Update app.py

app.py

@@ -40,13 +40,31 @@ def on_predict(row_label):
     idx = parse_index(row_label)
     row = df.iloc[idx][feature_cols]
     X_row = row.astype(float).values.reshape(1, -1)
+    
+    # Prediction
     pred = model.predict(X_row)[0]
     pred_rounded = float(np.round(pred, 3))
+
+    # Ground truth
+    actual = float(df.iloc[idx]["Yield_g_per_pot"])
+    
+    # Error (always positive)
+    error = abs(pred_rounded - actual)
+    error_rounded = float(np.round(error, 3))
+
+    # Markdown display
     features_md = "### Input Features\n\n" + row.to_frame().to_markdown()
-    result_md = f"### Predicted Yield (g per pot)\n\n**{pred_rounded}**"
+    result_md = (
+        f"### Results\n\n"
+        f"**Predicted Yield (g per pot):** {pred_rounded}\n\n"
+        f"**Actual Yield (Ground Truth):** {actual}\n\n"
+        f"**Absolute Error:** {error_rounded}"
+    )
+
     return "✅ Prediction complete", features_md, result_md
 
 
+
 row_choices = [make_row_label(i) for i in range(len(df))]
 
 with gr.Blocks(css="""