PFC 新版基础模块适配
This commit is contained in:
DrSmoothl
@@ -1,23 +1,26 @@
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import asyncio
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import random
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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 typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
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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.utils.utils_config import ExpressionConfigUtils
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from src.bw_learner.expression_learner import ExpressionLearner
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from src.bw_learner.jargon_miner import JargonMiner
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from src.chat.message_receive.chat_manager import BotChatSession
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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.message import SessionMessage
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from src.common.data_models.info_data_model import ActionPlannerInfo
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from src.common.data_models.message_component_data_model import MessageSequence, TextComponent
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from src.chat.message_receive.chat_manager import chat_manager as _chat_manager
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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.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_old import CycleDetail
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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.chat.heart_flow.heartFC_utils import CycleDetail
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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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@@ -31,7 +34,7 @@ from src.services import (
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from src.services.message_service import build_readable_messages_with_id, get_messages_before_time_in_chat
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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.chat.message_receive.message import SessionMessage
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ERROR_LOOP_INFO = {
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@@ -75,12 +78,20 @@ class BrainChatting:
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"""
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# 基础属性
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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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self.chat_stream: BotChatSession = _chat_manager.get_session_by_session_id(self.stream_id) # type: ignore[assignment]
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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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self.expression_learner = expression_learner_manager.get_expression_learner(self.stream_id)
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expr_use, jargon_learn, expr_learn = ExpressionConfigUtils.get_expression_config_for_chat(self.stream_id)
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self._enable_expression_use = expr_use
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self._enable_expression_learning = expr_learn
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self._enable_jargon_learning = jargon_learn
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self._expression_learner = ExpressionLearner(self.stream_id)
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self._jargon_miner = JargonMiner(self.stream_id, session_name=self.log_prefix.strip("[]"))
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self._min_messages_for_extraction = 30
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self._min_extraction_interval = 60
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self._last_extraction_time = 0.0
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self.action_manager = ActionManager()
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self.action_planner = BrainPlanner(chat_id=self.stream_id, action_manager=self.action_manager)
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@@ -163,6 +174,25 @@ class BrainChatting:
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+ (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "")
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)
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async def _trigger_expression_learning(self, messages: List[SessionMessage]) -> None:
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if not messages:
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return
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self._expression_learner.add_messages(messages)
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if time.time() - self._last_extraction_time < self._min_extraction_interval:
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return
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if self._expression_learner.get_cache_size() < self._min_messages_for_extraction:
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return
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if not self._enable_expression_learning:
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return
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self._last_extraction_time = time.time()
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try:
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jargon_miner = self._jargon_miner if self._enable_jargon_learning else None
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await self._expression_learner.learn(jargon_miner)
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except Exception as exc:
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logger.error(f"{self.log_prefix} 表达学习失败: {exc}", exc_info=True)
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async def _loopbody(self): # sourcery skip: hoist-if-from-if
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# 获取最新消息（用于上下文，但不影响是否调用 observe）
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recent_messages_list = message_api.get_messages_by_time_in_chat(
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@@ -197,8 +227,8 @@ class BrainChatting:
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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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response_set: MessageSequence,
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action_message: SessionMessage,
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cycle_timers: Dict[str, float],
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thinking_id,
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actions,
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@@ -212,11 +242,11 @@ class BrainChatting:
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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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platform = action_message.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 = Person(platform=platform, user_id=action_message.message_info.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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@@ -245,16 +275,15 @@ class BrainChatting:
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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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recent_messages_list: Optional[List[SessionMessage]] = 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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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
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asyncio.create_task(extract_and_distribute_messages(self.stream_id))
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if recent_messages_list:
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asyncio.create_task(self._trigger_expression_learning(recent_messages_list))
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cycle_timers, thinking_id = self.start_cycle()
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logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次思考")
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@@ -294,7 +323,7 @@ class BrainChatting:
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prompt_key="brain_planner",
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)
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_event_msg = build_event_message(
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EventType.ON_PLAN, llm_prompt=prompt_info[0], stream_id=self.chat_stream.stream_id
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EventType.ON_PLAN, llm_prompt=prompt_info[0], stream_id=self.chat_stream.session_id
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)
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continue_flag, modified_message = await event_bus.emit(EventType.ON_PLAN, _event_msg)
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if not continue_flag:
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@@ -454,7 +483,7 @@ class BrainChatting:
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action_data: dict,
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cycle_timers: Dict[str, float],
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thinking_id: str,
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action_message: Optional["DatabaseMessages"] = None,
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action_message: Optional[SessionMessage] = None,
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) -> tuple[bool, str, str]:
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"""
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处理规划动作，使用动作工厂创建相应的动作处理器
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@@ -508,11 +537,11 @@ class BrainChatting:
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async def _send_response(
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self,
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reply_set: MessageSequence,
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message_data: "DatabaseMessages",
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message_data: SessionMessage,
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selected_expressions: Optional[List[int]] = None,
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) -> str:
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new_message_count = message_api.count_new_messages(
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chat_id=self.chat_stream.stream_id, start_time=self.last_read_time, end_time=time.time()
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chat_id=self.chat_stream.session_id, start_time=self.last_read_time, end_time=time.time()
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)
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need_reply = new_message_count >= random.randint(2, 4)
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@@ -529,7 +558,7 @@ class BrainChatting:
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if not first_replied:
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await send_api.text_to_stream(
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text=data,
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stream_id=self.chat_stream.stream_id,
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stream_id=self.chat_stream.session_id,
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reply_message=message_data,
