WooooDyy/AgentGym
Code and implementations for the ACL 2025 paper "AgentGym: Evolving Large Language Model-based Agents across Diverse Environments" by Zhiheng Xi et al.
AgentGym is a framework that allows AI researchers to develop and evaluate large language model-based agents across a wide range of tasks and environments. It takes in an LLM agent and provides standardized feedback from diverse environments like web browsing, text games, and digital tasks. The output is an evaluated agent, its performance metrics, and detailed interaction trajectories, helping researchers understand and improve agent behaviors. This is for AI researchers and practitioners focused on building capable, generalist LLM agents.
742 stars. No commits in the last 6 months.
Use this if you are developing or evaluating large language model agents and need a unified platform with diverse environments and real-time feedback to train and benchmark their capabilities.
Not ideal if you are looking for a pre-built, production-ready AI agent for a specific real-world application, as this is a research and development framework.
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Python
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MIT
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Last pushed
Sep 11, 2025
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