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