acrolinx

Author: laujan

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

@@ -30,15 +30,15 @@ sections:
 
           There are no changes to pricing. The names Cognitive Services and Applied AI Services continue to be used in Azure billing, cost analysis, price lists, and price APIs.
 
-          There are no breaking changes to APIs or client libraries (SDKs). REST APIs and SDK versions 2024-02-29-preview, 2023-10-31-preview, and later are renamed `document intelligence`.
+          There are no breaking changes to APIs or client libraries. REST APIs and SDK versions 2024-02-29-preview, 2023-10-31-preview, and going forward are renamed `document intelligence`.
 
           Some platforms are still awaiting the renaming update. In Microsoft documentation, all mentions of Form Recognizer and Document Intelligence refer to the same Azure service.
 
       - question: |
           How is Document Intelligence related to document generative AI?
         answer: |
 
-          You can use a document generative AI solution to chat with your documents, generate captivating content from those documents, and access Azure OpenAI Service models on your data. With Azure AI Document Intelligence and Azure OpenAI combined, you can build an enterprise application to seamlessly interact with your documents by using natural languages, easily find answers and gain valuable insights, and generate new and engaging content from your existing documents. Find more details in the [technical community blog](https://techcommunity.microsoft.com/t5/azure-ai-services-blog/document-generative-ai-the-power-of-azure-ai-document/ba-p/3875015).
+          You can use a document generative AI solution to chat with your documents, generate captivating content from those documents, and access Azure OpenAI Service models on your data. With Azure AI Document Intelligence and Azure OpenAI combined, you can build an enterprise application to seamlessly interact with your documents. Find more details in the [technical community blog](https://techcommunity.microsoft.com/t5/azure-ai-services-blog/document-generative-ai-the-power-of-azure-ai-document/ba-p/3875015).
 
       - question: |
           How is Document Intelligence related to retrieval-augmented generation?
@@ -158,7 +158,7 @@ sections:
           What is a bounding box?
         answer: |
 
-          A bounding box (`polygon` in v3.0 and later versions) is an abstract rectangle that surrounds text elements in a document or form used as a reference point for object detection.
+          A bounding box (`polygon` in v3.0 and later versions) is an abstract rectangle that surrounds text elements in a document used as a reference point for object detection.
 
           The bounding box specifies position by using an x and y coordinate plane presented in an array of four numerical pairs. Each pair represents a corner of the box in the following order: upper left, upper right, lower right, lower left.
 
@@ -217,7 +217,7 @@ sections:
           I have multiple pages in a document. Why are only two pages analyzed in Document Intelligence Studio?
         answer: |
 
-          For free-tier (F0) resources, only the first two pages are analyzed whether you're using Document Intelligence Studio, the REST API, or SDKs.
+          For free-tier (F0) resources, only the first two pages are analyzed whether you're using Document Intelligence Studio, the REST API, or client libraries.
 
           In Document Intelligence Studio, select the **Settings** (gear) button, select the **Resources** tab, and check the price tier that you're using to analyze the documents. If you want to analyze all pages in a document, change to a paid (S0) resource.
 
@@ -262,9 +262,9 @@ sections:
 
           "Yes. Document Intelligence Studio has separate URL endpoints for sovereign cloud regions:"
 
-          - "URL for the Azure US Government cloud (Azure Fairfax): [Document Intelligence Studio US Government](https://formrecognizer.appliedai.azure.us/studio)".
+          - "URL for the Azure US Government cloud (Azure Fairfax): [Document Intelligence Studio US Government](https://formrecognizer.appliedai.azure.us/studio)."
 
-          - "URL Microsoft Azure operated by 21Vianet (Azure in China): [Document Intelligence Studio China](https://formrecognizer.appliedai.azure.cn/studio)."
+          - "URL Microsoft Azure operated by 21Vianet (Azure China): [Document Intelligence Studio China](https://formrecognizer.appliedai.azure.cn/studio)."
 
 
   - name: App development
@@ -288,7 +288,7 @@ sections:
           - [Python](https://pypi.org/project/azure-ai-formrecognizer/3.2.0/)
 
       - question: |
-          Where can I find the supported API version for the latest programming language SDKs?
+          Where can I find the supported API version for the latest programming language client libraries?
         answer:   |
 
           This table provides links to the latest SDK versions and shows the relationship between supported Document Intelligence SDK and API versions:
@@ -325,7 +325,7 @@ sections:
             How can I specify a range of pages to be analyzed in a document?
         answer:  |
 
