Update app.py

app.py

@@ -1,8 +1,4 @@
 import gradio as gr
-from flask import Flask, request, jsonify
-
-# Flask app setup
-app = Flask(__name__)
 
 # Corrected Food Database with consistent food item names
 FOOD_DATABASE = {
@@ -133,9 +129,9 @@ def process_message(message, history):
 # Gradio interface for the chatbot
 def create_gradio_interface():
     with gr.Blocks() as demo:
-        category_btns = gr.Radio(choices=["Vegetarian", "Non-Vegetarian"], label="Select Category", type="value")
-        ingredient_btns = gr.Radio(choices=VEG_INGREDIENTS + NONVEG_TYPES, label="Select Ingredient", type="value")
-        nutrition_btns = gr.Radio(choices=NUTRITION_OPTIONS, label="Select Nutrition", type="value")
+        category_btns = gr.ButtonGroup(choices=["Vegetarian", "Non-Vegetarian"], label="Select Category")
+        ingredient_btns = gr.ButtonGroup(choices=VEG_INGREDIENTS + NONVEG_TYPES, label="Select Ingredient")
+        nutrition_btns = gr.ButtonGroup(choices=NUTRITION_OPTIONS, label="Select Nutrition")
         chatbot = gr.Chatbot([])
         msg = gr.Textbox(show_label=False, placeholder="Enter text and press enter")
         clear = gr.Button("Clear")
@@ -161,19 +157,6 @@ def create_gradio_interface():
 
     return demo
 
-# Flask route to process messages
-@app.route("/process_message", methods=["POST"])
-def process_message_from_js():
-    data = request.get_json()
-    message = data.get('message')
-
-    # Process the message using the existing process_message function
-    history = []  # You may pass the history if needed, but keep it simple for now
-    bot_response = process_message(message, history)
-    
-    # Return the bot response as JSON
-    return jsonify({'response': bot_response})
-
 if __name__ == "__main__":
     # Create Gradio interface
     demo = create_gradio_interface()