Update app.py
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app.py
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import gradio as gr
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import subprocess
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with gr.Blocks() as demo:
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with gr.Row():
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pdf_file = gr.File(label='Upload a PDF', scale=1)
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mkd = gr.
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pdf_link = gr.Textbox(placeholder='Enter an arxiv link here', label='Provide a link', scale=1)
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demo.launch(debug=True)
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import gradio as gr
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import subprocess
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def nougat_ocr(file_name):
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# CLI Command to run
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cli_command = [
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'nougat',
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'--out', '/output',
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'pdf', f'{file_name}',
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'--checkpoint', '/nougat'
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]
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# Run the command and get .mmd file in an output folder
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subprocess.run(cli_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
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return
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def predict(pdf_file):
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print(f"temporary file - {pdf_file.name}")
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pdf_name = pdf_file.name.split('/')[-1].split('.')[0]
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print(f"pdf file name - {pdf_name}")
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#! Get prediction for a PDF using nougat
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nougat_ocr(pdf_file.name)
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# Open the multimarkdown (.mmd) file for reading
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with open(f'/content/output/{pdf_name}.mmd', 'r') as file:
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content = file.read()
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return content
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with gr.Blocks() as demo:
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with gr.Row():
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pdf_file = gr.File(label='Upload a PDF', scale=1)
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mkd = gr.Markdown('<h2><center><i>OR</i></center></h2>',scale=1)
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pdf_link = gr.Textbox(placeholder='Enter an arxiv link here', label='Provide a link', scale=1)
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btn = gr.Button()
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parsed_output = gr.Markdown()
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btn.click(predict, pdf_file, parsed_output )
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demo.queue()
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demo.launch(debug=True)
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