autogen-agentchat
AutoGen agents and teams library
Decision gist · record as of 2026-08-14
Yes, if you are building multi-agent applications and want a structured, batteries-included starting point. The low install friction, permissive MIT license, and position within an active ecosystem make it a reasonable choice for prototyping and production use. The aging maintenance status (318 days since last release) is not alarming for a stable library, but verify that autogen-core updates remain compatible before adopting in a fast-moving project.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; you must provide a model_client (typically from autogen-core or a compatible LLM integration).
- Low install friction with a single runtime dependency (autogen-core).
- Package is aging—last release was 318 days ago—but remains actively maintained within the autogen ecosystem.
License · maintenance · safety
permissive license (permissive) — MIT License permits commercial and private use, modification, and distribution with minimal restrictions; you may use this in proprietary projects provided you retain the copyright notice.
last release 2025-09-30 (318 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,056,308 downloads/mo, #4,431 on PyPI
Alternatives
Verify before relying
pip install autogen-agentchat
from autogen_agentchat.agents import AssistantAgent
agent = AssistantAgent(name="helper", model_client=your_model_client)- What specific multi-agent design patterns are included as presets—the fact sheet does not enumerate them.
- Whether autogen-core's event-driven model remains accessible to users who start with AgentChat.
- Performance characteristics or scalability limits for team-based agent systems.
What it is and what it does
AutoGen AgentChat is a high-level abstraction layer for building applications where multiple AI agents collaborate to solve tasks. It sits on top of autogen-core and is designed as the recommended entry point for developers new to multi-agent systems, offering intuitive defaults like preset agent behaviors and predefined team patterns rather than requiring manual orchestration. The package bundles agents with common configurations and teams with established multi-agent design patterns, reducing boilerplate and decision fatigue.
For typical use, you instantiate agents with preset behaviors, compose them into teams following established patterns, and let the framework handle inter-agent communication and coordination. The underlying autogen-core dependency provides the event-driven engine; AgentChat wraps it in a simpler, more opinionated interface. Advanced users can drop down to autogen-core for finer control, but most workflows stay within AgentChat's higher-level abstractions.
Use it for
- Build a customer support system where specialized agents handle different ticket categories and escalate to a supervisor agent.
- Create a research assistant that coordinates multiple agents—one for web search, one for document analysis, one for synthesis.
- Implement a code review workflow where agents check style, security, and functionality in parallel before merging.
- Design a data analysis pipeline where agents fetch data, clean it, and generate reports in sequence.
- Prototype a multi-turn conversation system where agents take turns responding and refining answers.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building multi-agent applications and want a structured, batteries-included starting point.
The low install friction, permissive MIT license, and position within an active ecosystem make it a reasonable choice for prototyping and production use. The aging maintenance status (318 days since last release) is not alarming for a stable library, but verify that autogen-core updates remain compatible before adopting in a fast-moving project.
Install
autogen-agentchat on PyPI
Before you install
Low install friction with a single runtime dependency (autogen-core). Package is aging—last release was 318 days ago—but remains actively maintained within the autogen ecosystem.
Requires Python 3.10 or later; you must provide a model_client (typically from autogen-core or a compatible LLM integration).
License in practice
MIT License permits commercial and private use, modification, and distribution with minimal restrictions; you may use this in proprietary projects provided you retain the copyright notice.
Quickstart
pip install autogen-agentchat
from autogen_agentchat.agents import AssistantAgent
agent = AssistantAgent(name="helper", model_client=your_model_client)Verify before relying
- What specific multi-agent design patterns are included as presets—the fact sheet does not enumerate them.
- Whether autogen-core's event-driven model remains accessible to users who start with AgentChat.
- Performance characteristics or scalability limits for team-based agent systems.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packageautogen-core |
| Maintenance | Aging 318 days since the last release |
| First released | |
| Downloads | 1,056,308 / month, #4,431 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3 |
Evidence: autogen_agentchat-0.7.5-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “multi-agent framework”
- autogen-agentchatProvides a high-level API for building multi-agent applications with…
- ai-parrotAI-Parrot is an async-first Python framework for building, extending,…
- pydantic-deepA Python framework and terminal assistant for building autonomous AI…
Give your agent the search over MCP, or paste the wish link into any chat.
More Artificial Intelligence packages
LiteLLM provides a unified Python interface to call 100+ LLM providers (OpenAI, Anthropic, Gemini, Bedrock, Azure, and others) using OpenAI-compatible API format, available as both a Python SDK and a self-hosted AI Gateway proxy server.
Install it if you need to work with multiple LLM providers or want to centralize LLM routing in your organization.
Client library and CLI tool for downloading, uploading, and managing models, datasets, and repositories on the Hugging Face Hub platform.
Install it if you work with Hugging Face Hub models or datasets.
LangChain provides a framework for building agents and LLM-powered applications by composing language models, tools, and memory through a unified API that abstracts over multiple model providers.
hf-xet provides chunk-based deduplication and efficient file transfer for the Hugging Face Hub, enabling faster uploads and downloads of large files with local disk caching.
Tokenizers converts raw text into token sequences for NLP models, with support for training custom vocabularies and using pre-built tokenizers (BPE, WordPiece) optimized for speed via Rust.
Transformers provides a unified framework for loading, fine-tuning, and running state-of-the-art pretrained models across text, vision, audio, video, and multimodal tasks using PyTorch, JAX, or TensorFlow.
Install it if you need to run or train any transformer-based model for NLP, vision, audio, or multimodal tasks.
See also autogen-core · autogen-ext · camel-ai · pyautogen · autogen · agent-framework-orchestrations · agent-framework-core · mindroom · phidata · microsoft-agents-hosting-teams