Update extractive_summarization.py

extractive_summarization.py

@@ -1,14 +1,3 @@
-"""from sumy.parsers.plaintext import PlaintextParser
-from sumy.nlp.tokenizers import Tokenizer
-from sumy.summarizers.lsa import LsaSummarizer
-from sumy.summarizers.lex_rank import LexRankSummarizer
-from sumy.summarizers.text_rank import TextRankSummarizer
-from pysummarization.nlpbase.auto_abstractor import AutoAbstractor
-from pysummarization.tokenizabledoc.simple_tokenizer import SimpleTokenizer
-from pysummarization.abstractabledoc.top_n_rank_abstractor import TopNRankAbstractor
-from sumy.nlp.stemmers import Stemmer
-from sumy.utils import get_stop_words"""
-
 from sumy.parsers.plaintext import PlaintextParser
 from sumy.nlp.tokenizers import Tokenizer
 from sumy.summarizers.text_rank import TextRankSummarizer
@@ -17,7 +6,7 @@ from sumy.summarizers.lex_rank import LexRankSummarizer
 import nltk
 nltk.download('punkt')
 
-def summarize_with_textrank(text, sentences_count=5):
+def summarize_with_textrank(text, sentences_count=10):
     """
     Summarizes the provided text using TextRank algorithm.
 
@@ -47,7 +36,7 @@ def summarize_with_textrank(text, sentences_count=5):
 
 
 # Define LSA summarization function
-def summarize_with_lsa(text, sentences_count=15):
+def summarize_with_lsa(text, sentences_count=10):
     """
     Summarizes the provided text using LSA (Latent Semantic Analysis) algorithm.
     Args: