added better missing model error handling

wan/utils/utils.py

@@ -34,6 +34,15 @@ def seed_everything(seed: int):
     if torch.backends.mps.is_available():
         torch.mps.manual_seed(seed)
 
+def expand_slist(slist, num_inference_steps ):
+    new_slist= []
+    inc =  len(slist) / num_inference_steps 
+    pos = 0
+    for i in range(num_inference_steps):
+        new_slist.append(slist[ int(pos)])
+        pos += inc
+    return new_slist
+
 def update_loras_slists(trans, slists, num_inference_steps ):
     from mmgp import offload
     slists = [ expand_slist(slist, num_inference_steps ) if isinstance(slist, list) else slist for slist in slists ]

wgp.py

@@ -16,6 +16,7 @@ import json
 import wan
 from wan.utils import notification_sound
 from wan.configs import MAX_AREA_CONFIGS, WAN_CONFIGS, SUPPORTED_SIZES, VACE_SIZE_CONFIGS
+from wan.utils.utils import expand_slist, update_loras_slists
 from wan.utils.utils import cache_video, convert_tensor_to_image, save_image, get_video_info, get_file_creation_date, convert_image_to_video
 from wan.utils.utils import extract_audio_tracks, combine_video_with_audio_tracks, cleanup_temp_audio_files
 
@@ -160,6 +161,7 @@ def process_prompt_and_add_tasks(state, model_choice):
     model_filename = state["model_filename"]
     model_type = state["model_type"]
     inputs = get_model_settings(state, model_type)
+
     if model_choice != model_type or inputs ==None:
         raise gr.Error("Webform can not be used as the App has been restarted since the form was displayed. Please refresh the page")
     
@@ -1740,6 +1742,8 @@ def get_model_type(model_filename):
 
 def get_model_family(model_type):
     model_type = get_base_model_type(model_type)
+    if model_type == None:
+        return "unknown"
     if "hunyuan" in model_type :
         return "hunyuan"
     elif "ltxv" in model_type:
@@ -1799,7 +1803,8 @@ def get_computed_fps(force_fps, base_model_type , video_guide, video_source ):
 
 def get_model_name(model_type, description_container = [""]):
     model_def = get_model_def(model_type)
-    if model_def == None: raise Exception(f"Unknown model {model_type}")
+    if model_def == None: 
+        return f"Unknown model {model_type}"
     model_name = model_def["name"]
     description = model_def["description"]
     description_container[0] = description
@@ -1832,7 +1837,7 @@ def get_model_filename(model_type, quantization ="int8", dtype_policy = "", is_m
         if choices == None: raise Exception(f"Invalid Module Id '{model_type}'")
     else:
         model_def = models_def.get(model_type, None)
-        if model_def == None: raise Exception(f"Unknown model type {model_type}") 
+        if model_def == None: return None 
         URLs = model_def["URLs"]
         if isinstance(URLs, str):
             if len(stack) > 10: raise Exception(f"Circular Reference in Model URLs dependencies: {stack}")
@@ -2120,11 +2125,18 @@ model_types = models_def.keys()
 displayed_model_types= []
 for model_type in model_types:
     model_def = get_model_def(model_type)
-    if not (model_def != None and model_def.get("visible", True) == False): 
+    if not model_def is None and model_def.get("visible", True): 
         displayed_model_types.append(model_type)
 
 
 transformer_types = server_config.get("transformer_types", [])
+new_transformer_types = []
+for model_type in transformer_types:
+    if get_model_def(model_type)  == None:
+        print(f"Model '{model_type}' is missing. Either install it in the finetune folder or remove this model in wgp_config.json")
+    else:
+        new_transformer_types.append(model_type)
+transformer_types = new_transformer_types
 transformer_type = server_config.get("last_model_type", None)
 advanced = server_config.get("last_advanced_choice", False)
 if args.advanced: advanced = True 
@@ -2729,7 +2741,7 @@ def generate_header(model_type, compile, attention_mode):
 
     description_container = [""]
     get_model_name(model_type, description_container)
-    model_filename = get_model_filename(model_type, transformer_quantization, transformer_dtype_policy)    
+    model_filename = get_model_filename(model_type, transformer_quantization, transformer_dtype_policy) or "" 
     description  = description_container[0]
     header = "<DIV style='height:40px'>" + description + "</DIV>"
 
@@ -3250,14 +3262,7 @@ def select_video(state, input_file_list, event_data: gr.EventData):
         html =  get_default_video_info()
     visible= len(file_list) > 0
     return choice, html, gr.update(visible=visible and not is_image) , gr.update(visible=visible and is_image), gr.update(visible=visible and not is_image) 
-def expand_slist(slist, num_inference_steps ):
-    new_slist= []
-    inc =  len(slist) / num_inference_steps 
-    pos = 0
-    for i in range(num_inference_steps):
-        new_slist.append(slist[ int(pos)])
-        pos += inc
-    return new_slist
+
 def convert_image(image):
 
     from PIL import ImageOps
@@ -7871,7 +7876,7 @@ def generate_info_tab():
 
 
 def  get_sorted_dropdown(dropdown_types):
-    families_order = {"wan":0, "ltxv":1, "hunyuan":2, "flux": 3 }
+    families_order = {"wan":0, "ltxv":1, "hunyuan":2, "flux": 3, "unknown": 100 }
     dropdown_classes = [  families_order[get_model_family(type)] for type in dropdown_types]
     dropdown_names = [ get_model_name(type) for type in dropdown_types]