Adds scripts/rechunk_legacy_precedents.py: selects every case_law with a tiny
chunk (content<50 — the pre-fix chunker fingerprint) and runs
ingest.reindex_case_law (re-chunk+re-embed from stored full_text only, no
re-OCR/LLM, idempotent). Batch-idempotent (re-queries the affected set).
Run result (2026-06-03): 73 precedents reindexed, 0 failed. Tiny chunks
483 -> 4 (99.2%); total precedent_chunks 5019 -> 3115 (fragments merged).
Search verified healthy (substantial coherent passages, no errors).
The 4 residual tiny chunks are isolated section headings ('דיון',
'טענות המשיבים', ...) emitted by the CURRENT (fixed) chunker — not legacy
fragments — and are already filtered at query time (>=50, #55). Minor
chunker edge case, candidate #55 follow-up.
The DB chunk migration is already applied to prod; this commit is the script
+ SCRIPTS.md entry only (no app code change, no deploy needed).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Covers GAP-11 (INV-RET4/G8) and GAP-14 (INV-QA1/G10). Retrieval quality was
never measured (only telemetry observation) and the halacha review backlog was
invisible (the 10/19 gap was found by accident).
Unit B — backlog visibility (pure code, container):
- metrics.halacha_backlog(conn) → {pending_review, approved, rejected, published,
total, oldest_pending_at}; surfaced in metrics.get_dashboard() (get_metrics MCP
tool) and /api/system/diagnostics. Live count revealed 178 pending / 1552 total,
oldest from 2026-05-03 — previously invisible.
Unit A — retrieval eval harness (host-side scripts):
- scripts/eval_gold_bootstrap.py — seeds data/eval/gold-set.jsonl. Two sources:
citations (cited==relevant via search_relevance_feedback — empty until decisions
cite precedents) and known_item (query=case_name → relevant=self; a real
citation-free signal, the methodology #52 checked by hand). Idempotent; preserves
source='chair' rows.
- scripts/eval_retrieval.py — runs the production retrieval path (search_library /
search_internal) over the gold-set; computes precision@k, recall@k, MRR, nDCG@k
(k=5,10); aggregates overall + per-corpus + per-practice_area; writes a report and
a delta vs committed baseline.json (which records the retrieval_config it reflects).
--self-test unit-checks the metric math offline.
Gold-set strategy = hybrid (chair decision): bootstrap + chair review. The citation
source is empty today (0 cited precedents in decisions), so the seed is known-item
(77 queries: 54 internal_decisions + 23 precedent_library). The gold-set is
PROVISIONAL until Dafna reviews it (the domain chair-gate).
Baseline (production config: multimodal+rerank on): R@10=0.987, MRR=0.837,
nDCG@10=0.872. Finding: MULTIMODAL_ENABLED=true slightly lowers known-item recall
(image-page results displace exact name matches) — relevant to #15. precedent_library
weaker than internal (R@10 0.957 vs 1.0) — one external precedent unfindable by name.
"CI gate" realized as discipline (re-runnable harness + committed baseline + run
before/after any retrieval-layer change) — retrieval needs prod DB + Voyage, no CI
runner has that access.
Spec: docs/superpowers/specs/2026-05-31-fu5-eval-harness-design.md
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Dry-run surfaced 2 rows with בל"מ prefix but proceeding_type=ערר. Since the
migration strips the prefix, a wrong proceeding_type would silently lose the
בל"מ signal — must be chair-adjudicated, not auto-applied. Chair table now
flags 4 rows: 2 DUP_CHECK (8047-23) + 2 PROC_MISMATCH.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Root cause of "agent can't find the Agasi decision in the corpus" (CMPA-55):
the decision was fully ingested, but the retrieval layer failed on the
realistic agent query — searching by case name.
- RC-A (#52): lexical tsvector covered only chunk content + halacha text,
so a bare-name query ("אגסי") matched decisions that *cite* the case, not
the case itself. Add meta_tsv on case_law(case_name, case_number) (SCHEMA
V20) and OR it into the lexical halacha/chunk SQL with a match boost, so a
name/number hit surfaces the case's own rows. Agasi: rank 4 → rank 1.
