Merge pull request #96657 from erhopf/luis-hackadoc-rest-py

[CogSvcs - LUIS Hackadoc] Review of Python REST Quickstart

Author: GitHubber17

articles/cognitive-services/LUIS/includes/get-key-quickstart.md

@@ -6,15 +6,15 @@ author: diberry
 manager: nitinme
 ms.service: cognitive-services
 ms.topic: include 
-ms.date: 10/17/2019
+ms.date: 11/20/2019
 ms.author: diberry
 ---
 
-Access to the keys and endpoints is provided in the LUIS portal in the Manage Section on the Azure Resources page. 
+Keys and endpoints are provided in the LUIS portal in the **Manage Section** on the **Azure Resources** page. 
 
-1. Sign in to the LUIS portal. 
-1. Select your app from the apps list.
+1. Sign in to the [LUIS portal](https://preview.luis.ai/). 
+1. Create a new app, or select an existing app from the apps list.
 1. Select **Manage** then select **Azure Resources**. 
-1. Copy the values for the key and endpoint for the Starter resource.
-
-    The **Starter** key allows free requests to the authoring API and up to 1000 queries to the prediction endpoint API per month for all your LUIS apps. 
+1. Copy the values for the key and endpoint for the Starter resource. You'll need these to run the sample below.
+   > [!NOTE]
+   > The **Starter** key allows free requests to the authoring API and up to 1000 queries to the prediction endpoint API per month for all your LUIS apps. 

articles/cognitive-services/LUIS/includes/get-started-get-intent-rest-csharp.md

@@ -6,36 +6,38 @@ author: diberry
 manager: nitinme
 ms.service: cognitive-services
 ms.topic: include 
-ms.date: 10/17/2019
+ms.date: 11/20/2019
 ms.author: diberry
 ---
 
 ## Prerequisites
 
 * [.NET Core V2.2+](https://dotnet.microsoft.com/download)
 * [Visual Studio Code](https://code.visualstudio.com/)
-* Public app ID: df67dcdb-c37d-46af-88e1-8b97951ca1c2
+* Public app ID: `df67dcdb-c37d-46af-88e1-8b97951ca1c2`
 
 ## Get LUIS key
 
 [!INCLUDE [Use authoring key for endpoint](../includes/get-key-quickstart.md)]
 
 ## Get intent programmatically
 
-Use C# to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-prediction) to get the prediction result. 
+Use C# (.NET Core) to query the [prediction endpoint](https://aka.ms/luis-apim-v3-prediction) and get a prediction result.
 
 1. Create a new console application targeting the C# language, with a project and folder name of `predict-with-rest`. 
 
     ```console
     dotnet new console -lang C# -n predict-with-rest
     ```
 
-1. Install required dependencies with the following dotnet CLI commands.
+1. Change to the `predict-with-rest` directory you just created, and install required dependencies with these commands:  
 
     ```console
+    cd predict-with-rest
     dotnet add package System.Net.Http
     ```
-1. Overwrite Program.cs with the following code:
+
+1. Open `Program.cs` in your favorite IDE or editor. Then overwrite `Program.cs` with the following code:
     
    ```csharp
     using System;
@@ -97,10 +99,10 @@ Use C# to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-pr
 
 1. Replace the following values:
 
-    * `YOUR-KEY` with your starter key
-    * `YOUR-ENDPOINT` with your endpoint, for example, `westus2.api.cognitive.microsoft.com`
+    * `YOUR-KEY` with your starter key.
+    * `YOUR-ENDPOINT` with your endpoint. For example, `westus2.api.cognitive.microsoft.com`.
 
-1. Build the console application. 
+1. Build the console application with this command: 
 
     ```console
     dotnet build
@@ -112,7 +114,7 @@ Use C# to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-pr
     dotnet run
     ```
 
-1. Review prediction response in JSON format:
+1. Review the prediction response, which is returned as JSON:
 
     ```console
     Hit ENTER to exit...

articles/cognitive-services/LUIS/includes/get-started-get-intent-rest-go.md

@@ -6,22 +6,23 @@ author: diberry
 manager: nitinme
 ms.service: cognitive-services
 ms.topic: include 
-ms.date: 10/17/2019
+ms.date: 11/20/2019
 ms.author: diberry
 ---
+
 ## Prerequisites
 
 * [Go](https://golang.org/) programming language  
 * [Visual Studio Code](https://code.visualstudio.com/)
-* Public app ID: df67dcdb-c37d-46af-88e1-8b97951ca1c2
+* Public app ID: `df67dcdb-c37d-46af-88e1-8b97951ca1c2`
 
 ## Get LUIS key
 
 [!INCLUDE [Use authoring key for endpoint](../includes/get-key-quickstart.md)]
 
 ## Get intent programmatically
 
-Use Go to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-prediction) to get the prediction result.
+Use Go to query the [prediction endpoint](https://aka.ms/luis-apim-v3-prediction) and get a prediction result.
 
