Using Azure Search / RAG in Azure AI Foundry Pipeline

[ThoSt81]

First, thanks for the great work! I can use my Azure AI just fine and it's working well!

However, since we are using an Azure Search index (RAG) holding documents/information for the AI to use, I cant find a way to add this to the configuration.

Essentially, the following needs to be added to the request body sent to Azure AI:

  "data_sources": [
    {
      "type": "azure_search",
      "parameters": {
        "filter": null,
        "endpoint": "https://xxx.search.windows.net",
        "index_name": "xxx",
        "project_resource_id": "xxx",
        "semantic_configuration": "azureml-default",
        "authentication": {
          "type": "system_assigned_managed_identity",
          "key": null
        },
        "embedding_dependency": null,
        "embeddingEndpoint": "xxx",
        "embeddingKey":"xxx",
        "query_type": "vectorSimpleHybrid",
        "in_scope": false,
        "role_information": "You are an AI assistant.",
        "strictness": 5,
        "top_n_documents": 20,
        "key": "xxx",
        "indexName": "xxx"
      }
    }
  ]

Is there an easy way to add this?

[owndev]

Hello @ThoSt81

I haven't used Azure AI Search yet and can't help with the details.

Theoretically, I could implement additional fields to add a custom body field. But then it would be defined for all configured models. I don't know how helpful this would be.

[ThoSt81]

That would be great! I dont think there is any harm if this additional body field is left empty but it would allow for greater flexibility.

Happy to test as I have a few different configurations to try.

[owndev]

I had Copilot write the extensions. Can you test it and give me some recommendations?

• https://github.com/owndev/Open-WebUI-Functions/blob/56579809c992c0ce934a9f34002d301287a89b50/pipelines/azure/azure_ai_foundry.py

Many new variables have been defined.
Is it better to define only one variable and then define the entire JSON there, or should I do it like Copilot did?

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#48 and #49

[ThoSt81]

Great! Thank you for the quick update! Will try this tomorrow and will let you know!

[ThoSt81]

The errors are gone but the settings dont seem to be respected. I will try to troubleshoot further but something important came up and it may take some time before I can test more.

[ThoSt81]

@owndev sorry for the late response. I have got this to work now, small problem in my json so your implementation seems fine.
What I noticed though, is that after I restart the container, the API key is not working any more and I need to re-enter it. The field is still filled with "encrypted:gAAAA*****". Once I copy past the API key and save the function, everything is working again until the next restart.

[owndev]

I've never had this problem before.
Does it affect both API keys or just one?

Is it possible that you haven't set the WEBUI_SECRET_KEY variable, which is preventing the encryption from working correctly?

[ThoSt81]

Hm, I did not set WEBUI_SECRET_KEY. I've donet his now and retest.

[ThoSt81]

Confirmed. Setting WEBUI_SECRET_KEY did the trick. Sorry for not spotting this earlier.