GenAgent：利用自动化工作流构建协作式人工智能系统 生成 - ComfyUI案例研究

GenAgent: Build Collaborative AI Systems with Automated Workflow Generation -- Case Studies on ComfyUI

September 2, 2024

作者: Xiangyuan Xue, Zeyu Lu, Di Huang, Wanli Ouyang, Lei Bai

cs.AI

摘要

先前许多人工智能研究都集中在开发单体模型，以最大化其智能和能力，主要目标是提高特定任务的性能。相比之下，本文探讨了一种替代方法：协作人工智能系统，利用工作流程集成模型、数据源和管道来解决复杂和多样化的任务。我们介绍了GenAgent，这是一个基于LLM的框架，可以自动生成复杂工作流程，相比单体模型具有更大的灵活性和可扩展性。GenAgent的核心创新在于用代码表示工作流程，并通过逐步构建工作流程的协作代理。我们在ComfyUI平台上实现了GenAgent，并提出了一个新的基准测试，OpenComfy。结果表明，GenAgent在运行级别和任务级别评估中均优于基准方法，显示其生成复杂工作流程的能力具有更高的效果和稳定性。

English

Much previous AI research has focused on developing monolithic models to maximize their intelligence and capability, with the primary goal of enhancing performance on specific tasks. In contrast, this paper explores an alternative approach: collaborative AI systems that use workflows to integrate models, data sources, and pipelines to solve complex and diverse tasks. We introduce GenAgent, an LLM-based framework that automatically generates complex workflows, offering greater flexibility and scalability compared to monolithic models. The core innovation of GenAgent lies in representing workflows with code, alongside constructing workflows with collaborative agents in a step-by-step manner. We implement GenAgent on the ComfyUI platform and propose a new benchmark, OpenComfy. The results demonstrate that GenAgent outperforms baseline approaches in both run-level and task-level evaluations, showing its capability to generate complex workflows with superior effectiveness and stability.