937 lines
48 KiB
Python
937 lines
48 KiB
Python
import asyncio
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import time
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import traceback
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from typing import List, Optional, Dict, Any, TYPE_CHECKING
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import json
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from src.plugins.chat.message import MessageRecv, BaseMessageInfo, MessageThinking, MessageSending
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from src.plugins.chat.message import MessageSet, Seg # Local import needed after move
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from src.plugins.chat.chat_stream import ChatStream
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from src.plugins.chat.message import UserInfo
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from src.plugins.chat.chat_stream import chat_manager
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from src.common.logger import get_module_logger, LogConfig, PFC_STYLE_CONFIG # 引入 DEFAULT_CONFIG
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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.utils_image import image_path_to_base64 # Local import needed after move
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from src.plugins.utils.timer_calculater import Timer # <--- Import Timer
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# --- Import necessary dependencies directly ---
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from .heartFC_generator import ResponseGenerator # Assuming this is the type for gpt
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from src.do_tool.tool_use import ToolUser
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from src.plugins.chat.emoji_manager import EmojiManager # Assuming this is the type
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from ..chat.message_sender import message_manager # <-- Import the global manager
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# --- End import ---
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INITIAL_DURATION = 60.0
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# 定义日志配置 (使用 loguru 格式)
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interest_log_config = LogConfig(
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console_format=PFC_STYLE_CONFIG["console_format"], # 使用默认控制台格式
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file_format=PFC_STYLE_CONFIG["file_format"], # 使用默认文件格式
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)
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logger = get_module_logger("HeartFCLoop", config=interest_log_config) # Logger Name Changed
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# Forward declaration for type hinting
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if TYPE_CHECKING:
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# Keep this if HeartFCController methods are still needed elsewhere,
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# but the instance variable will be removed from HeartFChatting
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# from .heartFC_controler import HeartFCController
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from src.heart_flow.heartflow import SubHeartflow, heartflow # <-- 同时导入 heartflow 实例用于类型检查
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PLANNER_TOOL_DEFINITION = [
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{
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"type": "function",
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"function": {
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"name": "decide_reply_action",
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"description": "根据当前聊天内容和上下文，决定机器人是否应该回复以及如何回复。",
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"parameters": {
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"type": "object",
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"properties": {
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"action": {
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"type": "string",
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"enum": ["no_reply", "text_reply", "emoji_reply"],
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"description": "决定采取的行动：'no_reply'(不回复), 'text_reply'(文本回复, 可选附带表情) 或 'emoji_reply'(仅表情回复)。",
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},
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"reasoning": {"type": "string", "description": "做出此决定的简要理由。"},
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"emoji_query": {
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"type": "string",
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"description": "如果行动是'emoji_reply'，指定表情的主题或概念。如果行动是'text_reply'且希望在文本后追加表情，也在此指定表情主题。",
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},
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},
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"required": ["action", "reasoning"],
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},
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},
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}
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]
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class HeartFChatting:
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"""
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管理一个连续的Plan-Replier-Sender循环
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用于在特定聊天流中生成回复，由计时器控制。
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只要计时器>0，循环就会继续。
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现在由其关联的 SubHeartflow 管理生命周期。
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"""
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def __init__(
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self,
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chat_id: str,
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# 显式依赖注入
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gpt_instance: ResponseGenerator, # 文本回复生成器
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tool_user_instance: ToolUser, # 工具使用实例
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emoji_manager_instance: EmojiManager, # 表情管理实例
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):
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"""
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HeartFChatting 初始化函数
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参数:
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chat_id: 聊天流唯一标识符(如stream_id)
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gpt_instance: 文本回复生成器实例
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tool_user_instance: 工具使用实例
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emoji_manager_instance: 表情管理实例
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"""
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# 基础属性
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self.stream_id: str = chat_id # 聊天流ID
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self.chat_stream: Optional[ChatStream] = None # 关联的聊天流
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self.sub_hf: SubHeartflow = None # 关联的子心流
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# 初始化状态控制
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self._initialized = False # 是否已初始化标志
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self._init_lock = asyncio.Lock() # 初始化锁(确保只初始化一次)
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self._processing_lock = asyncio.Lock() # 处理锁(确保单次Plan-Replier-Sender周期)
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self._timer_lock = asyncio.Lock() # 计时器锁(安全更新计时器)
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# 依赖注入存储
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self.gpt_instance = gpt_instance # 文本回复生成器
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self.tool_user = tool_user_instance # 工具使用实例
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self.emoji_manager = emoji_manager_instance # 表情管理实例
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# LLM规划器配置
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self.planner_llm = LLMRequest(
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model=global_config.llm_normal,
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temperature=global_config.llm_normal["temp"],
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max_tokens=1000,
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request_type="action_planning", # 用于动作规划
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)
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# 循环控制内部状态
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self._loop_timer: float = 0.0 # 循环剩余时间(秒)
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self._loop_active: bool = False # 循环是否正在运行
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self._loop_task: Optional[asyncio.Task] = None # 主循环任务
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self._trigger_count_this_activation: int = 0 # 当前激活周期内的触发计数
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self._initial_duration: float = INITIAL_DURATION # 首次触发增加的时间
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self._last_added_duration: float = self._initial_duration # 上次增加的时间
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def _get_log_prefix(self) -> str:
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"""获取日志前缀，包含可读的流名称"""
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stream_name = chat_manager.get_stream_name(self.stream_id) or self.stream_id
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return f"[{stream_name}]"
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async def _initialize(self) -> bool:
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"""
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懒初始化以使用提供的标识符解析chat_stream和sub_hf。
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确保实例已准备好处理触发器。
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"""
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async with self._init_lock:
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if self._initialized:
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return True
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log_prefix = self._get_log_prefix() # 获取前缀
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try:
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self.chat_stream = chat_manager.get_stream(self.stream_id)
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if not self.chat_stream:
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logger.error(f"{log_prefix} 获取ChatStream失败。")
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return False
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# <-- 在这里导入 heartflow 实例
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from src.heart_flow.heartflow import heartflow
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self.sub_hf = heartflow.get_subheartflow(self.stream_id)
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if not self.sub_hf:
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logger.warning(f"{log_prefix} 获取SubHeartflow失败。一些功能可能受限。")
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self._initialized = True
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logger.info(f"麦麦感觉到了，激发了HeartFChatting{log_prefix} 初始化成功。")
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return True
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except Exception as e:
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logger.error(f"{log_prefix} 初始化失败: {e}")
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logger.error(traceback.format_exc())
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return False
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async def add_time(self):
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"""
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为麦麦添加时间，麦麦有兴趣时，时间增加。
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"""
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log_prefix = self._get_log_prefix()
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if not self._initialized:
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if not await self._initialize():
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logger.error(f"{log_prefix} 无法添加时间: 未初始化。")
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return
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async with self._timer_lock:
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duration_to_add: float = 0.0
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if not self._loop_active: # First trigger for this activation cycle
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duration_to_add = self._initial_duration # 使用初始值
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self._last_added_duration = duration_to_add # 更新上次增加的值
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self._trigger_count_this_activation = 1 # Start counting
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logger.info(
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f"{log_prefix} 麦麦有兴趣！ #{self._trigger_count_this_activation}. 麦麦打算聊： {duration_to_add:.2f}s."
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)
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else: # Loop is already active, apply 50% reduction
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self._trigger_count_this_activation += 1
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duration_to_add = self._last_added_duration * 0.5
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if duration_to_add < 1.5:
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duration_to_add = 1.5
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# Update _last_added_duration only if it's >= 0.5 to prevent it from becoming too small
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self._last_added_duration = duration_to_add
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logger.info(
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f"{log_prefix} 麦麦兴趣增加！ #{self._trigger_count_this_activation}. 想继续聊： {duration_to_add:.2f}s, 麦麦还能聊： {self._loop_timer:.1f}s."
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)
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# 添加计算出的时间
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new_timer_value = self._loop_timer + duration_to_add
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# Add max timer duration limit? e.g., max(0, min(new_timer_value, 300))
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self._loop_timer = max(0, new_timer_value)
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# Log less frequently, e.g., every 10 seconds or significant change?
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# if self._trigger_count_this_activation % 5 == 0:
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# logger.info(f"{log_prefix} 麦麦现在想聊{self._loop_timer:.1f}秒")
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# Start the loop if it wasn't active and timer is positive
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if not self._loop_active and self._loop_timer > 0:
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self._loop_active = True
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if self._loop_task and not self._loop_task.done():
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logger.warning(f"{log_prefix} 发现意外的循环任务正在进行。取消它。")
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self._loop_task.cancel()
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self._loop_task = asyncio.create_task(self._run_pf_loop())
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self._loop_task.add_done_callback(self._handle_loop_completion)
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elif self._loop_active:
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logger.trace(f"{log_prefix} 循环已经激活。计时器延长。")
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def _handle_loop_completion(self, task: asyncio.Task):
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"""当 _run_pf_loop 任务完成时执行的回调。"""
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log_prefix = self._get_log_prefix()
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try:
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exception = task.exception()
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if exception:
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logger.error(f"{log_prefix} HeartFChatting: 麦麦脱离了聊天(异常): {exception}")
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logger.error(traceback.format_exc()) # Log full traceback for exceptions
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else:
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logger.debug(f"{log_prefix} HeartFChatting: 麦麦脱离了聊天 (正常完成)")
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except asyncio.CancelledError:
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logger.info(f"{log_prefix} HeartFChatting: 麦麦脱离了聊天(任务取消)")
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finally:
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self._loop_active = False
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self._loop_task = None
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self._last_added_duration = self._initial_duration
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self._trigger_count_this_activation = 0
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if self._processing_lock.locked():
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logger.warning(f"{log_prefix} HeartFChatting: 处理锁在循环结束时仍被锁定，强制释放。")
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self._processing_lock.release()
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# Instance removal is now handled by SubHeartflow
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# asyncio.create_task(self.heartfc_controller._remove_heartFC_chat_instance(self.stream_id)) # Removed
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async def _run_pf_loop(self):
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"""
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主循环，当计时器>0时持续进行计划并可能回复消息
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管理每个循环周期的处理锁
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"""
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log_prefix = self._get_log_prefix()
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logger.info(f"{log_prefix} HeartFChatting: 麦麦打算好好聊聊 (定时器: {self._loop_timer:.1f}s)")
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try:
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thinking_id = ""
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while True:
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cycle_timers = {} # <--- Initialize timers dict for this cycle
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# Access MessageManager directly
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if message_manager.check_if_sending_message_exist(self.stream_id, thinking_id):
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# logger.info(f"{log_prefix} HeartFChatting: 11111111111111111111111111111111麦麦还在发消息，等会再规划")
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await asyncio.sleep(1)
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continue
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else:
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# logger.info(f"{log_prefix} HeartFChatting: 11111111111111111111111111111111麦麦不发消息了，开始规划")
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pass
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async with self._timer_lock:
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current_timer = self._loop_timer
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if current_timer <= 0:
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logger.info(
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f"{log_prefix} HeartFChatting: 聊太久了，麦麦打算休息一下 (计时器为 {current_timer:.1f}s)。退出HeartFChatting。"
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)
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break
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# 记录循环周期开始时间，用于计时和休眠计算
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loop_cycle_start_time = time.monotonic()
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action_taken_this_cycle = False
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acquired_lock = False
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planner_start_db_time = 0.0 # 初始化
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try:
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with Timer("Total Cycle", cycle_timers) as _total_timer: # <--- Start total cycle timer
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# Use try_acquire pattern or timeout?
