Update app.py

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
 import pandas as pd
+import time
 from collections import defaultdict
 
 # Load the symptom-to-disease mapping
@@ -59,7 +60,7 @@ symptom_data = {
 # Global variables to track user state
 user_state = {}
 
-def chatbot(user_input, history):
+def chatbot(user_input):
     if "state" not in user_state:
         user_state["state"] = "greet"
     
@@ -108,18 +109,25 @@ def chatbot(user_input, history):
         user_state.clear()
         return f"Based on your symptoms, the most likely condition is: {probable_disease}. Please consult a doctor for confirmation."
 
-# Gradio Chatbot UI
+# Gradio Chatbot UI with improved features
 with gr.Blocks() as demo:
     gr.Markdown("# Symptom Chatbot")
     chatbot_ui = gr.Chatbot()
-    user_input = gr.Textbox(placeholder="Enter your response...")
+    user_input = gr.Textbox(placeholder="Enter your response...", label="Your Message")
     submit = gr.Button("Send")
+    clear_chat = gr.Button("Clear Chat")
     
     def respond(user_message, history):
-        bot_response = chatbot(user_message, history)
-        history.append((user_message, bot_response))
-        return history, ""
+        history.append((user_message, "Thinking..."))  # Show thinking message
+        yield history, ""  # Immediate update
+        
+        time.sleep(1.5)  # Simulate processing delay
+        bot_response = chatbot(user_message)
+        history[-1] = (user_message, bot_response)  # Update with real response
+        yield history, ""
     
     submit.click(respond, [user_input, chatbot_ui], [chatbot_ui, user_input])
+    user_input.submit(respond, [user_input, chatbot_ui], [chatbot_ui, user_input])
+    clear_chat.click(lambda: ([], ""), outputs=[chatbot_ui, user_input])
 
-demo.launch()
+demo.launch()