feat：回复温度现在会受到：人格-情绪-temp的链条影响;顺便修改了情绪激活度的取值

feat：回复温度现在会受到：人格-情绪-temp的链条影响;顺便修改了情绪激活度的取值

src/plugins/chat_module/reasoning_chat/reasoning_chat.py

@@ -1,7 +1,7 @@
 import time
 from random import random
 import re
-
+from typing import List
 from ...memory_system.Hippocampus import HippocampusManager
 from ...moods.moods import MoodManager
 from ...config.config import global_config
@@ -18,6 +18,7 @@ from src.common.logger import get_module_logger, CHAT_STYLE_CONFIG, LogConfig
 from ...chat.chat_stream import chat_manager
 from ...person_info.relationship_manager import relationship_manager
 from ...chat.message_buffer import message_buffer
+from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
 
 # 定义日志配置
 chat_config = LogConfig(
@@ -58,7 +59,11 @@ class ReasoningChat:
 
         return thinking_id
 
-    async def _send_response_messages(self, message, chat, response_set, thinking_id):
+    async def _send_response_messages(self, 
+                                      message, 
+                                      chat, 
+                                      response_set:List[str], 
+                                      thinking_id) -> MessageSending:
         """发送回复消息"""
         container = message_manager.get_container(chat.stream_id)
         thinking_message = None
@@ -77,6 +82,7 @@ class ReasoningChat:
         message_set = MessageSet(chat, thinking_id)
 
         mark_head = False
+        first_bot_msg = None
         for msg in response_set:
             message_segment = Seg(type="text", data=msg)
             bot_message = MessageSending(
@@ -96,9 +102,12 @@ class ReasoningChat:
             )
             if not mark_head:
                 mark_head = True
+                first_bot_msg = bot_message
             message_set.add_message(bot_message)
         message_manager.add_message(message_set)
 
+        return first_bot_msg
+
     async def _handle_emoji(self, message, chat, response):
         """处理表情包"""
         if random() < global_config.emoji_chance:
@@ -232,22 +241,34 @@ class ReasoningChat:
             timer2 = time.time()
             timing_results["创建思考消息"] = timer2 - timer1
             
+            logger.debug(f"创建捕捉器，thinking_id:{thinking_id}")
+                
+            info_catcher = info_catcher_manager.get_info_catcher(thinking_id)
+            info_catcher.catch_decide_to_response(message)
+
             # 生成回复
             timer1 = time.time()
-            response_set = await self.gpt.generate_response(message)
+            response_set = await self.gpt.generate_response(message,thinking_id)
             timer2 = time.time()
             timing_results["生成回复"] = timer2 - timer1
             
+            info_catcher.catch_after_generate_response(timing_results["生成回复"])
+
             if not response_set:
                 logger.info("为什么生成回复失败？")
                 return
 
             # 发送消息
             timer1 = time.time()
-            await self._send_response_messages(message, chat, response_set, thinking_id)
+            first_bot_msg = await self._send_response_messages(message, chat, response_set, thinking_id)
             timer2 = time.time()
             timing_results["发送消息"] = timer2 - timer1
             
+            info_catcher.catch_after_response(timing_results["发送消息"],response_set,first_bot_msg)
+                
+                
+            info_catcher.done_catch()
+
             # 处理表情包
             timer1 = time.time()
             await self._handle_emoji(message, chat, response_set)

src/plugins/chat_module/reasoning_chat/reasoning_generator.py

@@ -8,6 +8,7 @@ from ...chat.message import MessageThinking
 from .reasoning_prompt_builder import prompt_builder
 from ...chat.utils import process_llm_response
 from src.common.logger import get_module_logger, LogConfig, LLM_STYLE_CONFIG
+from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
 
 # 定义日志配置
 llm_config = LogConfig(
@@ -37,7 +38,7 @@ class ResponseGenerator:
         self.current_model_type = "r1"  # 默认使用 R1
         self.current_model_name = "unknown model"
 
-    async def generate_response(self, message: MessageThinking) -> Optional[Union[str, List[str]]]:
+    async def generate_response(self, message: MessageThinking,thinking_id:str) -> Optional[Union[str, List[str]]]:
         """根据当前模型类型选择对应的生成函数"""
         # 从global_config中获取模型概率值并选择模型
         if random.random() < global_config.MODEL_R1_PROBABILITY:
@@ -51,7 +52,7 @@ class ResponseGenerator:
             f"{self.current_model_type}思考:{message.processed_plain_text[:30] + '...' if len(message.processed_plain_text) > 30 else message.processed_plain_text}"
         )  # noqa: E501
 
-        model_response = await self._generate_response_with_model(message, current_model)
+        model_response = await self._generate_response_with_model(message, current_model,thinking_id)
 
         # print(f"raw_content: {model_response}")
 
@@ -64,8 +65,11 @@ class ResponseGenerator:
             logger.info(f"{self.current_model_type}思考，失败")
             return None
 
-    async def _generate_response_with_model(self, message: MessageThinking, model: LLM_request):
+    async def _generate_response_with_model(self, message: MessageThinking, model: LLM_request,thinking_id:str):
         sender_name = ""
+        
+        info_catcher = info_catcher_manager.get_info_catcher(thinking_id)
+        
         if message.chat_stream.user_info.user_cardname and message.chat_stream.user_info.user_nickname:
             sender_name = (
                 f"[({message.chat_stream.user_info.user_id}){message.chat_stream.user_info.user_nickname}]"
@@ -90,6 +94,14 @@ class ResponseGenerator:
 
         try:
             content, reasoning_content, self.current_model_name = await model.generate_response(prompt)
+            
+            info_catcher.catch_after_llm_generated(
+                prompt=prompt,
+                response=content,
+                reasoning_content=reasoning_content,
+                model_name=self.current_model_name)
+        
+        
         except Exception:
             logger.exception("生成回复时出错")
             return None

src/plugins/chat_module/think_flow_chat/think_flow_generator.py

@@ -10,6 +10,8 @@ from ...chat.utils import process_llm_response
 from src.common.logger import get_module_logger, LogConfig, LLM_STYLE_CONFIG
 from src.plugins.respon_info_catcher.info_catcher import info_catcher_manager
 
+from src.plugins.moods.moods import MoodManager
+
 # 定义日志配置
 llm_config = LogConfig(
     # 使用消息发送专用样式
@@ -40,7 +42,11 @@ class ResponseGenerator:
             f"思考:{message.processed_plain_text[:30] + '...' if len(message.processed_plain_text) > 30 else message.processed_plain_text}"
         )
         
+        arousal_multiplier = MoodManager.get_instance().get_arousal_multiplier()
+        
+        
         current_model = self.model_normal
+        current_model.temperature = 0.7 * arousal_multiplier #激活度越高，温度越高
         model_response = await self._generate_response_with_model(message, current_model,thinking_id)
 
         # print(f"raw_content: {model_response}")

src/plugins/moods/moods.py

@@ -19,7 +19,7 @@ logger = get_module_logger("mood_manager", config=mood_config)
 @dataclass
 class MoodState:
     valence: float  # 愉悦度 (-1.0 到 1.0)，-1表示极度负面，1表示极度正面
-    arousal: float  # 唤醒度 (0.0 到 1.0)，0表示完全平静，1表示极度兴奋
+    arousal: float  # 唤醒度 (-1.0 到 1.0)，-1表示抑制，1表示兴奋
     text: str  # 心情文本描述
 
 
@@ -42,7 +42,7 @@ class MoodManager:
         self._initialized = True
 
         # 初始化心情状态
-        self.current_mood = MoodState(valence=0.0, arousal=0.5, text="平静")
+        self.current_mood = MoodState(valence=0.0, arousal=0.0, text="平静")
 
