Merge branch 'dev' of https://github.com/MaiM-with-u/MaiBot into dev

src/plugins/chat_module/reasoning_chat/reasoning_chat.py

@@ -19,6 +19,7 @@ from ...chat.chat_stream import chat_manager
 from ...person_info.relationship_manager import relationship_manager
 from ...chat.message_buffer import message_buffer
 from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
+from ...utils.timer_calculater import Timer
 
 # 定义日志配置
 chat_config = LogConfig(
@@ -173,12 +174,10 @@ class ReasoningChat:
         await self.storage.store_message(message, chat)
 
         # 记忆激活
-        timer1 = time.time()
-        interested_rate = await HippocampusManager.get_instance().get_activate_from_text(
-            message.processed_plain_text, fast_retrieval=True
-        )
-        timer2 = time.time()
-        timing_results["记忆激活"] = timer2 - timer1
+        with Timer("记忆激活", timing_results):
+            interested_rate = await HippocampusManager.get_instance().get_activate_from_text(
+                message.processed_plain_text, fast_retrieval=True
+            )
 
         # 查询缓冲器结果，会整合前面跳过的消息，改变processed_plain_text
         buffer_result = await message_buffer.query_buffer_result(message)
@@ -228,10 +227,8 @@ class ReasoningChat:
             await willing_manager.before_generate_reply_handle(message.message_info.message_id)
 
             # 创建思考消息
-            timer1 = time.time()
-            thinking_id = await self._create_thinking_message(message, chat, userinfo, messageinfo)
-            timer2 = time.time()
-            timing_results["创建思考消息"] = timer2 - timer1
+            with Timer("创建思考消息", timing_results):
+                thinking_id = await self._create_thinking_message(message, chat, userinfo, messageinfo)
 
             logger.debug(f"创建捕捉器，thinking_id:{thinking_id}")
 
@@ -239,11 +236,9 @@ class ReasoningChat:
             info_catcher.catch_decide_to_response(message)
 
             # 生成回复
-            timer1 = time.time()
             try:
-                response_set = await self.gpt.generate_response(message, thinking_id)
-                timer2 = time.time()
-                timing_results["生成回复"] = timer2 - timer1
+                with Timer("生成回复", timing_results):
+                    response_set = await self.gpt.generate_response(message, thinking_id)
 
                 info_catcher.catch_after_generate_response(timing_results["生成回复"])
             except Exception as e:
@@ -255,26 +250,20 @@ class ReasoningChat:
                 return
 
             # 发送消息
-            timer1 = time.time()
-            first_bot_msg = await self._send_response_messages(message, chat, response_set, thinking_id)
-            timer2 = time.time()
-            timing_results["发送消息"] = timer2 - timer1
+            with Timer("发送消息", timing_results):
+                first_bot_msg = await self._send_response_messages(message, chat, response_set, thinking_id)
 
             info_catcher.catch_after_response(timing_results["发送消息"], response_set, first_bot_msg)
 
             info_catcher.done_catch()
 
             # 处理表情包
-            timer1 = time.time()
-            await self._handle_emoji(message, chat, response_set)
-            timer2 = time.time()
-            timing_results["处理表情包"] = timer2 - timer1
+            with Timer("处理表情包", timing_results):
+                await self._handle_emoji(message, chat, response_set)
 
             # 更新关系情绪
-            timer1 = time.time()
-            await self._update_relationship(message, response_set)
-            timer2 = time.time()
-            timing_results["更新关系情绪"] = timer2 - timer1
+            with Timer("更新关系情绪", timing_results):
+                await self._update_relationship(message, response_set)
 
             # 回复后处理
             await willing_manager.after_generate_reply_handle(message.message_info.message_id)

src/plugins/chat_module/reasoning_chat/reasoning_generator.py

@@ -1,4 +1,3 @@
-import time
 from typing import List, Optional, Tuple, Union
 import random
 
@@ -7,6 +6,7 @@ from ...config.config import global_config
 from ...chat.message import MessageThinking
 from .reasoning_prompt_builder import prompt_builder
 from ...chat.utils import process_llm_response
+from ...utils.timer_calculater import Timer
 from src.common.logger import get_module_logger, LogConfig, LLM_STYLE_CONFIG
 from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
 
