ai-agents-for-beginners

🛠️ 使用 Azure OpenAI(Responses API)進階工具使用示範 (.NET)

📋 學習目標

本筆記本示範如何在 .NET 中使用 Microsoft Agent Framework 與 Azure OpenAI(Responses API)整合企業等級的工具模式。您將學會建構具多種專業化工具的高級代理,利用 C# 強類型與 .NET 企業級功能。

您將掌握的進階工具功能

🎯 .NET 工具架構優勢

企業工具特色

生產環境準備模式

🔧 技術架構

核心 .NET 工具組件

工具執行流程

graph LR
    A[用戶請求] --> B[代理分析]
    B --> C[工具選擇]
    C --> D[類型驗證]
    B --> E[參數綁定]
    E --> F[工具執行]
    C --> F
    F --> G[結果處理]
    D --> G
    G --> H[回應]

🛠️ 工具類別與模式

1. 資料處理工具

2. 整合工具

3. 實用工具

準備好用 .NET 建造具強大類型安全工具能力的企業等級代理了嗎?讓我們架構一些專業級解決方案吧!🏢⚡

🚀 開始使用

先決條件

必要環境變數

# zsh/bash
export AZURE_OPENAI_ENDPOINT=https://<your-resource>.openai.azure.com
export AZURE_OPENAI_DEPLOYMENT=gpt-5-mini
# 然後登入,令 AzureCliCredential 可以取得權杖
az login
# PowerShell
$env:AZURE_OPENAI_ENDPOINT = "https://<your-resource>.openai.azure.com"
$env:AZURE_OPENAI_DEPLOYMENT = "gpt-5-mini"
# 然後登入,讓 AzureCliCredential 可以取得令牌
az login

範例程式碼

執行範例程式碼,

# zsh/bash
chmod +x ./04-dotnet-agent-framework.cs
./04-dotnet-agent-framework.cs

或使用 dotnet CLI:

dotnet run ./04-dotnet-agent-framework.cs

完整程式碼請參閱 04-dotnet-agent-framework.cs

#!/usr/bin/dotnet run

#:package Microsoft.Extensions.AI@10.*
#:package Microsoft.Agents.AI.OpenAI@1.*-*
#:package Azure.AI.OpenAI@2.1.0
#:package Azure.Identity@1.13.1

using System.ComponentModel;

using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;

using Azure.AI.OpenAI;
using Azure.Identity;

// Tool Function: Random Destination Generator
// This static method will be available to the agent as a callable tool
// The [Description] attribute helps the AI understand when to use this function
// This demonstrates how to create custom tools for AI agents
[Description("Provides a random vacation destination.")]
static string GetRandomDestination()
{
    // List of popular vacation destinations around the world
    // The agent will randomly select from these options
    var destinations = new List<string>
    {
        "Paris, France",
        "Tokyo, Japan",
        "New York City, USA",
        "Sydney, Australia",
        "Rome, Italy",
        "Barcelona, Spain",
        "Cape Town, South Africa",
        "Rio de Janeiro, Brazil",
        "Bangkok, Thailand",
        "Vancouver, Canada"
    };

    // Generate random index and return selected destination
    // Uses System.Random for simple random selection
    var random = new Random();
    int index = random.Next(destinations.Count);
    return destinations[index];
}

// Azure OpenAI with the Responses API (stable v1 endpoint). Sign in with `az login`.
var azureEndpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
    ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deployment = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT") ?? "gpt-5-mini";

var azureClient = new AzureOpenAIClient(new Uri(azureEndpoint), new AzureCliCredential());

// Define Agent Identity and Comprehensive Instructions
// Agent name for identification and logging purposes
var AGENT_NAME = "TravelAgent";

// Detailed instructions that define the agent's personality, capabilities, and behavior
// This system prompt shapes how the agent responds and interacts with users
var AGENT_INSTRUCTIONS = """
You are a helpful AI Agent that can help plan vacations for customers.

Important: When users specify a destination, always plan for that location. Only suggest random destinations when the user hasn't specified a preference.

When the conversation begins, introduce yourself with this message:
"Hello! I'm your TravelAgent assistant. I can help plan vacations and suggest interesting destinations for you. Here are some things you can ask me:
1. Plan a day trip to a specific location
2. Suggest a random vacation destination
3. Find destinations with specific features (beaches, mountains, historical sites, etc.)
4. Plan an alternative trip if you don't like my first suggestion

What kind of trip would you like me to help you plan today?"

Always prioritize user preferences. If they mention a specific destination like "Bali" or "Paris," focus your planning on that location rather than suggesting alternatives.
""";

// Create AI Agent with Advanced Travel Planning Capabilities
// Get the Responses client for the deployment and create the AI agent
// Configure agent with name, detailed instructions, and available tools
// This demonstrates the .NET agent creation pattern with full configuration
AIAgent agent = azureClient
    .GetChatClient(deployment)
    .AsAIAgent(
        name: AGENT_NAME,
        instructions: AGENT_INSTRUCTIONS,
        tools: [AIFunctionFactory.Create(GetRandomDestination)]
    );

// Create New Conversation Session for Context Management
// Initialize a new conversation session to maintain context across multiple interactions
// Sessions enable the agent to remember previous exchanges and maintain conversational state
// This is essential for multi-turn conversations and contextual understanding
await using var session = await agent.CreateSessionAsync();

// Execute Agent: First Travel Planning Request
// Run the agent with an initial request that will likely trigger the random destination tool
// The agent will analyze the request, use the GetRandomDestination tool, and create an itinerary
// Using the session parameter maintains conversation context for subsequent interactions
await foreach (var update in agent.RunStreamingAsync("Plan me a day trip", session))
{
    await Task.Delay(10);
    Console.Write(update);
}

Console.WriteLine();

// Execute Agent: Follow-up Request with Context Awareness
// Demonstrate contextual conversation by referencing the previous response
// The agent remembers the previous destination suggestion and will provide an alternative
// This showcases the power of conversation sessions and contextual understanding in .NET agents
await foreach (var update in agent.RunStreamingAsync("I don't like that destination. Plan me another vacation.", session))
{
    await Task.Delay(10);
    Console.Write(update);
}

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