diff --git a/delete_model_passthrough.py b/delete_model_passthrough.py
index 78cfd9b..1a7fafe 100644
--- a/delete_model_passthrough.py
+++ b/delete_model_passthrough.py
@@ -1,413 +1,3 @@
-# import torch, gc, psutil
-# import comfy.model_management as mm
-# from comfy.model_management import current_loaded_models, LoadedModel
-
-# class AnyType(str):
-#     def __ne__(self, __value: object) -> bool: return False
-# any_typ = AnyType("*")
-
-
-# def hard_free(model):
-#     """
-#     Forcefully free model memory by detaching parameters and clearing caches.
-#     """
-#     try:
-#         # Clear parameters and buffers
-#         if hasattr(model, "parameters"):
-#             for p in model.parameters():
-#                 if p is not None:
-#                     p.detach_()
-#                     if hasattr(p, 'data'):
-#                         del p.data
-#                     del p
-        
-#         if hasattr(model, "buffers"):
-#             for b in model.buffers():
-#                 if b is not None:
-#                     b.detach_()
-#                     if hasattr(b, 'data'):
-#                         del b.data
-#                     del b
-        
-#         # Clear any cached attributes
-#         for attr_name in list(vars(model).keys()):
-#             attr = getattr(model, attr_name)
-#             if isinstance(attr, torch.Tensor):
-#                 attr.detach_()
-#                 delattr(model, attr_name)
-                
-#     except Exception as e:
-#         print(f"Hard free error: {e}")
-
-#     try:
-#         del model
-#     except:
-#         pass
-
-#     gc.collect()
-#     mm.soft_empty_cache()
-
-
-# def purge_specific_from_comfy(model_obj):
-#     """
-#     Remove a specific model from ComfyUI's current_loaded_models list.
-#     Returns the model type if found and removed.
-#     """
-#     deleted_type = "Unknown"
-    
-#     try:
-#         # Check if it's a LoadedModel wrapper
-#         if isinstance(model_obj, LoadedModel):
-#             if model_obj in current_loaded_models:
-#                 current_loaded_models.remove(model_obj)
-#                 # Also detach the underlying model
-#                 if hasattr(model_obj, 'model_unload'):
-#                     model_obj.model_unload()
-#                 deleted_type = f"LoadedModel ({type(model_obj.model).__name__})"
-        
-#         # Check if it's a raw model that might be wrapped in LoadedModel
-#         else:
-#             for i, loaded_model in enumerate(current_loaded_models):
-#                 if loaded_model.model is model_obj:
-#                     current_loaded_models.pop(i)
-#                     if hasattr(loaded_model, 'model_unload'):
-#                         loaded_model.model_unload()
-#                     deleted_type = f"RawModel ({type(model_obj).__name__})"
-#                     break
-        
-#         # Additional cleanup for common model types
-#         if hasattr(model_obj, '__class__'):
-#             cls_name = model_obj.__class__.__name__.lower()
-#             if 'unet' in cls_name:
-#                 deleted_type = "UNet"
-#             elif 'clip' in cls_name:
-#                 deleted_type = "CLIP"
-#             elif 'vae' in cls_name:
-#                 deleted_type = "VAE"
-                
-#     except Exception as e:
-#         print(f"Cache purge error: {e}")
-    
-#     return deleted_type
-
-
-# class DeleteModelPassthrough:
-#     """
-#     ComfyUI Custom Node:
-#       - Accepts any input + a model (UNet/CLIP/VAE/latent).
-#       - Deletes ONLY that model from VRAM, RAM, and ComfyUI cache.
-#       - Auto-detects the model type and logs it.
-#       - Passes the data unchanged.
-#     """
-
-#     @classmethod
-#     def INPUT_TYPES(cls):
-#         return {"required": {"data": (any_typ,), "model": (any_typ,)}}
- 
-#     RETURN_TYPES = (any_typ,)
-#     RETURN_NAMES = ("output",)
