from googlesearch import search
from bs4 import BeautifulSoup
import requests

# Initialize BART tokenizer and summarization pipeline
tokenizer = BartTokenizer.from_pretrained('letgoofthepizza/Llama-3-8B-Instruct-ko-news-summary')
summarizer = pipeline("summarization", model="letgoofthepizza/Llama-3-8B-Instruct-ko-news-summary")

# Function to perform Google search and retrieve URLs, filtering by domain
def google_search(query: str, num_results: int = 10):
    """Perform a Google search and retrieve the URLs of the search results."""
    search_results = []
    for url in search(query, num_results=num_results):
        search_results.append(url)
    return search_results

# Function to fetch content from a URL and summarize it
def fetch_and_summarize_url(url: str):
    try:
        response = requests.get(url)
        response.raise_for_status()
        soup = BeautifulSoup(response.text, 'html.parser')
        
        # Extract relevant content (e.g., paragraphs or sections)
        paragraphs = [p.text for p in soup.find_all('p')]
        combined_text = " ".join(paragraphs[:3])  # Combine first few paragraphs for summary
        
        # Summarize using the pipeline
        if combined_text.strip():  # Ensure there is text to summarize
            summary = summarizer(combined_text, max_length=200, min_length=50, do_sample=False)
            return summary[0]['summary_text']
        else:
            return None
    except requests.RequestException as e:
        return None

# Function to perform Google search and aggregate summaries
def google_search_and_answer(question: str, keywords: str):
    search_query = f"{question} {keywords}"
    search_results = google_search(search_query)
    summaries = []
    for url in search_results:
        fetched_summary = fetch_and_summarize_url(url)
        if fetched_summary:
            # Add additional logic to filter summaries based on relevance
            # Example: Check if either question or keywords are present in fetched_summary
            if question.lower() in fetched_summary.lower() or keywords.lower() in fetched_summary.lower():
                summaries.append(fetched_summary)
    if summaries:
        return "\n\n".join(summaries)
    else:
        return "No relevant information found."

# Main function to run the script
def main():
    print("Intelligent Assistant")
    question = input("Enter your query: ")
    keywords = input("Enter specific keywords (e.g., 'Q1 2024 financial results Tesla'): ")
    answer = google_search_and_answer(question, keywords)
    print("Answer:", answer)

if __name__ == "__main__":
    main()