OpenWebAgent: An Open Toolkit to Enable Web Agents on Large Language Models
Iat Long Iong, Xiao Liu, Yuxuan Chen, Hanyu Lai, Shuntian Yao, Pengbo Shen, Hao Yu, Yuxiao Dong
Abstract
We introduce OpenWebAgent, an open toolkit designed to optimize web automation by integrating both large language models (LLMs) and large multimodal models (LMMs). This toolkit focuses on enhancing human-computer interactions on the web, simplifying complex tasks through an advanced HTML parser, a rapid action generation module, and an intuitive user interface. At the core of OpenWebAgent is an innovative web agent framework that uses a modular design to allow developers to seamlessly integrate a variety of models and tools to process web information and automate tasks on the web. This enables the development of powerful, task-oriented web agents, significantly enhancing user experience and operational efficiency on the web. The OpenWebAgent framework, Chrome plugin, and demo video are available at https://github.com/THUDM/OpenWebAgent/.
BibTeX
@inproceedings{iong-etal-2024-openwebagent,
title = "{O}pen{W}eb{A}gent: An Open Toolkit to Enable Web Agents on Large Language Models",
author = "Iong, Iat Long and
Liu, Xiao and
Chen, Yuxuan and
Lai, Hanyu and
Yao, Shuntian and
Shen, Pengbo and
Yu, Hao and
Dong, Yuxiao and
Tang, Jie",
editor = "Cao, Yixin and
Feng, Yang and
Xiong, Deyi",
booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.acl-demos.8/",
doi = "10.18653/v1/2024.acl-demos.8",
pages = "72--81"
}