README: reflect deployed state — 5,073 chunks, eval numbers, 6 tools
The scaffold-era README was out of sync with the shipped product: - Vendor counts stale (recon estimates, not actual deployed counts) - Trial data sources (gh_plot_reports + agripro_trials) entirely unmentioned - Tool list listed `corpus_status` (doesn't exist) and missed both `lookup_variety` and `search_trials` - Build-phase table showed everything as "pending" / "next" but Phases 1-8 + 11 all shipped Rewrite to reflect the deployed state: - Corpus inventory: 760 variety records + 4,313 trial documents = 5,073 chunks across 6 sources - All 6 MCP tools documented with their purpose - Eval baseline table (hybrid+rerank wins 100%, P@1 90%, MRR 0.905) with the surprising findings (dense alone is noise; hybrid w/o rerank is WORSE than BM25 alone) - Deploy mechanics: Watchtower chain, 4-GPU embedder pool, shared llama-rerank sidecar with the network-attach gotcha - Status table: ✅ on the phases that shipped, deferred work list (becks_pfr, 2023 plot backfill, NK trials, Channel Seed brand) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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# seed-mcp
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MCP server over the public catalogs of major US row-crop seed
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vendors — corn, soybeans, wheat. Sibling project to
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vendors — **variety identity** (what each hybrid IS) plus **yield-trial data** (how they actually perform in real cooperator fields). Sibling project to
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[`crop-chem-docs`](https://git.jpaul.io/justin/crop-chem-docs)
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(pesticide labels), feeding the same Drawbar farm-advisor AI.
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The server exposes per-variety records with **agronomic ratings**,
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**disease tolerance**, **trait stack**, **maturity**, and
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**regional notes** — so the advisor can answer questions like
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"which corn hybrid for sandy soil, drought-prone, RM ≤105 in
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northeast Iowa?" without rummaging through individual brand sites.
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**Deployed 2026-05-25** on trashpanda as a sibling sidecar to
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`chem-mcp`; the Drawbar advisor calls it via the `seed:` prefix.
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## Vendor coverage
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## What's in the corpus
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| Vendor | Verdict | Varieties | Notes |
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**5,073 indexed chunks** across two complementary surfaces:
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### Variety identity — 760 records
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| Source | Count | Vendor | Brand |
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|---|---|---|---|
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| Bayer seeds (DEKALB + Asgrow + WestBred) | 🟢 | ~475 | Same `cropscience.bayer.us` Next.js infra as crop-chem-docs |
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| Golden Harvest (Syngenta) | 🟢 | ~175 | Sitemap + server-rendered HTML + Syngenta CDN PDFs |
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| NK (Syngenta) | 🟢 | 29 | Shares PDF fetcher with Golden Harvest |
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| AgriPro (Syngenta wheat) | 🟢 | 24 | Drupal Views, server-rendered |
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| Beck's PFR | 🟡 | 2,089 | Public Sanity GROQ API (no auth) |
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| Beck's products | 🟡 | 860 | Identity-only until SeedIQ XHR sniffed |
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| Pioneer (Corteva) | 🔴 | — | ToS bans automation — curated fallback lesson instead |
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| `bayer_seeds` | 475 | Bayer | DEKALB (corn) / Asgrow (soy) / WestBred (wheat) |
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| `golden_harvest` | 139 | Syngenta | Golden Harvest (corn / soy) |
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| `nk` | 122 | Syngenta | NK (corn / soy) |
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| `agripro` | 24 | Syngenta | AgriPro (wheat — HRW / HRS / HWS / SWW) |
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### Yield-trial data — 4,313 documents
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| Source | Count | Notes |
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|---|---|---|
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| `gh_plot_reports` | 4,299 | Golden Harvest plot reports 2024+2025. **Cross-vendor head-to-head** — DEKALB / NK / GH / Pioneer / Channel all appear in the same trial rankings. The closest thing to independent comparison data the corpus has. |
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| `agripro_trials` | 14 | Regional wheat trial PDF summaries (PNW, Western Plains, Northern Plains, etc.) |
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### Not in the corpus (documented in `docs_mcp/lessons.md`)
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- **Pioneer / Corteva** — ToS bans automation. Curated fallback lesson points the farmer at pioneer.com / a local dealer.
