一位开发者在基于 LLM 的代理系统中遇到了持续的提示注入问题，导致行为受到外部数据的影响而产生非预期行为。为解决此问题，他们设计了一个网关系统，严格区分用户指令和数据输入。此方法旨在防止恶意或非预期的输入数据改变代理的核心指令，并保持对其操作的控制。 AI
影响 通过减轻提示注入风险，此方法可以提高基于 LLM 的代理系统的可靠性和安全性。
排序理由 开发者描述了 LLM 代理系统中一个常见问题的技术解决方案。
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