the state of the union address.First we load relevant modules:from langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.vectorstores import MomentoVectorIndexfrom langchain.document_loaders import TextLoaderThen we load the data:loader = TextLoader("../../modules/state_of_the_union.txt")documents = loader.load()len(documents)    1Note the data is one large file, hence there is only one document:len(documents[0].page_content)    38539Because this is one large text file, we split it into chunks for question answering. That way, user questions will be answered from the most relevant chunk.text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)docs = text_splitter.split_documents(documents)len(docs)    42Index your dataIndexing your data is as simple as instantiating the MomentoVectorIndex object. Here we use the from_documents helper to both instantiate and index the data:vector_db = MomentoVectorIndex.from_documents(    docs,    OpenAIEmbeddings(),    index_name="sotu")This connects to the Momento Vector Index service using your API key and indexes the data. If the index did not exist before, this process creates it for you. The data is now searchable.Query your dataAsk a question directly against the index‚ÄãThe most direct way to query the data is to search against the index. We can do that as follows using the VectorStore API:query = "What did the president say about Ketanji Brown Jackson"docs = vector_db.similarity_search(query)docs[0].page_content    'Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you‚Äôre at it, pass the Disclose Act so Americans can know who is funding our elections. \n\nTonight, I‚Äôd like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer‚Äîan Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer,
MVI: the most productive, easiest to use, serverless vector index for your data. To get started with MVI, simply sign up for an account. There's no need to handle infrastructure, manage servers, or be concerned about scaling. MVI is a service that scales automatically to meet your needs.
MVI: the most productive, easiest to use, serverless vector index for your data. To get started with MVI, simply sign up for an account. There's no need to handle infrastructure, manage servers, or be concerned about scaling. MVI is a service that scales automatically to meet your needs. ->: the state of the union address.First we load relevant modules:from langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.vectorstores import MomentoVectorIndexfrom langchain.document_loaders import TextLoaderThen we load the data:loader = TextLoader("../../modules/state_of_the_union.txt")documents = loader.load()len(documents)    1Note the data is one large file, hence there is only one document:len(documents[0].page_content)    38539Because this is one large text file, we split it into chunks for question answering. That way, user questions will be answered from the most relevant chunk.text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)docs = text_splitter.split_documents(documents)len(docs)    42Index your dataIndexing your data is as simple as instantiating the MomentoVectorIndex object. Here we use the from_documents helper to both instantiate and index the data:vector_db = MomentoVectorIndex.from_documents(    docs,    OpenAIEmbeddings(),    index_name="sotu")This connects to the Momento Vector Index service using your API key and indexes the data. If the index did not exist before, this process creates it for you. The data is now searchable.Query your dataAsk a question directly against the index‚ÄãThe most direct way to query the data is to search against the index. We can do that as follows using the VectorStore API:query = "What did the president say about Ketanji Brown Jackson"docs = vector_db.similarity_search(query)docs[0].page_content    'Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you‚Äôre at it, pass the Disclose Act so Americans can know who is funding our elections. \n\nTonight, I‚Äôd like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer‚Äîan Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer,