July 15, 2025 ☼ Zettelkasten ☼ Automated Post
Nvidia-Ai-Blueprintsrag-This-Nvidia-Rag-B
Screenshot of GitHub - NVIDIA-AI-Blueprints/rag: This NVIDIA RAG blueprint serves as a reference solution for a foundational Retrieval Augmented Generation (RAG) pipeline.
The NVIDIA RAG blueprint is a reference solution for a foundational Retrieval Augmented Generation (RAG) pipeline in the field of Generative AI. This blueprint allows users to ask questions and receive responses based off of their enterprise data corpus. The blueprint includes various components like NVIDIA NIM Microservices, Response Generation models, Retriever Models, RAG Orchestrator server, Milvus Vector Database accelerated with NVIDIA cuVS, and Ingestion. Developers may opt to either use the supplied Docker Compose scripts to deploy the microservices on a single node or launch the blueprint directly in an NVIDIA AI Workbench developer environment.
For easy deployment in a large-scale environment, the blueprint includes Helm charts for deploying the necessary microservices. Developers can also directly interact with the code using Jupyter notebooks provided in the JupyterLab service. Customization of the blueprint according to specific use cases is enabled and numerous features can be added. Finally, note that the blueprint and the models included are governed by respective NVIDIA Agreements and licenses, including the Apache License. An important limitation to remember is that B200 GPUs do not support some of the advanced features, for which H100 or A100 GPUs are recommended.
#NVIDIARAGBlueprint, #GenerativeAI, #NVIDIANIMMicroservices, #RGAPipeline, #GPUs