diff --git a/.gitignore b/.gitignore index 9e1b96811..a8c972ab4 100644 --- a/.gitignore +++ b/.gitignore @@ -35,7 +35,6 @@ config/bot_config.toml config/bot_config.toml.bak config/lpmm_config.toml config/lpmm_config.toml.bak -src/plugins/remote/client_uuid.json （测试版）麦麦生成人格.bat （临时版）麦麦开始学习.bat src/plugins/utils/statistic.py @@ -43,7 +42,7 @@ src/plugins/utils/statistic.py __pycache__/ *.py[cod] *$py.class -llm_statistics.txt +maibot_statistics.html mongodb napcat run_dev.bat diff --git a/bot.py b/bot.py index 8cecff756..3737279d3 100644 --- a/bot.py +++ b/bot.py @@ -1,7 +1,6 @@ import asyncio import hashlib import os -import shutil import sys from pathlib import Path import time @@ -15,6 +14,8 @@ from src.common.crash_logger import install_crash_handler from src.main import MainSystem from rich.traceback import install +from src.manager.async_task_manager import async_task_manager + install(extra_lines=3) # 设置工作目录为脚本所在目录 @@ -64,38 +65,6 @@ def easter_egg(): print(rainbow_text) -def init_config(): - # 初次启动检测 - if not os.path.exists("config/bot_config.toml"): - logger.warning("检测到bot_config.toml不存在，正在从模板复制") - - # 检查config目录是否存在 - if not os.path.exists("config"): - os.makedirs("config") - logger.info("创建config目录") - - shutil.copy("template/bot_config_template.toml", "config/bot_config.toml") - logger.info("复制完成，请修改config/bot_config.toml和.env中的配置后重新启动") - if not os.path.exists("config/lpmm_config.toml"): - logger.warning("检测到lpmm_config.toml不存在，正在从模板复制") - - # 检查config目录是否存在 - if not os.path.exists("config"): - os.makedirs("config") - logger.info("创建config目录") - - shutil.copy("template/lpmm_config_template.toml", "config/lpmm_config.toml") - logger.info("复制完成，请修改config/lpmm_config.toml和.env中的配置后重新启动") - - -def init_env(): - # 检测.env文件是否存在 - if not os.path.exists(".env"): - logger.error("检测到.env文件不存在") - shutil.copy("template/template.env", "./.env") - logger.info("已从template/template.env复制创建.env，请修改配置后重新启动") - - def load_env(): # 直接加载生产环境变量配置 if os.path.exists(".env"): @@ -140,6 +109,10 @@ def scan_provider(env_config: dict): async def graceful_shutdown(): try: logger.info("正在优雅关闭麦麦...") + + # 停止所有异步任务 + await async_task_manager.stop_and_wait_all_tasks() + tasks = [t for t in asyncio.all_tasks() if t is not asyncio.current_task()] for task in tasks: task.cancel() @@ -235,9 +208,9 @@ def raw_main(): check_eula() print("检查EULA和隐私条款完成") + easter_egg() - init_config() - init_env() + load_env() env_config = {key: os.getenv(key) for key in os.environ} diff --git a/src/do_tool/not_used/change_mood.py b/src/do_tool/not_used/change_mood.py index 5dee6ac98..5d1e7f7a6 100644 --- a/src/do_tool/not_used/change_mood.py +++ b/src/do_tool/not_used/change_mood.py @@ -1,10 +1,10 @@ -from src.do_tool.tool_can_use.base_tool import BaseTool -from src.config.config import global_config -from src.common.logger_manager import get_logger -from src.plugins.moods.moods import MoodManager - from typing import Any +from src.common.logger_manager import get_logger +from src.config.config import global_config +from src.do_tool.tool_can_use.base_tool import BaseTool +from src.manager.mood_manager import mood_manager + logger = get_logger("change_mood_tool") @@ -36,7 +36,6 @@ class ChangeMoodTool(BaseTool): response_set = function_args.get("response_set") _message_processed_plain_text = function_args.get("text") - mood_manager = MoodManager.get_instance() # gpt = ResponseGenerator() if response_set is None: diff --git a/src/heart_flow/chat_state_info.py b/src/heart_flow/chat_state_info.py index 619f372fc..bda5c26c0 100644 --- a/src/heart_flow/chat_state_info.py +++ b/src/heart_flow/chat_state_info.py @@ -1,4 +1,4 @@ -from src.plugins.moods.moods import MoodManager +from src.manager.mood_manager import mood_manager import enum @@ -13,5 +13,5 @@ class ChatStateInfo: self.chat_status: ChatState = ChatState.ABSENT self.current_state_time = 120 - self.mood_manager = MoodManager() - self.mood = self.mood_manager.get_prompt() + self.mood_manager = mood_manager + self.mood = self.mood_manager.get_mood_prompt() diff --git a/src/heart_flow/mai_state_manager.py b/src/heart_flow/mai_state_manager.py index d289a94a1..3c6c19d66 100644 --- a/src/heart_flow/mai_state_manager.py +++ b/src/heart_flow/mai_state_manager.py @@ -3,7 +3,7 @@ import time import random from typing import List, Tuple, Optional from src.common.logger_manager import get_logger -from src.plugins.moods.moods import MoodManager +from src.manager.mood_manager import mood_manager from src.config.config import global_config logger = get_logger("mai_state") @@ -88,7 +88,7 @@ class MaiStateInfo: self.last_min_check_time: float = time.time() # 上次1分钟规则检查时间 # Mood management is now part of MaiStateInfo - self.mood_manager = MoodManager.get_instance() # Use singleton instance + self.mood_manager = mood_manager # Use singleton instance def update_mai_status(self, new_status: MaiState) -> bool: """ @@ -124,7 +124,7 @@ class MaiStateInfo: def get_mood_prompt(self) -> str: """获取当前的心情提示词""" # Delegate to the internal mood manager - return self.mood_manager.get_prompt() + return self.mood_manager.get_mood_prompt() def get_current_state(self) -> MaiState: """获取当前的 MaiState""" diff --git a/src/main.py b/src/main.py index be71524e2..09570a4f2 100644 --- a/src/main.py +++ b/src/main.py @@ -1,7 +1,12 @@ import asyncio import time -from .plugins.utils.statistic import LLMStatistics -from .plugins.moods.moods import MoodManager + +from maim_message import MessageServer + +from .plugins.remote.remote import TelemetryHeartBeatTask +from .manager.async_task_manager import async_task_manager +from .plugins.utils.statistic import OnlineTimeRecordTask, StatisticOutputTask +from .manager.mood_manager import MoodPrintTask, MoodUpdateTask from .plugins.schedule.schedule_generator import bot_schedule from .plugins.emoji_system.emoji_manager import emoji_manager from .plugins.person_info.person_info import person_info_manager @@ -14,9 +19,8 @@ from .plugins.storage.storage import MessageStorage from .config.config import global_config from .plugins.chat.bot import chat_bot from .common.logger_manager import get_logger -from .plugins.remote import heartbeat_thread # noqa: F401 from .individuality.individuality import Individuality -from .common.server import global_server +from .common.server import global_server, Server from rich.traceback import install from .api.main import start_api_server @@ -27,17 +31,14 @@ logger = get_logger("main") class MainSystem: def __init__(self): - self.llm_stats = LLMStatistics("llm_statistics.txt") - self.mood_manager = MoodManager.get_instance() - self.hippocampus_manager = HippocampusManager.get_instance() - self._message_manager_started = False - self.individuality = Individuality.get_instance() + self.hippocampus_manager: HippocampusManager = HippocampusManager.get_instance() + self.individuality: Individuality = Individuality.get_instance() # 使用消息API替代直接的FastAPI实例 from .plugins.message import global_api - self.app = global_api - self.server = global_server + self.app: MessageServer = global_api + self.server: Server = global_server async def initialize(self): """初始化系统组件""" @@ -51,9 +52,15 @@ class MainSystem: async def _init_components(self): """初始化其他组件""" init_start_time = time.time() - # 启动LLM统计 - self.llm_stats.start() - logger.success("LLM统计功能启动成功") + + # 添加在线时间统计任务 + await async_task_manager.add_task(OnlineTimeRecordTask()) + + # 添加统计信息输出任务 + await async_task_manager.add_task(StatisticOutputTask()) + + # 添加遥测心跳任务 + await async_task_manager.add_task(TelemetryHeartBeatTask()) # 启动API服务器 start_api_server() @@ -62,9 +69,10 @@ class MainSystem: emoji_manager.initialize() logger.success("表情包管理器初始化成功") - # 启动情绪管理器 - self.mood_manager.start_mood_update(update_interval=global_config.mood_update_interval) - logger.success("情绪管理器启动成功") + # 添加情绪衰减任务 + await async_task_manager.add_task(MoodUpdateTask()) + # 添加情绪打印任务 + await async_task_manager.add_task(MoodPrintTask()) # 检查并清除person_info冗余字段，启动个人习惯推断 await person_info_manager.del_all_undefined_field() @@ -129,7 +137,6 @@ class MainSystem: self.build_memory_task(), self.forget_memory_task(), self.consolidate_memory_task(), - self.print_mood_task(), self.remove_recalled_message_task(), emoji_manager.start_periodic_check_register(), self.app.run(), @@ -163,12 +170,6 @@ class MainSystem: await HippocampusManager.get_instance().consolidate_memory() print("\033[1;32m[记忆整合]\033[0m 记忆整合完成") - async def print_mood_task(self): - """打印情绪状态""" - while True: - self.mood_manager.print_mood_status() - await asyncio.sleep(60) - @staticmethod async def remove_recalled_message_task(): """删除撤回消息任务""" diff --git a/src/manager/async_task_manager.py b/src/manager/async_task_manager.py new file mode 100644 index 000000000..720e918a9 --- /dev/null +++ b/src/manager/async_task_manager.py @@ -0,0 +1,150 @@ +from abc import abstractmethod + +import asyncio +from asyncio import Task, Event, Lock +from typing import Callable, Dict + +from src.common.logger_manager import get_logger + +logger = get_logger("async_task_manager") + + +class AsyncTask: + """异步任务基类""" + + def __init__(self, task_name: str | None = None, wait_before_start: int = 0, run_interval: int = 0): + self.task_name: str = task_name or self.__class__.__name__ + """任务名称""" + + self.wait_before_start: int = wait_before_start + """运行任务前是否进行等待（单位：秒，设为0则不等待）""" + + self.run_interval: int = run_interval + """多次运行的时间间隔（单位：秒，设为0则仅运行一次）""" + + @abstractmethod + async def run(self): + """ + 任务的执行过程 + """ + pass + + async def start_task(self, abort_flag: asyncio.Event): + if self.wait_before_start > 0: + # 等待指定时间后开始任务 + await asyncio.sleep(self.wait_before_start) + + while not abort_flag.is_set(): + await self.run() + if self.run_interval > 0: + await asyncio.sleep(self.run_interval) + else: + break + + +class AsyncTaskManager: + """异步任务管理器""" + + def __init__(self): + self.tasks: Dict[str, Task] = {} + """任务列表""" + + self.abort_flag: Event = Event() + """是否中止任务标志""" + + self._lock: Lock = Lock() + """异步锁，当可能出现await时需要加锁""" + + def _remove_task_call_back(self, task: Task): + """ + call_back: 任务完成后移除任务 + """ + task_name = task.get_name() + if task_name in self.tasks: + # 任务完成后移除任务 + del self.tasks[task_name] + logger.debug(f"已移除任务 '{task_name}'") + else: + logger.warning(f"尝试移除不存在的任务 '{task_name}'") + + @staticmethod + def _default_finish_call_back(task: Task): + """ + call_back: 默认的任务完成回调函数 + """ + try: + task.result() + logger.debug(f"任务 '{task.get_name()}' 完成") + except asyncio.CancelledError: + logger.debug(f"任务 '{task.get_name()}' 被取消") + except Exception as e: + logger.error(f"任务 '{task.get_name()}' 执行时发生异常: {e}", exc_info=True) + + async def add_task(self, task: AsyncTask, call_back: Callable[[asyncio.Task], None] | None = None): + """ + 添加任务 + """ + if not issubclass(task.__class__, AsyncTask): + raise TypeError(f"task '{task.__class__.