Update app.py

app.py

@@ -192,26 +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}")
-                continue
-
-            print(f"Loading model from: {path}")
-            try:
-                cpt = torch.load(path, map_location="cpu")
-                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']}"))
+            cpt = torch.load(f"/weights/{category_folder}/{character_name}/{model_name}", map_location="cpu")
+            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
         categories.append([category_title, category_folder, models])
     return categories