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chore: import upstream snapshot with attribution
2026-07-13 13:24:47 +08:00

56 lines
1.5 KiB
Python

import logging
from typing import Any, Dict, List, Text, Optional
from rasa.shared.core.slots import Slot
logger = logging.getLogger(__name__)
class LimitSlot(Slot):
"""
A slot for featurizing an amount as greater than or equal to vs. less than a given value.
Example of configuration in the domain.yml file:
slots:
my_slot:
type: custom.slots.LimitSlot
limit: 100
"""
type_name = "limit"
def __init__(
self,
name: Text,
limit: int,
mappings: List[Dict[Text, Any]],
initial_value: Any = None,
value_reset_delay: Optional[int] = None,
influence_conversation: bool = True,
) -> None:
super().__init__(
name=name,
initial_value=initial_value,
mappings=mappings,
value_reset_delay=value_reset_delay,
influence_conversation=influence_conversation,
)
self.limit = limit
def _as_feature(self) -> List[float]:
try:
greater_than_limit = float(self.value >= self.limit)
return [1.0, greater_than_limit]
except (TypeError, ValueError):
return [0.0, 0.0]
def persistence_info(self) -> Dict[Text, Any]:
"""Returns relevant information to persist this slot."""
d = super().persistence_info()
d["limit"] = self.limit
return d
def _feature_dimensionality(self) -> int:
return len(self.as_feature())