Chapter 6: Advanced RAG Architectures and Techniques

Previous chapters detailed the construction and scaling of distributed Retrieval-Augmented Generation systems. Now, we turn to architectural patterns that address more complex challenges and information needs. This section focuses on advanced designs that expand the capabilities of standard RAG implementations.

You will learn to:

Implement multi-hop and iterative RAG for multi-step reasoning.
Develop agentic RAG systems capable of using distributed tools and services.
Integrate knowledge graphs with RAG in distributed settings to enhance contextual understanding.
Design self-correcting and self-improving RAG systems through feedback loops.
Adapt RAG systems to process highly dynamic information and streaming data.
Address security considerations particular to large-scale RAG deployments.
Build cross-lingual and multimodal RAG systems for diverse content types.

By the end of this chapter, you will be equipped to architect RAG solutions for a wider range of demanding applications.

Sections

6.1 Multi-Hop and Iterative RAG at Scale
6.2 Agentic RAG Systems with Distributed Tool Usage
6.3 Knowledge Graph-Augmented RAG in Distributed Settings
6.4 Self-Correcting and Self-Improving RAG Systems
6.5 Handling Highly Dynamic and Streaming Data Sources
6.6 Security Considerations in Large-Scale RAG Deployments
6.7 Cross-Lingual and Multimodal RAG at Scale
6.8 Practice: Designing a Multi-Stage RAG System