osmr / tgchatbot

Telegram text/voice AI chatbot

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Telegram AI chatbot

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This is a chatbot for the Telegram instance messenger, which uses various free conversational Natural Language Understanding, Automatic Speech Recognition and Text-To-Speech neural networks for different languages.

Used neural networks

  1. Text Conversational networks

    1. Facebook's BlenderBot (English)
    2. Microsoft's DialogGPT (English, French, Russian)
  2. Text Neural Machine Translation

  3. Text Punctuation and Capitalization

  4. Automatic Speech Recognition

    1. PytorchCV QuartzNet models
    2. Facebook's Wav2Vec2 XLSR-53 models
    3. Facebook's Speech to Text Transformer models
  5. Text-To-Speech

    1. NVIDIA NeMo TTS models
    2. TensorSpeech TensorFlowTTS models
  6. Audio Language Identification

  7. Audio Emotion Recognition

    1. S3PRL's Wav2Vec2 based model
    2. S3PRL's Hubert based model

Used conversational AI cloud services

  1. Google Cloud
  2. Amazon Transcribe and Polly
  3. Yandex Cloud


Docker way

  1. Install docker engine (actual instructions):
sudo apt update
sudo apt upgrade -y
sudo apt dist-upgrade -y
sudo apt autoremove -y

sudo apt install -y apt-transport-https ca-certificates curl gnupg lsb-release
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

sudo apt update
sudo apt-get install docker-ce docker-ce-cli containerd.io

sudo systemctl status docker

sudo usermod -aG docker $USER
newgrp docker
  1. Install NVIDIA Container Toolkit (actual instructions):
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
   && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
   && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt update
sudo apt install -y nvidia-container-toolkit
sudo systemctl restart docker
  1. Build docker image:
git clone https://github.com/osmr/tgchatbot.git
cd tgchatbot
docker build -t tgchatbot .
  1. Run docker container (fill the token value):
docker run -it --rm --name=tgchatbot1 tgchatbot --token="<Your token>"


docker run -it --rm --gpus=all --name=tgchatbot1 tgchatbot --token="<Your token>" --use-cuda

Virtualenv way

NB: You need Python >= 3.7 due to requirements of the aiogram and SpeechBrain packages.

  1. Install prerequisites:
apt-get update && apt-get upgrade -y && apt-get autoremove
apt-get install -y libsndfile1-dev ffmpeg
  1. Install virtualenv (actual instructions):
sudo -H pip install --upgrade pip setuptools wheel
sudo -H pip install Cython
sudo -H pip install virtualenv
  1. Clone repo, create and activate environment:
git clone https://github.com/osmr/tgchatbot.git
cd tgchatbot
virtualenv venv
source venv/bin/activate
  1. Install dependencies:
pip install torch==1.9.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
pip install -r requirements.txt
pip install TensorFlowTTS==1.8
pip install huggingface-hub==0.0.17 six==1.16.0
pip install --upgrade numpy llvmlite numba typing-extensions h5py
pip install pytest
pip install .
  1. Run tests:
  1. Run the chatbot (fill the token value):
python -m tgchatbot.launch --token="<Your token>"
docker run -it --rm --name=tgchatbot1 tgchatbot --token="<Your token>"


python -m tgchatbot.launch --token="<Your token>" --use-cuda
  1. Deactivate environment:

Chatbot commands in Telegram

  1. /start or /help - Welcome information.
  2. /start en - Set input/output language to en (English). It can be en, fr, de, and ru.
  3. /lang - Show current input/output languages status.
  4. /lang_src - Show current input (your messages or speech) language status.
  5. /lang_dst - Show current output (chatbot's messages and speech) language status.
  6. /lang en - Set input/output language to en (English).
  7. /lang_src en - Set input language to en (English).
  8. /lang_dst en - Set output language to en (English).
  9. /tts - Show current Text-To-Speech (TTS) activity status. It can be yes or no.
  10. /tts yes - Activate TTS.
  11. /context - Show contest for text (NLU) chatbot context corresponding the current user and output language.
  12. /context "" - Erase NLU chatbot contest.
  13. Hello - Text Hello to the chatbot. You can text amy message.
  14. <Audio with speech> - Say something to the chatbot.
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Telegram text/voice AI chatbot

License:MIT License


Language:Python 98.7%Language:Dockerfile 1.3%