[2024 Best AI Paper] AutoGen Studio: A No-Code Developer Tool for Building and Debugging Multi-Agent
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Title: AutoGen Studio: A No-Code Developer Tool for Building and Debugging Multi-Agent Systems
Authors: Victor Dibia, Jingya Chen, Gagan Bansal, Suff Syed, Adam Fourney, Erkang Zhu, Chi Wang, Saleema Amershi
Abstract:
Multi-agent systems, where multiple agents (generative AI models + tools)
collaborate, are emerging as an effective pattern for solving long-running,
complex tasks in numerous domains. However, specifying their parameters (such
as models, tools, and orchestration mechanisms etc,.) and debugging them
remains challenging for most developers. To address this challenge, we present
AUTOGEN STUDIO, a no-code developer tool for rapidly prototyping, debugging,
and evaluating multi-agent workflows built upon the AUTOGEN framework. AUTOGEN
STUDIO offers a web interface and a Python API for representing LLM-enabled
agents using a declarative (JSON-based) specification. It provides an intuitive
drag-and-drop UI for agent workflow specification, interactive evaluation and
debugging of workflows, and a gallery of reusable agent components. We
highlight four design principles for no-code multi-agent developer tools and
contribute an open-source implementation at
https://github.com/microsoft/autogen/...