= 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", "author": "Biden"},)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.
Vectara is a API platform for building GenAI applications. It provides an easy-to-use API for document indexing and querying that is managed by Vectara and is optimized for performance and accuracy.
Vectara is a API platform for building GenAI applications. It provides an easy-to-use API for document indexing and querying that is managed by Vectara and is optimized for performance and accuracy. ->: = 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", "author": "Biden"},)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.