text: nationâ€™s top legal minds, who will continue Justice Breyerâ€™s legacy of excellence.Similarity search with scoreâ€‹The returned distance score is between 0-1. 0 is dissimilar, 1 is the most similardocs = db.similarity_search_with_score(query)print(docs[0])    (Document(page_content='And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nationâ€™s top legal minds, who will continue Justice Breyerâ€™s legacy of excellence.', metadata={'source': '../../../state_of_the_union.txt'}), 0.561813814013747)Restore the table created and added data beforeâ€‹AwaDB automatically persists added document dataIf you can restore the table you created and added before, you can just do this as below:awadb_client = awadb.Client()ret = awadb_client.Load("langchain_awadb")if ret:    print("awadb load table success")else:    print("awadb load table failed")awadb load table successPreviousAtlasNextAzure Cognitive SearchSimilarity search with scoreRestore the table created and added data beforeCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.