UZ CLI (SAMI)

Python SDK and CLI for the UnitZero / SAMI Dataset Distribution Platform. Upload, download, and manage robotics datasets in LeRobot format.

Note: Dataset uploads require platform admin privileges (globalRole: platform_admin). Regular users can browse and download datasets but cannot upload.

Installation

pip install uz-cli

For development:

cd sami-cli
pip install -e ".[dev]"

Quick Start (CLI)

# Login with invite code (simplest)
uz login --code <YOUR-INVITE-CODE>

# Or login via browser
uz login

# Or login with email/password
uz login --password

# List datasets
uz list

# Upload a dataset (requires admin)
uz upload ./my_dataset --name "Robot Arm Demo"

# Download a dataset
uz download <dataset-id> --output ./downloaded

# Show your info
uz whoami

# Logout
uz logout

CLI Reference

Command	Description
uz login --code <CODE>	Login with invite code
uz login	Authenticate via browser or email/password
uz logout	Clear saved credentials
uz whoami	Show current user info
uz config	View/set configuration
uz list	List accessible datasets
uz upload <path>	Upload a LeRobot dataset
uz download <id>	Download a dataset
uz info <id>	Show dataset details
uz delete <id>	Delete a dataset

Command Options

# Upload with options
uz upload ./dataset \
    --name "My Dataset" \
    --description "Kitchen manipulation tasks" \
    --task-category manipulation \
    --workers 8

# Download with options
uz download abc123 \
    --output ./my_data \
    --workers 8

# List with filters
uz list --status ready --limit 50

# Set custom API URL
uz config --api-url https://api.example.com/api/v1

Environment Variables

For CI/CD pipelines, you can use environment variables instead of uz login:

Variable	Description
SAMI_API_URL	Override API URL
SAMI_ACCESS_TOKEN	Use token directly (skip login)
SAMI_INVITE_CODE	Invite code for anonymous join (skip login)
SAMI_EMAIL	Email for login
SAMI_PASSWORD	Password for login

# Example: CI/CD usage with invite code
export SAMI_INVITE_CODE="your-invite-code"
uz list
uz download abc123

# Or use a token directly
export SAMI_ACCESS_TOKEN="your-jwt-token"
uz list

Python SDK

Using Saved Credentials

After running uz login, use credentials in Python:

from sami_cli import SamiClient

# Use saved credentials from ~/.uz/
client = SamiClient.from_saved_credentials()

# List datasets
datasets = client.list_datasets()
for ds in datasets:
    print(f"{ds.name}: {ds.episode_count} episodes")

Invite Code Authentication

from sami_cli import SamiClient

# Authenticate with invite code
client = SamiClient(invite_code="your-invite-code")

# Download a dataset
client.download_dataset(
    dataset_id="<dataset-id>",
    output_path="./downloaded_dataset",
)

Email/Password Authentication

from sami_cli import SamiClient

# Authenticate with email/password
client = SamiClient(
    email="user@example.com",
    password="your-password",
)

# Upload a LeRobot dataset (admin only)
dataset = client.upload_dataset(
    name="my-dataset-v1",
    path="/path/to/lerobot/dataset",
    description="Kitchen manipulation tasks",
    task_category="manipulation",
)
print(f"Uploaded: {dataset.id}")

API Methods

# Authentication
client.login(email, password)
client.get_current_user()

# Datasets
client.list_datasets(page=1, limit=20, status=None)
client.get_dataset(dataset_id)
client.upload_dataset(name, path, description=None, task_category=None, max_workers=4)
client.download_dataset(dataset_id, output_path, max_workers=4)
client.delete_dataset(dataset_id)

# Sharing
client.assign_dataset(dataset_id, organization_id, permission_level)
client.remove_assignment(dataset_id, assignment_id)

LeRobot Format

Datasets must be in LeRobot format:

my_dataset/
  meta/
    info.json       # Required: episodes, frames, fps, features
    stats.json      # Optional: statistics
    episodes/       # Optional: episode metadata
  data/
    chunk-000/      # Parquet files with episode data
    chunk-001/
  videos/           # Optional: video files
    chunk-000/

The meta/info.json must contain:

• total_episodes: Number of episodes
• total_frames: Total frame count
• fps: Frames per second

LeRobot Integration

Downloaded datasets work directly with LeRobot:

from lerobot.common.datasets.lerobot_dataset import LeRobotDataset

# Load downloaded dataset
dataset = LeRobotDataset("./my_dataset")

# Use in training
for batch in dataset:
    observation = batch["observation.state"]
    action = batch["action"]
    # ... train your model

Dataset Object

@dataclass
class Dataset:
    id: str
    name: str
    description: Optional[str]
    task_category: Optional[str]
    robot_type: Optional[str]
    episode_count: Optional[int]
    total_frames: Optional[int]
    fps: Optional[float]
    file_size_bytes: int
    upload_status: str  # pending, uploading, processing, ready, failed
    created_at: datetime
    organization_name: str
    features: Optional[Dict[str, Any]]
    assignments: List[Dict[str, Any]]

Exceptions

from sami_cli import (
    SamiError,              # Base exception
    AuthenticationError,    # Login failed
    NotFoundError,          # Resource not found
    PermissionDeniedError,  # Access denied
    UploadError,            # Upload failed
    DownloadError,          # Download failed
    ValidationError,        # Invalid dataset format
)

Requirements

• Python >= 3.9
• requests >= 2.28.0
• tqdm >= 4.65.0