Langchain scripts to pull Notion data

Notion to Langchain.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "89f29112",
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "!pip install langchain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0fdbe2dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 1: Import necessary libraries\n",
    "from getpass import getpass\n",
    "from langchain.document_loaders import NotionDBLoader\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f55d9631",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 2: Input your Notion integration token and database ID\n",
    "#print(\"Enter your Notion Integration Token:\")\n",
    "#NOTION_TOKEN = getpass()  # This securely gets your input without showing it\n",
    "\n",
    "#print(\"\\\\nEnter your Notion Database ID:\")\n",
    "#DATABASE_ID = getpass()  # This securely gets your input without showing it\n",
    "\n",
    "NOTION_TOKEN = \"your_token_here\"\n",
    "DATABASE_ID = \"your_database_id_here\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9101a84e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 3: Create a loader object with the Notion integration token and database ID\n",
    "loader = NotionDBLoader(\n",
    "    integration_token=NOTION_TOKEN,\n",
    "    database_id=DATABASE_ID,\n",
    "    request_timeout_sec=30,  # optional, defaults to 10\n",
    ")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b7c7a651",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 4: Load the documents from the Notion database\n",
    "docs = loader.load()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12b3884b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 5: Print the first document to check the result\n",
    "print(docs[0])\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}