REST API

Authorization: Bearer ul_your_api_key_here

curl -H "Authorization: Bearer ul_abc123..." \
  https://platform.ultralytics.com/api/datasets

https://platform.ultralytics.com/api

X-RateLimit-Limit: 60
X-RateLimit-Remaining: 55
X-RateLimit-Reset: 1640000000

{
  "success": true,
  "data": { ... },
  "meta": {
    "page": 1,
    "limit": 20,
    "total": 100
  }
}

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid dataset ID",
    "details": { ... }
  }
}

GET /api/datasets

{
    "success": true,
    "data": [
        {
            "id": "dataset_abc123",
            "name": "my-dataset",
            "slug": "my-dataset",
            "task": "detect",
            "imageCount": 1000,
            "classCount": 10,
            "visibility": "private",
            "createdAt": "2024-01-15T10:00:00Z"
        }
    ]
}

GET /api/datasets/{datasetId}

POST /api/datasets

{
    "name": "my-dataset",
    "task": "detect",
    "description": "A custom detection dataset"
}

DELETE /api/datasets/{datasetId}

POST /api/datasets/{datasetId}/export

GET /api/projects

GET /api/projects/{projectId}

POST /api/projects

{
    "name": "my-project",
    "description": "Detection experiments"
}

DELETE /api/projects/{projectId}

GET /api/models

GET /api/models/{modelId}

POST /api/models

DELETE /api/models/{modelId}

GET /api/models/{modelId}/files

POST /api/models/{modelId}/predict

{
    "success": true,
    "predictions": [
        {
            "class": "person",
            "confidence": 0.92,
            "box": { "x1": 100, "y1": 50, "x2": 300, "y2": 400 }
        }
    ]
}

POST /api/training/start

{
    "modelId": "model_abc123",
    "datasetId": "dataset_xyz789",
    "epochs": 100,
    "imageSize": 640,
    "gpuType": "rtx-4090"
}

GET /api/models/{modelId}/training

DELETE /api/models/{modelId}/training

GET /api/deployments

POST /api/deployments

{
    "modelId": "model_abc123",
    "region": "us-central1",
    "minInstances": 0,
    "maxInstances": 10
}

GET /api/deployments/{deploymentId}

POST /api/deployments/{deploymentId}/start

POST /api/deployments/{deploymentId}/stop

DELETE /api/deployments/{deploymentId}

GET /api/deployments/{deploymentId}/metrics

GET /api/deployments/{deploymentId}/logs

GET /api/exports

POST /api/exports

{
    "modelId": "model_abc123",
    "format": "onnx"
}

GET /api/exports/{exportId}

GET /api/activity

POST /api/activity/mark-seen

POST /api/activity/archive

GET /api/trash

POST /api/trash

{
    "itemId": "item_abc123",
    "type": "dataset"
}

POST /api/trash/empty

GET /api/billing/balance

{
    "success": true,
    "data": {
        "cashBalance": 5000000,
        "creditBalance": 20000000,
        "reservedAmount": 0,
        "totalBalance": 25000000
    }
}

GET /api/billing/usage-summary

POST /api/billing/checkout-session

{
    "amount": 25
}

POST /api/billing/subscription-checkout

POST /api/billing/portal-session

GET /api/billing/payments

GET /api/storage

{
    "success": true,
    "data": {
        "used": 1073741824,
        "limit": 107374182400,
        "percentage": 1.0
    }
}

POST /api/gdpr

{
    "action": "export"
}

GET /api/api-keys

POST /api/api-keys

{
    "name": "training-server",
    "scopes": ["training", "models"]
}

DELETE /api/api-keys/{keyId}

import os

from ultralytics import YOLO

# Set API key
os.environ["ULTRALYTICS_API_KEY"] = "ul_your_key"

# Train with Platform integration
model = YOLO("yolo11n.pt")
model.train(data="ul://username/datasets/my-dataset", project="username/my-project", name="experiment-1", epochs=100)

GET /api/datasets?page=2 &
limit=50

import time


def api_request_with_retry(url, max_retries=3):
    for attempt in range(max_retries):
        response = requests.get(url)
        if response.status_code != 429:
            return response
        wait = 2**attempt
        time.sleep(wait)
    raise Exception("Rate limit exceeded")