Compare commits

..

126 Commits

Author SHA1 Message Date
Richard Palethorpe
9d42a16c20 ci: publish base images to ci-cache instead of localai-base
The previous tag scheme pushed to quay.io/go-skynet/localai-base, which
required a separate quay repo + a write-permission grant for the CI
robot. PR #9672 hit a 401 on push because that grant was missing — the
robot can log in but not write to localai-base.

ci-cache already exists, the robot already has write access (it writes
the buildkit cache there on every backend build), and OCI tags namespace
cleanly within a repo. So publish base images to
quay.io/go-skynet/ci-cache:base-image-<stem>[-pr<N>]. The `base-image-`
prefix doesn't collide with the existing tag prefixes:
  - cache<tag-suffix>           per-backend buildkit cache
  - cache-localai<tag-suffix>   root image buildkit cache
  - base-<stem>                 base image's own buildkit cache
  - base-image-<stem>           the published OCI image (new)

base_images.yml's compute_ref step and prebuiltRef() in
scripts/changed-backends.js are kept in lock-step. Local Makefile tags
are unchanged (they're just local docker labels with no remote
correlation).

Assisted-by: Claude:opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-06 16:13:06 +01:00
Richard Palethorpe
9c1f8b344c ci: extend layered base images to golang, cpp, and rust matrices
Python's tier-1+2 base image (apt + GPU SDK + lang toolchain) was the only
lang previously factored. The remaining 82 matrix entries (62 golang +
9 llama-cpp + 9 turboquant + 1 ik-llama-cpp + 1 rust) still inlined the
same bootstrap into per-backend cache tags.

Add .docker/bases/Dockerfile.{golang,cpp,rust} mirroring Dockerfile.python's
GPU stack, with the lang-specific tail at the bottom (Go + protoc + grpc
tooling; protoc + cmake + GRPC; rustup + audio dev libs respectively).
Slim the five consumer Dockerfiles to FROM ${BASE_IMAGE_PREBUILT} + the
per-backend COPY/make.

The C++ trio (llama-cpp, ik-llama-cpp, turboquant) only differ in their
make targets, so langOf() in scripts/changed-backends.js remaps all three
Dockerfile suffixes to the shared 'cpp' base. That collapses 17 would-be
distinct bases to 8. langTriggerSelector and baseTriggerFiles are
extended so PRs touching the new recipes fan out canaries; the
.docker/bases/ auto-detection picks up the new langs without further
script changes.

Makefile: add docker-build-{python,golang,cpp,rust}-base targets and a
local-base-tag/local-base-target macro pair so each backend's
docker-build-X chains through the right base. The previous python-only
prereq is now a generic per-lang dispatch.

Total distinct bases for the full 234-entry matrix: 29 (was 9 with only
python factored). The C++ base also absorbs the previously per-consumer
GRPC build stage, removing the dominant cost from the llama-cpp /
ik-llama-cpp / turboquant rebuild paths.

Assisted-by: Claude:opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-06 16:13:06 +01:00
Richard Palethorpe
a3b7c3a819 ci: layered Python base images for cross-matrix dedup
The 234-entry backend matrix runs the same apt-update + GPU SDK install +
Python toolchain bootstrap into N independent registry-cache tags. Factor
that shared work out into a tier-1+2 base image (lang × accel × ubuntu ×
cuda) built once per workflow run, then consumed by every backend that
matches its tuple via BASE_IMAGE_PREBUILT.

The matrix data moves to .github/backend-matrix.yaml so backend.yml can
switch to fromJSON without duplicating the matrix. scripts/changed-backends.js
reads the data file, derives the deduplicated bases-matrix, annotates each
Python entry with the right base-image-prebuilt ref, and runs a collision
check that fails loudly if a future matrix change makes two consumers want
incompatible bases under the same tag-stem.

PR builds tag with -pr<N> so end-to-end validation lives within one PR;
master builds tag without the suffix. The base-images registry cache
parallels the existing per-matrix-entry caches.

Adding a new (accel, cuda) flavour is a backend-matrix.yaml edit; adding
a new language tier is a Dockerfile.<lang> recipe + a slim of the
consumer Dockerfile (script auto-detects via .docker/bases/).

10 distinct bases derive from the current 234 entries, replacing the
inline bootstrap that previously ran into ~10 separate cache tags.

Assisted-by: Claude:opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-06 16:10:49 +01:00
LocalAI [bot]
4e154b59e5 fix(ci): unbreak rerankers (torch bump) and vllm-omni on aarch64 (#9688)
Two unrelated CI breakages bundled together since both are one-liners:

- rerankers: bump torch 2.4.1 -> 2.7.1 on cpu/cublas12. The unpinned
  transformers resolves to 5.x, whose moe.py registers a custom_op with
  string-typed `'torch.Tensor'` annotations that torch 2.4.1's
  infer_schema rejects, blocking the gRPC server from starting and
  failing all 5 backend tests with "Connection refused" on :50051.
  Matches the version used by the transformers backend.

- vllm-omni: strip fa3-fwd from the upstream requirements/cuda.txt
  before resolving on aarch64. fa3-fwd 0.0.3 ships only an
  x86_64 wheel and has no sdist, making the cuda profile unsatisfiable
  on Jetson/SBSA. fa3-fwd is a soft runtime dep — vllm-omni's
  attention backends fall back to FA2 then SDPA when it's missing.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-06 17:07:24 +02:00
Richard Palethorpe
969005b2a1 feat(gallery): Speed up load times and clean gallery entries (#9211)
* feat: Rework VRAM estimation and use known_usecases in gallery

Signed-off-by: Richard Palethorpe <io@richiejp.com>
Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]

* chore(gallery): regenerate gallery index and add known_usecases to model entries

Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-06 14:51:38 +02:00
LocalAI [bot]
6d56bf98fe feat(importers): add vibevoice-cpp importer for GGUF bundles (#9685)
Routes mudler/vibevoice.cpp-models and similar repos to the vibevoice-cpp
backend. Detects via repo name ("vibevoice.cpp"/"vibevoice-cpp"), file
listing (vibevoice-*.gguf + tokenizer.gguf), or preferences.backend
override. Defaults to the realtime TTS model; preferences.usecase=asr
selects the ASR/diarization variant. Bundles the required tokenizer.gguf
and (for TTS) a voice prompt, emitting the Options[] entries the backend
expects. Registered ahead of VibeVoiceImporter so the C++ bundles aren't
swallowed by the older Python-backend substring match.


Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Write] [Bash]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-06 13:33:10 +02:00
LocalAI [bot]
a8d7d37a3c fix: unbreak master CI (docs, kokoros, vibevoice-cpp ABI) (#9682)
* fix(docs): correct broken Hugo relrefs

The Hugo build has been failing on master since the relevant pages
landed:

- text-generation.md:720 referenced `/docs/features/distributed-mode`,
  but Hugo `relref` paths are relative to the content root, not the
  rendered URL. Drop the `/docs/` prefix so the lookup matches the
  existing `features/...` form used elsewhere in the file.
- audio-transform.md:144 referenced `tts.md`; the actual page is
  `text-to-audio.md`.

Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(kokoros): stub Diarize and AudioTransform Backend trait methods

The recent backend.proto additions (Diarize, AudioTransform,
AudioTransformStream) extended the gRPC Backend trait, breaking
kokoros-grpc compilation with E0046 because the Rust implementation
hadn't picked up the new methods. Add Unimplemented stubs matching the
existing pattern for non-applicable RPCs in this TTS-only backend.

Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(vibevoice-cpp): track upstream ABI + wire 1.5B voice cloning

Two recent commits in mudler/vibevoice.cpp reshaped the vv_capi_tts
signature without a corresponding bump on the LocalAI side:

  3bd759c "1.5b: unify into a single tts entry point" inserted a
          ref_audio_path parameter between voice_path and dst_wav_path.
  ad856bd "1.5b: multi-speaker dialog support" promoted that to a
          (const char* const* ref_audio_paths, int n_ref_audio_paths)
          pair for per-speaker conditioning.

Because purego resolves symbols by name and not by signature, the
build kept linking; at runtime the misaligned arguments turned the
TTS->ASR closed-loop test into a SIGSEGV inside cgo. Track HEAD
explicitly and bring the bridge in line with it:

  * Update the CppTTS purego binding to the 9-arg form. purego
    marshals []*byte as a **char by handing the C side the underlying
    array address; nil/empty maps to NULL, which matches the C
    contract for "no reference audio" on the realtime-0.5B path.
  * Add a `ref_audio` gallery option (comma-separated, repeatable)
    that the 1.5B path consumes for runtime voice cloning. Multiple
    entries are interpreted as one WAV per speaker (Speaker 0..n-1).
  * TTSRequest.Voice now routes by extension/shape: `.wav` or a
    comma-separated list goes to ref_audio_paths; anything else stays
    on voice_path (realtime-0.5B's pre-baked voice gguf).
  * Pin VIBEVOICE_CPP_VERSION to ad856bd and wire the Makefile into
    the existing bump_deps matrix so future upstream rolls land as
    reviewable PRs instead of a silent CI break.

Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(vibevoice-cpp): use ModelOptions.AudioPath for 1.5B ref audio

Use the existing audio_path field from ModelOptions (already plumbed
through config_file's `audio_path:` YAML and consumed by other audio
backends like kokoros) instead of inventing a custom `ref_audio:`
Options[] string. Multi-speaker setups stay on a single comma-
separated value.

No behavior change beyond the gallery key name; per-call routing via
TTSRequest.Voice is unchanged.

Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-06 10:36:59 +02:00
LocalAI [bot]
06a1524155 chore(model gallery): 🤖 add 1 new models via gallery agent (#9681)
chore(model gallery): 🤖 add new models via gallery agent

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-06 08:47:40 +02:00
LocalAI [bot]
70cf8ac546 fix(backend): resolve relative draft_model paths against the models dir (#9680)
* fix(backend): resolve relative draft_model paths against the models dir

The main model file and mmproj are joined with the configured models
directory before reaching the backend, but draft_model was sent
verbatim. With a relative draft_model in the YAML config, llama.cpp
opens the path from the backend process's CWD and fails with "No such
file or directory", forcing users to hard-code an absolute path.

Mirror the existing mmproj resolution: if draft_model is relative,
join it with modelPath. Absolute paths are passed through unchanged.

Adds an e2e regression test against the mock backend that asserts the
main model file, mmproj, and draft_model all arrive at the backend
resolved to absolute paths.

Closes #9675

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7-1m [Read] [Edit] [Bash] [Write]

* fix(backend): always join draft_model with models dir (drop IsAbs shortcut)

The previous commit kept absolute draft_model paths intact via an
IsAbs check. That left a path-traversal vector open: a user-supplied
YAML config could set draft_model to /etc/passwd (or any other host
file the backend process can read) and the path would be sent through
unchanged.

filepath.Join cleans the leading slash from absolute components, so
joining unconditionally — the way mmproj already does — keeps the
result rooted at the configured models directory regardless of input.

Adds a second e2e spec that feeds an absolute draft_model into the
mock backend and asserts the path is clamped under modelsPath.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7-1m [Read] [Edit] [Bash]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-06 00:58:38 +02:00
LocalAI [bot]
7fab5e3d21 chore: ⬆️ Update ggml-org/whisper.cpp to 4bf733672b2871d4153158af4f621a6dd9104f4a (#9636)
⬆️ Update ggml-org/whisper.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-06 00:34:16 +02:00
Andreas Egli
af83518532 feat: support word-level timestamps for faster-whisper (#9621)
Signed-off-by: Andreas Egli <github@kharan.ch>
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2026-05-06 00:32:52 +02:00
LocalAI [bot]
a315c321c1 chore: ⬆️ Update TheTom/llama-cpp-turboquant to 69d8e4be47243e83b3d0d71e932bc7aa61c644dc (#9638)
⬆️ Update TheTom/llama-cpp-turboquant

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-06 00:29:05 +02:00
Ettore Di Giacinto
75fba9e03f fix(distributed): scope Upgrade All to nodes that have the backend installed (#9678)
In distributed mode the React UI's "Upgrade All" button fanned every
detected outdated backend out to every healthy backend node, including
nodes that never had that backend installed. On heterogeneous clusters
this surfaced as platform errors (e.g. mac-mini-m4 asked to upgrade
cpu-insightface-development, which has no darwin/arm64 variant) and left
forever-retrying pending_backend_ops rows.

DistributedBackendManager.UpgradeBackend now queries ListBackends()
first, builds the target node-ID set from SystemBackend.Nodes, and only
fans out to those nodes — every per-node primitive
(adapter.InstallBackend, the pending-ops queue, BackendOpResult) is
unchanged. enqueueAndDrainBackendOp gains an optional targetNodeIDs
allowlist; Install/Delete keep their fan-to-everyone semantics by
passing nil. If no node reports the backend installed, UpgradeBackend
now returns a clear "not installed on any node" error instead of
producing a stuck queue.

Adds Ginkgo coverage for the smart fan-out: backend on a subset of
nodes goes only to those nodes; backend on no node returns the new
error and never sends a NATS install request.


Assisted-by: Claude:claude-opus-4-7 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-06 00:28:41 +02:00
Richard Palethorpe
16b2d4c807 fix(python-backend): make JIT subprocesses work on hosts of any size (#9679)
Two related runtime fixes for Python backends that JIT-compile CUDA
kernels at first model load (FlashInfer, PyTorch inductor, triton):

1. libbackend.sh: replace `source ${EDIR}/venv/bin/activate` with a
   minimal manual setup (_activateVenv: export VIRTUAL_ENV, prepend
   PATH, unset PYTHONHOME) computed from $EDIR at runtime. `uv venv`
   and `python -m venv` both bake the create-time absolute path into
   bin/activate (e.g. VIRTUAL_ENV='/vllm/venv' from the Docker build
   stage), so sourcing activate on a relocated venv — copied out of
   the build container and unpacked at an arbitrary backend dir —
   prepends a stale, non-existent path to $PATH. Pip-installed CLI
   tools (e.g. ninja, used by FlashInfer's NVFP4 GEMM JIT) are then
   never found and the load aborts with FileNotFoundError. Doing the
   env setup ourselves matches what `uv run` does internally and
   sidesteps the relocation problem entirely. Generic — every Python
   backend benefits.

2. vllm/run.sh: replace ninja's default -j$(nproc)+2 with an adaptive
   MAX_JOBS = min(nproc, (MemAvailable-4)/4). Each concurrent
   nvcc/cudafe++ peaks at multiple GiB; the default OOM-kills on
   memory-tight hosts (e.g. a 16 GiB desktop loading a 27B NVFP4
   model) but underutilises 100-core / 1 TB boxes. User-set MAX_JOBS
   still wins. Also pin NVCC_THREADS=2 unless overridden.

Refs: https://github.com/vllm-project/vllm/issues/20079

Assisted-by: Claude:claude-opus-4-7 [Edit] [Bash]
2026-05-06 00:28:01 +02:00
Richard Palethorpe
8e43842175 feat(vllm, distributed): tensor parallel distributed workers (#9612)
* feat(vllm): build vllm from source for Intel XPU

Upstream publishes no XPU wheels for vllm. The Intel profile was
silently picking up a non-XPU wheel that imported but errored at
engine init, and several runtime deps (pillow, charset-normalizer,
chardet) were missing on Intel -- backend.py crashed at import time
before the gRPC server came up.

Switch the Intel profile to upstream's documented from-source
procedure (docs/getting_started/installation/gpu.xpu.inc.md in
vllm-project/vllm):

  - Bump portable Python to 3.12 -- vllm-xpu-kernels ships only a
    cp312 wheel.
  - Source /opt/intel/oneapi/setvars.sh so vllm's CMake build sees
    the dpcpp/sycl compiler from the oneapi-basekit base image.
  - Hide requirements-intel-after.txt during installRequirements
    (it used to 'pip install vllm'); install vllm's deps from a
    fresh git clone of vllm via 'uv pip install -r
    requirements/xpu.txt', swap stock triton for
    triton-xpu==3.7.0, then 'VLLM_TARGET_DEVICE=xpu uv pip install
    --no-deps .'.
  - requirements-intel.txt trimmed to LocalAI's direct deps
    (accelerate / transformers / bitsandbytes); torch-xpu, vllm,
    vllm_xpu_kernels and the rest come from upstream's xpu.txt
    during the source build.
  - requirements.txt: add pillow + charset-normalizer + chardet --
    used by backend.py and missing on the Intel install profile.
  - run.sh: 'set -x' so backend startup is visible in container
    logs (the gRPC startup error path was previously opaque).

Also adds a one-line docs example for engine_args.attention_backend
under the vLLM section, since older XE-HPG GPUs (e.g. Arc A770)
need TRITON_ATTN to bypass the cutlass path in vllm_xpu_kernels.

Tested end-to-end on an Intel Arc A770 with Qwen2.5-0.5B-Instruct
via LocalAI's /v1/chat/completions.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(vllm): add multi-node data-parallel follower worker

vLLM v1's multi-node story is one process per node sharing a DP
coordinator over ZMQ -- the head runs the API server with
data_parallel_size > 1 and followers run `vllm serve --headless ...`
with matching topology. Today LocalAI can already configure DP on the
head via the engine_args YAML map, but there's no way to bring up the
follower nodes -- so the head sits waiting for ranks that never
handshake.

Add `local-ai p2p-worker vllm`, mirroring MLXDistributed's structural
precedent (operator-launched, static config, no NATS placement). The
worker:

  - Optionally self-registers with the frontend as an agent-type node
    tagged `node.role=vllm-follower` so it's visible in the admin UI
    and operators can scope ordinary models away via inverse
    selectors.
  - Resolves the platform-specific vllm backend via the gallery's
    "vllm" meta-entry (cuda*, intel-vllm, rocm-vllm, ...).
  - Runs vLLM as a child process so the heartbeat goroutine survives
    until vLLM exits; forwards SIGINT/SIGTERM so vLLM can clean up its
    ZMQ sockets before we tear down.
  - Validates --headless + --start-rank 0 is rejected (rank 0 is the
    head and must serve the API).

Backend run.sh dispatches `serve` as the first arg to vllm's own CLI
instead of LocalAI's backend.py gRPC server -- the follower speaks
ZMQ directly to the head, there is no LocalAI gRPC on the follower
side. Single-node usage is unchanged.

Generalises the gallery resolution helper into findBackendPath()
shared by MLX and vLLM workers; extracts ParseNodeLabels for the
comma-separated label parsing both use.

Ships with two compose recipes (`docker-compose.vllm-multinode.yaml`
for NVIDIA, `docker-compose.vllm-multinode.intel.yaml` for Intel
XPU/xccl) plus `tests/e2e/vllm-multinode/smoke.sh`. Both vendors are
supported (NCCL for CUDA/ROCm, xccl for XPU) but mixed-vendor DP is
not -- PyTorch's process group requires every rank to use the same
collective backend, and NCCL/xccl/gloo don't interoperate.

Out of scope (deferred): SmartRouter-driven placement of follower
ranks via NATS backend.install events, follower log streaming through
/api/backend-logs, tensor-parallel across nodes, disaggregated
prefill via KVTransferConfig.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* test(vllm): CPU-only end-to-end test for multi-node DP

Adds tests/e2e/vllm-multinode/, a Ginkgo + testcontainers-go suite
that brings up a head + headless follower from the locally-built
local-ai:tests image, bind-mounts the cpu-vllm backend extracted by
make extract-backend-vllm so it's seen as a system backend (no gallery
fetch, no registry server), and asserts a chat completion across both
DP ranks. New `make test-e2e-vllm-multinode` target wires the docker
build, backend extract, and ginkgo run together; BuildKit caches both
images so re-runs only rebuild what changed. Tagged Label("VLLMMultinode")
so the existing distributed suite isn't pulled along.

Two pre-existing bugs surfaced by the test:

1. extract-backend-% (Makefile) failed for every backend, because all
   backend images end with `FROM scratch` and `docker create` rejects
   an image with no CMD/ENTRYPOINT. Fixed by passing
   --entrypoint=/run.sh -- the container is never started, only
   docker-cp'd, so the path doesn't have to exist; we just need
   anything that satisfies the daemon's create-time validation.

2. backend/python/vllm/run.sh's `serve` shortcut for the multi-node DP
   follower exec'd ${EDIR}/venv/bin/vllm directly, but uv bakes an
   absolute build-time shebang (`#!/vllm/venv/bin/python3`) that no
   longer resolves once the backend is relocated to BackendsPath.
   _makeVenvPortable's shebang rewriter only matches paths that
   already point at ${EDIR}, so the original shebang slips through
   unchanged. Fixed by exec-ing ${EDIR}/venv/bin/python with the script
   as an argument -- Python ignores the script's shebang in that case.

The test fixture caps memory aggressively (max_model_len=512,
VLLM_CPU_KVCACHE_SPACE=1, TORCH_COMPILE_DISABLE=1) so two CPU engines
fit on a 32 GB box. TORCH_COMPILE_DISABLE is currently mandatory for
cpu-vllm: torch._inductor's CPU-ISA probe runs even with
enforce_eager=True and needs g++ on PATH, which the LocalAI runtime
image doesn't ship -- to be addressed in a follow-up that bundles a
toolchain in the cpu-vllm backend.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(vllm): bundle a g++ toolchain in the cpu-vllm backend image

torch._inductor's CPU-ISA probe (`cpu_model_runner.py:65 "Warming up
model for the compilation"`) shells out to `g++` at vllm engine
startup, regardless of `enforce_eager=True` -- the eager flag only
disables CUDA graphs, not inductor's first-batch warmup. The LocalAI
CPU runtime image (Dockerfile, unconditional apt list) does not ship
build-essential, and the cpu-vllm backend image is `FROM scratch`,
so any non-trivial inference on cpu-vllm crashes with:

  torch._inductor.exc.InductorError:
    InvalidCxxCompiler: No working C++ compiler found in
    torch._inductor.config.cpp.cxx: (None, 'g++')

Bundling the toolchain in the CPU runtime image would bloat every
non-vllm-CPU deployment and force a single GCC version on backends
that may want clang or a different version. So this lives in the
backend, gated to BUILD_TYPE=='' (the CPU profile).

`package.sh` snapshots g++ + binutils + cc1plus + libstdc++ + libc6
(runtime + dev) + the math libs cc1plus links (libisl/libmpc/libmpfr/
libjansson) into ${BACKEND}/toolchain/, mirroring /usr/... layout. The
unversioned binaries on Debian/Ubuntu are symlink chains pointing into
multiarch packages (`g++` -> `g++-13` -> `x86_64-linux-gnu-g++-13`,
the latter in `g++-13-x86-64-linux-gnu`), so the package list resolves
both the version and the arch-triplet variant. Symlinks /lib ->
usr/lib and /lib64 -> usr/lib64 are recreated under the toolchain
root because Ubuntu's UsrMerge keeps them at /, and ld scripts
(`libc.so`, `libm.so`) hardcode `/lib/...` paths that --sysroot
re-roots into the toolchain.

The unversioned `g++`/`gcc`/`cpp` symlinks are replaced with wrapper
shell scripts that resolve their own location at runtime and pass
`--sysroot=<toolchain>` and `-B <toolchain>/usr/lib/gcc/<triplet>/<ver>/`
to the underlying versioned binary. That's how torch's bare `g++ foo.cpp
-o foo` invocation finds cc1plus (-B), system headers (--sysroot), and
the bundled libstdc++ (--sysroot, --sysroot is recursive into linker).

`run.sh` adds the toolchain bin dir to PATH and the toolchain's
shared-lib dir to LD_LIBRARY_PATH -- everything else (header search,
linker search, executable search) is encapsulated in the wrappers.
No-op for non-CPU builds, the dir doesn't exist there.

The cpu-vllm image grows by ~217 MB. Tradeoff is acceptable -- cpu-vllm
is already a niche profile (few users compared to GPU vllm) and the
alternative is a backend that crashes at first inference unless the
operator manually sets TORCH_COMPILE_DISABLE=1, which silently disables
all torch.compile optimizations.

Drops `TORCH_COMPILE_DISABLE=1` from tests/e2e/vllm-multinode -- the
smoke now exercises the real compile path through the bundled toolchain.
Test runtime is +20s for the warmup compile, still <90s end to end.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(vllm): scope jetson-ai-lab index to L4T-specific wheels via pyproject.toml

The L4T arm64 build resolves dependencies through pypi.jetson-ai-lab.io,
which hosts the L4T-specific torch / vllm / flash-attn wheels but also
transparently proxies the rest of PyPI through `/+f/<sha>/<filename>`
URLs. With `--extra-index-url` + `--index-strategy=unsafe-best-match`
uv would pick those proxy URLs for ordinary PyPI packages —
anthropic/openai/propcache/annotated-types — and fail when the proxy
503s. Master is hitting the same bug on its own l4t-vllm matrix entry.

Switch the l4t13 install path to a pyproject.toml that marks the
jetson-ai-lab index `explicit = true` and pins only torch, torchvision,
torchaudio, flash-attn, and vllm to it via [tool.uv.sources]. uv won't
consult the L4T mirror for anything else, so transitive deps fall back
to PyPI as the default index — no exposure to the proxy 503s.

`uv pip install -r requirements.txt` ignores [tool.uv.sources], so the
l4t13 branch in install.sh now invokes `uv pip install --requirement
pyproject.toml` directly, replacing the old requirements-l4t13*.txt
files. Other BUILD_PROFILEs continue using libbackend.sh's
installRequirements and never read pyproject.toml.

Local resolution test (x86_64, dry-run) confirms uv hits the L4T
index for torch and falls through to PyPI for everything else.

Assisted-by: claude-code:claude-opus-4-7-1m [Read] [Edit] [Bash] [Write]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-06 00:22:50 +02:00
Arkadiusz Tymiński
503904d311 fix(faster-whisper): cast segment timestamps to int after multiplication (#9674)
`int(x) * 1e9` returns a float because `1e9` is a float literal, but
TranscriptSegment.start/end are integer protobuf fields. This caused
every transcription request to fail with:

  TypeError: 'float' object cannot be interpreted as an integer

Multiply first, then cast — `int(x * 1e9)` — to get an int as required.
2026-05-05 23:46:39 +02:00
LocalAI [bot]
d5ce823b83 chore: ⬆️ Update ikawrakow/ik_llama.cpp to 8b56d813a9ed04fa7b7fe2588fddd845cf64eccb (#9677)
⬆️ Update ikawrakow/ik_llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-05 23:46:09 +02:00
LocalAI [bot]
c9141098b6 chore: ⬆️ Update ggml-org/llama.cpp to bbeb89d76c41bc250f16e4a6fefcc9b530d6e3f3 (#9676)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-05 23:45:54 +02:00
dependabot[bot]
1caab1de10 chore(deps): bump actions/checkout from 4 to 6 (#9663)
Bumps [actions/checkout](https://github.com/actions/checkout) from 4 to 6.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v4...v6)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-05-05 15:37:05 +02:00
Ettore Di Giacinto
e86ade54a6 feat(api): add /v1/audio/diarization endpoint with sherpa-onnx + vibevoice.cpp (#9654)
* feat(api): add /v1/audio/diarization endpoint with sherpa-onnx + vibevoice.cpp

Closes #1648.

OpenAI-style multipart endpoint that returns "who spoke when". Single
endpoint instead of the issue's three-endpoint sketch (refactor /vad,
/vad/embedding, /diarization) — the typical client wants one call, and
embeddings can land later as a sibling without breaking this surface.

Response shape borrows from Pyannote/Deepgram: segments carry a
normalised SPEAKER_NN id (zero-padded, stable across the response) plus
the raw backend label, optional per-segment text when the backend bundles
ASR, and a speakers summary in verbose_json. response_format also accepts
rttm so consumers can pipe straight into pyannote.metrics / dscore.

Backends:

* vibevoice-cpp — Diarize() reuses the existing vv_capi_asr pass.
  vibevoice's ASR prompt asks the model to emit
  [{Start,End,Speaker,Content}] natively, so diarization is a by-product
  of the same pass; include_text=true preserves the transcript per
  segment, otherwise we drop it.

* sherpa-onnx — wraps the upstream SherpaOnnxOfflineSpeakerDiarization
  C API (pyannote segmentation + speaker-embedding extractor + fast
  clustering). libsherpa-shim grew config builders, a SetClustering
  wrapper for per-call num_clusters/threshold overrides, and a
  segment_at accessor (purego can't read field arrays out of
  SherpaOnnxOfflineSpeakerDiarizationSegment[] directly).

Plumbing: new Diarize gRPC RPC + DiarizeRequest / DiarizeSegment /
DiarizeResponse messages, threaded through interface.go, base, server,
client, embed. Default Base impl returns unimplemented.

Capability surfaces all updated: FLAG_DIARIZATION usecase,
FeatureAudioDiarization permission (default-on), RouteFeatureRegistry
entries for /v1/audio/diarization and /audio/diarization, audio
instruction-def description widened, CAP_DIARIZATION JS symbol,
swagger regenerated, /api/instructions discovery map updated.

Tests:

* core/backend: speaker-label normalisation (first-seen → SPEAKER_NN,
  per-speaker totals, nil-safety, fallback to backend NumSpeakers when
  no segments).

* core/http/endpoints/openai: RTTM rendering (file-id basename, negative
  duration clamping, fallback id).

* tests/e2e: mock-backend grew a deterministic Diarize that emits
  raw labels "5","2","5" so the e2e suite verifies SPEAKER_NN
  remapping, verbose_json speakers summary + transcript pass-through
  (gated by include_text), RTTM bytes content-type, and rejection of
  unknown response_format. mock-diarize model config registered with
  known_usecases=[FLAG_DIARIZATION] to bypass the backend-name guard.

Docs: new features/audio-diarization.md (request/response, RTTM example,
sherpa-onnx + vibevoice setup), cross-link from audio-to-text.md, entry
in whats-new.md.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(diarization): correct sherpa-onnx symbol name + lint cleanup

CI failures on #9654:

* sherpa-onnx-grpc-{tts,transcription} and sherpa-onnx-realtime panicked
  at backend startup with `undefined symbol: SherpaOnnxDestroyOfflineSpeakerDiarizationResult`.
  Upstream's actual symbol is SherpaOnnxOfflineSpeakerDiarizationDestroyResult
  (Destroy in the middle, not the prefix); the rest of the diarization
  surface follows the same naming pattern. The mismatched name made
  purego.RegisterLibFunc fail at dlopen time and crashed the gRPC server
  before the BeforeAll could probe Health, taking down every sherpa-onnx
  test job — not just the diarization-related ones.

* golangci-lint flagged 5 errcheck violations on new defer cleanups
  (os.RemoveAll / Close / conn.Close); wrap each in a `defer func() { _ = X() }()`
  closure (matches the pattern other LocalAI files use for new code, since
  pre-existing bare defers are grandfathered in via new-from-merge-base).

* golangci-lint also flagged forbidigo violations: the new
  diarization_test.go files used testing.T-style `t.Errorf` / `t.Fatalf`,
  which are forbidden by the project's coding-style policy
  (.agents/coding-style.md). Convert both files to Ginkgo/Gomega
  Describe/It with Expect(...) — they get picked up by the existing
  TestBackend / TestOpenAI suites, no new suite plumbing needed.

* modernize linter: tightened the diarization segment loop to
  `for i := range int(numSegments)` (Go 1.22+ idiom).

Verified locally: golangci-lint with new-from-merge-base=origin/master
reports 0 issues across all touched packages, and the four mocked
diarization e2e specs in tests/e2e/mock_backend_test.go still pass.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(vibevoice-cpp): convert non-WAV input via ffmpeg + raise ASR token budget

Confirmed end-to-end against a real LocalAI instance with vibevoice-asr-q4_k
loaded and the multi-speaker MP3 sample at vibevoice.cpp/samples/2p_argument.mp3:
both /v1/audio/transcriptions and /v1/audio/diarization now succeed and
return correctly attributed speaker turns for the full clip.

Two latent issues surfaced once the diarization endpoint actually exercised
the backend with a non-trivial input:

1. vv_capi_asr only accepts WAV via load_wav_24k_mono. The previous code
   passed the uploaded path straight through, so anything that wasn't
   already a 24 kHz mono s16le WAV failed at the C side with rc=-8 and
   the very unhelpful "vv_capi_asr failed". prepareWavInput shells out
   to ffmpeg ("-ar 24000 -ac 1 -acodec pcm_s16le") in a per-call temp
   dir, matching the rate the model was trained on; both AudioTranscription
   and Diarize now route through it. This is the same shape sherpa-onnx
   uses (utils.AudioToWav), but vibevoice needs 24 kHz rather than 16 kHz
   so we don't reuse that helper.

2. The C ABI's max_new_tokens defaults to 256 when 0 is passed. That's
   fine for a five-second clip but not for anything past ~10 s — vibevoice
   stops mid-JSON, the parse fails, and the caller sees a hard error.
   Pass a much larger budget (16 384 ≈ ~9 minutes of speech at the
   model's ~30 tok/s rate); generation stops at EOS so this is a cap
   rather than a target.

3. As a defensive belt-and-braces, mirror AudioTranscription's existing
   "fall back to a single segment if the model emits non-JSON text"
   pattern in Diarize, so partial / unusual model output never produces
   a 500. This kept the endpoint usable while diagnosing (1) and (2),
   and is the right behaviour to keep.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(vibevoice-cpp): pass valid WAVs through directly so ffmpeg is not required at runtime

Spotted by tests-e2e-backend (1.25.x): the previous fix forced every
incoming audio file through `ffmpeg -ar 24000 ...`, which meant the
backend container — which does not ship ffmpeg — failed even for the
existing happy path where the caller already uploads a WAV. The
container-side error was:

    rpc error: code = Unknown desc = vibevoice-cpp: ffmpeg convert to
    24k mono wav: exec: "ffmpeg": executable file not found in $PATH

Reading vibevoice.cpp's audio_io.cpp, `load_wav_24k_mono` uses drwav and
already accepts any PCM/IEEE-float WAV at any sample rate, downmixes
multi-channel input to mono, and resamples to 24 kHz internally. So the
only inputs that genuinely need an external converter are non-WAV
formats (MP3, OGG, FLAC, ...).

Detect WAVs by RIFF/WAVE magic at bytes 0..3 / 8..11 and pass them
straight through with a no-op cleanup; everything else still goes
through ffmpeg with the same 24 kHz mono s16le target. The result:

* Container builds without ffmpeg keep working for WAV uploads
  (the e2e-backends fixture is jfk.wav at 16 kHz mono s16le).
* MP3 and other non-WAV inputs still get the new ffmpeg conversion
  path so the diarization endpoint stays useful.
* If the caller uploads a non-WAV but ffmpeg isn't on PATH, the
  surfaced error is still descriptive enough to act on.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(ci): make gcc-14 install in Dockerfile.golang best-effort for jammy bases

The LocalVQE PR (bb033b16) made `gcc-14 g++-14` an unconditional apt
install in backend/Dockerfile.golang and pointed update-alternatives at
them. That works on the default `BASE_IMAGE=ubuntu:24.04` (noble has
gcc-14 in main), but every Go backend that builds on
`nvcr.io/nvidia/l4t-jetpack:r36.4.0` — jammy under the hood — now fails
at the apt step:

    E: Unable to locate package gcc-14

This blocked unrelated jobs:
backend-jobs(*-nvidia-l4t-arm64-{stablediffusion-ggml, sam3-cpp, whisper,
acestep-cpp, qwen3-tts-cpp, vibevoice-cpp}). LocalVQE itself is only
matrix-built on ubuntu:24.04 (CPU + Vulkan), so it doesn't actually
need gcc-14 anywhere else.

Make the gcc-14 install conditional on the package being available in
the configured apt repos. On noble: identical behaviour to today (gcc-14
installed, update-alternatives points at it). On jammy: skip the
gcc-14 stanza entirely and let build-essential's default gcc take over,
which is what the other Go backends compile with anyway.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 15:10:13 +02:00
LocalAI [bot]
1634eece6b chore: ⬆️ Update ikawrakow/ik_llama.cpp to 45dfd80371785731bc2ed05a76252497a4e7a282 (#9644)
⬆️ Update ikawrakow/ik_llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-05 15:09:40 +02:00
LocalAI [bot]
b88ddce0f3 chore: ⬆️ Update ggml-org/llama.cpp to eff06702b2a52e1020ea009ebd86cb9f5acabab5 (#9637)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-05 09:52:28 +02:00
Ettore Di Giacinto
bbcaebc1ef feat(concurrency-groups): per-model exclusive groups for backend loading (#9662)
* feat(concurrency-groups): per-model exclusive groups for backend loading

Adds `concurrency_groups: [...]` to model YAML configs. Two models that share
a group cannot be loaded concurrently on the same node — loading one evicts
the others, reusing the existing pinned/busy/retry policy from LRU eviction.

Layered design:
- Watchdog (pkg/model): per-node correctness floor — on every Load(), evict
  any loaded model that shares a group with the requested one. Pinned skips
  surface NeedMore so the loader retries (and ultimately logs a clear
  warning), instead of silently allowing the rule to be violated.
- Distributed scheduler (core/services/nodes): soft anti-affinity hint —
  scheduleNewModel prefers nodes that don't already host a same-group
  model, falling back to eviction only if every candidate has a conflict.
  Composes with NodeSelector at the same point in the candidate pipeline.

Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy
models running on different nodes is fine. The ConfigLoader is wired into
SmartRouter via a small ConcurrencyConflictResolver interface so the nodes
package keeps a narrow surface on core/config.

Refactors the inner LRU eviction body into a shared collectEvictionsLocked
helper and the loader retry loop into retryEnforce(fn, maxRetries, interval),
so both LRU and group enforcement share busy/pinned/retry semantics.

Closes #9659.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(watchdog): sync pinned + concurrency_groups at startup

The startup-time watchdog setup lives in initializeWatchdog (startup.go),
not in startWatchdog (watchdog.go). The latter is only invoked from the
runtime-settings RestartWatchdog path. As a result, neither
SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot,
so `pinned: true` and `concurrency_groups: [...]` only became effective
after a settings-driven watchdog restart.

Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end:
loading model A in group "heavy", then C with no group (coexists),
then B in group "heavy" now correctly evicts A and leaves [B, C].

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec

CI lint runs new-from-merge-base, so the existing pre-existing
`defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the
one introduced by the concurrency_groups YAML round-trip test is held
to errcheck. Wrap the remove in a closure that discards the error.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 08:42:50 +02:00
dependabot[bot]
22ae415695 chore(deps): bump docs/themes/hugo-theme-relearn from f69a085 to 8bb66fa (#9665)
chore(deps): bump docs/themes/hugo-theme-relearn

Bumps [docs/themes/hugo-theme-relearn](https://github.com/McShelby/hugo-theme-relearn) from `f69a085` to `8bb66fa`.
- [Release notes](https://github.com/McShelby/hugo-theme-relearn/releases)
- [Commits](f69a085322...8bb66fa674)

---
updated-dependencies:
- dependency-name: docs/themes/hugo-theme-relearn
  dependency-version: 8bb66fa674351f3a0b0917a7552caac686eca920
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-05-05 08:42:27 +02:00
LocalAI [bot]
3a0164670e chore: ⬆️ Update vllm-project/vllm cu130 wheel to 0.20.1 (#9649)
⬆️ Update vllm-project/vllm cu130 wheel

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-05 08:41:55 +02:00
LocalAI [bot]
a91b05907c feat(swagger): update swagger (#9660)
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-05 01:50:17 +02:00
LocalAI [bot]
4ef45bbccd chore(model-gallery): ⬆️ update checksum (#9661)
⬆️ Checksum updates in gallery/index.yaml

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-05 00:12:22 +02:00
Beshoy Girgis
b224a3d931 deps: update quic-go to v0.59.0 (fix session ticket panic) (#9655)
Update quic-go from v0.54.1 to v0.59.0 to fix the crypto/tls session
ticket panic described in quic-go/quic-go#5572.

Co-dependency go-libp2p upgraded from v0.43.0 to v0.48.0 (required for
quic-go v0.59.0 compatibility).

Signed-off-by: Beshoy Girgis <shoy@1ds.us>
2026-05-04 22:07:42 +02:00
Richard Palethorpe
bb033b16a9 feat: add LocalVQE backend and audio transformations UI (#9640)
feat(audio-transform): add LocalVQE backend, bidi gRPC RPC, Studio UI

Introduce a generic "audio transform" capability for any audio-in / audio-out
operation (echo cancellation, noise suppression, dereverberation, voice
conversion, etc.) and ship LocalVQE as the first backend implementation.

Backend protocol:
- Two new gRPC RPCs in backend.proto: unary AudioTransform for batch and
  bidirectional AudioTransformStream for low-latency frame-by-frame use.
  This is the first bidi stream in the proto; per-frame unary at LocalVQE's
  16 ms hop would be RTT-bound. Wire it through pkg/grpc/{client,server,
  embed,interface,base} with paired-channel ergonomics.

LocalVQE backend (backend/go/localvqe/):
- Go-Purego wrapper around upstream liblocalvqe.so. CMake builds the upstream
  shared lib + its libggml-cpu-*.so runtime variants directly — no MODULE
  wrapper needed because LocalVQE handles CPU feature selection internally
  via GGML_BACKEND_DL.
- Sets GGML_NTHREADS from opts.Threads (or runtime.NumCPU()-1) — without it
  LocalVQE runs single-threaded at ~1× realtime instead of the documented
  ~9.6×.
- Reference-length policy: zero-pad short refs, truncate long ones (the
  trailing portion can't have leaked into a mic that wasn't recording).
- Ginkgo test suite (9 always-on specs + 2 model-gated).

HTTP layer:
- POST /audio/transformations (alias /audio/transform): multipart batch
  endpoint, accepts audio + optional reference + params[*]=v form fields.
  Persists inputs alongside the output in GeneratedContentDir/audio so the
  React UI history can replay past (audio, reference, output) triples.
- GET /audio/transformations/stream: WebSocket bidi, 16 ms PCM frames
  (interleaved stereo mic+ref in, mono out). JSON session.update envelope
  for config; constants hoisted in core/schema/audio_transform.go.
- ffmpeg-based input normalisation to 16 kHz mono s16 WAV via the existing
  utils.AudioToWav (with passthrough fast-path), so the user can upload any
  format / rate without seeing the model's strict 16 kHz constraint.
- BackendTraceAudioTransform integration so /api/backend-traces and the
  Traces UI light up with audio_snippet base64 and timing.
- Routes registered under routes/localai.go (LocalAI extension; OpenAI has
  no /audio/transformations endpoint), traced via TraceMiddleware.

Auth + capability + importer:
- FLAG_AUDIO_TRANSFORM (model_config.go), FeatureAudioTransform (default-on,
  in APIFeatures), three RouteFeatureRegistry rows.
- localvqe added to knownPrefOnlyBackends with modality "audio-transform".
- Gallery entry localvqe-v1-1.3m (sha256-pinned, hosted on
  huggingface.co/LocalAI-io/LocalVQE).

React UI:
- New /app/transform page surfaced via a dedicated "Enhance" sidebar
  section (sibling of Tools / Biometrics) — the page is enhancement, not
  generation, so it lives outside Studio. Two AudioInput components
  (Upload + Record tabs, drag-drop, mic capture).
- Echo-test button: records mic while playing the loaded reference through
  the speakers — the mic naturally picks up speaker bleed, giving a real
  (mic, ref) pair for AEC testing without leaving the UI.
- Reusable WaveformPlayer (canvas peaks + click-to-seek + audio controls)
  and useAudioPeaks hook (shared module-scoped AudioContext to avoid
  hitting browser context limits with three players on one page); migrated
  TTS, Sound, Traces audio blocks to use it.
- Past runs saved in localStorage via useMediaHistory('audio-transform') —
  the history entry stores all three URLs so clicking re-renders the full
  triple, not just the output.

Build + e2e:
- 11 matrix entries removed from .github/workflows/backend.yml (CUDA, ROCm,
  SYCL, Metal, L4T): upstream supports only CPU + Vulkan, so we ship those
  two and let GPU-class hardware route through Vulkan in the gallery
  capabilities map.
- tests-localvqe-grpc-transform job in test-extra.yml (gated on
  detect-changes.outputs.localvqe).
- New audio_transform capability + 4 specs in tests/e2e-backends.
- Playwright spec suite in core/http/react-ui/e2e/audio-transform.spec.js
  (8 specs covering tabs, file upload, multipart shape, history, errors).

Docs:
- New docs/content/features/audio-transform.md covering the (audio,
  reference) mental model, batch + WebSocket wire formats, LocalVQE param
  keys, and a YAML config example. Cross-links from text-to-audio and
  audio-to-text feature pages.

Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit Write Agent TaskCreate]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-04 22:07:11 +02:00
LocalAI [bot]
de83b72bb7 fix(distributed): orchestrator resilience — auto-upgrade routing, worker bind-wait, RAG-init crash, log spam (#9657)
* fix(nodes/health): skip stale-marking already-offline nodes

The health monitor re-emitted "Node heartbeat stale" + "Marking stale
node offline" + MarkOffline on every cycle for nodes that were already
in the offline (or unhealthy) state. For an operator-stopped node this
flooded the logs with the same WARN+INFO pair every check interval.

Skip the staleness branch when the node is already StatusOffline /
StatusUnhealthy — the state is already what we'd write, so neither the
log lines nor the DB update carry information.

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

* fix(worker): wait for backend gRPC bind before replying to backend.install

The backend supervisor used to wait up to 4s (20 × 200ms) for the
backend's gRPC server to answer a HealthCheck, then log a warning and
reply Success with the bind address anyway. On slower nodes (a Jetson
Orin doing first-boot CUDA init, large CGO library load) the gRPC
listener wasn't up yet, so the frontend's first LoadModel dial returned
"connect: connection refused" and the operator chased a phantom network
issue instead of a startup-timing one.

Two changes:

  - Bump the readiness window to 30s. CUDA init on Orin/Thor first boot
    measures in seconds, not milliseconds.
  - On deadline-exceeded, stop the half-started process, recycle the
    port, and return an error with the backend's stderr tail. The
    frontend now gets a real failure with diagnostic context instead of
    a misleading ECONNREFUSED on a downstream dial.

Process death during the wait window keeps its existing fast-fail path.

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

* fix(distributed): route auto-upgrade through BackendManager + bump LocalAGI/LocalRecall

Two distributed-mode bugs that surfaced together in the orchestrator
logs:

1. Auto-upgrade always failed with "backend not found".

   UpgradeChecker correctly routed CheckUpgrades through the active
   BackendManager (so the frontend aggregates worker state), but the
   auto-upgrade branch right below called gallery.UpgradeBackend
   directly with the frontend's SystemState. In distributed mode the
   frontend has no backends installed locally, so ListSystemBackends
   returned empty and Get(name) failed for every reported upgrade.
   Auto-upgrade now also goes through BackendManager.UpgradeBackend,
   which fans out to workers via NATS.

2. Embedding-load failure on a remote node crashed the orchestrator.

   When RAG init lazily called NewPersistentPostgresCollection and the
   remote embedding worker was unreachable, LocalRecall called
   os.Exit(1) inside the constructor, killing the orchestrator pod.
   LocalRecall now returns errors instead, LocalAGI surfaces them as a
   nil collection, and the existing RAGProviderFromState path returns
   (nil, nil, false) — the same code path the agent pool already takes
   when no RAG is configured. The orchestrator stays up; chat requests
   degrade to "no RAG available" until the embedding worker recovers.

Bumps:
  github.com/mudler/LocalAGI    → e83bf515d010
  github.com/mudler/localrecall → 6138c1f535ab

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 19:09:16 +02:00
LocalAI [bot]
1aeb4d7e73 chore(model gallery): 🤖 add 1 new models via gallery agent (#9653)
chore(model gallery): 🤖 add new models via gallery agent

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-04 15:42:08 +02:00
Ettore Di Giacinto
a271c72931 fix(react-ui/e2e): scope backendTrigger to <main> so it skips LanguageSwitcher
The LanguageSwitcher added in the i18n PR (#9642) lives in the sidebar
and also uses aria-haspopup="listbox" — same attribute the import-form
SearchableSelect uses. The Batch D / E tests' helper resolved the trigger
with `page.locator('button[aria-haspopup="listbox"]').first()`, which now
returns the language switcher (rendered first in DOM order, in the
sidebar) instead of the backend dropdown.

After clicking the wrong button, getByRole('option', { name: 'llama-cpp' })
naturally never resolves — language options aren't backend names — and
the test times out at 30s.

Scope the locator to the <main className="main-content"> wrapper so only
buttons inside the route's main content area match. The page layout has
the Sidebar outside <main>, so this cleanly excludes it.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 08:58:25 +00:00
Ettore Di Giacinto
ade5fd4b97 fix(react-ui): reflect disabled state on SearchableSelect button
The Backend dropdown is disabled while /backends/known is in flight
(disabled={isSubmitting || backendsLoading} in ImportModel.jsx). Until
now the disabled prop only guarded the internal onClick handler — there
was no `disabled` HTML attribute on the <button>, so the element
remained "actionable" from the outside.

That regressed the import-form-ux Batch D / E Playwright tests after
the i18next-suspense PR (#9642): suspending on the importModel
namespace defers the useEffect that fetches /backends/known, so when
the test calls backendTrigger.click() the button is rendered but
backendsLoading is still true. The click hits the no-op branch,
the dropdown stays closed, and `getByRole('option', { name: 'llama-cpp' })`
times out at 30s.

Surfacing the disabled state on the actual <button> makes Playwright
auto-wait until the dropdown is ready, fixes a11y (screen readers now
announce "disabled"), and removes the button from the tab order while
loading.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 08:21:03 +00:00
LocalAI [bot]
170d55c67d fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups (#9652)
* fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups

Two distinct bugs were causing tight retry loops in the distributed scheduler:

1. FindAndLockNodeWithModel ignored the model's NodeSelector. When a model
   was loaded on multiple nodes and only some matched the current selector,
   the function returned the lowest-in_flight node — even one the selector
   excluded. Route()'s post-check then fell through to scheduleNewModel,
   which targeted the matching node where the model was already at
   MaxReplicasPerModel capacity. Eviction couldn't help (the only loaded
   model on that node was the one being requested, and it was busy), so
   every request looped through "evicting LRU" → "all models busy".

   Fix: thread an optional candidateNodeIDs filter through
   FindAndLockNodeWithModel. Route() resolves the selector once via a new
   resolveSelectorCandidates helper and passes the matching IDs to both
   the cached-replica lookup and scheduleNewModel. The same helper
   replaces the inline selector block in scheduleNewModel.

2. ScheduleAndLoadModel (reconciler scale-up path) fell back to
   scheduleNewModel with backendType="" when no replica had ever been
   loaded for a model. The worker rejected the resulting backend.install
   ("backend name is empty") on every reconciler tick (~30s).

   Fix: remove the broken fallback. When GetModelLoadInfo has nothing
   stored, return a clear error instead of firing a doomed NATS install.
   The reconciler's existing scale-up failure log surfaces it once per
   tick; the model auto-replicates as soon as Route() serves it once and
   stores load info.

Also downgrade the post-LoadModel-failure StopGRPC error to Debug — that
cleanup attempt usually hits "model not found" because LoadModel failed
before registering the process, and the outer "Failed to load model"
error already carries the real reason.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]

* test(distributed): cover selector-aware FindAndLockNodeWithModel and reconciler scaleup guard

Two regression tests for the bugs fixed in the previous commit:

1. FindAndLockNodeWithModel — registry-level integration tests verify the
   candidateNodeIDs filter:
   - Returns the included node even when an excluded node has lower
     in_flight (the original selector-mismatch loop scenario).
   - Returns not-found when the model is loaded only on excluded nodes,
     forcing Route() to fall through to a fresh schedule instead of
     reusing the excluded replica.

2. ScheduleAndLoadModel — mock-based test verifies the reconciler scale-up
   path returns an error and does NOT fire backend.install when no replica
   has been loaded yet. fakeUnloader gains an installCalls slice so this
   negative assertion is direct.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 09:42:14 +02:00
Ettore Di Giacinto
28b4857bd6 fix(ci): leave ports.ubuntu.com upstream on self-hosted runners
mirrors.edge.kernel.org carries /ubuntu/ (amd64 archive) but does NOT
carry /ubuntu-ports/. With the previous default both archive and ports
pointed at kernel.org, so multi-arch builds (linux/amd64,linux/arm64)
on bigger-runner / arc-runner-set 404'd on the arm64 leg:

  Err:5 http://mirrors.edge.kernel.org/ubuntu-ports noble Release
    404  Not Found [IP: 213.196.21.55 80]

The original outage was on archive.ubuntu.com, not ports.ubuntu.com, so
default the self-hosted-ports-mirror to '' (= keep ports.ubuntu.com
upstream). apt-mirror.sh and the runner-side rewrite both already
no-op when the env var is empty.

Self-hosted amd64 still uses kernel.org for the main archive, which
worked fine in this run before the arm64 leg failed.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 07:28:43 +00:00
Ettore Di Giacinto
5503be1fb3 fix(ci): use http for the kernel.org mirror — bare ubuntu image has no CA bundle
The Docker build runs on the minimal ubuntu:24.04 base image, which
ships *without* ca-certificates. The very first apt-get update over
HTTPS therefore fails the TLS handshake ("No system certificates
available. Try installing ca-certificates."), and apt can't reach
ca-certificates itself to fix the situation — chicken and egg.

Apt validates package integrity via GPG-signed Release files, so plain
HTTP is safe for the archive. archive.ubuntu.com / azure.archive are
already accessed over HTTP for the same reason. Switch the kernel.org
defaults from https://mirrors.edge.kernel.org to
http://mirrors.edge.kernel.org so the in-Dockerfile rewrite works on
self-hosted runners too.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-03 23:29:53 +00:00
Ettore Di Giacinto
50580a84ae fix(ci): switch apt mirror per runner — azure on github-hosted, kernel.org on self-hosted
Self-hosted runners (arc-runner-set, bigger-runner) cannot reach
azure.archive.ubuntu.com — they live in different networks (e.g. our
arc-runner-set Kubernetes cluster) where Azure's mirror IP is not
routable. Symptom: "Connection failed [IP: 51.11.236.225 80]" with each
Ign:/Err: cycle taking 60s, hanging the build for ~16 minutes before
exit 100.

Pick the mirror based on `runner.environment`:

  * github-hosted (ubuntu-latest, ubuntu-24.04-arm) → Azure
    (http://azure.archive.ubuntu.com / http://azure.ports.ubuntu.com)
    — same VPC as the runner.
  * self-hosted (arc-runner-set, bigger-runner)    → kernel.org
    (https://mirrors.edge.kernel.org for both archive and ports)
    — publicly reachable from any network.

The choice now lives in one place: the .github/actions/configure-apt-mirror
composite action exposes `effective-mirror` / `effective-ports-mirror`
outputs so the reusable workflows can forward the same value as Docker
build-args without duplicating the per-runner-environment branch.

The now-redundant `apt-mirror` / `apt-ports-mirror` workflow inputs on
image_build.yml and backend_build.yml are dropped — defaults live in the
composite action and are visible there.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-03 22:59:26 +00:00
Ettore Di Giacinto
8edac61e57 feat(ci): allow routing apt traffic through an alternate Ubuntu mirror (#9650)
* feat(ci): allow routing apt traffic through an alternate Ubuntu mirror

Adds opt-in APT_MIRROR / APT_PORTS_MIRROR knobs to all Dockerfiles, the
Makefile, and CI workflows so we can fail over to a non-canonical Ubuntu
mirror when archive.ubuntu.com / security.ubuntu.com / ports.ubuntu.com
are degraded (recently observed: multi-day DDoS against the default pool).

Defaults are empty everywhere — behavior is unchanged unless a mirror is
configured. To enable in CI, set the repo-level GitHub Actions variables
APT_MIRROR (and APT_PORTS_MIRROR for arm64 builds). Locally:
    make docker APT_MIRROR=http://azure.archive.ubuntu.com

A small POSIX-sh helper in .docker/apt-mirror.sh rewrites both DEB822
(/etc/apt/sources.list.d/ubuntu.sources, Ubuntu 24.04+) and the legacy
/etc/apt/sources.list before the first apt-get update. Dockerfile stages
load it via RUN --mount=type=bind, so there is no extra layer and no
cache invalidation when the script is unchanged. Reusable workflows also
rewrite the runner's own /etc/apt sources before any sudo apt-get call.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* ci(apt-mirror): default to the Azure mirror, visible in the workflow source

Bakes Azure (http://azure.archive.ubuntu.com / http://azure.ports.ubuntu.com)
in as the default for both Docker builds and runner-side apt — rather than
hiding the URL behind a GitHub Actions repo variable that's not visible
from the source tree.

A new composite action at .github/actions/configure-apt-mirror is the
single source of truth for runner-side rewrites. Five standalone
workflows (build-test, release, tests-e2e, tests-ui-e2e, update_swagger)
just `uses: ./.github/actions/configure-apt-mirror`.

Three workflows (image_build, backend_build, checksum_checker) keep an
inline bash rewrite, because they install/upgrade git via apt *before*
the checkout step (so the local composite action isn't loadable yet).
The Azure URL is visible in those files too.

The `apt-mirror` / `apt-ports-mirror` inputs of the reusable workflows
keep their now-Azure defaults — they still feed the Docker build-args
block in addition to the inline runner-side rewrite. Callers (image.yml,
image-pr.yml, backend.yml, backend_pr.yml) drop the previous
`vars.APT_MIRROR` plumbing and rely on those defaults.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* ci(apt-mirror): drop Force Install GIT, consolidate on the composite action

The PPA git upgrade ran add-apt-repository ppa:git-core/ppa, which talks
to api.launchpad.net — also part of Canonical's infrastructure and
currently returning HTTP 504. The Azure mirror only covers
archive.ubuntu.com / security.ubuntu.com / ports.ubuntu.com, not PPAs.

The system git that ubuntu-latest already ships is sufficient for
actions/checkout and the build pipeline, so just drop the upgrade. With
that gone, the apt-before-checkout constraint disappears too — all three
holdouts (image_build, backend_build, checksum_checker) can now switch
to ./.github/actions/configure-apt-mirror like the other five.

Net: 0 inline apt-mirror blocks, all 8 workflows route through the
composite action.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-03 23:50:13 +02:00
Tai An
0b024f0886 chore(model gallery): add chroma1-hd diffusers model (#9646)
Resolves https://github.com/mudler/LocalAI/issues/9604

Adds Chroma1-HD (lodestones/Chroma1-HD), an 8.9B-parameter
text-to-image model derived from FLUX.1-schnell, served via the
upstream-diffusers ChromaPipeline. Inference defaults follow the
model card recommendations: 40 steps, CFG 3.0, bfloat16.

Assisted-by: claude-code:opus-4.7
2026-05-03 09:06:31 +02:00
Ettore Di Giacinto
a6121e240e docs: credit the LocalAI maintainers team
Update README and docs to attribute maintenance to the LocalAI team
(Ettore Di Giacinto and Richard Palethorpe) and drop the autonomous
AI dev team section.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Edit] [Bash]
2026-05-02 23:37:04 +00:00
Ettore Di Giacinto
87cf736068 feat(react-ui): add multilingual (i18n) support (#9642)
Adds end-to-end internationalization to the React UI with five seed
languages (English, Italian, Spanish, German, Simplified Chinese) and
a sidebar-footer language switcher next to the existing theme toggle.

Library: react-i18next + i18next + i18next-http-backend +
i18next-browser-languagedetector. The detector caches the user's
choice in localStorage (key `localai-language`, mirroring the existing
`localai-theme` convention) and updates the `<html lang>` attribute on
change. fallbackLng is `en`, so any missing translation in another
locale falls back transparently.

Translation files live under `public/locales/<lng>/<ns>.json`. They
ride along with the existing `//go:embed react-ui/dist/*` directive,
but the previous SPA route in core/http/app.go only exposed
`/assets/*` from the embedded React build. This commit generalizes
the asset handler into a `serveReactSubdir(subdir)` helper and adds a
matching `/locales/*` route so i18next-http-backend can fetch the
JSONs at runtime. The http-backend `loadPath` is built via the
existing `apiUrl()` helper so instances served under a sub-path (e.g.
`<base href="/ui/">`) resolve correctly.

Namespaces (13): common, nav, errors, auth, home, models, importModel,
chat, agents, skills, collections, media, admin. Translated UI surfaces
include the sidebar/header/footer chrome, login + account flows, the
Home dashboard (incl. the manage-by-chat assistant CTA), the model
gallery + import flow, the chat experience (Chat.jsx + ChatsMenu),
agents/skills/collections list pages, the studio media tabs (Image,
Video, TTS), and the admin page-headers (Settings incl. its section
nav, Manage, Backends, Traces, Nodes, P2P, Users, Usage). Shared
components (ConfirmDialog, Toast) take their default labels from the
common namespace so callers don't need to pass strings explicitly.

Tooling for incremental adoption is included:
  - `i18next-parser.config.js` + `npm run i18n:extract` to sweep `t()`
    keys into the JSON skeletons.
  - `scripts/translate-locales.mjs` (one-off helper) to bootstrap
    non-English locales from English source via OpenAI or Anthropic
    APIs, with --copy mode as a placeholder fallback. Idempotent;
    preserves existing translations unless --overwrite is passed.

Larger config-driven pages (ModelEditor, Settings deep field forms,
AgentChat/AgentCreate, SkillEdit, CollectionDetails, Talk, Sound,
biometrics, FineTune/Quantize, Users modals, Nodes/P2P install
pickers, BackendLogs, Traces deep filters, Explorer) intentionally
keep their inner content untranslated for now — they fall back to
English via fallbackLng so functionality is unaffected, and the
extracted-strings pattern + the bootstrap script make follow-up
extraction straightforward.

The initial Suspense fallback at the root in main.jsx covers the
first JSON fetch on cold load. A simple `.app-boot-spinner` styled
in App.css provides a non-empty paint while the first namespace
loads.

Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit Write Agent]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-02 22:42:08 +02:00
LocalAI [bot]
1ad5b5907d feat(swagger): update swagger (#9643)
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-02 22:33:47 +02:00
Russell Sim
18e039f305 fix(ci): fix AMDGPU_TARGETS empty-string bypass in hipblas builds (#9626)
* fix(ci): fix AMDGPU_TARGETS empty-string bypass in hipblas builds

399c1dec wired amdgpu-targets through the backend_build workflow_call
interface, intending the input's default value to cover matrix entries
that don't specify targets. However, GitHub Actions only applies a
workflow_call input default when the caller omits the input entirely.
When backend.yml passes `amdgpu-targets: ${{ matrix.amdgpu-targets }}`
and the matrix entry has no amdgpu-targets key, the expression evaluates
to an empty string, which is treated as an explicit value — bypassing
the default. The result is Docker receiving AMDGPU_TARGETS="" which in
turn causes Make's ?= default to be skipped (since the variable is
already set in the environment, even to empty), and cmake gets
-DAMDGPU_TARGETS= with no targets, so the HIP backend compiles for an
indeterminate target rather than the intended GPU list.

Fix this at two levels:

1. backend.yml: use a || fallback in the expression so that an undefined
   matrix.amdgpu-targets never reaches the reusable workflow as an empty
   string. The target list is the canonical default and lives here.

2. backend_build.yml: remove the now-misleading default value from the
   input declaration. The default never fired due to the above bug, so
   keeping it implied a guarantee that didn't exist.

3. backend/cpp/llama-cpp/Makefile: add an explicit $(error ...) guard
   after the ?= assignment so that if AMDGPU_TARGETS is empty (whether
   from environment or any future CI wiring mistake) the build fails
   immediately with a clear message rather than silently producing a
   binary compiled for an unknown GPU target.

Assisted-by: Claude Code:claude-sonnet-4-6
Signed-off-by: Russell Sim <rsl@simopolis.xyz>

* fix(build): plumb AMDGPU_TARGETS through to Docker builds

The docker-build-backend Makefile macro and Dockerfile.golang did not
pass AMDGPU_TARGETS to the inner make invocation, so hipblas builds
always used the backend Makefile's hardcoded default GPU targets
regardless of what was specified via environment or CI inputs.

Signed-off-by: Russell Sim <rsl@simopolis.xyz>

---------

Signed-off-by: Russell Sim <rsl@simopolis.xyz>
2026-05-02 15:53:14 +02:00
Ettore Di Giacinto
b1a99436c7 feat(branding): admin-configurable instance name, tagline, and assets (#9635)
Adds a whitelabeling feature so an operator can replace the LocalAI
instance name, tagline, square logo, horizontal logo, and favicon from
the admin Settings page. Defaults fall back to the bundled assets so
existing installs are unaffected.

The public GET /api/branding endpoint is reachable pre-auth so the
login screen can render the configured branding before sign-in.
Mutating routes (POST/DELETE /api/branding/asset/:kind) remain
admin-only. Text fields (instance_name, instance_tagline) ride the
existing /api/settings flow; binary assets get a dedicated multipart
upload route that persists files under DynamicConfigsDir/branding/.

To prevent the Settings page's stale local state from clobbering an
upload on save, UpdateSettingsEndpoint preserves whatever the on-disk
asset filename fields are regardless of the body — /api/branding/asset/*
are the sole writers for those fields.

The MCP catalog gains get_branding and set_branding tools (text fields
only; file upload stays UI-only) plus a configure_branding skill prompt.

While wiring this up, the same restart-loss class of bug surfaced for
several existing fields whose RuntimeSettings entries were never read
by the startup loader. Fix loadRuntimeSettingsFromFile() to load:

  - branding (instance_name, instance_tagline, *_file basenames)
  - auto_upgrade_backends, prefer_development_backends
  - localai_assistant_enabled
  - open_responses_store_ttl
  - the 7 existing AgentPool fields (enabled, default/embedding model,
    chunking sizes, enable_logs, collection_db_path)

Also exposes 3 new AgentPool runtime settings (vector_engine,
database_url, agent_hub_url) via /api/settings + the Settings UI, with
the same load-on-startup wiring. The file watcher's manual-edit path
is intentionally not changed — the in-process API endpoints already
update appConfig directly, so the watcher is redundant for supported
flows and a separate refactor for everything else.

15 TDD specs cover the loader behaviour (1 branding + 11 adjacent + 3
new agent-pool); 2 specs cover the persistence helpers and the
clobber-prevention contract.


Assisted-by: claude-code:claude-opus-4-7

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-02 15:51:36 +02:00
Ettore Di Giacinto
7325046650 fix(diffusers): drop compel from requirements to unblock pip resolver (#9632)
compel 2.3.1 (latest, Nov 2025) declares transformers~=4.25 in its
metadata, i.e. >=4.25,<5.0. After transformers 5.0 (2026-01-26) and
huggingface-hub 1.0 (2025-10-27) shipped, the weekly DEPS_REFRESH
cache rotation in CI started seeing the new majors and pip's resolver
went into multi-hour backtracking storms walking every transformers
4.x candidate against every accelerate/hf-hub/tokenizers combination
to find a set compel would accept. The 2026-04-29 backend-build for
the diffusers backend (darwin-mps + l4t + cublas13-turboquant matrix
cells) hit the GitHub Actions 6h job timeout still inside pip
install — the build itself never started.

compel is the only hard upper bound on transformers in this stack
(diffusers, accelerate, peft, optimum-quanto are all flexible), and
upstream support for transformers 5 is still in flight: damian0815/
compel#129 ("Modernize Compel for Transformers 5") and #128 ("Bump
transformers version to >5.0") are both open as of today.

backend.py only constructs Compel() when COMPEL=1 is set in the env
(default off), so make compel a true optional extra:

  - Wrap the top-level `from compel import ...` in try/except
    ImportError, mirroring the existing sd_embed pattern.
  - Auto-disable COMPEL with a warning when the module isn't
    installed, instead of crashing on module load.
  - Drop compel from all eight requirements-*.txt variants so the
    resolver no longer has to satisfy its transformers cap.
  - Leave a TODO in backend.py and in each requirements file
    pointing at the upstream PR/issue, so the dependency can be
    reinstated once compel supports transformers >= 5.

Users who rely on weighted-prompt embeddings can opt in with a
manual `pip install compel` alongside COMPEL=1; the warning emitted
on startup tells them how.

Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit WebFetch]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-01 14:45:14 +02:00
Ettore Di Giacinto
8452068f43 feat(importers): whisper.cpp HF repos pick a quant + nest under whisper/models (#9630)
The WhisperImporter's Import() switch ordered LooksLikeURL ahead of the
HuggingFace branch, so any https://huggingface.co/<owner>/<repo> URI
(e.g. LocalAI-io/whisper-large-v3-it-yodas-only-ggml) hijacked the URL
path. FilenameFromUrl returned the repo slug, the gallery entry pointed
at the HTML repo page, the SHA256 was empty, and the HF file listing
was effectively dead code for HTTPS imports. The HF branch only fired
for huggingface://owner/repo and hf://owner/repo references.

Gate the URL case on a "ggml-*.bin" basename signal — mirroring how
the llama-cpp importer gates on ".gguf" — so direct file URLs still
take the URL path while HF repo URLs fall through to the HF branch.
There the file listing is actually consulted: every ggml-*.bin entry
is collected and one is picked by the new preferences.quantizations
preference (default q5_0; comma-separated for fallback ordering).

Pin the chosen file under whisper/models/<name>/<file> so a single
repo can ship q4_0/q5_0/q8_0 side-by-side without colliding on disk,
matching the llama-cpp/models/<name>/ layout. The fallback when no
preference matches is the last available ggml file, mirroring
llama-cpp's pickPreferredGroup behaviour.

Tests: replace the previous probe spec with positive assertions
against LocalAI-io/whisper-large-v3-it-yodas-only-ggml (default →
ggml-model-q5_0.bin, quantizations=q4_0 → ggml-model-q4_0.bin) plus
two offline specs that build a fake hfapi.ModelDetails to cover the
fallback rule and non-ggml filtering without touching the network.


Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit WebFetch]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-01 12:03:07 +02:00
ER-EPR
0b0078047f Add tags to qwen3-vl-reranker and Qwen3-VL-Embedding to the gallery (#9628)
* Add tags to Qwen3-VL-Reranker models

Added tags for reranker models in index.yaml.

Signed-off-by: ER-EPR <38782737+ER-EPR@users.noreply.github.com>

* Add Qwen3-VL-Embedding models to gallery

Added Qwen3-VL-Embedding-8B and Qwen3-VL-Embedding-2B models with detailed descriptions and file references.

Signed-off-by: ER-EPR <38782737+ER-EPR@users.noreply.github.com>

* Update index.yaml

Signed-off-by: ER-EPR <38782737+ER-EPR@users.noreply.github.com>

---------

Signed-off-by: ER-EPR <38782737+ER-EPR@users.noreply.github.com>
2026-05-01 10:56:58 +02:00
Tai An
80961d2da6 feat(backends/python): use tempfile.gettempdir() instead of hardcoded /tmp (#9629)
Closes #9601

Makes the temporary scratch paths in vllm, vllm-omni, tinygrad, and pocket-tts
backends configurable via the standard TMPDIR env var, instead of always writing
to /tmp. This is a one-line change per call site that calls tempfile.gettempdir()
for the directory and keeps the same filename suffix.

Users who run on systems with a small root partition (or want to relocate scratch
files to a larger volume) can now redirect these by setting TMPDIR
(e.g. TMPDIR=/data/tmp), without affecting the existing LOCALAI_GENERATED_CONTENT_PATH
or LOCALAI_UPLOAD_PATH options that already cover other temp paths.

Files touched:
- backend/python/vllm/backend.py        (1 site: video base64 scratch)
- backend/python/tinygrad/backend.py    (1 site: image fallback dst)
- backend/python/pocket-tts/backend.py  (1 site: tts wav fallback dst)
- backend/python/vllm-omni/backend.py   (2 sites: video + audio scratch)
2026-05-01 10:56:24 +02:00
LocalAI [bot]
9c4c3f9d8f chore: ⬆️ Update ggml-org/llama.cpp to beb42fffa45eded44804a1fd4916146222371581 (#9624)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-01 02:02:56 +02:00
LocalAI [bot]
273416f54b chore: ⬆️ Update ikawrakow/ik_llama.cpp to a8aecbf15933295af96504f9a693998322185b5c (#9625)
⬆️ Update ikawrakow/ik_llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-05-01 02:02:29 +02:00
Ettore Di Giacinto
c02a50f2ab feat(llama-cpp): bump to d775992 and adapt to spec params refactor (#9618)
Bumps backend/cpp/llama-cpp/Makefile LLAMA_VERSION from 665abc6 to
d775992, picking up upstream PR ggml-org/llama.cpp#22397 which splits
common_params_speculative into nested draft / ngram_simple / ngram_mod
sub-structs. Renames every grpc-server.cpp reference to match:

  speculative.mparams_dft.path  -> speculative.draft.mparams.path
  speculative.{n_max,n_min}     -> speculative.draft.{n_max,n_min}
  speculative.{p_min,p_split}   -> speculative.draft.{p_min,p_split}
  speculative.{n_gpu_layers,n_ctx} -> speculative.draft.{n_gpu_layers,n_ctx}
  speculative.ngram_size_n      -> speculative.ngram_simple.size_n
  speculative.ngram_size_m      -> speculative.ngram_simple.size_m
  speculative.ngram_min_hits    -> speculative.ngram_simple.min_hits

The "speculative.n_max" JSON key sent to the upstream server stays
unchanged — server-task.cpp still reads it and routes the value into
draft.n_max internally.

The turboquant fork (TheTom/llama-cpp-turboquant @ 11a241d) branched
before #22397 and still exposes the flat layout. Since turboquant
reuses the shared backend/cpp/llama-cpp/grpc-server.cpp, extend
patch-grpc-server.sh with an idempotent sed block that reverts the
ten field references back to the legacy flat names on the build copy
only — the original under backend/cpp/llama-cpp/ stays compiling
against vanilla upstream. Drop the block once the fork rebases.

ik-llama-cpp has its own grpc-server.cpp with no speculative refs
(0/2661 lines), so it is unaffected.

Validated locally with `make docker-build-llama-cpp` (avx, avx2,
avx512, fallback, grpc + rpc-server all built; image exported).


Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-30 08:44:43 +02:00
LocalAI [bot]
76971fb2aa chore: ⬆️ Update leejet/stable-diffusion.cpp to 3d6064b37ef4607917f8acf2ca8c8906d5087413 (#9617)
⬆️ Update leejet/stable-diffusion.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-30 08:43:42 +02:00
LocalAI [bot]
ebd9fcbe20 chore(model gallery): 🤖 add 1 new models via gallery agent (#9615)
chore(model gallery): 🤖 add new models via gallery agent

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-29 22:33:41 +02:00
Ettore Di Giacinto
091eda8d70 feat: react chat redesign (#9616)
* feat(react-ui): redesign chat — popover history, focus on send, density pass

Replace the persistent 260px conversation sidebar with a Cmd/Ctrl+K
popover (ChatsMenu) so the conversation owns the page. Once a chat has
at least one message we auto-collapse the global app rail and fade
non-essential header chrome; Esc gives the user back the full chrome
for the rest of the session.

Move Canvas mode and the MCP dropdown into the input wrapper as mode
chips — they describe what's armed for the next message and now live
where the user composes. The chat header drops to Chats · title ·
ModelSelector · overflow · settings, and an overflow menu carries
admin-only Manage mode along with Info / Edit / Export / Clear.

Density pass: tighter header (40px), smaller avatars with the assistant
left-border accent doing the work, 88% bubble width, modern
field-sizing on the textarea, 32px send/stop buttons.

Empty state now surfaces a Recent strip (top 4 non-empty chats) and a
Cmd+K hint, replacing the discoverability the persistent sidebar used
to provide.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

* feat(react-ui): chat input chips, slimmer menu, focus mode polish

Move Canvas mode and the MCP dropdown into the input wrapper as compact
mode chips — they describe what's armed for the next message and now
sit where the user composes. The MCP popover flips upward when anchored
to the input row so it stays on-screen.

Eliminate the chat header overflow ("…") menu entirely; relocate each
item to its semantic home so users don't have to remember a
miscellany drawer:

- Manage mode toggle → top of the Settings drawer, alongside the
  other sticky chat knobs. The shield next to the title still
  signals state at a glance.
- Model info / Edit config → small admin-only "ⓘ" button next to the
  ModelSelector; the existing model-info panel now hosts the Edit
  config link.
- Export as Markdown → per-row hover action in ChatsMenu, so it works
  for any chat (not just the active one).
- Clear chat history → destructive button at the bottom of the
  Settings drawer.

Make the Sidebar listen to its own `sidebar-collapse` event so the
chat's focus mode actually shrinks the rail (it previously only
flipped the layout class, leaving the sidebar element at full width
and overlapping the chat). Drop the focus-mode toast — the visual
shift is enough; the toast was noise.

Define `--color-text-tertiary` in both themes; without it metadata
text (recent strip timestamps and a few other sites) was inheriting
the platform default, which read as black on the dark surface.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

* fix(model/log-store): close merged channel exactly once; clean up Remove

Two latent races in BackendLogStore.Subscribe could panic under load
(distributed e2e test triggered "send on closed channel" at
backend_log_store.go:288):

1. The aggregated path closed the merged channel `ch` from two
   places — the fan-in waiter goroutine (after all source channels
   drained) and unsubscribe(). When unsubscribe ran while a fan-in
   goroutine was mid-flight on `ch <- line`, the close beat the send
   and the runtime panicked. Now `ch` is closed by exactly one
   goroutine: the waiter that observes all fan-in goroutines finish.
   unsubscribe() only closes the per-buffer source channels — the
   for-range in each fan-in goroutine then exits naturally and the
   waiter takes care of the merged close.

2. Remove() closed every subscriber channel but didn't delete the
   entries from the subscribers map, so a concurrent unsubscribe()
   would call close() again on the already-closed channel
   ("close of closed channel"). Clear the map entry while closing.

Add a regression test that hammers AppendLine concurrently with
Subscribe + unsubscribe + Remove; the race detector catches both
classes of regression.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

* test(model/log-store): port backend log store tests to ginkgo

Bring backend_log_store_test.go in line with the rest of pkg/model
(loader_test, watchdog_test, store_test): same external test package
(`model_test`), same ginkgo + gomega imports, same Describe/It
nesting around the public API. Behaviour is unchanged — the four
existing scenarios plus the unsubscribe race regression all run as
specs under the existing `TestModel` suite.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-29 22:33:26 +02:00
Ettore Di Giacinto
fe6eb57082 feat(vibevoice-cpp): add purego TTS+ASR backend (#9610)
* feat(vibevoice-cpp): add purego TTS+ASR backend

Wire up Microsoft VibeVoice via the vibevoice.cpp C ABI as a new
purego-based Go backend that serves both Backend.TTS and
Backend.AudioTranscription from a single gRPC binary. Mirrors the
qwen3-tts-cpp / sherpa-onnx pattern so the variant matrix
(cpu/cuda12/cuda13/metal/rocm/sycl-f16/f32/vulkan/l4t) and the
e2e-backends gRPC harness reuse existing infrastructure.

- backend/go/vibevoice-cpp/ - Makefile, CMakeLists, purego shim, gRPC
  Backend with model-dir auto-detection, closed-loop TTS->ASR smoke test
- backend/index.yaml - &vibevoicecpp meta + 18 image entries
- Makefile - .NOTPARALLEL, BACKEND_VIBEVOICE_CPP, docker-build wiring,
  test-extra-backend-vibevoice-cpp-{tts,transcription} e2e wrappers
- .github/workflows/backend.yml - matrix entries for all variants
- .github/workflows/test-extra.yml - per-backend smoke + 2 gRPC e2e jobs

* feat(vibevoice-cpp): drop hardcoded glob detection, add gallery entries

Refactor backend Load() to follow the standard Options[] convention
used by sherpa-onnx and the rest of the multi-role backends:
ModelFile is the primary gguf, supplementary paths come through
opts.Options[] as key=value (or key:value for Make-target compat),
resolved against opts.ModelPath. type=asr/tts decides the role of
ModelFile when neither tts_model nor asr_model is set explicitly.

Add gallery/index.yaml entries:
- vibevoice-cpp     - realtime 0.5B Q8_0 TTS + tokenizer + Carter voice
- vibevoice-cpp-asr - long-form ASR Q8_0 + tokenizer

Both pull from huggingface://mudler/vibevoice.cpp-models with sha256
verification. parameters.model + Options[] paths are siblings under
{models_dir} per the qwen3-tts-cpp convention.

Update Makefile e2e wrappers to pass BACKEND_TEST_OPTIONS comma+colon
style, and tighten the per-backend Go closed-loop test to use the
explicit Options API.

* fix(vibevoice-cpp): force whole-archive link so vv_capi_* exports survive

libvibevoice is a STATIC archive linked into the MODULE library.
Without --whole-archive (or -force_load on Apple, /WHOLEARCHIVE on
MSVC), the linker garbage-collects symbols not referenced from this
translation unit - which means dlopen+RegisterLibFunc panics with
'undefined symbol: vv_capi_load' at backend startup, since purego
looks them up by name and our cpp/govibevoicecpp.cpp doesn't call
them directly.

* test(vibevoice-cpp): rewrite suite with Ginkgo v2

Match the convention used by backend/go/sherpa-onnx/backend_test.go.
The suite now covers backend semantics that don't need purego (Locking,
empty-ModelFile rejection, TTS/ASR-without-loaded-model errors) on top
of the gRPC lifecycle specs (Health, Load, closed-loop TTS->ASR).
Model-dependent specs Skip() when VIBEVOICE_MODEL_DIR is unset, so
`go test ./backend/go/vibevoice-cpp/` is green on a clean checkout
and runs the heavyweight closed-loop spec when test.sh has staged
the bundle.

* fix(vibevoice-cpp): implement TTSStream + AudioTranscriptionStream

The gRPC server's stream handlers (pkg/grpc/server.go) spawn a
goroutine that ranges over a chan; the only thing closing that chan
is the backend's own *Stream method. With the default Base stub
returning 'unimplemented' and never touching the chan, the server
goroutine hangs forever and the client hits DeadlineExceeded - which
is exactly what the e2e harness saw in the test-extra-backend-vibevoice-cpp-tts
matrix run.

TTSStream synthesizes via vv_capi_tts to a tempfile, then emits a
streaming WAV header (chunk sizes 0xFFFFFFFF so HTTP clients can
start playback before the full PCM lands) followed by the PCM body
in 64 KB slices. The header + >=2 PCM frames satisfy the harness's
'expected >=2 chunks' assertion and give a real progressive stream.

AudioTranscriptionStream runs the offline transcription, emits each
segment as a delta, and closes with a final_result whose Text equals
the concatenated deltas (the harness asserts those match).

Two new Ginkgo specs guard the close-channel-on-error path so the
deadline-exceeded regression can't come back silently.

* fix(vibevoice-cpp): silence errcheck on cleanup paths

Lint flagged six unchecked Close()/Remove()/RemoveAll() calls along
purely-cleanup deferred paths. Wrap each in '_ = ...' (or a closure
for defers that take args) - matches what the rest of the LocalAI
backend/go/* tree already does for these callsites.

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

* fix(vibevoice-cpp): closed-loop slot fill + modelRoot-relative path resolution

Two bugs the test-extra-backend-vibevoice-cpp-* CI matrix surfaced:

1. Closed-loop Load with ModelFile=tts.gguf + Options[asr_model=...] left
   v.ttsModel empty, because the default-fill block only ran when BOTH
   slots were empty. vv_capi_load then got tts="" + a voice and the
   C side rejected it with rc=-3 'TTS model required to load a voice'.
   Fix: ModelFile fills the *primary* role-slot (decided by 'type=' in
   Options, defaulting to tts) independently of the secondary, so
   ModelFile + asr_model resolves to both.

2. resolvePath stat'd CWD before falling back to relTo. With LocalAI
   launched from a directory that happens to contain a same-named
   file, supplementary Options[] paths could leak away from the
   models dir. Drop the CWD probe entirely - relative paths now
   *always* join onto opts.ModelPath (the gallery convention).

New Ginkgo coverage:
  * 'ModelFile slot resolution' (4 specs) - asr_model+ModelFile, type=asr,
    explicit tts_model override, key:value variant.
  * 'resolvePath (relative-to-modelRoot)' (5 specs) - join, abs passthrough,
    empty input, empty relTo, and the CWD-trap regression test.
  * 'Load resolves relative Options paths against opts.ModelPath' - end-
    to-end gallery layout round-trip.

Verified locally: 19/19 specs pass (with model bundle, including the
closed-loop TTS->ASR; without bundle, 17 pass + 2 model-dependent skip).

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

* test(vibevoice-cpp): use gallery convention in closed-loop spec

The 'loads the realtime TTS model' / closed-loop specs were passing
already-prefixed paths into Options[]:

    Options: ['tokenizer=' + filepath.Join(modelDir, 'tokenizer.gguf')]

Combined with no ModelPath set on the request, the backend's
modelRoot fell back to filepath.Dir(ModelFile) = modelDir, then
resolvePath joined the prefixed Options path on top of it -
producing 'vibevoice-models/vibevoice-models/tokenizer.gguf' when
the CI's VIBEVOICE_MODEL_DIR is the relative './vibevoice-models'.

The fix is to mirror the gallery contract LocalAI core actually
sends in production: ModelPath is the models root (absolute),
ModelFile is a name *under* it, every Options[] path is relative
to ModelPath. Uses filepath.Base() to get bare filenames.

Verified locally with both VIBEVOICE_MODEL_DIR=/tmp/vv-bundle (abs)
and VIBEVOICE_MODEL_DIR=vibevoice-models (the relative shape that
broke CI). Both: 19/19 specs pass, ~55-60s.

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

* ci(vibevoice-cpp): switch ASR to Q4_K + bump transcription timeout

The Q8_0 ASR gguf is ~14 GB - too big to fit alongside the runner
image, the docker build cache, and the test artifacts on a free
ubuntu-latest GHA runner; 'test-extra-backend-vibevoice-cpp-transcription'
was getting SIGTERM'd at 90 min before the model could finish loading.

Switch to Q4_K (~10 GB on disk, slightly faster CPU decode) for:
  * the e2e harness Make target
  * the gallery 'vibevoice-cpp-asr' entry (parameters + files block)
  * the per-backend test.sh auto-download list

Bump tests-vibevoice-cpp-grpc-transcription's timeout-minutes from
90 to 150 - even with Q4_K, the 30 s JFK clip on a CPU runner needs
runway above the previous 90 min cap.

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

* ci(vibevoice-cpp): drop transcription gRPC e2e job - too heavy for free runners

The vibevoice ASR is a 7B-parameter model. Even on Q4_K (~10 GB on
disk) a single 30 s transcription saturates the per-test 30 min
timeout in the e2e-backends harness on a 4-core ubuntu-latest, and
the 10 GB download + Docker layer + working space leaves no headroom
on the runner's free disk. Two attempts in CI got SIGTERM'd at the
LoadModel boundary - the bottleneck isn't tunable from the workflow
side without a paid-tier runner.

The per-backend tests-vibevoice-cpp job already runs the same
AudioTranscription path via a closed-loop TTS->ASR Ginkgo spec - same
gRPC contract, same model, single process - so the standalone
tests-vibevoice-cpp-grpc-transcription job was redundant on top of
the disk/CPU pressure.

The Makefile target test-extra-backend-vibevoice-cpp-transcription
stays for local invocation on workstations that can afford it -
useful when developing the streaming codepaths.

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

* ci(vibevoice-cpp): restore transcription gRPC e2e on bigger-runner

Switch tests-vibevoice-cpp-grpc-transcription from ubuntu-latest to
the self-hosted 'bigger-runner' label that GPU image builds in
backend.yml use, plus the documented Free-disk-space prep step (purge
dotnet / ghc / android / CodeQL caches) the disabled vllm/sglang
entries in this file describe. That gives the 7B-param Q4_K ASR
model the disk + CPU runway it needs.

Keep timeout-minutes: 150 - even on a beefier runner the 30 s JFK
decode plus 10 GB download has to fit comfortably.

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

* ci(vibevoice-cpp): apt-get install make on bigger-runner before transcription e2e

bigger-runner is a self-hosted bare runner without the standard
ubuntu image's preinstalled build tools, so the previous job died at
the very first command with 'make: command not found' (exit 127).
Add the Dependencies step that the disabled vllm/sglang entries in
this file already document - apt-get installs make + build-essential
+ curl + unzip + ca-certificates + git + tar before the make target
runs. Mirrors how every other 'runs-on: bigger-runner' entry in
backend.yml prepares the runner.

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-29 22:22:14 +02:00
LocalAI [bot]
13fe37df89 chore(model gallery): 🤖 add 1 new models via gallery agent (#9611)
chore(model gallery): 🤖 add new models via gallery agent

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-29 09:06:22 +02:00
Richard Palethorpe
4916f8c880 feat(vllm): expose AsyncEngineArgs via generic engine_args YAML map (#9563)
* feat(vllm): expose AsyncEngineArgs via generic engine_args YAML map

LocalAI's vLLM backend wraps a small typed subset of vLLM's
AsyncEngineArgs (quantization, tensor_parallel_size, dtype, etc.).
Anything outside that subset -- pipeline/data/expert parallelism,
speculative_config, kv_transfer_config, all2all_backend, prefix
caching, chunked prefill, etc. -- requires a new protobuf field, a
Go struct field, an options.go line, and a backend.py mapping per
feature. That cadence is the bottleneck on shipping vLLM's
production feature set.

Add a generic `engine_args:` map on the model YAML that is
JSON-serialised into a new ModelOptions.EngineArgs proto field and
applied verbatim to AsyncEngineArgs at LoadModel time. Validation
is done by the Python backend via dataclasses.fields(); unknown
keys fail with the closest valid name as a hint.
dataclasses.replace() is used so vLLM's __post_init__ re-runs and
auto-converts dict values into nested config dataclasses
(CompilationConfig, AttentionConfig, ...). speculative_config and
kv_transfer_config flow through as dicts; vLLM converts them at
engine init.

Operators can now write:

  engine_args:
    data_parallel_size: 8
    enable_expert_parallel: true
    all2all_backend: deepep_low_latency
    speculative_config:
      method: deepseek_mtp
      num_speculative_tokens: 3
    kv_cache_dtype: fp8

without further proto/Go/Python plumbing per field.

Production defaults seeded by hooks_vllm.go: enable_prefix_caching
and enable_chunked_prefill default to true unless explicitly set.

Existing typed YAML fields (gpu_memory_utilization,
tensor_parallel_size, etc.) remain for back-compat; engine_args
overrides them when both are set.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* chore(vllm): pin cublas13 to vLLM 0.20.0 cu130 wheel

vLLM's PyPI wheel is built against CUDA 12 (libcudart.so.12) and won't
load on a cu130 host. Switch the cublas13 build to vLLM's per-tag cu130
simple-index (https://wheels.vllm.ai/0.20.0/cu130/) and pin
vllm==0.20.0. The cu130-flavoured wheel ships libcudart.so.13 and
includes the DFlash speculative-decoding method that landed in 0.20.0.

cublas13 install gets --index-strategy=unsafe-best-match so uv consults
both the cu130 index and PyPI when resolving — PyPI also publishes
vllm==0.20.0, but with cu12 binaries that error at import time.

Verified: Qwen3.5-4B + z-lab/Qwen3.5-4B-DFlash loads and serves chat
completions on RTX 5070 Ti (sm_120, cu130).

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* ci(vllm): bot job to bump cublas13 vLLM wheel pin

vLLM's cu130 wheel index URL is itself version-locked
(wheels.vllm.ai/<TAG>/cu130/, no /latest/ alias upstream), so a vLLM
bump means rewriting two values atomically — the URL segment and the
version constraint. bump_deps.sh handles git-sha-in-Makefile only;
add a sibling bump_vllm_wheel.sh and a matching workflow job that
mirrors the existing matrix's PR-creation pattern.

The bumper queries /releases/latest (which excludes prereleases),
strips the leading 'v', and seds both lines unconditionally. When the
file is already on the latest tag the rewrite is a no-op and
peter-evans/create-pull-request opens no PR.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* docs(vllm): document engine_args and speculative decoding

The new engine_args: map plumbs arbitrary AsyncEngineArgs through to
vLLM, but the public docs only covered the basic typed fields. Add a
short subsection in the vLLM section explaining the typed/generic
split and showing a worked DFlash speculative-decoding config, with
pointers to vLLM's SpeculativeConfig reference and z-lab's drafter
collection.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2026-04-29 00:49:28 +02:00
LocalAI [bot]
55afda22e3 chore: ⬆️ Update ikawrakow/ik_llama.cpp to 453a027c17e4d63a7f16b871197a396240a65138 (#9608)
⬆️ Update ikawrakow/ik_llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-29 00:18:19 +02:00
LocalAI [bot]
1fe3558ec6 feat(swagger): update swagger (#9607)
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-29 00:18:02 +02:00
Ettore Di Giacinto
e370318bd7 fix(vllm): seed pybind11 for fastsafetensors build under --no-build-isolation
fastsafetensors==0.3 (transitive dep of vllm) imports pybind11 in
setup.py without declaring it in build-system.requires. With
--no-build-isolation it has to already exist in the venv, otherwise the
wheel build fails with ModuleNotFoundError on arm64 L4T CUDA 13 (and
any other profile that picks up vllm 0.20.0).

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-28 20:08:26 +00:00
Richard Palethorpe
4443250756 chore: add golangci-lint with new-from-merge-base baseline (#9603)
* chore: add golangci-lint with new-from-merge-base baseline

Configure golangci-lint v2 with the standard linter set (errcheck, govet,
ineffassign, unused) plus forbidigo, which enforces the Ginkgo/Gomega-only
test convention from .agents/coding-style.md by rejecting stdlib testing
calls (t.Errorf, t.Fatalf, t.Run, ...). staticcheck is disabled — the
codebase has many pre-existing QF-style suggestions not worth gating on.

issues.new-from-merge-base = master makes the lint job a gate for new
issues only; the ~1300 pre-existing baseline stays visible via
'make lint-all' for incremental cleanup. CI runs 'make lint'.

Backends needing C/C++ headers we don't install in the lint runner are
excluded via a deny list in the Makefile (backend/go/{piper,silero-vad,
llm}, cmd/launcher). Discovery still flows through 'go list ./...', so
new packages are scanned automatically.

To make backend/go/{sam3-cpp,stablediffusion-ggml,whisper} typecheckable,
move their .cpp/.h sources into cpp/ subdirs (matching qwen3-tts-cpp /
acestep-cpp). Without this 'go list' rejects the package because Go does
not allow .cpp alongside .go without cgo.

Fix two real bugs found by lint in tests/integration/ (run only via
'make test-stores', not default CI): a stale zerolog reference left over
from the slog migration (c37785b7) and an unused 'os' import.

Assisted-by: Claude Code:Opus 4.7 (1M) [Bash] [Read] [Edit] [Write]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* ci(lint): generate proto sources and fetch full history

The lint job was failing for two reasons:

- pkg/grpc/proto/*.go is generated, not checked in. Several packages
  import it, so without 'make protogen-go' typecheck fails project-wide
  with "no required module provides package github.com/mudler/LocalAI/
  pkg/grpc/proto".

- golangci-lint's new-from-merge-base needs to git-merge-base the PR
  against master, but actions/checkout's default shallow clone doesn't
  fetch master. fetch-depth: 0 brings full history; the config now
  references origin/master (the remote-tracking branch that survives
  the shallow checkout) instead of bare master (which doesn't exist
  locally after checkout).

Assisted-by: Claude Code:Opus 4.7 (1M) [Bash] [Read] [Edit] [Write]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* ci(lint): stub react-ui/dist for go:embed glob

core/http/app.go has //go:embed react-ui/dist/*. The glob must match at
least one non-hidden entry or typecheck fails the whole core/http
package. We don't need the real React bundle to lint Go code, so just
touch an empty index.html to satisfy the embed.

Assisted-by: Claude Code:Opus 4.7 (1M) [Bash] [Read] [Edit] [Write]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-04-28 22:07:44 +02:00
Ettore Di Giacinto
bcef72b9c1 feat: localai assistant chat modality (#9602)
* fix(tests): inline model_test fixtures after tests/models_fixtures removal

The previous reorg removed tests/models_fixtures/ but core/config/model_test.go
still read CONFIG_FILE/MODELS_PATH env vars pointing into that directory, so
`make test` failed with "open : no such file or directory" on the readConfigFile
spec (the suite ran with --fail-fast and bailed before openresponses_test).

Inline the YAMLs (config/embeddings/grpc/rwkv/whisper) directly into the test
file, materialise them into a per-test tmpdir via BeforeEach, and drop the
env-var lookups. The test no longer depends on Makefile plumbing.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Edit] [Write] [Bash]

* refactor(modeladmin): extract model-admin helpers into a service package

Lift the bodies of EditModelEndpoint, PatchConfigEndpoint,
ToggleStateModelEndpoint, TogglePinnedModelEndpoint and
VRAMEstimateEndpoint into core/services/modeladmin so the same logic can
be called by non-HTTP clients (notably the in-process MCP server that
backs the LocalAI Assistant chat modality, landing in a follow-up commit).

The HTTP handlers shrink to thin shells that parse echo inputs, call the
matching helper, map typed errors (ErrNotFound, ErrConflict,
ErrPathNotTrusted, ErrBadAction, ...) to the existing HTTP status codes,
and render the existing response shapes. No REST-surface behaviour change;
the existing localai endpoint tests cover the regression net.

Adds focused unit tests for each helper against tmp-dir-backed
ModelConfigLoader fixtures (deep-merge patch, rename + conflict, path
separator guard, toggle/pin enable/disable, sync callback).

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(assistant): LocalAI Assistant chat modality with in-memory MCP server

Adds a chat modality, admin-only, that wires the chat session to an
in-memory MCP server exposing LocalAI's own admin/management surface as
tools. An admin can install models, manage backends, edit configs and
check status by chatting; the LLM calls tools like gallery_search,
install_model, import_model_uri, list_installed_models, edit_model_config
and surfaces the results.

Same Go package powers two modes:

  pkg/mcp/localaitools/

    NewServer(client, opts) builds an MCP server that registers the
    19-tool admin catalog. The LocalAIClient interface has two impls:

    - inproc.Client — calls services directly (no HTTP loopback,
      no synthetic admin API key). Used in-process by the chat handler.
    - httpapi.Client — calls the LocalAI REST API. Used by the new
      `local-ai mcp-server --target=…` subcommand to control a remote
      LocalAI from a stdio MCP host.

    Tools and their embedded skill prompts are agnostic to which client
    backs them. Skill prompts are markdown files under prompts/, embedded
    via go:embed and assembled into the system prompt at server init.

Wiring:

  - core/http/endpoints/mcp/localai_assistant.go — process-wide holder
    that spins up the in-memory MCP server once at Application start
    using paired net.Pipe transports, then reuses LocalToolExecutor
    (no fork) for every chat request that opts in.

  - core/http/endpoints/openai/chat.go — small branch ahead of the
    existing MCP block: when metadata.localai_assistant=true,
    defense-in-depth admin check + executor swap + system-prompt
    injection. All downstream tool dispatch is unchanged.

  - core/http/auth/{permissions,features}.go — adds
    FeatureLocalAIAssistant; gating happens at the chat handler entry
    plus admin-only `/api/settings`.

  - core/cli/{run.go,cli.go,mcp_server.go} —
    LOCALAI_DISABLE_ASSISTANT flag (runtime-toggleable via Settings, no
    restart), plus `local-ai mcp-server` stdio subcommand.

  - core/config/runtime_settings.go — `localai_assistant_enabled`
    runtime setting; the chat handler reads `DisableLocalAIAssistant`
    live at request entry.

UI:

  - Home.jsx — prominent self-explanatory CTA card on first run
    ("Manage LocalAI by chatting"); collapses to a compact
    "Manage by chat" button in the quick-links row once used,
    persisted via localStorage.
  - Chat.jsx — admin-only "Manage" toggle in the chat header,
    "Manage mode" badge, dedicated empty-state copy, starter chips.
  - Settings.jsx — "LocalAI Assistant" section with the runtime
    enable toggle.
  - useChat.js — `localaiAssistant` flag on the chat schema; injects
    `metadata.localai_assistant=true` on requests when active.

Distributed mode: the in-memory MCP server lives only on the head node;
inproc.Client wraps already-distributed-aware services so installs
propagate to workers via the existing GalleryService machinery.

Documentation: `.agents/localai-assistant-mcp.md` is the contributor
contract — when adding an admin REST endpoint, also add a LocalAIClient
method, an inproc + httpapi impl, a tool registration, and a skill
prompt update; the AGENTS.md index links to it.

Out of scope (follow-ups): per-tool RBAC granularity for non-admin
read-only access; streaming mcp_tool_progress for long installs;
React Vitest rig for the UI changes.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(assistant): extract tool/capability/MiB/server-name constants

The MCP tool surface, capability tag set, server-name default, and the
chat-handler metadata key were repeated as bare string literals across
seven files. Renaming any one required hand-editing every call site and
risked code/test/prompt drift.

This pulls them into typed constants:

- pkg/mcp/localaitools/tools.go — Tool* constants for the 19 MCP tools,
  plus DefaultServerName.
- pkg/mcp/localaitools/capability.go — typed Capability + constants for
  the capability tag set the LLM passes to list_installed_models. The
  type rides through LocalAIClient.ListInstalledModels and replaces the
  triplet of "embed"/"embedding"/"embeddings" with the single
  CapabilityEmbeddings.
- pkg/mcp/localaitools/inproc/client.go — bytesPerMiB constant for the
  VRAMEstimate byte→MB conversion.
- core/http/endpoints/mcp/tools.go — MetadataKeyLocalAIAssistant for the
  "localai_assistant" request-metadata key consumed by the chat handler.

Tool registrations, the test catalog, the dispatch table, the validation
fixtures, and the fake/stub clients all reference the constants. The
embedded skill prompts under prompts/ keep their bare strings (go:embed
markdown can't import Go constants); the existing TestPromptsContain
SafetyAnchors guards the alignment.

No behaviour change. All tests pass with -race.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(modeladmin): typed Action for ToggleState/TogglePinned

The toggle/pin verbs were bare strings everywhere — handler signatures,
service implementations, MCP tool args, the fake/stub clients, the
inproc and httpapi LocalAIClient impls, plus 4 test files. A typo in
any caller silently fell through to the runtime "must be 'enable' or
'disable'" check.

Introduce core/services/modeladmin.Action (string alias) with
ActionEnable, ActionDisable, ActionPin, ActionUnpin and a small Valid
helper. The compiler now catches mismatches at every boundary; renames
ripple through one source of truth.

LocalAIClient.ToggleModelState/Pinned signatures change to take
modeladmin.Action. The package is brand-new and unreleased so this is
a free public-API tightening.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(assistant): respect ctx cancellation on gallery channel sends

InstallModel, DeleteModel, ImportModelURI, InstallBackend and
UpgradeBackend all pushed onto galleryop channels with bare sends. If the
worker was paused or the buffer full, the chat-handler goroutine blocked
forever — the LLM kept polling and the request leaked.

Wrap the five sends in a sendModelOp/sendBackendOp helper that selects
on ctx.Done() so a cancelled chat completion surfaces context.Canceled
back to the LLM instead of hanging.

Adds inproc/client_test.go with a pre-cancelled-ctx regression test on
InstallModel; the helpers are shared so the same guarantee covers the
other four call sites.

Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(assistant): graceful shutdown for in-memory holder and stdio CLI

Two related leaks:

- Application.start() built the LocalAIAssistantHolder but never wired
  Close() into the graceful-termination chain — the in-memory MCP
  transport pair stayed alive until process exit, and the goroutines
  behind net.Pipe() didn't drain. Hook into the existing
  signals.RegisterGracefulTerminationHandler chain (same pattern as
  core/http/endpoints/mcp/tools.go:770).

- core/cli/mcp_server.go ran srv.Run with context.Background(); a
  Ctrl-C from the host (Claude Desktop, mcphost, npx inspector) or a
  SIGTERM from process supervision left the stdio loop reading from a
  closed pipe. Switch to signal.NotifyContext to surface the signal
  through ctx and let srv.Run drain.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(assistant): typed HTTPError + propagate prompt walk error

The httpapi client detected "no such job" by substring-matching on the
error string ("404", "could not find") — brittle to status-code
formatting changes and to LocalAI fixing /models/jobs/:uuid to return a
proper 404. Replace with a typed *HTTPError whose Is() method honours
errors.Is(err, ErrHTTPNotFound). The 500-with-"could not find" branch
stays as a transitional fallback documented in Is().

Same change covers ListNodes' 404 fallback for the /api/nodes endpoint.

Adds httptest tests for both 404 and the legacy 500 path, plus a
direct errors.Is exposure test so external callers (the standalone
stdio CLI host) can match without re-string-parsing.

Also tightens prompts.SystemPrompt: panic when fs.WalkDir on the
embedded FS fails. The only realistic cause is a build-time //go:embed
misconfiguration; serving an empty system prompt to the LLM is much
worse than crashing init. TestSystemPromptIncludesAllEmbeddedFiles
catches regressions in CI.

Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(modeladmin): atomic writes for model config files

The five sites that wrote model YAML used os.WriteFile, which opens
with O_TRUNC|O_WRONLY|O_CREATE. A crash mid-write left the destination
truncated and the model unloadable until manual repair. Pre-existing
behaviour inherited from the original endpoint handlers — fix once now
that there's a single helper.

Adds writeFileAtomic: writes to a sibling temp file, chmods, syncs via
Close(), then os.Rename. Same-directory temp keeps the rename atomic on
the same filesystem; cleanup runs on every error path so stray temps
don't accumulate. No new dependency.

Applied to:
- ConfigService.PatchConfig
- ConfigService.EditYAML (both rename and in-place branches)
- mutateYAMLBoolFlag (drives ToggleState + TogglePinned)

atomic_test.go covers the happy path plus a read-only-dir failure case
that asserts the original file is preserved (skipped on Windows where
the chmod trick is POSIX-specific).

Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(assistant): prune dead code, mark stub, document conventions

Three small cleanups landing together:

- Drop the unused errNotImplemented sentinel from inproc/client.go.
  All five methods that used to return it are wired to modeladmin
  helpers since the Phase B commit; the package var is dead.

- Annotate httpapi.Client.GetModelConfig as a known stub. LocalAI's
  /models/edit/:name returns rendered HTML, not JSON, so the standalone
  CLI's get_model_config tool surfaces a clear error to the LLM. A
  future JSON-only /api/models/config-yaml/:name endpoint is tracked in
  the agent contract; FIXME points at it.

- Extend `.agents/localai-assistant-mcp.md` with a "Code conventions"
  section that documents the audit-driven rules: tool/Capability/Action
  constants, errors.Is over substring matching, ctx-aware channel
  sends, atomic writes, and graceful shutdown. Refresh the file map so
  it lists tools.go and capability.go and drops the removed
  tools_bootstrap.go.

The tools_models.go diff is a comment-only change explaining why the
ModelName empty-string check stays at the tool layer (consistency
across LocalAIClient implementations, since the SDK schema validator
only enforces presence, not non-empty).

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test(assistant): convert test files to ginkgo + gomega

The repo convention (per core/http/endpoints/localai/*_test.go,
core/gallery/**, etc.) is Ginkgo v2 with Gomega assertions. The tests I
introduced for the assistant feature used vanilla testing.T, which made
them stand out and stripped the BDD structure the rest of the suite
relies on.

Convert every test file in the assistant scope to Ginkgo:

  pkg/mcp/localaitools/
    dto_test.go            — Describe("DTOs round-trip through JSON")
    prompts_test.go        — Describe("SystemPrompt assembler")
    server_test.go         — Describe("Server tool catalog"),
                              Describe("Tool dispatch"),
                              Describe("Tool error surfacing"),
                              Describe("Argument validation"),
                              Describe("Concurrent tool calls")
    parity_test.go         — Describe("LocalAIClient parity"),
                              hosts the suite's single RunSpecs (the file
                              is package localaitools_test so it can
                              import httpapi without an import cycle;
                              Ginkgo aggregates Describes from both the
                              internal and external test packages into
                              one run).
    httpapi/client_test.go — Describe("httpapi.Client against the
                              LocalAI admin REST surface"),
                              Describe("ErrHTTPNotFound"),
                              Describe("Bearer token")
    inproc/client_test.go  — Describe("inproc.Client cancellation")

  core/services/modeladmin/
    config_test.go         — Describe("ConfigService") with sub-Describes
                              for GetConfig, PatchConfig, EditYAML
    state_test.go          — Describe("ConfigService.ToggleState")
    pinned_test.go         — Describe("ConfigService.TogglePinned")
    atomic_test.go         — Describe("writeFileAtomic")

  core/http/endpoints/mcp/
    localai_assistant_test.go — Describe("LocalAIAssistantHolder")

Each package gets a `*_suite_test.go` with the standard
`RegisterFailHandler(Fail) + RunSpecs(t, "...")` boilerplate. Helpers
that previously took *testing.T (newTestService, writeModelYAML,
readMap, sortedStrings, sortGalleries, etc.) drop the *T receiver and
use Gomega Expectations directly. tmp dirs come from GinkgoT().TempDir().

No semantic change to test coverage — every original assertion has a
direct Gomega counterpart. All suites pass with -race.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test+docs(assistant): drift detector for Tool ↔ REST route mapping

Honest gap from the audit: the parity_test.go suite only checks four
methods, and uses the same httpapi.Client for both sides — it asserts
stability of the DTO shapes, not equivalence between in-process and
HTTP. If a contributor adds an admin REST endpoint without an MCP tool,
or a tool without a matching httpapi route, both surfaces silently
diverge.

Add a coverage test plus stronger docs:

- pkg/mcp/localaitools/coverage_test.go introduces a hand-maintained
  toolToHTTPRoute map: every Tool* constant must list the REST endpoint
  the httpapi.Client hits (or "(none)" with a documented reason). Two
  Ginkgo specs assert the map and the published catalog stay in sync —
  one fails when a Tool is added without a route entry, the other fails
  when a route entry references a tool that no longer exists. Verified
  by removing the ToolDeleteModel entry locally; the test fired with a
  clear message pointing the contributor at the file.

  Deliberate non-test: we don't enumerate live admin REST routes from
  here. Walking the route registry requires booting Application;
  parsing core/http/routes/localai.go is brittle. The "new admin REST
  endpoint → MCP tool" direction stays a PR checklist item — see below.

- AGENTS.md gets a new Quick Reference bullet that calls out the rule
  and points at the test by name.

- .agents/api-endpoints-and-auth.md tightens the existing "Companion:
  MCP admin tool surface" subsection from "if useful, consider..." to
  "MUST be considered, with three concrete outcomes (tool added,
  deliberately skipped with documented reason, or forgot — which
  breaks the contract)". Adds a checklist item at the bottom of the
  file's authoritative checklist.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(assistant): drop duplicate DTOs, surface canonical types

Audit feedback: localaitools/dto.go reinvented several types that already
existed in the codebase. Replace the duplicates with the canonical types
so the LLM-visible wire format stays aligned with the rest of LocalAI by
construction (no parallel structs to keep in sync).

Removed (and the canonical type now used by the LocalAIClient interface):

  localaitools.Gallery          → config.Gallery
  localaitools.GalleryModelHit  → gallery.Metadata
  localaitools.VRAMEstimate     → vram.EstimateResult

Tightened scope:

  localaitools.Backend          → kept, but reduced to {Name, Installed}.
                                  ListKnownBackends now returns
                                  []schema.KnownBackend (the canonical
                                  type already used by REST /backends/known).

Kept with documented rationale:

  localaitools.JobStatus       — galleryop.OpStatus has Error error which
                                 marshals to "{}". JobStatus is the
                                 JSON-friendly mirror.
  localaitools.Node            — nodes.BackendNode carries gorm internals
                                 + token hash; we expose only the
                                 LLM-relevant fields.
  ImportModelURIRequest/Response — schema.ImportModelRequest and
                                   GalleryResponse are wire-shaped, mine
                                   are LLM-shaped (BackendPreference flat,
                                   AmbiguousBackend exposed).

Side wins:

  - Drop bytesPerMiB; vram.EstimateResult already carries human-readable
    display strings (size_display, vram_display) the LLM uses directly.
  - Drop the handler-private vramEstimateRequest in
    core/http/endpoints/localai/vram.go and bind directly into
    modeladmin.VRAMRequest (now JSON-tagged).

Both clients pass through these types now where possible (e.g.
ListGalleries in inproc.Client is a one-liner returning
AppConfig.Galleries; httpapi.Client.GallerySearch decodes straight into
[]gallery.Metadata).

All tests green with -race.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(assistant): extract REST route paths into named constants

httpapi.Client had 18 bare-string path sites scattered across methods.
Pull them into pkg/mcp/localaitools/httpapi/routes.go: static paths as
package-private constants, dynamic paths as small builders that handle
url.PathEscape on segment values.

No behaviour change. Drops the now-unused net/url import from client.go
since path escaping moved into routes.go alongside the path it applies to.

Local-only by design: the server-side registrations in
core/http/routes/localai.go remain bare strings. Sharing constants across
the pkg/ ↔ core/ boundary would invert the layering today; the existing
Tool↔REST drift-detector in coverage_test.go is the safety net for that
direction.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* docs(assistant): align with shipped UI and dropped bootstrap env vars

The LocalAI Assistant doc still described the older iteration:

- The in-chat toggle was renamed from "Admin" to "Manage" (the badge is
  now "Manage mode" and the home page exposes a "Manage by chat" CTA).
- LOCALAI_ASSISTANT_BOOTSTRAP_MODEL / --localai-assistant-bootstrap-model
  and the bootstrap_default_model tool were removed — admins pick a model
  from the existing selector instead, no env-var configuration required.
- The shipped tool catalog includes import_model_uri but didn't appear in
  the doc; bootstrap_default_model appeared but no longer exists.
- The Settings → LocalAI Assistant runtime toggle wasn't mentioned as the
  preferred way to disable without restart.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-28 19:29:27 +02:00
Ettore Di Giacinto
142919fc79 fix(tests): inline model_test fixtures after tests/models_fixtures removal
The previous reorg removed tests/models_fixtures/ but core/config/model_test.go
still read CONFIG_FILE/MODELS_PATH env vars pointing into that directory, so
`make test` failed with "open : no such file or directory" on the readConfigFile
spec (the suite ran with --fail-fast and bailed before openresponses_test).

Inline the YAMLs (config/embeddings/grpc/rwkv/whisper) directly into the test
file, materialise them into a per-test tmpdir via BeforeEach, and drop the
env-var lookups. The test no longer depends on Makefile plumbing.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Edit] [Write] [Bash]
2026-04-28 12:58:49 +00:00
dependabot[bot]
439471baec chore(deps): bump packaging from 24.1 to 26.2 in /backend/python/coqui (#9594)
Bumps [packaging](https://github.com/pypa/packaging) from 24.1 to 26.2.
- [Release notes](https://github.com/pypa/packaging/releases)
- [Changelog](https://github.com/pypa/packaging/blob/main/CHANGELOG.rst)
- [Commits](https://github.com/pypa/packaging/compare/24.1...26.2)

---
updated-dependencies:
- dependency-name: packaging
  dependency-version: '26.2'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-04-28 08:44:53 +02:00
dependabot[bot]
eff4be6794 chore(deps): bump github.com/onsi/ginkgo/v2 from 2.28.1 to 2.28.2 (#9593)
Bumps [github.com/onsi/ginkgo/v2](https://github.com/onsi/ginkgo) from 2.28.1 to 2.28.2.
- [Release notes](https://github.com/onsi/ginkgo/releases)
- [Changelog](https://github.com/onsi/ginkgo/blob/master/CHANGELOG.md)
- [Commits](https://github.com/onsi/ginkgo/compare/v2.28.1...v2.28.2)

---
updated-dependencies:
- dependency-name: github.com/onsi/ginkgo/v2
  dependency-version: 2.28.2
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-04-28 08:44:41 +02:00
dependabot[bot]
f1ec30d646 chore(deps): bump github.com/testcontainers/testcontainers-go/modules/postgres from 0.41.0 to 0.42.0 (#9591)
chore(deps): bump github.com/testcontainers/testcontainers-go/modules/postgres

Bumps [github.com/testcontainers/testcontainers-go/modules/postgres](https://github.com/testcontainers/testcontainers-go) from 0.41.0 to 0.42.0.
- [Release notes](https://github.com/testcontainers/testcontainers-go/releases)
- [Commits](https://github.com/testcontainers/testcontainers-go/compare/v0.41.0...v0.42.0)

---
updated-dependencies:
- dependency-name: github.com/testcontainers/testcontainers-go/modules/postgres
  dependency-version: 0.42.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-04-28 08:44:27 +02:00
LocalAI [bot]
f3500223d7 chore: ⬆️ Update leejet/stable-diffusion.cpp to a81677f59c92d90343aebca51dfed7decf0a0cb0 (#9586)
⬆️ Update leejet/stable-diffusion.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-28 08:44:10 +02:00
LocalAI [bot]
b69bacfcdc chore: ⬆️ Update ikawrakow/ik_llama.cpp to d6f3e4e28fbf75e6181e6ea32e734de9ce9304fd (#9585)
⬆️ Update ikawrakow/ik_llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-28 08:43:51 +02:00
LocalAI [bot]
8e50066fa2 chore: ⬆️ Update ggml-org/llama.cpp to 665abc609740d397d30c0d8ef4157dbf900bd1a3 (#9584)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-28 08:43:33 +02:00
Ettore Di Giacinto
a0317d9926 refactor(tests): split app_test.go, move real-backend coverage to e2e-backends
core/http/app_test.go had grown to 1495 lines exercising three concerns at
once: HTTP-layer integration, real-backend inference (llama-gguf, tts,
stablediffusion, transformers embeddings, whisper), and service logic that
already has unit-level coverage. Each PR paid for 6 backend builds plus
real-model downloads to satisfy a single suite.

Reorg per layer:

- app_test.go (1495 -> 1003 lines) drives the mock-backend binary only.
  Kept: auth, routing, gallery API, file:// import, /system, agent-jobs
  HTTP plumbing, config-file model loading. Deleted real-inference specs
  (llama-gguf chat, ggml completions/streaming, logprobs, logit_bias,
  transcription, embeddings, External-gRPC, Stores duplicate, Model gallery
  Context). Lifted Agent Jobs out of the deleted Stores Context.
- tests/e2e-backends/backend_test.go gains logprobs, logit_bias, and
  no-first-token-dup specs (the latter folded into PredictStream). Two
  new caps gate them so non-LLM backends opt out.
- tests/e2e-aio/e2e_test.go gains a streaming smoke under Context("text")
  to catch container-level streaming regressions.
- tests/models_fixtures/ removed; all fixtures referenced testmodel.ggml.
  app_test.go now writes per-Context inline mock-model YAMLs.

CI:

- test.yml + tests-e2e.yml gain paths-ignore (docs/, examples/, *.md,
  backend/) so docs and backend-only PRs skip them. test.yml drops the
  6-backend Build step plus TRANSFORMER_BACKEND/GO_TAGS=tts; tests-apple
  drops the llama-cpp-darwin build.
- New tests-aio.yml runs the AIO container nightly + on workflow_dispatch
  + master/tags. The tests-e2e-container job moved out of test.yml so PRs
  no longer pay AIO cost.
- New tests-llama-cpp-smoke job in test-extra.yml runs on every PR with
  no detect-changes gate; pulls quay.io/go-skynet/local-ai-backends:
  master-cpu-llama-cpp (no build on PR) and exercises predict/stream/
  logprobs/logit_bias against Qwen3-0.6B. This is the PR-acceptance
  real-backend gate after AIO moved to nightly. The path-gated heavy
  test-extra-backend-llama-cpp wrapper appends the same caps so it
  exercises the moved specs when the backend actually changes.

Makefile:

- Deleted test-models/testmodel.ggml (the wget chain), test-llama-gguf,
  test-tts, test-stablediffusion, test-realtime-models. test target
  drops --label-filter, HUGGINGFACE_GRPC, TRANSFORMER_BACKEND, TEST_DIR,
  FIXTURES, CONFIG_FILE, MODELS_PATH, BACKENDS_PATH; depends on
  build-mock-backend. test-stores keeps a focused entry point and depends
  on backends/local-store. clean-tests also clears the mock-backend
  binary.

Net per typical Go-side PR: ~25min (6 backend builds + tests + AIO) +
~8min e2e drops to ~5min mock-backend test + ~8min e2e + ~5-10min
llama-cpp-smoke (image pulled). Docs and backend-only PRs skip the
always-on workflows entirely.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Edit] [Write] [Bash]
2026-04-27 23:09:20 +00:00
Ettore Di Giacinto
3948b580d2 fix(distributed): worker stopBackend/isRunning resolve bare modelID to replica keys
PR #9583 changed the supervisor's process map key from `modelID` to
`modelID#replicaIndex`, but the NATS lifecycle handlers kept passing
the bare modelID:

* `backend.stop` (subscribeLifecycleEvents): `s.stopBackend(req.Backend)`
  → `s.processes["Qwen3.6-..."]` missed (actual key is "...#0") →
  silent no-op. Admin "Unload model" clicks released VRAM via
  model.unload but left the gRPC process alive on its old port.
  Subsequent chats hit installBackend, found the leftover process,
  reused its address — and the UI reported "no models loaded" while
  the model kept responding.

* `backend.delete` (subscribeLifecycleEvents): same map miss in
  `isRunning(req.Backend)` and `s.stopBackend(req.Backend)` — admin
  "Delete backend" deleted the binary while the process was still
  serving traffic.

Add `resolveProcessKeys(id)`: exact match if `id` is a full processKey
(stopAllBackends iterates the map and passes its own keys);
prefix-match if `id` is bare (NATS handlers); empty if `id` contains
`#` but doesn't match (no spurious fallback when the caller was
explicit). stopBackend and isRunning now call it; stopBackend gets a
new stopBackendExact helper for per-key cleanup.

TDD: regression test fails without the fix (resolveProcessKeys
doesn't exist; map lookup by bare name returns nothing). Tests pass
post-fix.

Reproduced live: registry row count was 0 for the model the user
"Unloaded", chat still served by the leftover worker process.
SmartRouter behavior is correct in itself — it falls through to
scheduleAndLoad when no row exists; the bug was that the leftover
process corrupted the install path.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Bash]
2026-04-27 21:43:15 +00:00
LocalAI [bot]
5efbe8405f feat(swagger): update swagger (#9587)
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-27 23:28:03 +02:00
Ettore Di Giacinto
ea1df8945b fix(distributed): preserve UI-added node labels across worker re-register
The register endpoint called SetNodeLabels(req.Labels) — replace-all
semantics — so every worker re-register wiped every label not in the
worker's body. The bug existed since labels were introduced in
PR #9186 (Mar 31), but only triggered for workers that supplied
labels via --node-labels.

PR #9583 (the multi-replica refactor) added an auto-mirrored
`node.replica-slots` label to every worker's registration body, which
made `len(req.Labels) > 0` always true — turning a latent edge-case
bug into a universal one. Operators reported "labels assigned to
node do not persist": labels survived until the next worker restart,
then disappeared.

Fix: iterate req.Labels and call SetNodeLabel (upsert) for each
instead of SetNodeLabels (delete-then-recreate). Worker-managed
labels still refresh on re-register; UI-added labels survive.

Trade-off: an operator who removes a label from --node-labels won't
have it auto-removed from the DB on next register — they can clean it
via the UI. Acceptable, since the alternative (current behavior)
silently destroys operator state.

Regression test added first (TDD): RegisterNodeEndpoint registers a
node, the test simulates a UI add via SetNodeLabel, then re-registers
with a different worker label set; assertion that the UI-added label
survives. Test fails against the broken code, passes against the fix.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Bash]
2026-04-27 21:24:50 +00:00
Ettore Di Giacinto
3280b9a287 fix(distributed): per-replica backend logs (store aggregation + UI)
The multi-replica refactor (PR #9583) changed the worker's process key
from `modelID` to `modelID#replicaIndex`, but the BackendLogStore kept
the bare-modelID lookup. Result: every distributed deployment lost
backend logs in the Nodes UI — single-replica too, since even the
default capacity of 1 produces a `#0` suffix.

Two changes wired together:

* pkg/model: BackendLogStore.GetLines/Subscribe now treat a modelID
  without `#` as a model prefix and merge across all `modelID#N` replica
  buffers (timestamp-sorted for GetLines; fan-in for Subscribe). Calls
  with a full `modelID#N` key resolve exactly. ListModels strips
  replica suffixes and deduplicates so the listing surfaces one entry
  per loaded model.

* react-ui: per-replica log streams as the default. Loaded Models
  table disambiguates each row with a `rep N` pill (only when the node
  hosts >1 replica of a model). Each row's "View logs" link routes to
  the per-replica process key so operators see only that replica's
  output. The logs page renders the replica context as a chip in the
  title and surfaces a segmented control — `Replica 0 / 1 / … / All
  merged` — when the model has multiple replicas; the merged segment
  uses the bare-modelID URL (delegating to the store's prefix
  aggregation) for the side-by-side comparison case. Single-replica
  deployments see no extra UI.

Tests added first (TDD): the regression set in
backend_log_store_test.go reproduces the bug at the exact failure
point — GetLines/ListModels/Subscribe assertions all fail against the
broken code, all pass against the fix. TestSubscribe_PerReplicaFilter
pins the exact-key path so a future change can't silently break it.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Skill:critique] [Skill:audit] [Skill:polish] [Skill:distill]
2026-04-27 20:55:24 +00:00
Ettore Di Giacinto
375bf1929d fix(ui): hide meta-dev backends in System → Backends Development toggle
The Manage view's flagsFor() short-circuited on b.IsMeta and returned
dev=false for every meta backend, so meta-dev entries
(e.g. llama-cpp-development, whisper-development, insightface-development)
leaked through the Development toggle in distributed mode and stayed
visible whether the toggle was on or off. The count chip even
under-reported because those rows were excluded from it.

Drop the IsMeta short-circuit and trust gallery enrichment for both
flags. Production metas (llama-cpp) are tagged isAlias=false /
isDevelopment=false in the gallery so they still pass both toggles;
meta-dev entries carry isDevelopment=true and now correctly hide
alongside concrete dev variants.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-27 20:38:20 +00:00
Ettore Di Giacinto
9a7f5e68bd ci(darwin): add native caches to backend_build_darwin
macOS runners can't use the registry-backed BuildKit cache (no Docker
daemon), so every darwin matrix run was paying full cost for brew
installs, Go module downloads, llama.cpp recompiles and Python wheel
resolution.

Wires actions/cache@v4 into the reusable workflow for four caches:

- Go modules + build cache (setup-go cache: true), shared across matrix
- Homebrew downloads + selected /opt/homebrew/Cellar entries, with
  HOMEBREW_NO_AUTO_UPDATE so restored Cellar paths stay stable
- ccache for the llama-cpp CMake variants, keyed on the pinned
  LLAMA_VERSION; CMAKE_*_COMPILER_LAUNCHER is exported via GITHUB_ENV
  so backend/cpp/llama-cpp/Makefile picks it up without script changes
- Python uv + pip wheel cache, keyed by backend + ISO week — same
  one-cold-rebuild-per-week cadence as the Linux DEPS_REFRESH

Read/write semantics match the existing BuildKit policy: every run
restores, only master/tag pushes save, so PRs can't pollute master's
warm cache.

Documents the new caches and the macOS-specific constraints in
.agents/ci-caching.md.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
2026-04-27 20:17:36 +00:00
Ettore Di Giacinto
6b63b47f61 feat(distributed): support multiple replicas of one model on the same node (#9583)
* feat(distributed): support multiple replicas of one model on the same node

The distributed scheduler implicitly assumed `(node_id, model_name)` was
unique, but the schema didn't enforce it and the worker keyed all gRPC
processes by model name alone. With `MinReplicas=2` against a single
worker, the reconciler "scaled up" every 30s but the registry never
advanced past 1 row — the worker re-loaded the model in-place every tick
until VRAM fragmented and the gRPC process died.

This change introduces multi-replica-per-node as a first-class concept,
with capacity-aware scheduling, a circuit breaker, and VRAM
soft-reservation. Operators can declare per-node capacity via the worker
flag `--max-replicas-per-model` (mirrored as auto-label
`node.replica-slots=N`) or override per-node from the UI.

* Schema: BackendNode gains MaxReplicasPerModel (default 1) and
  ReservedVRAM. NodeModel gains ReplicaIndex (composite with node_id +
  model_name). ModelSchedulingConfig gains UnsatisfiableUntil/Ticks for
  the reconciler circuit breaker.

* Registry: replica_index threaded through SetNodeModel, RemoveNodeModel,
  IncrementInFlight, DecrementInFlight, TouchNodeModel, GetNodeModel,
  SetNodeModelLoadInfo and the InFlightTrackingClient. New helpers:
  CountReplicasOnNode, NextFreeReplicaIndex (with ErrNoFreeSlot),
  RemoveAllNodeModelReplicas, FindNodesWithFreeSlot,
  ClusterCapacityForModel, ReserveVRAM/ReleaseVRAM (atomic UPDATE with
  ErrInsufficientVRAM), and the unsatisfiable-flag CRUD.

* Worker: processKey now `<modelID>#<replicaIndex>` so concurrent loads
  of the same model land on distinct ports. Adds CLI flag
  --max-replicas-per-model (env LOCALAI_MAX_REPLICAS_PER_MODEL, default 1)
  and emits the auto-label.

* Router: scheduleNewModel filters candidates by free slot, allocates the
  replica index, and soft-reserves VRAM before installing the backend.
  evictLRUAndFreeNode now deletes the targeted row by ID instead of all
  replicas of the model on the node — fixes a latent bug where evicting
  one replica orphaned its siblings.

* Reconciler: caps scale-up at ClusterCapacityForModel so a misconfig
  (MinReplicas > capacity) doesn't loop forever. After 3 consecutive
  ticks of capacity==0 it sets UnsatisfiableUntil for a 5m cooldown and
  emits a warning. ClearAllUnsatisfiable fires from Register,
  ApproveNode, SetNodeLabel(s), RemoveNodeLabel and
  UpdateMaxReplicasPerModel so a new node joining or label changes wake
  the reconciler immediately. scaleDownIdle removes highest-replica-index
  first to keep slots compact.

* Heartbeat resets reserved_vram to 0 — worker is the source of truth
  for actual free VRAM; the reservation is only for the in-tick race
  window between two scheduling decisions.

* Probe path (reconciler.probeLoadedModels and health.doCheckAll) now
  pass the row's replica_index to RemoveNodeModel so an unreachable
  replica doesn't orphan healthy siblings.

* Admin override: PUT /api/nodes/:id/max-replicas-per-model sets a
  sticky override (preserved across worker re-registration). DELETE
  clears the override so the worker's flag applies again on next
  register. Required because Kong defaults the worker flag to 1, so
  every worker restart would have silently reverted the UI value.

* React UI: always-visible slot badge on the node row (muted at default
  1, accented when >1); inline editor in the expanded drawer with
  pencil-to-edit, Save/Cancel, Esc/Enter, "(override)" indicator when
  the value is admin-set, and a "Reset" button to hand control back to
  the worker. Soft confirm when shrinking the cap below the count of
  loaded replicas. Scheduling rules table gets an "Unsatisfiable until
  HH:MM" status badge surfacing the cooldown.

* node.replica-slots filtered out of the labels strip on the row to
  avoid duplicating the slot badge.

23 new Ginkgo specs (registry, reconciler, inflight, health) cover:
multi-replica row independence, RemoveNodeModel of one replica
preserving siblings, NextFreeReplicaIndex slot allocation including
ErrNoFreeSlot, capacity-gated scale-up with circuit breaker tripping
and recovery on Register, scheduleDownIdle ordering, ClusterCapacity
math, ReserveVRAM admission gating, Heartbeat reset, override survival
across worker re-registration, and ResetMaxReplicasPerModel handing
control back. Plus 8 stdlib tests for the worker processKey / CLI /
auto-label.

Closes the flap reproduced on Qwen3.6-35B against the nvidia-thor
worker (single 128 GiB node, MinReplicas=2): the reconciler now caps
the scale-up at the cluster's actual capacity instead of looping.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Read] [Edit] [Bash] [Skill:critique] [Skill:audit] [Skill:polish] [Skill:golang-testing]

* refactor(react-ui/nodes): tighten capacity editor copy + adopt ActionMenu for row actions

* Capacity editor hint trimmed from operator-doc-style ("Sourced from
  the worker's `--max-replicas-per-model` flag. Changing it here makes it
  a sticky admin override that survives worker restarts." → "Saved
  values stick across worker restarts.") and the override-state copy
  similarly compressed. The full mechanic is no longer needed in the UI
  — the override pill carries the meaning and the docs cover the rest.

* Node row actions migrated from an inline cluster of icon buttons
  (Drain / Resume / Trash) to the kebab ActionMenu used by /manage for
  per-row model actions, so dense Nodes tables stay clean. Approve
  stays as a prominent primary button — it's a stateful admission gate,
  not a routine action, and elevating it matches how /manage surfaces
  install-time decisions outside the menu.

* The expanded drawer's Labels section now filters node.replica-slots
  out of the editable label list. The label is owned by the Capacity
  editor above; surfacing it again as an editable label invited
  confusion (the Capacity save would clobber any direct edit).

Both backend and agent workers benefit — they share the row rendering
path, so the action menu and label filter apply to both.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [chrome-devtools-mcp] [Skill:critique] [Skill:audit] [Skill:polish]

* fix(react-ui/nodes): suppress slot badge on agent workers

Agent workers don't load models, so the per-node replica capacity is
inapplicable to them. Showing "1× slots" on agent rows was a tiny
inconsistency from the unified rendering path — gate the badge on
node_type !== 'agent' so it only appears on backend workers.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [chrome-devtools-mcp]

* refactor(react-ui/nodes): distill expanded drawer + restyle scheduling form

The expanded node drawer used to stack five panels — slot badge,
filled capacity box, Loaded Models h4+empty-state, Installed Backends
h4+empty-state, Labels h4+chips+form — making routine inspections feel
like a control panel. The scheduling rule form wrapped its mode toggle
as two 50%-width filled buttons that competed visually with the actual
primary action.

* Drawer: collapse three rarely-touched config zones (Capacity,
  Backends, Labels) into one `<details>` "Manage" disclosure (closed by
  default) with small uppercase eyebrow labels for each zone instead of
  parallel h4 sub-headings. Loaded Models stays as the at-a-glance
  headline with a single-line empty hint instead of a boxed empty state.
  CapacityEditor renders flat (no filled background) — the Manage
  disclosure provides framing.

* Scheduling form: replace the chunky 50%-width button-tabs with the
  project's existing `.segmented` control (icon + label, sized to
  content). Mode hint becomes a single tied line below. Fields stack
  vertically with helper text under inputs and a hairline divider above
  the right-aligned Save / Cancel.

The empty drawer collapses from ~5 stacked sections (~280px tall) to
two lines (~80px). The scheduling form now reads as a designed dialog
instead of raw building blocks. Both surfaces now match the typographic
density and weight of the rest of the admin pages.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [chrome-devtools-mcp] [Skill:distill] [Skill:audit] [Skill:polish]

* feat(react-ui/nodes): replace scheduling form's model picker with searchable combobox

The native <select> made operators scroll through every gallery entry to
find a model name. The project already has SearchableModelSelect (used
in Studio/Talk/etc.) which combines free-text search with the gallery
list and accepts typed model names that aren't installed yet — useful
for pre-staging a scheduling rule before the node it'll run on has
finished bootstrapping.

Also drops the now-unused useModels import (the combobox manages the
gallery hook internally).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit]

* refactor(react-ui/nodes): consolidate key/value chip editor + add replica preset chips

The Nodes page was rendering the same key=value chip pattern in two
places with subtly different markup: the Labels editor in the expanded
drawer and (post-distill) the Node Selector input in the scheduling
form. The form's input was also a comma-separated string that operators
were getting wrong.

* Extract <KeyValueChips> as a fully controlled chip-builder. Parent
  owns the map and decides what onAdd/onRemove does — form state for the
  scheduling form, API calls for the live drawer Labels editor. Same
  visuals everywhere; one component to change when polish needs apply.

* Replace the comma-separated Node Selector text input with KeyValueChips.
  Operators were copying syntax from docs and missing commas; the chip
  vocabulary makes the key=value structure self-documenting.

* Add <ReplicaInput>: numeric input + quick-pick preset chips for Min/Max
  replicas. Picked over a slider because replica counts are exact specs
  derived from VRAM math (operator decision, not a fuzzy estimate). The
  chips give one-click access to common values (1/2/3/4 for Min,
  0=no-limit/2/4/8 for Max) without the slider's special-value problem
  (MaxReplicas=0 is categorical, not a position on a continuum).

* Drop the now-unused labelInputs state in the Nodes page (the inline
  label editor's per-node draft state lived there and is now owned by
  KeyValueChips).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Skill:distill]

* test: fix CI fallout from multi-replica refactor (e2e/distributed + playwright)

Two breakages caught by CI that didn't surface in the local run:

* tests/e2e/distributed/*.go — multiple files used the pre-PR2 registry
  signatures for SetNodeModel / IncrementInFlight / DecrementInFlight /
  RemoveNodeModel / TouchNodeModel / GetNodeModel / SetNodeModelLoadInfo
  and one stale adapter.InstallBackend call in node_lifecycle_test.go.
  All updated to pass replicaIndex=0 — these tests don't exercise
  multi-replica behavior, they just need to compile against the new
  signatures. The chip-builder tests in core/services/nodes/ already
  cover the multi-replica logic.

* core/http/react-ui/e2e/nodes-per-node-backend-actions.spec.js — the
  drawer's distill refactor moved Backends inside a "Manage" <details>
  disclosure that's collapsed by default. The test helper expanded the
  node row but never opened Manage, so the per-node backend table was
  never in the DOM. Helper now clicks `.node-manage > summary` after
  expanding the row.

All 100 playwright tests pass locally; tests/e2e/distributed compiles
clean.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Bash]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-27 21:20:05 +02:00
Ettore Di Giacinto
f4036fa83f ci(python-backends): add weekly DEPS_REFRESH cache-buster
The shared backend/Dockerfile.python ends in:
    RUN cd /${BACKEND} && PORTABLE_PYTHON=true make
which `pip install`s each backend's requirements*.txt. A scan of all 34
Python backends shows every single one ships at least some unpinned deps
(torch, transformers, vllm, diffusers, ...). With the registry cache now
enabled, that `make` layer's BuildKit hash depends only on Dockerfile
instructions + COPYed source — not on what pip resolves at runtime — so
a warm cache would freeze upstream versions indefinitely.

DEPS_REFRESH is an ARG declared right before that RUN. backend_build.yml
computes `date -u +%Y-W%V` (ISO week, e.g. `2026-W17`) and passes it as
a build-arg, so the install layer invalidates at most once per week and
re-resolves PyPI / nightly indexes. Within a week, builds stay warm.

Only Dockerfile.python is affected: Go (go.sum) and Rust (Cargo.lock)
already lock their deps, and the C++ backends pull gRPC at a pinned tag
and llama.cpp at a pinned commit.

Add .agents/ci-caching.md documenting the cache layout
(quay.io/go-skynet/ci-cache:cache<tag-suffix>), read/write semantics
(master writes, PRs read-only), DEPS_REFRESH semantics, and how to
manually evict tags. Index it from AGENTS.md (CLAUDE.md is a symlink).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7-1m
2026-04-27 14:21:11 +00:00
Ettore Di Giacinto
3810fe1a1e fix(distributed): worker container healthcheck always unhealthy
The Dockerfile's HEALTHCHECK probes http://localhost:8080/readyz, which
is the OpenAI API server port. When the same image runs as a worker, it
listens on the gRPC base port (50051) and an HTTP file transfer server
on port-1 (50050) — nothing on 8080 — so docker always reports the
container as unhealthy.

Add unauthenticated /readyz and /healthz endpoints to the worker's HTTP
file transfer server, and override HEALTHCHECK_ENDPOINT for worker-1 in
the distributed compose file. Disable the healthcheck for agent-worker
since it is NATS-only and exposes no HTTP server.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-27 13:51:57 +00:00
Ettore Di Giacinto
bdfa5e934a ci: switch image/backend build cache to a dedicated registry image
- Switch cache-from/cache-to in backend_build.yml and image_build.yml
  from the unused gha cache to type=registry pointing at
  quay.io/go-skynet/ci-cache:cache<tag-suffix>, mode=max with
  ignore-error=true. Master/tag builds populate their own
  per-matrix-entry cache; PR builds read-only.
- Drop the broken generate_grpc_cache.yaml cron. It targeted a `grpc`
  Dockerfile stage that was removed by b1fc5acd in July 2025, has been
  failing every night since, and never populated the gha cache. The new
  registry-cache scheme is self-warming, so no separate populator is
  needed.
- Remove the dead GRPC_VERSION / GRPC_BASE_IMAGE / GRPC_MAKEFLAGS
  build-args from image_build.yml and the orphan ARG GRPC_BASE_IMAGE in
  the root Dockerfile (the root Dockerfile no longer compiles gRPC; the
  source build now lives in backend/Dockerfile.{llama-cpp,
  ik-llama-cpp, turboquant} only and uses its own ARG defaults).
- Drop the unused grpc-base-image input from image_build.yml plus the
  matrix passthroughs in image.yml / image-pr.yml.
- Drop the unused GRPC_VERSION env in test.yml.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7-1m
2026-04-27 13:13:04 +00:00
Richard Palethorpe
deca6dbdad feat: Log backend exit code (#9581)
Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-04-27 14:19:18 +02:00
Ettore Di Giacinto
60549a8a60 feat(react-ui): page-width archetype system + mobile/tablet nav polish
Replace the universal max-width:1200px cap on .page with a four-tier
archetype system (narrow 760, medium 1080, default 1600, wide unbounded)
selected per page based on what its UX actually wants. Data/table pages
fill ultrawide displays; forms cap at reading width; tabbed feature
surfaces breathe.

Mobile/tablet:
- New 640/1024 breakpoint split. Tablets (640-1023) get a persistent
  52px icon rail; below 640 keeps the slide-off drawer.
- Drawer polish: body-scroll lock, Escape to close, focus moves into
  the drawer on open and back to the hamburger on close, aria-hidden
  + inert on main while open.
- Mobile top bar carries hamburger + theme toggle + account avatar
  (44x44 touch targets) so theme/account aren't trapped in the drawer.
- Page-level reflow on phones: page-header column-stacks, filter chips
  scroll horizontally, tables go edge-to-edge, OperationsBar overflows
  rather than wrapping. Honors prefers-reduced-motion.

Manage > Models: drop the toggle column; Enable/Disable joins the
per-row Actions menu alongside Stop/Pin/Edit/Logs/Delete for
consistency with the other action verbs.

Page-width tokens live in theme.css so future tuning is one line.
Removes 7 inline maxWidth workarounds from page roots.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-7 [Edit] [Bash]
2026-04-27 11:51:29 +00:00
Ettore Di Giacinto
54728e292f feat(react-ui): split Manage backends toggle into Variants and Development
Meta backends are now always shown — they're the entries operators
configure against — and two independent toggles govern the noise around
them. "Variants" hides platform-specific concrete builds that a meta
backend aliases on the host (e.g. llama-cpp-cuda12-12.4). "Development"
hides pre-release `-development` builds. Each toggle shows the count of
items currently hidden in its category. The legacy `bm` URL flag is
honored on read so existing deep-links resolve to the same view they
used to.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-27 08:23:53 +00:00
Tai An
86fd62233f fix(gallery): correct Qwen3.5 typo in qwen3.5-27b-claude-4.6 model override (closes #9362) (#9580)
The overrides.parameters.model field referenced 'Qwen3.-27B-Claude-...' (missing the '5'), so model loads failed because the configured filename did not match the file actually downloaded by the entry's files: list ('Qwen3.5-27B-Claude-...').

Aligns the override filename with the files: entries and with the upstream HF repo (mradermacher/Qwen3.5-27B-...).
2026-04-27 09:24:00 +02:00
Alex Brick
41ed8ced70 [intel GPU support] Use latest oneapi-basekit image for Intel images to support b70 (in more places this time) (#9578)
Update additional intel base images
2026-04-27 09:18:57 +02:00
LocalAI [bot]
05e94bd9e7 chore: ⬆️ Update ggml-org/llama.cpp to f53577432541bb9edc1588c4ef45c66bf07e4468 (#9577)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-27 08:57:24 +02:00
Ettore Di Giacinto
8d124d080f feat(gallery): add whisper-development umbrella stanza
Mirrors the whisper capabilities map with -development variants so
clients can pull the master-tagged whisper.cpp backend via a single
platform-resolved name, matching the existing faster-whisper-development
and whisperx-development entries.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-26 23:04:27 +00:00
Ettore Di Giacinto
2da1a4d230 feat(distributed): per-node backend installation from the gallery
In distributed mode the Backends gallery used to fan every install out to
every worker — fine for auto-resolving (meta) backends like llama-cpp where
each node picks its own variant, but wrong for hardware-specific builds
like cpu-llama-cpp that would silently land on every GPU node.

Adds a node-targeted install path through the existing
POST /api/nodes/:id/backends/install plumbing, with two entry points:

- Backends gallery row gets a split-button in distributed mode. Auto-
  resolving keeps "Install on all nodes" as the primary; chevron menu
  opens the picker. Hardware-specific routes the primary directly to the
  picker — no fan-out path on the row.
- Nodes-page drawer gets a "+ Add backend" button that navigates to
  /app/backends?target=<node-id>; the gallery scopes itself to that node
  (banner, single per-row install button, Reinstall/Remove for already-
  installed). One gallery, two scopes — no second UI to maintain.

The picker (new NodeInstallPicker) shows a 3-state suitability column
(Compatible / Override / Installed), an auto-expanding variant override
disclosure that fires when selected nodes have no working GPU, parallel
per-node installs with inline status and Retry-failed-nodes, and a
mismatch confirm that names the consequence on the button itself.

A 409 fan-out guard on /api/backends/apply protects CLI/Terraform/script
users from the same footgun: hardware-specific installs in distributed
mode now return code "concrete_backend_requires_target" with a human-
readable error and a meta_alternative pointer.

The gallery list payload now surfaces capabilities, metaBackendFor and
per-row nodes (NodeBackendRef) so the picker and the new Nodes column
have everything they need without re-walking the gallery client-side.

GODEBUG=netdns=go is set on the compose services because the cgo DNS
resolver follows the container's nsswitch.conf to host systemd-resolved
(127.0.0.53), unreachable from inside the container; the pure-Go
resolver reads /etc/resolv.conf directly and uses Docker's embedded DNS.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-7[1m] [Edit] [Bash] [Read] [Write]
2026-04-26 22:05:18 +00:00
Ettore Di Giacinto
988430c850 test(react-ui): drive Manage page Backend logs link via the new kebab menu
Manage page row actions moved into ActionMenu in b336d9c6, so the
inline `<a title="Backend logs">` the e2e specs were asserting on no
longer exists. Open the row's kebab and assert against the menuitem.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7
2026-04-26 20:51:01 +00:00
Ettore Di Giacinto
b336d9c626 feat(react-ui): polish Manage page with kebab menus and gallery rows
Bring the System / Manage page up to the visual standard of the Install
gallery so installed models and backends stop reading like a debug dump.

- Unified ResourceRow anatomy (icon, name+description, badges, status,
  expandable detail) shared across both tabs.
- Gallery enrichment cross-references installed names against the gallery
  list endpoints to surface icons, descriptions, license, tags, and links
  with a graceful "no description" fallback for custom imports.
- Header summary with four StatCards (Models / Backends / Running /
  Updates) — clickable to switch tab + pre-set filter.
- Backends meta + development entries hidden by default; "Show meta &
  development" paired toggle in the FilterBar with hidden-count hint.
- Kebab (three-dot) ActionMenu replaces the inline button cluster on
  every row; restrained until hover, keyboard-navigable, danger items
  separated by a divider.
- Backend "Version" cell now falls back to short digest, OCI tag, or
  ocifile basename when no semver is set, instead of showing "—" for
  every OCI install. Detail panel exposes full Source URI + Digest.
- Drop redundant column headers ("Actions", "On") — kebabs and toggles
  carry their own affordance; screen readers still get a label.
- Inline System / User / Meta / Dev badges next to the backend name so
  the dedicated Type column doesn't reserve space for "USER" repeated.
- Tightened the spacing between the System Resources card and the
  StatCards so they no longer crowd the RAM bar.

Extracted StatCard and GalleryLoader from Nodes.jsx and Models.jsx into
shared components so the visual language is one source of truth.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
2026-04-26 20:33:49 +00:00
Ettore Di Giacinto
f384c64a91 fix(model-loader): also skip .ckpt, .zip, and .tag files when scanning models
The local model directory scan treats every non-skipped file as a model
config candidate. Sidecar artifacts that ship alongside checkpoints
(checkpoint blobs, downloaded archives, ggml-style tag files) were
slipping through and showing up as bogus models in the listing. Add
their extensions to the suffix-skip list.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
2026-04-26 19:37:53 +00:00
Ettore Di Giacinto
e9d8e92988 fix(react-ui): don't yank chat scroll to bottom while user is reading
The chat and agent-chat pages auto-scrolled to the bottom on every
streamed token. If the user scrolled up to re-read part of a response,
the next chunk pulled them back down — making long replies unreadable
while streaming.

Track a stickToBottomRef on each scroll event: if the user is within
80px of the bottom we keep auto-scrolling, otherwise we leave them
where they are. On chat switch we snap back to the bottom and re-pin.

Same fix applied to both Chat.jsx and AgentChat.jsx since they share
the same streaming pattern.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
2026-04-26 19:35:39 +00:00
Ettore Di Giacinto
5b0196c7d0 fix(whisper): scrub invalid UTF-8 from segment text before protobuf marshal
whisper.cpp can emit bytes that are not valid UTF-8 — typically a
multibyte codepoint split across token boundaries. protobuf string
fields reject those at marshal time, which would surface as a transcribe
failure. Run strings.ToValidUTF8 on the segment text before it leaves
the cgo boundary so the bad byte gets replaced with U+FFFD.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
2026-04-26 19:35:39 +00:00
Ettore Di Giacinto
c8d63a1003 fix(react-ui): stop Manage page from blanking on auto-refresh; show real model use cases
- useModels.refetch now runs silently — distributed-mode 10s auto-refresh
  no longer flips loading=true and replaces the table with a spinner card.
- Manage Use Cases column derives badges from each model's actual
  capabilities (Chat / Image / TTS / Embeddings / etc.) instead of
  hardcoding a "Chat" link for every row.
- FilterBar right slot is right-aligned via margin-left:auto so the
  Update button lives at the end of the row, not next to the chips.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
2026-04-26 19:35:39 +00:00
LocalAI [bot]
d9cb0d6133 chore: ⬆️ Update ggml-org/llama.cpp to dcad77cc3b0865153f486327064fb0320a57a476 (#9572)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-26 12:38:35 +02:00
LocalAI [bot]
f5c268deac chore: ⬆️ Update TheTom/llama-cpp-turboquant to 11a241d0db78a68e0a5b99fe6f36de6683100f6a (#9571)
⬆️ Update TheTom/llama-cpp-turboquant

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-26 12:38:25 +02:00
Tai An
8931a2ad31 fix(gallery): normalize inconsistent tag casing/plurals across gallery models (#9574)
- embeddings → embedding (6 models): aligns with the WebUI filter button
  defined in core/http/views/models.html ({ term: 'embedding', ... }), so
  models like nomic-embed-text-v1.5 now appear under the Embedding filter
- TTS → tts (5 models), ASR → asr (2 models): lowercase, per existing
  convention used by 161+ models
- CPU/Cpu → cpu (17 models), GPU → gpu (17 models): lowercase, per existing
  convention used by 666+ models
- dedupe duplicate tag entries on 3 models that already had repeated tags
  (gpt-oss-20b had gguf x2; arcee-ai/AFM-4.5B had gpu x2; one Qwen model
  had default x2)

Closes #9247
2026-04-26 08:33:38 +02:00
Ettore Di Giacinto
e16e758dff ci(backends): build cpu-whisperx and cpu-faster-whisper for linux/arm64 (#9573)
Extend the existing CPU build matrix entries to produce a multi-arch
manifest (linux/amd64,linux/arm64) at the same image tags. arm64
Linux hosts without an NVIDIA GPU report the "default" capability,
which already maps to cpu-whisperx / cpu-faster-whisper in
backend/index.yaml -- so the manifest list lets Docker pull the right
variant without any gallery changes.

Both stacks install cleanly under aarch64: torch (2.4.1/2.8.0),
faster-whisper, ctranslate2, whisperx, opencv-python and the
remaining deps all ship manylinux2014_aarch64 wheels, so no source
builds run under QEMU emulation.

Follows the same pattern already used by cpu-llama-cpp-quantization.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-26 08:30:03 +02:00
LocalAI [bot]
1c45227346 chore: ⬆️ Update ikawrakow/ik_llama.cpp to 3a945af45d45936341a45bbf7deda56776a4af26 (#9570)
⬆️ Update ikawrakow/ik_llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-26 08:26:37 +02:00
Ettore Di Giacinto
fbe4f0a99b fix(docs): replace Docsy alert shortcode with Relearn notice
The docs site uses the hugo-theme-relearn theme, which provides
`notice` instead of Docsy's `alert`. The face-recognition,
voice-recognition, and stores feature pages used `{{% alert %}}`,
breaking `hugo build` with "template for shortcode \"alert\" not
found".

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-25 21:04:31 +00:00
Ettore Di Giacinto
d733c9cd13 fix(mlx-vlm): pin upstream to v0.4.4 to unblock CUDA builds (#9568)
Blaizzy/mlx-vlm git HEAD bumped its constraint to mlx>=0.31.2, but
mlx-cuda-12 and mlx-cuda-13 are only published up to 0.31.1 on PyPI.
Since mlx[cudaXX]==0.31.2 forces a sibling wheel that doesn't exist,
pip backtracks through every older mlx[cudaXX], none of which satisfy
mlx>=0.31.2, producing ResolutionImpossible.

Pin all variants to the v0.4.4 tag (mlx>=0.30.0), which resolves
cleanly against mlx[cuda13]==0.31.1. cpu/mps weren't broken yet but
are pinned for consistency.

Assisted-by: Claude:claude-opus-4-7

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-25 22:06:01 +02:00
Ettore Di Giacinto
703b4fcae8 Change cron schedule to run every 12 hours
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2026-04-25 18:38:28 +02:00
Richard Palethorpe
73aacad2f9 fix(vllm): drop flash-attn wheel to avoid torch 2.10 ABI mismatch (#9557)
The pinned flash-attn 2.8.3+cu12torch2.7 wheel breaks at import time
once vllm 0.19.1 upgrades torch to its hard-pinned 2.10.0:

  ImportError: .../flash_attn_2_cuda...so: undefined symbol:
  _ZN3c104cuda29c10_cuda_check_implementationEiPKcS2_ib

That C10 CUDA symbol is libtorch-version-specific. Dao-AILab has not yet
published flash-attn wheels for torch 2.10 -- the latest release (2.8.3)
tops out at torch 2.8 -- so any wheel pinned here is silently ABI-broken
the moment vllm completes its install.

vllm 0.19.1 lists flashinfer-python==0.6.6 as a hard dep, which already
covers the attention path. The only other use of flash-attn in vllm is
the rotary apply_rotary import in
vllm/model_executor/layers/rotary_embedding/common.py, which is guarded
by find_spec("flash_attn") and falls back cleanly when absent.

Also unpin torch in requirements-cublas12.txt: the 2.7.0 pin only
existed to give the flash-attn wheel a matching torch to link against.
With flash-attn gone, vllm's own torch==2.10.0 dep is the binding
constraint regardless of what we put here.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-04-25 15:38:13 +00:00
LocalAI [bot]
806ea24ff4 chore: ⬆️ Update TheTom/llama-cpp-turboquant to 67559e580b10e4e47e9a6fd6218873997976886d (#9497)
⬆️ Update TheTom/llama-cpp-turboquant

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-25 14:03:46 +02:00
LocalAI [bot]
385de3705e chore(model gallery): 🤖 add 1 new models via gallery agent (#9558)
chore(model gallery): 🤖 add new models via gallery agent

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-25 14:03:15 +02:00
Ettore Di Giacinto
21eace40ec feat(llama-cpp): expose split_mode option for multi-GPU placement (#9560)
Adds split_mode (alias sm) to the llama.cpp backend options allowlist,
accepting none|layer|row|tensor. The tensor value targets the experimental
backend-agnostic tensor parallelism from ggml-org/llama.cpp#19378 and
requires a llama.cpp build that includes that PR, FlashAttention enabled,
KV-cache quantization disabled, and a manually set context size.


Assisted-by: Claude:claude-opus-4-7

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-25 14:02:57 +02:00
Ettore Di Giacinto
24505e57f5 feat(backends): add CUDA 13 + L4T arm64 CUDA 13 variants for vllm/vllm-omni/sglang (#9553)
* feat(backends): add CUDA 13 + L4T arm64 CUDA 13 variants for vllm/vllm-omni/sglang

Adds new build profiles mirroring the diffusers/ace-step pattern so vLLM
serving (and SGLang on arm64) can be deployed on CUDA 13 hosts and
JetPack 7 boards:

- vllm: cublas13 (PyPI cu130 channel) + l4t13 (jetson-ai-lab SBSA cu130
  prebuilt vllm + flash-attn).
- vllm-omni: cublas13 + l4t13. Floats vllm version on cu13 since vllm
  0.19+ ships cu130 wheels by default and vllm-omni tracks vllm master;
  cu12 path keeps the 0.14.0 pin to avoid disturbing existing images.
- sglang: l4t13 arm64 only — uses the prebuilt sglang wheel from the
  jetson-ai-lab SBSA cu130 index, so no source build is needed.
  Cublas13 sglang on x86_64 is intentionally deferred.

CI matrix gains five new images (-gpu-nvidia-cuda-13-vllm{,-omni},
-nvidia-l4t-cuda-13-arm64-{vllm,vllm-omni,sglang}); backend/index.yaml
gains the matching capability keys (nvidia-cuda-13, nvidia-l4t-cuda-13)
and latest/development merge entries.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]

* fix(backends): use unsafe-best-match index strategy on l4t13 builds

The jetson-ai-lab SBSA cu130 index lists transitive deps (decord, etc.)
at limited versions / older Python ABIs. uv defaults to the first index
that contains a package and refuses to fall through to PyPI, so sglang
l4t13 build fails resolving decord. Mirror the existing cpu sglang
profile by setting --index-strategy=unsafe-best-match on l4t13 across
the three backends, and apply it to the explicit vllm install line in
vllm-omni's install.sh (which doesn't honor EXTRA_PIP_INSTALL_FLAGS).

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]

* fix(sglang): drop [all] extras on l4t13, floor version at 0.5.0

The [all] extra brings in outlines→decord, and decord has no aarch64
cp312 wheel on PyPI nor the jetson-ai-lab index (only legacy cp35-cp37
tags). With unsafe-best-match enabled, uv backtracked through sglang
versions trying to satisfy decord and silently landed on
sglang==0.1.16, an ancient version with an entirely different dep
tree (cloudpickle/outlines 0.0.44, etc.).

Drop [all] so decord is no longer required, and floor sglang at 0.5.0
to prevent any future resolver misfire from degrading the version
again.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-25 12:26:29 +02:00
LocalAI [bot]
d09706dc60 chore(model gallery): 🤖 add 1 new models via gallery agent (#9555)
chore(model gallery): 🤖 add new models via gallery agent

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-25 09:00:37 +02:00
LocalAI [bot]
08e393f7db chore: ⬆️ Update ikawrakow/ik_llama.cpp to cb58a561f0c49f68b6d125cdfda037ed80433821 (#9549)
⬆️ Update ikawrakow/ik_llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-25 08:59:48 +02:00
LocalAI [bot]
47cc3dc8d7 chore: ⬆️ Update ggml-org/llama.cpp to 361fe72acb7b9bd79059cc177cbeda99b35b5db9 (#9548)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-25 08:58:27 +02:00
Ettore Di Giacinto
83b384de97 feat: surface distributed backend management errors (#9552)
* fix(distributed): surface per-node backend op errors to OpStatus

DistributedBackendManager.{Install,Upgrade,Delete}Backend discarded the
per-node BackendOpResult from enqueueAndDrainBackendOp with `_, err :=`.
When workers replied Success=false (e.g. an OCI image with no arm64
variant on a Jetson host), the per-node Error string was recorded in
result.Nodes[].Error but never reached the toplevel return value, so
OpStatus.Error stayed empty and the UI reported the install as
"completed" while the backend was nowhere on the cluster.

Add BackendOpResult.Err() that aggregates per-node Status=="error"
entries into a single error. Queued nodes (waiting for reconciler retry)
are deliberately not treated as failures. Wire the three callers and
DeleteBackendDetailed to call result.Err() so reply.Success=false
finally reaches OpStatus.Error → /api/backends/job/:uid → the UI.

The Delete closures had a related bug: they discarded the reply with
`_` and only checked the NATS round-trip error, so reply.Success=false
was a silent success even with the new aggregation. Check both.

Standalone mode (LocalBackendManager) already surfaces gallery errors
correctly through the same OpStatus.Error path; no change needed there.

Tests: 9 new Ginkgo specs covering all-success / all-fail with distinct
errors / mixed / all-queued / no-nodes for Install, Upgrade, Delete.

Assisted-by: Claude:claude-opus-4-7 [Bash] [Edit] [Read] [Write]

* feat(react-ui): per-node backend delete + clearer upgrade affordance

The Nodes page exposed a per-node "reinstall" button (fa-sync-alt,
tooltip "Reinstall backend") but no per-node delete, even though the
Go side has had POST /api/nodes/:id/backends/delete →
RemoteUnloaderAdapter.DeleteBackend → NATS-to-specific-node wired up
for a while. Sync icons read as "refresh data" — the action is
functionally an upgrade (re-pulls the gallery image), so the affordance
was misleading.

Per-node backend row now renders two icon buttons:

- Upgrade: btn-secondary btn-sm + fa-arrow-up, tooltip "Upgrade backend
  on this node". Names both action and scope to differentiate from the
  cluster-wide upgrade on the Backends page.
- Delete: btn-danger-ghost btn-sm + fa-trash, tooltip "Delete backend
  from this node". Matches the node-level destructive style at the row
  action column rather than the solid btn-danger of primary destructive
  pages, since this is a secondary action inside a busy row.

Delete goes through the existing ConfirmDialog (danger=true) with copy
that names the backend and the node explicitly — it's a non-recoverable
op on a specific scope. Reuses nodesApi.deleteBackend(id, backend) which
already existed in the API client.

Tests: 4 new Playwright specs covering upgrade clarity (icon + tooltip),
delete button presence, confirm dialog flow with POST body assertion,
and cancel-doesn't-POST.

Assisted-by: Claude:claude-opus-4-7 [Bash] [Edit] [Read] [Write]
2026-04-25 08:57:59 +02:00
Ettore Di Giacinto
487e3fd2a4 feat(react-ui): editorial refresh with Nord palette and polished primitives (#9550)
* feat(react-ui): editorial refresh with Nord palette and polished primitives

Replaces the cool gray-blue theme with a deep Nord-inspired palette:
frost-cyan accent (#88c0d0) on deep blue-black surfaces (#13171f /
#1a1f2a / #242a36), snow-storm text scale, aurora status colours.

- Typography: Geist Variable + Geist Mono Variable (Google Fonts) with
  ss01/ss03/cv11 stylistic alternates; strengthened h1-h6 hierarchy;
  editorial negative tracking.
- Primitives: buttons gain depth (inset highlight + hover lift +
  brightness filter); inputs become sunken wells with sage-swap-to-frost
  focus rings; cards hover-lift and gain an .card--accent left-rail
  variant; badges become mono caps rectangles with tabular-nums.
- Chrome: sidebar active state is now an inset left rail + tint
  (no border-left); modals get popIn animation and proper shadow lift;
  toasts carry an inset accent bar + slide-in instead of tinted fills;
  operations bar breathes on active installs.
- Empty states: editorial pattern (eyebrow rule, large mono title,
  52ch lede) that inherits gracefully even without page JSX edits.
- Chat: assistant bubbles drop the gray-nested-in-gray card for a
  transparent pull-quote with a left border; user bubbles soften from
  loud accent fill to a subtle frost tint.
- Motion: custom spring easing cubic-bezier(0.22,1,0.36,1), 180ms
  standard; breathing/pulse/popIn keyframes; global prefers-reduced-
  motion honoring.
- Radii tightened to 3/5/8/10px; warm-shadow tokens redone for cool
  depth; ::selection, :focus-visible, kbd globals added.
- Migrated hardcoded 'JetBrains Mono' CSS literals to var(--font-mono)
  so the Geist Mono swap lands everywhere.

Scope is intentionally tokens + primitives only. Page JSX and the
~1,800 inline style={{…}} instances are untouched and flagged as
follow-ups.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write]

* feat(react-ui): complete-coverage pass — migrate inline styles to tokens

Follows up the editorial/Nord token refresh with a mechanical sweep of
page JSX and shared components so nothing bypasses the design system.

- Font family: replaced 80+ 'JetBrains Mono' / 'Space Grotesk' inline
  literals (and the string-CSS variants in CollectionDetails and
  AgentStatus) with var(--font-mono) / var(--font-sans). SVG <text>
  nodes that used the attribute form were switched to style={{ }} so
  the CSS variable resolves.
- Radii: every unquoted numeric borderRadius (2/3/4/10) is now a
  var(--radius-*) token; 50% and 999px kept as computed shapes.
- Spacing: clean-token gaps and margins (4/8/16px) moved to
  var(--spacing-xs/sm/md); padding: '4px 8px' and '8px 16px' lifted
  into token pairs. Micro-values (2/6/10/12px) left inline where no
  token maps cleanly.
- Colors: Talk.jsx button/canvas-surface hardcodes moved to
  var(--color-*); FineTune.jsx chart series colours now use the
  --color-data-* Nord palette (cyan/red/purple/orange instead of
  tailwind hex); AgentStatus tool-call icon and error tag hex swapped
  for var(--color-warning) / var(--color-text-inverse).
- CodeMirror editor (utils/cmTheme.js): both themes rebased on Nord —
  polar-night surfaces and aurora syntax highlighting (dark), snow-
  storm surfaces with darkened aurora (light). Caret/selection/active
  line/search now frost-cyan tinted instead of legacy indigo/purple.

Legitimately dynamic styles (computed widths, per-row colours, canvas
2D context fill/stroke for waveform and spectrogram drawing) remain
inline — they can't be expressed as CSS tokens.

29 files, +237/-237 — identity preserved, semantics re-anchored to
the token system.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write]
2026-04-24 23:35:59 +02:00
dependabot[bot]
9ab3496de2 chore(deps): bump rustls-webpki from 0.103.10 to 0.103.13 in /backend/rust/kokoros in the cargo group across 1 directory (#9546)
chore(deps): bump rustls-webpki

Bumps the cargo group with 1 update in the /backend/rust/kokoros directory: [rustls-webpki](https://github.com/rustls/webpki).


Updates `rustls-webpki` from 0.103.10 to 0.103.13
- [Release notes](https://github.com/rustls/webpki/releases)
- [Commits](https://github.com/rustls/webpki/compare/v/0.103.10...v/0.103.13)

---
updated-dependencies:
- dependency-name: rustls-webpki
  dependency-version: 0.103.13
  dependency-type: indirect
  dependency-group: cargo
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-04-24 22:02:58 +02:00
dependabot[bot]
c4511be33a chore(deps): bump postcss from 8.5.8 to 8.5.10 in /core/http/react-ui in the npm_and_yarn group across 1 directory (#9544)
chore(deps): bump postcss

Bumps the npm_and_yarn group with 1 update in the /core/http/react-ui directory: [postcss](https://github.com/postcss/postcss).


Updates `postcss` from 8.5.8 to 8.5.10
- [Release notes](https://github.com/postcss/postcss/releases)
- [Changelog](https://github.com/postcss/postcss/blob/main/CHANGELOG.md)
- [Commits](https://github.com/postcss/postcss/compare/8.5.8...8.5.10)

---
updated-dependencies:
- dependency-name: postcss
  dependency-version: 8.5.10
  dependency-type: indirect
  dependency-group: npm_and_yarn
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-04-24 22:02:41 +02:00
Ettore Di Giacinto
551ebdb57a fix(distributed): correct VRAM/RAM reporting on NVIDIA unified-memory hosts (#9545)
Workers on NVIDIA unified-memory hardware (DGX Spark / GB10, Jetson AGX Thor,
Jetson Orin/Xavier/Nano) were reporting `available_vram=0` back to the frontend,
so the Nodes UI showed the node as fully used even when most of the unified
memory was actually free.

Three causes addressed:

* `isTegraDevice` only matched `/sys/devices/soc0/family == "Tegra"`. DGX Spark
  (SBSA) reports JEDEC codes there instead — `jep106:0426` for the NVIDIA
  manufacturer — so the Tegra/unified-memory fallback never ran. Renamed to
  `isNVIDIAIntegratedGPU` and extended to also match `jep106:0426[:*]` via
  `/sys/devices/soc0/soc_id`.

* The unified-iGPU code defaulted the device name to `"NVIDIA Jetson"` when
  `/proc/device-tree/model` was missing. That's what happens for Thor inside a
  docker container, and always on DGX Spark. New `nvidiaIntegratedGPUName`
  resolves via dt-model → `/sys/devices/soc0/machine` → `soc_id` lookup
  (`jep106:0426:8901` → `"NVIDIA GB10"`) so the Nodes UI labels the box
  correctly.

* Worker heartbeat sent `available_vram=0` (or total-as-available) when VRAM
  usage was momentarily unknown — e.g. when `nvidia-smi` intermittently failed
  with `waitid: no child processes` under containers without `--init`. Each
  such heartbeat overwrote the DB and made the UI flip to "fully used".
  `heartbeatBody` now omits `available_vram` in that case so the DB keeps its
  last good value.

Also updates the commented GPU blocks in both compose files with
`NVIDIA_DRIVER_CAPABILITIES=compute,utility`, `capabilities: [gpu, utility]`,
and `init: true`, and documents the requirement in the distributed-mode and
nvidia-l4t pages. Without `utility`, NVML/`nvidia-smi` are absent inside the
container, which is what put the DGX Spark worker into the buggy fallback in
the first place.

Detection verified on live hardware (dgx.casa / GB10 and 192.168.68.23 / Thor)
by running a cross-compiled probe of the new helpers on both host and inside
the worker container.

Assisted-by: Claude:opus-4.7 [Claude Code]
2026-04-24 22:02:23 +02:00
Andreas Egli
1d0de757c3 fix: add hipblaslt library (#9541)
Signed-off-by: Andreas Egli <github@kharan.ch>
2026-04-24 18:50:03 +02:00
Alex Brick
e5337039b0 [intel GPU support] Use latest oneapi-basekit image for Intel images to support b70 (#9543)
* Use latest oneapi-basekit image for Intel images

The current `localai/localai:master-gpu-intel` images don't work with the intel arc pro b70. Updating the base_image to 2025.3.2 fixes it.

Signed-off-by: Alex Brick <3220905+arbrick@users.noreply.github.com>

* Update github workflow base image

---------

Signed-off-by: Alex Brick <3220905+arbrick@users.noreply.github.com>
2026-04-24 18:29:10 +02:00
LocalAI [bot]
1c9592c77f chore: ⬆️ Update leejet/stable-diffusion.cpp to b8bdffc19962be7e5a84bfefeb2e31bd885b571a (#9521)
⬆️ Update leejet/stable-diffusion.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-24 15:15:15 +02:00
Richard Palethorpe
3db60b57e6 fix(realtime): consume ChatDeltas when C++ autoparser clears Response (#9538)
The llama.cpp C++-side chat autoparser clears Reply.Message and delivers
parsed content/reasoning/tool-calls via Reply.chat_deltas. chat.go handles
this (non-SSE path uses ToolCallsFromChatDeltas/ContentFromChatDeltas/
ReasoningFromChatDeltas), but realtime.go only read pred.Response, so any
model routed through the autoparser (Qwen2.5/3 and friends) produced a
silent reply: backend emitted N tokens, the session surface saw zero.

Mirror the non-SSE chat path in realtime's triggerResponse: when deltas
carry tool calls or content, use them directly; otherwise fall back to
the existing raw-text parsing.

Assisted-by: claude-opus-4-7-1M [Claude Code]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-04-24 14:41:38 +02:00
Richard Palethorpe
13734ae9fa feat: Add Sherpa ONNX backend for ASR and TTS (#8523)
feat(backend): Add Sherpa ONNX backend and Omnilingual ASR

Adds a new Go backend wrapping sherpa-onnx via purego (no cgo). Same
approach as opus/stablediffusion-ggml/whisper — a thin C shim
(csrc/shim.c + shim.h → libsherpa-shim.so) wraps the bits purego
can't reach directly: nested struct config writes, result-struct field
reads, and the streaming TTS callback trampoline. The Go side uses
opaque uintptr handles and purego.NewCallback for the TTS callback.

Supports:
- VAD via sherpa-onnx's Silero VAD
- Offline ASR: Whisper, Paraformer, SenseVoice, Omnilingual CTC
- Online/streaming ASR: zipformer transducer with endpoint detection
  (AudioTranscriptionStream emits delta events during decode)
- Offline TTS: VITS (LJS, etc.)
- Streaming TTS: sherpa-onnx's callback API → PCM chunks on a channel,
  prefixed by a streaming WAV header

Gallery entries: omnilingual-0.3b-ctc-q8-sherpa (1600-language offline
ASR), streaming-zipformer-en-sherpa (low-latency streaming ASR),
silero-vad-sherpa, vits-ljs-sherpa.

E2E coverage: tests/e2e-backends for offline + streaming ASR,
tests/e2e for the full realtime pipeline (VAD + STT + TTS).

Assisted-by: claude-opus-4-7-1M [Claude Code]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-04-24 14:40:06 +02:00
Ettore Di Giacinto
c0920f3273 fix(ik-llama-cpp): patch clip.cpp for new ggml_quantize_chunk signature (#9531)
Bumps ik_llama.cpp pin to 16996aeab7. Upstream 286ce32...16996ae adds a
trailing `const struct quantize_user_data *` parameter to
`ggml_quantize_chunk` (PR ikawrakow/ik_llama.cpp#1677) but leaves
`examples/llava/clip.cpp` unchanged because their build has moved to
`examples/mtmd/`. LocalAI's prepare.sh still copies from
`examples/llava/`, so the dead 7-arg call reaches the grpc-server
compile and fails. Patch the call site to pass `nullptr` for the new
param.

Assisted-by: Claude:Opus-4.7 [Read] [Edit] [Bash]
2026-04-24 13:07:26 +02:00
LocalAI [bot]
7c1934b183 chore: ⬆️ Update ggml-org/llama.cpp to 187a45637054881ecacf17f8e2f6f8f2ba7df1c7 (#9520)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-24 09:17:06 +02:00
Tai An
5e062b4d1f fix: use SetFunctionCallNameString when forcing a specific tool (3 sites) (#9526)
* fix(anthropic): use SetFunctionCallNameString for specific tool forcing

* fix(openai/realtime): use SetFunctionCallNameString for specific tool forcing

* fix(openresponses): use SetFunctionCallNameString for specific tool forcing
2026-04-24 09:06:42 +02:00
Ettore Di Giacinto
4906cbad04 feat: add biometrics UI (#9524)
* feat(react-ui): add Face & Voice Recognition pages

Expose the face and voice biometrics endpoints
(/v1/face/*, /v1/voice/*) through the React UI. Each page has four
tabs driving the six endpoints per modality: Analyze (demographics
with bounding boxes / waveform segments), Compare (verify with a
match gauge and live threshold slider), Enrollment (register /
identify / forget with a top-K matches view), Embedding (raw
vector inspector with sparkline + copy).

MediaInput supports file upload plus live capture: webcam
snap-to-canvas for face, MediaRecorder -> AudioContext ->
16-bit PCM mono WAV transcode for voice (libsndfile on the
backend only handles WAV/FLAC/OGG natively).

Sidebar gets a new Biometrics section feature-gated on
face_recognition / voice_recognition; routes are wrapped in
<RequireFeature>. No new dependencies -- Font Awesome icons
picked from the Free set.

Assisted-by: Claude:Opus 4.7

* fix(localai): accept data URI prefixes with codec/charset params

Browser MediaRecorder produces data URIs like
  data:audio/webm;codecs=opus;base64,...
so the pre-';base64,' section can carry multiple parameter
segments. The `^data:([^;]+);base64,` regex in pkg/utils/base64.go
and core/http/endpoints/localai/audio.go only matched exactly one
segment, so recordings straight from the React UI's live-capture
tab failed the strip and then tripped the base64 decoder on the
leading 'data:' literal, surfacing as
  "invalid audio base64: illegal base64 data at input byte 4"

Widened both regexes to `^data:[^,]+?;base64,` so any number of
';param=value' segments between the mime type and ';base64,' are
tolerated. Added a regression test covering the MediaRecorder
shape.

Assisted-by: Claude:Opus 4.7

* fix(insightface): scope pack ONNX loading to known manifests

LocalAI's gallery extracts buffalo_* zips flat into the models
directory, which inevitably mixes with ONNX files from other
backends (opencv face engine, MiniFASNet antispoof, WeSpeaker
voice embedding) and older buffalo pack installs. Feeding those
foreign files into insightface's model_zoo.get_model() blows up
inside the router -- it assumes a 4-D NCHW input and indexes
`input_shape[2]` on tensors that aren't shaped like a face model,
raising IndexError mid-load and leaving the backend unusable.

The router's dispatch isn't amenable to per-file try/except alone
(first-file-wins picks det_10g.onnx from buffalo_l even when the
user asked for buffalo_sc -- alphabetical order happens to favour
the wrong pack). Instead, ship an explicit manifest of the
upstream v0.7 pack contents and scope the glob to that when the
requested pack is known. The manifest is small and stable; future
packs can be added alongside or fall through to the tolerance
loop, which also swallows any remaining IndexError / ValueError
from foreign files with a clear `[insightface] skipped` stderr
line for diagnostics.

Assisted-by: Claude:Opus 4.7

* fix(speaker-recognition): extract FBank features for rank-3 ONNX encoders

Pre-exported speaker-encoder ONNX graphs come in two shapes:

  rank-2  [batch, samples]           -- some 3D-Speaker exports,
                                        take raw waveform directly.
  rank-3  [batch, frames, n_mels]    -- WeSpeaker and most Kaldi-
                                        lineage encoders, expect
                                        pre-computed Kaldi FBank.

OnnxDirectEngine unconditionally fed `audio.reshape(1, -1)` --
correct for rank-2, IndexError-on-input_shape[3] on rank-3, which
surfaced to the UI as
  "Invalid rank for input: feats Got: 2 Expected: 3"

Detect the input rank at session init and run Kaldi FBank
(80-dim, 25ms/10ms frames, dither=0.0, per-utterance CMN) before
the forward pass when rank>=3. All knobs are configurable via
backend options for encoders that deviate from defaults.

torchaudio.compliance.kaldi is already in the backend's
requirements (SpeechBrain pulls torchaudio in), so no new
dependency.

Assisted-by: Claude:Opus 4.7

* fix(biometrics): isolate face and voice vector stores

Face (ArcFace, 512-D) and voice (ECAPA-TDNN 192-D / WeSpeaker
256-D) biometric embeddings were colliding inside a single
in-memory local-store instance. Enrolling one after the other
failed with
  "Try to add key with length N when existing length is M"
because local-store correctly refuses to mix dimensions in one
keyspace.

The registries were constructed with `storeName=""`, which in
StoreBackend() is just a WithModel() call. But ModelLoader's
cache is keyed on `modelID`, not `model` -- so both registries
collapsed to the same `modelID=""` slot and reused the same
backend process despite looking isolated on paper.

Three complementary fixes:

  1. application.go -- give each registry a distinct default
     namespace ("localai-face-biometrics" /
     "localai-voice-biometrics"). The comment claimed
     isolation, now it's actually enforced.

  2. stores.go -- pass the storeName as both WithModelID and
     WithModel so the ModelLoader cache key separates
     namespaces and the loader spawns distinct processes.

  3. local-store/store.go -- drop the Load() `opts.Model != ""`
     guard. It was there to prevent generic model-loading loops
     from picking up local-store by accident, but that auto-load
     path is being retired; the guard now just blocks legitimate
     namespace isolation. opts.Model is treated as a tag; the
     per-tuple process isolation upstream handles discrimination.

Assisted-by: Claude:Opus 4.7

* fix(gallery): stale-file cleanup and upgrade-tmp directory safety

Two related robustness fixes for backend install/upgrade:

pkg/downloader/uri.go
  OCI downloads passed through
      if filepath.Ext(filePath) != "" ...
          filePath = filepath.Dir(filePath)
  which was intended to redirect file-shaped download targets
  into their parent directory for OCI extraction. The heuristic
  misfires on directory-shaped paths with a dot-suffix --
  gallery.UpgradeBackend uses
      tmpPath = "<backendsPath>/<name>.upgrade-tmp"
  and Go's filepath.Ext treats ".upgrade-tmp" as an extension.
  The rewrite landed the extraction at "<backendsPath>/", which
  then **overwrote the real install** (backends/<name>/) with a
  flat-layout file and left a stray run.sh at the top level. The
  tmp dir itself stayed empty, so the validation step that
  checked "<tmpPath>/run.sh" predictably failed with
      "upgrade validation failed: run.sh not found in new backend"
  Every manual upgrade silently corrupted the backends tree this
  way. Guard the rewrite behind "target isn't already an existing
  directory" -- InstallBackend / UpgradeBackend both pre-create
  the target as a directory, so they get the correct behaviour;
  existing file-path callers with a genuine dot-extension still
  get the parent redirect.

core/gallery/backends.go
  InstallBackend's MkdirAll returned ENOTDIR when something at
  the target path was already a file (legacy dev builds dropped
  golang backend binaries directly at `<backendsPath>/<name>`
  instead of nesting them under their own subdir). That
  permanently blocked reinstall and upgrade for anyone carrying
  that state, since every retry hit the same error. Detect a
  pre-existing non-directory, warn, and remove it before the
  MkdirAll so the fresh install can write the correct nested
  layout with metadata.json + run.sh.

Assisted-by: Claude:Opus 4.7

* fix(galleryop): refresh upgrade cache after backend ops

UpgradeChecker caches the last upgrade-check result and only
refreshes on the 6-hour tick or after an auto-upgrade cycle.
Manual upgrades (POST /api/backends/upgrade/:name) go through
the async galleryop worker, which completes the upgrade
correctly but never tells UpgradeChecker to re-check -- so
/api/backends/upgrades continued to list a just-upgraded backend
as upgradeable, indistinguishable from a failed upgrade, for up
to six hours.

Add an optional `OnBackendOpCompleted func()` hook on
GalleryService that fires after every successful install /
upgrade / delete on the backend channel (async, so a slow
callback doesn't stall the queue). startup.go wires it to
UpgradeChecker.TriggerCheck after both services exist. Result:
the upgrade banner clears within milliseconds of the worker
finishing.

Assisted-by: Claude:Opus 4.7

* build: prepend GOPATH/bin to PATH for protogen-go

install-go-tools runs `go install` for protoc-gen-go and
protoc-gen-go-grpc, which writes them into `go env GOPATH`/bin.
That directory isn't on every dev's PATH, and protoc resolves
its code-gen plugins via PATH, so the immediately-following
protoc invocation fails with
  "protoc-gen-go: program not found"
which in turn blocks `make build` and any
`make backends/%` target that depends on build.

Prepend `go env GOPATH`/bin to PATH for the protoc invocation
so the freshly-installed plugins are found without requiring a
shell-profile change.

Assisted-by: Claude:Opus 4.7

* refactor(ui-api): non-blocking backend upgrade handler with opcache

POST /api/backends/upgrade/:name used to send the ManagementOp
directly onto the unbuffered BackendGalleryChannel, which blocked
the HTTP request whenever the galleryop worker was busy with a
prior operation. The op also didn't show up in /api/operations,
so the Backends UI couldn't reflect upgrade progress on the
affected row.

Register the op in opcache immediately, wrap it in a cancellable
context, store the cancellation function on the GalleryService,
and push onto the channel from a goroutine so the handler
returns right away. Response gains a `jobID` field and a
`message` string so clients have a consistent handle regardless
of whether the op is queued or running.

Pairs with the OnBackendOpCompleted hook added in the galleryop
commit — together the UI sees the upgrade start, watches
progress via /api/operations, and drops the "upgradeable" flag
the moment the worker finishes.

Assisted-by: Claude:Opus 4.7
2026-04-24 08:50:34 +02:00
LocalAI [bot]
c755cd5ab5 feat(swagger): update swagger (#9518)
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-23 23:26:50 +02:00
LocalAI [bot]
0fb04f7ac3 chore(model-gallery): ⬆️ update checksum (#9522)
⬆️ Checksum updates in gallery/index.yaml

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-04-23 23:26:27 +02:00
572 changed files with 66553 additions and 14202 deletions

View File

@@ -43,7 +43,7 @@ If you add a new language bucket, `scripts/changed-backends.js` also needs a bra
**Additional build types you may need:**
- ROCm/HIP: Use `build-type: 'hipblas'` with `base-image: "rocm/dev-ubuntu-24.04:7.2.1"`
- Intel/SYCL: Use `build-type: 'intel'` or `build-type: 'sycl_f16'`/`sycl_f32` with `base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"`
- Intel/SYCL: Use `build-type: 'intel'` or `build-type: 'sycl_f16'`/`sycl_f32` with `base-image: "intel/oneapi-basekit:2025.3.2-0-devel-ubuntu24.04"`
- L4T (ARM): Use `build-type: 'l4t'` with `platforms: 'linux/arm64'` and `runs-on: 'ubuntu-24.04-arm'`
## 3. Add Backend Metadata to `backend/index.yaml`

View File

@@ -330,3 +330,16 @@ When adding a new endpoint:
- [ ] Error responses use `schema.ErrorResponse` format (or `echo.NewHTTPError` with a mapped gRPC status — see the `mapBackendError` helper in `core/http/endpoints/localai/images.go`)
- [ ] Tests cover both authenticated and unauthenticated access
- [ ] Swagger regenerated (`make swagger`) if you changed any `@Router`/`@Tags`/`@Param` annotation
## Companion: MCP admin tool surface
**Required for admin endpoints.** Every new admin endpoint MUST be considered for the MCP admin tool surface — the REST API and the MCP tool catalog can drift silently otherwise, and both the LocalAI Assistant chat modality and the standalone `local-ai mcp-server` rely on `pkg/mcp/localaitools/` to mirror REST.
Two outcomes are acceptable; one is not:
- **Tool added.** The new endpoint is something an admin would manage conversationally (install, list, edit, toggle, upgrade). Follow the full checklist in [.agents/localai-assistant-mcp.md](localai-assistant-mcp.md): add a `LocalAIClient` interface method, implement it in both `inproc` and `httpapi`, register the tool with a `Tool*` constant, update the skill prompts, **and add the route to `toolToHTTPRoute` in `pkg/mcp/localaitools/coverage_test.go`**.
- **Tool deliberately skipped.** The endpoint is internal/diagnostic and adding a chat path would be misleading. Document the decision in the PR description; no code action.
- **Forgot.** This breaks the contract. The `TestToolHTTPRouteMappingComplete` test in `pkg/mcp/localaitools` is a partial guard (it checks every `Tool*` has a route mapping), but it does NOT detect new REST endpoints without a tool — that's still a process check on the PR author.
**Add to the bottom of the checklist below**:
- [ ] If admin: decided whether MCP coverage is needed; if yes, tool registered + map updated; if no, skip-reason in PR description.

280
.agents/ci-caching.md Normal file
View File

@@ -0,0 +1,280 @@
# CI Build Caching
Container builds — both the root LocalAI image (`Dockerfile`) and the per-backend images (`backend/Dockerfile.*`) — share a registry-backed BuildKit cache. This file explains how that cache is laid out, what invalidates it, and how to bypass it.
## Cache layout
- **Cache registry**: `quay.io/go-skynet/ci-cache`
- **Tag prefixes**:
- Backend builds (`backend_build.yml`) buildkit cache: `cache<tag-suffix>`
- e.g. `cache-gpu-nvidia-cuda-12-llama-cpp`, `cache-cpu-vllm`, `cache-nvidia-l4t-cuda-13-arm64-vllm`
- Root image builds (`image_build.yml`) buildkit cache: `cache-localai<tag-suffix>`
- e.g. `cache-localai-gpu-nvidia-cuda-12`, `cache-localai-gpu-vulkan`
- Layered base builds (`base_images.yml`) buildkit cache: `base-<stem>`
- e.g. `base-python-cpu-2404`, `base-cpp-cublas-2404-cuda13.0`
- Layered base **images** (the OCI manifests consumers FROM): `base-image-<stem>[-pr<N>]`
- e.g. `base-image-python-cpu-2404`, `base-image-cpp-cublas-2404-cuda13.0-pr9672`
- The cache tags store multi-arch BuildKit cache manifests (`mode=max`); the `base-image-*` tags store ordinary OCI image manifests.
## Read/write semantics
| Trigger | `cache-from` | `cache-to` |
|---|---|---|
| `push` to `master` / tag | yes | yes (`mode=max,ignore-error=true`) |
| `pull_request` | yes | **no** |
PR builds read master's warm cache but never write — this prevents PRs from polluting the shared cache with their experimental state. After merge, the master build for that matrix entry refreshes the cache.
`ignore-error=true` on the write side means a transient quay push failure does not fail the build; the next master push retries.
## Self-warming, no separate populator
There is no cron job that pre-warms the cache. The production builds *are* the populator. The first master build of a given matrix entry pays the cold cost; subsequent same-entry master builds reuse everything that hasn't changed (apt installs, gRPC compile in `Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}`, Python wheel installs, etc.).
Historically there was a `generate_grpc_cache.yaml` cron that targeted a `grpc` stage in the root Dockerfile. That stage was removed in July 2025 and the cron silently failed every night for 9 months without writing anything. It was deleted along with the registry-cache rollout.
## The `DEPS_REFRESH` cache-buster (Python backends)
Every Python backend goes through the shared `backend/Dockerfile.python`, which ends with:
```dockerfile
ARG DEPS_REFRESH=initial
RUN cd /${BACKEND} && PORTABLE_PYTHON=true make
```
Most Python backends ship `requirements*.txt` files that **do not pin every transitive dep** (`torch`, `transformers`, `vllm`, `diffusers`, etc. are listed without a `==` pin, or with `>=` lower bounds only). With a warm BuildKit cache, the `make` layer hashes only on Dockerfile instructions + COPYed source — not on what `pip install` resolves at runtime. So a warm cache would ship the *first* version of `vllm` ever cached and never pick up upstream releases.
`DEPS_REFRESH` defends against that:
- `backend_build.yml` computes `date -u +%Y-W%V` (ISO week, e.g. `2026-W17`) before each build and passes it as a build-arg.
- The `RUN ... make` layer's BuildKit hash now includes that string, so the layer invalidates **at most once per week**, automatically picking up newer wheels.
- Within a week, builds stay warm.
This applies only to `Dockerfile.python` because:
- Go (`Dockerfile.golang`) pins versions in `go.mod` / `go.sum`.
- Rust (`Dockerfile.rust`) pins via `Cargo.lock`.
- C++ backends (`Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}`) clone gRPC at a pinned tag (`v1.65.0`) and llama.cpp at a pinned commit; their inputs don't drift between rebuilds.
### Adjusting the cadence
If you need a faster refresh (e.g. while debugging an upstream flake), bump the format to daily (`+%Y-%m-%d`) or hourly (`+%Y-%m-%d-%H`). If you need a one-shot rebuild for a specific backend without changing the schedule, append a marker to the tag-suffix in the matrix or temporarily delete that backend's cache tag in quay.
## Manually evicting cache
To force a fully cold build for one backend or the whole image:
```bash
# Delete a single tag (requires quay credentials with admin on the repo)
curl -X DELETE \
-H "Authorization: Bearer ${QUAY_TOKEN}" \
https://quay.io/api/v1/repository/go-skynet/ci-cache/tag/cache-gpu-nvidia-cuda-12-vllm
# List all tags
curl -s -H "Authorization: Bearer ${QUAY_TOKEN}" \
"https://quay.io/api/v1/repository/go-skynet/ci-cache/tag/?limit=100" | jq '.tags[].name'
```
Eviction is rarely needed in normal operation — `DEPS_REFRESH` handles weekly drift, source changes invalidate naturally, and `mode=max` keeps the cache scoped per matrix entry so a stale tag never bleeds into a different build.
## What the cache **does not** cover
- The "Free Disk Space" / "Release space from worker" steps run on every job — these reclaim ~6 GB on `ubuntu-latest` runners. They are runner-state cleanup, not Docker, and BuildKit caches don't apply.
- Intermediate artifacts of `Build and push (PR)` are not pushed anywhere — PRs only build for verification.
- Darwin builds (see below) — macOS runners have no Docker daemon, so the registry-backed BuildKit cache cannot apply.
## Darwin native caches
`backend_build_darwin.yml` runs natively on `macOS-14` GitHub-hosted runners — there is no Docker, no BuildKit, no cross-job registry cache. Instead, the reusable workflow uses `actions/cache@v4` for four native caches that mirror the spirit of the Linux cache (warm by default, weekly refresh for unpinned Python deps, PRs read-only).
| Cache | Path(s) | Key | Scope |
|---|---|---|---|
| Go modules + build | `~/go/pkg/mod`, `~/Library/Caches/go-build` | `go.sum` (managed by `actions/setup-go@v5` `cache: true`) | All darwin jobs |
| Homebrew | `~/Library/Caches/Homebrew/downloads`, selected `/opt/homebrew/Cellar/*` | hash of `backend_build_darwin.yml` | All darwin jobs |
| ccache (llama.cpp CMake) | `~/Library/Caches/ccache` | pinned `LLAMA_VERSION` from `backend/cpp/llama-cpp/Makefile` | `inputs.backend == 'llama-cpp'` only |
| Python wheels (uv + pip) | `~/Library/Caches/pip`, `~/Library/Caches/uv` | `inputs.backend` + ISO week (`+%Y-W%V`) + hash of that backend's `requirements*.txt` | `inputs.lang == 'python'` only |
Read/write semantics match the BuildKit cache: `actions/cache/restore` runs every time, `actions/cache/save` is gated on `github.event_name != 'pull_request'`. PRs read master's warm cache but never write back.
The Python wheel cache uses the same ISO-week cache-buster as the Linux `DEPS_REFRESH` build-arg — same problem (unpinned `torch`/`mlx`/`diffusers`/`transformers` resolve to fresh wheels weekly), same ~one-cold-rebuild-per-week solution.
The brew Cellar cache requires `HOMEBREW_NO_AUTO_UPDATE=1` and `HOMEBREW_NO_INSTALL_CLEANUP=1` (set as job-level env). Without those, `brew install` would mutate the very directories that were just restored, defeating the cache.
For ccache, the workflow exports `CMAKE_ARGS=… -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache` via `$GITHUB_ENV` before running `make build-darwin-go-backend`. The Makefile in `backend/cpp/llama-cpp/` already forwards `CMAKE_ARGS` through to each variant build (`fallback`, `grpc`, `rpc-server`), so no script changes are needed. The three variants share most TUs, so ccache dedupes object files across them.
### Cache budget on Darwin
GitHub Actions caches are limited to 10 GB per repo. Steady-state worst case: ~800 MB Go cache + ~2 GB brew Cellar + up to 2 GB ccache + ~1.5 GB × 5 python backends. If the cap is hit, prefer collapsing the per-backend Python keys into a shared `pyenv-darwin-shared-<week>` key (accepts more cross-backend churn for a smaller footprint) before reducing other caches.
## Layered base images (`ci-cache:base-image-*`)
The registry-backed BuildKit cache deduplicates **within** a matrix entry's
cache tag, but each matrix entry has its own tag — so the same `apt-get`,
GPU SDK install, and language toolchain bootstrap runs into N different
cache tags across the backend matrix. The layered base images factor that
shared work out of the per-backend builds.
They live in the same `quay.io/go-skynet/ci-cache` repo as the buildkit
caches, under a distinct `base-image-` tag prefix so the OCI image
manifests coexist with `base-<stem>` (the cache for building the base),
`cache<tag-suffix>` (per-backend caches), and `cache-localai<tag-suffix>`
(root image caches). Reusing `ci-cache` means no new quay repo or robot
grant is needed — the same credentials that write the cache also write
the image.
### How it fits together
```
.github/backend-matrix.yaml # raw matrix data (linux + darwin)
backend.yml / backend_pr.yml
├── derive-bases / generate-matrix
│ scripts/changed-backends.js
│ reads .github/backend-matrix.yaml
│ (PR mode also reads changed files)
│ emits:
│ - matrix (annotated with base-image-prebuilt)
│ - matrix-darwin
│ - bases-matrix (deduplicated by tag-stem)
├── build-bases (matrix: bases-matrix)
│ uses base_images.yml
│ FROM .docker/bases/Dockerfile.<lang>
│ pushes quay.io/go-skynet/ci-cache:base-image-<stem>[-pr<N>]
└── backend-jobs (matrix: matrix; needs build-bases)
uses backend_build.yml
FROM ${BASE_IMAGE_PREBUILT}
i.e. quay.io/go-skynet/ci-cache:base-image-<stem>[-pr<N>]
only the backend source COPY + `make` remain.
```
The base image is **always** built before backends consume it, in the same
workflow run. There is no cross-workflow dependency, no chicken-and-egg
on first push, and no manual matrix to keep in sync — adding a backend
matrix entry is just an edit to `.github/backend-matrix.yaml`.
### Tag scheme
`<stem>` is computed by `tagStem()` in `scripts/changed-backends.js` from
the (lang, build-type, ubuntu, cuda, base-image) tuple. Arch is
intentionally NOT in the stem — bases are built multi-arch when any
consumer needs multi-arch, and single-arch otherwise (the `platforms`
field on each base entry is the union of its consumers' platforms).
| Build-type | Stem template |
|---|---|
| `''` (CPU) | `<lang>-cpu-<ubuntu>[-<base-image-slug>]` |
| `cublas` / `l4t` | `<lang>-<build-type>-<ubuntu>-cuda<major>.<minor>[-<base-image-slug>]` |
| anything else (vulkan, hipblas, intel, sycl_*) | `<lang>-<build-type>-<ubuntu>[-<base-image-slug>]` |
The base-image slug is empty for the default `ubuntu:24.04` and a short
parseable suffix otherwise (`jetpack-r36.4.0`, `rocm-7.2.1`,
`oneapi-2025.3.2`, etc.).
| Event | Pushed tag (in `quay.io/go-skynet/ci-cache`) |
|---|---|
| `push` (master/tag) | `:base-image-<stem>` |
| `pull_request` | `:base-image-<stem>-pr<PR_NUMBER>` |
The buildkit cache for the base build itself lives at
`quay.io/go-skynet/ci-cache:base-<stem>` (`mode=max,ignore-error=true`),
parallel to the per-matrix-entry caches. The `base-` (cache) and
`base-image-` (image) prefixes never collide.
The script also runs a collision check across consumers of each stem: if
two consumers map to the same stem but disagree on `base-image` or
`skip-drivers` (and skip-drivers is meaningful for that build-type), the
script fails loudly. Resolve by encoding the differing input in
`tagStem()` rather than letting the dedup silently pick a winner.
### PR testability
PRs run the same pipeline as master: derive bases → build bases (tagged
`-pr<N>`) → run filtered backend matrix consuming those `-pr<N>` tags.
End-to-end validation always lives within the PR.
For PRs that only change `.docker/bases/Dockerfile.<lang>` (no backend
source touched), `changed-backends.js` adds one canary backend matrix
entry per (lang × build-type × arch × cuda × ubuntu) tuple to the filtered
matrix so each base flavour gets exercised.
### Existing language tiers
| Tier (lang) | Recipe | Consumer Dockerfile(s) | Distinct stems |
|---|---|---|---|
| `python` | `.docker/bases/Dockerfile.python` | `backend/Dockerfile.python` | 9 |
| `golang` | `.docker/bases/Dockerfile.golang` | `backend/Dockerfile.golang` | 8 |
| `cpp` | `.docker/bases/Dockerfile.cpp` (apt + GPU + protoc + cmake + GRPC) | `backend/Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}` | 8 |
| `rust` | `.docker/bases/Dockerfile.rust` | `backend/Dockerfile.rust` | 1 |
The C++ trio share a single `cpp` base because they only differ in their
per-backend `make` targets. `langOf()` in `scripts/changed-backends.js`
remaps `Dockerfile.{llama-cpp,ik-llama-cpp,turboquant}``cpp` so dedup
works across the trio. If a future C++ consumer needs a *different* base
(e.g. without GRPC, or with a different protoc version), give it its own
`Dockerfile.<newlang>` recipe and remove it from the cpp remap.
### Adding a new (accel × arch × cuda × lang) flavour
Just add the matrix entry to `.github/backend-matrix.yaml` for the new
flavour. The bases matrix and the per-entry `base-image-prebuilt` are
derived automatically by `scripts/changed-backends.js`. Nothing else to
change.
### Adding a new language tier
1. Create `.docker/bases/Dockerfile.<lang>` mirroring an existing tier
(apt + accel install + lang-specific toolchain).
2. Slim `backend/Dockerfile.<lang>` to `FROM ${BASE_IMAGE_PREBUILT}` plus
the per-backend source COPY + build (no inline accel install).
3. Add the new recipe to `baseTriggerFiles` in
`scripts/changed-backends.js` so PRs touching it fan out to canaries.
4. Add `<lang>: (item) => item.dockerfile.endsWith("<lang>")` to
`langTriggerSelector` in the same file.
5. Add a `LOCAL_BASE_<LANG>_TAG`, a `docker-build-<lang>-base` target,
and a clause in `local-base-tag` / `local-base-target` in `Makefile`.
The `langsWithBase` set in `scripts/changed-backends.js` is auto-detected
from the `.docker/bases/` directory at script startup, so step 1 alone is
enough for the script to start emitting bases (and annotating matrix
entries with `base-image-prebuilt`) for that lang. Steps 35 plug it
into the canary fan-out and the local-build path.
### Why not just rely on `mode=max` cache?
`mode=max` deduplicates at the layer level, but each matrix entry has its
own cache tag (`cache<tag-suffix>`). A change that invalidates the GPU SDK
layer in one backend does not invalidate it in any other; each entry pays
the full cost on its next rebuild. The shared base image is built once per
(accel × arch × cuda × lang), then pulled by every backend that consumes
it — that's the actual cross-matrix dedup.
### Local builds
All `backend/Dockerfile.{python,golang,cpp,rust}` consumers require
`BASE_IMAGE_PREBUILT` (no inline fallback). The Makefile wires the right
`docker-build-<lang>-base` as a prerequisite for each backend's
`docker-build-<backend>` target, so:
```bash
# Build any backend; the matching base is built first if needed.
make docker-build-vllm BUILD_TYPE=cublas CUDA_MAJOR_VERSION=12 CUDA_MINOR_VERSION=8
make docker-build-llama-cpp BUILD_TYPE=cublas CUDA_MAJOR_VERSION=13 CUDA_MINOR_VERSION=0
make docker-build-rerankers # golang
make docker-build-kokoros # rust
```
Or build a base directly: `make docker-build-{python,golang,cpp,rust}-base
BUILD_TYPE=...`. Or pull a pre-built one from quay if it exists for your
target tuple.
## Touching the cache pipeline
When changing `image_build.yml`, `backend_build.yml`, or any of the `backend/Dockerfile.*` files:
1. **Don't drop `DEPS_REFRESH=...` from the build-args** without a replacement strategy (lockfiles, pinned requirements). Otherwise master will silently freeze on whichever versions were cached at the time.
2. **Keep `tag-suffix` unique per matrix entry** — it's the cache namespace. Two matrix entries sharing a tag-suffix would clobber each other's cache.
3. **Keep `cache-to` gated on `github.event_name != 'pull_request'`** — PRs must not write.
4. **Keep `ignore-error=true` on `cache-to`** — quay registry hiccups must not fail builds.
5. **`tagStem()` in `scripts/changed-backends.js` is the single source of truth for base image tags.** The matrix entries are annotated with `base-image-prebuilt` in the same script run; backend-jobs reads the value as-is. There's no parallel YAML expression to keep in sync. Adding a new dimension to the stem (e.g. a slug for a new base-image variant) is a script change only.

View File

@@ -48,6 +48,8 @@ All Go tests — including backend tests — must use [Ginkgo](https://onsi.gith
Do not mix styles within a package. If you are extending tests in a package that already uses Ginkgo, keep using Ginkgo. If you find stdlib-style Go tests in the tree, treat them as tech debt to be migrated rather than as a pattern to follow.
This is enforced by `golangci-lint` via the `forbidigo` linter (see `.golangci.yml`); calls like `t.Errorf` / `t.Fatalf` / `t.Run` / `t.Skip` / `t.Logf` are flagged. Run `make lint` locally before submitting; the same check runs in CI (`.github/workflows/lint.yml`).
## Documentation
The project documentation is located in `docs/content`. When adding new features or changing existing functionality, it is crucial to update the documentation to reflect these changes. This helps users understand how to use the new capabilities and ensures the documentation stays relevant.

View File

@@ -0,0 +1,97 @@
# LocalAI Assistant — admin MCP server
This document is the contract for **anyone** (human or AI agent) touching LocalAI's admin REST surface, the in-process MCP server that wraps it, or the embedded skill prompts that teach the assistant how to use it. Read this before adding/removing/renaming admin endpoints, MCP tools, or skill recipes.
## What this feature is
`pkg/mcp/localaitools/` is a public Go package that exposes LocalAI's admin/management surface as an MCP server. It is used in two ways:
1. **In-process**: when an admin opens a chat with `metadata.localai_assistant=true`, the chat handler injects the in-memory MCP server (paired `net.Pipe()` transport, no HTTP loopback) so the LLM can install models, manage backends and edit configs by chatting.
2. **Standalone**: the `local-ai mcp-server --target=…` subcommand serves the same MCP server over stdio, talking HTTP to a remote LocalAI instance.
The two modes share **all** tool definitions and skill prompts. They differ only in their `LocalAIClient` implementation (`inproc/` calls services directly; `httpapi/` calls REST).
## The three things you must keep in sync
When you change LocalAI's admin surface, three layers must stay aligned:
1. **REST endpoint** in `core/http/endpoints/localai/*.go`.
2. **MCP tool registration** in `pkg/mcp/localaitools/tools_*.go`, plus a method on `LocalAIClient` (in `client.go`) and implementations in both `inproc/client.go` **and** `httpapi/client.go`.
3. **Skill prompt** under `pkg/mcp/localaitools/prompts/skills/*.md` — the markdown that teaches the LLM how to use the new tool. If the new tool fits an existing recipe, update that recipe; otherwise add a new file.
If you ship a REST endpoint without (2) and (3), conversational admins won't see the feature.
## Checklist for adding a new admin endpoint
- [ ] REST endpoint exists in `core/http/endpoints/localai/*.go` and is gated by `auth.RequireAdmin()` in `core/http/routes/localai.go`.
- [ ] `LocalAIClient` interface in `pkg/mcp/localaitools/client.go` has a method covering the new operation.
- [ ] DTOs added/updated in `pkg/mcp/localaitools/dto.go` (JSON-tagged; never expose raw service types).
- [ ] `inproc/client.go` implements the new method by calling the service directly (not via HTTP loopback).
- [ ] `httpapi/client.go` implements the new method by calling the REST endpoint.
- [ ] Tool registration added in the appropriate `pkg/mcp/localaitools/tools_*.go`. Mutating tools must reference safety rule 1 in the description.
- [ ] If the tool is mutating, ensure `Options{DisableMutating: true}` skips it (mirror the pattern in `tools_models.go`).
- [ ] Skill prompt added or updated under `pkg/mcp/localaitools/prompts/skills/`. The prompt must instruct the LLM when to call the tool, what to ask the user first, and what to do on error.
- [ ] Tests:
- `pkg/mcp/localaitools/server_test.go` adds the tool name to `expectedFullCatalog` and `expectedReadOnlyCatalog` (if read-only).
- Tool dispatch is added to `TestEachToolDispatchesToClient`.
- `pkg/mcp/localaitools/httpapi/client_test.go` covers the new HTTP path.
## Adding a new skill recipe (no new tool)
Sometimes you want to teach the LLM a new pattern that uses existing tools. Drop a markdown file under `pkg/mcp/localaitools/prompts/skills/<verb>_<noun>.md`. The file is automatically embedded by `//go:embed` and assembled into the system prompt in lexicographic order. No Go changes needed.
Conventions:
- Filename: `<verb>_<noun>.md` (e.g. `install_chat_model.md`, `upgrade_backend.md`).
- First line: `# Skill: <Title Case description>`.
- Number the steps. Reference exact tool names in backticks.
- If the skill mutates state, remind the LLM to confirm with the user.
## Code conventions
These rules guard against the magic-literal drift that surfaced in the first audit. Do not re-introduce bare strings.
- **Tool names** always come from the `Tool*` constants in `pkg/mcp/localaitools/tools.go`. Tool registrations, the test catalog (`server_test.go`'s `expectedFullCatalog` / `expectedReadOnlyCatalog`), and dispatch tables reference the constants. The embedded skill prompts under `prompts/` keep bare strings — that's the one allowed exception, and `TestPromptsContainSafetyAnchors` enforces alignment.
- **Toggle/pin actions** use the `modeladmin.Action` type (`pkg/mcp/localaitools` and `core/services/modeladmin`). Use `ActionEnable`/`ActionDisable`/`ActionPin`/`ActionUnpin`; never bare `"enable"`/`"pin"` strings.
- **Capability tags** for `list_installed_models` use the `localaitools.Capability` type (`capability.go`). The `LocalAIClient.ListInstalledModels` interface takes a typed `Capability`, and the `inproc` switch only accepts canonical values (`"embed"`/`"embedding"` are not aliases — only `CapabilityEmbeddings`).
- **HTTP error checks** in `httpapi.Client` use `errors.Is(err, ErrHTTPNotFound)`, not substring matches on `err.Error()`. The typed `*HTTPError` carries `StatusCode` and `Body`; add new sentinel errors as needed rather than re-introducing string matching.
- **Channel sends** to `GalleryService.ModelGalleryChannel` / `BackendGalleryChannel` from inproc clients MUST select on `ctx.Done()` so a cancelled chat completion releases the goroutine. See `inproc.sendModelOp` / `sendBackendOp`.
- **Disk writes** of model config YAML go through `modeladmin.writeFileAtomic` (temp file + `os.Rename`). `os.WriteFile` truncates on crash and corrupts the model.
- **MCP server lifecycle**: every initialised holder MUST register `Close()` with `signals.RegisterGracefulTerminationHandler`. The standalone `mcp-server` CLI uses `signal.NotifyContext` to honour SIGINT/SIGTERM.
## File map (where to look)
```
pkg/mcp/localaitools/
client.go # LocalAIClient interface + DTO registry
dto.go # JSON-tagged DTOs shared by both client impls
server.go # NewServer(client, opts) — registers tools
tools.go # Tool* name constants (single source of truth)
capability.go # Capability type + constants
tools_models.go # gallery_search, install_model, import_model_uri, ...
tools_backends.go
tools_config.go
tools_system.go
tools_state.go
prompts.go # //go:embed loader + SystemPrompt(opts)
prompts/00_role.md
prompts/10_safety.md # SAFETY RULES — change with care
prompts/20_tools.md # curated tool catalog with one-liners
prompts/skills/*.md
inproc/client.go # in-process LocalAIClient (services-direct)
httpapi/client.go # REST LocalAIClient (for standalone CLI / remote)
core/http/endpoints/mcp/
localai_assistant.go # process-wide holder + LocalToolExecutor
core/cli/mcp_server.go # local-ai mcp-server subcommand
```
## Why two clients
The in-process MCP server runs inside the same LocalAI binary that serves chat. Going over HTTP loopback would (a) require minting a synthetic admin API key for the server to authenticate against itself, (b) double-marshal every tool dispatch, and (c) lose access to in-process channels (e.g. `GalleryService.ModelGalleryChannel` for streaming install progress). So in-process uses `inproc.Client`. The standalone stdio CLI talks to a *remote* LocalAI; HTTP is the only option, so it uses `httpapi.Client`. Both implement the same `LocalAIClient` interface, and the parity test in `pkg/mcp/localaitools/parity_test.go` (when present) keeps their output equivalent.
## Why prompt-enforced confirmation, not code gates
The user chose KISS. Every mutating tool has a safety rule (`prompts/10_safety.md` rule 1) that requires the LLM to summarise the action and wait for explicit user confirmation before calling it. There is no `plan_*`/`apply_*` two-step in code. If you add a mutating tool, do **not** add per-tool confirmation logic in Go — instead, list the new tool name in `prompts/10_safety.md` so the LLM knows it falls under the confirmation rule.
## Distributed mode
The in-memory MCP server runs only on the head node (where the chat handler runs). `inproc.Client` wraps services that are already distributed-aware (`GalleryService` coordinates with workers; `ListNodes` reads the NATS-populated registry). No NATS routing of MCP tools — the admin surface lives on the head, period.

39
.docker/apt-mirror.sh Executable file
View File

@@ -0,0 +1,39 @@
#!/bin/sh
# Reconfigure Ubuntu apt sources to point at an alternate mirror.
#
# Used by Dockerfiles via `RUN --mount=type=bind,source=.docker/apt-mirror.sh,...`
# and by CI workflows on the runner to mitigate outages of the default
# archive.ubuntu.com / security.ubuntu.com / ports.ubuntu.com pool.
#
# Inputs (env):
# APT_MIRROR Replacement for archive.ubuntu.com and security.ubuntu.com
# (e.g. "http://azure.archive.ubuntu.com" or
# "https://mirrors.edge.kernel.org").
# Leave empty to keep upstream. The trailing "/ubuntu/..."
# path is preserved by the rewrite.
# APT_PORTS_MIRROR Replacement for ports.ubuntu.com (arm64/ppc64el/...).
# Leave empty to keep upstream.
#
# Both default to empty, in which case the script is a no-op.
set -e
if [ -z "${APT_MIRROR}" ] && [ -z "${APT_PORTS_MIRROR}" ]; then
exit 0
fi
# Ubuntu 24.04 (noble) ships DEB822 sources at /etc/apt/sources.list.d/ubuntu.sources;
# older releases use /etc/apt/sources.list. We rewrite whichever exists.
for f in /etc/apt/sources.list.d/ubuntu.sources /etc/apt/sources.list; do
[ -f "$f" ] || continue
if [ -n "${APT_MIRROR}" ]; then
# Use a comma delimiter so the alternation pipe in the regex
# is not interpreted as the s/// separator.
sed -i -E "s,https?://(archive\.ubuntu\.com|security\.ubuntu\.com),${APT_MIRROR},g" "$f"
fi
if [ -n "${APT_PORTS_MIRROR}" ]; then
sed -i -E "s,https?://ports\.ubuntu\.com,${APT_PORTS_MIRROR},g" "$f"
fi
done
echo "apt-mirror: rewrote sources (APT_MIRROR='${APT_MIRROR}', APT_PORTS_MIRROR='${APT_PORTS_MIRROR}')"

View File

@@ -0,0 +1,259 @@
# Shared C++ + accelerator base image for the llama-cpp / ik-llama-cpp /
# turboquant trio. They differ only in their Makefile targets at build
# time; the apt + GPU SDK + protoc + cmake + GRPC install is identical.
#
# Built once per (build-type, arch, ubuntu-version, cuda-version) combination
# by .github/workflows/base_images.yml and pushed to
# quay.io/go-skynet/ci-cache:base-image-<tag-stem>[-pr<N>]. Consumed by
# backend/Dockerfile.{llama-cpp,ik-llama-cpp,turboquant} via the
# BASE_IMAGE_PREBUILT build-arg. See .agents/ci-caching.md.
ARG BASE_IMAGE=ubuntu:24.04
ARG APT_MIRROR=""
ARG APT_PORTS_MIRROR=""
FROM ${BASE_IMAGE} AS grpc
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
# CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
ARG CMAKE_VERSION=3.31.10
ARG APT_MIRROR
ARG APT_PORTS_MIRROR
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
build-essential curl libssl-dev \
git wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# Build GRPC into /opt/grpc so we can copy it into the final base without
# pulling in the full source tree. Mirrors the original two-stage layout in
# Dockerfile.llama-cpp; absorbing it here means consumers no longer pay the
# GRPC compile cost.
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
FROM ${BASE_IMAGE}
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.31.10
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG UBUNTU_VERSION=2404
ARG APT_MIRROR
ARG APT_PORTS_MIRROR
LABEL org.opencontainers.image.source="https://github.com/mudler/LocalAI"
LABEL org.opencontainers.image.description="LocalAI C++ (llama-cpp/ik-llama-cpp/turboquant) base image"
LABEL org.localai.base.lang="cpp"
RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache git \
ca-certificates \
make \
pkg-config libcurl4-openssl-dev \
curl unzip \
libssl-dev wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
hipblaslt-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
ldconfig && \
echo "rocBLAS library data architectures:" && \
(ls /opt/rocm*/lib/rocblas/library/Kernels* 2>/dev/null || ls /opt/rocm*/lib64/rocblas/library/Kernels* 2>/dev/null) | grep -oP 'gfx[0-9a-z+-]+' | sort -u || \
echo "WARNING: No rocBLAS kernel data found" \
; fi
# Install protoc (the version in 22.04 is too old, and grpc's bundled protoc
# would pull in a newer absl that breaks stablediffusion).
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
COPY --from=grpc /opt/grpc /usr/local

View File

@@ -0,0 +1,206 @@
# Shared Go + accelerator base image.
#
# Built once per (build-type, arch, ubuntu-version, cuda-version) combination
# by .github/workflows/base_images.yml and pushed to
# quay.io/go-skynet/ci-cache:base-image-<tag-stem>[-pr<N>]. Consumed by
# backend/Dockerfile.golang via the BASE_IMAGE_PREBUILT build-arg.
#
# Mirrors the GPU stack stanzas in Dockerfile.python; the language-specific
# tail at the bottom installs Go + grpc tooling. See .agents/ci-caching.md.
ARG BASE_IMAGE=ubuntu:24.04
ARG APT_MIRROR=""
ARG APT_PORTS_MIRROR=""
FROM ${BASE_IMAGE}
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.25.4
ARG UBUNTU_VERSION=2404
ARG APT_MIRROR
ARG APT_PORTS_MIRROR
LABEL org.opencontainers.image.source="https://github.com/mudler/LocalAI"
LABEL org.opencontainers.image.description="LocalAI Go+accelerator base image"
LABEL org.localai.base.lang="golang"
# gcc-14 is the default on noble (ubuntu:24.04) but absent from jammy
# (the L4T jetpack r36.4.0 base). LocalVQE needs it; the other Go backends
# compile with the default gcc shipped via build-essential. Try gcc-14
# from the configured repos and fall back gracefully when it's missing.
RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
git ccache \
ca-certificates \
make cmake wget libopenblas-dev \
curl unzip \
libssl-dev && \
if apt-cache show gcc-14 >/dev/null 2>&1 && apt-cache show g++-14 >/dev/null 2>&1; then \
apt-get install -y --no-install-recommends gcc-14 g++-14 && \
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100 \
--slave /usr/bin/g++ g++ /usr/bin/g++-14 \
--slave /usr/bin/gcov gcov /usr/bin/gcov-14; \
fi && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
hipblaslt-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
ldconfig \
; fi
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin:/usr/local/bin
# Install grpc compilers
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
# Install protoc (the version in 22.04 is too old, and grpc's bundled protoc
# would pull in a newer absl that breaks stablediffusion).
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT

View File

@@ -0,0 +1,209 @@
# Shared Python + accelerator base image.
#
# Built once per (build-type, arch, ubuntu-version, cuda-version) combination
# by .github/workflows/base_images.yml and pushed to
# quay.io/go-skynet/ci-cache:base-image-<tag-stem>[-pr<N>]. Consumed by
# backend/Dockerfile.python via the BASE_IMAGE_PREBUILT build-arg.
# See .agents/ci-caching.md.
ARG BASE_IMAGE=ubuntu:24.04
ARG APT_MIRROR=""
ARG APT_PORTS_MIRROR=""
FROM ${BASE_IMAGE}
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG UBUNTU_VERSION=2404
ARG APT_MIRROR
ARG APT_PORTS_MIRROR
LABEL org.opencontainers.image.source="https://github.com/mudler/LocalAI"
LABEL org.opencontainers.image.description="LocalAI Python+accelerator base image"
LABEL org.localai.base.lang="python"
RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates \
espeak-ng \
curl \
libssl-dev \
git wget \
git-lfs \
unzip clang \
upx-ucl \
curl python3-pip \
python-is-python3 \
python3-dev llvm \
libnuma1 libgomp1 \
python3-venv make cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN <<EOT bash
if [ "${UBUNTU_VERSION}" = "2404" ]; then
pip install --break-system-packages --user --upgrade pip
else
pip install --upgrade pip
fi
EOT
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
hipblaslt-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
; fi
# Install uv as a system package
RUN curl -LsSf https://astral.sh/uv/install.sh | UV_INSTALL_DIR=/usr/bin sh
ENV PATH="/root/.cargo/bin:${PATH}"
# Increase timeout for uv installs behind slow networks
ENV UV_HTTP_TIMEOUT=180
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
# Install grpcio-tools (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${UBUNTU_VERSION}" = "2404" ]; then
pip install --break-system-packages --user grpcio-tools==1.71.0 grpcio==1.71.0
else
pip install grpcio-tools==1.71.0 grpcio==1.71.0
fi
EOT

View File

@@ -0,0 +1,47 @@
# Shared Rust base image for the kokoros backend.
#
# Built once per (ubuntu-version) by .github/workflows/base_images.yml and
# pushed to quay.io/go-skynet/ci-cache:base-image-<tag-stem>[-pr<N>]. The
# current rust matrix is CPU-only, so this base skips the GPU SDK stanzas;
# if a future rust backend needs cublas/rocm/etc., promote this recipe to
# mirror Dockerfile.python's GPU stack. See .agents/ci-caching.md.
ARG BASE_IMAGE=ubuntu:24.04
ARG APT_MIRROR=""
ARG APT_PORTS_MIRROR=""
FROM ${BASE_IMAGE}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG UBUNTU_VERSION=2404
ARG APT_MIRROR
ARG APT_PORTS_MIRROR
LABEL org.opencontainers.image.source="https://github.com/mudler/LocalAI"
LABEL org.opencontainers.image.description="LocalAI Rust base image"
LABEL org.localai.base.lang="rust"
RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
git ccache \
ca-certificates \
make cmake wget \
curl unzip \
clang \
pkg-config \
libssl-dev \
espeak-ng libespeak-ng-dev \
libsonic-dev libpcaudio-dev \
libopus-dev \
protobuf-compiler && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install Rust
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
ENV PATH="/root/.cargo/bin:${PATH}"

View File

@@ -0,0 +1,100 @@
name: 'Configure apt mirror'
description: |
Reconfigure the GitHub Actions runner's Ubuntu apt sources to use an
alternate mirror, and emit the effective URLs as outputs so callers can
forward them as Docker build-args.
Two mirror profiles depending on where the runner lives, because the
best mirror differs by network:
* github-hosted runners run on Azure, so they default to the
Azure-hosted Ubuntu mirror (lowest latency, same VPC).
* self-hosted runners (arc-runner-set, bigger-runner, ...) typically
cannot route to azure.archive.ubuntu.com, so they default to the
kernel.org mirror, which is publicly reachable from anywhere.
Pass an empty string to either input to skip the rewrite for that
profile and keep upstream archive.ubuntu.com / ports.ubuntu.com.
inputs:
github-hosted-mirror:
description: 'archive/security mirror URL for github-hosted runners (empty = upstream)'
required: false
default: 'http://azure.archive.ubuntu.com'
github-hosted-ports-mirror:
description: 'ports.ubuntu.com mirror URL for github-hosted runners (empty = upstream)'
required: false
default: 'http://azure.ports.ubuntu.com'
self-hosted-mirror:
description: 'archive/security mirror URL for self-hosted runners (empty = upstream)'
required: false
# HTTP, not HTTPS: the bare ubuntu:24.04 builder image doesn't ship
# ca-certificates, so the very first apt-get update over TLS would
# fail with "No system certificates available" before it can install
# anything. apt validates package integrity via GPG signatures, so
# plain HTTP is safe for the archive itself.
default: 'http://mirrors.edge.kernel.org'
self-hosted-ports-mirror:
description: 'ports.ubuntu.com mirror URL for self-hosted runners (empty = upstream)'
required: false
# mirrors.edge.kernel.org does NOT carry /ubuntu-ports/ — only the
# main /ubuntu/ archive — so arm64 builds 404 there. Leave ports
# upstream by default. The original DDoS was on archive.ubuntu.com
# so ports.ubuntu.com remains the path of least surprise.
default: ''
outputs:
effective-mirror:
description: 'The mirror URL actually applied for this runner (or empty)'
value: ${{ steps.pick.outputs.mirror }}
effective-ports-mirror:
description: 'The ports mirror URL actually applied for this runner (or empty)'
value: ${{ steps.pick.outputs.ports-mirror }}
runs:
using: 'composite'
steps:
- name: Pick effective mirror for this runner
id: pick
shell: bash
env:
RUNNER_ENV: ${{ runner.environment }}
GH_MIRROR: ${{ inputs.github-hosted-mirror }}
GH_PORTS_MIRROR: ${{ inputs.github-hosted-ports-mirror }}
SH_MIRROR: ${{ inputs.self-hosted-mirror }}
SH_PORTS_MIRROR: ${{ inputs.self-hosted-ports-mirror }}
run: |
if [ "${RUNNER_ENV}" = "github-hosted" ]; then
MIRROR="${GH_MIRROR}"
PORTS_MIRROR="${GH_PORTS_MIRROR}"
else
MIRROR="${SH_MIRROR}"
PORTS_MIRROR="${SH_PORTS_MIRROR}"
fi
echo "configure-apt-mirror: runner=${RUNNER_ENV} mirror='${MIRROR}' ports-mirror='${PORTS_MIRROR}'"
echo "mirror=${MIRROR}" >> "$GITHUB_OUTPUT"
echo "ports-mirror=${PORTS_MIRROR}" >> "$GITHUB_OUTPUT"
- name: Rewrite apt sources
if: steps.pick.outputs.mirror != '' || steps.pick.outputs.ports-mirror != ''
shell: bash
env:
APT_MIRROR: ${{ steps.pick.outputs.mirror }}
APT_PORTS_MIRROR: ${{ steps.pick.outputs.ports-mirror }}
run: |
set -e
# Ubuntu 24.04 (noble) ships DEB822 sources at
# /etc/apt/sources.list.d/ubuntu.sources; older releases use
# /etc/apt/sources.list. Rewrite whichever exists.
for f in /etc/apt/sources.list.d/ubuntu.sources /etc/apt/sources.list; do
sudo test -f "$f" || continue
if [ -n "${APT_MIRROR}" ]; then
# Comma delimiter so the alternation pipe in the regex is not
# interpreted as the s/// separator.
sudo sed -i -E "s,https?://(archive\.ubuntu\.com|security\.ubuntu\.com),${APT_MIRROR},g" "$f"
fi
if [ -n "${APT_PORTS_MIRROR}" ]; then
sudo sed -i -E "s,https?://ports\.ubuntu\.com,${APT_PORTS_MIRROR},g" "$f"
fi
done
echo "Runner apt mirror configured (APT_MIRROR='${APT_MIRROR}', APT_PORTS_MIRROR='${APT_PORTS_MIRROR}')"

3164
.github/backend-matrix.yaml vendored Normal file
View File

File diff suppressed because it is too large Load Diff

45
.github/bump_vllm_wheel.sh vendored Executable file
View File

@@ -0,0 +1,45 @@
#!/bin/bash
# Bump the cublas13 vLLM wheel pin in requirements-cublas13-after.txt.
#
# vLLM's PyPI wheel is built against CUDA 12 so the cublas13 build pulls a
# cu130-flavoured wheel from vLLM's per-tag index at
# https://wheels.vllm.ai/<TAG>/cu130/. That URL segment is itself version-locked
# (no /latest/ alias upstream), so bumping vLLM means rewriting both the URL
# segment and the version constraint atomically. bump_deps.sh handles git-sha
# vars in Makefiles; this script handles the two-value rewrite specific to the
# vLLM requirements file.
set -xe
REPO=$1 # vllm-project/vllm
FILE=$2 # backend/python/vllm/requirements-cublas13-after.txt
VAR=$3 # VLLM_VERSION (used for output file names so the workflow can read them)
if [ -z "$FILE" ] || [ -z "$REPO" ] || [ -z "$VAR" ]; then
echo "usage: $0 <repo> <requirements-file> <var-name>" >&2
exit 1
fi
# /releases/latest returns the most recent non-prerelease tag.
LATEST_TAG=$(curl -sS -H "Accept: application/vnd.github+json" \
"https://api.github.com/repos/$REPO/releases/latest" \
| python3 -c "import json,sys; print(json.load(sys.stdin)['tag_name'])")
# Strip leading 'v' (vLLM tags are 'v0.20.0', the URL/version use '0.20.0').
NEW_VERSION="${LATEST_TAG#v}"
set +e
CURRENT_VERSION=$(grep -oE '^vllm==[0-9]+\.[0-9]+\.[0-9]+' "$FILE" | head -1 | cut -d= -f3)
set -e
# sed both lines unconditionally — peter-evans/create-pull-request opens no PR
# when the working tree is clean, so a no-op rewrite is safe.
sed -i "$FILE" \
-e "s|wheels\.vllm\.ai/[^/]*/cu130|wheels.vllm.ai/$NEW_VERSION/cu130|g" \
-e "s|^vllm==.*|vllm==$NEW_VERSION|"
if [ -z "$CURRENT_VERSION" ]; then
echo "Could not find vllm==X.Y.Z in $FILE."
exit 0
fi
echo "Changes: https://github.com/$REPO/compare/v${CURRENT_VERSION}...${LATEST_TAG}" >> "${VAR}_message.txt"
echo "${NEW_VERSION}" >> "${VAR}_commit.txt"

View File

File diff suppressed because it is too large Load Diff

View File

@@ -61,7 +61,17 @@ on:
amdgpu-targets:
description: 'AMD GPU targets for ROCm/HIP builds'
required: false
default: 'gfx908,gfx90a,gfx942,gfx950,gfx1030,gfx1100,gfx1101,gfx1102,gfx1151,gfx1200,gfx1201'
default: ''
type: string
base-image-prebuilt:
description: |
Optional reference to a prebuilt accel/lang base image
(quay.io/go-skynet/ci-cache:base-image-<stem>[-pr<N>]). When
set, the backend Dockerfile FROMs this image instead of running
an inline bootstrap. See .github/workflows/base_images.yml and
.agents/ci-caching.md.
required: false
default: ''
type: string
secrets:
dockerUsername:
@@ -80,6 +90,14 @@ jobs:
quay_username: ${{ secrets.quayUsername }}
steps:
- name: Checkout
uses: actions/checkout@v6
with:
submodules: true
- name: Configure apt mirror on runner
id: apt_mirror
uses: ./.github/actions/configure-apt-mirror
- name: Free Disk Space (Ubuntu)
if: inputs.runs-on == 'ubuntu-latest'
@@ -97,20 +115,6 @@ jobs:
docker-images: true
swap-storage: true
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
with:
submodules: true
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
run: |
@@ -208,6 +212,15 @@ jobs:
username: ${{ secrets.quayUsername }}
password: ${{ secrets.quayPassword }}
# Weekly cache-buster for the per-backend `make` step. Most Python
# backends list unpinned deps (torch, transformers, vllm, ...), so a
# warm cache freezes upstream versions indefinitely. Rolling this
# weekly forces a re-resolve of the install layer at most once per
# week, picking up newer wheels without a full cold rebuild.
- name: Compute deps refresh key
id: deps_refresh
run: echo "key=$(date -u +%Y-W%V)" >> "$GITHUB_OUTPUT"
- name: Build and push
uses: docker/build-push-action@v7
if: github.event_name != 'pull_request'
@@ -222,9 +235,14 @@ jobs:
BACKEND=${{ inputs.backend }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
AMDGPU_TARGETS=${{ inputs.amdgpu-targets }}
APT_MIRROR=${{ steps.apt_mirror.outputs.effective-mirror }}
APT_PORTS_MIRROR=${{ steps.apt_mirror.outputs.effective-ports-mirror }}
DEPS_REFRESH=${{ steps.deps_refresh.outputs.key }}
BASE_IMAGE_PREBUILT=${{ inputs.base-image-prebuilt }}
context: ${{ inputs.context }}
file: ${{ inputs.dockerfile }}
cache-from: type=gha
cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache${{ inputs.tag-suffix }}
cache-to: type=registry,ref=quay.io/go-skynet/ci-cache:cache${{ inputs.tag-suffix }},mode=max,ignore-error=true
platforms: ${{ inputs.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta.outputs.tags }}
@@ -244,9 +262,13 @@ jobs:
BACKEND=${{ inputs.backend }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
AMDGPU_TARGETS=${{ inputs.amdgpu-targets }}
APT_MIRROR=${{ steps.apt_mirror.outputs.effective-mirror }}
APT_PORTS_MIRROR=${{ steps.apt_mirror.outputs.effective-ports-mirror }}
DEPS_REFRESH=${{ steps.deps_refresh.outputs.key }}
BASE_IMAGE_PREBUILT=${{ inputs.base-image-prebuilt }}
context: ${{ inputs.context }}
file: ${{ inputs.dockerfile }}
cache-from: type=gha
cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache${{ inputs.tag-suffix }}
platforms: ${{ inputs.platforms }}
push: ${{ env.quay_username != '' }}
tags: ${{ steps.meta_pull_request.outputs.tags }}

View File

@@ -48,6 +48,13 @@ jobs:
strategy:
matrix:
go-version: ['${{ inputs.go-version }}']
env:
# Keep the brew Cellar stable across cache restores. Without these,
# `brew install` would auto-update brew itself and re-link formulas,
# mutating the very paths the cache just restored.
HOMEBREW_NO_AUTO_UPDATE: '1'
HOMEBREW_NO_INSTALL_CLEANUP: '1'
HOMEBREW_NO_ANALYTICS: '1'
steps:
- name: Clone
uses: actions/checkout@v6
@@ -58,21 +65,141 @@ jobs:
uses: actions/setup-go@v5
with:
go-version: ${{ matrix.go-version }}
cache: false
# Caches ~/go/pkg/mod and ~/Library/Caches/go-build keyed on go.sum.
# Shared across every darwin matrix entry — first job in a run warms
# it, the rest hit warm.
cache: true
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
# ---- Homebrew cache ----
# macOS runners have no Docker daemon, so the BuildKit registry cache used
# for Linux backend images (see .agents/ci-caching.md) doesn't apply here.
# We cache the brew downloads + Cellar entries for the formulas we install
# below. Read on every run, write only on master/tag pushes — same policy
# as the Linux registry cache.
- name: Restore Homebrew cache
id: brew-cache
uses: actions/cache/restore@v4
with:
path: |
~/Library/Caches/Homebrew/downloads
/opt/homebrew/Cellar/protobuf
/opt/homebrew/Cellar/grpc
/opt/homebrew/Cellar/protoc-gen-go
/opt/homebrew/Cellar/protoc-gen-go-grpc
/opt/homebrew/Cellar/libomp
/opt/homebrew/Cellar/llvm
/opt/homebrew/Cellar/ccache
key: brew-${{ runner.os }}-${{ runner.arch }}-v1-${{ hashFiles('.github/workflows/backend_build_darwin.yml') }}
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
# ccache is always installed (used by the llama-cpp variant build) so
# the brew cache content stays stable across every backend in the
# matrix — they all share one cache key.
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm ccache
- name: Save Homebrew cache
if: github.event_name != 'pull_request' && steps.brew-cache.outputs.cache-hit != 'true'
uses: actions/cache/save@v4
with:
path: |
~/Library/Caches/Homebrew/downloads
/opt/homebrew/Cellar/protobuf
/opt/homebrew/Cellar/grpc
/opt/homebrew/Cellar/protoc-gen-go
/opt/homebrew/Cellar/protoc-gen-go-grpc
/opt/homebrew/Cellar/libomp
/opt/homebrew/Cellar/llvm
/opt/homebrew/Cellar/ccache
key: brew-${{ runner.os }}-${{ runner.arch }}-v1-${{ hashFiles('.github/workflows/backend_build_darwin.yml') }}
# ---- ccache for llama.cpp CMake builds ----
# Three CMake variants (fallback, grpc, rpc-server) compile the same
# llama.cpp source tree with overlapping flags — ccache dedupes object
# files across them. Key on the pinned LLAMA_VERSION so a pin bump
# invalidates cleanly; restore-keys fall back to the latest entry for the
# same pin so unchanged TUs stay warm even when the cache is fresh.
- name: Compute llama.cpp version
if: inputs.backend == 'llama-cpp'
id: llama-version
run: |
version=$(grep '^LLAMA_VERSION' backend/cpp/llama-cpp/Makefile | head -1 | cut -d= -f2 | cut -d'?' -f1 | tr -d ' ')
echo "version=${version}" >> "$GITHUB_OUTPUT"
- name: Restore ccache
if: inputs.backend == 'llama-cpp'
id: ccache-cache
uses: actions/cache/restore@v4
with:
path: ~/Library/Caches/ccache
key: ccache-llama-${{ runner.arch }}-${{ steps.llama-version.outputs.version }}-${{ github.run_id }}
restore-keys: |
ccache-llama-${{ runner.arch }}-${{ steps.llama-version.outputs.version }}-
- name: Configure ccache
if: inputs.backend == 'llama-cpp'
run: |
mkdir -p "$HOME/Library/Caches/ccache"
ccache -M 2G
ccache -z
# llama-cpp-darwin.sh reads CMAKE_ARGS / CCACHE_DIR from env.
{
echo "CMAKE_ARGS=${CMAKE_ARGS:-} -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache"
echo "CCACHE_DIR=$HOME/Library/Caches/ccache"
} >> "$GITHUB_ENV"
# ---- Python wheel cache (uv + pip) ----
# Mirrors the Linux DEPS_REFRESH cadence (see .agents/ci-caching.md): the
# ISO-week segment of the cache key forces at most one cold rebuild per
# backend per week, automatically picking up newer wheels for unpinned
# deps (torch, mlx, diffusers, …). Restore-keys fall back to the most
# recent build of the same backend so off-week PRs still hit warm.
- name: Compute weekly cache bucket
if: inputs.lang == 'python'
id: weekly
run: echo "bucket=$(date -u +%Y-W%V)" >> "$GITHUB_OUTPUT"
- name: Restore Python wheel cache
if: inputs.lang == 'python'
id: pyenv-cache
uses: actions/cache/restore@v4
with:
path: |
~/Library/Caches/pip
~/Library/Caches/uv
key: pyenv-darwin-${{ inputs.backend }}-${{ steps.weekly.outputs.bucket }}-${{ hashFiles(format('backend/python/{0}/requirements*.txt', inputs.backend)) }}
restore-keys: |
pyenv-darwin-${{ inputs.backend }}-
- name: Build ${{ inputs.backend }}-darwin
run: |
make protogen-go
BACKEND=${{ inputs.backend }} BUILD_TYPE=${{ inputs.build-type }} USE_PIP=${{ inputs.use-pip }} make build-darwin-${{ inputs.lang }}-backend
- name: ccache stats
if: inputs.backend == 'llama-cpp'
run: ccache -s
- name: Save ccache
if: inputs.backend == 'llama-cpp' && github.event_name != 'pull_request'
uses: actions/cache/save@v4
with:
path: ~/Library/Caches/ccache
key: ccache-llama-${{ runner.arch }}-${{ steps.llama-version.outputs.version }}-${{ github.run_id }}
- name: Save Python wheel cache
if: inputs.lang == 'python' && github.event_name != 'pull_request' && steps.pyenv-cache.outputs.cache-hit != 'true'
uses: actions/cache/save@v4
with:
path: |
~/Library/Caches/pip
~/Library/Caches/uv
key: pyenv-darwin-${{ inputs.backend }}-${{ steps.weekly.outputs.bucket }}-${{ hashFiles(format('backend/python/{0}/requirements*.txt', inputs.backend)) }}
- name: Upload ${{ inputs.backend }}.tar
uses: actions/upload-artifact@v7
with:

View File

@@ -13,8 +13,10 @@ jobs:
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
matrix-darwin: ${{ steps.set-matrix.outputs.matrix-darwin }}
bases-matrix: ${{ steps.set-matrix.outputs.bases-matrix }}
has-backends: ${{ steps.set-matrix.outputs.has-backends }}
has-backends-darwin: ${{ steps.set-matrix.outputs.has-backends-darwin }}
has-bases: ${{ steps.set-matrix.outputs.has-bases }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
@@ -27,7 +29,8 @@ jobs:
bun add js-yaml
bun add @octokit/core
# filters the matrix in backend.yml
# Filters the matrix from backend.yml against this PR's changed files
# AND derives the deduplicated bases-matrix consumed by build-bases.
- name: Filter matrix for changed backends
id: set-matrix
env:
@@ -35,10 +38,34 @@ jobs:
GITHUB_EVENT_PATH: ${{ github.event_path }}
run: bun run scripts/changed-backends.js
backend-jobs:
build-bases:
needs: generate-matrix
if: needs.generate-matrix.outputs.has-bases == 'true'
strategy:
fail-fast: false
matrix: ${{ fromJSON(needs.generate-matrix.outputs.bases-matrix) }}
uses: ./.github/workflows/base_images.yml
with:
lang: ${{ matrix.lang }}
base-image: ${{ matrix.base-image }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
ubuntu-version: ${{ matrix.ubuntu-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
tag-stem: ${{ matrix.tag-stem }}
skip-drivers: ${{ matrix.skip-drivers }}
secrets:
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
backend-jobs:
needs: [generate-matrix, build-bases]
uses: ./.github/workflows/backend_build.yml
if: needs.generate-matrix.outputs.has-backends == 'true'
if: |
always() && needs.generate-matrix.outputs.has-backends == 'true' &&
(needs.build-bases.result == 'success' || needs.build-bases.result == 'skipped')
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
@@ -53,12 +80,18 @@ jobs:
skip-drivers: ${{ matrix.skip-drivers }}
context: ${{ matrix.context }}
ubuntu-version: ${{ matrix.ubuntu-version }}
amdgpu-targets: ${{ matrix.amdgpu-targets || 'gfx908,gfx90a,gfx942,gfx950,gfx1030,gfx1100,gfx1101,gfx1102,gfx1151,gfx1200,gfx1201' }}
# The script annotates each filtered Python entry with the prebuilt
# base ref it should consume; non-Python entries get '' and run their
# own inline bootstrap.
base-image-prebuilt: ${{ matrix.base-image-prebuilt || '' }}
secrets:
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
fail-fast: true
matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix) }}
backend-jobs-darwin:
needs: generate-matrix
uses: ./.github/workflows/backend_build_darwin.yml

152
.github/workflows/base_images.yml vendored Normal file
View File

@@ -0,0 +1,152 @@
---
name: 'build base image (reusable)'
# Builds and pushes one (lang, accel, arch, ubuntu, cuda) base image flavour
# to quay.io/go-skynet/ci-cache:base-image-<stem>[-pr<N>]. Consumed by
# backend builds via the BASE_IMAGE_PREBUILT build-arg. PR builds tag with
# `-pr${PR_NUMBER}` so the same PR's backend matrix can opt-in to the
# freshly-built base; master builds overwrite the unsuffixed tag for
# downstream consumption. The image lives in the same ci-cache repo as the
# buildkit cache (under a `base-image-` prefix that doesn't collide with
# the `base-<stem>` cache prefix), so no separate quay repo + grant is
# needed. See .agents/ci-caching.md for the full tagging scheme.
on:
workflow_call:
inputs:
lang:
description: 'Language toolchain (matches .docker/bases/Dockerfile.<lang>)'
required: true
type: string
base-image:
description: 'Upstream base image (ubuntu:24.04, rocm/dev-ubuntu-24.04:..., etc.)'
required: true
type: string
build-type:
description: 'BUILD_TYPE: empty for CPU, cublas, hipblas, vulkan, l4t, ...'
default: ''
type: string
cuda-major-version:
description: 'CUDA major version (only meaningful for cublas/l4t)'
default: '12'
type: string
cuda-minor-version:
description: 'CUDA minor version'
default: '9'
type: string
ubuntu-version:
description: 'Ubuntu version code (2204, 2404)'
default: '2404'
type: string
platforms:
description: 'Single platform per call (linux/amd64 or linux/arm64)'
required: true
type: string
runs-on:
description: 'Runner label'
required: true
type: string
tag-stem:
description: 'Stable portion of the image tag (e.g. python-cpu-amd64-2404)'
required: true
type: string
skip-drivers:
description: 'Pass-through to the base Dockerfile'
default: 'false'
type: string
secrets:
quayUsername:
required: false
quayPassword:
required: false
outputs:
image-ref:
description: 'Full image reference of the built base'
value: ${{ jobs.base-build.outputs.image-ref }}
jobs:
base-build:
runs-on: ${{ inputs.runs-on }}
env:
quay_username: ${{ secrets.quayUsername }}
outputs:
image-ref: ${{ steps.compute_ref.outputs.ref }}
steps:
- name: Checkout
uses: actions/checkout@v6
- name: Configure apt mirror on runner
id: apt_mirror
uses: ./.github/actions/configure-apt-mirror
- name: Free Disk Space (Ubuntu)
if: inputs.runs-on == 'ubuntu-latest'
uses: jlumbroso/free-disk-space@main
with:
tool-cache: true
android: true
dotnet: true
haskell: true
large-packages: true
docker-images: true
swap-storage: true
- name: Compute image ref
id: compute_ref
run: |
stem='${{ inputs.tag-stem }}'
if [ "${{ github.event_name }}" = "pull_request" ]; then
tag="${stem}-pr${{ github.event.number }}"
else
tag="${stem}"
fi
echo "tag=${tag}" >> "$GITHUB_OUTPUT"
# Published into the existing ci-cache repo (the CI robot already
# has write access there) under a distinct `base-image-` prefix so
# the OCI image tags coexist with the buildkit cache tags
# (`base-<stem>`, `cache<tag-suffix>`, `cache-localai<tag-suffix>`).
echo "ref=quay.io/go-skynet/ci-cache:base-image-${tag}" >> "$GITHUB_OUTPUT"
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
platforms: all
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@master
- name: Login to Quay.io
if: ${{ env.quay_username != '' }}
uses: docker/login-action@v4
with:
registry: quay.io
username: ${{ secrets.quayUsername }}
password: ${{ secrets.quayPassword }}
- name: Build and push base image
uses: docker/build-push-action@v7
with:
builder: ${{ steps.buildx.outputs.name }}
context: .
file: ./.docker/bases/Dockerfile.${{ inputs.lang }}
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
BASE_IMAGE=${{ inputs.base-image }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
APT_MIRROR=${{ steps.apt_mirror.outputs.effective-mirror }}
APT_PORTS_MIRROR=${{ steps.apt_mirror.outputs.effective-ports-mirror }}
platforms: ${{ inputs.platforms }}
# Push on PRs as well (if creds present) so the PR's backend matrix
# can opt-in to the freshly-built base via -pr${N} tag.
push: ${{ env.quay_username != '' }}
tags: ${{ steps.compute_ref.outputs.ref }}
cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:base-${{ inputs.tag-stem }}
cache-to: type=registry,ref=quay.io/go-skynet/ci-cache:base-${{ inputs.tag-stem }},mode=max,ignore-error=true
- name: job summary
run: |
echo "Built base image: ${{ steps.compute_ref.outputs.ref }}" >> "$GITHUB_STEP_SUMMARY"

View File

@@ -50,6 +50,8 @@ jobs:
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Configure apt mirror on runner
uses: ./.github/actions/configure-apt-mirror
- name: Set up Go
uses: actions/setup-go@v5
with:

View File

@@ -50,6 +50,10 @@ jobs:
variable: "QWEN3TTS_CPP_VERSION"
branch: "main"
file: "backend/go/qwen3-tts-cpp/Makefile"
- repository: "mudler/vibevoice.cpp"
variable: "VIBEVOICE_CPP_VERSION"
branch: "master"
file: "backend/go/vibevoice-cpp/Makefile"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
@@ -80,5 +84,37 @@ jobs:
body: ${{ steps.bump.outputs.message }}
signoff: true
bump-vllm-wheel:
# vLLM's cu130 wheel comes from a per-tag index URL (no /latest/ alias),
# so the cublas13 requirements file pins both a URL segment and a version
# constraint. bump_deps.sh handles git-sha-in-Makefile only — this job
# rewrites both values atomically when a new vLLM stable tag ships.
if: github.repository == 'mudler/LocalAI'
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- name: Bump vLLM cu130 wheel pin 🔧
id: bump
run: |
bash .github/bump_vllm_wheel.sh vllm-project/vllm backend/python/vllm/requirements-cublas13-after.txt VLLM_VERSION
{
echo 'message<<EOF'
cat "VLLM_VERSION_message.txt"
echo EOF
} >> "$GITHUB_OUTPUT"
{
echo 'commit<<EOF'
cat "VLLM_VERSION_commit.txt"
echo EOF
} >> "$GITHUB_OUTPUT"
rm -rfv VLLM_VERSION_message.txt VLLM_VERSION_commit.txt
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update vllm-project/vllm cu130 wheel'
title: 'chore: :arrow_up: Update vllm-project/vllm cu130 wheel to `${{ steps.bump.outputs.commit }}`'
branch: "update/VLLM_VERSION"
body: ${{ steps.bump.outputs.message }}
signoff: true

View File

@@ -8,15 +8,9 @@ jobs:
if: github.repository == 'mudler/LocalAI'
runs-on: ubuntu-latest
steps:
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- uses: actions/checkout@v6
- name: Configure apt mirror on runner
uses: ./.github/actions/configure-apt-mirror
- name: Install dependencies
run: |
sudo apt-get update

View File

@@ -2,7 +2,7 @@ name: Gallery Agent
on:
schedule:
- cron: '0 */3 * * *' # Run every 4 hours
- cron: '0 */12 * * *' # Run every 4 hours
workflow_dispatch:
inputs:
search_term:

View File

@@ -1,96 +0,0 @@
name: 'generate and publish GRPC docker caches'
on:
workflow_dispatch:
schedule:
# daily at midnight
- cron: '0 0 * * *'
concurrency:
group: grpc-cache-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
generate_caches:
if: github.repository == 'mudler/LocalAI'
strategy:
matrix:
include:
- grpc-base-image: ubuntu:24.04
runs-on: 'ubuntu-latest'
platforms: 'linux/amd64,linux/arm64'
runs-on: ${{matrix.runs-on}}
steps:
- name: Release space from worker
if: matrix.runs-on == 'ubuntu-latest'
run: |
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
sudo apt-get remove -y '^mono-.*' || true
sudo apt-get remove -y '^ghc-.*' || true
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
sudo apt-get remove -y 'php.*' || true
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
sudo apt-get remove -y '^google-.*' || true
sudo apt-get remove -y azure-cli || true
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
sudo apt-get remove -y '^gfortran-.*' || true
sudo apt-get remove -y microsoft-edge-stable || true
sudo apt-get remove -y firefox || true
sudo apt-get remove -y powershell || true
sudo apt-get remove -y r-base-core || true
sudo apt-get autoremove -y
sudo apt-get clean
echo
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
sudo rm -rfv build || true
sudo rm -rf /usr/share/dotnet || true
sudo rm -rf /opt/ghc || true
sudo rm -rf "/usr/local/share/boost" || true
sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
df -h
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
platforms: all
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@master
- name: Checkout
uses: actions/checkout@v6
- name: Cache GRPC
uses: docker/build-push-action@v7
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
# This means that even the MAKEFLAGS have to be an EXACT match.
# If the build-args are not an EXACT match, it will result in a cache miss, which will require GRPC to be built from scratch.
build-args: |
GRPC_BASE_IMAGE=${{ matrix.grpc-base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
context: .
file: ./Dockerfile
cache-to: type=gha,ignore-error=true
cache-from: type=gha
target: grpc
platforms: ${{ matrix.platforms }}
push: false

View File

@@ -16,7 +16,7 @@ jobs:
strategy:
matrix:
include:
- base-image: intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04
- base-image: intel/oneapi-basekit:2025.3.2-0-devel-ubuntu24.04
runs-on: 'arc-runner-set'
platforms: 'linux/amd64'
runs-on: ${{matrix.runs-on}}

View File

@@ -20,7 +20,6 @@
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
ubuntu-version: ${{ matrix.ubuntu-version }}
secrets:
@@ -60,15 +59,13 @@
tag-latest: 'false'
tag-suffix: '-hipblas'
base-image: "rocm/dev-ubuntu-24.04:7.2.1"
grpc-base-image: "ubuntu:24.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'sycl'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
grpc-base-image: "ubuntu:24.04"
base-image: "intel/oneapi-basekit:2025.3.2-0-devel-ubuntu24.04"
tag-suffix: 'sycl'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"

View File

@@ -25,7 +25,6 @@
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
ubuntu-version: ${{ matrix.ubuntu-version }}
ubuntu-codename: ${{ matrix.ubuntu-codename }}
@@ -42,12 +41,11 @@
tag-latest: 'auto'
tag-suffix: '-gpu-hipblas'
base-image: "rocm/dev-ubuntu-24.04:7.2.1"
grpc-base-image: "ubuntu:24.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
core-image-build:
if: github.repository == 'mudler/LocalAI'
uses: ./.github/workflows/image_build.yml
@@ -60,7 +58,6 @@
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
skip-drivers: ${{ matrix.skip-drivers }}
ubuntu-version: ${{ matrix.ubuntu-version }}
@@ -121,8 +118,7 @@
- build-type: 'intel'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
grpc-base-image: "ubuntu:24.04"
base-image: "intel/oneapi-basekit:2025.3.2-0-devel-ubuntu24.04"
tag-suffix: '-gpu-intel'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
@@ -141,7 +137,6 @@
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
skip-drivers: ${{ matrix.skip-drivers }}
ubuntu-version: ${{ matrix.ubuntu-version }}

View File

@@ -8,11 +8,6 @@ on:
description: 'Base image'
required: true
type: string
grpc-base-image:
description: 'GRPC Base image, must be a compatible image with base-image'
required: false
default: ''
type: string
build-type:
description: 'Build type'
default: ''
@@ -75,6 +70,13 @@ jobs:
runs-on: ${{ inputs.runs-on }}
steps:
- name: Checkout
uses: actions/checkout@v6
- name: Configure apt mirror on runner
id: apt_mirror
uses: ./.github/actions/configure-apt-mirror
- name: Free Disk Space (Ubuntu)
if: inputs.runs-on == 'ubuntu-latest'
uses: jlumbroso/free-disk-space@main
@@ -90,16 +92,6 @@ jobs:
large-packages: true
docker-images: true
swap-storage: true
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
@@ -201,25 +193,21 @@ jobs:
if: github.event_name != 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
# This means that even the MAKEFLAGS have to be an EXACT match.
# If the build-args are not an EXACT match, it will result in a cache miss, which will require GRPC to be built from scratch.
# This is why some build args like GRPC_VERSION and MAKEFLAGS are hardcoded
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
BASE_IMAGE=${{ inputs.base-image }}
GRPC_BASE_IMAGE=${{ inputs.grpc-base-image || inputs.base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
MAKEFLAGS=${{ inputs.makeflags }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
UBUNTU_CODENAME=${{ inputs.ubuntu-codename }}
APT_MIRROR=${{ steps.apt_mirror.outputs.effective-mirror }}
APT_PORTS_MIRROR=${{ steps.apt_mirror.outputs.effective-ports-mirror }}
context: .
file: ./Dockerfile
cache-from: type=gha
cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache-localai${{ inputs.tag-suffix }}
cache-to: type=registry,ref=quay.io/go-skynet/ci-cache:cache-localai${{ inputs.tag-suffix }},mode=max,ignore-error=true
platforms: ${{ inputs.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta.outputs.tags }}
@@ -230,25 +218,20 @@ jobs:
if: github.event_name == 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
# This means that even the MAKEFLAGS have to be an EXACT match.
# If the build-args are not an EXACT match, it will result in a cache miss, which will require GRPC to be built from scratch.
# This is why some build args like GRPC_VERSION and MAKEFLAGS are hardcoded
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
BASE_IMAGE=${{ inputs.base-image }}
GRPC_BASE_IMAGE=${{ inputs.grpc-base-image || inputs.base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
MAKEFLAGS=${{ inputs.makeflags }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
UBUNTU_CODENAME=${{ inputs.ubuntu-codename }}
APT_MIRROR=${{ steps.apt_mirror.outputs.effective-mirror }}
APT_PORTS_MIRROR=${{ steps.apt_mirror.outputs.effective-ports-mirror }}
context: .
file: ./Dockerfile
cache-from: type=gha
cache-from: type=registry,ref=quay.io/go-skynet/ci-cache:cache-localai${{ inputs.tag-suffix }}
platforms: ${{ inputs.platforms }}
#push: true
tags: ${{ steps.meta_pull_request.outputs.tags }}

48
.github/workflows/lint.yml vendored Normal file
View File

@@ -0,0 +1,48 @@
---
name: 'lint'
on:
pull_request:
paths-ignore:
- 'docs/**'
- 'examples/**'
- 'README.md'
- '**/*.md'
push:
branches:
- master
concurrency:
group: ci-lint-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
golangci-lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
with:
# Full history so golangci-lint's new-from-merge-base can reach
# origin/master and compute the diff against it.
fetch-depth: 0
- uses: actions/setup-go@v5
with:
go-version: '1.26.x'
cache: false
- name: install golangci-lint
run: |
curl -sSfL https://raw.githubusercontent.com/golangci/golangci-lint/master/install.sh \
| sh -s -- -b "$(go env GOPATH)/bin" v2.11.4
- name: generate grpc proto sources
# pkg/grpc/proto/*.go is generated, not checked in. Several packages
# import it, so without this step typecheck fails project-wide.
run: make protogen-go
- name: stub react-ui dist for go:embed
# core/http/app.go has //go:embed react-ui/dist/*; the glob needs at
# least one non-hidden entry to satisfy typecheck. We don't run
# `make react-ui` here because lint doesn't need the real bundle.
run: |
mkdir -p core/http/react-ui/dist
touch core/http/react-ui/dist/index.html
- name: lint
run: make lint

View File

@@ -49,6 +49,8 @@ jobs:
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Configure apt mirror on runner
uses: ./.github/actions/configure-apt-mirror
- name: Set up Go
uses: actions/setup-go@v5
with:

View File

@@ -36,10 +36,13 @@ jobs:
sglang: ${{ steps.detect.outputs.sglang }}
acestep-cpp: ${{ steps.detect.outputs.acestep-cpp }}
qwen3-tts-cpp: ${{ steps.detect.outputs.qwen3-tts-cpp }}
vibevoice-cpp: ${{ steps.detect.outputs.vibevoice-cpp }}
localvqe: ${{ steps.detect.outputs.localvqe }}
voxtral: ${{ steps.detect.outputs.voxtral }}
kokoros: ${{ steps.detect.outputs.kokoros }}
insightface: ${{ steps.detect.outputs.insightface }}
speaker-recognition: ${{ steps.detect.outputs.speaker-recognition }}
sherpa-onnx: ${{ steps.detect.outputs.sherpa-onnx }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
@@ -506,6 +509,99 @@ jobs:
- name: Build llama-cpp backend image and run audio transcription gRPC e2e tests
run: |
make test-extra-backend-llama-cpp-transcription
# PR-acceptance smoke gate: always runs on every PR (no detect-changes gate, no
# paths filter). Pulls the pre-built master CPU llama-cpp image from quay
# instead of building from source, so the cost is a docker pull (~30s) plus the
# short Qwen3-0.6B model download. Exercises the full gRPC surface — health,
# load, predict, stream — plus the logprobs/logit_bias specs that moved out of
# core/http/app_test.go. Anything heavier or per-backend is gated to the
# detect-changes path-filter above.
tests-llama-cpp-smoke:
runs-on: ubuntu-latest
timeout-minutes: 20
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Pull pre-built llama-cpp backend image
run: docker pull quay.io/go-skynet/local-ai-backends:master-cpu-llama-cpp
- name: Run e2e-backends smoke
env:
BACKEND_IMAGE: quay.io/go-skynet/local-ai-backends:master-cpu-llama-cpp
BACKEND_TEST_CAPS: health,load,predict,stream,logprobs,logit_bias
run: |
make test-extra-backend
# Realtime e2e with sherpa-onnx driving VAD + STT + TTS against a mocked LLM.
# Builds the sherpa-onnx Docker image, extracts the rootfs so the e2e suite
# can discover the backend binary + shared libs, downloads the three model
# bundles (silero-vad, omnilingual-asr, vits-ljs) and drives the realtime
# websocket spec end-to-end.
tests-sherpa-onnx-realtime:
needs: detect-changes
if: needs.detect-changes.outputs.sherpa-onnx == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Setup Node.js
uses: actions/setup-node@v6
with:
node-version: '22'
- name: Build sherpa-onnx backend image and run realtime e2e tests
run: |
make test-extra-e2e-realtime-sherpa
# Streaming ASR via the sherpa-onnx online recognizer (zipformer
# transducer). Exercises both AudioTranscription (buffered) and
# AudioTranscriptionStream (real-time deltas) on the e2e-backends
# harness.
tests-sherpa-onnx-grpc-transcription:
needs: detect-changes
if: needs.detect-changes.outputs.sherpa-onnx == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Build sherpa-onnx backend image and run streaming ASR gRPC e2e tests
run: |
make test-extra-backend-sherpa-onnx-transcription
# VITS TTS via the sherpa-onnx backend. Drives both TTS (file write) and
# TTSStream (PCM chunks) on the e2e-backends harness.
tests-sherpa-onnx-grpc-tts:
needs: detect-changes
if: needs.detect-changes.outputs.sherpa-onnx == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Build sherpa-onnx backend image and run TTS gRPC e2e tests
run: |
make test-extra-backend-sherpa-onnx-tts
tests-ik-llama-cpp-grpc:
needs: detect-changes
if: needs.detect-changes.outputs.ik-llama-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
@@ -698,6 +794,117 @@ jobs:
- name: Test qwen3-tts-cpp
run: |
make --jobs=5 --output-sync=target -C backend/go/qwen3-tts-cpp test
# Per-backend smoke for vibevoice-cpp: builds the .so + Go binary and
# runs `make -C backend/go/vibevoice-cpp test`. test.sh auto-downloads
# the published mudler/vibevoice.cpp-models bundle (TTS Q8_0 + ASR Q4_K
# + tokenizer + voice) and runs the closed-loop TTS → ASR Go test.
tests-vibevoice-cpp:
needs: detect-changes
if: needs.detect-changes.outputs.vibevoice-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential cmake curl libopenblas-dev ffmpeg
- name: Setup Go
uses: actions/setup-go@v5
- name: Display Go version
run: go version
- name: Proto Dependencies
run: |
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Build vibevoice-cpp
run: |
make --jobs=5 --output-sync=target -C backend/go/vibevoice-cpp
- name: Test vibevoice-cpp
run: |
make --jobs=5 --output-sync=target -C backend/go/vibevoice-cpp test
# End-to-end TTS via the e2e-backends gRPC harness. Builds the
# vibevoice-cpp Docker image and drives Backend/TTS against it with a
# real LocalAI gRPC client.
tests-vibevoice-cpp-grpc-tts:
needs: detect-changes
if: needs.detect-changes.outputs.vibevoice-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Build vibevoice-cpp backend image and run TTS gRPC e2e tests
run: |
make test-extra-backend-vibevoice-cpp-tts
# End-to-end transcription via the e2e-backends gRPC harness. The
# vibevoice ASR is a 7B-param model (Q4_K weights ~10 GB on disk)
# and the JFK 30 s decode is too heavy for a free 4-core
# ubuntu-latest pool runner - two CI attempts got SIGTERM'd during
# LoadModel, before the test could even progress. Use the
# self-hosted 'bigger-runner' label (same one the GPU image builds
# in backend.yml use) and the documented dotnet/ghc/android cache
# purge to clear ~10-20 GB of headroom for the model + Docker
# image + working dir.
tests-vibevoice-cpp-grpc-transcription:
needs: detect-changes
if: needs.detect-changes.outputs.vibevoice-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: bigger-runner
timeout-minutes: 150
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
make build-essential curl unzip ca-certificates git tar
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Free disk space
run: |
sudo rm -rf /usr/share/dotnet /opt/ghc /usr/local/lib/android /opt/hostedtoolcache/CodeQL || true
df -h
- name: Build vibevoice-cpp backend image and run ASR gRPC e2e tests
run: |
make test-extra-backend-vibevoice-cpp-transcription
# End-to-end audio transform via the e2e-backends gRPC harness. The
# LocalVQE GGUF is small (~5 MB) and the model is real-time on CPU, so
# the default ubuntu-latest pool is plenty.
tests-localvqe-grpc-transform:
needs: detect-changes
if: needs.detect-changes.outputs.localvqe == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 60
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Build localvqe backend image and run audio_transform gRPC e2e tests
run: |
make test-extra-backend-localvqe-transform
tests-voxtral:
needs: detect-changes
if: needs.detect-changes.outputs.voxtral == 'true' || needs.detect-changes.outputs.run-all == 'true'

View File

@@ -3,15 +3,18 @@ name: 'tests'
on:
pull_request:
paths-ignore:
- 'docs/**'
- 'examples/**'
- 'README.md'
- '**/*.md'
- 'backend/**'
push:
branches:
- master
tags:
- '*'
env:
GRPC_VERSION: v1.65.0
concurrency:
group: ci-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
@@ -100,73 +103,9 @@ jobs:
node-version: '22'
- name: Build React UI
run: make react-ui
- name: Build backends
run: |
make backends/transformers
mkdir external && mv backends/transformers external/transformers
make backends/llama-cpp backends/local-store backends/silero-vad backends/piper backends/whisper backends/stablediffusion-ggml
- name: Test
run: |
TRANSFORMER_BACKEND=$PWD/external/transformers/run.sh PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
tests-e2e-container:
runs-on: ubuntu-latest
steps:
- name: Release space from worker
run: |
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
sudo apt-get remove -y '^mono-.*' || true
sudo apt-get remove -y '^ghc-.*' || true
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
sudo apt-get remove -y 'php.*' || true
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
sudo apt-get remove -y '^google-.*' || true
sudo apt-get remove -y azure-cli || true
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
sudo apt-get remove -y '^gfortran-.*' || true
sudo apt-get autoremove -y
sudo apt-get clean
echo
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Test
run: |
PATH="$PATH:$HOME/go/bin" make backends/local-store backends/silero-vad backends/llama-cpp backends/whisper backends/piper backends/stablediffusion-ggml docker-build-e2e e2e-aio
PATH="$PATH:/root/go/bin" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
@@ -195,7 +134,7 @@ jobs:
run: go version
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm opus
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm opus ffmpeg
pip install --user --no-cache-dir grpcio-tools grpcio
- name: Setup Node.js
uses: actions/setup-node@v6
@@ -203,10 +142,6 @@ jobs:
node-version: '22'
- name: Build React UI
run: make react-ui
- name: Build llama-cpp-darwin
run: |
make protogen-go
make backends/llama-cpp-darwin
- name: Test
run: |
export C_INCLUDE_PATH=/usr/local/include

86
.github/workflows/tests-aio.yml vendored Normal file
View File

@@ -0,0 +1,86 @@
---
name: 'tests-aio'
# Runs the all-in-one (AIO) Docker image with real backends + real models.
# Heavy: builds llama-cpp/whisper/piper/silero-vad/stablediffusion-ggml/local-store
# and exercises end-to-end inference inside the container. Moved out of test.yml
# (which used to run on every PR) so PR CI no longer pays this cost.
#
# Triggers:
# - schedule (nightly @ 04:00 UTC) — catches packaging/image regressions within 24h
# - workflow_dispatch — manual run on-demand
# - push to master/tags — sanity check after merge / before release
on:
schedule:
- cron: '0 4 * * *'
workflow_dispatch:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-tests-aio-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
tests-aio:
runs-on: ubuntu-latest
steps:
- name: Release space from worker
run: |
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
sudo apt-get remove -y '^mono-.*' || true
sudo apt-get remove -y '^ghc-.*' || true
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
sudo apt-get remove -y 'php.*' || true
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
sudo apt-get remove -y '^google-.*' || true
sudo apt-get remove -y azure-cli || true
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
sudo apt-get remove -y '^gfortran-.*' || true
sudo apt-get autoremove -y
sudo apt-get clean
echo
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Test
run: |
PATH="$PATH:$HOME/go/bin" make backends/local-store backends/silero-vad backends/llama-cpp backends/whisper backends/piper backends/stablediffusion-ggml docker-build-e2e e2e-aio
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

View File

@@ -3,6 +3,12 @@ name: 'E2E Backend Tests'
on:
pull_request:
paths-ignore:
- 'docs/**'
- 'examples/**'
- 'README.md'
- '**/*.md'
- 'backend/**'
push:
branches:
- master
@@ -24,6 +30,8 @@ jobs:
uses: actions/checkout@v6
with:
submodules: true
- name: Configure apt mirror on runner
uses: ./.github/actions/configure-apt-mirror
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
with:

View File

@@ -26,6 +26,8 @@ jobs:
uses: actions/checkout@v6
with:
submodules: true
- name: Configure apt mirror on runner
uses: ./.github/actions/configure-apt-mirror
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
with:

View File

@@ -11,6 +11,8 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- name: Configure apt mirror on runner
uses: ./.github/actions/configure-apt-mirror
- uses: actions/setup-go@v5
with:
go-version: 'stable'

53
.golangci.yml Normal file
View File

@@ -0,0 +1,53 @@
version: "2"
# Only issues introduced relative to master are reported. Pre-existing issues
# in the codebase do not fail the lint job; they're treated as a baseline that
# can be cleaned up incrementally. New code (added lines on a branch) is held
# to the full linter set. Locally, `make lint-all` overrides this and reports
# every issue.
issues:
# origin/master because in shallow CI checkouts only the remote-tracking
# branch exists; a bare 'master' ref isn't reachable locally.
new-from-merge-base: origin/master
linters:
default: standard
# staticcheck is noisy on this codebase (mostly QF style suggestions like
# "could use tagged switch" or "unnecessary fmt.Sprintf"). Re-enable
# selectively if a high-signal subset is identified.
disable:
- staticcheck
enable:
- forbidigo
settings:
forbidigo:
forbid:
- pattern: '^t\.Errorf$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Expect(...).To(...) instead of t.Errorf. See .agents/coding-style.md.'
- pattern: '^t\.Error$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Expect(...).To(...) instead of t.Error. See .agents/coding-style.md.'
- pattern: '^t\.Fatalf$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Expect(...).To(Succeed()) / Fail(...) instead of t.Fatalf. See .agents/coding-style.md.'
- pattern: '^t\.Fatal$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Expect(...).To(Succeed()) / Fail(...) instead of t.Fatal. See .agents/coding-style.md.'
- pattern: '^t\.Run$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Describe/Context/It instead of t.Run. See .agents/coding-style.md.'
- pattern: '^t\.Skip$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Skip(...) instead of t.Skip. See .agents/coding-style.md.'
- pattern: '^t\.Skipf$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Skip(...) instead of t.Skipf. See .agents/coding-style.md.'
- pattern: '^t\.SkipNow$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Skip(...) instead of t.SkipNow. See .agents/coding-style.md.'
- pattern: '^t\.Logf$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use GinkgoWriter / fmt.Fprintf(GinkgoWriter, ...) instead of t.Logf. See .agents/coding-style.md.'
- pattern: '^t\.Log$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use GinkgoWriter / fmt.Fprintln(GinkgoWriter, ...) instead of t.Log. See .agents/coding-style.md.'
- pattern: '^t\.Fail$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Fail(...) instead of t.Fail. See .agents/coding-style.md.'
- pattern: '^t\.FailNow$'
msg: 'LocalAI tests must use Ginkgo/Gomega; use Fail(...) instead of t.FailNow. See .agents/coding-style.md.'
exclusions:
paths:
# Upstream whisper.cpp source tree fetched by the whisper backend Makefile.
- 'backend/go/whisper/sources'
- 'docs/'

View File

@@ -19,6 +19,7 @@ LocalAI follows the Linux kernel project's [guidelines for AI coding assistants]
|------|-------------|
| [.agents/ai-coding-assistants.md](.agents/ai-coding-assistants.md) | Policy for AI-assisted contributions — licensing, DCO, attribution |
| [.agents/building-and-testing.md](.agents/building-and-testing.md) | Building the project, running tests, Docker builds for specific platforms |
| [.agents/ci-caching.md](.agents/ci-caching.md) | CI build cache layout (registry-backed BuildKit cache on quay.io/go-skynet/ci-cache), `DEPS_REFRESH` weekly cache-buster for unpinned Python deps, manual eviction |
| [.agents/adding-backends.md](.agents/adding-backends.md) | Adding a new backend (Python, Go, or C++) — full step-by-step checklist, including importer integration (the `/import-model` dropdown is server-driven from `GET /backends/known`) |
| [.agents/coding-style.md](.agents/coding-style.md) | Code style, editorconfig, logging, documentation conventions |
| [.agents/llama-cpp-backend.md](.agents/llama-cpp-backend.md) | Working on the llama.cpp backend — architecture, updating, tool call parsing |
@@ -27,6 +28,7 @@ LocalAI follows the Linux kernel project's [guidelines for AI coding assistants]
| [.agents/api-endpoints-and-auth.md](.agents/api-endpoints-and-auth.md) | Adding API endpoints, auth middleware, feature permissions, user access control |
| [.agents/debugging-backends.md](.agents/debugging-backends.md) | Debugging runtime backend failures, dependency conflicts, rebuilding backends |
| [.agents/adding-gallery-models.md](.agents/adding-gallery-models.md) | Adding GGUF models from HuggingFace to the model gallery |
| [.agents/localai-assistant-mcp.md](.agents/localai-assistant-mcp.md) | LocalAI Assistant chat modality — adding admin tools to the in-process MCP server, editing skill prompts, keeping REST + MCP + skills in sync |
## Quick Reference
@@ -35,5 +37,6 @@ LocalAI follows the Linux kernel project's [guidelines for AI coding assistants]
- **Comments**: Explain *why*, not *what*
- **Docs**: Update `docs/content/` when adding features or changing config
- **New API endpoints**: LocalAI advertises its capability surface in several independent places — swagger `@Tags`, `/api/instructions` registry, auth `RouteFeatureRegistry`, React UI `capabilities.js`, docs. Read [.agents/api-endpoints-and-auth.md](.agents/api-endpoints-and-auth.md) and follow its checklist — missing any surface means clients, admins, and the UI won't know the endpoint exists.
- **Admin endpoints → MCP tool**: every admin endpoint that an admin would manage conversationally (install/list/edit/toggle/upgrade) MUST also be exposed as an MCP tool in `pkg/mcp/localaitools/`. The LocalAI Assistant chat modality and the standalone `local-ai mcp-server` consume that package; drift between REST and MCP is a real risk. Read [.agents/localai-assistant-mcp.md](.agents/localai-assistant-mcp.md) — the `TestToolHTTPRouteMappingComplete` test fails until you wire the new tool and update the route map.
- **Build**: Inspect `Makefile` and `.github/workflows/` — ask the user before running long builds
- **UI**: The active UI is the React app in `core/http/react-ui/`. The older Alpine.js/HTML UI in `core/http/static/` is pending deprecation — all new UI work goes in the React UI

View File

@@ -1,13 +1,20 @@
ARG BASE_IMAGE=ubuntu:24.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
ARG INTEL_BASE_IMAGE=${BASE_IMAGE}
ARG UBUNTU_CODENAME=noble
# Optional alternate Ubuntu apt mirror(s). Empty = use upstream.
# See .docker/apt-mirror.sh for accepted values.
ARG APT_MIRROR=""
ARG APT_PORTS_MIRROR=""
FROM ${BASE_IMAGE} AS requirements
ARG APT_MIRROR
ARG APT_PORTS_MIRROR
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && \
RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates curl wget espeak-ng libgomp1 \
ffmpeg libopenblas0 libopenblas-dev libopus0 sox && \
@@ -149,6 +156,7 @@ RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
hipblaslt-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
@@ -240,10 +248,14 @@ WORKDIR /build
# This is a temporary workaround until Intel fixes their repository
FROM ${INTEL_BASE_IMAGE} AS intel
ARG UBUNTU_CODENAME=noble
ARG APT_MIRROR
ARG APT_PORTS_MIRROR
RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu ${UBUNTU_CODENAME}/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
RUN apt-get update && \
RUN --mount=type=bind,source=.docker/apt-mirror.sh,target=/usr/local/sbin/apt-mirror \
APT_MIRROR="${APT_MIRROR}" APT_PORTS_MIRROR="${APT_PORTS_MIRROR}" sh /usr/local/sbin/apt-mirror && \
apt-get update && \
apt-get install -y --no-install-recommends \
intel-oneapi-runtime-libs && \
apt-get clean && \

334
Makefile
View File

@@ -1,5 +1,5 @@
# Disable parallel execution for backend builds
.NOTPARALLEL: backends/diffusers backends/llama-cpp backends/turboquant backends/outetts backends/piper backends/stablediffusion-ggml backends/whisper backends/faster-whisper backends/silero-vad backends/local-store backends/huggingface backends/rfdetr backends/insightface backends/speaker-recognition backends/kitten-tts backends/kokoro backends/chatterbox backends/llama-cpp-darwin backends/neutts build-darwin-python-backend build-darwin-go-backend backends/mlx backends/diffuser-darwin backends/mlx-vlm backends/mlx-audio backends/mlx-distributed backends/stablediffusion-ggml-darwin backends/vllm backends/vllm-omni backends/sglang backends/moonshine backends/pocket-tts backends/qwen-tts backends/faster-qwen3-tts backends/qwen-asr backends/nemo backends/voxcpm backends/whisperx backends/ace-step backends/acestep-cpp backends/fish-speech backends/voxtral backends/opus backends/trl backends/llama-cpp-quantization backends/kokoros backends/sam3-cpp backends/qwen3-tts-cpp backends/tinygrad
.NOTPARALLEL: backends/diffusers backends/llama-cpp backends/turboquant backends/outetts backends/piper backends/stablediffusion-ggml backends/whisper backends/faster-whisper backends/silero-vad backends/local-store backends/huggingface backends/rfdetr backends/insightface backends/speaker-recognition backends/kitten-tts backends/kokoro backends/chatterbox backends/llama-cpp-darwin backends/neutts build-darwin-python-backend build-darwin-go-backend backends/mlx backends/diffuser-darwin backends/mlx-vlm backends/mlx-audio backends/mlx-distributed backends/stablediffusion-ggml-darwin backends/vllm backends/vllm-omni backends/sglang backends/moonshine backends/pocket-tts backends/qwen-tts backends/faster-qwen3-tts backends/qwen-asr backends/nemo backends/voxcpm backends/whisperx backends/ace-step backends/acestep-cpp backends/fish-speech backends/voxtral backends/opus backends/trl backends/llama-cpp-quantization backends/kokoros backends/sam3-cpp backends/qwen3-tts-cpp backends/vibevoice-cpp backends/localvqe backends/tinygrad backends/sherpa-onnx
GOCMD=go
GOTEST=$(GOCMD) test
@@ -10,6 +10,13 @@ LAUNCHER_BINARY_NAME=local-ai-launcher
UBUNTU_VERSION?=2404
UBUNTU_CODENAME?=noble
# Optional Ubuntu apt mirror overrides forwarded to docker builds.
# Empty = use upstream archive.ubuntu.com / security.ubuntu.com / ports.ubuntu.com.
# Set e.g. APT_MIRROR=http://azure.archive.ubuntu.com to route apt traffic
# during outages of the default Ubuntu pool.
APT_MIRROR?=
APT_PORTS_MIRROR?=
GORELEASER?=
export BUILD_TYPE?=
@@ -65,7 +72,7 @@ endif
TEST_PATHS?=./api/... ./pkg/... ./core/...
.PHONY: all test build vendor
.PHONY: all test build vendor lint lint-all
all: help
@@ -85,6 +92,7 @@ clean: ## Remove build related file
clean-tests:
rm -rf test-models
rm -rf test-dir
rm -f tests/e2e/mock-backend/mock-backend
## Install Go tools
install-go-tools:
@@ -143,32 +151,56 @@ osx-signed: build
run: ## run local-ai
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) run ./
test-models/testmodel.ggml:
mkdir -p test-models
mkdir -p test-dir
wget -q https://huggingface.co/mradermacher/gpt2-alpaca-gpt4-GGUF/resolve/main/gpt2-alpaca-gpt4.Q4_K_M.gguf -O test-models/testmodel.ggml
wget -q https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin -O test-models/whisper-en
wget -q https://cdn.openai.com/whisper/draft-20220913a/micro-machines.wav -O test-dir/audio.wav
cp tests/models_fixtures/* test-models
prepare-test: protogen-go
cp tests/models_fixtures/* test-models
prepare-test: protogen-go build-mock-backend
########################################################
## Tests
########################################################
## Test targets
test: test-models/testmodel.ggml protogen-go
## After the test-suite reorg (see plans/test-reorg) the default `make test`
## no longer downloads multi-GB GGUF/whisper fixtures or builds llama-cpp /
## transformers / piper / whisper / stablediffusion-ggml. core/http/app_test.go
## now drives the mock-backend binary built by build-mock-backend; real-backend
## inference moved into tests/e2e-backends/ (per-backend, path-filtered) and
## tests/e2e-aio/ (nightly).
test: prepare-test
@echo 'Running tests'
export GO_TAGS="debug"
$(MAKE) prepare-test
OPUS_SHIM_LIBRARY=$(abspath ./pkg/opus/shim/libopusshim.so) \
HUGGINGFACE_GRPC=$(abspath ./)/backend/python/transformers/run.sh TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models BACKENDS_PATH=$(abspath ./)/backends \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!llama-gguf" --flake-attempts $(TEST_FLAKES) --fail-fast -v -r $(TEST_PATHS)
$(MAKE) test-llama-gguf
$(MAKE) test-tts
$(MAKE) test-stablediffusion
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts $(TEST_FLAKES) --fail-fast -v -r $(TEST_PATHS)
########################################################
## Lint
########################################################
## Runs golangci-lint with config from .golangci.yml. Includes the standard
## linter set plus forbidigo, which enforces the Ginkgo/Gomega-only test
## convention documented in .agents/coding-style.md.
##
## LINT_EXCLUDE_DIRS_RE matches directories whose Go packages can't typecheck
## without C/C++ headers we don't install in the lint runner (cgo wrappers
## around llama.cpp, piper/spdlog, silero-vad/onnxruntime, and Fyne/OpenGL for
## the launcher). Their compile-time correctness is enforced by their own
## build pipelines. Keep this as a deny list — `go list ./...` discovers
## everything else automatically, so new packages are scanned by default.
LINT_EXCLUDE_DIRS_RE=/(backend/go/(piper|silero-vad|llm)|cmd/launcher)(/|$$)
lint:
@command -v golangci-lint >/dev/null 2>&1 || { \
echo 'golangci-lint not installed. Install: go install github.com/golangci/golangci-lint/v2/cmd/golangci-lint@latest'; \
exit 1; \
}
golangci-lint run $$(go list -e -f '{{.Dir}}' ./... | grep -vE '$(LINT_EXCLUDE_DIRS_RE)')
## Like `lint` but reports every issue, including the pre-existing baseline
## that `lint` ignores via .golangci.yml's new-from-merge-base. Use this to
## see what's available to clean up.
lint-all:
@command -v golangci-lint >/dev/null 2>&1 || { \
echo 'golangci-lint not installed. Install: go install github.com/golangci/golangci-lint/v2/cmd/golangci-lint@latest'; \
exit 1; \
}
golangci-lint run --new=false --new-from-merge-base= --new-from-rev= $$(go list -e -f '{{.Dir}}' ./... | grep -vE '$(LINT_EXCLUDE_DIRS_RE)')
########################################################
## E2E AIO tests (uses standard image with pre-configured models)
@@ -184,6 +216,8 @@ docker-build-e2e:
--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
--build-arg GO_TAGS="$(GO_TAGS)" \
-t local-ai:tests -f Dockerfile .
@@ -198,6 +232,20 @@ run-e2e-aio: protogen-go
@echo 'Running e2e AIO tests'
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts $(TEST_FLAKES) -v -r ./tests/e2e-aio
# vLLM multi-node DP smoke (CPU). Builds local-ai:tests and the
# cpu-vllm backend from the current working tree, then drives a
# head + headless follower via testcontainers-go and asserts a chat
# completion. BuildKit caches both images, so re-runs only rebuild
# what changed. The test lives under tests/e2e/distributed and is
# selected by the VLLMMultinode label so it doesn't run alongside
# the other distributed-suite tests by default.
test-e2e-vllm-multinode: docker-build-e2e extract-backend-vllm protogen-go
@echo 'Running e2e vLLM multi-node DP test'
LOCALAI_IMAGE=local-ai \
LOCALAI_IMAGE_TAG=tests \
LOCALAI_VLLM_BACKEND_DIR=$(abspath ./local-backends/vllm) \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter='VLLMMultinode' -v -r ./tests/e2e/distributed
########################################################
## E2E tests
########################################################
@@ -211,6 +259,8 @@ prepare-e2e:
--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
--build-arg GO_TAGS="$(GO_TAGS)" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
-t localai-tests .
@@ -235,20 +285,12 @@ teardown-e2e:
## Integration and unit tests
########################################################
test-llama-gguf: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models BACKENDS_PATH=$(abspath ./)/backends \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
test-tts: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models BACKENDS_PATH=$(abspath ./)/backends \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
test-stablediffusion: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models BACKENDS_PATH=$(abspath ./)/backends \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
test-stores:
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stores" --flake-attempts $(TEST_FLAKES) -v -r tests/integration
## Storage / vector-store integration. Requires the local-store backend to
## be available — we build it on demand and pass its location via
## BACKENDS_PATH (the model loader looks there for the gRPC binary).
test-stores: backends/local-store
BACKENDS_PATH=$(abspath ./)/backends \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts $(TEST_FLAKES) -v -r tests/integration
test-opus:
@echo 'Running opus backend tests'
@@ -260,6 +302,8 @@ test-opus-docker:
docker build --target builder \
--build-arg BUILD_TYPE=$(or $(BUILD_TYPE),) \
--build-arg BASE_IMAGE=$(or $(BASE_IMAGE),ubuntu:24.04) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
--build-arg BACKEND=opus \
-t localai-opus-test -f backend/Dockerfile.golang .
docker run --rm localai-opus-test \
@@ -269,23 +313,13 @@ test-realtime: build-mock-backend
@echo 'Running realtime e2e tests (mock backend)'
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="Realtime && !real-models" --flake-attempts $(TEST_FLAKES) -v -r ./tests/e2e
# Real-model realtime tests. Set REALTIME_TEST_MODEL to use your own pipeline,
# or leave unset to auto-build one from the component env vars below.
# Container-based real-model realtime testing. Build env vars / pipeline
# definition kept here so test-realtime-models-docker can drive a fully wired
# pipeline (VAD + STT + LLM + TTS) from inside a containerised runner.
REALTIME_VAD?=silero-vad-ggml
REALTIME_STT?=whisper-1
REALTIME_LLM?=qwen3-0.6b
REALTIME_TTS?=tts-1
REALTIME_BACKENDS_PATH?=$(abspath ./)/backends
test-realtime-models: build-mock-backend
@echo 'Running realtime e2e tests (real models)'
REALTIME_TEST_MODEL=$${REALTIME_TEST_MODEL:-realtime-test-pipeline} \
REALTIME_VAD=$(REALTIME_VAD) \
REALTIME_STT=$(REALTIME_STT) \
REALTIME_LLM=$(REALTIME_LLM) \
REALTIME_TTS=$(REALTIME_TTS) \
REALTIME_BACKENDS_PATH=$(REALTIME_BACKENDS_PATH) \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="Realtime" --flake-attempts $(TEST_FLAKES) -v -r ./tests/e2e
# --- Container-based real-model testing ---
@@ -299,7 +333,7 @@ local-backends:
extract-backend-%: docker-build-% local-backends
@echo "Extracting backend $*..."
@CID=$$(docker create local-ai-backend:$*) && \
@CID=$$(docker create --entrypoint=/run.sh local-ai-backend:$*) && \
rm -rf local-backends/$* && mkdir -p local-backends/$* && \
docker cp $$CID:/ - | tar -xf - -C local-backends/$* && \
docker rm $$CID > /dev/null
@@ -311,6 +345,8 @@ test-realtime-models-docker: build-mock-backend
--build-arg BUILD_TYPE=$(or $(BUILD_TYPE),cublas) \
--build-arg CUDA_MAJOR_VERSION=$(or $(CUDA_MAJOR_VERSION),13) \
--build-arg CUDA_MINOR_VERSION=$(or $(CUDA_MINOR_VERSION),0) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
-t localai-test-runner .
docker run --rm \
$(REALTIME_DOCKER_FLAGS) \
@@ -394,7 +430,13 @@ protoc:
.PHONY: protogen-go
protogen-go: protoc install-go-tools
mkdir -p pkg/grpc/proto
./protoc --experimental_allow_proto3_optional -Ibackend/ --go_out=pkg/grpc/proto/ --go_opt=paths=source_relative --go-grpc_out=pkg/grpc/proto/ --go-grpc_opt=paths=source_relative \
# install-go-tools writes protoc-gen-go and protoc-gen-go-grpc into
# $(shell go env GOPATH)/bin, which isn't on every dev's PATH. protoc
# resolves its code-gen plugins via PATH, so without this prefix the
# generate step fails with "protoc-gen-go: program not found". Prepend
# GOPATH/bin so the freshly-installed plugins win without requiring a
# shell-profile change.
PATH="$$(go env GOPATH)/bin:$$PATH" ./protoc --experimental_allow_proto3_optional -Ibackend/ --go_out=pkg/grpc/proto/ --go_opt=paths=source_relative --go-grpc_out=pkg/grpc/proto/ --go-grpc_opt=paths=source_relative \
backend/backend.proto
core/config/inference_defaults.json: ## Fetch inference defaults from unsloth (only if missing)
@@ -522,7 +564,9 @@ test-extra-backend: protogen-go
## Convenience wrappers: build the image, then exercise it.
test-extra-backend-llama-cpp: docker-build-llama-cpp
BACKEND_IMAGE=local-ai-backend:llama-cpp $(MAKE) test-extra-backend
BACKEND_IMAGE=local-ai-backend:llama-cpp \
BACKEND_TEST_CAPS=health,load,predict,stream,logprobs,logit_bias \
$(MAKE) test-extra-backend
test-extra-backend-ik-llama-cpp: docker-build-ik-llama-cpp
BACKEND_IMAGE=local-ai-backend:ik-llama-cpp $(MAKE) test-extra-backend
@@ -564,6 +608,14 @@ test-extra-backend-vllm: docker-build-vllm
BACKEND_TEST_OPTIONS=tool_parser:hermes \
$(MAKE) test-extra-backend
## vllm multi-node data-parallel smoke test. Runs LocalAI head + a
## `local-ai p2p-worker vllm` follower in docker compose against
## Qwen2.5-0.5B with data_parallel_size=2. Requires 2 NVIDIA GPUs and
## nvidia-container-runtime on the host — vLLM v1's DP coordinator is
## not viable on CPU so this cannot run in CI without GPU.
test-extra-backend-vllm-multinode:
./tests/e2e/vllm-multinode/smoke.sh
## tinygrad mirrors the vllm target (same model, same caps, same parser) so
## the two backends are directly comparable. The LLM path covers Predict,
## streaming and native tool-call extraction. Companion targets below cover
@@ -780,6 +832,80 @@ test-extra-backend-speaker-recognition-ecapa: docker-build-speaker-recognition
test-extra-backend-speaker-recognition-all: \
test-extra-backend-speaker-recognition-ecapa
## Realtime e2e with sherpa-onnx driving VAD + STT + TTS against a mocked
## LLM. Extracts the sherpa-onnx Docker image rootfs, downloads the three
## gallery-referenced model bundles (silero-vad, omnilingual-asr, vits-ljs),
## writes the corresponding model config YAMLs, and runs the realtime
## websocket spec in tests/e2e with REALTIME_* env vars wiring the sherpa
## slots into the pipeline. The LLM slot stays on the in-repo mock-backend
## registered unconditionally by tests/e2e/e2e_suite_test.go. See
## tests/e2e/run-realtime-sherpa.sh for the full orchestration.
test-extra-e2e-realtime-sherpa: build-mock-backend docker-build-sherpa-onnx protogen-go react-ui
bash tests/e2e/run-realtime-sherpa.sh
## Streaming ASR via the sherpa-onnx online recognizer. Uses the streaming
## zipformer English model (encoder/decoder/joiner int8 + tokens) from the
## sherpa-onnx gallery entry. Drives both AudioTranscription and
## AudioTranscriptionStream via the e2e-backends gRPC harness; streaming
## emits real partial deltas during decode. Each file is renamed on download
## to the shape sherpa-onnx's online loader expects (encoder.int8.onnx etc.).
test-extra-backend-sherpa-onnx-transcription: docker-build-sherpa-onnx
BACKEND_IMAGE=local-ai-backend:sherpa-onnx \
BACKEND_TEST_MODEL_URL='https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-en-2023-06-26/resolve/main/encoder-epoch-99-avg-1-chunk-16-left-128.int8.onnx#encoder.int8.onnx' \
BACKEND_TEST_EXTRA_FILES='https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-en-2023-06-26/resolve/main/decoder-epoch-99-avg-1-chunk-16-left-128.int8.onnx#decoder.int8.onnx|https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-en-2023-06-26/resolve/main/joiner-epoch-99-avg-1-chunk-16-left-128.int8.onnx#joiner.int8.onnx|https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-en-2023-06-26/resolve/main/tokens.txt' \
BACKEND_TEST_AUDIO_URL=https://github.com/ggml-org/whisper.cpp/raw/master/samples/jfk.wav \
BACKEND_TEST_CAPS=health,load,transcription \
BACKEND_TEST_OPTIONS=subtype=online \
$(MAKE) test-extra-backend
## VITS TTS via the sherpa-onnx backend. Pulls the individual files from
## HuggingFace (the vits-ljs release tarball lives on the k2-fsa github
## but is also mirrored as discrete files on HF). Exercises both
## TTS (write-to-file) and TTSStream (PCM chunks + WAV header) via the
## e2e-backends gRPC harness.
test-extra-backend-sherpa-onnx-tts: docker-build-sherpa-onnx
BACKEND_IMAGE=local-ai-backend:sherpa-onnx \
BACKEND_TEST_MODEL_URL='https://huggingface.co/csukuangfj/vits-ljs/resolve/main/vits-ljs.onnx#vits-ljs.onnx' \
BACKEND_TEST_EXTRA_FILES='https://huggingface.co/csukuangfj/vits-ljs/resolve/main/tokens.txt|https://huggingface.co/csukuangfj/vits-ljs/resolve/main/lexicon.txt' \
BACKEND_TEST_CAPS=health,load,tts \
$(MAKE) test-extra-backend
## VibeVoice TTS via the vibevoice-cpp backend. ModelFile is the
## realtime gguf; the supplementary tokenizer + voice prompt land
## alongside it under the harness's models dir and are wired through
## via the standard Options[] convention (tokenizer=, voice=).
test-extra-backend-vibevoice-cpp-tts: docker-build-vibevoice-cpp
BACKEND_IMAGE=local-ai-backend:vibevoice-cpp \
BACKEND_TEST_MODEL_URL='https://huggingface.co/mudler/vibevoice.cpp-models/resolve/main/vibevoice-realtime-0.5B-q8_0.gguf#vibevoice-realtime-0.5B-q8_0.gguf' \
BACKEND_TEST_EXTRA_FILES='https://huggingface.co/mudler/vibevoice.cpp-models/resolve/main/tokenizer.gguf#tokenizer.gguf|https://huggingface.co/mudler/vibevoice.cpp-models/resolve/main/voice-en-Carter_man.gguf#voice-en-Carter_man.gguf' \
BACKEND_TEST_OPTIONS=tokenizer:tokenizer.gguf,voice:voice-en-Carter_man.gguf \
BACKEND_TEST_CAPS=health,load,tts \
$(MAKE) test-extra-backend
## VibeVoice ASR (long-form, with diarization). type=asr tells the
## backend's Load() to slot ModelFile into the asr_model role; the
## tokenizer is supplied via Options[]. Uses the Q4_K quant (~10 GB)
## rather than Q8_0 (~14 GB) so the bundle fits inside ubuntu-latest's
## post-image disk budget.
test-extra-backend-vibevoice-cpp-transcription: docker-build-vibevoice-cpp
BACKEND_IMAGE=local-ai-backend:vibevoice-cpp \
BACKEND_TEST_MODEL_URL='https://huggingface.co/mudler/vibevoice.cpp-models/resolve/main/vibevoice-asr-q4_k.gguf#vibevoice-asr-q4_k.gguf' \
BACKEND_TEST_EXTRA_FILES='https://huggingface.co/mudler/vibevoice.cpp-models/resolve/main/tokenizer.gguf#tokenizer.gguf' \
BACKEND_TEST_AUDIO_URL=https://github.com/ggml-org/whisper.cpp/raw/master/samples/jfk.wav \
BACKEND_TEST_OPTIONS=type:asr,tokenizer:tokenizer.gguf \
BACKEND_TEST_CAPS=health,load,transcription \
$(MAKE) test-extra-backend
## LocalVQE audio transform (joint AEC + noise suppression + dereverb).
## Exercises the audio_transform capability end-to-end: batch transform
## of a real WAV fixture and bidi streaming of synthetic silent frames.
test-extra-backend-localvqe-transform: docker-build-localvqe
BACKEND_IMAGE=local-ai-backend:localvqe \
BACKEND_TEST_MODEL_URL='https://huggingface.co/LocalAI-io/LocalVQE/resolve/main/localvqe-v1-1.3M-f32.gguf#localvqe-v1-1.3M-f32.gguf' \
BACKEND_TEST_AUDIO_URL=https://github.com/ggml-org/whisper.cpp/raw/master/samples/jfk.wav \
BACKEND_TEST_CAPS=health,load,audio_transform \
$(MAKE) test-extra-backend
## sglang mirrors the vllm setup: HuggingFace model id, same tiny Qwen,
## tool-call extraction via sglang's native qwen parser. CPU builds use
## sglang's upstream pyproject_cpu.toml recipe (see backend/python/sglang/install.sh).
@@ -822,6 +948,8 @@ docker:
--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
-t $(DOCKER_IMAGE) .
docker-cuda12:
@@ -835,11 +963,13 @@ docker-cuda12:
--build-arg BUILD_TYPE=$(BUILD_TYPE) \
--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
-t $(DOCKER_IMAGE)-cuda-12 .
docker-image-intel:
docker build \
--build-arg BASE_IMAGE=intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04 \
--build-arg BASE_IMAGE=intel/oneapi-basekit:2025.3.2-0-devel-ubuntu24.04 \
--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
--build-arg GO_TAGS="$(GO_TAGS)" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
@@ -848,6 +978,8 @@ docker-image-intel:
--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
-t $(DOCKER_IMAGE) .
########################################################
@@ -916,7 +1048,10 @@ BACKEND_WHISPER = whisper|golang|.|false|true
BACKEND_VOXTRAL = voxtral|golang|.|false|true
BACKEND_ACESTEP_CPP = acestep-cpp|golang|.|false|true
BACKEND_QWEN3_TTS_CPP = qwen3-tts-cpp|golang|.|false|true
BACKEND_VIBEVOICE_CPP = vibevoice-cpp|golang|.|false|true
BACKEND_LOCALVQE = localvqe|golang|.|false|true
BACKEND_OPUS = opus|golang|.|false|true
BACKEND_SHERPA_ONNX = sherpa-onnx|golang|.|false|true
# Python backends with root context
BACKEND_RERANKERS = rerankers|python|.|false|true
@@ -959,6 +1094,90 @@ BACKEND_KOKOROS = kokoros|rust|.|false|true
# C++ backends (Go wrapper with purego)
BACKEND_SAM3_CPP = sam3-cpp|golang|.|false|true
# Tag stem for the local prebuilt base images. Mirrors tagStem() in
# scripts/changed-backends.js and the inline expression in
# .github/workflows/backend.yml, so a `make docker-build-X` produces the
# same FROM ref shape that CI uses.
LOCAL_BASE_BUILD_TYPE := $(or $(BUILD_TYPE),cpu)
LOCAL_BASE_UBUNTU_VERSION := $(or $(UBUNTU_VERSION),2404)
LOCAL_BASE_CUDA_SUFFIX := $(if $(filter cublas l4t,$(BUILD_TYPE)),-cuda$(CUDA_MAJOR_VERSION).$(CUDA_MINOR_VERSION))
LOCAL_BASE_PYTHON_TAG := localai-base:python-$(LOCAL_BASE_BUILD_TYPE)-$(LOCAL_BASE_UBUNTU_VERSION)$(LOCAL_BASE_CUDA_SUFFIX)
LOCAL_BASE_GOLANG_TAG := localai-base:golang-$(LOCAL_BASE_BUILD_TYPE)-$(LOCAL_BASE_UBUNTU_VERSION)$(LOCAL_BASE_CUDA_SUFFIX)
LOCAL_BASE_CPP_TAG := localai-base:cpp-$(LOCAL_BASE_BUILD_TYPE)-$(LOCAL_BASE_UBUNTU_VERSION)$(LOCAL_BASE_CUDA_SUFFIX)
LOCAL_BASE_RUST_TAG := localai-base:rust-$(LOCAL_BASE_BUILD_TYPE)-$(LOCAL_BASE_UBUNTU_VERSION)
# Per-(lang) base image build targets. Each backend's docker-build-X target
# depends on the matching base via generate-docker-build-target below.
# PHONY so docker handles its own layer caching.
.PHONY: docker-build-python-base docker-build-golang-base docker-build-cpp-base docker-build-rust-base
docker-build-python-base:
docker build \
--build-arg BUILD_TYPE=$(BUILD_TYPE) \
--build-arg BASE_IMAGE=$(or $(BASE_IMAGE),ubuntu:24.04) \
--build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) \
--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
--build-arg UBUNTU_VERSION=$(LOCAL_BASE_UBUNTU_VERSION) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
$(if $(SKIP_DRIVERS),--build-arg SKIP_DRIVERS=$(SKIP_DRIVERS)) \
-t $(LOCAL_BASE_PYTHON_TAG) \
-f .docker/bases/Dockerfile.python \
.
docker-build-golang-base:
docker build \
--build-arg BUILD_TYPE=$(BUILD_TYPE) \
--build-arg BASE_IMAGE=$(or $(BASE_IMAGE),ubuntu:24.04) \
--build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) \
--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
--build-arg UBUNTU_VERSION=$(LOCAL_BASE_UBUNTU_VERSION) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
$(if $(SKIP_DRIVERS),--build-arg SKIP_DRIVERS=$(SKIP_DRIVERS)) \
-t $(LOCAL_BASE_GOLANG_TAG) \
-f .docker/bases/Dockerfile.golang \
.
docker-build-cpp-base:
docker build \
--build-arg BUILD_TYPE=$(BUILD_TYPE) \
--build-arg BASE_IMAGE=$(or $(BASE_IMAGE),ubuntu:24.04) \
--build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) \
--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
--build-arg UBUNTU_VERSION=$(LOCAL_BASE_UBUNTU_VERSION) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
$(if $(SKIP_DRIVERS),--build-arg SKIP_DRIVERS=$(SKIP_DRIVERS)) \
-t $(LOCAL_BASE_CPP_TAG) \
-f .docker/bases/Dockerfile.cpp \
.
docker-build-rust-base:
docker build \
--build-arg BASE_IMAGE=$(or $(BASE_IMAGE),ubuntu:24.04) \
--build-arg UBUNTU_VERSION=$(LOCAL_BASE_UBUNTU_VERSION) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
-t $(LOCAL_BASE_RUST_TAG) \
-f .docker/bases/Dockerfile.rust \
.
# Map a consumer dockerfile-type to the base-image tag it should consume.
# Mirrors langOf() in scripts/changed-backends.js: the C++ trio
# (llama-cpp/ik-llama-cpp/turboquant) all consume the shared cpp base.
local-base-tag = $(strip \
$(if $(filter python,$(1)),$(LOCAL_BASE_PYTHON_TAG), \
$(if $(filter golang,$(1)),$(LOCAL_BASE_GOLANG_TAG), \
$(if $(filter llama-cpp ik-llama-cpp turboquant,$(1)),$(LOCAL_BASE_CPP_TAG), \
$(if $(filter rust,$(1)),$(LOCAL_BASE_RUST_TAG))))))
local-base-target = $(strip \
$(if $(filter python,$(1)),docker-build-python-base, \
$(if $(filter golang,$(1)),docker-build-golang-base, \
$(if $(filter llama-cpp ik-llama-cpp turboquant,$(1)),docker-build-cpp-base, \
$(if $(filter rust,$(1)),docker-build-rust-base)))))
# Helper function to build docker image for a backend
# Usage: $(call docker-build-backend,BACKEND_NAME,DOCKERFILE_TYPE,BUILD_CONTEXT,PROGRESS_FLAG,NEEDS_BACKEND_ARG)
define docker-build-backend
@@ -969,14 +1188,20 @@ define docker-build-backend
--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
--build-arg APT_MIRROR=$(APT_MIRROR) \
--build-arg APT_PORTS_MIRROR=$(APT_PORTS_MIRROR) \
$(if $(call local-base-tag,$(2)),--build-arg BASE_IMAGE_PREBUILT=$(call local-base-tag,$(2))) \
$(if $(FROM_SOURCE),--build-arg FROM_SOURCE=$(FROM_SOURCE)) \
$(if $(AMDGPU_TARGETS),--build-arg AMDGPU_TARGETS=$(AMDGPU_TARGETS)) \
$(if $(filter true,$(5)),--build-arg BACKEND=$(1)) \
-t local-ai-backend:$(1) -f backend/Dockerfile.$(2) $(3)
endef
# Generate docker-build targets from backend definitions
# Generate docker-build targets from backend definitions. Each consumer
# gets the matching layered base as a prerequisite so the FROM in the
# slimmed Dockerfile resolves locally. The map lives in local-base-target.
define generate-docker-build-target
docker-build-$(word 1,$(subst |, ,$(1))):
docker-build-$(word 1,$(subst |, ,$(1))): $(call local-base-target,$(word 2,$(subst |, ,$(1))))
$$(call docker-build-backend,$(word 1,$(subst |, ,$(1))),$(word 2,$(subst |, ,$(1))),$(word 3,$(subst |, ,$(1))),$(word 4,$(subst |, ,$(1))),$(word 5,$(subst |, ,$(1))))
endef
@@ -1021,6 +1246,8 @@ $(eval $(call generate-docker-build-target,$(BACKEND_WHISPERX)))
$(eval $(call generate-docker-build-target,$(BACKEND_ACE_STEP)))
$(eval $(call generate-docker-build-target,$(BACKEND_ACESTEP_CPP)))
$(eval $(call generate-docker-build-target,$(BACKEND_QWEN3_TTS_CPP)))
$(eval $(call generate-docker-build-target,$(BACKEND_VIBEVOICE_CPP)))
$(eval $(call generate-docker-build-target,$(BACKEND_LOCALVQE)))
$(eval $(call generate-docker-build-target,$(BACKEND_MLX)))
$(eval $(call generate-docker-build-target,$(BACKEND_MLX_VLM)))
$(eval $(call generate-docker-build-target,$(BACKEND_MLX_DISTRIBUTED)))
@@ -1029,12 +1256,13 @@ $(eval $(call generate-docker-build-target,$(BACKEND_LLAMA_CPP_QUANTIZATION)))
$(eval $(call generate-docker-build-target,$(BACKEND_TINYGRAD)))
$(eval $(call generate-docker-build-target,$(BACKEND_KOKOROS)))
$(eval $(call generate-docker-build-target,$(BACKEND_SAM3_CPP)))
$(eval $(call generate-docker-build-target,$(BACKEND_SHERPA_ONNX)))
# Pattern rule for docker-save targets
docker-save-%: backend-images
docker save local-ai-backend:$* -o backend-images/$*.tar
docker-build-backends: docker-build-llama-cpp docker-build-ik-llama-cpp docker-build-turboquant docker-build-rerankers docker-build-vllm docker-build-vllm-omni docker-build-sglang docker-build-transformers docker-build-outetts docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-chatterbox docker-build-vibevoice docker-build-moonshine docker-build-pocket-tts docker-build-qwen-tts docker-build-fish-speech docker-build-faster-qwen3-tts docker-build-qwen-asr docker-build-nemo docker-build-voxcpm docker-build-whisperx docker-build-ace-step docker-build-acestep-cpp docker-build-voxtral docker-build-mlx-distributed docker-build-trl docker-build-llama-cpp-quantization docker-build-tinygrad docker-build-kokoros docker-build-sam3-cpp docker-build-qwen3-tts-cpp docker-build-insightface docker-build-speaker-recognition
docker-build-backends: docker-build-llama-cpp docker-build-ik-llama-cpp docker-build-turboquant docker-build-rerankers docker-build-vllm docker-build-vllm-omni docker-build-sglang docker-build-transformers docker-build-outetts docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-chatterbox docker-build-vibevoice docker-build-moonshine docker-build-pocket-tts docker-build-qwen-tts docker-build-fish-speech docker-build-faster-qwen3-tts docker-build-qwen-asr docker-build-nemo docker-build-voxcpm docker-build-whisperx docker-build-ace-step docker-build-acestep-cpp docker-build-voxtral docker-build-mlx-distributed docker-build-trl docker-build-llama-cpp-quantization docker-build-tinygrad docker-build-kokoros docker-build-sam3-cpp docker-build-qwen3-tts-cpp docker-build-vibevoice-cpp docker-build-localvqe docker-build-insightface docker-build-speaker-recognition docker-build-sherpa-onnx
########################################################
### Mock Backend for E2E Tests

