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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architectural-grid10/src/main.tsx
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architectural-grid10/src/main.tsx
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import {StrictMode} from 'react';
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import {createRoot} from 'react-dom/client';
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import App from './App.tsx';
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import './index.css';
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createRoot(document.getElementById('root')!).render(
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<StrictMode>
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<App />
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</StrictMode>,
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);
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