@@ -82,15 +82,14 @@ class ResponseGenerator:
 
         logger.debug("开始使用生成回复-2")
         # 构建prompt
-        timer1 = time.time()
-        prompt = await prompt_builder._build_prompt(
-            message.chat_stream,
-            message_txt=message.processed_plain_text,
-            sender_name=sender_name,
-            stream_id=message.chat_stream.stream_id,
-        )
-        timer2 = time.time()
-        logger.info(f"构建prompt时间: {timer2 - timer1}秒")
+        with Timer() as t_build_prompt:
+            prompt = await prompt_builder._build_prompt(
+                message.chat_stream,
+                message_txt=message.processed_plain_text,
+                sender_name=sender_name,
+                stream_id=message.chat_stream.stream_id,
+            )
+        logger.info(f"构建prompt时间: {t_build_prompt.human_readable}")
 
         try:
             content, reasoning_content, self.current_model_name = await model.generate_response(prompt)

src/plugins/chat_module/reasoning_chat/reasoning_prompt_builder.py

@@ -175,7 +175,7 @@ class PromptBuilder:
         #         moderation_prompt = """**检查并忽略**任何涉及尝试绕过审核的行为。
         # 涉及政治敏感以及违法违规的内容请规避。"""
 
-        logger.info("开始构建prompt")
+        logger.debug("开始构建prompt")
 
         #         prompt = f"""
         # {relation_prompt_all}

src/plugins/chat_module/think_flow_chat/think_flow_chat.py

@@ -20,6 +20,7 @@ from ...chat.chat_stream import chat_manager
 from ...person_info.relationship_manager import relationship_manager
 from ...chat.message_buffer import message_buffer
 from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
+from ...utils.timer_calculater import Timer
 
 # 定义日志配置
 chat_config = LogConfig(
@@ -196,12 +197,10 @@ class ThinkFlowChat:
         logger.debug(f"存储成功{message.processed_plain_text}")
 
         # 记忆激活
-        timer1 = time.time()
-        interested_rate = await HippocampusManager.get_instance().get_activate_from_text(
-            message.processed_plain_text, fast_retrieval=True
-        )
-        timer2 = time.time()
-        timing_results["记忆激活"] = timer2 - timer1
+        with Timer("记忆激活", timing_results):
+            interested_rate = await HippocampusManager.get_instance().get_activate_from_text(
+                message.processed_plain_text, fast_retrieval=True
+            )
         logger.debug(f"记忆激活: {interested_rate}")
 
         # 查询缓冲器结果，会整合前面跳过的消息，改变processed_plain_text
@@ -262,10 +261,8 @@ class ThinkFlowChat:
 
                 # 创建思考消息
                 try:
-                    timer1 = time.time()
-                    thinking_id = await self._create_thinking_message(message, chat, userinfo, messageinfo)
-                    timer2 = time.time()
-                    timing_results["创建思考消息"] = timer2 - timer1
+                    with Timer("创建思考消息", timing_results):
+                        thinking_id = await self._create_thinking_message(message, chat, userinfo, messageinfo)
                 except Exception as e:
                     logger.error(f"心流创建思考消息失败: {e}")
 
@@ -276,10 +273,8 @@ class ThinkFlowChat:
 
                 try:
                     # 观察
-                    timer1 = time.time()
-                    await heartflow.get_subheartflow(chat.stream_id).do_observe()
-                    timer2 = time.time()
-                    timing_results["观察"] = timer2 - timer1
+                    with Timer("观察", timing_results):
+                        await heartflow.get_subheartflow(chat.stream_id).do_observe()
                 except Exception as e:
                     logger.error(f"心流观察失败: {e}")
 
@@ -287,24 +282,22 @@ class ThinkFlowChat:
 
                 # 思考前脑内状态
                 try:
-                    timer1 = time.time()
-                    current_mind, past_mind = await heartflow.get_subheartflow(chat.stream_id).do_thinking_before_reply(
-                        message_txt=message.processed_plain_text,
-                        sender_name=message.message_info.user_info.user_nickname,
-                        chat_stream=chat,
-                    )
-                    timer2 = time.time()
-                    timing_results["思考前脑内状态"] = timer2 - timer1
+                    with Timer("思考前脑内状态", timing_results):
+                        current_mind, past_mind = await heartflow.get_subheartflow(
+                            chat.stream_id
+                        ).do_thinking_before_reply(
+                            message_txt=message.processed_plain_text,
+                            sender_name=message.message_info.user_info.user_nickname,
+                            chat_stream=chat,
+                        )
                 except Exception as e:
                     logger.error(f"心流思考前脑内状态失败: {e}")
 
                 info_catcher.catch_afer_shf_step(timing_results["思考前脑内状态"], past_mind, current_mind)
 
                 # 生成回复
-                timer1 = time.time()
-                response_set = await self.gpt.generate_response(message, thinking_id)
-                timer2 = time.time()
-                timing_results["生成回复"] = timer2 - timer1
+                with Timer("生成回复", timing_results):
+                    response_set = await self.gpt.generate_response(message, thinking_id)
 
                 info_catcher.catch_after_generate_response(timing_results["生成回复"])
 
@@ -314,10 +307,8 @@ class ThinkFlowChat:
 
                 # 发送消息
                 try:
-                    timer1 = time.time()
-                    first_bot_msg = await self._send_response_messages(message, chat, response_set, thinking_id)
-                    timer2 = time.time()
-                    timing_results["发送消息"] = timer2 - timer1
+                    with Timer("发送消息", timing_results):
+                        first_bot_msg = await self._send_response_messages(message, chat, response_set, thinking_id)
                 except Exception as e:
                     logger.error(f"心流发送消息失败: {e}")
 
@@ -327,28 +318,22 @@ class ThinkFlowChat:
 
                 # 处理表情包
                 try:
-                    timer1 = time.time()
-                    await self._handle_emoji(message, chat, response_set)
-                    timer2 = time.time()
-                    timing_results["处理表情包"] = timer2 - timer1
+                    with Timer("处理表情包", timing_results):
+                        await self._handle_emoji(message, chat, response_set)
                 except Exception as e:
                     logger.error(f"心流处理表情包失败: {e}")
 
                 # 更新心流
                 try:
-                    timer1 = time.time()
-                    await self._update_using_response(message, response_set)
-                    timer2 = time.time()
-                    timing_results["更新心流"] = timer2 - timer1
+                    with Timer("更新心流", timing_results):
+                        await self._update_using_response(message, response_set)
                 except Exception as e:
                     logger.error(f"心流更新失败: {e}")
 
                 # 更新关系情绪
                 try:
-                    timer1 = time.time()
-                    await self._update_relationship(message, response_set)
-                    timer2 = time.time()
-                    timing_results["更新关系情绪"] = timer2 - timer1
+                    with Timer("更新关系情绪", timing_results):
+                        await self._update_relationship(message, response_set)
                 except Exception as e:
                     logger.error(f"心流更新关系情绪失败: {e}")
 

src/plugins/chat_module/think_flow_chat/think_flow_generator.py

@@ -1,4 +1,3 @@
-import time
 from typing import List, Optional
 import random
 
@@ -10,6 +9,7 @@ from .think_flow_prompt_builder import prompt_builder
 from ...chat.utils import process_llm_response
 from src.common.logger import get_module_logger, LogConfig, LLM_STYLE_CONFIG
 from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
+from ...utils.timer_calculater import Timer
 
 from src.plugins.moods.moods import MoodManager
 
@@ -44,41 +44,40 @@ class ResponseGenerator:
 
         arousal_multiplier = MoodManager.get_instance().get_arousal_multiplier()
 
-        time1 = time.time()
-
-        checked = False
-        if random.random() > 0:
+        with Timer() as t_generate_response:
             checked = False
-            current_model = self.model_normal
-            current_model.temperature = 0.3 * arousal_multiplier  # 激活度越高，温度越高
-            model_response = await self._generate_response_with_model(
-                message, current_model, thinking_id, mode="normal"
-            )
+            if random.random() > 0:
+                checked = False
+                current_model = self.model_normal
+                current_model.temperature = 0.3 * arousal_multiplier  # 激活度越高，温度越高
+                model_response = await self._generate_response_with_model(
+                    message, current_model, thinking_id, mode="normal"
+                )
 
-            model_checked_response = model_response
-        else:
-            checked = True
-            current_model = self.model_normal
-            current_model.temperature = 0.3 * arousal_multiplier  # 激活度越高，温度越高
-            print(f"生成{message.processed_plain_text}回复温度是：{current_model.temperature}")
-            model_response = await self._generate_response_with_model(
-                message, current_model, thinking_id, mode="simple"
-            )
+                model_checked_response = model_response
+            else:
+                checked = True
+                current_model = self.model_normal
+                current_model.temperature = 0.3 * arousal_multiplier  # 激活度越高，温度越高
+                print(f"生成{message.processed_plain_text}回复温度是：{current_model.temperature}")
+                model_response = await self._generate_response_with_model(
+                    message, current_model, thinking_id, mode="simple"
+                )
 
-            current_model.temperature = 0.3
-            model_checked_response = await self._check_response_with_model(
-                message, model_response, current_model, thinking_id
-            )
-
-        time2 = time.time()
+                current_model.temperature = 0.3
+                model_checked_response = await self._check_response_with_model(
+                    message, model_response, current_model, thinking_id
+                )
 
         if model_response:
             if checked:
                 logger.info(
-                    f"{global_config.BOT_NICKNAME}的回复是：{model_response}，思忖后，回复是：{model_checked_response},生成回复时间: {time2 - time1}秒"
+                    f"{global_config.BOT_NICKNAME}的回复是：{model_response}，思忖后，回复是：{model_checked_response},生成回复时间: {t_generate_response.human_readable}"
                 )
             else:
-                logger.info(f"{global_config.BOT_NICKNAME}的回复是：{model_response},生成回复时间: {time2 - time1}秒")
+                logger.info(
+                    f"{global_config.BOT_NICKNAME}的回复是：{model_response},生成回复时间: {t_generate_response.human_readable}"
+                )
 
             model_processed_response = await self._process_response(model_checked_response)
 
@@ -105,23 +104,22 @@ class ResponseGenerator:
             sender_name = f"用户({message.chat_stream.user_info.user_id})"
 
         # 构建prompt
-        timer1 = time.time()
-        if mode == "normal":
-            prompt = await prompt_builder._build_prompt(
-                message.chat_stream,
-                message_txt=message.processed_plain_text,
-                sender_name=sender_name,
-                stream_id=message.chat_stream.stream_id,
-            )
-        elif mode == "simple":
-            prompt = await prompt_builder._build_prompt_simple(
-                message.chat_stream,
-                message_txt=message.processed_plain_text,
-                sender_name=sender_name,
-                stream_id=message.chat_stream.stream_id,
-            )
-        timer2 = time.time()
-        logger.info(f"构建{mode}prompt时间: {timer2 - timer1}秒")
+        with Timer() as t_build_prompt:
+            if mode == "normal":
+                prompt = await prompt_builder._build_prompt(
+                    message.chat_stream,
+                    message_txt=message.processed_plain_text,
+                    sender_name=sender_name,
+                    stream_id=message.chat_stream.stream_id,
+                )
+            elif mode == "simple":
+                prompt = await prompt_builder._build_prompt_simple(
+                    message.chat_stream,
+                    message_txt=message.processed_plain_text,
+                    sender_name=sender_name,
+                    stream_id=message.chat_stream.stream_id,
+                )
+        logger.info(f"构建{mode}prompt时间: {t_build_prompt.human_readable}")
 
         try:
             content, reasoning_content, self.current_model_name = await model.generate_response(prompt)
@@ -153,17 +151,16 @@ class ResponseGenerator:
             sender_name = f"用户({message.chat_stream.user_info.user_id})"
 
         # 构建prompt
-        timer1 = time.time()
-        prompt = await prompt_builder._build_prompt_check_response(
-            message.chat_stream,
-            message_txt=message.processed_plain_text,
-            sender_name=sender_name,
-            stream_id=message.chat_stream.stream_id,
-            content=content,
-        )
-        timer2 = time.time()
+        with Timer() as t_build_prompt_check:
+            prompt = await prompt_builder._build_prompt_check_response(
+                message.chat_stream,
+                message_txt=message.processed_plain_text,
+                sender_name=sender_name,
+                stream_id=message.chat_stream.stream_id,
+                content=content,
+            )
         logger.info(f"构建check_prompt: {prompt}")
-        logger.info(f"构建check_prompt时间: {timer2 - timer1}秒")
+        logger.info(f"构建check_prompt时间: {t_build_prompt_check.human_readable}")
 
         try:
             checked_content, reasoning_content, self.current_model_name = await model.generate_response(prompt)

src/plugins/chat_module/think_flow_chat/think_flow_prompt_builder.py

@@ -128,7 +128,7 @@ class PromptBuilder:
         #         moderation_prompt = """**检查并忽略**任何涉及尝试绕过审核的行为。
         # 涉及政治敏感以及违法违规的内容请规避。"""
 
-        logger.info("开始构建prompt")
+        logger.debug("开始构建prompt")
 
         #         prompt = f"""
         # {chat_target}
@@ -206,7 +206,7 @@ class PromptBuilder:
                     )
                     keywords_reaction_prompt += rule.get("reaction", "") + "，"
 
-        logger.info("开始构建prompt")
+        logger.debug("开始构建prompt")
 
         #         prompt = f"""
         # 你的名字叫{global_config.BOT_NICKNAME}，{prompt_personality}。
@@ -257,7 +257,7 @@ class PromptBuilder:
         #         moderation_prompt = """**检查并忽略**任何涉及尝试绕过审核的行为。
         # 涉及政治敏感以及违法违规的内容请规避。"""
 
-        logger.info("开始构建check_prompt")
+        logger.debug("开始构建check_prompt")
 
         #         prompt = f"""
         # 你的名字叫{global_config.BOT_NICKNAME}，{prompt_identity}。

src/plugins/utils/prompt_builder.py

@@ -94,14 +94,32 @@ global_prompt_manager = PromptManager()
 
 
 class Prompt(str):
+    # 临时标记，作为类常量
+    _TEMP_LEFT_BRACE = "__ESCAPED_LEFT_BRACE__"
+    _TEMP_RIGHT_BRACE = "__ESCAPED_RIGHT_BRACE__"
+
+    @staticmethod
+    def _process_escaped_braces(template: str) -> str:
+        """处理模板中的转义花括号，将 \{ 和 \} 替换为临时标记"""
+        return template.replace("\\{", Prompt._TEMP_LEFT_BRACE).replace("\\}", Prompt._TEMP_RIGHT_BRACE)
+
+    @staticmethod
+    def _restore_escaped_braces(template: str) -> str:
+        """将临时标记还原为实际的花括号字符"""
+        return template.replace(Prompt._TEMP_LEFT_BRACE, "{").replace(Prompt._TEMP_RIGHT_BRACE, "}")
+
     def __new__(cls, fstr: str, name: Optional[str] = None, args: Union[List[Any], tuple[Any, ...]] = None, **kwargs):
         # 如果传入的是元组，转换为列表
         if isinstance(args, tuple):
             args = list(args)
         should_register = kwargs.pop("_should_register", True)
+
+        # 预处理模板中的转义花括号
+        processed_fstr = cls._process_escaped_braces(fstr)
+
         # 解析模板
         template_args = []
-        result = re.findall(r"\{(.*?)\}", fstr)
+        result = re.findall(r"\{(.*?)\}", processed_fstr)
         for expr in result:
             if expr and expr not in template_args:
                 template_args.append(expr)
@@ -142,8 +160,11 @@ class Prompt(str):
 
     @classmethod
     def _format_template(cls, template: str, args: List[Any] = None, kwargs: Dict[str, Any] = None) -> str:
+        # 预处理模板中的转义花括号
+        processed_template = cls._process_escaped_braces(template)
+
         template_args = []
-        result = re.findall(r"\{(.*?)\}", template)
+        result = re.findall(r"\{(.*?)\}", processed_template)
         for expr in result:
             if expr and expr not in template_args:
                 template_args.append(expr)
@@ -177,13 +198,15 @@ class Prompt(str):
 
         try:
             # 先用位置参数格式化
-
             if args:
-                template = template.format(**formatted_args)
+                processed_template = processed_template.format(**formatted_args)
             # 再用关键字参数格式化
             if kwargs:
-                template = template.format(**formatted_kwargs)
-            return template
+                processed_template = processed_template.format(**formatted_kwargs)
+
+            # 将临时标记还原为实际的花括号
+            result = cls._restore_escaped_braces(processed_template)
+            return result
         except (IndexError, KeyError) as e:
             raise ValueError(
                 f"格式化模板失败: {template}, args={formatted_args}, kwargs={formatted_kwargs} {str(e)}"
@@ -198,7 +221,7 @@ class Prompt(str):
             _should_register=False,
             **kwargs if kwargs else self._kwargs,
         )
-        # print(f"prompt build result: {ret}  name: {ret.name} ")
+        # print(f"prompt build result: {ret} name: {ret.name} ")
         return str(ret)
 
     def __str__(self) -> str:

