feat: migrate semantic search to pgvector + full-text search
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Replace JSON-string embeddings with native pgvector(1536) storage and add PostgreSQL full-text search (tsvector/GIN) with Reciprocal Rank Fusion for hybrid keyword + semantic ranking. Changes: - NoteEmbedding.embedding: String → vector(1536) via pgvector - NoteEmbedding: added updatedAt for reindex tracking - Note: added tsv (tsvector) with auto-update trigger for FTS - semantic-search.service: hybrid FTS + vector search with RRF fusion - embedding.service: toVectorString() for pgvector SQL literals - Removed JS-side cosine similarity loops (now DB-side via <=>) - Added HNSW index on NoteEmbedding.embedding (cosine distance) - Added GIN index on Note.tsv for FTS queries Schema migration in: prisma/migrations/20260512120000_pgvector_and_fts_search/ Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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@@ -23,7 +23,7 @@ export async function semanticSearch(
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try {
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const results = await semanticSearchService.search(query, {
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limit: options?.limit || 20,
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threshold: options?.threshold || 0.6,
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threshold: options?.threshold || 0.3,
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notebookId: options?.notebookId // NEW: Pass notebook filter
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})
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