Update README.md

README.md

@@ -8,1067 +8,146 @@ sdk_version: 5.5.0
 app_file: app.py
 pinned: false
 ---
-# 📚 SmartMarks - AI Browser Bookmarks Manager
+📚 SmartMarks - AI Browser Bookmarks Manager
 
-![License](https://img.shields.io/badge/license-MIT-blue.svg)
-![Gradio](https://img.shields.io/badge/Gradio-v3.38.0-blue)
-![Python](https://img.shields.io/badge/Python-3.8%2B-blue.svg)
-![Hugging Face Spaces](https://img.shields.io/badge/Hugging%20Face-Spaces-green.svg)
 
-## 🌟 Overview
-
-**SmartMarks** is your intelligent assistant for managing browser bookmarks. Leveraging the power of AI, SmartMarks helps you organize, search, and interact with your bookmarks seamlessly. Whether you're looking to categorize your links, retrieve information quickly, or maintain an updated list, SmartMarks has you covered.
-
-### Key Features
-
-- **📂 Upload and Process Bookmarks:** Import your existing bookmarks and let SmartMarks analyze and categorize them for you.
-- **💬 Chat with Bookmarks:** Interact with your bookmarks using natural language queries to find relevant links effortlessly.
-- **🛠️ Manage Bookmarks:** View, edit, delete, and export your bookmarks with ease.
-- **🎨 Dynamic Color Theme:** Automatically adapts to your system or browser's light/dark mode preferences for optimal readability and aesthetics.
-
-## 🚀 How to Use SmartMarks
+🌟 Overview
+SmartMarks is your intelligent assistant for managing browser bookmarks. Leveraging the power of AI, SmartMarks helps you organize, search, and interact with your bookmarks seamlessly. Whether you're looking to categorize your links, retrieve information quickly, or maintain an updated list, SmartMarks has you covered.
 
+Key Features
+📂 Upload and Process Bookmarks: Import your existing bookmarks and let SmartMarks analyze and categorize them for you.
+💬 Chat with Bookmarks: Interact with your bookmarks using natural language queries to find relevant links effortlessly.
+🛠️ Manage Bookmarks: View, edit, delete, and export your bookmarks with ease.
+🚀 High Processing Speed: Enhanced performance through concurrent fetching and processing of bookmarks.
+🎨 Dynamic Color Theme: Automatically adapts to your system or browser's light/dark mode preferences for optimal readability and aesthetics.
+🚀 How to Use SmartMarks
 SmartMarks is divided into three main sections:
 
-1. **📂 Upload and Process Bookmarks:** Import and process your bookmarks.
-2. **💬 Chat with Bookmarks:** Ask questions about your bookmarks using natural language.
-3. **🛠️ Manage Bookmarks:** Manage your bookmarks by viewing, editing, deleting, and exporting them.
-
+📂 Upload and Process Bookmarks: Import and process your bookmarks.
+💬 Chat with Bookmarks: Ask questions about your bookmarks using natural language.
+🛠️ Manage Bookmarks: Manage your bookmarks by viewing, editing, deleting, and exporting them.
 Navigate through the tabs to explore each feature in detail.
 
-## 📦 Deployment on Hugging Face Spaces
-
-SmartMarks is designed to run seamlessly on [Hugging Face Spaces](https://huggingface.co/spaces), providing an interactive and user-friendly interface.
-
-### Prerequisites
-
-- **Hugging Face Account:** To deploy on Hugging Face Spaces, you need an account. Sign up [here](https://huggingface.co/join).
-- **API Key:** SmartMarks utilizes the Groq Cloud API for its chatbot functionality. Ensure you have a valid `GROQ_API_KEY`.
-
-### Repository Structure
-
-smartmarks/ │ ├── app.py ├── app.css ├── requirements.txt ├── README.md ├── LICENSE └── screenshots/ ├── light_mode.png └── dark_mode.png
-
-
-### Setting Up Environment Variables
-
-1. **GROQ_API_KEY:**  
-   SmartMarks requires the `GROQ_API_KEY` to interact with the Groq Cloud API. To set this up:
-
-   - Navigate to your Space's dashboard on Hugging Face.
-   - Go to **Settings** > **Secrets**.
-   - Add a new secret with the key `GROQ_API_KEY` and paste your API key as the value.
-
-   > **Note:** Keep your API keys secure. Never expose them in your code or repository.
-
-### Installing Dependencies
-
-Hugging Face Spaces automatically installs dependencies listed in the `requirements.txt` file. Ensure your `requirements.txt` includes all necessary packages:
-
-```plaintext
-gradio
-beautifulsoup4
-sentence-transformers
-faiss-cpu
-aiohttp
-openai
-uuid
-
-
-
-Thought for 8 seconds
-Certainly! Below are the updated app.css and README.md files for your SmartMarks - AI Browser Bookmarks Manager application. Additionally, I've included the necessary updates to your app.py to ensure that the external CSS file is properly integrated. These changes aim to enhance the application's appearance and maintainability by separating styles from the Python code.
-
-1. app.css
-This CSS file contains all the styles previously embedded within your app.py. By moving the styles to an external file, you enhance the maintainability and scalability of your application.
-
-css
-Copy code
-/* app.css */
-
-/* Card Styling */
-.card {
-    box-shadow: 0 4px 8px 0 rgba(0,0,0,0.2);
-    transition: 0.3s;
-    padding: 10px;
-    margin: 10px;
-    border-radius: 5px;
-}
-
-.card:hover {
-    box-shadow: 0 8px 16px 0 rgba(0,0,0,0.2);
-}
-
-/* Dynamic Theme Styling */
-@media (prefers-color-scheme: dark) {
-    body {
-        color: white;
-        background-color: #121212;
-    }
-    .card {
-        background-color: #1e1e1e;
-    }
-    a {
-        color: #bb86fc;
-    }
-    h1, h2, h3, p, strong {
-        color: inherit;
-    }
-}
-
-@media (prefers-color-scheme: light) {
-    body {
-        color: black;
-        background-color: white;
-    }
-    .card {
-        background-color: #fff;
-    }
-    a {
-        color: #1a0dab;
-    }
-    h1, h2, h3, p, strong {
-        color: inherit;
-    }
-}
-2. Updated app.py
-To integrate the external app.css file, update your app.py by modifying the gr.Blocks initialization to load the CSS from the app.css file instead of embedding it directly. Ensure that the app.css file is located in the same directory as your app.py or adjust the path accordingly.
-
-python
-Copy code
-# app.py
-
-import gradio as gr
-from bs4 import BeautifulSoup
-from sentence_transformers import SentenceTransformer
-import faiss
-import numpy as np
-import asyncio
-import aiohttp
-import re
-import base64
-import logging
-import os
-import sys
-import uuid  # For unique IDs
-
-# Import OpenAI library
-import openai
-
-# Set up logging to output to the console
-logger = logging.getLogger(__name__)
-logger.setLevel(logging.INFO)
-
-# Create a console handler
-console_handler = logging.StreamHandler(sys.stdout)
-console_handler.setLevel(logging.INFO)
-
-# Create a formatter and set it for the handler
-formatter = logging.Formatter('%(asctime)s %(levelname)s %(name)s %(message)s')
-console_handler.setFormatter(formatter)
-
-# Add the handler to the logger
-logger.addHandler(console_handler)
-
-# Initialize models and variables
-logger.info("Initializing models and variables")
-embedding_model = SentenceTransformer('all-MiniLM-L6-v2')
-faiss_index = faiss.IndexIDMap(faiss.IndexFlatL2(embedding_model.get_sentence_embedding_dimension()))
-bookmarks = []
-fetch_cache = {}
-
-# Define the categories
-CATEGORIES = [
-    "Social Media",
-    "News and Media",
-    "Education and Learning",
-    "Entertainment",
-    "Shopping and E-commerce",
-    "Finance and Banking",
-    "Technology",
-    "Health and Fitness",
-    "Travel and Tourism",
-    "Food and Recipes",
-    "Sports",
-    "Arts and Culture",
-    "Government and Politics",
-    "Business and Economy",
-    "Science and Research",
-    "Personal Blogs and Journals",
-    "Job Search and Careers",
-    "Music and Audio",
-    "Videos and Movies",
-    "Reference and Knowledge Bases",
-    "Dead Link",
-    "Uncategorized",
-]
-
-# Set up Groq Cloud API key and base URL
-GROQ_API_KEY = os.getenv('GROQ_API_KEY')
-
-if not GROQ_API_KEY:
-    logger.error("GROQ_API_KEY environment variable not set.")
-
-# Set OpenAI API key and base URL to use Groq Cloud API
-openai.api_key = GROQ_API_KEY
-openai.api_base = "https://api.groq.com/openai/v1"  # Corrected API base URL
-
-# Function to parse bookmarks from HTML
-def parse_bookmarks(file_content):
-    logger.info("Parsing bookmarks")
-    try:
-        soup = BeautifulSoup(file_content, 'html.parser')
-        extracted_bookmarks = []
-        for link in soup.find_all('a'):
-            url = link.get('href')
-            title = link.text.strip()
-            if url and title:
-                extracted_bookmarks.append({'url': url, 'title': title})
-        logger.info(f"Extracted {len(extracted_bookmarks)} bookmarks")
-        return extracted_bookmarks
-    except Exception as e:
-        logger.error("Error parsing bookmarks: %s", e)
-        raise
-
-# Asynchronous function to fetch URL info
-async def fetch_url_info(session, bookmark):
-    url = bookmark['url']
-    if url in fetch_cache:
-        bookmark.update(fetch_cache[url])
-        return bookmark
-
-    try:
-        logger.info(f"Fetching URL info for: {url}")
-        async with session.get(url, timeout=10) as response:
-            bookmark['etag'] = response.headers.get('ETag', 'N/A')
-            bookmark['status_code'] = response.status
-
-            if response.status >= 400:
-                bookmark['dead_link'] = True
-                bookmark['description'] = ''
-                logger.warning(f"Dead link detected: {url} with status {response.status}")
-            else:
-                bookmark['dead_link'] = False
-                content = await response.text()
-                soup = BeautifulSoup(content, 'html.parser')
-
-                # Extract meta description or Open Graph description
-                meta_description = soup.find('meta', attrs={'name': 'description'})
-                og_description = soup.find('meta', attrs={'property': 'og:description'})
-                if og_description and og_description.get('content'):
-                    description = og_description.get('content')
-                elif meta_description and meta_description.get('content'):
-                    description = meta_description.get('content')
-                else:
-                    # If no description, extract visible text
-                    texts = soup.stripped_strings
-                    description = ' '.join(texts[:200])  # Limit to first 200 words
-                    # Generate summary using LLM
-                    description = generate_summary_with_llm(description)
-
-                bookmark['description'] = description
-                logger.info(f"Fetched description for {url}")
-    except Exception as e:
-        bookmark['dead_link'] = True
-        bookmark['etag'] = 'N/A'
-        bookmark['status_code'] = 'N/A'
-        bookmark['description'] = ''
-        logger.error(f"Error fetching URL info for {url}: {e}")
-    finally:
-        fetch_cache[url] = {
-            'etag': bookmark.get('etag'),
-            'status_code': bookmark.get('status_code'),
-            'dead_link': bookmark.get('dead_link'),
-            'description': bookmark.get('description'),
-        }
-    return bookmark
-
-# Asynchronous processing of bookmarks
-async def process_bookmarks_async(bookmarks_list):
-    logger.info("Processing bookmarks asynchronously")
-    try:
-        async with aiohttp.ClientSession() as session:
-            tasks = []
-            for bookmark in bookmarks_list:
-                task = asyncio.ensure_future(fetch_url_info(session, bookmark))
-                tasks.append(task)
-            await asyncio.gather(*tasks)
-        logger.info("Completed processing bookmarks asynchronously")
-    except Exception as e:
-        logger.error(f"Error in asynchronous processing of bookmarks: {e}")
-        raise
-
-# Generate summary for a bookmark using LLM
-def generate_summary_with_llm(text):
-    logger.info("Generating summary with LLM")
-    try:
-        prompt = f"Summarize the following content in a concise manner:\n\n{text}"
-        response = openai.ChatCompletion.create(
-            model='gpt-3.5-turbo',  # Use appropriate model
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant that summarizes text."},
-                {"role": "user", "content": prompt}
-            ],
-            max_tokens=150,
-            temperature=0.5,
-        )
-        summary = response['choices'][0]['message']['content'].strip()
-        logger.info("Summary generated successfully")
-        return summary
-    except Exception as e:
-        logger.error(f"Error generating summary with LLM: {e}")
-        return "No summary available."
-
-# Generate summary for a bookmark
-def generate_summary(bookmark):
-    description = bookmark.get('description', '')
-    if description:
-        bookmark['summary'] = description
-    else:
-        # Fallback summary generation
-        title = bookmark.get('title', '')
-        if title:
-            bookmark['summary'] = title
-        else:
-            bookmark['summary'] = 'No summary available.'
-    logger.info(f"Generated summary for bookmark: {bookmark.get('url')}")
-    return bookmark
-
-# Assign category to a bookmark using LLM
-def assign_category_with_llm(summary):
-    logger.info("Assigning category with LLM")
-    try:
-        categories_str = ', '.join(CATEGORIES)
-        prompt = f"Assign the most appropriate category to the following summary from the list of categories.\n\nSummary: {summary}\n\nCategories: {categories_str}\n\nCategory:"
-        response = openai.ChatCompletion.create(
-            model='gpt-3.5-turbo',  # Use appropriate model
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant that assigns categories."},
-                {"role": "user", "content": prompt}
-            ],
-            max_tokens=10,
-            temperature=0.3,
-        )
-        category = response['choices'][0]['message']['content'].strip()
-        # Ensure the category is valid
-        if category in CATEGORIES:
-            logger.info(f"Assigned category '{category}' successfully")
-            return category
-        else:
-            logger.warning(f"Received invalid category '{category}' from LLM. Defaulting to 'Uncategorized'.")
-            return "Uncategorized"
-    except Exception as e:
-        logger.error(f"Error assigning category with LLM: {e}")
-        return "Uncategorized"
-
-# Assign category to a bookmark
-def assign_category(bookmark):
-    if bookmark.get('dead_link'):
-        bookmark['category'] = 'Dead Link'
-        logger.info(f"Assigned category 'Dead Link' to bookmark: {bookmark.get('url')}")
-        return bookmark
-
-    summary = bookmark.get('summary', '')
-    if summary:
-        category = assign_category_with_llm(summary)
-        bookmark['category'] = category
-    else:
-        bookmark['category'] = 'Uncategorized'
-        logger.info(f"No summary available to assign category for bookmark: {bookmark.get('url')}")
-    return bookmark
-
-# Vectorize summaries and build FAISS index
-def vectorize_and_index(bookmarks_list):
-    global faiss_index
-    logger.info("Vectorizing summaries and updating FAISS index")
-    try:
-        summaries = [bookmark['summary'] for bookmark in bookmarks_list]
-        embeddings = embedding_model.encode(summaries).astype('float32')
-        ids = [uuid.uuid4().int & (1<<64)-1 for _ in bookmarks_list]  # Generate unique 64-bit integer IDs
-        faiss_index.add_with_ids(embeddings, np.array(ids))
-        logger.info("FAISS index updated successfully")
-        return embeddings, ids
-    except Exception as e:
-        logger.error(f"Error in vectorizing and indexing: {e}")
-        raise
-
-# Remove vectors from FAISS index by IDs
-def remove_from_faiss(ids_to_remove):
-    global faiss_index
-    logger.info(f"Removing {len(ids_to_remove)} vectors from FAISS index")
-    try:
-        faiss_index.remove_ids(np.array(ids_to_remove))
-        logger.info("Vectors removed from FAISS index successfully")
-    except Exception as e:
-        logger.error(f"Error removing vectors from FAISS index: {e}")
-
-# Generate HTML display for bookmarks
-def display_bookmarks():
-    logger.info("Generating HTML display for bookmarks")
-    cards = ''
-    for i, bookmark in enumerate(bookmarks):
-        index = i + 1  # Start index at 1
-        status = "❌ Dead Link" if bookmark.get('dead_link') else "✅ Active"
-        title = bookmark['title']
-        url = bookmark['url']
-        etag = bookmark.get('etag', 'N/A')
-        summary = bookmark.get('summary', '')
-        category = bookmark.get('category', 'Uncategorized')
-
-        # Apply inline styles using CSS variables
-        if bookmark.get('dead_link'):
-            card_style = "border: 2px solid var(--error-color);"
-            text_style = "color: var(--error-color);"
-        else:
-            card_style = "border: 2px solid var(--success-color);"
-            text_style = "color: var(--text-color);"
-
-        card_html = f'''
-        <div class="card" style="{card_style}; padding: 10px; margin: 10px; border-radius: 5px;">
-            <div class="card-content">
-                <h3 style="{text_style}">{index}. {title} {status}</h3>
-                <p style="{text_style}"><strong>Category:</strong> {category}</p>
-                <p style="{text_style}"><strong>URL:</strong> <a href="{url}" target="_blank" style="{text_style}">{url}</a></p>
-                <p style="{text_style}"><strong>ETag:</strong> {etag}</p>
-                <p style="{text_style}"><strong>Summary:</strong> {summary}</p>
-            </div>
-        </div>
-        '''
-        cards += card_html
-    logger.info("HTML display generated")
-    return cards
-
-# Process the uploaded file
-def process_uploaded_file(file, state_bookmarks):
-    global bookmarks, faiss_index
-    logger.info("Processing uploaded file")
-    if file is None:
-        logger.warning("No file uploaded")
-        return (
-            "⚠️ Please upload a bookmarks HTML file.",
-            "",
-            gr.update(choices=[]),
-            display_bookmarks(),
-            state_bookmarks  # Return the unchanged state
-        )
-
-    try:
-        file_content = file.decode('utf-8')
-    except UnicodeDecodeError as e:
-        logger.error(f"Error decoding the file: {e}")
-        return (
-            "⚠️ Error decoding the file. Please ensure it's a valid HTML file.",
-            "",
-            gr.update(choices=[]),
-            display_bookmarks(),
-            state_bookmarks  # Return the unchanged state
-        )
-
-    try:
-        bookmarks = parse_bookmarks(file_content)
-    except Exception as e:
-        logger.error(f"Error parsing bookmarks: {e}")
-        return (
-            "⚠️ Error parsing the bookmarks HTML file.",
-            "",
-            gr.update(choices=[]),
-            display_bookmarks(),
-            state_bookmarks  # Return the unchanged state
-        )
-
-    if not bookmarks:
-        logger.warning("No bookmarks found in the uploaded file")
-        return (
-            "⚠️ No bookmarks found in the uploaded file.",
-            "",
-            gr.update(choices=[]),
-            display_bookmarks(),
-            state_bookmarks  # Return the unchanged state
-        )
-
-    # Asynchronously fetch bookmark info
-    try:
-        asyncio.run(process_bookmarks_async(bookmarks))
-    except Exception as e:
-        logger.error(f"Error processing bookmarks asynchronously: {e}")
-        return (
-            "⚠️ Error processing bookmarks.",
-            "",
-            gr.update(choices=[]),
-            display_bookmarks(),
-            state_bookmarks  # Return the unchanged state
-        )
-
-    # Generate summaries and assign categories
-    for bookmark in bookmarks:
-        generate_summary(bookmark)
-        assign_category(bookmark)
-
-    try:
-        embeddings, ids = vectorize_and_index(bookmarks)
-    except Exception as e:
-        logger.error(f"Error building FAISS index: {e}")
-        return (
-            "⚠️ Error building search index.",
-            "",
-            gr.update(choices=[]),
-            display_bookmarks(),
-            state_bookmarks  # Return the unchanged state
-        )
-
-    # Assign unique IDs to bookmarks
-    for bookmark, id_ in zip(bookmarks, ids):
-        bookmark['id'] = id_
-
-    message = f"✅ Successfully processed {len(bookmarks)} bookmarks."
-    logger.info(message)
-    bookmark_html = display_bookmarks()
-
-    # Prepare Manage Bookmarks tab outputs
-    choices = [f"{i+1}. {bookmark['title']} (Category: {bookmark['category']})" for i, bookmark in enumerate(bookmarks)]
-    bookmarks_html_manage = display_bookmarks()
-
-    # Update the shared state
-    updated_state = bookmarks.copy()
-
-    return (
-        message,
-        bookmark_html,
-        gr.update(choices=choices, value=[]),
-        bookmarks_html_manage,
-        updated_state  # Return the updated state
-    )
-
-# Delete selected bookmarks
-def delete_selected_bookmarks(selected_indices, state_bookmarks):
-    if not selected_indices:
-        return "⚠️ No bookmarks selected.", gr.update(choices=[]), display_bookmarks(), state_bookmarks
-
-    bookmarks = state_bookmarks.copy()
-    ids_to_remove = []
-    indices = []
-    for s in selected_indices:
-        try:
-            idx = int(s.split('.')[0]) - 1
-            if 0 <= idx < len(bookmarks):
-                ids_to_remove.append(bookmarks[idx]['id'])
-                indices.append(idx)
-            else:
-                logger.warning(f"Index out of range: {idx + 1}")
-        except ValueError:
-            logger.error(f"Invalid selection format: {s}")
-
-    # Remove bookmarks from the list
-    indices = sorted(indices, reverse=True)
-    for idx in indices:
-        logger.info(f"Deleting bookmark at index {idx + 1}")
-        bookmarks.pop(idx)
-
-    # Remove embeddings from FAISS index
-    remove_from_faiss(ids_to_remove)
-
-    message = "🗑️ Selected bookmarks deleted successfully."
-    logger.info(message)
-
-    # Regenerate HTML display
-    bookmarks_html = display_bookmarks()
-
-    # Update choices for selection
-    choices = [f"{i+1}. {bookmark['title']} (Category: {bookmark['category']})" for i, bookmark in enumerate(bookmarks)]
-
-    # Update the shared state
-    updated_state = bookmarks.copy()
-
-    return message, gr.update(choices=choices, value=[]), bookmarks_html, updated_state
-
-# Edit category of selected bookmarks
-def edit_selected_bookmarks_category(selected_indices, new_category, state_bookmarks):
-    if not selected_indices:
-        return (
-            "⚠️ No bookmarks selected.",
-            gr.update(choices=[f"{i+1}. {bookmark['title']} (Category: {bookmark['category']})" for i, bookmark in enumerate(state_bookmarks)], value=[]),
-            display_bookmarks(),
-            state_bookmarks
-        )
-
-    if not new_category:
-        return (
-            "⚠️ No new category selected.",
-            gr.update(choices=[f"{i+1}. {bookmark['title']} (Category: {bookmark['category']})" for i, bookmark in enumerate(state_bookmarks)], value=[]),
-            display_bookmarks(),
-            state_bookmarks
-        )
-
-    bookmarks = state_bookmarks.copy()
-    for s in selected_indices:
-        try:
-            idx = int(s.split('.')[0]) - 1
-            if 0 <= idx < len(bookmarks):
-                bookmarks[idx]['category'] = new_category
-                logger.info(f"Updated category for bookmark {idx + 1} to {new_category}")
-        except ValueError:
-            logger.error(f"Invalid selection format: {s}")
-
-    message = "✏️ Category updated for selected bookmarks."
-    logger.info(message)
-
-    # Regenerate HTML display
-    bookmarks_html = display_bookmarks()
-
-    # Update choices for selection
-    choices = [f"{i+1}. {bookmark['title']} (Category: {bookmark['category']})" for i, bookmark in enumerate(bookmarks)]
-
-    # Update the shared state
-    updated_state = bookmarks.copy()
-
-    return message, gr.update(choices=choices, value=[]), bookmarks_html, updated_state
-
-# Export bookmarks to HTML
-def export_bookmarks(state_bookmarks):
-    bookmarks = state_bookmarks
-    if not bookmarks:
-        logger.warning("No bookmarks to export")
-        return "⚠️ No bookmarks to export."
-    try:
-        logger.info("Exporting bookmarks to HTML")
-        # Create an HTML content similar to the imported bookmarks file
-        soup = BeautifulSoup("<!DOCTYPE NETSCAPE-Bookmark-file-1><Title>Bookmarks</Title><H1>Bookmarks</H1>", 'html.parser')
-        dl = soup.new_tag('DL')
-        for bookmark in bookmarks:
-            dt = soup.new_tag('DT')
-            a = soup.new_tag('A', href=bookmark['url'])
-            a.string = bookmark['title']
-            dt.append(a)
-            dl.append(dt)
-        soup.append(dl)
-        html_content = str(soup)
-        # Encode the HTML content to base64 for download
-        b64 = base64.b64encode(html_content.encode()).decode()
-        href = f'data:text/html;base64,{b64}'
-        logger.info("Bookmarks exported successfully")
-        return f'<a href="{href}" download="bookmarks.html">💾 Download Exported Bookmarks</a>'
-    except Exception as e:
-        logger.error(f"Error exporting bookmarks: {e}")
-        return "⚠️ Error exporting bookmarks."
-
-# Chatbot response using Groq Cloud API with FAISS search
-def chatbot_response(user_query, state_bookmarks):
-    if not GROQ_API_KEY:
-        logger.warning("GROQ_API_KEY not set.")
-        return "⚠️ API key not set. Please set the GROQ_API_KEY environment variable in the Hugging Face Space settings."
-
-    bookmarks = state_bookmarks
-    if not bookmarks:
-        logger.warning("No bookmarks available for chatbot")
-        return "⚠️ No bookmarks available. Please upload and process your bookmarks first."
-
-    logger.info(f"Chatbot received query: {user_query}")
-
-    # Prepare the prompt for the LLM using FAISS search
-    try:
-        # Encode the user query
-        query_embedding = embedding_model.encode([user_query]).astype('float32')
-
-        # Perform FAISS search
-        k = 5  # Number of top results to retrieve
-        distances, indices = faiss_index.search(query_embedding, k)
-
-        # Fetch the corresponding bookmarks
-        relevant_bookmarks = []
-        for idx in indices[0]:
-            if idx == -1:
-                continue  # No more results
-            # Find the bookmark with matching ID
-            for bookmark in bookmarks:
-                if bookmark.get('id') == idx:
-                    relevant_bookmarks.append(bookmark)
-                    break
-
-        if not relevant_bookmarks:
-            return "🔍 No relevant bookmarks found for your query."
-
-        # Prepare the summary of relevant bookmarks
-        bookmark_data = ""
-        for bm in relevant_bookmarks:
-            bookmark_data += f"Title: {bm['title']}\nURL: {bm['url']}\nSummary: {bm['summary']}\n\n"
-
-        # Construct the prompt
-        prompt = f"""
-You are an assistant that helps users find relevant bookmarks from their collection based on their queries.
-
-User Query:
-{user_query}
-
-Relevant Bookmarks:
-{bookmark_data}
-
-Please provide a concise summary of the most relevant bookmarks that match the user's query.
-"""
-
-        # Call the Groq Cloud API via the OpenAI client
-        response = openai.ChatCompletion.create(
-            model='gpt-3.5-turbo',  # Use appropriate model
-            messages=[
-                {"role": "system", "content": "You help users find relevant bookmarks based on their queries."},
-                {"role": "user", "content": prompt}
-            ],
-            max_tokens=500,
-            temperature=0.7,
-        )
-
-        # Extract the response text
-        answer = response['choices'][0]['message']['content'].strip()
-        logger.info("Chatbot response generated using Groq Cloud API")
-        return answer
-
-    except Exception as e:
-        error_message = f"⚠️ Error processing your query: {str(e)}"
-        logger.error(error_message)
-        print(error_message)  # Ensure error appears in Hugging Face Spaces logs
-        return error_message
-
-# Build the Gradio app
-def build_app():
-    try:
-        logger.info("Building Gradio app")
-        with gr.Blocks(css="app.css") as demo:  # Load external CSS file
-            # Shared states
-            state_bookmarks = gr.State([])
-            chat_history = gr.State([])
-
-            # General Overview
-            gr.Markdown("""
-# 📚 SmartMarks - AI Browser Bookmarks Manager
-
-Welcome to **SmartMarks**, your intelligent assistant for managing browser bookmarks. SmartMarks leverages AI to help you organize, search, and interact with your bookmarks seamlessly. Whether you're looking to categorize your links, retrieve information quickly, or maintain an updated list, SmartMarks has you covered.
-
----
-
-## 🚀 **How to Use SmartMarks**
-
-SmartMarks is divided into three main sections:
-
-1. **📂 Upload and Process Bookmarks:** Import your existing bookmarks and let SmartMarks analyze and categorize them for you.
-2. **💬 Chat with Bookmarks:** Interact with your bookmarks using natural language queries to find relevant links effortlessly.
-3. **🛠️ Manage Bookmarks:** View, edit, delete, and export your bookmarks with ease.
-
-Navigate through the tabs to explore each feature in detail.
-""")
-
-            # Define Manage Bookmarks components outside the tab for global access
-            bookmark_selector = gr.CheckboxGroup(label="✅ Select Bookmarks", choices=[])
-            bookmark_display_manage = gr.HTML(label="📄 Manage Bookmarks Display")
-
-            # Upload and Process Bookmarks Tab
-            with gr.Tab("Upload and Process Bookmarks"):
-                gr.Markdown("""
-## 📂 **Upload and Process Bookmarks**
-
-### 📝 **Steps to Upload and Process:**
-
-1. **🔽 Upload Bookmarks File:**
-   - Click on the **"📁 Upload Bookmarks HTML File"** button.
-   - Select your browser's exported bookmarks HTML file from your device.
-
-2. **⚙️ Process Bookmarks:**
-   - After uploading, click on the **"⚙️ Process Bookmarks"** button.
-   - SmartMarks will parse your bookmarks, fetch additional information, generate summaries, and categorize each link based on predefined categories.
-
-3. **📄 View Processed Bookmarks:**
-   - Once processing is complete, your bookmarks will be displayed in an organized and visually appealing format below.
-""")
-
-                upload = gr.File(label="📁 Upload Bookmarks HTML File", type='binary')
-                process_button = gr.Button("⚙️ Process Bookmarks")
-                output_text = gr.Textbox(label="✅ Output", interactive=False)
-                bookmark_display = gr.HTML(label="📄 Bookmarks")
-
-                process_button.click(
-                    process_uploaded_file,
-                    inputs=[upload, state_bookmarks],
-                    outputs=[output_text, bookmark_display, bookmark_selector, bookmark_display_manage, state_bookmarks]
-                )
-
-            # Chat with Bookmarks Tab
-            with gr.Tab("Chat with Bookmarks"):
-                gr.Markdown("""
-## 💬 **Chat with Bookmarks**
-
-### 🤖 **How to Interact:**
-
-1. **✍️ Enter Your Query:**
-   - In the **"✍️ Ask about your bookmarks"** textbox, type your question or keyword related to your bookmarks. For example, "Do I have any bookmarks about GenerativeAI?"
-
-2. **📨 Submit Your Query:**
-   - Click the **"📨 Send"** button to submit your query.
-
-3. **📈 Receive AI-Driven Responses:**
-   - SmartMarks will analyze your query and provide relevant bookmarks that match your request, making it easier to find specific links without manual searching.
-
-4. **🗂️ View Chat History:**
-   - All your queries and the corresponding AI responses are displayed in the chat history for your reference.
-""")
-
-                with gr.Row():
-                    chat_history_display = gr.Chatbot(label="🗨️ Chat History")
-                    with gr.Column(scale=1):
-                        chat_input = gr.Textbox(
-                            label="✍️ Ask about your bookmarks",
-                            placeholder="e.g., Do I have any bookmarks about GenerativeAI?",
-                            lines=1,
-                            interactive=True
-                        )
-                        chat_button = gr.Button("📨 Send")
-
-                # When user presses Enter in chat_input
-                chat_input.submit(
-                    chatbot_response,
-                    inputs=[chat_input, state_bookmarks],
-                    outputs=chat_history_display
-                )
-
-                # When user clicks Send button
-                chat_button.click(
-                    chatbot_response,
-                    inputs=[chat_input, state_bookmarks],
-                    outputs=chat_history_display
-                )
-
-            # Manage Bookmarks Tab
-            with gr.Tab("Manage Bookmarks"):
-                gr.Markdown("""
-## 🛠️ **Manage Bookmarks**
-
-### 🗂️ **Features:**
-
-1. **👁️ View Bookmarks:**
-   - All your processed bookmarks are displayed here with their respective categories and summaries.
+📂 Upload and Process Bookmarks
+📝 Steps:
+Upload Bookmarks File:
 
