diff --git a/scripts/physton_prompt/get_token_counter.py b/scripts/physton_prompt/get_token_counter.py
index 169f6e5..57bb097 100644
--- a/scripts/physton_prompt/get_token_counter.py
+++ b/scripts/physton_prompt/get_token_counter.py
@@ -1,44 +1,50 @@
 from modules import script_callbacks, extra_networks, prompt_parser, sd_models
-from modules.sd_hijack import model_hijack
-from functools import partial, reduce
+from functools import reduce
+
+# 嘗試載入 sd_hijack / model_hijack（A1111 / Forge Classic 才有）
+try:
+    from modules.sd_hijack import model_hijack
+except (ImportError, ModuleNotFoundError):
+    model_hijack = None
 
 
 def get_token_counter(text, steps):
-    # FIX: Use try-except to safely handle PyTorch/model access errors (TypeError NoneType)
-    # that occur during model loading/switching when the token counter API is triggered.
     try:
-        # copy from modules.ui.py
         try:
             text, _ = extra_networks.parse_prompt(text)
-
             _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
             prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
-
         except Exception:
-            # a parsing error can happen here during typing, and we don't want to bother the user with
-            # messages related to it in console
             prompt_schedules = [[[steps, text]]]
 
+        # 判斷是否 Forge
         try:
             from modules_forge import forge_version
             forge = True
-
         except:
             forge = False
 
         flat_prompts = reduce(lambda list1, list2: list1 + list2, prompt_schedules)
         prompts = [prompt_text for step, prompt_text in flat_prompts]
 
+        # 🚨 Forge Neo / 沒有 hijack：直接停用 token counter
+        if model_hijack is None:
+            return {"token_count": 0, "max_length": 0}
+
+        # A1111 / Forge Classic
         if forge:
             cond_stage_model = sd_models.model_data.sd_model.cond_stage_model
-            token_count, max_length = max([model_hijack.get_prompt_lengths(prompt,cond_stage_model) for prompt in prompts],
-                                        key=lambda args: args[0])
+            token_count, max_length = max(
+                [model_hijack.get_prompt_lengths(prompt, cond_stage_model) for prompt in prompts],
+                key=lambda args: args[0]
+            )
         else:
-            token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts],
-                                        key=lambda args: args[0])
+            token_count, max_length = max(
+                [model_hijack.get_prompt_lengths(prompt) for prompt in prompts],
+                key=lambda args: args[0]
+            )
 
         return {"token_count": token_count, "max_length": max_length}
 
-    except Exception as e:
-        # return 0 token count if any error (model instability, parsing error, etc.) occurs during calculation
+    except Exception:
         return {"token_count": 0, "max_length": 0}