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A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.

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Welcome to Microsoft Agent Framework!

Welcome to Microsoft's comprehensive multi-language framework for building, orchestrating, and deploying AI agents with support for both .NET and Python implementations. This framework provides everything from simple chat agents to complex multi-agent workflows with graph-based orchestration.

Watch the full Agent Framework introduction (30 min)

📋 Getting Started

📦 Installation

Python

pip install agent-framework --pre# This will install all sub-packages, see `python/packages` for individual packages.# It may take a minute on first install on Windows.

.NET

dotnet add package Microsoft.Agents.AI

📚 Documentation

Overview - High level overview of the framework
Quick Start - Get started with a simple agent
Tutorials - Step by step tutorials
User Guide - In-depth user guide for building agents and workflows
Migration from Semantic Kernel - Guide to migrate from Semantic Kernel
Migration from AutoGen - Guide to migrate from AutoGen

✨Highlights

Graph-based Workflows: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
- Python workflows |.NET workflows
AF Labs: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
- Labs directory
DevUI: Interactive developer UI for agent development, testing, and debugging workflows
- DevUI package

See the DevUI in action (1 min)

Python and C#/.NET Support: Full framework support for both Python and C#/.NET implementations with consistent APIs
- Python packages |.NET source
Observability: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
- Python observability |.NET telemetry
Multiple Agent Provider Support: Support for various LLM providers with more being added continuously
- Python examples |.NET examples
Middleware: Flexible middleware system for request/response processing, exception handling, and custom pipelines
- Python middleware |.NET middleware

💬We want your feedback!

For bugs, please file aGitHub issue.

Quickstart

Basic Agent - Python

Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework

# pip install agent-framework --pre# Use `az login` to authenticate with Azure CLIimportosimportasynciofromagent_framework.azureimportAzureOpenAIResponsesClientfromazure.identityimportAzureCliCredentialasyncdefmain():# Initialize a chat agent with Azure OpenAI Responses# the endpoint, deployment name, and api version can be set via environment variables# or they can be passed in directly to the AzureOpenAIResponsesClient constructoragent=AzureOpenAIResponsesClient(# endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],# deployment_name=os.environ["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"],# api_version=os.environ["AZURE_OPENAI_API_VERSION"],# api_key=os.environ["AZURE_OPENAI_API_KEY"],  # Optional if using AzureCliCredentialcredential=AzureCliCredential(),# Optional, if using api_key    ).create_agent(name="HaikuBot",instructions="You are an upbeat assistant that writes beautifully.",    )print(awaitagent.run("Write a haiku about Microsoft Agent Framework."))if__name__=="__main__":asyncio.run(main())

Basic Agent - .NET

Create a simple Agent, using OpenAI Responses, that writes a haiku about the Microsoft Agent Framework

// dotnet add package Microsoft.Agents.AI.OpenAI --prereleaseusingSystem;usingOpenAI;// Replace the <apikey> with your OpenAI API key.varagent=newOpenAIClient("<apikey>").GetOpenAIResponseClient("gpt-4o-mini").CreateAIAgent(name:"HaikuBot",instructions:"You are an upbeat assistant that writes beautifully.");Console.WriteLine(awaitagent.RunAsync("Write a haiku about Microsoft Agent Framework."));

Create a simple Agent, using Azure OpenAI Responses with token based auth, that writes a haiku about the Microsoft Agent Framework

// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease// dotnet add package Azure.Identity// Use `az login` to authenticate with Azure CLIusingSystem;usingOpenAI;// Replace <resource> and gpt-4o-mini with your Azure OpenAI resource name and deployment name.varagent=newOpenAIClient(newBearerTokenPolicy(newAzureCliCredential(),"https://ai.azure.com/.default"),newOpenAIClientOptions(){Endpoint=newUri("https://<resource>.openai.azure.com/openai/v1")}).GetOpenAIResponseClient("gpt-4o-mini").CreateAIAgent(name:"HaikuBot",instructions:"You are an upbeat assistant that writes beautifully.");Console.WriteLine(awaitagent.RunAsync("Write a haiku about Microsoft Agent Framework."));

More Examples & Samples

Python

Getting Started with Agents: basic agent creation and tool usage
Chat Client Examples: direct chat client usage patterns
Getting Started with Workflows: basic workflow creation and integration with agents

.NET

Getting Started with Agents: basic agent creation and tool usage
Agent Provider Samples: samples showing different agent providers
Workflow Samples: advanced multi-agent patterns and workflow orchestration

Contributor Resources

Important Notes

If you use the Microsoft Agent Framework to build applications that operate with third-party servers or agents, you do so at your own risk. We recommend reviewing all data being shared with third-party servers or agents and being cognizant of third-party practices for retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization's Azure compliance and geographic boundaries and any related implications.