mirror of
https://github.com/TriliumNext/Notes.git
synced 2025-07-29 02:52:27 +08:00
split up sendMessage into its own service
This commit is contained in:
perf3ct
parent
caada309ec
commit
14705eb1c5
@ -1,20 +1,10 @@
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import type { Request, Response } from "express";
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import log from "../../services/log.js";
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import options from "../../services/options.js";
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// @ts-ignore
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import { v4 as uuidv4 } from 'uuid';
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import becca from "../../becca/becca.js";
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import vectorStore from "../../services/llm/embeddings/index.js";
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import providerManager from "../../services/llm/providers/providers.js";
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import type { Message, ChatCompletionOptions } from "../../services/llm/ai_interface.js";
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// Import this way to prevent immediate instantiation
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import * as aiServiceManagerModule from "../../services/llm/ai_service_manager.js";
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import contextService from "../../services/llm/context_service.js";
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import sql from "../../services/sql.js";
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// Import the index service for knowledge base management
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import indexService from "../../services/llm/index_service.js";
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import { CONTEXT_PROMPTS, ERROR_PROMPTS, FORMATTING_PROMPTS } from '../../services/llm/constants/llm_prompt_constants.js';
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import { LLM_CONSTANTS } from '../../services/llm/constants/provider_constants.js';
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import restChatService from "../../services/llm/rest_chat_service.js";
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// Define basic interfaces
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interface ChatMessage {
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@ -53,7 +43,7 @@ interface SessionOptions {
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// In-memory storage for sessions
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// In a production app, this should be stored in a database
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const sessions = new Map<string, ChatSession>();
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const sessions = restChatService.getSessions();
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// Flag to track if cleanup timer has been initialized
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let cleanupInitialized = false;
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@ -63,22 +53,7 @@ let cleanupInitialized = false;
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* Only call this after database is initialized
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*/
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function initializeCleanupTimer() {
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if (cleanupInitialized) {
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return;
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}
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// Clean sessions that have expired based on the constants
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function cleanupOldSessions() {
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const expiryTime = new Date(Date.now() - LLM_CONSTANTS.SESSION.SESSION_EXPIRY_MS);
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for (const [sessionId, session] of sessions.entries()) {
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if (session.lastActive < expiryTime) {
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sessions.delete(sessionId);
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}
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}
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}
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// Run cleanup at the configured interval
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setInterval(cleanupOldSessions, LLM_CONSTANTS.SESSION.CLEANUP_INTERVAL_MS);
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restChatService.initializeCleanupTimer();
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cleanupInitialized = true;
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}
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@ -86,30 +61,14 @@ function initializeCleanupTimer() {
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* Check if the database is initialized
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*/
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function isDatabaseInitialized(): boolean {
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try {
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options.getOption('initialized');
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return true;
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} catch (error) {
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return false;
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}
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return restChatService.isDatabaseInitialized();
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}
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/**
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* Get the AI service manager in a way that doesn't crash at startup
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*/
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function safelyUseAIManager(): boolean {
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// Only use AI manager if database is initialized
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if (!isDatabaseInitialized()) {
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return false;
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}
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// Try to access the manager - will create instance only if needed
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try {
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return aiServiceManagerModule.default.isAnyServiceAvailable();
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} catch (error) {
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log.error(`Error accessing AI service manager: ${error}`);
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return false;
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}
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return restChatService.safelyUseAIManager();
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}
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/**
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@ -166,51 +125,7 @@ function safelyUseAIManager(): boolean {
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* tags: ["llm"]
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*/
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async function createSession(req: Request, res: Response) {
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try {
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// Initialize cleanup if not already done
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initializeCleanupTimer();
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const options: SessionOptions = req.body || {};
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const title = options.title || 'Chat Session';
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const sessionId = uuidv4();
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const now = new Date();
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// Initial system message if provided
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const messages: ChatMessage[] = [];
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if (options.systemPrompt) {
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messages.push({
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role: 'system',
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content: options.systemPrompt,
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timestamp: now
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});
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}
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// Store session info
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sessions.set(sessionId, {
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id: sessionId,
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title,
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messages,
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createdAt: now,
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lastActive: now,
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noteContext: options.contextNoteId,
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metadata: {
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temperature: options.temperature,
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maxTokens: options.maxTokens,
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model: options.model,
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provider: options.provider
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}
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});
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return {
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id: sessionId,
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title,
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createdAt: now
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};
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} catch (error: any) {
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log.error(`Error creating LLM session: ${error.message || 'Unknown error'}`);
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throw new Error(`Failed to create LLM session: ${error.message || 'Unknown error'}`);
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}
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return restChatService.createSession(req, res);
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}
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/**
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@ -263,28 +178,7 @@ async function createSession(req: Request, res: Response) {
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* tags: ["llm"]
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*/
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async function getSession(req: Request, res: Response) {
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try {
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const { sessionId } = req.params;
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// Check if session exists
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const session = sessions.get(sessionId);
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if (!session) {
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throw new Error(`Session with ID ${sessionId} not found`);
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}
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// Return session without internal metadata
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return {
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id: session.id,
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title: session.title,
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createdAt: session.createdAt,
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lastActive: session.lastActive,
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messages: session.messages,
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noteContext: session.noteContext
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};
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} catch (error: any) {
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log.error(`Error getting LLM session: ${error.message || 'Unknown error'}`);
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throw new Error(`Failed to get session: ${error.message || 'Unknown error'}`);
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}
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return restChatService.getSession(req, res);
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}
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/**
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@ -349,54 +243,7 @@ async function getSession(req: Request, res: Response) {
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* tags: ["llm"]
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*/
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async function updateSession(req: Request, res: Response) {
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try {
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const { sessionId } = req.params;
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const updates = req.body || {};
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// Check if session exists
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const session = sessions.get(sessionId);
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if (!session) {
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throw new Error(`Session with ID ${sessionId} not found`);
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}
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// Update allowed fields
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if (updates.title) {
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session.title = updates.title;
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}
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if (updates.noteContext) {
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session.noteContext = updates.noteContext;
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}
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// Update metadata
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if (updates.temperature !== undefined) {
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session.metadata.temperature = updates.temperature;
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}
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if (updates.maxTokens !== undefined) {
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session.metadata.maxTokens = updates.maxTokens;
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}
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if (updates.model) {
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session.metadata.model = updates.model;
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}
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if (updates.provider) {
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session.metadata.provider = updates.provider;
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}
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// Update timestamp
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session.lastActive = new Date();
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return {
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id: session.id,
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title: session.title,
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updatedAt: session.lastActive
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};
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} catch (error: any) {
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log.error(`Error updating LLM session: ${error.message || 'Unknown error'}`);
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throw new Error(`Failed to update session: ${error.message || 'Unknown error'}`);
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}
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return restChatService.updateSession(req, res);
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}
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/**
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@ -432,25 +279,7 @@ async function updateSession(req: Request, res: Response) {
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* tags: ["llm"]
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*/
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async function listSessions(req: Request, res: Response) {
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try {
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const sessionList = Array.from(sessions.values()).map(session => ({
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id: session.id,
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title: session.title,
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createdAt: session.createdAt,
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lastActive: session.lastActive,
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messageCount: session.messages.length
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}));
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// Sort by last activity (most recent first)
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sessionList.sort((a, b) => b.lastActive.getTime() - a.lastActive.getTime());
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return {
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sessions: sessionList
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};
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} catch (error: any) {
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log.error(`Error listing LLM sessions: ${error.message || 'Unknown error'}`);
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throw new Error(`Failed to list sessions: ${error.message || 'Unknown error'}`);
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}
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return restChatService.listSessions(req, res);
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}
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/**
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@ -475,176 +304,21 @@ async function listSessions(req: Request, res: Response) {
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* tags: ["llm"]
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*/
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async function deleteSession(req: Request, res: Response) {
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try {
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const { sessionId } = req.params;
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// Check if session exists
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if (!sessions.has(sessionId)) {
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throw new Error(`Session with ID ${sessionId} not found`);
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}
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// Delete session
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sessions.delete(sessionId);
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return {
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success: true,
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message: `Session ${sessionId} deleted successfully`
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};
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} catch (error: any) {
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log.error(`Error deleting LLM session: ${error.message || 'Unknown error'}`);
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throw new Error(`Failed to delete session: ${error.message || 'Unknown error'}`);
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}
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return restChatService.deleteSession(req, res);
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}
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/**
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* Find relevant notes based on search query
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*/
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async function findRelevantNotes(content: string, contextNoteId: string | null = null, limit = 5): Promise<NoteSource[]> {
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try {
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// If database is not initialized, we can't do this
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if (!isDatabaseInitialized()) {
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return [];
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}
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// Check if embeddings are available
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const enabledProviders = await providerManager.getEnabledEmbeddingProviders();
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if (enabledProviders.length === 0) {
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log.info("No embedding providers available, can't find relevant notes");
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return [];
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}
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// If content is too short, don't bother
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if (content.length < 3) {
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return [];
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}
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// Get the embedding for the query
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const provider = enabledProviders[0];
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const embedding = await provider.generateEmbeddings(content);
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let results;
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if (contextNoteId) {
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// For branch context, get notes specifically from that branch
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// TODO: This is a simplified implementation - we need to
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// properly get all notes in the subtree starting from contextNoteId
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// For now, just get direct children of the context note
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const contextNote = becca.notes[contextNoteId];
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if (!contextNote) {
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return [];
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}
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const childBranches = await sql.getRows(`
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SELECT branches.* FROM branches
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WHERE branches.parentNoteId = ?
