GETTING STARTED
SearchAssist Overview
SearchAssist Introduction
Onboarding SearchAssist
Build your first App
Glossary
Release Notes
What's new in SearchAssist
Previous Versions

CONCEPTS
Managing Sources
Introduction
Files
Web Pages
FAQs
Structured Data 
Connectors
Introduction to Connectors
Azure Storage Connector
Confluence Cloud Connector
Confluence Server Connector
Custom Connector
DotCMS Connector
Dropbox Connector
Google Drive Connector
Oracle Knowledge Connector
Salesforce Connector
ServiceNow Connector
SharePoint Connector
Zendesk Connector
RACL
Virtual Assistants
Managing Indices
Introduction
Index Fields
Traits
Workbench
Introduction to Workbench
Field Mapping
Entity Extraction
Traits Extraction
Keyword Extraction
Exclude Document
Semantic Meaning
Snippet Extraction
Custom LLM Prompts
Index Settings
Index Languages
Managing Chunks
Chunk Browser
Managing Relevance
Introduction
Weights
Highlighting
Presentable
Synonyms
Stop Words
Search Relevance
Spell Correction
Prefix Search
Custom Configurations
Personalizing Results
Introduction
Answer Snippets
Introduction
Extractive Model
Generative Model
Enabling Both Models
Simulation and Testing
Debugging
Best Practices and Points to Remember
Troubleshooting Answers
Answer Snippets Support Across Content Sources
Result Ranking
Facets
Business Rules
Introduction
Contextual Rules
NLP Rules
Engagement
Small Talk
Bot Actions
Designing Search Experience
Introduction
Search Interface
Result Templates
Testing
Preview and Test
Debug Tool
Running Experiments
Introduction
Experiments
Analyzing Search Performance
Overview
Dashboard
User Engagement
Search Insights
Result Insights
Answer Insights

ADMINISTRATION
General Settings
Credentials
Channels
Team
Collaboration
Integrations
OpenAI Integration
Azure OpenAI Integration
Custom Integration
Billing and Usage
Plan Details
Usage Logs
Order and Invoices
Smart Hibernation

SearchAssist APIs
API Introduction
API List

SearchAssist SDK

HOW TOs
Use Custom Fields to Filter Search Results and Answers
Add Custom Metadata to Ingested Content
Write Painless Scripts
Configure Business Rules for Generative Answers

How to Add Custom Metadata to Ingested Content

SearchAssist supports a ‘meta_data’ field that allows you to add custom information to your document metadata or record. This is useful as it enables you to add filters or business rules based on this field.  You can either manually add this field to the data, like in the case of structured data, or use a workbench stage to incorporate this field. Find more information on the meta_data field and how to use it here

This document describes how to use Workbench to include the meta_data field in the extracted content. 

Workbench tool provides you with different types of stages for different types of processing on the extracted content. To add a new field to the extracted content, we can use either the Field Mapping Stage or the Custom Script stage, depending upon the value to be .inserted to the field. 

For illustration, let’s incorporate the following field into content crawled from web pages

"meta_data": {
 "owner": "<value>"
}
  • Go to the Workbench and add the Custom Script stage. Refer to this guide to learn how to add a new stage
  • Since we are processing the web page content, set the condition as follows:
  • Next, add the script to create a new field meta_data with your custom JSON data. You can use the following script.
    //Create your JSON in string format.
    ctx.str_owner="{\"owner\":\"John\"}";
    
    //Add meta_data field to the document and set the JSON object as its value
    ctx.meta_data= Processors.json(ctx.str_owner);
    
    //Update the value of the custom field as required.
    ctx.meta_data.owner="Harry";

    You can now this custom metadata for further processing of data in Workbench or filtering results. 

How to Add Custom Metadata to Ingested Content

SearchAssist supports a ‘meta_data’ field that allows you to add custom information to your document metadata or record. This is useful as it enables you to add filters or business rules based on this field.  You can either manually add this field to the data, like in the case of structured data, or use a workbench stage to incorporate this field. Find more information on the meta_data field and how to use it here

This document describes how to use Workbench to include the meta_data field in the extracted content. 

Workbench tool provides you with different types of stages for different types of processing on the extracted content. To add a new field to the extracted content, we can use either the Field Mapping Stage or the Custom Script stage, depending upon the value to be .inserted to the field. 

For illustration, let’s incorporate the following field into content crawled from web pages

"meta_data": {
 "owner": "<value>"
}
  • Go to the Workbench and add the Custom Script stage. Refer to this guide to learn how to add a new stage
  • Since we are processing the web page content, set the condition as follows:
  • Next, add the script to create a new field meta_data with your custom JSON data. You can use the following script.
    //Create your JSON in string format.
    ctx.str_owner="{\"owner\":\"John\"}";
    
    //Add meta_data field to the document and set the JSON object as its value
    ctx.meta_data= Processors.json(ctx.str_owner);
    
    //Update the value of the custom field as required.
    ctx.meta_data.owner="Harry";

    You can now this custom metadata for further processing of data in Workbench or filtering results.