'''
cards += card_html
logger.info("HTML display generated")
return cards
# Process the uploaded file
def process_uploaded_file(file):
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()
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()
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()
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()
# 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()
# Generate summaries and assign categories
for bookmark in bookmarks:
generate_summary(bookmark)
assign_category(bookmark)
try:
faiss_index, embeddings = 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()
message = f"✅ Successfully processed {len(bookmarks)} bookmarks."
logger.info(message)
bookmark_html = display_bookmarks()
# Update bookmark_selector choices
choices = [f"{i+1}. {bookmark['title']} (Category: {bookmark['category']})" for i, bookmark in enumerate(bookmarks)]
bookmark_selector_update = gr.update(choices=choices, value=[])
# Update bookmark_display_manage
bookmark_display_manage_update = display_bookmarks()
return message, bookmark_html, bookmark_selector_update, bookmark_display_manage_update
# Delete selected bookmarks
def delete_selected_bookmarks(selected_indices):
global bookmarks, faiss_index
if not selected_indices:
return "⚠️ No bookmarks selected.", gr.update(choices=[]), display_bookmarks()
indices = [int(s.split('.')[0])-1 for s in selected_indices]
indices = sorted(indices, reverse=True)
for idx in indices:
if 0 <= idx < len(bookmarks):
logger.info(f"Deleting bookmark at index {idx + 1}")
bookmarks.pop(idx)
if bookmarks:
faiss_index, embeddings = vectorize_and_index(bookmarks)
else:
faiss_index = None
message = "🗑️ Selected bookmarks deleted successfully."
logger.info(message)
# Update bookmark_selector choices
choices = [f"{i+1}. {bookmark['title']} (Category: {bookmark['category']})" for i, bookmark in enumerate(bookmarks)]
bookmark_selector_update = gr.update(choices=choices, value=[])
# Update bookmarks display
bookmarks_html = display_bookmarks()
return message, bookmark_selector_update, bookmarks_html
# Edit category of selected bookmarks
def edit_selected_bookmarks_category(selected_indices, new_category):
if not selected_indices:
return "⚠️ No bookmarks selected.", '', gr.update()
if not new_category:
return "⚠️ No new category selected.", '', gr.update()
indices = [int(s.split('.')[0])-1 for s in selected_indices]
for idx in indices:
if 0 <= idx < len(bookmarks):
bookmarks[idx]['category'] = new_category
logger.info(f"Updated category for bookmark {idx + 1} to {new_category}")
message = "✏️ Category updated for selected bookmarks."
logger.info(message)
# Update bookmark_selector choices
choices = [f"{i+1}. {bookmark['title']} (Category: {bookmark['category']})" for i, bookmark in enumerate(bookmarks)]
bookmark_selector_update = gr.update(choices=choices, value=[])
# Update bookmarks display
bookmarks_html = display_bookmarks()
return message, bookmark_selector_update, bookmarks_html
# Export bookmarks to HTML
def export_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("Bookmarks
Bookmarks
", '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'💾 Download Exported Bookmarks'
except Exception as e:
logger.error(f"Error exporting bookmarks: {e}")
return "⚠️ Error exporting bookmarks."
# Chatbot response using Groq Cloud API
def chatbot_response(user_query):
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."
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
try:
# Limit the number of bookmarks to prevent exceeding token limits
max_bookmarks = 50 # Adjust as needed
bookmark_data = ""
for idx, bookmark in enumerate(bookmarks[:max_bookmarks]):
bookmark_data += f"{idx+1}. Title: {bookmark['title']}\nURL: {bookmark['url']}\nSummary: {bookmark['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}
Bookmarks:
{bookmark_data}
Please identify the most relevant bookmarks that match the user's query. Provide a concise list including the index, title, URL, and a brief summary.
