185 lines
7.3 KiB
Python
185 lines
7.3 KiB
Python
import time
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import asyncio
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import random
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from random import random as random_float
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from typing import Dict
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from ..config.config import global_config
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from .message import MessageSending, MessageThinking, MessageSet, MessageRecv
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from ..message.message_base import UserInfo, Seg
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from .message_sender import message_manager
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from ..moods.moods import MoodManager
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from ..chat_module.reasoning_chat.reasoning_generator import ResponseGenerator
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from src.common.logger import get_module_logger
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from src.heart_flow.heartflow import heartflow
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from ...common.database import db
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logger = get_module_logger("auto_speak")
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class AutoSpeakManager:
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def __init__(self):
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self._last_auto_speak_time: Dict[str, float] = {} # 记录每个聊天流上次自主发言的时间
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self.mood_manager = MoodManager.get_instance()
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self.gpt = ResponseGenerator() # 添加gpt实例
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self._started = False
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self._check_task = None
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self.db = db
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async def get_chat_info(self, chat_id: str) -> dict:
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"""从数据库获取聊天流信息"""
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chat_info = await self.db.chat_streams.find_one({"stream_id": chat_id})
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return chat_info
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async def start_auto_speak_check(self):
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"""启动自动发言检查任务"""
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if not self._started:
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self._check_task = asyncio.create_task(self._periodic_check())
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self._started = True
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logger.success("自动发言检查任务已启动")
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async def _periodic_check(self):
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"""定期检查是否需要自主发言"""
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while True and global_config.enable_think_flow:
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# 获取所有活跃的子心流
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active_subheartflows = []
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for chat_id, subheartflow in heartflow._subheartflows.items():
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if (
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subheartflow.is_active and subheartflow.current_state.willing > 0
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): # 只考虑活跃且意愿值大于0.5的子心流
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active_subheartflows.append((chat_id, subheartflow))
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logger.debug(
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f"发现活跃子心流 - 聊天ID: {chat_id}, 意愿值: {subheartflow.current_state.willing:.2f}"
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)
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if not active_subheartflows:
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logger.debug("当前没有活跃的子心流")
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await asyncio.sleep(20) # 添加异步等待
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continue
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# 随机选择一个活跃的子心流
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chat_id, subheartflow = random.choice(active_subheartflows)
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logger.info(f"随机选择子心流 - 聊天ID: {chat_id}, 意愿值: {subheartflow.current_state.willing:.2f}")
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# 检查是否应该自主发言
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if await self.check_auto_speak(subheartflow):
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logger.info(f"准备自主发言 - 聊天ID: {chat_id}")
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# 生成自主发言
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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="qq", # 默认使用qq平台
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)
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# 创建一个空的MessageRecv对象作为上下文
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message = MessageRecv(
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{
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"message_info": {
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"user_info": {"user_id": chat_id, "user_nickname": "", "platform": "qq"},
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"group_info": None,
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"platform": "qq",
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"time": time.time(),
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},
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"processed_plain_text": "",
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"raw_message": "",
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"is_emoji": False,
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}
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)
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await self.generate_auto_speak(
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subheartflow, message, bot_user_info, message.message_info["user_info"], message.message_info
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)
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else:
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logger.debug(f"不满足自主发言条件 - 聊天ID: {chat_id}")
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# 每分钟检查一次
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await asyncio.sleep(20)
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# await asyncio.sleep(5) # 发生错误时等待5秒再继续
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async def check_auto_speak(self, subheartflow) -> bool:
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"""检查是否应该自主发言"""
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if not subheartflow:
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return False
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current_time = time.time()
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chat_id = subheartflow.observe_chat_id
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# 获取上次自主发言时间
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if chat_id not in self._last_auto_speak_time:
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self._last_auto_speak_time[chat_id] = 0
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last_speak_time = self._last_auto_speak_time.get(chat_id, 0)
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# 如果距离上次自主发言不到5分钟，不发言
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if current_time - last_speak_time < 30:
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logger.debug(
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f"距离上次发言时间太短 - 聊天ID: {chat_id}, 剩余时间: {30 - (current_time - last_speak_time):.1f}秒"
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)
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return False
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# 获取当前意愿值
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current_willing = subheartflow.current_state.willing
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if current_willing > 0.1 and random_float() < 0.5:
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self._last_auto_speak_time[chat_id] = current_time
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logger.info(f"满足自主发言条件 - 聊天ID: {chat_id}, 意愿值: {current_willing:.2f}")
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return True
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logger.debug(f"不满足自主发言条件 - 聊天ID: {chat_id}, 意愿值: {current_willing:.2f}")
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return False
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async def generate_auto_speak(self, subheartflow, message, bot_user_info: UserInfo, userinfo, messageinfo):
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"""生成自主发言内容"""
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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=None, # 不需要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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message_manager.add_message(thinking_message)
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# 生成自主发言内容
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try:
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response, raw_content = await self.gpt.generate_response(message)
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except Exception as e:
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logger.error(f"生成自主发言内容时发生错误: {e}")
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return False
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if response:
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message_set = MessageSet(None, think_id) # 不需要chat_stream
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mark_head = False
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for msg in response:
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message_segment = Seg(type="text", data=msg)
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bot_message = MessageSending(
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message_id=think_id,
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chat_stream=None, # 不需要chat_stream
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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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thinking_start_time=thinking_time_point,
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)
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if not mark_head:
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mark_head = True
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message_set.add_message(bot_message)
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message_manager.add_message(message_set)
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# 更新情绪和关系
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stance, emotion = await self.gpt._get_emotion_tags(raw_content, message.processed_plain_text)
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self.mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor)
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return True
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return False
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# 创建全局AutoSpeakManager实例
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auto_speak_manager = AutoSpeakManager()
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