From 2c4bf9ae358a80cd2e4020d33134d3816a9b6498 Mon Sep 17 00:00:00 2001 From: Daniel Han Date: Tue, 5 May 2026 23:22:22 -0700 Subject: [PATCH] Route CPU-only Linux x86_64 to ggml-org/llama.cpp prebuilts (#5302) * Route CPU-only Linux x86_64 to ggml-org/llama.cpp prebuilts setup.sh hard-coded _HELPER_RELEASE_REPO=unslothai/llama.cpp for every non-Darwin host. unslothai/llama.cpp only publishes Linux CUDA bundles (app-*-linux-x64-cuda*.tar.gz), so a CPU-only Linux host walked ~30 releases looking for a non-existent app-*-linux-x64-cpu asset, exited the prebuilt planner with "no compatible Linux prebuilt asset was found", and fell through to a source build. Free CI runners (ubuntu-latest with no GPU) hit this on every install, and anyone running Studio on a Linux laptop without an NVIDIA GPU paid the ~3 minute cmake+make cost on first install. ggml-org publishes llama--bin-ubuntu-x64.tar.gz on every release and install_llama_prebuilt.py already knows how to fetch it: when called with --published-repo ggml-org/llama.cpp, the Linux x86_64 + not has_usable_nvidia branch in direct_upstream_release_plan picks up that asset directly. The fix is purely on the routing side. Tighten the gate so a Linux host routes to ggml-org only when it is x86_64 and has no GPU detection tool installed (nvidia-smi, rocminfo, amd-smi, hipconfig, hipinfo). Everything else stays on the current path: - macOS: already on ggml-org, unchanged - Windows: already on ggml-org via setup.ps1, unchanged - Linux CUDA: nvidia-smi present -> unslothai/llama.cpp, unchanged - Linux ROCm: rocminfo / amd-smi / hipconfig / hipinfo present -> unslothai/llama.cpp -> source build with HIP, unchanged - Linux Intel / Vulkan / SYCL: no NVIDIA / AMD tools, hits the new ggml-org route, gets upstream CPU asset (same as today's source-build CPU output, ~3 min faster) - Linux arm64 / s390x: not x86_64 -> unslothai/llama.cpp -> source build, unchanged * Tighten routing comment in studio/setup.sh --- studio/setup.sh | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/studio/setup.sh b/studio/setup.sh index 3e875eed30..1b6a3db343 100755 --- a/studio/setup.sh +++ b/studio/setup.sh @@ -582,11 +582,30 @@ _LLAMA_CPP_DEGRADED=false _LLAMA_FORCE_COMPILE="${UNSLOTH_LLAMA_FORCE_COMPILE:-0}" _REQUESTED_LLAMA_TAG="${UNSLOTH_LLAMA_TAG:-${_DEFAULT_LLAMA_TAG}}" _HOST_SYSTEM="$(uname -s 2>/dev/null || true)" +_HOST_MACHINE="$(uname -m 2>/dev/null || true)" + +# Pick the release repo install_llama_prebuilt.py plans against. +# unslothai/llama.cpp ships only Linux CUDA bundles, so CPU-only Linux +# x86_64 routes to ggml-org for bin-ubuntu-x64.tar.gz. Anything with a +# GPU tool installed stays on unslothai (CUDA bundle / ROCm source build). +_LINUX_HAS_GPU=false +for _GPU_TOOL in nvidia-smi rocminfo amd-smi hipconfig hipinfo; do + if command -v "$_GPU_TOOL" >/dev/null 2>&1; then + _LINUX_HAS_GPU=true + break + fi +done + if [ "$_HOST_SYSTEM" = "Darwin" ]; then _HELPER_RELEASE_REPO="ggml-org/llama.cpp" +elif [ "$_HOST_SYSTEM" = "Linux" ] \ + && [ "$_HOST_MACHINE" = "x86_64" ] \ + && [ "$_LINUX_HAS_GPU" = false ]; then + _HELPER_RELEASE_REPO="ggml-org/llama.cpp" else _HELPER_RELEASE_REPO="unslothai/llama.cpp" fi +unset _GPU_TOOL _LLAMA_PR="${UNSLOTH_LLAMA_PR:-}" _SKIP_PREBUILT_INSTALL=false _LLAMA_PR_FORCE="${UNSLOTH_LLAMA_PR_FORCE:-${_DEFAULT_LLAMA_PR_FORCE}}"