mirror of https://github.com/Mai-with-u/MaiBot.git
755 lines
33 KiB
Python
755 lines
33 KiB
Python
import asyncio
|
||
import time
|
||
import traceback
|
||
import random
|
||
from typing import List, Optional, Dict, Any, Tuple, TYPE_CHECKING
|
||
from rich.traceback import install
|
||
|
||
from src.config.config import global_config
|
||
from src.common.logger import get_logger
|
||
from src.common.data_models.info_data_model import ActionPlannerInfo
|
||
from src.common.data_models.message_data_model import ReplyContentType
|
||
from src.chat.message_receive.chat_stream import ChatStream, get_chat_manager
|
||
from src.chat.utils.prompt_builder import global_prompt_manager
|
||
from src.chat.utils.timer_calculator import Timer
|
||
from src.chat.brain_chat.brain_planner import BrainPlanner
|
||
from src.chat.planner_actions.action_modifier import ActionModifier
|
||
from src.chat.planner_actions.action_manager import ActionManager
|
||
from src.chat.heart_flow.hfc_utils import CycleDetail
|
||
from src.bw_learner.expression_learner import expression_learner_manager
|
||
from src.bw_learner.message_recorder import extract_and_distribute_messages
|
||
from src.person_info.person_info import Person
|
||
from src.plugin_system.base.component_types import EventType, ActionInfo
|
||
from src.plugin_system.core import events_manager
|
||
from src.plugin_system.apis import generator_api, send_api, message_api, database_api
|
||
from src.chat.utils.chat_message_builder import (
|
||
build_readable_messages_with_id,
|
||
get_raw_msg_before_timestamp_with_chat,
|
||
)
|
||
|
||
if TYPE_CHECKING:
|
||
from src.common.data_models.database_data_model import DatabaseMessages
|
||
from src.common.data_models.message_data_model import ReplySetModel
|
||
|
||
|
||
ERROR_LOOP_INFO = {
|
||
"loop_plan_info": {
|
||
"action_result": {
|
||
"action_type": "error",
|
||
"action_data": {},
|
||
"reasoning": "循环处理失败",
|
||
},
|
||
},
|
||
"loop_action_info": {
|
||
"action_taken": False,
|
||
"reply_text": "",
|
||
"command": "",
|
||
"taken_time": time.time(),
|
||
},
|
||
}
|
||
|
||
|
||
install(extra_lines=3)
|
||
|
||
# 注释：原来的动作修改超时常量已移除，因为改为顺序执行
|
||
|
||
logger = get_logger("bc") # Logger Name Changed
|
||
|
||
|
||
class BrainChatting:
|
||
"""
|
||
管理一个连续的私聊Brain Chat循环
|
||
用于在特定聊天流中生成回复。
|
||
"""
|
||
|
||
def __init__(self, chat_id: str):
|
||
"""
|
||
BrainChatting 初始化函数
|
||
|
||
参数:
|
||
chat_id: 聊天流唯一标识符(如stream_id)
|
||
on_stop_focus_chat: 当收到stop_focus_chat命令时调用的回调函数
|
||
performance_version: 性能记录版本号，用于区分不同启动版本
|
||
"""
|
||
# 基础属性
|
||
self.stream_id: str = chat_id # 聊天流ID
|
||
self.chat_stream: ChatStream = get_chat_manager().get_stream(self.stream_id) # type: ignore
|
||
if not self.chat_stream:
|
||
raise ValueError(f"无法找到聊天流: {self.stream_id}")
|
||
self.log_prefix = f"[{get_chat_manager().get_stream_name(self.stream_id) or self.stream_id}]"
|
||
|
||
self.expression_learner = expression_learner_manager.get_expression_learner(self.stream_id)
|
||
|
||
self.action_manager = ActionManager()
|
||
self.action_planner = BrainPlanner(chat_id=self.stream_id, action_manager=self.action_manager)
|
||
self.action_modifier = ActionModifier(action_manager=self.action_manager, chat_id=self.stream_id)
|
||
|
||
# 循环控制内部状态
|
||
self.running: bool = False
|
||
self._loop_task: Optional[asyncio.Task] = None # 主循环任务
|
||
|
||
# 添加循环信息管理相关的属性
|
||
self.history_loop: List[CycleDetail] = []
|
||
self._cycle_counter = 0
