Kiln-AI/Seahaven

Creating realistic RL environments requires collaboration between researchers, engineers, and domain experts across many dimensions: artifacts, environments tools, dynamism of the environment, reproducibility, and more. There is no open source framework for building these environments effectively. Until now.

Research infra for creating RL environments, post-training, and evals.

The universal bridge between agents and environments — evaluate, RL-train, and trace any agent, in any sandbox, on any model.

The official implementation of "EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis".

Evaluate and improve models and agents using environments

More is Different. A multi-agent world engine where AI agents live, talk, compete, ally.

RL environments + evals for AI agents. Define once, train anything.

The official code of Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence

A framework for building robust RL environments to train aligned AI.