Update app.py

app.py

@@ -488,7 +488,6 @@ def auto_ensemble_process(audio, model_keys, seg_size=128, overlap=0.1, out_form
                 while retry_count <= max_retries:
                     try:
                         progress((model_idx + 0.1) / total_models, desc=f"Loading {model_key} for chunk {chunk_idx}")
-                        # Check if model is cached
                         model_path = os.path.join(model_dir, model)
                         if not os.path.exists(model_path):
                             logger.info(f"Model {model} not cached, will download")
@@ -522,14 +521,13 @@ def auto_ensemble_process(audio, model_keys, seg_size=128, overlap=0.1, out_form
                         if retry_count > max_retries:
                             logger.error(f"Max retries reached for {model_key} chunk {chunk_idx}, skipping")
                             break
-                        time.sleep(1)  # Reduced delay to minimize overhead
+                        time.sleep(1)
                     finally:
                         separator = None
                         gc.collect()
                         if torch.cuda.is_available():
                             torch.cuda.empty_cache()
                             logger.info(f"Cleared CUDA cache after {model_key} chunk {chunk_idx}")
-                # Yield control to ZeroGPU scheduler
                 time.sleep(0.1)
         progress(0.8, desc="Combining stems...")
         for model_key, stems_dict in model_stems.items():
@@ -565,13 +563,19 @@ def auto_ensemble_process(audio, model_keys, seg_size=128, overlap=0.1, out_form
         progress(0.9, desc="Running ensemble...")
         logger.info(f"Running ensemble with args: {ensemble_args}")
         try:
-            ensemble_files(ensemble_args)
-            logger.info("Ensemble completed")
+            ensemble.ensemble_files(ensemble_args)
+            if not os.path.exists(output_file):
+                raise RuntimeError(f"Ensemble output file not created: {output_file}")
+            logger.info(f"Ensemble completed, output: {output_file}")
             progress(1.0, desc="Ensemble completed")
             return output_file, f"Ensemble completed with {ensemble_method}, excluded: {exclude_stems if exclude_stems else 'None'}"
         except Exception as e:
             logger.error(f"Ensemble processing error: {e}")
-            raise RuntimeError(f"Ensemble processing error: {e}")
+            if "numpy" in str(e).lower() or "copy" in str(e).lower():
+                error_msg = f"NumPy compatibility error: {e}. Try installing numpy<2.0.0 or contact support."
+            else:
+                error_msg = f"Ensemble processing error: {e}"
+            raise RuntimeError(error_msg)
     except Exception as e:
         logger.error(f"Ensemble error: {e}")
         if "ZeroGPU" in str(e) or "aborted" in str(e).lower():