This is my implementation of chatbot, based on the methods that were mentioned in this article ⬇️
Build Your First Python Chatbot Project
To implement the chatbot, I will be using Keras (which is a Deep Learning library), NLTK (which is a Natural Language Processing toolkit), and some helpful libraries.
Project File Structure:
Train_chatbot.py — In this file, we will build and train the deep learning model that can classify and identify what the user is asking to the bot.
Gui_Chatbot.py — This file is where we will build a graphical user interface to chat with our trained chatbot.
Intents.json — The intents file has all the data that we will use to train the model. It contains a collection of tags with their corresponding patterns and responses.
Chatbot_model.h5 — This is a hierarchical data format file in which we have stored the weights and the architecture of our trained model.
Classes.pkl — The pickle file can be used to store all the tag names to classify when we are predicting the message.
Words.pkl — The words.pkl pickle file contains all the unique words that are the vocabulary of our model.