Similarity search measures the distance between the question vector and every chunk vector in the index, then ranks the chunks by closeness. Because closeness in this space stands for similarity in meaning, the nearest chunks are the ones whose content is most related to the question. The result is an ordered list of candidate chunks rather than a single answer.
How AI Answers Questions About Documents It Never Learned