"""
# Call the Groq Cloud API via the OpenAI client
response = openai.ChatCompletion.create(
model='llama3-8b-8192', # Verify this model name with Groq Cloud API documentation
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="""
/* Define CSS Variables for Themes */
:root {
--background-color: #FFFFFF;
--text-color: #000000;
--success-color: #4CAF50;
--error-color: #D32F2F;
--card-shadow: rgba(0, 0, 0, 0.2);
}
.dark-theme {
--background-color: #121212;
--text-color: #FFFFFF;
--success-color: #81C784;
--error-color: #E57373;
--card-shadow: rgba(255, 255, 255, 0.2);
}
body {
background-color: var(--background-color);
color: var(--text-color);
}
.card {
box-shadow: 0 4px 8px 0 var(--card-shadow);
transition: 0.3s;
background-color: var(--background-color);
}
.card:hover {
box-shadow: 0 8px 16px 0 var(--card-shadow);
}
/* Toggle Switch Styles */
.theme-toggle {
display: flex;
align-items: center;
justify-content: flex-end;
padding: 10px;
}
.switch {
position: relative;
display: inline-block;
width: 60px;
height: 34px;
}
.switch input {
opacity: 0;
width: 0;
height: 0;
}
.slider {
position: absolute;
cursor: pointer;
top: 0;
left: 0;
right: 0;
bottom: 0;
background-color: #ccc;
transition: .4s;
border-radius: 34px;
}
.slider:before {
position: absolute;
content: "";
height: 26px;
width: 26px;
left: 4px;
bottom: 4px;
background-color: white;
transition: .4s;
border-radius: 50%;
}
input:checked + .slider {
background-color: #2196F3;
}
input:checked + .slider:before {
transform: translateX(26px);
}
/* Gradio Components Styling */
.gradio-container {
background-color: var(--background-color);
color: var(--text-color);
}
a {
color: var(--text-color);
}
""") as demo:
# Add Theme Toggle Switch
gr.HTML(
"""
Dark Mode
"""
)
# 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.
""")
# 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")
# Initialize Manage Bookmarks components
bookmark_selector = gr.CheckboxGroup(label="✅ Select Bookmarks", choices=[])
bookmark_display_manage = gr.HTML(label="📄 Manage Bookmarks Display")
process_button.click(
process_uploaded_file,
inputs=upload,
outputs=[output_text, bookmark_display, bookmark_selector, bookmark_display_manage]
)
# 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.
""")
user_input = gr.Textbox(label="✍️ Ask about your bookmarks", placeholder="e.g., Do I have any bookmarks about GenerativeAI?")
chat_output = gr.Textbox(label="💬 Chatbot Response", interactive=False)
chat_button = gr.Button("📨 Send")
chat_button.click(
chatbot_response,
inputs=user_input,
outputs=chat_output
)
# 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.
2. **✅ Select Bookmarks:**
- Use the checkboxes next to each bookmark to select one, multiple, or all bookmarks you wish to manage.
3. **🗑️ Delete Selected Bookmarks:**
- After selecting the desired bookmarks, click the **"Delete Selected Bookmarks"** button to remove them from your list.
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.
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.
""")
manage_output = gr.Textbox(label="🔄 Manage Output", interactive=False)
bookmark_display_manage = gr.HTML(label="📄 Manage Bookmarks Display")
bookmark_selector = gr.CheckboxGroup(label="✅ Select Bookmarks", choices=[])
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")
# Define button actions
delete_button.click(
delete_selected_bookmarks,
inputs=bookmark_selector,
outputs=[manage_output, bookmark_selector, bookmark_display_manage]
)
edit_category_button.click(
edit_selected_bookmarks_category,
inputs=[bookmark_selector, new_category_input],
outputs=[manage_output, bookmark_selector, bookmark_display_manage]
)
export_button.click(
export_bookmarks,
inputs=None,
outputs=download_link
)
# Initialize display after processing bookmarks
process_button.click(
process_uploaded_file,
inputs=upload,
outputs=[output_text, bookmark_display, bookmark_selector, bookmark_display_manage]
)
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}")
if __name__ == "__main__":
build_app()