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Advanced RAG Techniques Overview Recent developments in retrieval-augmented generation have led to three distinct paradigms: Naive RAG Advenced RAG Modular RAG This article explores these approaches and demonstrates how to implement an advanced RAG pipeline using LlamaIndex with Python. We'll cover three key optimization techniques: Pre-retr ...

Rendering a LlamaIndex Workflow as an Interactive Diagram The last missing piece in our exploration of LlamaIndex’s execution engine is the single line that turns the abstract workflow into a browsable picture. The helper draw_all_possible_flows consumes a workflow class and produces an HTML file that can be opened in any modern browser. from l ...

Current RAG Landscape Retrieval-Augmented Generation has evolved far beyond simple vector search. The latest survey "Retrieval-Augmented Generation for Large Language Models" highlights three active areas of innovation: Query-side augmentation (query transformation) Agentic orchestration of retrieval Post-retrieval refinement Self-R ...