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Navigate to the corresponding Business Model in the MOC UI (under Models).
Click on Schema.
Click on Generate Extended Schema.
You should see the following window pop-up:
Enter the data you want to use to infer a schema in the top box. The data must be formatted as one-line dictionaries, as in the following sample:
Code Block language py {"UUID": "9a5d9f42-3f36-4f38-88dd-22353fdb66a7", "amount": 8875.50, "home_ownership": "MORTGAGE", "age": "Over Forty", "credit_age": 4511, "employed": true, "label": 1, "prediction": 1} {"UUID": "f8d95245-a186-45a6-b951-376323d06d02", "amount": 9000, "home_ownership": "MORTGAGE", "age": "Under Forty", "credit_age": 7524, "employed": false, "label": 0, "prediction": 1} {"UUID": "8607e327-4dca-4372-a4b9-df7730f83c8e", "amount": 5000.50, "home_ownership": "RENT", "age": "Under Forty", "credit_age": null, "employed": true, "label": 0, "prediction": 0}Click on Generate Schema. The following generated schema should be produced:
The schema can then be downloaded or saved as Input/Output Schema.
The recommended best practice is to download the generated schema, and then add it as an asset to the business model being monitored in the model’s git repository. Once the schema is properly versioned along with the source code (e.g. in a Github repo), one doesn’t have to regenerate the schema anymore. Note that MOC will not push the generated schema to the model repo; it is up to the user to do so.
Note: If generating the extended schema for monitoring purposes, you should save it as an input schema; the OOTB monitors will look for an extended input schema to set the monitoring parameters.
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