Home of the generative models that power Brain Beats
- Clone the repo
- Navigate to the backend directory
- We reccommended you create a virtual environment. We use pipenv
Enter this in your command line:
pip install pipenv
pipenv shell
pipenv install
You can now run the project!. To run the API enter from the backend/ folder enter:
cd src/
uvicorn main:app --reload
or
uvicorn src.main:app --reload
If you run into any errors, double check those above commands
- Install Docker to your machine
- Clone the repo
- Navigate to the backend/ directory
We use an Ubuntu base image for Docker. This is because of Fluidsynth, the virtual software synth for helping generate workable audio files. Although Fluidsynth does work on Alpine, Python is buggy on alpine images, and tensorflow cant compile because lack of a gcc. Using Ubuntu results in large images so be weary.
Build the docker image
docker build -t docker-username/symphony .
Run the image
docker run -p 8000:8000 docker-username/symphony
To push the image to your docker repo use the command:
docker push docker-username/docker-reponame
- Make sure you add the source of model data to your .dockerignore or you will have a very large docker image