Predictive Intelligence is a paid plugin that we have to activate manually. To start using this for your organization please make sure you should have followed the below steps.
1- Before starting to train any dataset Please confirm that 'sharedservice.worker' this user should have platform_ml_read , platform_ml_write, platform_ml_create role.
**If 'sharedservice.worker' will not have the above roles then you may get several errors during data training**
2- Once the data training is successful than to test the output the tester should have the ml_admin role.
**If the tester doesn't have that role, then the test section of the output will not appear. **
3- Add the below script in your Script include and call that in the client script to get the output-
3.1- Get Classification Output:
getClassificationOutcome: function() {
/**
Get Classification Output
: {JSON} - input fields data
: {string} -Solution Name
@return : {JSON} - Output values of input data with threshold value and confidence
------------
Input Format
------------
var solutionInput = {
"short_description": "email",
"description": "outlook issue"}
*/
var result = {
'results': [],
'inputReceived': solutionInput
};
try {
var solutionInput = this.getParameter('sysparm_fields');
var solutionName = this.getParameter('sysparm_solutionName');
var version = this.getActiveVersion(solutionName);
var mlSolution = sn_ml.ClassificationSolutionStore.get(solutionName);
var input = [];
input[0] = JSON.parse(solutionInput);
var options = {}; // configure optional parameters
options.top_n = 1;
options.apply_threshold = false;
var results = mlSolution.getVersion(version).predict(input, options);
var obj = JSON.parse(results);
for (var i = 0; i < obj[Object.keys(obj)].length; i++) {
var temp = {};
temp.predictedValue = obj[Object.keys(obj)][i].predictedValue.toString();
temp.predictedSysId = obj[Object.keys(obj)][i].predictedSysId.toString();
temp.confidence = obj[Object.keys(obj)][i].confidence;
result.results.push(temp);
//this.addToLog('info', 'predictedValue: ' + obj[Object.keys(obj)][i].predictedValue.toString() + ' Confidence: ' + obj[Object.keys(obj)][i].confidence);
}
return JSON.stringify(result);
} catch (ex) {
result.reason = ex.message.toString();
//this.addToLog('error', ex.message);
return JSON.stringify(result);
}
}
3.2- Get Similarity output:
getSimilarityOutcome: function() {
/**
Get Similarity records Output
@param1: {JSON} - input fields data
@param2: {String} -Solution Name
@return : {JSON} - Output values of input data with threshold value and confidence
*/
var result = {
'results': [],
'inputReceived': solutionInput
};
try {
var solutionInput = this.getParameter('sysparm_fields');
var solutionName = this.getParameter('sysparm_solutionName');
var version = this.getActiveVersion(solutionName);
var mlSolution = sn_ml.SimilaritySolutionStore.get(solutionName);
var input = [JSON.parse(solutionInput)];
var options = {}; // configure optional parameters
options.top_n = 2; //It will return top 2 record if you need one or more record you can add your count
options.apply_threshold = false;
var results = mlSolution.getVersion(version).predict(input, options);
var obj = JSON.parse(results);
var x;
var y;
for (x in obj) {
for (y in obj[x]) {
var temp = {};
temp.predictedValue = obj[x][y].predictedValue.toString();
temp.predictedSysId = obj[x][y].predictedSysId.toString();
temp.confidence = obj[x][y].confidence;
temp.kb = this.getKBNumber(obj[x][y].predictedSysId.toString());//please copy and past the below 4th point in this article otherwise it will throw error
result.results.push(temp);
}
}
return JSON.stringify(result);
} catch (ex) {
result.reason = ex.message.toString();
//this.addToLog('error', ex.message);
return JSON.stringify(result);
}
}
4- Please add below functions in the same script include:
getKBNumber: function(id) {
/**
@parm1: {string} - sys_id of KB record
@return: {string} - number of the KB
*/
var kb = new GlideRecord('kb_knowledge');
kb.get(id);
return kb.number.toString();
},
getActiveVersion: function(solutionName) {
/*
@parm1: {string} - sys_id of solution name
@return: {number} - active version of the solution
*/
var solution = new GlideRecord('ml_solution');
solution.addActiveQuery();
solution.get(solutionName);
return solution.version;
}
5- Use below client script as per your requirement:
/**
Input Preparation
key should be the backend name of your field and you can modify the below solutionInput as per your requiremnet
*/
var solutionInput = {
"short_description": g_form.getValue('short_description'),
"description": g_form.getValue('description')
};
//predict using clasification
var ga = new GlideAjax('global.predictCustomUtils'); //script include name
ga.addParam('sysparm_name', 'getClassificationOutcome');
ga.addParam('sysparm_fields', JSON.stringify(solutionInput));
ga.addParam('sysparm_solutionName', '<<Your Solution Name>>');
ga.getXMLAnswer(callBack);
function callBack(response) {
var ans = response;
//alert(ans);
if (ans == '' || ans == undefined || ans == null) {
//g_form.addErrorMessage('No similar record found for this combination.' + ans);
} else {
var answer = JSON.parse(ans);
var output = "";
if (answer.results.length > 0) {
for (var i = 0; i < answer.results.length; i++) {
alert('The Predicted Value:- '+answer.results[i].predictedValue.toString());
}
}
}
}
//Predict using similarity
var ga = new GlideAjax('global.predictCustomUtils'); //script include name
ga.addParam('sysparm_name', 'getSimilarityOutcome');
ga.addParam('sysparm_fields', JSON.stringify(solutionInput));
ga.addParam('sysparm_solutionName', '<<Your Solution Name>>');
ga.getXMLAnswer(callBack);
function callBack(response) {
var ans = response;
if (ans == '' || ans == undefined || ans == null) {
g_form.addErrorMessage('No similar record found for this combination. - ' + ans);
} else {
var answer = JSON.parse(ans);
var output = "";
if (answer.results.length > 0) {
var kb = '';
var kbNumbers = '';
for (var i = 0; i < answer.results.length; i++) {
kb += '<b><a href="/kb_knowledge.do?sys_id=' + answer.results[i].predictedSysId + '" target="_blank">' + answer.results[i].kb + '</a></b> ';
//gs.addInfoMessage(kb); //uncomment this line if you predictimng KB article using above input
kbNumbers += answer.results[i].kb + ' ';
}
if (kbNumbers != '') {
alert('Predcited Value : ' + kbNumbers);
}
}
}
}
If you need any help Please reach out to me via LinkedIn or send me a message.
Please mark it helpful if somehow it helps you in any manner.
