# agent-framework **Repository Path**: mirrors_microsoft/agent-framework ## Basic Information - **Project Name**: agent-framework - **Description**: A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET. - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-10-02 - **Last Updated**: 2025-10-04 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README ![Microsoft Agent Framework](docs/assets/readme-banner.png) # Welcome to Microsoft Agent Framework! [![Microsoft Azure AI Foundry Discord](https://dcbadge.limes.pink/api/server/b5zjErwbQM?style=flat)](https://discord.gg/b5zjErwbQM) [![MS Learn Documentation](https://img.shields.io/badge/MS%20Learn-Documentation-blue)](https://learn.microsoft.com/en-us/agent-framework/) [![PyPI](https://img.shields.io/pypi/v/agent-framework)](https://pypi.org/project/agent-framework/) [![NuGet](https://img.shields.io/nuget/v/Microsoft.Agents.AI)](https://www.nuget.org/profiles/MicrosoftAgentFramework/) 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)

Watch the full Agent Framework introduction (30 min)

## 📋 Getting Started ### 📦 Installation Python ```bash 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 ```bash dotnet add package Microsoft.Agents.AI ``` ### 📚 Documentation - **[Overview](https://learn.microsoft.com/agent-framework/overview/agent-framework-overview)** - High level overview of the framework - **[Quick Start](https://learn.microsoft.com/agent-framework/tutorials/quick-start)** - Get started with a simple agent - **[Tutorials](https://learn.microsoft.com/agent-framework/tutorials/overview)** - Step by step tutorials - **[User Guide](https://learn.microsoft.com/en-us/agent-framework/user-guide/overview)** - In-depth user guide for building agents and workflows - **[Migration from Semantic Kernel](https://learn.microsoft.com/en-us/agent-framework/migration-guide/from-semantic-kernel)** - Guide to migrate from Semantic Kernel - **[Migration from AutoGen](https://learn.microsoft.com/en-us/agent-framework/migration-guide/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](./python/samples/getting_started/workflows/) | [.NET workflows](./dotnet/samples/GettingStarted/Workflows/) - **AF Labs**: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives - [Labs directory](./python/packages/lab/) - **DevUI**: Interactive developer UI for agent development, testing, and debugging workflows - [DevUI package](./python/packages/devui/)

See the DevUI in action

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](./python/packages/) | [.NET source](./dotnet/src/) - **Observability**: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging - [Python observability](./python/samples/getting_started/observability/) | [.NET telemetry](./dotnet/samples/GettingStarted/AgentOpenTelemetry/) - **Multiple Agent Provider Support**: Support for various LLM providers with more being added continuously - [Python examples](./python/samples/getting_started/agents/) | [.NET examples](./dotnet/samples/GettingStarted/AgentProviders/) - **Middleware**: Flexible middleware system for request/response processing, exception handling, and custom pipelines - [Python middleware](./python/samples/getting_started/middleware/) | [.NET middleware](./dotnet/samples/GettingStarted/Agents/Agent_Step14_Middleware/) ### 💬 **We want your feedback!** - For bugs, please file a [GitHub issue](https://github.com/microsoft/agent-framework/issues). ## Quickstart ### Basic Agent - Python Create a simple Azure Responses Agent that writes a haiku about the Microsoft Agent Framework ```python # pip install agent-framework --pre # Use `az login` to authenticate with Azure CLI import os import asyncio from agent_framework.azure import AzureOpenAIResponsesClient from azure.identity import AzureCliCredential async def main(): # 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 constructor agent = 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 AzureCliCredential credential=AzureCliCredential(), # Optional, if using api_key ).create_agent( name="HaikuBot", instructions="You are an upbeat assistant that writes beautifully.", ) print(await agent.run("Write a haiku about Microsoft Agent Framework.")) if __name__ == "__main__": asyncio.run(main()) ``` ### Basic Agent - .NET ```c# // dotnet add package Microsoft.Agents.AI.OpenAI --prerelease // dotnet add package Azure.AI.OpenAI // dotnet add package Azure.Identity // Use `az login` to authenticate with Azure CLI using System; using Azure.AI.OpenAI; using Azure.Identity; using Microsoft.Agents.AI; using OpenAI; var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")!; var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME")!; var agent = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()) .GetOpenAIResponseClient(deploymentName) .CreateAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully."); Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework.")); ``` ## More Examples & Samples ### Python - [Getting Started with Agents](./python/samples/getting_started/agents): basic agent creation and tool usage - [Chat Client Examples](./python/samples/getting_started/chat_client): direct chat client usage patterns - [Getting Started with Workflows](./python/samples/getting_started/workflows): basic workflow creation and integration with agents ### .NET - [Getting Started with Agents](./dotnet/samples/GettingStarted/Agents): basic agent creation and tool usage - [Agent Provider Samples](./dotnet/samples/GettingStarted/AgentProviders): samples showing different agent providers - [Workflow Samples](./dotnet/samples/GettingStarted/Workflows): advanced multi-agent patterns and workflow orchestration ## Contributor Resources - [Contributing Guide](./CONTRIBUTING.md) - [Python Development Guide](./python/DEV_SETUP.md) - [Design Documents](./docs/design) - [Architectural Decision Records](./docs/decisions) ## 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.