Getting Started
Configuring channels
Authoring conversations
Conversational interactions
Natural language understanding
Server installation
Kubernetes / OpenshiftSingle serverSingle server (VM)Configuration

Single server (VM)

An alternative option is to deploy all the services on a single machine. You can get a virtual machine from the Cloud Provider of your choice. We recommend a machine with at least 1 CPU and 2 Gb of RAM


This is for experimentation only. The following installation is not secure and not suitable for production.

  1. Create a virtual machine with Ubuntu installed, and note the external IP address. For this tutorial, we’ll assume the IP address is
  2. Install Node.js
wget -qO- | bash
export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")"
[ -s "$NVM_DIR/" ] && \. "$NVM_DIR/" # This loads nvm
nvm install lts/erbium
  1. Install Docker and Docker Compose
sudo apt-get -y update
sudo apt-get -y remove docker docker-engine
sudo apt -y install
sudo systemctl start docker
sudo systemctl enable docker
sudo apt install curl
sudo curl -L "$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose
  1. Install Botfront
npm install -g botfront
botfront init # create a project
  1. Edit the botfront.yml file
nano .botfront/botfront.yml

In the env section, change the root_url to the machine IP address (leave the port 8888 unchanged)

root_url: ''
  1. Launch Botfront
botfront up
  1. Open Botfront in your browser ( and setup your project
  2. Go to settings/credentials and change the base_url host to the IP address (keep the host unchanged)
session_persistence: true
socket_path: "/"
  1. Botfront is ready to use.
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