54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
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"""Schachstellen-Erkennung für unified Slot-Review."""
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from planning_exercise_path_builder import (
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_problematic_slots_from_path_qa,
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_slot_suggestion_accepted,
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)
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from planning_progression_roadmap import StageSpecArtifact
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def _spec(midx: int) -> StageSpecArtifact:
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return StageSpecArtifact(
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major_step_index=midx,
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learning_goal=f"Lernziel Slot {midx + 1}",
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load_profile=[],
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exercise_type="",
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success_criteria=[],
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anti_patterns=[],
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)
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def test_problematic_slots_from_optimization_hints():
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qa = {
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"optimization_hints": [
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{
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"action": "rematch_slot",
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"step_index": 1,
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"issue": "stage_mismatch",
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"reason": "Übung passt nicht zur Stufe",
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}
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],
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"off_topic_steps": [],
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}
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steps = [
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{"roadmap_major_step_index": 0, "exercise_id": 1, "title": "A"},
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{"roadmap_major_step_index": 1, "exercise_id": 2, "title": "B"},
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]
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specs = [_spec(0), _spec(1)]
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problems = _problematic_slots_from_path_qa(qa, steps, specs)
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assert 1 in problems
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assert any("Stufe" in r or "passt" in r for r in problems[1])
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def test_slot_suggestion_accepted_for_problem_slot():
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diff = {"baseline_exercise_id": 10, "proposed_exercise_id": 99}
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assert _slot_suggestion_accepted(
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baseline_qa={"optimization_hints": [{"action": "rematch_slot", "roadmap_major_step_index": 1}]},
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projected_qa={"optimization_hints": []},
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baseline_score=0.7,
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projected_score=0.7,
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diff=diff,
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off_topic=False,
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major_idx=1,
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slot_problem=True,
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)
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