text: First let's ingest the documents using the from_documents() method: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)vectara = Vectara.from_documents(    docs,    embedding=FakeEmbeddings(size=768),    doc_metadata={"speech": "state-of-the-union"},)Vectara's indexing API provides a file upload API where the file is handled directly by Vectara - pre-processed, chunked optimally and added to the Vectara vector store.