Previously, pymupdf4llm.to_markdown() was called twice - once in
PyMuPDFProcessor during indexing and again in PDFHighlighter during
visualization. Different image path lengths caused different character
offsets, leading to highlighted pages not matching their chunks.
Also fixed issue where all chunks on the same page showed all highlights
instead of just their own highlight. Now restores original page contents
between chunks using xref stream caching.
Changes:
- Add PDFHighlighter class requiring pre-computed page_boundaries and
full_text from document processor (no fallback extraction)
- Pass pre-computed data from processor to highlighter
- Extract page-relative portion of chunk text for cross-page chunks
- Add bounding box highlighting using text anchor search
- Run highlight generation in parallel with embedding/BM25
- Cache and restore page contents to isolate highlights per chunk
Results: Highlighting success rate improved from 51% to 95% (121/128).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Extract CSS and JavaScript into separate static files
- Created nextcloud_mcp_server/auth/static/vector-viz.css
- Created nextcloud_mcp_server/auth/static/vector-viz.js
- Updated templates to reference external assets
- Fix vector visualization issues:
- Normalize vectors before PCA to match Qdrant's cosine distance
- Add zero-norm and NaN detection/handling for large datasets
- Enable responsive Plotly sizing (autosize + responsive config)
- Widen plot area to full viewport width with minimized margins
- Improve visualization accuracy:
- Query point now positioned correctly relative to documents
- Handles 200+ points without JSON serialization errors
- Full-width plot maximizes screen space utilization
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Chris Coutinho