|
||
self._current_cycle_detail: CycleDetail = None # type: ignore
|
||
|
||
self.last_read_time = time.time() - 2
|
||
|
||
self.more_plan = False
|
||
|
||
# 最近一次是否成功进行了 reply，用于选择 BrainPlanner 的 Prompt
|
||
self._last_successful_reply: bool = False
|
||
|
||
async def start(self):
|
||
"""检查是否需要启动主循环，如果未激活则启动。"""
|
||
|
||
# 如果循环已经激活，直接返回
|
||
if self.running:
|
||
logger.debug(f"{self.log_prefix} BrainChatting 已激活，无需重复启动")
|
||
return
|
||
|
||
try:
|
||
# 标记为活动状态，防止重复启动
|
||
self.running = True
|
||
|
||
self._loop_task = asyncio.create_task(self._main_chat_loop())
|
||
self._loop_task.add_done_callback(self._handle_loop_completion)
|
||
logger.info(f"{self.log_prefix} BrainChatting 启动完成")
|
||
|
||
except Exception as e:
|
||
# 启动失败时重置状态
|
||
self.running = False
|
||
self._loop_task = None
|
||
logger.error(f"{self.log_prefix} BrainChatting 启动失败: {e}")
|
||
raise
|
||
|
||
def _handle_loop_completion(self, task: asyncio.Task):
|
||
"""当 _hfc_loop 任务完成时执行的回调。"""
|
||
try:
|
||
if exception := task.exception():
|
||
logger.error(f"{self.log_prefix} BrainChatting: 脱离了聊天(异常): {exception}")
|
||
logger.error(traceback.format_exc()) # Log full traceback for exceptions
|
||
else:
|
||
logger.info(f"{self.log_prefix} BrainChatting: 脱离了聊天 (外部停止)")
|
||
except asyncio.CancelledError:
|
||
logger.info(f"{self.log_prefix} BrainChatting: 结束了聊天")
|
||
|
||
def start_cycle(self) -> Tuple[Dict[str, float], str]:
|
||
self._cycle_counter += 1
|
||
self._current_cycle_detail = CycleDetail(self._cycle_counter)
|
||
self._current_cycle_detail.thinking_id = f"tid{str(round(time.time(), 2))}"
|
||
cycle_timers = {}
|
||
return cycle_timers, self._current_cycle_detail.thinking_id
|
||
|
||
def end_cycle(self, loop_info, cycle_timers):
|
||
self._current_cycle_detail.set_loop_info(loop_info)
|
||
self.history_loop.append(self._current_cycle_detail)
|
||
self._current_cycle_detail.timers = cycle_timers
|
||
self._current_cycle_detail.end_time = time.time()
|
||
|
||
def print_cycle_info(self, cycle_timers):
|
||
# 记录循环信息和计时器结果
|
||
timer_strings = []
|
||
for name, elapsed in cycle_timers.items():
|
||
formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒"
|
||
timer_strings.append(f"{name}: {formatted_time}")
|
||
|
||
logger.info(
|
||
f"{self.log_prefix} 第{self._current_cycle_detail.cycle_id}次思考,"
|
||
f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒" # type: ignore
|
||
+ (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "")
|
||
)
|
||
|
||
async def _loopbody(self): # sourcery skip: hoist-if-from-if
|
||
# 获取最新消息（用于上下文，但不影响是否调用 observe）
|
||
recent_messages_list = message_api.get_messages_by_time_in_chat(
|
||
chat_id=self.stream_id,
|
||
start_time=self.last_read_time,
|
||
end_time=time.time(),
|
||
limit=20,
|
||
limit_mode="latest",
|
||
filter_mai=True,
|
||
filter_command=False,
|
||
filter_intercept_message_level=1,
|
||
)
|
||
|
||
# 如果有新消息，更新 last_read_time
|
||
if len(recent_messages_list) >= 1:
|
||
self.last_read_time = time.time()
|
||
|
||
# 总是执行一次思考迭代（不管有没有新消息）
|
||
# wait 动作会在其内部等待，不需要在这里处理
|
||
should_continue = await self._observe(recent_messages_list=recent_messages_list)
|
||
|
||
if not should_continue:
|
||
# 选择了 complete_talk，返回 False 表示需要等待新消息
|
||
return False
|
||
|
||
# 继续下一次迭代（除非选择了 complete_talk）
|
||
# 短暂等待后再继续，避免过于频繁的循环
|
||
await asyncio.sleep(0.1)
|
||
|
||
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,
|
||
