public static string getConnStr(string connStrName = "Default")
{
    // 每次呼叫都會執行 string.Format、Base64 解碼與 AES 解密
    return getDecryptStr(_configuration.GetValue<string>(string.Format("ConnectionStrings:{0}", connStrName)));
}

public string Decrypt(string encryptedText)
{
    // 1. 這裡配置了一次全新的 byte[]
    var fullData = Convert.FromBase64String(encryptedText);

    // 2. LINQ 的 Take 與 Skip 每次都會在託管堆積（Heap）上
    // 「重新配置」並「複製」出兩份全新的 byte[] 陣列！
    byte[] iv = fullData.Take(16).ToArray();        // 又配置一次 byte[]
    byte[] cipherBytes = fullData.Skip(16).ToArray(); // 又配置一次 byte[]

    using var aes = Aes.Create();
    aes.Key = rgbKey;
    aes.IV = iv;
    // ... 後續解密流處理 ...

    // 3. 這裡又配置了全新的字串物件
    return sr.ReadToEnd();
}

private static readonly ConcurrentDictionary<string, Lazy<string>> _connStrCache =
    new ConcurrentDictionary<string, Lazy<string>>();

public static string getConnStr(string connStrName = "Default")
{
    var lazy = _connStrCache.GetOrAdd(connStrName, key =>
        new Lazy<string>(() =>
        {
            IConfigurationRoot configuration = CommonHelper.GetConfigurationRoot();
            if (configuration == null) return string.Empty;

            string encrypted = configuration.GetValue<string>($"ConnectionStrings:{key}");
            return getDecryptStr(encrypted);
        }, LazyThreadSafetyMode.ExecutionAndPublication));

    return lazy.Value;
}

public string Decrypt(string encryptedText)
{
    byte[] fullData = Convert.FromBase64String(encryptedText);
    ReadOnlySpan<byte> data = fullData;

    ReadOnlySpan<byte> ivSpan = data.Slice(0, 16);
    ReadOnlySpan<byte> cipherSpan = data.Slice(16);

    byte[] iv = ivSpan.ToArray();          // Aes.IV 需要 byte[]
    byte[] cipherBytes = cipherSpan.ToArray();

    using var aes = Aes.Create();
    aes.Key = rgbKey;
    aes.IV = iv;

    // ... 後續解密流處理 ...
}

// 舊的寫法：將 Stream 轉成 byte[]
public static byte[] CopyToByte(this Stream input)
{
    if (input == null) return null;
    if (input is MemoryStream) return (input as MemoryStream).ToArray();

    using (MemoryStream ms = new MemoryStream())
    {
        if (input.CanSeek) input.Position = 0;
        input.CopyTo(ms);
        return ms.ToArray(); // 內部複製一份全新 byte[] 回傳
    }
}

public static class StreamPool
{
    // Manager 本身是執行緒安全的，全域宣告一個即可
    public static readonly RecyclableMemoryStreamManager Manager = new RecyclableMemoryStreamManager();
}

public static Stream GetRecyclableStream(Stream inputStream)
{
    if (inputStream == null) return null;

    // 1. 從池子裡借一個專屬的記憶體流 (不寫 using，改由外部釋放)
    var memoryStream = StreamPool.Manager.GetStream();

    try
    {
        if (inputStream.CanSeek) inputStream.Position = 0;

        // 2. 將資料複製到池化 MemoryStream 中
        inputStream.CopyTo(memoryStream);

        // 3. 移回開頭，這樣外部讀取才能從第 0 個位元組開始
        memoryStream.Position = 0;

        return memoryStream;
    }
    catch
    {
        memoryStream.Dispose(); // 發生異常時才由內部確保釋放
        throw;
    }
}

[HttpGet("download")]
public IActionResult DownloadFile()
{
    Stream memoryInputStream = 原本的 MemoryStream ;

    // 轉換成高效能的池化 Stream
    Stream fileStream = GetRecyclableStream(memoryInputStream);

    // ASP.NET Core 框架會在檔案傳輸完成後，自動幫你呼叫 fileStream.Dispose()
    // 進而觸發機制，將記憶體完美還給 StreamPool
    return File(fileStream, "application/pdf", "report.pdf");
}

builder.Services.Configure<IdentityPasskeyOptions>(options =>
{
    options.ServerDomain = "yourdomain.com"; 
});

