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Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/deploy-models-serverless.md
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- An [Azure AI Foundry project](create-projects.md).
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- You have to disable the feature **Deploy models to Azure AI model inference service**. When this feature is on, serverless API endpoints are not available for deployment when using the Azure AI Foundry portal.
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:::image type="content" source="../model-inference/media/quickstart-ai-project/ai-project-inference-endpoint.gif" alt-text="An animation showing how to turn on the Deploy models to Azure AI model inference service feature in Azure AI Foundry portal." lightbox="../model-inference/media/quickstart-ai-project/ai-project-inference-endpoint.gif":::
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- Azure role-based access controls (Azure RBAC) are used to grant access to operations in Azure AI Foundry portal. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the resource group. For more information on permissions, see [Role-based access control in Azure AI Foundry portal](../concepts/rbac-ai-foundry.md).
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- You need to install the following software to work with Azure AI Foundry:
Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/develop/vscode.md
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## Use AI app templates
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AI app templates are linked from the right side of the **Code** tab of your project. These samples walk you through how to use the Azure AI SDKs to:
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AI app templates are linked from the right side of the **Templates** tab of your project. These samples walk you through how to use the Azure AI SDKs to:
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* Set up your development environment and connect to existing resources
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* Bring in your custom application code
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## Related content
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-[Get started building a chat app using the prompt flow SDK](../../quickstarts/get-started-code.md)
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-[Get started with Azure AI SDKs](sdk-overview.md)
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-[Get started with Azure AI Foundry SDKs](sdk-overview.md)
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> [!NOTE]
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> The following table is for pay-as-you-go. For information on Provisioned Throughput Unit (PTU) availability, see [provisioned throughput](../../openai/concepts/provisioned-throughput.md) in the Azure OpenAI documentation. `GlobalStandard` customers also have access to [global standard models](../../openai/concepts/models.md#global-standard-model-availability).
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Azure AI Language is updated on an ongoing basis. To stay up-to-date with recent developments, this article provides you with information about new releases and features.
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## March 2025
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* Our [Conversational PII redaction](personally-identifiable-information/how-to/redact-conversation-pii.md?tabs=client-libraries) service is now powered by an upgraded GA model. This updated 2024-02-01 version includes improved quality and accuracy in Credit card number entities and numeric identification entities, such as Social Security numbers, driver’s license numbers, policy numbers, Medicare Beneficiary Identifiers, and Financial account numbers.
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## February 2025
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* Document and text abstractive summarization is now powered by fine-tuned Phi-3.5-mini! Check out the [Announcing Blog](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/exciting-update-abstractive-summarization-in-azure-ai-language-now-powered-by-ph/4369025) for more information.
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* More skills are available in [Azure AI Foundry](https://ai.azure.com): Extract key phrase, Extract named entities, Analyze sentiment and Detect language. More skills are yet to come.
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## January 2025
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* .NET SDK for Azure AI Language text analytics, [Azure.AI.Language.Text 1.0.0-beta.2](https://www.nuget.org/packages/Azure.AI.Language.Text/1.0.0-beta.2#readme-body-tab), is now available. This client library supports the latest REST API version, 2024-11-01 and 2024-11-15-preview, for the following features:
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* Language detection
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* Sentiment analysis
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* Key phrase extraction
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* Named entity recognition (NER)
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* Personally identifiable information (PII) entity recognition
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* Entity linking
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* Text analytics for health
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* Custom named entity recognition (Custom NER)
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* Custom text classification
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* Extractive text summarization
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* Abstractive text summarization
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* Custom sentiment analysis (preview), custom text analytics for health (preview) and custom summarization (preview) were retired on January 10th, 2025, as Azure AI features are constantly evaluated based on customer demand and feedback. Based on the customers’ feedback of these preview features, Microsoft has decided to retire this feature and prioritize new custom model features leveraging the power of generative AI to better serve customers’ needs.
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## November 2024
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*[Native document support](native-document-support/overview.md) is now available in public preview `2024-11-15-preview` without gated preview limitations.
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* Azure AI Language is moving to [Azure AI Foundry](https://ai.azure.com). These skills are now available in AI Foundry playground: Extract health information, Extract PII from conversation, Extract PII from text, Summarize text, Summarize conversation, Summarize for call center. More skills follow.
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* Runtime Container for Conversational Language Understanding (CLU) is available for on-premise connection.
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* Both our [Text PII redaction service](personally-identifiable-information/overview.md?tabs=text-pii) and our Conversational PII service preview API (version 2024-11-15-preview) now support the option to mask detected sensitive entities with a label beyond just redaction characters. Customers can specify if personal data content such as names and phone numbers, that is, "John Doe received a call from 424-878-9192", are masked with a redaction character, that is, "******** received a call from ************", or masked with an entity label, that is, "`PERSON_1` received a call from `PHONENUMBER_1`". More on how to specify the redaction policy style for your outputs can be found in our [how-to guides](personally-identifiable-information/how-to-call.md).
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* Native document support gating is removed with the latest API version, 2024-11-15-preview, allowing customers to access native document support for PII redaction and summarization. Key updates in this version include:
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* Increased Maximum File Size Limits (from 1 MB to 10 MB).
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* Enhanced PII Redaction Customization: Customers can now specify whether they want only the redacted document or both the redacted document and a JSON file containing the detected entities.
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* Language detection is a preconfigured feature that can detect the language a document is written in and returns a language code for a wide range of languages, variants, dialects, and some regional/cultural languages. Today the general availability of [scription detection capability](language-detection/how-to/call-api.md#script-name-and-script-code), and 16 more languages support, which adds up to [139 total supported languages](language-detection/language-support.md) is announced.
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* [Named Entity Recognition service](named-entity-recognition/overview.md), [Entity Resolution](named-entity-recognition/concepts/entity-resolutions.md) was upgraded to the Entity Metadata starting in API version 2023-04-15-preview. If you're calling the preview version of the API equal or newer than 2023-04-15-preview, check out the Entity Metadata article to use the resolution feature. The service now supports the ability to specify a list of entity tags to be included into the response or excluded from the response. If a piece of text is classified as more than one entity type, the overlapPolicy parameter allows customers to specify how the service will handle the overlap. The inferenceOptions parameter allows for users to adjust the inference, such as excluding the detected entity values from being normalized and included in the metadata. Along with these optional input parameters we support an updated output structure (with new fields tags, type, and metadata) to ensure enhanced user customization and deeper analysis Learn more on our documentation.
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* Text analytics for health (TA4H) is a preconfigured feature that extracts and labels relevant medical information from unstructured texts such as doctor's notes, discharge summaries, clinical documents, and electronic health records. Today, we released support for Fast Healthcare Interoperability Resources (FHIR) structuring and temporal [assertion detection](text-analytics-for-health/concepts/assertion-detection.md) in the Generally Available API.
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