README.md

metadata

title: Quantum
emoji: 📈
colorFrom: gray
colorTo: red
sdk: docker
hf_oauth: false
pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Running locally

python app.py

By default the UI listens on http://127.0.0.1:7860. The EM and QLBM pages start in the background and expose themselves on http://127.0.0.1:8701 and http://127.0.0.1:8702.

Single-port / Hugging Face deployment

Spaces (and other single-port hosts) now work by running everything behind an internal reverse proxy. Set the following environment variables (the Dockerfile already does this):

Variable	Purpose
APP_HOST / APP_PORT	Internal address that app.py binds to (defaults: 127.0.0.1:8700).
EM_APP_PORT / QLBM_APP_PORT	Ports for the EM and QLBM subprocesses (defaults: 8701 and 8702).
EM_IFRAME_SRC / QLBM_IFRAME_SRC	Public paths served by the proxy (e.g., /em/ and /qlbm/).

The bundled docker/nginx.conf proxies incoming traffic on ${PORT:-7860} to the individual services so the browser never tries to contact 127.0.0.1 directly.

CUDA-Q backend on CPU-only hosts

The 3D lattice Boltzmann solver relies on CUDA-Q, which expects a CUDA-capable GPU. CPU-only runtimes such as Hugging Face Spaces automatically fall back to a lightweight "CPU demo" mode so the UI and preview still run. The plots update with an approximate synthetic evolution and clearly indicate the active backend. Use these environment variables to control the behavior:

Variable	Effect
DISABLE_CUDAQ=1	Skip loading the CUDA-Q backend (the CPU demo remains available).
FORCE_ENABLE_CUDAQ=1	Attempt to load the CUDA-Q backend even if the platform was auto-detected as CPU-only.

On GPU-enabled machines, leave both variables unset to run the full CUDA-Q solver. On CPU-only hosts you can still explore the workflow in demo mode, or deploy to a GPU- backed Space/local workstation and set FORCE_ENABLE_CUDAQ=1 to activate the quantum backend once hardware is available.