text: To run, you should have an OpenSearch Vector Search Edition instance up and running:Read the help document to quickly familiarize and configure OpenSearch Vector Search Edition instance.After the instance is up and running, follow these steps to split documents, get embeddings, connect to the alibaba cloud opensearch instance, index documents, and perform vector retrieval.We need to install the following Python packages first.#!pip install alibabacloud-ha3engineWe 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:")from langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.vectorstores import (    AlibabaCloudOpenSearch,    AlibabaCloudOpenSearchSettings,)Split documents and get embeddings.from langchain.document_loaders import TextLoaderloader = TextLoader("../../../state_of_the_union.txt")documents = loader.load()text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)docs = text_splitter.split_documents(documents)embeddings = OpenAIEmbeddings()Create opensearch settings.settings = AlibabaCloudOpenSearchSettings(    endpoint="The endpoint of opensearch instance, You can find it from the console of Alibaba Cloud OpenSearch.",    instance_id="The identify of opensearch instance, You can find it from the console of Alibaba Cloud OpenSearch.",    datasource_name="The name of the data source specified when creating it.",    username="The username specified when purchasing the instance.",    password="The password specified when purchasing the instance.",    embedding_index_name="The name of the vector attribute specified when configuring the instance attributes.",    field_name_mapping={        "id": "id",  # The id