As AI Agents based on Large Language Models (LLMs) have shown potential in practical applications across various fields, how to quickly deploy an AI agent and how to conveniently expand the application scenario of AI agents has become a challenge. Previous studies mainly focused on implementing all the reasoning capabilities of AI agents within a single LLM, which often makes the model more complex and also reduces the extensibility of AI agent functionality. In this paper, we propose CACA Agent (Capability Collaboration based AI Agent), using an open architecture inspired by service computing. CACA Agent integrates a set of collaborative capabilities to implement AI Agents, not only reducing the dependence on a single LLM, but also enhancing the extensibility of both the planning abilities and the tools available to AI agents. Utilizing the proposed system, we present a demo to illustrate the operation and the application scenario extension of CACA Agent.

翻译：基于大语言模型（LLMs）的AI智能体在各领域实际应用中已展现出潜力，但如何快速部署AI智能体、便捷扩展其应用场景仍面临挑战。已有研究主要聚焦于在单个大语言模型内实现AI智能体的全部推理能力，这往往使模型更为复杂，同时也降低了AI智能体功能的可扩展性。本文提出CACA Agent（基于能力协作的AI智能体），采用受服务计算启发的开放架构。CACA Agent通过整合一组协作能力来实现AI智能体，不仅降低了对单一LLM的依赖，还增强了AI智能体规划能力与可用工具的可扩展性。基于所提出的系统，我们通过演示案例展示了CACA Agent的运行机制及应用场景扩展过程。