text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChromaClarifaiClickHouse Vector SearchActiveloop's Deep LakeDocArrayHnswSearchDocArrayInMemorySearchElasticSearchFAISSHologresLanceDBMarqoMatchingEngineMilvusMongoDB AtlasMyScaleOpenSearchpg_embeddingPGVectorPineconeQdrantRedisRocksetSingleStoreDBscikit-learnStarRocksSupabase (Postgres)TairTigrisTypesenseVectaraWeaviateZillizGrouped by providerIntegrationsVector storesAtlasAtlasAtlas is a platform for interacting with both small and internet scale unstructured datasets by Nomic. This notebook shows you how to use functionality related to the AtlasDB vectorstore.pip install spacypython3 -m spacy download en_core_web_smpip install nomicimport timefrom langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import SpacyTextSplitterfrom langchain.vectorstores import AtlasDBfrom langchain.document_loaders import TextLoaderATLAS_TEST_API_KEY = "7xDPkYXSYDc1_ErdTPIcoAR9RNd8YDlkS3nVNXcVoIMZ6"loader = TextLoader("../../../state_of_the_union.txt")documents = loader.load()text_splitter = SpacyTextSplitter(separator="|")texts = []for doc in text_splitter.split_documents(documents):    texts.extend(doc.page_content.split("|"))texts = [e.strip() for e in texts]db =