# AI5.2 Retrieval Augmented Generation

This skill introduces the concept of Retrieval-Augmented Generation (RAG), where external knowledge sources are queried and integrated into the generation process. It covers retrieval pipelines, indexing strategies, and deployment in HPC environments.

## Requirements

* External: Familiarity with LLMs and vector search concepts
* Internal: None

## Learning Outcomes

* Define the RAG architecture and explain how it improves generative model performance.
* Describe the components of a retrieval pipeline, including query formulation, embedding, and indexing.
* Identify vector databases and similarity metrics used in AI retrieval tasks.
* Integrate retrieval results into prompt templates or model input streams.
* Evaluate RAG systems based on latency, accuracy, and grounding quality.

** Caution: All text is AI generated **