# What is Microsoft AutoGen? How it works and how to evaluate it

> Microsoft AutoGen is an open-source multi-agent framework that Microsoft has archived in favor of Microsoft Agent Framework. What it is and how to trace it.

Source: https://www.honeyhive.ai/learn/autogen-framework (updated 2026-11-06)

Microsoft AutoGen is an open-source framework for building applications where several LLM agents work together, with or without a person in the loop. It [started](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-autogen/) as a Microsoft Research project, and Microsoft has since archived it. The [repository](https://github.com/microsoft/autogen) now says the project "is no longer actively maintained by Microsoft" and that "New users should start with Microsoft Agent Framework."

## Where it came from

The [AutoGen paper](https://arxiv.org/abs/2308.08155) (Wu et al., first submitted in August 2023) describes agents that are customizable and can combine LLMs, human input and tools, with interactions defined in natural language and code. Its core idea is multi-agent conversation: agents pass messages to each other until the task is done. For the wider topic, see [multi-agent systems](/learn/multi-agent-systems) and [agent orchestration](/learn/agent-orchestration).

## How AutoGen is built

According to the [README](https://github.com/microsoft/autogen), AutoGen has three layers:

| Layer | What it does |
|---|---|
| Core | Message passing, event-driven agents, and local and distributed runtimes, for Python and .NET |
| AgentChat | A higher-level API for prototyping, built on Core, with two-agent chats and group chats |
| Extensions | First- and third-party additions such as LLM clients (OpenAI, AzureOpenAI) and code execution |

Two tools sit alongside: AutoGen Studio, a no-code GUI for prototyping, and AutoGen Bench, a benchmarking suite. The README lists Python 3.10 or later and installs AgentChat with `pip install -U "autogen-agentchat" "autogen-ext[openai]"`.

## Teams in AgentChat

AgentChat's [teams tutorial](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/teams.html) is where the orchestration choices live:

| Team | How the next speaker is chosen |
|---|---|
| RoundRobinGroupChat | Fixed turn order; each response goes to every other agent |
| SelectorGroupChat | A chat model picks the next speaker after each message |
| Swarm | The current agent hands off with a `HandoffMessage` |
| MagenticOneGroupChat | A generalist team for open-ended web and file tasks |

A team stops when a termination condition fires, such as `TextMentionTermination`, `TextMessageTermination` or `ExternalTermination`. Conditions combine with the `|` operator. The tutorial's round-robin setup is:

```python
text_termination = TextMentionTermination("APPROVE")
team = RoundRobinGroupChat([primary_agent, critic_agent], termination_condition=text_termination)
```

## AutoGen and Microsoft Agent Framework

Microsoft's [migration guide](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-autogen/) says Agent Framework is developed by the core AutoGen and Semantic Kernel teams. It lists the differences that matter when you port code:

- AutoGen pairs an event-driven core with a high-level `Team`; Agent Framework centers on a typed, graph-based `Workflow`.
- `AssistantAgent` is single-turn unless you raise `max_tool_iterations`; Agent Framework's `Agent` is multi-turn by default and keeps calling tools until it has a final answer.
- AutoGen has embedded and experimental distributed runtimes; the guide says Agent Framework focuses on single-process composition, with distributed execution planned.
- The guide's model client table still lists Anthropic and Ollama as planned, but as of November 2026 Agent Framework has [Anthropic](https://learn.microsoft.com/en-us/agent-framework/integrations/by-component/model-providers/anthropic) and [Ollama](https://learn.microsoft.com/en-us/agent-framework/integrations/by-component/model-providers/ollama) providers, installed as prerelease packages (`agent-framework-anthropic`, `agent-framework-ollama`). The table marks AutoGen's `ChatCompletionCache` response caching as planned.

The [Semantic Kernel and Agent Framework page](/learn/semantic-kernel-framework) covers the successor itself.

## Evaluating and tracing AutoGen agents

AutoGen has [native OpenTelemetry support](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-autogen/): runtime tracing, `execute_tool` spans for tools, and `create_agent` and `invoke_agent` spans for chat agents. That means the traces are standard [OpenTelemetry](/learn/opentelemetry) and can go to any backend. For what to look at in them, see [agent observability](/learn/agent-observability) and [testing AI agents](/learn/testing-ai-agents).

With HoneyHive, install the AgentChat instrumentor and initialize the tracer before you create agents:

```bash
pip install honeyhive autogen-agentchat "autogen-ext[openai]" \
    openinference-instrumentation-autogen-agentchat
```

```python
from honeyhive import HoneyHiveTracer
from openinference.instrumentation.autogen_agentchat import AutogenAgentChatInstrumentor

tracer = HoneyHiveTracer.init()  # reads HH_INGESTION_API_KEY from env
instrumentor = AutogenAgentChatInstrumentor()
instrumentor.instrument(tracer_provider=tracer.provider)
```

The [integration page](https://docs.honeyhive.ai/v2/integrations/autogen) says this captures agent and team runs, LLM calls made through `OpenAIChatCompletionClient` with token usage, tool executions, and handoffs in Swarm and SelectorGroupChat teams. Call `tracer.force_flush()` before the process exits. If you only see OpenAI spans, the OpenAI instrumentor is installed instead of the AgentChat one.

## FAQ

### Is Microsoft AutoGen still maintained?

No. The [GitHub README](https://github.com/microsoft/autogen) says the project "has been archived and is no longer actively maintained by Microsoft" and that Microsoft is not providing bug fixes, security fixes, new features or support.

### What replaces AutoGen?

Microsoft Agent Framework. The README says "New users should start with Microsoft Agent Framework," and a [migration guide](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-autogen/) maps AutoGen concepts to it.

### Is AutoGen free?

Yes. The [repository](https://github.com/microsoft/autogen) licenses the code under the MIT License and the documentation under CC-BY-4.0.

### What is AutoGen Studio?

A no-code GUI for building multi-agent workflows. The [README](https://github.com/microsoft/autogen) describes it as meant for prototyping, not production.

### How do I trace an AutoGen agent?

AutoGen has native OpenTelemetry support, and HoneyHive traces AgentChat through the open-source OpenInference AgentChat instrumentor. Setup is on the [HoneyHive AutoGen integration page](https://docs.honeyhive.ai/v2/integrations/autogen).