炸掉
This commit is contained in:
UnCLAS-Prommer
committed by
DrSmoothl
DrSmoothl
parent
3ea14a85c3
commit
cd81f943e3
@@ -16,8 +16,8 @@ from src.chat.brain_chat.brain_planner import BrainPlanner
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from src.chat.planner_actions.action_modifier import ActionModifier
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from src.chat.planner_actions.action_manager import ActionManager
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from src.chat.heart_flow.hfc_utils import CycleDetail
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from src.bw_learner.expression_learner import expression_learner_manager
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from src.bw_learner.message_recorder import extract_and_distribute_messages
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from src.bw_learner.expression_learner_old import expression_learner_manager
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from src.bw_learner.message_recorder_old import extract_and_distribute_messages
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from src.person_info.person_info import Person
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from src.core.types import ActionInfo, EventType
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from src.core.event_bus import event_bus
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@@ -63,7 +63,7 @@ class BrainChatting:
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用于在特定聊天流中生成回复。
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"""
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def __init__(self, chat_id: str):
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def __init__(self, session_id: str):
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"""
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BrainChatting 初始化函数
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@@ -73,8 +73,8 @@ class BrainChatting:
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performance_version: 性能记录版本号，用于区分不同启动版本
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"""
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# 基础属性
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self.stream_id: str = chat_id # 聊天流ID
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self.chat_stream: BotChatSession = _chat_manager.get_session_by_session_id(self.stream_id) # type: ignore
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self.stream_id: str = session_id # 聊天流ID
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self.chat_stream: ChatStream = get_chat_manager().get_stream(self.stream_id) # type: ignore
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if not self.chat_stream:
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raise ValueError(f"无法找到聊天流: {self.stream_id}")
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self.log_prefix = f"[{_chat_manager.get_session_name(self.stream_id) or self.stream_id}]"
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@@ -269,7 +269,7 @@ class BrainChatting:
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# Expression Reflection Check
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# 检查是否需要提问表达反思
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# -------------------------------------------------------------------------
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from src.bw_learner.expression_reflector import expression_reflector_manager
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from src.bw_learner.expression_reflector_old import expression_reflector_manager
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reflector = expression_reflector_manager.get_or_create_reflector(self.stream_id)
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asyncio.create_task(reflector.check_and_ask())
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@@ -10,6 +10,7 @@ from src.common.logger import get_logger
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from src.common.utils.utils_session import SessionUtils
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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
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from src.bw_learner.expression_reflector import ExpressionReflector
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if TYPE_CHECKING:
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from src.chat.message_receive.message import SessionMessage
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@@ -52,6 +53,9 @@ class HeartFChatting:
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# Asyncio Event 用于控制循环的开始和结束
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self._cycle_event = asyncio.Event()
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# 反思器
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self.reflector = ExpressionReflector(session_id)
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async def start(self):
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"""启动 HeartFChatting 的主循环"""
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# 先检查是否已经启动运行
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@@ -160,7 +164,12 @@ class HeartFChatting:
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async def _judge_and_response(self, mentioned_message: Optional["SessionMessage"] = None):
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"""判定和生成回复"""
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# TODO: 在expression和reflector重构完成后完成这里的逻辑
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await self.reflector.check_and_ask()
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if self.reflector.reflect_tracker.tracking and await self.reflector.reflect_tracker.trigger_tracker():
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logger.info(f"{self.log_prefix} 追踪检查已解决，结束追踪器")
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self.reflector.reflect_tracker.reset_tracker() # 结束当前追踪器
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# TODO: 完成反思器之后的逻辑
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def _handle_loop_completion(self, task: asyncio.Task):
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"""当 _hfc_func 任务完成时执行的回调。"""
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814
src/chat/heart_flow/heartFC_chat_old.py
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814
src/chat/heart_flow/heartFC_chat_old.py
Normal file
@@ -0,0 +1,814 @@
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import asyncio
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import time
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import traceback
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import random
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from typing import List, Optional, Dict, Any, Tuple, TYPE_CHECKING
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from rich.traceback import install
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from src.config.config import global_config
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from src.common.logger import get_logger
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from src.common.data_models.info_data_model import ActionPlannerInfo
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from src.common.data_models.message_data_model import ReplyContentType
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from src.chat.message_receive.chat_manager import chat_manager, BotChatSession
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from src.chat.utils.prompt_builder import global_prompt_manager
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from src.chat.utils.timer_calculator import Timer
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from src.chat.planner_actions.planner import ActionPlanner
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from src.chat.planner_actions.action_modifier import ActionModifier
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from src.chat.planner_actions.action_manager import ActionManager
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from src.chat.heart_flow.hfc_utils import CycleDetail
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from src.bw_learner.expression_learner_old import expression_learner_manager
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from src.chat.heart_flow.frequency_control import frequency_control_manager
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from src.bw_learner.reflect_tracker import reflect_tracker_manager
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from src.bw_learner.expression_reflector_old import expression_reflector_manager
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from src.bw_learner.message_recorder_old import extract_and_distribute_messages
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from src.person_info.person_info import Person
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from src.plugin_system.base.component_types import EventType, ActionInfo
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from src.plugin_system.core import events_manager
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from src.plugin_system.apis import generator_api, send_api, message_api, database_api
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from src.chat.utils.chat_message_builder import (
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build_readable_messages_with_id,
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get_raw_msg_before_timestamp_with_chat,
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)
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from src.chat.utils.utils import record_replyer_action_temp
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from src.memory_system.chat_history_summarizer import ChatHistorySummarizer
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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
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ERROR_LOOP_INFO = {
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"loop_plan_info": {
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"action_result": {
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"action_type": "error",
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"action_data": {},
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"reasoning": "循环处理失败",
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},
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},
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"loop_action_info": {
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"action_taken": False,
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"reply_text": "",
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"command": "",
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"taken_time": time.time(),
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},
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}
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install(extra_lines=3)
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# 注释：原来的动作修改超时常量已移除，因为改为顺序执行
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logger = get_logger("hfc") # Logger Name Changed
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class HeartFChatting:
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"""
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管理一个连续的Focus Chat循环
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用于在特定聊天流中生成回复。
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其生命周期现在由其关联的 SubHeartflow 的 FOCUSED 状态控制。
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"""
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def __init__(self, session_id: str):
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"""
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HeartFChatting 初始化函数
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参数:
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session_id: 聊天会话唯一标识符(如session_id)
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on_stop_focus_chat: 当收到stop_focus_chat命令时调用的回调函数
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performance_version: 性能记录版本号，用于区分不同启动版本
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"""
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# 基础属性
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self.session_id: str = session_id # 聊天会话ID
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session = chat_manager.get_session_by_session_id(session_id)
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if not session:
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raise ValueError(f"未找到 session_id={session_id} 的聊天会话")
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self.chat_session: BotChatSession = session
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self.log_prefix = f"[{chat_manager.get_session_name(self.session_id) or self.session_id}]"
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self.expression_learner = expression_learner_manager.get_expression_learner(self.session_id)
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self.action_manager = ActionManager()
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self.action_planner = ActionPlanner(chat_id=self.session_id, action_manager=self.action_manager)
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self.action_modifier = ActionModifier(action_manager=self.action_manager, chat_id=self.session_id)
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# 循环控制内部状态
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self.running: bool = False
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self._loop_task: Optional[asyncio.Task] = None # 主循环任务
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# 添加循环信息管理相关的属性
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self.history_loop: List[CycleDetail] = []
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self._cycle_counter = 0
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self._current_cycle_detail: CycleDetail = None # type: ignore
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self.last_read_time = time.time() - 2
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self.is_mute = False
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self.last_active_time = time.time() # 记录上一次非noreply时间
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self.question_probability_multiplier = 1
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self.questioned = False
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# 跟踪连续 no_reply 次数，用于动态调整阈值
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self.consecutive_no_reply_count = 0
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# 聊天内容概括器
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self.chat_history_summarizer = ChatHistorySummarizer(session_id=self.session_id)
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async def start(self):
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"""检查是否需要启动主循环，如果未激活则启动。"""
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# 如果循环已经激活，直接返回
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if self.running:
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logger.debug(f"{self.log_prefix} HeartFChatting 已激活，无需重复启动")
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return
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try:
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# 标记为活动状态，防止重复启动
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self.running = True
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self._loop_task = asyncio.create_task(self._main_chat_loop())
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self._loop_task.add_done_callback(self._handle_loop_completion)
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# 启动聊天内容概括器的后台定期检查循环
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await self.chat_history_summarizer.start()
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logger.info(f"{self.log_prefix} HeartFChatting 启动完成")
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except Exception as e:
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# 启动失败时重置状态
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self.running = False
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self._loop_task = None
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logger.error(f"{self.log_prefix} HeartFChatting 启动失败: {e}")
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raise
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def _handle_loop_completion(self, task: asyncio.Task):
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"""当 _hfc_loop 任务完成时执行的回调。"""
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try:
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if exception := task.exception():
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logger.error(f"{self.log_prefix} HeartFChatting: 脱离了聊天(异常): {exception}")
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logger.error(traceback.format_exc()) # Log full traceback for exceptions
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else:
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logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天 (外部停止)")
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except asyncio.CancelledError:
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logger.info(f"{self.log_prefix} HeartFChatting: 结束了聊天")
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def start_cycle(self) -> Tuple[Dict[str, float], str]:
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self._cycle_counter += 1
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self._current_cycle_detail = CycleDetail(self._cycle_counter)
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self._current_cycle_detail.thinking_id = f"tid{str(round(time.time(), 2))}"
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cycle_timers = {}
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return cycle_timers, self._current_cycle_detail.thinking_id
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def end_cycle(self, loop_info, cycle_timers):
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self._current_cycle_detail.set_loop_info(loop_info)
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self.history_loop.append(self._current_cycle_detail)
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self._current_cycle_detail.timers = cycle_timers
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self._current_cycle_detail.end_time = time.time()
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def print_cycle_info(self, cycle_timers):
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# 记录循环信息和计时器结果
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timer_strings = []
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for name, elapsed in cycle_timers.items():
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if elapsed < 0.1:
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# 不显示小于0.1秒的计时器
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continue
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formatted_time = f"{elapsed:.2f}秒"
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timer_strings.append(f"{name}: {formatted_time}")
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logger.info(
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f"{self.log_prefix} 第{self._current_cycle_detail.cycle_id}次思考,"
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f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒;" # type: ignore
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+ (f"详情: {'; '.join(timer_strings)}" if timer_strings else "")
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)
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async def _loopbody(self):
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recent_messages_list = message_api.get_messages_by_time_in_chat(
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chat_id=self.session_id,
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start_time=self.last_read_time,
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end_time=time.time(),
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limit=20,
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limit_mode="latest",
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filter_mai=True,
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filter_command=False,
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filter_intercept_message_level=0,
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)
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# 根据连续 no_reply 次数动态调整阈值
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# 3次 no_reply 时，阈值调高到 1.5（50%概率为1，50%概率为2）
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# 5次 no_reply 时，提高到 2（大于等于两条消息的阈值）
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if self.consecutive_no_reply_count >= 5:
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threshold = 2
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elif self.consecutive_no_reply_count >= 3:
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# 1.5 的含义：50%概率为1，50%概率为2
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threshold = 2 if random.random() < 0.5 else 1
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else:
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threshold = 1
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if len(recent_messages_list) >= threshold:
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# for message in recent_messages_list:
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# print(message.processed_plain_text)
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self.last_read_time = time.time()
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# !此处使at或者提及必定回复
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mentioned_message = None
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for message in recent_messages_list:
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if (message.is_mentioned or message.is_at) and global_config.chat.mentioned_bot_reply:
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mentioned_message = message
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# logger.info(f"{self.log_prefix} 当前talk_value: {TempMethods.get_talk_value(self.stream_id)}")
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# *控制频率用
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if mentioned_message:
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await self._observe(recent_messages_list=recent_messages_list, force_reply_message=mentioned_message)
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elif (
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random.random()
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< TempMethodsHFC.get_talk_value(self.session_id)
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* frequency_control_manager.get_or_create_frequency_control(self.session_id).get_talk_frequency_adjust()
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):
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await self._observe(recent_messages_list=recent_messages_list)
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else:
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# 没有提到，继续保持沉默，等待5秒防止频繁触发
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await asyncio.sleep(10)
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return True
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else:
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await asyncio.sleep(0.2)
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return True
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return True
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async def _send_and_store_reply(
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self,
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response_set: "ReplySetModel",
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action_message: "DatabaseMessages",
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cycle_timers: Dict[str, float],
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thinking_id,
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actions,
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selected_expressions: Optional[List[int]] = None,
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quote_message: Optional[bool] = None,
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) -> Tuple[Dict[str, Any], str, Dict[str, float]]:
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with Timer("回复发送", cycle_timers):
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reply_text = await self._send_response(
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reply_set=response_set,
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message_data=action_message,
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selected_expressions=selected_expressions,
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quote_message=quote_message,
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)
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# 获取 platform，如果不存在则从 chat_stream 获取，如果还是 None 则使用默认值
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platform = action_message.chat_info.platform
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if platform is None:
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platform = getattr(self.chat_stream, "platform", "unknown")
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person = Person(platform=platform, user_id=action_message.user_info.user_id)
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person_name = person.person_name
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action_prompt_display = f"你对{person_name}进行了回复：{reply_text}"
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await database_api.store_action_info(
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chat_stream=self.chat_stream,
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action_build_into_prompt=False,
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action_prompt_display=action_prompt_display,
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action_done=True,
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thinking_id=thinking_id,
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action_data={"reply_text": reply_text},
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action_name="reply",
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)
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# 构建循环信息
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loop_info: Dict[str, Any] = {
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"loop_plan_info": {
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"action_result": actions,
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},
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"loop_action_info": {
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"action_taken": True,
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"reply_text": reply_text,
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"command": "",
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"taken_time": time.time(),
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},
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}
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return loop_info, reply_text, cycle_timers
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async def _observe(
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self, # interest_value: float = 0.0,
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recent_messages_list: Optional[List["DatabaseMessages"]] = None,
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force_reply_message: Optional["DatabaseMessages"] = None,
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) -> bool: # sourcery skip: merge-else-if-into-elif, remove-redundant-if
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if recent_messages_list is None:
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recent_messages_list = []
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_reply_text = "" # 初始化reply_text变量，避免UnboundLocalError
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# -------------------------------------------------------------------------
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# ReflectTracker Check
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# 在每次回复前检查一次上下文，看是否有反思问题得到了解答
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# -------------------------------------------------------------------------
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reflector = expression_reflector_manager.get_or_create_reflector(self.session_id)
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await reflector.check_and_ask()
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tracker = reflect_tracker_manager.get_tracker(self.session_id)
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if tracker:
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resolved = await tracker.trigger_tracker()
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if resolved:
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reflect_tracker_manager.remove_tracker(self.session_id)
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logger.info(f"{self.log_prefix} ReflectTracker resolved and removed.")
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start_time = time.time()
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async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()):
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# 通过 MessageRecorder 统一提取消息并分发给 expression_learner 和 jargon_miner
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# 在 replyer 执行时触发，统一管理时间窗口，避免重复获取消息
|
||||
asyncio.create_task(extract_and_distribute_messages(self.session_id))
|
||||
|
||||
# 添加curious检测任务 - 检测聊天记录中的矛盾、冲突或需要提问的内容
|
||||
# asyncio.create_task(check_and_make_question(self.stream_id))
|
||||
# 添加聊天内容概括任务 - 累积、打包和压缩聊天记录
|
||||
# 注意：后台循环已在start()中启动，这里作为额外触发点，在有思考时立即处理
|
||||
# asyncio.create_task(self.chat_history_summarizer.process())
|
||||
|
||||
cycle_timers, thinking_id = self.start_cycle()
|
||||
logger.info(
|
||||
f"{self.log_prefix} 开始第{self._cycle_counter}次思考(频率: {TempMethodsHFC.get_talk_value(self.session_id)})"
|
||||
)
|
||||
|
||||
# 第一步：动作检查
|
||||
available_actions: Dict[str, ActionInfo] = {}
|
||||
try:
|
||||
await self.action_modifier.modify_actions()
|
||||
available_actions = self.action_manager.get_using_actions()
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 动作修改失败: {e}")
|
||||
|
||||
# 执行planner
|
||||
is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info()
|
||||
|
||||
message_list_before_now = get_raw_msg_before_timestamp_with_chat(
|
||||
chat_id=self.session_id,
|
||||
timestamp=time.time(),
|
||||
limit=int(global_config.chat.max_context_size * 0.6),
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
chat_content_block, message_id_list = build_readable_messages_with_id(
|
||||
messages=message_list_before_now,
|
||||
timestamp_mode="normal_no_YMD",
|
||||
read_mark=self.action_planner.last_obs_time_mark,
|
||||
truncate=True,
|
||||
show_actions=True,
|
||||
)
|
||||
|
||||
prompt_info = await self.action_planner.build_planner_prompt(
|
||||
is_group_chat=is_group_chat,
|
||||
chat_target_info=chat_target_info,
|
||||
current_available_actions=available_actions,
|
||||
chat_content_block=chat_content_block,
|
||||
message_id_list=message_id_list,
|
||||
)
|
||||
continue_flag, modified_message = await events_manager.handle_mai_events(
|
||||
EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id
|
||||
)
|
||||
if not continue_flag:
|
||||
return False
|
||||
if modified_message and modified_message._modify_flags.modify_llm_prompt:
|
||||
prompt_info = (modified_message.llm_prompt, prompt_info[1])
|
||||
|
||||
with Timer("规划器", cycle_timers):
|
||||
action_to_use_info = await self.action_planner.plan(
|
||||
loop_start_time=self.last_read_time,
|
||||
available_actions=available_actions,
|
||||
force_reply_message=force_reply_message,
|
||||
)
|
||||
|
||||
logger.info(
|
||||
f"{self.log_prefix} 决定执行{len(action_to_use_info)}个动作: {' '.join([a.action_type for a in action_to_use_info])}"
|
||||
)
|
||||
|
||||
# 3. 并行执行所有动作
|
||||
action_tasks = [
|
||||
asyncio.create_task(
|
||||
self._execute_action(action, action_to_use_info, thinking_id, available_actions, cycle_timers)
|
||||
)
|
||||
for action in action_to_use_info
|
||||
]
|
||||
|
||||
# 并行执行所有任务
|
||||
results = await asyncio.gather(*action_tasks, return_exceptions=True)
|
||||
|
||||
# 处理执行结果
|
||||
reply_loop_info = None
|
||||
reply_text_from_reply = ""
|
||||
action_success = False
|
||||
action_reply_text = ""
|
||||
|
||||
excute_result_str = ""
|
||||
for result in results:
|
||||
excute_result_str += f"{result['action_type']} 执行结果:{result['result']}\n"
|
||||
|
||||
if isinstance(result, BaseException):
|
||||
logger.error(f"{self.log_prefix} 动作执行异常: {result}")
|
||||
continue
|
||||
|
||||
if result["action_type"] != "reply":
|
||||
action_success = result["success"]
|
||||
action_reply_text = result["result"]
|
||||
elif result["action_type"] == "reply":
|
||||
if result["success"]:
|
||||
reply_loop_info = result["loop_info"]
|
||||
reply_text_from_reply = result["result"]
|
||||
else:
|
||||
logger.warning(f"{self.log_prefix} 回复动作执行失败")
|
||||
|
||||
self.action_planner.add_plan_excute_log(result=excute_result_str)
|
||||
|
||||
# 构建最终的循环信息
|
||||
if reply_loop_info:
|
||||
# 如果有回复信息，使用回复的loop_info作为基础
|
||||
loop_info = reply_loop_info
|
||||
# 更新动作执行信息
|
||||
loop_info["loop_action_info"].update(
|
||||
{
|
||||
"action_taken": action_success,
|
||||
"taken_time": time.time(),
|
||||
}
|
||||
)
|
||||
_reply_text = reply_text_from_reply
|
||||
else:
|
||||
# 没有回复信息，构建纯动作的loop_info
|
||||
loop_info = {
|
||||
"loop_plan_info": {
|
||||
"action_result": action_to_use_info,
|
||||
},
|
||||
"loop_action_info": {
|
||||
"action_taken": action_success,
|
||||
"reply_text": action_reply_text,
|
||||
"taken_time": time.time(),
|
||||
},
|
||||
}
|
||||
_reply_text = action_reply_text
|
||||
|
||||
self.end_cycle(loop_info, cycle_timers)
|
||||
self.print_cycle_info(cycle_timers)
|
||||
|
||||
end_time = time.time()
|
||||
if end_time - start_time < global_config.chat.planner_smooth:
|
||||
wait_time = global_config.chat.planner_smooth - (end_time - start_time)
|
||||
await asyncio.sleep(wait_time)
|
||||
else:
|
||||
await asyncio.sleep(0.1)
|
||||
return True
|
||||
|
||||
# async def _main_chat_loop(self):
|
||||
# """主循环，持续进行计划并可能回复消息，直到被外部取消。"""
|
||||
# try:
|
||||
# while self.running:
|
||||
# # 主循环
|
||||
# success = await self._loopbody()
|
||||
# await asyncio.sleep(0.1)
|
||||
# if not success:
|
||||
# break
|
||||
# except asyncio.CancelledError:
|
||||
# # 设置了关闭标志位后被取消是正常流程
|
||||
# logger.info(f"{self.log_prefix} 麦麦已关闭聊天")
|
||||
# except Exception:
|
||||
# logger.error(f"{self.log_prefix} 麦麦聊天意外错误，将于3s后尝试重新启动")
|
||||
# print(traceback.format_exc())
|
||||
# await asyncio.sleep(3)
|
||||
# self._loop_task = asyncio.create_task(self._main_chat_loop())
|
||||
# logger.error(f"{self.log_prefix} 结束了当前聊天循环")
|
||||
