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fix：让麦麦回复功能正常工作，输出一堆调戏信息

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SengokuCola
2025-03-29 19:13:32 +08:00
parent 6dbee3dc56
commit 2e0d358d93
11 changed files with 360 additions and 319 deletions
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406
src/plugins/chat/bot.py
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@@ -58,10 +58,7 @@ class ChatBot:
5. 更新关系
6. 更新情绪
"""
# message_json = json.loads(message_data)
# 哦我嘞个json
# 进入maimbot
message = MessageRecv(message_data)
groupinfo = message.message_info.group_info
userinfo = message.message_info.user_info
@@ -73,64 +70,62 @@ class ChatBot:
chat = await chat_manager.get_or_create_stream(
platform=messageinfo.platform,
user_info=userinfo,
group_info=groupinfo, # 我嘞个gourp_info
group_info=groupinfo,
)
message.update_chat_stream(chat)
# 创建 心流 观察
if global_config.enable_think_flow:
await outer_world.check_and_add_new_observe()
subheartflow_manager.create_subheartflow(chat.stream_id)
await outer_world.check_and_add_new_observe()
subheartflow_manager.create_subheartflow(chat.stream_id)
timer1 = time.time()
await relationship_manager.update_relationship(
chat_stream=chat,
)
await relationship_manager.update_relationship_value(chat_stream=chat, relationship_value=0)
timer2 = time.time()
logger.info(f"1关系更新时间: {timer2 - timer1}秒")
timer1 = time.time()
await message.process()
timer2 = time.time()
logger.info(f"2消息处理时间: {timer2 - timer1}秒")
# 过滤词
for word in global_config.ban_words:
if word in message.processed_plain_text:
logger.info(
f"[{chat.group_info.group_name if chat.group_info else '私聊'}]"
f"{userinfo.user_nickname}:{message.processed_plain_text}"
)
logger.info(f"[过滤词识别]消息中含有{word}，filtered")
return
# 正则表达式过滤
for pattern in global_config.ban_msgs_regex:
if re.search(pattern, message.raw_message):
logger.info(
f"[{chat.group_info.group_name if chat.group_info else '私聊'}]"
f"{userinfo.user_nickname}:{message.raw_message}"
)
logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
return
# 过滤词/正则表达式过滤
if (
self._check_ban_words(message.processed_plain_text, chat, userinfo)
or self._check_ban_regex(message.raw_message, chat, userinfo)
):
return
current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(messageinfo.time))
# 根据话题计算激活度
topic = ""
await self.storage.store_message(message, chat, topic[0] if topic else None)
await self.storage.store_message(message, chat)
timer1 = time.time()
interested_rate = 0
interested_rate = await HippocampusManager.get_instance().get_activate_from_text(
message.processed_plain_text, fast_retrieval=True
)
timer2 = time.time()
logger.info(f"3记忆激活时间: {timer2 - timer1}秒")
is_mentioned = is_mentioned_bot_in_message(message)
if global_config.enable_think_flow:
current_willing_old = willing_manager.get_willing(chat_stream=chat)
current_willing_new = (subheartflow_manager.get_subheartflow(chat.stream_id).current_state.willing - 5) / 4
print(f"旧回复意愿：{current_willing_old}，新回复意愿：{current_willing_new}")
print(f"4旧回复意愿：{current_willing_old}，新回复意愿：{current_willing_new}")
current_willing = (current_willing_old + current_willing_new) / 2
else:
current_willing = willing_manager.get_willing(chat_stream=chat)
willing_manager.set_willing(chat.stream_id, current_willing)
timer1 = time.time()
reply_probability = await willing_manager.change_reply_willing_received(
chat_stream=chat,
is_mentioned_bot=is_mentioned,
