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| import gradio as gr | |
| import base64 | |
| import os | |
| api_key = os.getenv('API_KEY') | |
| def predict(input, file_input): | |
| print("input:", input) | |
| print("file_input:", file_input.name) | |
| from gradio_client import Client | |
| client = Client(api_key) | |
| extract_result = client.predict( | |
| input, | |
| file_input.name, | |
| fn_index=1 | |
| ) | |
| if extract_result: | |
| print(extract_result) | |
| return extract_result | |
| else: | |
| return "Too many user, please wait a monument!" | |
| def view_pdf(pdf_file): | |
| with open(pdf_file.name, 'rb') as f: | |
| pdf_data = f.read() | |
| # print("pdf_file", pdf_file) | |
| # pdf_data = pdf_file | |
| b64_data = base64.b64encode(pdf_data).decode('utf-8') | |
| # print("b64_data", b64_data) | |
| return f"<embed src='data:application/pdf;base64,{b64_data}' type='application/pdf' width='100%' height='700px' />" | |
| en_1 = ["""could you please help me extract the information of 'title'/'journal'/'year'/'author'/'institution'/'email' from the previous content in a markdown table format? | |
| If any of this information was not available in the paper, please replaced it with the string `""`, If the property contains multiple entities, please use a list to contain. | |
| """] | |
| en_2 = ["""could you please help me extract the information of 'title'/'journal'/'year'/'author'/'institution'/'email' from the previous content in a json format? | |
| If any of this information was not available in the paper, please replaced it with the string `""`, If the property contains multiple entities, please use a list to contain. | |
| """] | |
| examples = [en_1, en_2] | |
| with gr.Blocks(title="ChatPaperGPT") as demo: | |
| gr.Markdown( | |
| '''<p align="center" width="100%"> | |
| <img src="https://big-cheng.com/img/pdf.png" alt="pdf-logo" width="50"/> | |
| <p> | |
| <h1 align="center"> Paper Extract GPT </h1> | |
| <p> How to use: | |
| <br> <strong>#1</strong>: Upload your pdf. | |
| <br> <strong>#2</strong>: Click the View PDF button to view it. | |
| <br> <strong>#3</strong>: Enter your extraction prompt in the input box (of course, you can click example to test). | |
| <br> <strong>#4</strong>: Click Generate to extract, and the extracted information will be displayed in markdown form. | |
| </p> | |
| ''' | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown('## Upload PDF') | |
| file_input = gr.File(type="filepath") | |
| viewer_button = gr.Button("View PDF") | |
| file_out = gr.HTML() | |
| with gr.Column(): | |
| with gr.Row(): | |
| model_input = gr.Textbox(lines=7, placeholder='Input prompt about extract information from paper', | |
| label='Input') | |
| with gr.Row(): | |
| gen = gr.Button("Generate") | |
| clr = gr.Button("Clear") | |
| example = gr.Examples(examples=examples, inputs=model_input) | |
| with gr.Row(): | |
| outputs = gr.Markdown(label='Output', show_label=True, value="""| Title | Journal | Year | Author | Institution | Email | | |
| |---------------------------------------------|--------------------|------|-----------------------------------------------|-------------------------------------------------------|-----------------------| | |
| | Paleomagnetic Study of Deccan Traps from Jabalpur to Amarkantak, Central India | J. Geomag. Geoelectr. | 1973 | R. K. VERMA, G. PULLAIAH, G.R. ANJANEYULU, P. K. MALLIK | National Geophysical Research Institute, Hyderabad, and Indian School o f Mines, Dhanbad | "" | | |
| """) | |
| inputs = [model_input, file_input] | |
| gen.click(fn=predict, inputs=inputs, outputs=outputs) | |
| clr.click(fn=lambda value: [gr.update(value=""), gr.update(value="")], inputs=clr, | |
| outputs=[model_input, outputs]) | |
| viewer_button.click(view_pdf, inputs=file_input, outputs=file_out) | |
| # parser_button.click(extract_text, inputs=file_input, outputs=[xml_out, md_out, rich_md_out]) | |
| demo.launch() | |