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Contributing

We welcome contributions to vllm-mlx!

Getting Started

# Clone the repository
git clone https://github.com/waybarrios/vllm-mlx.git
cd vllm-mlx

# Install with dev dependencies
pip install -e ".[dev]"

Development Workflow

Running Tests

# Run all tests
pytest tests/

# Run specific test file
pytest tests/test_paged_cache.py -v

# Run with coverage
pytest --cov=vllm_mlx tests/

Code Style

# Format code
black vllm_mlx/
isort vllm_mlx/

# Type checking
mypy vllm_mlx/

Running Benchmarks

# LLM benchmark
vllm-mlx-bench --model mlx-community/Qwen3-0.6B-8bit

# Image benchmark
vllm-mlx-bench --model mlx-community/Qwen3-VL-8B-Instruct-4bit

# Video benchmark
vllm-mlx-bench --model mlx-community/Qwen3-VL-8B-Instruct-4bit --video

Areas for Contribution

  • Bug fixes - Fix issues and improve stability
  • Performance optimizations - Improve inference speed
  • New features - Add functionality
  • Documentation - Improve docs and examples
  • Benchmarks - Test on different Apple Silicon chips
  • Model support - Test and add new models

Pull Request Process

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Run tests to ensure they pass
  5. Submit a pull request

Code Structure

See Architecture for details on the codebase structure.

Testing on Different Hardware

If you have access to different Apple Silicon chips (M1, M2, M3, M4), benchmark results are valuable:

vllm-mlx-bench --model mlx-community/Qwen3-0.6B-8bit --output results_m4.json

Questions?

Open an issue at GitHub Issues.