326 lines
12 KiB
Python
326 lines
12 KiB
Python
import re
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import time
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from random import random
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from loguru import logger
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from nonebot.adapters.onebot.v11 import (
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Bot,
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GroupMessageEvent,
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MessageEvent,
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PrivateMessageEvent,
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)
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from ..memory_system.memory import hippocampus
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from ..moods.moods import MoodManager # 导入情绪管理器
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from .config import global_config
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from .cq_code import CQCode, cq_code_tool # 导入CQCode模块
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from .cq_code import CQCode, cq_code_tool # 导入CQCode模块
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from .emoji_manager import emoji_manager # 导入表情包管理器
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from .llm_generator import ResponseGenerator
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from .message import MessageSending, MessageRecv, MessageThinking, MessageSet
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from .message_cq import (
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MessageRecvCQ,
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)
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from .chat_stream import chat_manager
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from .message_sender import message_manager # 导入新的消息管理器
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from .relationship_manager import relationship_manager
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from .storage import MessageStorage
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from .utils import calculate_typing_time, is_mentioned_bot_in_message
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from .utils_image import image_path_to_base64
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from .willing_manager import willing_manager # 导入意愿管理器
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from .message_base import UserInfo, GroupInfo, Seg
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class ChatBot:
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def __init__(self):
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self.storage = MessageStorage()
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self.gpt = ResponseGenerator()
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self.bot = None # bot 实例引用
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self._started = False
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self.mood_manager = MoodManager.get_instance() # 获取情绪管理器单例
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self.mood_manager.start_mood_update() # 启动情绪更新
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self.emoji_chance = 0.2 # 发送表情包的基础概率
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# self.message_streams = MessageStreamContainer()
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async def _ensure_started(self):
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"""确保所有任务已启动"""
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if not self._started:
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self._started = True
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async def handle_message(self, event: MessageEvent, bot: Bot) -> None:
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"""处理收到的消息"""
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self.bot = bot # 更新 bot 实例
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# 用户屏蔽,不区分私聊/群聊
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if event.user_id in global_config.ban_user_id:
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return
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# 处理私聊消息
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if isinstance(event, PrivateMessageEvent):
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if not global_config.enable_friend_chat: # 私聊过滤
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return
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else:
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user_info = UserInfo(
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user_id=event.user_id,
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user_nickname=(
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await bot.get_stranger_info(
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user_id=event.user_id, no_cache=True
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)
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)["nickname"],
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user_cardname=None,
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platform="qq",
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)
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logger.debug(user_info)
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# group_info = GroupInfo(group_id=0, group_name="私聊", platform="qq")
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group_info = None
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# 处理群聊消息
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else:
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# 白名单设定由nontbot侧完成
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if event.group_id:
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if event.group_id not in global_config.talk_allowed_groups:
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return
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user_info = UserInfo(
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user_id=event.user_id,
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user_nickname=event.sender.nickname,
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user_cardname=event.sender.card or None,
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platform="qq",
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)
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group_info = GroupInfo(
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group_id=event.group_id, group_name=None, platform="qq"
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)
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# group_info = await bot.get_group_info(group_id=event.group_id)
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# sender_info = await bot.get_group_member_info(group_id=event.group_id, user_id=event.user_id, no_cache=True)
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message_cq = MessageRecvCQ(
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message_id=event.message_id,
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user_info=user_info,
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raw_message=str(event.original_message),
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group_info=group_info,
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reply_message=event.reply,
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platform="qq",
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)
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message_json = message_cq.to_dict()
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# 进入maimbot
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message = MessageRecv(message_json)
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groupinfo = message.message_info.group_info
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userinfo = message.message_info.user_info
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messageinfo = message.message_info
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# 消息过滤，涉及到config有待更新
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chat = await chat_manager.get_or_create_stream(
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platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo
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)
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chat = await chat_manager.get_or_create_stream(
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platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo
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)
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message.update_chat_stream(chat)
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await relationship_manager.update_relationship(
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chat_stream=chat,
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)
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await relationship_manager.update_relationship_value(
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chat_stream=chat, relationship_value=0.5
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)
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await message.process()
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# 过滤词
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for word in global_config.ban_words:
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if word in message.processed_plain_text:
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logger.info(
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f"[{chat.group_info.group_name if chat.group_info.group_id else '私聊'}]{userinfo.user_nickname}:{message.processed_plain_text}"
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)
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logger.info(f"[过滤词识别]消息中含有{word}，filtered")
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return
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# 正则表达式过滤
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for pattern in global_config.ban_msgs_regex:
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if re.search(pattern, message.raw_message):
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logger.info(
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f"[{chat.group_info.group_name if chat.group_info.group_id else '私聊'}]{message.user_nickname}:{message.raw_message}"
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)
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logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
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return
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current_time = time.strftime(
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"%Y-%m-%d %H:%M:%S", time.localtime(messageinfo.time)
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)
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# topic=await topic_identifier.identify_topic_llm(message.processed_plain_text)
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topic = ""
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topic = ""
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interested_rate = 0
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interested_rate = (
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await hippocampus.memory_activate_value(message.processed_plain_text) / 100
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)
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logger.debug(f"对{message.processed_plain_text}" f"的激活度:{interested_rate}")
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# logger.info(f"\033[1;32m[主题识别]\033[0m 使用{global_config.topic_extract}主题: {topic}")
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await self.storage.store_message(message, chat, topic[0] if topic else None)
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await self.storage.store_message(message, chat, topic[0] if topic else None)
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is_mentioned = is_mentioned_bot_in_message(message)
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reply_probability = await willing_manager.change_reply_willing_received(
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chat_stream=chat,
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topic=topic[0] if topic else None,
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is_mentioned_bot=is_mentioned,
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config=global_config,
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is_emoji=message.is_emoji,
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interested_rate=interested_rate,
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)
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current_willing = willing_manager.get_willing(chat_stream=chat)
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logger.info(
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f"[{current_time}][{chat.group_info.group_name if chat.group_info.group_id else '私聊'}]{chat.user_info.user_nickname}:"
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f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]"
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)
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response = None
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if random() < reply_probability:
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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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think_id = "mt" + str(thinking_time_point)
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thinking_message = MessageThinking(
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message_id=think_id,
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chat_stream=chat,
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bot_user_info=bot_user_info,
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reply=message,
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)
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message_manager.add_message(thinking_message)
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willing_manager.change_reply_willing_sent(chat)
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response, raw_content = await self.gpt.generate_response(message)
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response, raw_content = await self.gpt.generate_response(message)
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# print(f"response: {response}")
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if response:
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# print(f"有response: {response}")
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container = message_manager.get_container(chat.stream_id)
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thinking_message = None
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# 找到message,删除
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# print(f"开始找思考消息")
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for msg in container.messages:
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if (
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isinstance(msg, MessageThinking)
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and msg.message_info.message_id == think_id
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):
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# print(f"找到思考消息: {msg}")
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thinking_message = msg
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container.messages.remove(msg)
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break
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# 如果找不到思考消息，直接返回
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if not thinking_message:
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logger.warning("未找到对应的思考消息，可能已超时被移除")
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return
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# 记录开始思考的时间，避免从思考到回复的时间太久
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thinking_start_time = thinking_message.thinking_start_time
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message_set = MessageSet(chat, think_id)
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# 计算打字时间，1是为了模拟打字，2是避免多条回复乱序
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accu_typing_time = 0
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mark_head = False
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for msg in response:
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# print(f"\033[1;32m[回复内容]\033[0m {msg}")
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# 通过时间改变时间戳
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typing_time = calculate_typing_time(msg)
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logger.debug(f"typing_time: {typing_time}")
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accu_typing_time += typing_time
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timepoint = thinking_time_point + accu_typing_time
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message_segment = Seg(type="text", data=msg)
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logger.info(f"message_segment: {message_segment}")
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bot_message = MessageSending(
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message_id=think_id,
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chat_stream=chat,
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bot_user_info=bot_user_info,
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sender_info=userinfo,
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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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)
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print(f"bot_message: {bot_message}")
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if not mark_head:
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mark_head = True
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print(f"添加消息到message_set: {bot_message}")
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message_set.add_message(bot_message)
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# message_set 可以直接加入 message_manager
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# print(f"\033[1;32m[回复]\033[0m 将回复载入发送容器")
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logger.debug("添加message_set到message_manager")
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message_manager.add_message(message_set)
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bot_response_time = thinking_time_point
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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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# 检查是否 <没有找到> emoji
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if emoji_raw != None:
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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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if random() < 0.5:
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bot_response_time = thinking_time_point - 1
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else:
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bot_response_time = bot_response_time + 1
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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=think_id,
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chat_stream=chat,
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bot_user_info=bot_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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)
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message_manager.add_message(bot_message)
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emotion = await self.gpt._get_emotion_tags(raw_content)
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logger.debug(f"为 '{response}' 获取到的情感标签为：{emotion}")
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valuedict = {
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"happy": 0.5,
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"angry": -1,
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"sad": -0.5,
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"surprised": 0.2,
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"disgusted": -1.5,
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"fearful": -0.7,
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"neutral": 0.1,
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}
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await relationship_manager.update_relationship_value(
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chat_stream=chat, relationship_value=valuedict[emotion[0]]
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)
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# 使用情绪管理器更新情绪
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self.mood_manager.update_mood_from_emotion(
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emotion[0], global_config.mood_intensity_factor
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)
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# willing_manager.change_reply_willing_after_sent(
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# chat_stream=chat
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# )
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# 创建全局ChatBot实例
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chat_bot = ChatBot()
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