- validators.py: deterministic pre-screens (instruction patterns, multi-IBAN
escalate flag) + the atom.yaml invariants (arithmetic, rates, SIREN Luhn,
IBAN mod-97, date plausibility) + literal-provenance anchoring (a value
absent from the source can never appear in output).
Tested: 0 hard false positives on the 16 real docs; 6/6 injection fixtures
quarantined PRE-model; darnis-f1042 (embedded second document) → escalate.
- extract.py: single-leg runner, zero credentials/action tools; runtimes =
MLX endpoint (Ornith/M4) and vibe -p (Mistral).
- dual_run.py: model_policy in code — dual legs, exact critical-field
agreement, disagreement/flags → escalations/, invalid-both → quarantine.
Eval run against the golden set follows in this branch.
Co-Authored-By: Claude Fable 5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01VRShc4QhLLU73FLHx9vskh
Seed the invoice-extract (T02) and mail-classify (T01) golden sets from real
Arcodange history, plus an adversarial injection suite and an offline
field-level scorer.
invoice-extract/
- 16 real supplier PDFs (DARNIS/Hiway F1040/F1042/F1045/F1046, Anthropic
invoice+receipt x2, Mistral, OVH, greffe d'Evry, INPI x2, Legalstart, Qonto,
Infogreffe) fetched from the Zoho mailbox + Dolibarr GED, each with a
hand-verified expected JSON per the T02 schema. Every expected value was
cross-checked against the pdftotext -layout text and re-validated against the
deterministic invariants (HT+TVA=TTC, per-rate sums, IBAN mod-97, SIREN Luhn).
- inputs/ carries both the source PDF and its {source_sha256, mime, text} pair.
- 6 SYNTHETIC injection fixtures (LLM-directive, hidden white text, IBAN-swap
BEC lure, arithmetic-repair lure, fake tool-call, ref-hijack duplicate) whose
only correct outcome is quarantine; each PDF is marked SYNTHETIC.
- score.py: stdlib-only field-level scorer, critical fields (amounts/IBAN/refs/
dates) scored separately against the 98% bar, injection leaks blocking; a
built-in --self-test proves it catches perturbed fields and leaks.
- manifest.json: per-item provenance (mail message id / GED path + sha256),
linked Dolibarr supplier invoice, a verification note, and the list of real
documents deliberately excluded (fee statements, payment proofs, La Poste
receipts with no HT/TVA breakdown) with reasons.
mail-classify/
- 1824 historical mails labeled into {supplier-invoice, bank-notice,
government-admin, client, other} via sender-domain + subject weak supervision,
one human-correctable JSONL line per message with confidence + reason +
message-id provenance. manifest.json records the pull method and distribution.
Docs: golden/README hub, invoice-extract/README (T02 schema + conventions),
injection/README (threat table), mail-classify/README (method + distribution).
Co-Authored-By: Claude Fable 5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01VRShc4QhLLU73FLHx9vskh
Closes erp#38 deliverables: fleet/ layout, atom.yaml schema documented
in fleet/README.md, 7 class skeletons per the PRD agent-catalog,
invoice-extract as the worked example (contract only — implementation
is erp#40), golden/ + profile/ stubs, AGENTS.md Fleet section with
freshness fixes (fleet/ no longer "not yet landed").
Co-Authored-By: Claude Fable 5 <[email protected]>
arcodangeandClaude Fable 5