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# Import necessary libraries
from flask import Flask, render_template, request, jsonify
from utils import model_predict, get_available_models
# Initialize Flask app
app = Flask(__name__)
@app.route("/")
def home():
models = get_available_models()
return render_template("index.html", models=models)
@app.route('/predict', methods=["POST"])
def predict():
"""
Handles form submission and returns prediction.
"""
email = request.form.get('email')
model_name = request.form.get('model')
if not email:
return render_template("index.html",
error="Please provide an email",
models=get_available_models())
if not model_name:
return render_template("index.html",
error="Please select a model",
models=get_available_models())
try:
prediction = model_predict(email, model_name)
result = "Spam" if prediction == 1 else "Not Spam"
return render_template("index.html",
prediction=result,
email=email,
selected_model=model_name,
models=get_available_models())
except Exception as e:
return render_template("index.html",
error=f"Error: {str(e)}",
models=get_available_models())
@app.route('/api/predict', methods=["POST"])
def predict_api():
"""
API endpoint that accepts a JSON payload and returns a prediction.
"""
try:
data = request.get_json()
email = data.get("email")
model_name = data.get("model")
if not email:
return jsonify({'error': 'No email provided'}), 400
if not model_name:
return jsonify({'error': 'No model selected'}), 400
prediction = model_predict(email, model_name)
result = "Spam" if prediction == 1 else "Not Spam"
return jsonify({
'email': email,
'model': model_name,
'prediction': result
})
except Exception as e:
return jsonify({'error': str(e)}), 400
if __name__ == "__main__":
app.run(host="0.0.0.0", port=5000, debug=True)
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