feat(ml): Add Docker support for Render deployment

[Harsh-vardhan09]

Summary

Containerize the ML FastAPI service to simplify deployment and make it compatible with container-based platforms such as Render.

Problem

The ML service currently requires manual setup:

• Create a Python virtual environment
• Install dependencies manually
• Ensure trained model artifacts are present
• Start the FastAPI server with Uvicorn

This increases onboarding time and makes deployment more error-prone.

Proposed Solution

Dockerize the ML service by adding the necessary Docker configuration.

Tasks

• Add ML/Dockerfile
• Add ML/.dockerignore
• Install dependencies inside the Docker image
• Copy application source and model artifacts into the container
• Expose the application port
• Start FastAPI using Uvicorn
• Support Render's dynamic PORT environment variable
• Document Docker build and deployment steps in SETUP.md and README.md

Example

Build the image:

docker build -t athlead-ml ./ML

[Harsh-vardhan09]

/claim

[github-actions]

🎉 Assigned! Welcome to the project, @Harsh-vardhan09.

⏳ Reminder: You have 2 days to submit a Pull Request. After 2 days of inactivity, you will be automatically unassigned to give others a chance.

💡 Please read CONTRIBUTION.md and star the repo.

Happy coding! 🚀

[Harsh-vardhan09]

Issue closed by Admin by Raising a PR