'CreateChatCompletionRequest', - 'CreateChatCompletionResponse', - 'CreateCompletionRequest', - 'CreateCompletionResponse', - 'ChatCompletionRequestMessage', - 'ChatCompletionRequestSystemMessage', - 'ChatCompletionRequestUserMessage', - 'ChatCompletionRequestAssistantMessage', - 'ChatCompletionResponseMessage', - 'ChatCompletionResponseChoice', - 'CompletionChoice', - 'CompletionUsage', - 'ModelList', - 'ModelData', - 'ValidationError', - - // Additional message types - 'ChatCompletionRequestFunctionMessage', - 'ChatCompletionRequestToolMessage', - 'ChatCompletionRequestMessageContentPart', - 'ChatCompletionRequestMessageContentPartText', - 'ChatCompletionRequestMessageContentPartImage', - - // Function calling - 'ChatCompletionFunction', - 'ChatCompletionFunctionCall', - 'ChatCompletionTool', - 'ChatCompletionToolCall', - 'ChatCompletionNamedToolChoice', - - // Response format - 'ChatCompletionRequestResponseFormat', - - // Logprobs - 'ChatCompletionLogprobs', - 'ChatCompletionLogprobToken', - 'ChatCompletionTopLogprobToken', -] - -// Copy schemas from cloud spec (handle both definitions and schemas) -if (cloudSpec.definitions || cloudSpec.components?.schemas) { - const sourceSchemas = - cloudSpec.definitions || cloudSpec.components?.schemas || {} - - schemasToInclude.forEach((schemaName) => { - if (sourceSchemas[schemaName]) { - localSpec.components.schemas[schemaName] = JSON.parse( - JSON.stringify(sourceSchemas[schemaName]) - ) - } - }) - - // Also copy any schemas that are referenced by the included schemas - const processedSchemas = new Set(schemasToInclude) - const schemasToProcess = [...schemasToInclude] - - while (schemasToProcess.length > 0) { - const currentSchema = schemasToProcess.pop() - const schema = localSpec.components.schemas[currentSchema] - if (!schema) continue - - // Find all $ref references - const schemaString = JSON.stringify(schema) - const refPattern = /#\/(?:definitions|components\/schemas)\/([^"]+)/g - let match - - while ((match = refPattern.exec(schemaString)) !== null) { - const referencedSchema = match[1] - if ( - !processedSchemas.has(referencedSchema) && - sourceSchemas[referencedSchema] - ) { - localSpec.components.schemas[referencedSchema] = JSON.parse( - JSON.stringify(sourceSchemas[referencedSchema]) - ) - processedSchemas.add(referencedSchema) - schemasToProcess.push(referencedSchema) - } - } - } -} - -// Add tokenization schemas manually -localSpec.components.schemas.TokenizeRequest = { - type: 'object', - properties: { - input: { - type: 'string', - description: 'The text to tokenize', - }, - model: { - type: 'string', - description: 'The model to use for tokenization', - enum: LOCAL_MODELS, - }, - }, - required: ['input'], -} - -localSpec.components.schemas.TokenizeResponse = { - type: 'object', - properties: { - tokens: { - type: 'array', - items: { - type: 'integer', - }, - description: 'Array of token IDs', - }, - }, - required: ['tokens'], -} - -localSpec.components.schemas.TokenCountResponse = { - type: 'object', - properties: { - count: { - type: 'integer', - description: 'Number of tokens', - }, - }, - required: ['count'], -} - -// Update model references in schemas to use local models -if ( - localSpec.components.schemas.CreateChatCompletionRequest?.properties?.model -) { - localSpec.components.schemas.CreateChatCompletionRequest.properties.model = { - ...localSpec.components.schemas.CreateChatCompletionRequest.properties - .model, - enum: LOCAL_MODELS, - example: LOCAL_MODELS[0], - description: `ID of the model to use. Available models: ${LOCAL_MODELS.join(', ')}`, - } -} - -if (localSpec.components.schemas.CreateCompletionRequest?.properties?.model) { - localSpec.components.schemas.CreateCompletionRequest.properties.model = { - ...localSpec.components.schemas.CreateCompletionRequest.properties.model, - enum: LOCAL_MODELS, - example: LOCAL_MODELS[0], - description: `ID of the model to use. Available models: ${LOCAL_MODELS.join(', ')}`, - } -} - -// Fix all $ref references to use components/schemas instead of definitions -function fixReferences(obj) { - if (typeof obj === 'string') { - return obj.replace(/#\/definitions\//g, '#/components/schemas/') - } - if (Array.isArray(obj)) { - return obj.map(fixReferences) - } - if (obj && typeof obj === 'object') { - const fixed = {} - for (const key in obj) { - fixed[key] = fixReferences(obj[key]) - } - return fixed - } - return obj -} - -// Apply reference fixes -localSpec.paths = fixReferences(localSpec.paths) -localSpec.components.schemas = fixReferences(localSpec.components.schemas) - -// Add x-jan-local-features -localSpec['x-jan-local-features'] = { - engine: 'llama.cpp', - features: [ - 'GGUF model support', - 'CPU and GPU acceleration', - 'Quantized model support (Q4, Q5, Q8)', - 'Metal acceleration on macOS', - 'CUDA support on NVIDIA GPUs', - 'ROCm support on AMD GPUs', - 'AVX/AVX2/AVX512 optimizations', - 'Memory-mapped model loading', - ], - privacy: { - local_processing: true, - no_telemetry: true, - offline_capable: true, - }, - model_formats: ['GGUF', 'GGML'], - default_settings: { - context_length: 4096, - batch_size: 512, - threads: 'auto', - }, -} - -// Write the fixed spec -fs.writeFileSync(outputPath, JSON.stringify(localSpec, null, 2), 'utf8') - -console.log('โœ… Local OpenAPI spec fixed successfully!') -console.log(`๐Ÿ“ Output: ${outputPath}`) -console.log(`๐Ÿ“Š Endpoints: ${Object.keys(localSpec.paths).length}`) -console.log(`๐Ÿ“Š Schemas: ${Object.keys(localSpec.components.schemas).length}`) -console.log( - `๐ŸŽฏ Examples: ${Object.keys(localSpec.paths).reduce((count, path) => { - return ( - count + - Object.keys(localSpec.paths[path]).reduce((c, method) => { - const examples = - localSpec.paths[path][method]?.requestBody?.content?.[ - 'application/json' - ]?.examples - return c + (examples ? Object.keys(examples).length : 0) - }, 0) - ) - }, 0)}` -) diff --git a/website/scripts/generate-cloud-spec.js b/website/scripts/generate-cloud-spec.js deleted file mode 100644 index 4ccfb339b..000000000 --- a/website/scripts/generate-cloud-spec.js +++ /dev/null @@ -1,421 +0,0 @@ -#!/usr/bin/env node - -import fs from 'fs' -import path from 'path' -import { fileURLToPath } from 'url' - -// Get current directory in ES modules -const __filename = fileURLToPath(import.meta.url) -const __dirname = path.dirname(__filename) - -const CONFIG = { - // Jan Server API spec URL - change this for different environments - JAN_SERVER_SPEC_URL: - process.env.JAN_SERVER_SPEC_URL || - 'https://api.jan.ai/api/swagger/doc.json', - - // Server URLs for different environments - SERVERS: { - production: { - url: process.env.JAN_SERVER_PROD_URL || 'https://api.jan.ai/v1', - description: 'Jan Server API (Production)', - }, - staging: { - url: - process.env.JAN_SERVER_STAGING_URL || 'https://staging-api.jan.ai/v1', - description: 'Jan Server API (Staging)', - }, - local: { - url: process.env.JAN_SERVER_LOCAL_URL || 'http://localhost:8000/v1', - description: 'Jan Server (Local Development)', - }, - minikube: { - url: - process.env.JAN_SERVER_MINIKUBE_URL || - 'http://jan-server.local:8000/v1', - description: 'Jan Server (Minikube)', - }, - }, - - // Output file path - OUTPUT_PATH: path.join(__dirname, '../public/openapi/cloud-openapi.json'), - - // Fallback to local spec if fetch fails - FALLBACK_SPEC_PATH: path.join(__dirname, '../public/openapi/openapi.json'), - - // Request timeout in milliseconds - FETCH_TIMEOUT: 10000, -} - -// Model examples for Jan Server (vLLM deployment) -const MODEL_EXAMPLES = [ - 'llama-3.1-8b-instruct', - 'mistral-7b-instruct-v0.3', - 'gemma-2-9b-it', - 'qwen2.5-7b-instruct', -] - -// ============================================================================= -// UTILITY FUNCTIONS -// ============================================================================= - -const colors = { - reset: '\x1b[0m', - green: '\x1b[32m', - yellow: '\x1b[33m', - red: '\x1b[31m', - cyan: '\x1b[36m', - bright: '\x1b[1m', -} - -function log(message, type = 'info') { - const prefix = - { - success: `${colors.green}โœ…`, - warning: `${colors.yellow}โš ๏ธ `, - error: `${colors.red}โŒ`, - info: `${colors.cyan}โ„น๏ธ `, - }[type] || '' - console.log(`${prefix} ${message}${colors.reset}`) -} - -async function fetchWithTimeout(url, options = {}) { - const controller = new AbortController() - const timeoutId = setTimeout(() => controller.abort(), CONFIG.FETCH_TIMEOUT) - - try { - const response = await fetch(url, { - ...options, - signal: controller.signal, - }) - clearTimeout(timeoutId) - return response - } catch (error) { - clearTimeout(timeoutId) - throw error - } -} - -// ============================================================================= -// SPEC ENHANCEMENT FUNCTIONS -// ============================================================================= - -function enhanceSpecWithBranding(spec) { - // Update info section with Jan Server branding - spec.info = { - ...spec.info, - 'title': '๐Ÿ‘‹Jan Server API', - 'description': - 'OpenAI-compatible API for Jan Server powered by vLLM. High-performance, scalable inference service with automatic batching and optimized memory management.', - 'version': spec.info?.version || '1.0.0', - 'x-logo': { - url: 'https://jan.ai/logo.png', - altText: '๐Ÿ‘‹Jan Server API', - }, - 'contact': { - name: 'Jan Server Support', - url: 'https://jan.ai/support', - email: 'support@jan.ai', - }, - 'license': { - name: 'Apache 2.0', - url: 'https://github.com/menloresearch/jan/blob/main/LICENSE', - }, - } - - // Update servers with our configured endpoints - spec.servers = Object.values(CONFIG.SERVERS) - - // Add global security requirement - spec.security = [{ bearerAuth: [] }] - - // Add tags for better organization - spec.tags = [ - { name: 'Models', description: 'List and describe available models' }, - { - name: 'Chat', - description: 'Chat completion endpoints for conversational AI', - }, - { name: 'Completions', description: 'Text completion endpoints' }, - { name: 'Embeddings', description: 'Generate embeddings for text' }, - { name: 'Usage', description: 'Monitor API usage and quotas' }, - ] - - return spec -} - -function enhanceSecuritySchemes(spec) { - if (!spec.components) spec.components = {} - if (!spec.components.securitySchemes) spec.components.securitySchemes = {} - - spec.components.securitySchemes.bearerAuth = { - type: 'http', - scheme: 'bearer', - bearerFormat: 'JWT', - description: - 'Enter your Jan Server API key. Configure authentication in your server settings.', - } - - return spec -} - -function addModelExamples(spec) { - const primaryModel = MODEL_EXAMPLES[0] - - // Helper function to update model fields in schemas - function updateModelField(modelField) { - if (!modelField) return - - modelField.example = primaryModel - modelField.description = `ID of the model to use. Available models: ${MODEL_EXAMPLES.join(', ')}` - - if (modelField.anyOf && modelField.anyOf[0]?.type === 'string') { - modelField.anyOf[0].example = primaryModel - modelField.anyOf[0].enum = MODEL_EXAMPLES - } else if (modelField.type === 'string') { - modelField.enum = MODEL_EXAMPLES - } - } - - // Update model fields in common request schemas - const schemas = spec.components?.schemas || {} - - if (schemas.CreateCompletionRequest?.properties?.model) { - updateModelField(schemas.CreateCompletionRequest.properties.model) - } - - if (schemas.CreateChatCompletionRequest?.properties?.model) { - updateModelField(schemas.CreateChatCompletionRequest.properties.model) - } - - if (schemas.CreateEmbeddingRequest?.properties?.model) { - updateModelField(schemas.CreateEmbeddingRequest.properties.model) - } - - return spec -} - -function addRequestExamples(spec) { - const primaryModel = MODEL_EXAMPLES[0] - - // Example request bodies - const examples = { - completion: { - 'text-completion': { - summary: 'Text Completion Example', - description: `Complete text using ${primaryModel}`, - value: { - model: primaryModel, - prompt: 'Once upon a time,', - max_tokens: 50, - temperature: 0.7, - top_p: 0.9, - stream: false, - }, - }, - }, - chatCompletion: { - 'simple-chat': { - summary: 'Simple Chat Example', - description: `Chat completion using ${primaryModel}`, - value: { - model: primaryModel, - messages: [ - { role: 'user', content: 'What is the capital of France?' }, - ], - max_tokens: 100, - temperature: 0.7, - stream: false, - }, - }, - }, - embedding: { - 'text-embedding': { - summary: 'Text Embedding Example', - description: `Generate embeddings using ${primaryModel}`, - value: { - model: primaryModel, - input: 'The quick brown fox jumps over the lazy dog', - }, - }, - }, - } - - // Add examples to path operations - Object.keys(spec.paths || {}).forEach((path) => { - Object.keys(spec.paths[path] || {}).forEach((method) => { - const operation = spec.paths[path][method] - - if (!operation.requestBody?.content?.['application/json']) return - - if (path.includes('/completions') && !path.includes('/chat')) { - operation.requestBody.content['application/json'].examples = - examples.completion - } else if (path.includes('/chat/completions')) { - operation.requestBody.content['application/json'].examples = - examples.chatCompletion - } else if (path.includes('/embeddings')) { - operation.requestBody.content['application/json'].examples = - examples.embedding - } - }) - }) - - return spec -} - -function addCloudFeatures(spec) { - // Add cloud-specific extension - spec['x-jan-server-features'] = { - vllm: { - version: '0.5.0', - features: [ - 'PagedAttention for efficient memory management', - 'Continuous batching for high throughput', - 'Tensor parallelism for multi-GPU serving', - 'Quantization support (AWQ, GPTQ, SqueezeLLM)', - 'Speculative decoding', - 'LoRA adapter support', - ], - }, - scaling: { - auto_scaling: true, - min_replicas: 1, - max_replicas: 100, - target_qps: 100, - }, - limits: { - max_tokens_per_request: 32768, - max_batch_size: 256, - timeout_seconds: 300, - }, - } - - return spec -} - -// ============================================================================= -// MAIN FUNCTIONS -// ============================================================================= - -async function fetchJanServerSpec() { - log(`Fetching Jan Server spec from: ${CONFIG.JAN_SERVER_SPEC_URL}`) - - try { - const response = await fetchWithTimeout(CONFIG.JAN_SERVER_SPEC_URL) - - if (!response.ok) { - throw new Error(`HTTP ${response.status}: ${response.statusText}`) - } - - const spec = await response.json() - log('Successfully fetched Jan Server specification', 'success') - return spec - } catch (error) { - log(`Failed to fetch Jan Server spec: ${error.message}`, 'warning') - - // If FORCE_UPDATE is set, don't use fallback - fail instead - if (process.env.FORCE_UPDATE === 'true') { - log('Force update requested - not using fallback', 'error') - throw error - } - - log(`Falling back to local spec: ${CONFIG.FALLBACK_SPEC_PATH}`, 'warning') - - if (fs.existsSync(CONFIG.FALLBACK_SPEC_PATH)) { - const fallbackSpec = JSON.parse( - fs.readFileSync(CONFIG.FALLBACK_SPEC_PATH, 'utf8') - ) - log('Using local fallback specification', 'warning') - return fallbackSpec - } else { - throw new Error('No fallback spec available') - } - } -} - -async function generateCloudSpec() { - console.log( - `${colors.bright}${colors.cyan}๐Ÿš€ Jan Server API Spec Generator${colors.reset}` - ) - console.log( - `${colors.cyan}โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”${colors.reset}` - ) - console.log(`๐Ÿ“ก Source: ${CONFIG.JAN_SERVER_SPEC_URL}`) - console.log(`๐Ÿ“ Output: ${CONFIG.OUTPUT_PATH}`) - console.log(`๐Ÿ—๏ธ Servers: ${Object.keys(CONFIG.SERVERS).join(', ')}`) - console.log('') - - try { - // Fetch the real Jan Server specification - let spec = await fetchJanServerSpec() - - // Apply all enhancements - spec = enhanceSpecWithBranding(spec) - spec = enhanceSecuritySchemes(spec) - spec = addModelExamples(spec) - spec = addRequestExamples(spec) - spec = addCloudFeatures(spec) - - // Ensure all paths have security requirements - Object.keys(spec.paths || {}).forEach((path) => { - Object.keys(spec.paths[path] || {}).forEach((method) => { - const operation = spec.paths[path][method] - if (!operation.security) { - operation.security = [{ bearerAuth: [] }] - } - }) - }) - - // Write the enhanced specification - fs.writeFileSync(CONFIG.OUTPUT_PATH, JSON.stringify(spec, null, 2), 'utf8') - - log('Jan Server specification generated successfully!', 'success') - console.log(`๐Ÿ“ Output: ${CONFIG.OUTPUT_PATH}`) - console.log('\n๐Ÿ“Š Summary:') - console.log(` - Endpoints: ${Object.keys(spec.paths || {}).length}`) - console.log(` - Servers: ${spec.servers?.length || 0}`) - console.log(` - Models: ${MODEL_EXAMPLES.length}`) - console.log(` - Security: Bearer token authentication`) - console.log( - ` - Engine: vLLM (${spec['x-jan-server-features']?.vllm?.version || 'unknown'})` - ) - - return true - } catch (error) { - log( - `Failed to generate Jan Server specification: ${error.message}`, - 'error' - ) - console.log('\n๐Ÿ”ง Troubleshooting:') - console.log(' 1. Check your internet connection') - console.log( - ` 2. Verify Jan Server is accessible at: ${CONFIG.JAN_SERVER_SPEC_URL}` - ) - console.log(' 3. Check if you need to set environment variables:') - console.log(' - JAN_SERVER_SPEC_URL') - console.log(' - JAN_SERVER_PROD_URL') - console.log(' - JAN_SERVER_LOCAL_URL') - return false - } -} - -// ============================================================================= -// EXECUTION -// ============================================================================= - -// Show configuration on startup -if (process.env.NODE_ENV !== 'test') { - console.log(`${colors.cyan}๐Ÿ”ง Configuration:${colors.reset}`) - console.log(` Spec URL: ${CONFIG.JAN_SERVER_SPEC_URL}`) - console.log(` Timeout: ${CONFIG.FETCH_TIMEOUT}ms`) - console.log(` Servers: ${Object.keys(CONFIG.SERVERS).length} configured`) - if (process.env.FORCE_UPDATE === 'true') { - console.log(` ${colors.yellow}Force Update: ENABLED${colors.reset}`) - } - console.log('') -} - -// Run the generator -const success = await generateCloudSpec() -process.exit(success ? 0 : 1) diff --git a/website/src/assets/add_assistant.png 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a/website/src/assets/vision5.png and /dev/null differ diff --git a/website/src/components/ApiReferenceLayout.astro b/website/src/components/ApiReferenceLayout.astro deleted file mode 100644 index 7906d24f3..000000000 --- a/website/src/components/ApiReferenceLayout.astro +++ /dev/null @@ -1,396 +0,0 @@ ---- -interface Props { - title: string; - description: string; -} - -const { title, description } = Astro.props; ---- - - - - - - - {title} | ๐Ÿ‘‹ Jan - - - - - - - - - - - - - -
-
- - ๐Ÿ‘‹ Jan - - - - -
- - - - - -
-
- -
- -
-
- - - - diff --git a/website/src/components/react/ScalarApiReferenceMulti.jsx b/website/src/components/react/ScalarApiReferenceMulti.jsx deleted file mode 100644 index 4558deda1..000000000 --- a/website/src/components/react/ScalarApiReferenceMulti.jsx +++ /dev/null @@ -1,214 +0,0 @@ -import { ApiReferenceReact } from '@scalar/api-reference-react' -import '@scalar/api-reference-react/style.css' -import { useEffect, useState } from 'react' - -const ScalarApiReferenceMulti = ({ - specUrl, - title, - description, - deployment = 'local', -}) => { - const [isDarkMode, setIsDarkMode] = useState(true) - const [serverUrl, setServerUrl] = useState('') - - useEffect(() => { - // Theme detection for Starlight - const getCurrentTheme = () => { - const htmlElement = document.documentElement - const theme = htmlElement.getAttribute('data-theme') - const isDark = - theme === 'dark' || - (theme !== 'light' && - window.matchMedia('(prefers-color-scheme: dark)').matches) - - setIsDarkMode(isDark) - } - - // Set initial theme - getCurrentTheme() - - // Watch for theme changes - const observer = new MutationObserver(() => { - getCurrentTheme() - }) - - observer.observe(document.documentElement, { - attributes: true, - attributeFilter: ['data-theme', 'class'], - }) - - // Watch for system theme changes - const mediaQuery = window.matchMedia('(prefers-color-scheme: dark)') - const handleSystemThemeChange = () => { - getCurrentTheme() - } - - mediaQuery.addEventListener('change', handleSystemThemeChange) - - // Check for custom server URL in localStorage or URL params - const params = new URLSearchParams(window.location.search) - const customServer = - params.get('server') || localStorage.getItem('jan-api-server') - if (customServer) { - setServerUrl(customServer) - } - - return () => { - observer.disconnect() - mediaQuery.removeEventListener('change', handleSystemThemeChange) - } - }, []) - - // Get deployment-specific servers - const getServers = () => { - const customServers = serverUrl - ? [{ url: serverUrl, description: 'Custom Server' }] - : [] - - if (deployment === 'cloud') { - return [ - ...customServers, - { - url: 'https://api.jan.ai/v1', - description: 'Jan Server (Production)', - }, - { - url: 'http://localhost:8000/v1', - description: 'Jan Server (Local Development)', - }, - ] - } - - // Local deployment - return [ - ...customServers, - { - url: 'http://127.0.0.1:1337', - description: 'Local Jan Server (Default)', - }, - { - url: 'http://localhost:1337', - description: 'Local Jan Server (localhost)', - }, - { - url: 'http://localhost:8080', - description: 'Local Jan Server (Alternative Port)', - }, - ] - } - - return ( -
- {/* Optional server URL input */} -
- - { - setServerUrl(e.target.value) - localStorage.setItem('jan-api-server', e.target.value) - }} - style={{ - padding: '0.25rem 0.5rem', - background: 'var(--sl-color-bg)', - border: '1px solid var(--sl-color-hairline)', - borderRadius: '4px', - color: 'var(--sl-color-text)', - fontFamily: 'monospace', - fontSize: '0.875rem', - flex: '1', - maxWidth: '300px', - }} - /> - -
- - -
- ) -} - -export default ScalarApiReferenceMulti diff --git a/website/src/config/README.md b/website/src/config/README.md deleted file mode 100644 index 255de0f59..000000000 --- a/website/src/config/README.md +++ /dev/null @@ -1,101 +0,0 @@ -# Navigation Configuration - -This directory contains configuration files for managing navigation across Jan's documentation sites. - -## Overview - -As Jan grows to include multiple products (Jan Desktop, Jan Server, Jan Mobile, etc.), we need a scalable way to manage navigation across different documentation sections. This configuration approach allows us to: - -1. **Maintain consistency** across different products -2. **Avoid duplication** in navigation code -3. **Scale easily** as new products are added -4. **Separate concerns** between regular docs and API reference pages - -## Structure - -### `navigation.js` -Central navigation configuration file containing: -- Product-specific navigation links -- API deployment configurations -- Helper functions for navigation management -- Feature flags for navigation behavior - -## Navigation Strategy - -### Regular Documentation Pages -- Navigation is injected via `astro.config.mjs` -- Shows "Docs" and "API Reference" links -- Appears in the main header next to search - -### API Reference Pages -- Have their own navigation via `ApiReferenceLayout.astro` -- Navigation is built into the layout (not injected) -- Prevents duplicate navigation elements - -## Adding New Products - -To add navigation for a new product: - -1. Update `navigation.js`: -```javascript -products: { - janServer: { - name: 'Jan Server', - links: [ - { href: '/server', text: 'Server Docs', isActive: (path) => path.startsWith('/server') }, - { href: '/server/api', text: 'Server API', isActive: (path) => path.startsWith('/server/api') } - ] - } -} -``` - -2. Update `astro.config.mjs` if needed to handle product-specific logic - -3. Create corresponding layout components if the product needs custom API reference pages - -## Configuration in astro.config.mjs - -The navigation injection in `astro.config.mjs` is kept minimal and clean: - -```javascript -const JAN_NAV_CONFIG = { - links: [/* navigation links */], - excludePaths: [/* paths that have their own navigation */] -}; -``` - -This configuration: -- Is easy to read and modify -- Doesn't interfere with API reference pages -- Can be extended for multiple products -- Maintains clean separation of concerns - -## Best Practices - -1. **Keep it simple**: Navigation configuration should be declarative, not complex logic -2. **Avoid duplication**: Use the configuration to generate navigation, don't hardcode it multiple places -3. **Test changes**: Always verify navigation works on both regular docs and API reference pages -4. **Document changes**: Update this README when adding new products or changing navigation strategy - -## Testing Navigation - -After making changes, verify: -1. Navigation appears correctly on regular docs pages -2. Navigation doesn't duplicate on API reference pages -3. Active states work correctly -4. Mobile responsiveness is maintained -5. Theme switching doesn't break navigation - -## Future Considerations - -- **Product switcher**: Add a dropdown to switch between different product docs -- **Version selector**: Add version switching for API documentation -- **Search integration**: Integrate product-specific search scopes -- **Analytics**: Track navigation usage to improve UX - -## Related Files - -- `/astro.config.mjs` - Navigation injection for regular docs -- `/src/components/ApiReferenceLayout.astro` - API reference navigation -- `/src/pages/api.astro` - API documentation landing page -- `/src/pages/api-reference/*.astro` - API reference pages \ No newline at end of file diff --git a/website/src/config/navigation.js b/website/src/config/navigation.js deleted file mode 100644 index f72c77890..000000000 --- a/website/src/config/navigation.js +++ /dev/null @@ -1,138 +0,0 @@ -/** - * Navigation Configuration - * - * Centralized navigation configuration for Jan documentation. - * This makes it easy to manage navigation across multiple products - * and maintain consistency across different documentation sections. - */ - -export const NAVIGATION_CONFIG = { - // Main product navigation links - products: { - jan: { - name: 'Jan', - links: [ - { - href: '/', - text: 'Docs', - isActive: (path) => path === '/' || (path.startsWith('/') && !path.startsWith('/api')), - description: 'Jan documentation and guides' - }, - { - href: '/api', - text: 'API Reference', - isActive: (path) => path.startsWith('/api'), - description: 'OpenAI-compatible API documentation' - } - ] - }, - // Future products can be added here - // Example: - // janServer: { - // name: 'Jan Server', - // links: [ - // { href: '/server', text: 'Server Docs', isActive: (path) => path.startsWith('/server') }, - // { href: '/server/api', text: 'Server API', isActive: (path) => path.startsWith('/server/api') } - // ] - // } - }, - - // API deployment configurations - apiDeployments: { - local: { - name: 'Local API', - defaultServers: [ - { url: 'http://127.0.0.1:1337', description: 'Local Jan Server (Default)' }, - { url: 'http://localhost:1337', description: 'Local Jan Server (localhost)' }, - { url: 'http://localhost:8080', description: 'Local Jan Server (Alternative Port)' } - ], - requiresAuth: false, - engine: 'llama.cpp' - }, - cloud: { - name: 'Jan Server', - defaultServers: [ - { url: 'https://api.jan.ai/v1', description: 'Jan Server (Production)' }, - { url: 'http://localhost:8000/v1', description: 'Jan Server (Local Development)' } - ], - requiresAuth: true, - engine: 'vLLM' - } - }, - - // Navigation styles configuration - styles: { - navLink: { - base: 'nav-link', - active: 'nav-link-active' - }, - container: { - base: 'custom-nav-links', - mobile: 'custom-nav-links-mobile' - } - }, - - // Feature flags for navigation behavior - features: { - persistCustomServer: true, - allowUrlParams: true, - showProductSwitcher: false, // For future multi-product support - mobileMenuBreakpoint: 768 - }, - - // Helper functions - helpers: { - /** - * Get navigation links for current product - * @param {string} productKey - The product identifier - * @returns {Array} Navigation links for the product - */ - getProductNav(productKey = 'jan') { - return this.products[productKey]?.links || []; - }, - - /** - * Determine if current path should show API reference navigation - * @param {string} path - Current pathname - * @returns {boolean} Whether to show API reference navigation - */ - isApiReferencePage(path) { - return path.startsWith('/api-reference/') || path.startsWith('/api/'); - }, - - /** - * Get server configuration for deployment type - * @param {string} deployment - 'local' or 'cloud' - * @returns {Object} Server configuration - */ - getServerConfig(deployment) { - return this.apiDeployments[deployment] || this.apiDeployments.local; - }, - - /** - * Build navigation HTML for injection - * @param {string} currentPath - Current page path - * @param {string} productKey - Product identifier - * @returns {string} HTML string for navigation - */ - buildNavigationHTML(currentPath, productKey = 'jan') { - const links = this.getProductNav(productKey); - - return links.map(link => ` - - ${link.text} - - `).join(''); - } - } -}; - -// Export for use in browser context -if (typeof window !== 'undefined') { - window.JanNavigationConfig = NAVIGATION_CONFIG; -} - -export default NAVIGATION_CONFIG; diff --git a/website/src/content.config.ts b/website/src/content.config.ts deleted file mode 100644 index 69d64c7c7..000000000 --- a/website/src/content.config.ts +++ /dev/null @@ -1,10 +0,0 @@ -import { defineCollection, z } from 'astro:content' -import { docsLoader } from '@astrojs/starlight/loaders' -import { docsSchema } from '@astrojs/starlight/schema' - -export const collections = { - docs: defineCollection({ - loader: docsLoader(), - schema: docsSchema(), - }), -} diff --git a/website/src/content/docs/browser/index.mdx b/website/src/content/docs/browser/index.mdx deleted file mode 100644 index 967ba90f2..000000000 --- a/website/src/content/docs/browser/index.mdx +++ /dev/null @@ -1,41 +0,0 @@ ---- -title: Jan Browser Extension -description: Bring your favorite AI models to any website with Jan's browser extension. -keywords: - [ - Jan Browser Extension, - Jan AI, - Browser AI, - Chrome extension, - Firefox addon, - local AI, - ChatGPT alternative - ] -banner: - content: 'Coming in September 2025. Currently testing it with selected users and internally. ๐Ÿค“' ---- - -import { Aside, Card, CardGrid } from '@astrojs/starlight/components'; - -![Jan Browser Extension](/gifs/extension.gif) - -## Your AI Models, Anywhere on the Web - -The Jan Browser Extension brings AI assistance directly to your browsing experience. -Connect to your local Jan installation or any remote AI provider to get contextual help -on any website without switching tabs. - - - -Access your preferred models without leaving your current page. Whether you're using local -Jan models or remote providers, get instant AI assistance while reading, writing, or researching -online. - -### Core Features Planned: -- **Universal Access**: Use any Jan-compatible model from any website -- **Context Integration**: Highlight text and get AI assistance instantly -- **Privacy Options**: Choose between local processing or remote providers -- **Seamless Experience**: No tab switching or workflow interruption required diff --git a/website/src/content/docs/index.mdx b/website/src/content/docs/index.mdx deleted file mode 100644 index 87cf331db..000000000 --- a/website/src/content/docs/index.mdx +++ /dev/null @@ -1,282 +0,0 @@ ---- -title: Jan -description: Working towards open superintelligence through community-driven AI -keywords: - [ - Jan, - Jan AI, - open superintelligence, - AI ecosystem, - local AI, - private AI, - self-hosted AI, - llama.cpp, - Model Context Protocol, - MCP, - GGUF models, - large language model, - LLM, - ] -banner: - content: | - We just launched something cool! ๐Ÿ‘‹Jan now supports image ๐Ÿ–ผ๏ธ attachments ๐ŸŽ‰ ---- - -import { Aside, LinkCard } from '@astrojs/starlight/components'; - - -![Jan's Cover Image](../../assets/jan_loaded.png) - -## Jan's Goal - -> We're working towards open superintelligence to make a viable open-source alternative to platforms like ChatGPT -and Claude that anyone can own and run. - -## What is Jan Today - -Jan is an open-source AI platform that runs on your hardware. We believe AI should be in the hands of many, not -controlled by a few tech giants. - -Today, Jan is: -- **A desktop app** that runs AI models locally or connects to cloud providers -- **A model hub** making the latest open-source models accessible -- **A connector system** that lets AI interact with real-world tools via MCP - -Tomorrow, Jan aims to be a complete ecosystem where open models rival or exceed closed alternatives. - - - -## The Jan Ecosystem - -### Jan Apps -**Available Now:** -- **Desktop**: Full-featured AI workstation for Windows, Mac, and Linux - -**Coming Late 2025:** -- **Mobile**: Jan on your phone -- **Web**: Browser-based access at jan.ai -- **Server**: Self-hosted for teams -- **Extensions**: Browser extension for Chrome-based browsers - -### Jan Model Hub -Making open-source AI accessible to everyone: -- **Easy Downloads**: One-click model installation -- **Jan Models**: Our own models optimized for local use - - **Jan-v1**: 4B reasoning model specialized in web search - - **Research Models** - - **Jan-Nano (32k/128k)**: 4B model for web search with MCP tools - - **Lucy**: 1.7B mobile-optimized for web search -- **Community Models**: Any GGUF from Hugging Face works in Jan -- **Cloud Models**: Connect your API keys for OpenAI, Anthropic, Gemini, and more - - -### Jan Connectors Hub -Connect AI to the tools you use daily via [Model Context Protocol](./mcp): - -**Creative & Design:** -- **Canva**: Generate and edit designs - -**Data & Analysis:** -- **Jupyter**: Run Python notebooks -- **E2B**: Execute code in sandboxes - -**Web & Search:** -- **Browserbase & Browser Use**: Browser automation -- **Exa, Serper, Perplexity**: Advanced web search -- **Octagon**: Deep research capabilities - -**Productivity:** -- **Linear**: Project management -- **Todoist**: Task management - -## Core Features - -- **Run Models Locally**: Download any GGUF model from Hugging Face, use OpenAI's gpt-oss models, -or connect to cloud providers -- **OpenAI-Compatible API**: Local server at `localhost:1337` works with tools like -[Continue](./server-examples/continue-dev) and [Cline](https://cline.bot/) -- **Extend with MCP Tools**: Browser automation, web search, data analysis, and design tools, all -through natural language -- **Your Choice of Infrastructure**: Run on your laptop, self-host on your servers (soon), or use -cloud when you need it - -## Philosophy - -Jan is built to be user-owned: -- **Open Source**: Apache 2.0 license -- **Local First**: Your data stays on your device. Internet is optional -- **Privacy Focused**: We don't collect or sell user data. See our [Privacy Policy](./privacy) -- **No Lock-in**: Export your data anytime. Use any model. Switch between local and cloud - - - -## The Path Forward - -### What Works Today -- Run powerful models locally on consumer hardware -- Connect to any cloud provider with your API keys -- Use MCP tools for real-world tasks - -### What We're Building -- More specialized models that excel at specific tasks -- Expanded app ecosystem (mobile, self-hosted server, web, extensions) -- Richer connector ecosystem -- An evaluation framework to build better models - -### The Long-Term Vision -We're working towards open superintelligence where: -- Open models match or exceed closed alternatives -- Anyone can run powerful AI on their own hardware -- The community drives innovation, not corporations -- AI capabilities are owned by users, not rented - - - -## Quick Start - -1. [Download Jan](./quickstart) for your operating system -2. Choose a model - download locally or add cloud API keys -3. Start chatting or connect tools via MCP -4. Build with our [local API](./api-server) -5. Explore the [API Reference](/api) for Local and Server endpoints - - - -## Acknowledgements - -Jan is built on the shoulders of giants: -- [Llama.cpp](https://github.com/ggerganov/llama.cpp) for inference -- [Model Context Protocol](https://modelcontextprotocol.io) for tool integration -- The open-source community that makes this possible - -## FAQs - -
-What is Jan? - -Jan is an open-source AI platform working towards a viable alternative to Big Tech AI. Today it's a desktop app that runs models locally or connects to cloud providers. Tomorrow it aims to be a complete ecosystem rivaling platforms like ChatGPT and Claude. -
- -
-How is this different from other AI platforms? - -Other platforms are models behind APIs you rent. Jan is a complete AI ecosystem you own. Run any model, use real tools through MCP, keep your data private, and never pay subscriptions for local use. -
- -
-What models can I use? - -**Jan Models:** -- Jan-Nano (32k/128k) - Research and analysis with MCP integration -- Lucy - Mobile-optimized search (1.7B) -- Jan-v1 - Reasoning and tool use (4B) - -**Open Source:** -- OpenAI's gpt-oss models (120b and 20b) -- Any GGUF model from Hugging Face - -**Cloud (with your API keys):** -- OpenAI, Anthropic, Mistral, Groq, and more -
- -
-What are MCP tools? - -MCP (Model Context Protocol) lets AI interact with real applications. Instead of just generating text, your AI can create designs in Canva, analyze data in Jupyter, browse the web, and execute code - all through conversation. -
- -
-Is Jan compatible with my system? - -**Supported OS**: -- [Windows 10+](/docs/desktop/windows#compatibility) -- [macOS 12+](/docs/desktop/mac#compatibility) -- [Linux (Ubuntu 20.04+)](/docs/desktop/linux) - -**Hardware**: -- Minimum: 8GB RAM, 10GB storage -- Recommended: 16GB RAM, GPU (NVIDIA/AMD/Intel/Apple), 50GB storage -
- -
-How realistic is 'open superintelligence'? - -Honestly? It's ambitious and uncertain. We believe the combination of rapidly improving open models, better consumer hardware, community innovation, and specialized models working together can eventually rival closed platforms. But this is a multi-year journey with no guarantees. What we can guarantee is that we'll keep building in the open, with the community, towards this goal. -
- -
-What can Jan actually do today? - -Right now, Jan can: -- Run models like Llama, Mistral, and our own Jan models locally -- Connect to cloud providers if you want more power -- Use MCP tools to create designs, analyze data, browse the web, and more -- Work completely offline once models are downloaded -- Provide an OpenAI-compatible API for developers -
- -
-Is Jan really free? - -**Local use**: Always free, no catches -**Cloud models**: You pay providers directly (we add no markup) -**Jan cloud**: Optional paid services coming 2025 - -The core platform will always be free and open source. -
- -
-How does Jan protect privacy? - -- Runs 100% offline once models are downloaded -- All data stored locally in [Jan Data Folder](/docs/data-folder) -- No telemetry without explicit consent -- Open source code you can audit - - -
- -
-Can I self-host Jan? - -Yes. Download directly or build from [source](https://github.com/menloresearch/jan). Jan Server for production deployments coming late 2025. -
- -
-When will mobile/web versions launch? - -- **Jan Web**: Beta late 2025 -- **Jan Mobile**: Late 2025 -- **Jan Server**: Late 2025 - -All versions will sync seamlessly. -
- -
