Fix for diaspatch issue (#1766)

articles/v4sdk/bot-builder-tutorial-dispatch.md

@@ -18,7 +18,8 @@ monikerRange: 'azure-bot-service-4.0'
 If a bot uses multiple LUIS models and QnA Maker knowledge bases (knowledge bases), you can use Dispatch tool to determine which LUIS model or QnA Maker knowledge base best matches the user input. The dispatch tool does this by creating a single LUIS app to route user input to the correct model. For more information about the Dispatch, including the CLI commands, refer to the [README][dispatch-readme].
 
 ## Prerequisites
-- Knowledge of [bot basics](bot-builder-basics.md), [LUIS][howto-luis], and [QnA Maker][howto-qna]. 
+
+- Knowledge of [bot basics](bot-builder-basics.md), [LUIS][howto-luis], and [QnA Maker][howto-qna].
 - [Dispatch tool](https://github.com/Microsoft/botbuilder-tools/tree/master/packages/Dispatch)
 - A copy of the **NLP with Dispatch** from either the [C# Sample][cs-sample] or [JS Sample][js-sample] code repository.
 - A [luis.ai](https://www.luis.ai/) account to publish LUIS apps.
@@ -53,7 +54,8 @@ This sample is based on a predefined set of LUIS and QnA Maker Apps.
 The handler calls the LUIS or QnA Maker service and returns the generated result back to the user.
 
 ## Create LUIS apps and QnA knowledge base
-Before you can create the dispatch model, you'll need to have your LUIS apps and QnA knowledge bases created and published. In this article, we'll publish the following models that are included with the _NLP With Dispatch_ sample in the `\CognitiveModels` folder: 
+
+Before you can create the dispatch model, you'll need to have your LUIS apps and QnA knowledge bases created and published. In this article, we'll publish the following models that are included with the _NLP With Dispatch_ sample in the `\CognitiveModels` folder:
 
 | Name | Description |
 |------|------|
@@ -62,11 +64,12 @@ Before you can create the dispatch model, you'll need to have your LUIS apps and
 | QnAMaker  | A QnA Maker knowledge base that provides answers to simple questions about the bot. |
 
 ### Create LUIS apps
+
 1. Log into the [LUIS web portal](https://www.luis.ai/). Under the _My apps_ section, select the Tab _Import new app_. The following Dialog Box will appear:
 
     ![Import LUIS json file](./media/tutorial-dispatch/import-new-luis-app.png)
 
-2. Select the button _Choose app file_, navigate to the CognitiveModel folder of your sample code and select the file 'HomeAutomation.json'. Leave the optional name field blank. 
+2. Select the button _Choose app file_, navigate to the CognitiveModel folder of your sample code and select the file 'HomeAutomation.json'. Leave the optional name field blank.
 
 3. Select _Done_.
 
@@ -86,12 +89,12 @@ Before you can create the dispatch model, you'll need to have your LUIS apps and
 
 The first step to setting up a QnA Maker knowledge base is to set up a QnA Maker service in Azure. To do that, follow the step-by-step instructions found [here](https://aka.ms/create-qna-maker).
 
-Once your QnA Maker Service has been created in Azure, you need to record the Cognitive Services _Key 1_ provided for your QnA Maker service. This will be used as \<azure-qna-service-key1> when adding the QnA Maker app to your dispatch application. 
+Once your QnA Maker Service has been created in Azure, you need to record the Cognitive Services _Key 1_ provided for your QnA Maker service. This will be used as \<azure-qna-service-key1> when adding the QnA Maker app to your dispatch application.
 
 Learn more about the [two different types of keys](https://docs.microsoft.com/azure/cognitive-services/qnamaker/how-to/set-up-qnamaker-service-azure#types-of-keys-in-qna-maker) used with QnA Maker.
 
 The following steps provide you with this key:
-    
+
 ![Select Cognitive Service](./media/tutorial-dispatch/select-qna-cognitive-service.png)
 
 1. From within your Azure portal, select your QnA Maker cognitive service.
@@ -104,16 +107,15 @@ The following steps provide you with this key:
 
 1. Copy the value of _Key 1_ to your clipboard and save this locally. this will later be used for the (-k) key value \<azure-qna-service-key1> when adding the QnA Maker app to your dispatch application.
 
-1. Now sign in to the [QnAMaker web portal](https://qnamaker.ai). 
+1. Now sign in to the [QnAMaker web portal](https://qnamaker.ai).
 
 1. At step 2, select the following:
 
-    * Your Azure AD account.
-    * Your Azure subscription name.
-    * The name you created for your QnA Maker service. (If your Azure QnA service does not initially appear in this pull down list, try refreshing the page.)
+    - Your Azure AD account.
+    - Your Azure subscription name.
+    - The name you created for your QnA Maker service. (If your Azure QnA service does not initially appear in this pull down list, try refreshing the page.)
 
-    ![Create QnA Step 2](./media/tutorial-dispatch/create-qna-step-2.png) 
-
+    ![Create QnA Step 2](./media/tutorial-dispatch/create-qna-step-2.png)
 
 1. At step 3, provide a name for your QnA Maker knowledge base. For this example use the name 'sample-qna'.
 
@@ -134,12 +136,12 @@ The following steps provide you with this key:
     Host: <your-hostname>  // NOTE - this is a URL.
     Authorization: EndpointKey <qna-maker-resource-key>
     ```
-    
-    The full URL string for your hostname will look like "https://< >.azure.net/qnamaker". These values will later be used within your `appsettings.json` or `.env` file.
+
+    The full URL string for your hostname will look like "https://<host-id>.azure.net/qnamaker". These values will later be used within your `appsettings.json` or `.env` file.
 
 ## Dispatch app needs read access to existing apps
 
-The dispatch tool needs authoring access to read the existing LUIS and QnA Maker apps in order to create a new parent LUIS app that dispatches to the LUIS and QnA Maker apps. This access is provided with the app IDs and authoring keys. 
+The dispatch tool needs authoring access to read the existing LUIS and QnA Maker apps in order to create a new parent LUIS app that dispatches to the LUIS and QnA Maker apps. This access is provided with the app IDs and authoring keys.
 
 ### Service authoring keys
 
@@ -148,9 +150,9 @@ The **authoring key** is only used for creating and editing the models. You need
 |App|Location of information|
 |--|--|
 |LUIS|**App ID** - found in the [LUIS portal](https://www.luis.ai) for each app, Manage -> Application Information<br>**Authoring Key** - found in the LUIS portal, top-right corner, select your own User, then Settings.|
-|QnA Maker| **App ID** - found in the [QnA Maker portal](https://http://qnamaker.ai) on the Settings page after you publish the app. This is the ID found in first part of the POST command after the knowledgebase. An example of where to find the app ID is `POST /knowledgebases/{APP-ID}/generateAnswer`.<br>**Authoring Key** - found in the Azure portal, for the QnA Maker resource, under the **Keys**. You only need one of the keys.|
+|QnA Maker| **App ID** - found in the [QnA Maker portal](https://http://qnamaker.ai) on the Settings page after you publish the app. This is the ID found in first part of the POST command after the knowledgebase. An example of where to find the app ID is `POST /knowledgebases/<APP-ID>/generateAnswer`.<br>**Authoring Key** - found in the Azure portal, for the QnA Maker resource, under the **Keys**. You only need one of the keys.|
 
-The authoring key is not used to get a prediction score or confidence score from the published application. You need the endpoint keys for this action. The **[endpoint keys](#service-endpoint-keys)** are found and used later in this tutorial. 
+The authoring key is not used to get a prediction score or confidence score from the published application. You need the endpoint keys for this action. The **[endpoint keys](#service-endpoint-keys)** are found and used later in this tutorial.
 
