Update app.py

app.py

@@ -59,7 +59,7 @@ SESSION.mount('https://', ADAPTER)
 UNIPROT_ENDPOINT = 'https://rest.uniprot.org/uniprotkb/{query}'
 
 CSS = """
-.help-tip {
+.help-tip > div {
   position: absolute;
   display: block;
   top: 0px;
@@ -386,7 +386,7 @@ def submit_predict(predict_filepath, task, preset, target_family, flag, progress
                 predictions = [pd.DataFrame(prediction) for prediction in predictions]
                 prediction_df = pd.concat([prediction_df, pd.concat(predictions, ignore_index=True)])
 
-                predictions_file = f'temp/{job_id}_predictions.csv'
+                predictions_file = f'{job_id}_predictions.csv'
                 prediction_df.to_csv(predictions_file, index=False)
 
                 return [predictions_file,
@@ -1135,7 +1135,7 @@ QALAHAYFAQYHDPDDEPVADPYDQSFESRDLLIDEWKSLTYDEVISFVPPPLDQEEMES
                 screen_df['X2'] = fasta
 
                 job_id = uuid4()
-                temp_file = Path(f'temp/{job_id}_input.csv').resolve()
+                temp_file = Path(f'{job_id}_input.csv').resolve()
                 screen_df.to_csv(temp_file, index=False)
                 if temp_file.is_file():
                     return {screen_data_for_predict: str(temp_file),
@@ -1172,7 +1172,7 @@ QALAHAYFAQYHDPDDEPVADPYDQSFESRDLLIDEWKSLTYDEVISFVPPPLDQEEMES
                 identify_df['X1'] = smiles
 
                 job_id = uuid4()
-                temp_file = Path(f'temp/{job_id}_input.csv').resolve()
+                temp_file = Path(f'{job_id}_input.csv').resolve()
                 identify_df.to_csv(temp_file, index=False)
                 if temp_file.is_file():
                     return {identify_data_for_predict: str(temp_file),