Update app.py

app.py

@@ -7,6 +7,7 @@ import os
 import uuid
 import shutil
 import gzip
+import io
 
 # Importing the model-related functions
 from stable_audio_tools import get_pretrained_model
@@ -81,19 +82,28 @@ def generate_audio(prompt, seconds_total=30, steps=100, cfg_scale=7):
     output = output.to(torch.float32).div(torch.max(torch.abs(output))).clamp(-1, 1).mul(32767).to(torch.int16).cpu()
     print("Audio normalized and converted.")
 
-    # Generate a unique filename for the output
-    unique_filename = f"output_{uuid.uuid4().hex}.wav"
-    print(f"Saving audio to file: {unique_filename}")
+    # # Generate a unique filename for the output
+    # unique_filename = f"output_{uuid.uuid4().hex}.wav"
+    # print(f"Saving audio to file: {unique_filename}")
 
-    # Save to file
-    torchaudio.save(unique_filename, output, sample_rate)
-    print(f"Audio saved: {unique_filename}")
+    # # Save to file
+    # torchaudio.save(unique_filename, output, sample_rate)
+    # print(f"Audio saved: {unique_filename}")
     
-    compressed_filename = compress_file(unique_filename)
-    return compressed_filename
+    # compressed_filename = compress_file(unique_filename)
+    # return compressed_filename
 
     # # Return the path to the generated audio file
     # return unique_filename
+    
+    # Convert audio tensor to bytes
+    byte_io = io.BytesIO()
+    torchaudio.save(byte_io, output, sample_rate, format="wav")
+    byte_io.seek(0)
+    audio_bytes = byte_io.read()
+    print("Audio converted to bytes.")
+
+    return audio_bytes
 
 
 DESCRIPTION = "Welcome to Raptor APIs"