Installation
The Vi SDK runs on Python 3.10 through 3.14 on Linux, macOS, and Windows. This page covers installation options, virtual environment setup, GPU configuration, and troubleshooting common issues.
Requirements
Check your Python version before installing:
The output should show Python 3.10 or higher.
Basic installation
The base install includes API functionality for:
- Dataset management
- Asset upload and download
- Annotation workflows
- Model operations
Optional feature sets
Install additional features as your workflow requires them.
Inference support
For running inference locally with vision-language models (Qwen2.5-VL, InternVL 3.5, Cosmos Reason1, NVILA):
Jupyter notebook support
For proper rich formatting and progress tracking in Jupyter notebooks:
Deployment support
For deploying models with NVIDIA NIM containers:
All features
Virtual environment setup
A virtual environment keeps Vi SDK's dependencies separate from other Python projects. This prevents version conflicts and makes your environment reproducible.
venv is included with Python and needs no additional install.Install conda via [Miniconda](https://docs.conda.io/en/latest/miniconda.html).uv is a fast alternative to pip and virtualenv.- venv: Built in, no setup needed. Good default.
- conda: Popular in data science. Manages Python versions directly.
- uv: Fastest install speeds. Good for large dependency trees like inference packages.
- virtualenvwrapper: Adds convenient shortcuts for managing multiple environments.
GPU support for inference
A GPU is not required for the base SDK or dataset operations, but it makes a significant difference for local inference. CPU inference works for development and small-scale testing.
NVIDIA GPUs (CUDA)
Verify CUDA is available:
import torch
print(f"CUDA available: {torch.cuda.is_available()}")
print(f"CUDA version: {torch.version.cuda}")
print(f"GPU count: {torch.cuda.device_count()}")
if torch.cuda.is_available():
print(f"GPU name: {torch.cuda.get_device_name(0)}")Apple Silicon (MPS)
PyTorch detects and uses Metal Performance Shaders automatically on Apple Silicon Macs with macOS 12.3+:
import torch
print(f"MPS available: {torch.backends.mps.is_available()}")
print(f"MPS built: {torch.backends.mps.is_built()}")CPU only
Performance reference:
Verifying the install
import vi
print(f"Vi SDK version: {vi.__version__}")
from vi import Client
from vi.dataset.loaders import ViDataset
print("Core modules loaded.")Platform-specific setup
Linux
macOS
Windows
Upgrading
Check your current version:
import vi
print(vi.__version__)Uninstalling
To remove everything including the virtual environment:
Troubleshooting
Next steps
Updated 4 months ago
