Update app.py

app.py

@@ -8,23 +8,21 @@ client = Groq(api_key="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"
 # Define the system message for the model
 system_message = {
     "role": "system",
-    "content": "You are an experienced fashion designer. Start the conversation with a greeting, provide valuable fashion advice, and only ask questions if the user has concerns. Gather basic inputs: name, age, gender, location, height, and weight."
+    "content": "You are an experienced Fashion designer who provides valuable fashion advice, asks relevant questions, and keeps the conversation focused on the user's style and preferences."
 }
 
 # Function to reset the chat
 def reset_chat():
     return [], "New Chat"
 
-# Function to handle the questionnaire submission
-def submit_questionnaire(name, age, location, gender, height, weight):
-    # Store basic responses in a DataFrame
+# Function to handle questionnaire submission
+def submit_questionnaire(name, age, gender, location):
+    # Store questionnaire responses in a DataFrame
     questionnaire_data = {
         "Name": name,
         "Age": age,
-        "Location": location,
         "Gender": gender,
-        "Height": height,
-        "Weight": weight
+        "Location": location
     }
 
     df = pd.DataFrame([questionnaire_data])  # Create DataFrame from dictionary
@@ -35,12 +33,12 @@ def submit_questionnaire(name, age, location, gender, height, weight):
     return "Thank you for completing the questionnaire!"
 
 # Function to handle chat
-def chat(user_input, messages, name, age, location, gender, height, weight):
+def chat(user_input, messages, name, age, location, gender):
     if user_input:
         # Create a user profile string
         user_profile_string = (
             f"User profile: Name: {name}, Age: {age}, Location: {location}, "
-            f"Gender: {gender}, Height: {height}, Weight: {weight}"
+            f"Gender: {gender}"
         )
 
         # Prepare messages for the API call, including the profile and the conversation history
@@ -85,23 +83,20 @@ with gr.Blocks() as demo:
             age = gr.Number(label="Age", value=25, minimum=1, maximum=100)
             location = gr.Textbox(label="Location")
             gender = gr.Radio(label="Gender", choices=["Male", "Female", "Other"])
-            height = gr.Number(label="Height (cm)", value=170, minimum=50, maximum=250)
-            weight = gr.Number(label="Weight (kg)", value=70, minimum=20, maximum=200)
-
-        with gr.Column():
             submit_btn = gr.Button("Submit Questionnaire")
             reset_btn = gr.Button("Reset Chat")
 
     # Chat functionality
-    chatbox = gr.Chatbot()
+    chatbox = gr.Chatbot(type='messages')
     user_input = gr.Textbox(label="Your Message", placeholder="Type your message here...")
 
+    # Output message for feedback
+    output_message = gr.Textbox(label="Output Message", interactive=False)
+
     # Connect the buttons to their respective functions
-    output_message = gr.Textbox(label="Output Message")  # Define an output component
-    submit_btn.click(submit_questionnaire, inputs=[name, age, location, gender, height, weight], outputs=output_message)
-    
-    reset_btn.click(reset_chat, outputs=[chatbox, "title"])
-    user_input.submit(chat, inputs=[user_input, chatbox, name, age, location, gender, height, weight], outputs=[chatbox, user_input])
+    submit_btn.click(submit_questionnaire, inputs=[name, age, location, gender], outputs=output_message)
+    reset_btn.click(reset_chat, outputs=[chatbox, output_message])
+    user_input.submit(chat, inputs=[user_input, chatbox, name, age, location, gender], outputs=[chatbox, user_input])
 
 # Run the app
 demo.launch()