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, Jie Tang
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/.- Anthology ID:
- 2024.acl-demos.8
- Volume:
- Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Yixin Cao, Yang Feng, Deyi Xiong
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 72–81
- Language:
- URL:
- https://aclanthology.org/2024.acl-demos.8
- DOI:
- 10.18653/v1/2024.acl-demos.8
- Cite (ACL):
- Iat Long Iong, Xiao Liu, Yuxuan Chen, Hanyu Lai, Shuntian Yao, Pengbo Shen, Hao Yu, Yuxiao Dong, and Jie Tang. 2024. OpenWebAgent: An Open Toolkit to Enable Web Agents on Large Language Models. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 72–81, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- OpenWebAgent: An Open Toolkit to Enable Web Agents on Large Language Models (Iong et al., ACL 2024)
- PDF:
- https://preview.aclanthology.org/autopr/2024.acl-demos.8.pdf