【迁移】工具系统再完善：工具缓存、ttl支持、自动记录、长期保存、自动清理缓存、将记录与执行分离、api记录查询、时间聊天工具筛选查询...

bot.py

@@ -31,7 +31,7 @@ from src.manager.async_task_manager import async_task_manager  # noqa
 from src.config.config import global_config  # noqa
 from src.common.database.database import initialize_sql_database  # noqa
 from src.common.database.sqlalchemy_models import initialize_database as init_db  # noqa
-        
+from src.common.tool_history import wrap_tool_executor #noqa
 
 logger = get_logger("main")
 
@@ -240,6 +240,8 @@ class MaiBotMain(BaseMain):
         self.setup_timezone()
         self.check_and_confirm_eula()
         self.initialize_database()
+        # 初始化工具历史记录
+        wrap_tool_executor()  
         return self.create_main_system()
 
 

src/chat/replyer/default_generator.py

@@ -235,7 +235,7 @@ class DefaultReplyer:
 
         from src.plugin_system.core.tool_use import ToolExecutor  # 延迟导入ToolExecutor，不然会循环依赖
 
-        self.tool_executor = ToolExecutor(chat_id=self.chat_stream.stream_id, enable_cache=False)
+        self.tool_executor = ToolExecutor(chat_id=self.chat_stream.stream_id)
 
     async def _build_cross_context_block(self, current_chat_id: str, target_user_info: Optional[Dict[str, Any]]) -> str:
         """构建跨群聊上下文"""

src/chat/utils/prompt_builder.py

@@ -7,11 +7,32 @@ from contextlib import asynccontextmanager
 from typing import Dict, Any, Optional, List, Union
 
 from src.common.logger import get_logger
+from src.common.tool_history import ToolHistoryManager
 
 install(extra_lines=3)
 
 logger = get_logger("prompt_build")
 
+# 创建工具历史管理器实例
+tool_history_manager = ToolHistoryManager()
+
+def get_tool_history_prompt(message_id: Optional[str] = None) -> str:
+    """获取工具历史提示词
+    
+    Args:
+        message_id: 会话ID, 用于只获取当前会话的历史
+        
+    Returns:
+        格式化的工具历史提示词
+    """
+    from src.config.config import global_config
+
+    if not global_config.tool.history.enable_prompt_history:
+        return ""
+
+    return tool_history_manager.get_recent_history_prompt(
+        chat_id=message_id
+    )
 
 class PromptContext:
     def __init__(self):
@@ -136,8 +157,37 @@ class PromptManager:
         return prompt
 
     async def format_prompt(self, name: str, **kwargs) -> str:
+        # 获取当前提示词
         prompt = await self.get_prompt_async(name)
-        return prompt.format(**kwargs)
+        # 获取当前会话ID
+        message_id = self._context._current_context
+
+        # 获取工具历史提示词
+        tool_history = ""
+        if name in ['action_prompt', 'replyer_prompt', 'planner_prompt', 'tool_executor_prompt']:
+            tool_history = get_tool_history_prompt(message_id)
+
+        # 获取基本格式化结果
+        result = prompt.format(**kwargs)
+
+        # 如果有工具历史，插入到适当位置
+        if tool_history:
+            # 查找合适的插入点
+            # 在人格信息和身份块之后，但在主要内容之前
+            identity_end = result.find("```\n现在，你说：")
+            if identity_end == -1:
+                # 如果找不到特定标记，尝试在第一个段落后插入
+                first_double_newline = result.find("\n\n")
+                if first_double_newline != -1:
+                    # 在第一个双换行后插入
+                    result = f"{result[:first_double_newline + 2]}{tool_history}\n{result[first_double_newline + 2:]}"
+                else:
+                    # 如果找不到合适的位置，添加到开头
+                    result = f"{tool_history}\n\n{result}"
+            else:
+                # 在找到的位置插入
+                result = f"{result[:identity_end]}\n{tool_history}\n{result[identity_end:]}"
+        return result
 
