import numpy as np
import bentoml
from bentoml.io import NumpyNdarray

# assuming modeltags holds all available models on device
runner_list = []
for model_tag in modeltags:
    runner_list.add[bentoml.sklearn.get("model_tag").to_runner()]

svc = bentoml.Service("detection", runners=runner_list)


for idx in range(len(runner_list)):
	@svc.api(input=NumpyNdarray(), output=NumpyNdarray(), route=f"runner_{idx}")
	def classify(input_series: np.ndarray) -> np.ndarray:
		result = iris_clf_runner[i].predict.run(input_series)
		return result