ROCm-RAG documentation#
2025-09-26
1 min read time
Build and deploy end-to-end AI pipelines with ROCm Retrieval-Augmented Generation (RAG) on AMD GPUs. RAG is a machine learning architecture that enhances Large Language Models by combining generation with information retrieval from external sources.
This documentation demonstrates how you can use RAG for document ingestion, embedding, retrieval, and generation. It outlines the necessary steps and components required to construct a complete RAG pipeline for this workflow.
See From Ingestion to Inference: RAG Pipelines on AMD GPUs for more information.
The component public repository is located at ROCm/rocm-rag.
To contribute to the documentation, refer to Contributing to ROCm.
You can find licensing information on the Licensing page.