voltagegpu-cli 1.1.0

VoltageGPU CLI - Manage GPU pods, confidential compute, and fine-tuning jobs from the command line. Deploy, train, and scale AI workloads on voltagegpu.com.

VoltageGPU CLI

Command-line interface and Python SDK for VoltageGPU - affordable GPU cloud computing for AI/ML workloads.

Installation

pip install voltagegpu-cli

Or install from source:

git clone https://github.com/voltagegpu/voltagegpu-cli.git
cd voltagegpu-cli
pip install -e .

Quick Start

1. Configure your API key

Set the environment variable:

export VOLT_API_KEY="your_api_key_here"

Or create a config file at ~/.volt/config.ini:

[api]
api_key = your_api_key_here

2. List available templates

volt templates list

3. Create a pod

volt pods create --template <template_id> --name my-gpu-pod

4. SSH into your pod

volt pods ssh <pod_id>

CLI Commands

Pods

# List all pods
volt pods list
volt pods list --json

# Get pod details
volt pods get <pod_id>

# Create a new pod
volt pods create --template <template_id> --name <name> [--gpu-count 1] [--ssh-key <key_id>]

# Start/Stop/Delete pods
volt pods start <pod_id>
volt pods stop <pod_id>
volt pods delete <pod_id> [--yes]

# Get SSH command
volt pods ssh <pod_id>

Templates

# List available templates
volt templates list
volt templates list --category llm
volt templates list --json

# Get template details
volt templates get <template_id>

SSH Keys

# List SSH keys
volt ssh-keys list

# Add a new SSH key
volt ssh-keys add --name "my-key" --file ~/.ssh/id_ed25519.pub
volt ssh-keys add --name "my-key" --key "ssh-ed25519 AAAA..."

# Delete an SSH key
volt ssh-keys delete <key_id>

Machines

# List available machines
volt machines list
volt machines list --gpu RTX4090
volt machines list --json

Account

# Check balance
volt account balance

# Get account info
volt account info

Configuration

# Show current configuration
volt config

Python SDK

You can also use VoltageGPU as a Python library:

from volt import VoltageGPUClient

# Initialize client (uses VOLT_API_KEY env var or ~/.volt/config.ini)
client = VoltageGPUClient()

# List pods
pods = client.list_pods()
for pod in pods:
    print(f"{pod.name}: {pod.status} ({pod.gpu_type})")

# Create a pod
pod = client.create_pod(
    template_id="template-123",
    name="my-training-pod",
    gpu_count=2
)
print(f"Created pod: {pod.id}")

# Get SSH connection info
pod = client.get_pod(pod.id)
print(f"SSH: ssh -p {pod.ssh_port} root@{pod.ssh_host}")

# Stop and delete
client.stop_pod(pod.id)
client.delete_pod(pod.id)

Context Manager

from volt import VoltageGPUClient

with VoltageGPUClient() as client:
    templates = client.list_templates()
    for t in templates:
        print(f"{t.name}: ${t.hourly_price}/hr")

Custom Configuration

from volt.sdk import Config, VoltageGPUClient

config = Config(
    api_key="your_api_key",
    base_url="https://voltagegpu.com/api"
)
client = VoltageGPUClient(config=config)

Environment Variables

Variable	Description	Default
VOLT_API_KEY	Your VoltageGPU API key	-
VOLT_BASE_URL	API base URL	https://voltagegpu.com/api
LIUM_API_KEY	Legacy API key (fallback)	-

Configuration File

Create ~/.volt/config.ini:

[api]
api_key = your_api_key_here

Output Formats

Most list commands support --json flag for machine-readable output:

volt pods list --json | jq '.[] | select(.status == "running")'

Examples

Launch a training job

# Find a suitable template
volt templates list --category ml

# Create pod with SSH key
volt pods create \
  --template pytorch-cuda12 \
  --name training-job \
  --gpu-count 4 \
  --ssh-key my-key-id

# Get SSH command
volt pods ssh <pod_id>

Monitor costs

# Check balance
volt account balance

# List running pods with costs
volt pods list | grep running

Batch operations with jq

# Stop all running pods
volt pods list --json | jq -r '.[] | select(.status == "running") | .id' | xargs -I {} volt pods stop {}

Support

• Website: https://voltagegpu.com
• Documentation: https://docs.voltagegpu.com
• Email: [e-mail]

License

MIT License - see LICENSE file for details.