GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #65
GENERATIVE-AI-ENGINEER-ASSOCIATE Question #65: Real Exam Question with Answer & Explanation
The correct answer is A: Use a reranker to order the documents based on the relevance scores.. Using a reranker allows the team to reorder retrieved documents based on their actual relevance scores, improving the quality of context fed to the LLM. This approach directly addresses mismatches between initial retrieval ranking and true relevancy, optimizing the RAG pipeline
Question
A team uses Mosaic AI Vector Search to retrieve documents for their Retrieval-Augmented Generation (RAG) pipeline. The search query returns five relevant documents, and the first three are added to the prompt as context. Performance evaluation with Agent Evaluation shows that some lower-ranked retrieved documents have higher context relevancy scores than higher- ranked documents. Which option should the team consider to optimize this workflow?
Options
- AUse a reranker to order the documents based on the relevance scores.
- BModify the prompt to instruct the LLM to order the documents based on the relevance scores.
- CUse a different embedding model for computing document embeddings.
- DIncrease the number of documents added to the prompt to improve context relevance.
Explanation
Using a reranker allows the team to reorder retrieved documents based on their actual relevance scores, improving the quality of context fed to the LLM. This approach directly addresses mismatches between initial retrieval ranking and true relevancy, optimizing the RAG pipeline
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