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Add HF eval-results benchmark registry and API endpoint
- Add canonical EEG_BENCHMARKS registry (8 datasets) in config/benchmarks.py - Add GET /api/benchmarks endpoint for benchmark metadata - Refactor leaderboard transform_data to loop over registry instead of hardcoding - Extract _build_entry_id helper for consistent unique ID generation - Add push_eval_yaml.py script to register benchmarks on HF Hub - Add pyyaml dependency6f5cc9b
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Migrate from Gradio to React + FastAPI architecture
Replace the old Gradio-based leaderboard with a React frontend and FastAPI backend, adapted from the Open LLM Leaderboard codebase for EEG model evaluation. Backend: FastAPI app with leaderboard, model submission, and voting endpoints. Frontend: React + MUI with leaderboard table, filters, model submission, voting, about page, and citations. Infrastructure: Dockerfile, docker-compose, and env configuration for HF Spaces.ee472e7