Listens to conversations, emitting events based on asking an LLM if the conversation is convering relevant things.
Using ollama (with llama3) and whisper, with wake words deciding if a call to the LLM is needed.
Not that great yet, need to improve how the audio is batched.
Some variant of the following to get the dependencies:
virtualenv -p python3 .venv
source .venv/bin/activate
pip install -r requirements.txt
Run ollama in a seperate terminal:
ollama pull llama3
ollama serve
Then you can run the code from your virtualenv with the following to use a file:
python3 convact prerecorded ./samples/config.json PATH_TO_FILE
or the following to use your microphone:
python3 convact realtime ./samples/config.json
Both support --model and --ollama to set the model and ollama endpoint.
Only tested on MacOS, on a M2 MacBook Air, with python installed via homebrew. Running everything locally.
MIT