import asyncio import time import traceback import random from typing import List, Optional, Dict, Any from rich.traceback import install from src.config.config import global_config from src.common.logger import get_logger from src.chat.message_receive.chat_stream import ChatStream, get_chat_manager from src.chat.utils.prompt_builder import global_prompt_manager from src.chat.utils.timer_calculator import Timer from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_chat from src.chat.planner_actions.planner import ActionPlanner from src.chat.planner_actions.action_modifier import ActionModifier from src.chat.planner_actions.action_manager import ActionManager from src.chat.chat_loop.hfc_utils import CycleDetail from src.person_info.relationship_builder_manager import relationship_builder_manager from src.person_info.person_info import get_person_info_manager from src.plugin_system.base.component_types import ActionInfo, ChatMode from src.plugin_system.apis import generator_api, send_api, message_api from src.chat.willing.willing_manager import get_willing_manager from src.mais4u.mai_think import mai_thinking_manager from maim_message.message_base import GroupInfo from src.mais4u.constant_s4u import ENABLE_S4U ERROR_LOOP_INFO = { "loop_plan_info": { "action_result": { "action_type": "error", "action_data": {}, "reasoning": "循环处理失败", }, }, "loop_action_info": { "action_taken": False, "reply_text": "", "command": "", "taken_time": time.time(), }, } NO_ACTION = { "action_result": { "action_type": "no_action", "action_data": {}, "reasoning": "规划器初始化默认", "is_parallel": True, }, "chat_context": "", "action_prompt": "", } install(extra_lines=3) # 注释：原来的动作修改超时常量已移除，因为改为顺序执行 logger = get_logger("hfc") # Logger Name Changed class HeartFChatting: """ 管理一个连续的Focus Chat循环 用于在特定聊天流中生成回复。 其生命周期现在由其关联的 SubHeartflow 的 FOCUSED 状态控制。 """ def __init__( self, chat_id: str, ): """ HeartFChatting 初始化函数 参数: chat_id: 聊天流唯一标识符(如stream_id) on_stop_focus_chat: 当收到stop_focus_chat命令时调用的回调函数 performance_version: 性能记录版本号，用于区分不同启动版本 """ # 基础属性 self.stream_id: str = chat_id # 聊天流ID self.chat_stream: ChatStream = get_chat_manager().get_stream(self.stream_id) # type: ignore if not self.chat_stream: raise ValueError(f"无法找到聊天流: {self.stream_id}") self.log_prefix = f"[{get_chat_manager().get_stream_name(self.stream_id) or self.stream_id}]" self.relationship_builder = relationship_builder_manager.get_or_create_builder(self.stream_id) self.loop_mode = ChatMode.NORMAL # 初始循环模式为普通模式 self.action_manager = ActionManager() self.action_planner = ActionPlanner(chat_id=self.stream_id, action_manager=self.action_manager) self.action_modifier = ActionModifier(action_manager=self.action_manager, chat_id=self.stream_id) # 循环控制内部状态 self.running: bool = False self._loop_task: Optional[asyncio.Task] = None # 主循环任务 self._energy_task: Optional[asyncio.Task] = None # 添加循环信息管理相关的属性 self.history_loop: List[CycleDetail] = [] self._cycle_counter = 0 self._current_cycle_detail: CycleDetail = None # type: ignore self.reply_timeout_count = 0 self.plan_timeout_count = 0 self.last_read_time = time.time() - 1 self.willing_manager = get_willing_manager() logger.info(f"{self.log_prefix} HeartFChatting 初始化完成") self.energy_value = 5 async def start(self): """检查是否需要启动主循环，如果未激活则启动。""" # 如果循环已经激活，直接返回 if self.running: logger.debug(f"{self.log_prefix} HeartFChatting 已激活，无需重复启动") return try: # 标记为活动状态，防止重复启动 self.running = True self._energy_task = asyncio.create_task(self._energy_loop()) self._energy_task.add_done_callback(self._handle_energy_completion) self._loop_task = asyncio.create_task(self._main_chat_loop()) self._loop_task.add_done_callback(self._handle_loop_completion) logger.info(f"{self.log_prefix} HeartFChatting 