Return of try except

app.py

@@ -197,47 +197,45 @@ def bot(
 
     # Use processor if images are present
     if processor is not None and has_images:
-        # try:
-        processor_history = []
-        for msg in history:
-            role = msg.get("role", "user")
-            content = msg.get("content")
-
-            if isinstance(content, str):
-                processor_history.append({"role": role, "content": [{"type": "text", "text": content}]})
-            elif isinstance(content, tuple):
-                formatted_content = []
-                tmp_path, _ = content 
-                image_input = {
-                    "type": "image",
-                    "url": f"{tmp_path}",
-                }
-
-                if processor_history[-1].get('role') == 'user':
-                    if isinstance(processor_history[-1].get('content'), str):
-                        previous_message = processor_history[-1].get('content')
-                        formatted_content.append({"type": "text", "text": previous_message})
+        try:
+            processor_history = []
+            for msg in history:
+                role = msg.get("role", "user")
+                content = msg.get("content")
+
+                if isinstance(content, str):
+                    processor_history.append({"role": role, "content": [{"type": "text", "text": content}]})
+                elif isinstance(content, tuple):
+                    formatted_content = []
+                    tmp_path, _ = content 
+                    image_input = {
+                        "type": "image",
+                        "url": f"{tmp_path}",
+                    }
+
+                    if processor_history[-1].get('role') == 'user':
+                        if isinstance(processor_history[-1].get('content'), str):
+                            previous_message = processor_history[-1].get('content')
+                            formatted_content.append({"type": "text", "text": previous_message})
+                            formatted_content.append(image_input)
+                            processor_history[-1]['content'] = formatted_content
+                        elif isinstance(processor_history[-1].get('content'), list):
+                            processor_history[-1]['content'].append(image_input)
+                    else:
                         formatted_content.append(image_input)
-                        processor_history[-1]['content'] = formatted_content
-                    elif isinstance(processor_history[-1].get('content'), list):
-                        processor_history[-1]['content'].append(image_input)
-                else:
-                    formatted_content.append(image_input)
-                    processor_history.append({"role": role, "content": formatted_content})
-
-        print(processor_history)
-
-        model_inputs = processor.apply_chat_template(
-            processor_history,
-            tokenize=True,
-            return_dict=True,
-            return_tensors="pt",
-            add_generation_prompt=True,
-        ).to(model.device)
-        print("Using processor for vision input")
-        # except Exception as exc:
-        #     print(f"Processor failed: {exc}")
-        #     model_inputs = None
+                        processor_history.append({"role": role, "content": formatted_content})
+
+            model_inputs = processor.apply_chat_template(
+                processor_history,
+                tokenize=True,
+                return_dict=True,
+                return_tensors="pt",
+                add_generation_prompt=True,
+            ).to(model.device)
+            print("Using processor for vision input")
+        except Exception as exc:
+            print(f"Processor failed: {exc}")
+            model_inputs = None
 
     # Fallback to tokenizer for text-only
     if model_inputs is None: