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- Added new functions for computing assignment quality scores and counting step assignment statistics, improving the evaluation of steps in path quality assessments. - Updated existing methods to incorporate the new scoring logic, enhancing the robustness of path evaluations. - Introduced UI components in the frontend to display detailed quality assessment results, including handling of split dimensions in path evaluations. - Enhanced tests to cover new functionalities and ensure accuracy in quality scoring and slot management processes.
63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
"""Getrennte Roadmap- vs. Besetzungs-QS."""
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from planning_exercise_path_qa import (
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build_assignment_qa_snapshot,
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build_path_qa_summary,
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compute_assignment_quality_score,
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merge_path_quality_scores,
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)
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def _empty_steps(n: int):
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return [{"roadmap_major_step_index": i, "exercise_id": None} for i in range(n)]
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def test_assignment_quality_all_empty_slots_is_low():
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steps = _empty_steps(5)
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score = compute_assignment_quality_score(steps=steps, off_topic_steps=[], gaps=[])
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assert score <= 0.15
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def test_assignment_quality_all_filled_is_high():
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steps = [{"roadmap_major_step_index": i, "exercise_id": i + 1} for i in range(5)]
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score = compute_assignment_quality_score(steps=steps, off_topic_steps=[], gaps=[])
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assert score >= 0.9
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def test_build_path_qa_summary_caps_llm_score_when_slots_empty():
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steps = _empty_steps(4)
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summary = build_path_qa_summary(
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gaps=[],
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bridge_inserts=[],
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ai_proposals=[],
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off_topic_steps=[],
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stripped_off_topic=[],
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llm_qa={
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"overall_ok": True,
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"quality_score": 0.88,
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"topic_coverage": "Roadmap deckt Ziel gut ab",
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"issues": [],
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"recommendations": ["Feinschliff Stufe 3"],
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},
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llm_applied=True,
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steps=steps,
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)
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assert summary["roadmap_qa"]["quality_score"] == 0.88
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assert summary["assignment_qa"]["empty_slot_count"] == 4
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assert summary["assignment_qa"]["quality_score"] <= 0.15
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assert summary["quality_score"] <= 0.15
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assert summary["overall_ok"] is False
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def test_merge_path_quality_uses_minimum():
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assert merge_path_quality_scores(
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{"quality_score": 0.88},
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{"quality_score": 0.12},
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) == 0.12
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def test_assignment_snapshot_reports_empty_slots():
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snap = build_assignment_qa_snapshot(steps=_empty_steps(3), off_topic_steps=[], gaps=[])
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assert snap["empty_slot_count"] == 3
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assert snap["overall_ok"] is False
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assert any("ohne Übung" in issue for issue in snap["issues"])
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