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Retrieval Augmented Generation

3 items tagged with "retrieval-augmented-generation"

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Best Practices1

Best Practice

Retrieval-Augmented Generation (RAG) Best Practices

RAG grounds a large language model in external documents retrieved at query time, reducing hallucination and letting answers reflect current, private data without retraining the model.

Tutorials1

Tutorial

How to build a RAG pipeline for question answering

Build a retrieval-augmented generation pipeline that grounds an LLM's answers in your own documents using chunking, embeddings, and a vector store.

Glossaries1

Glossary

Retrieval-Augmented Generation (RAG)

Retrieval-augmented generation is a technique that retrieves relevant documents at query time and supplies them to an LLM as context so its answers are grounded in external data.