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AND branches.isDeleted = 0
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`, [contextNoteId]);
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const childNoteIds = childBranches.map((branch: any) => branch.noteId);
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// Include the context note itself
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childNoteIds.push(contextNoteId);
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// Find similar notes in this context
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results = [];
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for (const noteId of childNoteIds) {
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const noteEmbedding = await vectorStore.getEmbeddingForNote(
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noteId,
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provider.name,
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provider.getConfig().model
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);
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if (noteEmbedding) {
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const similarity = vectorStore.cosineSimilarity(
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embedding,
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noteEmbedding.embedding
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);
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if (similarity > 0.65) {
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results.push({
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noteId,
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similarity
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});
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}
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}
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}
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// Sort by similarity
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results.sort((a, b) => b.similarity - a.similarity);
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results = results.slice(0, limit);
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} else {
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// General search across all notes
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results = await vectorStore.findSimilarNotes(
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embedding,
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provider.name,
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provider.getConfig().model,
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limit
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);
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}
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// Format the results
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const sources: NoteSource[] = [];
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for (const result of results) {
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const note = becca.notes[result.noteId];
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if (!note) continue;
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let noteContent: string | undefined = undefined;
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if (note.type === 'text') {
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const content = note.getContent();
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// Handle both string and Buffer types
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noteContent = typeof content === 'string' ? content :
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content instanceof Buffer ? content.toString('utf8') : undefined;
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}
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sources.push({
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noteId: result.noteId,
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title: note.title,
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content: noteContent,
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similarity: result.similarity,
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branchId: note.getBranches()[0]?.branchId
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});
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}
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return sources;
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} catch (error: any) {
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log.error(`Error finding relevant notes: ${error.message}`);
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return [];
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}
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return restChatService.findRelevantNotes(content, contextNoteId, limit);
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}
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/**
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* Build a prompt with context from relevant notes
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*/
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function buildContextFromNotes(sources: NoteSource[], query: string): string {
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console.log("Building context from notes with query:", query);
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console.log("Sources length:", sources ? sources.length : 0);
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// If no sources are available, just return the query without additional context
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if (!sources || sources.length === 0) {
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console.log("No sources available, using just the query");
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return query || '';
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}
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const noteContexts = sources
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.filter(source => source.content) // Only include sources with content
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.map((source) => {
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// Format each note with its title as a natural heading and wrap in <note> tags
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return `<note>\n### ${source.title}\n${source.content || 'No content available'}\n</note>`;
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})
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.join('\n\n');
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if (!noteContexts) {
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console.log("After filtering, no valid note contexts remain - using just the query");
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return query || '';
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}
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// Use the template from the constants file, replacing placeholders
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return CONTEXT_PROMPTS.CONTEXT_NOTES_WRAPPER
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.replace('{noteContexts}', noteContexts)
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.replace('{query}', query);
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return restChatService.buildContextFromNotes(sources, query);
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}
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/**
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@ -719,427 +393,7 @@ function buildContextFromNotes(sources: NoteSource[], query: string): string {
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* tags: ["llm"]
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*/
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async function sendMessage(req: Request, res: Response) {
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try {
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// Extract parameters differently based on the request method
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let content, useAdvancedContext, showThinking, sessionId;
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if (req.method === 'POST') {
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// For POST requests, get content from the request body
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const requestBody = req.body || {};
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content = requestBody.content;
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useAdvancedContext = requestBody.useAdvancedContext || false;
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showThinking = requestBody.showThinking || false;
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// Add logging for POST requests
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log.info(`LLM POST message: sessionId=${req.params.sessionId}, useAdvancedContext=${useAdvancedContext}, showThinking=${showThinking}, contentLength=${content ? content.length : 0}`);
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} else if (req.method === 'GET') {
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// For GET (streaming) requests, get format from query params
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// The content should have been sent in a previous POST request
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useAdvancedContext = req.query.useAdvancedContext === 'true';
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showThinking = req.query.showThinking === 'true';
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content = ''; // We don't need content for GET requests
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// Add logging for GET requests
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log.info(`LLM GET stream: sessionId=${req.params.sessionId}, useAdvancedContext=${useAdvancedContext}, showThinking=${showThinking}`);
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}
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// Get sessionId from URL params since it's part of the route
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sessionId = req.params.sessionId;
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// Get the Accept header once at the start
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const acceptHeader = req.get('Accept');
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const isStreamingRequest = req.method === 'GET' && req.query.format === 'stream';
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// For GET requests, ensure we have the format=stream parameter
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if (req.method === 'GET' && (!req.query.format || req.query.format !== 'stream')) {
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throw new Error('Stream format parameter is required for GET requests');
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}
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// For POST requests, validate the content
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if (req.method === 'POST' && (!content || typeof content !== 'string' || content.trim().length === 0)) {
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throw new Error('Content cannot be empty');
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}
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// Get session
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if (!sessionId || !sessions.has(sessionId)) {
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throw new Error('Session not found');
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}
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const session = sessions.get(sessionId)!;
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session.lastActive = new Date();
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// For POST requests, store the user message
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if (req.method === 'POST' && content) {
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// Add message to session
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session.messages.push({
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role: 'user',
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content,
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timestamp: new Date()
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});
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// Log a preview of the message
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log.info(`Processing LLM message: "${content.substring(0, 50)}${content.length > 50 ? '...' : ''}"`);
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}
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// Check if AI services are available
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if (!safelyUseAIManager()) {
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throw new Error('AI services are not available');
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}
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|
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// Get the AI service manager
|
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const aiServiceManager = aiServiceManagerModule.default.getInstance();
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// Get the default service - just use the first available one
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const availableProviders = aiServiceManager.getAvailableProviders();
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let service = null;
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|
||||
if (availableProviders.length > 0) {
|
||||
// Use the first available provider
|
||||
const providerName = availableProviders[0];
|
||||
// We know the manager has a 'services' property from our code inspection,
|
||||
// but TypeScript doesn't know that from the interface.
