AutoGen

AutoGen Expert Skill

AutoGen (by Microsoft Research) is a framework for conversational multi-agent AI. Unlike LangGraph's explicit graph topology or CrewAI's role-based crews, AutoGen uses agent-to-agent conversations as the orchestration primitive. Agents communicate through structured chat, with built-in patterns for nested conversations, group chat with routing, and code execution.

Core Paradigm

from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient

model_client = OpenAIChatCompletionClient(model="gpt-4o-mini")

assistant = AssistantAgent(
    name="assistant",
    system_message="You are a helpful assistant.",
    model_client=model_client,
)

⚠️ UserProxyAgent is NOT a human user. It is an automated proxy that can execute code. Despite the name, it runs autonomously unless human_input_mode is set to ALWAYS.

Core Principles

1. Conversations are the orchestration primitive. Agents send messages, receive replies, and the conversation structure determines the workflow.
2. UserProxyAgent is a code executor, not a human. Despite the name, it runs autonomously by default. Set human_input_mode="ALWAYS" for actual human-in-the-loop.
3. GroupChat routes between agents. RoundRobinGroupChat cycles fixed-order. SelectorGroupChat uses an LLM to pick the next speaker.
4. Nested chats delegate work. An agent can spawn a sub-conversation between specialist agents and return the result.
5. Docker is the safe code execution mode. Local code execution (LocalCommandLineCodeExecutor) runs LLM-generated code on your machine — use Docker in production.
6. Cancellation tokens stop runaway agents. Always pass CancellationToken for long-running tasks.

Where to Start

Quick Reference

Framework Routing Guide

Reference Files

Templates

Troubleshooting

When NOT to Use AutoGen

• Simple single-agent task — overkill, use direct API call
• Need fine-grained graph control — use LangGraph
• Need role-based teams with fixed processes — use CrewAI
• Need chain composition — use LangChain LCEL