All 7 RAG Pipeline Architecture questions
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Retrieval Augmented Generation (RAG) › RAG Pipeline Architecture

How does RAG Pipeline Architecture work

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Answer

A typical pipeline converts a user query into an embedding, retrieves relevant documents from a vector database, then feeds those documents along with the query into a language model to generate a final answer.
Real-world example A well designed RAG pipeline architecture ensures the retrieved documents are relevant before passing them to the language model for a final response.

Common follow-ups: What is Retrieval Augmented Generation (RAG), How is RAG Pipeline Architecture evaluated in practice, What tools are commonly used for RAG Pipeline Architecture

Retrieval Augmented Generation (RAG) topics: Introduction to Retrieval Augmented Generation Vector Databases for RAG Embedding Models for Retrieval
All 7 RAG Pipeline Architecture questions