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🛠️ Contributing to FastVideo

Thank you for your interest in contributing to FastVideo. We want the process to be smooth and beginner‑friendly, whether you are adding a new pipeline, improving performance, or fixing a bug.

Quick prerequisites

  • OS: Linux is the primary development target (WSL can work).
  • GPU: NVIDIA GPU recommended for inference and training workflows.
  • CUDA: Use a recent CUDA 12.x toolchain (see the installation guide for the current recommendation).

For a full install checklist, see docs/getting_started/installation/gpu.md.

Local development (UV + editable install)

If you previously used Conda for local setup, switch to uv for a faster and more stable development environment.

Install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh
# or
wget -qO- https://astral.sh/uv/install.sh | sh

Create and activate a uv environment (recommended):

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

Conda alternative (supported):

conda create -n fastvideo python=3.12 -y
conda activate fastvideo

Clone the repo:

git clone https://github.com/hao-ai-lab/FastVideo.git && cd FastVideo

Install FastVideo in editable mode and set up hooks:

uv pip install -e .[dev]

# Optional: FlashAttention (builds native kernels)
uv pip install flash-attn --no-build-isolation -v

# Linting, formatting, static typing
pre-commit install --hook-type pre-commit --hook-type commit-msg
pre-commit run --all-files

# Unit tests
pytest tests/

If you are on a Hopper GPU, installing FlashAttention 3 can improve performance (see docs/inference/optimizations.md).

Docker development (optional)

If you prefer a containerized environment, use the dev image documented in docs/contributing/developer_env/docker.md.

Testing

See the Testing Guide for how to add and run tests in FastVideo.

Attention backend development

If you are adding a new attention kernel or backend, follow Attention Backend Development.

Contributing with coding agents

For a step‑by‑step workflow on adding pipelines or components with coding agents, see docs/contributing/coding_agents.md.