Fix issues from @angyaloliver's feedback
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12 changed files with 30 additions and 26 deletions
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@ -43,6 +43,7 @@ results = [
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print(results)
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```
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1. Only return the outputs so we don't clutter up the terminal.
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> Run this script as a regular Python script by executing `python3 client.py`.
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@ -76,7 +76,7 @@ assert type_safe_greeter('Andras').output == 'Hi Andras'
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### Using `@parameter`
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If you wish to turn of logging or specify custom validation for your parameters, you can use the [@parameter][great_ai.parameter] decorator.
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If you wish to turn off logging or specify custom validation for your parameters, you can use the [@parameter][great_ai.parameter] decorator.
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!!! note
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By default, all parameters that are not affected by an explicit [@parameter][great_ai.parameter] or [@use_model][great_ai.use_model] are automatically decorated with [@parameter][great_ai.parameter] when [@GreatAI.create][great_ai.GreatAI.create] is called.
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@ -85,7 +85,7 @@ If you wish to turn of logging or specify custom validation for your parameters,
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from great_ai import GreatAI, use_model
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@GreatAI.create
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@use_model('name_of_my_model', version='latest')
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@parameter('your_name', disable_logging=True)
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def type_safe_greeter(your_name: str, model) -> str:
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return f'Hi {your_name}!'
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@ -105,7 +105,7 @@ from great_ai import save_model, GreatAI, parameter, use_model, log_metric
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save_model(4, 'secret-number') #(1)
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@GreatAI.create
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@parameter('positive_number', validator=lambda n: n > 0, disable_logging=True)
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@parameter('positive_number', validate=lambda n: n > 0, disable_logging=True)
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@use_model('secret-number', version='latest', model_kwarg_name='secret')
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def add_number(positive_number: int, secret: int) -> int:
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log_metric(
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@ -1,4 +1,4 @@
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# How to deploy a GreatAI service
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# How to perform prediction with GreatAI
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After [creating a GreatAI service](/how-to-guides/create-service) by wrapping your prediction function, and optionally [configuring it](/how-to-guides/configure-service), it's time to do some prediction.
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