def clean_up_sentence(sentence):
    # tokenizando frases
    sentence_words = nltk.word_tokenize(sentence)
    # stem
    sentence_words = [stemmer.stem(word.lower()) for word in sentence_words]
    return sentence_words

def bow(sentence, words, show_details=False):
    sentence_words = clean_up_sentence(sentence)
    bag = [0]*len(words)
    for s in sentence_words:
        for i,w in enumerate(words):
            if w == s:
                bag[i] = 1
                if show_details:
                    print ("found in bag: %s" % w)

    return(np.array(bag))

# In[31]:

p = bow("O que vocês vendem ?", words)
print (p)
print (classes)

# In[6]:

# load our saved model
model.load('./model.tflearn')