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articles/ai-services/containers/azure-kubernetes-recipe.md

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ms.service: azure-ai-language
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ms.topic: conceptual
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ms.date: 01/10/2022
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ms.date: 02/26/2024
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ms.author: aahi
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ms.custom: devx-track-azurecli
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articles/ai-services/language-service/whats-new.md

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ms.date: 01/31/2024
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ms.date: 02/26/2024
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---
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articles/ai-services/openai/concepts/use-your-data.md

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ms.topic: quickstart
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ms.date: 01/09/2023
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ms.date: 02/26/2024
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recommendations: false
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ms.custom: references_regions
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---
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In this example, the fields mapped to **Content data** and **Title** provide information to the model to answer questions. **Title** is also used to title citation text. The field mapped to **File name** generates the citation names in the response.
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Mapping these fields correctly helps ensure the model has better response and citation quality. You can additionally configure this [in the API](../reference.md#completions-extensions) using the `fieldsMapping` parameter.
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Mapping these fields correctly helps ensure the model has better response and citation quality. You can additionally configure this [in the API](../references/on-your-data.md) using the `fieldsMapping` parameter.
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### Search filter (API)
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If you want to implement additional value-based criteria for query execution, you can set up a search filter using the `filter` parameter in the [REST API](../references/azure-search.md).
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# [Azure Cosmos DB for MongoDB vCore](#tab/mongo-db)
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Data is ingested into Azure AI search using the following process:
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1. Ingestion assets are created in Azure AI Search resource and Azure storage account. Currently these assets are: indexers, indexes, data sources, a [custom skill](/azure/search/cognitive-search-custom-skill-interface) in the search resource, and a container (later called the chunks container) in the Azure storage account. You can specify the input Azure storage container using the [Azure OpenAI studio](https://oai.azure.com/), or the [ingestion API (preview)](../reference.md#start-an-ingestion-job-preview).
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1. Ingestion assets are created in Azure AI Search resource and Azure storage account. Currently these assets are: indexers, indexes, data sources, a [custom skill](/azure/search/cognitive-search-custom-skill-interface) in the search resource, and a container (later called the chunks container) in the Azure storage account. You can specify the input Azure storage container using the [Azure OpenAI studio](https://oai.azure.com/), or the [ingestion API (preview)](/rest/api/azureopenai/ingestion-jobs).
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2. Data is read from the input container, contents are opened and chunked into small chunks with a maximum of 1,024 tokens each. If vector search is enabled, the service calculates the vector representing the embeddings on each chunk. The output of this step (called the "preprocessed" or "chunked" data) is stored in the chunks container created in the previous step.
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### Runtime parameters
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You can modify the following additional settings in the **Data parameters** section in Azure OpenAI Studio and [the API](../reference.md#completions-extensions). You don't need to reingest your data when you update these parameters.
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You can modify the following additional settings in the **Data parameters** section in Azure OpenAI Studio and [the API](../references/on-your-data.md). You don't need to reingest your data when you update these parameters.
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|Parameter name | Description |
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You can define a system message to steer the model's reply when using Azure OpenAI On Your Data. This message allows you to customize your replies on top of the retrieval augmented generation (RAG) pattern that Azure OpenAI On Your Data uses. The system message is used in addition to an internal base prompt to provide the experience. To support this, we truncate the system message after a specific [number of tokens](#token-usage-estimation-for-azure-openai-on-your-data) to ensure the model can answer questions using your data. If you are defining extra behavior on top of the default experience, ensure that your system prompt is detailed and explains the exact expected customization.
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Once you select add your dataset, you can use the **System message** section in the Azure OpenAI Studio, or the `roleInformation` [parameter in the API](../reference.md#completions-extensions).
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Once you select add your dataset, you can use the **System message** section in the Azure OpenAI Studio, or the `roleInformation` [parameter in the API](../references/on-your-data.md).
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:::image type="content" source="../media/use-your-data/system-message.png" alt-text="A screenshot showing the system message option in Azure OpenAI Studio." lightbox="../media/use-your-data/system-message.png":::
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articles/ai-services/openai/toc.yml

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href: ./references/elasticsearch.md
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- name: Data source - Pinecone
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href: ./references/pinecone.md
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- name: Ingestion API (preview)
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href: /rest/api/azureopenai/ingestion-jobs
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- name: Azure Resource Manager/Bicep/Terraform
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href: /azure/templates/microsoft.cognitiveservices/accounts?pivots=deployment-language-bicep
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displayName: ARM, ARM template, template

articles/aks/azure-cni-overview.md

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* [Use an internal load balancer with Azure Kubernetes Service (AKS)](internal-lb.md)
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* [Create a basic ingress controller with external network connectivity][aks-ingress-basic]
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* [Enable the HTTP application routing add-on][aks-http-app-routing]
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* [Create an ingress controller that uses an internal, private network and IP address][aks-ingress-internal]
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* [Create an ingress controller with a dynamic public IP and configure Let's Encrypt to automatically generate TLS certificates][aks-ingress-tls]
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* [Create an ingress controller with a static public IP and configure Let's Encrypt to automatically generate TLS certificates][aks-ingress-static-tls]
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* [Use the application routing addon in Azure Kubernetes Service (AKS)](app-routing.md)
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<!-- IMAGES -->
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[advanced-networking-diagram-01]: ./media/networking-overview/advanced-networking-diagram-01.png
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[ManagedClusterAgentPoolProfile]: /azure/templates/microsoft.containerservice/managedclusters#managedclusteragentpoolprofile-object
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[aks-network-concepts]: concepts-network.md
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[aks-network-nsg]: concepts-network.md#network-security-groups
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[aks-ingress-basic]: ingress-basic.md
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[aks-ingress-tls]: ingress-tls.md
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[aks-ingress-static-tls]: ingress-static-ip.md
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[aks-http-app-routing]: http-application-routing.md
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[aks-ingress-internal]: ingress-internal-ip.md
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[az-extension-add]: /cli/azure/extension#az_extension_add
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[az-extension-update]: /cli/azure/extension#az_extension_update
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[az-feature-register]: /cli/azure/feature#az_feature_register

articles/aks/configure-azure-cni-dynamic-ip-allocation.md

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* [Use a static IP address with the Azure Kubernetes Service (AKS) load balancer](static-ip.md)
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* [Use an internal load balancer with Azure Kubernetes Service (AKS)](internal-lb.md)
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* [Create a basic ingress controller with external network connectivity][aks-ingress-basic]
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* [Enable the HTTP application routing add-on][aks-http-app-routing]
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* [Create an ingress controller that uses an internal, private network and IP address][aks-ingress-internal]
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* [Create an ingress controller with a dynamic public IP and configure Let's Encrypt to automatically generate TLS certificates][aks-ingress-tls]
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* [Create an ingress controller with a static public IP and configure Let's Encrypt to automatically generate TLS certificates][aks-ingress-static-tls]
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* [Use the application routing addon in Azure Kubernetes Service (AKS)](app-routing.md)
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<!-- LINKS - External -->
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[github]: https://raw.githubusercontent.com/microsoft/Docker-Provider/ci_prod/kubernetes/container-azm-ms-agentconfig.yaml
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<!-- LINKS - Internal -->
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[aks-ingress-basic]: ingress-basic.md
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[aks-ingress-tls]: ingress-tls.md
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[aks-ingress-static-tls]: ingress-static-ip.md
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[aks-http-app-routing]: http-application-routing.md
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[aks-ingress-internal]: ingress-internal-ip.md
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[azure-cni-prereq]: ./configure-azure-cni.md#prerequisites
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[azure-cni-deployment-parameters]: ./azure-cni-overview.md#deployment-parameters
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[az-aks-enable-addons]: /cli/azure/aks#az_aks_enable_addons

articles/aks/integrations.md

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| azure-policy | Use Azure Policy for AKS, which enables at-scale enforcements and safeguards on your clusters in a centralized, consistent manner. | [Understand Azure Policy for Kubernetes clusters][azure-policy-aks] | [GitHub][azure-policy-repo] |
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| azure-keyvault-secrets-provider | Use Azure Keyvault Secrets Provider addon.| [Use the Azure Key Vault Provider for Secrets Store CSI Driver in an AKS cluster][keyvault-secret-provider] | [GitHub][keyvault-secret-provider-repo] |
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| virtual-node | Use virtual nodes with your AKS cluster. | [Use virtual nodes][virtual-nodes] | [GitHub][virtual-nodes-oss-repo] |
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| http_application_routing | Configure ingress with automatic public DNS name creation for your AKS cluster (retired). | [HTTP application routing add-on on Azure Kubernetes Service (AKS) (retired)][http-app-routing] | [GitHub][app-routing-repo] |
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| open-service-mesh | Use Open Service Mesh with your AKS cluster (retired). | [Open Service Mesh AKS add-on (retired)][osm] | [GitHub][osm-repo] |
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## Extensions
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<!-- LINKS -->
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[container-insights]: ../azure-monitor/containers/container-insights-overview.md
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articles/aks/intro-kubernetes.md

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For more information, see the [Network concepts for applications in AKS][aks-networking].
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### Ingress with HTTP application routing
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### Ingress with application routing add-on
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The HTTP application routing add-on helps you easily access applications deployed to your AKS cluster. When enabled, the HTTP application routing solution configures an ingress controller in your AKS cluster.
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The application routing addon is the recommended way to configure an Ingress controller in AKS. The application routing addon is a fully managed, ingress controller for Azure Kubernetes Service (AKS) that provides the following features:
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* Easy configuration of managed NGINX Ingress controllers based on Kubernetes NGINX Ingress controller.
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* Integration with Azure DNS for public and private zone management.
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articles/aks/operator-best-practices-network.md

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Ingress controllers must be scheduled on a Linux node. Indicate that the resource should run on a Linux-based node using a node selector in your YAML manifest or Helm chart deployment. For more information, see [Use node selectors to control where pods are scheduled in AKS][concepts-node-selectors].
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## Ingress with the application routing addon
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There are many scenarios for ingress, including the following how-to guides:
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* [Create a basic ingress controller with external network connectivity][aks-ingress-basic]
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* [Create an ingress controller that uses an internal, private network and IP address][aks-ingress-internal]
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* [Create an ingress controller that uses your own TLS certificates][aks-ingress-own-tls]
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* Create an ingress controller that uses Let's Encrypt to automatically generate TLS certificates [with a dynamic public IP address][aks-ingress-tls] or [with a static public IP address][aks-ingress-static-tls]
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* Easy configuration of managed NGINX Ingress controllers based on Kubernetes NGINX Ingress controller.
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* Integration with Azure DNS for public and private zone management.
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[sp-delegation]: kubernetes-service-principal.md#delegate-access-to-other-azure-resources
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articles/aks/static-ip.md

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## Next steps
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<!-- LINKS - External -->
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[kubectl-describe]: https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#describe

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