365 lines
18 KiB
Python
365 lines
18 KiB
Python
import time
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from random import random
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import traceback
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from typing import List, Optional
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import asyncio
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from ...moods.moods import MoodManager
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from ....config.config import global_config
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from ...chat.emoji_manager import emoji_manager
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from .heartFC__generator import ResponseGenerator
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from ...chat.message import MessageSending, MessageRecv, MessageThinking, MessageSet
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from .messagesender import MessageManager
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from ...chat.utils_image import image_path_to_base64
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from ...message import UserInfo, Seg
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from src.heart_flow.heartflow import heartflow
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from src.common.logger import get_module_logger, CHAT_STYLE_CONFIG, LogConfig
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from ...person_info.relationship_manager import relationship_manager
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from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
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from ...utils.timer_calculater import Timer
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from src.do_tool.tool_use import ToolUser
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from .interest import InterestManager, InterestChatting
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# 定义日志配置
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chat_config = LogConfig(
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console_format=CHAT_STYLE_CONFIG["console_format"],
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file_format=CHAT_STYLE_CONFIG["file_format"],
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)
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logger = get_module_logger("heartFC_chat", config=chat_config)
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# 新增常量
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INTEREST_LEVEL_REPLY_THRESHOLD = 4.0
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INTEREST_MONITOR_INTERVAL_SECONDS = 1
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class HeartFC_Chat:
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def __init__(self):
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self.gpt = ResponseGenerator()
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self.mood_manager = MoodManager.get_instance()
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self.mood_manager.start_mood_update()
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self.tool_user = ToolUser()
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self.interest_manager = InterestManager()
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self._interest_monitor_task: Optional[asyncio.Task] = None
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async def start(self):
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"""Starts asynchronous tasks like the interest monitor."""
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logger.info("HeartFC_Chat starting asynchronous tasks...")
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await self.interest_manager.start_background_tasks()
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self._initialize_monitor_task()
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logger.info("HeartFC_Chat asynchronous tasks started.")
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def _initialize_monitor_task(self):
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"""启动后台兴趣监控任务"""
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if self._interest_monitor_task is None or self._interest_monitor_task.done():
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try:
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loop = asyncio.get_running_loop()
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self._interest_monitor_task = loop.create_task(self._interest_monitor_loop())
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logger.info(f"Interest monitor task created. Interval: {INTEREST_MONITOR_INTERVAL_SECONDS}s, Level Threshold: {INTEREST_LEVEL_REPLY_THRESHOLD}")
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except RuntimeError:
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logger.error("Failed to create interest monitor task: No running event loop.")
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raise
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else:
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logger.warning("Interest monitor task creation skipped: already running or exists.")
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async def _interest_monitor_loop(self):
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"""后台任务，定期检查兴趣度变化并触发回复"""
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logger.info("Interest monitor loop starting...")
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await asyncio.sleep(0.3)
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while True:
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await asyncio.sleep(INTEREST_MONITOR_INTERVAL_SECONDS)
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try:
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interest_items_snapshot: List[tuple[str, InterestChatting]] = []
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stream_ids = list(self.interest_manager.interest_dict.keys())
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for stream_id in stream_ids:
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chatting_instance = self.interest_manager.get_interest_chatting(stream_id)
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if chatting_instance:
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interest_items_snapshot.append((stream_id, chatting_instance))
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for stream_id, chatting_instance in interest_items_snapshot:
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triggering_message = chatting_instance.last_triggering_message
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current_interest = chatting_instance.get_interest()
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# 添加调试日志，检查触发条件
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# logger.debug(f"[兴趣监控][{stream_id}] 当前兴趣: {current_interest:.2f}, 阈值: {INTEREST_LEVEL_REPLY_THRESHOLD}, 触发消息存在: {triggering_message is not None}")
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if current_interest > INTEREST_LEVEL_REPLY_THRESHOLD and triggering_message is not None:
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logger.info(f"[{stream_id}] 检测到高兴趣度 ({current_interest:.2f} > {INTEREST_LEVEL_REPLY_THRESHOLD}). 基于消息 ID: {triggering_message.message_info.message_id} 的上下文触发回复") # 更新日志信息使其更清晰
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chatting_instance.reset_trigger_info()
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logger.debug(f"[{stream_id}] Trigger info reset before starting reply task.")
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asyncio.create_task(self._process_triggered_reply(stream_id, triggering_message))
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except asyncio.CancelledError:
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logger.info("Interest monitor loop cancelled.")
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break
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except Exception as e:
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logger.error(f"Error in interest monitor loop: {e}")
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logger.error(traceback.format_exc())
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await asyncio.sleep(5)
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async def _process_triggered_reply(self, stream_id: str, triggering_message: MessageRecv):
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"""Helper coroutine to handle the processing of a triggered reply based on interest level."""
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try:
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logger.info(f"[{stream_id}] Starting level-triggered reply generation for message ID: {triggering_message.message_info.message_id}...")
