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pull/1228/head
UnCLAS-Prommer 2025-09-02 14:38:25 +08:00
parent 9ac6801f87
commit 0811cff8bf
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217
src/chat/frequency_control/frequency_control.py
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@ -13,7 +13,7 @@ logger = get_logger("frequency_control")
class FrequencyControl:
"""
频率控制类，可以根据最近时间段的发言数量和发言人数动态调整频率
特点：
- 发言频率调整：基于最近10分钟的数据，评估单位为"消息数/10分钟"
- 专注度调整：基于最近10分钟的数据，评估单位为"消息数/10分钟"
@ -23,10 +23,10 @@ class FrequencyControl:
- 数据充足性检查：当历史数据不足50条时，不更新基准值；当基准值为默认值时，不进行动态调整
- 基准值更新：直接使用新计算的周均值，无平滑更新
"""
def __init__(self, chat_id: str):
self.chat_id = chat_id
self.chat_stream: ChatStream = get_chat_manager().get_stream(self.chat_id)
self.chat_stream: ChatStream = get_chat_manager().get_stream(self.chat_id) # type: ignore
if not self.chat_stream:
raise ValueError(f"无法找到聊天流: {chat_id}")
self.log_prefix = f"[{get_chat_manager().get_stream_name(self.chat_id) or self.chat_id}]"
@ -36,43 +36,43 @@ class FrequencyControl:
# 专注度调整值
self.focus_value_adjust: float = 1.0
self.focus_value_external_adjust: float = 1.0
# 动态调整相关参数
self.last_update_time = time.time()
self.update_interval = 60 # 每60秒更新一次
# 历史数据缓存
self._message_count_cache = 0
self._user_count_cache = 0
self._last_cache_time = 0
self._cache_duration = 30 # 缓存30秒
# 调整参数
self.min_adjust = 0.3 # 最小调整值
self.max_adjust = 2.0 # 最大调整值
self.max_adjust = 2.0 # 最大调整值
# 动态基准值（将根据历史数据计算）
self.base_message_count = 5 # 默认基准消息数量，将被动态更新
self.base_user_count = 3 # 默认基准用户数量，将被动态更新
self.base_message_count = 5 # 默认基准消息数量，将被动态更新
self.base_user_count = 3 # 默认基准用户数量，将被动态更新
# 平滑因子
self.smoothing_factor = 0.3
# 历史数据相关参数
self._last_historical_update = 0
self._historical_update_interval = 600 # 每十分钟更新一次历史基准值
self._historical_days = 7 # 使用最近7天的数据计算基准值
# 按小时统计的历史基准值
self._hourly_baseline = {
'messages': {}, # {0-23: 平均消息数}
'users': {} # {0-23: 平均用户数}
"messages": {}, # {0-23: 平均消息数}
"users": {}, # {0-23: 平均用户数}
}
# 初始化24小时的默认基准值
for hour in range(24):
self._hourly_baseline['messages'][hour] = 0.0
self._hourly_baseline['users'][hour] = 0.0
self._hourly_baseline["messages"][hour] = 0.0
self._hourly_baseline["users"][hour] = 0.0
def _update_historical_baseline(self):
"""
@ -80,75 +80,79 @@ class FrequencyControl:
使用最近一周的数据，按小时统计平均消息数量和用户数量
"""
current_time = time.time()
# 检查是否需要更新历史基准值
if current_time - self._last_historical_update < self._historical_update_interval:
return
try:
# 计算一周前的时间戳
week_ago = current_time - (self._historical_days * 24 * 3600)
# 获取最近一周的消息数据
historical_messages = message_api.get_messages_by_time_in_chat(
chat_id=self.chat_stream.stream_id,
start_time=week_ago,
end_time=current_time,
filter_mai=True,
filter_command=True
filter_command=True,
)
if historical_messages and len(historical_messages) >= 50:
# 按小时统计消息数和用户数
hourly_stats = {hour: {'messages': [], 'users': set()} for hour in range(24)}
hourly_stats = {hour: {"messages": [], "users": set()} for hour in range(24)}
for msg in historical_messages:
# 获取消息的小时（UTC时间）
msg_time = time.localtime(msg.time)
msg_hour = msg_time.tm_hour
# 统计消息数
hourly_stats[msg_hour]['messages'].append(msg)
hourly_stats[msg_hour]["messages"].append(msg)
# 统计用户数
if msg.user_info and msg.user_info.user_id:
hourly_stats[msg_hour]['users'].add(msg.user_info.user_id)
hourly_stats[msg_hour]["users"].add(msg.user_info.user_id)
# 计算每个小时的平均值（基于一周的数据）
for hour in range(24):
# 计算该小时的平均消息数（一周内该小时的总消息数 / 7天）
total_messages = len(hourly_stats[hour]['messages'])
total_users = len(hourly_stats[hour]['users'])
