diff --git a/src/chat/heart_flow/heartFC_chat.py b/src/chat/heart_flow/heartFC_chat.py index 9745fd81..5b840aee 100644 --- a/src/chat/heart_flow/heartFC_chat.py +++ b/src/chat/heart_flow/heartFC_chat.py @@ -381,21 +381,26 @@ class HeartFChatting: action_success = False action_reply_text = "" + excute_result_str = "" for result in results: + excute_result_str += f"{result['action_type']} 执行结果:{result['result']}\n" + if isinstance(result, BaseException): logger.error(f"{self.log_prefix} 动作执行异常: {result}") continue if result["action_type"] != "reply": action_success = result["success"] - action_reply_text = result["reply_text"] + action_reply_text = result["result"] elif result["action_type"] == "reply": if result["success"]: reply_loop_info = result["loop_info"] - reply_text_from_reply = result["reply_text"] + reply_text_from_reply = result["result"] else: logger.warning(f"{self.log_prefix} 回复动作执行失败") + self.action_planner.add_plan_excute_log(result=excute_result_str) + # 构建最终的循环信息 if reply_loop_info: # 如果有回复信息，使用回复的loop_info作为基础 @@ -490,23 +495,19 @@ class HeartFChatting: except Exception as e: logger.error(f"{self.log_prefix} 创建动作处理器时出错: {e}") traceback.print_exc() - return False, "", "" - - if not action_handler: - logger.warning(f"{self.log_prefix} 未能创建动作处理器: {action}") - return False, "", "" + return False, "" # 处理动作并获取结果（固定记录一次动作信息） result = await action_handler.execute() success, action_text = result - command = "" - return success, action_text, command + + return success, action_text except Exception as e: logger.error(f"{self.log_prefix} 处理{action}时出错: {e}") traceback.print_exc() - return False, "", "" + return False, "" async def _send_response( self, @@ -581,7 +582,7 @@ class HeartFChatting: ) - return {"action_type": "no_reply", "success": True, "reply_text": "", "command": ""} + return {"action_type": "no_reply", "success": True, "result": "选择不回复", "command": ""} elif action_planner_info.action_type == "no_reply_until_call": # 直接当场执行no_reply_until_call逻辑 @@ -601,46 +602,44 @@ class HeartFChatting: ) - return {"action_type": "no_reply_until_call", "success": True, "reply_text": "", "command": ""} + return {"action_type": "no_reply_until_call", "success": True, "result": "保持沉默，直到有人直接叫的名字", "command": ""} elif action_planner_info.action_type == "reply": # 直接当场执行reply逻辑 - try: - reason = action_planner_info.reasoning or "选择回复" - await database_api.store_action_info( - chat_stream=self.chat_stream, - action_build_into_prompt=False, - action_prompt_display=reason, - action_done=True, - thinking_id=thinking_id, - action_data={}, - action_name="reply", - action_reasoning=reason, - ) - success, llm_response = await generator_api.generate_reply( - chat_stream=self.chat_stream, - reply_message=action_planner_info.action_message, - available_actions=available_actions, - chosen_actions=chosen_action_plan_infos, - reply_reason=reason, - enable_tool=global_config.tool.enable_tool, - request_type="replyer", - from_plugin=False, - ) + reason = action_planner_info.reasoning or "选择回复" + await database_api.store_action_info( + chat_stream=self.chat_stream, + action_build_into_prompt=False, + action_prompt_display=reason, + action_done=True, + thinking_id=thinking_id, + action_data={}, + action_name="reply", + action_reasoning=reason, + ) + + success, llm_response = await generator_api.generate_reply( + chat_stream=self.chat_stream, + reply_message=action_planner_info.action_message, + available_actions=available_actions, + chosen_actions=chosen_action_plan_infos, + reply_reason=reason, + enable_tool=global_config.tool.enable_tool, + request_type="replyer", + from_plugin=False, + ) + + if not success or not llm_response or not llm_response.reply_set: + if action_planner_info.action_message: + logger.info( + f"对 {action_planner_info.action_message.processed_plain_text} 的回复生成失败" + ) + else: + logger.info("回复生成失败") + return {"action_type": "reply", "success": False, "result": "回复生成失败", "loop_info": None} - if not success or not llm_response or not llm_response.reply_set: - if action_planner_info.action_message: - logger.info( - f"对 {action_planner_info.action_message.processed_plain_text} 的回复生成失败" - ) - else: - logger.info("回复生成失败") - return {"action_type": "reply", "success": False, "reply_text": "", "loop_info": None} - except asyncio.CancelledError: - logger.debug(f"{self.log_prefix} 并行执行：回复生成任务已被取消") - return {"action_type": "reply", "success": False, "reply_text": "", "loop_info": None} response_set = llm_response.reply_set selected_expressions = llm_response.selected_expressions loop_info, reply_text, _ = await self._send_and_store_reply( @@ -654,13 +653,13 @@ class HeartFChatting: return { "action_type": "reply", "success": True, - "reply_text": reply_text, + "result": f"你回复内容{reply_text}", "loop_info": loop_info, } else: # 执行普通动作 with Timer("动作执行", cycle_timers): - success, reply_text, command = await self._handle_action( + success, result = await self._handle_action( action = action_planner_info.action_type, action_reasoning = action_planner_info.action_reasoning or "", action_data = action_planner_info.action_data or {}, @@ -671,8 +670,7 @@ class HeartFChatting: return { "action_type": action_planner_info.action_type, "success": success, - "reply_text": reply_text, - "command": command, + "result": result, } except Exception as e: @@ -681,7 +679,7 @@ class HeartFChatting: return { "action_type": action_planner_info.action_type, "success": False, - "reply_text": "", + "result": "", "loop_info": None, "error": str(e), } diff --git a/src/chat/planner_actions/planner.py b/src/chat/planner_actions/planner.py index 2e642d9d..1e773bbd 100644 --- a/src/chat/planner_actions/planner.py +++ b/src/chat/planner_actions/planner.py @@ -3,7 +3,7 @@ import time import traceback import random import re -from typing import Dict, Optional, Tuple, List, TYPE_CHECKING +from typing import Dict, Optional, Tuple, List, TYPE_CHECKING, Union from rich.traceback import install from datetime import datetime from json_repair import repair_json @@ -132,7 +132,7 @@ class ActionPlanner: self.last_obs_time_mark = 0.0 - self.plan_log:List[Tuple[str,str,ActionPlannerInfo]] = [] + self.plan_log: List[Tuple[str, float, Union[List[ActionPlannerInfo], str]]] = [] def find_message_by_id( self, message_id: str, message_id_list: List[Tuple[str, "DatabaseMessages"]] @@ -293,14 +293,24 @@ class ActionPlanner: def add_plan_log(self, reasoning: str, actions: List[ActionPlannerInfo]): self.plan_log.append((reasoning, time.time(), actions)) - if len(self.plan_log) > 100: + if len(self.plan_log) > 20: + self.plan_log.pop(0) + + def add_plan_excute_log(self, result: str): + self.plan_log.append(("", time.time(), result)) + if len(self.plan_log) > 20: self.plan_log.pop(0) def get_plan_log_str(self) -> str: plan_log_str = "" - for reasoning, time, actions in self.plan_log: - time = datetime.fromtimestamp(time).strftime("%H:%M:%S") - plan_log_str += f"{time}:{reasoning}|使用了{','.join([action.action_type for action in actions])}\n" + for reasoning, time, content in self.plan_log: + if isinstance(content, list) and all(isinstance(action, ActionPlannerInfo) for action in content): + time = datetime.fromtimestamp(time).strftime("%H:%M:%S") + plan_log_str += f"{time}:{reasoning}|你使用了{','.join([action.action_type for action in content])}\n" + else: + time = datetime.fromtimestamp(time).strftime("%H:%M:%S") + plan_log_str += f"{time}:{content}\n" + return plan_log_str