0.6.2的意愿文件

src/plugins/willing/mode_llmcheck.py

@@ -1,68 +1,87 @@
+"""
+llmcheck 模式：
+此模式的一些参数不会在配置文件中显示，要修改请在可变参数下修改
+此模式的特点：
+1.在群聊内的连续对话场景下，使用大语言模型来判断回复概率
+2.非连续对话场景,使用mxp模式的意愿管理器(可另外配置)
+3.默认配置的是model_v3,当前参数适用于deepseek-v3-0324
+
+继承自其他模式,实质上仅重写get_reply_probability方法,未来可能重构成一个插件,可方便地组装到其他意愿模式上。
+目前的使用方式是拓展到其他意愿管理模式
+
+"""
 import time
 from loguru import logger
-from ..schedule.schedule_generator import bot_schedule
 from ..models.utils_model import LLM_request
-
 from ..config.config import global_config
 from ..chat.chat_stream import ChatStream
-from .mode_classical import WillingManager
 from ..chat.utils import get_recent_group_detailed_plain_text
-
-
+from .willing_manager import BaseWillingManager
+from .mode_mxp import MxpWillingManager
 import re
-from src.common.logger import get_module_logger, CHAT_STYLE_CONFIG, LogConfig
+from functools import wraps
 
-# 定义日志配置
-chat_config = LogConfig(
-    # 使用消息发送专用样式
-    console_format=CHAT_STYLE_CONFIG["console_format"],
-    file_format=CHAT_STYLE_CONFIG["file_format"],
-)
 
-# 配置主程序日志格式
-logger = get_module_logger("llm_willing", config=chat_config)
+def is_continuous_chat(self, message_id: str):
+    # 判断是否是连续对话，出于成本考虑，默认限制5条
+    willing_info = self.ongoing_messages[message_id]
+    chat_id = willing_info.chat_id
+    group_info = willing_info.chat_id
+    config = self.global_config
+    length = 5 
+    if chat_id:
+        chat_talking_text = get_recent_group_detailed_plain_text(
+            chat_id, limit=length, combine=True
+        )
+        if group_info:
+            if str(config.BOT_QQ) in chat_talking_text:
+                return True
+            else:
+                return False
+    return False
 
-class WillingManager(WillingManager):
+def llmcheck_decorator(trigger_condition_func):
+    def decorator(func):
+        @wraps(func)
+        def wrapper(self, message_id: str):
+            if trigger_condition_func(self, message_id):
+                # 满足条件，走llm流程
+                return self.get_llmreply_probability(message_id)
+            else:
+                # 不满足条件，走默认流程
+                return func(self, message_id)
+        return wrapper
+    return decorator
+
+
+class LlmcheckWillingManager(MxpWillingManager):
 
     def __init__(self):
         super().__init__()
         self.model_v3 = LLM_request(model=global_config.llm_normal, temperature=0.3)
 
-    async def change_reply_willing_received(self, chat_stream: ChatStream, is_mentioned_bot: bool = False, config=None,
-                                            is_emoji: bool = False, interested_rate: float = 0, sender_id: str = None,
-                                            **kwargs) -> float:
-        stream_id = chat_stream.stream_id
-        if chat_stream.group_info and config:
-            if chat_stream.group_info.group_id not in config.talk_allowed_groups:
+
+
+    async def get_llmreply_probability(self, message_id: str):
+        message_info = self.ongoing_messages[message_id]
+        chat_id = message_info.chat_id
+        config = self.global_config
+        # 获取信息的长度
+        length = 5
+        if message_info.group_info and config:
+            if message_info.group_info.group_id not in config.talk_allowed_groups:
                 reply_probability = 0
                 return reply_probability
 
