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# ElasticSearch

This notebook shows how to use functionality related to the ElasticSearch database.

    from langchain.embeddings.openai import OpenAIEmbeddings
    from langchain.text_splitter import CharacterTextSplitter
    from langchain.vectorstores import ElasticVectorSearch
    from langchain.document_loaders import TextLoader

    from langchain.document_loaders import TextLoader
    loader = 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()

    db = ElasticVectorSearch.from_documents(docs, embeddings, elasticsearch_url="http://localhost:9200")

    query = "What did the president say about Ketanji Brown Jackson"
    docs = db.similarity_search(query)

    print(docs[0].page_content)

    In state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections.

    We cannot let this happen.

    Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections.

    Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service.

    One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court.

    And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.