29ee941037
First real-data test against the AXA car-insurance PDFs surfaced a noise problem: the new document is a brand refresh — every page flips font (PublicoBanner-Bold→PublicoHeadline-Bold) and colour (#893f4a→#2e3092). At medium-per-finding that crashed the diff score to 0.0 and drowned the bold-regression signal AXA actually flagged. Drop font, size, colour comparators. Keep bold + italic — the attributes the vision-LLM consistently misses on dense layouts. The LLM already narrates colour-scheme rebrands and font swaps in its Modified / Style-changes blocks; running both layers on the same visual change just double-counts it. Tests inverted from "X change is flagged" to "X change is NOT flagged" to lock the scope decision in. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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| .. | ||
| data | ||
| __init__.py | ||
| accessibility_checks.py | ||
| checks.py | ||
| diff_engine.py | ||
| diff_report_writer.py | ||
| dispatcher.py | ||
| formatting_diff.py | ||
| ingest.py | ||
| page_classifier.py | ||
| print_preflight_checks.py | ||
| result_writer.py | ||