Using the machine learning endpoint as an adopted application
- Get a list of registered endpoints
- Get the schema of an endpoint
- Retrieve a prediction for a given endpoint.
- Retrieve a detailed prediction for a given endpoint
This table shows the process of calling the endpoints through API Gateway:
Endpoint | Coleman/v1/endpoints | Coleman/v1/endpoints/{endpoint name}/schema | Coleman/v1/endpoints/{endpoint name}/prediction | Coleman/v1/endpoints/{endpoint name}/detailed-prediction |
---|---|---|---|---|
Method | GET | GET | POST | POST |
Type | List | Schema | Prediction | Detailed prediction |
Description | Get a list of endpoints. Retrieve a list of registered endpoints. |
Get the schema for a given endpoint. Retrieve the endpoint schema based on the endpoint name. Use the schema to create the input for the prediction method. |
Retrieve a prediction for a given endpoint. Provide input data for a given endpoint and retrieve prediction based on the input values. |
Retrieve a detailed prediction for a given endpoint. Provide input data for a given endpoint and retrieve prediction based on the input values. Input data is expected in key-value pairs according to the endpoint schema definition. The response is returned in the same format. |
Input | Status: Active | endpoint name | endpoint name Input values for prediction put into the JSON. For example:
Bulk & single upload of predictions schema |
endpoint name Input values for prediction put into an array of JSONs. For example:
|
Output |
|
JSON schema for selected endpoint name | predictions | input data with predictions, everything in the key-value pair format. Output of
the example from above:
|