-#     FUNCTION = "run"
-#     CATEGORY = "Memory Management"
-
-#     def run(self, data, model):
-#         if model is None:
-#             print("⚠️ No model provided to delete")
-#             return (data,)
-            
-#         # Get memory stats before deletion
-#         before_vram = torch.cuda.memory_allocated() if torch.cuda.is_available() else 0
-#         before_reserved = torch.cuda.memory_reserved() if torch.cuda.is_available() else 0
-#         before_ram = psutil.virtual_memory().percent
-
-#         # Remove from ComfyUI management and free memory
-#         deleted_type = purge_specific_from_comfy(model)
-#         hard_free(model)
-
-#         # Get memory stats after deletion
-#         after_vram = torch.cuda.memory_allocated() if torch.cuda.is_available() else 0
-#         after_reserved = torch.cuda.memory_reserved() if torch.cuda.is_available() else 0
-#         after_ram = psutil.virtual_memory().percent
-
-#         # Log results
-#         print(f"🗑️ Deleted model type: {deleted_type}")
-#         print(f"System RAM change: {before_ram - after_ram:.2f}%")
-        
-#         if torch.cuda.is_available():
-#             vram_freed = (before_vram - after_vram) / (1024 * 1024 * 1024)
-#             reserved_freed = (before_reserved - after_reserved) / (1024 * 1024 * 1024)
-#             print(f"GPU allocated freed: {vram_freed:.3f} GB")
-#             print(f"GPU reserved freed: {reserved_freed:.3f} GB")
-
-#         return (data,)
-
-
-# # Node mappings
-# NODE_CLASS_MAPPINGS = {"DeleteModelPassthrough": DeleteModelPassthrough}
-# NODE_DISPLAY_NAME_MAPPINGS = {"DeleteModelPassthrough": "Delete Model (Passthrough Any)"}
-
-
-# Testing Deepseek's more rigorous version
-
-# import torch, gc, psutil
-# import comfy.model_management as mm
-# from comfy.model_management import current_loaded_models, LoadedModel
-
-# class AnyType(str):
-#     def __ne__(self, __value: object) -> bool: return False
-# any_typ = AnyType("*")
-
-
-# def hard_free(model):
-#     """
-#     Forcefully free model memory by detaching parameters and clearing caches.
-#     Special handling for different model types.
-#     """
-#     if model is None:
-#         return
-        
-#     try:
-#         model_type = type(model).__name__
-#         print(f"🔧 Freeing {model_type} model...")
-        
-#         # Handle ModelPatcher objects (common for CLIP, UNet, VAE)
-#         if model_type == 'ModelPatcher' and hasattr(model, 'model'):
-#             print("   Detaching ModelPatcher parameters...")
-#             real_model = model.model
-#             if hasattr(real_model, "parameters"):
-#                 for p in real_model.parameters():
-#                     if p is not None:
-#                         p.detach_()
-#                         del p
-#             model.model = None
-        
-#         # Handle ControlNet models (they have different structure)
-#         elif 'Control' in model_type or 'control' in model_type.lower():
-#             print("   Detaching ControlNet parameters...")
-#             if hasattr(model, "parameters"):
-#                 for p in model.parameters():
-#                     if p is not None:
-#                         p.detach_()
-#                         del p
-#             if hasattr(model, "weights"):
-#                 model.weights = None
-#             if hasattr(model, "model"):
-#                 model.model = None
-        
-#         # Standard cleanup for any model
-#         if hasattr(model, "parameters"):
-#             for p in model.parameters():
-#                 if p is not None:
-#                     p.detach_()
-#                     del p
-        
-#         if hasattr(model, "buffers"):
-#             for b in model.buffers():
-#                 if b is not None:
-#                     b.detach_()
-#                     del b
-        
-#         # Clear any cached tensor attributes
-#         for attr_name in list(vars(model).keys()):
-#             attr = getattr(model, attr_name)
-#             if isinstance(attr, torch.Tensor):
-#                 attr.detach_()
-#                 delattr(model, attr_name)
-                
-#     except Exception as e:
-#         print(f"❌ Hard free error: {e}")
-
-#     try:
-#         del model
-#     except:
-#         pass
-
-#     gc.collect()
-#     mm.soft_empty_cache()
-
-
-# def print_tracked_models():
-#     """Print all models currently tracked by ComfyUI's main system"""
-#     print("📋 Models in current_loaded_models:")
-#     if not current_loaded_models:
-#         print("   No models tracked in main system")
-#         return 0
-    
-#     count = 0
-#     for i, loaded_model in enumerate(current_loaded_models):
-#         try:
-#             if hasattr(loaded_model, 'model'):
-#                 model_obj = loaded_model.model
-#                 model_type = type(model_obj).__name__
-#                 model_id = id(model_obj)
-#                 print(f"   {i}: {model_type} (id: {model_id})")
-#                 count += 1
-#         except Exception as e:
-#             print(f"   {i}: [Error: {e}]")
-    
-#     return count
-
-
-# def identify_model_type(model_obj):
-#     """Identify what type of model this is"""
-#     if model_obj is None:
-#         return "Unknown"
-    
-#     cls_name = model_obj.__class__.__name__.lower()
-    
-#     if 'clip' in cls_name:
-#         return "CLIP"
-#     elif 'unet' in cls_name:
-#         return "UNet"
-#     elif 'vae' in cls_name:
-#         return "VAE"
-#     elif 'control' in cls_name:
-#         return "ControlNet"
-#     elif 'modelpatcher' in cls_name:
-#         # Check what's inside the ModelPatcher
-#         if hasattr(model_obj, 'model') and model_obj.model is not None:
-#             inner_type = model_obj.model.__class__.__name__.lower()
-#             if 'clip' in inner_type:
-#                 return "CLIP (ModelPatcher)"
-#             elif 'unet' in inner_type:
-#                 return "UNet (ModelPatcher)"
-#             elif 'vae' in inner_type:
-#                 return "VAE (ModelPatcher)"
-#         return "ModelPatcher"
-#     elif 'diffusion' in cls_name:
-#         return "DiffusionModel"
-#     else:
-#         return f"Unknown ({model_obj.__class__.__name__})"
-
-
-# def purge_specific_from_comfy(model_obj):
-#     """
-#     Try to remove model from ComfyUI's tracking systems.
-#     Returns the identified model type.
-#     """
-#     if model_obj is None:
-#         return "None"
-    
-#     model_type = identify_model_type(model_obj)
-#     model_removed = False
-    
-#     print(f"🔍 Target model type: {model_type}")
-#     print(f"🔍 Model object type: {type(model_obj).__name__}")
-#     print(f"🔍 Model ID: {id(model_obj)}")
-    
-#     # Print current tracking state
-#     initial_count = print_tracked_models()
-    
-#     try:
-#         # Try to remove from main tracking system (for CLIP/UNet/VAE)
-#         if current_loaded_models:
-#             for i, loaded_model in enumerate(current_loaded_models):
-#                 try:
-#                     # Check if this LoadedModel contains our target model
-#                     if (hasattr(loaded_model, 'model') and 
-#                         (loaded_model.model is model_obj or 
-#                          (hasattr(model_obj, 'model') and loaded_model.model is model_obj.model))):
-                        
-#                         print(f"🗑️ Removing from tracked models: {type(loaded_model.model).__name__}")
-#                         current_loaded_models.pop(i)
-#                         if hasattr(loaded_model, 'model_unload'):
-#                             loaded_model.model_unload()
-#                         model_removed = True
-#                         break
-#                 except:
-#                     continue
-        
-#         if not model_removed:
-#             print("⚠️ Model not in main tracking system - may use different management")
-            
-#             # For ControlNet and other specially managed models, we can't remove them from tracking
-#             # but we can still free their memory
-#             if 'control' in model_type.lower():
-#                 print("💡 ControlNet models often use custom management systems")
-            
-#     except Exception as e:
-#         print(f"❌ Error during purge attempt: {e}")
-    
-#     # Print final tracking state
-#     final_count = print_tracked_models()
-#     print(f"📊 Tracking change: {initial_count} → {final_count} models")
-    
-#     return model_type
-
-
-# class DeleteModelPassthrough:
-#     """
-#     ComfyUI Custom Node: Deletes models from memory regardless of tracking system.
-#     """
-
-#     @classmethod
-#     def INPUT_TYPES(cls):
-#         return {"required": {"data": (any_typ,), "model": (any_typ,)}}
- 
-#     RETURN_TYPES = (any_typ,)
-#     RETURN_NAMES = ("output",)
-#     FUNCTION = "run"
-#     CATEGORY = "Memory Management"
-
-#     def run(self, data, model):
-#         if model is None:
-#             print("⚠️ No model provided to delete")
-#             return (data,)
-            
-#         # Get memory stats before deletion
-#         before_vram = torch.cuda.memory_allocated() if torch.cuda.is_available() else 0
-#         before_reserved = torch.cuda.memory_reserved() if torch.cuda.is_available() else 0
-#         before_ram = psutil.virtual_memory().percent
-
-#         print("=" * 60)
-#         print("🧹 Starting model deletion process")
-#         print("=" * 60)
-        
-#         # Try to remove from tracking and free memory
-#         deleted_type = purge_specific_from_comfy(model)
-#         hard_free(model)
-
-#         # Get memory stats after deletion
-#         after_vram = torch.cuda.memory_allocated() if torch.cuda.is_available() else 0
-#         after_reserved = torch.cuda.memory_reserved() if torch.cuda.is_available() else 0
-#         after_ram = psutil.virtual_memory().percent
-
-#         # Log results
-#         # print("=" * 60)
-#         # print("📊 Memory Free Results:")
-#         # print("=" * 60)
-#         # print(f"🗑️ Deleted model type: {deleted_type}")
-#         # print(f"💾 System RAM change: {before_ram - after_ram:+.2f}%")
-        
-#         if torch.cuda.is_available():
-#             vram_freed = (before_vram - after_vram) / (1024 * 1024 * 1024)
-#             reserved_freed = (before_reserved - after_reserved) / (1024 * 1024 * 1024)
-#             # print(f"🎮 GPU allocated freed: {vram_freed:.3f} GB")
-#             # print(f"🎮 GPU reserved freed: {reserved_freed:.3f} GB")
-#             # print(f"🎮 Final allocated: {after_vram / (1024 * 1024 * 1024):.3f} GB")
-#             # print(f"🎮 Final reserved: {after_reserved / (1024 * 1024 * 1024):.3f} GB")
-        
-#         print("=" * 60)
-        
-#         # Success determination based on memory freed
-#         if torch.cuda.is_available() and reserved_freed > 1:  # Freed at least 1000MB
-#             print("✅ SUCCESS: Significant memory freed!")
-#         elif torch.cuda.is_available() and reserved_freed > 0:
-#             print("⚠️ PARTIAL: Some memory freed, but model may still be referenced")
-#         else:
-#             print("❌ FAILED: No significant memory freed - model may be already freed or invalid")
-        
-#         print("=" * 60)
-
-#         return (data,)
-
-
-# # Node mappings
-# NODE_CLASS_MAPPINGS = {"DeleteModelPassthrough": DeleteModelPassthrough}
-# NODE_DISPLAY_NAME_MAPPINGS = {"DeleteModelPassthrough": "Delete Model (Passthrough Any)"}
-
-
-# Testing another one of Deepseek's more rigorous version
-
 import torch, gc, psutil
 import comfy.model_management as mm
 from comfy.model_management import loaded_models, free_memory, get_torch_device
@@ -418,9 +8,7 @@ any_typ = AnyType("*")
 