@@ -139,161 +134,246 @@ class ChatBot:
interested_rate=interested_rate,
sender_id=str(message.message_info.user_info.user_id),
)
timer2 = time.time()
logger.info(f"4计算意愿激活时间: {timer2 - timer1}秒")
#神秘的消息流数据结构处理
if chat.group_info:
if chat.group_info.group_name:
mes_name_dict = chat.group_info.group_name
mes_name = mes_name_dict.get('group_name', '无名群聊')
else:
mes_name = '群聊'
else:
mes_name = '私聊'
# print(f"mes_name: {mes_name}")
logger.info(
f"[{current_time}][{chat.group_info.group_name if chat.group_info else '私聊'}]"
f"[{current_time}][{mes_name}]"
f"{chat.user_info.user_nickname}:"
f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]"
)
response = None
if message.message_info.additional_config:
if "maimcore_reply_probability_gain" in message.message_info.additional_config.keys():
reply_probability += message.message_info.additional_config["maimcore_reply_probability_gain"]
# 开始组织语言
if random() < reply_probability:
bot_user_info = UserInfo(
user_id=global_config.BOT_QQ,
user_nickname=global_config.BOT_NICKNAME,
platform=messageinfo.platform,
)
# 开始思考的时间点
thinking_time_point = round(time.time(), 2)
# logger.debug(f"开始思考的时间点: {thinking_time_point}")
think_id = "mt" + str(thinking_time_point)
thinking_message = MessageThinking(
message_id=think_id,
chat_stream=chat,
bot_user_info=bot_user_info,
reply=message,
thinking_start_time=thinking_time_point,
)
message_manager.add_message(thinking_message)
willing_manager.change_reply_willing_sent(chat)
response, raw_content = await self.gpt.generate_response(message)
else:
# 决定不回复时，也更新回复意愿
willing_manager.change_reply_willing_not_sent(chat)
# print(f"response: {response}")
if response:
stream_id = message.chat_stream.stream_id
chat_talking_prompt = ""
if stream_id:
chat_talking_prompt = get_recent_group_detailed_plain_text(
stream_id, limit=global_config.MAX_CONTEXT_SIZE, combine=True
)
if subheartflow_manager.get_subheartflow(stream_id):
await subheartflow_manager.get_subheartflow(stream_id).do_after_reply(response, chat_talking_prompt)
else:
await subheartflow_manager.create_subheartflow(stream_id).do_after_reply(response, chat_talking_prompt)
# print(f"有response: {response}")
container = message_manager.get_container(chat.stream_id)
thinking_message = None
# 找到message,删除
# print(f"开始找思考消息")
for msg in container.messages:
if isinstance(msg, MessageThinking) and msg.message_info.message_id == think_id:
# print(f"找到思考消息: {msg}")
thinking_message = msg
container.messages.remove(msg)
break
# 如果找不到思考消息，直接返回
if not thinking_message:
logger.warning("未找到对应的思考消息，可能已超时被移除")
timer1 = time.time()
response_set, thinking_id = await self._generate_response_from_message(message, chat, userinfo, messageinfo)
timer2 = time.time()
logger.info(f"5生成回复时间: {timer2 - timer1}秒")
if not response_set:
logger.info("为什么生成回复失败？")
return
# 发送消息
timer1 = time.time()
await self._send_response_messages(message, chat, response_set, thinking_id)
timer2 = time.time()
logger.info(f"7发送消息时间: {timer2 - timer1}秒")
# 处理表情包
timer1 = time.time()
await self._handle_emoji(message, chat, response_set)
timer2 = time.time()
logger.info(f"8处理表情包时间: {timer2 - timer1}秒")
timer1 = time.time()
await self._update_using_response(message, chat, response_set)
timer2 = time.time()
logger.info(f"6更新htfl时间: {timer2 - timer1}秒")
# 更新情绪和关系
# await self._update_emotion_and_relationship(message, chat, response_set)
# 记录开始思考的时间，避免从思考到回复的时间太久
thinking_start_time = thinking_message.thinking_start_time
