Update app.py

app.py

@@ -13,47 +13,43 @@ from sklearn.pipeline import Pipeline
 from sklearn.linear_model import LogisticRegression
 from sklearn.metrics import accuracy_score, confusion_matrix, classification_report, roc_auc_score
 import gradio as gr
-
-
 def load_csv(file_obj):
-    try:
-        # Case 1: File path string (Gradio sometimes gives this)
-        if isinstance(file_obj, str):
+    # Case: path string
+    if isinstance(file_obj, str):
+        try:
+            return pd.read_csv(file_obj), None
+        except Exception as e_csv:
             try:
-                return pd.read_csv(file_obj), None
-            except Exception as e_csv:
-                try:
-                    return pd.read_excel(file_obj), None
-                except Exception as e_xls:
-                    return None, f"Failed to read file from path. CSV error: {e_csv} / Excel error: {e_xls}"
-
-        # Case 2: File-like object
-        if hasattr(file_obj, "read"):
+                return pd.read_excel(file_obj), None
+            except Exception as e_xls:
+                return None, f"Failed to read file from path. CSV error: {e_csv} / Excel error: {e_xls}"
+
+    # Case: file-like object
+    if hasattr(file_obj, "read"):
+        file_obj.seek(0)
+        try:
+            return pd.read_csv(file_obj), None
+        except Exception as e_csv:
             file_obj.seek(0)
             try:
-                return pd.read_csv(file_obj), None
-            except Exception as e_csv:
-                file_obj.seek(0)
-                try:
-                    return pd.read_excel(file_obj), None
-                except Exception as e_xls:
-                    return None, f"Failed to read file object. CSV error: {e_csv} / Excel error: {e_xls}"
-
-        return None, "Unsupported file type."
+                return pd.read_excel(file_obj), None
+            except Exception as e_xls:
+                return None, f"Failed to read file object. CSV error: {e_csv} / Excel error: {e_xls}"
 
-    except Exception as e:
-        return None, f"Unexpected error: {e}"
+    return None, "Unsupported file type."
 
 
-# Step 1: upload file -> return column choices
 def on_upload(file):
     if file is None:
         return gr.Dropdown.update(choices=[]), "No file uploaded", None
+
     df, err = load_csv(file)
     if err:
         return gr.Dropdown.update(choices=[]), f"Error: {err}", None
+
     cols = df.columns.tolist()
-    return gr.Dropdown.update(choices=cols, value=cols[-1] if len(cols)>0 else None), f"Loaded {len(df)} rows, {len(cols)} columns", df
+    default_target = cols[-1] if cols else None
+    return gr.Dropdown.update(choices=cols, value=default_target), f"Loaded {len(df)} rows, {len(cols)} columns", df
 
 
 # Helper: build preprocessing + model pipeline