I am currently using this type of vector storage: index = GPTVectorStoreIndex.from_documents( documents, service_context=service_context ) index.storage_context.persist(persist_dir=index_name)
But when I upload files of about 40 MB, everything is indexed for a very long time and the response takes up to 2-3 minutes. Can Weaviate solve this problem?
How do I integrate weaviate here.... My brain is already boiling. The functions described in the llamaindex documentation just don't work. The advice from kappa is very bad... I don't understand how to save embeddings. I want to keep the logic the same, so that only vectors work in weaviate: