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21 Commits

Author SHA1 Message Date
dependabot[bot]
738fe0f49d chore(deps): bump the pip group across 3 directories with 1 update
Bumps the pip group with 1 update in the /backend/python/sglang directory: torch.
Bumps the pip group with 1 update in the /backend/python/trl directory: torch.
Bumps the pip group with 1 update in the /backend/python/vllm-omni directory: torch.


Updates `torch` from 2.9.0 to 2.12.0+cpu

Updates `torch` from 2.10.0 to 2.12.0+cpu

Updates `torch` from 2.7.0 to 2.12.0+cu130

---
updated-dependencies:
- dependency-name: torch
  dependency-version: 2.12.0+cpu
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: torch
  dependency-version: 2.12.0+cpu
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: torch
  dependency-version: 2.12.0+cu130
  dependency-type: direct:production
  dependency-group: pip
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-06-28 09:54:23 +00:00
LocalAI [bot]
b7a1dec773 fix(kokoro): add explicit click dep so spacy CLI works on intel build (#10572)
The kokoro install.sh ends with `python -m spacy download en_core_web_sm`.
spaCy's CLI imports typer -> click, so click must be present at that point.

On the intel build profile, install.sh adds `--upgrade --index-strategy=unsafe-first-match`
against the Intel pip index. With that resolution strategy, click is not
resolved/installed, so the spacy CLI import fails with:

    ModuleNotFoundError: No module named 'click'
    make: *** [Makefile:3: kokoro] Error 1

Other profiles (cpu/cublas) pull click in transitively and build fine; only
the intel profile breaks. This surfaced in the v4.5.5 release CI as the
gpu-intel-kokoro backend image build failure.

Make click an explicit dependency in the base requirements.txt (installed for
every profile) so it is always present before `python -m spacy download` runs,
regardless of index resolution. Unpinned: spacy constrains the version.

Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-28 11:29:17 +02:00
LocalAI [bot]
de2ec2f136 feat(backends): add voice-detect + face-detect ggml backends (replace Python insightface/speaker-recognition) (#10441)
* feat(voice-detect): add Go purego backend for voice-detect.cpp

Add backend/go/voice-detect implementing the Backend gRPC voice subset
(VoiceEmbed/VoiceVerify/VoiceAnalyze) over libvoicedetect.so via purego,
mirroring the parakeet-cpp / omnivoice-cpp backends.

The flat voicedetect_capi C ABI is dlopen'd cgo-less; malloc'd string and
float-vector returns are owned by Go and released through the matching capi
free functions, with the per-ctx last error surfaced into Go errors. Calls are
serialized via base.SingleThread since the C context is not reentrant.

Proto field mapping:
- VoiceEmbed: VoiceEmbedRequest.audio (path) -> embed_path -> Embedding+Model.
- VoiceVerify: audio1/audio2 + threshold (<=0 falls back to the
  verify_threshold option, default 0.25) -> verify_paths -> verified/distance/
  threshold/confidence/model/processing_time_ms.
- VoiceAnalyze: audio (path) -> analyze_path_json; the JSON age/gender/emotion
  document maps to a single VoiceAnalysis segment (start/end 0; gender "label"
  -> dominant_gender with the remaining float scores as the gender map; emotion
  label/scores -> dominant_emotion/emotion).

The Makefile pins voice-detect.cpp to 47546430, clones+builds libvoicedetect.so
with ggml static-linked (PIC, GGML_NATIVE off) so dlopen needs no external
libggml/libvoicedetect; ldd on the artifact shows only system libs. Ginkgo
tests cover option parsing and analyze-JSON mapping; embed/verify smoke specs
gate on VOICEDETECT_BACKEND_TEST_MODEL + VOICEDETECT_BACKEND_TEST_WAV.

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

* feat(voice-detect): wire backend into index, gallery and build

Register the voice-detect.cpp speaker-recognition + voice-analysis
backend (added in Voice-INT-A) into LocalAI's distribution surfaces,
mirroring the ced backend (the closest mudler C++/ggml audio analogue):

- backend/index.yaml: add the &voicedetect meta-backend (capabilities
  platform map, no top-level uri) plus the full set of concrete per-arch
  image entries (cpu/cuda12/cuda13/metal/rocm/sycl/vulkan/l4t and the
  -development variants). Referential integrity audited - every alias
  target resolves.
- gallery/index.yaml: add 5 model entries on backend voice-detect -
  ECAPA-TDNN, WeSpeaker ResNet34, 3D-Speaker ERes2Net, CAM++ and the
  wav2vec2 age/gender/emotion analyze model. The engine architecture is
  read from GGUF metadata (voicedetect.arch) at load. GGUF artifacts are
  not yet published: each files: entry points at the intended
  mudler/voice-detect-gguf location with a TODO to fill sha256 after
  upload (no fabricated hashes).
- .github/backend-matrix.yml: add the linux build matrix block + the
  darwin metal entry mirroring ced.
- .github/workflows/bump_deps.yaml: track mudler/voice-detect.cpp via
  VOICEDETECT_VERSION (pin 47546430, = 4754643).
- core/config/backend_capabilities.go: register voice-detect in the
  backend capability map (VoiceVerify/VoiceEmbed/VoiceAnalyze ->
  speaker_recognition), mirroring speaker-recognition.

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

* feat(face-detect): add purego Go backend for face-detect.cpp

Add the LocalAI Go backend that dlopens libfacedetect.so (the flat
facedetect_capi_* C-ABI) via purego, mirroring the sibling voice-detect
backend. Implements the Face subset of the Backend gRPC service:

- Embeddings(PredictOptions): Images[0] base64 -> temp file -> embed_path
  -> L2-normalized ArcFace embedding.
- Detect(DetectOptions): src -> detect_path_json -> Detection boxes
  (class_name "face", [x1,y1,x2,y2] -> x/y/w/h).
- FaceVerify(FaceVerifyRequest): two images + threshold + anti_spoof ->
  verify_paths; best-effort img areas via detect.
- FaceAnalyze(FaceAnalyzeRequest): img -> analyze_path_json -> per-face
  age + gender ("M"/"F" normalized to "Man"/"Woman").

The Makefile pins face-detect.cpp to 636a1963 and builds the shared lib
with ggml + vendored libjpeg-turbo static (PIC), so the .so is
ldd-clean (no libggml) and exports only facedetect_capi_* (no jpeg_
symbols). Gated Ginkgo e2e mirrors voice-detect.

Note for the gallery-wiring task: backend registration (index.yaml,
gallery, core/config/backend_capabilities.go) is intentionally not
touched here.

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

* fix(voice-detect): replace em dashes in net-new descriptions

Project style forbids em/en dashes. Replace the three U+2014 chars
introduced by the voice-detect gallery/index wiring with `-`/`:`.

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

* feat(face-detect): wire backend into index, gallery and build

Register the face-detect.cpp face detection / embedding / verification /
analysis backend (added in Face-INT-A) into LocalAI's distribution
surfaces, mirroring the voice-detect wiring (the closest mudler C++/ggml
recognition analogue):

- backend/index.yaml: add the &facedetect meta-backend (capabilities
  platform map, no top-level uri to avoid the meta-backend gotcha) plus
  the full set of concrete per-arch image entries (cpu/cuda12/cuda13/
  metal/rocm/sycl-f16/sycl-f32/vulkan/l4t and the -development variants),
  22 entries. Referential integrity audited: every alias target resolves.
- gallery/index.yaml: add 4 model entries on backend face-detect -
  face-detect-buffalo-l/m/s (insightface SCRFD + ArcFace/MBF, NON-COMMERCIAL)
  and face-detect-yunet-sface (OpenCV-Zoo YuNet + SFace, APACHE-2.0, the
  commercial-friendly alternative). The detector/embedder architecture is
  read from GGUF metadata (facedetect.arch) at load; only the real
  verify_threshold option is set (0.35 buffalo, 0.363 sface). GGUF
  artifacts are not yet published: each files: entry points at the
  intended mudler/face-detect-gguf location with a TODO to fill sha256
  after upload (no fabricated hashes).
- core/config/backend_capabilities.go: register face-detect in the
  backend capability map (Embedding/Detect/FaceVerify/FaceAnalyze ->
  face_recognition), mirroring insightface.
- .github/backend-matrix.yml: add the linux build matrix block + the
  darwin metal entry mirroring voice-detect.
- .github/workflows/bump_deps.yaml: track mudler/face-detect.cpp via
  FACEDETECT_VERSION (pin 636a1963).

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

* fix(recon): voice-detect metal build branch + face-detect gallery usecases

Add the missing metal BUILD_TYPE branch to the voice-detect Makefile
forwarding -DVOICEDETECT_GGML_METAL=ON, mirroring face-detect, so the
darwin metal CI artifact is built with the Metal backend instead of
CPU-only.

Expand the 4 face-detect gallery models' known_usecases to
[face_recognition, detection, embeddings] to match the backend
capabilities map and the mirrored insightface-buffalo entries, so
auto-selection for /v1/detect and /embeddings works.

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

* docs(recon): document voice-detect and face-detect ggml backends

Document the new standalone C++/ggml biometric backends as the
recommended/default option for face and voice recognition, keeping the
existing Python insightface / speaker-recognition backends framed as the
legacy path.

- features/face-recognition.md: add a face-detect (ggml) backend section
  with the gallery entries (buffalo-l/m/s non-commercial, yunet-sface
  Apache-2.0), licensing, and verify/detect/analyze quickstart.
- features/voice-recognition.md: add a voice-detect (ggml) backend
  section with the gallery entries (ecapa-tdnn, wespeaker-resnet34,
  eres2net, campplus speaker recognizers; emotion-wav2vec2 non-commercial
  analyze head) and quickstart.
- reference/compatibility-table.md: add face-detect.cpp and
  voice-detect.cpp rows to the Vision, Detection & Recognition table.

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

* chore(gallery): publish recon backend GGUF uris + sha256

Fill in the published HuggingFace GGUF uris and verified sha256 for the
9 recon gallery entries (voice-detect-* and face-detect-*), and remove
the TODO publish markers. Correct the eres2net, campplus, and
emotion-wav2vec2 uris to the actual published filenames.

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

* feat(gallery): re-embed buffalo anti-spoof + add audeering age/gender voice model

Update the 3 buffalo face-detect GGUF sha256 (anti-spoof ensemble now
embedded and re-uploaded under the same filenames/uris) and note the
FaceVerify anti_spoof request flag in each description. Add a new
voice-detect-age-gender-wav2vec2 gallery entry mirroring the emotion
model.

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

* feat(gallery): add face-detect-buffalo-sc and antelopev2 packs

Add gallery entries for two newly-published insightface face packs on
the face-detect backend: buffalo_sc (smallest pack, SCRFD-500M + small
ArcFace) and antelopev2 (higher-accuracy, SCRFD-10G + ArcFace glint360k
R100, 512-d). Both are non-commercial research-only.

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

* feat(recon): honor LocalAI per-model threads in voice/face-detect backends

LocalAI spawns one backend process per model and serves requests
concurrently, so the engines' own min(hardware_concurrency, 8) default
can oversubscribe cores. Forward the per-model Threads value from the
gRPC LoadModel options into the engine via VOICEDETECT_THREADS /
FACEDETECT_THREADS (read at backend construction) before the capi load.
A non-positive Threads is treated as unset, leaving the engine default.

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

* chore(recon): bump backend pins to CPU-optimized engine commits

voice-detect.cpp -> 0d9c1b3 (radix-2 FFT FBank, threads, flash attn + cached
pos-conv); face-detect.cpp -> 523aee1 (thread-gated direct conv, threads).
Brings the CPU optimizations into the LocalAI backend builds. GGUF format and
parity unchanged, so the published HF GGUFs remain valid.

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

* chore(recon): bump backend pins to round-2 CPU-optimized engines

voice-detect.cpp -> fe7e6a3 (ERes2Net 1x1->mul_mat, CAM++ layout+context,
wav2vec2 conv-LN, ECAPA capture-drop, AVX512 dispatch opt-in); face-detect.cpp
-> 9c8adb7 (AVX2 Winograd F(2x2,3x3) for SCRFD/ArcFace 3x3 convs, ArcFace
BN-fold). Parity unchanged (cosine=1.0); GGUF format unchanged, HF GGUFs valid.

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

* chore(recon): bump backend pins to round-3 Winograd engines

voice-detect.cpp -> 45122ec (Winograd F(2x2,3x3) for WeSpeaker/ERes2Net 3x3
convs, -22%/-20% @8t); face-detect.cpp -> cd5c962 (Winograd F(4x4,3x3) for
SCRFD large maps, -22% @1t on top of F(2x2), more load-stable). Parity held
(cosine=1.0); GGUF format unchanged, HF GGUFs valid.

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

* chore(recon): bump backend pins to round-4 Winograd engines (CPU opt complete)

voice-detect.cpp -> d2839ca (CAM++ FCM 2D convs through Winograd, -15.5%/-10.3%);
face-detect.cpp -> c1db23d (AVX2-vectorized Winograd tile transforms, SCRFD
detect -14%/-9.6%). Final CPU optimization round; the conv-kernel lever class is
now exhausted (parity held cosine=1.0; GGUF/parity unchanged, HF GGUFs valid).

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

* chore(recon): bump face-detect pin to deep-kernel engine (7ae5c4d)

face-detect.cpp -> 7ae5c4d: register-blocked winograd-domain GEMM microkernel
(2.8x isolated GFLOP/s), AVX-512 zmm evolution behind runtime CPUID dispatch
(ship-safe, AVX2 fallback bit-identical), bias/relu fused into the winograd
output transform, and SFace Conv+BN fold + bias/PReLU fusion. SCRFD detect
~1.4x faster end-to-end vs the round-4 baseline; parity bit-exact; portable
single binary (function-multiversioned, no global -mavx512f).

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

* chore(recon): bump voice-detect pin to ECAPA operand-order win (e9c56ae)

voice-detect.cpp -> e9c56ae: weight-as-src0 mul_mat order in ECAPA's F32
conv1d_same (routes through tinyBLAS sgemm); ECAPA embed 1.67x @1t / ~1.3x @8t,
parity cosine=1.0. Isolated to encoder.cpp (ECAPA-only); ERes2Net/CAM++/WeSpeaker
do not call conv1d_same so are provably unaffected.

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

* chore(recon): bump pins to FMA-throughput engines (voice f7b9f89, face 2d2d5f0)

face -> 2d2d5f0: route ArcFace 3x3 body convs through the AVX-512 winograd
microkernel (kWinoMinSize 80->14); ArcFace 1.62x @1t, SCRFD detect to 0.966 of
MLAS @1t, no regression. voice -> f7b9f89: runtime-CPUID-dispatched AVX-512
winograd-GEMM microkernel (ship-safe, AVX2 fallback bit-identical); WeSpeaker
1.90x @1t. Parity cosine=1.0 throughout; portable single binaries.

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

* chore(recon): bump pins to MLAS-class direct-conv engines (voice 7ecfd07, face be22d67)

Hand-tuned nChw16c AVX-512 register-tiled direct-conv microkernel (~263 GFLOP/s,
within 6-7% of MLAS per-op efficiency), runtime-CPUID-dispatched + AVX2 fallback,
fused bias/relu. voice 7ecfd07: default 3x3-s1 kernel for WeSpeaker (+37%/+32%)
+ ERes2Net, CAM++ pinned to Winograd. face be22d67: shape-gated to the ArcFace
recognizer body (+25-27% @8t); SCRFD detector stays on Winograd (no regression).
Parity cosine=1.0 / detect <=1px on AVX-512 + AVX2 paths. Portable single binaries.

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

* chore(recon): bump voice pin to Phase-A blocked backbone (f4e7eef)

WeSpeaker ResNet34 runs as one nChw16c blocked island (2 reorders/forward vs
~60) on AVX-512, default; per-conv directconv fallback on AVX2. +2.9% @1t /
+17-19% @8t vs per-conv directconv, parity cosine=1.0. The conv microkernel is
already FMA-bound near peak (~0.86-0.98x MLAS-implied); residual to MLAS is
sub-peak edge + non-conv tail, documented in docs/cpu-optimization.md.

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

* chore(recon): bump pins to breadth blocked-backbone (voice 7f66871, face d80092b)

voice 7f66871: AVX2-vectorized (ymm) blocked island - AVX2-only hosts now run
the blocked backbone for WeSpeaker (2.3x over per-conv-AVX2, cosine=1.0);
ERes2Net stays per-conv (blocked regresses, opt-in only); CAM++ Winograd-pinned.
face d80092b: ArcFace recognizer blocked island, AVX-512 default (-13% @8t, ~0.90x
MLAS, the closest conv result), auto per-conv on AVX2; SCRFD untouched on Winograd
(0 island invocations during detect). Parity cosine=1.0 / detect <=1px throughout.

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

* chore(recon): bump pins to small-spatial + stem conv kernels (voice 99b1804, face 47fdab6)

Measured-gap-driven conv kernels: small-spatial (fill the register tile when
output width <= tile width) + small-IC stem + strided-1x1/downsample recovery.
ArcFace recognizer 0.57 -> 0.70x MLAS @1t (the closest conv model), WeSpeaker
0.65 -> 0.79x @1t. Parity cosine=1.0 / detect <=1px. The OC-block-sharing lever
was a measured dead-end (deep stride-1 is L3-weight-bandwidth bound, not
read-port bound) and was NOT shipped. Kernel ceiling reached; further gap needs
an algorithm-class change (cache-blocked weight-stationary GEMM, or q8 weights).

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

* chore(recon): bump pins to GPU persistent-graph + multi-model-safe cache (voice 45d2e6b, face 0a4799a)

GPU wins (CUDA/ggml backend, no CPU-path change): persistent per-shape graph+context
cache in Backend::compute() eliminates the per-call cudaGraph re-instantiation churn
-> wav2vec2 emotion+age-gender now AT GPU parity with torch-cuDNN on GB10 (0.97-0.98x),
CAM++ -5.7ms; bit-identical parity. Cache hardened multi-model-safe (invalidate-on-free
keyed by the ModelLoader weights buffer) so LocalAI multi-model hosting cannot stale-hit.
Conv models still trail cuDNN (im2col-materialization-bound) - cuDNN implicit-GEMM lever next.

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

* chore(recon): bump pins to cuDNN-conv-capable engines (voice b6e4356, face 6107a24)

Adds the opt-in cuDNN implicit-GEMM conv path (VOICEDETECT_GGML_CUDNN /
FACEDETECT_GGML_CUDNN, DEFAULT OFF -> zero build/runtime dep until enabled).
On GPU it kills the im2col-materialization bottleneck and reaches torch-cuDNN
parity on the spill-bound convs: SCRFD detect 14.8->6.4ms (2.3x, ~parity),
WeSpeaker ~parity, ERes2Net beats torch (1.10x); ArcFace/CAM++ neutral (no
spill). Parity exact (SCRFD <=1px, cosine=1.0). To USE it in LocalAI, the CUDA
backend build must enable the flag AND bundle libcudnn - deferred until a
cuDNN-bundled GPU image; flag stays OFF here.

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

* feat(recon): enable cuDNN conv path on arm64+CUDA13 recon backends

The voice-detect.cpp / face-detect.cpp engines have an opt-in cuDNN
implicit-GEMM conv path behind VOICEDETECT_GGML_CUDNN / FACEDETECT_GGML_CUDNN
(default OFF) that kills im2col on the GPU and reaches torch-cuDNN parity
(SCRFD 2.3x, WeSpeaker/ERes2Net parity), measured on the GB10
(arm64, CUDA 13, sm_121a).

Enable it for the CUDA build, but only where cuDNN actually ships: the
arm64 + CUDA 13 image (GB10/Jetson/L4T). x86 CUDA images carry no cuDNN,
so flipping it on globally for BUILD_TYPE=cublas would be a link failure.
The Makefiles gate on CUDA_MAJOR_VERSION=13 + arch (TARGETARCH from the
matrix/Docker build, uname -m fallback for local builds).

backend/Dockerfile.golang already installs the runtime libcudnn9-cuda-13
in the arm64+CUDA13 apt block; add the matching libcudnn9-dev-cuda-13 so
the build-time link resolves.

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

* chore(recon): bump voice-detect pin to ERes2Net blocked-default (30beecd)

Defaults VD_ERES2NET_BLOCKED ON: routes the ERes2Net Res2Net body through the
blocked nChw16c AVX-512 directconv island instead of the 1x1 mul_mat fast path
(CONT-transpose + skinny low-K GEMM). On the shipped GGML_NATIVE=OFF build (ggml
mul_mat is AVX2-only) this wins ~2x at every thread count (2.07x@1t, 2.2x@4t,
2.05x@8t); pure-AVX2 fallback still 1.3-1.62x. Parity exact (cosine=1.000000 vs
golden), so registered voices + verify/identify thresholds are unaffected. The
prior default-OFF rested on a stale comment whose 23pct regression only held on
the non-shipping GGML_NATIVE=ON build.

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

* docs(readme): announce native voice-detect + face-detect backends in Latest News

Add a Latest News entry for the new from-scratch C++/ggml biometric backends
(voice-detect.cpp + face-detect.cpp) that replace the Python insightface and
speaker-recognition backends: no Python/onnxruntime at inference, self-contained
GGUF, bit-exact parity, GPU cuDNN parity. Mirrors the parakeet.cpp /
locate-anything.cpp native-backend news entries. Refs PR #10441.

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

* chore(recon): re-pin to the squashed engine release commits

The voice-detect.cpp and face-detect.cpp histories were squashed to a single
release commit, which orphaned the previous pins (voice 30beecd, face 6107a24).
Re-pin to the new single-commit SHAs (voice 3d51077, face 06914b0); the tree is
identical, so the backend build is unchanged.

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-28 09:29:08 +02:00
LocalAI [bot]
d3a26f961d fix(ik-llama): port multimodal path to mtmd API and bump to f96eaddb (#10534) (#10568)
* fix(ik-llama): port multimodal path to mtmd API and bump to f96eaddb (#10534)

The IK_LLAMA_VERSION bump to f96eaddba8bed6a9a5e628bbf6a566775c70b49c pulls in
upstream commit "Prune examples/llava", which deletes examples/llava (clip.* /
llava.*). The ik-llama backend's grpc-server.cpp built a local `myclip` library
from those files and called the removed clip/llava C API, so the bump no longer
builds.

ik_llama keeps its multimodal stack in the surviving `mtmd` library
(examples/mtmd/, public headers mtmd.h + mtmd-helper.h). This ports the backend's
multimodal path onto the high-level mtmd_* / mtmd_helper_* API in place, leaving
the text path (which still uses ik_llama's retained old common API) untouched:

- Makefile: bump IK_LLAMA_VERSION to f96eaddb.
- prepare.sh: drop the clip/llava source copy + sed block; mtmd is a library
  target, no source copy needed.
- CMakeLists.txt: remove the `myclip` target; link `mtmd` and add its include
  dir; build grpc-server as C++17 (mtmd headers require it).
- patches: drop 0002 (targeted the deleted examples/llava/clip.cpp; the mtmd
  clip.cpp never calls ggml_quantize_chunk, so the fix is unneeded). Keep 0001
  (verified still applies).
- grpc-server.cpp / utils.hpp: replace clip_model_load + clip_image_load_from_bytes
  + llava_image_embed_make_with_clip_img + the manual [img-N] prefix splitting and
  per-image llava_embd_batch decode loop with mtmd_init_from_file (moved after the
  model load, which it requires), mtmd_helper_bitmap_init_from_buf, mtmd_tokenize
  and mtmd_helper_eval_chunks. Legacy [img-N] tags are translated, in order, into
  mtmd media markers (mtmd_default_marker()); the post-image suffix text stays on
  the normal token path so the sampling loop is unchanged.

Supersedes #10534.

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

* fix(ik-llama): align json alias to ordered_json to resolve mtmd.h conflict (#10534)

mtmd.h declares `using json = nlohmann::ordered_json` at global scope (and its
mtmd.cpp depends on it), while ik_llama's whole server/common stack also uses
ordered_json. Our grpc-server.cpp/utils.hpp kept a plain `nlohmann::json` alias,
which now collides with mtmd.h once it is included for the multimodal port:
"conflicting declaration 'using json = ...'". Switch our two aliases to
ordered_json to match; it is API-compatible (utils.hpp already used ordered_json
for its log helper) and our json never crosses into an unordered-json API.

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-28 08:57:11 +02:00
LocalAI [bot]
13b1ae53bc chore: ⬆️ Update ggml-org/llama.cpp to 0ed235ea2c17a19fc8238668653946721ed136fd (#10536)
* ⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

* fix(llama-cpp): link server-stream.cpp TU into grpc-server for upstream 0ed235ea (#10536)

Upstream llama.cpp 0ed235ea added an SSE stream-resumption layer in a new
translation unit tools/server/server-stream.cpp, which defines
stream_session, stream_pipe_producer and the g_stream_sessions manager.
server-context.cpp (already #included into grpc-server.cpp) now calls into
it via spipe->cleanup(), stream_aware_should_stop() and
stream_session_attach_pipe(), so without the new TU the grpc-server link
fails on every arch with:

  undefined reference to `stream_pipe_producer::cleanup()'

prepare.sh already copies every tools/server/* file into tools/grpc-server/,
so the source is present; the only missing piece was including its
definitions. Add an __has_include-guarded #include "server-stream.cpp"
before server-context.cpp, mirroring the existing server-chat.cpp and
server-schema.cpp guards, keeping the source compatible with older
pins/forks that predate the split. The file is self-contained (its only
external symbols come from server-common, already in the TU) so it adds no
new undefined references; the http route-handler factories it also defines
are unused in the grpc path but harmless.

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

* fix(llama-cpp): build renamed ggml-rpc-server target for upstream 0ed235ea (#10536)

Upstream renamed the RPC server CMake target and binary from `rpc-server`
to `ggml-rpc-server` (tools/rpc/CMakeLists.txt: `set(TARGET ggml-rpc-server)`),
so the RPC-enabled grpc build failed with "No rule to make target 'rpc-server'".
The grpc-server itself links fine after the server-stream.cpp fix; this only
updates the RPC target name and the binary path copied to llama-cpp-rpc-server.

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

---------

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-28 08:56:40 +02:00
LocalAI [bot]
e68ca109c5 chore: ⬆️ Update CrispStrobe/CrispASR to 6514c9da00b03a2f0f1b49a43fae4f3a01a41844 (#10535)
⬆️ Update CrispStrobe/CrispASR

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-06-28 08:56:24 +02:00
LocalAI [bot]
6740e988d2 chore: ⬆️ Update ggml-org/whisper.cpp to 0ae02cdb2c7317b50991367c165736ce42ed96ac (#10532)
⬆️ 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>
2026-06-28 08:56:06 +02:00
LocalAI [bot]
ade9cc9e37 fix(openresponses): bound resume-stream buffer and enforce response ownership (#10569)
The background=true resumable-stream path had two latent issues.

1. Unbounded resume buffer. AppendEvent grew StreamEvents without limit, so
   a long-running or abandoned background generation could consume process
   memory without bound. The store now caps the buffer (event count and total
   bytes, mirroring llama.cpp's byte-capped slot ring), evicting oldest events
   from the front and advancing a droppedThrough watermark. GetEventsAfter
   returns ErrOffsetLost when the requested starting_after is below the
   watermark, and handleStreamResume surfaces that as HTTP 409 before
   committing to the SSE response, so a resuming client gets a clear error
   instead of a silently truncated stream.

2. Missing ownership check (IDOR). GET /responses/:id, its stream resume, and
   /cancel looked up responses purely by ID, letting any caller who knows or
   guesses an ID read or cancel another caller's response. Responses now carry
   the creating caller's identity (auth.GetUser), stamped at creation and
   compared on read/cancel/resume; a mismatch returns 404 (not 403) so
   existence is not leaked. Backward compatible: responses with no owner
   (single-key / no-auth deployments) remain accessible.


Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-28 02:02:15 +02:00
LocalAI [bot]
471e38e4e7 chore: ⬆️ Update leejet/stable-diffusion.cpp to 9956436c925a367daeab097598b1ea1f32d3503f (#10533)
⬆️ 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>
2026-06-28 01:55:44 +02:00
LocalAI [bot]
f3d829e2ef feat(distributed): add LOCALAI_DISTRIBUTED_SHARED_MODELS to skip staging on shared volumes (#10556) (#10566)
In distributed mode, even when the frontend and workers share the same
models directory via a shared volume mount, starting a model on a worker
re-staged (re-downloaded) it: stageModelFiles always uploads model files
into a tracking-key-namespaced subdir on the worker, and the staging probe
only checks that staged location, so a file already present on the shared
volume at the canonical path was never reused.

Add a config switch LOCALAI_DISTRIBUTED_SHARED_MODELS (default false). When
enabled, the operator asserts that all nodes mount the SAME models directory
at the SAME path, so staging is unnecessary: the frontend's absolute model
paths are already valid on the worker. In that mode stageModelFiles returns
the cloned opts unchanged without uploading, leaving the path fields pointing
at their canonical absolute paths so the worker loads them directly from the
shared volume.

The value is plumbed from DistributedConfig through SmartRouterOptions into
the SmartRouter. Docs and docker-compose.distributed.yaml updated.


Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-28 01:23:07 +02:00
LocalAI [bot]
91885c2c7e fix(distributed): return empty backend list for agent nodes instead of failing backend.list (#10545) (#10565)
Opening an AGENT-type worker node's detail page errored with
"failed to list backends on node" / NATS "nodes.<id>.backend.list:
no responders available". Agent workers only subscribe to agent.*,
jobs.*, mcp.* and <prefix>.backend.stop; they never subscribe to
backend.list, so the per-node ListBackendsOnNodeEndpoint request had
no responder and timed out.

The aggregate cluster-wide list already guards this in
managers_distributed.go (skip nodes whose NodeType is set and not
"backend"). The single-node endpoint lacked the same guard. Thread the
NodeRegistry into ListBackendsOnNodeEndpoint and short-circuit to an
empty (non-nil) list for non-backend node types before issuing the
doomed NATS request, mirroring the aggregate-list gate so both views
stay consistent.


Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-28 01:22:48 +02:00
LocalAI [bot]
f1fcafb888 fix(gallery): match mmproj/model quant as a whole token so F16 no longer selects BF16 (#10559) (#10564)
pickPreferredGroup matched a quant preference against the shard base
filename with strings.Contains. Because `f16` is a substring of `bf16`,
asking for the `F16` mmproj quant would wrongly satisfy a `BF16` file and
select it when its group came first.

Match the preference as a whole token instead: it must be delimited by a
non-alphanumeric character (or the string start/end) on both outer edges.
Separators inside the preference itself (e.g. `ud-q4_k_xl`) are left
untouched, and all occurrences are scanned before rejecting.


Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-28 01:21:33 +02:00
LocalAI [bot]
fdff114701 ci(vibevoice): skip the ASR transcription e2e on release tag builds (#10567)
The `tests-vibevoice-cpp-grpc-transcription` job downloads the vibevoice ASR
model (`vibevoice-asr-q4_k.gguf`, ~10 GB) and decodes it through the
e2e-backends harness. On release tag pushes the detect step forces the full
matrix (run-all=true), so this job runs and consistently times out: the inner
`go test -timeout 30m` cannot pull a 10 GB file from HuggingFace's throttled
Xet CDN within budget (curl --max-time 600 x5 retries overruns the deadline),
leaving an orphaned curl and a 30m panic. It has been red on every release
(v4.5.3/4/5).

Guard the job's `if` with `!startsWith(github.ref, 'refs/tags/')` so it no
longer runs on tag/release builds. It still runs on PRs and branch pushes that
touch vibevoice-cpp, so real regressions are caught off the release path. A
proper fix (a small ASR test GGUF) can re-enable it on tags later.

Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-28 00:40:21 +02:00
LocalAI [bot]
1154be5eea fix(config): fall back to DefaultContextSize for unparseable GGUFs; pin NVFP4 gallery context_size (#10563)
The GGUF metadata parser (gpustack/gguf-parser-go) cannot read NVFP4-quantized
GGUFs at all: it errors with "read tensor info 0: This quantized type is
currently unsupported" because NVFP4 is a ggml tensor type it does not know.
When ParseGGUFFile errors, the llama-cpp defaults hook skips guessGGUFFromFile
entirely and the deferred fallback sets the context window to the conservative
GGUFFallbackContextSize (1024). The result: a model that trains to 262144
tokens runs with n_ctx=1024, and every prompt over ~1k tokens fails with
"request (N tokens) exceeds the available context size (1024 tokens)".

Two changes:

- Drop GGUFFallbackContextSize (1024) and fall back to DefaultContextSize
  (4096) in both the GGUF run-estimate path (gguf.go) and the deferred hook
  fallback (hooks_llamacpp.go). 1024 is a sensible floor for a tiny CPU GGUF
  but a footgun for a large, long-context model whose header simply cannot be
  parsed. Strengthen the existing "GGUF unreadable" test to assert the value.

- Set context_size explicitly on the four NVFP4 gallery entries
  (qwen3.6-35b-a3b-nvfp4-mtp, qwopus3.6-27b-v2-mtp-nvfp4,
  qwopus3.6-27b-coder-mtp-nvfp4, qwen3.6-27b-nvfp4-mtp) so the parser failure
  is irrelevant for them. 32768 matches sibling Qwen entries and is safe on
  memory; operators can raise it toward the 262144 train length.


Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-27 23:34:52 +02:00
LocalAI [bot]
8aba4fdba3 chore(fish-speech): drop the darwin/metal build target (#10561)
The fish-speech metal-darwin-arm64 backend build has been failing on every
release (v4.5.3, v4.5.4, v4.5.5) and is a standing red on the darwin backend
matrix. fish-speech pulls `tokenizers` transitively from its upstream source
(`pip install -e fish-speech-src`), and on darwin/arm64 there is no prebuilt
wheel for the pinned old `tokenizers` version, so pip builds it from source.
Modern rustc rejects that old crate as a hard error:

    error: casting `&T` to `&mut T` is undefined behavior ...
       --> tokenizers-lib/src/models/bpe/trainer.rs:517:47
       = note: `#[deny(invalid_reference_casting)]` on by default
    error: could not compile `tokenizers` (lib) due to 1 previous error

This is deterministic, not a flake, and there is no clean fix that does not
either pin a stale Rust toolchain or downgrade a soundness lint guarding real
UB. Until upstream fish-speech moves to a tokenizers version that compiles on
current toolchains, drop darwin support so the release backend build stays
green. The Linux/CUDA/ROCm/Intel/L4T variants are unaffected.

Removes:
- the `-metal-darwin-arm64-fish-speech` entry from `includeDarwin` in
  backend-matrix.yml
- the `metal:` capability mappings and the concrete `metal-fish-speech` /
  `metal-fish-speech-development` gallery entries in backend/index.yaml
- the now-unused darwin-only requirements-mps.txt

Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-27 23:24:21 +02:00
LocalAI [bot]
d7d7721eae feat(distributed): SyncedMap component + migrate finetune/quant/agent-tasks to cross-replica state (#10542)
* feat(distributed): add SyncedMap cross-replica in-memory state component

Introduce core/services/syncstate.SyncedMap[K,V]: a thread-safe in-memory map
that keeps itself consistent across frontend replicas via NATS, with an optional
pluggable durable Store and hydrate-from-source convergence.

Several features keep process-local state surfaced to the API (finetune/quant
jobs, agent tasks, model configs) and each hand-wired the same in-memory + NATS
broadcast + read-through-store legs - or forgot to, reintroducing cross-replica
staleness. SyncedMap makes that consistency a configuration choice:

- local writes mutate the map, write through the Store, then broadcast a delta;
- the apply path is memory-only and never re-publishes or re-writes the Store
  (structural echo-loop guard, mirroring galleryop.mergeStatus);
- on Start and on NATS reconnect the map re-hydrates from the source (Store, else
  Loader); an optional periodic Reconcile repairs silent drift;
- standalone mode (nil NATS client) is a strict in-memory no-op.

Reconnect re-hydrate is wired via a new *messaging.Client.OnReconnect callback,
consumed through an optional type-assertion so MessagingClient stays minimal.
Adds messaging.SubjectSyncStateDelta and a reusable testutil.FakeBus (synchronous
in-process MessagingClient with wildcard matching) for adopter tests.

Component only; service migrations follow in subsequent commits.

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

* refactor(finetune): back jobs with SyncedMap for cross-replica consistency

FineTuneService kept jobs in a process-local map and, although it wrote them to
Postgres, ListJobs/GetJob never read the store back and the wired natsClient was
never used - so in distributed mode a job created on one replica was invisible to
the others. Replace the map and the dead client with a syncstate.SyncedMap keyed
by job ID, value *schema.FineTuneJob (the exact REST shape, so responses are
unchanged).

- Add a Store adapter (core/services/finetune/syncstore.go) over FineTuneStore,
  plus FineTuneStore.ListAll (global hydrate; per-user List kept) and an
  idempotent Upsert (create-or-update; Create alone fails on dup key).
- Writes go through SyncedMap.Set/Delete (write-through + broadcast); reads use
  List/Get. The on-disk state.json path becomes the standalone Loader, keeping
  single-node restart recovery (stale->stopped / exporting->failed fixups).
- Fold SetNATSClient/SetFineTuneStore into NewFineTuneService; app.go passes the
  distributed NATS client + store when distributed, nil otherwise.

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

* refactor(agentpool): back agent tasks with SyncedMap for cross-replica consistency

AgentJobService.ListTasks read the process-local tasks map only, while ListJobs
already read through the DB persister + dispatcher NATS - so in distributed mode
a task created on one replica was invisible to the others. Back tasks with a
syncstate.SyncedMap keyed by task ID (value schema.Task, the exact REST shape);
jobs are left untouched.

- Store adapter (task_syncstore.go) over the existing JobPersister
  (LoadTasks/SaveTask/DeleteTask); reads svc.persister/userID live so a persister
  swap needs no rebuild. No new persister methods required.
- Task reads -> SyncedMap.List/Get; create/update -> Set (write-through +
  broadcast); delete -> Delete. The file persister now owns its own task set so
  the write-through path does not re-enter the SyncedMap lock (deadlock guard).
- The distributed NATS client is not available at construction (start() precedes
  initDistributed), so it is injected via SetTaskSyncNATS, which rebuilds the
  still-empty map before Start/hydrate. Wired at the main, restart, and per-user
  (UserServicesManager) distributed sites.

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

* refactor(quantization): back jobs with SyncedMap + durable QuantStore

QuantizationService kept jobs in a process-local map persisted only to a local
state.json, so in distributed mode jobs were neither visible across replicas nor
durable cluster-wide. Back jobs with a syncstate.SyncedMap keyed by job ID
(value *schema.QuantizationJob, the exact REST shape).

- New distributed.QuantStore (GORM, table quantization_jobs) mirroring
  FineTuneStore: Create/Get/ListAll/Upsert(idempotent)/Delete, registered for
  AutoMigrate via distributed.InitStores (Stores.Quant).
- New adapter (quantization/syncstore.go) over QuantStore implementing
  syncstate.Store, with record<->schema conversion.
- Reads go through List/Get, writes through Set/Delete (write-through +
  broadcast); state.json is kept as the standalone Loader for single-node restart
  recovery (stale-job fixups preserved).
- app.go passes the distributed NATS client + QuantStore when distributed, nil
  otherwise; Start/Close lifecycle mirrors finetune.

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

* fix(syncstate): annotate gosec G118 false positive on lifeCtx

gosec flagged the WithCancel in Start as "cancellation function not called"
because the returned cancel is stored on the struct rather than called/deferred
in scope. It is invoked in Close (covered by tests), and lifeCtx must outlive
Start to drive the reconnect/reconcile goroutines. Suppress the verified false
positive with a justified #nosec G118.

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

* test(distributed): e2e two-replica SyncedMap sync over real NATS + Postgres

Adds the real-infrastructure counterpart to the fake-bus unit tests, in the
existing distributed e2e suite (testcontainers NATS + PostgreSQL). Two SyncedMap
instances stand in for two frontend replicas - each with its OWN NATS connection
to a shared server and a SHARED Postgres store (the distributed-mode invariant) -
and assert, over the wire:

- a create on replica A is observed by replica B;
- an update and a delete propagate A -> B (delete prunes, which a reload cannot);
- a late-joining replica recovers a job it never received a delta for, via store
  hydrate on Start (the at-most-once gap a fake bus cannot exercise);
- a local Set is written through to the shared Postgres store.

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-27 23:23:51 +02:00
Nicholas Ciechanowski
c548150f99 fix(distributed): missing agent NATS permission (#10549)
Signed-off-by: Nicholas Ciechanowski <nicholas@ciech.anow.ski>
2026-06-27 21:10:12 +00:00
LocalAI [bot]
ec26b86dd4 docs: ⬆️ update docs version mudler/LocalAI (#10560)
⬆️ Update docs version mudler/LocalAI

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-06-27 22:36:02 +02:00
LocalAI [bot]
d11b202dd2 fix(backends): whisper darwin run.sh loads whichever fallback lib exists (.so/.dylib) (#10553)
fix(backends): whisper darwin run.sh loads whichever fallback lib exists

The macOS branch hardcoded WHISPER_LIBRARY=$CURDIR/libgowhisper-fallback.dylib,
but the cmake build emits a Mach-O named libgowhisper-fallback.so on darwin, so
the Go loader panicked at runtime ("dlopen ...dylib: no such file") and the
backend exited ("grpc service not ready") — breaking e.g. the silero-vad-ggml
VAD on darwin. Pick whichever of .dylib/.so is present so it is robust to the
build's naming either way.

Assisted-by: Claude:claude-opus-4-8

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-27 14:07:56 +02:00
LocalAI [bot]
e95018ef70 chore(model gallery): 🤖 add 1 new models via gallery agent (#10544)
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>
2026-06-27 09:42:46 +02:00
LocalAI [bot]
0258f8af55 fix(backends): repair release CI build/test breaks (kokoros, fish-speech, llama-cpp-quantization, sglang) (#10547)
* fix(kokoros): implement new Backend RPCs to fix the build

The backend.proto grew six RPCs (SoundDetection, Depth, TokenClassify,
Score and the bidi-streaming Forward) that the kokoros gRPC service never
implemented, so the trait impl no longer satisfies `Backend`:

    error[E0046]: not all trait items implemented, missing:
      `sound_detection`, `depth`, `token_classify`, `score`,
      `ForwardStream`, `forward`

kokoros is a TTS backend with no use for these, so add `unimplemented`
stubs (plus the `ForwardStream` associated type) matching the existing
pattern for every other unsupported RPC in this file.

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

* fix(fish-speech): add setuptools-rust for the editable source install

install.sh installs the fish-speech source tree editable with
`--no-build-isolation`, which means the build backends of its transitive
dependencies must already be present in the venv. One of them builds a
Rust extension and its metadata step fails with:

    ModuleNotFoundError: No module named 'setuptools_rust'

Add setuptools-rust to requirements.txt so installRequirements provisions
it before the editable install runs.

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

* fix(llama-cpp-quantization): vendor convert_hf_to_gguf.py with conversion/

Upstream llama.cpp split the model-specific logic out of the single
convert_hf_to_gguf.py file into a sibling `conversion/` package, so the
script now starts with `from conversion import ...`. Downloading just the
one file therefore fails at runtime with:

    ModuleNotFoundError: No module named 'conversion'

Clone the repo (reusing the clone already needed to build llama-quantize)
and copy both the script and the `conversion/` package into the backend
dir. Python puts the script's own directory on sys.path[0], so the package
resolves when it sits beside the script.

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

* fix(sglang): pin the CPU source build to sglang v0.5.11

The CPU profile builds sgl-kernel from a `git clone` of sglang with no
ref, so it always tracks master. Recent master added CPU kernels (e.g.
mamba/fla.cpp) that fail to compile in our builder:

    constexpr variable 'scale' must be initialized by a constant
    static library kineto_LIBRARY-NOTFOUND not found

Pin the clone to v0.5.11, the same release the GPU path already floors on
(requirements-cublas12-after.txt). Overridable via SGLANG_VERSION so the
pin can be bumped deliberately.

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-27 09:42:22 +02:00
106 changed files with 6471 additions and 511 deletions

View File

@@ -3745,6 +3745,302 @@ include:
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
# voice-detect
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "8"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-12-voice-detect'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-13-voice-detect'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/arm64'
skip-drivers: 'false'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-cuda-13-arm64-voice-detect'
base-image: "ubuntu:24.04"
ubuntu-version: '2404'
runs-on: 'ubuntu-24.04-arm'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: ''
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
platform-tag: 'amd64'
tag-latest: 'auto'
tag-suffix: '-cpu-voice-detect'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: ''
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/arm64'
platform-tag: 'arm64'
tag-latest: 'auto'
tag-suffix: '-cpu-voice-detect'
runs-on: 'ubuntu-24.04-arm'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'sycl_f32'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-voice-detect'
runs-on: 'ubuntu-latest'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
skip-drivers: 'false'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'sycl_f16'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f16-voice-detect'
runs-on: 'ubuntu-latest'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
skip-drivers: 'false'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'vulkan'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
platform-tag: 'amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-vulkan-voice-detect'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'vulkan'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/arm64'
platform-tag: 'arm64'
tag-latest: 'auto'
tag-suffix: '-gpu-vulkan-voice-detect'
runs-on: 'ubuntu-24.04-arm'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/arm64'
skip-drivers: 'false'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-arm64-voice-detect'
base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
runs-on: 'ubuntu-24.04-arm'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2204'
- build-type: 'hipblas'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-rocm-hipblas-voice-detect'
base-image: "rocm/dev-ubuntu-24.04:7.2.1"
runs-on: 'ubuntu-latest'
skip-drivers: 'false'
backend: "voice-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
# face-detect
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "8"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-12-face-detect'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-13-face-detect'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/arm64'
skip-drivers: 'false'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-cuda-13-arm64-face-detect'
base-image: "ubuntu:24.04"
ubuntu-version: '2404'
runs-on: 'ubuntu-24.04-arm'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: ''
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
platform-tag: 'amd64'
tag-latest: 'auto'
tag-suffix: '-cpu-face-detect'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: ''
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/arm64'
platform-tag: 'arm64'
tag-latest: 'auto'
tag-suffix: '-cpu-face-detect'
runs-on: 'ubuntu-24.04-arm'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'sycl_f32'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-face-detect'
runs-on: 'ubuntu-latest'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
skip-drivers: 'false'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'sycl_f16'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f16-face-detect'
runs-on: 'ubuntu-latest'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
skip-drivers: 'false'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'vulkan'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
platform-tag: 'amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-vulkan-face-detect'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'vulkan'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/arm64'
platform-tag: 'arm64'
tag-latest: 'auto'
tag-suffix: '-gpu-vulkan-face-detect'
runs-on: 'ubuntu-24.04-arm'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/arm64'
skip-drivers: 'false'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-arm64-face-detect'
base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
runs-on: 'ubuntu-24.04-arm'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2204'
- build-type: 'hipblas'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-rocm-hipblas-face-detect'
base-image: "rocm/dev-ubuntu-24.04:7.2.1"
runs-on: 'ubuntu-latest'
skip-drivers: 'false'
backend: "face-detect"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
# acestep-cpp
- build-type: ''
cuda-major-version: ""
@@ -4928,6 +5224,14 @@ includeDarwin:
tag-suffix: "-metal-darwin-arm64-ced"
build-type: "metal"
lang: "go"
- backend: "voice-detect"
tag-suffix: "-metal-darwin-arm64-voice-detect"
build-type: "metal"
lang: "go"
- backend: "face-detect"
tag-suffix: "-metal-darwin-arm64-face-detect"
build-type: "metal"
lang: "go"
- backend: "acestep-cpp"
tag-suffix: "-metal-darwin-arm64-acestep-cpp"
build-type: "metal"
@@ -4991,9 +5295,6 @@ includeDarwin:
- backend: "qwen-tts"
tag-suffix: "-metal-darwin-arm64-qwen-tts"
build-type: "mps"
- backend: "fish-speech"
tag-suffix: "-metal-darwin-arm64-fish-speech"
build-type: "mps"
- backend: "voxcpm"
tag-suffix: "-metal-darwin-arm64-voxcpm"
build-type: "mps"

View File

@@ -46,6 +46,14 @@ jobs:
variable: "CED_VERSION"
branch: "master"
file: "backend/go/ced/Makefile"
- repository: "mudler/voice-detect.cpp"
variable: "VOICEDETECT_VERSION"
branch: "master"
file: "backend/go/voice-detect/Makefile"
- repository: "mudler/face-detect.cpp"
variable: "FACEDETECT_VERSION"
branch: "master"
file: "backend/go/face-detect/Makefile"
- repository: "mudler/depth-anything.cpp"
variable: "DEPTHANYTHING_VERSION"
branch: "master"

View File

@@ -1008,7 +1008,11 @@ jobs:
# 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'
# Skip on release tag pushes: the ASR Q4_K model is ~10 GB and cannot be
# pulled from HF within the inner `go test -timeout 30m` budget on a CI
# runner, so every tag build hung and timed out. Still runs on PRs/branch
# pushes that touch vibevoice-cpp so regressions are caught off the release path.
if: (needs.detect-changes.outputs.vibevoice-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true') && !startsWith(github.ref, 'refs/tags/')
runs-on: bigger-runner
timeout-minutes: 150
steps:

View File

@@ -177,6 +177,7 @@ For more details, see the [Getting Started guide](https://localai.io/basics/gett
## Latest News
- **June 2026**: New native biometric backends from the LocalAI team: [voice-detect.cpp](https://github.com/mudler/voice-detect.cpp) for speaker recognition and voice analysis (ECAPA-TDNN, WeSpeaker, ERes2Net, CAM++, wav2vec2 age/gender/emotion) and [face-detect.cpp](https://github.com/mudler/face-detect.cpp) for face detection, recognition, demographics and anti-spoofing (SCRFD/ArcFace, YuNet/SFace). Both are from-scratch C++/ggml engines with no Python or onnxruntime at inference, self-contained GGUF weights, bit-exact parity with the reference, and GPU cuDNN parity, replacing the heavier Python `insightface` and `speaker-recognition` backends ([PR #10441](https://github.com/mudler/LocalAI/pull/10441)).
- **June 2026**: New [realtime voice assistant demo](https://github.com/localai-org/localai-realtime-demo) (a tiny Go client for the Realtime API with a full talk-back voice loop and tool calling), plus [streaming of the realtime LLM / TTS / transcription pipeline stages](https://github.com/mudler/LocalAI/pull/10176) and [configurable WebRTC ICE candidates](https://github.com/mudler/LocalAI/pull/10231).
- **June 2026**: Big speech push: the [parakeet.cpp](https://github.com/mudler/parakeet.cpp) ASR engine gains [NeMo-faithful segment timestamps](https://github.com/mudler/LocalAI/pull/10207), a [multilingual streaming Nemotron-3.5 model](https://github.com/mudler/LocalAI/pull/10199), [dynamic batching for concurrent transcription](https://github.com/mudler/LocalAI/pull/10112) and [CUDA graphs](https://github.com/mudler/LocalAI/pull/10273); the new [CrispASR backend](https://github.com/mudler/LocalAI/pull/10099) adds multi-architecture ASR + TTS, and [60 Piper TTS voices across 42 languages](https://github.com/mudler/LocalAI/pull/10296) land in the gallery (plus [per-request TTS instructions and params](https://github.com/mudler/LocalAI/pull/10172)).
- **June 2026**: New backends and models: [locate-anything.cpp](https://github.com/mudler/LocalAI/pull/10264) for open-vocabulary object detection via ggml, [Ideogram4 image generation](https://github.com/mudler/LocalAI/pull/10201) in stablediffusion-ggml, [llama.cpp video input](https://github.com/mudler/LocalAI/pull/10216), and the [Gemma 4 QAT family with MTP speculative-decoding pairs](https://github.com/mudler/LocalAI/pull/10215). Plus an [interactive CLI chat mode](https://github.com/mudler/LocalAI/pull/10226) and [RAG source citations in agent responses](https://github.com/mudler/LocalAI/pull/10228).

View File

@@ -137,7 +137,7 @@ RUN <<EOT bash
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}-${CUDA_MINOR_VERSION}
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} libcudnn9-dev-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/*

View File

@@ -1,15 +1,6 @@
## Clip/LLaVA library for multimodal support — built locally from copied sources
set(TARGET myclip)
add_library(${TARGET} clip.cpp clip.h llava.cpp llava.h)
install(TARGETS ${TARGET} LIBRARY)
target_include_directories(myclip PUBLIC .)
target_include_directories(myclip PUBLIC ../..)
target_include_directories(myclip PUBLIC ../../common)
target_link_libraries(${TARGET} PRIVATE common ggml llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
if (NOT MSVC)
target_compile_options(${TARGET} PRIVATE -Wno-cast-qual)
endif()
## Multimodal support is provided by the in-tree `mtmd` library target
## (examples/mtmd/), which the grpc-server links and includes below. clip/llava
## were pruned upstream; the high-level mtmd_* / mtmd_helper_* API is used instead.
set(TARGET grpc-server)
set(CMAKE_CXX_STANDARD 17)
@@ -67,12 +58,16 @@ add_library(hw_grpc_proto
${hw_proto_hdrs} )
add_executable(${TARGET} grpc-server.cpp json.hpp)
target_link_libraries(${TARGET} PRIVATE common llama myclip ${CMAKE_THREAD_LIBS_INIT} absl::flags hw_grpc_proto
# mtmd public headers (mtmd.h / mtmd-helper.h) live in examples/mtmd/.
# Linking the mtmd target also propagates this include dir, but we add it
# explicitly for clarity.
target_include_directories(${TARGET} PRIVATE ../mtmd)
target_link_libraries(${TARGET} PRIVATE common llama mtmd ${CMAKE_THREAD_LIBS_INIT} absl::flags hw_grpc_proto
absl::flags_parse
gRPC::${_REFLECTION}
gRPC::${_GRPC_GRPCPP}
protobuf::${_PROTOBUF_LIBPROTOBUF})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
target_compile_features(${TARGET} PRIVATE cxx_std_17)
if(TARGET BUILD_INFO)
add_dependencies(${TARGET} BUILD_INFO)
endif()

View File

@@ -1,5 +1,5 @@
IK_LLAMA_VERSION?=b84902d2ad27c34f989f23947200c4b91b1568fd
IK_LLAMA_VERSION?=f96eaddba8bed6a9a5e628bbf6a566775c70b49c
LLAMA_REPO?=https://github.com/ikawrakow/ik_llama.cpp
CMAKE_ARGS?=

View File

@@ -11,8 +11,8 @@
#include <memory>
#include <string>
#include <getopt.h>
#include "clip.h"
#include "llava.h"
#include "mtmd.h"
#include "mtmd-helper.h"
#include "log.h"
#include "common.h"
#include "json.hpp"
@@ -45,7 +45,9 @@ using backend::HealthMessage;
///// LLAMA.CPP server code below
using json = nlohmann::json;
// Match mtmd.h and ik_llama's server/common headers, which all use
// nlohmann::ordered_json; a plain nlohmann::json alias collides at global scope.
using json = nlohmann::ordered_json;
struct server_params
{
@@ -219,6 +221,11 @@ struct llama_client_slot
// multimodal
std::vector<slot_image> images;
// Full prompt with mtmd media markers (mtmd_default_marker()) substituted in
// place of the legacy [img-N] tags, covering the text up to and including the
// last image. The text after the last image is kept in params.input_suffix and
// decoded through the normal token path so the sampling loop is unchanged.
std::string mtmd_prompt;
// stats
size_t sent_count = 0;
@@ -252,14 +259,14 @@ struct llama_client_slot
for (slot_image & img : images)
{
free(img.image_embedding);
if (img.img_data) {
clip_image_u8_free(img.img_data);
if (img.bitmap) {
mtmd_bitmap_free(img.bitmap);
img.bitmap = nullptr;
}
img.prefix_prompt = "";
}
images.clear();
mtmd_prompt = "";
}
bool has_budget(gpt_params &global_params) {
@@ -396,46 +403,13 @@ struct llama_metrics {
}
};
struct llava_embd_batch {
std::vector<llama_pos> pos;
std::vector<int32_t> n_seq_id;
std::vector<llama_seq_id> seq_id_0;
std::vector<llama_seq_id *> seq_ids;
std::vector<int8_t> logits;
llama_batch batch;
llava_embd_batch(float * embd, int32_t n_tokens, llama_pos pos_0, llama_seq_id seq_id) {
pos .resize(n_tokens);
n_seq_id.resize(n_tokens);
seq_ids .resize(n_tokens + 1);
logits .resize(n_tokens);
seq_id_0.resize(1);
seq_id_0[0] = seq_id;
seq_ids [n_tokens] = nullptr;
batch = {
/*n_tokens =*/ n_tokens,
/*tokens =*/ nullptr,
/*embd =*/ embd,
/*pos =*/ pos.data(),
/*n_seq_id =*/ n_seq_id.data(),
/*seq_id =*/ seq_ids.data(),
/*logits =*/ logits.data(),
};
for (int i = 0; i < n_tokens; i++) {
batch.pos [i] = pos_0 + i;
batch.n_seq_id[i] = 1;
batch.seq_id [i] = seq_id_0.data();
batch.logits [i] = false;
}
}
};
struct llama_server_context
{
llama_model *model = nullptr;
llama_context *ctx = nullptr;
const llama_vocab * vocab = nullptr;
clip_ctx *clp_ctx = nullptr;
mtmd_context *mctx = nullptr;
gpt_params params;
@@ -491,11 +465,6 @@ struct llama_server_context
if (!params.mmproj.path.empty()) {
multimodal = true;
LOG_INFO("Multi Modal Mode Enabled", {});
clp_ctx = clip_model_load(params.mmproj.path.c_str(), /*verbosity=*/ 1);
if(clp_ctx == nullptr) {
LOG_ERR("unable to load clip model: %s", params.mmproj.path.c_str());
return false;
}
if (params.n_ctx < 2048) { // request larger context for the image embedding
params.n_ctx = 2048;
@@ -512,10 +481,24 @@ struct llama_server_context
}
if (multimodal) {
const int n_embd_clip = clip_n_mmproj_embd(clp_ctx);
const int n_embd_llm = llama_model_n_embd(model);
if (n_embd_clip != n_embd_llm) {
LOG("%s: embedding dim of the multimodal projector (%d) is not equal to that of LLaMA (%d). Make sure that you use the correct mmproj file.\n", __func__, n_embd_clip, n_embd_llm);
// mtmd_init_from_file requires the already-loaded text model, so it must
// run AFTER llama_init_from_gpt_params. It validates the projector
// against the model internally and returns nullptr on dim mismatch, so
// the explicit clip_n_mmproj_embd check is no longer needed.
mtmd_context_params mparams = mtmd_context_params_default();
mparams.use_gpu = params.mmproj_use_gpu;
mparams.print_timings = false;
mparams.n_threads = params.n_threads_mtmd != -1 ? params.n_threads_mtmd
: params.n_threads_batch != -1 ? params.n_threads_batch
: params.n_threads;
mparams.verbosity = GGML_LOG_LEVEL_INFO;
mparams.flash_attn_type = params.flash_attn ? LLAMA_FLASH_ATTN_TYPE_ENABLED
: LLAMA_FLASH_ATTN_TYPE_DISABLED;
mparams.image_min_tokens = params.image_min_tokens;
mparams.image_max_tokens = params.image_max_tokens;
mctx = mtmd_init_from_file(params.mmproj.path.c_str(), model, mparams);
if (mctx == nullptr) {
LOG_ERR("unable to load multimodal projector: %s", params.mmproj.path.c_str());
llama_free(ctx);
llama_free_model(model);
return false;
@@ -865,8 +848,8 @@ struct llama_server_context
slot_image img_sl;
img_sl.id = img.count("id") != 0 ? img["id"].get<int>() : slot->images.size();
img_sl.img_data = clip_image_u8_init();
if (!clip_image_load_from_bytes(image_buffer.data(), image_buffer.size(), img_sl.img_data))
img_sl.bitmap = mtmd_helper_bitmap_init_from_buf(mctx, image_buffer.data(), image_buffer.size());
if (img_sl.bitmap == nullptr)
{
LOG_ERR("%s: failed to load image, slot_id: %d, img_sl_id: %d",
__func__,
@@ -879,50 +862,74 @@ struct llama_server_context
{"slot_id", slot->id},
{"img_sl_id", img_sl.id}
});
img_sl.request_encode_image = true;
slot->images.push_back(img_sl);
}
// process prompt
// example: system prompt [img-102] user [img-103] describe [img-134] -> [{id: 102, prefix: 'system prompt '}, {id: 103, prefix: ' user '}, {id: 134, prefix: ' describe '}]}
// Translate the legacy [img-N] tags into mtmd media markers, in
// order, and collect the matching bitmaps in marker order so they
// line up with the markers passed to mtmd_tokenize(). The text after
// the last image stays in input_suffix and is decoded through the
// normal token path, so the sampling loop is unchanged.
// example: system prompt [img-102] user [img-103] describe [img-134]
if (slot->images.size() > 0 && !slot->prompt.is_array())
{
const std::string marker = mtmd_default_marker();
std::string prompt = slot->prompt.get<std::string>();
size_t pos = 0, begin_prefix = 0;
std::string built_prompt;
std::vector<slot_image> ordered;
size_t pos = 0, copy_from = 0;
std::string pattern = "[img-";
while ((pos = prompt.find(pattern, pos)) != std::string::npos) {
size_t end_prefix = pos;
pos += pattern.length();
size_t end_pos = prompt.find(']', pos);
if (end_pos != std::string::npos)
{
std::string image_id = prompt.substr(pos, end_pos - pos);
try
{
int img_id = std::stoi(image_id);
bool found = false;
for (slot_image &img : slot->images)
{
if (img.id == img_id) {
found = true;
img.prefix_prompt = prompt.substr(begin_prefix, end_prefix - begin_prefix);
begin_prefix = end_pos + 1;
break;
}
}
if (!found) {
LOG("ERROR: Image with id: %i, not found.\n", img_id);
slot->images.clear();
return false;
}
} catch (const std::invalid_argument& e) {
LOG("Invalid image number id in prompt\n");
slot->images.clear();
return false;
auto free_images = [&]() {
for (slot_image &img : slot->images) {
if (img.bitmap) {
mtmd_bitmap_free(img.bitmap);
img.bitmap = nullptr;
}
}
slot->images.clear();
};
while ((pos = prompt.find(pattern, pos)) != std::string::npos) {
size_t tag_begin = pos;
pos += pattern.length();
size_t end_pos = prompt.find(']', pos);
if (end_pos == std::string::npos) {
break;
}
std::string image_id = prompt.substr(pos, end_pos - pos);
try
{
int img_id = std::stoi(image_id);
bool found = false;
for (slot_image &img : slot->images)
{
if (img.id == img_id) {
found = true;
// text before this tag, then the media marker
built_prompt += prompt.substr(copy_from, tag_begin - copy_from);
built_prompt += marker;
copy_from = end_pos + 1;
ordered.push_back(img);
break;
}
}
if (!found) {
LOG("ERROR: Image with id: %i, not found.\n", img_id);
free_images();
return false;
}
} catch (const std::invalid_argument& e) {
LOG("Invalid image number id in prompt\n");
free_images();
return false;
}
pos = end_pos + 1;
}
// bitmaps are consumed in marker order by mtmd_tokenize()
slot->images = ordered;
slot->mtmd_prompt = built_prompt;
slot->prompt = "";
slot->params.input_suffix = prompt.substr(begin_prefix);
slot->params.input_suffix = prompt.substr(copy_from);
slot->params.cache_prompt = false; // multimodal doesn't support cache prompt
}
}
@@ -1176,21 +1183,10 @@ struct llama_server_context
bool process_images(llama_client_slot &slot) const
{
for (slot_image &img : slot.images)
{
if (!img.request_encode_image)
{
continue;
}
if (!llava_image_embed_make_with_clip_img(clp_ctx, params.n_threads, img.img_data, &img.image_embedding, &img.image_tokens)) {
LOG("Error processing the given image");
return false;
}
img.request_encode_image = false;
}
// With the mtmd pipeline, image encoding is no longer eager: the bitmaps
// are tokenized and encoded together with the surrounding text inside
// ingest_images() via mtmd_tokenize() + mtmd_helper_eval_chunks(). This
// just reports whether the slot carries any images to process.
return slot.images.size() > 0;
}
@@ -1435,69 +1431,70 @@ struct llama_server_context
}
}
// for multiple images processing
// Tokenize the multimodal prompt (text interleaved with media markers) together
// with the slot's bitmaps, then decode the resulting chunks into the llama
// context via the high-level mtmd helper. The helper runs llama_decode() on the
// text chunks and mtmd_encode() + llama_decode() on the image chunks, handling
// batching and any pre/post decode setup (e.g. non-causal attention for gemma3).
// Advances slot.n_past by the number of positions consumed, then leaves the
// post-image suffix tokens in `batch` so the normal decode + sampling loop
// produces the first generated token.
bool ingest_images(llama_client_slot &slot, int n_batch)
{
int image_idx = 0;
while (image_idx < (int) slot.images.size())
if (mctx == nullptr)
{
slot_image &img = slot.images[image_idx];
LOG("%s : multimodal context is not initialized\n", __func__);
return false;
}
// process prefix prompt
for (int32_t i = 0; i < (int32_t) batch.n_tokens; i += n_batch)
{
const int32_t n_tokens = std::min(n_batch, (int32_t) (batch.n_tokens - i));
llama_batch batch_view = {
n_tokens,
batch.token + i,
nullptr,
batch.pos + i,
batch.n_seq_id + i,
batch.seq_id + i,
batch.logits + i,
};
if (llama_decode(ctx, batch_view))
{
LOG("%s : failed to eval\n", __func__);
return false;
}
}
// bitmaps stay owned by slot.images (freed on reset()); pass non-owning ptrs
std::vector<const mtmd_bitmap *> bitmaps;
bitmaps.reserve(slot.images.size());
for (const slot_image &img : slot.images)
{
bitmaps.push_back(img.bitmap);
}
// process image with llm
for (int i = 0; i < img.image_tokens; i += n_batch)
{
int n_eval = img.image_tokens - i;
if (n_eval > n_batch)
{
n_eval = n_batch;
}
mtmd_input_text inp_txt;
inp_txt.text = slot.mtmd_prompt.c_str();
inp_txt.add_special = add_bos_token;
inp_txt.parse_special = true;
const int n_embd = llama_model_n_embd(model);
float * embd = img.image_embedding + i * n_embd;
llava_embd_batch llava_batch = llava_embd_batch(embd, n_eval, slot.n_past, 0);
if (llama_decode(ctx, llava_batch.batch))
{
LOG("%s : failed to eval image\n", __func__);
return false;
}
slot.n_past += n_eval;
}
image_idx++;
mtmd::input_chunks chunks(mtmd_input_chunks_init());
int32_t res = mtmd_tokenize(mctx,
chunks.ptr.get(),
&inp_txt,
bitmaps.data(),
bitmaps.size());
if (res != 0)
{
LOG("%s : failed to tokenize multimodal prompt, res = %d\n", __func__, res);
return false;
}
common_batch_clear(batch);
const llama_pos start_pos = (llama_pos) system_tokens.size() + slot.n_past;
llama_pos new_n_past = start_pos;
if (mtmd_helper_eval_chunks(mctx,
ctx,
chunks.ptr.get(),
start_pos,
slot.id,
n_batch,
/*logits_last=*/ false,
&new_n_past) != 0)
{
LOG("%s : failed to eval multimodal chunks\n", __func__);
return false;
}
slot.n_past += (int32_t) (new_n_past - start_pos);
// append prefix of next image
const auto json_prompt = (image_idx >= (int) slot.images.size()) ?
slot.params.input_suffix : // no more images, then process suffix prompt
(json)(slot.images[image_idx].prefix_prompt);
std::vector<llama_token> append_tokens = tokenize(json_prompt, false); // has next image
for (int i = 0; i < (int) append_tokens.size(); ++i)
{
common_batch_add(batch, append_tokens[i], system_tokens.size() + slot.n_past, { slot.id }, true);
slot.n_past += 1;
}
// queue the post-image suffix text for the normal decode + sampling path
common_batch_clear(batch);
std::vector<llama_token> suffix_tokens = tokenize(slot.params.input_suffix, false);
for (llama_token tok : suffix_tokens)
{
common_batch_add(batch, tok, system_tokens.size() + slot.n_past, { slot.id }, false);
slot.n_past += 1;
}
return true;
@@ -1884,8 +1881,11 @@ struct llama_server_context
const bool has_images = process_images(slot);
// process the prefix of first image
std::vector<llama_token> prefix_tokens = has_images ? tokenize(slot.images[0].prefix_prompt, add_bos_token) : prompt_tokens;
// For the multimodal path the whole pre-image / inter-image text is
// tokenized and decoded inside ingest_images() via mtmd, so no prefix
// tokens are queued here; the post-image suffix is appended by
// ingest_images() for the normal decode + sampling loop.
std::vector<llama_token> prefix_tokens = has_images ? std::vector<llama_token>() : prompt_tokens;
int32_t slot_npast = slot.n_past_se > 0 ? slot.n_past_se : slot.n_past;

View File

@@ -1,11 +0,0 @@
--- 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

@@ -17,28 +17,9 @@ cp -r grpc-server.cpp llama.cpp/examples/grpc-server/
cp -r utils.hpp llama.cpp/examples/grpc-server/
cp -rfv llama.cpp/vendor/nlohmann/json.hpp llama.cpp/examples/grpc-server/
## Copy clip/llava files for multimodal support (built as myclip library)
cp -rfv llama.cpp/examples/llava/clip.h llama.cpp/examples/grpc-server/clip.h
cp -rfv llama.cpp/examples/llava/clip.cpp llama.cpp/examples/grpc-server/clip.cpp
cp -rfv llama.cpp/examples/llava/llava.cpp llama.cpp/examples/grpc-server/llava.cpp
# Prepend llama.h include to llava.h
echo '#include "llama.h"' > llama.cpp/examples/grpc-server/llava.h
cat llama.cpp/examples/llava/llava.h >> llama.cpp/examples/grpc-server/llava.h
# Copy clip-impl.h if it exists
if [ -f llama.cpp/examples/llava/clip-impl.h ]; then
cp -rfv llama.cpp/examples/llava/clip-impl.h llama.cpp/examples/grpc-server/clip-impl.h
fi
# Copy stb_image.h
if [ -f llama.cpp/vendor/stb/stb_image.h ]; then
cp -rfv llama.cpp/vendor/stb/stb_image.h llama.cpp/examples/grpc-server/stb_image.h
elif [ -f llama.cpp/common/stb_image.h ]; then
cp -rfv llama.cpp/common/stb_image.h llama.cpp/examples/grpc-server/stb_image.h
fi
## Fix API compatibility in llava.cpp (llama_n_embd -> llama_model_n_embd)
if [ -f llama.cpp/examples/grpc-server/llava.cpp ]; then
sed -i 's/llama_n_embd(/llama_model_n_embd(/g' llama.cpp/examples/grpc-server/llava.cpp
fi
## Multimodal support is provided by the `mtmd` library target (examples/mtmd/),
## which the grpc-server links and includes directly. No source copy is needed:
## clip/llava were pruned upstream and the high-level mtmd_* API is used instead.
set +e
if grep -q "grpc-server" llama.cpp/examples/CMakeLists.txt; then

View File

@@ -11,9 +11,12 @@
#include "json.hpp"
#include "clip.h"
#include "mtmd.h"
using json = nlohmann::json;
// mtmd.h and ik_llama's entire server/common stack (chat.h, server-common.h,
// server-task.h, ...) declare `using json = nlohmann::ordered_json`, so match it
// here: a plain `nlohmann::json` alias collides with mtmd.h's at global scope.
using json = nlohmann::ordered_json;
extern bool server_verbose;
@@ -111,13 +114,12 @@ struct slot_image
{
int32_t id;
bool request_encode_image = false;
float * image_embedding = nullptr;
int32_t image_tokens = 0;
clip_image_u8 * img_data;
std::string prefix_prompt; // before of this image
// mtmd bitmap (image/audio) decoded from the request buffer. Owned by the
// slot; freed via mtmd_bitmap_free() on reset. The high-level mtmd pipeline
// (mtmd_tokenize + mtmd_helper_eval_chunks) consumes these directly, so the
// legacy eager-encode fields (embedding/tokens) and per-image prefix prompt
// are no longer needed.
mtmd_bitmap * bitmap = nullptr;
};
// completion token output with probabilities

View File

@@ -1,5 +1,5 @@
LLAMA_VERSION?=9d5d882d8cd0f0a9283d87ed5e6fe3ee0d925fb1
LLAMA_VERSION?=0ed235ea2c17a19fc8238668653946721ed136fd
LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
CMAKE_ARGS?=
@@ -156,11 +156,11 @@ llama-cpp-grpc: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build purge
$(info ${GREEN}I llama-cpp build info:grpc${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_RPC=ON -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" TARGET="--target grpc-server --target rpc-server" $(MAKE) VARIANT="llama-cpp-grpc-build" build-llama-cpp-grpc-server
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_RPC=ON -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" TARGET="--target grpc-server --target ggml-rpc-server" $(MAKE) VARIANT="llama-cpp-grpc-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/grpc-server llama-cpp-grpc
llama-cpp-rpc-server: llama-cpp-grpc
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/llama.cpp/build/bin/rpc-server llama-cpp-rpc-server
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/llama.cpp/build/bin/ggml-rpc-server llama-cpp-rpc-server
llama.cpp:
mkdir -p llama.cpp

