Create app.py

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+import joblib
+import numpy as np
+
+# Load the RandomForest model
+model = joblib.load('random_forest_model.pkl')  # Update with the actual path
+# Define a function for classification
+def classify(features):
+    # Convert the input features to a 2D numpy array
+    features_array = np.array([features])
+    # Make a prediction
+    prediction = model.predict(features_array)
+    return f"Predicted Age Category: {prediction[0]}"
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=classify,
+    inputs=[
+        gr.Slider(minimum=0, maximum=100, default=50, label=f"Feature {i+1}") for i in range(15)
+    ],
+    outputs="text",
+    title="Age Classification",
+    description="Enter the 15 features to classify the age category."
+)
+
+# Launch the interface
+iface.launch()