feat(agent): selectable fusion; adopt the measured 0.4/0.6 default weights

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]>
2026-09-19 16:57:51 -07:00
parent b23946e62d
commit 29baabbed2
7 changed files with 256 additions and 79 deletions
@@ -37,7 +37,7 @@
 //! let mem = AsyncHDF5Memory::open_with(path, config).await?;
 //! mem.save(entry).await?;           // buffered → background writer
 //! mem.save_batch(entries).await?;    // also buffered
-//! let results = mem.hybrid_search(emb, "query".into(), 0.7, 0.3, 5).await;
+//! let results = mem.hybrid_search(emb, "query".into(), 0.4, 0.6, 5).await;
 //! mem.shutdown().await?;             // final flush + stop
 //! ```