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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>
10 lines
445 B
Plaintext
10 lines
445 B
Plaintext
# GEMINI_API_KEY: Required for Gemini AI API calls.
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# AI Studio automatically injects this at runtime from user secrets.
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# Users configure this via the Secrets panel in the AI Studio UI.
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GEMINI_API_KEY="MY_GEMINI_API_KEY"
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# APP_URL: The URL where this applet is hosted.
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# AI Studio automatically injects this at runtime with the Cloud Run service URL.
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# Used for self-referential links, OAuth callbacks, and API endpoints.
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APP_URL="MY_APP_URL"
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