Kent C. Dodds Adds SQLite FTS5 to Vector Search
Kent C. Dodds added SQLite FTS5 to Vectorize embeddings after semantic search missed exact matches like "React Testing Library." The hybrid pipeline uses Reciprocal Rank Fusion. If your search fails on API names, add BM25 backup, not bigger embedding models.
Kent C. Dodds added SQLite FTS5 lexical search alongside existing Vectorize semantic embeddings after pure vector search failed to surface exact title matches like "React Testing Library." The hybrid pipeline runs both retrieval methods in parallel and merges candidates using Reciprocal Rank Fusion, combining BM25-ranked exact word matching with dense vector intent search. He built the entire first implementation in about 20 minutes using Cursor with GPT-5.4.
Read the original → Kent C. Dodds Blog
- #search
- #sqlite
- #vector-search
- #full-text-search
- #nextjs
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