|
||||
async def _handle_action(
|
||||
self,
|
||||
action: str,
|
||||
action_reasoning: str,
|
||||
action_data: dict,
|
||||
cycle_timers: Dict[str, float],
|
||||
thinking_id: str,
|
||||
action_message: Optional["DatabaseMessages"] = None,
|
||||
) -> tuple[bool, str, str]:
|
||||
"""
|
||||
处理规划动作，使用动作工厂创建相应的动作处理器
|
||||
|
||||
参数:
|
||||
action: 动作类型
|
||||
action_reasoning: 决策理由
|
||||
action_data: 动作数据，包含不同动作需要的参数
|
||||
cycle_timers: 计时器字典
|
||||
thinking_id: 思考ID
|
||||
action_message: 消息数据
|
||||
返回:
|
||||
tuple[bool, str, str]: (是否执行了动作, 思考消息ID, 命令)
|
||||
"""
|
||||
try:
|
||||
# 使用工厂创建动作处理器实例
|
||||
try:
|
||||
action_handler = self.action_manager.create_action(
|
||||
action_name=action,
|
||||
action_data=action_data,
|
||||
cycle_timers=cycle_timers,
|
||||
thinking_id=thinking_id,
|
||||
chat_stream=self.chat_stream,
|
||||
log_prefix=self.log_prefix,
|
||||
action_reasoning=action_reasoning,
|
||||
action_message=action_message,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 创建动作处理器时出错: {e}")
|
||||
traceback.print_exc()
|
||||
return False, ""
|
||||
|
||||
# 处理动作并获取结果（固定记录一次动作信息）
|
||||
result = await action_handler.execute()
|
||||
success, action_text = result
|
||||
|
||||
return success, action_text
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 处理{action}时出错: {e}")
|
||||
traceback.print_exc()
|
||||
return False, ""
|
||||
|
||||
async def _send_response(
|
||||
self,
|
||||
reply_set: "ReplySetModel",
|
||||
message_data: "DatabaseMessages",
|
||||
selected_expressions: Optional[List[int]] = None,
|
||||
quote_message: Optional[bool] = None,
|
||||
) -> str:
|
||||
# 根据 llm_quote 配置决定是否使用 quote_message 参数
|
||||
if global_config.chat.llm_quote:
|
||||
# 如果配置为 true，使用 llm_quote 参数决定是否引用回复
|
||||
if quote_message is None:
|
||||
logger.warning(f"{self.log_prefix} quote_message 参数为空，不引用")
|
||||
need_reply = False
|
||||
else:
|
||||
need_reply = quote_message
|
||||
if need_reply:
|
||||
logger.info(f"{self.log_prefix} LLM 决定使用引用回复")
|
||||
else:
|
||||
# 如果配置为 false，使用原来的模式
|
||||
new_message_count = message_api.count_new_messages(
|
||||
chat_id=self.chat_stream.stream_id, start_time=self.last_read_time, end_time=time.time()
|
||||
)
|
||||
need_reply = new_message_count >= random.randint(2, 3) or time.time() - self.last_read_time > 90
|
||||
if need_reply:
|
||||
logger.info(
|
||||
f"{self.log_prefix} 从思考到回复，共有{new_message_count}条新消息，使用引用回复，或者上次回复时间超过90秒"
|
||||
)
|
||||
|
||||
reply_text = ""
|
||||
first_replied = False
|
||||
for reply_content in reply_set.reply_data:
|
||||
if reply_content.content_type != ReplyContentType.TEXT:
|
||||
continue
|
||||
data: str = reply_content.content # type: ignore
|
||||
if not first_replied:
|
||||
await send_api.text_to_stream(
|
||||
text=data,
|
||||
stream_id=self.chat_stream.stream_id,
|
||||
reply_message=message_data,
|
||||
set_reply=need_reply,
|
||||
typing=False,
|
||||
selected_expressions=selected_expressions,
|
||||
)
|
||||
first_replied = True
|
||||
else:
|
||||
await send_api.text_to_stream(
|
||||
text=data,
|
||||
stream_id=self.chat_stream.stream_id,
|
||||
reply_message=message_data,
|
||||
set_reply=False,
|
||||
typing=True,
|
||||
selected_expressions=selected_expressions,
|
||||
)
|
||||
reply_text += data
|
||||
|
||||
return reply_text
|
||||
|
||||
async def _execute_action(
|
||||
self,
|
||||
action_planner_info: ActionPlannerInfo,
|
||||
chosen_action_plan_infos: List[ActionPlannerInfo],
|
||||
thinking_id: str,
|
||||
available_actions: Dict[str, ActionInfo],
|
||||
cycle_timers: Dict[str, float],
|
||||
):
|
||||
"""执行单个动作的通用函数"""
|
||||
try:
|
||||
with Timer(f"动作{action_planner_info.action_type}", cycle_timers):
|
||||
# 直接当场执行no_reply逻辑
|
||||
if action_planner_info.action_type == "no_reply":
|
||||
# 直接处理no_reply逻辑，不再通过动作系统
|
||||
reason = action_planner_info.reasoning or "选择不回复"
|
||||
# logger.info(f"{self.log_prefix} 选择不回复，原因: {reason}")
|
||||
|
||||
# 增加连续 no_reply 计数
|
||||
self.consecutive_no_reply_count += 1
|
||||
|
||||
await database_api.store_action_info(
|
||||
chat_stream=self.chat_stream,
|
||||
action_build_into_prompt=False,
|
||||
action_prompt_display=reason,
|
||||
action_done=True,
|
||||
thinking_id=thinking_id,
|
||||
action_data={},
|
||||
action_name="no_reply",
|
||||
action_reasoning=reason,
|
||||
)
|
||||
|
||||
return {"action_type": "no_reply", "success": True, "result": "选择不回复", "command": ""}
|
||||
|
||||
elif action_planner_info.action_type == "reply":
|
||||
# 直接当场执行reply逻辑
|
||||
self.questioned = False
|
||||
# 刷新主动发言状态
|
||||
# 重置连续 no_reply 计数
|
||||
self.consecutive_no_reply_count = 0
|
||||
|
||||
reason = action_planner_info.reasoning or ""
|
||||
# 根据 think_mode 配置决定 think_level 的值
|
||||
think_mode = global_config.chat.think_mode
|
||||
if think_mode == "default":
|
||||
think_level = 0
|
||||
elif think_mode == "deep":
|
||||
think_level = 1
|
||||
elif think_mode == "dynamic":
|
||||
# dynamic 模式：从 planner 返回的 action_data 中获取
|
||||
think_level = action_planner_info.action_data.get("think_level", 1)
|
||||
else:
|
||||
# 默认使用 default 模式
|
||||
think_level = 0
|
||||
# 使用 action_reasoning（planner 的整体思考理由）作为 reply_reason
|
||||
planner_reasoning = action_planner_info.action_reasoning or reason
|
||||
|
||||
record_replyer_action_temp(
|
||||
chat_id=self.session_id,
|
||||
reason=reason,
|
||||
think_level=think_level,
|
||||
)
|
||||
|
||||
await database_api.store_action_info(
|
||||
chat_stream=self.chat_stream,
|
||||
action_build_into_prompt=False,
|
||||
action_prompt_display=reason,
|
||||
action_done=True,
|
||||
thinking_id=thinking_id,
|
||||
action_data={},
|
||||
action_name="reply",
|
||||
action_reasoning=reason,
|
||||
)
|
||||
|
||||
# 从 Planner 的 action_data 中提取未知词语列表（仅在 reply 时使用）
|
||||
unknown_words = None
|
||||
quote_message = None
|
||||
