Jbollenbacher

Jbollenbacher / RLM

Public

A fully recursive RLM in Elixir

21
3
100% credibility
Found Feb 10, 2026 at 15 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Elixir
AI Summary

RLM is a chat tool that lets AI handle large amounts of text or files by recursively breaking them down through code it writes itself.

How It Works

1
🔍 Discover RLM

You stumble upon RLM on GitHub, a clever AI chat buddy that tackles huge documents without getting overwhelmed.

2
💻 Get it ready

You download the tool to your computer and prepare it in a few simple steps.

3
🔗 Link your AI

You connect it to an AI thinking service, like linking a smart friend who can reason deeply.

4
Pick your way
⚡
Quick question

Ask once about your text or file and get a fast answer.

💬
Chat session

Start a back-and-forth chat to explore ideas step by step.

5
📁 Add your stuff

You paste in a big document, text, or point it to a folder of files to analyze.

6
🧠 Ask smart questions

You type your question, and the AI magically breaks down the giant info into perfect insights.

🎉 Get amazing results

You receive clear, thorough answers that solve your tough problems, feeling like magic.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 15 to 21 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is RLM?

RLM is an Elixir CLI tool for recursive language models, letting LLMs tackle huge inputs like docs or repos without cramming them into limited context windows. You pipe data via stdin or load it directly, then query interactively or one-shot—models write Elixir code in a persistent REPL to chunk, grep, preview, and spawn sub-LLMs recursively. Add a workspace flag for read/write access to project files, all via OpenRouter or OpenAI-compatible APIs.

Why is it gaining traction?

It sidesteps context bloat entirely—data lives in variables, not prompts—enabling fully recursive processing that scales reasoning depth without massive models. Devs dig the seamless CLI for piping logs or summarizing codebases, plus session persistence for multi-turn chats. In a sea of RAG prompts, this fully recursive RLM delivers precise, decomposable analysis on GitHub repos or remote datasets.

Who should use this?

Elixir backend devs analyzing large logs, codebases, or ETL pipelines where context limits kill standard LLMs. AI prototype builders testing recursive agents on fully remote companies' data dumps. Ops engineers querying massive traces without truncation hacks.

Verdict

At 10 stars and 1.0% credibility, RLM is raw but functional—docs cover setup/CLI, tests run clean, making it a quick spin for recursive experiments. Grab it if you're chasing fully recursive meaning beyond basic chat; skip for production until more battle scars.

(178 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.