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https://github.com/TriliumNext/Notes.git
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openai finally works, respect embedding precedence
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perf3ct
parent
ac40fff8d1
commit
5ad730c153
@ -150,18 +150,23 @@ export async function findSimilarNotes(
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providerId: string;
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modelId: string;
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count: number;
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dimension: number;
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}
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// Get all available embedding providers and models
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// Get all available embedding providers and models with dimensions
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const availableEmbeddings = await sql.getRows(`
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SELECT DISTINCT providerId, modelId, COUNT(*) as count
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SELECT DISTINCT providerId, modelId, COUNT(*) as count, dimension
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FROM note_embeddings
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GROUP BY providerId, modelId
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ORDER BY count DESC`
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) as EmbeddingMetadata[];
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if (availableEmbeddings.length > 0) {
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log.info(`Available embeddings: ${JSON.stringify(availableEmbeddings)}`);
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log.info(`Available embeddings: ${JSON.stringify(availableEmbeddings.map(e => ({
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providerId: e.providerId,
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modelId: e.modelId,
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count: e.count
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})))}`);
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// Import the AIServiceManager to get provider precedence
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const { default: aiManager } = await import('../ai_service_manager.js');
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@ -210,24 +215,81 @@ export async function findSimilarNotes(
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const providerEmbeddings = availableEmbeddings.filter(e => e.providerId === provider);
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if (providerEmbeddings.length > 0) {
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// Use the model with the most embeddings
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const bestModel = providerEmbeddings.sort((a, b) => b.count - a.count)[0];
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// Find models that match the current embedding's dimensions
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const dimensionMatchingModels = providerEmbeddings.filter(e => e.dimension === embedding.length);
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log.info(`Trying fallback provider: ${provider}, model: ${bestModel.modelId}`);
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// If we have models with matching dimensions, use the one with most embeddings
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if (dimensionMatchingModels.length > 0) {
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const bestModel = dimensionMatchingModels.sort((a, b) => b.count - a.count)[0];
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log.info(`Found fallback provider with matching dimensions (${embedding.length}): ${provider}, model: ${bestModel.modelId}`);
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// Recursive call with the new provider/model, but disable further fallbacks
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return findSimilarNotes(
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embedding,
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provider,
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bestModel.modelId,
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limit,
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threshold,
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false // Prevent infinite recursion
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);
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// Recursive call with the new provider/model, but disable further fallbacks
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return findSimilarNotes(
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embedding,
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provider,
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bestModel.modelId,
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limit,
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threshold,
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false // Prevent infinite recursion
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);
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} else {
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// We need to regenerate embeddings with the new provider
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log.info(`No models with matching dimensions found for ${provider}. Available models: ${JSON.stringify(
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providerEmbeddings.map(e => ({ model: e.modelId, dimension: e.dimension }))
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)}`);
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try {
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// Import provider manager to get a provider instance
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const { default: providerManager } = await import('./providers.js');
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const providerInstance = providerManager.getEmbeddingProvider(provider);
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if (providerInstance) {
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// Use the model with the most embeddings
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const bestModel = providerEmbeddings.sort((a, b) => b.count - a.count)[0];
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// Configure the model by setting it in the config
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try {
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// Access the config safely through the getConfig method
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const config = providerInstance.getConfig();
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config.model = bestModel.modelId;
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log.info(`Trying to convert query to ${provider}/${bestModel.modelId} embedding format (dimension: ${bestModel.dimension})`);
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// Get the original query from the embedding cache if possible, or use a placeholder
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// This is a hack - ideally we'd pass the query text through the whole chain
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const originalQuery = "query"; // This is a placeholder, we'd need the original query text
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// Generate a new embedding with the fallback provider
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const newEmbedding = await providerInstance.generateEmbeddings(originalQuery);
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log.info(`Successfully generated new embedding with provider ${provider}/${bestModel.modelId} (dimension: ${newEmbedding.length})`);
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// Now try finding similar notes with the new embedding
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return findSimilarNotes(
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newEmbedding,
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provider,
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bestModel.modelId,
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limit,
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threshold,
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false // Prevent infinite recursion
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);
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} catch (configErr: any) {
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log.error(`Error configuring provider ${provider}: ${configErr.message}`);
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}
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}
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} catch (err: any) {
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log.error(`Error converting embedding format: ${err.message}`);
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}
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}
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}
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}
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log.info(`No suitable fallback providers found. Available embeddings: ${JSON.stringify(availableEmbeddings)}`);
