fixed cas9off

app.py

@@ -131,10 +131,11 @@ if selected_model == 'Cas9':
                 )
 
             # prediction button
-            if st.button('Predict off-target effects'):
+            if st.button('Predict off-target'):
                 if st.session_state.entry_method == ENTRY_METHODS['manual']:
                     user_input = st.session_state.manual_entry
-                    predictions = cas9off.process_input_and_predict(user_input, input_type='manual')
+                    if user_input:  # Check if user_input is not empty
+                        predictions = cas9off.process_input_and_predict(user_input, input_type='manual')
                 elif st.session_state.entry_method == ENTRY_METHODS['txt']:
                     uploaded_file = st.session_state.txt_entry
                     if uploaded_file is not None:
@@ -144,9 +145,7 @@ if selected_model == 'Cas9':
 
                 st.session_state.off_target_results = predictions
             else:
-                # Ensure that 'predictions' is defined even if the button hasn't been clicked
                 predictions = None
-
             progress = st.empty()
 
             # input error display

cas9off.py

@@ -108,17 +108,6 @@ def CRISPR_net_predict(X_test):
     return y_pred
 
 def process_input_and_predict(input_data, input_type='manual'):
-    """
-    Process the user input and predict.
-
-    Args:
-    input_data: A string of manual input or the path to an input file.
-    input_type: 'manual' for manual input, 'file' for file input.
-
-    Returns:
-    A DataFrame with the off-target predictions.
-    """
-
     if input_type == 'manual':
         # Process manual input string into DataFrame
         sequences = [seq.split(',') for seq in input_data.split('\n')]
@@ -132,6 +121,12 @@ def process_input_and_predict(input_data, input_type='manual'):
     for idx, row in inputs.iterrows():
         on_seq = row['on_seq']
         off_seq = row['off_seq']
+
+        # Validate on_seq and off_seq
+        if not on_seq or not off_seq:
+            # Skip the current row if either on_seq or off_seq is missing or empty
+            continue
+
         en = Encoder(on_seq=on_seq, off_seq=off_seq)
         input_codes.append(en.on_off_code)