__name__}' 必须是继承 AsyncTask 的子类") + + async with self._lock: # 由于可能需要await等待任务完成，所以需要加异步锁 + if task.task_name in self.tasks: + logger.warning(f"已存在名称为 '{task.task_name}' 的任务，正在尝试取消并替换") + self.tasks[task.task_name].cancel() # 取消已存在的任务 + await self.tasks[task.task_name] # 等待任务完成 + logger.info(f"成功结束任务 '{task.task_name}'") + + # 创建新任务 + task_inst = asyncio.create_task(task.start_task(self.abort_flag)) + task_inst.set_name(task.task_name) + task_inst.add_done_callback(self._remove_task_call_back) # 添加完成回调函数-完成任务后自动移除任务 + task_inst.add_done_callback( + call_back or self._default_finish_call_back + ) # 添加完成回调函数-用户自定义，或默认的FallBack + + self.tasks[task.task_name] = task_inst # 将任务添加到任务列表 + logger.info(f"已启动任务 '{task.task_name}'") + + def get_tasks_status(self) -> Dict[str, Dict[str, str]]: + """ + 获取所有任务的状态 + """ + tasks_status = {} + for task_name, task in self.tasks.items(): + tasks_status[task_name] = { + "status": "running" if not task.done() else "done", + } + return tasks_status + + async def stop_and_wait_all_tasks(self): + """ + 终止所有任务并等待它们完成（该方法会阻塞其它尝试add_task()的操作） + """ + async with self._lock: # 由于可能需要await等待任务完成，所以需要加异步锁 + # 设置中止标志 + self.abort_flag.set() + # 取消所有任务 + for name, inst in self.tasks.items(): + try: + inst.cancel() + except asyncio.CancelledError: + logger.info(f"已取消任务 '{name}'") + + # 等待所有任务完成 + for task_name, task_inst in self.tasks.items(): + if not task_inst.done(): + try: + await task_inst + except asyncio.CancelledError: # 此处再次捕获取消异常，防止stop_all_tasks()时延迟抛出异常 + logger.info(f"任务 {task_name} 已取消") + except Exception as e: + logger.error(f"任务 {task_name} 执行时发生异常: {e}", ext_info=True) + + # 清空任务列表 + self.tasks.clear() + self.abort_flag.clear() + logger.info("所有异步任务已停止") + + +async_task_manager = AsyncTaskManager() +"""全局异步任务管理器实例""" diff --git a/src/manager/local_store_manager.py b/src/manager/local_store_manager.py new file mode 100644 index 000000000..f172d8890 --- /dev/null +++ b/src/manager/local_store_manager.py @@ -0,0 +1,67 @@ +import json +import os + +from src.common.logger_manager import get_logger + +LOCAL_STORE_FILE_PATH = "data/local_store.json" + +logger = get_logger("local_storage") + + +class LocalStoreManager: + file_path: str + """本地存储路径""" + + store: dict[str, str | list | dict | int | float | bool] + """本地存储数据""" + + def __init__(self, local_store_path: str | None = None): + self.file_path = local_store_path or LOCAL_STORE_FILE_PATH + self.store = {} + self.load_local_store() + + def __getitem__(self, item: str) -> str | list | dict | int | float | bool | None: + """获取本地存储数据""" + return self.store.get(item, None) + + def __setitem__(self, key: str, value: str | list | dict | int | float | bool): + """设置本地存储数据""" + self.store[key] = value + self.save_local_store() + + def __contains__(self, item: str) -> bool: + """检查本地存储数据是否存在""" + return item in self.store + + def load_local_store(self): + """加载本地存储数据""" + if os.path.exists(self.file_path): + # 存在本地存储文件，加载数据 + logger.info("正在阅读记事本......我在看，我真的在看！") + logger.debug(f"加载本地存储数据: {self.file_path}") + try: + with open(self.file_path, "r", encoding="utf-8") as f: + self.store = json.load(f) + logger.success("全都记起来了！") + except json.JSONDecodeError: + logger.warning("啊咧？记事本被弄脏了，正在重建记事本......") + self.store = {} + with open(self.file_path, "w", encoding="utf-8") as f: + json.dump({}, f, ensure_ascii=False, indent=4) + logger.success("记事本重建成功！") + else: + # 不存在本地存储文件，创建新的目录和文件 + logger.warning("啊咧？记事本不存在，正在创建新的记事本......") + os.makedirs(os.path.dirname(self.file_path), exist_ok=True) + with open(self.file_path, "w", encoding="utf-8") as f: + json.dump({}, f, ensure_ascii=False, indent=4) + logger.success("记事本创建成功！") + + def save_local_store(self): + """保存本地存储数据""" + logger.debug(f"保存本地存储数据: {self.file_path}") + with open(self.file_path, "w", encoding="utf-8") as f: + json.dump(self.store, f, ensure_ascii=False, indent=4) + + +local_storage = LocalStoreManager("data/local_store.json") # 全局单例化 diff --git a/src/manager/mood_manager.py b/src/manager/mood_manager.py new file mode 100644 index 000000000..42677d4e1 --- /dev/null +++ b/src/manager/mood_manager.py @@ -0,0 +1,296 @@ +import asyncio +import math +import time +from dataclasses import dataclass +from typing import Dict, Tuple + +from ..config.config import global_config +from ..common.logger_manager import get_logger +from ..manager.async_task_manager import AsyncTask +from ..individuality.individuality import Individuality + +logger = get_logger("mood") + + +@dataclass +class MoodState: + valence: float + """愉悦度 (-1.0 到 1.0)，-1表示极度负面，1表示极度正面""" + arousal: float + """唤醒度 (-1.0 到 1.0)，-1表示抑制，1表示兴奋""" + text: str + """心情的文本描述""" + + +@dataclass +class MoodChangeHistory: + valence_direction_factor: int + """愉悦度变化的系数（正为增益，负为抑制）""" + arousal_direction_factor: int + """唤醒度变化的系数（正为增益，负为抑制）""" + + +class MoodUpdateTask(AsyncTask): + def __init__(self): + super().__init__( + task_name="Mood Update Task", + wait_before_start=global_config.mood_update_interval, + run_interval=global_config.mood_update_interval, + ) + + # 从配置文件获取衰减率 + self.decay_rate_valence: float = 1 - global_config.mood_decay_rate + """愉悦度衰减率""" + self.decay_rate_arousal: float = 1 - global_config.mood_decay_rate + """唤醒度衰减率""" + + self.last_update = time.time() + """上次更新时间""" + + async def run(self): + current_time = time.time() + time_diff = current_time - self.last_update + agreeableness_factor = 1 # 宜人性系数 + agreeableness_bias = 0 # 宜人性偏置 + neuroticism_factor = 0.5 # 神经质系数 + # 获取人格特质 + personality = Individuality.get_instance().personality + if personality: + # 神经质：影响情绪变化速度 + neuroticism_factor = 1 + (personality.neuroticism - 0.5) * 0.4 + agreeableness_factor = 1 + (personality.agreeableness - 0.5) * 0.4 + + # 宜人性：影响情绪基准线 + if personality.agreeableness < 0.2: + agreeableness_bias = (personality.agreeableness - 0.2) * 0.5 + elif personality.agreeableness > 0.8: + agreeableness_bias = (personality.agreeableness - 0.8) * 0.5 + else: + agreeableness_bias = 0 + + # 分别计算正向和负向的衰减率 + if mood_manager.current_mood.valence >= 0: + # 正向情绪衰减 + decay_rate_positive = self.decay_rate_valence * (1 / agreeableness_factor) + valence_target = 0 + agreeableness_bias + new_valence = valence_target + (mood_manager.current_mood.valence - valence_target) * math.exp( + -decay_rate_positive * time_diff * neuroticism_factor + ) + else: + # 负向情绪衰减 + decay_rate_negative = self.decay_rate_valence * agreeableness_factor + valence_target = 0 + agreeableness_bias + new_valence = valence_target + (mood_manager.current_mood.valence - valence_target) * math.exp( + -decay_rate_negative * time_diff * neuroticism_factor + ) + + # Arousal 向中性（0）回归 + arousal_target = 0 + new_arousal = arousal_target + (mood_manager.current_mood.arousal - arousal_target) * math.exp( + -self.decay_rate_arousal * time_diff * neuroticism_factor + ) + + mood_manager.set_current_mood(new_valence, new_arousal) + + self.last_update = current_time + + +class MoodPrintTask(AsyncTask): + def __init__(self): + super().__init__( + task_name="Mood Print Task", + wait_before_start=60, + run_interval=60, + ) + + async def run(self): + # 打印当前心情 + logger.info( + f"愉悦度: {mood_manager.current_mood.valence:.2f}, " + f"唤醒度: {mood_manager.current_mood.arousal:.2f}, " + f"心情: {mood_manager.current_mood.text}" + ) + + +class MoodManager: + # TODO: 改进，使用具有实验支持的新情绪模型 + + EMOTION_FACTOR_MAP: Dict[str, Tuple[float, float]] = { + "开心": (0.21, 0.6), + "害羞": (0.15, 0.2), + "愤怒": (-0.24, 0.8), + "恐惧": (-0.21, 0.7), + "悲伤": (-0.21, 0.3), + "厌恶": (-0.12, 0.4), + "惊讶": (0.06, 0.7), + "困惑": (0.0, 0.6), + "平静": (0.03, 0.5), + } + """ + 情绪词映射表 {mood: (valence, arousal)} + 将情绪描述词映射到愉悦度和唤醒度的元组 + """ + + EMOTION_POINT_MAP: Dict[Tuple[float, float], str] = { + # 第一象限：高唤醒，正愉悦 + (0.5, 0.4): "兴奋", + (0.3, 0.6): "快乐", + (0.2, 0.3): "满足", + # 第二象限：高唤醒，负愉悦 + (-0.5, 0.4): "愤怒", + (-0.3, 0.6): "焦虑", + (-0.2, 0.3): "烦躁", + # 第三象限：低唤醒，负愉悦 + (-0.5, -0.4): "悲伤", + (-0.3, -0.3): "疲倦", + (-0.4, -0.7): "疲倦", + # 第四象限：低唤醒，正愉悦 + (0.2, -0.1): "平静", + (0.3, -0.2): "安宁", + (0.5, -0.4): "放松", + } + """ + 情绪文本映射表 {(valence, arousal): mood} + 将量化的情绪状态元组映射到文本描述 + """ + + def __init__(self): + self.current_mood = MoodState( + valence=0.0, + arousal=0.0, + text="平静", + ) + """当前情绪状态""" + + self.mood_change_history: MoodChangeHistory = MoodChangeHistory( + valence_direction_factor=0, + arousal_direction_factor=0, + ) + """情绪变化历史""" + + self._lock = asyncio.Lock() + """异步锁，用于保护线程安全""" + + def set_current_mood(self, new_valence: float, new_arousal: float): + """ + 设置当前情绪状态 + :param new_valence: 新的愉悦度 + :param new_arousal: 新的唤醒度 + """ + # 限制范围 + self.current_mood.valence = max(-1.0, min(new_valence, 1.0)) + self.current_mood.arousal = max(-1.0, min(new_arousal, 1.0)) + + closest_mood = None + min_distance = float("inf") + + for (v, a), text in self.EMOTION_POINT_MAP.items(): + # 计算当前情绪状态与每个情绪文本的欧氏距离 + distance = math.sqrt((self.current_mood.valence - v) ** 2 + (self.current_mood.arousal - a) ** 2) + if distance < min_distance: + min_distance = distance + closest_mood = text + + if closest_mood: + self.current_mood.text = closest_mood + + def update_current_mood(self, valence_delta: float, arousal_delta: float): + """ + 根据愉悦度和唤醒度变化量更新当前情绪状态 + :param valence_delta: 愉悦度变化量 + :param arousal_delta: 唤醒度变化量 + """ + # 计算连续增益/抑制 + # 规则：多次相同方向的变化会有更大的影响系数，反方向的变化会清零影响系数（系数的正负号由变化方向决定） + if valence_delta * self.mood_change_history.valence_direction_factor > 0: + # 如果方向相同，则根据变化方向改变系数 + if valence_delta > 0: + self.mood_change_history.valence_direction_factor += 1 # 若为正向，则增加 + else: + self.mood_change_history.valence_direction_factor -= 1 # 若为负向，则减少 + else: + # 如果方向不同，则重置计数 + self.mood_change_history.valence_direction_factor = 0 + + if arousal_delta * self.mood_change_history.arousal_direction_factor > 0: + # 如果方向相同，则根据变化方向改变系数 + if arousal_delta > 0: + self.mood_change_history.arousal_direction_factor += 1 # 若为正向，则增加计数 + else: + self.mood_change_history.arousal_direction_factor -= 1 # 若为负向，则减少计数 + else: + # 如果方向不同，则重置计数 + self.mood_change_history.arousal_direction_factor = 0 + + # 计算增益/抑制的结果 + # 规则：如果当前情绪状态与变化方向相同，则增益；否则抑制 + if self.current_mood.valence * self.mood_change_history.valence_direction_factor > 0: + valence_delta = valence_delta * (1.01 ** abs(self.mood_change_history.valence_direction_factor)) + else: + valence_delta = valence_delta * (0.99 ** abs(self.mood_change_history.valence_direction_factor)) + + if self.current_mood.arousal * self.mood_change_history.arousal_direction_factor > 0: + arousal_delta = arousal_delta * (1.01 ** abs(self.mood_change_history.arousal_direction_factor)) + else: + arousal_delta = arousal_delta * (0.99 ** abs(self.mood_change_history.arousal_direction_factor)) + + self.set_current_mood( + new_valence=self.current_mood.valence + valence_delta, + new_arousal=self.current_mood.arousal + arousal_delta, + ) + + def get_mood_prompt(self) -> str: + """ + 根据当前情绪状态生成提示词 + """ + base_prompt = f"当前心情：{self.current_mood.text}。" + + # 根据情绪状态添加额外的提示信息 + if self.current_mood.valence > 0.5: + base_prompt += "你现在心情很好，" + elif self.current_mood.valence < -0.5: + base_prompt += "你现在心情不太好，" + + if self.current_mood.arousal > 0.4: + base_prompt += "情绪比较激动。" + elif self.current_mood.arousal < -0.4: + base_prompt += "情绪比较平静。" + + return base_prompt + + def get_arousal_multiplier(self) -> float: + """ + 根据当前情绪状态返回唤醒度乘数 + """ + if self.current_mood.arousal > 0.4: + multiplier = 1 + min(0.15, (self.current_mood.arousal - 0.4) / 3) + return multiplier + elif self.current_mood.arousal < -0.4: + multiplier = 1 - min(0.15, ((0 - self.current_mood.arousal) - 0.4) / 3) + return multiplier + return 1.0 + + def update_mood_from_emotion(self, emotion: str, intensity: float = 1.0) -> None: + """ + 根据情绪词更新心情状态 + :param emotion: 情绪词（如'开心', '悲伤'等位于self.EMOTION_FACTOR_MAP中的键） + :param intensity: 情绪强度（0.0-1.0） + """ + if emotion not in self.EMOTION_FACTOR_MAP: + logger.error(f"[情绪更新] 未知情绪词: {emotion}") + return + + valence_change, arousal_change = self.EMOTION_FACTOR_MAP[emotion] + old_valence = self.current_mood.valence + old_arousal = self.current_mood.arousal + old_mood = self.current_mood.text + + self.update_current_mood(valence_change, arousal_change) # 更新当前情绪状态 + + logger.info( + f"[情绪变化] {emotion}(强度:{intensity:.2f}) | 愉悦度:{old_valence:.2f}->{self.current_mood.valence:.2f}, 唤醒度:{old_arousal:.2f}->{self.current_mood.arousal:.2f} | 心情:{old_mood}->{self.current_mood.text}" + ) + + +mood_manager = MoodManager() +"""全局情绪管理器""" diff --git a/src/plugins/__init__.py b/src/plugins/__init__.py index 2e057e6fe..631d9bbb7 100644 --- a/src/plugins/__init__.py +++ b/src/plugins/__init__.py @@ -6,7 +6,6 @@ MaiMBot插件系统 from .chat.chat_stream import chat_manager from .emoji_system.emoji_manager import emoji_manager from .person_info.relationship_manager import relationship_manager -from .moods.moods import MoodManager from .willing.willing_manager import willing_manager from .schedule.schedule_generator import bot_schedule @@ -15,7 +14,6 @@ __all__ = [ "chat_manager", "emoji_manager", "relationship_manager", - "MoodManager", "willing_manager", "bot_schedule", ] diff --git a/src/plugins/chat/bot.py b/src/plugins/chat/bot.py index 9c4a33581..79e97c4f3 100644 --- a/src/plugins/chat/bot.py +++ b/src/plugins/chat/bot.py @@ -1,16 +1,15 @@ +import traceback from typing import Dict, Any -from ..moods.moods import MoodManager # 导入情绪管理器 -from ...config.config import global_config -from .message import MessageRecv -from ..PFC.pfc_manager import PFCManager -from .chat_stream import chat_manager -from .only_message_process import MessageProcessor - from src.common.logger_manager import get_logger +from src.manager.mood_manager import mood_manager # 导入情绪管理器 +from .chat_stream import chat_manager +from .message import MessageRecv +from .only_message_process import MessageProcessor +from ..PFC.pfc_manager import PFCManager from ..heartFC_chat.heartflow_processor import HeartFCProcessor from ..utils.prompt_builder import Prompt, global_prompt_manager -import traceback +from ...config.config import global_config # 定义日志配置 @@ -23,7 +22,7 @@ class ChatBot: def __init__(self): self.bot = None # bot 实例引用 self._started = False - self.mood_manager = MoodManager.get_instance() # 获取情绪管理器单例 + self.mood_manager = mood_manager # 获取情绪管理器单例 self.heartflow_processor = HeartFCProcessor() # 新增 # 创建初始化PFC管理器的任务，会在_ensure_started时执行 diff --git a/src/plugins/chat/utils.py b/src/plugins/chat/utils.py index 53e8f6f6e..c229f0a59 100644 --- a/src/plugins/chat/utils.py +++ b/src/plugins/chat/utils.py @@ -1,21 +1,20 @@ import random -import time import re +import time from collections import Counter import jieba import numpy as np -from src.common.logger import get_module_logger +from maim_message import UserInfo from pymongo.errors import PyMongoError +from src.common.logger import get_module_logger +from src.manager.mood_manager import mood_manager +from .message import MessageRecv from ..models.utils_model import LLMRequest from ..utils.typo_generator import ChineseTypoGenerator -from ...config.config import global_config -from .message import MessageRecv -from maim_message import UserInfo -from ..moods.moods import MoodManager from ...common.database import db - +from ...config.config import global_config logger = get_module_logger("chat_utils") @@ -405,7 +404,6 @@ def calculate_typing_time( - 在所有输入结束后，额外加上回车时间0.3秒 - 如果is_emoji为True，将使用固定1秒的输入时间 """ - mood_manager = MoodManager.get_instance() # 将0-1的唤醒度映射到-1到1 mood_arousal = mood_manager.current_mood.arousal # 映射到0.5到2倍的速度系数 diff --git a/src/plugins/heartFC_chat/heartFC_chat.py b/src/plugins/heartFC_chat/heartFC_chat.py index b594bf029..83abfbbed 100644 --- a/src/plugins/heartFC_chat/heartFC_chat.py +++ b/src/plugins/heartFC_chat/heartFC_chat.py @@ -1,33 +1,35 @@ import asyncio +import contextlib +import json # <--- 确保导入 json +import random # <--- 添加导入 import time import traceback -import random # <--- 添加导入 -import json # <--- 确保导入 json -from typing import List, Optional, Dict, Any, Deque, Callable, Coroutine from collections import deque +from typing import List, Optional, Dict, Any, Deque, Callable, Coroutine + +from rich.traceback import install + +from src.common.logger_manager import get_logger +from src.config.config import global_config +from src.heart_flow.observation import Observation +from src.heart_flow.sub_mind import SubMind +from src.heart_flow.utils_chat import get_chat_type_and_target_info +from src.manager.mood_manager import mood_manager +from src.plugins.chat.chat_stream import ChatStream +from src.plugins.chat.chat_stream import chat_manager from src.plugins.chat.message import MessageRecv, BaseMessageInfo, MessageThinking, MessageSending from src.plugins.chat.message import Seg # Local import needed after move -from src.plugins.chat.chat_stream import ChatStream from src.plugins.chat.message import UserInfo -from src.plugins.chat.chat_stream import chat_manager -from src.common.logger_manager import get_logger -from src.plugins.models.utils_model import LLMRequest -from src.config.config import global_config -from src.plugins.chat.utils_image import image_path_to_base64 # Local import needed after move -from src.plugins.utils.timer_calculator import Timer # <--- Import Timer -from src.plugins.emoji_system.emoji_manager import emoji_manager -from src.heart_flow.sub_mind import SubMind -from src.heart_flow.observation import Observation -from src.plugins.heartFC_chat.heartflow_prompt_builder import global_prompt_manager, prompt_builder -import contextlib -from src.plugins.utils.chat_message_builder import num_new_messages_since -from src.plugins.heartFC_chat.heartFC_Cycleinfo import CycleInfo -from .heartFC_sender import HeartFCSender from src.plugins.chat.utils import process_llm_response +from src.plugins.chat.utils_image import image_path_to_base64 # Local import needed after move +from src.plugins.emoji_system.emoji_manager import emoji_manager +from src.plugins.heartFC_chat.heartFC_Cycleinfo import CycleInfo +from src.plugins.heartFC_chat.heartflow_prompt_builder import global_prompt_manager, prompt_builder +from src.plugins.models.utils_model import LLMRequest from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager -from src.plugins.moods.moods import MoodManager -from src.heart_flow.utils_chat import get_chat_type_and_target_info -from rich.traceback import install +from src.plugins.utils.chat_message_builder import num_new_messages_since +from src.plugins.utils.timer_calculator import Timer # <--- Import Timer +from .heartFC_sender import HeartFCSender install(extra_lines=3) @@ -1275,7 +1277,7 @@ class HeartFChatting: """ try: # 1. 获取情绪影响因子并调整模型温度 - arousal_multiplier = MoodManager.get_instance().get_arousal_multiplier() + arousal_multiplier = mood_manager.get_arousal_multiplier() current_temp = global_config.llm_normal["temp"] * arousal_multiplier self.model_normal.temperature = current_temp # 动态调整温度 diff --git a/src/plugins/heartFC_chat/heartflow_prompt_builder.py b/src/plugins/heartFC_chat/heartflow_prompt_builder.py index c59168a7f..c4a137a78 100644 --- a/src/plugins/heartFC_chat/heartflow_prompt_builder.py +++ b/src/plugins/heartFC_chat/heartflow_prompt_builder.py @@ -10,7 +10,7 @@ import time from typing import Union, Optional, Deque, Dict, Any from ...common.database import db from ..chat.utils import get_recent_group_speaker -from ..moods.moods import MoodManager +from src.manager.mood_manager import mood_manager from ..memory_system.Hippocampus import HippocampusManager from ..schedule.schedule_generator import bot_schedule from ..knowledge.knowledge_lib import qa_manager @@ -341,8 +341,7 @@ class PromptBuilder: else: logger.warning(f"Invalid person tuple encountered for relationship prompt: {person}") - mood_manager = MoodManager.get_instance() - mood_prompt = mood_manager.get_prompt() + mood_prompt = mood_manager.get_mood_prompt() reply_styles1 = [ ("然后给出日常且口语化的回复，平淡一些", 0.4), ("给出非常简短的回复", 0.4), diff --git a/src/plugins/heartFC_chat/normal_chat.py b/src/plugins/heartFC_chat/normal_chat.py index be05f4d70..460e881a0 100644 --- a/src/plugins/heartFC_chat/normal_chat.py +++ b/src/plugins/heartFC_chat/normal_chat.py @@ -1,26 +1,26 @@ -import time import asyncio -import traceback import statistics # 导入 statistics 模块 +import time +import traceback from random import random from typing import List, Optional # 导入 Optional -from ..moods.moods import MoodManager -from ...config.config import global_config -from ..emoji_system.emoji_manager import emoji_manager -from .normal_chat_generator import NormalChatGenerator -from ..chat.message import MessageSending, MessageRecv, MessageThinking, MessageSet -from ..chat.message_sender import message_manager -from ..chat.utils_image import image_path_to_base64 -from ..willing.willing_manager import willing_manager from maim_message import UserInfo, Seg + from src.common.logger_manager import get_logger +from src.heart_flow.utils_chat import get_chat_type_and_target_info +from src.manager.mood_manager import mood_manager from src.plugins.chat.chat_stream import ChatStream, chat_manager from src.plugins.person_info.relationship_manager import relationship_manager from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager from src.plugins.utils.timer_calculator import Timer -from src.heart_flow.utils_chat import get_chat_type_and_target_info - +from .normal_chat_generator import NormalChatGenerator +from ..chat.message import MessageSending, MessageRecv, MessageThinking, MessageSet +from ..chat.message_sender import message_manager +from ..chat.utils_image import image_path_to_base64 +from ..emoji_system.emoji_manager import emoji_manager +from ..willing.willing_manager import willing_manager +from ...config.config import global_config logger = get_logger("chat") @@ -45,7 +45,7 @@ class NormalChat: # Other sync initializations self.gpt = NormalChatGenerator() - self.mood_manager = MoodManager.get_instance() + self.mood_manager = mood_manager self.start_time = time.time() self.last_speak_time = 0 self._chat_task: Optional[asyncio.Task] = None diff --git a/src/plugins/moods/moods.py b/src/plugins/moods/moods.py deleted file mode 100644 index 1c025319f..000000000 --- a/src/plugins/moods/moods.py +++ /dev/null @@ -1,293 +0,0 @@ -import math -import threading -import time -from dataclasses import dataclass - -from ...config.config import global_config -from src.common.logger_manager import get_logger -from ..person_info.relationship_manager import relationship_manager -from src.individuality.individuality import Individuality - - -logger = get_logger("mood") - - -@dataclass -class MoodState: - valence: float # 愉悦度 (-1.0 到 1.0)，-1表示极度负面，1表示极度正面 - arousal: float # 唤醒度 (-1.0 到 1.0)，-1表示抑制，1表示兴奋 - text: str # 心情文本描述 - - -class MoodManager: - _instance = None - _lock = threading.Lock() - - def __new__(cls): - with cls._lock: - if cls._instance is None: - cls._instance = super().