93 lines
3.1 KiB
Python
93 lines
3.1 KiB
Python
from __future__ import annotations
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import math
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import unittest
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from claridoc.models import (
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REVIEW_DIMENSIONS,
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Brief,
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DocumentType,
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ModelReview,
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PipelineConfig,
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QualityGate,
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SourcePack,
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ValidationError,
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)
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from claridoc.templates import mock_pipeline_config
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from tests.helpers import brief_dict, source_dict
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class ModelTests(unittest.TestCase):
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def test_valid_brief_round_trip(self) -> None:
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brief = Brief.from_dict(brief_dict())
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self.assertEqual(brief.document_type, DocumentType.TECHNICAL_BLOG)
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self.assertEqual(Brief.from_dict(brief.to_dict()).title, brief.title)
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def test_invalid_document_type_is_rejected(self) -> None:
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data = brief_dict()
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data["document_type"] = "essay"
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with self.assertRaises(ValidationError):
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Brief.from_dict(data)
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def test_duplicate_source_ids_are_rejected(self) -> None:
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data = source_dict()
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data["sources"].append(dict(data["sources"][0]))
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with self.assertRaises(ValidationError):
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SourcePack.from_dict(data)
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def test_target_words_range_is_enforced(self) -> None:
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data = brief_dict()
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data["constraints"]["target_words"] = 50
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with self.assertRaises(ValidationError):
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Brief.from_dict(data)
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def test_quality_gate_rejects_non_finite_weights(self) -> None:
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with self.assertRaises(ValidationError):
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QualityGate.from_dict({"deterministic_weight": math.nan, "model_weight": math.nan})
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def test_pipeline_requires_explicit_reviewers(self) -> None:
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data = mock_pipeline_config()
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data["reviewers"] = []
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with self.assertRaises(ValidationError):
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PipelineConfig.from_dict(data)
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def test_pipeline_rejects_duplicate_reviewer_roles(self) -> None:
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data = mock_pipeline_config()
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data["reviewers"].append({"role": "logic", "provider": "mock"})
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with self.assertRaises(ValidationError):
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PipelineConfig.from_dict(data)
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def test_review_requires_every_scoring_dimension(self) -> None:
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review = self._valid_review()
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del review["dimension_scores"][REVIEW_DIMENSIONS[0]]
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with self.assertRaises(ValidationError):
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ModelReview.from_dict(review, role="logic", provider="mock")
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def test_review_rejects_unknown_issue_severity(self) -> None:
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review = self._valid_review()
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review["issues"] = [
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{
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"section": "Mechanism",
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"problem": "A causal step is missing.",
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"why_it_matters": "The conclusion cannot be reproduced.",
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"fix": "Add the missing state transition.",
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"severity": "critical",
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}
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]
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with self.assertRaises(ValidationError):
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ModelReview.from_dict(review, role="logic", provider="mock")
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@staticmethod
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def _valid_review() -> dict:
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return {
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"score": 90,
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"dimension_scores": {name: 90 for name in REVIEW_DIMENSIONS},
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"issues": [],
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"strengths": ["The structure is explicit."],
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"questions": [],
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}
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if __name__ == "__main__":
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unittest.main()
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