app.py

import pickle
from flask import Flask, request, render_template, jsonify

# Create an instance of the Flask class
# with the name of the application’s modules
app = Flask(__name__, template_folder='templates')

# Create the / API route and render the root HTML page
@app.route('/', methods=['GET'])
def main():
    return(render_template('main.html'))

# Create the /predict API route
@app.route('/predict', methods=['GET', 'POST'])
def predict():
    # Use pickle to load in vectorizer
    with open(f'./model/vectorizer.pkl', 'rb') as f:
        vectorizer = pickle.load(f)

    # Use pickle to load in the pre-trained model
    with open(f'./model/model.pkl', 'rb') as f:
        model = pickle.load(f)
    
    # Get the message from the API request
    message = request.args.get('message')

    if request.method == 'GET' and message != None:
        mbpti_types = {
            0: "ENFJ (Extroversion, Intuition, Feeling, Judging)",
            1: "ENFP (Extroversion, Intuition, Feeling, Perceiving)",
            2: "ENTJ (Extroversion, Intuition, Thinking, Judging)",
            3: "ENTP (Extroversion, Intuition, Thinking, Perceiving)",
            4: "ESFJ (Extroversion, Sensing, Feeling, Judging)",
            5: "ESFP (Extroversion, Sensing, Feeling, Perceiving)",
            6: "ESTJ (Extroversion, Sensing, Thinking, Judging)",
            7: "ESTP (Extroversion, Sensing, Thinking, Perceiving)",
            8: "INFJ (Introversion, Intuition, Feeling, Judging)",
            9: "INFP (Introversion, Intuition, Feeling, Perceiving)",
            10: "INTJ (Introversion, Intuition, Thinking, Judging)",
            11: "INTP (Introversion, Intuition, Thinking, Perceiving)",
            12: "ISFJ (Introversion, Sensing, Feeling, Judging)",
            13: "ISFP (Introversion, Sensing, Feeling, Perceiving)",
            14: "ISTJ (Introversion, Sensing, Thinking, Judging)",
            15: "ISTP (Introversion, Sensing, Thinking, Perceiving)"
            }

        prediction = model.predict(vectorizer.transform([message]))
        result = mbpti_types[prediction[0]]

        data = {
            "message": message,
            "prediction": result
        }
        return jsonify(data)
    
    else :
        data = {
            "code": 400,
            "description": "Bad Request. No message was provided.",
            "message": "Use the message parameter to make a GET request."
        }
        return jsonify(data), 400

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