langfengQ/verl-agent
verl-agent is an extension of veRL, designed for training LLM/VLM agents via RL. verl-agent is also the official code for paper "Group-in-Group Policy Optimization for LLM Agent Training"
This tool helps AI researchers and machine learning engineers train large language models (LLMs) and vision-language models (VLMs) to act as intelligent agents in complex, multi-step environments. You input an LLM/VLM and a task environment (like ALFWorld or WebShop), and it outputs a fine-tuned agent capable of performing long-horizon tasks through reinforcement learning. It's designed for researchers developing advanced AI agents that interact dynamically and remember key information over many turns.
1,668 stars.
Use this if you are an AI researcher or machine learning engineer looking to train LLM or VLM agents to solve intricate, multi-step problems using reinforcement learning, especially when dealing with long interaction histories.
Not ideal if you are looking for a plug-and-play solution for simple text generation or a tool that doesn't require deep understanding of reinforcement learning concepts.
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1,668
Forks
148
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 27, 2026
Commits (30d)
0
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