from typing import List, Dict, Any from .chat_observer import ChatObserver from src.common.logger_manager import get_logger from src.chat.models.utils_model import LLMRequest from src.chat.person_info.person_info import person_info_manager from src.chat.person_info.relationship_manager import relationship_manager from src.chat.utils.chat_message_builder import build_readable_messages from .observation_info import ObservationInfo from .conversation_info import ConversationInfo from .pfc_utils import get_items_from_json, adjust_relationship_value_nonlinear from src.config.config import global_config # 导入全局配置 (向上两级到 src/, 再到 config) logger = get_logger("pfc_relationship") class PfcRelationshipUpdater: def __init__(self, private_name: str, bot_name: str): """ 初始化关系更新器。 Args: private_name (str): 当前私聊对象的名称 (用于日志)。 bot_name (str): 机器人自己的名称。 """ self.private_name = private_name self.bot_name = bot_name self.person_info_mng = person_info_manager self.relationship_mng = relationship_manager # 复用其实例方法 # LLM 实例 (为关系评估创建一个新的) # 尝试读取 llm_PFC_relationship_eval 配置，如果不存在则回退 llm_config_rel_eval = getattr(global_config, "llm_PFC_relationship_eval", None) if llm_config_rel_eval and isinstance(llm_config_rel_eval, dict): logger.info(f"[私聊][{self.private_name}] 使用 llm_PFC_relationship_eval 配置初始化关系评估LLM。") self.llm = LLMRequest( model=llm_config_rel_eval, temperature=llm_config_rel_eval.get("temp", 0.5), # 判断任务通常用较低温度 max_tokens=llm_config_rel_eval.get("max_tokens", 512), request_type="pfc_relationship_evaluation", ) else: logger.warning( f"[私聊][{self.private_name}] 未找到 llm_PFC_relationship_eval 配置或配置无效，将回退使用 llm_PFC_action_planner 的配置。" ) llm_config_action_planner = getattr(global_config, "llm_PFC_action_planner", None) if llm_config_action_planner and isinstance(llm_config_action_planner, dict): self.llm = LLMRequest( model=llm_config_action_planner, # 使用 action_planner 的模型配置 temperature=llm_config_action_planner.get("temp", 0.5), # 但温度可以尝试低一些 max_tokens=llm_config_action_planner.get("max_tokens", 512), request_type="pfc_relationship_evaluation_fallback", ) else: # 极端情况，连 action_planner 的配置都没有 logger.error(f"[私聊][{self.private_name}] 无法找到任何有效的LLM配置用于关系评估！关系更新功能将受限。") self.llm = None # LLM 未初始化 # 从 global_config 读取参数，若无则使用默认值 self.REL_INCREMENTAL_INTERVAL = getattr(global_config, "pfc_relationship_incremental_interval", 10) self.REL_INCREMENTAL_MSG_COUNT = getattr(global_config, "pfc_relationship_incremental_msg_count", 10) self.REL_INCREMENTAL_DEFAULT_CHANGE = getattr(global_config, "pfc_relationship_incremental_default_change", 1.0) self.REL_INCREMENTAL_MAX_CHANGE = getattr(global_config, "pfc_relationship_incremental_max_change", 5.0) self.REL_FINAL_MSG_COUNT = getattr(global_config, "pfc_relationship_final_msg_count", 30) self.REL_FINAL_DEFAULT_CHANGE = getattr(global_config, "pfc_relationship_final_default_change", 5.0) self.REL_FINAL_MAX_CHANGE = getattr(global_config, "pfc_relationship_final_max_change", 50.0) async def update_relationship_incremental( self, conversation_info: ConversationInfo, observation_info: ObservationInfo, chat_observer_for_history: ChatObserver, # ChatObserver 实例 ) -> None: if not self.llm: logger.error(f"[私聊][{self.private_name}] LLM未初始化，无法进行增量关系更新。") return if not conversation_info or not conversation_info.person_id or not observation_info: logger.debug(f"[私聊][{self.private_name}] 增量关系更新：缺少必要信息。") return if not ( conversation_info.current_instance_message_count % self.REL_INCREMENTAL_INTERVAL == 0 and conversation_info.current_instance_message_count > 0 ): return logger.info( f"[私聊][{self.private_name}] 达到增量关系更新阈值 ({conversation_info.current_instance_message_count}条消息)，开始评估..." ) messages_for_eval: List[Dict[str, Any]] = [] if chat_observer_for_history: messages_for_eval = chat_observer_for_history.get_cached_messages(limit=self.REL_INCREMENTAL_MSG_COUNT) elif