 
 # 全局单例

src/common/tool_history.py

@@ -0,0 +1,385 @@
+"""工具执行历史记录模块"""
+import functools
+import time
+from datetime import datetime, timedelta
+from typing import Any, Dict, List, Optional, Union
+import json
+from pathlib import Path
+import asyncio
+
+from .logger import get_logger
+from src.config.config import global_config
+
+logger = get_logger("tool_history")
+
+class ToolHistoryManager:
+    """工具执行历史记录管理器"""
+
+    _instance = None
+    _initialized = False
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+        return cls._instance
+
+    def __init__(self):
+        if not self._initialized:
+            self._history: List[Dict[str, Any]] = []
+            self._initialized = True
+            self._data_dir = Path("data/tool_history")
+            self._data_dir.mkdir(parents=True, exist_ok=True)
+            self._history_file = self._data_dir / "tool_history.jsonl"
+            self._load_history()
+
+    def _save_history(self):
+        """保存所有历史记录到文件"""
+        try:
+            with self._history_file.open("w", encoding="utf-8") as f:
+                for record in self._history:
+                    f.write(json.dumps(record, ensure_ascii=False) + "\n")
+        except Exception as e:
+            logger.error(f"保存工具调用记录失败: {e}")
+
+    def _save_record(self, record: Dict[str, Any]):
+        """保存单条记录到文件"""
+        try:
+            with self._history_file.open("a", encoding="utf-8") as f:
+                f.write(json.dumps(record, ensure_ascii=False) + "\n")
+        except Exception as e:
+            logger.error(f"保存工具调用记录失败: {e}")
+
+    def _clean_expired_records(self):
+        """清理已过期的记录"""
+        original_count = len(self._history)
+        self._history = [record for record in self._history if record.get("ttl_count", 0) < record.get("ttl", 5)]
+        cleaned_count = original_count - len(self._history)
+
+        if cleaned_count > 0:
+            logger.info(f"清理了 {cleaned_count} 条过期的工具历史记录，剩余 {len(self._history)} 条")
+            self._save_history()
+        else:
+            logger.debug("没有需要清理的过期工具历史记录")
+
+    def record_tool_call(self, 
+                        tool_name: str,
+                        args: Dict[str, Any],
+                        result: Any,
+                        execution_time: float,
+                        status: str,
+                        chat_id: Optional[str] = None,
+                        ttl: int = 5):
+        """记录工具调用
+        
+        Args:
+            tool_name: 工具名称
+            args: 工具调用参数
+            result: 工具返回结果
+            execution_time: 执行时间（秒）
+            status: 执行状态("completed"或"error")
+            chat_id: 聊天ID，与ChatManager中的chat_id对应，用于标识群聊或私聊会话
+            ttl: 该记录的生命周期值，插入提示词多少次后删除，默认为5
+        """
+        # 检查是否启用历史记录且ttl大于0
+        if not global_config.tool.history.enable_history or ttl <= 0:
+            return
+
+        # 先清理过期记录
+        self._clean_expired_records()
+
+        try:
+            # 创建记录
+            record = {
+                "tool_name": tool_name,
+                "timestamp": datetime.now().isoformat(),
+                "arguments": self._sanitize_args(args),
+                "result": self._sanitize_result(result),
+                "execution_time": execution_time,
+                "status": status,
+                "chat_id": chat_id,
+                "ttl": ttl,
+                "ttl_count": 0
+            }
+
+            # 添加到内存中的历史记录
+            self._history.append(record)
+
+            # 保存到文件
+            self._save_record(record)
+
+            if status == "completed":
+                logger.info(f"工具 {tool_name} 调用完成，耗时：{execution_time:.2f}s")
+            else:
+                logger.error(f"工具 {tool_name} 调用失败：{result}")
+
+        except Exception as e:
+            logger.error(f"记录工具调用时发生错误: {e}")
+
+    def find_cached_result(self, tool_name: str, args: Dict[str, Any]) -> Optional[Dict[str, Any]]:
+        """查找匹配的缓存记录
+        
+        Args:
+            tool_name: 工具名称
+            args: 工具调用参数
+            
+        Returns:
+            Optional[Dict[str, Any]]: 如果找到匹配的缓存记录则返回结果，否则返回None
+        """
+        # 检查是否启用历史记录
+        if not global_config.tool.history.enable_history:
+            return None
+
+        # 清理输入参数中的敏感信息以便比较