if isinstance(action_planner_info.action_data, dict):
|
||||
uw = action_planner_info.action_data.get("unknown_words")
|
||||
if isinstance(uw, list):
|
||||
cleaned_uw: List[str] = []
|
||||
for item in uw:
|
||||
if isinstance(item, str):
|
||||
s = item.strip()
|
||||
if s:
|
||||
cleaned_uw.append(s)
|
||||
if cleaned_uw:
|
||||
unknown_words = cleaned_uw
|
||||
|
||||
# 从 Planner 的 action_data 中提取 quote_message 参数
|
||||
qm = action_planner_info.action_data.get("quote")
|
||||
if qm is not None:
|
||||
# 支持多种格式：true/false, "true"/"false", 1/0
|
||||
if isinstance(qm, bool):
|
||||
quote_message = qm
|
||||
elif isinstance(qm, str):
|
||||
quote_message = qm.lower() in ("true", "1", "yes")
|
||||
elif isinstance(qm, (int, float)):
|
||||
quote_message = bool(qm)
|
||||
|
||||
logger.info(f"{self.log_prefix} {qm}引用回复设置: {quote_message}")
|
||||
|
||||
success, llm_response = await generator_api.generate_reply(
|
||||
chat_stream=self.chat_stream,
|
||||
reply_message=action_planner_info.action_message,
|
||||
available_actions=available_actions,
|
||||
chosen_actions=chosen_action_plan_infos,
|
||||
reply_reason=planner_reasoning,
|
||||
unknown_words=unknown_words,
|
||||
enable_tool=global_config.tool.enable_tool,
|
||||
request_type="replyer",
|
||||
from_plugin=False,
|
||||
reply_time_point=action_planner_info.action_data.get("loop_start_time", time.time()),
|
||||
think_level=think_level,
|
||||
)
|
||||
|
||||
if not success or not llm_response or not llm_response.reply_set:
|
||||
if action_planner_info.action_message:
|
||||
logger.info(f"对 {action_planner_info.action_message.processed_plain_text} 的回复生成失败")
|
||||
else:
|
||||
logger.info("回复生成失败")
|
||||
return {"action_type": "reply", "success": False, "result": "回复生成失败", "loop_info": None}
|
||||
|
||||
response_set = llm_response.reply_set
|
||||
selected_expressions = llm_response.selected_expressions
|
||||
loop_info, reply_text, _ = await self._send_and_store_reply(
|
||||
response_set=response_set,
|
||||
action_message=action_planner_info.action_message, # type: ignore
|
||||
cycle_timers=cycle_timers,
|
||||
thinking_id=thinking_id,
|
||||
actions=chosen_action_plan_infos,
|
||||
selected_expressions=selected_expressions,
|
||||
quote_message=quote_message,
|
||||
)
|
||||
self.last_active_time = time.time()
|
||||
return {
|
||||
"action_type": "reply",
|
||||
"success": True,
|
||||
"result": f"你使用reply动作，对' {action_planner_info.action_message.processed_plain_text} '这句话进行了回复，回复内容为: '{reply_text}'",
|
||||
"loop_info": loop_info,
|
||||
}
|
||||
|
||||
else:
|
||||
# 执行普通动作
|
||||
with Timer("动作执行", cycle_timers):
|
||||
success, result = await self._handle_action(
|
||||
action=action_planner_info.action_type,
|
||||
action_reasoning=action_planner_info.action_reasoning or "",
|
||||
action_data=action_planner_info.action_data or {},
|
||||
cycle_timers=cycle_timers,
|
||||
thinking_id=thinking_id,
|
||||
action_message=action_planner_info.action_message,
|
||||
)
|
||||
|
||||
self.last_active_time = time.time()
|
||||
return {
|
||||
"action_type": action_planner_info.action_type,
|
||||
"success": success,
|
||||
"result": result,
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 执行动作时出错: {e}")
|
||||
logger.error(f"{self.log_prefix} 错误信息: {traceback.format_exc()}")
|
||||
return {
|
||||
"action_type": action_planner_info.action_type,
|
||||
"success": False,
|
||||
"result": "",
|
||||
"loop_info": None,
|
||||
"error": str(e),
|
||||
}
|
||||
|
||||
|
||||
class TempMethodsHFC:
|
||||
@staticmethod
|
||||
def get_talk_value(chat_id: Optional[str]) -> float:
|
||||
result = global_config.chat.talk_value or 0.0000001
|
||||
if not global_config.chat.enable_talk_value_rules or not global_config.chat.talk_value_rules:
|
||||
return result
|
||||
import time
|
||||
|
||||
local_time = time.localtime()
|
||||
now_min = local_time.tm_hour * 60 + local_time.tm_min
|
||||
# 先处理特定规则
|
||||
if chat_id:
|
||||
for rule in global_config.chat.talk_value_rules:
|
||||
if not rule.platform and not rule.item_id:
|
||||
continue # 一起留空表示全局，跳过
|
||||
is_group = rule.rule_type == "group"
|
||||
from src.chat.message_receive.chat_stream import get_chat_manager
|
||||
|
||||
stream_id = get_chat_manager().get_stream_id(rule.platform, str(rule.item_id), is_group)
|
||||
if stream_id != chat_id:
|
||||
continue
|
||||
parsed_range = TempMethodsHFC._parse_range(rule.time)
|
||||
if not parsed_range:
|
||||
continue
|
||||
start_min, end_min = parsed_range
|
||||
in_range: bool = False
|
||||
if start_min <= end_min:
|
||||
in_range = start_min <= now_min <= end_min
|
||||
else:
|
||||
in_range = now_min >= start_min or now_min <= end_min
|
||||
if in_range:
|
||||
return rule.value or 0.0
|
||||
# 再处理全局规则
|
||||
for rule in global_config.chat.talk_value_rules:
|
||||
if rule.platform or rule.item_id:
|
||||
continue # 有指定表示特定，跳过
|
||||
parsed_range = TempMethodsHFC._parse_range(rule.time)
|
||||
if not parsed_range:
|
||||
continue
|
||||
start_min, end_min = parsed_range
|
||||
in_range: bool = False
|
||||
if start_min <= end_min:
|
||||
in_range = start_min <= now_min <= end_min
|
||||
else:
|
||||
in_range = now_min >= start_min or now_min <= end_min
|
||||
if in_range:
|
||||
return rule.value or 0.0000001
|
||||
return result
|
||||
|
||||
@staticmethod
|
||||
def _parse_range(range_str: str) -> Optional[tuple[int, int]]:
|
||||
"""解析 "HH:MM-HH:MM" 到 (start_min, end_min)。"""
|
||||
try:
|
||||
start_str, end_str = [s.strip() for s in range_str.split("-")]
|
||||
sh, sm = [int(x) for x in start_str.split(":")]
|
||||
eh, em = [int(x) for x in end_str.split(":")]
|
||||
return sh * 60 + sm, eh * 60 + em
|
||||
except Exception:
|
||||
return None
|
||||
@@ -12,13 +12,14 @@ from src.common.message_repository import count_messages
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class CyclePlanInfo:
|
||||
...
