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The Use search connectors currently states that Elser must be used in order for the AI Assistant to support it.
Since version 8.17, we now support querying search connectors using the semantic_text field. This update allows users to:
Choose their preferred embedding model: Users can opt for models like e5 (multilingual) instead of being limited to Elser
Incorporate custom indices: Users can create their own indices and include them in the knowledge base. This can be configured using the UI setting observability:aiAssistantSearchConnectorIndexPattern. In this case they can also use any model they want, as long as they use semantic_text
Description
The Use search connectors currently states that Elser must be used in order for the AI Assistant to support it.
Since version 8.17, we now support querying search connectors using the
semantic_text
field. This update allows users to:observability:aiAssistantSearchConnectorIndexPattern
. In this case they can also use any model they want, as long as they usesemantic_text
Resources
semantic_text
fields in search connectors kibana#200184Which documentation set does this change impact?
Stateful and Serverless
Feature differences
This feature is identical in serverless and stateful
What release is this request related to?
8.17
Collaboration model
The documentation team
Point of contact.
Main contact: @mdbirnstiehl @dedemorton
Stakeholders: @sorenlouv @teknogeek0
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