helixml / helix

Getting Started with Contributing to HelixML/Helix

HelixML is an open-source machine learning platform designed for building, deploying, and managing machine learning models. If you’re already familiar with the project and looking to contribute, this guide will walk you through the process.

Prerequisites

Before diving into contributing, ensure you have the following prerequisites installed:

  1. Docker: HelixML uses Docker for building, testing, and deploying. Install Docker from the official website.
  2. Git: HelixML is hosted on GitHub, so you’ll need Git for cloning the repository and managing your contributions. Install Git from the official website.

Forking the Repository

To contribute to HelixML, you’ll first need to fork the repository on GitHub. Follow these steps:

  1. Go to the HelixML GitHub page.
  2. Click the “Fork” button in the upper right corner.
  3. Select your GitHub account or organization to fork the repository to.

Cloning the Repository

Once you’ve forked the repository, clone it to your local machine:

git clone <your-forked-repository-url>

Building HelixML

To build HelixML, navigate to the project directory and run the following command:

make

This command will build the HelixML Docker image.

Generating HelixML Assets

To generate HelixML assets, run:

make assets

Running HelixML

To start the HelixML services, run:

docker-compose up -d

Testing HelixML

For testing instructions, consult the HelixML documentation.

Deploying HelixML

To deploy HelixML, you’ll need to push the HelixML Docker image to a registry. First, tag the image:

docker tag helixml/helix:<tag> <your-registry-username>/helixml/helix:<tag>

Replace <tag> with the desired tag and <your-registry-username> with your registry username. Then, push the image:

docker push <your-registry-username>/helixml/helix:<tag>

Additional HelixML Information

For additional deployment information, consult the HelixML documentation for private deployment.

To update Keycloak realm settings, use the ./update-realm-settings.sh script.

For runner attachment instructions, consult the HelixML documentation for controlplane.

Review the HelixML license terms before contributing.

Contributing Guidelines

When contributing to HelixML, please adhere to the following guidelines:

  1. Submit clear and concise pull requests: Clearly explain the changes you’ve made and why they’re beneficial.
  2. Write clean and readable code: Make sure your code is easy to understand and maintain.
  3. Test your changes: Ensure your changes don’t introduce new bugs or issues.
  4. Follow the project’s coding style: Adhere to the project’s existing coding style and conventions.

Reporting Issues

If you encounter any issues while contributing to HelixML, please report them in the Issues tab on GitHub.

Stay Informed

To stay informed about HelixML updates and developments, follow the project on GitHub and subscribe to the HelixML mailing list.

Conclusion

Contributing to HelixML is an excellent opportunity to learn, grow, and give back to the machine learning community. By following the guidelines outlined in this guide, you’ll be well on your way to making meaningful contributions to this exciting project.

Happy contributing!