AutoGen v0.4: Reimagining the foundation of agentic AI for scale, extensibility, and robustness

FRIEDERIKE NIEDTNER, Principal Technical Research Program Manager, Microsoft Research AI Frontiers: The following talk invites us to follow the journey of AutoGen (opens in new tab) from a leading open-source framework for multi-agent applications to a complete redesign that lays the foundation for the future of agentic AI research and applications with the release of AutoGen 0.4 (opens in new tab). The framework’s new layered architecture provides flexibility and scalability and includes an ecosystem of extensions and applications, some created by the same team, such as Magentic-One, a team of generalist agents, and Studio, a low-code developer tool. AutoGen 0.4 is also a story about collaboration between MSR, partners within Microsoft, and a vibrant open-source community.

GAGAN BASAL: Hi, I am Gagan Bansal and I am a researcher at Microsoft Research AI Frontiers. And today I’ll talk about some exciting technical updates to AutoGen, a leading open-source framework for agentic AI. And although I am presenting, this is joint work with many incredible colleagues and interns at Microsoft over the last year.  

AutoGen is a leading open-source framework for multi-agent applications that we released in fall 2023. It enables developers and researchers to create intelligent applications using large language models, tool use, and multi-agent collaboration patterns. With AutoGen, our goal has been to lead the innovation in agentic AI research. When we first launched AutoGen in Fall 2023, it quickly became the leading open-source framework for agentic AI, and it continues to empower developers and researchers in many, many domains, including business process automation, marketing, finance, security, and others. 

Since AutoGen’s launch, we’ve not just been maintaining it. We’ve been listening closely to feedback from developers and researchers, and in this rapidly evolving landscape of AI progress, their expectations were high. Users told us that they needed greater modularity and the ability to reuse agents seamlessly. They also asked for better support for debugging and scaling their agentic solutions. And finally, there were many apps to enhance the code quality and maturity of the platform. 

Pursuing these needs required us to question our assumptions and even possibly reimagine the platform. So, in early 2024, we used these learnings to experiment with alternate architectures, and we ended up adopting an actor model for multi-agent orchestration. The actor model is a well-known programming model for concurrent programing and high use systems. Here, actors are the computational building blocks that can exchange messages and also perform work. In Fall 2024, we announced a preview of this version and this new year, we’re thrilled to announce a full release. In summary, AutoGen v0.4 is our response to address our users’ feedback in this evolving landscape of AI research. AutoGen is now not just a framework, but it’s a whole ecosystem for agentic AI. It provides you with a framework that lets you build sophisticated agents and multi-agent applications, and it also provides you with developer tools and many well-defined applications. 

Let me first tell you about the AutoGen framework. At the heart of this release is a layered architecture that is designed for flexibility and scalability. At the base is AutoGen Core. This layer implements the actor model for agents. Building on core is AutoGen AgentChat. This layer provides a simple and easy to use API that is perfect for rapid prototyping. And building on Core and AgentChat is Extensions. 

This layer provides advanced clients, agents and teams, and integrations with third party software. This layered architecture is nice because whether you are an advanced developer or a researcher prototyping new ideas, AutoGen provides you with the tools you need for your project’s stage of development. The Core implements an actor model for agentic AI. At the highest level, this implementation provides two key features. 

The first is asynchronous message exchange between agents. It does so by providing a runtime, and then it also provides event-driven agents that perform computations in response to these messages. There are several implications of this design, and one of them is that it decouples how the messages are delivered between the agents from how the agents handle them. This naturally improves the modularity and scalability of agentic workflows built with AutoGen, especially for deployment. 

The Core’s event-driven architecture provides several other benefits. For example, it provides affordances to observe and control agent behavior, which is crucial for responsible development of agentic technology. It also enables running multiple agents on different processes and even implementing them using different languages. Finally, it enables developers to implement a large class of multi-agent patterns, including static and dynamic workflows. 

When we released AutoGen, one of the first things that the developers absolutely loved about it was its simplicity and the many pre-built agents and teams that it provided, such as the user proxy agent and the assistant agent, and the group chat between multiple agents. With the AutoGen AgentChat layer, we are maintaining these features and adding tons of more essential features such as streaming support, serialization, state management and memory for agents, and finally full-time support for a better development experience. 

Please check out the link below for the migration guide. Finally, the Extension layers provide advanced runtimes, tools, clients, and ecosystem integrations that continuously expand the framework’s capabilities. In addition to the framework, this new release also provides upgrades to essential developer tools and applications built using AutoGen. And here I’ll briefly mention two of them. In late 2023, we also released AutoGen Studio, which is a low code tool for authoring multi-agent applications. 

And we are excited to announce that with version 0.4, Studio has received massive upgrades. It now supports a drag and drop, multi-agent builder. It supports real time updates as agents solve tasks, flow visualizations and execution controls, so that the users remain in control, and component galleries so that the community can discover and build on each other’s work. We’ve always believed that the framework should enable state-of-the-art applications for solving complex tasks with agents, which is why we’ve been building applications with the framework ourselves and using that to guide the framework’s development. 

Last year, we released Magentic-One, a state-of-the-art multi-agent team for solving file- and web-related tasks built using AutoGen. And now its developer API, and general capabilities, such as sophisticated orchestrators and specialized agents such as the web server and the file server, are now available in the AutoGen ecosystem. For us, this new ecosystem is only the beginning and sets the stage for future innovation in agentic AI. 

Over the past two years, our team has made early progress in AI agents and we continue to deeply think about the changing landscape of current AI research and continue to invest in taking steps to help lead the innovation on agents. And by the way, we’re also working closely with our colleagues at Semantic Kernel, to provide an enterprise ready multi-agent runtime for AutoGen. 

Thank you for attending Microsoft Research Forum. Please check out these links to learn more about AutoGen.