AI应用管理双十一优惠活动

from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier

# 假设我们有一个用户行为数据集
data = pd.read_csv('user_behavior.csv')

# 分割数据集
X_train, X_test, y_train, y_test = train_test_split(data.drop('target', axis=1), data['target'], test_size=0.2)

# 训练模型
model = RandomForestClassifier()
model.fit(X_train, y_train)

# 预测
predictions = model.predict(X_test)

from flask import Flask, request, jsonify
import spacy

app = Flask(__name__)
nlp = spacy.load('en_core_web_sm')

@app.route('/chat', methods=['POST'])
def chat():
    user_message = request.json['message']
    doc = nlp(user_message)
    response = generate_response(doc)  # 自定义函数，根据输入生成回复
    return jsonify({'response': response})

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