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Retrieval-Augmented Generation(RAG)
Definition
A technique that enhances LLM outputs by retrieving relevant information from external knowledge bases before generating responses.In-Depth Explanation
RAG addresses LLM limitations like outdated knowledge and hallucinations by grounding responses in retrieved documents. The process involves encoding documents into vectors, retrieving relevant chunks based on the query, and including them in the LLM prompt for informed generation.
Real-World Example
A customer support chatbot using RAG retrieves relevant help articles before answering questions.
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