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 (Eric) Zhu ,
- Chi Wang ,
- Saleema Amershi
Preprint |
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 on GitHub. (opens in new tab)
AutoGen Update: Complex Tasks and Agents
Adam Fourney discusses the effectiveness of using multiple agents, working together, to complete complex multi-step tasks. He will showcase their capability to outperform previous single-agent solutions on benchmarks like GAIA, utilizing customizable arrangements of agents that collaborate, reason, and utilize tools to achieve complex outcomes.
What’s new in AutoGen?
Microsoft Research Forum | Episode 2 | March 5, 2024 Chi Wang discussed the latest updates on AutoGen – the multi-agent framework for next generation AI applications. This includes milestones achieved, community feedback, new exciting features, and ongoing research and challenges. See more at https://aka.ms/ResearchForum-Mar2024 (opens in new tab)