-How can I contribute? - -- Code: [GitHub](https://github.com/menloresearch/jan) -- Community: [Discord](https://discord.gg/FTk2MvZwJH) -- Testing: Help evaluate models and report bugs -- Documentation: Improve guides and tutorials -
- -
-Are you hiring? - -Yes! We love hiring from our community. Check [Careers](https://menlo.bamboohr.com/careers). -
diff --git a/website/src/content/docs/jan/assistants.mdx b/website/src/content/docs/jan/assistants.mdx deleted file mode 100644 index ca6d78ed6..000000000 --- a/website/src/content/docs/jan/assistants.mdx +++ /dev/null @@ -1,97 +0,0 @@ ---- -title: Assistants -description: A step-by-step guide on customizing and managing your assistants. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - manage assistants, - assistants, - ] ---- - -Jan allows you to give models specific sets of instructions without having to repeat yourself. We called these -models with your instructions, Assistants. Each of these assistants can also have their own set of configuration -which can help guide how the AI model should behave and respond to your inputs. You can add, edit, or delete -assistants, and customize their instructions and settings from the Assistants tab. - -![The Assistants management page, where you can view, add, edit, or delete assistants. Each assistant has a name, -description, and can be customized for different tasks.](../../../assets/assistants-ui-overview.png) - -To find the Assistants tab: - -1. Open Jan and look at the left sidebar. -2. Click on the **Assistants** tab (see highlighted section in the screenshot above). -3. The main panel will display all your current assistants. - -## Managing Assistants - -- **Add a New Assistant**: Click the `+` button in the Assistants panel to create a new assistant with your instructions. -- **Edit an Assistant**: Click the pencil (โœ๏ธ) icon on any assistant card to update its name, description, or instructions. -- **Delete an Assistant**: Click the trash (๐Ÿ—‘๏ธ) icon to remove an assistant you no longer need. - -## Customizing Assistant Instructions - -Each assistant can have its own set of instructions to guide its behavior. For example: - -``` -Act as a software engineering mentor focused on Python and JavaScript. -Provide detailed explanations with code examples when relevant. -Use markdown formatting for code blocks. -``` - -Or: - -``` -Respond in a casual, friendly tone. Keep explanations brief and use simple language. -Provide examples when explaining complex topics. -``` - -Or: - -``` -Respond in a casual, friendly tone. Keep explanations brief and use simple language. -Provide examples when explaining complex topics. -``` - -## Best Practices -- Be clear and specific about the desired behavior for each assistant. -- Include preferences for formatting, tone, or style. -- Include examples to increase the model's compliance with your request. -- Use different assistants for different tasks (e.g., translation, travel planning, financial advice). - - -## Switching and Managing Assistants in Chat - -You can quickly switch between assistants, or create and edit them, directly from the Chat screen using the -assistant dropdown menu at the top: - -![Assistant Dropdown](../../../assets/assistant-dropdown-updated.png) - -- Click the assistant's name (e.g., "Travel Planner") at the top of the Chat screen to open the dropdown menu. -- The dropdown lists all of your assistants. Click on any of the assistants available to switch to it for the -current chat session. -- To create a new assistant, select **Create Assistant** at the bottom of the dropdown. This opens the Add Assistant dialog: - -![Add Assistant Dialog](../../../assets/assistant-add-dialog.png) - -- To edit an existing assistant, click the gear (โš™๏ธ) icon next to its name in the dropdown. This opens the Edit Assistant dialog: - -![Edit Assistant Dialog](../../../assets/assistant-edit-dialog.png) - -### Add/Edit Assistant Dialogs -- Set an (optional) emoji and name for your assistant. -- Optionally add a description. -- Enter detailed instructions to guide the assistant's behavior. -- Adjust the predefined parameters (like Temperature, Top P, etc.) or add custom parameters as needed. -- Click **Save** to apply your changes. - -This workflow allows you to seamlessly manage and switch between assistants while chatting, making it easy to tailor -Jan to your needs in real time. diff --git a/website/src/content/docs/jan/custom-provider.mdx b/website/src/content/docs/jan/custom-provider.mdx deleted file mode 100644 index 23ad87a67..000000000 --- a/website/src/content/docs/jan/custom-provider.mdx +++ /dev/null @@ -1,288 +0,0 @@ ---- -title: Custom Providers -description: Connect Jan to any OpenAI-compatible AI service, from major cloud providers to local inference servers. -keywords: - [ - Jan, - custom providers, - OpenAI API, - Together AI, - vLLM, - LMStudio, - transformers, - SGLang, - API integration, - local AI, - cloud AI, - ] -sidebar: - badge: - text: New - variant: tip ---- - -import { Aside } from '@astrojs/starlight/components'; - -Jan's custom provider system lets you connect to any OpenAI-compatible API service. Whether you're using cloud providers like Together AI, Fireworks, or Replicate, or running local inference servers like vLLM, LMStudio, or transformers, Jan can integrate with them seamlessly. - -## What You Can Connect - -**Cloud Providers:** -- Together AI, Fireworks, Replicate -- Perplexity, DeepInfra, Anyscale -- Any OpenAI-compatible API service - -**Local Inference Servers:** -- vLLM, LMStudio, Ollama -- SGLang, transformers, text-generation-webui -- TensorRT-LLM, LocalAI - -**Self-Hosted Solutions:** -- Your own API deployments -- Enterprise AI gateways -- Custom model endpoints - -## Setup Process - -### Add a New Provider - -Navigate to **Settings > Model Providers** and click **Add Provider**. - -![Add custom provider button](../../../assets/customprovider.png) - -Enter a name for your provider. We'll use Together AI as our example. - -![Provider name modal](../../../assets/customprovider2.png) - -### Get Your API Credentials - -For cloud providers, you'll need an account and API key. Here's Together AI's dashboard showing your credits and API key location. - -![Together AI dashboard](../../../assets/customprovider3.png) - - - -### Configure the Provider - -Back in Jan, fill in your provider's details: - -**API Base URL:** The endpoint for your service (e.g., `https://api.together.xyz/`) -**API Key:** Your authentication token - -![Provider configuration](../../../assets/customprovider4.png) - -Common endpoints for popular services: -- **Together AI:** `https://api.together.xyz/` -- **Fireworks:** `https://api.fireworks.ai/` -- **Replicate:** `https://api.replicate.com/` -- **Local vLLM:** `http://localhost:8000/` (default) -- **LMStudio:** `http://localhost:1234/` (default) - -### Add Model IDs - -Click the `+` button to add specific models you want to access. Each provider offers different models with various capabilities. - -![Add model ID modal](../../../assets/customprovider5.png) - -For Together AI, we're adding `Qwen/Qwen3-235B-A22B-Thinking-2507`, one of the most capable reasoning models available. - -### Configure Model Features - -After adding a model, click the pencil icon to enable additional features like tools or vision capabilities. - -![Model configuration icon](../../../assets/customprovider6.png) - -Enable tools if your model supports function calling. This allows integration with Jan's MCP system for web search, code execution, and more. - -![Enable tools modal](../../../assets/customprovider7.png) - -### Start Using Your Custom Model - -Open a new chat and select your custom model from the provider dropdown. - -![Model selection in chat](../../../assets/customprovider8.png) - -If you enabled tools, click the tools icon to activate MCP integrations. Here we have Serper MCP enabled for web search capabilities. - -![Tools enabled in chat](../../../assets/customprovider9.png) - - - -### Example in Action - -Here's the Qwen model thinking through a complex query, searching the web, and providing detailed information about Sydney activities. - -![Example conversation](../../../assets/customprovider10.png) - -**Prompt used:** "What is happening in Sydney, Australia this week? What fun activities could I attend?" - -The model demonstrated reasoning, web search integration, and comprehensive response formattingโ€”all through Jan's custom provider system. - -## Provider-Specific Setup - -### Together AI -- **Endpoint:** `https://api.together.xyz/` -- **Popular Models:** `meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo`, `Qwen/Qwen2.5-Coder-32B-Instruct` -- **Features:** Fast inference, competitive pricing, latest models -- **Best For:** Production applications, latest model access - -### Fireworks AI -- **Endpoint:** `https://api.fireworks.ai/` -- **Popular Models:** `accounts/fireworks/models/llama-v3p1-405b-instruct`, `accounts/fireworks/models/qwen2p5-coder-32b-instruct` -- **Features:** Ultra-fast inference, function calling support -- **Best For:** Real-time applications, tool usage - -### vLLM (Local) -- **Endpoint:** `http://localhost:8000/` (configurable) -- **Setup:** Install vLLM, run `vllm serve MODEL_NAME --api-key YOUR_KEY` -- **Models:** Any HuggingFace model compatible with vLLM -- **Best For:** Self-hosted deployments, custom models - -### LMStudio (Local) -- **Endpoint:** `http://localhost:1234/` (default) -- **Setup:** Download LMStudio, load a model, start local server -- **Models:** GGUF models from HuggingFace -- **Best For:** Easy local setup, GUI management - -### Ollama (Local) -- **Endpoint:** `http://localhost:11434/` (with OpenAI compatibility) -- **Setup:** Install Ollama, run `OLLAMA_HOST=0.0.0.0 ollama serve` -- **Models:** Ollama model library (llama3, qwen2.5, etc.) -- **Best For:** Simple local deployment, model management - -## Example Prompts to Try - -### Advanced Reasoning -``` -I'm planning to start a sustainable urban garden on my apartment balcony. Consider my location (temperate climate), space constraints (4x6 feet), budget ($200), and goals (year-round fresh herbs and vegetables). Provide a detailed plan including plant selection, container setup, watering system, and seasonal rotation schedule. -``` - -### Research and Analysis -``` -Compare the environmental impact of electric vehicles vs hydrogen fuel cell vehicles in 2024. Include manufacturing emissions, energy sources, infrastructure requirements, and lifecycle costs. Provide specific data and cite recent studies. -``` - -### Creative Problem Solving -``` -Design a mobile app that helps people reduce food waste. Consider user psychology, practical constraints, monetization, and social impact. Include wireframes description, key features, and go-to-market strategy. -``` - -### Technical Deep Dive -``` -Explain how large language models use attention mechanisms to understand context. Start with the basics and build up to transformer architecture, including mathematical foundations and practical implications for different model sizes. -``` - -### Planning and Strategy -``` -I have 6 months to learn machine learning from scratch and land an ML engineering job. Create a week-by-week study plan including theory, practical projects, portfolio development, and job search strategy. Consider my background in software development. -``` - -## Advanced Configuration - -### Authentication Methods - -**API Key Header (Most Common):** -- Standard: `Authorization: Bearer YOUR_KEY` -- Custom: `X-API-Key: YOUR_KEY` - -**Query Parameters:** -- Some services use `?api_key=YOUR_KEY` - -**Custom Headers:** -- Enterprise gateways may require specific headers - -### Request Customization - -Most providers support OpenAI's standard parameters: -- `temperature`: Response creativity (0.0-1.0) -- `max_tokens`: Response length limit -- `top_p`: Token selection probability -- `frequency_penalty`: Repetition control -- `presence_penalty`: Topic diversity - -### Model Naming Conventions - -Different providers use various naming schemes: -- **HuggingFace:** `organization/model-name` -- **Together AI:** `meta-llama/Llama-2-70b-chat-hf` -- **Ollama:** `llama3:latest` -- **Local:** Often just the model name - -## Troubleshooting - -### Connection Issues -- Verify the API endpoint URL is correct -- Check if the service is running (for local providers) -- Confirm network connectivity and firewall settings - -### Authentication Failures -- Ensure API key is copied correctly (no extra spaces) -- Check if the key has necessary permissions -- Verify the authentication method matches provider requirements - -### Model Not Found -- Confirm the model ID exists on the provider -- Check spelling and capitalization -- Some models require special access or approval - -### Rate Limiting -- Most providers have usage limits -- Implement delays between requests if needed -- Consider upgrading to higher tier plans - -### Performance Issues -- Local providers may need more powerful hardware -- Cloud providers vary in response times -- Check provider status pages for service issues - -## Cost Management - -### Cloud Provider Pricing -- Most charge per token (input + output) -- Prices vary significantly between models -- Monitor usage through provider dashboards - -### Local Provider Costs -- Hardware requirements (RAM, GPU) -- Electricity consumption -- Initial setup and maintenance time - -### Optimization Tips -- Use smaller models for simple tasks -- Implement caching for repeated queries -- Set appropriate max_tokens limits -- Monitor and track usage patterns - -## Best Practices - -### Security -- Store API keys securely -- Use environment variables in production -- Rotate keys regularly -- Monitor for unauthorized usage - -### Performance -- Choose models appropriate for your tasks -- Implement proper error handling -- Cache responses when possible -- Use streaming for long responses - -### Reliability -- Have fallback providers configured -- Implement retry logic -- Monitor service availability -- Test regularly with different models - -## Next Steps - -Once you have custom providers configured, explore advanced integrations: -- Combine with [MCP tools](./mcp-examples/search/serper) for enhanced capabilities -- Set up multiple providers for different use cases -- Create custom assistants with provider-specific models -- Build workflows that leverage different model strengths - -Custom providers unlock Jan's full potential, letting you access cutting-edge models and maintain complete control over your AI infrastructure. Whether you prefer cloud convenience or local privacy, Jan adapts to your workflow. \ No newline at end of file diff --git a/website/src/content/docs/jan/data-folder.mdx b/website/src/content/docs/jan/data-folder.mdx deleted file mode 100644 index 98d605a03..000000000 --- a/website/src/content/docs/jan/data-folder.mdx +++ /dev/null @@ -1,216 +0,0 @@ ---- -title: Jan Data Folder -description: A guide to Jan's data structure. -sidebar_position: 2 -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - quickstart, - getting started, - using AI model, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -Jan stores your data locally in JSON format. Your data is yours alone. - -## Open Jan Data Folder - -Via Jan: -1. **Settings** > **General** -2. Click on the **Change Location** button. - -![Open Jan Data Folder](../../../assets/settings-11.png) - - -Via Terminal: - -```bash -# Windows -cd %APPDATA%/Jan/data - -# Mac -cd ~/Library/Application\ Support/Jan/data - -# Linux -cd $XDG_CONFIG_HOME/Jan/data # Custom install -cd ~/.config/Jan/data # Default install -``` - -## Directory Structure - - - -``` -/assistants/ - /jan/ - assistant.json -/engines/ - /llama.cpp/ -/extensions/ - extensions.json -/@janhq/ - /assistant-extension/ - /conversational-extension/ - /download-extension/ - /engine-management-extension/ - /hardware-management-extension/ - /inference-cortex-extension/ - /model-extension/ -/files/ -/logs/ - app.log -/models/ - /huggingface.co/ - /Model_Provider_A/ - /Model_A - model_A.gguf - model_A.yaml -/threads/ - /thread_A/ - messages.jsonl - thread.json - -``` - -### `assistants/` -Where AI personalities live. The default one (`/assistants/jan/`): - -```json -{ - "avatar": "๐Ÿ‘‹", - "id": "jan", - "object": "assistant", - "created_at": 1750945742.536, - "name": "Jan", - "description": "Jan is a helpful AI assistant that can use tools and help complete tasks for its users.", - "model": "*", - "instructions": "You have access to a set of tools to help you answer the userโ€™s question. You can use only one tool per message, and youโ€™ll receive the result of that tool in the userโ€™s next response. To complete a task, use tools step by stepโ€”each step should be guided by the outcome of the previous one.\nTool Usage Rules:\n1. Always provide the correct values as arguments when using tools. Do not pass variable namesโ€”use actual values instead.\n2. You may perform multiple tool steps to complete a task.\n3. Avoid repeating a tool call with exactly the same parameters to prevent infinite loops.", - "tools": [ - { - "type": "retrieval", - "enabled": false, - "useTimeWeightedRetriever": false, - "settings": { - "top_k": 2, - "chunk_size": 1024, - "chunk_overlap": 64, - "retrieval_template": "Use the following pieces of context to answer the question at the end.\n----------------\nCONTEXT: {CONTEXT}\n----------------\nQUESTION: {QUESTION}\n----------------\nHelpful Answer:" - } - } - ], - "file_ids": [] -} -``` - -Parameters: - -| Parameter | Description | Type | Default | -|------------------------|--------------------------------------------------------------|---------|---------| -| id | Assistant identifier | string | jan | -| avatar | Assistant image | string | None | -| object | OpenAI API compatibility marker | string | None | -| created_at | Creation timestamp | string | None | -| name | Display name | string | Jan | -| description | Role description | string | Default | -| model | Allowed models (* = all) | string | * | -| instructions | Default thread instructions | string | None | -| file_ids | OpenAI compatibility field | string | None | -| tools | Available tools (retrieval only currently) | array | retrieval| -| type | Tool type | string | retrieval| -| enabled | Tool status | boolean | true | -| useTimeWeightedRetriever| Time-weighted retrieval toggle | boolean | false | -| settings | Tool configuration | object | None | -| top_k | Max retrieval results | number | 2 | -| chunk_size | Text chunk size | number | 1024 | -| chunk_overlap | Chunk overlap amount | number | 64 | -| retrieval_template | Response format template | string | None | - -### `extensions/` -Add-on central. Organization extensions live in `@janhq/`, solo ones in root. - -### `logs/` -Debugging headquarters (`/logs/app.txt`): -- **[APP]**: Core logs -- **[SERVER]**: API drama -- **[SPECS]**: Hardware confessions - -### `models/` -The silicon brain collection. Each model has its own `model.json`. - - - -### `threads/` -Chat archive. Each thread (`/threads/jan_unixstamp/`) contains: - -- `messages.jsonl`: -```json - { - "completed_at": 0, - "content": [ - { - "text": { - "annotations": [], - "value": "Hello! I can help you with various tasks. I can search for information on the internet, including news, videos, images, shopping, and more. I can also scrape webpages to extract specific information. Let me know what you need!" - }, - "type": "text" - } - ], - "created_at": 1751012639307, - "id": "01JYR7S0JB5ZBGMJV52KWMW5VW", - "metadata": { - "assistant": { - "avatar": "๐Ÿ‘‹", - "id": "jan", - "instructions": "You have access to a set of tools to help you answer the user's question. You can use only one tool per message, and you'll receive the result of that tool in the user's next response. To complete a task, use tools step by stepโ€”each step should be guided by the outcome of the previous one.\nTool Usage Rules:\n1. Always provide the correct values as arguments when using tools. Do not pass variable namesโ€”use actual values instead.\n2. You may perform multiple tool steps to complete a task.\n3. Avoid repeating a tool call with exactly the same parameters to prevent infinite loops.", - "name": "Jan", - "parameters": "" - }, - "tokenSpeed": { - "lastTimestamp": 1751012637097, - "message": "01JYR7S0GW5M9PSHMRE7T8VQJM", - "tokenCount": 49, - "tokenSpeed": 22.653721682847895 - } - }, - "object": "thread.message", - "role": "assistant", - "status": "ready", - "thread_id": "8f2c9922-db49-4d1e-8620-279c05baf2d0", - "type": "text" - } -``` - -- `thread.json`: - -| Parameter | Description | -|------------|------------------------------------------------| -| assistants | Assistant configuration clone | -| created | Creation timestamp | -| id | Thread identifier | -| metadata | Additional thread data | -| model | Active model settings | -| object | OpenAI compatibility marker | -| title | Thread name | -| updated | Updated timestamp | - - - - -## Delete Jan Data - -Uninstall guides: [Mac](./installation/mac#step-2-clean-up-data-optional), -[Windows](./installation/windows#step-2-handle-jan-data), or [Linux](./installation/linux#uninstall-jan). diff --git a/website/src/content/docs/jan/explanation/model-parameters.mdx b/website/src/content/docs/jan/explanation/model-parameters.mdx deleted file mode 100644 index 038fc09d9..000000000 --- a/website/src/content/docs/jan/explanation/model-parameters.mdx +++ /dev/null @@ -1,108 +0,0 @@ ---- -title: Model Parameters -description: Customize how your AI models behave and perform. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - model settings, - parameters, - ] ---- -import { Aside, Steps } from '@astrojs/starlight/components' - -Model parameters control how your AI thinks and responds. Think of them as the AI's personality settings and performance controls. - -## How to Access Settings - -**For individual conversations:** -- In **Threads**, click the **gear icon** next to your selected model - -**For permanent model settings:** -- Go to **Settings > Model Providers > Llama.cpp**, click the **gear icon** next to a model - -**For model capabilities:** -- Click the **edit button** next to a model to enable features like vision or tools - -## Performance Settings (Gear Icon) - -These settings control how the model thinks and performs: - -| Setting | What It Does | Simple Explanation | -|---------|-------------|-------------------| -| **Context Size** | How much text the model remembers | Like the model's working memory. Larger = remembers more of your conversation, but uses more computer memory. | -| **GPU Layers** | How much work your graphics card does | More layers on GPU = faster responses, but needs more graphics memory. Start high and reduce if you get errors. | -| **Temperature** | How creative vs. predictable responses are | Low (0.1-0.3) = focused, consistent answers. High (0.7-1.0) = creative, varied responses. Try 0.7 for general use. | -| **Top K** | How many word choices the model considers | Smaller numbers (20-40) = more focused. Larger numbers (80-100) = more variety. Most people don't need to change this. | -| **Top P** | Another way to control word variety | Works with Top K. Values like 0.9 work well. Lower = more focused, higher = more creative. | -| **Min P** | Minimum chance a word needs to be chosen | Prevents very unlikely words. Usually fine at default settings. | -| **Repeat Last N** | How far back to check for repetition | Helps prevent the model from repeating itself. Default values usually work well. | -| **Repeat Penalty** | How much to avoid repeating words | Higher values (1.1-1.3) reduce repetition. Too high makes responses awkward. | -| **Presence Penalty** | Encourages talking about new topics | Higher values make the model explore new subjects instead of staying on one topic. | -| **Frequency Penalty** | Reduces word repetition | Similar to repeat penalty but focuses on how often words are used. | - -![Model Parameters](../../../../assets/model-parameters.png) - -## Model Capabilities (Edit Button) - -These toggle switches enable special features: - -- **Vision**: Let the model see and analyze images you share -- **Tools**: Enable advanced features like web search, file operations, and code execution -- **Embeddings**: Allow the model to create numerical representations of text (for advanced users) -- **Web Search**: Let the model search the internet for current information -- **Reasoning**: Enable step-by-step thinking for complex problems - -![Model Capabilities Edit 01](../../../../assets/model-capabilities-edit-01.png) -![Model Capabilities Edit 02](../../../../assets/model-capabilities-edit-02.png) - -## Hardware Settings - -These control how efficiently the model runs on your computer: - -### GPU Layers -Think of your model as a stack of layers, like a cake. Each layer can run on either your main processor (CPU) or graphics card (GPU). Your graphics card is usually much faster. - -- **More GPU layers** = Faster responses, but uses more graphics memory -- **Fewer GPU layers** = Slower responses, but uses less graphics memory - -Start with the maximum number and reduce if you get out-of-memory errors. - -### Context Length -This is like the model's short-term memory - how much of your conversation it can remember at once. - -- **Longer context** = Remembers more of your conversation, better for long discussions -- **Shorter context** = Uses less memory, runs faster, but might "forget" earlier parts of long conversations - - - -## Quick Setup Guide - -**For most users:** -1. Enable **Tools** if you want web search and code execution -2. Set **Temperature** to 0.7 for balanced creativity -3. Max out **GPU Layers** (reduce only if you get memory errors) -4. Leave other settings at defaults - -**For creative writing:** -- Increase **Temperature** to 0.8-1.0 -- Increase **Top P** to 0.95 - -**For factual/technical work:** -- Decrease **Temperature** to 0.1-0.3 -- Enable **Tools** for web search and calculations - -**Troubleshooting:** -- **Responses too repetitive?** Increase Temperature or Repeat Penalty -- **Out of memory errors?** Reduce GPU Layers or Context Size -- **Responses too random?** Decrease Temperature -- **Model running slowly?** Increase GPU Layers (if you have VRAM) or reduce Context Size diff --git a/website/src/content/docs/jan/installation/linux.mdx b/website/src/content/docs/jan/installation/linux.mdx deleted file mode 100644 index 4897e2c9c..000000000 --- a/website/src/content/docs/jan/installation/linux.mdx +++ /dev/null @@ -1,262 +0,0 @@ ---- -title: Linux -description: Get started quickly with Jan, an AI chat application that runs 100% offline on your desktop & mobile (*coming soon*). -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - quickstart, - getting started, - using AI model, - installation, - "desktop" - ] ---- - -import { Aside, Tabs, TabItem } from '@astrojs/starlight/components'; - -Instructions for installing Jan on Linux. - -## Compatibility -System requirements: - - - - #### Debian-based (Supports `.deb` and `AppImage`) - - - Debian - - Ubuntu and derivatives: - - Ubuntu Desktop LTS (official)/Ubuntu Server LTS (only for server) - - Edubuntu - - Kubuntu - - Lubuntu - - Ubuntu Budgie - - Ubuntu Cinnamon - - Ubuntu Kylin - - Ubuntu MATE - - Linux Mint - - Pop!_OS - - #### RHEL-based (Supports `.rpm` and `AppImage`) - - - RHEL-based (Server only) - - Fedora - - #### Arch-based - - - Arch Linux - - SteamOS - - #### Independent - - - openSUSE - - - - - Haswell processors (Q2 2013) and newer - - Tiger Lake (Q3 2020) and newer for Celeron and Pentium processors - - Excavator processors (Q2 2015) and newer - - - - - - - 8GB โ†’ up to 3B parameter models (int4) - - 16GB โ†’ up to 7B parameter models (int4) - - 32GB โ†’ up to 13B parameter models (int4) - - - - - - - 6GB โ†’ up to 3B parameter models (int4) - - 8GB โ†’ up to 7B parameter models (int4) - - 12GB โ†’ up to 13B parameter models (int4) - - - - - - Minimum 10GB of free disk space required. - - - -## Install Jan - -Installation steps: - - -### Step 1: Download Application - -Available releases: - - - Stable release: - - Ubuntu: [jan.deb](https://app.jan.ai/download/latest/linux-amd64-deb) - - Others: [Jan.AppImage](https://app.jan.ai/download/latest/linux-amd64-appimage) - - Official Website: https://jan.ai/download - - - - Development build: - - Ubuntu: [jan.deb](https://app.jan.ai/download/nightly/linux-amd64-deb) - - Others: [Jan.AppImage](https://app.jan.ai/download/nightly/linux-amd64-appimage) - - - - - -### Step 2: Install Application - -Installation commands: - - - - ##### dpkg - - ```bash - sudo dpkg -i jan-linux-amd64-{version}.deb - ``` - - ##### apt-get - - ```bash - sudo apt-get install ./jan-linux-amd64-{version}.deb - ``` - - - - From the terminal, run the following commands: - - ```bash - chmod +x jan-linux-x86_64-{version}.AppImage - ./jan-linux-x86_64-{version}.AppImage - ``` - - - - - -## Data Folder - -Default locations: - -```bash -# Custom installation directory -$XDG_CONFIG_HOME = /home/username/custom_config - -# or - -# Default installation directory -~/.config/Jan/data - -``` -See [Jan Data Folder](/docs/data-folder) for details. - - -## GPU Acceleration -Configuration for GPU support: - - - - ### Step 1: Verify Hardware & Install Dependencies - - **1.1. Check GPU Detection** - - ```sh - lspci | grep -i nvidia - ``` - - **1.2. Install Required components** - - **NVIDIA Driver:** - - 1. Install the [NVIDIA Driver](https://www.nvidia.com/en-us/drivers/), ideally via your package manager. - 2. Verify: - - ```sh - nvidia-smi - ``` - - **CUDA Toolkit:** - - 1. Install the [CUDA toolkit](https://developer.nvidia.com/cuda-downloads), ideally from your package manager (**11.7+**) - 2. Verify: - - ```sh - nvcc --version - ``` - - **Additional Requirements:** - - ```sh - sudo apt update - sudo apt install gcc-11 g++-11 cpp-11 - export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64 - ``` - [Documentation](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions) - - ### Step 2: Enable GPU Acceleration - - 1. Navigate to **Settings** > **Local Engine** > **Llama.cpp** - 2. Select appropriate backend in **llama-cpp Backend**. Details in our [guide](/docs/local-engines/llama-cpp). - - - - - - Requires Vulkan support. - - 1. Navigate to **Settings** > **Hardware** > **GPUs** - 2. Select appropriate backend in **llama-cpp Backend**. Details in our [guide](/docs/local-engines/llama-cpp). - - - - Requires Vulkan support. - - 1. Navigate to **Settings** > **Hardware** > **GPUs** - 2. Select appropriate backend in **llama-cpp Backend**. Details in our [guide](/docs/local-engines/llama-cpp). - - - -## Uninstall Jan - -Removal commands: - - - ```bash - sudo apt-get remove jan - rm -rf Jan - rm -rf ~/.config/Jan/data - rm -rf ~/.config/Jan/cache - ``` - - - - ```bash - rm jan-linux-x86_64-{version}.AppImage - rm -rf ~/.config/Jan - ``` - - - - diff --git a/website/src/content/docs/jan/installation/mac.mdx b/website/src/content/docs/jan/installation/mac.mdx deleted file mode 100644 index 80a8cf40f..000000000 --- a/website/src/content/docs/jan/installation/mac.mdx +++ /dev/null @@ -1,131 +0,0 @@ ---- -title: Mac -description: Get started quickly with Jan - a local AI that runs on your computer. Install Jan and pick your model to start chatting. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - quickstart, - getting started, - using AI model, - installation, - "desktop" - ] ---- - -import { Aside, Tabs, TabItem } from '@astrojs/starlight/components'; - - -Jan runs natively on both Apple Silicon and Intel-based Macs. - -## Compatibility - -### Minimum Requirements - -Your Mac needs: -- **Operating System:** MacOSX 13.6 or higher -- **Memory:** - - 8GB โ†’ up to 3B parameter models - - 16GB โ†’ up to 7B parameter models - - 32GB โ†’ up to 13B parameter models -- **Storage:** 10GB+ free space - -### Mac Performance Guide - - - -**Apple Silicon (M1, M2, M3)** -- Metal acceleration enabled by default -- GPU-accelerated processing - -**Intel-based Mac** -- CPU processing only -- Standard performance - -_Check your Mac's processor: Apple menu โ†’ About This Mac_ - -## Install Jan - -Installation steps: - -### Step 1: Download Application - -Select version: - - - - Get Jan from here: - - [Download Jan's Stable Version](https://app.jan.ai/download/latest/mac-universal) - - Official Website: https://jan.ai/download - - - - - Nightly: Latest features, less stable. - - [Download Jan's Nightly Version](https://app.jan.ai/download/nightly/mac-universal) - - - - - - -### Step 2: Install Application - -1. Open the Jan installer (`.dmg` file) -2. Drag Jan to **Applications** -3. Wait a moment -4. Launch Jan - - -## Jan Data Folder - -Default location: - -```sh -# Default installation directory -~/Library/Application\ Support/Jan/data -``` - -See [Jan Data Folder](../data-folder) for details. - - -## Uninstall Jan - - -### Step 1: Remove Application - -1. Close Jan if it's running -2. Open **Finder** -3. Go to **Applications** -4. Find Jan -5. Pick your removal method: - - Drag to **Trash** - - Right-click โ†’ **Move to Trash** - - **Command-Delete** - -### Step 2: Clean Up Data (Optional) - -Run this in **Terminal** to remove all data: - -```bash -rm -rf ~/Library/Application\ Support/Jan/data -``` - - diff --git a/website/src/content/docs/jan/installation/windows.mdx b/website/src/content/docs/jan/installation/windows.mdx deleted file mode 100644 index 45e80fad2..000000000 --- a/website/src/content/docs/jan/installation/windows.mdx +++ /dev/null @@ -1,189 +0,0 @@ ---- -title: Windows -description: Run AI models locally on your Windows machine with Jan. Quick setup guide for local inference and chat. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - quickstart, - getting started, - using AI model, - installation, - "desktop" - ] ---- - -import { Aside, Tabs, TabItem } from '@astrojs/starlight/components'; - - -## Compatibility - -**System requirements:** -- **Operating System**: Windows 10 or higher. -- **CPU** - - - - - Intel: Haswell (Q2 2013) or newer - - Intel Celeron/Pentium: Tiger Lake (Q3 2020) or newer - - - - Excavator processors (Q2 2015) and newer. - - - - - -**Memory (RAM)** -- 8GB โ†’ up to 3B parameter models (int4) -- 16GB โ†’ up to 7B parameter models (int4) -- 32GB โ†’ up to 13B parameter models (int4) - - - -**GPU**: -- 6GB โ†’ up to 3B parameter models -- 8GB โ†’ up to 7B parameter models -- 12GB โ†’ up to 13B parameter models - - - -**Storage:** 10GB free space minimum for app and models - - -## Install Jan - -### Step 1: Download Application - - - - - [Download Stable Jan](https://app.jan.ai/download/latest/win-x64) - - Official Website: [Download Jan](https://jan.ai/download) - - - - Nightly: Development build with latest features - - [Download Nightly Jan](https://app.jan.ai/download/nightly/win-x64) - - - - - -### Step 2: Install Application - -1. Run the downloaded `.exe` file -2. Wait for installation to complete -3. Launch Jan - -## Data Folder - -Default installation path: - -```sh -# Default installation directory -~\Users\\AppData\Roaming\Jan\data -``` - -See [Jan Data Folder](/docs/data-folder) for complete folder structure details. - - -## GPU Acceleration - - - - -### Step 1: Verify Hardware & Install Dependencies -**1.1. Check GPU Detection** - -Verify GPU is recognized: -- Right-click desktop > NVIDIA Control Panel -- Or check Device Manager > Display Adapters - -**1.2. Install Required components** -**NVIDIA Driver:** -1. Install [NVIDIA Driver](https://www.nvidia.com/en-us/drivers/) (version **470.63.01 or higher**) -2. Verify installation: - -```sh -nvidia-smi -``` - -**CUDA Toolkit:** -1. Install [CUDA toolkit](https://developer.nvidia.com/cuda-downloads) (**11.7 or higher**) -2. Verify installation: - -```sh -nvcc --version -``` -### Step 2: Enable GPU Acceleration - -Navigate to **Settings** > **Hardware** > **GPUs** -and toggle the **ON** switch if not enabled. - - - - - AMD GPUs require **Vulkan** support. - - Navigate to **Settings** > **Hardware** > **GPUs** - and toggle the **ON** switch if not enabled. - - - - - Intel Arc GPUs require **Vulkan** support. - - Navigate to **Settings** > **Hardware** > **GPUs** - and toggle the **ON** switch if not enabled. - - - - - - -## Uninstall Jan - -### Step 1: Remove Application through Control Panel - -1. Open **Control Panels** -2. Go to **Programs** section -3. Click **Uninstall Program** -4. Search for **Jan** -5. Click the **Three Dots Icon** > **Uninstall** -6. Click **Uninstall** again to confirm -7. Click **OK** - -### Step 2: Clean Up Remaining Files - -Remove app data: - -1. Navigate to `C:\Users\[username]\AppData\Roaming` -2. Delete Jan folder - -or via **Terminal**: - -```sh -cd C:\Users\%USERNAME%\AppData\Roaming -rmdir /S Jan -``` - - diff --git a/website/src/content/docs/jan/jan-models/jan-nano-128.mdx b/website/src/content/docs/jan/jan-models/jan-nano-128.mdx deleted file mode 100644 index 03ee1f17c..000000000 --- a/website/src/content/docs/jan/jan-models/jan-nano-128.mdx +++ /dev/null @@ -1,137 +0,0 @@ ---- -title: Jan Nano 128k -description: Jan Models -keywords: - [ - Jan, - Jan Models, - Jan Model, - Jan Model List, - Menlo Models, - Menlo Model, - Jan-Nano-Gguf, - ReZero, - Model Context Protocol, - MCP, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -> Enabling deeper research through extended context understanding. - -Jan-Nano-128k represents a notable advancement in compact language models for different applications. Building upon the -success of Jan-Nano-32k, this enhanced version features a native 128k context window that enables deeper, more comprehensive -research capabilities without the performance degradation typically associated with context extension methods. - -You can have a look at all of our models, and download them from the HuggingFace [Menlo Models page](https://huggingface.co/Menlo). - -**Key Improvements:** - -- ๐Ÿ” Deeper Research: Extended context allows for processing entire research papers, lengthy documents, and complex multi-turn conversations -- โšก Native 128k Window: Built to handle long contexts efficiently, maintaining performance across the full context range -- ๐Ÿ“ˆ Enhanced Performance: Unlike traditional context extension methods, Jan-Nano-128k's performance remains consistent with longer contexts - -This model maintains full compatibility with Model Context Protocol (MCP) servers while dramatically expanding the scope of research -tasks it can handle in a single session. - - -## Why Jan-Nano-128k? - -Most small models hit a wall at 8-32k tokens. Jan-Nano-128k goes beyond this limitation with a native 128k context windowโ€”that's roughly -300 pages of text or an entire novel's worth of information processed simultaneously. - -Unlike YaRN or PI methods that retrofit models beyond their limits and degrade performance, Jan-Nano-128k was architecturally rewired for -128k contexts from the ground up. The result: an inverse scaling behavior where performance actually improves with longer contexts, -maintaining consistent accuracy from 1k to 128k tokens as the model leverages more information for synthesis. - - - - -**Applications unlocked:** -- **Academic**: Extract key findings from 50+ papers simultaneously -- **Legal**: Pinpoint relevant clauses across thousand-page contracts -- **Code**: Trace specific functions through massive codebases -- **Business**: Distill insights from quarters of financial data -- **Content**: Maintain narrative coherence across book-length outputs - -**MCP Usage:** Jan-Nano-128k doesn't memorize, it orchestrates. With MCP integration, it becomes a research conductor that fetches dozens -of sources, holds everything in active memory, extracts precisely what's needed, and synthesizes findings across a marathon research session. It's -not about understanding every word; it's about finding the needle in a haystack of haystacks. - -## Evaluation - -Jan-Nano-128k has been rigorously evaluated on the SimpleQA benchmark using our MCP-based methodology, demonstrating superior performance compared to its predecessor: - -![Jan-Nano-128k Performance](../../../../assets/jan-nano-bench.png) - -**Key findings:** -- 15% improvement over Jan-Nano-32k on complex multi-document tasks -- Consistent performance across all context lengths (no cliff at 64k like other extended models) -- Superior citation accuracy when handling 10+ sources simultaneously - -## ๐Ÿ–ฅ๏ธ How to Run Locally - -### Demo - - - -### Quick Start Guide - -1. **Download Jan** -2. **Download Jan-Nano-128k** -3. **Enable MCP**, the serper or the exa MCPs work very well with Jan-Nano-128k -4. **Start researching** - -### Usage - -Deploy using VLLM: - -```bash -vllm serve Menlo/Jan-nano-128k \ - --host 0.0.0.0 \ - --port 1234 \ - --enable-auto-tool-choice \ - --tool-call-parser hermes \ - --rope-scaling '{"rope_type":"yarn","factor":3.2,"original_max_position_embeddings":40960}' --max-model-len 131072 -``` - -Or with `llama-server` from `llama.cpp`: - -```bash -llama-server ... --rope-scaling yarn --rope-scale 3.2 --yarn-orig-ctx 40960 -``` - -**Note:** The chat template is included in the tokenizer. For troubleshooting, download the [Non-think chat template](https://qwen.readthedocs.io/en/latest/_downloads/c101120b5bebcc2f12ec504fc93a965e/qwen3_nonthinking.jinja). - -### Recommended Sampling Parameters - -```yaml -Temperature: 0.7 -Top-p: 0.8 -Top-k: 20 -Min-p: 0.0 -``` - -### Hardware Requirements -- **Minimum**: 16GB RAM for Q4 quantization -- **Recommended**: 24GB RAM for Q8 quantization -- **Optimal**: 32GB+ RAM for full precision - -## ๐Ÿค Community & Support -- **Discussions**: [HuggingFace Community](https://huggingface.co/Menlo/Jan-nano-128k/discussions) -- **Issues**: [GitHub Repository](https://github.com/menloresearch/deep-research/issues) -- **Discord**: Join our research community for tips and best practices diff --git a/website/src/content/docs/jan/jan-models/jan-nano-32.mdx b/website/src/content/docs/jan/jan-models/jan-nano-32.mdx deleted file mode 100644 index c50771ec8..000000000 --- a/website/src/content/docs/jan/jan-models/jan-nano-32.mdx +++ /dev/null @@ -1,135 +0,0 @@ ---- -title: Jan Nano 32k -description: Jan-Nano-Gguf Model -keywords: - [ - Jan, - Jan Models, - Jan Model, - Jan Model List, - Menlo Models, - Menlo Model, - Jan-Nano-Gguf, - ReZero, - Model Context Protocol, - MCP, - ] -sidebar: - order: 1 ---- - -import { Aside } from '@astrojs/starlight/components'; - - -## Why Jan Nano? - -Most language models face a fundamental tradeoff where powerful capabilities require a lot of computational resources. Jan -Nano breaks this constraint through a focused design philosophy where instead of trying to know everything, it excels at -knowing how to find anything. - - -## What is Jan Nano? - -Jan Nano is a compact 4-billion parameter language model specifically designed and trained for deep research tasks. -This model has been optimized to work seamlessly with Model Context Protocol (MCP) servers, enabling efficient integration -with various research tools and data sources. - -The model and its different model variants are fully supported by Jan. - - - - -## System Requirements - -- Minimum Requirements: - - 8GB RAM (with iQ4_XS quantization) - - 12GB VRAM (for Q8 quantization) - - CUDA-compatible GPU -- Recommended Setup: - - 16GB+ RAM - - 16GB+ VRAM - - Latest CUDA drivers - - RTX 30/40 series or newer - - -## Using Jan-Nano-32k - -**Step 1** -Download Jan from [here](https://jan.ai/docs/desktop/). - -**Step 2** -Go to the Hub Tab, search for Jan-Nano-Gguf, and click on the download button to the best model size for your system. - -![Jan Nano](../../../../assets/jan-nano1.png) - -**Step 3** -Go to **Settings** > **Model Providers** > **Llama.cpp** click on the pencil icon and enable tool use for Jan-Nano-Gguf. - -**Step 4** -To take advantage of Jan-Nano's full capabilities, you need to enable MCP support. We're going to use it with Serper's -API. You can get a free API key from [here](https://serper.dev/). Sign up and they will immediately generate one for you. - -**Step 5** -Add the serper MCP to Jan via the **Settings** > **MCP Servers** tab. - -![Serper MCP](../../../../assets/serper-mcp.png) - -**Step 6** -Open up a new chat and ask Jan-Nano to search the web for you. - -![Jan Nano](/gifs/jan-nano-demo.gif) - -## Queries to Try - -Here are some example queries to showcase Jan-Nano's web search capabilities: - -1. **Current Events**: What are the latest developments in renewable energy adoption in Germany and Denmark? -2. **International Business**: What is the current status of Tesla's Gigafactory in Berlin and how has it impacted the local economy? -3. **Technology Trends**: What are the newest AI developments from Google, Microsoft, and Meta that were announced this week? -4. **Global Weather**: What's the current weather forecast for Tokyo, Japan for the next 5 days? -5. **Stock Market**: What are the current stock prices for Apple, Samsung, and Huawei, and how have they performed this month? -6. **Sports Updates**: What are the latest results from the Premier League matches played this weekend? -7. **Scientific Research**: What are the most recent findings about climate change impacts in the Arctic region? -8. **Cultural Events**: What major music festivals are happening in Europe this summer and who are the headliners? -9. **Health & Medicine**: What are the latest developments in mRNA vaccine technology and its applications beyond COVID-19? -10. **Space Exploration**: What are the current missions being conducted by NASA, ESA, and China's space program? - - -## FAQ - -- What are the recommended GGUF quantizations? - - Q8 GGUF is recommended for best performance - - iQ4_XS GGUF for very limited VRAM setups - - Avoid Q4_0 and Q4_K_M as they show significant performance degradation - -- Can I run this on a laptop with 8GB RAM? - - Yes, but use the recommended quantizations (iQ4_XS) - - Note that performance may be limited with Q4 quantizations - -- How much did the training cost? - - Training was done on internal A6000 clusters - - Estimated cost on RunPod would be under $100 using H200 - - Hardware used: - - 8xA6000 for training code - - 4xA6000 for vllm server (inferencing) - -- What frontend should I use? - - Jan Beta (recommended) - Minimalistic and polished interface - - Download link: https://jan.ai/docs/desktop/beta - -- Getting Jinja errors in LM Studio? - - Use Qwen3 template from other LM Studio compatible models - - Disable โ€œthinkingโ€ and add the required system prompt - - Fix coming soon in future GGUF releases -- Having model loading issues in Jan? - - Use latest beta version: Jan-beta_0.5.18-rc6-beta - - Ensure proper CUDA support for your GPU - - Check VRAM requirements match your quantization choice - -## Resources - -- [Jan-Nano Model on Hugging Face](https://huggingface.co/Menlo/Jan-nano) -- [Jan-Nano GGUF on Hugging Face](https://huggingface.co/Menlo/Jan-nano-gguf) diff --git a/website/src/content/docs/jan/jan-models/jan-v1.mdx b/website/src/content/docs/jan/jan-models/jan-v1.mdx deleted file mode 100644 index 2aca52a15..000000000 --- a/website/src/content/docs/jan/jan-models/jan-v1.mdx +++ /dev/null @@ -1,121 +0,0 @@ ---- -title: Jan-v1 -description: 4B parameter model with strong performance on reasoning benchmarks -sidebar: - order: 0 - badge: - text: New - variant: tip ---- - -import { Aside } from '@astrojs/starlight/components'; - -## Overview - -Jan-v1 is a 4B parameter model based on Qwen3-4B-thinking, designed for reasoning and problem-solving tasks. The model achieves 91.1% accuracy on SimpleQA through model scaling and fine-tuning approaches. - -## Performance - -### SimpleQA Benchmark - -Jan-v1 demonstrates strong factual question-answering capabilities: - -![Jan-v1 SimpleQA Performance](../../../../assets/simpleqa_jan_v1.png) - -At 91.1% accuracy, Jan-v1 outperforms several larger models on SimpleQA, including Perplexity's 70B model. This performance represents effective scaling and fine-tuning for a 4B parameter model. - -### Chat and Creativity Benchmarks - -Jan-v1 has been evaluated on conversational and creative tasks: - -![Jan-v1 Creativity Benchmarks](../../../../assets/creative_bench_jan_v1.png) - -These benchmarks (EQBench, CreativeWriting, and IFBench) measure the model's ability to handle conversational nuance, creative expression, and instruction following. - -## Requirements - -- **Memory**: - - Minimum: 8GB RAM (with Q4 quantization) - - Recommended: 16GB RAM (with Q8 quantization) -- **Hardware**: CPU or GPU -- **API Support**: OpenAI-compatible at localhost:1337 - -## Using Jan-v1 - -### Quick Start - -1. Download Jan Desktop -2. Select Jan-v1 from the model list -3. Start chatting - no additional configuration needed - -### Demo - -![Jan-v1 Demo](/gifs/jan_v1_demo.gif) - -### Deployment Options - -**Using vLLM:** -```bash -vllm serve janhq/Jan-v1-4B \ - --host 0.0.0.0 \ - --port 1234 \ - --enable-auto-tool-choice \ - --tool-call-parser hermes -``` - -**Using llama.cpp:** -```bash -llama-server --model jan-v1.gguf \ - --host 0.0.0.0 \ - --port 1234 \ - --jinja \ - --no-context-shift -``` - -### Recommended Parameters - -```yaml -temperature: 0.6 -top_p: 0.95 -top_k: 20 -min_p: 0.0 -max_tokens: 2048 -``` - -## What Jan-v1 Does Well - -- **Question Answering**: 91.1% accuracy on SimpleQA -- **Reasoning Tasks**: Built on thinking-optimized base model -- **Tool Calling**: Supports function calling through hermes parser -- **Instruction Following**: Reliable response to user instructions - -## Limitations - -- **Model Size**: 4B parameters limits complex reasoning compared to larger models -- **Specialized Tasks**: Optimized for Q&A and reasoning, not specialized domains -- **Context Window**: Standard context limitations apply - -## Available Formats - -### GGUF Quantizations - -- **Q4_K_M**: 2.5 GB - Good balance of size and quality -- **Q5_K_M**: 2.89 GB - Better quality, slightly larger -- **Q6_K**: 3.31 GB - Near-full quality -- **Q8_0**: 4.28 GB - Highest quality quantization - -## Models Available - -- [Jan-v1 on Hugging Face](https://huggingface.co/janhq/Jan-v1-4B) -- [Jan-v1 GGUF on Hugging Face](https://huggingface.co/janhq/Jan-v1-4B-GGUF) - -## Technical Notes - - - -## Community - -- **Discussions**: [HuggingFace Community](https://huggingface.co/janhq/Jan-v1-4B/discussions) -- **Support**: Available through Jan App at [jan.ai](https://jan.ai) diff --git a/website/src/content/docs/jan/jan-models/lucy.mdx b/website/src/content/docs/jan/jan-models/lucy.mdx deleted file mode 100644 index bb9e9327d..000000000 --- a/website/src/content/docs/jan/jan-models/lucy.mdx +++ /dev/null @@ -1,108 +0,0 @@ ---- -title: Lucy -description: Compact 1.7B model optimized for web search with tool calling ---- - -import { Aside } from '@astrojs/starlight/components'; - - -## Overview - -Lucy is a 1.7B parameter model built on Qwen3-1.7B, optimized for web search through tool calling. The model has been trained to work effectively with search APIs like Serper, enabling web search capabilities in resource-constrained environments. - -## Performance - -Lucy achieves competitive performance on SimpleQA despite its small size: - -![Lucy SimpleQA Performance](../../../../assets/simpleqa_lucy.png) - -The benchmark shows Lucy (1.7B) compared against models ranging from 4B to 600B+ parameters. While larger models generally perform better, Lucy demonstrates that effective web search integration can partially compensate for smaller model size. - -## Requirements - -- **Memory**: - - Minimum: 4GB RAM (with Q4 quantization) - - Recommended: 8GB RAM (with Q8 quantization) -- **Search API**: Serper API key required for web search functionality -- **Hardware**: Runs on CPU or GPU - - - -## Using Lucy - -### Quick Start - -1. Download Jan Desktop -2. Download Lucy from the Hub -3. Configure Serper MCP with your API key -4. Start using web search through natural language - -### Demo - -![Lucy Demo](/gifs/lucy_demo.gif) - -### Deployment Options - -**Using vLLM:** -```bash -vllm serve Menlo/Lucy-128k \ - --host 0.0.0.0 \ - --port 1234 \ - --enable-auto-tool-choice \ - --tool-call-parser hermes \ - --rope-scaling '{"rope_type":"yarn","factor":3.2,"original_max_position_embeddings":40960}' \ - --max-model-len 131072 -``` - -**Using llama.cpp:** -```bash -llama-server model.gguf \ - --host 0.0.0.0 \ - --port 1234 \ - --rope-scaling yarn \ - --rope-scale 3.2 \ - --yarn-orig-ctx 40960 -``` - -### Recommended Parameters - -```yaml -Temperature: 0.7 -Top-p: 0.9 -Top-k: 20 -Min-p: 0.0 -``` - -## What Lucy Does Well - -- **Web Search Integration**: Optimized to call search tools and process results -- **Small Footprint**: 1.7B parameters means lower memory requirements -- **Tool Calling**: Reliable function calling for search APIs - -## Limitations - -- **Requires Internet**: Web search functionality needs active connection -- **API Costs**: Serper API has usage limits and costs -- **Context Processing**: While supporting 128k context, performance may vary with very long inputs -- **General Knowledge**: Limited by 1.7B parameter size for tasks beyond search - -## Models Available - -- [Lucy on Hugging Face](https://huggingface.co/Menlo/Lucy-128k) -- [Lucy GGUF on Hugging Face](https://huggingface.co/Menlo/Lucy-128k-gguf) - -## Citation - -```bibtex -@misc{dao2025lucyedgerunningagenticweb, - title={Lucy: edgerunning agentic web search on mobile with machine generated task vectors}, - author={Alan Dao and Dinh Bach Vu and Alex Nguyen and Norapat Buppodom}, - year={2025}, - eprint={2508.00360}, - archivePrefix={arXiv}, - primaryClass={cs.CL}, - url={https://arxiv.org/abs/2508.00360}, -} -``` diff --git a/website/src/content/docs/jan/manage-models.mdx b/website/src/content/docs/jan/manage-models.mdx deleted file mode 100644 index b85cdc3c4..000000000 --- a/website/src/content/docs/jan/manage-models.mdx +++ /dev/null @@ -1,190 +0,0 @@ ---- -title: Models Overview -description: Manage AI models in Jan - local and cloud options -keywords: - [ - Jan, - AI models, - local models, - cloud models, - GGUF, - Llama.cpp, - model management, - OpenAI, - Anthropic, - model selection, - hardware requirements, - privacy, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -AI models power Jan's conversations. You can run models locally on your device for privacy, or connect to cloud providers for more power. - -## Quick Start - -**New to Jan?** Start with **Jan-v1** (4B) - it runs on most computers -**Limited hardware?** Use cloud models with your API keys -**Privacy focused?** Download any local model - your data never leaves your device - -## Local Models - -Local models are managed through [Llama.cpp](https://github.com/ggerganov/llama.cpp), and these models are in a format called GGUF. When you run them locally, they will use your computer's memory (RAM) and processing power, so please make sure that you download models that match the hardware specifications for your operating system: -- [Mac](/docs/desktop/mac#compatibility) -- [Windows](/docs/desktop/windows#compatibility) -- [Linux](/docs/desktop/linux#compatibility) - -### Adding Local Models - -#### 1. Download from Jan Hub (Recommended) - -The easiest way to get started is using Jan's built-in model hub (connected to [HuggingFace's Model Hub](https://huggingface.co/models)): -1. Go to the **Hub** tab -2. Browse available models and click on any model to see details -3. Choose a model that fits your needs & hardware specifications -4. Click **Download** on your chosen model - - - -![Download Model](../../../assets/model-management-01.png) - -#### 2. Import from Hugging Face - -You can download models with a direct link from Hugging Face: - -**Note:** Some models require a Hugging Face Access Token. Enter your token in **Settings > Model Providers > Hugging Face** before importing. - -1. Visit [Hugging Face Models](https://huggingface.co/models) -2. Find a GGUF model that fits your computer -3. Copy the **model ID** (e.g., TheBloke/Mistral-7B-v0.1-GGUF) -4. In Jan, paste the model ID to the **Search** bar in **Hub** page -5. Select your preferred quantized version to download - -**Copy the model ID:** -![Find HF Model](../../../assets/hf-unsloth.png) - -**Paste it in Jan's Hub Search Bar:** -![Import Model](../../../assets/model-management-02.png) - -#### 3. Import Local Files - -If you already have GGUF model files on your computer: -1. Go to **Settings > Model Providers > Llama.cpp** -2. Click **Import** and select your GGUF file(s) -3. Choose how to import: - - **Link Files:** Creates symbolic links (saves space) - - **Duplicate:** Copies files to Jan's directory -4. Click **Import** to complete - -![Import Settings](../../../assets/model-management-04.png) -![Import Dialog](../../../assets/model-import-04.png) -![Import Options](../../../assets/model-import-05.png) - -#### 4. Manual Setup - -For advanced users who want to add models not available in Jan Hub: - -##### Step 1: Create Model File - -1. Navigate to the [Jan Data Folder](./data-folder) -2. Open `models` folder -3. Create a new folder for your model -4. Add your `model.gguf` file -5. Add a `model.yml` configuration file. Example: - -```yaml -model_path: llamacpp/models/Jan-v1-4B-Q4_K_M/model.gguf -name: Jan-v1-4B-Q4_K_M -size_bytes: 2497281632 -``` - -That's it! Jan now uses a simplified YAML format. All other parameters (temperature, context length, etc.) can be configured directly in the UI when you select the model. - -##### Step 2: Customize in the UI - -Once your model is added: -1. Select it in a chat -2. Click the gear icon next to the model -3. Adjust any parameters you need - - - -### Delete Local Models - -1. Go to **Settings > Model Providers > Llama.cpp** -2. Find the model you want to remove -3. Click the three dots icon and select **Delete Model** - -![Delete Model](../../../assets/model-management-05.png) - -## Cloud Models - -Jan supports connecting to various AI cloud providers through OpenAI-compatible APIs, including OpenAI (GPT-4o, o1), Anthropic (Claude), Groq, Mistral, and more. - - - -### Setting Up Cloud Models - -1. Navigate to **Settings** -2. Under **Model Providers** in the left sidebar, choose your provider -3. Enter your API key -4. Activated cloud models appear in your model selector - -![Cloud Provider Settings](../../../assets/model-management-06.png) - -Once you add your API key, you can select any of that provider's models in the chat interface: - -![Select Cloud Model](../../../assets/quick-start-03.png) - -## Choosing Between Local and Cloud - -### Local Models -**Best for:** -- Privacy-sensitive work -- Offline usage -- Unlimited conversations without costs -- Full control over model behavior - -**Requirements:** -- 8GB RAM minimum (16GB+ recommended) -- 10-50GB storage per model -- CPU or GPU for processing - -### Cloud Models -**Best for:** -- Advanced capabilities (GPT-4, Claude 3) -- Limited hardware -- Occasional use -- Latest model versions - -**Requirements:** -- Internet connection -- API keys from providers -- Usage-based payment - -## Hardware Guidelines - -| RAM | Recommended Model Size | -|-----|----------------------| -| 8GB | 1-3B parameters | -| 16GB | 7B parameters | -| 32GB | 13B parameters | -| 64GB+ | 30B+ parameters | - - - -## Next Steps - -- [Explore Jan Models](./jan-models/jan-v1) - Our optimized models -- [Set up Cloud Providers](./remote-models/openai) - Connect external services -- [Learn Model Parameters](./explanation/model-parameters) - Fine-tune behavior -- [Create AI Assistants](./assistants) - Customize models with instructions diff --git a/website/src/content/docs/jan/mcp-examples/browser/browserbase.mdx b/website/src/content/docs/jan/mcp-examples/browser/browserbase.mdx deleted file mode 100644 index a8963d029..000000000 --- a/website/src/content/docs/jan/mcp-examples/browser/browserbase.mdx +++ /dev/null @@ -1,273 +0,0 @@ ---- -title: Browserbase MCP -description: Control browsers with natural language through Browserbase's cloud infrastructure. -keywords: - [ - Jan, - MCP, - Model Context Protocol, - Browserbase, - browser automation, - web scraping, - Stagehand, - headless browser, - tool calling, - ] ---- - -import { Aside, Steps } from '@astrojs/starlight/components' - -[Browserbase MCP](https://docs.browserbase.com/integrations/mcp/introduction) gives AI models actual browser control through cloud infrastructure. Built on Stagehand, it lets you navigate websites, extract data, and interact with web pages using natural language commands. - -The integration provides real browser sessions that AI can control, enabling tasks that go beyond simple web search APIs. - -## Available Tools - - - -### Multi-Session Tools -- `multi_browserbase_stagehand_session_create`: Create parallel browser sessions -- `multi_browserbase_stagehand_session_list`: Track active sessions -- `multi_browserbase_stagehand_session_close`: Clean up sessions -- `multi_browserbase_stagehand_navigate_session`: Navigate in specific session - -### Core Browser Actions -- `browserbase_stagehand_navigate`: Navigate to URLs -- `browserbase_stagehand_act`: Perform actions ("click the login button") -- `browserbase_stagehand_extract`: Extract text content -- `browserbase_stagehand_observe`: Find page elements -- `browserbase_screenshot`: Capture screenshots - -### Session Management -- `browserbase_session_create`: Create or reuse sessions -- `browserbase_session_close`: Close active sessions - -## Prerequisites - -- Jan with MCP enabled -- Browserbase account (includes 60 minutes free usage) -- Model with strong tool calling support -- Node.js installed - - - -## Setup - -### Enable MCP - -1. Go to **Settings** > **MCP Servers** -2. Toggle **Allow All MCP Tool Permission** ON - -![MCP settings page with toggle enabled](../../../../../assets/mcp-on.png) - -### Get Browserbase Credentials - -1. Sign up at [browserbase.com](https://browserbase.com) - - Email verification required - - Phone number authentication - - Thorough security process - -2. Access your dashboard and copy: - - **API Key** - - **Project ID** - -![Browserbase dashboard showing API key and project ID](../../../../../assets/browserbase.png) - -### Configure MCP Server - -Click `+` in MCP Servers section: - -**NPM Package Configuration:** -- **Server Name**: `browserbase` -- **Command**: `npx` -- **Arguments**: `@browserbasehq/mcp-server-browserbase` -- **Environment Variables**: - - Key: `BROWSERBASE_API_KEY`, Value: `your-api-key` - - Key: `BROWSERBASE_PROJECT_ID`, Value: `your-project-id` - -![Jan MCP server configuration with Browserbase settings](../../../../../assets/browserbase3.png) - -### Verify Setup - -Check the tools bubble in chat to confirm Browserbase tools are available: - -![Chat interface showing available Browserbase tools](../../../../../assets/browserbase2.png) - -## Real Usage Example - -### Live Information Query - -``` -Which sports matches are happening right now in Australia (irrespective of the sport)? -``` - -This simple query demonstrates browser automation in action: - -1. **Tool Activation** - - Model creates browser session - - Navigates to sports websites - - Extracts current match data - -![Model using browser tools to search for information](../../../../../assets/browserbase5.png) - -2. **Results Delivery** - - Real-time match information - - Multiple sports covered - - Current scores and timings - -![Final response with Australian sports matches](../../../../../assets/browserbase6.png) - -The AI successfully found: -- AFL matches with live scores -- NRL games in progress -- Upcoming Rugby Union fixtures - -## Common Issues - -### Tool Call Failures - -Sometimes tool calls fail due to parsing issues: - -![Tool call error showing parsing problem](../../../../../assets/browserbase7.png) - -**Solutions:** -- Try rephrasing your prompt -- Disable unnecessary tools -- Use simpler, more direct requests -- Switch to Claude 3.5+ Sonnet if using another model - -### Model Limitations - -Most models struggle with multiple tools. If experiencing issues: -- Start with single-purpose requests -- Build complexity gradually -- Consider which tools are actually needed -- Expect some trial and error initially - -## Usage Limits - -**Free Tier:** -- 60 minutes of browser time included -- Sessions auto-terminate after 5 minutes inactivity -- Can adjust timeout in Browserbase dashboard -- Usage visible in dashboard analytics - -**Session Management:** -- Each browser session counts against time -- Close sessions when done to conserve minutes -- Multi-session operations consume time faster - -## Practical Use Cases - -### Real-Time Data Collection -``` -Check current prices for MacBook Pro M4 at major Australian retailers and create a comparison table. -``` - -### Form Testing -``` -Navigate to myservice.gov.au and walk through the Medicare claim process, documenting each required field. -``` - -### Content Monitoring -``` -Visit ABC News Australia and extract the top 5 breaking news headlines with their timestamps. -``` - -### Multi-Site Analysis -``` -Compare flight prices from Sydney to Tokyo next week across Qantas, Jetstar, and Virgin Australia. -``` - -### Automated Verification -``` -Check if our company is listed correctly on Google Maps, Yelp, and Yellow Pages, noting any discrepancies. -``` - -## Advanced Techniques - -### Session Reuse -``` -Create a browser session, log into LinkedIn, then search for "AI engineers in Melbourne" and extract the first 10 profiles. -``` - -### Parallel Operations -``` -Create three browser sessions: monitor stock prices on ASX, check crypto on CoinSpot, and track forex on XE simultaneously. -``` - -### Sequential Workflows -``` -Go to seek.com.au, search for "data scientist" jobs in Sydney, apply filters for $150k+, then extract job titles and companies. -``` - -## Optimization Tips - -**Prompt Engineering:** -- Be specific about what to extract -- Name exact websites when possible -- Break complex tasks into steps -- Specify output format clearly - -**Tool Selection:** -- Use multi-session only when needed -- Close sessions promptly -- Choose observe before act when possible -- Screenshot sparingly to save time - -**Error Recovery:** -- Have fallback prompts ready -- Start simple, add complexity -- Watch for timeout warnings -- Monitor usage in dashboard - -## Troubleshooting - -**Connection Issues:** -- Verify API key and Project ID -- Check Browserbase service status -- Ensure NPX can download packages -- Restart Jan after configuration - -**Browser Failures:** -- Some sites block automation -- Try different navigation paths -- Check if site requires login -- Verify target site is accessible - -**Performance Problems:** -- Reduce concurrent sessions -- Simplify extraction requests -- Check remaining time quota -- Consider upgrading plan - -**Model Struggles:** -- Too many tools overwhelm most models -- Claude 3.5+ Sonnet most reliable -- Reduce available tools if needed -- Use focused, clear instructions - - - -## Browserbase vs Browser Use - -| Feature | Browserbase | Browser Use | -|---------|-------------|-------------| -| **Infrastructure** | Cloud browsers | Local browser | -| **Setup Complexity** | API key only | Python environment | -| **Performance** | Consistent | System dependent | -| **Cost** | Usage-based | Free (local resources) | -| **Reliability** | High | Variable | -| **Privacy** | Cloud-based | Fully local | - -## Next Steps - -Browserbase MCP provides genuine browser automation capabilities, not just web search. This enables complex workflows like form filling, multi-site monitoring, and data extraction that would be impossible with traditional APIs. - -The cloud infrastructure handles browser complexity while Jan maintains conversational privacy. Just remember: with great browser power comes occasional parsing errors. diff --git a/website/src/content/docs/jan/mcp-examples/data-analysis/e2b.mdx b/website/src/content/docs/jan/mcp-examples/data-analysis/e2b.mdx deleted file mode 100644 index 1c1bfcf7d..000000000 --- a/website/src/content/docs/jan/mcp-examples/data-analysis/e2b.mdx +++ /dev/null @@ -1,284 +0,0 @@ ---- -title: E2B Code Sandbox -description: Execute Python code securely in isolated sandbox environments with E2B. -keywords: - [ - Jan, - MCP, - Model Context Protocol, - E2B, - code execution, - sandbox, - data analysis, - Python, - secure computing, - tool calling, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -E2B MCP provides isolated Python execution environments. Your AI can run actual code instead of just describing what code might do. - -The real value emerges when you combine secure remote execution with Jan's flexible model selection. You can use -local models for conversation and reasoning while offloading actual computation to E2B's sandboxes. This means you -get the privacy and control of local models plus the computational power of cloud infrastructure, without the -complexity of managing Python environments or dependencies locally. - -## Setup - -### Prerequisites - -- Jan with MCP enabled -- E2B API key from [e2b.dev](https://e2b.dev/) -- Node.js installed -- Model with tool calling support - -### Configuration - -1. **Enable MCP**: Go to **Settings** > **MCP Servers**, toggle **Allow All MCP Tool Permission** ON - -![Turn on MCP](../../../../../assets/mcp-on.png) - -2. **Get API Key**: Sign up at [e2b.dev](https://e2b.dev/), generate an API key - -![E2B API Key](../../../../../assets/e2b-key.png) - -Add a meaningful name to your key. - -![E2B MCP Server](../../../../../assets/e2b-key1.png) - -3. **Add MCP Server**: Click `+` in MCP Servers section - -Configure: -- **Server Name**: `e2b-server` -- **Command**: `npx` -- **Arguments**: `@e2b/mcp-server` -- **Environment Variables**: - - Key: `E2B_API_KEY` - - Value: `your-api-key` - -![E2B MCP Server](../../../../../assets/e2b-key2.png) - -4. **Verify**: Check server shows as active - - -![E2B MCP Server](../../../../../assets/e2b-key3.png) - -## Pre-installed Libraries - -The sandbox includes these packages by default: - -**Data Analysis & Science:** -- `pandas` (1.5.3) - Data manipulation -- `numpy` (1.26.4) - Numerical computing -- `scipy` (1.12.0) - Scientific computing -- `scikit-learn` (1.4.1) - Machine learning -- `sympy` (1.12) - Symbolic mathematics - -**Visualization:** -- `matplotlib` (3.8.3) - Static plots -- `seaborn` (0.13.2) - Statistical visualization -- `plotly` (5.19.0) - Interactive charts -- `bokeh` (3.3.4) - Web-ready visualizations - -**Data Processing:** -- `requests` (2.26.0) - HTTP requests -- `beautifulsoup4` (4.12.3) - HTML/XML parsing -- `openpyxl` (3.1.2) - Excel files -- `python-docx` (1.1.0) - Word documents - -**Text & NLP:** -- `nltk` (3.8.1) - Natural language processing -- `spacy` (3.7.4) - Advanced NLP -- `textblob` (0.18.0) - Text processing -- `gensim` (4.3.2) - Topic modeling - -**Image & Audio:** -- `opencv-python` (4.9.0) - Computer vision -- `scikit-image` (0.22.0) - Image processing -- `imageio` (2.34.0) - Image I/O -- `librosa` (0.10.1) - Audio analysis - -Additional packages can be installed as needed. - -## Examples - - -For the following examples, we'll use Claude 4 Sonnet but you can use any local or remote -model with tool calling capabilities you'd like. - - - -![E2B MCP Server](../../../../../assets/e2b-key4.png) - -### Basic Data Analysis - -Start small. Open a new chat, confirm that the model has tools enabled and ask it to create a small dataset of 100 students with grades and study hours. - -![Chat and use E2B MCP ](../../../../../assets/e2b-key5.png) - - -``` -Create a small dataset of 100 students with grades and study hours. -Calculate the correlation and create a scatter plot. -``` - -The model will: -1. Generate data with pandas (100 rows) -2. Calculate correlation coefficient -3. Create a matplotlib scatter plot -4. Add trend line - - -![Chat and use E2B MCP ](../../../../../assets/e2b-key6.png) - -![Chat and use E2B MCP ](../../../../../assets/e2b-key7.png) - - - - - -### Statistical Computing - -``` -Run a Monte Carlo simulation with 10,000 iterations to estimate ฯ€. -``` - -Expected output: -- Numerical computation with numpy -- Convergence plot showing estimate improvement -- Final ฯ€ estimate - - -For more intensive simulations, increase iterations gradually and monitor performance. - -### Machine Learning - -``` -Create a simple 2-class dataset with 200 samples. Train a logistic regression -model and visualize the decision boundary. -``` - -The model will: -- Generate synthetic 2D classification data -- Train a single scikit-learn model -- Plot data points and decision boundary - - -### Time Series Analysis - -``` -Generate daily temperature data for one year. Calculate moving averages -and identify seasonal patterns. -``` - -Output includes: -- Line plot of temperature data -- Moving average overlay -- Simple seasonal decomposition - - -### Scaling Up - -Once basic examples work, you can increase complexity: -- Larger datasets (1000+ samples) -- Multiple models for comparison -- Complex visualizations with subplots -- Advanced statistical tests - -The sandbox handles moderate computational loads well. For very large datasets or intensive ML training, consider breaking work into smaller chunks. - -## Chart Generation - -E2B automatically detects and extracts charts from matplotlib code. Charts are returned as base64-encoded images and downloadable files. - -### Static Charts - -```python -import matplotlib.pyplot as plt -import numpy as np - -x = np.linspace(0, 10, 100) -y = np.sin(x) - -plt.figure(figsize=(10, 6)) -plt.plot(x, y) -plt.title('Sine Wave') -plt.xlabel('x') -plt.ylabel('sin(x)') -plt.show() -``` - -E2B captures the plot and makes it available for download. - -### Interactive Charts - -The system extracts chart data for frontend visualization: - -```python -plt.bar(['A', 'B', 'C'], [10, 20, 15]) -plt.title('Sample Bar Chart') -plt.show() -``` - -Returns structured data: -```json -{ - "type": "bar", - "title": "Sample Bar Chart", - "elements": [ - {"label": "A", "value": 10}, - {"label": "B", "value": 20}, - {"label": "C", "value": 15} - ] -} -``` - -Supported chart types: line, bar, scatter, pie, box plots. - -## Available Tools - -- **run_code**: Execute Python code -- **install_package**: Add Python packages -- **create_file**: Save files to sandbox -- **read_file**: Access sandbox files -- **list_files**: Browse sandbox contents - -## Troubleshooting - -**Connection Issues:** -- Verify API key is correct -- Check Node.js installation -- Restart Jan if server won't start - -**Execution Problems:** -- Free sandboxes have 2 cores and 1GB RAM - start with small datasets -- Large computations may time out or run out of memory -- Scale up complexity gradually after testing basic examples -- Some packages may require explicit installation - -**Package Installation:** -- Most data science packages install successfully -- System dependencies may cause failures for some packages -- Try alternative packages if installation fails - - - -## Use Cases - -E2B is useful for: - -- **Academic Research**: Statistical analysis, data visualization, hypothesis testing -- **Data Science**: Exploratory data analysis, model prototyping, result validation -- **Financial Analysis**: Portfolio optimization, risk calculations, market simulations -- **Scientific Computing**: Numerical simulations, mathematical modeling, algorithm testing -- **Prototyping**: Quick algorithm validation, proof-of-concept development - -The sandbox provides isolated execution without local environment setup or dependency management. diff --git a/website/src/content/docs/jan/mcp-examples/data-analysis/jupyter.mdx b/website/src/content/docs/jan/mcp-examples/data-analysis/jupyter.mdx deleted file mode 100644 index 64536b9cb..000000000 --- a/website/src/content/docs/jan/mcp-examples/data-analysis/jupyter.mdx +++ /dev/null @@ -1,335 +0,0 @@ ---- -title: Jupyter MCP -description: Real-time Jupyter notebook interaction and code execution through MCP integration. -keywords: - [ - Jan, - MCP, - Model Context Protocol, - Jupyter, - data analysis, - code execution, - notebooks, - Python, - visualization, - tool calling, - GPT-5, - OpenAI, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -[Jupyter MCP Server](https://jupyter-mcp-server.datalayer.tech/) enables real-time interaction with Jupyter notebooks, allowing AI models to edit, execute, and document code for data analysis and visualization. Instead of just generating code suggestions, AI can actually run Python code and see the results. - -This integration gives Jan the ability to execute analysis, create visualizations, and iterate based on actual results - turning your AI assistant into a capable data science partner. - - - -## Available Tools - -The Jupyter MCP Server provides [12 comprehensive tools](https://jupyter-mcp-server.datalayer.tech/tools/): - -### Core Operations -- `append_execute_code_cell`: Add and run code cells at notebook end -- `insert_execute_code_cell`: Insert and run code at specific positions -- `execute_cell_simple_timeout`: Execute cells with timeout control -- `execute_cell_streaming`: Long-running cells with progress updates -- `execute_cell_with_progress`: Execute with timeout and monitoring - -### Cell Management -- `append_markdown_cell`: Add documentation cells -- `insert_markdown_cell`: Insert markdown at specific positions -- `delete_cell`: Remove cells from notebook -- `overwrite_cell_source`: Update existing cell content - -### Information & Reading -- `get_notebook_info`: Retrieve notebook metadata -- `read_cell`: Examine specific cell content -- `read_all_cells`: Get complete notebook state - - - -## Prerequisites - -- Jan with MCP enabled -- Python 3.8+ with uv package manager -- Docker installed -- OpenAI API key for GPT-5 access -- Basic understanding of Jupyter notebooks - -## Setup - -### Enable MCP - -1. Go to **Settings** > **MCP Servers** -2. Toggle **Allow All MCP Tool Permission** ON - -![MCP settings page with toggle enabled](../../../../../assets/mcp-on.png) - -### Install uv Package Manager - -If you don't have uv installed: - -```bash -# macOS and Linux -curl -LsSf https://astral.sh/uv/install.sh | sh - -# Windows -powershell -c "irm https://astral.sh/uv/install.ps1 | iex" -``` - -### Create Python Environment - -Set up an isolated environment for Jupyter: - -```bash -# Create environment with Python 3.13 -uv venv .venv --python 3.13 - -# Activate environment -source .venv/bin/activate # Linux/macOS -# or -.venv\Scripts\activate # Windows - -# Install Jupyter dependencies -uv pip install jupyterlab==4.4.1 jupyter-collaboration==4.0.2 ipykernel -uv pip uninstall pycrdt datalayer_pycrdt -uv pip install datalayer_pycrdt==0.12.17 - -# Add data science libraries -uv pip install pandas numpy matplotlib altair -``` - -### Start JupyterLab Server - -Launch JupyterLab with authentication: - -```bash -jupyter