diff --git a/bot.py b/bot.py
index d547c360e..770f5365b 100644
--- a/bot.py
+++ b/bot.py
@@ -119,7 +119,6 @@ async def graceful_shutdown():
for task in tasks:
task.cancel()
await asyncio.gather(*tasks, return_exceptions=True)
-
except Exception as e:
logger.error(f"麦麦关闭失败: {e}")
diff --git a/requirements.txt b/requirements.txt
index 06068d888..91ae096c1 100644
Binary files a/requirements.txt and b/requirements.txt differ
diff --git a/scripts/interest_monitor_gui.py b/scripts/interest_monitor_gui.py
index 1f03b9695..0c44507c8 100644
--- a/scripts/interest_monitor_gui.py
+++ b/scripts/interest_monitor_gui.py
@@ -28,8 +28,26 @@ matplotlib.rcParams["font.sans-serif"] = ["SimHei", "Microsoft YaHei"]
matplotlib.rcParams["axes.unicode_minus"] = False # 解决负号'-'显示为方块的问题
+def get_random_color():
+ """生成随机颜色用于区分线条"""
+ return "#{:06x}".format(random.randint(0, 0xFFFFFF))
+
+
+def format_timestamp(ts):
+ """辅助函数：格式化时间戳，处理 None 或无效值"""
+ if ts is None:
+ return "N/A"
+ try:
+ # 假设 ts 是 float 类型的时间戳
+ dt_object = datetime.fromtimestamp(float(ts))
+ return dt_object.strftime("%Y-%m-%d %H:%M:%S")
+ except (ValueError, TypeError):
+ return "Invalid Time"
+
+
class InterestMonitorApp:
def __init__(self, root):
+ self._main_mind_loaded = None
self.root = root
self.root.title(WINDOW_TITLE)
self.root.geometry("1800x800") # 调整窗口大小以适应图表
@@ -173,10 +191,6 @@ class InterestMonitorApp:
"""当 Combobox 选择改变时调用，更新单个流的图表"""
self.update_single_stream_plot()
- def get_random_color(self):
- """生成随机颜色用于区分线条"""
- return "#{:06x}".format(random.randint(0, 0xFFFFFF))
-
def load_main_mind_history(self):
"""只读取包含main_mind的日志行，维护历史想法队列"""
if not os.path.exists(LOG_FILE_PATH):
@@ -332,7 +346,7 @@ class InterestMonitorApp:
new_probability_history[stream_id] = deque(maxlen=MAX_HISTORY_POINTS) # 创建概率 deque
# 检查是否已有颜色，没有则分配
if stream_id not in self.stream_colors:
- self.stream_colors[stream_id] = self.get_random_color()
+ self.stream_colors[stream_id] = get_random_color()
# *** 存储此 stream_id 最新的显示名称 ***
new_stream_display_names[stream_id] = group_name
@@ -593,17 +607,6 @@ class InterestMonitorApp:
# --- 新增：重新绘制画布 ---
self.canvas_single.draw()
- def format_timestamp(self, ts):
- """辅助函数：格式化时间戳，处理 None 或无效值"""
- if ts is None:
- return "N/A"
- try:
- # 假设 ts 是 float 类型的时间戳
- dt_object = datetime.fromtimestamp(float(ts))
- return dt_object.strftime("%Y-%m-%d %H:%M:%S")
- except (ValueError, TypeError):
- return "Invalid Time"
-
def update_single_stream_details(self, stream_id):
"""更新单个流详情区域的标签内容"""
if stream_id:
@@ -616,8 +619,8 @@ class InterestMonitorApp:
self.single_stream_sub_mind.set(f"想法: {sub_mind}")
self.single_stream_chat_state.set(f"状态: {chat_state}")
self.single_stream_threshold.set(f"阈值以上: {'是' if threshold else '否'}")
- self.single_stream_last_active.set(f"最后活跃: {self.format_timestamp(last_active_ts)}")
- self.single_stream_last_interaction.set(f"最后交互: {self.format_timestamp(last_interaction_ts)}")
+ self.single_stream_last_active.set(f"最后活跃: {format_timestamp(last_active_ts)}")
+ self.single_stream_last_interaction.set(f"最后交互: {format_timestamp(last_interaction_ts)}")
else:
# 如果没有选择流，则清空详情
self.single_stream_sub_mind.set("想法: N/A")
diff --git a/src/common/logger.py b/src/common/logger.py
index 6c95935ea..a0d621d9b 100644
--- a/src/common/logger.py
+++ b/src/common/logger.py
@@ -321,7 +321,7 @@ CHAT_STYLE_CONFIG = {
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 见闻 | {message}",
},
"simple": {
- "console_format": ("{time:MM-DD HH:mm} | 见闻 | {message}"), # noqa: E501
+ "console_format": "{time:MM-DD HH:mm} | 见闻 | {message}", # noqa: E501
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 见闻 | {message}",
},
}
@@ -353,7 +353,7 @@ SUB_HEARTFLOW_STYLE_CONFIG = {
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦小脑袋 | {message}",
},
"simple": {
- "console_format": ("{time:MM-DD HH:mm} | 麦麦水群 | {message}"), # noqa: E501
+ "console_format": "{time:MM-DD HH:mm} | 麦麦水群 | {message}", # noqa: E501
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦水群 | {message}",
},
}
@@ -369,7 +369,7 @@ SUB_HEARTFLOW_MIND_STYLE_CONFIG = {
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦小脑袋 | {message}",
},
"simple": {
- "console_format": ("{time:MM-DD HH:mm} | 麦麦小脑袋 | {message}"), # noqa: E501
+ "console_format": "{time:MM-DD HH:mm} | 麦麦小脑袋 | {message}", # noqa: E501
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦小脑袋 | {message}",
},
}
@@ -385,7 +385,7 @@ SUBHEARTFLOW_MANAGER_STYLE_CONFIG = {
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦水群[管理] | {message}",
},
"simple": {
- "console_format": ("{time:MM-DD HH:mm} | 麦麦水群[管理] | {message}"), # noqa: E501
+ "console_format": "{time:MM-DD HH:mm} | 麦麦水群[管理] | {message}", # noqa: E501
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦水群[管理] | {message}",
},
}
@@ -633,7 +633,7 @@ HFC_STYLE_CONFIG = {
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 专注聊天 | {message}",
},
"simple": {
- "console_format": ("{time:MM-DD HH:mm} | 专注聊天 | {message}"),
+ "console_format": "{time:MM-DD HH:mm} | 专注聊天 | {message}",
"file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 专注聊天 | {message}",
},
}
@@ -1031,7 +1031,7 @@ def add_custom_style_handler(
# retention=current_config["retention"],
# compression=current_config["compression"],
# encoding="utf-8",
- # filter=lambda record: record["extra"].get("module") == module_name
+ # message_filter=lambda record: record["extra"].get("module") == module_name
# and record["extra"].get("custom_style") == style_name,
# enqueue=True,
# )
diff --git a/src/common/message_repository.py b/src/common/message_repository.py
index fc7b7e542..72643f913 100644
--- a/src/common/message_repository.py
+++ b/src/common/message_repository.py
@@ -7,13 +7,16 @@ logger = get_module_logger(__name__)
def find_messages(
- filter: Dict[str, Any], sort: Optional[List[tuple[str, int]]] = None, limit: int = 0, limit_mode: str = "latest"
+ message_filter: Dict[str, Any],
+ sort: Optional[List[tuple[str, int]]] = None,
+ limit: int = 0,
+ limit_mode: str = "latest",
) -> List[Dict[str, Any]]:
"""
根据提供的过滤器、排序和限制条件查找消息。
Args:
- filter: MongoDB 查询过滤器。
+ message_filter: MongoDB 查询过滤器。
sort: MongoDB 排序条件列表，例如 [('time', 1)]。仅在 limit 为 0 时生效。
limit: 返回的最大文档数，0表示不限制。
limit_mode: 当 limit > 0 时生效。 'earliest' 表示获取最早的记录， 'latest' 表示获取最新的记录（结果仍按时间正序排列）。默认为 'latest'。
@@ -22,7 +25,7 @@ def find_messages(
消息文档列表，如果出错则返回空列表。
"""
try:
- query = db.messages.find(filter)
+ query = db.messages.find(message_filter)
