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# app.py
import gradio as gr
import requests
from bs4 import BeautifulSoup
import google.generativeai as genai
import os
# Configure Gemini API
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
genai.configure(api_key=GEMINI_API_KEY)
def fetch_article_content(url):
"""Fetch article content using requests and BeautifulSoup"""
try:
headers = {'User-Agent': 'Mozilla/5.0'}
response = requests.get(url, headers=headers, timeout=10)
response.raise_for_status()
soup = BeautifulSoup(response.text, 'html.parser')
# Extract text from <p> tags
paragraphs = soup.find_all('p')
content = ' '.join([p.get_text(strip=True) for p in paragraphs])
return content
except Exception as e:
return f"Error fetching article: {str(e)}"
def generate_platform_post(article_text):
"""Generate optimized post using Gemini API"""
try:
model = genai.GenerativeModel('gemini-1.5-pro')
prompt = f"""
Analyze this article content and create:
1. A compelling title (max 100 characters)
2. An optimized post in HTML format for Reddit/Quora
3. Include an image tag with descriptive alt text
Article content:
{article_text[:5000]} # Limit to 5000 chars for token limits
Format your response as:
[TITLE]
[HTML_CONTENT]
Requirements:
- Clean HTML formatting with paragraphs
- Add relevant image tag with descriptive alt text
- Mobile-friendly design
- Minimal CSS styling
"""
response = model.generate_content(prompt)
return parse_gemini_response(response.text)
except Exception as e:
return {"title": "Error generating post", "content": f"<p>{str(e)}</p>"}
def parse_gemini_response(response):
"""Parse Gemini's response into title and content"""
try:
title = response.split("[TITLE]")[1].split("[HTML_CONTENT]")[0].strip()
content = response.split("[HTML_CONTENT]")[1].strip()
except:
title = "Content Generation Error"
content = "<p>Failed to parse response from AI</p>"
return {"title": title, "content": content}
def process_url(url):
"""Main processing pipeline"""
article_text = fetch_article_content(url)
if article_text.startswith("Error"):
return {"title": "Processing Error", "content": f"<p>{article_text}</p>"}
return generate_platform_post(article_text)
# Create Gradio interface
url_input = gr.Textbox(label="Article URL", placeholder="https://example.com/article...")
title_output = gr.Textbox(label="Generated Title")
content_output = gr.HTML(label="Generated Post")
app = gr.Interface(
fn=process_url,
inputs=url_input,
outputs=[
gr.Textbox(label="Generated Title"),
gr.HTML(label="Formatted Post")
],
examples=[
["https://example.com/sample-article"]
],
title="Article to Reddit/Quora Post Converter",
description="Convert news articles into optimized Reddit/Quora-style posts with AI-generated formatting and image descriptions"
)
if __name__ == "__main__":
app.launch() |