Building an end-to-end Retrieval- Augmented Generation (RAG) workflow
This post provides a comprehensive guide on setting up a retrieval-augmented generation (RAG) pipeline using open source tools like Charmed OpenSearch and KServe, specifically in Azure and Ubuntu environments. It covers key components of a RAG system, including data processing, embedding models, retrieval, vector databases, and more, while emphasizing the importance of scalability, security, and the use of open source solutions.

