v3.10.29

## What ships — batched per "no constant releases"

Four independent threads:

1. **3rd BEIR dataset (ArguAna)** — strengthens 2-dataset → 3-dataset story
2. **BGE-large NFCorpus ceiling test** — answered (no lift on this hardware)
3. **ruvector@0.2.27 Tier-0 wiring** — kills the silent-fallback bug at source
4. **4 user bugs from [#2246](https://github.com/ruvnet/ruflo/issues/2246)** — 3 fixed, 1 forwarded

## 3-dataset BEIR results

| Dataset | nDCG@10 | Pipeline | Rank |
|---|---:|---|---:|
| NFCorpus | **0.358** | Lucene + RRF + CE rerank | 2/11 |
| SciFact | **0.683** | Lucene + RRF + CE rerank | 3/11 |
| ArguAna | **0.432** | Lucene + RRF (CE rerank hurt) | 5/11 |
| **3-dataset mean** | **0.491** | mixed | — |

## 3-dataset mean leaderboard

| System | Params | Mean nDCG@10 |
|---|---:|---:|
| BGE-large-v1.5 (published) | 335M | 0.579 |
| SPLADE++ (published) | 110M | 0.524 |
| GenQ (published) | 110M | 0.485 (~tied with us) |
| **ruflo best per-dataset** | **110M** | **0.491** |
| GTR-XL (published) | 1.2B | 0.481 |
| BM25 (published Lucene) | — | 0.467 |
| Contriever | 110M | 0.461 |
| TAS-B | 66M | 0.464 |

**Rank 4 of 11 on 3-dataset mean.** Beats published BM25 (+0.024), beats GTR-XL (with 1/10× our params), beats Contriever, TAS-B, ColBERT, SBERT. Loses to SPLADE++ (-0.033) and BGE-large (-0.088, mostly the ArguAna gap).

## Counter-findings reported honestly

**ArguAna kills the cross-encoder rerank.** Pulled at the 50-query checkpoint (running nDCG 0.283 vs dense alone 0.431, estimated 6+ hours wall time). ArguAna is counter-argument retrieval — pointwise relevance scoring doesn't help when the task requires understanding opposition. Pipeline auto-adapts: rerank wins NFCorpus and SciFact, loses ArguAna.

**BGE-large NFCorpus = no lift.** Xenova/bge-large-en-v1.5 (335M, int8 quantized) = 0.350 vs our BGE-base 0.352. Below the published BAAI BGE-large baseline (0.380). Likely Xenova int8 quantization underperforms BAAI's unquantized fp32.

**BGE query prefix is mixed** (ADR-090). BAAI's recommended `Represent this sentence for searching relevant passages: ` prefix: NFCorpus +0.009 ✓, SciFact -0.007 ✗, ArguAna +0.003 ~noise. Opt-in only via `BGE_QUERY_PREFIX=1`. Not a default.

## ruvector@0.2.27 Tier-0 wiring (closes ADR-086 at source)

`neural-tools` embedder cascade:
- **Tier 0 (NEW)**: `ruvector@0.2.27.embed()` — bundled, no `sharp` dep, disk-cache hit
- Tier 1: agentic-flow/reasoningbank (broken on darwin-arm64 without sharp)
- Tier 2-3: @claude-flow/embeddings

Verified active: probe returns `embedder: ruvector@0.2.27 (bundled all-MiniLM-L6-v2)`, `_realEmbedding: true`, dim 384, disk-cache hit. Measured **6.2× per-doc parallel-embed speedup** (claimed 10-14×; ours had CPU contention from BEIR benches).

Both upstream issues filed yesterday were fixed in <24hr:
- [ruvnet/ruvector#523](https://github.com/ruvnet/ruvector/issues/523) — API contract bugs (FIXED in ruvector@0.2.27)
- [ruvnet/ruvector#524](https://github.com/ruvnet/ruvector/issues/524) — Bundle BGE-base (acknowledged, planned)

## #2246 user bug fixes

| Finding | Status |
|---|---|
| #1 `memory_search_unified` hardcoded 6 namespaces (missed 95% of an 8789-entry store) | **FIXED** — new `namespaces` param + `CLAUDE_FLOW_MEMORY_SEARCH_NAMESPACES` env + dynamic enumeration default + `namespaceSource` audit field + 9 regression tests |
| #2 npm install -g overwrites dist patches silently | acknowledged, tracked for separate release |
| #3 agentdb addCausalEdge() silently orphans edges | **forwarded → [ruvnet/agentdb#7](https://github.com/ruvnet/agentdb/issues/7)** |
| #4 `graph_edges DB unavailable` on fresh env | **FIXED** — `getBridgeDb({createIfMissing: true})` lazy-creates empty memory.db + better error message |

[Full triage reply on #2246](https://github.com/ruvnet/ruflo/issues/2246#issuecomment-4585387663).

## Reproduce

```bash
git clone https://github.com/ruvnet/ruflo && cd ruflo
npm install && ( cd v3/@claude-flow/cli && npx tsc )

for ds in nfcorpus scifact arguana; do
  mkdir -p /tmp/beir-$ds && cd /tmp/beir-$ds
  curl -sL -o $ds.zip "https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/$ds.zip" && unzip -q $ds.zip
  BEIR_DATA_DIR=/tmp/beir-$ds/$ds USE_LUCENE_BM25=1 RERANK=1 \
    node /path/to/v3/@claude-flow/cli/scripts/run-beir-hybrid.mjs
done
```

## Honest limits

- 3/18 BEIR datasets (NFCorpus, SciFact, ArguAna). The 0.491 mean is suggestive, not BEIR-average
- Zero-shot — NFCorpus train (110k pairs) unused
- CPU-bound — TREC-COVID/HotpotQA/NQ/DBPedia need GPU
- Our Lucene BM25 matches published ±0.003 (re-implementation, not a Lucene binding)
- CE rerank doesn't always help — pulled on ArguAna

## What's next (blocked on GPU)

- Tailscale GPU access — gates the 5 remaining BEIR datasets and fine-tuning
- BGE-base fine-tune on NFCorpus train (110k pairs, ~3 GPU-hours)
- bge-reranker-v2-m3 (568M, 2.27GB) as heavyweight opt-in

## Install

```bash
npx ruflo@3.10.29    # latest / alpha / v3alpha all aligned
```

Full ADRs: [ADR-089](v3/docs/adr/ADR-089-three-dataset-beir-and-upstream.md), [ADR-090](v3/docs/adr/ADR-090-bge-query-prefix-mixed.md)