The is only aim of the project is to learn by creating a chatbot, retrieval based, using NLTK, Keras, etc
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
Intents.json – The data file which has predefined patterns and responses.
train_chatbot.py – In this Python file, we wrote a script to build the model and train our chatbot.
Words.pkl – This is a pickle file in which we store the words Python object that contains a list of our vocabulary.
Classes.pkl – The classes pickle file contains the list of categories.
Chatbot_model.h5 – This is the trained model that contains information about the model and has weights of the neurons.
Chatapp.py – This is the Python script in which we implemented GUI for our chatbot. Users can easily interact with the bot with this.
- Go ./main directory
- Run
pip install -r requirements.txt - Run
python train_chatbot.py - Then Run
python chatapp.pyto start the chat server.
One of the main resource used in making this project was https://data-flair.training/blogs/python-chatbot-project/