Chaim
df007784c9
- HALACHA_CORROBORATION_AUTO_APPROVE config (default ON, Dafna validated 2026-06-01) - approval_action(agg, has_overruled): overruled→demote, corroborated→approve, else None - 4 offline unit tests; Phase 2 plan + TaskMaster #75 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
68 lines
2.9 KiB
Python
68 lines
2.9 KiB
Python
from __future__ import annotations
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import pytest
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from legal_mcp.services import corroboration as cor
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@pytest.mark.parametrize("raw,expected", [
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({"treatment": "followed"}, "followed"),
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({"treatment": "OVERRULED"}, "overruled"), # case-insensitive
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({"treatment": "bananas"}, "mentioned"), # unknown -> neutral default
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({}, "mentioned"), # missing -> neutral default
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])
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def test_coerce_treatment(raw, expected):
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assert cor._coerce_treatment(raw) == expected
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def test_treatment_polarity():
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assert cor.is_positive("followed") and cor.is_positive("explained")
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assert cor.is_negative("distinguished") and cor.is_negative("overruled")
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assert not cor.is_positive("mentioned") and not cor.is_negative("mentioned")
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def test_match_accepts_above_threshold():
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assert cor.accept_match(("h1", 0.62), floor=0.50) == "h1"
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def test_match_rejects_below_threshold():
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assert cor.accept_match(("h1", 0.41), floor=0.50) is None
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def test_match_rejects_empty():
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assert cor.accept_match(None, floor=0.50) is None
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def _link(src, treatment):
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return {"source_id": src, "treatment": treatment}
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def test_aggregate_counts_distinct_positive():
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links = [_link("d1","followed"), _link("d1","explained"), _link("d2","followed")]
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agg = cor.aggregate(links, min_cites=2)
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assert agg["positive_sources"] == 2 # d1 counted once (INV-COR4 independence)
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assert agg["has_negative"] is False
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assert agg["corroborated"] is True
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def test_aggregate_negative_blocks():
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links = [_link("d1","followed"), _link("d2","followed"), _link("d3","distinguished")]
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agg = cor.aggregate(links, min_cites=2)
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assert agg["has_negative"] is True
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assert agg["corroborated"] is False # any negative -> not corroborated (INV-COR2)
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def test_aggregate_below_threshold():
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agg = cor.aggregate([_link("d1","followed")], min_cites=2)
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assert agg["corroborated"] is False # single source insufficient (INV-COR4)
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# --- Phase 2: approval decision (INV-COR2/COR4) ---
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def test_approval_action_corroborated_approves():
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agg = {"positive_sources": 2, "has_negative": False, "corroborated": True}
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assert cor.approval_action(agg, has_overruled=False) == "approve"
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def test_approval_action_overruled_demotes_even_if_corroborated():
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# overruled outranks any positive count (INV-COR2 strong form)
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agg = {"positive_sources": 3, "has_negative": True, "corroborated": False}
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assert cor.approval_action(agg, has_overruled=True) == "demote"
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def test_approval_action_single_source_noop():
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agg = {"positive_sources": 1, "has_negative": False, "corroborated": False}
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assert cor.approval_action(agg, has_overruled=False) is None
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def test_approval_action_negative_nonoverruled_noop():
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# distinguished blocks approval but does not demote (no overruled)
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agg = {"positive_sources": 2, "has_negative": True, "corroborated": False}
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assert cor.approval_action(agg, has_overruled=False) is None
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