How to Work with AI Workbench Projects

Overview

Projects are Git repositories with extra configuration files used by AI Workbench.

Projects hold your code and environment configuration along with a main configuration file, .project/spec.yaml.

Data and models can also be versioned in the repository, but more often than not these are downloaded and used on a machine by machine basis.

Projects use containers for development environments.

Each project has an editable and versioned containerized development environment. You customize it with package lists, scripts, and runtime configurations.

Projects are portable and reproducible.

AI Workbench handles the Git and container commands to build, run, and version your project.

You can version projects within the Desktop App and with Git natively.

The Desktop App has “easy buttons” for simple but end to end versioning workflows. For anything more complex, use Git in the terminal or a Git client.

You can work with any Git repository and AI Workbench will add the relevant configuration files.

If you clone a non-project in AI Workbench, it will prompt you to pick a base image for the development environment. It will also add in a scaffolded .project/spec.yaml file that is necessary for it to manage the repository.

Key Concepts

Project Container

A single container that serves as your development environment.

Project Specification

The .spec.yaml file that defines your project metadata and configuration. A versioned file that AI Workbench reads and writes to while handling the environment configuration.

Base Environments

Pre-configured container images from NVIDIA or custom containers.

Mounts

Persistent storage that survives container restarts.

Multi-Container Environments

Compose support for complex applications.

Git-LFS

Git large file support that can be used to version data files in the project. Can be configured in the spec.yaml file.

What’s Covered?

Topic Link	Description
Create, Clone, Publish and Delete Projects	Shows you how to create a new project in AI Workbench.
The Project Specification	Shows you how to understand the project specification in AI Workbench.