* Update Microsoft.Agents.AI.AzureAI for Azure.AI.Projects SDK 2.0.0 - Bump Azure.AI.Projects to 2.0.0-alpha.20260213.1 - Bump Azure.AI.Projects.OpenAI to 2.0.0-alpha.20260213.1 - Bump System.ClientModel to 1.9.0 (transitive dependency) - Switch both GetAgent and CreateAgentVersion to protocol methods with MEAI user-agent policy injection via RequestOptions - Migrate 29 CREATE-path tests from FakeAgentClient to HttpHandlerAssert pattern for real HTTP pipeline testing - Fix StructuredOutputDefinition constructor (BinaryData -> IDictionary) - Fix responses endpoint path (openai/responses -> /responses) - Add local-packages NuGet source for pre-release nupkgs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update Azure.AI.Projects to 2.0.0-beta.1 from NuGet.org - Update Azure.AI.Projects and Azure.AI.Projects.OpenAI to 2.0.0-beta.1 - Remove local-packages NuGet source (packages now on nuget.org) - Fix MemorySearchTool -> MemorySearchPreviewTool rename - Fix RedTeams.CreateAsync ambiguous call - Fix CreateAgentVersion/Async signature change (BinaryData -> string) - Suppress AAIP001 experimental warning for WorkflowAgentDefinition Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Move s_modelWriterOptionsWire field before methods that use it Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix flaky test: prevent spurious workflow_invoke Activity on timeout wake-up The StreamingRunEventStream run loop uses a 1-second timeout on WaitForInputAsync. When the timeout fires before the consumer calls StopAsync, the loop would create a spurious workflow_invoke Activity even though no actual input was provided. This caused the WorkflowRunActivity_IsStopped_Streaming_OffThread_MultiTurnAsync test to intermittently fail (expecting 2 activities but finding 3). Fix: guard the loop body with a HasUnprocessedMessages check. On timeout wake-ups with no work, the loop waits again without creating an activity or changing the run status. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix epoch race condition causing unit tests to hang on net10.0 and net472 The HasUnprocessedMessages guard (previous commit) correctly prevents spurious workflow_invoke Activity creation on timeout wake-ups, but exposed a latent race in the epoch-based signal filtering. The race: when the run loop processes messages quickly and calls Interlocked.Increment(ref _completionEpoch) before the consumer calls TakeEventStreamAsync, the consumer reads the already-incremented epoch and sets myEpoch = epoch + 1. This causes the consumer to skip the valid InternalHaltSignal (its epoch < myEpoch) and block forever waiting for a signal that will never arrive (since the guard prevents spurious signal generation). Fix: read _completionEpoch without +1. The +1 was originally needed to filter stale signals from timeout-driven spurious loop iterations, but those no longer exist thanks to the HasUnprocessedMessages guard. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Revert "Fix epoch race condition causing unit tests to hang on net10.0 and net472" This reverts commit6ce7f01be8. * Revert "Fix flaky test: prevent spurious workflow_invoke Activity on timeout wake-up" This reverts commit98963e17f2. * Skip hanging multi-turn declarative integration tests The ValidateMultiTurnAsync tests (ConfirmInput.yaml, RequestExternalInput.yaml) hang indefinitely in CI, blocking the merge queue. The hang is SDK-independent (reproduces with both Azure.AI.Projects 1.2.0-beta.5 and 2.0.0-beta.1) and is a pre-existing issue in the declarative workflow multi-turn test logic. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove unused using directive in IntegrationTest.cs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore Azure.AI.Projects 2.0.0-beta.1 version bump The merge from main accidentally reverted the package versions back to 1.2.0-beta.5. This is the primary change of this PR. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address merge conflict * Skip flaky WorkflowRunActivity_IsStopped_Streaming_OffThread_MultiTurnAsync test Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Skip CheckSystem test cases temporarily Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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
Still have questions? Join our weekly office hours or ask questions in our Discord channel to get help from the team and other users.
✨ Highlights
- Graph-based Workflows: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
- AF Labs: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
- DevUI: Interactive developer UI for agent development, testing, and debugging workflows
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
- Observability: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
- Multiple Agent Provider Support: Support for various LLM providers with more being added continuously
- Middleware: Flexible middleware system for request/response processing, exception handling, and custom pipelines
💬 We want your feedback!
- For bugs, please file a GitHub 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 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
).as_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
Create a simple Agent, using OpenAI Responses, that writes a haiku about the Microsoft Agent Framework
// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
using Microsoft.Agents.AI;
using OpenAI;
using OpenAI.Responses;
// Replace the <apikey> with your OpenAI API key.
var agent = new OpenAIClient("<apikey>")
.GetResponsesClient("gpt-4o-mini")
.AsAIAgent(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 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 CLI
using System.ClientModel.Primitives;
using Azure.Identity;
using Microsoft.Agents.AI;
using OpenAI;
using OpenAI.Responses;
// Replace <resource> and gpt-4o-mini with your Azure OpenAI resource name and deployment name.
var agent = new OpenAIClient(
new BearerTokenPolicy(new AzureCliCredential(), "https://ai.azure.com/.default"),
new OpenAIClientOptions() { Endpoint = new Uri("https://<resource>.openai.azure.com/openai/v1") })
.GetResponsesClient("gpt-4o-mini")
.AsAIAgent(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: progressive tutorial from hello-world to hosting
- Agent Concepts: deep-dive samples by topic (tools, middleware, providers, etc.)
- Getting Started with Workflows: 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.
