Update app.py

app.py

@@ -10,12 +10,11 @@ from nltk.tokenize import word_tokenize
 import os
 import pdfkit
 import yake
-from transformers import AutoTokenizer, AutoModelForPreTraining, AutoModel, AutoConfig
 from summarizer import Summarizer,TransformerSummarizer
 from transformers import pipelines
-nltk.download('punkt')
-
+#nltk.download('punkt')
 
+from transformers import AutoTokenizer, AutoModelForPreTraining
 model_name = 'nlpaueb/legal-bert-base-uncased'
 
 
@@ -25,13 +24,12 @@ model = AutoModelForPreTraining.from_pretrained(model_name)
 bert_legal_model = Summarizer(custom_model=model, custom_tokenizer=tokenizer)
  
 
-def get_response(input_text):
 
-  output_text= bert_legal_model(input_text,  min_length = 8, ratio = 0.05)
-  return output_text
-  
-  
- 
+def get_response(input_text):
+    output_text= bert_legal_model(input_text,  min_length = 8, ratio = 0.05)
+    return output_text
+    
+    
 iface = gr.Interface(
     get_response, 
     "text",