Skip to content

Doondi-Ashlesh/nvidia-sdk-orchestartor

Repository files navigation

NVIDIA SDK ORCHESTRATOR -v2

An interactive graph that maps NVIDIA's entire AI product stack — describe your goal in plain English and Nemotron AI generates the exact step-by-step path and generates an Notebook to get started with. (New system updates underway)

Workflow Path


What It Does

Developers approaching NVIDIA's AI stack face a fragmented landscape — NIM, NeMo, Triton, TensorRT, Brev — with no map showing how they relate or where to start.

This tool solves that by:

  • Visualising all 25 official NVIDIA AI services as an interactive hexagonal graph
  • Drawing documented connection edges between services (no invented relationships)
  • Letting you describe any goal in plain English — LlaMa 3.3 Nemotron super 49b v1 AI maps the right services in the correct layer order
  • Highlighting your path on the graph with animated edges + step-by-step guidance
  • Explore mode — click any node to see its official description and docs in the sidebar

Screenshots

AI-Generated Workflow Path

Describe a goal → Nemotron maps the exact NVIDIA services with roles and actions per step.

AI Path — Fine-tune an LLM


HUD Tooltip on Active Node

Hover any node during a workflow to see its official description and a direct link to NVIDIA docs.

HUD Tooltip


Explore Mode — Full Graph

Browse all 18 services freely with full visibility. All connections visible at once.

Explore Mode


Explore Mode — Click a Node

Click any node to load its full official description, tags, and connections in the sidebar.

Explore Mode — Node Detail



Features

Feature Description
AI Path Generator Type any AI goal — Groq (llama-3.3-70b) returns the correct NVIDIA service path with roles and actions per step
Strict layer ordering Paths always flow Access → SDK → Frameworks → Agentic AI → Serving → Enterprise
Cannot-verify fallback If no documented path exists, the AI declines and suggests relevant services instead of fabricating an answer
Interactive hex graph Pan, zoom, click — full React Flow canvas with smoothstep connection arrows
Game HUD tooltips Hover any node for a scanline-style panel with description, tags, and official docs link
Layer zoom Hover a layer column header to zoom the canvas into that layer's services
Explore mode Browse every service freely — click a node to load its full description and connections in the sidebar
Workflow step navigator Follow AI-generated paths step-by-step with auto-pan to each active node and a progress bar
Glassmorphism UI Hex nodes with blur + NVIDIA green glow on hover/active states, pitch-black canvas
Responsive Hamburger sidebar on mobile, abbreviated layer labels at tablet widths

Tech Stack

Technology
Framework Next.js 16 (App Router) + TypeScript
Styling Tailwind CSS v4
Graph @xyflow/react v12
Animations Framer Motion
AI Groq SDK — llama-3.3-70b-versatile
Icons Lucide React

NVIDIA Services Covered

18 services across 6 layers — all sourced from official NVIDIA documentation.

Layer Services
Access build.nvidia.com · NVIDIA Brev · NGC Catalog · DGX Cloud
SDK / Runtime CUDA Toolkit · cuDNN · TensorRT · TensorRT-LLM
Frameworks NVIDIA NeMo · NeMo Curator · NeMo Guardrails · NeMo Retriever · AI Workbench · RAPIDS
Agentic AI NVIDIA Nemotron · NeMo Agent Toolkit · NVIDIA Blueprints
Serving NVIDIA Dynamo-Triton · NIM Microservices
Enterprise NVIDIA AI Enterprise

Getting Started

Prerequisites

Installation

git clone https://github.com/Doondi-Ashlesh/nvidia-ecosystem-visualizer.git
cd nvidia-ecosystem-visualizer
npm install

Environment

Create .env.local in the project root:

GROQ_API_KEY=your_groq_api_key_here

Run

npm run dev

Open http://localhost:3000


Deploy to Vercel

Deploy with Vercel

  1. Click the button above or import the repo at vercel.com/new
  2. Add the environment variable: GROQ_API_KEY = your Groq API key
  3. Deploy — Vercel auto-detects Next.js

How the AI Path Generation Works

The Groq prompt enforces strict rules before returning any path:

  1. Layer ordering — steps must flow access → sdk → framework → agent → serving → enterprise
  2. Documented connections only — only officially-documented service relationships are used
  3. Self-verification — the model checks layer order, connection validity, and docs grounding before responding
  4. Cannot-verify fallback — unrecognised goals return a structured response listing suggested services to investigate, never a fabricated path

Project Structure

nvidia-ecosystem-visualizer/
├── app/
│   ├── api/generate-flow/    # Groq AI path generation endpoint
│   ├── page.tsx              # Root page — layout, state, layer column headers
│   ├── layout.tsx            # Root layout
│   └── globals.css           # Global styles + React Flow theme overrides
├── components/
│   ├── EcosystemGraph.tsx    # React Flow canvas — nodes, edges, fitView logic
│   ├── ServiceNode.tsx       # Custom hex node (glassmorphism + Framer Motion)
│   ├── NodeTooltip.tsx       # Game HUD hover tooltip
│   └── Sidebar.tsx           # Goal input · AI path navigator · explore panel
├── data/
│   └── nvidia.ts             # 18 services with source comments → official NVIDIA docs
├── types/
│   └── ecosystem.ts          # TypeScript types + NVIDIA brand colour constants
└── lib/
    └── workflow.ts           # Pure helpers: getWorkflowNodeIds, getWorkflowEdgePairs

Data Integrity

Every entry in data/nvidia.ts includes a source comment linking to the exact official NVIDIA page it was pulled from (docs.nvidia.com, developer.nvidia.com). No descriptions are invented or inferred.


Packages

 
 
 

Contributors