You can load Graders that have been previously created in the platform automatically using the Grader class (excluding Recipe Graders, which only exist as code within your custom recipe).

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Include AdaptiveGrader in InputConfig

In order to do this, you must only make sure that one or more AdaptiveGraders can be passed to your recipe as input: 
from pydantic import Field
from typing import Annotated, Set

from adaptive_harmony.runtime import InputConfig, AdaptiveGrader

class GraderRecipeConfig(InputConfig):
    graders: Annotated[
        Set[AdaptiveGrader],
        Field(
            description="The graders to load.
            title="Graders",
        ),
    ]
The AdaptiveGrader object will contain all the configuration necessary to instantiate a Grader in code, with the exact same properties you’ve defined in the Adaptive platform.

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Load with Grader.from_config

You can then automatically load and setup your graders with Grader.from_config(): 
from adaptive_harmony.graders import Grader
from adaptive_harmony.runtime import RecipeContext

@recipe_main
async def main(config: GraderRecipeConfig, ctx: RecipeContext):
    graders = []
    for grader in config.graders:
        this_grader = Grader.from_config(
            config=grader,
            client=ctx.client,
            # the following params are optional
            # used for Binary Judge and prebuilt Graders
            tp=2,   
            kv_cache_len=200_000
        )
        # setup Grader
        this_grader.setup()
        graders.append(this_grader)
Now the Graders are ready to use for training, evaluation, or anything else you find use for!