packet-gpu-cli

Command-line interface for packet.ai GPU cloud.

Installation

``bash
npm install -g packet-gpu-cli
`

Quick Start

`bash


Login to your packet.ai account

packet login

List available GPU types

packet gpus

Launch a GPU with VS Code pre-installed

packet launch --gpu rtx-pro-6000 --setup vscode

Launch a bare GPU and wait for SSH

packet launch --gpu h100 --wait

List your running instances

packet ps

SSH into an instance

packet ssh

View instance logs

packet logs

Terminate an instance

packet terminate
`

Commands

$3

| Command | Description |
|---------|-------------|
| packet login | Authenticate with your API key |
| packet logout | Remove stored credentials |
| packet whoami | Show current account and balance |

$3

| Command | Description |
|---------|-------------|
| packet gpus | List available GPU types and pricing |
| packet launch --gpu | Launch a new GPU instance |
| packet ps | List your running instances |
| packet ssh | SSH into an instance |
| packet logs | View instance status and info |
| packet terminate | Terminate an instance |

$3

| Command | Description |
|---------|-------------|
| packet setup list | List available setup presets |
| packet setup | Run a setup preset on an existing instance |
| packet launch --setup | Launch with auto-setup |

$3

Launch a new GPU instance.

Options:
- -g, --gpu - GPU type (e.g., rtx-pro-6000, h100)
- -n, --name - Instance name
- -s, --setup - Auto-setup preset (see below)
- --gpus - Number of GPUs (default: 1)
- -w, --wait - Wait for instance to be ready

$3

Auto-setup apps on GPU instances. Available presets:

| Preset | Description | Port |
|--------|-------------|------|
| vscode | VS Code in Browser (code-server) | 8080 |
| jupyter | Jupyter Lab with data science packages | 8888 |
| jupyter-torch | Jupyter Lab with PyTorch and CUDA | 8888 |
| workspace | Persistent workspace linking | - |
| full-dev | VS Code + Jupyter + Persistence | 8080, 8888 |

Launch with auto-setup:
`bash
packet launch --gpu rtx-pro-6000 --setup vscode
packet launch --gpu h100 --setup full-dev --name "my-dev-box"
`

Setup an existing instance:
`bash
packet setup vscode 12345
packet setup jupyter-torch 12345
`

List presets:
`bash
packet setup list
`

$3

SSH into a running instance. Automatically uses the correct credentials.

Options:
- -c, --command - Run a command instead of interactive shell
- --copy - Print the SSH command without connecting

$3

View instance status and connection info.

$3

Terminate a running instance.

Options:
- -f, --force - Skip confirmation prompt

Configuration

Credentials are stored securely in your system's config directory:
- macOS: ~/Library/Preferences/packet-cli-nodejs/
- Linux: ~/.config/packet-cli-nodejs/
- Windows: %APPDATA%/packet-cli-nodejs/

Requirements

- Node.js 18.0.0 or higher
- An account at packet.ai
- sshpass for packet setup on existing instances (install with brew install sshpass or apt install sshpass)

Examples

$3

`bash
packet launch --gpu rtx-pro-6000 --setup vscode --name "dev-server"
`

$3

`bash
packet launch --gpu h100 --setup full-dev


Includes VS Code (port 8080), Jupyter (port 8888), and persistent workspace


`

$3

`bash


Get your instance ID

packet ps

Install Jupyter + PyTorch

packet setup jupyter-torch 12345
`

$3

`bash


In GitHub Actions or similar


packet login --key $PACKET_API_KEY
INSTANCE=$(packet launch --gpu h100 --wait | grep "Instance ID" | awk '{print $3}')
packet ssh $INSTANCE -c "cd /workspace && python train.py"
packet terminate $INSTANCE -f
``

Support

- Website: packet.ai
- Documentation: packet.ai/cli
- Email: support@packet.ai

License

MIT