启动完成") except Exception as e: # 启动失败时重置状态 self.running = False self._loop_task = None logger.error(f"{self.log_prefix} HeartFChatting 启动失败: {e}") raise def _handle_loop_completion(self, task: asyncio.Task): """当 _hfc_loop 任务完成时执行的回调。""" try: if exception := task.exception(): logger.error(f"{self.log_prefix} HeartFChatting: 脱离了聊天(异常): {exception}") logger.error(traceback.format_exc()) # Log full traceback for exceptions else: logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天 (外部停止)") except asyncio.CancelledError: logger.info(f"{self.log_prefix} HeartFChatting: 结束了聊天") def start_cycle(self): self._cycle_counter += 1 self._current_cycle_detail = CycleDetail(self._cycle_counter) self._current_cycle_detail.thinking_id = f"tid{str(round(time.time(), 2))}" cycle_timers = {} return cycle_timers, self._current_cycle_detail.thinking_id def end_cycle(self, loop_info, cycle_timers): self._current_cycle_detail.set_loop_info(loop_info) self.history_loop.append(self._current_cycle_detail) self._current_cycle_detail.timers = cycle_timers self._current_cycle_detail.end_time = time.time() def _handle_energy_completion(self, task: asyncio.Task): if exception := task.exception(): logger.error(f"{self.log_prefix} HeartFChatting: 能量循环异常: {exception}") logger.error(traceback.format_exc()) else: logger.info(f"{self.log_prefix} HeartFChatting: 能量循环完成") async def _energy_loop(self): while self.running: await asyncio.sleep(10) if self.loop_mode == ChatMode.NORMAL: self.energy_value -= 0.3 self.energy_value = max(self.energy_value, 0.3) if self.loop_mode == ChatMode.FOCUS: self.energy_value -= 0.6 self.energy_value = max(self.energy_value, 0.3) def print_cycle_info(self, cycle_timers): # 记录循环信息和计时器结果 timer_strings = [] for name, elapsed in cycle_timers.items(): formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒" timer_strings.append(f"{name}: {formatted_time}") logger.info( f"{self.log_prefix} 第{self._current_cycle_detail.cycle_id}次思考," f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒, " # type: ignore f"选择动作: {self._current_cycle_detail.loop_plan_info.get('action_result', {}).get('action_type', '未知动作')}" + (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "") ) async def _loopbody(self): if self.loop_mode == ChatMode.FOCUS: if await self._observe(): self.energy_value -= 1 / global_config.chat.focus_value else: self.energy_value -= 3 / global_config.chat.focus_value if self.energy_value <= 1: self.energy_value = 1 self.loop_mode = ChatMode.NORMAL return True return True elif self.loop_mode == ChatMode.NORMAL: new_messages_data = get_raw_msg_by_timestamp_with_chat( chat_id=self.stream_id, timestamp_start=self.last_read_time, timestamp_end=time.time(), limit=10, limit_mode="earliest", filter_bot=True, ) if global_config.chat.focus_value != 0: if len(new_messages_data) > 3 / pow(global_config.chat.focus_value,0.5): self.loop_mode = ChatMode.FOCUS self.energy_value = 10 + (len(new_messages_data) / (3 / pow(global_config.chat.focus_value,0.5))) * 10 return True if self.energy_value >= 30: self.loop_mode = ChatMode.FOCUS return True if new_messages_data: earliest_messages_data = new_messages_data[0] self.last_read_time = earliest_messages_data.get("time") if_think = await self.normal_response(earliest_messages_data) if if_think: factor = max(global_config.chat.focus_value, 0.1) self.energy_value *= 1.1 * factor logger.info(f"{self.log_prefix} 进行了思考，能量值按倍数增加，当前能量值：{self.energy_value:.1f}") else: self.energy_value += 0.1 * global_config.chat.focus_value logger.debug(f"{self.log_prefix} 