diff --git a/dsRag/ElasticSearch/T6_DeepSeekRag.py b/dsRag/ElasticSearch/T6_DeepSeekRag.py
deleted file mode 100644
index 9542e0f5..00000000
--- a/dsRag/ElasticSearch/T6_DeepSeekRag.py
+++ /dev/null
@@ -1,114 +0,0 @@
-"""
-conda activate rag
-pip install openai
-"""
-from elasticsearch import Elasticsearch
-from openai import OpenAI
-from Config import Config
-
-# 初始化ES连接
-es = Elasticsearch(
-    hosts=Config.ES_CONFIG['hosts'],
-    basic_auth=Config.ES_CONFIG['basic_auth'],
-    verify_certs=Config.ES_CONFIG['verify_certs']
-)
-
-# 初始化DeepSeek客户端
-client = OpenAI(
-    api_key=Config.DEEPSEEK_API_KEY,
-    base_url=Config.DEEPSEEK_URL
-)
-
-def generate_report(query, context):
-    """使用DeepSeek生成报告"""
-    prompt = f"""根据以下关于'{query}'的相关信息，整理一份结构化的报告：
-要求：
-1. 分章节组织内容
-2. 包含关键数据和事实
-3. 语言简洁专业
-
-相关信息：
-{context}"""
-    
-    try:
-        response = client.chat.completions.create(
-            model="deepseek-chat",
-            messages=[
-                {"role": "system", "content": "你是一个专业的文档整理助手"},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.3,
-            stream=True
-        )
-        
-        # 流式输出处理
-        full_response = ""
-        for chunk in response:
-            if chunk.choices[0].delta.content:
-                content = chunk.choices[0].delta.content
-                print(content, end="", flush=True)
-                full_response += content
-        
-        return full_response
-    except Exception as e:
-        print(f"生成报告时出错: {str(e)}")
-        return ""
-
-def process_query(query):
-    """处理用户查询并生成报告"""
-    print(f"正在搜索与'{query}'相关的数据...")
-    context = search_related_data(query)
-    print(f"找到{len(context.split(chr(10)+chr(10)))}条相关数据")
-    
-    print("正在生成报告...")
-    report = generate_report(query, context)
-    
-    return report
-
-def search_related_data(query):
-    """搜索与查询相关的数据"""
-    # 向量搜索
-    vector_results = es.search(
-        index=Config.ES_CONFIG['index_name'],
-        body={
-            "query": {
-                "match": {
-                    "content": {
-                        "query": query,
-                        "analyzer": "ik_smart"  # 指定分词器
-                    }
-                }
-            },
-            "size": 5
-        }
-    )
-    
-    # 文本精确搜索
-    text_results = es.search(
-        index="raw_texts",
-        body={
-            "query": {
-                "match": {
-                    "text.keyword": query
-                }
-            },
-            "size": 5
-        }
-    )
-    
-    # 合并结果
-    context = ""
-    for hit in vector_results['hits']['hits']:
-        context += f"向量相似度结果(score={hit['_score']}):\n{hit['_source']['text']}\n\n"
-    
-    for hit in text_results['hits']['hits']:
-        context += f"文本精确匹配结果(score={hit['_score']}):\n{hit['_source']['text']}\n\n"
-    
-    return context
-
-if __name__ == "__main__":
-    #user_query = input("请输入您的查询要求：")
-    user_query = "小学数学"
-    report = process_query(user_query)
-    print("\n=== 生成的报告 ===\n")
-    print(report)
\ No newline at end of file
diff --git a/dsRag/ElasticSearch/T7_XiangLiangQuery.py b/dsRag/ElasticSearch/T6_XiangLiangQuery.py
similarity index 100%
rename from dsRag/ElasticSearch/T7_XiangLiangQuery.py
rename to dsRag/ElasticSearch/T6_XiangLiangQuery.py