mirror of https://github.com/Mai-with-u/MaiBot.git
487 lines
23 KiB
Python
487 lines
23 KiB
Python
import time
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import asyncio
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import traceback
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import statistics # 导入 statistics 模块
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from random import random
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from typing import List, Optional # 导入 Optional
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from ..moods.moods import MoodManager
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from ...config.config import global_config
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from ..emoji_system.emoji_manager import emoji_manager
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from .normal_chat_generator import NormalChatGenerator
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from ..chat.message import MessageSending, MessageRecv, MessageThinking, MessageSet
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from ..chat.message_sender import message_manager
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from ..chat.utils_image import image_path_to_base64
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from ..willing.willing_manager import willing_manager
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from maim_message import UserInfo, Seg
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from src.common.logger import get_module_logger, CHAT_STYLE_CONFIG, LogConfig
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from src.plugins.chat.chat_stream import ChatStream, chat_manager
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from src.plugins.person_info.relationship_manager import relationship_manager
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from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
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from src.plugins.utils.timer_calculator import Timer
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# 定义日志配置
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chat_config = LogConfig(
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console_format=CHAT_STYLE_CONFIG["console_format"],
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file_format=CHAT_STYLE_CONFIG["file_format"],
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)
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logger = get_module_logger("normal_chat", config=chat_config)
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class NormalChat:
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def __init__(self, chat_stream: ChatStream, interest_dict: dict):
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"""
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初始化 NormalChat 实例，针对特定的 ChatStream。
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Args:
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chat_stream (ChatStream): 此 NormalChat 实例关联的聊天流对象。
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"""
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self.chat_stream = chat_stream
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self.stream_id = chat_stream.stream_id
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self.stream_name = chat_manager.get_stream_name(self.stream_id) or self.stream_id
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self.interest_dict = interest_dict
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self.gpt = NormalChatGenerator()
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self.mood_manager = MoodManager.get_instance() # MoodManager 保持单例
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# 存储此实例的兴趣监控任务
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self.start_time = time.time()
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self._chat_task: Optional[asyncio.Task] = None
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logger.info(f"[{self.stream_name}] NormalChat 实例初始化完成。")
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# 改为实例方法
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async def _create_thinking_message(self, message: MessageRecv) -> str:
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"""创建思考消息"""
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messageinfo = message.message_info
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bot_user_info = UserInfo(
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user_id=global_config.BOT_QQ,
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user_nickname=global_config.BOT_NICKNAME,
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platform=messageinfo.platform,
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)
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thinking_time_point = round(time.time(), 2)
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thinking_id = "mt" + str(thinking_time_point)
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thinking_message = MessageThinking(
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message_id=thinking_id,
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chat_stream=self.chat_stream, # 使用 self.chat_stream
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bot_user_info=bot_user_info,
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reply=message,
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thinking_start_time=thinking_time_point,
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)
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await message_manager.add_message(thinking_message)
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return thinking_id
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# 改为实例方法
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async def _add_messages_to_manager(
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self, message: MessageRecv, response_set: List[str], thinking_id
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) -> Optional[MessageSending]:
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"""发送回复消息"""
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container = await message_manager.get_container(self.stream_id) # 使用 self.stream_id
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thinking_message = None
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for msg in container.messages[:]:
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if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
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thinking_message = msg
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container.messages.remove(msg)
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break
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if not thinking_message:
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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")
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return None
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thinking_start_time = thinking_message.thinking_start_time
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message_set = MessageSet(self.chat_stream, thinking_id) # 使用 self.chat_stream
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mark_head = False
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first_bot_msg = None
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for msg in response_set:
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message_segment = Seg(type="text", data=msg)
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bot_message = MessageSending(
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message_id=thinking_id,
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chat_stream=self.chat_stream, # 使用 self.chat_stream
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bot_user_info=UserInfo(
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user_id=global_config.BOT_QQ,
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user_nickname=global_config.BOT_NICKNAME,
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platform=message.message_info.platform,
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),
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sender_info=message.message_info.user_info,
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message_segment=message_segment,
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reply=message,
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is_head=not mark_head,
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is_emoji=False,
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thinking_start_time=thinking_start_time,
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apply_set_reply_logic=True,
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)
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if not mark_head:
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mark_head = True
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first_bot_msg = bot_message
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message_set.add_message(bot_message)
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await message_manager.add_message(message_set)
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return first_bot_msg
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# 改为实例方法
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async def _handle_emoji(self, message: MessageRecv, response: str):
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"""处理表情包"""
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if random() < global_config.emoji_chance:
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emoji_raw = await emoji_manager.get_emoji_for_text(response)
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if emoji_raw:
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emoji_path, description = emoji_raw
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emoji_cq = image_path_to_base64(emoji_path)
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thinking_time_point = round(message.message_info.time, 2)
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message_segment = Seg(type="emoji", data=emoji_cq)
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bot_message = MessageSending(
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message_id="mt" + str(thinking_time_point),
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chat_stream=self.chat_stream, # 使用 self.chat_stream
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bot_user_info=UserInfo(
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user_id=global_config.BOT_QQ,
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user_nickname=global_config.BOT_NICKNAME,
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platform=message.message_info.platform,
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),
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sender_info=message.message_info.user_info,
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message_segment=message_segment,
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reply=message,
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is_head=False,
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is_emoji=True,
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apply_set_reply_logic=True,
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)
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await message_manager.add_message(bot_message)
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# 改为实例方法 (虽然它只用 message.chat_stream, 但逻辑上属于实例)
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async def _update_relationship(self, message: MessageRecv, response_set):
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"""更新关系情绪"""
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ori_response = ",".join(response_set)
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stance, emotion = await self.gpt._get_emotion_tags(ori_response, message.processed_plain_text)
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await relationship_manager.calculate_update_relationship_value(
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chat_stream=self.chat_stream,
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label=emotion,
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stance=stance, # 使用 self.chat_stream
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)
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self.mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor)
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async def _reply_interested_message(self) -> None:
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"""
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后台任务方法，轮询当前实例关联chat的兴趣消息
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通常由start_monitoring_interest()启动
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"""
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while True:
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await asyncio.sleep(0.5) # 每秒检查一次
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# 检查任务是否已被取消
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if self._chat_task is None or self._chat_task.cancelled():
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logger.info(f"[{self.stream_name}] 兴趣监控任务被取消或置空，退出")
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break
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# 获取待处理消息列表
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items_to_process = list(self.interest_dict.items())
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if not items_to_process:
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continue
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# 处理每条兴趣消息
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for msg_id, (message, interest_value, is_mentioned) in items_to_process:
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try:
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# 处理消息
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await self.normal_response(
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message=message, is_mentioned=is_mentioned, interested_rate=interest_value
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)
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except Exception as e:
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logger.error(f"[{self.stream_name}] 处理兴趣消息{msg_id}时出错: {e}\n{traceback.format_exc()}")
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finally:
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self.interest_dict.pop(msg_id, None)
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# 改为实例方法, 移除 chat 参数
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async def normal_response(self, message: MessageRecv, is_mentioned: bool, interested_rate: float) -> None:
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# 检查收到的消息是否属于当前实例处理的 chat stream
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if message.chat_stream.stream_id != self.stream_id:
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logger.error(
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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。"
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)
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return
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timing_results = {}
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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
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# 意愿管理器：设置当前message信息
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willing_manager.setup(message, self.chat_stream, is_mentioned, interested_rate)
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# 获取回复概率
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is_willing = False
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# 仅在未被提及或基础概率不为1时查询意愿概率
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if reply_probability < 1: # 简化逻辑，如果未提及 (reply_probability 为 0)，则获取意愿概率
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is_willing = True
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reply_probability = await willing_manager.get_reply_probability(message.message_info.message_id)
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if message.message_info.additional_config:
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if "maimcore_reply_probability_gain" in message.message_info.additional_config.keys():
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reply_probability += message.message_info.additional_config["maimcore_reply_probability_gain"]
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reply_probability = min(max(reply_probability, 0), 1) # 确保概率在 0-1 之间
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# 打印消息信息
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mes_name = self.chat_stream.group_info.group_name if self.chat_stream.group_info else "私聊"
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current_time = time.strftime("%H:%M:%S", time.localtime(message.message_info.time))
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# 使用 self.stream_id
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willing_log = f"[回复意愿:{await willing_manager.get_willing(self.stream_id):.2f}]" if is_willing else ""
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logger.info(
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f"[{current_time}][{mes_name}]"
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f"{message.message_info.user_info.user_nickname}:" # 使用 self.chat_stream
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f"{message.processed_plain_text}{willing_log}[概率:{reply_probability * 100:.1f}%]"
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)
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do_reply = False
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response_set = None # 初始化 response_set
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if random() < reply_probability:
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do_reply = True
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# 回复前处理
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await willing_manager.before_generate_reply_handle(message.message_info.message_id)
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with Timer("创建思考消息", timing_results):
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thinking_id = await self._create_thinking_message(message)
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logger.debug(f"[{self.stream_name}] 创建捕捉器，thinking_id:{thinking_id}")
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info_catcher = info_catcher_manager.get_info_catcher(thinking_id)
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info_catcher.catch_decide_to_response(message)
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try:
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with Timer("生成回复", timing_results):
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response_set = await self.gpt.generate_response(
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message=message,
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thinking_id=thinking_id,
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)
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info_catcher.catch_after_generate_response(timing_results["生成回复"])
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except Exception as e:
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logger.error(f"[{self.stream_name}] 回复生成出现错误：{str(e)} {traceback.format_exc()}")
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response_set = None # 确保出错时 response_set 为 None
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if not response_set:
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logger.info(f"[{self.stream_name}] 模型未生成回复内容")
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# 如果模型未生成回复，移除思考消息
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container = await message_manager.get_container(self.stream_id) # 使用 self.stream_id
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for msg in container.messages[:]:
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if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
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container.messages.remove(msg)
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logger.debug(f"[{self.stream_name}] 已移除未产生回复的思考消息 {thinking_id}")
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break
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# 需要在此处也调用 not_reply_handle 和 delete 吗？
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# 如果是因为模型没回复，也算是一种 "未回复"
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await willing_manager.not_reply_handle(message.message_info.message_id)
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willing_manager.delete(message.message_info.message_id)
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return # 不执行后续步骤
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logger.info(f"[{self.stream_name}] 回复内容: {response_set}")
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# 发送回复 (不再需要传入 chat)
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with Timer("消息发送", timing_results):
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first_bot_msg = await self._add_messages_to_manager(message, response_set, thinking_id)
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# 检查 first_bot_msg 是否为 None (例如思考消息已被移除的情况)
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if first_bot_msg:
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info_catcher.catch_after_response(timing_results["消息发送"], response_set, first_bot_msg)
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else:
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logger.warning(f"[{self.stream_name}] 思考消息 {thinking_id} 在发送前丢失，无法记录 info_catcher")
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info_catcher.done_catch()
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# 处理表情包 (不再需要传入 chat)
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with Timer("处理表情包", timing_results):
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await self._handle_emoji(message, response_set[0])
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# 更新关系情绪 (不再需要传入 chat)
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with Timer("关系更新", timing_results):
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await self._update_relationship(message, response_set)
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# 回复后处理
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await willing_manager.after_generate_reply_handle(message.message_info.message_id)
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# 输出性能计时结果
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if do_reply and response_set: # 确保 response_set 不是 None
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timing_str = " | ".join([f"{step}: {duration:.2f}秒" for step, duration in timing_results.items()])
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trigger_msg = message.processed_plain_text
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response_msg = " ".join(response_set)
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logger.info(
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f"[{self.stream_name}] 触发消息: {trigger_msg[:20]}... | 推理消息: {response_msg[:20]}... | 性能计时: {timing_str}"
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)
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elif not do_reply:
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# 不回复处理
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await willing_manager.not_reply_handle(message.message_info.message_id)
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# else: # do_reply is True but response_set is None (handled above)
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# logger.info(f"[{self.stream_name}] 决定回复但模型未生成内容。触发: {message.processed_plain_text[:20]}...")
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# 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)
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willing_manager.delete(message.message_info.message_id)
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# --- 新增：处理初始高兴趣消息的私有方法 ---
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async def _process_initial_interest_messages(self):
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"""处理启动时存在于 interest_dict 中的高兴趣消息。"""
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items_to_process = list(self.interest_dict.items())
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if not items_to_process:
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return # 没有初始消息，直接返回
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logger.info(f"[{self.stream_name}] 发现 {len(items_to_process)} 条初始兴趣消息，开始处理高兴趣部分...")
