Merge pull request #683 from HeidiSteen/heidist-release

[azure search] CMK portal + updated resource demo/samples list

Author: Stacyrch140

articles/search/media/search-security-manage-encryption-keys/assign-key-vault-portal.png

@@ -9,7 +9,7 @@ ms.service: cognitive-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 07/29/2024
+ms.date: 10/07/2024
 ---
 
 # Demos - Azure AI Search
@@ -20,7 +20,5 @@ The Azure AI Search currently builds and hosts the following demos.
 
 | Demo name | Description | Source code |
 |-----------|------------ |-------------|
-| [Conversational Knowledge Mining](https://github.com/microsoft/Customer-Service-Conversational-Insights-with-Azure-OpenAI-Services) | Code and docs to create interactive solution to extract conversational insights from post-contact center transcripts in production environment. | [https://github.com/microsoft/Customer-Service-Conversational-Insights-with-Azure-OpenAI-Services](https://github.com/microsoft/Customer-Service-Conversational-Insights-with-Azure-OpenAI-Services) |
-| [Build your own copilot solution accelerator](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator) | Code and docs to build your own copilot to harness the power of generative AI across both structured and unstructured data for Client Advisor and Research Assistant business use case scenarios. | [https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator) |
 | [Chat with your data](https://entgptsearch.azurewebsites.net/) | An Azure web app that uses ChatGPT in Azure OpenAI with fictitious health plan data in a search index. | [https://github.com/Azure-Samples/azure-search-openai-demo/](https://github.com/Azure-Samples/azure-search-openai-demo/)  |
 | [Semantic ranking for retail](https://brave-meadow-0f59c9b1e.1.azurestaticapps.net/) | Web app for a fictitious online retailer, "Terra" | Not available |

articles/search/resource-demo-sites.md

@@ -7,7 +7,7 @@ manager: nitinme
 ms.author: heidist
 ms.service: cognitive-search
 ms.topic: conceptual
-ms.date: 07/02/2024
+ms.date: 10/07/2024
 ---
 
 # Productivity tools - Azure AI Search
@@ -16,7 +16,10 @@ Productivity tools are built by engineers at Microsoft, but aren't part of the A
 
 | Tool name | Description | Source code |
 |-----------|------------ |-------------|
-| [Back up and Restore](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore) | Download the retrievable fields of an index to your local device and then upload the index and its content to a new search service. | [https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore) |
+| [Azure AI Search Lab](https://github.com/jelledruyts/azure-ai-search-lab) | Learning and experimentation lab to try out AI-enabled search scenarios in Azure. It provides a web application front-end which uses Azure AI Search and Azure OpenAI to execute searches with a variety of options - ranging from simple keyword search, to semantic ranking, vector and hybrid search, and using generative AI to answer search queries. | [https://github.com/jelledruyts/azure-ai-search-lab](https://github.com/jelledruyts/azure-ai-search-lab)  |
+| [VoiceRAG: An Application Pattern for RAG + Voice](https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/voicerag-an-app-pattern-for-rag-voice-using-azure-ai-search-and/ba-p/4259116) | A simple architecture for voice-based generative AI applications that enables RAG on top of the real-time audio API with full-duplex audio streaming from client devices, while securely handling access to both model and retrieval system. | [https://github.com/Azure-Samples/aisearch-openai-rag-audio](https://github.com/Azure-Samples/aisearch-openai-rag-audio/blob/main/README.md) |
+| [Back up and Restore (C#)](https://github.com/Azure-Samples/azure-search-dotnet-utilities/blob/main/index-backup-restore) | Download the retrievable fields of an index to your local device and then upload the index and its content to a new search service. | [https://github.com/Azure-Samples/azure-search-dotnet-utilities/blob/main/index-backup-restore](https://github.com/Azure-Samples/azure-search-dotnet-utilities/blob/main/index-backup-restore) |
+| [Back up and Restore (Python)](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore) | Download the retrievable fields of an index to your local device and then upload the index and its content to a new search service. | [https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore) |
 | [Chat with your data solution accelerator](https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator/blob/main/README.md) |  Code and docs to create interactive search solution in production environments.  | [https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator](https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator) |
 | [Knowledge Mining Accelerator](https://github.com/Azure-Samples/azure-search-knowledge-mining/blob/main/README.md) | Code and docs to jump start a knowledge store using your data. | [https://github.com/Azure-Samples/azure-search-knowledge-mining](https://github.com/Azure-Samples/azure-search-knowledge-mining) |
 | [Performance testing solution](https://github.com/Azure-Samples/azure-search-performance-testing/blob/main/README.md) | This solution helps you load test Azure AI Search. It uses Apache JMeter as an open source load and performance testing tool and Terraform to dynamically provision and destroy the required infrastructure on Azure. | [https://github.com/Azure-Samples/azure-search-performance-testing](https://github.com/Azure-Samples/azure-search-performance-testing) |

articles/search/resource-tools.md

@@ -12,7 +12,7 @@ ms.custom:
   - devx-track-python
   - ignite-2023
 ms.topic: conceptual
-ms.date: 09/19/2024
+ms.date: 10/07/2024
 ---
 
 # Python samples for Azure AI Search
@@ -55,6 +55,7 @@ The following samples are also published by the Azure AI Search team, but aren't
 
 | Repository | Description |
 |------------|-------------|
+| [aisearch-openai-rag-audio](https://github.com/Azure-Samples/aisearch-openai-rag-audio) | A simple architecture for voice-based generative AI applications that enables RAG on top of the real-time audio API with full-duplex audio streaming from client devices, while securely handling access to both model and retrieval system. Backend code is written in Python. Frontend code is JavaScript. |
 | [azure-search-backup-and-restore.ipynb](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore) | Uses the **azure.search.documents** library in the Azure SDK for Python to make a local copy of the retrievable fields of a search index, and then push those fields to a new search index. |
 
 > [!TIP]

articles/search/samples-python.md

@@ -8,7 +8,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: cognitive-search
 ms.topic: how-to
-ms.date: 10/02/2024
+ms.date: 10/07/2024
 ms.custom:
   - references_regions
   - ignite-2023
@@ -69,8 +69,6 @@ Although double encryption is now available in all regions, support was rolled o
 
 + No support for Azure Key Vault Managed Hardware Security Model (HSM).
 
-+ No support for adding encryption keys in the Azure portal.
-
 + No cross-subscription support. Azure Key Vault and Azure AI Search must be in the same subscription.
 
 ## Key Vault tips
@@ -234,7 +232,9 @@ Wait a few minutes for the role assignment to become operational.
 
 ## Step 4: Encrypt content
 
-Encryption keys are added when you create an object. To add a customer-managed key on an index, synonym map, indexer, data source, or skillset, use the [Search REST API](/rest/api/searchservice/) or an Azure SDK to create an object that has encryption enabled. To add encryption using the Azure SDK, see the [Python example](#python-example-of-an-encryption-key-configuration) in this article.
+Encryption keys are added when you create an object. To add a customer-managed key on an index, synonym map, indexer, data source, or skillset, use the Azure portal, a [Search REST API](/rest/api/searchservice/), or an Azure SDK to create an object that has encryption enabled. To add encryption using the Azure SDK, see the [Python example](#python-example-of-an-encryption-key-configuration) in this article.
+
+### [**REST APIs**](#tab/rest)
 
 1. Call the creation APIs to specify the **encryptionKey** property:
 
@@ -291,6 +291,20 @@ None of these key vault details are considered secret and could be easily retrie
 > [!Important]
 > Encrypted content in Azure AI Search is configured to use a specific Azure Key Vault key with a specific *version*. If you change the key or version, the object must be updated to use it **before** you delete the previous one. Failing to do so renders the object unusable. You won't be able to decrypt the content if the key is lost.
 
+### [**Azure portal**](#tab/portal)
+
+When you create a new object in the Azure portal, you can specify a predefined customer-managed key in a key vault. You can enable CMK-encryption for:
+
++ Indexes
++ Data sources
++ Indexers
+
+In the Azure portal, skillsets are defined in JSON view. Use the JSON shown in the REST API examples to provide a customer-managed key on a skillset.
+
+:::image type="content" source="media/search-security-manage-encryption-keys/assign-key-vault-portal.png" alt-text="Screenshot of the encryption key page in the Azure portal.":::
+
+---
+
 ## Step 5: Test encryption
 
 To verify encryption is working, revoke the encryption key, query the index (it should be unusable), and then reinstate the encryption key.

articles/search/search-security-manage-encryption-keys.md

@@ -28,6 +28,7 @@ ms.custom:
 | [**Target filters in a hybrid search to just the vector queries**](hybrid-search-how-to-query.md#hybrid-search-with-filters-targeting-vector-subqueries-preview) | Feature | A filter on a hybrid query involves all subqueries on the request, regardless of type. You can override the global filter to scope the filter to a specific subquery. The new `filterOverride` parameter is available on hybrid queries using the [2024-09-01-preview](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-09-01-preview&preserve-view=true). |
 | [**Text Split skill (token chunking)**](cognitive-search-skill-textsplit.md) | Applied AI (skills) | This skill has new parameters that improve data chunking for embedding models. A new `unit` parameter lets you specify token chunking. You can now chunk by token length, setting the length to a value that makes sense for your embedding model. You can also specify the tokenizer and any tokens that shouldn't be split during data chunking. The new `unit` parameter and query subscore definitions are found in the [2024-09-01-preview](/rest/api/searchservice/skillsets/create-or-update?view=rest-searchservice-2024-09-01-preview&preserve-view=true). |
 | [**2024-09-01-preview**](/rest/api/searchservice/search-service-api-versions?view=rest-searchservice-2024-09-01-preview&preserve-view=true) | API | Preview release of REST APIs for truncated dimensions in text-embedding-3 models, targeted vector filtering for hybrid queries, RRF subscore details for debugging, and token chunking for Text Split skill.|
+| [**Portal support for customer-managed key encryption (CMK)**](search-security-manage-encryption-keys.md#step-4-encrypt-content) | Feature | When you create new objects in the Azure portal, you can now specify CMK-encryption and select an Azure Key Vault to provide the key. |
 
 ## August 2024