jan/web/hooks/useSendChatMessage.ts
hiro e6c10202e0
feat: Jan can see (#2069)
* feat: jan can see

feat: Add GPT-4 Vision model (Preview)

fix: Add visionModel as property in ModelInfo

fix: Fix condition to load local messages in useSetActiveThread hook

feat: Enable Image as input for chat

fix: Update model parameters in JSON files for remote GPT models

fix: Add thread as optional

fix: Add support for message as image

fix: Linter

fix: Update proxyModel to proxy_model and add textModel

chore: Change proxyModel to proxy_model

fix: Update settings with visionModel and textModel

fix: vision model passed through the retrieval tool

fix: linter

* fix: could not load image and request is not able to be sent

---------

Co-authored-by: Louis <louis@jan.ai>
2024-03-05 08:33:09 +07:00

371 lines
10 KiB
TypeScript

/* eslint-disable @typescript-eslint/no-explicit-any */
import { useEffect, useRef } from 'react'
import {
ChatCompletionMessage,
ChatCompletionRole,
ContentType,
MessageRequest,
MessageRequestType,
MessageStatus,
ExtensionTypeEnum,
Thread,
ThreadMessage,
events,
Model,
ConversationalExtension,
MessageEvent,
InferenceEngine,
ChatCompletionMessageContentType,
AssistantTool,
} from '@janhq/core'
import { atom, useAtom, useAtomValue, useSetAtom } from 'jotai'
import { ulid } from 'ulid'
import { selectedModelAtom } from '@/containers/DropdownListSidebar'
import {
currentPromptAtom,
editPromptAtom,
fileUploadAtom,
} from '@/containers/Providers/Jotai'
import { compressImage, getBase64 } from '@/utils/base64'
import { toRuntimeParams, toSettingParams } from '@/utils/modelParam'
import { loadModelErrorAtom, useActiveModel } from './useActiveModel'
import { extensionManager } from '@/extension/ExtensionManager'
import {
addNewMessageAtom,
deleteMessageAtom,
getCurrentChatMessagesAtom,
} from '@/helpers/atoms/ChatMessage.atom'
import {
activeThreadAtom,
engineParamsUpdateAtom,
getActiveThreadModelParamsAtom,
isGeneratingResponseAtom,
updateThreadAtom,
updateThreadWaitingForResponseAtom,
} from '@/helpers/atoms/Thread.atom'
export const queuedMessageAtom = atom(false)
export const reloadModelAtom = atom(false)
export default function useSendChatMessage() {
const activeThread = useAtomValue(activeThreadAtom)
const addNewMessage = useSetAtom(addNewMessageAtom)
const updateThread = useSetAtom(updateThreadAtom)
const updateThreadWaiting = useSetAtom(updateThreadWaitingForResponseAtom)
const setCurrentPrompt = useSetAtom(currentPromptAtom)
const deleteMessage = useSetAtom(deleteMessageAtom)
const setEditPrompt = useSetAtom(editPromptAtom)
const currentMessages = useAtomValue(getCurrentChatMessagesAtom)
const { activeModel } = useActiveModel()
const selectedModel = useAtomValue(selectedModelAtom)
const { startModel } = useActiveModel()
const setQueuedMessage = useSetAtom(queuedMessageAtom)
const loadModelFailed = useAtomValue(loadModelErrorAtom)
const modelRef = useRef<Model | undefined>()
const loadModelFailedRef = useRef<string | undefined>()
const activeModelParams = useAtomValue(getActiveThreadModelParamsAtom)
const engineParamsUpdate = useAtomValue(engineParamsUpdateAtom)
const setEngineParamsUpdate = useSetAtom(engineParamsUpdateAtom)
const setReloadModel = useSetAtom(reloadModelAtom)
const [fileUpload, setFileUpload] = useAtom(fileUploadAtom)
const setIsGeneratingResponse = useSetAtom(isGeneratingResponseAtom)
useEffect(() => {
modelRef.current = activeModel
}, [activeModel])
useEffect(() => {
loadModelFailedRef.current = loadModelFailed
}, [loadModelFailed])
const resendChatMessage = async (currentMessage: ThreadMessage) => {
if (!activeThread) {
console.error('No active thread')
return
}
setIsGeneratingResponse(true)
updateThreadWaiting(activeThread.id, true)
const messages: ChatCompletionMessage[] = [
activeThread.assistants[0]?.instructions,
]
.filter((e) => e && e.trim() !== '')
.map<ChatCompletionMessage>((instructions) => {
const systemMessage: ChatCompletionMessage = {
role: ChatCompletionRole.System,
content: instructions,
}
return systemMessage
})
.concat(
currentMessages
.filter(
(e) =>
currentMessage.role === ChatCompletionRole.User ||
e.id !== currentMessage.id
)
.map<ChatCompletionMessage>((msg) => ({
role: msg.role,
content: msg.content[0]?.text.value ?? '',
}))
)
const messageRequest: MessageRequest = {
id: ulid(),
type: MessageRequestType.Thread,
messages: messages,
threadId: activeThread.id,
model: activeThread.assistants[0].model ?? selectedModel,
}
const modelId = selectedModel?.id ?? activeThread.assistants[0].model.id
if (activeModel?.id !== modelId) {
setQueuedMessage(true)
startModel(modelId)
await waitForModelStarting(modelId)
setQueuedMessage(false)
}