-2. **✅ Select Bookmarks:**
-   - Use the checkboxes next to each bookmark to select one, multiple, or all bookmarks you wish to manage.
+Click on the "📁 Upload Bookmarks HTML File" button.
+Select your browser's exported bookmarks HTML file from your device.
+Process Bookmarks:
 
-3. **🗑️ Delete Selected Bookmarks:**
-   - After selecting the desired bookmarks, click the **"🗑️ Delete Selected Bookmarks"** button to remove them from your list.
+After uploading, click on the "⚙️ Process Bookmarks" button.
+SmartMarks will parse your bookmarks, fetch additional information, generate summaries, and categorize each link based on predefined categories.
+View Processed Bookmarks:
 
-4. **✏️ Edit Categories:**
-   - Select the bookmarks you want to re-categorize.
-   - Choose a new category from the dropdown menu labeled **"🆕 New Category"**.
-   - Click the **"✏️ Edit Category of Selected Bookmarks"** button to update their categories.
+Once processing is complete, your bookmarks will be displayed in an organized and visually appealing format.
+💬 Chat with Bookmarks
+🤖 How to Interact:
+Enter Your Query:
 
-5. **💾 Export Bookmarks:**
-   - Click the **"💾 Export Bookmarks"** button to download your updated bookmarks as an HTML file.
-   - This file can be uploaded back to your browser to reflect the changes made within SmartMarks.
+In the "✍️ Ask about your bookmarks" textbox, type your question or keyword related to your bookmarks. For example, "Do I have any bookmarks about AI?"
+Submit Your Query:
 
-6. **🔄 Refresh Bookmarks:**
-   - Click the **"🔄 Refresh Bookmarks"** button to ensure the latest state is reflected in the display.
-""")
+Click the "📨 Send" button to submit your query.
+Receive AI-Driven Responses:
 
-                manage_output = gr.Textbox(label="🔄 Manage Output", interactive=False)
-                new_category_input = gr.Dropdown(label="🆕 New Category", choices=CATEGORIES, value="Uncategorized")
-                with gr.Row():
-                    delete_button = gr.Button("🗑️ Delete Selected Bookmarks")
-                    edit_category_button = gr.Button("✏️ Edit Category of Selected Bookmarks")
-                    export_button = gr.Button("💾 Export Bookmarks")
-                download_link = gr.HTML(label="📥 Download Exported Bookmarks")
-                refresh_button = gr.Button("🔄 Refresh Bookmarks")
+SmartMarks will analyze your query and provide relevant bookmarks that match your request, making it easier to find specific links without manual searching.
+View Chat History:
 
-                # Define button actions
-                delete_button.click(
-                    delete_selected_bookmarks,
-                    inputs=[bookmark_selector, state_bookmarks],
-                    outputs=[manage_output, bookmark_selector, bookmark_display_manage, state_bookmarks]
-                )
+All your queries and the corresponding AI responses are displayed in the chat history for your reference.
+🛠️ Manage Bookmarks
+🗂️ Features:
+View Bookmarks:
 
-                edit_category_button.click(
-                    edit_selected_bookmarks_category,
-                    inputs=[bookmark_selector, new_category_input, state_bookmarks],
-                    outputs=[manage_output, bookmark_selector, bookmark_display_manage, state_bookmarks]
-                )
+All your processed bookmarks are displayed here with their respective categories and summaries.
+Select Bookmarks:
 
-                export_button.click(
-                    export_bookmarks,
-                    inputs=[state_bookmarks],
-                    outputs=download_link
-                )
+Use the checkboxes next to each bookmark to select one, multiple, or all bookmarks you wish to manage.
+Delete Selected Bookmarks:
 
-                refresh_button.click(
-                    lambda bookmarks: (
-                        [
-                            f"{i+1}. {bookmark['title']} (Category: {bookmark['category']})" for i, bookmark in enumerate(bookmarks)
-                        ],
-                        display_bookmarks()
-                    ),
-                    inputs=[state_bookmarks],
-                    outputs=[bookmark_selector, bookmark_display_manage]
-                )
+After selecting the desired bookmarks, click the "🗑️ Delete Selected" button to remove them from your list.
+Edit Categories:
 
