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