# Ticket AI Agent Assist
After you have created and configured the settings for the AiseraGPT base, navigate to \
Settings > Channels and add the Agent Assist channel to your tenant.
### To add the Agent Assist channel to your Tenant:
1. Navigate to Settings > Channels in the Aisera Admin UI.
2. Click the + New Channel button in the upper-right corner.
3. Select the Ticket AI Agent Assist icon.
4. Click Next.
5. The second part of the Agent Assist Channel configuration allows you to choose which options you want to see in your Agent Assist application/bot.
\
Default Widget Configuration (JSON)
```
[
{
"name": "top",
"layout": "column",
"sections": []
},
{
"name": "main",
"layout": "tabs",
"sections": [
{
"name": "Recommendations",
"description": "AI-generated content may contain inaccuracies or be misleading. Always verify its accuracy before drafting a response to customers.",
"enabled": true,
"sections": [
{
"name": "ticket_summary",
"enabled": true,
"config": {
"caseSummary": {
"title": "Case Summary",
"enabled": true,
"container": "expand",
"actions": {
"showCopy": true,
"showPost": false,
"showEmail": false
},
"feedback": {
"select": {
"label": "Select the reason you provided this rating.",
"options": [
{
"label": "Irrelevant Case Comments",
"value": "IrrelevantCaseComments"
},
{
"label": "Missing Important Case Details",
"value": "MissingImportantCaseDetails"
},
{
"label": "Missing Resolution / Summarization",
"value": "MissingResolutionOrSummarization"
},
{
"label": "No Response Provided",
"value": "NoResponseProvided"
},
{
"label": "Partially Correct",
"value": "PartiallyCorrect"
}
]
},
"text": {
"label": "Provide additional feedback for the selected reason.",
"placeholder": "Provide more information about the selected reason."
}
},
"autoRefresh": {
"default": 15000,
"maxTries": 2
}
},
"aiseraAnswer": {
"title": "Aisera Answer",
"enabled": true,
"container": "expand",
"actions": {
"showCopy": true,
"showPost": false,
"showEmail": false
},
"feedback": {
"select": {
"label": "Select the reason you provided this rating.",
"options": [
{
"label": "Irrelevant Answer",
"value": "IrrelevantAnswer"
},
{
"label": "Known Knowledge Article Not Found",
"value": "KnownKnowledgeArticleNotFound"
},
{
"label": "Misleading Answer",
"value": "MisleadingAnswer"
},
{
"label": "No Response Provided",
"value": "NoResponseProvided"
},
{
"label": "Partially Correct",
"value": "PartiallyCorrect"
},
{
"label": "Too General / Vague",
"value": "TooGeneralOrVague"
},
{
"label": "Wrong Product Area Focus",
"value": "WrongProductAreaFocus"
}
]
},
"text": {
"label": "Provide additional feedback for the selected reason.",
"placeholder": "Provide more information about the selected reason."
}
},
"autoRefresh": {
"default": 20000,
"maxTries": 3
}
}
}
},
{
"name": "next_best_action",
"enabled": false,
"config": {
"title": "Next Best Actions",
"container": "expand",
"actions": {
"showCopy": true,
"showPost": false,
"showEmail": false
},
"feedback": {
"select": {
"label": "Select the reason you provided this rating.",
"options": [
{
"label": "Incorrect Troubleshooting Steps",
"value": "IncorrectTroubleshootingSteps"
},
{
"label": "Misleading Answer",
"value": "MisleadingAnswer"
},
{
"label": "No Response Provided",
"value": "NoResponseProvided"
},
{
"label": "Partially Correct",
"value": "PartiallyCorrect"
},
{
"label": "Wrong Product Area Focus",
"value": "WrongProductAreaFocus"
}
]
},
"text": {
"label": "Provide additional feedback for the selected reason.",
"placeholder": "Provide more information about the selected reason."
}
},
"autoRefresh": {
"default": 20000,
"maxTries": 3
}
}
},
{
"name": "predictions",
"enabled": true,
"config": {
"title": "Field Predictions",
"colors": {
"success": "green",
"warning": "yellow",
"error": "error"
},
"showApplyAll": false,
"excludeFieldApply": [
"Product_Line__c",
"Product__c",
"Sub_Product__c",
"Area__c",
"Sub_Area__c"
],
"excludeFields": [],
"message": {
"missingCustomSettings": "No custom settings fields available.",
"missingCustomMetadata": "No custom metadata type fields mapping available.",
"emptyPredictions": "No field predictions available."
