Update app.py

app.py

@@ -30,11 +30,10 @@ os.makedirs(OUTPUT_DIR, exist_ok=True)
 # Initialize the Separator class (this might download the model on first run)
 logger.info(f"Initializing audio separator with model: {MODEL_NAME}...")
 try:
-    # You might need to specify log level or other options depending on audio-separator version
-    separator = Separator(model_name=MODEL_NAME,
-                          log_level='INFO',
+    # Initialize Separator WITHOUT the model_name argument first
+    separator = Separator(log_level='INFO',
                           # Optional: Specify device (e.g., 'cuda' if PyTorch GPU is setup, else 'cpu')
-                          # computation_device='cuda' 
+                          # computation_device='cuda'
                           )
     logger.info("Separator initialized successfully.")
 except Exception as e:
@@ -56,24 +55,25 @@ def enhance_vocal(input_audio_path):
     logger.info(f"Processing audio file: {input_audio_path}")
     processing_start_time = time.time()
 
-    try:
+     try:
         # --- Step 1: Vocal Separation using audio-separator (UVR5) ---
-        logger.info("Starting vocal separation...")
+        logger.info(f"Starting vocal separation using model: {MODEL_NAME}...") # Log model name here
         separation_start_time = time.time()
 
-        # Create a temporary directory for separation outputs
-        # This directory will be automatically cleaned up
         with tempfile.TemporaryDirectory(prefix=TEMP_SEP_DIR_PREFIX) as temp_sep_dir:
             logger.info(f"Using temporary directory for separation: {temp_sep_dir}")
-            
+
             try:
-                # Perform separation
-                # The library typically saves files named like:
-                # {basename}_(Vocals)_{model_name}.wav
-                # {basename}_(Instrumental)_{model_name}.wav
-                # Or similar, depending on the model type and library version.
-                output_paths = separator.separate(input_audio_path, output_dir=temp_sep_dir)
-                
+                # Perform separation - NOW we pass the model name HERE
+                # Check audio-separator documentation for your version if this exact syntax fails.
+                output_paths = separator.separate(
+                    input_audio_path,
+                    output_dir=temp_sep_dir,
+                    model_name=MODEL_NAME # Pass model name to the separate method
+                    # Other potential arguments might be needed depending on the version
+                    # e.g., output_format='wav'
+                )
+
                 separation_duration = time.time() - separation_start_time
                 logger.info(f"Separation completed in {separation_duration:.2f} seconds.")
                 logger.info(f"Separation output files: {output_paths}")