סוגר את לולאת פידבק-יו"ר→ידע-סוכנים. עד כה resolve רק עדכן את ה-DB; עכשיו
לחיצה ב-/feedback מעירה את ה-CEO שמקפל את הלקח לקובץ לפי הקטגוריה.
- paperclip_client.py: wake_ceo_for_feedback_fold() — יוצר issue ב-Paperclip
עם הלקח + rubric ניתוב (style→SKILL.md, wrong_structure→block-schema,
אחר→lessons.md), מעיר CEO. משכפל את דפוס wake_for_precedent_extraction
- db.py: get_chair_feedback(id) — שליפת הערה בודדת עם case_number/appeal_type
- app.py: resolve endpoint מקבל fold (ברירת מחדל true); BackgroundTask
fire-and-forget; guard — רק עם lesson_extracted. מחזיר fold_queued
- legal-ceo.md: dispatch ל-feedback_fold_ + סעיף "קיפול הערת יו"ר" עם rubric
- frontend: useResolveFeedback מקבל fold; /feedback שולח fold=true עם toast;
drafts-panel שולח fold=false (bookkeeping per-case, בלי קיפול כפול)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- בקאנד: GET לפני ה-async task — אם citation כבר קיים כ-external_upload מחזיר 409
- DB: get_external_case_law_by_citation — lookup לפי citation + source_kind
- פרונט: banner אדום עם פרטי הרשומה הקיימת ושני כפתורות:
• "הפעל חילוץ מחדש" — request-halachot ל-ID הקיים וסגירת הטופס
• "מחק את הרשומה" — DELETE עם confirm, ניקוי conflict לאחר מכן
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
strip_nevo_preamble's _DECISION_START only matched ועדת-ערר openings (בפנינו /
הערר שבנדון / ...), so Nevo COURT judgments — exactly the ones carrying a
מיני-רציו — slipped through unstripped. The editorial mini-ratio then leaked into
the chunked body, risking that the halacha extractor reads Nevo's answer key
(contamination) and polluting the corpus. Proven on בג"ץ 1764/05: its full_text
still contained the מיני-רציו (unstripped).
Fix:
- Extend _DECISION_START with court-ruling openings: פסק-דין/פסק דין header and
the authoring-judge line (השופט/ת, כב' השופט, הנשיא, המשנה לנשיא). re.search
picks the earliest line-start match → the real opinion start, not the prose
ratio above it.
- Widen the Nevo-marker detection window 400→1500 chars so a long court/parties
header doesn't push חקיקה שאוזכרה:/מיני-רציו: out of range.
Verified on the real 1764/05 full_text: strips 2702 chars, body now starts at
'השופט ס' ג'ובראן:', מיני-רציו gone. Regression: ועדת-ערר openings still strip;
non-Nevo text untouched; markers-past-400 now detected. Suite 182 passed (6 new).
This is the anti-contamination prerequisite for the Nevo-ratio gold-set (#86.3/#81.7).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
After a precedent finishes extracting, a claude_session pass folds facets of the
SAME legal question (below #82's dedup cosine — the שפר 14-vs-4 / 403-17→89
granularity gap) into one canonical; the rest are marked 'rejected' (reversible:
out of the active corpus AND the review queue, but recoverable). FOLD-ONLY —
never merges distinct legal questions, never invents.
- Engine: claude_session-as-judge (local CLI, zero cost), 'high' effort — folding
needs careful judgment. One pass per precedent, runs in _extract_impl once all
chunks are done (the prompt dedups within a chunk; this catches across chunks).
- Pure, unit-tested helpers in halacha_quality: CONSOLIDATE_SYSTEM,
build_consolidation_prompt, parse_fold_groups (fails SAFE → [] on any malformed
shape; drops <2-member groups; coerces/dedups indices).
- halacha_extractor._consolidate_precedent picks the canonical per group
(approved>pending, higher confidence, quote_verified, longer) and rejects the
rest via the existing update_halachot_batch (#84). Never rejects a canonical.
Fails OPEN on any error (no CLI / parse fail → 0 folds, data untouched).
- config: HALACHA_CONSOLIDATE_ENABLED/MODEL/EFFORT.
Verified: suite 176 passed (10 new); integration vs dev DB — a 2-facet group
folds to 1 canonical + 1 rejected (tagged), distinct rules untouched, claude
error → 0 folds (fail-open).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
#81.3 — a post-extraction validator that flags halachot whose rule_statement is
NOT entailed by its supporting_quote (the model over-reaching beyond its source).
- Engine: claude_session-as-judge (local CLI, zero API cost) per chaim's standing
preference — one batched judge call per chunk, NOT a hosted NLI model.
