LLM-Agent-UMF: LLM-based Agent Unified Modeling Framework for Seamless Integration of Multi Active/Passive Core-Agents

Amine B. Hassouna, Hana Chaari, Ines Belhaj
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Abstract

The integration of tools in LLM-based agents overcame the difficulties of standalone LLMs and traditional agents' limited capabilities. However, the conjunction of these technologies and the proposed enhancements in several state-of-the-art works followed a non-unified software architecture resulting in a lack of modularity. Indeed, they focused mainly on functionalities and overlooked the definition of the component's boundaries within the agent. This caused terminological and architectural ambiguities between researchers which we addressed in this paper by proposing a unified framework that establishes a clear foundation for LLM-based agents' development from both functional and software architectural perspectives. Our framework, LLM-Agent-UMF (LLM-based Agent Unified Modeling Framework), clearly distinguishes between the different components of an agent, setting LLMs, and tools apart from a newly introduced element: the core-agent, playing the role of the central coordinator of the agent which comprises five modules: planning, memory, profile, action, and security, the latter often neglected in previous works. Differences in the internal structure of core-agents led us to classify them into a taxonomy of passive and active types. Based on this, we proposed different multi-core agent architectures combining unique characteristics of various individual agents. For evaluation purposes, we applied this framework to a selection of state-of-the-art agents, thereby demonstrating its alignment with their functionalities and clarifying the overlooked architectural aspects. Moreover, we thoroughly assessed four of our proposed architectures by integrating distinctive agents into hybrid active/passive core-agents' systems. This analysis provided clear insights into potential improvements and highlighted the challenges involved in the combination of specific agents.
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LLM-Agent-UMF:基于 LLM 的面向多主动/被动核心代理无缝集成的代理统一建模框架
在基于 LLM 的代理中集成工具克服了独立 LLM 的困难和传统代理的有限能力。然而,这些技术的结合以及一些最新著作中提出的增强功能都遵循了非统一的软件架构,导致缺乏模块化。事实上,它们主要关注的是功能,而忽略了代理内部组件边界的定义。这就造成了研究者之间术语和架构上的歧义,我们在本文中提出了一个统一的框架,从功能和软件架构两个角度为基于 LLM 的代理开发奠定了清晰的基础,从而解决了这一问题。我们的框架,即 LLM-Agent-UMF(基于 LLM 的代理统一建模框架),明确区分了代理的不同组成部分,将 LLM 和工具与一个新引入的元素区分开来:核心代理,扮演代理中心协调者的角色,由五个模块组成:规划、记忆、配置文件、行动和安全,后者在以前的工作中经常被忽视。核心代理内部结构的差异促使我们将其分为被动型和主动型。在此基础上,我们提出了不同的多核代理架构,将不同代理的独特特征结合在一起。出于评估的目的,我们将这一框架应用于部分最先进的代理,从而证明了该框架与代理功能的一致性,并澄清了被忽视的架构方面的问题。此外,我们还通过将不同的代理集成到主动/被动混合核心代理系统中,对我们提出的四种架构进行了全面评估。这一分析为潜在的改进提供了清晰的洞察力,并强调了特定代理组合所面临的挑战。
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