def METHOD_NAME(product_id: ProductIdentifier, product: JSONType) -> None:
    """Predict categories for product and import predicted category insight.
    :param product_id: identifier of the product
    :param product: product as retrieved from MongoDB
    """
    if not product_id.server_type.is_food():
        # Category prediction is only available for Food products
        logger.info(
            "`server_type=%s`, skipping category prediction", product_id.server_type
        )
        return
    # predict category using neural model
    try:
        neural_predictions, _ = CategoryClassifier(
            get_taxonomy(TaxonomyType.category.name)
        ).predict(product, product_id)
        product_predictions = neural_predictions
    except requests.exceptions.HTTPError as e:
        resp = e.response
        logger.error(
            f"Category classifier returned an error: {resp.status_code}: %s", resp.text
        )
        return
    if len(product_predictions) < 1:
        return
    for prediction in product_predictions:
        prediction.barcode = product_id.barcode
        prediction.server_type = product_id.server_type
    import_result = import_insights(product_predictions, product_id.server_type)
    logger.info(import_result)