fix：修复流程
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SengokuCola
@@ -15,14 +15,12 @@ from ..storage.storage import MessageStorage
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from .chat_observer import ChatObserver
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from .pfc_utils import get_items_from_json
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from src.individuality.individuality import Individuality
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from .chat_states import NotificationHandler, Notification, NotificationType
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from .waiter import Waiter
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from .message_sender import DirectMessageSender
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from .notification_handler import PFCNotificationHandler
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from .conversation_info import ConversationInfo
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from .observation_info import ObservationInfo
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import time
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if TYPE_CHECKING:
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from .conversation import Conversation
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pass
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logger = get_module_logger("pfc")
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@@ -45,42 +43,55 @@ class GoalAnalyzer:
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self.max_goals = 3 # 同时保持的最大目标数量
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self.current_goal_and_reason = None
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async def analyze_goal(self) -> Tuple[str, str, str]:
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async def analyze_goal(self, conversation_info: ConversationInfo, observation_info: ObservationInfo):
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"""分析对话历史并设定目标
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Args:
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chat_history: 聊天历史记录列表
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conversation_info: 对话信息
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observation_info: 观察信息
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Returns:
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Tuple[str, str, str]: (目标, 方法, 原因)
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"""
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max_retries = 3
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for retry in range(max_retries):
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try:
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# 构建提示词
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messages = self.chat_observer.get_message_history(limit=20)
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chat_history_text = ""
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for msg in messages:
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time_str = datetime.datetime.fromtimestamp(msg["time"]).strftime("%H:%M:%S")
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user_info = UserInfo.from_dict(msg.get("user_info", {}))
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sender = user_info.user_nickname or f"用户{user_info.user_id}"
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if sender == self.name:
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sender = "你说"
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chat_history_text += f"{time_str},{sender}:{msg.get('processed_plain_text', '')}\n"
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personality_text = f"你的名字是{self.name}，{self.personality_info}"
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# 构建当前已有目标的文本
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existing_goals_text = ""
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if self.goals:
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existing_goals_text = "当前已有的对话目标:\n"
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for i, (goal, _, reason) in enumerate(self.goals):
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existing_goals_text += f"{i + 1}. 目标: {goal}, 原因: {reason}\n"
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prompt = f"""{personality_text}。现在你在参与一场QQ聊天，请分析以下聊天记录，并根据你的性格特征确定多个明确的对话目标。
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#构建对话目标
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goal_list = conversation_info.goal_list
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goal_text = ""
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for goal, reason in goal_list:
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goal_text += f"目标：{goal};"
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goal_text += f"原因：{reason}\n"
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# 获取聊天历史记录
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chat_history_list = observation_info.chat_history
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chat_history_text = ""
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for msg in chat_history_list:
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chat_history_text += f"{msg}\n"
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if observation_info.new_messages_count > 0:
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new_messages_list = observation_info.unprocessed_messages
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chat_history_text += f"有{observation_info.new_messages_count}条新消息：\n"
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for msg in new_messages_list:
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chat_history_text += f"{msg}\n"
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observation_info.clear_unprocessed_messages()
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personality_text = f"你的名字是{self.name}，{self.personality_info}"
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# 构建action历史文本
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action_history_list = conversation_info.done_action
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action_history_text = "你之前做的事情是："
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for action in action_history_list:
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action_history_text += f"{action}\n"
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prompt = f"""{personality_text}。现在你在参与一场QQ聊天，请分析以下聊天记录，并根据你的性格特征确定多个明确的对话目标。
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这些目标应该反映出对话的不同方面和意图。
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{existing_goals_text}
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{action_history_text}
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当前对话目标：
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{goal_text}
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聊天记录：
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{chat_history_text}
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@@ -91,54 +102,37 @@ class GoalAnalyzer:
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3. 添加新目标
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4. 删除不再相关的目标
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请以JSON格式输出一个当前最主要的对话目标，包含以下字段：
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请以JSON格式输出当前的所有对话目标，包含以下字段：
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1. goal: 对话目标（简短的一句话）
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2. reasoning: 对话原因，为什么设定这个目标（简要解释）
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输出格式示例：
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{{
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"goal": "回答用户关于Python编程的具体问题",
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"reasoning": "用户提出了关于Python的技术问题，需要专业且准确的解答"
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"goal": "回答用户关于Python编程的具体问题",
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"reasoning": "用户提出了关于Python的技术问题，需要专业且准确的解答"
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}},
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{{
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"goal": "回答用户关于python安装的具体问题",
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"reasoning": "用户提出了关于Python的技术问题，需要专业且准确的解答"
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}}"""
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logger.debug(f"发送到LLM的提示词: {prompt}")
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content, _ = await self.llm.generate_response_async(prompt)
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logger.debug(f"LLM原始返回内容: {content}")
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# 使用简化函数提取JSON内容
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success, result = get_items_from_json(
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content, "goal", "reasoning", required_types={"goal": str, "reasoning": str}
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)
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if not success:
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logger.error(f"无法解析JSON，重试第{retry + 1}次")
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continue
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goal = result["goal"]
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reasoning = result["reasoning"]
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# 使用默认的方法
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method = "以友好的态度回应"
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# 更新目标列表
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await self._update_goals(goal, method, reasoning)
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# 返回当前最主要的目标
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if self.goals:
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current_goal, current_method, current_reasoning = self.goals[0]
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return current_goal, current_method, current_reasoning
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else:
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return goal, method, reasoning
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except Exception as e:
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logger.error(f"分析对话目标时出错: {str(e)}，重试第{retry + 1}次")
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if retry == max_retries - 1:
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return "保持友好的对话", "以友好的态度回应", "确保对话顺利进行"
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continue
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# 所有重试都失败后的默认返回
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return "保持友好的对话", "以友好的态度回应", "确保对话顺利进行"
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logger.debug(f"发送到LLM的提示词: {prompt}")
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content, _ = await self.llm.generate_response_async(prompt)
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logger.debug(f"LLM原始返回内容: {content}")
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# 使用简化函数提取JSON内容
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success, result = get_items_from_json(
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content,
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"goal", "reasoning",
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required_types={"goal": str, "reasoning": str}
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)
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#TODO
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conversation_info.goal_list.append(result)
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async def _update_goals(self, new_goal: str, method: str, reasoning: str):
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"""更新目标列表
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