Retrieval-Augmented Generation (RAG)
NLP & Text
LLM enhanced with external knowledge retrieval
What is Retrieval-Augmented Generation (RAG)?
Combines LLMs with database search. Retrieves relevant documents, then generates responses based on retrieved context.
Real-World Examples
- •Chatbot answering from company docs
- •Q&A over documentation
- •Fact-based generation
When to Use This
When LLM needs up-to-date or specific domain knowledge
Related Terms
Learn more about concepts related to Retrieval-Augmented Generation (RAG)