AI connector

Serverless Preview Stack Preview 9.2.0

The AI Connector uses the Inference API to connect to third-party Large Language Model (LLM) services to enable AI-powered Kibana features such as AI Assistant. It can connect with LLM services including Amazon Bedrock, Azure, Google Gemini, and OpenAI. It can also connect with models you've enabled in Elastic Inference Service (EIS).

• A working LLM connector.
• Elastic Stack users: An Enterprise subscription.
• Serverless users: a project with the Security Analytics Complete feature tier.
• The Actions and Connectors : All privilege.

1. Use the global search field to find the Connectors page.
2. Click + Create connector. Select AI Connector.
3. Name your connector and select which LLM service to use.
4. In the Settings section, specify which model to use for this connector. You may need to refer to your selected LLM service's list of models. Model names and other model parameters must be exact.
5. In the Authentication section, provide the necessary credentials. All supported LLM services other than EIS require authentication. For information about how to generate authentication information for each one, refer to Enable LLM access.
6. Expand the Additional settings menu. Select a Task type that matches your selected model's purpose. Refer to the model information for your selected model to identify which task types it supports.
7. (Optional) In the Additional settings section, some LLM services allow you to set a Context window length. Enter a value to specify how many tokens to send to the model per request, or leave it blank to use the model's default.
8. Finally, click Save & test to verify that the connector is set up.

You can now select your newly configured connector for all Kibana features that rely on LLM connectors.