A Comparison of Popular AI Agent Frameworks: Which One is Right for You?

What Are AI Agent Frameworks?

The Contenders

1. Autogen
   Autogen is being hailed as the Swiss Army knife of AI frameworks. With the ability to manage multiple tasks, including live data streams, it’s perfect for setting up complex AI applications. Currently boasting over 27,500 stars on GitHub, it’s clear that the community trusts Autogen. What users love is its response time to issues and the flexibility it offers.
   Pros:
   • Handles complex plans with its powerful planning agent features.
   • Allows running multiple agents at once.
     Cons:
   • Requires coding knowledge, which may deter beginners.
2. Semantic Kernel
   Similar to Autogen, the Semantic Kernel is designed for continuous data handling but stands out for its built-in memory module which retains user preferences. Talk about a smart assistant that’s personalizes itself over time!
   Pros:
   • Flexibility as it can collaborate with Autogen agents.
   • Memory module saves user preferences.
     Cons:
   • It primarily utilizes C#, with features added for Python later on.
3. Promptflow
   The Promptflow has more of a mixed reputation. Users found it challenging and even frustrating at times. Despite its potential, many developers consider it user-unfriendly, particularly within certain tech environments, like Azure.
   Pros:
   • Visual representation of prompts which might appeal to some users.
     Cons:
   • Confusing interface and requires substantial setup.
4. LangChain
   If you’re looking for a vast community and features, then LangChain might be your pick. With around 86,000 stars on GitHub, it’s one of the most popular LLM frameworks. Unfortunately, some users have faced hiccups while following tutorials, which can be frustrating!
   Pros:
   • Large community support and extensive documentation.
     Cons:
   • Some errors reported when following tutorials, suggesting not ready for big-time projects just yet.
5. CrewAI
   The CrewAI framework is simpler and prides itself on making the choice of next agent easy. It’s designed for beginners who want quick results without diving deep into code.
   Pros:
   • Easy to use for beginners with minimal setup.
     Cons:
   • Doesn’t support streaming function calls, which can be a setback for certain projects.
6. Bonus Mention: MemGPT
   MemGPT isn’t a framework in the traditional sense, but it’s worthy of a mention! It’s a unique concept that allows the agent to remember conversations longer than its context window. Talk about smart!
   Pros:
   • Personalized interaction with users based on past conversations.
     Cons:
   • Currently lacks support due to the authors being busy with PhD projects.

Which One is Right for You?

1. Purpose

• If you need a framework for complex tasks and can tolerate a bit of a learning curve, then Autogen could be your best bet.
• For applications needing continuous memory features, definitely check out Semantic Kernel.
• A good choice for simple tasks or for beginners is CrewAI.

2. Programming Language

• If you’re comfortable with C#, then Semantic Kernel might be a good fit.
• For Python enthusiasts, LangChain offers extensive features.
• Lack of coding skills? Consider CrewAI to ease into it.

3. Community Support

• If community engagement matters, you’ll find robust resources and help groups around frameworks like LangChain and Autogen.

4. User Experience

• If ease of use is a priority, you may struggle with Promptflow and potentially with LangChain based on user reports.

Wrap Up