cympfh / mnist-mlops-learning

In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits

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Fastapi + MLflow + streamlit

Setup env. I hope I covered all.

pip install -r requirements.txt

Start app

Go in the root dir and run these

Streamlit

streamlit run frontend/streamlit_main.py

FastAPI

uvicorn backend.main:app

MLflow UI

mlflow ui --backend-store-uri sqlite:///db/backend.db

Docker

docker-compose build
docker-compose up

Architecture

image

UI

image image

TODO

  • Dockerize
  • Testing
  • Maybe add celery instead of that background task? (Needs extra configs though)
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In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits


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