Update app.py

app.py

@@ -65,24 +65,6 @@ pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension
 
 embedder = SentenceTransformer(modules=[word_embedding_model, pooling_model])
 
-def search(query):
-    Entrez.email = '[email protected]'
-    handle = Entrez.esearch(db='pubmed', 
-                            sort='relevance', 
-                            retmax='5',
-                            retmode='xml', 
-                            term=query)
-    results = Entrez.read(handle)
-    return results
-
-def fetch_details(id_list):
-    ids = ','.join(id_list)
-    Entrez.email = '[email protected]'
-    
-    handle_1 = Entrez.efetch(db='pubmed', retmode='xml', id=ids)
-    results_1 = Entrez.read(handle_1)
-    return results_1
-
 
 def remove_stopwords(sen):
     sen_new = " ".join([i for i in sen if i not in stop_words])
@@ -94,6 +76,7 @@ def keyphrase_generator(article_link, model_1, model_2, max_num_keywords):
   element=[]
   final_textrank_list=[]
   document=[]
+  cluster_list_final=[]
   text_doc=[]
   final_list=[]
   score_list=[]