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- Introduced a roadmap-first approach for retrieval, allowing for structured exercise suggestions based on stage specifications and major steps. - Added functionality to generate gap-fill offers for unfilled roadmap stages, improving the relevance of exercise recommendations. - Updated the `ExerciseProgressionPathBuilder` to support the new roadmap-first feature, enhancing user experience with clearer exercise paths. - Incremented application version to 0.8.206 and updated the database schema version to reflect these changes.
45 lines
1.6 KiB
Python
45 lines
1.6 KiB
Python
"""Tests Planungs-KI Phase C3/E/F — Pfad-Vorschläge."""
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from planning_exercise_path_builder import (
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_annotate_roadmap_step,
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_hit_to_path_step,
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_pick_best_path_hit,
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)
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from planning_progression_roadmap import MajorStep, StageSpecArtifact
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def test_pick_next_path_hit_skips_used():
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hits = [{"id": 1, "title": "A", "semantic_score": 0.2}, {"id": 2, "title": "B", "semantic_score": 0.2}, {"id": 3, "title": "C", "semantic_score": 0.2}]
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assert _pick_best_path_hit(hits, {1})["id"] == 2
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assert _pick_best_path_hit(hits, {1, 2, 3}) is None
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def test_hit_to_path_step_maps_variant():
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step = _hit_to_path_step(
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{
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"id": 10,
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"title": "Test",
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"score": 0.8,
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"reasons": ["Graph"],
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"suggested_variant_id": 7,
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"suggested_variant_name": "Leicht",
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"variants": [{"id": 7, "variant_name": "Leicht"}],
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}
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)
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assert step["exercise_id"] == 10
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assert step["variant_id"] == 7
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assert step["suggested_variant_name"] == "Leicht"
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def test_annotate_roadmap_step_adds_metadata():
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spec = StageSpecArtifact(major_step_index=1, learning_goal="Grundstellung Mae Geri")
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major = MajorStep(index=1, phase="grundlage", learning_goal=spec.learning_goal, consolidates=["m1"])
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step = _annotate_roadmap_step(
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{"exercise_id": 5, "title": "Test", "reasons": ["Bibliothek"]},
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stage_spec=spec,
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major_step=major,
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)
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assert step["roadmap_major_step_index"] == 1
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assert step["roadmap_phase"] == "grundlage"
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assert step["roadmap_match_source"] == "stage_spec"
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assert any("Roadmap:" in r for r in step["reasons"])
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