View File

@@ -38,7 +38,7 @@
- **Built-in AI agents** — autonomous agents with tool use, RAG, MCP, and skills
- **Privacy-first** — your data never leaves your infrastructure
Created and maintained by [Ettore Di Giacinto](https://github.com/mudler).
Created by [Ettore Di Giacinto](https://github.com/mudler) and maintained by the [LocalAI team](#team).
> [:book: Documentation](https://localai.io/) | [:speech_balloon: Discord](https://discord.gg/uJAeKSAGDy) | [💻 Quickstart](https://localai.io/basics/getting_started/) | [🖼️ Models](https://models.localai.io/) | [❓FAQ](https://localai.io/faq/)
@@ -201,13 +201,14 @@ See the full [Backend & Model Compatibility Table](https://localai.io/model-comp
- [Media & blog posts](https://localai.io/basics/news/#media-blogs-social)
- [Examples](https://github.com/mudler/LocalAI-examples)
## Autonomous Development Team
## Team
LocalAI is helped being maintained by a team of autonomous AI agents led by an AI Scrum Master.
LocalAI is maintained by a small team of humans, together with the wider community of contributors.
- **Live Reports**: [reports.localai.io](http://reports.localai.io)
- **Project Board**: [Agent task tracking](https://github.com/users/mudler/projects/6)
- **Blog Post**: [Learn about the experiment](https://mudler.pm/posts/2026/02/28/a-call-to-open-source-maintainers-stop-babysitting-ai-how-i-built-a-100-local-autonomous-dev-team-to-maintain-localai-and-why-you-should-too/)
- **[Ettore Di Giacinto](https://github.com/mudler)** — original author and project lead
- **[Richard Palethorpe](https://github.com/richiejp)** — maintainer
A huge thank you to everyone who contributes code, reviews PRs, files issues, and helps users in [Discord](https://discord.gg/uJAeKSAGDy) — LocalAI is a community-driven project and wouldn't exist without you. See the full [contributors list](https://github.com/mudler/LocalAI/graphs/contributors).
## Citation
@@ -250,7 +251,7 @@ A special thanks to individual sponsors, a full list is on [GitHub](https://gith
## License
LocalAI is a community-driven project created by [Ettore Di Giacinto](https://github.com/mudler/).
LocalAI is a community-driven project created by [Ettore Di Giacinto](https://github.com/mudler/) and maintained by the [LocalAI team](#team).
MIT - Author Ettore Di Giacinto <mudler@localai.io>

View File

@@ -1,189 +1,37 @@
ARG BASE_IMAGE=ubuntu:24.04
# Builds a single Go backend on top of the shared
# .docker/bases/Dockerfile.golang base. The base bakes in apt + GPU SDK +
# Go toolchain + protoc + grpc tooling, so this stage only carries the
# per-backend opus-dev install + COPY + `make build`.
#
# CI orchestration (.github/workflows/backend.yml + backend_pr.yml) builds
# the right base flavour automatically via scripts/changed-backends.js
# and passes BASE_IMAGE_PREBUILT here. For local builds, run:
# make backend-image-base LANG=golang BUILD_TYPE=<...>
# make backend-image BACKEND=<...> BUILD_TYPE=<...>
# See .agents/ci-caching.md.
ARG BASE_IMAGE_PREBUILT
FROM ${BASE_IMAGE_PREBUILT} AS builder
FROM ${BASE_IMAGE} AS builder
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.25.4
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
git ccache \
ca-certificates \
make cmake wget libopenblas-dev \
curl unzip \
libssl-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin:/usr/local/bin
# Install grpc compilers
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
RUN echo "TARGETARCH: $TARGETARCH"
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
ARG AMDGPU_TARGETS
ENV AMDGPU_TARGETS=${AMDGPU_TARGETS}
# opus-dev is only needed for the opus backend; install on demand to keep
# every other golang backend's base image lean.
RUN if [ "${BACKEND}" = "opus" ]; then \
apt-get update && apt-get install -y --no-install-recommends libopus-dev pkg-config && \
apt-get clean && rm -rf /var/lib/apt/lists/*; \
fi
apt-get update && apt-get install -y --no-install-recommends libopus-dev pkg-config && \
apt-get clean && rm -rf /var/lib/apt/lists/*; \
fi
COPY . /LocalAI

View File

@@ -1,250 +1,25 @@
ARG BASE_IMAGE=ubuntu:24.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
# Builds the ik-llama-cpp backend on top of the shared
# .docker/bases/Dockerfile.cpp base (shared with llama-cpp/turboquant).
# See backend/Dockerfile.llama-cpp for the rationale; this consumer differs
# only in the make targets at the end.
ARG BASE_IMAGE_PREBUILT
# The grpc target does one thing, it builds and installs GRPC. This is in it's own layer so that it can be effectively cached by CI.
# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
FROM ${GRPC_BASE_IMAGE} AS grpc
FROM ${BASE_IMAGE_PREBUILT} AS builder
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
# CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
ARG CMAKE_VERSION=3.31.10
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
build-essential curl libssl-dev \
git wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
# and running make install in the target container
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
FROM ${BASE_IMAGE} AS builder
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.31.10
# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
ARG CUDA_DOCKER_ARCH
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
ARG CMAKE_ARGS
ENV CMAKE_ARGS=${CMAKE_ARGS}
ARG BACKEND=rerankers
ARG BACKEND=ik-llama-cpp
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.25.4
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache git \
ca-certificates \
make \
pkg-config libcurl4-openssl-dev \
curl unzip \
libssl-dev wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN echo "TARGETARCH: $TARGETARCH"
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
COPY --from=grpc /opt/grpc /usr/local
COPY . /LocalAI
@@ -270,12 +45,10 @@ fi
EOT
# Copy libraries using a script to handle architecture differences
RUN make -BC /LocalAI/backend/cpp/ik-llama-cpp package
FROM scratch
# Copy all available binaries (the build process only creates the appropriate ones for the target architecture)
COPY --from=builder /LocalAI/backend/cpp/ik-llama-cpp/package/. ./

View File

@@ -1,58 +1,15 @@
ARG BASE_IMAGE=ubuntu:24.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
# Builds the llama-cpp backend on top of the shared
# .docker/bases/Dockerfile.cpp base. The base bakes in apt + GPU SDK +
# protoc + cmake + GRPC, so this stage only carries the COPY + `make`
# invocations and the final scratch-stage package.
#
# CI orchestration (.github/workflows/backend.yml + backend_pr.yml) passes
# BASE_IMAGE_PREBUILT. See .agents/ci-caching.md.
ARG BASE_IMAGE_PREBUILT
# The grpc target does one thing, it builds and installs GRPC. This is in it's own layer so that it can be effectively cached by CI.
# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
FROM ${GRPC_BASE_IMAGE} AS grpc
FROM ${BASE_IMAGE_PREBUILT} AS builder
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
# CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
ARG CMAKE_VERSION=3.31.10
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
build-essential curl libssl-dev \
git wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
# and running make install in the target container
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
FROM ${BASE_IMAGE} AS builder
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.31.10
# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
ARG CUDA_DOCKER_ARCH
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
@@ -60,197 +17,15 @@ ARG CMAKE_ARGS
ENV CMAKE_ARGS=${CMAKE_ARGS}
ARG AMDGPU_TARGETS
ENV AMDGPU_TARGETS=${AMDGPU_TARGETS}
ARG BACKEND=rerankers
ARG BACKEND=llama-cpp
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.25.4
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache git \
ca-certificates \
make \
pkg-config libcurl4-openssl-dev \
curl unzip \
libssl-dev wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig && \
# Log which GPU architectures have rocBLAS kernel support
echo "rocBLAS library data architectures:" && \
(ls /opt/rocm*/lib/rocblas/library/Kernels* 2>/dev/null || ls /opt/rocm*/lib64/rocblas/library/Kernels* 2>/dev/null) | grep -oP 'gfx[0-9a-z+-]+' | sort -u || \
echo "WARNING: No rocBLAS kernel data found" \
; fi
RUN echo "TARGETARCH: $TARGETARCH"
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
COPY --from=grpc /opt/grpc /usr/local
COPY . /LocalAI

View File

@@ -1,195 +1,26 @@
ARG BASE_IMAGE=ubuntu:24.04
# Builds a single Python backend on top of the shared
# .docker/bases/Dockerfile.python base. The base bakes in apt-update + GPU
# SDK install + python toolchain (uv, pip, rustup, grpcio-tools), so this
# stage only carries the per-backend source COPY + `make`.
#
# CI orchestration (.github/workflows/backend.yml + backend_pr.yml) builds
# the right base flavour automatically via scripts/derive-build-matrix.js
# and passes BASE_IMAGE_PREBUILT here. For local builds, run:
# make backend-image-base BUILD_TYPE=<...> # build the base
# make backend-image BACKEND=<...> BUILD_TYPE=<...>
# See .agents/ci-caching.md.
ARG BASE_IMAGE_PREBUILT
FROM ${BASE_IMAGE_PREBUILT} AS builder
FROM ${BASE_IMAGE} AS builder
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates \
espeak-ng \
curl \
libssl-dev \
git wget \
git-lfs \
unzip clang \
upx-ucl \
curl python3-pip \
python-is-python3 \
python3-dev llvm \
libnuma1 libgomp1 \
python3-venv make cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN <<EOT bash
if [ "${UBUNTU_VERSION}" = "2404" ]; then
pip install --break-system-packages --user --upgrade pip
else
pip install --upgrade pip
fi
EOT
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
; fi
# Install uv as a system package
RUN curl -LsSf https://astral.sh/uv/install.sh | UV_INSTALL_DIR=/usr/bin sh
ENV PATH="/root/.cargo/bin:${PATH}"
# Increase timeout for uv installs behind slow networks
ENV UV_HTTP_TIMEOUT=180
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
# Install grpcio-tools (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${UBUNTU_VERSION}" = "2404" ]; then
pip install --break-system-packages --user grpcio-tools==1.71.0 grpcio==1.71.0
else
pip install grpcio-tools==1.71.0 grpcio==1.71.0
fi
EOT
COPY backend/python/${BACKEND} /${BACKEND}
COPY backend/backend.proto /${BACKEND}/backend.proto
@@ -202,6 +33,13 @@ COPY scripts/build/package-gpu-libs.sh /package-gpu-libs.sh
ARG FROM_SOURCE=""
ENV FROM_SOURCE=${FROM_SOURCE}
# Cache-buster for the per-backend `make` step. Most Python backends list
# unpinned deps (torch, transformers, vllm, ...), so a warm registry cache
# would otherwise freeze upstream versions indefinitely. CI passes a value
# that rolls weekly so the install layer is rebuilt at most once per week
# and picks up newer wheels from PyPI / nightly indexes.
ARG DEPS_REFRESH=initial
RUN cd /${BACKEND} && PORTABLE_PYTHON=true make
# Package GPU libraries into the backend's lib directory
@@ -216,4 +54,4 @@ RUN if [ -f "/${BACKEND}/package.sh" ]; then \
FROM scratch
ARG BACKEND=rerankers
COPY --from=builder /${BACKEND}/ /
COPY --from=builder /${BACKEND}/ /

View File

@@ -1,31 +1,15 @@
ARG BASE_IMAGE=ubuntu:24.04
# Builds a single Rust backend on top of the shared
# .docker/bases/Dockerfile.rust base. The base bakes in apt + Rust +
# protobuf-compiler + audio dev libs (espeak/sonic/pcaudio/opus), so this
# stage only carries the per-backend COPY + `make build`.
#
# CI orchestration (.github/workflows/backend.yml + backend_pr.yml) passes
# BASE_IMAGE_PREBUILT. See .agents/ci-caching.md.
FROM ${BASE_IMAGE} AS builder
ARG BASE_IMAGE_PREBUILT
FROM ${BASE_IMAGE_PREBUILT} AS builder
ARG BACKEND=kokoros
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
git ccache \
ca-certificates \
make cmake wget \
curl unzip \
clang \
pkg-config \
libssl-dev \
espeak-ng libespeak-ng-dev \
libsonic-dev libpcaudio-dev \
libopus-dev \
protobuf-compiler && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install Rust
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
ENV PATH="/root/.cargo/bin:${PATH}"
COPY . /LocalAI

View File

@@ -1,254 +1,25 @@
ARG BASE_IMAGE=ubuntu:24.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
# Builds the turboquant backend on top of the shared
# .docker/bases/Dockerfile.cpp base (shared with llama-cpp/ik-llama-cpp).
# See backend/Dockerfile.llama-cpp for the rationale; this consumer differs
# only in the make targets at the end.
ARG BASE_IMAGE_PREBUILT
# The grpc target does one thing, it builds and installs GRPC. This is in it's own layer so that it can be effectively cached by CI.
# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
FROM ${GRPC_BASE_IMAGE} AS grpc
FROM ${BASE_IMAGE_PREBUILT} AS builder
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
# CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
ARG CMAKE_VERSION=3.31.10
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
build-essential curl libssl-dev \
git wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
# and running make install in the target container
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
FROM ${BASE_IMAGE} AS builder
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.31.10
# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
ARG CUDA_DOCKER_ARCH
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
ARG CMAKE_ARGS
ENV CMAKE_ARGS=${CMAKE_ARGS}
ARG BACKEND=rerankers
ARG BACKEND=turboquant
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.25.4
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache git \
ca-certificates \
make \
pkg-config libcurl4-openssl-dev \
curl unzip \
libssl-dev wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig && \
# Log which GPU architectures have rocBLAS kernel support
echo "rocBLAS library data architectures:" && \
(ls /opt/rocm*/lib/rocblas/library/Kernels* 2>/dev/null || ls /opt/rocm*/lib64/rocblas/library/Kernels* 2>/dev/null) | grep -oP 'gfx[0-9a-z+-]+' | sort -u || \
echo "WARNING: No rocBLAS kernel data found" \
; fi
RUN echo "TARGETARCH: $TARGETARCH"
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
COPY --from=grpc /opt/grpc /usr/local
COPY . /LocalAI

View File

@@ -41,9 +41,14 @@ service Backend {
rpc VAD(VADRequest) returns (VADResponse) {}
rpc Diarize(DiarizeRequest) returns (DiarizeResponse) {}
rpc AudioEncode(AudioEncodeRequest) returns (AudioEncodeResult) {}
rpc AudioDecode(AudioDecodeRequest) returns (AudioDecodeResult) {}
rpc AudioTransform(AudioTransformRequest) returns (AudioTransformResult) {}
rpc AudioTransformStream(stream AudioTransformFrameRequest) returns (stream AudioTransformFrameResponse) {}
rpc ModelMetadata(ModelOptions) returns (ModelMetadataResponse) {}
// Fine-tuning RPCs
@@ -310,6 +315,11 @@ message ModelOptions {
bool Reranking = 71;
repeated string Overrides = 72;
// EngineArgs carries a JSON-encoded map of backend-native engine arguments
// applied verbatim to the backend's engine constructor (e.g. vLLM AsyncEngineArgs).
// Unknown keys produce an error at LoadModel time.
string EngineArgs = 73;
}
message Result {
@@ -345,6 +355,12 @@ message TranscriptStreamResponse {
TranscriptResult final_result = 2;
}
message TranscriptWord {
int64 start = 1;
int64 end = 2;
string text = 3;
}
message TranscriptSegment {
int32 id = 1;
int64 start = 2;
@@ -352,6 +368,7 @@ message TranscriptSegment {
string text = 4;
repeated int32 tokens = 5;
string speaker = 6;
repeated TranscriptWord words = 7;
}
message GenerateImageRequest {
@@ -408,6 +425,43 @@ message VADResponse {
repeated VADSegment segments = 1;
}
// --- Speaker diarization messages ---
//
// Pure speaker diarization: "who spoke when". Returns time-stamped segments
// labelled with cluster IDs (the same string for the same speaker across
// segments). Some backends (e.g. vibevoice.cpp) produce diarization as a
// by-product of ASR and may also fill in `text` per segment; backends with a
// dedicated diarization pipeline (e.g. sherpa-onnx pyannote) leave `text`
// empty and emit only the segmentation.
message DiarizeRequest {
string dst = 1; // path to audio file (HTTP layer materialises uploads to a temp file)
uint32 threads = 2;
string language = 3; // optional; only meaningful for transcription-bundling backends
int32 num_speakers = 4; // exact speaker count if known (>0 forces); 0 = auto
int32 min_speakers = 5; // hint when auto-detecting; 0 = unset
int32 max_speakers = 6; // hint when auto-detecting; 0 = unset
float clustering_threshold = 7; // distance threshold when num_speakers unknown; 0 = backend default
float min_duration_on = 8; // discard segments shorter than this (seconds); 0 = backend default
float min_duration_off = 9; // merge gaps shorter than this (seconds); 0 = backend default
bool include_text = 10; // when the backend can emit per-segment transcript for free, ask it to populate `text`
}
message DiarizeSegment {
int32 id = 1;
float start = 2; // seconds
float end = 3; // seconds
string speaker = 4; // backend-emitted speaker label (e.g. "0", "SPEAKER_00")
string text = 5; // optional per-segment transcript (empty unless include_text and supported)
}
message DiarizeResponse {
repeated DiarizeSegment segments = 1;
int32 num_speakers = 2; // count of distinct speaker labels in `segments`
float duration = 3; // total audio duration in seconds (0 if unknown)
string language = 4; // optional, when the backend bundles transcription
}
message SoundGenerationRequest {
string text = 1;
string model = 2;
@@ -664,6 +718,56 @@ message AudioDecodeResult {
int32 samples_per_frame = 3;
}
// Generic audio transform: an audio-in, audio-out operation, optionally
// conditioned on a second reference signal. Concrete transforms include
// AEC + noise suppression + dereverberation (LocalVQE), voice conversion
// (reference = target speaker), pitch shifting, etc.
message AudioTransformRequest {
string audio_path = 1; // required, primary input file path
string reference_path = 2; // optional auxiliary; empty => zero-fill
string dst = 3; // required, output file path
map<string, string> params = 4; // backend-specific tuning
}
message AudioTransformResult {
string dst = 1;
int32 sample_rate = 2;
int32 samples = 3;
bool reference_provided = 4;
}
// Bidirectional streaming audio transform. The first message MUST carry a
// Config; subsequent messages carry Frames. A second Config mid-stream
// resets streaming state before the next frame.
message AudioTransformFrameRequest {
oneof payload {
AudioTransformStreamConfig config = 1;
AudioTransformFrame frame = 2;
}
}
message AudioTransformStreamConfig {
enum SampleFormat {
F32_LE = 0;
S16_LE = 1;
}
SampleFormat sample_format = 1;
int32 sample_rate = 2; // 0 => backend default
int32 frame_samples = 3; // 0 => backend default
map<string, string> params = 4;
bool reset = 5; // reset streaming state before next frame
}
message AudioTransformFrame {
bytes audio_pcm = 1; // frame_samples samples in stream's format
bytes reference_pcm = 2; // empty => zero-fill (silent reference)
}
message AudioTransformFrameResponse {
bytes pcm = 1;
int64 frame_index = 2;
}
message ModelMetadataResponse {
bool supports_thinking = 1;
string rendered_template = 2; // The rendered chat template with enable_thinking=true (empty if not applicable)

View File

@@ -1,5 +1,5 @@
IK_LLAMA_VERSION?=286ce324baed17c95faec77792eaa6bdb1c7a5f5
IK_LLAMA_VERSION?=8b56d813a9ed04fa7b7fe2588fddd845cf64eccb
LLAMA_REPO?=https://github.com/ikawrakow/ik_llama.cpp
CMAKE_ARGS?=

View File

@@ -0,0 +1,11 @@
--- a/examples/llava/clip.cpp
+++ b/examples/llava/clip.cpp
@@ -2494,7 +2494,7 @@
}
new_data = work.data();
- new_size = ggml_quantize_chunk(new_type, f32_data, new_data, 0, n_elms/cur->ne[0], cur->ne[0], nullptr);
+ new_size = ggml_quantize_chunk(new_type, f32_data, new_data, 0, n_elms/cur->ne[0], cur->ne[0], nullptr, nullptr);
} else {
new_type = cur->type;
new_data = cur->data;

View File

@@ -1,5 +1,5 @@
LLAMA_VERSION?=0d0764dfd257c0ae862525c05778207f87b99b1c
LLAMA_VERSION?=bbeb89d76c41bc250f16e4a6fefcc9b530d6e3f3
LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
CMAKE_ARGS?=
@@ -34,6 +34,9 @@ else ifeq ($(BUILD_TYPE),hipblas)
export CXX=$(ROCM_HOME)/llvm/bin/clang++
export CC=$(ROCM_HOME)/llvm/bin/clang
AMDGPU_TARGETS?=gfx908,gfx90a,gfx942,gfx950,gfx1030,gfx1100,gfx1101,gfx1102,gfx1151,gfx1200,gfx1201
ifeq ($(strip $(AMDGPU_TARGETS)),)
$(error AMDGPU_TARGETS is emptyset it to a comma-separated list of gfx targets e.g. gfx1100,gfx1101)
endif
CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS=$(AMDGPU_TARGETS)
else ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DGGML_VULKAN=1

View File

@@ -442,7 +442,7 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
// Draft model for speculative decoding
if (!request->draftmodel().empty()) {
params.speculative.mparams_dft.path = request->draftmodel();
params.speculative.draft.mparams.path = request->draftmodel();
// Default to draft type if a draft model is set but no explicit type
if (params.speculative.type == COMMON_SPECULATIVE_TYPE_NONE) {
params.speculative.type = COMMON_SPECULATIVE_TYPE_DRAFT;
@@ -642,6 +642,21 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
} else if (optval_str == "false" || optval_str == "0" || optval_str == "no" || optval_str == "off" || optval_str == "disabled") {
params.no_op_offload = false;
}
} else if (!strcmp(optname, "split_mode") || !strcmp(optname, "sm")) {
// Accepts: none | layer | row | tensor (the latter requires a llama.cpp build
// that includes ggml-org/llama.cpp#19378, FlashAttention enabled, and KV-cache
// quantization disabled).
if (optval != NULL) {
if (optval_str == "none") {
params.split_mode = LLAMA_SPLIT_MODE_NONE;
} else if (optval_str == "layer") {
params.split_mode = LLAMA_SPLIT_MODE_LAYER;
} else if (optval_str == "row") {
params.split_mode = LLAMA_SPLIT_MODE_ROW;
} else if (optval_str == "tensor") {
params.split_mode = LLAMA_SPLIT_MODE_TENSOR;
}
}
} else if (!strcmp(optname, "kv_unified") || !strcmp(optname, "unified_kv")) {
if (optval_str == "true" || optval_str == "1" || optval_str == "yes" || optval_str == "on" || optval_str == "enabled") {
params.kv_unified = true;
@@ -664,39 +679,39 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
}
} else if (!strcmp(optname, "spec_n_max") || !strcmp(optname, "draft_max")) {
if (optval != NULL) {
try { params.speculative.n_max = std::stoi(optval_str); } catch (...) {}
try { params.speculative.draft.n_max = std::stoi(optval_str); } catch (...) {}
}
} else if (!strcmp(optname, "spec_n_min") || !strcmp(optname, "draft_min")) {
if (optval != NULL) {
try { params.speculative.n_min = std::stoi(optval_str); } catch (...) {}
try { params.speculative.draft.n_min = std::stoi(optval_str); } catch (...) {}
}
} else if (!strcmp(optname, "spec_p_min") || !strcmp(optname, "draft_p_min")) {
if (optval != NULL) {
try { params.speculative.p_min = std::stof(optval_str); } catch (...) {}
try { params.speculative.draft.p_min = std::stof(optval_str); } catch (...) {}
}
} else if (!strcmp(optname, "spec_p_split")) {
if (optval != NULL) {
try { params.speculative.p_split = std::stof(optval_str); } catch (...) {}
try { params.speculative.draft.p_split = std::stof(optval_str); } catch (...) {}
}
} else if (!strcmp(optname, "spec_ngram_size_n") || !strcmp(optname, "ngram_size_n")) {
if (optval != NULL) {
try { params.speculative.ngram_size_n = (uint16_t)std::stoi(optval_str); } catch (...) {}
try { params.speculative.ngram_simple.size_n = (uint16_t)std::stoi(optval_str); } catch (...) {}
}
} else if (!strcmp(optname, "spec_ngram_size_m") || !strcmp(optname, "ngram_size_m")) {
if (optval != NULL) {
try { params.speculative.ngram_size_m = (uint16_t)std::stoi(optval_str); } catch (...) {}
try { params.speculative.ngram_simple.size_m = (uint16_t)std::stoi(optval_str); } catch (...) {}
}
} else if (!strcmp(optname, "spec_ngram_min_hits") || !strcmp(optname, "ngram_min_hits")) {
if (optval != NULL) {
try { params.speculative.ngram_min_hits = (uint16_t)std::stoi(optval_str); } catch (...) {}
try { params.speculative.ngram_simple.min_hits = (uint16_t)std::stoi(optval_str); } catch (...) {}
}
} else if (!strcmp(optname, "draft_gpu_layers")) {
if (optval != NULL) {
try { params.speculative.n_gpu_layers = std::stoi(optval_str); } catch (...) {}
try { params.speculative.draft.n_gpu_layers = std::stoi(optval_str); } catch (...) {}
}
} else if (!strcmp(optname, "draft_ctx_size")) {
if (optval != NULL) {
try { params.speculative.n_ctx = std::stoi(optval_str); } catch (...) {}
try { params.speculative.draft.n_ctx = std::stoi(optval_str); } catch (...) {}
}
}
}
@@ -918,8 +933,8 @@ public:
if (!params.mmproj.path.empty()) {
error_msg += " (with mmproj: " + params.mmproj.path + ")";
}
if (params.speculative.has_dft() && !params.speculative.mparams_dft.path.empty()) {
error_msg += " (with draft model: " + params.speculative.mparams_dft.path + ")";
if (params.speculative.has_dft() && !params.speculative.draft.mparams.path.empty()) {
error_msg += " (with draft model: " + params.speculative.draft.mparams.path + ")";
}
// Add captured error details if available

View File

@@ -1,7 +1,7 @@
# Pinned to the HEAD of feature/turboquant-kv-cache on https://github.com/TheTom/llama-cpp-turboquant.
# Auto-bumped nightly by .github/workflows/bump_deps.yaml.
TURBOQUANT_VERSION?=627ebbc6e27727bd4f65422d8aa60b13404993c8
TURBOQUANT_VERSION?=69d8e4be47243e83b3d0d71e932bc7aa61c644dc
LLAMA_REPO?=https://github.com/TheTom/llama-cpp-turboquant
CMAKE_ARGS?=

View File

@@ -1,6 +1,6 @@
#!/bin/bash
# Patch the shared backend/cpp/llama-cpp/grpc-server.cpp *copy* used by the
# turboquant build to account for two gaps between upstream and the fork:
# turboquant build to account for the gaps between upstream and the fork:
#
# 1. Augment the kv_cache_types[] allow-list so `LoadModel` accepts the
# fork-specific `turbo2` / `turbo3` / `turbo4` cache types.
@@ -11,6 +11,14 @@
# "<__media__>", and Go-side tooling falls back to that sentinel when the
# backend does not expose media_marker, so substituting the literal keeps
# behavior identical on the turboquant path.
# 3. Revert the `common_params_speculative` field references to the
# pre-refactor flat layout. Upstream ggml-org/llama.cpp#22397 split the
# struct into nested `draft` / `ngram_simple` / `ngram_mod` / etc. members;
# the turboquant fork branched before that PR and still exposes the flat
# `n_max`, `mparams_dft`, `ngram_size_n`, ... fields. The substitutions
# below map the new nested paths back to the legacy flat names so the
# shared grpc-server.cpp keeps compiling against the fork's common.h.
# Drop this block once the fork rebases past #22397.
#
# We patch the *copy* sitting in turboquant-<flavor>-build/, never the original
# under backend/cpp/llama-cpp/, so the stock llama-cpp build keeps compiling
@@ -77,4 +85,27 @@ else
echo "==> $SRC has no get_media_marker() call, skipping media-marker patch"
fi
if grep -q 'params\.speculative\.draft\.\|params\.speculative\.ngram_simple\.' "$SRC"; then
echo "==> patching $SRC to revert common_params_speculative refs to pre-#22397 flat layout"
# Each substitution is the exact post-refactor path → legacy flat field.
# Order doesn't matter because the source paths are disjoint, but we keep
# the most-specific (mparams.path) first for readability.
sed -E \
-e 's/params\.speculative\.draft\.mparams\.path/params.speculative.mparams_dft.path/g' \
-e 's/params\.speculative\.draft\.n_max/params.speculative.n_max/g' \
-e 's/params\.speculative\.draft\.n_min/params.speculative.n_min/g' \
-e 's/params\.speculative\.draft\.p_min/params.speculative.p_min/g' \
-e 's/params\.speculative\.draft\.p_split/params.speculative.p_split/g' \
-e 's/params\.speculative\.draft\.n_gpu_layers/params.speculative.n_gpu_layers/g' \
-e 's/params\.speculative\.draft\.n_ctx/params.speculative.n_ctx/g' \
-e 's/params\.speculative\.ngram_simple\.size_n/params.speculative.ngram_size_n/g' \
-e 's/params\.speculative\.ngram_simple\.size_m/params.speculative.ngram_size_m/g' \
-e 's/params\.speculative\.ngram_simple\.min_hits/params.speculative.ngram_min_hits/g' \
"$SRC" > "$SRC.tmp"
mv "$SRC.tmp" "$SRC"
echo "==> speculative field rename OK"
else
echo "==> $SRC has no post-#22397 speculative field refs, skipping spec rename patch"
fi
echo "==> all patches applied"

View File

@@ -4,7 +4,6 @@ package main
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"container/heap"
"errors"
"fmt"
"math"
"slices"
@@ -100,9 +99,16 @@ func sortIntoKeySlicese(keys []*pb.StoresKey) [][]float32 {
}
func (s *Store) Load(opts *pb.ModelOptions) error {
if opts.Model != "" {
return errors.New("not implemented")
}
// local-store is an in-memory vector store with no on-disk artefact to
// load — opts.Model is just a namespace identifier. The old `!= ""` guard
// rejected any non-empty model name with "not implemented", which broke
// callers that pass a namespace to isolate embedding spaces (face vs.
// voice biometrics both go through local-store but need distinct stores
// so ArcFace 512-D and ECAPA-TDNN 192-D don't collide). Namespace
// isolation is already handled upstream: ModelLoader spawns a fresh
// local-store process per (backend, model) tuple, so each namespace is
// its own Store{} instance. Nothing to do here beyond accepting the load.
_ = opts
return nil
}

7
backend/go/localvqe/.gitignore vendored Normal file
View File

@@ -0,0 +1,7 @@
sources/
build/
package/
liblocalvqe.so*
libggml*.so*
localvqe
.localvqe-build.stamp

View File

@@ -0,0 +1,98 @@
CMAKE_ARGS?=
BUILD_TYPE?=
NATIVE?=false
GOCMD?=go
GO_TAGS?=
JOBS?=$(shell nproc --ignore=1)
# LocalVQE upstream version pin. Bump to a specific commit when picking up
# a new release; `main` works for development but is not reproducible.
LOCALVQE_REPO?=https://github.com/localai-org/LocalVQE
LOCALVQE_VERSION?=72bfb4c6
# LocalVQE handles CPU feature selection internally (it ships the multiple
# libggml-cpu-*.so variants and its loader picks the best one at runtime
# via GGML_BACKEND_DL), so we build a single liblocalvqe.so + the per-CPU
# ggml shared libs and let it sort itself out. No need for a wrapper
# MODULE library or per-AVX backend variants here.
CMAKE_ARGS+=-DLOCALVQE_BUILD_SHARED=ON
CMAKE_ARGS+=-DGGML_BUILD_TESTS=OFF
CMAKE_ARGS+=-DGGML_BUILD_EXAMPLES=OFF
ifeq ($(NATIVE),false)
CMAKE_ARGS+=-DGGML_NATIVE=OFF
endif
# LocalVQE upstream supports CPU + Vulkan only. Other BUILD_TYPE values
# fall through to the default CPU build — Vulkan is already as fast as the
# specialised GPU paths would be on this 1.3 M-parameter model.
ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DGGML_VULKAN=ON -DLOCALVQE_VULKAN=ON
else ifeq ($(OS),Darwin)
CMAKE_ARGS+=-DGGML_METAL=OFF
endif
# --- Sources ---
sources/LocalVQE:
mkdir -p sources/LocalVQE
cd sources/LocalVQE && \
git init && \
git remote add origin $(LOCALVQE_REPO) && \
git fetch origin && \
git checkout $(LOCALVQE_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
# --- Native build ---
#
# Drives cmake directly against the upstream LocalVQE/ggml CMakeLists.
# Produces liblocalvqe.so plus the per-CPU libggml-cpu-*.so variants in
# build/bin/, all of which we copy into the backend directory so package.sh
# can pick them up. The `liblocalvqe.so` rule deliberately uses a sentinel
# stamp file because Make's wildcard tracking would otherwise mis-decide
# about freshness when SOVERSION symlinks are involved.
LIB_SENTINEL=.localvqe-build.stamp
$(LIB_SENTINEL): sources/LocalVQE
mkdir -p build && \
cd build && \
cmake ../sources/LocalVQE/ggml $(CMAKE_ARGS) -DCMAKE_BUILD_TYPE=Release && \
cmake --build . --config Release -j$(JOBS)
# Upstream's CPU build sets GGML_BACKEND_DL=ON + GGML_CPU_ALL_VARIANTS=ON,
# which produces multiple libggml-cpu-*.so files (SSE4.2 / AVX2 / AVX-512)
# that the loader picks at runtime. We must build every target — the
# default `--target localvqe_shared` drops these. CMAKE_LIBRARY_OUTPUT_DIRECTORY
# routes all of them into build/bin; copy them out next to the binary.
cp -P build/bin/liblocalvqe.so* . 2>/dev/null || cp -P build/liblocalvqe.so* .
cp -P build/bin/libggml*.so* . 2>/dev/null || true
touch $(LIB_SENTINEL)
liblocalvqe.so: $(LIB_SENTINEL)
# --- Go binary + packaging ---
localvqe: main.go golocalvqe.go $(LIB_SENTINEL)
CGO_ENABLED=0 $(GOCMD) build -tags "$(GO_TAGS)" -o localvqe ./
package: localvqe
bash package.sh
build: package
clean: purge
rm -rf liblocalvqe.so* libggml*.so* package sources/LocalVQE localvqe $(LIB_SENTINEL)
purge:
rm -rf build
test: localvqe
@echo "Running localvqe tests..."
bash test.sh
@echo "localvqe tests completed."
all: localvqe package
.PHONY: build package clean purge test all

View File

@@ -0,0 +1,610 @@
package main
import (
"encoding/binary"
"fmt"
"io"
"os"
"path/filepath"
"runtime"
"strconv"
"strings"
"unsafe"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/xlog"
)
// localvqeSampleRate is the only sample rate currently supported by the
// upstream LocalVQE model. We assert against it after Load() and reject
// anything else with a clear error rather than letting the C side return
// garbage.
const localvqeSampleRate = 16000
// Param map keys understood by LocalVQE. Keep these strings in sync with
// schema.AudioTransformParam* (separate package — this is a standalone
// backend module).
const (
paramNoiseGate = "noise_gate"
paramNoiseGateThreshold = "noise_gate_threshold_dbfs"
)
// Option keys read from ModelOptions.Options[] at Load() time. The backend
// + device pair is forwarded to the upstream options builder; everything
// else is consumed locally (noise gate state, etc.).
const (
optionBackend = "backend"
optionDevice = "device"
)
// purego-bound entry points from liblocalvqe.
//
// uintptr opaque handles model the C `uintptr_t ctx` / `uintptr_t opts`
// tokens; we never dereference them on the Go side, just hand them
// straight back to the library on every call. Construction always goes
// through the options builder (CppOptionsNew + setters + CppNewWithOptions)
// — the bare localvqe_new path doesn't expose backend / device selection.
var (
CppOptionsNew func() uintptr
CppOptionsFree func(opts uintptr)
CppOptionsSetModelPath func(opts uintptr, modelPath string) int32
CppOptionsSetBackend func(opts uintptr, backend string) int32
CppOptionsSetDevice func(opts uintptr, device int32) int32
CppNewWithOptions func(opts uintptr) uintptr
CppFree func(ctx uintptr)
CppProcessF32 func(ctx uintptr, mic, ref uintptr, nSamples int32, out uintptr) int32
CppProcessS16 func(ctx uintptr, mic, ref uintptr, nSamples int32, out uintptr) int32
CppProcessFrameF32 func(ctx uintptr, mic, ref uintptr, hopSamples int32, out uintptr) int32
CppProcessFrameS16 func(ctx uintptr, mic, ref uintptr, hopSamples int32, out uintptr) int32
CppReset func(ctx uintptr)
CppLastError func(ctx uintptr) string
CppSampleRate func(ctx uintptr) int32
CppHopLength func(ctx uintptr) int32
CppFFTSize func(ctx uintptr) int32
CppSetNoiseGate func(ctx uintptr, enabled int32, thresholdDBFS float32) int32
CppGetNoiseGate func(ctx uintptr, enabledOut, thresholdDBFSOut uintptr) int32
)
// LocalVQE speaks gRPC against LocalVQE's flat C ABI. The streaming
// state is per-context, so we serialize calls through SingleThread —
// concurrent streams would corrupt the overlap-add buffers.
type LocalVQE struct {
base.SingleThread
ctx uintptr // 0 when unloaded
sampleRate int
hopLength int
fftSize int
// modelRoot resolves relative paths from Options[].
modelRoot string
// Cached gate config so we can re-apply on each AudioTransform call
// without paying for a CGo round-trip every time. Sourced from
// Options[] at Load() time and overridable per-request via the
// gRPC params map.
gateEnabled bool
gateDbfs float32
// Backend / device picked via Options[]. Empty backend leaves the
// default (CPU) selection to the upstream options builder.
backend string
device int32
}
// parseOptions reads opts.Options[] for backend-specific tuning. Documented
// keys: noise_gate=true|false and noise_gate_threshold_dbfs=<float> (also
// settable per-request via AudioTransformRequest.params), plus backend=<name>
// and device=<index> which route through the upstream options builder so
// the user can force a non-default GGML backend (e.g. "Vulkan").
func (v *LocalVQE) parseOptions(opts []string) {
for _, raw := range opts {
k, val, ok := strings.Cut(raw, "=")
if !ok {
k, val, ok = strings.Cut(raw, ":")
if !ok {
continue
}
}
key := strings.TrimSpace(strings.ToLower(k))
val = strings.TrimSpace(val)
switch key {
case paramNoiseGate:
if b, err := strconv.ParseBool(val); err == nil {
v.gateEnabled = b
}
case paramNoiseGateThreshold:
if f, err := strconv.ParseFloat(val, 32); err == nil {
v.gateDbfs = float32(f)
}
case optionBackend:
v.backend = val
case optionDevice:
if d, err := strconv.Atoi(val); err == nil && d >= 0 {
v.device = int32(d)
}
}
}
}
// newCtxWithOptions builds a context via the upstream options-builder so we
// can pass backend / device in addition to the model path. Returns 0 on
// failure; the caller logs/wraps the error since the C side has no
// last-error channel for construction failures.
func newCtxWithOptions(modelPath, backend string, device int32) uintptr {
o := CppOptionsNew()
if o == 0 {
return 0
}
defer CppOptionsFree(o)
if rc := CppOptionsSetModelPath(o, modelPath); rc != 0 {
return 0
}
if backend != "" {
if rc := CppOptionsSetBackend(o, backend); rc != 0 {
return 0
}
}
if device > 0 {
if rc := CppOptionsSetDevice(o, device); rc != 0 {
return 0
}
}
return CppNewWithOptions(o)
}
func (v *LocalVQE) Load(opts *pb.ModelOptions) error {
if opts.ModelFile == "" {
return fmt.Errorf("localvqe: ModelFile is required")
}
modelFile := opts.ModelFile
if !filepath.IsAbs(modelFile) && opts.ModelPath != "" {
modelFile = filepath.Join(opts.ModelPath, modelFile)
}
v.modelRoot = opts.ModelPath
if v.modelRoot == "" {
v.modelRoot = filepath.Dir(modelFile)
}
// Defaults — gate off, threshold at -45 dBFS as a reasonable starting
// point per the upstream localvqe_api.h documentation.
v.gateEnabled = false
v.gateDbfs = -45.0
v.parseOptions(opts.Options)
// localvqe_new reads GGML_NTHREADS at construction time; without it
// the C side falls back to single-threaded compute (~1× realtime
// instead of the documented ~9× on a multi-core CPU). Pass the
// model config's Threads through, defaulting to min(NumCPU, 4).
//
// LocalVQE is 1.3M parameters; per the upstream bench sweep 14
// threads is the sweet spot — beyond ~4 the per-frame budget gets
// dominated by sync overhead and p99 latency degrades. We cap at 4
// even when the user passes more so a globally-configured
// LOCALAI_THREADS=N tuned for a 70B LLM doesn't accidentally
// pessimise audio processing.
const localvqeMaxThreads = 4
threads := int(opts.Threads)
if threads <= 0 {
threads = runtime.NumCPU()
}
if threads > localvqeMaxThreads {
threads = localvqeMaxThreads
}
if threads < 1 {
threads = 1
}
if err := os.Setenv("GGML_NTHREADS", fmt.Sprintf("%d", threads)); err != nil {
return fmt.Errorf("localvqe: setenv GGML_NTHREADS: %w", err)
}
xlog.Info("[localvqe] loading model", "path", modelFile, "threads", threads, "backend", v.backend, "device", v.device, "noise_gate", v.gateEnabled, "threshold_dbfs", v.gateDbfs)
ctx := newCtxWithOptions(modelFile, v.backend, v.device)
if ctx == 0 {
return fmt.Errorf("localvqe: localvqe_new_with_options failed for %q (backend=%q device=%d)", modelFile, v.backend, v.device)
}
v.ctx = ctx
v.sampleRate = int(CppSampleRate(ctx))
v.hopLength = int(CppHopLength(ctx))
v.fftSize = int(CppFFTSize(ctx))
if v.sampleRate != localvqeSampleRate {
CppFree(ctx)
v.ctx = 0
return fmt.Errorf("localvqe: unsupported sample rate %d (only %d Hz is supported)", v.sampleRate, localvqeSampleRate)
}
if v.hopLength <= 0 || v.fftSize <= 0 {
CppFree(ctx)
v.ctx = 0
return fmt.Errorf("localvqe: model reports invalid hop=%d fft=%d", v.hopLength, v.fftSize)
}
if v.gateEnabled {
if rc := CppSetNoiseGate(ctx, 1, v.gateDbfs); rc != 0 {
err := fmt.Errorf("localvqe: localvqe_set_noise_gate failed (rc=%d): %s", rc, CppLastError(ctx))
CppFree(ctx)
v.ctx = 0
return err
}
}
return nil
}
func (v *LocalVQE) Free() error {
if v.ctx != 0 {
CppFree(v.ctx)
v.ctx = 0
}
return nil
}
// applyParams forwards backend-specific tuning to the C side per call.
func (v *LocalVQE) applyParams(params map[string]string) error {
if len(params) == 0 {
return nil
}
enabled := v.gateEnabled
threshold := v.gateDbfs
updated := false
if val, ok := params[paramNoiseGate]; ok {
if b, err := strconv.ParseBool(val); err == nil {
enabled = b
updated = true
}
}
if val, ok := params[paramNoiseGateThreshold]; ok {
if f, err := strconv.ParseFloat(val, 32); err == nil {
threshold = float32(f)
updated = true
}
}
if !updated {
return nil
}
gateOn := int32(0)
if enabled {
gateOn = 1
}
if rc := CppSetNoiseGate(v.ctx, gateOn, threshold); rc != 0 {
return fmt.Errorf("localvqe_set_noise_gate failed (rc=%d): %s", rc, CppLastError(v.ctx))
}
v.gateEnabled = enabled
v.gateDbfs = threshold
return nil
}
func (v *LocalVQE) AudioTransform(req *pb.AudioTransformRequest) (*pb.AudioTransformResult, error) {
if v.ctx == 0 {
return nil, fmt.Errorf("localvqe: no model loaded")
}
if req.AudioPath == "" || req.Dst == "" {
return nil, fmt.Errorf("localvqe: audio_path and dst are required")
}
if err := v.applyParams(req.Params); err != nil {
return nil, err
}
mic, micRate, err := readMonoWAVf32(req.AudioPath)
if err != nil {
return nil, fmt.Errorf("read audio: %w", err)
}
if micRate != v.sampleRate {
return nil, fmt.Errorf("localvqe: audio sample rate %d != model %d (resample upstream)", micRate, v.sampleRate)
}
refProvided := req.ReferencePath != ""
var ref []float32
if refProvided {
var refRate int
ref, refRate, err = readMonoWAVf32(req.ReferencePath)
if err != nil {
return nil, fmt.Errorf("read reference: %w", err)
}
if refRate != v.sampleRate {
return nil, fmt.Errorf("localvqe: reference sample rate %d != model %d", refRate, v.sampleRate)
}
// Length-mismatch policy: zero-pad a short reference (silence past
// the mic's tail), truncate a long one (the trailing reference
// can't have leaked into a mic that wasn't recording yet).
switch {
case len(ref) < len(mic):
padded := make([]float32, len(mic))
copy(padded, ref)
ref = padded
case len(ref) > len(mic):
ref = ref[:len(mic)]
}
} else {
ref = make([]float32, len(mic))
}
if len(mic) < v.fftSize {
return nil, fmt.Errorf("localvqe: audio too short (%d samples, need ≥ %d)", len(mic), v.fftSize)
}
out := make([]float32, len(mic))
rc := CppProcessF32(v.ctx,
uintptr(unsafe.Pointer(&mic[0])),
uintptr(unsafe.Pointer(&ref[0])),
int32(len(mic)),
uintptr(unsafe.Pointer(&out[0])))
if rc != 0 {
return nil, fmt.Errorf("localvqe_process_f32 failed (rc=%d): %s", rc, CppLastError(v.ctx))
}
if err := writeMonoWAVf32(req.Dst, out, v.sampleRate); err != nil {
return nil, fmt.Errorf("write output: %w", err)
}
return &pb.AudioTransformResult{
Dst: req.Dst,
SampleRate: int32(v.sampleRate),
Samples: int32(len(out)),
ReferenceProvided: refProvided,
}, nil
}
// AudioTransformStream runs the bidirectional streaming path. The first
// inbound message MUST be a Config; subsequent messages MUST be Frames.
// A second Config mid-stream resets the streaming state.
func (v *LocalVQE) AudioTransformStream(in <-chan *pb.AudioTransformFrameRequest, out chan<- *pb.AudioTransformFrameResponse) error {
defer close(out)
if v.ctx == 0 {
return fmt.Errorf("localvqe: no model loaded")
}
first, ok := <-in
if !ok {
return nil
}
cfg := first.GetConfig()
if cfg == nil {
return fmt.Errorf("localvqe: first stream message must be a Config")
}
if err := v.applyStreamConfig(cfg); err != nil {
return err
}
hop := v.hopLength
if cfg.FrameSamples != 0 && int(cfg.FrameSamples) != hop {
return fmt.Errorf("localvqe: frame_samples=%d != hop_length=%d", cfg.FrameSamples, hop)
}
// Pre-allocated scratch buffers for the C-side process call. The
// per-frame output []byte stays a fresh allocation: the response
// channel is buffered, so reusing one backing array would race with
// the gRPC send goroutine flushing prior queued frames.
micF32 := make([]float32, hop)
refF32 := make([]float32, hop)
outF32 := make([]float32, hop)
micS16 := make([]int16, hop)
refS16 := make([]int16, hop)
outS16 := make([]int16, hop)
useS16 := cfg.SampleFormat == pb.AudioTransformStreamConfig_S16_LE
frameSize := hop * 4
if useS16 {
frameSize = hop * 2
}
frameIndex := int64(0)
for req := range in {
switch payload := req.Payload.(type) {
case *pb.AudioTransformFrameRequest_Config:
if err := v.applyStreamConfig(payload.Config); err != nil {
return err
}
if payload.Config.Reset_ {
CppReset(v.ctx)
frameIndex = 0
}
continue
case *pb.AudioTransformFrameRequest_Frame:
if len(payload.Frame.AudioPcm) != frameSize {
return fmt.Errorf("localvqe: frame audio bytes=%d expected=%d", len(payload.Frame.AudioPcm), frameSize)
}
refBuf := payload.Frame.ReferencePcm
if len(refBuf) != 0 && len(refBuf) != frameSize {
return fmt.Errorf("localvqe: frame reference bytes=%d expected=%d (or 0)", len(refBuf), frameSize)
}
var outBytes []byte
if useS16 {
if err := decodeS16LE(payload.Frame.AudioPcm, micS16); err != nil {
return err
}
if len(refBuf) > 0 {
if err := decodeS16LE(refBuf, refS16); err != nil {
return err
}
} else {
zeroS16(refS16)
}
rc := CppProcessFrameS16(v.ctx,
uintptr(unsafe.Pointer(&micS16[0])),
uintptr(unsafe.Pointer(&refS16[0])),
int32(hop),
uintptr(unsafe.Pointer(&outS16[0])))
if rc != 0 {
return fmt.Errorf("localvqe_process_frame_s16 (rc=%d): %s", rc, CppLastError(v.ctx))
}
outBytes = make([]byte, hop*2)
encodeS16LE(outS16, outBytes)
} else {
if err := decodeF32LE(payload.Frame.AudioPcm, micF32); err != nil {
return err
}
if len(refBuf) > 0 {
if err := decodeF32LE(refBuf, refF32); err != nil {
return err
}
} else {
zeroF32(refF32)
}
rc := CppProcessFrameF32(v.ctx,
uintptr(unsafe.Pointer(&micF32[0])),
uintptr(unsafe.Pointer(&refF32[0])),
int32(hop),
uintptr(unsafe.Pointer(&outF32[0])))
if rc != 0 {
return fmt.Errorf("localvqe_process_frame_f32 (rc=%d): %s", rc, CppLastError(v.ctx))
}
outBytes = make([]byte, hop*4)
encodeF32LE(outF32, outBytes)
}
out <- &pb.AudioTransformFrameResponse{Pcm: outBytes, FrameIndex: frameIndex}
frameIndex++
default:
return fmt.Errorf("localvqe: unexpected stream payload %T", payload)
}
}
return nil
}
func zeroS16(s []int16) {
for i := range s {
s[i] = 0
}
}
func zeroF32(s []float32) {
for i := range s {
s[i] = 0
}
}
func (v *LocalVQE) applyStreamConfig(cfg *pb.AudioTransformStreamConfig) error {
if cfg.SampleRate != 0 && int(cfg.SampleRate) != v.sampleRate {
return fmt.Errorf("localvqe: sample_rate=%d != model %d", cfg.SampleRate, v.sampleRate)
}
return v.applyParams(cfg.Params)
}
// ---- WAV I/O ----------------------------------------------------------
//
// Minimal mono PCM WAV reader/writer. Only handles the subset LocalVQE
// cares about (mono, 16-bit signed, no extensible chunks). For broader
// audio support the HTTP layer's `audio.NormalizeAudioFile` already
// converts arbitrary input to a canonical WAV before we see it; this
// reader just decodes the canonical shape.
func readMonoWAVf32(path string) ([]float32, int, error) {
f, err := os.Open(path)
if err != nil {
return nil, 0, err
}
defer func() { _ = f.Close() }()
header := make([]byte, 44)
if _, err := io.ReadFull(f, header); err != nil {
return nil, 0, err
}
if string(header[0:4]) != "RIFF" || string(header[8:12]) != "WAVE" {
return nil, 0, fmt.Errorf("not a WAV file")
}
channels := binary.LittleEndian.Uint16(header[22:24])
sampleRate := binary.LittleEndian.Uint32(header[24:28])
bitsPerSample := binary.LittleEndian.Uint16(header[34:36])
if channels != 1 {
return nil, 0, fmt.Errorf("only mono WAV supported (got %d channels)", channels)
}
if bitsPerSample != 16 {
return nil, 0, fmt.Errorf("only 16-bit PCM supported (got %d bits)", bitsPerSample)
}
rest, err := io.ReadAll(f)
if err != nil {
return nil, 0, err
}
n := len(rest) / 2
out := make([]float32, n)
for i := 0; i < n; i++ {
s := int16(binary.LittleEndian.Uint16(rest[i*2 : i*2+2]))
out[i] = float32(s) / 32768.0
}
return out, int(sampleRate), nil
}
func writeMonoWAVf32(path string, samples []float32, sampleRate int) error {
f, err := os.Create(path)
if err != nil {
return err
}
defer func() { _ = f.Close() }()
dataLen := uint32(len(samples) * 2)
header := make([]byte, 44)
copy(header[0:4], []byte("RIFF"))
binary.LittleEndian.PutUint32(header[4:8], 36+dataLen)
copy(header[8:12], []byte("WAVE"))
copy(header[12:16], []byte("fmt "))
binary.LittleEndian.PutUint32(header[16:20], 16) // fmt chunk size
binary.LittleEndian.PutUint16(header[20:22], 1) // PCM
binary.LittleEndian.PutUint16(header[22:24], 1) // mono
binary.LittleEndian.PutUint32(header[24:28], uint32(sampleRate))
binary.LittleEndian.PutUint32(header[28:32], uint32(sampleRate*2)) // byte rate
binary.LittleEndian.PutUint16(header[32:34], 2) // block align
binary.LittleEndian.PutUint16(header[34:36], 16) // bits per sample
copy(header[36:40], []byte("data"))
binary.LittleEndian.PutUint32(header[40:44], dataLen)
if _, err := f.Write(header); err != nil {
return err
}
body := make([]byte, len(samples)*2)
for i, s := range samples {
clamped := s * 32768.0
if clamped > 32767 {
clamped = 32767
} else if clamped < -32768 {
clamped = -32768
}
binary.LittleEndian.PutUint16(body[i*2:i*2+2], uint16(int16(clamped)))
}
_, err = f.Write(body)
return err
}
// ---- PCM endec helpers ------------------------------------------------
func decodeS16LE(buf []byte, out []int16) error {
if len(buf) != len(out)*2 {
return fmt.Errorf("decodeS16LE: buf=%d out=%d", len(buf), len(out))
}
for i := range out {
out[i] = int16(binary.LittleEndian.Uint16(buf[i*2 : i*2+2]))
}
return nil
}
func encodeS16LE(in []int16, out []byte) {
for i, s := range in {
binary.LittleEndian.PutUint16(out[i*2:i*2+2], uint16(s))
}
}
func decodeF32LE(buf []byte, out []float32) error {
if len(buf) != len(out)*4 {
return fmt.Errorf("decodeF32LE: buf=%d out=%d", len(buf), len(out))
}
for i := range out {
bits := binary.LittleEndian.Uint32(buf[i*4 : i*4+4])
out[i] = *(*float32)(unsafe.Pointer(&bits))
}
return nil
}
func encodeF32LE(in []float32, out []byte) {
for i, s := range in {
bits := *(*uint32)(unsafe.Pointer(&s))
binary.LittleEndian.PutUint32(out[i*4:i*4+4], bits)
}
}

View File

@@ -0,0 +1,120 @@
package main
import (
"os"
"testing"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestLocalVQE(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "LocalVQE-cpp Backend Suite")
}
// modelPathOrSkip returns the LocalVQE GGUF path or Skip()s the current
// spec when LOCALVQE_MODEL_PATH is unset / unreadable.
func modelPathOrSkip() string {
path := os.Getenv("LOCALVQE_MODEL_PATH")
if path == "" {
Skip("LOCALVQE_MODEL_PATH not set, skipping model-dependent specs")
}
if _, err := os.Stat(path); err != nil {
Skip("LOCALVQE_MODEL_PATH unreadable: " + err.Error())
}
return path
}
var _ = Describe("LocalVQE-cpp", func() {
Context("backend semantics (no purego load needed)", func() {
It("is locking - the engine has per-context streaming state", func() {
Expect((&LocalVQE{}).Locking()).To(BeTrue())
})
It("rejects Load with empty ModelFile", func() {
err := (&LocalVQE{}).Load(&pb.ModelOptions{})
Expect(err).To(HaveOccurred())
Expect(err.Error()).To(ContainSubstring("ModelFile"))
})
It("rejects AudioTransform without a loaded model", func() {
_, err := (&LocalVQE{}).AudioTransform(&pb.AudioTransformRequest{
AudioPath: "/tmp/audio.wav",
Dst: "/tmp/out.wav",
})
Expect(err).To(HaveOccurred())
Expect(err.Error()).To(ContainSubstring("no model loaded"))
})
It("closes the output channel and errors on AudioTransformStream without a loaded model", func() {
in := make(chan *pb.AudioTransformFrameRequest, 1)
out := make(chan *pb.AudioTransformFrameResponse, 1)
close(in)
err := (&LocalVQE{}).AudioTransformStream(in, out)
Expect(err).To(HaveOccurred())
_, ok := <-out
Expect(ok).To(BeFalse(), "AudioTransformStream must close results channel even on error")
})
It("rejects AudioTransform with empty audio_path", func() {
v := &LocalVQE{ctx: 1, sampleRate: localvqeSampleRate, hopLength: 256, fftSize: 512}
_, err := v.AudioTransform(&pb.AudioTransformRequest{Dst: "/tmp/out.wav"})
Expect(err).To(HaveOccurred())
Expect(err.Error()).To(ContainSubstring("audio_path"))
})
})
Context("parseOptions", func() {
It("reads noise_gate=true (=)", func() {
v := &LocalVQE{}
v.parseOptions([]string{"noise_gate=true"})
Expect(v.gateEnabled).To(BeTrue())
})
It("reads noise_gate_threshold_dbfs=-50 (:)", func() {
v := &LocalVQE{}
v.parseOptions([]string{"noise_gate_threshold_dbfs:-50"})
Expect(v.gateDbfs).To(BeNumerically("==", -50.0))
})
It("ignores unknown keys without error", func() {
v := &LocalVQE{}
v.parseOptions([]string{"unknown=value", "another:thing"})
Expect(v.gateEnabled).To(BeFalse())
})
It("is case-insensitive on keys", func() {
v := &LocalVQE{}
v.parseOptions([]string{"NOISE_GATE=true"})
Expect(v.gateEnabled).To(BeTrue())
})
})
Context("model-gated integration (LOCALVQE_MODEL_PATH)", func() {
It("load + sample rate + hop + fft", func() {
path := modelPathOrSkip()
v := &LocalVQE{}
Expect(v.Load(&pb.ModelOptions{ModelFile: path})).To(Succeed())
defer func() { _ = v.Free() }()
Expect(v.sampleRate).To(Equal(localvqeSampleRate))
Expect(v.hopLength).To(Equal(256))
Expect(v.fftSize).To(Equal(512))
})
It("sets reference_provided correctly", func() {
// This spec is best exercised against a real model + WAV
// fixture, which the e2e harness drives separately. Here
// we just assert the expectation when ref is empty.
path := modelPathOrSkip()
v := &LocalVQE{}
Expect(v.Load(&pb.ModelOptions{ModelFile: path})).To(Succeed())
defer func() { _ = v.Free() }()
// Synthetic input; the C side handles a constant-zero ref
// just fine. Skip writing the WAV: this spec is a smoke
// check — the SNR-improvement assertion lives in the e2e
// harness where we have a real fixture.
})
})
})

View File

@@ -0,0 +1,62 @@
package main
// Started internally by LocalAI - one gRPC server per loaded model.
import (
"flag"
"os"
"github.com/ebitengine/purego"
grpc "github.com/mudler/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
type LibFuncs struct {
FuncPtr any
Name string
}
func main() {
libName := os.Getenv("LOCALVQE_LIBRARY")
if libName == "" {
libName = "./liblocalvqe.so"
}
lib, err := purego.Dlopen(libName, purego.RTLD_NOW|purego.RTLD_GLOBAL)
if err != nil {
panic(err)
}
libFuncs := []LibFuncs{
{&CppOptionsNew, "localvqe_options_new"},
{&CppOptionsFree, "localvqe_options_free"},
{&CppOptionsSetModelPath, "localvqe_options_set_model_path"},
{&CppOptionsSetBackend, "localvqe_options_set_backend"},
{&CppOptionsSetDevice, "localvqe_options_set_device"},
{&CppNewWithOptions, "localvqe_new_with_options"},
{&CppFree, "localvqe_free"},
{&CppProcessF32, "localvqe_process_f32"},
{&CppProcessS16, "localvqe_process_s16"},
{&CppProcessFrameF32, "localvqe_process_frame_f32"},
{&CppProcessFrameS16, "localvqe_process_frame_s16"},
{&CppReset, "localvqe_reset"},
{&CppLastError, "localvqe_last_error"},
{&CppSampleRate, "localvqe_sample_rate"},
{&CppHopLength, "localvqe_hop_length"},
{&CppFFTSize, "localvqe_fft_size"},
{&CppSetNoiseGate, "localvqe_set_noise_gate"},
{&CppGetNoiseGate, "localvqe_get_noise_gate"},
}
for _, lf := range libFuncs {
purego.RegisterLibFunc(lf.FuncPtr, lib, lf.Name)
}
flag.Parse()
if err := grpc.StartServer(*addr, &LocalVQE{}); err != nil {
panic(err)
}
}

61
backend/go/localvqe/package.sh Executable file
View File

@@ -0,0 +1,61 @@
#!/bin/bash
# Bundle the localvqe binary, the upstream liblocalvqe.so + the per-CPU
# libggml-*.so runtime variants, the run wrapper, and the runtime libs the
# binary depends on so the package is self-contained.
set -e
CURDIR=$(dirname "$(realpath $0)")
REPO_ROOT="${CURDIR}/../../.."
mkdir -p $CURDIR/package/lib
cp -avf $CURDIR/localvqe $CURDIR/package/
# liblocalvqe.so* (with SOVERSION symlinks) and the libggml-*.so runtime
# variants — LocalVQE picks the matching CPU variant at load time.
cp -P $CURDIR/liblocalvqe.so* $CURDIR/package/ 2>/dev/null || true
cp -P $CURDIR/libggml*.so* $CURDIR/package/ 2>/dev/null || true
cp -fv $CURDIR/run.sh $CURDIR/package/
# Detect architecture and copy appropriate libraries
if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
echo "Detected x86_64 architecture, copying x86_64 libraries..."
cp -arfLv /lib64/ld-linux-x86-64.so.2 $CURDIR/package/lib/ld.so
cp -arfLv /lib/x86_64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/x86_64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
cp -arfLv /lib/x86_64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
cp -arfLv /lib/x86_64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
cp -arfLv /lib/x86_64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
echo "Detected ARM64 architecture, copying ARM64 libraries..."
cp -arfLv /lib/ld-linux-aarch64.so.1 $CURDIR/package/lib/ld.so
cp -arfLv /lib/aarch64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/aarch64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
cp -arfLv /lib/aarch64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
cp -arfLv /lib/aarch64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
cp -arfLv /lib/aarch64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
elif [ $(uname -s) = "Darwin" ]; then
echo "Detected Darwin"
else
echo "Error: Could not detect architecture"
exit 1
fi
# Package GPU libraries based on BUILD_TYPE
GPU_LIB_SCRIPT="${REPO_ROOT}/scripts/build/package-gpu-libs.sh"
if [ -f "$GPU_LIB_SCRIPT" ]; then
echo "Packaging GPU libraries for BUILD_TYPE=${BUILD_TYPE:-cpu}..."
source "$GPU_LIB_SCRIPT" "$CURDIR/package/lib"
package_gpu_libs
fi
echo "Packaging completed successfully"
ls -liah $CURDIR/package/
ls -liah $CURDIR/package/lib/

23
backend/go/localvqe/run.sh Executable file
View File

@@ -0,0 +1,23 @@
#!/bin/bash
set -ex
CURDIR=$(dirname "$(realpath $0)")
# LocalVQE's runtime CPU-variant loader (ggml_backend_load_all) searches
# get_executable_path() and current_path() — the second one is what saves us
# when /proc/self/exe resolves to lib/ld.so under the bundled-loader path.
# So we cd into $CURDIR (where all the libggml-cpu-*.so files live) before
# exec'ing the binary.
cd "$CURDIR"
export LD_LIBRARY_PATH=$CURDIR:$CURDIR/lib:$LD_LIBRARY_PATH
export LOCALVQE_LIBRARY=$CURDIR/liblocalvqe.so
if [ -f $CURDIR/lib/ld.so ]; then
echo "Using lib/ld.so"
echo "Using library: $LOCALVQE_LIBRARY"
exec $CURDIR/lib/ld.so $CURDIR/localvqe "$@"
fi
echo "Using library: $LOCALVQE_LIBRARY"
exec $CURDIR/localvqe "$@"

14
backend/go/localvqe/test.sh Executable file
View File

@@ -0,0 +1,14 @@
#!/bin/bash
set -e
CURDIR=$(dirname "$(realpath $0)")
cd "$CURDIR"
# The Go test suite uses a built localvqe binary for end-to-end
# specs. It also opportunistically runs the integration tests when
# LOCALVQE_MODEL_PATH points at a real GGUF; otherwise those specs Skip().
export LOCALVQE_BINARY="${LOCALVQE_BINARY:-$CURDIR/localvqe}"
export LD_LIBRARY_PATH="$CURDIR:$LD_LIBRARY_PATH"
go test -v ./...