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await self._processing_lock.acquire()
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acquired_lock = True
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# logger.debug(f"{log_prefix} HeartFChatting: 循环获取到处理锁")
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# 在规划前记录数据库时间戳
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planner_start_db_time = time.time()
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# --- Planner --- #
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planner_result = {}
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with Timer("Planner", cycle_timers): # <--- Start Planner timer
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planner_result = await self._planner()
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action = planner_result.get("action", "error")
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reasoning = planner_result.get("reasoning", "Planner did not provide reasoning.")
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emoji_query = planner_result.get("emoji_query", "")
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# current_mind = planner_result.get("current_mind", "[Mind unavailable]")
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# send_emoji_from_tools = planner_result.get("send_emoji_from_tools", "") # Emoji from tools
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observed_messages = planner_result.get("observed_messages", [])
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llm_error = planner_result.get("llm_error", False)
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if llm_error:
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logger.error(f"{log_prefix} Planner LLM 失败，跳过本周期回复尝试。理由: {reasoning}")
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# Optionally add a longer sleep?
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action_taken_this_cycle = False # Ensure no action is counted
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# Continue to timer decrement and sleep
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elif action == "text_reply":
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logger.debug(f"{log_prefix} HeartFChatting: 麦麦决定回复文本. 理由: {reasoning}")
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action_taken_this_cycle = True
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anchor_message = await self._get_anchor_message(observed_messages)
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if not anchor_message:
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logger.error(f"{log_prefix} 循环: 无法获取锚点消息用于回复. 跳过周期.")
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else:
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# --- Create Thinking Message (Moved) ---
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thinking_id = await self._create_thinking_message(anchor_message)
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if not thinking_id:
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logger.error(f"{log_prefix} 循环: 无法创建思考ID. 跳过周期.")
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else:
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replier_result = None
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try:
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# --- Replier Work --- #
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with Timer("Replier", cycle_timers): # <--- Start Replier timer
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replier_result = await self._replier_work(
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anchor_message=anchor_message,
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thinking_id=thinking_id,
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reason=reasoning,
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)
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except Exception as e_replier:
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logger.error(f"{log_prefix} 循环: 回复器工作失败: {e_replier}")
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# self._cleanup_thinking_message(thinking_id) <-- Remove cleanup call
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if replier_result:
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# --- Sender Work --- #
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try:
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with Timer("Sender", cycle_timers): # <--- Start Sender timer
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await self._sender(
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thinking_id=thinking_id,
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anchor_message=anchor_message,
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response_set=replier_result,
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send_emoji=emoji_query,
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)
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# logger.info(f"{log_prefix} 循环: 发送器完成成功.")
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except Exception as e_sender:
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logger.error(f"{log_prefix} 循环: 发送器失败: {e_sender}")
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# _sender should handle cleanup, but double check
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# self._cleanup_thinking_message(thinking_id) <-- Remove cleanup call
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else:
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logger.warning(f"{log_prefix} 循环: 回复器未产生结果. 跳过发送.")
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# self._cleanup_thinking_message(thinking_id) <-- Remove cleanup call
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elif action == "emoji_reply":
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logger.info(
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f"{log_prefix} HeartFChatting: 麦麦决定回复表情 ('{emoji_query}'). 理由: {reasoning}"
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)
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action_taken_this_cycle = True
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anchor = await self._get_anchor_message(observed_messages)
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if anchor:
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try:
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# --- Handle Emoji (Moved) --- #
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with Timer("Emoji Handler", cycle_timers): # <--- Start Emoji timer
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await self._handle_emoji(anchor, [], emoji_query)
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except Exception as e_emoji:
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logger.error(f"{log_prefix} 循环: 发送表情失败: {e_emoji}")
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else:
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logger.warning(f"{log_prefix} 循环: 无法发送表情, 无法获取锚点.")
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action_taken_this_cycle = True # 即使发送失败，Planner 也决策了动作
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elif action == "no_reply":
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logger.info(f"{log_prefix} HeartFChatting: 麦麦决定不回复. 原因: {reasoning}")
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action_taken_this_cycle = False # 标记为未执行动作
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# --- 新增：等待新消息 ---
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logger.debug(f"{log_prefix} HeartFChatting: 开始等待新消息 (自 {planner_start_db_time})...")
