Install the Run:AI Command-line Interface¶

The Run:AI Command-line Interface (CLI) is one of the ways for a Researcher to send deep learning workloads, acquire GPU-based containers, list jobs, etc.

The instructions below will guide you through the process of installing the CLI.

Prerequisites¶

• When installing the command-line interface, it is worth considering future upgrades:

  • Install the CLI on a dedicated Jumpbox machine. Researches will connect to the Jumpbox from which they can submit Run:AI commands
  • Install the CLI on a shared directory that is mounted on Researchers' machines.

• Kubectl (Kubernetes command-line interface) installed and configured to access your cluster. Please refer to https://kubernetes.io/docs/tasks/tools/install-kubectl/.

• Helm. See https://helm.sh/docs/intro/install/ on how to install Helm. Run:AI works with Helm version 3 only (not helm 2).
• A Kubernetes configuration file obtained from the Kubernetes cluster installation.

Researcher Authentication¶

When enabled, Researcher authentication requires additional setup when installing the CLI. To configure authentication see Setup Project-based Researcher Access Control. Use the modified Kubernetes configuration file described in the article.

Setup¶

Kubernetes Configuration¶

• On the Researcher's root folder, create a directory .kube. Copy the Kubernetes configuration file into the directory. Each Researcher should have a separate copy of the configuration file. The Researcher should have write access to the configuration file as it stores user defaults.
• If you choose to locate the file at a different location than ~/.kube/config, you must create a shell variable to point to the configuration file as follows:

export KUBECONFIG=<Kubernetes-config-file>

• Test the connection by running:

kubectl get nodes

Install Run:AI CLI¶

• Download the latest release from the Run:AI releases page
• For MacOS - download the darwin-amd64 release, For Linux - download the linux-amd64 release.
• Unarchive the downloaded file
• Install by running:

sudo ./install-runai.sh

• To verify the installation run:

runai list jobs

Install Command Auto-Completion¶

It is possible to configure your Linux/Mac shell to complete Run:AI CLI commands. This feature works on bash and zsh shells only.

Zsh¶

Edit the file ~/.zshrc. Add the lines:

autoload -U compinit; compinit -i
source <(runai completion zsh)

Bash¶

Install the bash-completion package:

• Mac: brew install bash-completion
• Ubundu/Debian: sudo apt-get install bash-completion
• Fedora/Centos: sudo yum install bash-completion

Edit the file ~/.bashrc. Add the lines:

[[ -r “/usr/local/etc/profile.d/bash_completion.sh” ]] && . “/usr/local/etc/profile.d/bash_completion.sh”
source <(runai completion bash)

Troubleshooting the CLI Installation¶

See Troubleshooting a CLI installation

Update the Run:AI CLI¶

To update the CLI to the latest version run:

sudo runai update

Use Run:AI on Windows¶

Install Docker for Windows.

Get the following folder from GitHub: https://github.com/run-ai/docs/tree/master/cli/windows.

Replace config with your Kubernetes Configuration file.

Run: build.sh to create a docker image named runai-cli.

Test the image by running:

docker run -it runai-cli bash

Try and connect to your cluster from inside the docker by running a Run:AI CLI command. E.g. runai list projects.

Distribute the image to Windows users.