Nouvelle méthode match_current_state_from_state(screen_state, workflow_id)
qui utilise directement le ScreenState enrichi (window_title, detected_text,
ui_elements) fourni par ExecutionLoop au lieu de reconstruire un stub
ScreenState("Unknown", ui_elements=[], ...).
Préfère HierarchicalMatcher si workflow chargeable, fallback FAISS sinon.
L'ancienne API match_current_state(screenshot_path, workflow_id) est
convertie en wrapper : appelle ScreenAnalyzer.analyze() puis délègue.
Rétrocompat préservée.
ExecutionLoop._execute_step utilise la nouvelle méthode -> plus de double
analyze() dans le chemin d'exécution (économie latence).
Premier vrai matching context-aware. 11 nouveaux tests + 2 tests
integration loop. 172 tests non-régression verts.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- 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>
