Webhooks

Webhooks allow you to receive real-time updates about your predictions. By specifying an endpoint when creating a prediction, VaikerAI will send HTTP POST requests to that URL whenever the prediction is created, updated, or completed.

Example Use Cases for Webhooks

• Storing Prediction Data and Files: Predictions made through the API, including input and output files, are automatically deleted after an hour. Webhooks enable you to capture all metadata from a completed prediction, allowing you to save the data in a database or transfer the output files to persistent storage before they expire.

• Notifying on Completion of Long-Running Predictions: Some predictions, such as training jobs, may take several minutes to complete. With a webhook handler, you can send notifications, such as emails or Slack messages, once the prediction is finished.

• Building Model Pipelines: Webhooks can be used to capture the output of a long-running prediction and feed it directly into another model as input, enabling seamless integration across multiple models.

Note:

While webhooks are highly useful, they are not required to use VaikerAI. You can also monitor predictions using alternative methods like polling the predictions API or leveraging server-sent events (SSEs) to track the status of predictions over time.