Merge branch 'dev' into feat-lpmm知识库加强
This commit is contained in:
Dawn ARC
GitHub
491
src/chat/brain_chat/PFC/action_planner.py
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491
src/chat/brain_chat/PFC/action_planner.py
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import time
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from typing import Tuple, Optional # 增加了 Optional
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from src.common.logger_manager import get_logger
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from ..models.utils_model import LLMRequest
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from ...config.config import global_config
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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 .observation_info import ObservationInfo
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from .conversation_info import ConversationInfo
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from src.plugins.utils.chat_message_builder import build_readable_messages
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logger = get_logger("pfc_action_planner")
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# --- 定义 Prompt 模板 ---
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# Prompt(1): 首次回复或非连续回复时的决策 Prompt
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PROMPT_INITIAL_REPLY = """{persona_text}。现在你在参与一场QQ私聊，请根据以下【所有信息】审慎且灵活的决策下一步行动，可以回复，可以倾听，可以调取知识，甚至可以屏蔽对方：
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【当前对话目标】
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{goals_str}
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{knowledge_info_str}
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【最近行动历史概要】
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{action_history_summary}
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【上一次行动的详细情况和结果】
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{last_action_context}
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【时间和超时提示】
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{time_since_last_bot_message_info}{timeout_context}
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【最近的对话记录】(包括你已成功发送的消息 和 新收到的消息)
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{chat_history_text}
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------
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可选行动类型以及解释：
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fetch_knowledge: 需要调取知识或记忆，当需要专业知识或特定信息时选择，对方若提到你不太认识的人名或实体也可以尝试选择
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listening: 倾听对方发言，当你认为对方话才说到一半，发言明显未结束时选择
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direct_reply: 直接回复对方
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rethink_goal: 思考一个对话目标，当你觉得目前对话需要目标，或当前目标不再适用，或话题卡住时选择。注意私聊的环境是灵活的，有可能需要经常选择
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end_conversation: 结束对话，对方长时间没回复或者当你觉得对话告一段落时可以选择
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block_and_ignore: 更加极端的结束对话方式，直接结束对话并在一段时间内无视对方所有发言（屏蔽），当对话让你感到十分不适，或你遭到各类骚扰时选择
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请以JSON格式输出你的决策：
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{{
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"action": "选择的行动类型 (必须是上面列表中的一个)",
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"reason": "选择该行动的详细原因 (必须有解释你是如何根据“上一次行动结果”、“对话记录”和自身设定人设做出合理判断的)"
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}}
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注意：请严格按照JSON格式输出，不要包含任何其他内容。"""
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# Prompt(2): 上一次成功回复后，决定继续发言时的决策 Prompt
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PROMPT_FOLLOW_UP = """{persona_text}。现在你在参与一场QQ私聊，刚刚你已经回复了对方，请根据以下【所有信息】审慎且灵活的决策下一步行动，可以继续发送新消息，可以等待，可以倾听，可以调取知识，甚至可以屏蔽对方：
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【当前对话目标】
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{goals_str}
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{knowledge_info_str}
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【最近行动历史概要】
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{action_history_summary}
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【上一次行动的详细情况和结果】
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{last_action_context}
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【时间和超时提示】
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{time_since_last_bot_message_info}{timeout_context}
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【最近的对话记录】(包括你已成功发送的消息 和 新收到的消息)
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{chat_history_text}
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------
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可选行动类型以及解释：
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fetch_knowledge: 需要调取知识，当需要专业知识或特定信息时选择，对方若提到你不太认识的人名或实体也可以尝试选择
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wait: 暂时不说话，留给对方交互空间，等待对方回复（尤其是在你刚发言后、或上次发言因重复、发言过多被拒时、或不确定做什么时，这是不错的选择）
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listening: 倾听对方发言（虽然你刚发过言，但如果对方立刻回复且明显话没说完，可以选择这个）
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send_new_message: 发送一条新消息继续对话，允许适当的追问、补充、深入话题，或开启相关新话题。**但是避免在因重复被拒后立即使用，也不要在对方没有回复的情况下过多的“消息轰炸”或重复发言**
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rethink_goal: 思考一个对话目标，当你觉得目前对话需要目标，或当前目标不再适用，或话题卡住时选择。注意私聊的环境是灵活的，有可能需要经常选择
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end_conversation: 结束对话，对方长时间没回复或者当你觉得对话告一段落时可以选择
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block_and_ignore: 更加极端的结束对话方式，直接结束对话并在一段时间内无视对方所有发言（屏蔽），当对话让你感到十分不适，或你遭到各类骚扰时选择
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请以JSON格式输出你的决策：
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{{
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"action": "选择的行动类型 (必须是上面列表中的一个)",
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"reason": "选择该行动的详细原因 (必须有解释你是如何根据“上一次行动结果”、“对话记录”和自身设定人设做出合理判断的。请说明你为什么选择继续发言而不是等待，以及打算发送什么类型的新消息连续发言，必须记录已经发言了几次)"
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}}
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注意：请严格按照JSON格式输出，不要包含任何其他内容。"""
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# 新增：Prompt(3): 决定是否在结束对话前发送告别语
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PROMPT_END_DECISION = """{persona_text}。刚刚你决定结束一场 QQ 私聊。
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【你们之前的聊天记录】
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{chat_history_text}
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你觉得你们的对话已经完整结束了吗？有时候，在对话自然结束后再说点什么可能会有点奇怪，但有时也可能需要一条简短的消息来圆满结束。
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如果觉得确实有必要再发一条简短、自然、符合你人设的告别消息（比如 "好，下次再聊~" 或 "嗯，先这样吧"），就输出 "yes"。
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如果觉得当前状态下直接结束对话更好，没有必要再发消息，就输出 "no"。
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请以 JSON 格式输出你的选择：
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{{
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"say_bye": "yes/no",
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"reason": "选择 yes 或 no 的原因和内心想法 (简要说明)"
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}}
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注意：请严格按照 JSON 格式输出，不要包含任何其他内容。"""
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# ActionPlanner 类定义，顶格
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class ActionPlanner:
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"""行动规划器"""
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def __init__(self, stream_id: str, private_name: str):
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self.llm = LLMRequest(
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model=global_config.llm_PFC_action_planner,
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temperature=global_config.llm_PFC_action_planner["temp"],
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max_tokens=1500,
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request_type="action_planning",
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)
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self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
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self.name = global_config.BOT_NICKNAME
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self.private_name = private_name
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self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
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# self.action_planner_info = ActionPlannerInfo() # 移除未使用的变量
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# 修改 plan 方法签名，增加 last_successful_reply_action 参数
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async def plan(
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self,
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observation_info: ObservationInfo,
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conversation_info: ConversationInfo,
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last_successful_reply_action: Optional[str],
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) -> Tuple[str, str]:
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"""规划下一步行动
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Args:
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observation_info: 决策信息
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conversation_info: 对话信息
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last_successful_reply_action: 上一次成功的回复动作类型 ('direct_reply' 或 'send_new_message' 或 None)
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Returns:
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Tuple[str, str]: (行动类型, 行动原因)
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"""
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# --- 获取 Bot 上次发言时间信息 ---
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# (这部分逻辑不变)
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time_since_last_bot_message_info = ""
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try:
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bot_id = str(global_config.BOT_QQ)
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if hasattr(observation_info, "chat_history") and observation_info.chat_history:
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for i in range(len(observation_info.chat_history) - 1, -1, -1):
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msg = observation_info.chat_history[i]
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if not isinstance(msg, dict):
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continue
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sender_info = msg.get("user_info", {})
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sender_id = str(sender_info.get("user_id")) if isinstance(sender_info, dict) else None
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msg_time = msg.get("time")
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if sender_id == bot_id and msg_time:
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time_diff = time.time() - msg_time
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if time_diff < 60.0:
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time_since_last_bot_message_info = (
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f"提示：你上一条成功发送的消息是在 {time_diff:.1f} 秒前。\n"
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)
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break
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else:
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logger.debug(
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f"[私聊][{self.private_name}]Observation info chat history is empty or not available for bot time check."
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)
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except AttributeError:
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logger.warning(
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f"[私聊][{self.private_name}]ObservationInfo object might not have chat_history attribute yet for bot time check."
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)
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except Exception as e:
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logger.warning(f"[私聊][{self.private_name}]获取 Bot 上次发言时间时出错: {e}")
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# --- 获取超时提示信息 ---
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# (这部分逻辑不变)
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timeout_context = ""
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try:
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if hasattr(conversation_info, "goal_list") and conversation_info.goal_list:
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last_goal_dict = conversation_info.goal_list[-1]
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if isinstance(last_goal_dict, dict) and "goal" in last_goal_dict:
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last_goal_text = last_goal_dict["goal"]
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if isinstance(last_goal_text, str) and "分钟，思考接下来要做什么" in last_goal_text:
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try:
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timeout_minutes_text = last_goal_text.split("，")[0].replace("你等待了", "")
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timeout_context = f"重要提示：对方已经长时间（{timeout_minutes_text}）没有回复你的消息了（这可能代表对方繁忙/不想回复/没注意到你的消息等情况，或在对方看来本次聊天已告一段落），请基于此情况规划下一步。\n"
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except Exception:
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timeout_context = "重要提示：对方已经长时间没有回复你的消息了（这可能代表对方繁忙/不想回复/没注意到你的消息等情况，或在对方看来本次聊天已告一段落），请基于此情况规划下一步。\n"
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else:
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logger.debug(
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f"[私聊][{self.private_name}]Conversation info goal_list is empty or not available for timeout check."
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)
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except AttributeError:
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logger.warning(
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f"[私聊][{self.private_name}]ConversationInfo object might not have goal_list attribute yet for timeout check."
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)
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except Exception as e:
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logger.warning(f"[私聊][{self.private_name}]检查超时目标时出错: {e}")
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# --- 构建通用 Prompt 参数 ---
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logger.debug(
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f"[私聊][{self.private_name}]开始规划行动：当前目标: {getattr(conversation_info, 'goal_list', '不可用')}"
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)
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# 构建对话目标 (goals_str)
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goals_str = ""
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try:
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if hasattr(conversation_info, "goal_list") and conversation_info.goal_list:
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for goal_reason in conversation_info.goal_list:
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if isinstance(goal_reason, dict):
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goal = goal_reason.get("goal", "目标内容缺失")
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reasoning = goal_reason.get("reasoning", "没有明确原因")
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else:
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goal = str(goal_reason)
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reasoning = "没有明确原因"
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goal = str(goal) if goal is not None else "目标内容缺失"
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reasoning = str(reasoning) if reasoning is not None else "没有明确原因"
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goals_str += f"- 目标：{goal}\n 原因：{reasoning}\n"
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if not goals_str:
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goals_str = "- 目前没有明确对话目标，请考虑设定一个。\n"
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else:
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goals_str = "- 目前没有明确对话目标，请考虑设定一个。\n"
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except AttributeError:
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logger.warning(
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f"[私聊][{self.private_name}]ConversationInfo object might not have goal_list attribute yet."
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)
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goals_str = "- 获取对话目标时出错。\n"
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except Exception as e:
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logger.error(f"[私聊][{self.private_name}]构建对话目标字符串时出错: {e}")
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goals_str = "- 构建对话目标时出错。\n"
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# --- 知识信息字符串构建开始 ---
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knowledge_info_str = "【已获取的相关知识和记忆】\n"
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try:
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# 检查 conversation_info 是否有 knowledge_list 并且不为空
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if hasattr(conversation_info, "knowledge_list") and conversation_info.knowledge_list:
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# 最多只显示最近的 5 条知识，防止 Prompt 过长
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recent_knowledge = conversation_info.knowledge_list[-5:]
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for i, knowledge_item in enumerate(recent_knowledge):
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if isinstance(knowledge_item, dict):
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query = knowledge_item.get("query", "未知查询")
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knowledge = knowledge_item.get("knowledge", "无知识内容")
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source = knowledge_item.get("source", "未知来源")
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# 只取知识内容的前 2000 个字，避免太长
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knowledge_snippet = knowledge[:2000] + "..." if len(knowledge) > 2000 else knowledge
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knowledge_info_str += (
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f"{i + 1}. 关于 '{query}' 的知识 (来源: {source}):\n {knowledge_snippet}\n"
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)
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else:
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# 处理列表里不是字典的异常情况
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knowledge_info_str += f"{i + 1}. 发现一条格式不正确的知识记录。\n"
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if not recent_knowledge: # 如果 knowledge_list 存在但为空
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knowledge_info_str += "- 暂无相关知识和记忆。\n"
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else:
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# 如果 conversation_info 没有 knowledge_list 属性，或者列表为空
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knowledge_info_str += "- 暂无相关知识记忆。\n"
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except AttributeError:
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logger.warning(f"[私聊][{self.private_name}]ConversationInfo 对象可能缺少 knowledge_list 属性。")
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knowledge_info_str += "- 获取知识列表时出错。\n"
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except Exception as e:
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logger.error(f"[私聊][{self.private_name}]构建知识信息字符串时出错: {e}")
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knowledge_info_str += "- 处理知识列表时出错。\n"
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# --- 知识信息字符串构建结束 ---
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# 获取聊天历史记录 (chat_history_text)
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try:
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if hasattr(observation_info, "chat_history") and observation_info.chat_history:
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chat_history_text = observation_info.chat_history_str
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if not chat_history_text:
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chat_history_text = "还没有聊天记录。\n"
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else:
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chat_history_text = "还没有聊天记录。\n"
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if hasattr(observation_info, "new_messages_count") and observation_info.new_messages_count > 0:
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if hasattr(observation_info, "unprocessed_messages") and observation_info.unprocessed_messages:
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new_messages_list = observation_info.unprocessed_messages
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new_messages_str = await build_readable_messages(
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new_messages_list,
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replace_bot_name=True,
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merge_messages=False,
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timestamp_mode="relative",
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read_mark=0.0,
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)
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chat_history_text += (
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f"\n--- 以下是 {observation_info.new_messages_count} 条新消息 ---\n{new_messages_str}"
|
||||
)
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||||
else:
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logger.warning(
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f"[私聊][{self.private_name}]ObservationInfo has new_messages_count > 0 but unprocessed_messages is empty or missing."
|
||||
)
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except AttributeError:
|
||||
logger.warning(
|
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f"[私聊][{self.private_name}]ObservationInfo object might be missing expected attributes for chat history."
|
||||
)
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chat_history_text = "获取聊天记录时出错。\n"
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except Exception as e:
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logger.error(f"[私聊][{self.private_name}]处理聊天记录时发生未知错误: {e}")
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||||
chat_history_text = "处理聊天记录时出错。\n"
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# 构建 Persona 文本 (persona_text)
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persona_text = f"你的名字是{self.name}，{self.personality_info}。"
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# 构建行动历史和上一次行动结果 (action_history_summary, last_action_context)
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# (这部分逻辑不变)
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||||
action_history_summary = "你最近执行的行动历史：\n"
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||||
last_action_context = "关于你【上一次尝试】的行动：\n"
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||||
action_history_list = []
|
||||
try:
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||||
if hasattr(conversation_info, "done_action") and conversation_info.done_action:
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||||
action_history_list = conversation_info.done_action[-5:]
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||||
else:
|
||||
logger.debug(f"[私聊][{self.private_name}]Conversation info done_action is empty or not available.")
|
||||
except AttributeError:
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]ConversationInfo object might not have done_action attribute yet."
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]访问行动历史时出错: {e}")
|
||||
|
||||
if not action_history_list:
|
||||
action_history_summary += "- 还没有执行过行动。\n"
|
||||
last_action_context += "- 这是你规划的第一个行动。\n"
|
||||
else:
|
||||
for i, action_data in enumerate(action_history_list):
|
||||
action_type = "未知"
|
||||
plan_reason = "未知"
|
||||
status = "未知"
|
||||
final_reason = ""
|
||||
action_time = ""
|
||||
|
||||
if isinstance(action_data, dict):
|
||||
action_type = action_data.get("action", "未知")
|
||||
plan_reason = action_data.get("plan_reason", "未知规划原因")
|
||||
status = action_data.get("status", "未知")
|
||||
final_reason = action_data.get("final_reason", "")
|
||||
action_time = action_data.get("time", "")
|
||||
elif isinstance(action_data, tuple):
|
||||
# 假设旧格式兼容
|
||||
if len(action_data) > 0:
|
||||
action_type = action_data[0]
|
||||
if len(action_data) > 1:
|
||||
plan_reason = action_data[1] # 可能是规划原因或最终原因
|
||||
if len(action_data) > 2:
|
||||
status = action_data[2]
|
||||
if status == "recall" and len(action_data) > 3:
|
||||
final_reason = action_data[3]
|
||||
elif status == "done" and action_type in ["direct_reply", "send_new_message"]:
|
||||
plan_reason = "成功发送" # 简化显示
|
||||
|
||||
reason_text = f", 失败/取消原因: {final_reason}" if final_reason else ""
|
||||
summary_line = f"- 时间:{action_time}, 尝试行动:'{action_type}', 状态:{status}{reason_text}"
|
||||
action_history_summary += summary_line + "\n"
|
||||
|
||||
if i == len(action_history_list) - 1:
|
||||
last_action_context += f"- 上次【规划】的行动是: '{action_type}'\n"
|
||||
last_action_context += f"- 当时规划的【原因】是: {plan_reason}\n"
|
||||
if status == "done":
|
||||
last_action_context += "- 该行动已【成功执行】。\n"
|
||||
# 记录这次成功的行动类型，供下次决策
|
||||
# self.last_successful_action_type = action_type # 不在这里记录，由 conversation 控制
|
||||
elif status == "recall":
|
||||
last_action_context += "- 但该行动最终【未能执行/被取消】。\n"
|
||||
if final_reason:
|
||||
last_action_context += f"- 【重要】失败/取消的具体原因是: “{final_reason}”\n"
|
||||
else:
|
||||
last_action_context += "- 【重要】失败/取消原因未明确记录。\n"
|
||||
# self.last_successful_action_type = None # 行动失败，清除记录
|
||||
else:
|
||||
last_action_context += f"- 该行动当前状态: {status}\n"
|
||||
# self.last_successful_action_type = None # 非完成状态，清除记录
|
||||
|
||||
# --- 选择 Prompt ---
|
||||
if last_successful_reply_action in ["direct_reply", "send_new_message"]:
|
||||
prompt_template = PROMPT_FOLLOW_UP
|
||||
logger.debug(f"[私聊][{self.private_name}]使用 PROMPT_FOLLOW_UP (追问决策)")
|
||||
else:
|
||||
prompt_template = PROMPT_INITIAL_REPLY
|
||||
logger.debug(f"[私聊][{self.private_name}]使用 PROMPT_INITIAL_REPLY (首次/非连续回复决策)")
|
||||
|
||||
# --- 格式化最终的 Prompt ---
|
||||
prompt = prompt_template.format(
|
||||
persona_text=persona_text,
|
||||
goals_str=goals_str if goals_str.strip() else "- 目前没有明确对话目标，请考虑设定一个。",
|
||||
action_history_summary=action_history_summary,
|
||||
last_action_context=last_action_context,
|
||||
time_since_last_bot_message_info=time_since_last_bot_message_info,
|
||||
timeout_context=timeout_context,
|
||||
chat_history_text=chat_history_text if chat_history_text.strip() else "还没有聊天记录。",
|
||||
knowledge_info_str=knowledge_info_str,
|
||||
)
|
||||
|
||||
logger.debug(f"[私聊][{self.private_name}]发送到LLM的最终提示词:\n------\n{prompt}\n------")
|
||||
try:
|
||||
content, _ = await self.llm.generate_response_async(prompt)
|
||||
logger.debug(f"[私聊][{self.private_name}]LLM (行动规划) 原始返回内容: {content}")
|
||||
|
||||
# --- 初始行动规划解析 ---
|
||||
success, initial_result = get_items_from_json(
|
||||
content,
|
||||
self.private_name,
|
||||
"action",
|
||||
"reason",
|
||||
default_values={"action": "wait", "reason": "LLM返回格式错误或未提供原因，默认等待"},
|
||||
)
|
||||
|
||||
initial_action = initial_result.get("action", "wait")
|
||||
initial_reason = initial_result.get("reason", "LLM未提供原因，默认等待")
|
||||
|
||||
# 检查是否需要进行结束对话决策 ---
|
||||
if initial_action == "end_conversation":
|
||||
logger.info(f"[私聊][{self.private_name}]初步规划结束对话，进入告别决策...")
|
||||
|
||||
# 使用新的 PROMPT_END_DECISION
|
||||
end_decision_prompt = PROMPT_END_DECISION.format(
|
||||
persona_text=persona_text, # 复用之前的 persona_text
|
||||
chat_history_text=chat_history_text, # 复用之前的 chat_history_text
|
||||
)
|
||||
|
||||
logger.debug(
|
||||
f"[私聊][{self.private_name}]发送到LLM的结束决策提示词:\n------\n{end_decision_prompt}\n------"
|
||||
)
|
||||
try:
|
||||
end_content, _ = await self.llm.generate_response_async(end_decision_prompt) # 再次调用LLM
|
||||
logger.debug(f"[私聊][{self.private_name}]LLM (结束决策) 原始返回内容: {end_content}")
|
||||
|
||||
# 解析结束决策的JSON
|
||||
end_success, end_result = get_items_from_json(
|
||||
end_content,
|
||||
self.private_name,
|
||||
"say_bye",
|
||||
"reason",
|
||||
default_values={"say_bye": "no", "reason": "结束决策LLM返回格式错误，默认不告别"},
|
||||
required_types={"say_bye": str, "reason": str}, # 明确类型
|
||||
)
|
||||
|
||||
say_bye_decision = end_result.get("say_bye", "no").lower() # 转小写方便比较
|
||||
end_decision_reason = end_result.get("reason", "未提供原因")
|
||||
|
||||
if end_success and say_bye_decision == "yes":
|
||||
# 决定要告别，返回新的 'say_goodbye' 动作
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]结束决策: yes, 准备生成告别语. 原因: {end_decision_reason}"
|
||||
)
|
||||
# 注意：这里的 reason 可以考虑拼接初始原因和结束决策原因，或者只用结束决策原因
|
||||
final_action = "say_goodbye"
|
||||
final_reason = f"决定发送告别语。决策原因: {end_decision_reason} (原结束理由: {initial_reason})"
|
||||
return final_action, final_reason
|
||||
else:
|
||||
# 决定不告别 (包括解析失败或明确说no)
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]结束决策: no, 直接结束对话. 原因: {end_decision_reason}"
|
||||
)
|
||||
# 返回原始的 'end_conversation' 动作
|
||||
final_action = "end_conversation"
|
||||
final_reason = initial_reason # 保持原始的结束理由
|
||||
return final_action, final_reason
|
||||
|
||||
except Exception as end_e:
|
||||
logger.error(f"[私聊][{self.private_name}]调用结束决策LLM或处理结果时出错: {str(end_e)}")
|
||||
# 出错时，默认执行原始的结束对话
|
||||
logger.warning(f"[私聊][{self.private_name}]结束决策出错，将按原计划执行 end_conversation")
|
||||
return "end_conversation", initial_reason # 返回原始动作和原因
|
||||
|
||||
else:
|
||||
action = initial_action
|
||||
reason = initial_reason
|
||||
|
||||
# 验证action类型 (保持不变)
|
||||
valid_actions = [
|
||||
"direct_reply",
|
||||
"send_new_message",
|
||||
"fetch_knowledge",
|
||||
"wait",
|
||||
"listening",
|
||||
"rethink_goal",
|
||||
"end_conversation", # 仍然需要验证，因为可能从上面决策后返回
|
||||
"block_and_ignore",
|
||||
"say_goodbye", # 也要验证这个新动作
|
||||
]
|
||||
if action not in valid_actions:
|
||||
logger.warning(f"[私聊][{self.private_name}]LLM返回了未知的行动类型: '{action}'，强制改为 wait")
|
||||
reason = f"(原始行动'{action}'无效，已强制改为wait) {reason}"
|
||||
action = "wait"
|
||||
|
||||
logger.info(f"[私聊][{self.private_name}]规划的行动: {action}")
|
||||
logger.info(f"[私聊][{self.private_name}]行动原因: {reason}")
|
||||
return action, reason
|
||||
|
||||
except Exception as e:
|
||||
# 外层异常处理保持不变
|
||||
logger.error(f"[私聊][{self.private_name}]规划行动时调用 LLM 或处理结果出错: {str(e)}")
|
||||
return "wait", f"行动规划处理中发生错误，暂时等待: {str(e)}"
|
||||
379
src/chat/brain_chat/PFC/chat_observer.py
Normal file
379
src/chat/brain_chat/PFC/chat_observer.py
Normal file
@@ -0,0 +1,379 @@
|
||||
import time
|
||||
import asyncio
|
||||
import traceback
|
||||
from typing import Optional, Dict, Any, List
|
||||
from src.common.logger import get_module_logger
|
||||
from maim_message import UserInfo
|
||||
from ...config.config import global_config
|
||||
from .chat_states import NotificationManager, create_new_message_notification, create_cold_chat_notification
|
||||
from .message_storage import MongoDBMessageStorage
|
||||
from rich.traceback import install
|
||||
|
||||
install(extra_lines=3)
|
||||
|
||||
logger = get_module_logger("chat_observer")
|
||||
|
||||
|
||||
class ChatObserver:
|
||||
"""聊天状态观察器"""
|
||||
|
||||
# 类级别的实例管理
|
||||
_instances: Dict[str, "ChatObserver"] = {}
|
||||
|
||||
@classmethod
|
||||
def get_instance(cls, stream_id: str, private_name: str) -> "ChatObserver":
|
||||
"""获取或创建观察器实例
|
||||
|
||||
Args:
|
||||
stream_id: 聊天流ID
|
||||
private_name: 私聊名称
|
||||
|
||||
Returns:
|
||||
ChatObserver: 观察器实例
|
||||
"""
|
||||
if stream_id not in cls._instances:
|
||||
cls._instances[stream_id] = cls(stream_id, private_name)
|
||||
return cls._instances[stream_id]
|
||||
|
||||
def __init__(self, stream_id: str, private_name: str):
|
||||
"""初始化观察器
|
||||
|
||||
Args:
|
||||
stream_id: 聊天流ID
|
||||
"""
|
||||
self.last_check_time = None
|
||||
self.last_bot_speak_time = None
|
||||
self.last_user_speak_time = None
|
||||
if stream_id in self._instances:
|
||||
raise RuntimeError(f"ChatObserver for {stream_id} already exists. Use get_instance() instead.")
|
||||
|
||||
self.stream_id = stream_id
|
||||
self.private_name = private_name
|
||||
self.message_storage = MongoDBMessageStorage()
|
||||
|
||||
# self.last_user_speak_time: Optional[float] = None # 对方上次发言时间
|
||||
# self.last_bot_speak_time: Optional[float] = None # 机器人上次发言时间
|
||||
# self.last_check_time: float = time.time() # 上次查看聊天记录时间
|
||||
self.last_message_read: Optional[Dict[str, Any]] = None # 最后读取的消息ID
|
||||
self.last_message_time: float = time.time()
|
||||
|
||||
self.waiting_start_time: float = time.time() # 等待开始时间，初始化为当前时间
|
||||
|
||||
# 运行状态
|
||||
self._running: bool = False
|
||||
self._task: Optional[asyncio.Task] = None
|
||||
self._update_event = asyncio.Event() # 触发更新的事件
|
||||
self._update_complete = asyncio.Event() # 更新完成的事件
|
||||
|
||||
# 通知管理器
|
||||
self.notification_manager = NotificationManager()
|
||||
|
||||
# 冷场检查配置
|
||||
self.cold_chat_threshold: float = 60.0 # 60秒无消息判定为冷场
|
||||
self.last_cold_chat_check: float = time.time()
|
||||
self.is_cold_chat_state: bool = False
|
||||
|
||||
self.update_event = asyncio.Event()
|
||||
self.update_interval = 2 # 更新间隔（秒）
|
||||
self.message_cache = []
|
||||
self.update_running = False
|
||||
|
||||
async def check(self) -> bool:
|
||||
"""检查距离上一次观察之后是否有了新消息
|
||||
|
||||
Returns:
|
||||
bool: 是否有新消息
|
||||
"""
|
||||
logger.debug(f"[私聊][{self.private_name}]检查距离上一次观察之后是否有了新消息: {self.last_check_time}")
|
||||
|
||||
new_message_exists = await self.message_storage.has_new_messages(self.stream_id, self.last_check_time)
|
||||
|
||||
if new_message_exists:
|
||||
logger.debug(f"[私聊][{self.private_name}]发现新消息")
|
||||
self.last_check_time = time.time()
|
||||
|
||||
return new_message_exists
|
||||
|
||||
async def _add_message_to_history(self, message: Dict[str, Any]):
|
||||
"""添加消息到历史记录并发送通知
|
||||
|
||||
Args:
|
||||
message: 消息数据
|
||||
"""
|
||||
try:
|
||||
# 发送新消息通知
|
||||
notification = create_new_message_notification(
|
||||
sender="chat_observer", target="observation_info", message=message
|
||||
)
|
||||
# print(self.notification_manager)
|
||||
await self.notification_manager.send_notification(notification)
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]添加消息到历史记录时出错: {e}")
|
||||
print(traceback.format_exc())
|
||||
|
||||
# 检查并更新冷场状态
|
||||
await self._check_cold_chat()
|
||||
|
||||
async def _check_cold_chat(self):
|
||||
"""检查是否处于冷场状态并发送通知"""
|
||||
current_time = time.time()
|
||||
|
||||
# 每10秒检查一次冷场状态
|
||||
if current_time - self.last_cold_chat_check < 10:
|
||||
return
|
||||
|
||||
self.last_cold_chat_check = current_time
|
||||
|
||||
# 判断是否冷场
|
||||
is_cold = (
|
||||
True
|
||||
if self.last_message_time is None
|
||||
else (current_time - self.last_message_time) > self.cold_chat_threshold
|
||||
)
|
||||
|
||||
# 如果冷场状态发生变化，发送通知
|
||||
if is_cold != self.is_cold_chat_state:
|
||||
self.is_cold_chat_state = is_cold
|
||||
notification = create_cold_chat_notification(sender="chat_observer", target="pfc", is_cold=is_cold)
|
||||
await self.notification_manager.send_notification(notification)
|
||||
|
||||
def new_message_after(self, time_point: float) -> bool:
|
||||
"""判断是否在指定时间点后有新消息
|
||||
|
||||
Args:
|
||||
time_point: 时间戳
|
||||
|
||||
Returns:
|
||||
bool: 是否有新消息
|
||||
"""
|
||||
|
||||
if self.last_message_time is None:
|
||||
logger.debug(f"[私聊][{self.private_name}]没有最后消息时间，返回 False")
|
||||
return False
|
||||
|
||||
has_new = self.last_message_time > time_point
|
||||
logger.debug(
|
||||
f"[私聊][{self.private_name}]判断是否在指定时间点后有新消息: {self.last_message_time} > {time_point} = {has_new}"
|
||||
)
|
||||
return has_new
|
||||
|
||||
def get_message_history(
|
||||
self,
|
||||
start_time: Optional[float] = None,
|
||||
end_time: Optional[float] = None,
|
||||
limit: Optional[int] = None,
|
||||
user_id: Optional[str] = None,
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""获取消息历史
|
||||
|
||||
Args:
|
||||
start_time: 开始时间戳
|
||||
end_time: 结束时间戳
|
||||
limit: 限制返回消息数量
|
||||
user_id: 指定用户ID
|
||||
|
||||
Returns:
|
||||
List[Dict[str, Any]]: 消息列表
|
||||
"""
|
||||
filtered_messages = self.message_history
|
||||
|
||||
if start_time is not None:
|
||||
filtered_messages = [m for m in filtered_messages if m["time"] >= start_time]
|
||||
|
||||
if end_time is not None:
|
||||
filtered_messages = [m for m in filtered_messages if m["time"] <= end_time]
|
||||
|
||||
if user_id is not None:
|
||||
filtered_messages = [
|
||||
m for m in filtered_messages if UserInfo.from_dict(m.get("user_info", {})).user_id == user_id
|
||||
]
|
||||
|
||||
if limit is not None:
|
||||
filtered_messages = filtered_messages[-limit:]
|
||||
|
||||
return filtered_messages
|
||||
|
||||
async def _fetch_new_messages(self) -> List[Dict[str, Any]]:
|
||||
"""获取新消息
|
||||
|
||||
Returns:
|
||||
List[Dict[str, Any]]: 新消息列表
|
||||
"""
|
||||
new_messages = await self.message_storage.get_messages_after(self.stream_id, self.last_message_time)
|
||||
|
||||
if new_messages:
|
||||
self.last_message_read = new_messages[-1]
|
||||
self.last_message_time = new_messages[-1]["time"]
|
||||
|
||||
# print(f"获取数据库中找到的新消息: {new_messages}")
|
||||
|
||||
return new_messages
|
||||
|
||||
async def _fetch_new_messages_before(self, time_point: float) -> List[Dict[str, Any]]:
|
||||
"""获取指定时间点之前的消息
|
||||
|
||||
Args:
|
||||
time_point: 时间戳
|
||||
|
||||
Returns:
|
||||
List[Dict[str, Any]]: 最多5条消息
|
||||
"""
|
||||
new_messages = await self.message_storage.get_messages_before(self.stream_id, time_point)
|
||||
|
||||
if new_messages:
|
||||
self.last_message_read = new_messages[-1]["message_id"]
|
||||
|
||||
logger.debug(f"[私聊][{self.private_name}]获取指定时间点111之前的消息: {new_messages}")
|
||||
|
||||
return new_messages
|
||||
|
||||
"""主要观察循环"""
|
||||
|
||||
async def _update_loop(self):
|
||||
"""更新循环"""
|
||||
# try:
|
||||
# start_time = time.time()
|
||||
# messages = await self._fetch_new_messages_before(start_time)
|
||||
# for message in messages:
|
||||
# await self._add_message_to_history(message)
|
||||
# logger.debug(f"[私聊][{self.private_name}]缓冲消息: {messages}")
|
||||
# except Exception as e:
|
||||
# logger.error(f"[私聊][{self.private_name}]缓冲消息出错: {e}")
|
||||
|
||||
while self._running:
|
||||
try:
|
||||
# 等待事件或超时（1秒）
|
||||
try:
|
||||
# print("等待事件")
|
||||
await asyncio.wait_for(self._update_event.wait(), timeout=1)
|
||||
|
||||
except asyncio.TimeoutError:
|
||||
# print("超时")
|
||||
pass # 超时后也执行一次检查
|
||||
|
||||
self._update_event.clear() # 重置触发事件
|
||||
self._update_complete.clear() # 重置完成事件
|
||||
|
||||
# 获取新消息
|
||||
new_messages = await self._fetch_new_messages()
|
||||
|
||||
if new_messages:
|
||||
# 处理新消息
|
||||
for message in new_messages:
|
||||
await self._add_message_to_history(message)
|
||||
|
||||
# 设置完成事件
|
||||
self._update_complete.set()
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]更新循环出错: {e}")
|
||||
logger.error(f"[私聊][{self.private_name}]{traceback.format_exc()}")
|
||||
self._update_complete.set() # 即使出错也要设置完成事件
|
||||
|
||||
def trigger_update(self):
|
||||
"""触发一次立即更新"""
|
||||
self._update_event.set()
|
||||
|
||||
async def wait_for_update(self, timeout: float = 5.0) -> bool:
|
||||
"""等待更新完成
|
||||
|
||||
Args:
|
||||
timeout: 超时时间（秒）
|
||||
|
||||
Returns:
|
||||
bool: 是否成功完成更新（False表示超时）
|
||||
"""
|
||||
try:
|
||||
await asyncio.wait_for(self._update_complete.wait(), timeout=timeout)
|
||||
return True
|
||||
except asyncio.TimeoutError:
|
||||
logger.warning(f"[私聊][{self.private_name}]等待更新完成超时（{timeout}秒）")
|
||||
return False
|
||||
|
||||
def start(self):
|
||||
"""启动观察器"""
|
||||
if self._running:
|
||||
return
|
||||
|
||||
self._running = True
|
||||
self._task = asyncio.create_task(self._update_loop())
|
||||
logger.debug(f"[私聊][{self.private_name}]ChatObserver for {self.stream_id} started")
|
||||
|
||||
def stop(self):
|
||||
"""停止观察器"""
|
||||
self._running = False
|
||||
self._update_event.set() # 设置事件以解除等待
|
||||
self._update_complete.set() # 设置完成事件以解除等待
|
||||
if self._task:
|
||||
self._task.cancel()
|
||||
logger.debug(f"[私聊][{self.private_name}]ChatObserver for {self.stream_id} stopped")
|
||||
|
||||
async def process_chat_history(self, messages: list):
|
||||
"""处理聊天历史
|
||||
|
||||
Args:
|
||||
messages: 消息列表
|
||||
"""
|
||||
self.update_check_time()
|
||||
|
||||
for msg in messages:
|
||||
try:
|
||||
user_info = UserInfo.from_dict(msg.get("user_info", {}))
|
||||
if user_info.user_id == global_config.BOT_QQ:
|
||||
self.update_bot_speak_time(msg["time"])
|
||||
else:
|
||||
self.update_user_speak_time(msg["time"])
|
||||
except Exception as e:
|
||||
logger.warning(f"[私聊][{self.private_name}]处理消息时间时出错: {e}")
|
||||
continue
|
||||
|
||||
def update_check_time(self):
|
||||
"""更新查看时间"""
|
||||
self.last_check_time = time.time()
|
||||
|
||||
def update_bot_speak_time(self, speak_time: Optional[float] = None):
|
||||
"""更新机器人说话时间"""
|
||||
self.last_bot_speak_time = speak_time or time.time()
|
||||
|
||||
def update_user_speak_time(self, speak_time: Optional[float] = None):
|
||||
"""更新用户说话时间"""
|
||||
self.last_user_speak_time = speak_time or time.time()
|
||||
|
||||
def get_time_info(self) -> str:
|
||||
"""获取时间信息文本"""
|
||||
current_time = time.time()
|
||||
time_info = ""
|
||||
|
||||
if self.last_bot_speak_time:
|
||||
bot_speak_ago = current_time - self.last_bot_speak_time
|
||||
time_info += f"\n距离你上次发言已经过去了{int(bot_speak_ago)}秒"
|
||||
|
||||
if self.last_user_speak_time:
|
||||
user_speak_ago = current_time - self.last_user_speak_time
|
||||
time_info += f"\n距离对方上次发言已经过去了{int(user_speak_ago)}秒"
|
||||
|
||||
return time_info
|
||||
|
||||
def get_cached_messages(self, limit: int = 50) -> List[Dict[str, Any]]:
|
||||
"""获取缓存的消息历史
|
||||
|
||||
Args:
|
||||
limit: 获取的最大消息数量，默认50
|
||||
|
||||
Returns:
|
||||
List[Dict[str, Any]]: 缓存的消息历史列表
|
||||
"""
|
||||
return self.message_cache[-limit:]
|
||||
|
||||
def get_last_message(self) -> Optional[Dict[str, Any]]:
|
||||
"""获取最后一条消息
|
||||
|
||||
Returns:
|
||||
Optional[Dict[str, Any]]: 最后一条消息，如果没有则返回None
|
||||
"""
|
||||
if not self.message_cache:
|
||||
return None
|
||||
return self.message_cache[-1]
|
||||
|
||||
def __str__(self):
|
||||
return f"ChatObserver for {self.stream_id}"
|
||||
290
src/chat/brain_chat/PFC/chat_states.py
Normal file
290
src/chat/brain_chat/PFC/chat_states.py
Normal file
@@ -0,0 +1,290 @@
|
||||
from enum import Enum, auto
|
||||
from typing import Optional, Dict, Any, List, Set
|
||||
from dataclasses import dataclass
|
||||
from datetime import datetime
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
|
||||
class ChatState(Enum):
|
||||
"""聊天状态枚举"""
|
||||
|
||||
NORMAL = auto() # 正常状态
|
||||
NEW_MESSAGE = auto() # 有新消息
|
||||
COLD_CHAT = auto() # 冷场状态
|
||||
ACTIVE_CHAT = auto() # 活跃状态
|
||||
BOT_SPEAKING = auto() # 机器人正在说话
|
||||
USER_SPEAKING = auto() # 用户正在说话
|
||||
SILENT = auto() # 沉默状态
|
||||
ERROR = auto() # 错误状态
|
||||
|
||||
|
||||
class NotificationType(Enum):
|
||||
"""通知类型枚举"""
|
||||
|
||||
NEW_MESSAGE = auto() # 新消息通知
|
||||
COLD_CHAT = auto() # 冷场通知
|
||||
ACTIVE_CHAT = auto() # 活跃通知
|
||||
BOT_SPEAKING = auto() # 机器人说话通知
|
||||
USER_SPEAKING = auto() # 用户说话通知
|
||||
MESSAGE_DELETED = auto() # 消息删除通知
|
||||
USER_JOINED = auto() # 用户加入通知
|
||||
USER_LEFT = auto() # 用户离开通知
|
||||
ERROR = auto() # 错误通知
|
||||
|
||||
|
||||
@dataclass
|
||||
class ChatStateInfo:
|
||||
"""聊天状态信息"""
|
||||
|
||||
state: ChatState
|
||||
last_message_time: Optional[float] = None
|
||||
last_message_content: Optional[str] = None
|
||||
last_speaker: Optional[str] = None
|
||||
message_count: int = 0
|
||||
cold_duration: float = 0.0 # 冷场持续时间（秒）
|
||||
active_duration: float = 0.0 # 活跃持续时间（秒）
|
||||
|
||||
|
||||
@dataclass
|
||||
class Notification:
|
||||
"""通知基类"""
|
||||
|
||||
type: NotificationType
|
||||
timestamp: float
|
||||
sender: str # 发送者标识
|
||||
target: str # 接收者标识
|
||||
data: Dict[str, Any]
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""转换为字典格式"""
|
||||
return {"type": self.type.name, "timestamp": self.timestamp, "data": self.data}
|
||||
|
||||
|
||||
@dataclass
|
||||
class StateNotification(Notification):
|
||||
"""持续状态通知"""
|
||||
|
||||
is_active: bool = True
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
base_dict = super().to_dict()
|
||||
base_dict["is_active"] = self.is_active
|
||||
return base_dict
|
||||
|
||||
|
||||
class NotificationHandler(ABC):
|
||||
"""通知处理器接口"""
|
||||
|
||||
@abstractmethod
|
||||
async def handle_notification(self, notification: Notification):
|
||||
"""处理通知"""
|
||||
pass
|
||||
|
||||
|
||||
class NotificationManager:
|
||||
"""通知管理器"""
|
||||
|
||||
def __init__(self):
|
||||
# 按接收者和通知类型存储处理器
|
||||
self._handlers: Dict[str, Dict[NotificationType, List[NotificationHandler]]] = {}
|
||||
self._active_states: Set[NotificationType] = set()
|
||||
self._notification_history: List[Notification] = []
|
||||
|
||||
def register_handler(self, target: str, notification_type: NotificationType, handler: NotificationHandler):
|
||||
"""注册通知处理器
|
||||
|
||||
Args:
|
||||
target: 接收者标识（例如："pfc"）
|
||||
notification_type: 要处理的通知类型
|
||||
handler: 处理器实例
|
||||
"""
|
||||
if target not in self._handlers:
|
||||
self._handlers[target] = {}
|
||||
if notification_type not in self._handlers[target]:
|
||||
self._handlers[target][notification_type] = []
|
||||
# print(self._handlers[target][notification_type])
|
||||
self._handlers[target][notification_type].append(handler)
|
||||
# print(self._handlers[target][notification_type])
|
||||
|
||||
def unregister_handler(self, target: str, notification_type: NotificationType, handler: NotificationHandler):
|
||||
"""注销通知处理器
|
||||
|
||||
Args:
|
||||
target: 接收者标识
|
||||
notification_type: 通知类型
|
||||
handler: 要注销的处理器实例
|
||||
"""
|
||||
if target in self._handlers and notification_type in self._handlers[target]:
|
||||
handlers = self._handlers[target][notification_type]
|
||||
if handler in handlers:
|
||||
handlers.remove(handler)
|
||||
# 如果该类型的处理器列表为空，删除该类型
|
||||
if not handlers:
|
||||
del self._handlers[target][notification_type]
|
||||
# 如果该目标没有任何处理器，删除该目标
|
||||
if not self._handlers[target]:
|
||||
del self._handlers[target]
|
||||
|
||||
async def send_notification(self, notification: Notification):
|
||||
"""发送通知"""
|
||||
self._notification_history.append(notification)
|
||||
|
||||
# 如果是状态通知，更新活跃状态
|
||||
if isinstance(notification, StateNotification):
|
||||
if notification.is_active:
|
||||
self._active_states.add(notification.type)
|
||||
else:
|
||||
self._active_states.discard(notification.type)
|
||||
|
||||
# 调用目标接收者的处理器
|
||||
target = notification.target
|
||||
if target in self._handlers:
|
||||
handlers = self._handlers[target].get(notification.type, [])
|
||||
# print(handlers)
|
||||
for handler in handlers:
|
||||
# print(f"调用处理器: {handler}")
|
||||
await handler.handle_notification(notification)
|
||||
|
||||
def get_active_states(self) -> Set[NotificationType]:
|
||||
"""获取当前活跃的状态"""
|
||||
return self._active_states.copy()
|
||||
|
||||
def is_state_active(self, state_type: NotificationType) -> bool:
|
||||
"""检查特定状态是否活跃"""
|
||||
return state_type in self._active_states
|
||||
|
||||
def get_notification_history(
|
||||
self, sender: Optional[str] = None, target: Optional[str] = None, limit: Optional[int] = None
|
||||
) -> List[Notification]:
|
||||
"""获取通知历史
|
||||
|
||||
Args:
|
||||
sender: 过滤特定发送者的通知
|
||||
target: 过滤特定接收者的通知
|
||||
limit: 限制返回数量
|
||||
"""
|
||||
history = self._notification_history
|
||||
|
||||
if sender:
|
||||
history = [n for n in history if n.sender == sender]
|
||||
if target:
|
||||
history = [n for n in history if n.target == target]
|
||||
|
||||
if limit is not None:
|
||||
history = history[-limit:]
|
||||
|
||||
return history
|
||||
|
||||
def __str__(self):
|
||||
str = ""
|
||||
for target, handlers in self._handlers.items():
|
||||
for notification_type, handler_list in handlers.items():
|
||||
str += f"NotificationManager for {target} {notification_type} {handler_list}"
|
||||
return str
|
||||
|
||||
|
||||
# 一些常用的通知创建函数
|
||||
def create_new_message_notification(sender: str, target: str, message: Dict[str, Any]) -> Notification:
|
||||
"""创建新消息通知"""
|
||||
return Notification(
|
||||
type=NotificationType.NEW_MESSAGE,
|
||||
timestamp=datetime.now().timestamp(),
|
||||
sender=sender,
|
||||
target=target,
|
||||
data={
|
||||
"message_id": message.get("message_id"),
|
||||
"processed_plain_text": message.get("processed_plain_text"),
|
||||
"detailed_plain_text": message.get("detailed_plain_text"),
|
||||
"user_info": message.get("user_info"),
|
||||
"time": message.get("time"),
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
def create_cold_chat_notification(sender: str, target: str, is_cold: bool) -> StateNotification:
|
||||
"""创建冷场状态通知"""
|
||||
return StateNotification(
|
||||
type=NotificationType.COLD_CHAT,
|
||||
timestamp=datetime.now().timestamp(),
|
||||
sender=sender,
|
||||
target=target,
|
||||
data={"is_cold": is_cold},
|
||||
is_active=is_cold,
|
||||
)
|
||||
|
||||
|
||||
def create_active_chat_notification(sender: str, target: str, is_active: bool) -> StateNotification:
|
||||
"""创建活跃状态通知"""
|
||||
return StateNotification(
|
||||
type=NotificationType.ACTIVE_CHAT,
|
||||
timestamp=datetime.now().timestamp(),
|
||||
sender=sender,
|
||||
target=target,
|
||||
data={"is_active": is_active},
|
||||
is_active=is_active,
|
||||
)
|
||||
|
||||
|
||||
class ChatStateManager:
|
||||
"""聊天状态管理器"""
|
||||
|
||||
def __init__(self):
|
||||
self.current_state = ChatState.NORMAL
|
||||
self.state_info = ChatStateInfo(state=ChatState.NORMAL)
|
||||
self.state_history: list[ChatStateInfo] = []
|
||||
|
||||
def update_state(self, new_state: ChatState, **kwargs):
|
||||
"""更新聊天状态
|
||||
|
||||
Args:
|
||||
new_state: 新的状态
|
||||
**kwargs: 其他状态信息
|
||||
"""
|
||||
self.current_state = new_state
|
||||
self.state_info.state = new_state
|
||||
|
||||
# 更新其他状态信息
|
||||
for key, value in kwargs.items():
|
||||
if hasattr(self.state_info, key):
|
||||
setattr(self.state_info, key, value)
|
||||
|
||||
# 记录状态历史
|
||||
self.state_history.append(self.state_info)
|
||||
|
||||
def get_current_state_info(self) -> ChatStateInfo:
|
||||
"""获取当前状态信息"""
|
||||
return self.state_info
|
||||
|
||||
def get_state_history(self) -> list[ChatStateInfo]:
|
||||
"""获取状态历史"""
|
||||
return self.state_history
|
||||
|
||||
def is_cold_chat(self, threshold: float = 60.0) -> bool:
|
||||
"""判断是否处于冷场状态
|
||||
|
||||
Args:
|
||||
threshold: 冷场阈值（秒）
|
||||
|
||||
Returns:
|
||||
bool: 是否冷场
|
||||
"""
|
||||
if not self.state_info.last_message_time:
|
||||
return True
|
||||
|
||||
current_time = datetime.now().timestamp()
|
||||
return (current_time - self.state_info.last_message_time) > threshold
|
||||
|
||||
def is_active_chat(self, threshold: float = 5.0) -> bool:
|
||||
"""判断是否处于活跃状态
|
||||
|
||||
Args:
|
||||
threshold: 活跃阈值（秒）
|
||||
|
||||
Returns:
|
||||
bool: 是否活跃
|
||||
"""
|
||||
if not self.state_info.last_message_time:
|
||||
return False
|
||||
|
||||
current_time = datetime.now().timestamp()
|
||||
return (current_time - self.state_info.last_message_time) <= threshold
|
||||
701
src/chat/brain_chat/PFC/conversation.py
Normal file
701
src/chat/brain_chat/PFC/conversation.py
Normal file
@@ -0,0 +1,701 @@
|
||||
import time
|
||||
import asyncio
|
||||
import datetime
|
||||
|
||||
# from .message_storage import MongoDBMessageStorage
|
||||
from src.plugins.utils.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat
|
||||
|
||||
# from ...config.config import global_config
|
||||
from typing import Dict, Any, Optional
|
||||
from ..chat.message import Message
|
||||
from .pfc_types import ConversationState
|
||||
from .pfc import ChatObserver, GoalAnalyzer
|
||||
from .message_sender import DirectMessageSender
|
||||
from src.common.logger_manager import get_logger
|
||||
from .action_planner import ActionPlanner
|
||||
from .observation_info import ObservationInfo
|
||||
from .conversation_info import ConversationInfo # 确保导入 ConversationInfo
|
||||
from .reply_generator import ReplyGenerator
|
||||
from ..chat.chat_stream import ChatStream
|
||||
from maim_message import UserInfo
|
||||
from src.plugins.chat.chat_stream import chat_manager
|
||||
from .pfc_KnowledgeFetcher import KnowledgeFetcher
|
||||
from .waiter import Waiter
|
||||
|
||||
import traceback
|
||||
from rich.traceback import install
|
||||
|
||||
install(extra_lines=3)
|
||||
|
||||
logger = get_logger("pfc")
|
||||
|
||||
|
||||
class Conversation:
|
||||
"""对话类，负责管理单个对话的状态和行为"""
|
||||
|
||||
def __init__(self, stream_id: str, private_name: str):
|
||||
"""初始化对话实例
|
||||
|
||||
Args:
|
||||
stream_id: 聊天流ID
|
||||
"""
|
||||
self.stream_id = stream_id
|
||||
self.private_name = private_name
|
||||
self.state = ConversationState.INIT
|
||||
self.should_continue = False
|
||||
self.ignore_until_timestamp: Optional[float] = None
|
||||
|
||||
# 回复相关
|
||||
self.generated_reply = ""
|
||||
|
||||
async def _initialize(self):
|
||||
"""初始化实例，注册所有组件"""
|
||||
|
||||
try:
|
||||
self.action_planner = ActionPlanner(self.stream_id, self.private_name)
|
||||
self.goal_analyzer = GoalAnalyzer(self.stream_id, self.private_name)
|
||||
self.reply_generator = ReplyGenerator(self.stream_id, self.private_name)
|
||||
self.knowledge_fetcher = KnowledgeFetcher(self.private_name)
|
||||
self.waiter = Waiter(self.stream_id, self.private_name)
|
||||
self.direct_sender = DirectMessageSender(self.private_name)
|
||||
|
||||
# 获取聊天流信息
|
||||
self.chat_stream = chat_manager.get_stream(self.stream_id)
|
||||
|
||||
self.stop_action_planner = False
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]初始化对话实例：注册运行组件失败: {e}")
|
||||
logger.error(f"[私聊][{self.private_name}]{traceback.format_exc()}")
|
||||
raise
|
||||
|
||||
try:
|
||||
# 决策所需要的信息，包括自身自信和观察信息两部分
|
||||
# 注册观察器和观测信息
|
||||
self.chat_observer = ChatObserver.get_instance(self.stream_id, self.private_name)
|
||||
self.chat_observer.start()
|
||||
self.observation_info = ObservationInfo(self.private_name)
|
||||
self.observation_info.bind_to_chat_observer(self.chat_observer)
|
||||
# print(self.chat_observer.get_cached_messages(limit=)
|
||||
|
||||
self.conversation_info = ConversationInfo()
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]初始化对话实例：注册信息组件失败: {e}")
|
||||
logger.error(f"[私聊][{self.private_name}]{traceback.format_exc()}")
|
||||
raise
|
||||
try:
|
||||
logger.info(f"[私聊][{self.private_name}]为 {self.stream_id} 加载初始聊天记录...")