- Pure, unit-tested helpers in halacha_quality: NLI_SYSTEM, build_nli_prompt,
parse_nli_verdicts (fails OPEN — any shape/label ambiguity → 'entailed').
- halacha_extractor._nli_check wraps the call; fails OPEN on any error (e.g. no
CLI in the container) so a flaky judge never blocks a genuine halacha.
- Non-entailed (neutral/contradiction) → quality_flag 'nli_unsupported' which
blocks auto-approve (routes to pending_review) via the existing store gate.
- config: HALACHA_NLI_ENABLED/MODEL/EFFORT (effort 'low' — entailment is simple).
Verified: suite 166 passed (10 new); LIVE smoke test against the real claude CLI
returned ['entailed','neutral'] for a supported vs unsupported rule.
Also commits TaskMaster #86 (Nevo preamble/ratio: anti-contamination strip fix +
gold-set benchmark) capturing today's strip_nevo_preamble findings.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Legacy Hebrew .doc precedents (e.g. nevo.co.il CP1255 OLE2) can now be
uploaded directly through the precedent-library, missing-precedent, and
training upload paths — the frontend already advertised .doc but the
backend gate rejected it before reaching the extractor.
- web/app.py: add .doc to ALLOWED_EXTENSIONS (covers all paths that share
the set: precedent library, missing-precedent, training).
- Dockerfile: install libreoffice-writer-nogui (no X11/Java) so the
extractor's existing _extract_doc LibreOffice conversion works in the
Coolify container (was missing → would fail at runtime).
- extractor.py: isolate the LibreOffice user profile per call to avoid a
profile-lock failure on concurrent .doc conversions.
Verified in python:3.12-slim (prod base): .doc→.docx→text yields text
byte-identical to a native Word .docx save (103 paragraphs, 24,341 chars).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Make the chair's pending-halacha review faster and less exhausting.
Backend:
- New 'deferred' review_status (snooze): stays out of the active library AND
out of the default pending queue, without the finality of 'rejected'.
update_halacha stamps reviewer+reviewed_at on defer; HALACHA_REVIEW_STATUSES
is the single source of valid statuses (PATCH validation now uses it).
- db.update_halachot_batch(ids, status, reviewer) — one atomic UPDATE for a
whole group; invalid status / empty ids are a no-op.
- POST /api/halachot/batch (HalachaBatchReviewRequest) wraps it.
- update_halacha now RETURNs quality_flags too (parity with list_halachot).
Frontend (halacha-review-panel):
- Quality-flag badges (#81: non_decision / truncated_quote / thin_restatement /
quote_unverified) so the chair sees WHY an item was held back.
- Defer action — button + keyboard 'D' — to snooze without rejecting (fixes the
'leave in pending forever' anti-pattern; reject stays the junk verb).
- Per-precedent batch bar: 'אשר הכל' / 'דחה הכל' via useBatchReviewHalachot
(one request, one refetch) with confirm guards.
- Halacha/HalachaPatch types gain quality_flags + 'deferred'.
Verified: mcp-server suite 156 passed; web build green; end-to-end integration
against dev DB (batch approve/reject, defer sets status+timestamp, pending
excludes approved+deferred, deferred queryable, invalid status no-op).
Note: api:types regen deferred until deploy (the batch hook is hand-typed, not
dependent on generated types).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
#83 pipeline robustness — the index-numbering correctness guarantee:
- Add CREATE UNIQUE INDEX idx_halachot_unique_index ON halachot(case_law_id,
halacha_index). The extractor assigns the index as MAX+1 under an in-process
store-lock + a cross-process pg advisory lock, so collisions shouldn't occur
in normal operation — but per the research (FireHydrant/OneUptime) the
constraint is the actual correctness guarantee while the lock is the
optimization. A racing/double run now fails LOUDLY (UniqueViolation, chunk
left un-checkpointed → clean resume) instead of silently appending the
duplicates that were the 2026-05/06 over-extraction root cause.
Data prep (run against the live DB before the constraint, backed up to
data/audit/halacha-reindex-backup-*.sql): the 6 precedents that still carried
colliding halacha_index values (9 groups, distinct principles that shared a
number — NOT content dups) were renumbered to unique sequential indices.
Verified: advisory lock holds cross-process and the DB path is direct asyncpg
(no transaction-pooler), so the session lock is safe (83.1); force=True does
delete+checkpoint-clear in one transaction (83.5); constraint rejects a
duplicate-index insert (integration-checked). Full suite 156 passed.
