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| name | description |
|---|---|
| dgx-spark-rag-ai-workbench | Install and use AI Workbench to clone and run a reproducible RAG application — on NVIDIA DGX Spark. Use when setting up rag-ai-workbench on Spark hardware. |
RAG Application in AI Workbench
Install and use AI Workbench to clone and run a reproducible RAG application
This walkthrough demonstrates how to set up and run an agentic retrieval-augmented generation (RAG) project using NVIDIA AI Workbench. You'll use AI Workbench to clone and run a pre-built agentic RAG application that intelligently routes queries, evaluates responses for relevancy and hallucination, and iterates through evaluation and generation cycles. The project uses a Gradio web interface and can work with both NVIDIA-hosted API endpoints or self-hosted models.
Outcome: You'll have a fully functional agentic RAG application running in NVIDIA AI Workbench with a web interface where you can submit queries and receive intelligent responses. The system will demonstrate advanced RAG capabilities including query routing, response evaluation, and iterative refinement, giving you hands-on experience with both AI Workbench's development environment and sophisticated RAG architectures.
Full playbook: /home/runner/work/dgx-spark-playbooks/dgx-spark-playbooks/nvidia/rag-ai-workbench/README.md