|
||||
initial_messages = get_raw_msg_before_timestamp_with_chat( #
|
||||
chat_id=self.stream_id,
|
||||
timestamp=time.time(),
|
||||
limit=30, # 加载最近30条作为初始上下文，可以调整
|
||||
)
|
||||
chat_talking_prompt = await build_readable_messages(
|
||||
initial_messages,
|
||||
replace_bot_name=True,
|
||||
merge_messages=False,
|
||||
timestamp_mode="relative",
|
||||
read_mark=0.0,
|
||||
)
|
||||
if initial_messages:
|
||||
# 将加载的消息填充到 ObservationInfo 的 chat_history
|
||||
self.observation_info.chat_history = initial_messages
|
||||
self.observation_info.chat_history_str = chat_talking_prompt + "\n"
|
||||
self.observation_info.chat_history_count = len(initial_messages)
|
||||
|
||||
# 更新 ObservationInfo 中的时间戳等信息
|
||||
last_msg = initial_messages[-1]
|
||||
self.observation_info.last_message_time = last_msg.get("time")
|
||||
last_user_info = UserInfo.from_dict(last_msg.get("user_info", {}))
|
||||
self.observation_info.last_message_sender = last_user_info.user_id
|
||||
self.observation_info.last_message_content = last_msg.get("processed_plain_text", "")
|
||||
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]成功加载 {len(initial_messages)} 条初始聊天记录。最后一条消息时间: {self.observation_info.last_message_time}"
|
||||
)
|
||||
|
||||
# 让 ChatObserver 从加载的最后一条消息之后开始同步
|
||||
self.chat_observer.last_message_time = self.observation_info.last_message_time
|
||||
self.chat_observer.last_message_read = last_msg # 更新 observer 的最后读取记录
|
||||
else:
|
||||
logger.info(f"[私聊][{self.private_name}]没有找到初始聊天记录。")
|
||||
|
||||
except Exception as load_err:
|
||||
logger.error(f"[私聊][{self.private_name}]加载初始聊天记录时出错: {load_err}")
|
||||
# 出错也要继续，只是没有历史记录而已
|
||||
# 组件准备完成，启动该论对话
|
||||
self.should_continue = True
|
||||
asyncio.create_task(self.start())
|
||||
|
||||
async def start(self):
|
||||
"""开始对话流程"""
|
||||
try:
|
||||
logger.info(f"[私聊][{self.private_name}]对话系统启动中...")
|
||||
asyncio.create_task(self._plan_and_action_loop())
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]启动对话系统失败: {e}")
|
||||
raise
|
||||
|
||||
async def _plan_and_action_loop(self):
|
||||
"""思考步，PFC核心循环模块"""
|
||||
while self.should_continue:
|
||||
# 忽略逻辑
|
||||
if self.ignore_until_timestamp and time.time() < self.ignore_until_timestamp:
|
||||
await asyncio.sleep(30)
|
||||
continue
|
||||
elif self.ignore_until_timestamp and time.time() >= self.ignore_until_timestamp:
|
||||
logger.info(f"[私聊][{self.private_name}]忽略时间已到 {self.stream_id}，准备结束对话。")
|
||||
self.ignore_until_timestamp = None
|
||||
self.should_continue = False
|
||||
continue
|
||||
try:
|
||||
# --- 在规划前记录当前新消息数量 ---
|
||||
initial_new_message_count = 0
|
||||
if hasattr(self.observation_info, "new_messages_count"):
|
||||
initial_new_message_count = self.observation_info.new_messages_count + 1 # 算上麦麦自己发的那一条
|
||||
else:
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]ObservationInfo missing 'new_messages_count' before planning."
|
||||
)
|
||||
|
||||
# --- 调用 Action Planner ---
|
||||
# 传递 self.conversation_info.last_successful_reply_action
|
||||
action, reason = await self.action_planner.plan(
|
||||
self.observation_info, self.conversation_info, self.conversation_info.last_successful_reply_action
|
||||
)
|
||||
|
||||
# --- 规划后检查是否有 *更多* 新消息到达 ---
|
||||
current_new_message_count = 0
|
||||
if hasattr(self.observation_info, "new_messages_count"):
|
||||
current_new_message_count = self.observation_info.new_messages_count
|
||||
else:
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]ObservationInfo missing 'new_messages_count' after planning."
|
||||
)
|
||||
|
||||
if current_new_message_count > initial_new_message_count + 2:
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]规划期间发现新增消息 ({initial_new_message_count} -> {current_new_message_count})，跳过本次行动，重新规划"
|
||||
)
|
||||
# 如果规划期间有新消息，也应该重置上次回复状态，因为现在要响应新消息了
|
||||
self.conversation_info.last_successful_reply_action = None
|
||||
await asyncio.sleep(0.1)
|
||||
continue
|
||||
|
||||
# 包含 send_new_message
|
||||
if initial_new_message_count > 0 and action in ["direct_reply", "send_new_message"]:
|
||||
if hasattr(self.observation_info, "clear_unprocessed_messages"):
|
||||
logger.debug(
|
||||
f"[私聊][{self.private_name}]准备执行 {action}，清理 {initial_new_message_count} 条规划时已知的新消息。"
|
||||
)
|
||||
await self.observation_info.clear_unprocessed_messages()
|
||||
if hasattr(self.observation_info, "new_messages_count"):
|
||||
self.observation_info.new_messages_count = 0
|
||||
else:
|
||||
logger.error(
|
||||
f"[私聊][{self.private_name}]无法清理未处理消息: ObservationInfo 缺少 clear_unprocessed_messages 方法！"
|
||||
)
|
||||
|
||||
await self._handle_action(action, reason, self.observation_info, self.conversation_info)
|
||||
|
||||
# 检查是否需要结束对话 (逻辑不变)
|
||||
goal_ended = False
|
||||
if hasattr(self.conversation_info, "goal_list") and self.conversation_info.goal_list:
|
||||
for goal_item in self.conversation_info.goal_list:
|
||||
if isinstance(goal_item, dict):
|
||||
current_goal = goal_item.get("goal")
|
||||
|
||||
if current_goal == "结束对话":
|
||||
goal_ended = True
|
||||
break
|
||||
|
||||
if goal_ended:
|
||||
self.should_continue = False
|
||||
logger.info(f"[私聊][{self.private_name}]检测到'结束对话'目标，停止循环。")
|
||||
|
||||
except Exception as loop_err:
|
||||
logger.error(f"[私聊][{self.private_name}]PFC主循环出错: {loop_err}")
|
||||
logger.error(f"[私聊][{self.private_name}]{traceback.format_exc()}")
|
||||
await asyncio.sleep(1)
|
||||
|
||||
if self.should_continue:
|
||||
await asyncio.sleep(0.1)
|
||||
|
||||
logger.info(f"[私聊][{self.private_name}]PFC 循环结束 for stream_id: {self.stream_id}")
|
||||
|
||||
def _check_new_messages_after_planning(self):
|
||||
"""检查在规划后是否有新消息"""
|
||||
# 检查 ObservationInfo 是否已初始化并且有 new_messages_count 属性
|
||||
if not hasattr(self, "observation_info") or not hasattr(self.observation_info, "new_messages_count"):
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]ObservationInfo 未初始化或缺少 'new_messages_count' 属性，无法检查新消息。"
|
||||
)
|
||||
return False # 或者根据需要抛出错误
|
||||
|
||||
if self.observation_info.new_messages_count > 2:
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]生成/执行动作期间收到 {self.observation_info.new_messages_count} 条新消息，取消当前动作并重新规划"
|
||||
)
|
||||
# 如果有新消息，也应该重置上次回复状态
|
||||
if hasattr(self, "conversation_info"): # 确保 conversation_info 已初始化
|
||||
self.conversation_info.last_successful_reply_action = None
|
||||
else:
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]ConversationInfo 未初始化，无法重置 last_successful_reply_action。"
|
||||
)
|
||||
return True
|
||||
return False
|
||||
|
||||
def _convert_to_message(self, msg_dict: Dict[str, Any]) -> Message:
|
||||
"""将消息字典转换为Message对象"""
|
||||
try:
|
||||
# 尝试从 msg_dict 直接获取 chat_stream，如果失败则从全局 chat_manager 获取
|
||||
chat_info = msg_dict.get("chat_info")
|
||||
if chat_info and isinstance(chat_info, dict):
|
||||
chat_stream = ChatStream.from_dict(chat_info)
|
||||
elif self.chat_stream: # 使用实例变量中的 chat_stream
|
||||
chat_stream = self.chat_stream
|
||||
else: # Fallback: 尝试从 manager 获取 (可能需要 stream_id)
|
||||
chat_stream = chat_manager.get_stream(self.stream_id)
|
||||
if not chat_stream:
|
||||
raise ValueError(f"无法确定 ChatStream for stream_id {self.stream_id}")
|
||||
|
||||
user_info = UserInfo.from_dict(msg_dict.get("user_info", {}))
|
||||
|
||||
return Message(
|
||||
message_id=msg_dict.get("message_id", f"gen_{time.time()}"), # 提供默认 ID
|
||||
chat_stream=chat_stream, # 使用确定的 chat_stream
|
||||
time=msg_dict.get("time", time.time()), # 提供默认时间
|
||||
user_info=user_info,
|
||||
processed_plain_text=msg_dict.get("processed_plain_text", ""),
|
||||
detailed_plain_text=msg_dict.get("detailed_plain_text", ""),
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"[私聊][{self.private_name}]转换消息时出错: {e}")
|
||||
# 可以选择返回 None 或重新抛出异常，这里选择重新抛出以指示问题
|
||||
raise ValueError(f"无法将字典转换为 Message 对象: {e}") from e
|
||||
|
||||
async def _handle_action(
|
||||
self, action: str, reason: str, observation_info: ObservationInfo, conversation_info: ConversationInfo
|
||||
):
|
||||
"""处理规划的行动"""
|
||||
|
||||
logger.debug(f"[私聊][{self.private_name}]执行行动: {action}, 原因: {reason}")
|
||||
|
||||
# 记录action历史 (逻辑不变)
|
||||
current_action_record = {
|
||||
"action": action,
|
||||
"plan_reason": reason,
|
||||
"status": "start",
|
||||
"time": datetime.datetime.now().strftime("%H:%M:%S"),
|
||||
"final_reason": None,
|
||||
}
|
||||
# 确保 done_action 列表存在
|
||||
if not hasattr(conversation_info, "done_action"):
|
||||
conversation_info.done_action = []
|
||||
conversation_info.done_action.append(current_action_record)
|
||||
action_index = len(conversation_info.done_action) - 1
|
||||
|
||||
action_successful = False # 用于标记动作是否成功完成
|
||||
|
||||
# --- 根据不同的 action 执行 ---
|
||||
|
||||
# send_new_message 失败后执行 wait
|
||||
if action == "send_new_message":
|
||||
max_reply_attempts = 3
|
||||
reply_attempt_count = 0
|
||||
is_suitable = False
|
||||
need_replan = False
|
||||
check_reason = "未进行尝试"
|
||||
final_reply_to_send = ""
|
||||
|
||||
while reply_attempt_count < max_reply_attempts and not is_suitable:
|
||||
reply_attempt_count += 1
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]尝试生成追问回复 (第 {reply_attempt_count}/{max_reply_attempts} 次)..."
|
||||
)
|
||||
self.state = ConversationState.GENERATING
|
||||
|
||||
# 1. 生成回复 (调用 generate 时传入 action_type)
|
||||
self.generated_reply = await self.reply_generator.generate(
|
||||
observation_info, conversation_info, action_type="send_new_message"
|
||||
)
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]第 {reply_attempt_count} 次生成的追问回复: {self.generated_reply}"
|
||||
)
|
||||
|
||||
# 2. 检查回复 (逻辑不变)
|
||||
self.state = ConversationState.CHECKING
|
||||
try:
|
||||
current_goal_str = conversation_info.goal_list[0]["goal"] if conversation_info.goal_list else ""
|
||||
is_suitable, check_reason, need_replan = await self.reply_generator.check_reply(
|
||||
reply=self.generated_reply,
|
||||
goal=current_goal_str,
|
||||
chat_history=observation_info.chat_history,
|
||||
chat_history_str=observation_info.chat_history_str,
|
||||
retry_count=reply_attempt_count - 1,
|
||||
)
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]第 {reply_attempt_count} 次追问检查结果: 合适={is_suitable}, 原因='{check_reason}', 需重新规划={need_replan}"
|
||||
)
|
||||
if is_suitable:
|
||||
final_reply_to_send = self.generated_reply
|
||||
break
|
||||
elif need_replan:
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]第 {reply_attempt_count} 次追问检查建议重新规划，停止尝试。原因: {check_reason}"
|
||||
)
|
||||
break
|
||||
except Exception as check_err:
|
||||
logger.error(
|
||||
f"[私聊][{self.private_name}]第 {reply_attempt_count} 次调用 ReplyChecker (追问) 时出错: {check_err}"
|
||||
)
|
||||
check_reason = f"第 {reply_attempt_count} 次检查过程出错: {check_err}"
|
||||
break
|
||||
|
||||
# 循环结束，处理最终结果
|
||||
if is_suitable:
|
||||
# 检查是否有新消息
|
||||
if self._check_new_messages_after_planning():
|
||||
logger.info(f"[私聊][{self.private_name}]生成追问回复期间收到新消息，取消发送，重新规划行动")
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"有新消息，取消发送追问: {final_reply_to_send}"}
|
||||
)
|
||||
return # 直接返回，重新规划
|
||||
|
||||
# 发送合适的回复
|
||||
self.generated_reply = final_reply_to_send
|
||||
# --- 在这里调用 _send_reply ---
|
||||
await self._send_reply() # <--- 调用恢复后的函数
|
||||
|
||||
# 更新状态: 标记上次成功是 send_new_message
|
||||
self.conversation_info.last_successful_reply_action = "send_new_message"
|
||||
action_successful = True # 标记动作成功
|
||||
|
||||
elif need_replan:
|
||||
# 打回动作决策
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]经过 {reply_attempt_count} 次尝试，追问回复决定打回动作决策。打回原因: {check_reason}"
|
||||
)
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"追问尝试{reply_attempt_count}次后打回: {check_reason}"}
|
||||
)
|
||||
|
||||
else:
|
||||
# 追问失败
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]经过 {reply_attempt_count} 次尝试，未能生成合适的追问回复。最终原因: {check_reason}"
|
||||
)
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"追问尝试{reply_attempt_count}次后失败: {check_reason}"}
|
||||
)
|
||||
# 重置状态: 追问失败，下次用初始 prompt
|
||||
self.conversation_info.last_successful_reply_action = None
|
||||
|
||||
# 执行 Wait 操作
|
||||
logger.info(f"[私聊][{self.private_name}]由于无法生成合适追问回复，执行 'wait' 操作...")
|
||||
self.state = ConversationState.WAITING
|
||||
await self.waiter.wait(self.conversation_info)
|
||||
wait_action_record = {
|
||||
"action": "wait",
|
||||
"plan_reason": "因 send_new_message 多次尝试失败而执行的后备等待",
|
||||
"status": "done",
|
||||
"time": datetime.datetime.now().strftime("%H:%M:%S"),
|
||||
"final_reason": None,
|
||||
}
|
||||
conversation_info.done_action.append(wait_action_record)
|
||||
|
||||
elif action == "direct_reply":
|
||||
max_reply_attempts = 3
|
||||
reply_attempt_count = 0
|
||||
is_suitable = False
|
||||
need_replan = False
|
||||
check_reason = "未进行尝试"
|
||||
final_reply_to_send = ""
|
||||
|
||||
while reply_attempt_count < max_reply_attempts and not is_suitable:
|
||||
reply_attempt_count += 1
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]尝试生成首次回复 (第 {reply_attempt_count}/{max_reply_attempts} 次)..."
|
||||
)
|
||||
self.state = ConversationState.GENERATING
|
||||
|
||||
# 1. 生成回复
|
||||
self.generated_reply = await self.reply_generator.generate(
|
||||
observation_info, conversation_info, action_type="direct_reply"
|
||||
)
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]第 {reply_attempt_count} 次生成的首次回复: {self.generated_reply}"
|
||||
)
|
||||
|
||||
# 2. 检查回复
|
||||
self.state = ConversationState.CHECKING
|
||||
try:
|
||||
current_goal_str = conversation_info.goal_list[0]["goal"] if conversation_info.goal_list else ""
|
||||
is_suitable, check_reason, need_replan = await self.reply_generator.check_reply(
|
||||
reply=self.generated_reply,
|
||||
goal=current_goal_str,
|
||||
chat_history=observation_info.chat_history,
|
||||
chat_history_str=observation_info.chat_history_str,
|
||||
retry_count=reply_attempt_count - 1,
|
||||
)
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]第 {reply_attempt_count} 次首次回复检查结果: 合适={is_suitable}, 原因='{check_reason}', 需重新规划={need_replan}"
|
||||
)
|
||||
if is_suitable:
|
||||
final_reply_to_send = self.generated_reply
|
||||
break
|
||||
elif need_replan:
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]第 {reply_attempt_count} 次首次回复检查建议重新规划，停止尝试。原因: {check_reason}"
|
||||
)
|
||||
break
|
||||
except Exception as check_err:
|
||||
logger.error(
|
||||
f"[私聊][{self.private_name}]第 {reply_attempt_count} 次调用 ReplyChecker (首次回复) 时出错: {check_err}"
|
||||
)
|
||||
check_reason = f"第 {reply_attempt_count} 次检查过程出错: {check_err}"
|
||||
break
|
||||
|
||||
# 循环结束，处理最终结果
|
||||
if is_suitable:
|
||||
# 检查是否有新消息
|
||||
if self._check_new_messages_after_planning():
|
||||
logger.info(f"[私聊][{self.private_name}]生成首次回复期间收到新消息，取消发送，重新规划行动")
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"有新消息，取消发送首次回复: {final_reply_to_send}"}
|
||||
)
|
||||
return # 直接返回，重新规划
|
||||
|
||||
# 发送合适的回复
|
||||
self.generated_reply = final_reply_to_send
|
||||
# --- 在这里调用 _send_reply ---
|
||||
await self._send_reply() # <--- 调用恢复后的函数
|
||||
|
||||
# 更新状态: 标记上次成功是 direct_reply
|
||||
self.conversation_info.last_successful_reply_action = "direct_reply"
|
||||
action_successful = True # 标记动作成功
|
||||
|
||||
elif need_replan:
|
||||
# 打回动作决策
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]经过 {reply_attempt_count} 次尝试，首次回复决定打回动作决策。打回原因: {check_reason}"
|
||||
)
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"首次回复尝试{reply_attempt_count}次后打回: {check_reason}"}
|
||||
)
|
||||
|
||||
else:
|
||||
# 首次回复失败
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]经过 {reply_attempt_count} 次尝试，未能生成合适的首次回复。最终原因: {check_reason}"
|
||||
)
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"首次回复尝试{reply_attempt_count}次后失败: {check_reason}"}
|
||||
)
|
||||
# 重置状态: 首次回复失败，下次还是用初始 prompt
|
||||
self.conversation_info.last_successful_reply_action = None
|
||||
|
||||
# 执行 Wait 操作 (保持原有逻辑)
|
||||
logger.info(f"[私聊][{self.private_name}]由于无法生成合适首次回复，执行 'wait' 操作...")
|
||||
self.state = ConversationState.WAITING
|
||||
await self.waiter.wait(self.conversation_info)
|
||||
wait_action_record = {
|
||||
"action": "wait",
|
||||
"plan_reason": "因 direct_reply 多次尝试失败而执行的后备等待",
|
||||
"status": "done",
|
||||
"time": datetime.datetime.now().strftime("%H:%M:%S"),
|
||||
"final_reason": None,
|
||||
}
|
||||
conversation_info.done_action.append(wait_action_record)
|
||||
|
||||
elif action == "fetch_knowledge":
|
||||
self.state = ConversationState.FETCHING
|
||||
knowledge_query = reason
|
||||
try:
|
||||
# 检查 knowledge_fetcher 是否存在
|
||||
if not hasattr(self, "knowledge_fetcher"):
|
||||
logger.error(f"[私聊][{self.private_name}]KnowledgeFetcher 未初始化，无法获取知识。")
|
||||
raise AttributeError("KnowledgeFetcher not initialized")
|
||||
|
||||
knowledge, source = await self.knowledge_fetcher.fetch(knowledge_query, observation_info.chat_history)
|
||||
logger.info(f"[私聊][{self.private_name}]获取到知识: {knowledge[:100]}..., 来源: {source}")
|
||||
if knowledge:
|
||||
# 确保 knowledge_list 存在
|
||||
if not hasattr(conversation_info, "knowledge_list"):
|
||||
conversation_info.knowledge_list = []
|
||||
conversation_info.knowledge_list.append(
|
||||
{"query": knowledge_query, "knowledge": knowledge, "source": source}
|
||||
)
|
||||
action_successful = True
|
||||
except Exception as fetch_err:
|
||||
logger.error(f"[私聊][{self.private_name}]获取知识时出错: {str(fetch_err)}")
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"获取知识失败: {str(fetch_err)}"}
|
||||
)
|
||||
self.conversation_info.last_successful_reply_action = None # 重置状态
|
||||
|
||||
elif action == "rethink_goal":
|
||||
self.state = ConversationState.RETHINKING
|
||||
try:
|
||||
# 检查 goal_analyzer 是否存在
|
||||
if not hasattr(self, "goal_analyzer"):
|
||||
logger.error(f"[私聊][{self.private_name}]GoalAnalyzer 未初始化，无法重新思考目标。")
|
||||
raise AttributeError("GoalAnalyzer not initialized")
|
||||
await self.goal_analyzer.analyze_goal(conversation_info, observation_info)
|
||||
action_successful = True
|
||||
except Exception as rethink_err:
|
||||
logger.error(f"[私聊][{self.private_name}]重新思考目标时出错: {rethink_err}")
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"重新思考目标失败: {rethink_err}"}
|
||||
)
|
||||
self.conversation_info.last_successful_reply_action = None # 重置状态
|
||||
|
||||
elif action == "listening":
|
||||
self.state = ConversationState.LISTENING
|
||||
logger.info(f"[私聊][{self.private_name}]倾听对方发言...")
|
||||
try:
|
||||
# 检查 waiter 是否存在
|
||||
if not hasattr(self, "waiter"):
|
||||
logger.error(f"[私聊][{self.private_name}]Waiter 未初始化，无法倾听。")
|
||||
raise AttributeError("Waiter not initialized")
|
||||
await self.waiter.wait_listening(conversation_info)
|
||||
action_successful = True # Listening 完成就算成功
|
||||
except Exception as listen_err:
|
||||
logger.error(f"[私聊][{self.private_name}]倾听时出错: {listen_err}")
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"倾听失败: {listen_err}"}
|
||||
)
|
||||
self.conversation_info.last_successful_reply_action = None # 重置状态
|
||||
|
||||
elif action == "say_goodbye":
|
||||
self.state = ConversationState.GENERATING # 也可以定义一个新的状态，如 ENDING
|
||||
logger.info(f"[私聊][{self.private_name}]执行行动: 生成并发送告别语...")
|
||||
try:
|
||||
# 1. 生成告别语 (使用 'say_goodbye' action_type)
|
||||
self.generated_reply = await self.reply_generator.generate(
|
||||
observation_info, conversation_info, action_type="say_goodbye"
|
||||
)
|
||||
logger.info(f"[私聊][{self.private_name}]生成的告别语: {self.generated_reply}")
|
||||
|
||||
# 2. 直接发送告别语 (不经过检查)
|
||||
if self.generated_reply: # 确保生成了内容
|
||||
await self._send_reply() # 调用发送方法
|
||||
# 发送成功后，标记动作成功
|
||||
action_successful = True
|
||||
logger.info(f"[私聊][{self.private_name}]告别语已发送。")
|
||||
else:
|
||||
logger.warning(f"[私聊][{self.private_name}]未能生成告别语内容，无法发送。")
|
||||
action_successful = False # 标记动作失败
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": "未能生成告别语内容"}
|
||||
)
|
||||
|
||||
# 3. 无论是否发送成功，都准备结束对话
|
||||
self.should_continue = False
|
||||
logger.info(f"[私聊][{self.private_name}]发送告别语流程结束，即将停止对话实例。")
|
||||
|
||||
except Exception as goodbye_err:
|
||||
logger.error(f"[私聊][{self.private_name}]生成或发送告别语时出错: {goodbye_err}")
|
||||
logger.error(f"[私聊][{self.private_name}]{traceback.format_exc()}")
|
||||
# 即使出错，也结束对话
|
||||
self.should_continue = False
|
||||
action_successful = False # 标记动作失败
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"生成或发送告别语时出错: {goodbye_err}"}
|
||||
)
|
||||
|
||||
elif action == "end_conversation":
|
||||
# 这个分支现在只会在 action_planner 最终决定不告别时被调用
|
||||
self.should_continue = False
|
||||
logger.info(f"[私聊][{self.private_name}]收到最终结束指令，停止对话...")
|
||||
action_successful = True # 标记这个指令本身是成功的
|
||||
|
||||
elif action == "block_and_ignore":
|
||||
logger.info(f"[私聊][{self.private_name}]不想再理你了...")
|
||||
ignore_duration_seconds = 10 * 60
|
||||
self.ignore_until_timestamp = time.time() + ignore_duration_seconds
|
||||
logger.info(
|
||||
f"[私聊][{self.private_name}]将忽略此对话直到: {datetime.datetime.fromtimestamp(self.ignore_until_timestamp)}"
|
||||
)
|
||||
self.state = ConversationState.IGNORED
|
||||
action_successful = True # 标记动作成功
|
||||
|
||||
else: # 对应 'wait' 动作
|
||||
self.state = ConversationState.WAITING
|
||||
logger.info(f"[私聊][{self.private_name}]等待更多信息...")
