Update inference_app.py

inference_app.py

@@ -60,15 +60,16 @@ def set_protein_to_new_coord(input_pdb_file, new_coord, output_file):
     file.write(output_file)
 
 
-def predict (input_sequence, input_ligand, input_msa, input_protein):
+def predict(input_sequence, input_ligand, input_msa, input_protein):
     start_time = time.time()
     
     # Do inference here
     mol = generate_input_conformer(input_ligand, minimize_maxIters=100)
-    with Chem.SDWriter("test_docking_pose.sdf") as writer:
-        writer.write(mol)
-    mol_coords = mol.GetConformer().GetPositions()
     
+    molwriter = Chem.SDWriter("test_docking_pose.sdf")
+    molwriter.write(mol)
+
+    mol_coords = mol.GetConformer().GetPositions()    
     # new_coord = [0, 0, 0]
     new_coord = np.mean(mol_coords, axis=1)
     output_file = "test_out.pdb"
@@ -108,9 +109,9 @@ with gr.Blocks() as app:
     gr.Examples(
         [
             [
-                None,
+                "",
                 "COc1ccc(cc1)n2c3c(c(n2)C(=O)N)CCN(C3=O)c4ccc(cc4)N5CCCCC5=O",
-                None,
+                "",
                 "test_out.pdb"
             ],
         ],
@@ -134,6 +135,6 @@ with gr.Blocks() as app:
     metrics = gr.JSON(label="Metrics")
     run_time = gr.Textbox(label="Runtime")
 
-    btn.click(predict, inputs=[input_sequence, input_ligand, input_msa, input_protein], outputs=[out,metrics, run_time])
+    btn.click(predict, inputs=[input_sequence, input_ligand, input_msa, input_protein], outputs=[out, metrics, run_time])
 
 app.launch()