) -> 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,
|
||
)
|
||
|
||
# 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,
|
||
) -> 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
|
||
|
||
# -------------------------------------------------------------------------
|
||
# ReflectTracker Check
|
||
# 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
|
||
# -------------------------------------------------------------------------
|
||
from src.bw_learner.reflect_tracker import reflect_tracker_manager
|
||
|
||
tracker = reflect_tracker_manager.get_tracker(self.stream_id)
|
||
if tracker:
|
||
resolved = await tracker.trigger_tracker()
|
||
if resolved:
|
||
reflect_tracker_manager.remove_tracker(self.stream_id)
|
||
logger.info(f"{self.log_prefix} ReflectTracker resolved and removed.")
|
||
|
||
# -------------------------------------------------------------------------
|
||
# Expression Reflection Check
|
||
# 检查是否需要提问表达反思
|
||
# -------------------------------------------------------------------------
|
||
from src.bw_learner.expression_reflector import expression_reflector_manager
|
||
|
||
reflector = expression_reflector_manager.get_or_create_reflector(self.stream_id)
|
||
asyncio.create_task(reflector.check_and_ask())
|
||
|
||
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.stream_id))
|
||
|
||
cycle_timers, thinking_id = self.start_cycle()
|
||
logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次思考")
|
||
|
||
# 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}")
|
||
|
||
# 获取必要信息
|
||
is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info()
|
||
|
||
# 一次思考迭代：Think - Act - Observe
|
||
# 获取聊天上下文
|
||
message_list_before_now = get_raw_msg_before_timestamp_with_chat(
|
||
chat_id=self.stream_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(
|
||
chat_target_info=chat_target_info,
|
||
current_available_actions=available_actions,
|
||
chat_content_block=chat_content_block,
|
||
message_id_list=message_id_list,
|
||
prompt_key="brain_planner_prompt_react",
|
||
)
|
||
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,
|
||
)
|
||
|
||
# 检查是否有 complete_talk 动作（会停止后续迭代）
|
||
has_complete_talk = any(
|
||
action.action_type == "complete_talk" for action in action_to_use_info
|
||
)
|
||
|
||
# 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 = ""
|
||
|
||
for result in results:
|
||
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["reply_text"]
|
||
elif result["action_type"] == "reply":
|
||
if result["success"]:
|
||
reply_loop_info = result["loop_info"]
|
||
reply_text_from_reply = result["reply_text"]
|
||
else:
|
||
logger.warning(f"{self.log_prefix} 回复动作执行失败")
|
||
|
||
# 更新观察时间标记
|
||
self.action_planner.last_obs_time_mark = time.time()
|
||
|
||
# 如果选择了 complete_talk，标记为完成，不再继续迭代
|
||
if has_complete_talk:
|
||
logger.info(f"{self.log_prefix} 检测到 complete_talk 动作，本次思考完成")
|
||
|
||
# 构建循环信息
|
||
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
|
||
|
||
# 如果选择了 complete_talk，返回 False 以停止 _loopbody 的循环
|
||
# 否则返回 True，让 _loopbody 继续下一次迭代
|
||
should_continue = not has_complete_talk
|
||
|
||
self.end_cycle(loop_info, cycle_timers)
|
||
self.print_cycle_info(cycle_timers)
|
||
|
||
# 如果选择了 complete_talk，返回 False 停止循环
|
||
# 否则返回 True，继续下一次思考迭代
|
||
return should_continue
|
||
|
||
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()
|
||
if not success:
|
||
# 选择了 complete，等待新消息
|
||
logger.info(f"{self.log_prefix} 选择了 complete，等待新消息...")