- RC-B (#53): precedent_library_list hard-defaulted source_kind=external_upload
and never exposed the param, hiding uploaded ערר/בל"מ (internal_committee)
decisions. Thread source_kind through service → tool → MCP tool (supports
'internal_committee' / 'all_committees').
- #54: agent instructions (researcher/analyst/writer) — search-by-name
protocol: add content/case-number, search both corpora, use all_committees
before declaring "not in corpus".
- #55: chunker produced tiny fragment chunks ("דיון", "החלטה") from header
keywords matched mid-sentence. Anchor SECTION_PATTERNS to line start +
merge sub-min sections; exclude <50-char fragments at query time (484
existing fragments hidden; full re-chunk tracked as #57).
Tests: scripts/test_retrieval_by_name.py (name ranks case above citer +
substantive regressions); chunker unit checks (0 tiny chunks). New findings
filed as tasks #56 (halacha source_kind leak) and #57 (re-chunk migration).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Address security-review finding: the host-side legal-chat-service was
binding 0.0.0.0:8770 with no authentication. The service spawns the
claude CLI, whose tool set includes Bash + Edit — so an unauthenticated
/chat/start is effectively RCE. Oracle Cloud's security list closes the
port externally, but defense-in-depth requires two independent layers:
1. Bind defaults to 10.0.1.1 (docker0 bridge gateway). Reachable from
containers on docker bridges (the legal-ai container has a route via
the coolify network), invisible to anything outside the host. The
--host flag is still configurable for local-dev (127.0.0.1) or
special-case deployments, but 0.0.0.0 is explicitly discouraged in
the docstring.
2. /chat/start requires Authorization: Bearer <LEGAL_CHAT_SHARED_SECRET>.
The secret is loaded from /home/chaim/.legal-chat-service.env (chmod
600, off-repo) by the pm2 ecosystem and mirrored as a Coolify env
var so the FastAPI chat_proxy sends a matching header. hmac.compare_digest
prevents timing oracles. /health stays unauthenticated (static OK,
no subprocess) so the FastAPI proxy can probe liveness without the
secret.
The service refuses to start if LEGAL_CHAT_SHARED_SECRET is empty or
shorter than 24 chars — no silent fallback to an open mode.
When the Infisical MCP comes back, migrate the secret into the vault
at /_GUIDELINES per the project secrets policy.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
The Style Studio's curator-prompt + chat features read reference docs
from disk at runtime. Two issues from the initial production run:
1. Dockerfile + .dockerignore excluded .claude/, docs/, and most of
skills/. Now COPY the four specific files the new endpoints need:
- .claude/agents/hermes-curator.md
- skills/decision/SKILL.md
- docs/legal-decision-lessons.md
- docs/corpus-analysis.md
.dockerignore opens whitelists for just those files.
2. Coolify's custom_docker_run_options=--add-host=host.docker.internal:host-gateway
is not honored on dockerimage build_pack apps (ExtraHosts stayed []).
Switch chat_proxy.py default to http://10.0.1.1:8770 — the docker0
bridge gateway, same pattern Paperclip uses for 3100. Bind the host
pm2 service to 0.0.0.0:8770 so the container can reach it via the
bridge IP. Oracle Cloud's security list keeps the port unreachable
from the public internet.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Six-phase upgrade of /training from a read-only dashboard into a full
Style Studio for managing Daphna's style corpus.
- Upload Sheet on /training: file → proofread preview → commit (no more
CLI-only `upload-training` skill).
- Rich corpus metadata: GET /api/training/corpus returns summary, outcome,
key_principles, page_count, parties (regex), legal_citation, lessons_count.
PATCH endpoint for chair edits. CorpusDetailDrawer with 4 tabs (details
/content/lessons/patterns) replaces the bare table row.
- LLM metadata enrichment: style_metadata_extractor + MCP tools
(style_corpus_enrich, style_corpus_pending_enrichment) fill summary
/outcome/key_principles via claude_session (free, host-side).
- Per-decision lessons: new decision_lessons table + 4 REST endpoints +
LessonsTab in drawer; hermes-curator now auto-posts findings as
decision_lessons(source=curator).
