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feat；更改了talk_value的含义，增加私聊模式

pull/1239/head
SengokuCola 2025-09-16 14:24:44 +08:00
parent 4f5dc810ef
commit f89c5521dc
8 changed files with 752 additions and 128 deletions
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2
changelogs/changelog.md
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@ -16,7 +16,7 @@
- 添加多种发送类型
- 优化识图token限制
- 为空回复添加重试机制
- 加入brainchat模式，为私聊支持做准备
## [0.10.2] - 2025-8-31

630
src/chat/heart_flow/brain_chat.py 100644
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@ -0,0 +1,630 @@
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.planner_actions.planner import ActionPlanner
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.chat.heart_flow.hfc_utils import send_typing, stop_typing
from src.chat.express.expression_learner import expression_learner_manager
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.mais4u.mai_think import mai_thinking_manager
from src.mais4u.s4u_config import s4u_config
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 = ActionPlanner(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.talk_threshold = global_config.chat.talk_value
self.no_reply_until_call = 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
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=True,
)
if len(recent_messages_list) >= 1:
# !处理no_reply_until_call逻辑
if self.no_reply_until_call:
for message in recent_messages_list:
if (
message.is_mentioned
or message.is_at
or len(recent_messages_list) >= 8
or time.time() - self.last_read_time > 600
):
self.no_reply_until_call = False
break
# 没有提到，继续保持沉默
if self.no_reply_until_call:
# logger.info(f"{self.log_prefix} 没有提到，继续保持沉默")
await asyncio.sleep(1)
return True
self.last_read_time = time.time()
await self._observe(
recent_messages_list=recent_messages_list
)
else:
# Normal模式：消息数量不足，等待
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,
) -> 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
if s4u_config.enable_s4u:
await send_typing()
async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()):
await self.expression_learner.trigger_learning_for_chat()
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}")
# 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.stream_id,
timestamp=time.time(),
limit=int(global_config.chat.max_context_size * 0.6),
)
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,
interest=global_config.personality.interest,
)
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,
)
has_reply = False
for action in action_to_use_info:
if action.action_type == "reply":
has_reply = True
break
if not has_reply:
action_to_use_info.append(
ActionPlannerInfo(
action_type="reply",
reasoning="进行回复",
action_data={},
action_message=recent_messages_list[0],
available_actions=available_actions,
)
)
# 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 = ""
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")
# 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)
"""S4U内容，暂时保留"""
if s4u_config.enable_s4u:
await stop_typing()
await mai_thinking_manager.get_mai_think(self.stream_id).do_think_after_response(reply_text)
"""S4U内容，暂时保留"""
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,
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,
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
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 == "no_reply":
# 直接处理no_action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}")
# 存储no_action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="no_action",
)
return {"action_type": "no_action", "success": True, "reply_text": "", "command": ""}
elif action_planner_info.action_type == "wait_time":
action_planner_info.action_data = action_planner_info.action_data or {}
logger.info(f"{self.log_prefix} 等待{action_planner_info.action_data['time']}秒后回复")
await asyncio.sleep(action_planner_info.action_data["time"])
return {"action_type": "wait_time", "success": True, "reply_text": "", "command": ""}
elif action_planner_info.action_type == "no_reply_until_call":
logger.info(f"{self.log_prefix} 保持沉默，直到有人直接叫的名字")
self.no_reply_until_call = True
return {"action_type": "no_reply_until_call", "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,
)
return {
"action_type": "reply",
"success": True,
"reply_text": reply_text,
"loop_info": loop_info,
}
# 其他动作
else:
# 执行普通动作
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,
)
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),
}

