update

app.py

@@ -32,6 +32,8 @@ def run_inference(
     # Read SMILES
     if smiles is None and smiles_path is None:
         raise TypeError("Pass either single SMILES or a file")
+    elif smiles is not None and smiles_path is not None:
+        raise TypeError("Pass either single SMILES or a file, not both")
     elif smiles is not None:
         smiles = [smiles]
     elif smiles_path is not None:
@@ -47,10 +49,8 @@ def run_inference(
     else:
         omic_path = None
 
-    # ToDo: Add progress bar for multiple smiles
-    results = []
+    result = pd.DataFrame({})
     for smi in tqdm(smiles, total=len(smiles)):
-        result = pd.DataFrame({})
         output = submission(
             drug={"smiles": smi},
             workspace_id="emulated_workspace_id",
@@ -71,8 +71,7 @@ def run_inference(
             result[f"epistemic_confidence_{smi}"] = (
                 output["aleatoric_confidence"].squeeze().round(3)
             )
-        results.append(result)
-    predicted_df = pd.concat(results)
+    predicted_df = result
 
     # Prepare DF to visualize
     if omic_path is None:
@@ -105,10 +104,6 @@ def run_inference(
     # Save to temporary dir
     temp_path = os.path.join(tempfile.gettempdir(), "paccmann_result.csv")
     result_df.to_csv(temp_path)
-    print("OUTPUT", result_df.columns)
-    print(result_df.head(2))
-    print()
-    print(result_df)
 
     return temp_path, result_df.head(25)