from flask import Flask, request, jsonify, render_template
import pandas as pd
import joblib

app = Flask(__name__)

# 加载模型
model_path = "cardio_predictor_model.pkl"
model = joblib.load(model_path)

@app.route('/')
def home():
    return render_template('index.html')

@app.route('/predict_cardio', methods=['POST'])
def predict_cardio():
    try:
        # 接收JSON请求数据
        data = request.json
        
        # 验证输入特征数量
        required_features = ['age', 'gender', 'height', 'weight', 'ap_hi', 'ap_lo', 
                            'cholesterol', 'gluc', 'smoke', 'alco', 'active']
        
        if not all(feature in data for feature in required_features):
            return jsonify({'error': '缺少必要的特征值'}), 400
        
        # 转换为DataFrame
        input_data = pd.DataFrame([data])
        
        # 执行与训练时相同的特征工程
        input_data['age_years'] = round(input_data['age'] / 365.25, 0)
        input_data['bmi'] = input_data['weight'] / ((input_data['height'] / 100) ** 2)
        
        # 删除原始age字段
        input_data = input_data.drop('age', axis=1)
        
        # 预测
        probability = model.predict_proba(input_data)[0][1]
        prediction = int(model.predict(input_data)[0])
        
        # 返回结果
        response = {
            'probability': float(probability),
            'prediction': prediction
        }
        
        return jsonify(response)
        
    except Exception as e:
        return jsonify({'error': str(e)}), 500

if __name__ == '__main__':
    app.run(debug=True, host='0.0.0.0', port=5000)