Update app.py

app.py

@@ -252,13 +252,13 @@ def get_data_from_smile(smile, eluent_list):
     return X_test
 
 def get_data_from_xlsx(file_name):
-    file = pd.read_excel(file_name)
-    smiles = file['SMILES'].values
-    PEs = file['PE'].values
-    EAs = file['EA'].values
-    DCMs = file['DCM'].values
-    MeOHs = file['MeOH'].values
-    Et2Os = file['Et2O'].values
+    file_open = pd.read_csv(file_name)
+    smiles = file_open['SMILES'].values
+    PEs = file_open['PE'].values
+    EAs = file_open['EA'].values
+    DCMs = file_open['DCM'].values
+    MeOHs = file_open['MeOH'].values
+    Et2Os = file_open['Et2O'].values
     X_test = np.zeros([len(smiles), 179])
     for i in range(len(smiles)):
         smile=smiles[i]
@@ -307,7 +307,10 @@ def predict_xlsx(file):
     X_test = get_data_from_xlsx(file_name)
     Model = Model_ML(config, X_test)
     Rf = Model.get_Rf()
-    return Rf
+    file_open = pd.read_csv(file_name)
+    file_open['Rf']=Rf
+    file_open.to_csv(file_name)
+    return file_name
 
 if __name__=='__main__':
 
@@ -342,8 +345,8 @@ if __name__=='__main__':
         gr.Markdown(model_card)
         with gr.Tab("Single prediction"):
             gr.Interface(fn=predict_single, inputs=["text", "number","number","number","number","number"], outputs='number')
-        with gr.Tab("xlsx prediction"):
-            gr.Interface(fn=predict_xlsx, inputs=["file"], outputs="dataframe")
+        with gr.Tab("csv prediction"):
+            gr.Interface(fn=predict_xlsx, inputs="file", outputs="file")
        
     demo.launch()
     # smile='O=C(OC1C(OC(C)=O)C(OC(C)=O)C(OC(C)=O)C(COC(C)=O)O1)C'