Update app.py

app.py

@@ -41,31 +41,27 @@ PREDICTOR = autogluon.tabular.TabularPredictor.load(
 
 
 def do_predict(height, width, depth, page_count):
-    row = {
-        "Height": float(height),
-        "Width": float(width),
-        "Depth": float(depth),
-        "Page Count": int(page_count),
-    }
-    X = pandas.DataFrame([row], columns=FEATURE_COLS)
-
-    pred_series = PREDICTOR.predict(X)
-    raw_pred = pred_series.iloc[0]
-
     try:
-        proba = PREDICTOR.predict_proba(X)
-        if isinstance(proba, pandas.Series):
-            proba = proba.to_frame().T
-    except Exception:
-        proba = None
+        row = {
+            "Height": float(height),
+            "Width": float(width),
+            "Depth": float(depth),
+            "Page Count": int(page_count),
+        }
+        X = pandas.DataFrame([row], columns=FEATURE_COLS)
 
-    proba_dict = None
-    if proba is not None:
+        proba = PREDICTOR.predict_proba(X)
         row0 = proba.iloc[0]
-        tmp = {str(cls): float(val) for cls, val in row0.items()}
-        proba_dict = dict(sorted(tmp.items(), key=lambda kv: kv[1], reverse=True))
 
-    return proba_dict
+        return dict(
+            sorted(
+                {str(cls): float(val) for cls, val in row0.items()}.items(),
+                key=lambda kv: kv[1],
+                reverse=True,
+            )
+        )
+    except Exception as e:
+        return {"Error": f"Invalid input: {e}"}
 
 
 EXAMPLES = [
@@ -79,7 +75,7 @@ with gradio.Blocks() as demo:
     gradio.Markdown("Enter book dimensions and page count to predict the genre.")
 
     with gradio.Row():
-        height = gradio.Slider(10, 30, step=0.5, value=20.0, label="Height (cm)")
+        height = gradio.Slider(10, 30, step=0.5, value=20.0, label="Height (cm)", info="Book height in centimeters")
         width = gradio.Slider(8, 25, step=0.5, value=13.0, label="Width (cm)")
     with gradio.Row():
         depth = gradio.Slider(1, 10, step=0.1, value=3.0, label="Depth (cm)")