- Add CoachingDecision enum (ACCEPT, REJECT, CORRECT, EXECUTE_MANUAL, SKIP)
- Add CoachingResponse dataclass for user decisions
- Add WAITING_COACHING state to ExecutionState
- Implement _request_coaching_decision() with callback or polling support
- Implement submit_coaching_decision() for external API/UI submission
- Implement _apply_coaching_correction() for applying user corrections
- Implement _record_coaching_feedback() integrating with:
- TrainingDataCollector for session recording
- FeedbackProcessor for statistics
- CorrectionPackIntegration for automatic correction capture
- Add get_coaching_stats() for session statistics
- Add 17 unit tests for COACHING functionality
COACHING mode now:
1. Suggests actions to user
2. Waits for user decision (accept/reject/correct/manual/skip)
3. Applies corrections if provided
4. Records all feedback for learning
5. Propagates corrections to Correction Packs automatically
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Importer les vraies classes Action, TargetSpec, WorkflowEdge, ActionType
- Convertir le type d'action en ActionType Enum au lieu de string
- Créer un ScreenState complet avec tous les niveaux (raw, perception, context)
- Corriger _serialize_state dans error_handler.py pour accès compatibles
- Ajouter import os pour manipulation des fichiers
- Sauvegarder les screenshots dans data/temp/
L'exécution réelle fonctionne maintenant - les erreurs "Target not found"
sont attendues car il faut une vraie interface utilisateur à l'écran.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
