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feat(TRUEREF-0020): add embedding profiles, default local embeddings, and version-scoped semantic retrieval

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- Add embedding_profiles table with provider registry pattern
- Install @xenova/transformers as runtime dependency
- Update snippet_embeddings with composite PK (snippet_id, profile_id)
- Seed default local profile using Xenova/all-MiniLM-L6-v2
- Add provider registry (local-transformers, openai-compatible)
- Update EmbeddingService to persist and retrieve by profileId
- Add version-scoped VectorSearch with optional versionId filtering
- Add searchMode (auto|keyword|semantic|hybrid) to HybridSearchService
- Update API /context route to load active profile, support searchMode/alpha params
- Extend MCP query-docs tool with searchMode and alpha parameters
- Update settings API to work with embedding_profiles table
- Add comprehensive test coverage for profiles, registry, version scoping

Status: 445/451 tests passing, core feature complete
This commit is contained in:
Giancarmine Salucci
2026-03-25 19:16:37 +01:00
parent fef6f66930
commit 169df4d984
19 changed files with 2668 additions and 246 deletions
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23
src/lib/server/embeddings/embedding.service.ts
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@@ -19,7 +19,8 @@ const TEXT_MAX_CHARS = 2048;
export class EmbeddingService {
constructor(
private readonly db: Database.Database,
private readonly provider: EmbeddingProvider
private readonly provider: EmbeddingProvider,
private readonly profileId: string = 'local-default'
) {}
/**
@@ -54,9 +55,9 @@ export class EmbeddingService {
.slice(0, TEXT_MAX_CHARS)
);
const insert = this.db.prepare<[string, string, number, Buffer]>(`
INSERT OR REPLACE INTO snippet_embeddings (snippet_id, model, dimensions, embedding, created_at)
VALUES (?, ?, ?, ?, unixepoch())
const insert = this.db.prepare<[string, string, string, number, Buffer]>(`
INSERT OR REPLACE INTO snippet_embeddings (snippet_id, profile_id, model, dimensions, embedding, created_at)
VALUES (?, ?, ?, ?, ?, unixepoch())
`);
for (let i = 0; i < snippets.length; i += BATCH_SIZE) {
@@ -71,6 +72,7 @@ export class EmbeddingService {
const embedding = embeddings[j];
insert.run(
snippet.id,
this.profileId,
embedding.model,
embedding.dimensions,
Buffer.from(embedding.values.buffer)
@@ -85,14 +87,17 @@ export class EmbeddingService {
/**
* Retrieve a stored embedding for a snippet as a Float32Array.
* Returns null when no embedding has been stored for the given snippet.
* Returns null when no embedding has been stored for the given snippet and profile.
*
* @param snippetId - Snippet UUID
* @param profileId - Embedding profile ID (default: 'local-default')
*/
getEmbedding(snippetId: string): Float32Array | null {
getEmbedding(snippetId: string, profileId: string = 'local-default'): Float32Array | null {
const row = this.db
.prepare<[string], { embedding: Buffer; dimensions: number }>(
`SELECT embedding, dimensions FROM snippet_embeddings WHERE snippet_id = ?`
.prepare<[string, string], { embedding: Buffer; dimensions: number }>(
`SELECT embedding, dimensions FROM snippet_embeddings WHERE snippet_id = ? AND profile_id = ?`
)
.get(snippetId);
.get(snippetId, profileId);
if (!row) return null;