const XMLHttpRequest = require("xmlhttprequest").XMLHttpRequest;
const btoa = require("btoa");
const wml_credentials = new Map();

function apiPost(scoring_url, token, mlInstanceID, payload, loadCallback, errorCallback){
	const oReq = new XMLHttpRequest();
	oReq.addEventListener("load", loadCallback);
	oReq.addEventListener("error", errorCallback);
	oReq.open("POST", scoring_url);
	oReq.setRequestHeader("Accept", "application/json");
	oReq.setRequestHeader("Authorization", token);
	oReq.setRequestHeader("ML-Instance-ID", mlInstanceID);
	oReq.setRequestHeader("Content-Type", "application/json;charset=UTF-8");
	oReq.send(payload);
}

// NOTE: generate iam_token based on provided documentation
const wmlToken = "Bearer " + iam_token;

// NOTE: retrieve ml_instance_id based on provided documentation
const mlInstanceId = ml_instance_id;

// NOTE: manually define and pass the array(s) of values to be scored in the next line
const payload = '{"input_data": [{"fields": ["id_prod", "tenand_id", "invoice_id", "quantity", "unit_value", "item_value", "customer_id", "doc_date", "total_discount", "total_tax", "total_value", "precio_productos", "name", "description", "list_price"], "values": [array_of_values_to_be_scored, another_array_of_values_to_be_scored]}]}';
const scoring_url = "https://us-south.ml.cloud.ibm.com/v4/deployments/ed641cae-5fa2-4c16-a611-4a1568e55901/predictions";

apiPost(scoring_url, wmlToken, mlInstanceId, payload, function (resp) {
	let parsedPostResponse;
	try {
		parsedPostResponse = JSON.parse(this.responseText);
	} catch (ex) {
		// TODO: handle parsing exception
	}
	console.log("Scoring response");
	console.log(parsedPostResponse);
}, function (error) {
	console.log(error);
});