mirror of https://github.com/Mai-with-u/MaiBot.git
355 lines
16 KiB
Python
355 lines
16 KiB
Python
import time
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import asyncio
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import random
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import traceback
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from typing import TYPE_CHECKING, Optional
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from src.common.logger_manager import get_logger
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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.plugins.chat.chat_stream import chat_manager, ChatStream
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from src.individuality.individuality import Individuality
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from src.plugins.utils.chat_message_builder import build_readable_messages
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from maim_message import UserInfo
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from ..chat_observer import ChatObserver
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from ..message_sender import DirectMessageSender
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# 导入富文本回溯，用于更好的错误展示
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from rich.traceback import install
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# 使用TYPE_CHECKING避免循环导入
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if TYPE_CHECKING:
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from ..conversation import Conversation
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install(extra_lines=3)
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# 获取当前模块的日志记录器
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logger = get_logger("idle_conversation_starter")
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class IdleConversationStarter:
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"""长时间无对话主动发起对话的组件
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该组件会在一段时间没有对话后，自动生成一条消息发送给用户，以保持对话的活跃度。
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时间阈值会在配置的最小和最大值之间随机选择，每次发送消息后都会重置。
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"""
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def __init__(self, stream_id: str, private_name: str):
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"""初始化空闲对话启动器
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Args:
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stream_id: 聊天流ID
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private_name: 私聊用户名称
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"""
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self.stream_id: str = stream_id
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self.private_name: str = private_name
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self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
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self.message_sender = DirectMessageSender(private_name)
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# 添加异步锁，保护对共享变量的访问
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self._lock: asyncio.Lock = asyncio.Lock()
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# LLM请求对象，用于生成主动对话内容
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self.llm = LLMRequest(
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model=global_config.llm_normal, temperature=0.8, max_tokens=500, request_type="idle_conversation_starter"
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)
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# 个性化信息
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self.personality_info: str = Individuality.get_instance().get_prompt(x_person=2, level=3)
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# 计算实际触发阈值（在min和max之间随机）
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self.actual_idle_threshold: int = random.randint(global_config.min_idle_time, global_config.max_idle_time)
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# 工作状态
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self.last_message_time: float = time.time()
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self._running: bool = False
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self._task: Optional[asyncio.Task] = None
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def start(self) -> None:
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"""启动空闲对话检测
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如果功能被禁用或已经在运行，则不会启动。
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"""
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# 如果功能被禁用，则不启动
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if not global_config.enable_idle_conversation:
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logger.info(f"[私聊][{self.private_name}]主动发起对话功能已禁用")
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return
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if self._running:
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logger.debug(f"[私聊][{self.private_name}]主动发起对话功能已在运行中")
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return
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self._running = True
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self._task = asyncio.create_task(self._check_idle_loop())
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logger.info(f"[私聊][{self.private_name}]启动空闲对话检测，阈值设置为{self.actual_idle_threshold}秒")
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def stop(self) -> None:
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"""停止空闲对话检测
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取消当前运行的任务并重置状态。
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"""
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if not self._running:
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return
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self._running = False
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if self._task:
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self._task.cancel()
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self._task = None
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logger.info(f"[私聊][{self.private_name}]停止空闲对话检测")
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async def update_last_message_time(self, message_time: Optional[float] = None) -> None:
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"""更新最后一条消息的时间
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Args:
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message_time: 消息时间戳，如果为None则使用当前时间
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"""
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async with self._lock:
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self.last_message_time = message_time or time.time()
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# 重新随机化下一次触发的时间阈值
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self.actual_idle_threshold = random.randint(global_config.min_idle_time, global_config.max_idle_time)
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logger.debug(
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f"[私聊][{self.private_name}]更新最后消息时间: {self.last_message_time}，新阈值: {self.actual_idle_threshold}秒"
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)
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def reload_config(self) -> None:
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"""重新加载配置
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记录当前配置参数，用于日志输出
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"""
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try:
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logger.debug(
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f"[私聊][{self.private_name}]重新加载主动对话配置: 启用={global_config.enable_idle_conversation}, 检查间隔={global_config.idle_check_interval}秒, 最短间隔={global_config.min_idle_time}秒, 最长间隔={global_config.max_idle_time}秒"
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)
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# 重新计算实际阈值
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async def update_threshold():
