自定义知识库聊天机器人.ipynb

{
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        "id": "view-in-github"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/esonwong/learning-python/blob/main/%E8%87%AA%E5%AE%9A%E4%B9%89%E7%9F%A5%E8%AF%86%E5%BA%93%E8%81%8A%E5%A4%A9%E6%9C%BA%E5%99%A8%E4%BA%BA.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q6FTkBlCgiaS"
      },
      "source": [
        "# 简介\n",
        "你只需要按照这份教程一步一步操作，即可实现一个「自定义知识库的聊天机器人」。 本教程的使用方法很简单，你只需要点击代码前的播放按钮即可。"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PyZRSxu15luG"
      },
      "source": [
        "# 安装依赖库\n",
        "\n",
        "点击下方代码前的播放按钮即可，这一步主要是安装好后续程序依赖的库。"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RrlM5y9p53ET",
        "outputId": "01f20973-3110-456c-fcbd-c9db6b38ca04"
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      "outputs": [],
      "source": [
        "!pip3 install llama-index"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x1eo2yzVoMHi"
      },
      "source": [
        "# 导入个人知识库数据\n",
        "\n",
        "1. 左侧文件夹菜单中新建 `data` 文件夹。\n",
        "\n",
        "2. 上传知识库文件到文件夹内。"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "gJLtujqg6mjG"
      },
      "source": [
        "# 设置 OpenAI API Key\n",
        "\n",
        "点击代码前的播放按钮，运行代码后，在框内输入你的个人 OpenAI API Key，黏贴完记得按下回车键。"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6NI-7ooZ6116",
        "outputId": "81a69b5a-22d5-460b-bc0b-b993bcba0751"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "os.environ[\"OPENAI_API_KEY\"] = input(\"将你的 OpenAI API Key 黏贴到这里：\")"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "WaI1QBqv57a0"
      },
      "source": [
        "# 构建索引 \n",
        "下面用 OpenAI 的 embedding API 来构建索引，这个 API 可以将文本转换为向量，这样就可以通过计算向量的相似度来判断两个文本的相似度。"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "F_LAX5XV56sY"
      },
      "outputs": [],
      "source": [
        "from llama_index import GPTSimpleVectorIndex, SimpleDirectoryReader\n",
        "documents = SimpleDirectoryReader('data').load_data()\n",
        "index = GPTSimpleVectorIndex.from_documents(documents)\n",
        "index.save_to_disk('index.json')"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "xrjoWNip-K6J"
      },
      "source": [
        "# 提问\n",
        "\n",
        "1. 加载 index.json\n",
        "\n",
        "2. 提问"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "id": "qIoAWYKQFukQ",
        "outputId": "20d6433f-6fa2-4604-e955-d9000e5eb6ac"
      },
      "outputs": [],
      "source": [
        "index = GPTSimpleVectorIndex.load_from_disk('index.json')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from IPython.display import Markdown, display\n",
        "query = input(\"请输入你的问题：\")\n",
        "response = index.query(query)\n",
        "display(Markdown(response.response))"
      ]
    }
  ],
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