fix: 后置emotion生成，大幅提高响应速度

src/plugins/chat/bot.py

@@ -119,7 +119,7 @@ class ChatBot:
 
             willing_manager.change_reply_willing_sent(thinking_message.group_id)
             
-            response, emotion = await self.gpt.generate_response(message)
+            response,raw_content = await self.gpt.generate_response(message)
 
             # if response is None:
                 # thinking_message.interupt=True
@@ -171,6 +171,13 @@ class ChatBot:
             message_manager.add_message(message_set)
             
             bot_response_time = tinking_time_point
+            emotion = await self.gpt._get_emotion_tags(raw_content)
+            print(f"为 '{response}' 获取到的情感标签为：{emotion}")
+            valuedict={
+            'happy':0.5,'angry':-1,'sad':-0.5,'surprised':0.5,'disgusted':-1.5,'fearful':-0.25,'neutral':0.25
+            }
+            await relationship_manager.update_relationship_value(message.user_id, relationship_value=valuedict[emotion[0]])
+
             if random() < global_config.emoji_chance:
                 emoji_path = await emoji_manager.get_emoji_for_emotion(emotion)
                 if emoji_path:

src/plugins/chat/llm_generator.py

@@ -44,19 +44,15 @@ class ResponseGenerator:
         print(f"+++++++++++++++++{global_config.BOT_NICKNAME}{self.current_model_type}思考中+++++++++++++++++")
         
         model_response = await self._generate_response_with_model(message, current_model)
+        raw_content=model_response
         
         if model_response:
             print(f'{global_config.BOT_NICKNAME}的回复是：{model_response}')
-            model_response, emotion = await self._process_response(model_response)
+            model_response = await self._process_response(model_response)
             if model_response:
-                print(f"为 '{model_response}' 获取到的情感标签为：{emotion}")
-                valuedict={
-                'happy':0.5,'angry':-1,'sad':-0.5,'surprised':0.5,'disgusted':-1.5,'fearful':-0.25,'neutral':0.25
-                }
-                await relationship_manager.update_relationship_value(message.user_id, relationship_value=valuedict[emotion[0]])
 
-            return model_response, emotion
-        return None, []
+                return model_response ,raw_content
+        return None,raw_content
 
     async def _generate_response_with_model(self, message: Message, model: LLM_request) -> Optional[str]:
         """使用指定的模型生成回复"""
@@ -158,10 +154,9 @@ class ResponseGenerator:
         if not content:
             return None, []
         
-        emotion_tags = await self._get_emotion_tags(content)
         processed_response = process_llm_response(content)
         
-        return processed_response, emotion_tags
+        return processed_response
 
 
 class InitiativeMessageGenerate: