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Merge pull request #280554 from MicrosoftDocs/main
7/10/2024 PM Publish
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.openpublishing.redirection.app-service.json

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"redirect_url": "/azure/app-service/scripts/powershell-scale-manual",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/app-service/get-resource-events.md",
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"redirect_url": "/azure/app-service/monitor-app-service",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/app-service/overview-monitoring.md",
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"redirect_url": "/azure/app-service/monitor-app-service",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/app-service/app-service-security-attributes.md",
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"redirect_url": "/azure/app-service/security-baseline",

.openpublishing.redirection.json

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"source_path_from_root": "/articles/azure-maps/tutorial-creator-feature-stateset.md",
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"redirect_url": "/azure/azure-maps/how-to-creator-feature-stateset",
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"redirect_url": "/azure/azure-maps/about-creator",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/azure-maps/schema-stateset-stylesobject.md",
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"redirect_url": "/azure/azure-maps/about-creator",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/azure-maps/indoor-map-dynamic-styling.md",
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"redirect_url": "/azure/azure-maps/about-creator",
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"redirect_document_id": false
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{
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"source_path_from_root": "/articles/azure-maps/how-to-creator-feature-stateset.md",
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"redirect_url": "/azure/azure-maps/about-creator",
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articles/ai-services/document-intelligence/faq.yml

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- You can find more details in the [technical community blog](https://techcommunity.microsoft.com/t5/azure-ai-services-blog/document-generative-ai-the-power-of-azure-ai-document/ba-p/3875015).
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- question: |
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Does Document Intelligence offer a semantic chunking solution for retrieval-augmented generation?
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Can Document Intelligence help with semantic chunking within documents for retrieval-augmented generation?
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answer: |
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**Yes.**
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Semantic chunking is a key step in retrieval-augmented generation (RAG) to ensure its efficient storage and retrieval.
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Document Intelligence can provide the building blocks to enable semantic chunking. Semantic chunking is a key step in retrieval-augmented generation (RAG) to ensure its efficient storage and retrieval.
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- Document Intelligence provides a layout model that segments documents into coherent units based on their semantic content.
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articles/ai-services/openai/includes/api-surface.md

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| API | Latest preview release | Latest GA release | Specifications | Description |
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|:---|:----|:----|:----|:---|
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| **Control plane** | `2024-04-01-preview` | [`2023-05-01`](/rest/api/aiservices/accountmanagement/deployments/create-or-update?view=rest-aiservices-accountmanagement-2023-05-01&tabs=HTTP&preserve-view=true) | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/resource-manager/Microsoft.CognitiveServices) | Azure OpenAI shares a common control plane with all other Azure AI Services. The control plane API is used for things like [creating Azure OpenAI resources](/rest/api/aiservices/accountmanagement/accounts/create?view=rest-aiservices-accountmanagement-2023-05-01&tabs=HTTP&preserve-view=true), [model deployment](/rest/api/aiservices/accountmanagement/deployments/create-or-update?view=rest-aiservices-accountmanagement-2023-05-01&tabs=HTTP&preserve-view=true), and other higher level resource management tasks. The control plane also governs what is possible to do with capabilities like Azure Resource Manager, Bicep, Terraform, and Azure CLI.|
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| **Data plane - authoring** | `2024-05-01-preview` | `2024-06-01` | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/data-plane/AzureOpenAI/authoring) | The data plane authoring API controls [fine-tuning](/rest/api/azureopenai/fine-tuning?view=rest-azureopenai-2024-05-01-preview&preserve-view=true), [file-upload](/rest/api/azureopenai/files/upload?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true), [ingestion jobs](/rest/api/azureopenai/ingestion-jobs/create?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true), and certain [model level queries](/rest/api/azureopenai/models/get?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true)
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| **Data plane - inference** | `2024-05-01-preview` | `2024-06-01` | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference) | The data plane inference API provides the inference capabilities/endpoints for features like completions, chat completions, embeddings, speech/whisper, on your data, Dall-e, assistants, etc. |
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| **Data plane - authoring** | [`2024-05-01-preview`](/rest/api/azureopenai/operation-groups?view=rest-azureopenai-2024-05-01-preview&preserve-view=true) | [`2024-06-01`](/rest/api/azureopenai/operation-groups?view=rest-azureopenai-2024-06-01&preserve-view=true) | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/data-plane/AzureOpenAI/authoring) | The data plane authoring API controls [fine-tuning](/rest/api/azureopenai/fine-tuning?view=rest-azureopenai-2024-05-01-preview&preserve-view=true), [file-upload](/rest/api/azureopenai/files/upload?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true), [ingestion jobs](/rest/api/azureopenai/ingestion-jobs/create?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true), and certain [model level queries](/rest/api/azureopenai/models/get?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true)
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| **Data plane - inference** | [`2024-05-01-preview`](/azure/ai-services/openai/reference-preview#data-plane-inference) | [`2024-06-01`](/azure/ai-services/openai/reference#data-plane-inference) | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference) | The data plane inference API provides the inference capabilities/endpoints for features like completions, chat completions, embeddings, speech/whisper, on your data, Dall-e, assistants, etc. |
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## Authentication
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articles/ai-services/speech-service/how-to-configure-azure-ad-auth.md

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::: zone-end
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::: zone pivot="programming-language-python"
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To get a Microsoft Entra access token in Java, use the [Azure Identity Client Library](/python/api/overview/azure/identity-readme).
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To get a Microsoft Entra access token in Python, use the [Azure Identity Client Library](/python/api/overview/azure/identity-readme).
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Here's an example of using Azure Identity to get a Microsoft Entra access token from an interactive browser:
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```Python

articles/aks/.openpublishing.redirection.aks.json

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{
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"source_path_from_root": "/articles/aks/concepts-clusters-workloads.md",
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"redirect_url": "/azure/aks/core-aks-concepts",
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"redirect_document_id": false
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"source_path_from_root": "/articles/aks/upgrade-windows-2019-2022.md",
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articles/aks/TOC.yml

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- name: Concepts
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items:
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- name: Core concepts
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href: concepts-clusters-workloads.md
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href: core-aks-concepts.md
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- name: Pricing tiers for AKS
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- name: Maintain and upgrade an AKS cluster
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- name: Resource reservations
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- name: Backup and recover cluster
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- name: Observability

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