Async smart 3D model creator and editor backend powered by GPT on top of FastAPI
It contains two generic entity models Interaction and Message. We store all of the data in the Postgres database. The interaction with the database is done with the SQLAlchemy library, and the simple GET and POST endpoints are exposed via the API, which is written with the FastAPI framework.
To manage dependencies, we use poetry.
To launch an API instance, you should:
- Have a running Postgres instance, e.g. in a container. The application will read the .env file to access the database.
- Create a virtual environment and install the dependencies in it. You can run
poetry install
for that. - Use start_app.sh to run the server. By default, it will bind to http://localhost:8000.
- An automatically generated documentation can be found at http://localhost:8000/docs. The endpoints are accessible at http://localhost:8000/api/<endpoint_name>.
You can also run the project via docker-compose
(i.e. docker compose up -d
) on port 80
in which you would need the .docker.env containing the following variable to create the database:
SQLALCHEMY_DATABASE_URI=postgresql+asyncpg://<username>:<password>@ai3d_db/<db-name>
poetry run python -m ai3d.commands create_superuser