Program.cs

// Import packages
using Microsoft.Extensions.Configuration;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Logging;
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.ChatCompletion;
using Microsoft.SemanticKernel.Connectors.OpenAI;

var config = new ConfigurationBuilder()
    .AddUserSecrets<Program>()
    .Build();

// Populate values from your OpenAI deployment
var modelId = config["ModelName"] ?? "";
var endpoint = config["BaseUrl"] ?? "";
var apiKey = config["ApiKey"] ?? "";

// Create a kernel with Azure OpenAI chat completion
#pragma warning disable SKEXP0010
var builder = Kernel.CreateBuilder().AddOpenAIChatCompletion(modelId: modelId, endpoint: new Uri(endpoint), apiKey: apiKey);
#pragma warning restore SKEXP0010

// Add enterprise components
builder.Services.AddLogging(services => services.AddConsole().SetMinimumLevel(LogLevel.Trace));

// Build the kernel
Kernel kernel = builder.Build();
var chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();

// Add a plugin (the LightsPlugin class is defined below)
kernel.Plugins.AddFromType<LightsPlugin>("Lights");


// Enable planning
OpenAIPromptExecutionSettings openAIPromptExecutionSettings = new()
{
    FunctionChoiceBehavior = FunctionChoiceBehavior.Auto(),
};

// Create a history store the conversation
var history = new ChatHistory();

// Initiate a back-and-forth chat
string? userInput;
do
{
    // Collect user input
    Console.Write("User > ");
    userInput = Console.ReadLine();

    // Add user input
    history.AddUserMessage(userInput);

    // Get the response from the AI
    var result = await chatCompletionService.GetChatMessageContentAsync(
        history,
        executionSettings: openAIPromptExecutionSettings,
        kernel: kernel);

    // Print the results
    Console.WriteLine("Assistant > " + result);

    // Add the message from the agent to the chat history
    history.AddMessage(result.Role, result.Content ?? string.Empty);
} while (userInput is not null);