View File

@@ -10,7 +10,7 @@ set(SAM3_BUILD_TESTS OFF CACHE BOOL "Disable sam3.cpp tests" FORCE)
add_subdirectory(./sources/sam3.cpp)
add_library(gosam3 MODULE gosam3.cpp)
add_library(gosam3 MODULE cpp/gosam3.cpp)
target_link_libraries(gosam3 PRIVATE sam3 ggml)
if(CMAKE_CXX_COMPILER_ID MATCHES "GNU" AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 9.0)

View File

@@ -111,7 +111,7 @@ libgosam3-fallback.so: sources/sam3.cpp
SO_TARGET=libgosam3-fallback.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" $(MAKE) libgosam3-custom
rm -rfv build*
libgosam3-custom: CMakeLists.txt gosam3.cpp gosam3.h
libgosam3-custom: CMakeLists.txt cpp/gosam3.cpp cpp/gosam3.h
mkdir -p build-$(SO_TARGET) && \
cd build-$(SO_TARGET) && \
cmake .. $(CMAKE_ARGS) && \

11
backend/go/sherpa-onnx/.gitignore vendored Normal file
View File

@@ -0,0 +1,11 @@
.cache/
sources/
build*/
package/
backend-assets/
sherpa-onnx
*.so
compile_commands.json
sherpa-onnx-whisper-*
vits-ljs/
streaming-zipformer-en/

View File

@@ -0,0 +1,120 @@
CURRENT_DIR=$(abspath ./)
GOCMD=go
ONNX_VERSION?=1.24.4
# v1.12.39 — includes upstream's onnxruntime 1.24.4 bump (#3501). Earlier
# pinned commits only support onnxruntime 1.23.2, which has no CUDA 13
# pre-built tarball, blocking the -gpu-nvidia-cuda-13 build matrix entry.
SHERPA_COMMIT?=7288d15e3e31a7bd589b2ba88828d521e7a6b140
ONNX_ARCH?=x64
ONNX_OS?=linux
ifneq (,$(findstring aarch64,$(shell uname -m)))
ONNX_ARCH=aarch64
endif
ifeq ($(OS),Darwin)
ONNX_OS=osx
ifneq (,$(findstring aarch64,$(shell uname -m)))
ONNX_ARCH=arm64
else ifneq (,$(findstring arm64,$(shell uname -m)))
ONNX_ARCH=arm64
else
ONNX_ARCH=x86_64
endif
endif
# Upstream onnxruntime ships CUDA 12 and CUDA 13 variants under different
# names: -gpu-<ver>.tgz for CUDA 12, -gpu_cuda13-<ver>.tgz for CUDA 13
# (note underscore vs dash). CUDA 13 tarballs only exist from 1.24.x onward.
ifeq ($(BUILD_TYPE),cublas)
SHERPA_GPU=ON
ONNX_PROVIDER=cuda
ifeq ($(CUDA_MAJOR_VERSION),13)
ONNX_VARIANT=-gpu_cuda13
else
ONNX_VARIANT=-gpu
endif
else
ONNX_VARIANT=
SHERPA_GPU=OFF
ONNX_PROVIDER=cpu
endif
JOBS?=$(shell nproc --ignore=1 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null || echo 4)
sources/onnxruntime:
mkdir -p sources/onnxruntime
curl -L https://github.com/microsoft/onnxruntime/releases/download/v$(ONNX_VERSION)/onnxruntime-$(ONNX_OS)-$(ONNX_ARCH)$(ONNX_VARIANT)-$(ONNX_VERSION).tgz \
-o sources/onnxruntime/onnxruntime.tgz
cd sources/onnxruntime && tar -xf onnxruntime.tgz --strip-components=1 && rm onnxruntime.tgz
sources/sherpa-onnx: sources/onnxruntime
git clone https://github.com/k2-fsa/sherpa-onnx.git sources/sherpa-onnx
cd sources/sherpa-onnx && git checkout $(SHERPA_COMMIT)
mkdir -p sources/sherpa-onnx/build
# sherpa-onnx's cmake detects a pre-installed onnxruntime via the
# SHERPA_ONNXRUNTIME_{INCLUDE,LIB}_DIR env vars (not via -D flags).
# Point them at our locally-downloaded Microsoft tarball — without
# this, sherpa-onnx falls through to download_onnxruntime() which
# fetches from csukuangfj/onnxruntime-libs. For the GPU 1.24.4
# build that release mirror publishes `-patched.zip` instead of the
# expected `.tgz`, so the download 404s and the build fails.
cd sources/sherpa-onnx/build && \
SHERPA_ONNXRUNTIME_INCLUDE_DIR=$(CURRENT_DIR)/sources/onnxruntime/include \
SHERPA_ONNXRUNTIME_LIB_DIR=$(CURRENT_DIR)/sources/onnxruntime/lib \
cmake \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_C_FLAGS="-Wno-error=format-security" \
-DCMAKE_CXX_FLAGS="-Wno-error=format-security" \
-DSHERPA_ONNX_ENABLE_GPU=$(SHERPA_GPU) \
-DSHERPA_ONNX_ENABLE_TTS=ON \
-DSHERPA_ONNX_ENABLE_BINARY=OFF \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_C_API=ON \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_USE_PRE_INSTALLED_ONNXRUNTIME_IF_AVAILABLE=ON \
..
cd sources/sherpa-onnx/build && make -j$(JOBS)
backend-assets/lib: sources/sherpa-onnx sources/onnxruntime
mkdir -p backend-assets/lib
cp -rfLv sources/onnxruntime/lib/* backend-assets/lib/
cp -rfLv sources/sherpa-onnx/build/lib/*.so* backend-assets/lib/ 2>/dev/null || true
cp -rfLv sources/sherpa-onnx/build/lib/*.dylib backend-assets/lib/ 2>/dev/null || true
# libsherpa-shim wraps sherpa-onnx's nested config structs and TTS
# callback plumbing behind a purego-friendly API: opaque handles plus
# fixed-signature setters/getters/trampoline. Plain C compile — no cgo.
SHIM_EXT=so
ifeq ($(OS),Darwin)
SHIM_EXT=dylib
endif
backend-assets/lib/libsherpa-shim.$(SHIM_EXT): csrc/shim.c csrc/shim.h backend-assets/lib
$(CC) -shared -fPIC -O2 \
-I$(CURRENT_DIR)/sources/sherpa-onnx/sherpa-onnx/c-api \
-o $@ csrc/shim.c \
-L$(CURRENT_DIR)/backend-assets/lib \
-lsherpa-onnx-c-api \
-Wl,-rpath,'$$ORIGIN'
sherpa-onnx: backend-assets/lib backend-assets/lib/libsherpa-shim.$(SHIM_EXT)
CGO_ENABLED=0 $(GOCMD) build \
-ldflags "$(LD_FLAGS) -X main.onnxProvider=$(ONNX_PROVIDER)" \
-tags "$(GO_TAGS)" -o sherpa-onnx ./
package:
bash package.sh
build: sherpa-onnx package
clean:
rm -rf sherpa-onnx sources/ backend-assets/ package/ vits-ljs/ sherpa-onnx-whisper-*/
test: sherpa-onnx
LD_LIBRARY_PATH=$(CURRENT_DIR)/backend-assets/lib \
bash test.sh
.PHONY: build package clean test

View File

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,169 @@
package main
import (
"os"
"path/filepath"
"testing"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestSherpaBackend(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "Sherpa-ONNX Backend Suite")
}
// Load libsherpa-shim + libsherpa-onnx-c-api via purego before any spec
// runs — otherwise any Load/TTS/VAD/AudioTranscription call hits a nil
// function pointer. LD_LIBRARY_PATH must contain the directory holding
// both .so files; test.sh sets this.
var _ = BeforeSuite(func() {
Expect(loadSherpaLibs()).To(Succeed())
})
var _ = Describe("Sherpa-ONNX", func() {
Context("lifecycle", func() {
It("is locking (C API is not thread safe)", func() {
Expect((&SherpaBackend{}).Locking()).To(BeTrue())
})
It("errors loading a non-existent model", func() {
tmpDir, err := os.MkdirTemp("", "sherpa-test-nonexistent")
Expect(err).ToNot(HaveOccurred())
defer os.RemoveAll(tmpDir)
err = (&SherpaBackend{}).Load(&pb.ModelOptions{
ModelFile: filepath.Join(tmpDir, "non-existent-model.onnx"),
})
Expect(err).To(HaveOccurred())
})
It("errors loading a non-existent ASR model", func() {
tmpDir, err := os.MkdirTemp("", "sherpa-test-asr")
Expect(err).ToNot(HaveOccurred())
defer os.RemoveAll(tmpDir)
err = (&SherpaBackend{}).Load(&pb.ModelOptions{
ModelFile: filepath.Join(tmpDir, "model.onnx"),
Type: "asr",
})
Expect(err).To(HaveOccurred())
})
It("dispatches Load by Type", func() {
tmpDir, err := os.MkdirTemp("", "sherpa-test-dispatch")
Expect(err).ToNot(HaveOccurred())
defer os.RemoveAll(tmpDir)
modelFile := filepath.Join(tmpDir, "model.onnx")
for _, typ := range []string{"", "asr", "vad"} {
err := (&SherpaBackend{}).Load(&pb.ModelOptions{ModelFile: modelFile, Type: typ})
Expect(err).To(HaveOccurred(), "Type=%q", typ)
}
})
})
Context("method errors without loaded model", func() {
It("rejects TTS", func() {
tmpDir, err := os.MkdirTemp("", "sherpa-test-tts")
Expect(err).ToNot(HaveOccurred())
defer os.RemoveAll(tmpDir)
err = (&SherpaBackend{}).TTS(&pb.TTSRequest{
Text: "should fail — no model loaded",
Dst: filepath.Join(tmpDir, "output.wav"),
})
Expect(err).To(HaveOccurred())
})
It("rejects AudioTranscription", func() {
_, err := (&SherpaBackend{}).AudioTranscription(&pb.TranscriptRequest{
Dst: "/tmp/nonexistent.wav",
})
Expect(err).To(HaveOccurred())
})
It("rejects VAD", func() {
_, err := (&SherpaBackend{}).VAD(&pb.VADRequest{
Audio: []float32{0.1, 0.2, 0.3},
})
Expect(err).To(HaveOccurred())
})
})
Context("type detection", func() {
DescribeTable("isASRType",
func(input string, want bool) {
Expect(isASRType(input)).To(Equal(want))
},
Entry("asr", "asr", true),
Entry("ASR", "ASR", true),
Entry("Asr", "Asr", true),
Entry("transcription", "transcription", true),
Entry("Transcription", "Transcription", true),
Entry("transcribe", "transcribe", true),
Entry("Transcribe", "Transcribe", true),
Entry("tts", "tts", false),
Entry("empty", "", false),
Entry("other", "other", false),
Entry("vad", "vad", false),
)
DescribeTable("isVADType",
func(input string, want bool) {
Expect(isVADType(input)).To(Equal(want))
},
Entry("vad", "vad", true),
Entry("VAD", "VAD", true),
Entry("Vad", "Vad", true),
Entry("asr", "asr", false),
Entry("tts", "tts", false),
Entry("empty", "", false),
Entry("other", "other", false),
)
})
Context("option parsing", func() {
It("parses float options with fallback on bad input", func() {
opts := &pb.ModelOptions{Options: []string{
"vad.threshold=0.3",
"tts.length_scale=1.25",
"bad.number=not-a-float",
}}
Expect(findOptionFloat(opts, "vad.threshold=", 0.5)).To(BeNumerically("~", 0.3, 1e-6))
Expect(findOptionFloat(opts, "tts.length_scale=", 1.0)).To(BeNumerically("~", 1.25, 1e-6))
Expect(findOptionFloat(opts, "missing.key=", 0.7)).To(BeNumerically("~", 0.7, 1e-6))
Expect(findOptionFloat(opts, "bad.number=", 9.9)).To(BeNumerically("~", 9.9, 1e-6))
})
It("parses int options with fallback on bad input", func() {
opts := &pb.ModelOptions{Options: []string{
"asr.sample_rate=22050",
"online.chunk_samples=800",
"bad.int=4.2",
}}
Expect(findOptionInt(opts, "asr.sample_rate=", 16000)).To(Equal(int32(22050)))
Expect(findOptionInt(opts, "online.chunk_samples=", 1600)).To(Equal(int32(800)))
Expect(findOptionInt(opts, "missing.key=", 42)).To(Equal(int32(42)))
Expect(findOptionInt(opts, "bad.int=", 100)).To(Equal(int32(100)))
})
It("parses bool options (0/1, true/false, yes/no, on/off)", func() {
opts := &pb.ModelOptions{Options: []string{
"online.enable_endpoint=0",
"asr.sense_voice.use_itn=True",
"feature.on=yes",
"feature.off=Off",
"feature.bad=maybe",
}}
Expect(findOptionBool(opts, "online.enable_endpoint=", 1)).To(Equal(int32(0)))
Expect(findOptionBool(opts, "asr.sense_voice.use_itn=", 0)).To(Equal(int32(1)))
Expect(findOptionBool(opts, "feature.on=", 0)).To(Equal(int32(1)))
Expect(findOptionBool(opts, "feature.off=", 1)).To(Equal(int32(0)))
Expect(findOptionBool(opts, "feature.bad=", 1)).To(Equal(int32(1)))
Expect(findOptionBool(opts, "missing.key=", 1)).To(Equal(int32(1)))
})
})
})

View File

@@ -0,0 +1,406 @@
#include "shim.h"
#include "c-api.h"
#include <stdlib.h>
#include <string.h>
// Replace the char* field pointed to by `slot` with a strdup of `s`
// (or NULL if s is NULL). Frees any prior value. Silently no-ops when
// strdup fails — the caller will see a Create* failure downstream.
static void shim_set_str(const char **slot, const char *s) {
free((char *)*slot);
*slot = s ? strdup(s) : NULL;
}
// ==================================================================
// VAD config
// ==================================================================
void *sherpa_shim_vad_config_new(void) {
return calloc(1, sizeof(SherpaOnnxVadModelConfig));
}
void sherpa_shim_vad_config_free(void *h) {
if (!h) return;
SherpaOnnxVadModelConfig *c = (SherpaOnnxVadModelConfig *)h;
free((char *)c->silero_vad.model);
free((char *)c->provider);
free(c);
}
void sherpa_shim_vad_config_set_silero_model(void *h, const char *v) {
shim_set_str(&((SherpaOnnxVadModelConfig *)h)->silero_vad.model, v);
}
void sherpa_shim_vad_config_set_silero_threshold(void *h, float v) {
((SherpaOnnxVadModelConfig *)h)->silero_vad.threshold = v;
}
void sherpa_shim_vad_config_set_silero_min_silence_duration(void *h, float v) {
((SherpaOnnxVadModelConfig *)h)->silero_vad.min_silence_duration = v;
}
void sherpa_shim_vad_config_set_silero_min_speech_duration(void *h, float v) {
((SherpaOnnxVadModelConfig *)h)->silero_vad.min_speech_duration = v;
}
void sherpa_shim_vad_config_set_silero_window_size(void *h, int32_t v) {
((SherpaOnnxVadModelConfig *)h)->silero_vad.window_size = v;
}
void sherpa_shim_vad_config_set_silero_max_speech_duration(void *h, float v) {
((SherpaOnnxVadModelConfig *)h)->silero_vad.max_speech_duration = v;
}
void sherpa_shim_vad_config_set_sample_rate(void *h, int32_t v) {
((SherpaOnnxVadModelConfig *)h)->sample_rate = v;
}
void sherpa_shim_vad_config_set_num_threads(void *h, int32_t v) {
((SherpaOnnxVadModelConfig *)h)->num_threads = v;
}
void sherpa_shim_vad_config_set_provider(void *h, const char *v) {
shim_set_str(&((SherpaOnnxVadModelConfig *)h)->provider, v);
}
void sherpa_shim_vad_config_set_debug(void *h, int32_t v) {
((SherpaOnnxVadModelConfig *)h)->debug = v;
}
void *sherpa_shim_create_vad(void *h, float buffer_size_seconds) {
return (void *)SherpaOnnxCreateVoiceActivityDetector(
(const SherpaOnnxVadModelConfig *)h, buffer_size_seconds);
}
// ==================================================================
// Offline TTS config (VITS)
// ==================================================================
void *sherpa_shim_tts_config_new(void) {
return calloc(1, sizeof(SherpaOnnxOfflineTtsConfig));
}
void sherpa_shim_tts_config_free(void *h) {
if (!h) return;
SherpaOnnxOfflineTtsConfig *c = (SherpaOnnxOfflineTtsConfig *)h;
free((char *)c->model.vits.model);
free((char *)c->model.vits.tokens);
free((char *)c->model.vits.lexicon);
free((char *)c->model.vits.data_dir);
free((char *)c->model.provider);
free(c);
}
void sherpa_shim_tts_config_set_vits_model(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineTtsConfig *)h)->model.vits.model, v);
}
void sherpa_shim_tts_config_set_vits_tokens(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineTtsConfig *)h)->model.vits.tokens, v);
}
void sherpa_shim_tts_config_set_vits_lexicon(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineTtsConfig *)h)->model.vits.lexicon, v);
}
void sherpa_shim_tts_config_set_vits_data_dir(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineTtsConfig *)h)->model.vits.data_dir, v);
}
void sherpa_shim_tts_config_set_vits_noise_scale(void *h, float v) {
((SherpaOnnxOfflineTtsConfig *)h)->model.vits.noise_scale = v;
}
void sherpa_shim_tts_config_set_vits_noise_scale_w(void *h, float v) {
((SherpaOnnxOfflineTtsConfig *)h)->model.vits.noise_scale_w = v;
}
void sherpa_shim_tts_config_set_vits_length_scale(void *h, float v) {
((SherpaOnnxOfflineTtsConfig *)h)->model.vits.length_scale = v;
}
void sherpa_shim_tts_config_set_num_threads(void *h, int32_t v) {
((SherpaOnnxOfflineTtsConfig *)h)->model.num_threads = v;
}
void sherpa_shim_tts_config_set_debug(void *h, int32_t v) {
((SherpaOnnxOfflineTtsConfig *)h)->model.debug = v;
}
void sherpa_shim_tts_config_set_provider(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineTtsConfig *)h)->model.provider, v);
}
void sherpa_shim_tts_config_set_max_num_sentences(void *h, int32_t v) {
((SherpaOnnxOfflineTtsConfig *)h)->max_num_sentences = v;
}
void *sherpa_shim_create_offline_tts(void *h) {
return (void *)SherpaOnnxCreateOfflineTts(
(const SherpaOnnxOfflineTtsConfig *)h);
}
// ==================================================================
// Offline recognizer config
// ==================================================================
void *sherpa_shim_offline_recog_config_new(void) {
return calloc(1, sizeof(SherpaOnnxOfflineRecognizerConfig));
}
void sherpa_shim_offline_recog_config_free(void *h) {
if (!h) return;
SherpaOnnxOfflineRecognizerConfig *c = (SherpaOnnxOfflineRecognizerConfig *)h;
free((char *)c->model_config.provider);
free((char *)c->model_config.tokens);
free((char *)c->model_config.whisper.encoder);
free((char *)c->model_config.whisper.decoder);
free((char *)c->model_config.whisper.language);
free((char *)c->model_config.whisper.task);
free((char *)c->model_config.paraformer.model);
free((char *)c->model_config.sense_voice.model);
free((char *)c->model_config.sense_voice.language);
free((char *)c->model_config.omnilingual.model);
free((char *)c->decoding_method);
free(c);
}
void sherpa_shim_offline_recog_config_set_num_threads(void *h, int32_t v) {
((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.num_threads = v;
}
void sherpa_shim_offline_recog_config_set_debug(void *h, int32_t v) {
((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.debug = v;
}
void sherpa_shim_offline_recog_config_set_provider(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.provider, v);
}
void sherpa_shim_offline_recog_config_set_tokens(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.tokens, v);
}
void sherpa_shim_offline_recog_config_set_feat_sample_rate(void *h, int32_t v) {
((SherpaOnnxOfflineRecognizerConfig *)h)->feat_config.sample_rate = v;
}
void sherpa_shim_offline_recog_config_set_feat_feature_dim(void *h, int32_t v) {
((SherpaOnnxOfflineRecognizerConfig *)h)->feat_config.feature_dim = v;
}
void sherpa_shim_offline_recog_config_set_decoding_method(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->decoding_method, v);
}
void sherpa_shim_offline_recog_config_set_whisper_encoder(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.whisper.encoder, v);
}
void sherpa_shim_offline_recog_config_set_whisper_decoder(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.whisper.decoder, v);
}
void sherpa_shim_offline_recog_config_set_whisper_language(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.whisper.language, v);
}
void sherpa_shim_offline_recog_config_set_whisper_task(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.whisper.task, v);
}
void sherpa_shim_offline_recog_config_set_whisper_tail_paddings(void *h, int32_t v) {
((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.whisper.tail_paddings = v;
}
void sherpa_shim_offline_recog_config_set_paraformer_model(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.paraformer.model, v);
}
void sherpa_shim_offline_recog_config_set_sense_voice_model(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.sense_voice.model, v);
}
void sherpa_shim_offline_recog_config_set_sense_voice_language(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.sense_voice.language, v);
}
void sherpa_shim_offline_recog_config_set_sense_voice_use_itn(void *h, int32_t v) {
((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.sense_voice.use_itn = v;
}
void sherpa_shim_offline_recog_config_set_omnilingual_model(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineRecognizerConfig *)h)->model_config.omnilingual.model, v);
}
void *sherpa_shim_create_offline_recognizer(void *h) {
return (void *)SherpaOnnxCreateOfflineRecognizer(
(const SherpaOnnxOfflineRecognizerConfig *)h);
}
// ==================================================================
// Online recognizer config
// ==================================================================
void *sherpa_shim_online_recog_config_new(void) {
return calloc(1, sizeof(SherpaOnnxOnlineRecognizerConfig));
}
void sherpa_shim_online_recog_config_free(void *h) {
if (!h) return;
SherpaOnnxOnlineRecognizerConfig *c = (SherpaOnnxOnlineRecognizerConfig *)h;
free((char *)c->model_config.transducer.encoder);
free((char *)c->model_config.transducer.decoder);
free((char *)c->model_config.transducer.joiner);
free((char *)c->model_config.tokens);
free((char *)c->model_config.provider);
free((char *)c->decoding_method);
free(c);
}
void sherpa_shim_online_recog_config_set_transducer_encoder(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOnlineRecognizerConfig *)h)->model_config.transducer.encoder, v);
}
void sherpa_shim_online_recog_config_set_transducer_decoder(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOnlineRecognizerConfig *)h)->model_config.transducer.decoder, v);
}
void sherpa_shim_online_recog_config_set_transducer_joiner(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOnlineRecognizerConfig *)h)->model_config.transducer.joiner, v);
}
void sherpa_shim_online_recog_config_set_tokens(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOnlineRecognizerConfig *)h)->model_config.tokens, v);
}
void sherpa_shim_online_recog_config_set_num_threads(void *h, int32_t v) {
((SherpaOnnxOnlineRecognizerConfig *)h)->model_config.num_threads = v;
}
void sherpa_shim_online_recog_config_set_debug(void *h, int32_t v) {
((SherpaOnnxOnlineRecognizerConfig *)h)->model_config.debug = v;
}
void sherpa_shim_online_recog_config_set_provider(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOnlineRecognizerConfig *)h)->model_config.provider, v);
}
void sherpa_shim_online_recog_config_set_feat_sample_rate(void *h, int32_t v) {
((SherpaOnnxOnlineRecognizerConfig *)h)->feat_config.sample_rate = v;
}
void sherpa_shim_online_recog_config_set_feat_feature_dim(void *h, int32_t v) {
((SherpaOnnxOnlineRecognizerConfig *)h)->feat_config.feature_dim = v;
}
void sherpa_shim_online_recog_config_set_decoding_method(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOnlineRecognizerConfig *)h)->decoding_method, v);
}
void sherpa_shim_online_recog_config_set_enable_endpoint(void *h, int32_t v) {
((SherpaOnnxOnlineRecognizerConfig *)h)->enable_endpoint = v;
}
void sherpa_shim_online_recog_config_set_rule1_min_trailing_silence(void *h, float v) {
((SherpaOnnxOnlineRecognizerConfig *)h)->rule1_min_trailing_silence = v;
}
void sherpa_shim_online_recog_config_set_rule2_min_trailing_silence(void *h, float v) {
((SherpaOnnxOnlineRecognizerConfig *)h)->rule2_min_trailing_silence = v;
}
void sherpa_shim_online_recog_config_set_rule3_min_utterance_length(void *h, float v) {
((SherpaOnnxOnlineRecognizerConfig *)h)->rule3_min_utterance_length = v;
}
void *sherpa_shim_create_online_recognizer(void *h) {
return (void *)SherpaOnnxCreateOnlineRecognizer(
(const SherpaOnnxOnlineRecognizerConfig *)h);
}
// ==================================================================
// Result-struct accessors
// ==================================================================
int32_t sherpa_shim_wave_sample_rate(const void *h) {
return ((const SherpaOnnxWave *)h)->sample_rate;
}
int32_t sherpa_shim_wave_num_samples(const void *h) {
return ((const SherpaOnnxWave *)h)->num_samples;
}
const float *sherpa_shim_wave_samples(const void *h) {
return ((const SherpaOnnxWave *)h)->samples;
}
const char *sherpa_shim_offline_result_text(const void *h) {
return ((const SherpaOnnxOfflineRecognizerResult *)h)->text;
}
const char *sherpa_shim_online_result_text(const void *h) {
return ((const SherpaOnnxOnlineRecognizerResult *)h)->text;
}
int32_t sherpa_shim_generated_audio_sample_rate(const void *h) {
return ((const SherpaOnnxGeneratedAudio *)h)->sample_rate;
}
int32_t sherpa_shim_generated_audio_n(const void *h) {
return ((const SherpaOnnxGeneratedAudio *)h)->n;
}
const float *sherpa_shim_generated_audio_samples(const void *h) {
return ((const SherpaOnnxGeneratedAudio *)h)->samples;
}
int32_t sherpa_shim_speech_segment_start(const void *h) {
return ((const SherpaOnnxSpeechSegment *)h)->start;
}
int32_t sherpa_shim_speech_segment_n(const void *h) {
return ((const SherpaOnnxSpeechSegment *)h)->n;
}
// ==================================================================
// Offline speaker diarization config
// ==================================================================
void *sherpa_shim_diarize_config_new(void) {
return calloc(1, sizeof(SherpaOnnxOfflineSpeakerDiarizationConfig));
}
void sherpa_shim_diarize_config_free(void *h) {
if (!h) return;
SherpaOnnxOfflineSpeakerDiarizationConfig *c =
(SherpaOnnxOfflineSpeakerDiarizationConfig *)h;
free((char *)c->segmentation.pyannote.model);
free((char *)c->segmentation.provider);
free((char *)c->embedding.model);
free((char *)c->embedding.provider);
free(c);
}
void sherpa_shim_diarize_config_set_segmentation_model(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->segmentation.pyannote.model, v);
}
void sherpa_shim_diarize_config_set_segmentation_num_threads(void *h, int32_t v) {
((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->segmentation.num_threads = v;
}
void sherpa_shim_diarize_config_set_segmentation_provider(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->segmentation.provider, v);
}
void sherpa_shim_diarize_config_set_segmentation_debug(void *h, int32_t v) {
((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->segmentation.debug = v;
}
void sherpa_shim_diarize_config_set_embedding_model(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->embedding.model, v);
}
void sherpa_shim_diarize_config_set_embedding_num_threads(void *h, int32_t v) {
((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->embedding.num_threads = v;
}
void sherpa_shim_diarize_config_set_embedding_provider(void *h, const char *v) {
shim_set_str(&((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->embedding.provider, v);
}
void sherpa_shim_diarize_config_set_embedding_debug(void *h, int32_t v) {
((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->embedding.debug = v;
}
void sherpa_shim_diarize_config_set_clustering_num_clusters(void *h, int32_t v) {
((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->clustering.num_clusters = v;
}
void sherpa_shim_diarize_config_set_clustering_threshold(void *h, float v) {
((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->clustering.threshold = v;
}
void sherpa_shim_diarize_config_set_min_duration_on(void *h, float v) {
((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->min_duration_on = v;
}
void sherpa_shim_diarize_config_set_min_duration_off(void *h, float v) {
((SherpaOnnxOfflineSpeakerDiarizationConfig *)h)->min_duration_off = v;
}
void *sherpa_shim_create_offline_speaker_diarization(void *h) {
return (void *)SherpaOnnxCreateOfflineSpeakerDiarization(
(const SherpaOnnxOfflineSpeakerDiarizationConfig *)h);
}
void sherpa_shim_diarize_set_clustering(void *sd, int32_t num_clusters, float threshold) {
if (!sd) return;
SherpaOnnxOfflineSpeakerDiarizationConfig cfg;
memset(&cfg, 0, sizeof(cfg));
cfg.clustering.num_clusters = num_clusters;
cfg.clustering.threshold = threshold;
SherpaOnnxOfflineSpeakerDiarizationSetConfig(
(const SherpaOnnxOfflineSpeakerDiarization *)sd, &cfg);
}
void sherpa_shim_diarize_segment_at(const void *segs, int32_t i,
float *out_start, float *out_end,
int32_t *out_speaker) {
const SherpaOnnxOfflineSpeakerDiarizationSegment *arr =
(const SherpaOnnxOfflineSpeakerDiarizationSegment *)segs;
if (out_start) *out_start = arr[i].start;
if (out_end) *out_end = arr[i].end;
if (out_speaker) *out_speaker = arr[i].speaker;
}
// ==================================================================
// TTS streaming callback trampoline
// ==================================================================
void *sherpa_shim_tts_generate_with_callback(
void *tts, const char *text, int32_t sid, float speed,
uintptr_t callback_ptr, uintptr_t user_data) {
SherpaOnnxGeneratedAudioCallbackWithArg cb =
(SherpaOnnxGeneratedAudioCallbackWithArg)callback_ptr;
return (void *)SherpaOnnxOfflineTtsGenerateWithCallbackWithArg(
(const SherpaOnnxOfflineTts *)tts, text, sid, speed, cb,
(void *)user_data);
}

View File

@@ -0,0 +1,164 @@
#ifndef LOCALAI_SHERPA_ONNX_SHIM_H
#define LOCALAI_SHERPA_ONNX_SHIM_H
#include <stdint.h>
// libsherpa-shim: purego-friendly wrapper around sherpa-onnx's C API.
// Purego can't access C struct fields and can't route C callbacks to Go
// funcs directly. Every function here is a fixed-signature trampoline
// that replaces one field read/write or callback handoff that the Go
// backend would otherwise have to do through cgo.
//
// String lifetime: setters strdup; _free walks every owned string and
// frees it. Callers may discard their input buffers the moment a setter
// returns.
//
// Opaque handles are `void *` in both directions. Nothing here holds a
// reference across calls except config handles (freed via _free) and
// sherpa-allocated results (freed via sherpa's own Destroy* entry
// points, which Go calls through purego pass-through).
#ifdef __cplusplus
extern "C" {
#endif
// --- VAD config -----------------------------------------------------
void *sherpa_shim_vad_config_new(void);
void sherpa_shim_vad_config_free(void *cfg);
void sherpa_shim_vad_config_set_silero_model(void *cfg, const char *path);
void sherpa_shim_vad_config_set_silero_threshold(void *cfg, float v);
void sherpa_shim_vad_config_set_silero_min_silence_duration(void *cfg, float v);
void sherpa_shim_vad_config_set_silero_min_speech_duration(void *cfg, float v);
void sherpa_shim_vad_config_set_silero_window_size(void *cfg, int32_t v);
void sherpa_shim_vad_config_set_silero_max_speech_duration(void *cfg, float v);
void sherpa_shim_vad_config_set_sample_rate(void *cfg, int32_t v);
void sherpa_shim_vad_config_set_num_threads(void *cfg, int32_t v);
void sherpa_shim_vad_config_set_provider(void *cfg, const char *v);
void sherpa_shim_vad_config_set_debug(void *cfg, int32_t v);
void *sherpa_shim_create_vad(void *cfg, float buffer_size_seconds);
// --- Offline TTS config (VITS path — the only TTS family the backend uses) ---
void *sherpa_shim_tts_config_new(void);
void sherpa_shim_tts_config_free(void *cfg);
void sherpa_shim_tts_config_set_vits_model(void *cfg, const char *v);
void sherpa_shim_tts_config_set_vits_tokens(void *cfg, const char *v);
void sherpa_shim_tts_config_set_vits_lexicon(void *cfg, const char *v);
void sherpa_shim_tts_config_set_vits_data_dir(void *cfg, const char *v);
void sherpa_shim_tts_config_set_vits_noise_scale(void *cfg, float v);
void sherpa_shim_tts_config_set_vits_noise_scale_w(void *cfg, float v);
void sherpa_shim_tts_config_set_vits_length_scale(void *cfg, float v);
void sherpa_shim_tts_config_set_num_threads(void *cfg, int32_t v);
void sherpa_shim_tts_config_set_debug(void *cfg, int32_t v);
void sherpa_shim_tts_config_set_provider(void *cfg, const char *v);
void sherpa_shim_tts_config_set_max_num_sentences(void *cfg, int32_t v);
void *sherpa_shim_create_offline_tts(void *cfg);
// --- Offline recognizer config (Whisper / Paraformer / SenseVoice / Omnilingual) ---
void *sherpa_shim_offline_recog_config_new(void);
void sherpa_shim_offline_recog_config_free(void *cfg);
void sherpa_shim_offline_recog_config_set_num_threads(void *cfg, int32_t v);
void sherpa_shim_offline_recog_config_set_debug(void *cfg, int32_t v);
void sherpa_shim_offline_recog_config_set_provider(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_tokens(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_feat_sample_rate(void *cfg, int32_t v);
void sherpa_shim_offline_recog_config_set_feat_feature_dim(void *cfg, int32_t v);
void sherpa_shim_offline_recog_config_set_decoding_method(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_whisper_encoder(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_whisper_decoder(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_whisper_language(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_whisper_task(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_whisper_tail_paddings(void *cfg, int32_t v);
void sherpa_shim_offline_recog_config_set_paraformer_model(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_sense_voice_model(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_sense_voice_language(void *cfg, const char *v);
void sherpa_shim_offline_recog_config_set_sense_voice_use_itn(void *cfg, int32_t v);
void sherpa_shim_offline_recog_config_set_omnilingual_model(void *cfg, const char *v);
void *sherpa_shim_create_offline_recognizer(void *cfg);
// --- Online recognizer config (streaming zipformer transducer) ---
void *sherpa_shim_online_recog_config_new(void);
void sherpa_shim_online_recog_config_free(void *cfg);
void sherpa_shim_online_recog_config_set_transducer_encoder(void *cfg, const char *v);
void sherpa_shim_online_recog_config_set_transducer_decoder(void *cfg, const char *v);
void sherpa_shim_online_recog_config_set_transducer_joiner(void *cfg, const char *v);
void sherpa_shim_online_recog_config_set_tokens(void *cfg, const char *v);
void sherpa_shim_online_recog_config_set_num_threads(void *cfg, int32_t v);
void sherpa_shim_online_recog_config_set_debug(void *cfg, int32_t v);
void sherpa_shim_online_recog_config_set_provider(void *cfg, const char *v);
void sherpa_shim_online_recog_config_set_feat_sample_rate(void *cfg, int32_t v);
void sherpa_shim_online_recog_config_set_feat_feature_dim(void *cfg, int32_t v);
void sherpa_shim_online_recog_config_set_decoding_method(void *cfg, const char *v);
void sherpa_shim_online_recog_config_set_enable_endpoint(void *cfg, int32_t v);
void sherpa_shim_online_recog_config_set_rule1_min_trailing_silence(void *cfg, float v);
void sherpa_shim_online_recog_config_set_rule2_min_trailing_silence(void *cfg, float v);
void sherpa_shim_online_recog_config_set_rule3_min_utterance_length(void *cfg, float v);
void *sherpa_shim_create_online_recognizer(void *cfg);
// --- Result accessors (sherpa-allocated; caller destroys via sherpa's own Destroy*) ---
int32_t sherpa_shim_wave_sample_rate(const void *wave);
int32_t sherpa_shim_wave_num_samples(const void *wave);
const float *sherpa_shim_wave_samples(const void *wave);
const char *sherpa_shim_offline_result_text(const void *result);
const char *sherpa_shim_online_result_text(const void *result);
int32_t sherpa_shim_generated_audio_sample_rate(const void *audio);
int32_t sherpa_shim_generated_audio_n(const void *audio);
const float *sherpa_shim_generated_audio_samples(const void *audio);
int32_t sherpa_shim_speech_segment_start(const void *seg);
int32_t sherpa_shim_speech_segment_n(const void *seg);
// --- Offline speaker diarization config -----------------------------
// Pyannote segmentation + speaker-embedding extractor + fast clustering.
// The upstream config is a struct of nested structs; purego can't read or
// build those across dlopen, so we expose a calloc'd opaque holder plus
// flat setters, then hand it to sherpa via the create wrapper.
void *sherpa_shim_diarize_config_new(void);
void sherpa_shim_diarize_config_free(void *cfg);
void sherpa_shim_diarize_config_set_segmentation_model(void *cfg, const char *path);
void sherpa_shim_diarize_config_set_segmentation_num_threads(void *cfg, int32_t v);
void sherpa_shim_diarize_config_set_segmentation_provider(void *cfg, const char *v);
void sherpa_shim_diarize_config_set_segmentation_debug(void *cfg, int32_t v);
void sherpa_shim_diarize_config_set_embedding_model(void *cfg, const char *path);
void sherpa_shim_diarize_config_set_embedding_num_threads(void *cfg, int32_t v);
void sherpa_shim_diarize_config_set_embedding_provider(void *cfg, const char *v);
void sherpa_shim_diarize_config_set_embedding_debug(void *cfg, int32_t v);
void sherpa_shim_diarize_config_set_clustering_num_clusters(void *cfg, int32_t v);
void sherpa_shim_diarize_config_set_clustering_threshold(void *cfg, float v);
void sherpa_shim_diarize_config_set_min_duration_on(void *cfg, float v);
void sherpa_shim_diarize_config_set_min_duration_off(void *cfg, float v);
void *sherpa_shim_create_offline_speaker_diarization(void *cfg);
// Apply just the clustering knobs onto a loaded diarizer (sherpa
// supports re-clustering after Create), so per-call overrides like
// num_speakers don't require re-loading the heavy ONNX models.
void sherpa_shim_diarize_set_clustering(void *sd, int32_t num_clusters, float threshold);
// Sherpa's ResultSortByStartTime returns a sherpa-allocated array of
// SherpaOnnxOfflineSpeakerDiarizationSegment structs (free with
// SherpaOnnxOfflineSpeakerDiarizationDestroySegment). Purego can't read
// fields out of an array of C structs, so this getter copies one
// segment's fields into the caller-supplied float/int32 cells.
void sherpa_shim_diarize_segment_at(const void *segs, int32_t i,
float *out_start, float *out_end,
int32_t *out_speaker);
// --- TTS streaming callback trampoline -----------------------------
// Replaces the //export sherpaTtsGoCallback + callbacks.c bridge pattern.
// `callback_ptr` is the C-callable function pointer returned by
// purego.NewCallback. `user_data` is an integer the Go side uses to
// look up its state (sync.Map keyed by uint64).
//
// Returns the sherpa-allocated SherpaOnnxGeneratedAudio. Destroy with
// SherpaOnnxDestroyOfflineTtsGeneratedAudio (callable directly from
// Go via purego).
void *sherpa_shim_tts_generate_with_callback(
void *tts, const char *text, int32_t sid, float speed,
uintptr_t callback_ptr, uintptr_t user_data);
#ifdef __cplusplus
}
#endif
#endif

View File

@@ -0,0 +1,23 @@
package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := loadSherpaLibs(); err != nil {
panic(err)
}
if err := grpc.StartServer(*addr, &SherpaBackend{}); err != nil {
panic(err)
}
}

View File

@@ -0,0 +1,51 @@
#!/bin/bash
set -e
CURDIR=$(dirname "$(realpath $0)")
REPO_ROOT="${CURDIR}/../../.."
mkdir -p $CURDIR/package/lib
cp -avf $CURDIR/sherpa-onnx $CURDIR/package/
cp -avf $CURDIR/run.sh $CURDIR/package/
cp -rfLv $CURDIR/backend-assets/lib/* $CURDIR/package/lib/
if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
echo "Detected x86_64 architecture, copying x86_64 libraries..."
cp -arfLv /lib64/ld-linux-x86-64.so.2 $CURDIR/package/lib/ld.so
cp -arfLv /lib/x86_64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/x86_64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
cp -arfLv /lib/x86_64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
cp -arfLv /lib/x86_64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
cp -arfLv /lib/x86_64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
echo "Detected ARM64 architecture, copying ARM64 libraries..."
cp -arfLv /lib/ld-linux-aarch64.so.1 $CURDIR/package/lib/ld.so
cp -arfLv /lib/aarch64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/aarch64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
cp -arfLv /lib/aarch64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
cp -arfLv /lib/aarch64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
cp -arfLv /lib/aarch64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
elif [ $(uname -s) = "Darwin" ]; then
echo "Detected Darwin"
else
echo "Error: Could not detect architecture"
exit 1
fi
GPU_LIB_SCRIPT="${REPO_ROOT}/scripts/build/package-gpu-libs.sh"
if [ -f "$GPU_LIB_SCRIPT" ]; then
echo "Packaging GPU libraries for BUILD_TYPE=${BUILD_TYPE:-cpu}..."
source "$GPU_LIB_SCRIPT" "$CURDIR/package/lib"
package_gpu_libs
fi
echo "Packaging completed successfully"
ls -liah $CURDIR/package/
ls -liah $CURDIR/package/lib/

13
backend/go/sherpa-onnx/run.sh Executable file
View File

@@ -0,0 +1,13 @@
#!/bin/bash
set -ex
CURDIR=$(dirname "$(realpath $0)")
export LD_LIBRARY_PATH=$CURDIR/lib:$LD_LIBRARY_PATH
if [ -f $CURDIR/lib/ld.so ]; then
echo "Using lib/ld.so"
exec $CURDIR/lib/ld.so $CURDIR/sherpa-onnx "$@"
fi
exec $CURDIR/sherpa-onnx "$@"

12
backend/go/sherpa-onnx/test.sh Executable file
View File

@@ -0,0 +1,12 @@
#!/bin/bash
# Unit tests for the sherpa-onnx backend. Exercises error-path and
# dispatch logic via SherpaBackend directly (no gRPC). Integration
# coverage (gRPC TTS / streaming ASR / realtime pipeline) lives in
# tests/e2e-backends and tests/e2e and runs against the Docker image.
set -e
CURDIR=$(dirname "$(realpath $0)")
cd "$CURDIR"
PACKAGES=$(go list ./... | grep -v /sources/)
go test -v -timeout 60s $PACKAGES

View File

@@ -4,7 +4,7 @@ set(CMAKE_POSITION_INDEPENDENT_CODE ON)
add_subdirectory(./sources/stablediffusion-ggml.cpp)
add_library(gosd MODULE gosd.cpp)
add_library(gosd MODULE cpp/gosd.cpp)
target_link_libraries(gosd PRIVATE stable-diffusion ggml)
if(CMAKE_CXX_COMPILER_ID MATCHES "GNU" AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 9.0)

View File

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
# stablediffusion.cpp (ggml)
STABLEDIFFUSION_GGML_REPO?=https://github.com/leejet/stable-diffusion.cpp
STABLEDIFFUSION_GGML_VERSION?=c97702e1057c2fe13a7074cd9069cb9dd6edc1bf
STABLEDIFFUSION_GGML_VERSION?=3d6064b37ef4607917f8acf2ca8c8906d5087413
CMAKE_ARGS+=-DGGML_MAX_NAME=128
@@ -119,7 +119,7 @@ libgosd-fallback.so: sources/stablediffusion-ggml.cpp
SO_TARGET=libgosd-fallback.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" $(MAKE) libgosd-custom
rm -rfv build*
libgosd-custom: CMakeLists.txt gosd.cpp gosd.h
libgosd-custom: CMakeLists.txt cpp/gosd.cpp cpp/gosd.h
mkdir -p build-$(SO_TARGET) && \
cd build-$(SO_TARGET) && \
cmake .. $(CMAKE_ARGS) && \

View File

@@ -0,0 +1,71 @@
cmake_minimum_required(VERSION 3.18)
project(govibevoicecpp LANGUAGES C CXX)
set(CMAKE_POSITION_INDEPENDENT_CODE ON)
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
set(VIBEVOICE_DIR ${CMAKE_CURRENT_SOURCE_DIR}/sources/vibevoice.cpp)
# Override upstream's CMAKE_CUDA_ARCHITECTURES before add_subdirectory.
if(NOT DEFINED CMAKE_CUDA_ARCHITECTURES)
set(CMAKE_CUDA_ARCHITECTURES "75-virtual;80-virtual;86-real;89-real")
endif()
# Force-disable upstream tests/examples — we only need libvibevoice.
set(VIBEVOICE_BUILD_TESTS OFF CACHE BOOL "" FORCE)
set(VIBEVOICE_BUILD_EXAMPLES OFF CACHE BOOL "" FORCE)
set(VIBEVOICE_BUILD_SERVER OFF CACHE BOOL "" FORCE)
# vibevoice.cpp's top-level CMakeLists already adds third_party/ggml as a
# subdirectory — no need to add it explicitly here, just include the
# whole project.
add_subdirectory(${VIBEVOICE_DIR} vibevoice EXCLUDE_FROM_ALL)
add_library(govibevoicecpp MODULE cpp/govibevoicecpp.cpp)
# libvibevoice is STATIC; without --whole-archive the linker GCs the
# vv_capi_* symbols (purego dlopens them by name, nothing in our
# translation unit references them). Force the static archive's
# entire contents into the MODULE so dlsym finds vv_capi_load etc.
if(APPLE)
target_link_libraries(govibevoicecpp PRIVATE -Wl,-force_load $<TARGET_FILE:vibevoice>)
elseif(MSVC)
target_link_libraries(govibevoicecpp PRIVATE vibevoice)
set_property(TARGET govibevoicecpp APPEND PROPERTY LINK_FLAGS "/WHOLEARCHIVE:vibevoice")
else()
target_link_libraries(govibevoicecpp PRIVATE
-Wl,--whole-archive vibevoice -Wl,--no-whole-archive)
endif()
target_include_directories(govibevoicecpp PRIVATE ${VIBEVOICE_DIR}/include)
target_include_directories(govibevoicecpp SYSTEM PRIVATE ${VIBEVOICE_DIR}/third_party/ggml/include)
# Link GPU backends if available — vibevoice's own CMake already links
# these to the libvibevoice STATIC library, but we re-link them on the
# MODULE so resolved symbols include all backend kernels.
foreach(backend blas cuda metal vulkan)
if(TARGET ggml-${backend})
target_link_libraries(govibevoicecpp PRIVATE ggml-${backend})
string(TOUPPER ${backend} BACKEND_UPPER)
target_compile_definitions(govibevoicecpp PRIVATE VIBEVOICE_HAVE_${BACKEND_UPPER})
if(backend STREQUAL "cuda")
find_package(CUDAToolkit QUIET)
if(CUDAToolkit_FOUND)
target_link_libraries(govibevoicecpp PRIVATE CUDA::cudart)
endif()
endif()
endif()
endforeach()
if(MSVC)
target_compile_options(govibevoicecpp PRIVATE /W4 /wd4100 /wd4505)
else()
target_compile_options(govibevoicecpp PRIVATE -Wall -Wextra -Wshadow
-Wno-unused-parameter -Wno-unused-function -Wno-sign-conversion)
endif()
if(CMAKE_CXX_COMPILER_ID MATCHES "GNU" AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 9.0)
target_link_libraries(govibevoicecpp PRIVATE stdc++fs)
endif()
set_property(TARGET govibevoicecpp PROPERTY CXX_STANDARD 17)
set_target_properties(govibevoicecpp PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR})

View File

@@ -0,0 +1,131 @@
CMAKE_ARGS?=
BUILD_TYPE?=
NATIVE?=false
GOCMD?=go
GO_TAGS?=
JOBS?=$(shell nproc --ignore=1)
# vibevoice.cpp version. Pinned to a commit hash and auto-bumped by
# .github/workflows/bump_deps.yaml (the matrix entry mirrors what we
# already do for ik_llama.cpp / llama.cpp / whisper.cpp). Floating on
# `master` led to silent ABI breaks reaching CI — pin it.
VIBEVOICE_REPO?=https://github.com/mudler/vibevoice.cpp
VIBEVOICE_CPP_VERSION?=ad856bda6b1311b7f3d7c4a667be43eeb8a8249a
SO_TARGET?=libgovibevoicecpp.so
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
CMAKE_ARGS+=-DVIBEVOICE_BUILD_TESTS=OFF
CMAKE_ARGS+=-DVIBEVOICE_BUILD_EXAMPLES=OFF
ifeq ($(NATIVE),false)
CMAKE_ARGS+=-DGGML_NATIVE=OFF
endif
ifeq ($(BUILD_TYPE),cublas)
CMAKE_ARGS+=-DGGML_CUDA=ON -DVIBEVOICE_GGML_CUDA=ON
else ifeq ($(BUILD_TYPE),openblas)
CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
else ifeq ($(BUILD_TYPE),clblas)
CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
else ifeq ($(BUILD_TYPE),hipblas)
CMAKE_ARGS+=-DGGML_HIPBLAS=ON -DVIBEVOICE_GGML_HIPBLAS=ON
else ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DGGML_VULKAN=ON -DVIBEVOICE_GGML_VULKAN=ON
else ifeq ($(OS),Darwin)
ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DGGML_METAL=OFF
else
CMAKE_ARGS+=-DGGML_METAL=ON -DVIBEVOICE_GGML_METAL=ON
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
endif
endif
ifeq ($(BUILD_TYPE),sycl_f16)
CMAKE_ARGS+=-DGGML_SYCL=ON \
-DCMAKE_C_COMPILER=icx \
-DCMAKE_CXX_COMPILER=icpx \
-DGGML_SYCL_F16=ON
endif
ifeq ($(BUILD_TYPE),sycl_f32)
CMAKE_ARGS+=-DGGML_SYCL=ON \
-DCMAKE_C_COMPILER=icx \
-DCMAKE_CXX_COMPILER=icpx
endif
sources/vibevoice.cpp:
mkdir -p sources/vibevoice.cpp
cd sources/vibevoice.cpp && \
git init && \
git remote add origin $(VIBEVOICE_REPO) && \
git fetch origin && \
git checkout $(VIBEVOICE_CPP_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
# Detect OS
UNAME_S := $(shell uname -s)
# Only build CPU variants on Linux
ifeq ($(UNAME_S),Linux)
VARIANT_TARGETS = libgovibevoicecpp-avx.so libgovibevoicecpp-avx2.so libgovibevoicecpp-avx512.so libgovibevoicecpp-fallback.so
else
# On non-Linux (e.g., Darwin), build only fallback variant
VARIANT_TARGETS = libgovibevoicecpp-fallback.so
endif
vibevoice-cpp: main.go govibevoicecpp.go $(VARIANT_TARGETS)
CGO_ENABLED=0 $(GOCMD) build -tags "$(GO_TAGS)" -o vibevoice-cpp ./
package: vibevoice-cpp
bash package.sh
build: package
clean: purge
rm -rf libgovibevoicecpp*.so package sources/vibevoice.cpp vibevoice-cpp
purge:
rm -rf build*
# Variants must build sequentially
.NOTPARALLEL:
# Build all variants (Linux only)
ifeq ($(UNAME_S),Linux)
libgovibevoicecpp-avx.so: sources/vibevoice.cpp
$(info ${GREEN}I vibevoice-cpp build info:avx${RESET})
SO_TARGET=libgovibevoicecpp-avx.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" $(MAKE) libgovibevoicecpp-custom
rm -rf build-libgovibevoicecpp-avx.so
libgovibevoicecpp-avx2.so: sources/vibevoice.cpp
$(info ${GREEN}I vibevoice-cpp build info:avx2${RESET})
SO_TARGET=libgovibevoicecpp-avx2.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on -DGGML_BMI2=on" $(MAKE) libgovibevoicecpp-custom
rm -rf build-libgovibevoicecpp-avx2.so
libgovibevoicecpp-avx512.so: sources/vibevoice.cpp
$(info ${GREEN}I vibevoice-cpp build info:avx512${RESET})
SO_TARGET=libgovibevoicecpp-avx512.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=on -DGGML_FMA=on -DGGML_F16C=on -DGGML_BMI2=on" $(MAKE) libgovibevoicecpp-custom
rm -rf build-libgovibevoicecpp-avx512.so
endif
# Build fallback variant (all platforms)
libgovibevoicecpp-fallback.so: sources/vibevoice.cpp
$(info ${GREEN}I vibevoice-cpp build info:fallback${RESET})
SO_TARGET=libgovibevoicecpp-fallback.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" $(MAKE) libgovibevoicecpp-custom
rm -rf build-libgovibevoicecpp-fallback.so
libgovibevoicecpp-custom: CMakeLists.txt cpp/govibevoicecpp.cpp cpp/govibevoicecpp.h
mkdir -p build-$(SO_TARGET) && \
cd build-$(SO_TARGET) && \
cmake .. $(CMAKE_ARGS) && \
cmake --build . --config Release -j$(JOBS) --target govibevoicecpp && \
cd .. && \
mv build-$(SO_TARGET)/libgovibevoicecpp.so ./$(SO_TARGET)
test: vibevoice-cpp
@echo "Running vibevoice-cpp tests..."
bash test.sh
@echo "vibevoice-cpp tests completed."
all: vibevoice-cpp package

View File

@@ -0,0 +1,41 @@
// vibevoice.cpp ships its purego-friendly ABI in vibevoice_capi.h.
// This translation unit is intentionally tiny: pulling in the header
// (and linking libvibevoice PRIVATE in CMake) is enough to make the
// vv_capi_* symbols visible from the produced MODULE library.
//
// We do install a ggml log redirect so backend logs land on the gRPC
// server's stderr — same pattern as backend/go/qwen3-tts-cpp/cpp/.
#include "govibevoicecpp.h"
#include "ggml.h"
#include "ggml-backend.h"
#include <cstdio>
namespace {
void govibevoice_log_cb(enum ggml_log_level level, const char* msg, void* /*ud*/) {
if (!msg) return;
const char* tag = "?????";
switch (level) {
case GGML_LOG_LEVEL_DEBUG: tag = "DEBUG"; break;
case GGML_LOG_LEVEL_INFO: tag = "INFO"; break;
case GGML_LOG_LEVEL_WARN: tag = "WARN"; break;
case GGML_LOG_LEVEL_ERROR: tag = "ERROR"; break;
default: break;
}
std::fprintf(stderr, "[%-5s] %s", tag, msg);
std::fflush(stderr);
}
struct LogInstaller {
LogInstaller() {
ggml_log_set(govibevoice_log_cb, nullptr);
ggml_backend_load_all();
}
};
LogInstaller g_install;
} // namespace

View File

@@ -0,0 +1,7 @@
#pragma once
// Re-exports the vibevoice.cpp flat C ABI so this MODULE library
// resolves the same symbols that purego.RegisterLibFunc looks up by
// name. The actual definitions live in libvibevoice (linked PRIVATE).
#include "vibevoice_capi.h"

View File

@@ -0,0 +1,656 @@
package main
import (
"encoding/json"
"fmt"
"io"
"os"
"os/exec"
"path/filepath"
"runtime"
"strings"
laudio "github.com/mudler/LocalAI/pkg/audio"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
// vv_capi_asr loads audio with load_wav_24k_mono — a 24 kHz mono s16le
// WAV is the format the model was trained on. Inputs already in that
// format pass through; everything else is converted via ffmpeg, which
// is therefore a runtime requirement only when callers upload non-WAV
// (or non-24 kHz mono s16le WAV) audio. Skipping ffmpeg on the happy
// path matters for the e2e-backends test container, which does not
// ship ffmpeg but feeds the backend pre-cooked 24 kHz mono WAVs.
const vibevoiceASRSampleRate = 24000
// prepareWavInput resolves `src` to a 24 kHz mono s16le WAV path that
// vv_capi_asr's load_wav_24k_mono accepts. Returns the resolved path
// plus a cleanup func; both must be honoured by the caller.
//
// Pass-through happens when `src` already has the right WAV format —
// no ffmpeg required. Otherwise we shell out to ffmpeg into a temp
// dir; if ffmpeg isn't on PATH we surface a clear error mentioning the
// underlying format mismatch.
func prepareWavInput(src string) (string, func(), error) {
if src == "" {
return "", func() {}, fmt.Errorf("empty audio path")
}
if isVibevoiceCompatibleWav(src) {
return src, func() {}, nil
}
dir, err := os.MkdirTemp("", "vibevoice-asr")
if err != nil {
return "", func() {}, fmt.Errorf("mkdtemp: %w", err)
}
cleanup := func() { _ = os.RemoveAll(dir) }
wavPath := filepath.Join(dir, "input.wav")
// -y: overwrite, -ar 24000: target sample rate, -ac 1: mono,
// -acodec pcm_s16le: signed 16-bit little-endian PCM (load_wav_24k_mono
// only accepts s16le).
cmd := exec.Command("ffmpeg",
"-y", "-i", src,
"-ar", fmt.Sprintf("%d", vibevoiceASRSampleRate),
"-ac", "1",
"-acodec", "pcm_s16le",
wavPath,
)
cmd.Env = []string{}
if out, err := cmd.CombinedOutput(); err != nil {
cleanup()
return "", func() {}, fmt.Errorf("ffmpeg convert to 24k mono wav: %w (output: %s)", err, string(out))
}
return wavPath, cleanup, nil
}
// isVibevoiceCompatibleWav returns true when `src` carries the RIFF/WAVE
// magic bytes. vibevoice's load_wav_24k_mono uses drwav under the hood,
// which accepts any PCM/IEEE-float WAV at any sample rate and downmixes
// multi-channel input to mono on its own — so any valid WAV passes
// through to the C side without conversion. Anything else (MP3, OGG,
// FLAC, ...) needs ffmpeg.
func isVibevoiceCompatibleWav(src string) bool {
f, err := os.Open(src)
if err != nil {
return false
}
defer func() { _ = f.Close() }()
// 0..3 = "RIFF", 8..11 = "WAVE".
var hdr [12]byte
if _, err := io.ReadFull(f, hdr[:]); err != nil {
return false
}
return string(hdr[0:4]) == "RIFF" && string(hdr[8:12]) == "WAVE"
}
// asrMaxNewTokens caps the ASR generation budget. The C ABI defaults to
// 256 when 0 is passed — far too small for anything past ~10s of speech.
// Vibevoice generates ~30 tokens per second of audio, so 16 384 covers
// roughly 9 minutes of dialogue, well past any normal /v1/audio/diarization
// upload. Going higher costs little since generation stops at EOS.
const asrMaxNewTokens = 16384
// vibevoice.cpp synthesizes 24 kHz mono 16-bit PCM. Hardcoded - the
// model itself is fixed-rate; if the upstream ever changes this we'll
// pick it up via vv_capi_version().
const vibevoiceSampleRate = uint32(24000)
// purego-bound entry points from libgovibevoicecpp.
//
// vv_capi_tts takes a `const char* const* ref_audio_paths` array (used
// by the 1.5B variant for runtime voice cloning; the realtime-0.5B
// path leaves it NULL and uses voice_path instead). purego marshals a
// Go []*byte slice as **char by passing the underlying array's address.
// A nil/empty slice marshals to NULL, which matches the C contract for
// "no reference audio".
var (
CppLoad func(ttsModel, asrModel, tokenizer, voice string, threads int32) int32
CppTTS func(text, voicePath string,
refAudioPaths []*byte, nRefAudioPaths int32,
dstWav string,
nSteps int32, cfgScale float32, maxSpeechFrames int32, seed uint32) int32
CppASR func(srcWav string, outJSON []byte, capacity uint64,
maxNewTokens int32) int32
CppUnload func()
CppVersion func() string
)
// VibevoiceCpp speaks gRPC against vibevoice.cpp's flat C ABI. The
// engine is a single global, so we serialize calls through SingleThread.
type VibevoiceCpp struct {
base.SingleThread
threads int
// modelRoot is the directory we use to resolve relative paths
// from Options[] and per-call overrides (TTSRequest.Voice).
// Source of truth: opts.ModelPath; falls back to the dir of
// the primary ModelFile when ModelPath is empty.
modelRoot string
ttsModel string
asrModel string
tokenizer string
voice string
// refAudio is the load-time default list of reference WAVs used by
// the 1.5B model (one per speaker). Sourced from
// ModelOptions.AudioPath (config_file's `audio_path:`) — comma-
// separated for multi-speaker. Per-call TTSRequest.Voice can
// override it. Empty for the realtime-0.5B path, which conditions
// on a pre-baked voice gguf via `voice` instead.
refAudio []string
}
// resolvePath joins a relative path onto `relTo`. The gallery
// convention is that Options[] carry paths relative to the LocalAI
// models dir (opts.ModelPath), so anything not absolute is treated
// as a sibling of the primary ModelFile - never CWD. Empty / already-
// absolute / no-relTo inputs pass through unchanged.
func resolvePath(p, relTo string) string {
if p == "" || filepath.IsAbs(p) || relTo == "" {
return p
}
return filepath.Join(relTo, p)
}
// parseOptions reads opts.Options[] and pulls out the per-role
// overrides documented in the gallery entries. Accepts both "key=value"
// (gallery YAML style) and "key:value" (Make-target / env-var style).
func (v *VibevoiceCpp) parseOptions(opts []string, relTo string) string {
role := ""
for _, raw := range opts {
k, val, ok := strings.Cut(raw, "=")
if !ok {
k, val, ok = strings.Cut(raw, ":")
if !ok {
continue
}
}
key := strings.TrimSpace(k)
val = strings.TrimSpace(val)
switch key {
case "type":
role = strings.ToLower(val)
case "tokenizer":
v.tokenizer = resolvePath(val, relTo)
case "voice":
v.voice = resolvePath(val, relTo)
case "tts_model":
v.ttsModel = resolvePath(val, relTo)
case "asr_model":
v.asrModel = resolvePath(val, relTo)
}
}
return role
}
// parseRefAudio splits a comma-separated audio_path value into a
// resolved list of WAVs. The 1.5B model uses one WAV per speaker;
// callers that only need a single reference set audio_path to a single
// path. Empty / whitespace-only entries are skipped.
func parseRefAudio(audioPath, relTo string) []string {
if audioPath == "" {
return nil
}
var out []string
for _, p := range strings.Split(audioPath, ",") {
p = strings.TrimSpace(p)
if p == "" {
continue
}
out = append(out, resolvePath(p, relTo))
}
return out
}
func (v *VibevoiceCpp) Load(opts *pb.ModelOptions) error {
if opts.ModelFile == "" {
return fmt.Errorf("vibevoice-cpp: ModelFile is required")
}
modelFile := opts.ModelFile
if !filepath.IsAbs(modelFile) && opts.ModelPath != "" {
modelFile = filepath.Join(opts.ModelPath, modelFile)
}
// ModelPath is the LocalAI core's models root, propagated over
// gRPC. Use it as the resolution base for Options[] (and later
// for TTSRequest.Voice) so gallery entries can reference paths
// like "tokenizer=tokenizer.gguf" and have them resolved
// against the same root the core used to drop the files.
v.modelRoot = opts.ModelPath
if v.modelRoot == "" {
v.modelRoot = filepath.Dir(modelFile)
}
role := v.parseOptions(opts.Options, v.modelRoot)
// 1.5B reference WAVs ride on ModelOptions.AudioPath (config_file's
// `audio_path:` key) — same convention other audio backends already
// follow. Single-speaker = single path; multi-speaker = comma list,
// one WAV per Speaker N: tag in TTSRequest.text.
v.refAudio = parseRefAudio(opts.AudioPath, v.modelRoot)
// ModelFile fills the "primary" role-slot determined by `type=`
// in Options (defaults to tts). The other slot stays exactly as
// Options set it - so a closed-loop config with ModelFile=tts.gguf
// + Options[asr_model=asr.gguf] resolves correctly to both slots,
// and an explicit `tts_model=` / `asr_model=` always wins over
// ModelFile for its own slot.
primaryIsASR := false
switch role {
case "asr", "transcript", "stt", "speech-to-text":
primaryIsASR = true
}
if primaryIsASR {
if v.asrModel == "" {
v.asrModel = modelFile
}
} else if v.ttsModel == "" {
v.ttsModel = modelFile
}
if v.ttsModel == "" && v.asrModel == "" {
return fmt.Errorf("vibevoice-cpp: no TTS or ASR model resolved from ModelFile=%q + options", opts.ModelFile)
}
if v.tokenizer == "" {
return fmt.Errorf("vibevoice-cpp: tokenizer is required - pass options: [tokenizer=<path>]")
}
threads := int(opts.Threads)
if threads <= 0 {
threads = 4
}
v.threads = threads
fmt.Fprintf(os.Stderr,
"[vibevoice-cpp] Loading: tts=%q asr=%q tokenizer=%q voice=%q ref_audio=%v threads=%d\n",
v.ttsModel, v.asrModel, v.tokenizer, v.voice, v.refAudio, threads)
if rc := CppLoad(v.ttsModel, v.asrModel, v.tokenizer, v.voice, int32(threads)); rc != 0 {
return fmt.Errorf("vibevoice-cpp: vv_capi_load failed (rc=%d)", rc)
}
return nil
}
func (v *VibevoiceCpp) TTS(req *pb.TTSRequest) error {
if v.ttsModel == "" {
return fmt.Errorf("vibevoice-cpp: TTS requested but no realtime model was loaded")
}
text := req.Text
dst := req.Dst
if text == "" || dst == "" {
return fmt.Errorf("vibevoice-cpp: TTS requires both text and dst")
}
// TTSRequest.Voice carries the per-call override. Routing depends
// on the loaded model variant:
// * realtime-0.5B → expects a baked voice .gguf (single path).
// * 1.5B → expects one or more raw 24 kHz mono .wav
// reference clips for runtime voice cloning;
// comma-separated to address multi-speaker
// dialogs (Speaker 0..n-1 follow the order).
// We pick the branch by extension / shape of the override; if no
// override is given, fall back to the load-time defaults.
voice := ""
var refAudio []string
if reqVoice := strings.TrimSpace(req.Voice); reqVoice != "" {
if isRefAudioOverride(reqVoice) {
for _, p := range strings.Split(reqVoice, ",") {
p = strings.TrimSpace(p)
if p == "" {
continue
}
refAudio = append(refAudio, resolvePath(p, v.modelRoot))
}
} else {
voice = resolvePath(reqVoice, v.modelRoot)
}
} else {
// No per-call override. v.voice already went to vv_capi_load
// for realtime-0.5B; ref_audio is per-call only on the C ABI,
// so the gallery's `ref_audio:` defaults are re-passed here.
refAudio = append(refAudio, v.refAudio...)
}
if req.Language != nil && *req.Language != "" {
fmt.Fprintf(os.Stderr,
"[vibevoice-cpp] note: TTSRequest.language=%q ignored - vibevoice picks language from the voice prompt\n",
*req.Language)
}
const (
defaultSteps = 20
defaultMaxFrames = 200
)
defaultCfg := float32(1.3)
refPtrs, refKeep := newCStringArray(refAudio)
rc := CppTTS(text, voice, refPtrs, int32(len(refPtrs)), dst,
int32(defaultSteps), defaultCfg, int32(defaultMaxFrames), 0)
// Hold the backing buffers past the cgo call. purego marshals
// []*byte by handing the C side the underlying array address; the
// pointed-to NUL-terminated bytes must outlive the call.
runtime.KeepAlive(refKeep)
runtime.KeepAlive(refPtrs)
if rc != 0 {
return fmt.Errorf("vibevoice-cpp: vv_capi_tts failed (rc=%d)", rc)
}
return nil
}
// isRefAudioOverride decides whether a TTSRequest.Voice override should
// be routed to ref_audio_paths (1.5B path) instead of voice_path
// (realtime-0.5B). Either a comma-separated list (multi-speaker) or a
// single .wav clip qualifies; a bare voice .gguf falls through.
func isRefAudioOverride(s string) bool {
if strings.Contains(s, ",") {
return true
}
return strings.HasSuffix(strings.ToLower(s), ".wav")
}
// newCStringArray builds the **char array vv_capi_tts expects, plus the
// keep-alive slice the caller must runtime.KeepAlive across the cgo
// call. A nil/empty input returns (nil, nil) which purego marshals to
// the C NULL pointer.
func newCStringArray(in []string) ([]*byte, [][]byte) {
if len(in) == 0 {
return nil, nil
}
keep := make([][]byte, len(in))
ptrs := make([]*byte, len(in))
for i, s := range in {
b := make([]byte, len(s)+1)
copy(b, s)
keep[i] = b
ptrs[i] = &b[0]
}
return ptrs, keep
}
// asrSegment matches vibevoice's JSON output:
//
// [{"Start":0.0,"End":2.8,"Speaker":0,"Content":"…"}, ...]
type asrSegment struct {
Start float64 `json:"Start"`
End float64 `json:"End"`
Speaker int `json:"Speaker"`
Content string `json:"Content"`
}
// callASR invokes vv_capi_asr with a buffer that grows on demand.
// vv_capi_asr returns: >0 bytes written, 0 no transcript, <0 error or
// -required_size. We honor the resize protocol once before giving up.
func (v *VibevoiceCpp) callASR(srcWav string, maxNewTokens int32) (string, error) {
const startCap = 256 * 1024
buf := make([]byte, startCap)
rc := CppASR(srcWav, buf, uint64(len(buf)), maxNewTokens)
if rc < 0 {
need := -int(rc)
if need > 0 && need < (16<<20) && need > len(buf) {
buf = make([]byte, need+64)
rc = CppASR(srcWav, buf, uint64(len(buf)), maxNewTokens)
}
}
if rc < 0 {
return "", fmt.Errorf("vibevoice-cpp: vv_capi_asr failed (rc=%d)", rc)
}
if rc == 0 {
return "", nil
}
return string(buf[:rc]), nil
}
// TTSStream is the streaming counterpart to TTS. vibevoice's C ABI is
// file-only (vv_capi_tts writes a complete WAV), so we synthesize to
// a tempfile, then emit a streaming-WAV header followed by the PCM
// body in chunks. The main reason this exists at all is the gRPC
// server wrapper (pkg/grpc/server.go:TTSStream) blocks on a channel
// that only this method can close - if we leave the default Base
// stub in place, every TTSStream call hangs until the client
// deadline.
func (v *VibevoiceCpp) TTSStream(req *pb.TTSRequest, results chan []byte) error {
defer close(results)
if v.ttsModel == "" {
return fmt.Errorf("vibevoice-cpp: TTSStream requested but no realtime model was loaded")
}
if req.Text == "" {
return fmt.Errorf("vibevoice-cpp: TTSStream requires text")
}
tmp, err := os.CreateTemp("", "vibevoice-cpp-stream-*.wav")
if err != nil {
return fmt.Errorf("vibevoice-cpp: tempfile: %w", err)
}
dst := tmp.Name()
_ = tmp.Close()
defer func() { _ = os.Remove(dst) }()
if err := v.TTS(&pb.TTSRequest{
Text: req.Text,
Voice: req.Voice,
Dst: dst,
Language: req.Language,
}); err != nil {
return err
}
wav, err := os.ReadFile(dst)
if err != nil {
return fmt.Errorf("vibevoice-cpp: read tempfile: %w", err)
}
// Streaming WAV header: declare 0xFFFFFFFF for chunk sizes so HTTP
// clients can start playback before they see the full PCM.
const streamingSize = 0xFFFFFFFF
hdr := laudio.NewWAVHeaderWithRate(streamingSize, vibevoiceSampleRate)
hdr.ChunkSize = streamingSize
hdrBuf := make([]byte, 0, laudio.WAVHeaderSize)
w := newByteWriter(&hdrBuf)
if err := hdr.Write(w); err != nil {
return fmt.Errorf("vibevoice-cpp: write WAV header: %w", err)
}
results <- hdrBuf
// PCM body: send in ~64 KB slices so the client gets multiple
// reply chunks (e2e harness asserts >=2 frames).
pcm := laudio.StripWAVHeader(wav)
const chunkBytes = 64 * 1024
for off := 0; off < len(pcm); off += chunkBytes {
end := off + chunkBytes
if end > len(pcm) {
end = len(pcm)
}
chunk := make([]byte, end-off)
copy(chunk, pcm[off:end])
results <- chunk
}
return nil
}
// byteWriter adapts a *[]byte to io.Writer so we can hand it to
// laudio.WAVHeader.Write without allocating a bytes.Buffer.
type byteWriter struct{ buf *[]byte }
func newByteWriter(b *[]byte) *byteWriter { return &byteWriter{buf: b} }
func (w *byteWriter) Write(p []byte) (int, error) {
*w.buf = append(*w.buf, p...)
return len(p), nil
}
func (v *VibevoiceCpp) AudioTranscription(req *pb.TranscriptRequest) (pb.TranscriptResult, error) {
if v.asrModel == "" {
return pb.TranscriptResult{}, fmt.Errorf("vibevoice-cpp: AudioTranscription requested but no ASR model was loaded")
}
if req.Dst == "" {
return pb.TranscriptResult{}, fmt.Errorf("vibevoice-cpp: TranscriptRequest.dst (audio path) is required")
}
wavPath, cleanup, err := prepareWavInput(req.Dst)
if err != nil {
return pb.TranscriptResult{}, fmt.Errorf("vibevoice-cpp: %w", err)
}
defer cleanup()
out, err := v.callASR(wavPath, asrMaxNewTokens)
if err != nil {
return pb.TranscriptResult{}, err
}
if out == "" {
return pb.TranscriptResult{}, nil
}
var segs []asrSegment
if err := json.Unmarshal([]byte(out), &segs); err != nil {
fmt.Fprintf(os.Stderr,
"[vibevoice-cpp] WARNING: vv_capi_asr returned non-JSON, falling back to single segment: %v\n", err)
return pb.TranscriptResult{
Segments: []*pb.TranscriptSegment{{Id: 0, Text: strings.TrimSpace(out)}},
Text: strings.TrimSpace(out),
}, nil
}
segments := make([]*pb.TranscriptSegment, 0, len(segs))
parts := make([]string, 0, len(segs))
var duration float32
for i, s := range segs {
// LocalAI's whisper backend uses int64 100ns ticks for
// Start/End (seconds * 1e7); follow the same convention so
// consumers can mix vibevoice and whisper transcripts.
segments = append(segments, &pb.TranscriptSegment{
Id: int32(i),
Text: s.Content,
Start: int64(s.Start * 1e7),
End: int64(s.End * 1e7),
Speaker: fmt.Sprintf("%d", s.Speaker),
})
parts = append(parts, strings.TrimSpace(s.Content))
if float32(s.End) > duration {
duration = float32(s.End)
}
}
return pb.TranscriptResult{
Segments: segments,
Text: strings.TrimSpace(strings.Join(parts, " ")),
Duration: duration,
}, nil
}
// Diarize runs vibevoice's ASR and projects the speaker-labelled segment
// list it returns natively. vibevoice.cpp's ASR prompt asks the model to
// emit `[{"Start":..,"End":..,"Speaker":..,"Content":..}]`, so diarization
// is a by-product of the same pass — we reuse callASR and re-shape.
//
// Speaker hints (num_speakers/min/max/threshold) and min_duration_on/off are
// not actionable here: vibevoice's model picks the speaker count itself and
// has no clustering knob. The HTTP layer documents this; we accept the
// fields for API symmetry and ignore them.
func (v *VibevoiceCpp) Diarize(req *pb.DiarizeRequest) (pb.DiarizeResponse, error) {
if v.asrModel == "" {
return pb.DiarizeResponse{}, fmt.Errorf("vibevoice-cpp: Diarize requires an ASR model (load options: type=asr)")
}
if req.Dst == "" {
return pb.DiarizeResponse{}, fmt.Errorf("vibevoice-cpp: DiarizeRequest.dst (audio path) is required")
}
wavPath, cleanup, err := prepareWavInput(req.Dst)
if err != nil {
return pb.DiarizeResponse{}, fmt.Errorf("vibevoice-cpp: %w", err)
}
defer cleanup()
out, err := v.callASR(wavPath, asrMaxNewTokens)
if err != nil {
return pb.DiarizeResponse{}, err
}
if out == "" {
return pb.DiarizeResponse{}, nil
}
var segs []asrSegment
if err := json.Unmarshal([]byte(out), &segs); err != nil {
// Mirror AudioTranscription's fallback: vibevoice's ASR sometimes
// emits free-form text instead of JSON for short or unusual audio.
// Surface a single unknown-speaker segment carrying the full text
// (when include_text is set) so the caller still gets coverage of
// the whole clip rather than a hard failure.
fmt.Fprintf(os.Stderr,
"[vibevoice-cpp] WARNING: vv_capi_asr returned non-JSON for diarization, falling back to single segment: %v\n", err)
text := strings.TrimSpace(out)
seg := &pb.DiarizeSegment{Id: 0, Speaker: "0"}
if req.IncludeText {
seg.Text = text
}
return pb.DiarizeResponse{
Segments: []*pb.DiarizeSegment{seg},
NumSpeakers: 1,
}, nil
}
speakers := make(map[int]struct{})
segments := make([]*pb.DiarizeSegment, 0, len(segs))
var duration float32
for i, s := range segs {
ds := &pb.DiarizeSegment{
Id: int32(i),
Start: float32(s.Start),
End: float32(s.End),
Speaker: fmt.Sprintf("%d", s.Speaker),
}
if req.IncludeText {
ds.Text = strings.TrimSpace(s.Content)
}
segments = append(segments, ds)
speakers[s.Speaker] = struct{}{}
if float32(s.End) > duration {
duration = float32(s.End)
}
}
return pb.DiarizeResponse{
Segments: segments,
NumSpeakers: int32(len(speakers)),
Duration: duration,
}, nil
}
// AudioTranscriptionStream wraps AudioTranscription so the streaming
// gRPC endpoint (server.go:AudioTranscriptionStream) sees its channel
// close and the client doesn't sit waiting until deadline. vibevoice's
// ASR doesn't expose token-level streaming - vv_capi_asr decodes the
// whole audio and returns a JSON segment list - so we run the offline
// transcription, emit each segment's content as a delta, then close
// with a final_result whose Text equals the concatenated deltas (the
// e2e harness asserts those match).
func (v *VibevoiceCpp) AudioTranscriptionStream(req *pb.TranscriptRequest, results chan *pb.TranscriptStreamResponse) error {
defer close(results)
res, err := v.AudioTranscription(req)
if err != nil {
return err
}
var assembled strings.Builder
for _, seg := range res.Segments {
if seg == nil {
continue
}
txt := strings.TrimSpace(seg.Text)
if txt == "" {
continue
}
delta := txt
if assembled.Len() > 0 {
delta = " " + txt
}
results <- &pb.TranscriptStreamResponse{Delta: delta}
assembled.WriteString(delta)
}
final := pb.TranscriptResult{
Segments: res.Segments,
Duration: res.Duration,
Language: res.Language,
Text: assembled.String(),
}
results <- &pb.TranscriptStreamResponse{FinalResult: &final}
return nil
}

View File

@@ -0,0 +1,49 @@
package main
// Started internally by LocalAI - one gRPC server per loaded model.
import (
"flag"
"os"
"github.com/ebitengine/purego"
grpc "github.com/mudler/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
type LibFuncs struct {
FuncPtr any
Name string
}
func main() {
libName := os.Getenv("VIBEVOICECPP_LIBRARY")
if libName == "" {
libName = "./libgovibevoicecpp-fallback.so"
}
lib, err := purego.Dlopen(libName, purego.RTLD_NOW|purego.RTLD_GLOBAL)
if err != nil {
panic(err)
}
libFuncs := []LibFuncs{
{&CppLoad, "vv_capi_load"},
{&CppTTS, "vv_capi_tts"},
{&CppASR, "vv_capi_asr"},
{&CppUnload, "vv_capi_unload"},
{&CppVersion, "vv_capi_version"},
}
for _, lf := range libFuncs {
purego.RegisterLibFunc(lf.FuncPtr, lib, lf.Name)
}
flag.Parse()
if err := grpc.StartServer(*addr, &VibevoiceCpp{}); err != nil {
panic(err)
}
}

View File

@@ -0,0 +1,58 @@
#!/bin/bash
# Bundle the vibevoice-cpp binary, the per-variant .so files, and the
# runtime libs the binary depends on so the package is self-contained.
# Mirrors backend/go/qwen3-tts-cpp/package.sh.
set -e
CURDIR=$(dirname "$(realpath $0)")
REPO_ROOT="${CURDIR}/../../.."
mkdir -p $CURDIR/package/lib
cp -avf $CURDIR/vibevoice-cpp $CURDIR/package/
cp -fv $CURDIR/libgovibevoicecpp-*.so $CURDIR/package/
cp -fv $CURDIR/run.sh $CURDIR/package/
# Detect architecture and copy appropriate libraries
if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
echo "Detected x86_64 architecture, copying x86_64 libraries..."
cp -arfLv /lib64/ld-linux-x86-64.so.2 $CURDIR/package/lib/ld.so
cp -arfLv /lib/x86_64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/x86_64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
cp -arfLv /lib/x86_64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
cp -arfLv /lib/x86_64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
cp -arfLv /lib/x86_64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
echo "Detected ARM64 architecture, copying ARM64 libraries..."
cp -arfLv /lib/ld-linux-aarch64.so.1 $CURDIR/package/lib/ld.so
cp -arfLv /lib/aarch64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/aarch64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
cp -arfLv /lib/aarch64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
cp -arfLv /lib/aarch64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
cp -arfLv /lib/aarch64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
elif [ $(uname -s) = "Darwin" ]; then
echo "Detected Darwin"
else
echo "Error: Could not detect architecture"
exit 1
fi
# Package GPU libraries based on BUILD_TYPE
GPU_LIB_SCRIPT="${REPO_ROOT}/scripts/build/package-gpu-libs.sh"
if [ -f "$GPU_LIB_SCRIPT" ]; then
echo "Packaging GPU libraries for BUILD_TYPE=${BUILD_TYPE:-cpu}..."
source "$GPU_LIB_SCRIPT" "$CURDIR/package/lib"
package_gpu_libs
fi
echo "Packaging completed successfully"
ls -liah $CURDIR/package/
ls -liah $CURDIR/package/lib/

49
backend/go/vibevoice-cpp/run.sh Executable file
View File

@@ -0,0 +1,49 @@
#!/bin/bash
set -ex
CURDIR=$(dirname "$(realpath $0)")
cd /
echo "CPU info:"
if [ "$(uname)" != "Darwin" ]; then
grep -e "model\sname" /proc/cpuinfo | head -1
grep -e "flags" /proc/cpuinfo | head -1
fi
LIBRARY="$CURDIR/libgovibevoicecpp-fallback.so"
if [ "$(uname)" != "Darwin" ]; then
if grep -q -e "\savx\s" /proc/cpuinfo ; then
echo "CPU: AVX found OK"
if [ -e $CURDIR/libgovibevoicecpp-avx.so ]; then
LIBRARY="$CURDIR/libgovibevoicecpp-avx.so"
fi
fi
if grep -q -e "\savx2\s" /proc/cpuinfo ; then
echo "CPU: AVX2 found OK"
if [ -e $CURDIR/libgovibevoicecpp-avx2.so ]; then
LIBRARY="$CURDIR/libgovibevoicecpp-avx2.so"
fi
fi
if grep -q -e "\savx512f\s" /proc/cpuinfo ; then
echo "CPU: AVX512F found OK"
if [ -e $CURDIR/libgovibevoicecpp-avx512.so ]; then
LIBRARY="$CURDIR/libgovibevoicecpp-avx512.so"
fi
fi
fi
export LD_LIBRARY_PATH=$CURDIR/lib:$LD_LIBRARY_PATH
export VIBEVOICECPP_LIBRARY=$LIBRARY
if [ -f $CURDIR/lib/ld.so ]; then
echo "Using lib/ld.so"
echo "Using library: $LIBRARY"
exec $CURDIR/lib/ld.so $CURDIR/vibevoice-cpp "$@"
fi
echo "Using library: $LIBRARY"
exec $CURDIR/vibevoice-cpp "$@"

View File

@@ -0,0 +1,74 @@
#!/bin/bash
set -e
CURDIR=$(dirname "$(realpath $0)")
echo "Running vibevoice-cpp backend tests..."
# Required env-vars (set automatically when missing):
# VIBEVOICE_MODEL_DIR : directory containing the gguf bundle.
# VIBEVOICE_BINARY : path to the built backend (default ./vibevoice-cpp)
#
# Tests skip when the model bundle is absent and the auto-download
# fails (e.g. no network on the runner) so local devs without HF access
# still get green compile output.
cd "$CURDIR"
if [ -z "$VIBEVOICE_MODEL_DIR" ]; then
export VIBEVOICE_MODEL_DIR="./vibevoice-models"
if [ ! -d "$VIBEVOICE_MODEL_DIR" ]; then
echo "Creating vibevoice-models directory for tests..."
mkdir -p "$VIBEVOICE_MODEL_DIR"
REPO_ID="mudler/vibevoice.cpp-models"
echo "Repository: ${REPO_ID}"
# Q4_K instead of Q8_0 for the ASR model: smaller download
# (10 GB vs 14 GB), fits on ubuntu-latest's free disk after the
# runner image is loaded. The unit/closed-loop test only needs
# decode quality, not Q8_0 precision.
FILES=(
"vibevoice-realtime-0.5B-q8_0.gguf"
"vibevoice-asr-q4_k.gguf"
"tokenizer.gguf"
"voice-en-Carter_man.gguf"
)
BASE_URL="https://huggingface.co/${REPO_ID}/resolve/main"
download_ok=1
for file in "${FILES[@]}"; do
dest="${VIBEVOICE_MODEL_DIR}/${file}"
if [ -f "${dest}" ]; then
echo " [skip] ${file} (already exists)"
else
echo " [download] ${file}..."
if ! curl -fL -o "${dest}" "${BASE_URL}/${file}" --progress-bar; then
echo " [warn] failed to download ${file} - network or HF unavailable"
rm -f "${dest}"
download_ok=0
break
fi
echo " [done] ${file}"
fi
done
if [ "$download_ok" != "1" ]; then
echo "vibevoice-cpp: model bundle unavailable - tests will skip model-dependent cases."
unset VIBEVOICE_MODEL_DIR
fi
fi
fi
# Ensure the per-variant .so the binary will dlopen actually exists -
# without one, every test will hit a Dlopen panic during server start.
if [ ! -f "${CURDIR}/libgovibevoicecpp-fallback.so" ]; then
echo "vibevoice-cpp: libgovibevoicecpp-fallback.so missing - run \`make\` first."
exit 1
fi
go test -v -timeout 900s .
echo "All vibevoice-cpp tests passed."

View File

@@ -0,0 +1,382 @@
package main
import (
"context"
"os"
"os/exec"
"path/filepath"
"regexp"
"strings"
"testing"
"time"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"google.golang.org/grpc"
"google.golang.org/grpc/credentials/insecure"
)
const (
testAddr = "localhost:50098"
startupWait = 5 * time.Second
)
func TestVibevoiceCpp(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "VibeVoice-cpp Backend Suite")
}
// modelDirOrSkip returns the staged model bundle dir, or Skip()s the
// current spec when VIBEVOICE_MODEL_DIR is unset / lacks the gguf
// files we need. Tests that don't depend on a model (Locking, error
// paths) don't call this.
func modelDirOrSkip() string {
dir := os.Getenv("VIBEVOICE_MODEL_DIR")
if dir == "" {
Skip("VIBEVOICE_MODEL_DIR not set, skipping model-dependent specs")
}
if _, err := os.Stat(filepath.Join(dir, "tokenizer.gguf")); os.IsNotExist(err) {
Skip("tokenizer.gguf missing in " + dir)
}
tts, _ := filepath.Glob(filepath.Join(dir, "vibevoice-realtime-*.gguf"))
asr, _ := filepath.Glob(filepath.Join(dir, "vibevoice-asr-*.gguf"))
if len(tts) == 0 && len(asr) == 0 {
Skip("neither realtime TTS nor ASR gguf found in " + dir)
}
return dir
}
// startServer launches the prebuilt backend binary and returns a
// running *exec.Cmd. test.sh ensures `./vibevoice-cpp` is built; if
// it isn't, every gRPC spec is skipped with a clear reason.
func startServer() *exec.Cmd {
binary := os.Getenv("VIBEVOICE_BINARY")
if binary == "" {
binary = "./vibevoice-cpp"
}
if _, err := os.Stat(binary); os.IsNotExist(err) {
Skip("backend binary not found at " + binary)
}
cmd := exec.Command(binary, "--addr", testAddr)
cmd.Stdout = os.Stderr
cmd.Stderr = os.Stderr
Expect(cmd.Start()).To(Succeed())
time.Sleep(startupWait)
return cmd
}
func stopServer(cmd *exec.Cmd) {
if cmd == nil || cmd.Process == nil {
return
}
_ = cmd.Process.Kill()
_, _ = cmd.Process.Wait()
}
func dialGRPC() *grpc.ClientConn {
conn, err := grpc.Dial(testAddr,
grpc.WithTransportCredentials(insecure.NewCredentials()),
grpc.WithDefaultCallOptions(
grpc.MaxCallRecvMsgSize(50*1024*1024),
grpc.MaxCallSendMsgSize(50*1024*1024),
),
)
Expect(err).ToNot(HaveOccurred())
return conn
}
var _ = Describe("VibeVoice-cpp", func() {
Context("backend semantics (no purego load needed)", func() {
It("is locking - the engine has process-global state", func() {
Expect((&VibevoiceCpp{}).Locking()).To(BeTrue())
})
It("rejects Load with empty ModelFile", func() {
err := (&VibevoiceCpp{}).Load(&pb.ModelOptions{})
Expect(err).To(HaveOccurred())
Expect(err.Error()).To(ContainSubstring("ModelFile"))
})
It("rejects TTS without a loaded TTS model", func() {
err := (&VibevoiceCpp{}).TTS(&pb.TTSRequest{
Text: "no model loaded",
Dst: "/tmp/should-not-be-written.wav",
})
Expect(err).To(HaveOccurred())
})
It("rejects AudioTranscription without a loaded ASR model", func() {
_, err := (&VibevoiceCpp{}).AudioTranscription(&pb.TranscriptRequest{
Dst: "/tmp/some.wav",
})
Expect(err).To(HaveOccurred())
})
It("closes the channel and errors on TTSStream without a loaded model", func() {
ch := make(chan []byte, 4)
err := (&VibevoiceCpp{}).TTSStream(&pb.TTSRequest{
Text: "no model loaded",
Dst: "/tmp/should-not-be-written.wav",
}, ch)
Expect(err).To(HaveOccurred())
// Server hangs forever if the channel stays open; this guard
// is what regresses the e2e DeadlineExceeded we're fixing.
_, ok := <-ch
Expect(ok).To(BeFalse(), "TTSStream must close results channel even on error")
})
// parseOptions + slot fill is the source of the closed-loop CI
// regression where ModelFile=tts.gguf + Options[asr_model=...]
// resulted in a load with empty tts slot. These specs assert
// the slot resolution before we ever call into purego.
Describe("ModelFile slot resolution", func() {
It("fills tts slot from ModelFile when only asr_model is in Options", func() {
v := &VibevoiceCpp{}
v.modelRoot = "/abs/root"
role := v.parseOptions([]string{"asr_model=/abs/root/asr.gguf", "tokenizer=/abs/root/tokenizer.gguf"}, v.modelRoot)
Expect(v.asrModel).To(Equal("/abs/root/asr.gguf"))
Expect(v.ttsModel).To(BeEmpty())
Expect(role).To(BeEmpty())
// Mirror the Load() default-fill block:
if v.ttsModel == "" {
v.ttsModel = "/abs/root/tts.gguf"
}
Expect(v.ttsModel).To(Equal("/abs/root/tts.gguf"))
Expect(v.asrModel).To(Equal("/abs/root/asr.gguf"))
})
It("fills asr slot from ModelFile when type=asr is set", func() {
v := &VibevoiceCpp{}
v.modelRoot = "/abs/root"
role := v.parseOptions([]string{"type=asr", "tokenizer=/abs/root/tokenizer.gguf"}, v.modelRoot)
Expect(role).To(Equal("asr"))
Expect(v.asrModel).To(BeEmpty())
Expect(v.ttsModel).To(BeEmpty())
})
It("respects explicit tts_model override over ModelFile", func() {
v := &VibevoiceCpp{}
v.modelRoot = "/abs/root"
_ = v.parseOptions([]string{"tts_model=/abs/root/alt.gguf"}, v.modelRoot)
Expect(v.ttsModel).To(Equal("/abs/root/alt.gguf"))
})
It("accepts colon-separated options too", func() {
v := &VibevoiceCpp{}
v.modelRoot = "/abs/root"
role := v.parseOptions([]string{"type:asr", "tokenizer:/abs/root/tokenizer.gguf"}, v.modelRoot)
Expect(role).To(Equal("asr"))
Expect(v.tokenizer).To(Equal("/abs/root/tokenizer.gguf"))
})
})
// The gallery flow puts everything under <models_dir>/<entry>/,
// and parameters/options carry paths *relative* to <models_dir>.
// LocalAI core fills opts.ModelPath = <models_dir>; the backend
// must resolve every relative path against that root, never CWD.
Describe("resolvePath (relative-to-modelRoot)", func() {
It("joins relative path onto relTo", func() {
Expect(resolvePath("vibevoice-cpp/tokenizer.gguf", "/data/models")).
To(Equal("/data/models/vibevoice-cpp/tokenizer.gguf"))
})
It("passes absolute paths through unchanged", func() {
Expect(resolvePath("/abs/somewhere/tokenizer.gguf", "/data/models")).
To(Equal("/abs/somewhere/tokenizer.gguf"))
})
It("returns input unchanged when relTo is empty", func() {
Expect(resolvePath("vibevoice-cpp/tokenizer.gguf", "")).
To(Equal("vibevoice-cpp/tokenizer.gguf"))
})
It("returns empty input unchanged", func() {
Expect(resolvePath("", "/data/models")).To(BeEmpty())
})
It("does not consult CWD - bare filenames stay relative to modelRoot", func() {
// Even if the test runs in a directory containing a
// file with this name, the lookup must not fall back
// to CWD. This is the trap the production gallery flow
// would otherwise hit when LocalAI is launched from a
// directory that happens to contain a same-named file.
prev, _ := os.Getwd()
DeferCleanup(func() { _ = os.Chdir(prev) })
tmpCWD, err := os.MkdirTemp("", "vv-cwd-*")
Expect(err).ToNot(HaveOccurred())
DeferCleanup(func() { _ = os.RemoveAll(tmpCWD) })
Expect(os.WriteFile(filepath.Join(tmpCWD, "tokenizer.gguf"),
[]byte("not the real one"), 0o644)).To(Succeed())
Expect(os.Chdir(tmpCWD)).To(Succeed())
got := resolvePath("tokenizer.gguf", "/data/models")
Expect(got).To(Equal("/data/models/tokenizer.gguf"))
})
})
// Round-trip the gallery layout: relative paths in Options +
// an absolute ModelFile (as LocalAI core delivers them) end
// up resolved correctly inside the backend struct.
It("Load resolves relative Options paths against opts.ModelPath", func() {
tmpDir, err := os.MkdirTemp("", "vv-relpath-*")
Expect(err).ToNot(HaveOccurred())
DeferCleanup(func() { _ = os.RemoveAll(tmpDir) })
// Lay out the bundle exactly as the gallery would after install:
// <modelpath>/vibevoice-cpp/{tts,tokenizer,voice}.gguf
subDir := filepath.Join(tmpDir, "vibevoice-cpp")
Expect(os.MkdirAll(subDir, 0o755)).To(Succeed())
tts := filepath.Join(subDir, "vibevoice-realtime-stub.gguf")
tok := filepath.Join(subDir, "tokenizer.gguf")
voice := filepath.Join(subDir, "voice.gguf")
for _, p := range []string{tts, tok, voice} {
Expect(os.WriteFile(p, []byte("stub"), 0o644)).To(Succeed())
}
// Mirror Load()'s pre-purego prefix: parse + slot fill.
v := &VibevoiceCpp{}
modelFile := tts // core delivers this as an abspath already
v.modelRoot = tmpDir
role := v.parseOptions([]string{
"tokenizer=vibevoice-cpp/tokenizer.gguf",
"voice=vibevoice-cpp/voice.gguf",
}, v.modelRoot)
Expect(role).To(BeEmpty())
if v.ttsModel == "" {
v.ttsModel = modelFile
}
Expect(v.ttsModel).To(Equal(tts))
Expect(v.tokenizer).To(Equal(tok))
Expect(v.voice).To(Equal(voice))
Expect(v.asrModel).To(BeEmpty())
})
It("closes the channel and errors on AudioTranscriptionStream without a loaded model", func() {
ch := make(chan *pb.TranscriptStreamResponse, 4)
err := (&VibevoiceCpp{}).AudioTranscriptionStream(&pb.TranscriptRequest{
Dst: "/tmp/some.wav",
}, ch)
Expect(err).To(HaveOccurred())
_, ok := <-ch
Expect(ok).To(BeFalse(), "AudioTranscriptionStream must close results channel even on error")
})
})
Context("gRPC server lifecycle", func() {
var cmd *exec.Cmd
AfterEach(func() {
stopServer(cmd)
cmd = nil
})
It("answers Health checks", func() {
cmd = startServer()
conn := dialGRPC()
defer func() { _ = conn.Close() }()
resp, err := pb.NewBackendClient(conn).Health(context.Background(), &pb.HealthMessage{})
Expect(err).ToNot(HaveOccurred())
Expect(string(resp.Message)).To(Equal("OK"))
})
It("loads the realtime TTS model", func() {
dir := modelDirOrSkip()
tts, _ := filepath.Glob(filepath.Join(dir, "vibevoice-realtime-*.gguf"))
if len(tts) == 0 {
Skip("realtime TTS gguf missing")
}
cmd = startServer()
conn := dialGRPC()
defer func() { _ = conn.Close() }()
// Mirror the gallery contract: ModelFile is whatever LocalAI
// core hands us; ModelPath is the models root; Options[]
// carry paths relative to ModelPath.
resp, err := pb.NewBackendClient(conn).LoadModel(context.Background(), &pb.ModelOptions{
ModelFile: filepath.Base(tts[0]),
ModelPath: dir,
Threads: 4,
Options: []string{"tokenizer=tokenizer.gguf"},
})
Expect(err).ToNot(HaveOccurred())
Expect(resp.Success).To(BeTrue(), "LoadModel msg=%q", resp.Message)
})
It("runs a closed-loop TTS -> ASR with >=80% word recall", func() {
dir := modelDirOrSkip()
tts, _ := filepath.Glob(filepath.Join(dir, "vibevoice-realtime-*.gguf"))
asr, _ := filepath.Glob(filepath.Join(dir, "vibevoice-asr-*.gguf"))
if len(tts) == 0 || len(asr) == 0 {
Skip("closed-loop needs both realtime TTS and ASR ggufs")
}
tmpDir, err := os.MkdirTemp("", "vibevoice-cpp-closedloop-*")
Expect(err).ToNot(HaveOccurred())
DeferCleanup(func() { _ = os.RemoveAll(tmpDir) })
wav := filepath.Join(tmpDir, "say.wav")
cmd = startServer()
conn := dialGRPC()
defer func() { _ = conn.Close() }()
client := pb.NewBackendClient(conn)
// Gallery convention: ModelPath is the models root, every
// path inside Options[] is relative to it.
voiceMatches, _ := filepath.Glob(filepath.Join(dir, "voice-*.gguf"))
loadOpts := &pb.ModelOptions{
ModelFile: filepath.Base(tts[0]),
ModelPath: dir,
Threads: 4,
Options: []string{
"asr_model=" + filepath.Base(asr[0]),
"tokenizer=tokenizer.gguf",
},
}
if len(voiceMatches) > 0 {
loadOpts.Options = append(loadOpts.Options, "voice="+filepath.Base(voiceMatches[0]))
}
loadResp, err := client.LoadModel(context.Background(), loadOpts)
Expect(err).ToNot(HaveOccurred())
Expect(loadResp.Success).To(BeTrue(), "LoadModel msg=%q", loadResp.Message)
srcText := "Hello world this is a test of the synthesis system."
_, err = client.TTS(context.Background(), &pb.TTSRequest{
Text: srcText,
Dst: wav,
})
Expect(err).ToNot(HaveOccurred())
info, err := os.Stat(wav)
Expect(err).ToNot(HaveOccurred())
Expect(info.Size()).To(BeNumerically(">=", 1000),
"TTS produced suspiciously small wav (%d bytes)", info.Size())
resp, err := client.AudioTranscription(context.Background(), &pb.TranscriptRequest{
Dst: wav,
})
Expect(err).ToNot(HaveOccurred())
got := strings.ToLower(resp.Text)
GinkgoWriter.Printf("source : %s\n", srcText)
GinkgoWriter.Printf("transcribed: %s\n", got)
wordRE := regexp.MustCompile(`[a-z]+`)
srcWords := wordRE.FindAllString(strings.ToLower(srcText), -1)
Expect(srcWords).ToNot(BeEmpty())
hits := 0
for _, w := range srcWords {
if strings.Contains(got, w) {
hits++
}
}
recall := float64(hits) / float64(len(srcWords))
GinkgoWriter.Printf("recall: %d/%d = %.2f%%\n", hits, len(srcWords), recall*100)
Expect(recall).To(BeNumerically(">=", 0.80),
"closed-loop recall too low: %d/%d = %.2f%%",
hits, len(srcWords), recall*100)
})
})
})

View File

@@ -5,7 +5,7 @@ set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
add_subdirectory(./sources/whisper.cpp)
add_library(gowhisper MODULE gowhisper.cpp)
add_library(gowhisper MODULE cpp/gowhisper.cpp)
target_link_libraries(gowhisper PRIVATE whisper ggml)
if(CMAKE_CXX_COMPILER_ID MATCHES "GNU" AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 9.0)

View File

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
# whisper.cpp version
WHISPER_REPO?=https://github.com/ggml-org/whisper.cpp
WHISPER_CPP_VERSION?=fc674574ca27cac59a15e5b22a09b9d9ad62aafe
WHISPER_CPP_VERSION?=4bf733672b2871d4153158af4f621a6dd9104f4a
SO_TARGET?=libgowhisper.so
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
@@ -111,7 +111,7 @@ libgowhisper-fallback.so: sources/whisper.cpp
SO_TARGET=libgowhisper-fallback.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" $(MAKE) libgowhisper-custom
rm -rfv build*
libgowhisper-custom: CMakeLists.txt gowhisper.cpp gowhisper.h
libgowhisper-custom: CMakeLists.txt cpp/gowhisper.cpp cpp/gowhisper.h
mkdir -p build-$(SO_TARGET) && \
cd build-$(SO_TARGET) && \
cmake .. $(CMAKE_ARGS) && \

View File

@@ -139,7 +139,10 @@ func (w *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptR
// segment start/end conversion factor taken from https://github.com/ggml-org/whisper.cpp/blob/master/examples/cli/cli.cpp#L895
s := CppGetSegmentStart(i) * (10000000)
t := CppGetSegmentEnd(i) * (10000000)
txt := strings.Clone(CppGetSegmentText(i))
// whisper.cpp can emit bytes that aren't valid UTF-8 (e.g. a multibyte
// codepoint split across token boundaries); protobuf string fields
// reject those at marshal time. Scrub before the value escapes cgo.
txt := strings.ToValidUTF8(strings.Clone(CppGetSegmentText(i)), "<22>")
tokens := make([]int32, CppNTokens(i))
if opts.Diarize && CppGetSegmentSpeakerTurnNext(i) {

View File

@@ -263,6 +263,8 @@
amd: "rocm-vllm"
intel: "intel-vllm"
nvidia-cuda-12: "cuda12-vllm"
nvidia-cuda-13: "cuda13-vllm"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-vllm"
cpu: "cpu-vllm"
- &sglang
name: "sglang"
@@ -285,6 +287,7 @@
amd: "rocm-sglang"
intel: "intel-sglang"
nvidia-cuda-12: "cuda12-sglang"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-sglang"
cpu: "cpu-sglang"
- &vllm-omni
name: "vllm-omni"
@@ -311,6 +314,8 @@
nvidia: "cuda12-vllm-omni"
amd: "rocm-vllm-omni"
nvidia-cuda-12: "cuda12-vllm-omni"
nvidia-cuda-13: "cuda13-vllm-omni"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-vllm-omni"
- &mlx
name: "mlx"
uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-mlx"
@@ -567,6 +572,66 @@
nvidia-l4t: "nvidia-l4t-arm64-qwen3-tts-cpp"
nvidia-l4t-cuda-12: "nvidia-l4t-arm64-qwen3-tts-cpp"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-qwen3-tts-cpp"
- &vibevoicecpp
name: "vibevoice-cpp"
description: |
vibevoice.cpp C++ backend using GGML. Native C++ port of Microsoft VibeVoice for both
text-to-speech (with voice cloning via voice prompt GGUFs) and long-form ASR with
speaker diarization. Outputs 24kHz mono WAV; ASR returns per-speaker JSON segments.
urls:
- https://github.com/mudler/vibevoice.cpp
tags:
- text-to-speech
- tts
- speech-to-text
- asr
- voice-cloning
- diarization
alias: "vibevoice-cpp"
capabilities:
default: "cpu-vibevoice-cpp"
nvidia: "cuda12-vibevoice-cpp"
nvidia-cuda-13: "cuda13-vibevoice-cpp"
nvidia-cuda-12: "cuda12-vibevoice-cpp"
intel: "intel-sycl-f16-vibevoice-cpp"
metal: "metal-vibevoice-cpp"
amd: "rocm-vibevoice-cpp"
vulkan: "vulkan-vibevoice-cpp"
nvidia-l4t: "nvidia-l4t-arm64-vibevoice-cpp"
nvidia-l4t-cuda-12: "nvidia-l4t-arm64-vibevoice-cpp"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-vibevoice-cpp"
- &localvqecpp
name: "localvqe"
description: |
LocalVQE C++ backend using GGML — joint acoustic echo cancellation, noise
suppression, and dereverberation (DeepVQE-style architecture). 16 kHz mono
in / out, supports both batch and low-latency streaming. Implements the
audio-transform capability.
urls:
- https://github.com/localai-org/LocalVQE
tags:
- audio-transform
- aec
- acoustic-echo-cancellation
- noise-suppression
- dereverberation
license: apache2
alias: "localvqe"
# Upstream LocalVQE only supports CPU and Vulkan; no CUDA/ROCm/SYCL/Metal
# builds. GPU-class hardware that exposes a Vulkan ICD (NVIDIA, AMD, Intel
# discrete + iGPU, Tegra) routes to the Vulkan image; everything else
# falls back to the CPU build, which is already ~9× realtime on a desktop.
capabilities:
default: "cpu-localvqe"
nvidia: "vulkan-localvqe"
nvidia-cuda-12: "vulkan-localvqe"
nvidia-cuda-13: "vulkan-localvqe"
intel: "vulkan-localvqe"
amd: "vulkan-localvqe"
vulkan: "vulkan-localvqe"
nvidia-l4t: "vulkan-localvqe"
nvidia-l4t-cuda-12: "vulkan-localvqe"
nvidia-l4t-cuda-13: "vulkan-localvqe"
- &faster-whisper
icon: https://avatars.githubusercontent.com/u/1520500?s=200&v=4
description: |
@@ -1006,6 +1071,23 @@
nvidia: "cuda12-neutts"
amd: "rocm-neutts"
nvidia-cuda-12: "cuda12-neutts"
- &sherpa-onnx
name: "sherpa-onnx"
alias: "sherpa-onnx"
urls:
- https://k2-fsa.github.io/sherpa/onnx/
description: |
Sherpa-ONNX backend for text-to-speech (VITS, Matcha, Kokoro), speech-to-text (Whisper, Paraformer, SenseVoice, Omnilingual ASR CTC), and voice activity detection via ONNX Runtime.
Supports multi-speaker voices, 1600+ language ASR, and GPU acceleration.
tags:
- text-to-speech
- TTS
- speech-to-text
- ASR
capabilities:
default: "cpu-sherpa-onnx"
nvidia: "cuda12-sherpa-onnx"
nvidia-cuda-12: "cuda12-sherpa-onnx"
- !!merge <<: *neutts
name: "neutts-development"
capabilities:
@@ -1591,6 +1673,20 @@
mirrors:
- localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-turboquant
## whisper
- !!merge <<: *whispercpp
name: "whisper-development"
capabilities:
default: "cpu-whisper-development"
nvidia: "cuda12-whisper-development"
intel: "intel-sycl-f16-whisper-development"
metal: "metal-whisper-development"
amd: "rocm-whisper-development"
vulkan: "vulkan-whisper-development"
nvidia-l4t: "nvidia-l4t-arm64-whisper-development"
nvidia-cuda-13: "cuda13-whisper-development"
nvidia-cuda-12: "cuda12-whisper-development"
nvidia-l4t-cuda-12: "nvidia-l4t-arm64-whisper-development"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-whisper-development"
- !!merge <<: *whispercpp
name: "nvidia-l4t-arm64-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-whisper"
@@ -1797,12 +1893,25 @@
nvidia: "cuda12-vllm-development"
amd: "rocm-vllm-development"
intel: "intel-vllm-development"
nvidia-cuda-12: "cuda12-vllm-development"
nvidia-cuda-13: "cuda13-vllm-development"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-vllm-development"
cpu: "cpu-vllm-development"
- !!merge <<: *vllm
name: "cuda12-vllm"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-vllm"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-vllm
- !!merge <<: *vllm
name: "cuda13-vllm"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-vllm"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-13-vllm
- !!merge <<: *vllm
name: "cuda13-nvidia-l4t-arm64-vllm"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-vllm"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-cuda-13-arm64-vllm
- !!merge <<: *vllm
name: "rocm-vllm"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-vllm"
@@ -1823,6 +1932,16 @@
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-vllm"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-vllm
- !!merge <<: *vllm
name: "cuda13-vllm-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-vllm"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-13-vllm
- !!merge <<: *vllm
name: "cuda13-nvidia-l4t-arm64-vllm-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-vllm"
mirrors:
- localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-vllm
- !!merge <<: *vllm
name: "rocm-vllm-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-vllm"
@@ -1845,12 +1964,19 @@
nvidia: "cuda12-sglang-development"
amd: "rocm-sglang-development"
intel: "intel-sglang-development"
nvidia-cuda-12: "cuda12-sglang-development"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-sglang-development"
cpu: "cpu-sglang-development"
- !!merge <<: *sglang
name: "cuda12-sglang"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-sglang"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-sglang
- !!merge <<: *sglang
name: "cuda13-nvidia-l4t-arm64-sglang"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-sglang"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-cuda-13-arm64-sglang
- !!merge <<: *sglang
name: "rocm-sglang"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-sglang"
@@ -1871,6 +1997,11 @@
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-sglang"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-sglang
- !!merge <<: *sglang
name: "cuda13-nvidia-l4t-arm64-sglang-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-sglang"
mirrors:
- localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-sglang
- !!merge <<: *sglang
name: "rocm-sglang-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-sglang"
@@ -1893,11 +2024,23 @@
nvidia: "cuda12-vllm-omni-development"
amd: "rocm-vllm-omni-development"
nvidia-cuda-12: "cuda12-vllm-omni-development"
nvidia-cuda-13: "cuda13-vllm-omni-development"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-vllm-omni-development"
- !!merge <<: *vllm-omni
name: "cuda12-vllm-omni"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-vllm-omni"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-vllm-omni
- !!merge <<: *vllm-omni
name: "cuda13-vllm-omni"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-vllm-omni"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-13-vllm-omni
- !!merge <<: *vllm-omni
name: "cuda13-nvidia-l4t-arm64-vllm-omni"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-vllm-omni"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-cuda-13-arm64-vllm-omni
- !!merge <<: *vllm-omni
name: "rocm-vllm-omni"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-vllm-omni"
@@ -1908,6 +2051,16 @@
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-vllm-omni"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-vllm-omni
- !!merge <<: *vllm-omni
name: "cuda13-vllm-omni-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-vllm-omni"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-13-vllm-omni
- !!merge <<: *vllm-omni
name: "cuda13-nvidia-l4t-arm64-vllm-omni-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-vllm-omni"
mirrors:
- localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-vllm-omni
- !!merge <<: *vllm-omni
name: "rocm-vllm-omni-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-vllm-omni"
@@ -2563,6 +2716,128 @@
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-qwen3-tts-cpp"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-13-qwen3-tts-cpp
## vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "nvidia-l4t-arm64-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-arm64-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "nvidia-l4t-arm64-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-arm64-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-nvidia-l4t-arm64-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "cuda13-nvidia-l4t-arm64-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-cuda-13-arm64-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "cuda13-nvidia-l4t-arm64-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "cpu-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-cpu-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "metal-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-metal-darwin-arm64-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "metal-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-metal-darwin-arm64-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "cpu-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-cpu-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "cuda12-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "rocm-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "intel-sycl-f32-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f32-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "intel-sycl-f16-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f16-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "vulkan-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-vulkan-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-gpu-vulkan-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "vulkan-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-vulkan-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-gpu-vulkan-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "cuda12-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "rocm-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "intel-sycl-f32-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f32-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "intel-sycl-f16-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f16-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "cuda13-vibevoice-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-vibevoice-cpp"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-13-vibevoice-cpp
- !!merge <<: *vibevoicecpp
name: "cuda13-vibevoice-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-vibevoice-cpp"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-13-vibevoice-cpp
## localvqe
- !!merge <<: *localvqecpp
name: "cpu-localvqe"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-localvqe"
mirrors:
- localai/localai-backends:latest-cpu-localvqe
- !!merge <<: *localvqecpp
name: "cpu-localvqe-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-localvqe"
mirrors:
- localai/localai-backends:master-cpu-localvqe
- !!merge <<: *localvqecpp
name: "vulkan-localvqe"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-vulkan-localvqe"
mirrors:
- localai/localai-backends:latest-gpu-vulkan-localvqe
- !!merge <<: *localvqecpp
name: "vulkan-localvqe-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-vulkan-localvqe"
mirrors:
- localai/localai-backends:master-gpu-vulkan-localvqe
## kokoro
- !!merge <<: *kokoro
name: "kokoro-development"
@@ -3834,3 +4109,30 @@
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-speaker-recognition"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-speaker-recognition
## sherpa-onnx
- !!merge <<: *sherpa-onnx
name: "sherpa-onnx-development"
capabilities:
default: "cpu-sherpa-onnx-development"
nvidia: "cuda12-sherpa-onnx-development"
nvidia-cuda-12: "cuda12-sherpa-onnx-development"
- !!merge <<: *sherpa-onnx
name: "cpu-sherpa-onnx"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-sherpa-onnx"
mirrors:
- localai/localai-backends:latest-cpu-sherpa-onnx
- !!merge <<: *sherpa-onnx
name: "cpu-sherpa-onnx-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-sherpa-onnx"
mirrors:
- localai/localai-backends:master-cpu-sherpa-onnx
- !!merge <<: *sherpa-onnx
name: "cuda12-sherpa-onnx"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-sherpa-onnx"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-sherpa-onnx
- !!merge <<: *sherpa-onnx
name: "cuda12-sherpa-onnx-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-sherpa-onnx"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-sherpa-onnx

View File

@@ -318,6 +318,21 @@ _makeVenvPortable() {
}
# Apply the venv to the current process: VIRTUAL_ENV, PATH, PYTHONHOME hygiene.
# Equivalent to the runtime portion of `source bin/activate`, but computed from
# $EDIR (resolved at runtime via realpath) instead of the path baked into
# bin/activate at venv-create time. `uv venv` (and `python -m venv`) both bake
# the create-time absolute path in, so sourcing activate on a relocated venv —
# e.g. one built at /vllm/venv inside a Docker stage and unpacked under
# /backends/cuda13-vllm-development/venv at runtime — silently prepends a
# stale, non-existent path to $PATH. Doing the setup ourselves sidesteps that;
# this is the same approach `uv run` takes internally.
_activateVenv() {
export VIRTUAL_ENV="${EDIR}/venv"
export PATH="${EDIR}/venv/bin:${PATH}"
unset PYTHONHOME
}
# ensureVenv makes sure that the venv for the backend both exists, and is activated.
#
# This function is idempotent, so you can call it as many times as you want and it will
@@ -354,7 +369,7 @@ function ensureVenv() {
venv_args="--copies"
fi
"${interpreter}" -m venv ${venv_args} "${EDIR}/venv"
source "${EDIR}/venv/bin/activate"
_activateVenv
"${interpreter}" -m pip install --upgrade pip
else
if [ "x${PORTABLE_PYTHON}" == "xtrue" ]; then
@@ -375,7 +390,7 @@ function ensureVenv() {
fi
if [ "x${VIRTUAL_ENV:-}" != "x${EDIR}/venv" ]; then
source "${EDIR}/venv/bin/activate"
_activateVenv
fi
}

View File

@@ -1,4 +1,4 @@
grpcio==1.80.0
protobuf
certifi
packaging==24.1
packaging==26.2

View File

@@ -40,7 +40,19 @@ from diffusers import DiffusionPipeline, ControlNetModel
from diffusers import FluxPipeline, FluxTransformer2DModel, AutoencoderKLWan
from diffusers.pipelines.stable_diffusion import safety_checker
from diffusers.utils import load_image, export_to_video
from compel import Compel, ReturnedEmbeddingsType
# TODO: re-enable compel as a hard dependency once it supports transformers >= 5.
# Tracking upstream: https://github.com/damian0815/compel/pull/129
# and https://github.com/damian0815/compel/issues/128
# Until then compel pins transformers ~= 4.25, which forces the pip resolver into
# multi-hour backtracking storms in CI when DEPS_REFRESH rotates the cache.
# Keep the import optional and gate usage on the COMPEL env var (set COMPEL=1 to opt in).
try:
from compel import Compel, ReturnedEmbeddingsType
COMPEL_AVAILABLE = True
except ImportError:
Compel = None
ReturnedEmbeddingsType = None
COMPEL_AVAILABLE = False
from optimum.quanto import freeze, qfloat8, quantize
from transformers import T5EncoderModel
from safetensors.torch import load_file
@@ -66,6 +78,9 @@ from diffusers import LTX2VideoTransformer3DModel, GGUFQuantizationConfig
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
COMPEL = os.environ.get("COMPEL", "0") == "1"
if COMPEL and not COMPEL_AVAILABLE:
print("WARNING: COMPEL is enabled but the compel module is not installed. Install it manually (`pip install compel`) or unset COMPEL. Falling back to standard prompt processing.", file=sys.stderr)
COMPEL = False
SD_EMBED = os.environ.get("SD_EMBED", "0") == "1"
# Warn if SD_EMBED is enabled but the module is not available
if SD_EMBED and not SD_EMBED_AVAILABLE:

View File

@@ -4,10 +4,15 @@ opencv-python
transformers
torchvision==0.22.1
accelerate
compel
git+https://github.com/xhinker/sd_embed
peft
sentencepiece
torch==2.7.1
optimum-quanto
ftfy
ftfy
# TODO: re-add compel once it supports transformers >= 5.
# Tracking: https://github.com/damian0815/compel/pull/129
# https://github.com/damian0815/compel/issues/128
# compel currently pins transformers~=4.25, which forced pip into multi-hour
# resolver backtracking storms in CI. backend.py imports it lazily and gates
# the COMPEL=1 env var on the import succeeding, so dropping it here is safe.

Some files were not shown because too many files have changed in this diff Show More