# 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
# 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 deeppavlov.core.agent.processor import Processor
from deeppavlov.core.agent.rich_content import RichMessage
from deeppavlov.agents.rich_content.default_rich_content import PlainText
"""Returns RichControl wrapped responses with highest confidence."""
def __init__(self, *args, **kwargs) -> None:
def __call__(self, utterances: list, batch_history: list, *responses: list) -> list:
"""Selects for each utterance response with highest confidence and wraps them to RichControl objects.
utterances_batch: Not used.
history_batch: Not used.
responses: Each response positional argument corresponds to
response of one of Agent skills and is represented by
batch (list) of (response, confidence) tuple structures.
result: A batch of responses corresponding to the utterance
batch received by agent.
responses, confidences = zip(*[zip(*r) for r in responses])
indexes = [c.index(max(c)) for c in zip(*confidences)]
result = 
for i, *responses in zip(indexes, *responses):
rich_message = RichMessage()
plain_text = PlainText(str(responses[i]))