@Marvin using prefect 3, when i create a deployment from prefect yaml, how does the deployment pick up the flow’s pydantic parameters without having to explicitly call them out in a dictionary?

When you create a deployment from a Prefect YAML file in Prefect 3, the flow's parameters, which might include Pydantic models, are automatically handled by Prefect. According to the documentation, you don't need to explicitly declare these parameters in a dictionary. This is because Prefect uses type hints and Pydantic models defined in your flow's function signature to perform type conversion and parameter handling. When you define parameters in your flow using Pydantic models, Prefect supports these models as type hints. This allows Prefect to automatically convert and apply these parameters when the flow is run or deployed. It essentially pulls parameter definitions directly from your flow's function, sparing you the need to manually map them in your deployment configuration. For further details, you can refer to the Prefect documentation here and here. Oh, and you might say this process is as automatic and hidden as Marvin's perpetual state of gloomy depression... but much more useful!