Notion_to_Chatbot.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyONKGQWGXfxDcJVvzPuRuWH",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Anil-matcha/Notion-to-Chatbot/blob/main/Notion_to_Chatbot.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": "code",
      "execution_count": null,
      "metadata": {
        "id": "wONp_EGeVMLq"
      },
      "outputs": [],
      "source": [
        "!pip install langchain openai chromadb tiktoken"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.document_loaders import NotionDBLoader\n",
        "\n",
        "loader = NotionDBLoader(\n",
        "    integration_token=\"notion-key\",\n",
        "    database_id=\"database-id\",\n",
        "    request_timeout_sec=30,  # optional, defaults to 10\n",
        ")\n",
        "\n",
        "docs = loader.load()"
      ],
      "metadata": {
        "id": "f6PzpRWvVRQQ"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain.chains import RetrievalQA\n",
        "from langchain.embeddings.openai import OpenAIEmbeddings\n",
        "from langchain.llms import OpenAI\n",
        "from langchain.text_splitter import CharacterTextSplitter\n",
        "from langchain.vectorstores import Chroma\n",
        "import os\n",
        "from langchain.docstore.document import Document\n",
        "os.environ[\"OPENAI_API_KEY\"] = \"openai-key\"\n",
        "\n",
        "text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
        "texts = text_splitter.split_documents(docs)\n",
        "texts = [Document(page_content=x.page_content) for x in texts]"
      ],
      "metadata": {
        "id": "rv08JkYDWJNc"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "embeddings = OpenAIEmbeddings()\n",
        "docsearch = Chroma.from_documents(texts, embeddings)\n",
        "\n",
        "qa = RetrievalQA.from_chain_type(llm=OpenAI(), chain_type=\"stuff\", retriever=docsearch.as_retriever())"
      ],
      "metadata": {
        "id": "VxO11rqVW7nO"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "qa.run(\"What is UUKI ?\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "id": "ccvyvCc_YbwK",
        "outputId": "70e70327-5fbd-4b68-de9e-65be2d45e97d"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:chromadb.db.index.hnswlib:Number of requested results 4 is greater than number of elements in index 1, updating n_results = 1\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "' UUKI is a community platform for creators.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 27
        }
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}