Repo/project rename to better reflect scope. PPLS is EPA's term for
their Pesticide Product Label System — accurate when the corpus was
EPA-only, narrow now that it also pulls from Bayer's own catalog
(and may expand to Syngenta/Corteva/BASF/FMC labels in the future).
crop-chem-docs scopes flexibly without acronyms to explain.
Renames:
- directory: ppls-docs → crop-chem-docs
- PRODUCT_NAME: ppls → crop_chem
- Chroma collection: ppls_docs → crop_chem_docs (in-place via .modify(), no re-embed)
- BM25 db: bm25/ppls_docs.db → bm25/crop_chem_docs.db
- MCP tool name: ppls_api_lessons → crop_chem_api_lessons
- FastMCP server name: ppls-docs → crop-chem-docs
- Env vars: PPLS_CORPUS_ROOT → CORPUS_ROOT
PPLS_CHROMA_DIR → CHROMA_DIR_OVERRIDE
- User-Agent: ppls-docs-scraper → crop-chem-docs-scraper
Preserved (intentional, correct):
- epa_ppls (source id) — refers specifically to EPA's PPLS database
- "EPA PPLS" mentions in regulatory text (lessons.md, server docstrings)
- PPLS_API_BASE / PPLS_PDF_BASE / PPLS_INDEX_URL_TEMPLATE in
scrape/sources/epa_ppls.py — these point at EPA's actual endpoints
Memory entries get updated in a follow-up commit so the rename is
isolated.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Cuts the PPIS-enumeration universe from 102K rows to ~11.5K rows by
dropping products from non-row-crop-ag registrants BEFORE the per-
product API call. This is the biggest cost lever we have on the EPA
scraper — full backfill drops from ~28 h to ~3.5 h.
scrape/sources/epa_registrant_allowlist.json holds the 34 verified
ag-chem company numbers (Syngenta, Bayer, BASF, Corteva, FMC, Nufarm,
ADAMA, UPL, Albaugh, Loveland, AMVAC, Helena, Drexel, Atticus, etc.).
Each entry was verified by querying the EPA PPLS API for the first
active product registered under that company number. Edit the JSON
freely — scraper loads it at run time. Bypass with
--no-registrant-filter when you suspect a row-crop product registered
to a specialty company not on the list.
Why a curated allowlist rather than blacklist consumer brands: the
102K PPIS rows are 89% non-ag-relevant; an allowlist is shorter to
maintain and harder to false-positive.
Excluded with intent (not omissions): Bayer Environmental Science
(turf/ornamental), Scotts (consumer lawn & garden), Wellmark/Zoecon
(animal flea/tick), Control Solutions (structural pest), Cleary
(turf), PBI/Gordon (mostly turf), Buckman Labs (industrial water).
Smoke test --limit 100:
- 1239 PPIS rows considered (in first slice of file)
- 1139 skipped by registrant filter (no API call paid)
- 100 hit API, 81 filtered by row-crop sites, 19 written
- = 91% API-call reduction over the prior version
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Both scrapers now honor PPLS_CORPUS_ROOT so the corpus can land on
external storage (USB drive, NAS mount, secondary partition) without
editing the repo. Default behavior unchanged: corpus/ at repo root
when the env var is unset.
Per-source subdirectory layout preserved: ${PPLS_CORPUS_ROOT}/bayer/,
${PPLS_CORPUS_ROOT}/epa_ppls/, etc.
Live-verified against /run/media/justin/USB (vfat, 59GB free):
PPLS_CORPUS_ROOT=/run/media/justin/USB/ppls-corpus \
python -m scrape.runner --source epa_ppls --reg-no 524-475
-> wrote to USB, root disk untouched
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
App focus is corn, soybeans, and wheat. Dropping the broader
US-row-crops allowlist (cotton/rice/sorghum/milo/barley/oats/rye/
sunflower/peanut/sugar-beet/dry-bean/canola/alfalfa).
Empirical impact (random N=100 sample): broad list matched 17/100
products, narrow list matches 16/100 — only 6% reduction, because
corn/soy/wheat dominate ag-chem registrations so thoroughly that
products registered for cotton/sorghum/etc. are almost always
co-registered for one of corn/soy/wheat. One sampled product was
dropped: a peanut-only herbicide (2749-614).
Verified live: 524-475 Roundup + 524-591 Warrant kept (CORN/SOYBEAN
sites); 2749-614 AG36448 (PEANUTS only) correctly filtered.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The farmer-advisor consumer only cares about US row crops, so the EPA
scraper now drops products without at least one row-crop site in the
PPLS API response. Filter is on by default; --no-row-crop-filter
overrides for one-off broader pulls.
Filter shape:
- Word-boundary regex match against each entry in the API's `sites`
array (e.g., "SOYBEANS (FOLIAR TREATMENT)" → keep, "SHIPS, BOATS,
SHIPHOLDS" → drop even though it contains "OATS" as substring).
- Allowlist covers the major US row + small-grain + oilseed + sugar/
fiber crops, plus alfalfa as a common rotation crop. See
ROW_CROP_KEYWORDS in scrape/sources/epa_ppls.py for the full list.
Cost model:
- 102K PPIS rows still need one API call each (no bulk filter
available upstream), so enumeration still takes ~28h at 1 req/sec.
- But PDF downloads drop from ~67K → ~5-10K (estimated row-crop
hit rate), saving ~17h wall time and ~60GB disk on a full backfill.
Smoke test (4 mixed reg nos):
524-475 Roundup Ultra → kept (CORN/SOYBEANS/COTTON sites)
524-591 Warrant → kept (CORN/SOYBEANS/SORGHUM sites)
100-1486 Advion Cockroach → filtered (building/transport sites only)
432-1276 (Bayer pet flea) → filtered (no row crops)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adapts the docs-mcp-template scraping layer for the pesticide-labels
domain. The template's bundle/version/platform concepts don't map to
labels (there's no "Bayer 8.1.0" — there's just the current accepted
label per EPA Reg No), so the scraper layer is reshaped around a
"source" abstraction: one source per manufacturer or regulator, one
per-product label per source.
Sources shipped:
- bayer — Bayer Crop Science US (Next.js JSON catalog + Scene7 PDFs)
- epa_ppls — EPA PPLS via PPIS bulk index + undocumented /cswu/ ORDS REST endpoint
Canonical sidecar schema (see scrape/README.md) unifies fields across
sources:
- active_ingredients always [{name, cas, percent}]
- label/* nested (url, filename, accepted_date, last_modified,
page_count, text_layer)
- all timestamps normalized to ISO 8601 UTC
- signal_word surfaced (operationally critical for the farmer advisor)
- source_key + epa_reg_no separate per-source PK from the
cross-source join key
bundles.json → sources.json. --bundle → --source. The runner walks
sources.json and dispatches by id; per-source modules remain
independently runnable for development.
PLAN.md gets a one-block domain note up front; later phases (chunking,
embeddings, retrieval, eval) still apply as written.
Smoke test:
python -m scrape.runner --all --limit 2 # works
python -m scrape.runner --source bayer --limit 3 # 3 written, idempotent re-run skips
python -m scrape.runner --source epa_ppls --reg-no 524-475 # Roundup Ultra, 167 pages, ISO last_modified
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
justin