- 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>
- Add CorrectionPackIntegration class to bridge learning components
- Modify TrainingDataCollector to auto-propagate corrections to packs
- Modify FeedbackProcessor to capture corrections on INCORRECT/PARTIAL feedback
- Add convenience functions: get_correction_pack_integration(), capture_coaching_correction()
- Add 19 integration tests (all passing)
Corrections made during COACHING mode are now automatically captured
into a dedicated "auto_captured_corrections" pack for cross-workflow reuse.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implement a complete system for capitalizing user corrections across multiple
workflows and sessions. This enables automatic application of learned fixes
when similar failures occur in different contexts.
New components:
- core/corrections/models.py: CorrectionKey, Correction, CorrectionPack models
- core/corrections/correction_repository.py: JSON storage with atomic writes
- core/corrections/aggregator.py: Aggregation by hash and quality filtering
- core/corrections/correction_pack_service.py: CRUD, export/import, versioning
- backend/api/correction_packs.py: REST API with 15 endpoints
Features:
- MD5-based key hashing for correction deduplication
- Export/import in JSON and YAML formats
- Version history with rollback support
- Cross-workflow pattern detection
- Integration with SelfHealingEngine for automatic application
- 29 unit tests (all passing)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>