大修_execute_request炸程序的问题

src/plugins/PFC/pfc.py

@@ -117,9 +117,12 @@ class GoalAnalyzer:
 }}"""
 
         logger.debug(f"发送到LLM的提示词: {prompt}")
-        content, _ = await self.llm.generate_response_async(prompt)
-        logger.debug(f"LLM原始返回内容: {content}")
-        
+        try:
+            content, _ = await self.llm.generate_response_async(prompt)
+            logger.debug(f"LLM原始返回内容: {content}")
+        except Exception as e:
+            logger.error(f"分析对话目标时出错: {str(e)}")
+            content = ""
         # 使用简化函数提取JSON内容
         success, result = get_items_from_json(
             content,

src/plugins/chat/emoji_manager.py

@@ -340,6 +340,9 @@ class EmojiManager:
 
                 if description is not None:
                     embedding = await get_embedding(description, request_type="emoji")
+                    if not embedding:
+                        logger.error("获取消息嵌入向量失败")
+                        raise ValueError("获取消息嵌入向量失败")
                     # 准备数据库记录
                     emoji_record = {
                         "filename": filename,

src/plugins/chat/utils.py

@@ -79,7 +79,13 @@ async def get_embedding(text, request_type="embedding"):
     """获取文本的embedding向量"""
     llm = LLM_request(model=global_config.embedding, request_type=request_type)
     # return llm.get_embedding_sync(text)
-    return await llm.get_embedding(text)
+    try:
+        embedding = await llm.get_embedding(text)
+    except Exception as e:
+        logger.error(f"获取embedding失败: {str(e)}")
+        embedding = None
+    return embedding
+
 
 
 async def get_recent_group_messages(chat_id: str, limit: int = 12) -> list:

src/plugins/memory_system/Hippocampus.py

@@ -1316,15 +1316,24 @@ class HippocampusManager:
         """从文本中获取相关记忆的公共接口"""
         if not self._initialized:
             raise RuntimeError("HippocampusManager 尚未初始化，请先调用 initialize 方法")
-        return await self._hippocampus.get_memory_from_text(
-            text, max_memory_num, max_memory_length, max_depth, fast_retrieval
-        )
+        try:
+            response = await self._hippocampus.get_memory_from_text(text, max_memory_num, max_memory_length, max_depth, fast_retrieval)
+        except Exception as e:
+            logger.error(f"文本激活记忆失败: {e}")
+            response = []
+        return response
+        
 
     async def get_activate_from_text(self, text: str, max_depth: int = 3, fast_retrieval: bool = False) -> float:
         """从文本中获取激活值的公共接口"""
         if not self._initialized:
             raise RuntimeError("HippocampusManager 尚未初始化，请先调用 initialize 方法")
-        return await self._hippocampus.get_activate_from_text(text, max_depth, fast_retrieval)
+        try:
+            response = await self._hippocampus.get_activate_from_text(text, max_depth, fast_retrieval)
+        except Exception as e:
+            logger.error(f"文本产生激活值失败: {e}")
+            response = 0.0
+        return response
 
     def get_memory_from_keyword(self, keyword: str, max_depth: int = 2) -> list:
         """从关键词获取相关记忆的公共接口"""

src/plugins/schedule/schedule_generator.py

@@ -121,7 +121,11 @@ class ScheduleGenerator:
             self.today_done_list = []
         if not self.today_schedule_text:
             logger.info(f"{today.strftime('%Y-%m-%d')}的日程不存在，准备生成新的日程")
-            self.today_schedule_text = await self.generate_daily_schedule(target_date=today)
+            try:
+                self.today_schedule_text = await self.generate_daily_schedule(target_date=today)
+            except Exception as e:
+                logger.error(f"生成日程时发生错误: {str(e)}")
+                self.today_schedule_text = ""
 
         self.save_today_schedule_to_db()
 

src/plugins/topic_identify/topic_identifier.py

@@ -29,10 +29,13 @@ class TopicIdentifier:
 消息内容：{text}"""
 
         # 使用 LLM_request 类进行请求
-        topic, _, _ = await self.llm_topic_judge.generate_response(prompt)
-
+        try:
+            topic, _, _ = await self.llm_topic_judge.generate_response(prompt)
+        except Exception as e:
+            logger.error(f"LLM 请求topic失败: {e}")
+            return None
         if not topic:
-            logger.error("LLM API 返回为空")
+            logger.error("LLM 得到的topic为空")
             return None
 
         # 直接在这里处理主题解析