+        sanitized_input_args = self._sanitize_args(args)
+
+        # 按时间倒序遍历历史记录
+        for record in reversed(self._history):
+            if (record["tool_name"] == tool_name and 
+                record["status"] == "completed" and
+                record["ttl_count"] < record.get("ttl", 5)):
+                # 比较参数是否匹配
+                if self._sanitize_args(record["arguments"]) == sanitized_input_args:
+                    logger.info(f"工具 {tool_name} 命中缓存记录")
+                    return record["result"]
+        return None
+
+    def _sanitize_args(self, args: Dict[str, Any]) -> Dict[str, Any]:
+        """清理参数中的敏感信息"""
+        sensitive_keys = ['api_key', 'token', 'password', 'secret']
+        sanitized = args.copy()
+
+        def _sanitize_value(value):
+            if isinstance(value, dict):
+                return {k: '***' if k.lower() in sensitive_keys else _sanitize_value(v)
+                       for k, v in value.items()}
+            return value
+
+        return {k: '***' if k.lower() in sensitive_keys else _sanitize_value(v)
+                for k, v in sanitized.items()}
+
+    def _sanitize_result(self, result: Any) -> Any:
+        """清理结果中的敏感信息"""
+        if isinstance(result, dict):
+            return self._sanitize_args(result)
+        return result
+
+    def _load_history(self):
+        """加载历史记录文件"""
+        try:
+            if self._history_file.exists():
+                self._history = []
+                with self._history_file.open("r", encoding="utf-8") as f:
+                    for line in f:
+                        try:
+                            record = json.loads(line)
+                            if record.get("ttl_count", 0) < record.get("ttl", 5):  # 只加载未过期的记录
+                                self._history.append(record)
+                        except json.JSONDecodeError:
+                            continue
+                logger.info(f"成功加载了 {len(self._history)} 条历史记录")
+        except Exception as e:
+            logger.error(f"加载历史记录失败: {e}")
+
+    def query_history(self,
+                     tool_names: Optional[List[str]] = None,
+                     start_time: Optional[Union[datetime, str]] = None,
+                     end_time: Optional[Union[datetime, str]] = None,
+                     chat_id: Optional[str] = None,
+                     limit: Optional[int] = None,
+                     status: Optional[str] = None) -> List[Dict[str, Any]]:
+        """查询工具调用历史
+        
+        Args:
+            tool_names: 工具名称列表，为空则查询所有工具
+            start_time: 开始时间，可以是datetime对象或ISO格式字符串
+            end_time: 结束时间，可以是datetime对象或ISO格式字符串
+            chat_id: 聊天ID，与ChatManager中的chat_id对应，用于查询特定群聊或私聊的历史记录
+            limit: 返回记录数量限制
+            status: 执行状态筛选("completed"或"error")
+            
+        Returns:
+            符合条件的历史记录列表
+        """
+        # 先清理过期记录
+        self._clean_expired_records()
+        def _parse_time(time_str: Optional[Union[datetime, str]]) -> Optional[datetime]:
+            if isinstance(time_str, datetime):
+                return time_str
+            elif isinstance(time_str, str):
+                return datetime.fromisoformat(time_str)
+            return None
+
+        filtered_history = self._history
+
+        # 按工具名筛选
+        if tool_names:
+            filtered_history = [
+                record for record in filtered_history 
+                if record["tool_name"] in tool_names
+            ]
+
+        # 按时间范围筛选
+        start_dt = _parse_time(start_time)
+        end_dt = _parse_time(end_time)
+
+        if start_dt:
+            filtered_history = [
+                record for record in filtered_history
+                if datetime.fromisoformat(record["timestamp"]) >= start_dt
+            ]
+
+        if end_dt:
+            filtered_history = [
+                record for record in filtered_history
+                if datetime.fromisoformat(record["timestamp"]) <= end_dt
+            ]
+
+        # 按聊天ID筛选
+        if chat_id:
+            filtered_history = [
+                record for record in filtered_history
+                if record.get("chat_id") == chat_id
+            ]
+
+        # 按状态筛选
+        if status:
+            filtered_history = [
+                record for record in filtered_history
