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@@ -144,7 +144,7 @@ If you already have existing Azure resources, you can re-use those by setting `a
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1. Run `azd env set AZURE_SEARCH_SERVICE_RESOURCE_GROUP {Name of existing resource group with ACS service}`
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1. If that resource group is in a different location than the one you'll pick for the `azd up` step,
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then run `azd env set AZURE_SEARCH_SERVICE_LOCATION {Location of existing service}`
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1. If the search service's SKU is not standard, then run `azd env set AZURE_SEARCH_SERVICE_SKU {Name of SKU}`. ([See possible values](https://learn.microsoft.com/en-us/azure/templates/microsoft.search/searchservices?pivots=deployment-language-bicep#sku))
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1. If the search service's SKU is not standard, then run `azd env set AZURE_SEARCH_SERVICE_SKU {Name of SKU}`. ([See possible values](https://learn.microsoft.com/azure/templates/microsoft.search/searchservices?pivots=deployment-language-bicep#sku))
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#### Other existing Azure resources
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@@ -320,6 +320,24 @@ The primary differences:
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* This repository includes multiple RAG (retrieval-augmented generation) approaches that chain the results of multiple API calls (to Azure OpenAI and ACS) together in different ways. The other repository uses only the built-in data sources option for the ChatCompletions API, which uses a RAG approach on the specified ACS index. That should work for most uses, but if you needed more flexibility, this sample may be a better option.
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* This repository is also a bit more experimental in other ways, since it's not tied to the Azure OpenAI Studio like the other repository.
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