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)

Python

pip install agent-framework
# 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

• 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

Still have questions? Join our weekly office hours or ask questions in our Discord channel to get help from the team and other users.

• 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

• For bugs, please file a GitHub issue.

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

# pip install agent-framework
# Use `az login` to authenticate with Azure CLI
import os
import asyncio
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient
from azure.identity import AzureCliCredential


async def main():
    # Initialize a chat agent with Microsoft Foundry
    # the endpoint, deployment name, and api version can be set via environment variables
    # or they can be passed in directly to the FoundryChatClient constructor
    agent = Agent(
      client=FoundryChatClient(
          credential=AzureCliCredential(),
          # project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
          # model=os.environ["FOUNDRY_MODEL_DEPLOYMENT_NAME"],
      ),
      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())

Create a simple Agent, using Microsoft Foundry with token-based auth, that writes a haiku about the Microsoft Agent Framework

// dotnet add package Microsoft.Agents.AI.Foundry
// Use `az login` to authenticate with Azure CLI
using Azure.AI.Projects;
using Azure.Identity;
using System;
using Azure.AI.Projects;
using Azure.Identity;

var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";

var agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
    .AsAIAgent(model: deploymentName, name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));

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

// dotnet add package Microsoft.Agents.AI.OpenAI
using System;
using OpenAI;
using OpenAI.Responses;

// Replace the <apikey> with your OpenAI API key.
var agent = new OpenAIClient("<apikey>")
    .GetResponsesClient()
    .AsAIAgent(model: "gpt-5.4-mini", name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));

• Getting Started: progressive tutorial from hello-world to hosting
• Agent Concepts: deep-dive samples by topic (tools, middleware, providers, etc.)
• Workflows: workflow creation and integration with agents
• Hosting: A2A, Azure Functions, Durable Task hosting
• End-to-End: full applications, evaluation, and demos

• Getting Started: progressive tutorial from hello agent to hosting
• Agent Concepts: basic agent creation and tool usage
• Agent Providers: samples showing different agent providers
• Workflows: advanced multi-agent patterns and workflow orchestration
• Hosting: A2A, Durable Agents, Durable Workflows
• End-to-End: full applications and demos

Tip: DefaultAzureCredential is convenient for development but in production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid latency issues, unintended credential probing, and potential security risks from fallback mechanisms.

The samples typically read configuration from environment variables. Common required variables:

• Contributing Guide
• Python Development Guide
• Design Documents
• Architectural Decision Records