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observation = None
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if self.sub_hf:
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observation = self.sub_hf._get_primary_observation()
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if observation:
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with Timer("Wait New Msg", cycle_timers): # <--- Start Wait timer
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wait_start_time = time.monotonic()
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while True:
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# 检查计时器是否耗尽
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async with self._timer_lock:
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if self._loop_timer <= 0:
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logger.info(f"{log_prefix} HeartFChatting: 等待新消息时计时器耗尽。")
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break # 计时器耗尽，退出等待
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# 检查是否有新消息
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has_new = await observation.has_new_messages_since(planner_start_db_time)
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if has_new:
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logger.info(f"{log_prefix} HeartFChatting: 检测到新消息，结束等待。")
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break # 收到新消息，退出等待
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# 检查等待是否超时（例如，防止无限等待）
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if time.monotonic() - wait_start_time > 60: # 等待60秒示例
|
||
logger.warning(f"{log_prefix} HeartFChatting: 等待新消息超时（60秒）。")
|
||
break # 超时退出
|
||
|
||
# 等待一段时间再检查
|
||
try:
|
||
await asyncio.sleep(1.5) # 检查间隔
|
||
except asyncio.CancelledError:
|
||
logger.info(f"{log_prefix} 等待新消息的 sleep 被中断。")
|
||
raise # 重新抛出取消错误，以便外层循环处理
|
||
else:
|
||
logger.warning(
|
||
f"{log_prefix} HeartFChatting: 无法获取 Observation 实例，无法等待新消息。"
|
||
)
|
||
# --- 等待结束 ---
|
||
|
||
elif action == "error": # Action specifically set to error by planner
|
||
logger.error(f"{log_prefix} HeartFChatting: Planner返回错误状态. 原因: {reasoning}")
|
||
action_taken_this_cycle = False
|
||
|
||
else: # Unknown action from planner
|
||
logger.warning(
|
||
f"{log_prefix} HeartFChatting: Planner返回未知动作 '{action}'. 原因: {reasoning}"
|
||
)
|
||
action_taken_this_cycle = False
|
||
|
||
# --- Print Timer Results --- #
|
||
if cycle_timers: # 先检查cycle_timers是否非空
|
||
timer_strings = []
|
||
for name, elapsed in cycle_timers.items():
|
||
# 直接格式化存储在字典中的浮点数 elapsed
|
||
formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒"
|
||
timer_strings.append(f"{name}: {formatted_time}")
|
||
|
||
if timer_strings: # 如果有有效计时器数据才打印
|
||
logger.debug(f"{log_prefix} 该次决策耗时: {'; '.join(timer_strings)}")
|
||
|
||
# --- Timer Decrement --- #
|
||
cycle_duration = time.monotonic() - loop_cycle_start_time
|
||
|
||
except Exception as e_cycle:
|
||
logger.error(f"{log_prefix} 循环周期执行时发生错误: {e_cycle}")
|
||
logger.error(traceback.format_exc())
|
||
if acquired_lock and self._processing_lock.locked():
|
||
self._processing_lock.release()
|
||
acquired_lock = False
|
||
logger.warning(f"{log_prefix} 由于循环周期中的错误释放了处理锁.")
|
||
|
||
finally:
|
||
if acquired_lock:
|
||
self._processing_lock.release()
|
||
# logger.trace(f"{log_prefix} 循环释放了处理锁.") # Reduce noise
|
||
|
||
async with self._timer_lock:
|
||
self._loop_timer -= cycle_duration
|
||
# Log timer decrement less aggressively
|
||
if cycle_duration > 0.1 or not action_taken_this_cycle:
|
||
logger.debug(
|
||
f"{log_prefix} HeartFChatting: 周期耗时 {cycle_duration:.2f}s. 剩余时间: {self._loop_timer:.1f}s."
|
||
)
|
||
|
||
# --- Delay --- #
|
||
try:
|
||
sleep_duration = 0.0
|
||
if not action_taken_this_cycle and cycle_duration < 1.5:
|
||
sleep_duration = 1.5 - cycle_duration
|
||
elif cycle_duration < 0.2:
|
||
sleep_duration = 0.2
|
||
|
||
if sleep_duration > 0:
|
||
# logger.debug(f"{log_prefix} Sleeping for {sleep_duration:.2f}s")
|
||
await asyncio.sleep(sleep_duration)
|
||
|
||
except asyncio.CancelledError:
|
||
logger.info(f"{log_prefix} Sleep interrupted, loop likely cancelling.")
|
||
break
|
||
|
||
except asyncio.CancelledError:
|
||
logger.info(f"{log_prefix} HeartFChatting: 麦麦的聊天主循环被取消了")
|
||
except Exception as e_loop_outer:
|
||
logger.error(f"{log_prefix} HeartFChatting: 麦麦的聊天主循环意外出错: {e_loop_outer}")
|
||
logger.error(traceback.format_exc())
|
||
finally:
|
||
# State reset is primarily handled by _handle_loop_completion callback
|
||
logger.info(f"{log_prefix} HeartFChatting: 麦麦的聊天主循环结束。")
|
||
|
||
async def _planner(self) -> Dict[str, Any]:
|
||
"""
|
||
规划器 (Planner): 使用LLM根据上下文决定是否和如何回复。
|
||
"""
|
||
log_prefix = self._get_log_prefix()
|
||
observed_messages: List[dict] = []
|
||
tool_result_info = {}
|
||
get_mid_memory_id = []
|
||
# send_emoji_from_tools = "" # Emoji suggested by tools
|
||
current_mind: Optional[str] = None
|
||
llm_error = False # Flag for LLM failure
|
||
|
||
# --- Ensure SubHeartflow is available ---
|
||
if not self.sub_hf:
|
||
# Attempt to re-fetch if missing (might happen if initialization order changes)
|
||
self.sub_hf = heartflow.get_subheartflow(self.stream_id)
|
||
if not self.sub_hf:
|
||
logger.error(f"{log_prefix}[Planner] SubHeartflow is not available. Cannot proceed.")
|
||
return {
|
||
"action": "error",
|
||
"reasoning": "SubHeartflow unavailable",
|
||
"llm_error": True,
|
||
"observed_messages": [],
|
||
}
|
||
|
||
try:
|
||
# Access observation via self.sub_hf
|
||
observation = self.sub_hf._get_primary_observation()
|
||
await observation.observe()
|
||
observed_messages = observation.talking_message
|
||
observed_messages_str = observation.talking_message_str
|
||
except Exception as e:
|
||
logger.error(f"{log_prefix}[Planner] 获取观察信息时出错: {e}")
|
||
# Handle error gracefully, maybe return an error state
|
||
observed_messages_str = "[Error getting observation]"
|
||
# Consider returning error here if observation is critical
|
||
# --- 结束获取观察信息 --- #
|
||
|
||
# --- (Moved from _replier_work) 1. 思考前使用工具 --- #
|
||
try:
|
||
# Access tool_user directly
|
||
tool_result = await self.tool_user.use_tool(
|
||
message_txt=observed_messages_str,
|
||
chat_stream=self.chat_stream,
|
||
observation=self.sub_hf._get_primary_observation(),
|
||
)
|
||
if tool_result.get("used_tools", False):
|
||
tool_result_info = tool_result.get("structured_info", {})
|
||
logger.debug(f"{log_prefix}[Planner] 规划前工具结果: {tool_result_info}")
|
||
|
||
get_mid_memory_id = [
|
||
mem["content"] for mem in tool_result_info.get("mid_chat_mem", []) if "content" in mem
|
||
]
|
||
|
||
except Exception as e_tool:
|
||
logger.error(f"{log_prefix}[Planner] 规划前工具使用失败: {e_tool}")
|
||
# --- 结束工具使用 --- #
|
||
|
||
# --- (Moved from _replier_work) 2. SubHeartflow 思考 --- #
|
||
try:
|
||
current_mind, _past_mind = await self.sub_hf.do_thinking_before_reply(
|
||
extra_info=tool_result_info,
|
||
obs_id=get_mid_memory_id,
|
||
)
|
||
# logger.debug(f"{log_prefix}[Planner] SubHF Mind: {current_mind}")
|
||
except Exception as e_subhf:
|
||
logger.error(f"{log_prefix}[Planner] SubHeartflow 思考失败: {e_subhf}")
|
||
current_mind = "[思考时出错]"
|
||
# --- 结束 SubHeartflow 思考 --- #
|
||
|
||
# --- 使用 LLM 进行决策 --- #
|
||
action = "no_reply" # Default action
|
||
emoji_query = "" # Default emoji query (used if action is emoji_reply or text_reply with emoji)
|
||
reasoning = "默认决策或获取决策失败"
|
||
|
||
try:
|
||
prompt = await self._build_planner_prompt(observed_messages_str, current_mind)
|
||
payload = {
|
||
"model": self.planner_llm.model_name,
|
||
"messages": [{"role": "user", "content": prompt}],
|
||
"tools": PLANNER_TOOL_DEFINITION,
|
||
"tool_choice": {"type": "function", "function": {"name": "decide_reply_action"}},
|
||
}
|
||
|
||
response = await self.planner_llm._execute_request(
|
||
endpoint="/chat/completions", payload=payload, prompt=prompt
|
||
)
|
||
|
||
if len(response) == 3:
|
||
_, _, tool_calls = response
|
||
if tool_calls and isinstance(tool_calls, list) and len(tool_calls) > 0:
|
||
tool_call = tool_calls[0]
|
||
if (
|
||
tool_call.get("type") == "function"
|
||
and tool_call.get("function", {}).get("name") == "decide_reply_action"
|
||
):
|
||
try:
|
||
arguments = json.loads(tool_call["function"]["arguments"])
|
||
action = arguments.get("action", "no_reply")
|
||
reasoning = arguments.get("reasoning", "未提供理由")
|
||
# Planner explicitly provides emoji query if action is emoji_reply or text_reply wants emoji
|
||
emoji_query = arguments.get("emoji_query", "")
|
||
logger.debug(
|
||
f"{log_prefix}[Planner] LLM Prompt: {prompt}\n决策: {action}, 理由: {reasoning}, EmojiQuery: '{emoji_query}'"
|
||
)
|
||
except json.JSONDecodeError as json_e:
|
||
logger.error(
|
||
f"{log_prefix}[Planner] 解析工具参数失败: {json_e}. Args: {tool_call['function'].get('arguments')}"
|
||
)
|
||
action = "error"
|
||
reasoning = "工具参数解析失败"
|
||
llm_error = True
|
||
except Exception as parse_e:
|
||
logger.error(f"{log_prefix}[Planner] 处理工具参数时出错: {parse_e}")
|
||
action = "error"
|
||
reasoning = "处理工具参数时出错"
|
||
llm_error = True
|
||
else:
|
||
logger.warning(
|
||
f"{log_prefix}[Planner] LLM 未按预期调用 'decide_reply_action' 工具。Tool calls: {tool_calls}"
|
||
)
|
||
action = "error"
|
||
reasoning = "LLM未调用预期工具"
|
||
llm_error = True
|
||
else:
|
||
logger.warning(f"{log_prefix}[Planner] LLM 响应中未包含有效的工具调用。Tool calls: {tool_calls}")
|
||
action = "error"
|
||
reasoning = "LLM响应无工具调用"
|
||
llm_error = True
|
||
else:
|
||
logger.warning(f"{log_prefix}[Planner] LLM 未返回预期的工具调用响应。Response parts: {len(response)}")
|
||
action = "error"
|
||
reasoning = "LLM响应格式错误"
|
||
llm_error = True
|
||
|
||
except Exception as llm_e:
|
||
logger.error(f"{log_prefix}[Planner] Planner LLM 调用失败: {llm_e}")
