1b3a2342ce
-更新PlusCommand以使用DatabaseMessages而不是MessageRecv。 -将消息处理逻辑重构到一个新模块message_processor.py中，以处理消息段并从消息字典中创建DatabaseMessages。 -删除了已弃用的MessageRecv类及其相关逻辑。 -调整了各种插件以适应新的DatabaseMessages结构。 -增强了消息处理功能中的错误处理和日志记录。
289 lines
11 KiB
Python
289 lines
11 KiB
Python
import base64
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import time
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from abc import ABCMeta, abstractmethod
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from dataclasses import dataclass
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from typing import Any, Optional, Union
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import urllib3
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from maim_message import BaseMessageInfo, MessageBase, Seg, UserInfo
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from rich.traceback import install
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from src.chat.message_receive.chat_stream import ChatStream
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from src.chat.utils.self_voice_cache import consume_self_voice_text
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from src.chat.utils.utils_image import get_image_manager
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from src.chat.utils.utils_video import get_video_analyzer, is_video_analysis_available
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from src.chat.utils.utils_voice import get_voice_text
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from src.common.data_models.database_data_model import DatabaseMessages
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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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install(extra_lines=3)
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logger = get_logger("chat_message")
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# 禁用SSL警告
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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# 这个类是消息数据类，用于存储和管理消息数据。
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# 它定义了消息的属性，包括群组ID、用户ID、消息ID、原始消息内容、纯文本内容和时间戳。
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# 它还定义了两个辅助属性：keywords用于提取消息的关键词，is_plain_text用于判断消息是否为纯文本。
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@dataclass
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class Message(MessageBase, metaclass=ABCMeta):
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chat_stream: Optional["ChatStream"] = None
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reply: Optional["Message"] = None
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processed_plain_text: str = ""
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memorized_times: int = 0
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def __init__(
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self,
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message_id: str,
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chat_stream: "ChatStream",
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user_info: UserInfo,
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message_segment: Seg | None = None,
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timestamp: float | None = None,
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reply: Optional["DatabaseMessages"] = None,
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processed_plain_text: str = "",
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):
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# 使用传入的时间戳或当前时间
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current_timestamp = timestamp if timestamp is not None else round(time.time(), 3)
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# 构造基础消息信息
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message_info = BaseMessageInfo(
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platform=chat_stream.platform,
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message_id=message_id,
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time=current_timestamp,
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group_info=chat_stream.group_info,
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user_info=user_info,
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)
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# 调用父类初始化
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super().__init__(message_info=message_info, message_segment=message_segment, raw_message=None) # type: ignore
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self.chat_stream = chat_stream
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# 文本处理相关属性
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self.processed_plain_text = processed_plain_text
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# 回复消息
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self.reply = reply
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async def _process_message_segments(self, segment: Seg) -> str:
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# sourcery skip: remove-unnecessary-else, swap-if-else-branches
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"""递归处理消息段，转换为文字描述
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Args:
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segment: 要处理的消息段
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Returns:
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str: 处理后的文本
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"""
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if segment.type == "seglist":
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# 处理消息段列表
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segments_text = []
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for seg in segment.data:
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processed = await self._process_message_segments(seg) # type: ignore
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if processed:
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segments_text.append(processed)
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return " ".join(segments_text)
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else:
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# 处理单个消息段
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return await self._process_single_segment(segment) # type: ignore
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@abstractmethod
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async def _process_single_segment(self, segment):
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pass
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@dataclass
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# MessageRecv 类已被完全移除，现在统一使用 DatabaseMessages
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# 如需从消息字典创建 DatabaseMessages，请使用：
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# from src.chat.message_receive.message_processor import process_message_from_dict
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#
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# 迁移完成日期: 2025-10-31
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@dataclass
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class MessageProcessBase(Message):
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"""消息处理基类，用于处理中和发送中的消息"""
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def __init__(
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self,
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message_id: str,
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chat_stream: "ChatStream",
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bot_user_info: UserInfo,
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message_segment: Seg | None = None,
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reply: Optional["DatabaseMessages"] = None,
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thinking_start_time: float = 0,
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timestamp: float | None = None,
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):
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# 调用父类初始化，传递时间戳
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super().__init__(
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message_id=message_id,
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timestamp=timestamp,
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chat_stream=chat_stream,
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user_info=bot_user_info,
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message_segment=message_segment,
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reply=reply,
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)
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# 处理状态相关属性
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self.thinking_start_time = thinking_start_time
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self.thinking_time = 0
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def update_thinking_time(self) -> float:
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"""更新思考时间"""
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self.thinking_time = round(time.time() - self.thinking_start_time, 2)
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return self.thinking_time
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async def _process_single_segment(self, seg: Seg) -> str | None:
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"""处理单个消息段
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Args:
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seg: 要处理的消息段
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Returns:
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str: 处理后的文本
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"""
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try:
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if seg.type == "text":
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return seg.data # type: ignore
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elif seg.type == "image":
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# 如果是base64图片数据
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if isinstance(seg.data, str):
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return await get_image_manager().get_image_description(seg.data)
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return "[图片，网卡了加载不出来]"
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elif seg.type == "emoji":
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if isinstance(seg.data, str):
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return await get_image_manager().get_emoji_tag(seg.data)
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return "[表情，网卡了加载不出来]"
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elif seg.type == "voice":
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# 检查消息是否由机器人自己发送
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# 检查消息是否由机器人自己发送
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if self.message_info and self.message_info.user_info and str(self.message_info.user_info.user_id) == str(global_config.bot.qq_account):
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logger.info(f"检测到机器人自身发送的语音消息 (User ID: {self.message_info.user_info.user_id})，尝试从缓存获取文本。")
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if isinstance(seg.data, str):
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cached_text = consume_self_voice_text(seg.data)
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if cached_text:
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logger.info(f"成功从缓存中获取语音文本: '{cached_text[:70]}...'")
