Update app.py

app.py

@@ -1,12 +1,11 @@
 import streamlit as st
 import logging
-import time
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+import time
 
 # Set the logger to display only CRITICAL messages
 logging.basicConfig(level=logging.CRITICAL)
 
-
 # Cache the model and tokenizer to avoid reloading it every time
 @st.experimental_singleton
 def load_model():
@@ -31,13 +30,20 @@ user_input = st.text_area("Enter your prompt:", "")
 
 if st.button("Submit"):
     if user_input:
+        # Generate text based on the input
         generated_text = generate_text(user_input)
-        for i in range(1, len(generated_text) + 1):
-            # Update the output placeholder with a substring of the generated text
-            output_placeholder.markdown(generated_text[:i])
-            # Sleep to simulate typing
-            time.sleep(0.1)  # Adjust the sleep time to speed up or slow down the "typing"
+        
+        # Initialize or reset the progress state
+        if 'text_progress' not in st.session_state:
+            st.session_state['text_progress'] = ""
+        
+        # Simulate typing effect
+        for i in range(len(generated_text)):
+            st.session_state['text_progress'] = generated_text[:i+1]
+            st.write(st.session_state['text_progress'])
+            time.sleep(0.05)  # Adjust as needed for the desired speed of the "typing" effect
+            
+        # Reset progress for next input
+        del st.session_state['text_progress']
     else:
-        st.write("Please enter a prompt to get started.")
-
-
+        st.write("Please enter a prompt.")