Robots taking over the world is a scenario Hollywood has used in Sci-Fi storylines for generations. But in the modern-day technology sector, bots are an everyday encounter. The Azure Bot Service on the Microsoft Bot Framework transforms the ways a developer designs, deploys and manages bots. Whether you are building a chatbot or a productivity bot, there are specific steps vital to the process.
Let us uncover the core components of building an intelligent, human-like bot on the Azure Bot Service.
Building AI Experiences with the Microsoft Bot Framework
The Microsoft Bot Framework provides tools to develop, test, launch, and manage intelligence bots in one location. By harnessing the modular and extensible framework provided by the software development kit (SDK), templates, tools, and AI services, developers can create bots that use speech, understand natural language, handle question dialogue, and more.
What is a Bot?
A bot is a piece of software that provides an experience that feels less like interacting with a computer and more like connecting with a human, or a highly intelligent robot. Bots can help us with simple, repetitive tasks such as gathering profile information or taking reservations by shifting these tasks to an automated system that does not require human intervention. Bots use text, interactive cards, and speech to interact. An interaction can be a quick question or an intelligent conversation, but either way, the bot can provide access to essential services.
Bots are very similar to modern web applications as they live on the internet and use APIs to send and receive messages. Advanced bot software depends on a stack of technology and tools to deliver complex experiences on a wide variety of platforms. However, a simple bot could receive a message and echo it back to the user with very little code involved. This example clearly illustrates that what is in a bot heavily depends on what kind of bot it is.
The Bot Lifecycle: Five Steps for Using the Azure Bot Service
It is vital to remember that not all bots are created the same way. But developers who use the Azure Bot Service to build these interactive, human-like creations follow five core components to drive the process. Whether a developer is building a chatbot with Azure or a productivity bot, they include these five steps to bring their creation to life and manage it along the way.
There are many factors developers need to consider while designing a bot. Various components need prioritization when creating your bot to maximize the odds that a bot will achieve its goal of attracting and keeping users. How “smart” the bot is, how much natural language the bot supports, and its voice does not necessarily guarantee its success. But its ability to efficiently solve the user’s problem with minimal steps, its ability to solve a user’s issue better/easier/faster than other experiences, and its discoverability and flexibility significantly impact the bot’s success.
Build and Develop
Once a developer outlines the bot’s design and understands the factors that need to be included, you can begin to build and develop your creation. This step is to decide the primary function of your bot, write adaptive dialogs, implement authentication, and apply specific skills. Each feature and factor come together to make your vision a reality. You can find C#.NET and Node.js Samples on the Bot Framework site.
Test and Debug
One of the most critical steps in the process is to test and debug the bot after development before deploying. This step ensures that the chatbot built with Azure can carry a conversation, or the productivity bot can complete the task you need all in a clear, concise manner. There are many methods developers use to debug a bot. With the Azure Bot Framework, they can use an integrated development environment (IDE) such as Visual Studio or Visual Studio Code. Additionally, they can deploy the bot to Azure to test in Web Chat.
Manage and Connect
The bot lifecycle does not merely begin and end with deployment. Management and connection are essential to the longevity and sustainability of a bot. After deploying a bot to Azure, developers can use bot analytics, an extension of Application Insights. Application Insights provides conversion-level reporting on the user, message, and channel data. This information is crucial when learning how to manage a bot and make improvements. A way to improve the functionality of the bot is to connect it to channels. A channel is a connection between the bot and communication apps, making it more accessible and useful for the user.
Building bots is not for everyone, but together with a Microsoft partner, you can harness the Azure Bot Framework’s wide-breadth of capabilities.