Vector Databases Quiz

Quiz covering RAG and Knowledge Bases

Questions in this quiz

A preview of the 5 questions covered. Start the quiz above to answer them, check your score, and read the explanations.

1. 1

   What is the primary purpose of a vector database in a RAG (Retrieval-Augmented Generation) pipeline?

2. 2

   When building a RAG system, why is it important to perform 'chunking' on your source documents before storing them in a vector database?

3. 3

   Which of the following metrics is commonly used to measure the similarity between two vectors in a vector database?

4. 4

   If your RAG system is returning irrelevant documents, which step in the pipeline should you investigate first?

5. 5

   In the context of HNSW (Hierarchical Navigable Small World) indexing, what is the primary trade-off being managed?