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- **NK yield-results** — fiddly ASMX/SOAP endpoint, needs a dedicated reverse-engineer session.
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- **Bayer per-variety trial data** — not publicly indexed (DEKALB / Asgrow trial data flows through Channel reps). Partially covered by the GH plot reports' cross-vendor results.
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## MCP tools (6)
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| Tool | Purpose |
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|---|---|
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| `search_docs` | Variety IDENTITY — what a hybrid IS (disease ratings, traits, maturity). Hybrid dense+BM25 + cross-encoder rerank + variety-code prefilter. |
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| `search_trials` | Variety PERFORMANCE — head-to-head yield trial results. Filterable by crop, state, year, product. |
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| `get_page` | Full canonical record for one variety + structured ratings header sourced from the sidecar JSON. |
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| `lookup_variety` | Raw sidecar JSON for one variety — **fact-check tool**; call before quoting any specific rating value. |
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| `list_versions` | Discover facets (sources, vendors, brands, crops) currently indexed. |
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| `crop_seed_api_lessons` | Curated knowledge: Pioneer fallback policy, scale-direction differences across vendors, trait glossary, SCN race coverage notes. |
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`search_docs` defaults to `data_type="variety"`; `search_trials` uses `data_type="trial"` — single Chroma collection, metadata-filtered.
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## Retrieval — eval-validated
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From `eval/results/baseline.md` (21 golden queries, k=5):
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| Retriever | Pass | Recall | P@1 | MRR | Avg ms |
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|---|---|---|---|---|---|
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| **hybrid+rerank** | **21/21** | **100%** | **90%** | **0.905** | 2064 |
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| bm25 | 20/21 | 95% | 81% | 0.833 | 5 |
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| hybrid (no rerank) | 15/21 | 71% | 62% | 0.619 | 73 |
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| dense | 14/21 | 67% | 38% | 0.440 | 79 |
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**Deploy config**: `HYBRID_SEARCH=true` + `RERANK_URL=http://llama-rerank:8080`.
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Some surprises worth knowing:
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1. **Dense embedding alone is the weakest config**. Variety codes (DKC62-08RIB), gene names (Rps3a), and trait codes (XF) have no semantic neighbors — nomic-embed-text returns noise on them.
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2. **Hybrid alone is WORSE than BM25 alone.** RRF dilutes BM25's strong ranking with dense noise. Don't ship without rerank.
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3. **BM25-alone (95% recall, 5 ms) is an excellent fallback** when the rerank sidecar is unavailable. The variety-code prefilter in `search_docs` does heavy lifting.
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4. **Anti-hallucination queries pass on every retriever** — Pioneer fallback + not-in-corpus product checks hold across all configs.
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## Quick start
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@@ -31,54 +75,121 @@ cd seed-mcp
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python -m venv venv && source venv/bin/activate
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pip install -r requirements.txt
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# Run one scraper
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python -m scrape.runner --source bayer_seeds --force
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# Sample-scrape just to verify wiring:
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python -m scrape.runner --source bayer_seeds --limit 3
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# Rebuild indexes
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python -m rag.index --rebuild
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# Full refresh (all 6 sources; expect ~25 min for gh_plot_reports
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# with 4 concurrent workers):
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python -m scrape.runner --all --force
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# Local MCP server (stdio for Claude Desktop dev)
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python -m docs_mcp.server --transport stdio
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# Rebuild Chroma + BM25 from the corpus:
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OLLAMA_URL=http://192.168.0.125:11434 PRODUCT_NAME=crop_seed \
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python -m rag.index --rebuild
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# Run the eval harness:
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RERANK_URL=http://localhost:18080 python -m eval.run_eval \
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--queries eval/queries.jsonl --k 5 \
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--output eval/results/baseline.md
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# Local MCP server (stdio for Claude Desktop dev):
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PRODUCT_NAME=crop_seed python -m docs_mcp.server --transport stdio
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# Local HTTP server (matches production transport):
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PRODUCT_NAME=crop_seed python -m docs_mcp.server \
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--transport streamable-http --port 8000
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```
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## Tools exposed
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## Repo layout
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| Tool | Purpose |
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| `search_docs` | Hybrid + rerank variety search with crop / RM / trait / region filters |
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| `get_page` | Full variety record by `(source, source_key)` |
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| `list_versions` | Discover crops, brands, traits, RM/MG ranges, wheat classes |
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| `corpus_status` | Counts + freshness; useful for health probes |
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| `crop_seed_api_lessons` | Curated agronomy lessons — Pioneer fallback, disease-scale normalization, regional placement heuristics |
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## Build phases
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This is a clone of [`docs-mcp-template`](https://git.jpaul.io/justin/docs-mcp-template).
