Create app.py

app.py

@@ -0,0 +1,39 @@
+import gradio as gr
+import joblib
+import pandas as pd
+
+# Load models
+model = joblib.load("isolation_forest_model.joblib")
+scaler = joblib.load("standard_scaler.joblib")
+features = joblib.load("features_to_scale.joblib")
+
+def predict(*inputs):
+    try:
+        # Create dataframe
+        data = pd.DataFrame([inputs], columns=features)
+
+        # Scale
+        scaled = scaler.transform(data)
+
+        # Predict
+        prediction = model.predict(scaled)
+
+        if prediction[0] == -1:
+            return "Anomaly Detected"
+        else:
+            return "Normal"
+
+    except Exception as e:
+        return str(e)
+
+# Create input fields dynamically
+inputs = [gr.Number(label=f) for f in features]
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=inputs,
+    outputs="text",
+    title="Anomaly Detection API"
+)
+
+demo.launch(server_name="0.0.0.0", server_port=7860)