Advanced RAG Techniques: Hybrid Search & Metadata Enrichment

AI Impact Summary

This document outlines strategies for improving Retrieval-Augmented Generation (RAG) pipelines, focusing on enhancing indexing, retrieval, and generation. The core recommendation is to implement hybrid search combining semantic vector search with keyword search, alongside techniques like semantic chunking and metadata enrichment using models like GLiNER. This approach aims to improve retrieval recall by leveraging both semantic understanding and precise keyword matching, ultimately boosting the quality of responses generated by the LLM.