In this Python project, we are going to build a chatbot using deep learning techniques. The chatbot will be trained on the dataset which contains categories (intents), pattern and responses. We use a special recurrent neural network (LSTM) to classify which category the user’s message belongs to and then we will give a random response from the list of responses.

1.Intents.json – The data file which has predefined patterns and responses.

2.train_chatbot.py – In this Python file, we wrote a script to build the model and train our chatbot.

3.Words.pkl – This is a pickle file in which we store the words Python object that contains a list of our vocabulary.

4.Classes.pkl – The classes pickle file contains the list of categories.

5.Chatbot_model.h5 – This is the trained model that contains information about the model and has weights of the neurons.

6.Chatgui.py – This is the Python script in which we implemented GUI for our chatbot. Users can easily interact with the bot.

Here are the 5 steps to create a new chatbot in Python from scratch:

1.Import and load the data file

2.Preprocess data

3.Create training and testing data

4.Build the model

5.Predict the response

To run the app:

1.python train_chatbot.py

2.python chatgui.py