+                if record["status"] == status
+            ]
+
+        # 应用数量限制
+        if limit:
+            filtered_history = filtered_history[-limit:]
+
+        return filtered_history
+
+    def get_recent_history_prompt(self, 
+                                limit: Optional[int] = None,
+                                chat_id: Optional[str] = None) -> str:
+        """
+        获取最近工具调用历史的提示词
+        
+        Args:
+            limit: 返回的历史记录数量,如果不提供则使用配置中的max_history
+            chat_id: 会话ID，用于只获取当前会话的历史
+            
+        Returns:
+            格式化的历史记录提示词
+        """
+        # 检查是否启用历史记录
+        if not global_config.tool.history.enable_history:
+            return ""
+
+        # 使用配置中的最大历史记录数
+        if limit is None:
+            limit = global_config.tool.history.max_history
+
+        recent_history = self.query_history(
+            chat_id=chat_id,
+            limit=limit
+        )
+
+        if not recent_history:
+            return ""
+
+        prompt = "\n工具执行历史:\n"
+        needs_save = False
+        updated_history = []
+
+        for record in recent_history:
+            # 增加ttl计数
+            record["ttl_count"] = record.get("ttl_count", 0) + 1
+            needs_save = True
+
+            # 如果未超过ttl，则添加到提示词中
+            if record["ttl_count"] < record.get("ttl", 5):
+                # 提取结果中的name和content
+                result = record['result']
+                if isinstance(result, dict):
+                    name = result.get('name', record['tool_name'])
+                    content = result.get('content', str(result))
+                else:
+                    name = record['tool_name']
+                    content = str(result)
+
+                # 格式化内容，去除多余空白和换行
+                content = content.strip().replace('\n', ' ')
+
+                # 如果内容太长则截断
+                if len(content) > 200:
+                    content = content[:200] + "..."
+
+                prompt += f"{name}: \n{content}\n\n"
+                updated_history.append(record)
+
+        # 更新历史记录并保存
+        if needs_save:
+            self._history = updated_history
+            self._save_history()
+
+        return prompt
+
+    def clear_history(self):
+        """清除历史记录"""
+        self._history.clear()
+        self._save_history()
+        logger.info("工具调用历史记录已清除")
+
+
+def wrap_tool_executor():
+    """
+    包装工具执行器以添加历史记录功能
+    这个函数应该在系统启动时被调用一次
+    """
+    from src.plugin_system.core.tool_use import ToolExecutor
+    original_execute = ToolExecutor.execute_tool_call
+    history_manager = ToolHistoryManager()
+
+    async def wrapped_execute_tool_call(self, tool_call, tool_instance=None):
+        start_time = time.time()
+
+        # 首先检查缓存
+        if cached_result := history_manager.find_cached_result(tool_call.func_name, tool_call.args):
+            logger.info(f"{self.log_prefix}使用缓存结果，跳过工具 {tool_call.func_name} 执行")
+            return cached_result
+
+        try:
+            result = await original_execute(self, tool_call, tool_instance)
+            execution_time = time.time() - start_time
+
+            # 获取工具的ttl值
+            ttl = getattr(tool_instance, 'history_ttl', 5) if tool_instance else 5
+
+            # 记录成功的调用
+            history_manager.record_tool_call(
+                tool_name=tool_call.func_name,
+                args=tool_call.args,
+                result=result,
+                execution_time=execution_time,
+                status="completed",
+                chat_id=getattr(self, 'chat_id', None),
+                ttl=ttl
+            )
+
+            return result
+
+        except Exception as e:
+            execution_time = time.time() - start_time
+            # 获取工具的ttl值
+            ttl = getattr(tool_instance, 'history_ttl', 5) if tool_instance else 5
+
+            # 记录失败的调用
+            history_manager.record_tool_call(
+                tool_name=tool_call.func_name,
+                args=tool_call.args,
+                result=str(e),
+                execution_time=execution_time,
+                status="error",
+                chat_id=getattr(self, 'chat_id', None),
+                ttl=ttl
+            )
+            raise
+
+    # 替换原始方法
+    ToolExecutor.execute_tool_call = wrapped_execute_tool_call

