Fix: Use try-except to stabilize token counter during model access

This fixes a server crash (TypeError NoneType in torch/nn/modules/module.py) when the token counter API is triggered during model load/switch.

Standard sequential null checks failed because the crash occurred inside PyTorch's internal attribute lookup process. The whole function is wrapped in try-except as a robust defense against this race condition.

scripts/physton_prompt/get_token_counter.py

@@ -4,11 +4,9 @@ from functools import partial, reduce
 
 
 def get_token_counter(text, steps):
-    # FIX: Robust Null Check to prevent TypeError during model loading/unloading.
-    # Checks for the existence of model_data and its property sd_model sequentially.
-    if sd_models.model_data is None or sd_models.model_data.sd_model is None:
-        return {"token_count": 0, "max_length": 0}
-
+    # 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)
@@ -40,3 +38,7 @@ def get_token_counter(text, steps):
                                         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
+        return {"token_count": 0, "max_length": 0}