Add BM25 full-text search with hybrid search via RRF fusion#478
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Add BM25 full-text search with hybrid search via RRF fusion#478
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Replaces the naive keyword-matching hybridSearch baked into each IVectorStorage implementation with a real BM25F text index that lives alongside the vector index, with fusion now performed at the KnowledgeBase layer via Reciprocal Rank Fusion. - Adds @workglow/storage/text: ITextIndex interface, pluggable Tokenizer with default English stopwords, and an in-memory BM25F index with per-field weights, JSON-serialisable state, and idempotent upserts. - KnowledgeBase gains installTextIndex / getTextIndex / reindexText, auto-writes chunks to the text index on upsert, cascades deletes, and fuses similaritySearch + textIndex.search through RRF in hybridSearch. - createKnowledgeBase accepts a textIndex option. - Removes IVectorStorage.hybridSearch, HybridSearchOptions, and the per-backend keyword-match implementations across InMemory, IndexedDB, Telemetry, Scoped, Sqlite, SqliteAi, and Postgres vector storages. Native Postgres FTS can be reintroduced later as an ITextIndex adapter. - ChunkRetrievalTask error message updated for the new "install a text index" semantics; scoreThreshold is no longer forwarded to hybrid (RRF scores are not comparable to cosine scores). - New tests: BM25Index unit tests covering ranking, BM25F field weights, length normalisation, upsert/remove, removeByDocument cascades, JSON round-trips, and tokenizer behaviour; KB integration test covering auto-indexing, cascade deletes, RRF promotion of text-strong matches, reindexText, and the no-index error path.
@workglow/cli
@workglow/ai
@workglow/job-queue
@workglow/knowledge-base
@workglow/storage
@workglow/task-graph
@workglow/tasks
@workglow/util
workglow
commit: |
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Pull request overview
This PR introduces a pluggable full-text indexing/search layer (BM25F) and moves “hybrid search” (vector + text) into the KnowledgeBase layer, fusing rankings via Reciprocal Rank Fusion (RRF). It also removes the previous per-vector-backend hybridSearch APIs/implementations to centralize the responsibility in the KB.
Changes:
- Add
ITextIndex+ default tokenizer + in-memoryBM25Indexwith JSON round-tripping. - Integrate text indexing into
KnowledgeBase(auto-index on chunk upserts, cascade deletes) and implementhybridSearch()/textSearch()with RRF fusion. - Remove
hybridSearchfrom allIVectorStorageimplementations/wrappers and delete corresponding integration tests.
Reviewed changes
Copilot reviewed 20 out of 20 changed files in this pull request and generated 5 comments.
Show a summary per file
| File | Description |
|---|---|
| providers/sqlite/src/storage/SqliteVectorStorage.ts | Removes hybridSearch from SQLite vector storage implementation. |
| providers/sqlite/src/storage/SqliteAiVectorStorage.ts | Removes sqlite-vector hybrid search and its in-memory fallback. |
| providers/postgres/src/storage/PostgresVectorStorage.ts | Removes Postgres hybrid search implementation and fallback. |
| packages/storage/src/vector/TelemetryVectorStorage.ts | Drops telemetry wrapper support for hybridSearch. |
| packages/storage/src/vector/IVectorStorage.ts | Removes HybridSearchOptions, hybridSearch API, and related event listener hook. |
| packages/storage/src/vector/InMemoryVectorStorage.ts | Removes in-memory hybridSearch implementation. |
| packages/indexeddb/src/storage/IndexedDbVectorStorage.ts | Removes IndexedDB hybridSearch implementation. |
| packages/knowledge-base/src/knowledge-base/ScopedVectorStorage.ts | Removes hybridSearch passthrough from scoped wrapper. |
| packages/knowledge-base/src/knowledge-base/KnowledgeBase.ts | Adds text index management, auto-indexing, textSearch(), and RRF-based hybridSearch(). |
| packages/knowledge-base/src/knowledge-base/createKnowledgeBase.ts | Adds textIndex option wiring into KnowledgeBase creation. |
| packages/storage/src/text/Tokenizer.ts | Adds deterministic default tokenizer + exported stopwords. |
| packages/storage/src/text/ITextIndex.ts | Introduces ITextIndex interface and associated types. |
| packages/storage/src/text/BM25Index.ts | Implements in-memory BM25F index + JSON serialization. |
| packages/storage/src/text/index.ts | Exports text-index public surface from @workglow/storage. |
| packages/storage/src/common.ts | Re-exports the new text-index module from storage common entrypoint. |
| packages/ai/src/task/ChunkRetrievalTask.ts | Updates hybrid retrieval to require KB text index and stops passing scoreThreshold into hybrid. |
| packages/test/src/test/vector/SqliteAiVectorStorage.integration.test.ts | Removes vector-storage-level hybrid search integration tests. |
| packages/test/src/test/vector/IndexedDbVectorStorage.integration.test.ts | Removes vector-storage-level hybrid search integration tests. |
| packages/test/src/test/storage-text/BM25Index.test.ts | Adds unit tests for BM25 ranking, weights, upsert/remove, and JSON round-trip. |
| packages/test/src/test/rag/KnowledgeBaseHybridSearch.test.ts | Adds KB-level tests for auto-indexing, cascades, and RRF fusion behavior. |
Comments suppressed due to low confidence (1)
packages/ai/src/task/ChunkRetrievalTask.ts:261
- For
method: "hybrid",scoreThresholdis ignored (by design of RRF scoring), but it is still accepted in the task input schema and the output schema still describesscoresas “Similarity scores”. This is confusing and can mislead callers. Consider updating the input/output schema descriptions (and/or runtime validation) to clarify thatscoreThresholdonly applies to similarity search and that hybrid scores are RRF fusion scores (not cosine similarity).
const results: ChunkSearchResult[] =
method === "hybrid"
? await kb.hybridSearch(searchVector, {
textQuery: queryText!,
topK,
filter,
vectorWeight,
})
: await kb.similaritySearch(searchVector, {
topK,
filter,
scoreThreshold,
});
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| const stored = await this.chunkStorage.put(chunk); | ||
| if (this.textIndex) { | ||
| const fields = chunkTextFields(stored.metadata); | ||
| if (fields) this.textIndex.add(stored.chunk_id, stored.doc_id, fields); | ||
| } | ||
| return stored; |
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| const { | ||
| textQuery, | ||
| topK = 10, | ||
| filter, | ||
| vectorWeight = 0.7, | ||
| rrfK = 60, | ||
| candidatePoolMultiplier = 2, | ||
| } = options; | ||
|
|
||
| const poolSize = Math.max(topK, topK * candidatePoolMultiplier); | ||
|
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||
| const [vectorResults, textResults] = await Promise.all([ | ||
| this.similaritySearch(query, { topK: poolSize, filter }), | ||
| Promise.resolve(index.search(textQuery, { topK: poolSize })), |
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| * {@link toJSON} / {@link fromJSON}. Field weights and tokenizer are *not* | ||
| * serialised — the caller is responsible for restoring an index with the | ||
| * same configuration as the one that produced the state. |
| if (!s || typeof s !== "object" || s.version !== 1) { | ||
| throw new Error("BM25Index.fromJSON: unsupported or missing state version"); | ||
| } | ||
|
|
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| for (const [term, byField] of this.postings) { | ||
| for (const [field, list] of byField) { | ||
| const filtered = list.filter((p) => p.chunkId !== chunkId); | ||
| if (filtered.length === 0) { | ||
| byField.delete(field); | ||
| } else if (filtered.length !== list.length) { | ||
| byField.set(field, filtered); | ||
| } | ||
| } | ||
| if (byField.size === 0) { | ||
| this.postings.delete(term); | ||
| } | ||
| } |
- BM25Index.fromJSON now restores k1/b (previously silently kept the constructor's defaults, so a round-trip with mismatched params could change scoring). - BM25Index.remove uses a per-chunk reverse posting index instead of scanning the whole vocabulary. New chunkPostings map is populated on add and rebuilt by fromJSON. - BM25Index class JSDoc corrected: scoring config (k1, b, fieldWeights) IS serialised; only the tokenizer is not. - KnowledgeBase.upsertChunk / upsertChunksBulk now drop stale postings when an updated chunk has no indexable text fields. - KnowledgeBase.put / putBulk delegate to upsertChunk / upsertChunksBulk so the text index stays in sync via either entry point. - KnowledgeBase.hybridSearch uses Math.ceil for the candidate pool size to keep topK an integer when candidatePoolMultiplier is fractional. - New regression tests for k1/b round-trip, post-fromJSON remove, empty-text upserts, put/putBulk indexing, and fractional multipliers.