|
||||
// This is a workaround to access it
|
||||
service = (aiServiceManager as any).services[providerName];
|
||||
}
|
||||
|
||||
if (!service) {
|
||||
throw new Error('No AI service is available');
|
||||
}
|
||||
|
||||
// Information to return to the client
|
||||
let aiResponse = '';
|
||||
let sourceNotes: NoteSource[] = [];
|
||||
|
||||
// For POST requests, we need to process the message
|
||||
// For GET (streaming) requests, we use the latest user message from the session
|
||||
if (req.method === 'POST' || isStreamingRequest) {
|
||||
// Get the latest user message for context
|
||||
const latestUserMessage = session.messages
|
||||
.filter(msg => msg.role === 'user')
|
||||
.pop();
|
||||
|
||||
if (!latestUserMessage && req.method === 'GET') {
|
||||
throw new Error('No user message found in session');
|
||||
}
|
||||
|
||||
// Use the latest message content for GET requests
|
||||
const messageContent = req.method === 'POST' ? content : latestUserMessage!.content;
|
||||
|
||||
// If Advanced Context is enabled, we use the improved method
|
||||
if (useAdvancedContext) {
|
||||
// Use the Trilium-specific approach
|
||||
const contextNoteId = session.noteContext || null;
|
||||
|
||||
// Log that we're calling contextService with the parameters
|
||||
log.info(`Using enhanced context with: noteId=${contextNoteId}, showThinking=${showThinking}`);
|
||||
|
||||
const results = await contextService.processQuery(
|
||||
messageContent,
|
||||
service,
|
||||
contextNoteId,
|
||||
showThinking
|
||||
);
|
||||
|
||||
// Get the generated context
|
||||
const context = results.context;
|
||||
// Convert from NoteSearchResult to NoteSource
|
||||
sourceNotes = results.sources.map(source => ({
|
||||
noteId: source.noteId,
|
||||
title: source.title,
|
||||
content: source.content || undefined, // Convert null to undefined
|
||||
similarity: source.similarity
|
||||
}));
|
||||
|
||||
// Build context from relevant notes
|
||||
const contextFromNotes = buildContextFromNotes(sourceNotes, messageContent);
|
||||
|
||||
// Add system message with the context
|
||||
const contextMessage: Message = {
|
||||
role: 'system',
|
||||
content: context
|
||||
};
|
||||
|
||||
// DEBUG: Log context details before sending to LLM
|
||||
log.info(`${FORMATTING_PROMPTS.DIVIDERS.CONTENT_SECTION} Context begins with: "${context.substring(0, 200)}..."`);
|
||||
log.info(`${FORMATTING_PROMPTS.DIVIDERS.CONTENT_SECTION} Context ends with: "...${context.substring(context.length - 200)}"`);
|
||||
log.info(`${FORMATTING_PROMPTS.DIVIDERS.NOTE_SECTION} Number of notes included: ${sourceNotes.length}`);
|
||||
|
||||
// Format messages for the LLM using the proper context
|
||||
const aiMessages = await contextService.buildMessagesWithContext(
|
||||
session.messages.slice(-LLM_CONSTANTS.SESSION.MAX_SESSION_MESSAGES).map(msg => ({
|
||||
role: msg.role,
|
||||
content: msg.content
|
||||
})),
|
||||
context,
|
||||
service
|
||||
);
|
||||
|
||||
// Add enhanced debug logging
|
||||
if (service.constructor.name === 'OllamaService') {
|
||||
// Log condensed version of the context so we can see if it's being properly formatted
|
||||
console.log(`Sending context to Ollama with length: ${context.length} chars`);
|
||||
console.log(`Context first 200 chars: ${context.substring(0, 200).replace(/\n/g, '\\n')}...`);
|
||||
console.log(`Context last 200 chars: ${context.substring(context.length - 200).replace(/\n/g, '\\n')}...`);
|
||||
|
||||
// Log the first user message to verify context injection is working
|
||||
const userMsg = aiMessages.find(m => m.role === 'user');
|
||||
if (userMsg) {
|
||||
console.log(`First user message (first 200 chars): ${userMsg.content.substring(0, 200).replace(/\n/g, '\\n')}...`);
|
||||
}
|
||||
}
|
||||
|
||||
// DEBUG: Log message structure being sent to LLM
|
||||
log.info(`Message structure being sent to LLM: ${aiMessages.length} messages total`);
|
||||
|
||||
// Configure chat options from session metadata
|
||||
const chatOptions: ChatCompletionOptions = {
|
||||
temperature: session.metadata.temperature || 0.7,
|
||||
maxTokens: session.metadata.maxTokens,
|
||||
model: session.metadata.model,
|
||||
stream: isStreamingRequest ? true : undefined
|
||||
};
|
||||
|
||||
// Process based on whether this is a streaming request
|
||||
if (isStreamingRequest) {
|
||||
// Set streaming headers once
|
||||
res.setHeader('Content-Type', 'text/event-stream');
|
||||
res.setHeader('Cache-Control', 'no-cache');
|
||||
res.setHeader('Connection', 'keep-alive');
|
||||
|
||||
// Flag to indicate we've handled the response directly
|
||||
// This lets the route handler know not to process the result
|
||||
(res as any).triliumResponseHandled = true;
|
||||
|
||||
let messageContent = '';
|
||||
|
||||
try {
|
||||
// Use the correct method name: generateChatCompletion
|
||||
const response = await service.generateChatCompletion(aiMessages, chatOptions);
|
||||
|
||||
// Handle streaming if the response includes a stream method
|
||||
if (response.stream) {
|
||||
await response.stream((chunk: { text: string; done: boolean }) => {
|
||||
if (chunk.text) {
|
||||
messageContent += chunk.text;
|
||||
// Only write if the response hasn't finished
|
||||
if (!res.writableEnded) {
|
||||
res.write(`data: ${JSON.stringify({ content: chunk.text })}\n\n`);
|
||||
}
|
||||
}
|
||||
|
||||
if (chunk.done) {
|
||||
// Signal the end of the stream when done, only if not already ended
|
||||
if (!res.writableEnded) {
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
}
|
||||
});
|
||||
} else {
|
||||
// If no streaming available, send the response as a single chunk
|
||||
messageContent = response.text;
|
||||
// Only write if the response hasn't finished
|
||||
if (!res.writableEnded) {
|
||||
res.write(`data: ${JSON.stringify({ content: messageContent })}\n\n`);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
}
|
||||
|
||||
// Store the full response for the session
|
||||
aiResponse = messageContent;
|
||||
|
||||
// Store the assistant's response in the session
|
||||
session.messages.push({
|
||||
role: 'assistant',
|
||||
content: aiResponse,
|
||||
timestamp: new Date()
|
||||
});
|
||||
|
||||
// For streaming requests we don't return anything as we've already sent the response
|
||||
return null;
|
||||
} catch (streamingError: any) {
|
||||
// If streaming fails and we haven't sent a response yet, throw the error
|
||||
if (!res.headersSent) {
|
||||
throw streamingError;
|
||||
} else {
|
||||
// If headers were already sent, try to send an error event
|
||||
try {
|
||||
if (!res.writableEnded) {
|
||||
res.write(`data: ${JSON.stringify({ error: streamingError.message })}\n\n`);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
} catch (e) {
|
||||
log.error(`Failed to write streaming error: ${e}`);
|
||||
}
|
||||
return null;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// Non-streaming approach for POST requests
|
||||
