157 lines
6.5 KiB
Python
157 lines
6.5 KiB
Python
# 定义了来自外部世界的信息
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# 外部世界可以是某个聊天 不同平台的聊天 也可以是任意媒体
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from datetime import datetime
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from src.plugins.models.utils_model import LLMRequest
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from src.config.config import global_config
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from src.common.logger import get_module_logger
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import traceback
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from src.plugins.utils.chat_message_builder import (
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get_raw_msg_before_timestamp_with_chat,
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build_readable_messages,
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get_raw_msg_by_timestamp_with_chat,
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num_new_messages_since,
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)
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logger = get_module_logger("observation")
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# 所有观察的基类
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class Observation:
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def __init__(self, observe_type, observe_id):
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self.observe_info = ""
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self.observe_type = observe_type
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self.observe_id = observe_id
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self.last_observe_time = datetime.now().timestamp() # 初始化为当前时间
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async def observe(self):
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pass
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# 聊天观察
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class ChattingObservation(Observation):
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def __init__(self, chat_id):
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super().__init__("chat", chat_id)
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self.chat_id = chat_id
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self.talking_message = []
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self.talking_message_str = ""
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self.name = global_config.BOT_NICKNAME
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self.nick_name = global_config.BOT_ALIAS_NAMES
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self.max_now_obs_len = global_config.observation_context_size
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self.overlap_len = global_config.compressed_length
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self.mid_memorys = []
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self.max_mid_memory_len = global_config.compress_length_limit
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self.mid_memory_info = ""
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self.llm_summary = LLMRequest(
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model=global_config.llm_observation, temperature=0.7, max_tokens=300, request_type="chat_observation"
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)
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async def initialize(self):
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initial_messages = get_raw_msg_before_timestamp_with_chat(self.chat_id, self.last_observe_time, 10)
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self.talking_message = initial_messages # 将这些消息设为初始上下文
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self.talking_message_str = await build_readable_messages(self.talking_message)
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# 进行一次观察 返回观察结果observe_info
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def get_observe_info(self, ids=None):
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if ids:
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mid_memory_str = ""
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for id in ids:
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print(f"id：{id}")
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try:
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for mid_memory in self.mid_memorys:
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if mid_memory["id"] == id:
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mid_memory_by_id = mid_memory
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msg_str = ""
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for msg in mid_memory_by_id["messages"]:
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msg_str += f"{msg['detailed_plain_text']}"
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# time_diff = int((datetime.now().timestamp() - mid_memory_by_id["created_at"]) / 60)
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# mid_memory_str += f"距离现在{time_diff}分钟前：\n{msg_str}\n"
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mid_memory_str += f"{msg_str}\n"
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except Exception as e:
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logger.error(f"获取mid_memory_id失败: {e}")
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traceback.print_exc()
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return self.talking_message_str
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return mid_memory_str + "现在群里正在聊：\n" + self.talking_message_str
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else:
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return self.talking_message_str
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async def observe(self):
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# 自上一次观察的新消息
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new_messages_list = get_raw_msg_by_timestamp_with_chat(
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chat_id=self.chat_id,
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timestamp_start=self.last_observe_time,
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timestamp_end=datetime.now().timestamp(),
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limit=self.max_now_obs_len,
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limit_mode="latest",
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)
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last_obs_time_mark = self.last_observe_time
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if new_messages_list:
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self.last_observe_time = new_messages_list[-1]["time"]
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self.talking_message.extend(new_messages_list)
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if len(self.talking_message) > self.max_now_obs_len:
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# 计算需要移除的消息数量，保留最新的 max_now_obs_len 条
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messages_to_remove_count = len(self.talking_message) - self.max_now_obs_len
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oldest_messages = self.talking_message[:messages_to_remove_count]
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self.talking_message = self.talking_message[messages_to_remove_count:] # 保留后半部分，即最新的
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oldest_messages_str = await build_readable_messages(
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messages=oldest_messages, timestamp_mode="normal", read_mark=0
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)
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# 调用 LLM 总结主题
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prompt = (
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f"请总结以下聊天记录的主题：\n{oldest_messages_str}\n用一句话概括包括人物事件和主要信息，不要分点："
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)
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summary = "没有主题的闲聊" # 默认值
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try:
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summary_result, _ = await self.llm_summary.generate_response_async(prompt)
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if summary_result: # 确保结果不为空
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summary = summary_result
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except Exception as e:
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logger.error(f"总结主题失败 for chat {self.chat_id}: {e}")
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# 保留默认总结 "没有主题的闲聊"
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mid_memory = {
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"id": str(int(datetime.now().timestamp())),
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"theme": summary,
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"messages": oldest_messages, # 存储原始消息对象
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"readable_messages": oldest_messages_str,
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# "timestamps": oldest_timestamps,
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"chat_id": self.chat_id,
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"created_at": datetime.now().timestamp(),
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}
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self.mid_memorys.append(mid_memory)
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if len(self.mid_memorys) > self.max_mid_memory_len:
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self.mid_memorys.pop(0) # 移除最旧的
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mid_memory_str = "之前聊天的内容概述是：\n"
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for mid_memory_item in self.mid_memorys: # 重命名循环变量以示区分
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time_diff = int((datetime.now().timestamp() - mid_memory_item["created_at"]) / 60)
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mid_memory_str += (
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f"距离现在{time_diff}分钟前(聊天记录id:{mid_memory_item['id']})：{mid_memory_item['theme']}\n"
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)
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self.mid_memory_info = mid_memory_str
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self.talking_message_str = await build_readable_messages(
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messages=self.talking_message,
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timestamp_mode="normal",
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read_mark=last_obs_time_mark,
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)
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logger.trace(
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f"Chat {self.chat_id} - 压缩早期记忆：{self.mid_memory_info}\n现在聊天内容：{self.talking_message_str}"
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)
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async def has_new_messages_since(self, timestamp: float) -> bool:
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"""检查指定时间戳之后是否有新消息"""
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count = num_new_messages_since(chat_id=self.chat_id, timestamp_start=timestamp)
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return count > 0
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