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return f"[语音：{cached_text}]"
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else:
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logger.warning("机器人自身语音消息缓存未命中，将回退到标准语音识别。")
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# 标准语音识别流程 (也作为缓存未命中的后备方案)
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if isinstance(seg.data, str):
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return await get_voice_text(seg.data)
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return "[发了一段语音，网卡了加载不出来]"
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elif seg.type == "at":
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# 处理at消息，格式为"昵称:QQ号"
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if isinstance(seg.data, str) and ":" in seg.data:
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nickname, qq_id = seg.data.split(":", 1)
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return f"@{nickname}"
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return f"@{seg.data}" if isinstance(seg.data, str) else "@未知用户"
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elif seg.type == "reply":
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if self.reply and hasattr(self.reply, "processed_plain_text"):
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# print(f"self.reply.processed_plain_text: {self.reply.processed_plain_text}")
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# print(f"reply: {self.reply}")
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return f"[回复<{self.reply.message_info.user_info.user_nickname}({self.reply.message_info.user_info.user_id})> 的消息：{self.reply.processed_plain_text}]" # type: ignore
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return None
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else:
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return f"[{seg.type}:{seg.data!s}]"
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except Exception as e:
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logger.error(f"处理消息段失败: {e!s}, 类型: {seg.type}, 数据: {seg.data}")
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return f"[处理失败的{seg.type}消息]"
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def _generate_detailed_text(self) -> str:
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"""生成详细文本，包含时间和用户信息"""
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# time_str = time.strftime("%m-%d %H:%M:%S", time.localtime(self.message_info.time))
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timestamp = self.message_info.time
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user_info = self.message_info.user_info
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name = f"<{self.message_info.platform}:{user_info.user_id}:{user_info.user_nickname}:{user_info.user_cardname}>" # type: ignore
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return f"[{timestamp}]，{name} 说：{self.processed_plain_text}\n"
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@dataclass
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class MessageSending(MessageProcessBase):
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"""发送状态的消息类"""
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def __init__(
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self,
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message_id: str,
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chat_stream: "ChatStream",
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bot_user_info: UserInfo,
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sender_info: UserInfo | None, # 用来记录发送者信息
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message_segment: Seg,
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display_message: str = "",
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reply: Optional["DatabaseMessages"] = None,
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is_head: bool = False,
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is_emoji: bool = False,
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thinking_start_time: float = 0,
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apply_set_reply_logic: bool = False,
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reply_to: str | None = None,
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):
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# 调用父类初始化
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super().__init__(
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message_id=message_id,
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chat_stream=chat_stream,
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bot_user_info=bot_user_info,
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message_segment=message_segment,
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reply=reply,
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thinking_start_time=thinking_start_time,
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)
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# 发送状态特有属性
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self.sender_info = sender_info
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# 从 DatabaseMessages 获取 message_id
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if reply:
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self.reply_to_message_id = reply.message_id
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else:
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self.reply_to_message_id = None
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self.is_head = is_head
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self.is_emoji = is_emoji
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self.apply_set_reply_logic = apply_set_reply_logic
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self.reply_to = reply_to
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# 用于显示发送内容与显示不一致的情况
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self.display_message = display_message
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self.interest_value = 0.0
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self.selected_expressions = selected_expressions
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def build_reply(self):
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"""设置回复消息"""
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if self.reply:
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# 从 DatabaseMessages 获取 message_id
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message_id = self.reply.message_id
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if message_id:
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self.reply_to_message_id = message_id
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self.message_segment = Seg(
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type="seglist",
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data=[
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Seg(type="reply", data=message_id), # type: ignore
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self.message_segment,
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],
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)
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async def process(self) -> None:
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"""处理消息内容，生成纯文本和详细文本"""
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if self.message_segment:
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self.processed_plain_text = await self._process_message_segments(self.message_segment)
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def to_dict(self):
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ret = super().to_dict()
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if self.chat_stream and self.chat_stream.user_info:
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ret["message_info"]["user_info"] = self.chat_stream.user_info.to_dict()
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return ret
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def is_private_message(self) -> bool:
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"""判断是否为私聊消息"""
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return self.message_info.group_info is None or self.message_info.group_info.group_id is None
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# message_recv_from_dict 和 message_from_db_dict 函数已被移除
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# 请使用: from src.chat.message_receive.message_processor import process_message_from_dict
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