#reinforcement-learning

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI.

SGLang is a high-performance serving framework for large language models and multimodal models.

A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

Optax is a gradient processing and optimization library for JAX.

Evaluate and improve models and agents using environments

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools, with 10x faster training through evolutionary hyperparameter optimization.

Our library for RL environments + evals

Isaac Lab API, powered by MuJoCo-Warp, for RL and robotics research

A simple framework that allows researchers and hobbyists to develop AI agents for Atari 2600 games

Agentic QE Fleet is an open-source AI-powered QA/QE platform designed for use with Coding Agents (works best with Claude Code) featuring specialized agents and skills to support testing activities for a product at any stage of the SDLC. Free to use, fork, build, and contribute. Based on the Agentic QE Framework created by Dragan Spiridonov.

Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation.