update code

.ipynb_checkpoints/app-checkpoint.py

@@ -12,9 +12,11 @@ if st.button('Click for predictions!'):
         
         result = get_single_prediction(feedback)
     
-    st.success(f'Your text has been predicted to fall under the following labels: {result[:-1]}. This text is {result[-1]}.')
+    st.success(f'Your text has been predicted to fall under the following topics: {result[:-1]}. The sentiment of this text is {result[-1]}.')
 
-st.text('Or... Upload a csv file if you have many texts')
+st.text("")
+st.subheader('Or... Upload a csv file if you have many texts')
+st.text("")
 
 uploaded_file = st.file_uploader("Please upload a csv file with only 1 column of texts.")
 

.ipynb_checkpoints/utils-checkpoint.py

@@ -94,6 +94,6 @@ def get_multiple_predictions(csv):
     
     # Append invalid rows
     if len(invalid) == 0:
-        return final_results
+        return final_results.to_csv().encode('utf-8')
     else:
-        return pd.concat([final_results, invalid]).reset_index(drop=True)
+        return pd.concat([final_results, invalid]).reset_index(drop=True).to_csv().encode('utf-8')

app.py

@@ -12,9 +12,11 @@ if st.button('Click for predictions!'):
         
         result = get_single_prediction(feedback)
     
-    st.success(f'Your text has been predicted to fall under the following labels: {result[:-1]}. This text is {result[-1]}.')
+    st.success(f'Your text has been predicted to fall under the following topics: {result[:-1]}. The sentiment of this text is {result[-1]}.')
 
-st.text('Or... Upload a csv file if you have many texts')
+st.text("")
+st.subheader('Or... Upload a csv file if you have many texts')
+st.text("")
 
 uploaded_file = st.file_uploader("Please upload a csv file with only 1 column of texts.")
 

utils.py

@@ -94,6 +94,6 @@ def get_multiple_predictions(csv):
     
     # Append invalid rows
     if len(invalid) == 0:
-        return final_results
+        return final_results.to_csv().encode('utf-8')
     else:
-        return pd.concat([final_results, invalid]).reset_index(drop=True)
+        return pd.concat([final_results, invalid]).reset_index(drop=True).to_csv().encode('utf-8')