Update handler.py

handler.py

@@ -4,6 +4,7 @@ import torch
 import soundfile as sf
 from transformers import AutoTokenizer, AutoModelForTextToWaveform
 import cloudinary.uploader
+import streamlit as st
 # Configure logging
 logging.basicConfig(level=logging.DEBUG)
 # Configure logging
@@ -34,6 +35,7 @@ class EndpointHandler():
         # Save the audio to a file
         sf.write("StoryAudio.wav", outputs["waveform"][0].numpy(), self.model.config.sampling_rate)
         uploadGraphFile("StoryAudio.wav")
+        st.audio("StoryAudio.wav")
         return 'StoryAudio.wav'
         # Check if the request was successful