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interest_values = [item[1][1] for item in items_to_process] # 提取兴趣值列表
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messages_to_reply = [] # 需要立即回复的消息
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if len(interest_values) == 1:
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# 如果只有一个消息，直接处理
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messages_to_reply.append(items_to_process[0])
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logger.info(f"[{self.stream_name}] 只有一条初始消息，直接处理。")
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elif len(interest_values) > 1:
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# 计算均值和标准差
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try:
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mean_interest = statistics.mean(interest_values)
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stdev_interest = statistics.stdev(interest_values)
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threshold = mean_interest + stdev_interest
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logger.info(
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f"[{self.stream_name}] 初始兴趣值 均值: {mean_interest:.2f}, 标准差: {stdev_interest:.2f}, 阈值: {threshold:.2f}"
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)
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# 找出高于阈值的消息
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for item in items_to_process:
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msg_id, (message, interest_value, is_mentioned) = item
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if interest_value > threshold:
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messages_to_reply.append(item)
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logger.info(f"[{self.stream_name}] 找到 {len(messages_to_reply)} 条高于阈值的初始消息进行处理。")
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except statistics.StatisticsError as e:
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logger.error(f"[{self.stream_name}] 计算初始兴趣统计值时出错: {e}，跳过初始处理。")
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# 处理需要回复的消息
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processed_count = 0
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# --- 修改：迭代前创建要处理的ID列表副本，防止迭代时修改 ---
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messages_to_process_initially = list(messages_to_reply) # 创建副本
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# --- 修改结束 ---
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for item in messages_to_process_initially: # 使用副本迭代
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msg_id, (message, interest_value, is_mentioned) = item
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# --- 修改：在处理前尝试 pop，防止竞争 ---
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popped_item = self.interest_dict.pop(msg_id, None)
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if popped_item is None:
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logger.warning(f"[{self.stream_name}] 初始兴趣消息 {msg_id} 在处理前已被移除，跳过。")
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continue # 如果消息已被其他任务处理（pop），则跳过
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# --- 修改结束 ---
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try:
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logger.info(f"[{self.stream_name}] 处理初始高兴趣消息 {msg_id} (兴趣值: {interest_value:.2f})")
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await self.normal_response(message=message, is_mentioned=is_mentioned, interested_rate=interest_value)
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processed_count += 1
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except Exception as e:
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logger.error(f"[{self.stream_name}] 处理初始兴趣消息 {msg_id} 时出错: {e}\\n{traceback.format_exc()}")
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logger.info(
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f"[{self.stream_name}] 初始高兴趣消息处理完毕，共处理 {processed_count} 条。剩余 {len(self.interest_dict)} 条待轮询。"
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)
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# --- 新增结束 ---
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# 保持 staticmethod, 因为不依赖实例状态, 但需要 chat 对象来获取日志上下文
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@staticmethod
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def _check_ban_words(text: str, chat: ChatStream, userinfo: UserInfo) -> bool:
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"""检查消息中是否包含过滤词"""
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stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id
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for word in global_config.ban_words:
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if word in text:
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logger.info(
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f"[{stream_name}][{chat.group_info.group_name if chat.group_info else '私聊'}]"
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f"{userinfo.user_nickname}:{text}"
|
||
)
|
||
logger.info(f"[{stream_name}][过滤词识别] 消息中含有 '{word}'，filtered")
|
||
return True
|
||
return False
|
||
|
||
# 保持 staticmethod, 因为不依赖实例状态, 但需要 chat 对象来获取日志上下文
|
||
@staticmethod
|
||
def _check_ban_regex(text: str, chat: ChatStream, userinfo: UserInfo) -> bool:
|
||
"""检查消息是否匹配过滤正则表达式"""
|
||
stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id
|
||
for pattern in global_config.ban_msgs_regex:
|
||
if pattern.search(text):
|
||
logger.info(
|
||
f"[{stream_name}][{chat.group_info.group_name if chat.group_info else '私聊'}]"
|
||
f"{userinfo.user_nickname}:{text}"
|
||
)
|
||
logger.info(f"[{stream_name}][正则表达式过滤] 消息匹配到 '{pattern.pattern}'，filtered")
|
||
return True
|
||
return False
|
||
|
||
# 改为实例方法, 移除 chat 参数
|
||
|
||
async def start_chat(self):
|
||
"""为此 NormalChat 实例关联的 ChatStream 启动聊天任务（如果尚未运行），
|
||
并在后台处理一次初始的高兴趣消息。""" # 文言文注释示例：启聊之始，若有遗珠，当于暗处拂拭，勿碍正途。
|
||
if self._chat_task is None or self._chat_task.done():
|
||
# --- 修改：使用 create_task 启动初始消息处理 ---
|
||
logger.info(f"[{self.stream_name}] 开始后台处理初始兴趣消息...")
|
||
# 创建一个任务来处理初始消息，不阻塞当前流程
|
||
_initial_process_task = asyncio.create_task(self._process_initial_interest_messages())
|
||
# 可以考虑给这个任务也添加完成回调来记录日志或处理错误
|
||
# initial_process_task.add_done_callback(...)
|
||
# --- 修改结束 ---
|
||
|
||
# 启动后台轮询任务 (这部分不变)
|
||
logger.info(f"[{self.stream_name}] 启动后台兴趣消息轮询任务...")
|
||
polling_task = asyncio.create_task(self._reply_interested_message()) # 注意变量名区分
|
||
polling_task.add_done_callback(lambda t: self._handle_task_completion(t))
|
||
self._chat_task = polling_task # self._chat_task 仍然指向主要的轮询任务
|
||
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}")
|
||
logger.error(traceback.format_exc())
|
||
except asyncio.CancelledError:
|
||
logger.info(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.info(f"[{self.stream_name}] 尝试取消聊天任务。")
|
||
task.cancel()
|
||
try:
|
||
await task # 等待任务响应取消
|
||
except asyncio.CancelledError:
|
||
logger.info(f"[{self.stream_name}] 聊天任务已成功取消。")
|
||
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}")
|
||
logger.error(traceback.format_exc())
|