View File

@@ -30,6 +30,19 @@
#define LOCALAI_HAS_SERVER_SCHEMA 1
#include "server-schema.cpp"
#endif
// server-stream.cpp exists only in llama.cpp after the upstream refactor that
// added the SSE stream-resumption layer (stream_session/stream_pipe_producer).
// server-context.cpp calls into it (spipe->cleanup(), stream_aware_should_stop,
// stream_session_attach_pipe), so its definitions must be part of this
// translation unit or the link fails with "undefined reference to
// stream_pipe_producer::cleanup()". The file is self-contained (its only
// external symbols come from server-common, already pulled in above) and the
// http route-handler factories it also defines are unused here but harmless.
// __has_include keeps the source compatible with older pins/forks that predate
// the split.
#if __has_include("server-stream.cpp")
#include "server-stream.cpp"
#endif
#include "server-context.cpp"
// LocalAI

View File

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
# CrispASR version (release tag)
CRISPASR_REPO?=https://github.com/CrispStrobe/CrispASR
CRISPASR_VERSION?=8f1218141b792b8868861c1af17ba1e361b05dc0
CRISPASR_VERSION?=6514c9da00b03a2f0f1b49a43fae4f3a01a41844
SO_TARGET?=libgocrispasr.so
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF

18
backend/go/face-detect/.gitignore vendored Normal file
View File

@@ -0,0 +1,18 @@
# Fetched upstream sources
sources/
# CMake build directories
build*/
# build artifacts staged in-tree by the Makefile (cp from sources/) or
# symlinked for local dev; the real sources live in face-detect.cpp upstream.
*.so
*.so.*
facedetect_capi.h
compile_commands.json
# Compiled backend binary
face-detect-grpc
# Packaging output
package/

View File

@@ -0,0 +1,110 @@
# face-detect backend Makefile.
#
# Upstream pin lives below as FACEDETECT_VERSION?=06914b0... (.github/bump_deps.sh
# can find and update it - matches the voice-detect / parakeet.cpp / whisper.cpp
# convention).
#
# Local dev shortcut: if you already have an out-of-tree face-detect.cpp build,
# symlink the .so + header into this directory and skip the clone/cmake steps:
#
# ln -sf /path/to/face-detect.cpp/build-shared/libfacedetect.so .
# ln -sf /path/to/face-detect.cpp/include/facedetect_capi.h .
# go build -o face-detect-grpc .
#
# The default target below does the proper clone-at-pin + cmake build so CI does
# not need a side-checkout.
FACEDETECT_VERSION?=06914b077d52f90d5421299138e7be6bdd06b5e8
FACEDETECT_REPO?=https://github.com/mudler/face-detect.cpp
GOCMD?=go
GO_TAGS?=
JOBS?=$(shell nproc 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null || echo 4)
BUILD_TYPE?=
NATIVE?=false
# Resolve the target arch. The backend matrix / Docker build pass TARGETARCH
# (amd64|arm64); fall back to uname -m (aarch64|x86_64) for a local build.
RECON_ARCH?=$(or $(TARGETARCH),$(shell uname -m))
# Build ggml + the vendored libjpeg-turbo statically into libfacedetect.so (PIC)
# so the shared lib is self-contained: dlopen needs no libggml*.so alongside it,
# only system libs (libstdc++/libgomp/libc) the runtime image already provides.
# The vendored jpeg symbols are hidden via -Wl,--exclude-libs,ALL on the C++
# side, so only the facedetect_capi_* surface is exported.
CMAKE_ARGS?=-DCMAKE_BUILD_TYPE=Release -DFACEDETECT_SHARED=ON -DFACEDETECT_BUILD_CLI=OFF -DFACEDETECT_BUILD_TESTS=OFF -DBUILD_SHARED_LIBS=OFF -DCMAKE_POSITION_INDEPENDENT_CODE=ON
ifeq ($(NATIVE),false)
CMAKE_ARGS+=-DGGML_NATIVE=OFF
endif
# face-detect.cpp gates its GGML backends behind FACEDETECT_GGML_* options and
# does set(GGML_CUDA ${FACEDETECT_GGML_CUDA} CACHE BOOL "" FORCE), so a bare
# -DGGML_CUDA=ON is overwritten back to OFF. Forward the FACEDETECT_GGML_*
# options instead. (openblas is not gated, so -DGGML_BLAS passes through.)
ifeq ($(BUILD_TYPE),cublas)
CMAKE_ARGS+=-DFACEDETECT_GGML_CUDA=ON
# Opt-in cuDNN implicit-GEMM conv path (kills im2col on GPU, SCRFD 2.3x
# vs torch-cuDNN parity). Only the arm64 + CUDA 13 image (GB10/Jetson/L4T)
# ships libcudnn9 + the -dev headers, so gate cuDNN to that variant.
# x86 CUDA images carry no cuDNN -> enabling it there is a link failure.
ifeq ($(CUDA_MAJOR_VERSION),13)
ifneq (,$(filter arm64 aarch64,$(RECON_ARCH)))
CMAKE_ARGS+=-DFACEDETECT_GGML_CUDNN=ON
endif
endif
else ifeq ($(BUILD_TYPE),openblas)
CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
else ifeq ($(BUILD_TYPE),hipblas)
CMAKE_ARGS+=-DFACEDETECT_GGML_HIP=ON
else ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DFACEDETECT_GGML_VULKAN=ON
else ifeq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DFACEDETECT_GGML_METAL=ON
endif
.PHONY: face-detect-grpc package build clean purge test all
all: face-detect-grpc
# Clone the upstream face-detect.cpp source at the pinned commit. Directory acts
# as the target so make only re-clones when missing. After a FACEDETECT_VERSION
# bump, run 'make purge && make' to refetch.
sources/face-detect.cpp:
mkdir -p sources/face-detect.cpp
cd sources/face-detect.cpp && \
git init -q && \
git remote add origin $(FACEDETECT_REPO) && \
git fetch --depth 1 origin $(FACEDETECT_VERSION) && \
git checkout FETCH_HEAD && \
git submodule update --init --recursive --depth 1 --single-branch
# Build the shared lib + header out-of-tree, then stage them next to the Go
# sources so purego.Dlopen("libfacedetect.so") and the cgo-less build both pick
# them up.
libfacedetect.so: sources/face-detect.cpp
cmake -B sources/face-detect.cpp/build-shared -S sources/face-detect.cpp $(CMAKE_ARGS)
cmake --build sources/face-detect.cpp/build-shared --config Release -j$(JOBS) --target facedetect
cp -fv sources/face-detect.cpp/build-shared/libfacedetect.so* ./ 2>/dev/null || true
cp -fv sources/face-detect.cpp/include/facedetect_capi.h ./
face-detect-grpc: libfacedetect.so main.go gofacedetect.go options.go
CGO_ENABLED=0 $(GOCMD) build -tags "$(GO_TAGS)" -o face-detect-grpc .
package: face-detect-grpc
bash package.sh
build: package
# Test target. The embed/detect/verify/analyze smoke specs are gated on
# FACEDETECT_BACKEND_TEST_MODEL + FACEDETECT_BACKEND_TEST_IMAGE; without them the
# heavy specs auto-skip and only the pure-Go parsing specs run.
test:
LD_LIBRARY_PATH=$(CURDIR):$$LD_LIBRARY_PATH $(GOCMD) test ./... -count=1
clean: purge
rm -rf libfacedetect.so* facedetect_capi.h package face-detect-grpc
purge:
rm -rf sources/face-detect.cpp

View File

@@ -0,0 +1,431 @@
package main
import (
"encoding/base64"
"encoding/json"
"errors"
"fmt"
"math"
"os"
"path/filepath"
"strconv"
"strings"
"time"
"unsafe"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/xlog"
)
// purego-bound entry points from libfacedetect.so. Names match
// facedetect_capi.h exactly so a `nm libfacedetect.so | grep facedetect_capi`
// is enough to spot drift.
//
// The opaque ctx and the malloc'd char*/float* return values are declared as
// uintptr so we get the raw pointer back and can release it via the matching
// capi free function. purego's native string/[]float32 returns would copy and
// forget the original pointer, leaking the C-owned buffer on every call.
var (
CppAbiVersion func() int32
CppLoad func(ggufPath string) uintptr
CppFree func(ctx uintptr)
CppLastError func(ctx uintptr) string
CppFreeString func(s uintptr)
CppFreeVec func(v uintptr)
CppEmbedPath func(ctx uintptr, imagePath string, outVec, outDim unsafe.Pointer) int32
CppEmbedRGB func(ctx uintptr, rgb []byte, width, height int32, outVec, outDim unsafe.Pointer) int32
CppDetectJSON func(ctx uintptr, imagePath string) uintptr
CppVerifyPaths func(ctx uintptr, a, b string, threshold float32, antiSpoof int32, outDistance, outVerified unsafe.Pointer) int32
CppAnalyzeJSON func(ctx uintptr, imagePath string) uintptr
)
// FaceDetect implements the face-recognition (biometric) subset of the Backend
// gRPC service over libfacedetect.so. The C side keeps a single loaded model
// pack plus a per-ctx last-error buffer and is not reentrant, so
// base.SingleThread serializes every call.
type FaceDetect struct {
base.SingleThread
opts loadOptions
ctxPtr uintptr
}
func (f *FaceDetect) Load(opts *pb.ModelOptions) error {
model := opts.ModelFile
if model == "" {
model = opts.ModelPath
}
if !filepath.IsAbs(model) && opts.ModelPath != "" {
model = filepath.Join(opts.ModelPath, model)
}
if model == "" {
return errors.New("face-detect: ModelFile is required")
}
f.opts = parseOptions(opts.Options)
if f.opts.modelName == "" {
f.opts.modelName = filepath.Base(model)
}
// Propagate LocalAI's per-model thread budget to the engine. LocalAI spawns
// one backend process per model and serves requests concurrently, so the
// engine's own min(hardware_concurrency, 8) default can oversubscribe cores.
// FACEDETECT_THREADS is read by the engine at backend construction, so it
// must be set before the capi load. A non-positive Threads means "unset":
// leave the env alone so the engine keeps its sane default.
threads := opts.Threads
if threads > 0 {
if err := os.Setenv("FACEDETECT_THREADS", strconv.Itoa(int(threads))); err != nil {
return fmt.Errorf("face-detect: set FACEDETECT_THREADS: %w", err)
}
xlog.Info("face-detect: applying LocalAI thread budget", "threads", threads)
}
xlog.Info("face-detect: loading model", "model", model,
"verify_threshold", f.opts.verifyThreshold, "abi", CppAbiVersion())
ctx := CppLoad(model)
if ctx == 0 {
// The last-error buffer lives on the ctx that was never returned, so
// surface the path the operator tried to load instead.
return fmt.Errorf("face-detect: facedetect_capi_load failed for %q", model)
}
f.ctxPtr = ctx
return nil
}
// Embeddings returns the L2-normalized ArcFace embedding of the primary face in
// the supplied image. Mirroring the Python face backend, the image is read from
// Images[0] as a base64 payload; materializeImage decodes it to a temp file so
// the path-based C-API can run its own decode (cv2.imread parity). The gRPC
// server wraps the returned slice in an EmbeddingResult.
func (f *FaceDetect) Embeddings(req *pb.PredictOptions) ([]float32, error) {
if f.ctxPtr == 0 {
return nil, errors.New("face-detect: model not loaded")
}
if len(req.Images) == 0 || req.Images[0] == "" {
return nil, errors.New("face-detect: Embedding requires Images[0] to be a base64 image")
}
path, cleanup, err := materializeImage(req.Images[0])
if err != nil {
return nil, err
}
defer cleanup()
return f.embedPath(path)
}
func (f *FaceDetect) embedPath(path string) ([]float32, error) {
var vec uintptr
var dim int32
rc := CppEmbedPath(f.ctxPtr, path, unsafe.Pointer(&vec), unsafe.Pointer(&dim))
if rc != 0 || vec == 0 || dim <= 0 {
return nil, f.lastErr("embed", path)
}
defer CppFreeVec(vec)
// Copy out of the C-owned malloc'd buffer before freeing it. The
// uintptr->Pointer conversion trips vet's unsafeptr check, which can't tell
// a C heap pointer from Go-managed memory; safe here, the GC neither tracks
// nor moves this buffer and we copy immediately.
src := unsafe.Slice((*float32)(unsafe.Pointer(vec)), int(dim)) //nolint:govet // C-owned malloc'd vector, copied out before free
out := make([]float32, int(dim))
copy(out, src)
return out, nil
}
// Detect runs SCRFD over the image and returns one Detection per face. The
// C-API emits a box as [x1,y1,x2,y2] in pixels; the proto carries x/y plus
// width/height, so the corners are converted. The 5 facial landmarks the engine
// also returns are dropped: the Detection message has no field for them.
func (f *FaceDetect) Detect(req *pb.DetectOptions) (pb.DetectResponse, error) {
if f.ctxPtr == 0 {
return pb.DetectResponse{}, errors.New("face-detect: model not loaded")
}
if req.Src == "" {
return pb.DetectResponse{}, errors.New("face-detect: src image is required")
}
path, cleanup, err := materializeImage(req.Src)
if err != nil {
return pb.DetectResponse{}, err
}
defer cleanup()
faces, err := f.detectFaces(path)
if err != nil {
return pb.DetectResponse{}, err
}
dets := make([]*pb.Detection, 0, len(faces))
for _, fc := range faces {
if req.Threshold > 0 && fc.Score < req.Threshold {
continue
}
x, y, w, h := fc.xywh()
dets = append(dets, &pb.Detection{
X: x,
Y: y,
Width: w,
Height: h,
Confidence: fc.Score,
ClassName: "face",
})
}
return pb.DetectResponse{Detections: dets}, nil
}
// FaceVerify embeds the primary face in each image and reports whether they are
// the same identity by cosine distance against a threshold. A request threshold
// <= 0 falls back to the model-configured default (verify_threshold option,
// 0.35 if unset). When anti_spoofing is set, the C-API applies a MiniFASNet
// veto internally (verified forced false on a spoof); the per-image liveness
// scores are not exposed by the verify entry point, so img*_is_real /
// img*_antispoof_score stay at their zero values.
func (f *FaceDetect) FaceVerify(req *pb.FaceVerifyRequest) (pb.FaceVerifyResponse, error) {
if f.ctxPtr == 0 {
return pb.FaceVerifyResponse{}, errors.New("face-detect: model not loaded")
}
if req.Img1 == "" || req.Img2 == "" {
return pb.FaceVerifyResponse{}, errors.New("face-detect: img1 and img2 are required")
}
path1, cleanup1, err := materializeImage(req.Img1)
if err != nil {
return pb.FaceVerifyResponse{}, err
}
defer cleanup1()
path2, cleanup2, err := materializeImage(req.Img2)
if err != nil {
return pb.FaceVerifyResponse{}, err
}
defer cleanup2()
threshold := req.Threshold
if threshold <= 0 {
threshold = f.opts.verifyThreshold
}
antiSpoof := int32(0)
if req.AntiSpoofing {
antiSpoof = 1
}
started := time.Now()
var distance float32
var verified int32
rc := CppVerifyPaths(f.ctxPtr, path1, path2, threshold, antiSpoof,
unsafe.Pointer(&distance), unsafe.Pointer(&verified))
if rc != 0 {
return pb.FaceVerifyResponse{}, f.lastErr("verify", req.Img1[:min(8, len(req.Img1))]+"...")
}
elapsedMs := float32(time.Since(started).Seconds() * 1000.0)
// Confidence decays linearly from 100 at distance 0 to 0 at the threshold,
// matching the Python face backend's reporting.
confidence := float32(0)
if threshold > 0 {
confidence = float32(math.Max(0, math.Min(100, (1.0-float64(distance)/float64(threshold))*100.0)))
}
return pb.FaceVerifyResponse{
Verified: verified != 0,
Distance: distance,
Threshold: threshold,
Confidence: confidence,
Model: f.opts.modelName,
Img1Area: f.bestArea(path1),
Img2Area: f.bestArea(path2),
ProcessingTimeMs: elapsedMs,
}, nil
}
// FaceAnalyze runs the genderage head on every detected face. The C-API returns
// "M"/"F" gender labels and a rounded age; the labels are normalized to the
// "Man"/"Woman" values the proto documents.
func (f *FaceDetect) FaceAnalyze(req *pb.FaceAnalyzeRequest) (pb.FaceAnalyzeResponse, error) {
if f.ctxPtr == 0 {
return pb.FaceAnalyzeResponse{}, errors.New("face-detect: model not loaded")
}
if req.Img == "" {
return pb.FaceAnalyzeResponse{}, errors.New("face-detect: img is required")
}
path, cleanup, err := materializeImage(req.Img)
if err != nil {
return pb.FaceAnalyzeResponse{}, err
}
defer cleanup()
ptr := CppAnalyzeJSON(f.ctxPtr, path)
if ptr == 0 {
return pb.FaceAnalyzeResponse{}, f.lastErr("analyze", path)
}
defer CppFreeString(ptr)
faces, err := parseAnalyzeJSON(goStringFromCPtr(ptr))
if err != nil {
return pb.FaceAnalyzeResponse{}, fmt.Errorf("face-detect: analyze JSON: %w", err)
}
return pb.FaceAnalyzeResponse{Faces: faces}, nil
}
// faceBox is one entry of the detect/analyze JSON documents the engine emits.
type faceBox struct {
Score float32 `json:"score"`
Box []float32 `json:"box"`
Age float32 `json:"age"`
Gender string `json:"gender"`
}
// xywh converts the engine's [x1,y1,x2,y2] box into the x/y/width/height the
// proto carries. A short or missing box yields zeros.
func (b faceBox) xywh() (x, y, w, h float32) {
if len(b.Box) < 4 {
return 0, 0, 0, 0
}
return b.Box[0], b.Box[1], b.Box[2] - b.Box[0], b.Box[3] - b.Box[1]
}
type facesJSON struct {
Faces []faceBox `json:"faces"`
}
func (f *FaceDetect) detectFaces(path string) ([]faceBox, error) {
ptr := CppDetectJSON(f.ctxPtr, path)
if ptr == 0 {
return nil, f.lastErr("detect", path)
}
defer CppFreeString(ptr)
var doc facesJSON
if err := json.Unmarshal([]byte(goStringFromCPtr(ptr)), &doc); err != nil {
return nil, fmt.Errorf("face-detect: detect JSON: %w", err)
}
return doc.Faces, nil
}
// bestArea returns the FacialArea of the highest-scoring face in an image, or an
// empty area when detection fails or finds nothing. Best-effort: verify already
// succeeded, so a missing region must not turn a valid match into an error.
func (f *FaceDetect) bestArea(path string) *pb.FacialArea {
faces, err := f.detectFaces(path)
if err != nil || len(faces) == 0 {
return &pb.FacialArea{}
}
best := faces[0]
for _, fc := range faces[1:] {
if fc.Score > best.Score {
best = fc
}
}
x, y, w, h := best.xywh()
return &pb.FacialArea{X: x, Y: y, W: w, H: h}
}
// parseAnalyzeJSON maps the engine's analyze document onto FaceAnalysis entries.
// The engine reports gender as "M"/"F"; both the dominant label and the score
// map are filled with the "Man"/"Woman" form the proto documents.
func parseAnalyzeJSON(doc string) ([]*pb.FaceAnalysis, error) {
var parsed facesJSON
if err := json.Unmarshal([]byte(doc), &parsed); err != nil {
return nil, err
}
out := make([]*pb.FaceAnalysis, 0, len(parsed.Faces))
for _, fc := range parsed.Faces {
x, y, w, h := fc.xywh()
fa := &pb.FaceAnalysis{
Region: &pb.FacialArea{X: x, Y: y, W: w, H: h},
FaceConfidence: fc.Score,
Age: fc.Age,
}
if label := normalizeGender(fc.Gender); label != "" {
fa.DominantGender = label
fa.Gender = map[string]float32{label: 1.0}
}
out = append(out, fa)
}
return out, nil
}
// normalizeGender maps the engine's "M"/"F" code to the "Man"/"Woman" labels the
// proto documents. Unknown codes pass through unchanged.
func normalizeGender(g string) string {
switch strings.ToUpper(strings.TrimSpace(g)) {
case "M":
return "Man"
case "F":
return "Woman"
case "":
return ""
default:
return g
}
}
// materializeImage decodes a base64 image payload into a temp file and returns
// its path plus a cleanup func. As a convenience for callers that already pass a
// filesystem path (e.g. a test fixture), an existing path is used as-is with a
// no-op cleanup. data: URI prefixes are stripped before decoding.
func materializeImage(src string) (path string, cleanup func(), err error) {
noop := func() {}
if src == "" {
return "", noop, errors.New("face-detect: empty image input")
}
if _, statErr := os.Stat(src); statErr == nil {
return src, noop, nil
}
payload := src
if i := strings.Index(payload, ","); strings.HasPrefix(payload, "data:") && i >= 0 {
payload = payload[i+1:]
}
data, decErr := base64.StdEncoding.DecodeString(strings.TrimSpace(payload))
if decErr != nil || len(data) == 0 {
return "", noop, errors.New("face-detect: image is neither an existing path nor valid base64")
}
tmp, createErr := os.CreateTemp("", "face-detect-*.img")
if createErr != nil {
return "", noop, fmt.Errorf("face-detect: create temp image: %w", createErr)
}
cleanup = func() { _ = os.Remove(tmp.Name()) }
if _, wErr := tmp.Write(data); wErr != nil {
_ = tmp.Close()
cleanup()
return "", noop, fmt.Errorf("face-detect: write temp image: %w", wErr)
}
if cErr := tmp.Close(); cErr != nil {
cleanup()
return "", noop, fmt.Errorf("face-detect: close temp image: %w", cErr)
}
return tmp.Name(), cleanup, nil
}
// lastErr wraps the C-API's per-ctx last-error buffer into a Go error.
func (f *FaceDetect) lastErr(op, subject string) error {
msg := strings.TrimSpace(CppLastError(f.ctxPtr))
if msg == "" {
msg = "no error detail"
}
return fmt.Errorf("face-detect: %s failed for %q: %s", op, subject, msg)
}
// goStringFromCPtr copies a NUL-terminated C string into Go memory. cptr is a
// malloc'd buffer the caller owns; release it via CppFreeString after the copy.
//
// The uintptr->Pointer conversion trips vet's unsafeptr check, which can't tell
// a C heap pointer from Go-managed memory. Safe here: the GC neither tracks nor
// moves the buffer and we dereference it immediately to copy the bytes out.
func goStringFromCPtr(cptr uintptr) string {
if cptr == 0 {
return ""
}
p := unsafe.Pointer(cptr) //nolint:govet // C-owned malloc'd buffer, not Go-GC memory (see doc above)
n := 0
for *(*byte)(unsafe.Add(p, n)) != 0 {
n++
}
return string(unsafe.Slice((*byte)(p), n))
}

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package main
import (
"encoding/base64"
"os"
"sync"
"testing"
"github.com/ebitengine/purego"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestFaceDetect(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "face-detect Backend Suite")
}
var (
libLoadOnce sync.Once
libLoadErr error
)
// ensureLibLoaded mirrors main.go's bootstrap so a Go test can drive the C-API
// bridge without spinning up the gRPC server. Records the error (the smoke
// specs skip themselves) when libfacedetect.so is not loadable from cwd
// (LD_LIBRARY_PATH or a symlink in ./).
func ensureLibLoaded() error {
libLoadOnce.Do(func() {
libName := os.Getenv("FACEDETECT_LIBRARY")
if libName == "" {
libName = "libfacedetect.so"
}
lib, err := purego.Dlopen(libName, purego.RTLD_NOW|purego.RTLD_GLOBAL)
if err != nil {
libLoadErr = err
return
}
purego.RegisterLibFunc(&CppAbiVersion, lib, "facedetect_capi_abi_version")
purego.RegisterLibFunc(&CppLoad, lib, "facedetect_capi_load")
purego.RegisterLibFunc(&CppFree, lib, "facedetect_capi_free")
purego.RegisterLibFunc(&CppLastError, lib, "facedetect_capi_last_error")
purego.RegisterLibFunc(&CppFreeString, lib, "facedetect_capi_free_string")
purego.RegisterLibFunc(&CppFreeVec, lib, "facedetect_capi_free_vec")
purego.RegisterLibFunc(&CppEmbedPath, lib, "facedetect_capi_embed_path")
purego.RegisterLibFunc(&CppEmbedRGB, lib, "facedetect_capi_embed_rgb")
purego.RegisterLibFunc(&CppDetectJSON, lib, "facedetect_capi_detect_path_json")
purego.RegisterLibFunc(&CppVerifyPaths, lib, "facedetect_capi_verify_paths")
purego.RegisterLibFunc(&CppAnalyzeJSON, lib, "facedetect_capi_analyze_path_json")
})
return libLoadErr
}
var _ = Describe("parseOptions", func() {
It("defaults verify_threshold to 0.35", func() {
o := parseOptions(nil)
Expect(o.verifyThreshold).To(Equal(float32(0.35)))
Expect(o.modelName).To(Equal(""))
})
It("parses verify_threshold, threshold alias and model_name", func() {
o := parseOptions([]string{"verify_threshold:0.4", "model_name:buffalo_l", "unknown:x"})
Expect(o.verifyThreshold).To(Equal(float32(0.4)))
Expect(o.modelName).To(Equal("buffalo_l"))
o2 := parseOptions([]string{"threshold:0.3"})
Expect(o2.verifyThreshold).To(Equal(float32(0.3)))
})
It("ignores non-positive thresholds and keeps the default", func() {
o := parseOptions([]string{"verify_threshold:0", "threshold:-1"})
Expect(o.verifyThreshold).To(Equal(float32(0.35)))
})
})
var _ = Describe("normalizeGender", func() {
It("maps M/F codes to Man/Woman", func() {
Expect(normalizeGender("M")).To(Equal("Man"))
Expect(normalizeGender("f")).To(Equal("Woman"))
Expect(normalizeGender(" m ")).To(Equal("Man"))
})
It("passes empty and unknown codes through", func() {
Expect(normalizeGender("")).To(Equal(""))
Expect(normalizeGender("nonbinary")).To(Equal("nonbinary"))
})
})
var _ = Describe("faceBox.xywh", func() {
It("converts an [x1,y1,x2,y2] box to x/y/width/height", func() {
b := faceBox{Box: []float32{10, 20, 50, 80}}
x, y, w, h := b.xywh()
Expect(x).To(Equal(float32(10)))
Expect(y).To(Equal(float32(20)))
Expect(w).To(Equal(float32(40)))
Expect(h).To(Equal(float32(60)))
})
It("returns zeros for a short box", func() {
x, y, w, h := faceBox{Box: []float32{1, 2}}.xywh()
Expect([]float32{x, y, w, h}).To(Equal([]float32{0, 0, 0, 0}))
})
})
var _ = Describe("parseAnalyzeJSON", func() {
It("maps region, age and gender for each face", func() {
doc := `{"faces":[
{"score":0.997,"box":[10,20,50,80],"age":31,"gender":"M"},
{"score":0.81,"box":[0,0,40,40],"age":24,"gender":"F"}]}`
faces, err := parseAnalyzeJSON(doc)
Expect(err).ToNot(HaveOccurred())
Expect(faces).To(HaveLen(2))
Expect(faces[0].FaceConfidence).To(BeNumerically("~", 0.997, 1e-4))
Expect(faces[0].Age).To(BeNumerically("~", 31, 1e-4))
Expect(faces[0].DominantGender).To(Equal("Man"))
Expect(faces[0].Gender).To(HaveKeyWithValue("Man", float32(1.0)))
Expect(faces[0].Region.W).To(Equal(float32(40)))
Expect(faces[0].Region.H).To(Equal(float32(60)))
Expect(faces[1].DominantGender).To(Equal("Woman"))
})
It("tolerates a missing gender field", func() {
faces, err := parseAnalyzeJSON(`{"faces":[{"score":0.5,"box":[0,0,10,10],"age":40}]}`)
Expect(err).ToNot(HaveOccurred())
Expect(faces).To(HaveLen(1))
Expect(faces[0].DominantGender).To(Equal(""))
Expect(faces[0].Gender).To(BeEmpty())
})
It("returns no faces for an empty document", func() {
faces, err := parseAnalyzeJSON(`{"faces":[]}`)
Expect(err).ToNot(HaveOccurred())
Expect(faces).To(BeEmpty())
})
It("returns an error on malformed JSON", func() {
_, err := parseAnalyzeJSON(`{not-json`)
Expect(err).To(HaveOccurred())
})
})
var _ = Describe("materializeImage", func() {
It("decodes a base64 payload to a temp file", func() {
payload := base64.StdEncoding.EncodeToString([]byte("\xff\xd8\xff\xe0fake-jpeg"))
path, cleanup, err := materializeImage(payload)
Expect(err).ToNot(HaveOccurred())
defer cleanup()
data, rerr := os.ReadFile(path)
Expect(rerr).ToNot(HaveOccurred())
Expect(data).To(Equal([]byte("\xff\xd8\xff\xe0fake-jpeg")))
})
It("strips a data: URI prefix before decoding", func() {
payload := "data:image/png;base64," + base64.StdEncoding.EncodeToString([]byte("hello"))
path, cleanup, err := materializeImage(payload)
Expect(err).ToNot(HaveOccurred())
defer cleanup()
data, rerr := os.ReadFile(path)
Expect(rerr).ToNot(HaveOccurred())
Expect(data).To(Equal([]byte("hello")))
})
It("uses an existing path as-is", func() {
tmp, err := os.CreateTemp("", "face-detect-fixture-*.bin")
Expect(err).ToNot(HaveOccurred())
defer func() { _ = os.Remove(tmp.Name()) }()
Expect(tmp.Close()).To(Succeed())
path, cleanup, err := materializeImage(tmp.Name())
Expect(err).ToNot(HaveOccurred())
defer cleanup()
Expect(path).To(Equal(tmp.Name()))
})
It("errors on input that is neither a path nor base64", func() {
_, _, err := materializeImage("not base64!!!")
Expect(err).To(HaveOccurred())
})
})
// The specs below exercise the real C-API end to end. They run only when both a
// model GGUF and a test image are provided, and skip cleanly otherwise so the
// suite stays green without large assets.
var _ = Describe("FaceDetect end-to-end", Ordered, func() {
var (
f *FaceDetect
modelPath = os.Getenv("FACEDETECT_BACKEND_TEST_MODEL")
imagePath = os.Getenv("FACEDETECT_BACKEND_TEST_IMAGE")
)
BeforeAll(func() {
if modelPath == "" || imagePath == "" {
Skip("set FACEDETECT_BACKEND_TEST_MODEL and FACEDETECT_BACKEND_TEST_IMAGE to run the e2e specs")
}
if err := ensureLibLoaded(); err != nil {
Skip("libfacedetect.so not loadable: " + err.Error())
}
f = &FaceDetect{}
Expect(f.Load(&pb.ModelOptions{ModelFile: modelPath})).To(Succeed())
})
It("embeds the primary face in an image", func() {
emb, err := f.Embeddings(&pb.PredictOptions{Images: []string{imagePath}})
Expect(err).ToNot(HaveOccurred())
Expect(emb).ToNot(BeEmpty())
})
It("detects at least one face", func() {
resp, err := f.Detect(&pb.DetectOptions{Src: imagePath})
Expect(err).ToNot(HaveOccurred())
Expect(resp.Detections).ToNot(BeEmpty())
Expect(resp.Detections[0].ClassName).To(Equal("face"))
})
It("verifies an image against itself as the same identity", func() {
resp, err := f.FaceVerify(&pb.FaceVerifyRequest{Img1: imagePath, Img2: imagePath})
Expect(err).ToNot(HaveOccurred())
Expect(resp.Verified).To(BeTrue())
Expect(resp.Distance).To(BeNumerically("<=", resp.Threshold))
})
It("analyzes age/gender for each face", func() {
resp, err := f.FaceAnalyze(&pb.FaceAnalyzeRequest{Img: imagePath})
Expect(err).ToNot(HaveOccurred())
Expect(resp.Faces).ToNot(BeEmpty())
})
})

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package main
// Started internally by LocalAI - one gRPC server per loaded model.
//
// Loads libfacedetect.so via purego and registers the flat C-API entry points
// declared in facedetect_capi.h. The library name can be overridden with
// FACEDETECT_LIBRARY (mirrors the VOICEDETECT_LIBRARY / PARAKEET_LIBRARY
// convention in the sibling backends); the default looks for the .so next to
// this binary (resolved via LD_LIBRARY_PATH by run.sh).
import (
"flag"
"fmt"
"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("FACEDETECT_LIBRARY")
if libName == "" {
libName = "libfacedetect.so"
}
lib, err := purego.Dlopen(libName, purego.RTLD_NOW|purego.RTLD_GLOBAL)
if err != nil {
panic(fmt.Errorf("face-detect: dlopen %q: %w", libName, err))
}
// Bound 1:1 to facedetect_capi.h. char*/float* returns are registered as
// uintptr so the raw pointer can be freed via the matching capi free fn.
libFuncs := []LibFuncs{
{&CppAbiVersion, "facedetect_capi_abi_version"},
{&CppLoad, "facedetect_capi_load"},
{&CppFree, "facedetect_capi_free"},
{&CppLastError, "facedetect_capi_last_error"},
{&CppFreeString, "facedetect_capi_free_string"},
{&CppFreeVec, "facedetect_capi_free_vec"},
{&CppEmbedPath, "facedetect_capi_embed_path"},
{&CppEmbedRGB, "facedetect_capi_embed_rgb"},
{&CppDetectJSON, "facedetect_capi_detect_path_json"},
{&CppVerifyPaths, "facedetect_capi_verify_paths"},
{&CppAnalyzeJSON, "facedetect_capi_analyze_path_json"},
}
for _, lf := range libFuncs {
purego.RegisterLibFunc(lf.FuncPtr, lib, lf.Name)
}
fmt.Fprintf(os.Stderr, "[face-detect] ABI=%d\n", CppAbiVersion())
flag.Parse()
if err := grpc.StartServer(*addr, &FaceDetect{}); err != nil {
panic(err)
}
}

View File

@@ -0,0 +1,47 @@
package main
import (
"strconv"
"strings"
)
// defaultVerifyThreshold is the cosine-distance cutoff used when a request does
// not set one. Matches the insightface buffalo_l ArcFace R50 default the Python
// face backend ships with so the two implementations agree on verdicts out of
// the box.
const defaultVerifyThreshold float32 = 0.35
// loadOptions holds the parsed model-level options for face-detect.
type loadOptions struct {
verifyThreshold float32
modelName string
}
func splitOption(o string) (key, value string, ok bool) {
i := strings.Index(o, ":")
if i < 0 {
return "", "", false
}
return strings.TrimSpace(o[:i]), strings.TrimSpace(o[i+1:]), true
}
// parseOptions reads the backend "key:value" option slice. Unknown keys are
// ignored. Defaults: verify_threshold 0.35, model_name derived from the file.
func parseOptions(opts []string) loadOptions {
o := loadOptions{verifyThreshold: defaultVerifyThreshold}
for _, oo := range opts {
key, value, ok := splitOption(oo)
if !ok {
continue
}
switch key {
case "verify_threshold", "threshold":
if f, err := strconv.ParseFloat(value, 32); err == nil && f > 0 {
o.verifyThreshold = float32(f)
}
case "model_name":
o.modelName = value
}
}
return o
}

View File

@@ -0,0 +1,68 @@
#!/bin/bash
#
# Bundle the face-detect-grpc binary, libfacedetect.so, the core runtime libs
# (libc/libstdc++/libgomp + ld.so) and the GPU runtime for the active BUILD_TYPE
# so the package is self-contained. Mirrors backend/go/voice-detect/package.sh;
# run.sh routes the (CGO_ENABLED=0) binary through lib/ld.so so the packaged libc
# is used instead of the host's.
set -e
CURDIR=$(dirname "$(realpath "$0")")
REPO_ROOT="${CURDIR}/../../.."
mkdir -p "$CURDIR/package/lib"
cp -avf "$CURDIR/face-detect-grpc" "$CURDIR/package/"
cp -avf "$CURDIR/run.sh" "$CURDIR/package/"
# libfacedetect.so + any soname symlinks. purego.Dlopen resolves it via
# LD_LIBRARY_PATH, which run.sh points at lib/.
cp -avf "$CURDIR"/libfacedetect.so* "$CURDIR/package/lib/" 2>/dev/null || {
echo "ERROR: libfacedetect.so not found in $CURDIR, run 'make' first" >&2
exit 1
}
# Detect architecture and copy the core runtime libs libfacedetect.so links
# against, plus the matching dynamic loader as lib/ld.so.
if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
echo "Detected x86_64 architecture, copying x86_64 libraries..."
cp -arfLv /lib64/ld-linux-x86-64.so.2 "$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 (CUDA/ROCm/Intel/Vulkan loader + ICDs + drivers) based on
# BUILD_TYPE so the backend can reach the GPU without the runtime base image
# shipping those drivers.
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/" "$CURDIR/package/lib/"

View File

@@ -0,0 +1,16 @@
#!/bin/bash
set -e
CURDIR=$(dirname "$(realpath "$0")")
export LD_LIBRARY_PATH="$CURDIR/lib:$CURDIR:${LD_LIBRARY_PATH:-}"
# If a self-contained ld.so was packaged, route through it so the packaged
# libc / libstdc++ are used instead of the host's (matches the voice-detect /
# whisper / parakeet backends' runtime layout).
if [ -f "$CURDIR/lib/ld.so" ]; then
echo "Using lib/ld.so"
exec "$CURDIR/lib/ld.so" "$CURDIR/face-detect-grpc" "$@"
fi
exec "$CURDIR/face-detect-grpc" "$@"

View File

@@ -0,0 +1,15 @@
#!/bin/bash
set -e
CURDIR=$(dirname "$(realpath "$0")")
cd "$CURDIR"
echo "Running face-detect backend tests..."
# The pure-Go parsing specs always run. The embed/detect/verify/analyze smoke
# specs run only when a model + image are provided via
# FACEDETECT_BACKEND_TEST_MODEL and FACEDETECT_BACKEND_TEST_IMAGE; otherwise they
# auto-skip.
LD_LIBRARY_PATH="$CURDIR:${LD_LIBRARY_PATH:-}" go test -v -timeout 1200s .
echo "face-detect tests completed."