if (currentMessage.role !== ChatCompletionRole.User) {
// Delete last response before regenerating
deleteMessage(currentMessage.id ?? '')
if (activeThread) {
await extensionManager
.get<ConversationalExtension>(ExtensionTypeEnum.Conversational)
?.writeMessages(
activeThread.id,
currentMessages.filter((msg) => msg.id !== currentMessage.id)
)
}
}
events.emit(MessageEvent.OnMessageSent, messageRequest)
}
const sendChatMessage = async (message: string) => {
if (!message || message.trim().length === 0) return
if (!activeThread) {
console.error('No active thread')
return
}
setIsGeneratingResponse(true)
if (engineParamsUpdate) setReloadModel(true)
const runtimeParams = toRuntimeParams(activeModelParams)
const settingParams = toSettingParams(activeModelParams)
updateThreadWaiting(activeThread.id, true)
const prompt = message.trim()
setCurrentPrompt('')
setEditPrompt('')
let base64Blob = fileUpload[0]
? await getBase64(fileUpload[0].file)
: undefined
const fileContentType = fileUpload[0]?.type
const msgId = ulid()
const isDocumentInput = base64Blob && fileContentType === 'pdf'
const isImageInput = base64Blob && fileContentType === 'image'
if (isImageInput && base64Blob) {
// Compress image
base64Blob = await compressImage(base64Blob, 512)
}
const messages: ChatCompletionMessage[] = [
activeThread.assistants[0]?.instructions,
]
.filter((e) => e && e.trim() !== '')
.map<ChatCompletionMessage>((instructions) => {
const systemMessage: ChatCompletionMessage = {
role: ChatCompletionRole.System,
content: instructions,
}
return systemMessage
})
.concat(
currentMessages
.map<ChatCompletionMessage>((msg) => ({
role: msg.role,
content: msg.content[0]?.text.value ?? '',
}))
.concat([
{
role: ChatCompletionRole.User,
content:
selectedModel && base64Blob
? [
{
type: ChatCompletionMessageContentType.Text,
text: prompt,
},
isDocumentInput
? {
type: ChatCompletionMessageContentType.Doc,
doc_url: {
url: `threads/${activeThread.id}/files/${msgId}.pdf`,
},
}
: null,
isImageInput
? {
type: ChatCompletionMessageContentType.Image,
image_url: {
url: base64Blob,
},
}
: null,
].filter((e) => e !== null)
: prompt,
} as ChatCompletionMessage,
])
)
let modelRequest = selectedModel ?? activeThread.assistants[0].model
if (runtimeParams.stream == null) {
runtimeParams.stream = true
}
// Add middleware to the model request with tool retrieval enabled
if (
activeThread.assistants[0].tools?.some(
(tool: AssistantTool) => tool.type === 'retrieval' && tool.enabled
)
) {
modelRequest = {
...modelRequest,
// Tool retrieval support document input only for now
...(isDocumentInput
? {
engine: InferenceEngine.tool_retrieval_enabled,
proxy_model: modelRequest.engine,
}
: {}),
}
}
const messageRequest: MessageRequest = {
id: msgId,
type: MessageRequestType.Thread,
threadId: activeThread.id,
messages,
model: {
...modelRequest,
settings: settingParams,
parameters: runtimeParams,
},
thread: activeThread,
}
const timestamp = Date.now()
const content: any = []
if (base64Blob && fileUpload[0]?.type === 'image') {
content.push({
type: ContentType.Image,
text: {
value: prompt,
annotations: [base64Blob],
},
})
}
if (base64Blob && fileUpload[0]?.type === 'pdf') {
content.push({
type: ContentType.Pdf,
text: {
value: prompt,
annotations: [base64Blob],
name: fileUpload[0].file.name,
size: fileUpload[0].file.size,
},
})
}
if (prompt && !base64Blob) {
content.push({
type: ContentType.Text,
text: {
value: prompt,
annotations: [],
},
})
}
const threadMessage: ThreadMessage = {
id: msgId,
thread_id: activeThread.id,
role: ChatCompletionRole.User,
status: MessageStatus.Ready,
created: timestamp,
updated: timestamp,
object: 'thread.message',
content: content,
}
addNewMessage(threadMessage)
if (base64Blob) {
setFileUpload([])
}
const updatedThread: Thread = {
...activeThread,
updated: timestamp,
metadata: {
...(activeThread.metadata ?? {}),
lastMessage: prompt,
},
}
// change last update thread when send message
updateThread(updatedThread)
await extensionManager
.get<ConversationalExtension>(ExtensionTypeEnum.Conversational)
?.addNewMessage(threadMessage)
const modelId = selectedModel?.id ?? activeThread.assistants[0].model.id
if (activeModel?.id !== modelId) {
setQueuedMessage(true)
startModel(modelId)
await waitForModelStarting(modelId)
setQueuedMessage(false)
}
events.emit(MessageEvent.OnMessageSent, messageRequest)
setReloadModel(false)
setEngineParamsUpdate(false)
}
const waitForModelStarting = async (modelId: string) => {
return new Promise<void>((resolve) => {
setTimeout(async () => {
if (modelRef.current?.id !== modelId && !loadModelFailedRef.current) {
await waitForModelStarting(modelId)
resolve()
} else {
resolve()
}
}, 200)
})
}
return {
sendChatMessage,
resendChatMessage,
}
}