__new__(cls) - cls._instance._initialized = False - return cls._instance - - def __init__(self): - # 确保初始化代码只运行一次 - if self._initialized: - return - - self._initialized = True - - # 初始化心情状态 - self.current_mood = MoodState(valence=0.0, arousal=0.0, text="平静") - - # 从配置文件获取衰减率 - self.decay_rate_valence = 1 - global_config.mood_decay_rate # 愉悦度衰减率 - self.decay_rate_arousal = 1 - global_config.mood_decay_rate # 唤醒度衰减率 - - # 上次更新时间 - self.last_update = time.time() - - # 线程控制 - self._running = False - self._update_thread = None - - # 情绪词映射表 (valence, arousal) - self.emotion_map = { - "开心": (0.21, 0.6), - "害羞": (0.15, 0.2), - "愤怒": (-0.24, 0.8), - "恐惧": (-0.21, 0.7), - "悲伤": (-0.21, 0.3), - "厌恶": (-0.12, 0.4), - "惊讶": (0.06, 0.7), - "困惑": (0.0, 0.6), - "平静": (0.03, 0.5), - } - - # 情绪文本映射表 - self.mood_text_map = { - # 第一象限：高唤醒，正愉悦 - (0.5, 0.4): "兴奋", - (0.3, 0.6): "快乐", - (0.2, 0.3): "满足", - # 第二象限：高唤醒，负愉悦 - (-0.5, 0.4): "愤怒", - (-0.3, 0.6): "焦虑", - (-0.2, 0.3): "烦躁", - # 第三象限：低唤醒，负愉悦 - (-0.5, -0.4): "悲伤", - (-0.3, -0.3): "疲倦", - (-0.4, -0.7): "疲倦", - # 第四象限：低唤醒，正愉悦 - (0.2, -0.1): "平静", - (0.3, -0.2): "安宁", - (0.5, -0.4): "放松", - } - - @classmethod - def get_instance(cls) -> "MoodManager": - """获取MoodManager的单例实例""" - if cls._instance is None: - cls._instance = MoodManager() - return cls._instance - - def start_mood_update(self, update_interval: float = 5.0) -> None: - """ - 启动情绪更新线程 - :param update_interval: 更新间隔（秒） - """ - if self._running: - return - - self._running = True - self._update_thread = threading.Thread( - target=self._continuous_mood_update, args=(update_interval,), daemon=True - ) - self._update_thread.start() - - def stop_mood_update(self) -> None: - """停止情绪更新线程""" - self._running = False - if self._update_thread and self._update_thread.is_alive(): - self._update_thread.join() - - def _continuous_mood_update(self, update_interval: float) -> None: - """ - 持续更新情绪状态的线程函数 - :param update_interval: 更新间隔（秒） - """ - while self._running: - self._apply_decay() - self._update_mood_text() - time.sleep(update_interval) - - def _apply_decay(self) -> None: - """应用情绪衰减，正向和负向情绪分开计算""" - current_time = time.time() - time_diff = current_time - self.last_update - agreeableness_factor = 1 - agreeableness_bias = 0 - neuroticism_factor = 0.5 - - # 获取人格特质 - personality = Individuality.get_instance().personality - if personality: - # 神经质：影响情绪变化速度 - neuroticism_factor = 1 + (personality.neuroticism - 0.5) * 0.4 - agreeableness_factor = 1 + (personality.agreeableness - 0.5) * 0.4 - - # 宜人性：影响情绪基准线 - if personality.agreeableness < 0.2: - agreeableness_bias = (personality.agreeableness - 0.2) * 0.5 - elif personality.agreeableness > 0.8: - agreeableness_bias = (personality.agreeableness - 0.8) * 0.5 - else: - agreeableness_bias = 0 - - # 分别计算正向和负向的衰减率 - if self.current_mood.valence >= 0: - # 正向情绪衰减 - decay_rate_positive = self.decay_rate_valence * (1 / agreeableness_factor) - valence_target = 0 + agreeableness_bias - self.current_mood.valence = valence_target + (self.current_mood.valence - valence_target) * math.exp( - -decay_rate_positive * time_diff * neuroticism_factor - ) - else: - # 负向情绪衰减 - decay_rate_negative = self.decay_rate_valence * agreeableness_factor - valence_target = 0 + agreeableness_bias - self.current_mood.valence = valence_target + (self.current_mood.valence - valence_target) * math.exp( - -decay_rate_negative * time_diff * neuroticism_factor - ) - - # Arousal 向中性（0）回归 - arousal_target = 0 - self.current_mood.arousal = arousal_target + (self.current_mood.arousal - arousal_target) * math.exp( - -self.decay_rate_arousal * time_diff * neuroticism_factor - ) - - # 确保值在合理范围内 - self.current_mood.valence = max(-1.0, min(1.0, self.current_mood.valence)) - self.current_mood.arousal = max(-1.0, min(1.0, self.current_mood.arousal)) - - self.last_update = current_time - - def update_mood_from_text(self, text: str, valence_change: float, arousal_change: float) -> None: - """根据输入文本更新情绪状态""" - - self.current_mood.valence += valence_change - self.current_mood.arousal += arousal_change - - # 限制范围 - self.current_mood.valence = max(-1.0, min(1.0, self.current_mood.valence)) - self.current_mood.arousal = max(-1.0, min(1.0, self.current_mood.arousal)) - - self._update_mood_text() - - def set_mood_text(self, text: str) -> None: - """直接设置心情文本""" - self.current_mood.text = text - - def _update_mood_text(self) -> None: - """根据当前情绪状态更新文本描述""" - closest_mood = None - min_distance = float("inf") - - for (v, a), text in self.mood_text_map.items(): - distance = math.sqrt((self.current_mood.valence - v) ** 2 + (self.current_mood.arousal - a) ** 2) - if distance < min_distance: - min_distance = distance - closest_mood = text - - if closest_mood: - self.current_mood.text = closest_mood - - def update_mood_by_user(self, user_id: str, valence_change: float, arousal_change: float) -> None: - """根据用户ID更新情绪状态""" - - # 这里可以根据用户ID添加特定的权重或规则 - weight = 1.0 # 默认权重 - - self.current_mood.valence += valence_change * weight - self.current_mood.arousal += arousal_change * weight - - # 限制范围 - self.current_mood.valence = max(-1.0, min(1.0, self.current_mood.valence)) - self.current_mood.arousal = max(-1.0, min(1.0, self.current_mood.arousal)) - - self._update_mood_text() - - def get_prompt(self) -> str: - """根据当前情绪状态生成提示词""" - - base_prompt = f"当前心情：{self.current_mood.text}。" - - # 根据情绪状态添加额外的提示信息 - if self.current_mood.valence > 0.5: - base_prompt += "你现在心情很好，" - elif self.current_mood.valence < -0.5: - base_prompt += "你现在心情不太好，" - - if self.current_mood.arousal > 0.4: - base_prompt += "情绪比较激动。" - elif self.current_mood.arousal < -0.4: - base_prompt += "情绪比较平静。" - - return base_prompt - - def get_arousal_multiplier(self) -> float: - """根据当前情绪状态返回唤醒度乘数""" - if self.current_mood.arousal > 0.4: - multiplier = 1 + min(0.15, (self.current_mood.arousal - 0.4) / 3) - return multiplier - elif self.current_mood.arousal < -0.4: - multiplier = 1 - min(0.15, ((0 - self.current_mood.arousal) - 0.4) / 3) - return multiplier - return 1.0 - - def get_current_mood(self) -> MoodState: - """获取当前情绪状态""" - return self.current_mood - - def print_mood_status(self) -> None: - """打印当前情绪状态""" - logger.info( - f"愉悦度: {self.current_mood.valence:.2f}, " - f"唤醒度: {self.current_mood.arousal:.2f}, " - f"心情: {self.current_mood.text}" - ) - - def update_mood_from_emotion(self, emotion: str, intensity: float = 1.0) -> None: - """ - 根据情绪词更新心情状态 - :param emotion: 情绪词（如'happy', 'sad'等） - :param intensity: 情绪强度（0.0-1.0） - """ - if emotion not in self.emotion_map: - logger.debug(f"[情绪更新] 未知情绪词: {emotion}") - return - - valence_change, arousal_change = self.emotion_map[emotion] - old_valence = self.current_mood.valence - old_arousal = self.current_mood.arousal - old_mood = self.current_mood.text - - valence_change = relationship_manager.feedback_to_mood(valence_change) - - # 应用情绪强度 - valence_change *= intensity - arousal_change *= intensity - - # 更新当前情绪状态 - self.current_mood.valence += valence_change - self.current_mood.arousal += arousal_change - - # 限制范围 - self.current_mood.valence = max(-1.0, min(1.0, self.current_mood.valence)) - self.current_mood.arousal = max(-1.0, min(1.0, self.current_mood.arousal)) - - self._update_mood_text() - - logger.info( - f"[情绪变化] {emotion}(强度:{intensity:.2f}) | 愉悦度:{old_valence:.2f}->{self.current_mood.valence:.2f}, 唤醒度:{old_arousal:.2f}->{self.current_mood.arousal:.2f} | 心情:{old_mood}->{self.current_mood.text}" - ) diff --git a/src/plugins/person_info/relationship_manager.py b/src/plugins/person_info/relationship_manager.py index 862f23984..e9dad4b74 100644 --- a/src/plugins/person_info/relationship_manager.py +++ b/src/plugins/person_info/relationship_manager.py @@ -6,6 +6,9 @@ from .person_info import person_info_manager import time import random from maim_message import UserInfo + +from ...manager.mood_manager import mood_manager + # import re # import traceback @@ -22,9 +25,7 @@ class RelationshipManager: @property def mood_manager(self): if self._mood_manager is None: - from ..moods.moods import MoodManager # 延迟导入 - - self._mood_manager = MoodManager.get_instance() + self._mood_manager = mood_manager return self._mood_manager def positive_feedback_sys(self, label: str, stance: str): @@ -60,9 +61,7 @@ class RelationshipManager: def mood_feedback(self, value): """情绪反馈""" mood_manager = self.mood_manager - mood_gain = mood_manager.get_current_mood().valence ** 2 * math.copysign( - 1, value * mood_manager.get_current_mood().valence - ) + mood_gain = mood_manager.current_mood.valence**2 * math.copysign(1, value * mood_manager.current_mood.valence) value += value * mood_gain logger.info(f"当前relationship增益系数：{mood_gain:.3f}") return value diff --git a/src/plugins/remote/__init__.py b/src/plugins/remote/__init__.py deleted file mode 100644 index 4cbce96d1..000000000 --- a/src/plugins/remote/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from .remote import main - -# 启动心跳线程 -heartbeat_thread = main() diff --git a/src/plugins/remote/remote.py b/src/plugins/remote/remote.py index 68b023969..1d26df01b 100644 --- a/src/plugins/remote/remote.py +++ b/src/plugins/remote/remote.py @@ -1,248 +1,142 @@ +import asyncio + import requests -import time -import uuid import platform -import os -import json -import threading -import subprocess # from loguru import logger from src.common.logger_manager import get_logger from src.config.config import global_config +from src.manager.async_task_manager import AsyncTask +from src.manager.local_store_manager import local_storage logger = get_logger("remote") -# --- 使用向上导航的方式定义路径 --- - -# 1. 获取当前文件 (remote.py) 所在的目录 -current_dir = os.path.dirname(os.path.abspath(__file__)) - -# 2. 从当前目录向上导航三级找到项目根目录 -# (src/plugins/remote/ -> src/plugins/ -> src/ -> project_root) -root_dir = os.path.abspath(os.path.join(current_dir, "..", "..", "..")) - -# 3. 定义 data 目录的路径 (位于项目根目录下) -data_dir = os.path.join(root_dir, "data") - -# 4. 定义 UUID 文件在 data 目录下的完整路径 -UUID_FILE = os.path.join(data_dir, "client_uuid.json") - -# --- 路径定义结束 --- +TELEMETRY_SERVER_URL = "http://localhost:8080" +"""遥测服务地址""" -# 生成或获取客户端唯一ID -def get_unique_id(): - # --- 在尝试读写 UUID_FILE 之前确保 data 目录存在 --- - # 将目录检查和创建逻辑移到这里，在首次需要写入前执行 - try: - # exist_ok=True 意味着如果目录已存在也不会报错 - os.makedirs(data_dir, exist_ok=True) - except OSError as e: - # 处理可能的权限错误等 - logger.error(f"无法创建数据目录 {data_dir}: {e}") - # 根据你的错误处理逻辑，可能需要在这里返回错误或抛出异常 - # 暂且返回 None 或抛出，避免继续执行导致问题 - raise RuntimeError(f"无法创建必要的数据目录 {data_dir}") from e - # --- 目录检查结束 --- +class TelemetryHeartBeatTask(AsyncTask): + HEARTBEAT_INTERVAL = 300 - # 检查是否已经有保存的UUID - if os.path.exists(UUID_FILE): - try: - with open(UUID_FILE, "r", encoding="utf-8") as f: # 指定 encoding - data = json.load(f) - if "client_id" in data: - logger.debug(f"从本地文件读取客户端ID: {UUID_FILE}") - return data["client_id"] - except (json.JSONDecodeError, IOError) as e: - logger.warning(f"读取UUID文件 {UUID_FILE} 出错: {e}，将生成新的UUID") - except Exception as e: # 捕捉其他可能的异常 - logger.error(f"读取UUID文件 {UUID_FILE} 时发生未知错误: {e}") + def __init__(self): + super().