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await self.trigger_reply_generation(triggering_message)
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# 在回复处理后降低兴趣度，降低固定值：新阈值的一半
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decrease_value = INTEREST_LEVEL_REPLY_THRESHOLD / 2
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self.interest_manager.decrease_interest(stream_id, value=decrease_value)
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post_trigger_interest = self.interest_manager.get_interest(stream_id)
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# 更新日志以反映降低的是基于新阈值的固定值
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logger.info(f"[{stream_id}] Interest decreased by fixed value {decrease_value:.2f} (LevelThreshold/2) after processing level-triggered reply. Current interest: {post_trigger_interest:.2f}")
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except Exception as e:
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logger.error(f"Error processing level-triggered reply for stream_id {stream_id}, context message_id {triggering_message.message_info.message_id}: {e}")
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logger.error(traceback.format_exc())
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async def _create_thinking_message(self, message: MessageRecv):
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"""创建思考消息 (从 message 获取信息)"""
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chat = message.chat_stream
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if not chat:
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logger.error(f"Cannot create thinking message, chat_stream is None for message ID: {message.message_info.message_id}")
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return None
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userinfo = message.message_info.user_info # 发起思考的用户（即原始消息发送者）
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messageinfo = message.message_info # 原始消息信息
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bot_user_info = UserInfo(
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user_id=global_config.BOT_QQ,
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user_nickname=global_config.BOT_NICKNAME,
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platform=messageinfo.platform,
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)
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thinking_time_point = round(time.time(), 2)
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thinking_id = "mt" + str(thinking_time_point)
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thinking_message = MessageThinking(
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message_id=thinking_id,
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chat_stream=chat,
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bot_user_info=bot_user_info, # 思考消息的发出者是 bot
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reply=message, # 回复的是原始消息
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thinking_start_time=thinking_time_point,
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)
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MessageManager().add_message(thinking_message)
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return thinking_id
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async def _send_response_messages(self, message: MessageRecv, response_set: List[str], thinking_id) -> MessageSending:
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chat = message.chat_stream
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container = MessageManager().get_container(chat.stream_id)
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thinking_message = None
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for msg in container.messages:
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if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
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thinking_message = msg
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container.messages.remove(msg)
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break
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if not thinking_message:
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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 None
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thinking_start_time = thinking_message.thinking_start_time
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message_set = MessageSet(chat, thinking_id)
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mark_head = False
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first_bot_msg = None
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for msg in response_set:
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message_segment = Seg(type="text", data=msg)
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bot_message = MessageSending(
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message_id=thinking_id,
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chat_stream=chat,
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bot_user_info=UserInfo(
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user_id=global_config.BOT_QQ,
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user_nickname=global_config.BOT_NICKNAME,
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platform=message.message_info.platform, # 从传入的 message 获取 platform
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),
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sender_info=message.message_info.user_info, # 发送给谁
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message_segment=message_segment,
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reply=message, # 回复原始消息
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is_head=not mark_head,
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is_emoji=False,
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thinking_start_time=thinking_start_time,
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)
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if not mark_head:
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mark_head = True
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first_bot_msg = bot_message
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message_set.add_message(bot_message)
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MessageManager().add_message(message_set)
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return first_bot_msg
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async def _handle_emoji(self, message: MessageRecv, response_set, send_emoji=""):
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"""处理表情包 (从 message 获取信息)"""
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chat = message.chat_stream
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if send_emoji:
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emoji_raw = await emoji_manager.get_emoji_for_text(send_emoji)
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else:
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emoji_text_source = "".join(response_set) if response_set else ""
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emoji_raw = await emoji_manager.get_emoji_for_text(emoji_text_source)
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if 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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thinking_time_point = round(message.message_info.time, 2)
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message_segment = Seg(type="emoji", data=emoji_cq)
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bot_message = MessageSending(
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message_id="mt" + str(thinking_time_point),
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chat_stream=chat,
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bot_user_info=UserInfo(
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user_id=global_config.BOT_QQ,
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user_nickname=global_config.BOT_NICKNAME,
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platform=message.message_info.platform,
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),
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sender_info=message.message_info.user_info, # 发送给谁
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message_segment=message_segment,
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reply=message, # 回复原始消息
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is_head=False,
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is_emoji=True,
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)
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MessageManager().add_message(bot_message)
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async def _update_relationship(self, message: MessageRecv, response_set):
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"""更新关系情绪"""
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ori_response = ",".join(response_set)
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stance, emotion = await self.gpt._get_emotion_tags(ori_response, message.processed_plain_text)
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await relationship_manager.calculate_update_relationship_value(
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chat_stream=message.chat_stream, label=emotion, stance=stance
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)
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self.mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor)
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async def trigger_reply_generation(self, message: MessageRecv):
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"""根据意愿阈值触发的实际回复生成和发送逻辑 (V3 - 简化参数)"""
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chat = message.chat_stream
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userinfo = message.message_info.user_info
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messageinfo = message.message_info
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timing_results = {}
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response_set = None
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thinking_id = None
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info_catcher = None
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try:
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try:
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with Timer("观察", timing_results):
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sub_hf = heartflow.get_subheartflow(chat.stream_id)
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if not sub_hf:
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logger.warning(f"尝试观察时未找到 stream_id {chat.stream_id} 的 subheartflow")
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return
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await sub_hf.do_observe()
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except Exception as e:
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logger.error(f"心流观察失败: {e}")
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logger.error(traceback.format_exc())
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container = MessageManager().get_container(chat.stream_id)
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thinking_count = container.count_thinking_messages()
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max_thinking_messages = getattr(global_config, 'max_concurrent_thinking_messages', 3)
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if thinking_count >= max_thinking_messages:
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logger.warning(f"聊天流 {chat.stream_id} 已有 {thinking_count} 条思考消息，取消回复。触发消息: {message.processed_plain_text[:30]}...")