213
src/chat/heart_flow/heartFC_chat.py
View File

@ -50,16 +50,6 @@ ERROR_LOOP_INFO = {
},
}
# ?什么时候发言：
# 1.聊天频率较低：与过去该时段发言频率进行比较
# 2.感兴趣的话题：暂时使用Emb计算
# 3.感兴趣的人：认识次数
# 4.直接提及
# 什么时候不发言：
# 1.敏感话题：判断较难
# 2.发言频率太高：近时判断，例如发言频率> 1/人数 *2
# 3.明确被拒绝：planner判断
install(extra_lines=3)
@ -106,7 +96,7 @@ class HeartFChatting:
self._cycle_counter = 0
self._current_cycle_detail: CycleDetail = None # type: ignore
self.last_read_time = time.time() - 10
self.last_read_time = time.time() - 2
self.talk_threshold = global_config.chat.talk_value
@ -172,16 +162,6 @@ class HeartFChatting:
+ (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "")
)
def get_talk_threshold(self):
talk_value = global_config.chat.talk_value
# 处理talk_value：取整数部分和小数部分
base_value = int(talk_value)
probability = talk_value - base_value
# 根据概率决定是否+1
think_len = base_value + 1 if random.random() < probability else base_value
self.talk_threshold = think_len
logger.info(f"{self.log_prefix} 思考频率阈值: {self.talk_threshold}")
async def _loopbody(self): # sourcery skip: hoist-if-from-if
recent_messages_list = message_api.get_messages_by_time_in_chat(
chat_id=self.stream_id,
@ -193,7 +173,7 @@ class HeartFChatting:
filter_command=True,
)
if len(recent_messages_list) >= self.talk_threshold:
if len(recent_messages_list) >= 1:
# !处理no_reply_until_call逻辑
if self.no_reply_until_call:
for message in recent_messages_list:
@ -212,10 +192,21 @@ class HeartFChatting:
return True
self.last_read_time = time.time()
# !此处使at或者提及必定回复
metioned_message = None
for message in recent_messages_list:
if (message.is_mentioned or message.is_at) and global_config.chat.mentioned_bot_reply:
metioned_message = message
# *控制频率用
if not metioned_message:
if random.random() > global_config.chat.talk_value:
return True
await self._observe(
recent_messages_list=recent_messages_list,
recent_messages_list=recent_messages_list,force_reply_message=metioned_message
)
self.get_talk_threshold()
else:
# Normal模式：消息数量不足，等待
await asyncio.sleep(0.2)
@ -274,7 +265,7 @@ class HeartFChatting:
async def _observe(
self, # interest_value: float = 0.0,
recent_messages_list: Optional[List["DatabaseMessages"]] = None,
recent_messages_list: Optional[List["DatabaseMessages"]] = None, force_reply_message:"DatabaseMessages" = None
) -> bool: # sourcery skip: merge-else-if-into-elif, remove-redundant-if
if recent_messages_list is None:
recent_messages_list = []
@ -335,25 +326,19 @@ class HeartFChatting:
available_actions=available_actions,
)
# !此处使at或者提及必定回复
metioned_message = None
for message in recent_messages_list:
if (message.is_mentioned or message.is_at) and global_config.chat.mentioned_bot_reply:
metioned_message = message
has_reply = False
for action in action_to_use_info:
if action.action_type == "reply":
has_reply = True
break
if not has_reply and metioned_message:
if not has_reply and force_reply_message:
action_to_use_info.append(
ActionPlannerInfo(
action_type="reply",
reasoning="有人提到了你，进行回复",
action_data={},
action_message=metioned_message,
action_message=force_reply_message,
available_actions=available_actions,
)
)
@ -556,92 +541,94 @@ class HeartFChatting:
):
"""执行单个动作的通用函数"""
try:
if action_planner_info.action_type == "no_reply":
# 直接处理no_action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}")
with Timer(f"动作{action_planner_info.action_type}", cycle_timers):
if action_planner_info.action_type == "no_reply":
# 直接处理no_action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}")
# 存储no_action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="no_action",
)
return {"action_type": "no_action", "success": True, "reply_text": "", "command": ""}
elif action_planner_info.action_type == "wait_time":
action_planner_info.action_data = action_planner_info.action_data or {}
logger.info(f"{self.log_prefix} 等待{action_planner_info.action_data['time']}秒后回复")
await asyncio.sleep(action_planner_info.action_data["time"])
return {"action_type": "wait_time", "success": True, "reply_text": "", "command": ""}
elif action_planner_info.action_type == "no_reply_until_call":
logger.info(f"{self.log_prefix} 保持沉默，直到有人直接叫的名字")
self.no_reply_until_call = True
return {"action_type": "no_reply_until_call", "success": True, "reply_text": "", "command": ""}
elif action_planner_info.action_type == "reply":
try:
success, llm_response = await generator_api.generate_reply(
# 存储no_action信息到数据库
await database_api.store_action_info(
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,
action_build_into_prompt=False,
action_prompt_display=reason,
action_done=True,
thinking_id=thinking_id,
action_data={"reason": reason},
action_name="no_action",
)
return {"action_type": "no_action", "success": True, "reply_text": "", "command": ""}
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")
elif action_planner_info.action_type == "wait_time":
action_planner_info.action_data = action_planner_info.action_data or {}
logger.info(f"{self.log_prefix} 等待{action_planner_info.action_data['time']}秒后回复")
await asyncio.sleep(action_planner_info.action_data["time"])
return {"action_type": "wait_time", "success": True, "reply_text": "", "command": ""}
elif action_planner_info.action_type == "no_reply_until_call":
logger.info(f"{self.log_prefix} 保持沉默，直到有人直接叫的名字")
self.no_reply_until_call = True
return {"action_type": "no_reply_until_call", "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}
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,
)
return {
"action_type": "reply",
"success": True,
"reply_text": reply_text,
"loop_info": loop_info,
}
# 其他动作
else:
# 执行普通动作
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,
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,
)
return {
"action_type": action_planner_info.action_type,
"success": success,
"reply_text": reply_text,
"command": command,
}
return {
"action_type": "reply",
"success": True,
"reply_text": reply_text,
"loop_info": loop_info,
}
# 其他动作
else:
# 执行普通动作
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,
)
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}")