-            Use the `pages` parameter (supported in v2.1, v3.0, and later versions of the REST API) to specify pages for multiple-page PDF and TIFF documents. Accepted input includes the following ranges:
+            Use the `pages` parameter (supported in v2.1, v3.0, and later versions of the REST API) and specify pages for multiple-page PDF and TIFF documents. Accepted input includes the following ranges:
 
             - Single pages. For example, if you specify `1, 2`, pages 1 and 2 are processed.
             - Finite ranges. For example, if you specify `2-5`, pages 2 to 5 are processed.
@@ -368,7 +368,7 @@ sections:
 
           - When the service analyzes Microsoft Word and HTML files that the read and layout models support, it counts pages in blocks of 3,000 characters each. For example, if your document contains 7,000 characters, the two pages with 3,000 characters each and one page with 1,000 characters add up to a total of three pages.
 
-          - When you're using the read or layout model to analyze Microsoft Word, Excel, PowerPoint, and HTML files, embedded or linked images aren't supported. So the service doesn't count them as added images.
+          - The read and layout models don't support analysis of embedded or linked images in Microsoft Word, Excel, PowerPoint, and HTML files. Therefore, service doesn't count them as added images.
 
           - Training a custom model is always free with Document Intelligence. You're charged only when the service uses a model to analyze a document.
 
@@ -449,7 +449,7 @@ sections:
 
           Document Intelligence doesn't have an explicit retrain operation. Each train operation generates a new model.
 
-          If you find that your model needs retraining, add more samples to your training dataset and train a new model.
+          If you find that your model needs to retrain, add more samples to your training dataset and train a new model.
 
       - question: |
           How many custom models can I compose into a single custom model?
@@ -554,7 +554,7 @@ sections:
 
           [Disconnected containers](../../ai-services/containers/disconnected-containers.md) enable you to use APIs that are disconnected from the internet. [Billing information](../../ai-services/containers/disconnected-container-faq.yml#how-does-billing-work) isn't sent via the internet. Instead, you're charged based on a purchased commitment tier. Currently, disconnected container usage is available for Document Intelligence custom and invoice models.
 
-          The model capabilities provided in connected and disconnected containers are the same and are supported by Document Intelligence v2.1.
+          The  Document Intelligence v2.1 model capabilities for connected and disconnected containers are the same.
 
       - question: |
           What data do connected containers send to the cloud?
@@ -565,7 +565,7 @@ sections:
           For an example of the information that connected containers send to Microsoft for billing, see the [Azure AI container FAQ](../../ai-services/containers/disconnected-container-faq.yml#how-does-billing-work).
 
       - question: |
-           Why am I receiving the error "Container isn't in a valid state. Subscription validation failed with status 'OutOfQuota' API key is out of quota"?
+           Why am I receiving the error *Container isn't in a valid state. Subscription validation failed with status 'OutOfQuota' API key is out of quota*?
         answer: |
 
           Document Intelligence connected containers send billing information to Azure by using a Document Intelligence resource on your Azure account. You could get this message if the containers can't communicate with the billing endpoint.
@@ -624,7 +624,7 @@ sections:
       - question: |
             Where can I find more solutions to my Azure AI Document Intelligence questions?
         answer: |
-             [Microsoft Q&A](/answers/topics/azure-form-recognizer.html) is the home for technical questions and answers at Microsoft. You can filter queries that are specific to Document Intelligence.
+             [Microsoft Q & A](/answers/topics/azure-form-recognizer.html) is the home for technical questions and answers at Microsoft. You can filter queries that are specific to Document Intelligence.
 
       - question: |
             What should I do if the service doesn't recognize specific text, or recognizes it incorrectly, when I'm labeling documents?

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

@@ -8,7 +8,7 @@ ms.service: azure-ai-document-intelligence
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 07/18/2023
+ms.date: 05/23/2024
 ms.author: vikurpad
 monikerRange: '<=doc-intel-4.0.0'
 ---
@@ -50,43 +50,43 @@ Configure each of the resources to ensure that the resources can communicate wit
 
 * Configure the Document Intelligence Studio to use the newly created Document Intelligence resource by accessing the settings page and selecting the resource.
 
-* Validate that the configuration works by selecting the Read API and analyzing a sample document. If the resource was configured correctly, the request successfully completes.
+* Ensure and validate that the configuration works by selecting the Read API and analyzing a sample document. If the resource was configured correctly, the request successfully completes.
 
 * Add a training dataset to a container in the Storage account you created.
 
 * Select the custom model tile to create a custom project. Ensure that you select the same Document Intelligence resource and the storage account you created in the previous step.
 
 * Select the container with the training dataset you uploaded in the previous step. Ensure that if the training dataset is within a folder, the folder path is set appropriately.
 
