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What is Retrieval-Augmented Generation (RAG), and why is it important?
原题Explain the architecture of a basic RAG system.
原题What are the key components of a RAG pipeline?
原题What are chunking strategies, and how do you choose the right chunk size?
原题Compare fixed-size chunking, semantic chunking, and recursive chunking.
原题What is Contextual Retrieval, and how does it improve RAG?
原题What are embedding models, and how do they convert text to vectors?
原题How do you choose an embedding model for your RAG system?
原题Explain Agentic RAG.
原题What is hybrid search, and why is it better than pure vector search?
原题What is re-ranking, and how does it improve RAG retrieval quality?
原题What is ColBERT, and how does late interaction retrieval work?
原题Compare reranker architectures: cross-encoder, ColBERT, and LLM-based rerankers.
原题How do you handle multi-document and multi-hop questions in RAG?
原题What is the "lost in the middle" problem in RAG systems?
原题How do you evaluate a RAG system? Explain faithfulness, relevance, and context precision/recall.
原题Explain Self-RAG. How does the model decide when to retrieve?
原题What is GraphRAG, and when would you use it over traditional RAG?
原题Vectorless RAG
原题How do you handle structured data (tables, SQL databases) in a RAG pipeline?
原题What are the common failure modes of RAG systems, and how do you debug them?
原题How do you handle document updates and maintain freshness in a RAG system?
原题How do you optimize RAG for latency in production?
原题What is the role of metadata filtering in RAG systems?
原题Compare RAG vs fine-tuning. When would you use each?
原题Long context windows keep getting cheaper. When should you use retrieval (RAG) vs putting everything in the context window?
原题What is query transformation in RAG (HyDE, query decomposition, step-back prompting)?
原题How do you implement citation and source attribution in RAG?
原题How do you scale a RAG system to millions of documents?
原题What is parent-child chunking, and how does it improve retrieval?
原题Your RAG system is hallucinating despite having the right context. How do you fix it?
原题Your RAG chunk overlap causes redundant results. How do you reduce redundancy?
原题Your RAG retrieval is too slow with a large knowledge base. How do you speed it up?
原题Your RAG system returns duplicate results. How do you deduplicate?
原题Your RAG system needs per-user access control on internal documents. How do you implement it?
原题Your RAG system fails on domain-specific jargon. How do you fix it?
原题Your text-only RAG system now needs to handle images and tables. How do you extend it?
原题Your RAG knowledge base gets updated frequently and needs versioning. How do you manage it?
原题Your RAG system fails on multi-hop questions that require combining multiple facts. How do you fix it?
原题Your enterprise RAG system returns contradictory answers from different source documents. How do you resolve conflicts?
原题Your RAG system returns outdated answers from an evolving knowledge base. How do you keep it current?
原题Your RAG system struggles with PDF documents containing tables and layouts. How do you fix PDF parsing?
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