重构整个插件系统，尝试恢复可启动性，新增插件系统maibot-plugin-sdk依赖
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DrSmoothl
169
src/chat/event_helpers.py
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169
src/chat/event_helpers.py
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"""
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事件消息构建工具
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将 chat 层的消息对象 (SessionMessage / MessageSending) 转换为
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核心事件系统使用的 MaiMessages，供调用 event_bus.emit() 前使用。
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"""
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from typing import List, Optional, TYPE_CHECKING
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from src.common.logger import get_logger
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from src.core.types import EventType, MaiMessages
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if TYPE_CHECKING:
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from src.chat.message_receive.message import MessageSending, SessionMessage
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from src.common.data_models.llm_data_model import LLMGenerationDataModel
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logger = get_logger("event_helpers")
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def build_event_message(
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event_type: EventType | str,
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message: Optional["SessionMessage | MessageSending | MaiMessages"] = None,
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llm_prompt: Optional[str] = None,
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llm_response: Optional["LLMGenerationDataModel"] = None,
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stream_id: Optional[str] = None,
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action_usage: Optional[List[str]] = None,
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) -> Optional[MaiMessages]:
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"""根据事件类型和输入，准备和转换消息对象。
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迁移自 events_manager._prepare_message，保持相同的行为。
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"""
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if isinstance(message, MaiMessages):
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return message.deepcopy()
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if message:
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return _transform_event_message(message, llm_prompt, llm_response)
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if event_type not in (EventType.ON_START, EventType.ON_STOP):
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assert stream_id, "如果没有消息，必须为非启动/关闭事件提供流ID"
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if event_type in (EventType.ON_MESSAGE, EventType.ON_PLAN, EventType.POST_LLM, EventType.AFTER_LLM):
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return _build_message_from_stream(stream_id, llm_prompt, llm_response)
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else:
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return _build_message_without_raw(stream_id, llm_prompt, llm_response, action_usage)
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return None # ON_START / ON_STOP 没有消息体
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def _transform_event_message(
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message: "SessionMessage | MessageSending",
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llm_prompt: Optional[str] = None,
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llm_response: Optional["LLMGenerationDataModel"] = None,
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) -> MaiMessages:
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"""将 SessionMessage / MessageSending 转换为 MaiMessages。"""
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from maim_message import Seg
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from src.chat.message_receive.message import MessageSending
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transformed = MaiMessages(
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llm_prompt=llm_prompt,
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llm_response_content=llm_response.content if llm_response else None,
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llm_response_reasoning=llm_response.reasoning if llm_response else None,
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llm_response_model=llm_response.model if llm_response else None,
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llm_response_tool_call=llm_response.tool_calls if llm_response else None,
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raw_message=message.processed_plain_text or "",
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additional_data={},
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)
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# 消息段处理
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if isinstance(message, MessageSending):
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if message.message_segment.type == "seglist":
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transformed.message_segments = list(message.message_segment.data) # type: ignore
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else:
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transformed.message_segments = [message.message_segment]
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else:
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transformed.message_segments = [Seg(type="text", data=message.processed_plain_text or "")]
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# stream_id
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transformed.stream_id = message.session_id if hasattr(message, "session_id") else ""
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# 处理后文本
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transformed.plain_text = message.processed_plain_text
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# 基本信息
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if isinstance(message, MessageSending):
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transformed.message_base_info["platform"] = message.platform
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if message.session.group_id:
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transformed.is_group_message = True
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group_name = ""
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if (
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message.session.context
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and message.session.context.message
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and message.session.context.message.message_info.group_info
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):
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group_name = message.session.context.message.message_info.group_info.group_name
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transformed.message_base_info.update(
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{
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"group_id": message.session.group_id,
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"group_name": group_name,
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}
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)
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transformed.message_base_info.update(
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{
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"user_id": message.bot_user_info.user_id,
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"user_cardname": message.bot_user_info.user_cardname,
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"user_nickname": message.bot_user_info.user_nickname,
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}
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)
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if not transformed.is_group_message:
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transformed.is_private_message = True
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elif hasattr(message, "message_info") and message.message_info:
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if message.platform:
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transformed.message_base_info["platform"] = message.platform
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if message.message_info.group_info:
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transformed.is_group_message = True
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transformed.message_base_info.update(
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{
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"group_id": message.message_info.group_info.group_id,
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"group_name": message.message_info.group_info.group_name,
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}
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)
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if message.message_info.user_info:
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if not transformed.is_group_message:
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transformed.is_private_message = True
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transformed.message_base_info.update(
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{
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"user_id": message.message_info.user_info.user_id,
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"user_cardname": message.message_info.user_info.user_cardname,
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"user_nickname": message.message_info.user_info.user_nickname,
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}
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)
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return transformed
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def _build_message_from_stream(
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stream_id: str,
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llm_prompt: Optional[str] = None,
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llm_response: Optional["LLMGenerationDataModel"] = None,
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) -> MaiMessages:
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"""从 stream_id 查找会话消息并转换。"""
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from src.chat.message_receive.chat_manager import chat_manager
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session = chat_manager.get_session_by_session_id(stream_id)
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assert session, f"未找到流ID为 {stream_id} 的会话"
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return _transform_event_message(session.context.message, llm_prompt, llm_response)
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def _build_message_without_raw(
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stream_id: str,
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llm_prompt: Optional[str] = None,
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llm_response: Optional["LLMGenerationDataModel"] = None,
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action_usage: Optional[List[str]] = None,
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) -> MaiMessages:
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"""没有原始消息对象时，从 stream_id 构建最小 MaiMessages。"""
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from src.chat.message_receive.chat_manager import chat_manager
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session = chat_manager.get_session_by_session_id(stream_id)
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assert session, f"未找到流ID为 {stream_id} 的会话"
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return MaiMessages(
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stream_id=stream_id,
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llm_prompt=llm_prompt,
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llm_response_content=llm_response.content if llm_response else None,
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llm_response_reasoning=llm_response.reasoning if llm_response else None,
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llm_response_model=llm_response.model if llm_response else None,
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llm_response_tool_call=llm_response.tool_calls if llm_response else None,
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is_group_message=session.is_group_session,
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is_private_message=not session.is_group_session,
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action_usage=action_usage,
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additional_data={"response_is_processed": True},
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)
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