LingoNaut for Python

Welcome to LingoNaut! This repository contains a very simple python script for creating a custom speech-to-speech multilingual language learning assistant.

LingoNaut uses OpenAI's Whisper for speech-to-text, any Ollama model of your choice for the LLM, and the TTS package for text-to-speech.

Installation

1. Make sure you have ffmpeg installed on your system with the location of the bin/ folder added to your path.
2. Install Ollama on your system. Windows users will need to serve Ollama from WSL, but can then run client scripts from Powershell.
3. Install conda or miniconda on your system.
4. Navigate to this repo, and use conda env create -f environment.yml to install.
5. Use conda activate lingonaut to activate your environment.
6. Run python create_lingonaut_ollama.py to create the custom model.
7. Run python lingonaut.py to launch the session with the language assistant.

Usage Instructions

• There are no special options for which language to learn. All models used are fully multilingual, simply state your intention and let the assistant guide you.
• After running the Python script, you will see a message in the terminal that says "Awaiting user input..." when it is your move.
  • To ask the assistant questions in English, hold down Ctrl and ask your question. On key release, your message will be passed to assistant.
  • When practicing another language, hold down SHIFT to use a larger version of the Whisper model which is more accurate in non-English transcription.