lab --port 8888 --IdentityProvider.token heyheyyou --ip 0.0.0.0 -``` - -![Terminal showing JupyterLab startup](../../../../../assets/jupyter1.png) - -The server opens in your browser: - -![JupyterLab interface in browser](../../../../../assets/jupyter.png) - -### Create Target Notebook - -Create a new notebook named `for_jan.ipynb`: - -![Notebook created in JupyterLab](../../../../../assets/jupyter2.png) - -### Configure MCP Server in Jan - -Click `+` in MCP Servers section: - -**Configuration for macOS/Windows:** -- **Server Name**: `jupyter` -- **Command**: `docker` -- **Arguments**: - ``` - run -i --rm -e DOCUMENT_URL -e DOCUMENT_TOKEN -e DOCUMENT_ID -e RUNTIME_URL -e RUNTIME_TOKEN datalayer/jupyter-mcp-server:latest - ``` -- **Environment Variables**: - - Key: `DOCUMENT_URL`, Value: `http://host.docker.internal:8888` - - Key: `DOCUMENT_TOKEN`, Value: `heyheyyou` - - Key: `DOCUMENT_ID`, Value: `for_jan.ipynb` - - Key: `RUNTIME_URL`, Value: `http://host.docker.internal:8888` - - Key: `RUNTIME_TOKEN`, Value: `heyheyyou` - -![Jan MCP server configuration](../../../../../assets/jupyter3.png) - -## Using OpenAI's GPT-5 - -### Configure OpenAI Provider - -Navigate to **Settings** > **Model Providers** > **OpenAI**: - -![OpenAI settings page](../../../../../assets/openai-settings.png) - -### Add GPT-5 Model - -Since GPT-5 is new, you'll need to manually add it to Jan: - -![Manually adding GPT-5 model name](../../../../../assets/gpt5-add.png) - - - -### Enable Tool Calling - -Ensure tools are enabled for GPT-5: - -![Enabling tools for GPT-5](../../../../../assets/gpt5-tools.png) - -## Usage - -### Verify Tool Availability - -Start a new chat with GPT-5. The tools bubble shows all available Jupyter operations: - -![GPT-5 ready in chat with Jupyter tools visible](../../../../../assets/gpt5-chat.png) - -### Initial Test - -Start with establishing the notebook as your workspace: - -``` -You have access to a jupyter notebook, please use it as our data analysis scratchpad. Let's start by printing "Hello Jan" in a new cell. -``` - -GPT-5 creates and executes the code successfully: - -![First message showing successful tool use](../../../../../assets/gpt5-msg.png) - -### Advanced Data Analysis - -Try a more complex task combining multiple operations: - -``` -Generate synthetic data with numpy, move it to a pandas dataframe and create a pivot table, and then make a cool animated plot using matplotlib. Your use case will be sales analysis in the luxury fashion industry. -``` - -![Complex analysis with luxury fashion sales data](../../../../../assets/gpt5-msg2.png) - -Watch the complete output unfold: - - - -## Example Prompts to Try - -### Financial Analysis -``` -Create a Monte Carlo simulation for portfolio risk analysis. Generate 10,000 scenarios, calculate VaR at 95% confidence, and visualize the distribution. -``` - -### Time Series Forecasting -``` -Generate synthetic time series data representing daily website traffic over 2 years with weekly seasonality and trend. Build an ARIMA model and forecast the next 30 days. -``` - -### Machine Learning Pipeline -``` -Build a complete classification pipeline: generate a dataset with 3 classes and 5 features, split the data, try multiple algorithms (RF, SVM, XGBoost), and create a comparison chart of their performance. -``` - -### Interactive Dashboards -``` -Create an interactive visualization using matplotlib widgets showing how changing interest rates affects loan payments over different time periods. -``` - -### Statistical Testing -``` -Generate two datasets representing A/B test results for an e-commerce site. Perform appropriate statistical tests and create visualizations to determine if the difference is significant. -``` - -## Performance Considerations - - - -### Context Management -- Each tool call adds to conversation history -- 12 available tools means substantial system prompt overhead -- Local models may need reduced tool sets for reasonable performance -- Consider disabling unused tools to conserve context - -### Cloud vs Local Trade-offs -- **Cloud models (GPT-5)**: Handle multiple tools efficiently with large context windows -- **Local models**: May require optimization, reduced tool sets, or smaller context sizes -- **Hybrid approach**: Use cloud for complex multi-tool workflows, local for simple tasks - -## Security Considerations - - - -### Authentication Tokens -- **Always use strong tokens** - avoid simple passwords -- **Never commit tokens** to version control -- **Rotate tokens regularly** for production use -- **Use different tokens** for different environments - -### Network Security -- JupyterLab is network-accessible with `--ip 0.0.0.0` -- Consider using `--ip 127.0.0.1` for local-only access -- Implement firewall rules to restrict access -- Use HTTPS in production environments - -### Code Execution Risks -- AI has full Python execution capabilities -- Review generated code before execution -- Use isolated environments for sensitive work -- Monitor resource usage and set limits - -### Data Privacy -- Notebook content is processed by AI models -- When using cloud models like GPT-5, data leaves your system -- Keep sensitive data in secure environments -- Consider model provider's data policies - -## Best Practices - -### Environment Management -- Use virtual environments for isolation -- Document required dependencies -- Version control your notebooks -- Regular environment cleanup - -### Performance Optimization -- Start with simple operations -- Monitor memory usage during execution -- Close unused notebooks -- Restart kernels when needed - -### Effective Prompting -- Be specific about desired outputs -- Break complex tasks into steps -- Ask for explanations with code -- Request error handling in critical operations - -## Troubleshooting - -**Connection Problems:** -- Verify JupyterLab is running -- Check token matches configuration -- Confirm Docker can reach host -- Test with curl to verify connectivity - -**Execution Failures:** -- Check Python package availability -- Verify kernel is running -- Look for syntax errors in generated code -- Restart kernel if stuck - -**Tool Calling Errors:** -- Ensure model supports tool calling -- Verify all 12 tools appear in chat -- Check MCP server is active -- Review Docker logs for errors - -**API Rate Limits:** -- Monitor OpenAI usage dashboard -- Implement retry logic for transient errors -- Consider fallback to local models -- Cache results when possible - -## Conclusion - -The Jupyter MCP integration combined with GPT-5's advanced capabilities creates an exceptionally powerful data science environment. With GPT-5's built-in reasoning and expert-level intelligence, complex analyses that once required extensive manual coding can now be accomplished through natural conversation. - -Whether you're exploring data, building models, or creating visualizations, this integration provides the computational power of Jupyter with the intelligence of GPT-5 - all within Jan's privacy-conscious interface. - -Remember: with great computational power comes the responsibility to use it securely. Always validate generated code, use strong authentication, and be mindful of data privacy when using cloud-based models. diff --git a/website/src/content/docs/jan/mcp-examples/deepresearch/octagon.mdx b/website/src/content/docs/jan/mcp-examples/deepresearch/octagon.mdx deleted file mode 100644 index aba5cc9d9..000000000 --- a/website/src/content/docs/jan/mcp-examples/deepresearch/octagon.mdx +++ /dev/null @@ -1,259 +0,0 @@ ---- -title: Octagon Deep Research MCP -description: Finance-focused deep research with AI-powered analysis through Octagon's MCP integration. -keywords: - [ - Jan, - MCP, - Model Context Protocol, - Octagon, - deep research, - financial research, - private equity, - market analysis, - technical research, - tool calling, - ] ---- - -import { Aside, Steps } from '@astrojs/starlight/components' - - -[Octagon Deep Research MCP](https://docs.octagonagents.com/guide/deep-research-mcp.html) provides specialized AI research capabilities with a strong focus on financial markets and business intelligence. Unlike general research tools, Octagon excels at complex financial analysis, market dynamics, and investment research. - -The integration delivers comprehensive reports that combine multiple data sources, cross-verification, and actionable insights - particularly useful for understanding market structures, investment strategies, and business models. - -## Available Tools - -### octagon-agent -Orchestrates comprehensive market intelligence research, particularly strong in: -- Financial market analysis -- Private equity and M&A research -- Corporate structure investigations -- Investment strategy evaluation - -### octagon-scraper-agent -Specialized web scraping for public and private market data: -- SEC filings and regulatory documents -- Company financials and metrics -- Market transaction data -- Industry reports and analysis - -### octagon-deep-research-agent -Comprehensive research synthesis combining: -- Multi-source data aggregation -- Cross-verification of claims -- Historical trend analysis -- Actionable insights generation - -## Prerequisites - -- Jan with MCP enabled -- Octagon account (includes 2-week Pro trial) -- Model with tool calling support -- Node.js installed - - - -## Setup - -### Enable MCP - -1. Go to **Settings** > **MCP Servers** -2. Toggle **Allow All MCP Tool Permission** ON - -![MCP settings page with toggle enabled](../../../../../assets/mcp-on.png) - -### Get Octagon API Key - -1. Sign up at [Octagon signup page](https://app.octagonai.co/signup/?redirectToAfterSignup=https://app.octagonai.co/api-keys) -2. Navigate to the API playground -3. Copy your API key from the dashboard - -![Octagon API playground showing API key location](../../../../../assets/octagon2.png) - -### Configure MCP Server - -Click `+` in MCP Servers section: - -**NPM Package Configuration:** -- **Server Name**: `octagon-mcp-server` -- **Command**: `npx` -- **Arguments**: `-y octagon-mcp@latest` -- **Environment Variables**: - - Key: `OCTAGON_API_KEY`, Value: `your-api-key` - -![Jan MCP server configuration with Octagon settings](../../../../../assets/octagon3.png) - -### Verify Setup - -Check the tools bubble in chat to confirm Octagon tools are available: - -![Chat interface showing available Octagon tools with moonshotai/kimi-k2 model](../../../../../assets/octagon4.png) - -## Real-World Example: Private Equity Analysis - -Here's an actual deep research query demonstrating Octagon's financial analysis capabilities: - -### The Prompt - -``` -Break apart the private equity paradox: How did an industry that promises to "unlock value" become synonymous with gutting companies, yet still attracts the world's smartest money? - -Start with the mechanicsโ€”how PE firms use other people's money to buy companies with borrowed cash, then charge fees for the privilege. Trace the evolution from corporate raiders of the 1980s to today's trillion-dollar titans like Blackstone, KKR, and Apollo. Use SEC filings, M&A databases, and bankruptcy records to map their empires. - -Dig into specific deals that illustrate the dual nature: companies genuinely transformed versus those stripped and flipped. Compare Toys "R" Us's death to Hilton's resurrection. Examine how PE-owned companies fare during economic downturnsโ€”do they really have "patient capital" or do they bleed portfolio companies dry through dividend recaps? - -Investigate the fee structure that makes partners billionaires regardless of performance. Calculate the real returns after the 2-and-20 (or worse) fee structures. Why do pension funds and endowments keep pouring money in despite academic studies showing they'd do better in index funds? - -Explore the revolving door between PE, government, and central banks. How many Fed officials and Treasury secretaries came from or went to PE? Map the political donations and lobbying expenditures that keep carried interest taxed as capital gains. - -Address the human cost through labor statistics and case studiesโ€”what happens to employees when PE takes over? But also examine when PE genuinely saves failing companies and preserves jobs. - -Write this as if explaining to a skeptical but curious friend over drinksโ€”clear language, no jargon without explanation, and enough dry humor to make the absurdities apparent. Think Michael Lewis meets Matt Levine. Keep it under 3,000 words but pack it with hard data and real examples. The goal: help readers understand why PE is simultaneously capitalism's most sophisticated expression and its most primitive. -``` - -![Prompt entered in Jan UI](../../../../../assets/octagon5.png) - -### Research Process - -The AI engages multiple Octagon tools to gather comprehensive data: - -![Kimi model using Octagon tools for research](../../../../../assets/octagon6.png) - -### The Results - -Octagon delivers a detailed analysis covering: - -**Part 1: The Mechanics Explained** -![First part of the research report](../../../../../assets/octagon7.png) - -**Part 2: Historical Analysis and Case Studies** -![Second part showing PE evolution and specific deals](../../../../../assets/octagon8.png) - -**Part 3: Financial Engineering and Human Impact** -![Final section on fee structures and consequences](../../../../../assets/octagon9.png) - -The report demonstrates Octagon's ability to: -- Access and analyze SEC filings -- Compare multiple deal outcomes -- Calculate real returns after fees -- Track political connections -- Assess human impact with data - -## Finance-Focused Use Cases - -### Investment Research -``` -Analyze Tesla's vertical integration strategy vs traditional automakers. Include supply chain dependencies, margin analysis, and capital efficiency metrics from the last 5 years. -``` - -### Market Structure Analysis -``` -Map the concentration of market makers in US equities. Who controls order flow, what are their profit margins, and how has this changed since zero-commission trading? -``` - -### Corporate Governance -``` -Investigate executive compensation at the 10 largest US banks post-2008. Compare pay ratios, stock buybacks vs R&D spending, and correlation with shareholder returns. -``` - -### Private Market Intelligence -``` -Track Series B+ funding rounds in AI/ML companies in 2024. Identify valuation trends, investor concentration, and compare to public market multiples. -``` - -### Regulatory Analysis -``` -Examine how Basel III implementation differs across major markets. Which banks gained competitive advantages and why? -``` - -### M&A Strategy -``` -Analyze Microsoft's acquisition strategy under Nadella. Calculate actual vs projected synergies, integration success rates, and impact on market position. -``` - -## Technical Research Capabilities - -While finance-focused, Octagon also handles technical research: - -### Framework Evaluation -``` -Compare Kubernetes alternatives for edge computing. Consider resource usage, latency, reliability, and operational complexity with real deployment data. -``` - -### API Economics -``` -Analyze the unit economics of major AI API providers. Include pricing history, usage patterns, and margin estimates based on reported compute costs. -``` - -### Open Source Sustainability -``` -Research funding models for critical open source infrastructure. Which projects are at risk and what are the economic incentives misalignments? -``` - -## Research Quality - -Octagon's reports typically include: -- **Primary Sources**: SEC filings, earnings calls, regulatory documents -- **Quantitative Analysis**: Financial metrics, ratios, trend analysis -- **Comparative Studies**: Peer benchmarking, historical context -- **Narrative Clarity**: Complex topics explained accessibly -- **Actionable Insights**: Not just data, but implications - -## Troubleshooting - -**Authentication Issues:** -- Verify API key from Octagon dashboard -- Check trial status hasn't expired -- Ensure correct API key format -- Contact Octagon support if needed - -**Research Failures:** -- Some queries may exceed scope (try narrowing) -- Financial data may have access restrictions -- Break complex queries into parts -- Allow time for comprehensive research - -**Tool Calling Problems:** -- Not all models handle multiple tools well -- Kimi-k2 via OpenRouter works reliably -- Claude 3.5+ Sonnet also recommended -- Enable tool calling in model settings - -**Performance Considerations:** -- Deep research takes time (be patient) -- Complex financial analysis may take minutes -- Monitor API usage in dashboard -- Consider query complexity vs urgency - - - -## Pricing After Trial - -After the 2-week Pro trial: -- Check current pricing at octagonagents.com -- Usage-based pricing for API access -- Different tiers for research depth -- Educational discounts may be available - -## Octagon vs Other Research Tools - -| Feature | Octagon | ChatGPT Deep Research | Perplexity | -|---------|---------|----------------------|------------| -| **Finance Focus** | Specialized | General | General | -| **Data Sources** | Financial databases | Web-wide | Web-wide | -| **SEC Integration** | Native | Limited | Limited | -| **Market Data** | Comprehensive | Basic | Basic | -| **Research Depth** | Very Deep | Deep | Moderate | -| **Speed** | Moderate | Slow | Fast | - -## Next Steps - -Octagon Deep Research MCP excels at complex financial analysis that would typically require a team of analysts. The integration provides institutional-quality research capabilities within Jan's conversational interface. - -Whether analyzing market structures, evaluating investments, or understanding business models, Octagon delivers the depth and accuracy that financial professionals expect, while maintaining readability for broader audiences. diff --git a/website/src/content/docs/jan/mcp-examples/design/canva.mdx b/website/src/content/docs/jan/mcp-examples/design/canva.mdx deleted file mode 100644 index 008bff70f..000000000 --- a/website/src/content/docs/jan/mcp-examples/design/canva.mdx +++ /dev/null @@ -1,279 +0,0 @@ ---- -title: Canva MCP -description: Create and manage designs through natural language commands with Canva's official MCP server. -keywords: - [ - Jan, - MCP, - Model Context Protocol, - Canva, - design automation, - graphic design, - presentations, - templates, - tool calling, - ] ---- - -import { Aside, Steps } from '@astrojs/starlight/components' - -[Canva MCP](https://www.canva.com/newsroom/news/deep-research-integration-mcp-server/) gives AI models the ability to create, search, and manage designs directly within Canva. As the first design platform with native MCP integration, it lets you generate presentations, logos, and marketing materials through conversation rather than clicking through design interfaces. - -The integration provides comprehensive design capabilities without leaving your chat, though actual editing still happens in Canva's interface. - -## Available Tools - - - -### Design Operations -- **generate-design**: Create new designs using AI prompts -- **search-designs**: Search docs, presentations, videos, whiteboards -- **get-design**: Get detailed information about a Canva design -- **get-design-pages**: List pages in multi-page designs -- **get-design-content**: Extract content from designs -- **resize-design**: Adapt designs to different dimensions -- **get-design-resize-status**: Check resize operation status -- **get-design-generation-job**: Track AI generation progress - -### Import/Export -- **import-design-from-url**: Import files from URLs as new designs -- **get-design-import-from-url**: Check import status -- **export-design**: Export designs in various formats -- **get-export-formats**: List available export options -- **get-design-export-status**: Track export progress - -### Organization -- **create-folder**: Create folders in Canva -- **move-item-to-folder**: Organize designs and assets -- **list-folder-items**: Browse folder contents - -### Collaboration -- **comment-on-design**: Add comments to designs -- **list-comments**: View design comments -- **list-replies**: See comment threads -- **reply-to-comment**: Respond to feedback - -### Legacy Tools -- **search**: ChatGPT connector (use search-designs instead) -- **fetch**: Content retrieval for ChatGPT - -## Prerequisites - -- Jan with MCP enabled -- Canva account (free or paid) -- Model with tool calling support -- Node.js installed -- Internet connection for Canva API access - -## Setup - -### Enable MCP - -1. Go to **Settings** > **MCP Servers** -2. Toggle **Allow All MCP Tool Permission** ON - -![MCP settings page with toggle enabled](../../../../../assets/mcp-on.png) - -### Configure Canva MCP Server - -Click `+` in MCP Servers section: - -**Configuration:** -- **Server Name**: `Canva` -- **Command**: `npx` -- **Arguments**: `-y mcp-remote@latest https://mcp.canva.com/mcp` -- **Environment Variables**: Leave empty (authentication handled via OAuth) - -![Canva MCP server configuration in Jan](../../../../../assets/canva.png) - -### Authentication Process - -When you first use Canva tools: - -1. **Browser Opens Automatically** - - Canva authentication page appears in your default browser - - Log in with your Canva account - -![Canva authentication page](../../../../../assets/canva2.png) - -2. **Team Selection & Permissions** - - Select your team (if you have multiple) - - Review permissions the AI will have - - Click **Allow** to grant access - -![Canva team selection and permissions](../../../../../assets/canva3.png) - -The permissions include: -- Reading your profile and designs -- Creating new designs -- Managing folders and content -- Accessing team brand templates -- Commenting on designs - -### Model Configuration - -Use a tool-enabled model: - -- **Anthropic Claude 3.5+ Sonnet** -- **OpenAI GPT-4o** -- **Google Gemini Pro** - -## Real-World Usage Example - -Here's an actual workflow creating a company logo: - -### Initial Setup Confirmation - -``` -Are you able to access my projects? -``` - -The AI explains available capabilities: - -![AI response about available actions](../../../../../assets/canva4.png) - -### Design Creation Request - -``` -Create new designs with AI. Call it "VibeBusiness" and have it be a company focused on superintelligence for the benefit of humanity. -``` - -The AI initiates design generation: - -![AI generating design with tool call visible](../../../../../assets/canva5.png) - -### Design Options - -The AI creates multiple logo variations: - -**First Option:** -![First logo design option](../../../../../assets/canva6.png) - -**Selected Design:** -![Selected logo design](../../../../../assets/canva7.png) - -### Final Result - -After selection, the AI confirms: - -![Final response with design ready](../../../../../assets/canva8.png) - -Clicking the design link opens it directly in Canva: - -![Design opened in Canva browser tab](../../../../../assets/canva9.png) - -## Practical Use Cases - -### Marketing Campaign Development -``` -Create a social media campaign for our new product launch. Generate Instagram posts, Facebook covers, and LinkedIn banners with consistent branding. -``` - -### Presentation Automation -``` -Search for our Q4 sales presentation and create a simplified 5-slide version for the board meeting. -``` - -### Brand Asset Management -``` -List all designs in our "2025 Marketing" folder and export the approved ones as PDFs. -``` - -### Design Iteration -``` -Find our company logo designs from last month and resize them for business cards, letterheads, and email signatures. -``` - -### Content Extraction -``` -Extract all text from our employee handbook presentation so I can update it in our documentation. -``` - -### Collaborative Review -``` -Add a comment to the new website mockup asking the design team about the color scheme choices. -``` - -## Workflow Tips - -### Effective Design Generation -- **Be specific**: "Create a minimalist tech company logo with blue and silver colors" -- **Specify format**: "Generate an Instagram story template for product announcements" -- **Include context**: "Design a professional LinkedIn banner for a AI research company" -- **Request variations**: Ask for multiple options to choose from - -### Organization Best Practices -- Create folders before generating multiple designs -- Use descriptive names for easy searching later -- Move designs to appropriate folders immediately -- Export important designs for backup - -### Integration Patterns -- Generate designs โ†’ Review options โ†’ Select preferred โ†’ Open in Canva for fine-tuning -- Search existing designs โ†’ Extract content โ†’ Generate new versions -- Create templates โ†’ Resize for multiple platforms โ†’ Export all variants - -## Limitations and Considerations - -**Design Editing**: While the MCP can create and manage designs, actual editing requires opening Canva's interface. - -**Project Access**: The integration may not access all historical projects immediately, focusing on designs created or modified after connection. - -**Generation Time**: AI design generation takes a few moments. The tool provides job IDs to track progress. - -**Team Permissions**: Access depends on your Canva team settings and subscription level. - -## Troubleshooting - -**Authentication Issues:** -- Clear browser cookies for Canva -- Try logging out and back into Canva -- Ensure pop-ups aren't blocked for OAuth flow -- Check team admin permissions if applicable - -**Design Generation Failures:** -- Verify you have creation rights in selected team -- Check Canva subscription limits -- Try simpler design prompts first -- Ensure stable internet connection - -**Tool Availability:** -- Some tools require specific Canva plans -- Team features need appropriate permissions -- Verify MCP server is showing as active -- Restart Jan after authentication - -**Search Problems:** -- Use search-designs (not the legacy search tool) -- Be specific with design types and names -- Check folder permissions for team content -- Allow time for new designs to index - - - -## Advanced Workflows - -### Batch Operations -``` -Create 5 variations of our product announcement banner, then resize all of them for Twitter, LinkedIn, and Facebook. -``` - -### Content Migration -``` -Import all designs from [URLs], organize them into a "2025 Campaign" folder, and add review comments for the team. -``` - -### Automated Reporting -``` -Search for all presentation designs created this month, extract their content, and summarize the key themes. -``` - -## Next Steps - -Canva MCP bridges the gap between conversational AI and visual design. Instead of describing what you want and then manually creating it, you can generate professional designs directly through natural language commands. - -The real power emerges when combining multiple tools - searching existing assets, generating new variations, organizing content, and collaborating with teams, all within a single conversation flow. diff --git a/website/src/content/docs/jan/mcp-examples/productivity/linear.mdx b/website/src/content/docs/jan/mcp-examples/productivity/linear.mdx deleted file mode 100644 index 60824eadc..000000000 --- a/website/src/content/docs/jan/mcp-examples/productivity/linear.mdx +++ /dev/null @@ -1,265 +0,0 @@ ---- -title: Linear MCP -description: Manage software projects and issue tracking through natural language with Linear integration. -keywords: - [ - Jan, - MCP, - Model Context Protocol, - Linear, - project management, - issue tracking, - agile, - software development, - tool calling, - ] -sidebar: - badge: - text: New - variant: tip ---- - -import { Aside } from '@astrojs/starlight/components'; - -[Linear MCP](https://linear.app) provides comprehensive project management capabilities through natural conversation. Transform your software development workflow by managing issues, projects, and team collaboration directly through AI. - -## Available Tools - -Linear MCP offers extensive project management capabilities: - -### Issue Management -- `list_issues`: View all issues in your workspace -- `get_issue`: Get details of a specific issue -- `create_issue`: Create new issues with full details -- `update_issue`: Modify existing issues -- `list_my_issues`: See your assigned issues -- `list_issue_statuses`: View available workflow states -- `list_issue_labels`: See and manage labels -- `create_issue_label`: Create new labels - -### Project & Team -- `list_projects`: View all projects -- `get_project`: Get project details -- `create_project`: Start new projects -- `update_project`: Modify project settings -- `list_teams`: See all teams -- `get_team`: Get team information -- `list_users`: View team members - -### Documentation & Collaboration -- `list_documents`: Browse documentation -- `get_document`: Read specific documents -- `search_documentation`: Find information -- `list_comments`: View issue comments -- `create_comment`: Add comments to issues -- `list_cycles`: View sprint cycles - -## Prerequisites - -- Linear account (free for up to 250 issues) -- Model with strong tool calling support -- Active internet connection - - - -## Setup - -### Create Linear Account - -1. Sign up at [linear.app](https://linear.app) -2. Complete the onboarding process - -![Linear signup page](../../../../../assets/linear1.png) - -Once logged in, you'll see your workspace: - -![Linear main dashboard](../../../../../assets/linear2.png) - -### Enable MCP in Jan - -1. Go to **Settings > MCP Servers** -2. Toggle **Allow All MCP Tool Permission** ON - -### Configure Linear MCP - -Click the `+` button to add Linear MCP: - -**Configuration:** -- **Server Name**: `linear` -- **Command**: `npx` -- **Arguments**: `-y mcp-remote https://mcp.linear.app/sse` - -![Linear MCP configuration in Jan](../../../../../assets/linear3.png) - -### Authenticate with Linear - -When you first use Linear tools, a browser tab will open for authentication: - -![Linear authentication page](../../../../../assets/linear4.png) - -Complete the OAuth flow to grant Jan access to your Linear workspace. - -## Usage - -### Select a Model with Tool Calling - -For this example, we'll use kimi-k2 from Groq: - -1. Add the model in Groq settings: `moonshotai/kimi-k2-instruct` - -![Adding kimi-k2 model](../../../../../assets/linear6.png) - -2. Enable tools for the model: - -![Enable tools for kimi-k2](../../../../../assets/linear7.png) - -### Verify Available Tools - -You should see all Linear tools in the chat interface: - -![Linear tools available in chat](../../../../../assets/linear8.png) - -### Epic Project Management - -Watch AI transform mundane tasks into epic narratives: - -![Linear MCP creating Shakespearean war epic tasks](/gifs/mcplinear2.gif) - -## Creative Examples - -### ๐ŸŽญ Shakespearean Sprint Planning -``` -Create Linear tickets in the '๐Ÿ‘‹Jan' team for my AGI project as battles in a Shakespearean war epic. Each sprint is a military campaign, bugs are enemy spies, and merge conflicts are sword fights between rival houses. Invent unique epic titles and dramatic descriptions with battle cries and victory speeches. Characterize bugs as enemy villains and developers as heroic warriors in this noble quest for AGI glory. Make tasks like model training, testing, and deployment sound like grand military campaigns with honor and valor. -``` - -### ๐Ÿš€ Space Mission Development -``` -Transform our mobile app redesign into a NASA space mission. Create issues where each feature is a mission objective, bugs are space debris to clear, and releases are launch windows. Add dramatic mission briefings, countdown sequences, and astronaut logs. Priority levels become mission criticality ratings. -``` - -### ๐Ÿดโ€โ˜ ๏ธ Pirate Ship Operations -``` -Set up our e-commerce platform project as a pirate fleet adventure. Features are islands to conquer, bugs are sea monsters, deployments are naval battles. Create colorful pirate-themed tickets with treasure maps, crew assignments, and tales of high seas adventure. -``` - -### ๐ŸŽฎ Video Game Quest Log -``` -Structure our API refactoring project like an RPG quest system. Create issues as quests with XP rewards, boss battles for major features, side quests for minor tasks. Include loot drops (completed features), skill trees (learning requirements), and epic boss fight descriptions for challenging bugs. -``` - -### ๐Ÿณ Gordon Ramsay's Kitchen -``` -Manage our restaurant app project as if Gordon Ramsay is the head chef. Create brutally honest tickets criticizing code quality, demanding perfection in UX like a Michelin star dish. Bugs are "bloody disasters" and successful features are "finally, some good code." Include Kitchen Nightmares-style rescue plans. -``` - -## Practical Workflows - -### Sprint Planning -``` -Review all open issues in the Backend team, identify the top 10 by priority, and create a new sprint cycle called "Q1 Performance Sprint" with appropriate issues assigned. -``` - -### Bug Triage -``` -List all bugs labeled "critical" or "high-priority", analyze their descriptions, and suggest which ones should be fixed first based on user impact. Update their status to "In Progress" for the top 3. -``` - -### Documentation Audit -``` -Search our documentation for anything related to API authentication. Create issues for any gaps or outdated sections you find, labeled as "documentation" with detailed improvement suggestions. -``` - -### Team Workload Balance -``` -Show me all active issues grouped by assignee. Identify anyone with more than 5 high-priority items and suggest redistributions to balance the workload. -``` - -### Release Planning -``` -Create a project called "v2.0 Release" with milestones for: feature freeze, beta testing, documentation, and launch. Generate appropriate issues for each phase with realistic time estimates. -``` - -## Advanced Integration Patterns - -### Cross-Project Dependencies -``` -Find all issues labeled "blocked" across all projects. For each one, identify what they're waiting on and create linked issues for the blocking items if they don't exist. -``` - -### Automated Status Updates -``` -Look at all issues assigned to me that haven't been updated in 3 days. Add a comment with a status update based on their current state and any blockers. -``` - -### Smart Labeling -``` -Analyze all unlabeled issues in our workspace. Based on their titles and descriptions, suggest appropriate labels and apply them. Create any missing label categories we need. -``` - -### Sprint Retrospectives -``` -Generate a retrospective report for our last completed cycle. List what was completed, what was pushed to next sprint, and create discussion issues for any patterns you notice. -``` - -## Tips for Maximum Productivity - -- **Batch Operations**: Create multiple related issues in one request -- **Smart Templates**: Ask AI to remember your issue templates -- **Natural Queries**: "Show me what John is working on this week" -- **Context Awareness**: Reference previous issues in new requests -- **Automated Workflows**: Set up recurring management tasks - -## Troubleshooting - -**Authentication Issues:** -- Clear browser cookies for Linear -- Re-authenticate through the OAuth flow -- Check Linear workspace permissions -- Verify API access is enabled - -**Tool Calling Errors:** -- Ensure model supports multiple tool calls -- Try breaking complex requests into steps -- Verify all required fields are provided -- Check Linear service status - -**Missing Data:** -- Refresh authentication token -- Verify workspace access permissions -- Check if issues are in archived projects -- Ensure proper team selection - -**Performance Issues:** -- Linear API has rate limits (see dashboard) -- Break bulk operations into batches -- Cache frequently accessed data -- Use specific filters to reduce data - - - -## Integration Ideas - -Combine Linear with other MCP tools: - -- **Serper + Linear**: Research technical solutions, then create implementation tickets -- **Jupyter + Linear**: Analyze project metrics, generate data-driven sprint plans -- **Todoist + Linear**: Sync personal tasks with work issues -- **E2B + Linear**: Run code tests, automatically create bug reports - -## Privacy & Security - -Linear MCP uses OAuth for authentication, meaning: -- Your credentials are never shared with Jan -- Access can be revoked anytime from Linear settings -- Data stays within Linear's infrastructure -- Only requested permissions are granted - -## Next Steps - -Linear MCP transforms project management from clicking through interfaces into natural conversation. Whether you're planning sprints, triaging bugs, or crafting epic development sagas, AI becomes your project management companion. - -Start with simple issue creation, then explore complex workflows like automated sprint planning and workload balancing. The combination of Linear's powerful platform with AI's creative capabilities makes project management both efficient and entertaining! diff --git a/website/src/content/docs/jan/mcp-examples/productivity/todoist.mdx b/website/src/content/docs/jan/mcp-examples/productivity/todoist.mdx deleted file mode 100644 index 15548a011..000000000 --- a/website/src/content/docs/jan/mcp-examples/productivity/todoist.mdx +++ /dev/null @@ -1,256 +0,0 @@ ---- -title: Todoist MCP -description: Manage your tasks and todo lists through natural language with Todoist integration. -keywords: - [ - Jan, - MCP, - Model Context Protocol, - Todoist, - task management, - productivity, - todo list, - tool calling, - ] -sidebar: - badge: - text: New - variant: tip ---- - -import { Aside } from '@astrojs/starlight/components'; - -[Todoist MCP Server](https://github.com/abhiz123/todoist-mcp-server) enables AI models to manage your Todoist tasks through natural conversation. Instead of switching between apps, you can create, update, and complete tasks by simply chatting with your AI assistant. - -## Available Tools - -- `todoist_create_task`: Add new tasks to your todo list -- `todoist_get_tasks`: Retrieve and view your current tasks -- `todoist_update_task`: Modify existing tasks -- `todoist_complete_task`: Mark tasks as done -- `todoist_delete_task`: Remove tasks from your list - -## Prerequisites - -- Todoist account (free or premium) -- Model with strong tool calling support -- Node.js installed - - - -## Setup - -### Create Todoist Account - -1. Sign up at [todoist.com](https://todoist.com) or log in if you have an account -2. Complete the onboarding process - -![Todoist welcome screen](../../../../../assets/todoist1.png) - -Once logged in, you'll see your main dashboard: - -![Todoist main dashboard](../../../../../assets/todoist2.png) - -### Get Your API Token - -1. Click **Settings** (gear icon) -2. Navigate to **Integrations** -3. Click on the **Developer** tab -4. Copy your API token (it's already generated for you) - -![Todoist API token in settings](../../../../../assets/todoist3.png) - -### Enable MCP in Jan - -1. Go to **Settings > MCP Servers** -2. Toggle **Allow All MCP Tool Permission** ON - -### Configure Todoist MCP - -Click the `+` button to add a new MCP server: - -**Configuration:** -- **Server Name**: `todoist` -- **Command**: `npx` -- **Arguments**: `-y @abhiz123/todoist-mcp-server` -- **Environment Variables**: - - Key: `TODOIST_API_TOKEN`, Value: `your_api_token_here` - -![Todoist MCP configuration in Jan](../../../../../assets/todoist4.png) - -## Usage - -### Select a Model with Tool Calling - -Open a new chat and select a model that excels at tool calling. Make sure tools are enabled for your chosen model. - -![Model selection with tools enabled](../../../../../assets/gpt5-add.png) - -### Verify Tools Available - -You should see the Todoist tools in the tools panel: - -![Todoist tools available in chat](../../../../../assets/todoist5.png) - -### Start Managing Tasks - -Now you can manage your todo list through natural conversation: - -![Todoist MCP in action](/gifs/mcptodoist_extreme.gif) - -## Example Prompts - -### Blog Writing Workflow -``` -I need to write a blog post about AI and productivity tools today. Please add some tasks to my todo list to make sure I have a good set of steps to accomplish this task. -``` - -The AI will create structured tasks like: -- Research AI productivity tools -- Create blog outline -- Write introduction -- Draft main sections -- Add examples and screenshots -- Edit and proofread -- Publish and promote - -### Weekly Meal Planning -``` -Help me plan meals for the week. Create a grocery shopping list and cooking schedule for Monday through Friday, focusing on healthy, quick dinners. -``` - -### Home Improvement Project -``` -I'm renovating my home office this weekend. Break down the project into manageable tasks including shopping, prep work, and the actual renovation steps. -``` - -### Study Schedule -``` -I have a statistics exam in 2 weeks. Create a study plan with daily tasks covering all chapters, practice problems, and review sessions. -``` - -### Fitness Goals -``` -Set up a 30-day fitness challenge for me. Include daily workout tasks, rest days, and weekly progress check-ins. -``` - -### Event Planning -``` -I'm organizing a surprise birthday party for next month. Create a comprehensive task list covering invitations, decorations, food, entertainment, and day-of coordination. -``` - -## Advanced Usage - -### Task Management Commands - -**View all tasks:** -``` -Show me all my pending tasks for today -``` - -**Update priorities:** -``` -Make "Write blog introduction" high priority and move it to the top of my list -``` - -**Bulk completion:** -``` -Mark all my morning routine tasks as complete -``` - -**Clean up:** -``` -Delete all completed tasks from last week -``` - -### Project Organization - -Todoist supports projects, though the MCP may have limitations. Try: -``` -Create a new project called "Q1 Goals" and add 5 key objectives as tasks -``` - -### Recurring Tasks - -Set up repeating tasks: -``` -Add a daily task to review my calendar at 9 AM -Add a weekly task for meal prep on Sundays -Add a monthly task to pay bills on the 1st -``` - -## Creative Use Cases - -### ๐ŸŽฎ Game Development Sprint -``` -I'm participating in a 48-hour game jam. Create an hour-by-hour task schedule covering ideation, prototyping, art creation, programming, testing, and submission. -``` - -### ๐Ÿ“š Book Writing Challenge -``` -I'm doing NaNoWriMo (writing a novel in a month). Break down a 50,000-word goal into daily writing tasks with word count targets and plot milestones. -``` - -### ๐ŸŒฑ Garden Planning -``` -It's spring planting season. Create a gardening schedule for the next 3 months including soil prep, planting dates for different vegetables, watering reminders, and harvest times. -``` - -### ๐ŸŽ‚ Baking Business Launch -``` -I'm starting a home bakery. Create tasks for getting permits, setting up social media, creating a menu, pricing strategy, and first week's baking schedule. -``` - -### ๐Ÿ  Moving Checklist -``` -I'm moving to a new apartment next month. Generate a comprehensive moving checklist including utilities setup, packing by room, change of address notifications, and moving day logistics. -``` - -## Tips for Best Results - -- **Be specific**: "Add task: Call dentist tomorrow at 2 PM" works better than "remind me about dentist" -- **Use natural language**: The AI understands context, so chat naturally -- **Batch operations**: Ask to create multiple related tasks at once -- **Review regularly**: Ask the AI to show your tasks and help prioritize -- **Iterate**: If the tasks aren't quite right, ask the AI to modify them - -## Troubleshooting - -**Tasks not appearing in Todoist:** -- Verify API token is correct -- Check Todoist website/app and refresh -- Ensure MCP server shows as active - -**Tool calling errors:** -- Confirm model supports tool calling -- Enable tools in model settings -- Try a different model (Claude 3.5+ or GPT-4o recommended) - -**Connection issues:** -- Check internet connectivity -- Verify Node.js installation -- Restart Jan after configuration - -**Rate limiting:** -- Todoist API has rate limits -- Space out bulk operations -- Wait a moment between large task batches - - - -## Privacy Note - -Your tasks are synced with Todoist's servers. While the MCP runs locally, task data is stored in Todoist's cloud for sync functionality. Review Todoist's privacy policy if you're handling sensitive information. - -## Next Steps - -Combine Todoist MCP with other tools for powerful workflows: -- Use Serper MCP to research topics, then create action items in Todoist -- Generate code with E2B, then add testing tasks to your todo list -- Analyze data with Jupyter, then create follow-up tasks for insights - -Task management through natural language makes staying organized effortless. Let your AI assistant handle the overhead while you focus on getting things done! diff --git a/website/src/content/docs/jan/mcp-examples/search/exa.mdx b/website/src/content/docs/jan/mcp-examples/search/exa.mdx deleted file mode 100644 index 19c7a5dde..000000000 --- a/website/src/content/docs/jan/mcp-examples/search/exa.mdx +++ /dev/null @@ -1,224 +0,0 @@ ---- -title: Exa Search MCP -description: Connect Jan to real-time web search with Exa's AI-powered search engine. -keywords: - [ - Jan, - MCP, - Model Context Protocol, - Exa, - web search, - real-time search, - research, - AI search, - tool calling, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -[Exa MCP](https://docs.exa.ai/examples/exa-mcp) provides real-time web search capabilities for AI -models. Instead of relying on training data, models can access current web content through Exa's search API. - -## Available Tools - -Exa MCP includes eight search functions: -- `web_search_exa`: General web search with content extraction -- `research_paper_search`: Academic papers and research content -- `company_research`: Company analysis and business intelligence -- `crawling`: Extract content from specific URLs -- `competitor_finder`: Find business competitors -- `linkedin_search`: Search LinkedIn profiles and companies -- `wikipedia_search_exa`: Wikipedia content retrieval -- `github_search`: Repository and code search - -## Prerequisites - -- Jan with MCP enabled -- Exa API key from [dashboard.exa.ai](https://dashboard.exa.ai/api-keys) -- Model with tool calling support -- Node.js installed - - - -## Setup - -### Enable MCP - -1. Go to **Settings** > **MCP Servers** -2. Toggle **Allow All MCP Tool Permission** ON - -![MCP settings page with toggle enabled](../../../../../assets/mcp-on.png) - -### Get API Key - -1. Visit [dashboard.exa.ai/api-keys](https://dashboard.exa.ai/api-keys) -2. Create account or sign in -3. Generate API key -4. Save the key - -![Exa API Key](../../../../../assets/exa.png) - -### Configure MCP Server - -Click `+` in MCP Servers section: - -**Configuration:** -- **Server Name**: `exa` -- **Command**: `npx` -- **Arguments**: `-y exa-mcp-server` -- **Environment Variables**: - - Key: `EXA_API_KEY` - - Value: `your-api-key` - -![Exa Jan MCP Server](../../../../../assets/exa1.png) - -### Verify Setup - -Check server status in the MCP Servers list. - -![Exa Jan MCP Server](../../../../../assets/exa2.png) - -### Model Configuration - -Use a compatible model provider: - -- **Jan Nano 32k** -- **Anthropic** -- **OpenAI** -- **OpenRouter** - -![E2B MCP Server](../../../../../assets/e2b-key4.png) - -## Usage - -Start a new chat with a tool-enabled model. Exa tools will appear in the available tools list. - -![Exa Tools Available](../../../../../assets/exa3.png) - -### Example Queries - -**Current Events & Activities:** - -``` -What is happening this week, mid July 2025, in Sydney, Australia? -``` - -![Exa Tools Available](../../../../../assets/exa4.png) - -**Investment Research:** - -``` -Find recent research papers about quantum computing startups that received Series A funding in 2024-2025 -``` - -**Tech Discovery:** - -``` -Find GitHub repositories for WebAssembly runtime engines written in Rust with active development -``` - -**Career Intelligence:** - -``` -Search LinkedIn for AI safety researchers at major tech companies who published papers in the last 6 months -``` - -**Competitive Analysis:** - -``` -Research emerging competitors to OpenAI in the large language model space, focusing on companies founded after 2023 -``` - -**Travel & Local Research:** - -``` -Find authentic local food experiences in Tokyo that aren't in typical tourist guides, mentioned in recent travel blogs -``` - -**Academic Research:** - -``` -Find recent papers about carbon capture technology breakthroughs published in Nature or Science during 2025 -``` - -**Creator Economy:** - -``` -Research successful creators who transitioned from TikTok to longer-form content platforms in 2024-2025 -``` - -**Emerging Tech Trends:** - -``` -Find startups working on brain-computer interfaces that have raised funding in the past 12 months -``` - -**Health & Wellness:** - -``` -Extract information about the latest longevity research findings from Peter Attia's recent podcast episodes -``` - -**Regulatory Intelligence:** - -``` -Find recent AI regulation developments in the EU that could impact US companies, focusing on July 2025 updates -``` - -**Supply Chain Research:** - -``` -Research companies developing sustainable packaging alternatives that have partnerships with major retailers -``` - -## Use Cases - -### Academic Research -Literature reviews, finding recent papers, tracking research trends. - -### Business Intelligence -Competitor analysis, market research, company information gathering. - -### Technical Research -Finding libraries, tools, and code repositories. Documentation research. - -### Content Analysis -Extracting and analyzing content from specific URLs for research. - -### Professional Search -LinkedIn searches for industry connections and expertise. - -## Troubleshooting - -**Connection Issues:** -- Verify API key accuracy -- Check Node.js installation -- Restart Jan -- Make sure you have enough credits in your Exa account - -**Tool Calling Problems:** -- Confirm tool calling is enabled for your model -- Try Jan Nano 32k, Claude, Gemini, GPT-4o and above models -- Check MCP server status - -**Search Quality:** -- Use specific, descriptive queries -- Prefer natural language over keywords - -**API Errors:** -- Verify API key at [dashboard.exa.ai](https://dashboard.exa.ai) -- Check rate limits on your plan -- Regenerate API key if needed - - - -## Next Steps - -Exa MCP enables real-time web search within Jan's privacy-focused environment. Models can access current -information while maintaining local conversation processing. diff --git a/website/src/content/docs/jan/mcp-examples/search/serper.mdx b/website/src/content/docs/jan/mcp-examples/search/serper.mdx deleted file mode 100644 index 191b72c84..000000000 --- a/website/src/content/docs/jan/mcp-examples/search/serper.mdx +++ /dev/null @@ -1,157 +0,0 @@ ---- -title: Serper Search MCP -description: Connect Jan to real-time web search with Google results through Serper API. -sidebar: - badge: - text: New - variant: tip ---- - -import { Aside } from '@astrojs/starlight/components'; - -[Serper](https://serper.dev) provides Google search results through a simple API, making it -perfect for giving AI models access to current web information. The Serper MCP integration -enables Jan models to search the web and retrieve real-time information. - -## Available Tools - -- `google_search`: Search Google and retrieve results with snippets -- `scrape`: Extract content from specific web pages - -## Prerequisites - -- Serper API key from [serper.dev](https://serper.dev) -- Model with tool calling support (recommended: Jan v1) - - - -## Setup - -### Enable MCP - -1. Go to **Settings** > **MCP Servers** -2. Toggle **Allow All MCP Tool Permission** ON - -![Turn on MCP](../../../../../assets/turn_on_mcp.png) - -### Get Serper API Key - -1. Visit [serper.dev](https://serper.dev) -2. Sign up for a free account -3. Copy your API key from the playground - -![Serper homepage](../../../../../assets/serper_page.png) - -![Serper playground with API key](../../../../../assets/serper_playground.png) - -### Configure MCP Server - -Click `+` in MCP Servers section: - -**Configuration:** -- **Server Name**: `serper` -- **Command**: `npx` -- **Arguments**: `-y serper-search-scrape-mcp-server` -- **Environment Variables**: - - Key: `SERPER_API_KEY`, Value: `your-api-key` - -![Serper MCP configuration in Jan](../../../../../assets/serper_janparams.png) - -### Download Jan v1 - -Jan v1 is optimized for tool calling and works excellently with Serper: - -1. Go to the **Hub** tab -2. Search for **Jan v1** -3. Choose your preferred quantization -4. Click **Download** - -![Download Jan v1 from Hub](../../../../../assets/download_janv1.png) - -### Enable Tool Calling - -Tool calling is now enabled by default on Jan. - -## Usage - -### Start a New Chat - -With Jan v1 selected, you'll see the available Serper tools: - -![Chat view with Serper tools](../../../../../assets/chat_jan_v1.png) - -### Example Queries - -**Current Information:** -``` -What are the latest developments in quantum computing this week? -``` - -**Comparative Analysis:** -``` -What are the main differences between the Rust programming language and C++? Be spicy, hot -takes are encouraged. ๐Ÿ˜Œ -``` - - -**Research Tasks:** -``` -Find the current stock price of NVIDIA and recent news about their AI chips. -``` - -**Fact-Checking:** -``` -Is it true that the James Webb telescope found signs of life on an exoplanet? What's the latest? -``` - -**Local Information:** -``` -What restaurants opened in San Francisco this month? Focus on Japanese cuisine. -``` - -## How It Works - -1. **Query Processing**: Jan v1 analyzes your question and determines what to search -2. **Web Search**: Calls Serper API to get Google search results -3. **Content Extraction**: Can scrape specific pages for detailed information -4. **Synthesis**: Combines search results into a comprehensive answer - -## Tips for Best Results - -- **Be specific**: "Tesla Model 3 2024 price Australia" works better than "Tesla price" -- **Request recent info**: Add "latest", "current", or "2024/2025" to get recent results -- **Ask follow-ups**: Jan v1 maintains context for deeper research -- **Combine with analysis**: Ask for comparisons, summaries, or insights - -## Troubleshooting - -**No search results:** -- Verify API key is correct -- Check remaining credits at serper.dev - -**Tools not appearing:** -- Restart Jan after configuration changes -- Ensure MCP Server shows as active - -**Poor search quality:** -- Use more specific search terms -- Try rephrasing your question -- Check if Serper service is operational - - - -## API Limits - -- **Free tier**: 2,500 searches -- **Paid plans**: Starting at $50/month for 50,000 searches -- **Rate limits**: 100 requests per second - -## Next Steps - -Serper MCP enables models to access current web information, making them powerful research -assistants. Combine with other MCP tools for even more capabilities - use Serper for search, -then E2B for data analysis, or Jupyter for visualization. diff --git a/website/src/content/docs/jan/mcp.mdx b/website/src/content/docs/jan/mcp.mdx deleted file mode 100644 index 110108227..000000000 --- a/website/src/content/docs/jan/mcp.mdx +++ /dev/null @@ -1,298 +0,0 @@ ---- -title: Model Context Protocol -description: Extend Jan's capabilities with tools and external integrations through MCP. -keywords: - [ - Jan, - MCP, - Model Context Protocol, - tools, - integrations, - AI tools, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - large language models, - external APIs, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -## Tools in Jan - -Jan supports powerful tool integrations that extend your AI's capabilities beyond simple text generation. These tools are implemented through the **Model Context Protocol (MCP)**, allowing your AI to search the web, execute code, manage files, and interact with external services. - -**Available tool categories:** -- **Web & Search** - Real-time web search, browser automation -- **Code & Analysis** - Jupyter notebooks, code execution, data analysis -- **Productivity** - Task management, calendar integration, note-taking -- **Creative** - Design tools, content generation, media manipulation -- **File Management** - Document processing, file operations, data extraction - -Tools work with both local and cloud models, though compatibility varies. Cloud models like GPT-4 and Claude typically offer the best tool-calling performance, while newer local models are rapidly improving their tool capabilities. - -```mermaid -graph TD - subgraph "What is MCP?" - You[You using Jan Desktop] - Claude[Jan AI Assistant] - - subgraph "Your Connected Tools" - Files[๐Ÿ“ Your Files
Documents, folders,
text files] - Database[๐Ÿ“Š Your Data
Spreadsheets,
databases] - WebServices[๐ŸŒ Online Services
GitHub, Slack,
Google Drive] - Custom[๐Ÿ”ง Custom Tools
Special programs
you've added] - end - - subgraph "What Jan Can Do" - Read[Read & Understand
- View your files
- Check your data
- See updates] - Action[Take Actions
- Search for info
- Create content
- Run commands] - Templates[Use Templates
- Common tasks
- Saved prompts
- Workflows] - end - end - - You --> Claude - Claude -->|"Can I see this file?"| Files - Claude -->|"What's in my database?"| Database - Claude -->|"Check my GitHub"| WebServices - Claude -->|"Run this tool"| Custom - - Files --> Read - Database --> Read - WebServices --> Action - Custom --> Templates - - style You fill:transparent - style Claude fill:transparent - style Files fill:transparent - style Database fill:transparent - style WebServices fill:transparent - style Custom fill:transparent - style Read fill:transparent - style Action fill:transparent - style Templates fill:transparent -``` - -## What is MCP? - -Jan supports the **Model Context Protocol (MCP)**, an open standard that allows AI models to interact with external tools and data sources in a secure, standardized way. - -MCP solves the integration challenge by creating a common interface between AI models and external tools. Instead of building custom connectors for every model-tool combination, MCP provides a universal protocol that any compatible model can use with any compatible tool. - -**How it works:** -- **MCP Servers** provide tools, data sources, and capabilities -- **MCP Clients** (like Jan) connect models to these servers -- **Standardized Protocol** ensures compatibility across different implementations - -This architecture means you can easily add new capabilities to your AI without complex integrations, and tools built for one AI system work with others that support MCP. - -## Core Benefits - -**Standardization:** MCP eliminates the "M x N" integration problem where every AI model needs unique connectors for every tool. One standard interface works everywhere. - -**Extensibility:** Add powerful new capabilities to your AI models. Search local codebases, query databases, interact with web APIs, automate browser tasks, and more. - -**Flexibility:** Swap models and tools easily. Your MCP setup works whether you're using local models, Claude, GPT-4, or future AI systems. - -**Security:** User-controlled permissions ensure you decide which tools can access what resources. Tools run in isolated environments with explicit consent. - - - -## Model Compatibility Requirements - - - -## Security and Considerations - -MCP provides powerful capabilities that require careful security consideration: - -**Security Model:** -- **Explicit permissions** for each tool and capability -- **Isolated execution** prevents cross-tool interference -- **User approval** required for sensitive operations -- **Audit trails** track all tool usage and outputs - -**Performance Impact:** -- **Context usage:** Active tools consume model context window space -- **Response time:** More tools may slow generation slightly -- **Resource usage:** Some tools require additional system resources - -**Best Practices:** -- Enable only tools you actively need -- Review tool permissions regularly -- Monitor system resource usage -- Keep MCP servers updated for security patches - -## Setting Up MCP in Jan - -### Prerequisites - -Ensure you have the required runtime environments: -- **Node.js** - Download from [nodejs.org](https://nodejs.org/) -- **Python** - Download from [python.org](https://www.python.org/) - -Most MCP tools require one or both of these environments. - -### Enable MCP Support - -Navigate to **Settings โ†’ MCP Servers** and toggle **Allow All MCP Tool Permission** to ON. - -![Enable MCP in Jan](../../../assets/mcp-on.png) - -This global setting allows Jan to connect to MCP servers. You'll still control individual tool permissions. - -### Example: Browser MCP Setup - -Let's configure Browser MCP for web automation as a practical example: - -#### Step 1: Add MCP Server - -Click the `+` button in the MCP Servers section: - -![Add new MCP server](../../../assets/mcp-setup-1.png) - -#### Step 2: Configure Browser MCP - -Enter these details: -- **Server Name:** `browsermcp` -- **Command:** `npx` -- **Arguments:** `@browsermcp/mcp` -- **Environment Variables:** Leave empty - -![Configure Browser MCP](../../../assets/mcp-setup-2.png) - -#### Step 3: Verify Connection - -Confirm the server shows as active: - -![Server confirmation](../../../assets/mcp-setup-3.png) - -#### Step 4: Install Browser Extension - -Install the [Browser MCP Chrome Extension](https://chromewebstore.google.com/detail/browser-mcp-automate-your/bjfgambnhccakkhmkepdoekmckoijdlc) to enable browser control: - -![Browser MCP extension](../../../assets/mcp-setup-6.png) - -#### Step 5: Configure Extension - -Enable the extension for private browsing (recommended for clean sessions): - -![Extension private mode](../../../assets/mcp-setup-7.png) - -Connect the extension to your MCP server: - -![Extension connection](../../../assets/mcp-setup-8.png) - -#### Step 6: Enable Model Tools - -Select a model with strong tool-calling capabilities and enable tools: - -![Enable model tools](../../../assets/mcp-setup-9.png) - -Verify tool calling is active: - -![Verify tools enabled](../../../assets/mcp-setup-10.png) - -## Available MCP Integrations - -Jan supports a growing ecosystem of MCP tools: - -### Web & Search -- **Browser Control** - Automate web browsing tasks -- **Web Search** - Real-time search with Serper, Exa -- **Screenshot** - Capture and analyze web content - -### Development -- **Code Execution** - Run code in secure sandboxes -- **GitHub** - Repository management and analysis -- **Documentation** - Generate and maintain docs - -### Productivity -- **Task Management** - Todoist, Linear integration -- **Calendar** - Schedule and meeting management -- **Note Taking** - Obsidian, Notion connectivity - -### Creative -- **Design Tools** - Canva integration for graphics -- **Content Generation** - Blog posts, social media -- **Media Processing** - Image and video manipulation - -Explore specific integrations in our [MCP Examples](./mcp-examples/browser/browserbase) section. - -## Troubleshooting - -### Connection Issues - -**MCP server won't connect:** -- Verify Node.js and Python are installed correctly -- Check command syntax in server configuration -- Restart Jan after adding new servers -- Review server logs for specific error messages - -**Tools not appearing:** -- Ensure model has tool calling enabled -- Verify MCP permissions are active -- Check that the server status shows as running -- Try with a different model known for good tool support - -### Performance Problems - -**Slow responses with tools:** -- Reduce number of active tools -- Use models with larger context windows -- Monitor system resource usage -- Consider using faster local models or cloud providers - -**Model not using tools effectively:** -- Switch to models specifically trained for tool calling -- Provide more explicit instructions about tool usage -- Check model documentation for tool-calling examples -- Test with proven tool-compatible models first - -### Model Compatibility - -**Local models not calling tools:** -- Ensure the model supports function calling in its training -- Enable tool calling in model capabilities settings -- Try newer model versions with improved tool support -- Consider switching to cloud models for complex tool workflows - -## Future Development - -MCP integration in Jan continues evolving with new capabilities: - -**Planned Features:** -- **Visual tool builder** for custom MCP servers -- **Tool marketplace** for easy discovery and installation -- **Enhanced security** with granular permission controls -- **Performance optimization** for faster tool execution - -**Ecosystem Growth:** -- More professional tools (CRM, analytics, design) -- Better local model tool-calling performance -- Cross-platform mobile tool support -- Enterprise-grade security and compliance features - -The MCP ecosystem enables increasingly sophisticated AI workflows. As more tools become available and models improve their tool-calling abilities, Jan becomes a more powerful platform for augmented productivity and creativity. - -Start with simple tools like web search or code execution, then gradually expand your toolkit as you discover new use cases and workflows that benefit from AI-tool collaboration. \ No newline at end of file diff --git a/website/src/content/docs/jan/multi-modal.mdx b/website/src/content/docs/jan/multi-modal.mdx deleted file mode 100644 index c1e67310e..000000000 --- a/website/src/content/docs/jan/multi-modal.mdx +++ /dev/null @@ -1,175 +0,0 @@ ---- -title: Multi-Modal Support -description: Use images with AI models in Jan - local vision models and cloud providers with image understanding. -keywords: - [ - Jan, - multi-modal, - vision models, - image recognition, - Gemma3, - Qwen3, - Claude, - GPT-4V, - image attachment, - visual AI, - ] -sidebar: - badge: - text: New - variant: tip ---- - -import { Aside } from '@astrojs/starlight/components'; - -Jan supports image attachments with both local and cloud AI models. Upload images directly in your chats and get visual understanding, analysis, and creative responses from compatible models. - -## Local Vision Models - -Local models with image support work immediately without configuration. Popular vision models include the latest Gemma3 and Qwen3 series, which excel at image understanding while running entirely on your device. - -**Recommended Local Vision Models:** -- **Gemma3 4B** - Excellent balance of performance and resource usage -- **Qwen3 7B/14B** - Superior image analysis capabilities -- **LLaVA models** - Specialized for visual question answering - -### Example: Image Analysis - -Here's Gemma3 4B analyzing a meme with some personality: - -![AI meme for analysis](../../../assets/meme.png) - -Load a vision model like [Gemma3 4B](https://huggingface.co/unsloth/gemma-3-4b-it-GGUF) and attach your image: - -![Vision model chat setup](../../../assets/vision.png) - -**Prompt used:** "Describe what you see in the image please. Be a bit sarcastic." - -The model delivers contextual analysis with the requested tone: - -![Vision model response](../../../assets/vision2.png) - - - -## Cloud Vision Models - -Cloud providers like OpenAI (GPT-4V), Anthropic (Claude), and Google (Gemini) offer powerful vision capabilities. However, image support must be manually enabled for each model. - -### Enabling Vision for Cloud Models - -Navigate to your model settings and enable vision support: - -![Claude vision settings](../../../assets/vision3.png) - -Toggle both **Tools** and **Vision** if you want to combine image understanding with web search or other MCP capabilities. - -### Example: Creative Image Analysis - -With Claude 3.5 Sonnet configured for vision, upload an image and get creative responses: - -![Claude vision chat](../../../assets/vision4.png) - -**Prompt used:** "Write an AI joke about the image attached please." - -Claude combines image understanding with humor: - -![Claude vision response](../../../assets/vision5.png) - -## Supported Use Cases - -### Creative and Fun -- Meme analysis and creation -- Visual jokes and commentary -- Art critique and style analysis -- Creative writing from visual prompts - -### Practical Applications -- Document analysis and OCR -- Chart and graph interpretation -- Product identification and comparison -- Technical diagram explanation - -### Educational and Research -- Historical photo analysis -- Scientific image interpretation -- Visual learning assistance -- Research documentation - -## Model Capabilities Comparison - -| Model Type | Image Support | Setup Required | Privacy | Best For | -|------------|---------------|----------------|---------|----------| -| **Local (Gemma3, Qwen3)** | Automatic | None | Complete | Privacy, offline use | -| **GPT-4V** | Manual enable | API key + toggle | Cloud processed | Advanced analysis | -| **Claude 3.5 Sonnet** | Manual enable | API key + toggle | Cloud processed | Creative tasks | -| **Gemini Pro Vision** | Manual enable | API key + toggle | Cloud processed | Multi-language | - -## Image Format Support - -Jan accepts common image formats: -- **JPEG/JPG** - Most compatible -- **PNG** - Full transparency support -- **WebP** - Modern web format -- **GIF** - Static images only - - - -## Example Prompts - -### Technical Analysis -``` -Analyze this circuit diagram and explain how it works. Identify any potential issues or improvements. -``` - -### Creative Tasks -``` -Look at this artwork and write a short story inspired by the mood and colors you see. -``` - -### Educational Support -``` -Help me understand this math problem shown in the image. Walk through the solution step by step. -``` - -### Business Applications -``` -Review this presentation slide and suggest improvements for clarity and visual impact. -``` - -### OCR and Document Processing -``` -Extract all the text from this document and format it as a clean markdown list. -``` - -## Future Improvements - -We're actively improving multi-modal support: - -**Automatic Detection:** Models will show visual capabilities without manual configuration -**Batch Processing:** Upload multiple images for comparison and analysis -**Better Indicators:** Clear visual cues for vision-enabled models -**Enhanced Formats:** Support for more image types and sizes - -## Performance Tips - -**Local Models:** -- Ensure sufficient RAM (8GB+ recommended for vision models) -- Use GPU acceleration for faster image processing -- Start with smaller models if resources are limited - -**Cloud Models:** -- Monitor API usage as vision requests typically cost more -- Resize large images before upload to save bandwidth -- Combine with tools for enhanced workflows - -## Privacy Considerations - -**Local Processing:** Images processed by local models never leave your device. Complete privacy for sensitive visual content. - -**Cloud Processing:** Images sent to cloud providers are processed on their servers. Check provider privacy policies for data handling practices. - -Multi-modal AI opens new possibilities for visual understanding and creative assistance. Whether you prefer local privacy or cloud capabilities, Jan makes it easy to work with images and text together. diff --git a/website/src/content/docs/jan/privacy.mdx b/website/src/content/docs/jan/privacy.mdx deleted file mode 100644 index 3e0d8301e..000000000 --- a/website/src/content/docs/jan/privacy.mdx +++ /dev/null @@ -1,140 +0,0 @@ ---- -title: Jan Privacy Policy -description: Jan's data collection practices, privacy measures, and your rights. Learn how we protect your data and maintain transparency. -keywords: - [ - Jan AI, - Jan, - local AI, - private AI, - conversational AI, - no-subscription fee, - large language model, - about Jan, - desktop application, - privacy policy, - data protection, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -
- Last Updated: January 16, 2025 -
- -Jan is your AI. Here's what we do with data. - - - -## 1. Data Collection and Consent - -### No Data Collection Until You Allow It - -Menlo Research Pte Ltd (the "Company") doesn't collect anything until you explicitly allow tracking. - -### Your Choice - -You'll choose tracking preferences at first launch. Change them anytime in Settings or Privacy Settings. - -### Legal Basis (GDPR) - -Under EU GDPR Article 6(1)(a), we process data based on your explicit consent: - -- Clear consent required before any data collection -- Withdraw consent anytime through Settings -- Withdrawal doesn't affect previous lawful processing -- Processing stops immediately upon withdrawal - -## 2. What We Never Collect - -Jan will **never** access your chats, settings, or model choices without permission: - -- **Chat History**: Your conversations stay private -- **Chat Settings**: Your personalized settings remain with you -- **Language Models**: We don't track which models you use -- **Files**: No scanning, uploading, or viewing -- **Personal Identity**: No personally identifiable information -- **Prompts**: Your prompts and templates aren't monitored -- **Conversation Metrics**: No context or conversation length tracking -- **Model Usage**: Specific models and types aren't tracked - -## 3. Data We Track (With Permission) - -We track basic app usage to improve Jan. - -### Product Analytics - -When allowed, we collect: - -- **Active Users**: Daily active users to gauge engagement -- **Retention**: User retention metrics to ensure ongoing value - -Everything's tied to a random ID - not your personal information. Your chats remain private. - - - -## 4. Cloud Model Use - -Cloud models (like GPT, Claude) need to see your messages to work. That's between you and the cloud provider - Jan facilitates the connection. - -- **API Processing**: Cloud providers process your messages directly -- **Jan Access**: We don't access or store these messages -- **Local Models**: Keep everything on your device with no external access - -## 5. Data Storage and Security - -### Analytics Provider - -[PostHog EU](https://posthog.com/eu) handles our analytics. All EU-based, GDPR-compliant data processing. - -### Security Measures - -- **Encryption**: All transfers use TLS encryption -- **EU Processing**: Data processed within European Union -- **Secure Storage**: PostHog manages data securely - -Details in their [GDPR docs](https://posthog.com/docs/privacy/gdpr-compliance). - -## 6. Data Retention - -- **Retention Period**: Analytics data kept for up to 12 months -- **Deletion Requests**: Request deletion by emailing hello@jan.ai -- **Legal Requirements**: May retain longer if legally required - -## 7. Your Rights - -- **Access and Control**: Modify tracking preferences anytime in Settings -- **Data Requests**: Contact hello@jan.ai for any data-related requests -- **Withdrawal**: Stop data collection immediately through Settings - -## 8. Children's Privacy - -Services not targeted at children under 13. We don't knowingly collect data from children under 13. If we become aware of such collection, we'll delete the information. - -## 9. Cookies and Tracking - -Our website uses cookies to: - -- Enhance user experience -- Measure website traffic and usage - -Most browsers let you manage cookies and adjust privacy preferences. See our Cookie Policy for details. - -## 10. Policy Changes - -We may update this policy to reflect practice or legal changes. We'll notify you of significant changes via: - -- App notifications -- Website announcements -- Email (if provided) - -Continued use means you accept the changes. - -## 11. Contact Us - -Questions about privacy or data practices? Contact hello@menlo.ai. diff --git a/website/src/content/docs/jan/quickstart.mdx b/website/src/content/docs/jan/quickstart.mdx deleted file mode 100644 index 25b0cde2e..000000000 --- a/website/src/content/docs/jan/quickstart.mdx +++ /dev/null @@ -1,137 +0,0 @@ ---- -title: QuickStart -description: Get started with Jan and start chatting with AI in minutes. -keywords: - [ - Jan, - local AI, - LLM, - chat, - threads, - models, - download, - installation, - conversations, - ] -banner: - content: | - ๐Ÿ‘‹Jan now supports image ๐Ÿ–ผ๏ธ attachments ๐ŸŽ‰ ---- - -import { Aside } from '@astrojs/starlight/components'; - -Get up and running with Jan in minutes. This guide will help you install Jan, download a model, and start chatting immediately. - -### Step 1: Install Jan - -1. [Download Jan](/download) -2. Install the app ([Mac](/docs/desktop/mac), [Windows](/docs/desktop/windows), [Linux](/docs/desktop/linux)) -3. Launch Jan - -### Step 2: Download Jan v1 - -We recommend starting with **Jan v1**, our 4B parameter model optimized for reasoning and tool calling: - -1. Go to the **Hub Tab** -2. Search for **Jan v1** -3. Choose a quantization that fits your hardware: - - **Q4_K_M** (2.5 GB) - Good balance for most users - - **Q8_0** (4.28 GB) - Best quality if you have the RAM -4. Click **Download** - -![Download Jan v1](../../../assets/download_janv1.png) - - - -### Step 3: Start Chatting - -1. Click the **New Chat** icon -2. Select your model in the input field dropdown -3. Type your message and start chatting - -![Create New Thread](../../../assets/jan_loaded.png) - -Try asking Jan v1 questions like: -- "Explain quantum computing in simple terms" -- "Help me write a Python function to sort a list" -- "What are the pros and cons of electric vehicles?" - - - -## Managing Conversations - -Jan organizes conversations into threads for easy tracking and revisiting. - -### View Chat History - -- **Left sidebar** shows all conversations -- Click any chat to open the full conversation -- **Favorites**: Pin important threads for quick access -- **Recents**: Access recently used threads - -![Favorites and Recents](../../../assets/threads-favorites-and-recents-updated.png) - -### Edit Chat Titles - -1. Hover over a conversation in the sidebar -2. Click the **three dots** icon -3. Click **Rename** -4. Enter new title and save - -![Context Menu](../../../assets/threads-context-menu-updated.png) - -### Delete Threads - - - -**Single thread:** -1. Hover over thread in sidebar -2. Click the **three dots** icon -3. Click **Delete** - -**All threads:** -1. Hover over `Recents` category -2. Click the **three dots** icon -3. Select **Delete All** - -## Advanced Features - -### Custom Assistant Instructions - -Customize how models respond: - -1. Use the assistant dropdown in the input field -2. Or go to the **Assistant tab** to create custom instructions -3. Instructions work across all models - -![Assistant Instruction](../../../assets/assistant-dropdown.png) - -![Add an Assistant Instruction](../../../assets/assistant-edit-dialog.png) - -### Model Parameters - -Fine-tune model behavior: -- Click the **Gear icon** next to your model -- Adjust parameters in **Assistant Settings** -- Switch models via the **model selector** - -![Chat with a Model](../../../assets/model-parameters.png) - -### Connect Cloud Models (Optional) - -Connect to OpenAI, Anthropic, Groq, Mistral, and others: - -1. Open any thread -2. Select a cloud model from the dropdown -3. Click the **Gear icon** beside the provider -4. Add your API key (ensure sufficient credits) - -![Connect Remote APIs](../../../assets/quick-start-03.png) - -For detailed setup, see [Remote APIs](/docs/remote-models/openai). diff --git a/website/src/content/docs/jan/remote-models/anthropic.mdx b/website/src/content/docs/jan/remote-models/anthropic.mdx deleted file mode 100644 index 595590a2c..000000000 --- a/website/src/content/docs/jan/remote-models/anthropic.mdx +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: Anthropic -description: Learn how to integrate Anthropic with Jan for enhanced functionality. -keywords: - [ - Anthropic API, - Jan, - Jan AI, - ChatGPT alternative, - conversational AI, - large language model, - integration, - Anthropic integration, - API integration - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -Jan supports all of [Anthropic's models](https://anthropic.com/) via API integration, allowing -you to chat with Claude's latest Opus, Sonnet and Haiku models. - -## Integrate Anthropic API with Jan - - -### Step 1: Get Your API Key - -1. Visit [Anthropic Console](https://console.anthropic.com/settings/keys) and sign in -2. Create & copy a new API key or copy your existing one - - - -### Step 2: Configure Jan - -1. Navigate to the **Settings** page -2. Under **Model Providers**, select **Anthropic** -3. Insert your **API Key** - -![Anthropic](../../../../assets/model-management-06.png) - -### Step 3: Start Using Anthropic's Models - -1. In any existing **Chat** or create a new one -2. Select an Anthropic model from **model selector** -3. Start chatting - - -## Available Anthropic Models - -Jan automatically includes Anthropic's available models. In case you want to use a specific Anthropic model -that you cannot find in **Jan**, follow instructions in [Add Cloud Models](/docs/manage-models#add-models-1): -- See list of available models in [Anthropic Models](https://docs.anthropic.com/claude/docs/models-overview). -- The `id` property must match the model name in the list. For example, `claude-opus-4@20250514`, `claude-sonnet-4@20250514`, or `claude-3-5-haiku@20241022`. - -## Troubleshooting - -Common issues and solutions: - -**1. API Key Issues** -- Verify your API key is correct and not expired -- Check if you have billing set up on your Anthropic account -- Ensure you have access to the model you're trying to use - -**2. Connection Problems** -- Check your internet connection -- Verify Anthropic's system status -- Look for error messages in [Jan's logs](/docs/troubleshooting#how-to-get-error-logs) - -**3. Model Unavailable** -- Confirm your API key has access to the model -- Check if you're using the correct model ID -- Verify your Anthropic account has the necessary permissions - -Need more help? Join our [Discord community](https://discord.gg/FTk2MvZwJH) or check the -[Anthropic's documentation](https://docs.anthropic.com/claude/docs). diff --git a/website/src/content/docs/jan/remote-models/cohere.mdx b/website/src/content/docs/jan/remote-models/cohere.mdx deleted file mode 100644 index 91ba75b10..000000000 --- a/website/src/content/docs/jan/remote-models/cohere.mdx +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: Cohere -description: Learn how to integrate Cohere with Jan for enhanced functionality. -keywords: - [ - Cohere API, - Jan, - Jan AI, - ChatGPT alternative, - conversational AI, - large language model, - integration, - Cohere integration, - API integration - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -Jan supports [Cohere](https://cohere.com/) API integration, allowing you to use Cohere's -models (Command, Command-R and more) through Jan's interface. - -## Integrate Cohere API with Jan - - -### Step 1: Get Your API Key - -1. Visit [Cohere Dashboard](https://dashboard.cohere.com/api-keys) and sign in -2. Create a new API key and/or copy your existing one - - - -### Step 2: Configure Jan - -1. Navigate to the **Settings** page -2. Under **Model Providers**, select **Cohere** -3. Insert your **API Key** - -![Cohere](../../../../assets/cohere.png) - - -### Step 3: Start Using Cohere's Models - -1. Jump into any existing **Chat** or create a new one -2. Select a Cohere model from **model selector** options -3. Start chatting - - -## Available Cohere Models - -Jan automatically includes Cohere's available models. In case you want to use a specific -Cohere model that you cannot find in **Jan**, follow instructions in [Add Cloud Models](/docs/manage-models): -- See list of available models in [Cohere Documentation](https://docs.cohere.com/v2/docs/models). -- The `id` property must match the model name in the list. For example, `command-nightly` or `command-light`. - -## Troubleshooting - -Common issues and solutions: - -**1. API Key Issues** -- Verify your API key is correct and not expired -- Check if you have billing set up on your Cohere account -- Ensure you have access to the model you're trying to use - -**2. Connection Problems** -- Check your internet connection -- Verify Cohere's [system status](https://status.cohere.com/) -- Look for error messages in [Jan's logs](/docs/troubleshooting#how-to-get-error-logs) - -**3. Model Unavailable** -- Confirm your API key has access to the model -- Check if you're using the correct model ID -- Verify your Cohere account has the necessary permissions - -Need more help? Join our [Discord community](https://discord.gg/FTk2MvZwJH) or check the [Cohere documentation](https://docs.cohere.com). diff --git a/website/src/content/docs/jan/remote-models/google.mdx b/website/src/content/docs/jan/remote-models/google.mdx deleted file mode 100644 index 41aa7ed1c..000000000 --- a/website/src/content/docs/jan/remote-models/google.mdx +++ /dev/null @@ -1,75 +0,0 @@ ---- -title: Google -description: Learn how to integrate Google with Jan for enhanced functionality. -keywords: - [ - Anthropic API, - Jan, - Jan AI, - ChatGPT alternative, - conversational AI, - large language model, - integration, - Anthropic integration, - API integration - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -Jan supports [Google](https://ai.google/get-started/our-models/) API integration, allowing you to use Google models (like Gemini series) through Jan's interface. - -## Integrate Google API with Jan - -### Step 1: Get Your API Key - -1. Visit [Google AI Studio](https://aistudio.google.com/app/apikey) and sign in -2. Create & copy a new API key or copy your existing one - - - -### Step 2: Configure Jan - -1. Navigate to the **Settings** page -2. Under **Model Providers**, select **Gemini** -3. Insert your **API Key** - -![Google](../../../../assets/google.png) - - -### Step 3: Start Using Google's Models - -1. Got to any existing **Chat** or create a new one -2. Select an Gemini model from **model selector** -3. Start chatting - - -## Available Google Models - -Jan automatically includes Google's available models like Gemini series. In case you want to use a specific -Gemini model that you cannot find in **Jan**, follow instructions in [Add Cloud Models](/docs/manage-models#add-models-1): -- See list of available models in [Google Models](https://ai.google.dev/gemini-api/docs/models/gemini). -- The `id` property must match the model name in the list. For example, `gemini-1.5-pro` or `gemini-2.0-flash-lite-preview`. - -## Troubleshooting - -Common issues and solutions: - -**1. API Key Issues** -- Verify your API key is correct and not expired -- Check if you have billing set up on your Google account -- Ensure you have access to the model you're trying to use - -**2. Connection Problems** -- Check your internet connection -- Verify [Gemini's system status](https://www.google.com/appsstatus/dashboard/) -- Look for error messages in [Jan's logs](/docs/troubleshooting#how-to-get-error-logs) - -**3. Model Unavailable** -- Confirm your API key has access to the model -- Check if you're using the correct model ID -- Verify your Google account has the necessary permissions - -Need more help? Join our [Discord community](https://discord.gg/FTk2MvZwJH). diff --git a/website/src/content/docs/jan/remote-models/groq.mdx b/website/src/content/docs/jan/remote-models/groq.mdx deleted file mode 100644 index cd67a63c3..000000000 --- a/website/src/content/docs/jan/remote-models/groq.mdx +++ /dev/null @@ -1,74 +0,0 @@ ---- -title: Groq API -description: Learn how to integrate Groq API with Jan for enhanced functionality. -keywords: - [ - Groq API, - Jan, - Jan AI, - ChatGPT alternative, - conversational AI, - large language model, - integration, - Groq integration, - API integration - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -Jan supports [Groq](https://groq.com/) API integration, allowing you to use Groq's high-performance LLM models (LLaMA 2, Mixtral and more) through Jan's interface. - -## Integrate Groq API with Jan - -### Step 1: Get Your API Key - -1. Visit [Groq Console](https://console.groq.com/keys) and sign in -2. Create & copy a new API key or copy your existing one - - - -### Step 2: Configure Jan - -1. Navigate to the **Settings** page -2. Under **Model Providers**, select **Groq** -3. Insert your **API Key** - -![Groq](../../../../assets/groq.png) - - -### Step 3: Start Using Groq's Models - -1. Jump into any existing **Chat** or create a new one -2. Select a Groq model from **model selector** -3. Start chatting - -## Available Models Through Groq - -Jan automatically includes Groq's available models. In case you want to use a specific Groq model that -you cannot find in **Jan**, follow the instructions in the [Add Cloud Models](/docs/manage-models#add-models-1): -- See list of available models in [Groq Documentation](https://console.groq.com/docs/models). -- The `id` property must match the model name in the list. For example, if you want to use Llama3.3 70B, you must set the `id` property to `llama-3.3-70b-versatile`. - -## Troubleshooting - -Common issues and solutions: - -**1. API Key Issues** -- Verify your API key is correct and not expired -- Check if you have billing set up on your Groq account -- Ensure you have access to the model you're trying to use - -**2. Connection Problems** -- Check your internet connection -- Verify Groq's system status -- Look for error messages in [Jan's logs](/docs/troubleshooting#how-to-get-error-logs) - -**3. Model Unavailable** -- Confirm your API key has access to the model -- Check if you're using the correct model ID -- Verify your Groq account has the necessary permissions - -Need more help? Join our [Discord community](https://discord.gg/FTk2MvZwJH) or check the [Groq documentation](https://console.groq.com/docs). diff --git a/website/src/content/docs/jan/remote-models/huggingface.mdx b/website/src/content/docs/jan/remote-models/huggingface.mdx deleted file mode 100644 index 32100ff41..000000000 --- a/website/src/content/docs/jan/remote-models/huggingface.mdx +++ /dev/null @@ -1,136 +0,0 @@ ---- -title: Hugging Face -description: Learn how to integrate Hugging Face models with Jan using the Router or Inference Endpoints. -keywords: - [ - Hugging Face, - Jan, - Jan AI, - Hugging Face Router, - Hugging Face Inference Endpoints, - Hugging Face API, - Hugging Face Integration, - Hugging Face API Integration - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - - -Jan supports Hugging Face models through two methods: the new **HF Router** (recommended) and **Inference Endpoints**. Both methods require a Hugging Face token and **billing to be set up**. - -![HuggingFace Inference Providers](../../../../assets/hf_providers.png) - -## Option 1: HF Router (Recommended) - -The HF Router provides access to models from multiple providers (Replicate, Together AI, SambaNova, Fireworks, Cohere, and more) through a single endpoint. - -### Step 1: Get Your HF Token - -Visit [Hugging Face Settings > Access Tokens](https://huggingface.co/settings/tokens) and create a token. Make sure you have billing set up on your account. - -### Step 2: Configure Jan - -1. Go to **Settings** > **Model Providers** > **HuggingFace** -2. Enter your HF token -3. Use this URL: `https://router.huggingface.co/v1` - -![Jan HF Setup](../../../../assets/hf_jan_setup.png) - -You can find out more about the HF Router [here](https://huggingface.co/docs/inference-providers/index). - -### Step 3: Start Using Models - -Jan comes with three HF Router models pre-configured. Select one and start chatting immediately. - - - -## Option 2: HF Inference Endpoints - -For more control over specific models and deployment configurations, you can use Hugging Face Inference Endpoints. - -### Step 1: Navigate to the HuggingFace Model Hub - -Visit the [Hugging Face Model Hub](https://huggingface.co/models) (make sure you are logged in) and pick the model you want to use. - -![HuggingFace Model Hub](../../../../assets/hf_hub.png) - -### Step 2: Configure HF Inference Endpoint and Deploy - -After you have selected the model you want to use, click on the **Deploy** button and select a deployment method. We will select HF Inference Endpoints for this one. - -![HuggingFace Deployment](../../../../assets/hf_jan_nano.png) - -This will take you to the deployment set up page. For this example, we will leave the default settings as they are under the GPU tab and click on **Create Endpoint**. - -![HuggingFace Deployment](../../../../assets/hf_jan_nano_2.png) - -Once your endpoint is ready, test that it works on the **Test your endpoint** tab. - -![HuggingFace Deployment](../../../../assets/hf_jan_nano_3.png) - -If you get a response, you can click on **Copy** to copy the endpoint URL and API key. - - - -### Step 3: Configure Jan - -If you do not have an API key you can create one under **Settings** > **Access Tokens** [here](https://huggingface.co/settings/tokens). Once you finish, copy the token and add it to Jan alongside your endpoint URL at **Settings** > **Model Providers** > **HuggingFace**. - -**3.1 HF Token** -![Get Token](../../../../assets/hf_jan_nano_5.png) - -**3.2 HF Endpoint URL** -![Endpoint URL](../../../../assets/hf_jan_nano_4.png) - -**3.3 Jan Settings** -![Jan Settings](../../../../assets/hf_jan_nano_6.png) - - - -**3.4 Add Model Details** -![Add Model Details](../../../../assets/hf_jan_nano_7.png) - -### Step 4: Start Using the Model - -Now you can start using the model in any chat. - -![Start Using the Model](../../../../assets/hf_jan_nano_8.png) - -If you want to learn how to use Jan Nano with MCP, check out [the guide here](../jan-models/jan-nano-32). - -## Available Hugging Face Models - -**Option 1 (HF Router):** Access to models from multiple providers as shown in the providers image above. - -**Option 2 (Inference Endpoints):** You can follow the steps above with a large amount of models on Hugging Face and bring them to Jan. Check out other models in the [Hugging Face Model Hub](https://huggingface.co/models). - -## Troubleshooting - -Common issues and solutions: - -**1. Started a chat but the model is not responding** -- Verify your API_KEY/HF_TOKEN is correct and not expired -- Ensure you have billing set up on your HF account -- For Inference Endpoints: Ensure the model you're trying to use is running again since, after a while, they go idle so that you don't get charged when you are not using it - -![Model Running](../../../../assets/hf_jan_nano_9.png) - -**2. Connection Problems** -- Check your internet connection -- Verify Hugging Face's system status -- Look for error messages in [Jan's logs](/docs/troubleshooting#how-to-get-error-logs) - -**3. Model Unavailable** -- Confirm your API key has access to the model -- Check if you're using the correct model ID -- Verify your Hugging Face account has the necessary permissions - -Need more help? Join our [Discord community](https://discord.gg/FTk2MvZwJH) or check the -[Hugging Face's documentation](https://docs.huggingface.co/en/inference-endpoints/index). diff --git a/website/src/content/docs/jan/remote-models/mistralai.mdx b/website/src/content/docs/jan/remote-models/mistralai.mdx deleted file mode 100644 index f2a6bbaab..000000000 --- a/website/src/content/docs/jan/remote-models/mistralai.mdx +++ /dev/null @@ -1,77 +0,0 @@ ---- -title: Mistral AI API -description: A step-by-step guide on integrating Jan with Mistral AI. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - Mistral integration, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -Jan supports all models available via the [Mistral AI](https://mistral.ai/) API, allowing you to use Mistral's -powerful models (Mistral Large, Mistral Medium, Mistral Small and more) through Jan's interface. - -## Integrate Mistral AI with Jan - -### Step 1: Get Your API Key - -1. Visit the [Mistral AI Platform](https://console.mistral.ai/api-keys/) and sign in -2. Create & copy a new API key or copy your existing one - - - -### Step 2: Configure Jan - -1. Navigate to the **Settings** page -2. Under **Model Providers**, select **Mistral AI** -3. Insert your **API Key** - -![Mistral](../../../../assets/mistralai.png) - -### Step 3: Start Using Mistral's Models - -1. Open any existing **Chat** or create a new one -2. Select a Mistral model from **model selector** -3. Start chatting - - -## Available Mistral Models - -Jan automatically includes Mistral's available models. In case you want to use a specific Mistral model -that you cannot find in **Jan**, follow the instructions in [Add Cloud Models](/docs/manage-models#add-models-1): -- See list of available models in [Mistral AI Documentation](https://docs.mistral.ai/platform/endpoints). -- The `id` property must match the model name in the list. For example, if you want to use -Mistral Large, you must set the `id` property to `mistral-large-latest` - -## Troubleshooting - -Common issues and solutions: - -**1. API Key Issues** -- Verify your API key is correct and not expired -- Check if you have billing set up on your Mistral AI account -- Ensure you have access to the model you're trying to use - -**2. Connection Problems** -- Check your internet connection -- Verify Mistral AI's system status -- Look for error messages in [Jan's logs](/docs/troubleshooting#how-to-get-error-logs) - -**3. Model Unavailable** -- Confirm your API key has access to the model -- Check if you're using the correct model ID -- Verify your Mistral AI account has the necessary permissions - -Need more help? Join our [Discord community](https://discord.gg/FTk2MvZwJH) or check the [Mistral AI documentation](https://docs.mistral.ai/). diff --git a/website/src/content/docs/jan/remote-models/openai.mdx b/website/src/content/docs/jan/remote-models/openai.mdx deleted file mode 100644 index f1eb33ba5..000000000 --- a/website/src/content/docs/jan/remote-models/openai.mdx +++ /dev/null @@ -1,81 +0,0 @@ ---- -title: OpenAI API -description: A step-by-step guide on integrating Jan with Azure OpenAI. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - integration, - Azure OpenAI Service, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -Jan supports most [OpenAI](https://openai.com/) as well as the many OpenAI-compatible APIs out there, -allowing you to use all models from OpenAI (GPT-4o, o3 and even those from Together AI, DeepSeek, Fireworks -and more) through Jan's interface. - -## Integrate OpenAI API with Jan - -### Step 1: Get Your API Key -1. Visit the [OpenAI Platform](https://platform.openai.com/api-keys) and sign in -2. Create & copy a new API key or copy your existing one - - - -### Step 2: Configure Jan - -1. Navigate to the **Settings** page -2. Under Remote Engines, select OpenAI -3. Insert your API Key - -![OpenAI](../../../../assets/openai.png) - - -### Step 3: Start Using OpenAI's Models - -In any existing Threads or create a new one -Select an OpenAI model from model selector -Start chatting - - -## Available OpenAI Models - -Jan automatically includes popular OpenAI models. In case you want to use a specific model that you -cannot find in Jan, follow instructions in [Add Cloud Models](/docs/manage-models#add-models-1): -- See list of available models in [OpenAI Platform](https://platform.openai.com/docs/models/overview). -- The id property must match the model name in the list. For example, if you want to use the -[GPT-4.5](https://platform.openai.com/docs/models/), you must set the id property -to respective one. - -## Troubleshooting - -Common issues and solutions: - -1. API Key Issues -- Verify your API key is correct and not expired -- Check if you have billing set up on your OpenAI account -- Ensure you have access to the model you're trying to use - -2. Connection Problems -- Check your internet connection -- Verify OpenAI's [system status](https://status.openai.com) -- Look for error messages in [Jan's logs](/docs/troubleshooting#how-to-get-error-logs) - -3. Model Unavailable -- Confirm your API key has access to the model -- Check if you're using the correct model ID -- Verify your OpenAI account has the necessary permissions - -Need more help? Join our [Discord community](https://discord.gg/FTk2MvZwJH) or check the -[OpenAI documentation](https://platform.openai.com/docs). diff --git a/website/src/content/docs/jan/remote-models/openrouter.mdx b/website/src/content/docs/jan/remote-models/openrouter.mdx deleted file mode 100644 index 614bc58e6..000000000 --- a/website/src/content/docs/jan/remote-models/openrouter.mdx +++ /dev/null @@ -1,90 +0,0 @@ ---- -title: OpenRouter -description: A step-by-step guide on integrating Jan with OpenRouter. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - OpenRouter integration, - OpenRouter, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -## Integrate OpenRouter with Jan - -[OpenRouter](https://openrouter.ai/) is a tool that gathers AI model APIs and provides access to all -via a unified API. Developers can use the API to interact with LLMs, generative image models, and -even models that generate 3D objects, all with a competitive pricing. - -Jan supports the OpenRouter API, allowing you to use models from various providers (Anthropic, Google, -Meta and more) and helping you avoid having to get an API from all of your favorite ones. - -OpenRouter even offers a few free models! ๐Ÿ™Œ - -## Integrate OpenRouter with Jan - -### Step 1: Get Your API Key -1. Visit [OpenRouter](https://openrouter.ai/keys) and sign in -2. Create & copy a new API key or copy your existing one - - - -### Step 2: Configure Jan - -1. Navigate to the **Settings** page -2. Under **Model Providers**, select **OpenRouter** -3. Insert your **API Key** - -![OpenRouter](../../../../assets/openrouter.png) - -### Step 3: Start Using OpenRouter Models - -1. Pick any existing **Chat** or create a new one -2. Select any model from **model selector** under OpenRouter -3. Start chatting - -## Available Models Through OpenRouter - -Jan automatically use your default OpenRouter's available models. For custom configurations: - -**Model Field Settings:** -- Leave empty to use your account's default model -- Specify a model using the format: `organization/model-name` -- Available options can be found in [OpenRouter's Model Reference](https://openrouter.ai/models) - -**Examples of Model IDs:** -- Claude 4 Opus: `anthropic/claude-opus-4` -- Google Gemini 2.5 Pro: `google/gemini-2.5-pro-preview` -- DeepSeek R1 Latest: `deepseek/deepseek-r1-0528` - -## Troubleshooting - -Common issues and solutions: - -**1. API Key Issues** -- Verify your API key is correct and not expired -- Check if you have sufficient credits in your OpenRouter account -- Ensure you have access to the model you're trying to use - -**2. Connection Problems** -- Check your internet connection -- Verify OpenRouter's [system status](https://status.openrouter.ai) -- Look for error messages in [Jan's logs](/docs/troubleshooting#how-to-get-error-logs) - -**3. Model Unavailable** -- Confirm the model is currently available on OpenRouter -- Check if you're using the correct model ID format -- Verify the model provider is currently operational - -Need more help? Join our [Discord community](https://discord.gg/FTk2MvZwJH) or check the [OpenRouter documentation](https://openrouter.ai/docs). diff --git a/website/src/content/docs/jan/settings.mdx b/website/src/content/docs/jan/settings.mdx deleted file mode 100644 index baba03570..000000000 --- a/website/src/content/docs/jan/settings.mdx +++ /dev/null @@ -1,215 +0,0 @@ ---- -title: Settings -description: Explore how to adjust Jan's settings to suit your specific requirements. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - Advanced Settings, - HTTPS Proxy, - SSL, - settings, - Jan settings, - ] ---- - -import { Aside } from '@astrojs/starlight/components'; - -To access the **Settings**, click icon in the bottom left corner of Jan. - -## Model Management - -Manage your installed AI models in **Settings** > **Model Providers**: - -### Import Models -- **From Hugging Face:** - - Enter a model's Hugging Face ID (e.g., `org/model_name_or_id`) in the Hub's search bar. - - **Note:** Some models require a Hugging Face Access Token. Enter your token in **Settings > Model Providers > Hugging Face**. -- **From Local Files:** - - Click **Import Model** and select your GGUF files. - -### Remove Models - -- Click the trash icon next to the **Start** button and then click **Delete**. - -### Start Models - -1. Open a new chat and select the model you want to start. -2. Click the **Start** button on the **Settings > Model Providers** - -### Hugging Face Access Token -To download models from Hugging Face that require authentication, for example, like the llama models from meta: -1. Get your token from [Hugging Face Tokens](https://huggingface.co/docs/hub/en/security-tokens) -2. Enter it in **Settings > Model Providers > Hugging Face**. - -## Model Settings (Gear Icon) - -![Model Settings](../../../assets/trouble-shooting-04.png) - -Click the gear icon next to a model to configure advanced settings: -- **Context Size**: Maximum prompt context length -- **GPU Layers**: Number of model layers to offload to GPU. If you have an NVIDIA GPU and notice that your model won't fully load in it, you can reduce this value to load smaller parts of the model and try again. -- **Temperature**: Controls randomness (higher = more random) -- **Top K**: Limits token selection to K most likely next tokens (smaller K = more focused responses) -- **Top P**: Limits token selection to tokens comprising P probability mass (smaller P = more focused responses) -- **Min P**: Sets a minimum threshold for words the model can select (higher values filter out less likely words) -- **Repeat Last N**: Determines how many recent words the model checks to avoid repetition -- **Repeat Penalty**: Controls how strongly the model avoids repeating phrases (higher values reduce repetition) -- **Presence Penalty**: Discourages reusing words that already appeared in the text (helps with variety) - -_See [Model Parameters](/docs/model-parameters) for a more detailed explanation._ - - -## Hardware - -Monitor and manage system resources at **Settings > Hardware**: -- **CPU, RAM, GPU**: View usage and specs -- **GPU Acceleration**: Enable/disable and configure GPU settings - -![Hardware](../../../assets/hardware.png) - - -## Preferences - -### Appearance & Theme - -Control the visual theme of Jan's interface with any color combo you'd like. You can also control the color use in the code blocks. - -![Appearance](../../../assets/settings-04.png) - -### Spell Check - -Jan includes a built-in spell check feature to help catch typing errors in your messages. - -![Spell Check](../../../assets/settings-06.png) - -## Privacy - -At **Settings** > **Privacy**, you can control anonymous analytics in Jan: - -### Analytics -Jan is built with privacy at its core. By default, no data is collected. Everything stays local on your device. -You can help improve Jan by sharing anonymous usage data: -1. Toggle on **Analytics** to share anonymous data -2. You can change this setting at any time - - - -![Analytics](../../../assets/settings-07.png) - -### Log Management - -**1. View Logs** -- Logs are stored at: - - App log: `~/Library/Application\ Support/jan/data/logs/app.log` - - Cortex log: `~/Library/Application\ Support/jan/data/logs/cortex.log` -- To open logs from Jan's interface: at **Logs**, click icon to open App Logs & Cortex Logs: - -![View Logs](../../../assets/settings-08.png) - -**2. Clear Logs** - -Jan retains your logs for only **24 hours**. To remove all logs from Jan, at **Clear Logs**, click the **Clear** button: - - - -![Clear Logs](../../../assets/settings-09.png) - - -### Jan Data Folder -Jan stores your data locally in your own filesystem in a universal file format. See detailed [Jan Folder Structure](./data-folder#folder-structure). - -**1. Open Jan Data Folder** - -At **Jan Data Folder**, click icon to open Jan application's folder: - -![Open Jan Data Folder](../../../assets/settings-11.png) - -**2. Edit Jan Data Folder** - -1. At **Jan Data Folder** icon to edit Jan application's folder -2. Choose a new directory & click **Select**, make sure the new folder is empty -3. Confirmation pop-up shows up: - -> Are you sure you want to relocate Jan Data Folder to `new directory`? -Jan Data Folder will be duplicated into the new location while the original folder remains intact. -An app restart will be required afterward. - -4. Click **Yes, Proceed** - -![Edit Jan Data Folder](../../../assets/settings-12.png) - -### HTTPs Proxy - -HTTPS Proxy encrypts data between your browser and the internet, making it hard for outsiders to intercept -or read. It also helps you maintain your privacy and security while bypassing regional restrictions on the internet. - - - -1. **Enable** the proxy toggle -2. Enter your proxy server details in the following format: - -``` -http://:@: -``` -Where: -- ``: Your proxy username (if authentication is required) -- ``: Your proxy password (if authentication is required) -- ``: Your proxy server's domain name or IP address -- ``: The port number for the proxy server - -![HTTPs Proxy](../../../assets/settings-13.png) - -**Ignore SSL Certificates** - -This setting allows Jan to accept self-signed or unverified SSL certificates. This may be necessary when: -- Working with corporate proxies using internal certificates -- Testing in development environments -- Connecting through specialized network security setups - - - -![Ignore SSL Certificates](../../../assets/settings-14.png) - -### Factory Reset - -Reset to Factory Settings restores Jan to its initial state by erasing all user data, including downloaded -models and chat history. This action is irreversible and should only be used as a last resort when experiencing -serious application issues. - - - -Only use factory reset if: -- The application is corrupted -- You're experiencing persistent technical issues that other solutions haven't fixed -- You want to completely start fresh with a clean installation - -To begin the process: -1. At **Reset to Factory Settings**, click **Reset** button - -![Jan Quick Ask](../../../assets/settings-17.png) - -2. In the confirmation dialog: -- Type the word **RESET** to confirm -- Optionally check **Keep the current app data location** to maintain the same data folder -- Click **Reset Now** -3. App restart is required upon confirmation -![Jan Quick Ask](../../../assets/settings-18.png) diff --git a/website/src/content/docs/jan/troubleshooting.mdx b/website/src/content/docs/jan/troubleshooting.mdx deleted file mode 100644 index d2d417ad0..000000000 --- a/website/src/content/docs/jan/troubleshooting.mdx +++ /dev/null @@ -1,344 +0,0 @@ ---- -title: Troubleshooting -description: Fix common issues and optimize Jan's performance with this comprehensive guide. -keywords: - [ - Jan, - troubleshooting, - error fixes, - performance issues, - GPU problems, - installation issues, - common errors, - local AI, - technical support, - ] ---- - -import { Tabs, TabItem } from '@astrojs/starlight/components'; -import { Aside } from '@astrojs/starlight/components'; -import { Steps } from '@astrojs/starlight/components'; - -## Getting Help: Error Logs - -When Jan isn't working properly, error logs help identify the problem. Here's how to get them: - -### Quick Access to Logs - -**In Jan Interface:** -1. Look for **System Monitor** in the footer -2. Click **App Log** - -![App log](../../../assets/trouble-shooting-02.png) - -**Via Terminal:** - - - - -**Application Logs:** -```bash -tail -n 50 ~/Library/Application\ Support/Jan/data/logs/app.log -``` - -**Server Logs:** -```bash -tail -n 50 ~/Library/Application\ Support/Jan/data/logs/cortex.log -``` - - - - -**Application Logs:** -```cmd -type %APPDATA%\Jan\data\logs\app.log -``` - -**Server Logs:** -```cmd -type %APPDATA%\Jan\data\logs\cortex.log -``` - - - - - - -## Common Issues & Solutions - -### Jan Won't Start (Broken Installation) - -If Jan gets stuck after installation or won't start properly: - - - - -**Clean Reinstall Steps:** - -1. **Uninstall Jan** from Applications folder - -2. **Delete all Jan data:** -```bash -rm -rf ~/Library/Application\ Support/Jan -``` - -3. **Kill any background processes** (for versions before 0.4.2): -```bash -ps aux | grep nitro -# Find process IDs and kill them: -kill -9 -``` - -4. **Download fresh copy** from [jan.ai](/download) - - - - -**Clean Reinstall Steps:** - -1. **Uninstall Jan** via Control Panel - -2. **Delete application data:** -```cmd -cd C:\Users\%USERNAME%\AppData\Roaming -rmdir /S Jan -``` - -3. **Kill background processes** (for versions before 0.4.2): -```cmd -# Find nitro processes -tasklist | findstr "nitro" -# Kill them by PID -taskkill /F /PID -``` - -4. **Download fresh copy** from [jan.ai](/download) - - - - -**Clean Reinstall Steps:** - -1. **Uninstall Jan:** -```bash -# For Debian/Ubuntu -sudo apt-get remove jan - -# For AppImage - just delete the file -``` - -2. **Delete application data:** -```bash -# Default location -rm -rf ~/.config/Jan - -# Or custom location -rm -rf $XDG_CONFIG_HOME/Jan -``` - -3. **Kill background processes** (for versions before 0.4.2): -```bash -ps aux | grep nitro -kill -9 -``` - -4. **Download fresh copy** from [jan.ai](/download) - - - - - - -### NVIDIA GPU Not Working - -If Jan isn't using your NVIDIA graphics card for acceleration: - -#### Step 1: Verify Hardware and System Requirements - -**Check GPU Detection:** - -*Windows:* Right-click desktop โ†’ NVIDIA Control Panel, or check Device Manager โ†’ Display Adapters - -*Linux:* Run `lspci | grep -i nvidia` - -**Install Required Software:** - -**NVIDIA Driver (470.63.01 or newer):** -1. Download from [nvidia.com/drivers](https://www.nvidia.com/drivers/) -2. Test: Run `nvidia-smi` in terminal - -**CUDA Toolkit (11.7 or newer):** -1. Download from [CUDA Downloads](https://developer.nvidia.com/cuda-downloads) -2. Test: Run `nvcc --version` - -**Linux Additional Requirements:** -```bash -# Install required packages -sudo apt update && sudo apt install gcc-11 g++-11 cpp-11 - -# Set CUDA environment -export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64 -``` - -#### Step 2: Enable GPU Acceleration in Jan - -1. Open **Settings** > **Hardware** -2. Turn on **GPU Acceleration** -3. Check **System Monitor** (footer) to verify GPU is detected - -![Hardware](../../../assets/trouble-shooting-01.png) - -#### Step 3: Verify Configuration - -1. Go to **Settings** > **Advanced Settings** > **Data Folder** -2. Open `settings.json` file -3. Check these settings: - -```json -{ - "run_mode": "gpu", // Should be "gpu" - "nvidia_driver": { - "exist": true, // Should be true - "version": "531.18" - }, - "cuda": { - "exist": true, // Should be true - "version": "12" - }, - "gpus": [ - { - "id": "0", - "vram": "12282" // Your GPU memory in MB - } - ] -} -``` - -#### Step 4: Restart Jan - -Close and restart Jan to apply changes. - -#### Tested Working Configurations - -**Desktop Systems:** -- Windows 11 + RTX 4070Ti + CUDA 12.2 + Driver 531.18 -- Ubuntu 22.04 + RTX 4070Ti + CUDA 12.2 + Driver 545 - -**Virtual Machines:** -- Ubuntu on Proxmox + GTX 1660Ti + CUDA 12.1 + Driver 535 - - - -### "Failed to Fetch" or "Something's Amiss" Errors - -When models won't respond or show these errors: - -**1. Check System Requirements** -- **RAM:** Use models under 80% of available memory - - 8GB system: Use models under 6GB - - 16GB system: Use models under 13GB -- **Hardware:** Verify your system meets [minimum requirements](/docs/desktop/) - -**2. Adjust Model Settings** -- Open model settings in the chat sidebar -- Lower the **GPU Layers (ngl)** setting -- Start low and increase gradually - -**3. Check Port Conflicts** -If logs show "Bind address failed": - -```bash -# Check if ports are in use -# macOS/Linux -netstat -an | grep 1337 - -# Windows -netstat -ano | find "1337" -``` - -**Default Jan ports:** -- API Server: `1337` -- Documentation: `3001` - -**4. Try Factory Reset** -1. **Settings** > **Advanced Settings** -2. Click **Reset** under "Reset To Factory Settings" - - - -**5. Clean Reinstall** -If problems persist, do a complete clean installation (see "Jan Won't Start" section above). - -### Permission Denied Errors - -If you see permission errors during installation: - -```bash -# Fix npm permissions (macOS/Linux) -sudo chown -R $(whoami) ~/.npm - -# Windows - run as administrator -``` - -### OpenAI API Issues ("Unexpected Token") - -For OpenAI connection problems: - -**1. Verify API Key** -- Get valid key from [OpenAI Platform](https://platform.openai.com/) -- Ensure sufficient credits and permissions - -**2. Check Regional Access** -- Some regions have API restrictions -- Try using a VPN from a supported region -- Test network connectivity to OpenAI endpoints - -### Performance Issues - -**Models Running Slowly:** -- Enable GPU acceleration (see NVIDIA section) -- Use appropriate model size for your hardware -- Close other memory-intensive applications -- Check Task Manager/Activity Monitor for resource usage - -**High Memory Usage:** -- Switch to smaller model variants -- Reduce context length in model settings -- Enable model offloading in engine settings - -**Frequent Crashes:** -- Update graphics drivers -- Check system temperature -- Reduce GPU layers if using GPU acceleration -- Verify adequate power supply (desktop systems) - -## Need More Help? - -If these solutions don't work: - -**1. Gather Information:** -- Copy your error logs (see top of this page) -- Note your system specifications -- Describe what you were trying to do when the problem occurred - -**2. Get Community Support:** -- Join our [Discord](https://discord.com/invite/FTk2MvZwJH) -- Post in the **#๐Ÿ†˜|jan-help** channel -- Include your logs and system info - -**3. Check Resources:** -- [System requirements](./installation) -- [Model compatibility guides](./manage-models) -- [Hardware setup guides](./installation) - - diff --git a/website/src/content/docs/local-server/api-server.mdx b/website/src/content/docs/local-server/api-server.mdx deleted file mode 100644 index 491c31db9..000000000 --- a/website/src/content/docs/local-server/api-server.mdx +++ /dev/null @@ -1,100 +0,0 @@ ---- -title: Local API Server -description: Run Jan's OpenAI-compatible API server on your local machine for private, offline AI development. -keywords: - [ - Jan, - local AI server, - OpenAI API, - local API, - self-hosted AI, - offline AI, - privacy-focused AI, - API integration, - local LLM server, - llama.cpp, - CORS, - API key - ] ---- -import { Aside, Steps } from '@astrojs/starlight/components' - -Jan provides a built-in, OpenAI-compatible API server that runs entirely on your computer, powered by `llama.cpp`. Use it as a drop-in replacement for cloud APIs to build private, offline-capable AI applications. - -![Jan's Local API Server Settings UI](../../../assets/api-server-ui.png) - -## Quick Start - -### Start the Server -1. Navigate to **Settings** > **Local API Server**. -2. Enter a custom **API Key** (e.g., `secret-key-123`). This is required for all requests. -3. Click **Start Server**. - -The server is ready when the logs show `JAN API listening at http://127.0.0.1:1337`. - -### Test with cURL -Open a terminal and make a request. Replace `YOUR_MODEL_ID` with the ID of an available model in Jan. - -```bash -curl http://127.0.0.1:1337/v1/chat/completions \ - -H "Content-Type: application/json" \ - -H "Authorization: Bearer secret-key-123" \ - -d '{ - "model": "YOUR_MODEL_ID", - "messages": [{"role": "user", "content": "Tell me a joke."}] - }' -``` - -## Server Configuration - -These settings control the network accessibility and basic behavior of your local server. - -### Server Host -The network address the server listens on. -- **`127.0.0.1`** (Default): The server is only accessible from your own computer. This is the most secure option for personal use. -- **`0.0.0.0`**: The server is accessible from other devices on your local network (e.g., your phone or another computer). Use this with caution. - -### Server Port -The port number for the API server. -- **`1337`** (Default): A common alternative port. -- You can change this to any available port number (e.g., `8000`). - -### API Prefix -The base path for all API endpoints. -- **`/v1`** (Default): Follows OpenAI's convention. The chat completions endpoint would be `http://127.0.0.1:1337/v1/chat/completions`. -- You can change this or leave it empty if desired. - -### API Key -A mandatory secret key to authenticate requests. -- You must set a key. It can be any string (e.g., `a-secure-password`). -- All API requests must include this key in the `Authorization: Bearer YOUR_API_KEY` header. - -### Trusted Hosts -A comma-separated list of hostnames allowed to access the server. This provides an additional layer of security when the server is exposed on your network. - -### Request timeout -Request timeout for local model response in seconds. -- **`600`** (Default): You can change this to any suitable value. - -## Advanced Settings - -### Cross-Origin Resource Sharing (CORS) -- **(Enabled by default)** Allows web applications (like a custom web UI you are building) running on different domains to make requests to the API server. -- **Disable this** if your API will only be accessed by non-browser-based applications (e.g., scripts, command-line tools) for slightly improved security. - -### Verbose Server Logs -- **(Enabled by default)** Provides detailed, real-time logs of all incoming requests, responses, and server activity. -- This is extremely useful for debugging application behavior and understanding exactly what is being sent to the models. - -## Troubleshooting - - - -- **Connection Refused:** The server is not running, or your application is pointing to the wrong host or port. -- **401 Unauthorized:** Your API Key is missing from the `Authorization` header or is incorrect. -- **404 Not Found:** - - The `model` ID in your request body does not match an available model in Jan. - - Your request URL is incorrect (check the API Prefix). -- **CORS Error (in a web browser):** Ensure the CORS toggle is enabled in Jan's settings. diff --git a/website/src/content/docs/local-server/index.mdx b/website/src/content/docs/local-server/index.mdx deleted file mode 100644 index 76c7de6b7..000000000 --- a/website/src/content/docs/local-server/index.mdx +++ /dev/null @@ -1,114 +0,0 @@ ---- -title: Local API Server -description: Build AI applications with Jan's OpenAI-compatible API server. ---- - -import { Aside, LinkCard } from '@astrojs/starlight/components'; - -Jan provides an OpenAI-compatible API server that runs entirely on your computer. Use the same API patterns you know from OpenAI, but with complete control over your models and data. - -## Features - -- **OpenAI-compatible** - Drop-in replacement for OpenAI API -- **Local models** - Run GGUF models via llama.cpp -- **Cloud models** - Proxy to OpenAI, Anthropic, and others -- **Privacy-first** - Local models never send data externally -- **No vendor lock-in** - Switch between providers seamlessly - -## Quick Start - -Start the server in **Settings > Local API Server** and make requests to `http://localhost:1337/v1`: - -```bash -curl http://localhost:1337/v1/chat/completions \ - -H "Content-Type: application/json" \ - -H "Authorization: Bearer YOUR_API_KEY" \ - -d '{ - "model": "MODEL_ID", - "messages": [{"role": "user", "content": "Hello!"}] - }' -``` - -## Documentation - -- [**API Reference**](/api) - Interactive API documentation with Try It Out -- [**API Configuration**](./api-server) - Server settings, authentication, CORS -- [**Engine Settings**](./llama-cpp) - Configure llama.cpp for your hardware -- [**Server Settings**](./settings) - Advanced configuration options - - - -## Integration Examples - -### Continue (VS Code) -```json -{ - "models": [{ - "title": "Jan", - "provider": "openai", - "baseURL": "http://localhost:1337/v1", - "apiKey": "YOUR_API_KEY", - "model": "MODEL_ID" - }] -} -``` - -### Python (OpenAI SDK) -```python -from openai import OpenAI - -client = OpenAI( - base_url="http://localhost:1337/v1", - api_key="YOUR_API_KEY" -) - -response = client.chat.completions.create( - model="MODEL_ID", - messages=[{"role": "user", "content": "Hello!"}] -) -``` - -### JavaScript/TypeScript -```javascript -const response = await fetch('http://localhost:1337/v1/chat/completions', { - method: 'POST', - headers: { - 'Content-Type': 'application/json', - 'Authorization': 'Bearer YOUR_API_KEY' - }, - body: JSON.stringify({ - model: 'MODEL_ID', - messages: [{ role: 'user', content: 'Hello!' }] - }) -}); -``` - -## Supported Endpoints - -| Endpoint | Description | -|----------|-------------| -| `/v1/chat/completions` | Chat completions (streaming supported) | -| `/v1/models` | List available models | -| `/v1/models/{id}` | Get model information | - - - -## Why Use Jan's API? - -**Privacy** - Your data stays on your machine with local models -**Cost** - No API fees for local model usage -**Control** - Choose your models, parameters, and hardware -**Flexibility** - Mix local and cloud models as needed - -## Related Resources - -- [Models Overview](/docs/jan/manage-models) - Available models -- [Data Storage](/docs/jan/data-folder) - Where Jan stores data -- [Troubleshooting](/docs/jan/troubleshooting) - Common issues -- [GitHub Repository](https://github.com/janhq/jan) - Source code diff --git a/website/src/content/docs/local-server/integrations/continue-dev.mdx b/website/src/content/docs/local-server/integrations/continue-dev.mdx deleted file mode 100644 index 6be87d943..000000000 --- a/website/src/content/docs/local-server/integrations/continue-dev.mdx +++ /dev/null @@ -1,97 +0,0 @@ ---- -title: Continue.dev -description: A step-by-step guide on integrating Jan with Continue and VS Code. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - Continue integration, - VSCode integration, - ] ---- - -import { Tabs, TabItem } from '@astrojs/starlight/components'; - -## Integrate with Continue VS Code - -[Continue](https://continue.dev/docs/intro) is an open-source autopilot compatible with Visual Studio Code and JetBrains, offering the simplest method to code with any LLM (Local Language Model). - -To integrate Jan with a local AI language model, follow the steps below: - -1. **Installing Continue on Visual Studio Code** - - Follow this [guide](https://continue.dev/docs/quickstart) to install the Continue extension on Visual Studio Code. -2. **Enable the Jan API Server** - To set up Continue for use with Jan's Local Server, you must activate the Jan API Server with your chosen model. - 1. Press the `โš™๏ธ Settings` button. - 2. Locate `Local API Server`. - 3. Setup the server, which includes the **IP Port**, **Cross-Origin-Resource-Sharing (CORS)** and **Verbose Server Logs**. - 4. Include your user-defined API Key. - 5. Press the **Start Server** button -3. **Configure Continue to Use Jan's Local Server** - 1. Go to the `~/.continue` directory. - - - ```bash - cd ~/.continue - ``` - - - ```bash - C:/Users//.continue - ``` - - - ```bash - cd ~/.continue - ``` - - - - ```yaml title="~/.continue/config.yaml" - name: Local Assistant - version: 1.0.0 - schema: v1 - models: - - name: Jan - provider: openai - model: #MODEL_NAME (e.g. qwen3:0.6b) - apiKey: #YOUR_USER_DEFINED_API_KEY_HERE (e.g. hello) - apiBase: http://localhost:1337/v1 - context: - - provider: code - - provider: docs - - provider: diff - - provider: terminal - - provider: problems - - provider: folder - - provider: codebase - ``` - 2. Ensure the file has the following configurations: - - Ensure `openai` is selected as the `provider`. - - Match the `model` with the one enabled in the Jan API Server. - - Set `apiBase` to `http://localhost:1337/v1`. -4. **Ensure the Using Model Is Activated in Jan** - 1. Navigate to `Settings` > `Model Providers`. - 2. Under Llama.cpp, find the model that you would want to use. - 3. Select the **Start Model** button to activate the model. - -## Use Jan with Continue in Visual Studio Code - -### 1. Exploring Code with Jan - -1. Highlight a code. -2. Press `Command + Shift + M` to open the Left Panel. -3. Click "Jan" at the bottom of the panel and submit your query, such as `Explain this code`. - -### 2. Enhancing Code with the Help of a Large Language Model - -1. Select a code snippet. -2. Press `Command + Shift + L`. -3. Type in your specific request, for example, `Add comments to this code`. diff --git a/website/src/content/docs/local-server/integrations/llmcord.mdx b/website/src/content/docs/local-server/integrations/llmcord.mdx deleted file mode 100644 index 4724e2d27..000000000 --- a/website/src/content/docs/local-server/integrations/llmcord.mdx +++ /dev/null @@ -1,63 +0,0 @@ ---- -title: llmcord (Discord) -description: A step-by-step guide on integrating Jan with a Discord bot. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - Discord integration, - Discord, - bot, - ] ---- - -import { Aside, Steps } from '@astrojs/starlight/components'; - -## Integrate llmcord.py with Jan - -[llmcord.py](https://github.com/jakobdylanc/discord-llm-chatbot) lets you and your friends chat with LLMs directly in your Discord server. - -To integrate Jan with llmcord.py, follow the steps below: - - - -1. **Clone the Repository** - Clone the discord bot's [repository](https://github.com/jakobdylanc/discord-llm-chatbot) by using the following command: - ```bash - git clone https://github.com/jakobdylanc/discord-llm-chatbot.git - ``` -2. **Install the Required Libraries** - After cloning the repository, run the following command: - ```bash - pip install -r requirements.txt - ``` - -3. **Set the Environment** - 1. Create a copy of `.env.example`. - 2. Change the name to `.env`. - 3. Set the environment with the following options: - - | Setting | Instructions | - | :----------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | - | `DISCORD_BOT_TOKEN` | Create a new Discord bot at [discord.com/developers/applications](https://discord.com/developers/applications), obtain a token from the Bot tab, and enable MESSAGE CONTENT INTENT. | - | `DISCORD_CLIENT_ID` | Found under the OAuth2 tab of the Discord bot you just made. | - | `LLM` | For Jan, set to `local/openai/(MODEL_NAME)`, where `(MODEL_NAME)` is your loaded model's name. | - | `LLM_SYSTEM_PROMPT` | Adjust the bot's behavior as needed. | - | `LOCAL_SERVER_URL` | URL of your local API server. For Jan, set it to `http://localhost:1337/v1`. | - - For more configuration options, refer to llmcord.py's [README](https://github.com/jakobdylanc/discord-llm-chatbot/tree/main?tab=readme-ov-file#instructions). -4. **Run the Bot** - Run the bot by using the following command in your command prompt: - ```bash - python llmcord.py - ``` - The bot's invite URL will be printed in the console. Use it to add the bot to your server. - - diff --git a/website/src/content/docs/local-server/integrations/n8n.mdx b/website/src/content/docs/local-server/integrations/n8n.mdx deleted file mode 100644 index 80b89a0b5..000000000 --- a/website/src/content/docs/local-server/integrations/n8n.mdx +++ /dev/null @@ -1,72 +0,0 @@ ---- -title: n8n -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - n8n integration, - n8n, - ] -description: A step-by-step guide on integrating Jan with n8n. ---- - -import { Steps } from '@astrojs/starlight/components'; - -## Integrate n8n with Jan - -[n8n](https://n8n.io/) is an open-source workflow automation tool that allows you to connect to more than 400+ integrations and services to automate repetitive tasks. With its visual interface, you can create complex workflows conveniently. To integrate n8n with Jan, follow the steps below: - - -1. **Run your preferred model with Jan server** - 1. Open Jan app. - 2. Go to the **Hub** and download your preferred model - 3. Run the Jan server -2. **Start n8n service** - Start n8n immediately using npx: - ```sh - npx n8n - ``` - - Or deploy with Docker: - ```sh - docker run -it --rm --name n8n -p 5678:5678 docker.n8n.io/n8nio/n8n - ``` -3. **Integrate Jan with n8n service using HTTP Request** - Integrate Jan by selecting the HTTP Request node in n8n and importing the following cURL command: - - ```bash - curl -X 'POST' \ - 'http://127.0.0.1:1337/v1/chat/completions' \ - -H 'accept: application/json' \ - -H 'Content-Type: application/json' \ - -d '{ - "messages": [ - { - "content": "You are a helpful assistant.", - "role": "system" - }, - { - "content": "Hello!", - "role": "user" - } - ], - "model": "tinyllama-1.1b", - "stream": true, - "max_tokens": 2048, - "stop": [ - "hello" - ], - "frequency_penalty": 0, - "presence_penalty": 0, - "temperature": 0.7, - "top_p": 0.95 - }' - ``` - diff --git a/website/src/content/docs/local-server/integrations/tabby.mdx b/website/src/content/docs/local-server/integrations/tabby.mdx deleted file mode 100644 index 1d69f5635..000000000 --- a/website/src/content/docs/local-server/integrations/tabby.mdx +++ /dev/null @@ -1,88 +0,0 @@ ---- -title: Tabby -description: A step-by-step guide on integrating Jan with Tabby and VSCode, JetBrains, or other IDEs. -keywords: - [ - Jan, - Customizable Intelligence, LLM, - local AI, - privacy focus, - free and open source, - private and offline, - conversational AI, - no-subscription fee, - large language models, - Tabby integration, - VSCode integration, - JetBrains integration, - ] ---- - -import { Steps } from '@astrojs/starlight/components'; - -## Integrate Jan with Tabby and Your Favorite IDEs - -[Tabby](https://www.tabbyml.com/) is an open-source, self-hosted AI coding assistant. -With Tabby, teams can easily set up their own LLM-powered code completion server. - -Tabby provides integrations with VSCode, JetBrains, and other IDEs to help developers code more efficiently, -and it can be used with various LLM services, including Jan. - -To integrate Jan with Tabby, follow these steps: - - - -1. **Enable the Jan API Server** - To set up Tabby with Jan's Local Server, you must activate the Jan API Server with your chosen model. - 1. Click the `Local API Server` (`<>`) button above the Settings. Jan will direct you to the **Local API Server** section. - 2. Configure the server, including the **IP Port**, **Cross-Origin Resource Sharing (CORS)**, and **Verbose Server Logs**. - 3. Press the **Start Server** button. -2. **Find the Model ID and Ensure the Model is Activated** - 1. Go to `Settings` > `My Models`. - 2. Models are listed with their **Model ID** beneath their names. - 3. Click the **three dots (โ‹ฎ)** button next to the model. - 4. Select **Start Model** to activate the model. -3. **Installing Tabby Server** - Use the following documentation to install the Tabby server: - - [Docker](https://tabby.tabbyml.com/docs/quick-start/installation/docker/) - - [Apple Silicon](https://tabby.tabbyml.com/docs/quick-start/installation/apple/) - - [Linux](https://tabby.tabbyml.com/docs/quick-start/installation/linux/) - - [Windows](https://tabby.tabbyml.com/docs/quick-start/installation/windows/) - Then, follow the steps to connect Jan with the Tabby server: - [Connect Jan with Tabby](https://tabby.tabbyml.com/docs/references/models-http-api/jan.ai/). - For example, to connect Jan with Tabby, save the following configuration under `~/.tabby/config.toml`: - - ```toml - # ~/.tabby/config.toml - [model.chat.http] - kind = "openai/chat" - model_name = "model_id" - api_endpoint = "http://localhost:1337/v1" - api_key = "" - ``` - Currently, the Jan completion and embedding API is under construction. - Once completed, you can also connect Jan with Tabby for completion and embedding tasks. - -4. **Installing Tabby on Your Favorite IDEs** - Refer to the following documentation to install the Tabby extension on your favorite IDEs: - - [Visual Studio Code](https://tabby.tabbyml.com/docs/extensions/installation/vscode/) - - [JetBrains IntelliJ Platform](https://tabby.tabbyml.com/docs/extensions/installation/intellij/) - - [VIM / NeoVIM](https://tabby.tabbyml.com/docs/extensions/installation/vim/) - - - -## How to Use Tabby with Jan Integration - -### Answer Engine: Chat with Your Codes and Documentation - -Tabby offers an [Answer Engine](https://tabby.tabbyml.com/docs/administration/answer-engine/) on the homepage, -which can leverage the Jan LLM and related contexts like code, documentation, and web pages to answer user questions. - -Simply open the Tabby homepage at [localhost:8080](http://localhost:8080) and ask your questions. - -### IDE Chat Sidebar - -After installing the Tabby extension on your preferred IDEs, you can engage in a conversation with Jan to: - -1. Discuss your code, receive suggestions, and seek assistance. -2. Request Jan to inline edit your code, and then review and accept the proposed changes. diff --git a/website/src/content/docs/local-server/llama-cpp.mdx b/website/src/content/docs/local-server/llama-cpp.mdx deleted file mode 100644 index 4263c80c3..000000000 --- a/website/src/content/docs/local-server/llama-cpp.mdx +++ /dev/null @@ -1,388 +0,0 @@ ---- -title: llama.cpp Engine -description: Configure Jan's local AI engine for optimal performance on your hardware. -keywords: - [ - Jan, - local AI, - llama.cpp, - AI engine, - local models, - performance, - GPU acceleration, - CPU processing, - model optimization, - CUDA, - Metal, - Vulkan, - ] ---- - -import { Aside, Tabs, TabItem } from '@astrojs/starlight/components'; - -## What is llama.cpp? - -llama.cpp is the core inference engine that powers Jan's ability to run AI models locally on your computer. Created by Georgi Gerganov, it's designed to run large language models efficiently on consumer hardware without requiring specialized AI accelerators or cloud connections. - -**Key benefits:** -- Run models entirely offline after download -- Use your existing hardware (CPU, GPU, or Apple Silicon) -- Complete privacy - conversations never leave your device -- No API costs or subscription fees - -## Accessing Engine Settings - -Navigate to **Settings** > **Model Providers** > **Llama.cpp**: - -![llama.cpp Settings](../../../assets/llama.cpp-01-updated.png) - - - -## Engine Management - -| Feature | What It Does | When to Use | -|---------|-------------|-------------| -| **Engine Version** | Shows current llama.cpp version | Check when models require newer engine | -| **Check Updates** | Downloads latest engine | Update for new model support or bug fixes | -| **Backend Selection** | Choose hardware-optimized version | After hardware changes or performance issues | - -## Selecting the Right Backend - -Different backends are optimized for specific hardware. Choose the one that matches your system: - - - - -### NVIDIA Graphics Cards -Check your CUDA version in NVIDIA Control Panel, then select: - -**CUDA 12.0 (Most Common):** -- `llama.cpp-avx2-cuda-12-0` - Modern CPUs with AVX2 -- `llama.cpp-avx512-cuda-12-0` - Newer Intel/AMD CPUs with AVX512 -- `llama.cpp-avx-cuda-12-0` - Older CPUs without AVX2 - -**CUDA 11.7 (Older Drivers):** -- `llama.cpp-avx2-cuda-11-7` - Modern CPUs -- `llama.cpp-avx-cuda-11-7` - Older CPUs - -### CPU Only -- `llama.cpp-avx2` - Most modern CPUs (2013+) -- `llama.cpp-avx512` - High-end Intel/AMD CPUs -- `llama.cpp-avx` - Older CPUs (2011-2013) -- `llama.cpp-noavx` - Very old CPUs (pre-2011) - -### AMD/Intel Graphics -- `llama.cpp-vulkan` - AMD Radeon, Intel Arc, Intel integrated - - - - - - - -### Apple Silicon (M1/M2/M3/M4) -- `llama.cpp-mac-arm64` - Automatically uses GPU acceleration via Metal - -### Intel Macs -- `llama.cpp-mac-amd64` - CPU-only processing - - - - - - - -### NVIDIA Graphics Cards -- `llama.cpp-avx2-cuda-12-0` - CUDA 12.0+ with modern CPU -- `llama.cpp-avx2-cuda-11-7` - CUDA 11.7+ with modern CPU - -### CPU Only -- `llama.cpp-avx2` - x86_64 modern CPUs -- `llama.cpp-avx512` - High-end Intel/AMD CPUs -- `llama.cpp-arm64` - ARM processors (Raspberry Pi, etc.) - -### AMD/Intel Graphics -- `llama.cpp-vulkan` - Open-source GPU acceleration - - - - -## Performance Settings - -Configure how the engine processes requests: - -### Core Performance - -| Setting | What It Does | Default | When to Adjust | -|---------|-------------|---------|----------------| -| **Auto-update engine** | Automatically updates llama.cpp to latest version | Enabled | Disable if you need version stability | -| **Auto-Unload Old Models** | Frees memory by unloading unused models | Disabled | Enable if switching between many models | -| **Threads** | CPU cores for text generation (`-1` = all cores) | -1 | Reduce if you need CPU for other tasks | -| **Threads (Batch)** | CPU cores for batch processing | -1 | Usually matches Threads setting | -| **Context Shift** | Removes old text to fit new text in memory | Disabled | Enable for very long conversations | -| **Max Tokens to Predict** | Maximum response length (`-1` = unlimited) | -1 | Set a limit to control response size | - -**Simple Analogy:** Think of threads like workers in a factory. More workers (threads) means faster production, but if you need workers elsewhere (other programs), you might want to limit how many the factory uses. - -### Batch Processing - -| Setting | What It Does | Default | When to Adjust | -|---------|-------------|---------|----------------| -| **Batch Size** | Logical batch size for prompt processing | 2048 | Lower if you have memory issues | -| **uBatch Size** | Physical batch size for hardware | 512 | Match your GPU's capabilities | -| **Continuous Batching** | Process multiple requests at once | Enabled | Keep enabled for efficiency | - -**Simple Analogy:** Batch size is like the size of a delivery truck. A bigger truck (batch) can carry more packages (tokens) at once, but needs a bigger garage (memory) and more fuel (processing power). - -### Multi-GPU Settings - -| Setting | What It Does | Default | When to Adjust | -|---------|-------------|---------|----------------| -| **GPU Split Mode** | How to divide model across GPUs | Layer | Change only with multiple GPUs | -| **Main GPU Index** | Primary GPU for processing | 0 | Select different GPU if needed | - -**When to tweak:** Only adjust if you have multiple GPUs and want to optimize how the model is distributed across them. - -## Memory Configuration - -Control how models use system and GPU memory: - -### Memory Management - -| Setting | What It Does | Default | When to Adjust | -|---------|-------------|---------|----------------| -| **Flash Attention** | Optimized memory usage for attention | Enabled | Disable only if having stability issues | -| **Disable mmap** | Turn off memory-mapped file loading | Disabled | Enable if experiencing crashes | -| **MLock** | Lock model in RAM (no swap to disk) | Disabled | Enable if you have plenty of RAM | -| **Disable KV Offload** | Keep conversation memory on CPU | Disabled | Enable if GPU memory is limited | - -**Simple Analogy:** Think of your computer's memory like a desk workspace: -- **mmap** is like keeping reference books open to specific pages (efficient) -- **mlock** is like gluing papers to your desk so they can't fall off (uses more space but faster access) -- **Flash Attention** is like using sticky notes instead of full pages (saves space) - -### KV Cache Configuration - -| Setting | What It Does | Options | When to Adjust | -|---------|-------------|---------|----------------| -| **KV Cache K Type** | Precision for "keys" in memory | f16, q8_0, q4_0 | Lower precision saves memory | -| **KV Cache V Type** | Precision for "values" in memory | f16, q8_0, q4_0 | Lower precision saves memory | -| **KV Cache Defragmentation Threshold** | When to reorganize memory (0.1 = 10% fragmented) | 0.1 | Increase if seeing memory errors | - -**Memory Precision Guide:** -- **f16** (default): Full quality, uses most memory - like HD video -- **q8_0**: Good quality, moderate memory - like standard video -- **q4_0**: Acceptable quality, least memory - like compressed video - -**When to adjust:** Start with f16. If you run out of memory, try q8_0. Only use q4_0 if absolutely necessary. - -## Advanced Settings - -### RoPE (Rotary Position Embeddings) - -| Setting | What It Does | Default | When to Adjust | -|---------|-------------|---------|----------------| -| **RoPE Scaling Method** | How to extend context length | None | For contexts beyond model's training | -| **RoPE Scale Factor** | Context extension multiplier | 1 | Increase for longer contexts | -| **RoPE Frequency Base** | Base frequency (0 = auto) | 0 | Leave at 0 unless specified | -| **RoPE Frequency Scale Factor** | Frequency adjustment | 1 | Advanced users only | - -**Simple Analogy:** RoPE is like the model's sense of position in a conversation. Imagine reading a book: -- **Normal**: You remember where you are on the page -- **RoPE Scaling**: Like using a magnifying glass to fit more words on the same page -- Scaling too much can make the text (context) blurry (less accurate) - -**When to use:** Only adjust if you need conversations longer than the model's default context length and understand the quality tradeoffs. - -### Mirostat Sampling - -| Setting | What It Does | Default | When to Adjust | -|---------|-------------|---------|----------------| -| **Mirostat Mode** | Alternative text generation method | Disabled | Try for more consistent output | -| **Mirostat Learning Rate** | How quickly it adapts (eta) | 0.1 | Lower = more stable | -| **Mirostat Target Entropy** | Target randomness (tau) | 5 | Lower = more focused | - -**Simple Analogy:** Mirostat is like cruise control for text generation: -- **Regular sampling**: You manually control speed (randomness) with temperature -- **Mirostat**: Automatically adjusts to maintain consistent "speed" (perplexity) -- **Target Entropy**: Your desired cruising speed -- **Learning Rate**: How quickly the cruise control adjusts - -**When to use:** Enable Mirostat if you find regular temperature settings produce inconsistent results. Start with defaults and adjust tau (3-7 range) for different styles. - -### Structured Output - -| Setting | What It Does | Default | When to Adjust | -|---------|-------------|---------|----------------| -| **Grammar File** | BNF grammar to constrain output | None | For specific output formats | -| **JSON Schema File** | JSON schema to enforce structure | None | For JSON responses | - -**Simple Analogy:** These are like templates or forms the model must fill out: -- **Grammar**: Like Mad Libs - the model can only put words in specific places -- **JSON Schema**: Like a tax form - specific fields must be filled with specific types of data - -**When to use:** Only when you need guaranteed structured output (like JSON for an API). Most users won't need these. - -## Quick Optimization Guide - -### For Best Performance -1. **Enable**: Flash Attention, Continuous Batching -2. **Set Threads**: -1 (use all CPU cores) -3. **Batch Size**: Keep defaults (2048/512) - -### For Limited Memory -1. **Enable**: Auto-Unload Models, Flash Attention -2. **KV Cache**: Set both to q8_0 or q4_0 -3. **Reduce**: Batch Size to 512/128 - -### For Long Conversations -1. **Enable**: Context Shift -2. **Consider**: RoPE scaling (with quality tradeoffs) -3. **Monitor**: Memory usage in System Monitor - -### For Multiple Models -1. **Enable**: Auto-Unload Old Models -2. **Disable**: MLock (saves RAM) -3. **Use**: Default memory settings - -## Troubleshooting Settings - -**Model crashes or errors:** -- Disable mmap -- Reduce Batch Size -- Switch KV Cache to q8_0 - -**Out of memory:** -- Enable Auto-Unload -- Reduce KV Cache precision -- Lower Batch Size - -**Slow performance:** -- Check Threads = -1 -- Enable Flash Attention -- Verify GPU backend is active - -**Inconsistent output:** -- Try Mirostat mode -- Adjust temperature in model settings -- Check if Context Shift is needed - -## Model-Specific Settings - -Each model can override engine defaults. Access via the gear icon next to any model: - -![Model Settings](../../../assets/trouble-shooting-04.png) - -| Setting | What It Controls | Impact | -|---------|-----------------|---------| -| **Context Length** | Conversation history size | Higher = more memory usage | -| **GPU Layers** | Model layers on GPU | Higher = faster but more VRAM | -| **Temperature** | Response randomness | 0.1 = focused, 1.0 = creative | -| **Top P** | Token selection pool | Lower = more focused responses | - - - -## Troubleshooting - -### Models Won't Load -1. **Wrong backend:** Try CPU-only backend first (`avx2` or `avx`) -2. **Insufficient memory:** Check RAM/VRAM requirements -3. **Outdated engine:** Update to latest version -4. **Corrupted download:** Re-download the model - -### Slow Performance -1. **No GPU acceleration:** Verify correct CUDA/Vulkan backend -2. **Too few GPU layers:** Increase in model settings -3. **CPU bottleneck:** Check thread count matches cores -4. **Memory swapping:** Reduce context size or use smaller model - -### Out of Memory -1. **Reduce quality:** Switch KV Cache to q8_0 or q4_0 -2. **Lower context:** Decrease context length in model settings -3. **Fewer layers:** Reduce GPU layers -4. **Smaller model:** Use quantized versions (Q4 vs Q8) - -### Crashes or Instability -1. **Backend mismatch:** Use more stable variant (avx vs avx2) -2. **Driver issues:** Update GPU drivers -3. **Overheating:** Monitor temperatures, improve cooling -4. **Power limits:** Check PSU capacity for high-end GPUs - -## Performance Benchmarks - -Typical performance with different configurations: - -| Hardware | Model Size | Backend | Tokens/sec | -|----------|------------|---------|------------| -| RTX 4090 | 7B Q4 | CUDA 12 | 80-120 | -| RTX 3070 | 7B Q4 | CUDA 12 | 40-60 | -| M2 Pro | 7B Q4 | Metal | 30-50 | -| Ryzen 9 | 7B Q4 | AVX2 | 10-20 | - - - -## Advanced Configuration - -### Custom Compilation - -For maximum performance, compile llama.cpp for your specific hardware: - -```bash -# Clone and build with specific optimizations -git clone https://github.com/ggerganov/llama.cpp -cd llama.cpp - -# Examples for different systems -make LLAMA_CUDA=1 # NVIDIA GPUs -make LLAMA_METAL=1 # Apple Silicon -make LLAMA_VULKAN=1 # AMD/Intel GPUs -``` - -### Environment Variables - -Fine-tune behavior with environment variables: - -```bash -# Force specific GPU -export CUDA_VISIBLE_DEVICES=0 - -# Thread tuning -export OMP_NUM_THREADS=8 - -# Memory limits -export GGML_CUDA_NO_PINNED=1 -``` - -## Best Practices - -**For Beginners:** -1. Use default settings -2. Start with smaller models (3-7B parameters) -3. Enable GPU acceleration if available - -**For Power Users:** -1. Match backend to hardware precisely -2. Tune memory settings for your VRAM -3. Experiment with parallel slots for multi-tasking - -**For Developers:** -1. Enable verbose logging for debugging -2. Use consistent settings across deployments -3. Monitor resource usage during inference - -## Related Resources - -- [Model Parameters Guide](/docs/jan/explanation/model-parameters) - Fine-tune model behavior -- [Troubleshooting Guide](/docs/jan/troubleshooting) - Detailed problem-solving -- [Hardware Requirements](/docs/desktop/mac#compatibility) - System specifications -- [API Server Settings](./api-server) - Configure the local API diff --git a/website/src/content/docs/local-server/settings.mdx b/website/src/content/docs/local-server/settings.mdx deleted file mode 100644 index a95691de6..000000000 --- a/website/src/content/docs/local-server/settings.mdx +++ /dev/null @@ -1,125 +0,0 @@ ---- -title: Server Settings -description: Configure advanced server settings for Jan's local API. -keywords: - [ - Jan, - local server, - settings, - configuration, - API server, - performance, - logging, - ] ---- - -import { Aside } from '@astrojs/starlight/components' - -This page covers server-specific settings for Jan's local API. For general Jan settings, see the main [Settings Guide](/docs/jan/settings). - -## Accessing Server Settings - -Navigate to **Settings** in Jan to configure server-related options. - -## Server Configuration - -### API Server Settings - -Configure the local API server at **Settings > Local API Server**: - -- **Host & Port** - Network binding configuration -- **API Key** - Authentication for API requests -- **CORS** - Cross-origin resource sharing -- **Verbose Logging** - Detailed request/response logs - -See our [API Configuration Guide](./api-server) for complete details. - -### Engine Configuration - -Configure llama.cpp engine at **Settings > Model Providers > Llama.cpp**: - -- **Backend Selection** - Hardware-optimized versions -- **Performance Settings** - Batching, threading, memory -- **Model Defaults** - Context size, GPU layers - -See our [Engine Settings Guide](./llama-cpp) for optimization tips. - -## Logging & Monitoring - -### Server Logs - -Monitor API activity in real-time: - -1. Enable **Verbose Server Logs** in API settings -2. View logs at **System Monitor** > **App Log** -3. Filter by `[SERVER]` tags for API-specific events - -### Log Management - -- **Location**: Stored in [Jan Data Folder](/docs/jan/data-folder) -- **Retention**: Automatically cleared after 24 hours -- **Manual Clear**: Settings > Advanced > Clear Logs - - - -## Performance Tuning - -### Memory Management - -For optimal server performance: - -- **High Traffic**: Increase parallel slots in engine settings -- **Limited RAM**: Reduce KV cache quality (q8_0 or q4_0) -- **Multiple Models**: Enable model unloading after idle timeout - -### Network Configuration - -Advanced networking options: - -- **Local Only**: Use `127.0.0.1` (default, most secure) -- **LAN Access**: Use `0.0.0.0` (allows network connections) -- **Custom Port**: Change from default `1337` if conflicts exist - -## Security Considerations - -### API Authentication - -- Always set a strong API key -- Rotate keys regularly for production use -- Never expose keys in client-side code - -### Network Security - -- Keep server on `localhost` unless LAN access is required -- Use firewall rules to restrict access -- Consider VPN for remote access needs - -## Troubleshooting Server Issues - -### Common Problems - -**Server won't start:** -- Check port availability (`netstat -an | grep 1337`) -- Verify no other instances running -- Try different port number - -**Connection refused:** -- Ensure server is started -- Check host/port configuration -- Verify firewall settings - -**Authentication failures:** -- Confirm API key matches configuration -- Check Authorization header format -- Ensure no extra spaces in key - -For more issues, see our [Troubleshooting Guide](/docs/jan/troubleshooting). - -## Related Resources - -- [API Configuration](./api-server) - Detailed API settings -- [Engine Settings](./llama-cpp) - Hardware optimization -- [Data Folder](/docs/jan/data-folder) - Storage locations -- [Models Overview](/docs/jan/manage-models) - Model management \ No newline at end of file diff --git a/website/src/content/docs/mobile/index.mdx b/website/src/content/docs/mobile/index.mdx deleted file mode 100644 index ed62d4b6a..000000000 --- a/website/src/content/docs/mobile/index.mdx +++ /dev/null @@ -1,35 +0,0 @@ ---- -title: Jan Mobile -description: Your AI assistant, on the go. Get ready for a seamless mobile experience with local and cloud capabilities. -keywords: - [ - Jan Mobile, - Jan AI, - mobile AI, - local AI on phone, - private AI app, - iOS, - Android, - offline AI, - ChatGPT alternative mobile - ] -banner: - content: 'Coming Q4 2025: Jan Mobile is currently in development.' ---- -import { Aside, Card, CardGrid } from '@astrojs/starlight/components'; - -## Your AI, Everywhere - -Jan Mobile brings the full power of a private, local-first AI to your iOS and Android devices. Connect to your home desktop, your company's server, or run models directly on your phone for complete offline privacy. - - - -The goal is a seamless experience that adapts to your environment without requiring you to change settings. - -### Core Features Planned: -- **Three Connection Modes**: Seamlessly switch between Local, Desktop, and Server modes. -- **Offline Capability**: Run `Jan Nano` or other small models directly on your device. -- **Voice-First Interface**: Interact with your AI naturally through voice commands. -- **Privacy by Design**: End-to-end encryption and full control over your data. diff --git a/website/src/content/docs/server/index.mdx b/website/src/content/docs/server/index.mdx deleted file mode 100644 index 6da7d4f7a..000000000 --- a/website/src/content/docs/server/index.mdx +++ /dev/null @@ -1,37 +0,0 @@ ---- -title: Jan Server -description: Your self-hosted, private AI cloud for teams and enterprises. -keywords: - [ - Jan Server, - Jan AI, - self-hosted AI, - private AI cloud, - local LLM server, - enterprise AI, - Docker, - Kubernetes, - on-premise AI - ] -banner: - content: 'Coming Q3 2025: Jan Server is currently in development.' ---- -import { Aside, Card } from '@astrojs/starlight/components'; - -## Your Private AI Cloud - -Jan Server allows you to deploy a powerful, multi-user AI environment on your -own infrastructure. It's designed for teams and enterprises that require full -data control, privacy, and predictable costs without sacrificing performance. - - - -By self-hosting, you ensure that your sensitive data and intellectual property never leave your network. - -### Core Features Planned: -- **Multi-User Management**: Control access with individual accounts and API keys. -- **Enterprise Authentication**: Integrate with your existing SSO, LDAP, or AD. -- **Flexible Deployment**: Deploy easily via Docker, Kubernetes, or on bare metal. -- **Centralized Admin Dashboard**: Monitor usage, manage models, and oversee system health. diff --git a/website/src/pages/api-reference.astro b/website/src/pages/api-reference.astro deleted file mode 100644 index 81e7c3f87..000000000 --- a/website/src/pages/api-reference.astro +++ /dev/null @@ -1,22 +0,0 @@ - - - - - - Redirecting to API Documentation | Jan - - - - -
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Redirecting...

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If you are not redirected automatically, click here to go to the API Documentation.

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- - - diff --git a/website/src/pages/api-reference/cloud.astro b/website/src/pages/api-reference/cloud.astro deleted file mode 100644 index 7fb634e58..000000000 --- a/website/src/pages/api-reference/cloud.astro +++ /dev/null @@ -1,331 +0,0 @@ ---- -import ApiReferenceLayout from '../../components/ApiReferenceLayout.astro' -import ScalarApiReferenceMulti from '../../components/react/ScalarApiReferenceMulti.jsx' - -const title = 'Jan Server API Reference' -const description = 'OpenAI-compatible API documentation for Jan Server powered by vLLM' ---- - - -
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Jan Server API Reference

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- Self-hostable Jan Server powered by vLLM for high-throughput serving -

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- Base URL: - http://your-server:8000/v1 -
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- Authentication Required: All requests to Jan Server require authentication. - Include your API key in the Authorization header as Bearer YOUR_API_KEY. - Configure authentication in your server settings. -
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High Performance

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Powered by vLLM's PagedAttention for efficient memory usage and high throughput

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Auto-Scaling

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Automatically scales to handle your workload with intelligent load balancing

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Multi-Model Support

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Support for various model formats and sizes with optimized serving configurations

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Local API Reference

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- Run Jan locally on your machine with llama.cpp's high-performance inference engine -

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๐Ÿ‘‹Jan API Documentation

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OpenAI-compatible API for local and server deployments

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Local API

- llama.cpp -
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Run Jan locally with complete privacy.

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- http://localhost:1337/v1 - Privacy-first โ€ข GGUF models โ€ข CPU/GPU -
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Jan Server

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Self-hostable server for high-throughput inference.

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- http://your-server:8000/v1 - Open source โ€ข Auto-scaling โ€ข Multi-GPU -
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Quick Start

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- - - diff --git a/website/src/styles/global.css b/website/src/styles/global.css deleted file mode 100644 index 48b9bc50a..000000000 --- a/website/src/styles/global.css +++ /dev/null @@ -1,72 +0,0 @@ -@font-face { - font-family: 'Studio Feixen Sans'; - src: url('/assets/fonts/StudioFeixenSans-Regular.otf') format('opentype'); - font-weight: 400; - font-style: normal; - font-display: swap; -} - -@font-face { - font-family: 'Studio Feixen Sans'; - src: url('/assets/fonts/StudioFeixenSans-Light.otf') format('opentype'); - font-weight: 300; - font-style: normal; - font-display: swap; -} - -@font-face { - font-family: 'Studio Feixen Sans'; - src: url('/assets/fonts/StudioFeixenSans-Book.otf') format('opentype'); - font-weight: 350; - font-style: normal; - font-display: swap; -} - -@font-face { - font-family: 'Studio Feixen Sans'; - src: url('/assets/fonts/StudioFeixenSans-Medium.otf') format('opentype'); - font-weight: 500; - font-style: normal; - font-display: swap; -} - -@font-face { - font-family: 'Studio Feixen Sans'; - src: url('/assets/fonts/StudioFeixenSans-Semibold.otf') format('opentype'); - font-weight: 600; - font-style: normal; - font-display: swap; -} - -@font-face { - font-family: 'Studio Feixen Sans'; - src: url('/assets/fonts/StudioFeixenSans-Bold.otf') format('opentype'); - font-weight: 700; - font-style: normal; - font-display: swap; -} - -@font-face { - font-family: 'Studio Feixen Sans'; - src: url('/assets/fonts/StudioFeixenSans-Ultralight.otf') format('opentype'); - font-weight: 200; - font-style: normal; - font-display: swap; -} - -:root { - --sl-font: 'Studio Feixen Sans', -apple-system, BlinkMacSystemFont, 'Segoe UI', - 'Roboto', 'Oxygen', 'Ubuntu', 'Cantarell', 'Fira Sans', 'Droid Sans', - 'Helvetica Neue', sans-serif; - --sl-font-mono: 'SF Mono', 'Monaco', 'Inconsolata', 'Roboto Mono', - 'Oxygen Mono', 'Ubuntu Monospace', 'Source Code Pro', 'Fira Mono', - 'Droid Sans Mono', 'Courier New', monospace; -} - -html { - font-family: var(--sl-font); -} - -body { - font-family: var(--sl-font); -} diff --git a/website/tsconfig.json b/website/tsconfig.json deleted file mode 100644 index ed034fd2e..000000000 --- a/website/tsconfig.json +++ /dev/null @@ -1,17 +0,0 @@ -{ - "extends": "astro/tsconfigs/strict", - "compilerOptions": { - "baseUrl": ".", - "paths": { - "@/*": ["src/*"], - "@/components/*": ["src/components/*"], - "@/layouts/*": ["src/layouts/*"], - "@/assets/*": ["src/assets/*"], - "@/content/*": ["src/content/*"], - "@/styles/*": ["src/styles/*"], - "@/utils/*": ["src/utils/*"] - } - }, - "include": [".astro/types.d.ts", "**/*"], - "exclude": ["dist"] -}