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‎articles/ai-foundry/how-to/develop/get-started-projects-vs-code.md

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ms.service: azure-ai-foundry
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content_well_notification:
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- AI-contribution
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ai-usage: ai-assisted
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ms.topic: how-to
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ms.date: 04/28/2025
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ms.date: 05/07/2025
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ms.reviewer: erichen
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ms.author: johalexander
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author: ms-johnalex
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With the Azure AI Foundry for Visual Studio Code extension, you can accomplish much of this workflow directly from Visual Studio Code. It also comes with other features, such as code templates, playgrounds, and integration with other VS Code extensions and features.
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This article shoes you how to quickly get started using the features of the Azure AI Foundry for Visual Studio Code extension.
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This article shows you how to quickly get started using the features of the Azure AI Foundry for Visual Studio Code extension.
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[!INCLUDE [feature-preview](../../includes/feature-preview.md)]
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The Azure resources that you created in this article are billed to your Azure subscription. If you don't expect to need these resources in the future, delete them to avoid incurring more charges.
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### Delete your agents
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1. In the VS Code navbar, refresh the **Azure AI Foundry Extension**. In the **Resources** section, expand the **Agents** subsection to display the list of deployed agents.
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1. Right-click on your deployed agent to delete and select the **Delete** option.
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:::image type="content" source="../../media/how-to/get-started-projects-vs-code/delete-agent.png" alt-text="Screenshot of the AI Foundry portal with 'Agents' from the navigation menu on the left and the **Delete** button highlighted." lightbox="../../media/how-to/get-started-projects-vs-code/delete-agent.png":::
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### Delete your models
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1. In the VS Code navbar, refresh the **Azure AI Foundry Extension**. In the **Resources** section, expand the **Models** subsection to display the list of deployed models.

‎articles/ai-foundry/how-to/develop/vs-code-agents.md

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ms.service: azure-ai-foundry
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content_well_notification:
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- AI-contribution
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ai-usage: ai-assisted
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ms.topic: how-to
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ms.date: 04/29/2025
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ms.date: 05/07/2025
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ms.reviewer: erichen
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ms.author: johalexander
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author: ms-johnalex
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### Add tools to the Azure AI Agent
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Azure AI Agent Service has a set of knowledge and action tools that you can use to interact with your data sources, such as:
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- [Grounding with Bing search](/azure/ai-services/agents/how-to/tools/bing-grounding?tabs=python&pivots=overview)
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- [Azure AI Search](/azure/ai-services/agents/how-to/tools/file-search?tabs=python&pivots=overview)
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- [Azure Functions](/azure/ai-services/agents/how-to/tools/file-search?tabs=python&pivots=overview)
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- [File retrieval](/azure/ai-services/agents/how-to/tools/azure-functions?tabs=python&pivots=overview)
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Azure AI Agent Service has a set of knowledge and action tools that you can use to interact with your data sources.
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#### Available tools for Azure AI Agents
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The following tools are available:
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- Knowledge tools:
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- [Grounding with Bing search](/azure/ai-services/agents/how-to/tools/bing-grounding?tabs=python&pivots=overview)
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- [File search]( /azure/ai-services/agents/how-to/tools/file-search?tabs=python&pivots=overview)
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- [Azure AI Search](/azure/ai-services/agents/how-to/tools/azure-ai-search?tabs=azurecli%2Cpython&pivots=overview-azure-ai-search)
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- [Microsoft Fabric](/azure/ai-services/agents/how-to/tools/fabric?tabs=csharp&pivots=overview)
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- [Use licensed data](/azure/ai-services/agents/how-to/tools/licensed-data)
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- Action tools:
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- [Azure AI Agents function calling](/azure/ai-services/agents/how-to/tools/function-calling?tabs=python&pivots=overview)
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- [Code interpreter](/azure/ai-services/agents/how-to/tools/code-interpreter?tabs=python&pivots=overview)
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- [OpenAPI Specified tools](/azure/ai-services/agents/how-to/tools/openapi-spec?tabs=python&pivots=overview)
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- [Azure Functions](/azure/ai-services/agents/how-to/tools/azure-functions?tabs=python&pivots=overview)
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#### Configure the tools YAML file
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The Agent Designer adds tools to an AI Agent via .yaml files.
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Create a tool configuration .yaml file using the following steps:
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1. Perform any setup steps that might be required. See the article for the tool you’re interested in using. For example, [Grounding with Bing search](/azure/ai-services/agents/how-to/tools/bing-grounding?tabs=python&pivots=overview#setup).
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1. Choose a tool from the [available tools for Azure AI Agents](#available-tools-for-azure-ai-agents). Perform any setup steps that might be required. For example, [Grounding with Bing search](/azure/ai-services/agents/how-to/tools/bing-grounding?tabs=python&pivots=overview#setup).
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1. Once you complete the setup, create a yaml code file that specifies the tool’s configuration. For example, this format for Grounding with Bing Search:
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```yml
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type: bing_grounding
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name: bing_search
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configuration:
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options:
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tool_connections:
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- >-
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/subscriptions/<Azure Subscription ID>/resourceGroups/<Azure Resource Group name>/providers/Microsoft.MachineLearningServices/workspaces/<Azure AI Foundry Project name>/connections/<Bing connection name>

