azure-openai-responses-agent

title: Azure OpenAI Responses Agents
description: Learn how to use Microsoft Agent Framework with Azure OpenAI Responses service.
zone_pivot_groups: programming-languages
author: westey-m
ms.topic: tutorial
ms.author: westey
ms.date: 09/24/2025
ms.service: agent-framework

Azure OpenAI Responses Agents

Microsoft Agent Framework supports creating agents that use the [Azure OpenAI Responses](/azure/ai-foundry/openai/how-to/responses) service.

::: zone pivot="programming-language-csharp"

Getting Started

Add the required NuGet packages to your project.

dotnet add package Azure.AI.OpenAI --prerelease
dotnet add package Azure.Identity
dotnet add package Microsoft.Agents.AI.OpenAI --prerelease

Create an Azure OpenAI Responses Agent

As a first step you need to create a client to connect to the Azure OpenAI service.

using System;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using OpenAI;

AzureOpenAIClient client = new AzureOpenAIClient(
    new Uri("https://<myresource>.openai.azure.com/"),
    new AzureCliCredential());

Azure OpenAI supports multiple services that all provide model calling capabilities. Pick the Responses service to create a Responses based agent.

#pragma warning disable OPENAI001 // Type is for evaluation purposes only and is subject to change or removal in future updates.
var responseClient = client.GetOpenAIResponseClient("gpt-4o-mini");
#pragma warning restore OPENAI001

Finally, create the agent using the `AsAIAgent` extension method on the `ResponseClient`.

AIAgent agent = responseClient.AsAIAgent(
    instructions: "You are good at telling jokes.",
    name: "Joker");

// Invoke the agent and output the text result.
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

Using the Agent

The agent is a standard `AIAgent` and supports all standard `AIAgent` operations.

For more information on how to run and interact with agents, see the [Agent getting started tutorials](../../../tutorials/overview.md).

::: zone-end ::: zone pivot="programming-language-python"

Configuration

Environment Variables

Before using Azure OpenAI Responses agents, you need to set up these environment variables:

export AZURE_OPENAI_ENDPOINT="https://<myresource>.openai.azure.com"
export AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME="gpt-4o-mini"

Optionally, you can also set:

export AZURE_OPENAI_API_VERSION="preview"  # Required for Responses API
export AZURE_OPENAI_API_KEY="<your-api-key>"  # If not using Azure CLI authentication

Installation

Add the Agent Framework package to your project:

pip install agent-framework-core --pre

Getting Started

Authentication

Azure OpenAI Responses agents use Azure credentials for authentication. The simplest approach is to use `AzureCliCredential` after running `az login`:

from azure.identity import AzureCliCredential

credential = AzureCliCredential()

Create an Azure OpenAI Responses Agent

Basic Agent Creation

The simplest way to create an agent is using the `AzureOpenAIResponsesClient` with environment variables:

import asyncio
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential

async def main():
    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).as_agent(
        instructions="You are good at telling jokes.",
        name="Joker"
    )

    result = await agent.run("Tell me a joke about a pirate.")
    print(result.text)

asyncio.run(main())

Explicit Configuration

You can also provide configuration explicitly instead of using environment variables:

import asyncio
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential

async def main():
    agent = AzureOpenAIResponsesClient(
        endpoint="https://<myresource>.openai.azure.com",
        deployment_name="gpt-4o-mini",
        api_version="preview",
        credential=AzureCliCredential()
    ).as_agent(
        instructions="You are good at telling jokes.",
        name="Joker"
    )

    result = await agent.run("Tell me a joke about a pirate.")
    print(result.text)

asyncio.run(main())

Agent Features

Reasoning Models

Azure OpenAI Responses agents support advanced reasoning models like o1 for complex problem-solving:

import asyncio
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential

async def main():
    agent = AzureOpenAIResponsesClient(
        deployment_name="o1-preview",  # Use reasoning model
        credential=AzureCliCredential()
    ).as_agent(
        instructions="You are a helpful assistant that excels at complex reasoning.",
        name="ReasoningAgent"
    )
    
    result = await agent.run("Solve this logic puzzle: If A > B, B > C, and C > D, and we know D = 5, B = 10, what can we determine about A?")
    print(result.text)

asyncio.run(main())

Structured Output

Get structured responses from Azure OpenAI Responses agents:

import asyncio
from typing import Annotated
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential
from pydantic import BaseModel, Field

class WeatherForecast(BaseModel):
    location: Annotated[str, Field(description="The location")]
    temperature: Annotated[int, Field(description="Temperature in Celsius")]
    condition: Annotated[str, Field(description="Weather condition")]
    humidity: Annotated[int, Field(description="Humidity percentage")]

async def main():
    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).as_agent(
        instructions="You are a weather assistant that provides structured forecasts.",
        response_format=WeatherForecast
    )
    
    result = await agent.run("What's the weather like in Pari