gr.HTML("<h1><center>Nougat: Neural Optical Understanding for Academic Documents<center><h1>")
  gr.HTML("<h3><center>Lukas Blecher et al. <a href='https://arxiv.org/pdf/2308.13418.pdf' target='_blank'>Paper</a>, <a href='https://facebookresearch.github.io/nougat/'>Project</a><center></h3>")

  with gr.Row():
    mkd = gr.Markdown('<h4><center>Upload a PDF</center></h4>', scale=1)
    mkd = gr.Markdown('<h4><center><i>OR</i></center></h4>', scale=1)
    mkd = gr.Markdown('<h4><center>Provide a PDF link</center></h4>', scale=1)

  with gr.Row(equal_height=True):
    pdf_file = gr.File(label='PDF📃', file_count='single', scale=1)
    pdf_link = gr.Textbox(placeholder='Enter an Arxiv link here', label='PDF link🔗🌐', scale=1)

  with gr.Row():
    btn = gr.Button('Run NOUGAT🍫')
    clr = gr.Button('Clear🚿')

  output_headline = gr.Markdown("<h3>PDF converted to markup language through Nougat-OCR👇:</h3>")
  parsed_output = gr.Markdown(elem_id='mkd', value='📃🔤OCR Output')
  mmd_file_download = gr.File(label='Download .mmd file', interactive=False)

  def handle_predict(pdf_file, pdf_link):
      content, mmd_file_path = predict(pdf_file, pdf_link)
      return gr.update(value=content), mmd_file_path

  btn.click(handle_predict, [pdf_file, pdf_link], [parsed_output, mmd_file_download])
  clr.click(lambda: (gr.update(value=None),
                     gr.update(value=None),
                     gr.update(value=None)),
            [],
            [pdf_file, pdf_link, parsed_output, mmd_file_download])

  gr.Examples(
      [["input/nougat.pdf", ""], [None, "https://arxiv.org/pdf/2308.08316.pdf"]],
      inputs=[pdf_file, pdf_link],
      outputs=parsed_output,
      fn=process_example,
      cache_examples=True,
      label='Click on any Examples below to get Nougat OCR results quickly:'
  )

demo.queue()
demo.launch(debug=True)