# Copyright 2017 Neural Networks and Deep Learning lab, MIPT
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from abc import ABCMeta, abstractmethod
from typing import Tuple, Optional, Union
from deeppavlov.core.models.component import Component
[docs]class Skill(Component, metaclass=ABCMeta):
"""Abstract class for skills.
Skill is a DeepPavlov component, which provides handling dialog state,
dialog history and rich content.
"""
@abstractmethod
def __call__(self, utterances_batch: list, history_batch: list,
states_batch: Optional[list]=None) -> Union[Tuple[list, list], Tuple[list, list, Optional[list]]]:
"""Returns skill inference result.
Returns batches of skill inference results, estimated confidence
levels and up to date states corresponding to incoming utterance
batch.
Args:
utterances_batch: A batch of utterances of any type.
history_batch: A batch of list typed histories for each utterance.
states_batch: Optional. A batch of arbitrary typed states for
each utterance.
Returns:
response: A batch of arbitrary typed skill inference results.
confidence: A batch of float typed confidence levels for each of
skill inference result.
states: Optional. A batch of arbitrary typed states for each
response.
"""