|
||||
try:
|
||||
# 检查 waiter 是否存在
|
||||
if not hasattr(self, "waiter"):
|
||||
logger.error(f"[私聊][{self.private_name}]Waiter 未初始化，无法等待。")
|
||||
raise AttributeError("Waiter not initialized")
|
||||
_timeout_occurred = await self.waiter.wait(self.conversation_info)
|
||||
action_successful = True # Wait 完成就算成功
|
||||
except Exception as wait_err:
|
||||
logger.error(f"[私聊][{self.private_name}]等待时出错: {wait_err}")
|
||||
conversation_info.done_action[action_index].update(
|
||||
{"status": "recall", "final_reason": f"等待失败: {wait_err}"}
|
||||
)
|
||||
self.conversation_info.last_successful_reply_action = None # 重置状态
|
||||
|
||||
# --- 更新 Action History 状态 ---
|
||||
# 只有当动作本身成功时，才更新状态为 done
|
||||
if action_successful:
|
||||
conversation_info.done_action[action_index].update(
|
||||
{
|
||||
"status": "done",
|
||||
"time": datetime.datetime.now().strftime("%H:%M:%S"),
|
||||
}
|
||||
)
|
||||
# 重置状态: 对于非回复类动作的成功，清除上次回复状态
|
||||
if action not in ["direct_reply", "send_new_message"]:
|
||||
self.conversation_info.last_successful_reply_action = None
|
||||
logger.debug(f"[私聊][{self.private_name}]动作 {action} 成功完成，重置 last_successful_reply_action")
|
||||
# 如果动作是 recall 状态，在各自的处理逻辑中已经更新了 done_action
|
||||
|
||||
async def _send_reply(self):
|
||||
"""发送回复"""
|
||||
if not self.generated_reply:
|
||||
logger.warning(f"[私聊][{self.private_name}]没有生成回复内容，无法发送。")
|
||||
return
|
||||
|
||||
try:
|
||||
_current_time = time.time()
|
||||
reply_content = self.generated_reply
|
||||
|
||||
# 发送消息 (确保 direct_sender 和 chat_stream 有效)
|
||||
if not hasattr(self, "direct_sender") or not self.direct_sender:
|
||||
logger.error(f"[私聊][{self.private_name}]DirectMessageSender 未初始化，无法发送回复。")
|
||||
return
|
||||
if not self.chat_stream:
|
||||
logger.error(f"[私聊][{self.private_name}]ChatStream 未初始化，无法发送回复。")
|
||||
return
|
||||
|
||||
await self.direct_sender.send_message(chat_stream=self.chat_stream, content=reply_content)
|
||||
|
||||
# 发送成功后，手动触发 observer 更新可能导致重复处理自己发送的消息
|
||||
# 更好的做法是依赖 observer 的自动轮询或数据库触发器（如果支持）
|
||||
# 暂时注释掉，观察是否影响 ObservationInfo 的更新
|
||||
# self.chat_observer.trigger_update()
|
||||
# if not await self.chat_observer.wait_for_update():
|
||||
# logger.warning(f"[私聊][{self.private_name}]等待 ChatObserver 更新完成超时")
|
||||
|
||||
self.state = ConversationState.ANALYZING # 更新状态
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]发送消息或更新状态时失败: {str(e)}")
|
||||
logger.error(f"[私聊][{self.private_name}]{traceback.format_exc()}")
|
||||
self.state = ConversationState.ANALYZING
|
||||
|
||||
async def _send_timeout_message(self):
|
||||
"""发送超时结束消息"""
|
||||
try:
|
||||
messages = self.chat_observer.get_cached_messages(limit=1)
|
||||
if not messages:
|
||||
return
|
||||
|
||||
latest_message = self._convert_to_message(messages[0])
|
||||
await self.direct_sender.send_message(
|
||||
chat_stream=self.chat_stream, content="TODO:超时消息", reply_to_message=latest_message
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]发送超时消息失败: {str(e)}")
|
||||
10
src/chat/brain_chat/PFC/conversation_info.py
Normal file
10
src/chat/brain_chat/PFC/conversation_info.py
Normal file
@@ -0,0 +1,10 @@
|
||||
from typing import Optional
|
||||
|
||||
|
||||
class ConversationInfo:
|
||||
def __init__(self):
|
||||
self.done_action = []
|
||||
self.goal_list = []
|
||||
self.knowledge_list = []
|
||||
self.memory_list = []
|
||||
self.last_successful_reply_action: Optional[str] = None
|
||||
81
src/chat/brain_chat/PFC/message_sender.py
Normal file
81
src/chat/brain_chat/PFC/message_sender.py
Normal file
@@ -0,0 +1,81 @@
|
||||
import time
|
||||
from typing import Optional
|
||||
from src.common.logger import get_module_logger
|
||||
from ..chat.chat_stream import ChatStream
|
||||
from ..chat.message import Message
|
||||
from maim_message import UserInfo, Seg
|
||||
from src.plugins.chat.message import MessageSending, MessageSet
|
||||
from src.plugins.chat.message_sender import message_manager
|
||||
from ..storage.storage import MessageStorage
|
||||
from ...config.config import global_config
|
||||
from rich.traceback import install
|
||||
|
||||
install(extra_lines=3)
|
||||
|
||||
|
||||
logger = get_module_logger("message_sender")
|
||||
|
||||
|
||||
class DirectMessageSender:
|
||||
"""直接消息发送器"""
|
||||
|
||||
def __init__(self, private_name: str):
|
||||
self.private_name = private_name
|
||||
self.storage = MessageStorage()
|
||||
|
||||
async def send_message(
|
||||
self,
|
||||
chat_stream: ChatStream,
|
||||
content: str,
|
||||
reply_to_message: Optional[Message] = None,
|
||||
) -> None:
|
||||
"""发送消息到聊天流
|
||||
|
||||
Args:
|
||||
chat_stream: 聊天流
|
||||
content: 消息内容
|
||||
reply_to_message: 要回复的消息（可选）
|
||||
"""
|
||||
try:
|
||||
# 创建消息内容
|
||||
segments = Seg(type="seglist", data=[Seg(type="text", data=content)])
|
||||
|
||||
# 获取麦麦的信息
|
||||
bot_user_info = UserInfo(
|
||||
user_id=global_config.BOT_QQ,
|
||||
user_nickname=global_config.BOT_NICKNAME,
|
||||
platform=chat_stream.platform,
|
||||
)
|
||||
|
||||
# 用当前时间作为message_id，和之前那套sender一样
|
||||
message_id = f"dm{round(time.time(), 2)}"
|
||||
|
||||
# 构建消息对象
|
||||
message = MessageSending(
|
||||
message_id=message_id,
|
||||
chat_stream=chat_stream,
|
||||
bot_user_info=bot_user_info,
|
||||
sender_info=reply_to_message.message_info.user_info if reply_to_message else None,
|
||||
message_segment=segments,
|
||||
reply=reply_to_message,
|
||||
is_head=True,
|
||||
is_emoji=False,
|
||||
thinking_start_time=time.time(),
|
||||
)
|
||||
|
||||
# 处理消息
|
||||
await message.process()
|
||||
|
||||
# 不知道有什么用，先留下来了，和之前那套sender一样
|
||||
_message_json = message.to_dict()
|
||||
|
||||
# 发送消息
|
||||
message_set = MessageSet(chat_stream, message_id)
|
||||
message_set.add_message(message)
|
||||
await message_manager.add_message(message_set)
|
||||
await self.storage.store_message(message, chat_stream)
|
||||
logger.info(f"[私聊][{self.private_name}]PFC消息已发送: {content}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]PFC消息发送失败: {str(e)}")
|
||||
raise
|
||||
119
src/chat/brain_chat/PFC/message_storage.py
Normal file
119
src/chat/brain_chat/PFC/message_storage.py
Normal file
@@ -0,0 +1,119 @@
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import List, Dict, Any
|
||||
from src.common.database import db
|
||||
|
||||
|
||||
class MessageStorage(ABC):
|
||||
"""消息存储接口"""
|
||||
|
||||
@abstractmethod
|
||||
async def get_messages_after(self, chat_id: str, message: Dict[str, Any]) -> List[Dict[str, Any]]:
|
||||
"""获取指定消息ID之后的所有消息
|
||||
|
||||
Args:
|
||||
chat_id: 聊天ID
|
||||
message: 消息
|
||||
|
||||
Returns:
|
||||
List[Dict[str, Any]]: 消息列表
|
||||
"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def get_messages_before(self, chat_id: str, time_point: float, limit: int = 5) -> List[Dict[str, Any]]:
|
||||
"""获取指定时间点之前的消息
|
||||
|
||||
Args:
|
||||
chat_id: 聊天ID
|
||||
time_point: 时间戳
|
||||
limit: 最大消息数量
|
||||
|
||||
Returns:
|
||||
List[Dict[str, Any]]: 消息列表
|
||||
"""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def has_new_messages(self, chat_id: str, after_time: float) -> bool:
|
||||
"""检查是否有新消息
|
||||
|
||||
Args:
|
||||
chat_id: 聊天ID
|
||||
after_time: 时间戳
|
||||
|
||||
Returns:
|
||||
bool: 是否有新消息
|
||||
"""
|
||||
pass
|
||||
|
||||
|
||||
class MongoDBMessageStorage(MessageStorage):
|
||||
"""MongoDB消息存储实现"""
|
||||
|
||||
async def get_messages_after(self, chat_id: str, message_time: float) -> List[Dict[str, Any]]:
|
||||
query = {"chat_id": chat_id, "time": {"$gt": message_time}}
|
||||
# print(f"storage_check_message: {message_time}")
|
||||
|
||||
return list(db.messages.find(query).sort("time", 1))
|
||||
|
||||
async def get_messages_before(self, chat_id: str, time_point: float, limit: int = 5) -> List[Dict[str, Any]]:
|
||||
query = {"chat_id": chat_id, "time": {"$lt": time_point}}
|
||||
|
||||
messages = list(db.messages.find(query).sort("time", -1).limit(limit))
|
||||
|
||||
# 将消息按时间正序排列
|
||||
messages.reverse()
|
||||
return messages
|
||||
|
||||
async def has_new_messages(self, chat_id: str, after_time: float) -> bool:
|
||||
query = {"chat_id": chat_id, "time": {"$gt": after_time}}
|
||||
|
||||
return db.messages.find_one(query) is not None
|
||||
|
||||
|
||||
# # 创建一个内存消息存储实现，用于测试
|
||||
# class InMemoryMessageStorage(MessageStorage):
|
||||
# """内存消息存储实现，主要用于测试"""
|
||||
|
||||
# def __init__(self):
|
||||
# self.messages: Dict[str, List[Dict[str, Any]]] = {}
|
||||
|
||||
# async def get_messages_after(self, chat_id: str, message_id: Optional[str] = None) -> List[Dict[str, Any]]:
|
||||
# if chat_id not in self.messages:
|
||||
# return []
|
||||
|
||||
# messages = self.messages[chat_id]
|
||||
# if not message_id:
|
||||
# return messages
|
||||
|
||||
# # 找到message_id的索引
|
||||
# try:
|
||||
# index = next(i for i, m in enumerate(messages) if m["message_id"] == message_id)
|
||||
# return messages[index + 1:]
|
||||
# except StopIteration:
|
||||
# return []
|
||||
|
||||
# async def get_messages_before(self, chat_id: str, time_point: float, limit: int = 5) -> List[Dict[str, Any]]:
|
||||
# if chat_id not in self.messages:
|
||||
# return []
|
||||
|
||||
# messages = [
|
||||
# m for m in self.messages[chat_id]
|
||||
# if m["time"] < time_point
|
||||
# ]
|
||||
|
||||
# return messages[-limit:]
|
||||
|
||||
# async def has_new_messages(self, chat_id: str, after_time: float) -> bool:
|
||||
# if chat_id not in self.messages:
|
||||
# return False
|
||||
|
||||
# return any(m["time"] > after_time for m in self.messages[chat_id])
|
||||
|
||||
# # 测试辅助方法
|
||||
# def add_message(self, chat_id: str, message: Dict[str, Any]):
|
||||
# """添加测试消息"""
|
||||
# if chat_id not in self.messages:
|
||||
# self.messages[chat_id] = []
|
||||
# self.messages[chat_id].append(message)
|
||||
# self.messages[chat_id].sort(key=lambda m: m["time"])
|
||||
389
src/chat/brain_chat/PFC/observation_info.py
Normal file
389
src/chat/brain_chat/PFC/observation_info.py
Normal file
@@ -0,0 +1,389 @@
|
||||
from typing import List, Optional, Dict, Any, Set
|
||||
from maim_message import UserInfo
|
||||
import time
|
||||
from src.common.logger import get_module_logger
|
||||
from .chat_observer import ChatObserver
|
||||
from .chat_states import NotificationHandler, NotificationType, Notification
|
||||
from src.plugins.utils.chat_message_builder import build_readable_messages
|
||||
import traceback # 导入 traceback 用于调试
|
||||
|
||||
logger = get_module_logger("observation_info")
|
||||
|
||||
|
||||
class ObservationInfoHandler(NotificationHandler):
|
||||
"""ObservationInfo的通知处理器"""
|
||||
|
||||
def __init__(self, observation_info: "ObservationInfo", private_name: str):
|
||||
"""初始化处理器
|
||||
|
||||
Args:
|
||||
observation_info: 要更新的ObservationInfo实例
|
||||
private_name: 私聊对象的名称，用于日志记录
|
||||
"""
|
||||
self.observation_info = observation_info
|
||||
# 将 private_name 存储在 handler 实例中
|
||||
self.private_name = private_name
|
||||
|
||||
async def handle_notification(self, notification: Notification): # 添加类型提示
|
||||
# 获取通知类型和数据
|
||||
notification_type = notification.type
|
||||
data = notification.data
|
||||
|
||||
try: # 添加错误处理块
|
||||
if notification_type == NotificationType.NEW_MESSAGE:
|
||||
# 处理新消息通知
|
||||
# logger.debug(f"[私聊][{self.private_name}]收到新消息通知data: {data}") # 可以在需要时取消注释
|
||||
message_id = data.get("message_id")
|
||||
processed_plain_text = data.get("processed_plain_text")
|
||||
detailed_plain_text = data.get("detailed_plain_text")
|
||||
user_info_dict = data.get("user_info") # 先获取字典
|
||||
time_value = data.get("time")
|
||||
|
||||
# 确保 user_info 是字典类型再创建 UserInfo 对象
|
||||
user_info = None
|
||||
if isinstance(user_info_dict, dict):
|
||||
try:
|
||||
user_info = UserInfo.from_dict(user_info_dict)
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"[私聊][{self.private_name}]从字典创建 UserInfo 时出错: {e}, 字典内容: {user_info_dict}"
|
||||
)
|
||||
# 可以选择在这里返回或记录错误，避免后续代码出错
|
||||
return
|
||||
elif user_info_dict is not None:
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]收到的 user_info 不是预期的字典类型: {type(user_info_dict)}"
|
||||
)
|
||||
# 根据需要处理非字典情况，这里暂时返回
|
||||
return
|
||||
|
||||
message = {
|
||||
"message_id": message_id,
|
||||
"processed_plain_text": processed_plain_text,
|
||||
"detailed_plain_text": detailed_plain_text,
|
||||
"user_info": user_info_dict, # 存储原始字典或 UserInfo 对象，取决于你的 update_from_message 如何处理
|
||||
"time": time_value,
|
||||
}
|
||||
# 传递 UserInfo 对象（如果成功创建）或原始字典
|
||||
await self.observation_info.update_from_message(message, user_info) # 修改：传递 user_info 对象
|
||||
|
||||
elif notification_type == NotificationType.COLD_CHAT:
|
||||
# 处理冷场通知
|
||||
is_cold = data.get("is_cold", False)
|
||||
await self.observation_info.update_cold_chat_status(is_cold, time.time()) # 修改：改为 await 调用
|
||||
|
||||
elif notification_type == NotificationType.ACTIVE_CHAT:
|
||||
# 处理活跃通知 (通常由 COLD_CHAT 的反向状态处理)
|
||||
is_active = data.get("is_active", False)
|
||||
self.observation_info.is_cold = not is_active
|
||||
|
||||
elif notification_type == NotificationType.BOT_SPEAKING:
|
||||
# 处理机器人说话通知 (按需实现)
|
||||
self.observation_info.is_typing = False
|
||||
self.observation_info.last_bot_speak_time = time.time()
|
||||
|
||||
elif notification_type == NotificationType.USER_SPEAKING:
|
||||
# 处理用户说话通知
|
||||
self.observation_info.is_typing = False
|
||||
self.observation_info.last_user_speak_time = time.time()
|
||||
|
||||
elif notification_type == NotificationType.MESSAGE_DELETED:
|
||||
# 处理消息删除通知
|
||||
message_id = data.get("message_id")
|
||||
# 从 unprocessed_messages 中移除被删除的消息
|
||||
original_count = len(self.observation_info.unprocessed_messages)
|
||||
self.observation_info.unprocessed_messages = [
|
||||
msg for msg in self.observation_info.unprocessed_messages if msg.get("message_id") != message_id
|
||||
]
|
||||
if len(self.observation_info.unprocessed_messages) < original_count:
|
||||
logger.info(f"[私聊][{self.private_name}]移除了未处理的消息 (ID: {message_id})")
|
||||
|
||||
elif notification_type == NotificationType.USER_JOINED:
|
||||
# 处理用户加入通知 (如果适用私聊场景)
|
||||
user_id = data.get("user_id")
|
||||
if user_id:
|
||||
self.observation_info.active_users.add(str(user_id)) # 确保是字符串
|
||||
|
||||
elif notification_type == NotificationType.USER_LEFT:
|
||||
# 处理用户离开通知 (如果适用私聊场景)
|
||||
user_id = data.get("user_id")
|
||||
if user_id:
|
||||
self.observation_info.active_users.discard(str(user_id)) # 确保是字符串
|
||||
|
||||
elif notification_type == NotificationType.ERROR:
|
||||
# 处理错误通知
|
||||
error_msg = data.get("error", "未提供错误信息")
|
||||
logger.error(f"[私聊][{self.private_name}]收到错误通知: {error_msg}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]处理通知时发生错误: {e}")
|
||||
logger.error(traceback.format_exc()) # 打印详细堆栈信息
|
||||
|
||||
|
||||
# @dataclass <-- 这个，不需要了（递黄瓜）
|
||||
class ObservationInfo:
|
||||
"""决策信息类，用于收集和管理来自chat_observer的通知信息 (手动实现 __init__)"""
|
||||
|
||||
# 类型提示保留，可用于文档和静态分析
|
||||
private_name: str
|
||||
chat_history: List[Dict[str, Any]]
|
||||
chat_history_str: str
|
||||
unprocessed_messages: List[Dict[str, Any]]
|
||||
active_users: Set[str]
|
||||
last_bot_speak_time: Optional[float]
|
||||
last_user_speak_time: Optional[float]
|
||||
last_message_time: Optional[float]
|
||||
last_message_id: Optional[str]
|
||||
last_message_content: str
|
||||
last_message_sender: Optional[str]
|
||||
bot_id: Optional[str]
|
||||
chat_history_count: int
|
||||
new_messages_count: int
|
||||
cold_chat_start_time: Optional[float]
|
||||
cold_chat_duration: float
|
||||
is_typing: bool
|
||||
is_cold_chat: bool
|
||||
changed: bool
|
||||
chat_observer: Optional[ChatObserver]
|
||||
handler: Optional[ObservationInfoHandler]
|
||||
|
||||
def __init__(self, private_name: str):
|
||||
"""
|
||||
手动初始化 ObservationInfo 的所有实例变量。
|
||||
"""
|
||||
|
||||
# 接收的参数
|
||||
self.private_name: str = private_name
|
||||
|
||||
# data_list
|
||||
self.chat_history: List[Dict[str, Any]] = []
|
||||
self.chat_history_str: str = ""
|
||||
self.unprocessed_messages: List[Dict[str, Any]] = []
|
||||
self.active_users: Set[str] = set()
|
||||
|
||||
# data
|
||||
self.last_bot_speak_time: Optional[float] = None
|
||||
self.last_user_speak_time: Optional[float] = None
|
||||
self.last_message_time: Optional[float] = None
|
||||
self.last_message_id: Optional[str] = None
|
||||
self.last_message_content: str = ""
|
||||
self.last_message_sender: Optional[str] = None
|
||||
self.bot_id: Optional[str] = None
|
||||
self.chat_history_count: int = 0
|
||||
self.new_messages_count: int = 0
|
||||
self.cold_chat_start_time: Optional[float] = None
|
||||
self.cold_chat_duration: float = 0.0
|
||||
|
||||
# state
|
||||
self.is_typing: bool = False
|
||||
self.is_cold_chat: bool = False
|
||||
self.changed: bool = False
|
||||
|
||||
# 关联对象
|
||||
self.chat_observer: Optional[ChatObserver] = None
|
||||
|
||||
self.handler: ObservationInfoHandler = ObservationInfoHandler(self, self.private_name)
|
||||
|
||||
def bind_to_chat_observer(self, chat_observer: ChatObserver):
|
||||
"""绑定到指定的chat_observer
|
||||
|
||||
Args:
|
||||
chat_observer: 要绑定的 ChatObserver 实例
|
||||
"""
|
||||
if self.chat_observer:
|
||||
logger.warning(f"[私聊][{self.private_name}]尝试重复绑定 ChatObserver")
|
||||
return
|
||||
|
||||
self.chat_observer = chat_observer
|
||||
try:
|
||||
if not self.handler: # 确保 handler 已经被创建
|
||||
logger.error(f"[私聊][{self.private_name}] 尝试绑定时 handler 未初始化！")
|
||||
self.chat_observer = None # 重置，防止后续错误
|
||||
return
|
||||
|
||||
# 注册关心的通知类型
|
||||
self.chat_observer.notification_manager.register_handler(
|
||||
target="observation_info", notification_type=NotificationType.NEW_MESSAGE, handler=self.handler
|
||||
)
|
||||
self.chat_observer.notification_manager.register_handler(
|
||||
target="observation_info", notification_type=NotificationType.COLD_CHAT, handler=self.handler
|
||||
)
|
||||
# 可以根据需要注册更多通知类型
|
||||
# self.chat_observer.notification_manager.register_handler(
|
||||
# target="observation_info", notification_type=NotificationType.MESSAGE_DELETED, handler=self.handler
|
||||
# )
|
||||
logger.info(f"[私聊][{self.private_name}]成功绑定到 ChatObserver")
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]绑定到 ChatObserver 时出错: {e}")
|
||||
self.chat_observer = None # 绑定失败，重置
|
||||
|
||||
def unbind_from_chat_observer(self):
|
||||
"""解除与chat_observer的绑定"""
|
||||
if (
|
||||
self.chat_observer and hasattr(self.chat_observer, "notification_manager") and self.handler
|
||||
): # 增加 handler 检查
|
||||
try:
|
||||
self.chat_observer.notification_manager.unregister_handler(
|
||||
target="observation_info", notification_type=NotificationType.NEW_MESSAGE, handler=self.handler
|
||||
)
|
||||
self.chat_observer.notification_manager.unregister_handler(
|
||||
target="observation_info", notification_type=NotificationType.COLD_CHAT, handler=self.handler
|
||||
)
|
||||
# 如果注册了其他类型，也要在这里注销
|
||||
# self.chat_observer.notification_manager.unregister_handler(
|
||||
# target="observation_info", notification_type=NotificationType.MESSAGE_DELETED, handler=self.handler
|
||||
# )
|
||||
logger.info(f"[私聊][{self.private_name}]成功从 ChatObserver 解绑")
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]从 ChatObserver 解绑时出错: {e}")
|
||||
finally: # 确保 chat_observer 被重置
|
||||
self.chat_observer = None
|
||||
else:
|
||||
logger.warning(f"[私聊][{self.private_name}]尝试解绑时 ChatObserver 不存在、无效或 handler 未设置")
|
||||
|
||||
# 修改：update_from_message 接收 UserInfo 对象
|
||||
async def update_from_message(self, message: Dict[str, Any], user_info: Optional[UserInfo]):
|
||||
"""从消息更新信息
|
||||
|
||||
Args:
|
||||
message: 消息数据字典
|
||||
user_info: 解析后的 UserInfo 对象 (可能为 None)
|
||||
"""
|
||||
message_time = message.get("time")
|
||||
message_id = message.get("message_id")
|
||||
processed_text = message.get("processed_plain_text", "")
|
||||
|
||||
# 只有在新消息到达时才更新 last_message 相关信息
|
||||
if message_time and message_time > (self.last_message_time or 0):
|
||||
self.last_message_time = message_time
|
||||
self.last_message_id = message_id
|
||||
self.last_message_content = processed_text
|
||||
# 重置冷场计时器
|
||||
self.is_cold_chat = False
|
||||
self.cold_chat_start_time = None
|
||||
self.cold_chat_duration = 0.0
|
||||
|
||||
if user_info:
|
||||
sender_id = str(user_info.user_id) # 确保是字符串
|
||||
self.last_message_sender = sender_id
|
||||
# 更新发言时间
|
||||
if sender_id == self.bot_id:
|
||||
self.last_bot_speak_time = message_time
|
||||
else:
|
||||
self.last_user_speak_time = message_time
|
||||
self.active_users.add(sender_id) # 用户发言则认为其活跃
|
||||
else:
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]处理消息更新时缺少有效的 UserInfo 对象, message_id: {message_id}"
|
||||
)
|
||||
self.last_message_sender = None # 发送者未知
|
||||
|
||||
# 将原始消息字典添加到未处理列表
|
||||
self.unprocessed_messages.append(message)
|
||||
self.new_messages_count = len(self.unprocessed_messages) # 直接用列表长度
|
||||
|
||||
# logger.debug(f"[私聊][{self.private_name}]消息更新: last_time={self.last_message_time}, new_count={self.new_messages_count}")
|
||||
self.update_changed() # 标记状态已改变
|
||||
else:
|
||||
# 如果消息时间戳不是最新的，可能不需要处理，或者记录一个警告
|
||||
pass
|
||||
# logger.warning(f"[私聊][{self.private_name}]收到过时或无效时间戳的消息: ID={message_id}, time={message_time}")
|
||||
|
||||
def update_changed(self):
|
||||
"""标记状态已改变，并重置标记"""
|
||||
# logger.debug(f"[私聊][{self.private_name}]状态标记为已改变 (changed=True)")
|
||||
self.changed = True
|
||||
|
||||
async def update_cold_chat_status(self, is_cold: bool, current_time: float):
|
||||
"""更新冷场状态
|
||||
|
||||
Args:
|
||||
is_cold: 是否处于冷场状态
|
||||
current_time: 当前时间戳
|
||||
"""
|
||||
if is_cold != self.is_cold_chat: # 仅在状态变化时更新
|
||||
self.is_cold_chat = is_cold
|
||||
if is_cold:
|
||||
# 进入冷场状态
|
||||
self.cold_chat_start_time = (
|
||||
self.last_message_time or current_time
|
||||
) # 从最后消息时间开始算，或从当前时间开始
|
||||
logger.info(f"[私聊][{self.private_name}]进入冷场状态，开始时间: {self.cold_chat_start_time}")
|
||||
else:
|
||||
# 结束冷场状态
|
||||
if self.cold_chat_start_time:
|
||||
self.cold_chat_duration = current_time - self.cold_chat_start_time
|
||||
logger.info(f"[私聊][{self.private_name}]结束冷场状态，持续时间: {self.cold_chat_duration:.2f} 秒")
|
||||
self.cold_chat_start_time = None # 重置开始时间
|
||||
self.update_changed() # 状态变化，标记改变
|
||||
|
||||
# 即使状态没变，如果是冷场状态，也更新持续时间
|
||||
if self.is_cold_chat and self.cold_chat_start_time:
|
||||
self.cold_chat_duration = current_time - self.cold_chat_start_time
|
||||
|
||||
def get_active_duration(self) -> float:
|
||||
"""获取当前活跃时长 (距离最后一条消息的时间)
|
||||
|
||||
Returns:
|
||||
float: 最后一条消息到现在的时长（秒）
|
||||
"""
|
||||
if not self.last_message_time:
|
||||
return 0.0
|
||||
return time.time() - self.last_message_time
|
||||
|
||||
def get_user_response_time(self) -> Optional[float]:
|
||||
"""获取用户最后响应时间 (距离用户最后发言的时间)
|
||||
|
||||
Returns:
|
||||
Optional[float]: 用户最后发言到现在的时长（秒），如果没有用户发言则返回None
|
||||
"""
|
||||
if not self.last_user_speak_time:
|
||||
return None
|
||||
return time.time() - self.last_user_speak_time
|
||||
|
||||
def get_bot_response_time(self) -> Optional[float]:
|
||||
"""获取机器人最后响应时间 (距离机器人最后发言的时间)
|
||||
|
||||
Returns:
|
||||
Optional[float]: 机器人最后发言到现在的时长（秒），如果没有机器人发言则返回None
|
||||
"""
|
||||
if not self.last_bot_speak_time:
|
||||
return None
|
||||
return time.time() - self.last_bot_speak_time
|
||||
|
||||
async def clear_unprocessed_messages(self):
|
||||
"""将未处理消息移入历史记录，并更新相关状态"""
|
||||
if not self.unprocessed_messages:
|
||||
return # 没有未处理消息，直接返回
|
||||
|
||||
# logger.debug(f"[私聊][{self.private_name}]处理 {len(self.unprocessed_messages)} 条未处理消息...")
|
||||
# 将未处理消息添加到历史记录中 (确保历史记录有长度限制，避免无限增长)
|
||||
max_history_len = 100 # 示例：最多保留100条历史记录
|
||||
self.chat_history.extend(self.unprocessed_messages)
|
||||
if len(self.chat_history) > max_history_len:
|
||||
self.chat_history = self.chat_history[-max_history_len:]
|
||||
|
||||
# 更新历史记录字符串 (只使用最近一部分生成，例如20条)
|
||||
history_slice_for_str = self.chat_history[-20:]
|
||||
try:
|
||||
self.chat_history_str = await build_readable_messages(
|
||||
history_slice_for_str,
|
||||
replace_bot_name=True,
|
||||
merge_messages=False,
|
||||
timestamp_mode="relative",
|
||||
read_mark=0.0, # read_mark 可能需要根据逻辑调整
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]构建聊天记录字符串时出错: {e}")
|
||||
self.chat_history_str = "[构建聊天记录出错]" # 提供错误提示
|
||||
|
||||
# 清空未处理消息列表和计数
|
||||
# cleared_count = len(self.unprocessed_messages)
|
||||
self.unprocessed_messages.clear()
|
||||
self.new_messages_count = 0
|
||||
# self.has_unread_messages = False # 这个状态可以通过 new_messages_count 判断
|
||||
|
||||
self.chat_history_count = len(self.chat_history) # 更新历史记录总数
|
||||
# logger.debug(f"[私聊][{self.private_name}]已处理 {cleared_count} 条消息，当前历史记录 {self.chat_history_count} 条。")
|
||||
|
||||
self.update_changed() # 状态改变
|
||||
345
src/chat/brain_chat/PFC/pfc.py
Normal file
345
src/chat/brain_chat/PFC/pfc.py
Normal file
@@ -0,0 +1,345 @@
|
||||
from typing import List, Tuple, TYPE_CHECKING
|
||||
from src.common.logger import get_module_logger
|
||||
from ..models.utils_model import LLMRequest
|
||||
from ...config.config import global_config
|
||||
from .chat_observer import ChatObserver
|
||||
from .pfc_utils import get_items_from_json
|
||||
from src.individuality.individuality import Individuality
|
||||
from .conversation_info import ConversationInfo
|
||||
from .observation_info import ObservationInfo
|
||||
from src.plugins.utils.chat_message_builder import build_readable_messages
|
||||
from rich.traceback import install
|
||||
|
||||
install(extra_lines=3)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
pass
|
||||
|
||||
logger = get_module_logger("pfc")
|
||||
|
||||
|
||||
def _calculate_similarity(goal1: str, goal2: str) -> float:
|
||||
"""简单计算两个目标之间的相似度
|
||||
|
||||
这里使用一个简单的实现，实际可以使用更复杂的文本相似度算法
|
||||
|
||||
Args:
|
||||
goal1: 第一个目标
|
||||
goal2: 第二个目标
|
||||
|
||||
Returns:
|
||||
float: 相似度得分 (0-1)
|
||||
"""
|
||||
# 简单实现：检查重叠字数比例
|
||||
words1 = set(goal1)
|
||||
words2 = set(goal2)
|
||||
overlap = len(words1.intersection(words2))
|
||||
total = len(words1.union(words2))
|
||||
return overlap / total if total > 0 else 0
|
||||
|
||||
|
||||
class GoalAnalyzer:
|
||||
"""对话目标分析器"""
|
||||
|
||||
def __init__(self, stream_id: str, private_name: str):
|
||||
self.llm = LLMRequest(
|
||||
model=global_config.llm_normal, temperature=0.7, max_tokens=1000, request_type="conversation_goal"
|
||||
)
|
||||
|
||||
self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
|
||||
self.name = global_config.BOT_NICKNAME
|
||||
self.nick_name = global_config.BOT_ALIAS_NAMES
|
||||
self.private_name = private_name
|
||||
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
|
||||
|
||||
# 多目标存储结构
|
||||
self.goals = [] # 存储多个目标
|
||||
self.max_goals = 3 # 同时保持的最大目标数量
|
||||
self.current_goal_and_reason = None
|
||||
|
||||
async def analyze_goal(self, conversation_info: ConversationInfo, observation_info: ObservationInfo):
|
||||
"""分析对话历史并设定目标
|
||||
|
||||
Args:
|
||||
conversation_info: 对话信息
|
||||
observation_info: 观察信息
|
||||
|
||||
Returns:
|
||||
Tuple[str, str, str]: (目标, 方法, 原因)
|
||||
"""
|
||||
# 构建对话目标
|
||||
goals_str = ""
|
||||
if conversation_info.goal_list:
|
||||
for goal_reason in conversation_info.goal_list:
|
||||
if isinstance(goal_reason, dict):
|
||||
goal = goal_reason.get("goal", "目标内容缺失")
|
||||
reasoning = goal_reason.get("reasoning", "没有明确原因")
|
||||
else:
|
||||
goal = str(goal_reason)
|
||||
reasoning = "没有明确原因"
|
||||
|
||||
goal_str = f"目标：{goal}，产生该对话目标的原因：{reasoning}\n"
|
||||
goals_str += goal_str
|
||||
else:
|
||||
goal = "目前没有明确对话目标"
|
||||
reasoning = "目前没有明确对话目标，最好思考一个对话目标"
|
||||
goals_str = f"目标：{goal}，产生该对话目标的原因：{reasoning}\n"
|
||||
|
||||
# 获取聊天历史记录
|
||||
chat_history_text = observation_info.chat_history_str
|
||||
|
||||
if observation_info.new_messages_count > 0:
|
||||
new_messages_list = observation_info.unprocessed_messages
|
||||
new_messages_str = await build_readable_messages(
|
||||
new_messages_list,
|
||||
replace_bot_name=True,
|
||||
merge_messages=False,
|
||||
timestamp_mode="relative",
|
||||
read_mark=0.0,
|
||||
)
|
||||
chat_history_text += f"\n--- 以下是 {observation_info.new_messages_count} 条新消息 ---\n{new_messages_str}"
|
||||
|
||||
# await observation_info.clear_unprocessed_messages()
|
||||
|
||||
persona_text = f"你的名字是{self.name}，{self.personality_info}。"
|
||||
# 构建action历史文本
|
||||
action_history_list = conversation_info.done_action
|
||||
action_history_text = "你之前做的事情是："
|
||||
for action in action_history_list:
|
||||
action_history_text += f"{action}\n"
|
||||
|
||||
prompt = f"""{persona_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。
|
||||
这些目标应该反映出对话的不同方面和意图。
|
||||
|
||||
{action_history_text}
|
||||
当前对话目标：
|
||||
{goals_str}
|
||||
|
||||
聊天记录：
|
||||
{chat_history_text}
|
||||
|
||||
请分析当前对话并确定最适合的对话目标。你可以：
|
||||
1. 保持现有目标不变
|
||||
2. 修改现有目标
|
||||
3. 添加新目标
|
||||
4. 删除不再相关的目标
|
||||
5. 如果你想结束对话，请设置一个目标，目标goal为"结束对话"，原因reasoning为你希望结束对话
|
||||
|
||||
请以JSON数组格式输出当前的所有对话目标，每个目标包含以下字段：
|
||||
1. goal: 对话目标（简短的一句话）
|
||||
2. reasoning: 对话原因，为什么设定这个目标（简要解释）
|
||||
|
||||
输出格式示例：
|
||||
[
|
||||
{{
|
||||
"goal": "回答用户关于Python编程的具体问题",
|
||||
"reasoning": "用户提出了关于Python的技术问题，需要专业且准确的解答"
|
||||
}},
|
||||
{{
|
||||
"goal": "回答用户关于python安装的具体问题",
|
||||
"reasoning": "用户提出了关于Python的技术问题，需要专业且准确的解答"
|
||||
}}
|
||||
]"""
|
||||
|
||||
logger.debug(f"[私聊][{self.private_name}]发送到LLM的提示词: {prompt}")
|
||||
try:
|
||||
content, _ = await self.llm.generate_response_async(prompt)
|
||||
logger.debug(f"[私聊][{self.private_name}]LLM原始返回内容: {content}")
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]分析对话目标时出错: {str(e)}")
|
||||
content = ""
|
||||
|
||||
# 使用改进后的get_items_from_json函数处理JSON数组
|
||||
success, result = get_items_from_json(
|
||||
content,
|
||||
self.private_name,
|
||||
"goal",
|
||||
"reasoning",
|
||||
required_types={"goal": str, "reasoning": str},
|
||||
allow_array=True,
|
||||
)
|
||||
|
||||
if success:
|
||||
# 判断结果是单个字典还是字典列表
|
||||
if isinstance(result, list):
|
||||
# 清空现有目标列表并添加新目标
|
||||
conversation_info.goal_list = []
|
||||
for item in result:
|
||||
conversation_info.goal_list.append(item)
|
||||
|
||||
# 返回第一个目标作为当前主要目标（如果有）
|
||||
if result:
|
||||
first_goal = result[0]
|
||||
return first_goal.get("goal", ""), "", first_goal.get("reasoning", "")
|
||||
else:
|
||||
# 单个目标的情况
|
||||
conversation_info.goal_list.append(result)
|
||||
return goal, "", reasoning
|
||||
|
||||
# 如果解析失败，返回默认值
|
||||
return "", "", ""
|
||||
|
||||
async def _update_goals(self, new_goal: str, method: str, reasoning: str):
|
||||
"""更新目标列表
|
||||
|
||||
Args:
|
||||
new_goal: 新的目标
|
||||
method: 实现目标的方法
|
||||
reasoning: 目标的原因
|
||||
"""
|
||||
# 检查新目标是否与现有目标相似
|
||||
for i, (existing_goal, _, _) in enumerate(self.goals):
|
||||
if _calculate_similarity(new_goal, existing_goal) > 0.7: # 相似度阈值
|
||||
# 更新现有目标
|
||||
self.goals[i] = (new_goal, method, reasoning)
|
||||
# 将此目标移到列表前面（最主要的位置）
|
||||
self.goals.insert(0, self.goals.pop(i))
|
||||
return
|
||||
|
||||
# 添加新目标到列表前面
|
||||
self.goals.insert(0, (new_goal, method, reasoning))
|
||||
|
||||
# 限制目标数量
|
||||
if len(self.goals) > self.max_goals:
|
||||
self.goals.pop() # 移除最老的目标
|
||||
|
||||
async def get_all_goals(self) -> List[Tuple[str, str, str]]:
|
||||
"""获取所有当前目标
|
||||
|
||||
Returns:
|
||||
List[Tuple[str, str, str]]: 目标列表，每项为(目标, 方法, 原因)
|
||||
"""
|
||||
return self.goals.copy()
|
||||
|
||||
async def get_alternative_goals(self) -> List[Tuple[str, str, str]]:
|
||||
"""获取除了当前主要目标外的其他备选目标
|
||||
|
||||
Returns:
|
||||
List[Tuple[str, str, str]]: 备选目标列表
|
||||
"""
|
||||
if len(self.goals) <= 1:
|
||||
return []
|
||||
return self.goals[1:].copy()
|
||||
|
||||
async def analyze_conversation(self, goal, reasoning):
|
||||
messages = self.chat_observer.get_cached_messages()
|
||||
chat_history_text = await build_readable_messages(
|
||||
messages,
|
||||
replace_bot_name=True,
|
||||
merge_messages=False,
|
||||
timestamp_mode="relative",
|
||||
read_mark=0.0,
|
||||
)
|
||||
|
||||
persona_text = f"你的名字是{self.name}，{self.personality_info}。"
|
||||
# ===> Persona 文本构建结束 <===
|
||||
|
||||
# --- 修改 Prompt 字符串，使用 persona_text ---
|
||||
prompt = f"""{persona_text}。现在你在参与一场QQ聊天，
|
||||
当前对话目标：{goal}
|
||||
产生该对话目标的原因：{reasoning}
|
||||
|
||||
请分析以下聊天记录，并根据你的性格特征评估该目标是否已经达到，或者你是否希望停止该次对话。
|
||||
聊天记录：
|
||||
{chat_history_text}
|
||||
请以JSON格式输出，包含以下字段：
|
||||
1. goal_achieved: 对话目标是否已经达到（true/false）
|
||||
2. stop_conversation: 是否希望停止该次对话（true/false）
|
||||
3. reason: 为什么希望停止该次对话（简要解释）
|
||||
|
||||
输出格式示例：
|
||||
{{
|
||||
"goal_achieved": true,
|
||||
"stop_conversation": false,
|
||||
"reason": "虽然目标已达成，但对话仍然有继续的价值"
|
||||
}}"""
|
||||
|
||||
try:
|
||||
content, _ = await self.llm.generate_response_async(prompt)
|
||||
logger.debug(f"[私聊][{self.private_name}]LLM原始返回内容: {content}")
|
||||
|
||||
# 尝试解析JSON
|
||||
success, result = get_items_from_json(
|
||||
content,
|
||||
self.private_name,
|
||||
"goal_achieved",
|
||||
"stop_conversation",
|
||||
"reason",
|
||||
required_types={"goal_achieved": bool, "stop_conversation": bool, "reason": str},
|
||||
)
|
||||
|
||||
if not success:
|
||||
logger.error(f"[私聊][{self.private_name}]无法解析对话分析结果JSON")
|
||||
return False, False, "解析结果失败"
|
||||
|
||||
goal_achieved = result["goal_achieved"]
|
||||
stop_conversation = result["stop_conversation"]
|
||||
reason = result["reason"]
|
||||
|
||||
return goal_achieved, stop_conversation, reason
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]分析对话状态时出错: {str(e)}")
|
||||
return False, False, f"分析出错: {str(e)}"
|
||||
|
||||
|
||||
# 先注释掉，万一以后出问题了还能开回来（（（
|
||||
# class DirectMessageSender:
|
||||
# """直接发送消息到平台的发送器"""
|
||||
|
||||
# def __init__(self, private_name: str):
|
||||
# self.logger = get_module_logger("direct_sender")
|
||||
# self.storage = MessageStorage()
|
||||
# self.private_name = private_name
|
||||
|
||||
# async def send_via_ws(self, message: MessageSending) -> None:
|
||||
# try:
|
||||
# await global_api.send_message(message)
|
||||
# except Exception as e:
|
||||
# raise ValueError(f"未找到平台：{message.message_info.platform} 的url配置，请检查配置文件") from e
|
||||
|
||||
# async def send_message(
|
||||
# self,
|
||||
# chat_stream: ChatStream,
|
||||
# content: str,
|
||||
# reply_to_message: Optional[Message] = None,
|
||||
# ) -> None:
|
||||
# """直接发送消息到平台
|
||||
|
||||
# Args:
|
||||
# chat_stream: 聊天流
|
||||
# content: 消息内容
|
||||
# reply_to_message: 要回复的消息
|
||||
# """
|
||||
# # 构建消息对象
|
||||
# message_segment = Seg(type="text", data=content)
|
||||
# bot_user_info = UserInfo(
|
||||
# user_id=global_config.BOT_QQ,
|
||||
# user_nickname=global_config.BOT_NICKNAME,
|
||||
# platform=chat_stream.platform,
|
||||
# )
|
||||
|
||||
# message = MessageSending(
|
||||
# message_id=f"dm{round(time.time(), 2)}",
|
||||
# chat_stream=chat_stream,
|
||||
# bot_user_info=bot_user_info,
|
||||
# sender_info=reply_to_message.message_info.user_info if reply_to_message else None,
|
||||
# message_segment=message_segment,
|
||||
# reply=reply_to_message,
|
||||
# is_head=True,
|
||||
# is_emoji=False,
|
||||
# thinking_start_time=time.time(),
|
||||
# )
|
||||
|
||||
# # 处理消息
|
||||
# await message.process()
|
||||
|
||||
# _message_json = message.to_dict()
|
||||
|
||||
# # 发送消息
|
||||
# try:
|
||||
# await self.send_via_ws(message)
|
||||
# await self.storage.store_message(message, chat_stream)
|
||||
# logger.success(f"[私聊][{self.private_name}]PFC消息已发送: {content}")
|
||||
# except Exception as e:
|
||||
# logger.error(f"[私聊][{self.private_name}]PFC消息发送失败: {str(e)}")
|
||||
85
src/chat/brain_chat/PFC/pfc_KnowledgeFetcher.py
Normal file
85
src/chat/brain_chat/PFC/pfc_KnowledgeFetcher.py
Normal file
@@ -0,0 +1,85 @@
|
||||
from typing import List, Tuple
|
||||
from src.common.logger import get_module_logger