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return
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try:
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with Timer("创建思考消息", timing_results):
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thinking_id = await self._create_thinking_message(message)
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except Exception as e:
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logger.error(f"心流创建思考消息失败: {e}")
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return
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if not thinking_id:
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logger.error("未能成功创建思考消息 ID，无法继续回复流程。")
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return
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logger.trace(f"创建捕捉器，thinking_id:{thinking_id}")
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info_catcher = info_catcher_manager.get_info_catcher(thinking_id)
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info_catcher.catch_decide_to_response(message)
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get_mid_memory_id = []
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tool_result_info = {}
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send_emoji = ""
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try:
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with Timer("思考前使用工具", timing_results):
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tool_result = await self.tool_user.use_tool(
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message.processed_plain_text,
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userinfo.user_nickname,
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chat,
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heartflow.get_subheartflow(chat.stream_id),
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)
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if tool_result.get("used_tools", False):
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if "structured_info" in tool_result:
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tool_result_info = tool_result["structured_info"]
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get_mid_memory_id = []
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for tool_name, tool_data in tool_result_info.items():
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if tool_name == "mid_chat_mem":
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for mid_memory in tool_data:
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get_mid_memory_id.append(mid_memory["content"])
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if tool_name == "send_emoji":
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send_emoji = tool_data[0]["content"]
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except Exception as e:
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logger.error(f"思考前工具调用失败: {e}")
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logger.error(traceback.format_exc())
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current_mind, past_mind = "", ""
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try:
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with Timer("思考前脑内状态", timing_results):
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sub_hf = heartflow.get_subheartflow(chat.stream_id)
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if sub_hf:
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current_mind, past_mind = await sub_hf.do_thinking_before_reply(
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message_txt=message.processed_plain_text,
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sender_info=userinfo,
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chat_stream=chat,
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obs_id=get_mid_memory_id,
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extra_info=tool_result_info,
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)
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else:
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logger.warning(f"尝试思考前状态时未找到 stream_id {chat.stream_id} 的 subheartflow")
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except Exception as e:
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logger.error(f"心流思考前脑内状态失败: {e}")
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logger.error(traceback.format_exc())
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if info_catcher:
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info_catcher.catch_afer_shf_step(timing_results.get("思考前脑内状态"), past_mind, current_mind)
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try:
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with Timer("生成回复", timing_results):
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response_set = await self.gpt.generate_response(message, thinking_id)
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except Exception as e:
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logger.error(f"GPT 生成回复失败: {e}")
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logger.error(traceback.format_exc())
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if info_catcher: info_catcher.done_catch()
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return
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if info_catcher:
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info_catcher.catch_after_generate_response(timing_results.get("生成回复"))
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if not response_set:
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logger.info("回复生成失败，返回为空")
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if info_catcher: info_catcher.done_catch()
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return
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first_bot_msg = None
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try:
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with Timer("发送消息", timing_results):
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first_bot_msg = await self._send_response_messages(message, response_set, thinking_id)
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except Exception as e:
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logger.error(f"心流发送消息失败: {e}")
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if info_catcher:
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info_catcher.catch_after_response(timing_results.get("发送消息"), response_set, first_bot_msg)
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info_catcher.done_catch()
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try:
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with Timer("处理表情包", timing_results):
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if send_emoji:
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logger.info(f"麦麦决定发送表情包{send_emoji}")
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await self._handle_emoji(message, response_set, send_emoji)
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except Exception as e:
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logger.error(f"心流处理表情包失败: {e}")
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timing_str = " | ".join([f"{step}: {duration:.2f}秒" for step, duration in timing_results.items()])
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trigger_msg = message.processed_plain_text
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response_msg = " ".join(response_set) if response_set else "无回复"
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logger.info(f"回复任务完成: 触发消息: {trigger_msg[:20]}... | 思维消息: {response_msg[:20]}... | 性能计时: {timing_str}")
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if first_bot_msg:
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try:
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with Timer("更新关系情绪", timing_results):
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await self._update_relationship(message, response_set)
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except Exception as e:
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logger.error(f"更新关系情绪失败: {e}")
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logger.error(traceback.format_exc())
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except Exception as e:
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logger.error(f"回复生成任务失败 (trigger_reply_generation V3): {e}")
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logger.error(traceback.format_exc())
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finally:
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pass
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