What is qna in bob?

The sample solution is called QnABot. The QnABot uses Amazon to give you answers to questions. Users can ask questions and get quick answers. QnABot can ask questions and process answers.

You can integrate voice and text chat into your applications with Amazon Lex. You can offer a hands-free voice interface to your users in their homes or workplace with the help of Amazon's voice service. QnABot has the best of both worlds.

QnABot uses the Amazon Elasticsearch Service and the Amazon Kendra to make your questions and answers searchable. Behind the scenes, the machine learning natural language search engine and the full-text search engine are used to find the answer to a question.

We'll show you how to do it in the following sections.

We'll show you how QnABot works, and give you some ideas for how you can make it better.

Click here to open the console.

You can launch your chatbot with the Stack Launch button.

The source code is available in our repository. To deploy QnABot to additional regions, follow the instructions in the README.

The QnABot Content Designer admin user can enter their email and password on the Parameters page.

When deployment in an Amazon region, set the LexBotVersion to 'LexV2 Only'.

The Review page can be displayed next to it.

To deploy QnABot, select the acknowledgment and create stack.

The master CloudFormation stack uses nested stacks to create resources.

The master stack Output tab shows when the deployment is over.

You will receive an email with the subject "QnABot Signup Verification Code" You can use the generated temporary password to log in to your account.

Your new password must be at least 8 characters long and contain upper-case and lower-case characters, plus numbers and special characters.

Before you turn QnABot over to your users, you need to load question and answer data using the Content Designer. Your data is stored in a place called Amazon. The data can be searched later when users ask questions using either a hands-free device or an Amazon Lex client.

The steps that follow show you how to use sample questions to demonstrate the features of the QnABot. Substitute your own content when you want.

You can launch QnABot from a browser on your computer, phone, or tablets.

QnABot can be used with any Amazon device, including the Amazon FireTV, to give your users answers to questions from your content.

The QnABot can be enabled by using an Amazon skill.

We've provided instructions because QnABot can't automatically create the skill at this time. Log in to the QnABot Content Designer, and choose the voice assistant from the menu.

Follow the instructions to create a skill in your Amazon account. It will take a few minutes.

Even if you don't have an Amazon device, you can test your new skill in the Developer Console.

If you want to make your QnA skill accessible to other users, you can submit it for certification. Unpublished skills are only accessible to those who have an Amazon account, while published skills are available to everyone.

You can add image attachments to your answers that can be displayed on a user's touch screen, or on the website of your choice, such as the Amazon Web Client. Images can be used to depict places and products relevant to the question.

Host your images on Amazon S3 or a photo sharing service.

You can use QnABot to create beautiful rich text versions of your answers for display on the WebUI client or on the Slack platform. Content Designer has a field called the 'Alternate Markdown answer'.

Our webUI supports Markdown.

The latest version of QnABot gives you more control over the speech generation.

Content Designer can be used to populate the 'SSML answer' field.

SSML answers give you control over the voice responses.

You can use both SSML and Markdown to get QnABot to say one thing while displaying another. This feature can be used to deliver short answers while using the webUI to display rich, illustrated answers.

QnABot remembers the topic from the last question you asked, so you can ask follow-up questions.

The answer depends on the context. You can use this feature by assigning a value to the Topic field.

Adding buttons to your answers will help your user figure out what to do next. You attach buttons to response cards. Let's try it

Make your answers engaging and light as you define your content. Try to keep your style consistent.

Images can be used to improve verbal answers. Make your bot friendly with flourish.

For example, teach it how to reply to achat.

This is easy to try.

You should teach QnABot to respond with instructions when your users say Help.

QnABot now lets you use Handlebars templates in your answers so you can include variable substitution and conditional elements.

Let's use a simple example to show the concept.

QnABot users can use the Chatbot WebUI to log in.

When users are verified, the chatbotUI adds a signed token as a session attribute. QnABot uses the token to make additional user attributes available, such as Given Name, Family Name, and Email address.

You can do more with handlebars, such as randomly selecting content from a list, setting and accessing session attributes, and generating S3 presigned URLs. The Handlebars_READMe.md is in the repository.

Content Designer allows you to specify your own hook function for any item.

QnABot will call your function when the item is matched to a user's question, if you specify the name of the function in the Lambda Hook field. Your function can run code to integrate with other services and perform actions.

QnABot has a simple function example that you can use.

To see more information about creating your own hook functions, choose the Lambda Hooks from the Content Designer tools menu.

You can package lambda hooks in your own copy of the QnABot repository.

For more information on using QnABot, see the README.

QnABot can be more accurate when answering questions via Amazon Elasticsearch and can admit more readily when it doesn't know the answer. When Amazon kendra is used to find answers,Keyword filters do not apply.

The part of speech that applies to each word you say is determined by using Amazon Comprehend. By default, nouns, verbs, and interjections are used as 'keywords'.

Any answer returned by QnABot must have questions that match the words used.

If QnABot can't find any answers that match the rules, it will admit that it doesn't know the answer and will guess an answer that doesn't match the rules.

You can see the questions that QnABot can't answer in the dashboard, but we'll show you a little later.

If the feature causes problems for you, you can either modify its settings or disabling it altogether.