|
||||
from src.plugins.memory_system.Hippocampus import HippocampusManager
|
||||
from ..models.utils_model import LLMRequest
|
||||
from ...config.config import global_config
|
||||
from ..chat.message import Message
|
||||
from ..knowledge.knowledge_lib import qa_manager
|
||||
from ..utils.chat_message_builder import build_readable_messages
|
||||
|
||||
logger = get_module_logger("knowledge_fetcher")
|
||||
|
||||
|
||||
class KnowledgeFetcher:
|
||||
"""知识调取器"""
|
||||
|
||||
def __init__(self, private_name: str):
|
||||
self.llm = LLMRequest(
|
||||
model=global_config.llm_normal,
|
||||
temperature=global_config.llm_normal["temp"],
|
||||
max_tokens=1000,
|
||||
request_type="knowledge_fetch",
|
||||
)
|
||||
self.private_name = private_name
|
||||
|
||||
def _lpmm_get_knowledge(self, query: str) -> str:
|
||||
"""获取相关知识
|
||||
|
||||
Args:
|
||||
query: 查询内容
|
||||
|
||||
Returns:
|
||||
str: 构造好的,带相关度的知识
|
||||
"""
|
||||
|
||||
logger.debug(f"[私聊][{self.private_name}]正在从LPMM知识库中获取知识")
|
||||
try:
|
||||
knowledge_info = qa_manager.get_knowledge(query)
|
||||
logger.debug(f"[私聊][{self.private_name}]LPMM知识库查询结果: {knowledge_info:150}")
|
||||
return knowledge_info
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]LPMM知识库搜索工具执行失败: {str(e)}")
|
||||
return "未找到匹配的知识"
|
||||
|
||||
async def fetch(self, query: str, chat_history: List[Message]) -> Tuple[str, str]:
|
||||
"""获取相关知识
|
||||
|
||||
Args:
|
||||
query: 查询内容
|
||||
chat_history: 聊天历史
|
||||
|
||||
Returns:
|
||||
Tuple[str, str]: (获取的知识, 知识来源)
|
||||
"""
|
||||
# 构建查询上下文
|
||||
chat_history_text = await build_readable_messages(
|
||||
chat_history,
|
||||
replace_bot_name=True,
|
||||
merge_messages=False,
|
||||
timestamp_mode="relative",
|
||||
read_mark=0.0,
|
||||
)
|
||||
|
||||
# 从记忆中获取相关知识
|
||||
related_memory = await HippocampusManager.get_instance().get_memory_from_text(
|
||||
text=f"{query}\n{chat_history_text}",
|
||||
max_memory_num=3,
|
||||
max_memory_length=2,
|
||||
max_depth=3,
|
||||
fast_retrieval=False,
|
||||
)
|
||||
knowledge_text = ""
|
||||
sources_text = "无记忆匹配" # 默认值
|
||||
if related_memory:
|
||||
sources = []
|
||||
for memory in related_memory:
|
||||
knowledge_text += memory[1] + "\n"
|
||||
sources.append(f"记忆片段{memory[0]}")
|
||||
knowledge_text = knowledge_text.strip()
|
||||
sources_text = "，".join(sources)
|
||||
|
||||
knowledge_text += "\n现在有以下**知识**可供参考：\n "
|
||||
knowledge_text += self._lpmm_get_knowledge(query)
|
||||
knowledge_text += "\n请记住这些**知识**，并根据**知识**回答问题。\n"
|
||||
|
||||
return knowledge_text or "未找到相关知识", sources_text or "无记忆匹配"
|
||||
115
src/chat/brain_chat/PFC/pfc_manager.py
Normal file
115
src/chat/brain_chat/PFC/pfc_manager.py
Normal file
@@ -0,0 +1,115 @@
|
||||
import time
|
||||
from typing import Dict, Optional
|
||||
from src.common.logger import get_module_logger
|
||||
from .conversation import Conversation
|
||||
import traceback
|
||||
|
||||
logger = get_module_logger("pfc_manager")
|
||||
|
||||
|
||||
class PFCManager:
|
||||
"""PFC对话管理器，负责管理所有对话实例"""
|
||||
|
||||
# 单例模式
|
||||
_instance = None
|
||||
|
||||
# 会话实例管理
|
||||
_instances: Dict[str, Conversation] = {}
|
||||
_initializing: Dict[str, bool] = {}
|
||||
|
||||
@classmethod
|
||||
def get_instance(cls) -> "PFCManager":
|
||||
"""获取管理器单例
|
||||
|
||||
Returns:
|
||||
PFCManager: 管理器实例
|
||||
"""
|
||||
if cls._instance is None:
|
||||
cls._instance = PFCManager()
|
||||
return cls._instance
|
||||
|
||||
async def get_or_create_conversation(self, stream_id: str, private_name: str) -> Optional[Conversation]:
|
||||
"""获取或创建对话实例
|
||||
|
||||
Args:
|
||||
stream_id: 聊天流ID
|
||||
private_name: 私聊名称
|
||||
|
||||
Returns:
|
||||
Optional[Conversation]: 对话实例，创建失败则返回None
|
||||
"""
|
||||
# 检查是否已经有实例
|
||||
if stream_id in self._initializing and self._initializing[stream_id]:
|
||||
logger.debug(f"[私聊][{private_name}]会话实例正在初始化中: {stream_id}")
|
||||
return None
|
||||
|
||||
if stream_id in self._instances and self._instances[stream_id].should_continue:
|
||||
logger.debug(f"[私聊][{private_name}]使用现有会话实例: {stream_id}")
|
||||
return self._instances[stream_id]
|
||||
if stream_id in self._instances:
|
||||
instance = self._instances[stream_id]
|
||||
if (
|
||||
hasattr(instance, "ignore_until_timestamp")
|
||||
and instance.ignore_until_timestamp
|
||||
and time.time() < instance.ignore_until_timestamp
|
||||
):
|
||||
logger.debug(f"[私聊][{private_name}]会话实例当前处于忽略状态: {stream_id}")
|
||||
# 返回 None 阻止交互。或者可以返回实例但标记它被忽略了喵？
|
||||
# 还是返回 None 吧喵。
|
||||
return None
|
||||
|
||||
# 检查 should_continue 状态
|
||||
if instance.should_continue:
|
||||
logger.debug(f"[私聊][{private_name}]使用现有会话实例: {stream_id}")
|
||||
return instance
|
||||
# else: 实例存在但不应继续
|
||||
try:
|
||||
# 创建新实例
|
||||
logger.info(f"[私聊][{private_name}]创建新的对话实例: {stream_id}")
|
||||
self._initializing[stream_id] = True
|
||||
# 创建实例
|
||||
conversation_instance = Conversation(stream_id, private_name)
|
||||
self._instances[stream_id] = conversation_instance
|
||||
|
||||
# 启动实例初始化
|
||||
await self._initialize_conversation(conversation_instance)
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{private_name}]创建会话实例失败: {stream_id}, 错误: {e}")
|
||||
return None
|
||||
|
||||
return conversation_instance
|
||||
|
||||
async def _initialize_conversation(self, conversation: Conversation):
|
||||
"""初始化会话实例
|
||||
|
||||
Args:
|
||||
conversation: 要初始化的会话实例
|
||||
"""
|
||||
stream_id = conversation.stream_id
|
||||
private_name = conversation.private_name
|
||||
|
||||
try:
|
||||
logger.info(f"[私聊][{private_name}]开始初始化会话实例: {stream_id}")
|
||||
# 启动初始化流程
|
||||
await conversation._initialize()
|
||||
|
||||
# 标记初始化完成
|
||||
self._initializing[stream_id] = False
|
||||
|
||||
logger.info(f"[私聊][{private_name}]会话实例 {stream_id} 初始化完成")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{private_name}]管理器初始化会话实例失败: {stream_id}, 错误: {e}")
|
||||
logger.error(f"[私聊][{private_name}]{traceback.format_exc()}")
|
||||
# 清理失败的初始化
|
||||
|
||||
async def get_conversation(self, stream_id: str) -> Optional[Conversation]:
|
||||
"""获取已存在的会话实例
|
||||
|
||||
Args:
|
||||
stream_id: 聊天流ID
|
||||
|
||||
Returns:
|
||||
Optional[Conversation]: 会话实例，不存在则返回None
|
||||
"""
|
||||
return self._instances.get(stream_id)
|
||||
23
src/chat/brain_chat/PFC/pfc_types.py
Normal file
23
src/chat/brain_chat/PFC/pfc_types.py
Normal file
@@ -0,0 +1,23 @@
|
||||
from enum import Enum
|
||||
from typing import Literal
|
||||
|
||||
|
||||
class ConversationState(Enum):
|
||||
"""对话状态"""
|
||||
|
||||
INIT = "初始化"
|
||||
RETHINKING = "重新思考"
|
||||
ANALYZING = "分析历史"
|
||||
PLANNING = "规划目标"
|
||||
GENERATING = "生成回复"
|
||||
CHECKING = "检查回复"
|
||||
SENDING = "发送消息"
|
||||
FETCHING = "获取知识"
|
||||
WAITING = "等待"
|
||||
LISTENING = "倾听"
|
||||
ENDED = "结束"
|
||||
JUDGING = "判断"
|
||||
IGNORED = "屏蔽"
|
||||
|
||||
|
||||
ActionType = Literal["direct_reply", "fetch_knowledge", "wait"]
|
||||
127
src/chat/brain_chat/PFC/pfc_utils.py
Normal file
127
src/chat/brain_chat/PFC/pfc_utils.py
Normal file
@@ -0,0 +1,127 @@
|
||||
import json
|
||||
import re
|
||||
from typing import Dict, Any, Optional, Tuple, List, Union
|
||||
from src.common.logger import get_module_logger
|
||||
|
||||
logger = get_module_logger("pfc_utils")
|
||||
|
||||
|
||||
def get_items_from_json(
|
||||
content: str,
|
||||
private_name: str,
|
||||
*items: str,
|
||||
default_values: Optional[Dict[str, Any]] = None,
|
||||
required_types: Optional[Dict[str, type]] = None,
|
||||
allow_array: bool = True,
|
||||
) -> Tuple[bool, Union[Dict[str, Any], List[Dict[str, Any]]]]:
|
||||
"""从文本中提取JSON内容并获取指定字段
|
||||
|
||||
Args:
|
||||
content: 包含JSON的文本
|
||||
private_name: 私聊名称
|
||||
*items: 要提取的字段名
|
||||
default_values: 字段的默认值，格式为 {字段名: 默认值}
|
||||
required_types: 字段的必需类型，格式为 {字段名: 类型}
|
||||
allow_array: 是否允许解析JSON数组
|
||||
|
||||
Returns:
|
||||
Tuple[bool, Union[Dict[str, Any], List[Dict[str, Any]]]]: (是否成功, 提取的字段字典或字典列表)
|
||||
"""
|
||||
content = content.strip()
|
||||
result = {}
|
||||
|
||||
# 设置默认值
|
||||
if default_values:
|
||||
result.update(default_values)
|
||||
|
||||
# 首先尝试解析为JSON数组
|
||||
if allow_array:
|
||||
try:
|
||||
# 尝试找到文本中的JSON数组
|
||||
array_pattern = r"\[[\s\S]*\]"
|
||||
array_match = re.search(array_pattern, content)
|
||||
if array_match:
|
||||
array_content = array_match.group()
|
||||
json_array = json.loads(array_content)
|
||||
|
||||
# 确认是数组类型
|
||||
if isinstance(json_array, list):
|
||||
# 验证数组中的每个项目是否包含所有必需字段
|
||||
valid_items = []
|
||||
for item in json_array:
|
||||
if not isinstance(item, dict):
|
||||
continue
|
||||
|
||||
# 检查是否有所有必需字段
|
||||
if all(field in item for field in items):
|
||||
# 验证字段类型
|
||||
if required_types:
|
||||
type_valid = True
|
||||
for field, expected_type in required_types.items():
|
||||
if field in item and not isinstance(item[field], expected_type):
|
||||
type_valid = False
|
||||
break
|
||||
|
||||
if not type_valid:
|
||||
continue
|
||||
|
||||
# 验证字符串字段不为空
|
||||
string_valid = True
|
||||
for field in items:
|
||||
if isinstance(item[field], str) and not item[field].strip():
|
||||
string_valid = False
|
||||
break
|
||||
|
||||
if not string_valid:
|
||||
continue
|
||||
|
||||
valid_items.append(item)
|
||||
|
||||
if valid_items:
|
||||
return True, valid_items
|
||||
except json.JSONDecodeError:
|
||||
logger.debug(f"[私聊][{private_name}]JSON数组解析失败，尝试解析单个JSON对象")
|
||||
except Exception as e:
|
||||
logger.debug(f"[私聊][{private_name}]尝试解析JSON数组时出错: {str(e)}")
|
||||
|
||||
# 尝试解析JSON对象
|
||||
try:
|
||||
json_data = json.loads(content)
|
||||
except json.JSONDecodeError:
|
||||
# 如果直接解析失败，尝试查找和提取JSON部分
|
||||
json_pattern = r"\{[^{}]*\}"
|
||||
json_match = re.search(json_pattern, content)
|
||||
if json_match:
|
||||
try:
|
||||
json_data = json.loads(json_match.group())
|
||||
except json.JSONDecodeError:
|
||||
logger.error(f"[私聊][{private_name}]提取的JSON内容解析失败")
|
||||
return False, result
|
||||
else:
|
||||
logger.error(f"[私聊][{private_name}]无法在返回内容中找到有效的JSON")
|
||||
return False, result
|
||||
|
||||
# 提取字段
|
||||
for item in items:
|
||||
if item in json_data:
|
||||
result[item] = json_data[item]
|
||||
|
||||
# 验证必需字段
|
||||
if not all(item in result for item in items):
|
||||
logger.error(f"[私聊][{private_name}]JSON缺少必要字段，实际内容: {json_data}")
|
||||
return False, result
|
||||
|
||||
# 验证字段类型
|
||||
if required_types:
|
||||
for field, expected_type in required_types.items():
|
||||
if field in result and not isinstance(result[field], expected_type):
|
||||
logger.error(f"[私聊][{private_name}]{field} 必须是 {expected_type.__name__} 类型")
|
||||
return False, result
|
||||
|
||||
# 验证字符串字段不为空
|
||||
for field in items:
|
||||
if isinstance(result[field], str) and not result[field].strip():
|
||||
logger.error(f"[私聊][{private_name}]{field} 不能为空")
|
||||
return False, result
|
||||
|
||||
return True, result
|
||||
183
src/chat/brain_chat/PFC/reply_checker.py
Normal file
183
src/chat/brain_chat/PFC/reply_checker.py
Normal file
@@ -0,0 +1,183 @@
|
||||
import json
|
||||
from typing import Tuple, List, Dict, Any
|
||||
from src.common.logger import get_module_logger
|
||||
from ..models.utils_model import LLMRequest
|
||||
from ...config.config import global_config
|
||||
from .chat_observer import ChatObserver
|
||||
from maim_message import UserInfo
|
||||
|
||||
logger = get_module_logger("reply_checker")
|
||||
|
||||
|
||||
class ReplyChecker:
|
||||
"""回复检查器"""
|
||||
|
||||
def __init__(self, stream_id: str, private_name: str):
|
||||
self.llm = LLMRequest(
|
||||
model=global_config.llm_PFC_reply_checker, temperature=0.50, max_tokens=1000, request_type="reply_check"
|
||||
)
|
||||
self.name = global_config.BOT_NICKNAME
|
||||
self.private_name = private_name
|
||||
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
|
||||
self.max_retries = 3 # 最大重试次数
|
||||
|
||||
async def check(
|
||||
self, reply: str, goal: str, chat_history: List[Dict[str, Any]], chat_history_text: str, retry_count: int = 0
|
||||
) -> Tuple[bool, str, bool]:
|
||||
"""检查生成的回复是否合适
|
||||
|
||||
Args:
|
||||
reply: 生成的回复
|
||||
goal: 对话目标
|
||||
chat_history: 对话历史记录
|
||||
chat_history_text: 对话历史记录文本
|
||||
retry_count: 当前重试次数
|
||||
|
||||
Returns:
|
||||
Tuple[bool, str, bool]: (是否合适, 原因, 是否需要重新规划)
|
||||
"""
|
||||
# 不再从 observer 获取，直接使用传入的 chat_history
|
||||
# messages = self.chat_observer.get_cached_messages(limit=20)
|
||||
try:
|
||||
# 筛选出最近由 Bot 自己发送的消息
|
||||
bot_messages = []
|
||||
for msg in reversed(chat_history):
|
||||
user_info = UserInfo.from_dict(msg.get("user_info", {}))
|
||||
if str(user_info.user_id) == str(global_config.BOT_QQ): # 确保比较的是字符串
|
||||
bot_messages.append(msg.get("processed_plain_text", ""))
|
||||
if len(bot_messages) >= 2: # 只和最近的两条比较
|
||||
break
|
||||
# 进行比较
|
||||
if bot_messages:
|
||||
# 可以用简单比较，或者更复杂的相似度库 (如 difflib)
|
||||
# 简单比较：是否完全相同
|
||||
if reply == bot_messages[0]: # 和最近一条完全一样
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]ReplyChecker 检测到回复与上一条 Bot 消息完全相同: '{reply}'"
|
||||
)
|
||||
return (
|
||||
False,
|
||||
"被逻辑检查拒绝：回复内容与你上一条发言完全相同，可以选择深入话题或寻找其它话题或等待",
|
||||
True,
|
||||
) # 不合适，需要返回至决策层
|
||||
# 2. 相似度检查 (如果精确匹配未通过)
|
||||
import difflib # 导入 difflib 库
|
||||
|
||||
# 计算编辑距离相似度，ratio() 返回 0 到 1 之间的浮点数
|
||||
similarity_ratio = difflib.SequenceMatcher(None, reply, bot_messages[0]).ratio()
|
||||
logger.debug(f"[私聊][{self.private_name}]ReplyChecker - 相似度: {similarity_ratio:.2f}")
|
||||
|
||||
# 设置一个相似度阈值
|
||||
similarity_threshold = 0.9
|
||||
if similarity_ratio > similarity_threshold:
|
||||
logger.warning(
|
||||
f"[私聊][{self.private_name}]ReplyChecker 检测到回复与上一条 Bot 消息高度相似 (相似度 {similarity_ratio:.2f}): '{reply}'"
|
||||
)
|
||||
return (
|
||||
False,
|
||||
f"被逻辑检查拒绝：回复内容与你上一条发言高度相似 (相似度 {similarity_ratio:.2f})，可以选择深入话题或寻找其它话题或等待。",
|
||||
True,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
import traceback
|
||||
|
||||
logger.error(f"[私聊][{self.private_name}]检查回复时出错: 类型={type(e)}, 值={e}")
|
||||
logger.error(f"[私聊][{self.private_name}]{traceback.format_exc()}") # 打印详细的回溯信息
|
||||
|
||||
prompt = f"""你是一个聊天逻辑检查器，请检查以下回复或消息是否合适：
|
||||
|
||||
当前对话目标：{goal}
|
||||
最新的对话记录：
|
||||
{chat_history_text}
|
||||
|
||||
待检查的消息：
|
||||
{reply}
|
||||
|
||||
请结合聊天记录检查以下几点：
|
||||
1. 这条消息是否依然符合当前对话目标和实现方式
|
||||
2. 这条消息是否与最新的对话记录保持一致性
|
||||
3. 是否存在重复发言，或重复表达同质内容（尤其是只是换一种方式表达了相同的含义）
|
||||
4. 这条消息是否包含违规内容（例如血腥暴力，政治敏感等）
|
||||
5. 这条消息是否以发送者的角度发言（不要让发送者自己回复自己的消息）
|
||||
6. 这条消息是否通俗易懂
|
||||
7. 这条消息是否有些多余，例如在对方没有回复的情况下，依然连续多次“消息轰炸”（尤其是已经连续发送3条信息的情况，这很可能不合理，需要着重判断）
|
||||
8. 这条消息是否使用了完全没必要的修辞
|
||||
9. 这条消息是否逻辑通顺
|
||||
10. 这条消息是否太过冗长了（通常私聊的每条消息长度在20字以内，除非特殊情况）
|
||||
11. 在连续多次发送消息的情况下，这条消息是否衔接自然，会不会显得奇怪（例如连续两条消息中部分内容重叠）
|
||||
|
||||
请以JSON格式输出，包含以下字段：
|
||||
1. suitable: 是否合适 (true/false)
|
||||
2. reason: 原因说明
|
||||
3. need_replan: 是否需要重新决策 (true/false)，当你认为此时已经不适合发消息，需要规划其它行动时，设为true
|
||||
|
||||
输出格式示例：
|
||||
{{
|
||||
"suitable": true,
|
||||
"reason": "回复符合要求，虽然有可能略微偏离目标，但是整体内容流畅得体",
|
||||
"need_replan": false
|
||||
}}
|
||||
|
||||
注意：请严格按照JSON格式输出，不要包含任何其他内容。"""
|
||||
|
||||
try:
|
||||
content, _ = await self.llm.generate_response_async(prompt)
|
||||
logger.debug(f"[私聊][{self.private_name}]检查回复的原始返回: {content}")
|
||||
|
||||
# 清理内容，尝试提取JSON部分
|
||||
content = content.strip()
|
||||
try:
|
||||
# 尝试直接解析
|
||||
result = json.loads(content)
|
||||
except json.JSONDecodeError:
|
||||
# 如果直接解析失败，尝试查找和提取JSON部分
|
||||
import re
|
||||
|
||||
json_pattern = r"\{[^{}]*\}"
|
||||
json_match = re.search(json_pattern, content)
|
||||
if json_match:
|
||||
try:
|
||||
result = json.loads(json_match.group())
|
||||
except json.JSONDecodeError:
|
||||
# 如果JSON解析失败，尝试从文本中提取结果
|
||||
is_suitable = "不合适" not in content.lower() and "违规" not in content.lower()
|
||||
reason = content[:100] if content else "无法解析响应"
|
||||
need_replan = "重新规划" in content.lower() or "目标不适合" in content.lower()
|
||||
return is_suitable, reason, need_replan
|
||||
else:
|
||||
# 如果找不到JSON，从文本中判断
|
||||
is_suitable = "不合适" not in content.lower() and "违规" not in content.lower()
|
||||
reason = content[:100] if content else "无法解析响应"
|
||||
need_replan = "重新规划" in content.lower() or "目标不适合" in content.lower()
|
||||
return is_suitable, reason, need_replan
|
||||
|
||||
# 验证JSON字段
|
||||
suitable = result.get("suitable", None)
|
||||
reason = result.get("reason", "未提供原因")
|
||||
need_replan = result.get("need_replan", False)
|
||||
|
||||
# 如果suitable字段是字符串，转换为布尔值
|
||||
if isinstance(suitable, str):
|
||||
suitable = suitable.lower() == "true"
|
||||
|
||||
# 如果suitable字段不存在或不是布尔值，从reason中判断
|
||||
if suitable is None:
|
||||
suitable = "不合适" not in reason.lower() and "违规" not in reason.lower()
|
||||
|
||||
# 如果不合适且未达到最大重试次数，返回需要重试
|
||||
if not suitable and retry_count < self.max_retries:
|
||||
return False, reason, False
|
||||
|
||||
# 如果不合适且已达到最大重试次数，返回需要重新规划
|
||||
if not suitable and retry_count >= self.max_retries:
|
||||
return False, f"多次重试后仍不合适: {reason}", True
|
||||
|
||||
return suitable, reason, need_replan
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]检查回复时出错: {e}")
|
||||
# 如果出错且已达到最大重试次数，建议重新规划
|
||||
if retry_count >= self.max_retries:
|
||||
return False, "多次检查失败，建议重新规划", True
|
||||
return False, f"检查过程出错，建议重试: {str(e)}", False
|
||||
228
src/chat/brain_chat/PFC/reply_generator.py
Normal file
228
src/chat/brain_chat/PFC/reply_generator.py
Normal file
@@ -0,0 +1,228 @@
|
||||
from typing import Tuple, List, Dict, Any
|
||||
from src.common.logger import get_module_logger
|
||||
from ..models.utils_model import LLMRequest
|
||||
from ...config.config import global_config
|
||||
from .chat_observer import ChatObserver
|
||||
from .reply_checker import ReplyChecker
|
||||
from src.individuality.individuality import Individuality
|
||||
from .observation_info import ObservationInfo
|
||||
from .conversation_info import ConversationInfo
|
||||
from src.plugins.utils.chat_message_builder import build_readable_messages
|
||||
|
||||
logger = get_module_logger("reply_generator")
|
||||
|
||||
# --- 定义 Prompt 模板 ---
|
||||
|
||||
# Prompt for direct_reply (首次回复)
|
||||
PROMPT_DIRECT_REPLY = """{persona_text}。现在你在参与一场QQ私聊，请根据以下信息生成一条回复：
|
||||
|
||||
当前对话目标：{goals_str}
|
||||
|
||||
{knowledge_info_str}
|
||||
|
||||
最近的聊天记录：
|
||||
{chat_history_text}
|
||||
|
||||
|
||||
请根据上述信息，结合聊天记录，回复对方。该回复应该：
|
||||
1. 符合对话目标，以"你"的角度发言（不要自己与自己对话！）
|
||||
2. 符合你的性格特征和身份细节
|
||||
3. 通俗易懂，自然流畅，像正常聊天一样，简短（通常20字以内，除非特殊情况）
|
||||
4. 可以适当利用相关知识，但不要生硬引用
|
||||
5. 自然、得体，结合聊天记录逻辑合理，且没有重复表达同质内容
|
||||
|
||||
请注意把握聊天内容，不要回复的太有条理，可以有个性。请分清"你"和对方说的话，不要把"你"说的话当做对方说的话，这是你自己说的话。
|
||||
可以回复得自然随意自然一些，就像真人一样，注意把握聊天内容，整体风格可以平和、简短，不要刻意突出自身学科背景，不要说你说过的话，可以简短，多简短都可以，但是避免冗长。
|
||||
请你注意不要输出多余内容(包括前后缀，冒号和引号，括号，表情等)，只输出回复内容。
|
||||
不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )。
|
||||
|
||||
请直接输出回复内容，不需要任何额外格式。"""
|
||||
|
||||
# Prompt for send_new_message (追问/补充)
|
||||
PROMPT_SEND_NEW_MESSAGE = """{persona_text}。现在你在参与一场QQ私聊，**刚刚你已经发送了一条或多条消息**，现在请根据以下信息再发一条新消息：
|
||||
|
||||
当前对话目标：{goals_str}
|
||||
|
||||
{knowledge_info_str}
|
||||
|
||||
最近的聊天记录：
|
||||
{chat_history_text}
|
||||
|
||||
|
||||
请根据上述信息，结合聊天记录，继续发一条新消息（例如对之前消息的补充，深入话题，或追问等等）。该消息应该：
|
||||
1. 符合对话目标，以"你"的角度发言（不要自己与自己对话！）
|
||||
2. 符合你的性格特征和身份细节
|
||||
3. 通俗易懂，自然流畅，像正常聊天一样，简短（通常20字以内，除非特殊情况）
|
||||
4. 可以适当利用相关知识，但不要生硬引用
|
||||
5. 跟之前你发的消息自然的衔接，逻辑合理，且没有重复表达同质内容或部分重叠内容
|
||||
|
||||
请注意把握聊天内容，不用太有条理，可以有个性。请分清"你"和对方说的话，不要把"你"说的话当做对方说的话，这是你自己说的话。
|
||||
这条消息可以自然随意自然一些，就像真人一样，注意把握聊天内容，整体风格可以平和、简短，不要刻意突出自身学科背景，不要说你说过的话，可以简短，多简短都可以，但是避免冗长。
|
||||
请你注意不要输出多余内容(包括前后缀，冒号和引号，括号，表情等)，只输出消息内容。
|
||||
不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )。
|
||||
|
||||
请直接输出回复内容，不需要任何额外格式。"""
|
||||
|
||||
# Prompt for say_goodbye (告别语生成)
|
||||
PROMPT_FAREWELL = """{persona_text}。你在参与一场 QQ 私聊，现在对话似乎已经结束，你决定再发一条最后的消息来圆满结束。
|
||||
|
||||
最近的聊天记录：
|
||||
{chat_history_text}
|
||||
|
||||
请根据上述信息，结合聊天记录，构思一条**简短、自然、符合你人设**的最后的消息。
|
||||
这条消息应该：
|
||||
1. 从你自己的角度发言。
|
||||
2. 符合你的性格特征和身份细节。
|
||||
3. 通俗易懂，自然流畅，通常很简短。
|
||||
4. 自然地为这场对话画上句号，避免开启新话题或显得冗长、刻意。
|
||||
|
||||
请像真人一样随意自然，**简洁是关键**。
|
||||
不要输出多余内容（包括前后缀、冒号、引号、括号、表情包、at或@等）。
|
||||
|
||||
请直接输出最终的告别消息内容，不需要任何额外格式。"""
|
||||
|
||||
|
||||
class ReplyGenerator:
|
||||
"""回复生成器"""
|
||||
|
||||
def __init__(self, stream_id: str, private_name: str):
|
||||
self.llm = LLMRequest(
|
||||
model=global_config.llm_PFC_chat,
|
||||
temperature=global_config.llm_PFC_chat["temp"],
|
||||
max_tokens=300,
|
||||
request_type="reply_generation",
|
||||
)
|
||||
self.personality_info = Individuality.get_instance().get_prompt(x_person=2, level=3)
|
||||
self.name = global_config.BOT_NICKNAME
|
||||
self.private_name = private_name
|
||||
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
|
||||
self.reply_checker = ReplyChecker(stream_id, private_name)
|
||||
|
||||
# 修改 generate 方法签名，增加 action_type 参数
|
||||
async def generate(
|
||||
self, observation_info: ObservationInfo, conversation_info: ConversationInfo, action_type: str
|
||||
) -> str:
|
||||
"""生成回复
|
||||
|
||||
Args:
|
||||
observation_info: 观察信息
|
||||
conversation_info: 对话信息
|
||||
action_type: 当前执行的动作类型 ('direct_reply' 或 'send_new_message')
|
||||
|
||||
Returns:
|
||||
str: 生成的回复
|
||||
"""
|
||||
# 构建提示词
|
||||
logger.debug(
|
||||
f"[私聊][{self.private_name}]开始生成回复 (动作类型: {action_type})：当前目标: {conversation_info.goal_list}"
|
||||
)
|
||||
|
||||
# --- 构建通用 Prompt 参数 ---
|
||||
# (这部分逻辑基本不变)
|
||||
|
||||
# 构建对话目标 (goals_str)
|
||||
goals_str = ""
|
||||
if conversation_info.goal_list:
|
||||
for goal_reason in conversation_info.goal_list:
|
||||
if isinstance(goal_reason, dict):
|
||||
goal = goal_reason.get("goal", "目标内容缺失")
|
||||
reasoning = goal_reason.get("reasoning", "没有明确原因")
|
||||
else:
|
||||
goal = str(goal_reason)
|
||||
reasoning = "没有明确原因"
|
||||
|
||||
goal = str(goal) if goal is not None else "目标内容缺失"
|
||||
reasoning = str(reasoning) if reasoning is not None else "没有明确原因"
|
||||
goals_str += f"- 目标：{goal}\n 原因：{reasoning}\n"
|
||||
else:
|
||||
goals_str = "- 目前没有明确对话目标\n" # 简化无目标情况
|
||||
|
||||
# --- 新增：构建知识信息字符串 ---
|
||||
knowledge_info_str = "【供参考的相关知识和记忆】\n" # 稍微改下标题，表明是供参考
|
||||
try:
|
||||
# 检查 conversation_info 是否有 knowledge_list 并且不为空
|
||||
if hasattr(conversation_info, "knowledge_list") and conversation_info.knowledge_list:
|
||||
# 最多只显示最近的 5 条知识
|
||||
recent_knowledge = conversation_info.knowledge_list[-5:]
|
||||
for i, knowledge_item in enumerate(recent_knowledge):
|
||||
if isinstance(knowledge_item, dict):
|
||||
query = knowledge_item.get("query", "未知查询")
|
||||
knowledge = knowledge_item.get("knowledge", "无知识内容")
|
||||
source = knowledge_item.get("source", "未知来源")
|
||||
# 只取知识内容的前 2000 个字
|
||||
knowledge_snippet = knowledge[:2000] + "..." if len(knowledge) > 2000 else knowledge
|
||||
knowledge_info_str += (
|
||||
f"{i + 1}. 关于 '{query}' (来源: {source}): {knowledge_snippet}\n" # 格式微调，更简洁
|
||||
)
|
||||
else:
|
||||
knowledge_info_str += f"{i + 1}. 发现一条格式不正确的知识记录。\n"
|
||||
|
||||
if not recent_knowledge:
|
||||
knowledge_info_str += "- 暂无。\n" # 更简洁的提示
|
||||
|
||||
else:
|
||||
knowledge_info_str += "- 暂无。\n"
|
||||
except AttributeError:
|
||||
logger.warning(f"[私聊][{self.private_name}]ConversationInfo 对象可能缺少 knowledge_list 属性。")
|
||||
knowledge_info_str += "- 获取知识列表时出错。\n"
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]构建知识信息字符串时出错: {e}")
|
||||
knowledge_info_str += "- 处理知识列表时出错。\n"
|
||||
|
||||
# 获取聊天历史记录 (chat_history_text)
|
||||
chat_history_text = observation_info.chat_history_str
|
||||
if observation_info.new_messages_count > 0 and observation_info.unprocessed_messages:
|
||||
new_messages_list = observation_info.unprocessed_messages
|
||||
new_messages_str = await build_readable_messages(
|
||||
new_messages_list,
|
||||
replace_bot_name=True,
|
||||
merge_messages=False,
|
||||
timestamp_mode="relative",
|
||||
read_mark=0.0,
|
||||
)
|
||||
chat_history_text += f"\n--- 以下是 {observation_info.new_messages_count} 条新消息 ---\n{new_messages_str}"
|
||||
elif not chat_history_text:
|
||||
chat_history_text = "还没有聊天记录。"
|
||||
|
||||
# 构建 Persona 文本 (persona_text)
|
||||
persona_text = f"你的名字是{self.name}，{self.personality_info}。"
|
||||
|
||||
# --- 选择 Prompt ---
|
||||
if action_type == "send_new_message":
|
||||
prompt_template = PROMPT_SEND_NEW_MESSAGE
|
||||
logger.info(f"[私聊][{self.private_name}]使用 PROMPT_SEND_NEW_MESSAGE (追问生成)")
|
||||
elif action_type == "say_goodbye": # 处理告别动作
|
||||
prompt_template = PROMPT_FAREWELL
|
||||
logger.info(f"[私聊][{self.private_name}]使用 PROMPT_FAREWELL (告别语生成)")
|
||||
else: # 默认使用 direct_reply 的 prompt (包括 'direct_reply' 或其他未明确处理的类型)
|
||||
prompt_template = PROMPT_DIRECT_REPLY
|
||||
logger.info(f"[私聊][{self.private_name}]使用 PROMPT_DIRECT_REPLY (首次/非连续回复生成)")
|
||||
|
||||
# --- 格式化最终的 Prompt ---
|
||||
prompt = prompt_template.format(
|
||||
persona_text=persona_text,
|
||||
goals_str=goals_str,
|
||||
chat_history_text=chat_history_text,
|
||||
knowledge_info_str=knowledge_info_str,
|
||||
)
|
||||
|
||||
# --- 调用 LLM 生成 ---
|
||||
logger.debug(f"[私聊][{self.private_name}]发送到LLM的生成提示词:\n------\n{prompt}\n------")
|
||||
try:
|
||||
content, _ = await self.llm.generate_response_async(prompt)
|
||||
logger.debug(f"[私聊][{self.private_name}]生成的回复: {content}")
|
||||
# 移除旧的检查新消息逻辑，这应该由 conversation 控制流处理
|
||||
return content
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[私聊][{self.private_name}]生成回复时出错: {e}")
|
||||
return "抱歉，我现在有点混乱，让我重新思考一下..."
|
||||
|
||||
# check_reply 方法保持不变
|
||||
async def check_reply(
|
||||
self, reply: str, goal: str, chat_history: List[Dict[str, Any]], chat_history_str: str, retry_count: int = 0
|
||||
) -> Tuple[bool, str, bool]:
|
||||
"""检查回复是否合适
|
||||
(此方法逻辑保持不变)
|
||||
"""
|
||||
return await self.reply_checker.check(reply, goal, chat_history, chat_history_str, retry_count)
|
||||
79
src/chat/brain_chat/PFC/waiter.py
Normal file
79
src/chat/brain_chat/PFC/waiter.py
Normal file
@@ -0,0 +1,79 @@
|
||||
from src.common.logger import get_module_logger
|
||||
from .chat_observer import ChatObserver
|
||||
from .conversation_info import ConversationInfo
|
||||
|
||||
# from src.individuality.individuality import Individuality # 不再需要
|
||||
from ...config.config import global_config
|
||||
import time
|
||||
import asyncio
|
||||
|
||||
logger = get_module_logger("waiter")
|
||||
|
||||
# --- 在这里设定你想要的超时时间（秒） ---
|
||||
# 例如： 120 秒 = 2 分钟
|
||||
DESIRED_TIMEOUT_SECONDS = 300
|
||||
|
||||
|
||||
class Waiter:
|
||||
"""等待处理类"""
|
||||
|
||||
def __init__(self, stream_id: str, private_name: str):
|
||||
self.chat_observer = ChatObserver.get_instance(stream_id, private_name)
|
||||
self.name = global_config.BOT_NICKNAME
|
||||
self.private_name = private_name
|
||||
# self.wait_accumulated_time = 0 # 不再需要累加计时
|
||||
|
||||
async def wait(self, conversation_info: ConversationInfo) -> bool:
|
||||
"""等待用户新消息或超时"""
|
||||
wait_start_time = time.time()
|
||||
logger.info(f"[私聊][{self.private_name}]进入常规等待状态 (超时: {DESIRED_TIMEOUT_SECONDS} 秒)...")
|
||||
|
||||
while True:
|
||||
# 检查是否有新消息
|
||||
if self.chat_observer.new_message_after(wait_start_time):
|
||||
logger.info(f"[私聊][{self.private_name}]等待结束，收到新消息")
|
||||
return False # 返回 False 表示不是超时
|
||||
|
||||
# 检查是否超时
|
||||
elapsed_time = time.time() - wait_start_time
|
||||
if elapsed_time > DESIRED_TIMEOUT_SECONDS:
|
||||
logger.info(f"[私聊][{self.private_name}]等待超过 {DESIRED_TIMEOUT_SECONDS} 秒...添加思考目标。")
|
||||
wait_goal = {
|
||||
"goal": f"你等待了{elapsed_time / 60:.1f}分钟，注意可能在对方看来聊天已经结束，思考接下来要做什么",
|
||||
"reasoning": "对方很久没有回复你的消息了",
|
||||
}
|
||||
conversation_info.goal_list.append(wait_goal)
|
||||
logger.info(f"[私聊][{self.private_name}]添加目标: {wait_goal}")
|
||||
return True # 返回 True 表示超时
|
||||
|
||||
await asyncio.sleep(5) # 每 5 秒检查一次
|
||||
logger.debug(
|
||||
f"[私聊][{self.private_name}]等待中..."
|
||||
) # 可以考虑把这个频繁日志注释掉，只在超时或收到消息时输出
|
||||
|
||||
async def wait_listening(self, conversation_info: ConversationInfo) -> bool:
|
||||
"""倾听用户发言或超时"""
|
||||
wait_start_time = time.time()
|
||||
logger.info(f"[私聊][{self.private_name}]进入倾听等待状态 (超时: {DESIRED_TIMEOUT_SECONDS} 秒)...")
|
||||
|
||||
while True:
|
||||
# 检查是否有新消息
|
||||
if self.chat_observer.new_message_after(wait_start_time):
|
||||
logger.info(f"[私聊][{self.private_name}]倾听等待结束，收到新消息")
|
||||
return False # 返回 False 表示不是超时
|
||||
|
||||
# 检查是否超时
|
||||
elapsed_time = time.time() - wait_start_time
|
||||
if elapsed_time > DESIRED_TIMEOUT_SECONDS:
|
||||
logger.info(f"[私聊][{self.private_name}]倾听等待超过 {DESIRED_TIMEOUT_SECONDS} 秒...添加思考目标。")
|
||||
wait_goal = {
|
||||
# 保持 goal 文本一致
|
||||
"goal": f"你等待了{elapsed_time / 60:.1f}分钟，对方似乎话说一半突然消失了，可能忙去了？也可能忘记了回复？要问问吗？还是结束对话？或继续等待？思考接下来要做什么",
|
||||
"reasoning": "对方话说一半消失了，很久没有回复",
|
||||
}
|
||||
conversation_info.goal_list.append(wait_goal)
|
||||
logger.info(f"[私聊][{self.private_name}]添加目标: {wait_goal}")
|
||||
return True # 返回 True 表示超时
|
||||
|
||||
await asyncio.sleep(5) # 每 5 秒检查一次
|
||||
logger.debug(f"[私聊][{self.private_name}]倾听等待中...") # 同上，可以考虑注释掉
|
||||
@@ -16,7 +16,8 @@ from src.chat.brain_chat.brain_planner import BrainPlanner
|
||||
from src.chat.planner_actions.action_modifier import ActionModifier
|
||||
from src.chat.planner_actions.action_manager import ActionManager
|
||||
from src.chat.heart_flow.hfc_utils import CycleDetail
|
||||
from src.express.expression_learner import expression_learner_manager
|
||||
from src.bw_learner.expression_learner import expression_learner_manager
|
||||
from src.bw_learner.message_recorder import extract_and_distribute_messages
|
||||
from src.person_info.person_info import Person
|
||||
from src.plugin_system.base.component_types import EventType, ActionInfo
|
||||
from src.plugin_system.core import events_manager
|
||||
@@ -96,6 +97,9 @@ class BrainChatting:
|
||||
|
||||
self.more_plan = False
|
||||
|
||||
# 最近一次是否成功进行了 reply，用于选择 BrainPlanner 的 Prompt
|
||||
self._last_successful_reply: bool = False
|
||||
|
||||
async def start(self):
|
||||
"""检查是否需要启动主循环，如果未激活则启动。"""
|
||||
|
||||
@@ -157,6 +161,7 @@ class BrainChatting:
|
||||
)
|
||||
|
||||
async def _loopbody(self): # sourcery skip: hoist-if-from-if
|
||||
# 获取最新消息（用于上下文，但不影响是否调用 observe）
|
||||
recent_messages_list = message_api.get_messages_by_time_in_chat(
|
||||
chat_id=self.stream_id,
|
||||
start_time=self.last_read_time,
|
||||
@@ -165,17 +170,25 @@ class BrainChatting:
|
||||
limit_mode="latest",
|
||||
filter_mai=True,
|
||||
filter_command=False,
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
|
||||
# 如果有新消息，更新 last_read_time
|
||||
if len(recent_messages_list) >= 1:
|
||||
self.last_read_time = time.time()
|
||||
await self._observe(recent_messages_list=recent_messages_list)
|
||||
|
||||
else:
|
||||
# Normal模式：消息数量不足，等待
|
||||
await asyncio.sleep(0.2)
|
||||
return True
|
||||
# 总是执行一次思考迭代（不管有没有新消息）
|
||||
# wait 动作会在其内部等待，不需要在这里处理
|
||||
should_continue = await self._observe(recent_messages_list=recent_messages_list)
|
||||
|
||||
if not should_continue:
|
||||
# 选择了 complete_talk，返回 False 表示需要等待新消息
|
||||
return False
|
||||
|
||||
# 继续下一次迭代（除非选择了 complete_talk）
|
||||
# 短暂等待后再继续，避免过于频繁的循环
|
||||
await asyncio.sleep(0.1)
|
||||
|
||||
return True
|
||||
|
||||
async def _send_and_store_reply(
|
||||
@@ -240,7 +253,7 @@ class BrainChatting:
|
||||
# ReflectTracker Check
|
||||
# 在每次回复前检查一次上下文，看是否有反思问题得到了解答
|
||||
# -------------------------------------------------------------------------
|
||||
from src.express.reflect_tracker import reflect_tracker_manager
|
||||
from src.bw_learner.reflect_tracker import reflect_tracker_manager
|
||||
|
||||
tracker = reflect_tracker_manager.get_tracker(self.stream_id)
|
||||
if tracker:
|
||||
@@ -253,13 +266,15 @@ class BrainChatting:
|
||||
# Expression Reflection Check
|
||||
# 检查是否需要提问表达反思
|
||||
# -------------------------------------------------------------------------
|
||||
from src.express.expression_reflector import expression_reflector_manager
|
||||
from src.bw_learner.expression_reflector import expression_reflector_manager
|
||||
|
||||
reflector = expression_reflector_manager.get_or_create_reflector(self.stream_id)
|
||||
asyncio.create_task(reflector.check_and_ask())
|
||||
|
||||
async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()):
|
||||
asyncio.create_task(self.expression_learner.trigger_learning_for_chat())
|
||||
# 通过 MessageRecorder 统一提取消息并分发给 expression_learner 和 jargon_miner
|
||||
# 在 replyer 执行时触发，统一管理时间窗口，避免重复获取消息
|
||||
asyncio.create_task(extract_and_distribute_messages(self.stream_id))
|
||||
|
||||
cycle_timers, thinking_id = self.start_cycle()
|
||||
logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次思考")
|
||||
@@ -272,14 +287,16 @@ class BrainChatting:
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 动作修改失败: {e}")
|
||||
|
||||
# 执行planner
|
||||
# 获取必要信息
|
||||
is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info()
|
||||
|
||||
# 一次思考迭代：Think - Act - Observe
|
||||
# 获取聊天上下文
|
||||
message_list_before_now = get_raw_msg_before_timestamp_with_chat(
|
||||
chat_id=self.stream_id,
|
||||
timestamp=time.time(),
|
||||
limit=int(global_config.chat.max_context_size * 0.6),
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
chat_content_block, message_id_list = build_readable_messages_with_id(
|
||||
messages=message_list_before_now,
|
||||
@@ -290,12 +307,11 @@ class BrainChatting:
|
||||
)
|
||||
|
||||
prompt_info = await self.action_planner.build_planner_prompt(
|
||||
is_group_chat=is_group_chat,
|
||||
chat_target_info=chat_target_info,
|
||||
current_available_actions=available_actions,
|
||||
chat_content_block=chat_content_block,
|
||||
message_id_list=message_id_list,
|
||||
interest=global_config.personality.interest,
|
||||
prompt_key="brain_planner_prompt_react",
|
||||
)
|
||||
continue_flag, modified_message = await events_manager.handle_mai_events(
|
||||
EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id
|
||||
@@ -311,7 +327,10 @@ class BrainChatting:
|
||||
available_actions=available_actions,
|
||||
)
|
||||
|
||||
# 3. 并行执行所有动作
|
||||
# 检查是否有 complete_talk 动作（会停止后续迭代）
|
||||
has_complete_talk = any(action.action_type == "complete_talk" for action in action_to_use_info)
|
||||
|
||||
# 并行执行所有动作
|
||||
action_tasks = [
|
||||
asyncio.create_task(
|
||||
self._execute_action(action, action_to_use_info, thinking_id, available_actions, cycle_timers)
|
||||
@@ -343,7 +362,14 @@ class BrainChatting:
|
||||
else:
|
||||
logger.warning(f"{self.log_prefix} 回复动作执行失败")
|
||||
|
||||
# 构建最终的循环信息
|
||||
# 更新观察时间标记
|
||||
self.action_planner.last_obs_time_mark = time.time()
|
||||
|
||||
# 如果选择了 complete_talk，标记为完成，不再继续迭代
|
||||
if has_complete_talk:
|
||||
logger.info(f"{self.log_prefix} 检测到 complete_talk 动作，本次思考完成")
|
||||
|
||||
# 构建循环信息
|
||||
if reply_loop_info:
|
||||
# 如果有回复信息，使用回复的loop_info作为基础
|
||||
loop_info = reply_loop_info
|
||||
@@ -369,10 +395,16 @@ class BrainChatting:
|
||||
}
|
||||
_reply_text = action_reply_text
|
||||
|
||||
# 如果选择了 complete_talk，返回 False 以停止 _loopbody 的循环
|
||||
# 否则返回 True，让 _loopbody 继续下一次迭代
|
||||
should_continue = not has_complete_talk
|
||||
|
||||
self.end_cycle(loop_info, cycle_timers)
|
||||
self.print_cycle_info(cycle_timers)
|
||||
|
||||
return True
|
||||
# 如果选择了 complete_talk，返回 False 停止循环
|
||||
# 否则返回 True，继续下一次思考迭代
|
||||
return should_continue
|
||||
|
||||
async def _main_chat_loop(self):
|
||||
"""主循环，持续进行计划并可能回复消息，直到被外部取消。"""
|
||||
@@ -380,9 +412,13 @@ class BrainChatting:
|
||||
while self.running:
|
||||
# 主循环
|
||||
success = await self._loopbody()
|
||||
await asyncio.sleep(0.1)
|
||||
if not success:
|
||||
break
|
||||
# 选择了 complete，等待新消息
|
||||
logger.info(f"{self.log_prefix} 选择了 complete，等待新消息...")
