Merge remote-tracking branch 'upstream/debug' into tc_refractor
This commit is contained in:
Rikki
@@ -1,3 +1,4 @@
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import re
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import time
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from random import random
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from loguru import logger
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@@ -31,10 +32,10 @@ class ChatBot:
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self._started = False
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self.mood_manager = MoodManager.get_instance() # 获取情绪管理器单例
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self.mood_manager.start_mood_update() # 启动情绪更新
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self.emoji_chance = 0.2 # 发送表情包的基础概率
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# self.message_streams = MessageStreamContainer()
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async def _ensure_started(self):
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"""确保所有任务已启动"""
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if not self._started:
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@@ -42,9 +43,9 @@ class ChatBot:
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async def handle_message(self, event: GroupMessageEvent, bot: Bot) -> None:
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"""处理收到的群消息"""
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self.bot = bot # 更新 bot 实例
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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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@@ -96,8 +97,17 @@ 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.processed_plain_text:
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logger.info(f"\033[1;32m[{groupinfo.group_name}]{userinfo.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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logger.info(
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f"[{groupinfo.group_name}]{userinfo.user_nickname}:{message.processed_plain_text}")
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logger.info(f"[过滤词识别]消息中含有{word}，filtered")
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return
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# 正则表达式过滤
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for pattern in global_config.ban_msgs_regex:
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if re.search(pattern, message.raw_message):
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logger.info(
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f"[{message.group_name}]{message.user_nickname}:{message.raw_message}")
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logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
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return
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current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(messageinfo.time))
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@@ -107,8 +117,9 @@ class ChatBot:
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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"对{message.processed_plain_text}"
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f"的激活度:{interested_rate}")
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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,chat, topic[0] if topic else None)
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@@ -124,7 +135,10 @@ class ChatBot:
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)
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current_willing = willing_manager.get_willing(chat_stream=chat)
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print(f"\033[1;32m[{current_time}][{chat.group_info.group_name}]{chat.user_info.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.info(
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f"[{current_time}][{chat.group_info.group_name}]{chat.user_info.user_nickname}:"
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f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]"
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)
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response = None
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@@ -159,13 +173,13 @@ class ChatBot:
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thinking_message = msg
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container.messages.remove(msg)
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break
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# 如果找不到思考消息，直接返回
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if not thinking_message:
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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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logger.warning("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(chat, think_id)
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message_set = MessageSet(chat, think_id)
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@@ -175,7 +189,7 @@ class ChatBot:
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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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@@ -193,19 +207,19 @@ class ChatBot:
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if not mark_head:
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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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bot_response_time = tinking_time_point
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if random() < global_config.emoji_chance:
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emoji_raw = await emoji_manager.get_emoji_for_text(response)
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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, description = emoji_raw
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emoji_cq = image_path_to_base64(emoji_path)
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@@ -226,8 +240,8 @@ class ChatBot:
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)
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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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@@ -240,9 +254,10 @@ class ChatBot:
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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(
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chat_stream=chat
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)
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# willing_manager.change_reply_willing_after_sent(
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# chat_stream=chat
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# )
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# 创建全局ChatBot实例
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chat_bot = ChatBot()
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chat_bot = ChatBot()
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