Magentic-One, AutoGen, LangGraph, CrewAI, or OpenAI Swarm: Which Multi-AI Agent Framework is Best?

Rifx.Online
Programming , Machine Learning , Chatbots
20 Nov, 2024

Pros and Cons of popular Multi-Agent Orchestration framework

The Multi AI Agent topic in Generative AI is heating up and every major tech giant has released some framework around it.

But which Multi-AI Agent framework to choose?

They are just too many !!

And with OpenAI releasing Swarm and Microsoft’s Magentic-One, this space has become very cluttered. So to clear any doubts, I will try to explain the key-features, pros and cons of each of these frameworks and let you decide what suits you well. We will be talking about

AutoGen (Microsoft)

LangGraph (LangChain)

CrewAI

OpenAI Swarm (OpenAI)

Magentic-One (Microsoft)

Let’s get started !!

1. Autogen

AutoGen is the most popular and the earliest framework in the space by Microsoft, more suitable for software development tasks

Features:

It majorly involves two agents, the User and the Assistant.
User-Agent & Assistant-Agent Interaction: In Autogen’s user-assistant agent model, the User Agent can provide prompts or requirements, while the Assistant Agent generates and executes the code.
The Assistant Agent handles not just code generation but also the execution, giving results back to the user or other agents in the setup.
Specializes in multi-agent orchestration for code tasks but can handle other tasks as well.
Human guidance can be provided in between the interactions.
Strong community support from Microsoft.

Limitations:

Not intuitive enough, and not suitable for non-programmers.
A complicated setup, especially with local LLMs; requires a proxy server.
If not a software development task, can be pretty mediocre

2. CrewAI

CrewAI is usually the go-to choice for folks to build a quick demo for any Multi AI Agent task given it’s very intuitive and easy to set up.

Features:

Very intuitive, and primarily relies on prompt writing.
Creating new agents and adding to the ecosystem is very easy. You can create 100s of agents in minutes
Easy to use for non-technical users.
Works well with most LLM providers and local LLMs, thanks to LangChain integration.

Limitations:

Limited flexibility and customization.
Suitable for basic use cases and not ideal for complex programming tasks.
There are some bugs during interactions between agents.
Community support is limited

3. Langraph

My personal favourite, LangGraph can be used for any Multi-AI Agent tasks and provides a lot of flexibility.

Features:

Built on top of LangChain; based on the idea of Directed Cyclic Graph.
It’s not just a multi-AI agent framework, but a lot more.
Very flexible and customizable, supporting nearly any multi-agent orchestration application.
It is an extension of LangChain, hence got great community support.
Works well with open-sourced LLMs and any API

Limitations:

Lacks thorough documentation.
Not user-friendly for non-programmers or beginner programmers.
Requires decent programming skills, particularly in understanding graphs and logic flows.

4. OpenAI Swarm

OpenAI recently released Swarm, and I must say, it’s the easiest Multi-AI agent framework out there if you wish to get started

Features

Suitable for newbies in Multi-AI Agent
The major focus is on simplifying “Agent creation” and context switching between agents (called Handoffs).
Creating a short demo is super easy

Limitations

Doesn’t support LLMs other than OpenAI API
Not good for production deployments
Not flexible enough.
Community support is poor. You can’t even raise issues on Git Hub!

5. Magentic-One

The latest addition to this list is Magentic-One by Microsoft (their 2nd framework) which also, is an attempt to simplify their existing AutoGen framework

Features

Similar to Swarm, this is suitable for non-programmers and easy to run
Comes with a default pack of 5 agents, one manager agent and other 4 being: WebSurfer navigates and interacts with webpages through a browser, FileSurfer manages and navigates local files, Coder focuses on writing and analyzing code, and ComputerTerminal provides console access for running programs and installing libraries.
Built on top of AutoGen, and is more of a generalist framework.
Includes AutoGenBench, a tool specific for analysing agent performance.

Limitations

Support for open-source LLMs is complicated
Not flexible enough; appears more like an application rather than a framework to me
Documentation and community support is nil as of now

So, what’s the best Multi-AI Agent framework?

According to my views (I have used all these packages),

For Software Development: AutoGen (Microsoft) — Best suited for tasks involving code generation and complex multi-agent coding workflows.
Best for Newbies: OpenAI Swarm & CrewAI — User-friendly, making it ideal for those new to multi-agent AI without complex setup requirements.
Best for Complex Tasks: LangGraph — Offers high flexibility and is built for advanced users, allowing custom logic and orchestration.
Open-Source LLMs: LangGraph — Integrates well with open-source LLMs and supports various APIs, unlike some other frameworks. Even CrewAI is fine.
Best community support: AutoGen has decent community support helping you with out-of-the-way issues
Ready from Word Go: CrewAI — Quick to set up and intuitive, suitable for demos or tasks that require rapid agent creation. Even Swarm and Magentic-One are pretty good but don’t have enough community support
Cost-Effective: Magnetic-One — Comes with a pre-packaged setup and a generalist approach, potentially saving on initial costs. Even Swarm and CrewAI can be considered.