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HTTP Methods and Webhooks

HTTP Methods and Webhooks: How Client-Server Interaction Works

Take all the best from the server!

During the lecture, you’ll learn the following:

  • HTTP methods in CRUD context
  • How, where and when to use HTTPs methods on the server
  • Status codes and their meaning
  • Introduction to webhooks

Enjoy your learning!

 

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Web development basics

In the first lesson, the student can learn how to build a very basic one-page website. This lesson is for you if you ever want to create simple chatbot, but also have no idea where to start. This is if you want a step by step overview on the basics.

No one can start learning web development without the right foundation. Learn these tips and let’s build the right basic chatbot together!

What will you learn from this lecture?

  • What is Node.js and it works?
  • How to initialize your Node.js project?
  • How to create “Hello world” Express.js server
  • Introduction to Express.js syntax

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Introduction

The Chatbot Development Process!

Chatbots.Studio created the course for developers and business owners to understand how to build chatbot in a  step by step manner.

Our chatbot developer shows you how to build conversational interfaces in messengers with a chatbot’s deep understanding of user intents and producing the relevant answer.

What will you take away from the course:

  • Recommendations for Node.js server and chatbot development
  • How to work with HTTP methods. What exactly is Webhook?
  • How to work with Git and GitFlow
  • What is .env? How to get the configuration for the local and production server.
  • How to work with MongoDB and Mongoose
  • Asynchrony in Node.js. Promises

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Stabilization Stage

The last part of the development process is stabilization. It is the stage when the system gets approved for deployment. The stabilizing phase conducts testing on a solution whose features are complete. The team focuses on resolving and triaging (prioritizing) bugs, environment defining and preparing the solution for release.

See in the video a detailed explanation for each of these activities.

Before implementation, we need to consider specific activities:

  • Define the launch approach
  • Execute conversational test cases and make the changes if applicable
  • Define specific environments for NLP Engine
  • Live agent training

 

See in the video a detailed explanation for each of these activities.

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Test Cases

The majority of the bots fail to recognize intents and thus respond appropriately to a user, so the creation of a correct test case to validate bot behavior is vital for project success. While developing standard positive and negative test cases, we invite you to consider the cases for dialog testing we presented in the video.   

 

See the next lesson Stabilization Stage

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Unit Tests. Onboarding Strategy

The outcome of the development stage is a software product that is ready for QA. In this chapter, we will focus on specific activities related to AI chatbot development. We would assume that the reader is familiar with industry standards in software development, and thus does not need to focus on that.

In this video, the speaker considers how to define a client’s onboarding strategy and unit tests. This provides some inspiration regarding possible sources in the video.

The bot architecture could be rather complex and it will have an integration with the many other systems that are generally connected via Rest APIs

One of the issues with such architecture is that the API could be changed and the user (bot or other system components) could not be notified about said change, and that could lead to issues that are hard to predict. That is specifically relevant when the component is not mature and its development is still in process.  

So our recommendation would be to cover the API with unit tests (in case you do not own it), so any issues related to changes in API could be quickly identified and addressed.

The majority of the bots fail to recognize intents and thus respond appropriately to a user, so the creation of a correct test case to validate bot behavior is vital for project success. While developing standard positive and negative test cases, we invite you to consider the cases for dialog testing we presented in video.  

 

See the next lesson Test Cases

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Technologies

Before chatbot development, there should be identified the NLP Engine, programming language, and database management system.

The full technical landscape is presented in the video. 

Conversational Engine component manages the conversational logic, maintain the session, route the conversation between interfaces. To play out these actions, developers could use the solutions Botkin, Botpress or use own by using the plain programming.

NLP Engine component defines intents (Natural Language Understanding), holds the context of the conversation. The possible solutions to implement mentioned actions are Luis, DialogFlow, Amazon Lex, Rasa.ai and Wit.ai.

Live agent component is a dedicated software which is used to handle the conversation takeover from the bot to real human. Such software should provide the interface for chatting with a user, history of conversation, the ability to support simultaneous conversation with several users and etc. FB, for example, has its own interface for live agents while unfortunately, it is lacking many enterprise features.

UI framework component presents a layer for the web bot and admin part. Angular and React are most commonly used options. If you are building web widget please you may use already existing components. We recommend our clients use https://telerik.com/conversational-ui

 

See the next lesson Unit Tests. Onboarding Strategy

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Decisions for AI

Everyone thinks that every chatbot includes Artificial Intelligence.  The one more important decision for envisioning is how much AI should be in the project.

In the video, the speaker explains in what cases the chatbot project should include or exclude Artificial Intelligence.

It could be a whole range starting from how pure the conversation is, the absence of limitations, all the way up to the free-flowing conversation.

The mixed chatbot has both – some controls and part of AI.

 

See the next lesson Technologies

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Phase Activities

During this phase, the team prepares the functional specification, works through the design process, and prepares work plans, cost estimates, and schedules for the various deliverables.

See details for each activity in the video below.

Before implementation of the project, we need to have a detailed plan which includes specification, requirements, technical tools that will be used, and the team that works on the project.

During this video and few next we will discuss a lot of specific activities that have to be accomplished for planning successful AI chatbot implementation:

  • Define the detailed conversation flow
  • Define the bot character
  • The approach to AI implementation
  • Define strategy for bot training
  • Gather corpus of data
  • Select development tools
  • Define requirements for integration
  • Select the live agent platform

 

See the next lesson Decisions for AI

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AI Existence in the Project

Everyone thinks that every chatbot includes Artificial Intelligence.  The one more important decision for envisioning is how much AI should be in the project.

In the video, the speaker explains in what cases the chatbot project should include or exclude Artificial Intelligence.

It could be a whole range starting from how pure the conversation is, the absence of limitations, all the way up to the free-flowing conversation.

The mixed chatbot has both – some controls and part of AI.

 

See the next lesson Phase Activities

 

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