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RLM

Inference library letting language models recursively call themselves via a REPL

  • Agent frameworks and tools
  • AI models and runtimes
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What it is

A Python library implementing Recursive Language Models, where an LLM handles very long inputs by loading them into a variable inside a code REPL and launching sub-model calls on pieces of it. It wraps API-based and local models behind a drop-in completion call and can run generated code locally, in IPython, Docker, or cloud sandboxes such as Modal, E2B, Daytona, and Prime. A training environment for reinforcement learning is included, and researchers and developers use it to experiment with long-context reasoning beyond a model's native window.

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Facts

Stars
5,703 GitHub stars.
5,703

Forks
918
Commits
143
Contributors
21
Language
Python
License
MIT
Last commit
Sep 24, 2026
On GitHub since
December 2025
First release
January 2026
Platforms
library
Self-hostable
No
Author
az
Tags
  • agent-sandbox
  • reinforcement-learning
  • llm-inference
  • context-engineering
  • ai-agents

Last synced from GitHub on Oct 20, 2026

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