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from flask import Flask, request, jsonify
from joblib import load
# Initialize Flask app
app = Flask(__name__)
# Load the spam detection model
clf_loaded = load('./QuietML.joblib')
@app.route('/predict', methods=['POST'])
def predict():
# Get the email text from the incoming request
email_text = request.json.get('email_text')
if not email_text:
return jsonify({'error': 'No email_text provided'}), 400
# Make the prediction using the spam detector model
prediction = clf_loaded.predict([email_text])
probabilities = clf_loaded.predict_proba([email_text])
# Return the result as JSON
result = "Spam" if prediction == 1 else "Ham"
if prediction==1:
probabilities=probabilities[0][1]
else:
probabilities=probabilities[0][0]
return jsonify({'prediction': result,'probability': probabilities})
if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0', port=5000)
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