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The 13 phases in `PLAN.md` apply:
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| Phase | Status |
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| 0 — scaffold | done |
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| 1 — first scraper (bayer_seeds) | next |
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| 2 — chunk + index | pending |
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| 3 — baseline MCP tools | template defaults |
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| 4-5 — Dockerfile + CI | done (placeholders filled) |
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| 6 — reranker | shares `llama-rerank` sidecar with crop-chem-docs |
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| 7 — eval harness | pending (curate ~25 queries) |
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| 8 — hybrid search | done (template) |
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| 9 — diff_versions, list_cluster | optional |
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| 11 — `crop_seed_api_lessons` curated layer | pending |
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See `CLAUDE.md` for the canonical sidecar schema and the
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disease-scale-normalization gotcha (Golden Harvest is reversed).
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```
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.
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├── CLAUDE.md # Canonical agent guide. Read first.
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├── PLAN.md # Template's 13-phase build guide.
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├── README.md
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├── requirements.txt
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├── Dockerfile
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├── sources.json # Source catalog (one entry per scraper)
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├── deploy/docker-compose.yml # Drop-in compose snippet for Drawbar
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├── .gitea/workflows/
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│ ├── refresh.yml # Monthly cron: scrape + index + image push
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│ └── image-only.yml # On-demand code-only ship cycle
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├── scrape/
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│ ├── runner.py # `python -m scrape.runner --source <id>`
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│ ├── changelog.py # Reused from template
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│ └── sources/
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│ ├── bayer_seeds.py # ~475 varieties across 3 brands
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│ ├── golden_harvest.py # ~139 varieties (post-discontinued filter)
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│ ├── nk.py # 122 varieties (corn + soy)
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│ ├── agripro.py # 24 wheat varieties
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│ ├── gh_plot_reports.py # 4,299 cross-vendor yield trials
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│ ├── agripro_trials.py # 14 regional trial PDFs
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│ └── becks_pfr.py # stub — Sanity GROQ research corpus
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├── rag/
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│ ├── embeddings.py # nomic-embed-text via Ollama
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│ ├── chunk.py # one-chunk-per-variety + trial chunker
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│ ├── index.py # Chroma + BM25 builder
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│ └── bm25.py # FTS5 lexical index w/ seed-domain facets
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├── docs_mcp/
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│ ├── server.py # FastMCP — 6 tools, hybrid+rerank
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│ ├── lessons.md # Curated knowledge layer (Pioneer fallback)
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│ └── usage.py # TimedCall + JSONL telemetry
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├── eval/
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│ ├── queries.jsonl # 21 golden queries
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│ ├── retrievers.py # dense / bm25 / hybrid / hybrid+rerank
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│ ├── run_eval.py # MRR / Recall@k / Precision@1
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│ └── results/baseline.md # Current deploy-config eval numbers
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└── corpus/ # Committed scrape output (CI-refreshed)
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├── bayer_seeds/
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├── golden_harvest/
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├── nk/
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├── agripro/
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├── gh_plot_reports/
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└── agripro_trials/
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```
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## Infrastructure
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- **Registry**: `git.jpaul.io/justin/seed-mcp:latest` (Watchtower) /
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`:corpus-YYYY.MM.DD` (production pin)
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- **Embedder**: shared Ollama pool with crop-chem-docs (Gitea-host
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GPUs + Windows Ollama; CI never hits trashpanda's production Ollama)
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- **Reranker**: shared `llama-rerank` sidecar on trashpanda's Tesla
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P4 (one container, both MCPs use it)
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- **PRODUCT_NAME**: `crop_seed` (not `seed_mcp` — used in Chroma
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collection, BM25 db filename, and `crop_seed_api_lessons` tool)
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- **Registry**: pushes to `192.168.0.2:1234` (LAN, no CF body cap); deploys pull `git.jpaul.io/justin/seed-mcp:latest` (public, CF tunnel). Also tagged `:<sha12>` for rollback pinning and `:corpus-YYYY.MM.DD` for snapshot pinning.
