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Official CLI and Python SDK for Prime Intellect - access GPU compute, remote sandboxes, RL environments, and distributed training infrastructure for AI development at scale.
Command line interface and SDKs for managing Prime Intellect GPU resources, sandboxes, and environments.
Quick Start
# Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install prime
uv tool install prime
# Authenticate
prime login
# Browse verified environments
prime env list
# List available GPU resources
prime availability list
Features
Environments - Access hundreds of verified environments on our community hub
Evaluations - Push and manage evaluation results (supports JSON and verifiers format)
GPU Resource Management - Query and filter available GPU resources
Pod Management - Create, monitor, and terminate compute pods
Sandboxes - Easily run AI-generated code in the cloud
SSH Access - Direct SSH access to running pods
Team Support - Manage resources across team environments
Installation
Using uv (recommended)
First, install uv if you haven't already:
curl -LsSf https://astral.sh/uv/install.sh | sh
Then install prime:
uv tool install prime
Using pip
pip install prime
Sandboxes SDK Only
If you only need the sandboxes SDK (lightweight, ~50KB):
# Interactive mode (recommended - hides input)
prime config set-api-key
# Non-interactive mode (for automation)
prime config set-api-key YOUR_API_KEY
# Environment variable (most secure for scripts)export PRIME_API_KEY="your-api-key-here"
Other Configuration
# Configure SSH key for pod access
prime config set-ssh-key-path
# View current configuration
prime config view
Security Note: When using non-interactive mode, the API key may be visible in your shell history. For enhanced security, use interactive mode or environment variables.
Environments Hub
Access hundreds of verified environments on our community hub with deep integrations with sandboxes, training, and evaluation stack.
# Browse available environments
prime env list
# View environment details
prime env info <environment-name># Install an environment locally
prime env install <environment-name># Create and push your own environment
prime env init my-environment
prime env push my-environment
GPU Resources
# List all available GPUs
prime availability list
# Filter by GPU type
prime availability list --gpu-type H100_80GB
# Show available GPU types
prime availability gpu-types
Pod Management
# List your pods
prime pods list
# Create a pod
prime pods create
prime pods create --id <ID># With specific GPU config
prime pods create --name my-pod # With custom name# Monitor and manage pods
prime pods status <pod-id>
prime pods terminate <pod-id>
prime pods ssh <pod-id>
Evaluations
Push and manage evaluation results to the Environments hub. Supports verifiers format and JSON format.
# Auto-discover and push evaluations from current directory
prime eval push
# Push specific directory
prime eval push examples/verifiers_example
# List all evaluations
prime eval list
# Get evaluation details
prime eval get <eval-id># View evaluation samples
prime eval samples <eval-id>
# List teams
prime teams list
# Set team context
prime config set-team-id
Development
# Clone the repository
git clone https://github.com/PrimeIntellect-ai/prime-cli
cd prime-cli
# Set up workspace (installs all packages in editable mode)
uv sync
# Install CLI globally in editable mode
uv tool install -e packages/prime
# Now you can use the CLI directly
prime --help
# Run tests
uv run pytest packages/prime/tests
uv run pytest packages/prime-sandboxes/tests
All packages (prime-core, prime-sandboxes, prime) are installed in editable mode. Changes to code are immediately reflected.
Releasing
This monorepo contains two independently versioned packages: prime (CLI + full SDK) and prime-sandboxes (lightweight SDK).
Versions are single-sourced from each package's __init__.py file:
Update the __version__ string in the appropriate __init__.py file
Commit and push the change
Tagging and publishing to PyPI is handled automatically by CI.
Version sync considerations:
When releasing prime, consider whether prime-sandboxes should also be bumped, as prime depends on prime-sandboxes. The packages can be released independently or together depending on what changed.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Official CLI and Python SDK for Prime Intellect - access GPU compute, remote sandboxes, RL environments, and distributed training infrastructure for AI development at scale.