// Program.cs
builder.Services.AddDefaultIdentity<IdentityUser>(options =>
{
    // 測試用，所以先關掉驗證 Email 的設定
    options.SignIn.RequireConfirmedAccount = false;
    // 重要：必須指定 Version3 才能使用 Passkey 功能
    options.Stores.SchemaVersion = IdentitySchemaVersions.Version3;
})
.AddEntityFrameworkStores<ApplicationDbContext>()
.AddSignInManager()
.AddDefaultTokenProviders();

builder.Services.Configure<IdentityPasskeyOptions>(options =>
{
    options.ServerDomain = "localhost";            // 伺服器網域
    options.AuthenticatorTimeout = TimeSpan.FromMinutes(3); // 等待逾時
    options.UserVerificationRequirement = "required";       // 強制使用者驗證（生物辨識/PIN）
    options.ResidentKeyRequirement = "preferred";
});

using Microsoft.AspNetCore.Mvc;
using Microsoft.AspNetCore.Mvc.RazorPages;
using Microsoft.AspNetCore.Identity;
using Microsoft.AspNetCore.WebUtilities;

public class IndexModel : PageModel
{
    private readonly UserManager<IdentityUser> _userManager;
    private readonly SignInManager<IdentityUser> _signInManager;
    private readonly ILogger<IndexModel> _logger;
    public IList<UserPasskeyInfo> Passkeys { get; private set; } = [];

    public IndexModel(UserManager<IdentityUser> userManager
    , SignInManager<IdentityUser> signInManager
    , ILogger<IndexModel> logger)
    {
        _userManager = userManager;
        _signInManager = signInManager;
        _logger = logger;
    }

    public async Task OnGetAsync()
    {
        if (User.Identity?.IsAuthenticated != true) return;

        var user = await _userManager.GetUserAsync(User);
        if (user is null) return;

        // 查詢該使用者所有已註冊的 Passkey
        Passkeys = await _userManager.GetPasskeysAsync(user);
    }
}

public async Task<IActionResult> OnPostPasskeyCreationOptions()
{
    if (User.Identity?.IsAuthenticated != true) return Unauthorized();

    var user = await _userManager.GetUserAsync(User);
    if (user is null) return NotFound();

    var userId = await _userManager.GetUserIdAsync(user);
    var userName = await _userManager.GetUserNameAsync(user);

    // 向 SignInManager 取得 WebAuthn 註冊選項 JSON
    // 此方法會查詢 DB 取得既有 Passkey，並填入 excludeCredentials 避免重複
    var optionsJson = await _signInManager.MakePasskeyCreationOptionsAsync(new PasskeyUserEntity
    {
        Id = userId,
        Name = userName,
        DisplayName = userName
    });

    return Content(optionsJson, "application/json");
}

public async Task<IActionResult> OnPostPasskeyRegistration([FromBody] string credentialJson)
{
    if (User.Identity?.IsAuthenticated != true) return Unauthorized();

    var user = await _userManager.GetUserAsync(User);
    if (user is null) return NotFound();

    // 驗證 attestation（確認 challenge、origin、rpId 等都正確）
    var attestationResult = await _signInManager.PerformPasskeyAttestationAsync(credentialJson);

    if (!attestationResult.Succeeded)
        return BadRequest($"Attestation failed: {attestationResult.Failure?.Message}");

    // 將 Passkey 公鑰等資料寫入 AspNetUserPasskeys 資料表
    var addResult = await _userManager.AddOrUpdatePasskeyAsync(user, attestationResult.Passkey);

    if (!addResult.Succeeded)
        return BadRequest("Failed to store passkey");

    return new JsonResult(new { message = "Passkey registered successfully" });
}

public async Task<IActionResult> OnPostPasskeyRequestOptions()
{
    // 傳 null 表示不限定使用者（讓裝置自行選擇 discoverable credential）
    var optionsJson = await _signInManager.MakePasskeyRequestOptionsAsync(null);
    return Content(optionsJson, "application/json");
}

public async Task<IActionResult> OnPostPasskeySignIn([FromBody] string credentialJson)
{
    // PasskeySignInAsync 內部呼叫 PerformPasskeyAssertionAsync，驗證後自動建立 Session
    var result = await _signInManager.PasskeySignInAsync(credentialJson);

    if (result.Succeeded)
        return new OkObjectResult(new { message = "Sign in successful" });

    return Unauthorized();
}

public async Task<IActionResult> OnPostDeletePasskey([FromBody] string credentialIdBase64Url)
{
    if (User.Identity?.IsAuthenticated != true) return Unauthorized();

    var user = await _userManager.GetUserAsync(User);
    if (user is null) return NotFound();

    // credentialId 以 Base64Url 格式傳遞，需先解碼
    byte[] credentialId = WebEncoders.Base64UrlDecode(credentialIdBase64Url);

    var result = await _userManager.RemovePasskeyAsync(user, credentialId);

    if (!result.Succeeded) return BadRequest("Failed to delete passkey");

    return new JsonResult(new { message = "Passkey deleted successfully" });
}

// 開發環境使用，請依實際狀況進行調整
builder.Services.AddCors(options =>
{
    options.AddPolicy("AllowAll", policy =>
    {
        policy.AllowAnyOrigin()
              .AllowAnyHeader()
              .AllowAnyMethod();
    });

});

var tenantId = "<YOUR_TENANT_ID>";
var authorityV2 = $"https://login.microsoftonline.com/{tenantId}/v2.0";
var mcpScope = "https://mcpserver.公司domain/mcp/<YOUR_SCOPE_NAME>";

builder.Services.AddAuthentication(options =>
{
    options.DefaultAuthenticateScheme = JwtBearerDefaults.AuthenticationScheme;
    options.DefaultChallengeScheme = McpAuthenticationDefaults.AuthenticationScheme;
}).AddJwtBearer(options =>
{
    options.Authority = authorityV2;
    options.TokenValidationParameters = new TokenValidationParameters
    {
        ValidateIssuer = true,
        ValidateAudience = true,
        ValidateLifetime = true,
        ValidateIssuerSigningKey = true,
        ValidAudiences = new[]
        {
            "<YOUR_MCP_SERVER_APP_CLIENT_ID>"
        },
        ValidIssuers = new[]
            {
                authorityV2
            },

        NameClaimType = "name",
        RoleClaimType = "roles"
    };

    options.Events = new JwtBearerEvents
    {
        OnTokenValidated = context =>
        {
            var name = context.Principal?.Identity?.Name ?? "unknown";
            var email = context.Principal?.FindFirstValue("preferred_username") ?? "unknown";
            Console.WriteLine($"Token validated for: {name} ({email})");
            return Task.CompletedTask;
        },
        OnAuthenticationFailed = context =>
        {
            Console.WriteLine($"Authentication failed: {context.Exception.Message}");
            return Task.CompletedTask;
        },
        OnChallenge = context =>
        {
            Console.WriteLine($"Challenging client to authenticate with Entra ID");
            return Task.CompletedTask;
        }
    };
})
.AddMcp(options =>
{
    options.ResourceMetadata = new()
    {
        AuthorizationServers = { authorityV2 },
        ScopesSupported = { mcpScope },
    };
});

builder.Services.AddAuthorization();

var mcpBuilder = builder.Services.AddMcpServer()
    .WithHttpTransport(options =>
    {
        options.Stateless = true;
    })
    .WithResourcesFromAssembly()
    .WithToolsFromAssembly()
    .WithPromptsFromAssembly();

mcpBuilder.AddAuthorizationFilters();

var app = builder.Build();

// Configure the HTTP request pipeline.

app.UseHttpsRedirection();
app.UseCors("AllowAll");

app.UseAuthentication();
app.UseAuthorization();

// api
app.MapGet("/api/healthy", () => "Healthy");

app.MapGet("/api/docs", () =>
{
    return new
    {
        name = "HR MCP Server",
        description = "提供請假、行事曆、文件等企業服務的 MCP 伺服器",
        version = "1.0.0",
        tools = new[] { "RequestTimeOff", "PlanTimeOff", "GetCalendarInfo" },
        scopes = new[] { mcpScope }
    };
});

app.MapMcp("/mcp")
    .RequireAuthorization();

app.Run();

string dbFile = "mydb.sqlite";
string connectionString = $"Data Source={dbFile}";

using var connection = new SqliteConnection(connectionString);

// 查詢 table_1
string sql = "SELECT Id, Name FROM table_1 WHERE Name=@name";
string name = args[0];

var p1 = new DynamicParameters();
p1.Add("name", name);
IEnumerable<Table1> results = connection.Query<Table1>(sql, p1);


public class Table1
{
    public int Id { get; set; }
    public string Name { get; set; }
}

