SemanticKernelStudy/Docs/02.1.快速入门指南.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "id": "261d91b6",
   "metadata": {},
   "source": [
    "快速入门指南\n",
    "==========="
   ]
  },
  {
   "cell_type": "markdown",
   "id": "034c3c59",
   "metadata": {},
   "source": [
    "只需执行几个步骤，即可在 Python、.NET 或 Java 中使用语义内核生成第一个 AI 代理。以C#为例： \n",
    "\n",
    "+ 安装所需的包\n",
    "+ 使用 AI 创建来回对话\n",
    "+ 使 AI 代理能够运行代码\n",
    "+ 观看 AI 动态创建计划"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70d6d69f",
   "metadata": {},
   "source": [
    "## 初始化基础设施"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "becd4e47",
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     "name": "polyglot-notebook"
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    "polyglot_notebook": {
     "kernelName": "csharp"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "初始化完毕！\r\n"
     ]
    }
   ],
   "source": [
    "#!import ./ini.ipynb"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f942ceb2",
   "metadata": {},
   "source": [
    "## 安装 SDK"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "145ba5d7",
   "metadata": {},
   "source": [
    "语义内核有多个 NuGet 包可用。 但是，对于大多数方案，通常只需要 Microsoft.SemanticKernel。\n",
    "\n",
    "可以使用以下命令安装它：\n",
    "\n",
    "```Bash\n",
    "    dotnet add package Microsoft.SemanticKernel\n",
    "```\n",
    "\n",
    "有关 Nuget 包的完整列表，请参阅 [支持的语言文章](https://learn.microsoft.com/zh-cn/semantic-kernel/get-started/supported-languages?pivots=programming-language-csharp)。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e796f0a",
   "metadata": {},
   "source": [
    "## 快速开始使用笔记本"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3ecfe91",
   "metadata": {},
   "source": [
    "C# 开发人员，可以快速开始使用笔记本。 这些笔记本提供了有关如何使用语义内核生成 AI 代理的分步指南。\n",
    "![快速开始](./Assets/Images/getting_started_notebooks.png)\n",
    "\n",
    "要开始，请按照以下步骤操作：\n",
    "\n",
    "1. 克隆[语义内核存储库](https://github.com/microsoft/semantic-kernel)\n",
    "2. 在 Visual Studio Code 中打开存储库\n",
    "3. 导航到 _/dotnet/notebooks\n",
    "4. 打开 00-getting-started.ipynb 以开始设置环境并创建第一个 AI 代理！\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e1ffa9a",
   "metadata": {},
   "source": [
    "## 编写第一个控制台应用"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eeba44ee",
   "metadata": {},
   "source": [
    "1. 使用以下命令创建新的 .NET 控制台项目：\n",
    "\n",
    "    ```bash\n",
    "    dotnet new console\n",
    "    ```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "765fd394",
   "metadata": {},
   "source": [
    "2. 安装以下 .NET 依赖项：\n",
    "\n",
    "    ```baSH\n",
    "    dotnet add package Microsoft.SemanticKernel\n",
    "    dotnet add package Microsoft.Extensions.Logging\n",
    "    dotnet add package Microsoft.Extensions.Logging.Console\n",
    "    ```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c9b17d0",
   "metadata": {},
   "source": [
    "3. 将 Program.cs 文件的内容替换为以下代码：\n",
    "\n",
    "```csharp\n",
    "    // Import packages\n",
    "    using Microsoft.Extensions.DependencyInjection;\n",
    "    using Microsoft.Extensions.Logging;\n",
    "    using Microsoft.SemanticKernel;\n",
    "    using Microsoft.SemanticKernel.ChatCompletion;\n",
    "    using Microsoft.SemanticKernel.Connectors.OpenAI;\n",
    "\n",
    "    // Populate values from your OpenAI deployment\n",
    "    var modelId = \"\";\n",
    "    var endpoint = \"\";\n",
    "    var apiKey = \"\";\n",
