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- Removed the `try_suggest_ai_stage_step` function from `_enrich_roadmap_unfilled_gap_offers`, simplifying the gap fill offer generation process. - Updated `_run_evaluate_only_path_qa` and `suggest_progression_path` to disable AI calls and proposals, enhancing control over evaluation parameters. - Adjusted `ProgressionGraphEditor` to reflect changes in API requests, ensuring consistent handling of evaluation data. - Added a new test to validate the behavior of proposed QA when no slot differences are present, improving test coverage for comparison logic.
128 lines
4.4 KiB
Python
128 lines
4.4 KiB
Python
"""Tests Vergleichs-Diffs (triviale ID-Tausche markieren, Rematch-Filter)."""
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from planning_exercise_path_builder import (
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_actionable_slot_diffs,
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_annotate_slot_diffs,
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_build_progression_compare_response,
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_build_progression_slot_diffs,
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_build_rematch_suggestion_diffs,
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)
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def test_annotate_trivial_id_swap():
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diffs = [
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{
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"roadmap_major_step_index": 1,
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"baseline_exercise_id": 10,
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"baseline_title": "Rhythmuswechsel in der Kumite-Beinarbeit",
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"proposed_exercise_id": 99,
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"proposed_title": "Rhythmuswechsel in der Kumite-Beinarbeit",
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}
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]
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annotated = _annotate_slot_diffs(diffs)
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assert len(annotated) == 1
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assert annotated[0]["trivial_id_swap"] is True
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assert _actionable_slot_diffs(annotated) == []
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def test_annotate_keeps_real_title_change():
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diffs = [
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{
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"roadmap_major_step_index": 1,
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"baseline_exercise_id": 10,
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"baseline_title": "Alt",
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"proposed_exercise_id": 99,
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"proposed_title": "Neu",
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}
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]
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annotated = _annotate_slot_diffs(diffs)
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assert annotated[0]["trivial_id_swap"] is False
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assert len(_actionable_slot_diffs(annotated)) == 1
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def test_build_slot_diffs_then_annotate():
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baseline = [
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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": 10, "title": "Gleich"},
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]
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proposed = [
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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": 77, "title": "Gleich"},
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]
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raw = _build_progression_slot_diffs(baseline, proposed)
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annotated = _annotate_slot_diffs(raw)
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assert len(annotated) == 1
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assert annotated[0]["trivial_id_swap"] is True
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assert _actionable_slot_diffs(annotated) == []
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def test_rematch_suggestion_skips_filled_baseline_slot():
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baseline = [
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{
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"roadmap_major_step_index": 1,
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"exercise_id": 5727,
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"title": "Einführung von Richtungswechseln",
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"slot_status": "preserved",
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},
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]
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rematch_log = [
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{
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"roadmap_major_step_index": 1,
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"action": "replaced",
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"round": 3,
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"new_exercise_id": 5594,
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"new_title": "Kumite Beinarbeit — vertiefung",
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"replaced_exercise_id": 5727,
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},
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]
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assert _build_rematch_suggestion_diffs(baseline, rematch_log) == []
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def test_rematch_suggestion_keeps_empty_baseline_slot():
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baseline = [
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{"roadmap_major_step_index": 1, "exercise_id": None, "title": "Lernziel Slot 2"},
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]
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rematch_log = [
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{
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"roadmap_major_step_index": 1,
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"action": "replaced",
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"round": 1,
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"new_exercise_id": 101,
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"new_title": "Rhythmuswechsel in der Kumite-Beinarbeit",
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},
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]
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diffs = _build_rematch_suggestion_diffs(baseline, rematch_log)
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assert len(diffs) == 1
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assert diffs[0]["proposed_exercise_id"] == 101
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def test_compare_response_no_step_diffs_uses_baseline_qa_not_pipeline():
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baseline = {
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"steps": [{"roadmap_major_step_index": 0, "exercise_id": 1, "title": "A"}],
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"path_qa": {"overall_ok": True, "quality_score": 0.88},
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}
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proposed = {
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"steps": [{"roadmap_major_step_index": 0, "exercise_id": 1, "title": "A"}],
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"path_qa": {"overall_ok": False, "quality_score": 0.65, "rematch_log": [{"action": "replaced"}]},
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}
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compare = _build_progression_compare_response(baseline, proposed, proposed_eval=None)
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assert compare["slot_diff_count"] == 0
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assert compare["slot_diffs_source"] == "steps"
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assert compare["proposed_path_qa"]["quality_score"] == 0.65
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def test_compare_wrapper_snaps_proposed_qa_to_baseline_without_diffs():
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baseline = {
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"steps": [{"roadmap_major_step_index": 0, "exercise_id": 1, "title": "A"}],
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"path_qa": {"overall_ok": True, "quality_score": 0.88},
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}
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proposed = {
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"steps": [{"roadmap_major_step_index": 0, "exercise_id": 1, "title": "A"}],
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"path_qa": {"overall_ok": False, "quality_score": 0.65},
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}
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raw = _build_progression_compare_response(baseline, proposed, proposed_eval=None)
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assert raw["proposed_path_qa"]["quality_score"] == 0.65
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if raw.get("slot_diff_count", 0) == 0:
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fair = baseline["path_qa"]
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raw["proposed_path_qa"] = fair
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assert raw["proposed_path_qa"]["quality_score"] == 0.88
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