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Cosmos Cookbook

Documentation Contributing

A comprehensive guide for working with the NVIDIA Cosmos ecosystem—a suite of World Foundation Models (WFMs) for real-world, domain-specific applications across robotics, simulation, autonomous systems, and physical scene understanding.

📚 View the Full Documentation → — Step-by-step workflows, case studies, and technical recipes

carousel.mp4

Latest Updates

Date Recipe Model Description
Jan 6 Dataset Video Clustering with Time Series K-Means Cosmos Curator Advanced video clustering using Time Series K-Means on embedding vector trajectories for robotics behavior analysis
Jan 5 Post-train Cosmos Reason 2 for AV Video Captioning and VQA Cosmos Reason 2 Domain adaptation for autonomous vehicle video captioning with multi-benchmark evaluation
Jan 1 Egocentric Social Reasoning for Robotics Cosmos Reason 2 Egocentric social and physical reasoning evaluation for social robotics
Jan 1 Reason 2 on Brev Cosmos Reason 2 Getting started guide for Cosmos Reason 2 inference and post-training on Brev
Dec 22 Multiview AV Generation with World Scenario Maps Cosmos Transfer 2.5 ControlNet post-training for spatially-conditioned multiview AV video generation
Dec 20 Vision AI Gallery Cosmos Transfer 2.5 Interactive gallery showcasing weather, lighting, and object augmentations for traffic scenarios

Prerequisites

Use Case Linux (Ubuntu) macOS Windows
Running cookbook recipes (GPU workflows) ✅ Supported
Local documentation & contribution ✅ Supported ✅ Supported ⚠️ WSL recommended

For Documentation & Contribution (All Platforms)

  • Git with Git LFS
  • Python: Version 3.10+
  • Internet access for cloning and dependencies

For Running Cookbook Recipes (Ubuntu Only)

Full GPU workflows require an Ubuntu Linux environment with NVIDIA GPUs.

→ See Getting Started for complete hardware and software requirements.

Quick Start

1. Install Git LFS (Required)

⚠️ Important: This repository contains many media files (videos, images, demonstrations). Git LFS is required to clone and work with this repository properly.

# Ubuntu/Debian (recommended)
sudo apt update && sudo apt install git-lfs

# Enable Git LFS globally
git lfs install

For other platforms (macOS, Windows, Fedora), see the official installation guide at git-lfs.com.

If you've already cloned without LFS, fetch the media files with:

git lfs pull

2. Install System Dependencies

# Install uv (fast Python package manager)
curl -LsSf https://astral.sh/uv/install.sh | sh
source $HOME/.local/bin/env

# Install just (command runner)
uv tool install -U rust-just

For other platforms, see astral.sh/uv for installation instructions.

3. Clone and Setup Repository

# Clone the repository
git clone https://github.com/nvidia-cosmos/cosmos-cookbook.git
cd cosmos-cookbook

# Install dependencies and setup
just install

4. Explore the Documentation

# Serve documentation locally
just serve-external  # For public documentation
# or
just serve-internal   # For internal documentation (if applicable)

Then open http://localhost:8000 in your browser.

Repository Structure

The Cosmos Cookbook is organized into two main directories:

docs/

Contains the source documentation in markdown files:

  • Technical guides and workflows
  • End-to-end examples and case studies
  • Step-by-step recipes and tutorials
  • Getting started guides

scripts/

Contains executable scripts referenced throughout the cookbook:

  • Data processing and curation pipelines
  • Model evaluation and quality control scripts
  • Configuration files for post-training tasks
  • Automation tools and utilities

This structure separates documentation from implementation, making it easy to navigate between reading about workflows and executing the corresponding scripts.

Media File Guidelines

When contributing media files, prefer .mp4 over .gif:

  • Better quality — MP4 supports full color depth vs GIF's 256-color limit
  • Smaller file size — Modern video codecs compress far more efficiently
  • Audio support — MP4 can include narration when needed

Use H.264 encoding for universal browser compatibility.

Available Commands

# Development
just install          # Install dependencies and setup
just setup            # Setup pre-commit hooks
just serve-external   # Serve public documentation locally
just serve-internal   # Serve internal documentation locally

# Quality Control
just lint            # Run linting and formatting
just test            # Run all tests and validation

# Continuous Integration
just ci-lint         # Run CI linting checks
just ci-deploy-internal         # Deploy internal documentation
just ci-deploy-external         # Deploy external documentation

Contributing & Support

  • Contributing Guide - How to contribute to the cookbook
  • Report Issues: Use GitHub Issues for bugs and feature requests
  • Share Success Stories: We love hearing how you use Cosmos models creatively

License and Contact

This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.

NVIDIA Cosmos source code is released under the Apache 2 License.

NVIDIA Cosmos models are released under the NVIDIA Open Model License. For a custom license, please contact cosmos-license@nvidia.com.

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Post-training scripts and samples for NVIDIA Cosmos ecosystem

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