This is the Linux app named Agent Reinforcement Trainer whose latest release can be downloaded as openpipe_art-0.5.9.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Agent Reinforcement Trainer
DESCRIPTION
Agent Reinforcement Trainer, or ART is an open-source reinforcement learning framework tailored to training large language model agents through experience, making them more reliable and performant on multi-turn, multi-step tasks. Instead of just manually crafting prompts or relying on supervised fine-tuning, ART uses techniques like Group Relative Policy Optimization (GRPO) to let agents learn from environmental feedback and reward signals. The framework is designed to integrate easily with Python applications, abstracting much of the RL infrastructure so developers can train agents without deep RL expertise or heavy infrastructure overhead. ART also supports scalable training patterns, observability tools, and integration with hosted platforms like Weights & Biases, and it provides notebooks that demonstrate training on standard benchmarks and tasks.
Features
- Reinforcement learning training for multi-step agents
- Group Relative Policy Optimization (GRPO) support
- Python-friendly API and integration model
- Infrastructure abstraction for easier deployment
- Support for monitoring with tools like W&B
- Example notebooks demonstrating tasks and training
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/art.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