- Curator Portrait tab: prompt rendered with link to Gitea, recent
curator findings, style_analyzer training prompts, propose-change
form that writes proposals to data/curator-proposals/ for manual
chair review (no auto-mutation of the agent file).
- Style chat tab: SSE-streamed conversations with the style agent.
New host-side pm2 service (legal-chat-service, port 8770) wraps
claude CLI with stream-json + --resume continuation; FastAPI proxies
via host.docker.internal. Zero API cost — uses chaim's claude.ai
subscription. chat_conversations + chat_messages persist history.
Architecture: keeps the existing rule that claude_session only runs
on the host (not the container). The new legal-chat-service is the
canonical bridge between the container and the local CLI for the chat
feature; everything else (upload, metadata, lessons) stays within the
container's existing capabilities.
Audit script (scripts/audit_training_corpus.py) included for verifying
which corpus rows still need enrichment.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
After the proceeding_type field landed, users started flipping cases
to בל"מ via the edit dialog. But the case-header badge + cases-table
filter were still gated on isBlamSubtype(appeal_subtype), so the badge
didn't appear when only the proceeding_type changed. Now the badge
shows when either proceeding_type === 'בל"מ' OR appeal_subtype is an
extension_request_* variant — the legacy path stays so existing rows
that never got a proceeding_type still render correctly.
Also regen types.ts from prod (proceeding_type now in OpenAPI schema)
and register the one-shot process_pending_blam.py script.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Same case_number can exist as both a regular appeal (ערר) and an
extension-of-time request (בל"מ), and we were inferring the difference
from appeal_subtype prefixes — fragile, and case-number lookups
weren't disambiguated. Now stored as a first-class field on both
case_law (corpus) and cases (live cases), with partial unique indexes
on (case_number, proceeding_type).
- SCHEMA_V15: column + CHECK constraints + backfill from
appeal_subtype LIKE 'extension_request_%' + partial unique indexes
replace the old global UNIQUE(case_number).
- derive_proceeding_type() centralizes the inference rule
(extension_request_* → בל"מ; subject regex fallback; default ערר).
- Metadata extractor prompt asks Claude to populate the new field
explicitly; apply_to_record writes it for internal_committee rows.
- internal_decision_upload, case_create, case_update accept an
optional proceeding_type; FastAPI request models expose it.
- Wizard + edit dialog get a sided Select; case header renders the
resolved label (ערר / בל"מ).
- Uploaded the 2 staged בל"מ decisions on betterment levy:
8126/24 (סופר נוח, 13 chunks), 8047/23 (הרנון, 48 chunks).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Four parallel sub-agents closed the remaining critical gaps from the
26/05 Stage A/B sprint. Each block independently tested; aggregated here.
## #30/#31 finalizers (sub-agent A)
* Auto-derive practice_area in case_create from case_number prefix
(1xxx→rishuy_uvniya, 8xxx→betterment_levy, 9xxx→compensation_197);
default for CaseCreateRequest is now "" (the DB constraint catches
any stray "appeals_committee").
* practice_area.py: derive_subtype now handles axis-B domain values
(rishuy_uvniya/betterment_levy/compensation_197) without parsing the
case number; new helper derive_domain_practice_area().
* Halacha re-extraction verified unnecessary — all 6 reclassified
records already had is_binding=false and approved halachot.
* Regression tests: 6 cases in tests/test_corpus_constraints.py
covering practice_area enum, internal-committee chair/district,
external-upload arar prefix, MCP guard.
* UI: district input → Select dropdown (7 districts) in
precedent-edit-sheet.tsx, preserving legacy free-text values.
## #37 בל"מ subtypes (sub-agent B)
* 3 new appeal_subtypes: extension_request_{building_permit,
betterment_levy,compensation}. APPEALS_COMMITTEE_SUBTYPES extended,
SUBTYPES_BY_AREA mappings added.
* New helpers: is_blam_subject(), is_blam_subtype(),
derive_subtype_with_blam(case_number, subject, practice_area).
case_create now uses it to auto-detect "בקשה להארכת מועד" subjects.
