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In today’s modern era of Artificial Intelligence and
Serverless computing, “BOT” is one of the most buzz term. We have been using
BOTs for quite a long but still, if the term is unfamiliar to you, you might
ponder what it is and how it works precisely. In simple terms, BOT is an
intelligent and smart program designed to perform robotized tasks. In this article, I am going to articulate on how to
fabricate a QnA (FAQ) ChatBot leveraging Azure BOT Service and QnA Maker – a
Microsoft Cognitive service and consume the chat Bot in SharePoint Online
environment. QnA Bot effectively processes questions from the end user,
searches up for a matching question (require not be exact) in the knowledge
base, retrieves the appropriate response with the highest score and sends it
back to the end client. Despite the fact that the question asked by a person
isn’t the very same way it is put away in the information base, the BOT is
sufficiently wise to coordinate the answer in the source and give answers in
like manner. However, if the BOT doesn’t discover a match in the mapped
knowledge base, it will answer back with a pre-defined “No match message”. As stated above, I will consume QnA Maker Cognitive Service
to build the QnA Bot. Briefly, QnA Maker is a web-based Microsoft Cognitive
Services that trains AI to reply to any questions in a conversational pattern.
It basically provides an FAQ data source/knowledge base with a predefined set
of FAQ data, which can be queried from BOT/ Application. The knowledge base
content is stored in Azure Storage by the QnA Maker tool. Now we have a brief understanding of what is QnA Bot and QnA
Maker service. Let’s follow the below steps and build the BOT, and consume it
in SharePoint Online. This will give us the practical handle of the process. The first step in
this process is to create and nourish the FAQ Data source/ knowledge base for
the BOTLet’s navigate to QnA Maker
web portal and login with your Microsoft Live account to create a QnA
service and the knowledge base. In the portal, click on “Create a new service”
menu link. This will open a form to fill in the details of the service·        
Name of the service·        
FAQ data source/knowledge base in the below
You can directly enter the public website URL of
an existing FAQ pageb.      
You can upload a file/questionnaire with
questions and answers by clicking on “Select file”. The information about restricted
file format and size is displayed in the form.c.      
You can do either of the above (a or b) or both
or multiple websites or multiple files or you don’t have to do either and just
type questions and answers from scratch. It’s completely up to you. You can create
questions and answers post creation of the service.

Once the service is created, you will be presented with the
below screenFollow the steps as mentioned in the above figureStep 1: Click on
“+Add new QnA pair”. This will enable the placeholder to add new questions and
answers to the knowledge baseStep 2: Add
question and answer pairsStep 3: Click on
“Save and retrain”. This will extract data and train the knowledge baseStep 4: This will
publish and push the changes. Before publishing the changes, verify if you are
getting correct responses from your knowledge base

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To verify the knowledge base, click on “Test” link in the
left navigation. Let’s consider the question “Can you help me finding a manual related to semiconductors?” Lets’
type the question as “find manual”. Even though this doesn’t match the exact
question what is stored in the knowledge base, the BOT is intelligent enough to
find a match and reply back. If the BOT doesn’t find any suitable answer in the
knowledge base, it extracts all answers which it thinks are relevant and list
down the questions to the end user.Post verification of the knowledge base you can publish it.
Once published, a summary screen of the count of questions and answers will be
displayed. Even you will be provided an option to view the differential data of
your knowledge base

Click on Publish in the summary screen will deploy the knowledge
base for the service and the HTTP endpoint for the service will be exposed. The
end-point can be consumed in a Bot/Application to process a question and
respond accordingly In the above figure, we can see the end-point for the
service. Also, this provides the knowledgebase ID and subscription key for the
service. Make a note of these IDs, which will be required in the further steps
while creating the BOTSo, we are done with the creation of the knowledge base for
the BOT. Let’s go ahead and
create the BOT using Azure BOT ServiceLogin to Azure Portal,
search for “Web App BOT” in the Azure marketplace and click on “Create”

This will open-up a form and ask us to enter the details for
the BOT. Enter the details accordingly and select the template for the BOT as “Question and Answer”. You can select
the pricing tier as F0 as we are creating a Demo Bot.Once you enter all required details, click on Create, which will
allow the BOT to use QnA template. Before testing the BOT, we need to feed the
Knowledge Base ID and Subscription Key (that I mentioned before) of my QnA
Service to the BOT.

Navigate to the Demo BOT App that you created in the above
step. To feed the QnA service details to the BOT, click on “Application
Settings” link from the left links blade.In the above figure, you can see keys: QnAKnowldegebaseId and QnASubscriptionKey,
enter the values (that we have noted before) for the keys and click on Save

We are done with the set-up and all configurations. Now we
can test the BOT in web chat. To do so, click on “Test in a Web Chat” from left
links blade and let’s consider the same question that we have used for
verifying the knowledge base – “Can you
help me finding a manual related to semiconductors”In the above dialog code, if we set the last optional
parameter ‘top’ to some value greater than 1, the QnA Maker utilizes active
learning to learn from the utterances that come into the framework. In this process,
QnA Maker responds with different pertinent QnAs for low certainty situations
and requests that end user stamp the right response. The end user feedback is
logged and models are refreshed once the system has assembled enough
illustrations. Users will be able to see enhanced response based on the
feedback received. However, if this value is not set or set to 1, the Bot responds
back the answer with the highest score.Let’s say we need to respond back to questions with a multi-line
of description and images, we can trim the data accordingly in the knowledge
base. Accordingly, we can customize the Dialog Code of the Bot to manipulate
the data received from the knowledge base and respond back to end userFollow the below
steps to integrate the BOT in SharePoint Online

Navigate to the above created Web App Bot in the Azure
Portal. Click on “Channels” in the left blade. This Bot can be connected to all
channels displayed over here. This also gives the provision to configure web
chat. Click on “Get Bot embed codes”, will open a pane with the embed code.The iframe src URL has a secret token parameter. Click on
“Show” for the first secret code, copy it and append it to the iframe src URL

Now, add a content editor or script editor web part in a
page in your SharePoint Online portal. Embed the above iframe code in the web
part and publish the page. We are all done now! The QnA bot will be now
rendered in the page on your SharePoint Online site.We can also customize the display of the BOT to expand and
collapse accordingly.

Finally, we are done! Is it not interesting? We can make it
even more interesting by integrating other fabulous Azure Cognitive Services
like Vision, Speech and Language and Machine Learning. So, now you can have
your own QnA bot up and running and play around with the Bot. 

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