import floret  # Assuming Floret is already installed


class FloretLangIdentifier:
    def __init__(self, model_path):
        self.model = floret.load_model(model_path)

    def predict(self, text):
        predictions = self.model.predict(text)
        return predictions






from transformers import Pipeline


class MyPipeline(Pipeline):
    def _sanitize_parameters(self, **kwargs):
        preprocess_kwargs = {}
        if "maybe_arg" in kwargs:
            preprocess_kwargs["maybe_arg"] = kwargs["maybe_arg"]
        return preprocess_kwargs, {}, {}

    def preprocess(self, inputs, maybe_arg=2):
        return inputs

    def _forward(self, model_inputs):
        # model_inputs == {"model_input": model_input}
        outputs = self.model.predict_language(**model_inputs)
        # Maybe {"logits": Tensor(...)}
        return outputs

    def postprocess(self, model_outputs):
        return model_outputs