2e3dd44ee9
- Updated imports and references from ChatStream to BotChatSession across multiple files. - Adjusted method signatures and internal logic to accommodate the new session management. - Ensured compatibility with existing functionality while improving code clarity and maintainability.
458 lines
16 KiB
Python
458 lines
16 KiB
Python
"""
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发送API模块
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专门负责发送各种类型的消息，采用标准Python包设计模式
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使用方式：
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from src.plugin_system.apis import send_api
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# 方式1：直接使用stream_id（推荐）
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await send_api.text_to_stream("hello", stream_id)
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await send_api.emoji_to_stream(emoji_base64, stream_id)
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await send_api.custom_to_stream("video", video_data, stream_id)
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# 方式2：使用群聊/私聊指定函数
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await send_api.text_to_group("hello", "123456")
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await send_api.text_to_user("hello", "987654")
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# 方式3：使用通用custom_message函数
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await send_api.custom_message("video", video_data, "123456", True)
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"""
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import traceback
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import time
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from typing import Optional, Union, Dict, List, TYPE_CHECKING, Tuple
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from src.common.logger import get_logger
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from src.common.data_models.message_data_model import ReplyContentType
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from src.config.config import global_config
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from src.chat.message_receive.chat_manager import chat_manager as _chat_manager
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from src.chat.message_receive.uni_message_sender import UniversalMessageSender
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from maim_message import Seg
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from src.common.data_models.mai_message_data_model import MaiMessage, UserInfo
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from src.chat.message_receive.message import MessageSending
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if TYPE_CHECKING:
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from src.common.data_models.database_data_model import DatabaseMessages
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from src.common.data_models.message_data_model import ReplySetModel, ReplyContent, ForwardNode
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logger = get_logger("send_api")
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# =============================================================================
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# 内部实现函数（不暴露给外部）
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# =============================================================================
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async def _send_to_target(
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message_segment: Seg,
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stream_id: str,
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display_message: str = "",
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typing: bool = False,
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set_reply: bool = False,
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reply_message: Optional["DatabaseMessages"] = None,
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storage_message: bool = True,
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show_log: bool = True,
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selected_expressions: Optional[List[int]] = None,
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) -> bool:
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"""向指定目标发送消息的内部实现
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Args:
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message_segment:
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stream_id: 目标流ID
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display_message: 显示消息
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typing: 是否模拟打字等待。
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reply_to: 回复消息，格式为"发送者:消息内容"
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storage_message: 是否存储消息到数据库
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show_log: 发送是否显示日志
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Returns:
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bool: 是否发送成功
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"""
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try:
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if set_reply and not reply_message:
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logger.warning("[SendAPI] 使用引用回复，但未提供回复消息")
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return False
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if show_log:
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logger.debug(f"[SendAPI] 发送{message_segment.type}消息到 {stream_id}")
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# 查找目标聊天流
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target_stream = _chat_manager.get_session_by_session_id(stream_id)
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if not target_stream:
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logger.error(f"[SendAPI] 未找到聊天流: {stream_id}")
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return False
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# 创建发送器
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message_sender = UniversalMessageSender()
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# 生成消息ID
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current_time = time.time()
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message_id = f"send_api_{int(current_time * 1000)}"
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# 构建机器人用户信息
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bot_user_info = UserInfo(
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user_id=global_config.bot.qq_account,
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user_nickname=global_config.bot.nickname,
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)
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reply_to_platform_id = ""
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anchor_message: Optional[MaiMessage] = None
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if reply_message:
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anchor_message = db_message_to_mai_message(reply_message)
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if anchor_message:
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logger.debug(f"[SendAPI] 找到匹配的回复消息，发送者: {anchor_message.message_info.user_info.user_id}")
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reply_to_platform_id = (
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f"{anchor_message.platform}:{anchor_message.message_info.user_info.user_id}"
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)
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# 构建 sender_info（私聊时为接收者信息）
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sender_info = None
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if target_stream.context and target_stream.context.message:
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sender_info = target_stream.context.message.message_info.user_info
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# 构建发送消息对象
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bot_message = MessageSending(
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message_id=message_id,
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session=target_stream,
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bot_user_info=bot_user_info,
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sender_info=sender_info,
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message_segment=message_segment,
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display_message=display_message,
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reply=anchor_message,
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is_head=True,
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is_emoji=(message_segment.type == "emoji"),
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thinking_start_time=current_time,
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reply_to=reply_to_platform_id,
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selected_expressions=selected_expressions,
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)
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# 发送消息
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sent_msg = await message_sender.send_message(
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bot_message,
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typing=typing,
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set_reply=set_reply,
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storage_message=storage_message,
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show_log=show_log,
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)
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if sent_msg:
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logger.debug(f"[SendAPI] 成功发送消息到 {stream_id}")
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return True
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else:
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logger.error("[SendAPI] 发送消息失败")
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return False
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except Exception as e:
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logger.error(f"[SendAPI] 发送消息时出错: {e}")
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traceback.print_exc()
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return False
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def db_message_to_mai_message(message_obj: "DatabaseMessages") -> Optional[MaiMessage]:
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"""将数据库消息重建为 MaiMessage 对象，用于回复引用。
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Args:
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message_obj: 插件系统的 DatabaseMessages 数据对象
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Returns:
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Optional[MaiMessage]: 构建的消息对象，如果信息不足则返回 None
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"""
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from datetime import datetime
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from src.common.data_models.mai_message_data_model import GroupInfo, MessageInfo
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from src.common.data_models.message_component_data_model import MessageSequence
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user_info = UserInfo(
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user_id=message_obj.user_info.user_id or "",
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user_nickname=message_obj.user_info.user_nickname or "",
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user_cardname=message_obj.user_info.user_cardname,
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)
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group_info = None
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if message_obj.chat_info.group_info:
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group_info = GroupInfo(
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group_id=message_obj.chat_info.group_info.group_id or "",
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group_name=message_obj.chat_info.group_info.group_name or "",
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)
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msg = MaiMessage(
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message_id=message_obj.message_id,
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timestamp=datetime.fromtimestamp(message_obj.time) if message_obj.time else datetime.now(),
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)
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msg.message_info = MessageInfo(user_info=user_info, group_info=group_info)
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msg.platform = message_obj.chat_info.platform or ""
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msg.session_id = message_obj.chat_info.stream_id or ""
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msg.processed_plain_text = message_obj.processed_plain_text
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msg.raw_message = MessageSequence(components=[])
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msg.initialized = True
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return msg
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# =============================================================================
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# 公共API函数 - 预定义类型的发送函数
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# =============================================================================
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async def text_to_stream(
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text: str,
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stream_id: str,
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typing: bool = False,
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set_reply: bool = False,
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reply_message: Optional["DatabaseMessages"] = None,
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storage_message: bool = True,
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selected_expressions: Optional[List[int]] = None,
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) -> bool:
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"""向指定流发送文本消息
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Args:
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text: 要发送的文本内容
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stream_id: 聊天流ID
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typing: 是否显示正在输入
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reply_to: 回复消息，格式为"发送者:消息内容"
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storage_message: 是否存储消息到数据库
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Returns:
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bool: 是否发送成功
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"""
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return await _send_to_target(
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message_segment=Seg(type="text", data=text),
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stream_id=stream_id,
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display_message="",
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typing=typing,
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set_reply=set_reply,
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reply_message=reply_message,
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storage_message=storage_message,
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selected_expressions=selected_expressions,
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)
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async def emoji_to_stream(
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emoji_base64: str,
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stream_id: str,
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storage_message: bool = True,
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set_reply: bool = False,
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reply_message: Optional["DatabaseMessages"] = None,
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) -> bool:
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"""向指定流发送表情包
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Args:
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emoji_base64: 表情包的base64编码
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stream_id: 聊天流ID
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storage_message: 是否存储消息到数据库
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Returns:
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bool: 是否发送成功
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"""
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return await _send_to_target(
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message_segment=Seg(type="emoji", data=emoji_base64),
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stream_id=stream_id,
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display_message="",
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typing=False,
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storage_message=storage_message,
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set_reply=set_reply,
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reply_message=reply_message,
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)
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async def image_to_stream(
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image_base64: str,
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stream_id: str,
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storage_message: bool = True,
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set_reply: bool = False,
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reply_message: Optional["DatabaseMessages"] = None,
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) -> bool:
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"""向指定流发送图片
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Args:
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image_base64: 图片的base64编码
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stream_id: 聊天流ID
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storage_message: 是否存储消息到数据库
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Returns:
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bool: 是否发送成功
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"""
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return await _send_to_target(
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message_segment=Seg(type="image", data=image_base64),
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stream_id=stream_id,
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display_message="",
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typing=False,
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storage_message=storage_message,
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set_reply=set_reply,
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reply_message=reply_message,
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)
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async def command_to_stream(
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command: Union[str, dict],
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stream_id: str,
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storage_message: bool = True,
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display_message: str = "",
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) -> bool:
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"""向指定流发送命令
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Args:
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command: 命令
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stream_id: 聊天流ID
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storage_message: 是否存储消息到数据库
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display_message: 显示消息
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Returns:
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bool: 是否发送成功
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"""
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return await _send_to_target(
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message_segment=Seg(type="command", data=command), # type: ignore
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stream_id=stream_id,
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display_message=display_message,
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typing=False,
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storage_message=storage_message,
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set_reply=False,
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)
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async def custom_to_stream(
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message_type: str,
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content: str | Dict,
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stream_id: str,
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display_message: str = "",
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typing: bool = False,
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reply_message: Optional["DatabaseMessages"] = None,
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set_reply: bool = False,
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storage_message: bool = True,
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show_log: bool = True,
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) -> bool:
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"""向指定流发送自定义类型消息
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Args:
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message_type: 消息类型，如"text"、"image"、"emoji"、"video"、"file"等
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content: 消息内容（通常是base64编码或文本）
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stream_id: 聊天流ID
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display_message: 显示消息
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typing: 是否显示正在输入
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reply_to: 回复消息，格式为"发送者:消息内容"
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storage_message: 是否存储消息到数据库
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show_log: 是否显示日志
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Returns:
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bool: 是否发送成功
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"""
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return await _send_to_target(
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message_segment=Seg(type=message_type, data=content), # type: ignore
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stream_id=stream_id,
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display_message=display_message,
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typing=typing,
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reply_message=reply_message,
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set_reply=set_reply,
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storage_message=storage_message,
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show_log=show_log,
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)
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async def custom_reply_set_to_stream(
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reply_set: "ReplySetModel",
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stream_id: str,
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display_message: str = "", # 基本没用
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typing: bool = False,
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reply_message: Optional["DatabaseMessages"] = None,
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set_reply: bool = False,
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storage_message: bool = True,
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show_log: bool = True,
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) -> bool:
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"""
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向指定流发送混合型消息集
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Args:
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reply_set: ReplySetModel 对象，包含多个 ReplyContent
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stream_id: 聊天流ID
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display_message: 显示消息
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typing: 是否显示正在输入
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reply_to: 回复消息，格式为"发送者:消息内容"
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storage_message: 是否存储消息到数据库
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show_log: 是否显示日志
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"""
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flag: bool = True
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for reply_content in reply_set.reply_data:
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status: bool = False
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message_seg, need_typing = _parse_content_to_seg(reply_content)
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status = await _send_to_target(
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message_segment=message_seg,
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stream_id=stream_id,
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display_message=display_message,
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typing=bool(need_typing and typing),
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reply_message=reply_message,
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set_reply=set_reply,
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storage_message=storage_message,
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show_log=show_log,
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)
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if not status:
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flag = False
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logger.error(
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f"[SendAPI] 发送{repr(reply_content.content_type)}消息失败，消息内容：{str(reply_content.content)[:100]}"
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)
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return flag
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def _parse_content_to_seg(reply_content: "ReplyContent") -> Tuple[Seg, bool]:
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"""
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把 ReplyContent 转换为 Seg 结构 (Forward 中仅递归一次)
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Args:
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reply_content: ReplyContent 对象
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Returns:
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Tuple[Seg, bool]: 转换后的 Seg 结构和是否需要typing的标志
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"""
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content_type = reply_content.content_type
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if content_type == ReplyContentType.TEXT:
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text_data: str = reply_content.content # type: ignore
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return Seg(type="text", data=text_data), True
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elif content_type == ReplyContentType.IMAGE:
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return Seg(type="image", data=reply_content.content), False # type: ignore
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elif content_type == ReplyContentType.EMOJI:
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return Seg(type="emoji", data=reply_content.content), False # type: ignore
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elif content_type == ReplyContentType.COMMAND:
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return Seg(type="command", data=reply_content.content), False # type: ignore
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elif content_type == ReplyContentType.VOICE:
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return Seg(type="voice", data=reply_content.content), False # type: ignore
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elif content_type == ReplyContentType.HYBRID:
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hybrid_message_list_data: List[ReplyContent] = reply_content.content # type: ignore
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assert isinstance(hybrid_message_list_data, list), "混合类型内容必须是列表"
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sub_seg_list: List[Seg] = []
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for sub_content in hybrid_message_list_data:
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sub_content_type = sub_content.content_type
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sub_content_data = sub_content.content
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if sub_content_type == ReplyContentType.TEXT:
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sub_seg_list.append(Seg(type="text", data=sub_content_data)) # type: ignore
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elif sub_content_type == ReplyContentType.IMAGE:
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sub_seg_list.append(Seg(type="image", data=sub_content_data)) # type: ignore
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elif sub_content_type == ReplyContentType.EMOJI:
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sub_seg_list.append(Seg(type="emoji", data=sub_content_data)) # type: ignore
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else:
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logger.warning(f"[SendAPI] 混合类型中不支持的子内容类型: {repr(sub_content_type)}")
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continue
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return Seg(type="seglist", data=sub_seg_list), True
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elif content_type == ReplyContentType.FORWARD:
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forward_message_list_data: List["ForwardNode"] = reply_content.content # type: ignore
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assert isinstance(forward_message_list_data, list), "转发类型内容必须是列表"
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forward_message_list: List[Dict] = []
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for forward_node in forward_message_list_data:
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message_segment = Seg(type="id", data=forward_node.content) # type: ignore
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user_info: Optional[UserInfo] = None
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if forward_node.user_id and forward_node.user_nickname:
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assert isinstance(forward_node.content, list), "转发节点内容必须是列表"
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user_info = UserInfo(user_id=forward_node.user_id, user_nickname=forward_node.user_nickname)
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single_node_content: List[Seg] = []
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for sub_content in forward_node.content:
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if sub_content.content_type != ReplyContentType.FORWARD:
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sub_seg, _ = _parse_content_to_seg(sub_content)
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single_node_content.append(sub_seg)
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message_segment = Seg(type="seglist", data=single_node_content)
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forward_message_list.append(
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MessageBase(
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message_segment=message_segment, message_info=BaseMessageInfo(user_info=user_info)
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).to_dict()
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)
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return Seg(type="forward", data=forward_message_list), False # type: ignore
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else:
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message_type_in_str = content_type.value if isinstance(content_type, ReplyContentType) else str(content_type)
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return Seg(type=message_type_in_str, data=reply_content.content), True # type: ignore
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