results: List[Dict[str, Any]] = []
if limit > 0:
@@ -46,28 +49,28 @@ def find_messages(
return results
except Exception as e:
log_message = (
- f"查找消息失败 (filter={filter}, sort={sort}, limit={limit}, limit_mode={limit_mode}): {e}\n"
+ f"查找消息失败 (filter={message_filter}, sort={sort}, limit={limit}, limit_mode={limit_mode}): {e}\n"
+ traceback.format_exc()
)
logger.error(log_message)
return []
-def count_messages(filter: Dict[str, Any]) -> int:
+def count_messages(message_filter: Dict[str, Any]) -> int:
"""
根据提供的过滤器计算消息数量。
Args:
- filter: MongoDB 查询过滤器。
+ message_filter: MongoDB 查询过滤器。
Returns:
符合条件的消息数量，如果出错则返回 0。
"""
try:
- count = db.messages.count_documents(filter)
+ count = db.messages.count_documents(message_filter)
return count
except Exception as e:
- log_message = f"计数消息失败 (filter={filter}): {e}\n" + traceback.format_exc()
+ log_message = f"计数消息失败 (message_filter={message_filter}): {e}\n" + traceback.format_exc()
logger.error(log_message)
return 0
diff --git a/src/heart_flow/background_tasks.py b/src/heart_flow/background_tasks.py
index 56fee2a91..383606530 100644
--- a/src/heart_flow/background_tasks.py
+++ b/src/heart_flow/background_tasks.py
@@ -25,6 +25,33 @@ STATE_UPDATE_INTERVAL_SECONDS = 60
LOG_INTERVAL_SECONDS = 3
+async def _run_periodic_loop(
+ task_name: str, interval: int, task_func: Callable[..., Coroutine[Any, Any, None]], **kwargs
+):
+ """周期性任务主循环"""
+ while True:
+ start_time = asyncio.get_event_loop().time()
+ # logger.debug(f"开始执行后台任务: {task_name}")
+
+ try:
+ await task_func(**kwargs) # 执行实际任务
+ except asyncio.CancelledError:
+ logger.info(f"任务 {task_name} 已取消")
+ break
+ except Exception as e:
+ logger.error(f"任务 {task_name} 执行出错: {e}")
+ logger.error(traceback.format_exc())
+
+ # 计算并执行间隔等待
+ elapsed = asyncio.get_event_loop().time() - start_time
+ sleep_time = max(0, interval - elapsed)
+ # if sleep_time < 0.1: # 任务超时处理, DEBUG 时可能干扰断点
+ # logger.warning(f"任务 {task_name} 超时执行 ({elapsed:.2f}s > {interval}s)")
+ await asyncio.sleep(sleep_time)
+
+ logger.debug(f"任务循环结束: {task_name}") # 调整日志信息
+
+
class BackgroundTaskManager:
"""管理 Heartflow 的后台周期性任务。"""
@@ -143,32 +170,6 @@ class BackgroundTaskManager:
# 第三步：清空任务列表
self._tasks = [] # 重置任务列表
- async def _run_periodic_loop(
- self, task_name: str, interval: int, task_func: Callable[..., Coroutine[Any, Any, None]], **kwargs
- ):
- """周期性任务主循环"""
- while True:
- start_time = asyncio.get_event_loop().time()
- # logger.debug(f"开始执行后台任务: {task_name}")
-
- try:
- await task_func(**kwargs) # 执行实际任务
- except asyncio.CancelledError:
- logger.info(f"任务 {task_name} 已取消")
- break
- except Exception as e:
- logger.error(f"任务 {task_name} 执行出错: {e}")
- logger.error(traceback.format_exc())
-
- # 计算并执行间隔等待
- elapsed = asyncio.get_event_loop().time() - start_time
- sleep_time = max(0, interval - elapsed)
- # if sleep_time < 0.1: # 任务超时处理, DEBUG 时可能干扰断点
- # logger.warning(f"任务 {task_name} 超时执行 ({elapsed:.2f}s > {interval}s)")
- await asyncio.sleep(sleep_time)
-
- logger.debug(f"任务循环结束: {task_name}") # 调整日志信息
-
async def _perform_state_update_work(self):
"""执行状态更新工作"""
previous_status = self.mai_state_info.get_current_state()
@@ -249,33 +250,33 @@ class BackgroundTaskManager:
# --- Specific Task Runners --- #
async def _run_state_update_cycle(self, interval: int):
- await self._run_periodic_loop(
+ await _run_periodic_loop(
task_name="State Update", interval=interval, task_func=self._perform_state_update_work
)
async def _run_absent_into_chat(self, interval: int):
- await self._run_periodic_loop(
+ await _run_periodic_loop(
task_name="Into Chat", interval=interval, task_func=self._perform_absent_into_chat
)
async def _run_normal_chat_timeout_check_cycle(self, interval: int):
- await self._run_periodic_loop(
+ await _run_periodic_loop(
task_name="Normal Chat Timeout Check", interval=interval, task_func=self._normal_chat_timeout_check_work
)
async def _run_cleanup_cycle(self):
- await self._run_periodic_loop(
+ await _run_periodic_loop(
task_name="Subflow Cleanup", interval=CLEANUP_INTERVAL_SECONDS, task_func=self._perform_cleanup_work
)
async def _run_logging_cycle(self):
- await self._run_periodic_loop(
+ await _run_periodic_loop(
task_name="State Logging", interval=LOG_INTERVAL_SECONDS, task_func=self._perform_logging_work
)
# --- 新增兴趣评估任务运行器 ---
async def _run_into_focus_cycle(self):
- await self._run_periodic_loop(
+ await _run_periodic_loop(
task_name="Into Focus",
interval=INTEREST_EVAL_INTERVAL_SECONDS,
task_func=self._perform_into_focus_work,
diff --git a/src/heart_flow/interest_logger.py b/src/heart_flow/interest_logger.py
index 04cdb6f43..06d3f1cb0 100644
--- a/src/heart_flow/interest_logger.py
+++ b/src/heart_flow/interest_logger.py
@@ -23,6 +23,12 @@ LOG_DIRECTORY = "logs/interest"
HISTORY_LOG_FILENAME = "interest_history.log"
+def _ensure_log_directory():
+ """确保日志目录存在。"""
+ os.makedirs(LOG_DIRECTORY, exist_ok=True)
+ logger.info(f"已确保日志目录 '{LOG_DIRECTORY}' 存在")
+
+
class InterestLogger:
"""负责定期记录主心流和所有子心流的状态到日志文件。"""
@@ -37,12 +43,7 @@ class InterestLogger:
self.subheartflow_manager = subheartflow_manager
self.heartflow = heartflow # 存储 Heartflow 实例
self._history_log_file_path = os.path.join(LOG_DIRECTORY, HISTORY_LOG_FILENAME)
- self._ensure_log_directory()
-
- def _ensure_log_directory(self):
- """确保日志目录存在。"""
- os.makedirs(LOG_DIRECTORY, exist_ok=True)
- logger.info(f"已确保日志目录 '{LOG_DIRECTORY}' 存在")
+ _ensure_log_directory()
async def get_all_subflow_states(self) -> Dict[str, Dict]:
"""并发获取所有活跃子心流的当前完整状态。"""
diff --git a/src/heart_flow/sub_mind.py b/src/heart_flow/sub_mind.py
index fbf1be870..f1716d249 100644
--- a/src/heart_flow/sub_mind.py
+++ b/src/heart_flow/sub_mind.py
@@ -86,6 +86,7 @@ def calculate_replacement_probability(similarity: float) -> float:
class SubMind:
def __init__(self, subheartflow_id: str, chat_state: ChatStateInfo, observations: Observation):
+ self.last_active_time = None
self.subheartflow_id = subheartflow_id
self.llm_model = LLMRequest(
diff --git a/src/plugins/PFC/chat_observer.py b/src/plugins/PFC/chat_observer.py
index 102c95028..2822e1111 100644
--- a/src/plugins/PFC/chat_observer.py
+++ b/src/plugins/PFC/chat_observer.py
@@ -37,6 +37,10 @@ class ChatObserver:
Args:
stream_id: 聊天流ID
"""
+ self.last_check_time = None
+ self.last_check_time = None
+ self.last_bot_speak_time = None
+ self.last_user_speak_time = None
if stream_id in self._instances:
raise RuntimeError(f"ChatObserver for {stream_id} already exists. Use get_instance() instead.")
