A demo of creating a gradio app with nbdev

app.ipynb

{
 "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/2022-11-07-spaces) on how to use this notebook."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acf7644f-42b3-4d8d-a1d0-f8c3a2358e27",
   "metadata": {},
   "source": [
    "## Install dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3a57baf-bb8a-4b32-904a-820fb85be1a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install git+https://github.com/fastai/nbdev.git gradio fastcore"
   ]
  },
  {
   "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": "88424f53-cd78-41fe-9e06-8a6209001064",
   "metadata": {},
   "source": [
    "## Create a `requirements.txt` file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "db4a30aa-9090-460e-acf9-4eb359161125",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%writefile requirements.txt\n",
    "fastcore"
   ]
  },
  {
   "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
}

The last step "Convert this notebook into a Gradio app" silently fails, no app.py is created. Tried on VSCode, jupyter, juypter lab, colab and kaggle. When I try the CLI with nbdev_export I get the following error. Is there another way to auto-generate the app.py without manual editing? Thanks.

Traceback (most recent call last):
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/bin/nbdev_export", line 8, in
sys.exit(nbdev_export())
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/lib/python3.9/site-packages/fastcore/script.py", line 119, in _f
return tfunc(**merge(args, args_from_prog(func, xtra)))
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/lib/python3.9/site-packages/nbdev/doclinks.py", line 138, in nbdev_export
_build_modidx()
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/lib/python3.9/site-packages/nbdev/doclinks.py", line 96, in _build_modidx
res['settings'] = {k:v for k,v in get_config().d.items()
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/lib/python3.9/site-packages/nbdev/doclinks.py", line 96, in
res['settings'] = {k:v for k,v in get_config().d.items()
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/lib/python3.9/_collections_abc.py", line 851, in iter
yield (key, self._mapping[key])
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/lib/python3.9/configparser.py", line 1258, in getitem
return self._parser.get(self._name, key)
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/lib/python3.9/configparser.py", line 799, in get
return self._interpolation.before_get(self, section, option, value,
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/lib/python3.9/configparser.py", line 395, in before_get
self._interpolate_some(parser, option, L, value, section, defaults, 1)
File "/opt/homebrew/Caskroom/miniforge/base/envs/MLME-22/lib/python3.9/configparser.py", line 434, in _interpolate_some
raise InterpolationMissingOptionError(
configparser.InterpolationMissingOptionError: Bad value substitution: option 'lib_name' in section 'DEFAULT' contains an interpolation key 'repo' which is not a valid option name. Raw value: '%(repo)s'

Tried also installing nbdev with conda or pip, since this PR#1024 seems to be included in release 2.3.9 but still no success. These were in place of first input of the notebook, which installs nbdev 2.3.10. But none of them worked. Also inserted debug=True before name but still silent. What else could I try? Thanks.

Don't use the CLI, use the method I suggested in the blog post 😄 , I'm not certain that the CLI nbdev_export supports this.

Tried also installing nbdev with conda or pip, since this AnswerDotAI/nbdev#1204 seems to be included in release 2.3.9 but still no success. These were in place of first input of the notebook, which installs nbdev 2.3.10. But none of them worked. Also inserted debug=True before name but still silent. What else could I try? Thanks.

Per the blog post, install from github pip install git+https://github.com/fastai/nbdev.git

Thanks, CLI was a fallback, the method in your blog post runs in 0.3 secs, but no app.py in the folder (or nowhere else). Relative or absolute paths like lib_path='/Users/cer/vc/projects/hfds-size/' did not matter. Can't really figure out why it fails. In any case, thanks for the idea and blog post.

from nbdev.export import nb_export
nb_export('app.ipynb', lib_path='.', name='app') 

the method in your blog post runs in 0.3 secs, but no app.py in the folder

It's hard to debug this way, if you would like to provide a minimally reproducible example it might be easier. The code in a repo format is on HFhub incase that helps. https://huggingface.co/spaces/hamel/hfspace_demo/tree/main

It helped!!! When I downloaded the raw notebook from the gist, somehow the export decorators were damaged under my edits. I think I managed to change one “|” to “!”. My bad. Now I downloaded app.ipynb directly from https://huggingface.co/spaces/hamel/hfspace_demo/tree/main and it worked Seems to be also working with conda or pip versions 2.3.9. Thanks so much, I’ll now clean up and rewrite my app.

…

On 14 Nov 2022, at 18.38, Hamel Husain ***@***.***> wrote: Re: hamelsmu/app.ipynb @hamelsmu commented on this gist.the method in your blog post runs in 0.3 secs, but no app.py in the folder It's hard to debug this way, if you would like to provide a minimally reproducible example it might be easier. The code in a repo format is on HFhub incase that helps. https://huggingface.co/spaces/hamel/hfspace_demo/tree/main — Reply to this email directly, view it on GitHub or unsubscribe. You are receiving this email because you commented on a thread. Triage notifications on the go with GitHub Mobile for iOS or Android.