AI Agents 相关度: 9/10

Agent Lifecycle Toolkit (ALTK): Reusable Middleware Components for Robust AI Agents

Zidane Wright, Jason Tsay, Anupama Murthi, Osher Elhadad, Diego Del Rio, Saurabh Goyal, Kiran Kate, Jim Laredo, Koren Lazar, Vinod Muthusamy, Yara Rizk
arXiv: 2603.15473v1 发布: 2026-03-16 更新: 2026-03-16

AI 摘要

ALTK是一个开源工具包,提供模块化中间件,用于检测、修复和缓解AI Agent生命周期中的常见故障。

主要贡献

  • 提出了Agent Lifecycle Toolkit (ALTK)
  • 提供了模块化的中间件组件,解决Agent的常见故障
  • 与现有pipeline和低代码/无代码工具兼容

方法论

ALTK通过在Agent生命周期的关键阶段(例如,LLM提示前后,工具使用前后)介入,提供检测、修复和缓解故障的模块化组件。

原文摘要

As AI agents move from demos into enterprise deployments, their failure modes become consequential: a misinterpreted tool argument can corrupt production data, a silent reasoning error can go undetected until damage is done, and outputs that violate organizational policy can create legal or compliance risk. Yet, most agent frameworks leave builders to handle these failure modes ad hoc, resulting in brittle, one-off safeguards that are hard to reuse or maintain. We present the Agent Lifecycle Toolkit (ALTK), an open-source collection of modular middleware components that systematically address these gaps across the full agent lifecycle. Across the agent lifecycle, we identify opportunities to intervene and improve, namely, post-user-request, pre-LLM prompt conditioning, post-LLM output processing, pre-tool validation, post-tool result checking, and pre-response assembly. ALTK provides modular middleware that detects, repairs, and mitigates common failure modes. It offers consistent interfaces that fit naturally into existing pipelines. It is compatible with low-code and no-code tools such as the ContextForge MCP Gateway and Langflow. Finally, it significantly reduces the effort of building reliable, production-grade agents.

标签

AI Agents Middleware Failure Mitigation Robustness Open-Source

arXiv 分类

cs.AI