def report(model_file, text_file):
pl = Pipeline()
model = KNN.load(model_file)
nlp = en_core_web_sm.load()
make_doc = lambda text: nlp(unidecode(text).strip())
text = [line for line in open(text_file) if line.strip()]
docs = [make_doc(line) for line in text]
sentences = [sent.text for doc in docs for sent in doc.sents]
print('\n'.join(text))
predictions = pl.predict(model, sentences, print_pred=False)
print('\n \n ############### Soft Skills ############\n')
print(
*[sent for sent, pred in zip(sentences, predictions) if 'yes' == pred],
sep='\n')
