AutoGen Studio: A No-Code Developer Tool for Building and Debugging Multi-Agent Systems
Victor Dibia, Jingya Chen, Gagan Bansal, Suff Syed, Adam Fourney,, Erkang Zhu, Chi Wang, Saleema Amershi

TL;DR
AutoGen Studio is a no-code tool that simplifies the creation, debugging, and evaluation of multi-agent AI systems through an intuitive web interface and Python API, facilitating rapid prototyping and reuse.
Contribution
It introduces a no-code platform with a declarative specification and interactive features for multi-agent system development, addressing complexity and debugging challenges.
Findings
Enables rapid prototyping of multi-agent workflows
Provides an intuitive drag-and-drop interface for developers
Open-source implementation available for community use
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…
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Taxonomy
TopicsMulti-Agent Systems and Negotiation · Simulation Techniques and Applications · Scheduling and Optimization Algorithms