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?=8caa3f908ae6d4a4bef531e73b9a969f266a3d1f
STABLEDIFFUSION_GGML_VERSION?=9956436c925a367daeab097598b1ea1f32d3503f
CMAKE_ARGS+=-DGGML_MAX_NAME=128

18
backend/go/voice-detect/.gitignore vendored Normal file
View File

@@ -0,0 +1,18 @@
# Fetched upstream sources
sources/
# CMake build directories
build*/
# build artifacts staged in-tree by the Makefile (cp from sources/) or
# symlinked for local dev; the real sources live in voice-detect.cpp upstream.
*.so
*.so.*
voicedetect_capi.h
compile_commands.json
# Compiled backend binary
voice-detect-grpc
# Packaging output
package/

View File

@@ -0,0 +1,107 @@
# voice-detect backend Makefile.
#
# Upstream pin lives below as VOICEDETECT_VERSION?=3d51077... (.github/bump_deps.sh
# can find and update it - matches the parakeet.cpp / whisper.cpp / ds4 convention).
#
# Local dev shortcut: if you already have an out-of-tree voice-detect.cpp build,
# symlink the .so + header into this directory and skip the clone/cmake steps:
#
# ln -sf /path/to/voice-detect.cpp/build-shared/libvoicedetect.so .
# ln -sf /path/to/voice-detect.cpp/include/voicedetect_capi.h .
# go build -o voice-detect-grpc .
#
# The default target below does the proper clone-at-pin + cmake build so CI does
# not need a side-checkout.
VOICEDETECT_VERSION?=3d510772357538c5182808ac7de2278b84824e24
VOICEDETECT_REPO?=https://github.com/mudler/voice-detect.cpp
GOCMD?=go
GO_TAGS?=
JOBS?=$(shell nproc 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null || echo 4)
BUILD_TYPE?=
NATIVE?=false
# Resolve the target arch. The backend matrix / Docker build pass TARGETARCH
# (amd64|arm64); fall back to uname -m (aarch64|x86_64) for a local build.
RECON_ARCH?=$(or $(TARGETARCH),$(shell uname -m))
# Build ggml statically into libvoicedetect.so (PIC) so the shared lib is
# self-contained: dlopen needs no libggml*.so alongside it, only system libs
# (libstdc++/libgomp/libc) that the runtime image already provides.
CMAKE_ARGS?=-DCMAKE_BUILD_TYPE=Release -DVOICEDETECT_SHARED=ON -DVOICEDETECT_BUILD_CLI=OFF -DVOICEDETECT_BUILD_TESTS=OFF -DBUILD_SHARED_LIBS=OFF -DCMAKE_POSITION_INDEPENDENT_CODE=ON
ifeq ($(NATIVE),false)
CMAKE_ARGS+=-DGGML_NATIVE=OFF
endif
# voice-detect.cpp gates its GGML backends behind VOICEDETECT_GGML_* options and
# does set(GGML_CUDA ${VOICEDETECT_GGML_CUDA} CACHE BOOL "" FORCE), so a bare
# -DGGML_CUDA=ON is overwritten back to OFF. Forward the VOICEDETECT_GGML_*
# options instead. (openblas is not gated, so -DGGML_BLAS passes through.)
ifeq ($(BUILD_TYPE),cublas)
CMAKE_ARGS+=-DVOICEDETECT_GGML_CUDA=ON
# Opt-in cuDNN implicit-GEMM conv path (kills im2col on GPU, reaches
# torch-cuDNN parity). Only the arm64 + CUDA 13 image (GB10/Jetson/L4T)
# ships libcudnn9 + the -dev headers, so gate cuDNN to that variant.
# x86 CUDA images carry no cuDNN -> enabling it there is a link failure.
ifeq ($(CUDA_MAJOR_VERSION),13)
ifneq (,$(filter arm64 aarch64,$(RECON_ARCH)))
CMAKE_ARGS+=-DVOICEDETECT_GGML_CUDNN=ON
endif
endif
else ifeq ($(BUILD_TYPE),openblas)
CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
else ifeq ($(BUILD_TYPE),hipblas)
CMAKE_ARGS+=-DVOICEDETECT_GGML_HIP=ON
else ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DVOICEDETECT_GGML_VULKAN=ON
else ifeq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DVOICEDETECT_GGML_METAL=ON
endif
.PHONY: voice-detect-grpc package build clean purge test all
all: voice-detect-grpc
# Clone the upstream voice-detect.cpp source at the pinned commit. Directory acts
# as the target so make only re-clones when missing. After a VOICEDETECT_VERSION
# bump, run 'make purge && make' to refetch.
sources/voice-detect.cpp:
mkdir -p sources/voice-detect.cpp
cd sources/voice-detect.cpp && \
git init -q && \
git remote add origin $(VOICEDETECT_REPO) && \
git fetch --depth 1 origin $(VOICEDETECT_VERSION) && \
git checkout FETCH_HEAD && \
git submodule update --init --recursive --depth 1 --single-branch
# Build the shared lib + header out-of-tree, then stage them next to the Go
# sources so purego.Dlopen("libvoicedetect.so") and the cgo-less build both pick
# them up.
libvoicedetect.so: sources/voice-detect.cpp
cmake -B sources/voice-detect.cpp/build-shared -S sources/voice-detect.cpp $(CMAKE_ARGS)
cmake --build sources/voice-detect.cpp/build-shared --config Release -j$(JOBS) --target voicedetect
cp -fv sources/voice-detect.cpp/build-shared/libvoicedetect.so* ./ 2>/dev/null || true
cp -fv sources/voice-detect.cpp/include/voicedetect_capi.h ./
voice-detect-grpc: libvoicedetect.so main.go govoicedetect.go options.go
CGO_ENABLED=0 $(GOCMD) build -tags "$(GO_TAGS)" -o voice-detect-grpc .
package: voice-detect-grpc
bash package.sh
build: package
# Test target. The embed/verify/analyze smoke specs are gated on
# VOICEDETECT_BACKEND_TEST_MODEL + VOICEDETECT_BACKEND_TEST_WAV; without them the
# heavy specs auto-skip and only the pure-Go parsing specs run.
test:
LD_LIBRARY_PATH=$(CURDIR):$$LD_LIBRARY_PATH $(GOCMD) test ./... -count=1
clean: purge
rm -rf libvoicedetect.so* voicedetect_capi.h package voice-detect-grpc
purge:
rm -rf sources/voice-detect.cpp

View File

@@ -0,0 +1,273 @@
package main
import (
"encoding/json"
"errors"
"fmt"
"math"
"os"
"path/filepath"
"strconv"
"strings"
"time"
"unsafe"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/xlog"
)
// purego-bound entry points from libvoicedetect.so. Names match
// voicedetect_capi.h exactly so a `nm libvoicedetect.so | grep voicedetect_capi`
// is enough to spot drift.
//
// The opaque ctx and the malloc'd char*/float* return values are declared as
// uintptr so we get the raw pointer back and can release it via the matching
// capi free function. purego's native string/[]float32 returns would copy and
// forget the original pointer, leaking the C-owned buffer on every call.
var (
CppAbiVersion func() int32
CppLoad func(ggufPath string) uintptr
CppFree func(ctx uintptr)
CppLastError func(ctx uintptr) string
CppFreeString func(s uintptr)
CppFreeVec func(v uintptr)
CppEmbedPath func(ctx uintptr, wavPath string, outVec, outDim unsafe.Pointer) int32
CppEmbedPCM func(ctx uintptr, pcm []float32, nSamples, sampleRate int32, outVec, outDim unsafe.Pointer) int32
CppVerifyPaths func(ctx uintptr, a, b string, threshold float32, outDistance, outVerified unsafe.Pointer) int32
CppAnalyzeJSON func(ctx uintptr, wavPath string) uintptr
)
// VoiceDetect implements the speaker-recognition voice subset of the Backend
// gRPC service over libvoicedetect.so. The C side keeps a single loaded model
// plus a per-ctx last-error buffer and is not reentrant, so base.SingleThread
// serializes every call.
type VoiceDetect struct {
base.SingleThread
opts loadOptions
ctxPtr uintptr
}
func (v *VoiceDetect) Load(opts *pb.ModelOptions) error {
model := opts.ModelFile
if model == "" {
model = opts.ModelPath
}
if !filepath.IsAbs(model) && opts.ModelPath != "" {
model = filepath.Join(opts.ModelPath, model)
}
if model == "" {
return errors.New("voice-detect: ModelFile is required")
}
v.opts = parseOptions(opts.Options)
if v.opts.modelName == "" {
v.opts.modelName = filepath.Base(model)
}
// Propagate LocalAI's per-model thread budget to the engine. LocalAI spawns
// one backend process per model and serves requests concurrently, so the
// engine's own min(hardware_concurrency, 8) default can oversubscribe cores.
// VOICEDETECT_THREADS is read by the engine at backend construction, so it
// must be set before the capi load. A non-positive Threads means "unset":
// leave the env alone so the engine keeps its sane default.
threads := opts.Threads
if threads > 0 {
if err := os.Setenv("VOICEDETECT_THREADS", strconv.Itoa(int(threads))); err != nil {
return fmt.Errorf("voice-detect: set VOICEDETECT_THREADS: %w", err)
}
xlog.Info("voice-detect: applying LocalAI thread budget", "threads", threads)
}
xlog.Info("voice-detect: loading model", "model", model,
"verify_threshold", v.opts.verifyThreshold, "abi", CppAbiVersion())
ctx := CppLoad(model)
if ctx == 0 {
// The last-error buffer lives on the ctx that was never returned, so
// surface the path the operator tried to load instead.
return fmt.Errorf("voice-detect: voicedetect_capi_load failed for %q", model)
}
v.ctxPtr = ctx
return nil
}
// VoiceEmbed returns the L2-normalized speaker embedding for an audio clip.
// The request carries a filesystem PATH; the HTTP layer materializes
// base64/URL/data-URI inputs to a temp file before the gRPC call.
func (v *VoiceDetect) VoiceEmbed(req *pb.VoiceEmbedRequest) (pb.VoiceEmbedResponse, error) {
if v.ctxPtr == 0 {
return pb.VoiceEmbedResponse{}, errors.New("voice-detect: model not loaded")
}
if req.Audio == "" {
return pb.VoiceEmbedResponse{}, errors.New("voice-detect: audio path is required")
}
emb, err := v.embedPath(req.Audio)
if err != nil {
return pb.VoiceEmbedResponse{}, err
}
return pb.VoiceEmbedResponse{Embedding: emb, Model: v.opts.modelName}, nil
}
func (v *VoiceDetect) embedPath(path string) ([]float32, error) {
var vec uintptr
var dim int32
rc := CppEmbedPath(v.ctxPtr, path, unsafe.Pointer(&vec), unsafe.Pointer(&dim))
if rc != 0 || vec == 0 || dim <= 0 {
return nil, v.lastErr("embed", path)
}
defer CppFreeVec(vec)
// Copy out of the C-owned malloc'd buffer before freeing it. The
// uintptr->Pointer conversion trips vet's unsafeptr check, which can't tell
// a C heap pointer from Go-managed memory; safe here, the GC neither tracks
// nor moves this buffer and we copy immediately.
src := unsafe.Slice((*float32)(unsafe.Pointer(vec)), int(dim)) //nolint:govet // C-owned malloc'd vector, copied out before free
out := make([]float32, int(dim))
copy(out, src)
return out, nil
}
// VoiceVerify embeds two clips and reports whether they are the same speaker by
// cosine distance against a threshold. A request threshold <= 0 falls back to
// the model-configured default (verify_threshold option, 0.25 if unset).
func (v *VoiceDetect) VoiceVerify(req *pb.VoiceVerifyRequest) (pb.VoiceVerifyResponse, error) {
if v.ctxPtr == 0 {
return pb.VoiceVerifyResponse{}, errors.New("voice-detect: model not loaded")
}
if req.Audio1 == "" || req.Audio2 == "" {
return pb.VoiceVerifyResponse{}, errors.New("voice-detect: audio1 and audio2 are required")
}
threshold := req.Threshold
if threshold <= 0 {
threshold = v.opts.verifyThreshold
}
started := time.Now()
var distance float32
var verified int32
rc := CppVerifyPaths(v.ctxPtr, req.Audio1, req.Audio2, threshold,
unsafe.Pointer(&distance), unsafe.Pointer(&verified))
if rc != 0 {
return pb.VoiceVerifyResponse{}, v.lastErr("verify", req.Audio1+","+req.Audio2)
}
elapsedMs := float32(time.Since(started).Seconds() * 1000.0)
// Confidence decays linearly from 100 at distance 0 to 0 at the threshold,
// matching the Python speaker-recognition backend's reporting.
confidence := float32(0)
if threshold > 0 {
confidence = float32(math.Max(0, math.Min(100, (1.0-float64(distance)/float64(threshold))*100.0)))
}
return pb.VoiceVerifyResponse{
Verified: verified != 0,
Distance: distance,
Threshold: threshold,
Confidence: confidence,
Model: v.opts.modelName,
ProcessingTimeMs: elapsedMs,
}, nil
}
// VoiceAnalyze runs the age/gender/emotion heads on a single clip. The C-API
// always evaluates every supported head, so the request's actions filter is
// advisory and the full analysis is returned as a single segment (the engine
// does not produce time-bounded segments).
func (v *VoiceDetect) VoiceAnalyze(req *pb.VoiceAnalyzeRequest) (pb.VoiceAnalyzeResponse, error) {
if v.ctxPtr == 0 {
return pb.VoiceAnalyzeResponse{}, errors.New("voice-detect: model not loaded")
}
if req.Audio == "" {
return pb.VoiceAnalyzeResponse{}, errors.New("voice-detect: audio path is required")
}
ptr := CppAnalyzeJSON(v.ctxPtr, req.Audio)
if ptr == 0 {
return pb.VoiceAnalyzeResponse{}, v.lastErr("analyze", req.Audio)
}
defer CppFreeString(ptr)
seg, err := parseAnalyzeJSON(goStringFromCPtr(ptr))
if err != nil {
return pb.VoiceAnalyzeResponse{}, fmt.Errorf("voice-detect: analyze JSON for %q: %w", req.Audio, err)
}
return pb.VoiceAnalyzeResponse{Segments: []*pb.VoiceAnalysis{seg}}, nil
}
// analyzeJSON mirrors the document returned by voicedetect_capi_analyze_path_json:
//
// {"age":42.0,
// "gender":{"label":"female","female":0.88,"male":0.12},
// "emotion":{"label":"neutral","scores":{"neutral":0.7, ...}}}
//
// gender is a mixed object (a "label" string plus per-class float scores), so
// it is decoded into raw messages and split in parseAnalyzeJSON.
type analyzeJSON struct {
Age float32 `json:"age"`
Gender map[string]json.RawMessage `json:"gender"`
Emotion struct {
Label string `json:"label"`
Scores map[string]float32 `json:"scores"`
} `json:"emotion"`
}
// parseAnalyzeJSON maps the engine's analyze document onto a VoiceAnalysis.
// start/end stay 0: the model emits a single whole-utterance result, not
// time-bounded segments.
func parseAnalyzeJSON(doc string) (*pb.VoiceAnalysis, error) {
var a analyzeJSON
if err := json.Unmarshal([]byte(doc), &a); err != nil {
return nil, err
}
seg := &pb.VoiceAnalysis{
Age: a.Age,
DominantEmotion: a.Emotion.Label,
Emotion: a.Emotion.Scores,
}
if len(a.Gender) > 0 {
gender := make(map[string]float32, len(a.Gender))
for k, raw := range a.Gender {
if k == "label" {
_ = json.Unmarshal(raw, &seg.DominantGender)
continue
}
var score float32
if err := json.Unmarshal(raw, &score); err == nil {
gender[k] = score
}
}
seg.Gender = gender
}
return seg, nil
}
// lastErr wraps the C-API's per-ctx last-error buffer into a Go error.
func (v *VoiceDetect) lastErr(op, subject string) error {
msg := strings.TrimSpace(CppLastError(v.ctxPtr))
if msg == "" {
msg = "no error detail"
}
return fmt.Errorf("voice-detect: %s failed for %q: %s", op, subject, msg)
}
// goStringFromCPtr copies a NUL-terminated C string into Go memory. cptr is a
// malloc'd buffer the caller owns; release it via CppFreeString after the copy.
//
// The uintptr->Pointer conversion trips vet's unsafeptr check, which can't tell
// a C heap pointer from Go-managed memory. Safe here: the GC neither tracks nor
// moves the buffer and we dereference it immediately to copy the bytes out.
func goStringFromCPtr(cptr uintptr) string {
if cptr == 0 {
return ""
}
p := unsafe.Pointer(cptr) //nolint:govet // C-owned malloc'd buffer, not Go-GC memory (see doc above)
n := 0
for *(*byte)(unsafe.Add(p, n)) != 0 {
n++
}
return string(unsafe.Slice((*byte)(p), n))
}

View File

@@ -0,0 +1,144 @@
package main
import (
"os"
"sync"
"testing"
"github.com/ebitengine/purego"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestVoiceDetect(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "voice-detect Backend Suite")
}
var (
libLoadOnce sync.Once
libLoadErr error
)
// ensureLibLoaded mirrors main.go's bootstrap so a Go test can drive the C-API
// bridge without spinning up the gRPC server. Records the error (the smoke
// specs skip themselves) when libvoicedetect.so is not loadable from cwd
// (LD_LIBRARY_PATH or a symlink in ./).
func ensureLibLoaded() error {
libLoadOnce.Do(func() {
libName := os.Getenv("VOICEDETECT_LIBRARY")
if libName == "" {
libName = "libvoicedetect.so"
}
lib, err := purego.Dlopen(libName, purego.RTLD_NOW|purego.RTLD_GLOBAL)
if err != nil {
libLoadErr = err
return
}
purego.RegisterLibFunc(&CppAbiVersion, lib, "voicedetect_capi_abi_version")
purego.RegisterLibFunc(&CppLoad, lib, "voicedetect_capi_load")
purego.RegisterLibFunc(&CppFree, lib, "voicedetect_capi_free")
purego.RegisterLibFunc(&CppLastError, lib, "voicedetect_capi_last_error")
purego.RegisterLibFunc(&CppFreeString, lib, "voicedetect_capi_free_string")
purego.RegisterLibFunc(&CppFreeVec, lib, "voicedetect_capi_free_vec")
purego.RegisterLibFunc(&CppEmbedPath, lib, "voicedetect_capi_embed_path")
purego.RegisterLibFunc(&CppEmbedPCM, lib, "voicedetect_capi_embed_pcm")
purego.RegisterLibFunc(&CppVerifyPaths, lib, "voicedetect_capi_verify_paths")
purego.RegisterLibFunc(&CppAnalyzeJSON, lib, "voicedetect_capi_analyze_path_json")
})
return libLoadErr
}
var _ = Describe("parseOptions", func() {
It("defaults verify_threshold to 0.25", func() {
o := parseOptions(nil)
Expect(o.verifyThreshold).To(Equal(float32(0.25)))
Expect(o.modelName).To(Equal(""))
})
It("parses verify_threshold, threshold alias and model_name", func() {
o := parseOptions([]string{"verify_threshold:0.4", "model_name:ecapa", "unknown:x"})
Expect(o.verifyThreshold).To(Equal(float32(0.4)))
Expect(o.modelName).To(Equal("ecapa"))
o2 := parseOptions([]string{"threshold:0.3"})
Expect(o2.verifyThreshold).To(Equal(float32(0.3)))
})
It("ignores non-positive thresholds and keeps the default", func() {
o := parseOptions([]string{"verify_threshold:0", "threshold:-1"})
Expect(o.verifyThreshold).To(Equal(float32(0.25)))
})
})
var _ = Describe("parseAnalyzeJSON", func() {
It("maps age, gender label+scores and emotion label+scores", func() {
doc := `{"age":42.0,
"gender":{"label":"female","female":0.88,"male":0.12},
"emotion":{"label":"neutral","scores":{"neutral":0.7,"happy":0.2,"sad":0.1}}}`
seg, err := parseAnalyzeJSON(doc)
Expect(err).ToNot(HaveOccurred())
Expect(seg.Age).To(BeNumerically("~", 42.0, 1e-4))
Expect(seg.Start).To(Equal(float32(0)))
Expect(seg.End).To(Equal(float32(0)))
Expect(seg.DominantGender).To(Equal("female"))
Expect(seg.Gender).To(HaveKeyWithValue("female", BeNumerically("~", 0.88, 1e-4)))
Expect(seg.Gender).To(HaveKeyWithValue("male", BeNumerically("~", 0.12, 1e-4)))
// The "label" entry is consumed into DominantGender, not the score map.
Expect(seg.Gender).ToNot(HaveKey("label"))
Expect(seg.DominantEmotion).To(Equal("neutral"))
Expect(seg.Emotion).To(HaveKeyWithValue("neutral", BeNumerically("~", 0.7, 1e-4)))
Expect(seg.Emotion).To(HaveKeyWithValue("happy", BeNumerically("~", 0.2, 1e-4)))
})
It("tolerates a missing gender block", func() {
seg, err := parseAnalyzeJSON(`{"age":30.0,"emotion":{"label":"happy","scores":{"happy":1.0}}}`)
Expect(err).ToNot(HaveOccurred())
Expect(seg.DominantGender).To(Equal(""))
Expect(seg.DominantEmotion).To(Equal("happy"))
})
It("returns an error on malformed JSON", func() {
_, err := parseAnalyzeJSON(`{not-json`)
Expect(err).To(HaveOccurred())
})
})
// The specs below exercise the real C-API end to end. They run only when both a
// model GGUF and a test WAV are provided, and skip cleanly otherwise so the
// suite stays green without large assets.
var _ = Describe("VoiceDetect end-to-end", Ordered, func() {
var (
v *VoiceDetect
modelPath = os.Getenv("VOICEDETECT_BACKEND_TEST_MODEL")
wavPath = os.Getenv("VOICEDETECT_BACKEND_TEST_WAV")
)
BeforeAll(func() {
if modelPath == "" || wavPath == "" {
Skip("set VOICEDETECT_BACKEND_TEST_MODEL and VOICEDETECT_BACKEND_TEST_WAV to run the e2e specs")
}
if err := ensureLibLoaded(); err != nil {
Skip("libvoicedetect.so not loadable: " + err.Error())
}
v = &VoiceDetect{}
Expect(v.Load(&pb.ModelOptions{ModelFile: modelPath})).To(Succeed())
})
It("embeds an audio clip", func() {
resp, err := v.VoiceEmbed(&pb.VoiceEmbedRequest{Audio: wavPath})
Expect(err).ToNot(HaveOccurred())
Expect(resp.Embedding).ToNot(BeEmpty())
Expect(resp.Model).ToNot(BeEmpty())
})
It("verifies a clip against itself as the same speaker", func() {
resp, err := v.VoiceVerify(&pb.VoiceVerifyRequest{Audio1: wavPath, Audio2: wavPath})
Expect(err).ToNot(HaveOccurred())
Expect(resp.Verified).To(BeTrue())
Expect(resp.Distance).To(BeNumerically("<=", resp.Threshold))
})
})

View File

@@ -0,0 +1,64 @@
package main
// Started internally by LocalAI - one gRPC server per loaded model.
//
// Loads libvoicedetect.so via purego and registers the flat C-API entry points
// declared in voicedetect_capi.h. The library name can be overridden with
// VOICEDETECT_LIBRARY (mirrors the PARAKEET_LIBRARY / OMNIVOICE_LIBRARY
// convention in the sibling backends); the default looks for the .so next to
// this binary (resolved via LD_LIBRARY_PATH by run.sh).
import (
"flag"
"fmt"
"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("VOICEDETECT_LIBRARY")
if libName == "" {
libName = "libvoicedetect.so"
}
lib, err := purego.Dlopen(libName, purego.RTLD_NOW|purego.RTLD_GLOBAL)
if err != nil {
panic(fmt.Errorf("voice-detect: dlopen %q: %w", libName, err))
}
// Bound 1:1 to voicedetect_capi.h. char*/float* returns are registered as
// uintptr so the raw pointer can be freed via the matching capi free fn.
libFuncs := []LibFuncs{
{&CppAbiVersion, "voicedetect_capi_abi_version"},
{&CppLoad, "voicedetect_capi_load"},
{&CppFree, "voicedetect_capi_free"},
{&CppLastError, "voicedetect_capi_last_error"},
{&CppFreeString, "voicedetect_capi_free_string"},
{&CppFreeVec, "voicedetect_capi_free_vec"},
{&CppEmbedPath, "voicedetect_capi_embed_path"},
{&CppEmbedPCM, "voicedetect_capi_embed_pcm"},
{&CppVerifyPaths, "voicedetect_capi_verify_paths"},
{&CppAnalyzeJSON, "voicedetect_capi_analyze_path_json"},
}
for _, lf := range libFuncs {
purego.RegisterLibFunc(lf.FuncPtr, lib, lf.Name)
}
fmt.Fprintf(os.Stderr, "[voice-detect] ABI=%d\n", CppAbiVersion())
flag.Parse()
if err := grpc.StartServer(*addr, &VoiceDetect{}); err != nil {
panic(err)
}
}

View File

@@ -0,0 +1,46 @@
package main
import (
"strconv"
"strings"
)
// defaultVerifyThreshold is the cosine-distance cutoff used when a request does
// not set one. Matches the Python speaker-recognition backend's default so the
// two implementations agree on verdicts out of the box.
const defaultVerifyThreshold float32 = 0.25
// loadOptions holds the parsed model-level options for voice-detect.
type loadOptions struct {
verifyThreshold float32
modelName string
}
func splitOption(o string) (key, value string, ok bool) {
i := strings.Index(o, ":")
if i < 0 {
return "", "", false
}
return strings.TrimSpace(o[:i]), strings.TrimSpace(o[i+1:]), true
}
// parseOptions reads the backend "key:value" option slice. Unknown keys are
// ignored. Defaults: verify_threshold 0.25, model_name derived from the file.
func parseOptions(opts []string) loadOptions {
o := loadOptions{verifyThreshold: defaultVerifyThreshold}
for _, oo := range opts {
key, value, ok := splitOption(oo)
if !ok {
continue
}
switch key {
case "verify_threshold", "threshold":
if f, err := strconv.ParseFloat(value, 32); err == nil && f > 0 {
o.verifyThreshold = float32(f)
}
case "model_name":
o.modelName = value
}
}
return o
}

View File

@@ -0,0 +1,68 @@
#!/bin/bash
#
# Bundle the voice-detect-grpc binary, libvoicedetect.so, the core runtime libs
# (libc/libstdc++/libgomp + ld.so) and the GPU runtime for the active BUILD_TYPE
# so the package is self-contained. Mirrors backend/go/parakeet-cpp/package.sh;
# run.sh routes the (CGO_ENABLED=0) binary through lib/ld.so so the packaged libc
# is used instead of the host's.
set -e
CURDIR=$(dirname "$(realpath "$0")")
REPO_ROOT="${CURDIR}/../../.."
mkdir -p "$CURDIR/package/lib"
cp -avf "$CURDIR/voice-detect-grpc" "$CURDIR/package/"
cp -avf "$CURDIR/run.sh" "$CURDIR/package/"
# libvoicedetect.so + any soname symlinks. purego.Dlopen resolves it via
# LD_LIBRARY_PATH, which run.sh points at lib/.
cp -avf "$CURDIR"/libvoicedetect.so* "$CURDIR/package/lib/" 2>/dev/null || {
echo "ERROR: libvoicedetect.so not found in $CURDIR, run 'make' first" >&2
exit 1
}
# Detect architecture and copy the core runtime libs libvoicedetect.so links
# against, plus the matching dynamic loader as lib/ld.so.
if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
echo "Detected x86_64 architecture, copying x86_64 libraries..."
cp -arfLv /lib64/ld-linux-x86-64.so.2 "$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 (CUDA/ROCm/Intel/Vulkan loader + ICDs + drivers) based on
# BUILD_TYPE so the backend can reach the GPU without the runtime base image
# shipping those drivers.
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/" "$CURDIR/package/lib/"

16
backend/go/voice-detect/run.sh Executable file
View File

@@ -0,0 +1,16 @@
#!/bin/bash
set -e
CURDIR=$(dirname "$(realpath "$0")")
export LD_LIBRARY_PATH="$CURDIR/lib:$CURDIR:${LD_LIBRARY_PATH:-}"
# If a self-contained ld.so was packaged, route through it so the packaged
# libc / libstdc++ are used instead of the host's (matches the whisper /
# parakeet backends' runtime layout).
if [ -f "$CURDIR/lib/ld.so" ]; then
echo "Using lib/ld.so"
exec "$CURDIR/lib/ld.so" "$CURDIR/voice-detect-grpc" "$@"
fi
exec "$CURDIR/voice-detect-grpc" "$@"

14
backend/go/voice-detect/test.sh Executable file
View File

@@ -0,0 +1,14 @@
#!/bin/bash
set -e
CURDIR=$(dirname "$(realpath "$0")")
cd "$CURDIR"
echo "Running voice-detect backend tests..."
# The pure-Go parsing specs always run. The embed/verify/analyze smoke specs run
# only when a model + WAV are provided via VOICEDETECT_BACKEND_TEST_MODEL and
# VOICEDETECT_BACKEND_TEST_WAV; otherwise they auto-skip.
LD_LIBRARY_PATH="$CURDIR:${LD_LIBRARY_PATH:-}" go test -v -timeout 1200s .
echo "voice-detect tests completed."

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?=43d78af5be58f41d6ffbc227d608f104577741ea
WHISPER_CPP_VERSION?=0ae02cdb2c7317b50991367c165736ce42ed96ac
SO_TARGET?=libgowhisper.so
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF

View File

@@ -13,8 +13,14 @@ if [ "$(uname)" != "Darwin" ]; then
fi
if [ "$(uname)" = "Darwin" ]; then
# macOS: single dylib variant (Metal or Accelerate)
LIBRARY="$CURDIR/libgowhisper-fallback.dylib"
# macOS: single fallback variant (Metal/Accelerate). The cmake build emits a
# Mach-O named .so, but tolerate .dylib too — pick whichever exists so the Go
# loader doesn't panic on a hardcoded name that isn't on disk.
if [ -e "$CURDIR/libgowhisper-fallback.dylib" ]; then
LIBRARY="$CURDIR/libgowhisper-fallback.dylib"
else
LIBRARY="$CURDIR/libgowhisper-fallback.so"
fi
export DYLD_LIBRARY_PATH="$CURDIR"/lib:$DYLD_LIBRARY_PATH
else
LIBRARY="$CURDIR/libgowhisper-fallback.so"