没有进行思考，能量值线性增加，当前能量值：{self.energy_value:.1f}") logger.debug(f"{self.log_prefix} 当前能量值：{self.energy_value:.1f}") return True await asyncio.sleep(1) return True async def build_reply_to_str(self, message_data: dict): person_info_manager = get_person_info_manager() person_id = person_info_manager.get_person_id( message_data.get("chat_info_platform"), # type: ignore message_data.get("user_id"), # type: ignore ) person_name = await person_info_manager.get_value(person_id, "person_name") return f"{person_name}:{message_data.get('processed_plain_text')}" async def send_typing(self): group_info = GroupInfo(platform="amaidesu_default", group_id="114514", group_name="内心") chat = await get_chat_manager().get_or_create_stream( platform="amaidesu_default", user_info=None, group_info=group_info, ) await send_api.custom_to_stream( message_type="state", content="typing", stream_id=chat.stream_id, storage_message=False ) async def stop_typing(self): group_info = GroupInfo(platform="amaidesu_default", group_id="114514", group_name="内心") chat = await get_chat_manager().get_or_create_stream( platform="amaidesu_default", user_info=None, group_info=group_info, ) await send_api.custom_to_stream( message_type="state", content="stop_typing", stream_id=chat.stream_id, storage_message=False ) async def _observe(self, message_data: Optional[Dict[str, Any]] = None): # sourcery skip: hoist-statement-from-if, merge-comparisons, reintroduce-else if not message_data: message_data = {} action_type = "no_action" # 创建新的循环信息 cycle_timers, thinking_id = self.start_cycle() logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次思考[模式：{self.loop_mode}]") if ENABLE_S4U: await self.send_typing() async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()): loop_start_time = time.time() await self.relationship_builder.build_relation() available_actions = {} # 第一步：动作修改 with Timer("动作修改", cycle_timers): try: await self.action_modifier.modify_actions() available_actions = self.action_manager.get_using_actions() except Exception as e: logger.error(f"{self.log_prefix} 动作修改失败: {e}") # 如果normal，开始一个回复生成进程，先准备好回复（其实是和planer同时进行的） if self.loop_mode == ChatMode.NORMAL: reply_to_str = await self.build_reply_to_str(message_data) gen_task = asyncio.create_task(self._generate_response(message_data, available_actions, reply_to_str)) with Timer("规划器", cycle_timers): plan_result, target_message = await self.action_planner.plan(mode=self.loop_mode) action_result: dict = plan_result.get("action_result", {}) # type: ignore action_type, action_data, reasoning, is_parallel = ( action_result.get("action_type", "error"), action_result.get("action_data", {}), action_result.get("reasoning", "未提供理由"), action_result.get("is_parallel", True), ) action_data["loop_start_time"] = loop_start_time if self.loop_mode == ChatMode.NORMAL: if action_type == "no_action": logger.info(f"{self.log_prefix}{global_config.bot.nickname} 决定进行回复") elif is_parallel: logger.info( f"{self.log_prefix}{global_config.bot.nickname} 决定进行回复, 同时执行{action_type}动作" ) else: logger.info(f"{self.log_prefix}{global_config.bot.nickname} 决定执行{action_type}动作") if action_type == "no_action": # 等待回复生成完毕 gather_timeout = global_config.chat.thinking_timeout try: response_set = await asyncio.wait_for(gen_task, timeout=gather_timeout) except asyncio.TimeoutError: response_set = None if response_set: content = " ".join([item[1] for item in response_set if item[0] == "text"]) # 模型炸了，没有回复内容生成 if not response_set: logger.warning(f"{self.log_prefix}模型未生成回复内容") return False elif action_type not in ["no_action"] and not is_parallel: logger.info( f"{self.log_prefix}{global_config.bot.nickname} 原本想要回复：{content}，但选择执行{action_type}，不发表回复" ) return