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>
Closes the loop so דפנה's positions (written inline in the UI and
saved to analysis-and-research.md) automatically become binding
direction for the legal-writer agent — no manual copy-paste,
no bypass.
Backend:
- research_md.extract_chair_directions(path) returns a compact dict
with status (missing/empty/partial/complete), filled_count,
empty_count, and a reduced list of threshold_claims + issues each
with {id, number, title, direction}. Designed to be directly usable
as direction_doc by the writer.
- New MCP tool: drafting.get_chair_directions(case_number) wraps the
helper, resolves the case research file path via config.find_case_dir,
returns formatted JSON.
- Registered in server.py as mcp__legal-ai__get_chair_directions.
legal-writer agent update:
- Adds get_chair_directions to the tools list.
- New mandatory "שלב 1ב" before any block writing: call
get_chair_directions, branch on status.
- missing → halt, report "legal-analyst לא רץ עדיין"
- empty → halt, instruct Dafna to fill positions via the UI URL
- partial → halt unless user confirms; write only filled sections
- complete → proceed
- New "שלב 1ג" constructs an internal direction_doc from the
received chair rulings before writing block י.
- Block י section expanded with 5 binding rules:
1. Open each discussion with Dafna's ruling as the thesis
2. Frame the reasoning in her style (use get_style_guide phrases)
3. Match her tone (decisive vs nuanced)
4. Must NOT contradict her position — if she disagreed with your
own inclination, her position rules
5. Use legal_questions from the analysis file as the analytical
structure (principle question first, concrete application second)
- New bullet section for block יא: summarize each chair ruling
briefly, state final outcome, close with the signed date formula.
Verified all four status paths (missing/empty/partial/complete) via
local test. Now Dafna's workflow is fully end-to-end: she reads the
analyst report in the UI, fills "עמדת ועדת הערר" in each card, hits
blur to auto-save, then triggers legal-writer — which picks up her
positions as direction without any file shuffle.
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>
- Remove cases/new|in-progress|completed subdivision (status managed in DB)
- Rename documents/original → documents/originals (consistent plural)
- Move exports from global data/exports/ into cases/{num}/exports/
- Add documents/research/ for case law and analysis files
- Update all agents, scripts, config, web API endpoints, and DB paths
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Replace single CASES_DIR with find_case_dir() that searches across
all status directories. New cases created in cases/new/{number}/.
Config: CASES_BASE, CASES_NEW, CASES_IN_PROGRESS, CASES_COMPLETED
Docker: added -v /home/chaim/legal-ai/cases:/cases volume mount
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
New architecture: MCP provides context, Claude Code writes.
New functions:
- get_block_context(case_id, block_id) → returns full context package
(prompt, source docs, claims, direction, precedents, style guide)
WITHOUT calling Anthropic API
- save_block_content(case_id, block_id, content) → saves block to DB
New MCP tools: get_block_context, save_block_content
The old write_block (API-based) still works as fallback.
The new flow uses Claude Code's own model (Opus 4.6, 1M context)
which has no separate API billing.
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
