Update app.py

app.py

@@ -188,14 +188,14 @@ def retrieval():
     st.markdown('### Target')
 
     st.write(f'The top-{selected_k} most active drug coupounds from {selected_dataset} predicted by HyperPCM are: ')
-        dummy_smiles = ['CC(=O)OC1=CC=CC=C1C(=O)O', 'COc1cc(C=O)ccc1O', 'CC(=O)Nc1ccc(O)cc1', 'CC(=O)Nc1ccc(OS(=O)(=O)O)cc1', 'CC(=O)Nc1ccc(O[C@@H]2O[C@H](C(=O)O)[C@@H](O)[C@H](O)[C@H]2O)cc1']
-        cols = st.columns(5)
-        for j, col in enumerate(cols):
-            with col:
-                for i in range(int(selected_k/5)):
-                    mol = Chem.MolFromSmiles(dummy_smiles[j])
-                    mol_img = Chem.Draw.MolToImage(mol)
-                    st.image(mol_img) 
+    dummy_smiles = ['CC(=O)OC1=CC=CC=C1C(=O)O', 'COc1cc(C=O)ccc1O', 'CC(=O)Nc1ccc(O)cc1', 'CC(=O)Nc1ccc(OS(=O)(=O)O)cc1', 'CC(=O)Nc1ccc(O[C@@H]2O[C@H](C(=O)O)[C@@H](O)[C@H](O)[C@H]2O)cc1']
+    cols = st.columns(5)
+    for j, col in enumerate(cols):
+        with col:
+            for i in range(int(selected_k/5)):
+                mol = Chem.MolFromSmiles(dummy_smiles[j])
+                mol_img = Chem.Draw.MolToImage(mol)
+                st.image(mol_img) 
 
     '''
     col1, col2, col3, col4 = st.columns(4)