Update app.py

app.py

@@ -8,6 +8,8 @@ import spaces
 import torch
 import tempfile
 import io
+import uuid
+from pathlib import Path
 
 # Initialize the model
 def load_model():
@@ -17,7 +19,7 @@ semanticodec = load_model()
 
 @spaces.GPU(duration=20)
 def encode_audio(audio_path):
-    """Encode audio file to tokens and return them as a binary buffer"""
+    """Encode audio file to tokens and return them as a file"""
     tokens = semanticodec.encode(audio_path)
     # Move tokens to CPU before converting to numpy
     if isinstance(tokens, torch.Tensor):
@@ -31,19 +33,27 @@ def encode_audio(audio_path):
     # Verify the buffer has content
     if buffer.getbuffer().nbytes == 0:
         raise Exception("Failed to create token buffer")
-        
-    return buffer, f"Encoded to {len(tokens)} tokens"
+    
+    # Create a temporary file in /tmp which is writable in Spaces
+    temp_dir = "/tmp"
+    os.makedirs(temp_dir, exist_ok=True)
+    temp_file_path = os.path.join(temp_dir, f"tokens_{uuid.uuid4()}.oterin")
+    
+    # Write buffer to the temporary file
+    with open(temp_file_path, "wb") as f:
+        f.write(buffer.getvalue())
+    
+    return temp_file_path, f"Encoded to {len(tokens)} tokens"
 
 @spaces.GPU(duration=60)
-def decode_tokens(token_buffer):
+def decode_tokens(token_file):
     """Decode tokens to audio"""
-    # Ensure the buffer has content
-    if not token_buffer or token_buffer.getbuffer().nbytes == 0:
-        return None, "Error: Empty token buffer"
+    # Ensure the file exists and has content
+    if not token_file or not os.path.exists(token_file):
+        return None, "Error: Empty or missing token file"
     
-    # Reset buffer position to start
-    token_buffer.seek(0)
-    tokens = np.load(token_buffer)
+    # Load tokens from file
+    tokens = np.load(token_file)
     
     # Convert to torch tensor if needed by the model
     if hasattr(semanticodec, 'decode_requires_tensor') and semanticodec.decode_requires_tensor: