import tensorflow as tf
from tensorflow_serving.apis import predict_pb2, prediction_service_pb2_grpc

class CustomModelHandler:
    def __init__(self, model_path):
        self.model = tf.keras.models.load_model(model_path)

    def predict(self, request: predict_pb2.PredictRequest) -> predict_pb2.PredictResponse:
        # Custom preprocessing
        inputs = request.inputs['input_tensor'].numpy()

        # Model prediction
        predictions = self.model.predict(inputs)

        # Custom postprocessing
        response = predict_pb2.PredictResponse()
        response.outputs['output_tensor'].CopyFrom(tf.make_tensor_proto(predictions))
        return response

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