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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.