* 3 methodology templates under docs/methodology/extension-request-*.md.
* paperclip_client.py mapping updated for the 3 new subtypes
(extension_request_building_permit→CMP, the other two→CMPA).
* Frontend: bilingual "בל"מ" badge + filter dropdown on cases list +
detail header; appeal-type-bars collapseBlam() merges בל"מ into its
parent domain for aggregate bars.
* Wizard auto-detects בל"מ from subject during case creation.
* 3 Berlinger cases (1017/1018/1019-03-26) migrated to
appeal_subtype=extension_request_building_permit via psql.
## #35 missing_precedents feature (sub-agent C)
* Schema V13: missing_precedents table (citation, case_id, party,
legal_topic, status, linked_case_law_id, claim_quote, ...) +
FK constraints + 3 indexes. Applied via psql + idempotent migration.
* 6 db.py service functions, 3 MCP tools, 6 FastAPI endpoints
(POST/GET/PATCH/DELETE/upload — upload routes by citation prefix
to ingest_internal_decision or ingest_precedent).
* Next.js page /missing-precedents with 5 status tabs + filters +
sidebar badge counter + detail drawer with metadata edit + smart
upload form that switches fields per committee/court.
* Bootstrap: 7 rows imported from the JSON file
(3 citations × cases, all status=closed with linked_case_law_id).
* legal-researcher.md: new §2ב.5 with missing_precedent_create
usage + dedup semantics + tool grant.
## #36 legal_arguments aggregation (sub-agent D)
* Schema V14: legal_arguments + legal_argument_propositions M:M.
Applied via psql.
* New service argument_aggregator.py with two functions —
aggregate_claims_to_arguments() (Claude CLI / claude_session) and
get_legal_arguments(). Graceful llm_unavailable handling when CLI
is missing (containers).
* 2 MCP tools + 2 API endpoints (POST .../aggregate-arguments as
BackgroundTask, GET .../legal-arguments).
* Frontend: shadcn Accordion + new legal-arguments-panel.tsx with
hierarchical (party → priority badge → arguments) display, "טיעונים"
tab on the case page, "חשב/חשב מחדש" buttons.
* scripts/backfill_legal_arguments.py + SCRIPTS.md entry — dry-run
found 8 candidate cases including 1017/1018/1019.
## Open follow-ups (intentionally deferred)
* npm run api:types in web-ui (CLAUDE.md flow) — recommended before
the next UI commit; not required for backend deployment.
* Run backfill_legal_arguments.py --apply once the container picks up
the new aggregator service.
* webhook on missing-precedents upload-close to Paperclip (optional).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- P3-T1: --check-instructions flag + check_instructions() prints a table of all
agents' instructionsFilePath with status (✅ OK / ❌ MISSING / ⚠ NOT SET),
size, mtime, and ⚠ DRIFT when file has changed since last sync
- P3-T2: --apply now runs a pre-flight check on master agents and aborts if any
instruction file is missing, before touching the DB or calling any API
- P3-T3: get_claude_md_mtime() helper; --apply stamps claude_md_mtime and
claude_md_last_synced into each mirror agent's metadata via the PATCH call
- P3-T4: alias check-agents added to ~/.bashrc
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
A/B test (2026-05-05) showed DeepSeek V4-Pro is 2-3x faster and ~20x cheaper
than Sonnet for style/lexicon pattern analysis, with comparable quality.
Adds adapters/deepseek-paperclip-adapter/ package, documents adapter requirements
(env injection, run-id headers), updates CLAUDE.md with adapter integration notes,
and records lessons from ערר 1200-25 (block order for 1xxx, "להלן מתוך" pattern,
expanded factual background, bridge planning analysis, flat heading structure).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
paperclip-dev is for maintaining the Paperclip codebase itself — not
relevant to legal work. Removed from all 14 agents (was on CMPA mirror).
paperclip-converting-plans-to-tasks helps decompose a plan into assigned
issues. Useful for the planning-heavy agents (CEO, analyst). Now scoped
to those two — removed from the other 5 in CMPA where it had crept in.
