GETTING STARTED
SearchAssist Overview
SearchAssist Introduction
Onboarding SearchAssist
Build your first App
Glossary
Release Notes
Current Version
Recent Updates
Previous Versions

CONCEPTS
Managing Sources
Introduction
Files
Web Pages
FAQs
Structured Data 
Connectors
Introduction to Connectors
SharePoint Connector
Confluence Connector
Zendesk Connector
ServiceNow Connector
Salesforce Connector
Azure Storage Connector
Google Drive Connector
Dropbox Connector
Oracle Knowledge Connector
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
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
Collaboration
Integrations
OpenAI Integration
Azure OpenAI Integration
Billing and Usage
Plan Details
Usage Logs
Order and Invoices

SearchAssist PUBLIC 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

Enabling Both Models

Answer snippets are generated based on the models enabled and the priority assigned to the models. For example, if only the extractive model is enabled for an application, it will display the extractive snippets generated from the source data. 

You can enable one or both models to display answer snippets. When both models are enabled, the model with the highest priority is first used to generate snippets. If it does not provide any snippet, the model, next in priority, is used to generate answer snippets. The priority is determined by the position of the models on the left. The model at the top of the list is the model with the highest priority.  For example, in the case shown below, the Extractive model is set to a higher priority. 

To change the priority of the models, use the drag dots icon and place the models as required. 

Points to remember

  • When both models are enabled, the answer from the model with higher priority is displayed on the top. 
  • It is recommended to enable both models only while testing your application.
  • Different models use different chunking strategies, hence the result may vary depending on the source content.

On this Page

Enabling Both Models

Answer snippets are generated based on the models enabled and the priority assigned to the models. For example, if only the extractive model is enabled for an application, it will display the extractive snippets generated from the source data. 

You can enable one or both models to display answer snippets. When both models are enabled, the model with the highest priority is first used to generate snippets. If it does not provide any snippet, the model, next in priority, is used to generate answer snippets. The priority is determined by the position of the models on the left. The model at the top of the list is the model with the highest priority.  For example, in the case shown below, the Extractive model is set to a higher priority. 

To change the priority of the models, use the drag dots icon and place the models as required. 

Points to remember

  • When both models are enabled, the answer from the model with higher priority is displayed on the top. 
  • It is recommended to enable both models only while testing your application.
  • Different models use different chunking strategies, hence the result may vary depending on the source content.