It is evident that the current state of Large Language Models (LLMs)
necessitates the incorporation of external tools. The lack of straightforward
algebraic and logical reasoning is well documented and prompted researchers to
develop frameworks which allow LLMs to operate via external tools. The
ontological nature of tool utilization for a specific task can be well
formulated with a Directed Acyclic Graph (DAG). The central aim of the paper is
to highlight the importance of graph based approaches to LLM-tool interaction
in near future. We propose an exemplary framework to guide the orchestration of
exponentially increasing numbers of external tools with LLMs,where objectives
and functionalities of tools are graph encoded hierarchically. Assuming that
textual segments of a Chain-of-Thought (CoT) can be imagined as a tool as
defined here, the graph based framework can pave new avenues in that particular
direction as well.

当前大型语言模型 (LLMs) 的现状需要融入外部工具。目前已有研究证明缺乏直接的代数和逻辑推理，促使研究人员开发了允许 LLMs 通过外部工具操作的框架。本文的核心目的是强调图形化方法在 LLM 与工具互动中的重要性。我们提出了一个示例框架，用于指导将外部工具与 LLMs 的数量呈指数增长的协同工作，其中工具的目标和功能以图形编码的层次结构呈现。假设文本的思维链 (CoT) 可以被想象为一个工具，基于图形的框架也可以在这一特定方向上开辟新的途径。