justin
bd71f30ca7
Phase 6 — Reranker integration
- New _rerank(query, [(cid, doc), ...]) helper in server.py calls
llama.cpp's /v1/rerank endpoint, returns reranker-ordered ids
or None on failure (graceful fallback — search never blocks
on the sidecar).
- search_docs + search_trials both call _rerank() on the post-
hybrid pool BEFORE truncating to k. The variety-code prefilter
still pins exact matches on top.
- Per-doc truncation to 2000 chars to fit jina-reranker-v2-base's
per-pair token budget. Full chunk text still returned to the
caller — truncation is rerank-input-only.
- Telemetry adds `reranked: true|false` so usage logs distinguish
reranked calls.
Phase 7 — Eval harness
- eval/queries.jsonl: 21 golden queries spanning:
* variety-code lookups (DKC62-08RIB, AG29XF4, WB6430, E085Z5,
AP Iliad)
* semantic variety queries (drought-tolerant corn, SCN MG-3
soy, Rps3a, XtendFlex, HRS stripe rust, SWW PNW, Goss's Wilt)
* trial queries (IA/IN/MN regional, AP Iliad ID, NK1701 head-
to-head, silage Ton/Acre, product=DKC65-95)
* anti-hallucination (Pioneer P1142 fallback, DKC65-20 not-in-
corpus expected_empty)
- eval/retrievers.py: 4 named retrievers — dense, bm25, hybrid
(dense+bm25+RRF), hybrid+rerank — all sharing the same filter
shape as docs_mcp/server.py._build_where.
- eval/run_eval.py: runs each retriever against each query,
reports Recall / Precision@1 / MRR / avg latency. Markdown
output in eval/results/baseline.md.
Baseline results (k=5, 21 queries):
| Retriever | Pass | Recall | P@1 | MRR | Avg ms |
|-----------------|-------|--------|-------|-------|--------|
| hybrid+rerank | 21/21 | 100% | 90% | 0.905 | 2064 |
| bm25 | 20/21 | 95% | 81% | 0.833 | 5 |
| hybrid | 15/21 | 71% | 62% | 0.619 | 73 |
| dense | 14/21 | 67% | 38% | 0.440 | 79 |
Key findings:
1. hybrid+rerank wins on quality — 100% pass, 90% P@1.
2. BM25 alone is surprisingly competitive (95% pass) at 5 ms —
excellent fallback when rerank is down. The variety-code
prefilter in search_docs is doing a lot of work here.
3. Dense embedding alone is the WEAKEST configuration on this
corpus — variety identity tokens (DKC62-08RIB, AP Iliad,
Rps3a) have no semantic neighbors, so nomic-embed-text returns
noise. The hybrid (no rerank) layer actively hurts because
RRF dilutes the BM25 ranking with dense noise.
4. Anti-hallucination queries (Pioneer fallback, DKC65-20 not-
in-corpus) pass on ALL retrievers including dense-only —
the must_not_contain + expected_empty design holds.
Deploy decision: HYBRID_SEARCH=true + RERANK_URL set
(production env already has both — refresh.yml + image-only.yml
+ deploy/docker-compose.yml all configured).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
42 lines
2.1 KiB
Markdown
42 lines
2.1 KiB
Markdown
# seed-mcp retrieval eval — k=5
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_21 golden queries × 4 retrievers_
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## Summary
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| Retriever | Passed | Recall | P@1 | MRR | Avg ms |
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|---|---|---|---|---|---|
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| **hybrid+rerank** | 21/21 | 100.00% | 90.48% | 0.905 | 2064 |
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| **bm25** | 20/21 | 95.24% | 80.95% | 0.833 | 5 |
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| **hybrid** | 15/21 | 71.43% | 61.90% | 0.619 | 73 |
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| **dense** | 14/21 | 66.67% | 38.10% | 0.440 | 79 |
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**Recall** = % of queries where ≥1 top-k chunk satisfied the spec. **P@1** = % where the very first result satisfied it. **MRR** = mean of `1 / rank-of-first-satisfying-result` (0 if missed).
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## Per-query results
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| Query | bm25 | dense | hybrid | hybrid+rerank |
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|---|---|---|---|---|
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| `DKC62-08RIB ratings` | ✅ #1 | ❌ | ❌ | ✅ #1 |
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| `AG29XF4 disease ratings` | ✅ #1 | ❌ | ❌ | ✅ #1 |
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| `WB6430 westbred wheat` | ✅ #1 | ❌ | ❌ | ✅ #1 |
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| `E085Z5 corn` | ✅ #1 | ❌ | ❌ | ✅ #1 |
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| `AP Iliad wheat performance` | ✅ #1 | ❌ | ❌ | ✅ #1 |
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| `drought tolerant corn for sandy soil short season Iowa` | ✅ #2 | ✅ #1 | ✅ #1 | ✅ #1 |
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| `soybean cyst nematode SCN resistant variety` | ✅ #1 | ✅ #1 | ✅ #1 | ✅ #1 |
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| `Phytophthora resistance Rps3a soybean` | ✅ #1 | ✅ #2 | ✅ #1 | ✅ #1 |
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| `XtendFlex soybean Northern Plains` | ❌ | ✅ #1 | ✅ #1 | ✅ #1 |
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| `Hard Red Spring wheat stripe rust resistance` | ✅ #1 | ✅ #3 | ✅ #1 | ✅ #1 |
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| `Soft White Winter wheat Pacific Northwest` | ✅ #1 | ✅ #5 | ✅ #1 | ✅ #1 |
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| `Goss's Wilt resistance corn` | ✅ #1 | ✅ #1 | ✅ #1 | ✅ #1 |
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| `best corn 2024 Iowa` | ✅ #1 | ✅ #1 | ✅ #1 | ✅ #1 |
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| `Indiana corn yield comparison 2024` | ✅ #1 | ✅ #1 | ✅ #1 | ✅ #1 |
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| `AP Iliad Idaho wheat trial` | ✅ #1 | ✅ #5 | ✅ #1 | ✅ #1 |
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| `DKC65-95 corn yield in trials` | ✅ #1 | ❌ | ✅ #1 | ✅ #1 |
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| `NK1701 corn trials head to head` | ✅ #1 | ❌ | ❌ | ✅ #1 |
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| `silage corn high milk per acre dairy` | ✅ #1 | ✅ #1 | ✅ #1 | ✅ #1 |
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| `soybean 2025 Minnesota top performers` | ✅ #1 | ✅ #1 | ✅ #1 | ✅ #1 |
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| `Pioneer P1142 hybrid recommendation` | ✅ | ✅ | ✅ | ✅ |
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| `DKC65-20 yield Alabama trial` | ✅ | ✅ | ✅ | ✅ |
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