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14.nlp-with-dispatch

README.md

This sample shows how to integrate QnA Maker in a simple bot with ASP.Net Core 2 and Application Insights.

Concepts introduced in this sample

Dispatch is a tool to create and evaluate LUIS models used for NLP (Natural Language Processing). Dispatch works across multiple bot modules such as LUIS applications, QnA knowledge bases, and other NLP sources (added to dispatch as a file type). Use the Dispatch model in cases when:

  • Your bot consists of multiple modules and you need assistance in routing user's utterances to these modules and evaluate the bot integration.
  • Evaluate quality of intents classification of a single LUIS model.
  • Create a text classification model from text files.

The Language Understanding Intelligent Service (LUIS), is a machine learning-based service to build natural language into apps, bots, and IoT devices. LUIS allows to Quickly create enterprise-ready, custom models that continuously improve.

The QnA maker Service enables you to build, train and publish a simple question and answer bot based on FAQ URLs, structured documents or editorial content in minutes.

The Application Insights enables you to discover actionable insights through application performance management and instant analytics.

In this sample, we demonstrate how to use the Dispatch service to route utterances when there are multiple LUIS models and QnA maker services for different scenarios supported by a bot. In this case, we configure dispatch with multiple LUIS models for conversations around home automation and weather information, plus QnA maker service to answer questions based on a FAQ text file as input.

To try this sample

  • Clone the samples repository
git clone https://github.com/Microsoft/botbuilder-samples.git

Install BotBuilder tools

  • In a terminal, navigate to the samples folder (botbuilder-samples/samples/csharp_dotnetcore/14.nlp-with-dispatch)

    cd botbuilder-samples/samples/csharp_dotnetcore/14.nlp-with-dispatch

  • Install required tools - to successfully setup and configure all services this bot depend on, you need to install the MSBOT, LUIS, QnAMaker, Ludown, Dispatch CLI tools.

    Ensure you have Node.js version 8.5 or higher

    npm i -g msbot luis-apis qnamaker ludown botdispatch

  • Configure required LUIS, QnA Maker and Dispatch services. See here

Configure Services

This sample relies on LUIS, QnA Maker and Dispatch services.

Deploy this bot to Azure and configure services

You can use the MSBot Bot Builder CLI tool to clone and configure any services this sample depends on.

To install all Bot Builder tools -

Ensure you have Node.js version 8.5 or higher

npm i -g msbot chatdown ludown qnamaker luis-apis botdispatch luisgen

Creating a .bot file

To create a .bot file, type the following while in the 14.nlp-with-dispatch/ folder:

msbot init --name "<NAME>" --endpoint http://localhost:3978/api/messages

Note: Where "<NAME>" is the name of your choosing. For this walkthrough, the name used is the name of this sample: "nlp-with-dispatch".

Then set the "botFilePath" value in appsettings.json with the name of your .bot file.

After creating the .bot file, it is recommended to change the name of the endpoint service from the name of the bot to "development". This is for local development and testing purposes. An example of the modified "endpoint"-type service can be found below:

{
    "type": "endpoint",
    "name": "development",
    "endpoint": "http://localhost:3978/api/messages",
    "appId": "",
    "appPassword": "",
    "id": "173"
}

To clone this bot, perform the following:

  • Collect your Luis Authoring Key from the LUIS portal by selecting your name in the top right corner. Save this key for the next step.

  • Run the following command from the project directory:

msbot clone services --name "<NAME>" --luisAuthoringKey "<YOUR AUTHORING KEY>" --folder "DeploymentScripts/MsbotClone" --location "ie, westus" --appId <YOUR APP ID> --appSecret <YOUR APP SECRET PASSWORD>

NOTE: You can obtain your appId and appSecret at the Microsoft's Application Registration Portal

NOTE: By default your Luis Applications will be deployed to your free starter endpoint. An Azure LUIS service will be deployed along with your bot but you must manually add and publish to it from the luis.ai portal and update your key in the .bot file.

  • Note the generated secret generated by msbot.
  • The secret key is used later in for the emulator and configuration.
The secret used to decrypt <NAME>.bot is:
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX=
NOTE: This secret is not recoverable and you should store this secret in a secure place according to best security practices.
Your project may be configured to rely on this secret and you should update it as appropriate.

  • Inspect Bot configuration file.

  • The msbot clone command above generates a bot configuration file.

  • The name of the bot configuration file is .bot, where is the name of your bot used in the msbot clone step.

  • The configuration file can be loaded by the Microsoft Bot Framework Emulator.

  • Update NlpDispatchBot.cs

    • Update Line 40: "DispatchKey":

      Update the following line to add a prefix with the name of your bot (plus underscore '_').

      private const string DispatchKey = "<NAME>_nlp-with-dispatchDispatch";

    • Update Line 30, "HomeAutomationLuisKey":

      Update the following line to add a prefix with the name of your bot (plus underscore '_').

      private const string HomeAutomationLuisKey = "<NAME>_Home Automation";

    • Update Line 35, "HomeAutomationLuisKey":

      Update the following line to add a prefix with the name of your bot (plus underscore '_').

      const WEATHER_LUIS_CONFIGURATION = '<NAME>_Weather';

Alternately you can configure the required services by following the steps below.