View File

@@ -209,6 +209,78 @@
nvidia-cuda-12: "cuda12-ced"
nvidia-l4t-cuda-12: "nvidia-l4t-arm64-ced"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-ced"
- &voicedetect
name: "voice-detect"
alias: "voice-detect"
license: mit
icon: https://avatars.githubusercontent.com/u/95302084
description: |
voice-detect speaker recognition and voice analysis.
voice-detect.cpp is a C++/ggml engine that produces L2-normalised
speaker embeddings (ECAPA-TDNN, WeSpeaker ResNet34, 3D-Speaker
ERes2Net, CAM++) for voice verification and 1:N identification, plus
a wav2vec2 age / gender / emotion analysis head. It replaces the
Python speaker-recognition backend and is exposed through the Voice*
gRPC rpcs and the /v1/voice/* REST endpoints. It runs on CPU, NVIDIA
CUDA, AMD ROCm/HIP, Intel SYCL, Vulkan and NVIDIA Jetson (L4T) targets.
urls:
- https://github.com/mudler/voice-detect.cpp
tags:
- voice-recognition
- speaker-verification
- speaker-embedding
- CPU
- GPU
- CUDA
- HIP
capabilities:
default: "cpu-voice-detect"
nvidia: "cuda12-voice-detect"
intel: "intel-sycl-f16-voice-detect"
metal: "metal-voice-detect"
amd: "rocm-voice-detect"
vulkan: "vulkan-voice-detect"
nvidia-l4t: "nvidia-l4t-arm64-voice-detect"
nvidia-cuda-13: "cuda13-voice-detect"
nvidia-cuda-12: "cuda12-voice-detect"
nvidia-l4t-cuda-12: "nvidia-l4t-arm64-voice-detect"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-voice-detect"
- &facedetect
name: "face-detect"
alias: "face-detect"
license: mit
icon: https://avatars.githubusercontent.com/u/95302084
description: |
face-detect face detection, embedding, verification and analysis.
face-detect.cpp is a C++/ggml engine that runs SCRFD / YuNet face
detection and ArcFace / SFace 512-d (or 128-d) L2-normalised face
embeddings for verification and 1:N identification, plus a landmark /
age / gender analysis head. It replaces the Python insightface backend
and is exposed through the Embedding, Detect and Face* gRPC rpcs and
the /v1/face/* REST endpoints. It runs on CPU, NVIDIA CUDA, AMD
ROCm/HIP, Intel SYCL, Vulkan and NVIDIA Jetson (L4T) targets.
urls:
- https://github.com/mudler/face-detect.cpp
tags:
- face-recognition
- face-verification
- face-embedding
- CPU
- GPU
- CUDA
- HIP
capabilities:
default: "cpu-face-detect"
nvidia: "cuda12-face-detect"
intel: "intel-sycl-f16-face-detect"
metal: "metal-face-detect"
amd: "rocm-face-detect"
vulkan: "vulkan-face-detect"
nvidia-l4t: "nvidia-l4t-arm64-face-detect"
nvidia-cuda-13: "cuda13-face-detect"
nvidia-cuda-12: "cuda12-face-detect"
nvidia-l4t-cuda-12: "nvidia-l4t-arm64-face-detect"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-face-detect"
- &voxtral
name: "voxtral"
alias: "voxtral"
@@ -1356,7 +1428,6 @@
intel: "intel-fish-speech"
amd: "rocm-fish-speech"
nvidia-l4t: "nvidia-l4t-fish-speech"
metal: "metal-fish-speech"
default: "cpu-fish-speech"
nvidia-cuda-13: "cuda13-fish-speech"
nvidia-cuda-12: "cuda12-fish-speech"
@@ -2828,6 +2899,236 @@
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-ced"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-13-ced
## voice-detect
- !!merge <<: *voicedetect
name: "voice-detect-development"
capabilities:
default: "cpu-voice-detect-development"
nvidia: "cuda12-voice-detect-development"
intel: "intel-sycl-f16-voice-detect-development"
metal: "metal-voice-detect-development"
amd: "rocm-voice-detect-development"
vulkan: "vulkan-voice-detect-development"
nvidia-l4t: "nvidia-l4t-arm64-voice-detect-development"
nvidia-cuda-13: "cuda13-voice-detect-development"
nvidia-cuda-12: "cuda12-voice-detect-development"
nvidia-l4t-cuda-12: "nvidia-l4t-arm64-voice-detect-development"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-voice-detect-development"
- !!merge <<: *voicedetect
name: "nvidia-l4t-arm64-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-voice-detect"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-arm64-voice-detect
- !!merge <<: *voicedetect
name: "nvidia-l4t-arm64-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-arm64-voice-detect"
mirrors:
- localai/localai-backends:master-nvidia-l4t-arm64-voice-detect
- !!merge <<: *voicedetect
name: "cuda13-nvidia-l4t-arm64-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-voice-detect"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-cuda-13-arm64-voice-detect
- !!merge <<: *voicedetect
name: "cuda13-nvidia-l4t-arm64-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-voice-detect"
mirrors:
- localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-voice-detect
- !!merge <<: *voicedetect
name: "cpu-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-voice-detect"
mirrors:
- localai/localai-backends:latest-cpu-voice-detect
- !!merge <<: *voicedetect
name: "cpu-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-voice-detect"
mirrors:
- localai/localai-backends:master-cpu-voice-detect
- !!merge <<: *voicedetect
name: "metal-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-voice-detect"
mirrors:
- localai/localai-backends:latest-metal-darwin-arm64-voice-detect
- !!merge <<: *voicedetect
name: "metal-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-voice-detect"
mirrors:
- localai/localai-backends:master-metal-darwin-arm64-voice-detect
- !!merge <<: *voicedetect
name: "cuda12-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-voice-detect"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-voice-detect
- !!merge <<: *voicedetect
name: "cuda12-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-voice-detect"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-voice-detect
- !!merge <<: *voicedetect
name: "rocm-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-voice-detect"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-voice-detect
- !!merge <<: *voicedetect
name: "rocm-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-voice-detect"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-voice-detect
- !!merge <<: *voicedetect
name: "intel-sycl-f32-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-voice-detect"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f32-voice-detect
- !!merge <<: *voicedetect
name: "intel-sycl-f32-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-voice-detect"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f32-voice-detect
- !!merge <<: *voicedetect
name: "intel-sycl-f16-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-voice-detect"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f16-voice-detect
- !!merge <<: *voicedetect
name: "intel-sycl-f16-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-voice-detect"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f16-voice-detect
- !!merge <<: *voicedetect
name: "vulkan-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-vulkan-voice-detect"
mirrors:
- localai/localai-backends:latest-gpu-vulkan-voice-detect
- !!merge <<: *voicedetect
name: "vulkan-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-vulkan-voice-detect"
mirrors:
- localai/localai-backends:master-gpu-vulkan-voice-detect
- !!merge <<: *voicedetect
name: "cuda13-voice-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-voice-detect"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-13-voice-detect
- !!merge <<: *voicedetect
name: "cuda13-voice-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-voice-detect"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-13-voice-detect
## face-detect
- !!merge <<: *facedetect
name: "face-detect-development"
capabilities:
default: "cpu-face-detect-development"
nvidia: "cuda12-face-detect-development"
intel: "intel-sycl-f16-face-detect-development"
metal: "metal-face-detect-development"
amd: "rocm-face-detect-development"
vulkan: "vulkan-face-detect-development"
nvidia-l4t: "nvidia-l4t-arm64-face-detect-development"
nvidia-cuda-13: "cuda13-face-detect-development"
nvidia-cuda-12: "cuda12-face-detect-development"
nvidia-l4t-cuda-12: "nvidia-l4t-arm64-face-detect-development"
nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-face-detect-development"
- !!merge <<: *facedetect
name: "nvidia-l4t-arm64-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-face-detect"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-arm64-face-detect
- !!merge <<: *facedetect
name: "nvidia-l4t-arm64-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-arm64-face-detect"
mirrors:
- localai/localai-backends:master-nvidia-l4t-arm64-face-detect
- !!merge <<: *facedetect
name: "cuda13-nvidia-l4t-arm64-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-face-detect"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-cuda-13-arm64-face-detect
- !!merge <<: *facedetect
name: "cuda13-nvidia-l4t-arm64-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-face-detect"
mirrors:
- localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-face-detect
- !!merge <<: *facedetect
name: "cpu-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-face-detect"
mirrors:
- localai/localai-backends:latest-cpu-face-detect
- !!merge <<: *facedetect
name: "cpu-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-face-detect"
mirrors:
- localai/localai-backends:master-cpu-face-detect
- !!merge <<: *facedetect
name: "metal-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-face-detect"
mirrors:
- localai/localai-backends:latest-metal-darwin-arm64-face-detect
- !!merge <<: *facedetect
name: "metal-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-face-detect"
mirrors:
- localai/localai-backends:master-metal-darwin-arm64-face-detect
- !!merge <<: *facedetect
name: "cuda12-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-face-detect"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-face-detect
- !!merge <<: *facedetect
name: "cuda12-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-face-detect"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-face-detect
- !!merge <<: *facedetect
name: "rocm-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-face-detect"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-face-detect
- !!merge <<: *facedetect
name: "rocm-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-face-detect"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-face-detect
- !!merge <<: *facedetect
name: "intel-sycl-f32-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-face-detect"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f32-face-detect
- !!merge <<: *facedetect
name: "intel-sycl-f32-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-face-detect"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f32-face-detect
- !!merge <<: *facedetect
name: "intel-sycl-f16-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-face-detect"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f16-face-detect
- !!merge <<: *facedetect
name: "intel-sycl-f16-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-face-detect"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f16-face-detect
- !!merge <<: *facedetect
name: "vulkan-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-vulkan-face-detect"
mirrors:
- localai/localai-backends:latest-gpu-vulkan-face-detect
- !!merge <<: *facedetect
name: "vulkan-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-vulkan-face-detect"
mirrors:
- localai/localai-backends:master-gpu-vulkan-face-detect
- !!merge <<: *facedetect
name: "cuda13-face-detect"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-face-detect"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-13-face-detect
- !!merge <<: *facedetect
name: "cuda13-face-detect-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-face-detect"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-13-face-detect
## stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "cpu-stablediffusion-ggml"
@@ -4870,7 +5171,6 @@
intel: "intel-fish-speech-development"
amd: "rocm-fish-speech-development"
nvidia-l4t: "nvidia-l4t-fish-speech-development"
metal: "metal-fish-speech-development"
default: "cpu-fish-speech-development"
nvidia-cuda-13: "cuda13-fish-speech-development"
nvidia-cuda-12: "cuda12-fish-speech-development"
@@ -4946,16 +5246,6 @@
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-fish-speech"
mirrors:
- localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-fish-speech
- !!merge <<: *fish-speech
name: "metal-fish-speech"
uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-fish-speech"
mirrors:
- localai/localai-backends:latest-metal-darwin-arm64-fish-speech
- !!merge <<: *fish-speech
name: "metal-fish-speech-development"
uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-fish-speech"
mirrors:
- localai/localai-backends:master-metal-darwin-arm64-fish-speech
## faster-qwen3-tts
- !!merge <<: *faster-qwen3-tts
name: "faster-qwen3-tts-development"

View File

@@ -1,2 +0,0 @@
torch
torchaudio

View File

@@ -7,3 +7,7 @@ setuptools
six
scipy
numpy
# fish-speech is installed editable with --no-build-isolation, so the build
# backends of its transitive deps must already be in the venv. One of them
# builds a Rust extension and needs setuptools-rust present at metadata time.
setuptools-rust

View File

@@ -3,4 +3,5 @@ protobuf
certifi
packaging==24.1
pip
chardet
chardet
click

View File

@@ -11,14 +11,31 @@ fi
EXTRA_PIP_INSTALL_FLAGS+=" --upgrade "
installRequirements
# Fetch convert_hf_to_gguf.py from llama.cpp
# Fetch convert_hf_to_gguf.py from llama.cpp.
# Upstream split the model-specific logic out of the single file into a
# sibling `conversion/` package (convert_hf_to_gguf.py now does
# `from conversion import ...`), so a single-file download no longer runs —
# it fails with `ModuleNotFoundError: No module named 'conversion'`. We clone
# the repo and copy both the script and the package; Python puts the script's
# own directory on sys.path[0], so the package resolves when placed beside it.
LLAMA_CPP_CONVERT_VERSION="${LLAMA_CPP_CONVERT_VERSION:-master}"
LLAMA_CPP_SRC="${EDIR}/llama.cpp"
CONVERT_SCRIPT="${EDIR}/convert_hf_to_gguf.py"
if [ ! -f "${CONVERT_SCRIPT}" ]; then
echo "Downloading convert_hf_to_gguf.py from llama.cpp (${LLAMA_CPP_CONVERT_VERSION})..."
curl -L --fail --retry 3 \
"https://raw.githubusercontent.com/ggml-org/llama.cpp/${LLAMA_CPP_CONVERT_VERSION}/convert_hf_to_gguf.py" \
-o "${CONVERT_SCRIPT}" || echo "Warning: Failed to download convert_hf_to_gguf.py."
cloneLlamaCpp() {
if [ ! -d "${LLAMA_CPP_SRC}/.git" ]; then
git clone --depth 1 --branch "${LLAMA_CPP_CONVERT_VERSION}" \
https://github.com/ggml-org/llama.cpp.git "${LLAMA_CPP_SRC}" 2>/dev/null || \
git clone --depth 1 https://github.com/ggml-org/llama.cpp.git "${LLAMA_CPP_SRC}"
fi
}
if [ ! -f "${CONVERT_SCRIPT}" ] || [ ! -d "${EDIR}/conversion" ]; then
echo "Fetching convert_hf_to_gguf.py + conversion/ from llama.cpp (${LLAMA_CPP_CONVERT_VERSION})..."
cloneLlamaCpp
cp "${LLAMA_CPP_SRC}/convert_hf_to_gguf.py" "${CONVERT_SCRIPT}"
rm -rf "${EDIR}/conversion"
cp -r "${LLAMA_CPP_SRC}/conversion" "${EDIR}/conversion"
fi
# Install gguf package from the same llama.cpp commit to keep them in sync
@@ -41,12 +58,7 @@ QUANTIZE_BIN="${EDIR}/llama-quantize"
if [ ! -x "${QUANTIZE_BIN}" ] && ! command -v llama-quantize &>/dev/null; then
if command -v cmake &>/dev/null; then
echo "Building llama-quantize from llama.cpp (${LLAMA_CPP_CONVERT_VERSION})..."
LLAMA_CPP_SRC="${EDIR}/llama.cpp"
if [ ! -d "${LLAMA_CPP_SRC}" ]; then
git clone --depth 1 --branch "${LLAMA_CPP_CONVERT_VERSION}" \
https://github.com/ggml-org/llama.cpp.git "${LLAMA_CPP_SRC}" 2>/dev/null || \
git clone --depth 1 https://github.com/ggml-org/llama.cpp.git "${LLAMA_CPP_SRC}"
fi
cloneLlamaCpp # reuses the clone fetched for convert_hf_to_gguf.py
cmake -B "${LLAMA_CPP_SRC}/build" -S "${LLAMA_CPP_SRC}" -DGGML_NATIVE=OFF -DBUILD_SHARED_LIBS=OFF
cmake --build "${LLAMA_CPP_SRC}/build" --target llama-quantize -j"$(nproc 2>/dev/null || echo 2)"
cp "${LLAMA_CPP_SRC}/build/bin/llama-quantize" "${QUANTIZE_BIN}"

View File

@@ -85,9 +85,15 @@ if [ "x${BUILD_TYPE}" == "x" ] || [ "x${FROM_SOURCE:-}" == "xtrue" ]; then
# The resulting binary still requires an AVX-512 capable CPU at runtime,
# same constraint sglang upstream documents in docker/xeon.Dockerfile.
# Pin the source build to the same release the GPU path floors on
# (0.5.11, see requirements-cublas12-after.txt). An unpinned master clone
# pulls in newer CPU kernels (e.g. mamba/fla.cpp) that fail to compile
# (constexpr non-constant + kineto_LIBRARY-NOTFOUND). Bump deliberately.
SGLANG_VERSION="${SGLANG_VERSION:-v0.5.11}"
_sgl_src=$(mktemp -d)
trap 'rm -rf "${_sgl_src}"' EXIT
git clone --depth 1 https://github.com/sgl-project/sglang "${_sgl_src}/sglang"
git clone --depth 1 --branch "${SGLANG_VERSION}" \
https://github.com/sgl-project/sglang "${_sgl_src}/sglang"
# Patch -march=native → -march=sapphirerapids in the CPU kernel CMakeLists
sed -i 's/-march=native/-march=sapphirerapids/g' \

View File

@@ -1,6 +1,6 @@
--extra-index-url https://download.pytorch.org/whl/cpu
accelerate
torch==2.9.0
torch==2.12.0+cpu
torchvision
torchaudio
transformers

View File

@@ -6,7 +6,7 @@
# for cublas12 so uv consults this index alongside PyPI.
--extra-index-url https://download.pytorch.org/whl/cu128
accelerate
torch==2.9.1
torch==2.12.0+cpu
torchvision
torchaudio
transformers

View File

@@ -1,9 +1,9 @@
--extra-index-url https://download.pytorch.org/whl/cpu
torch==2.10.0
torch==2.12.0+cpu
trl
peft
datasets>=3.0.0
transformers>=4.56.2
transformers>=5.12.1
accelerate>=1.4.0
huggingface-hub>=1.3.0
sentencepiece

View File

@@ -1,8 +1,8 @@
torch==2.10.0
torch==2.12.0+cpu
trl
peft
datasets>=3.0.0
transformers>=4.56.2
transformers>=5.12.1
accelerate>=1.4.0
huggingface-hub>=1.3.0
sentencepiece

View File

@@ -1,8 +1,8 @@
torch==2.10.0
torch==2.12.0+cpu
trl
peft
datasets>=3.0.0
transformers>=4.56.2
transformers>=5.12.1
accelerate>=1.4.0
huggingface-hub>=1.3.0
sentencepiece

View File

@@ -1,8 +1,8 @@
torch==2.10.0
torch==2.12.0+cpu
trl
peft
datasets>=3.0.0
transformers>=4.56.2
transformers>=5.12.1
accelerate>=1.4.0
huggingface-hub>=1.3.0
sentencepiece

View File

@@ -1,4 +1,4 @@
accelerate
torch==2.7.0
torch==2.12.0+cu130
transformers
bitsandbytes

View File

@@ -570,6 +570,43 @@ impl Backend for KokorosService {
) -> Result<Response<backend::Result>, Status> {
Err(Status::unimplemented("Not supported"))
}
async fn sound_detection(
&self,
_: Request<backend::SoundDetectionRequest>,
) -> Result<Response<backend::SoundDetectionResponse>, Status> {
Err(Status::unimplemented("Not supported"))
}
async fn depth(
&self,
_: Request<backend::DepthRequest>,
) -> Result<Response<backend::DepthResponse>, Status> {
Err(Status::unimplemented("Not supported"))
}
async fn token_classify(
&self,
_: Request<backend::TokenClassifyRequest>,
) -> Result<Response<backend::TokenClassifyResponse>, Status> {
Err(Status::unimplemented("Not supported"))
}
async fn score(
&self,
_: Request<backend::ScoreRequest>,
) -> Result<Response<backend::ScoreResponse>, Status> {
Err(Status::unimplemented("Not supported"))
}
type ForwardStream = ReceiverStream<Result<backend::ForwardReply, Status>>;
async fn forward(
&self,
_: Request<tonic::Streaming<backend::ForwardRequest>>,
) -> Result<Response<Self::ForwardStream>, Status> {
Err(Status::unimplemented("Not supported"))
}
}
#[cfg(test)]

View File

@@ -37,6 +37,8 @@ func (a *Application) RestartAgentJobService() error {
if d.JobStore != nil {
agentJobService.SetDistributedJobStore(d.JobStore)
}
// Keep agent tasks consistent across replicas (same client the dispatcher uses).
agentJobService.SetTaskSyncNATS(d.Nats)
}
// Start the service

View File

@@ -604,6 +604,10 @@ func (a *Application) StartAgentPool() {
usm.SetJobDBStore(s)
}
}
// Keep per-user agent tasks consistent across replicas (nil in standalone).
if d := a.Distributed(); d != nil {
usm.SetJobSyncNATS(d.Nats)
}
aps.SetUserServicesManager(usm)
a.agentPoolService.Store(aps)

View File

@@ -355,6 +355,7 @@ func initDistributed(cfg *config.ApplicationConfig, authDB *gorm.DB, configLoade
PrefixProvider: prefixProvider,
PrefixConfig: prefixCfg,
Pressure: pressure,
SharedModels: cfg.Distributed.SharedModels,
})
// Wire staging-progress broadcasting so file-staging shows up on every

View File

@@ -280,6 +280,9 @@ func New(opts ...config.AppOption) (*Application, error) {
if application.agentJobService != nil {
application.agentJobService.SetDistributedBackends(distSvc.Dispatcher)
application.agentJobService.SetDistributedJobStore(distSvc.JobStore)
// Keep agent tasks consistent across replicas (jobs already sync via the
// dispatcher + DB read-through). Same NATS client the dispatcher uses.
application.agentJobService.SetTaskSyncNATS(distSvc.Nats)
}
// Wire skill store into AgentPoolService (wired at pool start time via closure)
// The actual wiring happens in StartAgentPool since the pool doesn't exist yet.

View File

@@ -160,6 +160,7 @@ type RunCMD struct {
RegistrationRequireAuth bool `env:"LOCALAI_REGISTRATION_REQUIRE_AUTH" default:"false" help:"Fail startup when distributed mode is enabled but LOCALAI_REGISTRATION_TOKEN is empty (node endpoints and worker file-transfer server would otherwise be unauthenticated)" group:"distributed"`
DistributedRequireAuth bool `env:"LOCALAI_DISTRIBUTED_REQUIRE_AUTH" default:"false" help:"Umbrella switch: require BOTH NATS JWT credentials and a registration token when distributed mode is enabled (implies --nats-require-auth and --registration-require-auth)" group:"distributed"`
AutoApproveNodes bool `env:"LOCALAI_AUTO_APPROVE_NODES" default:"false" help:"Auto-approve new worker nodes (skip admin approval)" group:"distributed"`
DistributedSharedModels bool `env:"LOCALAI_DISTRIBUTED_SHARED_MODELS" default:"false" help:"Assert that every node mounts the SAME models directory at the SAME path (shared volume). When true, the router skips staging model files to workers and loads them directly from the shared path, avoiding re-downloads." group:"distributed"`
DistributedPrefixCache bool `env:"LOCALAI_DISTRIBUTED_PREFIX_CACHE" default:"true" help:"Enable prefix-cache-aware routing in distributed mode (default true). When false, routing falls back to round-robin." group:"distributed"`
DistributedPrefixCacheTTL string `env:"LOCALAI_DISTRIBUTED_PREFIX_CACHE_TTL" help:"Idle-timeout for prefix-cache index entries; also drives the background eviction cadence (every TTL/2). Default 5m." group:"distributed"`
BackendInstallTimeout string `env:"LOCALAI_NATS_BACKEND_INSTALL_TIMEOUT" help:"NATS round-trip timeout for backend.install requests sent to worker nodes (default 15m). Increase for slow links pulling multi-GB images." group:"distributed"`
@@ -310,6 +311,9 @@ func (r *RunCMD) Run(ctx *cliContext.Context) error {
if r.DistributedRequireAuth {
opts = append(opts, config.EnableDistributedRequireAuth)
}
if r.DistributedSharedModels {
opts = append(opts, config.EnableDistributedSharedModels)
}
if r.NatsAccountSeed != "" {
opts = append(opts, config.WithNatsAccountSeed(r.NatsAccountSeed))
}

View File

@@ -542,6 +542,19 @@ var BackendCapabilities = map[string]BackendCapability{
DefaultUsecases: []string{UsecaseSpeakerRecognition},
Description: "Speaker recognition — voice identity verification and analysis",
},
"voice-detect": {
GRPCMethods: []GRPCMethod{MethodVoiceVerify, MethodVoiceEmbed, MethodVoiceAnalyze},
PossibleUsecases: []string{UsecaseSpeakerRecognition},
DefaultUsecases: []string{UsecaseSpeakerRecognition},
Description: "voice-detect.cpp: C++/ggml speaker embedding, verification and voice analysis (age/gender/emotion)",
},
"face-detect": {
GRPCMethods: []GRPCMethod{MethodEmbedding, MethodDetect, MethodFaceVerify, MethodFaceAnalyze},
PossibleUsecases: []string{UsecaseEmbeddings, UsecaseDetection, UsecaseFaceRecognition},
DefaultUsecases: []string{UsecaseFaceRecognition},
AcceptsImages: true,
Description: "face-detect.cpp: C++/ggml face detection, embedding, verification and attribute analysis",
},
"silero-vad": {
GRPCMethods: []GRPCMethod{MethodVAD},
PossibleUsecases: []string{UsecaseVAD},

View File

@@ -12,14 +12,12 @@ package config
// these; config never imports backend.
const (
// DefaultContextSize is the fallback context window when none is configured
// or estimable from the model.
// or estimable from the model. It is also the fallback for a GGUF whose
// metadata yields no usable estimate or that the parser cannot read at all
// (e.g. a quant type it does not know, such as NVFP4): a model-agnostic
// safe default beats a tiny, surprising window that truncates real prompts.
DefaultContextSize = 4096
// GGUFFallbackContextSize is the context window for a GGUF model whose
// metadata yields no usable estimate (see guessGGUFFromFile). Deliberately
// smaller than DefaultContextSize to stay conservative on memory there.
GGUFFallbackContextSize = 1024
// DefaultNGPULayers means "offload all layers"; the backend (fit_params)
// clamps to what actually fits in device memory.
DefaultNGPULayers = 99999999

View File

@@ -31,6 +31,14 @@ type DistributedConfig struct {
// available to enforce just one layer.
RequireAuth bool // LOCALAI_DISTRIBUTED_REQUIRE_AUTH
AutoApproveNodes bool // --auto-approve-nodes / LOCALAI_AUTO_APPROVE_NODES (skip admin approval for new workers)
// SharedModels asserts that every node (frontend and workers) mounts the
// SAME models directory at the SAME path (e.g. a shared volume, as in
// docker-compose.distributed.yaml). When true, the router skips staging
// model files to workers entirely: the frontend's absolute model paths are
// already valid on the worker, so re-uploading them into a per-model
// subdirectory only re-downloads what is already present (#10556). Default
// false preserves the historical per-node staging behavior.
SharedModels bool // --distributed-shared-models / LOCALAI_DISTRIBUTED_SHARED_MODELS
// NATS JWT auth (optional; see pkg/natsauth and docs/features/distributed-mode.md)
NatsAccountSeed string // LOCALAI_NATS_ACCOUNT_SEED — account signing seed to mint per-node worker JWTs
@@ -282,6 +290,13 @@ var EnableAutoApproveNodes = func(o *ApplicationConfig) {
o.Distributed.AutoApproveNodes = true
}
// EnableDistributedSharedModels marks the cluster as sharing one models
// directory across all nodes, so the router skips staging model files to
// workers (see DistributedConfig.SharedModels).
var EnableDistributedSharedModels = func(o *ApplicationConfig) {
o.Distributed.SharedModels = true
}
// DisablePrefixCache turns off prefix-cache-aware routing (falls back to
// round-robin). Prefix-cache routing is enabled by default in distributed mode.
var DisablePrefixCache = func(o *ApplicationConfig) {

View File

@@ -33,7 +33,7 @@ func guessGGUFFromFile(cfg *ModelConfig, f *gguf.GGUFFile, defaultCtx int) {
cSize := int(ctxSize)
cfg.ContextSize = &cSize
} else {
defaultCtx = GGUFFallbackContextSize
defaultCtx = DefaultContextSize
cfg.ContextSize = &defaultCtx
}
}

View File

@@ -34,7 +34,7 @@ func llamaCppDefaults(cfg *ModelConfig, modelPath string) {
// Default context size if not set, regardless of whether GGUF parsing succeeds
defer func() {
if cfg.ContextSize == nil {
ctx := GGUFFallbackContextSize
ctx := DefaultContextSize
cfg.ContextSize = &ctx
}
}()

View File

@@ -248,7 +248,11 @@ var _ = Describe("Backend hooks and parser defaults", func() {
}
cfg.SetDefaults(ModelPath(dir))
// An unreadable/unparseable GGUF (e.g. a quant type the parser does
// not know, such as NVFP4) yields no estimate, so the hook must fall
// back to DefaultContextSize rather than a tiny, surprising value.
Expect(cfg.ContextSize).NotTo(BeNil())
Expect(*cfg.ContextSize).To(Equal(DefaultContextSize))
})
})

View File

@@ -25,8 +25,8 @@ var (
type LlamaCPPImporter struct{}
func (i *LlamaCPPImporter) Name() string { return "llama-cpp" }
func (i *LlamaCPPImporter) Modality() string { return "text" }
func (i *LlamaCPPImporter) Name() string { return "llama-cpp" }
func (i *LlamaCPPImporter) Modality() string { return "text" }
func (i *LlamaCPPImporter) AutoDetects() bool { return true }
// AdditionalBackends advertises drop-in replacements that share the
@@ -293,7 +293,7 @@ func pickPreferredGroup(groups []hfapi.ShardGroup, prefs []string) *hfapi.ShardG
for _, pref := range prefs {
lower := strings.ToLower(pref)
for i := range groups {
if strings.Contains(strings.ToLower(groups[i].Base), lower) {
if quantTokenMatches(strings.ToLower(groups[i].Base), lower) {
return &groups[i]
}
}
@@ -301,6 +301,39 @@ func pickPreferredGroup(groups []hfapi.ShardGroup, prefs []string) *hfapi.ShardG
return &groups[len(groups)-1]
}
// quantTokenMatches reports whether pref appears in base as a whole token
// rather than as a substring of a larger alphanumeric run. Both arguments
// must already be lowercased.
//
// A plain strings.Contains is wrong here: `f16` is a substring of `bf16`, so
// asking for the `F16` quant used to wrongly select a `BF16` file (#10559).
// Only the OUTER edges of the matched preference must hit a boundary — a
// non-alphanumeric char (or the start/end of base). Separators inside the
// preference itself (e.g. `ud-q4_k_xl`) are intentionally left untouched.
func quantTokenMatches(base, pref string) bool {
if pref == "" {
return false
}
for start := strings.Index(base, pref); start != -1; {
end := start + len(pref)
leftOK := start == 0 || !isAlphaNum(base[start-1])
rightOK := end == len(base) || !isAlphaNum(base[end])
if leftOK && rightOK {
return true
}
next := strings.Index(base[start+1:], pref)
if next == -1 {
break
}
start += next + 1
}
return false
}
func isAlphaNum(b byte) bool {
return (b >= 'a' && b <= 'z') || (b >= '0' && b <= '9')
}
// maybeApplyMTPDefaults parses the picked GGUF header (range-fetched over
// HTTP for HF/URL imports) and, if the file declares a Multi-Token Prediction
// head, appends the auto-MTP option keys to modelConfig.Options. Failures

View File

@@ -374,6 +374,104 @@ var _ = Describe("LlamaCPPImporter", func() {
})
})
Context("quant token boundary matching", func() {
// Regression for #10559: the quant preference must match as a whole
// token, not as a substring. Asking for `F16` used to select a
// `BF16` mmproj because strings.Contains("...bf16.gguf", "f16") is
// true — the leading `b` was ignored.
const repoBase = "https://huggingface.co/acme/example-GGUF/resolve/main/"
hfFile := func(path, sha string) hfapi.ModelFile {
return hfapi.ModelFile{
Path: path,
SHA256: sha,
URL: repoBase + path,
}
}
withHF := func(preferences string, files ...hfapi.ModelFile) Details {
d := Details{
URI: "https://huggingface.co/acme/example-GGUF",
HuggingFace: &hfapi.ModelDetails{
ModelID: "acme/example-GGUF",
Files: files,
},
}
if preferences != "" {
d.Preferences = json.RawMessage(preferences)
}
return d
}
It("selects the F16 mmproj over BF16 (BF16 listed first)", func() {
details := withHF(`{"name":"VL","mmproj_quantizations":"F16"}`,
hfFile("model-Q4_K_M.gguf", "model"),
hfFile("mmproj-x-BF16.gguf", "bf16"),
hfFile("mmproj-x-F16.gguf", "f16"),
)
modelConfig, err := importer.Import(details)
Expect(err).ToNot(HaveOccurred())
Expect(modelConfig.ConfigFile).To(ContainSubstring("mmproj: llama-cpp/mmproj/VL/mmproj-x-F16.gguf"), fmt.Sprintf("%+v", modelConfig))
Expect(modelConfig.ConfigFile).ToNot(ContainSubstring("BF16"), fmt.Sprintf("%+v", modelConfig))
})
It("selects the F16 mmproj over BF16 (F16 listed first)", func() {
details := withHF(`{"name":"VL","mmproj_quantizations":"F16"}`,
hfFile("model-Q4_K_M.gguf", "model"),
hfFile("mmproj-x-F16.gguf", "f16"),
hfFile("mmproj-x-BF16.gguf", "bf16"),
)
modelConfig, err := importer.Import(details)
Expect(err).ToNot(HaveOccurred())
Expect(modelConfig.ConfigFile).To(ContainSubstring("mmproj: llama-cpp/mmproj/VL/mmproj-x-F16.gguf"), fmt.Sprintf("%+v", modelConfig))
Expect(modelConfig.ConfigFile).ToNot(ContainSubstring("BF16"), fmt.Sprintf("%+v", modelConfig))
})
It("selects BF16 when BF16 is the requested mmproj quant", func() {
details := withHF(`{"name":"VL","mmproj_quantizations":"BF16"}`,
hfFile("model-Q4_K_M.gguf", "model"),
hfFile("mmproj-x-F16.gguf", "f16"),
hfFile("mmproj-x-BF16.gguf", "bf16"),
)
modelConfig, err := importer.Import(details)
Expect(err).ToNot(HaveOccurred())
Expect(modelConfig.ConfigFile).To(ContainSubstring("mmproj: llama-cpp/mmproj/VL/mmproj-x-BF16.gguf"), fmt.Sprintf("%+v", modelConfig))
})
It("still matches a normal model quant with internal separators", func() {
// ud-q4_k_xl contains `-`/`_` internally; only the outer edges
// must hit a token boundary.
details := withHF(`{"name":"M","quantizations":"ud-q4_k_xl"}`,
hfFile("model-UD-Q4_K_XL.gguf", "xl"),
hfFile("model-Q3_K_M.gguf", "q3"),
)
modelConfig, err := importer.Import(details)
Expect(err).ToNot(HaveOccurred())
Expect(modelConfig.ConfigFile).To(ContainSubstring("model: llama-cpp/models/M/model-UD-Q4_K_XL.gguf"), fmt.Sprintf("%+v", modelConfig))
})
It("falls back to the last group when no preference matches", func() {
details := withHF(`{"name":"M","quantizations":"Q2_K"}`,
hfFile("model-Q8_0.gguf", "q8"),
hfFile("model-Q3_K_M.gguf", "q3"),
)
modelConfig, err := importer.Import(details)
Expect(err).ToNot(HaveOccurred())
Expect(modelConfig.ConfigFile).To(ContainSubstring("model: llama-cpp/models/M/model-Q3_K_M.gguf"), fmt.Sprintf("%+v", modelConfig))
})
})
Context("AdditionalBackends", func() {
It("advertises ik-llama-cpp and turboquant as drop-in replacements", func() {
entries := importer.AdditionalBackends()

View File

@@ -23,8 +23,10 @@ import (
"github.com/mudler/LocalAI/core/application"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/distributed"
"github.com/mudler/LocalAI/core/services/finetune"
"github.com/mudler/LocalAI/core/services/galleryop"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/LocalAI/core/services/nodes"
"github.com/mudler/LocalAI/core/services/quantization"
@@ -400,25 +402,45 @@ func API(application *application.Application) (*echo.Echo, error) {
routes.RegisterAgentPoolRoutes(e, application, agentsMw, skillsMw, collectionsMw)
// Fine-tuning routes
fineTuningMw := auth.RequireFeature(application.AuthDB(), auth.FeatureFineTuning)
// In distributed mode pass the shared NATS client + PostgreSQL store so
// fine-tune jobs stay consistent across replicas (the SyncedMap broadcasts
// mutations and hydrates from the DB); standalone passes nil for both.
var ftNats messaging.MessagingClient
var ftStore *distributed.FineTuneStore
if d := application.Distributed(); d != nil {
ftNats = d.Nats
if d.DistStores != nil && d.DistStores.FineTune != nil {
ftStore = d.DistStores.FineTune
}
}
ftService := finetune.NewFineTuneService(
application.ApplicationConfig(),
application.ModelLoader(),
application.ModelConfigLoader(),
ftNats,
ftStore,
)
if d := application.Distributed(); d != nil {
ftService.SetNATSClient(d.Nats)
if d.DistStores != nil && d.DistStores.FineTune != nil {
ftService.SetFineTuneStore(d.DistStores.FineTune)
}
}
routes.RegisterFineTuningRoutes(e, ftService, application.ApplicationConfig(), fineTuningMw)
// Quantization routes
quantizationMw := auth.RequireFeature(application.AuthDB(), auth.FeatureQuantization)
// In distributed mode pass the shared NATS client + PostgreSQL store so
// quantization jobs stay consistent across replicas (the SyncedMap broadcasts
// mutations and hydrates from the DB); standalone passes nil for both.
var quantNats messaging.MessagingClient
var quantStore *distributed.QuantStore
if d := application.Distributed(); d != nil {
quantNats = d.Nats
if d.DistStores != nil && d.DistStores.Quant != nil {
quantStore = d.DistStores.Quant
}
}
qService := quantization.NewQuantizationService(
application.ApplicationConfig(),
application.ModelLoader(),
application.ModelConfigLoader(),
quantNats,
quantStore,
)
routes.RegisterQuantizationRoutes(e, qService, application.ApplicationConfig(), quantizationMw)

View File

@@ -25,6 +25,7 @@ import (
"github.com/mudler/LocalAI/core/http/auth"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/galleryop"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/LocalAI/core/services/nodes"
"github.com/mudler/LocalAI/core/services/nodes/prefixcache"
"github.com/mudler/LocalAI/pkg/httpclient"
@@ -550,12 +551,23 @@ func DeleteBackendOnNodeEndpoint(unloader nodes.NodeCommandSender) echo.HandlerF
}
// ListBackendsOnNodeEndpoint lists installed backends on a worker node via NATS.
func ListBackendsOnNodeEndpoint(unloader nodes.NodeCommandSender) echo.HandlerFunc {
func ListBackendsOnNodeEndpoint(unloader nodes.NodeCommandSender, registry *nodes.NodeRegistry) echo.HandlerFunc {
return func(c echo.Context) error {
nodeID := c.Param("id")
// Agent-type workers don't run backends and never subscribe to the
// nodes.<id>.backend.list NATS subject, so the request would hang
// until timeout with "no responders". Their backend list is simply
// empty. Mirror the aggregate-list guard in managers_distributed.go
// (skip nodes whose NodeType is set and not "backend") so the
// single-node and cluster-wide views stay consistent.
if node, err := registry.Get(c.Request().Context(), nodeID); err == nil {
if node.NodeType != "" && node.NodeType != nodes.NodeTypeBackend {
return c.JSON(http.StatusOK, []messaging.NodeBackendInfo{})
}
}
if unloader == nil {
return c.JSON(http.StatusServiceUnavailable, nodeError(http.StatusServiceUnavailable, "NATS not configured"))
}
nodeID := c.Param("id")
reply, err := unloader.ListBackends(nodeID)
if err != nil {
xlog.Error("Failed to list backends on node", "node", nodeID, "error", err)

View File

@@ -0,0 +1,103 @@
package localai
import (
"context"
"encoding/json"
"net/http"
"net/http/httptest"
"github.com/labstack/echo/v4"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/LocalAI/core/services/nodes"
"github.com/mudler/LocalAI/core/services/testutil"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
// stubNodeCommandSender records whether ListBackends was invoked so the test can
// assert the endpoint short-circuits (no NATS request) for agent-type nodes.
type stubNodeCommandSender struct {
listBackendsCalled bool
}
func (s *stubNodeCommandSender) InstallBackend(_, _, _, _, _, _, _ string, _ int, _ string, _ func(messaging.BackendInstallProgressEvent)) (*messaging.BackendInstallReply, error) {
return &messaging.BackendInstallReply{}, nil
}
func (s *stubNodeCommandSender) UpgradeBackend(_, _, _, _, _, _ string, _ int, _ string, _ func(messaging.BackendInstallProgressEvent)) (*messaging.BackendUpgradeReply, error) {
return &messaging.BackendUpgradeReply{}, nil
}
func (s *stubNodeCommandSender) DeleteBackend(_, _ string) (*messaging.BackendDeleteReply, error) {
return &messaging.BackendDeleteReply{Success: true}, nil
}
func (s *stubNodeCommandSender) ListBackends(_ string) (*messaging.BackendListReply, error) {
s.listBackendsCalled = true
return &messaging.BackendListReply{Backends: []messaging.NodeBackendInfo{{Name: "llama-cpp"}}}, nil
}
func (s *stubNodeCommandSender) StopBackend(_, _ string) error { return nil }
func (s *stubNodeCommandSender) UnloadModelOnNode(_, _ string) error { return nil }
var _ = Describe("ListBackendsOnNodeEndpoint", func() {
var registry *nodes.NodeRegistry
BeforeEach(func() {
db := testutil.SetupTestDB()
var err error
registry, err = nodes.NewNodeRegistry(db)
Expect(err).ToNot(HaveOccurred())
})
callEndpoint := func(unloader nodes.NodeCommandSender, nodeID string) *httptest.ResponseRecorder {
e := echo.New()
req := httptest.NewRequest(http.MethodGet, "/", nil)
rec := httptest.NewRecorder()
c := e.NewContext(req, rec)
c.SetParamNames("id")
c.SetParamValues(nodeID)
handler := ListBackendsOnNodeEndpoint(unloader, registry)
Expect(handler(c)).To(Succeed())
return rec
}
It("returns an empty list for an agent node without issuing a NATS request", func() {
ctx := context.Background()
node := &nodes.BackendNode{Name: "agent-1", NodeType: nodes.NodeTypeAgent}
Expect(registry.Register(ctx, node, true)).To(Succeed())
stub := &stubNodeCommandSender{}
rec := callEndpoint(stub, node.ID)
Expect(rec.Code).To(Equal(http.StatusOK))
Expect(stub.listBackendsCalled).To(BeFalse(),
"agent workers don't subscribe to backend.list; the endpoint must not issue the doomed NATS request")
var list []messaging.NodeBackendInfo
Expect(json.Unmarshal(rec.Body.Bytes(), &list)).To(Succeed())
Expect(list).To(BeEmpty())
// Must be `[]`, not `null`, so the UI can render it.
Expect(rec.Body.String()).To(ContainSubstring("[]"))
})
It("consults the unloader (NATS) for a backend node", func() {
ctx := context.Background()
node := &nodes.BackendNode{Name: "backend-1", NodeType: nodes.NodeTypeBackend, Address: "10.0.0.1:50051"}
Expect(registry.Register(ctx, node, true)).To(Succeed())
stub := &stubNodeCommandSender{}
rec := callEndpoint(stub, node.ID)
Expect(rec.Code).To(Equal(http.StatusOK))
Expect(stub.listBackendsCalled).To(BeTrue(),
"backend nodes must still be queried over NATS")
var list []messaging.NodeBackendInfo
Expect(json.Unmarshal(rec.Body.Bytes(), &list)).To(Succeed())
Expect(list).To(HaveLen(1))
Expect(list[0].Name).To(Equal("llama-cpp"))
})
})

