Skyvern Automations
skyvern
Automate your daily tasks with Skyvern on Each AI
Partner Model
Fast Inference
REST API
Model Information
Response Time~160 sec
StatusActive
Version
0.0.1
Updated21 days ago
Live Demo
Average runtime: ~160 seconds
Input
Configure model parameters
Output
View generated results
Result
Preview, share or download your results with a single click.

Each execution costs $0.11 With $1 you can run this model about 9 times.
API Reference
View Full DocumentationPrerequisites
- Create an API Key from the Eachlabs Console
- Install the required dependencies for your chosen language (e.g., requests for Python)
API Integration Steps
1. Create a Prediction
Send a POST request to create a new prediction. This will return a prediction ID that you'll use to check the result. The request should include your model inputs and API key.
import requestsimport timeAPI_KEY = "YOUR_API_KEY" # Replace with your API keyHEADERS = {"X-API-Key": API_KEY,"Content-Type": "application/json"}def create_prediction():response = requests.post("https://api.eachlabs.ai/v1/prediction/",headers=HEADERS,json={"model": "skyvern","version": "0.0.1","input": {"extracted_information_schema": "{\"product_image\": \"fill with the fetched product\"}","navigation_payload": "your navigation payload here","proxy_location": "RESIDENTIAL","data_extraction_goal": "Extract the URL of the main product image displayed on the product detail page.","navigation_goal": "Navigate to the product detail page using the provided URL. COMPLETE when the page is fully loaded and the product details are visible. Avoid clicking on any other links or buttons that might redirect away from the product page.","url": "https://www.amazon.com"}})prediction = response.json()if prediction["status"] != "success":raise Exception(f"Prediction failed: {prediction}")return prediction["predictionID"]
2. Get Prediction Result
Poll the prediction endpoint with the prediction ID until the result is ready. The API uses long-polling, so you'll need to repeatedly check until you receive a success status.
def get_prediction(prediction_id):while True:result = requests.get(f"https://api.eachlabs.ai/v1/prediction/{prediction_id}",headers=HEADERS).json()if result["status"] == "success":return resultelif result["status"] == "error":raise Exception(f"Prediction failed: {result}")time.sleep(1) # Wait before polling again
3. Complete Example
Here's a complete example that puts it all together, including error handling and result processing. This shows how to create a prediction and wait for the result in a production environment.
try:# Create predictionprediction_id = create_prediction()print(f"Prediction created: {prediction_id}")# Get resultresult = get_prediction(prediction_id)print(f"Output URL: {result['output']}")print(f"Processing time: {result['metrics']['predict_time']}s")except Exception as e:print(f"Error: {e}")
Additional Information
- The API uses a two-step process: create prediction and poll for results
- Response time: ~160 seconds
- Rate limit: 60 requests/minute
- Concurrent requests: 10 maximum
- Use long-polling to check prediction status until completion