Errors

Explanation and suggested solutions for common errors.

Unauthorized

You do not have the proper authentication.

• Check that the organization id and model id are both correct (check 👉 here)

• If these are correct, then generate a new ML API secret token as it is possible your previous one was invalidated or expired (generate 👉 here )

Organization {} does not have read permissions for model {}

You do not have the proper authentication to query the given model.

• Check that the model id is listed under model ids to which you have read and/or write access (check 👉 here )

• Check that the organization id and model id are both correct (check 👉 here)

Bad Request

The JSON input is not formatted correctly.

• If you are passing in a file make sure the path is correct

• Make sure the input is written using JSON syntax, for example:

  • booleans are lowercase (true, false)

  • null should be used rather than nan, NaN, None

• Look for trailing commas:

  • {"exampleFloat": 4, "exampleString": "example",}

Internal Server Error

The server could not process your request.

• Make sure you input json has the correct types

  • Check that your data and times are in ISO 8601 format

  • Check that ints and floats are consistent with their specified type

Error Message Including Schema Path

Example :

{"message":[{"instancePath":"","schemaPath":"/properties/weightClass","keyword":"properties","params":{"error":"missing","missingProperty":"weightClass"},"message":"must have property 'weightClass'"}]}

• Check if there is a parameter missing from your input JSON. In the example above the missing parameter is weightClass

• Check that the "Content-Type" is specified correctly in the header of your API request