Merge pull request #282144 from HeidiSteen/main

[azure search] Add accelerators

Author: prmerger-automator[bot]

articles/search/resource-demo-sites.md

@@ -9,7 +9,7 @@ ms.service: cognitive-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 07/22/2024
+ms.date: 07/29/2024
 ---
 
 # Demos - Azure AI Search
@@ -20,5 +20,7 @@ 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 AI Assistant](https://github.com/microsoft/Build-your-own-AI-Assistant-Solution-Accelerator) | Code and docs to build your own AI Assistant to accelerates the overall document review and content generation process in production environment. | [https://github.com/microsoft/Build-your-own-AI-Assistant-Solution-Accelerator](https://github.com/microsoft/Build-your-own-AI-Assistant-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/retrieval-augmented-generation-overview.md

@@ -10,7 +10,7 @@ ms.service: cognitive-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 04/22/2024
+ms.date: 07/29/2024
 ---
 
 # Retrieval Augmented Generation (RAG) in Azure AI Search
@@ -239,17 +239,21 @@ print("\n-------------------\nPrompt:\n" + prompt)
 
 + [Use Azure OpenAI Studio and "bring your own data"](/azure/ai-services/openai/concepts/use-your-data) to experiment with prompts on an existing search index in a playground. This step helps you decide what model to use, and shows you how well your existing index works in a RAG scenario.
 
-+ ["Chat with your data" solution accelerator](https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator), built by the Azure AI Search team, helps you create your own custom RAG solution.
++ [Try this quickstart](search-get-started-rag.md) for a demonstration of query integration with chat models over a search index.
 
-+ [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:
++ 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.
+  + ["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.
+  + ["Build Your Own AI Assistant" solution accelerator](https://github.com/microsoft/Build-your-own-AI-Assistant-Solution-Accelerator), 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.
+
++ [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:
 
   + [.NET](https://aka.ms/azai/net)
   + [Python](https://aka.ms/azai/py)
   + [JavaScript](https://aka.ms/azai/js)
   + [Java](https://aka.ms/azai/javat)
 
-<!-- + For another helpful demo, here's [AOAISearchDemo](https://github.com/Azure-Samples/openai/blob/main/End_to_end_Solutions/AOAISearchDemo/README.md) from the Azure OpenAI team. This demo uses an unstructured .pdf data consisting of publicly available documentation on Microsoft Surface devices. -->
-
 + [Review indexing concepts and strategies](search-what-is-an-index.md) to determine how you want to ingest and refresh data. Decide whether to use vector search, keyword search, or hybrid search. The kind of content you need to search over, and the type of queries you want to run, determines index design.
 
 + [Review creating queries](search-query-create.md) to learn more search request syntax and requirements.

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: 07/09/2024
+ms.date: 07/29/2024
 ---
 
 # What's Azure AI Search?
@@ -90,6 +90,14 @@ 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.
 
+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.
+
++ [**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.
+
++ [**Build Your Own AI Assistant** solution accelerator](https://github.com/microsoft/Build-your-own-AI-Assistant-Solution-Accelerator), 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.
+
 > [!TIP]
 > For help with complex or custom solutions, [**contact a partner**](resource-partners-knowledge-mining.md) with deep expertise in Azure AI Search technology.
 

articles/search/whats-new.md

@@ -7,7 +7,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: cognitive-search
 ms.topic: overview
-ms.date: 06/14/2024
+ms.date: 07/29/2024
 ms.custom:
   - references_regions
 ---
@@ -19,6 +19,14 @@ ms.custom:
 > [!NOTE]
 > Preview features are announced here, but we also maintain a [preview features list](search-api-preview.md) so you can find them in one place.
 
+## July 2024
+
+| Item                         | Type |  Description |
+|-----------------------------|------|--------------|
+[Chat with your data](https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator) | Accelerator| A solution accelerator for the RAG pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to create conversational search experiences. The code with sample data is available for use case scenarios such as financial advisor and contract review and summarization.|
+[Conversational Knowledge Mining](https://github.com/microsoft/Customer-Service-Conversational-Insights-with-Azure-OpenAI-Services) | Accelerator|	A solution accelerator built on top of Azure AI Search, Azure Speech and Azure OpenAI services that allows customers to extract actionable insights from post-contact center conversations. |
+[Build Your Own AI Assistant](https://github.com/microsoft/Build-your-own-AI-Assistant-Solution-Accelerator) | Accelerator| A solution built on Azure Open AI Service, Azure AI Search and Microsoft Fabric, to identify relevant documents, summarize and categorize vast amounts of unstructured information, and accelerate the overall document review and content generation process. |
+
 ## June 2024
 
 | Item                         | Type |  Description |