Update app.py

app.py

@@ -1,32 +1,28 @@
-from flask import Flask, jsonify, request
+import gradio as gr
 from transformers import pipeline
 
-app = Flask(__name__)
-
-# Load the Hugging Face chatbot model (example: DialoGPT)
+# Initialize Hugging Face's DialoGPT model for conversational AI
 generator = pipeline("conversational", model="microsoft/DialoGPT-medium")
 
-# Initialize the chatbot with a starting message
-initial_message = "Hi! Would you like to customize food?"
-
-@app.route('/')
-def index():
-    return "Food Customization Assistant is running"
-
-@app.route('/chat', methods=['POST'])
-def chat():
-    user_input = request.json.get('message')
-    if not user_input:
-        return jsonify({'error': 'No message provided'}), 400
-
-    # Generate a response using the Hugging Face model
+# Function that interacts with the Hugging Face model
+def chatbot_response(user_input):
     response = generator(user_input)
-    bot_reply = response[0]['generated_text']
-
-    return jsonify({
-        'user_message': user_input,
-        'bot_message': bot_reply
-    })
-
-if __name__ == '__main__':
-    app.run(debug=True)
+    return response[0]['generated_text']
+
+# Gradio interface setup
+def create_gradio_interface():
+    # Create a Gradio interface with input and output components
+    interface = gr.Interface(
+        fn=chatbot_response,
+        inputs=gr.Textbox(label="Your Message", placeholder="Ask about food customization..."),
+        outputs=gr.Textbox(label="Bot Response"),
+        title="Food Customization Assistant",
+        description="Talk to the bot and customize your food preferences. Ask about recipes, categories, or ingredients.",
+        theme="compact"  # You can customize the theme
+    )
+
+    return interface
+
+if __name__ == "__main__":
+    interface = create_gradio_interface()
+    interface.launch()