# Advanced Patterns: Agentic, Graph and Multimodal RAG — Retrieval-Augmented Generation (RAG)

Source: https://www.geekswithgeeks.com/en/rag/p-advanced

> Know when simple retrieve-then-read is not enough.

## When one retrieval is not enough

Some questions need more than a single search. **Agentic RAG** lets the model decide to search several times, rewrite its query, choose between tools (documents, SQL, web) and stop when it has enough evidence; it is more capable but slower, costlier and harder to test. **Graph RAG** builds a knowledge graph of entities and relations to answer questions that span many documents ("which suppliers are linked to project X?"). **Multimodal RAG** retrieves images, tables and charts, for example through captions or multimodal embeddings. **Structured data** questions are often best answered by generating SQL rather than retrieving text. Adopt these only after the basic pipeline is measured and its limits are clear.

**Quiz:** When is agentic RAG most useful?

- [ ] To avoid evaluation
- [ ] For one-line FAQ lookups
- [x] When a question needs several searches or tools to answer
- [ ] To remove the LLM

*Answer:* When a question needs several searches or tools to answer. Multi-step questions benefit from iterative retrieval, at a cost in speed and complexity.