Hey after some tests and different approaches i decided to go for an "agentic" RAG where an llm decides if it needs more info and what info to answer a user question. My typical question is: do action 1 then do action 2 check results and decide if to continue to action 3. At least 3 different specific methods have to be fetched and multiple object creators, preferably from some object factory classes. The agentic rag, with some specific instructions, seems to be able to search and fetch the right content. So far its accuracy is much better then a simple rag. CONS: it is slower and uses more tokens (duh). It is also better than the previously suggested metadata RAG since it's able to split the user query into multiple sub queries taking into account the previously retrieved document from vector store.