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Andreas Peters dd97a2de3d Merge branch 'v2.2.1.av1' of AVENTER/nlp-backend into master 9 months ago
app Fix return type to prevent promise error (#98) 10 months ago
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app.json updated app.json to add heroku build packs 1 year ago
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README.md

IKY

Build Status

An AI Chatbot framework built in Python

Building a chatbot can sound daunting, but it’s totally doable. IKY is an AI powered conversational dialog interface built in Python. With IKY it’s easy to create Natural Language conversational scenarios with no coding efforts whatsoever. The smooth UI makes it effortless to create and train conversations to the bot and it continuously gets smarter as it learns from conversations it has with people. IKY can live on any channel of your choice (such as Messenger, Slack etc.) by integrating it’s API with that platform.

You don’t need to be an expert at artificial intelligence to create an awesome chatbot that has artificial intelligence. With this basic project you can create an artificial intelligence powered chatting machine in no time.There may be scores of bugs. So feel free to contribute via pull requests.

Installation

Using docker-compose (Recommended)

docker-compose build
docker-compose up -d
docker-compose exec iky_backend python manage.py init

Using Docker


# build docker images
docker build -t iky_backend:2.0.0 .
docker build -t iky_gateway:2.0.0 frontend/.

# start iky backend
docker run --name=iky_backend -e="APPLICATION_ENV=Production" iky_backend:2.0.0

# setup default intents
docker exec -it iky_backend python manage.py init

# start iky gateway with frontend
docker run --name=iky_gateway --link iky_backend:iky_backend -p 8080:80 iky_gateway:2.0.0

without docker

backend

  • Setup Virtualenv and install python requirements ```sh make setup

make run_dev

source venv/bin/activate && python manage.py init

* Production
```sh
make run_prod

frontend

  • Development sh cd frontend npm install ng serve
  • Production sh cd frontend ng build --prod --environment=python serve files in dist/ folder using nginx or any webserver

Heroku

Deploy

  • add your dev/production configurations in config.py

DB

Restore

You can import some default intents using follwing steps

Screenshots

Tutorial

Checkout this basic tutorial on youtube,

IMAGE ALT TEXT HERE

Watch tutorial on Fullfilling your Chatbot Intent with an API Call - Recipe Search Bot

Please visit my website to see my personal chatbot in action

Todos

  • Write Unit Tests
  • PEP-8 compliance
  • Word2Vec Integration
  • NLTK to Spacy migration
  • PyCRFSuite to sklearn-crfsuite migration
  • Support follow up conversations

### Dependencies documentations

Free Software, Hell Yeah!


Made with :heart: at God’s Own Country.