Merge pull request #285284 from MicrosoftDocs/main

8/22/2024 AM Publish

Author: Taojunshen

articles/ai-services/document-intelligence/faq.yml

@@ -134,7 +134,15 @@ sections:
         answer: |
          **Yes.**
 
-         If your Document Intelligence resource is configured with a firewall or virtual network, you need to add the dedicated IP address 20.3.165.95 to the firewall allowlist for your Document Intelligence resource.
+         If your Document Intelligence resource is configured with a firewall or virtual network, you need to add the dedicated IP address 20.3.165.95 to the firewall allowlist for your Document Intelligence resource.  Please note that some functions in custom projects (e.g. auto-label, project management and human in the loop) won't work if the public network access is disabled.
+
+      - question: |
+         When I upload a file in Document Intelligence Studio by "Fetch from URL" function, can I use a URL from my blob storage?
+
+        answer: |
+         **Yes.** 
+         
+         If your Azure blob storage URL includes a SAS token and is accessible from public networks.  You cannot use the **Fetch** function for storage accounts where the key access is disabled or behind a firewall/VNet.
 
       - question: |
           Can I reuse or customize the labeling experience from Document Intelligence Studio and build it into my own application?

articles/ai-services/document-intelligence/managed-identities-secured-access.md

@@ -114,7 +114,7 @@ To ensure that the Document Intelligence resource can access the training datase
 
     :::image type="content" source="media/managed-identities/v2-stg-role-assign-role.png" alt-text="Screenshot of add role assignment window.":::
 
-1. On the **Role** tab, search for and select the **Storage Blob Data Reader** permission and select **Next**.
+1. On the **Role** tab, search for and select the **Storage Blob Data Contributor** permission and select **Next**.
 
     :::image type="content" source="media/managed-identities/v2-stg-role-assignment.png" alt-text="Screenshot of choose a role tab.":::
 
@@ -279,7 +279,7 @@ That's it! You can now configure secure access for your Document Intelligence re
 
    :::image type="content" source="media/managed-identities/content-source-error.png" alt-text="Screenshot of content source not accessible error.":::
 
-    **Resolution**: Make sure you grant your Document Intelligence managed identity the role of **Storage Blob Data Reader** and enabled **Trusted services** access or **Resource instance** rules on the networking tab.
+    **Resolution**: Make sure you grant your Document Intelligence managed identity the role of **Storage Blob Data Contributor** and enabled **Trusted services** access or **Resource instance** rules on the networking tab.
 
 * **AccessDenied**:
 

articles/ai-services/document-intelligence/quickstarts/includes/javascript-sdk.md

@@ -151,14 +151,14 @@ Extract text, selection marks, text styles, table structures, and bounding regio
   const { AzureKeyCredential } = require("@azure/core-auth");
 
     // set `<your-key>` and `<your-endpoint>` variables with the values from the Azure portal.
-    const key = "<your-key";
+    const key = "<your-key>";
     const endpoint = "<your-endpoint>";
 
     // sample document
     const formUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/form-recognizer/sample-layout.pdf"
 
    async function main() {
-    const client = DocumentIntelligence(endpoint, new AzureKeyCredential(key:key));
+    const client = DocumentIntelligence(endpoint, new AzureKeyCredential(key));
 
 
     const initialResponse = await client
@@ -329,7 +329,7 @@ const { AzureKeyCredential } = require("@azure/core-auth");
 
 async function main() {
 
-    const client = DocumentIntelligence(endpoint, new AzureKeyCredential(key:key));
+    const client = DocumentIntelligence(endpoint, new AzureKeyCredential(key));
 
     const initialResponse = await client
     .path("/documentModels/{modelId}:analyze", "prebuilt-invoice")

articles/ai-services/language-service/custom-named-entity-recognition/includes/roles-for-resource-and-storage.md

@@ -37,5 +37,16 @@ Use the following steps to set the required roles for your Language resource and
 5. Select **Select members**
 6. Select your subscription, and **Language** as the managed identity. You can search for user names in the **Select** field. 
 
+### Roles for your user
+> [!IMPORTANT]
+> If you skip this step, you'll have a 403 error when trying to connect to your custom project. It's important that your current user has this role to access storage account blob data, even if you're the owner of the storage account.
+> 
+1. Go to your storage account page in the [Azure portal](https://portal.azure.com/).
+2. Select **Access Control (IAM)** in the left navigation menu.
+3. Select **Add** to **Add Role Assignments**, and choose the **Storage blob data contributor** role on the storage account.
+4. Within **Assign access to**, select **User, group, or service principal**. 
+5. Select **Select members**
+6. Select your User. You can search for user names in the **Select** field. 
+
 > [!IMPORTANT]
 > If you have a virtual network or private endpoint, be sure to select **Allow Azure services on the trusted services list to access this storage account** in the Azure portal.

articles/ai-services/language-service/custom-text-classification/concepts/data-formats.md

@@ -27,39 +27,40 @@ Your Labels file should be in the `json` format below. This will enable you to [
     "projectFileVersion": "2022-05-01",
     "stringIndexType": "Utf16CodeUnit",
     "metadata": {
-      "projectKind": "CustomMultiLabelClassification",
-      "storageInputContainerName": "{CONTAINER-NAME}",
-      "projectName": "{PROJECT-NAME}",
-      "multilingual": false,
-      "description": "Project-description",
-      "language": "en-us"
+        "projectKind": "CustomMultiLabelClassification",
+        "storageInputContainerName": "{CONTAINER-NAME}",
+        "projectName": "{PROJECT-NAME}",
+        "multilingual": false,
+        "description": "Project-description",
+        "language": "en-us"
     },
     "assets": {
-      "projectKind": "CustomMultiLabelClassification",
-      "classes": [
-        {
-          "category": "Class1"
-        },
-        {
-          "category": "Class2"
-        }
-      ],
-      "documents": [
-          {
-              "location": "{DOCUMENT-NAME}",
-              "language": "{LANGUAGE-CODE}",
-              "dataset": "{DATASET}",
-              "classes": [
-                  {
-                      "category": "Class1"
-                  },
-                  {
-                      "category": "Class2"
-                  }
-              ]
-          }
-      ]
-  }
+        "projectKind": "CustomMultiLabelClassification",
+        "classes": [
+            {
+                "category": "Class1"
+            },
+            {
+                "category": "Class2"
+            }
+        ],
+        "documents": [
+            {
+                "location": "{DOCUMENT-NAME}",
+                "language": "{LANGUAGE-CODE}",
+                "dataset": "{DATASET}",
+                "classes": [
+                    {
+                        "category": "Class1"
+                    },
+                    {
+                        "category": "Class2"
+                    }
+                ]
+            }
+        ]
+    }
+}
 ```
 
 |Key  |Placeholder  |Value  | Example |
@@ -81,43 +82,44 @@ Your Labels file should be in the `json` format below. This will enable you to [
     "projectFileVersion": "2022-05-01",
     "stringIndexType": "Utf16CodeUnit",
     "metadata": {
-      "projectKind": "CustomSingleLabelClassification",
-      "storageInputContainerName": "{CONTAINER-NAME}",
-      "settings": {},
-      "projectName": "{PROJECT-NAME}",
-      "multilingual": false,
-      "description": "Project-description",
-      "language": "en-us"
+        "projectKind": "CustomSingleLabelClassification",
+        "storageInputContainerName": "{CONTAINER-NAME}",
+        "settings": {},
+        "projectName": "{PROJECT-NAME}",
+        "multilingual": false,
+        "description": "Project-description",
+        "language": "en-us"
     },
     "assets": {
-      "projectKind": "CustomSingleLabelClassification",
-      "classes": [
-          {
-              "category": "Class1"
-          },
-          {
-              "category": "Class2"
-          }
-      ],
-      "documents": [
-          {
-              "location": "{DOCUMENT-NAME}",
-              "language": "{LANGUAGE-CODE}",
-              "dataset": "{DATASET}",
-              "class": {
-                  "category": "Class2"
-              }
-          },
-          {
-              "location": "{DOCUMENT-NAME}",
-              "language": "{LANGUAGE-CODE}",
-              "dataset": "{DATASET}",
-              "class": {
-                  "category": "Class1"
-              }
-          }
-      ]
-  }
+        "projectKind": "CustomSingleLabelClassification",
+        "classes": [
+            {
+                "category": "Class1"
+            },
+            {
+                "category": "Class2"
+            }
+        ],
+        "documents": [
+            {
+                "location": "{DOCUMENT-NAME}",
+                "language": "{LANGUAGE-CODE}",
+                "dataset": "{DATASET}",
+                "class": {
+                    "category": "Class2"
+                }
+            },
+            {
+                "location": "{DOCUMENT-NAME}",
+                "language": "{LANGUAGE-CODE}",
+                "dataset": "{DATASET}",
+                "class": {
+                    "category": "Class1"
+                }
+            }
+        ]
+    }
+}
 ```
 |Key  |Placeholder  |Value  | Example |
 |---------|---------|----------|--|

articles/ai-studio/concepts/content-filtering.md

@@ -106,7 +106,9 @@ Now, you can go to the playground to test whether the content filter works as ex
 
 ### Configurability (preview)
 
-The default content filtering configuration for the GPT model series is set to filter at the medium severity threshold for all four content harm categories (hate, violence, sexual, and self-harm) and applies to both prompts (text, multi-modal text/image) and completions (text). This means that content that is detected at severity level medium or high is filtered, while content detected at severity level low isn't filtered by the content filters. For DALL-E, the default severity threshold is set to low for both prompts (text) and completions (images), so content detected at severity levels low, medium, or high is filtered. The configurability feature is available in preview and allows customers to adjust the settings, separately for prompts and completions, to filter content for each content category at different severity levels as described in the table below:
+The default content filtering configuration for the GPT model series is set to filter at the medium severity threshold for all four content harm categories (hate, violence, sexual, and self-harm) and applies to both prompts (text, multi-modal text/image) and completions (text). This means that content that is detected at severity level medium or high is filtered, while content detected at severity level low isn't filtered by the content filters. For DALL-E, the default severity threshold is set to low for both prompts (text) and completions (images), so content detected at severity levels low, medium, or high is filtered. 
+
+The configurability feature allows customers to adjust the settings, separately for prompts and completions, to filter content for each content category at different severity levels as described in the table below:
 
 | Severity filtered | Configurable for prompts | Configurable for completions | Descriptions |
 |-------------------|--------------------------|------------------------------|--------------|

articles/ai-studio/reference/region-support.md

@@ -20,7 +20,7 @@ Azure AI Studio brings together various Azure AI capabilities that previously we
 
 ## Azure Public regions
 
-Azure AI Studio is currently available in preview in the following Azure regions. You can create [Azure AI Studio hubs](../how-to/create-azure-ai-resource.md) and Azure AI Studio projects in these regions.
+Azure AI Studio is currently available in the following Azure regions. You can create [Azure AI Studio hubs](../how-to/create-azure-ai-resource.md) and Azure AI Studio projects in these regions.
 
 - Australia East
 - Brazil South
@@ -45,7 +45,7 @@ Azure AI Studio is currently available in preview in the following Azure regions
 
 ### Azure Government regions
 
-Azure AI Studio preview is currently not available in Azure Government regions or air-gap regions.
+Azure AI Studio is currently not available in Azure Government regions or air-gap regions.
 
 ## Azure OpenAI
 

articles/application-gateway/application-gateway-websocket.md

@@ -6,7 +6,7 @@ ms.author: greglin
 ms.service: azure-application-gateway
 services: application-gateway
 ms.topic: conceptual
-ms.date: 11/16/2019
+ms.date: 08/22/2024
 ---
 
 # Overview of WebSocket support in Application Gateway
@@ -26,7 +26,9 @@ To establish a WebSocket connection, a specific HTTP-based handshake is exchange
 ![Diagram compares a client interacting with a web server, connecting twice to get two replies, with a WebSocket interaction, where a client connects to a server once to get multiple replies.](./media/application-gateway-websocket/websocket.png)
 
 > [!NOTE]
-> As described, the HTTP protocol is used only to perform a handshake when establishing a WebSocket connection. Once the handshake is completed, a WebSocket connection gets opened for transmitting the data, and the Web Application Firewall (WAF) cannot parse any contents. Therefore, WAF doesn't perform any inspections on such data.
+> After a connection is upgraded to WebSocket, as an intermediary/terminating proxy, Application Gateway will simply send the data received from the frontend to the backend and vice-versa, without any inspection or manipulation capability.
+> Therefore, the Web Application Firewall (WAF) cannot parse any content and doesn't perform any inspections on such data. Similarly, any manipulations like Header Rewrites, URL Rewrites, or Overriding Hostname in the Backend Settings will not apply after establishing a WebSocket connection.
+
 
 ### Listener configuration element
 

articles/azure-functions/TOC.yml

@@ -579,8 +579,8 @@
           href: disable-function.md
         - name: Networking
           href: configure-networking-how-to.md
-        - name: Move across regions
-          href: functions-move-across-regions.md
+        - name: Relocate to another region
+          href: ../operational-excellence/relocation-functions.md?toc=/azure/azure-functions/toc.json
         - name: Work with legacy Functions Proxies
           href: legacy-proxies.md  
     - name: Migrate