Educational Chatbot (Rasa NLU-Rasa Core) Test phase, srs, design phase and source code final deliverable
Project Domain / Category
Web Application, Artificial Intelligence, Machine Learning
Abstract / Introduction
In online educational system, students need answers related to their queries about programming courses urgently. So it is required to have a chatbot in each course that could answer queries related to course material from its intelligence. For such type of chatbot, there must be an automated system behind it, that works like a brain of teacher and give correct answers. Python is a high level programming language, that is taught as introductory courses of programming at undergraduate level of Computer Science and Information Technology universities. Students of this projects are required to build this chatbot as a web application that could answers students queries related to their course theoretically. Coding examples are not required at this level.
Functional Requirements:
- Chatbot Interface:
Students will build a GUI( Graphical User Interface) which shows interface like given in screen shot here.
Answers to queries should be correct according to the fundamentals and its accuracy must be mentioned.
Rasa framework is to use Rasa NLU (Natural language understanding), Rasa Core and other features of Rasa for classification, training and testing model.
Visit this website for complete documentation and designing and logic’s for Rasa models..
- User Role
User will write his/her query in chatbot about C++ concepts theoretically and will get reply from chatbot in this chatbot.
- Chatbot Role
Chatbot will get the message from input box and builds Rasa NLU and Rasa Core models and pretrain these models to pick correct reply for this input and then perform test to know accuracy of models. Then answer the query of user by getting correct answer from back-end Rasa models.
- Building of Chatbot
- Training
Take 70% of data for training.
Write complete code in python from scratch.
Write all the methods used for training like tokenizer, entity extractor, classifier etc and train the model.Also include required libraries to use those methods.
Check accuracy of the model.
- Testing
Take 30% of remaining data for testing of models. Check accuracy of the model.
- Execution
Build front end of chatbot using any tool of GUI and attach it with back-end. User will ask questions and chatbot will reply answers using this front end. Supporting material:
- Take data for training and testing only from mentioned chapters of given book (download from given link)
Chapter No. Title…………………………………..……………………Page No
Chapter 1. Introduction to Programming……………………………………. 69
Chapter 1. Introduction to Programming……………………………………. 69
Chapter 2. Primitive Types and Variables …………………………………. 111
Chapter 3. Operators and Expressions ……………………………………… 139
Chapter 4. Console Input and Output ………………………………………. 165
Chapter 5. Conditional Statements ………………………………………….. 195
Chapter 6. Loops ………………………………………………………………….. 211
Chapter 7. Arrays …………………………………………………………………. 235
Chapter 8. Numeral Systems ………………………………………………….. 265
Chapter 9. Methods ………………………………………………………………. 293 Chapter 11. Creating and Using Objects …………………………………… 385
Chapter 12. Exception Handling ……………………………………………… 415
Chapter 13. Strings and Text Processing ………………………………….. 457
Chapter 14. Defining Classes ………………………………………………….. 499
Chapter 16. Linear Data Structures …………………………………………. 641
Chapter 20. Object-Oriented Programming Principles ………………… 807
Chapter 21. High-Quality Programming Code ……………………………. 853
- Build Chatbot Using Rasa in Python https://www.youtube.com/watch?v=PmETWC1fkhY
Watch above given video to understand how Rasa chatbot is configured, work and execute.Which algorithms are used for tokenization , featurization, entity extraction,
classification and further processing.
- Helping Book to understand Python, Chatbot, Machine Learning, Artificial Intelligence concepts.
Tools:
Rasa Frame work(Rasa NLU, Rasa Core)
Tensor flow library
Python language,
HMTL, CSS and any styling tools for GUI
Supervisor:
Name: Neelam Alam
