Update app.py

app.py

@@ -15,7 +15,6 @@ menu_items = {
 	'Report a bug': 'https://www.linkedin.com/in/ayomide-ishola-924014162/',
 	'About': '''
 	## My Custom App
-
 	Some markdown to show in the About dialog.
 	'''
 }
@@ -39,7 +38,7 @@ def main():
         st.sidebar.markdown("<h4 style = 'color:green; align:center; font-size: 20px;'> Model Settings</h1>", unsafe_allow_html=True)
         max_length= st.sidebar.slider("Maximum length of the generated text",min_value=100,max_value=500)
         min_length= st.sidebar.slider("Minimum length of the generated text",min_value=30)
-        model_type = st.sidebar.selectbox("Model type", options=["Bart","T5", "SSR",])
+        model_type = st.sidebar.selectbox("Model type", options=["Bart","T5", "Bart + T5"])
         
         # This function is used to upload a .txt, .pdf, .docx file for summarization
         upload_doc = st.file_uploader("Upload a .txt, .pdf, .docx file for summarisation")
@@ -75,17 +74,17 @@ def main():
                     text="Loading T5 Model and Extracting summary. This might take a few seconds depending on the length of your text..."):
                     summarizer_model = t5()
                     summarized_text = summarizer_model(text_to_summarize, max_length=max_length, min_length=min_length)
-                    summarized_text = ' '.join([summ['summary_text'] for summ in summarized_text])                      
-
-            elif model_type == "ssr":
+                    summarized_text = ' '.join([summ['summary_text'] for summ in summarized_text]) 
+                    
+            elif model_type == "Bart + T5":
                 text_to_summarize = clean_text
 
                 with st.spinner(
-                    text="Loading SSR Model and Extracting summary. This might take a few seconds depending on the length of your text..."):
-                    summarizer_model = ssr()
+                    text="Loading Bart + T5 Models and Extracting summary. This might take a few seconds depending on the length of your text..."):
+                    summarizer_model = bart_t5()
                     summarized_text = summarizer_model(text_to_summarize, max_length=max_length, min_length=min_length)
-                    summarized_text = ' '.join([summ['summary_text'] for summ in summarized_text])
-          
+                    summarized_text = ' '.join([summ['summary_text'] for summ in summarized_text])                     
+
             res_col1 ,res_col2 = st.columns(2)
             with res_col1:
                 st.subheader("Generated Text Visualisation")