Azure OpenAI 响应代理

Microsoft代理框架支持创建使用 Azure OpenAI 响应 服务的代理。

入门

将所需的 NuGet 包添加到项目。

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

创建 Azure OpenAI 响应代理

首先需要创建客户端以连接到 Azure OpenAI 服务。

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 支持多个服务，这些服务都提供模型调用功能。 我们需要选择响应服务来创建基于响应的代理。

#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

最后，使用 CreateAIAgent 扩展方法在 ResponseClient 上创建代理。

AIAgent agent = responseClient.CreateAIAgent(
    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."));

使用代理

代理是标准的AIAgent，支持所有标准AIAgent操作。

有关如何运行和与代理交互的详细信息，请参阅 代理入门教程 。

配置

环境变量

在使用 Azure OpenAI 响应代理之前，需要设置以下环境变量：

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

（可选）还可以设置：

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

将 Agent Framework 包添加到项目：

pip install agent-framework --pre

入门

Authentication

Azure OpenAI 响应代理使用 Azure 凭据进行身份验证。 最简单的方法是在运行AzureCliCredential后使用az login：

from azure.identity import AzureCliCredential

credential = AzureCliCredential()

创建 Azure OpenAI 响应代理

基本代理创建

创建代理的最简单方法是使用 AzureOpenAIResponsesClient 和环境变量：

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

async def main():
    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).create_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())

显式配置

还可以显式提供配置，而不是使用环境变量：

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()
    ).create_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())

代理功能

函数工具

可以向 Azure OpenAI 响应代理提供自定义函数工具：

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

def get_weather(
    location: Annotated[str, Field(description="The location to get the weather for.")],
) -> str:
    """Get the weather for a given location."""
    return f"The weather in {location} is sunny with a high of 25°C."

async def main():
    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).create_agent(
        instructions="You are a helpful weather assistant.",
        tools=get_weather
    )

    result = await agent.run("What's the weather like in Seattle?")
    print(result.text)

asyncio.run(main())

代码解释器

Azure OpenAI 响应代理支持通过托管代码解释器执行代码：

import asyncio
from agent_framework import ChatAgent, HostedCodeInterpreterTool
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential

async def main():
    async with ChatAgent(
        chat_client=AzureOpenAIResponsesClient(credential=AzureCliCredential()),
        instructions="You are a helpful assistant that can write and execute Python code.",
        tools=HostedCodeInterpreterTool()
    ) as agent:
        result = await agent.run("Calculate the factorial of 20 using Python code.")
        print(result.text)

asyncio.run(main())

流式处理响应

使用流式处理生成时立即获取响应：

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

async def main():
    agent = AzureOpenAIResponsesClient(credential=AzureCliCredential()).create_agent(
        instructions="You are a helpful assistant."
    )

    print("Agent: ", end="", flush=True)
    async for chunk in agent.run_stream("Tell me a short story about a robot"):
        if chunk.text:
            print(chunk.text, end="", flush=True)
    print()

asyncio.run(main())

使用代理

代理是标准 BaseAgent 代理，支持所有标准代理操作。

有关如何运行和与代理交互的详细信息，请参阅 代理入门教程 。

后续步骤

OpenAI 聊天完成代理