Initial release

scripts/demo.sh

@@ -0,0 +1,34 @@
+#!/usr/bin/env bash
+# Build and launch the demo server (CUDA lib + Go server) in the demo container.
+# The container carries a matching glibc/libstdc++/Go so both the CUDA
+# libtrellis2.so and the Go binary that dlopens it share one runtime — a NixOS
+# host binary won't run inside the CUDA image (different dynamic loader).
+#
+#   scripts/demo.sh            # fine path (needs the shape-SLAT GGUFs)
+#   scripts/demo.sh -coarse    # 64^3 marching-cubes preview only
+set -euo pipefail
+
+ROOT="$(cd "$(dirname "$0")/.." && pwd)"
+cd "$ROOT"
+PORT="${PORT:-8742}"
+
+docker build -f docker/Dockerfile.demo -t trellis2-demo docker
+
+docker run --rm -v "$ROOT":/work -w /work -e GOCACHE=/tmp/gocache trellis2-demo bash -c '
+  cmake -B build-cuda-shared -G Ninja -DCMAKE_BUILD_TYPE=Release -DGGML_CUDA=ON \
+        -DCMAKE_CUDA_ARCHITECTURES=120 -DBUILD_SHARED_LIBS=ON \
+        -DTRELLIS2_FETCH_PRINT_REMESH_DEPS=ON \
+        -DTRELLIS2_PRINT_REMESH_DEPS_DIR=/work/.deps/print-remesh >/dev/null 2>&1 &&
+  cmake --build build-cuda-shared -j"$(nproc)" &&
+  cd server && CGO_ENABLED=0 go build -o trellis2-server-linux .'
+
+# Fetch prebuilt f16 GGUFs from the public LocalAI-io repos. Files already present
+# are skipped, so this is a no-op once ggufs/ is populated; it lets fresh demo
+# users skip the separate download_models.sh + convert_all.sh steps.
+scripts/download_ggufs.sh
+
+docker rm -f trellis2-demo-run 2>/dev/null || true
+exec docker run --rm --name trellis2-demo-run --device nvidia.com/gpu=all \
+    -v "$ROOT":/work -w /work/server -p "$PORT":8742 trellis2-demo \
+    ./trellis2-server-linux -lib /work/build-cuda-shared/libtrellis2.so \
+    -ggufs /work/ggufs -store /work/generations -unload-idle -addr :8742 "$@"