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.openpublishing.redirection.azure-monitor.json

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"redirect_url": "/azure/azure-monitor/vm/scom-managed-instance-overview",
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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-monitor/vm/scom-managed-instance-overview.md",
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"redirect_url": "/azure/azure-monitor/scom-manage-instance/overview",
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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-monitor/best-practices.md",
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"redirect_url": "/azure/azure-monitor/getting-started",
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"source_path_from_root": "/articles/azure-monitor/essentials/pipeline-overview.md",
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"redirect_url": "/azure/azure-monitor/essentials/data-collection-rule-overview",
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"redirect_document_id": false
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}
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},
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{
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"source_path_from_root": "/articles/azure-monitor/agents/azure-monitor-agent-migration-tools.md",
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"redirect_url": "/azure/azure-monitor/agents/azure-monitor-agent-migration",
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"redirect_document_id": false
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}
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]
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}

.openpublishing.redirection.json

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"redirect_url": "/sql/sql-server/stretch-database/stretch-database-databases-and-tables-stretch-database-advisor",
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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/dms/tutorial-azure-postgresql-to-azure-postgresql-online-portal.md",
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"redirect_url": "/azure/postgresql/migrate/migration-service/tutorial-migration-service-single-to-flexible",
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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/vs-azure-tools-access-private-azure-clouds-with-visual-studio.md",
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"redirect_url": "/visualstudio/azure/vs-azure-tools-access-private-azure-clouds-with-visual-studio",
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"redirect_document_id": false
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{
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"source_path_from_root": "/articles/data-factory/continuous-integration-delivery-automate-github-actions.md",
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"source_path_from_root": "/articles/openshift/tutorial-create-cluster.md",
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"redirect_url": "/azure/openshift/create-cluster",
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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/openshift/tutorial-connect-cluster.md",
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"redirect_url": "/azure/openshift/connect-cluster",
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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/openshift/tutorial-delete-cluster.md",
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"redirect_url": "/azure/openshift/delete-cluster",
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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/openshift/quickstart-portal.md",
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"redirect_url": "/azure/openshift/create-cluster",
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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/data-factory/continuous-integration-delivery-automate-github-actions.md",
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"redirect_url": "/azure",
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"redirect_document_id": false
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articles/ai-services/computer-vision/overview-image-analysis.md

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| Japan East || | || |
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### Query rates
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tbd
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## Data privacy and security
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As with all of the Azure AI services, developers using the Azure AI Vision service should be aware of Microsoft's policies on customer data. See the [Azure AI services page](https://www.microsoft.com/trustcenter/cloudservices/cognitiveservices) on the Microsoft Trust Center to learn more.

articles/ai-services/openai/how-to/gpt-with-vision.md

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> [!IMPORTANT]
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> Remember to set a `"max_tokens"` value, or the return output will be cut off.
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> [!IMPORTANT]
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> When uploading images, there is a limit of 10 images per chat request.
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```json
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{
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"messages": [

articles/ai-services/openai/how-to/quota.md

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manager: nitinme
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ms.service: azure-ai-openai
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ms.topic: how-to
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ms.date: 05/31/2024
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ms.date: 06/18/2024
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As requests come into the deployment endpoint, the estimated max-processed-token count is added to a running token count of all requests that is reset each minute. If at any time during that minute, the TPM rate limit value is reached, then further requests will receive a 429 response code until the counter resets.
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> [!IMPORTANT]
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> The token count used in the rate limit calculation is an estimate based in part on the character count of the API request. The rate limit token estimate is not the same as the token calculation that is used for billing/determining that a request is below a model's input token limit. Due to the approximate nature of the rate limit token calculation, it is expected behavior that a rate limit can be triggered prior to what might be expected in comparison to an exact token count measurement for each request.
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RPM rate limits are based on the number of requests received over time. The rate limit expects that requests be evenly distributed over a one-minute period. If this average flow isn't maintained, then requests may receive a 429 response even though the limit isn't met when measured over the course of a minute. To implement this behavior, Azure OpenAI Service evaluates the rate of incoming requests over a small period of time, typically 1 or 10 seconds. If the number of requests received during that time exceeds what would be expected at the set RPM limit, then new requests will receive a 429 response code until the next evaluation period. For example, if Azure OpenAI is monitoring request rate on 1-second intervals, then rate limiting will occur for a 600-RPM deployment if more than 10 requests are received during each 1-second period (600 requests per minute = 10 requests per second).
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### Rate limit best practices

articles/ai-services/openai/how-to/working-with-models.md

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description: Learn about managing model deployment life cycle, updates, & retirement.
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ms.topic: conceptual
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ms.date: 10/04/2023
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ms.date: 06/18/2023
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ms.custom: references_regions, build-2023, build-2023-dataai, devx-track-azurepowershell
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author: mrbullwinkle #ChrisHMSFT
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|`NoAutoUpgrade` | The model deployment never automatically upgrades. Once the retirement date is reached the model deployment stops working. You need to update your code referencing that deployment to point to a nonexpired model deployment. |
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> [!NOTE]
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> `null` is equivalent to `AutoUpgradeWhenExpired`. If the **Version update policy** option is not present in the properties for a model that supports model upgrades this indicates the value is currently `null`. Once you explicitly modify this value, the property is visible in the studio properties page as well as via the REST API.
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> `null` is equivalent to `OnceCurrentVersionExpired`. If the **Version update policy** option is not present in the properties for a model that supports model upgrades this indicates the value is currently `null`. Once you explicitly modify this value, the property is visible in the studio properties page as well as via the REST API.
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### Examples
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articles/ai-services/openai/includes/model-matrix/provisioned-models.md

