def generate_summary(documents, sentences, tf_vectorizer, key_words, topic):
'''
Aggregate all functions created to generate summaries to generate summary.
'''
summary_object = Summarizer(documents, sentences, tf_vectorizer, key_words,
topic)
summary_object.get_sentence_scores()
summary_object.summarize()
summary, summary_array = summary_object.format_summary()
return summary, summary_array
def generate_summary(formatted_sentences, sentences_tok, tf_vectorizer,
key_words, topic, length):
'''
INPUT: Sentenced tokenized book by section, tokenized sentences, term-frequency vector object, key words, topic number, length of summary
OUTPUT: Summary
'''
summary_object = Summarizer(formatted_sentences, sentences_tok,
tf_vectorizer, key_words, topic, length)
summary_object.get_sentence_scores()
summary = summary_object.summarize()
summary = summary_object.format_summary()
return summary