__init__(task_name="Telemetry Heart Beat Task", run_interval=self.HEARTBEAT_INTERVAL) + self.server_url = TELEMETRY_SERVER_URL + """遥测服务地址""" - # 如果没有保存的UUID或读取出错，则生成新的 - client_id = generate_unique_id() - logger.info(f"生成新的客户端ID: {client_id}") + self.client_uuid = local_storage["mmc_uuid"] if "mmc_uuid" in local_storage else None + """客户端UUID""" - # 保存UUID到文件 - try: - # 再次确认目录存在 (虽然理论上前面已创建，但更保险) - os.makedirs(data_dir, exist_ok=True) - with open(UUID_FILE, "w", encoding="utf-8") as f: # 指定 encoding - json.dump({"client_id": client_id}, f, indent=4) # 添加 indent 使json可读 - logger.info(f"已保存新生成的客户端ID到本地文件: {UUID_FILE}") - except IOError as e: - logger.error(f"保存UUID时出错: {UUID_FILE} - {e}") - except Exception as e: # 捕捉其他可能的异常 - logger.error(f"保存UUID文件 {UUID_FILE} 时发生未知错误: {e}") + self.info_dict = self._get_sys_info() + """系统信息字典""" - return client_id + @staticmethod + def _get_sys_info() -> dict[str, str]: + """获取系统信息""" + info_dict = { + "os_type": "Unknown", + "py_version": platform.python_version(), + "mmc_version": global_config.MAI_VERSION, + } + match platform.system(): + case "Windows": + info_dict["os_type"] = "Windows" + case "Linux": + info_dict["os_type"] = "Linux" + case "Darwin": + info_dict["os_type"] = "macOS" + case _: + info_dict["os_type"] = "Unknown" -# 生成客户端唯一ID -def generate_unique_id(): - # 基于机器码生成唯一ID，同一台机器上生成的UUID是固定的，只要机器码不变 - import hashlib + return info_dict - system_info = platform.system() - machine_code = None + async def _req_uuid(self) -> bool: + """ + 向服务端请求UUID（不应在已存在UUID的情况下调用，会覆盖原有的UUID） + """ - try: - if system_info == "Windows": - # 使用wmic命令获取主机UUID（更稳定） - result = subprocess.check_output( - "wmic csproduct get uuid", shell=True, stderr=subprocess.DEVNULL, stdin=subprocess.DEVNULL - ) - lines = result.decode(errors="ignore").splitlines() - # 过滤掉空行和表头，只取有效UUID - uuids = [line.strip() for line in lines if line.strip() and line.strip().lower() != "uuid"] - if uuids: - uuid_val = uuids[0] - # logger.debug(f"主机UUID: {uuid_val}") - # 增加无效值判断 - if uuid_val and uuid_val.lower() not in ["to be filled by o.e.m.", "none", "", "standard"]: - machine_code = uuid_val - elif system_info == "Linux": - # 优先读取 /etc/machine-id，其次 /var/lib/dbus/machine-id，取第一个非空且内容有效的 - for path in ["/etc/machine-id", "/var/lib/dbus/machine-id"]: - if os.path.exists(path): - with open(path, "r") as f: - code = f.read().strip() - # 只要内容非空且不是全0 - if code and set(code) != {"0"}: - machine_code = code - break - elif system_info == "Darwin": - # macOS: 使用IOPlatformUUID - result = subprocess.check_output( - "ioreg -rd1 -c IOPlatformExpertDevice | awk '/IOPlatformUUID/'", shell=True - ) - uuid_line = result.decode(errors="ignore") - # 解析出 "IOPlatformUUID" = "xxxx-xxxx-xxxx-xxxx" - import re - - m = re.search(r'"IOPlatformUUID"\s*=\s*"([^"]+)"', uuid_line) - if m: - uuid_val = m.group(1) - logger.debug(f"IOPlatformUUID: {uuid_val}") - if uuid_val and uuid_val.lower() not in ["to be filled by o.e.m.", "none", "", "standard"]: - machine_code = uuid_val - except Exception as e: - logger.debug(f"获取机器码失败: {e}") - - # 如果主板序列号无效，尝试用MAC地址 - if not machine_code: - try: - mac = uuid.getnode() - if (mac >> 40) % 2 == 0: # 不是本地伪造MAC - machine_code = str(mac) - except Exception as e: - logger.debug(f"获取MAC地址失败: {e}") - - def md5_to_uuid(md5hex): - # 将32位md5字符串格式化为8-4-4-4-12的UUID格式 - return f"{md5hex[0:8]}-{md5hex[8:12]}-{md5hex[12:16]}-{md5hex[16:20]}-{md5hex[20:32]}" - - if machine_code: - # print(f"machine_code={machine_code!r}") # 可用于调试 - md5 = hashlib.md5(machine_code.encode("utf-8")).hexdigest() - uuid_str = md5_to_uuid(md5) - else: - uuid_str = str(uuid.uuid4()) - - unique_id = f"{system_info}-{uuid_str}" - return unique_id - - -def send_heartbeat(server_url, client_id): - """向服务器发送心跳""" - sys = platform.system() - try: - headers = {"Client-ID": client_id, "User-Agent": f"HeartbeatClient/{client_id[:8]}"} - data = json.dumps( - {"system": sys, "Version": global_config.MAI_VERSION}, - ) - logger.debug(f"正在发送心跳到服务器: {server_url}") - logger.debug(f"心跳数据: {data}") - response = requests.post(f"{server_url}/api/clients", headers=headers, data=data) - - if response.status_code == 201: - data = response.json() - logger.debug(f"心跳发送成功。服务器响应: {data}") - return True - else: - logger.debug(f"心跳发送失败。状态码: {response.status_code}, 响应内容: {response.text}") + if "deploy_time" not in local_storage: + logger.error("本地存储中缺少部署时间，无法请求UUID") return False - except requests.RequestException as e: - # 如果请求异常，可能是网络问题，不记录错误 - logger.debug(f"发送心跳时出错: {e}") - return False + try_count: int = 0 + while True: + # 如果不存在，则向服务端请求一个新的UUID（注册客户端） + logger.info("正在向遥测服务端请求UUID...") + try: + response = requests.post( + f"{TELEMETRY_SERVER_URL}/stat/reg_client", + json={"deploy_time": local_storage["deploy_time"]}, + ) -class HeartbeatThread(threading.Thread): - """心跳线程类""" + if response.status_code == 200: + data = response.json() + client_id = data.get("mmc_uuid") + if client_id: + # 将UUID存储到本地 + local_storage["mmc_uuid"] = client_id + self.client_uuid = client_id + logger.info(f"成功获取UUID: {self.client_uuid}") + return True # 成功获取UUID，返回True + else: + logger.error("无效的服务端响应") + else: + logger.error(f"请求UUID失败，状态码: {response.status_code}, 响应内容: {response.text}") + except requests.RequestException as e: + logger.error(f"请求UUID时出错: {e}") # 可能是网络问题 - def __init__(self, server_url, interval): - super().__init__(daemon=True) # 设置为守护线程，主程序结束时自动结束 - self.server_url = server_url - self.interval = interval - self.client_id = get_unique_id() - self.running = True - self.stop_event = threading.Event() # 添加事件对象用于可中断的等待 - self.last_heartbeat_time = 0 # 记录上次发送心跳的时间 - - def run(self): - """线程运行函数""" - logger.debug(f"心跳线程已启动，客户端ID: {self.client_id}") - - while self.running: - # 发送心跳 - if send_heartbeat(self.server_url, self.client_id): - logger.info(f"{self.interval}秒后发送下一次心跳...") + # 请求失败，重试次数+1 + try_count += 1 + if try_count > 3: + # 如果超过3次仍然失败，则退出 + logger.error("获取UUID失败，请检查网络连接或服务端状态") + return False else: - logger.info(f"{self.interval}秒后重试...") + # 如果可以重试，等待后继续（指数退避） + await asyncio.sleep(4**try_count) - self.last_heartbeat_time = time.time() + async def _send_heartbeat(self): + """向服务器发送心跳""" + try: + headers = { + "Client-UUID": self.client_uuid, + "User-Agent": f"HeartbeatClient/{self.client_uuid[:8]}", + } - # 使用可中断的等待代替 sleep - # 每秒检查一次是否应该停止或发送心跳 - remaining_wait = self.interval - while remaining_wait > 0 and self.running: - # 每次最多等待1秒，便于及时响应停止请求 - wait_time = min(1, remaining_wait) - if self.stop_event.wait(wait_time): - break # 如果事件被设置，立即退出等待 - remaining_wait -= wait_time + logger.debug(f"正在发送心跳到服务器: {self.server_url}") - # 检查是否由于外部原因导致间隔异常延长 - if time.time() - self.last_heartbeat_time >= self.interval * 1.5: - logger.warning("检测到心跳间隔异常延长，立即发送心跳") - break + response = requests.post( + f"{self.server_url}/stat/client_heartbeat", + headers=headers, + json=self.info_dict, + ) - def stop(self): - """停止线程""" - self.running = False - self.stop_event.set() # 设置事件，中断等待 - logger.debug("心跳线程已收到停止信号") + # 处理响应 + if 200 <= response.status_code < 300: + # 成功 + logger.debug(f"心跳发送成功，状态码: {response.status_code}") + elif response.status_code == 403: + # 403 Forbidden + logger.error( + "心跳发送失败，403 Forbidden: 可能是UUID无效或未注册。" + "处理措施：重置UUID，下次发送心跳时将尝试重新注册。" + ) + self.client_uuid = None + del local_storage["mmc_uuid"] # 删除本地存储的UUID + else: + # 其他错误 + logger.error(f"心跳发送失败，状态码: {response.status_code}, 响应内容: {response.text}") + except requests.RequestException as e: + logger.error(f"心跳发送失败: {e}") -def main(): - if global_config.remote_enable: - """主函数，启动心跳线程""" - # 配置 - server_url = "http://hyybuth.xyz:10058" - # server_url = "http://localhost:10058" - heartbeat_interval = 300 # 5分钟（秒） + async def run(self): + # 发送心跳 + if global_config.remote_enable: + if self.client_uuid is None: + if not await self._req_uuid(): + logger.error("获取UUID失败，跳过此次心跳") + return - # 创建并启动心跳线程 - heartbeat_thread = HeartbeatThread(server_url, heartbeat_interval) - heartbeat_thread.start() - - return heartbeat_thread # 返回线程对象，便于外部控制 - return None - - -# --- 测试用例 --- -if __name__ == "__main__": - print("测试唯一ID生成：") - print("唯一ID:", get_unique_id()) + await self._send_heartbeat() diff --git a/src/plugins/utils/statistic.py b/src/plugins/utils/statistic.py index b1660d720..4c11ba3d8 100644 --- a/src/plugins/utils/statistic.py +++ b/src/plugins/utils/statistic.py @@ -1,354 +1,765 @@ -import threading -import time from collections import defaultdict from datetime import datetime, timedelta -from typing import Any, Dict, List +from typing import Any, Dict, Tuple, List + from src.common.logger import get_module_logger +from src.manager.async_task_manager import AsyncTask from ...common.database import db +from src.manager.local_store_manager import local_storage -logger = get_module_logger("llm_statistics") +logger = get_module_logger("maibot_statistic") + +# 统计数据的键 +TOTAL_REQ_CNT = "total_requests" +TOTAL_COST = "total_cost" +REQ_CNT_BY_TYPE = "requests_by_type" +REQ_CNT_BY_USER = "requests_by_user" +REQ_CNT_BY_MODEL = "requests_by_model" +IN_TOK_BY_TYPE = "in_tokens_by_type" +IN_TOK_BY_USER = "in_tokens_by_user" +IN_TOK_BY_MODEL = "in_tokens_by_model" +OUT_TOK_BY_TYPE = "out_tokens_by_type" +OUT_TOK_BY_USER = "out_tokens_by_user" +OUT_TOK_BY_MODEL = "out_tokens_by_model" +TOTAL_TOK_BY_TYPE = "tokens_by_type" +TOTAL_TOK_BY_USER = "tokens_by_user" +TOTAL_TOK_BY_MODEL = "tokens_by_model" +COST_BY_TYPE = "costs_by_type" +COST_BY_USER = "costs_by_user" +COST_BY_MODEL = "costs_by_model" +ONLINE_TIME = "online_time" +TOTAL_MSG_CNT = "total_messages" +MSG_CNT_BY_CHAT = "messages_by_chat" -class LLMStatistics: - def __init__(self, output_file: str = "llm_statistics.txt"): - """初始化LLM统计类 +class OnlineTimeRecordTask(AsyncTask): + """在线时间记录任务""" - Args: - output_file: 统计结果输出文件路径 - """ - self.output_file = output_file - self.running = False - self.stats_thread = None - self.console_thread = None - self._init_database() - self.name_dict: Dict[List] = {} + def __init__(self): + super().