SOVA NLU

SOVA NLU is an intent classification solution based on BERT architecture. It is designed as a REST API service and it can be customized (both code and models) for your needs.

Installation

The easiest way to deploy the service is via docker-compose, so you have to install Docker and docker-compose first. Here's a brief instruction for Ubuntu:

Docker installation

• Install Docker:

sudo apt-get update
sudo apt-get install \
    apt-transport-https \
    ca-certificates \
    curl \
    gnupg-agent \
    software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo apt-key fingerprint 0EBFCD88
sudo add-apt-repository \
   "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
   $(lsb_release -cs) \
   stable"
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io
sudo usermod -aG docker $(whoami)

In order to run docker commands without sudo you might need to relogin.

• Install docker-compose:

sudo curl -L "https://github.com/docker/compose/releases/download/1.25.5/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose

• (Optional) If you're planning on using CUDA run these commands:

curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | \
  sudo apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list | \
  sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list
sudo apt-get update
sudo apt-get install nvidia-container-runtime

Add the following content to the file /etc/docker/daemon.json:

{
    "runtimes": {
        "nvidia": {
            "path": "nvidia-container-runtime",
            "runtimeArgs": []
        }
    },
    "default-runtime": "nvidia"
}

Restart the service:

sudo systemctl restart docker.service

Build and deploy

• Checkout repository and models from Git LFS (you can also download pre-trained models manually):

  git clone https://github.com/sovaai/sova-nlu
  cd sova-nlu
  git lfs install
  git lfs pull

• Build docker image

  • If you're planning on using CPU only: build sova-nlu image using the following command:

  sudo docker-compose build

  • If you're planning on using GPU: modify Dockerfile, docker-compose.yml (uncomment the runtime and environment sections) and build sova-nlu image:

  sudo docker-compose build

• Run web service in a docker container

  sudo docker-compose up -d sova-nlu

Testing

To test the service you can send a POST request:

curl --request POST 'http://localhost:8000/get_intent' --header "Content-Type: application/json" --data '{"text": "Включи режиссерскую версию Лиги справедливости"}'

You can also use web interface by opening http://localhost:8000/docs.

Training

• Use the same Docker image that was already built for the service. Customize the hyperparameters in config.py and use your own data/data.csv for training.
• To start training simply run:

  sudo docker-compose up -d sova-nlu-train

The trained model will be saved to data/intent_classifier.pt.

Licenses

SOVA NLU is licensed under Apache License 2.0 by Virtual Assistant, LLC.