-        logger.info("Launching Gradio app")
-        demo.launch(debug=True)
-    except Exception as e:
-        logger.error(f"Error building the app: {e}")
-        print(f"Error building the app: {e}")
+Select the bookmarks you want to re-categorize.
+Choose a new category from the dropdown menu labeled "🆕 New Category".
+Click the "✏️ Edit Category" button to update their categories.
+Export Bookmarks:
 
-if __name__ == "__main__":
-    build_app()
-Key Changes:
+Click the "💾 Export" button to download your updated bookmarks as an HTML file.
+This file can be uploaded back to your browser to reflect the changes made within SmartMarks.
+Refresh Bookmarks:
 
-External CSS Integration:
-Changed gr.Blocks(css=""" ... """) to gr.Blocks(css="app.css") to load styles from the external app.css file.
-Folder Structure Consideration:
-Ensure that the app.css file is located in the same directory as app.py or adjust the path accordingly.
-3. Updated README.md
-The updated README.md now reflects the addition of the external app.css file and provides clear instructions on maintaining and organizing your project files.
+Click the "🔄 Refresh Bookmarks" button to ensure the latest state is reflected in the display.
+📦 Deployment on Hugging Face Spaces
+SmartMarks is designed to run seamlessly on Hugging Face Spaces, providing an interactive and user-friendly interface.
 
+Prerequisites
+Hugging Face Account: To deploy on Hugging Face Spaces, you need an account. Sign up here.
+API Key: SmartMarks utilizes the Groq Cloud API for its chatbot functionality. Ensure you have a valid GROQ_API_KEY.
+Repository Structure
 markdown
 Copy code
-# 📚 SmartMarks - AI Browser Bookmarks Manager
-
-![License](https://img.shields.io/badge/license-MIT-blue.svg)
-![Gradio](https://img.shields.io/badge/Gradio-v3.38.0-blue)
-![Python](https://img.shields.io/badge/Python-3.8%2B-blue.svg)
-![Hugging Face Spaces](https://img.shields.io/badge/Hugging%20Face-Spaces-green.svg)
-
-## 🌟 Overview
-
-**SmartMarks** is your intelligent assistant for managing browser bookmarks. Leveraging the power of AI, SmartMarks helps you organize, search, and interact with your bookmarks seamlessly. Whether you're looking to categorize your links, retrieve information quickly, or maintain an updated list, SmartMarks has you covered.
-
-### Key Features
-
-- **📂 Upload and Process Bookmarks:** Import your existing bookmarks and let SmartMarks analyze and categorize them for you.
-- **💬 Chat with Bookmarks:** Interact with your bookmarks using natural language queries to find relevant links effortlessly.
-- **🛠️ Manage Bookmarks:** View, edit, delete, and export your bookmarks with ease.
-- **🎨 Dynamic Color Theme:** Automatically adapts to your system or browser's light/dark mode preferences for optimal readability and aesthetics.
-
-## 🚀 How to Use SmartMarks
-
-SmartMarks is divided into three main sections:
-
-1. **📂 Upload and Process Bookmarks:** Import and process your bookmarks.
-2. **💬 Chat with Bookmarks:** Ask questions about your bookmarks using natural language.
-3. **🛠️ Manage Bookmarks:** Manage your bookmarks by viewing, editing, deleting, and exporting them.
-
-Navigate through the tabs to explore each feature in detail.
-
-## 📦 Deployment on Hugging Face Spaces
+smartmarks/
+├── app.py
+├── app.css
+├── requirements.txt
+├── README.md
+└── screenshots/
+    ├── light_mode.png
+    └── dark_mode.png
+Setting Up Environment Variables
+GROQ_API_KEY: SmartMarks requires the GROQ_API_KEY to interact with the Groq Cloud API. To set this up:
 
-SmartMarks is designed to run seamlessly on [Hugging Face Spaces](https://huggingface.co/spaces), providing an interactive and user-friendly interface.
+Navigate to your Space's dashboard on Hugging Face.
 
-### Prerequisites
+Go to Settings > Secrets.
 
-- **Hugging Face Account:** To deploy on Hugging Face Spaces, you need an account. Sign up [here](https://huggingface.co/join).
-- **API Key:** SmartMarks utilizes the Groq Cloud API for its chatbot functionality. Ensure you have a valid `GROQ_API_KEY`.
+Add a new secret with the key GROQ_API_KEY and paste your API key as the value.
 
-### Repository Structure
+Note: Keep your API keys secure. Never expose them in your code or repository.
 
-smartmarks/ │ ├── app.py ├── app.css ├── requirements.txt ├── README.md ├── LICENSE └── screenshots/ ├── light_mode.png └── dark_mode.png
+Installing Dependencies
+Hugging Face Spaces automatically installs dependencies listed in the requirements.txt file. Ensure your requirements.txt includes all necessary packages:
 
-markdown
+shell
 Copy code
-
-### Setting Up Environment Variables
-
-1. **GROQ_API_KEY:**  
-   SmartMarks requires the `GROQ_API_KEY` to interact with the Groq Cloud API. To set this up:
-
-   - Navigate to your Space's dashboard on Hugging Face.
-   - Go to **Settings** > **Secrets**.
-   - Add a new secret with the key `GROQ_API_KEY` and paste your API key as the value.
-
-   > **Note:** Keep your API keys secure. Never expose them in your code or repository.
-
-### Installing Dependencies
-
-Hugging Face Spaces automatically installs dependencies listed in the `requirements.txt` file. Ensure your `requirements.txt` includes all necessary packages:
-
-```plaintext
 gradio
 beautifulsoup4
 sentence-transformers
 faiss-cpu
-aiohttp
-openai
-uuid
-Note: The uuid library is part of Python's standard library and doesn't require installation. You can remove it from requirements.txt if preferred.
-
-Deploying the Space
-Create a New Space:
-
-Navigate to Hugging Face Spaces and click on "Create new Space".
-Choose the Gradio SDK and set the visibility (public or private) as desired.
-Upload Your Code:
+requests
+numpy
+openai>=0.27.0,<1.0.0
+Note: The uuid library is part of Python's standard library and doesn't require installation via pip. You can remove it from requirements.txt if it was previously included.
 
