justin
c737871c4c
This PR introduces TRIAL data — yield-performance results from real
field trials — as a SEPARATE data type alongside variety identity.
The two are complementary:
search_docs → "What's the disease resistance of DKC62-08RIB?"
(variety identity — what it IS)
search_trials → "Which corn hybrid won the IA 2024 trials?"
(performance data — how it PERFORMED)
scrape/sources/gh_plot_reports.py — Golden Harvest plot reports
- 4,618 expected (2024+2025; 2023 deferred to a backfill pass).
- URL: /<crop>/plot-report/<state>/<year>/<plot_id>
- Cross-vendor: each plot lists products from multiple brands
(NK / DEKALB / Golden Harvest / Enogen / Pioneer / Channel) side
by side at one cooperator's field — the kind of independent
comparison data Bayer doesn't publish itself.
- Generic per-column metrics dict (Yield/MST/Test Weight/$/Ac for
corn+soy, Ton/Acre + Milk + Beef columns for silage).
- Politeness: 1 req/sec, retries on 429/5xx, no redirect-follow.
scrape/sources/agripro_trials.py — AgriPro regional trial PDFs
- 14 unique PDFs (38 sitemap links deduped) at /trials-data
- pdfplumber text extraction, region/year detection from filename
- Verbatim PDF text preserved in chunk body so variety + yield
number adjacency drives retrieval (AP Iliad's Aberdeen ID yield
matches a query about "AP Iliad Idaho yield")
rag/chunk.py — chunks_from_trial() dispatching by source
- Plot reports: identity preamble + Top-5 by primary metric + full
ranking table. Metric labels chosen from the data (corn/soy use
"Yield", silage uses "Ton/Acre").
- AgriPro PDFs: identity preamble + verbatim trial body inline so
per-location yields surface for region+variety queries.
- Variety chunks get data_type="variety" metadata; trial chunks get
data_type="trial". Single Chroma collection; the tool router
filters by data_type rather than maintaining two collections.
rag/index.py — dispatch by sidecar's data_type field
rag/bm25.py — new filter columns (data_type, year, state)
docs_mcp/server.py — sixth MCP tool: search_trials(crop?, state?,
year?, product?, k=10)
- Filters trial chunks via where={"data_type": "trial", ...}
- Optional product substring post-filter for "DKC62-08RIB Iowa 2024"
style searches
- search_docs now defaults to data_type="variety" so trial chunks
don't bleed into variety identity queries
- Tool docstring routes the agent: "use lookup_variety to verify
identity details on any trial winner you surface"
NK trial endpoint (/NKSeeds/wsProxy.asmx/GetPlotResult) is documented
as deferred — the ASMX-SOAP shape returned empty XML on initial
probe. Bayer per-variety yield data is not publicly indexed at all
— documented in the trial-scope note (DEKALB/Asgrow trial data flows
through Channel reps, not the web). AgRevival research books exist
as 10 large annual PDFs but are deferred (low ROI per parse).
Initial corpus shipped in this PR: 14 AgriPro trial PDFs. The 4,618
Golden Harvest plot reports are scraping in background and will be
added in a follow-up corpus-snapshot PR (~70 min ETA).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
scrape/
Per-vendor seed catalog scrapers + the runner that dispatches to
them. Each source lives in scrape/sources/<name>.py with a main()
entrypoint. The runner is a thin shim:
python -m scrape.runner --source bayer_seeds --force
python -m scrape.runner --source golden_harvest --limit 20
python -m scrape.runner --all # only GREEN sources
Output layout
Each scraper writes:
corpus/<source>/<source_key>.md— LLM-visible body (chunk_0 preamble + the variety's marketing + agronomic narrative)corpus/<source>/<source_key>.json— sidecar metadata (per CLAUDE.md's canonical schema)
source_key is a stable per-vendor slug — typically <brand>-<sku>
lowercased, e.g. dekalb-dkc62-08rib. Stability matters: it's the
join key the MCP uses for get_page(source, source_key).
Sources
| Source | Module | Verdict | Notes |
|---|---|---|---|
bayer_seeds |
bayer_seeds.py |
🟢 | DEKALB + Asgrow + WestBred, ~475 varieties |
golden_harvest |
golden_harvest.py |
🟢 | ~175 varieties, 9-to-1 disease scale (reverse) |
nk |
nk.py |
🟢 | 29 varieties, ratings in CDN PDFs |
agripro |
agripro.py |
🟢 | 24 wheat varieties |
becks_pfr |
becks_pfr.py |
🟡 | 2,089 research docs via public Sanity GROQ |
becks_products |
becks_products.py |
🟡 | 860 products, identity-only (SeedIQ-gated) |
Pioneer is intentionally absent — see CLAUDE.md and the curated
Pioneer fallback in docs_mcp/lessons.md.
Tips
- Sniff before you scrape. Most catalogs are SPAs that call a
backend API. The recon docs in
~/.claude/projects/-home-justin/ memory/reference_seed_vendor_recon.mdalready capture the endpoints; if you find new ones, update that file. - Idempotent re-scrapes. Without
--force, skip pages already on disk. With--force, re-fetch everything — that's the monthly cron mode. - Respect the portals. Backoff on 429s. Set a recognizable
user-agent (
seed-mcp-scraper/<version>). - Normalize at chunk time, not at scrape time. The chunker
(Phase 2) handles the 9-to-1 → 1-9 disease-scale flip for Golden
Harvest, NOT this scraper. Sidecar JSON should preserve the
vendor's raw values + a
_scale_directionfield; the chunker reads that and normalizes the markdown body.
changelog.py
Reusable as-is from the template. Walks git diff --name-status
output for the commit summary, and git log for the digest history
(Phase 13).