BBB-Translation-Bot is a tool designed to enhance communication in BigBlueButton (BBB) meetings by providing real-time transcription and translation services. Utilizing OpenAI's cutting-edge Whisper technology, the bot joins a BBB meeting's audio channel and transcribes/translates spoken words into text, seamlessly integrating the transcripts into BBB's closed captions feature.

Follow these simple steps to quickly set up the BBB-Translation-Bot.

This setup was testet with a Nvidia RTX 2070 and RTX 3070 GPU. The GPU is used for the transcription and translation of the audio stream.

Refer to the official Nvidia documentation:

sudo apt update
sudo apt install linux-headers-$(uname -r)
distribution=$(. /etc/os-release;echo $ID$VERSION_ID | sed -e 's/\.//g')
wget https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64/cuda-keyring_1.0-1_all.deb
sudo dpkg -i cuda-keyring_1.0-1_all.deb
sudo apt update
sudo apt -y install cuda-drivers
sudo reboot now

Ensure Docker with GPU support is installed on your system: Refer to the official Nvidia documentation

sudo apt update

curl -sSL https://get.docker.com | sh

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
  && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
    sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list \
  && \
    sudo apt-get update

sudo apt install nvidia-container-runtime

which nvidia-container-runtime-hook

sudo systemctl restart docker

docker run -it --rm --gpus all ubuntu nvidia-smi # Test GPU support

1. Clone the repository:

   git clone https://github.com/bigbluebutton-bot/bbb-translation-bot
   cd bbb-translation-bot

2. Configure the bot: Copy the example configuration file and modify it according to your preferences:

   cp .env_example .env

3. Launch the bot: With Docker, you can easily start the bot:

   docker-compose up -d

To set up the environment for development purposes, follow the instructions below.

1. Install Nvidia drivers for Ubuntu: Refer to the official Nvidia documentation:

   sudo apt install linux-headers-$(uname -r)
   distribution=$(. /etc/os-release;echo $ID$VERSION_ID | sed -e 's/\.//g')
   wget https://developer.download.nvidia.com/compute/cuda/repos/$distribution/x86_64/cuda-keyring_1.0-1_all.deb
   sudo dpkg -i cuda-keyring_1.0-1_all.deb
   sudo apt update
   sudo apt -y install cuda-drivers
   sudo reboot now

2. Install Python dependencies:

   cd server
   sudo apt update
   sudo apt install python3-pip python3-dev ffmpeg -y
   python3 -m venv .translation-server
   source .translation-server/bin/activate
   pip3 install -r requirements-server.txt --no-cache-dir

3. Run the server:

   python3 server.py

4. Exit the virtual environment:

   deactivate

1. Install Golang: Follow the official Golang installation guide:

   cd client
   sudo apt update
   wget https://go.dev/dl/go1.21.3.linux-amd64.tar.gz
   sudo rm -rf /usr/local/go && sudo tar -C /usr/local -xzf go1.21.3.linux-amd64.tar.gz
   export PATH=$PATH:/usr/local/go/bin

2. Install node.js: Use Node Version Manager to install Node.js:

   curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.5/install.sh | bash
   export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")"
   [ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm
   nvm install node

3. Install Go dependencies:

   go get .

4. Run the client:

   go run .