src/plugins/utils/timer_calculater.py

@@ -0,0 +1,151 @@
+from time import perf_counter
+from functools import wraps
+from typing import Optional, Dict, Callable
+import asyncio
+
+"""
+# 更好的计时器
+
+使用形式：
+- 上下文
+- 装饰器
+- 直接实例化
+
+使用场景：
+- 使用Timer：在需要测量代码执行时间时（如性能测试、计时器工具），Timer类是更可靠、高精度的选择。
+- 使用time.time()的场景：当需要记录实际时间点（如日志、时间戳）时使用，但避免用它测量时间间隔。
+
+使用方式：
+
+【装饰器】
+time_dict = {}
+@Timer("计数", time_dict)
+def func():
+    pass
+print(time_dict)
+
+【上下文_1】
+def func():
+    with Timer() as t:
+        pass
+    print(t)
+    print(t.human_readable)
+
+【上下文_2】
+def func():
+    time_dict = {}
+    with Timer("计数", time_dict):
+        pass
+    print(time_dict)
+
+【直接实例化】
+a = Timer()
+print(a)         # 直接输出当前 perf_counter 值
+
+参数：
+- name：计时器的名字，默认为 None
+- storage：计时器结果存储字典，默认为 None
+- auto_unit：自动选择单位（毫秒或秒），默认为 True（自动根据时间切换毫秒或秒）
+- do_type_check：是否进行类型检查，默认为 False（不进行类型检查）
+    
+属性：human_readable
+
+自定义错误：TimerTypeError
+"""
+
+
+class TimerTypeError(TypeError):
+    """自定义类型错误"""
+
+    __slots__ = ()
+
+    def __init__(self, param, expected_type, actual_type):
+        super().__init__(f"参数 '{param}' 类型错误，期望 {expected_type}，实际得到 {actual_type.__name__}")
+
+
+class Timer:
+    """
+    Timer 支持三种模式：
+      1. 装饰器模式：用于测量函数/协程运行时间
+      2. 上下文管理器模式：用于 with 语句块内部计时
+      3. 直接实例化：如果不调用 __enter__，打印对象时将显示当前 perf_counter 的值
+    """
+
+    __slots__ = ("name", "storage", "elapsed", "auto_unit", "start")
+
+    def __init__(
+        self,
+        name: Optional[str] = None,
+        storage: Optional[Dict[str, float]] = None,
+        auto_unit: bool = True,
+        do_type_check: bool = False,
+    ):
+        if do_type_check:
+            self._validate_types(name, storage)
+
+        self.name = name
+        self.storage = storage
+        self.elapsed = None
+
+        self.auto_unit = auto_unit
+        self.start = None
+
+    def _validate_types(self, name, storage):
+        """类型检查"""
+        if name is not None and not isinstance(name, str):
+            raise TimerTypeError("name", "Optional[str]", type(name))
+
+        if storage is not None and not isinstance(storage, dict):
+            raise TimerTypeError("storage", "Optional[dict]", type(storage))
+
+    def __call__(self, func: Optional[Callable] = None) -> Callable:
+        """装饰器模式"""
+        if func is None:
+            return lambda f: Timer(name=self.name or f.__name__, storage=self.storage, auto_unit=self.auto_unit)(f)
+
+        @wraps(func)
+        async def async_wrapper(*args, **kwargs):
+            with self:
+                return await func(*args, **kwargs)
+
+        @wraps(func)
+        def sync_wrapper(*args, **kwargs):
+            with self:
+                return func(*args, **kwargs)
+
+        wrapper = async_wrapper if asyncio.iscoroutinefunction(func) else sync_wrapper
+        wrapper.__timer__ = self  # 保留计时器引用
+        return wrapper
+
+    def __enter__(self):
+        """上下文管理器入口"""
+        self.start = perf_counter()
+        return self
+
+    def __exit__(self, *args):
+        self.elapsed = perf_counter() - self.start
+        self._record_time()
+        return False
+
+    def _record_time(self):
+        """记录时间"""
+        if self.storage is not None and self.name:
+            self.storage[self.name] = self.elapsed
+
+    @property
+    def human_readable(self) -> str:
+        """人类可读时间格式"""
+        if self.elapsed is None:
+            return "未计时"
+
+        if self.auto_unit:
+            return f"{self.elapsed * 1000:.2f}毫秒" if self.elapsed < 1 else f"{self.elapsed:.2f}秒"
+        return f"{self.elapsed:.4f}秒"
+
+    def __str__(self):
+        if self.start is not None:
+            if self.elapsed is None:
+                current_elapsed = perf_counter() - self.start
+                return f"<Timer {self.name or '匿名'} [计时中: {current_elapsed:.4f}秒]>"
+            return f"<Timer {self.name or '匿名'} [{self.human_readable}]>"
+        return f"{perf_counter()}"