-Clone your Space repository or use the web interface to upload app.py, app.css, requirements.txt, README.md, and LICENSE.
-Launch the Space:
-
-Once all files are uploaded, Hugging Face Spaces will automatically build and deploy your application.
-Access your Space via the provided URL.
 🌈 Dynamic Color Theme
 SmartMarks automatically detects your system or browser's preferred color scheme and adjusts the application's theme accordingly:
 
 Dark Mode: White text on a dark background for reduced eye strain in low-light environments.
 Light Mode: Black text on a light background for bright environments.
-This dynamic theming ensures optimal readability and aesthetics without any manual intervention.
+These styles ensure that the text and background colors adapt based on the user's system or browser theme settings.
 
-How It Works
-The application uses CSS media queries to detect the user's preferred color scheme and applies appropriate styles by loading them from the external app.css file:
+📸 Screenshots
+Note: Replace the placeholders below with actual screenshots of your application in both light and dark modes.
 
-css
-Copy code
-/* app.css */
+Light Mode
 
-/* Card Styling */
-.card {
-    box-shadow: 0 4px 8px 0 rgba(0,0,0,0.2);
-    transition: 0.3s;
-    padding: 10px;
-    margin: 10px;
-    border-radius: 5px;
-}
+Dark Mode
 
-.card:hover {
-    box-shadow: 0 8px 16px 0 rgba(0,0,0,0.2);
-}
+🔧 Configuration
+Ensure that the GROQ_API_KEY environment variable is set correctly, as it's essential for the chatbot functionality to interact with the Groq Cloud API.
 
-/* Dynamic Theme Styling */
-@media (prefers-color-scheme: dark) {
-    body {
-        color: white;
-        background-color: #121212;
-    }
-    .card {
-        background-color: #1e1e1e;
-    }
-    a {
-        color: #bb86fc;
-    }
-    h1, h2, h3, p, strong {
-        color: inherit;
-    }
-}
+Setting Up Environment Variables
+Navigate to Space Settings:
 
-@media (prefers-color-scheme: light) {
-    body {
-        color: black;
-        background-color: white;
-    }
-    .card {
-        background-color: #fff;
-    }
-    a {
-        color: #1a0dab;
-    }
-    h1, h2, h3, p, strong {
-        color: inherit;
-    }
-}
-These styles ensure that the text and background colors adapt based on the user's system or browser theme settings.
+Go to your Space's dashboard on Hugging Face.
+Add Secret:
 
-📸 Screenshots
-Note: Replace the placeholders below with actual screenshots of your application in both light and dark modes.
+Click on Settings > Secrets.
 
-Light Mode
+Add a new secret with the key GROQ_API_KEY and paste your API key as the value.
 
-Dark Mode
+Note: Keep your API keys secure. Never expose them in your code or repository.
 
 📋 Features in Detail
 📂 Upload and Process Bookmarks
@@ -1082,17 +161,17 @@ After uploading, click on the "⚙️ Process Bookmarks" button.
 SmartMarks will parse your bookmarks, fetch additional information, generate summaries, and categorize each link based on predefined categories.
 View Processed Bookmarks:
 
-Once processing is complete, your bookmarks will be displayed in an organized and visually appealing format below.
+Once processing is complete, your bookmarks will be displayed in an organized and visually appealing format.
 💬 Chat with Bookmarks
 Enter Your Query:
 
-In the "✍️ Ask about your bookmarks" textbox, type your question or keyword related to your bookmarks. For example, "Do I have any bookmarks about GenerativeAI?"
+In the "✍️ Ask about your bookmarks" textbox, type your question or keyword related to your bookmarks. For example, "Do I have any bookmarks about AI?"
 Submit Your Query:
 
 Click the "📨 Send" button to submit your query.
 Receive AI-Driven Responses:
 
-SmartMarks will analyze your query and provide relevant bookmarks that match your request, making it easier to find specific links without manual searching.
+SmartMarks will analyze your query and provide relevant bookmarks that match your request.
 View Chat History:
 
 All your queries and the corresponding AI responses are displayed in the chat history for your reference.
@@ -1105,32 +184,19 @@ Select Bookmarks:
 Use the checkboxes next to each bookmark to select one, multiple, or all bookmarks you wish to manage.
 Delete Selected Bookmarks:
 
-After selecting the desired bookmarks, click the "🗑️ Delete Selected Bookmarks" button to remove them from your list.
+After selecting the desired bookmarks, click the "🗑️ Delete Selected" button to remove them from your list.
 Edit Categories:
 
 Select the bookmarks you want to re-categorize.
 Choose a new category from the dropdown menu labeled "🆕 New Category".
-Click the "✏️ Edit Category of Selected Bookmarks" button to update their categories.
+Click the "✏️ Edit Category" button to update their categories.
 Export Bookmarks:
 
-Click the "💾 Export Bookmarks" button to download your updated bookmarks as an HTML file.
+Click the "💾 Export" button to download your updated bookmarks as an HTML file.
 This file can be uploaded back to your browser to reflect the changes made within SmartMarks.
 Refresh Bookmarks:
 
 Click the "🔄 Refresh Bookmarks" button to ensure the latest state is reflected in the display.
-🔧 Configuration
-Ensure that the GROQ_API_KEY environment variable is set correctly, as it's essential for the chatbot functionality to interact with the Groq Cloud API.
-
-Setting Up Environment Variables
-Navigate to Space Settings:
-
-Go to your Space's dashboard on Hugging Face.
-Add Secret:
-
-Click on Settings > Secrets.
-Add a new secret with the key GROQ_API_KEY and paste your API key as the value.
-Note: Keep your API keys secure. Never expose them in your code or repository.
-
 🤝 Contributing
 Contributions are welcome! Please follow these steps to contribute:
 
@@ -1165,10 +231,10 @@ Open a Pull Request:
 
 Navigate to your forked repository on GitHub and click on "Compare & pull request".
 📜 License
-This project is licensed under the MIT License. See the LICENSE file for details.
+This project is licensed under the MIT License.
 
 📞 Contact
-For any questions or feedback, please contact your-email@example.com.
+For any questions or feedback, please contact siddhartharya@gmail.com
 
 Happy Bookmarking with SmartMarks! 🚀📚