Name
global.DefaultAutoResolutionPostProcessingExtPoint
Description
Implements extension point global.AutoResolutionPostProcessingExtPoint This extension point is used to post process ML prediction results as required by the BU s during the Issue Auto-Resolution flow. This will be evaluated in the Auto-resolution flow once the ML API s for prediction - LanguageX returns the response for a given task and before any notification to the task caller is sent.
Script
var DefaultAutoResolutionPostProcessingExtPoint = Class.create();
DefaultAutoResolutionPostProcessingExtPoint.prototype = {
STATUS_SUCCESS : global.AutoResolutionConstants.STATUS_SUCCESS,
STATUS_ERROR : global.AutoResolutionConstants.STATUS_ERROR,
// criticality states
CRITICALITY_NON_CRITICAL: global.AutoResolutionConstants.CRITICALITY_NON_CRITICAL,
CRITICALITY_CRITICAL: global.AutoResolutionConstants.CRITICALITY_CRITICAL,
CRITICALITY_INCONCLUSIVE: global.AutoResolutionConstants.CRITICALITY_INCONCLUSIVE,
initialize: function() {
},
/**
* Return the normalized prediction results to update the prediction table - sys_cs_auto_resolution_prediction
*
* @param logger
* @param parameterBag : The keys in the bag: language_x_result, ar_config_id
*
* eg: {
* "language_x_result" : <object>, // the result from the languageX. see below.
* "ar_config_id" : "a0ff3e68533101105400ddeeff7b12e8" // Auto resolution configuration sys Id
* }
*
* where language_x_result object looks like this -
*
* {
* "schemaVersion": "1.0",
* "status": {
* "code": 200,
* "message": "SUCCESS"
* },
* "result": [
* {
* "input": {
* "id": "feda6b70072120109c3e59bf1ad30010",
* "tableName": "hr_core_case",
* "fields": {
* "description": "I have received incorrect salary amount"
* }
* },
* "output": [
* {
* "service": "languageDetection",
* "serviceOutput": "en",
* "serviceOutputScore": 0.9963439,
* "serviceOutputDetails": ""
* },
* {
* "service": "criticalityDetection",
* "serviceOutput": "PayContributions-Critical",
* "serviceOutputScore": 0.94924694,
* "serviceOutputDetails": "{\"status\":\"success\",\"response\":{\"utterance\":\"I have received incorrect salary amount\",\"intents\":[{\"intentName\":\"PayContributions-Critical\",\"nluModelName\":\"ml_x_snc_global_global_087ad49d1b9eb0101115da01b24bcb70\",\"score\":0.94924694,\"intents\":[]}],\"properties\":{\"inference.time\":\"12\",\"nluPlatformLanguage\":\"en\",\"nluPlatformVersion\":\"3.1.2-HYB\"}}}"
* },
* {
* "service": "searchQueryGeneration",
* "serviceOutput": "",
* "serviceOutputScore": "",
* "serviceOutputDetails": "[{\"query\":\"incorrect salary\",\"score\":\"0.83\"},{\"query\":\"salary amount\",\"score\":\"0.73\"}]"
* }
* ]
* }
* ]
* }
*
* @returns : JSON object that contains field name-value pairs to update the prediction table - sys_cs_auto_resolution_prediction
* the name in the result should be the same as the field name in the table
*
* eg: {
* status: this.SUCCESS,
* message: ''
* result: [ // the block that contains name-value pairs
* {
* predicted_language : 'en', // optional. If omitted, the value from the payload will be used
* predicted_search_query: 'incorrect salary' , // optional. If omitted, the search terms that exceed the threshold will be used.
* predicted_criticality: this.CRITICALITY_NON_CRITICAL, this.CRITICALITY_CRITICAL or this.CRITICALITY_INCONCLUSIVE
* }
* ]
* }
*/
process: function(logger, parameterBag) {
logger.info("Starting the post-processing extension: {0}", this.type);
var response = {status:this.STATUS_SUCCESS, message:'', result: []};
//the payload is guaranteed to exist.
var payload = parameterBag.language_x_result;
var status = payload.status;
response.message = status.message;
if (status.code != 200) {
// if the code != 200, there was an error and let's abort the process
response.status = this.STATUS_ERROR;
logger.warn("Aborting the post-processing extension:{0}. status-code:{1}, status-message:{2}, payload:{3}",
this.type, status.code, status.message, JSON.stringify(payload));
return response;
}
if (payload.result.length == 0) {
response.status = this.STATUS_ERROR;
logger.warn("Aborting the post-processing extension:{0}. reason: no result found. status-code:{1}, status-message:{2}, payload:{3}",
this.type, status.code, status.message, JSON.stringify(payload));
return response;
}
var obj = {};
// Note that currently, Auto-Resolution supports only one result, but may be extended in the future.
var elements = payload.result[0].output;
for (var i=0; i<elements.length; i++) {
var output = elements[i];
switch(output.service) {
case global.AutoResolutionConstants.LANGUAGE_DETECTION_SERVICE_NAME:
obj.predicted_language = this.getDetectedLanguage(output.serviceOutput , logger);
break;
case global.AutoResolutionConstants.CRITICALITY_PREDICTION_SERVICE_NAME:
obj.predicted_criticality = this.getCriticality(output.serviceOutput , logger);
break;
case global.AutoResolutionConstants.SEARCH_QUERY_GENERATION_SERVICE_NAME:
obj.predicted_search_query = this.getSearchQueries(output.serviceOutputDetails , logger);
break;
}
}
// add this object into the array.
response.result.push(obj);
logger.info("The execution of post-processing extension:{0} is completed", this.type);
return response;
},
/**
* Returns the normalized criticality
* @return criticality {String}
*/
getCriticality:function(output, logger) {
var val = output.toLowerCase();
var rtnVal = this.CRITICALITY_INCONCLUSIVE; // default is inconclusive.
if (gs.nil(val)) // if empty string, treat it as inconclusive
rtnVal = this.CRITICALITY_INCONCLUSIVE;
else if (val.indexOf("_noncritical") != -1) // noncritical suffix
rtnVal = this.CRITICALITY_NON_CRITICAL;
else if (val.indexOf("_critical") != -1) // critical suffix
rtnVal = this.CRITICALITY_CRITICAL;
else if (val.indexOf("noncritical") != -1)
rtnVal = this.CRITICALITY_NON_CRITICAL;
else if (val.indexOf("critical") != -1)
rtnVal = this.CRITICALITY_CRITICAL;
else if (val.indexOf("inconclusive") != -1)
rtnVal = this.CRITICALITY_INCONCLUSIVE;
// if not exist, return the critical
logger.info('The post-processing extension: {0} - retuning {1} for the predicted criticality', this.type, rtnVal);
return rtnVal;
},
getSearchQueries:function(details, logger) {
return ''; // add a particular logic if needed. If an empty string is returned, the search terms that exceed the threshold will be used.
},
getDetectedLanguage:function(output, logger) {
return ''; // add a particular logic if needed. If an empty string is returned, the found value in the payload will be used.
},
type: 'DefaultAutoResolutionPostProcessingExtPoint'
};Sys ID
0b913be2ebf5011054009861eb522883