Failed to create vector index.

Question

Hi All,

Iam getting the below error when i try to add azure ai search as a knowledge for the azure foundry agent.

Failed to create vector index. Your request for data was not sent. Here are some things to try: Check your network and internet connection, make sure a proxy server is not blocking your connection, check if you have an ad blocker turned on.

I asked with out IT team, they said that there is no blockage for azure foundry domain.

Does this error mean something else?

Please let me know

Answer 1

Hello RayDev

Thank you for sharing the details. This error message can be confusing, but in most Azure AI Foundry cases, it doesn’t actually mean there’s a browser, proxy, or internet issue, even though it may seem that way.

Usually, the error “Failed to create vector index. Your request for data was not sent” happens when Azure AI Foundry can’t connect to your Azure AI Search service while creating a vector index. This is often due to networking restrictions, permissions, or index requirements, rather than a corporate network block.

Here are some key things to check:

1. Azure AI Search networking: If public access is off, strict IP firewall rules are set, or a private endpoint is used, the Foundry portal may not be able to create or manage vector indexes. It’s recommended to enable public access or allow trusted Azure services. Docs:
   • Configure network access and firewall rules for Azure AI Search: https://learn.microsoft.com/azure/search/service-configure-firewall
   • Security and network access overview for Azure AI Search: https://learn.microsoft.com/azure/search/search-security-overview
2. Permissions (RBAC): If Entra ID (keyless) authentication is used, make sure the user or the Foundry project’s managed identity has the necessary roles on the search service, like Search Service Contributor and Search Index Data Contributor. Missing roles can cause this error. Docs:
   • Create a vector index – prerequisites and permissions: https://learn.microsoft.com/azure/search/vector-search-how-to-create-index
3. Vector index requirements: The search index must meet vector search requirements (such as having a Collection(Edm.Single) vector field with supported dimensions). If the schema isn’t compatible, index creation can fail. Docs:
   • Vector index schema and requirements: https://learn.microsoft.com/azure/search/vector-search-how-to-create-index
4. Foundry and Azure AI Search compatibility: Foundry agents have certain limitations with private or locked-down Azure AI Search resources accessed from the portal. These limitations are documented and can cause this error even if networking looks fine. Docs:
   • Use Azure AI Search with Azure AI Foundry agents: https://learn.microsoft.com/azure/ai-foundry/agents/how-to/tools-classic/azure-ai-search

This error is usually related to service configuration or permissions, not an IT internet block. Checking Azure AI Search network access, RBAC roles, and vector index compatibility should help resolve it.

If the suggestions above did not help resolve your issue, we have contacted you via private message for some additional details. Please review the message and share the requested information along with a screenshot of the error message so we can continue assisting you.

Thanks,
Suchitra.

Answer 2

The error message "Failed to create vector index" can be related to several issues, even if your IT team has confirmed that there are no network blockages. Here are some common reasons and troubleshooting steps you can consider:

1. Quota Limitations: Ensure that you have not exceeded the index quota for your Azure service. If you have reached the limit, you may need to delete unused indexes or upgrade your service for higher limits.
2. Permissions Issues: Verify that the credentials you are using have the necessary permissions to create an index. Ensure that the Azure OpenAI identity has the Search Service Contributor role for the search service.
3. Preprocessing Timeout Issues: If the error occurs during the processing of input documents, consider breaking down larger documents into smaller ones and trying again.
4. Service Availability: Check the Azure service status to ensure there are no ongoing outages or issues that might be affecting the service.

If the problem persists after checking these points, you may want to consult the Azure documentation or support for further assistance.

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References:

• Azure AI Search tool
• Troubleshooting