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set_reply=need_reply,
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typing=False,
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@@ -539,7 +568,7 @@ class BrainChatting:
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else:
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await send_api.text_to_stream(
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text=data,
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stream_id=self.chat_stream.stream_id,
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stream_id=self.chat_stream.session_id,
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reply_message=message_data,
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set_reply=False,
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typing=True,
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@@ -585,9 +614,8 @@ class BrainChatting:
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cleaned_uw: List[str] = []
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for item in uw:
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if isinstance(item, str):
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s = item.strip()
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if s:
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cleaned_uw.append(s)
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if stripped_item := item.strip():
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cleaned_uw.append(stripped_item)
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if cleaned_uw:
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unknown_words = cleaned_uw
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@@ -1,798 +0,0 @@
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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_old 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.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(cycle_id=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
|
||||
# 3次 no_reply 时，阈值调高到 1.5（50%概率为1，50%概率为2）
|
||||
# 5次 no_reply 时，提高到 2（大于等于两条消息的阈值）
|
||||
if self.consecutive_no_reply_count >= 5:
|
||||
threshold = 2
|
||||
elif self.consecutive_no_reply_count >= 3:
|
||||
# 1.5 的含义：50%概率为1，50%概率为2
|
||||
threshold = 2 if random.random() < 0.5 else 1
|
||||
else:
|
||||
threshold = 1
|
||||
|
||||
if len(recent_messages_list) >= threshold:
|
||||
# for message in recent_messages_list:
|
||||
# print(message.processed_plain_text)
|
||||
|
||||
self.last_read_time = time.time()
|
||||
|
||||
# !此处使at或者提及必定回复
|
||||
mentioned_message = None
|
||||
for message in recent_messages_list:
|
||||
if (message.is_mentioned or message.is_at) and global_config.chat.mentioned_bot_reply:
|
||||
mentioned_message = message
|
||||
|
||||
# logger.info(f"{self.log_prefix} 当前talk_value: {TempMethods.get_talk_value(self.stream_id)}")
|
||||
|
||||
# *控制频率用
|
||||
if mentioned_message:
|
||||
await self._observe(recent_messages_list=recent_messages_list, force_reply_message=mentioned_message)
|
||||
elif (
|
||||
random.random()
|
||||
< TempMethodsHFC.get_talk_value(self.session_id)
|
||||
* frequency_control_manager.get_or_create_frequency_control(self.session_id).get_talk_frequency_adjust()
|
||||
):
|
||||
await self._observe(recent_messages_list=recent_messages_list)
|
||||
else:
|
||||
# 没有提到，继续保持沉默，等待5秒防止频繁触发
|
||||
await asyncio.sleep(10)
|
||||
return True
|
||||
else:
|
||||
await asyncio.sleep(0.2)
|
||||
return True
|
||||
return True
|
||||
|
||||
async def _send_and_store_reply(
|
||||
self,
|
||||
response_set: "ReplySetModel",
|
||||
action_message: "DatabaseMessages",
|
||||
cycle_timers: Dict[str, float],
|
||||
thinking_id,
|
||||
actions,
|
||||
selected_expressions: Optional[List[int]] = None,
|
||||
quote_message: Optional[bool] = None,
|
||||
) -> Tuple[Dict[str, Any], str, Dict[str, float]]:
|
||||
with Timer("回复发送", cycle_timers):
|
||||
reply_text = await self._send_response(
|
||||
reply_set=response_set,
|
||||
message_data=action_message,
|
||||
selected_expressions=selected_expressions,
|
||||
quote_message=quote_message,
|
||||
)
|
||||
|
||||
# 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
|
||||
platform = action_message.chat_info.platform
|
||||
if platform is None:
|
||||
platform = getattr(self.chat_stream, "platform", "unknown")
|
||||
|
||||
person = Person(platform=platform, user_id=action_message.user_info.user_id)
|
||||
person_name = person.person_name
|
||||
action_prompt_display = f"你对{person_name}进行了回复：{reply_text}"
|
||||
|
||||
await database_api.store_action_info(
|
||||
chat_stream=self.chat_stream,
|
||||
action_build_into_prompt=False,
|
||||
action_prompt_display=action_prompt_display,
|
||||
action_done=True,
|
||||
thinking_id=thinking_id,
|
||||
action_data={"reply_text": reply_text},
|
||||
action_name="reply",
|
||||
)
|
||||
|
||||
# 构建循环信息
|
||||
loop_info: Dict[str, Any] = {
|
||||
"loop_plan_info": {
|
||||
"action_result": actions,
|
||||
},
|
||||
"loop_action_info": {
|
||||
"action_taken": True,
|
||||
"reply_text": reply_text,
|
||||
"command": "",
|
||||
"taken_time": time.time(),
|
||||
},
|
||||
}
|
||||
|
||||
return loop_info, reply_text, cycle_timers
|
||||
|
||||
async def _observe(
|
||||
self, # interest_value: float = 0.0,
|
||||
recent_messages_list: Optional[List["DatabaseMessages"]] = None,
|
||||
force_reply_message: Optional["DatabaseMessages"] = None,
|
||||
) -> bool: # sourcery skip: merge-else-if-into-elif, remove-redundant-if
|
||||
if recent_messages_list is None:
|
||||
recent_messages_list = []
|
||||
_reply_text = "" # 初始化reply_text变量，避免UnboundLocalError
|
||||
|
||||
start_time = time.time()
|
||||
async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()):
|
||||
# 通过 MessageRecorder 统一提取消息并分发给 expression_learner 和 jargon_miner
|
||||
# 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
|
