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* feat: Python derived-field classifier with shadow telemetry for PO ingest Port the site_code/trade/fiscal_year rules from EXTRACTION_PROMPT into a pure, total derived_fields module applied in the shared enrich_parsed() post-stage. Python fills gaps on both parse paths (the template path has no LLM values, closing the derived-field gap opened by the PR #105 two-PR split) and never overwrites a non-null LLM value; on ai_fallback a DerivedFieldAgreement EMF record per field shadows Python against the LLM during the bake. Rules hardened against a full-corpus backtest (3,422 real emails vs the LLM-written baseline): site_code 99.4% with zero Python-wrong cases, fiscal_year 100%, trade 96.8% ex-deliberate. Also: quantity/price now declared numeric in the prompt, and derived_fields.py added to the po_stack bundling copy (deploy-time ImportError otherwise). * fix: security-review hardening — EMF value length clamp, aggregate trade CPU budget sh-security-review (4 detectors + proof-or-kill verifier): PASS, 0 confirmed critical/high. Fixes the one confirmed low (unbounded LLM-value str() into the DerivedFieldAgreement EMF log line, clamped to 64 chars) and adds the verifier-recommended defense-in-depth aggregate character budget across line items in derive_trade (per-item caps alone allowed ~10s full-core on a pathological direct-call input; unreachable through the deployed handler but cheap to bound). Bundling cp list now carries a warning comment (GPT-4.1 cross-review FIX). |
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| tests | ||
| derived_fields.py | ||
| handler.py | ||
| requirements.txt | ||
| ses_auth.py | ||
| template_parser.py | ||