Demystifying Advanced RAG Pipelines: This web content aims to shed light on how advanced RAG pipelines, powered by large language models, work. While frameworks like LlamaIndex and Haystack provide abstraction for building these pipelines, they lack transparency. The content explains the inner workings of RAG pipelines, including the processes of retrieval-augmented generation, sub-question generation, vector/summary retrieval, and response aggregation. It emphasizes the importance of prompt templates and reveals challenges such as question sensitivity and cost dynamics. Understanding these intricacies is crucial for building robust and efficient question answering systems.
https://github.com/pchunduri6/rag-demystified