Design and optimize a RAG system

Q: Design and optimize a RAG system

This question evaluates knowledge and competency in designing and optimizing Retrieval-Augmented Generation (RAG) systems, including components like ingestion, chunking, embeddings, indexing, retrieval, reranking, generation, and evaluation.

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Question

Scenario

You are building a Retrieval-Augmented Generation (RAG) system for question answering over an internal document corpus.

Task

Design the end-to-end architecture and describe optimization strategies.

Requirements

Ingest documents continuously (new/updated docs).
High answer quality with citations.
Low latency for interactive use.
Handle long documents and heterogeneous formats (PDF/HTML/wiki pages).

Deliverables

Components (ingestion, chunking, embeddings, index, retriever, reranker, generator).
How you improve relevance and reduce hallucinations.
Evaluation plan (offline + online) and monitoring for drift.

Design and optimize a RAG system

Scenario

Task

Requirements

Deliverables

Solution

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Design and optimize a RAG system

Overview

Scenario

Task

Requirements

Deliverables

Solution

Comments (0)