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A project with multi app deployment for ML with docker. A frontend with streamlit and a backend with FastAPI.

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AbhishekRS4/ML_multi_app_deployment

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ML multi app deployment

Info

  • A machine learning project deployment scenario with multiple applications / docker containers
  • The main code for training the model can be found in another repo
  • The project involves a streamlit application for the frontend and a FastAPI application for the backend / ML service

Backend

  • Run the following command to build the container for backend
cd backend/
docker build -t ml_water_potability_backend -f backend.dockerfile .

Frontend

  • Run the following command to build the container for frontend
cd frontend/
docker build -t ml_water_potability_frontend -f frontend.dockerfile .

Deployment with docker-compose (locally)

  • Run the following command (in the same directory with the docker-compose.yaml file) to deploy and run both the containers
docker-compose up

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A project with multi app deployment for ML with docker. A frontend with streamlit and a backend with FastAPI.

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