I am deciding between frameworks for a new Artificial Intelligence project. AutoGen (Microsoft Agent Framework) seems great for conversation, but LangGraph claims to have better control over "cycles" and state. In a multi-agent setup, does Microsoft’s framework allow for specific routing, like "If Agent A says X, go to Agent C instead of Agent B"?
3 answers
The primary difference lies in the philosophy. AutoGen (Microsoft Agent Framework) is event-driven and conversation-centric. For routing, you use a GroupChatManager which can be customized with a "speaker selection" function. This function is essentially your router; it looks at the last message and decides who speaks next. LangGraph is more like a state machine where you explicitly draw the edges. If your project is about open-ended collaboration and brainstorming, Microsoft's approach is more natural. If it’s a very strict, step-by-step industrial process, LangGraph might feel more "controlled," but this framework is catching up fast with its v0.4 updates.
That speaker selection function sounds like it could get messy with 10+ agents. In the AutoGen (Microsoft Agent Framework), is there a way to visualize these "routes" before running the code? I worry about creating an infinite loop where two agents just keep "checking" each other's work forever without finishing the task.
I’ve used both, and I find the Microsoft framework much easier to debug because the logs look like a standard chat transcript rather than a complex node graph.
Totally agree, Michelle. When things go wrong, reading a "chat history" to see where the logic failed is much more intuitive for our junior devs.
To avoid loops, Alice, you should always implement a "Terminator" agent or a specific string like "TERMINATE" that signals the end of the work. You can also use the max_round parameter in the GroupChat to force a hard stop. For visualization, AutoGen Studio is currently the best way to see the "flow" of a conversation, though it's not as "graph-like" as LangGraph's visualizer yet.