🤖 自动格式化代码 [skip ci]

src/do_tool/tool_can_use/get_knowledge.py

@@ -6,39 +6,35 @@ from typing import Dict, Any, Union
 
 logger = get_module_logger("get_knowledge_tool")
 
+
 class SearchKnowledgeTool(BaseTool):
     """从知识库中搜索相关信息的工具"""
+
     name = "search_knowledge"
     description = "从知识库中搜索相关信息"
     parameters = {
         "type": "object",
         "properties": {
-            "query": {
-                "type": "string",
-                "description": "搜索查询关键词"
-            },
-            "threshold": {
-                "type": "number",
-                "description": "相似度阈值，0.0到1.0之间"
-            }
+            "query": {"type": "string", "description": "搜索查询关键词"},
+            "threshold": {"type": "number", "description": "相似度阈值，0.0到1.0之间"},
         },
-        "required": ["query"]
+        "required": ["query"],
     }
-    
+
     async def execute(self, function_args: Dict[str, Any], message_txt: str = "") -> Dict[str, Any]:
         """执行知识库搜索
-        
+
         Args:
             function_args: 工具参数
             message_txt: 原始消息文本
-            
+
         Returns:
             Dict: 工具执行结果
         """
         try:
             query = function_args.get("query", message_txt)
             threshold = function_args.get("threshold", 0.4)
-            
+
             # 调用知识库搜索
             embedding = await get_embedding(query, request_type="info_retrieval")
             if embedding:
@@ -47,38 +43,29 @@ class SearchKnowledgeTool(BaseTool):
                     content = f"你知道这些知识: {knowledge_info}"
                 else:
                     content = f"你不太了解有关{query}的知识"
-                return {
-                    "name": "search_knowledge",
-                    "content": content
-                }
-            return {
-                "name": "search_knowledge",
-                "content": f"无法获取关于'{query}'的嵌入向量"
-            }
+                return {"name": "search_knowledge", "content": content}
+            return {"name": "search_knowledge", "content": f"无法获取关于'{query}'的嵌入向量"}
         except Exception as e:
             logger.error(f"知识库搜索工具执行失败: {str(e)}")
-            return {
-                "name": "search_knowledge",
-                "content": f"知识库搜索失败: {str(e)}"
-            }
-    
+            return {"name": "search_knowledge", "content": f"知识库搜索失败: {str(e)}"}
+
     def get_info_from_db(
         self, query_embedding: list, limit: int = 1, threshold: float = 0.5, return_raw: bool = False
     ) -> Union[str, list]:
         """从数据库中获取相关信息
-        
+
         Args:
             query_embedding: 查询的嵌入向量
             limit: 最大返回结果数
             threshold: 相似度阈值
             return_raw: 是否返回原始结果
-            
+
         Returns:
             Union[str, list]: 格式化的信息字符串或原始结果列表
         """
         if not query_embedding:
             return "" if not return_raw else []
-        
+
         # 使用余弦相似度计算
         pipeline = [
             {
@@ -143,5 +130,6 @@ class SearchKnowledgeTool(BaseTool):
             # 返回所有找到的内容，用换行分隔
             return "\n".join(str(result["content"]) for result in results)
 
+
 # 注册工具
 register_tool(SearchKnowledgeTool)