const response = await service.generateChatCompletion(aiMessages, chatOptions);
|
||||
aiResponse = response.text; // Extract the text from the response
|
||||
|
||||
// Store the assistant's response in the session
|
||||
session.messages.push({
|
||||
role: 'assistant',
|
||||
content: aiResponse,
|
||||
timestamp: new Date()
|
||||
});
|
||||
|
||||
// Return the response for POST requests
|
||||
return {
|
||||
content: aiResponse,
|
||||
sources: sourceNotes.map(note => ({
|
||||
noteId: note.noteId,
|
||||
title: note.title,
|
||||
similarity: note.similarity
|
||||
}))
|
||||
};
|
||||
}
|
||||
} else {
|
||||
// Original approach - find relevant notes through direct embedding comparison
|
||||
const relevantNotes = await findRelevantNotes(
|
||||
messageContent,
|
||||
session.noteContext || null,
|
||||
5
|
||||
);
|
||||
|
||||
sourceNotes = relevantNotes;
|
||||
|
||||
// Build context from relevant notes
|
||||
const context = buildContextFromNotes(relevantNotes, messageContent);
|
||||
|
||||
// Get messages with context properly formatted for the specific LLM provider
|
||||
const aiMessages = await contextService.buildMessagesWithContext(
|
||||
session.messages.slice(-LLM_CONSTANTS.SESSION.MAX_SESSION_MESSAGES).map(msg => ({
|
||||
role: msg.role,
|
||||
content: msg.content
|
||||
})),
|
||||
context,
|
||||
service
|
||||
);
|
||||
|
||||
// Configure chat options from session metadata
|
||||
const chatOptions: ChatCompletionOptions = {
|
||||
temperature: session.metadata.temperature || 0.7,
|
||||
maxTokens: session.metadata.maxTokens,
|
||||
model: session.metadata.model,
|
||||
stream: isStreamingRequest ? true : undefined
|
||||
};
|
||||
|
||||
if (isStreamingRequest) {
|
||||
// Set streaming headers once
|
||||
res.setHeader('Content-Type', 'text/event-stream');
|
||||
res.setHeader('Cache-Control', 'no-cache');
|
||||
res.setHeader('Connection', 'keep-alive');
|
||||
|
||||
// Flag to indicate we've handled the response directly
|
||||
// This lets the route handler know not to process the result
|
||||
(res as any).triliumResponseHandled = true;
|
||||
|
||||
let messageContent = '';
|
||||
|
||||
try {
|
||||
// Use the correct method name: generateChatCompletion
|
||||
const response = await service.generateChatCompletion(aiMessages, chatOptions);
|
||||
|
||||
// Handle streaming if the response includes a stream method
|
||||
if (response.stream) {
|
||||
await response.stream((chunk: { text: string; done: boolean }) => {
|
||||
if (chunk.text) {
|
||||
messageContent += chunk.text;
|
||||
// Only write if the response hasn't finished
|
||||
if (!res.writableEnded) {
|
||||
res.write(`data: ${JSON.stringify({ content: chunk.text })}\n\n`);
|
||||
}
|
||||
}
|
||||
|
||||
if (chunk.done) {
|
||||
// Signal the end of the stream when done, only if not already ended
|
||||
if (!res.writableEnded) {
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
}
|
||||
});
|
||||
} else {
|
||||
// If no streaming available, send the response as a single chunk
|
||||
messageContent = response.text;
|
||||
// Only write if the response hasn't finished
|
||||
if (!res.writableEnded) {
|
||||
res.write(`data: ${JSON.stringify({ content: messageContent })}\n\n`);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
}
|
||||
|
||||
// Store the full response for the session
|
||||
aiResponse = messageContent;
|
||||
|
||||
// Store the assistant's response in the session
|
||||
session.messages.push({
|
||||
role: 'assistant',
|
||||
content: aiResponse,
|
||||
timestamp: new Date()
|
||||
});
|
||||
|
||||
// For streaming requests we don't return anything as we've already sent the response
|
||||
return null;
|
||||
} catch (streamingError: any) {
|
||||
// If streaming fails and we haven't sent a response yet, throw the error
|
||||
if (!res.headersSent) {
|
||||
throw streamingError;
|
||||
} else {
|
||||
// If headers were already sent, try to send an error event
|
||||
try {
|
||||
if (!res.writableEnded) {
|
||||
res.write(`data: ${JSON.stringify({ error: streamingError.message })}\n\n`);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
} catch (e) {
|
||||
log.error(`Failed to write streaming error: ${e}`);
|
||||
}
|
||||
return null;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// Non-streaming approach for POST requests
|
||||
const response = await service.generateChatCompletion(aiMessages, chatOptions);
|
||||
aiResponse = response.text; // Extract the text from the response
|
||||
|
||||
// Store the assistant's response in the session
|
||||
session.messages.push({
|
||||
role: 'assistant',
|
||||
content: aiResponse,
|
||||
timestamp: new Date()
|
||||
});
|
||||
|
||||
// Return the response for POST requests
|
||||
return {
|
||||
content: aiResponse,
|
||||
sources: sourceNotes.map(note => ({
|
||||
noteId: note.noteId,
|
||||
title: note.title,
|
||||
similarity: note.similarity
|
||||
}))
|
||||
};
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// If it's not a POST or streaming GET request, return the session's message history
|
||||
return {
|
||||
id: session.id,
|
||||
messages: session.messages
|
||||
};
|
||||
}
|
||||
} catch (error: any) {
|
||||
log.error(`Error in LLM query processing: ${error}`);
|
||||
return {
|
||||
error: ERROR_PROMPTS.USER_ERRORS.GENERAL_ERROR
|
||||
};
|
||||
}
|
||||
return restChatService.handleSendMessage(req, res);
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
893
src/services/llm/rest_chat_service.ts
Normal file
893
src/services/llm/rest_chat_service.ts
Normal file
@ -0,0 +1,893 @@
|
||||
import log from "../log.js";
|
||||
import type { Request, Response } from "express";
|
||||
import type { Message, ChatCompletionOptions } from "./ai_interface.js";
|
||||
import contextService from "./context_service.js";
|
||||
import { LLM_CONSTANTS } from './constants/provider_constants.js';
|
||||
import { ERROR_PROMPTS } from './constants/llm_prompt_constants.js';
|
||||
import * as aiServiceManagerModule from "./ai_service_manager.js";
|
||||
import becca from "../../becca/becca.js";
|
||||
import vectorStore from "./embeddings/index.js";
|
||||
import providerManager from "./providers/providers.js";
|
||||
// @ts-ignore
|
||||
import { v4 as uuidv4 } from 'uuid';
|
||||
import options from "../../services/options.js";
|
||||
|
||||
// Define interfaces for the REST API
|
||||
export interface NoteSource {
|
||||
noteId: string;
|
||||
title: string;
|
||||
content?: string;
|
||||
similarity?: number;
|
||||
branchId?: string;
|
||||
}
|
||||
|
||||
export interface ChatSession {
|
||||
id: string;
|
||||
title: string;
|
||||
messages: ChatMessage[];
|
||||
createdAt: Date;
|
||||
lastActive: Date;
|
||||
noteContext?: string;
|
||||
metadata: Record<string, any>;
|
||||
}
|
||||
|
||||
export interface ChatMessage {
|
||||
role: 'user' | 'assistant' | 'system';
|
||||
content: string;
|
||||
timestamp?: Date;
|
||||
}
|
||||
|
||||
// In-memory storage for sessions
