一站式网上办事大厅

import requests

from sklearn.feature_extraction.text import TfidfVectorizer

from sklearn.naive_bayes import MultinomialNB

# 模拟AI助手分类

def classify_issue(text):

vectorizer = TfidfVectorizer()

X = vectorizer.fit_transform(["设备故障", "网络问题", "水电问题"])

y = ["设备", "网络", "水电"]

model = MultinomialNB()

model.fit(X, y)

new_text = vectorizer.transform([text])

return model.predict(new_text)[0]

# 提交报修请求

def submit_complaint(issue_type, description):

payload = {

"issue_type": issue_type,

"description": description

}

response = requests.post("https://api.one-stop.com/submit", json=payload)

return response.json()

# 示例使用

issue = "打印机无法打印"

category = classify_issue(issue)

result = submit_complaint(category, issue)

print(result)