||||
@@ -1,8 +1,8 @@
|
||||
from typing import Dict, Optional, Tuple
|
||||
|
||||
from src.chat.message_receive.chat_manager import BotChatSession
|
||||
from src.chat.message_receive.message import SessionMessage
|
||||
from src.common.logger import get_logger
|
||||
from src.common.data_models.database_data_model import DatabaseMessages
|
||||
from src.core.component_registry import component_registry, ActionExecutor
|
||||
from src.core.types import ActionInfo
|
||||
|
||||
@@ -52,7 +52,7 @@ class ActionManager:
|
||||
chat_stream: BotChatSession,
|
||||
log_prefix: str,
|
||||
shutting_down: bool = False,
|
||||
action_message: Optional[DatabaseMessages] = None,
|
||||
action_message: Optional[SessionMessage] = None,
|
||||
) -> Optional[ActionHandle]:
|
||||
"""
|
||||
创建动作执行句柄
|
||||
|
||||
@@ -24,13 +24,13 @@ from src.services.message_service import (
|
||||
from src.chat.utils.utils import get_chat_type_and_target_info, is_bot_self
|
||||
from src.chat.planner_actions.action_manager import ActionManager
|
||||
from src.chat.message_receive.chat_manager import chat_manager as _chat_manager
|
||||
from src.chat.message_receive.message import SessionMessage
|
||||
from src.core.types import ActionActivationType, ActionInfo, ComponentType
|
||||
from src.core.component_registry import component_registry
|
||||
from src.person_info.person_info import Person
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from src.common.data_models.info_data_model import TargetPersonInfo
|
||||
from src.common.data_models.database_data_model import DatabaseMessages
|
||||
|
||||
logger = get_logger("planner")
|
||||
|
||||
@@ -56,8 +56,8 @@ class ActionPlanner:
|
||||
self.unknown_words_cache_limit = 10
|
||||
|
||||
def find_message_by_id(
|
||||
self, message_id: str, message_id_list: List[Tuple[str, "DatabaseMessages"]]
|
||||
) -> Optional["DatabaseMessages"]:
|
||||
self, message_id: str, message_id_list: List[Tuple[str, "SessionMessage"]]
|
||||
) -> Optional["SessionMessage"]:
|
||||
# sourcery skip: use-next
|
||||
"""
|
||||
根据message_id从message_id_list中查找对应的原始消息
|
||||
@@ -75,7 +75,7 @@ class ActionPlanner:
|
||||
return None
|
||||
|
||||
def _replace_message_ids_with_text(
|
||||
self, text: Optional[str], message_id_list: List[Tuple[str, "DatabaseMessages"]]
|
||||
self, text: Optional[str], message_id_list: List[Tuple[str, "SessionMessage"]]
|
||||
) -> Optional[str]:
|
||||
"""将文本中的 m+数字 消息ID替换为原消息内容，并添加双引号"""
|
||||
if not text:
|
||||
@@ -122,13 +122,7 @@ class ActionPlanner:
|
||||
msg_text = re.sub(pic_pattern, replace_pic_id, msg_text)
|
||||
|
||||
# 替换用户引用格式：回复<aaa:bbb> 和 @<aaa:bbb>
|
||||
platform = (
|
||||
getattr(message, "user_info", None)
|
||||
and message.user_info.platform
|
||||
or getattr(message, "chat_info", None)
|
||||
and message.chat_info.platform
|
||||
or "qq"
|
||||
)
|
||||
platform = message.platform or "qq"
|
||||
msg_text = replace_user_references(msg_text, platform, replace_bot_name=True)
|
||||
|
||||
# 替换单独的 <用户名:用户ID> 格式（replace_user_references 已处理回复<和@<格式）
|
||||
@@ -160,7 +154,7 @@ class ActionPlanner:
|
||||
def _parse_single_action(
|
||||
self,
|
||||
action_json: dict,
|
||||
message_id_list: List[Tuple[str, "DatabaseMessages"]],
|
||||
message_id_list: List[Tuple[str, "SessionMessage"]],
|
||||
current_available_actions: List[Tuple[str, ActionInfo]],
|
||||
extracted_reasoning: str = "",
|
||||
) -> List[ActionPlannerInfo]:
|
||||
@@ -245,10 +239,10 @@ class ActionPlanner:
|
||||
|
||||
return action_planner_infos
|
||||
|
||||
def _is_message_from_self(self, message: "DatabaseMessages") -> bool:
|
||||
def _is_message_from_self(self, message: "SessionMessage") -> bool:
|
||||
"""判断消息是否由机器人自身发送（支持多平台，包括 WebUI）"""
|
||||
try:
|
||||
return is_bot_self(message.user_info.platform or "", str(message.user_info.user_id))
|
||||
return is_bot_self(message.platform or "", str(message.message_info.user_info.user_id))
|
||||
except AttributeError:
|
||||
logger.warning(f"{self.log_prefix}检测消息发送者失败，缺少必要字段")
|
||||
return False
|
||||
@@ -380,7 +374,7 @@ class ActionPlanner:
|
||||
self,
|
||||
available_actions: Dict[str, ActionInfo],
|
||||
loop_start_time: float = 0.0,
|
||||
force_reply_message: Optional["DatabaseMessages"] = None,
|
||||
force_reply_message: Optional["SessionMessage"] = None,
|
||||
) -> List[ActionPlannerInfo]:
|
||||
# sourcery skip: use-named-expression
|
||||
"""
|
||||
@@ -395,7 +389,7 @@ class ActionPlanner:
|
||||
limit=int(global_config.chat.max_context_size * 0.6),
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
message_id_list: list[Tuple[str, "DatabaseMessages"]] = []
|
||||
message_id_list: list[Tuple[str, "SessionMessage"]] = []
|
||||
chat_content_block, message_id_list = build_readable_messages_with_id(
|
||||
messages=message_list_before_now,
|
||||
timestamp_mode="normal_no_YMD",
|
||||
@@ -552,10 +546,10 @@ class ActionPlanner:
|
||||
is_group_chat: bool,
|
||||
chat_target_info: Optional["TargetPersonInfo"],
|
||||
current_available_actions: Dict[str, ActionInfo],
|
||||
message_id_list: List[Tuple[str, "DatabaseMessages"]],
|
||||
message_id_list: List[Tuple[str, "SessionMessage"]],
|
||||
chat_content_block: str = "",
|
||||
interest: str = "",
|
||||
) -> tuple[str, List[Tuple[str, "DatabaseMessages"]]]:
|
||||
) -> tuple[str, List[Tuple[str, "SessionMessage"]]]:
|
||||
"""构建 Planner LLM 的提示词 (获取模板并填充数据)"""
|
||||
try:
|
||||
actions_before_now_block = self.get_plan_log_str()
|
||||
@@ -710,7 +704,7 @@ class ActionPlanner:
|
||||
async def _execute_main_planner(
|
||||
self,
|
||||
prompt: str,
|
||||
message_id_list: List[Tuple[str, "DatabaseMessages"]],
|
||||
message_id_list: List[Tuple[str, "SessionMessage"]],
|
||||
filtered_actions: Dict[str, ActionInfo],
|
||||
available_actions: Dict[str, ActionInfo],
|
||||
loop_start_time: float,
|
||||
|
||||
Reference in New Issue
Block a user