Models (OpenAI): gpt-3.5-turbo, whisper-1
- Messaging
- Reply detection
- Rate limiting
- Comprehensive logging
- Music
- YouTube search
- Queue controls
- Voice
- Live transcriptions
- Transcription-based replies
- Text to speech
- Music controls
For local development:
- rust
- ffmpeg
- opus
- yt-dlp
OR
For Dockerized development:
- docker
- docker-compose
Create a .env
file from .env.example
, then tweak src/cfg.rs
to your needs.
Running:
# Locally
cargo run
# Using Docker
docker-compose up
python@^3.11
poetry
Create a new file model/<name>.jsonl
and update the path in model/tune.py
.
Alternatively, update model/train.jsonl
directly.
To queue up a fine-tuning job on OpenAI:
cd model
poetry shell
poetry install
poetry run python tune.py