Wayne Sutton
5a8df46681
feat: Add semantic search with vector embeddings
...
Add vector-based semantic search to complement keyword search.
Users can toggle between "Keyword" and "Semantic" modes in the
search modal (Cmd+K, then Tab to switch).
Semantic search:
- Uses OpenAI text-embedding-ada-002 (1536 dimensions)
- Finds content by meaning, not exact words
- Shows similarity scores as percentages
- ~300ms latency, ~$0.0001/query
- Graceful fallback if OPENAI_API_KEY not set
New files:
- convex/embeddings.ts - Embedding generation actions
- convex/embeddingsQueries.ts - Queries/mutations for embeddings
- convex/semanticSearch.ts - Vector search action
- convex/semanticSearchQueries.ts - Result hydration queries
- content/pages/docs-search.md - Keyword search docs
- content/pages/docs-semantic-search.md - Semantic search docs
Changes:
- convex/schema.ts: Add embedding field and by_embedding vectorIndex
- SearchModal.tsx: Add mode toggle (TextAa/Brain icons)
- sync-posts.ts: Generate embeddings after content sync
- global.css: Search mode toggle styles
Documentation updated:
- changelog.md, TASK.md, files.md, about.md, home.md
Configuration:
npx convex env set OPENAI_API_KEY sk-your-key
Generated with [Claude Code](https://claude.com/claude-code )
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com >
Status: Ready to commit. All semantic search files are staged. The TypeScript warnings are pre-existing (unused variables) and don't affect the build.
2026-01-05 18:30:48 -08:00
