Hey, I'm one of the authors of Plexe. Overall, I'd say we like smolagents: it's simple, easy to understand, and you can get a project set up very quickly. It also has some neat features, such as the "step callbacks" (functions that are executed after every step the agent takes).

However, the library does feel somewhat immature, and has some drawbacks that hinder building a production application. Some of the issues we've ran into include:

1. It's not easy to customise the agents' system prompts. You have to "patch" the smolagents library's YAML templates in a hacky way. 2. There is no "shared memory" abstraction out of the box to help you manage communication between agents. We had to implement an "ObjectRegistry" class into which the agents can register objects, so that another agent can retrieve the object just by knowing the object's key string. As we scale, we will need to build more complex communication abstractions (tasks queues etc). Given that communication is a key element of multi-agent systems, I would have expected a popular library like smolagents to have some kind of built-in support for it. 3. No "structured response" where you can pass a Pydantic BaseModel (or similar) to specify what structure the agent response should have. 4. "Managed agents" are always executed synchronously. If you have a hierarchy of managed agents, only one agent will ever be working at any given time. So we'll have to build an async execution mechanism ourselves.

I think we've run into some other limitations as well, but these are the first that come to my mind :) hope this helps!