 Learn more about the [two different types of keys](https://docs.microsoft.com/azure/cognitive-services/qnamaker/how-to/set-up-qnamaker-service-azure#types-of-keys-in-qna-maker) used with QnA Maker.
 
@@ -197,7 +199,7 @@ The generated LUIS app defines intents for each of the child apps and the knowle
 - `None`
 - `q_sample-qna`
 
-These services need to be published under the correct names for the bot to run properly. 
+These services need to be published under the correct names for the bot to run properly.
 The bot needs information about the published services, so that it can access those services.
 
 ### Service endpoint keys
@@ -207,32 +209,32 @@ The bot needs the query prediction endpoints for the three LUIS apps (dispatch,
 |App|Query endpoint key location|
 |--|--|
 |LUIS|In the LUIS portal, for each LUIS app, in the Manage section, select **Keys and Endpoint settings** to find the keys associated with each app. If you are following this tutorial, the endpoint key is the same key as the `<your-luis-authoring-key>`. The authoring key allows for 1000 endpoint hits then expires.|
-|QnA Maker|In the QnA Maker portal, for the knowledge base, in the Manage settings, use the key value shows in the Postman settings for the **Authorization** header, without the text of `EndpointKey `.|
+|QnA Maker|In the QnA Maker portal, for the knowledge base, in the Manage settings, use the key value shows in the Postman settings for the **Authorization** header, without the text of `EndpointKey`.|
 
 These values are used in the **appsettings.json** for C# and the **.env** file for javascript.
 
 ## [C#](#tab/cs)
 
 ### Installing packages
 
-Prior to running this app for the first time ensure that several nuget packages are installed:
+Prior to running this app for the first time ensure that several NuGet packages are installed:
 
-**Microsoft.Bot.Builder**
-
-**Microsoft.Bot.Builder.AI.Luis**
-
-**Microsoft.Bot.Builder.AI.QnA**
+- **Microsoft.Bot.Builder**
+- **Microsoft.Bot.Builder.AI.Luis**
+- **Microsoft.Bot.Builder.AI.QnA**
 
 ### Manually update your appsettings.json file
 
 Once all of your service apps are created, the information for each needs to be added into your 'appsettings.json' file. The initial [C# Sample][cs-sample] code contains an empty appsettings.json file:
 
-**appsettings.json**  
+**appsettings.json**
+
 [!code-json[AppSettings](~/../botbuilder-samples/samples/csharp_dotnetcore/14.nlp-with-dispatch/AppSettings.json?range=8-17)]
 
 For each of the entities shown below, add the values you recorded earlier in these instructions:
 
 **appsettings.json**
+
 ```json
 "MicrosoftAppId": "",
 "MicrosoftAppPassword": "",
@@ -245,6 +247,7 @@ For each of the entities shown below, add the values you recorded earlier in the
 "LuisAPIKey": "<your-luis-endpoint-key>",
 "LuisAPIHostName": "<your-dispatch-app-region>",
 ```
+
 When all changes are complete, save this file.
 
 ## [JavaScript](#tab/js)
@@ -257,6 +260,7 @@ Prior to running this app for the first time you will need to install several np
 npm install --save botbuilder
 npm install --save botbuilder-ai
 ```
+
 To use the .env configuration file, your bot needs an extra package included:
 
 ```powershell
@@ -299,14 +303,16 @@ To connect to the Dispatch, LUIS, and QnA Maker services, your bot pulls informa
 
 In **BotServices.cs**, the information contained within configuration file _appsettings.json_ is used to connect your dispatch bot to the `Dispatch` and `SampleQnA` services. The constructors use the values you provided to connect to these services.
 
