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Contributing

The spirit of this project is to produce a framework that solves distributed serving of LLMs in a non-specific way to the inference engine running the weights. All features should be implemented with this in mind.

Getting Started

  1. Fork the repository
  2. Clone your fork: git clone https://github.com/your-username/inference-stack.git
  3. Install Helm and helm-unittest

Making Changes

  1. Create a feature branch: git checkout -b feature-name

  2. Make your changes to templates, values, or examples

  3. Test your changes:

    helm lint .
helm unittest .
helm template test-release . --values examples/single-vllm.yaml

  4. Update tests if needed

  5. Commit with conventional commits: feat:, fix:, docs:, etc.

Submitting

  1. Push your branch: git push origin feature-name
  2. Create a Pull Request with:
    • Clear description of changes
    • Test results showing lint and unittest pass
    • Example usage if adding new features

Project Structure

  • templates/ - Helm templates
  • examples/ - Example values files
  • tests/ - Unit tests
  • values.yaml - Default configuration

Need Help?

Open an issue for questions or feature requests. Reach out at: hello@doubleword.ai!