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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>
14 lines
311 B
HTML
14 lines
311 B
HTML
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>My Google AI Studio App</title>
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<body>
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<div id="root"></div>
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<script type="module" src="/src/main.tsx"></script>
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</body>
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