Update app.py

app.py

@@ -1,14 +1,19 @@
+import logging
 from flask import Flask, render_template, request
 import pickle
 
+logging.basicConfig(level=logging.DEBUG)
 app = Flask(__name__)
 
-# Load the trained model
-# with open('random_forest_model.pkl', 'rb') as file:
-  #  model = pickle.load(file)
+app.logger.debug("Starting Flask app initialization.")
 
-import logging
-logging.basicConfig(level=logging.DEBUG)
+# Load the model
+try:
+    with open("random_forest_model.pkl", "rb") as file:
+        model = pickle.load(file)
+    app.logger.debug("Model loaded successfully.")
+except Exception as e:
+    app.logger.error(f"Error loading model: {e}")
 
 @app.route('/')
 def index():
@@ -17,21 +22,18 @@ def index():
 
 @app.route('/predict', methods=['POST'])
 def predict():
+    app.logger.debug("Predict route accessed.")
     try:
-        # Log incoming form data
-        app.logger.debug(f"Form data: {request.form}")
         precipitation = float(request.form['precipitation'])
         temp_max = float(request.form['temp_max'])
         temp_min = float(request.form['temp_min'])
         wind = float(request.form['wind'])
-        
-        # Log model prediction attempt
-        app.logger.debug("Making a prediction.")
         prediction = model.predict([[precipitation, temp_max, temp_min, wind]])
         return render_template('result.html', prediction=prediction[0])
     except Exception as e:
-        app.logger.error(f"Error during prediction: {e}")
-        return "An error occurred. Check logs."
+        app.logger.error(f"Error in predict route: {e}")
+        return "An error occurred during prediction."
+
 
 
 if __name__ == '__main__':