update java to single script

Author: laujan

articles/applied-ai-services/form-recognizer/quickstarts/try-v3-csharp-sdk.md

@@ -11,7 +11,10 @@ ms.date: 03/14/2022
 ms.author: lajanuar
 recommendations: false
 ---
+
 <!-- markdownlint-disable MD025 -->
+<!-- markdownlint-disable MD036 -->
+
 # Get started: Form Recognizer C# SDK v3.0 | Preview
 
 >[!NOTE]
@@ -152,7 +155,7 @@ Analyze and extract text, tables, structure, key-value pairs, and named entities
 > * We've added the file URI value to the `Uri fileUri` variable at the top of the script.
 > * For simplicity, all the entity fields that the service returns are not shown here. To see the list of all supported fields and corresponding types, see the [General document](../concept-general-document.md#named-entity-recognition-ner-categories) concept page.
 
-**Add the following code sample to the Program.cs file:**
+**Add the following code sample to the Program.cs file. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal:**
 
 ```csharp
 using Azure;
@@ -280,7 +283,7 @@ Extract text, selection marks, text styles, table structures, and bounding regio
 > * We've added the file URI value to the `Uri fileUri` variable at the top of the script.
 > * To extract the layout from a given file at a URI, use the `StartAnalyzeDocumentFromUri` method and pass `prebuilt-layout` as the model ID. The returned value is an `AnalyzeResult` object containing data from the submitted document.
 
-**Add the following code sample to the Program.cs file:**
+**Add the following code sample to the Program.cs file. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal:**
 
 ```csharp
 using Azure;
@@ -368,7 +371,6 @@ for (int i = 0; i < result.Tables.Count; i++)
 
 Visit the Azure samples repository on GitHub to view the [layout model output](https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/dotnet/FormRecognizer/v3-csharp-sdk-layout-output.md).
 
-
 ## Prebuilt model
 
 Analyze and extract common fields from specific document types using a prebuilt model. In this example, we'll analyze an invoice using the **prebuilt-invoice** model.
@@ -383,7 +385,7 @@ Analyze and extract common fields from specific document types using a prebuilt
 > * To analyze a given file at a URI, use the `StartAnalyzeDocumentFromUri` method and pass `prebuilt-invoice` as the model ID. The returned value is an `AnalyzeResult` object containing data from the submitted document.
 > * For simplicity, all the key-value pairs that the service returns are not shown here. To see the list of all supported fields and corresponding types, see our [Invoice](../concept-invoice.md#field-extraction) concept page.
 
-**Add the following code sample to your Program.cs file:**
+**Add the following code sample to your Program.cs file. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal:**
 
 ```csharp
 

articles/applied-ai-services/form-recognizer/quickstarts/try-v3-java-sdk.md

@@ -60,7 +60,7 @@ In this quickstart you'll use following features to analyze and extract data and
 
 ## Set up
 
-#### Create a new Gradle project
+### Create a new Gradle project
 
 1. In console window (such as cmd, PowerShell, or Bash), create a new directory for your app called **form-recognizer-app**, and navigate to it.
 
@@ -78,7 +78,7 @@ In this quickstart you'll use following features to analyze and extract data and
 
 1. Accept the default project name (form-recognizer-app)
 
-#### Install the client library
+### Install the client library
 
 This quickstart uses the Gradle dependency manager. You can find the client library and information for other dependency managers on the [Maven Central Repository](https://mvnrepository.com/artifact/com.azure/azure-ai-formrecognizer).
 
@@ -100,7 +100,7 @@ This quickstart uses the Gradle dependency manager. You can find the client libr
     }
     ```
 
-#### Create a Java application
+### Create a Java application
 
 To interact with the Form Recognizer service, you'll need to create an instance of the `DocumentAnalysisClient` class. To do so, you'll create an `AzureKeyCredential` with your key from the Azure portal and a `DocumentAnalysisClient` instance with the `AzureKeyCredential` and your Form Recognizer `endpoint`.
 
@@ -145,7 +145,7 @@ Extract text, tables, structure, key-value pairs, and named entities from docume
 > * We've added the file URI value to the `documentUrl` variable in the main method.
 > * For simplicity, all the entity fields that the service returns are not shown here. To see the list of all supported fields and corresponding types, see our [General document](../concept-general-document.md#named-entity-recognition-ner-categories) concept page.
 
-**Add the following code sample to the `FormRecognizer` class. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal:
+**Add the following code sample to the `FormRecognizer` class. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal:**
 
 ```java
 
@@ -164,16 +164,19 @@ Extract text, tables, structure, key-value pairs, and named entities from docume
 
     public class FormRecognizer {
 
-      private static final String key = "PASTE_YOUR_FORM_RECOGNIZER_SUBSCRIPTION_KEY_HERE";
-      private static final String endpoint = "PASTE_YOUR_FORM_RECOGNIZER_ENDPOINT_HERE";
+      // set `<your-endpoint>` and `<your-key>` variables with the values from the Azure portal
+      private static final String endpoint = "<your-endpoint>";
+      private static final String key = "<your-key>";
 
       public static void main(String[] args) {
 
+          // create your `DocumentAnalysisClient` instance and `AzureKeyCredential` variable
           DocumentAnalysisClient client = new DocumentAnalysisClientBuilder()
               .credential(new AzureKeyCredential(key))
               .endpoint(endpoint)
               .buildClient();
 
+          // sample document
           String documentUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/form-recognizer/sample-layout.pdf";
           String modelId = "prebuilt-document";
           SyncPoller < DocumentOperationResult, AnalyzeResult> analyzeDocumentPoller =
@@ -238,8 +241,6 @@ Extract text, tables, structure, key-value pairs, and named entities from docume
     }
 ```
 
-
-
 ## Layout model
 
 Extract text, selection marks, text styles, table structures, and bounding region coordinates from documents.

articles/applied-ai-services/form-recognizer/quickstarts/try-v3-python-sdk.md

@@ -89,7 +89,7 @@ Extract text, tables, structure, key-value pairs, and named entities from docume
 > * For simplicity, all the entity fields that the service returns are not shown here. To see the list of all supported fields and corresponding types, see our [General document](../concept-general-document.md#named-entity-recognition-ner-categories) concept page.
 
 <!-- markdownlint-disable MD036 -->
-**Add the following code sample to your form_recognizer_quickstart.py application. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal**
+**Add the following code sample to your form_recognizer_quickstart.py application. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal:**
 
 ```python
 
@@ -239,7 +239,7 @@ Extract text, selection marks, text styles, table structures, and bounding regio
 > * We've added the file URL value to the `formUrl` variable in the `analyze_layout` function.
 > * To analyze a given file at a URL, you'll use the `begin_analyze_document_from_url` method and pass in `prebuilt-layout` as the model Id. The returned value is a `result` object containing data about the submitted document.
 
-**Add the following code sample to your form_recognizer_quickstart.py application. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal**
+**Add the following code sample to your form_recognizer_quickstart.py application. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal:**
 
 ```python
 
@@ -370,7 +370,7 @@ Analyze and extract common fields from specific document types using a prebuilt
 > * To analyze a given file at a URI, you'll use the `beginAnalyzeDocuments` method and pass `PrebuiltModels.Invoice` as the model Id. The returned value is a `result` object containing data about the submitted document.
 > * For simplicity, all the key-value pairs that the service returns are not shown here. To see the list of all supported fields and corresponding types, see our [Invoice](../concept-invoice.md#field-extraction) concept page.
 
-**Add the following code sample to your form_recognizer_quickstart.py application. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal**
+**Add the following code sample to your form_recognizer_quickstart.py application. Make sure you update the key and endpoint variables with values from your Form Recognizer instance in the Azure portal:**
 
 ```python
 # import libraries