Merge pull request #703 from HeidiSteen/heidist-release

Accelerator updates

Author: JamesJBarnett

articles/search/resource-tools.md

@@ -7,20 +7,27 @@ manager: nitinme
 ms.author: heidist
 ms.service: cognitive-search
 ms.topic: conceptual
-ms.date: 10/07/2024
+ms.date: 10/08/2024
 ---
 
-# Productivity tools - Azure AI Search
+# Productivity tools and accelerators - Azure AI Search
 
 Productivity tools are built by engineers at Microsoft, but aren't part of the Azure AI Search service and aren't under Service Level Agreement (SLA). These tools are provided as source code that you can download, modify, and build to create an app that helps you develop or maintain a search solution.
 
+## Tools
+
 | Tool name | Description | Source code |
 |-----------|------------ |-------------|
 | [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)  |
-| [Azure AI Search 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) |
 | [Visual Studio Code extension](https://github.com/microsoft/vscode-azurecognitivesearch) | Although the extension is no longer available in the Visual Studio Code Marketplace, the code is open source. You can clone and modify the tool for your own use. | [https://github.com/microsoft/vscode-azurecognitivesearch](https://github.com/microsoft/vscode-azurecognitivesearch) |
+
+## Accelerators
+
+| Accelerator | Description | Source code |
+|-----------|------------ |-------------|
+| [Build your own copilot Solution Accelerator](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator) | Code and docs to build a copilot for specific use cases.| [Client advisor](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ClientAdvisor/README.md) <br>[Generic document generator](https://github.com/microsoft/Generic-Build-your-own-copilot-Solution-Accelerator) <br>[Research assistant](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ResearchAssistant/README.md) |
+| [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) |

articles/search/retrieval-augmented-generation-overview.md

@@ -226,15 +226,17 @@ A RAG solution that includes Azure AI Search can leverage [built-in data chunkin
 
 + Start with solution accelerators:
 
-  + ["Chat with your data" solution accelerator](https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator) helps you create a custom RAG solution over your content.
+  + [Chat with your data solution accelerator](https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator)
 
-  + ["Conversational Knowledge Mining" solution accelerator](https://github.com/microsoft/Customer-Service-Conversational-Insights-with-Azure-OpenAI-Services), helps you create an interactive solution to extract actionable insights from post-contact center transcripts.
+  + [Conversational Knowledge Mining solution accelerator](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), leverages Azure OpenAI Service, Azure AI Search and Microsoft Fabric, to create custom copilot solutions.
+  + [Build your own copilot solution accelerator](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator)
 
-    + [Client Advisor](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ClientAdvisor/README.md) all-in-one custom copilot empowers Client Advisor to harness the power of generative AI across both structured and unstructured data. Help our customers to optimize daily tasks and foster better interactions with more clients
+    + [Client Advisor](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ClientAdvisor/README.md)
 
-    + [Research Assistant](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ResearchAssistant/README.md) helps build your own AI Assistant to identify relevant documents, summarize and categorize vast amounts of unstructured information, and accelerate the overall document review and content generation.
+    + [Research Assistant](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ResearchAssistant/README.md)
+
+    + [Generic copilot](https://github.com/microsoft/Generic-Build-your-own-copilot-Solution-Accelerator)
 
 + [Use enterprise chat app templates](https://aka.ms/azai) deploy Azure resources, code, and sample grounding data using fictitious health plan documents for Contoso and Northwind. This end-to-end solution gives you an operational chat app in as little as 15 minutes. Code for these templates is the **azure-search-openai-demo** featured in several presentations. The following links provide language-specific versions:
 

articles/search/samples-python.md

@@ -55,7 +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. |
+| [aisearch-openai-rag-audio](https://github.com/Azure-Samples/aisearch-openai-rag-audio) | A simple architecture for voice-based generative AI applications that enables Azure AI Search 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/search-what-is-azure-search.md

@@ -8,7 +8,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: cognitive-search
 ms.topic: overview
-ms.date: 08/15/2024
+ms.date: 10/08/2024
 ---
 
 # What's Azure AI Search?
@@ -77,6 +77,8 @@ For more information about specific functionality, see [Features of Azure AI Sea
 
 Functionality is exposed through the Azure portal, simple [REST APIs](/rest/api/searchservice/), or Azure SDKs like the [Azure SDK for .NET](search-howto-dotnet-sdk.md). The Azure portal supports service administration and content management, with tools for prototyping and querying your indexes and skillsets. 
 
+### Use the Azure portal
+
 An end-to-end exploration of core search features can be accomplished in four steps:
 
 1. [**Decide on a tier**](search-sku-tier.md) and region. One free search service is allowed per subscription. All quickstarts can be completed on the free tier. For more capacity and capabilities, you'll need a [billable tier](https://azure.microsoft.com/pricing/details/search/).
@@ -87,6 +89,8 @@ An end-to-end exploration of core search features can be accomplished in four st
 
 1. [**Finish with Search Explorer**](search-explorer.md), using a portal client to query the search index you just created.
 
+### Use APIs
+
 Alternatively, you can create, load, and query a search index in atomic steps:
 
 1. [**Create a search index**](search-what-is-an-index.md) using the portal, [REST API](/rest/api/searchservice/indexes/create), [.NET SDK](search-howto-dotnet-sdk.md), or another SDK. The index schema defines the structure of searchable content.
@@ -95,6 +99,8 @@ Alternatively, you can create, load, and query a search index in atomic steps:
 
 1. [**Query an index**](search-query-overview.md) using [Search explorer](search-explorer.md) in the portal, [REST API](search-get-started-rest.md), [.NET SDK](/dotnet/api/azure.search.documents.searchclient.search), or another SDK.
 
+### Use accelerators
+
 Or, try solution accelerators:
 
 + [**Chat with your data** solution accelerator](https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator) helps you create a custom RAG solution over your content.
@@ -103,6 +109,8 @@ Or, try solution accelerators:
 
 + [**Build your own copilot** solution accelerator](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator), leverages Azure OpenAI Service, Azure AI Search and Microsoft Fabric, to create custom copilot solutions.
 
+  + [Generic copilot](https://github.com/microsoft/Generic-Build-your-own-copilot-Solution-Accelerator) helps you build your own copilot to identify relevant documents, summarize unstructured information, and generate Word document templates using your own data.
+
   + [Client Advisor](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ClientAdvisor/README.md) all-in-one custom copilot empowers Client Advisor to harness the power of generative AI across both structured and unstructured data. Help our customers to optimize daily tasks and foster better interactions with more clients
 
   + [Research Assistant](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ResearchAssistant/README.md) helps build your own AI Assistant to identify relevant documents, summarize and categorize vast amounts of unstructured information, and accelerate the overall document review and content generation.