some optimizations about config loading

config/settings.py

@@ -8,6 +8,19 @@ import typing as t
 
 from config.utils import *
 
+
+"""
+修改配置：用with打开Config，修改后自动保存。可以修改多个配置。
+with Config() as config:
+    config.api.embedding_models.base_url = '123'
+使用配置：每次使用前实例化Config
+！！！注意：如果不重新实例化，config的值不会改变！！！
+应当将Config视为一次性的实例。如果要缓存这个实例，应当保证这个缓存在使用的生命周期内，config不会被改变。
+对于改不了的屎山代码，请在实例化Config时，将keep_tracked参数设置为True。注意：设置后，这个缓存将是只读的。
+
+每次重新实例化不会重新读盘。在内存中有一个缓存。
+"""
+
 CONFIG_DIR = os.path.dirname(os.path.abspath(__file__))
 CONFIG_FILE = os.path.join(CONFIG_DIR, 'config.yaml')
 CONFIG_EXAMPLE_FILE = os.path.join(CONFIG_DIR, 'config.example.yaml')
@@ -71,17 +84,17 @@ class BaseConfig(BaseModel, frozen=False, extra='allow'):
     #                 'value': value
     #             })
 
-class ObserverdDict(dict):
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        self.__dict__['settled_dicts'] = []
-    def __setitem__(self, key, value):
-        print(f"setitem:{key}-{value}")
-        if not isinstance(value, BaseConfig):
-            self.__dict__['settled_dicts'].append({
-                'key': [key],
-                'value': value
-            })
+# class ObserverdDict(dict):
+#     def __init__(self, *args, **kwargs):
+#         super().__init__(*args, **kwargs)
+#         self.__dict__['settled_dicts'] = []
+#     def __setitem__(self, key, value):
+#         print(f"setitem:{key}-{value}")
+#         if not isinstance(value, BaseConfig):
+#             self.__dict__['settled_dicts'].append({
+#                 'key': [key],
+#                 'value': value
+#             })
 
 class EmbeddingModelConfig(BaseConfig):
     name: str
@@ -179,7 +192,7 @@ class Config(BaseConfig):
 
 
 
-    def __init__(self):
+    def __init__(self, keep_tracked = False):
         if sys.gettrace() is not None:
             frame = inspect.currentframe().f_back
             filename = frame.f_code.co_filename
@@ -191,9 +204,13 @@ class Config(BaseConfig):
                 print('loading config')
             data = load_yaml_file(CONFIG_FILE)
             config_cache.set_config(data)
+        if keep_tracked:
+            self.__dict__['keep_tracked'] = True
         super().__init__(**data)
 
     def __enter__(self):
+        if self.__dict__['keep_tracked']:
+            raise RuntimeError('Config object is being tracked, which cannot be modified.')
         return self
 
     def __exit__(self, exc_type, exc_val, exc_tb):
@@ -213,7 +230,6 @@ class Config(BaseConfig):
     #     print('Config object is being deleted')
 
 
-
     @property
     def base_dir(self) -> str:
         """获取项目根目录"""
@@ -250,6 +266,12 @@ class Config(BaseConfig):
         """获取缓存文件的绝对路径"""
         return os.path.join(self.base_dir,self.paths.label_images_cache_file)
 
+    def __getattr__(self, item):
+        if self.__dict__['keep_tracked']:
+            return Config().__getattr__(item)
+        else:
+            return super().__getattr__(item)
+
     # def reload(self) -> None:
     #     """重新加载配置文件"""
     #     new_config = Config()
@@ -267,5 +289,7 @@ if __name__ == '__main__':
     with Config() as config:
         config.api.embedding_models.base_url = '123'
     """使用配置：每次使用前实例化Config"""
+    """注意：如果不重新实例化，config的值不会改变！应当将Config视为一次新的实例。如果要缓存这个实例，应当保证config缓存在使用的生命周期内不会改变。"""
     print(Config().api.embedding_models.base_url)
 
+

pages/label_images.py

@@ -67,8 +67,8 @@ if st.session_state.result_folder_name == '' and 'image_folder_name' in st.sessi
     st.session_state.result_folder_name = st.session_state.image_folder_name
 if 'pre_generate_result' not in st.session_state:
     st.session_state.pre_generate_result = {}
-if 'resource_pack_service' not in st.session_state:
-    st.session_state.resource_pack_service = ResourcePackService()
+# if 'resource_pack_service' not in st.session_state:
+#     st.session_state.resource_pack_service = ResourcePackService()
 
 # api
 if 'api_key' not in st.session_state:
@@ -211,7 +211,7 @@ with st.sidebar:
                 cover_path = st.session_state.cropped_cover_path if pack_cover else None
                 
                 # 创建资源包
-                pack_dir = st.session_state.resource_pack_service.create_resource_pack(
+                pack_dir = ResourcePackService().create_resource_pack(
                     name=pack_name,
                     version=pack_version,
                     author=pack_author,
@@ -224,7 +224,7 @@ with st.sidebar:
                     
                 # 生成zip文件
                 try:
-                    zip_path = st.session_state.resource_pack_service.export_resource_pack(pack_dir)
+                    zip_path = ResourcePackService().export_resource_pack(pack_dir)
                     
                     # 提供zip文件下载
                     with open(zip_path, "rb") as f:

services/embedding_service.py

@@ -18,6 +18,7 @@ import threading
 
 class EmbeddingService:
     def __init__(self):
+        self.config = Config(keep_tracked=True)
         self.api_key = Config().api.embedding_models.api_key
         self.base_url = Config().api.embedding_models.base_url
         self.local_models = {}

services/image_search.py

@@ -22,7 +22,11 @@ class ImageSearch:
         self.image_data = None
         self._try_load_cache()
 
+    def __reload_class_cache(self):
+        self.embedding_service = EmbeddingService()
+
     def _try_load_cache(self) -> None:
+        self.__reload_class_cache()
         """尝试加载缓存"""
         # 获取所有启用的资源包的缓存文件
         cache_files = self.resource_pack_manager.get_cache_files()
@@ -133,6 +137,7 @@ class ImageSearch:
         return self.image_data is not None
 
     def generate_cache(self, progress_bar) -> None:
+        self.__reload_class_cache()
         """生成缓存"""
         if self.embedding_service.mode == 'local':
             # 确保模型已加载
@@ -170,6 +175,7 @@ class ImageSearch:
             raise RuntimeError(error_message)
 
     def _generate_pack_cache(self, pack_id: str, pack_info: Dict, progress_bar) -> None:
+        self.__reload_class_cache()
         """为指定的资源包生成缓存"""
         img_dir = pack_info["path"]
         if not os.path.isabs(img_dir):
@@ -359,6 +365,7 @@ class ImageSearch:
         return np.dot(a, b)
 
     def search(self, query: str, top_k: int = 5, api_key: Optional[str] = None) -> List[str]:
+        self.__reload_class_cache()
         """语义搜索最匹配的图片"""
         if not self.has_cache():
             return []