|
||||
await self._wait_for_new_message()
|
||||
# 有新消息后继续循环
|
||||
continue
|
||||
await asyncio.sleep(0.1)
|
||||
except asyncio.CancelledError:
|
||||
# 设置了关闭标志位后被取消是正常流程
|
||||
logger.info(f"{self.log_prefix} 麦麦已关闭聊天")
|
||||
@@ -393,6 +429,33 @@ class BrainChatting:
|
||||
self._loop_task = asyncio.create_task(self._main_chat_loop())
|
||||
logger.error(f"{self.log_prefix} 结束了当前聊天循环")
|
||||
|
||||
async def _wait_for_new_message(self):
|
||||
"""等待新消息到达"""
|
||||
last_check_time = self.last_read_time
|
||||
check_interval = 1.0 # 每秒检查一次
|
||||
|
||||
while self.running:
|
||||
# 检查是否有新消息
|
||||
recent_messages_list = message_api.get_messages_by_time_in_chat(
|
||||
chat_id=self.stream_id,
|
||||
start_time=last_check_time,
|
||||
end_time=time.time(),
|
||||
limit=20,
|
||||
limit_mode="latest",
|
||||
filter_mai=True,
|
||||
filter_command=False,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
|
||||
# 如果有新消息，更新 last_read_time 并返回
|
||||
if len(recent_messages_list) >= 1:
|
||||
self.last_read_time = time.time()
|
||||
logger.info(f"{self.log_prefix} 检测到新消息，恢复循环")
|
||||
return
|
||||
|
||||
# 等待一段时间后再次检查
|
||||
await asyncio.sleep(check_interval)
|
||||
|
||||
async def _handle_action(
|
||||
self,
|
||||
action: str,
|
||||
@@ -506,12 +569,12 @@ class BrainChatting:
|
||||
"""执行单个动作的通用函数"""
|
||||
try:
|
||||
with Timer(f"动作{action_planner_info.action_type}", cycle_timers):
|
||||
if action_planner_info.action_type == "no_reply":
|
||||
# 直接处理no_reply逻辑，不再通过动作系统
|
||||
reason = action_planner_info.reasoning or "选择不回复"
|
||||
# logger.info(f"{self.log_prefix} 选择不回复，原因: {reason}")
|
||||
if action_planner_info.action_type == "complete_talk":
|
||||
# 直接处理complete_talk逻辑，不再通过动作系统
|
||||
reason = action_planner_info.reasoning or "选择完成对话"
|
||||
logger.info(f"{self.log_prefix} 选择完成对话，原因: {reason}")
|
||||
|
||||
# 存储no_reply信息到数据库
|
||||
# 存储complete_talk信息到数据库
|
||||
await database_api.store_action_info(
|
||||
chat_stream=self.chat_stream,
|
||||
action_build_into_prompt=False,
|
||||
@@ -519,9 +582,9 @@ class BrainChatting:
|
||||
action_done=True,
|
||||
thinking_id=thinking_id,
|
||||
action_data={"reason": reason},
|
||||
action_name="no_reply",
|
||||
action_name="complete_talk",
|
||||
)
|
||||
return {"action_type": "no_reply", "success": True, "reply_text": "", "command": ""}
|
||||
return {"action_type": "complete_talk", "success": True, "reply_text": "", "command": ""}
|
||||
|
||||
elif action_planner_info.action_type == "reply":
|
||||
try:
|
||||
@@ -543,11 +606,17 @@ class BrainChatting:
|
||||
)
|
||||
else:
|
||||
logger.info("回复生成失败")
|
||||
return {"action_type": "reply", "success": False, "reply_text": "", "loop_info": None}
|
||||
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(
|
||||
@@ -558,6 +627,8 @@ class BrainChatting:
|
||||
actions=chosen_action_plan_infos,
|
||||
selected_expressions=selected_expressions,
|
||||
)
|
||||
# 标记这次循环已经成功进行了回复
|
||||
self._last_successful_reply = True
|
||||
return {
|
||||
"action_type": "reply",
|
||||
"success": True,
|
||||
@@ -567,7 +638,88 @@ class BrainChatting:
|
||||
|
||||
# 其他动作
|
||||
else:
|
||||
# 执行普通动作
|
||||
# 内建 wait / listening：不通过插件系统，直接在这里处理
|
||||
if action_planner_info.action_type in ["wait", "listening"]:
|
||||
reason = action_planner_info.reasoning or ""
|
||||
action_data = action_planner_info.action_data or {}
|
||||
|
||||
if action_planner_info.action_type == "wait":
|
||||
# 获取等待时间（必填）
|
||||
wait_seconds = action_data.get("wait_seconds")
|
||||
if wait_seconds is None:
|
||||
logger.warning(f"{self.log_prefix} wait 动作缺少 wait_seconds 参数，使用默认值 5 秒")
|
||||
wait_seconds = 5
|
||||
else:
|
||||
try:
|
||||
wait_seconds = float(wait_seconds)
|
||||
if wait_seconds < 0:
|
||||
logger.warning(f"{self.log_prefix} wait_seconds 不能为负数，使用默认值 5 秒")
|
||||
wait_seconds = 5
|
||||
except (ValueError, TypeError):
|
||||
logger.warning(f"{self.log_prefix} wait_seconds 参数格式错误，使用默认值 5 秒")
|
||||
wait_seconds = 5
|
||||
|
||||
logger.info(f"{self.log_prefix} 执行 wait 动作，等待 {wait_seconds} 秒")
|
||||
|
||||
# 记录动作信息
|
||||
await database_api.store_action_info(
|
||||
chat_stream=self.chat_stream,
|
||||
action_build_into_prompt=False,
|
||||
action_prompt_display=reason or f"等待 {wait_seconds} 秒",
|
||||
action_done=True,
|
||||
thinking_id=thinking_id,
|
||||
action_data={"reason": reason, "wait_seconds": wait_seconds},
|
||||
action_name="wait",
|
||||
)
|
||||
|
||||
# 等待指定时间
|
||||
await asyncio.sleep(wait_seconds)
|
||||
|
||||
logger.info(f"{self.log_prefix} wait 动作完成，继续下一次思考")
|
||||
|
||||
# 这些动作本身不产生文本回复
|
||||
self._last_successful_reply = False
|
||||
return {
|
||||
"action_type": "wait",
|
||||
"success": True,
|
||||
"reply_text": "",
|
||||
"command": "",
|
||||
}
|
||||
|
||||
# listening 已合并到 wait，如果遇到则转换为 wait（向后兼容）
|
||||
elif action_planner_info.action_type == "listening":
|
||||
logger.debug(f"{self.log_prefix} 检测到 listening 动作，已合并到 wait，自动转换")
|
||||
# 使用默认等待时间
|
||||
wait_seconds = 3
|
||||
|
||||
logger.info(f"{self.log_prefix} 执行 listening（转换为 wait）动作，等待 {wait_seconds} 秒")
|
||||
|
||||
# 记录动作信息
|
||||
await database_api.store_action_info(
|
||||
chat_stream=self.chat_stream,
|
||||
action_build_into_prompt=False,
|
||||
action_prompt_display=reason or f"倾听并等待 {wait_seconds} 秒",
|
||||
action_done=True,
|
||||
thinking_id=thinking_id,
|
||||
action_data={"reason": reason, "wait_seconds": wait_seconds},
|
||||
action_name="listening",
|
||||
)
|
||||
|
||||
# 等待指定时间
|
||||
await asyncio.sleep(wait_seconds)
|
||||
|
||||
logger.info(f"{self.log_prefix} listening 动作完成，继续下一次思考")
|
||||
|
||||
# 这些动作本身不产生文本回复
|
||||
self._last_successful_reply = False
|
||||
return {
|
||||
"action_type": "listening",
|
||||
"success": True,
|
||||
"reply_text": "",
|
||||
"command": "",
|
||||
}
|
||||
|
||||
# 其余动作：走原有插件 Action 体系
|
||||
with Timer("动作执行", cycle_timers):
|
||||
success, reply_text, command = await self._handle_action(
|
||||
action_planner_info.action_type,
|
||||
@@ -577,6 +729,10 @@ class BrainChatting:
|
||||
thinking_id,
|
||||
action_planner_info.action_message,
|
||||
)
|
||||
# 非 reply 类动作执行成功时，清空最近成功回复标记，让下一轮回到 initial Prompt
|
||||
if success and action_planner_info.action_type != "reply":
|
||||
self._last_successful_reply = False
|
||||
|
||||
return {
|
||||
"action_type": action_planner_info.action_type,
|
||||
"success": success,
|
||||
|
||||
@@ -35,12 +35,13 @@ install(extra_lines=3)
|
||||
|
||||
|
||||
def init_prompt():
|
||||
# ReAct 形式的 Planner Prompt
|
||||
Prompt(
|
||||
"""
|
||||
{time_block}
|
||||
{name_block}
|
||||
你的兴趣是：{interest}
|
||||
{chat_context_description}，以下是具体的聊天内容
|
||||
|
||||
**聊天内容**
|
||||
{chat_content_block}
|
||||
|
||||
@@ -57,11 +58,35 @@ reply
|
||||
"reason":"回复的原因"
|
||||
}}
|
||||
|
||||
no_reply
|
||||
wait
|
||||
动作描述：
|
||||
等待，保持沉默，等待对方发言
|
||||
暂时不再发言，等待指定时间。适用于以下情况：
|
||||
- 你已经表达清楚一轮，想给对方留出空间
|
||||
- 你感觉对方的话还没说完，或者自己刚刚发了好几条连续消息
|
||||
- 你想要等待一定时间来让对方把话说完，或者等待对方反应
|
||||
- 你想保持安静，专注"听"而不是马上回复
|
||||
请你根据上下文来判断要等待多久，请你灵活判断：
|
||||
- 如果你们交流间隔时间很短，聊的很频繁，不宜等待太久
|
||||
- 如果你们交流间隔时间很长，聊的很少，可以等待较长时间
|
||||
{{
|
||||
"action": "no_reply",
|
||||
"action": "wait",
|
||||
"target_message_id":"想要作为这次等待依据的消息id（通常是对方的最新消息）",
|
||||
"wait_seconds": 等待的秒数（必填，例如：5 表示等待5秒）,
|
||||
"reason":"选择等待的原因"
|
||||
}}
|
||||
|
||||
complete_talk
|
||||
动作描述：
|
||||
当前聊天暂时结束了，对方离开，没有更多话题了
|
||||
你可以使用该动作来暂时休息，等待对方有新发言再继续：
|
||||
- 多次wait之后，对方迟迟不回复消息才用
|
||||
- 如果对方只是短暂不回复，应该使用wait而不是complete_talk
|
||||
- 聊天内容显示当前聊天已经结束或者没有新内容时候，选择complete_talk
|
||||
选择此动作后，将不再继续循环思考，直到收到对方的新消息
|
||||
{{
|
||||
"action": "complete_talk",
|
||||
"target_message_id":"触发完成对话的消息id（通常是对方的最新消息）",
|
||||
"reason":"选择完成对话的原因"
|
||||
}}
|
||||
|
||||
{action_options_text}
|
||||
@@ -92,7 +117,7 @@ no_reply
|
||||
```
|
||||
|
||||
""",
|
||||
"brain_planner_prompt",
|
||||
"brain_planner_prompt_react",
|
||||
)
|
||||
|
||||
Prompt(
|
||||
@@ -123,6 +148,9 @@ class BrainPlanner:
|
||||
|
||||
self.last_obs_time_mark = 0.0
|
||||
|
||||
# 计划日志记录
|
||||
self.plan_log: List[Tuple[str, float, List[ActionPlannerInfo]]] = []
|
||||
|
||||
def find_message_by_id(
|
||||
self, message_id: str, message_id_list: List[Tuple[str, "DatabaseMessages"]]
|
||||
) -> Optional["DatabaseMessages"]:
|
||||
@@ -152,10 +180,11 @@ class BrainPlanner:
|
||||
action_planner_infos = []
|
||||
|
||||
try:
|
||||
action = action_json.get("action", "no_reply")
|
||||
action = action_json.get("action", "complete_talk")
|
||||
logger.debug(f"{self.log_prefix}解析动作JSON: action={action}, json={action_json}")
|
||||
reasoning = action_json.get("reason", "未提供原因")
|
||||
action_data = {key: value for key, value in action_json.items() if key not in ["action", "reason"]}
|
||||
# 非no_reply动作需要target_message_id
|
||||
# 非complete_talk动作需要target_message_id
|
||||
target_message = None
|
||||
|
||||
if target_message_id := action_json.get("target_message_id"):
|
||||
@@ -171,16 +200,28 @@ class BrainPlanner:
|
||||
|
||||
# 验证action是否可用
|
||||
available_action_names = [action_name for action_name, _ in current_available_actions]
|
||||
internal_action_names = ["no_reply", "reply", "wait_time"]
|
||||
# 内部保留动作（不依赖插件系统）
|
||||
# 注意：listening 已合并到 wait 中，如果遇到 listening 则转换为 wait
|
||||
internal_action_names = ["complete_talk", "reply", "wait_time", "wait", "listening"]
|
||||
|
||||
logger.debug(
|
||||
f"{self.log_prefix}动作验证: action={action}, internal={internal_action_names}, available={available_action_names}"
|
||||
)
|
||||
|
||||
# 将 listening 转换为 wait（向后兼容）
|
||||
if action == "listening":
|
||||
logger.debug(f"{self.log_prefix}检测到 listening 动作，已合并到 wait，自动转换")
|
||||
action = "wait"
|
||||
|
||||
if action not in internal_action_names and action not in available_action_names:
|
||||
logger.warning(
|
||||
f"{self.log_prefix}LLM 返回了当前不可用或无效的动作: '{action}' (可用: {available_action_names})，将强制使用 'no_reply'"
|
||||
f"{self.log_prefix}LLM 返回了当前不可用或无效的动作: '{action}' (内部动作: {internal_action_names}, 可用插件动作: {available_action_names})，将强制使用 'complete_talk'"
|
||||
)
|
||||
reasoning = (
|
||||
f"LLM 返回了当前不可用的动作 '{action}' (可用: {available_action_names})。原始理由: {reasoning}"
|
||||
)
|
||||
action = "no_reply"
|
||||
action = "complete_talk"
|
||||
logger.warning(f"{self.log_prefix}动作已转换为 complete_talk")
|
||||
|
||||
# 创建ActionPlannerInfo对象
|
||||
# 将列表转换为字典格式
|
||||
@@ -201,7 +242,7 @@ class BrainPlanner:
|
||||
available_actions_dict = dict(current_available_actions)
|
||||
action_planner_infos.append(
|
||||
ActionPlannerInfo(
|
||||
action_type="no_reply",
|
||||
action_type="complete_talk",
|
||||
reasoning=f"解析单个action时出错: {e}",
|
||||
action_data={},
|
||||
action_message=None,
|
||||
@@ -218,7 +259,7 @@ class BrainPlanner:
|
||||
) -> List[ActionPlannerInfo]:
|
||||
# sourcery skip: use-named-expression
|
||||
"""
|
||||
规划器 (Planner): 使用LLM根据上下文决定做出什么动作。
|
||||
规划器 (Planner): 使用LLM根据上下文决定做出什么动作（ReAct模式）。
|
||||
"""
|
||||
|
||||
# 获取聊天上下文
|
||||
@@ -226,7 +267,7 @@ class BrainPlanner:
|
||||
chat_id=self.chat_id,
|
||||
timestamp=time.time(),
|
||||
limit=int(global_config.chat.max_context_size * 0.6),
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
message_id_list: list[Tuple[str, "DatabaseMessages"]] = []
|
||||
chat_content_block, message_id_list = build_readable_messages_with_id(
|
||||
@@ -257,18 +298,19 @@ class BrainPlanner:
|
||||
|
||||
logger.debug(f"{self.log_prefix}过滤后有{len(filtered_actions)}个可用动作")
|
||||
|
||||
# 构建包含所有动作的提示词
|
||||
# 构建包含所有动作的提示词：使用统一的 ReAct Prompt
|
||||
prompt_key = "brain_planner_prompt_react"
|
||||
# 这里不记录日志，避免重复打印，由调用方按需控制 log_prompt
|
||||
prompt, message_id_list = await self.build_planner_prompt(
|
||||
is_group_chat=is_group_chat,
|
||||
chat_target_info=chat_target_info,
|
||||
current_available_actions=filtered_actions,
|
||||
chat_content_block=chat_content_block,
|
||||
message_id_list=message_id_list,
|
||||
interest=global_config.personality.interest,
|
||||
prompt_key=prompt_key,
|
||||
)
|
||||
|
||||
# 调用LLM获取决策
|
||||
actions = await self._execute_main_planner(
|
||||
reasoning, actions = await self._execute_main_planner(
|
||||
prompt=prompt,
|
||||
message_id_list=message_id_list,
|
||||
filtered_actions=filtered_actions,
|
||||
@@ -276,16 +318,22 @@ class BrainPlanner:
|
||||
loop_start_time=loop_start_time,
|
||||
)
|
||||
|
||||
# 记录和展示计划日志
|
||||
logger.info(
|
||||
f"{self.log_prefix}Planner: {reasoning}。选择了{len(actions)}个动作: {' '.join([a.action_type for a in actions])}"
|
||||
)
|
||||
self.add_plan_log(reasoning, actions)
|
||||
|
||||
return actions
|
||||
|
||||
async def build_planner_prompt(
|
||||
self,
|
||||
is_group_chat: bool,
|
||||
chat_target_info: Optional["TargetPersonInfo"],
|
||||
current_available_actions: Dict[str, ActionInfo],
|
||||
message_id_list: List[Tuple[str, "DatabaseMessages"]],
|
||||
chat_content_block: str = "",
|
||||
interest: str = "",
|
||||
prompt_key: str = "brain_planner_prompt_react",
|
||||
) -> tuple[str, List[Tuple[str, "DatabaseMessages"]]]:
|
||||
"""构建 Planner LLM 的提示词 (获取模板并填充数据)"""
|
||||
try:
|
||||
@@ -321,7 +369,7 @@ class BrainPlanner:
|
||||
name_block = f"你的名字是{bot_name}{bot_nickname}，请注意哪些是你自己的发言。"
|
||||
|
||||
# 获取主规划器模板并填充
|
||||
planner_prompt_template = await global_prompt_manager.get_prompt_async("brain_planner_prompt")
|
||||
planner_prompt_template = await global_prompt_manager.get_prompt_async(prompt_key)
|
||||
prompt = planner_prompt_template.format(
|
||||
time_block=time_block,
|
||||
chat_context_description=chat_context_description,
|
||||
@@ -431,17 +479,18 @@ class BrainPlanner:
|
||||
filtered_actions: Dict[str, ActionInfo],
|
||||
available_actions: Dict[str, ActionInfo],
|
||||
loop_start_time: float,
|
||||
) -> List[ActionPlannerInfo]:
|
||||
) -> Tuple[str, List[ActionPlannerInfo]]:
|
||||
"""执行主规划器"""
|
||||
llm_content = None
|
||||
actions: List[ActionPlannerInfo] = []
|
||||
extracted_reasoning = ""
|
||||
|
||||
try:
|
||||
# 调用LLM
|
||||
llm_content, (reasoning_content, _, _) = await self.planner_llm.generate_response_async(prompt=prompt)
|
||||
|
||||
# logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
|
||||
# logger.info(f"{self.log_prefix}规划器原始响应: {llm_content}")
|
||||
logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
|
||||
logger.info(f"{self.log_prefix}规划器原始响应: {llm_content}")
|
||||
|
||||
if global_config.debug.show_planner_prompt:
|
||||
logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
|
||||
@@ -456,10 +505,11 @@ class BrainPlanner:
|
||||
|
||||
except Exception as req_e:
|
||||
logger.error(f"{self.log_prefix}LLM 请求执行失败: {req_e}")
|
||||
return [
|
||||
extracted_reasoning = f"LLM 请求失败，模型出现问题: {req_e}"
|
||||
return extracted_reasoning, [
|
||||
ActionPlannerInfo(
|
||||
action_type="no_reply",
|
||||
reasoning=f"LLM 请求失败，模型出现问题: {req_e}",
|
||||
action_type="complete_talk",
|
||||
reasoning=extracted_reasoning,
|
||||
action_data={},
|
||||
action_message=None,
|
||||
available_actions=available_actions,
|
||||
@@ -469,24 +519,32 @@ class BrainPlanner:
|
||||
# 解析LLM响应
|
||||
if llm_content:
|
||||
try:
|
||||
if json_objects := self._extract_json_from_markdown(llm_content):
|
||||
logger.debug(f"{self.log_prefix}从响应中提取到{len(json_objects)}个JSON对象")
|
||||
json_objects, extracted_reasoning = self._extract_json_from_markdown(llm_content)
|
||||
if json_objects:
|
||||
logger.info(f"{self.log_prefix}从响应中提取到{len(json_objects)}个JSON对象")
|
||||
for i, json_obj in enumerate(json_objects):
|
||||
logger.info(f"{self.log_prefix}解析第{i + 1}个JSON对象: {json_obj}")
|
||||
filtered_actions_list = list(filtered_actions.items())
|
||||
for json_obj in json_objects:
|
||||
actions.extend(self._parse_single_action(json_obj, message_id_list, filtered_actions_list))
|
||||
parsed_actions = self._parse_single_action(json_obj, message_id_list, filtered_actions_list)
|
||||
logger.info(f"{self.log_prefix}解析后的动作: {[a.action_type for a in parsed_actions]}")
|
||||
actions.extend(parsed_actions)
|
||||
else:
|
||||
# 尝试解析为直接的JSON
|
||||
logger.warning(f"{self.log_prefix}LLM没有返回可用动作: {llm_content}")
|
||||
actions = self._create_no_reply("LLM没有返回可用动作", available_actions)
|
||||
extracted_reasoning = extracted_reasoning or "LLM没有返回可用动作"
|
||||
actions = self._create_complete_talk(extracted_reasoning, available_actions)
|
||||
|
||||
except Exception as json_e:
|
||||
logger.warning(f"{self.log_prefix}解析LLM响应JSON失败 {json_e}. LLM原始输出: '{llm_content}'")
|
||||
actions = self._create_no_reply(f"解析LLM响应JSON失败: {json_e}", available_actions)
|
||||
extracted_reasoning = f"解析LLM响应JSON失败: {json_e}"
|
||||
actions = self._create_complete_talk(extracted_reasoning, available_actions)
|
||||
traceback.print_exc()
|
||||
else:
|
||||
actions = self._create_no_reply("规划器没有获得LLM响应", available_actions)
|
||||
extracted_reasoning = "规划器没有获得LLM响应"
|
||||
actions = self._create_complete_talk(extracted_reasoning, available_actions)
|
||||
|
||||
# 添加循环开始时间到所有非no_reply动作
|
||||
# 添加循环开始时间到所有动作
|
||||
for action in actions:
|
||||
action.action_data = action.action_data or {}
|
||||
action.action_data["loop_start_time"] = loop_start_time
|
||||
@@ -495,13 +553,15 @@ class BrainPlanner:
|
||||
f"{self.log_prefix}规划器决定执行{len(actions)}个动作: {' '.join([a.action_type for a in actions])}"
|
||||
)
|
||||
|
||||
return actions
|
||||
return extracted_reasoning, actions
|
||||
|
||||
def _create_no_reply(self, reasoning: str, available_actions: Dict[str, ActionInfo]) -> List[ActionPlannerInfo]:
|
||||
"""创建no_reply"""
|
||||
def _create_complete_talk(
|
||||
self, reasoning: str, available_actions: Dict[str, ActionInfo]
|
||||
) -> List[ActionPlannerInfo]:
|
||||
"""创建complete_talk"""
|
||||
return [
|
||||
ActionPlannerInfo(
|
||||
action_type="no_reply",
|
||||
action_type="complete_talk",
|
||||
reasoning=reasoning,
|
||||
action_data={},
|
||||
action_message=None,
|
||||
@@ -509,33 +569,122 @@ class BrainPlanner:
|
||||
)
|
||||
]
|
||||
|
||||
def _extract_json_from_markdown(self, content: str) -> List[dict]:
|
||||
def add_plan_log(self, reasoning: str, actions: List[ActionPlannerInfo]):
|
||||
"""添加计划日志"""
|
||||
self.plan_log.append((reasoning, time.time(), actions))
|
||||
if len(self.plan_log) > 20:
|
||||
self.plan_log.pop(0)
|
||||
|
||||
def _extract_json_from_markdown(self, content: str) -> Tuple[List[dict], str]:
|
||||
# sourcery skip: for-append-to-extend
|
||||
"""从Markdown格式的内容中提取JSON对象"""
|
||||
"""从Markdown格式的内容中提取JSON对象和推理内容"""
|
||||
json_objects = []
|
||||
reasoning_content = ""
|
||||
|
||||
# 使用正则表达式查找```json包裹的JSON内容
|
||||
json_pattern = r"```json\s*(.*?)\s*```"
|
||||
matches = re.findall(json_pattern, content, re.DOTALL)
|
||||
markdown_matches = re.findall(json_pattern, content, re.DOTALL)
|
||||
|
||||
for match in matches:
|
||||
# 提取JSON之前的内容作为推理文本
|
||||
first_json_pos = len(content)
|
||||
if markdown_matches:
|
||||
# 找到第一个```json的位置
|
||||
first_json_pos = content.find("```json")
|
||||
if first_json_pos > 0:
|
||||
reasoning_content = content[:first_json_pos].strip()
|
||||
# 清理推理内容中的注释标记
|
||||
reasoning_content = re.sub(r"^//\s*", "", reasoning_content, flags=re.MULTILINE)
|
||||
reasoning_content = reasoning_content.strip()
|
||||
|
||||
# 处理```json包裹的JSON
|
||||
for match in markdown_matches:
|
||||
try:
|
||||
# 清理可能的注释和格式问题
|
||||
json_str = re.sub(r"//.*?\n", "\n", match) # 移除单行注释
|
||||
json_str = re.sub(r"/\*.*?\*/", "", json_str, flags=re.DOTALL) # 移除多行注释
|
||||
if json_str := json_str.strip():
|
||||
json_obj = json.loads(repair_json(json_str))
|
||||
if isinstance(json_obj, dict):
|
||||
json_objects.append(json_obj)
|
||||
elif isinstance(json_obj, list):
|
||||
for item in json_obj:
|
||||
if isinstance(item, dict):
|
||||
json_objects.append(item)
|
||||
# 先尝试将整个块作为一个JSON对象或数组（适用于多行JSON）
|
||||
try:
|
||||
json_obj = json.loads(repair_json(json_str))
|
||||
if isinstance(json_obj, dict):
|
||||
json_objects.append(json_obj)
|
||||
elif isinstance(json_obj, list):
|
||||
for item in json_obj:
|
||||
if isinstance(item, dict):
|
||||
json_objects.append(item)
|
||||
except json.JSONDecodeError:
|
||||
# 如果整个块解析失败，尝试按行分割（适用于多个单行JSON对象）
|
||||
lines = [line.strip() for line in json_str.split("\n") if line.strip()]
|
||||
for line in lines:
|
||||
try:
|
||||
# 尝试解析每一行作为独立的JSON对象
|
||||
json_obj = json.loads(repair_json(line))
|
||||
if isinstance(json_obj, dict):
|
||||
json_objects.append(json_obj)
|
||||
elif isinstance(json_obj, list):
|
||||
for item in json_obj:
|
||||
if isinstance(item, dict):
|
||||
json_objects.append(item)
|
||||
except json.JSONDecodeError:
|
||||
# 单行解析失败，继续下一行
|
||||
continue
|
||||
except Exception as e:
|
||||
logger.warning(f"解析JSON块失败: {e}, 块内容: {match[:100]}...")
|
||||
logger.warning(f"{self.log_prefix}解析JSON块失败: {e}, 块内容: {match[:100]}...")
|
||||
continue
|
||||
|
||||
return json_objects
|
||||
# 如果没有找到完整的```json```块，尝试查找不完整的代码块（缺少结尾```）
|
||||
if not json_objects:
|
||||
json_start_pos = content.find("```json")
|
||||
if json_start_pos != -1:
|
||||
# 找到```json之后的内容
|
||||
json_content_start = json_start_pos + 7 # ```json的长度
|
||||
# 提取从```json之后到内容结尾的所有内容
|
||||
incomplete_json_str = content[json_content_start:].strip()
|
||||
|
||||
# 提取JSON之前的内容作为推理文本
|
||||
if json_start_pos > 0:
|
||||
reasoning_content = content[:json_start_pos].strip()
|
||||
reasoning_content = re.sub(r"^//\s*", "", reasoning_content, flags=re.MULTILINE)
|
||||
reasoning_content = reasoning_content.strip()
|
||||
|
||||
if incomplete_json_str:
|
||||
try:
|
||||
# 清理可能的注释和格式问题
|
||||
json_str = re.sub(r"//.*?\n", "\n", incomplete_json_str)
|
||||
json_str = re.sub(r"/\*.*?\*/", "", json_str, flags=re.DOTALL)
|
||||
json_str = json_str.strip()
|
||||
|
||||
if json_str:
|
||||
# 尝试按行分割，每行可能是一个JSON对象
|
||||
lines = [line.strip() for line in json_str.split("\n") if line.strip()]
|
||||
for line in lines:
|
||||
try:
|
||||
json_obj = json.loads(repair_json(line))
|
||||
if isinstance(json_obj, dict):
|
||||
json_objects.append(json_obj)
|
||||
elif isinstance(json_obj, list):
|
||||
for item in json_obj:
|
||||
if isinstance(item, dict):
|
||||
json_objects.append(item)
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
|
||||
# 如果按行解析没有成功，尝试将整个块作为一个JSON对象或数组
|
||||
if not json_objects:
|
||||
try:
|
||||
json_obj = json.loads(repair_json(json_str))
|
||||
if isinstance(json_obj, dict):
|
||||
json_objects.append(json_obj)
|
||||
elif isinstance(json_obj, list):
|
||||
for item in json_obj:
|
||||
if isinstance(item, dict):
|
||||
json_objects.append(item)
|
||||
except Exception as e:
|
||||
logger.debug(f"尝试解析不完整的JSON代码块失败: {e}")
|
||||
except Exception as e:
|
||||
logger.debug(f"处理不完整的JSON代码块时出错: {e}")
|
||||
|
||||
return json_objects, reasoning_content
|
||||
|
||||
|
||||
init_prompt()
|
||||
|
||||
@@ -271,7 +271,7 @@ def _to_emoji_objects(data: Any) -> Tuple[List["MaiEmoji"], int]:
|
||||
|
||||
emoji.description = emoji_data.description
|
||||
# Deserialize emotion string from DB to list
|
||||
emoji.emotion = emoji_data.emotion.split(",") if emoji_data.emotion else []
|
||||
emoji.emotion = emoji_data.emotion.replace("，", ",").split(",") if emoji_data.emotion else []
|
||||
emoji.usage_count = emoji_data.usage_count
|
||||
|
||||
db_last_used_time = emoji_data.last_used_time
|
||||
@@ -732,7 +732,7 @@ class EmojiManager:
|
||||
emoji_record = Emoji.get_or_none(Emoji.emoji_hash == emoji_hash)
|
||||
if emoji_record and emoji_record.emotion:
|
||||
logger.info(f"[缓存命中] 从数据库获取表情包情感标签: {emoji_record.emotion[:50]}...")
|
||||
return emoji_record.emotion.split(",")
|
||||
return emoji_record.emotion.replace("，", ",").split(",")
|
||||
except Exception as e:
|
||||
logger.error(f"从数据库查询表情包情感标签时出错: {e}")
|
||||
|
||||
@@ -993,7 +993,7 @@ class EmojiManager:
|
||||
)
|
||||
|
||||
# 处理情感列表
|
||||
emotions = [e.strip() for e in emotions_text.split(",") if e.strip()]
|
||||
emotions = [e.strip() for e in emotions_text.replace("，", ",").split(",") if e.strip()]
|
||||
|
||||
# 根据情感标签数量随机选择 - 超过5个选3个，超过2个选2个
|
||||
if len(emotions) > 5:
|
||||
|
||||
@@ -1,163 +0,0 @@
|
||||
from datetime import datetime
|
||||
import time
|
||||
import asyncio
|
||||
from typing import Dict
|
||||
|
||||
from src.chat.utils.chat_message_builder import (
|
||||
get_raw_msg_by_timestamp_with_chat,
|
||||
build_readable_messages,
|
||||
)
|
||||
from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
|
||||
from src.config.config import global_config, model_config
|
||||
from src.llm_models.utils_model import LLMRequest
|
||||
from src.common.logger import get_logger
|
||||
from src.plugin_system.apis import frequency_api
|
||||
|
||||
|
||||
def init_prompt():
|
||||
Prompt(
|
||||
"""{name_block}
|
||||
{time_block}
|
||||
你现在正在聊天，请根据下面的聊天记录判断是否有用户觉得你的发言过于频繁或者发言过少
|
||||
{message_str}
|
||||
|
||||
如果用户觉得你的发言过于频繁，请输出"过于频繁"，否则输出"正常"
|
||||
如果用户觉得你的发言过少，请输出"过少"，否则输出"正常"
|
||||
**你只能输出以下三个词之一，不要输出任何其他文字、解释或标点：**
|
||||
- 正常
|
||||
- 过于频繁
|
||||
- 过少
|
||||
""",
|
||||
"frequency_adjust_prompt",
|
||||
)
|
||||
|
||||
|
||||
logger = get_logger("frequency_control")
|
||||
|
||||
|
||||
class FrequencyControl:
|
||||
"""简化的频率控制类，仅管理不同chat_id的频率值"""
|
||||
|
||||
def __init__(self, chat_id: str):
|
||||
self.chat_id = chat_id
|
||||
# 发言频率调整值
|
||||
self.talk_frequency_adjust: float = 1.0
|
||||
|
||||
self.last_frequency_adjust_time: float = 0.0
|
||||
self.frequency_model = LLMRequest(
|
||||
model_set=model_config.model_task_config.utils_small, request_type="frequency.adjust"
|
||||
)
|
||||
# 频率调整锁，防止并发执行
|
||||
self._adjust_lock = asyncio.Lock()
|
||||
|
||||
def get_talk_frequency_adjust(self) -> float:
|
||||
"""获取发言频率调整值"""
|
||||
return self.talk_frequency_adjust
|
||||
|
||||
def set_talk_frequency_adjust(self, value: float) -> None:
|
||||
"""设置发言频率调整值"""
|
||||
self.talk_frequency_adjust = max(0.1, min(5.0, value))
|
||||
|
||||
async def trigger_frequency_adjust(self) -> None:
|
||||
# 使用异步锁防止并发执行
|
||||
async with self._adjust_lock:
|
||||
# 在锁内检查，避免并发触发
|
||||
current_time = time.time()
|
||||
previous_adjust_time = self.last_frequency_adjust_time
|
||||
|
||||
msg_list = get_raw_msg_by_timestamp_with_chat(
|
||||
chat_id=self.chat_id,
|
||||
timestamp_start=previous_adjust_time,
|
||||
timestamp_end=current_time,
|
||||
)
|
||||
|
||||
if current_time - previous_adjust_time < 160 or len(msg_list) <= 20:
|
||||
return
|
||||
|
||||
# 立即更新调整时间，防止并发触发
|
||||
self.last_frequency_adjust_time = current_time
|
||||
|
||||
try:
|
||||
new_msg_list = get_raw_msg_by_timestamp_with_chat(
|
||||
chat_id=self.chat_id,
|
||||
timestamp_start=previous_adjust_time,
|
||||
timestamp_end=current_time,
|
||||
limit=20,
|
||||
limit_mode="latest",
|
||||
)
|
||||
|
||||
message_str = build_readable_messages(
|
||||
new_msg_list,
|
||||
replace_bot_name=True,
|
||||
timestamp_mode="relative",
|
||||
read_mark=0.0,
|
||||
show_actions=False,
|
||||
)
|
||||
time_block = f"当前时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
|
||||
bot_name = global_config.bot.nickname
|
||||
bot_nickname = (
|
||||
f",也有人叫你{','.join(global_config.bot.alias_names)}" if global_config.bot.alias_names else ""
|
||||
)
|
||||
name_block = f"你的名字是{bot_name}{bot_nickname}，请注意哪些是你自己的发言。"
|
||||
|
||||
prompt = await global_prompt_manager.format_prompt(
|
||||
"frequency_adjust_prompt",
|
||||
name_block=name_block,
|
||||
time_block=time_block,
|
||||
message_str=message_str,
|
||||
)
|
||||
response, (reasoning_content, _, _) = await self.frequency_model.generate_response_async(
|
||||
prompt,
|
||||
)
|
||||
|
||||
# logger.info(f"频率调整 prompt: {prompt}")
|
||||
# logger.info(f"频率调整 response: {response}")
|
||||
|
||||
if global_config.debug.show_prompt:
|
||||
logger.info(f"频率调整 prompt: {prompt}")
|
||||
logger.info(f"频率调整 response: {response}")
|
||||
logger.info(f"频率调整 reasoning_content: {reasoning_content}")
|
||||
|
||||
final_value_by_api = frequency_api.get_current_talk_value(self.chat_id)
|
||||
|
||||
# LLM依然输出过多内容时取消本次调整。合法最多4个字，但有的模型可能会输出一些markdown换行符等，需要长度宽限
|
||||
if len(response) < 20:
|
||||
if "过于频繁" in response:
|
||||
logger.info(f"频率调整: 过于频繁，调整值到{final_value_by_api}")
|
||||
self.talk_frequency_adjust = max(0.1, min(1.5, self.talk_frequency_adjust * 0.8))
|
||||
elif "过少" in response:
|
||||
logger.info(f"频率调整: 过少，调整值到{final_value_by_api}")
|
||||
self.talk_frequency_adjust = max(0.1, min(1.5, self.talk_frequency_adjust * 1.2))
|
||||
except Exception as e:
|
||||
logger.error(f"频率调整失败: {e}")
|
||||
# 即使失败也保持时间戳更新，避免频繁重试
|
||||
|
||||
|
||||
class FrequencyControlManager:
|
||||
"""频率控制管理器，管理多个聊天流的频率控制实例"""
|
||||
|
||||
def __init__(self):
|
||||
self.frequency_control_dict: Dict[str, FrequencyControl] = {}
|
||||
|
||||
def get_or_create_frequency_control(self, chat_id: str) -> FrequencyControl:
|
||||
"""获取或创建指定聊天流的频率控制实例"""
|
||||
if chat_id not in self.frequency_control_dict:
|
||||
self.frequency_control_dict[chat_id] = FrequencyControl(chat_id)
|
||||
return self.frequency_control_dict[chat_id]
|
||||
|
||||
def remove_frequency_control(self, chat_id: str) -> bool:
|
||||
"""移除指定聊天流的频率控制实例"""
|
||||
if chat_id in self.frequency_control_dict:
|
||||
del self.frequency_control_dict[chat_id]
|
||||
return True
|
||||
return False
|
||||
|
||||
def get_all_chat_ids(self) -> list[str]:
|
||||
"""获取所有有频率控制的聊天ID"""
|
||||
return list(self.frequency_control_dict.keys())
|
||||
|
||||
|
||||
init_prompt()
|
||||
|
||||
# 创建全局实例
|
||||
frequency_control_manager = FrequencyControlManager()
|
||||
50
src/chat/heart_flow/frequency_control.py
Normal file
50
src/chat/heart_flow/frequency_control.py
Normal file
@@ -0,0 +1,50 @@
|
||||
from typing import Dict
|
||||
|
||||
from src.common.logger import get_logger
|
||||
|
||||
logger = get_logger("frequency_control")
|
||||
|
||||
|
||||
class FrequencyControl:
|
||||
"""简化的频率控制类，仅管理不同chat_id的频率值"""
|
||||
|
||||
def __init__(self, chat_id: str):
|
||||
self.chat_id = chat_id
|
||||
# 发言频率调整值
|
||||
self.talk_frequency_adjust: float = 1.0
|
||||
|
||||
def get_talk_frequency_adjust(self) -> float:
|
||||
"""获取发言频率调整值"""
|
||||
return self.talk_frequency_adjust
|
||||
|
||||
def set_talk_frequency_adjust(self, value: float) -> None:
|
||||
"""设置发言频率调整值"""
|
||||
self.talk_frequency_adjust = max(0.1, min(5.0, value))
|
||||
|
||||
|
||||
class FrequencyControlManager:
|
||||
"""频率控制管理器，管理多个聊天流的频率控制实例"""
|
||||
|
||||
def __init__(self):
|
||||
self.frequency_control_dict: Dict[str, FrequencyControl] = {}
|
||||
|
||||
def get_or_create_frequency_control(self, chat_id: str) -> FrequencyControl:
|
||||
"""获取或创建指定聊天流的频率控制实例"""
|
||||
if chat_id not in self.frequency_control_dict:
|
||||
self.frequency_control_dict[chat_id] = FrequencyControl(chat_id)
|
||||
return self.frequency_control_dict[chat_id]
|
||||
|
||||
def remove_frequency_control(self, chat_id: str) -> bool:
|
||||
"""移除指定聊天流的频率控制实例"""
|
||||
if chat_id in self.frequency_control_dict:
|
||||
del self.frequency_control_dict[chat_id]
|
||||
return True
|
||||
return False
|
||||
|
||||
def get_all_chat_ids(self) -> list[str]:
|
||||
"""获取所有有频率控制的聊天ID"""
|
||||
return list(self.frequency_control_dict.keys())
|
||||
|
||||
|
||||
# 创建全局实例
|
||||
frequency_control_manager = FrequencyControlManager()
|
||||
@@ -16,11 +16,11 @@ from src.chat.planner_actions.planner import ActionPlanner
|
||||
from src.chat.planner_actions.action_modifier import ActionModifier
|
||||
from src.chat.planner_actions.action_manager import ActionManager
|
||||
from src.chat.heart_flow.hfc_utils import CycleDetail
|
||||
from src.express.expression_learner import expression_learner_manager
|
||||
from src.chat.frequency_control.frequency_control import frequency_control_manager
|
||||
from src.express.reflect_tracker import reflect_tracker_manager
|
||||
from src.express.expression_reflector import expression_reflector_manager
|
||||
from src.jargon import extract_and_store_jargon
|
||||
from src.bw_learner.expression_learner import expression_learner_manager
|
||||
from src.chat.heart_flow.frequency_control import frequency_control_manager
|
||||
from src.bw_learner.reflect_tracker import reflect_tracker_manager
|
||||
from src.bw_learner.expression_reflector import expression_reflector_manager
|
||||
from src.bw_learner.message_recorder import extract_and_distribute_messages
