Building an Effective RAG Pipeline: A Guide to Integrating Self-RAG, Corrective RAG, and Adaptive RAG

A comprehensive guide to building an effective Retrieval-Augmented Generation (RAG) pipeline by integrating Self-RAG, Corrective RAG, and Adaptive RAG. This pipeline aims to intelligently handle questions of varying complexity, ensure information accuracy, and generate useful answers. It leverages LangGraph for stateful, multi-agent workflows, and includes methods for routing questions, retrieving documents, evaluating relevance, and grading output quality.