An overview of advanced RAG
The vanilla RAG framework we just presented doesn’t address many fundamental aspects that impact the quality of the retrieval and answer generation, such as:
- Are the retrieved documents relevant to the user’s question?
- Is the retrieved context enough to answer the user’s question?
- Is there any redundant information that only adds noise to the augmented prompt?
- Does the latency of the retrieval step match our requirements?
- What do we do if we can’t generate a valid answer using the retrieved information?
From the questions above, we can draw two conclusions. The first one is that we need a robust evaluation module for our RAG system that can quantify and measure the quality of the retrieved data and generate answers relative to the user’s question. We will discuss this topic in more detail in Chapter 9. The second conclusion is that we must improve our RAG framework to address...
