feat:为s4u添加优先级信息

This commit is contained in:
SengokuCola
2025-07-13 00:05:12 +08:00
parent 16c2a8b68e
commit 7757931da5
3 changed files with 27 additions and 935 deletions

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@@ -1,923 +0,0 @@
import asyncio
import time
from typing import Optional
from src.config.config import global_config
from src.common.logger import get_logger
from src.chat.message_receive.chat_stream import ChatStream, get_chat_manager
from ..message_receive.message import MessageThinking
from src.chat.message_receive.normal_message_sender import message_manager
from src.chat.normal_chat.willing.willing_manager import get_willing_manager
from src.chat.planner_actions.action_manager import ActionManager
from src.person_info.relationship_builder_manager import relationship_builder_manager
from ..focus_chat.priority_manager import PriorityManager
import traceback
from src.chat.planner_actions.planner import ActionPlanner
from src.chat.planner_actions.action_modifier import ActionModifier
from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_chat_inclusive
from src.chat.utils.utils import get_chat_type_and_target_info
willing_manager = get_willing_manager()
logger = get_logger("normal_chat")
LOOP_INTERVAL = 0.3
class NormalChat:
"""
普通聊天处理类,负责处理非核心对话的聊天逻辑。
每个聊天私聊或群聊都会有一个独立的NormalChat实例。
"""
def __init__(
self,
chat_stream: ChatStream,
on_switch_to_focus_callback=None,
get_cooldown_progress_callback=None,
):
"""
初始化NormalChat实例。
Args:
chat_stream (ChatStream): 聊天流对象,包含与特定聊天相关的所有信息。
"""
self.chat_stream = chat_stream
self.stream_id = chat_stream.stream_id
self.last_read_time = time.time()-1
self.stream_name = get_chat_manager().get_stream_name(self.stream_id) or self.stream_id
self.relationship_builder = relationship_builder_manager.get_or_create_builder(self.stream_id)
self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.stream_id)
self.willing_amplifier = 1
self.start_time = time.time()
# self.mood_manager = mood_manager
self.start_time = time.time()
self.running = False
self._initialized = False # Track initialization status
# Planner相关初始化
self.action_manager = ActionManager()
self.planner = ActionPlanner(self.stream_id, self.action_manager, mode="normal")
self.action_modifier = ActionModifier(self.action_manager, self.stream_id)
self.enable_planner = global_config.normal_chat.enable_planner # 从配置中读取是否启用planner
# 记录最近的回复内容,每项包含: {time, user_message, response, is_mentioned, is_reference_reply}
self.recent_replies = []
self.max_replies_history = 20 # 最多保存最近20条回复记录
# 添加回调函数用于在满足条件时通知切换到focus_chat模式
self.on_switch_to_focus_callback = on_switch_to_focus_callback
# 添加回调函数,用于获取冷却进度
self.get_cooldown_progress_callback = get_cooldown_progress_callback
self._disabled = False # 增加停用标志
self.timeout_count = 0
self.action_type: Optional[str] = None # 当前动作类型
self.is_parallel_action: bool = False # 是否是可并行动作
# 任务管理
self._chat_task: Optional[asyncio.Task] = None
self._priority_chat_task: Optional[asyncio.Task] = None # for priority mode consumer
self._disabled = False # 停用标志
# 新增:回复模式和优先级管理器
self.reply_mode = self.chat_stream.context.get_priority_mode()
if self.reply_mode == "priority":
self.priority_manager = PriorityManager(
normal_queue_max_size=5,
)
else:
self.priority_manager = None
async def disable(self):
"""停用 NormalChat 实例,停止所有后台任务"""
self._disabled = True
if self._chat_task and not self._chat_task.done():
self._chat_task.cancel()
if self.reply_mode == "priority" and self._priority_chat_task and not self._priority_chat_task.done():
self._priority_chat_task.cancel()
logger.info(f"[{self.stream_name}] NormalChat 已停用。")
# async def _interest_mode_loopbody(self):
# try:
# await asyncio.sleep(LOOP_INTERVAL)
# if self._disabled:
# return False
# now = time.time()
# new_messages_data = get_raw_msg_by_timestamp_with_chat_inclusive(
# chat_id=self.stream_id, timestamp_start=self.last_read_time, timestamp_end=now, limit_mode="earliest"
# )
# if new_messages_data:
# self.last_read_time = now
# for msg_data in new_messages_data:
# try:
# self.adjust_reply_frequency()
# await self.normal_response(
# message_data=msg_data,
# is_mentioned=msg_data.get("is_mentioned", False),
# interested_rate=msg_data.get("interest_rate", 0.0) * self.willing_amplifier,
# )
# return True
# except Exception as e:
# logger.error(f"[{self.stream_name}] 处理消息时出错: {e} {traceback.format_exc()}")
# except asyncio.CancelledError:
# logger.info(f"[{self.stream_name}] 兴趣模式轮询任务被取消")
# return False
# except Exception:
# logger.error(f"[{self.stream_name}] 兴趣模式轮询循环出现错误: {traceback.format_exc()}", exc_info=True)
# await asyncio.sleep(10)
async def _priority_mode_loopbody(self):
try:
await asyncio.sleep(LOOP_INTERVAL)
if self._disabled:
return False
now = time.time()
new_messages_data = get_raw_msg_by_timestamp_with_chat_inclusive(
chat_id=self.stream_id, timestamp_start=self.last_read_time, timestamp_end=now, limit_mode="earliest"
)
if new_messages_data:
self.last_read_time = now
for msg_data in new_messages_data:
try:
if self.priority_manager:
self.priority_manager.add_message(msg_data, msg_data.get("interest_rate", 0.0))
return True
except Exception as e:
logger.error(f"[{self.stream_name}] 添加消息到优先级队列时出错: {e} {traceback.format_exc()}")
except asyncio.CancelledError:
logger.info(f"[{self.stream_name}] 优先级消息生产者任务被取消")
return False
except Exception:
logger.error(f"[{self.stream_name}] 优先级消息生产者循环出现错误: {traceback.format_exc()}", exc_info=True)
await asyncio.sleep(10)
# async def _interest_message_polling_loop(self):
# """
# [Interest Mode] 通过轮询数据库获取新消息并直接处理。
# """
# logger.info(f"[{self.stream_name}] 兴趣模式消息轮询任务开始")
# try:
# while not self._disabled:
# success = await self._interest_mode_loopbody()
# if not success:
# break
# except asyncio.CancelledError:
# logger.info(f"[{self.stream_name}] 兴趣模式消息轮询任务被优雅地取消了")
async def _priority_chat_loop(self):
"""
使用优先级队列的消息处理循环。
"""
while not self._disabled:
try:
if self.priority_manager and not self.priority_manager.is_empty():
# 获取最高优先级的消息,现在是字典
message_data = self.priority_manager.get_highest_priority_message()
if message_data:
logger.info(
f"[{self.stream_name}] 从队列中取出消息进行处理: User {message_data.get('user_id')}, Time: {time.strftime('%H:%M:%S', time.localtime(message_data.get('time')))}"
)
do_reply = await self.reply_one_message(message_data)
response_set = do_reply if do_reply else []
factor = 0.5
cnt = sum([len(r) for r in response_set])
await asyncio.sleep(max(1, factor * cnt - 3)) # 等待tts
# 等待一段时间再检查队列
await asyncio.sleep(1)
except asyncio.CancelledError:
logger.info(f"[{self.stream_name}] 优先级聊天循环被取消。")
break
except Exception:
logger.error(f"[{self.stream_name}] 优先级聊天循环出现错误: {traceback.format_exc()}", exc_info=True)
# 出现错误时,等待更长时间避免频繁报错
await asyncio.sleep(10)
# 改为实例方法
# async def _create_thinking_message(self, message_data: dict, timestamp: Optional[float] = None) -> str:
# """创建思考消息"""
# bot_user_info = UserInfo(
# user_id=global_config.bot.qq_account,
# user_nickname=global_config.bot.nickname,
# platform=message_data.get("chat_info_platform"),
# )
# thinking_time_point = round(time.time(), 2)
# thinking_id = "tid" + str(thinking_time_point)
# thinking_message = MessageThinking(
# message_id=thinking_id,
# chat_stream=self.chat_stream,
# bot_user_info=bot_user_info,
# reply=None,
# thinking_start_time=thinking_time_point,
# timestamp=timestamp if timestamp is not None else None,
# )
# await message_manager.add_message(thinking_message)
# return thinking_id
# 改为实例方法
# async def _add_messages_to_manager(
# self, message_data: dict, response_set: List[str], thinking_id
# ) -> Optional[MessageSending]:
# """发送回复消息"""
# container = await message_manager.get_container(self.stream_id) # 使用 self.stream_id
# thinking_message = None
# for msg in container.messages[:]:
# if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
# thinking_message = msg
# container.messages.remove(msg)
# break
# if not thinking_message:
# logger.warning(f"[{self.stream_name}] 未找到对应的思考消息 {thinking_id},可能已超时被移除")
# return None
# thinking_start_time = thinking_message.thinking_start_time
# message_set = MessageSet(self.chat_stream, thinking_id) # 使用 self.chat_stream
# sender_info = UserInfo(
# user_id=message_data.get("user_id"),
# user_nickname=message_data.get("user_nickname"),
# platform=message_data.get("chat_info_platform"),
# )
# reply = message_from_db_dict(message_data)
# mark_head = False
# first_bot_msg = None
# for msg in response_set:
# if global_config.debug.debug_show_chat_mode:
# msg += "ⁿ"
# message_segment = Seg(type="text", data=msg)
# bot_message = MessageSending(
# message_id=thinking_id,
# chat_stream=self.chat_stream, # 使用 self.chat_stream
# bot_user_info=UserInfo(
# user_id=global_config.bot.qq_account,
# user_nickname=global_config.bot.nickname,
# platform=message_data.get("chat_info_platform"),
# ),
# sender_info=sender_info,
# message_segment=message_segment,
# reply=reply,
# is_head=not mark_head,
# is_emoji=False,
# thinking_start_time=thinking_start_time,
# apply_set_reply_logic=True,
# )
# if not mark_head:
# mark_head = True
# first_bot_msg = bot_message
# message_set.add_message(bot_message)
# await message_manager.add_message(message_set)
# return first_bot_msg
# 改为实例方法, 移除 chat 参数
# async def normal_response(self, message_data: dict, is_mentioned: bool, interested_rate: float) -> None:
# """
# 处理接收到的消息。
# 在"兴趣"模式下,判断是否回复并生成内容。
# """
# if self._disabled:
# return
# # 新增在auto模式下检查是否需要直接切换到focus模式
# if global_config.chat.chat_mode == "auto":
# if await self._check_should_switch_to_focus():
# logger.info(f"[{self.stream_name}] 检测到切换到focus聊天模式的条件尝试执行切换")
# if self.on_switch_to_focus_callback:
# switched_successfully = await self.on_switch_to_focus_callback()
# if switched_successfully:
# logger.info(f"[{self.stream_name}] 成功切换到focus模式中止NormalChat处理")
# return
# else:
# logger.info(f"[{self.stream_name}] 切换到focus模式失败可能在冷却中继续NormalChat处理")
# else:
# logger.warning(f"[{self.stream_name}] 没有设置切换到focus聊天模式的回调函数无法执行切换")
# # --- 以下为 "兴趣" 模式逻辑 (从 _process_message 合并而来) ---
# timing_results = {}
# reply_probability = (
# 1.0 if is_mentioned and global_config.normal_chat.mentioned_bot_inevitable_reply else 0.0
# ) # 如果被提及且开启了提及必回复则基础概率为1否则需要意愿判断
# # 意愿管理器设置当前message信息
# willing_manager.setup(message_data, self.chat_stream)
# # 获取回复概率
# # is_willing = False
# # 仅在未被提及或基础概率不为1时查询意愿概率
# if reply_probability < 1: # 简化逻辑,如果未提及 (reply_probability 为 0),则获取意愿概率
# # is_willing = True
# reply_probability = await willing_manager.get_reply_probability(message_data.get("message_id"))
# additional_config = message_data.get("additional_config", {})
# if additional_config and "maimcore_reply_probability_gain" in additional_config:
# reply_probability += additional_config["maimcore_reply_probability_gain"]
# reply_probability = min(max(reply_probability, 0), 1) # 确保概率在 0-1 之间
# # 处理表情包
# if message_data.get("is_emoji") or message_data.get("is_picid"):
# reply_probability = 0
# # 应用疲劳期回复频率调整
# fatigue_multiplier = self._get_fatigue_reply_multiplier()
# original_probability = reply_probability
# reply_probability *= fatigue_multiplier
# # 如果应用了疲劳调整,记录日志
# if fatigue_multiplier < 1.0:
# logger.info(
# f"[{self.stream_name}] 疲劳期回复频率调整: {original_probability * 100:.1f}% -> {reply_probability * 100:.1f}% (系数: {fatigue_multiplier:.2f})"
# )
# # 打印消息信息
# mes_name = self.chat_stream.group_info.group_name if self.chat_stream.group_info else "私聊"
# if reply_probability > 0.1:
# logger.info(
# f"[{mes_name}]"
# f"{message_data.get('user_nickname')}:"
# f"{message_data.get('processed_plain_text')}[兴趣:{interested_rate:.2f}][回复概率:{reply_probability * 100:.1f}%]"
# )
# do_reply = False
# response_set = None # 初始化 response_set
# if random() < reply_probability:
# with Timer("获取回复", timing_results):
# await willing_manager.before_generate_reply_handle(message_data.get("message_id"))
# do_reply = await self.reply_one_message(message_data)
# response_set = do_reply if do_reply else None
# # 输出性能计时结果
# if do_reply and response_set: # 确保 response_set 不是 None
# timing_str = " | ".join([f"{step}: {duration:.2f}秒" for step, duration in timing_results.items()])
# trigger_msg = message_data.get("processed_plain_text")
# response_msg = " ".join([item[1] for item in response_set if item[0] == "text"])
# logger.info(
# f"[{self.stream_name}]回复消息: {trigger_msg[:30]}... | 回复内容: {response_msg[:30]}... | 计时: {timing_str}"
# )
# await willing_manager.after_generate_reply_handle(message_data.get("message_id"))
# elif not do_reply:
# # 不回复处理
# await willing_manager.not_reply_handle(message_data.get("message_id"))
# # 意愿管理器注销当前message信息 (无论是否回复,只要处理过就删除)
# willing_manager.delete(message_data.get("message_id"))
# async def _generate_normal_response(
# self, message_data: dict, available_actions: Optional[list]
# ) -> Optional[list]:
# """生成普通回复"""
# try:
# person_info_manager = get_person_info_manager()
# person_id = person_info_manager.get_person_id(
# message_data.get("chat_info_platform"), message_data.get("user_id")
# )
# person_name = await person_info_manager.get_value(person_id, "person_name")
# reply_to_str = f"{person_name}:{message_data.get('processed_plain_text')}"
# success, reply_set = await generator_api.generate_reply(
# chat_stream=self.chat_stream,
# reply_to=reply_to_str,
# available_actions=available_actions,
# enable_tool=global_config.tool.enable_in_normal_chat,
# request_type="normal.replyer",
# )
# if not success or not reply_set:
# logger.info(f"对 {message_data.get('processed_plain_text')} 的回复生成失败")
# return None
# return reply_set
# except Exception as e:
# logger.error(f"[{self.stream_name}] 回复生成出现错误:{str(e)} {traceback.format_exc()}")
# return None
# async def _plan_and_execute_actions(self, message_data: dict, thinking_id: str) -> Optional[dict]:
# """规划和执行额外动作"""
# no_action = {
# "action_result": {
# "action_type": "no_action",
# "action_data": {},
# "reasoning": "规划器初始化默认",
# "is_parallel": True,
# },
# "chat_context": "",
# "action_prompt": "",
# }
# if not self.enable_planner:
# logger.debug(f"[{self.stream_name}] Planner未启用跳过动作规划")
# return no_action
# try:
# # 检查是否应该跳过规划
# if self.action_modifier.should_skip_planning():
# logger.debug(f"[{self.stream_name}] 没有可用动作,跳过规划")
# self.action_type = "no_action"
# return no_action
# # 执行规划
# plan_result = await self.planner.plan()
# action_type = plan_result["action_result"]["action_type"]
# action_data = plan_result["action_result"]["action_data"]
# reasoning = plan_result["action_result"]["reasoning"]
# is_parallel = plan_result["action_result"].get("is_parallel", False)
# if action_type == "no_action":
# logger.info(f"[{self.stream_name}] {global_config.bot.nickname} 决定进行回复")
# elif is_parallel:
# logger.info(
# f"[{self.stream_name}] {global_config.bot.nickname} 决定进行回复, 同时执行{action_type}动作"
# )
# else:
# logger.info(f"[{self.stream_name}] {global_config.bot.nickname} 决定执行{action_type}动作")
# self.action_type = action_type # 更新实例属性
# self.is_parallel_action = is_parallel # 新增:保存并行执行标志
# # 如果规划器决定不执行任何动作
# if action_type == "no_action":
# logger.debug(f"[{self.stream_name}] Planner决定不执行任何额外动作")
# return no_action
# # 执行额外的动作(不影响回复生成)
# action_result = await self._handle_action(action_type, action_data, message_data, thinking_id)
# if action_result is not None:
# logger.info(f"[{self.stream_name}] 额外动作 {action_type} 执行完成")
# else:
# logger.warning(f"[{self.stream_name}] 额外动作 {action_type} 执行失败")
# return {
# "action_type": action_type,
# "action_data": action_data,
# "reasoning": reasoning,
# "is_parallel": is_parallel,
# }
# except Exception as e:
# logger.error(f"[{self.stream_name}] Planner执行失败: {e}")
# return no_action
# async def reply_one_message(self, message_data: dict) -> None:
# # 回复前处理
# await self.relationship_builder.build_relation()
# thinking_id = await self._create_thinking_message(message_data)
# # 如果启用planner预先修改可用actions避免在并行任务中重复调用
# available_actions = None
# if self.enable_planner:
# try:
# await self.action_modifier.modify_actions(mode="normal", message_content=message_data.get("processed_plain_text"))
# available_actions = self.action_manager.get_using_actions_for_mode("normal")
# except Exception as e:
# logger.warning(f"[{self.stream_name}] 获取available_actions失败: {e}")
# available_actions = None
# # 并行执行回复生成和动作规划
# self.action_type = None # 初始化动作类型
# self.is_parallel_action = False # 初始化并行动作标志
# gen_task = asyncio.create_task(self._generate_normal_response(message_data, available_actions))
# plan_task = asyncio.create_task(self._plan_and_execute_actions(message_data, thinking_id))
# try:
# gather_timeout = global_config.chat.thinking_timeout
# results = await asyncio.wait_for(
# asyncio.gather(gen_task, plan_task, return_exceptions=True),
# timeout=gather_timeout,
# )
# response_set, plan_result = results
# except asyncio.TimeoutError:
# gen_timed_out = not gen_task.done()
# plan_timed_out = not plan_task.done()
# timeout_details = []
# if gen_timed_out:
# timeout_details.append("回复生成(gen)")
# if plan_timed_out:
# timeout_details.append("动作规划(plan)")
# timeout_source = " 和 ".join(timeout_details)
# logger.warning(
# f"[{self.stream_name}] {timeout_source} 任务超时 ({global_config.chat.thinking_timeout}秒),正在取消相关任务..."
# )
# # print(f"111{self.timeout_count}")
# self.timeout_count += 1
# if self.timeout_count > 5:
# logger.warning(
# f"[{self.stream_name}] 连续回复超时次数过多,{global_config.chat.thinking_timeout}秒 内大模型没有返回有效内容请检查你的api是否速度过慢或配置错误。建议不要使用推理模型推理模型生成速度过慢。或者尝试拉高thinking_timeout参数这可能导致回复时间过长。"
# )
# # 取消未完成的任务
# if not gen_task.done():
# gen_task.cancel()
# if not plan_task.done():
# plan_task.cancel()
# # 清理思考消息
# await self._cleanup_thinking_message_by_id(thinking_id)
# response_set = None
# plan_result = None
# # 处理生成回复的结果
# if isinstance(response_set, Exception):
# logger.error(f"[{self.stream_name}] 回复生成异常: {response_set}")
# response_set = None
# # 处理规划结果(可选,不影响回复)
# if isinstance(plan_result, Exception):
# logger.error(f"[{self.stream_name}] 动作规划异常: {plan_result}")
# elif plan_result:
# logger.debug(f"[{self.stream_name}] 额外动作处理完成: {self.action_type}")
# if response_set:
# content = " ".join([item[1] for item in response_set if item[0] == "text"])
# if not response_set or (
# self.enable_planner and self.action_type not in ["no_action"] and not self.is_parallel_action
# ):
# if not response_set:
# logger.warning(f"[{self.stream_name}] 模型未生成回复内容")
# elif self.enable_planner and self.action_type not in ["no_action"] and not self.is_parallel_action:
# logger.info(
# f"[{self.stream_name}] {global_config.bot.nickname} 原本想要回复:{content},但选择执行{self.action_type},不发表回复"
# )
# # 如果模型未生成回复,移除思考消息
# await self._cleanup_thinking_message_by_id(thinking_id)
# return False
# logger.info(f"[{self.stream_name}] {global_config.bot.nickname} 决定的回复内容: {content}")
# if self._disabled:
# logger.info(f"[{self.stream_name}] 已停用,忽略 normal_response。")
# return False
# # 提取回复文本
# reply_texts = [item[1] for item in response_set if item[0] == "text"]
# if not reply_texts:
# logger.info(f"[{self.stream_name}] 回复内容中没有文本,不发送消息")
# await self._cleanup_thinking_message_by_id(thinking_id)
# return False
# # 发送回复 (不再需要传入 chat)
# first_bot_msg = await add_messages_to_manager(message_data, reply_texts, thinking_id)
# # 检查 first_bot_msg 是否为 None (例如思考消息已被移除的情况)
# if first_bot_msg:
# # 消息段已在接收消息时更新,这里不需要额外处理
# # 记录回复信息到最近回复列表中
# reply_info = {
# "time": time.time(),
# "user_message": message_data.get("processed_plain_text"),
# "user_info": {
# "user_id": message_data.get("user_id"),
# "user_nickname": message_data.get("user_nickname"),
# },
# "response": response_set,
# "is_reference_reply": message_data.get("reply") is not None, # 判断是否为引用回复
# }
# self.recent_replies.append(reply_info)
# # 保持最近回复历史在限定数量内
# if len(self.recent_replies) > self.max_replies_history:
# self.recent_replies = self.recent_replies[-self.max_replies_history :]
# return response_set if response_set else False
# 改为实例方法, 移除 chat 参数
async def start_chat(self):
"""启动聊天任务。"""
# 重置停用标志
self._disabled = False
# 检查是否已有运行中的任务
if self._chat_task and not self._chat_task.done():
logger.info(f"[{self.stream_name}] 聊天轮询任务已在运行中。")
return
# 清理可能存在的已完成任务引用
if self._chat_task and self._chat_task.done():
self._chat_task = None
if self._priority_chat_task and self._priority_chat_task.done():
self._priority_chat_task = None
try:
logger.info(f"[{self.stream_name}] 创建新的聊天轮询任务,模式: {self.reply_mode}")
if self.reply_mode == "priority":
# Start producer loop
producer_task = asyncio.create_task(self._priority_message_producer_loop())
self._chat_task = producer_task
self._chat_task.add_done_callback(lambda t: self._handle_task_completion(t, "priority_producer"))
# Start consumer loop
consumer_task = asyncio.create_task(self._priority_chat_loop())
self._priority_chat_task = consumer_task
self._priority_chat_task.add_done_callback(lambda t: self._handle_task_completion(t, "priority_consumer"))
else: # Interest mode
polling_task = asyncio.create_task(self._interest_message_polling_loop())
self._chat_task = polling_task
self._chat_task.add_done_callback(lambda t: self._handle_task_completion(t, "interest_polling"))
self.running = True
logger.debug(f"[{self.stream_name}] 聊天任务启动完成")
except Exception as e:
logger.error(f"[{self.stream_name}] 启动聊天任务失败: {e}")
self._chat_task = None
self._priority_chat_task = None
raise
# def _handle_task_completion(self, task: asyncio.Task, task_name: str = "unknown"):
# """任务完成回调处理"""
# try:
# logger.debug(f"[{self.stream_name}] 任务 '{task_name}' 完成回调被调用")
# if task is self._chat_task:
# self._chat_task = None
# elif task is self._priority_chat_task:
# self._priority_chat_task = None
# else:
# logger.debug(f"[{self.stream_name}] 回调的任务 '{task_name}' 不是当前管理的任务")
# return
# logger.debug(f"[{self.stream_name}] 任务 '{task_name}' 引用已清理")
# if task.cancelled():
# logger.debug(f"[{self.stream_name}] 任务 '{task_name}' 已取消")
# elif task.done():
# exc = task.exception()
# if exc:
# logger.error(f"[{self.stream_name}] 任务 '{task_name}' 异常: {type(exc).__name__}: {exc}", exc_info=exc)
# else:
# logger.debug(f"[{self.stream_name}] 任务 '{task_name}' 正常完成")
# except Exception as e:
# logger.error(f"[{self.stream_name}] 任务完成回调处理出错: {e}")
# self._chat_task = None
# self._priority_chat_task = None
# 改为实例方法, 移除 stream_id 参数
async def stop_chat(self):
"""停止当前实例的兴趣监控任务。"""
logger.debug(f"[{self.stream_name}] 开始停止聊天任务")
self._disabled = True
if self._chat_task and not self._chat_task.done():
self._chat_task.cancel()
if self._priority_chat_task and not self._priority_chat_task.done():
self._priority_chat_task.cancel()
self._chat_task = None
self._priority_chat_task = None
# def adjust_reply_frequency(self):
# """
# 根据预设规则动态调整回复意愿willing_amplifier
# - 评估周期10分钟
# - 目标频率:由 global_config.chat.talk_frequency 定义(例如 1条/分钟)
# - 调整逻辑:
# - 0条回复 -> 5.0x 意愿
# - 达到目标回复数 -> 1.0x 意愿(基准)
# - 达到目标2倍回复数 -> 0.2x 意愿
# - 中间值线性变化
# - 增益抑制如果最近5分钟回复过快则不增加意愿。
# """
# # --- 1. 定义参数 ---
# evaluation_minutes = 10.0
# target_replies_per_min = global_config.chat.get_current_talk_frequency(
# self.stream_id
# ) # 目标频率e.g. 1条/分钟
# target_replies_in_window = target_replies_per_min * evaluation_minutes # 10分钟内的目标回复数
# if target_replies_in_window <= 0:
# logger.debug(f"[{self.stream_name}] 目标回复频率为0或负数不调整意愿放大器。")
# return
# # --- 2. 获取近期统计数据 ---
# stats_10_min = get_recent_message_stats(minutes=evaluation_minutes, chat_id=self.stream_id)
# bot_reply_count_10_min = stats_10_min["bot_reply_count"]
# # --- 3. 