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386 lines
12 KiB
Python
386 lines
12 KiB
Python
"""
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Behavioral tests for base_candidate module.
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Tests Candidate dataclass with evidence management and scoring logic.
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"""
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import pytest
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class TestCandidateInit:
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"""Tests for Candidate dataclass initialization."""
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def test_basic_construction(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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c = Candidate(name="Lake X")
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assert c.name == "Lake X"
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def test_evidence_defaults_empty_dict(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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c = Candidate(name="Lake X")
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assert c.evidence == {}
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def test_score_defaults_zero(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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c = Candidate(name="Lake X")
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assert c.score == 0.0
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def test_metadata_defaults_empty_dict(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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c = Candidate(name="Lake X")
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assert c.metadata == {}
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class TestCandidateAddEvidence:
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"""Tests for Candidate.add_evidence() method."""
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def test_add_single_evidence(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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e = Evidence(
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claim="formed in ice age",
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type=EvidenceType.RESEARCH_FINDING,
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source="wiki",
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)
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c.add_evidence("c1", e)
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assert "c1" in c.evidence
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assert c.evidence["c1"] is e
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def test_add_multiple_evidence(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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e1 = Evidence(
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claim="claim1", type=EvidenceType.DIRECT_STATEMENT, source="s1"
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)
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e2 = Evidence(
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claim="claim2", type=EvidenceType.NEWS_REPORT, source="s2"
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)
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c.add_evidence("c1", e1)
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c.add_evidence("c2", e2)
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assert len(c.evidence) == 2
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def test_overwrite_existing_evidence(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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e1 = Evidence(claim="old", type=EvidenceType.INFERENCE, source="s1")
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e2 = Evidence(
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claim="new", type=EvidenceType.DIRECT_STATEMENT, source="s2"
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)
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c.add_evidence("c1", e1)
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c.add_evidence("c1", e2)
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assert c.evidence["c1"].claim == "new"
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class TestCandidateCalculateScore:
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"""Tests for Candidate.calculate_score() method."""
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def test_empty_constraints_returns_zero(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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c = Candidate(name="Lake X")
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assert c.calculate_score([]) == 0.0
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def test_single_constraint_with_evidence(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.constraints.base_constraint import (
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Constraint,
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ConstraintType,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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constraint = Constraint(
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id="c1",
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type=ConstraintType.PROPERTY,
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description="d",
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value="v",
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weight=1.0,
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)
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evidence = Evidence(
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claim="supports",
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type=EvidenceType.DIRECT_STATEMENT,
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source="s",
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confidence=0.8,
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)
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c.add_evidence("c1", evidence)
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score = c.calculate_score([constraint])
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assert score == pytest.approx(0.8)
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def test_score_considers_weight(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.constraints.base_constraint import (
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Constraint,
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ConstraintType,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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c1 = Constraint(
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id="c1",
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type=ConstraintType.PROPERTY,
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description="d",
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value="v",
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weight=2.0,
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)
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c2 = Constraint(
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id="c2",
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type=ConstraintType.EVENT,
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description="d",
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value="v",
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weight=1.0,
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)
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e1 = Evidence(
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claim="e1",
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type=EvidenceType.DIRECT_STATEMENT,
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source="s",
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confidence=0.9,
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)
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e2 = Evidence(
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claim="e2",
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type=EvidenceType.NEWS_REPORT,
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source="s",
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confidence=0.3,
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)
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c.add_evidence("c1", e1)
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c.add_evidence("c2", e2)
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score = c.calculate_score([c1, c2])
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# (0.9*2.0 + 0.3*1.0) / (2.0 + 1.0) = 2.1 / 3.0 = 0.7
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assert score == pytest.approx(0.7)
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def test_missing_evidence_contributes_zero(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.constraints.base_constraint import (
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Constraint,
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ConstraintType,
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)
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c = Candidate(name="Lake X")
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constraint = Constraint(
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id="c1",
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type=ConstraintType.PROPERTY,
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description="d",
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value="v",
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weight=1.0,
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)
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score = c.calculate_score([constraint])
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assert score == 0.0
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def test_score_stored_on_candidate(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.constraints.base_constraint import (
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Constraint,
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ConstraintType,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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constraint = Constraint(
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id="c1", type=ConstraintType.PROPERTY, description="d", value="v"
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)
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evidence = Evidence(
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claim="c",
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type=EvidenceType.DIRECT_STATEMENT,
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source="s",
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confidence=0.7,
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)
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c.add_evidence("c1", evidence)
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c.calculate_score([constraint])
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assert c.score == pytest.approx(0.7)
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class TestCandidateGetUnverifiedConstraints:
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"""Tests for Candidate.get_unverified_constraints() method."""
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def test_all_unverified_when_no_evidence(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.constraints.base_constraint import (
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Constraint,
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ConstraintType,
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)
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c = Candidate(name="Lake X")
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constraints = [
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Constraint(
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id="c1",
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type=ConstraintType.PROPERTY,
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description="d",
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value="v",
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),
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Constraint(
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id="c2", type=ConstraintType.EVENT, description="d", value="v"
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),
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]
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unverified = c.get_unverified_constraints(constraints)
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assert len(unverified) == 2
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def test_none_unverified_when_all_have_evidence(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.constraints.base_constraint import (
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Constraint,
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ConstraintType,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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constraint = Constraint(
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id="c1", type=ConstraintType.PROPERTY, description="d", value="v"
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)
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c.add_evidence(
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"c1", Evidence(claim="c", type=EvidenceType.INFERENCE, source="s")
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)
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assert len(c.get_unverified_constraints([constraint])) == 0
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def test_partial_evidence_returns_missing(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.constraints.base_constraint import (
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Constraint,
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ConstraintType,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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c1 = Constraint(
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id="c1", type=ConstraintType.PROPERTY, description="d", value="v"
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)
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c2 = Constraint(
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id="c2", type=ConstraintType.EVENT, description="d", value="v"
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)
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c.add_evidence(
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"c1", Evidence(claim="c", type=EvidenceType.INFERENCE, source="s")
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)
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unverified = c.get_unverified_constraints([c1, c2])
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assert len(unverified) == 1
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assert unverified[0].id == "c2"
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class TestCandidateGetWeakEvidence:
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"""Tests for Candidate.get_weak_evidence() method."""
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def test_empty_evidence_returns_empty(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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c = Candidate(name="Lake X")
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assert c.get_weak_evidence() == []
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def test_returns_low_confidence_ids(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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c.add_evidence(
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"c1",
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Evidence(
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claim="weak",
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type=EvidenceType.SPECULATION,
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source="s",
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confidence=0.1,
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),
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)
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c.add_evidence(
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"c2",
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Evidence(
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claim="strong",
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type=EvidenceType.DIRECT_STATEMENT,
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source="s",
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confidence=0.9,
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),
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)
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weak = c.get_weak_evidence(threshold=0.5)
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assert "c1" in weak
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assert "c2" not in weak
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def test_custom_threshold(self):
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from local_deep_research.advanced_search_system.candidates.base_candidate import (
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Candidate,
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)
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from local_deep_research.advanced_search_system.evidence.base_evidence import (
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Evidence,
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EvidenceType,
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)
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c = Candidate(name="Lake X")
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c.add_evidence(
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"c1",
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Evidence(
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claim="c",
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type=EvidenceType.NEWS_REPORT,
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source="s",
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confidence=0.75,
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),
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)
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# Default threshold is 0.5 - should not be weak
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assert "c1" not in c.get_weak_evidence(threshold=0.5)
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# Higher threshold - should be weak
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assert "c1" in c.get_weak_evidence(threshold=0.8)
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