|
||||
from src.person_info.person_info import Person
|
||||
from src.plugin_system.base.component_types import EventType, ActionInfo
|
||||
from src.plugin_system.core import events_manager
|
||||
@@ -29,6 +29,7 @@ from src.chat.utils.chat_message_builder import (
|
||||
build_readable_messages_with_id,
|
||||
get_raw_msg_before_timestamp_with_chat,
|
||||
)
|
||||
from src.chat.utils.utils import record_replyer_action_temp
|
||||
from src.hippo_memorizer.chat_history_summarizer import ChatHistorySummarizer
|
||||
|
||||
if TYPE_CHECKING:
|
||||
@@ -99,7 +100,6 @@ class HeartFChatting:
|
||||
self._current_cycle_detail: CycleDetail = None # type: ignore
|
||||
|
||||
self.last_read_time = time.time() - 2
|
||||
self.no_reply_until_call = False
|
||||
|
||||
self.is_mute = False
|
||||
|
||||
@@ -190,7 +190,7 @@ class HeartFChatting:
|
||||
limit_mode="latest",
|
||||
filter_mai=True,
|
||||
filter_command=False,
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=0,
|
||||
)
|
||||
|
||||
# 根据连续 no_reply 次数动态调整阈值
|
||||
@@ -207,23 +207,6 @@ class HeartFChatting:
|
||||
if len(recent_messages_list) >= threshold:
|
||||
# for message in recent_messages_list:
|
||||
# print(message.processed_plain_text)
|
||||
# !处理no_reply_until_call逻辑
|
||||
if self.no_reply_until_call:
|
||||
for message in recent_messages_list:
|
||||
if (
|
||||
message.is_mentioned
|
||||
or message.is_at
|
||||
or len(recent_messages_list) >= 8
|
||||
or time.time() - self.last_read_time > 600
|
||||
):
|
||||
self.no_reply_until_call = False
|
||||
self.last_read_time = time.time()
|
||||
break
|
||||
# 没有提到，继续保持沉默
|
||||
if self.no_reply_until_call:
|
||||
# logger.info(f"{self.log_prefix} 没有提到，继续保持沉默")
|
||||
await asyncio.sleep(1)
|
||||
return True
|
||||
|
||||
self.last_read_time = time.time()
|
||||
|
||||
@@ -303,90 +286,6 @@ class HeartFChatting:
|
||||
|
||||
return loop_info, reply_text, cycle_timers
|
||||
|
||||
async def _run_planner_without_reply(
|
||||
self,
|
||||
available_actions: Dict[str, ActionInfo],
|
||||
cycle_timers: Dict[str, float],
|
||||
) -> List[ActionPlannerInfo]:
|
||||
"""执行planner，但不包含reply动作（用于并行执行场景，提及时使用简化版提示词）"""
|
||||
try:
|
||||
with Timer("规划器", cycle_timers):
|
||||
action_to_use_info = await self.action_planner.plan(
|
||||
loop_start_time=self.last_read_time,
|
||||
available_actions=available_actions,
|
||||
is_mentioned=True, # 标记为提及时，使用简化版提示词
|
||||
)
|
||||
# 过滤掉reply动作（虽然提及时不应该有reply，但为了安全还是过滤一下）
|
||||
return [action for action in action_to_use_info if action.action_type != "reply"]
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} Planner执行失败: {e}")
|
||||
traceback.print_exc()
|
||||
return []
|
||||
|
||||
async def _generate_mentioned_reply(
|
||||
self,
|
||||
force_reply_message: "DatabaseMessages",
|
||||
thinking_id: str,
|
||||
cycle_timers: Dict[str, float],
|
||||
available_actions: Dict[str, ActionInfo],
|
||||
) -> Dict[str, Any]:
|
||||
"""当被提及时，独立生成回复的任务"""
|
||||
try:
|
||||
self.questioned = False
|
||||
# 重置连续 no_reply 计数
|
||||
self.consecutive_no_reply_count = 0
|
||||
reason = ""
|
||||
|
||||
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,
|
||||
)
|
||||
|
||||
with Timer("提及回复生成", cycle_timers):
|
||||
success, llm_response = await generator_api.generate_reply(
|
||||
chat_stream=self.chat_stream,
|
||||
reply_message=force_reply_message,
|
||||
available_actions=available_actions,
|
||||
chosen_actions=[], # 独立回复，不依赖planner的动作
|
||||
reply_reason=reason,
|
||||
enable_tool=global_config.tool.enable_tool,
|
||||
request_type="replyer",
|
||||
from_plugin=False,
|
||||
reply_time_point=self.last_read_time,
|
||||
)
|
||||
|
||||
if not success or not llm_response or not llm_response.reply_set:
|
||||
logger.warning(f"{self.log_prefix} 提及回复生成失败")
|
||||
return {"action_type": "reply", "success": False, "result": "提及回复生成失败", "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(
|
||||
response_set=response_set,
|
||||
action_message=force_reply_message,
|
||||
cycle_timers=cycle_timers,
|
||||
thinking_id=thinking_id,
|
||||
actions=[], # 独立回复，不依赖planner的动作
|
||||
selected_expressions=selected_expressions,
|
||||
)
|
||||
self.last_active_time = time.time()
|
||||
return {
|
||||
"action_type": "reply",
|
||||
"success": True,
|
||||
"result": f"你回复内容{reply_text}",
|
||||
"loop_info": loop_info,
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 提及回复生成异常: {e}")
|
||||
traceback.print_exc()
|
||||
return {"action_type": "reply", "success": False, "result": f"提及回复生成异常: {e}", "loop_info": None}
|
||||
|
||||
async def _observe(
|
||||
self, # interest_value: float = 0.0,
|
||||
recent_messages_list: Optional[List["DatabaseMessages"]] = None,
|
||||
@@ -412,15 +311,12 @@ class HeartFChatting:
|
||||
|
||||
start_time = time.time()
|
||||
async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()):
|
||||
asyncio.create_task(self.expression_learner.trigger_learning_for_chat())
|
||||
asyncio.create_task(
|
||||
frequency_control_manager.get_or_create_frequency_control(self.stream_id).trigger_frequency_adjust()
|
||||
)
|
||||
# 通过 MessageRecorder 统一提取消息并分发给 expression_learner 和 jargon_miner
|
||||
# 在 replyer 执行时触发，统一管理时间窗口，避免重复获取消息
|
||||
asyncio.create_task(extract_and_distribute_messages(self.stream_id))
|
||||
|
||||
# 添加curious检测任务 - 检测聊天记录中的矛盾、冲突或需要提问的内容
|
||||
# asyncio.create_task(check_and_make_question(self.stream_id))
|
||||
# 添加jargon提取任务 - 提取聊天中的黑话/俚语并入库（内部自行取消息并带冷却）
|
||||
asyncio.create_task(extract_and_store_jargon(self.stream_id))
|
||||
# 添加聊天内容概括任务 - 累积、打包和压缩聊天记录
|
||||
# 注意：后台循环已在start()中启动，这里作为额外触发点，在有思考时立即处理
|
||||
# asyncio.create_task(self.chat_history_summarizer.process())
|
||||
@@ -438,95 +334,50 @@ class HeartFChatting:
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 动作修改失败: {e}")
|
||||
|
||||
# 如果被提及，让回复生成和planner并行执行
|
||||
if force_reply_message:
|
||||
logger.info(f"{self.log_prefix} 检测到提及，回复生成与planner并行执行")
|
||||
# 执行planner
|
||||
is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info()
|
||||
|
||||
# 并行执行planner和回复生成
|
||||
planner_task = asyncio.create_task(
|
||||
self._run_planner_without_reply(
|
||||
available_actions=available_actions,
|
||||
cycle_timers=cycle_timers,
|
||||
)
|
||||
message_list_before_now = get_raw_msg_before_timestamp_with_chat(
|
||||
chat_id=self.stream_id,
|
||||
timestamp=time.time(),
|
||||
limit=int(global_config.chat.max_context_size * 0.6),
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
chat_content_block, message_id_list = build_readable_messages_with_id(
|
||||
messages=message_list_before_now,
|
||||
timestamp_mode="normal_no_YMD",
|
||||
read_mark=self.action_planner.last_obs_time_mark,
|
||||
truncate=True,
|
||||
show_actions=True,
|
||||
)
|
||||
|
||||
prompt_info = await self.action_planner.build_planner_prompt(
|
||||
is_group_chat=is_group_chat,
|
||||
chat_target_info=chat_target_info,
|
||||
current_available_actions=available_actions,
|
||||
chat_content_block=chat_content_block,
|
||||
message_id_list=message_id_list,
|
||||
)
|
||||
continue_flag, modified_message = await events_manager.handle_mai_events(
|
||||
EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id
|
||||
)
|
||||
if not continue_flag:
|
||||
return False
|
||||
if modified_message and modified_message._modify_flags.modify_llm_prompt:
|
||||
prompt_info = (modified_message.llm_prompt, prompt_info[1])
|
||||
|
||||
with Timer("规划器", cycle_timers):
|
||||
action_to_use_info = await self.action_planner.plan(
|
||||
loop_start_time=self.last_read_time,
|
||||
available_actions=available_actions,
|
||||
force_reply_message=force_reply_message,
|
||||
)
|
||||
reply_task = asyncio.create_task(
|
||||
self._generate_mentioned_reply(
|
||||
force_reply_message=force_reply_message,
|
||||
thinking_id=thinking_id,
|
||||
cycle_timers=cycle_timers,
|
||||
available_actions=available_actions,
|
||||
)
|
||||
)
|
||||
|
||||
# 等待两个任务完成
|
||||
planner_result, reply_result = await asyncio.gather(planner_task, reply_task, return_exceptions=True)
|
||||
|
||||
# 处理planner结果
|
||||
if isinstance(planner_result, BaseException):
|
||||
logger.error(f"{self.log_prefix} Planner执行异常: {planner_result}")
|
||||
action_to_use_info = []
|
||||
else:
|
||||
action_to_use_info = planner_result
|
||||
|
||||
# 处理回复结果
|
||||
if isinstance(reply_result, BaseException):
|
||||
logger.error(f"{self.log_prefix} 回复生成异常: {reply_result}")
|
||||
reply_result = {
|
||||
"action_type": "reply",
|
||||
"success": False,
|
||||
"result": "回复生成异常",
|
||||
"loop_info": None,
|
||||
}
|
||||
else:
|
||||
# 正常流程：只执行planner
|
||||
is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info()
|
||||
|
||||
message_list_before_now = get_raw_msg_before_timestamp_with_chat(
|
||||
chat_id=self.stream_id,
|
||||
timestamp=time.time(),
|
||||
limit=int(global_config.chat.max_context_size * 0.6),
|
||||
filter_no_read_command=True,
|
||||
)
|
||||
chat_content_block, message_id_list = build_readable_messages_with_id(
|
||||
messages=message_list_before_now,
|
||||
timestamp_mode="normal_no_YMD",
|
||||
read_mark=self.action_planner.last_obs_time_mark,
|
||||
truncate=True,
|
||||
show_actions=True,
|
||||
)
|
||||
|
||||
prompt_info = await self.action_planner.build_planner_prompt(
|
||||
is_group_chat=is_group_chat,
|
||||
chat_target_info=chat_target_info,
|
||||
current_available_actions=available_actions,
|
||||
chat_content_block=chat_content_block,
|
||||
message_id_list=message_id_list,
|
||||
interest=global_config.personality.interest,
|
||||
)
|
||||
continue_flag, modified_message = await events_manager.handle_mai_events(
|
||||
EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id
|
||||
)
|
||||
if not continue_flag:
|
||||
return False
|
||||
if modified_message and modified_message._modify_flags.modify_llm_prompt:
|
||||
prompt_info = (modified_message.llm_prompt, prompt_info[1])
|
||||
|
||||
with Timer("规划器", cycle_timers):
|
||||
action_to_use_info = await self.action_planner.plan(
|
||||
loop_start_time=self.last_read_time,
|
||||
available_actions=available_actions,
|
||||
)
|
||||
reply_result = None
|
||||
|
||||
# 只在提及情况下过滤掉planner返回的reply动作（提及时已有独立回复生成）
|
||||
if force_reply_message:
|
||||
action_to_use_info = [action for action in action_to_use_info if action.action_type != "reply"]
|
||||
|
||||
logger.info(
|
||||
f"{self.log_prefix} 决定执行{len(action_to_use_info)}个动作: {' '.join([a.action_type for a in action_to_use_info])}"
|
||||
)
|
||||
|
||||
# 3. 并行执行所有动作（不包括reply，reply已经独立执行）
|
||||
# 3. 并行执行所有动作
|
||||
action_tasks = [
|
||||
asyncio.create_task(
|
||||
self._execute_action(action, action_to_use_info, thinking_id, available_actions, cycle_timers)
|
||||
@@ -537,10 +388,6 @@ class HeartFChatting:
|
||||
# 并行执行所有任务
|
||||
results = await asyncio.gather(*action_tasks, return_exceptions=True)
|
||||
|
||||
# 如果有独立的回复结果，添加到结果列表中
|
||||
if reply_result:
|
||||
results = list(results) + [reply_result]
|
||||
|
||||
# 处理执行结果
|
||||
reply_loop_info = None
|
||||
reply_text_from_reply = ""
|
||||
@@ -751,31 +598,6 @@ class HeartFChatting:
|
||||
|
||||
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
|
||||
logger.info(f"{self.log_prefix} 保持沉默，直到有人直接叫的名字")
|
||||
reason = action_planner_info.reasoning or "选择不回复"
|
||||
|
||||
# 增加连续 no_reply 计数
|
||||
self.consecutive_no_reply_count += 1
|
||||
self.no_reply_until_call = True
|
||||
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="no_reply_until_call",
|
||||
action_reasoning=reason,
|
||||
)
|
||||
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
|
||||
self.questioned = False
|
||||
@@ -784,8 +606,27 @@ class HeartFChatting:
|
||||
self.consecutive_no_reply_count = 0
|
||||
|
||||
reason = action_planner_info.reasoning or ""
|
||||
# 根据 think_mode 配置决定 think_level 的值
|
||||
think_mode = global_config.chat.think_mode
|
||||
if think_mode == "default":
|
||||
think_level = 0
|
||||
elif think_mode == "deep":
|
||||
think_level = 1
|
||||
elif think_mode == "dynamic":
|
||||
# dynamic 模式：从 planner 返回的 action_data 中获取
|
||||
think_level = action_planner_info.action_data.get("think_level", 1)
|
||||
else:
|
||||
# 默认使用 default 模式
|
||||
think_level = 0
|
||||
# 使用 action_reasoning（planner 的整体思考理由）作为 reply_reason
|
||||
planner_reasoning = action_planner_info.action_reasoning or reason
|
||||
|
||||
record_replyer_action_temp(
|
||||
chat_id=self.stream_id,
|
||||
reason=reason,
|
||||
think_level=think_level,
|
||||
)
|
||||
|
||||
await database_api.store_action_info(
|
||||
chat_stream=self.chat_stream,
|
||||
action_build_into_prompt=False,
|
||||
@@ -807,6 +648,7 @@ class HeartFChatting:
|
||||
request_type="replyer",
|
||||
from_plugin=False,
|
||||
reply_time_point=action_planner_info.action_data.get("loop_start_time", time.time()),
|
||||
think_level=think_level,
|
||||
)
|
||||
|
||||
if not success or not llm_response or not llm_response.reply_set:
|
||||
|
||||
@@ -7,7 +7,6 @@ from maim_message import UserInfo, Seg, GroupInfo
|
||||
|
||||
from src.common.logger import get_logger
|
||||
from src.config.config import global_config
|
||||
from src.mood.mood_manager import mood_manager # 导入情绪管理器
|
||||
from src.chat.message_receive.chat_stream import get_chat_manager
|
||||
from src.chat.message_receive.message import MessageRecv
|
||||
from src.chat.message_receive.storage import MessageStorage
|
||||
@@ -73,7 +72,6 @@ class ChatBot:
|
||||
def __init__(self):
|
||||
self.bot = None # bot 实例引用
|
||||
self._started = False
|
||||
self.mood_manager = mood_manager # 获取情绪管理器单例
|
||||
self.heartflow_message_receiver = HeartFCMessageReceiver() # 新增
|
||||
|
||||
async def _ensure_started(self):
|
||||
@@ -83,7 +81,7 @@ class ChatBot:
|
||||
|
||||
self._started = True
|
||||
|
||||
async def _process_commands_with_new_system(self, message: MessageRecv):
|
||||
async def _process_commands(self, message: MessageRecv):
|
||||
# sourcery skip: use-named-expression
|
||||
"""使用新插件系统处理命令"""
|
||||
try:
|
||||
@@ -115,17 +113,21 @@ class ChatBot:
|
||||
|
||||
try:
|
||||
# 执行命令
|
||||
success, response, intercept_message = await command_instance.execute()
|
||||
message.is_no_read_command = bool(intercept_message)
|
||||
success, response, intercept_message_level = await command_instance.execute()
|
||||
message.intercept_message_level = intercept_message_level
|
||||
|
||||
# 记录命令执行结果
|
||||
if success:
|
||||
logger.info(f"命令执行成功: {command_class.__name__} (拦截: {intercept_message})")
|
||||
logger.info(f"命令执行成功: {command_class.__name__} (拦截等级: {intercept_message_level})")
|
||||
else:
|
||||
logger.warning(f"命令执行失败: {command_class.__name__} - {response}")
|
||||
|
||||
# 根据命令的拦截设置决定是否继续处理消息
|
||||
return True, response, not intercept_message # 找到命令，根据intercept_message决定是否继续
|
||||
return (
|
||||
True,
|
||||
response,
|
||||
not bool(intercept_message_level),
|
||||
) # 找到命令，根据intercept_message决定是否继续
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"执行命令时出错: {command_class.__name__} - {e}")
|
||||
@@ -295,7 +297,7 @@ class ChatBot:
|
||||
# return
|
||||
|
||||
# 命令处理 - 使用新插件系统检查并处理命令
|
||||
is_command, cmd_result, continue_process = await self._process_commands_with_new_system(message)
|
||||
is_command, cmd_result, continue_process = await self._process_commands(message)
|
||||
|
||||
# 如果是命令且不需要继续处理，则直接返回
|
||||
if is_command and not continue_process:
|
||||
|
||||
@@ -122,7 +122,7 @@ class MessageRecv(Message):
|
||||
self.is_notify = False
|
||||
|
||||
self.is_command = False
|
||||
self.is_no_read_command = False
|
||||
self.intercept_message_level = 0
|
||||
|
||||
self.priority_mode = "interest"
|
||||
self.priority_info = None
|
||||
@@ -213,6 +213,68 @@ class MessageRecv(Message):
|
||||
}
|
||||
"""
|
||||
return ""
|
||||
elif segment.type == "video_card":
|
||||
# 处理视频卡片消息
|
||||
self.is_picid = False
|
||||
self.is_emoji = False
|
||||
self.is_voice = False
|
||||
if isinstance(segment.data, dict):
|
||||
file_name = segment.data.get("file", "未知视频")
|
||||
file_size = segment.data.get("file_size", "")
|
||||
url = segment.data.get("url", "")
|
||||
text = f"[视频: {file_name}"
|
||||
if file_size:
|
||||
text += f", 大小: {file_size}字节"
|
||||
text += "]"
|
||||
if url:
|
||||
text += f" 链接: {url}"
|
||||
return text
|
||||
return "[视频]"
|
||||
elif segment.type == "music_card":
|
||||
# 处理音乐卡片消息
|
||||
self.is_picid = False
|
||||
self.is_emoji = False
|
||||
self.is_voice = False
|
||||
if isinstance(segment.data, dict):
|
||||
title = segment.data.get("title", "未知歌曲")
|
||||
singer = segment.data.get("singer", "")
|
||||
tag = segment.data.get("tag", "") # 音乐来源，如"网易云音乐"
|
||||
jump_url = segment.data.get("jump_url", "")
|
||||
music_url = segment.data.get("music_url", "")
|
||||
text = f"[音乐: {title}"
|
||||
if singer:
|
||||
text += f" - {singer}"
|
||||
if tag:
|
||||
text += f" ({tag})"
|
||||
text += "]"
|
||||
if jump_url:
|
||||
text += f" 跳转链接: {jump_url}"
|
||||
if music_url:
|
||||
text += f" 音乐链接: {music_url}"
|
||||
return text
|
||||
return "[音乐]"
|
||||
elif segment.type == "miniapp_card":
|
||||
# 处理小程序分享卡片（如B站视频分享）
|
||||
self.is_picid = False
|
||||
self.is_emoji = False
|
||||
self.is_voice = False
|
||||
if isinstance(segment.data, dict):
|
||||
title = segment.data.get("title", "") # 小程序名称
|
||||
desc = segment.data.get("desc", "") # 内容描述
|
||||
source_url = segment.data.get("source_url", "") # 原始链接
|
||||
url = segment.data.get("url", "") # 小程序链接
|
||||
text = "[小程序分享"
|
||||
if title:
|
||||
text += f" - {title}"
|
||||
text += "]"
|
||||
if desc:
|
||||
text += f" {desc}"
|
||||
if source_url:
|
||||
text += f" 链接: {source_url}"
|
||||
elif url:
|
||||
text += f" 链接: {url}"
|
||||
return text
|
||||
return "[小程序分享]"
|
||||
else:
|
||||
return ""
|
||||
except Exception as e:
|
||||
|
||||
@@ -72,7 +72,7 @@ class MessageStorage:
|
||||
key_words = ""
|
||||
key_words_lite = ""
|
||||
selected_expressions = message.selected_expressions
|
||||
is_no_read_command = False
|
||||
intercept_message_level = 0
|
||||
else:
|
||||
filtered_display_message = ""
|
||||
interest_value = message.interest_value
|
||||
@@ -86,7 +86,7 @@ class MessageStorage:
|
||||
is_picid = message.is_picid
|
||||
is_notify = message.is_notify
|
||||
is_command = message.is_command
|
||||
is_no_read_command = getattr(message, "is_no_read_command", False)
|
||||
intercept_message_level = getattr(message, "intercept_message_level", 0)
|
||||
# 序列化关键词列表为JSON字符串
|
||||
key_words = MessageStorage._serialize_keywords(message.key_words)
|
||||
key_words_lite = MessageStorage._serialize_keywords(message.key_words_lite)
|
||||
@@ -138,7 +138,7 @@ class MessageStorage:
|
||||
is_picid=is_picid,
|
||||
is_notify=is_notify,
|
||||
is_command=is_command,
|
||||
is_no_read_command=is_no_read_command,
|
||||
intercept_message_level=intercept_message_level,
|
||||
key_words=key_words,
|
||||
key_words_lite=key_words_lite,
|
||||
selected_expressions=selected_expressions,
|
||||
|
||||
@@ -40,6 +40,93 @@ def is_webui_virtual_group(group_id: str) -> bool:
|
||||
return group_id and group_id.startswith(VIRTUAL_GROUP_ID_PREFIX)
|
||||
|
||||
|
||||
def parse_message_segments(segment) -> list:
|
||||
"""解析消息段，转换为 WebUI 可用的格式
|
||||
|
||||
参考 NapCat 适配器的消息解析逻辑
|
||||
|
||||
Args:
|
||||
segment: Seg 消息段对象
|
||||
|
||||
Returns:
|
||||
list: 消息段列表，每个元素为 {"type": "...", "data": ...}
|
||||
"""
|
||||
|
||||
result = []
|
||||
|
||||
if segment is None:
|
||||
return result
|
||||
|
||||
if segment.type == "seglist":
|
||||
# 处理消息段列表
|
||||
if segment.data:
|
||||
for seg in segment.data:
|
||||
result.extend(parse_message_segments(seg))
|
||||
elif segment.type == "text":
|
||||
# 文本消息
|
||||
if segment.data:
|
||||
result.append({"type": "text", "data": segment.data})
|
||||
elif segment.type == "image":
|
||||
# 图片消息（base64）
|
||||
if segment.data:
|
||||
result.append({"type": "image", "data": f"data:image/png;base64,{segment.data}"})
|
||||
elif segment.type == "emoji":
|
||||
# 表情包消息（base64）
|
||||
if segment.data:
|
||||
result.append({"type": "emoji", "data": f"data:image/gif;base64,{segment.data}"})
|
||||
elif segment.type == "imageurl":
|
||||
# 图片链接消息
|
||||
if segment.data:
|
||||
result.append({"type": "image", "data": segment.data})
|
||||
elif segment.type == "face":
|
||||
# 原生表情
|
||||
result.append({"type": "face", "data": segment.data})
|
||||
elif segment.type == "voice":
|
||||
# 语音消息（base64）
|
||||
if segment.data:
|
||||
result.append({"type": "voice", "data": f"data:audio/wav;base64,{segment.data}"})
|
||||
elif segment.type == "voiceurl":
|
||||
# 语音链接
|
||||
if segment.data:
|
||||
result.append({"type": "voice", "data": segment.data})
|
||||
elif segment.type == "video":
|
||||
# 视频消息（base64）
|
||||
if segment.data:
|
||||
result.append({"type": "video", "data": f"data:video/mp4;base64,{segment.data}"})
|
||||
elif segment.type == "videourl":
|
||||
# 视频链接
|
||||
if segment.data:
|
||||
result.append({"type": "video", "data": segment.data})
|
||||
elif segment.type == "music":
|
||||
# 音乐消息
|
||||
result.append({"type": "music", "data": segment.data})
|
||||
elif segment.type == "file":
|
||||
# 文件消息
|
||||
result.append({"type": "file", "data": segment.data})
|
||||
elif segment.type == "reply":
|
||||
# 回复消息
|
||||
result.append({"type": "reply", "data": segment.data})
|
||||
elif segment.type == "forward":
|
||||
# 转发消息
|
||||
forward_items = []
|
||||
if segment.data:
|
||||
for item in segment.data:
|
||||
forward_items.append(
|
||||
{
|
||||
"content": parse_message_segments(item.get("message_segment", {}))
|
||||
if isinstance(item, dict)
|
||||
else []
|
||||
}
|
||||
)
|
||||
result.append({"type": "forward", "data": forward_items})
|
||||
else:
|
||||
# 未知类型，尝试作为文本处理
|
||||
if segment.data:
|
||||
result.append({"type": "unknown", "original_type": segment.type, "data": str(segment.data)})
|
||||
|
||||
return result
|
||||
|
||||
|
||||
async def _send_message(message: MessageSending, show_log=True) -> bool:
|
||||
"""合并后的消息发送函数，包含WS发送和日志记录"""
|
||||
message_preview = truncate_message(message.processed_plain_text, max_length=200)
|
||||
@@ -50,17 +137,31 @@ async def _send_message(message: MessageSending, show_log=True) -> bool:
|
||||
# 检查是否是 WebUI 平台的消息，或者是 WebUI 虚拟群的消息
|
||||
chat_manager, webui_platform = get_webui_chat_broadcaster()
|
||||
is_webui_message = (platform == webui_platform) or is_webui_virtual_group(group_id)
|
||||
|
||||
|
||||
if is_webui_message and chat_manager is not None:
|
||||
# WebUI 聊天室消息（包括虚拟身份模式），通过 WebSocket 广播
|
||||
import time
|
||||
from src.config.config import global_config
|
||||
|
||||
# 解析消息段，获取富文本内容
|
||||
message_segments = parse_message_segments(message.message_segment)
|
||||
|
||||
# 判断消息类型
|
||||
# 如果只有一个文本段，使用简单的 text 类型
|
||||
# 否则使用 rich 类型，包含完整的消息段
|
||||
if len(message_segments) == 1 and message_segments[0].get("type") == "text":
|
||||
message_type = "text"
|
||||
segments = None
|
||||
else:
|
||||
message_type = "rich"
|
||||
segments = message_segments
|
||||
|
||||
await chat_manager.broadcast(
|
||||
{
|
||||
"type": "bot_message",
|
||||
"content": message.processed_plain_text,
|
||||
"message_type": "text",
|
||||
"message_type": message_type,
|
||||
"segments": segments, # 富文本消息段
|
||||
"timestamp": time.time(),
|
||||
"group_id": group_id, # 包含群 ID 以便前端区分不同的聊天标签
|
||||
"sender": {
|
||||
@@ -81,11 +182,70 @@ async def _send_message(message: MessageSending, show_log=True) -> bool:
|
||||
logger.info(f"已将消息 '{message_preview}' 发往 WebUI 聊天室")
|
||||
return True
|
||||
|
||||
# 直接调用API发送消息
|
||||
await get_global_api().send_message(message)
|
||||
if show_log:
|
||||
logger.info(f"已将消息 '{message_preview}' 发往平台'{message.message_info.platform}'")
|
||||
return True
|
||||
# Fallback 逻辑: 尝试通过 API Server 发送
|
||||
async def send_with_new_api(legacy_exception=None):
|
||||
try:
|
||||
from src.config.config import global_config
|
||||
|
||||
# 如果未开启 API Server，直接跳过 Fallback
|
||||
if not global_config.maim_message.enable_api_server:
|
||||
if legacy_exception:
|
||||
raise legacy_exception
|
||||
return False
|
||||
|
||||
global_api = get_global_api()
|
||||
extra_server = getattr(global_api, "extra_server", None)
|
||||
|
||||
if extra_server and extra_server.is_running():
|
||||
# Fallback: 使用极其简单的 Platform -> API Key 映射
|
||||
# 只有收到过该平台的消息，我们才知道该平台的 API Key，才能回传消息
|
||||
platform_map = getattr(global_api, "platform_map", {})
|
||||
target_api_key = platform_map.get(platform)
|
||||
|
||||
if target_api_key:
|
||||
# 构造 APIMessageBase
|
||||
from maim_message.message import APIMessageBase, MessageDim
|
||||
|
||||
msg_dim = MessageDim(api_key=target_api_key, platform=platform)
|
||||
|
||||
api_message = APIMessageBase(
|
||||
message_info=message.message_info,
|
||||
message_segment=message.message_segment,
|
||||
message_dim=msg_dim,
|
||||
)
|
||||
|
||||
# 直接调用 Server 的 send_message 接口，它会自动处理路由
|
||||
results = await extra_server.send_message(api_message)
|
||||
|
||||
# 检查是否有任何连接发送成功
|
||||
if any(results.values()):
|
||||
if show_log:
|
||||
logger.info(
|
||||
f"已通过API Server Fallback将消息 '{message_preview}' 发往平台'{platform}' (key: {target_api_key})"
|
||||
)
|
||||
return True
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# 如果 Fallback 失败，且存在 legacy 异常，则抛出 legacy 异常
|
||||
if legacy_exception:
|
||||
raise legacy_exception
|
||||
return False
|
||||
|
||||
try:
|
||||
send_result = await get_global_api().send_message(message)
|
||||
# if send_result:
|
||||
if show_log:
|
||||
logger.info(f"已将消息 '{message_preview}' 发往平台'{message.message_info.platform}'")
|
||||
return True
|
||||
|
||||
# Legacy API 返回 False (发送失败但未报错)，尝试 Fallback
|
||||
# return await send_with_new_api()
|
||||
|
||||
except Exception as legacy_e:
|
||||
# Legacy API 抛出异常，尝试 Fallback
|
||||
# 如果 Fallback 也失败，将重新抛出 legacy_e
|
||||
return await send_with_new_api(legacy_exception=legacy_e)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"发送消息 '{message_preview}' 发往平台'{message.message_info.platform}' 失败: {str(e)}")
|
||||
|
||||
@@ -69,7 +69,7 @@ class ActionModifier:
|
||||
chat_id=self.chat_stream.stream_id,
|
||||
timestamp=time.time(),
|
||||
limit=min(int(global_config.chat.max_context_size * 0.33), 10),
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
|
||||
chat_content = build_readable_messages(
|
||||
|
||||
@@ -15,12 +15,15 @@ from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
|
||||
from src.chat.utils.chat_message_builder import (
|
||||
build_readable_messages_with_id,
|
||||
get_raw_msg_before_timestamp_with_chat,
|
||||
replace_user_references,
|
||||
)
|
||||
from src.chat.utils.utils import get_chat_type_and_target_info
|
||||
from src.chat.planner_actions.action_manager import ActionManager
|
||||
from src.chat.message_receive.chat_stream import get_chat_manager
|
||||
from src.plugin_system.base.component_types import ActionInfo, ComponentType, ActionActivationType
|
||||
from src.plugin_system.core.component_registry import component_registry
|
||||
from src.plugin_system.apis.message_api import translate_pid_to_description
|
||||
from src.person_info.person_info import Person
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from src.common.data_models.info_data_model import TargetPersonInfo
|
||||
@@ -36,7 +39,6 @@ def init_prompt():
|
||||
"""
|
||||
{time_block}
|
||||
{name_block}
|
||||
你的兴趣是：{interest}
|
||||
{chat_context_description}，以下是具体的聊天内容
|
||||
**聊天内容**
|
||||
{chat_content_block}
|
||||
@@ -46,9 +48,10 @@ reply
|
||||
动作描述：
|
||||
1.你可以选择呼叫了你的名字，但是你没有做出回应的消息进行回复
|
||||
2.你可以自然的顺着正在进行的聊天内容进行回复或自然的提出一个问题
|
||||
3.不要回复你自己发送的消息
|
||||
4.不要单独对表情包进行回复
|
||||
{{"action":"reply", "target_message_id":"消息id(m+数字)", "reason":"原因"}}
|
||||
3.最好一次对一个话题进行回复，免得啰嗦或者回复内容太乱。
|
||||
4.不要选择回复你自己发送的消息
|
||||
5.不要单独对表情包进行回复
|
||||
{reply_action_example}
|
||||
|
||||
no_reply
|
||||
动作描述：
|
||||
@@ -56,75 +59,37 @@ no_reply
|
||||
控制聊天频率，不要太过频繁的发言
|
||||
{{"action":"no_reply"}}
|
||||
|
||||
{no_reply_until_call_block}
|
||||
|
||||
{action_options_text}
|
||||
|
||||
|
||||
**你之前的action执行和思考记录**
|
||||
{actions_before_now_block}
|
||||
|
||||
请选择**可选的**且符合使用条件的action，并说明触发action的消息id(消息id格式:m+数字)
|
||||
不要回复你自己发送的消息
|
||||
先输出你的简短的选择思考理由，再输出你选择的action，理由不要分点，精简。
|
||||
**动作选择要求**
|
||||
请你根据聊天内容,用户的最新消息和以下标准选择合适的动作:
|
||||
{plan_style}
|
||||
{moderation_prompt}
|
||||
|
||||
请选择所有符合使用要求的action，动作用json格式输出，用```json包裹，如果输出多个json，每个json都要单独一行放在同一个```json代码块内，你可以重复使用同一个动作或不同动作:
|
||||
target_message_id为必填，表示触发消息的id
|
||||
请选择所有符合使用要求的action，每个动作最多选择一次，但是可以选择多个动作；
|
||||
动作用json格式输出，用```json包裹，如果输出多个json，每个json都要单独一行放在同一个```json代码块内:
|
||||
**示例**
|
||||
// 理由文本（简短）
|
||||
```json
|
||||
{{"action":"动作名", "target_message_id":"m123", "reason":"原因"}}
|
||||
{{"action":"动作名", "target_message_id":"m456", "reason":"原因"}}
|
||||
{{"action":"动作名", "target_message_id":"m123", .....}}
|
||||
{{"action":"动作名", "target_message_id":"m456", .....}}
|
||||
```""",
|
||||
"planner_prompt",
|
||||
)
|
||||
|
||||
Prompt(
|
||||
"""{time_block}
|
||||
{name_block}
|
||||
{chat_context_description}，以下是具体的聊天内容
|
||||
**聊天内容**
|
||||
{chat_content_block}
|
||||
|
||||
**可选的action**
|
||||
no_reply
|
||||
动作描述：
|
||||
没有合适的可以使用的动作，不使用action
|
||||
{{"action":"no_reply"}}
|
||||
|
||||
{action_options_text}
|
||||
|
||||
**你之前的action执行和思考记录**
|
||||
{actions_before_now_block}
|
||||
|
||||
请选择**可选的**且符合使用条件的action，并说明触发action的消息id(消息id格式:m+数字)
|
||||
先输出你的简短的选择思考理由，再输出你选择的action，理由不要分点，精简。
|
||||
**动作选择要求**
|
||||
请你根据聊天内容,用户的最新消息和以下标准选择合适的动作:
|
||||
1.思考**所有**的可用的action中的**每个动作**是否符合当下条件，如果动作使用条件符合聊天内容就使用
|
||||
2.如果相同的内容已经被执行，请不要重复执行
|
||||
{moderation_prompt}
|
||||
|
||||
请选择所有符合使用要求的action，动作用json格式输出，用```json包裹，如果输出多个json，每个json都要单独一行放在同一个```json代码块内，你可以重复使用同一个动作或不同动作:
|
||||
**示例**
|
||||
// 理由文本（简短）
|
||||
```json
|
||||
{{"action":"动作名", "target_message_id":"m123", "reason":"原因"}}
|
||||
{{"action":"动作名", "target_message_id":"m456", "reason":"原因"}}
|
||||
```""",
|
||||
"planner_prompt_mentioned",
|
||||
)
|
||||
|
||||
Prompt(
|
||||
"""
|
||||
{action_name}
|
||||
动作描述：{action_description}
|
||||
使用条件{parallel_text}：
|
||||
{action_require}
|
||||
{{"action":"{action_name}",{action_parameters}, "target_message_id":"消息id(m+数字)", "reason":"原因"}}
|
||||
{{"action":"{action_name}",{action_parameters}, "target_message_id":"消息id(m+数字)"}}
|
||||
""",
|
||||
"action_prompt",
|
||||
)
|
||||
@@ -195,11 +160,41 @@ class ActionPlanner:
|
||||
logger.warning(f"{self.log_prefix}planner理由引用 {msg_id} 未找到对应消息，保持原样")
|
||||
return msg_id
|
||||
|
||||
msg_text = (message.processed_plain_text or message.display_message or "").strip()
|
||||
msg_text = (message.processed_plain_text or "").strip()
|
||||
if not msg_text:
|
||||
logger.warning(f"{self.log_prefix}planner理由引用 {msg_id} 的消息内容为空，保持原样")
|
||||
return msg_id
|
||||
|
||||
# 替换 [picid:xxx] 为 [图片：描述]
|
||||
pic_pattern = r"\[picid:([^\]]+)\]"
|
||||
def replace_pic_id(pic_match: re.Match) -> str:
|
||||
pic_id = pic_match.group(1)
|
||||
description = translate_pid_to_description(pic_id)
|
||||
return f"[图片：{description}]"
|
||||
msg_text = re.sub(pic_pattern, replace_pic_id, msg_text)
|
||||
|
||||
# 替换用户引用格式：回复<aaa:bbb> 和 @<aaa:bbb>
|
||||
platform = getattr(message, "user_info", None) and message.user_info.platform or getattr(message, "chat_info", None) and message.chat_info.platform or "qq"
|
||||
msg_text = replace_user_references(msg_text, platform, replace_bot_name=True)
|
||||
|
||||
# 替换单独的 <用户名:用户ID> 格式（replace_user_references 已处理回复<和@<格式）
|
||||
# 匹配所有 <aaa:bbb> 格式，由于 replace_user_references 已经替换了回复<和@<格式，
|
||||
# 这里匹配到的应该都是单独的格式
|
||||
user_ref_pattern = r"<([^:<>]+):([^:<>]+)>"
|
||||
def replace_user_ref(user_match: re.Match) -> str:
|
||||
user_name = user_match.group(1)
|
||||
user_id = user_match.group(2)
|
||||
try:
|
||||
# 检查是否是机器人自己
|
||||
if user_id == global_config.bot.qq_account:
|
||||
return f"{global_config.bot.nickname}(你)"
|
||||
person = Person(platform=platform, user_id=user_id)
|
||||
return person.person_name or user_name
|
||||
except Exception:
|
||||
# 如果解析失败，使用原始昵称
|
||||
return user_name
|
||||
msg_text = re.sub(user_ref_pattern, replace_user_ref, msg_text)
|
||||
|
||||
preview = msg_text if len(msg_text) <= 100 else f"{msg_text[:97]}..."