|
||
await self._wait_for_new_message()
|
||
# 有新消息后继续循环
|
||
continue
|
||
await asyncio.sleep(0.1)
|
||
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 _wait_for_new_message(self):
|
||
"""等待新消息到达"""
|
||
last_check_time = self.last_read_time
|
||
check_interval = 1.0 # 每秒检查一次
|
||
|
||
while self.running:
|
||
# 检查是否有新消息
|
||
recent_messages_list = message_api.get_messages_by_time_in_chat(
|
||
chat_id=self.stream_id,
|
||
start_time=last_check_time,
|
||
end_time=time.time(),
|
||
limit=20,
|
||
limit_mode="latest",
|
||
filter_mai=True,
|
||
filter_command=False,
|
||
filter_intercept_message_level=1,
|
||
)
|
||
|
||
# 如果有新消息，更新 last_read_time 并返回
|
||
if len(recent_messages_list) >= 1:
|
||
self.last_read_time = time.time()
|
||
logger.info(f"{self.log_prefix} 检测到新消息，恢复循环")
|
||
return
|
||
|
||
# 等待一段时间后再次检查
|
||
await asyncio.sleep(check_interval)
|
||
|
||
async def _handle_action(
|
||
self,
|
||
action: str,
|
||
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
|
||
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
|
||
|
||
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,
|
||
action_reasoning=reasoning,
|
||
cycle_timers=cycle_timers,
|
||
thinking_id=thinking_id,
|
||
chat_stream=self.chat_stream,
|
||
log_prefix=self.log_prefix,
|
||
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, "", ""
|
||
|
||
if not action_handler:
|
||
logger.warning(f"{self.log_prefix} 未能创建动作处理器: {action}")
|
||
return False, "", ""
|
||
|
||
# 处理动作并获取结果（固定记录一次动作信息）
|
||
# BaseAction 定义了异步方法 execute() 作为统一执行入口
|
||
# 这里调用 execute() 以兼容所有 Action 实现
|
||
result = await action_handler.execute()
|
||
success, action_text = result
|
||
command = ""
|
||
|
||
return success, action_text, command
|
||
|
||
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,
|
||
) -> str:
|
||
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, 4)
|
||
|
||
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")
|
||
|
||
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):
|
||
if action_planner_info.action_type == "complete_talk":
|
||
# 直接处理complete_talk逻辑，不再通过动作系统
|
||
reason = action_planner_info.reasoning or "选择完成对话"
|
||
logger.info(f"{self.log_prefix} 选择完成对话，原因: {reason}")
|
||
|
||
# 存储complete_talk信息到数据库
|
||
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={"reason": reason},
|
||
action_name="complete_talk",
|
||
)
|
||
return {"action_type": "complete_talk", "success": True, "reply_text": "", "command": ""}
|
||
|
||
elif action_planner_info.action_type == "reply":
|
||
try:
|
||
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=action_planner_info.reasoning or "",
|
||
enable_tool=global_config.tool.enable_tool,
|
||
request_type="replyer",
|
||
from_plugin=False,
|
||
)
|
||
|
||
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,
|
||
"reply_text": "",
|
||
"loop_info": None,
|
||
}
|
||
|
||
except asyncio.CancelledError:
|
||
logger.debug(f"{self.log_prefix} 并行执行：回复生成任务已被取消")
|
||
return {"action_type": "reply", "success": False, "reply_text": "", "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,
|
||
)
|
||
# 标记这次循环已经成功进行了回复
|
||
self._last_successful_reply = True
|
||
return {
|
||
"action_type": "reply",
|
||
"success": True,
|
||
"reply_text": reply_text,
|
||
"loop_info": loop_info,
|
||
}
|
||
|
||
