text: embedding,               1 -(documents.embedding <=> query_embedding) AS similarity           FROM               documents           ORDER BY               documents.embedding <=> query_embedding           LIMIT match_count;       END;       $$;# with pippip install supabase# with conda# !conda install -c conda-forge supabaseWe want to use OpenAIEmbeddings so we have to get the OpenAI API Key.import osimport getpassos.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")os.environ["SUPABASE_URL"] = getpass.getpass("Supabase URL:")os.environ["SUPABASE_SERVICE_KEY"] = getpass.getpass("Supabase Service Key:")# If you're storing your Supabase and OpenAI API keys in a .env file, you can load them with dotenvfrom dotenv import load_dotenvload_dotenv()import osfrom supabase.client import Client, create_clientsupabase_url = os.environ.get("SUPABASE_URL")supabase_key = os.environ.get("SUPABASE_SERVICE_KEY")supabase: Client = create_client(supabase_url, supabase_key)from langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.vectorstores import SupabaseVectorStorefrom langchain.document_loaders import TextLoaderfrom langchain.document_loaders import TextLoaderloader = TextLoader("../../../state_of_the_union.txt")documents = loader.load()text_splitter =