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- Introduced a roadmap-first approach for the planning AI, allowing for a structured progression graph that aligns with the overall project roadmap. - Added new functionality to strip off-topic steps from exercise paths, improving the relevance of generated exercise suggestions. - Implemented a detailed goal text generation for AI proposals, enhancing the context provided for new exercises. - Updated the ExerciseProgressionPathBuilder component to support new features, including roadmap previews and improved focus area handling. - Incremented application version to 0.8.205 and updated database schema version to 20260606086 to reflect these changes.
53 lines
2.0 KiB
Python
53 lines
2.0 KiB
Python
"""Tests Planungs-KI Phase F — Progressions-Roadmap Pipeline."""
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from planning_progression_roadmap import (
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PROMPT_SLUG_GOAL_ANALYSIS,
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PROMPT_SLUG_ROADMAP,
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PROMPT_SLUG_STAGE_SPEC,
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build_goal_analysis,
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consolidate_micro_to_major,
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develop_micro_objectives,
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progression_roadmap_to_api_dict,
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run_progression_roadmap_pipeline,
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)
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from planning_exercise_semantics import build_semantic_brief
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def test_run_progression_roadmap_pipeline_major_step_count():
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ctx = run_progression_roadmap_pipeline(
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"Von Erlernen bis zur Perfektion des Fußtritts Mae Geri",
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max_steps=5,
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)
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assert ctx.roadmap is not None
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assert len(ctx.roadmap.major_steps) == 5
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assert len(ctx.roadmap.micro_objectives) >= 6
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assert len(ctx.stage_specs) == 5
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assert ctx.goal_analysis is not None
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assert "Mae" in ctx.goal_analysis.primary_topic or "mae" in ctx.goal_analysis.primary_topic.lower()
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def test_consolidate_micro_to_major_reduces_count():
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brief = build_semantic_brief("Mae Geri")
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ga = build_goal_analysis("Mae Geri Perfektion", brief)
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micro = develop_micro_objectives(brief, goal_analysis=ga, min_count=8)
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majors, notes = consolidate_micro_to_major(micro, max_steps=5)
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assert len(majors) == 5
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if len(micro) > 5:
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assert notes
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assert all(m.learning_goal for m in majors)
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def test_major_steps_have_learning_goals():
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ctx = run_progression_roadmap_pipeline("Mae Geri Grundlagen", max_steps=3)
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for step in ctx.roadmap.major_steps:
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assert step.learning_goal.strip()
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assert step.consolidates
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def test_api_dict_exposes_prompt_slug_catalog():
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ctx = run_progression_roadmap_pipeline("Mae Geri", max_steps=3, include_llm_roadmap=False)
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api = progression_roadmap_to_api_dict(ctx)
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assert api["prompt_slug_catalog"]["goal_analysis"] == PROMPT_SLUG_GOAL_ANALYSIS
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assert api["prompt_slug_catalog"]["roadmap"] == PROMPT_SLUG_ROADMAP
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assert api["prompt_slug_catalog"]["stage_spec"] == PROMPT_SLUG_STAGE_SPEC
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assert api["prompt_slugs"] == []
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