__init__(task_name="Online Time Record Task", run_interval=60) + + self.record_id: str | None = None + """记录ID""" + + self._init_database() # 初始化数据库 @staticmethod def _init_database(): - """初始化数据库集合""" + """初始化数据库""" if "online_time" not in db.list_collection_names(): + # 初始化数据库（在线时长） db.create_collection("online_time") - db.online_time.create_index([("timestamp", 1)]) + # 创建索引 + if ("end_timestamp", 1) not in db.online_time.list_indexes(): + db.online_time.create_index([("end_timestamp", 1)]) - def start(self): - """启动统计线程""" - if not self.running: - self.running = True - # 启动文件统计线程 - self.stats_thread = threading.Thread(target=self._stats_loop) - self.stats_thread.daemon = True - self.stats_thread.start() - # 启动控制台输出线程 - self.console_thread = threading.Thread(target=self._console_output_loop) - self.console_thread.daemon = True - self.console_thread.start() + async def run(self): + try: + if self.record_id: + # 如果有记录，则更新结束时间 + db.online_time.update_one( + {"_id": self.record_id}, + { + "$set": { + "end_timestamp": datetime.now() + timedelta(minutes=1), + } + }, + ) + else: + # 如果没有记录，检查一分钟以内是否已有记录 + current_time = datetime.now() + recent_record = db.online_time.find_one( + {"end_timestamp": {"$gte": current_time - timedelta(minutes=1)}} + ) - def stop(self): - """停止统计线程""" - self.running = False - if self.stats_thread: - self.stats_thread.join() - if self.console_thread: - self.console_thread.join() + if not recent_record: + # 若没有记录，则插入新的在线时间记录 + self.record_id = db.online_time.insert_one( + { + "start_timestamp": current_time, + "end_timestamp": current_time + timedelta(minutes=1), + } + ).inserted_id + else: + # 如果有记录，则更新结束时间 + self.record_id = recent_record["_id"] + db.online_time.update_one( + {"_id": self.record_id}, + { + "$set": { + "end_timestamp": current_time + timedelta(minutes=1), + } + }, + ) + except Exception: + logger.exception("在线时间记录失败") + + +def _format_online_time(online_seconds: int) -> str: + """ + 格式化在线时间 + :param online_seconds: 在线时间（秒） + :return: 格式化后的在线时间字符串 + """ + total_oneline_time = timedelta(seconds=online_seconds) + + days = total_oneline_time.days + hours = total_oneline_time.seconds // 3600 + minutes = (total_oneline_time.seconds // 60) % 60 + seconds = total_oneline_time.seconds % 60 + if days > 0: + # 如果在线时间超过1天，则格式化为“X天X小时X分钟” + total_oneline_time_str = f"{total_oneline_time.days}天{hours}小时{minutes}分钟{seconds}秒" + elif hours > 0: + # 如果在线时间超过1小时，则格式化为“X小时X分钟X秒” + total_oneline_time_str = f"{hours}小时{minutes}分钟{seconds}秒" + else: + # 其他情况格式化为“X分钟X秒” + total_oneline_time_str = f"{minutes}分钟{seconds}秒" + + return total_oneline_time_str + + +class StatisticOutputTask(AsyncTask): + """统计输出任务""" + + SEP_LINE = "-" * 84 + + def __init__(self, record_file_path: str = "maibot_statistics.html"): + # 延迟300秒启动，运行间隔300秒 + super().__init__(task_name="Statistics Data Output Task", wait_before_start=0, run_interval=300) + + self.name_mapping: Dict[str, Tuple[str, float]] = {} + """ + 联系人/群聊名称映射 {聊天ID: (联系人/群聊名称, 记录时间（timestamp）)} + 注：设计记录时间的目的是方便更新名称，使联系人/群聊名称保持最新 + """ + + self.record_file_path: str = record_file_path + """ + 记录文件路径 + """ + + now = datetime.now() + if "deploy_time" in local_storage: + # 如果存在部署时间，则使用该时间作为全量统计的起始时间 + deploy_time = datetime.fromtimestamp(local_storage["deploy_time"]) + else: + # 否则，使用最大时间范围，并记录部署时间为当前时间 + deploy_time = datetime(2000, 1, 1) + local_storage["deploy_time"] = now.timestamp() + + self.stat_period: List[Tuple[str, timedelta, str]] = [ + ("all_time", now - deploy_time, "自部署以来"), # 必须保留“all_time” + ("last_7_days", timedelta(days=7), "最近7天"), + ("last_24_hours", timedelta(days=1), "最近24小时"), + ("last_hour", timedelta(hours=1), "最近1小时"), + ] + """ + 统计时间段 [(统计名称, 统计时间段, 统计描述), ...] + """ + + def _statistic_console_output(self, stats: Dict[str, Any], now: datetime): + """ + 输出统计数据到控制台 + :param stats: 统计数据 + :param now: 基准当前时间 + """ + # 输出最近一小时的统计数据 + + output = [ + self.SEP_LINE, + f" 最近1小时的统计数据 (自{now.strftime('%Y-%m-%d %H:%M:%S')}开始，详细信息见文件：{self.record_file_path})", + self.SEP_LINE, + self._format_total_stat(stats["last_hour"]), + "", + self._format_model_classified_stat(stats["last_hour"]), + "", + self._format_chat_stat(stats["last_hour"]), + self.SEP_LINE, + "", + ] + + logger.info("\n" + "\n".join(output)) + + async def run(self): + try: + now = datetime.now() + # 收集统计数据 + stats = self._collect_all_statistics(now) + + # 输出统计数据到控制台 + self._statistic_console_output(stats, now) + # 输出统计数据到html文件 + self._generate_html_report(stats, now) + except Exception as e: + logger.exception(f"输出统计数据过程中发生异常，错误信息：{e}") + + # -- 以下为统计数据收集方法 -- @staticmethod - def _record_online_time(): - """记录在线时间""" - current_time = datetime.now() - # 检查5分钟内是否已有记录 - recent_record = db.online_time.find_one({"timestamp": {"$gte": current_time - timedelta(minutes=5)}}) - - if not recent_record: - db.online_time.insert_one( - { - "timestamp": current_time, - "duration": 5, # 5分钟 - } - ) - - def _collect_statistics_for_period(self, start_time: datetime) -> Dict[str, Any]: - """收集指定时间段的LLM请求统计数据 - - Args: - start_time: 统计开始时间 + def _collect_model_request_for_period(collect_period: List[Tuple[str, datetime]]) -> Dict[str, Any]: """ + 收集指定时间段的LLM请求统计数据 + + :param collect_period: 统计时间段 + """ + if len(collect_period) <= 0: + return {} + else: + # 排序-按照时间段开始时间降序排列（最晚的时间段在前） + collect_period.sort(key=lambda x: x[1], reverse=True) + stats = { - "total_requests": 0, - "requests_by_type": defaultdict(int), - "requests_by_user": defaultdict(int), - "requests_by_model": defaultdict(int), - "average_tokens": 0, - "total_tokens": 0, - "total_cost": 0.0, - "costs_by_user": defaultdict(float), - "costs_by_type": defaultdict(float), - "costs_by_model": defaultdict(float), - # 新增token统计字段 - "tokens_by_type": defaultdict(int), - "tokens_by_user": defaultdict(int), - "tokens_by_model": defaultdict(int), - # 新增在线时间统计 - "online_time_minutes": 0, - # 新增消息统计字段 - "total_messages": 0, - "messages_by_user": defaultdict(int), - "messages_by_chat": defaultdict(int), + period_key: { + # 总LLM请求数 + TOTAL_REQ_CNT: 0, + # 请求次数统计 + REQ_CNT_BY_TYPE: defaultdict(int), + REQ_CNT_BY_USER: defaultdict(int), + REQ_CNT_BY_MODEL: defaultdict(int), + # 输入Token数 + IN_TOK_BY_TYPE: defaultdict(int), + IN_TOK_BY_USER: defaultdict(int), + IN_TOK_BY_MODEL: defaultdict(int), + # 输出Token数 + OUT_TOK_BY_TYPE: defaultdict(int), + OUT_TOK_BY_USER: defaultdict(int), + OUT_TOK_BY_MODEL: defaultdict(int), + # 总Token数 + TOTAL_TOK_BY_TYPE: defaultdict(int), + TOTAL_TOK_BY_USER: defaultdict(int), + TOTAL_TOK_BY_MODEL: defaultdict(int), + # 总开销 + TOTAL_COST: 0.0, + # 请求开销统计 + COST_BY_TYPE: defaultdict(float), + COST_BY_USER: defaultdict(float), + COST_BY_MODEL: defaultdict(float), + } + for period_key, _ in collect_period } - cursor = db.llm_usage.find({"timestamp": {"$gte": start_time}}) - total_requests = 0 + # 以最早的时间戳为起始时间获取记录 + for record in db.llm_usage.find({"timestamp": {"$gte": collect_period[-1][1]}}): + record_timestamp = record.get("timestamp") + for idx, (_, period_start) in enumerate(collect_period): + if record_timestamp >= period_start: + # 如果记录时间在当前时间段内，则它一定在更早的时间段内 + # 因此，我们可以直接跳过更早的时间段的判断，直接更新当前以及更早时间段的统计数据 + for period_key, _ in collect_period[idx:]: + stats[period_key][TOTAL_REQ_CNT] += 1 - for doc in cursor: - stats["total_requests"] += 1 - request_type = doc.get("request_type", "unknown") - user_id = str(doc.get("user_id", "unknown")) - model_name = doc.get("model_name", "unknown") + request_type = record.get("request_type", "unknown") # 请求类型 + user_id = str(record.get("user_id", "unknown")) # 用户ID + model_name = record.get("model_name", "unknown") # 模型名称 - stats["requests_by_type"][request_type] += 1 - stats["requests_by_user"][user_id] += 1 - stats["requests_by_model"][model_name] += 1 + stats[period_key][REQ_CNT_BY_TYPE][request_type] += 1 + stats[period_key][REQ_CNT_BY_USER][user_id] += 1 + stats[period_key][REQ_CNT_BY_MODEL][model_name] += 1 - prompt_tokens = doc.get("prompt_tokens", 0) - completion_tokens = doc.get("completion_tokens", 0) - total_tokens = prompt_tokens + completion_tokens - stats["tokens_by_type"][request_type] += total_tokens - stats["tokens_by_user"][user_id] += total_tokens - stats["tokens_by_model"][model_name] += total_tokens - stats["total_tokens"] += total_tokens + prompt_tokens = record.get("prompt_tokens", 0) # 输入Token数 + completion_tokens = record.get("completion_tokens", 0) # 输出Token数 + total_tokens = prompt_tokens + completion_tokens # Token总数 = 输入Token数 + 输出Token数 - cost = doc.get("cost", 0.0) - stats["total_cost"] += cost - stats["costs_by_user"][user_id] += cost - stats["costs_by_type"][request_type] += cost - stats["costs_by_model"][model_name] += cost + stats[period_key][IN_TOK_BY_TYPE][request_type] += prompt_tokens + stats[period_key][IN_TOK_BY_USER][user_id] += prompt_tokens + stats[period_key][IN_TOK_BY_MODEL][model_name] += prompt_tokens - total_requests += 1 + stats[period_key][OUT_TOK_BY_TYPE][request_type] += completion_tokens + stats[period_key][OUT_TOK_BY_USER][user_id] += completion_tokens + stats[period_key][OUT_TOK_BY_MODEL][model_name] += completion_tokens - if total_requests > 0: - stats["average_tokens"] = stats["total_tokens"] / total_requests + stats[period_key][TOTAL_TOK_BY_TYPE][request_type] += total_tokens + stats[period_key][TOTAL_TOK_BY_USER][user_id] += total_tokens + stats[period_key][TOTAL_TOK_BY_MODEL][model_name] += total_tokens - # 统计在线时间 - online_time_cursor = db.online_time.find({"timestamp": {"$gte": start_time}}) - for doc in online_time_cursor: - stats["online_time_minutes"] += doc.get("duration", 0) - - # 统计消息量 - messages_cursor = db.messages.find({"time": {"$gte": start_time.timestamp()}}) - for doc in messages_cursor: - stats["total_messages"] += 1 - # user_id = str(doc.get("user_info", {}).get("user_id", "unknown")) - chat_info = doc.get("chat_info", {}) - user_info = doc.get("user_info", {}) - user_id = str(user_info.get("user_id", "unknown")) - message_time = doc.get("time", 0) - group_info = chat_info.get("group_info") if chat_info else {} - # print(f"group_info: {group_info}") - group_name = None - if group_info: - group_id = f"g{group_info.get('group_id')}" - group_name = group_info.get("group_name", f"群{group_info.get('group_id')}") - if user_info and not group_name: - group_id = f"u{user_info['user_id']}" - group_name = user_info["user_nickname"] - if self.name_dict.get(group_id): - if message_time > self.name_dict.get(group_id)[1]: - self.name_dict[group_id] = [group_name, message_time] - else: - self.name_dict[group_id] = [group_name, message_time] - # print(f"group_name: {group_name}") - stats["messages_by_user"][user_id] += 1 - stats["messages_by_chat"][group_id] += 1 + cost = record.get("cost", 0.0) + stats[period_key][TOTAL_COST] += cost + stats[period_key][COST_BY_TYPE][request_type] += cost + stats[period_key][COST_BY_USER][user_id] += cost + stats[period_key][COST_BY_MODEL][model_name] += cost + break # 取消更早时间段的判断 return stats - def _collect_all_statistics(self) -> Dict[str, Dict[str, Any]]: - """收集所有时间范围的统计数据""" - now = datetime.now() - # 使用2000年1月1日作为"所有时间"的起始时间，这是一个更合理的起始点 - all_time_start = datetime(2000, 1, 1) + @staticmethod + def _collect_online_time_for_period(collect_period: List[Tuple[str, datetime]], now: datetime) -> Dict[str, Any]: + """ + 收集指定时间段的在线时间统计数据 - return { - "all_time": self._collect_statistics_for_period(all_time_start), - "last_7_days": self._collect_statistics_for_period(now - timedelta(days=7)), - "last_24_hours": self._collect_statistics_for_period(now - timedelta(days=1)), - "last_hour": self._collect_statistics_for_period(now - timedelta(hours=1)), + :param collect_period: 统计时间段 + """ + if len(collect_period) <= 0: + return {} + else: + # 排序-按照时间段开始时间降序排列（最晚的时间段在前） + collect_period.sort(key=lambda x: x[1], reverse=True) + + stats = { + period_key: { + # 在线时间统计 + ONLINE_TIME: 0.0, + } + for period_key, _ in collect_period } - def _format_stats_section(self, stats: Dict[str, Any], title: str) -> str: - """格式化统计部分的输出""" - output = ["\n" + "-" * 84, f"{title}", "-" * 84, f"总请求数: {stats['total_requests']}"] + # 统计在线时间 + for record in db.online_time.find({"end_timestamp": {"$gte": collect_period[-1][1]}}): + end_timestamp: datetime = record.get("end_timestamp") + for idx, (_, period_start) in enumerate(collect_period): + if end_timestamp >= period_start: + # 由于end_timestamp会超前标记时间，所以我们需要判断是否晚于当前时间，如果是，则使用当前时间作为结束时间 + if end_timestamp > now: + end_timestamp = now + # 如果记录时间在当前时间段内，则它一定在更早的时间段内 + # 因此，我们可以直接跳过更早的时间段的判断，直接更新当前以及更早时间段的统计数据 + for period_key, _period_start in collect_period[idx:]: + start_timestamp: datetime = record.get("start_timestamp") + if start_timestamp < _period_start: + # 如果开始时间在查询边界之前，则使用开始时间 + stats[period_key][ONLINE_TIME] += (end_timestamp - _period_start).total_seconds() + else: + # 否则，使用开始时间 + stats[period_key][ONLINE_TIME] += (end_timestamp - start_timestamp).total_seconds() + break # 取消更早时间段的判断 - if stats["total_requests"] > 0: - output.append(f"总Token数: {stats['total_tokens']}") - output.append(f"总花费: {stats['total_cost']:.4f}¥") - output.append(f"在线时间: {stats['online_time_minutes']}分钟") - output.append(f"总消息数: {stats['total_messages']}\n") + return stats - data_fmt = "{:<32} {:>10} {:>14} {:>13.4f} ¥" + def _collect_message_count_for_period(self, collect_period: List[Tuple[str, datetime]]) -> Dict[str, Any]: + """ + 收集指定时间段的消息统计数据 - # 按模型统计 - output.append("按模型统计:") - output.append("模型名称 调用次数 Token总量 累计花费") - for model_name, count in sorted(stats["requests_by_model"].items()): - tokens = stats["tokens_by_model"][model_name] - cost = stats["costs_by_model"][model_name] - output.append( - data_fmt.format(model_name[:30] + ".." if len(model_name) > 32 else model_name, count, tokens, cost) - ) - output.append("") + :param collect_period: 统计时间段 + """ + if len(collect_period) <= 0: + return {} + else: + # 排序-按照时间段开始时间降序排列（最晚的时间段在前） + collect_period.sort(key=lambda x: x[1], reverse=True) - # 按请求类型统计 - output.append("按请求类型统计:") - output.append("模型名称 调用次数 Token总量 累计花费") - for req_type, count in sorted(stats["requests_by_type"].items()): - tokens = stats["tokens_by_type"][req_type] - cost = stats["costs_by_type"][req_type] - output.append( - data_fmt.format(req_type[:22] + ".." if len(req_type) > 24 else req_type, count, tokens, cost) - ) - output.append("") + stats = { + period_key: { + # 消息统计 + TOTAL_MSG_CNT: 0, + MSG_CNT_BY_CHAT: defaultdict(int), + } + for period_key, _ in collect_period + } - # 修正用户统计列宽 - output.append("按用户统计:") - output.append("用户ID 调用次数 Token总量 累计花费") - for user_id, count in sorted(stats["requests_by_user"].items()): - tokens = stats["tokens_by_user"][user_id] - cost = stats["costs_by_user"][user_id] - output.append( - data_fmt.format( - user_id[:22], # 不再添加省略号，保持原始ID - count, - tokens, - cost, - ) - ) - output.append("") + # 统计消息量 + for message in db.messages.find({"time": {"$gte": collect_period[-1][1].timestamp()}}): + chat_info = message.get("chat_info", None) # 聊天信息 + user_info = message.get("user_info", None) # 用户信息（消息发送人） + message_time = message.get("time", 0) # 消息时间 - # 添加聊天统计 - output.append("群组统计:") - output.append("群组名称 消息数量") - for group_id, count in sorted(stats["messages_by_chat"].items()): - output.append(f"{self.name_dict[group_id][0][:32]:<32} {count:>10}") + group_info = chat_info.get("group_info") if chat_info else None # 尝试获取群聊信息 + if group_info is not None: + # 若有群聊信息 + chat_id = f"g{group_info.get('group_id')}" + chat_name = group_info.get("group_name", f"群{group_info.get('group_id')}") + elif user_info: + # 若没有群聊信息，则尝试获取用户信息 + chat_id = f"u{user_info['user_id']}" + chat_name = user_info["user_nickname"] + else: + continue # 如果没有群组信息也没有用户信息，则跳过 - return "\n".join(output) + if chat_id in self.name_mapping: + if chat_name != self.name_mapping[chat_id][0] and message_time > self.name_mapping[chat_id][1]: + # 如果用户名称不同，且新消息时间晚于之前记录的时间，则更新用户名称 + self.name_mapping[chat_id] = (chat_name, message_time) + else: + self.name_mapping[chat_id] = (chat_name, message_time) - def _format_stats_section_lite(self, stats: Dict[str, Any], title: str) -> str: - """格式化统计部分的输出""" - output = ["\n" + "-" * 84, f"{title}", "-" * 84] + for idx, (_, period_start) in enumerate(collect_period): + if message_time >= period_start.timestamp(): + # 如果记录时间在当前时间段内，则它一定在更早的时间段内 + # 因此，我们可以直接跳过更早的时间段的判断，直接更新当前以及更早时间段的统计数据 + for period_key, _ in collect_period[idx:]: + stats[period_key][TOTAL_MSG_CNT] += 1 + stats[period_key][MSG_CNT_BY_CHAT][chat_id] += 1 + break - # output.append(f"总请求数: {stats['total_requests']}") - if stats["total_requests"] > 0: - # output.append(f"总Token数: {stats['total_tokens']}") - output.append(f"总花费: {stats['total_cost']:.4f}¥") - # output.append(f"在线时间: {stats['online_time_minutes']}分钟") - output.append(f"总消息数: {stats['total_messages']}\n") + return stats - data_fmt = "{:<32} {:>10} {:>14} {:>13.4f} ¥" + def _collect_all_statistics(self, now: datetime) -> Dict[str, Dict[str, Any]]: + """ + 收集各时间段的统计数据 + :param now: 基准当前时间 + """ - # 按模型统计 - output.append("按模型统计:") - output.append("模型名称 调用次数 Token总量 累计花费") - for model_name, count in sorted(stats["requests_by_model"].items()): - tokens = stats["tokens_by_model"][model_name] - cost = stats["costs_by_model"][model_name] - output.append( - data_fmt.format(model_name[:30] + ".." if len(model_name) > 32 else model_name, count, tokens, cost) - ) - output.append("") + last_all_time_stat = None - # 按请求类型统计 - # output.append("按请求类型统计:") - # output.append(("模型名称 调用次数 Token总量 累计花费")) - # for req_type, count in sorted(stats["requests_by_type"].items()): - # tokens = stats["tokens_by_type"][req_type] - # cost = stats["costs_by_type"][req_type] - # output.append( - # data_fmt.format(req_type[:22] + ".." if len(req_type) > 24 else req_type, count, tokens, cost) - # ) - # output.append("") + if "last_full_statistics_timestamp" in local_storage and "last_full_statistics" in local_storage: + # 若存有上次完整统计的时间戳，则使用该时间戳作为"所有时间"的起始时间，进行增量统计 + last_full_stat_ts: float = local_storage["last_full_statistics_timestamp"] + last_all_time_stat = local_storage["last_full_statistics"] + self.stat_period = [item for item in self.stat_period if item[0] != "all_time"] # 删除"所有时间"的统计时段 + self.stat_period.append(("all_time", now - datetime.fromtimestamp(last_full_stat_ts), "自部署以来的")) - # 修正用户统计列宽 - # output.append("按用户统计:") - # output.append(("用户ID 调用次数 Token总量 累计花费")) - # for user_id, count in sorted(stats["requests_by_user"].items()): - # tokens = stats["tokens_by_user"][user_id] - # cost = stats["costs_by_user"][user_id] - # output.append( - # data_fmt.format( - # user_id[:22], # 不再添加省略号，保持原始ID - # count, - # tokens, - # cost, - # ) - # ) - # output.append("") + stat_start_timestamp = [(period[0], now - period[1]) for period in self.stat_period] - # 添加聊天统计 - output.append("群组统计:") - output.append("群组名称 消息数量") - for group_id, count in sorted(stats["messages_by_chat"].items()): - output.append(f"{self.name_dict[group_id][0][:32]:<32} {count:>10}") + stat = {item[0]: {} for item in self.stat_period} - return "\n".join(output) + model_req_stat = self._collect_model_request_for_period(stat_start_timestamp) + online_time_stat = self._collect_online_time_for_period(stat_start_timestamp, now) + message_count_stat = self._collect_message_count_for_period(stat_start_timestamp) - def _save_statistics(self, all_stats: Dict[str, Dict[str, Any]]): - """将统计结果保存到文件""" - current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + # 统计数据合并 + # 合并三类统计数据 + for period_key, _ in stat_start_timestamp: + stat[period_key].update(model_req_stat[period_key]) + stat[period_key].update(online_time_stat[period_key]) + stat[period_key].update(message_count_stat[period_key]) - output = [f"LLM请求统计报告 (生成时间: {current_time})"] + if last_all_time_stat: + # 若存在上次完整统计数据，则将其与当前统计数据合并 + for key, val in last_all_time_stat.items(): + if isinstance(val, dict): + # 是字典类型，则进行合并 + for sub_key, sub_val in val.items(): + stat["all_time"][key][sub_key] += sub_val + else: + # 直接合并 + stat["all_time"][key] += val - # 添加各个时间段的统计 - sections = [ - ("所有时间统计", "all_time"), - ("最近7天统计", "last_7_days"), - ("最近24小时统计", "last_24_hours"), - ("最近1小时统计", "last_hour"), + # 更新上次完整统计数据的时间戳 + local_storage["last_full_statistics_timestamp"] = now.timestamp() + # 更新上次完整统计数据 + local_storage["last_full_statistics"] = stat["all_time"] + + return stat + + # -- 以下为统计数据格式化方法 -- + + @staticmethod + def _format_total_stat(stats: Dict[str, Any]) -> str: + """ + 格式化总统计数据 + """ + + output = [ + f"总在线时间: {_format_online_time(stats[ONLINE_TIME])}", + f"总消息数: {stats[TOTAL_MSG_CNT]}", + f"总请求数: {stats[TOTAL_REQ_CNT]}", + f"总花费: {stats[TOTAL_COST]:.4f}¥", + "", ] - for title, key in sections: - output.append(self._format_stats_section(all_stats[key], title)) + return "\n".join(output) - # 写入文件 - with open(self.output_file, "w", encoding="utf-8") as f: - f.write("\n".join(output)) + @staticmethod + def _format_model_classified_stat(stats: Dict[str, Any]) -> str: + """ + 格式化按模型分类的统计数据 + """ + if stats[TOTAL_REQ_CNT] > 0: + data_fmt = "{:<32} {:>10} {:>12} {:>12} {:>12} {:>9.4f}¥" - def _console_output_loop(self): - """控制台输出循环，每5分钟输出一次最近1小时的统计""" - while self.running: - # 等待5分钟 - for _ in range(300): # 5分钟 = 300秒 - if not self.running: - break - time.sleep(1) - try: - # 收集最近1小时的统计数据 - now = datetime.now() - hour_stats = self._collect_statistics_for_period(now - timedelta(hours=1)) + output = [ + "按模型分类统计:", + " 模型名称 调用次数 输入Token 输出Token Token总量 累计花费", + ] + for model_name, count in sorted(stats[REQ_CNT_BY_MODEL].items()): + name = model_name[:29] + "..." if len(model_name) > 32 else model_name + in_tokens = stats[IN_TOK_BY_MODEL][model_name] + out_tokens = stats[OUT_TOK_BY_MODEL][model_name] + tokens = stats[TOTAL_TOK_BY_MODEL][model_name] + cost = stats[COST_BY_MODEL][model_name] + output.append(data_fmt.format(name, count, in_tokens, out_tokens, tokens, cost)) - # 使用logger输出 - stats_output = self._format_stats_section_lite( - hour_stats, "最近1小时统计：详细信息见根目录文件：llm_statistics.txt" + output.append("") + return "\n".join(output) + else: + return "" + + def _format_chat_stat(self, stats: Dict[str, Any]) -> str: + """ + 格式化聊天统计数据 + """ + if stats[TOTAL_MSG_CNT] > 0: + output = ["聊天消息统计:", " 联系人/群组名称 消息数量"] + for chat_id, count in sorted(stats[MSG_CNT_BY_CHAT].items()): + output.append(f"{self.name_mapping[chat_id][0][:32]:<32} {count:>10}") + + output.append("") + return "\n".join(output) + else: + return "" + + def _generate_html_report(self, stat: dict[str, Any], now: datetime): + """ + 生成HTML格式的统计报告 + :param stat: 统计数据 + :param now: 基准当前时间 + :return: HTML格式的统计报告 + """ + + tab_list = [ + f'' + for period in self.stat_period + ] + + def _format_stat_data(stat_data: dict[str, Any], div_id: str, start_time: datetime) -> str: + """ + 格式化一个时间段的统计数据到html div块 + :param stat_data: 统计数据 + :param div_id: div的ID + :param start_time: 统计时间段开始时间 + """ + # format总在线时间 + + # 生成HTML + return f""" +
+