Net effect: zero drift on paperclipai/* skills across all 7 master+mirror
pairs. Verified via the new Agents tab dashboard.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Brings the legal-ai ↔ Paperclip integration in line with the official
Paperclip skill. Net effect: HEARTBEAT.md -47% (370→195 lines), all 14
agents on uniform runtime_config + budget + instructionsBundleMode, and
two cross-company helpers replacing manual SQL.
Highlights:
- HEARTBEAT.md refactor: project-specific only, delegates to the official
paperclipai/paperclip skill (loaded per agent). Adds heartbeat-context
fast-path (§1.7) and PAPERCLIP_WAKE_PAYLOAD_JSON shortcut (§1.5).
- Issue Thread Interactions API: legal-ceo.md now uses
ask_user_questions / request_confirmation / suggest_tasks instead of
free-text comments — gives chair structured UI with idempotency keys.
- pc.sh + paperclip_api.pc_request: every API call goes through helpers
that inject Authorization + X-Paperclip-Run-Id (audit trail).
- sync_agents_across_companies.py: master(CMP)→mirror(CMPA) sync via
Paperclip API, idempotent, with --verify and --apply modes.
- skills/new-company-setup: 11-step blueprint distilling all 11 gaps
into a single onboarding runbook for the next company.
- .taskmaster: 12 tasks covering each gap (one already closed: #29).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The first-pass retrofit re-extracted via extractor.extract_text, which
re-runs Google Vision OCR on scanned pages. OCR is non-deterministic,
so the new text didn't match the chunk content stored in the DB
(produced by the original OCR run) — only ~7% of chunks were located.
New approach (no OCR cost):
1. Use the stored documents.extracted_text from the DB — the exact
text the chunks were produced from, so chunk lookups match.
2. Anchor page boundaries via PyMuPDF direct text reads (free, no
OCR). Pages with usable direct text are anchored by snippet match;
OCR-only pages are linearly interpolated between anchors.
3. Search each chunk in extracted_text using a whitespace-tolerant
helper — needed because the chunker joins paragraphs with single
'\\n' while extracted_text uses '\\n\\n' as page separators.
Verified on 8174-24 (5 docs, 307 chunks) + 8137-24 (9 docs, 512
chunks): 100% chunks tagged, 13s total, $0 cost.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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>
Stage C: per-page image embeddings via voyage-multimodal-3 + hybrid
text+image search. Off by default; enable with MULTIMODAL_ENABLED=true.
- Schema V9: document_image_embeddings + precedent_image_embeddings
(vector(1024), page_number, image_thumbnail_path)
- extractor.render_pages_for_multimodal renders PDF pages at
MULTIMODAL_DPI (144) for embedding + JPEG thumbnails at
MULTIMODAL_THUMB_DPI (96) for UI preview, in one pass
- embeddings.embed_images calls voyage-multimodal-3 in 50-page batches
- services/hybrid_search.py orchestrator: rerank applied to text side
first (rerank-2 is text-only); image side cosine; weighted merge
with text_weight 0.65 (env-tunable); image-only pages surface as
match_type='image' so dense scanned content still appears
- processor.process_document and precedent_library.ingest_precedent
gated by flag — non-fatal on multimodal failure
- scripts/multimodal_backfill.py — idempotent per-case CLI to embed
existing documents without re-extracting text
Validated locally on a 5-page response brief: render 0.31s, embed 8.32s,
hybrid merge surfaces image rows correctly. Production rollout starts
with flag=false (no behavior change), then per-case A/B.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Phase A — voyage-3 migration (executed):
- VOYAGE_MODEL=voyage-3 set in Coolify (legal-ai app) and ~/.env
- scripts/reembed_voyage.py: re-embeds document_chunks (6157),
case_law_embeddings (9), precedent_chunks (385), and halachot (400)
using the new model. paragraph_embeddings was empty. 6951 rows
re-embedded in 93s, ~75 rows/sec.
- Same 1024 dim → no schema change needed.
Why voyage-3 over voyage-law-2: benchmark on 3 Hebrew legal queries
with real passages from the corpus gave voyage-3 perfect ordering on
3/3 tests AND the largest separation (+0.483 vs voyage-law-2's
+0.238). voyage-4 family had bigger separation but missed top-1 on
the hardest test.