src/config/official_configs.py

@@ -396,13 +396,29 @@ class ExpressionConfig(ValidatedConfigBase):
         return None
 
 
+class ToolHistoryConfig(ValidatedConfigBase):
+    """工具历史记录配置类"""
+
+    enable_history: bool = True
+    """是否启用工具历史记录"""
+
+    enable_prompt_history: bool = True
+    """是否在提示词中加入工具历史记录"""
+
+    max_history: int = 5
+    """注入到提示词中的最大工具历史记录数量"""
+
+    data_dir: str = "data/tool_history"
+    """历史记录保存目录"""
+
 
 class ToolConfig(ValidatedConfigBase):
     """工具配置类"""
 
     enable_tool: bool = Field(default=False, description="启用工具")
 
-
+    history: ToolHistoryConfig = Field(default_factory=ToolHistoryConfig)
+    """工具历史记录配置"""
 
 class VoiceConfig(ValidatedConfigBase):
     """语音识别配置类"""

src/plugin_system/apis/tool_api.py

@@ -1,7 +1,9 @@
-from typing import Optional, Type
+from typing import Any, Dict, List, Optional, Type, Union
+from datetime import datetime
 from src.plugin_system.base.base_tool import BaseTool
 from src.plugin_system.base.component_types import ComponentType
 
+from src.common.tool_history import ToolHistoryManager
 from src.common.logger import get_logger
 
 logger = get_logger("tool_api")
@@ -32,3 +34,109 @@ def get_llm_available_tool_definitions():
 
     llm_available_tools = component_registry.get_llm_available_tools()
     return [(name, tool_class.get_tool_definition()) for name, tool_class in llm_available_tools.items()]
+
+def get_tool_history(
+    tool_names: Optional[List[str]] = None,
+    start_time: Optional[Union[datetime, str]] = None,
+    end_time: Optional[Union[datetime, str]] = None,
+    chat_id: Optional[str] = None,
+    limit: Optional[int] = None,
+    status: Optional[str] = None
+) -> List[Dict[str, Any]]:
+    """
+    获取工具调用历史记录
+    
+    Args:
+        tool_names: 工具名称列表，为空则查询所有工具
+        start_time: 开始时间，可以是datetime对象或ISO格式字符串
+        end_time: 结束时间，可以是datetime对象或ISO格式字符串
+        chat_id: 会话ID，用于筛选特定会话的调用
+        limit: 返回记录数量限制
+        status: 执行状态筛选("completed"或"error")
+        
+    Returns:
+        List[Dict]: 工具调用记录列表，每条记录包含以下字段：
+            - tool_name: 工具名称
+            - timestamp: 调用时间
+            - arguments: 调用参数
+            - result: 调用结果
+            - execution_time: 执行时间
+            - status: 执行状态
+            - chat_id: 会话ID
+    """
+    history_manager = ToolHistoryManager()
+    return history_manager.query_history(
+        tool_names=tool_names,
+        start_time=start_time,
+        end_time=end_time,
+        chat_id=chat_id,
+        limit=limit,
+        status=status
+    )
+
+
+def get_tool_history_text(
+    tool_names: Optional[List[str]] = None,
+    start_time: Optional[Union[datetime, str]] = None,
+    end_time: Optional[Union[datetime, str]] = None,
+    chat_id: Optional[str] = None,
+    limit: Optional[int] = None,
+    status: Optional[str] = None
+) -> str:
+    """
+    获取工具调用历史记录的文本格式
+    
+    Args:
+        tool_names: 工具名称列表，为空则查询所有工具
+        start_time: 开始时间，可以是datetime对象或ISO格式字符串
+        end_time: 结束时间，可以是datetime对象或ISO格式字符串
+        chat_id: 会话ID，用于筛选特定会话的调用
+        limit: 返回记录数量限制
+        status: 执行状态筛选("completed"或"error")
+        
+    Returns:
+        str: 格式化的工具调用历史记录文本
+    """
+    history = get_tool_history(
+        tool_names=tool_names,
+        start_time=start_time,
+        end_time=end_time,
+        chat_id=chat_id,
+        limit=limit,
+        status=status
+    )
+
+    if not history:
+        return "没有找到工具调用记录"
+
+    text = "工具调用历史记录:\n"
+    for record in history:
+        # 提取结果中的name和content
+        result = record['result']
+        if isinstance(result, dict):
+            name = result.get('name', record['tool_name'])
+            content = result.get('content', str(result))
+        else:
+            name = record['tool_name']
+            content = str(result)
+
+        # 格式化内容
+        content = content.strip().replace('\n', ' ')
+        if len(content) > 200:
+            content = content[:200] + "..."
+
+        # 格式化时间
+        timestamp = datetime.fromisoformat(record['timestamp']).strftime("%Y-%m-%d %H:%M:%S")
+
+        text += f"[{timestamp}] {name}\n"
+        text += f"结果: {content}\n\n"
+
+    return text
+
+
+def clear_tool_history() -> None:
+    """
+    清除所有工具调用历史记录
+    """
+    history_manager = ToolHistoryManager()
+    history_manager.clear_history()