22
src/chat/heart_flow/heartflow.py
View File

@ -1,8 +1,11 @@
import traceback
from typing import Any, Optional, Dict
from src.chat.message_receive.chat_stream import get_chat_manager
from src.common.logger import get_logger
from src.chat.heart_flow.heartFC_chat import HeartFChatting
from src.chat.heart_flow.brain_chat import BrainChatting
from src.chat.message_receive.chat_stream import ChatStream
logger = get_logger("heartflow")
@ -11,19 +14,26 @@ class Heartflow:
"""主心流协调器，负责初始化并协调聊天"""
def __init__(self):
self.heartflow_chat_list: Dict[Any, HeartFChatting] = {}
self.heartflow_chat_list: Dict[Any, HeartFChatting | BrainChatting] = {}
async def get_or_create_heartflow_chat(self, chat_id: Any) -> Optional[HeartFChatting]:
async def get_or_create_heartflow_chat(self, chat_id: Any) -> Optional[HeartFChatting | BrainChatting]:
"""获取或创建一个新的HeartFChatting实例"""
try:
if chat_id in self.heartflow_chat_list:
if chat := self.heartflow_chat_list.get(chat_id):
return chat
else:
new_chat = HeartFChatting(chat_id=chat_id)
await new_chat.start()
self.heartflow_chat_list[chat_id] = new_chat
return new_chat
chat_stream: ChatStream = get_chat_manager().get_stream(chat_id)
if chat_stream.group_info:
new_chat = HeartFChatting(chat_id=chat_id)
await new_chat.start()
self.heartflow_chat_list[chat_id] = new_chat
return new_chat
else:
new_chat = BrainChatting(chat_id=chat_id)
await new_chat.start()
self.heartflow_chat_list[chat_id] = new_chat
return new_chat
except Exception as e:
logger.error(f"创建心流聊天 {chat_id} 失败: {e}", exc_info=True)
traceback.print_exc()

6
src/chat/planner_actions/planner.py
View File

@ -177,7 +177,7 @@ class ActionPlanner:
target_message = message_id_list[-1][1]
else:
target_message = message_id_list[-1][1]
logger.info(f"{self.log_prefix}动作'{action}'缺少target_message_id，使用最新消息作为target_message")
logger.debug(f"{self.log_prefix}动作'{action}'缺少target_message_id，使用最新消息作为target_message")
# 验证action是否可用
available_action_names = [action_name for action_name, _ in current_available_actions]
@ -263,7 +263,7 @@ class ActionPlanner:
# 应用激活类型过滤
filtered_actions = self._filter_actions_by_activation_type(available_actions, chat_content_block_short)
logger.info(f"{self.log_prefix}过滤后有{len(filtered_actions)}个可用动作")
logger.debug(f"{self.log_prefix}过滤后有{len(filtered_actions)}个可用动作")
# 构建包含所有动作的提示词
prompt, message_id_list = await self.build_planner_prompt(
@ -483,7 +483,7 @@ class ActionPlanner:
if llm_content:
try:
if json_objects := self._extract_json_from_markdown(llm_content):
logger.info(f"{self.log_prefix}从响应中提取到{len(json_objects)}个JSON对象")
logger.debug(f"{self.log_prefix}从响应中提取到{len(json_objects)}个JSON对象")
filtered_actions_list = list(filtered_actions.items())
for json_obj in json_objects:
actions.extend(self._parse_single_action(json_obj, message_id_list, filtered_actions_list))

2
src/chat/replyer/default_generator.py
View File

@ -278,7 +278,7 @@ class DefaultReplyer:
expression_habits_title = ""
if style_habits_str.strip():
expression_habits_title = (
"在回复时,你可以参考以下的语言习惯，当情景合适就使用，但不要生硬使用，以合理的方式结合到你的回复中："
"在回复时,你可以参考以下的语言习惯，不要生硬使用："
)
expression_habits_block += f"{style_habits_str}\n"

3
src/config/official_configs.py
View File

@ -456,9 +456,6 @@ class ExperimentalConfig(ConfigBase):
enable_friend_chat: bool = False
"""是否启用好友聊天"""
pfc_chatting: bool = False
"""是否启用PFC"""
@dataclass
class MaimMessageConfig(ConfigBase):

2
template/bot_config_template.toml
View File

@ -181,4 +181,4 @@ key_file = "" # SSL密钥文件路径，仅在use_wss=true时有效
enable = true
[experimental] #实验性功能
enable_friend_chat = false # 是否启用好友聊天
none = false # 暂无