mnist-mlops-learning
# Fastapi + MLflow + streamlit Setup env. I hope I covered all. ```bash pip install -r requirements.txt ``` # Start app Go in the root dir and run these Streamlit ```bash streamlit run frontend/streamlit_main.py ``` FastAPI ``` uvicorn backend.main:app ``` MLflow UI ```bash mlflow ui --backend-store-uri sqlite:///db/bakckend.db ``` ## Docker - Mlflow: http://localhost:5000 - FastApi: http://localhost:8000/docs - Streamlit: http://localhost:8501/ ```bash docker-compose build docker-compose up ``` # Architecture  # UI   ## TODO - [x] Dockerize - [ ] Testing - [ ] Maybe add celery instead of that background task? (Needs extra configs though)