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feat：修改log,优化关系构建逻辑，节省token，

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This commit is contained in:
SengokuCola
2025-07-08 02:04:31 +08:00
parent 723870bcde
commit f17f5cf46c
10 changed files with 303 additions and 322 deletions
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192
src/plugins/built_in/core_actions/no_reply.py
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@@ -103,6 +103,8 @@ class NoReplyAction(BaseAction):
logger.info(f"{self.log_prefix} 选择不回复(第{count}次)，开始摸鱼，原因: {reason}")
# 进入等待状态
while True:
current_time = time.time()
elapsed_time = current_time - start_time
@@ -141,19 +143,9 @@ class NoReplyAction(BaseAction):
# 判定条件：累计3条消息或等待超过5秒且有新消息
time_since_last_judge = current_time - last_judge_time
should_judge = (
new_message_count >= 3 # 累计3条消息
or (new_message_count > 0 and time_since_last_judge >= 15.0) # 等待超过5秒且有新消息
)
should_judge, trigger_reason = self._should_trigger_judge(new_message_count, time_since_last_judge)
if should_judge and time_since_last_judge >= min_judge_interval:
# 判断触发原因
trigger_reason = ""
if new_message_count >= 3:
trigger_reason = f"累计{new_message_count}条消息"
elif time_since_last_judge >= 10.0:
trigger_reason = f"等待{time_since_last_judge:.1f}秒且有新消息"
logger.info(f"{self.log_prefix} 触发判定({trigger_reason})，进行智能判断...")
# 获取最近的消息内容用于判断
@@ -166,7 +158,10 @@ class NoReplyAction(BaseAction):
if recent_messages:
# 使用message_api构建可读的消息字符串
messages_text = message_api.build_readable_messages(
messages=recent_messages, timestamp_mode="normal_no_YMD", truncate=False, show_actions=False
messages=recent_messages,
timestamp_mode="normal_no_YMD",
truncate=False,
show_actions=False,
)
# 获取身份信息
@@ -189,81 +184,13 @@ class NoReplyAction(BaseAction):
history_block += "\n"
# 检查过去10分钟的发言频率
frequency_block = ""
should_skip_llm_judge = False # 是否跳过LLM判断
try:
# 获取过去10分钟的所有消息
past_10min_time = current_time - 600 # 10分钟前
all_messages_10min = message_api.get_messages_by_time_in_chat(
chat_id=self.chat_id,
start_time=past_10min_time,
end_time=current_time,
)
# 手动过滤bot自己的消息
bot_message_count = 0
if all_messages_10min:
user_id = global_config.bot.qq_account
for message in all_messages_10min:
# 检查消息发送者是否是bot
sender_id = message.get("user_id", "")
if sender_id == user_id:
bot_message_count += 1
talk_frequency_threshold = global_config.chat.get_current_talk_frequency(self.chat_id) * 10
if bot_message_count > talk_frequency_threshold:
over_count = bot_message_count - talk_frequency_threshold
# 根据超过的数量设置不同的提示词和跳过概率
skip_probability = 0
if over_count <= 3:
frequency_block = "你感觉稍微有些累，回复的有点多了。\n"
elif over_count <= 5:
frequency_block = "你今天说话比较多，感觉有点疲惫，想要稍微休息一下。\n"
elif over_count <= 8:
frequency_block = "你发现自己说话太多了，感觉很累，想要安静一会儿，除非有重要的事情否则不想回复。\n"
skip_probability = self._skip_probability
else:
frequency_block = "你感觉非常累，想要安静一会儿。\n"
skip_probability = 1
# 根据配置和概率决定是否跳过LLM判断
if self._skip_judge_when_tired and random.random() < skip_probability:
should_skip_llm_judge = True
logger.info(
f"{self.log_prefix} 发言过多(超过{over_count}条)，随机决定跳过此次LLM判断(概率{skip_probability * 100:.0f}%)"
)
logger.info(
f"{self.log_prefix} 过去10分钟发言{bot_message_count}条，超过阈值{talk_frequency_threshold}，添加疲惫提示"
)
else:
# 回复次数少时的正向提示
under_count = talk_frequency_threshold - bot_message_count
if under_count >= talk_frequency_threshold * 0.8: # 回复很少（少于20%）
frequency_block = "你感觉精力充沛，状态很好，积极参与聊天。\n"
elif under_count >= talk_frequency_threshold * 0.5: # 回复较少（少于50%）
frequency_block = "你感觉状态不错。\n"
else: # 刚好达到阈值
frequency_block = ""
logger.info(
f"{self.log_prefix} 过去10分钟发言{bot_message_count}条，未超过阈值{talk_frequency_threshold}，添加正向提示"
)
except Exception as e:
logger.warning(f"{self.log_prefix} 检查发言频率时出错: {e}")
frequency_block = ""
frequency_block, should_skip_llm_judge = self._get_fatigue_status(current_time)
# 如果决定跳过LLM判断，直接更新时间并继续等待
if should_skip_llm_judge:
logger.info(f"{self.log_prefix} 疲劳,继续等待。")
last_judge_time = time.time() # 更新判断时间，避免立即重新判断
start_time = current_time # 更新消息检查的起始时间，以避免重复判断
continue # 跳过本次LLM判断，继续循环等待
# 构建判断上下文
@@ -379,6 +306,105 @@ class NoReplyAction(BaseAction):
)
return False, f"不回复动作执行失败: {e}"
def _should_trigger_judge(self, new_message_count: int, time_since_last_judge: float) -> Tuple[bool, str]:
"""判断是否应该触发智能判断，并返回触发原因。
Args:
new_message_count: 新消息的数量。
time_since_last_judge: 距离上次判断的时间。
Returns:
一个元组 (should_judge, reason)。
- should_judge: 一个布尔值，指示是否应该触发判断。
- reason: 触发判断的原因字符串。
"""
# 判定条件：累计3条消息或等待超过15秒且有新消息
should_judge_flag = new_message_count >= 3 or (new_message_count > 0 and time_since_last_judge >= 15.0)
if not should_judge_flag:
return False, ""
# 判断触发原因
if new_message_count >= 3:
return True, f"累计{new_message_count}条消息"
elif new_message_count > 0 and time_since_last_judge >= 15.0:
return True, f"等待{time_since_last_judge:.1f}秒且有新消息"
return False, ""
def _get_fatigue_status(self, current_time: float) -> Tuple[str, bool]:
"""
根据最近的发言频率生成疲劳提示，并决定是否跳过判断。
Args:
current_time: 当前时间戳。
Returns:
一个元组 (frequency_block, should_skip_judge)。
- frequency_block: 疲劳度相关的提示字符串。
- should_skip_judge: 是否应该跳过LLM判断的布尔值。
"""
try:
# 获取过去10分钟的所有消息
past_10min_time = current_time - 600 # 10分钟前
all_messages_10min = message_api.get_messages_by_time_in_chat(
chat_id=self.chat_id,
start_time=past_10min_time,
end_time=current_time,
)
# 手动过滤bot自己的消息
bot_message_count = 0
if all_messages_10min:
user_id = global_config.bot.qq_account
for message in all_messages_10min:
sender_id = message.get("user_id", "")
if sender_id == user_id:
bot_message_count += 1
talk_frequency_threshold = global_config.chat.get_current_talk_frequency(self.chat_id) * 10
if bot_message_count > talk_frequency_threshold:
over_count = bot_message_count - talk_frequency_threshold
skip_probability = 0
frequency_block = ""
if over_count <= 3:
frequency_block = "你感觉稍微有些累，回复的有点多了。\n"
elif over_count <= 5:
frequency_block = "你今天说话比较多，感觉有点疲惫，想要稍微休息一下。\n"
elif over_count <= 8:
frequency_block = "你发现自己说话太多了，感觉很累，想要安静一会儿，除非有重要的事情否则不想回复。\n"
skip_probability = self._skip_probability
else:
frequency_block = "你感觉非常累，想要安静一会儿。\n"
skip_probability = 1
should_skip_judge = self._skip_judge_when_tired and random.random() < skip_probability
if should_skip_judge:
logger.info(
f"{self.log_prefix} 发言过多(超过{over_count}条)，随机决定跳过此次LLM判断(概率{skip_probability * 100:.0f}%)"
)
logger.info(f"{self.log_prefix} 过去10分钟发言{bot_message_count}条，超过阈值{talk_frequency_threshold}，添加疲惫提示")
return frequency_block, should_skip_judge
else:
# 回复次数少时的正向提示
under_count = talk_frequency_threshold - bot_message_count
frequency_block = ""
if under_count >= talk_frequency_threshold * 0.8:
frequency_block = "你感觉精力充沛，状态很好，积极参与聊天。\n"
elif under_count >= talk_frequency_threshold * 0.5:
frequency_block = "你感觉状态不错。\n"
logger.info(f"{self.log_prefix} 过去10分钟发言{bot_message_count}条，未超过阈值{talk_frequency_threshold}，添加正向提示")
return frequency_block, False
except Exception as e:
logger.warning(f"{self.log_prefix} 检查发言频率时出错: {e}")
return "", False
def _check_no_activity_and_exit_focus(self, current_time: float) -> bool:
"""检查过去10分钟是否完全没有发言，决定是否退出专注模式