# Import necessary libraries
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):
    try:
        response = requests.get(url)
        soup = BeautifulSoup(response.content, 'html.parser')

        # Extract title and content
        title = soup.find('title').get_text()
        paragraphs = soup.find_all('p')
        content = '\n'.join([para.get_text() for para in paragraphs])

        return title, content
    except Exception as e:
        return None, f"Error fetching content: {str(e)}"

# Function to summarize content in the selected language
def summarize_content(content, language):
    # Define the prompt based on selected language
    language_prompts = {
        "Hindi": "in Hindi",
        "English": "in English",
        "Telugu": "in Telugu",
        "Kannada": "in Kannada",
        "Marathi": "in Marathi",
        "Bengali": "in Bengali",
            "Tamil": "in Tamil",
        "Gujarati": "in Gujarati",
        "Malayalam": "in Malayalam"
    }

    prompt = f"Summarize the following news article {language_prompts[language]} in about 200 words:\n\n{content}\n\n"

    try:
        # Generate summary using the OpenAI Chat API
        response = openai.chat.completions.create(
            model="gpt-4o",  # Use the latest GPT model
            messages=[
                {"role": "system", "content": f"You are a highly skilled news editor and summarization assistant. Your task is to produce clear, concise, and accurate summaries of news articles {language_prompts[language]}. Focus on capturing the key points, context, and implications while preserving the original tone and intent of the article. Ensure the summary is engaging, fact-based, and suitable for readers seeking a quick yet comprehensive understanding of the news."},
                {"role": "user", "content": prompt}
            ],
            max_tokens=500,  # Allows responses of up to ~200 words
            temperature=0.2  # More deterministic output
        )
        # Extract the summary from the response
        summary = response.choices[0].message.content.strip()
        return summary
    except Exception as e:
        return f"Error generating summary: {str(e)}"

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

    title, content = scrape_content(url)

    if content.startswith("Error"):
        return content

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

# Gradio interface
iface = gr.Interface(
    fn=process_url,
    inputs=[
        gr.Textbox(lines=2, placeholder="Enter URL here...", label="News Article URL"),
        gr.Dropdown(
            ["Hindi","English", "Telugu", "Kannada", "Marathi", "Bengali", "Gujarati","Tamil","Malayalam"],
            label="Select Language",
            value="Hindi"
        )
    ],
    outputs="text",
    title="Multilingual News Article Summarizer",
    description="Enter a News Site URL and select a language to generate a 200-word summary."
)

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