observation_info.chat_history: messages_for_eval = observation_info.chat_history[-self.REL_INCREMENTAL_MSG_COUNT :] if not messages_for_eval: logger.warning(f"[私聊][{self.private_name}] 增量关系更新：没有足够的消息进行评估。") return readable_history_for_llm = await build_readable_messages( messages_for_eval, replace_bot_name=True, merge_messages=False, timestamp_mode="relative" ) current_relationship_value = await self.person_info_mng.get_value( conversation_info.person_id, "relationship_value" ) current_relationship_value = self.relationship_mng.ensure_float( current_relationship_value, conversation_info.person_id ) relationship_prompt = f"""你是{self.bot_name}。你正在与{self.private_name}私聊。 你们当前的关系值大约是 {current_relationship_value:.0f} (范围通常在-1000到1000，越高越代表关系越好)。 以下是你们最近的对话内容： --- {readable_history_for_llm} --- 请基于以上对话，判断你与{self.private_name}的关系值应该如何“谨慎地”调整。 请输出一个JSON对象，包含一个 "adjustment" 字段，其值为一个介于 -{self.REL_INCREMENTAL_MAX_CHANGE} 和 +{self.REL_INCREMENTAL_MAX_CHANGE} 之间的整数，代表关系值的变化。 例如：{{ "adjustment": 3 }}。如果对话内容不明确或难以判断，请倾向于输出较小的调整值（如0, 1, -1）。""" raw_adjustment_val = self.REL_INCREMENTAL_DEFAULT_CHANGE try: logger.debug(f"[私聊][{self.private_name}] 增量关系评估Prompt:\n{relationship_prompt}") content, _ = await self.llm.generate_response_async(relationship_prompt) logger.debug(f"[私聊][{self.private_name}] 增量关系评估LLM原始返回: {content}") success, result = get_items_from_json( content, self.private_name, "adjustment", default_values={"adjustment": self.REL_INCREMENTAL_DEFAULT_CHANGE}, required_types={"adjustment": (int, float)}, ) raw_adjustment = result.get("adjustment", self.REL_INCREMENTAL_DEFAULT_CHANGE) if not isinstance(raw_adjustment, (int, float)): raw_adjustment_val = self.REL_INCREMENTAL_DEFAULT_CHANGE else: raw_adjustment_val = float(raw_adjustment) raw_adjustment_val = max( -self.REL_INCREMENTAL_MAX_CHANGE, min(self.REL_INCREMENTAL_MAX_CHANGE, raw_adjustment_val) ) except Exception as e: logger.error(f"[私聊][{self.private_name}] 增量关系评估LLM调用或解析失败: {e}") adjustment_val = await adjust_relationship_value_nonlinear(current_relationship_value, raw_adjustment_val) new_relationship_value = max(-1000.0, min(1000.0, current_relationship_value + adjustment_val)) await self.person_info_mng.update_one_field( conversation_info.person_id, "relationship_value", new_relationship_value ) logger.info( f"[私聊][{self.private_name}] 增量关系值更新：与【{self.private_name}】的关系值从 {current_relationship_value:.2f} 调整了 {adjustment_val:.2f}，变为 {new_relationship_value:.2f}" ) if conversation_info.person_id: conversation_info.relationship_text = await self.relationship_mng.build_relationship_info( conversation_info.person_id, is_id=True ) async def update_relationship_final( self, conversation_info: ConversationInfo, observation_info: ObservationInfo, chat_observer_for_history: ChatObserver, ) -> None: if not self.llm: logger.error(f"[私聊][{self.private_name}] LLM未初始化，无法进行最终关系更新。") return if not conversation_info or not conversation_info.person_id or not observation_info: logger.debug(f"[私聊][{self.private_name}] 最终关系更新：缺少必要信息。") return logger.info(f"[私聊][{self.private_name}] 私聊结束，开始最终关系评估...") messages_for_eval: List[Dict[str, Any]] = [] if chat_observer_for_history: messages_for_eval = chat_observer_for_history.get_cached_messages(limit=self.REL_FINAL_MSG_COUNT) elif observation_info.chat_history: messages_for_eval = observation_info.chat_history[-self.REL_FINAL_MSG_COUNT :] if not messages_for_eval: logger.warning(f"[私聊][{self.private_name}] 最终关系更新：没有足够的消息进行评估。") return readable_history_for_llm = await build_readable_messages( messages_for_eval, replace_bot_name=True, merge_messages=False, timestamp_mode="relative" ) current_relationship_value = await self.person_info_mng.get_value( conversation_info.person_id, "relationship_value" ) current_relationship_value = self.relationship_mng.ensure_float( current_relationship_value, conversation_info.person_id ) relationship_prompt = f"""你是{self.bot_name}。