Can someone correct my concepts here (if I am wrong),
After creating an index, the retriever is utilized to fetch the most relevant texts (nodes), after which this information is passed to the synthesizer along with the prompt (if provided) to generate the final response. Right?
And the query engine is built on top of the index. Does this mean that if we utilize a model from Hugging Face to generate embeddings for indexing, and then we use this index to create a retriever, will this retriever be utilizing our embedding model or not?
retriever = VectorIndexRetriever(
index=index,
similarity_top_k=5,
)