mirror of https://github.com/Mai-with-u/MaiBot.git
265 lines
10 KiB
Python
265 lines
10 KiB
Python
import asyncio
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import math
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from typing import Tuple
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from src.chat.memory_system.Hippocampus import hippocampus_manager
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from src.chat.message_receive.message import MessageRecv, MessageRecvS4U
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from maim_message.message_base import GroupInfo
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from src.chat.message_receive.storage import MessageStorage
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from src.chat.message_receive.chat_stream import get_chat_manager
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from src.chat.utils.timer_calculator import Timer
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from src.chat.utils.utils import is_mentioned_bot_in_message
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from src.common.logger import get_logger
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from src.config.config import global_config
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from src.mais4u.mais4u_chat.body_emotion_action_manager import action_manager
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from src.mais4u.mais4u_chat.s4u_mood_manager import mood_manager
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from src.mais4u.mais4u_chat.s4u_watching_manager import watching_manager
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from src.mais4u.mais4u_chat.context_web_manager import get_context_web_manager
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from src.mais4u.mais4u_chat.gift_manager import gift_manager
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from src.mais4u.mais4u_chat.screen_manager import screen_manager
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from .s4u_chat import get_s4u_chat_manager
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# from ..message_receive.message_buffer import message_buffer
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logger = get_logger("chat")
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async def _calculate_interest(message: MessageRecv) -> Tuple[float, bool]:
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"""计算消息的兴趣度
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Args:
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message: 待处理的消息对象
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Returns:
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Tuple[float, bool]: (兴趣度, 是否被提及)
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"""
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is_mentioned, _ = is_mentioned_bot_in_message(message)
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interested_rate = 0.0
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if global_config.memory.enable_memory:
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with Timer("记忆激活"):
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interested_rate,_ ,_= await hippocampus_manager.get_activate_from_text(
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message.processed_plain_text,
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fast_retrieval=True,
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)
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logger.debug(f"记忆激活率: {interested_rate:.2f}")
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text_len = len(message.processed_plain_text)
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# 根据文本长度分布调整兴趣度，采用分段函数实现更精确的兴趣度计算
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# 基于实际分布：0-5字符(26.57%), 6-10字符(27.18%), 11-20字符(22.76%), 21-30字符(10.33%), 31+字符(13.86%)
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if text_len == 0:
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base_interest = 0.01 # 空消息最低兴趣度
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elif text_len <= 5:
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# 1-5字符：线性增长 0.01 -> 0.03
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base_interest = 0.01 + (text_len - 1) * (0.03 - 0.01) / 4
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elif text_len <= 10:
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# 6-10字符：线性增长 0.03 -> 0.06
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base_interest = 0.03 + (text_len - 5) * (0.06 - 0.03) / 5
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elif text_len <= 20:
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# 11-20字符：线性增长 0.06 -> 0.12
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base_interest = 0.06 + (text_len - 10) * (0.12 - 0.06) / 10
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elif text_len <= 30:
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# 21-30字符：线性增长 0.12 -> 0.18
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base_interest = 0.12 + (text_len - 20) * (0.18 - 0.12) / 10
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elif text_len <= 50:
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# 31-50字符：线性增长 0.18 -> 0.22
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base_interest = 0.18 + (text_len - 30) * (0.22 - 0.18) / 20
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elif text_len <= 100:
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# 51-100字符：线性增长 0.22 -> 0.26
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base_interest = 0.22 + (text_len - 50) * (0.26 - 0.22) / 50
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else:
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# 100+字符：对数增长 0.26 -> 0.3，增长率递减
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base_interest = 0.26 + (0.3 - 0.26) * (math.log10(text_len - 99) / math.log10(901)) # 1000-99=901
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# 确保在范围内
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base_interest = min(max(base_interest, 0.01), 0.3)
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interested_rate += base_interest
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if is_mentioned:
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interest_increase_on_mention = 1
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interested_rate += interest_increase_on_mention
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return interested_rate, is_mentioned
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class S4UMessageProcessor:
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"""心流处理器，负责处理接收到的消息并计算兴趣度"""
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def __init__(self):
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"""初始化心流处理器，创建消息存储实例"""
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self.storage = MessageStorage()
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async def process_message(self, message: MessageRecvS4U, skip_gift_debounce: bool = False) -> None:
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"""处理接收到的原始消息数据
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主要流程:
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1. 消息解析与初始化
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2. 消息缓冲处理
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3. 过滤检查
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4. 兴趣度计算
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5. 关系处理
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Args:
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message_data: 原始消息字符串
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"""
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# 1. 消息解析与初始化
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groupinfo = message.message_info.group_info
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userinfo = message.message_info.user_info
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message_info = message.message_info
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chat = await get_chat_manager().get_or_create_stream(
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platform=message_info.platform,
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user_info=userinfo,
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group_info=groupinfo,
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)
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if await self.handle_internal_message(message):
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return
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if await self.hadle_if_voice_done(message):
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return
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# 处理礼物消息，如果消息被暂存则停止当前处理流程
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if not skip_gift_debounce and not await self.handle_if_gift(message):
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return
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await self.check_if_fake_gift(message)
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# 处理屏幕消息
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if await self.handle_screen_message(message):
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return
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await self.storage.store_message(message, chat)
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s4u_chat = get_s4u_chat_manager().get_or_create_chat(chat)
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await s4u_chat.add_message(message)
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_interested_rate, _ = await _calculate_interest(message)
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await mood_manager.start()
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# 一系列llm驱动的前处理
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chat_mood = mood_manager.get_mood_by_chat_id(chat.stream_id)
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asyncio.create_task(chat_mood.update_mood_by_message(message))
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chat_action = action_manager.get_action_state_by_chat_id(chat.stream_id)
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asyncio.create_task(chat_action.update_action_by_message(message))
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# 视线管理：收到消息时切换视线状态
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chat_watching = watching_manager.get_watching_by_chat_id(chat.stream_id)
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await chat_watching.on_message_received()
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# 上下文网页管理：启动独立task处理消息上下文
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asyncio.create_task(self._handle_context_web_update(chat.stream_id, message))
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# 日志记录
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if message.is_gift:
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logger.info(f"[S4U-礼物] {userinfo.user_nickname} 送出了 {message.gift_name} x{message.gift_count}")
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else:
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logger.info(f"[S4U]{userinfo.user_nickname}:{message.processed_plain_text}")
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async def handle_internal_message(self, message: MessageRecvS4U):
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if message.is_internal:
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group_info = GroupInfo(platform = "amaidesu_default",group_id = 660154,group_name = "内心")
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chat = await get_chat_manager().get_or_create_stream(
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platform = "amaidesu_default",
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user_info = message.message_info.user_info,
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group_info = group_info
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)
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s4u_chat = get_s4u_chat_manager().get_or_create_chat(chat)
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message.message_info.group_info = s4u_chat.chat_stream.group_info
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message.message_info.platform = s4u_chat.chat_stream.platform
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s4u_chat.internal_message.append(message)
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s4u_chat._new_message_event.set()
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logger.info(f"[{s4u_chat.stream_name}] 添加内部消息-------------------------------------------------------: {message.processed_plain_text}")
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return True
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return False
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async def handle_screen_message(self, message: MessageRecvS4U):
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if message.is_screen:
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screen_manager.set_screen(message.screen_info)
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return True
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return False
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async def hadle_if_voice_done(self, message: MessageRecvS4U):
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if message.voice_done:
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s4u_chat = get_s4u_chat_manager().get_or_create_chat(message.chat_stream)
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s4u_chat.voice_done = message.voice_done
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return True
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return False
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async def check_if_fake_gift(self, message: MessageRecvS4U) -> bool:
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"""检查消息是否为假礼物"""
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if message.is_gift:
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return False
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gift_keywords = ["送出了礼物", "礼物", "送出了","投喂"]
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if any(keyword in message.processed_plain_text for keyword in gift_keywords):
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message.is_fake_gift = True
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return True
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return False
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async def handle_if_gift(self, message: MessageRecvS4U) -> bool:
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"""处理礼物消息
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Returns:
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bool: True表示应该继续处理消息，False表示消息已被暂存不需要继续处理
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"""
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if message.is_gift:
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# 定义防抖完成后的回调函数
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def gift_callback(merged_message: MessageRecvS4U):
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"""礼物防抖完成后的回调"""
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# 创建异步任务来处理合并后的礼物消息，跳过防抖处理
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asyncio.create_task(self.process_message(merged_message, skip_gift_debounce=True))
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# 交给礼物管理器处理，并传入回调函数
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# 对于礼物消息，handle_gift 总是返回 False（消息被暂存）
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await gift_manager.handle_gift(message, gift_callback)
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return False # 消息被暂存，不继续处理
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return True # 非礼物消息，继续正常处理
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async def _handle_context_web_update(self, chat_id: str, message: MessageRecv):
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"""处理上下文网页更新的独立task
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Args:
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chat_id: 聊天ID
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message: 消息对象
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"""
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try:
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logger.debug(f"🔄 开始处理上下文网页更新: {message.message_info.user_info.user_nickname}")
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context_manager = get_context_web_manager()
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# 只在服务器未启动时启动（避免重复启动）
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if context_manager.site is None:
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logger.info("🚀 首次启动上下文网页服务器...")
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await context_manager.start_server()
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# 添加消息到上下文并更新网页
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await asyncio.sleep(1.5)
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await context_manager.add_message(chat_id, message)
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logger.debug(f"✅ 上下文网页更新完成: {message.message_info.user_info.user_nickname}")
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except Exception as e:
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logger.error(f"❌ 处理上下文网页更新失败: {e}", exc_info=True)
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