continues to remove cache parameter

app.py

@@ -174,7 +174,7 @@ def initialize_model_safely():
     """
     model_name = 'ucaslcl/GOT-OCR2_0'
     device = 'cuda' if torch.cuda.is_available() else 'cpu'
-    
+
     try:
         # Initialize tokenizer with proper settings
         tokenizer = AutoTokenizer.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True)
@@ -262,6 +262,58 @@ def direct_model_call(model, method_name, *args, **kwargs):
     method = getattr(model, method_name)
     return method(*args, **clean_kwargs)
 
+def safe_model_call_with_dynamic_cache_fix(model, method_name, *args, **kwargs):
+    """
+    Safe model call that handles DynamicCache errors specifically
+    """
+    try:
+        return direct_model_call(model, method_name, *args, **kwargs)
+    except AttributeError as e:
+        if "get_max_length" in str(e) and "DynamicCache" in str(e):
+            # This is the specific DynamicCache error we need to handle
+            print("DynamicCache error detected, applying workaround...")
+            
+            # Try to clear any existing cache
+            try:
+                if hasattr(model, 'clear_cache'):
+                    model.clear_cache()
+                # Also try to clear transformers cache
+                import torch
+                if torch.cuda.is_available():
+                    torch.cuda.empty_cache()
+            except:
+                pass
+            
+            # Try the call again with minimal parameters
+            try:
+                # Create minimal kwargs with only essential parameters
+                minimal_kwargs = {}
+                essential_params = ['ocr_type', 'render', 'save_render_file', 'ocr_box', 'ocr_color']
+                for key, value in kwargs.items():
+                    if key in essential_params and 'cache' not in key.lower():
+                        minimal_kwargs[key] = value
+                
+                method = getattr(model, method_name)
+                return method(*args, **minimal_kwargs)
+            except Exception as retry_error:
+                # If still failing, try with even more minimal approach
+                try:
+                    # Try with only the most basic parameters
+                    basic_kwargs = {}
+                    if 'ocr_type' in kwargs:
+                        basic_kwargs['ocr_type'] = kwargs['ocr_type']
+                    
+                    method = getattr(model, method_name)
+                    return method(*args, **basic_kwargs)
+                except Exception as final_error:
+                    raise Exception(f"DynamicCache workaround failed: {str(final_error)}")
+        else:
+            # Re-raise if it's not the DynamicCache error
+            raise e
+    except Exception as e:
+        # Handle other errors
+        raise e
+
 @spaces.GPU()
 def process_image(image, task, ocr_type=None, ocr_box=None, ocr_color=None):
     """
@@ -293,22 +345,22 @@ def process_image(image, task, ocr_type=None, ocr_box=None, ocr_color=None):
         else:
             return "Error: Unsupported image format", None, None
 
-        # Use direct model calls without any cache management
+        # Use safe model calls with DynamicCache error handling
         try:
             if task == "Plain Text OCR":
-                res = direct_model_call(model, 'chat', tokenizer, image_path, ocr_type='ocr')
+                res = safe_model_call_with_dynamic_cache_fix(model, 'chat', tokenizer, image_path, ocr_type='ocr')
                 return res, None, unique_id
             else:
                 if task == "Format Text OCR":
-                    res = direct_model_call(model, 'chat', tokenizer, image_path, ocr_type='format', render=True, save_render_file=result_path)
+                    res = safe_model_call_with_dynamic_cache_fix(model, 'chat', tokenizer, image_path, ocr_type='format', render=True, save_render_file=result_path)
                 elif task == "Fine-grained OCR (Box)":
-                    res = direct_model_call(model, 'chat', tokenizer, image_path, ocr_type=ocr_type, ocr_box=ocr_box, render=True, save_render_file=result_path)
+                    res = safe_model_call_with_dynamic_cache_fix(model, 'chat', tokenizer, image_path, ocr_type=ocr_type, ocr_box=ocr_box, render=True, save_render_file=result_path)
                 elif task == "Fine-grained OCR (Color)":
-                    res = direct_model_call(model, 'chat', tokenizer, image_path, ocr_type=ocr_type, ocr_color=ocr_color, render=True, save_render_file=result_path)
+                    res = safe_model_call_with_dynamic_cache_fix(model, 'chat', tokenizer, image_path, ocr_type=ocr_type, ocr_color=ocr_color, render=True, save_render_file=result_path)
                 elif task == "Multi-crop OCR":
-                    res = direct_model_call(model, 'chat_crop', tokenizer, image_path, ocr_type='format', render=True, save_render_file=result_path)
+                    res = safe_model_call_with_dynamic_cache_fix(model, 'chat_crop', tokenizer, image_path, ocr_type='format', render=True, save_render_file=result_path)
                 elif task == "Render Formatted OCR":
-                    res = direct_model_call(model, 'chat', tokenizer, image_path, ocr_type='format', render=True, save_render_file=result_path)
+                    res = safe_model_call_with_dynamic_cache_fix(model, 'chat', tokenizer, image_path, ocr_type='format', render=True, save_render_file=result_path)
                 
                 if os.path.exists(result_path):
                     with open(result_path, 'r') as f:
@@ -317,7 +369,7 @@ def process_image(image, task, ocr_type=None, ocr_box=None, ocr_color=None):
                 else:
                     return res, None, unique_id
         except Exception as e:
-            # If direct call fails, try with cache manager as fallback
+            # If safe call fails, try with cache manager as fallback
             try:
                 if task == "Plain Text OCR":
                     res = cache_manager.safe_call('chat', tokenizer, image_path, ocr_type='ocr')
@@ -348,7 +400,7 @@ def process_image(image, task, ocr_type=None, ocr_box=None, ocr_color=None):
     finally:
         if os.path.exists(image_path):
             os.remove(image_path)
-
+            
 def update_image_input(task):
     if task == "Fine-grained OCR (Color)":
         return gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)