apprentice/component_map.yaml at main · jmcentire/apprentice · GitHub

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core_models:
  Story:
    module: "apprentice.models.story"
    dependencies: ["pydantic", "typing", "datetime"]
    purpose: "Multi-step narrative representation with metadata"

  StoryStep:
    module: "apprentice.models.story_step"
    dependencies: ["pydantic", "TrainingExample"]
    purpose: "Individual step within story journey"

collection_layer:
  StoryCollector:
    module: "apprentice.collectors.story_collector"
    dependencies: ["Story", "StoryStep", "Chronicler"]
    purpose: "Aggregate and process story data from Chronicler"
    interfaces:
      - collect_story_events()
      - validate_story_consistency()
      - emit_training_examples()

evaluation_layer:
  JourneyEvaluator:
    module: "apprentice.evaluators.journey_evaluator"
    dependencies: ["Story", "metrics"]
    purpose: "Analyze journey patterns and efficiency"
    interfaces:
      - evaluate_journey_completion()
      - measure_step_efficiency()
      - detect_backtracking()
      - score_consistency()

orchestration:
  EnhancedPhaseManager:
    module: "apprentice.orchestration.phase_manager"
    dependencies: ["existing PhaseManager", "JourneyEvaluator"]
    purpose: "Per-journey-type phase transition tracking"
    extension_points:
      - journey_type_registration()
      - phase_transition_callbacks()
      - journey_specific_metrics()

configuration:
  StoryLearningConfig:
    module: "apprentice.config.story_learning"
    dependencies: ["pydantic", "base config"]
    purpose: "Story learning feature configuration"
    fields:
      - story_learning_enabled: bool = False
      - max_story_length: int = 50
      - story_retention_days: int = 30

integration_points:
  existing_atomic_router:
    modification: "none - preserved as-is"
    integration: "parallel story collection when enabled"

  training_orchestrator:
    modification: "extended to handle Story objects"
    backward_compatibility: "TrainingExample processing unchanged"