Update app.py

app.py

@@ -2,29 +2,11 @@ import gradio as gr
 import pandas as pd
 from huggingface_hub import InferenceClient
 
-# Load the AI model and clothing database
-# NOTE: Replace 'microsoft/phi-4' with the actual model ID if different
-# The client is used for generating the AI's text response.
-client = InferenceClient("microsoft/phi-4")
-
-# Load the clothing database CSV. Make sure 'clothing.csv' is in the same directory.
-try:
-    clothing_df = pd.read_csv("clothing.csv")
-except FileNotFoundError:
-    print("Error: 'clothing.csv' not found. Please ensure the file is in the same directory.")
-    clothing_df = pd.DataFrame(columns=['weather', 'formality', 'category', 'image_path'])
 
-# Simple filtering function to get clothing suggestions based on a query
-import gradio as gr
-import pandas as pd
-from huggingface_hub import InferenceClient
 
-# Load the AI model and clothing database
-# NOTE: Replace 'microsoft/phi-4' with the actual model ID if different
-# The client is used for generating the AI's text response.
 client = InferenceClient("microsoft/phi-4")
 
-# Load the clothing database CSV. Make sure 'clothing.csv' is in the same directory.
+# Load the clothing database CSV. 
 try:
     clothing_df = pd.read_csv("clothing.csv")
 except FileNotFoundError:
@@ -113,24 +95,6 @@ def get_suggestions(query):
     # Return the updated chat history and the image paths
     return chat_history, image_paths
 
-# Gradio UI ---
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("## Fashioneer - your fashion pioneer!")
-    gr.Markdown("Ask me what to wear and I'll suggest clothing with images from the database.")
-
-    # This is the search bar at the top
-    user_input = gr.Textbox(label="Type your outfit requirements here", placeholder="e.g., What should I wear on a rainy day?")
-    
-    # This row will place the chatbot and gallery side-by-side
-    with gr.Row():
-        chatbot = gr.Chatbot(label="Chatbot Conversation")
-        gallery = gr.Gallery(label="Recommended Clothing", columns=2, height='auto')
-
-    # This is the original line that connects the input and output
-    user_input.submit(fn=respond, inputs=[user_input, chatbot], outputs=[chatbot, gallery])
-
-# This starts the Gradio app
-demo.launch()
 
 # Chatbot + image output function
 def respond(message, chat_history):