PaperPulse / app.py
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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 asyncio
import aiohttp
import aiofiles
from concurrent.futures import ThreadPoolExecutor
import re
from datetime import datetime
import base64
# ... (keep all the previous functions up to create_date_directory)
async def download_and_process_pdf(session, title, paper_info, directory):
pdf_url = paper_info['pdf_link']
if not pdf_url:
return f"No PDF link available for: {title}", None, None
try:
timeout = aiohttp.ClientTimeout(total=60) # 60 seconds timeout
async with session.get(pdf_url, timeout=timeout) as response:
if response.status != 200:
return f"Failed to download PDF for {title}: HTTP {response.status}", None, None
pdf_content = await response.read()
file_length = len(pdf_content)
if file_length < 5000: # Check if the PDF is less than 5KB
return f"Downloaded PDF for {title} is too small ({file_length} bytes). Skipping.", None, None
# Convert PDF to text
pdf_file = io.BytesIO(pdf_content)
pdf_reader = PyPDF2.PdfReader(pdf_file)
text = ""
for page in pdf_reader.pages:
text += page.extract_text()
if len(text) < 5000: # Check if the extracted text is less than 5KB
return f"Extracted text for {title} is too small ({len(text)} characters). Skipping.", None, None
safe_title = safe_filename(title)
txt_filename = f"{safe_title}.txt"
txt_filepath = os.path.join(directory, txt_filename)
async with aiofiles.open(txt_filepath, 'w', encoding='utf-8') as f:
await f.write(text)
return f"Successfully processed: {txt_filename} (File length: {file_length} bytes)", txt_filepath, text
except asyncio.TimeoutError:
return f"Timeout while downloading PDF for {title}", None, None
except Exception as e:
return f"Error processing PDF for {title}: {str(e)}", None, None
async def process_papers(data, directory, progress=gr.Progress()):
async with aiohttp.ClientSession() as session:
tasks = []
for title, paper_info in data.items():
task = asyncio.ensure_future(download_and_process_pdf(session, title, paper_info, directory))
tasks.append(task)
results = []
successful_downloads = []
errors = []
for i, task in enumerate(asyncio.as_completed(tasks), start=1):
result, filepath, text = await task
results.append(result)
if filepath and text:
successful_downloads.append((filepath, text))
else:
errors.append(result)
progress(i / len(tasks), f"Processed {i}/{len(tasks)} papers")
return results, successful_downloads, errors
def get_base64_download_link(content, filename):
"""Create a base64 download link for text content."""
b64 = base64.b64encode(content.encode()).decode()
return f'<a href="data:text/plain;base64,{b64}" download="{filename}">Download {filename}</a>'
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)
date_directory = create_date_directory()
results, successful_downloads, errors = asyncio.run(process_papers(all_data, date_directory, progress))
summary = f"Papers processed: {len(all_data)}\n"
summary += f"Successfully downloaded and converted: {len(successful_downloads)}\n"
summary += f"Errors: {len(errors)}\n\n"
summary += "Error List:\n" + "\n".join(errors) if errors else "No errors occurred."
download_links = []
text_contents = []
for filepath, text in successful_downloads:
filename = os.path.basename(filepath)
download_links.append(get_base64_download_link(text, filename))
text_contents.append(f"--- {filename} ---\n\n{text[:1000]}...\n\n") # Show first 1000 characters
return summary, "<br>".join(download_links), "\n".join(text_contents)
with gr.Blocks() as demo:
gr.Markdown("<h1><center>Papers Leaderboard</center></h1>")
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("πŸ“š Download All Papers", variant="primary")
download_output = gr.Textbox(label="Download Status")
download_links = gr.HTML(label="Download Links")
text_output = gr.Code(label="Paper Contents", language="text")
download_button.click(fn=download_all_papers, inputs=None, outputs=[download_output, download_links, text_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)