计算新的意愿放大器 (willing_amplifier) ---
# # 基于回复数在 [0, target*2] 区间内进行分段线性映射
# if bot_reply_count_10_min <= target_replies_in_window:
# # 在 [0, 目标数] 区间,意愿从 5.0 线性下降到 1.0
# new_amplifier = 5.0 + (bot_reply_count_10_min - 0) * (1.0 - 5.0) / (target_replies_in_window - 0)
# elif bot_reply_count_10_min <= target_replies_in_window * 2:
# # 在 [目标数, 目标数*2] 区间,意愿从 1.0 线性下降到 0.2
# over_target_cap = target_replies_in_window * 2
# new_amplifier = 1.0 + (bot_reply_count_10_min - target_replies_in_window) * (0.2 - 1.0) / (
# over_target_cap - target_replies_in_window
# )
# else:
# # 超过目标数2倍直接设为最小值
# new_amplifier = 0.2
# # --- 4. 检查是否需要抑制增益 ---
# # "如果邻近5分钟内回复数量 > 频率/2就不再进行增益"
# suppress_gain = False
# if new_amplifier > self.willing_amplifier: # 仅在计算结果为增益时检查
# suppression_minutes = 5.0
# # 5分钟内目标回复数的一半
# suppression_threshold = (target_replies_per_min / 2) * suppression_minutes # e.g., (1/2)*5 = 2.5
# stats_5_min = get_recent_message_stats(minutes=suppression_minutes, chat_id=self.stream_id)
# bot_reply_count_5_min = stats_5_min["bot_reply_count"]
# if bot_reply_count_5_min > suppression_threshold:
# suppress_gain = True
# # --- 5. 更新意愿放大器 ---
# if suppress_gain:
# logger.debug(
# f"[{self.stream_name}] 回复增益被抑制。最近5分钟内回复数 ({bot_reply_count_5_min}) "
# f"> 阈值 ({suppression_threshold:.1f})。意愿放大器保持在 {self.willing_amplifier:.2f}"
# )
# # 不做任何改动
# else:
# # 限制最终值在 [0.2, 5.0] 范围内
# self.willing_amplifier = max(0.2, min(5.0, new_amplifier))
# logger.debug(
# f"[{self.stream_name}] 调整回复意愿。10分钟内回复: {bot_reply_count_10_min} (目标: {target_replies_in_window:.0f}) -> "
# f"意愿放大器更新为: {self.willing_amplifier:.2f}"
# )
# async def _execute_action(
# self, action_type: str, action_data: dict, message_data: dict, thinking_id: str
# ) -> Optional[bool]:
# """执行具体的动作,只返回执行成功与否"""
# try:
# # 创建动作处理器实例
# action_handler = self.action_manager.create_action(
# action_name=action_type,
# action_data=action_data,
# reasoning=action_data.get("reasoning", ""),
# cycle_timers={}, # normal_chat使用空的cycle_timers
# thinking_id=thinking_id,
# chat_stream=self.chat_stream,
# log_prefix=self.stream_name,
# shutting_down=self._disabled,
# )
# if action_handler:
# # 执行动作
# result = await action_handler.handle_action()
# success = False
# if result and isinstance(result, tuple) and len(result) >= 2:
# # handle_action返回 (success: bool, message: str)
# success = result[0]
# elif result:
# # 如果返回了其他结果,假设成功
# success = True
# return success
# except Exception as e:
# logger.error(f"[{self.stream_name}] 执行动作 {action_type} 失败: {e}")
# return False
# def get_action_manager(self) -> ActionManager:
# """获取动作管理器实例"""
# return self.action_manager
# def _get_fatigue_reply_multiplier(self) -> float:
# """获取疲劳期回复频率调整系数
# Returns:
# float: 回复频率调整系数范围0.5-1.0
# """
# if not self.get_cooldown_progress_callback:
# return 1.0 # 没有冷却进度回调,返回正常系数
# try:
# cooldown_progress = self.get_cooldown_progress_callback()
# if cooldown_progress >= 1.0:
# return 1.0 # 冷却完成,正常回复频率
# # 疲劳期间从0.5逐渐恢复到1.0
# # progress=0时系数为0.5progress=1时系数为1.0
# multiplier = 0.2 + (0.8 * cooldown_progress)
# return multiplier
# except Exception as e:
# logger.warning(f"[{self.stream_name}] 获取疲劳调整系数时出错: {e}")
# return 1.0 # 出错时返回正常系数
async def _check_should_switch_to_focus(self) -> bool:
"""
检查是否满足切换到focus模式的条件
Returns:
bool: 是否应该切换到focus模式
"""
# 检查思考消息堆积情况
container = await message_manager.get_container(self.stream_id)
if container:
thinking_count = sum(1 for msg in container.messages if isinstance(msg, MessageThinking))
if thinking_count >= 4 * global_config.chat.auto_focus_threshold: # 如果堆积超过阈值条思考消息
logger.debug(f"[{self.stream_name}] 检测到思考消息堆积({thinking_count}条)切换到focus模式")
return True
if not self.recent_replies:
return False
current_time = time.time()
time_threshold = 120 / global_config.chat.auto_focus_threshold
reply_threshold = 6 * global_config.chat.auto_focus_threshold
one_minute_ago = current_time - time_threshold
# 统计指定时间内的回复数量
recent_reply_count = sum(1 for reply in self.recent_replies if reply["time"] > one_minute_ago)
should_switch = recent_reply_count > reply_threshold
