mirror of https://github.com/Mai-with-u/MaiBot.git
refactor: logger in src\plugins\chat\bot.py
AL76
parent
288dbb68b5
commit
5746afaa2a
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@ -53,8 +53,8 @@ class ChatBot:
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group_info = await bot.get_group_info(group_id=event.group_id)
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sender_info = await bot.get_group_member_info(group_id=event.group_id, user_id=event.user_id, no_cache=True)
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await relationship_manager.update_relationship(user_id = event.user_id, data = sender_info)
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await relationship_manager.update_relationship_value(user_id = event.user_id, relationship_value = 0.5)
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await relationship_manager.update_relationship(user_id=event.user_id, data=sender_info)
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await relationship_manager.update_relationship_value(user_id=event.user_id, relationship_value=0.5)
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message = Message(
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group_id=event.group_id,
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@ -70,19 +70,19 @@ class ChatBot:
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# 过滤词
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for word in global_config.ban_words:
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if word in message.detailed_plain_text:
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logger.info(f"\033[1;32m[{message.group_name}]{message.user_nickname}:\033[0m {message.processed_plain_text}")
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logger.info(
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f"\033[1;32m[{message.group_name}]{message.user_nickname}:\033[0m {message.processed_plain_text}")
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logger.info(f"\033[1;32m[过滤词识别]\033[0m 消息中含有{word}，filtered")
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return
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current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(message.time))
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# topic=await topic_identifier.identify_topic_llm(message.processed_plain_text)
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topic = ''
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interested_rate = 0
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interested_rate = await hippocampus.memory_activate_value(message.processed_plain_text)/100
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print(f"\033[1;32m[记忆激活]\033[0m 对{message.processed_plain_text}的激活度:---------------------------------------{interested_rate}\n")
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interested_rate = await hippocampus.memory_activate_value(message.processed_plain_text) / 100
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logger.debug(f"\033[1;32m[记忆激活]\033[0m 对{message.processed_plain_text}"
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"的激活度:---------------------------------------{interested_rate}\n")
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# logger.info(f"\033[1;32m[主题识别]\033[0m 使用{global_config.topic_extract}主题: {topic}")
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await self.storage.store_message(message, topic[0] if topic else None)
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@ -99,23 +99,23 @@ class ChatBot:
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)
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current_willing = willing_manager.get_willing(event.group_id)
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print(f"\033[1;32m[{current_time}][{message.group_name}]{message.user_nickname}:\033[0m {message.processed_plain_text}\033[1;36m[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]\033[0m")
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logger.debug(
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f"\033[1;32m[{current_time}][{message.group_name}]{message.user_nickname}:\033[0m "
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"{message.processed_plain_text}\033[1;36m[回复意愿:{current_willing:.2f}][概率:{reply_probability * "
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"100:.1f}%]\033[0m")
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response = ""
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if random() < reply_probability:
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tinking_time_point = round(time.time(), 2)
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think_id = 'mt' + str(tinking_time_point)
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thinking_message = Message_Thinking(message=message,message_id=think_id)
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thinking_message = Message_Thinking(message=message, message_id=think_id)
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message_manager.add_message(thinking_message)
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willing_manager.change_reply_willing_sent(thinking_message.group_id)
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response,raw_content = await self.gpt.generate_response(message)
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response, raw_content = await self.gpt.generate_response(message)
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if response:
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container = message_manager.get_container(event.group_id)
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@ -133,17 +133,18 @@ class ChatBot:
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print(f"\033[1;33m[警告]\033[0m 未找到对应的思考消息，可能已超时被移除")
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return
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#记录开始思考的时间，避免从思考到回复的时间太久
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# 记录开始思考的时间，避免从思考到回复的时间太久
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thinking_start_time = thinking_message.thinking_start_time
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message_set = MessageSet(event.group_id, global_config.BOT_QQ, think_id) # 发送消息的id和产生发送消息的message_thinking是一致的
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#计算打字时间，1是为了模拟打字，2是避免多条回复乱序
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message_set = MessageSet(event.group_id, global_config.BOT_QQ,
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think_id) # 发送消息的id和产生发送消息的message_thinking是一致的
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# 计算打字时间，1是为了模拟打字，2是避免多条回复乱序
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accu_typing_time = 0
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# print(f"\033[1;32m[开始回复]\033[0m 开始将回复1载入发送容器")
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mark_head = False
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for msg in response:
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# print(f"\033[1;32m[回复内容]\033[0m {msg}")
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#通过时间改变时间戳
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# 通过时间改变时间戳
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typing_time = calculate_typing_time(msg)
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accu_typing_time += typing_time
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timepoint = tinking_time_point + accu_typing_time
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@ -157,8 +158,8 @@ class ChatBot:
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processed_plain_text=msg,
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user_nickname=global_config.BOT_NICKNAME,
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group_name=message.group_name,
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time=timepoint, #记录了回复生成的时间
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thinking_start_time=thinking_start_time, #记录了思考开始的时间
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time=timepoint, # 记录了回复生成的时间
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thinking_start_time=thinking_start_time, # 记录了思考开始的时间
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reply_message_id=message.message_id
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)
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await bot_message.initialize()
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@ -167,7 +168,7 @@ class ChatBot:
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mark_head = True
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message_set.add_message(bot_message)
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#message_set 可以直接加入 message_manager
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# message_set 可以直接加入 message_manager
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# print(f"\033[1;32m[回复]\033[0m 将回复载入发送容器")
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message_manager.add_message(message_set)
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@ -178,7 +179,7 @@ class ChatBot:
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# 检查是否 <没有找到> emoji
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if emoji_raw != None:
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emoji_path,discription = emoji_raw
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emoji_path, discription = emoji_raw
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emoji_cq = CQCode.create_emoji_cq(emoji_path)
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@ -206,8 +207,8 @@ class ChatBot:
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await bot_message.initialize()
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message_manager.add_message(bot_message)
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emotion = await self.gpt._get_emotion_tags(raw_content)
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print(f"为 '{response}' 获取到的情感标签为：{emotion}")
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valuedict={
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logger.debug(f"为 '{response}' 获取到的情感标签为：{emotion}")
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valuedict = {
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'happy': 0.5,
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'angry': -1,
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'sad': -0.5,
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@ -216,11 +217,13 @@ class ChatBot:
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'fearful': -0.7,
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'neutral': 0.1
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}
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await relationship_manager.update_relationship_value(message.user_id, relationship_value=valuedict[emotion[0]])
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await relationship_manager.update_relationship_value(message.user_id,
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relationship_value=valuedict[emotion[0]])
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# 使用情绪管理器更新情绪
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self.mood_manager.update_mood_from_emotion(emotion[0], global_config.mood_intensity_factor)
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# willing_manager.change_reply_willing_after_sent(event.group_id)
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# 创建全局ChatBot实例
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chat_bot = ChatBot()
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