         current_date = time.strftime("%Y-%m-%d", time.localtime())
         current_time = time.strftime("%H:%M:%S", time.localtime())
-        chat_in_group = True
         chat_talking_prompt = ""
-        if stream_id:
+        if chat_id:
             chat_talking_prompt = get_recent_group_detailed_plain_text(
-                stream_id, limit=5, combine=True
+                chat_id, limit=length, combine=True
             )
-            if chat_stream.group_info:
-                if str(config.BOT_QQ) in chat_talking_prompt:
-                    pass
-                    # logger.info(f"{chat_talking_prompt}")
-                    # logger.info(f"bot在群聊中5条内发过言，启动llm计算回复概率")
-                else:
-                    return self.default_change_reply_willing_received(
-                        chat_stream=chat_stream,
-                        is_mentioned_bot=is_mentioned_bot,
-                        config=config,
-                        is_emoji=is_emoji,
-                        interested_rate=interested_rate,
-                        sender_id=sender_id,
-                    )
-            else:
-                chat_in_group = False
-                chat_talking_prompt = chat_talking_prompt
-                # print(f"\033[1;34m[调试]\033[0m 已从数据库获取群 {group_id} 的消息记录:{chat_talking_prompt}")
+        else:
+            return 0
 
         # if is_mentioned_bot:
         #     return 1.0
@@ -76,21 +95,12 @@ class WillingManager(WillingManager):
         仅输出在0到1区间内的概率值，不要给出你的判断依据。
         """
 
-        # 非群聊的意愿管理 未来可能可以用对话缓冲区来确定合适的回复时机
-        if not chat_in_group:
-            prompt = f"""
-        假设你在和网友聊天，网名叫{global_config.BOT_NICKNAME}，你还有很多别名: {"/".join(global_config.BOT_ALIAS_NAMES)}，
-        现在你和朋友私聊的内容是{chat_talking_prompt}，
-        今天是{current_date}，现在是{current_time}。
-        综合以上的内容，给出你认为最新的消息是在和你交流的概率，数值在0到1之间。如果现在是个人休息时间，直接概率为0，请注意是决定是否需要发言，而不是编写回复内容，
-        仅输出在0到1区间内的概率值，不要给出你的判断依据。
-        """
         content_check, reasoning_check, _ = await self.model_v3.generate_response(prompt)
         # logger.info(f"{prompt}")
         logger.info(f"{content_check} {reasoning_check}")
         probability = self.extract_marked_probability(content_check)
         # 兴趣系数修正 无关激活效率太高，暂时停用，待新记忆系统上线后调整
-        probability += (interested_rate * 0.25)
+        probability += (message_info.interested_rate * 0.25)
         probability = min(1.0, probability)
         if probability <= 0.1:
             probability = min(0.03, probability)
@@ -98,8 +108,8 @@ class WillingManager(WillingManager):
             probability = max(probability, 0.90)
 
         # 当前表情包理解能力较差，少说就少错
-        if is_emoji:
-            probability *= 0.1
+        if message_info.is_emoji:
+            probability *= global_config.emoji_response_penalty
 
         return probability
 
@@ -143,21 +153,8 @@ class WillingManager(WillingManager):
         except (ValueError, ZeroDivisionError):
             return 0
 
-    def default_change_reply_willing_received(self, chat_stream: ChatStream, is_mentioned_bot: bool = False, config=None,
-                                            is_emoji: bool = False, interested_rate: float = 0, sender_id: str = None,
-                                            **kwargs) -> float:
-
-        current_willing = self.chat_reply_willing.get(chat_stream.stream_id, 0)
-        interested_rate = interested_rate * config.response_interested_rate_amplifier
-        if interested_rate > 0.4:
-            current_willing += interested_rate - 0.3
-        if is_mentioned_bot and current_willing < 1.0:
-            current_willing += 1
-        elif is_mentioned_bot:
-            current_willing += 0.05
-        if is_emoji:
-            current_willing *= 0.5
-        self.chat_reply_willing[chat_stream.stream_id] = min(current_willing, 3.0)
-        reply_probability = min(max((current_willing - 0.5), 0.01) * config.response_willing_amplifier * 2, 1)
-
-        return reply_probability
+    @llmcheck_decorator(is_continuous_chat)
+    def get_reply_probability(self, message_id):
+        return super().get_reply_probability(
+            message_id
+        )