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OpenPipe/ART

An open-source framework for training multi-step LLM agents using reinforcement learning (GRPO) to learn from experience, offering a serverless RL training service.

Core Features

Trains multi-step LLM agents for real-world tasks.

Utilizes GRPO (Generalized Reinforcement Policy Optimization) for agent training.

Offers a serverless RL training service (W&B Training) with lower costs and faster training.

Provides fully managed infrastructure, eliminating DevOps overhead.

Supports various LLMs like Qwen, GPT-OSS, and Llama.

Quick Start

pip install openpipe-art

Detailed Introduction

ART (Agent Reinforcement Trainer) is an open-source framework designed to enhance the reliability of large language model (LLM) agents by enabling them to learn from experience through reinforcement learning. It integrates GRPO (Generalized Reinforcement Policy Optimization) to facilitate the training of multi-step agents for complex, real-world tasks. Complementing this, ART offers "W&B Training," a serverless RL service that automates infrastructure management, significantly reducing training costs, accelerating feedback cycles, and eliminating DevOps complexities, making advanced RL accessible and efficient for developers.