大修LLMReq

src/llm_models/model_manager_bak.py

@@ -0,0 +1,92 @@
+import importlib
+from typing import Dict
+
+from src.config.config import model_config
+from src.config.api_ada_configs import ModuleConfig, ModelUsageArgConfig
+from src.common.logger import get_logger
+
+from .model_client import ModelRequestHandler, BaseClient
+
+logger = get_logger("模型管理器")
+
+class ModelManager:
+    # TODO: 添加读写锁，防止异步刷新配置时发生数据竞争
+
+    def __init__(
+        self,
+        config: ModuleConfig,
+    ):
+        self.config: ModuleConfig = config
+        """配置信息"""
+
+        self.api_client_map: Dict[str, BaseClient] = {}
+        """API客户端映射表"""
+        
+        self._request_handler_cache: Dict[str, ModelRequestHandler] = {}
+        """ModelRequestHandler缓存，避免重复创建"""
+
+        for provider_name, api_provider in self.config.api_providers.items():
+            # 初始化API客户端
+            try:
+                # 根据配置动态加载实现
+                client_module = importlib.import_module(
+                    f".model_client.{api_provider.client_type}_client", __package__
+                )
+                client_class = getattr(
+                    client_module, f"{api_provider.client_type.capitalize()}Client"
+                )
+                if not issubclass(client_class, BaseClient):
+                    raise TypeError(
+                        f"'{client_class.__name__}' is not a subclass of 'BaseClient'"
+                    )
+                self.api_client_map[api_provider.name] = client_class(
+                    api_provider
+                )  # 实例化，放入api_client_map
+            except ImportError as e:
+                logger.error(f"Failed to import client module: {e}")
+                raise ImportError(
+                    f"Failed to import client module for '{provider_name}': {e}"
+                ) from e
+
+    def __getitem__(self, task_name: str) -> ModelRequestHandler:
+        """
+        获取任务所需的模型客户端（封装）
+        使用缓存机制避免重复创建ModelRequestHandler
+        :param task_name: 任务名称
+        :return: 模型客户端
+        """
+        if task_name not in self.config.task_model_arg_map:
+            raise KeyError(f"'{task_name}' not registered in ModelManager")
+
+        # 检查缓存中是否已存在
+        if task_name in self._request_handler_cache:
+            logger.debug(f"🚀 [性能优化] 从缓存获取ModelRequestHandler: {task_name}")
+            return self._request_handler_cache[task_name]
+
+        # 创建新的ModelRequestHandler并缓存
+        logger.debug(f"🔧 [性能优化] 创建并缓存ModelRequestHandler: {task_name}")
+        handler = ModelRequestHandler(
+            task_name=task_name,
+            config=self.config,
+            api_client_map=self.api_client_map,
+        )
+        self._request_handler_cache[task_name] = handler
+        return handler
+
+    def __setitem__(self, task_name: str, value: ModelUsageArgConfig):
+        """
+        注册任务的模型使用配置
+        :param task_name: 任务名称
+        :param value: 模型使用配置
+        """
+        self.config.task_model_arg_map[task_name] = value
+
+    def __contains__(self, task_name: str):
+        """
+        判断任务是否已注册
+        :param task_name: 任务名称
+        :return: 是否在模型列表中
+        """
+        return task_name in self.config.task_model_arg_map
+
+