@Scout: how i can use config_schema with dbt_assets decorator

The

dbt_assets

decorator in Dagster is used to create assets from a dbt project. When using

dbt_assets

, you typically specify the path to the dbt project's manifest file and optionally provide a custom

DagsterDbtTranslator

for customizing how dbt assets are represented in Dagster. However, the

dbt_assets

decorator itself does not directly accept a

config_schema

argument for defining configuration schemas like you would with individual ops or assets. Instead, the configuration for dbt assets is generally derived from the dbt project configuration and the

DbtCliResource

that is used to execute dbt commands. If you need to pass specific configuration to dbt when using

dbt_assets

, you would configure the

DbtCliResource

that is passed to the

dbt_assets

function. This resource can be configured with the necessary dbt project directory, profiles directory, and other dbt-related settings. Here's an example from the documentation on how to use the

dbt_assets

decorator:

python from dagster import AssetExecutionContext, dbt_assets from dagster_dbt import DbtCliResource  @dbt_assets(     manifest_path="path/to/manifest.json",     # Additional arguments like io_manager_key can be specified here ) def my_dbt_assets(context: AssetExecutionContext, dbt: DbtCliResource):     # Execute dbt commands using the dbt CLI resource     yield from dbt.cli(["build"], context=context).stream()

In this example, the

DbtCliResource

is implicitly used by the

dbt_assets

function, and you can configure it separately in your job or repository definition to include the necessary dbt configuration. If you need to customize the configuration of the

DbtCliResource

, you can do so when defining your job or repository. Here's an example of how to configure the `DbtCliResource`:

python from dagster import job from dagster_dbt import dbt_cli_resource  my_job = job(     resource_defs={         "dbt": dbt_cli_resource.configured(             {                 "project_dir": "path/to/dbt/project",                 "profiles_dir": "path/to/dbt/profiles",                 # Other dbt CLI configurations can be specified here             }         )     } )

In this job definition, the

dbt_cli_resource

is configured with the necessary dbt project and profiles directories. You can add additional configuration options as needed for your dbt project. Remember that the configuration for dbt assets is primarily driven by the dbt project's own configuration files (

dbt_project.yml

and

profiles.yml

) and the settings provided to the

DbtCliResource

. The

dbt_assets

decorator leverages these configurations to execute dbt commands and create assets in Dagster.