diff --git a/src/plugins/PFC/message_storage.py b/src/plugins/PFC/message_storage.py
index b57f5d2b5..cd6a01e34 100644
--- a/src/plugins/PFC/message_storage.py
+++ b/src/plugins/PFC/message_storage.py
@@ -51,11 +51,9 @@ class MongoDBMessageStorage(MessageStorage):
"""MongoDB消息存储实现"""
async def get_messages_after(self, chat_id: str, message_time: float) -> List[Dict[str, Any]]:
- query = {"chat_id": chat_id}
+ query = {"chat_id": chat_id, "time": {"$gt": message_time}}
# print(f"storage_check_message: {message_time}")
- query["time"] = {"$gt": message_time}
-
return list(db.messages.find(query).sort("time", 1))
async def get_messages_before(self, chat_id: str, time_point: float, limit: int = 5) -> List[Dict[str, Any]]:
diff --git a/src/plugins/PFC/observation_info.py b/src/plugins/PFC/observation_info.py
index 35f393014..af7f537bc 100644
--- a/src/plugins/PFC/observation_info.py
+++ b/src/plugins/PFC/observation_info.py
@@ -158,6 +158,10 @@ class ObservationInfo:
# meta_plan_trigger: bool = False
# --- 修改：移除 __post_init__ 的参数 ---
+ def __init__(self):
+ self.chat_observer = None
+ self.chat_observer = None
+
def __post_init__(self):
"""初始化后创建handler并进行必要的设置"""
self.chat_observer: Optional[ChatObserver] = None # 添加类型提示
diff --git a/src/plugins/PFC/pfc.py b/src/plugins/PFC/pfc.py
index d6f4c5192..e12cb2429 100644
--- a/src/plugins/PFC/pfc.py
+++ b/src/plugins/PFC/pfc.py
@@ -147,14 +147,14 @@ class GoalAnalyzer:
# 返回第一个目标作为当前主要目标（如果有）
if result:
first_goal = result[0]
- return (first_goal.get("goal", ""), "", first_goal.get("reasoning", ""))
+ return first_goal.get("goal", ""), "", first_goal.get("reasoning", "")
else:
# 单个目标的情况
conversation_info.goal_list.append(result)
- return (goal, "", reasoning)
+ return goal, "", reasoning
# 如果解析失败，返回默认值
- return ("", "", "")
+ return "", "", ""
async def _update_goals(self, new_goal: str, method: str, reasoning: str):
"""更新目标列表
diff --git a/src/plugins/chat/bot.py b/src/plugins/chat/bot.py
index 8051d0a8e..7ca1483cc 100644
--- a/src/plugins/chat/bot.py
+++ b/src/plugins/chat/bot.py
@@ -1,3 +1,5 @@
+from typing import Dict, Any
+
from ..moods.moods import MoodManager # 导入情绪管理器
from ...config.config import global_config
from .message import MessageRecv
@@ -46,7 +48,7 @@ class ChatBot:
except Exception as e:
logger.error(f"创建PFC聊天失败: {e}")
- async def message_process(self, message_data: str) -> None:
+ async def message_process(self, message_data: Dict[str, Any]) -> None:
"""处理转化后的统一格式消息
这个函数本质是预处理一些数据，根据配置信息和消息内容，预处理消息，并分发到合适的消息处理器中
heart_flow模式：使用思维流系统进行回复
diff --git a/src/plugins/chat/message_sender.py b/src/plugins/chat/message_sender.py
index 493397bbd..30d943d97 100644
--- a/src/plugins/chat/message_sender.py
+++ b/src/plugins/chat/message_sender.py
@@ -17,6 +17,40 @@ from src.common.logger_manager import get_logger
logger = get_logger("sender")
+async def send_via_ws(message: MessageSending) -> None:
+ """通过 WebSocket 发送消息"""
+ try:
+ await send_message(message)
+ except Exception as e:
+ logger.error(f"WS发送失败: {e}")
+ raise ValueError(f"未找到平台：{message.message_info.platform} 的url配置，请检查配置文件") from e
+
+
+async def send_message(
+ message: MessageSending,
+) -> None:
+ """发送消息（核心发送逻辑）"""
+
+ # --- 添加计算打字和延迟的逻辑 (从 heartflow_message_sender 移动并调整) ---
+ typing_time = calculate_typing_time(
+ input_string=message.processed_plain_text,
+ thinking_start_time=message.thinking_start_time,
+ is_emoji=message.is_emoji,
+ )
+ # logger.trace(f"{message.processed_plain_text},{typing_time},计算输入时间结束") # 减少日志
+ await asyncio.sleep(typing_time)
+ # logger.trace(f"{message.processed_plain_text},{typing_time},等待输入时间结束") # 减少日志
+ # --- 结束打字延迟 ---
+
+ message_preview = truncate_message(message.processed_plain_text)
+
+ try:
+ await send_via_ws(message)
+ logger.success(f"发送消息 '{message_preview}' 成功") # 调整日志格式
+ except Exception as e:
+ logger.error(f"发送消息 '{message_preview}' 失败: {str(e)}")
+
+
class MessageSender:
"""发送器 (不再是单例)"""
@@ -29,39 +63,6 @@ class MessageSender:
"""设置当前bot实例"""
pass
- async def send_via_ws(self, message: MessageSending) -> None:
- """通过 WebSocket 发送消息"""
- try:
- await global_api.send_message(message)
- except Exception as e:
- logger.error(f"WS发送失败: {e}")
- raise ValueError(f"未找到平台：{message.message_info.platform} 的url配置，请检查配置文件") from e
-
- async def send_message(
- self,
- message: MessageSending,
- ) -> None:
- """发送消息（核心发送逻辑）"""
-
- # --- 添加计算打字和延迟的逻辑 (从 heartflow_message_sender 移动并调整) ---
- typing_time = calculate_typing_time(
- input_string=message.processed_plain_text,
- thinking_start_time=message.thinking_start_time,
- is_emoji=message.is_emoji,
- )
- # logger.trace(f"{message.processed_plain_text},{typing_time},计算输入时间结束") # 减少日志
- await asyncio.sleep(typing_time)
- # logger.trace(f"{message.processed_plain_text},{typing_time},等待输入时间结束") # 减少日志
- # --- 结束打字延迟 ---
-
- message_preview = truncate_message(message.processed_plain_text)
-
- try:
- await self.send_via_ws(message)
- logger.success(f"发送消息 '{message_preview}' 成功") # 调整日志格式
- except Exception as e:
- logger.error(f"发送消息 '{message_preview}' 失败: {str(e)}")
-
class MessageContainer:
"""单个聊天流的发送/思考消息容器"""
@@ -119,7 +120,7 @@ class MessageContainer:
"""移除指定的消息对象，如果消息存在则返回True，否则返回False"""
try:
_initial_len = len(self.messages)
- # 使用列表推导式或 filter 创建新列表，排除要删除的元素
+ # 使用列表推导式或 message_filter 创建新列表，排除要删除的元素
# self.messages = [msg for msg in self.messages if msg is not message_to_remove]
# 或者直接 remove (如果确定对象唯一性)
if message_to_remove in self.messages:
@@ -146,6 +147,7 @@ class MessageManager:
"""管理所有聊天流的消息容器 (不再是单例)"""
def __init__(self):
+ self._processor_task = None
self.containers: Dict[str, MessageContainer] = {}
self.storage = MessageStorage() # 添加 storage 实例
self._running = True # 处理器运行状态
@@ -226,7 +228,7 @@ class MessageManager:
await message.process() # 预处理消息内容
# 使用全局 message_sender 实例
- await message_sender.send_message(message)
+ await send_message(message)
await self.storage.store_message(message, message.chat_stream)
# 移除消息要在发送 *之后*
diff --git a/src/plugins/chat/utils.py b/src/plugins/chat/utils.py
index 71980f484..16581f3aa 100644
--- a/src/plugins/chat/utils.py
+++ b/src/plugins/chat/utils.py
@@ -263,7 +263,7 @@ def split_into_sentences_w_remove_punctuation(text: str) -> List[str]:
if char in separators:
# 检查分割条件：如果分隔符左右都是英文字母，则不分割
can_split = True
- if i > 0 and i < len(text) - 1:
+ if 0 < i < len(text) - 1:
prev_char = text[i - 1]
next_char = text[i + 1]
# if is_english_letter(prev_char) and is_english_letter(next_char) and char == ' ': # 原计划只对空格应用此规则，现应用于所有分隔符
diff --git a/src/plugins/emoji_system/emoji_manager.py b/src/plugins/emoji_system/emoji_manager.py
index d6da4ce3f..a75a4f904 100644
--- a/src/plugins/emoji_system/emoji_manager.py
+++ b/src/plugins/emoji_system/emoji_manager.py
@@ -16,7 +16,6 @@ from ..chat.utils_image import image_path_to_base64, image_manager
from ..models.utils_model import LLMRequest
from src.common.logger_manager import get_logger
-
logger = get_logger("emoji")
BASE_DIR = os.path.join("data")
@@ -24,7 +23,6 @@ EMOJI_DIR = os.path.join(BASE_DIR, "emoji") # 表情包存储目录
EMOJI_REGISTED_DIR = os.path.join(BASE_DIR, "emoji_registed") # 已注册的表情包注册目录
MAX_EMOJI_FOR_PROMPT = 20 # 最大允许的表情包描述数量于图片替换的 prompt 中
-
"""
还没经过测试，有些地方数据库和内存数据同步可能不完全
@@ -225,6 +223,140 @@ class MaiEmoji:
return False
+def _emoji_objects_to_readable_list(emoji_objects):
+ """将表情包对象列表转换为可读的字符串列表
+
+ 参数:
+ emoji_objects: MaiEmoji对象列表
+
+ 返回:
+ list[str]: 可读的表情包信息字符串列表
+ """
+ emoji_info_list = []
+ for i, emoji in enumerate(emoji_objects):
+ # 转换时间戳为可读时间
+ time_str = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(emoji.register_time))
+ # 构建每个表情包的信息字符串
+ emoji_info = f"编号: {i + 1}\n描述: {emoji.description}\n使用次数: {emoji.usage_count}\n添加时间: {time_str}\n"
+ emoji_info_list.append(emoji_info)
+ return emoji_info_list
+
+
+def _to_emoji_objects(data):
+ emoji_objects = []
+ load_errors = 0
+ emoji_data_list = list(data)
+
+ for emoji_data in emoji_data_list:
+ full_path = emoji_data.get("full_path")
+ if not full_path:
+ logger.warning(f"[加载错误] 数据库记录缺少 'full_path' 字段: {emoji_data.get('_id')}")
+ load_errors += 1
+ continue # 跳过缺少 full_path 的记录
+
+ try:
+ # 使用 full_path 初始化 MaiEmoji 对象
+ emoji = MaiEmoji(full_path=full_path)
+
+ # 设置从数据库加载的属性
+ emoji.hash = emoji_data.get("hash", "")
+ # 如果 hash 为空，也跳过？取决于业务逻辑
+ if not emoji.hash:
+ logger.warning(f"[加载错误] 数据库记录缺少 'hash' 字段: {full_path}")
+ load_errors += 1
+ continue
+
+ emoji.description = emoji_data.get("description", "")
+ emoji.emotion = emoji_data.get("emotion", [])
+ emoji.usage_count = emoji_data.get("usage_count", 0)
+ # 优先使用 last_used_time，否则用 timestamp，最后用当前时间
+ last_used = emoji_data.get("last_used_time")
+ timestamp = emoji_data.get("timestamp")
+ emoji.last_used_time = (
+ last_used if last_used is not None else (timestamp if timestamp is not None else time.time())
+ )
+ emoji.register_time = timestamp if timestamp is not None else time.time()
+ emoji.format = emoji_data.get("format", "") # 加载格式
+
+ # 不需要再手动设置 path 和 filename，__init__ 会自动处理
+
+ emoji_objects.append(emoji)
+
+ except ValueError as ve: # 捕获 __init__ 可能的错误
+ logger.error(f"[加载错误] 初始化 MaiEmoji 失败 ({full_path}): {ve}")
+ load_errors += 1
+ except Exception as e:
+ logger.error(f"[加载错误] 处理数据库记录时出错 ({full_path}): {str(e)}")
+ load_errors += 1
+ return emoji_objects, load_errors
+ return emoji_objects, load_errors
+
+
+def _ensure_emoji_dir():
+ """确保表情存储目录存在"""
+ os.makedirs(EMOJI_DIR, exist_ok=True)
+ os.makedirs(EMOJI_REGISTED_DIR, exist_ok=True)
+
+
+async def clear_temp_emoji():
+ """清理临时表情包
+ 清理/data/emoji和/data/image目录下的所有文件
+ 当目录中文件数超过100时，会全部删除
+ """
+
+ logger.info("[清理] 开始清理缓存...")
+
+ for need_clear in (os.path.join(BASE_DIR, "emoji"), os.path.join(BASE_DIR, "image")):
+ if os.path.exists(need_clear):
+ files = os.listdir(need_clear)
+ # 如果文件数超过50就全部删除
+ if len(files) > 100:
+ for filename in files:
+ file_path = os.path.join(need_clear, filename)
+ if os.path.isfile(file_path):
+ os.remove(file_path)
+ logger.debug(f"[清理] 删除: {filename}")
+
+ logger.success("[清理] 完成")
+
+
+async def clean_unused_emojis(emoji_dir, emoji_objects):
+ """清理指定目录中未被 emoji_objects 追踪的表情包文件"""
+ if not os.path.exists(emoji_dir):
+ logger.warning(f"[清理] 目标目录不存在，跳过清理: {emoji_dir}")
+ return
+
+ try:
+ # 获取内存中所有有效表情包的完整路径集合
+ tracked_full_paths = {emoji.full_path for emoji in emoji_objects if not emoji.is_deleted}
+ cleaned_count = 0
+
+ # 遍历指定目录中的所有文件
+ for file_name in os.listdir(emoji_dir):
+ file_full_path = os.path.join(emoji_dir, file_name)
+
+ # 确保处理的是文件而不是子目录
+ if not os.path.isfile(file_full_path):
+ continue
+
+ # 如果文件不在被追踪的集合中，则删除
+ if file_full_path not in tracked_full_paths:
+ try:
+ os.remove(file_full_path)
+ logger.info(f"[清理] 删除未追踪的表情包文件: {file_full_path}")
+ cleaned_count += 1
+ except Exception as e:
+ logger.error(f"[错误] 删除文件时出错 ({file_full_path}): {str(e)}")
+
+ if cleaned_count > 0:
+ logger.success(f"[清理] 在目录 {emoji_dir} 中清理了 {cleaned_count} 个破损表情包。")
+ else:
+ logger.info(f"[清理] 目录 {emoji_dir} 中没有需要清理的。")
+
+ except Exception as e:
+ logger.error(f"[错误] 清理未使用表情包文件时出错 ({emoji_dir}): {str(e)}")
+
+
class EmojiManager:
_instance = None
@@ -235,6 +367,7 @@ class EmojiManager:
return cls._instance
def __init__(self):
+ self._initialized = None
self._scan_task = None
self.vlm = LLMRequest(model=global_config.vlm, temperature=0.3, max_tokens=1000, request_type="emoji")
self.llm_emotion_judge = LLMRequest(
@@ -248,23 +381,18 @@ class EmojiManager:
logger.info("启动表情包管理器")
- def _ensure_emoji_dir(self):
- """确保表情存储目录存在"""
- os.makedirs(EMOJI_DIR, exist_ok=True)
- os.makedirs(EMOJI_REGISTED_DIR, exist_ok=True)
-
def initialize(self):
"""初始化数据库连接和表情目录"""
if not self._initialized:
try:
self._ensure_emoji_collection()
- self._ensure_emoji_dir()
+ _ensure_emoji_dir()
self._initialized = True
# 更新表情包数量
# 启动时执行一次完整性检查
# await self.check_emoji_file_integrity()
- except Exception:
- logger.exception("初始化表情管理器失败")
+ except Exception as e:
+ logger.exception(f"初始化表情管理器失败: {e}")
def _ensure_db(self):
"""确保数据库已初始化"""
@@ -291,12 +419,12 @@ class EmojiManager:
db.emoji.create_index([("embedding", "2dsphere")])
db.emoji.create_index([("filename", 1)], unique=True)
- def record_usage(self, hash: str):
+ def record_usage(self, emoji_hash: str):
"""记录表情使用次数"""
try:
- db.emoji.update_one({"hash": hash}, {"$inc": {"usage_count": 1}})
+ db.emoji.update_one({"hash": emoji_hash}, {"$inc": {"usage_count": 1}})
for emoji in self.emoji_objects:
- if emoji.hash == hash:
+ if emoji.hash == emoji_hash:
emoji.usage_count += 1
break
@@ -458,7 +586,7 @@ class EmojiManager:
self.emoji_objects = [e for e in self.emoji_objects if e not in objects_to_remove]
# 清理 EMOJI_REGISTED_DIR 目录中未被追踪的文件
- await self.clean_unused_emojis(EMOJI_REGISTED_DIR, self.emoji_objects)
+ await clean_unused_emojis(EMOJI_REGISTED_DIR, self.emoji_objects)
# 输出清理结果
if removed_count > 0:
@@ -477,7 +605,7 @@ class EmojiManager:
while True:
logger.info("[扫描] 开始检查表情包完整性...")
await self.check_emoji_file_integrity()
- await self.clear_temp_emoji()
+ await clear_temp_emoji()
logger.info("[扫描] 开始扫描新表情包...")
# 检查表情包目录是否存在
@@ -531,51 +659,7 @@ class EmojiManager:
self._ensure_db()
logger.info("[数据库] 开始加载所有表情包记录...")
- all_emoji_data = list(db.emoji.find())
- emoji_objects = []
- load_errors = 0
-
- for emoji_data in all_emoji_data:
- full_path = emoji_data.get("full_path")
- if not full_path:
- logger.warning(f"[加载错误] 数据库记录缺少 'full_path' 字段: {emoji_data.get('_id')}")
- load_errors += 1
- continue # 跳过缺少 full_path 的记录
-
- try:
- # 使用 full_path 初始化 MaiEmoji 对象
- emoji = MaiEmoji(full_path=full_path)
-
- # 设置从数据库加载的属性
- emoji.hash = emoji_data.get("hash", "")
- # 如果 hash 为空，也跳过？取决于业务逻辑
- if not emoji.hash:
- logger.warning(f"[加载错误] 数据库记录缺少 'hash' 字段: {full_path}")
- load_errors += 1
- continue
-
- emoji.description = emoji_data.get("description", "")
- emoji.emotion = emoji_data.get("emotion", [])
- emoji.usage_count = emoji_data.get("usage_count", 0)
- # 优先使用 last_used_time，否则用 timestamp，最后用当前时间
- last_used = emoji_data.get("last_used_time")
- timestamp = emoji_data.get("timestamp")
- emoji.last_used_time = (
- last_used if last_used is not None else (timestamp if timestamp is not None else time.time())
- )
- emoji.register_time = timestamp if timestamp is not None else time.time()
- emoji.format = emoji_data.get("format", "") # 加载格式
-
- # 不需要再手动设置 path 和 filename，__init__ 会自动处理
-
- emoji_objects.append(emoji)
-
- except ValueError as ve: # 捕获 __init__ 可能的错误
- logger.error(f"[加载错误] 初始化 MaiEmoji 失败 ({full_path}): {ve}")
- load_errors += 1
- except Exception as e:
- logger.error(f"[加载错误] 处理数据库记录时出错 ({full_path}): {str(e)}")
- load_errors += 1
+ emoji_objects, load_errors = _to_emoji_objects(db.emoji.find())
# 更新内存中的列表和数量
self.emoji_objects = emoji_objects
@@ -590,11 +674,11 @@ class EmojiManager:
self.emoji_objects = [] # 加载失败则清空列表
self.emoji_num = 0
- async def get_emoji_from_db(self, hash=None):
+ async def get_emoji_from_db(self, emoji_hash=None):
"""获取指定哈希值的表情包并初始化为MaiEmoji类对象列表 (主要用于调试或特定查找)
参数:
- hash: 可选，如果提供则只返回指定哈希值的表情包
+ emoji_hash: 可选，如果提供则只返回指定哈希值的表情包
返回:
list[MaiEmoji]: 表情包对象列表
@@ -603,49 +687,14 @@ class EmojiManager:
self._ensure_db()
query = {}
- if hash:
- query = {"hash": hash}
+ if emoji_hash:
+ query = {"hash": emoji_hash}
else:
logger.warning(
"[查询] 未提供 hash，将尝试加载所有表情包，建议使用 get_all_emoji_from_db 更新管理器状态。"
)
- emoji_data_list = list(db.emoji.find(query))
- emoji_objects = []
- load_errors = 0
-
- for emoji_data in emoji_data_list:
- full_path = emoji_data.get("full_path")
- if not full_path:
- logger.warning(f"[加载错误] 数据库记录缺少 'full_path' 字段: {emoji_data.get('_id')}")
- load_errors += 1
- continue
-
- try:
- emoji = MaiEmoji(full_path=full_path)
- emoji.hash = emoji_data.get("hash", "")
- if not emoji.hash:
- logger.warning(f"[加载错误] 数据库记录缺少 'hash' 字段: {full_path}")
- load_errors += 1
- continue
-
- emoji.description = emoji_data.get("description", "")
- emoji.emotion = emoji_data.get("emotion", [])
- emoji.usage_count = emoji_data.get("usage_count", 0)
- last_used = emoji_data.get("last_used_time")
- timestamp = emoji_data.get("timestamp")
- emoji.last_used_time = (
- last_used if last_used is not None else (timestamp if timestamp is not None else time.time())
- )
- emoji.register_time = timestamp if timestamp is not None else time.time()
- emoji.format = emoji_data.get("format", "")
- emoji_objects.append(emoji)
- except ValueError as ve:
- logger.error(f"[加载错误] 初始化 MaiEmoji 失败 ({full_path}): {ve}")
- load_errors += 1
- except Exception as e:
- logger.error(f"[加载错误] 处理数据库记录时出错 ({full_path}): {str(e)}")
- load_errors += 1
+ emoji_objects, load_errors = _to_emoji_objects(db.emoji.find(query))
if load_errors > 0:
logger.warning(f"[查询] 加载过程中出现 {load_errors} 个错误。")
@@ -656,17 +705,17 @@ class EmojiManager:
logger.error(f"[错误] 从数据库获取表情包对象失败: {str(e)}")
return []
- async def get_emoji_from_manager(self, hash) -> Optional[MaiEmoji]:
+ async def get_emoji_from_manager(self, emoji_hash) -> Optional[MaiEmoji]:
"""从内存中的 emoji_objects 列表获取表情包
参数:
- hash: 要查找的表情包哈希值
+ emoji_hash: 要查找的表情包哈希值
返回:
MaiEmoji 或 None: 如果找到则返回 MaiEmoji 对象，否则返回 None
"""
for emoji in self.emoji_objects:
# 确保对象未被标记为删除且哈希值匹配
- if not emoji.is_deleted and emoji.hash == hash:
+ if not emoji.is_deleted and emoji.hash == emoji_hash:
return emoji
return None # 如果循环结束还没找到，则返回 None
@@ -709,26 +758,6 @@ class EmojiManager:
logger.error(traceback.format_exc())
return False
- def _emoji_objects_to_readable_list(self, emoji_objects):
- """将表情包对象列表转换为可读的字符串列表
-
- 参数:
- emoji_objects: MaiEmoji对象列表
-
- 返回:
- list[str]: 可读的表情包信息字符串列表
- """
- emoji_info_list = []
- for i, emoji in enumerate(emoji_objects):
- # 转换时间戳为可读时间
- time_str = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(emoji.register_time))
- # 构建每个表情包的信息字符串
- emoji_info = (
- f"编号: {i + 1}\n描述: {emoji.description}\n使用次数: {emoji.usage_count}\n添加时间: {time_str}\n"
- )
- emoji_info_list.append(emoji_info)
- return emoji_info_list
-
async def replace_a_emoji(self, new_emoji: MaiEmoji):
"""替换一个表情包
@@ -755,7 +784,7 @@ class EmojiManager:
)
# 将表情包信息转换为可读的字符串
- emoji_info_list = self._emoji_objects_to_readable_list(selected_emojis)
+ emoji_info_list = _emoji_objects_to_readable_list(selected_emojis)
# 构建提示词
prompt = (
@@ -853,7 +882,7 @@ class EmojiManager:
'''
content, _ = await self.vlm.generate_response_for_image(prompt, image_base64, image_format)
if content == "否":
- return None, []
+ return "", []
# 分析情感含义
emotion_prompt = f"""
@@ -989,76 +1018,6 @@ class EmojiManager:
logger.error(f"[错误] 删除异常处理文件时出错: {remove_error}")
return False
- async def clear_temp_emoji(self):
- """清理临时表情包
- 清理/data/emoji和/data/image目录下的所有文件
- 当目录中文件数超过100时，会全部删除
- """
-
- logger.info("[清理] 开始清理缓存...")
-
- # 清理emoji目录
- emoji_dir = os.path.join(BASE_DIR, "emoji")
- if os.path.exists(emoji_dir):
- files = os.listdir(emoji_dir)
- # 如果文件数超过50就全部删除
- if len(files) > 100:
- for filename in files:
- file_path = os.path.join(emoji_dir, filename)
- if os.path.isfile(file_path):
- os.remove(file_path)
- logger.debug(f"[清理] 删除: {filename}")
-
- # 清理image目录
- image_dir = os.path.join(BASE_DIR, "image")
- if os.path.exists(image_dir):
- files = os.listdir(image_dir)
- # 如果文件数超过50就全部删除
- if len(files) > 100:
- for filename in files:
- file_path = os.path.join(image_dir, filename)
- if os.path.isfile(file_path):
- os.remove(file_path)
- logger.debug(f"[清理] 删除图片: {filename}")
-
- logger.success("[清理] 完成")
-
- async def clean_unused_emojis(self, emoji_dir, emoji_objects):
- """清理指定目录中未被 emoji_objects 追踪的表情包文件"""
- if not os.path.exists(emoji_dir):
- logger.warning(f"[清理] 目标目录不存在，跳过清理: {emoji_dir}")
- return
-
- try:
- # 获取内存中所有有效表情包的完整路径集合
- tracked_full_paths = {emoji.full_path for emoji in emoji_objects if not emoji.is_deleted}
- cleaned_count = 0
-
- # 遍历指定目录中的所有文件
- for file_name in os.listdir(emoji_dir):
- file_full_path = os.path.join(emoji_dir, file_name)
-
- # 确保处理的是文件而不是子目录
- if not os.path.isfile(file_full_path):
- continue
-
- # 如果文件不在被追踪的集合中，则删除
- if file_full_path not in tracked_full_paths:
- try:
- os.remove(file_full_path)
- logger.info(f"[清理] 删除未追踪的表情包文件: {file_full_path}")
- cleaned_count += 1
- except Exception as e:
- logger.error(f"[错误] 删除文件时出错 ({file_full_path}): {str(e)}")
-
- if cleaned_count > 0:
- logger.success(f"[清理] 在目录 {emoji_dir} 中清理了 {cleaned_count} 个破损表情包。")
- else:
- logger.info(f"[清理] 目录 {emoji_dir} 中没有需要清理的。")
-
- except Exception as e:
- logger.error(f"[错误] 清理未使用表情包文件时出错 ({emoji_dir}): {str(e)}")
-
# 创建全局单例
emoji_manager = EmojiManager()
diff --git a/src/plugins/heartFC_chat/heartFC_chat.py b/src/plugins/heartFC_chat/heartFC_chat.py
index 73d679e4e..47d420dd7 100644
--- a/src/plugins/heartFC_chat/heartFC_chat.py
+++ b/src/plugins/heartFC_chat/heartFC_chat.py
@@ -144,6 +144,25 @@ class SenderError(HeartFCError):
pass
+async def _handle_cycle_delay(action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str):
+ """处理循环延迟"""
+ cycle_duration = time.monotonic() - cycle_start_time
+
+ try:
+ sleep_duration = 0.0
+ if not action_taken_this_cycle and cycle_duration < 1:
+ sleep_duration = 1 - cycle_duration
+ elif cycle_duration < 0.2:
+ sleep_duration = 0.2
+
+ if sleep_duration > 0:
+ await asyncio.sleep(sleep_duration)
+
+ except asyncio.CancelledError:
+ logger.info(f"{log_prefix} Sleep interrupted, loop likely cancelling.")
+ raise
+
+
class HeartFChatting:
"""
管理一个连续的Plan-Replier-Sender循环
@@ -327,7 +346,7 @@ class HeartFChatting:
self._current_cycle.timers = cycle_timers
# 防止循环过快消耗资源
- await self._handle_cycle_delay(action_taken, loop_cycle_start_time, self.log_prefix)
+ await _handle_cycle_delay(action_taken, loop_cycle_start_time, self.log_prefix)
# 完成当前循环并保存历史
self._current_cycle.complete_cycle()
@@ -715,24 +734,6 @@ class HeartFChatting:
if not self._shutting_down:
logger.debug(f"{log_prefix} 该次决策耗时: {'; '.join(timer_strings)}")
- async def _handle_cycle_delay(self, action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str):
- """处理循环延迟"""
- cycle_duration = time.monotonic() - cycle_start_time
-
- try:
- sleep_duration = 0.0
- if not action_taken_this_cycle and cycle_duration < 1:
- sleep_duration = 1 - cycle_duration
- elif cycle_duration < 0.2:
- sleep_duration = 0.2
-
- if sleep_duration > 0:
- await asyncio.sleep(sleep_duration)
-
- except asyncio.CancelledError:
- logger.info(f"{log_prefix} Sleep interrupted, loop likely cancelling.")