total_messages = len(hourly_stats[hour]["messages"])
total_users = len(hourly_stats[hour]["users"])
# 只计算有消息的时段，没有消息的时段设为0
if total_messages > 0:
avg_messages = total_messages / self._historical_days
avg_users = total_users / self._historical_days
self._hourly_baseline['messages'][hour] = avg_messages
self._hourly_baseline['users'][hour] = avg_users
self._hourly_baseline["messages"][hour] = avg_messages
self._hourly_baseline["users"][hour] = avg_users
else:
# 没有消息的时段设为0，表示该时段不活跃
self._hourly_baseline['messages'][hour] = 0.0
self._hourly_baseline['users'][hour] = 0.0
self._hourly_baseline["messages"][hour] = 0.0
self._hourly_baseline["users"][hour] = 0.0
# 更新整体基准值（用于兼容性）- 基于原始数据计算，不受max(1.0)限制影响
overall_avg_messages = sum(len(hourly_stats[hour]['messages']) for hour in range(24)) / (24 * self._historical_days)
overall_avg_users = sum(len(hourly_stats[hour]['users']) for hour in range(24)) / (24 * self._historical_days)
overall_avg_messages = sum(len(hourly_stats[hour]["messages"]) for hour in range(24)) / (
24 * self._historical_days
)
overall_avg_users = sum(len(hourly_stats[hour]["users"]) for hour in range(24)) / (
24 * self._historical_days
)
self.base_message_count = overall_avg_messages
self.base_user_count = overall_avg_users
logger.info(
f"{self.log_prefix} 历史基准值更新完成: "
f"整体平均消息数={overall_avg_messages:.2f}, 整体平均用户数={overall_avg_users:.2f}"
)
# 记录几个关键时段的基准值
key_hours = [8, 12, 18, 22] # 早、中、晚、夜
for hour in key_hours:
# 计算该小时平均每10分钟的消息数和用户数
hourly_10min_messages = self._hourly_baseline['messages'][hour] / 6 # 1小时 = 6个10分钟
hourly_10min_users = self._hourly_baseline['users'][hour] / 6
hourly_10min_messages = self._hourly_baseline["messages"][hour] / 6 # 1小时 = 6个10分钟
hourly_10min_users = self._hourly_baseline["users"][hour] / 6
logger.info(
f"{self.log_prefix} {hour}时基准值: "
f"消息数={self._hourly_baseline['messages'][hour]:.2f}/小时 "
@ -156,37 +160,34 @@ class FrequencyControl:
f"用户数={self._hourly_baseline['users'][hour]:.2f}/小时 "
f"({hourly_10min_users:.2f}/10分钟)"
)
elif historical_messages and len(historical_messages) < 50:
# 历史数据不足50条，不更新基准值
logger.info(f"{self.log_prefix} 历史数据不足50条({len(historical_messages)}条)，不更新基准值")
else:
# 如果没有历史数据，不更新基准值
logger.info(f"{self.log_prefix} 无历史数据，不更新基准值")
except Exception as e:
logger.error(f"{self.log_prefix} 更新历史基准值时出错: {e}")
# 出错时保持原有基准值不变
self._last_historical_update = current_time
def _get_current_hour_baseline(self) -> tuple[float, float]:
"""
获取当前小时的基准值
Returns:
tuple: (基准消息数, 基准用户数)
"""
current_hour = time.localtime().tm_hour
return (
self._hourly_baseline['messages'][current_hour],
self._hourly_baseline['users'][current_hour]
)
return (self._hourly_baseline["messages"][current_hour], self._hourly_baseline["users"][current_hour])
def get_dynamic_talk_frequency_adjust(self) -> float:
"""
获取纯动态调整值（不包含配置文件基础值）
Returns:
float: 动态调整值
"""
@ -196,7 +197,7 @@ class FrequencyControl:
def get_dynamic_focus_value_adjust(self) -> float:
"""
获取纯动态调整值（不包含配置文件基础值）
Returns:
float: 动态调整值
"""
@ -209,14 +210,14 @@ class FrequencyControl:
适合人少话多的时候：人少但消息多，提高回复频率
"""
current_time = time.time()
# 检查是否需要更新
if current_time - self.last_update_time < self.update_interval:
return
# 先更新历史基准值
self._update_historical_baseline()
try:
# 获取最近10分钟的数据（发言频率更敏感）
recent_messages = message_api.get_messages_by_time_in_chat(
@ -224,9 +225,9 @@ class FrequencyControl:
start_time=current_time - 600, # 10分钟前
end_time=current_time,
filter_mai=True,
filter_command=True
filter_command=True,
)
# 计算消息数量和用户数量
message_count = len(recent_messages)
user_ids = set()
