Backend for the halacha approval-queue triage (#84). The keyboard UI, batch actions and defer/reject (#84.4–6) already shipped; this adds the gating, prioritization and metrics the queue was missing. db.list_halachot — two opt-in triage controls: * exclude_low_quality (#84.1): drop items carrying ANY quality_flag (application / quote_unverified / truncated / non_decision / thin / nli_unsupported / near_duplicate) — they belong in a 'needs extraction fix' bucket, not the chair's approve queue. * order_by_priority (#84.3): active-learning order — negatively-treated first, then most-uncertain (lowest confidence), then oldest — instead of FIFO, so the highest-value decisions surface first. halachot_pending (MCP) — now gated + prioritized BY DEFAULT; include_low_quality= true reveals the needs-fix bucket. The agent review path benefits immediately. GET /api/halachot — same two params, default OFF (non-breaking; the UI opts in). metrics.halacha_backlog (#84.7) — splits pending into clean vs flagged, adds deferred, reviewed_total, approve_ratio, and a pending_by_flag breakdown, so the backlog distinguishes real review work from extraction noise. Deferred (documented): #84.2 near-duplicate cluster cards and wiring the UI fetch to the new params require frontend work + an api:types regen AFTER this deploys (the new query params aren't in prod's OpenAPI until then) — a clean follow-up. The backend fully supports both now. Verified against the live DB (read-only): - pending 177 → gated-clean 110, 0 flagged items leak into the clean queue. - priority order surfaces the lowest-confidence items first (0.55, 0.55, ...). - backlog: pending_clean=110 / pending_flagged=67 / approve_ratio=0.916, pending_by_flag={nli_unsupported:59, quote_unverified:3, thin:3, truncated:2}. - pytest tests/test_halacha_quality.py — 52 passed (no regression). Invariants: G1 (gate at source — SQL filter, not post-hoc); G2 (no parallel path — same list_halachot); §6 (flagged items routed to a bucket, never dropped). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
244 KiB
244 KiB