from flask import Flask, request, jsonify#--jsonify will return the data
    from keras.models import load_model
    import numpy as np
    import pandas as pd
    
    
    
    #creates the web service running on port 127.0.0.1:12345 and answer post requests on adress/api
    app = Flask(__name__)
    
    
    model=load_model('flask_model.h5')
    
    @app.route("/")
    def hello():
        return "machine learning model APIs!"
    
    
    @app.route('/api', methods=["POST"])
    def predict():
        
        # get the json send from the post as data
        data=request.get_json(force=True)
        print (data)
        
        #i expected jason to have the following values
        predict_request=[data["accx"], data["accy"], data["accz"],data["gyrx"], data["gyry"], data["gyrz"]]
        print (predict_request)
        
        predict_request= np.array(predict_request)
        print (predict_request)
    
        pred= model.predict(predict_request)
        print (pred)
        
        output=[pred[0]]
        print (output)
        
        #take a list of dictionaries and convert them to jason
        return jsonify(results=output)
        
    
    if __name__ == '__main__':
         app.run(port=8000, debug=True)