Update app.py

app.py

@@ -8,7 +8,7 @@ from nltk.tokenize import sent_tokenize
 
 st.caption(" © Aviv Lazar & Moran Shemesh")
 
-def textrank(corpus, ratio=0.2):    
+def textrank(corpus, ratio):    
   if type(corpus) is str:        
       corpus = [corpus]    
   summaries = [gensim.summarization.summarize(txt, ratio=ratio) for txt in corpus][0]
@@ -16,11 +16,11 @@ def textrank(corpus, ratio=0.2):
   return summaries
 #end textrank
 
-def start_summarize(long_text, model):
+def start_summarize(long_text, model, size):
   num_of_sentences = len(sent_tokenize(long_text))
   if num_of_sentences > 4:
     if model=="RankText":
-      summary = textrank(long_text)
+      summary = textrank(long_text, size/100)
       # if summary=="":
       # summary = long_text
     elif model=="Bart":
@@ -49,7 +49,7 @@ if start:
   start = False
   st.markdown("Summary")
   with st.spinner("We are summarizing your text..."):
-    start_summarize(user_text, model_type)
+    start_summarize(user_text, model_type, textrank_summary_size)