Update handler.py

handler.py

@@ -3,7 +3,7 @@ import logging
 import torch
 import soundfile as sf
 from transformers import AutoTokenizer, AutoModelForTextToWaveform
-
+import streamlit as st
 # Configure logging
 logging.basicConfig(level=logging.DEBUG)
 # Configure logging
@@ -13,6 +13,7 @@ logging.basicConfig(level=logging.WARNING)
 
 
 
+
 class EndpointHandler():
     def __init__(self, path=""):
         
@@ -32,7 +33,7 @@ class EndpointHandler():
 
         # Save the audio to a file
         sf.write("StoryAudio.wav", outputs["waveform"][0].numpy(), self.model.config.sampling_rate)
-  
+        st.audio("StoryAudio.wav")
         return 'StoryAudio.wav'
         # Check if the request was successful