@ -234,14 +235,14 @@ class FrequencyControl:
if msg.user_info and msg.user_info.user_id:
user_ids.add(msg.user_info.user_id)
user_count = len(user_ids)
# 获取当前小时的基准值
current_hour_base_messages, current_hour_base_users = self._get_current_hour_baseline()
# 计算当前小时平均每10分钟的基准值
current_hour_10min_messages = current_hour_base_messages / 6 # 1小时 = 6个10分钟
current_hour_10min_users = current_hour_base_users / 6
# 发言频率调整逻辑：根据活跃度双向调整
# 检查是否有足够的数据进行分析
if user_count > 0 and message_count >= 2: # 至少需要2条消息才能进行有意义的分析
@ -250,8 +251,10 @@ class FrequencyControl:
# 计算人均消息数（10分钟窗口）
messages_per_user = message_count / user_count
# 使用当前小时每10分钟的基准人均消息数
base_messages_per_user = current_hour_10min_messages / current_hour_10min_users if current_hour_10min_users > 0 else 1.0
base_messages_per_user = (
current_hour_10min_messages / current_hour_10min_users if current_hour_10min_users > 0 else 1.0
)
# 双向调整逻辑
if messages_per_user > base_messages_per_user * 1.2:
# 活跃度很高：提高回复频率
@ -268,19 +271,18 @@ class FrequencyControl:
else:
# 数据不足：不调整
target_talk_adjust = 1.0
# 限制调整范围
target_talk_adjust = max(self.min_adjust, min(self.max_adjust, target_talk_adjust))
# 记录调整前的值
old_adjust = self.talk_frequency_adjust
# 平滑调整
self.talk_frequency_adjust = (
self.talk_frequency_adjust * (1 - self.smoothing_factor) +
target_talk_adjust * self.smoothing_factor
self.talk_frequency_adjust * (1 - self.smoothing_factor) + target_talk_adjust * self.smoothing_factor
)
# 判断调整方向
if target_talk_adjust > 1.0:
adjust_direction = "提高"
@ -291,7 +293,7 @@ class FrequencyControl:
adjust_direction = "不调整(该时段无活跃度)"
else:
adjust_direction = "保持"
# 计算实际变化方向
actual_change = ""
if self.talk_frequency_adjust > old_adjust:
@ -300,14 +302,14 @@ class FrequencyControl:
actual_change = f"{old_adjust:.2f}x → {self.talk_frequency_adjust:.2f}x"
else:
actual_change = f"无变化: {self.talk_frequency_adjust:.2f}x"
logger.info(
f"{self.log_prefix} 发言频率调整: "
f"{user_count}名用户正在参与聊天，当前消息数: {message_count}|"
f"群基准: {current_hour_10min_messages:.2f}消息/{current_hour_10min_users:.2f}用户|"
f"[{adjust_direction}]{actual_change}"
)
except Exception as e:
logger.error(f"{self.log_prefix} 更新发言频率调整值时出错: {e}")
@ -317,11 +319,11 @@ class FrequencyControl:
适合人多话多的时候：人多且消息多，提高专注度（LLM消耗更多，但回复更精准）
"""
current_time = time.time()
# 检查是否需要更新
if current_time - self.last_update_time < self.update_interval:
return
try:
# 获取最近10分钟的数据（与发言频率保持一致）
recent_messages = message_api.get_messages_by_time_in_chat(
@ -329,9 +331,9 @@ class FrequencyControl:
start_time=current_time - 600, # 10分钟前
end_time=current_time,
filter_mai=True,
filter_command=True
filter_command=True,
)
# 计算消息数量和用户数量
message_count = len(recent_messages)
user_ids = set()
@ -339,14 +341,14 @@ class FrequencyControl:
if msg.user_info and msg.user_info.user_id:
user_ids.add(msg.user_info.user_id)
user_count = len(user_ids)
# 获取当前小时的基准值
current_hour_base_messages, current_hour_base_users = self._get_current_hour_baseline()
# 计算当前小时平均每10分钟的基准值
current_hour_10min_messages = current_hour_base_messages / 6 # 1小时 = 6个10分钟
current_hour_10min_users = current_hour_base_users / 6
# 专注度调整逻辑：根据活跃度双向调整
# 检查是否有足够的数据进行分析
if user_count > 0 and current_hour_10min_users > 0 and message_count >= 2:
@ -355,8 +357,10 @@ class FrequencyControl:
# 计算用户活跃度比率（基于10分钟数据）
user_ratio = user_count / current_hour_10min_users
# 计算消息活跃度比率（基于10分钟数据）
message_ratio = message_count / current_hour_10min_messages if current_hour_10min_messages > 0 else 1.0
message_ratio = (
message_count / current_hour_10min_messages if current_hour_10min_messages > 0 else 1.0
)