src/plugin_system/base/base_tool.py

@@ -28,6 +28,8 @@ class BaseTool(ABC):
     """
     available_for_llm: bool = False
     """是否可供LLM使用"""
+    history_ttl: int = 5
+    """工具调用历史记录的TTL值，默认为5。设为0表示不记录历史"""
 
     def __init__(self, plugin_config: Optional[dict] = None):
         self.plugin_config = plugin_config or {}  # 直接存储插件配置字典

src/plugin_system/core/tool_use.py

@@ -40,13 +40,12 @@ class ToolExecutor:
     可以直接输入聊天消息内容，自动判断并执行相应的工具，返回结构化的工具执行结果。
     """
 
-    def __init__(self, chat_id: str, enable_cache: bool = False, cache_ttl: int = 3):
+    def __init__(self, chat_id: str):
         """初始化工具执行器
 
         Args:
             executor_id: 执行器标识符，用于日志记录
-            enable_cache: 是否启用缓存机制
+            chat_id: 聊天标识符，用于日志记录
-            cache_ttl: 缓存生存时间（周期数）
         """
         self.chat_id = chat_id
         self.chat_stream = get_chat_manager().get_stream(self.chat_id)
@@ -54,12 +53,7 @@ class ToolExecutor:
 
         self.llm_model = LLMRequest(model_set=model_config.model_task_config.tool_use, request_type="tool_executor")
 
-        # 缓存配置
+        logger.info(f"{self.log_prefix}工具执行器初始化完成")
-        self.enable_cache = enable_cache
-        self.cache_ttl = cache_ttl
-        self.tool_cache = {}  # 格式: {cache_key: {"result": result, "ttl": ttl, "timestamp": timestamp}}
-
-        logger.info(f"{self.log_prefix}工具执行器初始化完成，缓存{'启用' if enable_cache else '禁用'}，TTL={cache_ttl}")
 
     async def execute_from_chat_message(
         self, target_message: str, chat_history: str, sender: str, return_details: bool = False
@@ -77,18 +71,6 @@ class ToolExecutor:
             如果return_details为True: Tuple[List[Dict], List[str], str] - (结果列表, 使用的工具, 提示词)
         """
 
-        # 首先检查缓存
-        cache_key = self._generate_cache_key(target_message, chat_history, sender)
-        if cached_result := self._get_from_cache(cache_key):
-            logger.info(f"{self.log_prefix}使用缓存结果，跳过工具执行")
-            if not return_details:
-                return cached_result, [], ""
-
-            # 从缓存结果中提取工具名称
-            used_tools = [result.get("tool_name", "unknown") for result in cached_result]
-            return cached_result, used_tools, ""
-
-        # 缓存未命中，执行工具调用
         # 获取可用工具
         tools = self._get_tool_definitions()
 
@@ -117,10 +99,6 @@ class ToolExecutor:
         # 执行工具调用
         tool_results, used_tools = await self.execute_tool_calls(tool_calls)
 
-        # 缓存结果
-        if tool_results:
-            self._set_cache(cache_key, tool_results)
-
         if used_tools:
             logger.info(f"{self.log_prefix}工具执行完成，共执行{len(used_tools)}个工具: {used_tools}")
 
