# RAG Ecosystem and Paradigm Analysis ## RAG Ecosystem ### Downstream Tasks - Dialogue - Question answering - Summarization - Fact verification ### Technology Stacks - Langchain - LlamaIndex - FlowiseAI - AutoGen ## RAG Prospect ### Challenges - RAG in Long Context Length - Hybrid - Robustness - Scaling-laws for RAG - Production-ready RAG ### Modality Extension - Image - Audio - Video - Code ### Ecosystem - Customization - Simplification - Specialization ## The RAG Paradigm ### Progression 1. Naive RAG 2. Advanced RAG 3. Modular RAG ## Techniques for Better RAG ### Retrieval Techniques - Chunk Optimization - Iterative Retrieval - Retriever Fine-tuning - Query Transformation - Recursive Retrieval - Generator Fine-tuning - Context Selection - Adaptive Retrieval - Dual Fine-tuning ## Key Issues of RAG - What to retrieve - When to retrieve - How to use Retrieval ## Evaluation of RAG ### Evaluation Target - Retrieval Quality - Generation Quality ### Evaluation Aspects - Answer Relevance - Context Relevance - Answer Faithfulness - Noise Robustness - Negation Rejection - Information Integration - Counterfactual Robustness ### Evaluation Framework #### Benchmarks - CRUD - RGB - RECALL #### Tools - TruLens - RAGAS - ARES