{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "33205b12",
   "metadata": {},
   "source": [
    "# Figma\n",
    "\n",
    "This notebook covers how to load data from the Figma REST API into a format that can be ingested into LangChain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90b69c94",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "from langchain.document_loaders import FigmaFileLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "13deb0f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "loader = FigmaFileLoader(\n",
    "    os.environ.get('ACCESS_TOKEN'),\n",
    "    os.environ.get('NODE_IDS'),\n",
    "    os.environ.get('FILE_KEY')\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9ccc1e2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "loader.load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3e64cac2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "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": "3.9.1"
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 },
 "nbformat": 4,
 "nbformat_minor": 5
}