if should_switch:
logger.debug(
f"[{self.stream_name}] 检测到{time_threshold:.0f}秒内回复数量({recent_reply_count})大于{reply_threshold}满足切换到focus模式条件"
)
return should_switch
# async def _cleanup_thinking_message_by_id(self, thinking_id: str):
# """根据ID清理思考消息"""
# try:
# container = await message_manager.get_container(self.stream_id)
# if container:
# for msg in container.messages[:]:
# if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
# container.messages.remove(msg)
# logger.info(f"[{self.stream_name}] 已清理思考消息 {thinking_id}")
# break
# except Exception as e:
# logger.error(f"[{self.stream_name}] 清理思考消息 {thinking_id} 时出错: {e}")
# def get_recent_message_stats(minutes: int = 30, chat_id: str = None) -> dict:
# """
# Args:
# minutes (int): 检索的分钟数默认30分钟
# chat_id (str, optional): 指定的chat_id仅统计该chat下的消息。为None时统计全部。
# Returns:
# dict: {"bot_reply_count": int, "total_message_count": int}
# """
# now = time.time()
# start_time = now - minutes * 60
# bot_id = global_config.bot.qq_account
# filter_base = {"time": {"$gte": start_time}}
# if chat_id is not None:
# filter_base["chat_id"] = chat_id
# # 总消息数
# total_message_count = count_messages(filter_base)
# # bot自身回复数
# bot_filter = filter_base.copy()
# bot_filter["user_id"] = bot_id
# bot_reply_count = count_messages(bot_filter)
# return {"bot_reply_count": bot_reply_count, "total_message_count": total_message_count}

View File

@@ -10,6 +10,7 @@ from src.chat.message_receive.message import MessageSending, MessageRecv
from src.config.config import global_config
from src.common.message.api import get_global_api
from src.chat.message_receive.storage import MessageStorage
import json
logger = get_logger("S4U_chat")
@@ -168,27 +169,40 @@ class S4UChat:
self.normal_queue_max_size = 50 # 普通队列最大容量
logger.info(f"[{self.stream_name}] S4UChat with two-queue system initialized.")
def _is_vip(self, message: MessageRecv) -> bool:
def _get_priority_info(self, message: MessageRecv) -> dict:
"""安全地从消息中提取和解析 priority_info"""
priority_info_raw = message.raw.get("priority_info")
priority_info = {}
if isinstance(priority_info_raw, str):
try:
priority_info = json.loads(priority_info_raw)
except json.JSONDecodeError:
logger.warning(f"Failed to parse priority_info JSON: {priority_info_raw}")
elif isinstance(priority_info_raw, dict):
priority_info = priority_info_raw
return priority_info
def _is_vip(self, priority_info: dict) -> bool:
"""检查消息是否来自VIP用户。"""
# 您需要修改此处或在配置文件中定义VIP用户
vip_user_ids = ["1026294844"]
vip_user_ids = [""]
return message.message_info.user_info.user_id in vip_user_ids
return priority_info.get("message_type") == "vip"
def _get_interest_score(self, user_id: str) -> float:
"""获取用户的兴趣分默认为1.0"""
return self.interest_dict.get(user_id, 1.0)
def _calculate_base_priority_score(self, message: MessageRecv) -> float:
def _calculate_base_priority_score(self, message: MessageRecv, priority_info: dict) -> float:
"""
为消息计算基础优先级分数。分数越高,优先级越高。
"""
score = 0.0
# 如果消息 @ 了机器人,则增加一个很大的分数
if f"@{global_config.bot.nickname}" in message.processed_plain_text or any(
f"@{alias}" in message.processed_plain_text for alias in global_config.bot.alias_names
):
score += self.at_bot_priority_bonus
# if f"@{global_config.bot.nickname}" in message.processed_plain_text or any(
# f"@{alias}" in message.processed_plain_text for alias in global_config.bot.alias_names
# ):
# score += self.at_bot_priority_bonus
# 加上消息自带的优先级
score += priority_info.get("message_priority", 0.0)
# 加上用户的固有兴趣分
score += self._get_interest_score(message.message_info.user_info.user_id)
@@ -196,8 +210,9 @@ class S4UChat:
async def add_message(self, message: MessageRecv) -> None:
"""根据VIP状态和中断逻辑将消息放入相应队列。"""
is_vip = self._is_vip(message)
new_priority_score = self._calculate_base_priority_score(message)
priority_info = self._get_priority_info(message)
is_vip = self._is_vip(priority_info)
new_priority_score = self._calculate_base_priority_score(message, priority_info)
should_interrupt = False
if self._current_generation_task and not self._current_generation_task.done():