|
||||
logger.info(f"{self.log_prefix}planner理由引用 {msg_id} -> 消息（{preview}）")
|
||||
return f"消息（{msg_text}）"
|
||||
@@ -218,11 +213,14 @@ class ActionPlanner:
|
||||
|
||||
try:
|
||||
action = action_json.get("action", "no_reply")
|
||||
original_reasoning = action_json.get("reason", "未提供原因")
|
||||
reasoning = self._replace_message_ids_with_text(original_reasoning, message_id_list)
|
||||
if reasoning is None:
|
||||
reasoning = original_reasoning
|
||||
action_data = {key: value for key, value in action_json.items() if key not in ["action", "reason"]}
|
||||
# 使用 extracted_reasoning（整体推理文本）作为 reasoning
|
||||
if extracted_reasoning:
|
||||
reasoning = self._replace_message_ids_with_text(extracted_reasoning, message_id_list)
|
||||
if reasoning is None:
|
||||
reasoning = extracted_reasoning
|
||||
else:
|
||||
reasoning = "未提供原因"
|
||||
action_data = {key: value for key, value in action_json.items() if key not in ["action"]}
|
||||
# 非no_reply动作需要target_message_id
|
||||
target_message = None
|
||||
|
||||
@@ -248,7 +246,7 @@ class ActionPlanner:
|
||||
|
||||
# 验证action是否可用
|
||||
available_action_names = [action_name for action_name, _ in current_available_actions]
|
||||
internal_action_names = ["no_reply", "reply", "wait_time", "no_reply_until_call"]
|
||||
internal_action_names = ["no_reply", "reply", "wait_time"]
|
||||
|
||||
if action not in internal_action_names and action not in available_action_names:
|
||||
logger.warning(
|
||||
@@ -304,7 +302,7 @@ class ActionPlanner:
|
||||
self,
|
||||
available_actions: Dict[str, ActionInfo],
|
||||
loop_start_time: float = 0.0,
|
||||
is_mentioned: bool = False,
|
||||
force_reply_message: Optional["DatabaseMessages"] = None,
|
||||
) -> List[ActionPlannerInfo]:
|
||||
# sourcery skip: use-named-expression
|
||||
"""
|
||||
@@ -316,7 +314,7 @@ class ActionPlanner:
|
||||
chat_id=self.chat_id,
|
||||
timestamp=time.time(),
|
||||
limit=int(global_config.chat.max_context_size * 0.6),
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
message_id_list: list[Tuple[str, "DatabaseMessages"]] = []
|
||||
chat_content_block, message_id_list = build_readable_messages_with_id(
|
||||
@@ -345,11 +343,6 @@ class ActionPlanner:
|
||||
|
||||
logger.debug(f"{self.log_prefix}过滤后有{len(filtered_actions)}个可用动作")
|
||||
|
||||
# 如果是提及时且没有可用动作，直接返回空列表，不调用LLM以节省token
|
||||
if is_mentioned and not filtered_actions:
|
||||
logger.info(f"{self.log_prefix}提及时没有可用动作，跳过plan调用")
|
||||
return []
|
||||
|
||||
# 构建包含所有动作的提示词
|
||||
prompt, message_id_list = await self.build_planner_prompt(
|
||||
is_group_chat=is_group_chat,
|
||||
@@ -357,8 +350,6 @@ class ActionPlanner:
|
||||
current_available_actions=filtered_actions,
|
||||
chat_content_block=chat_content_block,
|
||||
message_id_list=message_id_list,
|
||||
interest=global_config.personality.interest,
|
||||
is_mentioned=is_mentioned,
|
||||
)
|
||||
|
||||
# 调用LLM获取决策
|
||||
@@ -370,6 +361,34 @@ class ActionPlanner:
|
||||
loop_start_time=loop_start_time,
|
||||
)
|
||||
|
||||
# 如果有强制回复消息，确保回复该消息
|
||||
if force_reply_message:
|
||||
# 检查是否已经有回复该消息的 action
|
||||
has_reply_to_force_message = False
|
||||
for action in actions:
|
||||
if action.action_type == "reply" and action.action_message and action.action_message.message_id == force_reply_message.message_id:
|
||||
has_reply_to_force_message = True
|
||||
break
|
||||
|
||||
# 如果没有回复该消息，强制添加回复 action
|
||||
if not has_reply_to_force_message:
|
||||
# 移除所有 no_reply action（如果有）
|
||||
actions = [a for a in actions if a.action_type != "no_reply"]
|
||||
|
||||
# 创建强制回复 action
|
||||
available_actions_dict = dict(current_available_actions)
|
||||
force_reply_action = ActionPlannerInfo(
|
||||
action_type="reply",
|
||||
reasoning="用户提及了我，必须回复该消息",
|
||||
action_data={"loop_start_time": loop_start_time},
|
||||
action_message=force_reply_message,
|
||||
available_actions=available_actions_dict,
|
||||
action_reasoning=None,
|
||||
)
|
||||
# 将强制回复 action 放在最前面
|
||||
actions.insert(0, force_reply_action)
|
||||
logger.info(f"{self.log_prefix} 检测到强制回复消息，已添加回复动作")
|
||||
|
||||
logger.info(
|
||||
f"{self.log_prefix}Planner:{reasoning}。选择了{len(actions)}个动作: {' '.join([a.action_type for a in actions])}"
|
||||
)
|
||||
@@ -430,32 +449,6 @@ class ActionPlanner:
|
||||
|
||||
return plan_log_str
|
||||
|
||||
def _has_consecutive_no_reply(self, min_count: int = 3) -> bool:
|
||||
"""
|
||||
检查是否有连续min_count次以上的no_reply
|
||||
|
||||
Args:
|
||||
min_count: 需要连续的最少次数，默认3
|
||||
|
||||
Returns:
|
||||
如果有连续min_count次以上no_reply返回True，否则返回False
|
||||
"""
|
||||
consecutive_count = 0
|
||||
|
||||
# 从后往前遍历plan_log，检查最新的连续记录
|
||||
for _reasoning, _timestamp, content in reversed(self.plan_log):
|
||||
if isinstance(content, list) and all(isinstance(action, ActionPlannerInfo) for action in content):
|
||||
# 检查所有action是否都是no_reply
|
||||
if all(action.action_type == "no_reply" for action in content):
|
||||
consecutive_count += 1
|
||||
if consecutive_count >= min_count:
|
||||
return True
|
||||
else:
|
||||
# 如果遇到非no_reply的action，重置计数
|
||||
break
|
||||
|
||||
return False
|
||||
|
||||
async def build_planner_prompt(
|
||||
self,
|
||||
is_group_chat: bool,
|
||||
@@ -464,7 +457,6 @@ class ActionPlanner:
|
||||
message_id_list: List[Tuple[str, "DatabaseMessages"]],
|
||||
chat_content_block: str = "",
|
||||
interest: str = "",
|
||||
is_mentioned: bool = False,
|
||||
) -> tuple[str, List[Tuple[str, "DatabaseMessages"]]]:
|
||||
"""构建 Planner LLM 的提示词 (获取模板并填充数据)"""
|
||||
try:
|
||||
@@ -485,47 +477,25 @@ class ActionPlanner:
|
||||
)
|
||||
name_block = f"你的名字是{bot_name}{bot_nickname}，请注意哪些是你自己的发言。"
|
||||
|
||||
# 根据是否是提及时选择不同的模板
|
||||
if is_mentioned:
|
||||
# 提及时使用简化版提示词，不需要reply、no_reply、no_reply_until_call
|
||||
planner_prompt_template = await global_prompt_manager.get_prompt_async("planner_prompt_mentioned")
|
||||
prompt = planner_prompt_template.format(
|
||||
time_block=time_block,
|
||||
chat_context_description=chat_context_description,
|
||||
chat_content_block=chat_content_block,
|
||||
actions_before_now_block=actions_before_now_block,
|
||||
action_options_text=action_options_block,
|
||||
moderation_prompt=moderation_prompt_block,
|
||||
name_block=name_block,
|
||||
interest=interest,
|
||||
plan_style=global_config.personality.plan_style,
|
||||
)
|
||||
# 根据 think_mode 配置决定 reply action 的示例 JSON
|
||||
if global_config.chat.think_mode == "classic":
|
||||
reply_action_example = '{{"action":"reply", "target_messamge_id":"消息id(m+数字)"}}'
|
||||
else:
|
||||
# 正常流程使用完整版提示词
|
||||
# 检查是否有连续3次以上no_reply，如果有则添加no_reply_until_call选项
|
||||
no_reply_until_call_block = ""
|
||||
if self._has_consecutive_no_reply(min_count=3):
|
||||
no_reply_until_call_block = """no_reply_until_call
|
||||
动作描述：
|
||||
保持沉默，直到有人直接叫你的名字
|
||||
当前话题不感兴趣时使用，或有人不喜欢你的发言时使用
|
||||
当你频繁选择no_reply时使用，表示话题暂时与你无关
|
||||
{{"action":"no_reply_until_call"}}
|
||||
"""
|
||||
reply_action_example = '5.think_level表示思考深度，0表示该回复不需要思考和回忆，1表示该回复需要进行回忆和思考\n{{"action":"reply", "think_level":数值等级(0或1), "target_messamge_id":"消息id(m+数字)"}}'
|
||||
|
||||
planner_prompt_template = await global_prompt_manager.get_prompt_async("planner_prompt")
|
||||
prompt = planner_prompt_template.format(
|
||||
time_block=time_block,
|
||||
chat_context_description=chat_context_description,
|
||||
chat_content_block=chat_content_block,
|
||||
actions_before_now_block=actions_before_now_block,
|
||||
action_options_text=action_options_block,
|
||||
no_reply_until_call_block=no_reply_until_call_block,
|
||||
moderation_prompt=moderation_prompt_block,
|
||||
name_block=name_block,
|
||||
interest=interest,
|
||||
plan_style=global_config.personality.plan_style,
|
||||
)
|
||||
planner_prompt_template = await global_prompt_manager.get_prompt_async("planner_prompt")
|
||||
prompt = planner_prompt_template.format(
|
||||
time_block=time_block,
|
||||
chat_context_description=chat_context_description,
|
||||
chat_content_block=chat_content_block,
|
||||
actions_before_now_block=actions_before_now_block,
|
||||
action_options_text=action_options_block,
|
||||
moderation_prompt=moderation_prompt_block,
|
||||
name_block=name_block,
|
||||
interest=interest,
|
||||
plan_style=global_config.personality.plan_style,
|
||||
reply_action_example=reply_action_example,
|
||||
)
|
||||
|
||||
return prompt, message_id_list
|
||||
except Exception as e:
|
||||
|
||||
@@ -18,13 +18,12 @@ from src.chat.message_receive.uni_message_sender import UniversalMessageSender
|
||||
from src.chat.utils.timer_calculator import Timer # <--- Import Timer
|
||||
from src.chat.utils.utils import get_chat_type_and_target_info
|
||||
from src.chat.utils.prompt_builder import global_prompt_manager
|
||||
from src.mood.mood_manager import mood_manager
|
||||
from src.chat.utils.chat_message_builder import (
|
||||
build_readable_messages,
|
||||
get_raw_msg_before_timestamp_with_chat,
|
||||
replace_user_references,
|
||||
)
|
||||
from src.express.expression_selector import expression_selector
|
||||
from src.bw_learner.expression_selector import expression_selector
|
||||
from src.plugin_system.apis.message_api import translate_pid_to_description
|
||||
|
||||
# from src.memory_system.memory_activator import MemoryActivator
|
||||
@@ -36,7 +35,7 @@ from src.chat.replyer.prompt.lpmm_prompt import init_lpmm_prompt
|
||||
from src.chat.replyer.prompt.replyer_prompt import init_replyer_prompt
|
||||
from src.chat.replyer.prompt.rewrite_prompt import init_rewrite_prompt
|
||||
from src.memory_system.memory_retrieval import init_memory_retrieval_prompt, build_memory_retrieval_prompt
|
||||
from src.jargon.jargon_explainer import explain_jargon_in_context
|
||||
from src.bw_learner.jargon_explainer import explain_jargon_in_context
|
||||
|
||||
init_lpmm_prompt()
|
||||
init_replyer_prompt()
|
||||
@@ -73,6 +72,7 @@ class DefaultReplyer:
|
||||
stream_id: Optional[str] = None,
|
||||
reply_message: Optional[DatabaseMessages] = None,
|
||||
reply_time_point: Optional[float] = time.time(),
|
||||
think_level: int = 1,
|
||||
) -> Tuple[bool, LLMGenerationDataModel]:
|
||||
# sourcery skip: merge-nested-ifs
|
||||
"""
|
||||
@@ -98,8 +98,10 @@ class DefaultReplyer:
|
||||
available_actions = {}
|
||||
try:
|
||||
# 3. 构建 Prompt
|
||||
timing_logs = []
|
||||
almost_zero_str = ""
|
||||
with Timer("构建Prompt", {}): # 内部计时器，可选保留
|
||||
prompt, selected_expressions = await self.build_prompt_reply_context(
|
||||
prompt, selected_expressions, timing_logs, almost_zero_str = await self.build_prompt_reply_context(
|
||||
extra_info=extra_info,
|
||||
available_actions=available_actions,
|
||||
chosen_actions=chosen_actions,
|
||||
@@ -107,6 +109,7 @@ class DefaultReplyer:
|
||||
reply_message=reply_message,
|
||||
reply_reason=reply_reason,
|
||||
reply_time_point=reply_time_point,
|
||||
think_level=think_level,
|
||||
)
|
||||
llm_response.prompt = prompt
|
||||
llm_response.selected_expressions = selected_expressions
|
||||
@@ -135,10 +138,22 @@ class DefaultReplyer:
|
||||
content, reasoning_content, model_name, tool_call = await self.llm_generate_content(prompt)
|
||||
# logger.debug(f"replyer生成内容: {content}")
|
||||
|
||||
logger.info(f"replyer生成内容: {content}")
|
||||
if global_config.debug.show_replyer_reasoning:
|
||||
logger.info(f"replyer生成推理:\n{reasoning_content}")
|
||||
logger.info(f"replyer生成模型: {model_name}")
|
||||
# 统一输出所有日志信息，使用try-except确保即使某个步骤出错也能输出
|
||||
try:
|
||||
# 1. 输出回复准备日志
|
||||
timing_log_str = f"回复准备: {'; '.join(timing_logs)}; {almost_zero_str} <0.1s" if timing_logs or almost_zero_str else "回复准备: 无计时信息"
|
||||
logger.info(timing_log_str)
|
||||
# 2. 输出Prompt日志
|
||||
if global_config.debug.show_replyer_prompt:
|
||||
logger.info(f"\n{prompt}\n")
|
||||
else:
|
||||
logger.debug(f"\nreplyer_Prompt:{prompt}\n")
|
||||
# 3. 输出模型生成内容和推理日志
|
||||
logger.info(f"模型: [{model_name}][思考等级:{think_level}]生成内容: {content}")
|
||||
if global_config.debug.show_replyer_reasoning and reasoning_content:
|
||||
logger.info(f"模型: [{model_name}][思考等级:{think_level}]生成推理:\n{reasoning_content}")
|
||||
except Exception as e:
|
||||
logger.warning(f"输出日志时出错: {e}")
|
||||
|
||||
llm_response.content = content
|
||||
llm_response.reasoning = reasoning_content
|
||||
@@ -162,6 +177,21 @@ class DefaultReplyer:
|
||||
except Exception as llm_e:
|
||||
# 精简报错信息
|
||||
logger.error(f"LLM 生成失败: {llm_e}")
|
||||
# 即使LLM生成失败，也尝试输出已收集的日志信息
|
||||
try:
|
||||
# 1. 输出回复准备日志
|
||||
timing_log_str = f"回复准备: {'; '.join(timing_logs)}; {almost_zero_str} <0.1s" if timing_logs or almost_zero_str else "回复准备: 无计时信息"
|
||||
logger.info(timing_log_str)
|
||||
# 2. 输出Prompt日志
|
||||
if global_config.debug.show_replyer_prompt:
|
||||
logger.info(f"\n{prompt}\n")
|
||||
else:
|
||||
logger.debug(f"\nreplyer_Prompt:{prompt}\n")
|
||||
# 3. 输出模型生成失败信息
|
||||
logger.info("模型生成失败，无法输出生成内容和推理")
|
||||
except Exception as log_e:
|
||||
logger.warning(f"输出日志时出错: {log_e}")
|
||||
|
||||
return False, llm_response # LLM 调用失败则无法生成回复
|
||||
|
||||
return True, llm_response
|
||||
@@ -228,7 +258,7 @@ class DefaultReplyer:
|
||||
return False, llm_response
|
||||
|
||||
async def build_expression_habits(
|
||||
self, chat_history: str, target: str, reply_reason: str = ""
|
||||
self, chat_history: str, target: str, reply_reason: str = "", think_level: int = 1
|
||||
) -> Tuple[str, List[int]]:
|
||||
# sourcery skip: for-append-to-extend
|
||||
"""构建表达习惯块
|
||||
@@ -237,6 +267,7 @@ class DefaultReplyer:
|
||||
chat_history: 聊天历史记录
|
||||
target: 目标消息内容
|
||||
reply_reason: planner给出的回复理由
|
||||
think_level: 思考级别，0/1/2
|
||||
|
||||
Returns:
|
||||
str: 表达习惯信息字符串
|
||||
@@ -249,14 +280,19 @@ class DefaultReplyer:
|
||||
# 使用从处理器传来的选中表达方式
|
||||
# 使用模型预测选择表达方式
|
||||
selected_expressions, selected_ids = await expression_selector.select_suitable_expressions(
|
||||
self.chat_stream.stream_id, chat_history, max_num=8, target_message=target, reply_reason=reply_reason
|
||||
self.chat_stream.stream_id,
|
||||
chat_history,
|
||||
max_num=8,
|
||||
target_message=target,
|
||||
reply_reason=reply_reason,
|
||||
think_level=think_level,
|
||||
)
|
||||
|
||||
if selected_expressions:
|
||||
logger.debug(f"使用处理器选中的{len(selected_expressions)}个表达方式")
|
||||
for expr in selected_expressions:
|
||||
if isinstance(expr, dict) and "situation" in expr and "style" in expr:
|
||||
style_habits.append(f"当{expr['situation']}时，使用 {expr['style']}")
|
||||
style_habits.append(f"当{expr['situation']}时：{expr['style']}")
|
||||
else:
|
||||
logger.debug("没有从处理器获得表达方式，将使用空的表达方式")
|
||||
# 不再在replyer中进行随机选择，全部交给处理器处理
|
||||
@@ -272,13 +308,6 @@ class DefaultReplyer:
|
||||
|
||||
return f"{expression_habits_title}\n{expression_habits_block}", selected_ids
|
||||
|
||||
async def build_mood_state_prompt(self) -> str:
|
||||
"""构建情绪状态提示"""
|
||||
if not global_config.mood.enable_mood:
|
||||
return ""
|
||||
mood_state = await mood_manager.get_mood_by_chat_id(self.chat_stream.stream_id).get_mood()
|
||||
return f"你现在的心情是：{mood_state}"
|
||||
|
||||
async def build_tool_info(self, chat_history: str, sender: str, target: str, enable_tool: bool = True) -> str:
|
||||
"""构建工具信息块
|
||||
|
||||
@@ -459,6 +488,10 @@ class DefaultReplyer:
|
||||
duration = end_time - start_time
|
||||
return name, result, duration
|
||||
|
||||
async def _build_disabled_jargon_explanation(self) -> str:
|
||||
"""当关闭黑话解释时使用的占位协程，避免额外的LLM调用"""
|
||||
return ""
|
||||
|
||||
def build_chat_history_prompts(
|
||||
self, message_list_before_now: List[DatabaseMessages], target_user_id: str, sender: str
|
||||
) -> Tuple[str, str]:
|
||||
@@ -606,7 +639,7 @@ class DefaultReplyer:
|
||||
# 获取基础personality
|
||||
prompt_personality = global_config.personality.personality
|
||||
|
||||
# 检查是否需要随机替换为状态
|
||||
# 检查是否需要随机替换为状态（personality 本体）
|
||||
if (
|
||||
global_config.personality.states
|
||||
and global_config.personality.state_probability > 0
|
||||
@@ -705,7 +738,8 @@ class DefaultReplyer:
|
||||
chosen_actions: Optional[List[ActionPlannerInfo]] = None,
|
||||
enable_tool: bool = True,
|
||||
reply_time_point: Optional[float] = time.time(),
|
||||
) -> Tuple[str, List[int]]:
|
||||
think_level: int = 1,
|
||||
) -> Tuple[str, List[int], List[str], str]:
|
||||
"""
|
||||
构建回复器上下文
|
||||
|
||||
@@ -751,14 +785,14 @@ class DefaultReplyer:
|
||||
chat_id=chat_id,
|
||||
timestamp=reply_time_point,
|
||||
limit=global_config.chat.max_context_size * 1,
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
|
||||
message_list_before_short = get_raw_msg_before_timestamp_with_chat(
|
||||
chat_id=chat_id,
|
||||
timestamp=reply_time_point,
|
||||
limit=int(global_config.chat.max_context_size * 0.33),
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
|
||||
person_list_short: List[Person] = []
|
||||
@@ -789,10 +823,18 @@ class DefaultReplyer:
|
||||
show_actions=True,
|
||||
)
|
||||
|
||||
# 并行执行八个构建任务（包括黑话解释）
|
||||
# 根据配置决定是否启用黑话解释
|
||||
enable_jargon_explanation = getattr(global_config.expression, "enable_jargon_explanation", True)
|
||||
if enable_jargon_explanation:
|
||||
jargon_coroutine = explain_jargon_in_context(chat_id, message_list_before_short, chat_talking_prompt_short)
|
||||
else:
|
||||
jargon_coroutine = self._build_disabled_jargon_explanation()
|
||||
|
||||
# 并行执行八个构建任务（包括黑话解释，可配置关闭）
|
||||
task_results = await asyncio.gather(
|
||||
self._time_and_run_task(
|
||||
self.build_expression_habits(chat_talking_prompt_short, target, reply_reason), "expression_habits"
|
||||
self.build_expression_habits(chat_talking_prompt_short, target, reply_reason, think_level=think_level),
|
||||
"expression_habits",
|
||||
),
|
||||
self._time_and_run_task(
|
||||
self.build_tool_info(chat_talking_prompt_short, sender, target, enable_tool=enable_tool), "tool_info"
|
||||
@@ -800,17 +842,13 @@ class DefaultReplyer:
|
||||
self._time_and_run_task(self.get_prompt_info(chat_talking_prompt_short, sender, target), "prompt_info"),
|
||||
self._time_and_run_task(self.build_actions_prompt(available_actions, chosen_actions), "actions_info"),
|
||||
self._time_and_run_task(self.build_personality_prompt(), "personality_prompt"),
|
||||
self._time_and_run_task(self.build_mood_state_prompt(), "mood_state_prompt"),
|
||||
self._time_and_run_task(
|
||||
build_memory_retrieval_prompt(
|
||||
chat_talking_prompt_short, sender, target, self.chat_stream, self.tool_executor
|
||||
chat_talking_prompt_short, sender, target, self.chat_stream, think_level=think_level
|
||||
),
|
||||
"memory_retrieval",
|
||||
),
|
||||
self._time_and_run_task(
|
||||
explain_jargon_in_context(chat_id, message_list_before_short, chat_talking_prompt_short),
|
||||
"jargon_explanation",
|
||||
),
|
||||
self._time_and_run_task(jargon_coroutine, "jargon_explanation"),
|
||||
)
|
||||
|
||||
# 任务名称中英文映射
|
||||
@@ -821,7 +859,6 @@ class DefaultReplyer:
|
||||
"prompt_info": "获取知识",
|
||||
"actions_info": "动作信息",
|
||||
"personality_prompt": "人格信息",
|
||||
"mood_state_prompt": "情绪状态",
|
||||
"memory_retrieval": "记忆检索",
|
||||
"jargon_explanation": "黑话解释",
|
||||
}
|
||||
@@ -839,7 +876,8 @@ class DefaultReplyer:
|
||||
continue
|
||||
|
||||
timing_logs.append(f"{chinese_name}: {duration:.1f}s")
|
||||
logger.info(f"回复准备: {'; '.join(timing_logs)}; {almost_zero_str} <0.1s")
|
||||
# 不再在这里输出日志，而是返回给调用者统一输出
|
||||
# logger.info(f"回复准备: {'; '.join(timing_logs)}; {almost_zero_str} <0.1s")
|
||||
|
||||
expression_habits_block, selected_expressions = results_dict["expression_habits"]
|
||||
expression_habits_block: str
|
||||
@@ -851,14 +889,8 @@ class DefaultReplyer:
|
||||
personality_prompt: str = results_dict["personality_prompt"]
|
||||
memory_retrieval: str = results_dict["memory_retrieval"]
|
||||
keywords_reaction_prompt = await self.build_keywords_reaction_prompt(target)
|
||||
mood_state_prompt: str = results_dict["mood_state_prompt"]
|
||||
jargon_explanation: str = results_dict.get("jargon_explanation") or ""
|
||||
|
||||
# 从 chosen_actions 中提取 planner 的整体思考理由
|
||||
planner_reasoning = ""
|
||||
if global_config.chat.include_planner_reasoning and reply_reason:
|
||||
# 如果没有 chosen_actions，使用 reply_reason 作为备选
|
||||
planner_reasoning = f"你的想法是：{reply_reason}"
|
||||
planner_reasoning = f"你的想法是：{reply_reason}"
|
||||
|
||||
if extra_info:
|
||||
extra_info_block = f"以下是你在回复时需要参考的信息，现在请你阅读以下内容，进行决策\n{extra_info}\n以上是你在回复时需要参考的信息，现在请你阅读以下内容，进行决策"
|
||||
@@ -893,14 +925,31 @@ class DefaultReplyer:
|
||||
chat_prompt_content = self.get_chat_prompt_for_chat(chat_id)
|
||||
chat_prompt_block = f"{chat_prompt_content}\n" if chat_prompt_content else ""
|
||||
|
||||
# 固定使用群聊回复模板
|
||||
# 根据think_level选择不同的回复模板
|
||||
# think_level=0: 轻量回复（简短平淡）
|
||||
# think_level=1: 中等回复（日常口语化）
|
||||
if think_level == 0:
|
||||
prompt_name = "replyer_prompt_0"
|
||||
else: # think_level == 1 或默认
|
||||
prompt_name = "replyer_prompt"
|
||||
|
||||
# 根据配置构建最终的 reply_style：支持 multiple_reply_style 按概率随机替换
|
||||
reply_style = global_config.personality.reply_style
|
||||
multi_styles = getattr(global_config.personality, "multiple_reply_style", None) or []
|
||||
multi_prob = getattr(global_config.personality, "multiple_probability", 0.0) or 0.0
|
||||
if multi_styles and multi_prob > 0 and random.random() < multi_prob:
|
||||
try:
|
||||
reply_style = random.choice(list(multi_styles))
|
||||
except Exception:
|
||||
# 兜底：即使 multiple_reply_style 配置异常也不影响正常回复
|
||||
reply_style = global_config.personality.reply_style
|
||||
|
||||
return await global_prompt_manager.format_prompt(
|
||||
"replyer_prompt",
|
||||
prompt_name,
|
||||
expression_habits_block=expression_habits_block,
|
||||
tool_info_block=tool_info,
|
||||
bot_name=global_config.bot.nickname,
|
||||
knowledge_prompt=prompt_info,
|
||||
mood_state=mood_state_prompt,
|
||||
# relation_info_block=relation_info,
|
||||
extra_info_block=extra_info_block,
|
||||
jargon_explanation=jargon_explanation,
|
||||
@@ -910,13 +959,13 @@ class DefaultReplyer:
|
||||
dialogue_prompt=dialogue_prompt,
|
||||
time_block=time_block,
|
||||
reply_target_block=reply_target_block,
|
||||
reply_style=global_config.personality.reply_style,
|
||||
reply_style=reply_style,
|
||||
keywords_reaction_prompt=keywords_reaction_prompt,
|
||||
moderation_prompt=moderation_prompt_block,
|
||||
memory_retrieval=memory_retrieval,
|
||||
chat_prompt=chat_prompt_block,
|
||||
planner_reasoning=planner_reasoning,
|
||||
), selected_expressions
|
||||
), selected_expressions, timing_logs, almost_zero_str
|
||||
|
||||
async def build_prompt_rewrite_context(
|
||||
self,
|
||||
@@ -926,8 +975,6 @@ class DefaultReplyer:
|
||||
) -> str: # sourcery skip: merge-else-if-into-elif, remove-redundant-if
|
||||
chat_stream = self.chat_stream
|
||||
chat_id = chat_stream.stream_id
|
||||
is_group_chat = bool(chat_stream.group_info)
|
||||
|
||||
sender, target = self._parse_reply_target(reply_to)
|
||||
target = replace_user_references(target, chat_stream.platform, replace_bot_name=True)
|
||||
|
||||
@@ -941,7 +988,7 @@ class DefaultReplyer:
|
||||
chat_id=chat_id,
|
||||
timestamp=time.time(),
|
||||
limit=min(int(global_config.chat.max_context_size * 0.33), 15),
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
chat_talking_prompt_half = build_readable_messages(
|
||||
message_list_before_now_half,
|
||||
@@ -967,61 +1014,42 @@ class DefaultReplyer:
|
||||
|
||||
if sender and target:
|
||||
# 使用预先分析的内容类型结果
|
||||
if is_group_chat:
|
||||
if sender:
|
||||
if has_only_pics and not has_text:
|
||||
# 只包含图片
|
||||
reply_target_block = (
|
||||
f"现在{sender}发送的图片：{pic_part}。引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
)
|
||||
elif has_text and pic_part:
|
||||
# 既有图片又有文字
|
||||
reply_target_block = f"现在{sender}发送了图片：{pic_part}，并说：{text_part}。引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
else:
|
||||
# 只包含文字
|
||||
reply_target_block = (
|
||||
f"现在{sender}说的:{text_part}。引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
)
|
||||
elif target:
|
||||
reply_target_block = f"现在{target}引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
if sender:
|
||||
if has_only_pics and not has_text:
|
||||
# 只包含图片
|
||||
reply_target_block = (
|
||||
f"现在{sender}发送的图片：{pic_part}。引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
)
|
||||
elif has_text and pic_part:
|
||||
# 既有图片又有文字
|
||||
reply_target_block = f"现在{sender}发送了图片：{pic_part}，并说：{text_part}。引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
else:
|
||||
reply_target_block = "现在，你想要在群里发言或者回复消息。"
|
||||
else: # private chat
|
||||
if sender:
|
||||
if has_only_pics and not has_text:
|
||||
# 只包含图片
|
||||
reply_target_block = f"现在{sender}发送的图片：{pic_part}。引起了你的注意，针对这条消息回复。"
|
||||
elif has_text and pic_part:
|
||||
# 既有图片又有文字
|
||||
reply_target_block = (
|
||||
f"现在{sender}发送了图片：{pic_part}，并说：{text_part}。引起了你的注意，针对这条消息回复。"
|
||||
)
|
||||
else:
|
||||
# 只包含文字
|
||||
reply_target_block = f"现在{sender}说的:{text_part}。引起了你的注意，针对这条消息回复。"
|
||||
elif target:
|
||||
reply_target_block = f"现在{target}引起了你的注意，针对这条消息回复。"
|
||||
else:
|
||||
reply_target_block = "现在，你想要回复。"
|
||||
# 只包含文字
|
||||
reply_target_block = (
|
||||
f"现在{sender}说的:{text_part}。引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
)
|
||||
elif target:
|
||||
reply_target_block = f"现在{target}引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
else:
|
||||
reply_target_block = "现在，你想要在群里发言或者回复消息。"
|
||||
else:
|
||||
reply_target_block = ""
|
||||
|
||||
if is_group_chat:
|
||||
chat_target_1 = await global_prompt_manager.get_prompt_async("chat_target_group1")
|
||||
chat_target_2 = await global_prompt_manager.get_prompt_async("chat_target_group2")
|
||||
else:
|
||||
chat_target_name = "对方"
|
||||
if self.chat_target_info:
|
||||
chat_target_name = self.chat_target_info.person_name or self.chat_target_info.user_nickname or "对方"
|
||||
chat_target_1 = await global_prompt_manager.format_prompt(
|
||||
"chat_target_private1", sender_name=chat_target_name
|
||||
)
|
||||
chat_target_2 = await global_prompt_manager.format_prompt(
|
||||
"chat_target_private2", sender_name=chat_target_name
|
||||
)
|
||||
chat_target_1 = await global_prompt_manager.get_prompt_async("chat_target_group1")
|
||||
chat_target_2 = await global_prompt_manager.get_prompt_async("chat_target_group2")
|
||||
|
||||
template_name = "default_expressor_prompt"
|
||||
|
||||
# 根据配置构建最终的 reply_style：支持 multiple_reply_style 按概率随机替换
|
||||
reply_style = global_config.personality.reply_style
|
||||
multi_styles = getattr(global_config.personality, "multiple_reply_style", None) or []
|
||||
multi_prob = getattr(global_config.personality, "multiple_probability", 0.0) or 0.0
|
||||
if multi_styles and multi_prob > 0 and random.random() < multi_prob:
|
||||
try:
|
||||
reply_style = random.choice(list(multi_styles))
|
||||
except Exception:
|
||||
reply_style = global_config.personality.reply_style
|
||||
|
||||
return await global_prompt_manager.format_prompt(
|
||||
template_name,
|
||||
expression_habits_block=expression_habits_block,
|
||||
@@ -1034,7 +1062,7 @@ class DefaultReplyer:
|
||||
reply_target_block=reply_target_block,
|
||||
raw_reply=raw_reply,
|
||||
reason=reason,
|
||||
reply_style=global_config.personality.reply_style,
|
||||
reply_style=reply_style,
|
||||
keywords_reaction_prompt=keywords_reaction_prompt,
|
||||
moderation_prompt=moderation_prompt_block,
|
||||
)
|
||||
@@ -1078,10 +1106,11 @@ class DefaultReplyer:
|
||||
# 直接使用已初始化的模型实例
|
||||
# logger.info(f"\n{prompt}\n")
|
||||
|
||||
if global_config.debug.show_replyer_prompt:
|
||||
logger.info(f"\n{prompt}\n")
|
||||
else:
|
||||
logger.debug(f"\nreplyer_Prompt:{prompt}\n")
|
||||
# 不再在这里输出日志，而是返回给调用者统一输出
|
||||
# if global_config.debug.show_replyer_prompt:
|
||||
# logger.info(f"\n{prompt}\n")
|
||||
# else:
|
||||
# logger.debug(f"\nreplyer_Prompt:{prompt}\n")
|
||||
|
||||
content, (reasoning_content, model_name, tool_calls) = await self.express_model.generate_response_async(
|
||||
prompt
|
||||
@@ -1090,7 +1119,7 @@ class DefaultReplyer:
|
||||
# 移除 content 前后的换行符和空格
|
||||
content = content.strip()
|
||||
|
||||
logger.info(f"使用 {model_name} 生成回复内容: {content}")
|
||||
# logger.info(f"使用 {model_name} 生成回复内容: {content}")
|
||||
return content, reasoning_content, model_name, tool_calls
|
||||
|
||||
async def get_prompt_info(self, message: str, sender: str, target: str):
|
||||
|
||||
@@ -23,9 +23,8 @@ from src.chat.utils.chat_message_builder import (
|
||||
get_raw_msg_before_timestamp_with_chat,
|
||||
replace_user_references,
|
||||
)
|
||||
from src.express.expression_selector import expression_selector
|
||||
from src.bw_learner.expression_selector import expression_selector
|
||||
from src.plugin_system.apis.message_api import translate_pid_to_description
|
||||
from src.mood.mood_manager import mood_manager
|
||||
|
||||
# from src.memory_system.memory_activator import MemoryActivator
|
||||
|
||||
@@ -34,13 +33,13 @@ from src.plugin_system.base.component_types import ActionInfo, EventType
|
||||
from src.plugin_system.apis import llm_api
|
||||
|
||||
from src.chat.replyer.prompt.lpmm_prompt import init_lpmm_prompt
|
||||
from src.chat.replyer.prompt.replyer_prompt import init_replyer_prompt
|
||||
from src.chat.replyer.prompt.replyer_private_prompt import init_replyer_private_prompt
|
||||
from src.chat.replyer.prompt.rewrite_prompt import init_rewrite_prompt
|
||||
from src.memory_system.memory_retrieval import init_memory_retrieval_prompt, build_memory_retrieval_prompt
|
||||
from src.jargon.jargon_explainer import explain_jargon_in_context
|
||||
from src.bw_learner.jargon_explainer import explain_jargon_in_context
|
||||
|
||||
init_lpmm_prompt()
|
||||
init_replyer_prompt()
|
||||
init_replyer_private_prompt()
|
||||
init_rewrite_prompt()
|
||||
init_memory_retrieval_prompt()
|
||||
|
||||
@@ -72,6 +71,7 @@ class PrivateReplyer:
|
||||
chosen_actions: Optional[List[ActionPlannerInfo]] = None,
|
||||
enable_tool: bool = True,
|
||||
from_plugin: bool = True,
|
||||
think_level: int = 1,
|
||||
stream_id: Optional[str] = None,
|
||||
reply_message: Optional[DatabaseMessages] = None,
|
||||
reply_time_point: Optional[float] = time.time(),
|
||||
@@ -271,7 +271,7 @@ class PrivateReplyer:
|
||||
logger.debug(f"使用处理器选中的{len(selected_expressions)}个表达方式")
|
||||
for expr in selected_expressions:
|
||||
if isinstance(expr, dict) and "situation" in expr and "style" in expr:
|
||||
style_habits.append(f"当{expr['situation']}时，使用 {expr['style']}")
|
||||
style_habits.append(f"当{expr['situation']}时：{expr['style']}")
|
||||
else:
|
||||
logger.debug("没有从处理器获得表达方式，将使用空的表达方式")
|
||||
# 不再在replyer中进行随机选择，全部交给处理器处理
|
||||
@@ -287,13 +287,6 @@ class PrivateReplyer:
|
||||
|
||||
return f"{expression_habits_title}\n{expression_habits_block}", selected_ids
|
||||
|
||||
async def build_mood_state_prompt(self) -> str:
|
||||
"""构建情绪状态提示"""
|
||||
if not global_config.mood.enable_mood:
|
||||
return ""
|
||||
mood_state = await mood_manager.get_mood_by_chat_id(self.chat_stream.stream_id).get_mood()
|
||||
return f"你现在的心情是：{mood_state}"
|
||||
|
||||
async def build_tool_info(self, chat_history: str, sender: str, target: str, enable_tool: bool = True) -> str:
|
||||
"""构建工具信息块
|
||||
|
||||
@@ -474,6 +467,10 @@ class PrivateReplyer:
|
||||
duration = end_time - start_time
|
||||
return name, result, duration
|
||||
|
||||
async def _build_disabled_jargon_explanation(self) -> str:
|
||||
"""当关闭黑话解释时使用的占位协程，避免额外的LLM调用"""
|
||||
return ""
|
||||
|
||||
async def build_actions_prompt(
|
||||
self, available_actions: Dict[str, ActionInfo], chosen_actions_info: Optional[List[ActionPlannerInfo]] = None
|
||||
) -> str:
|
||||
@@ -663,7 +660,7 @@ class PrivateReplyer:
|
||||
chat_id=chat_id,
|
||||
timestamp=time.time(),
|
||||
limit=global_config.chat.max_context_size,
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
|
||||
dialogue_prompt = build_readable_messages(
|
||||
@@ -678,7 +675,7 @@ class PrivateReplyer:
|
||||
chat_id=chat_id,
|
||||
timestamp=time.time(),
|
||||
limit=int(global_config.chat.max_context_size * 0.33),
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
|
||||
person_list_short: List[Person] = []
|
||||
@@ -709,7 +706,14 @@ class PrivateReplyer:
|
||||
show_actions=True,
|
||||
)
|
||||
|
||||
# 并行执行九个构建任务（包括黑话解释）
|
||||
# 根据配置决定是否启用黑话解释
|
||||
enable_jargon_explanation = getattr(global_config.expression, "enable_jargon_explanation", True)
|
||||
if enable_jargon_explanation:
|
||||
jargon_coroutine = explain_jargon_in_context(chat_id, message_list_before_short, chat_talking_prompt_short)
|
||||
else:
|
||||
jargon_coroutine = self._build_disabled_jargon_explanation()
|
||||
|
||||
# 并行执行九个构建任务（包括黑话解释，可配置关闭）
|
||||
task_results = await asyncio.gather(
|
||||
self._time_and_run_task(
|
||||
self.build_expression_habits(chat_talking_prompt_short, target, reply_reason), "expression_habits"
|
||||
@@ -721,17 +725,13 @@ class PrivateReplyer:
|
||||
self._time_and_run_task(self.get_prompt_info(chat_talking_prompt_short, sender, target), "prompt_info"),
|
||||
self._time_and_run_task(self.build_actions_prompt(available_actions, chosen_actions), "actions_info"),
|
||||
self._time_and_run_task(self.build_personality_prompt(), "personality_prompt"),
|
||||
self._time_and_run_task(self.build_mood_state_prompt(), "mood_state_prompt"),
|
||||
self._time_and_run_task(
|
||||
build_memory_retrieval_prompt(
|
||||
chat_talking_prompt_short, sender, target, self.chat_stream, self.tool_executor
|
||||
),
|
||||
"memory_retrieval",
|
||||
),
|
||||
self._time_and_run_task(
|
||||
explain_jargon_in_context(chat_id, message_list_before_short, chat_talking_prompt_short),
|
||||
"jargon_explanation",
|
||||
),
|
||||
self._time_and_run_task(jargon_coroutine, "jargon_explanation"),
|
||||
)
|
||||
|
||||
# 任务名称中英文映射
|
||||
@@ -742,7 +742,6 @@ class PrivateReplyer:
|
||||
"prompt_info": "获取知识",
|
||||
"actions_info": "动作信息",
|
||||
"personality_prompt": "人格信息",
|
||||
"mood_state_prompt": "情绪状态",
|
||||
"memory_retrieval": "记忆检索",
|
||||
"jargon_explanation": "黑话解释",
|
||||
}
|
||||
@@ -770,16 +769,10 @@ class PrivateReplyer:
|
||||
prompt_info: str = results_dict["prompt_info"] # 直接使用格式化后的结果
|
||||
actions_info: str = results_dict["actions_info"]
|
||||
personality_prompt: str = results_dict["personality_prompt"]
|
||||
mood_state_prompt: str = results_dict["mood_state_prompt"]
|
||||
memory_retrieval: str = results_dict["memory_retrieval"]
|
||||
keywords_reaction_prompt = await self.build_keywords_reaction_prompt(target)
|
||||
jargon_explanation: str = results_dict.get("jargon_explanation") or ""
|
||||
|
||||
# 从 chosen_actions 中提取 planner 的整体思考理由
|
||||
planner_reasoning = ""
|
||||
if global_config.chat.include_planner_reasoning and reply_reason:
|
||||
# 如果没有 chosen_actions，使用 reply_reason 作为备选
|
||||
planner_reasoning = f"你的想法是：{reply_reason}"
|
||||
planner_reasoning = f"你的想法是：{reply_reason}"
|
||||
|
||||
if extra_info:
|
||||
extra_info_block = f"以下是你在回复时需要参考的信息，现在请你阅读以下内容，进行决策\n{extra_info}\n以上是你在回复时需要参考的信息，现在请你阅读以下内容，进行决策"
|
||||
@@ -814,7 +807,6 @@ class PrivateReplyer:
|
||||
expression_habits_block=expression_habits_block,
|
||||
tool_info_block=tool_info,
|
||||
knowledge_prompt=prompt_info,
|
||||
mood_state=mood_state_prompt,
|
||||
relation_info_block=relation_info,
|
||||
extra_info_block=extra_info_block,
|
||||
identity=personality_prompt,
|
||||
@@ -837,7 +829,6 @@ class PrivateReplyer:
|
||||
expression_habits_block=expression_habits_block,
|
||||
tool_info_block=tool_info,
|
||||
knowledge_prompt=prompt_info,
|
||||
mood_state=mood_state_prompt,
|
||||
relation_info_block=relation_info,
|
||||
extra_info_block=extra_info_block,
|
||||
identity=personality_prompt,
|
||||
@@ -878,7 +869,7 @@ class PrivateReplyer:
|
||||
chat_id=chat_id,
|
||||
timestamp=time.time(),
|
||||
limit=min(int(global_config.chat.max_context_size * 0.33), 15),
|
||||
filter_no_read_command=True,
|
||||
filter_intercept_message_level=1,
|
||||
)
|
||||
chat_talking_prompt_half = build_readable_messages(
|
||||
message_list_before_now_half,
|
||||
@@ -904,59 +895,30 @@ class PrivateReplyer:
|
||||
)
|
||||
|
||||
if sender and target:
|
||||
# 使用预先分析的内容类型结果
|
||||
if is_group_chat:
|
||||
if sender:
|
||||
if has_only_pics and not has_text:
|
||||
# 只包含图片
|
||||
reply_target_block = (
|
||||
f"现在{sender}发送的图片：{pic_part}。引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
)
|
||||
elif has_text and pic_part:
|
||||
# 既有图片又有文字
|
||||
reply_target_block = f"现在{sender}发送了图片：{pic_part}，并说：{text_part}。引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
else:
|
||||
# 只包含文字
|
||||
reply_target_block = (
|
||||
f"现在{sender}说的:{text_part}。引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
)
|
||||
elif target:
|
||||
reply_target_block = f"现在{target}引起了你的注意，你想要在群里发言或者回复这条消息。"
|
||||
if sender:
|
||||
if has_only_pics and not has_text:
|
||||
# 只包含图片
|
||||
reply_target_block = f"现在{sender}发送的图片：{pic_part}。引起了你的注意，针对这条消息回复。"
|
||||
elif has_text and pic_part:
|
||||
# 既有图片又有文字
|
||||
reply_target_block = (
|
||||
f"现在{sender}发送了图片：{pic_part}，并说：{text_part}。引起了你的注意，针对这条消息回复。"
|
||||
)
|
||||
else:
|
||||
reply_target_block = "现在，你想要在群里发言或者回复消息。"
|
||||
else: # private chat
|
||||
if sender:
|
||||
if has_only_pics and not has_text:
|
||||
# 只包含图片
|
||||
reply_target_block = f"现在{sender}发送的图片：{pic_part}。引起了你的注意，针对这条消息回复。"
|
||||
elif has_text and pic_part:
|
||||
# 既有图片又有文字
|
||||
reply_target_block = (
|
||||
f"现在{sender}发送了图片：{pic_part}，并说：{text_part}。引起了你的注意，针对这条消息回复。"
|
||||
)
|
||||
else:
|
||||
# 只包含文字
|
||||
reply_target_block = f"现在{sender}说的:{text_part}。引起了你的注意，针对这条消息回复。"
|
||||
elif target:
|
||||
reply_target_block = f"现在{target}引起了你的注意，针对这条消息回复。"
|
||||
else:
|
||||
reply_target_block = "现在，你想要回复。"
|
||||
# 只包含文字
|
||||
reply_target_block = f"现在{sender}说的:{text_part}。引起了你的注意，针对这条消息回复。"
|
||||
elif target:
|
||||
reply_target_block = f"现在{target}引起了你的注意，针对这条消息回复。"
|
||||
else:
|
||||
reply_target_block = "现在，你想要回复。"
|
||||
else:
|
||||
reply_target_block = ""
|
||||
|
||||
if is_group_chat:
|
||||
chat_target_1 = await global_prompt_manager.get_prompt_async("chat_target_group1")
|
||||
chat_target_2 = await global_prompt_manager.get_prompt_async("chat_target_group2")
|
||||
else:
|
||||
chat_target_name = "对方"
|
||||
if self.chat_target_info:
|
||||
chat_target_name = self.chat_target_info.person_name or self.chat_target_info.user_nickname or "对方"
|
||||
chat_target_1 = await global_prompt_manager.format_prompt(
|
||||
"chat_target_private1", sender_name=chat_target_name
|
||||
)
|
||||
chat_target_2 = await global_prompt_manager.format_prompt(
|
||||
"chat_target_private2", sender_name=chat_target_name
|
||||
)
|
||||
chat_target_name = "对方"
|
||||
if self.chat_target_info:
|
||||
chat_target_name = self.chat_target_info.person_name or self.chat_target_info.user_nickname or "对方"
|
||||
chat_target_1 = await global_prompt_manager.format_prompt("chat_target_private1", sender_name=chat_target_name)
|
||||
chat_target_2 = await global_prompt_manager.format_prompt("chat_target_private2", sender_name=chat_target_name)
|
||||
|
||||
template_name = "default_expressor_prompt"
|
||||
|
||||
|
||||
41
src/chat/replyer/prompt/replyer_private_prompt.py
Normal file
41
src/chat/replyer/prompt/replyer_private_prompt.py
Normal file
@@ -0,0 +1,41 @@
|
||||
from src.chat.utils.prompt_builder import Prompt
|
||||
|
||||
|
||||
def init_replyer_private_prompt():
|
||||
Prompt(
|
||||
"""{knowledge_prompt}{tool_info_block}{extra_info_block}
|
||||
{expression_habits_block}{memory_retrieval}{jargon_explanation}
|
||||
|
||||
你正在和{sender_name}聊天，这是你们之前聊的内容:
|
||||
{time_block}
|
||||
{dialogue_prompt}
|
||||
|
||||
{reply_target_block}。
|
||||
{planner_reasoning}
|
||||
{identity}
|
||||
{chat_prompt}你正在和{sender_name}聊天,现在请你读读之前的聊天记录，然后给出日常且口语化的回复，平淡一些，
|
||||
尽量简短一些。{keywords_reaction_prompt}请注意把握聊天内容，不要回复的太有条理。
|
||||
{reply_style}
|
||||
请注意不要输出多余内容(包括前后缀，冒号和引号，括号，表情等)，只输出回复内容。
|
||||
{moderation_prompt}不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )。""",
|
||||
"private_replyer_prompt",
|
||||
)
|
||||
|
||||
Prompt(
|
||||
"""{knowledge_prompt}{tool_info_block}{extra_info_block}
|
||||
{expression_habits_block}{memory_retrieval}{jargon_explanation}
|
||||
|
||||
你正在和{sender_name}聊天，这是你们之前聊的内容:
|
||||
{time_block}
|
||||
{dialogue_prompt}
|
||||
|
||||
你现在想补充说明你刚刚自己的发言内容：{target}，原因是{reason}
|
||||
请你根据聊天内容，组织一条新回复。注意，{target} 是刚刚你自己的发言，你要在这基础上进一步发言，请按照你自己的角度来继续进行回复。注意保持上下文的连贯性。
|
||||
{identity}
|
||||
{chat_prompt}尽量简短一些。{keywords_reaction_prompt}请注意把握聊天内容，不要回复的太有条理，可以有个性。
|
||||
{reply_style}
|
||||
请注意不要输出多余内容(包括前后缀，冒号和引号，括号，表情等)，只输出回复内容。
|
||||
{moderation_prompt}不要输出多余内容(包括冒号和引号，括号，表情包，at或 @等 )。
|
||||
""",
|
||||
"private_replyer_self_prompt",
|
||||
)
|
||||
@@ -3,8 +3,27 @@ from src.chat.utils.prompt_builder import Prompt
|
||||
|
||||
|
||||
def init_replyer_prompt():
|
||||
Prompt("正在群里聊天", "chat_target_group2")
|
||||
Prompt("和{sender_name}聊天", "chat_target_private2")
|
||||
Prompt(
|
||||
"""{knowledge_prompt}{tool_info_block}{extra_info_block}
|
||||
{expression_habits_block}{memory_retrieval}{jargon_explanation}
|
||||
|
||||
你正在qq群里聊天，下面是群里正在聊的内容，其中包含聊天记录和聊天中的图片
|
||||
其中标注 {bot_name}(你) 的发言是你自己的发言，请注意区分:
|
||||
{time_block}
|
||||
{dialogue_prompt}
|
||||
|
||||
{reply_target_block}。
|
||||
{planner_reasoning}
|
||||
{identity}
|
||||
{chat_prompt}你正在群里聊天,现在请你读读之前的聊天记录，然后给出日常且口语化的回复，
|
||||
尽量简短一些。{keywords_reaction_prompt}
|
||||
请注意把握聊天内容，不要回复的太有条理。
|
||||
{reply_style}
|
||||
请注意不要输出多余内容(包括不必要的前后缀，冒号，括号，表情包，at或 @等 )，只输出发言内容就好。
|
||||
最好一次对一个话题进行回复，免得啰嗦或者回复内容太乱。
|
||||
现在，你说：""",
|
||||
"replyer_prompt_0",
|
||||
)
|
||||
|
||||
Prompt(
|
||||
"""{knowledge_prompt}{tool_info_block}{extra_info_block}
|
||||
@@ -18,49 +37,12 @@ def init_replyer_prompt():
|
||||
{reply_target_block}。
|
||||
{planner_reasoning}
|
||||
{identity}
|
||||
{chat_prompt}你正在群里聊天,现在请你读读之前的聊天记录，然后给出日常且口语化的回复，平淡一些，{mood_state}
|
||||
尽量简短一些。{keywords_reaction_prompt}请注意把握聊天内容，不要回复的太有条理，可以有个性。
|
||||
{chat_prompt}你正在群里聊天,现在请你读读之前的聊天记录，把握当前的话题，然后给出日常且简短的回复。
|
||||
最好一次对一个话题进行回复，免得啰嗦或者回复内容太乱。
|
||||
{keywords_reaction_prompt}
|
||||
请注意把握聊天内容。
|
||||
{reply_style}
|
||||
请注意不要输出多余内容(包括前后缀，冒号和引号，括号，表情等)，只输出一句回复内容就好。
|
||||
不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )。
|
||||
请注意不要输出多余内容(包括不必要的前后缀，冒号，括号，at或 @等 )，只输出发言内容就好。
|
||||
现在，你说：""",
|
||||
"replyer_prompt",
|
||||
)
|
||||
|
||||
Prompt(
|
||||
"""{knowledge_prompt}{tool_info_block}{extra_info_block}
|
||||
{expression_habits_block}{memory_retrieval}{jargon_explanation}
|
||||
|
||||
你正在和{sender_name}聊天，这是你们之前聊的内容:
|
||||
{time_block}
|
||||
{dialogue_prompt}
|
||||
|
||||
{reply_target_block}。
|
||||
{planner_reasoning}
|
||||
{identity}
|
||||
{chat_prompt}你正在和{sender_name}聊天,现在请你读读之前的聊天记录，然后给出日常且口语化的回复，平淡一些，{mood_state}
|
||||
尽量简短一些。{keywords_reaction_prompt}请注意把握聊天内容，不要回复的太有条理，可以有个性。
|
||||
{reply_style}
|
||||
请注意不要输出多余内容(包括前后缀，冒号和引号，括号，表情等)，只输出回复内容。
|
||||
{moderation_prompt}不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )。""",
|
||||
"private_replyer_prompt",
|
||||
)
|
||||
|
||||
Prompt(
|
||||
"""{knowledge_prompt}{tool_info_block}{extra_info_block}
|
||||
{expression_habits_block}{memory_retrieval}{jargon_explanation}
|
||||
|
||||
你正在和{sender_name}聊天，这是你们之前聊的内容:
|
||||
{time_block}
|
||||
{dialogue_prompt}
|
||||
|
||||
你现在想补充说明你刚刚自己的发言内容：{target}，原因是{reason}
|
||||
请你根据聊天内容，组织一条新回复。注意，{target} 是刚刚你自己的发言，你要在这基础上进一步发言，请按照你自己的角度来继续进行回复。注意保持上下文的连贯性。{mood_state}
|
||||
{identity}
|
||||
{chat_prompt}尽量简短一些。{keywords_reaction_prompt}请注意把握聊天内容，不要回复的太有条理，可以有个性。
|
||||
{reply_style}
|
||||
请注意不要输出多余内容(包括前后缀，冒号和引号，括号，表情等)，只输出回复内容。
|
||||
{moderation_prompt}不要输出多余内容(包括冒号和引号，括号，表情包，at或 @等 )。
|
||||
""",
|
||||
"private_replyer_self_prompt",
|
||||
)
|
||||
|
||||
@@ -120,7 +120,7 @@ def get_raw_msg_by_timestamp_with_chat(
|
||||
limit_mode: str = "latest",
|
||||
filter_bot=False,
|
||||
filter_command=False,
|
||||
filter_no_read_command=False,
|
||||
filter_intercept_message_level: Optional[int] = None,
|
||||
) -> List[DatabaseMessages]:
|
||||
"""获取在特定聊天从指定时间戳到指定时间戳的消息，按时间升序排序，返回消息列表
|
||||
limit: 限制返回的消息数量，0为不限制
|
||||
@@ -138,7 +138,7 @@ def get_raw_msg_by_timestamp_with_chat(
|
||||
limit_mode=limit_mode,
|
||||
filter_bot=filter_bot,
|
||||
filter_command=filter_command,
|
||||
filter_no_read_command=filter_no_read_command,
|
||||
filter_intercept_message_level=filter_intercept_message_level,
|
||||
)
|
||||
|
||||
|
||||
@@ -150,7 +150,7 @@ def get_raw_msg_by_timestamp_with_chat_inclusive(
|
||||
limit_mode: str = "latest",
|
||||
filter_bot=False,
|
||||
filter_command=False,
|
||||
filter_no_read_command=False,
|
||||
filter_intercept_message_level: Optional[int] = None,
|
||||
) -> List[DatabaseMessages]:
|
||||
"""获取在特定聊天从指定时间戳到指定时间戳的消息（包含边界），按时间升序排序，返回消息列表
|
||||
limit: 限制返回的消息数量，0为不限制
|
||||
@@ -167,7 +167,7 @@ def get_raw_msg_by_timestamp_with_chat_inclusive(
|
||||
limit_mode=limit_mode,
|
||||
filter_bot=filter_bot,
|
||||
filter_command=filter_command,
|
||||
filter_no_read_command=filter_no_read_command,
|
||||
filter_intercept_message_level=filter_intercept_message_level,
|
||||
)
|
||||
|
||||
|
||||
@@ -303,7 +303,7 @@ def get_raw_msg_before_timestamp(timestamp: float, limit: int = 0) -> List[Datab
|
||||
|
||||
|
||||
def get_raw_msg_before_timestamp_with_chat(
|
||||
chat_id: str, timestamp: float, limit: int = 0, filter_no_read_command: bool = False
|
||||
chat_id: str, timestamp: float, limit: int = 0, filter_intercept_message_level: Optional[int] = None
|
||||
) -> List[DatabaseMessages]:
|
||||
"""获取指定时间戳之前的消息，按时间升序排序，返回消息列表
|
||||
limit: 限制返回的消息数量，0为不限制
|
||||
@@ -311,7 +311,10 @@ def get_raw_msg_before_timestamp_with_chat(
|
||||
filter_query = {"chat_id": chat_id, "time": {"$lt": timestamp}}
|
||||
sort_order = [("time", 1)]
|
||||
return find_messages(
|
||||
message_filter=filter_query, sort=sort_order, limit=limit, filter_no_read_command=filter_no_read_command
|
||||
message_filter=filter_query,
|
||||
sort=sort_order,
|
||||
limit=limit,
|
||||
filter_intercept_message_level=filter_intercept_message_level,
|
||||
)
|
||||
|
||||
|
||||
|
||||
@@ -1,362 +0,0 @@
|
||||
"""
|
||||
记忆遗忘任务
|
||||
每5分钟进行一次遗忘检查，根据不同的遗忘阶段删除记忆
|
||||
"""
|
||||
|
||||
import time
|
||||
import random
|
||||
from typing import List
|
||||
|
||||
from src.common.logger import get_logger
|
||||
from src.common.database.database_model import ChatHistory
|
||||
from src.manager.async_task_manager import AsyncTask
|
||||
|
||||
logger = get_logger("memory_forget_task")
|
||||
|
||||
|
||||
class MemoryForgetTask(AsyncTask):
|
||||
"""记忆遗忘任务，每5分钟执行一次"""
|
||||
|
||||
def __init__(self):
|
||||
# 每5分钟执行一次（300秒）
|
||||
super().__init__(task_name="Memory Forget Task", wait_before_start=0, run_interval=300)
|
||||
|
||||
async def run(self):
|
||||
"""执行遗忘检查"""
|
||||
try:
|
||||
current_time = time.time()