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async with self._lock:
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self.actual_idle_threshold = random.randint(
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global_config.min_idle_time, global_config.max_idle_time
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)
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logger.debug(f"[私聊][{self.private_name}]更新空闲检测阈值为: {self.actual_idle_threshold}秒")
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# 创建一个任务来异步更新阈值
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asyncio.create_task(update_threshold())
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except Exception as e:
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logger.error(f"[私聊][{self.private_name}]重新加载配置时出错: {str(e)}")
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logger.error(traceback.format_exc())
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async def _check_idle_loop(self) -> None:
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"""检查空闲状态的循环
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定期检查是否长时间无对话，如果达到阈值则尝试主动发起对话。
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"""
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try:
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config_reload_counter = 0
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config_reload_interval = 100 # 每100次检查重新加载一次配置
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while self._running:
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# 定期重新加载配置
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config_reload_counter += 1
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if config_reload_counter >= config_reload_interval:
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self.reload_config()
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config_reload_counter = 0
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# 检查是否启用了主动对话功能
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if not global_config.enable_idle_conversation:
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# 如果禁用了功能，就等待一段时间后再次检查配置
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await asyncio.sleep(global_config.idle_check_interval)
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continue
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# 使用锁保护对共享变量的读取
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current_time = time.time()
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async with self._lock:
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idle_time = current_time - self.last_message_time
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threshold = self.actual_idle_threshold
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if idle_time >= threshold:
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logger.info(f"[私聊][{self.private_name}]检测到长时间({idle_time:.0f}秒)无对话，尝试主动发起聊天")
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await self._initiate_conversation()
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# 更新时间，避免连续触发
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await self.update_last_message_time()
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# 等待下一次检查
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await asyncio.sleep(global_config.idle_check_interval)
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except asyncio.CancelledError:
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logger.debug(f"[私聊][{self.private_name}]空闲对话检测任务被取消")
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except Exception as e:
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logger.error(f"[私聊][{self.private_name}]空闲对话检测出错: {str(e)}")
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logger.error(traceback.format_exc())
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# 尝试重新启动检测循环
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if self._running:
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logger.info(f"[私聊][{self.private_name}]尝试重新启动空闲对话检测")
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self._task = asyncio.create_task(self._check_idle_loop())
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async def _initiate_conversation(self) -> None:
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"""生成并发送主动对话内容
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获取聊天历史记录，使用LLM生成合适的开场白（大概），然后发送消息。
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"""
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try:
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# 获取聊天历史记录，用于生成更合适的开场白
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messages = self.chat_observer.get_cached_messages(limit=12) # 获取最近12条消息
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chat_history_text = await build_readable_messages(
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messages,
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replace_bot_name=True,
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merge_messages=False,
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timestamp_mode="relative",
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read_mark=0.0,
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)
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# 构建提示词
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prompt = f"""{self.personality_info}。你的名字是{global_config.BOT_NICKNAME}。
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你正在与用户{self.private_name}进行QQ私聊,
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但已经有一段时间没有对话了。
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你想要主动发起一个友好的对话，可以说说自己在做的事情或者询问对方在做什么。
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请基于以下之前的对话历史，生成一条自然、友好、符合你个性的主动对话消息。
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这条消息应该能够引起用户的兴趣，重新开始对话。
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最近的对话历史（可能已经过去了很久）：
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{chat_history_text}
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请直接输出一条消息，不要有任何额外的解释或引导文字。消息要简短自然，就像是在日常聊天中的开场白。
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消息内容尽量简短,不要超过20个字,不要添加任何表情符号。
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"""
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# 尝试生成回复，添加超时处理
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try:
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content, _ = await asyncio.wait_for(
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self.llm.generate_response_async(prompt),
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timeout=30, # 30秒超时
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)
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except asyncio.TimeoutError:
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logger.error(f"[私聊][{self.private_name}]生成主动对话内容超时")
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return
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except Exception as llm_err:
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logger.error(f"[私聊][{self.private_name}]生成主动对话内容失败: {str(llm_err)}")
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logger.error(traceback.format_exc())
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return
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# 清理结果
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content = content.strip()
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content = content.strip("\"'")
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if not content:
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logger.error(f"[私聊][{self.private_name}]生成的主动对话内容为空")
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return
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# 统一错误处理，从这里开始所有操作都在同一个try-except块中
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logger.debug(f"[私聊][{self.private_name}]成功生成主动对话内容: {content}，准备发送")
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# 在函数内部导入PFCManager，避免循环导入
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from ..pfc_manager import PFCManager
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# 获取当前实例 - 注意这是同步方法，不需要await
