更新API密钥管理，优化意图识别和Excel数据验证功能，增强日志记录，改进错误处理机制，支持文档检索功能，提升代码可读性和灵活性。

rag2_0/intent_recognition/ProfessionalNounVector.py

@@ -93,7 +93,7 @@ class ProfessionalNounVectorizer:
             logging.info(f"总共加载了 {len(merged_terms)} 条专业名词")
             return merged_terms
         except Exception as e:
-            logging.error(f"加载多个文件失败: {e}")
+            logging.error(f"加载多个文件失败: {e}", exc_info=True)
             return []
                 
     def vectorize_files_and_save(self, file_paths: List[str]) -> bool:
@@ -139,7 +139,7 @@ class ProfessionalNounVectorizer:
             logging.info("完成多文件专业名词向量化和索引创建")
             return True
         except Exception as e:
-            logging.error(f"多文件向量化处理失败: {e}")
+            logging.error(f"多文件向量化处理失败: {e}", exc_info=True)
             return False
     
     def _updata_suffix_item(self)->Tuple[List[str], List[Dict]] :
@@ -246,7 +246,7 @@ class ProfessionalNounVectorizer:
             faiss_index.save_local(folder_path=self.index_path)
             logging.info(f"FAISS索引已保存至 {self.index_path}")
         except Exception as e:
-            logging.error(f"保存FAISS索引失败: {e}")
+            logging.error(f"保存FAISS索引失败: {e}", exc_info=True)
             raise e
 
 
@@ -349,5 +349,5 @@ class ProfessionalNounRetriever:
             return [json.loads(item) for item in intersection]
      
         except Exception as e:
-            logging.error(f"查询FAISS索引失败: {e}")
+            logging.error(f"查询FAISS索引失败: {e}", exc_info=True)
             return []