Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import pandas as pd
 import gradio as gr
 from sklearn.ensemble import RandomForestClassifier
@@ -32,6 +31,12 @@ model.fit(X_train, y_train)
 
 # Gradio interface function
 def predict_survival(Pclass, Gender, Age, SibSp, Parch, Fare, Embarked):
+    # Handle missing or invalid inputs
+    if not Gender:
+        return "⚠️ Error: Please select a Gender."
+    if not Embarked:
+        return "⚠️ Error: Please select a Port of Embarkation."
+
     # Encode Gender and Embarked
     Gender_encoded = 1 if Gender.lower() == 'female' else 0
     Embarked_encoded = {'s': 0, 'c': 1, 'q': 2}.get(Embarked.lower(), 0)
@@ -42,7 +47,7 @@ def predict_survival(Pclass, Gender, Age, SibSp, Parch, Fare, Embarked):
     
     # Predict
     prediction = model.predict(input_data)
-    return "Survived" if prediction[0] == 1 else "Did Not Survive"
+    return "✅ Survived" if prediction[0] == 1 else "❌ Did Not Survive"
 
 # Gradio inputs and outputs
 inputs = [
@@ -55,7 +60,7 @@ inputs = [
     gr.Radio(["S (Southampton)", "C (Cherbourg)", "Q (Queenstown)"], label="Port of Embarkation (Embarked)")
 ]
 
-outputs = gr.Textbox(label="Prediction")
+outputs = gr.Textbox(label="Prediction or Error Message")
 
 # Launch Gradio interface
 gr.Interface(fn=predict_survival, inputs=inputs, outputs=outputs, title="Titanic Survival Predictor").launch()