📄 中文摘要
该研究展示了如何在真实世界环境中评估工具使用代理的能力。通过构建一个名为 OpenEnv 的框架，研究者能够模拟多种复杂场景，以测试代理在使用工具时的表现。实验结果表明，代理在特定任务中能够有效利用工具，显示出其在解决实际问题时的潜力。此外，研究还分析了代理在不同环境中的适应能力，强调了环境因素对工具使用效率的影响。这些发现为未来的人工智能应用提供了重要的参考，尤其是在需要工具辅助的复杂任务中。
OpenEnv 实践：在真实环境中评估工具使用代理
📄 English Summary
OpenEnv in Practice: Evaluating Tool-Using Agents in Real-World Environments
This study demonstrates how to evaluate the capabilities of tool-using agents in real-world environments. By constructing a framework called OpenEnv, researchers can simulate various complex scenarios to test the performance of agents when using tools. Experimental results indicate that agents can effectively utilize tools for specific tasks, showcasing their potential in solving real-world problems. Additionally, the research analyzes the adaptability of agents in different environments, emphasizing the impact of environmental factors on tool usage efficiency. These findings provide significant insights for future artificial intelligence applications, particularly in complex tasks that require tool assistance.