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openai finally works, respect embedding precedence

pull/1325/head
perf3ct 2025-03-17 21:36:14 +07:00
parent ac40fff8d1
commit 5ad730c153
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2 changed files with 147 additions and 28 deletions
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123
src/services/llm/embeddings/storage.ts
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@ -150,18 +150,23 @@ export async function findSimilarNotes(
providerId: string;
modelId: string;
count: number;
dimension: number;
}
// Get all available embedding providers and models
// Get all available embedding providers and models with dimensions
const availableEmbeddings = await sql.getRows(`
SELECT DISTINCT providerId, modelId, COUNT(*) as count
SELECT DISTINCT providerId, modelId, COUNT(*) as count, dimension
FROM note_embeddings
GROUP BY providerId, modelId
ORDER BY count DESC`
) as EmbeddingMetadata[];
if (availableEmbeddings.length > 0) {
log.info(`Available embeddings: ${JSON.stringify(availableEmbeddings)}`);
log.info(`Available embeddings: ${JSON.stringify(availableEmbeddings.map(e => ({
providerId: e.providerId,
modelId: e.modelId,
count: e.count
})))}`);
// Import the AIServiceManager to get provider precedence
const { default: aiManager } = await import('../ai_service_manager.js');
@ -210,24 +215,81 @@ export async function findSimilarNotes(
const providerEmbeddings = availableEmbeddings.filter(e => e.providerId === provider);
if (providerEmbeddings.length > 0) {
// Use the model with the most embeddings
const bestModel = providerEmbeddings.sort((a, b) => b.count - a.count)[0];
log.info(`Trying fallback provider: ${provider}, model: ${bestModel.modelId}`);
// Recursive call with the new provider/model, but disable further fallbacks
return findSimilarNotes(
embedding,
provider,
bestModel.modelId,
limit,
threshold,
false // Prevent infinite recursion
);
// Find models that match the current embedding's dimensions
const dimensionMatchingModels = providerEmbeddings.filter(e => e.dimension === embedding.length);
// If we have models with matching dimensions, use the one with most embeddings
if (dimensionMatchingModels.length > 0) {
const bestModel = dimensionMatchingModels.sort((a, b) => b.count - a.count)[0];
log.info(`Found fallback provider with matching dimensions (${embedding.length}): ${provider}, model: ${bestModel.modelId}`);
// Recursive call with the new provider/model, but disable further fallbacks
return findSimilarNotes(
embedding,
provider,
bestModel.modelId,
limit,
threshold,
false // Prevent infinite recursion
);
} else {
// We need to regenerate embeddings with the new provider
log.info(`No models with matching dimensions found for ${provider}. Available models: ${JSON.stringify(
providerEmbeddings.map(e => ({ model: e.modelId, dimension: e.dimension }))
)}`);
try {
// Import provider manager to get a provider instance
const { default: providerManager } = await import('./providers.js');
const providerInstance = providerManager.getEmbeddingProvider(provider);
if (providerInstance) {
// Use the model with the most embeddings
const bestModel = providerEmbeddings.sort((a, b) => b.count - a.count)[0];
// Configure the model by setting it in the config
try {
// Access the config safely through the getConfig method
const config = providerInstance.getConfig();
config.model = bestModel.modelId;
log.info(`Trying to convert query to ${provider}/${bestModel.modelId} embedding format (dimension: ${bestModel.dimension})`);
// Get the original query from the embedding cache if possible, or use a placeholder
// This is a hack - ideally we'd pass the query text through the whole chain
const originalQuery = "query"; // This is a placeholder, we'd need the original query text
// Generate a new embedding with the fallback provider
const newEmbedding = await providerInstance.generateEmbeddings(originalQuery);
log.info(`Successfully generated new embedding with provider ${provider}/${bestModel.modelId} (dimension: ${newEmbedding.length})`);
// Now try finding similar notes with the new embedding
return findSimilarNotes(
newEmbedding,
provider,
bestModel.modelId,
limit,
threshold,
false // Prevent infinite recursion
);
} catch (configErr: any) {
log.error(`Error configuring provider ${provider}: ${configErr.message}`);
}
}
} catch (err: any) {
log.error(`Error converting embedding format: ${err.message}`);
}
}
}
}
log.info(`No suitable fallback providers found. Available embeddings: ${JSON.stringify(availableEmbeddings)}`);
log.error(`No suitable fallback providers found with compatible dimensions. Current embedding dimension: ${embedding.length}`);
log.info(`Available embeddings: ${JSON.stringify(availableEmbeddings.map(e => ({
providerId: e.providerId,
modelId: e.modelId,
dimension: e.dimension,
count: e.count
})))}`);
} else {
log.info(`No embeddings found in the database at all. You need to generate embeddings first.`);
}
@ -240,14 +302,27 @@ export async function findSimilarNotes(
}
// Calculate similarity for each embedding
const similarities = rows.map(row => {
const similarities = [];
for (const row of rows) {
const rowData = row as any;
const rowEmbedding = bufferToEmbedding(rowData.embedding, rowData.dimension);
return {
noteId: rowData.noteId,
similarity: cosineSimilarity(embedding, rowEmbedding)
};
});
// Check if dimensions match before calculating similarity
if (rowEmbedding.length !== embedding.length) {
log.info(`Skipping embedding ${rowData.embedId} - dimension mismatch: ${rowEmbedding.length} vs ${embedding.length}`);
continue;
}
try {
const similarity = cosineSimilarity(embedding, rowEmbedding);
similarities.push({
noteId: rowData.noteId,
similarity
});
} catch (err: any) {
log.error(`Error calculating similarity for note ${rowData.noteId}: ${err.message}`);
}
}
// Filter by threshold and sort by similarity (highest first)
const results = similarities

52
src/services/llm/index_service.ts
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@ -490,16 +490,61 @@ class IndexService {
}
try {
// Get all enabled embedding providers
const providers = await providerManager.getEnabledEmbeddingProviders();
if (!providers || providers.length === 0) {
throw new Error("No embedding providers available");
}
// Use the first enabled provider
const provider = providers[0];
// Get the embedding provider precedence
const options = (await import('../options.js')).default;
let preferredProviders: string[] = [];
const embeddingPrecedence = await options.getOption('embeddingProviderPrecedence');
let provider;
if (embeddingPrecedence) {
// Parse the precedence string
if (embeddingPrecedence.startsWith('[') && embeddingPrecedence.endsWith(']')) {
preferredProviders = JSON.parse(embeddingPrecedence);
} else if (typeof embeddingPrecedence === 'string') {
if (embeddingPrecedence.includes(',')) {
preferredProviders = embeddingPrecedence.split(',').map(p => p.trim());
} else {
preferredProviders = [embeddingPrecedence];
}
}
// Find first enabled provider by precedence order
for (const providerName of preferredProviders) {
const matchedProvider = providers.find(p => p.name === providerName);
if (matchedProvider) {
provider = matchedProvider;
break;
}
}
// If no match found, use first available
if (!provider && providers.length > 0) {
provider = providers[0];
}
} else {
// Default to first available provider
provider = providers[0];
}
if (!provider) {
throw new Error("No suitable embedding provider found");
}
log.info(`Searching with embedding provider: ${provider.name}, model: ${provider.getConfig().model}`);
// Generate embedding for the query
const embedding = await provider.generateEmbeddings(query);
log.info(`Generated embedding for query: "${query}" (${embedding.length} dimensions)`);
// Get Note IDs to search, optionally filtered by branch
let similarNotes = [];
// Check if we need to restrict search to a specific branch
if (contextNoteId) {
@ -525,7 +570,6 @@ class IndexService {
collectNoteIds(contextNoteId);
// Get embeddings for all notes in the branch
const similarNotes = [];
const config = provider.getConfig();
for (const noteId of branchNoteIds) {
@ -557,7 +601,7 @@ class IndexService {
} else {
// Search across all notes
const config = provider.getConfig();
const similarNotes = await vectorStore.findSimilarNotes(
similarNotes = await vectorStore.findSimilarNotes(
embedding,
provider.name,
config.model,