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Update app.py
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app.py
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import gradio as gr
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import spaces
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# ============================================================
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#
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# This satisfies Hugging Face's startup requirement
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# ============================================================
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@spaces.GPU(duration=1)
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def noop_gpu_function():
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"""
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This dummy function satisfies the Hugging Face Space
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startup requirement. It doesn't actually use GPU.
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"""
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pass
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# ============================================================
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#
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# ============================================================
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def
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"""
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# ============================================================
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#
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# ============================================================
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demo = gr.Interface(
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fn=
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inputs=
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)
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# ============================================================
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#
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# ============================================================
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demo.launch(server_name="0.0.0.0", server_port=7860)
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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 spaces
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# ============================================================
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# REQUIRED: @spaces.GPU decorator for Hugging Face
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# ============================================================
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@spaces.GPU(duration=1)
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def noop_gpu_function():
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"""Dummy function to satisfy Hugging Face startup"""
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pass
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# ============================================================
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# SCRAPER FUNCTION
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# ============================================================
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def scrape_website(url, keyword, max_results=5):
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"""Scrape a website and extract links containing the keyword"""
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results = []
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# Ensure URL has protocol
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if not url.startswith(('http://', 'https://')):
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url = 'https://' + url
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try:
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# Fetch the webpage
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headers = {
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'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
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}
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response = requests.get(url, headers=headers, timeout=30)
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response.raise_for_status()
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# Parse HTML
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soup = BeautifulSoup(response.text, 'html.parser')
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# Remove unwanted elements
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for element in soup(['script', 'style', 'nav', 'footer', 'header']):
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element.decompose()
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# Find all links
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links = soup.find_all('a', href=True)
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keyword_lower = keyword.lower()
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for link in links:
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try:
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href = link.get('href', '')
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text = link.get_text(strip=True)
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# Skip invalid links
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if not href or href.startswith('#') or href.startswith('javascript:') or not text:
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continue
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# Check if keyword is in the link text or URL
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if keyword_lower in text.lower() or keyword_lower in href.lower():
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results.append({
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'title': text[:100],
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'url': href,
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'source': url
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})
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if len(results) >= max_results:
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break
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except Exception as e:
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continue
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# Format results for display
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if results:
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output = f"✅ **Found {len(results)} results for '{keyword}':**\n\n"
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for i, item in enumerate(results, 1):
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output += f"**{i}. {item['title']}**\n"
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output += f" 🔗 {item['url']}\n\n"
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return output
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else:
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return f"⚠️ No results found for '{keyword}' at {url}"
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except requests.exceptions.RequestException as e:
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return f"❌ Network error: {str(e)}"
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except Exception as e:
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return f"❌ Error: {str(e)}"
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# ============================================================
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# GRADIO INTERFACE
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# ============================================================
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demo = gr.Interface(
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fn=scrape_website,
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inputs=[
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gr.Textbox(
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label="URL",
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placeholder="https://www.pinterest.com/search/pins/?q=planner",
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value="https://www.pinterest.com/search/pins/?q=planner"
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),
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gr.Textbox(
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label="Keyword",
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placeholder="planner, notion, template, etc.",
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value="planner"
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),
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gr.Slider(
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minimum=1,
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maximum=20,
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value=5,
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step=1,
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label="Max Results"
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)
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],
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outputs=gr.Markdown(label="Results"),
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title="🕷️ Market Scraper",
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description="Scrape websites to find content related to your market research keywords."
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)
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# ============================================================
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# LAUNCH (MUST be at module level)
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# ============================================================
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demo.launch(server_name="0.0.0.0", server_port=7860)
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