mirror of https://github.com/Mai-with-u/MaiBot.git
Implement chat type-aware processing for private and group chats
Cursor Agent
parent
918aa57b01
commit
6fce7f8dcd
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@ -383,8 +383,21 @@ class HeartFChatting:
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task_to_name_map = {}
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processor_time_costs = {} # 新增: 记录每个处理器耗时
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# 获取聊天类型
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chat_stream = await asyncio.to_thread(chat_manager.get_stream, self.stream_id)
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is_group_chat = chat_stream.group_info is not None
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# 根据聊天类型选择处理器
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selected_processors = []
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for processor in self.processors:
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processor_name = processor.__class__.log_prefix
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# 私聊时跳过某些处理器
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if not is_group_chat and processor_name in ["MindProcessor", "ToolProcessor"]:
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continue
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selected_processors.append(processor)
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for processor in selected_processors:
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processor_name = processor.__class__.log_prefix
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async def run_with_timeout(proc=processor):
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return await asyncio.wait_for(
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@ -465,9 +478,14 @@ class HeartFChatting:
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self.all_observations = observations
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# 获取聊天类型
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chat_stream = await asyncio.to_thread(chat_manager.get_stream, self.stream_id)
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is_group_chat = chat_stream.group_info is not None
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with Timer("调整动作", cycle_timers):
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# 处理特殊的观察
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await self.action_modifier.modify_actions(observations=observations)
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if is_group_chat: # 只在群聊中调整动作
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await self.action_modifier.modify_actions(observations=observations)
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await self.action_observation.observe()
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observations.append(self.action_observation)
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@ -497,59 +515,41 @@ class HeartFChatting:
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}
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with Timer("规划器", cycle_timers):
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plan_result = await self.action_planner.plan(all_plan_info, running_memorys)
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# 私聊时使用简单规划
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if not is_group_chat:
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plan_result = await self.action_planner.plan_simple(all_plan_info, running_memorys)
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else:
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plan_result = await self.action_planner.plan(all_plan_info, running_memorys)
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loop_plan_info = {
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"action_result": plan_result.get("action_result", {}),
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"current_mind": plan_result.get("current_mind", ""),
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"observed_messages": plan_result.get("observed_messages", ""),
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}
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loop_plan_info = {
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"action_result": plan_result,
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}
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with Timer("执行动作", cycle_timers):
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action_type, action_data, reasoning = (
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plan_result.get("action_result", {}).get("action_type", "error"),
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plan_result.get("action_result", {}).get("action_data", {}),
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plan_result.get("action_result", {}).get("reasoning", "未提供理由"),
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action_taken, action_command, action_reason = await self._handle_action(
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action=plan_result["action_type"],
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reasoning=plan_result["reasoning"],
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action_data=plan_result["action_data"],
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cycle_timers=cycle_timers,
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thinking_id=thinking_id,
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)
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if action_type == "reply":
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action_str = "回复"
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elif action_type == "no_reply":
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action_str = "不回复"
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else:
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action_str = action_type
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loop_action_info = {
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"action_taken": action_taken,
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"command": action_command,
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"reason": action_reason,
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}
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logger.debug(f"{self.log_prefix} 麦麦想要：'{action_str}', 原因'{reasoning}'")
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success, reply_text, command = await self._handle_action(
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action_type, reasoning, action_data, cycle_timers, thinking_id
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)
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loop_action_info = {
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"action_taken": success,
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"reply_text": reply_text,
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"command": command,
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"taken_time": time.time(),
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}
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loop_info = {
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return {
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"loop_observation_info": loop_observation_info,
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"loop_processor_info": loop_processor_info,
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"loop_plan_info": loop_plan_info,
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"loop_action_info": loop_action_info,
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}
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return loop_info
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except Exception as e:
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logger.error(f"{self.log_prefix} FOCUS聊天处理失败: {e}")
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logger.error(traceback.format_exc())
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return {
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"loop_observation_info": {},
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"loop_processor_info": {},
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"loop_plan_info": {},
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"loop_action_info": {"action_taken": False, "reply_text": "", "command": ""},
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}
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logger.error(f"{self.log_prefix} 循环处理出错: {e}")
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traceback.print_exc()
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raise
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async def _handle_action(
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self,
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@ -16,6 +16,8 @@ from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
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from src.individuality.individuality import individuality
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from src.chat.focus_chat.planners.action_manager import ActionManager
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from json_repair import repair_json
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from src.chat.focus_chat.info.chat_info import ChattingInfo
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from src.chat.focus_chat.info.workingmemory_info import WorkingMemoryInfo
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logger = get_logger("planner")
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@ -85,6 +87,61 @@ class ActionPlanner:
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self.action_manager = action_manager
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async def plan_simple(self, all_plan_info: List[InfoBase], running_memorys: List[Dict[str, Any]]) -> Dict[str, Any]:
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"""
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为私聊提供的简单规划方法。
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主要关注ChattingInfo和WorkingMemory，不考虑复杂的心智状态和工具使用。
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Args:
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all_plan_info: 所有处理器提供的信息
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running_memorys: 当前激活的记忆
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Returns:
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Dict[str, Any]: 包含action_type, action_data和reasoning的字典
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"""
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# 提取聊天信息
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chatting_info = None
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working_memory_info = None
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for info in all_plan_info:
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if isinstance(info, ChattingInfo):
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chatting_info = info
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elif isinstance(info, WorkingMemoryInfo):
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working_memory_info = info
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if not chatting_info:
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return {
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"action_type": "no_reply",
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"action_data": {},
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"reasoning": "没有检测到新的聊天信息",
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}
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# 检查是否有新消息需要回复
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if not chatting_info.new_messages:
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return {
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"action_type": "no_reply",
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"action_data": {},
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"reasoning": "没有新消息需要回复",
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}
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# 获取最新消息
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latest_message = chatting_info.new_messages[-1]
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# 检查工作记忆中是否有相关上下文
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context = ""
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if working_memory_info and working_memory_info.related_memory:
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context = working_memory_info.related_memory
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# 构建回复动作
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return {
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"action_type": "reply",
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"action_data": {
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"message": latest_message,
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"context": context,
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"style": "direct", # 私聊使用直接回复风格
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},
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"reasoning": "收到新的私聊消息，直接回复",
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}
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async def plan(self, all_plan_info: List[InfoBase], running_memorys: List[Dict[str, Any]]) -> Dict[str, Any]:
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"""
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规划器 (Planner): 使用LLM根据上下文决定做出什么动作。
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@ -219,7 +219,7 @@ class SubHeartflowManager:
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"""
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接收来自 HeartFChatting 的请求，将特定子心流的状态转换为 NORMAL。
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通常在连续多次 "no_reply" 后被调用。
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对于私聊和群聊，都转换为 NORMAL。
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对于群聊转换为 NORMAL，对于私聊转换为 ABSENT。
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Args:
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subflow_id: 需要转换状态的子心流 ID。
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@ -234,8 +234,9 @@ class SubHeartflowManager:
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current_state = subflow.chat_state.chat_status
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if current_state == ChatState.FOCUSED:
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target_state = ChatState.NORMAL
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log_reason = "转为NORMAL"
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# 根据聊天类型决定目标状态
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target_state = ChatState.NORMAL if subflow.is_group_chat else ChatState.ABSENT
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log_reason = "转为NORMAL" if subflow.is_group_chat else "转为ABSENT(私聊)"
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logger.info(
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f"[状态转换请求] 接收到请求，将 {stream_name} (当前: {current_state.value}) 尝试转换为 {target_state.value} ({log_reason})"
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