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| import gradio as gr | |
| from main import main | |
| import json | |
| import subprocess | |
| def installChrome(): | |
| subprocess.run(['apt-get', 'update']) | |
| subprocess.run(['apt-get', 'install', '-y', 'wget', 'unzip']) | |
| subprocess.run(['wget', 'https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb']) | |
| subprocess.run(['apt-get', 'install', '-y', './google-chrome-stable_current_amd64.deb']) | |
| subprocess.run(['rm', 'google-chrome-stable_current_amd64.deb']) | |
| subprocess.run(['apt-get', 'clean']) | |
| def rexplore_summarizer(url, id, access_key): | |
| response = json.loads(main(url, id, access_key)) | |
| data = json.dumps(response, ensure_ascii=False, indent=4) | |
| if response["mindmap_status"] != "success": | |
| mindmap = "error" | |
| else: | |
| mindmap = response["mindmap"] | |
| if response["summary_status"] != "success": | |
| summary = "error" | |
| else: | |
| summary = response["summary"] | |
| return data, summary, mindmap | |
| def clear_everything(url, id, access_key, raw_data, summary, mindmap): | |
| return None, None, None, None, None, None | |
| theme = gr.themes.Soft( | |
| primary_hue="purple", | |
| secondary_hue="cyan", | |
| neutral_hue="slate", | |
| font=[ | |
| gr.themes.GoogleFont("Syne"), | |
| gr.themes.GoogleFont("Poppins"), | |
| gr.themes.GoogleFont("Poppins"), | |
| gr.themes.GoogleFont("Poppins") | |
| ], | |
| ) | |
| with gr.Blocks(theme=theme, title="ReXplore Summarizer", fill_height=True) as app: | |
| gr.HTML( | |
| value =""" | |
| <h1 style="text-align: center;">ReXplore Summarizer <p style="text-align: center;">Designed and Developed by <a href="https://raannakasturi.eu.org" target="_blank" rel="nofollow noreferrer external">Nayan Kasturi</a></p> </h1> | |
| <p style="text-align: center;">This app uses a hybrid approach to summarize PDF documents based on CPU as well as GPU.</p> | |
| <p style="text-align: center;">The app uses traditional methodologies such as TextRank, LSA, Luhn algorithms as well as large language model (LLM) to generate summaries as well as mindmaps.</p> | |
| <p style="text-align: center;">The summarization process can take some time depending on the size of the text corpus and the complexity of the content.</p> | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| url = gr.Textbox(label="PDF URL", placeholder="Paste the PDF URL here") | |
| id = gr.Textbox(label="DOI/arXiv ID", placeholder="Enter the DOI or arXiv ID of the Research Paper") | |
| access_key = gr.Textbox(label="Access Key", placeholder="Enter the Access Key", type="password") | |
| with gr.Row(): | |
| clear_btn = gr.Button(value="Clear", variant="stop") | |
| summarize_btn = gr.Button(value="Summarize", variant="primary") | |
| raw_data = gr.TextArea(label="Raw Data", placeholder="The generated raw data will be displayed here", lines=7, interactive=False, show_copy_button=True) | |
| with gr.Row(): | |
| summary = gr.TextArea(label="Summary", placeholder="The generated summary will be displayed here", lines=7, interactive=False, show_copy_button=True) | |
| mindmap = gr.TextArea(label="Mindmap", placeholder="The generated mindmap will be displayed here", lines=7, interactive=False, show_copy_button=True) | |
| summarize_btn.click( | |
| rexplore_summarizer, | |
| inputs=[url, id, access_key], | |
| outputs=[raw_data, summary, mindmap], | |
| concurrency_limit=25, | |
| scroll_to_output=True, | |
| show_api=True, | |
| api_name="rexplore_summarizer", | |
| show_progress="full", | |
| ) | |
| clear_btn.click(clear_everything, inputs=[url, id, raw_data, summary, mindmap, access_key], outputs=[url, id, raw_data, summary, mindmap, access_key], show_api=False) | |
| installChrome() | |
| app.queue(default_concurrency_limit=25).launch(show_api=True, ssr_mode=False) | |