import asyncio import statistics # 导入 statistics 模块 import time import traceback from random import random from typing import List, Optional # 导入 Optional from maim_message import UserInfo, Seg from src.common.logger_manager import get_logger from src.chat.heart_flow.utils_chat import get_chat_type_and_target_info from src.manager.mood_manager import mood_manager from src.chat.message_receive.chat_stream import ChatStream, chat_manager from src.person_info.relationship_manager import relationship_manager from src.chat.utils.info_catcher import info_catcher_manager from src.chat.utils.timer_calculator import Timer from src.chat.utils.prompt_builder import global_prompt_manager from .normal_chat_generator import NormalChatGenerator from ..message_receive.message import MessageSending, MessageRecv, MessageThinking, MessageSet from src.chat.message_receive.message_sender import message_manager from src.chat.utils.utils_image import image_path_to_base64 from src.chat.emoji_system.emoji_manager import emoji_manager from src.chat.normal_chat.willing.willing_manager import willing_manager from src.config.config import global_config logger = get_logger("normal_chat") class NormalChat: def __init__(self, chat_stream: ChatStream, interest_dict: dict = None, on_switch_to_focus_callback=None): """初始化 NormalChat 实例。只进行同步操作。""" self.chat_stream = chat_stream self.stream_id = chat_stream.stream_id self.stream_name = chat_manager.get_stream_name(self.stream_id) or self.stream_id # Interest dict self.interest_dict = interest_dict self.is_group_chat: bool = False self.chat_target_info: Optional[dict] = None # Other sync initializations self.gpt = NormalChatGenerator() self.mood_manager = mood_manager self.start_time = time.time() self._chat_task: Optional[asyncio.Task] = None self._initialized = False # Track initialization status # 记录最近的回复内容，每项包含: {time, user_message, response, is_mentioned, is_reference_reply} self.recent_replies = [] self.max_replies_history = 20 # 最多保存最近20条回复记录 # 添加回调函数，用于在满足条件时通知切换到focus_chat模式 self.on_switch_to_focus_callback = on_switch_to_focus_callback async def initialize(self): """异步初始化，获取聊天类型和目标信息。""" if self._initialized: return self.is_group_chat, self.chat_target_info = await get_chat_type_and_target_info(self.stream_id) self.stream_name = chat_manager.get_stream_name(self.stream_id) or self.stream_id self._initialized = True logger.info(f"[{self.stream_name}] NormalChat 实例 initialize 完成 (异步部分)。") # 改为实例方法 async def _create_thinking_message(self, message: MessageRecv, timestamp: Optional[float] = None) -> str: """创建思考消息""" messageinfo = message.message_info bot_user_info = UserInfo( user_id=global_config.bot.qq_account, 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=self.chat_stream, bot_user_info=bot_user_info, reply=message, thinking_start_time=thinking_time_point, timestamp=timestamp if timestamp is not None else None, ) await message_manager.add_message(thinking_message) return thinking_id # 改为实例方法 async def _add_messages_to_manager( self, message: MessageRecv, response_set: List[str], thinking_id ) -> Optional[MessageSending]: """发送回复消息""" container = await message_manager.get_container(self.stream_id) # 使用 self.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"[{self.stream_name}] 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(self.chat_stream, thinking_id) # 使用 self.chat_stream mark_head = False first_bot_msg = None for msg in response_set: if global_config.experimental.debug_show_chat_mode: msg += "ⁿ" message_segment = Seg(type="text", data=msg) bot_message = MessageSending( message_id=thinking_id, chat_stream=self.chat_stream, # 使用 self.chat_stream bot_user_info=UserInfo( user_id=global_config.bot.qq_account, 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 # 改为实例方法 async def _handle_emoji(self, message: MessageRecv, response: str): """处理表情包""" if random() < global_config.normal_chat.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=self.chat_stream, # 使用 self.chat_stream bot_user_info=UserInfo( user_id=global_config.bot.qq_account, 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) # 改为实例方法 (虽然它只用 message.chat_stream, 但逻辑上属于实例) 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) user_info = message.message_info.user_info platform = user_info.platform await relationship_manager.calculate_update_relationship_value( user_info, platform, label=emotion, stance=stance, # 使用 self.chat_stream ) self.mood_manager.update_mood_from_emotion(emotion, global_config.mood.mood_intensity_factor) async def _reply_interested_message(self) -> None: """ 后台任务方法，轮询当前实例关联chat的兴趣消息 通常由start_monitoring_interest()启动 """ while True: async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()): await asyncio.sleep(0.5) # 每秒检查一次 # 检查任务是否已被取消 if self._chat_task is None or self._chat_task.cancelled(): logger.info(f"[{self.stream_name}] 兴趣监控任务被取消或置空，退出") break items_to_process = list(self.interest_dict.items()) if not items_to_process: continue # 处理每条兴趣消息 for msg_id, (message, interest_value, is_mentioned) in items_to_process: try: # 处理消息 await self.normal_response( message=message, is_mentioned=is_mentioned, interested_rate=interest_value, rewind_response=False, ) except Exception as e: logger.error(f"[{self.stream_name}] 处理兴趣消息{msg_id}时出错: {e}\n{traceback.format_exc()}") finally: self.interest_dict.pop(msg_id, None) # 改为实例方法, 移除 chat 参数 async def normal_response( self, message: MessageRecv, is_mentioned: bool, interested_rate: float, rewind_response: bool = False ) -> None: # 检查收到的消息是否属于当前实例处理的 chat stream if message.chat_stream.stream_id != self.stream_id: logger.error( f"[{self.stream_name}] normal_response 收到不匹配的消息 (来自 {message.chat_stream.stream_id})，预期 {self.stream_id}。已忽略。" ) return timing_results = {} reply_probability = 1.0 if is_mentioned else 0.0 # 如果被提及，基础概率为1，否则需要意愿判断 # 意愿管理器：设置当前message信息 willing_manager.setup(message, self.chat_stream, is_mentioned, interested_rate) # 获取回复概率 is_willing = False # 仅在未被提及或基础概率不为1时查询意愿概率 if reply_probability < 1: # 简化逻辑，如果未提及 (reply_probability 为 0)，则获取意愿概率 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"] reply_probability = min(max(reply_probability, 0), 1) # 确保概率在 0-1 之间 # 打印消息信息 mes_name = self.chat_stream.group_info.group_name if self.chat_stream.group_info else "私聊" current_time = time.strftime("%H:%M:%S", time.localtime(message.message_info.time)) # 使用 self.stream_id willing_log = f"[回复意愿:{await willing_manager.get_willing(self.stream_id):.2f}]" if is_willing else "" logger.info( f"[{current_time}][{mes_name}]" f"{message.message_info.user_info.user_nickname}:" # 使用 self.chat_stream f"{message.processed_plain_text}{willing_log}[概率:{reply_probability * 100:.1f}%]" ) do_reply = False response_set = None # 初始化 response_set if random() < reply_probability: do_reply = True # 回复前处理 await willing_manager.before_generate_reply_handle(message.message_info.message_id) with Timer("创建思考消息", timing_results): if rewind_response: thinking_id = await self._create_thinking_message(message, message.message_info.time) else: thinking_id = await self._create_thinking_message(message) logger.debug(f"[{self.stream_name}] 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) try: with Timer("生成回复", timing_results): response_set = await self.gpt.generate_response( 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"[{self.stream_name}] 回复生成出现错误：{str(e)} {traceback.format_exc()}") response_set = None # 确保出错时 response_set 为 None if not response_set: logger.info(f"[{self.stream_name}] 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(self.stream_id) # 使用 self.stream_id for msg in container.messages[:]: if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id: container.messages.remove(msg) logger.debug(f"[{self.stream_name}] 已移除未产生回复的思考消息 {thinking_id}") break # 需要在此处也调用 not_reply_handle 和 delete 吗？ # 如果是因为模型没回复，也算是一种 "未回复" await willing_manager.not_reply_handle(message.message_info.message_id) willing_manager.delete(message.message_info.message_id) return # 不执行后续步骤 logger.info(f"[{self.stream_name}] 回复内容: {response_set}") # 发送回复 (不再需要传入 chat) with Timer("消息发送", timing_results): first_bot_msg = await self._add_messages_to_manager(message, response_set, thinking_id) # 检查 first_bot_msg 是否为 None (例如思考消息已被移除的情况) if first_bot_msg: info_catcher.catch_after_response(timing_results["消息发送"], response_set, first_bot_msg) # 记录回复信息到最近回复列表中 reply_info = { "time": time.time(), "user_message": message.processed_plain_text, "user_info": { "user_id": message.message_info.user_info.user_id, "user_nickname": message.message_info.user_info.user_nickname, }, "response": response_set, "is_mentioned": is_mentioned, "is_reference_reply": message.reply is not None, # 判断是否为引用回复 "timing": {k: round(v, 2) for k, v in timing_results.items()}, } self.recent_replies.append(reply_info) # 保持最近回复历史在限定数量内 if len(self.recent_replies) > self.max_replies_history: self.recent_replies = self.recent_replies[-self.max_replies_history :] # 检查是否需要切换到focus模式 await self._check_switch_to_focus() else: logger.warning(f"[{self.stream_name}] 思考消息 {thinking_id} 在发送前丢失，无法记录 info_catcher") info_catcher.done_catch() # 处理表情包 (不再需要传入 chat) with Timer("处理表情包", timing_results): await self._handle_emoji(message, response_set[0]) # 更新关系情绪 (不再需要传入 chat) 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 and response_set: # 确保 response_set 不是 None 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) logger.info( f"[{self.stream_name}] 触发消息: {trigger_msg[:20]}... | 推理消息: {response_msg[:20]}... | 性能计时: {timing_str}" ) elif not do_reply: # 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 (无论是否回复，只要处理过就删除) willing_manager.delete(message.message_info.message_id) # 改为实例方法, 移除 chat 参数 async def start_chat(self): """先进行异步初始化，然后启动聊天任务。""" if not self._initialized: await self.initialize() # Ensure initialized before starting tasks if self._chat_task is None or self._chat_task.done(): logger.info(f"[{self.stream_name}] 开始处理兴趣消息...") polling_task = asyncio.create_task(self._reply_interested_message()) polling_task.add_done_callback(lambda t: self._handle_task_completion(t)) self._chat_task = polling_task else: logger.info(f"[{self.stream_name}] 聊天轮询任务已在运行中。") def _handle_task_completion(self, task: asyncio.Task): """任务完成回调处理""" if task is not self._chat_task: logger.warning(f"[{self.stream_name}] 收到未知任务回调") return try: if exc := task.exception(): logger.error(f"[{self.stream_name}] 任务异常: {exc}") traceback.print_exc() except asyncio.CancelledError: logger.debug(f"[{self.stream_name}] 任务已取消") except Exception as e: logger.error(f"[{self.stream_name}] 回调处理错误: {e}") finally: if self._chat_task is task: self._chat_task = None logger.debug(f"[{self.stream_name}] 任务清理完成") # 改为实例方法, 移除 stream_id 参数 async def stop_chat(self): """停止当前实例的兴趣监控任务。""" if self._chat_task and not self._chat_task.done(): task = self._chat_task logger.debug(f"[{self.stream_name}] 尝试取消normal聊天任务。") task.cancel() try: await task # 等待任务响应取消 except asyncio.CancelledError: logger.info(f"[{self.stream_name}] 结束一般聊天模式。") except Exception as e: # 回调函数 _handle_task_completion 会处理异常日志 logger.warning(f"[{self.stream_name}] 等待监控任务取消时捕获到异常 (可能已在回调中记录): {e}") finally: # 确保任务状态更新，即使等待出错 (回调函数也会尝试更新) if self._chat_task is task: self._chat_task = None # 清理所有未处理的思考消息 try: container = await message_manager.get_container(self.stream_id) if container: # 查找并移除所有 MessageThinking 类型的消息 thinking_messages = [msg for msg in container.messages[:] if isinstance(msg, MessageThinking)] if thinking_messages: for msg in thinking_messages: container.messages.remove(msg) logger.info(f"[{self.stream_name}] 清理了 {len(thinking_messages)} 条未处理的思考消息。") except Exception as e: logger.error(f"[{self.stream_name}] 清理思考消息时出错: {e}") traceback.print_exc() # 获取最近回复记录的方法 def get_recent_replies(self, limit: int = 10) -> List[dict]: """获取最近的回复记录 Args: limit: 最大返回数量，默认10条 Returns: List[dict]: 最近的回复记录列表，每项包含： time: 回复时间戳 user_message: 用户消息内容 user_info: 用户信息(user_id, user_nickname) response: 回复内容 is_mentioned: 是否被提及(@) is_reference_reply: 是否为引用回复 timing: 各阶段耗时 """ # 返回最近的limit条记录，按时间倒序排列 return sorted(self.recent_replies[-limit:], key=lambda x: x["time"], reverse=True) async def _check_switch_to_focus(self) -> None: """检查是否满足切换到focus模式的条件""" if not self.on_switch_to_focus_callback: return # 如果没有设置回调函数，直接返回 current_time = time.time() time_threshold = 120 / global_config.focus_chat.auto_focus_threshold reply_threshold = 6 * global_config.focus_chat.auto_focus_threshold one_minute_ago = current_time - time_threshold # 统计1分钟内的回复数量 recent_reply_count = sum(1 for reply in self.recent_replies if reply["time"] > one_minute_ago) # print(111111111111111333333333333333333333333331111111111111111111111111111111111) # print(recent_reply_count) # 如果1分钟内回复数量大于8，触发切换到focus模式 if recent_reply_count > reply_threshold: logger.info( f"[{self.stream_name}] 检测到1分钟内回复数量({recent_reply_count})大于{reply_threshold}，触发切换到focus模式" ) try: # 调用回调函数通知上层切换到focus模式 await self.on_switch_to_focus_callback() except Exception as e: logger.error(f"[{self.stream_name}] 触发切换到focus模式时出错: {e}\n{traceback.format_exc()}")