View File

@@ -3,6 +3,7 @@ package openresponses
import (
"context"
"encoding/json"
"errors"
"fmt"
"time"
@@ -10,6 +11,7 @@ import (
"github.com/labstack/echo/v4"
"github.com/mudler/LocalAI/core/backend"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/http/auth"
mcpTools "github.com/mudler/LocalAI/core/http/endpoints/mcp"
openaiEndpoint "github.com/mudler/LocalAI/core/http/endpoints/openai"
"github.com/mudler/LocalAI/core/http/middleware"
@@ -246,8 +248,11 @@ func ResponsesEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, eval
// Create cancellable context for background execution
bgCtx, bgCancel := context.WithCancel(context.Background())
// Store the background response
// Store the background response and stamp its owner before the ID
// is returned to the client, so later GET/cancel/resume can verify
// the caller owns it.
store.StoreBackground(responseID, input, queuedResponse, bgCancel, input.Stream)
store.SetOwner(responseID, ownerFromContext(c))
// Start background processing goroutine
go func() {
@@ -1587,6 +1592,7 @@ func handleOpenResponsesNonStream(c echo.Context, responseID string, createdAt i
if shouldStore {
store := GetGlobalStore()
store.Store(responseID, input, response)
store.SetOwner(responseID, ownerFromContext(c))
}
return c.JSON(200, response)
@@ -2322,6 +2328,7 @@ func handleOpenResponsesStream(c echo.Context, responseID string, createdAt int6
if shouldStore {
store := GetGlobalStore()
store.Store(responseID, input, responseCompleted)
store.SetOwner(responseID, ownerFromContext(c))
}
// Send [DONE]
@@ -2966,6 +2973,18 @@ func convertORToolsToOpenAIFormat(orTools []schema.ORFunctionTool) []functions.T
return result
}
// ownerFromContext returns the identity (user ID) of the authenticated
// caller, or empty string when no authentication was performed (single-key /
// no-auth deployments). It is the value stamped on a response at creation and
// compared on read/cancel/resume to prevent one caller from accessing
// another's response by guessing its ID.
func ownerFromContext(c echo.Context) string {
if u := auth.GetUser(c); u != nil {
return u.ID
}
return ""
}
// GetResponseEndpoint returns a handler for GET /responses/:id
// This endpoint is used for polling background responses or resuming streaming
// @Summary Get a response by ID
@@ -2991,6 +3010,12 @@ func GetResponseEndpoint() func(c echo.Context) error {
return sendOpenResponsesError(c, 404, "not_found", fmt.Sprintf("response not found: %s", responseID), "id")
}
// Enforce response ownership. Return 404 (not 403) on mismatch so the
// existence of another caller's response is not leaked.
if !accessAllowed(stored, ownerFromContext(c)) {
return sendOpenResponsesError(c, 404, "not_found", fmt.Sprintf("response not found: %s", responseID), "id")
}
// Check if streaming resume is requested
streamParam := c.QueryParam("stream")
if streamParam == "true" {
@@ -3022,16 +3047,21 @@ func GetResponseEndpoint() func(c echo.Context) error {
// handleStreamResume handles resuming a streaming response from a specific sequence number
func handleStreamResume(c echo.Context, store *ResponseStore, responseID string, stored *StoredResponse, startingAfter int) error {
// Fetch buffered events before committing to an SSE response so an
// offset-lost gap can be reported as a clean HTTP status rather than a
// silently truncated event stream.
events, err := store.GetEventsAfter(responseID, startingAfter)
if err != nil {
if errors.Is(err, ErrOffsetLost) {
return sendOpenResponsesError(c, 409, "invalid_request_error", fmt.Sprintf("starting_after=%d is older than the oldest retained event; the resume buffer evicted those events and the stream cannot be resumed from that point", startingAfter), "starting_after")
}
return sendOpenResponsesError(c, 500, "server_error", fmt.Sprintf("failed to get events: %v", err), "")
}
c.Response().Header().Set("Content-Type", "text/event-stream")
c.Response().Header().Set("Cache-Control", "no-cache")
c.Response().Header().Set("Connection", "keep-alive")
// Get buffered events after the starting point
events, err := store.GetEventsAfter(responseID, startingAfter)
if err != nil {
return sendOpenResponsesError(c, 500, "server_error", fmt.Sprintf("failed to get events: %v", err), "")
}
// Send all buffered events
for _, event := range events {
fmt.Fprintf(c.Response().Writer, "event: %s\ndata: %s\n\n", event.EventType, string(event.Data))
@@ -3126,6 +3156,17 @@ func CancelResponseEndpoint() func(c echo.Context) error {
}
store := GetGlobalStore()
// Look up first so ownership can be checked before any mutation.
stored, err := store.Get(responseID)
if err != nil {
return sendOpenResponsesError(c, 404, "not_found", fmt.Sprintf("response not found: %s", responseID), "id")
}
// Return 404 (not 403) on owner mismatch so existence is not leaked.
if !accessAllowed(stored, ownerFromContext(c)) {
return sendOpenResponsesError(c, 404, "not_found", fmt.Sprintf("response not found: %s", responseID), "id")
}
response, err := store.Cancel(responseID)
if err != nil {
return sendOpenResponsesError(c, 404, "not_found", fmt.Sprintf("response not found: %s", responseID), "id")

View File

@@ -3,6 +3,7 @@ package openresponses
import (
"context"
"encoding/json"
"errors"
"fmt"
"sync"
"time"
@@ -11,6 +12,30 @@ import (
"github.com/mudler/xlog"
)
const (
// defaultMaxStreamEvents bounds how many resume-buffer events a single
// background response retains. Without a cap, a long-running or abandoned
// background generation grows StreamEvents without limit and can exhaust
// process memory. When the cap is exceeded the oldest events are evicted
// from the front (see AppendEvent). Mirrors llama.cpp's byte-capped slot
// ring used for resumable /slots state.
defaultMaxStreamEvents = 8192
// defaultMaxStreamBytes caps the total serialized size of retained
// resume-buffer events, evicting oldest-first when exceeded. This guards
// against a handful of very large events defeating the count cap. 0
// disables the byte cap (count cap still applies).
defaultMaxStreamBytes = 64 << 20 // 64 MiB
)
// ErrOffsetLost is returned by GetEventsAfter when the requested
// starting_after sequence number is older than the oldest event still
// retained in the resume buffer (i.e. the events between the requested
// offset and the current watermark were evicted by the cap). Callers should
// surface this to clients as a distinct error instead of silently returning
// a truncated stream that omits the dropped events.
var ErrOffsetLost = errors.New("resume offset lost: requested events were evicted from the buffer")
// ResponseStore provides thread-safe storage for Open Responses API responses
type ResponseStore struct {
mu sync.RWMutex
@@ -18,6 +43,12 @@ type ResponseStore struct {
ttl time.Duration // Time-to-live for stored responses (0 = no expiration)
cleanupCtx context.Context
cleanupCancel context.CancelFunc
// maxStreamEvents / maxStreamBytes bound the per-response resume buffer.
// Set once at construction from the default constants; tests may lower
// them. A value <= 0 disables that particular cap.
maxStreamEvents int
maxStreamBytes int
}
// StreamedEvent represents a buffered SSE event for streaming resume
@@ -35,6 +66,12 @@ type StoredResponse struct {
StoredAt time.Time
ExpiresAt *time.Time // nil if no expiration
// Owner is the identity (user ID) that created this response. It is set
// once at creation and never mutated, so it can be read without holding
// mu. Empty means "no owner" (single-key / no-auth deployments), in which
// case ownership checks are skipped for backward compatibility.
Owner string
// Background execution support
CancelFunc context.CancelFunc // For cancellation of background tasks
StreamEvents []StreamedEvent // Buffered events for streaming resume
@@ -42,6 +79,14 @@ type StoredResponse struct {
IsBackground bool // Was created with background=true
EventsChan chan struct{} // Signals new events for live subscribers
mu sync.RWMutex // Protect concurrent access to this response
// streamBytes tracks the total serialized size of the events currently
// retained in StreamEvents, used to enforce the byte cap. droppedThrough
// is the highest sequence number evicted from the front of the buffer
// (-1 = nothing evicted); it is the watermark GetEventsAfter compares
// against to detect a lost resume offset. Both are guarded by mu.
streamBytes int
droppedThrough int
}
var getGlobalStore = sync.OnceValue(func() *ResponseStore {
@@ -81,8 +126,10 @@ func (s *ResponseStore) SetTTL(ttl time.Duration) {
// If ttl is 0, responses are stored indefinitely
func NewResponseStore(ttl time.Duration) *ResponseStore {
store := &ResponseStore{
responses: make(map[string]*StoredResponse),
ttl: ttl,
responses: make(map[string]*StoredResponse),
ttl: ttl,
maxStreamEvents: defaultMaxStreamEvents,
maxStreamBytes: defaultMaxStreamBytes,
}
// Start cleanup goroutine if TTL is set
@@ -109,11 +156,12 @@ func (s *ResponseStore) Store(responseID string, request *schema.OpenResponsesRe
}
stored := &StoredResponse{
Request: request,
Response: response,
Items: items,
StoredAt: time.Now(),
ExpiresAt: nil,
Request: request,
Response: response,
Items: items,
StoredAt: time.Now(),
ExpiresAt: nil,
droppedThrough: -1,
}
// Set expiration if TTL is configured
@@ -256,16 +304,17 @@ func (s *ResponseStore) StoreBackground(responseID string, request *schema.OpenR
}
stored := &StoredResponse{
Request: request,
Response: response,
Items: items,
StoredAt: time.Now(),
ExpiresAt: nil,
CancelFunc: cancelFunc,
StreamEvents: []StreamedEvent{},
StreamEnabled: streamEnabled,
IsBackground: true,
EventsChan: make(chan struct{}, 100), // Buffered channel for event notifications
Request: request,
Response: response,
Items: items,
StoredAt: time.Now(),
ExpiresAt: nil,
CancelFunc: cancelFunc,
StreamEvents: []StreamedEvent{},
StreamEnabled: streamEnabled,
IsBackground: true,
EventsChan: make(chan struct{}, 100), // Buffered channel for event notifications
droppedThrough: -1,
}
// Set expiration if TTL is configured
@@ -349,6 +398,25 @@ func (s *ResponseStore) AppendEvent(responseID string, event *schema.ORStreamEve
EventType: event.Type,
Data: data,
})
stored.streamBytes += len(data)
// Evict oldest events from the front once either cap is exceeded. The
// byte cap never evicts the only remaining event (a single oversized
// event is still served once). Each eviction advances droppedThrough so
// a later resume below the watermark is reported as ErrOffsetLost rather
// than silently skipping the dropped events.
for (s.maxStreamEvents > 0 && len(stored.StreamEvents) > s.maxStreamEvents) ||
(s.maxStreamBytes > 0 && stored.streamBytes > s.maxStreamBytes && len(stored.StreamEvents) > 1) {
evicted := stored.StreamEvents[0]
stored.streamBytes -= len(evicted.Data)
if evicted.SequenceNumber > stored.droppedThrough {
stored.droppedThrough = evicted.SequenceNumber
}
// Release the evicted payload so it can be GC'd even though the
// backing array element is still owned by the slice until reuse.
stored.StreamEvents[0].Data = nil
stored.StreamEvents = stored.StreamEvents[1:]
}
stored.mu.Unlock()
// Notify any subscribers of new event
@@ -374,6 +442,14 @@ func (s *ResponseStore) GetEventsAfter(responseID string, startingAfter int) ([]
stored.mu.RLock()
defer stored.mu.RUnlock()
// If the requested offset is older than the watermark, the events the
// client expects next (those in (startingAfter, droppedThrough]) were
// evicted by the cap. Signal the gap rather than returning a stream that
// silently skips them.
if startingAfter < stored.droppedThrough {
return nil, ErrOffsetLost
}
var result []StreamedEvent
for _, event := range stored.StreamEvents {
if event.SequenceNumber > startingAfter {
@@ -447,3 +523,30 @@ func (s *ResponseStore) IsStreamEnabled(responseID string) (bool, error) {
return stored.StreamEnabled, nil
}
// SetOwner records the identity that owns a stored response. It is called
// once, right after the response is stored and before its ID is handed back
// to any client, so no lock on the stored response is required. A no-op for
// an empty owner or unknown response ID.
func (s *ResponseStore) SetOwner(responseID, owner string) {
if owner == "" {
return
}
s.mu.RLock()
stored, exists := s.responses[responseID]
s.mu.RUnlock()
if !exists {
return
}
stored.Owner = owner
}
// accessAllowed reports whether a caller identified by callerID may read or
// mutate the given stored response. An empty owner (single-key / no-auth
// deployments) is accessible by anyone, preserving backward compatibility;
// otherwise the caller identity must match the recorded owner.
func accessAllowed(stored *StoredResponse, callerID string) bool {
return stored.Owner == "" || stored.Owner == callerID
}

View File

@@ -585,6 +585,86 @@ var _ = Describe("ResponseStore", func() {
Expect(enabled2).To(BeFalse())
})
It("should bound the resume buffer and evict oldest events past the cap", func() {
// Lower the caps so the test stays fast; production defaults are
// large. Same-package access to the unexported fields is fine.
store.maxStreamEvents = 5
store.maxStreamBytes = 0 // count cap only for this test
responseID := "resp_buffer_cap"
request := &schema.OpenResponsesRequest{Model: "test"}
response := &schema.ORResponseResource{
ID: responseID,
Object: "response",
Status: schema.ORStatusInProgress,
}
_, cancel := context.WithCancel(context.Background())
defer cancel()
store.StoreBackground(responseID, request, response, cancel, true)
// Append well past the cap.
const total = 20
for i := range total {
err := store.AppendEvent(responseID, &schema.ORStreamEvent{
Type: "response.output_text.delta",
SequenceNumber: i,
})
Expect(err).ToNot(HaveOccurred())
}
stored, err := store.Get(responseID)
Expect(err).ToNot(HaveOccurred())
// (a) Buffer length stays bounded by the cap.
Expect(len(stored.StreamEvents)).To(Equal(5))
// (b) Oldest events were evicted: only the last 5 sequence numbers
// remain (15..19).
Expect(stored.StreamEvents[0].SequenceNumber).To(Equal(15))
Expect(stored.StreamEvents[len(stored.StreamEvents)-1].SequenceNumber).To(Equal(19))
// Asking for events after the last retained seq still works.
retained, err := store.GetEventsAfter(responseID, 14)
Expect(err).ToNot(HaveOccurred())
Expect(retained).To(HaveLen(5))
// (c) Asking below the dropped watermark returns ErrOffsetLost.
_, err = store.GetEventsAfter(responseID, 0)
Expect(err).To(MatchError(ErrOffsetLost))
_, err = store.GetEventsAfter(responseID, -1)
Expect(err).To(MatchError(ErrOffsetLost))
})
It("should record and enforce response ownership", func() {
responseID := "resp_owner_test"
request := &schema.OpenResponsesRequest{Model: "test"}
response := &schema.ORResponseResource{ID: responseID, Object: "response", Status: schema.ORStatusCompleted}
store.Store(responseID, request, response)
store.SetOwner(responseID, "userA")
stored, err := store.Get(responseID)
Expect(err).ToNot(HaveOccurred())
Expect(stored.Owner).To(Equal("userA"))
// Owner matches -> allowed; different identity -> denied.
Expect(accessAllowed(stored, "userA")).To(BeTrue())
Expect(accessAllowed(stored, "userB")).To(BeFalse())
// Backward compatibility: a response with no owner is accessible
// by any caller (single-key / no-auth deployments).
noOwnerID := "resp_no_owner"
store.Store(noOwnerID, request, &schema.ORResponseResource{ID: noOwnerID, Object: "response"})
noOwner, err := store.Get(noOwnerID)
Expect(err).ToNot(HaveOccurred())
Expect(noOwner.Owner).To(BeEmpty())
Expect(accessAllowed(noOwner, "anyone")).To(BeTrue())
Expect(accessAllowed(noOwner, "")).To(BeTrue())
})
It("should notify subscribers of new events", func() {
responseID := "resp_events_chan"
request := &schema.OpenResponsesRequest{Model: "test"}

View File

@@ -88,7 +88,7 @@ func RegisterNodeAdminRoutes(e *echo.Echo, registry *nodes.NodeRegistry, unloade
admin.POST("/:id/approve", localai.ApproveNodeEndpoint(registry, authDB, hmacSecret, natsCfg))
// Backend management on workers
admin.GET("/:id/backends", localai.ListBackendsOnNodeEndpoint(unloader))
admin.GET("/:id/backends", localai.ListBackendsOnNodeEndpoint(unloader, registry))
admin.POST("/:id/backends/install", localai.InstallBackendOnNodeEndpoint(unloader, galleryService, opcache, appConfig))
admin.POST("/:id/backends/delete", localai.DeleteBackendOnNodeEndpoint(unloader))

View File

@@ -30,6 +30,8 @@ import (
mcpTools "github.com/mudler/LocalAI/core/http/endpoints/mcp"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/jobs"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/LocalAI/core/services/syncstate"
"github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/httpclient"
"github.com/mudler/LocalAI/pkg/model"
@@ -43,8 +45,18 @@ type AgentJobService struct {
configLoader *config.ModelConfigLoader
evaluator *templates.Evaluator
// tasks is the cross-replica task store: an in-memory map kept consistent
// across replicas via NATS, with read-through to the configured persister
// (file in standalone, PostgreSQL in distributed). Unlike jobs - which already
// converge via the dispatcher + DB read-through - tasks previously read
// in-memory only, so ListTasks went stale on non-originating replicas.
tasks *syncstate.SyncedMap[string, schema.Task]
// taskNats is the distributed NATS client backing the tasks SyncedMap. It is
// not available at construction time, so it is injected via SetTaskSyncNATS
// during distributed wiring; nil keeps tasks in-memory-only (standalone).
taskNats messaging.MessagingClient
// Storage (in-memory primary, persister for secondary persistence)
tasks *xsync.SyncedMap[string, schema.Task]
jobs *xsync.SyncedMap[string, schema.Job]
persister JobPersister
userID string // Scoping: empty for global (main service), set for per-user instances
@@ -96,6 +108,31 @@ func (s *AgentJobService) SetDistributedJobStore(store *jobs.JobStore) {
s.persister = &dbJobPersister{store: store}
}
// SetTaskSyncNATS wires the distributed NATS client used to keep agent *tasks*
// consistent across replicas (jobs already converge via the dispatcher + DB
// read-through, so they are left untouched). The client is not available when the
// service is constructed, so it is injected here during distributed wiring and the
// tasks SyncedMap is rebuilt to pick it up. It is always called before Start /
// hydrate, while the map is still empty, so rebuilding loses no state. Passing nil
// (standalone) keeps the map in-memory-only with no broadcast.
func (s *AgentJobService) SetTaskSyncNATS(nats messaging.MessagingClient) {
s.taskNats = nats
s.buildTasksMap()
}
// buildTasksMap (re)constructs the cross-replica tasks SyncedMap from the current
// taskNats. The Store adapter reads s.persister/s.userID live, so a persister swap
// (SetDistributedJobStore) needs no rebuild; only the NATS client, fixed at
// New-time, forces one - hence SetTaskSyncNATS calls this.
func (s *AgentJobService) buildTasksMap() {
s.tasks = syncstate.New(syncstate.Config[string, schema.Task]{
Name: "agent.tasks",
Key: func(t schema.Task) string { return t.ID },
Nats: s.taskNats,
Store: &taskStoreAdapter{svc: s},
})
}
// Dispatcher returns the distributed dispatcher (nil if not in distributed mode).
func (s *AgentJobService) Dispatcher() DistributedDispatcher {
return s.dispatcher
@@ -106,13 +143,6 @@ func (s *AgentJobService) DBStore() *jobs.JobStore {
return s.rawDBStore
}
// saveTasks persists tasks via the configured persister (file or DB).
func (s *AgentJobService) saveTasks(task schema.Task) {
if err := s.persister.SaveTask(s.userID, task); err != nil {
xlog.Warn("Failed to persist task", "error", err, "task_id", task.ID)
}
}
// saveJobs persists jobs via the configured persister (file or DB).
func (s *AgentJobService) saveJobs(job schema.Job) {
if err := s.persister.SaveJob(s.userID, job); err != nil {
@@ -129,18 +159,8 @@ func (s *AgentJobService) LoadFromDB() {
// loadFromPersister loads tasks and jobs from the configured persister into memory.
func (s *AgentJobService) loadFromPersister() {
if tasks, err := s.persister.LoadTasks(s.userID); err != nil {
if err := s.hydrateTasks(s.appConfig.Context); err != nil {
xlog.Warn("Failed to load tasks from persister", "error", err)
} else {
for _, task := range tasks {
s.tasks.Set(task.ID, task)
if task.Enabled && task.Cron != "" {
if err := s.ScheduleCronTask(task); err != nil {
xlog.Warn("Failed to schedule cron task on load", "error", err, "task_id", task.ID)
}
}
}
xlog.Info("Loaded tasks from persister", "count", len(tasks))
}
if loadedJobs, err := s.persister.LoadJobs(s.userID); err != nil {
@@ -153,6 +173,27 @@ func (s *AgentJobService) loadFromPersister() {
}
}
// hydrateTasks loads tasks into the cross-replica SyncedMap and (re)schedules
// cron entries for enabled tasks. Hydration goes through the SyncedMap's Store
// read-through (Start), not Set, so it neither re-persists nor re-broadcasts the
// loaded tasks. Each service instance hydrates exactly once: the main service via
// Start -> loadFromPersister, per-user services via LoadFromDB or LoadTasksFromFile.
func (s *AgentJobService) hydrateTasks(ctx context.Context) error {
if err := s.tasks.Start(ctx); err != nil {
return err
}
tasks := s.tasks.List()
for _, task := range tasks {
if task.Enabled && task.Cron != "" {
if err := s.ScheduleCronTask(task); err != nil {
xlog.Warn("Failed to schedule cron task on load", "error", err, "task_id", task.ID)
}
}
}
xlog.Info("Loaded tasks from persister", "count", len(tasks))
return nil
}
// JobExecution represents a job to be executed
type JobExecution struct {
Job schema.Job
@@ -200,21 +241,19 @@ func NewAgentJobServiceWithPaths(
) *AgentJobService {
retentionDays := cmp.Or(appConfig.AgentJobRetentionDays, 30)
tasks := xsync.NewSyncedMap[string, schema.Task]()
jobsMap := xsync.NewSyncedMap[string, schema.Job]()
return &AgentJobService{
s := &AgentJobService{
appConfig: appConfig,
modelLoader: modelLoader,
configLoader: configLoader,
evaluator: evaluator,
tasks: tasks,
jobs: jobsMap,
persister: &fileJobPersister{
tasks: tasks,
jobs: jobsMap,
tasksFile: tasksFile,
jobsFile: jobsFile,
taskSet: make(map[string]schema.Task),
},
jobQueue: make(chan JobExecution, 100), // Buffer for 100 jobs
cancellations: xsync.NewSyncedMap[string, context.CancelFunc](),
@@ -222,25 +261,17 @@ func NewAgentJobServiceWithPaths(
cronEntries: xsync.NewSyncedMap[string, cron.EntryID](),
retentionDays: retentionDays,
}
// Build the cross-replica tasks map standalone (nil NATS); SetTaskSyncNATS
// rebuilds it with the distributed client once that is available, before Start.
s.buildTasksMap()
return s
}
// LoadTasksFromFile loads tasks from the persister into the in-memory map
// and schedules cron entries. Named "FromFile" for backward compat; in DB
// mode it loads from the database.
func (s *AgentJobService) LoadTasksFromFile() error {
tasks, err := s.persister.LoadTasks(s.userID)
if err != nil {
return err
}
for _, task := range tasks {
s.tasks.Set(task.ID, task)
if task.Enabled && task.Cron != "" {
if err := s.ScheduleCronTask(task); err != nil {
xlog.Warn("Failed to schedule cron task on load", "error", err, "task_id", task.ID)
}
}
}
return nil
return s.hydrateTasks(s.appConfig.Context)
}
// SaveTasksToFile flushes the current tasks map via the persister. File
@@ -293,8 +324,12 @@ func (s *AgentJobService) CreateTask(task schema.Task) (string, error) {
task.Enabled = true // Default to enabled
}
// Store task
s.tasks.Set(id, task)
// Store task: Set updates the in-memory map, write-throughs to the persister
// (file or DB), and broadcasts the create to peer replicas. Background ctx
// because CreateTask carries no request ctx (mirrors the finetune service).
if err := s.tasks.Set(context.Background(), task); err != nil {
return "", fmt.Errorf("failed to persist task: %w", err)
}
// Schedule cron if enabled and has cron expression
if task.Enabled && task.Cron != "" {
@@ -303,16 +338,15 @@ func (s *AgentJobService) CreateTask(task schema.Task) (string, error) {
}
}
s.saveTasks(task)
return id, nil
}
// UpdateTask updates an existing task
func (s *AgentJobService) UpdateTask(id string, task schema.Task) error {
if !s.tasks.Exists(id) {
existing, ok := s.tasks.Get(id)
if !ok {
return fmt.Errorf("%w: %s", ErrTaskNotFound, id)
}
existing := s.tasks.Get(id)
// Preserve ID and CreatedAt
task.ID = id
@@ -324,8 +358,10 @@ func (s *AgentJobService) UpdateTask(id string, task schema.Task) error {
s.UnscheduleCronTask(id)
}
// Store updated task
s.tasks.Set(id, task)
// Store updated task: write-through + broadcast (see CreateTask).
if err := s.tasks.Set(context.Background(), task); err != nil {
return fmt.Errorf("failed to persist task: %w", err)
}
// Schedule new cron if enabled and has cron expression
if task.Enabled && task.Cron != "" {
@@ -334,24 +370,22 @@ func (s *AgentJobService) UpdateTask(id string, task schema.Task) error {
}
}
s.saveTasks(task)
return nil
}
// DeleteTask deletes a task
func (s *AgentJobService) DeleteTask(id string) error {
if !s.tasks.Exists(id) {
if _, ok := s.tasks.Get(id); !ok {
return fmt.Errorf("%w: %s", ErrTaskNotFound, id)
}
// Unschedule cron
s.UnscheduleCronTask(id)
// Remove from memory
s.tasks.Delete(id)
if err := s.persister.DeleteTask(id); err != nil {
xlog.Warn("Failed to delete task from persister", "error", err, "task_id", id)
// Delete removes from the in-memory map, deletes from the persister, and
// broadcasts the removal to peer replicas.
if err := s.tasks.Delete(context.Background(), id); err != nil {
xlog.Warn("Failed to delete task from store", "error", err, "task_id", id)
}
return nil
@@ -359,8 +393,8 @@ func (s *AgentJobService) DeleteTask(id string) error {
// GetTask retrieves a task by ID
func (s *AgentJobService) GetTask(id string) (*schema.Task, error) {
task := s.tasks.Get(id)
if task.ID == "" {
task, ok := s.tasks.Get(id)
if !ok {
return nil, fmt.Errorf("%w: %s", ErrTaskNotFound, id)
}
return &task, nil
@@ -368,7 +402,7 @@ func (s *AgentJobService) GetTask(id string) (*schema.Task, error) {
// ListTasks returns all tasks, sorted by creation date (newest first)
func (s *AgentJobService) ListTasks() []schema.Task {
tasks := s.tasks.Values()
tasks := s.tasks.List()
// Sort by CreatedAt descending (newest first), then by Name for stability
slices.SortFunc(tasks, func(a, b schema.Task) int {
if a.CreatedAt.Equal(b.CreatedAt) {
@@ -397,8 +431,8 @@ func (s *AgentJobService) buildPrompt(templateStr string, params map[string]stri
// ExecuteJob creates and queues a job for execution
// multimedia can be nil for backward compatibility
func (s *AgentJobService) ExecuteJob(taskID string, params map[string]string, triggeredBy string, multimedia *schema.MultimediaAttachment) (string, error) {
task := s.tasks.Get(taskID)
if task.ID == "" {
task, ok := s.tasks.Get(taskID)
if !ok {
return "", fmt.Errorf("%w: %s", ErrTaskNotFound, taskID)
}
@@ -1451,6 +1485,12 @@ func (s *AgentJobService) Stop() error {
if s.cronScheduler != nil {
s.cronScheduler.Stop()
}
// Release the tasks SyncedMap subscription / background workers.
if s.tasks != nil {
if err := s.tasks.Close(); err != nil {
xlog.Warn("Error closing tasks sync map", "error", err)
}
}
xlog.Info("AgentJobService stopped")
return nil
}

View File

@@ -14,24 +14,38 @@ import (
)
// fileJobPersister persists tasks and jobs to JSON files.
// It holds references to the service's syncmaps and serializes the entire
// map contents on each save (bulk write). Reads at runtime return nil
// (the in-memory map is the authoritative source); LoadTasks/LoadJobs
// are used only at startup to bootstrap the syncmaps.
//
// Jobs serialize the service's in-memory jobs syncmap on each save (bulk write).
// Tasks are kept in this persister's own taskSet map instead: the tasks SyncedMap
// calls SaveTask/DeleteTask while holding its internal lock (write-through), so
// reading back the SyncedMap here would re-enter that lock and deadlock. The
// self-contained taskSet, seeded by LoadTasks, lets a per-task write rewrite the
// whole bulk file without touching the SyncedMap.
//
// Runtime reads (GetJob/ListJobs) return nil (the in-memory state is the
// authoritative source); LoadTasks/LoadJobs bootstrap state at startup.
type fileJobPersister struct {
tasks *xsync.SyncedMap[string, schema.Task]
jobs *xsync.SyncedMap[string, schema.Job]
tasksFile string
jobsFile string
mu sync.Mutex
// taskSet is the persister's own view of all tasks, seeded by LoadTasks and
// updated by SaveTask/DeleteTask. The bulk JSON file is rewritten from it.
taskSet map[string]schema.Task
}
func (p *fileJobPersister) SaveTask(_ string, _ schema.Task) error {
return p.saveTasksToFile()
func (p *fileJobPersister) SaveTask(_ string, task schema.Task) error {
p.mu.Lock()
defer p.mu.Unlock()
p.taskSet[task.ID] = task
return p.writeTasksLocked()
}
func (p *fileJobPersister) DeleteTask(_ string) error {
return p.saveTasksToFile()
func (p *fileJobPersister) DeleteTask(taskID string) error {
p.mu.Lock()
defer p.mu.Unlock()
delete(p.taskSet, taskID)
return p.writeTasksLocked()
}
func (p *fileJobPersister) SaveJob(_ string, _ schema.Job) error {
@@ -43,7 +57,9 @@ func (p *fileJobPersister) DeleteJob(_ string) error {
}
func (p *fileJobPersister) FlushTasks() error {
return p.saveTasksToFile()
p.mu.Lock()
defer p.mu.Unlock()
return p.writeTasksLocked()
}
func (p *fileJobPersister) FlushJobs() error {
@@ -83,6 +99,12 @@ func (p *fileJobPersister) LoadTasks(_ string) ([]schema.Task, error) {
return nil, fmt.Errorf("failed to parse tasks file: %w", err)
}
// Seed the in-memory set so subsequent per-task SaveTask/DeleteTask merge into
// (rather than overwrite) the persisted tasks when the bulk file is rewritten.
for _, t := range tf.Tasks {
p.taskSet[t.ID] = t
}
xlog.Info("Loaded tasks from file", "count", len(tf.Tasks))
return tf.Tasks, nil
}
@@ -118,19 +140,20 @@ func (p *fileJobPersister) CleanupOldJobs(_ time.Duration) (int64, error) {
return 0, nil // cleanup handled via in-memory filtering
}
// saveTasksToFile serializes the entire tasks map to the JSON file.
func (p *fileJobPersister) saveTasksToFile() error {
// writeTasksLocked serializes the persister's task set to the JSON file. Callers
// must hold p.mu.
func (p *fileJobPersister) writeTasksLocked() error {
if p.tasksFile == "" {
return nil
}
p.mu.Lock()
defer p.mu.Unlock()
tf := schema.TasksFile{
Tasks: p.tasks.Values(),
tasks := make([]schema.Task, 0, len(p.taskSet))
for _, t := range p.taskSet {
tasks = append(tasks, t)
}
tf := schema.TasksFile{Tasks: tasks}
data, err := json.MarshalIndent(tf, "", " ")
if err != nil {
return fmt.Errorf("failed to marshal tasks: %w", err)

View File

@@ -20,28 +20,26 @@ var _ = Describe("JobPersister", func() {
Context("fileJobPersister", func() {
var (
p *fileJobPersister
tasks *xsync.SyncedMap[string, schema.Task]
jobsMap *xsync.SyncedMap[string, schema.Job]
tmpDir string
)
BeforeEach(func() {
tmpDir = GinkgoT().TempDir()
tasks = xsync.NewSyncedMap[string, schema.Task]()
jobsMap = xsync.NewSyncedMap[string, schema.Job]()
p = &fileJobPersister{
tasks: tasks,
jobs: jobsMap,
tasksFile: filepath.Join(tmpDir, "tasks.json"),
jobsFile: filepath.Join(tmpDir, "jobs.json"),
// taskSet is the persister's own task view (decoupled from the tasks
// SyncedMap to avoid re-entering its lock during write-through).
taskSet: make(map[string]schema.Task),
}
})
It("SaveTask writes all tasks to file", func() {
tasks.Set("t1", schema.Task{ID: "t1", Name: "Task One", Model: "m", Prompt: "p"})
tasks.Set("t2", schema.Task{ID: "t2", Name: "Task Two", Model: "m", Prompt: "p"})
Expect(p.SaveTask("", schema.Task{})).To(Succeed())
Expect(p.SaveTask("", schema.Task{ID: "t1", Name: "Task One", Model: "m", Prompt: "p"})).To(Succeed())
Expect(p.SaveTask("", schema.Task{ID: "t2", Name: "Task Two", Model: "m", Prompt: "p"})).To(Succeed())
// Verify file contents
data, err := os.ReadFile(p.tasksFile)
@@ -52,11 +50,9 @@ var _ = Describe("JobPersister", func() {
})
It("DeleteTask writes updated tasks to file", func() {
tasks.Set("t1", schema.Task{ID: "t1", Name: "Keep"})
tasks.Set("t2", schema.Task{ID: "t2", Name: "Delete"})
Expect(p.SaveTask("", schema.Task{ID: "t1", Name: "Keep"})).To(Succeed())
Expect(p.SaveTask("", schema.Task{ID: "t2", Name: "Delete"})).To(Succeed())
// Simulate deletion from memory (caller does this before calling persister)
tasks.Delete("t2")
Expect(p.DeleteTask("t2")).To(Succeed())
data, err := os.ReadFile(p.tasksFile)

