• Post category:StudyBullet-17
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Mastering Chatbots with Botpress, Rasa3 & LLMs Flowise
All you need to develop your next AI Chatbot using Open-Source tools like Botpress, Rasa, Transformers and FastAPI

What you will learn

Developing Chatbots using Open-Source tools like Botpress, Rasa and Transformers. No cloud based solutions.

Understand all of the Chatbot developing pillars like intent-detection, entity-recognition, conversation flow and more.

Learn the Concepts of Prompt Engineering using LangChain, ChatGPT and HuggingFace

Develop Neural Networks models to detect entities and Recognize entities in the user messages.

Integrate with third parties and APIs to develop mature chatbots with live data.

Develop web applications using fastAPI to support the chatbot services.

Learn via developing a set of real-world chatbot projects.

Description

Are you ready to learn how to build powerful and AI-supported chatbots from scratch?

there are a lot of courses out there that teach you how to develop chatbots. So what makes this course DIFFERENT?

  • We’re NOT going to use any cloud-based chatbot solutions like Dialogflow, IBM Watson, or Microsoft Azure. Instead, we’ll be focusing on free and open-source technologies that are just as robust and powerful.
  • We’re NOT just going to talk only about the basics of chatbot development. We’re going to dive deeply into this world.
  • This course is full of project-based tutorials. A lot of techniques will be derived via developing a set of chatbot projects

Chatbots are everywhere and are becoming an increasingly important part of our daily lives. They’re used for a wide range of applications, from customer service to online shopping, and they’re only getting more advanced and sophisticated.


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In the course, we delve into the different types of chatbots and their use cases, including rule-based chatbots, AI-powered chatbots, and conversational AI. We also cover the various technologies and platforms that are used to build chatbots, such as natural language processing (NLP), machine learning (ML), and chatbot development open-source projects like Botpress, Rasa, Transformers, langChain, fastAPI, Docker, and more.

In this course, you will learn:

  • How to Setup Your Development Environment Tools
  • How to Install and start your first Botpress project
  • You will Understand what the conversation flow studio is
  • Develop the different types of chatbot response templates
  • You will learn how to Integrate with third parties and APIs to provide external information for users
  • How to Develop a QnA chatbots
  • Understand the problem intent detection and how to solve it using either rule-based or neural network techniques
  • How to recognize entities in the user message and how to fill the slots.
  • How to collect user data and forward them to an external API or store them in a database.
  • How to develop your Rasa Chatbot Assistant models
  • How to integrate Botpress with Rasa Chatbot Assistant
  • How to develop a fastAPI app to serve your AI projects
  • How to integrate your chatbot with popular messaging platforms like Facebook Messenger and Telegram
  • How to use the modern Large Language Models (LLMs) like OpenAI to support your chatbots
  • Learn all the basics of building a robust application using ChatGPT and open-source Large Language Models
  • How to use Drage-Drop UI Tools like Flowise to Develop LLM chatbots
  • How to use LLMs to develop AIΒ Engines and Chatbots
  • More ..

By the end of the course, students will have a comprehensive understanding of the current state of chatbot technology and how it is being used in real-world applications. This knowledge will equip students with the skills and confidence to embark on their chatbot projects and contribute to the rapidly evolving field of conversational AI.

English
language

Content

Course Introduction

Course Introduction
Install Botpress Locally (faster & optional)

Installing Docker

Introduction
Install Docker – Ubuntu
Install Docker – Windows
Using of WSL – Windows
Docker Files

Setup Basic Tools

Setup MiniConda
Setup JupyterLab
How to use JupyterLab
Conclusion

BotPress Basics

Introduction
Why to Use BotPress
Setup BotPress
Your First Chatbot
Hello Buddy Chatbot – Part 1/2
Hello Buddy Chatbot – Part 2/2
Variable Types
Conclusion

USA Population Chatbot

Introduction
API Supported Chatbot
Data Validation Action
Debugging Action Logs
Sub Flows
Choices Skill
Conclusion

API Actions

Develop an API Action
Custom Fallbacks

Response Templates

Introduction
Texts and Images
Cards
Carousels
Files
Dropdown Menus
Videos
Conclusion

Questining and Answering (QnA) Chatbots

Introduction
Feeding Inputs
Train the QnA Chatbot
Exporting and Importing Training Data
Rich Answers
Conclusion

Botpress NLU Engine

Introduction
Introduction to Intent and Entity Recognition
Botpress Intent Dection
Botpress Entity Recognition
Conclusion

Restaurant Survey Chatbot

Introduction
Basic Chatbot Developing- Part 1/4
Basic Chatbot Developing- Part 2/4
Basic Chatbot Developing- Part 3/4
Basic Chatbot Developing- Part 4/4
Setup PgAdmin
Setup Feedbacks Database
Storing Feedbacks into Database 1/2
Storing Feedbacks into Database 2/2
Conclusion

NLP Basics

Introduction
Introduction to Neural Networks
Introduction to Text Representation
Conclusion

Rasa NLU

Introduction
Why Rasa
Introduction to Intent and Entity Recognition
Rasa Data Architecture
Rasa Dataset 1/3
Rasa Dataset 2/3
Rasa Dataset 3/3
Train a Rasa Model
Conclusion

Football Chatbot 1/2

Introduction
What will you build ?
How to Plan the Project ?
Train Rasa Model
FastAPI Project 1/6
FastAPI Project 2/6
FastAPI Project 3/6
FastAPI Project 4/6
FastAPI Project 5/6
FastAPI Project 6/6
Conclusion

Football Chatbot 2/2

Introduction
Botpress Chatbot 1/6
Botpress Chatbot 2/6
Botpress Chatbot 3/6
Botpress Chatbot 4/6
Botpress Chatbot 5/6
Botpress Chatbot 6/6
Conclusion

Prompt Engineering using LangChain | Basic Concepts

Introduction
Introduction to Machine Learning
Base and Instruction-Tuned Large Language Models
Introduction to Tokenizers
Why LangChain?
How to use Google Colab

Prompt Engineering using LangChain | ChatGPT and HuggingFace

How to load OpenAI models
How to load HuggingFace Models
Calculate your tokens
Hide your secrets
Conclusion

Prompt Engineering using LangChain | Templates (In progress)

Prompt Templates

Messaging Platforms Integration

Introduction
Botpress Integration
Setup Ngrok – Ubuntu
Setup Ngrok – Windows
Facebook Integration
Telegram Integration
Website Integration
Conclusion