 1. Create a new file named `predict.go`. Add the following code:
 
@@ -79,8 +80,8 @@ Use Go to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-pr
 
 1. Replace the following values:
 
-    * `YOUR-KEY` with your starter key
-    * `YOUR-ENDPOINT` with your endpoint, for example, `westus2.api.cognitive.microsoft.com`
+    * `YOUR-KEY` with your starter key.
+    * `YOUR-ENDPOINT` with your endpoint. For example, `westus2.api.cognitive.microsoft.com`.
 
 1. With a command prompt in the same directory as where you created the file, enter the following command to compile the Go file:
 

articles/cognitive-services/LUIS/includes/get-started-get-intent-rest-java.md

@@ -6,22 +6,22 @@ author: diberry
 manager: nitinme
 ms.service: cognitive-services
 ms.topic: include 
-ms.date: 10/17/2019
+ms.date: 11/20/2019
 ms.author: diberry
 ---
 ## Prerequisites
 
 * [JDK SE](https://aka.ms/azure-jdks)  (Java Development Kit, Standard Edition)
 * [Visual Studio Code](https://code.visualstudio.com/) or your favorite IDE
-* Public app ID: df67dcdb-c37d-46af-88e1-8b97951ca1c2
+* Public app ID: `df67dcdb-c37d-46af-88e1-8b97951ca1c2`
 
 ## Get LUIS key
 
 [!INCLUDE [Use authoring key for endpoint](../includes/get-key-quickstart.md)]
 
 ## Get intent programmatically
 
-Use Java to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-prediction) to get the prediction result.
+Use Java to query the [prediction endpoint](https://aka.ms/luis-apim-v3-prediction) and get a prediction result.
 
 1. Make a subdirectory named `lib` and copy in the following java libs:
 
@@ -31,7 +31,6 @@ Use Java to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-
 
