feat(retrieval): track page_number on text chunks for multimodal hybrid boost

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>

web/app.py

@@ -3500,7 +3500,7 @@ async def _process_training_document(task_id: str, source: Path, req: ClassifyRe
 
     # Extract text
     await _progress.set(task_id, {"status": "processing", "filename": req.filename, "step": "extracting"})
-    text, page_count = await extractor.extract_text(str(dest))
+    text, page_count, _ = await extractor.extract_text(str(dest))
 
     # Parse date
     d_date = None