app.py

import requests
from bs4 import BeautifulSoup
import openai
import gradio as gr
import os
from dotenv import load_dotenv

# Load environment variables from .env file
load_dotenv()
openai.api_key = os.getenv("OPENAI_API_KEY")

# Function to scrape content from a URL
def scrape_content(url):
    response = requests.get(url)
    soup = BeautifulSoup(response.content, 'html.parser')

    # Example of extracting title and body content - modify based on actual structure of the websites
    title = soup.find('title').get_text()
    paragraphs = soup.find_all('p')
    content = '\n'.join([para.get_text() for para in paragraphs])

    return title, content

# Function to summarize content using OpenAI
def summarize_content(content):
    prompt = f"Summarize the following news article in about 100 words:\n\n{content}\n\n"

    response = openai.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "system", "content": "You are a helpful assistant that summarizes news articles in about 60 words."},
            {"role": "user", "content": prompt}
        ],
        max_tokens=300,
        temperature=0.2
    )

    summary = response.choices[0].message.content.strip()
    return summary

# Function to process a single URL and generate a summary
def process_url(url):
    if not url:
        return "No URL provided."

    title, content = scrape_content(url)
    summary = summarize_content(content)
    return f"Title: {title}\n\nSummary:\n{summary}"

# Gradio interface
iface = gr.Interface(
    fn=process_url,
    inputs=gr.Textbox(lines=2, placeholder="Enter URL here..."),
    outputs="text",
    title="News Article Summarizer",
    description="Enter a News Site URL to generate a 100-word summary."
)

# Launch the interface
if __name__ == "__main__":
    iface.launch(share=True)