fix 思考者修复，回复意愿提供自定义

参考新的template文件

src/plugins/chat/bot.py

@@ -1,6 +1,4 @@
 import time
-
-# from .message_stream import MessageStream, MessageStreamContainer
 from random import random
 
 from loguru import logger
@@ -129,6 +127,11 @@ class ChatBot:
                     container.messages.remove(msg)
                     # print(f"\033[1;32m[思考消息删除]\033[0m 已找到思考消息对象，开始删除")
                     break
+                    
+            # 如果找不到思考消息，直接返回
+            if not thinking_message:
+                print(f"\033[1;33m[警告]\033[0m 未找到对应的思考消息，可能已超时被移除")
+                return
             
             #记录开始思考的时间，避免从思考到回复的时间太久
             thinking_start_time = thinking_message.thinking_start_time

src/plugins/chat/config.py

@@ -21,6 +21,12 @@ class BotConfig:
     
     talk_allowed_groups = set()
     talk_frequency_down_groups = set()
+    thinking_timeout: int = 100  # 思考时间
+    
+    response_willing_amplifier: float = 1.0  # 回复意愿放大系数
+    response_interested_rate_amplifier: float = 1.0  # 回复兴趣度放大系数
+    down_frequency_rate: float = 3.5  # 降低回复频率的群组回复意愿降低系数
+    
     ban_user_id = set()
     
     build_memory_interval: int = 30  # 记忆构建间隔（秒）
@@ -172,6 +178,10 @@ class BotConfig:
                 config.MAX_CONTEXT_SIZE = msg_config.get("max_context_size", config.MAX_CONTEXT_SIZE)
                 config.emoji_chance = msg_config.get("emoji_chance", config.emoji_chance)
                 config.ban_words=msg_config.get("ban_words",config.ban_words)
+                config.thinking_timeout = msg_config.get("thinking_timeout", config.thinking_timeout)
+                config.response_willing_amplifier = msg_config.get("response_willing_amplifier", config.response_willing_amplifier)
+                config.response_interested_rate_amplifier = msg_config.get("response_interested_rate_amplifier", config.response_interested_rate_amplifier)
+                config.down_frequency_rate = msg_config.get("down_frequency_rate", config.down_frequency_rate)
 
             if "memory" in toml_dict:
                 memory_config = toml_dict["memory"]

src/plugins/chat/message_sender.py

@@ -8,6 +8,7 @@ from .cq_code import cq_code_tool
 from .message import Message, Message_Sending, Message_Thinking, MessageSet
 from .storage import MessageStorage
 from .utils import calculate_typing_time
+from .config import global_config
 
 
 class Message_Sender:
@@ -162,6 +163,11 @@ class MessageManager:
                 message_earliest.update_thinking_time()
                 thinking_time = message_earliest.thinking_time
                 print(f"\033[1;34m[调试]\033[0m 消息正在思考中，已思考{int(thinking_time)}秒\033[K\r", end='', flush=True)
+                
+                # 检查是否超时
+                if thinking_time > global_config.thinking_timeout:
+                    print(f"\033[1;33m[警告]\033[0m 消息思考超时({thinking_time}秒)，移除该消息")
+                    container.remove_message(message_earliest)
             else:# 如果不是message_thinking就只能是message_sending    
                 print(f"\033[1;34m[调试]\033[0m 消息'{message_earliest.processed_plain_text}'正在发送中")
                 #直接发，等什么呢

src/plugins/chat/willing_manager.py

@@ -1,4 +1,5 @@
 import asyncio
+from .config import global_config
 
 
 class WillingManager:
@@ -38,11 +39,14 @@ class WillingManager:
             current_willing *= 0.1
             print(f"表情包, 当前意愿: {current_willing}")
         
+        print(f"放大系数_interested_rate: {global_config.response_interested_rate_amplifier}")
+        interested_rate *= global_config.response_interested_rate_amplifier #放大回复兴趣度
         if interested_rate > 0.4:
-            print(f"兴趣度: {interested_rate}, 当前意愿: {current_willing}")
-            current_willing += interested_rate-0.1
+            # print(f"兴趣度: {interested_rate}, 当前意愿: {current_willing}")
+            current_willing += interested_rate-0.4
         
-        self.group_reply_willing[group_id] = min(current_willing, 3.0)
+        current_willing *= global_config.response_willing_amplifier #放大回复意愿
+        # print(f"放大系数_willing: {global_config.response_willing_amplifier}, 当前意愿: {current_willing}")
         
         reply_probability = max((current_willing - 0.45) * 2, 0)
         if group_id not in config.talk_allowed_groups:
@@ -50,11 +54,14 @@ class WillingManager:
             reply_probability = 0
             
         if group_id in config.talk_frequency_down_groups:
-            reply_probability = reply_probability / 3.5
+            reply_probability = reply_probability / global_config.down_frequency_rate
 
         reply_probability = min(reply_probability, 1)
         if reply_probability < 0:
             reply_probability = 0
+            
+            
+        self.group_reply_willing[group_id] = min(current_willing, 3.0)
         return reply_probability
     
     def change_reply_willing_sent(self, group_id: int):

src/plugins/memory_system/memory.py

@@ -531,7 +531,8 @@ class Hippocampus:
         # 计算每个识别出的主题与记忆主题的相似度
         for topic in topics:
             if debug_info:
-                print(f"\033[1;32m[{debug_info}]\033[0m 正在思考有没有见过: {topic}")
+                # print(f"\033[1;32m[{debug_info}]\033[0m 正在思考有没有见过: {topic}")
+                pass
                 
             topic_vector = text_to_vector(topic)
             has_similar_topic = False
@@ -549,11 +550,13 @@ class Hippocampus:
                 if similarity >= similarity_threshold:
                     has_similar_topic = True
                     if debug_info:
-                        print(f"\033[1;32m[{debug_info}]\033[0m 找到相似主题: {topic} -> {memory_topic} (相似度: {similarity:.2f})")
+                        # print(f"\033[1;32m[{debug_info}]\033[0m 找到相似主题: {topic} -> {memory_topic} (相似度: {similarity:.2f})")
+                        pass
                     all_similar_topics.append((memory_topic, similarity))
                     
             if not has_similar_topic and debug_info:
-                print(f"\033[1;31m[{debug_info}]\033[0m 没有见过: {topic}  ，呃呃")
+                # print(f"\033[1;31m[{debug_info}]\033[0m 没有见过: {topic}  ，呃呃")
+                pass
                 
         return all_similar_topics
         

src/plugins/models/utils_model.py

@@ -226,7 +226,7 @@ class LLM_request:
                     await asyncio.sleep(wait_time)
                 else:
                     logger.critical(f"请求失败: {str(e)}")
-                    logger.critical(f"请求头: {await self._build_headers()} 请求体: {payload}")
+                    logger.critical(f"请求头: {await self._build_headers(no_key=True)} 请求体: {payload}")
                     raise RuntimeError(f"API请求失败: {str(e)}")
 
         logger.error("达到最大重试次数，请求仍然失败")
@@ -324,12 +324,19 @@ class LLM_request:
             reasoning = ""
         return content, reasoning
 
-    async def _build_headers(self) -> dict:
+    async def _build_headers(self, no_key: bool = False) -> dict:
         """构建请求头"""
-        return {
-            "Authorization": f"Bearer {self.api_key}",
-            "Content-Type": "application/json"
-        }
+        if no_key:
+            return {
+                "Authorization": f"Bearer **********",
+                "Content-Type": "application/json"
+            }
+        else:
+            return {
+                "Authorization": f"Bearer {self.api_key}",
+                "Content-Type": "application/json"
+            } 
+        # 防止小朋友们截图自己的key
 
     async def generate_response(self, prompt: str) -> Tuple[str, str]:
         """根据输入的提示生成模型的异步响应"""

template/bot_config_template.toml

@@ -17,6 +17,11 @@ prompt_schedule = "一个曾经学习地质,现在学习心理学和脑科学的
 min_text_length = 2 # 与麦麦聊天时麦麦只会回答文本大于等于此数的消息
 max_context_size = 15 # 麦麦获得的上文数量
 emoji_chance = 0.2 # 麦麦使用表情包的概率
+thinking_timeout = 10 # 麦麦思考时间
+
+response_willing_amplifier = 1 # 麦麦回复意愿放大系数，一般为1
+response_interested_rate_amplifier = 1 # 麦麦回复兴趣度放大系数,听到记忆里的内容时放大系数
+down_frequency_rate = 3.5 # 降低回复频率的群组回复意愿降低系数
 ban_words = [
     # "403","张三"
     ]