Python SDK

pip install sinkove

import sinkove as sk

# Initialize with your API key
client = sk.client("your_API_KEY")

# Get all your datasets
datasets = client.list_datasets()

for dataset in datasets:
    print(f"Dataset: {dataset.id} - Status: {dataset.status}")

# Get dataset by ID
dataset = client.dataset("dataset_id_here")

# Check dataset status
if dataset.ready():
    print("Dataset is ready for download")
else:
    print(f"Dataset status: {dataset.status}")

import time

# Get dataset
dataset = client.dataset("dataset_id_here")

# Wait for completion
while not dataset.ready():
    print("Waiting for dataset to be ready...")
    time.sleep(10)

# Download to local file
dataset.save("./my_dataset.zip")
print("Dataset downloaded successfully!")

# Create a new dataset
dataset_config = {
    "model": "chest-xray-v2",
    "prompts": [
        "Severe cardiomegaly",
        "Normal chest X-ray",
        "Pneumonia with bilateral infiltrates"
    ],
    "size": 100
}

new_dataset = client.create_dataset(dataset_config)
print(f"Created dataset: {new_dataset.id}")

def wait_for_dataset(dataset, poll_interval=30):
    """Wait for dataset completion with progress updates"""
    while not dataset.ready():
        status = dataset.status
        progress = getattr(dataset, 'progress', 'Unknown')
        print(f"Dataset {dataset.id}: {status} - {progress}")
        time.sleep(poll_interval)

    print(f"Dataset {dataset.id} is ready!")
    return dataset

# Usage
dataset = client.dataset("your_dataset_id")
completed_dataset = wait_for_dataset(dataset)

# Download multiple datasets
dataset_ids = ["id1", "id2", "id3"]

for dataset_id in dataset_ids:
    dataset = client.dataset(dataset_id)
    if dataset.ready():
        filename = f"./datasets/{dataset_id}.zip"
        dataset.save(filename)
        print(f"Downloaded {dataset_id}")
    else:
        print(f"Dataset {dataset_id} not ready yet")

import sinkove as sk
from sinkove.exceptions import SinkovelAuthError, SinkovelAPIError

try:
    client = sk.client("your_API_KEY")
    dataset = client.dataset("dataset_id")

    if dataset.ready():
        dataset.save("./dataset.zip")
    else:
        print(f"Dataset not ready. Status: {dataset.status}")

except SinkovelAuthError:
    print("Authentication failed. Check your API key.")
except SinkovelAPIError as e:
    print(f"API error: {e}")
except Exception as e:
    print(f"Unexpected error: {e}")

export SINKOVE_API_KEY="your_api_key_here"
export SINKOVE_BASE_URL="https://api.sinkove.com"  # Optional

import os
import sinkove as sk

# SDK will automatically use SINKOVE_API_KEY
client = sk.client()

# Or override with custom settings
client = sk.client(
    api_key=os.getenv("SINKOVE_API_KEY"),
    base_url=os.getenv("SINKOVE_BASE_URL", "https://api.sinkove.com")
)

import sinkove as sk
import time
import os

def generate_and_download_dataset():
    """Complete example: create, monitor, and download dataset"""

    # Initialize client
    client = sk.client(os.getenv("SINKOVE_API_KEY"))

    # Create dataset
    config = {
        "model": "chest-xray-v2",
        "prompts": [
            "Severe cardiomegaly",
            "Bilateral pneumonia",
            "Normal chest X-ray"
        ],
        "size": 50
    }

    print("Creating dataset...")
    dataset = client.create_dataset(config)
    print(f"Dataset created: {dataset.id}")

    # Monitor progress
    print("Waiting for completion...")
    while not dataset.ready():
        print(f"Status: {dataset.status}")
        time.sleep(30)

    # Download
    filename = f"./medical_dataset_{dataset.id}.zip"
    dataset.save(filename)
    print(f"Dataset downloaded to: {filename}")

if __name__ == "__main__":
    generate_and_download_dataset()