Update app.py

app.py

@@ -22,9 +22,18 @@ def inference(audio_file: str, model_name: str, vocals: bool, drums: bool, bass:
     yield None, stream_log("Starting separation process...")
     yield None, stream_log(f"Loading audio file: {audio_file}")
     
+    # Check if audio_file is None
+    if audio_file is None:
+        yield None, stream_log("Error: No audio file provided")
+        raise gr.Error("Please upload an audio file")
+
     # Load the audio file with the correct samplerate and audio channels
-    wav, sr = load_track(audio_file, samplerate=separator.samplerate, audio_channels=2)
-    
+    try:
+        wav, sr = load_track(audio_file, samplerate=separator.samplerate, audio_channels=2)
+    except Exception as e:
+        yield None, stream_log(f"Error loading audio file: {str(e)}")
+        raise gr.Error(f"Failed to load audio file: {str(e)}")
+
     # Check the number of channels and adjust if necessary
     if wav.dim() == 1:
         wav = wav.unsqueeze(0)  # Add channel dimension if mono
@@ -40,8 +49,12 @@ def inference(audio_file: str, model_name: str, vocals: bool, drums: bool, bass:
     yield None, stream_log("Audio loaded successfully. Applying model...")
     
     # Use apply_model as a standalone function
-    sources = apply_model(separator, wav.to(device), device=device)
-    
+    try:
+        sources = apply_model(separator, wav.to(device), device=device)
+    except Exception as e:
+        yield None, stream_log(f"Error applying model: {str(e)}")
+        raise gr.Error(f"Failed to apply model: {str(e)}")
+
     # Process the sources
     sources = [source * ref.view(1, -1) + ref.view(1, -1) for source in sources]