超级Ruff

src/llm_models/model_client/base_client.py

@@ -174,7 +174,7 @@ class ClientRegistry:
                 return client_class(api_provider)
             else:
                 raise KeyError(f"'{api_provider.client_type}' 类型的 Client 未注册")
-        
+
         # 正常的缓存逻辑
         if api_provider.name not in self.client_instance_cache:
             if client_class := self.client_registry.get(api_provider.client_type):

src/llm_models/model_client/openai_client.py

@@ -531,7 +531,7 @@ class OpenaiClient(BaseClient):
             # 添加详细的错误信息以便调试
             logger.error(f"OpenAI API连接错误（嵌入模型）: {str(e)}")
             logger.error(f"错误类型: {type(e)}")
-            if hasattr(e, '__cause__') and e.__cause__:
+            if hasattr(e, "__cause__") and e.__cause__:
                 logger.error(f"底层错误: {str(e.__cause__)}")
             raise NetworkConnectionError() from e
         except APIStatusError as e:

src/llm_models/payload_content/__init__.py

@@ -1,3 +1,3 @@
 from .tool_option import ToolCall
 
-__all__ = ["ToolCall"]
+__all__ = ["ToolCall"]

src/llm_models/payload_content/resp_format.py

@@ -48,8 +48,7 @@ def _json_schema_type_check(instance) -> str | None:
     elif not isinstance(instance["name"], str) or instance["name"].strip() == "":
         return "schema的'name'字段必须是非空字符串"
     if "description" in instance and (
-        not isinstance(instance["description"], str)
-        or instance["description"].strip() == ""
+        not isinstance(instance["description"], str) or instance["description"].strip() == ""
     ):
         return "schema的'description'字段只能填入非空字符串"
     if "schema" not in instance:
@@ -101,9 +100,7 @@ def _link_definitions(schema: dict[str, Any]) -> dict[str, Any]:
             # 如果当前Schema是列表，则遍历每个元素
             for i in range(len(sub_schema)):
                 if isinstance(sub_schema[i], dict):
-                    sub_schema[i] = link_definitions_recursive(
-                        f"{path}/{str(i)}", sub_schema[i], defs
-                    )
+                    sub_schema[i] = link_definitions_recursive(f"{path}/{str(i)}", sub_schema[i], defs)
         else:
             # 否则为字典
             if "$defs" in sub_schema:
@@ -125,9 +122,7 @@ def _link_definitions(schema: dict[str, Any]) -> dict[str, Any]:
             for key, value in sub_schema.items():
                 if isinstance(value, (dict, list)):
                     # 如果当前值是字典或列表，则递归调用
-                    sub_schema[key] = link_definitions_recursive(
-                        f"{path}/{key}", value, defs
-                    )
+                    sub_schema[key] = link_definitions_recursive(f"{path}/{key}", value, defs)
 
         return sub_schema
 
@@ -163,9 +158,7 @@ class RespFormat:
     def _generate_schema_from_model(schema):
         json_schema = {
             "name": schema.__name__,
-            "schema": _remove_defs(
-                _link_definitions(_remove_title(schema.model_json_schema()))
-            ),
+            "schema": _remove_defs(_link_definitions(_remove_title(schema.model_json_schema()))),
             "strict": False,
         }
         if schema.__doc__:

src/llm_models/utils.py

@@ -155,7 +155,13 @@ class LLMUsageRecorder:
             logger.error(f"创建 LLMUsage 表失败: {str(e)}")
 
     def record_usage_to_database(
-        self, model_info: ModelInfo, model_usage: UsageRecord, user_id: str, request_type: str, endpoint: str, time_cost: float = 0.0
+        self,
+        model_info: ModelInfo,
+        model_usage: UsageRecord,
+        user_id: str,
+        request_type: str,
+        endpoint: str,
+        time_cost: float = 0.0,
     ):
         input_cost = (model_usage.prompt_tokens / 1000000) * model_info.price_in
         output_cost = (model_usage.completion_tokens / 1000000) * model_info.price_out
@@ -173,7 +179,7 @@ class LLMUsageRecorder:
                 completion_tokens=model_usage.completion_tokens or 0,
                 total_tokens=model_usage.total_tokens or 0,
                 cost=total_cost or 0.0,
-                time_cost = round(time_cost or 0.0, 3),
+                time_cost=round(time_cost or 0.0, 3),
                 status="success",
                 timestamp=datetime.now(),  # Peewee 会处理 DateTimeField
             )
@@ -186,4 +192,5 @@ class LLMUsageRecorder:
         except Exception as e:
             logger.error(f"记录token使用情况失败: {str(e)}")
 
-llm_usage_recorder = LLMUsageRecorder()
+
+llm_usage_recorder = LLMUsageRecorder()