|
||||
// In a production app, this should be stored in a database
|
||||
const sessions = new Map<string, ChatSession>();
|
||||
|
||||
// Flag to track if cleanup timer has been initialized
|
||||
let cleanupInitialized = false;
|
||||
|
||||
/**
|
||||
* Service to handle chat API interactions
|
||||
*/
|
||||
class RestChatService {
|
||||
/**
|
||||
* Initialize the session cleanup timer to remove old/inactive sessions
|
||||
*/
|
||||
initializeCleanupTimer(): void {
|
||||
if (cleanupInitialized) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Clean sessions that have expired based on the constants
|
||||
function cleanupOldSessions() {
|
||||
const expiryTime = new Date(Date.now() - LLM_CONSTANTS.SESSION.SESSION_EXPIRY_MS);
|
||||
for (const [sessionId, session] of sessions.entries()) {
|
||||
if (session.lastActive < expiryTime) {
|
||||
sessions.delete(sessionId);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Run cleanup at the configured interval
|
||||
setInterval(cleanupOldSessions, LLM_CONSTANTS.SESSION.CLEANUP_INTERVAL_MS);
|
||||
cleanupInitialized = true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Check if the database is initialized
|
||||
*/
|
||||
isDatabaseInitialized(): boolean {
|
||||
try {
|
||||
options.getOption('initialized');
|
||||
return true;
|
||||
} catch (error) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the AI service manager in a way that doesn't crash at startup
|
||||
*/
|
||||
safelyUseAIManager(): boolean {
|
||||
// Only use AI manager if database is initialized
|
||||
if (!this.isDatabaseInitialized()) {
|
||||
log.info("AI check failed: Database is not initialized");
|
||||
return false;
|
||||
}
|
||||
|
||||
// Try to access the manager - will create instance only if needed
|
||||
try {
|
||||
const aiManager = aiServiceManagerModule.default;
|
||||
|
||||
if (!aiManager) {
|
||||
log.info("AI check failed: AI manager module is not available");
|
||||
return false;
|
||||
}
|
||||
|
||||
const isAvailable = aiManager.isAnyServiceAvailable();
|
||||
log.info(`AI service availability check result: ${isAvailable}`);
|
||||
|
||||
if (isAvailable) {
|
||||
// Additional diagnostics
|
||||
try {
|
||||
const providers = aiManager.getAvailableProviders();
|
||||
log.info(`Available AI providers: ${providers.join(', ')}`);
|
||||
} catch (err) {
|
||||
log.info(`Could not get available providers: ${err}`);
|
||||
}
|
||||
}
|
||||
|
||||
return isAvailable;
|
||||
} catch (error) {
|
||||
log.error(`Error accessing AI service manager: ${error}`);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Find relevant notes based on search query
|
||||
*/
|
||||
async findRelevantNotes(content: string, contextNoteId: string | null = null, limit = 5): Promise<NoteSource[]> {
|
||||
try {
|
||||
// If database is not initialized, we can't do this
|
||||
if (!this.isDatabaseInitialized()) {
|
||||
return [];
|
||||
}
|
||||
|
||||
// Check if embeddings are available
|
||||
const enabledProviders = await providerManager.getEnabledEmbeddingProviders();
|
||||
if (enabledProviders.length === 0) {
|
||||
log.info("No embedding providers available, can't find relevant notes");
|
||||
return [];
|
||||
}
|
||||
|
||||
// If content is too short, don't bother
|
||||
if (content.length < 3) {
|
||||
return [];
|
||||
}
|
||||
|
||||
// Get the embedding for the query
|
||||
const provider = enabledProviders[0];
|
||||
const embedding = await provider.generateEmbeddings(content);
|
||||
|
||||
let results;
|
||||
if (contextNoteId) {
|
||||
// For branch context, get notes specifically from that branch
|
||||
const contextNote = becca.notes[contextNoteId];
|
||||
if (!contextNote) {
|
||||
return [];
|
||||
}
|
||||
|
||||
const sql = require("../../services/sql.js").default;
|
||||
const childBranches = await sql.getRows(`
|
||||
SELECT branches.* FROM branches
|
||||
WHERE branches.parentNoteId = ?
|
||||
AND branches.isDeleted = 0
|
||||
`, [contextNoteId]);
|
||||
|
||||
const childNoteIds = childBranches.map((branch: any) => branch.noteId);
|
||||
|
||||
// Include the context note itself
|
||||
childNoteIds.push(contextNoteId);
|
||||
|
||||
// Find similar notes in this context
|
||||
results = [];
|
||||
|
||||
for (const noteId of childNoteIds) {
|
||||
const noteEmbedding = await vectorStore.getEmbeddingForNote(
|
||||
noteId,
|
||||
provider.name,
|
||||
provider.getConfig().model
|
||||
);
|
||||
|
||||
if (noteEmbedding) {
|
||||
const similarity = vectorStore.cosineSimilarity(
|
||||
embedding,
|
||||
noteEmbedding.embedding
|
||||
);
|
||||
|
||||
if (similarity > 0.65) {
|
||||
results.push({
|
||||
noteId,
|
||||
similarity
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Sort by similarity
|
||||
results.sort((a, b) => b.similarity - a.similarity);
|
||||
results = results.slice(0, limit);
|
||||
} else {
|
||||
// General search across all notes
|
||||
results = await vectorStore.findSimilarNotes(
|
||||
embedding,
|
||||
provider.name,
|
||||
provider.getConfig().model,
|
||||
limit
|
||||
);
|
||||
}
|
||||
|
||||
// Format the results
|
||||
const sources: NoteSource[] = [];
|
||||
|
||||
for (const result of results) {
|
||||
const note = becca.notes[result.noteId];
|
||||
if (!note) continue;
|
||||
|
||||
let noteContent: string | undefined = undefined;
|
||||
if (note.type === 'text') {
|
||||
const content = note.getContent();
|
||||
// Handle both string and Buffer types
|
||||
noteContent = typeof content === 'string' ? content :
|
||||
content instanceof Buffer ? content.toString('utf8') : undefined;
|
||||
}
|
||||
|
||||
sources.push({
|
||||
noteId: result.noteId,
|
||||
title: note.title,
|
||||
content: noteContent,
|
||||
similarity: result.similarity,
|
||||
branchId: note.getBranches()[0]?.branchId
|
||||
});
|
||||
}
|
||||
|
||||
return sources;
|
||||
} catch (error: any) {
|
||||
log.error(`Error finding relevant notes: ${error.message}`);
|
||||
return [];
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle a message sent to an LLM and get a response
|
||||
*/
|
||||
async handleSendMessage(req: Request, res: Response) {
|
||||
log.info("=== Starting handleSendMessage ===");
|
||||
try {
|
||||
// Extract parameters differently based on the request method
|
||||
let content, useAdvancedContext, showThinking, sessionId;
|
||||
|
||||
if (req.method === 'POST') {
|
||||
// For POST requests, get content from the request body
|
||||
const requestBody = req.body || {};
|
||||
content = requestBody.content;
|
||||
useAdvancedContext = requestBody.useAdvancedContext || false;
|
||||
showThinking = requestBody.showThinking || false;
|
||||
|
||||
// Add logging for POST requests
|
||||
log.info(`LLM POST message: sessionId=${req.params.sessionId}, useAdvancedContext=${useAdvancedContext}, showThinking=${showThinking}, contentLength=${content ? content.length : 0}`);
|
||||
} else if (req.method === 'GET') {
|
||||
// For GET (streaming) requests, get format from query params
