import time import threading # 导入 threading from random import random import traceback import asyncio from typing import List, Dict from ..moods.moods import MoodManager from ...config.config import global_config from ..chat.emoji_manager import emoji_manager from .normal_chat_generator import ResponseGenerator from ..chat.message import MessageSending, MessageRecv, MessageThinking, MessageSet from ..chat.message_sender import message_manager from ..storage.storage import MessageStorage from ..chat.utils import is_mentioned_bot_in_message from ..chat.utils_image import image_path_to_base64 from ..willing.willing_manager import willing_manager from ..message import UserInfo, Seg from src.common.logger import get_module_logger, CHAT_STYLE_CONFIG, LogConfig 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_calculater import Timer from src.heart_flow.heartflow import heartflow from src.heart_flow.sub_heartflow import ChatState from src.heart_flow.heartflow import heartflow # 定义日志配置 chat_config = LogConfig( console_format=CHAT_STYLE_CONFIG["console_format"], file_format=CHAT_STYLE_CONFIG["file_format"], ) logger = get_module_logger("normal_chat", config=chat_config) class NormalChat: _instance = None _lock = threading.Lock() _initialized = False def __new__(cls, *args, **kwargs): if cls._instance is None: with cls._lock: # Double-check locking if cls._instance is None: cls._instance = super().__new__(cls) return cls._instance def __init__(self): # 防止重复初始化 if self._initialized: return with self.__class__._lock: # 使用类锁确保线程安全 if self._initialized: return logger.info("正在初始化 NormalChat 单例...") # 添加日志 self.storage = MessageStorage() self.gpt = ResponseGenerator() self.mood_manager = MoodManager.get_instance() # 用于存储每个 chat stream 的兴趣监控任务 self._interest_monitoring_tasks: Dict[str, asyncio.Task] = {} self._initialized = True logger.info("NormalChat 单例初始化完成。") # 添加日志 @classmethod def get_instance(cls): """获取 NormalChat 的单例实例。""" if cls._instance is None: # 如果实例还未创建（理论上应该在 main 中初始化，但作为备用） logger.warning("NormalChat 实例在首次 get_instance 时创建。") cls() # 调用构造函数来创建实例 return cls._instance @staticmethod async def _create_thinking_message(message, chat, userinfo, messageinfo): """创建思考消息""" bot_user_info = UserInfo( user_id=global_config.BOT_QQ, user_nickname=global_config.BOT_NICKNAME, platform=messageinfo.platform, ) thinking_time_point = round(time.time(), 2) thinking_id = "mt" + str(thinking_time_point) thinking_message = MessageThinking( message_id=thinking_id, chat_stream=chat, bot_user_info=bot_user_info, reply=message, thinking_start_time=thinking_time_point, ) message_manager.add_message(thinking_message) return thinking_id @staticmethod async def _send_response_messages(message, chat, response_set: List[str], thinking_id) -> MessageSending: """发送回复消息""" container = await message_manager.get_container(chat.stream_id) thinking_message = None for msg in container.messages[:]: if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id: thinking_message = msg container.messages.remove(msg) break if not thinking_message: logger.warning(f"[{chat.stream_id}] 未找到对应的思考消息 {thinking_id}，可能已超时被移除") return None thinking_start_time = thinking_message.thinking_start_time message_set = MessageSet(chat, thinking_id) mark_head = False first_bot_msg = None for msg in response_set: message_segment = Seg(type="text", data=msg) bot_message = MessageSending( message_id=thinking_id, chat_stream=chat, bot_user_info=UserInfo( user_id=global_config.BOT_QQ, user_nickname=global_config.BOT_NICKNAME, platform=message.message_info.platform, ), sender_info=message.message_info.user_info, message_segment=message_segment, reply=message, is_head=not mark_head, is_emoji=False, thinking_start_time=thinking_start_time, apply_set_reply_logic=True ) if not mark_head: mark_head = True first_bot_msg = bot_message message_set.add_message(bot_message) await message_manager.add_message(message_set) return first_bot_msg @staticmethod async def _handle_emoji(message, chat, response): """处理表情包""" if random() < global_config.emoji_chance: emoji_raw = await emoji_manager.get_emoji_for_text(response) if emoji_raw: emoji_path, description = emoji_raw emoji_cq = image_path_to_base64(emoji_path) thinking_time_point = round(message.message_info.time, 2) message_segment = Seg(type="emoji", data=emoji_cq) bot_message = MessageSending( message_id="mt" + str(thinking_time_point), chat_stream=chat, bot_user_info=UserInfo( user_id=global_config.BOT_QQ, user_nickname=global_config.BOT_NICKNAME, platform=message.message_info.platform, ), sender_info=message.message_info.user_info, message_segment=message_segment, reply=message, is_head=False, is_emoji=True, apply_set_reply_logic=True ) await message_manager.add_message(bot_message) async def _update_relationship(self, message: MessageRecv, response_set): """更新关系情绪""" ori_response = ",".join(response_set) stance, emotion = await self.gpt._get_emotion_tags(ori_response, message.processed_plain_text) await relationship_manager.calculate_update_relationship_value( chat_stream=message.chat_stream, label=emotion, stance=stance ) self.mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor) async def _find_interested_message(self, chat: ChatStream) -> None: # 此函数设计为后台任务，轮询指定 chat 的兴趣消息。 # 它通常由外部代码在 chat 流活跃时启动。 stream_id = chat.stream_id # 获取 stream_id # logger.info(f"[{stream_id}] 兴趣消息监控任务启动。") # 减少日志 while True: await asyncio.sleep(1) # 每秒检查一次 subheartflow = heartflow.get_subheartflow(stream_id) if not subheartflow or subheartflow.should_stop: # logger.info(f"[{stream_id}] SubHeartflow 不存在或已停止，兴趣消息监控任务退出。") # 减少日志 break interest_dict = subheartflow.get_interest_dict() items_to_process = list(interest_dict.items()) if not items_to_process: continue for msg_id, (message, interest_value, is_mentioned) in items_to_process: # --- 在处理前检查 SubHeartflow 的状态 --- # current_chat_state = subheartflow.chat_state.chat_status stream_name = chat_manager.get_stream_name(stream_id) or stream_id if current_chat_state != ChatState.CHAT: # 如果不是闲聊状态 (可能是 ABSENT 或 FOCUSED)，则跳过推理聊天 # logger.debug(f"[{stream_name}] 跳过处理兴趣消息 {msg_id}，因为当前状态为 {current_chat_state.value}") # 移除消息并继续下一个 removed_item = interest_dict.pop(msg_id, None) if removed_item: # logger.debug(f"[{stream_name}] 已从兴趣字典中移除消息 {msg_id} (因状态跳过)") # 减少日志 pass continue # 处理下一条消息 # --- 结束状态检查 --- # # --- 检查 HeartFChatting 是否活跃 (改为检查 SubHeartflow 状态) --- # is_focused = subheartflow.chat_state.chat_status == ChatState.FOCUSED if is_focused: # New check: If the subflow is focused, NormalChat shouldn't process removed_item = interest_dict.pop(msg_id, None) if removed_item: # logger.debug(f"[{stream_name}] SubHeartflow 处于 FOCUSED 状态，已跳过并移除 NormalChat 兴趣消息 {msg_id}") # Reduce noise pass continue # --- 结束检查 --- # # 只有当状态为 CHAT 且 HeartFChatting 不活跃 (即 Subflow 不是 FOCUSED) 时才执行以下处理逻辑 try: await self.normal_normal_chat( message=message, chat=chat, is_mentioned=is_mentioned, interested_rate=interest_value, ) except Exception as e: logger.error(f"[{stream_name}] 处理兴趣消息 {msg_id} 时出错: {e}\n{traceback.format_exc()}") finally: removed_item = interest_dict.pop(msg_id, None) if removed_item: # logger.debug(f"[{stream_name}] 已从兴趣字典中移除消息 {msg_id}") # 减少日志 pass async def normal_normal_chat( self, message: MessageRecv, chat: ChatStream, is_mentioned: bool, interested_rate: float ) -> None: timing_results = {} userinfo = message.message_info.user_info messageinfo = message.message_info stream_id = chat.stream_id stream_name = chat_manager.get_stream_name(stream_id) or stream_id # --- 在开始时检查 SubHeartflow 状态 --- # sub_hf = heartflow.get_subheartflow(stream_id) if not sub_hf: logger.warning(f"[{stream_name}] 无法获取 SubHeartflow，无法执行 normal_normal_chat。") return current_chat_state = sub_hf.chat_state.chat_status if current_chat_state != ChatState.CHAT: logger.debug( f"[{stream_name}] 跳过 normal_normal_chat，因为 SubHeartflow 状态为 {current_chat_state.value} (需要 CHAT)。" ) # 可以在这里添加 not_reply_handle 逻辑吗？ 如果不回复，也需要清理意愿。 # 注意：willing_manager.setup 尚未调用 willing_manager.setup(message, chat, is_mentioned, interested_rate) # 先 setup await willing_manager.not_reply_handle(message.message_info.message_id) willing_manager.delete(message.message_info.message_id) return # --- 结束状态检查 --- # # --- 接下来的逻辑只在 ChatState.CHAT 状态下执行 --- # is_mentioned, reply_probability = is_mentioned_bot_in_message(message) # 意愿管理器：设置当前message信息 willing_manager.setup(message, chat, is_mentioned, interested_rate) # 获取回复概率 is_willing = False if reply_probability != 1: is_willing = True reply_probability = await willing_manager.get_reply_probability(message.message_info.message_id) if message.message_info.additional_config: if "maimcore_reply_probability_gain" in message.message_info.additional_config.keys(): reply_probability += message.message_info.additional_config["maimcore_reply_probability_gain"] # 打印消息信息 mes_name = chat.group_info.group_name if chat.group_info else "私聊" current_time = time.strftime("%H:%M:%S", time.localtime(message.message_info.time)) willing_log = f"[回复意愿:{await willing_manager.get_willing(chat.stream_id):.2f}]" if is_willing else "" logger.info( f"[{current_time}][{mes_name}]" f"{chat.user_info.user_nickname}:" f"{message.processed_plain_text}{willing_log}[概率:{reply_probability * 100:.1f}%]" ) do_reply = False if random() < reply_probability: do_reply = True # 回复前处理 await willing_manager.before_generate_reply_handle(message.message_info.message_id) # 创建思考消息 with Timer("创建思考消息", timing_results): thinking_id = await self._create_thinking_message(message, chat, userinfo, messageinfo) logger.debug(f"创建捕捉器，thinking_id:{thinking_id}") info_catcher = info_catcher_manager.get_info_catcher(thinking_id) info_catcher.catch_decide_to_response(message) # 生成回复 sub_hf = heartflow.get_subheartflow(stream_id) try: with Timer("生成回复", timing_results): response_set = await self.gpt.generate_response( sub_hf=sub_hf, message=message, thinking_id=thinking_id, ) info_catcher.catch_after_generate_response(timing_results["生成回复"]) except Exception as e: logger.error(f"回复生成出现错误：{str(e)} {traceback.format_exc()}") response_set = None if not response_set: logger.info(f"[{chat.stream_id}] 模型未生成回复内容") # 如果模型未生成回复，移除思考消息 container = await message_manager.get_container(chat.stream_id) # thinking_message = None for msg in container.messages[:]: # Iterate over a copy if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id: # thinking_message = msg container.messages.remove(msg) # container.remove_message(msg) # 直接移除 logger.debug(f"[{chat.stream_id}] 已移除未产生回复的思考消息 {thinking_id}") break return # 不发送回复 logger.info(f"[{chat.stream_id}] 回复内容: {response_set}") # 发送回复 with Timer("消息发送", timing_results): first_bot_msg = await self._send_response_messages(message, chat, response_set, thinking_id) info_catcher.catch_after_response(timing_results["消息发送"], response_set, first_bot_msg) info_catcher.done_catch() # 处理表情包 with Timer("处理表情包", timing_results): await self._handle_emoji(message, chat, response_set[0]) # 更新关系情绪 with Timer("关系更新", timing_results): await self._update_relationship(message, response_set) # 回复后处理 await willing_manager.after_generate_reply_handle(message.message_info.message_id) # 输出性能计时结果 if do_reply: timing_str = " | ".join([f"{step}: {duration:.2f}秒" for step, duration in timing_results.items()]) trigger_msg = message.processed_plain_text response_msg = " ".join(response_set) if response_set else "无回复" logger.info(f"触发消息: {trigger_msg[:20]}... | 推理消息: {response_msg[:20]}... | 性能计时: {timing_str}") else: # 不回复处理 await willing_manager.not_reply_handle(message.message_info.message_id) # 意愿管理器：注销当前message信息 willing_manager.delete(message.message_info.message_id) @staticmethod def _check_ban_words(text: str, chat, userinfo) -> bool: """检查消息中是否包含过滤词""" for word in global_config.ban_words: if word in text: logger.info( f"[{chat.group_info.group_name if chat.group_info else '私聊'}]{userinfo.user_nickname}:{text}" ) logger.info(f"[过滤词识别]消息中含有{word}，filtered") return True return False @staticmethod def _check_ban_regex(text: str, chat, userinfo) -> bool: """检查消息是否匹配过滤正则表达式""" for pattern in global_config.ban_msgs_regex: if pattern.search(text): logger.info( f"[{chat.group_info.group_name if chat.group_info else '私聊'}]{userinfo.user_nickname}:{text}" ) logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered") return True return False async def start_monitoring_interest(self, chat: ChatStream): """为指定的 ChatStream 启动兴趣消息监控任务（如果尚未运行）。""" stream_id = chat.stream_id if stream_id not in self._interest_monitoring_tasks or self._interest_monitoring_tasks[stream_id].done(): logger.info(f"为聊天流 {stream_id} 启动兴趣消息监控任务...") # 创建新任务 task = asyncio.create_task(self._find_interested_message(chat)) # 添加完成回调 task.add_done_callback(lambda t: self._handle_task_completion(stream_id, t)) self._interest_monitoring_tasks[stream_id] = task # else: # logger.debug(f"聊天流 {stream_id} 的兴趣消息监控任务已在运行。") def _handle_task_completion(self, stream_id: str, task: asyncio.Task): """兴趣监控任务完成时的回调函数。""" try: # 检查任务是否因异常而结束 exception = task.exception() if exception: logger.error(f"聊天流 {stream_id} 的兴趣监控任务因异常结束: {exception}") logger.error(traceback.format_exc()) # 记录完整的 traceback else: logger.info(f"聊天流 {stream_id} 的兴趣监控任务正常结束。") except asyncio.CancelledError: logger.info(f"聊天流 {stream_id} 的兴趣监控任务被取消。") except Exception as e: logger.error(f"处理聊天流 {stream_id} 任务完成回调时出错: {e}") finally: # 从字典中移除已完成或取消的任务 if stream_id in self._interest_monitoring_tasks: del self._interest_monitoring_tasks[stream_id] logger.debug(f"已从监控任务字典中移除 {stream_id}") async def stop_monitoring_interest(self, stream_id: str): """停止指定聊天流的兴趣监控任务。""" if stream_id in self._interest_monitoring_tasks: task = self._interest_monitoring_tasks[stream_id] if task and not task.done(): task.cancel() # 尝试取消任务 logger.info(f"尝试取消聊天流 {stream_id} 的兴趣监控任务。") try: await task # 等待任务响应取消 except asyncio.CancelledError: logger.info(f"聊天流 {stream_id} 的兴趣监控任务已成功取消。") except Exception as e: logger.error(f"等待聊天流 {stream_id} 监控任务取消时出现异常: {e}") # 在回调函数 _handle_task_completion 中移除任务 # else: # logger.debug(f"聊天流 {stream_id} 没有正在运行的兴趣监控任务可停止。")