|
||||
# logger.info("[记忆遗忘] 开始遗忘检查...")
|
||||
|
||||
# 执行4个阶段的遗忘检查
|
||||
await self._forget_stage_1(current_time)
|
||||
await self._forget_stage_2(current_time)
|
||||
await self._forget_stage_3(current_time)
|
||||
await self._forget_stage_4(current_time)
|
||||
|
||||
# logger.info("[记忆遗忘] 遗忘检查完成")
|
||||
except Exception as e:
|
||||
logger.error(f"[记忆遗忘] 执行遗忘检查时出错: {e}", exc_info=True)
|
||||
|
||||
async def _forget_stage_1(self, current_time: float):
|
||||
"""
|
||||
第一次遗忘检查：
|
||||
搜集所有：记忆还未被遗忘检查过（forget_times=0），且已经是30分钟之外的记忆
|
||||
取count最高25%和最低25%，删除，然后标记被遗忘检查次数为1
|
||||
"""
|
||||
try:
|
||||
# 30分钟 = 1800秒
|
||||
time_threshold = current_time - 1800
|
||||
|
||||
# 查询符合条件的记忆：forget_times=0 且 end_time < time_threshold
|
||||
candidates = list(
|
||||
ChatHistory.select().where((ChatHistory.forget_times == 0) & (ChatHistory.end_time < time_threshold))
|
||||
)
|
||||
|
||||
if not candidates:
|
||||
logger.debug("[记忆遗忘-阶段1] 没有符合条件的记忆")
|
||||
return
|
||||
|
||||
logger.info(f"[记忆遗忘-阶段1] 找到 {len(candidates)} 条符合条件的记忆")
|
||||
|
||||
# 按count排序
|
||||
candidates.sort(key=lambda x: x.count, reverse=True)
|
||||
|
||||
# 计算要删除的数量（最高25%和最低25%）
|
||||
total_count = len(candidates)
|
||||
delete_count = int(total_count * 0.25) # 25%
|
||||
|
||||
if delete_count == 0:
|
||||
logger.debug("[记忆遗忘-阶段1] 删除数量为0，跳过")
|
||||
return
|
||||
|
||||
# 选择要删除的记录（处理count相同的情况：随机选择）
|
||||
to_delete = []
|
||||
to_delete.extend(self._handle_same_count_random(candidates, delete_count, "high"))
|
||||
to_delete.extend(self._handle_same_count_random(candidates, delete_count, "low"))
|
||||
|
||||
# 去重（避免重复删除），使用id去重
|
||||
seen_ids = set()
|
||||
unique_to_delete = []
|
||||
for record in to_delete:
|
||||
if record.id not in seen_ids:
|
||||
seen_ids.add(record.id)
|
||||
unique_to_delete.append(record)
|
||||
to_delete = unique_to_delete
|
||||
|
||||
# 删除记录并更新forget_times
|
||||
deleted_count = 0
|
||||
for record in to_delete:
|
||||
try:
|
||||
record.delete_instance()
|
||||
deleted_count += 1
|
||||
except Exception as e:
|
||||
logger.error(f"[记忆遗忘-阶段1] 删除记录失败: {e}")
|
||||
|
||||
# 更新剩余记录的forget_times为1
|
||||
to_delete_ids = {r.id for r in to_delete}
|
||||
remaining = [r for r in candidates if r.id not in to_delete_ids]
|
||||
if remaining:
|
||||
# 批量更新
|
||||
ids_to_update = [r.id for r in remaining]
|
||||
ChatHistory.update(forget_times=1).where(ChatHistory.id.in_(ids_to_update)).execute()
|
||||
|
||||
logger.info(
|
||||
f"[记忆遗忘-阶段1] 完成：删除了 {deleted_count} 条记忆，更新了 {len(remaining)} 条记忆的forget_times为1"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[记忆遗忘-阶段1] 执行失败: {e}", exc_info=True)
|
||||
|
||||
async def _forget_stage_2(self, current_time: float):
|
||||
"""
|
||||
第二次遗忘检查：
|
||||
搜集所有：记忆遗忘检查为1，且已经是8小时之外的记忆
|
||||
取count最高7%和最低7%，删除，然后标记被遗忘检查次数为2
|
||||
"""
|
||||
try:
|
||||
# 8小时 = 28800秒
|
||||
time_threshold = current_time - 28800
|
||||
|
||||
# 查询符合条件的记忆：forget_times=1 且 end_time < time_threshold
|
||||
candidates = list(
|
||||
ChatHistory.select().where((ChatHistory.forget_times == 1) & (ChatHistory.end_time < time_threshold))
|
||||
)
|
||||
|
||||
if not candidates:
|
||||
logger.debug("[记忆遗忘-阶段2] 没有符合条件的记忆")
|
||||
return
|
||||
|
||||
logger.info(f"[记忆遗忘-阶段2] 找到 {len(candidates)} 条符合条件的记忆")
|
||||
|
||||
# 按count排序
|
||||
candidates.sort(key=lambda x: x.count, reverse=True)
|
||||
|
||||
# 计算要删除的数量（最高7%和最低7%）
|
||||
total_count = len(candidates)
|
||||
delete_count = int(total_count * 0.07) # 7%
|
||||
|
||||
if delete_count == 0:
|
||||
logger.debug("[记忆遗忘-阶段2] 删除数量为0，跳过")
|
||||
return
|
||||
|
||||
# 选择要删除的记录
|
||||
to_delete = []
|
||||
to_delete.extend(self._handle_same_count_random(candidates, delete_count, "high"))
|
||||
to_delete.extend(self._handle_same_count_random(candidates, delete_count, "low"))
|
||||
|
||||
# 去重
|
||||
to_delete = list(set(to_delete))
|
||||
|
||||
# 删除记录
|
||||
deleted_count = 0
|
||||
for record in to_delete:
|
||||
try:
|
||||
record.delete_instance()
|
||||
deleted_count += 1
|
||||
except Exception as e:
|
||||
logger.error(f"[记忆遗忘-阶段2] 删除记录失败: {e}")
|
||||
|
||||
# 更新剩余记录的forget_times为2
|
||||
to_delete_ids = {r.id for r in to_delete}
|
||||
remaining = [r for r in candidates if r.id not in to_delete_ids]
|
||||
if remaining:
|
||||
ids_to_update = [r.id for r in remaining]
|
||||
ChatHistory.update(forget_times=2).where(ChatHistory.id.in_(ids_to_update)).execute()
|
||||
|
||||
logger.info(
|
||||
f"[记忆遗忘-阶段2] 完成：删除了 {deleted_count} 条记忆，更新了 {len(remaining)} 条记忆的forget_times为2"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[记忆遗忘-阶段2] 执行失败: {e}", exc_info=True)
|
||||
|
||||
async def _forget_stage_3(self, current_time: float):
|
||||
"""
|
||||
第三次遗忘检查：
|
||||
搜集所有：记忆遗忘检查为2，且已经是48小时之外的记忆
|
||||
取count最高5%和最低5%，删除，然后标记被遗忘检查次数为3
|
||||
"""
|
||||
try:
|
||||
# 48小时 = 172800秒
|
||||
time_threshold = current_time - 172800
|
||||
|
||||
# 查询符合条件的记忆：forget_times=2 且 end_time < time_threshold
|
||||
candidates = list(
|
||||
ChatHistory.select().where((ChatHistory.forget_times == 2) & (ChatHistory.end_time < time_threshold))
|
||||
)
|
||||
|
||||
if not candidates:
|
||||
logger.debug("[记忆遗忘-阶段3] 没有符合条件的记忆")
|
||||
return
|
||||
|
||||
logger.info(f"[记忆遗忘-阶段3] 找到 {len(candidates)} 条符合条件的记忆")
|
||||
|
||||
# 按count排序
|
||||
candidates.sort(key=lambda x: x.count, reverse=True)
|
||||
|
||||
# 计算要删除的数量（最高5%和最低5%）
|
||||
total_count = len(candidates)
|
||||
delete_count = int(total_count * 0.05) # 5%
|
||||
|
||||
if delete_count == 0:
|
||||
logger.debug("[记忆遗忘-阶段3] 删除数量为0，跳过")
|
||||
return
|
||||
|
||||
# 选择要删除的记录
|
||||
to_delete = []
|
||||
to_delete.extend(self._handle_same_count_random(candidates, delete_count, "high"))
|
||||
to_delete.extend(self._handle_same_count_random(candidates, delete_count, "low"))
|
||||
|
||||
# 去重
|
||||
to_delete = list(set(to_delete))
|
||||
|
||||
# 删除记录
|
||||
deleted_count = 0
|
||||
for record in to_delete:
|
||||
try:
|
||||
record.delete_instance()
|
||||
deleted_count += 1
|
||||
except Exception as e:
|
||||
logger.error(f"[记忆遗忘-阶段3] 删除记录失败: {e}")
|
||||
|
||||
# 更新剩余记录的forget_times为3
|
||||
to_delete_ids = {r.id for r in to_delete}
|
||||
remaining = [r for r in candidates if r.id not in to_delete_ids]
|
||||
if remaining:
|
||||
ids_to_update = [r.id for r in remaining]
|
||||
ChatHistory.update(forget_times=3).where(ChatHistory.id.in_(ids_to_update)).execute()
|
||||
|
||||
logger.info(
|
||||
f"[记忆遗忘-阶段3] 完成：删除了 {deleted_count} 条记忆，更新了 {len(remaining)} 条记忆的forget_times为3"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[记忆遗忘-阶段3] 执行失败: {e}", exc_info=True)
|
||||
|
||||
async def _forget_stage_4(self, current_time: float):
|
||||
"""
|
||||
第四次遗忘检查：
|
||||
搜集所有：记忆遗忘检查为3，且已经是7天之外的记忆
|
||||
取count最高2%和最低2%，删除，然后标记被遗忘检查次数为4
|
||||
"""
|
||||
try:
|
||||
# 7天 = 604800秒
|
||||
time_threshold = current_time - 604800
|
||||
|
||||
# 查询符合条件的记忆：forget_times=3 且 end_time < time_threshold
|
||||
candidates = list(
|
||||
ChatHistory.select().where((ChatHistory.forget_times == 3) & (ChatHistory.end_time < time_threshold))
|
||||
)
|
||||
|
||||
if not candidates:
|
||||
logger.debug("[记忆遗忘-阶段4] 没有符合条件的记忆")
|
||||
return
|
||||
|
||||
logger.info(f"[记忆遗忘-阶段4] 找到 {len(candidates)} 条符合条件的记忆")
|
||||
|
||||
# 按count排序
|
||||
candidates.sort(key=lambda x: x.count, reverse=True)
|
||||
|
||||
# 计算要删除的数量（最高2%和最低2%）
|
||||
total_count = len(candidates)
|
||||
delete_count = int(total_count * 0.02) # 2%
|
||||
|
||||
if delete_count == 0:
|
||||
logger.debug("[记忆遗忘-阶段4] 删除数量为0，跳过")
|
||||
return
|
||||
|
||||
# 选择要删除的记录
|
||||
to_delete = []
|
||||
to_delete.extend(self._handle_same_count_random(candidates, delete_count, "high"))
|
||||
to_delete.extend(self._handle_same_count_random(candidates, delete_count, "low"))
|
||||
|
||||
# 去重
|
||||
to_delete = list(set(to_delete))
|
||||
|
||||
# 删除记录
|
||||
deleted_count = 0
|
||||
for record in to_delete:
|
||||
try:
|
||||
record.delete_instance()
|
||||
deleted_count += 1
|
||||
except Exception as e:
|
||||
logger.error(f"[记忆遗忘-阶段4] 删除记录失败: {e}")
|
||||
|
||||
# 更新剩余记录的forget_times为4
|
||||
to_delete_ids = {r.id for r in to_delete}
|
||||
remaining = [r for r in candidates if r.id not in to_delete_ids]
|
||||
if remaining:
|
||||
ids_to_update = [r.id for r in remaining]
|
||||
ChatHistory.update(forget_times=4).where(ChatHistory.id.in_(ids_to_update)).execute()
|
||||
|
||||
logger.info(
|
||||
f"[记忆遗忘-阶段4] 完成：删除了 {deleted_count} 条记忆，更新了 {len(remaining)} 条记忆的forget_times为4"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[记忆遗忘-阶段4] 执行失败: {e}", exc_info=True)
|
||||
|
||||
def _handle_same_count_random(
|
||||
self, candidates: List[ChatHistory], delete_count: int, mode: str
|
||||
) -> List[ChatHistory]:
|
||||
"""
|
||||
处理count相同的情况，随机选择要删除的记录
|
||||
|
||||
Args:
|
||||
candidates: 候选记录列表（已按count排序）
|
||||
delete_count: 要删除的数量
|
||||
mode: "high" 表示选择最高count的记录，"low" 表示选择最低count的记录
|
||||
|
||||
Returns:
|
||||
要删除的记录列表
|
||||
"""
|
||||
if not candidates or delete_count == 0:
|
||||
return []
|
||||
|
||||
to_delete = []
|
||||
|
||||
if mode == "high":
|
||||
# 从最高count开始选择
|
||||
start_idx = 0
|
||||
while start_idx < len(candidates) and len(to_delete) < delete_count:
|
||||
# 找到所有count相同的记录
|
||||
current_count = candidates[start_idx].count
|
||||
same_count_records = []
|
||||
idx = start_idx
|
||||
while idx < len(candidates) and candidates[idx].count == current_count:
|
||||
same_count_records.append(candidates[idx])
|
||||
idx += 1
|
||||
|
||||
# 如果相同count的记录数量 <= 还需要删除的数量，全部选择
|
||||
needed = delete_count - len(to_delete)
|
||||
if len(same_count_records) <= needed:
|
||||
to_delete.extend(same_count_records)
|
||||
else:
|
||||
# 随机选择需要的数量
|
||||
to_delete.extend(random.sample(same_count_records, needed))
|
||||
|
||||
start_idx = idx
|
||||
|
||||
else: # mode == "low"
|
||||
# 从最低count开始选择
|
||||
start_idx = len(candidates) - 1
|
||||
while start_idx >= 0 and len(to_delete) < delete_count:
|
||||
# 找到所有count相同的记录
|
||||
current_count = candidates[start_idx].count
|
||||
same_count_records = []
|
||||
idx = start_idx
|
||||
while idx >= 0 and candidates[idx].count == current_count:
|
||||
same_count_records.append(candidates[idx])
|
||||
idx -= 1
|
||||
|
||||
# 如果相同count的记录数量 <= 还需要删除的数量，全部选择
|
||||
needed = delete_count - len(to_delete)
|
||||
if len(same_count_records) <= needed:
|
||||
to_delete.extend(same_count_records)
|
||||
else:
|
||||
# 随机选择需要的数量
|
||||
to_delete.extend(random.sample(same_count_records, needed))
|
||||
|
||||
start_idx = idx
|
||||
|
||||
return to_delete
|
||||
@@ -8,7 +8,7 @@ from typing import Any, Dict, Tuple, List
|
||||
|
||||
from src.common.logger import get_logger
|
||||
from src.common.database.database import db
|
||||
from src.common.database.database_model import OnlineTime, LLMUsage, Messages
|
||||
from src.common.database.database_model import OnlineTime, LLMUsage, Messages, ActionRecords
|
||||
from src.manager.async_task_manager import AsyncTask
|
||||
from src.manager.local_store_manager import local_storage
|
||||
from src.config.config import global_config
|
||||
@@ -505,13 +505,6 @@ class StatisticOutputTask(AsyncTask):
|
||||
for period_key, _ in collect_period
|
||||
}
|
||||
|
||||
# 获取bot的QQ账号
|
||||
bot_qq_account = (
|
||||
str(global_config.bot.qq_account)
|
||||
if hasattr(global_config, "bot") and hasattr(global_config.bot, "qq_account")
|
||||
else ""
|
||||
)
|
||||
|
||||
query_start_timestamp = collect_period[-1][1].timestamp() # Messages.time is a DoubleField (timestamp)
|
||||
for message in Messages.select().where(Messages.time >= query_start_timestamp): # type: ignore
|
||||
message_time_ts = message.time # This is a float timestamp
|
||||
@@ -537,7 +530,7 @@ class StatisticOutputTask(AsyncTask):
|
||||
if not chat_id: # Should not happen if above logic is correct
|
||||
continue
|
||||
|
||||
# Update name_mapping
|
||||
# Update name_mapping（仅用于展示聊天名称）
|
||||
try:
|
||||
if chat_id in self.name_mapping:
|
||||
if chat_name != self.name_mapping[chat_id][0] and message_time_ts > self.name_mapping[chat_id][1]:
|
||||
@@ -549,19 +542,30 @@ class StatisticOutputTask(AsyncTask):
|
||||
# 重置为正确的格式
|
||||
self.name_mapping[chat_id] = (chat_name, message_time_ts)
|
||||
|
||||
# 检查是否是bot发送的消息（回复）
|
||||
is_bot_reply = False
|
||||
if bot_qq_account and message.user_id == bot_qq_account:
|
||||
is_bot_reply = True
|
||||
|
||||
for idx, (_, period_start_dt) in enumerate(collect_period):
|
||||
if message_time_ts >= period_start_dt.timestamp():
|
||||
for period_key, _ in collect_period[idx:]:
|
||||
stats[period_key][TOTAL_MSG_CNT] += 1
|
||||
stats[period_key][MSG_CNT_BY_CHAT][chat_id] += 1
|
||||
if is_bot_reply:
|
||||
stats[period_key][TOTAL_REPLY_CNT] += 1
|
||||
break
|
||||
|
||||
# 使用 ActionRecords 中的 reply 动作次数作为回复数基准
|
||||
try:
|
||||
action_query_start_timestamp = collect_period[-1][1].timestamp()
|
||||
for action in ActionRecords.select().where(ActionRecords.time >= action_query_start_timestamp): # type: ignore
|
||||
# 仅统计已完成的 reply 动作
|
||||
if action.action_name != "reply" or not action.action_done:
|
||||
continue
|
||||
|
||||
action_time_ts = action.time
|
||||
for idx, (_, period_start_dt) in enumerate(collect_period):
|
||||
if action_time_ts >= period_start_dt.timestamp():
|
||||
for period_key, _ in collect_period[idx:]:
|
||||
stats[period_key][TOTAL_REPLY_CNT] += 1
|
||||
break
|
||||
except Exception as e:
|
||||
logger.warning(f"统计 reply 动作次数失败，将回复数视为 0，错误信息：{e}")
|
||||
|
||||
return stats
|
||||
|
||||
def _collect_all_statistics(self, now: datetime) -> Dict[str, Dict[str, Any]]:
|
||||
@@ -742,7 +746,7 @@ class StatisticOutputTask(AsyncTask):
|
||||
data_fmt = "{:<32} {:>10} {:>12} {:>12} {:>12} {:>9.2f}¥ {:>10.1f} {:>10.1f} {:>12} {:>12}"
|
||||
|
||||
total_replies = stats.get(TOTAL_REPLY_CNT, 0)
|
||||
|
||||
|
||||
output = [
|
||||
"按模型分类统计:",
|
||||
" 模型名称 调用次数 输入Token 输出Token Token总量 累计花费 平均耗时(秒) 标准差(秒) 每次回复平均调用次数 每次回复平均Token数",
|
||||
@@ -755,11 +759,11 @@ class StatisticOutputTask(AsyncTask):
|
||||
cost = stats[COST_BY_MODEL][model_name]
|
||||
avg_time_cost = stats[AVG_TIME_COST_BY_MODEL][model_name]
|
||||
std_time_cost = stats[STD_TIME_COST_BY_MODEL][model_name]
|
||||
|
||||
|
||||
# 计算每次回复平均值
|
||||
avg_count_per_reply = count / total_replies if total_replies > 0 else 0.0
|
||||
avg_tokens_per_reply = tokens / total_replies if total_replies > 0 else 0.0
|
||||
|
||||
|
||||
# 格式化大数字
|
||||
formatted_count = _format_large_number(count)
|
||||
formatted_in_tokens = _format_large_number(in_tokens)
|
||||
@@ -767,7 +771,7 @@ class StatisticOutputTask(AsyncTask):
|
||||
formatted_tokens = _format_large_number(tokens)
|
||||
formatted_avg_count = _format_large_number(avg_count_per_reply) if total_replies > 0 else "N/A"
|
||||
formatted_avg_tokens = _format_large_number(avg_tokens_per_reply) if total_replies > 0 else "N/A"
|
||||
|
||||
|
||||
output.append(
|
||||
data_fmt.format(
|
||||
name,
|
||||
@@ -796,7 +800,7 @@ class StatisticOutputTask(AsyncTask):
|
||||
data_fmt = "{:<32} {:>10} {:>12} {:>12} {:>12} {:>9.2f}¥ {:>10.1f} {:>10.1f} {:>12} {:>12}"
|
||||
|
||||
total_replies = stats.get(TOTAL_REPLY_CNT, 0)
|
||||
|
||||
|
||||
output = [
|
||||
"按模块分类统计:",
|
||||
" 模块名称 调用次数 输入Token 输出Token Token总量 累计花费 平均耗时(秒) 标准差(秒) 每次回复平均调用次数 每次回复平均Token数",
|
||||
@@ -809,11 +813,11 @@ class StatisticOutputTask(AsyncTask):
|
||||
cost = stats[COST_BY_MODULE][module_name]
|
||||
avg_time_cost = stats[AVG_TIME_COST_BY_MODULE][module_name]
|
||||
std_time_cost = stats[STD_TIME_COST_BY_MODULE][module_name]
|
||||
|
||||
|
||||
# 计算每次回复平均值
|
||||
avg_count_per_reply = count / total_replies if total_replies > 0 else 0.0
|
||||
avg_tokens_per_reply = tokens / total_replies if total_replies > 0 else 0.0
|
||||
|
||||
|
||||
# 格式化大数字
|
||||
formatted_count = _format_large_number(count)
|
||||
formatted_in_tokens = _format_large_number(in_tokens)
|
||||
@@ -821,7 +825,7 @@ class StatisticOutputTask(AsyncTask):
|
||||
formatted_tokens = _format_large_number(tokens)
|
||||
formatted_avg_count = _format_large_number(avg_count_per_reply) if total_replies > 0 else "N/A"
|
||||
formatted_avg_tokens = _format_large_number(avg_tokens_per_reply) if total_replies > 0 else "N/A"
|
||||
|
||||
|
||||
output.append(
|
||||
data_fmt.format(
|
||||
name,
|
||||
|
||||
@@ -4,6 +4,8 @@ import time
|
||||
import jieba
|
||||
import json
|
||||
import ast
|
||||
import os
|
||||
from datetime import datetime
|
||||
|
||||
from typing import Optional, Tuple, List, TYPE_CHECKING
|
||||
|
||||
@@ -196,21 +198,54 @@ def split_into_sentences_w_remove_punctuation(text: str) -> list[str]:
|
||||
List[str]: 分割和合并后的句子列表
|
||||
"""
|
||||
# 预处理：处理多余的换行符
|
||||
# 1. 将连续的换行符替换为单个换行符
|
||||
# 1. 将连续的换行符替换为单个换行符（保留换行符用于分割）
|
||||
text = re.sub(r"\n\s*\n+", "\n", text)
|
||||
# 2. 处理换行符和其他分隔符的组合
|
||||
text = re.sub(r"\n\s*([，,。;\s])", r"\1", text)
|
||||
text = re.sub(r"([，,。;\s])\s*\n", r"\1", text)
|
||||
# 2. 处理换行符和其他分隔符的组合（保留换行符，删除其他分隔符）
|
||||
text = re.sub(r"\n\s*([，,。;\s])", r"\n\1", text)
|
||||
text = re.sub(r"([，,。;\s])\s*\n", r"\1\n", text)
|
||||
|
||||
# 处理两个汉字中间的换行符
|
||||
text = re.sub(r"([\u4e00-\u9fff])\n([\u4e00-\u9fff])", r"\1。\2", text)
|
||||
# 处理两个汉字中间的换行符（保留换行符，不替换为句号，让换行符强制分割）
|
||||
# text = re.sub(r"([\u4e00-\u9fff])\n([\u4e00-\u9fff])", r"\1。\2", text) # 注释掉，保留换行符用于分割
|
||||
|
||||
len_text = len(text)
|
||||
if len_text < 3:
|
||||
return list(text) if random.random() < 0.01 else [text]
|
||||
|
||||
# 定义分隔符
|
||||
separators = {"，", ",", " ", "。", ";"}
|
||||
# 先标记哪些位置位于成对引号内部，避免在引号内部进行句子分割
|
||||
# 支持的引号包括：中英文单/双引号和常见中文书名号/引号
|
||||
quote_chars = {
|
||||
'"',
|
||||
"'",
|
||||
"“",
|
||||
"”",
|
||||
"‘",
|
||||
"’",
|
||||
"「",
|
||||
"」",
|
||||
"『",
|
||||
"』",
|
||||
}
|
||||
inside_quote = [False] * len_text
|
||||
in_quote = False
|
||||
current_quote_char = ""
|
||||
for idx, ch in enumerate(text):
|
||||
if ch in quote_chars:
|
||||
# 遇到引号时切换状态（英文引号本身开闭相同，用同一个字符表示）
|
||||
if not in_quote:
|
||||
in_quote = True
|
||||
current_quote_char = ch
|
||||
inside_quote[idx] = False
|
||||
else:
|
||||
# 只有遇到同一类引号才视为关闭
|
||||
if ch == current_quote_char or ch in {'"', "'"} and current_quote_char in {'"', "'"}:
|
||||
in_quote = False
|
||||
current_quote_char = ""
|
||||
inside_quote[idx] = False
|
||||
else:
|
||||
inside_quote[idx] = in_quote
|
||||
|
||||
# 定义分隔符（包含换行符）
|
||||
separators = {"，", ",", " ", "。", ";", "\n"}
|
||||
segments = []
|
||||
current_segment = ""
|
||||
|
||||
@@ -219,24 +254,42 @@ def split_into_sentences_w_remove_punctuation(text: str) -> list[str]:
|
||||
while i < len(text):
|
||||
char = text[i]
|
||||
if char in separators:
|
||||
# 检查分割条件：如果空格左右都是英文字母、数字，或数字和英文之间，则不分割（仅对空格应用此规则）
|
||||
can_split = True
|
||||
if 0 < i < len(text) - 1:
|
||||
prev_char = text[i - 1]
|
||||
next_char = text[i + 1]
|
||||
# 只对空格应用"不分割数字和数字、数字和英文、英文和数字、英文和英文之间的空格"规则
|
||||
if char == " ":
|
||||
prev_is_alnum = prev_char.isdigit() or is_english_letter(prev_char)
|
||||
next_is_alnum = next_char.isdigit() or is_english_letter(next_char)
|
||||
if prev_is_alnum and next_is_alnum:
|
||||
can_split = False
|
||||
# 引号内部一律不作为分割点（包括换行）
|
||||
if inside_quote[i]:
|
||||
can_split = False
|
||||
else:
|
||||
# 换行符在不在引号内时都强制分割
|
||||
if char == "\n":
|
||||
can_split = True
|
||||
else:
|
||||
# 检查分割条件
|
||||
can_split = True
|
||||
# 检查分隔符左右是否有冒号（中英文），如果有则不分割
|
||||
if i > 0:
|
||||
prev_char = text[i - 1]
|
||||
if prev_char in {":", "："}:
|
||||
can_split = False
|
||||
if i < len(text) - 1:
|
||||
next_char = text[i + 1]
|
||||
if next_char in {":", "："}:
|
||||
can_split = False
|
||||
|
||||
# 如果左右没有冒号，再检查空格的特殊情况
|
||||
if can_split and char == " " and i > 0 and i < len(text) - 1:
|
||||
prev_char = text[i - 1]
|
||||
next_char = text[i + 1]
|
||||
# 不分割数字和数字、数字和英文、英文和数字、英文和英文之间的空格
|
||||
prev_is_alnum = prev_char.isdigit() or is_english_letter(prev_char)
|
||||
next_is_alnum = next_char.isdigit() or is_english_letter(next_char)
|
||||
if prev_is_alnum and next_is_alnum:
|
||||
can_split = False
|
||||
|
||||
if can_split:
|
||||
# 只有当当前段不为空时才添加
|
||||
if current_segment:
|
||||
segments.append((current_segment, char))
|
||||
# 如果当前段为空，但分隔符是空格，则也添加一个空段（保留空格）
|
||||
elif char == " ":
|
||||
# 如果当前段为空，但分隔符是空格或换行符，则也添加一个空段（保留分隔符）
|
||||
elif char in {" ", "\n"}:
|
||||
segments.append(("", char))
|
||||
current_segment = ""
|
||||
else:
|
||||
@@ -641,6 +694,42 @@ def get_chat_type_and_target_info(chat_id: str) -> Tuple[bool, Optional["TargetP
|
||||
return is_group_chat, chat_target_info
|
||||
|
||||
|
||||
def record_replyer_action_temp(chat_id: str, reason: str, think_level: int) -> None:
|
||||
"""
|
||||
临时记录replyer动作被选择的信息（仅群聊）
|
||||
|
||||
Args:
|
||||
chat_id: 聊天ID
|
||||
reason: 选择理由
|
||||
think_level: 思考深度等级
|
||||
"""
|
||||
try:
|
||||
# 确保data/temp目录存在
|
||||
temp_dir = "data/temp"
|
||||
os.makedirs(temp_dir, exist_ok=True)
|
||||
|
||||
# 创建记录数据
|
||||
record_data = {
|
||||
"chat_id": chat_id,
|
||||
"reason": reason,
|
||||
"think_level": think_level,
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
}
|
||||
|
||||
# 生成文件名（使用时间戳避免冲突）
|
||||
timestamp_str = datetime.now().strftime("%Y%m%d_%H%M%S_%f")
|
||||
filename = f"replyer_action_{timestamp_str}.json"
|
||||
filepath = os.path.join(temp_dir, filename)
|
||||
|
||||
# 写入文件
|
||||
with open(filepath, "w", encoding="utf-8") as f:
|
||||
json.dump(record_data, f, ensure_ascii=False, indent=2)
|
||||
|
||||
logger.debug(f"已记录replyer动作选择: chat_id={chat_id}, think_level={think_level}")
|
||||
except Exception as e:
|
||||
logger.warning(f"记录replyer动作选择失败: {e}")
|
||||
|
||||
|
||||
def assign_message_ids(messages: List[DatabaseMessages]) -> List[Tuple[str, DatabaseMessages]]:
|
||||
"""
|
||||
为消息列表中的每个消息分配唯一的简短随机ID
|
||||
|
||||
@@ -130,12 +130,10 @@ class ImageManager:
|
||||
try:
|
||||
# 清理Images表中type为emoji的记录
|
||||
deleted_images = Images.delete().where(Images.type == "emoji").execute()
|
||||
|
||||
|
||||
# 清理ImageDescriptions表中type为emoji的记录
|
||||
deleted_descriptions = (
|
||||
ImageDescriptions.delete().where(ImageDescriptions.type == "emoji").execute()
|
||||
)
|
||||
|
||||
deleted_descriptions = ImageDescriptions.delete().where(ImageDescriptions.type == "emoji").execute()
|
||||
|
||||
total_deleted = deleted_images + deleted_descriptions
|
||||
if total_deleted > 0:
|
||||
logger.info(
|
||||
@@ -166,7 +164,7 @@ class ImageManager:
|
||||
|
||||
async def _save_emoji_file_if_needed(self, image_base64: str, image_hash: str, image_format: str) -> None:
|
||||
"""如果启用了steal_emoji且表情包未注册，保存文件到data/emoji目录
|
||||
|
||||
|
||||
Args:
|
||||
image_base64: 图片的base64编码
|
||||
image_hash: 图片的MD5哈希值
|
||||
@@ -174,7 +172,7 @@ class ImageManager:
|
||||
"""
|
||||
if not global_config.emoji.steal_emoji:
|
||||
return
|
||||
|
||||
|
||||
try:
|
||||
from src.chat.emoji_system.emoji_manager import EMOJI_DIR
|
||||
from src.chat.emoji_system.emoji_manager import get_emoji_manager
|
||||
@@ -236,12 +234,16 @@ class ImageManager:
|
||||
# 优先使用情感标签，如果没有则使用详细描述
|
||||
result_text = ""
|
||||
if cache_record.emotion_tags:
|
||||
logger.info(f"[缓存命中] 使用EmojiDescriptionCache表中的情感标签: {cache_record.emotion_tags[:50]}...")
|
||||
logger.info(
|
||||
f"[缓存命中] 使用EmojiDescriptionCache表中的情感标签: {cache_record.emotion_tags[:50]}..."
|
||||
)
|
||||
result_text = f"[表情包：{cache_record.emotion_tags}]"
|
||||
elif cache_record.description:
|
||||
logger.info(f"[缓存命中] 使用EmojiDescriptionCache表中的描述: {cache_record.description[:50]}...")
|
||||
logger.info(
|
||||
f"[缓存命中] 使用EmojiDescriptionCache表中的描述: {cache_record.description[:50]}..."
|
||||
)
|
||||
result_text = f"[表情包：{cache_record.description}]"
|
||||
|
||||
|
||||
# 即使缓存命中，如果启用了steal_emoji，也检查是否需要保存文件
|
||||
if result_text:
|
||||
await self._save_emoji_file_if_needed(image_base64, image_hash, image_format)
|
||||
|
||||
Reference in New Issue
Block a user