Update vector-search-vectorizer-custom-web-api.md

Updated with supported ENTRA ID registered application ID formats allowed.

Author: gmndrg

articles/search/vector-search-vectorizer-custom-web-api.md

@@ -8,7 +8,7 @@ ms.service: cognitive-search
 ms.custom:
   - build-2024
 ms.topic: reference
-ms.date: 05/28/2024
+ms.date: 07/22/2024
 ---
 
 # Custom Web API vectorizer
@@ -27,7 +27,7 @@ Parameters are case-sensitive.
 | `uri` | The URI of the Web API to which the JSON payload is sent. Only the **https** URI scheme is allowed. |
 | `httpMethod` | The method to use while sending the payload. Allowed methods are `PUT` or `POST` |
 | `httpHeaders` | A collection of key-value pairs where the keys represent header names and values represent header values that are sent to your Web API along with the payload. The following headers are prohibited from being in this collection:  `Accept`, `Accept-Charset`, `Accept-Encoding`, `Content-Length`, `Content-Type`, `Cookie`, `Host`, `TE`, `Upgrade`, `Via`. |
-| `authResourceId` | (Optional) A string that if set, indicates that this vectorizer should use a managed identity on the connection to the function or app hosting the code. This property takes an application (client) ID or app's registration in Microsoft Entra ID, in a [supported format](../active-directory/develop/security-best-practices-for-app-registration.md#application-id-uri): `api://<appId>`. This value is used to scope the authentication token retrieved by the indexer, and is sent along with the custom Web API request to the function or app. Setting this property requires that your search service is [configured for managed identity](search-howto-managed-identities-data-sources.md) and your Azure function app is [configured for a Microsoft Entra sign in](../app-service/configure-authentication-provider-aad.md). |
+| `authResourceId` | (Optional) A string that if set, indicates that this vectorizer should use a managed identity on the connection to the function or app hosting the code. This property takes an application (client) ID or app's registration in Microsoft Entra ID, in any of these formats: `api://<appId>`, `<appId>/.default`, `api://<appId>/.default`. This value is used to scope the authentication token retrieved by the indexer, and is sent along with the custom Web API request to the function or app. Setting this property requires that your search service is [configured for managed identity](search-howto-managed-identities-data-sources.md) and your Azure function app is [configured for a Microsoft Entra sign in](../app-service/configure-authentication-provider-aad.md). |
 | `authIdentity`   | (Optional) A user-managed identity used by the search service for connecting to the function or app hosting the code. You can use either a [system or user managed identity](search-howto-managed-identities-data-sources.md). To use a system manged identity, leave `authIdentity` blank. |
 | `timeout` | (Optional) When specified, indicates the timeout for the http client making the API call. It must be formatted as an XSD "dayTimeDuration" value (a restricted subset of an [ISO 8601 duration](https://www.w3.org/TR/xmlschema11-2/#dayTimeDuration) value). For example, `PT60S` for 60 seconds. If not set, a default value of 30 seconds is chosen. The timeout can be set to a maximum of 230 seconds and a minimum of 1 second. |
 
@@ -89,4 +89,4 @@ There are the following other considerations to make when implementing a web API
 + [Integrated vectorization](vector-search-integrated-vectorization.md)
 + [How to configure a vectorizer in a search index](vector-search-how-to-configure-vectorizer.md)
 + [Custom Web API skill](cognitive-search-custom-skill-web-api.md)
-+ [Hugging Face Embeddings Generator power skill (can be used for a custom web API vectorizer as well)](https://github.com/Azure-Samples/azure-search-power-skills/tree/main/Vector/EmbeddingGenerator)
++ [Hugging Face Embeddings Generator power skill (can be used for a custom web API vectorizer as well)](https://github.com/Azure-Samples/azure-search-power-skills/tree/main/Vector/EmbeddingGenerator)