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https://github.com/TriliumNext/Notes.git
synced 2025-07-29 11:02:28 +08:00
it errors, but works
This commit is contained in:
perf3ct
parent
cf0e9242a0
commit
ef6ecdc42d
@ -133,8 +133,20 @@ export default class LlmChatPanel extends BasicWidget {
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try {
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const useAdvancedContext = this.useAdvancedContextCheckbox.checked;
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// Setup streaming
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const source = new EventSource(`./api/llm/messages?sessionId=${this.sessionId}&format=stream`);
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// Create the message parameters
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const messageParams = {
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content,
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contextNoteId: this.currentNoteId,
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useAdvancedContext
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};
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// First, send the message via POST request
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await server.post<any>(`llm/sessions/${this.sessionId}/messages`, messageParams);
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// Then set up streaming via EventSource
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const streamUrl = `./api/llm/sessions/${this.sessionId}/messages?format=stream&useAdvancedContext=${useAdvancedContext}`;
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const source = new EventSource(streamUrl);
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let assistantResponse = '';
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// Handle streaming response
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@ -171,18 +183,6 @@ export default class LlmChatPanel extends BasicWidget {
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toastService.showError('Error connecting to the LLM service. Please try again.');
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};
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// Send the actual message
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const response = await server.post<any>('llm/messages', {
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sessionId: this.sessionId,
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content,
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contextNoteId: this.currentNoteId,
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useAdvancedContext
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});
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// Handle sources if returned in non-streaming response
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if (response && response.sources && response.sources.length > 0) {
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this.showSources(response.sources);
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}
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} catch (error) {
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this.hideLoadingIndicator();
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toastService.showError('Error sending message: ' + (error as Error).message);
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@ -449,26 +449,57 @@ Now, based on the above notes, please answer: ${query}`;
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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 the content from the request body
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const { content, sessionId, useAdvancedContext = false } = req.body || {};
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// Extract parameters differently based on the request method
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let content, useAdvancedContext, sessionId;
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// Validate the content
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if (!content || typeof content !== 'string' || content.trim().length === 0) {
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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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} 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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content = ''; // We don't need content for GET requests
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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 = acceptHeader && acceptHeader.includes('text/event-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 or create the session
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let session: ChatSession;
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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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if (sessionId && sessions.has(sessionId)) {
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session = sessions.get(sessionId)!;
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session.lastActive = new Date();
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} else {
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const result = await createSession(req, res);
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if (!result?.id) {
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throw new Error('Failed to create a new session');
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}
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session = sessions.get(result.id)!;
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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)}${content.length > 50 ? '...' : ''}"`);
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}
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// Check if AI services are available
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@ -495,184 +526,225 @@ async function sendMessage(req: Request, res: Response) {
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throw new Error('No AI service is available');
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}
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// Create user message
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const userMessage: Message = {
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role: 'user',
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content
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};
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// Add message to session
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session.messages.push({
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role: 'user',
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content,
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timestamp: new Date()
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});
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// Log a preview of the message
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log.info(`Processing LLM message: "${content.substring(0, 50)}${content.length > 50 ? '...' : ''}"`);
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// Information to return to the client
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let aiResponse = '';
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let sourceNotes: NoteSource[] = [];
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// If Advanced Context is enabled, we use the improved method
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if (useAdvancedContext) {
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// Use the Trilium-specific approach
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const contextNoteId = session.noteContext || null;
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const results = await triliumContextService.processQuery(content, service, contextNoteId);
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// For POST requests, we need to process the message
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// For GET (streaming) requests, we use the latest user message from the session
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if (req.method === 'POST' || isStreamingRequest) {
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// Get the latest user message for context
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const latestUserMessage = session.messages
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.filter(msg => msg.role === 'user')
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.pop();
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// Get the generated context
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const context = results.context;
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sourceNotes = results.notes;
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if (!latestUserMessage && req.method === 'GET') {
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throw new Error('No user message found in session');
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}
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// Add system message with the context
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const contextMessage: Message = {
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role: 'system',
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content: context
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};
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// Use the latest message content for GET requests
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const messageContent = req.method === 'POST' ? content : latestUserMessage!.content;
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// Format all messages for the AI
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const aiMessages: Message[] = [
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contextMessage,
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...session.messages.slice(-10).map(msg => ({
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role: msg.role,
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content: msg.content
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}))
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];
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// If Advanced Context is enabled, we use the improved method
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if (useAdvancedContext) {
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// Use the Trilium-specific approach
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const contextNoteId = session.noteContext || null;
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const results = await triliumContextService.processQuery(messageContent, service, contextNoteId);
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// Configure chat options from session metadata
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const chatOptions: ChatCompletionOptions = {
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temperature: session.metadata.temperature || 0.7,
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maxTokens: session.metadata.maxTokens,
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model: session.metadata.model
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// 'provider' property has been removed as it's not in the ChatCompletionOptions type
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};
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// Get the generated context
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const context = results.context;
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sourceNotes = results.notes;
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// Get streaming response if requested
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const acceptHeader = req.get('Accept');
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if (acceptHeader && acceptHeader.includes('text/event-stream')) {
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res.setHeader('Content-Type', 'text/event-stream');
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res.setHeader('Cache-Control', 'no-cache');
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res.setHeader('Connection', 'keep-alive');
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// Add system message with the context
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const contextMessage: Message = {
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role: 'system',
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content: context
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};
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let messageContent = '';
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// Format all messages for the AI
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const aiMessages: Message[] = [
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contextMessage,
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...session.messages.slice(-10).map(msg => ({
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role: msg.role,
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content: msg.content
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}))
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];
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// Stream the response
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await service.sendChatCompletion(
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aiMessages,
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chatOptions,
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(chunk: string) => {
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messageContent += chunk;
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res.write(`data: ${JSON.stringify({ content: chunk })}\n\n`);
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// Configure chat options from session metadata
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const chatOptions: ChatCompletionOptions = {
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temperature: session.metadata.temperature || 0.7,
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maxTokens: session.metadata.maxTokens,
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model: session.metadata.model,
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stream: isStreamingRequest ? true : undefined
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};
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// Process based on whether this is a streaming request
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if (isStreamingRequest) {
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res.setHeader('Content-Type', 'text/event-stream');
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res.setHeader('Cache-Control', 'no-cache');
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res.setHeader('Connection', 'keep-alive');
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let messageContent = '';
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// Use the correct method name: generateChatCompletion
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const response = await service.generateChatCompletion(aiMessages, chatOptions);
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// Handle streaming if the response includes a stream method
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if (response.stream) {
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await response.stream((chunk: { text: string; done: boolean }) => {
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if (chunk.text) {
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messageContent += chunk.text;
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res.write(`data: ${JSON.stringify({ content: chunk.text })}\n\n`);
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}
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if (chunk.done) {
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// Signal the end of the stream when done
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res.write('data: [DONE]\n\n');
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res.end();
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}
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});
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} else {
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// If no streaming available, send the response as a single chunk
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messageContent = response.text;
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res.write(`data: ${JSON.stringify({ content: messageContent })}\n\n`);
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res.write('data: [DONE]\n\n');
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res.end();
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}
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// Store the full response for the session
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aiResponse = messageContent;
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// Store the assistant's response in the session
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session.messages.push({
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role: 'assistant',
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content: aiResponse,
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timestamp: new Date()
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});
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} else {
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// Non-streaming approach for POST requests
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const response = await service.generateChatCompletion(aiMessages, chatOptions);
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aiResponse = response.text; // Extract the text from the response
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// Store the assistant's response in the session
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session.messages.push({
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role: 'assistant',
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content: aiResponse,
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timestamp: new Date()
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});
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// Return the response for POST requests
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return {
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content: aiResponse,
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sources: sourceNotes.map(note => ({
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noteId: note.noteId,
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title: note.title,
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similarity: note.similarity,
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branchId: note.branchId
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}))
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};
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}
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} else {
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// Original approach - find relevant notes through direct embedding comparison
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const relevantNotes = await findRelevantNotes(
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content,
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session.noteContext || null,
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5
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);
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// Close the stream
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res.write('data: [DONE]\n\n');
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res.end();
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sourceNotes = relevantNotes;
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// Store the full response
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aiResponse = messageContent;
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} else {
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// Non-streaming approach
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aiResponse = await service.sendChatCompletion(aiMessages, chatOptions);
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}
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} else {
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// Original approach - find relevant notes through direct embedding comparison
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const relevantNotes = await findRelevantNotes(
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content,
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session.noteContext || null,
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5
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);
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// Build context from relevant notes
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const context = buildContextFromNotes(relevantNotes, content);
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sourceNotes = relevantNotes;
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// Add system message with the context
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const contextMessage: Message = {
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role: 'system',
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content: context
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};
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// Build context from relevant notes
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const context = buildContextFromNotes(relevantNotes, content);
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// Format all messages for the AI
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const aiMessages: Message[] = [
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contextMessage,
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...session.messages.slice(-10).map(msg => ({
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role: msg.role,
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content: msg.content
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}))
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];
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// Add system message with the context
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const contextMessage: Message = {
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role: 'system',
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content: context
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};
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// Configure chat options from session metadata
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const chatOptions: ChatCompletionOptions = {
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temperature: session.metadata.temperature || 0.7,
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maxTokens: session.metadata.maxTokens,
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model: session.metadata.model,
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stream: isStreamingRequest ? true : undefined
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};
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// Format all messages for the AI
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const aiMessages: Message[] = [
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contextMessage,
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...session.messages.slice(-10).map(msg => ({
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role: msg.role,
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content: msg.content
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}))
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];
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if (isStreamingRequest) {
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res.setHeader('Content-Type', 'text/event-stream');
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res.setHeader('Cache-Control', 'no-cache');
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res.setHeader('Connection', 'keep-alive');
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// Configure chat options from session metadata
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const chatOptions: ChatCompletionOptions = {
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temperature: session.metadata.temperature || 0.7,
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maxTokens: session.metadata.maxTokens,
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model: session.metadata.model
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// 'provider' property has been removed as it's not in the ChatCompletionOptions type
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};
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let messageContent = '';
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// Get streaming response if requested
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const acceptHeader = req.get('Accept');
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if (acceptHeader && acceptHeader.includes('text/event-stream')) {
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res.setHeader('Content-Type', 'text/event-stream');
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res.setHeader('Cache-Control', 'no-cache');
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res.setHeader('Connection', 'keep-alive');
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// Use the correct method name: generateChatCompletion
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const response = await service.generateChatCompletion(aiMessages, chatOptions);
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let messageContent = '';
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// Handle streaming if the response includes a stream method
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if (response.stream) {
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await response.stream((chunk: { text: string; done: boolean }) => {
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if (chunk.text) {
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messageContent += chunk.text;
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res.write(`data: ${JSON.stringify({ content: chunk.text })}\n\n`);
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}
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// Stream the response
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await service.sendChatCompletion(
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aiMessages,
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chatOptions,
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(chunk: string) => {
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messageContent += chunk;
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res.write(`data: ${JSON.stringify({ content: chunk })}\n\n`);
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if (chunk.done) {
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// Signal the end of the stream when done
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res.write('data: [DONE]\n\n');
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res.end();
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}
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});
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} else {
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// If no streaming available, send the response as a single chunk
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messageContent = response.text;
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res.write(`data: ${JSON.stringify({ content: messageContent })}\n\n`);
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res.write('data: [DONE]\n\n');
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res.end();
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}
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);
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// Close the stream
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res.write('data: [DONE]\n\n');
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res.end();
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// Store the full response for the session
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aiResponse = messageContent;
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// Store the full response
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aiResponse = messageContent;
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} else {
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// Non-streaming approach
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aiResponse = await service.sendChatCompletion(aiMessages, chatOptions);
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// Store the assistant's response in the session
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session.messages.push({
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role: 'assistant',
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content: aiResponse,
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timestamp: new Date()
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});
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} else {
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// Non-streaming approach for POST requests
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const response = await service.generateChatCompletion(aiMessages, chatOptions);
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aiResponse = response.text; // Extract the text from the response
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// Store the assistant's response in the session
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session.messages.push({
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role: 'assistant',
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content: aiResponse,
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timestamp: new Date()
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});
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// Return the response for POST requests
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return {
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content: aiResponse,
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sources: sourceNotes.map(note => ({
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noteId: note.noteId,
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title: note.title,
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similarity: note.similarity,
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branchId: note.branchId
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}))
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};
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}
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}
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}
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// Only store the assistant's message if we're not streaming (otherwise we already did)
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const acceptHeader = req.get('Accept');
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if (!acceptHeader || !acceptHeader.includes('text/event-stream')) {
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// Store the assistant's response in the session
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session.messages.push({
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role: 'assistant',
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content: aiResponse,
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timestamp: new Date()
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});
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// Return the response
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return {
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content: aiResponse,
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sources: sourceNotes.map(note => ({
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noteId: note.noteId,
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title: note.title,
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similarity: note.similarity,
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branchId: note.branchId
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}))
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};
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} else {
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// For streaming responses, we've already sent the data
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// But we still need to add the message to the session
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session.messages.push({
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role: 'assistant',
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content: aiResponse,