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log.error(`No suitable fallback providers found with compatible dimensions. Current embedding dimension: ${embedding.length}`);
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log.info(`Available embeddings: ${JSON.stringify(availableEmbeddings.map(e => ({
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providerId: e.providerId,
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modelId: e.modelId,
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dimension: e.dimension,
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count: e.count
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})))}`);
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} else {
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log.info(`No embeddings found in the database at all. You need to generate embeddings first.`);
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}
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@ -240,14 +302,27 @@ export async function findSimilarNotes(
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}
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// Calculate similarity for each embedding
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const similarities = rows.map(row => {
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const similarities = [];
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for (const row of rows) {
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const rowData = row as any;
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const rowEmbedding = bufferToEmbedding(rowData.embedding, rowData.dimension);
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return {
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noteId: rowData.noteId,
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similarity: cosineSimilarity(embedding, rowEmbedding)
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};
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});
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// Check if dimensions match before calculating similarity
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if (rowEmbedding.length !== embedding.length) {
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log.info(`Skipping embedding ${rowData.embedId} - dimension mismatch: ${rowEmbedding.length} vs ${embedding.length}`);
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continue;
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}
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try {
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const similarity = cosineSimilarity(embedding, rowEmbedding);
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similarities.push({
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noteId: rowData.noteId,
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similarity
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});
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} catch (err: any) {
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log.error(`Error calculating similarity for note ${rowData.noteId}: ${err.message}`);
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}
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}
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// Filter by threshold and sort by similarity (highest first)
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const results = similarities
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@ -490,16 +490,61 @@ class IndexService {
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}
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try {
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// Get all enabled embedding providers
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const providers = await providerManager.getEnabledEmbeddingProviders();
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if (!providers || providers.length === 0) {
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throw new Error("No embedding providers available");
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}
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// Use the first enabled provider
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const provider = providers[0];
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// Get the embedding provider precedence
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const options = (await import('../options.js')).default;
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let preferredProviders: string[] = [];
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const embeddingPrecedence = await options.getOption('embeddingProviderPrecedence');
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let provider;
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if (embeddingPrecedence) {
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// Parse the precedence string
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if (embeddingPrecedence.startsWith('[') && embeddingPrecedence.endsWith(']')) {
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preferredProviders = JSON.parse(embeddingPrecedence);
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} else if (typeof embeddingPrecedence === 'string') {
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if (embeddingPrecedence.includes(',')) {
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preferredProviders = embeddingPrecedence.split(',').map(p => p.trim());
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} else {
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preferredProviders = [embeddingPrecedence];
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}
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}
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// Find first enabled provider by precedence order
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for (const providerName of preferredProviders) {
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const matchedProvider = providers.find(p => p.name === providerName);
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if (matchedProvider) {
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provider = matchedProvider;
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break;
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}
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}
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// If no match found, use first available
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if (!provider && providers.length > 0) {
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provider = providers[0];
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}
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} else {
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// Default to first available provider
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provider = providers[0];
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}
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if (!provider) {
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throw new Error("No suitable embedding provider found");
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}
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log.info(`Searching with embedding provider: ${provider.name}, model: ${provider.getConfig().model}`);
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// Generate embedding for the query
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const embedding = await provider.generateEmbeddings(query);
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log.info(`Generated embedding for query: "${query}" (${embedding.length} dimensions)`);
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// Get Note IDs to search, optionally filtered by branch
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let similarNotes = [];
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// Check if we need to restrict search to a specific branch
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if (contextNoteId) {
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@ -525,7 +570,6 @@ class IndexService {
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collectNoteIds(contextNoteId);
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// Get embeddings for all notes in the branch
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const similarNotes = [];
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const config = provider.getConfig();
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for (const noteId of branchNoteIds) {
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@ -557,7 +601,7 @@ class IndexService {
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} else {
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// Search across all notes
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const config = provider.getConfig();
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const similarNotes = await vectorStore.findSimilarNotes(
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similarNotes = await vectorStore.findSimilarNotes(
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embedding,
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provider.name,
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config.model,
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