Adds two orthogonal columns — practice_area (top-level legal domain:
appeals_committee / national_insurance / labor_law) and appeal_subtype
(building_permit / betterment_levy / compensation_197) — denormalized
into cases, documents, document_chunks, decisions, and style_corpus so
vector searches can filter without JOINs.
Why: the system handles two unrelated sub-domains under the same
appeals committee (1xxx building permits and 8xxx/9xxx betterment/197),
with different rules and writing style. Without a separation axis,
search_similar() and the block-writer's precedent lookup were free to
surface betterment-levy paragraphs while drafting a building-permit
decision — a real risk of cross-domain contamination. The same axis
also lets future domains (national insurance, labor law) coexist
without separate schemas.
Schema (V4 migration in db.py):
- ALTER ... ADD COLUMN IF NOT EXISTS on all five tables + composite
indexes (practice_area first).
- Idempotent backfill: case_number ~ '^1' → building_permit, '^8' →
betterment_levy, '^9' → compensation_197; propagated to documents,
chunks, and decisions via case_id; training-corpus rows (case_id NULL)
default to appeals_committee.
Code:
- New services/practice_area.py with derive_subtype, validate, and
is_override + enum constants.
- db.create_case / create_document / store_chunks / create_decision
inherit practice_area from the parent case (or take an explicit
override for the case_id=None training corpus).
- db.search_similar and search_similar_paragraphs accept practice_area
+ appeal_subtype filters using the denormalized columns.
- tools/search.py auto-resolves the filter from case_number when given.
- block_writer._build_precedents_context now passes the active case's
practice_area to search_similar_paragraphs — closes the contamination
hole for the discussion-block precedent fetch.
- tools/cases.case_create auto-derives subtype from case_number; an
explicit override that disagrees writes a case_subtype_override entry
to audit_log so we can spot bad classifications later.
- tools/documents.document_upload_training tags new training material
with practice_area + subtype end-to-end (corpus, document, chunks).
UI (web/static/index.html + web/app.py):
- New-case wizard gets a practice_area dropdown (others disabled until
national_insurance / labor_law arrive) and an appeal_subtype dropdown
with JS auto-fill from the case-number prefix; manual edits stick.
- Case header shows a blue badge with practice_area · subtype.
- CaseCreateRequest plumbs both fields through to cases_tools.case_create.
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
