本文聚焦于Agent开发中的核心技术问题:如何精确计算用户消息(prompt)占用的上下文窗口大小。作者提出在实际开发中,上下文窗口有限,需包含系统提示词、模型返回结果及工具调用等元素,因此需要有效估算工具以避免溢出。文章探讨了可视化工具和其他实用方法,帮助开发者优化Agent性能,提升资源利用效率。这一指南对AI开发者极具参考价值,尤其适用于大模型应用场景,能有效解决上下文管理难题,推动Agent技术落地。
原文链接:Linux.do
本文聚焦于Agent开发中的核心技术问题:如何精确计算用户消息(prompt)占用的上下文窗口大小。作者提出在实际开发中,上下文窗口有限,需包含系统提示词、模型返回结果及工具调用等元素,因此需要有效估算工具以避免溢出。文章探讨了可视化工具和其他实用方法,帮助开发者优化Agent性能,提升资源利用效率。这一指南对AI开发者极具参考价值,尤其适用于大模型应用场景,能有效解决上下文管理难题,推动Agent技术落地。
原文链接:Linux.do
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