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Create app.py
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app.py
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import gradio as gr
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import requests
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from bs4 import BeautifulSoup
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import pdfkit
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import os
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import math
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# Function to extract all links from a website
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def extract_links(url):
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try:
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response = requests.get(url, headers={"User-Agent": "Mozilla/5.0"})
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if response.status_code != 200:
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return f"Error: Unable to fetch page (Status Code {response.status_code})", []
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soup = BeautifulSoup(response.text, "html.parser")
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base_url = "/".join(url.split("/")[:3]) # Extract base domain
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links = []
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for a_tag in soup.find_all("a", href=True):
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href = a_tag["href"]
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if not href.startswith("http"): # Convert relative links to absolute
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href = base_url + href if href.startswith("/") else base_url + "/" + href
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links.append(href)
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links = list(set(links)) # Remove duplicates
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if not links:
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return "No links found on the website.", []
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return f"✅ {len(links)} links found! Select which ones to convert into PDFs:", links
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except Exception as e:
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return f"Error: {str(e)}", []
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# Function to clean unwanted content (like headers, footers, etc.)
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def clean_content(soup):
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# Remove common unwanted elements
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for tag in soup.find_all(["header", "footer", "nav", "aside", "script", "style"]):
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tag.decompose() # Remove the tag completely
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# You can also remove specific classes or IDs if necessary, for example:
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# for tag in soup.find_all(attrs={"class": "footer"}):
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# tag.decompose()
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# Get the cleaned text from the remaining content
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return soup.get_text(separator="\n", strip=True)
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# Function to scrape selected links and generate PDFs
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def scrape_and_generate_pdfs(selected_links):
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try:
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if not selected_links:
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return "No links selected.", None
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pdf_files = []
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batch_size = 4 # Each PDF contains up to 4 links
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# Process selected links in batches of 4
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for i in range(0, len(selected_links), batch_size):
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batch_links = selected_links[i:i + batch_size]
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all_text = ""
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# Scrape text content from each selected link
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for link in batch_links:
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try:
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response = requests.get(link, headers={"User-Agent": "Mozilla/5.0"})
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if response.status_code == 200:
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soup = BeautifulSoup(response.text, "html.parser")
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page_text = clean_content(soup)
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all_text += f"--- Content from: {link} ---\n\n" + page_text + "\n\n"
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except:
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all_text += f"Failed to fetch content from {link}\n\n"
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if all_text:
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pdf_filename = f"output_{(i//batch_size) + 1}.pdf"
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# Save as temporary HTML file
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html_path = f"temp_{i}.html"
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with open(html_path, "w", encoding="utf-8") as f:
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f.write(f"<html><body><pre>{all_text}</pre></body></html>")
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# Convert HTML to PDF
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pdfkit.from_file(html_path, pdf_filename)
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os.remove(html_path)
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pdf_files.append(pdf_filename)
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return pdf_files # Return list of generated PDFs
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except Exception as e:
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return f"Error: {str(e)}", None
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# Gradio UI with link selection
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def show_links_and_generate_pdfs(url):
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message, links = extract_links(url)
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if not links:
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return message, gr.update(choices=[], value=[])
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return message, gr.update(choices=links, value=[])
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iface = gr.Blocks()
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with iface:
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gr.Markdown("### 🌐 Web Scraper & PDF Generator")
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gr.Markdown("Enter a website URL to extract internal links, then select which links to convert into PDFs (4 links per PDF).")
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url_input = gr.Textbox(label="Enter Website URL")
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extract_btn = gr.Button("Extract Links")
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message_output = gr.Markdown("")
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link_selector = gr.CheckboxGroup([], label="Select Links to Convert", interactive=True)
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generate_btn = gr.Button("Generate PDFs")
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pdf_output = gr.File(label="Download Generated PDFs")
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extract_btn.click(show_links_and_generate_pdfs, inputs=url_input, outputs=[message_output, link_selector])
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generate_btn.click(scrape_and_generate_pdfs, inputs=link_selector, outputs=pdf_output)
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iface.launch()
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