# app.py
import gradio as gr
from bs4 import BeautifulSoup
import requests
from transformers import pipeline
from sentence_transformers import SentenceTransformer
import faiss
import numpy as np

# Initialize models and variables
summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
embedding_model = SentenceTransformer('all-MiniLM-L6-v2')
index = None
bookmarks = []
fetch_cache = {}

# Helper functions as defined above...

def parse_bookmarks(file_content):
    # [Code from Step 4.1]

def fetch_url_info(bookmark):
    # [Code from Step 4.2]

def generate_summary(bookmark):
    # [Code from Step 4.3]

def vectorize_and_index(bookmarks):
    # [Code from Step 4.4]

def process_uploaded_file(file):
    # [Code from Step 5.1]

def chatbot_response(user_query):
    # [Code from Step 5.2]

def display_bookmarks():
    # [Code from Step 5.3]

def edit_bookmark(index, new_title, new_url):
    # [Code from Step 5.3]

def delete_bookmark(index):
    # [Code from Step 5.3]

def build_app():
    # [Code from Step 6]

if __name__ == "__main__":
    build_app()