{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "eed6bcd0-6cf8-4aa9-bedf-5eca5a6b7a9c",
   "metadata": {},
   "source": [
    "# Hugging Face Spaces From A Notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15fe30a9-cfeb-4ec0-ae40-334072046464",
   "metadata": {},
   "source": [
    "Please reference [this blog post](https://nbdev.fast.ai/blog/posts/2022-11-10-spaces) on how to use this notebook."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ca22d1e-1bd0-49c0-9b89-c480ad1a29c4",
   "metadata": {},
   "source": [
    "# Make an app with Gradio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "00cf4fad-a920-41dc-be42-3992c7fcefac",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "import gradio as gr\n",
    "from fastcore.net import urljson, HTTPError"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "38a4389f-ef53-4626-a6f5-a859354f854b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#|export\n",
    "def size(repo:str):\n",
    "    \"Returns the size in GB of a HuggingFace Dataset.\"\n",
    "    url = f'https://huggingface.co/api/datasets/{repo}'\n",
    "    try: resp = urljson(f'{url}/treesize/main')\n",
    "    except HTTPError: return f'Did not find repo: {url}'\n",
    "    gb = resp['size'] / 1e9\n",
    "    return f'{gb:.2f} GB'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95bc32b8-d8ff-4761-a2d7-0880c51d0a42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'5.49 GB'"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "size(\"tglcourse/CelebA-faces-cropped-128\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b20e2a1-b622-4970-9069-0202ce10a2ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7860\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"500\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(<gradio.routes.App>, 'http://127.0.0.1:7860/', None)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#|export\n",
    "iface = gr.Interface(fn=size, inputs=gr.Text(value=\"tglcourse/CelebA-faces-cropped-128\"), outputs=\"text\")\n",
    "iface.launch(width=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39d7be72-9389-42cf-91b1-78e8f4bbd083",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Closing server running on port: 7860\n"
     ]
    }
   ],
   "source": [
    "# this is only necessary in a notebook\n",
    "iface.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "249b2cd7-3123-45bf-945f-882b8a964cf5",
   "metadata": {},
   "source": [
    "## Convert This Notebook Into A Gradio App"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6706d92c-5785-4f09-9773-b9a944c493a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nbdev.export import nb_export\n",
    "nb_export('app.ipynb', lib_path='.', name='app')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0182403f-d1d6-48c0-8e66-46aefb23a9ab",
   "metadata": {},
   "source": [
    "<div>\n",
    "<link rel=\"stylesheet\" href=\"https://gradio.s3-us-west-2.amazonaws.com/2.6.5/static/bundle.css\">\n",
    "<div id=\"target\"></div>\n",
    "<script src=\"https://gradio.s3-us-west-2.amazonaws.com/2.6.5/static/bundle.js\"></script>\n",
    "<script>\n",
    "launchGradioFromSpaces(\"abidlabs/question-answering\", \"#target\")\n",
    "</script>\n",
    "</div>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}