|
||||
// The content should have been sent in a previous POST request
|
||||
useAdvancedContext = req.query.useAdvancedContext === 'true';
|
||||
showThinking = req.query.showThinking === 'true';
|
||||
content = ''; // We don't need content for GET requests
|
||||
|
||||
// Add logging for GET requests
|
||||
log.info(`LLM GET stream: sessionId=${req.params.sessionId}, useAdvancedContext=${useAdvancedContext}, showThinking=${showThinking}`);
|
||||
}
|
||||
|
||||
// Get sessionId from URL params since it's part of the route
|
||||
sessionId = req.params.sessionId;
|
||||
|
||||
// For GET requests, ensure we have the format=stream parameter
|
||||
if (req.method === 'GET' && (!req.query.format || req.query.format !== 'stream')) {
|
||||
throw new Error('Stream format parameter is required for GET requests');
|
||||
}
|
||||
|
||||
// For POST requests, validate the content
|
||||
if (req.method === 'POST' && (!content || typeof content !== 'string' || content.trim().length === 0)) {
|
||||
throw new Error('Content cannot be empty');
|
||||
}
|
||||
|
||||
// Get session
|
||||
if (!sessionId || !sessions.has(sessionId)) {
|
||||
throw new Error('Session not found');
|
||||
}
|
||||
|
||||
const session = sessions.get(sessionId)!;
|
||||
session.lastActive = new Date();
|
||||
|
||||
// For POST requests, store the user message
|
||||
if (req.method === 'POST' && content) {
|
||||
// Add message to session
|
||||
session.messages.push({
|
||||
role: 'user',
|
||||
content,
|
||||
timestamp: new Date()
|
||||
});
|
||||
|
||||
// Log a preview of the message
|
||||
log.info(`Processing LLM message: "${content.substring(0, 50)}${content.length > 50 ? '...' : ''}"`);
|
||||
}
|
||||
|
||||
// Check if AI services are enabled before proceeding
|
||||
const aiEnabled = await options.getOptionBool('aiEnabled');
|
||||
log.info(`AI enabled setting: ${aiEnabled}`);
|
||||
if (!aiEnabled) {
|
||||
log.info("AI services are disabled by configuration");
|
||||
return {
|
||||
error: "AI features are disabled. Please enable them in the settings."
|
||||
};
|
||||
}
|
||||
|
||||
// Check if AI services are available
|
||||
log.info("Checking if AI services are available...");
|
||||
if (!this.safelyUseAIManager()) {
|
||||
log.info("AI services are not available - checking for specific issues");
|
||||
|
||||
try {
|
||||
const aiManager = aiServiceManagerModule.default;
|
||||
|
||||
if (!aiManager) {
|
||||
log.error("AI service manager is not initialized");
|
||||
return {
|
||||
error: "AI service is not properly initialized. Please check your configuration."
|
||||
};
|
||||
}
|
||||
|
||||
const availableProviders = aiManager.getAvailableProviders();
|
||||
if (availableProviders.length === 0) {
|
||||
log.error("No AI providers are available");
|
||||
return {
|
||||
error: "No AI providers are configured or available. Please check your AI settings."
|
||||
};
|
||||
}
|
||||
} catch (err) {
|
||||
log.error(`Detailed AI service check failed: ${err}`);
|
||||
}
|
||||
|
||||
return {
|
||||
error: "AI services are currently unavailable. Please check your configuration."
|
||||
};
|
||||
}
|
||||
|
||||
// Get the AI service manager
|
||||
const aiServiceManager = aiServiceManagerModule.default.getInstance();
|
||||
|
||||
// Get the default service - just use the first available one
|
||||
const availableProviders = aiServiceManager.getAvailableProviders();
|
||||
|
||||
if (availableProviders.length === 0) {
|
||||
log.error("No AI providers are available after manager check");
|
||||
return {
|
||||
error: "No AI providers are configured or available. Please check your AI settings."
|
||||
};
|
||||
}
|
||||
|
||||
// Use the first available provider
|
||||
const providerName = availableProviders[0];
|
||||
log.info(`Using AI provider: ${providerName}`);
|
||||
|
||||
// We know the manager has a 'services' property from our code inspection,
|
||||
// but TypeScript doesn't know that from the interface.
|
||||
// This is a workaround to access it
|
||||
const service = (aiServiceManager as any).services[providerName];
|
||||
|
||||
if (!service) {
|
||||
log.error(`AI service for provider ${providerName} not found`);
|
||||
return {
|
||||
error: `Selected AI provider (${providerName}) is not available. Please check your configuration.`
|
||||
};
|
||||
}
|
||||
|
||||
// Information to return to the client
|
||||
let aiResponse = '';
|
||||
let sourceNotes: NoteSource[] = [];
|
||||
|
||||
// Check if this is a streaming request
|
||||
const isStreamingRequest = req.method === 'GET' && req.query.format === 'stream';
|
||||
|
||||
// For POST requests, we need to process the message
|
||||
// For GET (streaming) requests, we use the latest user message from the session
|
||||
if (req.method === 'POST' || isStreamingRequest) {
|
||||
// Get the latest user message for context
|
||||
const latestUserMessage = session.messages
|
||||
.filter(msg => msg.role === 'user')
|
||||
.pop();
|
||||
|
||||
if (!latestUserMessage && req.method === 'GET') {
|
||||
throw new Error('No user message found in session');
|
||||
}
|
||||
|
||||
// Use the latest message content for GET requests
|
||||
const messageContent = req.method === 'POST' ? content : latestUserMessage!.content;
|
||||
|
||||
try {
|
||||
// If Advanced Context is enabled, we use the improved method
|
||||
if (useAdvancedContext) {
|
||||
sourceNotes = await this.processAdvancedContext(
|
||||
messageContent,
|
||||
session,
|
||||
service,
|
||||
isStreamingRequest,
|
||||
res,
|
||||
showThinking
|
||||
);
|
||||
} else {
|
||||
sourceNotes = await this.processStandardContext(
|
||||
messageContent,
|
||||
session,
|
||||
service,
|
||||
isStreamingRequest,
|
||||
res
|
||||
);
|
||||
}
|
||||
|
||||
// For streaming requests we don't return anything as we've already sent the response
|
||||
if (isStreamingRequest) {
|
||||
return null;
|
||||
}
|
||||
|
||||
// For POST requests, return the response
|
||||
if (req.method === 'POST') {
|
||||
// Get the latest assistant message for the response
|
||||
const latestAssistantMessage = session.messages
|
||||
.filter(msg => msg.role === 'assistant')
|
||||
.pop();
|
||||
|
||||
return {
|
||||
content: latestAssistantMessage?.content || '',
|
||||
sources: sourceNotes.map(note => ({
|
||||
noteId: note.noteId,
|
||||
title: note.title,
|
||||
similarity: note.similarity
|
||||
}))
|
||||
};
|
||||
}
|
||||
} catch (processingError: any) {
|
||||
log.error(`Error processing message: ${processingError}`);
|
||||
return {
|
||||
error: `Error processing your request: ${processingError.message}`
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
// If it's not a POST or streaming GET request, return the session's message history
|
||||
return {
|
||||
id: session.id,
|
||||
messages: session.messages
|
||||
};
|
||||
} catch (error: any) {
|
||||
log.error(`Error in LLM query processing: ${error}`);
|
||||
return {
|
||||