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- **Embedder pool (CI)**: 3 GPU-pinned Ollama endpoints, weighted toward `.0.125` (RTX 40-series, 242 embeds/sec):
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- `.0.125:11434` ×4 (4090)
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- `.0.2:11436` ×2 (GPU-pinned)
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- `.0.2:11435` ×1 (GPU-pinned)
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- Do NOT use `.0.2:11434` (not GPU-pinned) or `localhost:11434` (works in dev, breaks in CI — runner container has no Ollama on its loopback).
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- **Reranker**: shared `llama-rerank` sidecar on trashpanda's Tesla P4 (jina-reranker-v2-base via llama.cpp). One container serves both seed-mcp and crop-chem-docs. **Must be on `drawbar-backend_default` Docker network** — see `deploy/docker-compose.yml` for the network-attach gotcha that caused silent rerank degradation on chem-mcp prior to 2026-05-25.
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- **PRODUCT_NAME**: `crop_seed` — used in the Chroma collection name (`crop_seed_docs`), the BM25 db filename (`bm25/crop_seed_docs.db`), and the `crop_seed_api_lessons` tool name. Not `seed_mcp` — that would conflict with the container/service name.
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## Deploy mechanics
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Watchtower handles auto-deploy. Every push to `seed-mcp/main` that touches `docs_mcp/`, `rag/`, `scrape/`, `requirements.txt`, `Dockerfile`, or `sources.json` triggers `image-only.yml`:
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1. Checks out main with full corpus
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2. Rebuilds Chroma + BM25 (~3 min on the GPU pool)
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3. `docker build` + push three tags to the LAN registry
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4. Links the package to the repo via Gitea API
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5. Watchtower on trashpanda polls `:latest` every 5 min → pulls + recreates `drawbar-backend-seed-mcp-1`
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Corpus refresh runs monthly via `refresh.yml` (1st of each month, 06:00 UTC) — re-scrapes all GREEN sources, commits any corpus diff, rebuilds indexes, ships a new image with `:corpus-YYYY.MM.DD` tagged.
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See `CLAUDE.md` for canonical sidecar schemas, the reversed disease-scale gotcha (NK + AgriPro publish 1=best, vs Bayer/GH 9=best), and the scraper conventions.
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## Status
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| Phase | Status |
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|---|---|
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| 0 — scaffold | ✅ |
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| 1 — scrapers (bayer_seeds / golden_harvest / nk / agripro / gh_plot_reports / agripro_trials) | ✅ |
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| 2 — chunk + index | ✅ |
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| 3 — MCP tools (6) | ✅ |
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| 4-5 — Dockerfile + Gitea CI | ✅ |
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| 6 — reranker integration | ✅ (eval-validated; deploy uses hybrid+rerank) |
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| 7 — eval harness | ✅ (21 golden queries, baseline committed) |
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| 8 — hybrid search | ✅ (default ON) |
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| 11 — `crop_seed_api_lessons` curated layer | ✅ (Pioneer fallback + 7 other lessons) |
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| 13 — weekly_digest | not planned for seed-mcp |
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Remaining work (deferred, not blocking):
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- `becks_pfr` scraper (2,089 research docs via public Sanity GROQ)
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- 2023 GH plot reports backfill (~3,619 more docs)
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- NK yield-results endpoint reverse-engineer
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- Channel Seed brand (~320 more Bayer varieties — separate brand under the same sitemap)
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