Update app.py

app.py

@@ -476,13 +476,13 @@ def auto_ensemble_process(audio, model_keys, state, seg_size=64, overlap=0.1, ou
                 "model_outputs": {}
             }
 
-        # Yeni audio dosyası kontrolü
-        if state["current_audio"] != audio or state["current_model_idx"] >= len(model_keys):
+        # Yeni audio dosyası kontrolü - yalnızca audio değiştiğinde sıfırlıyoruz
+        if state["current_audio"] != audio:
             state["current_audio"] = audio
             state["current_model_idx"] = 0
             state["processed_stems"] = []
             state["model_outputs"] = {model_key: {"vocals": [], "other": []} for model_key in model_keys}
-            logger.info("New audio or completed cycle detected, resetting ensemble state.")
+            logger.info("New audio detected, resetting ensemble state.")
 
         use_tta = use_tta == "True"
         base_name = os.path.splitext(os.path.basename(audio))[0]
@@ -499,8 +499,10 @@ def auto_ensemble_process(audio, model_keys, state, seg_size=64, overlap=0.1, ou
 
         # Şu anki modeli işle
         current_idx = state["current_model_idx"]
+        logger.info(f"Current model index: {current_idx}, total models: {len(model_keys)}")
+
+        # Tüm modeller işlendiyse ensemble işlemini yap
         if current_idx >= len(model_keys):
-            # Tüm modeller işlendiyse ensemble işlemini yap
             logger.info("All models processed, running ensemble...")
             progress(0.9, desc="Running ensemble...")
 
@@ -646,6 +648,11 @@ def auto_ensemble_process(audio, model_keys, state, seg_size=64, overlap=0.1, ou
         elapsed = time.time() - start_time
         logger.info(f"Model {model_key} completed in {elapsed:.2f}s")
 
+        # Eğer bu son modelse, ensemble işlemini hemen başlat
+        if state["current_model_idx"] >= len(model_keys):
+            logger.info("Last model processed, running ensemble immediately...")
+            return auto_ensemble_process(audio, model_keys, state, seg_size, overlap, out_format, use_tta, model_dir, output_dir, norm_thresh, amp_thresh, batch_size, ensemble_method, exclude_stems, weights_str, progress)
+
         # Çıktılar
         file_list = state["processed_stems"]
         status = f"Model {model_key} (Model {current_idx + 1}/{len(model_keys)}) completed in {elapsed:.2f}s<br>Click 'Run Ensemble!' to process the next model.<br>Processed stems:<ul>"
@@ -669,7 +676,7 @@ def auto_ensemble_process(audio, model_keys, state, seg_size=64, overlap=0.1, ou
                 logger.warning(f"Failed to delete temporary file {temp_audio_path}: {e}")
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
-            logger.info("GPU memory cleared")  
+            logger.info("GPU memory cleared") 
             
 def update_roformer_models(category):
     """Update Roformer model dropdown based on selected category."""