# 其他动作
|
||
else:
|
||
# 内建 wait / listening：不通过插件系统，直接在这里处理
|
||
if action_planner_info.action_type in ["wait", "listening"]:
|
||
reason = action_planner_info.reasoning or ""
|
||
action_data = action_planner_info.action_data or {}
|
||
|
||
if action_planner_info.action_type == "wait":
|
||
# 获取等待时间（必填）
|
||
wait_seconds = action_data.get("wait_seconds")
|
||
if wait_seconds is None:
|
||
logger.warning(f"{self.log_prefix} wait 动作缺少 wait_seconds 参数，使用默认值 5 秒")
|
||
wait_seconds = 5
|
||
else:
|
||
try:
|
||
wait_seconds = float(wait_seconds)
|
||
if wait_seconds < 0:
|
||
logger.warning(f"{self.log_prefix} wait_seconds 不能为负数，使用默认值 5 秒")
|
||
wait_seconds = 5
|
||
except (ValueError, TypeError):
|
||
logger.warning(f"{self.log_prefix} wait_seconds 参数格式错误，使用默认值 5 秒")
|
||
wait_seconds = 5
|
||
|
||
logger.info(f"{self.log_prefix} 执行 wait 动作，等待 {wait_seconds} 秒")
|
||
|
||
# 记录动作信息
|
||
await database_api.store_action_info(
|
||
chat_stream=self.chat_stream,
|
||
action_build_into_prompt=False,
|
||
action_prompt_display=reason or f"等待 {wait_seconds} 秒",
|
||
action_done=True,
|
||
thinking_id=thinking_id,
|
||
action_data={"reason": reason, "wait_seconds": wait_seconds},
|
||
action_name="wait",
|
||
)
|
||
|
||
# 等待指定时间
|
||
await asyncio.sleep(wait_seconds)
|
||
|
||
logger.info(f"{self.log_prefix} wait 动作完成，继续下一次思考")
|
||
|
||
# 这些动作本身不产生文本回复
|
||
self._last_successful_reply = False
|
||
return {
|
||
"action_type": "wait",
|
||
"success": True,
|
||
"reply_text": "",
|
||
"command": "",
|
||
}
|
||
|
||
# listening 已合并到 wait，如果遇到则转换为 wait（向后兼容）
|
||
elif action_planner_info.action_type == "listening":
|
||
logger.debug(f"{self.log_prefix} 检测到 listening 动作，已合并到 wait，自动转换")
|
||
# 使用默认等待时间
|
||
wait_seconds = 3
|
||
|
||
logger.info(f"{self.log_prefix} 执行 listening（转换为 wait）动作，等待 {wait_seconds} 秒")
|
||
|
||
# 记录动作信息
|
||
await database_api.store_action_info(
|
||
chat_stream=self.chat_stream,
|
||
action_build_into_prompt=False,
|
||
action_prompt_display=reason or f"倾听并等待 {wait_seconds} 秒",
|
||
action_done=True,
|
||
thinking_id=thinking_id,
|
||
action_data={"reason": reason, "wait_seconds": wait_seconds},
|
||
action_name="listening",
|
||
)
|
||
|
||
# 等待指定时间
|
||
await asyncio.sleep(wait_seconds)
|
||
|
||
logger.info(f"{self.log_prefix} listening 动作完成，继续下一次思考")
|
||
|
||
# 这些动作本身不产生文本回复
|
||
self._last_successful_reply = False
|
||
return {
|
||
"action_type": "listening",
|
||
"success": True,
|
||
"reply_text": "",
|
||
"command": "",
|
||
}
|
||
|
||
# 其余动作：走原有插件 Action 体系
|
||
with Timer("动作执行", cycle_timers):
|
||
success, reply_text, command = await self._handle_action(
|
||
action_planner_info.action_type,
|
||
action_planner_info.reasoning or "",
|
||
action_planner_info.action_data or {},
|
||
cycle_timers,
|
||
thinking_id,
|
||
action_planner_info.action_message,
|
||
)
|
||
# 非 reply 类动作执行成功时，清空最近成功回复标记，让下一轮回到 initial Prompt
|
||
if success and action_planner_info.action_type != "reply":
|
||
self._last_successful_reply = False
|
||
|
||
return {
|
||
"action_type": action_planner_info.action_type,
|
||
"success": success,
|
||
"reply_text": reply_text,
|
||
"command": command,
|
||
}
|
||
|
||
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,
|
||
"reply_text": "",
|
||
"loop_info": None,
|
||
"error": str(e),
|
||
}
|