Manually configure required services

Configure the LUIS service

To create LUIS Subscription Keys for this bot, follow these instructions.

To create required LUIS applications for this sample bot,

  • Create an account with LUIS. If you already have an account, login to your account.
  • Click on your name on top right corner of the screen -> settings and grab your authoring key.

To create the LUIS application this bot needs and update the .bot file configuration, in a terminal,

  • Clone this repository
  • Navigate to botbuilder-samples/csharp_dotnetcore/samples/14.nlp-with-dispatch
  • Run the following commands
ludown parse toluis --in Resources/homeautomation.lu -o CognitiveModels --out homeautomation.luis -n "Home Automation" -d "Home Automation LUIS application - Bot Builder Samples" --verbose

ludown parse toluis --in Resources/weather.lu -o CognitiveModels --out weather.luis -n Weather -d "Weather LUIS application - Bot Builder Samples" --verbose

luis import application --in CognitiveModels/homeautomation.luis --authoringKey <LUIS-AUTHORING-KEY> --region <LUIS-AUTHORING-REGION> --msbot | msbot connect luis --stdin

luis import application --in CognitiveModels/weather.luis --authoringKey <LUIS-AUTHORING-KEY> --region <LUIS-AUTHORING-REGION> --msbot | msbot connect luis --stdin

If you decide to change the names passed to msbot such as weather.luis, then you need to update the constants in NlpDispatchBot.cs. For example, if you change homeautomation.luis to just home, you would update the HomeAutomationLuisKey variable to "home" and the homeAutomationDispatchKey to the intent name assigned by dispatcher, which in this case will be "l_home".

Note: You can create the LUIS applications in one of the LUIS authoring regions. You can use a different region, such as westus, westeurope or australiaeast via https://LUIS-Authoring-Region.api.cognitive.microsoft.com/luis/api/v2.0 in the commands above.

Train and publish the LUIS models

You need to train and publish the LUIS models that were created for this sample to work. You can do so using the following CLI commands

msbot get "Home Automation" | luis train version --wait --stdin
msbot get "Weather" | luis train version --wait --stdin 
msbot get "Home Automation" | luis publish version --stdin
msbot get "Weather" | luis publish version --stdin

Configure QnA Maker service

To create a new QnA Maker application for the bot,

  • Follow instructions here to create a new QnA Maker Azure resource.
  • Navigate to your QnA Maker resource -> keys and copy the subscription key

To create the QnA Maker application and update the .bot file with the QnA Maker configuration,

  • Open a terminal
  • Navigate to samples/csharp_dotnetcore/14.nlp-with-dispatch
  • Run the following commands
ludown parse toqna --in resources/sample-qna.lu -o cognitiveModels --out dispatch.qna --verbose

qnamaker create kb --in cognitiveModels/dispatch.qna --subscriptionKey <QNA-MAKER-SUBSCRIPTION-KEY> --msbot | msbot connect qna --stdin

Train and publish the QnA Maker KB

You need to train and publish the QnA Maker Knowledge Bases that were created for this sample to work. You can do so using the following CLI commands

msbot get "sample-qna" | qnamaker publish kb --stdin

Configure the Dispatch application

Dispatch is a CLI tool that enables you to create a dispatch NLP model across the different LUIS applications and / or QnA Maker Knowledge Bases you have for your bot. For this sample, you would have already created 2 LUIS applications (Home Automation and Weather) and one QnA Maker Knowledge base.

To create a new dispatch model for these services and update the .bot file configuration, in a terminal:

  • Navigate to samples/csharp_dotnetcore/14.nlp-with-dispatch
  • Run the following commands
dispatch create -b nlp-with-dispatch.bot | msbot connect dispatch --stdin
  • Then update the dispatch service in your bot to have a "subscriptionKey". You can use the subscription key from one of the other LUIS services in the .bot file.

Securing keys in your .bot file

Since your .bot file contains service Ids, subscription and authoring keys, its best to encrypt them. To encrypt the .bot file, run

msbot secret -n

Then set the "botFileSecret" value in appsettings.json with the secret output from msbot secret -n.

This will generate a strong key, encrypt the bot file and print the key. Please keep this key securely. Any time the bot file is encrypted, make sure to set the botFileSecret environment variable this sample relies on (either through the .env file or other means).

Running Locally

Visual Studio

  • Navigate to the samples folder (botbuilder-samples/samples/csharp_dotnetcore/14.nlp-with-dispatch) and open NLP-With-Dispatch-Bot.csproj in Visual Studio
  • Select the "NLP-With-Dispatch-Bot" from the dropdown menu of Startup Projects
  • Run the project (press F5 key)

.NET Core CLI

  • Install the .NET Core CLI tools.
  • Using the command line, navigate to botbuilder-samples/samples/csharp_dotnetcore/14.nlp-with-dispatch folder
  • type dotnet run

Testing the bot using Bot Framework Emulator

Microsoft Bot Framework Emulator is a desktop application that allows bot developers to test and debug their bots on localhost or running remotely through a tunnel.

  • Install the Bot Framework Emulator from here.

Connect to bot using Bot Framework Emulator V4

  • Launch Bot Framework Emulator
  • File -> Open bot and navigate to botbuilder-samples/samples/csharp_dotnetcore/14.nlp-with-dispatch folder
  • Select nlp-with-dispatch.bot file

Further reading