Update app.py

app.py

@@ -72,38 +72,40 @@ if sidebar_selectbox == "Bulk upload and mark":
        data_file = st.file_uploader("Upload CSV",type=["csv"])
        
        if data_file is not None:
-              file_details = {"filename":data_file.name, "filetype":data_file.type, "filesize":data_file.size}
-              # st.write(file_details)
-              df = pd.read_csv(data_file)
-              
-              # Get length of df.shape (might not need this)
-              #total_rows = df.shape[0]
-              
-              similarity_scores = []
-              
-              for idx, row in df.iterrows():
-                     # st.write(idx, row['Sentences'])
+              with st.spinner('Wait for it...'):
+                     file_details = {"filename":data_file.name, "filetype":data_file.type, "filesize":data_file.size}
+                     # st.write(file_details)
+                     df = pd.read_csv(data_file)
                      
-                     # Create an empty sentence list
-                     sentences = []
+                     # Get length of df.shape (might not need this)
+                     #total_rows = df.shape[0]
                      
-                     # Compare the setences two by two
-                     sentence_comparison = row['Sentences']
-                     sentences.append(sentence_reference)
-                     sentences.append(sentence_comparison)
+                     similarity_scores = []
                      
-                     sentence_embeddings = model.encode(sentences)
+                     for idx, row in df.iterrows():
+                            # st.write(idx, row['Sentences'])
+                            
+                            # Create an empty sentence list
+                            sentences = []
+                            
+                            # Compare the setences two by two
+                            sentence_comparison = row['Sentences']
+                            sentences.append(sentence_reference)
+                            sentences.append(sentence_comparison)
+                            
+                            sentence_embeddings = model.encode(sentences)
+                            
+                            cos_sim = cosine_similarity(sentence_embeddings[0].reshape(1, -1), sentence_embeddings[1].reshape(1, -1))[0][0]
+                            cos_sim = round(cos_sim * 100)
+                            
+                            similarity_scores.append(cos_sim)                    
                      
-                     cos_sim = cosine_similarity(sentence_embeddings[0].reshape(1, -1), sentence_embeddings[1].reshape(1, -1))[0][0]
-                     cos_sim = round(cos_sim * 100)
+                     # Append new column to dataframe
                      
-                     similarity_scores.append(cos_sim)                    
-              
-              # Append new column to dataframe
-              
-              df['Similarity (%)'] = similarity_scores
-              
-              st.dataframe(df)
+                     df['Similarity (%)'] = similarity_scores
+                     
+                     st.dataframe(df)
+              st.success('Done!')  
               
               @st.cache
               def convert_df(df):