         # 从配置文件获取衰减率
         self.decay_rate_valence = 1 - global_config.mood_decay_rate  # 愉悦度衰减率
@@ -71,21 +71,21 @@ class MoodManager:
         # 情绪文本映射表
         self.mood_text_map = {
             # 第一象限：高唤醒，正愉悦
-            (0.5, 0.7): "兴奋",
+            (0.5, 0.4): "兴奋",
-            (0.3, 0.8): "快乐",
+            (0.3, 0.6): "快乐",
-            (0.2, 0.65): "满足",
+            (0.2, 0.3): "满足",
             # 第二象限：高唤醒，负愉悦
-            (-0.5, 0.7): "愤怒",
+            (-0.5, 0.4): "愤怒",
-            (-0.3, 0.8): "焦虑",
+            (-0.3, 0.6): "焦虑",
-            (-0.2, 0.65): "烦躁",
+            (-0.2, 0.3): "烦躁",
             # 第三象限：低唤醒，负愉悦
-            (-0.5, 0.3): "悲伤",
+            (-0.5, -0.4): "悲伤",
-            (-0.3, 0.35): "疲倦",
+            (-0.3, -0.3): "疲倦",
-            (-0.4, 0.15): "疲倦",
+            (-0.4, -0.7): "疲倦",
             # 第四象限：低唤醒，正愉悦
-            (0.2, 0.45): "平静",
+            (0.2, -0.1): "平静",
-            (0.3, 0.4): "安宁",
+            (0.3, -0.2): "安宁",
-            (0.5, 0.3): "放松",
+            (0.5, -0.4): "放松",
         }
 
     @classmethod
@@ -164,15 +164,15 @@ class MoodManager:
                 -decay_rate_negative * time_diff * neuroticism_factor
             )
 
-        # Arousal 向中性（0.5）回归
+        # Arousal 向中性（0）回归
-        arousal_target = 0.5
+        arousal_target = 0
         self.current_mood.arousal = arousal_target + (self.current_mood.arousal - arousal_target) * math.exp(
             -self.decay_rate_arousal * time_diff * neuroticism_factor
         )
 
         # 确保值在合理范围内
         self.current_mood.valence = max(-1.0, min(1.0, self.current_mood.valence))
-        self.current_mood.arousal = max(0.0, min(1.0, self.current_mood.arousal))
+        self.current_mood.arousal = max(-1.0, min(1.0, self.current_mood.arousal))
 
         self.last_update = current_time
 
@@ -184,7 +184,7 @@ class MoodManager:
 
         # 限制范围
         self.current_mood.valence = max(-1.0, min(1.0, self.current_mood.valence))
-        self.current_mood.arousal = max(0.0, min(1.0, self.current_mood.arousal))
+        self.current_mood.arousal = max(-1.0, min(1.0, self.current_mood.arousal))
 
         self._update_mood_text()
 
@@ -217,7 +217,7 @@ class MoodManager:
 
         # 限制范围
         self.current_mood.valence = max(-1.0, min(1.0, self.current_mood.valence))
-        self.current_mood.arousal = max(0.0, min(1.0, self.current_mood.arousal))
+        self.current_mood.arousal = max(-1.0, min(1.0, self.current_mood.arousal))
 
         self._update_mood_text()
 
@@ -232,13 +232,23 @@ class MoodManager:
         elif self.current_mood.valence < -0.5:
             base_prompt += "你现在心情不太好，"
 
-        if self.current_mood.arousal > 0.7:
+        if self.current_mood.arousal > 0.4:
             base_prompt += "情绪比较激动。"
-        elif self.current_mood.arousal < 0.3:
+        elif self.current_mood.arousal < -0.4:
             base_prompt += "情绪比较平静。"
 
         return base_prompt
     
+    def get_arousal_multiplier(self) -> float:
+        """根据当前情绪状态返回唤醒度乘数"""
+        if self.current_mood.arousal > 0.4:
+            multiplier = 1 + min(0.15,(self.current_mood.arousal - 0.4)/3)
+            return multiplier
+        elif self.current_mood.arousal < -0.4:
+            multiplier = 1 - min(0.15,((0 - self.current_mood.arousal) - 0.4)/3)
+            return multiplier
+        return 1.0
+
     def get_current_mood(self) -> MoodState:
         """获取当前情绪状态"""
         return self.current_mood
@@ -278,7 +288,7 @@ class MoodManager:
 
         # 限制范围
         self.current_mood.valence = max(-1.0, min(1.0, self.current_mood.valence))
-        self.current_mood.arousal = max(0.0, min(1.0, self.current_mood.arousal))
+        self.current_mood.arousal = max(-1.0, min(1.0, self.current_mood.arousal))
 
         self._update_mood_text()