import logging
from rasa_core.slots import Slot

logger = logging.getLogger(__name__)

# This slot was designed to hold an "object" (called a struct here). Really this slot could hold anything, because there's
# not really any validation on the type of `self.value`. What relly matters is the answer to the question
# "How would an object/dict translate into a feature used for machine learning?".
# In this example, it's a simple feature based on whether or not there's *anything* stored in the slot. A more complex slot
# may take into account the contents of the object/dict and provide a different result in `as_feature()` (and
# `feature_dimensionality()` as well).
class StructSlot(Slot):
    def __init__(self, name,
                 initial_value=None,
                 value_reset_delay=None):
        super(StructSlot, self).__init__(name, initial_value, value_reset_delay)

    def as_feature(self):
        if self.value is not None:
            return [1.0]
        else:
            return [0.0]