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Generative AI
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Supervisor Agent or Knowledge assistant not available

tensorwrangler
New Contributor II

I am unable to make use of the Supervisor Agent or Knowledge assistant.
I have this issue on multiple Databricks environments / workspace (Databricks native / azure / ....)

  • The databricks native one has a premium account with a credit card associated.
  • The Azure one is billed through an azure subscription
  • Previews are enabled

tensorwrangler_0-1785251706703.png

What do I need to do in orde to enable this ? help@databricks.com has forwarded me to this forum.

Thanks in advance.

 

6 REPLIES 6

emma_s
Databricks Employee
Databricks Employee

Hi,

I think the most likely thing is regional availbilty and that would be the first thing I'd check.

Here is the link to current availability by region for Azure and AWS:

https://learn.microsoft.com/en-us/azure/databricks/resources/feature-region-support

https://docs.databricks.com/aws/en/resources/feature-region-support#ai-agent-features-availability

If the region you've deployed too looks llike it should be there also look for the little icon next to it, it may be that you have to enable cross geo to get it to work. https://learn.microsoft.com/en-us/azure/databricks/resources/databricks-geos

Other causes coudl be
- Partner Powered AI Features being toggled off

- serverless compute not available or budget set to zero (unlikely as you've just set up the workspace)

-UC not enabled (again unlikely as it should be enabled by default)

- Missing model serving access.

I hope this helps.


Thanks,

Emma

 

I thought that if there was a region availability issue that it was mentioned in the error message.

  • I'm on azure swedencentral so that should be ok.  (All agent boxes ticked on the azure databricks region support page.)
  • Cross Geo is enabled in databricks
  • Serverless compute is available with budget
  • UC is enabled
  • Not sure how to check model serving access. (there are serving endpoints in state ready that I can use)

emma_s
Databricks Employee
Databricks Employee

Hi,

Just looked into it again and I agree with you, you should work. The only thing I think you could try is the enablement of partner powered features?  You didn't mention that in your list above.


Thanks,

Emma

honey_sharma
New Contributor II

Hi, if you're seeing "Supervisor Agent or Knowledge Assistant not available" across multiple Databricks workspaces (including Databricks-native and Azure), even with preview features enabled and appropriate billing, it's worth checking whether these features are supported in your workspace region and enabled at both the account and workspace levels. In some cases, availability depends on the cloud provider, workspace region, account entitlements, or a phased rollout rather than workspace configuration. You can review the prerequisites here:

https://docs.databricks.com/aws/en/agents/

https://docs.databricks.com/gcp/en/agents/agent-bricks/multi-agent-supervisor

https://docs.databricks.com/aws/en/generative-ai/ai-assistant/

Could you also share which cloud provider (AWS, Azure, or GCP) and region your workspaces are running in? If everything appears to be configured correctly, this may require Databricks Support to verify feature availability for your account.

  • Azure :  swedencentral  - everything should be supported
  • Databricks (native ? - the one you convert to premium after a trial, not triggered from AWS or Azure don't know how you call that deploy option) seems to be running on AWS us-west-2. Also a region where everything is supported.

    | just notied that the supervisor agent started working on us-west-2. I did contact sales (As indicated in the error msg) but never got a reply back. perhaps they did something ?
    tensorwrangler_1-1785764674862.png

     




    the one on Azure stil shows me the same error 

tensorwrangler_0-1785764629401.png

 

 



emma_s
Databricks Employee
Databricks Employee

Hi,

Sorry you're still having issues but glad it seems to be working on the AWS one. It should be working in that region in Azure as far as I can tell. It could be an issue with model availability on Azure, at the point you tried it. If you have an Azure agreement with support you can actually file a support ticket through that and they may be able to advise.


Thanks,

Emma