TY - GEN
T1 - ComfyUI-Copilot
T2 - 63rd Annual Meeting of the Association for Computational Linguistics, ACL 2025
AU - Xu, Zhenran
AU - Yang, Xue
AU - Wang, Yiyu
AU - Hu, Qingli
AU - Wu, Zijiao
AU - Wang, Longyue
AU - Luo, Weihua
AU - Zhang, Kaifu
AU - Hu, Baotian
AU - Zhang, Min
N1 - Publisher Copyright:
©2025 Association for Computational Linguistics.
PY - 2025
Y1 - 2025
N2 - We introduce ComfyUI-Copilot, a large language model-powered plugin designed to enhance the usability and efficiency of ComfyUI, an open-source platform for AI-driven art creation. Despite its flexibility and user-friendly interface, ComfyUI can present challenges to newcomers, including limited documentation, model misconfigurations, and the complexity of workflow design. ComfyUI-Copilot addresses these challenges by offering intelligent node and model recommendations, along with automated one-click workflow construction. At its core, the system employs a hierarchical multi-agent framework comprising a central assistant agent for task delegation and specialized worker agents for different usages, supported by our curated ComfyUI knowledge bases to streamline debugging and deployment. We validate the effectiveness of ComfyUI-Copilot through both offline quantitative evaluations and online user feedback, showing that it accurately recommends nodes and accelerates workflow development. Additionally, use cases illustrate that ComfyUI-Copilot lowers entry barriers for beginners and enhances workflow efficiency for experienced users. The ComfyUI-Copilot installation package and a demo video are available at https://github.com/AIDC-AI/ComfyUI-Copilot.
AB - We introduce ComfyUI-Copilot, a large language model-powered plugin designed to enhance the usability and efficiency of ComfyUI, an open-source platform for AI-driven art creation. Despite its flexibility and user-friendly interface, ComfyUI can present challenges to newcomers, including limited documentation, model misconfigurations, and the complexity of workflow design. ComfyUI-Copilot addresses these challenges by offering intelligent node and model recommendations, along with automated one-click workflow construction. At its core, the system employs a hierarchical multi-agent framework comprising a central assistant agent for task delegation and specialized worker agents for different usages, supported by our curated ComfyUI knowledge bases to streamline debugging and deployment. We validate the effectiveness of ComfyUI-Copilot through both offline quantitative evaluations and online user feedback, showing that it accurately recommends nodes and accelerates workflow development. Additionally, use cases illustrate that ComfyUI-Copilot lowers entry barriers for beginners and enhances workflow efficiency for experienced users. The ComfyUI-Copilot installation package and a demo video are available at https://github.com/AIDC-AI/ComfyUI-Copilot.
UR - https://www.scopus.com/pages/publications/105020379818
U2 - 10.18653/v1/2025.acl-demo.61
DO - 10.18653/v1/2025.acl-demo.61
M3 - 会议稿件
AN - SCOPUS:105020379818
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 632
EP - 643
BT - System Demonstrations
A2 - Mishra, Pushkar
A2 - Muresan, Smaranda
A2 - Yu, Tao
PB - Association for Computational Linguistics (ACL)
Y2 - 27 July 2025 through 1 August 2025
ER -