text: # Google Compute Engine implementation of the elevent NLP API
  
  from google.cloud.language import enums
  from google.cloud.language import types
  
  def entities(text, salience, client):
  		'''Detects entities in the text with a minimum salience'''
  
  		document = types.Document(content=text, type=enums.Document.Type.PLAIN_TEXT)
  		entities = client.analyze_entities(document).entities
  
  		keywords = set()
  		for entity in entities:
  			if entity.salience > salience:
  				keywords.add(entity.name.lower().replace('.',''))
  
  		return keywords
  
  
  def classifications(text, confidence, client):
  		'''Classifies the text with a minimum confidence'''
  
  		document = types.Document(content=text.encode('utf-8'), type=enums.Document.Type.PLAIN_TEXT)
  		categories = client.classify_text(document).categories
  
  		unique_words = set()
  		for category in categories:
  			if category.confidence > confidence:
  				keywords = category.name.lower().replace('/', ' ').replace('&', '').split()
  				for word in keywords:
  					unique_words.add(word)
  
  		return unique_words
  