@@ -151,9 +129,19 @@ class ToolExecutor:
             return [], []
         
         # 提取tool_calls中的函数名称
-        func_names = [call.func_name for call in tool_calls if call.func_name]
+        func_names = []
+        for call in tool_calls:
+            try:
+                if hasattr(call, 'func_name'):
+                    func_names.append(call.func_name)
+            except Exception as e:
+                logger.error(f"{self.log_prefix}获取工具名称失败: {e}")
+                continue
         
+        if func_names:
             logger.info(f"{self.log_prefix}开始执行工具调用: {func_names}")
+        else:
+            logger.warning(f"{self.log_prefix}未找到有效的工具调用")
 
         # 执行每个工具调用
         for tool_call in tool_calls:
@@ -216,88 +204,24 @@ class ToolExecutor:
                 logger.warning(f"未知工具名称: {function_name}")
                 return None
 
-            # 执行工具
+            # 执行工具并记录日志
+            logger.debug(f"{self.log_prefix}执行工具 {function_name}，参数: {function_args}")
             result = await tool_instance.execute(function_args)
             if result:
+                logger.debug(f"{self.log_prefix}工具 {function_name} 执行成功，结果: {result}")
                 return {
                     "tool_call_id": tool_call.call_id,
                     "role": "tool",
                     "name": function_name,
                     "type": "function",
-                    "content": result["content"],
+                    "content": result.get("content", "")
                 }
+            logger.warning(f"{self.log_prefix}工具 {function_name} 返回空结果")
             return None
         except Exception as e:
             logger.error(f"执行工具调用时发生错误: {str(e)}")
             raise e
 
-    def _generate_cache_key(self, target_message: str, chat_history: str, sender: str) -> str:
-        """生成缓存键
-
-        Args:
-            target_message: 目标消息内容
-            chat_history: 聊天历史
-            sender: 发送者
-
-        Returns:
-            str: 缓存键
-        """
-        import hashlib
-
-        # 使用消息内容和群聊状态生成唯一缓存键
-        content = f"{target_message}_{chat_history}_{sender}"
-        return hashlib.md5(content.encode()).hexdigest()
-
-    def _get_from_cache(self, cache_key: str) -> Optional[List[Dict]]:
-        """从缓存获取结果
-
-        Args:
-            cache_key: 缓存键
-
-        Returns:
-            Optional[List[Dict]]: 缓存的结果，如果不存在或过期则返回None
-        """
-        if not self.enable_cache or cache_key not in self.tool_cache:
-            return None
-
-        cache_item = self.tool_cache[cache_key]
-        if cache_item["ttl"] <= 0:
-            # 缓存过期，删除
-            del self.tool_cache[cache_key]
-            logger.debug(f"{self.log_prefix}缓存过期，删除缓存键: {cache_key}")
-            return None
-
-        # 减少TTL
-        cache_item["ttl"] -= 1
-        logger.debug(f"{self.log_prefix}使用缓存结果，剩余TTL: {cache_item['ttl']}")
-        return cache_item["result"]
-
-    def _set_cache(self, cache_key: str, result: List[Dict]):
-        """设置缓存
-
-        Args:
-            cache_key: 缓存键
-            result: 要缓存的结果
-        """
-        if not self.enable_cache:
-            return
-
-        self.tool_cache[cache_key] = {"result": result, "ttl": self.cache_ttl, "timestamp": time.time()}
-        logger.debug(f"{self.log_prefix}设置缓存，TTL: {self.cache_ttl}")
-
-    def _cleanup_expired_cache(self):
-        """清理过期的缓存"""
-        if not self.enable_cache:
-            return
-
-        expired_keys = []
-        expired_keys.extend(cache_key for cache_key, cache_item in self.tool_cache.items() if cache_item["ttl"] <= 0)
-        for key in expired_keys:
-            del self.tool_cache[key]
-
-        if expired_keys:
-            logger.debug(f"{self.log_prefix}清理了{len(expired_keys)}个过期缓存")
-
     async def execute_specific_tool_simple(self, tool_name: str, tool_args: Dict) -> Optional[Dict]:
         """直接执行指定工具
 
