A community member is building a RAG system using LlamaIndex and the VectorStoreIndex.from_documents function. They are unsure about the purpose of a specific parameter used in this function, which includes the embedding content, embedding model, and a tokenizer. Another community member is confused about which parameter the original poster is referring to. There is no explicitly marked answer in the comments.
Hi! I am building a RAG system using LlamaIndex and I am using the VectorStoreIndex.from_documents function, to create my index. As parameters, this function uses the documents conforming the embedding content, the embedding model to use (I'm testing some of them), and a tokenizer. What does this variable do in this function? It is not clear to me from the documentation. Does anyone know? Thanks in advance!
