一站式网上办事大厅

import flask

from flask import request

import nltk

from sklearn.feature_extraction.text import TfidfVectorizer

from sklearn.linear_model import LogisticRegression

app = flask.Flask(__name__)

model = LogisticRegression() # 假设已经训练好的分类模型

vectorizer = TfidfVectorizer() # 特征提取器

@app.route('/chat', methods=['POST'])

def chat():

user_input = request.json['input']

features = vectorizer.transform([user_input])

prediction = model.predict(features)[0]

return {'response': f'您说的是：{prediction}'}

if __name__ == '__main__':

app.run(debug=True)