Also commits the TaskMaster tracking for the whole halacha-quality initiative
(#81-#84 + research-backed subtasks, statuses).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Bake the 2026-06-03 strict-cleanup rubric into the extraction pipeline so the
corpus stays clean at the source instead of accumulating duplicates, obiter
dicta, truncated quotes and thin restatements that clog the review queue.
#81 — quality gate:
- New pure module halacha_quality.py with unit-tested validators:
non-decision/obiter (Wambaugh markers), truncated-quote (mid-word cut),
thin-restatement (rule≈quote), quote-unverified.
- Validators run in halacha_extractor._process; a non-decision is re-typed
obiter; flags persist in new halachot.quality_flags column.
- Auto-approve now requires confidence>=threshold AND no quality flags;
flagged items route to pending_review regardless of confidence.
- Both extraction prompts hardened: reject undecided dicta, exclude
case-specific applications, require abstraction, forbid over-splitting.
#82 — dedup-on-insert (store_halachot_for_chunk):
- Within the same precedent, skip a halacha whose normalized supporting_quote
already exists, or whose rule-embedding has cosine>=HALACHA_DEDUP_COSINE
(0.93) against an already-stored one. Makes re-runs idempotent.
Migration: halachot.quality_flags TEXT[] (additive, idempotent ALTER).
Tests: 19 new unit tests; full suite 156 passed. Validated end-to-end against
dev DB (dedup skips dups, flag blocks auto-approve, re-run inserts 0).
Calibration: flags fire on only ~10% of current survivors (low false-positive).
Spec: docs/halacha-strict-rubric.md
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A section that opens with a short header line ('דיון', 'טענות המשיבים')
followed by a paragraph larger than chunk_size flushed the header alone as a
tiny chunk. #55 added a query-time >=50 filter to hide these; this removes
them at the source.
_split_section: (1) don't flush a buffer still below MIN_CHUNK_CHARS — let it
absorb the next paragraph even if that overflows chunk_size, so a short header
rides with its following content; (2) fold a trailing tiny chunk back into its
predecessor.
Verified: re-chunked the 4 corpus docs that still had a tiny chunk
(ע"א 5138/04, בר"מ 2340/02, בג"ץ 6525/15, 403-17) — corpus-wide chunks<50
went 4 -> 0; all 4 stay embedded/searchable and rank top in a relevant search
(נווה שלום #1 for the s.19(ג)(1) exemption query). No regression.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
xhigh is the quality sweet-spot for a single precedent but very slow at scale
(64-chunk case ≈ 20 min). Bulk queue-drains (process_pending over many
precedents) now use a lighter effort to cut wall-clock; interactive single
re-extraction keeps xhigh quality.
- config.HALACHA_BULK_EXTRACT_EFFORT (env, default 'high'; set 'medium' for max
speed, 'xhigh' to match single).
- extract()/_extract_impl()/_extract_chunk() take an `effort` override threaded
to claude_session.query_json; None falls back to HALACHA_EXTRACT_EFFORT (xhigh).
- process_pending_extractions(kind='halacha') passes the bulk effort; single
reextract_halachot keeps xhigh.
Verified end-to-end (mocked LLM): _extract_chunk(effort='medium') → query_json
effort='medium'; effort=None → 'xhigh' fallback. Closes the open item in #72.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Halacha extraction held ALL chunk results in memory and stored once at the very
end — a crash/interrupt mid-run (e.g. the 2026-05-31 freeze) lost everything and
re-paid the full LLM cost on retry.
Now each chunk's halachot are stored AND the chunk is checkpointed
(precedent_chunks.halacha_extracted_at) the moment it finishes:
- V25 schema: precedent_chunks.halacha_extracted_at (per-chunk checkpoint).
- db.store_halachot_for_chunk: atomic per-chunk insert (halacha_index continues
from MAX, caller serializes via an in-process store-lock) + checkpoint mark.
- db.reset_halacha_extraction (force) / mark_all_chunks_extracted (legacy backfill).
- _extract_impl rewritten: resume by default (skip checkpointed chunks; failed
chunks stay pending and are retried; status stays 'processing' until all done);
force=True wipes + redoes all. reextract_halachot passes force=True; the queue
drain (process_pending) resumes by default.
- Legacy guard: a pre-V25 precedent (halachot exist, no checkpoints) is
backfilled and treated as complete — never re-extracted (would duplicate).
Verified on 9002-24 (55 halachot, legacy): resume → legacy-backfill, NO
duplication (stays 55), all chunks checkpointed. Index continuation: store at
55,56 after max 54, no collision. Tracks #72.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-05-31: opus-4-8 @ xhigh extraction + overlapping driver processes (agent
fallback retries each spawn an independent `python -c` driver; process_pending is
serial WITHIN a process but the box ran 4-5 drivers in parallel) → 12-16 concurrent
xhigh `claude -p` procs → load 69 → hard reboot.
Fix: halacha_extractor.extract() now takes a Postgres advisory lock
(pg_try_advisory_lock, key 'HALA') before any work. If another extraction (any
process/agent/driver — all share the legal-ai DB) holds it, the call returns
status='busy' and the precedent stays pending for the next drain. Guarantees ONE
extraction at a time ACROSS PROCESSES — an in-process Semaphore cannot (drivers
are separate OS processes). Core logic moved to _extract_impl (unchanged) under
the lock. CHUNK_CONCURRENCY now env-tunable (HALACHA_CHUNK_CONCURRENCY, default 3).
Verified: while a lock is held, extract() returns 'busy' with no LLM call; lock
releases cleanly and the next extraction proceeds. Tracks #72.
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>
Wire db.recompute_searchable into the ingest pipeline (after statuses are set) and into
extract_and_apply (after fields are persisted to DB, success path only).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add SCHEMA_V21_SQL (searchable boolean column + index on case_law), wire it
into _run_schema_migrations, and implement _compute_searchable (pure predicate)
+ recompute_searchable (idempotent async backfill/update). All 5 unit tests pass.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
pipeline always queues both extraction kinds (INV-ING3); remove the
now-meaningless queue_halachot param from ingest_internal_decision and
migrate_from_style_corpus. Also trim chunker/extractor/rerank from the
precedent_library module-top import (chunking/extraction moved to ingest.py).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Reported: an agent claimed the case had no documents because document_list
returned empty — but the documents exist. Root cause: get_case_by_number did
an exact `WHERE case_number = $1`, so any formatting variant of the number
silently failed to resolve. Verified on 8137-24 (9 docs): "8137/24",
"ערר 8137-24", leading/trailing space, and "בל\"מ 8126/03/25" all returned
"תיק לא נמצא", which the agent read as "no documents" and went blind.
Add _normalize_case_number (strip leading proceeding-type prefix to the first
digit, trim, unify '/'→'-') and a normalized fallback in the lookup query
(exact match preferred via ORDER BY). One fix covers every case_number-scoped
tool (document_list, extract_references, search_case_documents, get_claims,
drafting, ...). Bogus numbers still correctly resolve to "not found". (#58)
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>
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>
Until now, "case_number" was the only stored identifier for a precedent.
But a *citation per the Israeli unified citation rules* is a different
beast — it has bold parties, an unbold prefix (court abbrev + panel/
district parenthetical + case number), and an unbold trailing reporter
(נבו / פ"ד...). Without storing it as a first-class field we couldn't
hand the chair a one-click "copy as citation" experience for pasting
into decisions.
Changes:
- Schema V19: case_law.citation_formatted TEXT (Markdown — parties
wrapped in **…** so the copy helper can render <strong> for Word/Docs
paste and keep plain-text fallback meaningful).
- Metadata extractor: composes citation_formatted from the document
text per the unified citation rules, with worked examples for ע"א /
עת"מ / ערר / בל"מ in the prompt. Refuses to store half-formed strings.
- PATCH /api/precedent-library/{id} accepts citation_formatted so the
chair can correct LLM mistakes.
- /precedents/[id]: dedicated "מראה מקום" block with bold rendering,
a copy-to-clipboard button (text/html + text/plain so Word keeps
the bolds), and an inline edit textarea.
- /precedents list rows: link displays the formatted citation when
available, with a small inline copy button — falls back to the bare
case_number for older rows.
Backfill of existing rows happens by re-stamping the extraction queue
once V19 has rolled out and the new field is reachable.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The missing-precedents drawer + general precedent upload both required
the user to type chair_name, district, practice_area, court, date etc.
upfront — even though those fields can be (and already are, post-upload)
extracted from the document text by the LLM. The metadata-extraction
wakeup also only fired for the /precedent-library/upload path, leaving
missing-precedents committee uploads stuck with whatever stub the user
typed.
Changes:
- Extractor learns chair_name + district, overwrites the new
PLACEHOLDER_PENDING_EXTRACTION sentinel for internal_committee rows
(the DB CHECK forces non-empty; we stamp the placeholder at insert).
- missing_precedent_upload no longer 400s on missing chair/district;
it infers district from the citation when possible, falls back to
the placeholder, and always fires pc_wake_for_precedent_extraction
so the LLM can fill in the rest.
- Both upload sheets default to file (+ citation) only; every other
field is tucked into a closed <details> labeled "אופציונלי — דריסה
ידנית של שדות שיחולצו אוטומטית". Required validators on chair/
district/practice_area dropped — the LLM fills them.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