-* If you have the required permissions, the Studio sets the CORS setting required to access the storage account. If you don't have the permissions, you need to ensure that the CORS settings are configured on the Storage account before you can proceed.
+* Ensure that you have the required permissions, the Studio sets the CORS setting required to access the storage account. If you don't have the permissions, you need to make certain that the CORS settings are configured on the Storage account before you can proceed.
 
-* Validate that the Studio is configured to access your training data, if you can see your documents in the labeling experience, all the required connections are established.
+* Ensure and validate that the Studio is configured to access your training data. If you can see your documents in the labeling experience, all the required connections are established.
 
 You now have a working implementation of all the components needed to build a Document Intelligence solution with the default security model:
 
   :::image type="content" source="media/managed-identities/default-config-di.png" alt-text="Screenshot of default security configuration.":::
 
 Next, complete the following steps:
 
-* Setup managed identity on the Document Intelligence resource.
+* Configure managed identity on the Document Intelligence resource.
 
 * Secure the storage account to restrict traffic from only specific virtual networks and IP addresses.
 
 * Configure the Document Intelligence managed identity to communicate with the storage account.
 
-* Disable public access to the Document Intelligence resource and create a private endpoint to make it accessible from only specific virtual networks and IP addresses.
+* Disable public access to the Document Intelligence resource and create a private endpoint. Your resource is then only accessible from specific virtual networks and IP addresses.
 
 * Add a private endpoint for the storage account in a selected virtual network.
 
-* Validate that you can train models and analyze documents from within the virtual network.
+* Ensure and validate that you can train models and analyze documents from within the virtual network.
 
 ## Setup managed identity for Document Intelligence
 
 Navigate to the Document Intelligence resource in the Azure portal and select the **Identity** tab. Toggle the **System assigned** managed identity to **On** and save the changes:
 
   :::image type="content" source="media/managed-identities/v2-fr-mi.png" alt-text="Screenshot of configure managed identity.":::
 
-## Secure the Storage account to limit traffic
+## Secure the Storage account
 
 Start configuring secure communications by navigating to the **Networking** tab on your **Storage account** in the Azure portal.
 
@@ -141,7 +141,7 @@ Great! You configured your Document Intelligence resource to use a managed ident
 > When you try the [Document Intelligence Studio](https://formrecognizer.appliedai.azure.com/studio), you'll see the READ API and other prebuilt models don't require storage access to process documents. However, training a custom model requires additional configuration because the Studio can't directly communicate with a storage account.
   > You can enable storage access by selecting **Add your client IP address** from the **Networking** tab of the storage account to configure your machine to access the storage account via IP allowlisting.
 
-## Configure private endpoints for access from VNETs
+## Configure private endpoints for access from `VNET`s
 
 > [!NOTE]
 >
@@ -252,7 +252,7 @@ To validate your deployment, you can deploy a virtual machine (VM) to the virtua
 
 1. Configure a [Data Science VM](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-dsvm.dsvm-win-2019?tab=Overview) in the virtual network.
 
-1. Remotely connect into the VM from your desktop to launch a browser session to access Document Intelligence Studio.
+1. Remotely connect into the VM from your desktop and launch a browser session that accesses Document Intelligence Studio.
 
 1. Analyze requests and the training operations should now work successfully.
 
@@ -267,13 +267,13 @@ That's it! You can now configure secure access for your Document Intelligence re
   **Resolution**:
     1. [Configure CORS](quickstarts/try-document-intelligence-studio.md#configure-cors).
 
-    1. Make sure the client computer can access Document Intelligence resource and storage account, either they are in the same VNET, or client IP address is allowed in **Networking > Firewalls and virtual networks** setting page of both Document Intelligence resource and storage account.
+    1. Make sure the client computer can access Document Intelligence resource and storage account, either they are in the same `VNET`, or client IP address is allowed in **Networking > Firewalls and virtual networks** setting page of both Document Intelligence resource and storage account.
 
 * **AuthorizationFailure**:
 
   :::image type="content" source="media/managed-identities/auth-failure.png" alt-text="Screenshot of authorization failure error.":::
 
-  **Resolution**: Make sure the client computer can access Document Intelligence resource and storage account, either they are in the same VNET, or client IP address is allowed in **Networking > Firewalls and virtual networks** setting page of both Document Intelligence resource and storage account.
+  **Resolution**: Make sure the client computer can access Document Intelligence resource and storage account, either they are in the same `VNET`, or client IP address is allowed in **Networking > Firewalls and virtual networks** setting page of both Document Intelligence resource and storage account.
 
 * **ContentSourceNotAccessible**: