Contributing to vLLM¶

Thank you for your interest in contributing to vLLM! Our community is open to everyone and welcomes all kinds of contributions, no matter how small or large. There are several ways you can contribute to the project:

• Identify and report any issues or bugs.
• Request or add support for a new model.
• Suggest or implement new features.
• Improve documentation or contribute a how-to guide.

We also believe in the power of community support; thus, answering queries, offering PR reviews, and assisting others are also highly regarded and beneficial contributions.

Finally, one of the most impactful ways to support us is by raising awareness about vLLM. Talk about it in your blog posts and highlight how it's driving your incredible projects. Express your support on social media if you're using vLLM, or simply offer your appreciation by starring our repository!

Job Board¶

Unsure on where to start? Check out the following links for tasks to work on:

• Good first issues
  • Selected onboarding tasks
• New model requests
  • Models with multi-modal capabilities

License¶

See LICENSE.

Developing¶

The first step of contributing to vLLM is to clone the GitHub repository:

git clone https://github.com/vllm-project/vllm.git
cd vllm

Then, configure your Python virtual environment.

It's recommended to use uv, a very fast Python environment manager, to create and manage Python environments. Please follow the documentation to install uv. After installing uv, you can create a new Python environment using the following commands:

uv venv --python 3.12 --seed --managed-python
source .venv/bin/activate

If you are only developing vLLM's Python code, install vLLM using:

VLLM_USE_PRECOMPILED=1 uv pip install -e .

To rebuild only the Rust frontend binary:

./build_rust.sh          # release build
./build_rust.sh --debug  # faster build for development

If you are developing vLLM's Python and CUDA/C++ code, install Pytorch first: