RAG 시스템 실전 구축 (v38)

RAG combines retrieval, augmentation, and generation. Retrieval finds relevant documents via embeddings, augmentation injects context into prompts, and generation produces responses. Basic pipelines illustrate this loop with vector databases, embedding models, and LLMs.