Update app.py

app.py

@@ -1,44 +1,17 @@
-import os
-import pickle
-import numpy as np
 from flask import Flask, request, jsonify
+import joblib
+import numpy as np
 
 app = Flask(__name__)
 
-# Load model
-MODEL_PATH = "predictive_model_smote.pkl"
-
-with open(MODEL_PATH, "rb") as f:
-    model = pickle.load(f)
+model = joblib.load("predictive_model.pkl")
 
 @app.route("/")
 def home():
-    return {"message": "Predictive Maintenance API is running"}
+    return "Predictive Maintenance API Running"
 
 @app.route("/predict", methods=["POST"])
 def predict():
-    try:
-        data = request.json
-        
-        # Expected input features in correct order
-        features = [
-            data["Air temperature [K]"],
-            data["Process temperature [K]"],
-            data["Rotational speed [rpm]"],
-            data["Torque [Nm]"],
-            data["Tool wear [min]"]
-        ]
-
-        features_array = np.array([features])
-        prediction = model.predict(features_array)[0]
-
-        return jsonify({
-            "prediction": int(prediction)
-        })
-
-    except Exception as e:
-        return jsonify({"error": str(e)})
-
-if __name__ == "__main__":
-    port = int(os.environ.get("PORT", 7860))
-    app.run(host="0.0.0.0", port=port)
+    data = request.json["features"]
+    prediction = model.predict([data])
+    return jsonify({"prediction": int(prediction[0])})