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Microsoft AutoGen
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Microsoft AutoGen

Active·★ 58.5k·CC-BY-4.0·Updated 2026-04-15
★ Most Popular★ Trending★ Essential

A framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks.

AutoGen is a versatile framework for developing multi-agent AI applications that can operate autonomously or in collaboration with humans. It offers a layered, extensible design, including Core and AgentChat APIs, along with developer tools like AutoGen Studio for no-code GUI development and AutoGen Bench for performance evaluation.

#Multi-Agent AI#AI Framework#Python#LLM Orchestration#No-code AI#Coding
$ Install
$ pip install -U "autogen-agentchat" "autogen-ext[openai]"
↗ Visit site★ GitHub
01

Features

01Framework for multi-agent AI applications
02Supports autonomous or human-collaborative agents
03Layered and extensible design (Core, AgentChat, Extensions APIs)
04No-code GUI for workflow prototyping (AutoGen Studio)
05Benchmarking suite for agent performance (AutoGen Bench)
02

Compatibility

Python
Native
Verified via docs
.NET
Supported
Verified via docs
AutoGen Studio
Native
Verified via docs
OpenAI
Native
Verified via docs
Playwright MCP
Supported
Verified via docs
03

Quick start

1
$ pip install -U "autogen-agentchat" "autogen-ext[openai]"
04

Use cases

↳Developing multi-agent AI applications
↳Building specialized AI assistants (e.g., web browsing, domain experts)
↳Prototyping multi-agent workflows using a no-code GUI
05

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Related searches

Microsoft AutoGen AlternativesBest Multi-Agent Tools 2026Open Source Multi-AgentMicrosoft AutoGen TutorialMicrosoft AutoGen Vs CompetitorsMulti-Agent AIAI FrameworkPython

Comments

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  • S
    Sam GarciaMay 10, 2026

    Our team uses this for automated code reviews. Catches things that humans miss on first pass.

  • K
    Kendall ClarkApr 21, 2026

    still getting my head around agent termination conditions. docs could be clearer on edge cases there

  • F
    Finley ClarkMar 25, 2026

    Built a customer support triage system using AutoGen. The human-in-the-loop pattern works exactly as advertised.

  • E
    Elliot ZhangMar 10, 2026

    Compared AutoGen to LangGraph for complex workflows. AutoGen wins on conversation-heavy patterns; LangGraph is better for explicit state management.

  • Emerson Chen
    Emerson ChenMar 8, 2026

    for building RAG-augmented agent workflows this integrates cleanly with most retrieval setups

  • R
    Remy HarrisFeb 23, 2026

    Works well with Azure OpenAI endpoints. If you're already in the Microsoft ecosystem the integration story is smooth.

  • R
    River ClarkDec 25, 2025

    The v0.4 refactor significantly cleaned up the API. Worth upgrading if you're on an older version — breaking changes but the new design is much cleaner.

  • Oaklyn Chen
    Oaklyn ChenDec 17, 2025

    AutoGen's conversation patterns are the most flexible I've used for multi-agent LLM orchestration. Running it in production for code review automation — the agent back-and-forth is reliable.

  • Alex Kim
    Alex KimDec 6, 2025

    the two-agent chat example got me going in maybe 30 mins. way less boilerplate than expected from a Microsoft project

On this page
01Features02Compatibility03Quick start04Use cases05Alternatives
Stats
GitHub Stars★ 58.5k
Last commit1mo ago
StatusActive
LicenseCC-BY-4.0
CategoryMulti-Agent
Trend (30d)
+2.3k↑ 4.9%
Links
Documentation↗Discussion↗Issues↗Releases↗

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