Update app.py

app.py

@@ -12,9 +12,6 @@ from spacy.matcher import PhraseMatcher
 from spacy.tokens import Span
 #import en_ner_bc5cdr_md
 import re
-import torch
-from transformers import BartTokenizer, BartForConditionalGeneration
-from transformers import T5Tokenizer, T5ForConditionalGeneration
 
 
 from streamlit.components.v1 import html
@@ -212,16 +209,6 @@ if not(btnPastHistory) and not(btnDailyNarrative):
 
 ##===== BERT Summary tokenizer =====
 
-def BertSummarizer(input_text):
-    from transformers import BigBirdTokenizer
-    from summarizer import Summarizer
-
-    bertsummarizer = Summarizer()
-
-    model = Summarizer()
-    result = model(input_text,ratio=0.4)
-    
-    return result
 ##======================== Start of NER Tagging ========================
 # ====== Old NER ======
 # doc = nlp(str(original_text2))
@@ -317,12 +304,9 @@ ent_html = displacy.render(doc0, style='ent', options=options)
 
 def run_model(input_text):    
     if model == "BertSummarizer":
-#        output = original_text['BertSummarizer2s'].values
-#        st.write('Summary')
-        output = BertSummarizer(input_text)
+        output = original_text['BertSummarizer2s'].values
         st.write('Summary')
-        st.success(output)
-        
+               
 #    elif model == "BertGPT2":
 #        output = original_text['BertGPT2'].values
 #        st.write('Summary')