error: ERROR_PROMPTS.USER_ERRORS.GENERAL_ERROR
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Process a request with advanced context
|
||||
*/
|
||||
private async processAdvancedContext(
|
||||
messageContent: string,
|
||||
session: ChatSession,
|
||||
service: any,
|
||||
isStreamingRequest: boolean,
|
||||
res: Response,
|
||||
showThinking: boolean
|
||||
): Promise<NoteSource[]> {
|
||||
// Use the Trilium-specific approach
|
||||
const contextNoteId = session.noteContext || null;
|
||||
|
||||
// Log that we're calling contextService with the parameters
|
||||
log.info(`Using enhanced context with: noteId=${contextNoteId}, showThinking=${showThinking}`);
|
||||
|
||||
const results = await contextService.processQuery(
|
||||
messageContent,
|
||||
service,
|
||||
contextNoteId,
|
||||
showThinking
|
||||
);
|
||||
|
||||
// Get the generated context
|
||||
const context = results.context;
|
||||
// Convert from NoteSearchResult to NoteSource
|
||||
const sourceNotes = results.sources.map(source => ({
|
||||
noteId: source.noteId,
|
||||
title: source.title,
|
||||
content: source.content || undefined, // Convert null to undefined
|
||||
similarity: source.similarity
|
||||
}));
|
||||
|
||||
// Format messages for the LLM using the proper context
|
||||
const aiMessages = await contextService.buildMessagesWithContext(
|
||||
session.messages.slice(-LLM_CONSTANTS.SESSION.MAX_SESSION_MESSAGES).map(msg => ({
|
||||
role: msg.role,
|
||||
content: msg.content
|
||||
})),
|
||||
context,
|
||||
service
|
||||
);
|
||||
|
||||
// DEBUG: Log message structure being sent to LLM
|
||||
log.info(`Message structure being sent to LLM: ${aiMessages.length} messages total`);
|
||||
|
||||
// Configure chat options from session metadata
|
||||
const chatOptions: ChatCompletionOptions = {
|
||||
temperature: session.metadata.temperature || 0.7,
|
||||
maxTokens: session.metadata.maxTokens,
|
||||
model: session.metadata.model,
|
||||
stream: isStreamingRequest ? true : undefined
|
||||
};
|
||||
|
||||
// Process based on whether this is a streaming request
|
||||
if (isStreamingRequest) {
|
||||
await this.handleStreamingResponse(res, aiMessages, chatOptions, service, session);
|
||||
} else {
|
||||
// Non-streaming approach for POST requests
|
||||
const response = await service.generateChatCompletion(aiMessages, chatOptions);
|
||||
const aiResponse = response.text; // Extract the text from the response
|
||||
|
||||
// Store the assistant's response in the session
|
||||
session.messages.push({
|
||||
role: 'assistant',
|
||||
content: aiResponse,
|
||||
timestamp: new Date()
|
||||
});
|
||||
}
|
||||
|
||||
return sourceNotes;
|
||||
}
|
||||
|
||||
/**
|
||||
* Process a request with standard context
|
||||
*/
|
||||
private async processStandardContext(
|
||||
messageContent: string,
|
||||
session: ChatSession,
|
||||
service: any,
|
||||
isStreamingRequest: boolean,
|
||||
res: Response
|
||||
): Promise<NoteSource[]> {
|
||||
// Original approach - find relevant notes through direct embedding comparison
|
||||
const relevantNotes = await this.findRelevantNotes(
|
||||
messageContent,
|
||||
session.noteContext || null,
|
||||
5
|
||||
);
|
||||
|
||||
// Build context from relevant notes
|
||||
const context = this.buildContextFromNotes(relevantNotes, messageContent);
|
||||
|
||||
// Get messages with context properly formatted for the specific LLM provider
|
||||
const aiMessages = await contextService.buildMessagesWithContext(
|
||||
session.messages.slice(-LLM_CONSTANTS.SESSION.MAX_SESSION_MESSAGES).map(msg => ({
|
||||
role: msg.role,
|
||||
content: msg.content
|
||||
})),
|
||||
context,
|
||||
service
|
||||
);
|
||||
|
||||
// Configure chat options from session metadata
|
||||
const chatOptions: ChatCompletionOptions = {
|
||||
temperature: session.metadata.temperature || 0.7,
|
||||
maxTokens: session.metadata.maxTokens,
|
||||
model: session.metadata.model,
|
||||
stream: isStreamingRequest ? true : undefined
|
||||
};
|
||||
|
||||
if (isStreamingRequest) {
|
||||
await this.handleStreamingResponse(res, aiMessages, chatOptions, service, session);
|
||||
} else {
|
||||
// Non-streaming approach for POST requests
|
||||
const response = await service.generateChatCompletion(aiMessages, chatOptions);
|
||||
const aiResponse = response.text; // Extract the text from the response
|
||||
|
||||
// Store the assistant's response in the session
|
||||
session.messages.push({
|
||||
role: 'assistant',
|
||||
content: aiResponse,
|
||||
timestamp: new Date()
|
||||
});
|
||||
}
|
||||
|
||||
return relevantNotes;
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle streaming response from LLM
|
||||
*/
|
||||
private async handleStreamingResponse(
|
||||
res: Response,
|
||||
aiMessages: Message[],
|
||||
chatOptions: ChatCompletionOptions,
|
||||
service: any,
|
||||
session: ChatSession
|
||||
) {
|
||||
// Set streaming headers once
|
||||
res.setHeader('Content-Type', 'text/event-stream');
|
||||
res.setHeader('Cache-Control', 'no-cache');
|
||||
res.setHeader('Connection', 'keep-alive');
|
||||
|
||||
// Flag to indicate we've handled the response directly
|
||||
// This lets the route handler know not to process the result
|
||||
(res as any).triliumResponseHandled = true;
|
||||
|
||||
let messageContent = '';
|
||||
|
||||
try {
|
||||
// Use the correct method name: generateChatCompletion
|
||||
const response = await service.generateChatCompletion(aiMessages, chatOptions);
|
||||
|
||||
// Handle streaming if the response includes a stream method
|
||||
if (response.stream) {
|
||||
await response.stream((chunk: { text: string; done: boolean }) => {
|
||||
if (chunk.text) {
|
||||
messageContent += chunk.text;
|
||||
// Only write if the response hasn't finished
|
||||
if (!res.writableEnded) {
|
||||
res.write(`data: ${JSON.stringify({ content: chunk.text })}\n\n`);
|
||||
}
|
||||
}
|
||||
|
||||
if (chunk.done) {
|
||||
// Signal the end of the stream when done, only if not already ended
|
||||
if (!res.writableEnded) {
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
}
|
||||
});
|
||||
} else {
|
||||
// If no streaming available, send the response as a single chunk
|
||||
messageContent = response.text;
|
||||
// Only write if the response hasn't finished
|
||||
if (!res.writableEnded) {
|
||||
res.write(`data: ${JSON.stringify({ content: messageContent })}\n\n`);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
}
|
||||
|
||||
// Store the full response for the session
|
||||
const aiResponse = messageContent;
|
||||
|
||||
// Store the assistant's response in the session
|
||||
session.messages.push({
|
||||
role: 'assistant',
|
||||
content: aiResponse,
|
||||
timestamp: new Date()
|
||||
});
|
||||
} catch (streamingError: any) {
|
||||
// If streaming fails and we haven't sent a response yet, throw the error
|
||||
if (!res.headersSent) {
|
||||
throw streamingError;
|
||||
} else {
|
||||
// If headers were already sent, try to send an error event