message_set = MessageSet(chat, think_id)
# 计算打字时间，1是为了模拟打字，2是避免多条回复乱序
# accu_typing_time = 0
async def _generate_response_from_message(self, message, chat, userinfo, messageinfo):
"""生成回复内容
Args:
message: 接收到的消息
chat: 聊天流对象
userinfo: 用户信息对象
messageinfo: 消息信息对象
Returns:
tuple: (response, raw_content) 回复内容和原始内容
"""
bot_user_info = UserInfo(
user_id=global_config.BOT_QQ,
user_nickname=global_config.BOT_NICKNAME,
platform=messageinfo.platform,
)
thinking_time_point = round(time.time(), 2)
thinking_id = "mt" + str(thinking_time_point)
thinking_message = MessageThinking(
message_id=thinking_id,
chat_stream=chat,
bot_user_info=bot_user_info,
reply=message,
thinking_start_time=thinking_time_point,
)
mark_head = False
for msg in response:
# print(f"\033[1;32m[回复内容]\033[0m {msg}")
# 通过时间改变时间戳
# typing_time = calculate_typing_time(msg)
# logger.debug(f"typing_time: {typing_time}")
# accu_typing_time += typing_time
# timepoint = thinking_time_point + accu_typing_time
message_segment = Seg(type="text", data=msg)
# logger.debug(f"message_segment: {message_segment}")
message_manager.add_message(thinking_message)
willing_manager.change_reply_willing_sent(chat)
response_set = await self.gpt.generate_response(message)
return response_set, thinking_id
async def _update_using_response(self, message, chat, response_set):
# 更新心流状态
stream_id = message.chat_stream.stream_id
chat_talking_prompt = ""
if stream_id:
chat_talking_prompt = get_recent_group_detailed_plain_text(
stream_id, limit=global_config.MAX_CONTEXT_SIZE, combine=True
)
if subheartflow_manager.get_subheartflow(stream_id):
await subheartflow_manager.get_subheartflow(stream_id).do_after_reply(response_set, chat_talking_prompt)
else:
await subheartflow_manager.create_subheartflow(stream_id).do_after_reply(response_set, chat_talking_prompt)
async def _send_response_messages(self, message, chat, response_set, thinking_id):
container = message_manager.get_container(chat.stream_id)
thinking_message = None
logger.info(f"开始发送消息准备")
for msg in container.messages:
if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
thinking_message = msg
container.messages.remove(msg)
break
if not thinking_message:
logger.warning("未找到对应的思考消息，可能已超时被移除")
return
logger.info(f"开始发送消息")
thinking_start_time = thinking_message.thinking_start_time
message_set = MessageSet(chat, thinking_id)
mark_head = False
for msg in response_set:
message_segment = Seg(type="text", data=msg)
bot_message = MessageSending(
message_id=thinking_id,
chat_stream=chat,
bot_user_info=UserInfo(
user_id=global_config.BOT_QQ,
user_nickname=global_config.BOT_NICKNAME,
platform=message.message_info.platform,
),
sender_info=message.message_info.user_info,
message_segment=message_segment,
reply=message,
is_head=not mark_head,
is_emoji=False,
thinking_start_time=thinking_start_time,
)
if not mark_head:
mark_head = True
message_set.add_message(bot_message)
logger.info(f"开始添加发送消息")
message_manager.add_message(message_set)
async def _handle_emoji(self, message, chat, response):
"""处理表情包
Args:
message: 接收到的消息
chat: 聊天流对象
response: 生成的回复
"""
if random() < global_config.emoji_chance:
emoji_raw = await emoji_manager.get_emoji_for_text(response)
if emoji_raw:
emoji_path, description = emoji_raw
emoji_cq = image_path_to_base64(emoji_path)
thinking_time_point = round(message.message_info.time, 2)
bot_response_time = thinking_time_point + (1 if random() < 0.5 else -1)
