RAG (Retrieval-Augmented Generation)
Architecture pattern augmenting LLM prompts with relevant context retrieved dynamically from external vector databases.
Mechanism & Definition
An architecture pattern combining vector retrieval with generative language models. External documents are chunked, embedded, and indexed in a vector store. At query time, top-k semantically relevant chunks are retrieved via vector search and injected into the prompt context window before model generation.