jan/web-app/src/lib/completion.ts
Louis b8de48c9e9
fix: enhance tool use and model provider not persisted issues (#5094)
* chore: enhance tool use loop

* fix: create new custom provider is not saved

* chore: bump llama.cpp b5488

* chore: normalize reasoning assistant response

* chore: fix tool call parse in stream mode

* fix: give tool call default generated id

* fix: system instruction should be on top of the history

* chore: allow users to add parameters
2025-05-26 15:12:55 +07:00

348 lines
9.2 KiB
TypeScript

import {
ContentType,
ChatCompletionRole,
ThreadMessage,
MessageStatus,
EngineManager,
ModelManager,
} from '@janhq/core'
import { invoke } from '@tauri-apps/api/core'
import {
ChatCompletionMessageParam,
ChatCompletionTool,
CompletionResponse,
CompletionResponseChunk,
models,
StreamCompletionResponse,
TokenJS,
} from 'token.js'
import { ulid } from 'ulidx'
import { normalizeProvider } from './models'
import { MCPTool } from '@/types/completion'
import { CompletionMessagesBuilder } from './messages'
import { ChatCompletionMessageToolCall } from 'openai/resources'
import { callTool } from '@/services/mcp'
/**
* @fileoverview Helper functions for creating thread content.
* These functions are used to create thread content objects
* for different types of content, such as text and image.
* The functions return objects that conform to the `ThreadContent` type.
* @param content - The content of the thread
* @returns
*/
export const newUserThreadContent = (
threadId: string,
content: string
): ThreadMessage => ({
type: 'text',
role: ChatCompletionRole.User,
content: [
{
type: ContentType.Text,
text: {
value: content,
annotations: [],
},
},
],
id: ulid(),
object: 'thread.message',
thread_id: threadId,
status: MessageStatus.Ready,
created_at: 0,
completed_at: 0,
})
/**
* @fileoverview Helper functions for creating thread content.
* These functions are used to create thread content objects
* for different types of content, such as text and image.
* The functions return objects that conform to the `ThreadContent` type.
* @param content - The content of the thread
* @returns
*/
export const newAssistantThreadContent = (
threadId: string,
content: string
): ThreadMessage => ({
type: 'text',
role: ChatCompletionRole.Assistant,
content: [
{
type: ContentType.Text,
text: {
value: content,
annotations: [],
},
},
],
id: ulid(),
object: 'thread.message',
thread_id: threadId,
status: MessageStatus.Ready,
created_at: 0,
completed_at: 0,
})
/**
* Empty thread content object.
* @returns
*/
export const emptyThreadContent: ThreadMessage = {
type: 'text',
role: ChatCompletionRole.Assistant,
id: ulid(),
object: 'thread.message',
thread_id: '',
content: [],
status: MessageStatus.Ready,
created_at: 0,
completed_at: 0,
}
/**
* @fileoverview Helper function to send a completion request to the model provider.
* @param thread
* @param provider
* @param messages
* @returns
*/
export const sendCompletion = async (
thread: Thread,
provider: ModelProvider,
messages: ChatCompletionMessageParam[],
abortController: AbortController,
tools: MCPTool[] = [],
stream: boolean = true,
params: Record<string, object> = {}
): Promise<StreamCompletionResponse | CompletionResponse | undefined> => {
if (!thread?.model?.id || !provider) return undefined
let providerName = provider.provider as unknown as keyof typeof models
if (!Object.keys(models).some((key) => key === providerName))
providerName = 'openai-compatible'
const tokenJS = new TokenJS({
apiKey: provider.api_key ?? (await invoke('app_token')),
// TODO: Retrieve from extension settings
baseURL: provider.base_url,
})
// TODO: Add message history
const completion = stream
? await tokenJS.chat.completions.create(
{
stream: true,
provider: providerName,
model: thread.model?.id,
messages,
tools: normalizeTools(tools),
tool_choice: tools.length ? 'auto' : undefined,
...params,
},
{
signal: abortController.signal,
}
)
: await tokenJS.chat.completions.create({
stream: false,
provider: providerName,
model: thread.model?.id,
messages,
tools: normalizeTools(tools),
tool_choice: tools.length ? 'auto' : undefined,
...params,
})
return completion
}
export const isCompletionResponse = (
response: StreamCompletionResponse | CompletionResponse
): response is CompletionResponse => {
return 'choices' in response
}
/**
* @fileoverview Helper function to start a model.
* This function loads the model from the provider.
* @deprecated This function is deprecated and will be removed in the future.
* Provider's chat function will handle loading the model.
* @param provider
* @param model
* @returns
*/
export const startModel = async (
provider: ProviderObject,
model: string,
abortController?: AbortController
): Promise<void> => {
const providerObj = EngineManager.instance().get(
normalizeProvider(provider.provider)
)
const modelObj = provider.models.find((m) => m.id === model)
if (providerObj && modelObj)
return providerObj?.loadModel(
{
id: modelObj.id,
settings: Object.fromEntries(
Object.entries(modelObj.settings ?? {}).map(([key, value]) => [
key,
value.controller_props?.value, // assuming each setting is { value: ... }
])
),
},
abortController
)
}
/**
* @fileoverview Helper function to stop a model.
* This function unloads the model from the provider.
* @param provider
* @param model
* @returns
*/
export const stopModel = async (
provider: string,
model: string
): Promise<void> => {
const providerObj = EngineManager.instance().get(normalizeProvider(provider))
const modelObj = ModelManager.instance().get(model)
if (providerObj && modelObj) return providerObj?.unloadModel(modelObj)
}
/**
* @fileoverview Helper function to normalize tools for the chat completion request.
* This function converts the MCPTool objects to ChatCompletionTool objects.
* @param tools
* @returns
*/
export const normalizeTools = (
tools: MCPTool[]
): ChatCompletionTool[] | undefined => {
if (tools.length === 0) return undefined
return tools.map((tool) => ({
type: 'function',
function: {
name: tool.name,
description: tool.description?.slice(0, 1024),
parameters: tool.inputSchema,
strict: false,
},
}))
}
/**
* @fileoverview Helper function to extract tool calls from the completion response.
* @param part
* @param calls
*/
export const extractToolCall = (
part: CompletionResponseChunk,
currentCall: ChatCompletionMessageToolCall | null,
calls: ChatCompletionMessageToolCall[]
) => {
const deltaToolCalls = part.choices[0].delta.tool_calls
// Handle the beginning of a new tool call
if (deltaToolCalls?.[0]?.index !== undefined && deltaToolCalls[0]?.function) {
const index = deltaToolCalls[0].index
// Create new tool call if this is the first chunk for it
if (!calls[index]) {
calls[index] = {
id: deltaToolCalls[0]?.id || ulid(),
function: {
name: deltaToolCalls[0]?.function?.name || '',
arguments: deltaToolCalls[0]?.function?.arguments || '',
},
type: 'function',
}
currentCall = calls[index]
} else {
// Continuation of existing tool call
currentCall = calls[index]
// Append to function name or arguments if they exist in this chunk
if (
deltaToolCalls[0]?.function?.name &&
currentCall!.function.name !== deltaToolCalls[0]?.function?.name
) {
currentCall!.function.name += deltaToolCalls[0].function.name
}
if (deltaToolCalls[0]?.function?.arguments) {
currentCall!.function.arguments += deltaToolCalls[0].function.arguments
}
}
}
return calls
}
/**
* @fileoverview Helper function to process the completion response.
* @param calls
* @param builder
* @param message
* @param content
*/
export const postMessageProcessing = async (
calls: ChatCompletionMessageToolCall[],
builder: CompletionMessagesBuilder,
message: ThreadMessage,
abortController: AbortController
) => {
// Handle completed tool calls
if (calls.length) {
for (const toolCall of calls) {
if (abortController.signal.aborted) break
const toolId = ulid()
const toolCallsMetadata =
message.metadata?.tool_calls &&
Array.isArray(message.metadata?.tool_calls)
? message.metadata?.tool_calls
: []
message.metadata = {
...(message.metadata ?? {}),
tool_calls: [
...toolCallsMetadata,
{
tool: {
...(toolCall as object),
id: toolId,
},
response: undefined,
state: 'pending',
},
],
}
const result = await callTool({
toolName: toolCall.function.name,
arguments: toolCall.function.arguments.length
? JSON.parse(toolCall.function.arguments)
: {},
})
if ('error' in result && result.error) break
message.metadata = {
...(message.metadata ?? {}),
tool_calls: [
...toolCallsMetadata,
{
tool: {
...toolCall,
id: toolId,
},
response: result,
state: 'ready',
},
],
}
builder.addToolMessage(result.content[0]?.text ?? '', toolCall.id)
// update message metadata
return message
}
}
}