Updated resource demo/samples list

Author: HeidiSteen

articles/search/media/tutorial-rag-solution/scalar-vector-index.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]