RAG addresses LLM limitations around knowledge cutoffs and hallucination by grounding responses in retrieved documents.
Components
- Retriever: Finds relevant documents
- Knowledge base: Source documents
- Generator: LLM that synthesizes answer
Benefits
- Current information access
- Reduced hallucination
- Verifiable sources
- Domain specialization