},
"container": "expand"
}
}
]
},
{
"name": "Assistant",
"description": "",
"enabled": true,
"sections": [
{
"name": "aisera_assistant",
"enabled": true
}
]
}
]
},
{
"name": "bottom",
"sections": []
}
]
```
Default Widget Policy (JSON)
```
{
"enabled": true,
"queryFields": [
"title",
"description"
],
"preProcessingV2": {
"title": "functionsetTitle(title){if(title.startsWith(\"'\")){title=title.replace(\"'\",'');}if(title.endsWith(\"'\")){title=title.substring(0,title.length-1);}returntitle;}",
"description": "function(description){varpre='Message:ShortDescriptionofIssue:';vari=description.toLowerCase().indexOf(pre.toLowerCase());if(i>=0){returndescription.substring(i+pre.length(),description.length());}returndescription;}"
},
"processing": {
"fields": [
"title+description"
],
"sequentialStopScore": 90
},
"confidenceScoreThreshold": {
"intent": 20
},
"scoreNormalization": {
"intent": "function(score){return(score-80)*(100-95)/(100-80)+95;}"
},
"useTenantClientRestAPI": true,
"useKBClassifier": false,
"useKBClassifierV2": false,
"KBClassifierMode": "append",
"predictionTimeout": {
"similarTickets": 10,
"search": 6,
"icmv2": 20,
"sentiment": 20,
"nlp": 10,
"summary": 10,
"answer": 30,
"intentExtraction": 5
},
"aclKeys": [],
"intentExtractorService": {
"enabled": false,
"deadlineInSec": 10
}
}
```
\
Default Post-Processing Instructions (JavaScript)
```
function postProcessing(predictionInputObj){
/* predictionInputObj contains responseData and ticketObj as json */
var predictionObj = {};
try {
var inputTicketObj = predictionInputObj.ticketObj;
predictionObj = predictionInputObj.responseData;
} catch (err) {
console.log(err);
predictionObj = { errorMessage: err, input: predictionInputObj };
}
return predictionObj;
}
```
Default Post-Processing Field Predictions (JavaScript)
```
function predictionPostProcessing(predictionInputObj){
/* predictionInputObj contains responseData and ticketObj as json */
var predictionObj = {};
try {
var inputTicketObj = predictionInputObj.ticketObj;
predictionObj = predictionInputObj.responseData;
} catch (err) {
console.log(err);
predictionObj = { errorMessage: err, input: predictionInputObj };
return predictionObj;
}
return predictionObj;
}
```
Default Post-Processing Similar Tickets (JavaScript)
```
function similarTicketsPostProcessing(predictionInputObj){
/* predictionInputObj contains responseData and ticketObj as json */
var predictionObj = {};
try {
var inputTicketObj = predictionInputObj.ticketObj;
predictionObj = predictionInputObj.responseData;
} catch (err) {
predictionObj = { errorMessage: err, input: predictionInputObj };
return predictionObj;
}
return predictionObj;
}
```
Default Post-Processing Sentiment Predictions (JavaScript)
```
function sentimentPostProcessing(predictionInputObj){
/* predictionInputObj contains responseData and ticketObj as json */
var predictionObj = {};
try {
var inputTicketObj = predictionInputObj.ticketObj;
predictionObj = predictionInputObj.responseData;
} catch (err) {
predictionObj = { errorMessage: err, input: predictionInputObj };
return predictionObj;
}
return predictionObj;
}
```
Default Post-Processing Knowledge Article Predictions (JavaScript)
```
function relatedKBPostProcessing(predictionInputObj){
/* predictionInputObj contains responseData and ticketObj as json */
var predictionObj = {};
try {
var inputTicketObj = predictionInputObj.ticketObj;
predictionObj = predictionInputObj.responseData;
} catch (err) {
predictionObj = { errorMessage: err, input: predictionInputObj };
return predictionObj;
}
return predictionObj;
}
```
System User Email
Click the **OK** button.
### To choose the Agent Assist channel for your application/bot:
---
# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://docs.aisera.com/aisera-platform/channels/ticket-ai-agent-assist.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.