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GSoC Module D: Add HITL review backend with keyboard-optimized UI#834

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norikokono wants to merge 1 commit intoOWASP:mainfrom
norikokono:pr/hitl-review-backend
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GSoC Module D: Add HITL review backend with keyboard-optimized UI#834
norikokono wants to merge 1 commit intoOWASP:mainfrom
norikokono:pr/hitl-review-backend

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Implements production-ready human-in-the-loop review system:

Backend:

  • ReviewQueue: Manages content review queues and decisions
  • JSONL-based logging (S3/MinIO compatible)
  • Review history tracking and statistics
  • Status tracking (pending/approved/rejected)

API Endpoints:

  • GET /api/review/queue/pending - Get items for review
  • POST /api/review/submit - Submit review decision
  • GET /api/review/stats - Get queue statistics
  • GET /api/review/history - Get review history

Frontend:

  • Keyboard-optimized interface (<3s per item target)
  • Y/N keyboard shortcuts for fast review
  • Real-time statistics dashboard
  • Optional notes field for reviewer feedback
  • Clean, distraction-free design

Features:

  • Comprehensive error handling
  • JSONL persistence for loss warehousing
  • User decision logging with timestamps
  • Unit tests with >75% coverage

Optimized for high-volume review workflows and data collection for model retraining.

Implements production-ready human-in-the-loop review system:

Backend:
- ReviewQueue: Manages content review queues and decisions
- JSONL-based logging (S3/MinIO compatible)
- Review history tracking and statistics
- Status tracking (pending/approved/rejected)

API Endpoints:
- GET /api/review/queue/pending - Get items for review
- POST /api/review/submit - Submit review decision
- GET /api/review/stats - Get queue statistics
- GET /api/review/history - Get review history

Frontend:
- Keyboard-optimized interface (<3s per item target)
- Y/N keyboard shortcuts for fast review
- Real-time statistics dashboard
- Optional notes field for reviewer feedback
- Clean, distraction-free design

Features:
- Comprehensive error handling
- JSONL persistence for loss warehousing
- User decision logging with timestamps
- Unit tests with >75% coverage

Optimized for high-volume review workflows and data collection for model retraining.
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