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SkyRL

SkyRL is a full-stack reinforcement learning library for training LLMs, designed for modularity and extensibility.

Critical Rules

  • Always use uv run --isolated to run commands. Never use bare python, pip, or pip install.
  • Log output to files: <cmd> > /tmp/results_1.log 2>&1 for persistence.
  • Backend extras (fsdp, megatron, jax) conflict with each other -- never combine them.
  • Always read the relevant documentation files in .claude/docs before troubleshooting or working on any changes. Follow the routing rules below.

Test Commands

# CPU tests
uv run --extra dev --extra jax pytest tests/tx/ tests/tinker/ tests/utils/
uv run --extra dev pytest tests/train/ tests/backends/skyrl_train/ --ignore=tests/backends/skyrl_train/gpu/

# GPU tests (requires Ray cluster with GPUs)
uv run --isolated --extra dev --extra fsdp pytest tests/backends/skyrl_train/gpu/gpu_ci/test_engine_generation.py
uv run --isolated --extra dev --extra megatron pytest tests/backends/skyrl_train/gpu/gpu_ci/test_megatron_worker.py

# Lint / format
bash format.sh

Training Quick Start

uv run --isolated --extra megatron -m skyrl.train.entrypoints.main_base \
  trainer.strategy=megatron trainer.policy.model.path=<model> environment.env_class=gsm8k ...

Routing Rules

When working on these areas, read the corresponding doc first:

Area Read first
Package management, uv, formatting .claude/docs/development.md
Overall guide for modifying or working with SkyRL .claude/docs/contributing.md
Tests, fixtures, CI quirks .claude/docs/testing.md
Project layout, Ray actors, config .claude/docs/architecture.md
Training entrypoints, configs .claude/docs/training.md
Inference engines, vLLM, PD disagg .claude/docs/inference.md
GitHub Actions, Anyscale CI .claude/docs/ci.md
Tinker API server .claude/docs/tinker.md
Megatron backend .claude/docs/backends/megatron.md
FSDP backend .claude/docs/backends/fsdp.md
JAX/TPU backend .claude/docs/backends/jax.md
Weight sync .claude/docs/weight_sync.md

Troubleshooting

For troubleshooting training runs with SkyRL:

  1. Go through the troubleshooting section in the docs for known errors: docs/content/docs/troubleshooting/troubleshooting.mdx
  2. Go through the contributing guide for overall guidelines: .claude/docs/contributing.md