BENCHMARKS.md has recorded since the weight sweep that the 0.7/0.3 default is
strictly dominated by 0.4/0.6 over the full LongMemEval haystack, but the
shipping code never adopted it: unified_search and the OpenClaw backend both
passed 0.7/0.3. Re-running the sweep here (500 questions, real MiniLM
embeddings on a GPU) reproduces it — turn-level Hit@1 51.6% vs 44.2%, Hit@5
81.4% vs 79.2%, Hit@10 87.8% vs 85.8%, MRR 0.6430 vs 0.5856 — so both now use
hybrid::DEFAULT_FUSION, which is that operating point and carries the
reasoning. A unit test pins it.
Fusion is also selectable now. hybrid::Fusion is either Weighted { vector,
keyword } or Rrf { k }; hybrid::fuse applies either to one candidate list per
stage, and merge_vector_keyword / hybrid_search delegate to it, so the public
API is unchanged. New HDF5Memory::hybrid_search_with and
hybrid::hybrid_search_fused take a Fusion. Reciprocal rank fusion was
implemented but reachable only as a free function over a linear scan, so it
had never been compared with the weighted sum on equal terms; it is now a mode
in the LongMemEval bench (measurement to follow).
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Fusion min-max normalises over every keyword match, so hybrid_search asked
BM25 for a ranked list of the whole corpus: a hash insert per posting, then a
sort of every match, then the merge sorted every candidate again to keep k.
- BM25Index::scores returns every match unsorted, accumulated in a dense array
(contributions are strictly positive, so zero means untouched). search() is
built on it with the bounded heap.
- merge_vector_keyword partitions out its top k (select_nth) and orders only
those, with the same score-then-id order.
- Both hybrid paths use scores().
Rankings are identical (equivalence tests for both changes). p50 0.24 -> 0.07
ms (1K), 2.1 -> 0.49 ms (10K), 23 -> 4.65 ms (100K).
The harness gains --fusion-study, which measured the alternative — capping the
keyword pool — and found it changes the top-10 for most queries (overlap
0.83-0.92, different #1 for 10-35%) for only a 2x saving. Not adopted.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
test_hebbian_activation_boost failed intermittently. Root causes, all in the
query path:
- normalize_scores mapped a set of identical scores — including the
single-candidate case — to 0.0, so a lone perfect match contributed nothing
to the fused score. Identical positive scores now normalise to 1.0 (all
equally the best match); identical non-positive scores stay 0.0.
- merge_vector_keyword sorted a HashMap's entries by score alone and then
truncated, so which ties survived varied from run to run; hybrid_search had
the same problem in its final sort. Both now break ties by index.
- hybrid_search applied the Hebbian boost to every returned record, including
the zero-score filler that pads the list when fewer than k records match.
With random tie-breaking a filler record could collect as many boosts as the
real hit. Only records with a positive fused score are reinforced now.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Resolves two gaps found in a project-state review:
1. Python build was broken: PyO3/numpy 0.23 caps at Python 3.13 but the
environment has 3.14. Bumped to 0.28 and updated the two breaking APIs
(PyObject -> Py<PyAny>, allow_threads -> detach). The extension module now
imports and round-trips under Python 3.14, unblocking cargo build --workspace.
2. The "HNSW vector search over agent memories" headline was unwired:
clawhdf5-ann had zero dependents and the agent used a linear cosine+BM25 scan.
- clawhdf5-ann is now a live index: insert, mark_deleted (soft delete with a
deleted bitset, traversed but never returned), compact, and a format
version tag (v2) with backward-compatible load of v1 files.
- clawhdf5-agent wires HNSW behind the `hnsw` feature (ON by default). The
index mirrors the cache (node id == cache index) and self-heals: it rebuilds
whenever hnsw_synced_len drifts from cache.len(), so unhooked pushes can't
desync it. Non-indexable stores (no/zero-dim/mixed embeddings) and queries
whose dim doesn't match fall back to the exact linear scan.
- hybrid.rs gains merge_vector_keyword, shared by the linear and HNSW paths.
- tests/hnsw_integration.rs validates recall vs a brute-force oracle plus
insert/delete/batch behaviour.
Disable HNSW for exact search with `--no-default-features --features float16`.
Co-Authored-By: Claude Opus 4.8 (1M context) <[email protected]>
