WebOlympus: An Open Platform for Web Agents on Live Websites

Boyuan Zheng, Boyu Gou, Scott Salisbury, Zheng Du, Huan Sun, Yu Su


Abstract
Web agents are emerging as powerful tools capable of performing complex tasks across diverse web environments. The rapid development of large multimodal models is further enhancing this advancement. However, there is a lack of standardized and user-friendly tools for research and development, as well as experimental platforms on live websites. To address this challenge, we present WebOlympus, an open platform for web agents operating on live websites. WebOlympus offers a Chrome extension-based UI, enabling users without programming experience to easily utilize the platform. It allows users to run web agents with various designs using only a few lines of code or simple clicks on the Chrome extension. To ensure the trustworthiness of web agents, a safety monitor module that prevents harmful actions through human supervision or model-based control is incorporated. WebOlympus supports diverse applications, including annotation interfaces for web agent trajectories and data crawling.
Anthology ID:
2024.emnlp-demo.20
Volume:
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
November
Year:
2024
Address:
Miami, Florida, USA
Editors:
Delia Irazu Hernandez Farias, Tom Hope, Manling Li
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
187–197
Language:
URL:
https://aclanthology.org/2024.emnlp-demo.20
DOI:
Bibkey:
Cite (ACL):
Boyuan Zheng, Boyu Gou, Scott Salisbury, Zheng Du, Huan Sun, and Yu Su. 2024. WebOlympus: An Open Platform for Web Agents on Live Websites. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 187–197, Miami, Florida, USA. Association for Computational Linguistics.
Cite (Informal):
WebOlympus: An Open Platform for Web Agents on Live Websites (Zheng et al., EMNLP 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.emnlp-demo.20.pdf