统一消息系统

import pandas as pd

from sklearn.feature_extraction.text import TfidfVectorizer

from sklearn.model_selection import train_test_split

from sklearn.naive_bayes import MultinomialNB

# 模拟数据集

data = {

'message': [

"优惠活动即将结束！",

"您的订单已发货。",

"垃圾邮件，请勿回复。",

"请参加我们的抽奖活动！"

],

'label': ['promotion', 'order', 'spam', 'promotion']

}

df = pd.DataFrame(data)

# 特征提取

vectorizer = TfidfVectorizer()

X = vectorizer.fit_transform(df['message'])

y = df['label']

# 划分训练集与测试集

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)

# 训练模型

model = MultinomialNB()

model.fit(X_train, y_train)

# 测试模型

print(model.score(X_test, y_test))

import pika

def callback(ch, method, properties, body):

print(f" [x] Received {body}")

connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))

channel = connection.channel()

channel.queue_declare(queue='task_queue', durable=True)

channel.basic_consume(queue='task_queue', on_message_callback=callback, auto_ack=True)

print(' [*] Waiting for messages. To exit press CTRL+C')

channel.start_consuming()