Update app.py

app.py

@@ -9,6 +9,7 @@ import streamlit as st
 import sentencepiece
 from gtts import gTTS
 import base64
+import time
 from transformers import pipeline, T5Tokenizer, T5ForConditionalGeneration
 
 model=T5ForConditionalGeneration.from_pretrained("Logeswaransr/T5_MineAI_Prototype").to("cpu")
@@ -32,6 +33,13 @@ for message in st.session_state.messages:
         st.markdown(message['content'])
         
 ## messages element format: {'role':'user', 'content':'<user prompt>'}
+
+tts=gTTS("Here is your answer")
+tts.save(audio_stream)
+with open(audio_stream, 'rb') as file:
+    audio_data=file.read()
+audio_base64 = base64.b64encode(audio_data).decode('utf-8')
+audio_tag = f'<audio autoplay="true" src="data:audio/mp3;base64,{audio_base64}">'
         
 if st.session_state.messages==[]:
     for gr in greetings:
@@ -45,6 +53,7 @@ if st.session_state.messages==[]:
         audio_base64 = base64.b64encode(audio_data).decode('utf-8')
         audio_tag = f'<audio autoplay="true" src="data:audio/mp3;base64,{audio_base64}">'
         st.markdown(audio_tag, unsafe_allow_html=True)
+        time.sleep(5)
     
         st.session_state.messages.append({
             'role':'assistant',
@@ -66,12 +75,6 @@ if prompt:=st.chat_input("Enter your query"):
     with st.chat_message("assistant"):
         st.markdown(response)
 
-    tts=gTTS(response)
-    tts.save(audio_stream)
-    with open(audio_stream, 'rb') as file:
-        audio_data=file.read()
-    audio_base64 = base64.b64encode(audio_data).decode('utf-8')
-    audio_tag = f'<audio autoplay="true" src="data:audio/mp3;base64,{audio_base64}">'
     st.markdown(audio_tag, unsafe_allow_html=True)
         
     st.session_state.messages.append({