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pfc_manager = PFCManager.get_instance()
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# 结束当前对话实例（如果存在）
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current_conversation = await pfc_manager.get_conversation(self.stream_id)
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if current_conversation:
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logger.info(f"[私聊][{self.private_name}]结束当前对话实例，准备创建新实例")
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try:
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await current_conversation.stop()
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await pfc_manager.remove_conversation(self.stream_id)
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except Exception as e:
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logger.warning(f"[私聊][{self.private_name}]结束当前对话实例时出错: {str(e)}，继续创建新实例")
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logger.warning(traceback.format_exc())
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# 创建新的对话实例
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logger.info(f"[私聊][{self.private_name}]创建新的对话实例以发送主动消息")
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new_conversation = None
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try:
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new_conversation = await pfc_manager.get_or_create_conversation(self.stream_id, self.private_name)
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except Exception as e:
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logger.error(f"[私聊][{self.private_name}]创建新对话实例失败: {str(e)}")
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logger.error(traceback.format_exc())
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return
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# 确保新对话实例已初始化完成
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chat_stream = await self._get_chat_stream(new_conversation)
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if not chat_stream:
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logger.error(f"[私聊][{self.private_name}]无法获取有效的聊天流，取消发送主动消息")
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return
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# 发送消息
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try:
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await self.message_sender.send_message(chat_stream=chat_stream, content=content, reply_to_message=None)
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# 更新空闲会话启动器的最后消息时间
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await self.update_last_message_time()
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# 如果新对话实例有一个聊天观察者，请触发更新
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if new_conversation and hasattr(new_conversation, "chat_observer"):
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logger.info(f"[私聊][{self.private_name}]触发聊天观察者更新")
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try:
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new_conversation.chat_observer.trigger_update()
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except Exception as e:
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logger.warning(f"[私聊][{self.private_name}]触发聊天观察者更新失败: {str(e)}")
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logger.warning(traceback.format_exc())
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logger.info(f"[私聊][{self.private_name}]成功主动发起对话: {content}")
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except Exception as e:
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logger.error(f"[私聊][{self.private_name}]发送主动对话消息失败: {str(e)}")
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logger.error(traceback.format_exc())
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except Exception as e:
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# 顶级异常处理，确保任何未捕获的异常都不会导致整个进程崩溃
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logger.error(f"[私聊][{self.private_name}]主动发起对话过程中发生未预期的错误: {str(e)}")
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logger.error(traceback.format_exc())
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async def _get_chat_stream(self, conversation: Optional["Conversation"] = None) -> Optional[ChatStream]:
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"""获取可用的聊天流
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尝试多种方式获取聊天流：
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1. 从传入的对话实例中获取
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2. 从全局聊天管理器中获取
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3. 创建一个新的聊天流
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Args:
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conversation: 对话实例，可以为None
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Returns:
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Optional[ChatStream]: 如果成功获取则返回聊天流，否则返回None
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"""
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chat_stream = None
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# 1. 尝试从对话实例获取
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if conversation and hasattr(conversation, "should_continue"):
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# 等待一小段时间，确保初始化完成
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retry_count = 0
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max_retries = 10
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while not conversation.should_continue and retry_count < max_retries:
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await asyncio.sleep(0.5)
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retry_count += 1
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logger.debug(f"[私聊][{self.private_name}]等待新对话实例初始化完成: 尝试 {retry_count}/{max_retries}")
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if not conversation.should_continue:
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logger.warning(f"[私聊][{self.private_name}]新对话实例初始化可能未完成，但仍将尝试获取聊天流")
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# 尝试使用对话实例的聊天流
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if hasattr(conversation, "chat_stream") and conversation.chat_stream:
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logger.info(f"[私聊][{self.private_name}]使用新对话实例的聊天流")
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return conversation.chat_stream
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# 2. 尝试从聊天管理器获取
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try:
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logger.info(f"[私聊][{self.private_name}]尝试从chat_manager获取聊天流")
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chat_stream = chat_manager.get_stream(self.stream_id)
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if chat_stream:
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return chat_stream
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except Exception as e:
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logger.warning(f"[私聊][{self.private_name}]从chat_manager获取聊天流失败: {str(e)}")
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logger.warning(traceback.format_exc())
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# 3. 创建新的聊天流
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try:
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logger.warning(f"[私聊][{self.private_name}]无法获取现有聊天流，创建新的聊天流")
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# 创建用户信息对象
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user_info = UserInfo(user_id=global_config.BOT_QQ, user_nickname=global_config.BOT_NICKNAME, platform="qq")
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# 创建聊天流
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return ChatStream(self.stream_id, "qq", user_info)
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except Exception as e:
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logger.error(f"[私聊][{self.private_name}]创建新聊天流失败: {str(e)}")
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logger.error(traceback.format_exc())
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return None
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