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articles/active-directory-b2c/oauth2-error-technical-profile.md

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ms.service: active-directory
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ms.topic: reference
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ms.date: 01/11/2024
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ms.date: 05/07/2024
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ms.author: kengaderdus
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ms.subservice: B2C
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</ClaimsProviders> -->
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```
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## Define claims transformation to generate custom values of error code and error message
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Use these steps to generate custom values of error code and error message:
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1. Locate the `ClaimsTransformations` element, then add the following code inside it
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```xml
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<!--
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<ClaimsTransformations> -->
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<ClaimsTransformation Id="GenerateErrorCode" TransformationMethod="CreateStringClaim">
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<InputParameters>
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<InputParameter Id="value" DataType="string" Value="Error_001" />
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</InputParameters>
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<OutputClaims>
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<OutputClaim ClaimTypeReferenceId="errorCode" TransformationClaimType="createdClaim" />
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</OutputClaims>
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</ClaimsTransformation>
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<ClaimsTransformation Id="GenerateErrorMessage" TransformationMethod="CreateStringClaim">
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<InputParameters>
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<InputParameter Id="value" DataType="string" Value="Insert error description." />
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</InputParameters>
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<OutputClaims>
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<OutputClaim ClaimTypeReferenceId="errorMessage" TransformationClaimType="createdClaim" />
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</OutputClaims>
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</ClaimsTransformation>
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<!--
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</ClaimsTransformations> -->
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```
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1. Add the two claims transformations in the `OutputClaimsTransformations` element of any technical profile before Oauth2 technical that you define:
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```xml
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<OutputClaimsTransformations>
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<OutputClaimsTransformation ReferenceId="generateErrorCode" />
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<OutputClaimsTransformation ReferenceId="generateErrorMessage" />
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</OutputClaimsTransformations>
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```
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## Input claims
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The **InputClaims** element contains a list of claims required to return OAuth2 error.
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</UserJourney>
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```
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Optionally, you can use preconditions to manipulate the Oauth2 error technical profile. For example, if there is no email claim, you can set to call Oauth2 error technical profile:
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```xml
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<OrchestrationStep Order="3" Type="SendClaims" CpimIssuerTechnicalProfileReferenceId="ReturnOAuth2Error">
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<Preconditions>
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<Precondition Type="ClaimsExist" ExecuteActionsIf="false">
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<Value>email</Value>
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<Action>SkipThisOrchestrationStep</Action>
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</Precondition>
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</Preconditions>
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</OrchestrationStep>
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```
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## Next steps
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Learn about [UserJourneys](userjourneys.md)

articles/ai-services/computer-vision/how-to/find-similar-faces.md

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[!code-csharp[](~/cognitive-services-quickstart-code/dotnet/Face/FaceQuickstart.cs?name=snippet_loadfaces)]
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#### [JavaScript](#tab/javascript)
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The following face detection method is optimized for comparison operations. It doesn't extract detailed face attributes, and it uses an optimized recognition model.
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:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Face/sdk_quickstart.js" id="recognize":::
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The following code uses the above method to get face data from a series of images.
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:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Face/sdk_quickstart.js" id="snippet_loadfaces":::
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#### [REST API](#tab/rest)
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Copy the following cURL command and insert your key and endpoint where appropriate. Then run the command to detect one of the target faces.
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[!code-csharp[](~/cognitive-services-quickstart-code/dotnet/Face/FaceQuickstart.cs?name=snippet_find_similar_print)]
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#### [JavaScript](#tab/javascript)
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The following method takes a set of target faces and a single source face. Then, it compares them and finds all the target faces that are similar to the source face. Finally, it prints the match details to the console.
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:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Face/sdk_quickstart.js" id="find_similar":::
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#### [REST API](#tab/rest)
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articles/ai-services/computer-vision/includes/quickstarts-sdk/identity-javascript-sdk.md

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Get started with facial recognition using the Face client library for JavaScript. Follow these steps to install the package and try out the example code for basic tasks. The Face service provides you with access to advanced algorithms for detecting and recognizing human faces in images. Follow these steps to install the package and try out the example code for basic face identification using remote images.
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[Reference documentation](/javascript/api/overview/azure/cognitiveservices-face-readme) | [Package (npm)](https://www.npmjs.com/package/@azure/cognitiveservices-face) | [Samples](/samples/browse/?products=azure&term=face&languages=javascript)
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[Reference documentation](https://aka.ms/azsdk-javascript-face-ref) | [Library source code](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/face/ai-vision-face-rest) | [Package (npm)](https://www.npmjs.com/package/@azure-rest/ai-vision-face) | [Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/face/ai-vision-face-rest/samples)
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## Prerequisites
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npm init
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```
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1. Install the `ms-rest-azure` and `azure-cognitiveservices-face` npm packages:
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1. Install the `@azure-rest/ai-vision-face` npm packages:
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```console
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npm install @azure/cognitiveservices-face @azure/ms-rest-js uuid
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npm install @azure-rest/ai-vision-face
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```
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Your app's `package.json` file is updated with the dependencies.
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Done adding faces to person group.
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Training person group: c08484e0-044b-4610-8b7e-c957584e5d2d.
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Waiting 10 seconds...
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Training status: succeeded.
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No persons identified for face with ID 259dd648-be70-499c-9942-3512594e21eb
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Person: Family1-Mom is identified for face in: identification1.jpg with ID: b7f7f542-c338-4a40-ad52-e61772bc6e14. Confidence: 0.96921.
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Person: Family1-Son is identified for face in: identification1.jpg with ID: 600dc1b4-b2c4-4516-87de-edbbdd8d7632. Confidence: 0.92886.
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Person: Family1-Dad is identified for face in: identification1.jpg with ID: e83b494f-9ad2-473f-9d86-3de79c01e345. Confidence: 0.96725.
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Verification result between face bb7f7f542-c338-4a40-ad52-e61772bc6e14 and person de1d7dea-a393-4f69-9062-10cb66d4cf17: true with confidence: 0.96921
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Verification result between face 600dc1b4-b2c4-4516-87de-edbbdd8d7632 and person 05fd84e4-41b0-4716-b767-4376e33fa207: true with confidence: 0.92886
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Verification result between face e83b494f-9ad2-473f-9d86-3de79c01e345 and person c5124fe2-39dd-47ba-9163-1ed2998fdeb2: true with confidence: 0.96725
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Deleting person group: c08484e0-044b-4610-8b7e-c957584e5d2d
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Done.
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```
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> [Specify a face detection model version](../../how-to/specify-detection-model.md)
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* [What is the Face service?](../../overview-identity.md)
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* More extensive sample code can be found on [GitHub](https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/javascript/Face/sdk_quickstart.js).
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* More extensive sample code can be found on [GitHub](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/face/ai-vision-face-rest/samples).

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

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| `gpt-35-turbo` | 0125 | No earlier than Feb 22, 2025 |
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| `gpt-4`<br>`gpt-4-32k` | 0314 | No earlier than July 13, 2024 |
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| `gpt-4`<br>`gpt-4-32k` | 0613 | No earlier than Sep 30, 2024 |
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| `gpt-4` | 1106-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on June 10, 2024, or later **<sup>1</sup>** |
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| `gpt-4` | 0125-preview |To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on June 10, 2024, or later **<sup>1</sup>** |
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| `gpt-4` | vision-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on June 10, 2024, or later **<sup>1</sup>** |
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| `gpt-4` | 1106-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on July 15, 2024, or later **<sup>1</sup>** |
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| `gpt-4` | 0125-preview |To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on July 15, 2024, or later **<sup>1</sup>** |
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| `gpt-4` | vision-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on July 15, 2024, or later **<sup>1</sup>** |
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| `gpt-3.5-turbo-instruct` | 0914 | No earlier than Sep 14, 2025 |
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| `text-embedding-ada-002` | 2 | No earlier than April 3, 2025 |
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| `text-embedding-ada-002` | 1 | No earlier than April 3, 2025 |

articles/ai-services/openai/faq.yml

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answer: |
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* Inference cost (input and output) of the base model you're using for each Assistant (for example gpt-4-0125). If you've created multiple Assistants, you will be charged for the base model attached to each Assistant.
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* If you've enabled the Code Interpreter tool. For example if your assistant calls Code Interpreter simultaneously in two different threads, this would create two Code Interpreter sessions, each of which would be charged. Each session is active by default for one hour, which means that you would only pay this fee once if your user keeps giving instructions to Code Interpreter in the same thread for up to one hour.
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* File search is currently not billed.
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For more information, see the [pricing page](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/).
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