'commit'

dsSchoolBuddy/ElasticSearch/Utils/EsSearchUtil.py

@@ -1,18 +1,15 @@
 import logging
 import warnings
-import hashlib  # 导入哈希库
+import hashlib
 import time
 from Config.Config import ES_CONFIG
 from ElasticSearch.Utils.ElasticsearchConnectionPool import ElasticsearchConnectionPool
-from elasticsearch import Elasticsearch
 from langchain_core.documents import Document
 from langchain_text_splitters import RecursiveCharacterTextSplitter
 from langchain_openai import OpenAIEmbeddings
 from pydantic import SecretStr
-
 from Config import Config
 
-
 # 初始化日志
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.INFO)
@@ -111,9 +108,7 @@ class EsSearchUtil:
             # 释放连接回连接池
             self.es_pool.release_connection(conn)
 
-
+    def split_text_into_chunks(self,text: str, chunk_size: int = 200, chunk_overlap: int = 0) -> list:
-
-def split_text_into_chunks(text: str, chunk_size: int = 200, chunk_overlap: int = 0) -> list:
         """
         将文本切割成块
 
@@ -137,8 +132,7 @@ def split_text_into_chunks(text: str, chunk_size: int = 200, chunk_overlap: int
 
         return [split.page_content for split in all_splits]
 
-
+    def insert_long_text_to_es(self,long_text: str, tags: list = None) -> bool:
-def insert_long_text_to_es(long_text: str, tags: list = None) -> bool:
         """
         将长文本切割后向量化并插入到Elasticsearch，基于文本内容哈希实现去重
 
@@ -185,7 +179,7 @@ def insert_long_text_to_es(long_text: str, tags: list = None) -> bool:
                 print(f"索引 '{index_name}' 创建成功")
 
             # 4. 切割文本
-        text_chunks = split_text_into_chunks(long_text)
+            text_chunks = self.split_text_into_chunks(long_text)
 
             # 5. 准备标签
             if tags is None:
@@ -236,7 +230,6 @@ def insert_long_text_to_es(long_text: str, tags: list = None) -> bool:
                 search_util.es_pool.release_connection(conn)
 
 
-
 # 添加main函数进行测试
 if __name__ == "__main__":
     try: