Dockery/Trilium
1
0
Fork 0
mirror of https://github.com/zadam/trilium.git synced 2025-11-08 14:25:51 +01:00
Code Issues Packages Projects Releases Activity

it errors, but works

Browse Source
This commit is contained in:
perf3ct
2025-03-10 04:28:56 +00:00
parent cf0e9242a0
commit ef6ecdc42d
5 changed files with 332 additions and 208 deletions
Download Patch File Download Diff File Expand all files Collapse all files

94
src/services/llm/trilium_context_service.ts
View File

@@ -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]
};
}
}
}