app.py

from flask import Flask, request, jsonify
from flask_cors import CORS
import pickle
import nltk
import string
from nltk.corpus import stopwords
from nltk.stem import PorterStemmer

app = Flask(__name__)
CORS(app)  # Enable CORS for all routes

# Load model and vectorizer
tfidf = pickle.load(open('vectorizer.pkl', 'rb'))
model = pickle.load(open('model.pkl', 'rb'))
ps = PorterStemmer()

# Text preprocessing function
def transform_text(text):
    text = text.lower()
    text = nltk.word_tokenize(text)

    y = []
    for i in text:
        if i.isalnum():
            y.append(i)

    text = y[:]
    y.clear()

    for i in text:
        if i not in stopwords.words('english') and i not in string.punctuation:
            y.append(i)

    text = y[:]
    y.clear()

    for i in text:
        y.append(ps.stem(i))

    return " ".join(y)

# Prediction endpoint
@app.route('/predict', methods=['POST'])
def predict():
    data = request.get_json(force=True)
    text = data['text']

    transformed_sms = transform_text(text)
    vector_input = tfidf.transform([transformed_sms])
    result = int(model.predict(vector_input)[0])  # Convert result to integer

    return jsonify({'result': result})


if __name__ == '__main__':
    app.run(debug=True)