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9fdad88 4a9c2e6 9fdad88 4a9c2e6 9fdad88 4a9c2e6 9fdad88 9597931 4a9c2e6 9597931 4a9c2e6 9fdad88 9597931 9fdad88 9597931 4a9c2e6 8d648d2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | import logging
from flask import Flask, render_template, request
import pickle
logging.basicConfig(level=logging.DEBUG)
app = Flask(__name__)
app.logger.debug("Starting Flask app initialization.")
# 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():
app.logger.info("Accessed '/' route.")
return render_template('index.html')
@app.route('/predict', methods=['POST'])
def predict():
app.logger.debug("Predict route accessed.")
try:
precipitation = float(request.form['precipitation'])
temp_max = float(request.form['temp_max'])
temp_min = float(request.form['temp_min'])
wind = float(request.form['wind'])
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 in predict route: {e}")
return "An error occurred during prediction."
if __name__ == '__main__':
app.run(host='0.0.0.0', port=7860, debug=False)
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