Implementation of a Contextual Chatbot in PyTorch.

Simple chatbot implementation with PyTorch.

• The implementation should be easy to follow for beginners and provide a basic understanding of chatbots.
• The implementation is straightforward with a Feed Forward Neural net with 2 hidden layers.
• Customization for your own use case is super easy. Just modify intents.json with possible patterns and responses and re-run the training (see below for more info).

The approach is inspired by this article and ported to PyTorch: https://chatbotsmagazine.com/contextual-chat-bots-with-tensorflow-4391749d0077.

Watch the Tutorial

Installation

Create an environment

Whatever you prefer (e.g. conda or venv)

mkdir myproject
$ cd myproject
$ python3 -m venv venv

Activate it

Mac / Linux:

. venv/bin/activate

Windows:

venv\Scripts\activate

Install PyTorch and dependencies

For Installation of PyTorch see official website.

You also need nltk:

pip install nltk

If you get an error during the first run, you also need to install nltk.tokenize.punkt: Run this once in your terminal:

$ python>>> import nltk>>> nltk.download('punkt')

Usage

Run

python train.py

This will dump data.pth file. And then run

python chat.py

Customize

Have a look at intents.json. You can customize it according to your own use case. Just define a new tag, possible patterns, and possible responses for the chat bot. You have to re-run the training whenever this file is modified.

{ "intents": [ { "tag": "greeting", "patterns": [ "Hi", "Hey", "How are you", "Is anyone there?", "Hello", "Good day" ], "responses": [ "Hey :-)", "Hello, thanks for visiting", "Hi there, what can I do for you?", "Hi there, how can I help?" ] }, ... ]}