ai-agents-for-beginners

🔍 Paggalugad sa Microsoft Agent Framework - Basic Agent (.NET)

📋 Mga Layunin sa Pagkatuto

Ang halimbawang ito ay naglalaman ng mga pangunahing konsepto ng Microsoft Agent Framework sa pamamagitan ng isang simpleng implementasyon ng agent sa .NET. Matututuhan mo ang mga pangunahing pattern ng agentic at mauunawaan kung paano gumagana ang mga intelligent agents gamit ang C# at ang .NET ecosystem.

Ano ang Iyong Matutuklasan

🎯 Mga Pangunahing Konseptong Tinalakay

Mga Prinsipyo ng Agentic Framework

Mga Teknikal na Komponent

🔧 Teknikal na Stack

Mga Pangunahing Teknolohiya

Mga Kakayahan ng Agent

📚 Paghahambing ng Framework

Ipinapakita ng halimbawang ito ang diskarte ng Microsoft Agent Framework kumpara sa iba pang mga agentic framework:

Tampok Microsoft Agent Framework Iba Pang Framework
Integrasyon Katutubong Microsoft ecosystem Iba-ibang compatibility
Kalinawan Malinis, intuitive na API Madalas komplikadong setup
Extensibility Madaling integrasyon ng tool Depende sa framework
Handa para sa Enterprise Ginawa para sa produksyon Nag-iiba depende sa framework

🚀 Pagsisimula

Mga Kinakailangan

Kinakailangang Environment Variables

# zsh/bash
export GH_TOKEN=<your_github_token>
export GH_ENDPOINT=https://models.github.ai/inference
export GH_MODEL_ID=openai/gpt-5-mini
# PowerShell
$env:GH_TOKEN = "<your_github_token>"
$env:GH_ENDPOINT = "https://models.github.ai/inference"
$env:GH_MODEL_ID = "openai/gpt-5-mini"

Halimbawang Code

Upang patakbuhin ang halimbawa ng code,

# zsh/bash
chmod +x ./02-dotnet-agent-framework.cs
./02-dotnet-agent-framework.cs

O gamit ang dotnet CLI:

dotnet run ./02-dotnet-agent-framework.cs

Tingnan ang 02-dotnet-agent-framework.cs para sa kumpletong code.

#!/usr/bin/dotnet run

#:package Microsoft.Extensions.AI@10.*
#:package Microsoft.Agents.AI.OpenAI@1.*-*

using System.ClientModel;
using System.ComponentModel;

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

using OpenAI;

// 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];
}

// Extract configuration from environment variables
// Retrieve the GitHub Models API endpoint, defaults to https://models.github.ai/inference if not specified
// Retrieve the model ID, defaults to openai/gpt-5-mini if not specified
// Retrieve the GitHub token for authentication, throws exception if not specified
var github_endpoint = Environment.GetEnvironmentVariable("GH_ENDPOINT") ?? "https://models.github.ai/inference";
var github_model_id = Environment.GetEnvironmentVariable("GH_MODEL_ID") ?? "openai/gpt-5-mini";
var github_token = Environment.GetEnvironmentVariable("GH_TOKEN") ?? throw new InvalidOperationException("GH_TOKEN is not set.");

// Configure OpenAI Client Options
// Create configuration options to point to GitHub Models endpoint
// This redirects OpenAI client calls to GitHub's model inference service
var openAIOptions = new OpenAIClientOptions()
{
    Endpoint = new Uri(github_endpoint)
};

// Initialize OpenAI Client with GitHub Models Configuration
// Create OpenAI client using GitHub token for authentication
// Configure it to use GitHub Models endpoint instead of OpenAI directly
var openAIClient = new OpenAIClient(new ApiKeyCredential(github_token), openAIOptions);

// 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
// Initialize complete agent pipeline: OpenAI client → Chat client → AI agent
// Configure agent with name, detailed instructions, and available tools
// This demonstrates the .NET agent creation pattern with full configuration
AIAgent agent = openAIClient
    .GetChatClient(github_model_id)
    .CreateAIAgent(
        name: AGENT_NAME,
        instructions: AGENT_INSTRUCTIONS,
        tools: [AIFunctionFactory.Create(GetRandomDestination)]
    );

// Create New Conversation Thread for Context Management
// Initialize a new conversation thread to maintain context across multiple interactions
// Threads enable the agent to remember previous exchanges and maintain conversational state
// This is essential for multi-turn conversations and contextual understanding
AgentThread thread = agent.GetNewThread();

// 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 thread parameter maintains conversation context for subsequent interactions
await foreach (var update in agent.RunStreamingAsync("Plan me a day trip", thread))
{
    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 threads and contextual understanding in .NET agents
await foreach (var update in agent.RunStreamingAsync("I don't like that destination. Plan me another vacation.", thread))
{
    await Task.Delay(10);
    Console.Write(update);
}

🎓 Mga Pangunahing Aral

  1. Arkitektura ng Agent: Ang Microsoft Agent Framework ay nagbibigay ng malinis, type-safe na diskarte sa paggawa ng AI agents sa .NET
  2. Integrasyon ng Tool: Ang mga function na may [Description] attributes ay nagiging magagamit na mga tool para sa agent
  3. Konteksto ng Usapan: Ang thread management ay nagbibigay-daan sa multi-turn na usapan na may ganap na kamalayan sa konteksto
  4. Pamamahala ng Konfigurasyon: Ang mga environment variable at secure na paghawak ng kredensyal ay sumusunod sa pinakamahusay na kasanayan ng .NET
  5. OpenAI Compatibility: Ang integrasyon ng GitHub Models ay gumagana nang maayos sa pamamagitan ng OpenAI-compatible APIs

🔗 Karagdagang Mga Mapagkukunan


Paunawa:
Ang dokumentong ito ay isinalin gamit ang AI translation service na Co-op Translator. Bagamat sinisikap naming maging tumpak, mangyaring tandaan na ang mga awtomatikong pagsasalin ay maaaring maglaman ng mga pagkakamali o hindi pagkakatugma. Ang orihinal na dokumento sa kanyang katutubong wika ang dapat ituring na opisyal na sanggunian. Para sa mahalagang impormasyon, inirerekomenda ang propesyonal na pagsasalin ng tao. Hindi kami mananagot sa anumang hindi pagkakaunawaan o maling interpretasyon na dulot ng paggamit ng pagsasaling ito.