From 058f59b71c58f214cc87dc0b32bb71f6a6eaba34 Mon Sep 17 00:00:00 2001
From: HuangHai <10402852@qq.com>
Date: Fri, 27 Jun 2025 15:06:40 +0800
Subject: [PATCH] 'commit'

---
 dsRag/ElasticSearch/T6_XiangLiangQuery.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/dsRag/ElasticSearch/T6_XiangLiangQuery.py b/dsRag/ElasticSearch/T6_XiangLiangQuery.py
index 642866fd..428a7015 100644
--- a/dsRag/ElasticSearch/T6_XiangLiangQuery.py
+++ b/dsRag/ElasticSearch/T6_XiangLiangQuery.py
@@ -8,7 +8,7 @@ logger = logging.getLogger(__name__)
 logger.setLevel(logging.INFO)
 
 # 初始化EsSearchUtil
-es_search_util = EsSearchUtil(ES_CONFIG)
+esClient = EsSearchUtil(ES_CONFIG)
 
 
 def main():
@@ -19,12 +19,12 @@ def main():
     print(f"原始查询文本: {query}")
 
     # 执行混合搜索
-    es_conn = es_search_util.es_pool.get_connection()
+    es_conn = esClient.es_pool.get_connection()
     try:
         # 向量搜索
         print("\n=== 向量搜索阶段 ===")
         print("1. 文本分词和向量化处理中...")
-        query_embedding = es_search_util.text_to_embedding(query)
+        query_embedding = esClient.text_to_embedding(query)
         print(f"2. 生成的查询向量维度: {len(query_embedding)}")
         print(f"3. 前3维向量值: {query_embedding[:3]}")
         
@@ -99,7 +99,7 @@ def main():
             # print(f"      详细: {hit['_source']['tags']['full_content']}")
         
     finally:
-        es_search_util.es_pool.release_connection(es_conn)
+        esClient.es_pool.release_connection(es_conn)
 
 if __name__ == "__main__":
     main()