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from flask import Flask, render_template, request, jsonify
import joblib
import pandas as pd
import numpy as np
import os
app = Flask(__name__)
# Load model and scalers
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
MODEL_PATH = os.path.join(BASE_DIR, 'fraud_model.joblib')
SCALER_AMOUNT_PATH = os.path.join(BASE_DIR, 'scaler_amount.joblib')
SCALER_TIME_PATH = os.path.join(BASE_DIR, 'scaler_time.joblib')
DATA_PATH = os.path.join(BASE_DIR, 'creditcard.csv')
model = joblib.load(MODEL_PATH)
scaler_amount = joblib.load(SCALER_AMOUNT_PATH)
scaler_time = joblib.load(SCALER_TIME_PATH)
# Cache some samples for the frontend
df_all = pd.read_csv(DATA_PATH)
fraud_samples = df_all[df_all['Class'] == 1].sample(10).to_dict('records')
normal_samples = df_all[df_all['Class'] == 0].sample(10).to_dict('records')
@app.route('/')
def index():
return render_template('index.html')
@app.route('/get_samples', methods=['GET'])
def get_samples():
return jsonify({
"fraud": fraud_samples,
"normal": normal_samples
})
@app.route('/predict', methods=['POST'])
def predict():
try:
data = request.json
# Prepare feature vector (V1-V28, scaled_amount, scaled_time)
v_features = [float(data.get(f'V{i}', 0)) for i in range(1, 29)]
amount = float(data.get('Amount', 0))
time = float(data.get('Time', 0))
scaled_amount = scaler_amount.transform([[amount]])[0][0]
scaled_time = scaler_time.transform([[time]])[0][0]
# Combine all features
# Training script Order: X = df.drop('Class', axis=1)
# df had columns in order: V1...V28, scaled_amount, scaled_time (since original were dropped)
feature_vector = np.array(v_features + [scaled_amount, scaled_time]).reshape(1, -1)
prediction = int(model.predict(feature_vector)[0])
probability = model.predict_proba(feature_vector)[0].tolist()
return jsonify({
"is_fraud": prediction == 1,
"confidence": max(probability) * 100,
"class": "Fraudulent" if prediction == 1 else "Legitimate"
})
except Exception as e:
return jsonify({"error": str(e)}), 400
if __name__ == '__main__':
# Use port 7860 for Hugging Face Spaces
port = int(os.environ.get("PORT", 7860))
app.run(debug=True, host='0.0.0.0', port=port)
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