fix: pre-download embedding model during Docker build to avoid DNS failures on HF Spaces
FocusFlow Assistant
3c23e28
- Pre-cache sentence-transformers/all-MiniLM-L6-v2 model in Docker image
- Set TRANSFORMERS_OFFLINE=1 and HF_HUB_OFFLINE=1 to prevent runtime downloads
- Add DNS warmup delay in startup script
- Increase health check timeout to 90 seconds
- Add .dockerignore to exclude venv/ and local data dirs
- Update embeddings config with explicit CPU device and normalization
Add OCR fallback for scanned/image PDFs using pytesseract + pdf2image
FocusFlow Assistant
2c32e38
fix: Add robust startup with health checks and error logging
FocusFlow Assistant
76a5867
- Health check loop waits up to 60s for backend
- Logs backend errors if startup fails
- Uses exec for proper signal handling
- Creates logs/ directory for debugging
- Added test_backend.sh for local debugging
Add Supabase persistent storage support
FocusFlow Assistant
479eeb5
- Created supabase_storage.py adapter with comprehensive error handling
- Modified student_data.py to conditionally use Supabase or local JSON
- Added USE_SUPABASE env var to Dockerfile
- Maintains backward compatibility with local deployments
- Graceful fallback if Supabase unavailable
Restore Dockerfile and README for HF Spaces deployment
FocusFlow Assistant
23d2ce2
Add Hugging Face Spaces deployment configuration
FocusFlow Assistant
d5f1e20
- Dockerfile: Multi-stage Docker build for HF Spaces
- README.md: Space metadata and feature description
- DEPLOYMENT.md: Complete guide for local and cloud deployment
- Updated .streamlit/config.toml for production
Ready to deploy as public demo on Hugging Face Spaces