- raise
-
async def _get_submind_thinking(self, cycle_timers: dict) -> str:
"""
获取子思维的思考结果
diff --git a/src/plugins/heartFC_chat/heartFC_sender.py b/src/plugins/heartFC_chat/heartFC_sender.py
index 9e65edcfb..a41036679 100644
--- a/src/plugins/heartFC_chat/heartFC_sender.py
+++ b/src/plugins/heartFC_chat/heartFC_sender.py
@@ -12,6 +12,22 @@ from src.plugins.chat.utils import calculate_typing_time
logger = get_logger("sender")
+async def send_message(message: MessageSending) -> None:
+ """合并后的消息发送函数，包含WS发送和日志记录"""
+ message_preview = truncate_message(message.processed_plain_text)
+
+ try:
+ # 直接调用API发送消息
+ await send_message(message)
+ logger.success(f"发送消息 '{message_preview}' 成功")
+
+ except Exception as e:
+ logger.error(f"发送消息 '{message_preview}' 失败: {str(e)}")
+ if not message.message_info.platform:
+ raise ValueError(f"未找到平台：{message.message_info.platform} 的url配置，请检查配置文件") from e
+ raise e # 重新抛出其他异常
+
+
class HeartFCSender:
"""管理消息的注册、即时处理、发送和存储，并跟踪思考状态。"""
@@ -21,21 +37,6 @@ class HeartFCSender:
self.thinking_messages: Dict[str, Dict[str, MessageThinking]] = {}
self._thinking_lock = asyncio.Lock() # 保护 thinking_messages 的锁
- async def send_message(self, message: MessageSending) -> None:
- """合并后的消息发送函数，包含WS发送和日志记录"""
- message_preview = truncate_message(message.processed_plain_text)
-
- try:
- # 直接调用API发送消息
- await global_api.send_message(message)
- logger.success(f"发送消息 '{message_preview}' 成功")
-
- except Exception as e:
- logger.error(f"发送消息 '{message_preview}' 失败: {str(e)}")
- if not message.message_info.platform:
- raise ValueError(f"未找到平台：{message.message_info.platform} 的url配置，请检查配置文件") from e
- raise e # 重新抛出其他异常
-
async def register_thinking(self, thinking_message: MessageThinking):
"""注册一个思考中的消息。"""
if not thinking_message.chat_stream or not thinking_message.message_info.message_id:
@@ -73,7 +74,7 @@ class HeartFCSender:
thinking_message = self.thinking_messages.get(chat_id, {}).get(message_id)
return thinking_message.thinking_start_time if thinking_message else None
- async def type_and_send_message(self, message: MessageSending, type=False):
+ async def type_and_send_message(self, message: MessageSending, typing=False):
"""
立即处理、发送并存储单个 MessageSending 消息。
调用此方法前，应先调用 register_thinking 注册对应的思考消息。
@@ -100,7 +101,7 @@ class HeartFCSender:
await message.process()
- if type:
+ if typing:
typing_time = calculate_typing_time(
input_string=message.processed_plain_text,
thinking_start_time=message.thinking_start_time,
@@ -108,7 +109,7 @@ class HeartFCSender:
)
await asyncio.sleep(typing_time)
- await self.send_message(message)
+ await send_message(message)
await self.storage.store_message(message, message.chat_stream)
except Exception as e:
@@ -136,7 +137,7 @@ class HeartFCSender:
await asyncio.sleep(0.5)
- await self.send_message(message) # 使用现有的发送方法
+ await send_message(message) # 使用现有的发送方法
await self.storage.store_message(message, message.chat_stream) # 使用现有的存储方法
except Exception as e:
diff --git a/src/plugins/heartFC_chat/heartflow_processor.py b/src/plugins/heartFC_chat/heartflow_processor.py
index f7f3819cf..5bd63b14a 100644
--- a/src/plugins/heartFC_chat/heartflow_processor.py
+++ b/src/plugins/heartFC_chat/heartflow_processor.py
@@ -12,11 +12,134 @@ from ..chat.chat_stream import chat_manager
from ..chat.message_buffer import message_buffer
from ..utils.timer_calculator import Timer
from src.plugins.person_info.relationship_manager import relationship_manager
-from typing import Optional, Tuple
+from typing import Optional, Tuple, Dict, Any
logger = get_logger("chat")
+async def _handle_error(error: Exception, context: str, message: Optional[MessageRecv] = None) -> None:
+ """统一的错误处理函数
+
+ Args:
+ error: 捕获到的异常
+ context: 错误发生的上下文描述
+ message: 可选的消息对象，用于记录相关消息内容
+ """
+ logger.error(f"{context}: {error}")
+ logger.error(traceback.format_exc())
+ if message and hasattr(message, "raw_message"):
+ logger.error(f"相关消息原始内容: {message.raw_message}")
+
+
+async def _process_relationship(message: MessageRecv) -> None:
+ """处理用户关系逻辑
+
+ Args:
+ message: 消息对象，包含用户信息
+ """
+ platform = message.message_info.platform
+ user_id = message.message_info.user_info.user_id
+ nickname = message.message_info.user_info.user_nickname
+ cardname = message.message_info.user_info.user_cardname or nickname
+
+ is_known = await relationship_manager.is_known_some_one(platform, user_id)
+
+ if not is_known:
+ logger.info(f"首次认识用户: {nickname}")
+ await relationship_manager.first_knowing_some_one(platform, user_id, nickname, cardname, "")
+ elif not await relationship_manager.is_qved_name(platform, user_id):
+ logger.info(f"给用户({nickname},{cardname})取名: {nickname}")
+ await relationship_manager.first_knowing_some_one(platform, user_id, nickname, cardname, "")
+
+
+async def _calculate_interest(message: MessageRecv) -> Tuple[float, bool]:
+ """计算消息的兴趣度
+
+ Args:
+ message: 待处理的消息对象
+
+ Returns:
+ Tuple[float, bool]: (兴趣度, 是否被提及)
+ """
+ is_mentioned, _ = is_mentioned_bot_in_message(message)
+ interested_rate = 0.0
+
+ with Timer("记忆激活"):
+ interested_rate = await HippocampusManager.get_instance().get_activate_from_text(
+ message.processed_plain_text,
+ fast_retrieval=True,
+ )
+ logger.trace(f"记忆激活率: {interested_rate:.2f}")
+
+ if is_mentioned:
+ interest_increase_on_mention = 1
+ interested_rate += interest_increase_on_mention
+
+ return interested_rate, is_mentioned
+
+
+def _get_message_type(message: MessageRecv) -> str:
+ """获取消息类型
+
+ Args:
+ message: 消息对象
+
+ Returns:
+ str: 消息类型
+ """
+ if message.message_segment.type != "seglist":
+ return message.message_segment.type
+
+ if (
+ isinstance(message.message_segment.data, list)
+ and all(isinstance(x, Seg) for x in message.message_segment.data)
+ and len(message.message_segment.data) == 1
+ ):
+ return message.message_segment.data[0].type
+
+ return "seglist"
+
+
+def _check_ban_words(text: str, chat, userinfo) -> bool:
+ """检查消息是否包含过滤词
+
+ Args:
+ text: 待检查的文本
+ chat: 聊天对象
+ userinfo: 用户信息
+
+ Returns:
+ bool: 是否包含过滤词
+ """
+ for word in global_config.ban_words:
+ if word in text:
+ chat_name = chat.group_info.group_name if chat.group_info else "私聊"
+ logger.info(f"[{chat_name}]{userinfo.user_nickname}:{text}")
+ logger.info(f"[过滤词识别]消息中含有{word}，filtered")
+ return True
+ return False
+
+
+def _check_ban_regex(text: str, chat, userinfo) -> bool:
+ """检查消息是否匹配过滤正则表达式
+
+ Args:
+ text: 待检查的文本
+ chat: 聊天对象
+ userinfo: 用户信息
+
+ Returns:
+ bool: 是否匹配过滤正则
+ """
+ for pattern in global_config.ban_msgs_regex:
+ if pattern.search(text):
+ chat_name = chat.group_info.group_name if chat.group_info else "私聊"
+ logger.info(f"[{chat_name}]{userinfo.user_nickname}:{text}")
+ logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
+ return True
+ return False
+
+
class HeartFCProcessor:
"""心流处理器，负责处理接收到的消息并计算兴趣度"""
@@ -24,86 +147,7 @@ class HeartFCProcessor:
"""初始化心流处理器，创建消息存储实例"""
self.storage = MessageStorage()
- async def _handle_error(self, error: Exception, context: str, message: Optional[MessageRecv] = None) -> None:
- """统一的错误处理函数
-
- Args:
- error: 捕获到的异常
- context: 错误发生的上下文描述
- message: 可选的消息对象，用于记录相关消息内容
- """
- logger.error(f"{context}: {error}")
- logger.error(traceback.format_exc())
- if message and hasattr(message, "raw_message"):
- logger.error(f"相关消息原始内容: {message.raw_message}")
-
- async def _process_relationship(self, message: MessageRecv) -> None:
- """处理用户关系逻辑
-
- Args:
- message: 消息对象，包含用户信息
- """
- platform = message.message_info.platform
- user_id = message.message_info.user_info.user_id
- nickname = message.message_info.user_info.user_nickname
- cardname = message.message_info.user_info.user_cardname or nickname
-
- is_known = await relationship_manager.is_known_some_one(platform, user_id)
-
- if not is_known:
- logger.info(f"首次认识用户: {nickname}")
- await relationship_manager.first_knowing_some_one(platform, user_id, nickname, cardname, "")
- elif not await relationship_manager.is_qved_name(platform, user_id):
- logger.info(f"给用户({nickname},{cardname})取名: {nickname}")
- await relationship_manager.first_knowing_some_one(platform, user_id, nickname, cardname, "")
-
- async def _calculate_interest(self, message: MessageRecv) -> Tuple[float, bool]:
- """计算消息的兴趣度
-
- Args:
- message: 待处理的消息对象
-
- Returns:
- Tuple[float, bool]: (兴趣度, 是否被提及)
- """
- is_mentioned, _ = is_mentioned_bot_in_message(message)
- interested_rate = 0.0
-
- with Timer("记忆激活"):
- interested_rate = await HippocampusManager.get_instance().get_activate_from_text(
- message.processed_plain_text,
- fast_retrieval=True,
- )
- logger.trace(f"记忆激活率: {interested_rate:.2f}")
-
- if is_mentioned:
- interest_increase_on_mention = 1
- interested_rate += interest_increase_on_mention
-
- return interested_rate, is_mentioned
-
- def _get_message_type(self, message: MessageRecv) -> str:
- """获取消息类型
-
- Args:
- message: 消息对象
-
- Returns:
- str: 消息类型
- """
- if message.message_segment.type != "seglist":
- return message.message_segment.type
-
- if (
- isinstance(message.message_segment.data, list)
- and all(isinstance(x, Seg) for x in message.message_segment.data)
- and len(message.message_segment.data) == 1
- ):
- return message.message_segment.data[0].type
-
- return "seglist"
-
- async def process_message(self, message_data: str) -> None:
+ async def process_message(self, message_data: Dict[str, Any]) -> None:
"""处理接收到的原始消息数据
主要流程:
@@ -138,7 +182,7 @@ class HeartFCProcessor:
await message.process()
# 3. 过滤检查
- if self._check_ban_words(message.processed_plain_text, chat, userinfo) or self._check_ban_regex(
+ if _check_ban_words(message.processed_plain_text, chat, userinfo) or _check_ban_regex(
message.raw_message, chat, userinfo
):
return
@@ -146,7 +190,7 @@ class HeartFCProcessor:
# 4. 缓冲检查
buffer_result = await message_buffer.query_buffer_result(message)
if not buffer_result:
- msg_type = self._get_message_type(message)
+ msg_type = _get_message_type(message)
type_messages = {
"text": f"触发缓冲，消息：{message.processed_plain_text}",
"image": "触发缓冲，表情包/图片等待中",
@@ -160,7 +204,7 @@ class HeartFCProcessor:
logger.trace(f"存储成功: {message.processed_plain_text}")
# 6. 兴趣度计算与更新
- interested_rate, is_mentioned = await self._calculate_interest(message)
+ interested_rate, is_mentioned = await _calculate_interest(message)
await subheartflow.interest_chatting.increase_interest(value=interested_rate)
subheartflow.interest_chatting.add_interest_dict(message, interested_rate, is_mentioned)
@@ -175,45 +219,7 @@ class HeartFCProcessor:
)
# 8. 关系处理
- await self._process_relationship(message)
+ await _process_relationship(message)
except Exception as e:
- await self._handle_error(e, "消息处理失败", message)
-
- def _check_ban_words(self, text: str, chat, userinfo) -> bool:
- """检查消息是否包含过滤词
-
- Args:
- text: 待检查的文本
- chat: 聊天对象
- userinfo: 用户信息
-
- Returns:
- bool: 是否包含过滤词
- """
- for word in global_config.ban_words:
- if word in text:
- chat_name = chat.group_info.group_name if chat.group_info else "私聊"
- logger.info(f"[{chat_name}]{userinfo.user_nickname}:{text}")
- logger.info(f"[过滤词识别]消息中含有{word}，filtered")
- return True
- return False
-
- def _check_ban_regex(self, text: str, chat, userinfo) -> bool:
- """检查消息是否匹配过滤正则表达式
-
- Args:
- text: 待检查的文本
- chat: 聊天对象
- userinfo: 用户信息
-
- Returns:
- bool: 是否匹配过滤正则
- """
- for pattern in global_config.ban_msgs_regex:
- if pattern.search(text):
- chat_name = chat.group_info.group_name if chat.group_info else "私聊"
- logger.info(f"[{chat_name}]{userinfo.user_nickname}:{text}")
- logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
- return True
- return False
+ await _handle_error(e, "消息处理失败", message)
diff --git a/src/plugins/heartFC_chat/heartflow_prompt_builder.py b/src/plugins/heartFC_chat/heartflow_prompt_builder.py
index 40819f013..9b83f2652 100644
--- a/src/plugins/heartFC_chat/heartflow_prompt_builder.py
+++ b/src/plugins/heartFC_chat/heartflow_prompt_builder.py
@@ -151,6 +151,96 @@ JSON 结构如下，包含三个字段 "action", "reasoning", "emoji_query":
Prompt("\n你有以下这些**知识**：\n{prompt_info}\n请你**记住上面的知识**，之后可能会用到。\n", "knowledge_prompt")
+async def _build_prompt_focus(
+ reason, current_mind_info, structured_info, chat_stream, sender_name
+) -> tuple[str, str]:
+ individuality = Individuality.get_instance()
+ prompt_personality = individuality.get_prompt(x_person=0, level=2)
+ # 日程构建
+ # schedule_prompt = f'''你现在正在做的事情是：{bot_schedule.get_current_num_task(num = 1,time_info = False)}'''
+
+ if chat_stream.group_info:
+ chat_in_group = True
+ else:
+ chat_in_group = False
+
+ message_list_before_now = get_raw_msg_before_timestamp_with_chat(
+ chat_id=chat_stream.stream_id,
+ timestamp=time.time(),
+ limit=global_config.observation_context_size,
+ )
+
+ chat_talking_prompt = await build_readable_messages(
+ message_list_before_now,
+ replace_bot_name=True,
+ merge_messages=False,
+ timestamp_mode="normal",
+ read_mark=0.0,
+ truncate=True,
+ )
+
+ # 中文高手(新加的好玩功能)
+ prompt_ger = ""
+ if random.random() < 0.04:
+ prompt_ger += "你喜欢用倒装句"
+ if random.random() < 0.02:
+ prompt_ger += "你喜欢用反问句"
+
+ reply_styles1 = [
+ ("给出日常且口语化的回复，平淡一些", 0.4), # 40%概率
+ ("给出非常简短的回复", 0.4), # 40%概率
+ ("给出缺失主语的回复，简短", 0.15), # 15%概率
+ ("给出带有语病的回复，朴实平淡", 0.05), # 5%概率
+ ]
+ reply_style1_chosen = random.choices(
+ [style[0] for style in reply_styles1], weights=[style[1] for style in reply_styles1], k=1
+ )[0]
+
+ reply_styles2 = [
+ ("不要回复的太有条理，可以有个性", 0.6), # 60%概率
+ ("不要回复的太有条理，可以复读", 0.15), # 15%概率
+ ("回复的认真一些", 0.2), # 20%概率
+ ("可以回复单个表情符号", 0.05), # 5%概率
+ ]
+ reply_style2_chosen = random.choices(
+ [style[0] for style in reply_styles2], weights=[style[1] for style in reply_styles2], k=1
+ )[0]
+
+ if structured_info:
+ structured_info_prompt = await global_prompt_manager.format_prompt(
+ "info_from_tools", structured_info=structured_info
+ )
+ else:
+ structured_info_prompt = ""
+
+ logger.debug("开始构建prompt")
+
+ prompt = await global_prompt_manager.format_prompt(
+ "heart_flow_prompt",
+ info_from_tools=structured_info_prompt,
+ chat_target=await global_prompt_manager.get_prompt_async("chat_target_group1")
+ if chat_in_group
+ else await global_prompt_manager.get_prompt_async("chat_target_private1"),
+ chat_talking_prompt=chat_talking_prompt,
+ bot_name=global_config.BOT_NICKNAME,
+ prompt_personality=prompt_personality,
+ chat_target_2=await global_prompt_manager.get_prompt_async("chat_target_group2")
+ if chat_in_group
+ else await global_prompt_manager.get_prompt_async("chat_target_private2"),
+ current_mind_info=current_mind_info,
+ reply_style2=reply_style2_chosen,
+ reply_style1=reply_style1_chosen,
+ reason=reason,
+ prompt_ger=prompt_ger,
+ moderation_prompt=await global_prompt_manager.get_prompt_async("moderation_prompt"),
+ sender_name=sender_name,
+ )
+
+ logger.debug(f"focus_chat_prompt: \n{prompt}")
+
+ return prompt
+
+
class PromptBuilder:
def __init__(self):
self.prompt_built = ""
@@ -170,7 +260,7 @@ class PromptBuilder:
return await self._build_prompt_normal(chat_stream, message_txt, sender_name)
elif build_mode == "focus":
- return await self._build_prompt_focus(
+ return await _build_prompt_focus(
reason,
current_mind_info,
structured_info,
@@ -179,95 +269,6 @@ class PromptBuilder:
)
return None
- async def _build_prompt_focus(
- self, reason, current_mind_info, structured_info, chat_stream, sender_name
- ) -> tuple[str, str]:
- individuality = Individuality.get_instance()
- prompt_personality = individuality.get_prompt(x_person=0, level=2)
- # 日程构建
- # schedule_prompt = f'''你现在正在做的事情是：{bot_schedule.get_current_num_task(num = 1,time_info = False)}'''
-
- if chat_stream.group_info:
- chat_in_group = True
- else:
- chat_in_group = False
-
- message_list_before_now = get_raw_msg_before_timestamp_with_chat(
- chat_id=chat_stream.stream_id,
- timestamp=time.time(),
- limit=global_config.observation_context_size,
- )
-
- chat_talking_prompt = await build_readable_messages(
- message_list_before_now,
- replace_bot_name=True,
- merge_messages=False,
- timestamp_mode="normal",
- read_mark=0.0,
- truncate=True,
- )
-
- # 中文高手(新加的好玩功能)
- prompt_ger = ""
- if random.random() < 0.04:
- prompt_ger += "你喜欢用倒装句"
- if random.random() < 0.02:
- prompt_ger += "你喜欢用反问句"
-
- reply_styles1 = [
- ("给出日常且口语化的回复，平淡一些", 0.4), # 40%概率
- ("给出非常简短的回复", 0.4), # 40%概率
- ("给出缺失主语的回复，简短", 0.15), # 15%概率
- ("给出带有语病的回复，朴实平淡", 0.05), # 5%概率
- ]
- reply_style1_chosen = random.choices(
- [style[0] for style in reply_styles1], weights=[style[1] for style in reply_styles1], k=1
- )[0]
-
- reply_styles2 = [
- ("不要回复的太有条理，可以有个性", 0.6), # 60%概率
- ("不要回复的太有条理，可以复读", 0.15), # 15%概率
- ("回复的认真一些", 0.2), # 20%概率
- ("可以回复单个表情符号", 0.05), # 5%概率
- ]
- reply_style2_chosen = random.choices(
- [style[0] for style in reply_styles2], weights=[style[1] for style in reply_styles2], k=1
- )[0]
-
- if structured_info:
- structured_info_prompt = await global_prompt_manager.format_prompt(
- "info_from_tools", structured_info=structured_info
- )
- else:
- structured_info_prompt = ""
-
- logger.debug("开始构建prompt")
-
- prompt = await global_prompt_manager.format_prompt(
- "heart_flow_prompt",
- info_from_tools=structured_info_prompt,
- chat_target=await global_prompt_manager.get_prompt_async("chat_target_group1")
- if chat_in_group
- else await global_prompt_manager.get_prompt_async("chat_target_private1"),
- chat_talking_prompt=chat_talking_prompt,
- bot_name=global_config.BOT_NICKNAME,
- prompt_personality=prompt_personality,
- chat_target_2=await global_prompt_manager.get_prompt_async("chat_target_group2")
- if chat_in_group
- else await global_prompt_manager.get_prompt_async("chat_target_private2"),
- current_mind_info=current_mind_info,
- reply_style2=reply_style2_chosen,
- reply_style1=reply_style1_chosen,
- reason=reason,
- prompt_ger=prompt_ger,
- moderation_prompt=await global_prompt_manager.get_prompt_async("moderation_prompt"),
- sender_name=sender_name,
- )
-
- logger.debug(f"focus_chat_prompt: \n{prompt}")
-
- return prompt
-
async def _build_prompt_normal(self, chat_stream, message_txt: str, sender_name: str = "某人") -> tuple[str, str]:
individuality = Individuality.get_instance()
prompt_personality = individuality.get_prompt(x_person=2, level=2)
diff --git a/src/plugins/knowledge/src/qa_manager.py b/src/plugins/knowledge/src/qa_manager.py
index a09879a17..11067d0e5 100644
--- a/src/plugins/knowledge/src/qa_manager.py
+++ b/src/plugins/knowledge/src/qa_manager.py
@@ -27,7 +27,7 @@ class QAManager:
self.kg_manager = kg_manager
self.llm_client_list = {
"embedding": llm_client_embedding,
- "filter": llm_client_filter,
+ "message_filter": llm_client_filter,
"qa": llm_client_qa,
}
diff --git a/src/plugins/respon_info_catcher/info_catcher.py b/src/plugins/respon_info_catcher/info_catcher.py
index 5cb67a16d..08be4a76b 100644
--- a/src/plugins/respon_info_catcher/info_catcher.py
+++ b/src/plugins/respon_info_catcher/info_catcher.py
@@ -185,32 +185,24 @@ class InfoCatcher:
try:
# 将消息对象转换为可序列化的字典喵~
- thinking_log_data = {
- "chat_id": self.chat_id,
- # "response_mode": self.response_mode, # 这个也删掉喵~
- "trigger_text": self.trigger_response_text,
- "response_text": self.response_text,
- "trigger_info": {
+ thinking_log_data = {"chat_id": self.chat_id, "trigger_text": self.trigger_response_text,
+ "response_text": self.response_text, "trigger_info": {
"time": self.trigger_response_time,
"message": self.message_to_dict(self.trigger_response_message),
- },
- "response_info": {
+ }, "response_info": {
"time": self.response_time,
"message": self.response_messages,
- },
- "timing_results": self.timing_results,
- "chat_history": self.message_list_to_dict(self.chat_history),
- "chat_history_in_thinking": self.message_list_to_dict(self.chat_history_in_thinking),
- "chat_history_after_response": self.message_list_to_dict(self.chat_history_after_response),
- }
+ }, "timing_results": self.timing_results, "chat_history": self.message_list_to_dict(self.chat_history),
+ "chat_history_in_thinking": self.message_list_to_dict(self.chat_history_in_thinking),
+ "chat_history_after_response": self.message_list_to_dict(
+ self.chat_history_after_response), "heartflow_data": self.heartflow_data,
+ "reasoning_data": self.reasoning_data}
# 根据不同的响应模式添加相应的数据喵~ # 现在直接都加上去好了喵~
# if self.response_mode == "heart_flow":
# thinking_log_data["mode_specific_data"] = self.heartflow_data
# elif self.response_mode == "reasoning":
# thinking_log_data["mode_specific_data"] = self.reasoning_data
- thinking_log_data["heartflow_data"] = self.heartflow_data
- thinking_log_data["reasoning_data"] = self.reasoning_data
# 将数据插入到 thinking_log 集合中喵~
db.thinking_log.insert_one(thinking_log_data)
diff --git a/src/plugins/schedule/schedule_generator.py b/src/plugins/schedule/schedule_generator.py
index 761fcb7dc..ee7bdee15 100644
--- a/src/plugins/schedule/schedule_generator.py
+++ b/src/plugins/schedule/schedule_generator.py
@@ -30,6 +30,7 @@ class ScheduleGenerator:
def __init__(self):
# 使用离线LLM模型
+ self.enable_output = None
self.llm_scheduler_all = LLMRequest(
model=global_config.llm_reasoning,
temperature=global_config.SCHEDULE_TEMPERATURE + 0.3,
diff --git a/src/plugins/utils/chat_message_builder.py b/src/plugins/utils/chat_message_builder.py
index a7eef4431..75fca69cf 100644
--- a/src/plugins/utils/chat_message_builder.py
+++ b/src/plugins/utils/chat_message_builder.py
@@ -123,7 +123,7 @@ def num_new_messages_since(chat_id: str, timestamp_start: float = 0.0, timestamp
return 0 # 起始时间大于等于结束时间，没有新消息
filter_query = {"chat_id": chat_id, "time": {"$gt": timestamp_start, "$lt": _timestamp_end}}
- return count_messages(filter=filter_query)
+ return count_messages(message_filter=filter_query)
def num_new_messages_since_with_users(
@@ -137,7 +137,7 @@ def num_new_messages_since_with_users(
"time": {"$gt": timestamp_start, "$lt": timestamp_end},
"user_id": {"$in": person_ids},
}
- return count_messages(filter=filter_query)
+ return count_messages(message_filter=filter_query)
async def _build_readable_messages_internal(
@@ -227,7 +227,7 @@ async def _build_readable_messages_internal(
replace_content = "......（太长了）"
truncated_content = content
- if limit > 0 and original_len > limit:
+ if 0 < limit < original_len:
truncated_content = f"{content[:limit]}{replace_content}"
message_details.append((timestamp, name, truncated_content))
diff --git a/src/plugins/willing/mode_custom.py b/src/plugins/willing/mode_custom.py
index c3a5c3078..4b2e8f3c3 100644
--- a/src/plugins/willing/mode_custom.py
+++ b/src/plugins/willing/mode_custom.py
@@ -2,5 +2,23 @@ from .willing_manager import BaseWillingManager
class CustomWillingManager(BaseWillingManager):
+ async def async_task_starter(self) -> None:
+ pass
+
+ async def before_generate_reply_handle(self, message_id: str):
+ pass
+
+ async def after_generate_reply_handle(self, message_id: str):
+ pass
+
+ async def not_reply_handle(self, message_id: str):
+ pass
+
+ async def get_reply_probability(self, message_id: str):
+ pass
+
+ async def bombing_buffer_message_handle(self, message_id: str):
+ pass
+
def __init__(self):
super().__init__()