‎articles/ai-services/openai/concepts/content-filter.md

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**HTTP Response Code** | **Response behavior**
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|------------------------|----------------------|
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| 200 | If the content filtering system is down or otherwise unable to complete the operation in time, your request will still complete without content filtering. You can determine that the filtering wasn't applied by looking for an error message in the `content_filter_result` object.|
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| 200 | If the content filtering system is down or otherwise unable to complete the operation in time, your request will still complete without content filtering. You can determine that the filtering wasn't applied by looking for an error message in the `content_filter_results` object.|
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**Example request payload:**
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"index": 0,
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"finish_reason": "length",
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"logprobs": null,
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"content_filter_result": {
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"content_filter_results": {
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"error": {
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"message": "The contents are not filtered"
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except openai.error.InvalidRequestError as e:
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if e.error.code == "content_filter" and e.error.innererror:
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content_filter_result = e.error.innererror.content_filter_result
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content_filter_results = e.error.innererror.content_filter_result
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# print the formatted JSON
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print(content_filter_results)
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# or access the individual categories and details
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for category, details in content_filter_result.items():
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for category, details in content_filter_results.items():
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```
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"content_filter_results": {
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- Decide how you want to handle scenarios where your users send prompts containing content that is classified at a filtered category and severity level or otherwise misuse your application.
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- Check the `finish_reason` to see if a completion is filtered.
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- Check that there's no error object in the `content_filter_result` (indicating that content filters didn't run).
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- Check that there's no error object in the `content_filter_results` (indicating that content filters didn't run).
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- If you're using the protected material code model in annotate mode, display the citation URL when you're displaying the code in your application.
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## Next steps

‎articles/ai-services/openai/concepts/model-retirements.md

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2. At least 60 days notice before model retirement for Generally Available (GA) models.
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3. At least 30 days notice before preview model version upgrades.
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Retirements are done on a rolling basis, region by region.
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Retirements are done on a rolling basis, region by region. Notifications are sent from an unmonitored mailbox, `[email protected]`.
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## Model availability
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| `gpt-4.1-nano` | 2025-04-14 | No earlier than April 11, 2026 | |
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| `gpt-4o` | 2024-05-13 | No earlier than June 30, 2025 | `gpt-4.1` version: `2025-04-14` |
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| `gpt-4o` | 2024-08-06 | No earlier than August 6, 2025 | `gpt-4.1` version: `2025-04-14` |
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| `gpt-4o` | 2024-11-20 | No earlier than January 30, 2026 | `gpt-4.1` version: `2025-04-14` |
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| `gpt-4o` | 2024-11-20 | No earlier than March 1, 2026 | `gpt-4.1` version: `2025-04-14` |
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| `gpt-4o-mini` | 2024-07-18 | August 16, 2025 | `gpt-4.1-mini` version: `2025-04-14` |
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| `gpt-3.5-turbo-instruct` | 0914 | No earlier than May 31, 2025 | |
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| `gpt-image-1` | 2025-04-15 | No earlier than August 01, 2025 | |