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| **Region** | **gpt-4**, **0613** | **gpt-4**, **1106-Preview** | **gpt-4**, **0125-Preview** | **gpt-4**, **turbo-2024-04-09** | **gpt-4o**, **2024-05-13** | **gpt-4-32k**, **0613** | **gpt-35-turbo**, **1106** | **gpt-35-turbo**, **0125** |
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|:-------------------|:-------------------:|:---------------------------:|:---------------------------:|:-------------------------------:|:--------------------------:|:-----------------------:|:--------------------------:|:--------------------------:|
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| australiaeast ||||| - ||||
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| australiaeast ||||| ||||
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| brazilsouth |||| - | - ||| - |
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| canadacentral || - | - | - | - || - ||
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| canadaeast ||| - || - | - || - |
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| canadaeast ||| - || | - || - |
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articles/ai-services/openai/whats-new.md

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---
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* GPT-4o is now also available in:
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- Japan East, Korea Central, Sweden Central, Switzerland North, & West US 3 for provisioned deployment.
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- Australia East, Canada East, Japan East, Korea Central, Sweden Central, Switzerland North, & West US 3 for provisioned deployment.
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For the latest information on model availability, see the [models page](./concepts/models.md).
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articles/ai-services/speech-service/includes/how-to/professional-voice/train-voice/speech-studio.md

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:::image type="content" source="../../../../media/custom-voice/cnv-train-neural.png" alt-text="Screenshot that shows how to select neural training.":::
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1. Select a version of the training recipe for your model. The latest version is selected by default. The supported features and training time can vary by version. Normally, we recommend the latest version. In some cases, you can choose an earlier version to reduce training time. See [Bilingual training](#bilingual-training) for more information about bilingual training and differences between locales.
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> [!NOTE]
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> Model versions `V2.2021.07`, `V4.2021.10`, `V5.2022.05`, `V6.2022.11`, and `V9.2023.10` will be retired by October 1, 2024. The voice models already created on these retired versions won't be affected.
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1. Select the data that you want to use for training. Duplicate audio names are removed from the training. Make sure that the data you select doesn't contain the same audio names across multiple *.zip* files.
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You can select only successfully processed datasets for training. If you don't see your training set in the list, check your data processing status.

articles/ai-services/speech-service/regions.md

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| ------------- | -------------------- | --------------------------------------- |
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| Africa | South Africa North | `southafricanorth` <sup>6</sup> |
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| Asia Pacific | East Asia | `eastasia` <sup>5</sup> |
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| Asia Pacific | Southeast Asia | `southeastasia` <sup>1,2,4,5,7,9</sup> |
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| Asia Pacific | Southeast Asia | `southeastasia` <sup>1,2,4,5,7,9,10</sup> |
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| Asia Pacific | Australia East | `australiaeast` <sup>1,2,4,7</sup> |
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| Asia Pacific | Central India | `centralindia` <sup>1,2,4,5</sup> |
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| Asia Pacific | Japan East | `japaneast` <sup>2,5</sup> |
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| Asia Pacific | Japan West | `japanwest` <sup>3</sup> |
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| Asia Pacific | Korea Central | `koreacentral` <sup>2</sup> |
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| Canada | Canada Central | `canadacentral` <sup>1</sup> |
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| Europe | North Europe | `northeurope` <sup>1,2,4,5,7</sup> |
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| Europe | West Europe | `westeurope` <sup>1,2,4,5,7,9</sup> |
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| Europe | West Europe | `westeurope` <sup>1,2,4,5,7,9,10</sup> |
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| South America | Brazil South | `brazilsouth` <sup>6</sup> |
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| US | Central US | `centralus` |
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| US | East US | `eastus` <sup>1,2,4,5,7,9</sup> |
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| US | East US | `eastus` <sup>1,2,4,5,7,9,11</sup> |
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| US | East US 2 | `eastus2` <sup>1,2,4,5</sup> |
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| US | North Central US | `northcentralus` <sup>4,6</sup> |
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| US | South Central US | `southcentralus` <sup>1,2,4,5,6,7</sup> |
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| US | West Central US | `westcentralus` <sup>3,5</sup> |
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| US | West US 2 | `westus2` <sup>1,2,4,5,7,10</sup> |
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<sup>1</sup> The region has dedicated hardware for custom speech training. If you plan to train a custom model with audio data, use one of the regions with dedicated hardware for faster training. Then you can [copy the trained model](how-to-custom-speech-train-model.md#copy-a-model) to another region.
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<sup>9</sup> The region supports personal voice.
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<sup>10</sup> The region supports text to speech avatar.
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<sup>11</sup> The region supports video translation.
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## Intent recognition
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Available regions for intent recognition via the Speech SDK are in the following table.

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