Source code for mycroft.skills.common_query_skill

# Copyright 2018 Mycroft AI Inc.
#
# 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 enum import IntEnum
from abc import ABC, abstractmethod
from mycroft import MycroftSkill
from mycroft.messagebus.message import Message


class CQSMatchLevel(IntEnum):
    EXACT = 1  # Skill could find a specific answer for the question
    CATEGORY = 2  # Skill could find an answer from a category in the query
    GENERAL = 3  # The query could be processed as a general quer


# Copy of CQSMatchLevel to use if the skill returns visual media
CQSVisualMatchLevel = IntEnum('CQSVisualMatchLevel',
                              [e.name for e in CQSMatchLevel])


def is_CQSVisualMatchLevel(match_level):
    return isinstance(match_level, type(CQSVisualMatchLevel.EXACT))


VISUAL_DEVICES = ['mycroft_mark_2']


def handles_visuals(self, platform):
    return platform in VISUAL_DEVICES


[docs]class CommonQuerySkill(MycroftSkill, ABC): """ Question answering skills should be based on this class. The skill author needs to implement `CQS_match_query_phrase` returning an answer and can optionally implement `CQS_action` to perform additional actions if the skill's answer is selected. This class works in conjunction with skill-query which collects answers from several skills presenting the best one available. """ def __init__(self, name=None, bus=None): super().__init__(name, bus)
[docs] def bind(self, bus): """ Overrides the default bind method of MycroftSkill. This registers messagebus handlers for the skill during startup but is nothing the skill author needs to consider. """ if bus: super().bind(bus) self.add_event('question:query', self.__handle_question_query) self.add_event('question:action', self.__handle_query_action)
def __handle_question_query(self, message): search_phrase = message.data["phrase"] # First, notify the requestor that we are attempting to handle # (this extends a timeout while this skill looks for a match) self.bus.emit(message.response({"phrase": search_phrase, "skill_id": self.skill_id, "searching": True})) # Now invoke the CQS handler to let the skill perform its search result = self.CQS_match_query_phrase(search_phrase) if result: match = result[0] level = result[1] answer = result[2] callback = result[3] if len(result) > 3 else None confidence = self.__calc_confidence(match, search_phrase, level) self.bus.emit(message.response({"phrase": search_phrase, "skill_id": self.skill_id, "answer": answer, "callback_data": callback, "conf": confidence})) else: # Signal we are done (can't handle it) self.bus.emit(message.response({"phrase": search_phrase, "skill_id": self.skill_id, "searching": False})) def __calc_confidence(self, match, phrase, level): # Assume the more of the words that get consumed, the better the match consumed_pct = len(match.split()) / len(phrase.split()) if consumed_pct > 1.0: consumed_pct = 1.0 # Add bonus if match has visuals and the device supports them. platform = self.config_core.get('enclosure', {}).get('platform') if is_CQSVisualMatchLevel(level) and handles_visuals(platform): bonus = 0.1 else: bonus = 0 if int(level) == int(CQSMatchLevel.EXACT): return 0.9 + (consumed_pct / 10) + bonus elif int(level) == int(CQSMatchLevel.CATEGORY): return 0.6 + (consumed_pct / 10) + bonus elif int(level) == int(CQSMatchLevel.GENERAL): return 0.5 + (consumed_pct / 10) + bonus else: return 0.0 # should never happen def __handle_query_action(self, message): """ Message handler for question:action. Extracts phrase and data from message forward this to the skills CQS_action method. """ if message.data["skill_id"] != self.skill_id: # Not for this skill! return phrase = message.data["phrase"] data = message.data.get("callback_data") # Invoke derived class to provide playback data self.CQS_action(phrase, data)
[docs] @abstractmethod def CQS_match_query_phrase(self, phrase): """ Analyze phrase to see if it is a play-able phrase with this skill. Needs to be implemented by the skill. Args: phrase (str): User phrase uttered after "Play", e.g. "some music" Returns: (match, CQSMatchLevel[, callback_data]) or None: Tuple containing a string with the appropriate matching phrase, the PlayMatch type, and optionally data to return in the callback if the match is selected. """ # Derived classes must implement this, e.g. return None
[docs] def CQS_action(self, phrase, data): """ Take additional action IF the skill is selected. The speech is handled by the common query but if the chosen skill wants to display media, set a context or prepare for sending information info over e-mail this can be implemented here. Args: phrase (str): User phrase uttered after "Play", e.g. "some music" data (dict): Callback data specified in match_query_phrase() """ # Derived classes may implement this if they use additional media # or wish to set context after being called. pass