False logger.info(f"{self.log_prefix}{global_config.bot.nickname} 决定的回复内容: {content}") # 发送回复 (不再需要传入 chat) reply_text = await self._send_response(response_set, reply_to_str, loop_start_time,message_data) if ENABLE_S4U: await self.stop_typing() await mai_thinking_manager.get_mai_think(self.stream_id).do_think_after_response(reply_text) return True else: action_message: Dict[str, Any] = message_data or target_message # type: ignore # 动作执行计时 with Timer("动作执行", cycle_timers): success, reply_text, command = await self._handle_action( action_type, reasoning, action_data, cycle_timers, thinking_id, action_message ) loop_info = { "loop_plan_info": { "action_result": plan_result.get("action_result", {}), }, "loop_action_info": { "action_taken": success, "reply_text": reply_text, "command": command, "taken_time": time.time(), }, } if loop_info["loop_action_info"]["command"] == "stop_focus_chat": logger.info(f"{self.log_prefix} 麦麦决定停止专注聊天") return False # 停止该聊天模式的循环 self.end_cycle(loop_info, cycle_timers) self.print_cycle_info(cycle_timers) if self.loop_mode == ChatMode.NORMAL: await self.willing_manager.after_generate_reply_handle(message_data.get("message_id", "")) # 管理no_reply计数器：当执行了非no_reply动作时，重置计数器 if action_type != "no_reply" and action_type != "no_action": # 导入NoReplyAction并重置计数器 from src.plugins.built_in.core_actions.no_reply import NoReplyAction NoReplyAction.reset_consecutive_count() logger.info(f"{self.log_prefix} 执行了{action_type}动作，重置no_reply计数器") return True elif action_type == "no_action": # 当执行回复动作时，也重置no_reply计数器 from src.plugins.built_in.core_actions.no_reply import NoReplyAction NoReplyAction.reset_consecutive_count() logger.info(f"{self.log_prefix} 执行了回复动作，重置no_reply计数器") return True async def _main_chat_loop(self): """主循环，持续进行计划并可能回复消息，直到被外部取消。""" try: while self.running: # 主循环 success = await self._loopbody() await asyncio.sleep(0.1) if not success: break logger.info(f"{self.log_prefix} 麦麦已强制离开聊天") except asyncio.CancelledError: # 设置了关闭标志位后被取消是正常流程 logger.info(f"{self.log_prefix} 麦麦已关闭聊天") except Exception: logger.error(f"{self.log_prefix} 麦麦聊天意外错误") print(traceback.format_exc()) # 理论上不能到这里 logger.error(f"{self.log_prefix} 麦麦聊天意外错误，结束了聊天循环") async def _handle_action( self, action: str, reasoning: str, action_data: dict, cycle_timers: dict, thinking_id: str, action_message: dict, ) -> tuple[bool, str, str]: """ 处理规划动作，使用动作工厂创建相应的动作处理器 参数: action: 动作类型 reasoning: 决策理由 action_data: 动作数据，包含不同动作需要的参数 cycle_timers: 计时器字典 thinking_id: 思考ID 返回: tuple[bool, str, str]: (是否执行了动作, 思考消息ID, 命令) """ try: # 使用工厂创建动作处理器实例 try: action_handler = self.action_manager.create_action( action_name=action, action_data=action_data, reasoning=reasoning, cycle_timers=cycle_timers, thinking_id=thinking_id, chat_stream=self.chat_stream, log_prefix=self.log_prefix, action_message=action_message, ) except Exception as e: logger.error(f"{self.log_prefix} 创建动作处理器时出错: {e}") traceback.print_exc() return False, "", "" if not action_handler: logger.warning(f"{self.log_prefix} 未能创建动作处理器: {action}") return False, "", "" # 处理动作并获取结果 result = await action_handler.handle_action() success, reply_text = result command = "" if reply_text == "timeout": self.reply_timeout_count += 1 if self.reply_timeout_count > 5: logger.warning( f"[{self.log_prefix} ] 连续回复超时次数过多，{global_config.chat.thinking_timeout}秒 内大模型没有返回有效内容，请检查你的api是否速度过慢或配置错误。建议不要使用推理模型，推理模型生成速度过慢。或者尝试拉高thinking_timeout参数，这可能导致回复时间过长。" ) logger.warning(f"{self.log_prefix} 回复生成超时{global_config.chat.thinking_timeout}s，已跳过") return False, "", "" return success, reply_text, command except Exception as e: logger.error(f"{self.log_prefix} 处理{action}时出错: {e}") traceback.print_exc() return False, "", "" async def normal_response(self, message_data: dict) -> bool: """ 处理接收到的消息。 