Commit Graph

4 Commits

Author SHA1 Message Date
LocalAI [bot]
4ac67d255d feat: single-build ggml CPU_ALL_VARIANTS for llama-cpp + turboquant (x86/arm64/apple) (#10497)
* feat(llama-cpp): single x86 CPU build via ggml CPU_ALL_VARIANTS

Replace the per-microarch avx/avx2/avx512/fallback multi-binary build on
x86 with a single grpc-server plus the dlopen-able libggml-cpu-*.so set
that ggml's backend registry selects at runtime by probing host CPU
features. One build instead of four, broader microarch coverage (adds
alderlake AVX-VNNI, zen4 AVX512-BF16, sapphirerapids AMX), and the
shell-side /proc/cpuinfo probing in run.sh goes away.

Build/link notes:
- CPU_ALL_VARIANTS requires GGML_BACKEND_DL + BUILD_SHARED_LIBS=ON, so
  ggml/llama become shared objects. SHARED_LIBS is now a make variable
  (default OFF) so the override survives the recursive sub-make into the
  VARIANT build dir instead of being re-clobbered by the base flags.
- The cpu-all target also builds "--target ggml": the per-microarch
  backends are runtime-dlopened, not link deps, so they only compile via
  ggml's add_dependencies().
- hw_grpc_proto is pinned STATIC. Under BUILD_SHARED_LIBS=ON it would
  otherwise become a DSO referencing hidden-visibility symbols in the
  static libprotobuf.a, which fails to link ("hidden symbol ... is
  referenced by DSO"). Keeping it static links gRPC/protobuf into the
  executable while only ggml/llama stay shared, so no PIC or base-image
  change is required.
- package.sh bundles the libggml-*.so set into package/lib; ggml finds
  them by scanning the bundled ld.so directory (/proc/self/exe), which
  run.sh launches from.

Scope: x86 only. arm64/darwin keep the single fallback build. The
ik-llama-cpp / turboquant forks and the other ggml C++ backends are
unchanged; the same recipe applies but is out of scope here.

Validated with a full docker build plus a live inference smoke test:
the model loads, ggml selects the AVX512_BF16 variant on a Zen-class
host, and tokens generate correctly.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]

* feat(llama-cpp,turboquant): extend CPU_ALL_VARIANTS to arm64 + turboquant

- llama-cpp: x86 AND arm64 now use the single llama-cpp-cpu-all build
  (only hipblas keeps the fallback build). ggml's arm64 variant table
  (armv8.x / armv9.x, plus apple_m* on darwin) is selected at runtime.
- turboquant: same recipe via a turboquant-cpu-all target. turboquant
  copies backend/cpp/llama-cpp's CMakeLists.txt + Makefile per flavor, so
  the hw_grpc_proto STATIC fix and the SHARED_LIBS / EXTRA_CMAKE_ARGS
  make-vars are inherited; the target just passes SHARED_LIBS=ON, the DL
  flags and --target ggml through, then collects the .so set. run.sh and
  package.sh updated to ship/select turboquant-cpu-all.
- Makefile lib-collection find now also matches *.dylib (for the darwin
  build, which emits dylibs rather than .so).

ik-llama-cpp is intentionally left unchanged: its pinned ggml has no
CPU_ALL_VARIANTS support and its IQK kernels require AVX2, so the
per-microarch dynamic backend set does not apply.

Scope still excludes the darwin packaging wiring (separate change).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]

* feat(llama-cpp,turboquant): arm64 gcc-14 for SME variants + darwin cpu-all packaging

- arm64: ggml CPU_ALL_VARIANTS builds armv9.2 SME variants whose -march=...+sme
  is rejected by the Ubuntu 24.04 default gcc-13. Build the arm64 variants with
  gcc-14 (installed in the compile step). The host only selects a variant it
  actually supports at runtime, but every variant must still compile.
- darwin: scripts/build/llama-cpp-darwin.sh builds llama-cpp-cpu-all instead of
  the fallback binary, keeps Metal (GGML_METAL stays ON; --target ggml also builds
  ggml-metal). The per-microarch libggml-cpu-*.dylib are placed in the package
  root next to the binary (darwin has no bundled ld.so, so ggml's executable-dir
  scan looks there), while the other shared dylibs go in lib/ for DYLD_LIBRARY_PATH.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]

* fix(llama-cpp-darwin): distribute ggml backends by suffix (.so root, .dylib lib)

ggml emits its loadable backends (per-microarch CPU variants, metal, blas) with a
.so suffix even on darwin, while the core libraries (ggml-base/ggml/llama/
llama-common/mtmd) use .dylib. Split the distribution by suffix: .so DL backends
go in the package root for ggml's executable-directory scan, .dylib core libs go
in lib/ for DYLD_LIBRARY_PATH. The previous .dylib name-pattern matched none of the
variants.

