zzj0402 / chatbot

Dialogflow Lumi chatbot interface exported as JSON files

Lumi Chatbot NLU

This project is part of the Lumi Chatbot initiative. Natural Language Understanding (NLU) module and chatbot interface.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

This project consideres only Unix based OSes, running Python 3.7.6 as the default Python version. A different version of Python might cause the requirements installation to fail. The rest of these instructions will consider the use of Linux Ubuntu 16.04. Follow the steps below to install the required packages to run the project.

1. Install Pip, Venv and Git

sudo apt-get update && sudo apt-get install -y python3-pip python3-venv git

2. Install Poetry

curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python

Installing

Please follow the step by step series of instructions below to get the development environment ready.

1. Clone repository

git clone [e-mail]:lumichatbot/chatbot.git lumi-chatbot

2. Install project dependencies

cd lumi-chatbot
poetry install

2. Activate project virtual environment

poetry shell

Training

The project comes with an initial training dataset for the demo, but after cloning the repo, you must train the model before running it.

cd nlu-engine
rasa train

Running

After installing and training the NLU model, use the command below to expose a Rest API for the frontend.

cd nlu-engine
rasa run --enable-api --debug

To access the NLU parse API you can use the command below.

curl -XPOST localhost:5005/model/parse -d '{ "text": "Hey Lumi, please block traffic for all students." }'

Alternatively, you can run the command below to test the trained NLU model locally

cd nlu-engine
rasa shell

Deployment

The steps below describe how to easily run a deployment environment of the NIKSUN NLU Demo using Docker. The Docker container created automatically trains a new version of the model and runs it.

1. Install Docker.

• Alternatively, you may run the install.sh script in the project root.

2. Build docker container from image.

cd lumi-chatbot
docker build -t "lumi-chatbot" .

3. Run docker container (and remove any old versions running).

cd lumi-chatbot
docker ps -a -q --filter "name=lumi-chatbot" | grep -q . && docker stop lumi-chatbot && docker rm -fv lumi-chatbot
docker run --name "lumi-chatbot" -d -p 5005:5005 --restart unless-stopped "lumi-chatbot"

4. Check logs to see if its running properly.

docker logs lumi-chatbot --follow

Built With

• RASA - The NLU framework used
• Poetry - Python Dependency Management
• Docker - Used for deployment

Authors

• Arthur Jacobs - Initial work - asjacobs92