Reasoning Gym is a Python library for generating procedural reasoning datasets and creating verifiable reasoning environments for training models with reinforcement learning. It targets researchers and developers building AI systems that require robust reasoning capabilities, offering a flexible way to create virtually infinite training data with adjustable complexity across diverse domains.

How It Works

The library provides over 100 task generators covering algebra, logic, geometry, and games, among others. It supports tasks with single or multiple correct answers and includes a standard interface for algorithmic verification of solutions. This procedural generation and verification approach allows for scalable, high-fidelity training data creation tailored to specific reasoning challenges.

Quick Start & Requirements

• Install via pip: pip install reasoning-gym
• Requires Python >= 3.10.
• Example usage and dataset generation details are available in the README and linked scripts.

Highlighted Details

• Offers over 100 tasks across domains like algebra, logic, and graph theory.
• Supports algorithmic verification of task solutions.
• Enables creation of composite datasets with weighted task distributions.
• Integrates with RL training frameworks and HuggingFace datasets.

Maintenance & Community

• Active development is indicated.
• Community contributions are encouraged via GitHub issues and the #reasoning-gym channel on the GPU-Mode Discord server.
• Projects like Verifiers, ProRL, and Atropos are listed as users.

Licensing & Compatibility

• The library is released under an unspecified license. The README does not explicitly state the license type.

Limitations & Caveats

The PyPI version may lag behind the main development branch. The specific license is not clearly stated in the README, which could impact commercial use or closed-source integration.