|
||
# logger.error(traceback.format_exc()) # Maybe too verbose for loop?
|
||
action = "error"
|
||
reasoning = f"LLM 调用失败: {llm_e}"
|
||
llm_error = True
|
||
# --- 结束 LLM 决策 --- #
|
||
|
||
return {
|
||
"action": action,
|
||
"reasoning": reasoning,
|
||
"emoji_query": emoji_query, # Explicit query from Planner/LLM
|
||
"current_mind": current_mind,
|
||
# "send_emoji_from_tools": send_emoji_from_tools, # Emoji suggested by tools (used as fallback)
|
||
"observed_messages": observed_messages,
|
||
"llm_error": llm_error,
|
||
}
|
||
|
||
async def _get_anchor_message(self, observed_messages: List[dict]) -> Optional[MessageRecv]:
|
||
"""
|
||
重构观察到的最后一条消息作为回复的锚点，
|
||
如果重构失败或观察为空，则创建一个占位符。
|
||
"""
|
||
|
||
try:
|
||
# --- Create Placeholder --- #
|
||
placeholder_id = f"mid_pf_{int(time.time() * 1000)}"
|
||
placeholder_user = UserInfo(
|
||
user_id="system_trigger", user_nickname="System Trigger", platform=self.chat_stream.platform
|
||
)
|
||
placeholder_msg_info = BaseMessageInfo(
|
||
message_id=placeholder_id,
|
||
platform=self.chat_stream.platform,
|
||
group_info=self.chat_stream.group_info,
|
||
user_info=placeholder_user,
|
||
time=time.time(),
|
||
)
|
||
placeholder_msg_dict = {
|
||
"message_info": placeholder_msg_info.to_dict(),
|
||
"processed_plain_text": "[System Trigger Context]",
|
||
"raw_message": "",
|
||
"time": placeholder_msg_info.time,
|
||
}
|
||
anchor_message = MessageRecv(placeholder_msg_dict)
|
||
anchor_message.update_chat_stream(self.chat_stream)
|
||
logger.info(
|
||
f"{self._get_log_prefix()} Created placeholder anchor message: ID={anchor_message.message_info.message_id}"
|
||
)
|
||
return anchor_message
|
||
|
||
except Exception as e:
|
||
logger.error(f"{self._get_log_prefix()} Error getting/creating anchor message: {e}")
|
||
logger.error(traceback.format_exc())
|
||
return None
|
||
|
||
# def _cleanup_thinking_message(self, thinking_id: str):
|
||
# """Safely removes the thinking message."""
|
||
# log_prefix = self._get_log_prefix()
|
||
# try:
|
||
# # Access MessageManager directly
|
||
# container = await message_manager.get_container(self.stream_id)
|
||
# # container.remove_message(thinking_id, msg_type=MessageThinking) # Need to find the message object first
|
||
# found_msg = None
|
||
# for msg in container.get_all_messages():
|
||
# if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
|
||
# found_msg = msg
|
||
# break
|
||
# if found_msg:
|
||
# container.remove_message(found_msg)
|
||
# logger.debug(f"{log_prefix} Cleaned up thinking message {thinking_id}.")
|
||
# else:
|
||
# logger.warning(f"{log_prefix} Could not find thinking message {thinking_id} to cleanup.")
|
||
# except Exception as e:
|
||
# logger.error(f"{log_prefix} Error cleaning up thinking message {thinking_id}: {e}")
|
||
|
||
# --- 发送器 (Sender) --- #
|
||
async def _sender(
|
||
self,
|
||
thinking_id: str,
|
||
anchor_message: MessageRecv,
|
||
response_set: List[str],
|
||
send_emoji: str, # Emoji query decided by planner or tools
|
||
):
|
||
"""
|
||
发送器 (Sender): 使用本类的方法发送生成的回复。
|
||
处理相关的操作，如发送表情和更新关系。
|
||
"""
|
||
log_prefix = self._get_log_prefix()
|
||
|
||
first_bot_msg: Optional[MessageSending] = None
|
||
# 尝试发送回复消息
|
||
first_bot_msg = await self._send_response_messages(anchor_message, response_set, thinking_id)
|
||
if first_bot_msg:
|
||
# --- 处理关联表情(如果指定) --- #
|
||
if send_emoji:
|
||
logger.info(f"{log_prefix}[Sender-{thinking_id}] 正在发送关联表情: '{send_emoji}'")
|
||
# 优先使用first_bot_msg作为锚点，否则回退到原始锚点
|
||
emoji_anchor = first_bot_msg if first_bot_msg else anchor_message
|
||
await self._handle_emoji(emoji_anchor, response_set, send_emoji)
|
||
|
||
else:
|
||
# logger.warning(f"{log_prefix}[Sender-{thinking_id}] 发送回复失败(_send_response_messages返回None)。思考消息{thinking_id}可能已被移除。")
|
||
# 无需清理，因为_send_response_messages返回None意味着已处理/已删除
|
||
raise RuntimeError("发送回复失败，_send_response_messages返回None")
|
||
|
||
async def shutdown(self):
|
||
"""
|
||
Gracefully shuts down the HeartFChatting instance by cancelling the active loop task.
|
||
"""
|
||
log_prefix = self._get_log_prefix()
|
||
logger.info(f"{log_prefix} Shutting down HeartFChatting...")
|
||
if self._loop_task and not self._loop_task.done():
|
||
logger.info(f"{log_prefix} Cancelling active PF loop task.")
|
||
self._loop_task.cancel()
|
||
try:
|
||
await asyncio.wait_for(self._loop_task, timeout=1.0) # Shorter timeout?
|
||
except asyncio.CancelledError:
|
||
logger.info(f"{log_prefix} PF loop task cancelled successfully.")
