Update app.py

app.py

@@ -4,7 +4,6 @@ import nltkmodule
 from newspaper import Article
 from newspaper import fulltext
 import requests
-
 from nltk.tokenize import word_tokenize
 from sentence_transformers import SentenceTransformer
 import pandas as pd
@@ -31,7 +30,9 @@ import en_core_sci_lg
 import string
 from nltk.stem.wordnet import WordNetLemmatizer
 import gradio as gr
+import inflect
 
+inflect_op = inflect.engine()
 nlp = en_core_sci_lg.load()
 sp = en_core_sci_lg.load()
 all_stopwords = sp.Defaults.stop_words
@@ -102,6 +103,7 @@ def keyphrase_generator(article_link, model_1, model_2, max_num_keywords):
     text_doc.append([X.text for X in doc_1.ents])
   entity_list = [item for sublist in text_doc for item in sublist]
   entity_list = [word for word in entity_list if not word in all_stopwords]
+  entity_list = [word_entity for word_entity in entity_list if(inflect_op.singular_noun(word_entity) == False)]
   entity_list=list(dict.fromkeys(entity_list))
   doc_embedding = model_2.encode([doc])
   candidates=entity_list