# 双向调整逻辑
if user_ratio > 1.3 and message_ratio > 1.3:
# 活跃度很高：提高专注度，消耗更多LLM资源但回复更精准
@ -376,23 +380,22 @@ class FrequencyControl:
else:
# 数据不足：不调整
target_focus_adjust = 1.0
# 限制调整范围
target_focus_adjust = max(self.min_adjust, min(self.max_adjust, target_focus_adjust))
# 记录调整前的值
old_focus_adjust = self.focus_value_adjust
# 平滑调整
self.focus_value_adjust = (
self.focus_value_adjust * (1 - self.smoothing_factor) +
target_focus_adjust * self.smoothing_factor
self.focus_value_adjust * (1 - self.smoothing_factor) + target_focus_adjust * self.smoothing_factor
)
# 计算当前小时平均每10分钟的基准值
current_hour_10min_messages = current_hour_base_messages / 6 # 1小时 = 6个10分钟
current_hour_10min_users = current_hour_base_users / 6
# 判断调整方向
if target_focus_adjust > 1.0:
adjust_direction = "提高"
@ -403,7 +406,7 @@ class FrequencyControl:
adjust_direction = "不调整(该时段无活跃度)"
else:
adjust_direction = "保持"
# 计算实际变化方向
actual_change = ""
if self.focus_value_adjust > old_focus_adjust:
@ -412,23 +415,30 @@ class FrequencyControl:
actual_change = f"{old_focus_adjust:.2f}x → {self.focus_value_adjust:.2f}x"
else:
actual_change = f"无变化: {self.focus_value_adjust:.2f}x"
logger.info(
f"{self.log_prefix} 专注度调整: "
f"{user_count}名用户正在参与聊天，当前消息数: {message_count}|"
f"群基准: {current_hour_10min_messages:.2f}消息/{current_hour_10min_users:.2f}用户|"
f"[{adjust_direction}]{actual_change}"
)
except Exception as e:
logger.error(f"{self.log_prefix} 更新专注度调整值时出错: {e}")
def get_final_talk_frequency(self) -> float:
return get_config_base_talk_frequency(self.chat_stream.stream_id) * self.get_dynamic_talk_frequency_adjust() * self.talk_frequency_external_adjust
return (
get_config_base_talk_frequency(self.chat_stream.stream_id)
* self.get_dynamic_talk_frequency_adjust()
* self.talk_frequency_external_adjust
)
def get_final_focus_value(self) -> float:
return get_config_base_focus_value(self.chat_stream.stream_id) * self.get_dynamic_focus_value_adjust() * self.focus_value_external_adjust
return (
get_config_base_focus_value(self.chat_stream.stream_id)
* self.get_dynamic_focus_value_adjust()
* self.focus_value_external_adjust
)
def set_adjustment_parameters(
self,
@ -439,11 +449,11 @@ class FrequencyControl:
smoothing_factor: Optional[float] = None,
update_interval: Optional[int] = None,
historical_update_interval: Optional[int] = None,
historical_days: Optional[int] = None
historical_days: Optional[int] = None,
):
"""
设置调整参数
Args:
min_adjust: 最小调整值
max_adjust: 最大调整值
@ -474,17 +484,17 @@ class FrequencyControlManager:
"""
频率控制管理器，管理多个聊天流的频率控制实例
"""
def __init__(self):
self.frequency_control_dict: Dict[str, FrequencyControl] = {}
def get_or_create_frequency_control(self, chat_id: str) -> FrequencyControl:
"""
获取或创建指定聊天流的频率控制实例
Args:
chat_id: 聊天流ID
Returns:
FrequencyControl: 频率控制实例
"""
@ -492,9 +502,6 @@ class FrequencyControlManager:
self.frequency_control_dict[chat_id] = FrequencyControl(chat_id)
return self.frequency_control_dict[chat_id]
# 创建全局实例
frequency_control_manager = FrequencyControlManager()

4
src/chat/replyer/default_generator.py
View File

@ -374,8 +374,6 @@ class DefaultReplyer:
running_memories = await self.memory_activator.activate_memory_with_chat_history(
target_message=target, chat_history=chat_history
)
running_memories = None
if not running_memories:
return ""
@ -680,7 +678,7 @@ class DefaultReplyer:
async def build_prompt_reply_context(
self,
reply_message: DatabaseMessages,
reply_message: Optional[DatabaseMessages] = None,
extra_info: str = "",
reply_reason: str = "",
available_actions: Optional[Dict[str, ActionInfo]] = None,