|
||||
try {
|
||||
if (!res.writableEnded) {
|
||||
res.write(`data: ${JSON.stringify({ error: streamingError.message })}\n\n`);
|
||||
res.write('data: [DONE]\n\n');
|
||||
res.end();
|
||||
}
|
||||
} catch (e) {
|
||||
log.error(`Failed to write streaming error: ${e}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Build context from relevant notes
|
||||
*/
|
||||
buildContextFromNotes(sources: NoteSource[], query: string): string {
|
||||
if (!sources || sources.length === 0) {
|
||||
return query || '';
|
||||
}
|
||||
|
||||
const noteContexts = sources
|
||||
.filter(source => source.content) // Only include sources with content
|
||||
.map((source) => {
|
||||
// Format each note with its title as a natural heading and wrap in <note> tags
|
||||
return `<note>\n### ${source.title}\n${source.content || 'No content available'}\n</note>`;
|
||||
})
|
||||
.join('\n\n');
|
||||
|
||||
if (!noteContexts) {
|
||||
return query || '';
|
||||
}
|
||||
|
||||
// Import the CONTEXT_PROMPTS constant
|
||||
const { CONTEXT_PROMPTS } = require('./constants/llm_prompt_constants.js');
|
||||
|
||||
// Use the template from the constants file, replacing placeholders
|
||||
return CONTEXT_PROMPTS.CONTEXT_NOTES_WRAPPER
|
||||
.replace('{noteContexts}', noteContexts)
|
||||
.replace('{query}', query);
|
||||
}
|
||||
|
||||
/**
|
||||
* Get all sessions
|
||||
*/
|
||||
getSessions() {
|
||||
return sessions;
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a new chat session
|
||||
*/
|
||||
async createSession(req: Request, res: Response) {
|
||||
try {
|
||||
// Initialize cleanup if not already done
|
||||
this.initializeCleanupTimer();
|
||||
|
||||
const options: any = req.body || {};
|
||||
const title = options.title || 'Chat Session';
|
||||
|
||||
const sessionId = uuidv4();
|
||||
const now = new Date();
|
||||
|
||||
// Initial system message if provided
|
||||
const messages: ChatMessage[] = [];
|
||||
if (options.systemPrompt) {
|
||||
messages.push({
|
||||
role: 'system',
|
||||
content: options.systemPrompt,
|
||||
timestamp: now
|
||||
});
|
||||
}
|
||||
|
||||
// Store session info
|
||||
sessions.set(sessionId, {
|
||||
id: sessionId,
|
||||
title,
|
||||
messages,
|
||||
createdAt: now,
|
||||
lastActive: now,
|
||||
noteContext: options.contextNoteId,
|
||||
metadata: {
|
||||
temperature: options.temperature,
|
||||
maxTokens: options.maxTokens,
|
||||
model: options.model,
|
||||
provider: options.provider
|
||||
}
|
||||
});
|
||||
|
||||
return {
|
||||
id: sessionId,
|
||||
title,
|
||||
createdAt: now
|
||||
};
|
||||
} catch (error: any) {
|
||||
log.error(`Error creating LLM session: ${error.message || 'Unknown error'}`);
|
||||
throw new Error(`Failed to create LLM session: ${error.message || 'Unknown error'}`);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get a specific chat session by ID
|
||||
*/
|
||||
async getSession(req: Request, res: Response) {
|
||||
try {
|
||||
const { sessionId } = req.params;
|
||||
|
||||
// Check if session exists
|
||||
const session = sessions.get(sessionId);
|
||||
if (!session) {
|
||||
throw new Error(`Session with ID ${sessionId} not found`);
|
||||
}
|
||||
|
||||
// Return session without internal metadata
|
||||
return {
|
||||
id: session.id,
|
||||
title: session.title,
|
||||
createdAt: session.createdAt,
|
||||
lastActive: session.lastActive,
|
||||
messages: session.messages,
|
||||
noteContext: session.noteContext
|
||||
};
|
||||
} catch (error: any) {
|
||||
log.error(`Error getting LLM session: ${error.message || 'Unknown error'}`);
|
||||
throw new Error(`Failed to get session: ${error.message || 'Unknown error'}`);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Update a chat session's settings
|
||||
*/
|
||||
async updateSession(req: Request, res: Response) {
|
||||
try {
|
||||
const { sessionId } = req.params;
|
||||
const updates = req.body || {};
|
||||
|
||||
// Check if session exists
|
||||
const session = sessions.get(sessionId);
|
||||
if (!session) {
|
||||
throw new Error(`Session with ID ${sessionId} not found`);
|
||||
}
|
||||
|
||||
// Update allowed fields
|
||||
if (updates.title) {
|
||||
session.title = updates.title;
|
||||
}
|
||||
|
||||
if (updates.noteContext) {
|
||||
session.noteContext = updates.noteContext;
|
||||
}
|
||||
|
||||
// Update metadata
|
||||
if (updates.temperature !== undefined) {
|
||||
session.metadata.temperature = updates.temperature;
|
||||
}
|
||||
|
||||
if (updates.maxTokens !== undefined) {
|
||||
session.metadata.maxTokens = updates.maxTokens;
|
||||
}
|
||||
|
||||
if (updates.model) {
|
||||
session.metadata.model = updates.model;
|
||||
}
|
||||
|
||||
if (updates.provider) {
|
||||
session.metadata.provider = updates.provider;
|
||||
}
|
||||
|
||||
// Update timestamp
|
||||
session.lastActive = new Date();
|
||||
|
||||
return {
|
||||
id: session.id,
|
||||
title: session.title,
|
||||
updatedAt: session.lastActive
|
||||
};
|
||||
} catch (error: any) {
|
||||
log.error(`Error updating LLM session: ${error.message || 'Unknown error'}`);
|
||||
throw new Error(`Failed to update session: ${error.message || 'Unknown error'}`);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* List all chat sessions
|
||||
*/
|
||||
async listSessions(req: Request, res: Response) {
|
||||
try {
|
||||
const sessionList = Array.from(sessions.values()).map(session => ({
|
||||
id: session.id,
|
||||
title: session.title,
|
||||
createdAt: session.createdAt,
|
||||
lastActive: session.lastActive,
|
||||
messageCount: session.messages.length
|
||||
}));
|
||||
|
||||
// Sort by last activity (most recent first)
|
||||
sessionList.sort((a, b) => b.lastActive.getTime() - a.lastActive.getTime());
|
||||
|
||||
return {
|
||||
sessions: sessionList
|
||||
};
|
||||
} catch (error: any) {
|
||||
log.error(`Error listing LLM sessions: ${error.message || 'Unknown error'}`);
|
||||
throw new Error(`Failed to list sessions: ${error.message || 'Unknown error'}`);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Delete a chat session
|
||||
*/
|
||||
async deleteSession(req: Request, res: Response) {
|
||||
try {
|
||||
const { sessionId } = req.params;
|
||||
|
||||
// Check if session exists
|
||||
if (!sessions.has(sessionId)) {
|
||||
throw new Error(`Session with ID ${sessionId} not found`);
|
||||
}
|
||||
|
||||
// Delete session
|
||||
sessions.delete(sessionId);
|
||||
|
||||
return {
|
||||
success: true,
|
||||
message: `Session ${sessionId} deleted successfully`
|
||||
};
|
||||
} catch (error: any) {
|
||||
log.error(`Error deleting LLM session: ${error.message || 'Unknown error'}`);
|
||||
throw new Error(`Failed to delete session: ${error.message || 'Unknown error'}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Create singleton instance
|
||||
const restChatService = new RestChatService();
|
||||
export default restChatService;
|
||||
Loading…
x
Reference in New Issue
Block a user