2 Commits

Author SHA1 Message Date
8a815ecff5 fix(retrieval): rewrite chunk-page retrofit to skip OCR
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The first-pass retrofit re-extracted via extractor.extract_text, which
re-runs Google Vision OCR on scanned pages. OCR is non-deterministic,
so the new text didn't match the chunk content stored in the DB
(produced by the original OCR run) — only ~7% of chunks were located.

New approach (no OCR cost):

1. Use the stored documents.extracted_text from the DB — the exact
   text the chunks were produced from, so chunk lookups match.
2. Anchor page boundaries via PyMuPDF direct text reads (free, no
   OCR). Pages with usable direct text are anchored by snippet match;
   OCR-only pages are linearly interpolated between anchors.
3. Search each chunk in extracted_text using a whitespace-tolerant
   helper — needed because the chunker joins paragraphs with single
   '\\n' while extracted_text uses '\\n\\n' as page separators.

Verified on 8174-24 (5 docs, 307 chunks) + 8137-24 (9 docs, 512
chunks): 100% chunks tagged, 13s total, $0 cost.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 20:04:33 +00:00
81ccf3a888 feat(retrieval): track page_number on text chunks for multimodal hybrid boost
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The legacy chunker did not track which PDF page each chunk came from.
Stored chunks had page_number=NULL, which blocked the multimodal
hybrid retriever's text+image boost — it joins (chunk, image) on
(document_id, page_number) and the join could never fire.

This change:

- extractor.extract_text now returns (text, page_count, page_offsets);
  page_offsets[i] is the start char offset of page (i+1) in the joined
  text. None for non-PDFs.
- chunker.chunk_document accepts an optional page_offsets and tags
  each chunk with the page that contains its first character (uses
  the existing chunker logic; pages assigned post-hoc by content
  search to keep the diff minimal).
- processor.process_document and precedent_library.ingest_precedent
  forward page_offsets through the chunker. New uploads now carry
  accurate page_number on every chunk.
- Other extract_text callers (tools/documents, tools/workflow,
  web/app.py) updated to unpack the third element (ignored).
- scripts/backfill_chunk_pages.py: per-case retrofit. Re-extracts each
  PDF (re-OCRs via Google Vision if needed, ~$0.0015/page), computes
  page_offsets, and updates page_number on every chunk by content
  search. Idempotent; --force re-runs on already-tagged docs.

Forward-only would leave the 419 image embeddings backfilled on
cases 8174-24 + 8137-24 unable to boost their corresponding text
chunks. The retrofit script closes that gap (cost ~$0.60).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 19:49:41 +00:00