import requests from bs4 import BeautifulSoup import pandas as pd import gradio as gr import time import os import json import PyPDF2 import io import markdown import asyncio import aiohttp import aiofiles from concurrent.futures import ThreadPoolExecutor # ... (keep the existing functions like get_rank_papers, load_cached_data, save_cached_data, format_dataframe, load_and_cache_data, update_display, load_all_data) async def download_and_convert_pdf(session, title, paper_info): pdf_url = paper_info['pdf_link'] cache_file = f"cache/{title.replace(' ', '_')}.md" if os.path.exists(cache_file): async with aiofiles.open(cache_file, 'r') as f: return await f.read() if not pdf_url: return f"# {title}\n\nNo PDF link available.\n\n---\n\n" try: async with session.get(pdf_url) as response: pdf_content = await response.read() pdf_file = io.BytesIO(pdf_content) pdf_reader = PyPDF2.PdfReader(pdf_file) text = "" for page in pdf_reader.pages: text += page.extract_text() markdown_text = f"# {title}\n\n{text}\n\n---\n\n" os.makedirs('cache', exist_ok=True) async with aiofiles.open(cache_file, 'w') as f: await f.write(markdown_text) return markdown_text except Exception as e: return f"# {title}\n\nError processing PDF: {str(e)}\n\n---\n\n" async def process_papers(data, progress=gr.Progress()): async with aiohttp.ClientSession() as session: tasks = [] for title, paper_info in data.items(): task = asyncio.ensure_future(download_and_convert_pdf(session, title, paper_info)) tasks.append(task) consolidated_text = "" for i, task in enumerate(asyncio.as_completed(tasks), start=1): markdown_text = await task consolidated_text += markdown_text progress(i / len(tasks), f"Processed {i}/{len(tasks)} papers") return consolidated_text def download_all_papers(progress=gr.Progress()): all_data = {} for category in ["top", "latest", "greatest"]: cache_file = f"{category}_papers_cache.json" data = load_cached_data(cache_file) if data: all_data.update(data) consolidated_text = asyncio.run(process_papers(all_data, progress)) with open("consolidated_papers.md", "w", encoding="utf-8") as f: f.write(consolidated_text) return "All papers have been downloaded and consolidated into 'consolidated_papers.md'" with gr.Blocks() as demo: gr.Markdown("

Papers Leaderboard

") with gr.Tab("Top Trending Papers"): top_count = gr.Textbox(label="Number of Papers Fetched") top_html = gr.HTML() top_button = gr.Button("Refresh Leaderboard") top_button.click(fn=lambda: update_display("top"), inputs=None, outputs=[top_count, top_html]) with gr.Tab("New Papers"): new_count = gr.Textbox(label="Number of Papers Fetched") new_html = gr.HTML() new_button = gr.Button("Refresh Leaderboard") new_button.click(fn=lambda: update_display("latest"), inputs=None, outputs=[new_count, new_html]) with gr.Tab("Greatest Papers"): greatest_count = gr.Textbox(label="Number of Papers Fetched") greatest_html = gr.HTML() greatest_button = gr.Button("Refresh Leaderboard") greatest_button.click(fn=lambda: update_display("greatest"), inputs=None, outputs=[greatest_count, greatest_html]) download_button = gr.Button("📚 Download All Papers", variant="primary") download_output = gr.Textbox(label="Download Status") markdown_output = gr.Markdown(label="Paper Content") download_button.click(fn=download_all_papers, inputs=None, outputs=[download_output, markdown_output]) # Load initial data for all tabs demo.load(fn=load_all_data, outputs=[top_count, top_html, new_count, new_html, greatest_count, greatest_html]) # Launch the Gradio interface with a public link demo.launch(share=True)