|
||
except asyncio.TimeoutError:
|
||
logger.warning(f"{log_prefix} Timeout waiting for PF loop task cancellation.")
|
||
except Exception as e:
|
||
logger.error(f"{log_prefix} Error during loop task cancellation: {e}")
|
||
else:
|
||
logger.info(f"{log_prefix} No active PF loop task found to cancel.")
|
||
|
||
self._loop_active = False
|
||
self._loop_task = None
|
||
if self._processing_lock.locked():
|
||
logger.warning(f"{log_prefix} Releasing processing lock during shutdown.")
|
||
self._processing_lock.release()
|
||
logger.info(f"{log_prefix} HeartFChatting shutdown complete.")
|
||
|
||
async def _build_planner_prompt(self, observed_messages_str: str, current_mind: Optional[str]) -> str:
|
||
"""构建 Planner LLM 的提示词"""
|
||
|
||
prompt = f"你的名字是 {global_config.BOT_NICKNAME}。是一个女大二学生，正在QQ聊天，正在决定是否以及如何回应当前的聊天。\n"
|
||
|
||
if observed_messages_str:
|
||
prompt += "观察到的最新聊天内容如下 (最近的消息在最后)：\n---\n"
|
||
prompt += observed_messages_str
|
||
prompt += "\n---"
|
||
else:
|
||
prompt += "当前没有观察到新的聊天内容。\n"
|
||
|
||
prompt += "\n看了以上内容，你产生的内心想法是："
|
||
if current_mind:
|
||
prompt += f"\n---\n{current_mind}\n---\n\n"
|
||
else:
|
||
prompt += " [没有特别的想法] \n\n"
|
||
|
||
prompt += (
|
||
"请结合你的内心想法和观察到的聊天内容，分析情况并使用 'decide_reply_action' 工具来决定你的最终行动。\n"
|
||
"决策依据：\n"
|
||
"1. 如果聊天内容无聊、与你无关、或者你的内心想法认为不适合回复（例如在讨论你不懂或不感兴趣的话题），选择 'no_reply'。\n"
|
||
"2. 如果聊天内容值得回应，且适合用文字表达（参考你的内心想法），选择 'text_reply'。如果你有情绪想表达，想在文字后追加一个表达情绪的表情，请同时提供 'emoji_query' (例如：'开心的'、'惊讶的')。\n"
|
||
"3. 如果聊天内容或你的内心想法适合用一个表情来回应（例如表示赞同、惊讶、无语等），选择 'emoji_reply' 并提供表情主题 'emoji_query'。\n"
|
||
"4. 如果最后一条消息是你自己发的，并且之后没有人回复你，通常选择 'no_reply'，除非有特殊原因需要追问。\n"
|
||
"5. 除非大家都在这么做，或者有特殊理由，否则不要重复别人刚刚说过的话或简单附和。\n"
|
||
"6. 表情包是用来表达情绪的，不要直接回复或评价别人的表情包，而是根据对话内容和情绪选择是否用表情回应。\n"
|
||
"7. 如果观察到的内容只有你自己的发言，选择 'no_reply'。\n"
|
||
"8. 不要回复你自己的话，不要把自己的话当做别人说的。\n"
|
||
"必须调用 'decide_reply_action' 工具并提供 'action' 和 'reasoning'。如果选择了 'emoji_reply' 或者选择了 'text_reply' 并想追加表情，则必须提供 'emoji_query'。"
|
||
)
|
||
|
||
return prompt
|
||
|
||
# --- 回复器 (Replier) 的定义 --- #
|
||
async def _replier_work(
|
||
self,
|
||
reason: str,
|
||
anchor_message: MessageRecv,
|
||
thinking_id: str,
|
||
) -> Optional[List[str]]:
|
||
"""
|
||
回复器 (Replier): 核心逻辑用于生成回复。
|
||
"""
|
||
log_prefix = self._get_log_prefix()
|
||
response_set: Optional[List[str]] = None
|
||
try:
|
||
# --- Generate Response with LLM --- #
|
||
# Access gpt instance directly
|
||
# logger.debug(f"{log_prefix}[Replier-{thinking_id}] Calling LLM to generate response...")
|
||
|
||
# Ensure generate_response has access to current_mind if it's crucial context
|
||
# Access gpt_instance directly
|
||
response_set = await self.gpt_instance.generate_response(
|
||
current_mind_info=self.sub_hf.current_mind,
|
||
reason=reason,
|
||
message=anchor_message, # Pass anchor_message positionally (matches 'message' parameter)
|
||
thinking_id=thinking_id, # Pass thinking_id positionally
|
||
)
|
||
|
||
if not response_set:
|
||
logger.warning(f"{log_prefix}[Replier-{thinking_id}] LLM生成了一个空回复集。")