在"兴趣"模式下，判断是否回复并生成内容。 """ interested_rate = (message_data.get("interest_value") or 0.0) * global_config.chat.willing_amplifier self.willing_manager.setup(message_data, self.chat_stream) reply_probability = await self.willing_manager.get_reply_probability(message_data.get("message_id", "")) talk_frequency = -1.00 if reply_probability < 1: # 简化逻辑，如果未提及 (reply_probability 为 0)，则获取意愿概率 additional_config = message_data.get("additional_config", {}) if additional_config and "maimcore_reply_probability_gain" in additional_config: reply_probability += additional_config["maimcore_reply_probability_gain"] reply_probability = min(max(reply_probability, 0), 1) # 确保概率在 0-1 之间 talk_frequency = global_config.chat.get_current_talk_frequency(self.stream_id) reply_probability = talk_frequency * reply_probability # 处理表情包 if message_data.get("is_emoji") or message_data.get("is_picid"): reply_probability = 0 # 打印消息信息 mes_name = self.chat_stream.group_info.group_name if self.chat_stream.group_info else "私聊" # logger.info(f"[{mes_name}] 当前聊天频率: {talk_frequency:.2f},兴趣值: {interested_rate:.2f},回复概率: {reply_probability * 100:.1f}%") if reply_probability > 0.05: logger.info( f"[{mes_name}]" f"{message_data.get('user_nickname')}:" f"{message_data.get('processed_plain_text')}[兴趣:{interested_rate:.2f}][回复概率:{reply_probability * 100:.1f}%]" ) if random.random() < reply_probability: await self.willing_manager.before_generate_reply_handle(message_data.get("message_id", "")) await self._observe(message_data=message_data) return True # 意愿管理器：注销当前message信息 (无论是否回复，只要处理过就删除) self.willing_manager.delete(message_data.get("message_id", "")) return False async def _generate_response( self, message_data: dict, available_actions: Optional[Dict[str, ActionInfo]], reply_to: str ) -> Optional[list]: """生成普通回复""" try: success, reply_set, _ = await generator_api.generate_reply( chat_stream=self.chat_stream, reply_to=reply_to, available_actions=available_actions, enable_tool=global_config.tool.enable_in_normal_chat, request_type="chat.replyer.normal", ) if not success or not reply_set: logger.info(f"对 {message_data.get('processed_plain_text')} 的回复生成失败") return None return reply_set except Exception as e: logger.error(f"{self.log_prefix}回复生成出现错误：{str(e)} {traceback.format_exc()}") return None async def _send_response(self, reply_set, reply_to, thinking_start_time, message_data): current_time = time.time() new_message_count = message_api.count_new_messages( chat_id=self.chat_stream.stream_id, start_time=thinking_start_time, end_time=current_time ) platform = message_data.get("user_platform", "") user_id = message_data.get("user_id", "") reply_to_platform_id = f"{platform}:{user_id}" need_reply = new_message_count >= random.randint(2, 4) if need_reply: logger.info( f"{self.log_prefix} 从思考到回复，共有{new_message_count}条新消息，使用引用回复" ) else: logger.debug( f"{self.log_prefix} 从思考到回复，共有{new_message_count}条新消息，不使用引用回复" ) reply_text = "" first_replied = False for reply_seg in reply_set: data = reply_seg[1] if not first_replied: if need_reply: await send_api.text_to_stream( text=data, stream_id=self.chat_stream.stream_id, reply_to=reply_to, reply_to_platform_id=reply_to_platform_id, typing=False, ) else: await send_api.text_to_stream( text=data, stream_id=self.chat_stream.stream_id, reply_to_platform_id=reply_to_platform_id, typing=False, ) first_replied = True else: await send_api.text_to_stream( text=data, stream_id=self.chat_stream.stream_id, reply_to_platform_id=reply_to_platform_id, typing=True, ) reply_text += data return reply_text