-**BotServices.cs**  
+**BotServices.cs**
+
 [!code-csharp[ReadConfigurationInfo](~/../botbuilder-samples/samples/csharp_dotnetcore/14.nlp-with-dispatch/BotServices.cs?range=14-30)]
 
 ## [JavaScript](#tab/js)
 
 In **dispatchBot.js** the information contained within configuration file _.env_ is used to connect your dispatch bot to the _LuisRecognizer(dispatch)_ and _QnAMaker_ services. The constructors use the values you provided to connect to these services.
 
-**bots/dispatchBot.js**  
+**bots/dispatchBot.js**
+
 [!code-javascript[ReadConfigurationInfo](~/../botbuilder-samples/samples/javascript_nodejs/14.nlp-with-dispatch/bots/dispatchBot.js?range=11-24)]
 
 ---
@@ -319,14 +325,15 @@ For each input  from your user, the bot logic checks user input against the comb
 
 In the **DispatchBot.cs** file whenever the `OnMessageActivityAsync` method is called, we check the incoming user message against the Dispatch model. We then pass the Dispatch Model's `topIntent` and  `recognizerResult` on to the correct method to call the service and return the result.
 
-**bots\DispatchBot.cs**  
+**bots\DispatchBot.cs**
+
 [!code-csharp[OnMessageActivity](~/../botbuilder-samples/samples/csharp_dotnetcore/14.nlp-with-dispatch/bots/DispatchBot.cs?range=26-36)]
 
 ## [JavaScript](#tab/js)
 
 In the **dispatchBot.js** `onMessage` method, we check the user input message against the Dispatch model, find the _topIntent_, then pass this on by calling _dispatchToTopIntentAsync_.
 
-**bots/dispatchBot.js**  
+**bots/dispatchBot.js**
 
 [!code-javascript[OnMessageActivity](~/../botbuilder-samples/samples/javascript_nodejs/14.nlp-with-dispatch/bots/dispatchBot.js?range=29-42)]
 
@@ -338,7 +345,8 @@ In the **dispatchBot.js** `onMessage` method, we check the user input message ag
 
 When the model produces a result, it indicates which service can most appropriately process the utterance. The code in this bot routes the request to the corresponding service, and then summarizes the response from the called service. Depending on the _intent_ returned from Dispatch, this code uses the returned intent to route to the correct LUIS model or QnA service.
 
-**bots\DispatchBot.cs**  
+**bots\DispatchBot.cs**
+
 [!code-csharp[DispatchToTop](~/../botbuilder-samples/samples/csharp_dotnetcore/14.nlp-with-dispatch/bots/DispatchBot.cs?range=51-69)]
 
 If method `ProcessHomeAutomationAsync` or `ProcessWeatherAsync` are invoked, they are passed the results from the dispatch model within _luisResult.ConnectedServiceResult_. The specified method then provides user feedback showing the dispatch model top intent, plus a ranked listing of all intents and entities that were detected.
@@ -383,9 +391,9 @@ If method `q_sample-qna` is invoked, it uses the user input contained within the
 
 ## Dispatch for user utterance to QnA Maker
 
-1. In the bot emulator, enter the text `hi` and submit the utterance. The bot submits this query to the dispatch LUIS app and gets back a response indicating which child app should get this utterance for further processing. 
+1. In the bot emulator, enter the text `hi` and submit the utterance. The bot submits this query to the dispatch LUIS app and gets back a response indicating which child app should get this utterance for further processing.
 
-1. By selecting the `LUIS Trace` line in the log, you can see the LUIS response in the bot emulator . The LUIS result from the dispatch LUIS app displays in the Inspector. 
+1. By selecting the `LUIS Trace` line in the log, you can see the LUIS response in the bot emulator . The LUIS result from the dispatch LUIS app displays in the Inspector.
 
     ```json
     {
@@ -417,10 +425,10 @@ If method `q_sample-qna` is invoked, it uses the user input contained within the
       }
     }
     ```
-
-    Because the utterance, `hi`, is part of the dispatch LUIS app's **q_sample-qna** intent, and is selected as the `topScoringIntent`, the bot will make a second request, this time to the QnA Maker app, with the same utterance. 
 