View File

@@ -0,0 +1,152 @@
package agentpool
// White-box tests (package agentpool) so a spec can build two AgentJobService
// instances sharing one in-memory bus and assert that agent *tasks* converge
// across replicas - the bug this migration fixes (ListTasks used to read
// in-memory only, so a task created on replica A was invisible on replica B).
// Jobs are deliberately untouched here: they already converge via the dispatcher
// + DB read-through.
import (
"context"
"time"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/LocalAI/core/services/syncstate"
"github.com/mudler/LocalAI/core/services/testutil"
"github.com/mudler/LocalAI/pkg/system"
)
// newTaskSyncService builds an AgentJobService wired to the given bus and a
// throwaway data dir (so the file persister has somewhere to write). Model/config
// loaders are nil because the task sync paths under test never touch them.
func newTaskSyncService(bus messaging.MessagingClient) *AgentJobService {
tmpDir := GinkgoT().TempDir()
sysState := &system.SystemState{}
sysState.Model.ModelsPath = tmpDir
appConfig := config.NewApplicationConfig(
config.WithDynamicConfigDir(tmpDir),
config.WithContext(context.Background()),
)
appConfig.SystemState = sysState
svc := NewAgentJobServiceWithPaths(appConfig, nil, nil, nil,
// Distinct per-replica files so the file persister write-through never
// crosses replicas: convergence here must be proven via the bus alone.
tmpDir+"/tasks.json", tmpDir+"/jobs.json")
svc.SetTaskSyncNATS(bus)
return svc
}
var _ = Describe("AgentJobService task cross-replica sync", func() {
Describe("two replicas sharing one bus", func() {
var (
bus *testutil.FakeBus
a, b *AgentJobService
)
BeforeEach(func() {
// One shared bus, two replicas: exactly the distributed topology where a
// round-robin request may land on a replica that did not originate the
// change.
bus = testutil.NewFakeBus()
a = newTaskSyncService(bus)
b = newTaskSyncService(bus)
// Start hydrates (empty here) and subscribes both replicas to deltas.
Expect(a.Start(context.Background())).To(Succeed())
Expect(b.Start(context.Background())).To(Succeed())
})
AfterEach(func() {
Expect(a.Stop()).To(Succeed())
Expect(b.Stop()).To(Succeed())
})
It("makes a task created on A visible via B's GetTask and ListTasks", func() {
id, err := a.CreateTask(schema.Task{Name: "Shared", Model: "m", Prompt: "p"})
Expect(err).NotTo(HaveOccurred())
got, err := b.GetTask(id)
Expect(err).NotTo(HaveOccurred(), "B must see a task A just created")
Expect(got.Name).To(Equal("Shared"))
listed := b.ListTasks()
Expect(listed).To(HaveLen(1))
Expect(listed[0].ID).To(Equal(id))
})
It("propagates a task update from A to B", func() {
id, err := a.CreateTask(schema.Task{Name: "Before", Model: "m", Prompt: "p"})
Expect(err).NotTo(HaveOccurred())
Expect(a.UpdateTask(id, schema.Task{Name: "After", Model: "m", Prompt: "p"})).To(Succeed())
got, err := b.GetTask(id)
Expect(err).NotTo(HaveOccurred())
Expect(got.Name).To(Equal("After"), "an update on A must be visible on B")
})
It("removes a task from B when it is deleted on A", func() {
id, err := a.CreateTask(schema.Task{Name: "Doomed", Model: "m", Prompt: "p"})
Expect(err).NotTo(HaveOccurred())
_, err = b.GetTask(id)
Expect(err).NotTo(HaveOccurred(), "precondition: B must have the task before the delete")
Expect(a.DeleteTask(id)).To(Succeed())
_, err = b.GetTask(id)
Expect(err).To(HaveOccurred(), "a delete on A must remove the task from B")
Expect(b.ListTasks()).To(BeEmpty())
})
It("does not re-broadcast a delta it received (echo-loop guard)", func() {
subject := messaging.SubjectSyncStateDelta("agent.tasks")
_, err := a.CreateTask(schema.Task{Name: "Once", Model: "m", Prompt: "p"})
Expect(err).NotTo(HaveOccurred())
// Exactly one publish: A's create. B applies it without re-publishing,
// otherwise this would be 2+ and a real bus would storm.
Expect(bus.PublishCount(subject)).To(Equal(1))
})
})
Describe("ListTasks ordering and scoping", func() {
var svc *AgentJobService
BeforeEach(func() {
svc = newTaskSyncService(testutil.NewFakeBus())
Expect(svc.Start(context.Background())).To(Succeed())
})
AfterEach(func() { Expect(svc.Stop()).To(Succeed()) })
It("sorts newest-first, breaking ties by name", func() {
// CreateTask stamps CreatedAt with time.Now(); space them out so ordering
// is deterministic rather than relying on the sub-millisecond gap.
oldID, err := svc.CreateTask(schema.Task{Name: "Old", Model: "m", Prompt: "p"})
Expect(err).NotTo(HaveOccurred())
time.Sleep(5 * time.Millisecond)
newID, err := svc.CreateTask(schema.Task{Name: "New", Model: "m", Prompt: "p"})
Expect(err).NotTo(HaveOccurred())
listed := svc.ListTasks()
Expect(listed).To(HaveLen(2))
Expect(listed[0].ID).To(Equal(newID), "newest first")
Expect(listed[1].ID).To(Equal(oldID))
})
})
Describe("compile-time adapter contract", func() {
It("satisfies syncstate.Store for tasks", func() {
// Mirrors the var assertion in task_syncstore.go; keeps the type
// referenced from a spec so drift surfaces here too.
var _ syncstate.Store[string, schema.Task] = (*taskStoreAdapter)(nil)
Expect(&taskStoreAdapter{}).ToNot(BeNil())
})
})
})

View File

@@ -0,0 +1,47 @@
package agentpool
import (
"context"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/syncstate"
)
// taskStoreAdapter bridges the existing JobPersister (file- or DB-backed) to the
// generic syncstate.Store the tasks SyncedMap consumes. Only tasks are migrated:
// jobs already converge across replicas via the dispatcher (NATS) plus the DB
// read-through in ListJobs/GetJob, whereas ListTasks read in-memory only and so
// went stale on replicas that did not originate the change.
//
// The adapter reads svc.persister and svc.userID live (rather than capturing
// them) because both are configured by setters - SetDistributedJobStore swaps the
// file persister for the DB one, SetUserID scopes per-user queries - AFTER the
// service, and thus this adapter, is constructed. Reading them at call time means
// the SyncedMap never has to be rebuilt when the persister is swapped.
//
// The SyncedMap value type is schema.Task: the exact shape ListTasks returns, so
// reads need no conversion and REST responses are provably unchanged.
type taskStoreAdapter struct {
svc *AgentJobService
}
// compile-time assertion that the adapter satisfies the component's Store.
var _ syncstate.Store[string, schema.Task] = (*taskStoreAdapter)(nil)
// List hydrates the map from durable storage on Start/reconnect: the file's task
// list (standalone) or every task row (DB / distributed).
func (a *taskStoreAdapter) List(_ context.Context) ([]schema.Task, error) {
return a.svc.persister.LoadTasks(a.svc.userID)
}
// Upsert write-through persists a single task created/updated locally; the
// SyncedMap then broadcasts the delta to peers.
func (a *taskStoreAdapter) Upsert(_ context.Context, task schema.Task) error {
return a.svc.persister.SaveTask(a.svc.userID, task)
}
// Delete write-through removes a task locally; the SyncedMap then broadcasts the
// removal to peers.
func (a *taskStoreAdapter) Delete(_ context.Context, id string) error {
return a.svc.persister.DeleteTask(id)
}

View File

@@ -7,6 +7,7 @@ import (
"github.com/mudler/LocalAGI/webui/collections"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/services/jobs"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/xlog"
@@ -28,6 +29,9 @@ type UserServicesManager struct {
// Shared distributed backends (set once, inherited by per-user job services)
jobDispatcher DistributedDispatcher
jobDBStore *jobs.JobStore
// jobNats keeps per-user agent tasks consistent across replicas (nil in
// standalone). Inherited by each per-user AgentJobService.
jobNats messaging.MessagingClient
}
// NewUserServicesManager creates a new UserServicesManager.
@@ -162,6 +166,10 @@ func (m *UserServicesManager) GetJobs(userID string) (*AgentJobService, error) {
if m.jobDispatcher != nil {
svc.SetDistributedBackends(m.jobDispatcher)
}
// Inherit the NATS client so per-user tasks broadcast across replicas. Must be
// set before the hydrate below (LoadFromDB / LoadTasksFromFile) so the tasks
// SyncedMap is rebuilt with the client while it is still empty.
svc.SetTaskSyncNATS(m.jobNats)
if m.jobDBStore != nil {
svc.SetDistributedJobStore(m.jobDBStore)
// Load tasks/jobs from DB immediately (per-user services skip Start())
@@ -189,6 +197,12 @@ func (m *UserServicesManager) SetJobDBStore(s *jobs.JobStore) {
m.jobDBStore = s
}
// SetJobSyncNATS sets the NATS client used to keep per-user agent tasks consistent
// across replicas.
func (m *UserServicesManager) SetJobSyncNATS(nats messaging.MessagingClient) {
m.jobNats = nats
}
// ListAllUserIDs returns all user IDs that have scoped data directories.
func (m *UserServicesManager) ListAllUserIDs() ([]string, error) {
return m.storage.ListUserDirs()

View File

@@ -8,6 +8,7 @@ import (
"github.com/google/uuid"
"github.com/mudler/LocalAI/core/services/advisorylock"
"gorm.io/gorm"
"gorm.io/gorm/clause"
)
// FineTuneJobRecord tracks fine-tune jobs in PostgreSQL.
@@ -80,6 +81,34 @@ func (s *FineTuneStore) List(userID string) ([]FineTuneJobRecord, error) {
return jobs, q.Find(&jobs).Error
}
// ListAll returns every fine-tune job across all users. The SyncedMap that backs
// FineTuneService is a single global map (the REST API filters by user at read
// time), so hydrate needs the full set rather than the per-user List above.
func (s *FineTuneStore) ListAll() ([]FineTuneJobRecord, error) {
var jobs []FineTuneJobRecord
return jobs, s.db.Order("created_at DESC").Find(&jobs).Error
}
// Upsert idempotently inserts or fully replaces a job row by primary key. The
// SyncedMap write-through path issues a single Set per mutation regardless of
// whether the job already exists, so it needs one create-or-update primitive
// (Create alone fails on a duplicate key, UpdateStatus alone misses new rows and
// only touches a few columns).
func (s *FineTuneStore) Upsert(job *FineTuneJobRecord) error {
if job.ID == "" {
job.ID = uuid.New().String()
}
now := time.Now()
if job.CreatedAt.IsZero() {
job.CreatedAt = now
}
job.UpdatedAt = now
return s.db.Clauses(clause.OnConflict{
Columns: []clause.Column{{Name: "id"}},
UpdateAll: true,
}).Create(job).Error
}
// UpdateStatus updates the status and message of a fine-tune job.
func (s *FineTuneStore) UpdateStatus(id, status, message string) error {
return s.db.Model(&FineTuneJobRecord{}).Where("id = ?", id).Updates(map[string]any{

View File

@@ -0,0 +1,13 @@
package distributed_test
import (
"testing"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestDistributed(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "Distributed Suite")
}

View File

@@ -0,0 +1,61 @@
package distributed_test
import (
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"github.com/mudler/LocalAI/core/services/distributed"
"github.com/mudler/LocalAI/core/services/testutil"
)
var _ = Describe("FineTuneStore", func() {
var store *distributed.FineTuneStore
BeforeEach(func() {
db := testutil.SetupTestDB()
var err error
store, err = distributed.NewFineTuneStore(db)
Expect(err).ToNot(HaveOccurred())
})
Describe("ListAll", func() {
It("returns jobs across all users (unlike per-user List)", func() {
Expect(store.Create(&distributed.FineTuneJobRecord{ID: "j1", UserID: "u1", Status: "queued"})).To(Succeed())
Expect(store.Create(&distributed.FineTuneJobRecord{ID: "j2", UserID: "u2", Status: "queued"})).To(Succeed())
all, err := store.ListAll()
Expect(err).ToNot(HaveOccurred())
Expect(all).To(HaveLen(2))
perUser, err := store.List("u1")
Expect(err).ToNot(HaveOccurred())
Expect(perUser).To(HaveLen(1), "List stays per-user")
})
})
Describe("Upsert", func() {
It("inserts a new row", func() {
Expect(store.Upsert(&distributed.FineTuneJobRecord{ID: "up-1", UserID: "u1", Status: "queued"})).To(Succeed())
got, err := store.Get("up-1")
Expect(err).ToNot(HaveOccurred())
Expect(got.Status).To(Equal("queued"))
})
It("idempotently updates an existing row on a repeated key", func() {
Expect(store.Upsert(&distributed.FineTuneJobRecord{ID: "up-2", UserID: "u1", Status: "queued"})).To(Succeed())
// Second Upsert with the same primary key must update, not error on a
// duplicate-key violation (this is the SyncedMap write-through contract).
Expect(store.Upsert(&distributed.FineTuneJobRecord{ID: "up-2", UserID: "u1", Status: "completed", Message: "done"})).To(Succeed())
got, err := store.Get("up-2")
Expect(err).ToNot(HaveOccurred())
Expect(got.Status).To(Equal("completed"))
Expect(got.Message).To(Equal("done"))
all, err := store.ListAll()
Expect(err).ToNot(HaveOccurred())
Expect(all).To(HaveLen(1), "upsert must not create a duplicate")
})
})
})

View File

@@ -11,6 +11,7 @@ import (
type Stores struct {
Gallery *GalleryStore
FineTune *FineTuneStore
Quant *QuantStore
Skills *SkillStore
}
@@ -26,15 +27,21 @@ func InitStores(db *gorm.DB) (*Stores, error) {
return nil, fmt.Errorf("fine-tune store: %w", err)
}
quant, err := NewQuantStore(db)
if err != nil {
return nil, fmt.Errorf("quantization store: %w", err)
}
skills, err := NewSkillStore(db)
if err != nil {
return nil, fmt.Errorf("skills store: %w", err)
}
xlog.Info("Distributed stores initialized (Gallery, FineTune, Skills)")
xlog.Info("Distributed stores initialized (Gallery, FineTune, Quant, Skills)")
return &Stores{
Gallery: gallery,
FineTune: ft,
Quant: quant,
Skills: skills,
}, nil
}

View File

@@ -0,0 +1,105 @@
package distributed
import (
"context"
"fmt"
"time"
"github.com/google/uuid"
"github.com/mudler/LocalAI/core/services/advisorylock"
"gorm.io/gorm"
"gorm.io/gorm/clause"
)
// QuantJobRecord tracks quantization jobs in PostgreSQL. The columns mirror the
// API shape (schema.QuantizationJob); the structured Config and ExtraOptions are
// serialized into JSON text columns so a record fully reconstructs the job.
type QuantJobRecord struct {
ID string `gorm:"primaryKey;size:36" json:"id"`
UserID string `gorm:"index;size:36" json:"user_id,omitempty"`
Model string `gorm:"size:255" json:"model"`
Backend string `gorm:"size:64" json:"backend"`
ModelID string `gorm:"size:255" json:"model_id,omitempty"`
QuantizationType string `gorm:"size:32" json:"quantization_type"`
Status string `gorm:"index;size:32;default:queued" json:"status"` // queued, downloading, converting, quantizing, completed, failed, stopped
Message string `gorm:"type:text" json:"message,omitempty"`
OutputDir string `gorm:"size:512" json:"output_dir,omitempty"`
OutputFile string `gorm:"size:512" json:"output_file,omitempty"`
ConfigJSON string `gorm:"column:config;type:text" json:"-"`
ExtraOptsJSON string `gorm:"column:extra_options;type:text" json:"-"`
ImportStatus string `gorm:"size:32" json:"import_status,omitempty"`
ImportMessage string `gorm:"type:text" json:"import_message,omitempty"`
ImportModelName string `gorm:"size:255" json:"import_model_name,omitempty"`
CreatedAt time.Time `json:"created_at"`
UpdatedAt time.Time `json:"updated_at"`
}
func (QuantJobRecord) TableName() string { return "quantization_jobs" }
// QuantStore manages quantization job state in PostgreSQL.
type QuantStore struct {
db *gorm.DB
}
// NewQuantStore creates a new QuantStore and auto-migrates.
// Uses a PostgreSQL advisory lock to prevent concurrent migration races
// when multiple instances (frontend + workers) start at the same time.
func NewQuantStore(db *gorm.DB) (*QuantStore, error) {
if err := advisorylock.WithLockCtx(context.Background(), db, advisorylock.KeySchemaMigrate, func() error {
return db.AutoMigrate(&QuantJobRecord{})
}); err != nil {
return nil, fmt.Errorf("migrating quantization_jobs: %w", err)
}
return &QuantStore{db: db}, nil
}
// Create stores a new quantization job.
func (s *QuantStore) Create(job *QuantJobRecord) error {
if job.ID == "" {
job.ID = uuid.New().String()
}
job.CreatedAt = time.Now()
job.UpdatedAt = job.CreatedAt
return s.db.Create(job).Error
}
// Get retrieves a quantization job by ID.
func (s *QuantStore) Get(id string) (*QuantJobRecord, error) {
var job QuantJobRecord
if err := s.db.First(&job, "id = ?", id).Error; err != nil {
return nil, err
}
return &job, nil
}
// ListAll returns every quantization job across all users. The SyncedMap that
// backs QuantizationService is a single global map (the REST API filters by user
// at read time), so hydrate needs the full set.
func (s *QuantStore) ListAll() ([]QuantJobRecord, error) {
var jobs []QuantJobRecord
return jobs, s.db.Order("created_at DESC").Find(&jobs).Error
}
// Upsert idempotently inserts or fully replaces a job row by primary key. The
// SyncedMap write-through path issues a single Set per mutation regardless of
// whether the job already exists, so it needs one create-or-update primitive
// (Create alone fails on a duplicate key).
func (s *QuantStore) Upsert(job *QuantJobRecord) error {
if job.ID == "" {
job.ID = uuid.New().String()
}
now := time.Now()
if job.CreatedAt.IsZero() {
job.CreatedAt = now
}
job.UpdatedAt = now
return s.db.Clauses(clause.OnConflict{
Columns: []clause.Column{{Name: "id"}},
UpdateAll: true,
}).Create(job).Error
}
// Delete removes a quantization job.
func (s *QuantStore) Delete(id string) error {
return s.db.Where("id = ?", id).Delete(&QuantJobRecord{}).Error
}

View File

@@ -0,0 +1,57 @@
package distributed_test
import (
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"github.com/mudler/LocalAI/core/services/distributed"
"github.com/mudler/LocalAI/core/services/testutil"
)
var _ = Describe("QuantStore", func() {
var store *distributed.QuantStore
BeforeEach(func() {
db := testutil.SetupTestDB()
var err error
store, err = distributed.NewQuantStore(db)
Expect(err).ToNot(HaveOccurred())
})
Describe("ListAll", func() {
It("returns jobs across all users", func() {
Expect(store.Create(&distributed.QuantJobRecord{ID: "j1", UserID: "u1", Status: "queued"})).To(Succeed())
Expect(store.Create(&distributed.QuantJobRecord{ID: "j2", UserID: "u2", Status: "queued"})).To(Succeed())
all, err := store.ListAll()
Expect(err).ToNot(HaveOccurred())
Expect(all).To(HaveLen(2))
})
})
Describe("Upsert", func() {
It("inserts a new row", func() {
Expect(store.Upsert(&distributed.QuantJobRecord{ID: "up-1", UserID: "u1", Status: "queued"})).To(Succeed())
got, err := store.Get("up-1")
Expect(err).ToNot(HaveOccurred())
Expect(got.Status).To(Equal("queued"))
})
It("idempotently updates an existing row on a repeated key", func() {
Expect(store.Upsert(&distributed.QuantJobRecord{ID: "up-2", UserID: "u1", Status: "queued"})).To(Succeed())
// Second Upsert with the same primary key must update, not error on a
// duplicate-key violation (this is the SyncedMap write-through contract).
Expect(store.Upsert(&distributed.QuantJobRecord{ID: "up-2", UserID: "u1", Status: "completed", Message: "done"})).To(Succeed())
got, err := store.Get("up-2")
Expect(err).ToNot(HaveOccurred())
Expect(got.Status).To(Equal("completed"))
Expect(got.Message).To(Equal("done"))
all, err := store.ListAll()
Expect(err).ToNot(HaveOccurred())
Expect(all).To(HaveLen(1), "upsert must not create a duplicate")
})
})
})

View File

@@ -0,0 +1,13 @@
package finetune
import (
"testing"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestFinetune(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "Finetune Suite")
}

View File

@@ -19,6 +19,7 @@ import (
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/distributed"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/LocalAI/core/services/syncstate"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/utils"
@@ -32,44 +33,63 @@ type FineTuneService struct {
modelLoader *model.ModelLoader
configLoader *config.ModelConfigLoader
mu sync.Mutex
jobs map[string]*schema.FineTuneJob
// mu serializes the read-modify-write of job values. The SyncedMap guards its
// own map structure, but a job is a pointer mutated in place (e.g. the export
// goroutine), so the service still needs a lock to keep those field updates
// and the subsequent Set atomic with respect to readers.
mu sync.Mutex
// Distributed mode (nil when not in distributed mode)
natsClient messaging.Publisher
fineTuneStore *distributed.FineTuneStore
// jobs is the cross-replica job store: an in-memory map kept consistent across
// replicas via NATS, optionally read-through to PostgreSQL in distributed mode.
jobs *syncstate.SyncedMap[string, *schema.FineTuneJob]
}
// SetNATSClient sets the NATS client for distributed progress publishing.
func (s *FineTuneService) SetNATSClient(nc messaging.Publisher) {
s.mu.Lock()
defer s.mu.Unlock()
s.natsClient = nc
}
// SetFineTuneStore sets the PostgreSQL fine-tune store for distributed persistence.
func (s *FineTuneService) SetFineTuneStore(store *distributed.FineTuneStore) {
s.mu.Lock()
defer s.mu.Unlock()
s.fineTuneStore = store
}
// NewFineTuneService creates a new FineTuneService.
// NewFineTuneService creates a new FineTuneService. In distributed mode pass the
// shared NATS client and PostgreSQL store so jobs stay consistent across
// replicas; pass nil for both in standalone mode, where the disk Loader hydrates
// the map and there is nothing to broadcast.
func NewFineTuneService(
appConfig *config.ApplicationConfig,
modelLoader *model.ModelLoader,
configLoader *config.ModelConfigLoader,
nats messaging.MessagingClient,
store *distributed.FineTuneStore,
) *FineTuneService {
s := &FineTuneService{
appConfig: appConfig,
modelLoader: modelLoader,
configLoader: configLoader,
jobs: make(map[string]*schema.FineTuneJob),
}
s.loadAllJobs()
// Only attach a Store interface when a concrete store exists, otherwise the
// SyncedMap would see a non-nil interface wrapping a nil pointer and try to
// hydrate/write through a nil DB.
var syncStore syncstate.Store[string, *schema.FineTuneJob]
if store != nil {
syncStore = &fineTuneStoreAdapter{store: store}
}
s.jobs = syncstate.New(syncstate.Config[string, *schema.FineTuneJob]{
Name: "finetune.jobs",
Key: func(j *schema.FineTuneJob) string { return j.ID },
Nats: nats,
Store: syncStore,
Loader: s.loadJobsFromDisk, // ignored when Store is set (distributed mode)
})
// Hydrate + subscribe. A hydrate failure must not take the server down: log
// and continue degraded (standalone), mirroring the OpCache wiring.
if err := s.jobs.Start(appConfig.Context); err != nil {
xlog.Warn("FineTune SyncedMap start failed; running degraded", "error", err)
}
return s
}
// Close releases the SyncedMap subscription and background workers.
func (s *FineTuneService) Close() error {
return s.jobs.Close()
}
// fineTuneBaseDir returns the base directory for fine-tune job data.
func (s *FineTuneService) fineTuneBaseDir() string {
return filepath.Join(s.appConfig.DataPath, "fine-tune")
@@ -100,15 +120,18 @@ func (s *FineTuneService) saveJobState(job *schema.FineTuneJob) {
}
}
// loadAllJobs scans the fine-tune directory for persisted jobs and loads them.
func (s *FineTuneService) loadAllJobs() {
// loadJobsFromDisk scans the fine-tune directory for persisted jobs and returns
// them. It is the SyncedMap Loader used in standalone mode (no DB); the returned
// slice hydrates the map on Start.
func (s *FineTuneService) loadJobsFromDisk(_ context.Context) ([]*schema.FineTuneJob, error) {
baseDir := s.fineTuneBaseDir()
entries, err := os.ReadDir(baseDir)
if err != nil {
// Directory doesn't exist yet — that's fine
return
// Directory doesn't exist yet — that's fine, start empty.
return nil, nil
}
var jobs []*schema.FineTuneJob
for _, entry := range entries {
if !entry.IsDir() {
continue
@@ -137,12 +160,13 @@ func (s *FineTuneService) loadAllJobs() {
job.ExportMessage = "Server restarted while export was running"
}
s.jobs[job.ID] = &job
jobs = append(jobs, &job)
}
if len(s.jobs) > 0 {
xlog.Info("Loaded persisted fine-tune jobs", "count", len(s.jobs))
if len(jobs) > 0 {
xlog.Info("Loaded persisted fine-tune jobs", "count", len(jobs))
}
return jobs, nil
}
// StartJob starts a new fine-tuning job.
@@ -236,27 +260,13 @@ func (s *FineTuneService) StartJob(ctx context.Context, userID string, req schem
CreatedAt: time.Now().UTC().Format(time.RFC3339),
Config: &req,
}
s.jobs[jobID] = job
s.saveJobState(job)
// Persist to PostgreSQL in distributed mode
if s.fineTuneStore != nil {
configJSON, _ := json.Marshal(req)
extraJSON, _ := json.Marshal(req.ExtraOptions)
s.fineTuneStore.Create(&distributed.FineTuneJobRecord{
ID: jobID,
UserID: userID,
Model: req.Model,
Backend: backendName,
ModelID: modelID,
TrainingType: req.TrainingType,
TrainingMethod: req.TrainingMethod,
Status: "queued",
OutputDir: outputDir,
ConfigJSON: string(configJSON),
ExtraOptsJSON: string(extraJSON),
})
// Set write-through persists to PostgreSQL (distributed) and broadcasts to
// peer replicas; the disk state.json is written separately for restart
// recovery / standalone hydrate.
if err := s.jobs.Set(ctx, job); err != nil {
return nil, fmt.Errorf("failed to persist job: %w", err)
}
s.saveJobState(job)
return &schema.FineTuneJobResponse{
ID: jobID,
@@ -270,7 +280,7 @@ func (s *FineTuneService) GetJob(userID, jobID string) (*schema.FineTuneJob, err
s.mu.Lock()
defer s.mu.Unlock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
return nil, fmt.Errorf("job not found: %s", jobID)
}
@@ -286,7 +296,7 @@ func (s *FineTuneService) ListJobs(userID string) []*schema.FineTuneJob {
defer s.mu.Unlock()
var result []*schema.FineTuneJob
for _, job := range s.jobs {
for _, job := range s.jobs.List() {
if userID == "" || job.UserID == userID {
result = append(result, job)
}
@@ -302,7 +312,7 @@ func (s *FineTuneService) ListJobs(userID string) []*schema.FineTuneJob {
// StopJob stops a running fine-tuning job.
func (s *FineTuneService) StopJob(ctx context.Context, userID, jobID string, saveCheckpoint bool) error {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return fmt.Errorf("job not found: %s", jobID)
@@ -323,10 +333,10 @@ func (s *FineTuneService) StopJob(ctx context.Context, userID, jobID string, sav
s.mu.Lock()
job.Status = "stopped"
job.Message = "Training stopped by user"
s.saveJobState(job)
if s.fineTuneStore != nil {
s.fineTuneStore.UpdateStatus(jobID, "stopped", "Training stopped by user")
if err := s.jobs.Set(ctx, job); err != nil {
xlog.Warn("Failed to persist stopped job", "job_id", jobID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
return nil
@@ -335,7 +345,7 @@ func (s *FineTuneService) StopJob(ctx context.Context, userID, jobID string, sav
// DeleteJob removes a fine-tuning job and its associated data from disk.
func (s *FineTuneService) DeleteJob(userID, jobID string) error {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return fmt.Errorf("job not found: %s", jobID)
@@ -360,9 +370,10 @@ func (s *FineTuneService) DeleteJob(userID, jobID string) error {
}
exportModelName := job.ExportModelName
delete(s.jobs, jobID)
if s.fineTuneStore != nil {
s.fineTuneStore.Delete(jobID)
// Delete write-through removes the DB row (distributed) and broadcasts the
// removal to peer replicas. DeleteJob has no ctx, so use Background.
if err := s.jobs.Delete(context.Background(), jobID); err != nil {
xlog.Warn("Failed to delete job from store", "job_id", jobID, "error", err)
}
s.mu.Unlock()
@@ -398,7 +409,7 @@ func (s *FineTuneService) DeleteJob(userID, jobID string) error {
// StreamProgress opens a gRPC progress stream and calls the callback for each update.
func (s *FineTuneService) StreamProgress(ctx context.Context, userID, jobID string, callback func(event *schema.FineTuneProgressEvent)) error {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return fmt.Errorf("job not found: %s", jobID)
@@ -427,7 +438,7 @@ func (s *FineTuneService) StreamProgress(ctx context.Context, userID, jobID stri
}, func(update *pb.FineTuneProgressUpdate) {
// Update job status and persist
s.mu.Lock()
if j, ok := s.jobs[jobID]; ok {
if j, ok := s.jobs.Get(jobID); ok {
// Don't let progress updates overwrite terminal states
isTerminal := j.Status == "stopped" || j.Status == "completed" || j.Status == "failed"
if !isTerminal {
@@ -436,10 +447,10 @@ func (s *FineTuneService) StreamProgress(ctx context.Context, userID, jobID stri
if update.Message != "" {
j.Message = update.Message
}
s.saveJobState(j)
if s.fineTuneStore != nil {
s.fineTuneStore.UpdateStatus(jobID, j.Status, j.Message)
if err := s.jobs.Set(ctx, j); err != nil {
xlog.Warn("Failed to persist progress update", "job_id", jobID, "error", err)
}
s.saveJobState(j)
}
s.mu.Unlock()
@@ -474,7 +485,7 @@ func (s *FineTuneService) StreamProgress(ctx context.Context, userID, jobID stri
// ListCheckpoints lists checkpoints for a job.
func (s *FineTuneService) ListCheckpoints(ctx context.Context, userID, jobID string) ([]*pb.CheckpointInfo, error) {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return nil, fmt.Errorf("job not found: %s", jobID)
@@ -520,7 +531,7 @@ func sanitizeModelName(s string) string {
// ExportModel starts an async model export from a checkpoint and returns the intended model name immediately.
func (s *FineTuneService) ExportModel(ctx context.Context, userID, jobID string, req schema.ExportRequest) (string, error) {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return "", fmt.Errorf("job not found: %s", jobID)
@@ -572,6 +583,9 @@ func (s *FineTuneService) ExportModel(ctx context.Context, userID, jobID string,
job.ExportStatus = "exporting"
job.ExportMessage = ""
job.ExportModelName = ""
if err := s.jobs.Set(ctx, job); err != nil {
xlog.Warn("Failed to persist export start", "job_id", jobID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
@@ -662,24 +676,30 @@ func (s *FineTuneService) ExportModel(ctx context.Context, userID, jobID string,
xlog.Info("Model exported and registered", "job_id", jobID, "model_name", modelName, "format", req.ExportFormat)
// Runs after the HTTP request returns, so use Background rather than the
// (now likely cancelled) request ctx for the write-through.
s.mu.Lock()
job.ExportStatus = "completed"
job.ExportModelName = modelName
job.ExportMessage = ""
s.saveJobState(job)
if s.fineTuneStore != nil {
s.fineTuneStore.UpdateExportStatus(jobID, "completed", "", modelName)
if err := s.jobs.Set(context.Background(), job); err != nil {
xlog.Warn("Failed to persist export completion", "job_id", jobID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
}()
return modelName, nil
}
// setExportMessage updates the export message and persists the job state.
// setExportMessage updates the export message and persists the job state. Called
// from the background export goroutine, so it uses Background for write-through.
func (s *FineTuneService) setExportMessage(job *schema.FineTuneJob, msg string) {
s.mu.Lock()
job.ExportMessage = msg
if err := s.jobs.Set(context.Background(), job); err != nil {
xlog.Warn("Failed to persist export message", "job_id", job.ID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
}
@@ -687,7 +707,7 @@ func (s *FineTuneService) setExportMessage(job *schema.FineTuneJob, msg string)
// GetExportedModelPath returns the path to the exported model directory and its name.
func (s *FineTuneService) GetExportedModelPath(userID, jobID string) (string, string, error) {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return "", "", fmt.Errorf("job not found: %s", jobID)
@@ -723,10 +743,10 @@ func (s *FineTuneService) setExportFailed(job *schema.FineTuneJob, message strin
s.mu.Lock()
job.ExportStatus = "failed"
job.ExportMessage = message
s.saveJobState(job)
if s.fineTuneStore != nil {
s.fineTuneStore.UpdateExportStatus(job.ID, "failed", message, "")
if err := s.jobs.Set(context.Background(), job); err != nil {
xlog.Warn("Failed to persist export failure", "job_id", job.ID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
}

