2024-02-15 08:38:05 +07:00

290 lines
7.9 KiB
TypeScript

import {
fs,
Assistant,
MessageRequest,
events,
InferenceEngine,
MessageEvent,
InferenceEvent,
joinPath,
executeOnMain,
AssistantExtension,
AssistantEvent,
} from '@janhq/core'
export default class JanAssistantExtension extends AssistantExtension {
private static readonly _homeDir = 'file://assistants'
private static readonly _threadDir = 'file://threads'
controller = new AbortController()
isCancelled = false
retrievalThreadId: string | undefined = undefined
async onLoad() {
// making the assistant directory
const assistantDirExist = await fs.existsSync(
JanAssistantExtension._homeDir
)
if (
localStorage.getItem(`${EXTENSION_NAME}-version`) !== VERSION ||
!assistantDirExist
) {
if (!assistantDirExist) await fs.mkdirSync(JanAssistantExtension._homeDir)
// Write assistant metadata
await this.createJanAssistant()
// Finished migration
localStorage.setItem(`${EXTENSION_NAME}-version`, VERSION)
// Update the assistant list
events.emit(AssistantEvent.OnAssistantsUpdate, {})
}
// Events subscription
events.on(MessageEvent.OnMessageSent, (data: MessageRequest) =>
JanAssistantExtension.handleMessageRequest(data, this)
)
events.on(InferenceEvent.OnInferenceStopped, () => {
JanAssistantExtension.handleInferenceStopped(this)
})
}
private static async handleInferenceStopped(instance: JanAssistantExtension) {
instance.isCancelled = true
instance.controller?.abort()
}
private static async handleMessageRequest(
data: MessageRequest,
instance: JanAssistantExtension
) {
instance.isCancelled = false
instance.controller = new AbortController()
if (
data.model?.engine !== InferenceEngine.tool_retrieval_enabled ||
!data.messages ||
// TODO: Since the engine is defined, its unsafe to assume that assistant tools are defined
// That could lead to an issue where thread stuck at generating response
!data.thread?.assistants[0]?.tools
) {
return
}
const latestMessage = data.messages[data.messages.length - 1]
// 1. Ingest the document if needed
if (
latestMessage &&
latestMessage.content &&
typeof latestMessage.content !== 'string' &&
latestMessage.content.length > 1
) {
const docFile = latestMessage.content[1]?.doc_url?.url
if (docFile) {
await executeOnMain(
NODE,
'toolRetrievalIngestNewDocument',
docFile,
data.model?.proxyEngine
)
}
} else if (
// Check whether we need to ingest document or not
// Otherwise wrong context will be sent
!(await fs.existsSync(
await joinPath([
JanAssistantExtension._threadDir,
data.threadId,
'memory',
])
))
) {
// No document ingested, reroute the result to inference engine
const output = {
...data,
model: {
...data.model,
engine: data.model.proxyEngine,
},
}
events.emit(MessageEvent.OnMessageSent, output)
return
}
// 2. Load agent on thread changed
if (instance.retrievalThreadId !== data.threadId) {
await executeOnMain(NODE, 'toolRetrievalLoadThreadMemory', data.threadId)
instance.retrievalThreadId = data.threadId
// Update the text splitter
await executeOnMain(
NODE,
'toolRetrievalUpdateTextSplitter',
data.thread.assistants[0].tools[0]?.settings?.chunk_size ?? 4000,
data.thread.assistants[0].tools[0]?.settings?.chunk_overlap ?? 200
)
}
// 3. Using the retrieval template with the result and query
if (latestMessage.content) {
const prompt =
typeof latestMessage.content === 'string'
? latestMessage.content
: latestMessage.content[0].text
// Retrieve the result
const retrievalResult = await executeOnMain(
NODE,
'toolRetrievalQueryResult',
prompt
)
console.debug('toolRetrievalQueryResult', retrievalResult)
// Update message content
if (data.thread?.assistants[0]?.tools && retrievalResult)
data.messages[data.messages.length - 1].content =
data.thread.assistants[0].tools[0].settings?.retrieval_template
?.replace('{CONTEXT}', retrievalResult)
.replace('{QUESTION}', prompt)
}
// Filter out all the messages that are not text
data.messages = data.messages.map((message) => {
if (
message.content &&
typeof message.content !== 'string' &&
(message.content.length ?? 0) > 0
) {
return {
...message,
content: [message.content[0]],
}
}
return message
})
// 4. Reroute the result to inference engine
const output = {
...data,
model: {
...data.model,
engine: data.model.proxyEngine,
},
}
events.emit(MessageEvent.OnMessageSent, output)
}
/**
* Called when the extension is unloaded.
*/
onUnload(): void {}
async createAssistant(assistant: Assistant): Promise<void> {
const assistantDir = await joinPath([
JanAssistantExtension._homeDir,
assistant.id,
])
if (!(await fs.existsSync(assistantDir))) await fs.mkdirSync(assistantDir)
// store the assistant metadata json
const assistantMetadataPath = await joinPath([
assistantDir,
'assistant.json',
])
try {
await fs.writeFileSync(
assistantMetadataPath,
JSON.stringify(assistant, null, 2)
)
} catch (err) {
console.error(err)
}
}
async getAssistants(): Promise<Assistant[]> {
// get all the assistant directories
// get all the assistant metadata json
const results: Assistant[] = []
const allFileName: string[] = await fs.readdirSync(
JanAssistantExtension._homeDir
)
for (const fileName of allFileName) {
const filePath = await joinPath([
JanAssistantExtension._homeDir,
fileName,
])
if (filePath.includes('.DS_Store')) continue
const jsonFiles: string[] = (await fs.readdirSync(filePath)).filter(
(file: string) => file === 'assistant.json'
)
if (jsonFiles.length !== 1) {
// has more than one assistant file -> ignore
continue
}
const content = await fs.readFileSync(
await joinPath([filePath, jsonFiles[0]]),
'utf-8'
)
const assistant: Assistant =
typeof content === 'object' ? content : JSON.parse(content)
results.push(assistant)
}
return results
}
async deleteAssistant(assistant: Assistant): Promise<void> {
if (assistant.id === 'jan') {
return Promise.reject('Cannot delete Jan Assistant')
}
// remove the directory
const assistantDir = await joinPath([
JanAssistantExtension._homeDir,
assistant.id,
])
await fs.rmdirSync(assistantDir)
return Promise.resolve()
}
private async createJanAssistant(): Promise<void> {
const janAssistant: Assistant = {
avatar: '',
thread_location: undefined,
id: 'jan',
object: 'assistant',
created_at: Date.now(),
name: 'Jan',
description: 'A default assistant that can use all downloaded models',
model: '*',
instructions: '',
tools: [
{
type: 'retrieval',
enabled: 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. If you don't know the answer, just say that you don't know, don't try to make up an answer.
----------------
CONTEXT: {CONTEXT}
----------------
QUESTION: {QUESTION}
----------------
Helpful Answer:`,
},
},
],
file_ids: [],
metadata: undefined,
}
await this.createAssistant(janAssistant)
}
}