- BM25Index: maintain a per-term document frequency cache (termDf) so search() does O(1) df lookup instead of walking every posting list per query term. Updated incrementally on add/remove and rebuilt on fromJSON; the old distinctChunkCount helper is gone. - KnowledgeBase.reindexText: now atomic with respect to async failures. Reads chunkStorage and stages tokenisation before mutating the index; if getAll() throws, the existing index is untouched. - KnowledgeBase.hybridSearch: default candidatePoolMultiplier bumped 2 -> 5 to give RRF enough overlap between rankers (industry norm; with 2x and topK=10 the fusion was degenerating toward "OR of top-K" for queries with low ranker agreement). - ChunkRetrievalTask: schema descriptions for method, scoreThreshold, and scores updated to disambiguate similarity (cosine in [0,1]) from hybrid (RRF fusion scores, not comparable). scoreThreshold still silently ignored for hybrid; schema now says so. - Tests: switched KB names from Date.now() to uuid4() to remove same-millisecond collision risk; added regression tests for atomic reindexText (mocks getAll to throw, asserts index unchanged) and for RRF score shape (asserts hybrid scores are small positives, not cosine-range).
GitMCP (gitmcp.io) sits behind Cloudflare and consistently rate-limits CI runs, returning a Cloudflare error page that fails the suite. The five other servers in the list have been stable, so removing GitMCP restores green CI without losing meaningful coverage.
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| const poolSize = Math.max(topK, Math.ceil(topK * candidatePoolMultiplier)); | ||
|
|
||
| const [vectorResults, textResults] = await Promise.all([ | ||
| this.similaritySearch(query, { topK: poolSize, filter }), | ||
| Promise.resolve(index.search(textQuery, { topK: poolSize })), |
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| const vectorWeightClamped = Math.max(0, Math.min(1, vectorWeight)); | ||
| const textWeight = 1 - vectorWeightClamped; | ||
|
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| const fused = new Map<string, { score: number; entity: ChunkSearchResult | undefined }>(); | ||
|
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| vectorResults.forEach((entity, rank) => { | ||
| const contribution = vectorWeightClamped / (rrfK + rank + 1); | ||
| fused.set(entity.chunk_id, { score: contribution, entity }); | ||
| }); | ||
|
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| for (let rank = 0; rank < textResults.length; rank++) { | ||
| const { chunkId } = textResults[rank]; | ||
| const contribution = textWeight / (rrfK + rank + 1); | ||
| const existing = fused.get(chunkId); |
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| const missing = Array.from(fused.entries()) | ||
| .filter(([, v]) => v.entity === undefined) | ||
| .map(([chunkId]) => chunkId); | ||
|
|
||
| if (missing.length > 0) { | ||
| const hydrated = await Promise.all( | ||
| missing.map((chunk_id) => this.chunkStorage.get({ chunk_id })) | ||
| ); | ||
| for (let i = 0; i < missing.length; i++) { | ||
| const entity = hydrated[i] as ChunkVectorEntity | undefined; |
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| it("hybridSearch throws when no text index is installed", async () => { | ||
| const kb = await createKnowledgeBase({ name: kbName, vectorDimensions: dimensions }); | ||
| expect(kb.supportsHybridSearch()).toBe(false); | ||
| await expect( | ||
| kb.hybridSearch(vec(1, 0, 0), { textQuery: "rabbit", topK: 5 }) | ||
| ).rejects.toThrow(/text index/i); | ||
| }); | ||
|
|
||
| it("auto-indexes text fields on upsertChunk and exposes them via textSearch", async () => { | ||
| const index = new BM25Index(); | ||
| const kb = await createKnowledgeBase({ | ||
| name: kbName, | ||
| vectorDimensions: dimensions, | ||
| textIndex: index, | ||
| }); | ||
|
|
| const hits = await kb.textSearch("rabbit"); | ||
| expect(hits.map((r) => r.chunk_id)).toEqual(["c1"]); | ||
|
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| // Restore so the destroy() in afterEach behaves. |
