Addresses Dafna's observation that licensing decisions lack comprehensive
planning discussion. Systematic corpus analysis of all 24 training decisions
revealed the system learned writing style but not substantive content.
Changes:
- Corpus analysis of all 24 decisions (docs/corpus-analysis.md)
- 5 content checklists by appeal subtype injected into block-yod prompt
- chair_feedback DB table + API endpoints + MCP tools
- Feedback management page in Next.js UI (/feedback)
- Navigation updated with "הערות יו״ר" link
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- DELETE /api/training/corpus/{id} + delete button on training page,
with confirmation dialog and recompute hint
- /api/system/tasks + floating process panel (bottom-left) showing
active background tasks with live 3s polling
- /api/system/recent-activity derives a feed from cases, style_corpus,
and last style_patterns run; sidebar on home page renders with
relative timestamps
- /api/system/diagnostics + /#/diagnostics page showing DB health,
row counts per table, active tasks, stuck documents (>10 min),
failed extractions
- Cosmetic: signature phrase headline now prefers clean phrases over
bracket-heavy templates for display
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Add delete_document_chunks for reprocessing, save extracted text to disk
- Expand case directory structure (original/extracted/proofread/backup)
- Update classifier patterns (תגובה, הודעת עמדה)
- Fix proofreader agent paths for new directory layout
- Update HEARTBEAT to notify on every task completion
- Improve bidi_table with LRE/PDF directional embedding
- Add Paperclip project verification and auto-close setup issue
- Add auto-sync-cases.sh for Gitea synchronization
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Add expected_outcome field to cases (rejection/partial/full/betterment_levy)
- New lessons.py module with golden ratios, templates, and drafting guidance per outcome type
- Style analyzer now uses Opus with full decision text (no truncation), with multi-pass fallback for large corpora
- Drafting tool provides outcome-specific templates, section guidance, and ratio comments
- Improved JSON extraction with bracket-matching fallback
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Ezer Mishpati - AI legal decision drafting system with:
- MCP server (FastMCP) with document processing pipeline
- Web upload interface (FastAPI) for file upload and classification
- pgvector-based semantic search
- Hebrew legal document chunking and embedding
