The EASIEST Possible Strategy for Accurate RAG (Step by Step Guide)
AI Summary
This video provides a practical guide on enhancing Retrieval Augmented Generation (RAG) accuracy through Contextual Retrieval, specifically contextual embeddings introduced by Anthropic. The tutorial demonstrates how to build an AI agent using N8N that effectively retrieves external knowledge from various document sources, such as Google Drive. The video outlines the limitations of basic RAG and emphasizes the importance of adding context to improve accuracy. Key strategies discussed include contextual retrieval, embedding documents into a vector database, and combining different enhancement strategies to significantly reduce retrieval failure rates to less than 3%. The presenter also shares implementation techniques, considerations for cost-effectiveness, and showcases a simple integration of contextual retrieval in Python. Overall, viewers learn how to implement this approach to build robust AI agents, alongside valuable resources and links for further exploration.