| Name | prime JSON |
| Version |
0.4.9
JSON |
| download |
| home_page | None |
| Summary | Prime Intellect CLI + SDK |
| upload_time | 2025-10-29 17:28:04 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.14,>=3.10 |
| license | None |
| keywords |
cli
cloud
compute
gpu
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<p align="center">
<picture>
<source media="(prefers-color-scheme: light)" srcset="https://github.com/user-attachments/assets/40c36e38-c5bd-4c5a-9cb3-f7b902cd155d">
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/user-attachments/assets/6414bc9b-126b-41ca-9307-9e982430cde8">
<img alt="Prime Intellect" src="https://github.com/user-attachments/assets/40c36e38-c5bd-4c5a-9cb3-f7b902cd155d" width="312" style="max-width: 100%;">
</picture>
</p>
---
<h3 align="center">
Prime Intellect CLI & SDKs
</h3>
---
<div align="center">
[](https://pypi.org/project/prime/)
[](https://pypi.org/project/prime/)
[](https://pypi.org/project/prime/)
Command line interface and SDKs for managing Prime Intellect GPU resources, sandboxes, and environments.
</div>
## Overview
Prime is the official CLI and Python SDK for [Prime Intellect](https://primeintellect.ai), providing seamless access to GPU compute infrastructure, remote code execution environments (sandboxes), and AI inference capabilities.
**What can you do with Prime?**
- Deploy GPU pods with H100, A100, and other high-performance GPUs
- Create and manage isolated sandbox environments for running code
- Access hundreds of pre-configured development environments
- SSH directly into your compute instances
- Manage team resources and permissions
- Run OpenAI-compatible inference requests
## Installation
### Using uv (recommended)
First, install uv if you haven't already:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
Then install prime:
```bash
uv tool install prime
```
### Using pip
```bash
pip install prime
```
## Quick Start
### Authentication
```bash
# Interactive login (recommended)
prime login
# Or set API key directly
prime config set-api-key
# Or use environment variable
export PRIME_API_KEY="your-api-key-here"
```
Get your API key from the [Prime Intellect Dashboard](https://app.primeintellect.ai).
### Basic Usage
```bash
# Browse environments on the hub
prime env list
# List available GPUs
prime availability list
# Create a GPU pod
prime pods create --gpu A100 --count 1
# SSH into a pod
prime pods ssh <pod-id>
# Create a sandbox
prime sandbox create --image python:3.11
```
## Features
### Environments Hub
Access hundreds of RL environments on our community hub with deep integrations with sandboxes, training, and evaluation stack.
```bash
# 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
```
Environments provide pre-configured setups for machine learning, data science, and development workflows, tested and verified by the Prime Intellect community.
### GPU Pod Management
Deploy and manage GPU compute instances:
```bash
# Browse available configurations
prime availability list --gpu-type H100_80GB
# Create a pod with specific configuration
prime pods create --id <config-id> --name my-training-pod
# Monitor pod status
prime pods status <pod-id>
# SSH access
prime pods ssh <pod-id>
# Terminate when done
prime pods terminate <pod-id>
```
### Sandboxes
Isolated environments for running code remotely:
```bash
# Create a sandbox
prime sandbox create --image python:3.11
# List sandboxes
prime sandbox list
# Execute commands
prime sandbox exec <sandbox-id> "python script.py"
# Upload/download files
prime sandbox upload <sandbox-id> local_file.py /remote/path/
prime sandbox download <sandbox-id> /remote/file.txt ./local/
# Clean up
prime sandbox delete <sandbox-id>
```
### Team Management
Manage resources across team contexts:
```bash
# List your teams
prime teams list
# Set team context
prime config set-team-id <team-id>
# All subsequent commands use team context
prime pods list # Shows team's pods
```
## Configuration
### API Key
Multiple ways to configure your API key:
```bash
# Option 1: Interactive (hides input)
prime config set-api-key
# Option 2: Direct
prime config set-api-key YOUR_API_KEY
# Option 3: Environment variable
export PRIME_API_KEY="your-api-key"
```
Configuration priority: CLI config > Environment variable
### SSH Key
Configure SSH key for pod access:
```bash
prime config set-ssh-key-path ~/.ssh/id_rsa.pub
```
### View Configuration
```bash
prime config view
```
## Python SDK
Prime also provides a Python SDK for programmatic access:
```python
from prime_sandboxes import APIClient, SandboxClient, CreateSandboxRequest
# Initialize client
client = APIClient(api_key="your-api-key")
sandbox_client = SandboxClient(client)
# Create a sandbox
sandbox = sandbox_client.create(CreateSandboxRequest(
name="my-sandbox",
docker_image="python:3.11-slim",
cpu_cores=2,
memory_gb=4,
))
# Wait for creation
sandbox_client.wait_for_creation(sandbox.id)
# Execute commands
result = sandbox_client.execute_command(sandbox.id, "python --version")
print(result.stdout)
# Clean up
sandbox_client.delete(sandbox.id)
```
### Async SDK
```python
import asyncio
from prime_sandboxes import AsyncSandboxClient, CreateSandboxRequest
async def main():
async with AsyncSandboxClient(api_key="your-api-key") as client:
sandbox = await client.create(CreateSandboxRequest(
name="async-sandbox",
docker_image="python:3.11-slim",
))
await client.wait_for_creation(sandbox.id)
result = await client.execute_command(sandbox.id, "echo 'Hello'")
print(result.stdout)
await client.delete(sandbox.id)
asyncio.run(main())
```
## Use Cases
### Machine Learning Training
```bash
# Deploy a pod with 8x H100 GPUs
prime pods create --gpu H100 --count 8 --name ml-training
# SSH and start training
prime pods ssh <pod-id>
```
## Support & Resources
- **Documentation**: [github.com/PrimeIntellect-ai/prime-cli](https://github.com/PrimeIntellect-ai/prime-cli)
- **Dashboard**: [app.primeintellect.ai](https://app.primeintellect.ai)
- **API Docs**: [api.primeintellect.ai/docs](https://api.primeintellect.ai/docs)
- **Discord**: [discord.gg/primeintellect](https://discord.gg/primeintellect)
- **Website**: [primeintellect.ai](https://primeintellect.ai)
## Related Packages
- **prime-sandboxes** - Lightweight SDK for sandboxes only (if you don't need the full CLI)
## License
MIT License - see [LICENSE](https://github.com/PrimeIntellect-ai/prime-cli/blob/main/LICENSE) file for details.
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"description": "<p align=\"center\">\n <picture>\n <source media=\"(prefers-color-scheme: light)\" srcset=\"https://github.com/user-attachments/assets/40c36e38-c5bd-4c5a-9cb3-f7b902cd155d\">\n <source media=\"(prefers-color-scheme: dark)\" srcset=\"https://github.com/user-attachments/assets/6414bc9b-126b-41ca-9307-9e982430cde8\">\n <img alt=\"Prime Intellect\" src=\"https://github.com/user-attachments/assets/40c36e38-c5bd-4c5a-9cb3-f7b902cd155d\" width=\"312\" style=\"max-width: 100%;\">\n </picture>\n</p>\n\n---\n\n<h3 align=\"center\">\nPrime Intellect CLI & SDKs\n</h3>\n\n---\n\n<div align=\"center\">\n\n[](https://pypi.org/project/prime/)\n[](https://pypi.org/project/prime/)\n[](https://pypi.org/project/prime/)\n\nCommand line interface and SDKs for managing Prime Intellect GPU resources, sandboxes, and environments.\n</div>\n\n## Overview\n\nPrime is the official CLI and Python SDK for [Prime Intellect](https://primeintellect.ai), providing seamless access to GPU compute infrastructure, remote code execution environments (sandboxes), and AI inference capabilities.\n\n**What can you do with Prime?**\n\n- Deploy GPU pods with H100, A100, and other high-performance GPUs\n- Create and manage isolated sandbox environments for running code\n- Access hundreds of pre-configured development environments\n- SSH directly into your compute instances\n- Manage team resources and permissions\n- Run OpenAI-compatible inference requests\n\n## Installation\n\n### Using uv (recommended)\n\nFirst, install uv if you haven't already:\n\n```bash\ncurl -LsSf https://astral.sh/uv/install.sh | sh\n```\n\nThen install prime:\n\n```bash\nuv tool install prime\n```\n\n### Using pip\n\n```bash\npip install prime\n```\n\n## Quick Start\n\n### Authentication\n\n```bash\n# Interactive login (recommended)\nprime login\n\n# Or set API key directly\nprime config set-api-key\n\n# Or use environment variable\nexport PRIME_API_KEY=\"your-api-key-here\"\n```\n\nGet your API key from the [Prime Intellect Dashboard](https://app.primeintellect.ai).\n\n### Basic Usage\n\n```bash\n# Browse environments on the hub\nprime env list\n\n# List available GPUs\nprime availability list\n\n# Create a GPU pod\nprime pods create --gpu A100 --count 1\n\n# SSH into a pod\nprime pods ssh <pod-id>\n\n# Create a sandbox\nprime sandbox create --image python:3.11\n```\n\n## Features\n\n### Environments Hub\n\nAccess hundreds of RL environments on our community hub with deep integrations with sandboxes, training, and evaluation stack.\n\n```bash\n# Browse available environments\nprime env list\n\n# View environment details\nprime env info <environment-name>\n\n# Install an environment locally\nprime env install <environment-name>\n\n# Create and push your own environment\nprime env init my-environment\nprime env push my-environment\n```\n\nEnvironments provide pre-configured setups for machine learning, data science, and development workflows, tested and verified by the Prime Intellect community.\n\n### GPU Pod Management\n\nDeploy and manage GPU compute instances:\n\n```bash\n# Browse available configurations\nprime availability list --gpu-type H100_80GB\n\n# Create a pod with specific configuration\nprime pods create --id <config-id> --name my-training-pod\n\n# Monitor pod status\nprime pods status <pod-id>\n\n# SSH access\nprime pods ssh <pod-id>\n\n# Terminate when done\nprime pods terminate <pod-id>\n```\n\n### Sandboxes\n\nIsolated environments for running code remotely:\n\n```bash\n# Create a sandbox\nprime sandbox create --image python:3.11\n\n# List sandboxes\nprime sandbox list\n\n# Execute commands\nprime sandbox exec <sandbox-id> \"python script.py\"\n\n# Upload/download files\nprime sandbox upload <sandbox-id> local_file.py /remote/path/\nprime sandbox download <sandbox-id> /remote/file.txt ./local/\n\n# Clean up\nprime sandbox delete <sandbox-id>\n```\n\n### Team Management\n\nManage resources across team contexts:\n\n```bash\n# List your teams\nprime teams list\n\n# Set team context\nprime config set-team-id <team-id>\n\n# All subsequent commands use team context\nprime pods list # Shows team's pods\n```\n\n## Configuration\n\n### API Key\n\nMultiple ways to configure your API key:\n\n```bash\n# Option 1: Interactive (hides input)\nprime config set-api-key\n\n# Option 2: Direct\nprime config set-api-key YOUR_API_KEY\n\n# Option 3: Environment variable\nexport PRIME_API_KEY=\"your-api-key\"\n```\n\nConfiguration priority: CLI config > Environment variable\n\n### SSH Key\n\nConfigure SSH key for pod access:\n\n```bash\nprime config set-ssh-key-path ~/.ssh/id_rsa.pub\n```\n\n### View Configuration\n\n```bash\nprime config view\n```\n\n## Python SDK\n\nPrime also provides a Python SDK for programmatic access:\n\n```python\nfrom prime_sandboxes import APIClient, SandboxClient, CreateSandboxRequest\n\n# Initialize client\nclient = APIClient(api_key=\"your-api-key\")\nsandbox_client = SandboxClient(client)\n\n# Create a sandbox\nsandbox = sandbox_client.create(CreateSandboxRequest(\n name=\"my-sandbox\",\n docker_image=\"python:3.11-slim\",\n cpu_cores=2,\n memory_gb=4,\n))\n\n# Wait for creation\nsandbox_client.wait_for_creation(sandbox.id)\n\n# Execute commands\nresult = sandbox_client.execute_command(sandbox.id, \"python --version\")\nprint(result.stdout)\n\n# Clean up\nsandbox_client.delete(sandbox.id)\n```\n\n### Async SDK\n\n```python\nimport asyncio\nfrom prime_sandboxes import AsyncSandboxClient, CreateSandboxRequest\n\nasync def main():\n async with AsyncSandboxClient(api_key=\"your-api-key\") as client:\n sandbox = await client.create(CreateSandboxRequest(\n name=\"async-sandbox\",\n docker_image=\"python:3.11-slim\",\n ))\n\n await client.wait_for_creation(sandbox.id)\n result = await client.execute_command(sandbox.id, \"echo 'Hello'\")\n print(result.stdout)\n\n await client.delete(sandbox.id)\n\nasyncio.run(main())\n```\n\n## Use Cases\n\n### Machine Learning Training\n\n```bash\n# Deploy a pod with 8x H100 GPUs\nprime pods create --gpu H100 --count 8 --name ml-training\n\n# SSH and start training\nprime pods ssh <pod-id>\n```\n## Support & Resources\n\n- **Documentation**: [github.com/PrimeIntellect-ai/prime-cli](https://github.com/PrimeIntellect-ai/prime-cli)\n- **Dashboard**: [app.primeintellect.ai](https://app.primeintellect.ai)\n- **API Docs**: [api.primeintellect.ai/docs](https://api.primeintellect.ai/docs)\n- **Discord**: [discord.gg/primeintellect](https://discord.gg/primeintellect)\n- **Website**: [primeintellect.ai](https://primeintellect.ai)\n\n## Related Packages\n\n- **prime-sandboxes** - Lightweight SDK for sandboxes only (if you don't need the full CLI)\n\n## License\n\nMIT License - see [LICENSE](https://github.com/PrimeIntellect-ai/prime-cli/blob/main/LICENSE) file for details.\n",
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