270 lines
12 KiB
Python
270 lines
12 KiB
Python
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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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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get_person_id_list,
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)
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from src.plugins.utils.prompt_builder import global_prompt_manager
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from typing import Optional
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import difflib
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from src.plugins.chat.message import MessageRecv # 添加 MessageRecv 导入
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from src.heart_flow.observation import Observation
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from src.common.logger_manager import get_logger
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from src.heart_flow.utils_chat import get_chat_type_and_target_info
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logger = get_logger(__name__)
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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_id)
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self.chat_id = chat_id
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# --- Initialize attributes (defaults) ---
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self.is_group_chat: bool = False
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self.chat_target_info: Optional[dict] = None
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# --- End Initialization ---
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# --- Other attributes initialized in __init__ ---
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self.talking_message = []
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self.talking_message_str = ""
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self.talking_message_str_truncate = ""
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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.person_list = []
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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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self.is_group_chat, self.chat_target_info = await get_chat_type_and_target_info(self.chat_id)
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logger.debug(f"初始化observation: self.is_group_chat: {self.is_group_chat}")
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logger.debug(f"初始化observation: self.chat_target_info: {self.chat_target_info}")
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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
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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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def serch_message_by_text(self, text: str) -> Optional[MessageRecv]:
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"""
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根据回复的纯文本
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1. 在talking_message中查找最新的，最匹配的消息
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2. 如果找到，则返回消息
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"""
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msg_list = []
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find_msg = None
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reverse_talking_message = list(reversed(self.talking_message))
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for message in reverse_talking_message:
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if message["processed_plain_text"] == text:
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find_msg = message
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logger.debug(f"找到的锚定消息：find_msg: {find_msg}")
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break
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else:
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similarity = difflib.SequenceMatcher(None, text, message["processed_plain_text"]).ratio()
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msg_list.append({"message": message, "similarity": similarity})
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logger.debug(f"对锚定消息检查：message: {message['processed_plain_text']},similarity: {similarity}")
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if not find_msg:
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if msg_list:
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msg_list.sort(key=lambda x: x["similarity"], reverse=True)
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if msg_list[0]["similarity"] >= 0.5: # 只返回相似度大于等于0.5的消息
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find_msg = msg_list[0]["message"]
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else:
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logger.debug("没有找到锚定消息,相似度低")
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return None
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else:
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logger.debug("没有找到锚定消息，没有消息捕获")
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return None
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# logger.debug(f"找到的锚定消息：find_msg: {find_msg}")
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group_info = find_msg.get("chat_info", {}).get("group_info")
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user_info = find_msg.get("chat_info", {}).get("user_info")
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content_format = ""
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accept_format = ""
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template_items = {}
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template_name = {}
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template_default = True
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format_info = {"content_format": content_format, "accept_format": accept_format}
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template_info = {
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"template_items": template_items,
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}
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message_info = {
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"platform": find_msg.get("platform"),
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"message_id": find_msg.get("message_id"),
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"time": find_msg.get("time"),
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"group_info": group_info,
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"user_info": user_info,
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"format_info": find_msg.get("format_info"),
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"template_info": find_msg.get("template_info"),
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"additional_config": find_msg.get("additional_config"),
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"format_info": format_info,
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"template_info": template_info,
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}
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message_dict = {
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"message_info": message_info,
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"raw_message": find_msg.get("processed_plain_text"),
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"detailed_plain_text": find_msg.get("processed_plain_text"),
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"processed_plain_text": find_msg.get("processed_plain_text"),
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}
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find_rec_msg = MessageRecv(message_dict)
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logger.debug(f"锚定消息处理后：find_rec_msg: {find_rec_msg}")
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return find_rec_msg
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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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# --- Build prompt using template ---
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prompt = None # Initialize prompt as None
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try:
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# 构建 Prompt - 根据 is_group_chat 选择模板
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if self.is_group_chat:
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prompt_template_name = "chat_summary_group_prompt"
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prompt = await global_prompt_manager.format_prompt(
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prompt_template_name, chat_logs=oldest_messages_str
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)
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else:
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# For private chat, add chat_target to the prompt variables
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prompt_template_name = "chat_summary_private_prompt"
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# Determine the target name for the prompt
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chat_target_name = "对方" # Default fallback
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if self.chat_target_info:
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# Prioritize person_name, then nickname
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chat_target_name = (
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self.chat_target_info.get("person_name")
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or self.chat_target_info.get("user_nickname")
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or chat_target_name
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)
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# Format the private chat prompt
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prompt = await global_prompt_manager.format_prompt(
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prompt_template_name,
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# Assuming the private prompt template uses {chat_target}
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chat_target=chat_target_name,
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chat_logs=oldest_messages_str,
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)
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except Exception as e:
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logger.error(f"构建总结 Prompt 失败 for chat {self.chat_id}: {e}")
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# prompt remains None
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summary = "没有主题的闲聊" # 默认值
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if prompt: # Check if prompt was built successfully
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try:
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summary_result, _, _ = await self.llm_summary.generate_response(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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else:
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logger.warning(f"因 Prompt 构建失败，跳过 LLM 总结 for chat {self.chat_id}")
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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="lite",
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read_mark=last_obs_time_mark,
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)
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self.talking_message_str_truncate = 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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truncate=True,
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)
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self.person_list = await get_person_id_list(self.talking_message)
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# print(f"self.11111person_list: {self.person_list}")
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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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