 
 def hard_free_model(model):
-    """
-    Forcefully free model memory using ComfyUI's proper methods
-    """
+        
     if model is None:
         return
         
@@ -430,17 +18,17 @@ def hard_free_model(model):
         
         # Handle dictionary-style models (common in some workflows)
         if isinstance(model, dict):
-            print("📦 Handling dictionary-style model container...")
+            # print("📦 Handling dictionary-style model container...")
             for key, value in list(model.items()):
                 if hasattr(value, 'parameters') or hasattr(value, 'model'):
-                    print(f"   Freeing {key}: {type(value).__name__}")
+                    # print(f"   Freeing {key}: {type(value).__name__}")
                     hard_free_model(value)
                 del model[key]
             return
         
         # Handle ModelPatcher objects
         if hasattr(model, 'model') and model.model is not None:
-            print("   Detaching inner model from ModelPatcher...")
+            # print("   Detaching inner model from ModelPatcher...")
             inner_model = model.model
             if hasattr(inner_model, "parameters"):
                 for p in inner_model.parameters():
@@ -546,12 +134,10 @@ class DeleteModelPassthrough:
         before_reserved = torch.cuda.memory_reserved() if torch.cuda.is_available() else 0
         before_ram = psutil.virtual_memory().percent
 
-        print("=" * 60)
-        print("🧹 Starting proper model deletion process")
-        print("=" * 60)
+
         
         model_type = identify_model_type(model)
-        print(f"🔍 Target model type: {model_type}")
+        # print(f"🔍 Target model type: {model_type}")
         
         # Print current state
         initial_count = print_currently_loaded()
@@ -561,7 +147,7 @@ class DeleteModelPassthrough:
         current_models = mm.loaded_models()
         
         if model in current_models:
-            print("🗑️ Removing model from ComfyUI management...")
+            # print("🗑️ Removing model from ComfyUI management...")
             current_models.remove(model)
             model_removed = True
         else:
@@ -571,7 +157,7 @@ class DeleteModelPassthrough:
                     if (hasattr(managed_model, 'model') and 
                         (managed_model.model is model or 
                          (hasattr(model, 'model') and managed_model.model is model.model))):
-                        print("🗑️ Removing wrapped model from ComfyUI management...")
+                        # print("🗑️ Removing wrapped model from ComfyUI management...")
                         current_models.remove(managed_model)
                         model_removed = True
                         break
@@ -579,11 +165,11 @@ class DeleteModelPassthrough:
                     continue
         
         # Free memory using ComfyUI's proper methods
-        print("💾 Freeing memory using ComfyUI's system...")
+        # print("💾 Freeing memory using ComfyUI's system...")
         mm.free_memory(1e30, mm.get_torch_device(), mm.loaded_models())
         
         # Additional forceful cleanup
-        print("🧹 Forceful cleanup...")
+        # print("🧹 Forceful cleanup...")
         hard_free_model(model)
         
         # ComfyUI's cache cleanup
@@ -603,31 +189,26 @@ class DeleteModelPassthrough:
         # Print final state
         final_count = print_currently_loaded()
         
-        # Log results
-        print("=" * 60)
-        print("📊 Deletion Results:")
-        print("=" * 60)
-        print(f"🗑️ Model type: {model_type}")
         print(f"📊 Managed models: {initial_count} → {final_count}")
         print(f"💾 System RAM change: {before_ram - after_ram:+.2f}%")
         
         if torch.cuda.is_available():
             vram_freed = (before_vram - after_vram) / (1024 * 1024 * 1024)
             reserved_freed = (before_reserved - after_reserved) / (1024 * 1024 * 1024)
-            print(f"🎮 GPU allocated freed: {vram_freed:.3f} GB")
-            print(f"🎮 GPU reserved freed: {reserved_freed:.3f} GB")
-            print(f"🎮 Final allocated: {after_vram / (1024 * 1024 * 1024):.3f} GB")
-            print(f"🎮 Final reserved: {after_reserved / (1024 * 1024 * 1024):.3f} GB")
+            print(f"GPU allocated freed: {vram_freed:.3f} GB")
+            print(f"GPU reserved freed: {reserved_freed:.3f} GB")
+            # print(f"Final allocated: {after_vram / (1024 * 1024 * 1024):.3f} GB")
+            # print(f"Final reserved: {after_reserved / (1024 * 1024 * 1024):.3f} GB")
         
         print("=" * 60)
         
         # Success determination
         if model_removed:
-            print("✅ SUCCESS: Model removed from management system!")
+            print("SUCCESS: Model removed from management system!")
         elif torch.cuda.is_available() and reserved_freed > 0.1:
-            print("✅ SUCCESS: Significant memory freed (model may use custom management)")
+            print("SUCCESS: Significant memory freed (model may use custom management)")
         else:
-            print("⚠️  PARTIAL: Model may still be referenced somewhere")
+            print("⚠PARTIAL: Model may still be referenced somewhere")
         
         print("=" * 60)