生产就绪的 LLM 代理:离线评估的综合框架

📄 中文摘要

随着智能代理系统的不断发展,构建复杂的代理系统已变得相当成熟。然而,验证这些系统的有效性却缺乏相应的严谨性。提出了一种综合框架,旨在对大规模语言模型(LLM)代理进行离线评估,以确保其在实际生产环境中的可靠性和性能。该框架不仅考虑了代理的功能性,还涵盖了安全性和可解释性等关键因素,从而为开发者提供了一个全面的评估工具,促进了 LLM 代理的实际应用和改进。

📄 English Summary

Production-Ready LLM Agents: A Comprehensive Framework for Offline Evaluation

The development of sophisticated agent systems has advanced significantly, yet the rigor in validating their effectiveness remains underdeveloped. A comprehensive framework for offline evaluation of large language model (LLM) agents is proposed, aimed at ensuring their reliability and performance in real-world production environments. This framework considers not only the functionality of the agents but also critical factors such as safety and interpretability. By providing developers with a thorough evaluation tool, it facilitates the practical application and enhancement of LLM agents.

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数据源: OpenAI, Google AI, DeepMind, AWS ML Blog, HuggingFace 等