Phase B (voyage-context-3) and Phase C (voyage-multimodal-3.5 for
scanned + appraiser docs) are designed in docs/voyage-upgrades-plan.md
but deferred — to be picked up in a fresh conversation. The plan
includes:
- Phase B: contextualized embeddings refactor (~49% recall lift on
legal docs per Anthropic's research). Same dim, but ingestion
pipeline must pass full doc context per chunk.
- Phase C: page-level image embeddings via voyage-multimodal-3.5,
stored in a parallel *_image_embeddings table. Hybrid text+image
search. Targets appraiser report tables and scanned PDFs where
current OCR loses layout.
After this commit: MCP server needs a /mcp reconnect to pick up the
new VOYAGE_MODEL env, and the legal-ai container will pick it up on
its next redeploy.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The claude_session bridge had two structural defects that made any
non-trivial document extraction unreliable:
1. subprocess.run() blocks the asyncio event loop in the MCP server
for the full duration of every LLM call (60-180s typical).
2. The 120-second timeout was below the cold-cache cost of any
document over ~12K Hebrew characters. Three back-to-back timeouts
on case 8174-24 dropped 43 appellant claims on the floor.
Phase 1 of the remediation plan — keeps claude_session as the engine
(no Anthropic API switch) and restructures around it:
claude_session.py
• query / query_json are now async — asyncio.create_subprocess_exec
instead of subprocess.run, so MCP server can serve other coroutines
while a call is in flight.
• DEFAULT_TIMEOUT 120 → 1800 (30 min). High enough that no realistic
document hits it; bounded so a runaway never zombifies forever.
• LONG_TIMEOUT 300 → 3600 for opus block writing on full case context.
• TimeoutError now actually kills the subprocess (asyncio.wait_for
cancellation alone leaves the child running).
claims_extractor.py
• _split_by_sections: chunks at numbered sections / Hebrew letter
headings / "פרק" markers / markdown ##, falls back to paragraph
breaks, then to hard splits. Targets 12K chars per chunk — small
enough that each chunk reliably finishes inside the timeout.
• _extract_chunk: per-chunk retry (1 attempt by default) with
structured logging on failure. Failed chunks no longer crash the
overall extraction; they're skipped with a partial-result warning.
• extract_claims_with_ai now runs chunks in parallel via
asyncio.gather bounded by a semaphore (CHUNK_CONCURRENCY=3).
For a 25K-char appeal: was sequential 150-300s, now ~70-90s.
Updated all 9 callers (claims, appraiser facts, block writer, qa
validator, brainstorm, learning loop, style analyzer × 3) to await
the now-async API.
The one-shot scripts/extract_claims_8174.py used to recover 43
appellant claims on case 8174-24 has been moved to .archive/ — phase 1
makes it obsolete. SCRIPTS.md updated.
Phase 2 (background-task wrapper around LLM-bound MCP tools, persistent
llm_tasks table, SSE progress) is the structural follow-up — separate PR.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Fixes critical bug in 1033-25: user-uploaded עריכה-*.docx files were
orphaned on disk while exports kept rebuilding from stale DB blocks.
