Refactoring: Minor changes.

Author: ggeop

src/jarvis/jarvis/core/nlp.py

@@ -113,7 +113,7 @@ def _create_response(self, sentence):
  noun = self._extract_noun(parts_of_speech)
 
  # ----------------------------
- # Question type classification
+ # Command type classification
  # ----------------------------
  if self.is_question_with_modal(parts_of_speech):
  logging.info('The user speech has a modal question')
@@ -122,7 +122,7 @@ def _create_response(self, sentence):
  logging.info('The user speech has an inverse question')
  answer = 'I ' + ' ' + verb + ' ' + noun
  else:
- logging.debug('Unclassified question type')
+ logging.info('Unclassified user command..')
  answer = ''
 
  return re.sub('\s\s+', ' ', answer)

src/jarvis/jarvis/core/processor.py

@@ -39,11 +39,11 @@ def __init__(self, console_manager, settings_):
  self.settings = settings_
  self.response_creator = ResponseCreator()
  self.skill_analyzer = SkillAnalyzer(
-  weight_measure=TfidfVectorizer,
-  similarity_measure=cosine_similarity,
-  args=self.settings.SKILL_ANALYZER.get('args'),
-  sensitivity=self.settings.SKILL_ANALYZER.get('sensitivity'),
-  )
+ weight_measure=TfidfVectorizer,
+ similarity_measure=cosine_similarity,
+ args=self.settings.SKILL_ANALYZER.get('args'),
+ sensitivity=self.settings.SKILL_ANALYZER.get('sensitivity'),
+ )
 
  def run(self):
  """
@@ -61,26 +61,50 @@ def run(self):
  skill = self.skill_analyzer.extract(transcript)
 
  if skill:
- skill_to_execute = {'voice_transcript': transcript, 'skill': skill}
-
- response = self.response_creator.create_positive_response(transcript) if skill_to_execute \
- else self.response_creator.create_negative_response(transcript)
+ # ----------------------------------------------------------------------------------------------------------
+ # Successfully extracted skill
+ # ----------------------------------------------------------------------------------------------------------
+
+ # ---------------
+ # Positive answer
+ # ---------------
+ response = self.response_creator.create_positive_response(transcript)
  jarvis.output_engine.assistant_response(response)
 
+ # ---------------
+ # Skill execution
+ # ---------------
+ skill_to_execute = {'voice_transcript': transcript, 'skill': skill}
  self._execute_skill(skill_to_execute)
 
  else:
- # If no skill to execute, it calls the WolframAlpha API
+ # ----------------------------------------------------------------------------------------------------------
+ # No skill extracted
+ # ----------------------------------------------------------------------------------------------------------
+
+ # ---------------
+ # Negative answer
+ # ---------------
+ response = self.response_creator.create_negative_response(transcript)
+ jarvis.output_engine.assistant_response(response)
+
+ # ---------------
+ # WolframAlpha API Call
+ # ---------------
  skill_to_execute = {'voice_transcript': transcript,
  'skill': {'name': WolframSkills.call_wolframalpha.__name__}
  }
 
  response = WolframSkills.call_wolframalpha(transcript)
 
+ # --------------------------------------------------------------------------------------------------------------
+ # Add new record to history
+ # --------------------------------------------------------------------------------------------------------------
+
  record = {'user_transcript': transcript,
  'response': response if response else '--',
  'executed_skill': skill_to_execute if skill_to_execute else '--'
- }
+  }
 
  db.insert_many_documents('history', [record])
 
@@ -94,5 +118,5 @@ def _execute_skill(self, skill):
  skill_func = skill_objects[skill_func_name]
  skill_func(**skill)
  except Exception as e:
- self.console_manager.console_output(error_log="Failed to execute skill {0} with message {1}"
+ self.console_manager.console_output(error_log="Failed to execute skill {0} with message: {1}"
  .format(skill_func_name, e))