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articles/search/resource-tools.md

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| [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. |
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| [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. |
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| [Document knowledge mining solution accelerator](https://github.com/microsoft/Document-Knowledge-Mining-Solution-Accelerator/blob/main/README.md) | Code and docs built on Azure OpenAI in Azure AI Foundry Models and Azure AI Document Intelligence. It processes and extracts summaries, entities, and metadata from unstructured, multimodal documents to enable searching and chatting over this data. |
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| [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. |
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## Tools
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articles/search/samples-dotnet.md

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| Samples | Repository | Description |
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|---------|------------|-------------|
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| Search + QnA Maker Accelerator | [search-qna-maker-accelerator](https://github.com/Azure-Samples/search-qna-maker-accelerator)| A [solution](https://techcommunity.microsoft.com/t5/azure-ai/qna-with-azure-cognitive-search/ba-p/2081381) combining the power of Search and QnA Maker. See the live [demo site](https://aka.ms/qnaWithAzureSearchDemo). |
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| [Knowledge Mining Solution Accelerator](/shows/ai-show/knowledge-mining-with-azure-search) | [azure-search-knowledge-mining](https://github.com/azure-samples/azure-search-knowledge-mining/tree/main/) | Includes templates, support files, and analytical reports to help you prototype an end-to-end knowledge mining solution. |
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## Demos
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articles/search/samples-python.md

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[**aisearch-openai-rag-audio**](https://github.com/Azure-Samples/aisearch-openai-rag-audio) is "voice to RAG". This sample demonstrates 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 the model and retrieval system. Backend code is written in Python, while frontend code is written in JavaScript. For an introduction, watch this [video](https://www.youtube.com/watch?v=vXJka8xZ9Ko).
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## Accelerators
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An accelerator is an end-to-end solution that includes code and documentation that you can adapt for your own implementation of a specific scenario.
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| Repository | Description |
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|------------|-------------|
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| [RAG Experiment Accelerator](https://github.com/microsoft/rag-experiment-accelerator) | Conduct experiments and evaluations using Azure AI Search and the RAG pattern. This accelerator has code for loading multiple data sources, using a variety of models, and creating a variety of search indexes and queries. |
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## Other samples
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The following samples are also published by the Azure AI Search team but aren't referenced in documentation. Associated readme files provide usage instructions.

articles/search/tutorial-skillset.md

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zone_pivot_groups: tutorial-create-skillset
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# Quickstart: Skillsets in Azure AI Search
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# Tutorial: Skillsets in Azure AI Search
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::: zone pivot="csharp"
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[!INCLUDE [C# quickstart](includes/tutorials/skillset-csharp.md)]
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[!INCLUDE [C# tutorial](includes/tutorials/skillset-csharp.md)]
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::: zone-end
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::: zone pivot="rest"
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[!INCLUDE [REST quickstart](includes/tutorials/skillset-rest.md)]
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[!INCLUDE [REST tutorial](includes/tutorials/skillset-rest.md)]
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::: zone-end

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