‎articles/ai-services/openai/how-to/provisioned-throughput-onboarding.md

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For example, for `gpt-4.1:2025-04-14`, 1 output token counts as 4 input tokens towards your utilization limit which matches the [pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/). Older models use a different ratio and for a deeper understanding on how different ratios of input and output tokens impact the throughput your workload needs, see the [Azure OpenAI capacity calculator](https://ai.azure.com/resource/calculator).
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|Topic| **gpt-4.1** | **gpt-4.1-mini** | **o3-mini** | **o1** | **gpt-4o** | **gpt-4o-mini** |
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| --- | --- | --- | --- | --- | --- | --- |
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|Global & data zone provisioned minimum deployment|15|15|15|15|15|15|
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|Global & data zone provisioned scale increment|5|5|5|5|5|5|
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|Regional provisioned minimum deployment|50|25|25|25|50|25|
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|Regional provisioned scale increment|50|25|25|50|50|25|
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|Input TPM per PTU|3,000|14,900|2,500|230|2,500|37,000|
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|Latency Target Value|44 Tokens Per Second|50 Tokens Per Second| 66 Tokens Per Second |25 Tokens Per Second|25 Tokens Per Second|33 Tokens Per Second|
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|Topic| **gpt-4o** | **gpt-4o-mini** | **o1**| gpt-4.1 |
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| --- | --- | --- | --- | --- |
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|Global & data zone provisioned scale increment|5|5|5| 5 |
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|Regional provisioned minimum deployment|50|25|50| 50 |
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|Regional provisioned scale increment|50|25|50| 50 |
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|Latency Target Value |25 Tokens Per Second|33 Tokens Per Second|25 Tokens Per Second| 44 Tokens Per Second |
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For a full list, see the [Azure OpenAI Service in Azure AI Foundry portal calculator](https://ai.azure.com/resource/calculator).
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‎articles/ai-services/openai/how-to/use-blocklists.md

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‎articles/ai-services/openai/includes/language-overview/python.md

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‎articles/ai-services/openai/includes/model-matrix/datazone-provisioned-managed.md

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| **Region** | **gpt-4.1**, **2025-04-14** | **o3-mini**, **2025-01-31** | **o1**, **2024-12-17** | **gpt-4o**, **2024-05-13** | **gpt-4o**, **2024-08-06** | **gpt-4o**, **2024-11-20** | **gpt-4o-mini**, **2024-07-18** |
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|:-------------------|:---------------------------:|:---------------------------:|:----------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:-------------------------------:|
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| eastus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| eastus2 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| francecentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| germanywestcentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| italynorth | ✅ | - | - | - | - | - | - |
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| northcentralus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| polandcentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| southcentralus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| spaincentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| swedencentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westeurope | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westus3 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| **Region** | **gpt-4.1**, **2025-04-14** | **gpt-4.1-mini**, **2025-04-14** | **o3-mini**, **2025-01-31** | **o1**, **2024-12-17** | **gpt-4o**, **2024-05-13** | **gpt-4o**, **2024-08-06** | **gpt-4o**, **2024-11-20** | **gpt-4o-mini**, **2024-07-18** |
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|:-------------------|:---------------------------:|:--------------------------------:|:---------------------------:|:----------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:-------------------------------:|
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| eastus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| eastus2 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| francecentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| germanywestcentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| italynorth | ✅ | - | - | - | - | - | - | - |
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| northcentralus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| polandcentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| southcentralus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| spaincentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| swedencentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westeurope | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westus3 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |

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