Chaim
6b2fd562ae
extract() routes to _extract_via_panel when HALACHA_PANEL_REGIME_ENABLED: the 3-model panel proposes → votes/score → approval rule → dedup vs corpus (known links as citation, frees a cap slot) → cap HALACHA_PANEL_MAX_NEW genuinely-new principles/decision (by score), rest dropped. Replaces single-model auto-approve; legacy path kept as <2-judge fallback. db.store_panel_principles persists the pre-decided verdict + source-aware canonical create/link (G9 reviewer=panel:...). Dry-run validated on 29468-08-23: ~18 → 4 principles. 6 new tests; full suite 422 green. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
93 lines
3.6 KiB
Python
93 lines
3.6 KiB
Python
"""Phase B selection logic — cap-of-5 + dedup-frees-slot in _extract_via_panel (#152).
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Drives the orchestrator in dry_run mode with panel_extract / corpus-dedup / chunk
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selection monkeypatched, so the cap and the "linked-existing frees a slot" rule
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are verified without LLM/DB.
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"""
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from __future__ import annotations
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import asyncio
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from uuid import uuid4
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import pytest
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from legal_mcp import config
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from legal_mcp.services import halacha_extractor as he
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CID = uuid4()
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def _cluster(rule, verdict, votes=3, score=0.9):
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return {"rule_statement": rule, "supporting_quote": f"q:{rule}",
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"reasoning_summary": "", "rule_type": "interpretive",
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"votes": votes, "score": score, "voters": ["claude", "deepseek", "gemini"][:votes],
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"verdict": verdict, "embedding": [1.0, 0.0]}
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def _patch_common(monkeypatch, clusters):
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async def fake_case(_id):
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return {"id": CID, "source_kind": "external_upload", "is_binding": True,
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"full_text": " ".join(f"q:{c['rule_statement']}" for c in clusters)}
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async def fake_chunks(_id):
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return ([{"content": "reasoning text"}], False)
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async def fake_panel(text, **kw):
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return clusters
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async def none_match(emb, threshold=0.85, status_filter=()):
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return None # default: nothing known → all new (tests override per-case)
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monkeypatch.setattr(he.db, "get_case_law", fake_case)
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monkeypatch.setattr(he, "_select_extractable_chunks", fake_chunks)
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monkeypatch.setattr(he.panel_extraction, "panel_extract", fake_panel)
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monkeypatch.setattr(he.db, "nearest_canonical_halacha", none_match)
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def _run(monkeypatch, clusters, nearest_fn=None):
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if nearest_fn:
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monkeypatch.setattr(he.db, "nearest_canonical_halacha", nearest_fn)
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return asyncio.run(he._extract_via_panel(CID, dry_run=True))
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def test_drops_rejected_keeps_approved_and_pending(monkeypatch):
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clusters = [
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_cluster("A", "approved"), _cluster("B", "pending_review", votes=2, score=0.7),
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_cluster("C", "rejected", votes=1, score=0.9),
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]
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_patch_common(monkeypatch, clusters)
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res = _run(monkeypatch, clusters)
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rules = [p["rule_statement"] for p in res["to_store"]]
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assert "A" in rules and "B" in rules and "C" not in rules
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def test_cap_limits_new_to_max(monkeypatch):
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monkeypatch.setattr(config, "HALACHA_PANEL_MAX_NEW", 3)
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clusters = [_cluster(f"R{i}", "approved") for i in range(6)]
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_patch_common(monkeypatch, clusters)
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async def none_match(emb, threshold=0.85, status_filter=()):
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return None # all new
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res = _run(monkeypatch, clusters, none_match)
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assert res["new"] == 3 and res["dropped_over_cap"] == 3
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assert len(res["to_store"]) == 3
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def test_linked_existing_does_not_consume_cap(monkeypatch):
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monkeypatch.setattr(config, "HALACHA_PANEL_MAX_NEW", 2)
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# 5 candidates; the first 3 are "known" (link), last 2 are new
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clusters = [_cluster(f"K{i}", "approved") for i in range(3)] + \
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[_cluster(f"N{i}", "approved") for i in range(2)]
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_patch_common(monkeypatch, clusters)
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known = {"K0", "K1", "K2"}
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async def nearest(emb, threshold=0.85, status_filter=()):
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# called per candidate in order; pop from a queue mirroring clusters
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rule = nearest._order.pop(0)
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return ("canon", 0.99) if rule in known else None
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nearest._order = [c["rule_statement"] for c in clusters]
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res = _run(monkeypatch, clusters, nearest)
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# 3 linked (free) + 2 new (within cap) → all 5 stored, nothing dropped
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assert res["linked"] == 3 and res["new"] == 2 and res["dropped_over_cap"] == 0
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assert len(res["to_store"]) == 5
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