skills.rest
yo-steven
yo-stevenCOMMUNITY
Explore all skills by this author →
GitHub

rag-blueprint

Deploy and manage NVIDIA RAG blueprints across Docker, Helm/Kubernetes, and library modes.

Updated May 23, 2026
Search Tags:#deployment#troubleshooting#rag#kubernetes#observability#docker compose#gpu inference
One-click install
npx skills add https://github.com/yo-steven/skills-exploration-20260522 --skill rag-blueprint
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rag-blueprint
Source: https://github.com/yo-steven/skills-exploration-20260522/tree/main/skills/rag/rag-blueprint
Command: npx skills add https://github.com/yo-steven/skills-exploration-20260522 --skill rag-blueprint

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill eliminates the trial-and-error needed to stand up and maintain an NVIDIA RAG stack by automatically routing requests to the right deployment, configuration, troubleshooting, and teardown procedures.

Core Features & Use Cases

  • Intent-based deployment & lifecycle management: Deploy, configure, debug, enable/disable, and shut down RAG components by interpreting user intent and selecting the correct operational reference flow.
  • Cross-platform orchestration (Docker, Helm/Kubernetes, and library mode): Detects what’s running locally (containers/pods/processes) and applies changes in the correct mode and config location.
  • Operational readiness, verification, and guided recovery: Performs environment analysis, health checks, platform detection, GPU/VRAM checks, and routes failures to troubleshooting playbooks without destructive actions unless explicitly requested.
  • Feature configuration coverage for the full RAG pipeline: Handles VLM, guardrails, query rewriting/decomposition, ingestion types, search/retrieval tuning, model/profile changes, summarization, observability, multimodal querying, MCP integration, and migration planning.

Quick Start

Deploy the RAG stack and get it healthy locally using the command: run rag-blueprint to deploy RAG.

Frequently Asked Questions about rag-blueprint

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy a production-grade RAG system with Kubernetes and Docker Compose?▼

Deploy a production-grade RAG system by interpreting user intent to automatically select the correct Docker, Helm/Kubernetes, or library mode configuration and apply the necessary setup workflows.

Can I configure guardrails and multimodal queries for my retrieval-augmented generation pipeline?▼

Yes, you can configure guardrails and multimodal queries for your retrieval-augmented generation pipeline, alongside VLM, query rewriting, and ingestion variants to tune the full search and retrieval workflow.

Does GPU inference require automated environment detection and VRAM checks before setup?▼

Yes, GPU inference requires automated environment detection and VRAM checks to ensure operational readiness, performing platform analysis and routing failures to troubleshooting playbooks without destructive actions.

What is the best way to troubleshoot an NVIDIA RAG stack that is not working?▼

The best way to troubleshoot an NVIDIA RAG stack is to use automated environment analysis and health checks via service endpoints, routing failures to guided recovery playbooks based on detected containers, pods, or processes.

Why do I need to safely prompt for NGC API keys and destructive cleanup during RAG teardown?▼

You need to safely prompt for NGC API keys and destructive cleanup during RAG teardown to prevent accidental data loss, ensuring the system avoids destructive actions unless explicitly requested by the user.

Do I need observability and MCP integration to run a multimodal RAG stack locally?▼

You need observability and MCP integration to run a multimodal RAG stack locally if you require monitoring and external tool communication, both of which are supported as configurable features in the pipeline.

Related Skills

Explore More Software Engineering Skills→
NVIDIANVIDIA
189

amc-setup-calibration-stack

Deploy AutoMagicCalib microservice and web UI via Docker Compose from NGC images.

Official
Advanced
llama-farmllama-farm
835

rag-skills

Audit and optimize RAG pipelines with LlamaIndex, ChromaDB, and Celery best practices.

Official
Basic
Divith123Divith123

Part XV - Infrastructure and Deployment

Define deployment and management guidelines for AI infrastructure with CI/CD pipelines.

Community
Advanced
Ced3-hanCed3-han

awq-quantization

Automate 4-bit activation-aware quantization for large language models.

Community
Advanced