Update app.py

app.py

@@ -35,7 +35,7 @@ def predict_stability_with_pdb(model_choice, organism_choice, pdb_files, cfg=Con
                "binary prediction value": []
                }
     file_names = []
-    sequences = []
+    input_sequences = []
 
     for pdb_file in pdb_files:
         pdb_path = pdb_file.name
@@ -49,9 +49,9 @@ def predict_stability_with_pdb(model_choice, organism_choice, pdb_files, cfg=Con
 
         sequence = sequences[2] if model_choice == "SaProt" else sequences[0]
         file_names.append(pdb_file.name.split("/")[-1])
-        sequences.append(sequence)
+        input_sequences.append(sequence)
 
-    raw_prediction, binary_prediction = predict_stability_core(model_choice, organism_choice, sequences, cfg)
+    raw_prediction, binary_prediction = predict_stability_core(model_choice, organism_choice, input_sequences, cfg)
     results["file_name"] = results["file_name"] + file_names
     results["raw prediction value"] = results["raw prediction value"] + raw_prediction
     results["binary prediction value"] = results["binary prediction value"] + binary_prediction
@@ -66,7 +66,7 @@ def predict_stability_with_sequence(model_choice, organism_choice, sequence, cfg
     try:
         if not sequence:
             return "No valid sequence provided."
-        raw_prediction, binary_prediction = predict_stability_core(model_choice, organism_choice, sequence, cfg)
+        raw_prediction, binary_prediction = predict_stability_core(model_choice, organism_choice, [sequence], cfg)
         df = pd.DataFrame({"sequence": sequence, "raw prediction value": raw_prediction, "binary prediction value": binary_prediction})
         output_csv = "/tmp/predictions.csv"
         df.to_csv(output_csv, index=False)