Installation

Install the Python package:

pip install "rlmesh[gymnasium,numpy]"

RLMesh supports Python 3.10 and newer. Start with Gymnasium for environments and the NumPy backend for examples and notebooks, then follow the Quickstart.

Optional Extras

Install only the extras you need:

pip install rlmesh
pip install "rlmesh[numpy]"
pip install "rlmesh[gymnasium]"
pip install "rlmesh[torch]"
pip install "rlmesh[hf]"

Pick gymnasium when serving a Gymnasium environment, or gym for a legacy classic-Gym stack. torch decodes client-side values as Torch tensors; numpy decodes them as arrays. hf adds host-side, container-less resolution of hf:// model weights and EnvHub sources; in a sandbox the container fetches them for you. See Framework Backends for how the backend extras change value decoding.

Repository Examples

Inside this repository, use the pinned development environment:

mise install
mise run setup

Then run examples with uv run. Sandbox examples need Docker access. Optional example folders keep their own lockfiles and environments, so heavier dependencies stay out of the root development environment.