|
||||
|
||||
class CyclePlanInfo: ...
|
||||
|
||||
|
||||
@dataclass
|
||||
class CycleActionInfo:
|
||||
...
|
||||
class CycleActionInfo: ...
|
||||
|
||||
|
||||
class CycleDetail:
|
||||
"""循环信息记录类"""
|
||||
|
||||
561
src/chat/message_receive/message_old.py
Normal file
561
src/chat/message_receive/message_old.py
Normal file
@@ -0,0 +1,561 @@
|
||||
import time
|
||||
import asyncio
|
||||
import urllib3
|
||||
|
||||
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.config.config import global_config
|
||||
from src.chat.utils.utils_image import get_image_manager
|
||||
from src.common.utils.utils_voice import get_voice_text
|
||||
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)
|
||||
|
||||
# VLM 处理并发限制（避免同时处理太多图片导致卡死）
|
||||
_vlm_semaphore = asyncio.Semaphore(3)
|
||||
|
||||
# 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 = ""
|
||||
|
||||
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 - 使用并行处理提升性能
|
||||
# tasks = [self._process_message_segments(seg) for seg in segment.data] # type: ignore
|
||||
# results = await asyncio.gather(*tasks, return_exceptions=True)
|
||||
# segments_text = []
|
||||
# for result in results:
|
||||
# if isinstance(result, Exception):
|
||||
# logger.error(f"处理消息段时出错: {result}")
|
||||
# continue
|
||||
# if result:
|
||||
# segments_text.append(result)
|
||||
# return " ".join(segments_text)
|
||||
# elif segment.type == "forward":
|
||||
# # 处理转发消息 - 使用并行处理
|
||||
# async def process_forward_node(node_dict):
|
||||
# message = MessageBase.from_dict(node_dict) # type: ignore
|
||||
# processed_text = await self._process_message_segments(message.message_segment)
|
||||
# if processed_text:
|
||||
# return f"{global_config.bot.nickname}: {processed_text}"
|
||||
# return None
|
||||
|
||||
# tasks = [process_forward_node(node_dict) for node_dict in segment.data]
|
||||
# results = await asyncio.gather(*tasks, return_exceptions=True)
|
||||
# segments_text = []
|
||||
# for result in results:
|
||||
# if isinstance(result, Exception):
|
||||
# logger.error(f"处理转发节点时出错: {result}")
|
||||
# continue
|
||||
# if result:
|
||||
# segments_text.append(result)
|
||||
# return "[合并消息]: " + "\n-- ".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) -> str:
|
||||
# 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_mentioned = None
|
||||
self.is_at = False
|
||||
self.reply_probability_boost = 0.0
|
||||
self.is_notify = False
|
||||
|
||||
self.is_command = False
|
||||
self.intercept_message_level = 0
|
||||
|
||||
self.priority_mode = "interest"
|
||||
self.priority_info = None
|
||||
self.interest_value: float = None # type: ignore
|
||||
|
||||
self.key_words = []
|
||||
self.key_words_lite = []
|
||||
|
||||
# 兼容适配器通过 additional_config 传入的 @ 标记
|
||||
try:
|
||||
msg_info_dict = message_dict.get("message_info", {})
|
||||
add_cfg = msg_info_dict.get("additional_config") or {}
|
||||
if isinstance(add_cfg, dict) and add_cfg.get("at_bot"):
|
||||
# 标记为被提及，提高后续回复优先级
|
||||
self.is_mentioned = True # type: ignore
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
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。
|
||||
# """
|
||||
# # print(f"self.message_segment: {self.message_segment}")
|
||||
# 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
|
||||
# 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
|
||||
# image_manager = get_image_manager()
|
||||
# # 使用 semaphore 限制 VLM 并发，避免同时处理太多图片
|
||||
# async with _vlm_semaphore:
|
||||
# _, 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
|
||||
# if isinstance(segment.data, str):
|
||||
# # 使用 semaphore 限制 VLM 并发
|
||||
# async with _vlm_semaphore:
|
||||
# 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
|
||||
# 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_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_card":
|
||||
# # 处理视频卡片消息
|
||||
# self.is_picid = False
|
||||
# self.is_emoji = False
|
||||
# self.is_voice = False
|
||||
# if isinstance(segment.data, dict):
|
||||
# file_name = segment.data.get("file", "未知视频")
|
||||
# file_size = segment.data.get("file_size", "")
|
||||
# url = segment.data.get("url", "")
|
||||
# text = f"[视频: {file_name}"
|
||||
# if file_size:
|
||||
# text += f", 大小: {file_size}字节"
|
||||
# text += "]"
|
||||
# if url:
|
||||
# text += f" 链接: {url}"
|
||||
# return text
|
||||
# return "[视频]"
|
||||
# elif segment.type == "music_card":
|
||||
# # 处理音乐卡片消息
|
||||
# self.is_picid = False
|
||||
# self.is_emoji = False
|
||||
# self.is_voice = False
|
||||
# if isinstance(segment.data, dict):
|
||||
# title = segment.data.get("title", "未知歌曲")
|
||||
# singer = segment.data.get("singer", "")
|
||||
# tag = segment.data.get("tag", "") # 音乐来源，如"网易云音乐"
|
||||
# jump_url = segment.data.get("jump_url", "")
|
||||
# music_url = segment.data.get("music_url", "")
|
||||
# text = f"[音乐: {title}"
|
||||
# if singer:
|
||||
# text += f" - {singer}"
|
||||
# if tag:
|
||||
# text += f" ({tag})"
|
||||
# text += "]"
|
||||
# if jump_url:
|
||||
# text += f" 跳转链接: {jump_url}"
|
||||
# if music_url:
|
||||
# text += f" 音乐链接: {music_url}"
|
||||
# return text
|
||||
# return "[音乐]"
|
||||
# elif segment.type == "miniapp_card":
|
||||
# # 处理小程序分享卡片（如B站视频分享）
|
||||
# self.is_picid = False
|
||||
# self.is_emoji = False
|
||||
# self.is_voice = False
|
||||
# if isinstance(segment.data, dict):
|
||||
# title = segment.data.get("title", "") # 小程序名称
|
||||
# desc = segment.data.get("desc", "") # 内容描述
|
||||
# source_url = segment.data.get("source_url", "") # 原始链接
|
||||
# url = segment.data.get("url", "") # 小程序链接
|
||||
# text = "[小程序分享"
|
||||
# if title:
|
||||
# text += f" - {title}"
|
||||
# text += "]"
|
||||
# if desc:
|
||||
# text += f" {desc}"
|
||||
# if source_url:
|
||||
# text += f" 链接: {source_url}"
|
||||
# elif url:
|
||||
# text += f" 链接: {url}"
|
||||
