Installation

This guide sets up a single-node environment for Agent Lightning v1.0. After completing it, you can run single-machine training jobs.

Before getting started, install uv and NVIDIA CUDA. We support CUDA 12.9 or 13.0.

Step 1: UV Sync

From the project root, run:

cd <this-repo>
uv sync

This installs the base Python environment into .venv under the project root.

Step 2: Install verl and FlashAttention

Agent Lightning uses verl as its training backend. The compatible versions of verl, vllm, and torch are tightly coupled, and installing flash-attn can also be error-prone. We recommend using scripts/setup_verl.sh to install the tested, pinned GPU stack and build flash-attn from source.

Pass the verl version and CUDA wheel variant explicitly. The script supports verl==0.7.1 or verl==0.8.0, and CUDA wheel variant cu129 or cu130. We recommend CUDA 13.0 with verl==0.8.0:

source .venv/bin/activate
bash scripts/setup_verl.sh 0.8.0 cu130

# or

bash scripts/setup_verl.sh 0.7.1 cu129

For verl==0.7.1, the script installs vllm==0.12.0. For verl==0.8.0, it installs vllm==0.20.2 first, then installs verl==0.8.0. Both paths build flash-attn==2.8.3 locally against the selected environment. Depending on the number of CPU cores available, the script can take 10-30 minutes to complete.

Step 3: W&B Login

By default, all tasks upload logs and trajectories to Weights & Biases. Log in to W&B before running a task:

uv run wandb login