feat: hybrid search — FTS5 + sqlite-vec + RRF fusion (Phase 2a)#228
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- **Embedding pipeline** for Phase 2 hybrid search — notes are chunked, embedded via bge-small-en-v1.5 (q8, 384-dim), and stored in sqlite-vec with content-hash gating - **New modules:** `embedder.ts` (factory-closure, lazy ONNX model loading), `chunker.ts` (heading-aware splitting with paragraph sub-split), `plaintext.ts` (Obsidian markdown → plain text) - **Search index** gains vector tables (`note_chunks` + `note_vectors`), three-pass rebuild (Pass 3 = embedding), `embedNote` for incremental updates via file watcher - **`EMBEDDING_ENABLED`** env var (default: `true`) — when `false`, no model download, no vector tables, FTS5-only search Does **not** change `vault_search` behavior — that's PR \#3 (hybrid search with RRF fusion). - [x] 1130 tests pass (53 new: 10 embedder, 15 chunker, 15 plaintext, 8 search-index embedding, 5 config) - [x] TypeScript compiles clean (`tsc --noEmit`) - [x] Docker builds successfully - [x] Content-hash gating verified: re-embedding same content skips all chunks - [x] `EMBEDDING_ENABLED=false` verified: no vector tables created, embedNote is no-op - [x] removeNote cleans up vectors + chunks - [x] rebuildFromVault Pass 3 embeds all notes - [ ] Deploy to Lightsail via `phase2_deploy.yml` and verify search/memory/reads still work BREAKING CHANGE: Search index factory `createSearchIndex` gains an optional second parameter (`embedder`). Existing callers are unaffected. 🤖 Generated with [Claude Code](https://claude.com/claude-code) https://claude.ai/code/session_01JPDgHMKBvJ51V2YrrMYZET <!-- This is an auto-generated comment: release notes by coderabbit.ai --> * **New Features** * Added optional embedding-based search support, with a new setting to turn it on or off. * Notes are now chunked and embedded to improve search quality, while keeping basic search available as a fallback. * Updated container support to use a Debian-based image for broader compatibility. * **Documentation** * Updated setup and deployment guidance to explain the new search configuration option. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…ately (#218) - **Server blocked for ~5 min on first startup** while embedding every note — FTS was ready but the server didn't accept requests until Pass 3 finished - `rebuildFromVault` now returns after FTS indexing (Passes 1+2) and fires embedding (Pass 3) in the background - Return type changes from `number` to `{ count, embedding }` — server ignores the promise, tests can await it - [x] 1131 tests pass - [x] TypeScript compiles clean - [x] Embedding test awaits the background promise to verify embeddings complete - [ ] Deploy and verify server responds to health check within seconds of startup (not minutes) 🤖 Generated with [Claude Code](https://claude.com/claude-code) https://claude.ai/code/session_01JPDgHMKBvJ51V2YrrMYZET <!-- This is an auto-generated comment: release notes by coderabbit.ai --> * **New Features** * Added `EMBEDDING_ENABLED` feature flag (default: `true`) to disable the embedding pipeline and run search using FTS5 only. * Added `MEMORY_ENABLED` feature flag (default: `true`) to the local/remote compose setups. * **Bug Fixes** * Improved incremental indexing so unchanged content isn’t re-embedded and rebuilds preserve existing vector data. * Fixed missed re-embeds when an earlier embedding attempt fails, ensuring subsequent updates still proceed. * **Documentation / Tests** * Updated indexing documentation and environment-variable references; expanded search/indexing test coverage. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
## Summary - Add hybrid search (FTS5 + sqlite-vec vector + RRF fusion) to `vault_search` tool - Transparent upgrade: uses hybrid ranking when embeddings are available, falls back to FTS-only when they are not - Three new functions: `computeRrfScores` (pure RRF), `vectorSearch` (KNN), `hybridSearch` (orchestrator) - Updated `vault_search` tool description to reflect hybrid search capabilities ## Spike result 8/9 previously-failed queries fixed, 0 regressions, ~8ms latency (RRF-only mode). ## Test plan - [x] 9 `computeRrfScores` unit tests (table-driven: single/both systems, bonuses, custom k, sort order) - [x] 12 `hybridSearch` integration tests (fallback, hybrid ranking, filters, limits, dedup, callouts) - [x] All 1177 tests pass - [x] Build and lint clean - [ ] Deploy to Lightsail and run 9-query eval against live vault 🤖 Generated with [Claude Code](https://claude.com/claude-code) https://claude.ai/code/session_018ZbaHwP28ASYTpQnZk6MqM <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Search now uses a hybrid ranking approach that blends keyword and semantic matching for more relevant results. * Results can now fall back to keyword-only search when embeddings aren’t available. * Search snippets and result metadata are more complete for semantic matches, with improved relevance ordering. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
## Summary - ARCHITECTURE.md: hybrid search flow, RRF algorithm, fallback behavior, `search_mode`, Mermaid diagrams - README.md: value prop → "Hybrid search", Phase 2 status → "In progress", "AI agent" terminology - AGENTS.md: search module description updated in structure tree - .devin/wiki.json: hybrid search functions and conditional description documented - DEPLOY.md: `EMBEDDING_ENABLED` row clarified - 3x .env.example: "for hybrid search" instead of "for vector search" ## Test plan - [x] Build and tests pass (1182) - [x] Docs-only changes — no code modified <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Search now supports hybrid ranking, combining keyword and semantic results for more relevant matches. * Search responses now include the search mode used, making results clearer. * **Bug Fixes** * Search falls back cleanly to keyword-only matching when embeddings are unavailable or disabled. * Timestamps in search results are now handled more reliably. * **Documentation** * Updated setup and product docs to reflect hybrid search behavior and embedding configuration options. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
## What does this PR do? Updates README.md and ARCHITECTURE.md to reflect Phase 2a (hybrid search) as shipped — the final doc pass before merging `phase-2` into `main`. **README.md:** - Intro paragraph: `full-text search` → `hybrid search` in the bold callout - Roadmap table: split Phase 2 into Phase 2a (hybrid search, Complete) and Phase 2b (reranker, In progress) - How It Works mermaid diagram: `SQLite FTS5` → `SQLite FTS5 + sqlite-vec`, edge label updated to `FTS5 + vector` - Prose below diagram: accurately describes both persistence strategies (FTS rebuilds on startup, vectors persist with content-hash gating) and RRF fusion **ARCHITECTURE.md:** - Phasing section: `Phase 2 is in progress` → `Phase 2a` as shipped, with forward reference to Phase 2b (reranker) - Component diagram: moved sqlite-vec from a separate "Phase 2" subgraph with dotted arrows into the Docker Compose subgraph with solid arrows - Key Decisions table: two new rows — "Hybrid search over LightRAG" (grounded in the actual decision journey: LightRAG too heavy, qmd showed lightweight approach) and "RRF fusion (k=60)" (rank-based over score-based, validation results) - Search module decomposition: 5-module table (search-index, search-queries, search-helpers, fts-query, rrf) added before MCP Prompts section ## Type of change - [x] Documentation ## Checklist - [x] `npm test` passes - [x] `npm run lint` passes - [x] `npm run prettier:check` passes - [x] `npm run build` succeeds - [x] README or ARCHITECTURE.md updated (if user-facing behavior changed) > `npm test`, `npm run lint`, and `npm run build` require Node 24 (not available in this environment). Changes are docs-only — no code modified. --- _Generated by [Claude Code](https://claude.ai/code/session_01NP25qUqi8Phdro6EeMJjVo)_ <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Documentation** * Updated the product and architecture documentation to reflect the current search experience and roadmap. * Clarified that search now uses a hybrid approach, with improved description of how results are ranked and refreshed. * Revised roadmap details to split the upcoming search work into two stages, including a later reranking phase. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Claude <noreply@anthropic.com>
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## Summary - Folder inputs with trailing slashes (e.g. `"Projects/"`) produced a LIKE pattern with `//` (`Projects//%`) that silently returned zero results - Added `stripTrailingSlashes` helper in search-helpers.ts, applied at all 5 folder filter sites in search-queries.ts - 5 unit tests for the new helper Found by qodo in PR #228 review. ## Test plan - [x] `stripTrailingSlashes` unit tests (5 cases: single slash, multiple, no slash, internal slashes, bare name) - [x] Full search test suite passes (298 tests) 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
vault_searchnow combines FTS5 keyword ranking with sqlite-vec vector similarity via Reciprocal Rank Fusion (RRF). Keywords stay precise on exact terms; vectors bridge vocabulary gaps. 30% of natural-language queries that failed on FTS-only now return relevant results.EMBEDDING_ENABLED=falsedisables the pipeline entirely. Each query falls back to FTS-only when vectors aren't available.search_moderesponse field tells clients which ranking was used.PRs included
Test plan
EMBEDDING_ENABLED=false🤖 Generated with Claude Code