message_segment = Seg(type="emoji", data=emoji_cq)
bot_message = MessageSending(
message_id=think_id,
message_id="mt" + str(thinking_time_point),
chat_stream=chat,
bot_user_info=bot_user_info,
sender_info=userinfo,
bot_user_info=UserInfo(
user_id=global_config.BOT_QQ,
user_nickname=global_config.BOT_NICKNAME,
platform=message.message_info.platform,
),
sender_info=message.message_info.user_info,
message_segment=message_segment,
reply=message,
is_head=not mark_head,
is_emoji=False,
thinking_start_time=thinking_start_time,
is_head=False,
is_emoji=True,
)
if not mark_head:
mark_head = True
message_set.add_message(bot_message)
if len(str(bot_message)) < 1000:
logger.debug(f"bot_message: {bot_message}")
logger.debug(f"添加消息到message_set: {bot_message}")
else:
logger.debug(f"bot_message: {str(bot_message)[:1000]}...{str(bot_message)[-10:]}")
logger.debug(f"添加消息到message_set: {str(bot_message)[:1000]}...{str(bot_message)[-10:]}")
# message_set 可以直接加入 message_manager
# print(f"\033[1;32m[回复]\033[0m 将回复载入发送容器")
message_manager.add_message(bot_message)
logger.debug("添加message_set到message_manager")
async def _update_emotion_and_relationship(self, message, chat, response, raw_content):
"""更新情绪和关系
Args:
message: 接收到的消息
chat: 聊天流对象
response: 生成的回复
raw_content: 原始内容
"""
stance, emotion = await self.gpt._get_emotion_tags(raw_content, message.processed_plain_text)
logger.debug(f"为 '{response}' 立场为：{stance} 获取到的情感标签为：{emotion}")
await relationship_manager.calculate_update_relationship_value(
chat_stream=chat, label=emotion, stance=stance
)
self.mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor)
message_manager.add_message(message_set)
bot_response_time = thinking_time_point
if random() < global_config.emoji_chance:
emoji_raw = await emoji_manager.get_emoji_for_text(response)
# 检查是否 <没有找到> emoji
if emoji_raw != None:
emoji_path, description = emoji_raw
emoji_cq = image_path_to_base64(emoji_path)
if random() < 0.5:
bot_response_time = thinking_time_point - 1
else:
bot_response_time = bot_response_time + 1
message_segment = Seg(type="emoji", data=emoji_cq)
bot_message = MessageSending(
message_id=think_id,
chat_stream=chat,
bot_user_info=bot_user_info,
sender_info=userinfo,
message_segment=message_segment,
reply=message,
is_head=False,
is_emoji=True,
)
message_manager.add_message(bot_message)
# 获取立场和情感标签，更新关系值
stance, emotion = await self.gpt._get_emotion_tags(raw_content, message.processed_plain_text)
logger.debug(f"为 '{response}' 立场为：{stance} 获取到的情感标签为：{emotion}")
await relationship_manager.calculate_update_relationship_value(
chat_stream=chat, label=emotion, stance=stance
)
# 使用情绪管理器更新情绪
self.mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor)
# willing_manager.change_reply_willing_after_sent(
# chat_stream=chat
# )
def _check_ban_words(self, text: str, chat, userinfo) -> bool:
"""检查消息中是否包含过滤词
Args:
text: 要检查的文本
chat: 聊天流对象
userinfo: 用户信息对象
Returns:
bool: 如果包含过滤词返回True，否则返回False
"""
for word in global_config.ban_words:
if word in text:
logger.info(
f"[{chat.group_info.group_name if chat.group_info else '私聊'}]"
f"{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: 要检查的文本
chat: 聊天流对象
userinfo: 用户信息对象
Returns:
bool: 如果匹配过滤正则返回True，否则返回False
"""
for pattern in global_config.ban_msgs_regex:
if re.search(pattern, text):
logger.info(
f"[{chat.group_info.group_name if chat.group_info else '私聊'}]"
f"{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
# 创建全局ChatBot实例
chat_bot = ChatBot()