feat(tool_system): implement declarative caching for tools

This commit refactors the tool caching system to be more robust, configurable, and easier to use. The caching logic is centralized within the `wrap_tool_executor`, removing the need for boilerplate code within individual tool implementations.

Key changes:
- Adds `enable_cache`, `cache_ttl`, and `semantic_cache_query_key` attributes to `BaseTool` for declarative cache configuration.
- Moves caching logic from a simple history-based lookup and individual tools into a unified handling process in `wrap_tool_executor`.
- The new system leverages the central `tool_cache` manager for both exact and semantic caching based on tool configuration.
- Refactors `WebSurfingTool` and `URLParserTool` to utilize the new declarative caching mechanism, simplifying their code.

src/plugins/built_in/web_search_tool/tools/url_parser.py

@@ -30,6 +30,12 @@ class URLParserTool(BaseTool):
     parameters = [
         ("urls", ToolParamType.STRING, "要理解的网站", True, None),
     ]
+
+    # --- 新的缓存配置 ---
+    enable_cache: bool = True
+    cache_ttl: int = 86400  # 缓存24小时
+    semantic_cache_query_key: str = "urls"
+    # --------------------
     
     def __init__(self, plugin_config=None):
         super().__init__(plugin_config)
@@ -42,10 +48,11 @@ class URLParserTool(BaseTool):
         if exa_api_keys is None:
             # 从插件配置文件读取
             exa_api_keys = self.get_config("exa.api_keys", [])
-        
+
         # 创建API密钥管理器
+        from typing import cast, List
         self.api_manager = create_api_key_manager_from_config(
-            exa_api_keys,
+            cast(List[str], exa_api_keys),
             lambda key: Exa(api_key=key),
             "Exa URL Parser"
         )
@@ -135,16 +142,6 @@ class URLParserTool(BaseTool):
         """
         执行URL内容提取和总结。优先使用Exa，失败后尝试本地解析。
         """
-        # 获取当前文件路径用于缓存键
-        import os
-        current_file_path = os.path.abspath(__file__)
-
-        # 检查缓存
-        cached_result = await tool_cache.get(self.name, function_args, current_file_path)
-        if cached_result:
-            logger.info(f"缓存命中: {self.name} -> {function_args}")
-            return cached_result
-            
         urls_input = function_args.get("urls")
         if not urls_input:
             return {"error": "URL列表不能为空。"}
@@ -235,8 +232,4 @@ class URLParserTool(BaseTool):
             "errors": error_messages
         }
         
-        # 保存到缓存
-        if "error" not in result:
-            await tool_cache.set(self.name, function_args, current_file_path, result)
-
         return result

src/plugins/built_in/web_search_tool/tools/web_search.py

@@ -31,6 +31,12 @@ class WebSurfingTool(BaseTool):
         ("time_range", ToolParamType.STRING, "指定搜索的时间范围，可以是 'any', 'week', 'month'。默认为 'any'。", False, ["any", "week", "month"])
     ] # type: ignore
 
+    # --- 新的缓存配置 ---
+    enable_cache: bool = True
+    cache_ttl: int = 7200  # 缓存2小时
+    semantic_cache_query_key: str = "query"
+    # --------------------
+
     def __init__(self, plugin_config=None):
         super().__init__(plugin_config)
         # 初始化搜索引擎
@@ -46,16 +52,6 @@ class WebSurfingTool(BaseTool):
         if not query:
             return {"error": "搜索查询不能为空。"}
 
-        # 获取当前文件路径用于缓存键
-        import os
-        current_file_path = os.path.abspath(__file__)
-
-        # 检查缓存
-        cached_result = await tool_cache.get(self.name, function_args, current_file_path, semantic_query=query)
-        if cached_result:
-            logger.info(f"缓存命中: {self.name} -> {function_args}")
-            return cached_result
-
         # 读取搜索配置
         enabled_engines = config_api.get_global_config("web_search.enabled_engines", ["ddg"])
         search_strategy = config_api.get_global_config("web_search.search_strategy", "single")
@@ -69,10 +65,6 @@ class WebSurfingTool(BaseTool):
             result = await self._execute_fallback_search(function_args, enabled_engines)
         else:  # single
             result = await self._execute_single_search(function_args, enabled_engines)
-        
-        # 保存到缓存
-        if "error" not in result:
-            await tool_cache.set(self.name, function_args, current_file_path, result, semantic_query=query)
             
         return result