New architecture:
- User-uploaded DOCX becomes the source of truth (cases.active_draft_path)
- System edits via XML surgery with real Word <w:ins>/<w:del> revisions
- User can Accept/Reject each change from within Word
Components:
- docx_reviser.py: XML surgery for Track Changes (15 tests)
- docx_retrofit.py: retroactive bookmark injection with Hebrew marker
detection + heading heuristic (9 tests)
- docx_exporter.py: emits bookmarks around each of the 12 blocks
- 3 new MCP tools: apply_user_edit, list_bookmarks, revise_draft
- 4 new/updated endpoints: upload (auto-registers active draft),
/exports/revise, /exports/bookmarks, /exports/{filename}/retrofit,
/active-draft
- DB migration: cases.active_draft_path column
- UI: correct banner using real v-numbers, "מקור האמת" badge,
detailed upload toast with bookmarks_added/missing_blocks
- agents: legal-exporter (3 export modes), legal-ceo (stage G for
revision handling), legal-writer (revision mode)
Multi-tenancy:
- Works for both CMP (1xxx cases) and CMPA (8xxx/9xxx cases)
- New revise-draft skill added to both companies
- deploy-track-changes.sh syncs skills CMP ↔ CMPA
- retrofit_case.py: one-off retrofit of existing files
Tests: 34 passing (15 reviser + 9 retrofit + 4 exporter bookmarks + 6 e2e)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Active scripts (5): auto-sync-cases.sh, backup-db.sh, restore-db.sh,
notify.py, bidi_table.py
Archived (17): one-time migration/seeding scripts whose functionality
is now in MCP server or web API. Moved to scripts/.archive/
Deleted (5): zero-value scripts (duplicates, hardcoded single-case,
debug scripts)
Added scripts/SCRIPTS.md — registry of all scripts with purpose,
status, and what superseded them. CLAUDE.md updated with rule:
any script change requires SCRIPTS.md update.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- CLAUDE.md: clarify vault was deleted, knowledge is in docs/+training/
- Remove import-final-decisions.py (migration completed, all decisions in DB)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Assets live in ezer-mishpati/paperclip-config (cloned at ~/.paperclip).
Deploy via: ~/.paperclip/hebrew/apply-hebrew.sh
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- CEO agent now sends email via notify.py when awaiting human response
- CEO creates child issues (parentId) instead of flat disconnected issues
- Fix notify.py email address to chaim+paperclip@marcus-law.co.il
- Move Paperclip UI assets (RTL CSS + Hebrew JS) into repo under scripts/
- Add deploy.sh script to push assets to live Paperclip instance
- Fix comment box positioning: newest comment on top, input below it
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- auto-sync-cases.sh: fix broken directory scan (was looking for
status subdirs that don't exist), fix env var word-splitting bug,
add safe.directory handling and error logging
- cases.py: auto-create Gitea repo on case_create, fix
documents/original → documents/originals naming mismatch
- app.py: add GET /api/cases/{case_number}/git-status endpoint
- web-ui: add SyncIndicator component in case header showing
sync status (synced/pending/no remote) with last commit time
- pyproject.toml: add httpx dependency
- CLAUDE.md: update Paperclip wakeup API docs
- settings page: switch tag input from Select to free-text with datalist
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Visual dashboard at #/style-report with 4 sections:
- Hero: 24 decisions, char counts, subject donut, timeline
- Anatomy: average section-length breakdown (intro → ruling → conclusion)
- Signature Phrases Wall: pattern cards with real corpus frequencies, filter
chips by type, click → modal with examples
- Contribution: per-decision "new vs confirmed" patterns, growth curve SVG
Backend:
- /api/training/style-report endpoint computes all 4 sections in one call
- Headlines in Hebrew are computed server-side from real data
- Backfill script for style_patterns.frequency using _strip_nikud +
pattern-variant extraction (templates with [placeholders], / alternatives,
ellipsis all handled)
Real findings from the 24-decision corpus:
- דיון משפטי = 49% of avg decision (the focus)
- 23/24 use "לפנינו ערר" opening formula
- 21/24 use "ניתנה פה אחד" closing
- After 7 decisions we already learned 85% of her style patterns
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- New proofreader service strips Nevo editorial additions (front matter,
postamble, page headers, watermarks, inline codes) from DOCX/PDF/MD
- PDF pages use Google Vision OCR for clean Hebrew RTL extraction
- New training page at #/training with drag-and-drop upload, automatic
metadata extraction (decision number, date, categories), reviewable
preview, and style pattern report grouped by type
- API endpoints: /api/training/{analyze,upload,corpus,patterns,
analyze-style,analyze-style/status}
- Fix claude_session.query to pipe prompt via stdin, avoiding ARG_MAX
overflow when analyzing 900K+ char corpus
- CLI scripts for batch proofreading and corpus upload
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>
New: scripts/notify.py — sends via SMTP (notify@marcus-law.co.il → paperclip+chaim@marcus-law.co.il)
Updated: HEARTBEAT.md — agents must send email when waiting for human decision
Triggers: outcome choice, direction approval, QA failures, review ready.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
