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Microsoft AutoGen

by MicrosoftUpdated Jun 15, 2025

Microsoft's framework for building multi-agent systems where agents can converse with each other, use tools, and collaborate on complex tasks. AutoGen 0.4 introduced a complete rewrite with an event-driven architecture, async-first design, and a modular component system. Complements Semantic Kernel for enterprise scenarios with Azure integration.

Architecture Overview

AutoGen 0.4 uses an event-driven, actor-based architecture where agents communicate through an AgentRuntime message bus. Each agent is an independent actor that receives and sends messages asynchronously. Teams (like RoundRobinGroupChat, SelectorGroupChat) orchestrate multi-agent conversations with configurable termination conditions. The framework separates the core agent protocol from specific implementations, enabling custom agent types.

When to Use Microsoft AutoGen

Multi-agent debates and discussions
Enterprise workflows with Azure integration
Complex problem-solving with agent collaboration
Code generation and review pipelines
Research and analysis with multiple specialist agents

Strengths & Weaknesses

Strengths

Mature multi-agent conversation patterns
Event-driven async architecture (v0.4)
Deep Azure and Microsoft ecosystem integration
Multi-language support (Python, C#)
Flexible team orchestration patterns

Weaknesses

Major API changes between v0.2 and v0.4 can cause confusion
Complex setup for simple use cases
Heavy enterprise focus may overwhelm smaller projects
Documentation split between old and new versions

Quick Start

python

from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.conditions import TextMentionTermination
from autogen_ext.models.openai import OpenAIChatCompletionClient

# Create a model client
model_client = OpenAIChatCompletionClient(model="gpt-4o")

# Define agents
primary_agent = AssistantAgent(
    "primary",
    model_client=model_client,
    system_message="You are a helpful AI assistant. Say 'APPROVE' when the task is done.",
)

critic_agent = AssistantAgent(
    "critic",
    model_client=model_client,
    system_message="You review responses and provide constructive feedback. Say 'APPROVE' when satisfied.",
)

# Create a team with termination condition
termination = TextMentionTermination("APPROVE")
team = RoundRobinGroupChat(
    [primary_agent, critic_agent],
    termination_condition=termination,
)

# Run the team
import asyncio

async def main():
    result = await team.run(task="Write a haiku about AI agents.")
    print(result.messages[-1].content)

asyncio.run(main())

Features at a Glance

Developer	Microsoft
Language	Python, C#
License	MIT
GitHub Stars	38k+
MCP Support	Yes
Multi-Agent	Yes

Notable Users

MicrosoftAccentureEYMcKinsey

Resources

Official Documentation

https://microsoft.github.io/autogen/

GitHub Repository

https://github.com/microsoft/autogen

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