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import pandas as pd
import gradio as gr
# Load the menu data from the Excel file
def load_menu(file_path="menu.xlsx"):
menu_data = pd.read_excel(file_path)
required_columns = ["Category", "Dish Name", "Price", "Image URL", "Description", "Ingredients", "Allergen Info", "Recommended Items", "Spice Levels"]
# Check for missing columns
missing_columns = [col for col in required_columns if col not in menu_data.columns]
if missing_columns:
raise ValueError(f"Missing columns in Excel file: {missing_columns}")
return menu_data
if preference != "All":
filtered_data = menu_data[menu_data["Category"] == preference]
else:
filtered_data = menu_data
# Generate HTML for the menu
html_content = ""
for _, item in filtered_data.iterrows():
html_content += f"""
<div style="display: flex; align-items: center; border: 1px solid #ddd; border-radius: 8px; padding: 15px; margin-bottom: 10px; box-shadow: 0px 4px 8px rgba(0, 0, 0, 0.1);">
<div style="flex: 1; margin-right: 15px;">
<h3 style="margin: 0; font-size: 18px;">{item['Dish Name']}</h3>
<p style="margin: 5px 0; font-size: 16px; color: #888;">₹{item['Price']}</p>
<p style="margin: 5px 0; font-size: 14px; color: #555;">{item['Description']}</p>
</div>
<div style="flex-shrink: 0; text-align: center;">
<img src="{item['Image URL']}" alt="{item['Dish Name']}" style="width: 100px; height: 100px; border-radius: 8px; object-fit: cover; margin-bottom: 10px;">
<button style="background-color: #28a745; color: white; border: none; padding: 8px 15px; font-size: 14px; border-radius: 5px; cursor: pointer;">Add</button>
</div>
</div>
"""
return html_content
# Gradio app definition
def app():
preferences = ["All", "Vegan", "Halal", "Guilt-Free"]
with gr.Blocks() as demo:
gr.Markdown("# Dynamic Menu with Preferences")
# Radio buttons for preferences
selected_preference = gr.Radio(preferences, label="Choose a Preference")
# Display the filtered menu
menu_output = gr.HTML()
selected_preference.change(filter_menu, inputs=[selected_preference], outputs=[menu_output])
# Initial menu load (all items)
menu_output.value = filter_menu("All")
return demo
# Run the app
if __name__ == "__main__":
demo = app()
demo.launch()
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