import time from random import random import re from ...memory_system.Hippocampus import HippocampusManager from ...moods.moods import MoodManager from ...config.config import global_config from ...chat.emoji_manager import emoji_manager from .reasoning_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 ...chat.chat_stream import chat_manager # 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("reasoning_chat", config=chat_config) class ReasoningChat: def __init__(self): self.storage = MessageStorage() self.gpt = ResponseGenerator() self.mood_manager = MoodManager.get_instance() self.mood_manager.start_mood_update() async def _create_thinking_message(self, 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) willing_manager.change_reply_willing_sent(chat) return thinking_id async def _send_response_messages(self, message, chat, response_set, thinking_id): """发送回复消息""" container = 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("未找到对应的思考消息,可能已超时被移除") return thinking_start_time = thinking_message.thinking_start_time message_set = MessageSet(chat, thinking_id) mark_head = False 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, ) if not mark_head: mark_head = True message_set.add_message(bot_message) message_manager.add_message(message_set) async def _handle_emoji(self, 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, ) message_manager.add_message(bot_message) async def process_message(self, message_data: str) -> None: """处理消息并生成回复""" timing_results = {} response_set = None message = MessageRecv(message_data) groupinfo = message.message_info.group_info userinfo = message.message_info.user_info messageinfo = message.message_info if groupinfo == None and global_config.enable_friend_chat:#如果是私聊 pass elif groupinfo.group_id not in global_config.talk_allowed_groups: return # logger.info("使用推理聊天模式") # 创建聊天流 chat = await chat_manager.get_or_create_stream( platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo, ) message.update_chat_stream(chat) await message.process() # 过滤词/正则表达式过滤 if self._check_ban_words(message.processed_plain_text, chat, userinfo) or self._check_ban_regex( message.raw_message, chat, userinfo ): return await self.storage.store_message(message, chat) # 记忆激活 timer1 = time.time() interested_rate = await HippocampusManager.get_instance().get_activate_from_text( message.processed_plain_text, fast_retrieval=True ) timer2 = time.time() timing_results["记忆激活"] = timer2 - timer1 is_mentioned = is_mentioned_bot_in_message(message) # 计算回复意愿 current_willing = willing_manager.get_willing(chat_stream=chat) willing_manager.set_willing(chat.stream_id, current_willing) # 意愿激活 timer1 = time.time() reply_probability = await willing_manager.change_reply_willing_received( chat_stream=chat, is_mentioned_bot=is_mentioned, config=global_config, is_emoji=message.is_emoji, interested_rate=interested_rate, sender_id=str(message.message_info.user_info.user_id), ) timer2 = time.time() timing_results["意愿激活"] = timer2 - timer1 # 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(messageinfo.time)) logger.info( f"[{current_time}][{mes_name}]" f"{chat.user_info.user_nickname}:" f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]" ) 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"] do_reply = False if random() < reply_probability: do_reply = True # 创建思考消息 timer1 = time.time() thinking_id = await self._create_thinking_message(message, chat, userinfo, messageinfo) timer2 = time.time() timing_results["创建思考消息"] = timer2 - timer1 # 生成回复 timer1 = time.time() response_set = await self.gpt.generate_response(message) timer2 = time.time() timing_results["生成回复"] = timer2 - timer1 if not response_set: logger.info("为什么生成回复失败?") return # 发送消息 timer1 = time.time() await self._send_response_messages(message, chat, response_set, thinking_id) timer2 = time.time() timing_results["发送消息"] = timer2 - timer1 # 处理表情包 timer1 = time.time() await self._handle_emoji(message, chat, response_set) timer2 = time.time() timing_results["处理表情包"] = timer2 - timer1 # 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}") def _check_ban_words(self, 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 def _check_ban_regex(self, 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 re.search(pattern, 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