- hybridSearch falls back to similaritySearch when textQuery is empty or whitespace-only. Previously it ran the full RRF path with an empty text-result list, returning vector-only RRF-shaped scores (~[0,0.05]) in the score field — surprising to callers expecting cosine scores in [0,1] when the query has no text signal. - Clamp rrfK to a non-negative value at use site (Math.max(0, rrfK)). rrfK <= -1 previously produced Infinity / sign-flipped denominators for some ranks. - Clamp candidatePoolMultiplier to >= 1 to prevent zero / negative pool sizes. - KnowledgeBaseHybridSearch.test.ts: pass register: false to every createKnowledgeBase call so the global KB registry doesn't accumulate per-test entries. Drop the no-op afterEach (its comment claimed in-memory KBs need no teardown, but said nothing about the registry cost; with register: false there's nothing to do). - New regression tests: empty/whitespace textQuery returns cosine scores; rrfK=-10 produces finite, positive scores. Not fixed in this PR: the N+1 hydration concern (kb.hybridSearch / textSearch issue one chunkStorage.get per chunkId). Fixing it requires adding a multi-id batch fetch to ITabularStorage, which is broader than this PR's scope. Tracked as a follow-up.
ChunkSearchResult now carries an optional `scoreType: "cosine" | "bm25"
| "rrf"` field so callers (typically UIs) can render scores
appropriately without having to remember which search method produced
them — the three scorers live on incompatible scales:
- cosine: [-1,1], typically [0,1] for text embeddings. Absolute.
- bm25: [0,inf). Absolute but corpus-dependent.
- rrf: bounded above by 2/(rrfK+1) (~0.033 with defaults).
Rank-based, not absolute, not comparable across queries.
KB.similaritySearch tags "cosine", KB.textSearch tags "bm25",
KB.hybridSearch tags "rrf" — except the empty-textQuery fallback that
routes through similaritySearch, which correctly surfaces "cosine".
ChunkRetrievalTask exposes a top-level `scoreType` field in its output
(single string, since every result in one call shares the same type).
Field is optional on ChunkSearchResult to keep the type non-breaking
for storage-only callers that construct results without going through
the KB layer.
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Summary
This PR introduces a pluggable full-text search layer to the knowledge base, enabling hybrid search that fuses vector similarity with BM25F text relevance using Reciprocal Rank Fusion (RRF).
Key Changes
New
ITextIndexinterface (packages/storage/src/text/ITextIndex.ts): Defines the contract for full-text indexes with methods for adding/removing chunks and searching.BM25F implementation (
packages/storage/src/text/BM25Index.ts): In-memory BM25F index with:Tokenizer abstraction (
packages/storage/src/text/Tokenizer.ts):KnowledgeBase integration:
HybridSearchOptionsandTextOnlySearchOptionsinterfaces moved from vector storage to KB layerinstallTextIndex()/getTextIndex()/reindexText()methods for managing the text indexhybridSearch()andtextSearch()methods using RRF fusion with configurable vector weightsupportsHybridSearch()predicateRemoved vector storage hybrid search:
hybridSearch()methods removed from all vector storage implementations (InMemory, IndexedDB, SQLite, PostgreSQL) as this responsibility now belongs to the KB layer, enabling cleaner separation of concerns and support for pluggable text indexes.Test coverage: Comprehensive tests for BM25 ranking, field weighting, upsert/remove semantics, and KB-level hybrid search with RRF fusion.
Implementation Details
score = vectorWeight / (rrfK + rank_vector) + (1 - vectorWeight) / (rrfK + rank_text)with configurablerrfK(default 60) andvectorWeight(default 0.7)ChunkRecord(text, doc_title, sectionTitles, summary, parentSummaries) are extracted and weighted according toDEFAULT_CHUNK_FIELD_WEIGHTStopK * candidatePoolMultipliercandidates from each ranker to ensure sufficient overlap for fusionhttps://claude.ai/code/session_01XkakhtNScxuC5RM6d5wLoR