 1. Copy the following code to create a class in a file named `Predict.java`:
 
-
     ```java
     import java.io.*;
     import java.net.URI;
@@ -102,10 +101,10 @@ Use Java to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-
 1. Replace the following values:
 
     * `YOUR-KEY` with your starter key
-    * `YOUR-ENDPOINT` with your endpoint, for example, `westus2.api.cognitive.microsoft.com`
+    * `YOUR-ENDPOINT` with your endpoint. For example, `westus2.api.cognitive.microsoft.com`.
 
 
-1. Compile the java program from a command line: 
+1. Compile the java program from the command line: 
 
     ```console
     javac -cp ":lib/*" Predict.java
@@ -117,7 +116,7 @@ Use Java to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-
     java -cp ":lib/*" Predict
     ```
 
-1. Review prediction response in JSON format:
+1. Review the prediction response, which is returned as JSON:
 
     ```console
     {'query': 'turn on all lights', 'prediction': {'topIntent': 'HomeAutomation.TurnOn', 'intents': {'HomeAutomation.TurnOn': {'score': 0.5375382}, 'None': {'score': 0.08687421}, 'HomeAutomation.TurnOff': {'score': 0.0207554}}, 'entities': {'HomeAutomation.Operation': ['on'], '$instance': {'HomeAutomation.Operation': [{'type': 'HomeAutomation.Operation', 'text': 'on', 'startIndex': 5, 'length': 2, 'score': 0.724984169, 'modelTypeId': -1, 'modelType': 'Unknown', 'recognitionSources': ['model']}]}}}}

articles/cognitive-services/LUIS/includes/get-started-get-intent-rest-nodejs.md

@@ -6,23 +6,23 @@ author: diberry
 manager: nitinme
 ms.service: cognitive-services
 ms.topic: include 
-ms.date: 10/18/2019
+ms.date: 11/20/2019
 ms.author: diberry
 ---
 
 ## Prerequisites
 
 * [Node.js](https://nodejs.org/) programming language 
 * [Visual Studio Code](https://code.visualstudio.com/)
-* Public app ID: df67dcdb-c37d-46af-88e1-8b97951ca1c2
+* Public app ID: `df67dcdb-c37d-46af-88e1-8b97951ca1c2`
 
 ## Get LUIS key
 
 [!INCLUDE [Use authoring key for endpoint](../includes/get-key-quickstart.md)]
 
 ## Get intent programmatically
 
-Use Node.js to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-prediction) to get the prediction result.
+Use Node.js to query the [prediction endpoint](https://aka.ms/luis-apim-v3-prediction) and get a prediction result.
 
 1. Copy the following code snippet to a file named `predict.js`:
 
@@ -71,24 +71,24 @@ Use Node.js to query the prediction endpoint GET [API](https://aka.ms/luis-apim-
     getPrediction().then(()=>console.log("done")).catch((err)=>console.log(err));
     ```
 
-1. Set the following values:
+1. Replace the following values:
 
-    * `YOUR-KEY` to your starter key
-    * `YOUR-ENDPOINT` to your endpoint URL
+    * `YOUR-KEY` to your starter key.
+    * `YOUR-ENDPOINT` to your endpoint URL. For example, `westus2.api.cognitive.microsoft.com`.
 
-1. Install dependencies by running the following command at the command-line: 
+1. Install the `request`, `request-promise`, and `querystring` dependencies with this command: 
 
     ```console
     npm install request request-promise querystring
     ```
 
-1. Run the code with the following command:
+1. Run your app with this command:
 
     ```console
     node predict.js
     ```
 
- 1. Review prediction response in JSON format:   
+ 1. Review the prediction response, which is returned as JSON:   
 
     ```console
     {"query":"turn on all lights","prediction":{"topIntent":"HomeAutomation.TurnOn","intents":{"HomeAutomation.TurnOn":{"score":0.5375382},"None":{"score":0.08687421},"HomeAutomation.TurnOff":{"score":0.0207554}},"entities":{"HomeAutomation.Operation":["on"],"$instance":{"HomeAutomation.Operation":[{"type":"HomeAutomation.Operation","text":"on","startIndex":5,"length":2,"score":0.724984169,"modelTypeId":-1,"modelType":"Unknown","recognitionSources":["model"]}]}}}}

articles/cognitive-services/LUIS/includes/get-started-get-intent-rest-python.md

@@ -6,24 +6,25 @@ author: diberry
 manager: nitinme
 ms.service: cognitive-services
 ms.topic: include 
-ms.date: 10/18/2019
+ms.date: 11/20/2019
 ms.author: diberry
 ---
 
 ## Prerequisites
 
 * [Python 3.6](https://www.python.org/downloads/) or later.
 * [Visual Studio Code](https://code.visualstudio.com/)
+* Public app ID: `df67dcdb-c37d-46af-88e1-8b97951ca1c2`
 
 ## Get LUIS key
 
 [!INCLUDE [Use authoring key for endpoint](../includes/get-key-quickstart.md)]
 
-## Get intent  programmatically
+## Get intent from the prediction endpoint
 
-Use Python to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v3-prediction) to get the prediction result.
+Use Python to query the [prediction endpoint](https://aka.ms/luis-apim-v3-prediction) and get a prediction result.
 
-1. Copy one of the following code snippets to a file called `predict.py`:
+1. Copy this code snippet into a file called `predict.py`:
 
     ```python
     ########### Python 3.6 #############
@@ -58,28 +59,28 @@ Use Python to query the prediction endpoint GET [API](https://aka.ms/luis-apim-v
 
 1. Replace the following values:
 
-    * `YOUR-KEY` with your starter key
-    * `YOUR-ENDPOINT` with your endpoint, for example, `westus2.api.cognitive.microsoft.com`
+    * `YOUR-KEY` with your starter key.
+    * `YOUR-ENDPOINT` with your endpoint. For example, `westus2.api.cognitive.microsoft.com`.
 
-1. Install dependencies with the following console command:
+1. Install the `requests` dependency. This is used to make HTTP requests:
 
     ```console
     pip install requests
     ```
 
-1. Run the script with the following console command:
+1. Run your script with this console command:
 
     ```console
     python predict.py
     ``` 
 
-1. Review prediction response in JSON format:
+1. Review the prediction response, which is returned as JSON:
 
     ```console
     {'query': 'turn on all lights', 'prediction': {'topIntent': 'HomeAutomation.TurnOn', 'intents': {'HomeAutomation.TurnOn': {'score': 0.5375382}, 'None': {'score': 0.08687421}, 'HomeAutomation.TurnOff': {'score': 0.0207554}}, 'entities': {'HomeAutomation.Operation': ['on'], '$instance': {'HomeAutomation.Operation': [{'type': 'HomeAutomation.Operation', 'text': 'on', 'startIndex': 5, 'length': 2, 'score': 0.724984169, 'modelTypeId': -1, 'modelType': 'Unknown', 'recognitionSources': ['model']}]}}}}
     ```
 
-    The JSON response formatted for readability: 
+    Here's the JSON response formatted for readability: 
 
     ```JSON
     {