+ 统计时段: + {start_time.strftime("%Y-%m-%d %H:%M:%S")} ~ {now.strftime("%Y-%m-%d %H:%M:%S")} +

+

总在线时间: {_format_online_time(stat_data[ONLINE_TIME])}

+

总消息数: {stat_data[TOTAL_MSG_CNT]}

+

总请求数: {stat_data[TOTAL_REQ_CNT]}

+

总花费: {stat_data[TOTAL_COST]:.4f} ¥

+ +

按模型分类统计

+ + + + { + "\n".join( + [ + f"" + f"" + f"" + f"" + f"" + f"" + f"" + f"" + for model_name, count in sorted(stat_data[REQ_CNT_BY_MODEL].items()) + ] ) - logger.info("\n" + stats_output + "\n" + "=" * 50) + } + +
模型名称调用次数输入Token输出TokenToken总量累计花费
{model_name}{count}{stat_data[IN_TOK_BY_MODEL][model_name]}{stat_data[OUT_TOK_BY_MODEL][model_name]}{stat_data[TOTAL_TOK_BY_MODEL][model_name]}{stat_data[COST_BY_MODEL][model_name]:.4f} ¥
+ +

按请求类型分类统计

+ + + + + + { + "\n".join( + [ + f"" + f"" + f"" + f"" + f"" + f"" + f"" + f"" + for req_type, count in sorted(stat_data[REQ_CNT_BY_TYPE].items()) + ] + ) + } + +
请求类型调用次数输入Token输出TokenToken总量累计花费
{req_type}{count}{stat_data[IN_TOK_BY_TYPE][req_type]}{stat_data[OUT_TOK_BY_TYPE][req_type]}{stat_data[TOTAL_TOK_BY_TYPE][req_type]}{stat_data[COST_BY_TYPE][req_type]:.4f} ¥
+ +

按用户分类统计

+ + + + + + { + "\n".join( + [ + f"" + f"" + f"" + f"" + f"" + f"" + f"" + f"" + for user_id, count in sorted(stat_data[REQ_CNT_BY_USER].items()) + ] + ) + } + +
用户名称调用次数输入Token输出TokenToken总量累计花费
{user_id}{count}{stat_data[IN_TOK_BY_USER][user_id]}{stat_data[OUT_TOK_BY_USER][user_id]}{stat_data[TOTAL_TOK_BY_USER][user_id]}{stat_data[COST_BY_USER][user_id]:.4f} ¥
+ +

聊天消息统计

+ + + + + + { + "\n".join( + [ + f"" + for chat_id, count in sorted(stat_data[MSG_CNT_BY_CHAT].items()) + ] + ) + } + +
联系人/群组名称消息数量
{self.name_mapping[chat_id][0]}{count}
+
+ """ - except Exception: - logger.exception("控制台统计数据输出失败") + tab_content_list = [ + _format_stat_data(stat[period[0]], period[0], now - period[1]) + for period in self.stat_period + if period[0] != "all_time" + ] - def _stats_loop(self): - """统计循环，每5分钟运行一次""" - while self.running: - try: - # 记录在线时间 - self._record_online_time() - # 收集并保存统计数据 - all_stats = self._collect_all_statistics() - self._save_statistics(all_stats) - except Exception: - logger.exception("统计数据处理失败") + tab_content_list.append( + _format_stat_data(stat["all_time"], "all_time", datetime.fromtimestamp(local_storage["deploy_time"])) + ) - # 等待5分钟 - for _ in range(300): # 5分钟 = 300秒 - if not self.running: - break - time.sleep(1) + html_template = ( + """ + + + + + + MaiBot运行统计报告 + + + +""" + + f""" +
+

MaiBot运行统计报告

+

统计截止时间: {now.strftime("%Y-%m-%d %H:%M:%S")}

+ +
+ {"\n".join(tab_list)} +
+ + {"\n".join(tab_content_list)} +
+""" + + """ + + + + """ + ) + + with open(self.record_file_path, "w", encoding="utf-8") as f: + f.write(html_template)