# 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_skill import MycroftSkill
from mycroft.util.file_utils import resolve_resource_file
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))
"""these are for the confidence calculation"""
# how much each topic word is worth
# when found in the answer
TOPIC_MATCH_RELEVANCE = 5
# elevate relevance above all else
RELEVANCE_MULTIPLIER = 2
# we like longer articles but only so much
MAX_ANSWER_LEN_FOR_CONFIDENCE = 50
# higher number - less bias for word length
WORD_COUNT_DIVISOR = 100
[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)
noise_words_filepath = "text/%s/noise_words.list" % (self.lang,)
noise_words_filename = resolve_resource_file(noise_words_filepath)
self.translated_noise_words = []
try:
if noise_words_filename:
with open(noise_words_filename) as f:
read_noise_words = f.read().strip()
self.translated_noise_words = read_noise_words.split()
else:
raise FileNotFoundError
except FileNotFoundError:
self.log.warning("Missing noise_words.list file in "
f"res/text/{self.lang}")
# these should probably be configurable
self.level_confidence = {
CQSMatchLevel.EXACT: 0.9,
CQSMatchLevel.CATEGORY: 0.6,
CQSMatchLevel.GENERAL: 0.5
}
[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, answer)
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}))
[docs] def remove_noise(self, phrase):
"""remove noise to produce essence of question"""
phrase = ' ' + phrase + ' '
for word in self.translated_noise_words:
mtch = ' ' + word + ' '
if phrase.find(mtch) > -1:
phrase = phrase.replace(mtch, " ")
phrase = ' '.join(phrase.split())
return phrase.strip()
def __calc_confidence(self, match, phrase, level, answer):
# 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
consumed_pct /= 10
# bonus for more sentences
num_sentences = float(float(len(answer.split("."))) / float(10))
# Add bonus if match has visuals and the device supports them.
bonus = 0.0
if is_CQSVisualMatchLevel(level) and self.gui.connected:
bonus = 0.1
# extract topic
topic = self.remove_noise(match)
# calculate relevance
answer = answer.lower()
matches = 0
for word in topic.split(' '):
if answer.find(word) > -1:
matches += TOPIC_MATCH_RELEVANCE
answer_size = len(answer.split(" "))
answer_size = min(MAX_ANSWER_LEN_FOR_CONFIDENCE, answer_size)
relevance = 0.0
if answer_size > 0:
relevance = float(float(matches) / float(answer_size))
relevance = relevance * RELEVANCE_MULTIPLIER
# extra credit for more words up to a point
wc_mod = float(float(answer_size) / float(WORD_COUNT_DIVISOR)) * 2
confidence = self.level_confidence[level] + \
consumed_pct + bonus + num_sentences + relevance + wc_mod
return confidence
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, "What is an aardwark"
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