You're building a system where a language model should answer questions using a specific document collection instead of relying only on pretraining. You decide to use retrieval-augmented generation so responses stay grounded in source material.
What is retrieval-augmented generation (RAG)?
Understanding of retrieval plus generation as a two-stage NLP patternKnowledge of vector search and document chunkingAbility to connect retrieval quality to answer qualityAwareness of grounded evaluation for LLM outputs