Hugging Face's smolagent- a review

Welcome to Tactical Thursday!

Hugging Face just dropped their new AI agent framework, smolagent. And boy, did I get excited to play with it! You know me - I couldn't resist putting it through its paces with my competitors research agent. Here's the tea: ☕

1. 🎯 First impression: smolagent is like that minimalist friend who somehow has everything you need! It comes with three built-in tools:
   1. DuckDuckGo web search (for when your agent needs to stalk the internet)
   2. Python code executioner (for when your agent wants to show off its coding skills)
   3. Speech-to-text transcriber (bit random, but hey, maybe our agents are becoming better listeners than some humans I know! 😅)
2. 🧩 The abstraction puzzle: Here's where it gets... interesting. Working with AI agents is like trying to teach a toddler quantum physics - sometimes things just don't click! When connecting multiple agents, bugs popped up faster than moles in a whack-a-mole game. Sure, I could rewrite the system template to specify outputs, but at that point, I might as well code it myself while sipping my coffee! ☕
3. No workflows? Confession time! I'm actually a huge fan of agentic workflows. They're like the responsible adult in the room- boring, but reliable. But smolagent seems to be all about those pure AI agents, leaving workflow enthusiasts like me hanging. Sometimes you just want a good old reliable Big Mac, and not the most interesting fine dining experience.

Has anyone else taken smolagent for a spin? I'd love to hear your adventures!