import time import urllib3 import base64 from abc import abstractmethod from dataclasses import dataclass from rich.traceback import install from typing import Optional, Any, List from maim_message import Seg, UserInfo, BaseMessageInfo, MessageBase from src.common.logger import get_logger from src.chat.utils.utils_image import get_image_manager from src.chat.utils.utils_voice import get_voice_text from src.chat.utils.utils_video import get_video_analyzer from src.config.config import global_config from .chat_stream import ChatStream install(extra_lines=3) logger = get_logger("chat_message") # 禁用SSL警告 urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) # 这个类是消息数据类，用于存储和管理消息数据。 # 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。 # 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。 @dataclass class Message(MessageBase): chat_stream: "ChatStream" = None # type: ignore reply: Optional["Message"] = None processed_plain_text: str = "" memorized_times: int = 0 def __init__( self, message_id: str, chat_stream: "ChatStream", user_info: UserInfo, message_segment: Optional[Seg] = None, timestamp: Optional[float] = None, reply: Optional["MessageRecv"] = None, processed_plain_text: str = "", ): # 使用传入的时间戳或当前时间 current_timestamp = timestamp if timestamp is not None else round(time.time(), 3) # 构造基础消息信息 message_info = BaseMessageInfo( platform=chat_stream.platform, message_id=message_id, time=current_timestamp, group_info=chat_stream.group_info, user_info=user_info, ) # 调用父类初始化 super().__init__(message_info=message_info, message_segment=message_segment, raw_message=None) # type: ignore self.chat_stream = chat_stream # 文本处理相关属性 self.processed_plain_text = processed_plain_text # 回复消息 self.reply = reply async def _process_message_segments(self, segment: Seg) -> str: # sourcery skip: remove-unnecessary-else, swap-if-else-branches """递归处理消息段，转换为文字描述 Args: segment: 要处理的消息段 Returns: str: 处理后的文本 """ if segment.type == "seglist": # 处理消息段列表 segments_text = [] for seg in segment.data: processed = await self._process_message_segments(seg) # type: ignore if processed: segments_text.append(processed) return " ".join(segments_text) else: # 处理单个消息段 return await self._process_single_segment(segment) # type: ignore @abstractmethod async def _process_single_segment(self, segment): pass @dataclass class MessageRecv(Message): """接收消息类，用于处理从MessageCQ序列化的消息""" def __init__(self, message_dict: dict[str, Any]): """从MessageCQ的字典初始化 Args: message_dict: MessageCQ序列化后的字典 """ self.message_info = BaseMessageInfo.from_dict(message_dict.get("message_info", {})) self.message_segment = Seg.from_dict(message_dict.get("message_segment", {})) self.raw_message = message_dict.get("raw_message") self.processed_plain_text = message_dict.get("processed_plain_text", "") self.is_emoji = False self.has_emoji = False self.is_picid = False self.has_picid = False self.is_voice = False self.is_video = False self.is_mentioned = None self.is_notify = False self.is_command = False self.priority_mode = "interest" self.priority_info = None self.interest_value: float = 0.0 def update_chat_stream(self, chat_stream: "ChatStream"): self.chat_stream = chat_stream async def process(self) -> None: """处理消息内容，生成纯文本和详细文本 这个方法必须在创建实例后显式调用，因为它包含异步操作。 """ self.processed_plain_text = await self._process_message_segments(self.message_segment) async def _process_single_segment(self, segment: Seg) -> str: """处理单个消息段 Args: segment: 消息段 Returns: str: 处理后的文本 """ try: if segment.type == "text": self.is_picid = False self.is_emoji = False self.is_video = False return segment.data # type: ignore elif segment.type == "image": # 如果是base64图片数据 if isinstance(segment.data, str): self.has_picid = True self.is_picid = True self.is_emoji = False self.is_video = False image_manager = get_image_manager() # print(f"segment.data: {segment.data}") _, processed_text = await image_manager.process_image(segment.data) return processed_text return "[发了一张图片，网卡了加载不出来]" elif segment.type == "emoji": self.has_emoji = True self.is_emoji = True self.is_picid = False self.is_voice = False self.is_video = False if isinstance(segment.data, str): return await get_image_manager().get_emoji_description(segment.data) return "[发了一个表情包，网卡了加载不出来]" elif segment.type == "voice": self.is_picid = False self.is_emoji = False self.is_voice = True self.is_video = False if isinstance(segment.data, str): return await get_voice_text(segment.data) return "[发了一段语音，网卡了加载不出来]" elif segment.type == "mention_bot": self.is_picid = False self.is_emoji = False self.is_voice = False self.is_video = False self.is_mentioned = float(segment.data) # type: ignore return "" elif segment.type == "priority_info": self.is_picid = False self.is_emoji = False self.is_voice = False if isinstance(segment.data, dict): # 处理优先级信息 self.priority_mode = "priority" self.priority_info = segment.data """ { 'message_type': 'vip', # vip or normal 'message_priority': 1.0, # 优先级，大为优先，float } """ return "" elif segment.type == "video": self.is_picid = False self.is_emoji = False self.is_voice = False self.is_video = True logger.info(f"接收到视频消息，数据类型: {type(segment.data)}") if global_config.video_analysis.enable: logger.info("已启用视频识别,开始识别") if isinstance(segment.data, dict): try: # 从Adapter接收的视频数据 video_base64 = segment.data.get("base64") filename = segment.data.get("filename", "video.mp4") logger.info(f"视频文件名: {filename}") logger.info(f"Base64数据长度: {len(video_base64) if video_base64 else 0}") if video_base64: # 解码base64视频数据 video_bytes = base64.b64decode(video_base64) logger.info(f"解码后视频大小: {len(video_bytes)} 字节") # 使用video analyzer分析视频 video_analyzer = get_video_analyzer() result = await video_analyzer.analyze_video_from_bytes( video_bytes, filename, prompt="请详细分析这个视频的内容，包括场景、人物、动作、情感等" ) logger.info(f"视频分析结果: {result}") # 返回视频分析结果 summary = result.get("summary", "") if summary: return f"[视频内容] {summary}" else: return "[已收到视频，但分析失败]" else: logger.warning("视频消息中没有base64数据") return "[收到视频消息，但数据异常]" except Exception as e: logger.error(f"视频处理失败: {str(e)}") import traceback logger.error(f"错误详情: {traceback.format_exc()}") return "[收到视频，但处理时出现错误]" else: logger.warning(f"视频消息数据不是字典格式: {type(segment.data)}") return "[发了一个视频，但格式不支持]" else: return "" else: logger.info("未启用视频识别") return "[视频]" except Exception as e: logger.error(f"处理消息段失败: {str(e)}, 类型: {segment.type}, 数据: {segment.data}") return f"[处理失败的{segment.type}消息]" @dataclass class MessageRecvS4U(MessageRecv): def __init__(self, message_dict: dict[str, Any]): super().__init__(message_dict) self.is_gift = False self.is_fake_gift = False self.is_superchat = False self.gift_info = None self.gift_name = None self.gift_count: Optional[str] = None self.superchat_info = None self.superchat_price = None self.superchat_message_text = None self.is_screen = False self.is_internal = False self.voice_done = None self.chat_info = None async def process(self) -> None: self.processed_plain_text = await self._process_message_segments(self.message_segment) async def _process_single_segment(self, segment: Seg) -> str: """处理单个消息段 Args: segment: 消息段 Returns: str: 处理后的文本 """ try: if segment.type == "text": self.is_voice = False self.is_picid = False self.is_emoji = False return segment.data # type: ignore elif segment.type == "image": self.is_voice = False # 如果是base64图片数据 if isinstance(segment.data, str): self.has_picid = True self.is_picid = True self.is_emoji = False image_manager = get_image_manager() # print(f"segment.data: {segment.data}") _, processed_text = await image_manager.process_image(segment.data) return processed_text return "[发了一张图片，网卡了加载不出来]" elif segment.type == "emoji": self.has_emoji = True self.is_emoji = True self.is_picid = False if isinstance(segment.data, str): return await get_image_manager().get_emoji_description(segment.data) return "[发了一个表情包，网卡了加载不出来]" elif segment.type == "voice": self.has_picid = False self.is_picid = False self.is_emoji = False self.is_voice = True if isinstance(segment.data, str): return await get_voice_text(segment.data) return "[发了一段语音，网卡了加载不出来]" elif segment.type == "mention_bot": self.is_voice = False self.is_picid = False self.is_emoji = False self.is_mentioned = float(segment.data) # type: ignore return "" elif segment.type == "priority_info": self.is_voice = False self.is_picid = False self.is_emoji = False if isinstance(segment.data, dict): # 处理优先级信息 self.priority_mode = "priority" self.priority_info = segment.data """ { 'message_type': 'vip', # vip or normal 'message_priority': 1.0, # 优先级，大为优先，float } """ return "" elif segment.type == "gift": self.is_voice = False self.is_gift = True # 解析gift_info，格式为"名称:数量" name, count = segment.data.split(":", 1) # type: ignore self.gift_info = segment.data self.gift_name = name.strip() self.gift_count = int(count.strip()) return "" elif segment.type == "voice_done": msg_id = segment.data logger.info(f"voice_done: {msg_id}") self.voice_done = msg_id return "" elif segment.type == "superchat": self.is_superchat = True self.superchat_info = segment.data price, message_text = segment.data.split(":", 1) # type: ignore self.superchat_price = price.strip() self.superchat_message_text = message_text.strip() self.processed_plain_text = str(self.superchat_message_text) self.processed_plain_text += ( f"（注意：这是一条超级弹幕信息，价值{self.superchat_price}元，请你认真回复）" ) return self.processed_plain_text elif segment.type == "screen": self.is_screen = True self.screen_info = segment.data return "屏幕信息" elif segment.type == "video": self.is_voice = False self.is_picid = False self.is_emoji = False logger.info(f"接收到视频消息，数据类型: {type(segment.data)}") if global_config.video_analysis.enable: logger.info("已启用视频识别,开始识别") if isinstance(segment.data, dict): try: # 从Adapter接收的视频数据 video_base64 = segment.data.get("base64") filename = segment.data.get("filename", "video.mp4") logger.info(f"视频文件名: {filename}") logger.info(f"Base64数据长度: {len(video_base64) if video_base64 else 0}") if video_base64: # 解码base64视频数据 video_bytes = base64.b64decode(video_base64) logger.info(f"解码后视频大小: {len(video_bytes)} 字节") # 使用video analyzer分析视频 video_analyzer = get_video_analyzer() result = await video_analyzer.analyze_video_from_bytes( video_bytes, filename, prompt="请详细分析这个视频的内容，包括场景、人物、动作、情感等" ) logger.info(f"视频分析结果: {result}") # 返回视频分析结果 summary = result.get("summary", "") if summary: return f"[视频内容] {summary}" else: return "[已收到视频，但分析失败]" else: logger.warning("视频消息中没有base64数据") return "[收到视频消息，但数据异常]" except Exception as e: logger.error(f"视频处理失败: {str(e)}") import traceback logger.error(f"错误详情: {traceback.format_exc()}") return "[收到视频，但处理时出现错误]" else: logger.warning(f"视频消息数据不是字典格式: {type(segment.data)}") return "[发了一个视频，但格式不支持]" else: return "" else: logger.info("未启用视频识别") return "[视频]" except Exception as e: logger.error(f"处理消息段失败: {str(e)}, 类型: {segment.type}, 数据: {segment.data}") return f"[处理失败的{segment.type}消息]" @dataclass class MessageProcessBase(Message): """消息处理基类，用于处理中和发送中的消息""" def __init__( self, message_id: str, chat_stream: "ChatStream", bot_user_info: UserInfo, message_segment: Optional[Seg] = None, reply: Optional["MessageRecv"] = None, thinking_start_time: float = 0, timestamp: Optional[float] = None, ): # 调用父类初始化，传递时间戳 super().__init__( message_id=message_id, timestamp=timestamp, chat_stream=chat_stream, user_info=bot_user_info, message_segment=message_segment, reply=reply, ) # 处理状态相关属性 self.thinking_start_time = thinking_start_time self.thinking_time = 0 def update_thinking_time(self) -> float: """更新思考时间""" self.thinking_time = round(time.time() - self.thinking_start_time, 2) return self.thinking_time async def _process_single_segment(self, seg: Seg) -> str | None: """处理单个消息段 Args: seg: 要处理的消息段 Returns: str: 处理后的文本 """ try: if seg.type == "text": return seg.data # type: ignore elif seg.type == "image": # 如果是base64图片数据 if isinstance(seg.data, str): return await get_image_manager().get_image_description(seg.data) return "[图片，网卡了加载不出来]" elif seg.type == "emoji": if isinstance(seg.data, str): return await get_image_manager().get_emoji_tag(seg.data) return "[表情，网卡了加载不出来]" elif seg.type == "voice": if isinstance(seg.data, str): return await get_voice_text(seg.data) return "[发了一段语音，网卡了加载不出来]" elif seg.type == "at": return f"[@{seg.data}]" elif seg.type == "reply": if self.reply and hasattr(self.reply, "processed_plain_text"): # print(f"self.reply.processed_plain_text: {self.reply.processed_plain_text}") # print(f"reply: {self.reply}") 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 return None else: return f"[{seg.type}:{str(seg.data)}]" except Exception as e: logger.error(f"处理消息段失败: {str(e)}, 类型: {seg.type}, 数据: {seg.data}") return f"[处理失败的{seg.type}消息]" def _generate_detailed_text(self) -> str: """生成详细文本，包含时间和用户信息""" # time_str = time.strftime("%m-%d %H:%M:%S", time.localtime(self.message_info.time)) timestamp = self.message_info.time user_info = self.message_info.user_info name = f"<{self.message_info.platform}:{user_info.user_id}:{user_info.user_nickname}:{user_info.user_cardname}>" # type: ignore return f"[{timestamp}]，{name} 说：{self.processed_plain_text}\n" @dataclass class MessageSending(MessageProcessBase): """发送状态的消息类""" def __init__( self, message_id: str, chat_stream: "ChatStream", bot_user_info: UserInfo, sender_info: UserInfo | None, # 用来记录发送者信息 message_segment: Seg, display_message: str = "", reply: Optional["MessageRecv"] = None, is_head: bool = False, is_emoji: bool = False, thinking_start_time: float = 0, apply_set_reply_logic: bool = False, reply_to: Optional[str] = None, selected_expressions:List[int] = None, ): # 调用父类初始化 super().__init__( message_id=message_id, chat_stream=chat_stream, bot_user_info=bot_user_info, message_segment=message_segment, reply=reply, thinking_start_time=thinking_start_time, ) # 发送状态特有属性 self.sender_info = sender_info self.reply_to_message_id = reply.message_info.message_id if reply else None self.is_head = is_head self.is_emoji = is_emoji self.apply_set_reply_logic = apply_set_reply_logic self.reply_to = reply_to # 用于显示发送内容与显示不一致的情况 self.display_message = display_message self.interest_value = 0.0 self.selected_expressions = selected_expressions def build_reply(self): """设置回复消息""" if self.reply: self.reply_to_message_id = self.reply.message_info.message_id self.message_segment = Seg( type="seglist", data=[ Seg(type="reply", data=self.reply.message_info.message_id), # type: ignore self.message_segment, ], ) async def process(self) -> None: """处理消息内容，生成纯文本和详细文本""" if self.message_segment: self.processed_plain_text = await self._process_message_segments(self.message_segment) def to_dict(self): ret = super().to_dict() ret["message_info"]["user_info"] = self.chat_stream.user_info.to_dict() return ret def is_private_message(self) -> bool: """判断是否为私聊消息""" return self.message_info.group_info is None or self.message_info.group_info.group_id is None @dataclass class MessageSet: """消息集合类，可以存储多个发送消息""" def __init__(self, chat_stream: "ChatStream", message_id: str): self.chat_stream = chat_stream self.message_id = message_id self.messages: list[MessageSending] = [] self.time = round(time.time(), 3) # 保留3位小数 def add_message(self, message: MessageSending) -> None: """添加消息到集合""" if not isinstance(message, MessageSending): raise TypeError("MessageSet只能添加MessageSending类型的消息") self.messages.append(message) self.messages.sort(key=lambda x: x.message_info.time) # type: ignore def get_message_by_index(self, index: int) -> Optional[MessageSending]: """通过索引获取消息""" return self.messages[index] if 0 <= index < len(self.messages) else None def get_message_by_time(self, target_time: float) -> Optional[MessageSending]: """获取最接近指定时间的消息""" if not self.messages: return None left, right = 0, len(self.messages) - 1 while left < right: mid = (left + right) // 2 if self.messages[mid].message_info.time < target_time: # type: ignore left = mid + 1 else: right = mid return self.messages[left] def clear_messages(self) -> None: """清空所有消息""" self.messages.clear() def remove_message(self, message: MessageSending) -> bool: """移除指定消息""" if message in self.messages: self.messages.remove(message) return True return False def __str__(self) -> str: return f"MessageSet(id={self.message_id}, count={len(self.messages)})" def __len__(self) -> int: return len(self.messages) def message_recv_from_dict(message_dict: dict) -> MessageRecv: return MessageRecv(message_dict) def message_from_db_dict(db_dict: dict) -> MessageRecv: """从数据库字典创建MessageRecv实例""" # 转换扁平的数据库字典为嵌套结构 message_info_dict = { "platform": db_dict.get("chat_info_platform"), "message_id": db_dict.get("message_id"), "time": db_dict.get("time"), "group_info": { "platform": db_dict.get("chat_info_group_platform"), "group_id": db_dict.get("chat_info_group_id"), "group_name": db_dict.get("chat_info_group_name"), }, "user_info": { "platform": db_dict.get("user_platform"), "user_id": db_dict.get("user_id"), "user_nickname": db_dict.get("user_nickname"), "user_cardname": db_dict.get("user_cardname"), }, } processed_text = db_dict.get("processed_plain_text", "") # 构建 MessageRecv 需要的字典 recv_dict = { "message_info": message_info_dict, "message_segment": {"type": "text", "data": processed_text}, # 从纯文本重建消息段 "raw_message": None, # 数据库中未存储原始消息 "processed_plain_text": processed_text, } # 创建 MessageRecv 实例 msg = MessageRecv(recv_dict) # 从数据库字典中填充其他可选字段 msg.interest_value = db_dict.get("interest_value", 0.0) msg.is_mentioned = db_dict.get("is_mentioned") msg.priority_mode = db_dict.get("priority_mode", "interest") msg.priority_info = db_dict.get("priority_info") msg.is_emoji = db_dict.get("is_emoji", False) msg.is_picid = db_dict.get("is_picid", False) return msg