Verified on an M4: ggml loads the apple_m4 CPU variant (SME=1) and Metal, model
loads and generates correct tokens.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]

* fix(llama-cpp,turboquant): only CPU_ALL_VARIANTS for pure-CPU builds, GPU uses fallback

The previous gate sent every non-hipblas build through llama-cpp-cpu-all, so the
GPU image builds (cublas, sycl_f16/f32, vulkan, nvidia l4t) compiled the whole CPU
microarch variant matrix on top of their already-huge GPU backend - blowing the
build time (the sycl job was only 59% done after 2h11m) - and the arm64 l4t build
failed at `apt-get install gcc-14` (exit 100) on the Jetson base.

Gate on an empty BUILD_TYPE instead: only the pure CPU image (build-type: '' in
.github/backend-matrix.yml) builds the CPU_ALL_VARIANTS set; every GPU build gets a
single fallback CPU grpc-server, since the accelerator does the compute. This also
confines the arm64 gcc-14 step (needed for the armv9.2 SME variants) to the CPU
build, away from the GPU base images.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]

* docs(llama-cpp): correct run.sh comment for arm64/darwin cpu-all

arm64 and darwin CPU images now also ship llama-cpp-cpu-all (not fallback-only);
only GPU images ship fallback-only. Fix the stale comment to match.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-25 15:47:03 +02:00
Ettore Di Giacinto
f891d60d26 fix(llama.cpp): bundle libdl, librt, libpthread in llama-cpp backend (#9099)
chore(llama.cpp): bundle libdl, librt, libpthread in llama-cpp backend

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-03-22 00:58:14 +01:00
Copilot
fd53978a7b feat: package GPU libraries inside backend containers for unified base image (#7891)
* Initial plan

* Add GPU library packaging for isolated backend environments

- Create scripts/build/package-gpu-libs.sh for packaging CUDA, ROCm, SYCL, and Vulkan libraries
- Update llama-cpp, whisper, stablediffusion-ggml package.sh to include GPU libraries
- Update Dockerfile.python to package GPU libraries into Python backends
- Update libbackend.sh to set LD_LIBRARY_PATH for GPU library loading

Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>

* Address code review feedback: fix variable consistency and quoting

Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>

* Fix code review issues: improve glob handling and remove redundant variable

Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>

* Simplify main Dockerfile and workflow to use unified base image

- Remove GPU-specific driver installation from Dockerfile (CUDA, ROCm, Vulkan, Intel)
- Simplify image.yml workflow to build single unified base image for linux/amd64 and linux/arm64
- GPU libraries are now packaged in individual backend containers

Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2026-01-07 15:48:51 +01:00
Ettore Di Giacinto
294f7022f3 feat: do not bundle llama-cpp anymore (#5790)
* Build llama.cpp separately

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* WIP

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* WIP

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* WIP

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Start to try to attach some tests

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add git and small fixups

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix: correctly autoload external backends

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Try to run AIO tests

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Slightly update the Makefile helps

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Adapt auto-bumper

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Try to run linux test

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add llama-cpp into build pipelines

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add default capability (for cpu)

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Drop llama-cpp specific logic from the backend loader

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* drop grpc install in ci for tests

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fixups

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Pass by backends path for tests

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Build protogen at start

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(tests): set backends path consistently

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Correctly configure the backends path

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Try to build for darwin

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* WIP

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Compile for metal on arm64/darwin

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Try to run build off from cross-arch

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add to the backend index nvidia-l4t and cpu's llama-cpp backends

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Build also darwin-x86 for llama-cpp

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Disable arm64 builds temporary

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Test backend build on PR

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fixup build backend reusable workflow

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* pass by skip drivers

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Use crane

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Skip drivers

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fixups

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* x86 darwin

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add packaging step for llama.cpp

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fixups

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fix leftover from bark-cpp extraction

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Try to fix hipblas build

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-18 13:24:12 +02:00