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Infrastructure for recursive artificial intelligence models

Developed for Recursive Language Models, rlm is a plug-and-play inference library that supports different sandboxes. This Python-based tool standardizes complex language model processes, making them easier to integrate into different systems.

Updates

  • August 2, 2026: Stars 4,987 → 5,343, latest release v0.1.3 (June 26, 2026).

What you get

  • Infinite length context management
  • Plug-and-play architecture running in a code environment
  • Secure integration with different sandbox environments

Installation

Quick installation
pip install rlms
Manual installation
curl -LsSf https://astral.sh/uv/install.sh | sh
uv init && uv venv --python 3.12  # change version as needed
uv pip install -e .

Running it

Quick test run
make quickstart

If you don't write code

🤖 Paste this into your AI agent (Claude Code · Codex · Antigravity)

Using the RLM library, build a structure that allows the language model to break down input, analyze it, and make recursive calls within itself. When instantiating the RLM class, define the configuration of the model you use as the backend and allow the model to interact with the code environment to solve complex tasks.

Related dictionary terms

Who it is forIt is for developers who want to standardize complex language model processes and work with recursive model calls.
LicenseMIT

Links

TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-06-18: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. This page was machine-translated from the Turkish original · the Turkish version prevails.