Retrieval Augmented Generation Quiz

What you'll be asked

1. What is the primary purpose of using Retrieval Augmented Generation (RAG) with a Large Language Model?
2. In a typical Azure AI Search RAG pipeline, what is the role of the 'embedding' step?
3. When configuring an Azure AI Search index for RAG, why is 'chunking' your source documents important?
4. If your RAG application is returning irrelevant information, which of the following actions is the most effective way to improve retrieval quality?
5. You are implementing a RAG system and notice that the model occasionally ignores the retrieved context and answers based on its internal knowledge. What is the most likely cause?

Answers and explanations come after you submit.