app.py

from flask import Flask, request, jsonify, render_template

app = Flask(__name__)

# Route for the home page
@app.route('/')
def index():
    return render_template('index.html')

# Prediction endpoint (mock prediction for now)
@app.route('/predict', methods=['POST'])
def predict():
    data = request.json
    activities = data.get('activities')
    
    # Placeholder logic for prediction (replace with your ML model)
    if activities:
        predicted_score = sum(activities) / len(activities)  # Example logic
        return jsonify({'predicted_score': predicted_score})
    return jsonify({'error': 'No activities provided'}), 400

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860)