Gemini APIを Semantic Kernel で利用してみた【サンプルコード】

前提

Google AI StudioのGemini APIのページのGet API Keyで、APIキーを発行・取得済みであること

手順

コンソールアプリケーションの作成

dotnet new console -n GeminiSemanticKernelConsoleApp

プロジェクトディレクトリに移動

cd GeminiSemanticKernelConsoleApp

必要なパッケージのインストール

dotnet add package Microsoft.SemanticKernel
dotnet add package Microsoft.SemanticKernel.Connectors.Google --prerelease

Program.csを以下に変更

using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.ChatCompletion;
using Microsoft.SemanticKernel.Connectors.OpenAI;

Console.WriteLine(
    "============= Google AI - Gemini Chat Completion =============");

string geminiApiKey = "APIキーをここに記述";
string geminiModelId = "gemini-1.5-flash";

if (geminiApiKey is null || geminiModelId is null)
{
    Console.WriteLine("Gemini credentials not found. Skipping example.");
    return;
}

#pragma warning disable SKEXP0070
Kernel kernel = Kernel.CreateBuilder()
    .AddGoogleAIGeminiChatCompletion(
        modelId: geminiModelId,
        apiKey: geminiApiKey)
    .Build();
#pragma warning restore SKEXP0070

Console.WriteLine("======== Simple Chat ========");

var systemMessage = """
    You are an expert in finance and economics.
    """;
var chatHistory = new ChatHistory(systemMessage);
var chat = kernel.GetRequiredService<IChatCompletionService>();

OpenAIPromptExecutionSettings settings = new()
{
    MaxTokens = 100,
};

while (true)
{
    // your message
    Console.Write("user: ");
    var input = Console.ReadLine() ?? "";

    if (input == "exit") { break; }
    chatHistory.AddUserMessage(input);

    // bot assistant message
    var reply = await chat.GetChatMessageContentAsync(chatHistory, settings);
    chatHistory.Add(reply);
    Console.WriteLine($"{reply.Role}: {reply.Content}");
}