# return text
|
||||
# return "[小程序分享]"
|
||||
# else:
|
||||
# return ""
|
||||
# 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, segment: Seg) -> str:
|
||||
# """处理单个消息段
|
||||
|
||||
# Args:
|
||||
# segment: 要处理的消息段
|
||||
|
||||
# Returns:
|
||||
# str: 处理后的文本
|
||||
# """
|
||||
# try:
|
||||
# if segment.type == "text":
|
||||
# return segment.data # type: ignore
|
||||
# elif segment.type == "image":
|
||||
# # 如果是base64图片数据
|
||||
# if isinstance(segment.data, str):
|
||||
# return await get_image_manager().get_image_description(segment.data)
|
||||
# return "[图片，网卡了加载不出来]"
|
||||
# elif segment.type == "emoji":
|
||||
# if isinstance(segment.data, str):
|
||||
# return await get_image_manager().get_emoji_tag(segment.data)
|
||||
# return "[表情，网卡了加载不出来]"
|
||||
# elif segment.type == "voice":
|
||||
# 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 == "at":
|
||||
# return f"[@{segment.data}]"
|
||||
# elif segment.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 ""
|
||||
# else:
|
||||
# return f"[{segment.type}:{str(segment.data)}]"
|
||||
# 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]"
|
||||
|
||||
# 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: Optional[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
|
||||
@@ -7,7 +7,7 @@ from maim_message import Seg
|
||||
from src.common.message_server.api import get_global_api
|
||||
from src.common.logger import get_logger
|
||||
from src.common.database.database import get_db_session
|
||||
from src.chat.message_receive.message import MessageSending
|
||||
from src.chat.message_receive.message_old import MessageSending
|
||||
from src.chat.utils.utils import truncate_message
|
||||
from src.chat.utils.utils import calculate_typing_time
|
||||
|
||||
|
||||
@@ -12,11 +12,8 @@ from src.common.data_models.info_data_model import ActionPlannerInfo
|
||||
from src.common.data_models.llm_data_model import LLMGenerationDataModel
|
||||
from src.config.config import global_config, model_config
|
||||
from src.llm_models.utils_model import LLMRequest
|
||||
from maim_message import Seg
|
||||
|
||||
from src.common.data_models.mai_message_data_model import MaiMessage, UserInfo
|
||||
from src.chat.message_receive.message import MessageSending
|
||||
from src.chat.message_receive.chat_manager import BotChatSession
|
||||
from src.chat.message_receive.message_old import UserInfo, Seg, MessageRecv, MessageSending
|
||||
from src.chat.message_receive.chat_stream import ChatStream
|
||||
from src.chat.message_receive.uni_message_sender import UniversalMessageSender
|
||||
from src.chat.utils.timer_calculator import Timer # <--- Import Timer
|
||||
from src.chat.utils.utils import get_chat_type_and_target_info, is_bot_self
|
||||
@@ -27,16 +24,16 @@ from src.chat.utils.chat_message_builder import (
|
||||
replace_user_references,
|
||||
)
|
||||
from src.bw_learner.expression_selector import expression_selector
|
||||
from src.services.message_service import translate_pid_to_description
|
||||
from src.plugin_system.apis.message_api import translate_pid_to_description
|
||||
|
||||
# from src.memory_system.memory_activator import MemoryActivator
|
||||
from src.person_info.person_info import Person
|
||||
from src.core.types import ActionInfo, EventType
|
||||
from src.services import llm_service as llm_api
|
||||
from src.plugin_system.base.component_types import ActionInfo, EventType
|
||||
from src.plugin_system.apis import llm_api
|
||||
|
||||
from src.chat.logger.plan_reply_logger import PlanReplyLogger
|
||||
from src.memory_system.memory_retrieval import init_memory_retrieval_sys, build_memory_retrieval_prompt
|
||||
from src.bw_learner.jargon_explainer import explain_jargon_in_context, retrieve_concepts_with_jargon
|
||||
from src.bw_learner.jargon_explainer_old import explain_jargon_in_context, retrieve_concepts_with_jargon
|
||||
from src.chat.utils.common_utils import TempMethodsExpression
|
||||
|
||||
init_memory_retrieval_sys()
|
||||
@@ -48,17 +45,17 @@ logger = get_logger("replyer")
|
||||
class DefaultReplyer:
|
||||
def __init__(
|
||||
self,
|
||||
chat_stream: BotChatSession,
|
||||
chat_stream: ChatStream,
|
||||
request_type: str = "replyer",
|
||||
):
|
||||
self.express_model = LLMRequest(model_set=model_config.model_task_config.replyer, request_type=request_type)
|
||||
self.chat_stream = chat_stream
|
||||
self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.session_id)
|
||||
self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.stream_id)
|
||||
self.heart_fc_sender = UniversalMessageSender()
|
||||
|
||||
from src.chat.tool_executor import ToolExecutor
|
||||
from src.plugin_system.core.tool_use import ToolExecutor # 延迟导入ToolExecutor，不然会循环依赖
|
||||
|
||||
self.tool_executor = ToolExecutor(chat_id=self.chat_stream.session_id, enable_cache=True, cache_ttl=3)
|
||||
self.tool_executor = ToolExecutor(chat_id=self.chat_stream.stream_id, enable_cache=True, cache_ttl=3)
|
||||
|
||||
async def generate_reply_with_context(
|
||||
self,
|
||||
@@ -135,7 +132,7 @@ class DefaultReplyer:
|
||||
if log_reply:
|
||||
try:
|
||||
PlanReplyLogger.log_reply(
|
||||
chat_id=self.chat_stream.session_id,
|
||||
chat_id=self.chat_stream.stream_id,
|
||||
prompt="",
|
||||
output=None,
|
||||
processed_output=None,
|
||||
@@ -149,13 +146,11 @@ class DefaultReplyer:
|
||||
except Exception:
|
||||
logger.exception("记录reply日志失败")
|
||||
return False, llm_response
|
||||
from src.core.event_bus import event_bus
|
||||
from src.chat.event_helpers import build_event_message
|
||||
from src.plugin_system.core.events_manager import events_manager
|
||||
|
||||
if not from_plugin:
|
||||
_event_msg = build_event_message(EventType.POST_LLM, llm_prompt=prompt, stream_id=stream_id)
|
||||
continue_flag, modified_message = await event_bus.emit(
|
||||
EventType.POST_LLM, _event_msg
|
||||
continue_flag, modified_message = await events_manager.handle_mai_events(
|
||||
EventType.POST_LLM, None, prompt, None, stream_id=stream_id
|
||||
)
|
||||
if not continue_flag:
|
||||
raise UserWarning("插件于请求前中断了内容生成")
|
||||
@@ -207,7 +202,7 @@ class DefaultReplyer:
|
||||
try:
|
||||
if log_reply:
|
||||
PlanReplyLogger.log_reply(
|
||||
chat_id=self.chat_stream.session_id,
|
||||
chat_id=self.chat_stream.stream_id,
|
||||
prompt=prompt,
|
||||
output=content,
|
||||
processed_output=None,
|
||||
@@ -219,9 +214,8 @@ class DefaultReplyer:
|
||||
)
|
||||
except Exception:
|
||||
logger.exception("记录reply日志失败")
|
||||
_event_msg = build_event_message(EventType.AFTER_LLM, llm_prompt=prompt, llm_response=llm_response, stream_id=stream_id)
|
||||
continue_flag, modified_message = await event_bus.emit(
|
||||
EventType.AFTER_LLM, _event_msg
|
||||
continue_flag, modified_message = await events_manager.handle_mai_events(
|
||||
EventType.AFTER_LLM, None, prompt, llm_response, stream_id=stream_id
|
||||
)
|
||||
if not from_plugin and not continue_flag:
|
||||
raise UserWarning("插件于请求后取消了内容生成")
|
||||
@@ -265,7 +259,7 @@ class DefaultReplyer:
|
||||
if log_reply:
|
||||
try:
|
||||
PlanReplyLogger.log_reply(
|
||||
chat_id=self.chat_stream.session_id,
|
||||
chat_id=self.chat_stream.stream_id,
|
||||
prompt=prompt or "",
|
||||
output=None,
|
||||
processed_output=None,
|
||||
@@ -359,14 +353,14 @@ class DefaultReplyer:
|
||||
str: 表达习惯信息字符串
|
||||
"""
|
||||
# 检查是否允许在此聊天流中使用表达
|
||||
use_expression, _, _ = TempMethodsExpression.get_expression_config_for_chat(self.chat_stream.session_id)
|
||||
use_expression, _, _ = TempMethodsExpression.get_expression_config_for_chat(self.chat_stream.stream_id)
|
||||
if not use_expression:
|
||||
return "", []
|
||||
style_habits = []
|
||||
# 使用从处理器传来的选中表达方式
|
||||
# 使用模型预测选择表达方式
|
||||
selected_expressions, selected_ids = await expression_selector.select_suitable_expressions(
|
||||
self.chat_stream.session_id,
|
||||
self.chat_stream.stream_id,
|
||||
chat_history,
|
||||
max_num=8,
|
||||
target_message=target,
|
||||
@@ -708,11 +702,10 @@ class DefaultReplyer:
|
||||
# 判断是否为群聊
|
||||
is_group = stream_type == "group"
|
||||
|
||||
from src.common.utils.utils_session import SessionUtils
|
||||
# 使用 ChatManager 提供的接口生成 chat_id，避免在此重复实现逻辑
|
||||
from src.chat.message_receive.chat_stream import get_chat_manager
|
||||
|
||||
chat_id = SessionUtils.calculate_session_id(
|
||||
platform, group_id=str(id_str) if is_group else None, user_id=str(id_str) if not is_group else None
|
||||
)
|
||||
chat_id = get_chat_manager().get_stream_id(platform, str(id_str), is_group=is_group)
|
||||
return chat_id, prompt_content
|
||||
|
||||
except (ValueError, IndexError):
|
||||
@@ -785,7 +778,7 @@ class DefaultReplyer:
|
||||
if available_actions is None:
|
||||
available_actions = {}
|
||||
chat_stream = self.chat_stream
|
||||
chat_id = chat_stream.session_id
|
||||
chat_id = chat_stream.stream_id
|
||||
_is_group_chat = bool(chat_stream.group_info)
|
||||
platform = chat_stream.platform
|
||||
|
||||
@@ -1012,7 +1005,7 @@ class DefaultReplyer:
|
||||
reply_to: str,
|
||||
) -> str: # sourcery skip: merge-else-if-into-elif, remove-redundant-if
|
||||
chat_stream = self.chat_stream
|
||||
chat_id = chat_stream.session_id
|
||||
chat_id = chat_stream.stream_id
|
||||
sender, target = self._parse_reply_target(reply_to)
|
||||
target = replace_user_references(target, chat_stream.platform, replace_bot_name=True)
|
||||
|
||||
@@ -1112,27 +1105,29 @@ class DefaultReplyer:
|
||||
is_emoji: bool,
|
||||
thinking_start_time: float,
|
||||
display_message: str,
|
||||
anchor_message: Optional[MaiMessage] = None,
|
||||
anchor_message: Optional[MessageRecv] = None,
|
||||
) -> MessageSending:
|
||||
"""构建单个发送消息"""
|
||||
|
||||
bot_user_info = UserInfo(
|
||||
user_id=str(global_config.bot.qq_account),
|
||||
user_nickname=global_config.bot.nickname,
|
||||
platform=self.chat_stream.platform,
|
||||
)
|
||||
|
||||
# await anchor_message.process()
|
||||
sender_info = anchor_message.message_info.user_info if anchor_message else None
|
||||
|
||||
return MessageSending(
|
||||
message_id=message_id,
|
||||
session=self.chat_stream,
|
||||
message_id=message_id, # 使用片段的唯一ID
|
||||
chat_stream=self.chat_stream,
|
||||
bot_user_info=bot_user_info,
|
||||
sender_info=sender_info,
|
||||
message_segment=message_segment,
|
||||
reply=anchor_message,
|
||||
reply=anchor_message, # 回复原始锚点
|
||||
is_head=reply_to,
|
||||
is_emoji=is_emoji,
|
||||
thinking_start_time=thinking_start_time,
|
||||
thinking_start_time=thinking_start_time, # 传递原始思考开始时间
|
||||
display_message=display_message,
|
||||
)
|
||||
|
||||
|
||||
@@ -15,7 +15,7 @@ from src.llm_models.utils_model import LLMRequest
|
||||
from maim_message import Seg
|
||||
|
||||
from src.common.data_models.mai_message_data_model import MaiMessage, UserInfo
|
||||
from src.chat.message_receive.message import MessageSending
|
||||
from src.chat.message_receive.message_old import MessageSending
|
||||
from src.chat.message_receive.chat_manager import BotChatSession
|
||||
from src.chat.message_receive.uni_message_sender import UniversalMessageSender
|
||||
from src.chat.utils.timer_calculator import Timer
|
||||
@@ -35,7 +35,7 @@ from src.person_info.person_info import Person, is_person_known
|
||||
from src.core.types import ActionInfo, EventType
|
||||
from src.services import llm_service as llm_api
|
||||
from src.memory_system.memory_retrieval import init_memory_retrieval_sys, build_memory_retrieval_prompt
|
||||
from src.bw_learner.jargon_explainer import explain_jargon_in_context
|
||||
from src.bw_learner.jargon_explainer_old import explain_jargon_in_context
|
||||
|
||||
init_memory_retrieval_sys()
|
||||
|
||||
|
||||
Reference in New Issue
Block a user