IEnumerable<Table1> results = connection.Query<Table1>(sql, new { name });

using Microsoft.SemanticKernel;
using System.ComponentModel;


public class WeatherPlugin
{
    private static readonly string[] Conditions = { "晴天","多雲","下雨", "豪雨" };
    private static readonly Random Random = new Random();


    [KernelFunction]
    [Description("取得特定日期及特定地點的天氣預測")]
    public string GetWeatherForecastForLocationAndDate([Description("取得特定日期及特定地點的天氣預測的參數")] WeatherRequest weatherRequest)
    {
        var condition = Conditions[Random.Next(Conditions.Length)];
        var highTemp = Random.Next(0, 40);
        var lowTemp = Random.Next(10, 20);

        return $"在 {weatherRequest.Date.ToShortDateString()}，{weatherRequest.Location} 的天氣預測是 {condition}，氣溫方面最高 {highTemp}°F，最低 {lowTemp}°F。";
    }
}

public class WeatherRequest
{
    [Description("查詢天氣的地點")]
    public string Location { get; set; }

    [Description("查詢天氣的日期")]
    public DateTime Date { get; set; }
}

using Microsoft.SemanticKernel;
using System.Text;

var apikey = "你的 openai api key";
var modelId = "gpt-4.1";
// 建立 KernelBuilder
var kernelBuilder = Kernel.CreateBuilder();
// 加入 OpenAI ChatCompletion 服務
var kernel = kernelBuilder
            .AddOpenAIChatCompletion(modelId, apikey)
            .Build();
// 註冊 plugin
kernel.ImportPluginFromType<WeatherPlugin>();
OpenAIPromptExecutionSettings settings = new() { ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions };
Console.OutputEncoding = UTF8Encoding.UTF8;
Console.InputEncoding = UTF8Encoding.UTF8;
// 直接輸出結果
Console.WriteLine(await kernel.InvokePromptAsync("今2024/9/1 在台中的天氣如何?", new(settings)));

using Microsoft.SemanticKernel;
using System.Text;
using Microsoft.SemanticKernel.Plugins.Core;

var apikey = "你的 openai api key";
var modelId = "gpt-4.1";
// 建立 KernelBuilder
var kernelBuilder = Kernel.CreateBuilder();
// 加入 OpenAI ChatCompletion 服務
var kernel = kernelBuilder
            .AddOpenAIChatCompletion(modelId, apikey)
            .Build();
// 註冊 plugin
kernel.ImportPluginFromType<ConversationSummaryPlugin>();
OpenAIPromptExecutionSettings settings = new() { ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions };
Console.OutputEncoding = UTF8Encoding.UTF8;
Console.InputEncoding = UTF8Encoding.UTF8;
var chatTranscript = """
George：Mary，我在想我們是不是應該跟銀行借點錢來擴大生意。

Mary：嗯，我也有這個想法。不過你打算借多少？

George：大概新台幣兩百萬，主要是要添購新的設備。

Mary：兩百萬不算小數目，你覺得我們的還款能力足夠嗎？

George：以目前的營收，加上新設備帶來的產能，應該能在五年內還清。

Mary：那利率部分你有查過嗎？現在銀行大概是年利率 2.5% 到 3%。

George：我看過一些資料，如果有公司財報跟資產擔保，應該可以談到 2.2% 左右。

Mary：聽起來不錯，但我們還需要準備好貸款計畫書，銀行才會比較容易審核。

George：對，我打算先整理最近三年的財務報表，還有未來三年的營運計畫。

Mary：好，那我來準備市場分析的部分，讓銀行看到我們成長的潛力。

George：太好了！等資料都準備好，我們就一起去銀行洽談吧。
""";
Console.WriteLine(await kernel.InvokePromptAsync($"請總結以下的對話內容，{chatTranscript}", new(settings)));

using Microsoft.SemanticKernel;
using System.Text;
using Microsoft.SemanticKernel.Plugins.Core;

var apikey = "你的 openai api key";
var modelId = "gpt-4.1";
// 建立 KernelBuilder
var kernelBuilder = Kernel.CreateBuilder();
// 加入 OpenAI ChatCompletion 服務
var kernel = kernelBuilder
            .AddOpenAIChatCompletion(modelId, apikey)
            .Build();
OpenAIPromptExecutionSettings settings = new() { ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions };
Console.OutputEncoding = UTF8Encoding.UTF8;
Console.InputEncoding = UTF8Encoding.UTF8;

// 註冊 plugin
var prompts = kernel.CreatePluginFromPromptDirectory("Prompts");
var fun = prompts["ComposeGovDoc"];
// 民眾陳情內容
var userMessage = @"陳情人:陳芊城陳述，在114年7月1日，在台北市林森北路52號巷口路燈不亮";
// 透過 RAG 取出相似的公文內容
var ragResult = @"主旨：關於民眾反映里內路燈故障一案，請查照。
說明：
一、依據民眾於113年9月1日陳情台北市承德路三段199號巷口路燈不亮。
二、經查現場路燈編號A12、A13不亮。
辦法：請工務課儘速派員檢修，完成後回復。";
var arguments = new KernelArguments
{
    ["user_complaint"] = userMessage,
    ["similar_examples"] = ragResult,
    ["doc_type"] = "函",
    ["target_agency"] = "工務課",
    ["deadline_days"] = "14"
};
// 呼叫並傳入參數
var result = await kernel.InvokeAsync(fun,  arguments);
Console.WriteLine(result);

using Microsoft.SemanticKernel;
using System.ComponentModel;

public class BookManagementPlugin
{
    [KernelFunction]
    [Description("Change the price of a book in the database ")]
    public void ChangePrice([Description("The book id to update")] int bookId, [Description("The new price")] int newPrice)
    {
        //update the price of the book in the database
    }
}

public class ApprovalFilter() : IFunctionInvocationFilter
{
    public async Task OnFunctionInvocationAsync(FunctionInvocationContext context, Func<FunctionInvocationContext, Task> next)
    {
        if (context.Function.PluginName == "BookManagementPlugin" && context.Function.Name == "ChangePrice")
        {

            Console.WriteLine($"系統想要更新書本的價格，您要繼續嗎？ （Y/N）");
            string shouldProceed = Console.ReadLine()!;

            if (shouldProceed != "Y")
            {
                context.Result = new FunctionResult(context.Result, "價格變動未獲得批准");
                return;
            }
        }

        await next(context);
    }

}

using Microsoft.SemanticKernel;
using System.Text;
using Microsoft.SemanticKernel.Plugins.Core;

var apikey = "你的 openai api key";
var modelId = "gpt-4.1";
// 建立 KernelBuilder
var kernelBuilder = Kernel.CreateBuilder();
// 註冊 Plugin
kernelBuilder.Plugins.AddFromType<BookManagementPlugin>();
// 加入 ApprovalFilter
kernelBuilder.Services.AddSingleton<IFunctionInvocationFilter, ApprovalFilter>();

// 加入 OpenAI ChatCompletion 服務
var kernel = kernelBuilder
            .AddOpenAIChatCompletion(modelId, apikey)
            .Build();
OpenAIPromptExecutionSettings settings = new() { ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions };
Console.OutputEncoding = UTF8Encoding.UTF8;
Console.InputEncoding = UTF8Encoding.UTF8;
var chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();
ChatHistory chatHistory = new();
string userMessage = string.Empty;
while (userMessage != "quit")
{
    Console.WriteLine("Enter your question:");
    userMessage = Console.ReadLine();
    chatHistory.AddUserMessage(userMessage);
    var assistantMessage = await chatCompletionService.GetChatMessageContentAsync(chatHistory, settings, kernel);
    Console.WriteLine(assistantMessage);
    chatHistory.Add(assistantMessage);
}

using Microsoft.SemanticKernel;
using System.Text;
using Microsoft.SemanticKernel.Plugins.Core;
using Microsoft.SemanticKernel.Plugins.OpenApi;
var apikey = "你的 openai api key";
var modelId = "gpt-4.1";
// 建立 KernelBuilder
var kernelBuilder = Kernel.CreateBuilder();
// 加入 OpenAI ChatCompletion 服務
var kernel = kernelBuilder
            .AddOpenAIChatCompletion(modelId, apikey)
            .Build();
// 註冊 OpenAPI Plugin
await kernel.ImportPluginFromOpenApiAsync(
     pluginName: "weatherforecast",
     uri: new Uri("http://localhost:5129/openapi/v1.json"),
               executionParameters: new OpenApiFunctionExecutionParameters()
               {
                   EnablePayloadNamespacing = true
               }
    );
OpenAIPromptExecutionSettings settings = new() { ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions };
Console.OutputEncoding = UTF8Encoding.UTF8;
Console.InputEncoding = UTF8Encoding.UTF8;
Console.WriteLine(await kernel.InvokePromptAsync("今天天氣的如何", new(settings)));
Console.ReadLine();

using Microsoft.SemanticKernel;
using System.Text;

var apikey = "你的 openai api key";
var modelId = "gpt-4.1";
// 建立 KernelBuilder
var kernelBuilder = Kernel.CreateBuilder();
// 加入 OpenAI ChatCompletion 服務
var kernel = kernelBuilder
            .AddOpenAIChatCompletion(modelId, apikey)
            .Build();
Console.OutputEncoding = UTF8Encoding.UTF8;
Console.InputEncoding = UTF8Encoding.UTF8;
string userMessage = string.Empty;
// 讓使用者輸入訊息來與 LLM 對話
while(userMessage != "quit")
{
    Console.WriteLine("Enter you message:");
    userMessage = Console.ReadLine();
    Console.WriteLine(await kernel.InvokePromptAsync(userMessage));
}

using Microsoft.SemanticKernel;
using System.Text;
using Microsoft.SemanticKernel.TextToImage;

var apikey = "你的 openai api key";
var imageModelId = "dall-e-3";
// 建立 KernelBuilder
var kernelBuilder = Kernel.CreateBuilder();
// 加入 OpenAI Text to image 服務
#pragma warning disable SKEXP0010, SKEXP0001
var kernel = kernelBuilder
            .AddOpenAITextToImage(modelId: imageModelId, apiKey: apikey)
            .Build();
// 取得 TextToImage Service
ITextToImageService imageService = kernel.GetRequiredService<ITextToImageService>();
string prompt =
"""
創建一幅逼真的圖片，描繪RM的咖啡店。這家店擁有迷人的鄉村外觀，紅磚外牆、大型玻璃窗，和在入口上方懸掛的經典木製招牌，
上面用優雅的手繪字體寫著「RM's Coffee Shop」。入口處有一道復古風格的木製門，上面有一個小鈴鐺，以及門外顯示今日特價的黑板招牌，
包括「柚香拿鐵」、「櫻桃咖啡」和「南瓜咖啡」。
""";
var image = await imageService.GenerateImageAsync(prompt, 1792, 1024);
Console.WriteLine("Image URL: " + image);

using Microsoft.SemanticKernel;
using System.ComponentModel;

public class TimePlugin
{
    [KernelFunction]
    [Description("取得現在UTC的日期及時間")]
    public string GetCurrentDateAndTime()
    {
        return DateTime.UtcNow.ToString("R");
    }
}

using Microsoft.SemanticKernel;
using System.Text;

var apikey = "你的 openai api key";
var modelId = "gpt-4.1";
// 建立 KernelBuilder
var kernelBuilder = Kernel.CreateBuilder();
// 加入 OpenAI ChatCompletion 服務
var kernel = kernelBuilder
            .AddOpenAIChatCompletion(modelId, apikey)
            .Build();
// 註冊 plugin
kernel.ImportPluginFromType<TimePlugin>();
OpenAIPromptExecutionSettings settings = new() { ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions };
Console.OutputEncoding = UTF8Encoding.UTF8;
Console.InputEncoding = UTF8Encoding.UTF8;
Console.WriteLine(await kernel.InvokePromptAsync("今天日期是? ", new(settings)));

using System.Dynamic;
using System.Net.Http.Headers;
using System.Text;
using System.Text.Json;
using System.Text.Json.Nodes;

var clientId = "{Application (client) ID}";
var clientSecret = "{clientSecret}";
var tenantId = "{Directory (tenant) ID}";
var userPrincipalName = "{通常是email}";

Console.OutputEncoding = Encoding.UTF8;
var contentType = "application/json";
var client = new HttpClient();

var getTokenUrl = $"https://login.microsoftonline.com/{tenantId}/oauth2/v2.0/token";
var authBody = $"grant_type=client_credentials&client_id={clientId}&client_secret={clientSecret}&scope=https://graph.microsoft.com/.default";
var authResponse = await client.PostAsync(getTokenUrl, new StringContent(authBody, Encoding.UTF8, "application/x-www-form-urlencoded"));
//取得 AccessToken
var authResult = await authResponse.Content.ReadAsStringAsync();
var options = new JsonSerializerOptions
{
    PropertyNameCaseInsensitive = true
};
dynamic tokenResponse = JsonSerializer.Deserialize<ExpandoObject>(authResult, options);
var authObj = JsonNode.Parse(authResult);
accessToken = (string)authObj["access_token"];

Console.WriteLine("======== access Token =========");
Console.WriteLine(accessToken);

var getUserUrl = $"https://graph.microsoft.com/v1.0/users/{userPrincipalName}";
client.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue(contentType));
client.DefaultRequestHeaders.Add("Authorization", $"Bearer {accessToken}");
var userResponse = await client.GetAsync(getUserUrl);
var userResult = await userResponse.Content.ReadAsStringAsync();
var userObj = JsonNode.Parse(userResult);
var userId = (string)userObj["id"];
Console.WriteLine("======== Azure AD User Id =========");
Console.WriteLine(userId);

var searchSubject = "TID";
var getEventsBySubjectFilterUrl = $"https://graph.microsoft.com/v1.0/users/{userId}/events?$filter=startswith(subject, '{searchSubject}')";
//也可以用 日期 Filter
//var getEventsByDateFilterUrl = $"https://graph.microsoft.com/v1.0/users/{userId}/events?$filter=start/dateTime ge '2025/03/19' and start/dateTime le '2025/03/20' ";
var eventsResponse = await client.GetAsync(getEventsBySubjectFilterUrl);
var eventsResult = await eventsResponse.Content.ReadAsStringAsync();
var eventsObj = JsonNode.Parse(eventsResult);
var eventList = eventsObj["value"].AsArray();
Console.WriteLine("======== Events =========");
foreach (var eventItem in eventList)
{
    var onlineMeeting = eventItem["onlineMeeting"];
    if (onlineMeeting != null)
    {
        var subject = eventItem["subject"].ToString();
        Console.WriteLine($"{subject}:{onlineMeeting["joinUrl"].ToString()}");
    }
}

var joinWebUrl = @"https://teams.microsoft.com/l/meetup-join/.....";
var getOnlineMeetingsUrl = $"https://graph.microsoft.com/v1.0/users/{userId}/onlineMeetings?$filter=JoinWebUrl eq '{joinWebUrl}'";
var onlineMeetingsResponse = await client.GetAsync(getOnlineMeetingsUrl);
var onlineMeetingsResult = await onlineMeetingsResponse.Content.ReadAsStringAsync();
Console.WriteLine("======== Online Meeting Id =========");
var meetingsObj = JsonNode.Parse(onlineMeetingsResult);
var meetingId = "";
//onlineMeetingResult
if (meetingsObj["error"] != null)
{
    Console.WriteLine(meetingsObj["error"]["message"]);
}
else
{
    meetingId = (string)meetingsObj["value"][0]["id"];
    Console.WriteLine(meetingId);
    Console.WriteLine((string)meetingsObj["value"][0]["subject"]);
}

var getMeetingTranscriptsUrl = $"https://graph.microsoft.com/v1.0/users/{userId}/onlineMeetings/{meetingId}/transcripts";
var meetingTranscriptsResponse = await client.GetAsync(getMeetingTranscriptsUrl);
var meetingTranscriptsResult = await meetingTranscriptsResponse.Content.ReadAsStringAsync();

var meetingTranscriptsObj = JsonNode.Parse(meetingTranscriptsResult);
var transcriptsCount = meetingTranscriptsObj["@odata.count"];
meetingTranscriptsObj["value"].AsArray();

Console.WriteLine($"Total Transcripts Count:{transcriptsCount}");
//the latest transcript
var lastTranscript = meetingTranscriptsObj["value"].AsArray().LastOrDefault();
var lastTranscriptId = (string)lastTranscript["id"];

var meetingTranscriptUrl = $"https://graph.microsoft.com/v1.0/users/{userId}/onlineMeetings/{meetingId}/transcripts('{lastTranscriptId}')/content?$format=text/vtt";
var meetingTranscriptResponse = await client.GetAsync(meetingTranscriptUrl);
var meetingTranscriptResult = await meetingTranscriptResponse.Content.ReadAsStringAsync();
Console.WriteLine($"=== Transcript ===============");
Console.WriteLine(meetingTranscriptResult.Substring(0, 500));

public enum MemberStatus
{
    入會,
    暫停,
    退會
}

public static class MemberStatusExtensions
{
    private static readonly Dictionary<MemberStatus, List<MemberStatus>> AllowedTransitions = new()
    {
        [MemberStatus.入會] = [MemberStatus.暫停, MemberStatus.退會],
        [MemberStatus.暫停] = [MemberStatus.入會, MemberStatus.退會],
        [MemberStatus.退會] = [MemberStatus.入會]
    };

    public static bool CanTransitionTo(this MemberStatus current, MemberStatus target)
    {
        return AllowedTransitions.TryGetValue(current, out var nexts) && nexts.Contains(target);
    }
}

var current = MemberStatus.入會;
var target = MemberStatus.退會;
if (current.CanTransitionTo(target))
{
    Console.WriteLine("允許轉換");
}
else
{
    Console.WriteLine("不允許轉換");
}

