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NeoCodes

Self Supervised task generation for teaching AI Coding Agents to become Recursive language models.

Code Demo Video Cerebral Valley

Core trick

Deletes a source file from a real Python repo and scores the agent's rewrite by the repo's own test pass rate plus structural validity.

Tags

dev tools

Description

Self Supervised task generation for teaching AI Coding Agents to become Recursive language models. You can use *any* open-source (or closed) repository, as long as it has good test coverage. Parts of the repository are removed during training, and the tests for that part act as the verification. Ran out of time - need to explain more, did not have time for demo video. But I am very confident in this idea, I hope I will still be considered. Thank you. My Projects key innovations: - Recursive Language Models training environment, specifically for AI Coding Agents - Self-supervised Task generation - Take any repository that has well-defined tests, and the environment can use that to generate tasks in a self-supervised manner
Kking112/rlm_forge_v1★ 00 forksPythonCreated Mar 8, 2026 · last push Mar 8, 2026

README excerpt

---
title: RLM-Forge
emoji: 🚀
colorFrom: blue
colorTo: indigo
sdk: gradio
python_version: 3.11
sdk_version: 6.9.0
app_file: server/app.py
base_path: /rlm_forge
---

# RLM-Forge

**Recursive Language Model training environment for AI coding agents.**

RLM-Forge is an [OpenEnv](https://github.com/meta-pytorch/OpenEnv) environment that trains language models to solve coding tasks on real Python repositories using Recursive Language Model (RLM) patterns.

## How It Works

1. **Clone** a real Python repo (e.g., python-slugify, humanize)
2. **Extract** a source file and replace it with a broken stub (correct signatures, wrong implementations)
3. **Agent** explores the repo via a sandboxed multi-step REPL with built-in tools
4. **Reward** = test pass rate (55%) + structural validity (15%) + efficiency (30%)
5. **Train** with GRPO to improve the agent's coding ability over time

### The REPL Tools

The agent has access to these functions in the sandbox:

| Function | Description |
|----------|-------------|
| `read_file(path)` | Read a file from the repo |
| `list_dir(path='.')` | List directory contents |
| `search(pattern, path='.')` | Grep for a pattern |
| `write_file(path, content)` | Write/create a file |
| `run_tests(test_path=None)` | Run pytest |
| `spawn_agent(scope, mission)` | Explore a directory scope |
| `FINAL()` | Signal implementation is complete |

## Project Structure

```
rlm_forge/
├── __init__.py              # Package exports
├── models.py                # Pyda

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