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https://github.com/TriliumNext/Notes.git
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improve LLM response parsing
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perf3ct
parent
c40c702761
commit
14acd1cd89
@ -29,7 +29,7 @@ class TriliumContextService {
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// Configuration
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private cacheExpiryMs = 5 * 60 * 1000; // 5 minutes
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private metaPrompt = `You are an AI assistant that decides what information needs to be retrieved from a knowledge base to answer the user's question.
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private metaPrompt = `You are an AI assistant that decides what information needs to be retrieved from a user's knowledge base called TriliumNext Notes to answer the user's question.
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Given the user's question, generate 3-5 specific search queries that would help find relevant information.
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Each query should be focused on a different aspect of the question.
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Format your answer as a JSON array of strings, with each string being a search query.
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@ -127,28 +127,74 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
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const responseText = response.text; // Extract the text from the response object
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try {
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// Parse the JSON response
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const jsonStr = responseText.trim().replace(/```json|```/g, '').trim();
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const queries = JSON.parse(jsonStr);
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// Remove code blocks, quotes, and clean up the response text
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let jsonStr = responseText
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.replace(/```(?:json)?|```/g, '') // Remove code block markers
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.replace(/[\u201C\u201D]/g, '"') // Replace smart quotes with straight quotes
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.trim();
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if (Array.isArray(queries) && queries.length > 0) {
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return queries;
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} else {
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throw new Error("Invalid response format");
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// Check if the text might contain a JSON array (has square brackets)
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if (jsonStr.includes('[') && jsonStr.includes(']')) {
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// Extract just the array part if there's explanatory text
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const arrayMatch = jsonStr.match(/\[[\s\S]*\]/);
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if (arrayMatch) {
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jsonStr = arrayMatch[0];
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}
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// Try to parse the JSON
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try {
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const queries = JSON.parse(jsonStr);
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if (Array.isArray(queries) && queries.length > 0) {
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return queries.map(q => typeof q === 'string' ? q : String(q)).filter(Boolean);
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}
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} catch (innerError) {
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// If parsing fails, log it and continue to the fallback
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log.info(`JSON parse error: ${innerError}. Will use fallback parsing for: ${jsonStr}`);
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}
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}
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} catch (parseError) {
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// Fallback: if JSON parsing fails, try to extract queries line by line
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// Fallback 1: Try to extract an array manually by splitting on commas between quotes
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if (jsonStr.includes('[') && jsonStr.includes(']')) {
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const arrayContent = jsonStr.substring(
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jsonStr.indexOf('[') + 1,
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jsonStr.lastIndexOf(']')
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);
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// Use regex to match quoted strings, handling escaped quotes
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const stringMatches = arrayContent.match(/"((?:\\.|[^"\\])*)"/g);
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if (stringMatches && stringMatches.length > 0) {
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return stringMatches
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.map((m: string) => m.substring(1, m.length - 1)) // Remove surrounding quotes
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.filter((s: string) => s.length > 0);
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}
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}
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// Fallback 2: Extract queries line by line
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const lines = responseText.split('\n')
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.map((line: string) => line.trim())
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.filter((line: string) => line.length > 0 && !line.startsWith('```'));
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.filter((line: string) =>
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line.length > 0 &&
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!line.startsWith('```') &&
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!line.match(/^\d+\.?\s*$/) && // Skip numbered list markers alone
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!line.match(/^\[|\]$/) // Skip lines that are just brackets
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);
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if (lines.length > 0) {
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return lines.map((line: string) => line.replace(/^["'\d\.\-\s]+/, '').trim());
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// Remove numbering, quotes and other list markers from each line
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return lines.map((line: string) => {
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return line
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.replace(/^\d+\.?\s*/, '') // Remove numbered list markers (1., 2., etc)
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.replace(/^[-*•]\s*/, '') // Remove bullet list markers
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.replace(/^["']|["']$/g, '') // Remove surrounding quotes
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.trim();
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}).filter((s: string) => s.length > 0);
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}
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// If all else fails, just use the original question
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return [userQuestion];
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} catch (parseError) {
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log.error(`Error parsing search queries: ${parseError}`);
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}
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// If all else fails, just use the original question
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return [userQuestion];
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} catch (error: unknown) {
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const errorMessage = error instanceof Error ? error.message : String(error);
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log.error(`Error generating search queries: ${errorMessage}`);
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@ -195,10 +241,14 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
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// Set to keep track of note IDs we've seen to avoid duplicates
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const seenNoteIds = new Set<string>();
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// Log the provider and model being used
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log.info(`Searching with embedding provider: ${this.provider.name}, model: ${this.provider.getConfig().model}`);
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// Process each query
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for (const query of queries) {
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// Get embeddings for this query using the correct method name
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const queryEmbedding = await this.provider.generateEmbeddings(query);
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log.info(`Generated embedding for query: "${query}" (${queryEmbedding.length} dimensions)`);
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// Find notes similar to this query
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let results;
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@ -209,6 +259,7 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
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contextNoteId,
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Math.min(limit, 5) // Limit per query
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);
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log.info(`Found ${results.length} notes within branch context for query: "${query}"`);
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} else {
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// Search all notes
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results = await vectorStore.findSimilarNotes(
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@ -218,6 +269,7 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
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Math.min(limit, 5), // Limit per query
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0.5 // Lower threshold to get more diverse results
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);
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log.info(`Found ${results.length} notes in vector store for query: "${query}"`);
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}
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// Process results
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@ -246,6 +298,8 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
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.sort((a, b) => b.similarity - a.similarity)
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.slice(0, limit);
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log.info(`Total unique relevant notes found across all queries: ${sortedResults.length}`);
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// Cache the results
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this.recentQueriesCache.set(cacheKey, {
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timestamp: Date.now(),
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@ -362,22 +416,33 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
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"with general knowledge about Trilium or other topics you're interested in.";
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}
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let context = `I've found some relevant information in your notes that may help answer: "${query}"\n\n`;
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// Get provider name to adjust context for different models
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const providerId = this.provider?.name || 'default';
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// Import the constants dynamically to avoid circular dependencies
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const { LLM_CONSTANTS } = await import('../../routes/api/llm.js');
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// Get appropriate context size and format based on provider
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const maxTotalLength =
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providerId === 'openai' ? LLM_CONSTANTS.CONTEXT_WINDOW.OPENAI :
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providerId === 'anthropic' ? LLM_CONSTANTS.CONTEXT_WINDOW.ANTHROPIC :
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providerId === 'ollama' ? LLM_CONSTANTS.CONTEXT_WINDOW.OLLAMA :
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LLM_CONSTANTS.CONTEXT_WINDOW.DEFAULT;
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// Use a format appropriate for the model family
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// Anthropic has a specific system message format that works better with certain structures
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const isAnthropicFormat = providerId === 'anthropic';
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// Start with different headers based on provider
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let context = isAnthropicFormat
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? `I'm your AI assistant helping with your Trilium notes database. For your query: "${query}", I found these relevant notes:\n\n`
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: `I've found some relevant information in your notes that may help answer: "${query}"\n\n`;
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// Sort sources by similarity if available to prioritize most relevant
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if (sources[0] && sources[0].similarity !== undefined) {
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sources = [...sources].sort((a, b) => (b.similarity || 0) - (a.similarity || 0));
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}
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// Get provider name to adjust context for different models
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const providerId = this.provider?.name || 'default';
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// Get approximate max length based on provider using constants
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// Import the constants dynamically to avoid circular dependencies
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const { LLM_CONSTANTS } = await import('../../routes/api/llm.js');
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const maxTotalLength = providerId === 'ollama' ? LLM_CONSTANTS.CONTEXT_WINDOW.OLLAMA :
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providerId === 'openai' ? LLM_CONSTANTS.CONTEXT_WINDOW.OPENAI :
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LLM_CONSTANTS.CONTEXT_WINDOW.ANTHROPIC;
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// Track total context length to avoid oversized context
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let currentLength = context.length;
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const maxNoteContentLength = Math.min(LLM_CONSTANTS.CONTENT.MAX_NOTE_CONTENT_LENGTH,
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@ -387,7 +452,7 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
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// Check if adding this source would exceed our total limit
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if (currentLength >= maxTotalLength) return;
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// Build source section
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// Build source section with formatting appropriate for the provider
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let sourceSection = `### ${source.title}\n`;
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// Add relationship context if available
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@ -429,11 +494,16 @@ Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`;
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}
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});
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// Add clear instructions about how to reference the notes
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context += "When referring to information from these notes in your response, please cite them by their titles " +
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"(e.g., \"According to your note on [Title]...\") rather than using labels like \"Note 1\" or \"Note 2\".\n\n";
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context += "If the information doesn't contain what you need, just say so and use your general knowledge instead.";
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// Add provider-specific instructions
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if (isAnthropicFormat) {
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context += "When you refer to any information from these notes, cite the note title explicitly (e.g., \"According to the note [Title]...\"). " +
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"If the provided notes don't answer the query fully, acknowledge that and then use your general knowledge to help.\n\n" +
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"Be concise but thorough in your responses.";
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} else {
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context += "When referring to information from these notes in your response, please cite them by their titles " +
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"(e.g., \"According to your note on [Title]...\") rather than using labels like \"Note 1\" or \"Note 2\".\n\n" +
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"If the information doesn't contain what you need, just say so and use your general knowledge instead.";
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}
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return context;
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}
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