    "\n",
    "    // Create a kernel with Azure OpenAI chat completion\n",
    "    var builder = Kernel.CreateBuilder().AddAzureOpenAIChatCompletion(modelId, endpoint, apiKey);\n",
    "\n",
    "    // Add enterprise components\n",
    "    builder.Services.AddLogging(services => services.AddConsole().SetMinimumLevel(LogLevel.Trace));\n",
    "\n",
    "    // Build the kernel\n",
    "    Kernel kernel = builder.Build();\n",
    "    var chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();\n",
    "\n",
    "    // Add a plugin (the LightsPlugin class is defined below)\n",
    "    kernel.Plugins.AddFromType<LightsPlugin>(\"Lights\");\n",
    "\n",
    "    // Enable planning\n",
    "    OpenAIPromptExecutionSettings openAIPromptExecutionSettings = new() \n",
    "    {\n",
    "        FunctionChoiceBehavior = FunctionChoiceBehavior.Auto()\n",
    "    };\n",
    "\n",
    "    // Create a history store the conversation\n",
    "    var history = new ChatHistory();\n",
    "\n",
    "    // Initiate a back-and-forth chat\n",
    "    string? userInput;\n",
    "    do {\n",
    "        // Collect user input\n",
    "        Console.Write(\"User > \");\n",
    "        userInput = Console.ReadLine();\n",
    "\n",
    "        // Add user input\n",
    "        history.AddUserMessage(userInput);\n",
    "\n",
    "        // Get the response from the AI\n",
    "        var result = await chatCompletionService.GetChatMessageContentAsync(\n",
    "            history,\n",
    "            executionSettings: openAIPromptExecutionSettings,\n",
    "            kernel: kernel);\n",
    "\n",
    "        // Print the results\n",
    "        Console.WriteLine(\"Assistant > \" + result);\n",
    "\n",
    "        // Add the message from the agent to the chat history\n",
    "        history.AddMessage(result.Role, result.Content ?? string.Empty);\n",
    "    } while (userInput is not null);\n",
    "\n",
    "```\n",
    "\n",
    "以下来回聊天应类似于你在控制台中看到的内容。 下面添加了函数调用，以演示 AI 如何在后台利用插件。\n",
    "\n",
    "| 角色                   | 消息                             |\n",
    "| ------------------ -   | -----------                      |\n",
    "| 🔵 用户               |  请切换灯                         |\n",
    "| 🔴 助手（函数调用）    | LightsPlugin.GetState() |\n",
    "| 🟢 工具               | off |\n",
    "| 🔴 助手（函数调用）    | LightsPlugin.ChangeState(true) |\n",
    "| 🟢 工具               | on |\n",
    "| 🔴 助手               | 灯现在打开 |\n",
    "\n",
    "如果有兴趣了解有关上述代码的详细信息，我们将在下一部分中将其分解。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7e846a6",
   "metadata": {},
   "source": [
    "## 了解代码"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31f3881d",
   "metadata": {},
   "source": [
    "为了更轻松地开始使用语义内核构建企业应用，我们创建了一个分步指导你完成创建内核的过程，并使用它与 AI 服务交互。\n",
    "\n",
    "![过程](./Assets/Images/dotnetmap.png)\n",
    "\n",
    "在以下部分中，我们将通过演练步骤 1、2、3、4、6、9 和 10 来解包上述示例。 构建由 AI 服务提供支持且可以运行代码的简单代理所需的一切。\n",
    "+ 导入包\n",
    "+ 添加 AI 服务\n",
    "+ 企业组件\n",
    "+ 生成内核\n",
    "+ 添加内存（已跳过）\n",
    "+ 添加插件\n",
    "+ 创建内核参数（已跳过）\n",
    "+ 创建提示（跳过）\n",
    "+ 规划\n",
    "+ Invoke"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9b47cb5",
   "metadata": {},
   "source": [
    "### １导入包"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "382cfdf5",
   "metadata": {},
   "source": [
    "### ２添加 AI 服务"
   ]
  }
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