Update app.py

app.py

@@ -174,7 +174,6 @@ def infer(name, path, index, vc_input, vc_upload, tts_text, tts_voice, f0_up_key
         info = traceback.format_exc()
         print(info)
         return info, (None, None)
-
 def load_model():
     categories = []
     with open("/weights/folder_info.json", "r", encoding="utf-8") as f:
@@ -193,26 +192,26 @@ def load_model():
                 continue
             model_title = info['title']
             model_name = info['model_path']
-            model_author = info.get("author", None)
-            model_cover = f"/weights/{category_folder}/{character_name}/{info['cover']}"
-            model_index = f"/weights/{category_folder}/{character_name}/{info['feature_retrieval_library']}"
-            if info['feature_retrieval_library'] == "None":
-                model_index = None
-            if model_index:
-               assert os.path.exists(model_index), f"Model {model_title} failed to load index."
-            if not (model_author in authors or "/" in model_author or "&" in model_author):
-                authors.append(model_author)
-            model_path =  f"/weights/{category_folder}/{character_name}/{model_name}"
-            import pickle
             path = f"/weights/{category_folder}/{character_name}/{model_name}"
-                
+
+            # ファイルの存在確認
             if not os.path.exists(path):
                 print(f"Model file not found: {path}")
-            cpt = torch.load(f"/weights/{category_folder}/{character_name}/{model_name}", map_location="cpu", pickle_module=pickle)
-            model_version = cpt.get("version", "v1")
-            print(f"Indexed model {model_title} by {model_author} ({model_version})")
-            models.append((character_name, model_title, model_author, model_cover, model_version, model_path, model_index))
-            del cpt
+                continue
+
+            print(f"Loading model from: {path}")
+            try:
+                cpt = torch.load(path, map_location="cpu", pickle_module=pickle)
+                model_version = cpt.get("version", "v1")
+                print(f"Indexed model {model_title} by {info.get('author', 'Unknown')} ({model_version})")
+            except Exception as e:
+                print(f"Error loading model {model_title}: {e}")
+                continue
+
+            models.append((character_name, model_title, info.get('author', 'Unknown'), 
+                           f"/weights/{category_folder}/{character_name}/{info['cover']}", 
+                           model_version, path, 
+                           f"/weights/{category_folder}/{character_name}/{info['feature_retrieval_library']}"))
         categories.append([category_title, category_folder, models])
     return categories