-1. Select the `QnAMaker Trace` line in the bot emulator log. The QnA Maker result displays in the Inspector. 
+    Because the utterance, `hi`, is part of the dispatch LUIS app's **q_sample-qna** intent, and is selected as the `topScoringIntent`, the bot will make a second request, this time to the QnA Maker app, with the same utterance.
+
+1. Select the `QnAMaker Trace` line in the bot emulator log. The QnA Maker result displays in the Inspector.
 
 ```json
 {
@@ -444,14 +452,17 @@ If method `q_sample-qna` is invoked, it uses the user input contained within the
 
 ## Resolving incorrect top intent from Dispatch
 
-Once your bot is running, it is possible to improve the bot's performance by removing similar or overlapping utterances between the dispatched apps. For example, let's say that in the `Home Automation` LUIS app requests like "turn my lights on" map to a "TurnOnLights" intent, but requests like "Why won't my lights turn on?" map to a "None" intent so that they can be passed on to QnA Maker. These two utterances are too close for the dispatch LUIS app to determine if the correct child app is the LUIS app or the QnA Maker app.
+Once your bot is running, it is possible to improve the bot's performance by removing similar or overlapping utterances between the dispatched apps.
+<!--For example, let's say that in the `Home Automation` LUIS app requests like "turn my lights on" map to a "TurnOnLights" intent, but requests like "Why won't my lights turn on?" map to a "None" intent so that they can be passed on to QnA Maker. These two utterances are too close for the dispatch LUIS app to determine if the correct child app is the LUIS app or the QnA Maker app.
 
 When you combine the LUIS app and the QnA Maker app using dispatch, you need to do _one_ of the following:
 
-* Remove the "None" intent from the child `Home Automation` LUIS app, and instead add the utterances from that intent to the "None" intent in the dispatcher app.
-* Add logic in your bot to pass the messages that match the Dispatch LUIS app's "None" intent on to the QnA maker service. Compare the score of the Dispatch LUIS app's score and the score of the QnA Maker app. Use the highest score. This effectively removes QnA Maker from the Dispatch cycle. 
+- Remove the "None" intent from the child `Home Automation` LUIS app, and instead add the utterances from that intent to the "None" intent in the dispatcher app.
+- Add logic in your bot to pass the messages that match the Dispatch LUIS app's "None" intent on to the QnA maker service. Compare the score of the Dispatch LUIS app's score and the score of the QnA Maker app. Use the highest score. This effectively removes QnA Maker from the Dispatch cycle.
 
 Either of the above two actions will reduce the number of times that your bot responds back to your users with the message, 'Couldn't find an answer.'
+-->
+You can use the [Dispatch][dispatch-readme] command-line tool to test and evaluate your dispatch model.
 
 ### To update or create a new LUIS model
 
@@ -481,11 +492,13 @@ To delete QnA Maker resources:
 
 To improve services used in this sample, refer to best practice for [LUIS](https://docs.microsoft.com/azure/cognitive-services/luis/luis-concept-best-practices), and [QnA Maker](https://docs.microsoft.com/azure/cognitive-services/qnamaker/concepts/best-practices).
 
+<!-- Foot-note style links -->
 
 [howto-luis]: bot-builder-howto-v4-luis.md
 [howto-qna]: bot-builder-howto-qna.md
 
 [cs-sample]: https://aka.ms/dispatch-sample-cs
 [js-sample]: https://aka.ms/dispatch-sample-js
 
-[dispatch-readme]: https://aka.ms/botbuilder-tools-dispatch
+[dispatch-readme]: https://aka.ms/dispatch-command-line-tool
+<!--[dispatch-evaluate]: https://aka.ms/dispatch-command-line-tool#evaluating-your-dispatch-model-->