Update app.py

app.py

@@ -20,24 +20,6 @@ import wget
 import warnings
 import gradio as gr
 warnings.filterwarnings("ignore")
-theme = gr.themes.Monochrome(
-    primary_hue="indigo",
-    secondary_hue="blue",
-    neutral_hue="slate",
-)
-model_card = f"""
-## Description\n
-It is a app for predicting Rf values of a compound under given eluents in TLC.\n
-input: smiles of one compounds, such as CC(OCC)=O; \n
-       the ratio of five solvents (example: 20 1 0 0 0 for PE:EA=20:1)\n
-output: the predicted Rf value.\n
-
-## Citation\n
-Welcome to cite our work:\n
-H. Xu, J. Lin, Q. Liu, Y. Chen, J. Zhang, Y. Yang, M.C. Young, Y. Xu, D. Zhang, F. Mo
-High-throughput discovery of chemical structure-polarity relationships combining automation and machine-learning techniques
-Chem (2022), pp. 1-13, 10.1016/j.chempr.2022.08.008
-"""
 
 Eluent_smiles=['CCCCCC','CC(OCC)=O','C(Cl)Cl','CO','CCOCC']
 def parse_args():
@@ -282,6 +264,25 @@ def predict_single(smile,PE,EA,DCM,MeOH,Et20):
     return Rf[0]
 
 if __name__=='__main__':
+        theme = gr.themes.Monochrome(
+        primary_hue="indigo",
+        secondary_hue="blue",
+        neutral_hue="slate",
+    )
+    model_card = f"""
+    ## Description\n
+    It is a app for predicting Rf values of a compound under given eluents in TLC.\n
+    input: smiles of one compounds, such as CC(OCC)=O; \n
+           the ratio of five solvents (example: 20 1 0 0 0 for PE:EA=20:1)\n
+    output: the predicted Rf value.\n
+    
+    ## Citation\n
+    Welcome to cite our work:\n
+    H. Xu, J. Lin, Q. Liu, Y. Chen, J. Zhang, Y. Yang, M.C. Young, Y. Xu, D. Zhang, F. Mo
+    High-throughput discovery of chemical structure-polarity relationships combining automation and machine-learning techniques
+    Chem (2022), pp. 1-13, 10.1016/j.chempr.2022.08.008
+    """
+
     with gr.Blocks(theme=theme) as demo:
         gr.Markdown('''
                 <div>