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timestamp: new Date()
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});
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}
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} catch (error: any) {
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log.error(`Error sending message to LLM: ${error.message}`);
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throw new Error(`Failed to send message: ${error.message}`);
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@ -387,6 +387,7 @@ function register(app: express.Application) {
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apiRoute(PATCH, "/api/llm/sessions/:sessionId", llmRoute.updateSession);
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apiRoute(DEL, "/api/llm/sessions/:sessionId", llmRoute.deleteSession);
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apiRoute(PST, "/api/llm/sessions/:sessionId/messages", llmRoute.sendMessage);
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route(GET, "/api/llm/sessions/:sessionId/messages", [auth.checkApiAuth, csrfMiddleware], llmRoute.sendMessage, apiResultHandler);
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// Ollama API endpoints
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route(PST, "/api/ollama/list-models", [auth.checkApiAuth, csrfMiddleware], ollamaRoute.listModels, apiResultHandler);
|
||||
|
||||
@ -40,7 +40,20 @@ export class AIServiceManager {
|
||||
|
||||
if (customOrder) {
|
||||
try {
|
||||
const parsed = JSON.parse(customOrder);
|
||||
// Try to parse as JSON first
|
||||
let parsed;
|
||||
|
||||
// Handle both array in JSON format and simple string format
|
||||
if (customOrder.startsWith('[') && customOrder.endsWith(']')) {
|
||||
parsed = JSON.parse(customOrder);
|
||||
} else if (typeof customOrder === 'string') {
|
||||
// If it's a simple string (like "ollama"), convert to single-item array
|
||||
parsed = [customOrder];
|
||||
} else {
|
||||
// Fallback to default
|
||||
parsed = defaultOrder;
|
||||
}
|
||||
|
||||
// Validate that all providers are valid
|
||||
if (Array.isArray(parsed) &&
|
||||
parsed.every(p => Object.keys(this.services).includes(p))) {
|
||||
|
||||
@ -102,12 +102,13 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
|
||||
maxTokens: 300
|
||||
};
|
||||
|
||||
// Get the response from the LLM
|
||||
const response = await llmService.sendTextCompletion(messages, options);
|
||||
// Get the response from the LLM using the correct method name
|
||||
const response = await llmService.generateChatCompletion(messages, options);
|
||||
const responseText = response.text; // Extract the text from the response object
|
||||
|
||||
try {
|
||||
// Parse the JSON response
|
||||
const jsonStr = response.trim().replace(/```json|```/g, '').trim();
|
||||
const jsonStr = responseText.trim().replace(/```json|```/g, '').trim();
|
||||
const queries = JSON.parse(jsonStr);
|
||||
|
||||
if (Array.isArray(queries) && queries.length > 0) {
|
||||
@ -117,7 +118,7 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
|
||||
}
|
||||
} catch (parseError) {
|
||||
// Fallback: if JSON parsing fails, try to extract queries line by line
|
||||
const lines = response.split('\n')
|
||||
const lines = responseText.split('\n')
|
||||
.map((line: string) => line.trim())
|
||||
.filter((line: string) => line.length > 0 && !line.startsWith('```'));
|
||||
|
||||
@ -176,8 +177,8 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
|
||||
|
||||
// Process each query
|
||||
for (const query of queries) {
|
||||
// Get embeddings for this query
|
||||
const queryEmbedding = await this.provider.getEmbedding(query);
|
||||
// Get embeddings for this query using the correct method name
|
||||
const queryEmbedding = await this.provider.generateEmbeddings(query);
|
||||
|
||||
// Find notes similar to this query
|
||||
let results;
|
||||
@ -192,8 +193,8 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
|
||||
// Search all notes
|
||||
results = await vectorStore.findSimilarNotes(
|
||||
queryEmbedding,
|
||||
this.provider.id,
|
||||
this.provider.modelId,
|
||||
this.provider.name, // Use name property instead of id
|
||||
this.provider.getConfig().model, // Use getConfig().model instead of modelId
|
||||
Math.min(limit, 5), // Limit per query
|
||||
0.5 // Lower threshold to get more diverse results
|
||||
);
|
||||
@ -265,8 +266,8 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
|
||||
for (const noteId of subtreeNoteIds) {
|
||||
const noteEmbedding = await vectorStore.getEmbeddingForNote(
|
||||
noteId,
|
||||
this.provider.id,
|
||||
this.provider.modelId
|
||||
this.provider.name, // Use name property instead of id
|
||||
this.provider.getConfig().model // Use getConfig().model instead of modelId
|
||||
);
|
||||
|
||||
if (noteEmbedding) {
|
||||
@ -338,7 +339,10 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
|
||||
*/
|
||||
buildContextFromNotes(sources: any[], query: string): string {
|
||||
if (!sources || sources.length === 0) {
|
||||
return "";
|
||||
// Return a default context instead of empty string
|
||||
return "I am an AI assistant helping you with your Trilium notes. " +
|
||||
"I couldn't find any specific notes related to your query, but I'll try to assist you " +
|
||||
"with general knowledge about Trilium or other topics you're interested in.";
|
||||
}
|
||||
|
||||
let context = `The following are relevant notes from your knowledge base that may help answer the query: "${query}"\n\n`;
|
||||
@ -382,28 +386,62 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
|
||||
*/
|
||||
async processQuery(userQuestion: string, llmService: any, contextNoteId: string | null = null) {
|
||||
if (!this.initialized) {
|
||||
await this.initialize();
|
||||
try {
|
||||
await this.initialize();
|
||||
} catch (error) {
|
||||
log.error(`Failed to initialize TriliumContextService: ${error}`);
|
||||
// Return a fallback response if initialization fails
|
||||
return {
|
||||
context: "I am an AI assistant helping you with your Trilium notes. " +
|
||||
"I'll try to assist you with general knowledge about your query.",
|
||||
notes: [],
|
||||
queries: [userQuestion]
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
// Step 1: Generate search queries
|
||||
const searchQueries = await this.generateSearchQueries(userQuestion, llmService);
|
||||
log.info(`Generated search queries: ${JSON.stringify(searchQueries)}`);
|
||||
try {
|
||||
// Step 1: Generate search queries
|
||||
let searchQueries: string[];
|
||||
try {
|
||||
searchQueries = await this.generateSearchQueries(userQuestion, llmService);
|
||||
} catch (error) {
|
||||
log.error(`Error generating search queries, using fallback: ${error}`);
|
||||
searchQueries = [userQuestion]; // Fallback to using the original question
|
||||
}
|
||||
log.info(`Generated search queries: ${JSON.stringify(searchQueries)}`);
|
||||
|
||||
// Step 2: Find relevant notes using those queries
|
||||
const relevantNotes = await this.findRelevantNotesMultiQuery(
|
||||
searchQueries,
|
||||
contextNoteId,
|
||||
8 // Get more notes since we're using multiple queries
|
||||
);
|
||||
// Step 2: Find relevant notes using those queries
|
||||
let relevantNotes: any[] = [];
|
||||
try {
|
||||
relevantNotes = await this.findRelevantNotesMultiQuery(
|
||||
searchQueries,
|
||||
contextNoteId,
|
||||
8 // Get more notes since we're using multiple queries
|
||||
);
|
||||
} catch (error) {
|
||||
log.error(`Error finding relevant notes: ${error}`);
|
||||
// Continue with empty notes list
|
||||
}
|
||||
|
||||
// Step 3: Build context from the notes
|
||||
const context = this.buildContextFromNotes(relevantNotes, userQuestion);
|
||||
// Step 3: Build context from the notes
|
||||
const context = this.buildContextFromNotes(relevantNotes, userQuestion);
|
||||
|
||||
return {
|
||||
context,
|
||||
notes: relevantNotes,
|
||||
queries: searchQueries
|
||||
};
|
||||
return {
|
||||
context,
|
||||
notes: relevantNotes,
|
||||
queries: searchQueries
|
||||
};
|
||||
} catch (error) {
|
||||
log.error(`Error in processQuery: ${error}`);
|
||||
// Return a fallback response if anything fails
|
||||
return {
|
||||
context: "I am an AI assistant helping you with your Trilium notes. " +
|
||||
"I encountered an error while processing your query, but I'll try to assist you anyway.",
|
||||
notes: [],
|
||||
queries: [userQuestion]
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user