|
||
return None
|
||
|
||
# --- 准备并返回结果 --- #
|
||
# logger.info(f"{log_prefix}[Replier-{thinking_id}] 成功生成了回复集: {' '.join(response_set)[:50]}...")
|
||
return response_set
|
||
|
||
except Exception as e:
|
||
logger.error(f"{log_prefix}[Replier-{thinking_id}] Unexpected error in replier_work: {e}")
|
||
logger.error(traceback.format_exc())
|
||
return None
|
||
|
||
# --- Methods moved from HeartFCController start ---
|
||
async def _create_thinking_message(self, anchor_message: Optional[MessageRecv]) -> Optional[str]:
|
||
"""创建思考消息 (尝试锚定到 anchor_message)"""
|
||
if not anchor_message or not anchor_message.chat_stream:
|
||
logger.error(f"{self._get_log_prefix()} 无法创建思考消息，缺少有效的锚点消息或聊天流。")
|
||
return None
|
||
|
||
chat = anchor_message.chat_stream
|
||
messageinfo = anchor_message.message_info
|
||
bot_user_info = UserInfo(
|
||
user_id=global_config.BOT_QQ,
|
||
user_nickname=global_config.BOT_NICKNAME,
|
||
platform=messageinfo.platform,
|
||
)
|
||
|
||
thinking_time_point = round(time.time(), 2)
|
||
thinking_id = "mt" + str(thinking_time_point)
|
||
thinking_message = MessageThinking(
|
||
message_id=thinking_id,
|
||
chat_stream=chat,
|
||
bot_user_info=bot_user_info,
|
||
reply=anchor_message, # 回复的是锚点消息
|
||
thinking_start_time=thinking_time_point,
|
||
)
|
||
# Access MessageManager directly
|
||
await message_manager.add_message(thinking_message)
|
||
return thinking_id
|
||
|
||
async def _send_response_messages(
|
||
self, anchor_message: Optional[MessageRecv], response_set: List[str], thinking_id: str
|
||
) -> Optional[MessageSending]:
|
||
"""发送回复消息 (尝试锚定到 anchor_message)"""
|
||
if not anchor_message or not anchor_message.chat_stream:
|
||
logger.error(f"{self._get_log_prefix()} 无法发送回复，缺少有效的锚点消息或聊天流。")
|
||
return None
|
||
|
||
chat = anchor_message.chat_stream
|
||
# Access MessageManager directly
|
||
container = await message_manager.get_container(chat.stream_id)
|
||
thinking_message = None
|
||
|
||
# 移除思考消息
|
||
for msg in container.messages[:]: # Iterate over a copy
|
||
if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
|
||
thinking_message = msg
|
||
container.messages.remove(msg) # Remove the message directly here
|
||
logger.debug(f"{self._get_log_prefix()} Removed thinking message {thinking_id} via iteration.")
|
||
break
|
||
|
||
if not thinking_message:
|
||
stream_name = chat_manager.get_stream_name(chat.stream_id) or chat.stream_id # 获取流名称
|
||
logger.warning(f"[{stream_name}] {thinking_id}，思考太久了，超时被移除")
|
||
return None
|
||
|
||
thinking_start_time = thinking_message.thinking_start_time
|
||
message_set = MessageSet(chat, thinking_id)
|
||
mark_head = False
|
||
first_bot_msg = None
|
||
bot_user_info = UserInfo(
|
||
user_id=global_config.BOT_QQ,
|
||
user_nickname=global_config.BOT_NICKNAME,
|
||
platform=anchor_message.message_info.platform,
|
||
)
|
||
for msg_text in response_set:
|
||
message_segment = Seg(type="text", data=msg_text)
|
||
bot_message = MessageSending(
|
||
message_id=thinking_id, # 使用 thinking_id 作为批次标识
|
||
chat_stream=chat,
|
||
bot_user_info=bot_user_info,
|
||
sender_info=anchor_message.message_info.user_info, # 发送给锚点消息的用户
|
||
message_segment=message_segment,
|
||
reply=anchor_message, # 回复锚点消息
|
||
is_head=not mark_head,
|
||
is_emoji=False,
|
||
thinking_start_time=thinking_start_time,
|
||
)
|
||
if not mark_head:
|
||
mark_head = True
|
||
first_bot_msg = bot_message
|
||
message_set.add_message(bot_message)
|
||
|
||
# Access MessageManager directly
|
||
await message_manager.add_message(message_set)
|
||
return first_bot_msg
|
||
|
||
async def _handle_emoji(self, anchor_message: Optional[MessageRecv], response_set: List[str], send_emoji: str = ""):
|
||
"""处理表情包 (尝试锚定到 anchor_message)"""
|
||
|
||
if not anchor_message or not anchor_message.chat_stream:
|
||
logger.error(f"{self._get_log_prefix()} 无法处理表情包，缺少有效的锚点消息或聊天流。")
|
||
return
|
||
|
||
chat = anchor_message.chat_stream
|
||
# Access emoji_manager directly
|
||
# emoji_manager_instance = self.heartfc_controller.emoji_manager # Removed
|
||
if send_emoji:
|
||
# Use self.emoji_manager directly
|
||
emoji_raw = await self.emoji_manager.get_emoji_for_text(send_emoji)
|
||
else:
|
||
emoji_text_source = "".join(response_set) if response_set else ""
|
||
# Use self.emoji_manager directly
|
||
emoji_raw = await self.emoji_manager.get_emoji_for_text(emoji_text_source)
|
||
|
||
if emoji_raw:
|
||
emoji_path, _description = emoji_raw
|
||
emoji_cq = image_path_to_base64(emoji_path)
|
||
thinking_time_point = round(time.time(), 2)
|
||
message_segment = Seg(type="emoji", data=emoji_cq)
|
||
bot_user_info = UserInfo(
|
||
user_id=global_config.BOT_QQ,
|
||
user_nickname=global_config.BOT_NICKNAME,
|
||
platform=anchor_message.message_info.platform,
|
||
)
|
||
bot_message = MessageSending(
|
||
message_id="me" + str(thinking_time_point), # 使用不同的 ID 前缀?
|
||
chat_stream=chat,
|
||
bot_user_info=bot_user_info,
|
||
sender_info=anchor_message.message_info.user_info,
|
||
message_segment=message_segment,
|
||
reply=anchor_message, # 回复锚点消息
|
||
is_head=False,
|
||
is_emoji=True,
|
||
)
|
||
# Access MessageManager directly
|
||
await message_manager.add_message(bot_message)
|