IKernelBuilder builder = Kernel.CreateBuilder();
const string apikey = "sk-請給 openai apikey";
const string model = "gpt-4.1-mini";

builder.AddOpenAIChatCompletion(model, apikey);
Kernel kernel = builder.Build();

var chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();

ChatHistory chatHistory = new();
string textContent = "請將摘要這張圖片中的文字。\r\n";
bool isUseUri = true; //or false

if (isUseUri)
{
    chatHistory.Add(
        new()
        {
            Role = AuthorRole.User,
            Items = [
                new TextContent(textContent),
            new ImageContent(new Uri($"{對外的ImageUrl}"))
            ]
        }
    );
}
else
{
    byte[] imageBytes = File.ReadAllBytes("path/to/your/image.png");
    chatHistory.Add(
        new()
        {
            Role = AuthorRole.User,
            Items = [
               new TextContent(textContent),
                new ImageContent(imageBytes, "image/png")
            ]
        }
    );
}


var reply = await chatCompletionService.GetChatMessageContentAsync(chatHistory);
Console.WriteLine("================");
Console.WriteLine(reply.Content);
Console.WriteLine("================");
Helper.OutputInnerContent(reply.InnerContent as OpenAI.Chat.ChatCompletion);



public static void OutputInnerContent(OpenAI.Chat.ChatCompletion innerContent)
{
    Console.WriteLine($"Message role: {innerContent.Role}"); // Available as a property of ChatMessageContent
    Console.WriteLine($"Message content: {innerContent.Content[0].Text}"); // Available as a property of ChatMessageContent

    Console.WriteLine($"Model: {innerContent.Model}"); // Model doesn't change per chunk, so we can get it from the first chunk only
    Console.WriteLine($"Created At: {innerContent.CreatedAt}");

    Console.WriteLine($"Finish reason: {innerContent.FinishReason}");
    Console.WriteLine($"Input tokens usage: {innerContent.Usage.InputTokenCount}");
    Console.WriteLine($"Output tokens usage: {innerContent.Usage.OutputTokenCount}");
    Console.WriteLine($"Total tokens usage: {innerContent.Usage.TotalTokenCount}");
    Console.WriteLine($"Refusal: {innerContent.Refusal} ");
    Console.WriteLine($"Id: {innerContent.Id}");
    Console.WriteLine($"System fingerprint: {innerContent.SystemFingerprint}");

    if (innerContent.ContentTokenLogProbabilities.Count > 0)
    {
        Console.WriteLine("Content token log probabilities:");
        foreach (var contentTokenLogProbability in innerContent.ContentTokenLogProbabilities)
        {
            Console.WriteLine($"Token: {contentTokenLogProbability.Token}");
            Console.WriteLine($"Log probability: {contentTokenLogProbability.LogProbability}");

            Console.WriteLine("   Top log probabilities for this token:");
            foreach (var topLogProbability in contentTokenLogProbability.TopLogProbabilities)
            {
                Console.WriteLine($"   Token: {topLogProbability.Token}");
                Console.WriteLine($"   Log probability: {topLogProbability.LogProbability}");
                Console.WriteLine("   =======");
            }

            Console.WriteLine("--------------");
        }
    }

    if (innerContent.RefusalTokenLogProbabilities.Count > 0)
    {
        Console.WriteLine("Refusal token log probabilities:");
        foreach (var refusalTokenLogProbability in innerContent.RefusalTokenLogProbabilities)
        {
            Console.WriteLine($"Token: {refusalTokenLogProbability.Token}");
            Console.WriteLine($"Log probability: {refusalTokenLogProbability.LogProbability}");

            Console.WriteLine("   Refusal top log probabilities for this token:");
            foreach (var topLogProbability in refusalTokenLogProbability.TopLogProbabilities)
            {
                Console.WriteLine($"   Token: {topLogProbability.Token}");
                Console.WriteLine($"   Log probability: {topLogProbability.LogProbability}");
                Console.WriteLine("   =======");
            }
        }
    }
}