# 🌍 AI Travel Agent with Microsoft Agent Framework (.NET)

## 📋 Scenario Overview

This example demonstrates how to build an intelligent travel planning agent using the Microsoft Agent Framework for .NET. The agent can automatically generate personalized day-trip itineraries for random destinations around the world.

### Key Capabilities:

- 🎲 **Random Destination Selection**: Uses a custom tool to pick vacation spots
- 🗺️ **Intelligent Trip Planning**: Creates detailed day-by-day itineraries
- 🔄 **Real-time Streaming**: Supports both immediate and streaming responses
- 🛠️ **Custom Tool Integration**: Demonstrates how to extend agent capabilities

## 🔧 Technical Architecture

### Core Technologies

- **Microsoft Agent Framework**: Latest .NET implementation for AI agent development
- **Azure OpenAI (Responses API)**: Uses the Azure OpenAI Responses API for model inference
- **Azure Identity**: Secure sign-in via `AzureCliCredential` (`az login`)
- **Secure Configuration**: Environment-based endpoint management

### Key Components

1. **AIAgent**: The main agent orchestrator that handles conversation flow
2. **Custom Tools**: `GetRandomDestination()` function available to the agent
3. **Responses Client**: Azure OpenAI Responses-based conversation interface
4. **Streaming Support**: Real-time response generation capabilities

### Integration Pattern

```mermaid
graph LR
    A[User Request] --> B[AI Agent]
    B --> C[Azure OpenAI (Responses API)]
    B --> D[GetRandomDestination Tool]
    C --> E[Travel Itinerary]
    D --> E
```

## 🚀 Getting Started

### Prerequisites

- [.NET 10 SDK](https://dotnet.microsoft.com/download/dotnet/10.0) or higher
- An [Azure subscription](https://azure.microsoft.com/free/) with an Azure OpenAI resource and a model deployment
- The [Azure CLI](https://learn.microsoft.com/cli/azure/install-azure-cli) — sign in with `az login`

### Required Environment Variables

```bash
# zsh/bash
export AZURE_OPENAI_ENDPOINT=https://<your-resource>.openai.azure.com
export AZURE_OPENAI_DEPLOYMENT=gpt-5-mini
# Then sign in so AzureCliCredential can get a token
az login
```

```powershell
# PowerShell
$env:AZURE_OPENAI_ENDPOINT = "https://<your-resource>.openai.azure.com"
$env:AZURE_OPENAI_DEPLOYMENT = "gpt-5-mini"
# Then sign in so AzureCliCredential can get a token
az login
```

### Sample Code

To run the code example,

```bash
# zsh/bash
chmod +x ./01-dotnet-agent-framework.cs
./01-dotnet-agent-framework.cs
```

Or using the dotnet CLI:

```bash
dotnet run ./01-dotnet-agent-framework.cs
```

See [`01-dotnet-agent-framework.cs`](./01-dotnet-agent-framework.cs) for the complete code.

```csharp
#!/usr/bin/dotnet run

#:package Microsoft.Extensions.AI@10.4.1
#:package Microsoft.Agents.AI.OpenAI@1.1.0
#: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());

// Create AI Agent with Travel Planning Capabilities
// Get the Responses client for the specified deployment and create the AI agent
// Configure agent with travel planning instructions and random destination tool
// The agent can now plan trips using the GetRandomDestination function
AIAgent agent = azureClient
    .GetChatClient(deployment)
    .AsAIAgent(
        instructions: "You are a helpful AI Agent that can help plan vacations for customers at random destinations",
        tools: [AIFunctionFactory.Create(GetRandomDestination)]
    );

// Execute Agent: Plan a Day Trip
// Run the agent with streaming enabled for real-time response display
// Shows the agent's thinking and response as it generates the content
// Provides better user experience with immediate feedback
await foreach (var update in agent.RunStreamingAsync("Plan me a day trip"))
{
    await Task.Delay(10);
    Console.Write(update);
}
```

## 🎓 Key Takeaways

1. **Agent Architecture**: The Microsoft Agent Framework provides a clean, type-safe approach to building AI agents in .NET
2. **Tool Integration**: Functions decorated with `[Description]` attributes become available tools for the agent
3. **Configuration Management**: Environment variables and secure credential handling follow .NET best practices
4. **Azure OpenAI Responses API**: The agent uses the Azure OpenAI Responses API through the Azure.AI.OpenAI SDK

## 🔗 Additional Resources

- [Microsoft Agent Framework Documentation](https://learn.microsoft.com/agent-framework)
- [Azure OpenAI in Microsoft Foundry](https://learn.microsoft.com/azure/ai-services/openai/)
- [Microsoft.Extensions.AI](https://learn.microsoft.com/dotnet/ai/microsoft-extensions-ai)
- [.NET Single File Apps](https://devblogs.microsoft.com/dotnet/announcing-dotnet-run-app)