OpenAgents: An Open Platform for Language Agents in the Wild

Original Paper: https://arxiv.org/abs/2310.10634

By: Tianbao Xie, Fan Zhou, Zhoujun Cheng, Peng Shi, Luoxuan Weng, Yitao Liu, Toh Jing Hua, Junning Zhao, Qian Liu, Che Liu, Leo Z. Liu, Yiheng Xu, Hongjin Su, Dongchan Shin, Caiming Xiong, Tao Yu

Abstract:

Language agents show potential in being capable of utilizing natural language for varied and intricate tasks in diverse environments, particularly when built upon large language models (LLMs). Current language agent frameworks aim to facilitate the construction of proof-of-concept language agents while neglecting the non-expert user access to agents and paying little attention to application-level designs. We present OpenAgents, an open platform for using and hosting language agents in the wild of everyday life. OpenAgents includes three agents: (1) Data Agent for data analysis with Python/SQL and data tools (2) Plugins Agent with 200+ daily API tools (3) Web Agent for autonomous web browsing. OpenAgents enables general users to interact with agent functionalities through a web user interface optimized for swift responses and common failures while offering developers and researchers a seamless deployment experience on local setups, providing a foundation for crafting innovative language agents and facilitating real-world evaluations. We elucidate the challenges and opportunities, aspiring to set a foundation for future research and development of real-world language agents.

Summary Notes

Figure: The OpenAgents platform for general users, developers, and researchers. (a) General users can interact with the agents via our online web interface, instead of programmer-oriented console or packages. (b) Developers can effortlessly deploy the front end and back end for further developments given our codes. (c) Researchers can build new language agents or agent-related methods given the examples and shared components, and see how they perform with the web UI. Our OpenAgents serves to be a simple and versatile platform for using, developing, and evaluating language agents.

Introduction

Imagine a world where language agents can seamlessly assist you with diverse tasks, from data analysis and web browsing to utilizing a vast array of plugins for everyday needs. This world is closer than ever with OpenAgents, an open platform that democratizes access to language agents. Built on the capabilities of large language models (LLMs), OpenAgents aims to bring these powerful tools out of research labs and into the hands of general users, developers, and researchers.

The Research Question

The primary question that OpenAgents addresses is how to create a robust, user-friendly platform that allows non-experts to leverage the capabilities of language agents for a variety of real-world applications. This involves not only making the agents accessible but also ensuring they can perform reliably in diverse, uncontrolled environments.

Key Methodologies

OpenAgents employs several innovative methodologies to achieve its goals:

1. User-friendly Web Interface: Designed for general users, the web interface allows interaction with agents without requiring any coding skills.
2. Local Deployment for Developers: Provides a seamless experience for developers to deploy and further develop the platform locally.
3. In-the-Wild Evaluation: Facilitates real-world evaluations by capturing human-agent interactions and feedback for continuous improvement.

Main Findings and Results

OpenAgents includes three specialized agents:

1. Data Agent: Handles data analysis tasks using Python, SQL, and various data tools.
2. Plugins Agent: Integrates over 200 API tools for daily tasks like shopping, weather updates, and concept visualization.
3. Web Agent: Enables autonomous web browsing, interacting with web pages to perform tasks like booking flights or summarizing movie reviews.

Implications and Potential Applications

The implications of OpenAgents are vast. For general users, it simplifies complex tasks without needing technical expertise. Developers can build and deploy their language agents effortlessly, while researchers can use the platform as a testbed for new agent models and methods.

Potential applications include:

• Personal Assistants: Automating daily tasks like scheduling, searching for information, or managing emails.
• Data Analysis: Performing complex data manipulations, visualizations, and interpretations.
• E-commerce: Assisting with shopping, price comparisons, and product recommendations.
• Web Navigation: Automating repetitive web tasks, such as filling out forms or extracting information from websites.

Conclusion

OpenAgents represents a significant step forward in making language agents accessible and practical for real-world applications. By offering an open platform that caters to general users, developers, and researchers, OpenAgents sets the stage for a future where intelligent agents are an integral part of our daily lives.