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RAGEN

Reinforcement learning framework for training reasoning LLM agents over multi-turn episodes with the StarPO algorithm.

Harness by mll-lab-nu

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RAGEN is a reinforcement learning framework for training reasoning LLM agents through multi-turn interactions, built on the StarPO algorithm. It ships 10 built-in environments such as Sokoban, FrozenLake and WebShop, a Gym-compatible interface for adding environments, and reasoning-collapse diagnostics with reward-variance rollout filtering.

Use cases: model-inference

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Languages
Python

Facts extracted by Claude Haiku 5.5 from the linked sources on Oct 24, 2026. Wrong fact? Tell us.

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Frameworks for the same language with a similar way of orchestrating agents.

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2,825
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28
Last commit
Aug 23, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
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RAGEN. Agent Mart. https://agentmart.dev/harnesses/ragen (last updated 2026-10-24)