Create app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+import pandas as pd
+import numpy as np
+import joblib
+
+# Load the trained model
+model = joblib.load("predictive_maintenance_model.pkl")
+
+# Define the prediction function
+def predict_maintenance(feature1, feature2, feature3, feature4):
+    input_data = np.array([[feature1, feature2, feature3, feature4]])  # Modify according to your dataset
+    prediction = model.predict(input_data)
+    return f"Predicted Maintenance Requirement: {prediction[0]}"
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=predict_maintenance,
+    inputs=[
+        gr.Number(label="Feature 1"),
+        gr.Number(label="Feature 2"),
+        gr.Number(label="Feature 3"),
+        gr.Number(label="Feature 4"),
+    ],
+    outputs=gr.Textbox(label="Prediction"),
+    title="Predictive Maintenance for Industrial Equipment",
+    description="Enter sensor readings to predict maintenance requirements."
+)
+
+# Launch the app
+interface.launch()