Update handler.py

handler.py

@@ -3,7 +3,7 @@ import logging
 import torch
 import soundfile as sf
 from transformers import AutoTokenizer, AutoModelForTextToWaveform
-
+import cloudinary.uploader
 # Configure logging
 logging.basicConfig(level=logging.DEBUG)
 # Configure logging
@@ -33,8 +33,17 @@ class EndpointHandler():
 
         # Save the audio to a file
         sf.write("StoryAudio.wav", outputs["waveform"][0].numpy(), self.model.config.sampling_rate)
-
+        uploadGraphFile("StoryAudio.wav")
         return 'StoryAudio.wav'
         # Check if the request was successful
         
-
+def uploadGraphFile(fileName):
+    # Configure Cloudinary credentials
+    cloudinary.config( 
+        cloud_name = "dm9tdqvp6", 
+        api_key ="793865869491345", 
+        api_secret = "0vhdvBoM35IWcO29NyI04Qj1PMo" 
+    )
+    # Upload a file to Cloudinary
+    result = cloudinary.uploader.upload(fileName, folder="poc-graph", resource_type="raw")
+    return result