你与{self.private_name}的私聊刚刚结束。 你们当前的关系值大约是 {current_relationship_value:.0f} (范围通常在-1000到1000，越高越好)。 以下是你们本次私聊最后部分的对话内容： --- {readable_history_for_llm} --- 请基于以上对话的整体情况，判断你与【{self.private_name}】的关系值应该如何进行一次总结性的调整。 请输出一个JSON对象，包含一个 "final_adjustment" 字段，其值为一个整数，代表关系值的变化量（例如，可以是 -{self.REL_FINAL_MAX_CHANGE} 到 +{self.REL_FINAL_MAX_CHANGE} 之间的一个值）。 请大胆评估，但也要合理。""" raw_adjustment_val = self.REL_FINAL_DEFAULT_CHANGE try: logger.debug(f"[私聊][{self.private_name}] 最终关系评估Prompt:\n{relationship_prompt}") content, _ = await self.llm.generate_response_async(relationship_prompt) logger.debug(f"[私聊][{self.private_name}] 最终关系评估LLM原始返回: {content}") success, result = get_items_from_json( content, self.private_name, "final_adjustment", default_values={"final_adjustment": self.REL_FINAL_DEFAULT_CHANGE}, required_types={"final_adjustment": (int, float)}, ) raw_adjustment = result.get("final_adjustment", self.REL_FINAL_DEFAULT_CHANGE) if not isinstance(raw_adjustment, (int, float)): raw_adjustment_val = self.REL_FINAL_DEFAULT_CHANGE else: raw_adjustment_val = float(raw_adjustment) raw_adjustment_val = max( -self.REL_INCREMENTAL_MAX_CHANGE, min(self.REL_INCREMENTAL_MAX_CHANGE, raw_adjustment_val) ) except Exception as e: logger.error(f"[私聊][{self.private_name}] 最终关系评估LLM调用或解析失败: {e}") adjustment_val = await adjust_relationship_value_nonlinear(current_relationship_value, raw_adjustment_val) new_relationship_value = max(-1000.0, min(1000.0, current_relationship_value + adjustment_val)) await self.person_info_mng.update_one_field( conversation_info.person_id, "relationship_value", new_relationship_value ) logger.info( f"[私聊][{self.private_name}] 最终关系值更新：与【{self.private_name}】的关系值从 {current_relationship_value:.2f} 调整了 {adjustment_val:.2f}，最终为 {new_relationship_value:.2f}" ) if conversation_info.person_id: # 虽然通常结束了，但更新一下无妨 conversation_info.relationship_text = await self.relationship_mng.build_relationship_info( conversation_info.person_id, is_id=True ) class PfcRepationshipTranslator: """直接完整导入群聊的relationship_manager.py可能不可取 因为对于PFC的planner来说 其暗示了选择回复 所以新建代码文件来适配PFC的决策层面""" def __init__(self, private_name: str): self.private_name = private_name async def translate_relationship_value_to_text(self, relationship_value: float) -> str: """ 将数值型的关系值转换为PFC私聊场景下简洁的关系描述文本。 """ level_num = self._calculate_relationship_level_num(relationship_value, self.private_name) relationship_descriptions = [ "厌恶", # level_num 0 "冷漠", # level_num 1 "初识", # level_num 2 "友好", # level_num 3 "喜欢", # level_num 4 "依赖", # level_num 5 ] if 0 <= level_num < len(relationship_descriptions): description = relationship_descriptions[level_num] else: description = "普通" # 默认或错误情况 logger.warning(f"[私聊][{self.private_name}] 计算出的 level_num ({level_num}) 无效，关系描述默认为 '普通'") return f"{description}。" @staticmethod def _calculate_relationship_level_num(relationship_value: float, private_name: str) -> int: """ 根据关系值计算关系等级编号 (0-5)。 这里的阈值应与 relationship_manager.py 中的保持一致 """ if not isinstance(relationship_value, (int, float)): logger.warning( f"[私聊][{private_name}] 传入的 relationship_value '{relationship_value}' 不是有效的数值类型，默认为0。" ) relationship_value = 0.0 if -1000 <= relationship_value < -227: level_num = 0 # 厌恶 elif -227 <= relationship_value < -73: level_num = 1 # 冷漠 elif -73 <= relationship_value < 227: level_num = 2 # 普通/认识 elif 227 <= relationship_value < 587: level_num = 3 # 友好 elif 587 <= relationship_value < 900: level_num = 4 # 喜欢 elif 900 <= relationship_value <= 1000: level_num = 5 # 暧昧 else: # 超出范围的值处理 if relationship_value > 1000: level_num = 5 elif relationship_value < -1000: level_num = 0 else: # 理论上不会到这里，除非前面的条件逻辑有误 logger.warning(f"[私聊][{private_name}] 关系值 {relationship_value} 未落入任何预设范围，默认为普通。") level_num = 2 return level_num