@@ -336,86 +260,30 @@ class ToolExecutor:
 
         return None
 
-    def clear_cache(self):
-        """清空所有缓存"""
-        if self.enable_cache:
-            cache_count = len(self.tool_cache)
-            self.tool_cache.clear()
-            logger.info(f"{self.log_prefix}清空了{cache_count}个缓存项")
-
-    def get_cache_status(self) -> Dict:
-        """获取缓存状态信息
-
-        Returns:
-            Dict: 包含缓存统计信息的字典
-        """
-        if not self.enable_cache:
-            return {"enabled": False, "cache_count": 0}
-
-        # 清理过期缓存
-        self._cleanup_expired_cache()
-
-        total_count = len(self.tool_cache)
-        ttl_distribution = {}
-
-        for cache_item in self.tool_cache.values():
-            ttl = cache_item["ttl"]
-            ttl_distribution[ttl] = ttl_distribution.get(ttl, 0) + 1
-
-        return {
-            "enabled": True,
-            "cache_count": total_count,
-            "cache_ttl": self.cache_ttl,
-            "ttl_distribution": ttl_distribution,
-        }
-
-    def set_cache_config(self, enable_cache: Optional[bool] = None, cache_ttl: int = -1):
-        """动态修改缓存配置
-
-        Args:
-            enable_cache: 是否启用缓存
-            cache_ttl: 缓存TTL
-        """
-        if enable_cache is not None:
-            self.enable_cache = enable_cache
-            logger.info(f"{self.log_prefix}缓存状态修改为: {'启用' if enable_cache else '禁用'}")
-
-        if cache_ttl > 0:
-            self.cache_ttl = cache_ttl
-            logger.info(f"{self.log_prefix}缓存TTL修改为: {cache_ttl}")
 
 
 """
 ToolExecutor使用示例：
 
-# 1. 基础使用 - 从聊天消息执行工具（启用缓存，默认TTL=3）
+# 1. 基础使用 - 从聊天消息执行工具
-executor = ToolExecutor(executor_id="my_executor")
+executor = ToolExecutor(chat_id=my_chat_id)
 results, _, _ = await executor.execute_from_chat_message(
-    talking_message_str="今天天气怎么样？现在几点了？",
+    target_message="今天天气怎么样？现在几点了？",
-    is_group_chat=False
+    chat_history="",
+    sender="用户"
 )
 
-# 2. 禁用缓存的执行器
+# 2. 获取详细信息
-no_cache_executor = ToolExecutor(executor_id="no_cache", enable_cache=False)
-
-# 3. 自定义缓存TTL
-long_cache_executor = ToolExecutor(executor_id="long_cache", cache_ttl=10)
-
-# 4. 获取详细信息
 results, used_tools, prompt = await executor.execute_from_chat_message(
-    talking_message_str="帮我查询Python相关知识",
+    target_message="帮我查询Python相关知识",
-    is_group_chat=False,
+    chat_history="",
+    sender="用户",
     return_details=True
 )
 
-# 5. 直接执行特定工具
+# 3. 直接执行特定工具
 result = await executor.execute_specific_tool_simple(
     tool_name="get_knowledge",
     tool_args={"query": "机器学习"}
 )
-
-# 6. 缓存管理
-cache_status = executor.get_cache_status()  # 查看缓存状态
-executor.clear_cache()  # 清空缓存
-executor.set_cache_config(cache_ttl=5)  # 动态修改缓存配置
 """

template/bot_config_template.toml

@@ -1,5 +1,5 @@
 [inner]
-version = "6.5.2"
+version = "6.5.3"
 
 #----以下是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
 #如果你想要修改配置文件，请递增version的值
@@ -213,6 +213,11 @@ willing_mode = "classical" # 回复意愿模式 —— 经典模式：classical
 [tool]
 enable_tool = true # 是否在普通聊天中启用工具
 
+[tool.history]
+enable_history = true # 是否启用工具调用历史记录
+enable_prompt_history = true # 是否在提示词中加入工具历史记录
+max_history = 5 # 每个会话最多保留的历史记录数
+
 [mood]
 enable_mood = true # 是否启用情绪系统
 mood_update_threshold = 1 # 情绪更新阈值,越高，更新越慢