using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.Connectors.OpenAI;
var builder = Kernel.CreateBuilder;
// 選擇您的提供者：OpenAI 或 Azure OpenAI
builder.AddOpenAIChatCompletion(
modelId: "gpt-4o-mini", // 或您偏好的模型
apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
);
var kernel = builder.Build;

using Microsoft.SemanticKernel.SemanticFunctions;
var prompt = @"您是一位簡潔的解釋者。
請用 3 個要點向初學者解釋「{topic}」的概念。";
var explainFunc = kernel.CreateFunctionFromPrompt(prompt);
var result = await explainFunc.InvokeAsync(kernel, new { ["topic"] = "vector embeddings" });
Console.WriteLine(result);

public class WeatherPlugin
{
[KernelFunction, Description("Get weather for a city")]
public async Task<string> GetWeatherAsync(
[Description("City name")] string city)
{
// Call your weather API here
var temp = 22; // placeholder
return $"Weather in {city}: {temp}°C and clear";
}
}
// 註冊外掛程式
var weather = new WeatherPlugin;
kernel.Plugins.AddFromObject(weather, pluginName: "weather");

var prompt = @"
您是一個分類引擎。
任務：將 `message` 分類為 [帳單、技術支援、銷售] 之一。
傳回嚴格的 JSON：{ \"label\": string, \"confidence\": number }
message: {message}
";
var classify = kernel.CreateFunctionFromPrompt(prompt);
var output = await classify.InvokeAsync(kernel, new { ["message"] = "I can’t log into my account." });
Console.WriteLine(output); // {"label":"Tech Support","confidence":0.89}

using Microsoft.SemanticKernel.Memory;
var memory = new MemoryBuilder
.WithMemoryStore(new VolatileMemoryStore) // 替換為向量資料庫（Qdrant、Pinecone、Azure AI Search）
.WithTextEmbeddingGeneration(
new OpenAITextEmbeddingGeneration("text-embedding-3-small", Environment.GetEnvironmentVariable("OPENAI_API_KEY")))
.Build;
await memory.SaveInformationAsync(
collection: "policies", id: "refund-policy",
text: "Customers can request a refund within 30 days of purchase with proof of receipt."
);
// 稍後：檢索並塞入提示
var results = memory.SearchAsync("refund window", collection: "policies", limit: 3, minRelevanceScore: 0.7);
await foreach (var item in results)
{
Console.WriteLine($"Relevant: {item.Metadata.Text}");
}

// 1) 像以前一樣定義外掛程式（語義 + 原生）
// 2) 使用規劃器（API 介面可能因版本而異）
var goal = "Summarize the attached policy, classify risk, and email a report";
// 假設我們有外掛程式：files、summarize、classify、email
// 規劃器將組裝一個計劃：files.Load → summarize.Run → classify.Run → email.Send
// 依序執行計劃，驗證步驟之間的 JSON 輸出

var kernel = Kernel.CreateBuilder
.AddOpenAIChatCompletion("gpt-4o-mini", apiKey)
.Build;
var fastKernel = Kernel.CreateBuilder
.AddOpenAIChatCompletion("gpt-4o-mini", apiKey) // 速度最佳化
.Build;
// 將較簡單的提示路由到 fastKernel；將複雜的任務路由到 kernel

record Classification(string label, double confidence);
bool TryParseClassification(string text, out Classification cls)
{
try { cls = System.Text.Json.JsonSerializer.Deserialize<Classification>(text)!; return true; }
catch { cls = default!; return false; }
}

// 1) 將文件提取到記憶中
await memory.SaveInformationAsync("handbook", "vacation-policy",
"Employees accrue 1.5 days of PTO per month and can carry over 5 days.");
// 2) 檢索問題的上下文
var top = memory.SearchAsync("carry over PTO", "handbook", limit: 3, minRelevanceScore: 0.75);
var contexts = new List<string>;
await foreach (var r in top) contexts.Add(r.Metadata.Text);
// 3) 詢問上下文並請求引用
var qaPrompt = @"
You answer strictly from the provided context. If missing, say you don't know.
Include inline citations like [source i] using the index of context items starting at 1.
Context:
1) {{ctx1}}
2) {{ctx2}}
Question: {{q}}
";
var qa = kernel.CreateFunctionFromPrompt(qaPrompt);
var variables = new KernelArguments
{
["ctx1"] = contexts.ElementAtOrDefault(0) ?? "",
["ctx2"] = contexts.ElementAtOrDefault(1) ?? "",
["q"] = "How many PTO days can I carry over?"
};
var answer = await qa.InvokeAsync(kernel, variables);
Console.WriteLine(answer);