View File

@@ -0,0 +1,185 @@
package finetune
// White-box tests (package finetune) so a spec can drive the service's internal
// SyncedMap the same way StartJob does (via jobs.Set) without standing up a
// training backend, then assert the cross-replica reads (GetJob/ListJobs) and
// the adapter conversions that keep REST responses byte-for-byte unchanged.
import (
"context"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/distributed"
"github.com/mudler/LocalAI/core/services/testutil"
)
// newTestService builds a standalone FineTuneService wired to the given bus. The
// model/config loaders are nil because the read/sync paths under test never touch
// them; the data dir is a throwaway temp dir so the disk Loader finds nothing.
func newTestService(bus *testutil.FakeBus) *FineTuneService {
appConfig := &config.ApplicationConfig{
Context: context.Background(),
DataPath: GinkgoT().TempDir(),
}
return NewFineTuneService(appConfig, nil, nil, bus, nil)
}
var _ = Describe("FineTuneService", func() {
ctx := context.Background()
Describe("cross-replica job visibility", func() {
var (
bus *testutil.FakeBus
a, b *FineTuneService
)
BeforeEach(func() {
// One shared bus, two replicas: exactly the distributed topology where
// a round-robin request may land on a replica that did not originate
// the change.
bus = testutil.NewFakeBus()
a = newTestService(bus)
b = newTestService(bus)
})
AfterEach(func() {
Expect(a.Close()).To(Succeed())
Expect(b.Close()).To(Succeed())
})
It("makes a job created on A visible via B's GetJob and ListJobs", func() {
job := &schema.FineTuneJob{ID: "job-1", UserID: "user-1", Status: "queued", CreatedAt: "2026-06-27T10:00:00Z"}
// StartJob persists via jobs.Set; drive that directly to avoid a backend.
Expect(a.jobs.Set(ctx, job)).To(Succeed())
got, err := b.GetJob("user-1", "job-1")
Expect(err).ToNot(HaveOccurred(), "B must see a job A just created")
Expect(got.Status).To(Equal("queued"))
listed := b.ListJobs("user-1")
Expect(listed).To(HaveLen(1))
Expect(listed[0].ID).To(Equal("job-1"))
})
It("removes a job from B when it is deleted on A", func() {
job := &schema.FineTuneJob{ID: "job-2", UserID: "user-1", Status: "completed", CreatedAt: "2026-06-27T10:00:00Z"}
Expect(a.jobs.Set(ctx, job)).To(Succeed())
_, err := b.GetJob("user-1", "job-2")
Expect(err).ToNot(HaveOccurred(), "precondition: B must have the job before the delete")
Expect(a.jobs.Delete(ctx, "job-2")).To(Succeed())
_, err = b.GetJob("user-1", "job-2")
Expect(err).To(HaveOccurred(), "a delete on A must remove the job from B")
})
It("propagates a status update from A to B", func() {
job := &schema.FineTuneJob{ID: "job-3", UserID: "user-1", Status: "training", CreatedAt: "2026-06-27T10:00:00Z"}
Expect(a.jobs.Set(ctx, job)).To(Succeed())
updated := &schema.FineTuneJob{ID: "job-3", UserID: "user-1", Status: "completed", CreatedAt: "2026-06-27T10:00:00Z"}
Expect(a.jobs.Set(ctx, updated)).To(Succeed())
got, err := b.GetJob("user-1", "job-3")
Expect(err).ToNot(HaveOccurred())
Expect(got.Status).To(Equal("completed"))
})
})
Describe("ListJobs", func() {
var svc *FineTuneService
BeforeEach(func() {
svc = newTestService(testutil.NewFakeBus())
})
AfterEach(func() { Expect(svc.Close()).To(Succeed()) })
It("filters by user and sorts newest-first", func() {
Expect(svc.jobs.Set(ctx, &schema.FineTuneJob{ID: "old", UserID: "u1", CreatedAt: "2026-06-25T10:00:00Z"})).To(Succeed())
Expect(svc.jobs.Set(ctx, &schema.FineTuneJob{ID: "new", UserID: "u1", CreatedAt: "2026-06-27T10:00:00Z"})).To(Succeed())
Expect(svc.jobs.Set(ctx, &schema.FineTuneJob{ID: "other", UserID: "u2", CreatedAt: "2026-06-26T10:00:00Z"})).To(Succeed())
jobs := svc.ListJobs("u1")
Expect(jobs).To(HaveLen(2), "only u1's jobs")
Expect(jobs[0].ID).To(Equal("new"), "newest first")
Expect(jobs[1].ID).To(Equal("old"))
})
It("returns every user's jobs when the userID filter is empty", func() {
Expect(svc.jobs.Set(ctx, &schema.FineTuneJob{ID: "a", UserID: "u1", CreatedAt: "2026-06-25T10:00:00Z"})).To(Succeed())
Expect(svc.jobs.Set(ctx, &schema.FineTuneJob{ID: "b", UserID: "u2", CreatedAt: "2026-06-26T10:00:00Z"})).To(Succeed())
Expect(svc.ListJobs("")).To(HaveLen(2))
})
It("rejects GetJob for a job owned by another user", func() {
Expect(svc.jobs.Set(ctx, &schema.FineTuneJob{ID: "x", UserID: "owner", CreatedAt: "2026-06-25T10:00:00Z"})).To(Succeed())
_, err := svc.GetJob("intruder", "x")
Expect(err).To(HaveOccurred(), "a different user must not read someone else's job")
})
})
Describe("store adapter conversion", func() {
// The SyncedMap value type is *schema.FineTuneJob (the exact REST shape).
// These specs prove the DB adapter round-trips it losslessly, so hydrate
// and write-through in distributed mode keep responses unchanged.
It("round-trips a job through jobToRecord/recordToJob preserving the API shape", func() {
original := &schema.FineTuneJob{
ID: "rt-1",
UserID: "user-1",
Model: "base-model",
Backend: "trl",
ModelID: "trl-finetune-rt-1",
TrainingType: "lora",
TrainingMethod: "sft",
Status: "completed",
Message: "done",
OutputDir: "/data/fine-tune/rt-1",
ExtraOptions: map[string]string{"hf_token": "secret"},
CreatedAt: "2026-06-27T10:00:00Z",
ExportStatus: "completed",
ExportMessage: "",
ExportModelName: "base-model-ft-rt-1",
Config: &schema.FineTuneJobRequest{Model: "base-model", Backend: "trl", DatasetSource: "data.jsonl"},
}
rec := jobToRecord(original)
Expect(rec.ID).To(Equal("rt-1"))
Expect(rec.ConfigJSON).ToNot(BeEmpty(), "structured config must serialize into the JSON column")
Expect(rec.ExtraOptsJSON).ToNot(BeEmpty())
back := recordToJob(rec)
Expect(back.ID).To(Equal(original.ID))
Expect(back.UserID).To(Equal(original.UserID))
Expect(back.Model).To(Equal(original.Model))
Expect(back.Backend).To(Equal(original.Backend))
Expect(back.ModelID).To(Equal(original.ModelID))
Expect(back.TrainingType).To(Equal(original.TrainingType))
Expect(back.TrainingMethod).To(Equal(original.TrainingMethod))
Expect(back.Status).To(Equal(original.Status))
Expect(back.Message).To(Equal(original.Message))
Expect(back.OutputDir).To(Equal(original.OutputDir))
Expect(back.ExportStatus).To(Equal(original.ExportStatus))
Expect(back.ExportModelName).To(Equal(original.ExportModelName))
Expect(back.CreatedAt).To(Equal(original.CreatedAt))
Expect(back.ExtraOptions).To(Equal(original.ExtraOptions))
Expect(back.Config).ToNot(BeNil())
Expect(back.Config.DatasetSource).To(Equal("data.jsonl"))
})
})
Describe("compile-time adapter contract", func() {
It("satisfies syncstate.Store for *distributed.FineTuneStore", func() {
// Guards against drift between the adapter and the component interface;
// the var assertion in syncstore.go covers it at build time, this keeps
// the type referenced from a spec too.
var _ *distributed.FineTuneStore
Expect(&fineTuneStoreAdapter{}).ToNot(BeNil())
})
})
})

View File

@@ -0,0 +1,114 @@
package finetune
import (
"context"
"encoding/json"
"time"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/distributed"
"github.com/mudler/LocalAI/core/services/syncstate"
)
// fineTuneStoreAdapter bridges the distributed PostgreSQL FineTuneStore to the
// generic syncstate.Store the SyncedMap consumes. It is only wired in distributed
// mode; standalone leaves Store nil and hydrates from disk via a Loader instead.
//
// The SyncedMap value type is *schema.FineTuneJob (the exact shape the REST API
// returns) so reads need no conversion and the response JSON is provably
// unchanged. The adapter is the single place that translates between that API
// shape and the DB FineTuneJobRecord.
type fineTuneStoreAdapter struct {
store *distributed.FineTuneStore
}
// compile-time assertion that the adapter satisfies the component's Store.
var _ syncstate.Store[string, *schema.FineTuneJob] = (*fineTuneStoreAdapter)(nil)
func (a *fineTuneStoreAdapter) List(_ context.Context) ([]*schema.FineTuneJob, error) {
records, err := a.store.ListAll()
if err != nil {
return nil, err
}
jobs := make([]*schema.FineTuneJob, 0, len(records))
for i := range records {
jobs = append(jobs, recordToJob(&records[i]))
}
return jobs, nil
}
func (a *fineTuneStoreAdapter) Upsert(_ context.Context, job *schema.FineTuneJob) error {
return a.store.Upsert(jobToRecord(job))
}
func (a *fineTuneStoreAdapter) Delete(_ context.Context, id string) error {
return a.store.Delete(id)
}
// recordToJob maps a persisted DB record back to the API shape, reconstructing
// the structured Config / ExtraOptions from their JSON columns.
func recordToJob(r *distributed.FineTuneJobRecord) *schema.FineTuneJob {
job := &schema.FineTuneJob{
ID: r.ID,
UserID: r.UserID,
Model: r.Model,
Backend: r.Backend,
ModelID: r.ModelID,
TrainingType: r.TrainingType,
TrainingMethod: r.TrainingMethod,
Status: r.Status,
Message: r.Message,
OutputDir: r.OutputDir,
ExportStatus: r.ExportStatus,
ExportMessage: r.ExportMessage,
ExportModelName: r.ExportModelName,
CreatedAt: r.CreatedAt.UTC().Format(time.RFC3339),
}
if r.ExtraOptsJSON != "" {
// Best-effort: a malformed column must not drop the whole job from the API.
_ = json.Unmarshal([]byte(r.ExtraOptsJSON), &job.ExtraOptions)
}
if r.ConfigJSON != "" {
var cfg schema.FineTuneJobRequest
if err := json.Unmarshal([]byte(r.ConfigJSON), &cfg); err == nil {
job.Config = &cfg
}
}
return job
}
// jobToRecord maps the API shape to a DB record for write-through, serializing
// the structured Config / ExtraOptions into their JSON columns. CreatedAt is
// parsed back from the RFC3339 string the service stamps; an unparseable value
// is left zero so FineTuneStore.Upsert stamps "now".
func jobToRecord(job *schema.FineTuneJob) *distributed.FineTuneJobRecord {
rec := &distributed.FineTuneJobRecord{
ID: job.ID,
UserID: job.UserID,
Model: job.Model,
Backend: job.Backend,
ModelID: job.ModelID,
TrainingType: job.TrainingType,
TrainingMethod: job.TrainingMethod,
Status: job.Status,
Message: job.Message,
OutputDir: job.OutputDir,
ExportStatus: job.ExportStatus,
ExportMessage: job.ExportMessage,
ExportModelName: job.ExportModelName,
}
if job.Config != nil {
if data, err := json.Marshal(job.Config); err == nil {
rec.ConfigJSON = string(data)
}
}
if job.ExtraOptions != nil {
if data, err := json.Marshal(job.ExtraOptions); err == nil {
rec.ExtraOptsJSON = string(data)
}
}
if t, err := time.Parse(time.RFC3339, job.CreatedAt); err == nil {
rec.CreatedAt = t
}
return rec
}

View File

@@ -22,6 +22,14 @@ const subscribeConfirmTimeout = 5 * time.Second
type Client struct {
conn *nats.Conn
mu sync.RWMutex
// reconnectCbs are invoked after the underlying connection is
// re-established. nats.go transparently resubscribes existing
// subscriptions on reconnect, but it cannot know that a consumer kept
// derived in-memory state (e.g. syncstate.SyncedMap) that may have drifted
// while the link was down — these callbacks let such consumers re-hydrate.
cbMu sync.Mutex
reconnectCbs []func()
}
// New creates a new NATS client with auto-reconnect.
@@ -31,6 +39,10 @@ func New(url string, opts ...Option) (*Client, error) {
o(&cfg)
}
// Allocate the client up front so the reconnect handler closure can reach
// it; conn is populated after nats.Connect succeeds below.
c := &Client{}
natsOpts := []nats.Option{
nats.RetryOnFailedConnect(true),
nats.MaxReconnects(-1),
@@ -41,6 +53,7 @@ func New(url string, opts ...Option) (*Client, error) {
}),
nats.ReconnectHandler(func(_ *nats.Conn) {
xlog.Info("NATS reconnected")
c.runReconnectCallbacks()
}),
nats.ClosedHandler(func(_ *nats.Conn) {
xlog.Info("NATS connection closed")
@@ -103,7 +116,33 @@ func New(url string, opts ...Option) (*Client, error) {
return nil, fmt.Errorf("connecting to NATS at %s: %w", sanitize.URL(url), err)
}
return &Client{conn: nc}, nil
c.conn = nc
return c, nil
}
// OnReconnect registers a callback invoked after the NATS connection is
// re-established. It is consumed via an optional interface type-assertion
// (interface{ OnReconnect(func()) }) rather than being added to MessagingClient,
// so the messaging abstraction stays minimal and standalone/test clients are not
// forced to implement reconnect semantics. A nil callback is ignored.
func (c *Client) OnReconnect(cb func()) {
if cb == nil {
return
}
c.cbMu.Lock()
c.reconnectCbs = append(c.reconnectCbs, cb)
c.cbMu.Unlock()
}
// runReconnectCallbacks invokes registered reconnect callbacks. It copies the
// slice under the lock so a callback that (re)registers cannot deadlock.
func (c *Client) runReconnectCallbacks() {
c.cbMu.Lock()
cbs := append([]func(){}, c.reconnectCbs...)
c.cbMu.Unlock()
for _, cb := range cbs {
cb()
}
}
// Publish marshals data as JSON and publishes it to the given subject.

View File

@@ -380,6 +380,20 @@ func SubjectCacheInvalidateCollection(name string) string {
return "cache.invalidate.collections." + sanitizeSubjectToken(name)
}
// SyncedMap State Sync (Pub/Sub — broadcast to all frontends)
//
// The reusable syncstate.SyncedMap component publishes a {op,key,value} delta on
// this subject whenever a replica mutates a piece of cross-replica in-memory
// state. Peers subscribe and apply the delta to their own map, so a round-robin
// API request that lands on a replica which did not originate the change still
// sees it. Convergence on (re)connect is done by re-hydrating from the durable
// source, so no request/reply snapshot subject is needed here.
func SubjectSyncStateDelta(name string) string {
return subjectSyncStatePrefix + sanitizeSubjectToken(name) + ".delta"
}
const subjectSyncStatePrefix = "state."
// Prefix-Cache Routing Sync (Pub/Sub - broadcast to all frontends)
//
// Frontends share prefix-cache observations so a request routed to any replica

View File

@@ -63,6 +63,11 @@ type SmartRouterOptions struct {
// The reconciler reads the same instance to autoscale a saturated cache-warm
// replica. nil disables recording (the disabled path stays a no-op).
Pressure *prefixcache.Pressure
// SharedModels asserts that every node mounts the same models directory at
// the same path. When true, stageModelFiles skips all uploading and leaves
// the absolute model paths untouched so the worker loads them directly from
// the shared volume (#10556). See config.DistributedConfig.SharedModels.
SharedModels bool
}
// SmartRouter routes inference requests to the best available backend node.
@@ -93,6 +98,9 @@ type SmartRouter struct {
// per-request routing doesn't stall behind a busy backend's serialized
// HealthCheck/Predict. See probe_cache.go for the rationale.
probeCache *probeCache
// sharedModels skips file staging when all nodes mount the same models
// directory at the same path (see SmartRouterOptions.SharedModels).
sharedModels bool
}
// probeCacheTTL is how long a successful gRPC HealthCheck on a backend is
@@ -122,6 +130,7 @@ func NewSmartRouter(registry ModelRouter, opts SmartRouterOptions) *SmartRouter
prefixProvider: opts.PrefixProvider,
prefixConfig: opts.PrefixConfig,
pressure: opts.Pressure,
sharedModels: opts.SharedModels,
}
}
@@ -947,6 +956,19 @@ func (r *SmartRouter) buildClientForAddr(node *BackendNode, addr string, paralle
// simply remove the {ModelsPath}/{trackingKey}/ directory.
func (r *SmartRouter) stageModelFiles(ctx context.Context, node *BackendNode, opts *pb.ModelOptions, trackingKey string) (*pb.ModelOptions, error) {
opts = proto.Clone(opts).(*pb.ModelOptions)
// Shared-models mode: every node mounts the same models directory at the
// same path, so the frontend's absolute model paths are already valid on the
// worker. Staging would only re-upload files that already exist on the shared
// volume (under a tracking-key subdir the probe never reuses), re-downloading
// the model on every load (#10556). Return the clone untouched: no upload, no
// path rewrite, no staging tracker.
if r.sharedModels {
xlog.Info("Skipping model file staging: shared-models mode is on (LOCALAI_DISTRIBUTED_SHARED_MODELS); worker loads directly from the shared volume",
"node", node.Name, "modelFile", opts.ModelFile, "trackingKey", trackingKey)
return opts, nil
}
xlog.Info("Staging model files for remote node", "node", node.Name, "modelFile", opts.ModelFile, "trackingKey", trackingKey)
// Derive the frontend models directory from ModelFile and Model.

View File

@@ -0,0 +1,85 @@
package nodes
import (
"context"
"os"
"path/filepath"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
// These tests cover shared-models mode (LOCALAI_DISTRIBUTED_SHARED_MODELS): when
// every node mounts the same models directory at the same path, the router must
// NOT stage model files to workers. The canonical absolute path is already valid
// on the worker, so staging would only re-download what is already present
// (#10556).
var _ = Describe("stageModelFiles shared-models mode", func() {
var (
stager *fakeFileStager
node *BackendNode
tmp string
gguf string
modelID = "ornith-1.0-35b"
)
BeforeEach(func() {
stager = &fakeFileStager{}
node = &BackendNode{ID: "node-1", Name: "node-1", Address: "10.0.0.1:50051"}
tmp = GinkgoT().TempDir()
modelDir := filepath.Join(tmp, "models", "llama-cpp", "models")
Expect(os.MkdirAll(modelDir, 0o755)).To(Succeed())
gguf = filepath.Join(modelDir, "ornith.gguf")
Expect(os.WriteFile(gguf, []byte("weights"), 0o644)).To(Succeed())
})
It("does not stage and keeps the canonical absolute ModelFile when shared-models is enabled", func() {
router := &SmartRouter{
fileStager: stager,
stagingTracker: NewStagingTracker(),
sharedModels: true,
}
opts := &pb.ModelOptions{
Model: "llama-cpp/models/ornith.gguf",
ModelFile: gguf,
}
staged, err := router.stageModelFiles(context.Background(), node, opts, modelID)
Expect(err).ToNot(HaveOccurred())
// The file stager must never be touched: no upload, no re-download.
Expect(stager.ensureCalls).To(BeEmpty())
// The worker loads directly from the shared volume, so the path is unchanged.
Expect(staged.ModelFile).To(Equal(gguf))
})
It("stages files (existing behavior) when shared-models is disabled", func() {
router := &SmartRouter{
fileStager: stager,
stagingTracker: NewStagingTracker(),
sharedModels: false,
}
opts := &pb.ModelOptions{
Model: "llama-cpp/models/ornith.gguf",
ModelFile: gguf,
}
staged, err := router.stageModelFiles(context.Background(), node, opts, modelID)
Expect(err).ToNot(HaveOccurred())
// Default mode uploads the model file to the worker.
Expect(stager.ensureCalls).ToNot(BeEmpty())
stagedLocals := make([]string, 0, len(stager.ensureCalls))
for _, c := range stager.ensureCalls {
stagedLocals = append(stagedLocals, c.localPath)
}
Expect(stagedLocals).To(ContainElement(gguf))
// ModelFile is rewritten to the remote (tracking-key namespaced) path.
Expect(staged.ModelFile).ToNot(Equal(gguf))
})
})

View File

@@ -0,0 +1,13 @@
package quantization
import (
"testing"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestQuantization(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "Quantization Suite")
}

View File

@@ -17,6 +17,9 @@ import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/gallery/importers"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/distributed"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/LocalAI/core/services/syncstate"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/utils"
@@ -30,26 +33,63 @@ type QuantizationService struct {
modelLoader *model.ModelLoader
configLoader *config.ModelConfigLoader
mu sync.Mutex
jobs map[string]*schema.QuantizationJob
// mu serializes the read-modify-write of job values. The SyncedMap guards its
// own map structure, but a job is a pointer mutated in place (e.g. the import
// goroutine), so the service still needs a lock to keep those field updates and
// the subsequent Set atomic with respect to readers.
mu sync.Mutex
// jobs is the cross-replica job store: an in-memory map kept consistent across
// replicas via NATS, optionally read-through to PostgreSQL in distributed mode.
jobs *syncstate.SyncedMap[string, *schema.QuantizationJob]
}
// NewQuantizationService creates a new QuantizationService.
// NewQuantizationService creates a new QuantizationService. In distributed mode
// pass the shared NATS client and PostgreSQL store so jobs stay consistent across
// replicas; pass nil for both in standalone mode, where the disk Loader hydrates
// the map and there is nothing to broadcast.
func NewQuantizationService(
appConfig *config.ApplicationConfig,
modelLoader *model.ModelLoader,
configLoader *config.ModelConfigLoader,
nats messaging.MessagingClient,
store *distributed.QuantStore,
) *QuantizationService {
s := &QuantizationService{
appConfig: appConfig,
modelLoader: modelLoader,
configLoader: configLoader,
jobs: make(map[string]*schema.QuantizationJob),
}
s.loadAllJobs()
// Only attach a Store interface when a concrete store exists, otherwise the
// SyncedMap would see a non-nil interface wrapping a nil pointer and try to
// hydrate/write through a nil DB.
var syncStore syncstate.Store[string, *schema.QuantizationJob]
if store != nil {
syncStore = &quantStoreAdapter{store: store}
}
s.jobs = syncstate.New(syncstate.Config[string, *schema.QuantizationJob]{
Name: "quant.jobs",
Key: func(j *schema.QuantizationJob) string { return j.ID },
Nats: nats,
Store: syncStore,
Loader: s.loadJobsFromDisk, // ignored when Store is set (distributed mode)
})
// Hydrate + subscribe. A hydrate failure must not take the server down: log and
// continue degraded (standalone), mirroring the FineTune/OpCache wiring.
if err := s.jobs.Start(appConfig.Context); err != nil {
xlog.Warn("Quantization SyncedMap start failed; running degraded", "error", err)
}
return s
}
// Close releases the SyncedMap subscription and background workers.
func (s *QuantizationService) Close() error {
return s.jobs.Close()
}
// quantizationBaseDir returns the base directory for quantization job data.
func (s *QuantizationService) quantizationBaseDir() string {
return filepath.Join(s.appConfig.DataPath, "quantization")
@@ -80,15 +120,18 @@ func (s *QuantizationService) saveJobState(job *schema.QuantizationJob) {
}
}
// loadAllJobs scans the quantization directory for persisted jobs and loads them.
func (s *QuantizationService) loadAllJobs() {
// loadJobsFromDisk scans the quantization directory for persisted jobs and
// returns them. It is the SyncedMap Loader used in standalone mode (no DB); the
// returned slice hydrates the map on Start.
func (s *QuantizationService) loadJobsFromDisk(_ context.Context) ([]*schema.QuantizationJob, error) {
baseDir := s.quantizationBaseDir()
entries, err := os.ReadDir(baseDir)
if err != nil {
// Directory doesn't exist yet — that's fine
return
// Directory doesn't exist yet — that's fine, start empty.
return nil, nil
}
var jobs []*schema.QuantizationJob
for _, entry := range entries {
if !entry.IsDir() {
continue
@@ -117,12 +160,13 @@ func (s *QuantizationService) loadAllJobs() {
job.ImportMessage = "Server restarted while import was running"
}
s.jobs[job.ID] = &job
jobs = append(jobs, &job)
}
if len(s.jobs) > 0 {
xlog.Info("Loaded persisted quantization jobs", "count", len(s.jobs))
if len(jobs) > 0 {
xlog.Info("Loaded persisted quantization jobs", "count", len(jobs))
}
return jobs, nil
}
// StartJob starts a new quantization job.
@@ -188,7 +232,12 @@ func (s *QuantizationService) StartJob(ctx context.Context, userID string, req s
CreatedAt: time.Now().UTC().Format(time.RFC3339),
Config: &req,
}
s.jobs[jobID] = job
// Set write-through persists to PostgreSQL (distributed) and broadcasts to
// peer replicas; the disk state.json is written separately for restart
// recovery / standalone hydrate.
if err := s.jobs.Set(ctx, job); err != nil {
return nil, fmt.Errorf("failed to persist job: %w", err)
}
s.saveJobState(job)
return &schema.QuantizationJobResponse{
@@ -203,7 +252,7 @@ func (s *QuantizationService) GetJob(userID, jobID string) (*schema.Quantization
s.mu.Lock()
defer s.mu.Unlock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
return nil, fmt.Errorf("job not found: %s", jobID)
}
@@ -219,7 +268,7 @@ func (s *QuantizationService) ListJobs(userID string) []*schema.QuantizationJob
defer s.mu.Unlock()
var result []*schema.QuantizationJob
for _, job := range s.jobs {
for _, job := range s.jobs.List() {
if userID == "" || job.UserID == userID {
result = append(result, job)
}
@@ -235,7 +284,7 @@ func (s *QuantizationService) ListJobs(userID string) []*schema.QuantizationJob
// StopJob stops a running quantization job.
func (s *QuantizationService) StopJob(ctx context.Context, userID, jobID string) error {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return fmt.Errorf("job not found: %s", jobID)
@@ -256,6 +305,9 @@ func (s *QuantizationService) StopJob(ctx context.Context, userID, jobID string)
s.mu.Lock()
job.Status = "stopped"
job.Message = "Quantization stopped by user"
if err := s.jobs.Set(ctx, job); err != nil {
xlog.Warn("Failed to persist stopped job", "job_id", jobID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
@@ -265,7 +317,7 @@ func (s *QuantizationService) StopJob(ctx context.Context, userID, jobID string)
// DeleteJob removes a quantization job and its associated data from disk.
func (s *QuantizationService) DeleteJob(userID, jobID string) error {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return fmt.Errorf("job not found: %s", jobID)
@@ -289,7 +341,11 @@ func (s *QuantizationService) DeleteJob(userID, jobID string) error {
}
importModelName := job.ImportModelName
delete(s.jobs, jobID)
// Delete write-through removes the DB row (distributed) and broadcasts the
// removal to peer replicas. DeleteJob has no ctx, so use Background.
if err := s.jobs.Delete(context.Background(), jobID); err != nil {
xlog.Warn("Failed to delete job from store", "job_id", jobID, "error", err)
}
s.mu.Unlock()
// Remove job directory (state.json, output files)
@@ -324,7 +380,7 @@ func (s *QuantizationService) DeleteJob(userID, jobID string) error {
// StreamProgress opens a gRPC progress stream and calls the callback for each update.
func (s *QuantizationService) StreamProgress(ctx context.Context, userID, jobID string, callback func(event *schema.QuantizationProgressEvent)) error {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return fmt.Errorf("job not found: %s", jobID)
@@ -353,7 +409,7 @@ func (s *QuantizationService) StreamProgress(ctx context.Context, userID, jobID
}, func(update *pb.QuantizationProgressUpdate) {
// Update job status and persist
s.mu.Lock()
if j, ok := s.jobs[jobID]; ok {
if j, ok := s.jobs.Get(jobID); ok {
// Don't let progress updates overwrite terminal states
isTerminal := j.Status == "stopped" || j.Status == "completed" || j.Status == "failed"
if !isTerminal {
@@ -365,6 +421,9 @@ func (s *QuantizationService) StreamProgress(ctx context.Context, userID, jobID
if update.OutputFile != "" {
j.OutputFile = update.OutputFile
}
if err := s.jobs.Set(ctx, j); err != nil {
xlog.Warn("Failed to persist progress update", "job_id", jobID, "error", err)
}
s.saveJobState(j)
}
s.mu.Unlock()
@@ -399,7 +458,7 @@ func sanitizeQuantModelName(s string) string {
// ImportModel imports a quantized model into LocalAI asynchronously.
func (s *QuantizationService) ImportModel(ctx context.Context, userID, jobID string, req schema.QuantizationImportRequest) (string, error) {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return "", fmt.Errorf("job not found: %s", jobID)
@@ -459,6 +518,9 @@ func (s *QuantizationService) ImportModel(ctx context.Context, userID, jobID str
job.ImportStatus = "importing"
job.ImportMessage = ""
job.ImportModelName = ""
if err := s.jobs.Set(ctx, job); err != nil {
xlog.Warn("Failed to persist import start", "job_id", jobID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
@@ -514,10 +576,15 @@ func (s *QuantizationService) ImportModel(ctx context.Context, userID, jobID str
xlog.Info("Quantized model imported and registered", "job_id", jobID, "model_name", modelName)
// Runs after the HTTP request returns, so use Background rather than the
// (now likely cancelled) request ctx for the write-through.
s.mu.Lock()
job.ImportStatus = "completed"
job.ImportModelName = modelName
job.ImportMessage = ""
if err := s.jobs.Set(context.Background(), job); err != nil {
xlog.Warn("Failed to persist import completion", "job_id", jobID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
}()
@@ -525,10 +592,14 @@ func (s *QuantizationService) ImportModel(ctx context.Context, userID, jobID str
return modelName, nil
}
// setImportMessage updates the import message and persists the job state.
// setImportMessage updates the import message and persists the job state. Called
// from the background import goroutine, so it uses Background for write-through.
func (s *QuantizationService) setImportMessage(job *schema.QuantizationJob, msg string) {
s.mu.Lock()
job.ImportMessage = msg
if err := s.jobs.Set(context.Background(), job); err != nil {
xlog.Warn("Failed to persist import message", "job_id", job.ID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
}
@@ -539,6 +610,9 @@ func (s *QuantizationService) setImportFailed(job *schema.QuantizationJob, messa
s.mu.Lock()
job.ImportStatus = "failed"
job.ImportMessage = message
if err := s.jobs.Set(context.Background(), job); err != nil {
xlog.Warn("Failed to persist import failure", "job_id", job.ID, "error", err)
}
s.saveJobState(job)
s.mu.Unlock()
}
@@ -546,7 +620,7 @@ func (s *QuantizationService) setImportFailed(job *schema.QuantizationJob, messa
// GetOutputPath returns the path to the quantized model file and a download name.
func (s *QuantizationService) GetOutputPath(userID, jobID string) (string, string, error) {
s.mu.Lock()
job, ok := s.jobs[jobID]
job, ok := s.jobs.Get(jobID)
if !ok {
s.mu.Unlock()
return "", "", fmt.Errorf("job not found: %s", jobID)

View File

@@ -0,0 +1,187 @@
package quantization
// White-box tests (package quantization) so a spec can drive the service's
// internal SyncedMap the same way StartJob does (via jobs.Set) without standing
// up a quantization backend, then assert the cross-replica reads
// (GetJob/ListJobs) and the adapter conversions that keep REST responses
// byte-for-byte unchanged.
import (
"context"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/distributed"
"github.com/mudler/LocalAI/core/services/testutil"
)
// newTestService builds a standalone QuantizationService wired to the given bus.
// The model/config loaders are nil because the read/sync paths under test never
// touch them; the data dir is a throwaway temp dir so the disk Loader finds
// nothing.
func newTestService(bus *testutil.FakeBus) *QuantizationService {
appConfig := &config.ApplicationConfig{
Context: context.Background(),
DataPath: GinkgoT().TempDir(),
}
return NewQuantizationService(appConfig, nil, nil, bus, nil)
}
var _ = Describe("QuantizationService", func() {
ctx := context.Background()
Describe("cross-replica job visibility", func() {
var (
bus *testutil.FakeBus
a, b *QuantizationService
)
BeforeEach(func() {
// One shared bus, two replicas: exactly the distributed topology where a
// round-robin request may land on a replica that did not originate the
// change.
bus = testutil.NewFakeBus()
a = newTestService(bus)
b = newTestService(bus)
})
AfterEach(func() {
Expect(a.Close()).To(Succeed())
Expect(b.Close()).To(Succeed())
})
It("makes a job created on A visible via B's GetJob and ListJobs", func() {
job := &schema.QuantizationJob{ID: "job-1", UserID: "user-1", Status: "queued", CreatedAt: "2026-06-27T10:00:00Z"}
// StartJob persists via jobs.Set; drive that directly to avoid a backend.
Expect(a.jobs.Set(ctx, job)).To(Succeed())
got, err := b.GetJob("user-1", "job-1")
Expect(err).ToNot(HaveOccurred(), "B must see a job A just created")
Expect(got.Status).To(Equal("queued"))
listed := b.ListJobs("user-1")
Expect(listed).To(HaveLen(1))
Expect(listed[0].ID).To(Equal("job-1"))
})
It("removes a job from B when it is deleted on A", func() {
job := &schema.QuantizationJob{ID: "job-2", UserID: "user-1", Status: "completed", CreatedAt: "2026-06-27T10:00:00Z"}
Expect(a.jobs.Set(ctx, job)).To(Succeed())
_, err := b.GetJob("user-1", "job-2")
Expect(err).ToNot(HaveOccurred(), "precondition: B must have the job before the delete")
Expect(a.jobs.Delete(ctx, "job-2")).To(Succeed())
_, err = b.GetJob("user-1", "job-2")
Expect(err).To(HaveOccurred(), "a delete on A must remove the job from B")
})
It("propagates a status update from A to B", func() {
job := &schema.QuantizationJob{ID: "job-3", UserID: "user-1", Status: "quantizing", CreatedAt: "2026-06-27T10:00:00Z"}
Expect(a.jobs.Set(ctx, job)).To(Succeed())
updated := &schema.QuantizationJob{ID: "job-3", UserID: "user-1", Status: "completed", CreatedAt: "2026-06-27T10:00:00Z"}
Expect(a.jobs.Set(ctx, updated)).To(Succeed())
got, err := b.GetJob("user-1", "job-3")
Expect(err).ToNot(HaveOccurred())
Expect(got.Status).To(Equal("completed"))
})
})
Describe("ListJobs", func() {
var svc *QuantizationService
BeforeEach(func() {
svc = newTestService(testutil.NewFakeBus())
})
AfterEach(func() { Expect(svc.Close()).To(Succeed()) })
It("filters by user and sorts newest-first", func() {
Expect(svc.jobs.Set(ctx, &schema.QuantizationJob{ID: "old", UserID: "u1", CreatedAt: "2026-06-25T10:00:00Z"})).To(Succeed())
Expect(svc.jobs.Set(ctx, &schema.QuantizationJob{ID: "new", UserID: "u1", CreatedAt: "2026-06-27T10:00:00Z"})).To(Succeed())
Expect(svc.jobs.Set(ctx, &schema.QuantizationJob{ID: "other", UserID: "u2", CreatedAt: "2026-06-26T10:00:00Z"})).To(Succeed())
jobs := svc.ListJobs("u1")
Expect(jobs).To(HaveLen(2), "only u1's jobs")
Expect(jobs[0].ID).To(Equal("new"), "newest first")
Expect(jobs[1].ID).To(Equal("old"))
})
It("returns every user's jobs when the userID filter is empty", func() {
Expect(svc.jobs.Set(ctx, &schema.QuantizationJob{ID: "a", UserID: "u1", CreatedAt: "2026-06-25T10:00:00Z"})).To(Succeed())
Expect(svc.jobs.Set(ctx, &schema.QuantizationJob{ID: "b", UserID: "u2", CreatedAt: "2026-06-26T10:00:00Z"})).To(Succeed())
Expect(svc.ListJobs("")).To(HaveLen(2))
})
It("rejects GetJob for a job owned by another user", func() {
Expect(svc.jobs.Set(ctx, &schema.QuantizationJob{ID: "x", UserID: "owner", CreatedAt: "2026-06-25T10:00:00Z"})).To(Succeed())
_, err := svc.GetJob("intruder", "x")
Expect(err).To(HaveOccurred(), "a different user must not read someone else's job")
})
})
Describe("store adapter conversion", func() {
// The SyncedMap value type is *schema.QuantizationJob (the exact REST shape).
// These specs prove the DB adapter round-trips it losslessly, so hydrate and
// write-through in distributed mode keep responses unchanged.
It("round-trips a job through jobToRecord/recordToJob preserving the API shape", func() {
original := &schema.QuantizationJob{
ID: "rt-1",
UserID: "user-1",
Model: "base-model",
Backend: "llama-cpp-quantization",
ModelID: "llama-cpp-quantization-quantize-rt-1",
QuantizationType: "q4_k_m",
Status: "completed",
Message: "done",
OutputDir: "/data/quantization/rt-1",
OutputFile: "/data/quantization/rt-1/model.gguf",
ExtraOptions: map[string]string{"hf_token": "secret"},
CreatedAt: "2026-06-27T10:00:00Z",
ImportStatus: "completed",
ImportMessage: "",
ImportModelName: "base-model-q4_k_m-rt-1",
Config: &schema.QuantizationJobRequest{Model: "base-model", Backend: "llama-cpp-quantization", QuantizationType: "q4_k_m"},
}
rec := jobToRecord(original)
Expect(rec.ID).To(Equal("rt-1"))
Expect(rec.ConfigJSON).ToNot(BeEmpty(), "structured config must serialize into the JSON column")
Expect(rec.ExtraOptsJSON).ToNot(BeEmpty())
back := recordToJob(rec)
Expect(back.ID).To(Equal(original.ID))
Expect(back.UserID).To(Equal(original.UserID))
Expect(back.Model).To(Equal(original.Model))
Expect(back.Backend).To(Equal(original.Backend))
Expect(back.ModelID).To(Equal(original.ModelID))
Expect(back.QuantizationType).To(Equal(original.QuantizationType))
Expect(back.Status).To(Equal(original.Status))
Expect(back.Message).To(Equal(original.Message))
Expect(back.OutputDir).To(Equal(original.OutputDir))
Expect(back.OutputFile).To(Equal(original.OutputFile))
Expect(back.ImportStatus).To(Equal(original.ImportStatus))
Expect(back.ImportModelName).To(Equal(original.ImportModelName))
Expect(back.CreatedAt).To(Equal(original.CreatedAt))
Expect(back.ExtraOptions).To(Equal(original.ExtraOptions))
Expect(back.Config).ToNot(BeNil())
Expect(back.Config.QuantizationType).To(Equal("q4_k_m"))
})
})
Describe("compile-time adapter contract", func() {
It("satisfies syncstate.Store for *distributed.QuantStore", func() {
// Guards against drift between the adapter and the component interface;
// the var assertion in syncstore.go covers it at build time, this keeps
// the type referenced from a spec too.
var _ *distributed.QuantStore
Expect(&quantStoreAdapter{}).ToNot(BeNil())
})
})
})

View File

@@ -0,0 +1,114 @@
package quantization
import (
"context"
"encoding/json"
"time"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services/distributed"
"github.com/mudler/LocalAI/core/services/syncstate"
)
// quantStoreAdapter bridges the distributed PostgreSQL QuantStore to the generic
// syncstate.Store the SyncedMap consumes. It is only wired in distributed mode;
// standalone leaves Store nil and hydrates from disk via a Loader instead.
//
// The SyncedMap value type is *schema.QuantizationJob (the exact shape the REST
// API returns) so reads need no conversion and the response JSON is provably
// unchanged. The adapter is the single place that translates between that API
// shape and the DB QuantJobRecord.
type quantStoreAdapter struct {
store *distributed.QuantStore
}
// compile-time assertion that the adapter satisfies the component's Store.
var _ syncstate.Store[string, *schema.QuantizationJob] = (*quantStoreAdapter)(nil)
func (a *quantStoreAdapter) List(_ context.Context) ([]*schema.QuantizationJob, error) {
records, err := a.store.ListAll()
if err != nil {
return nil, err
}
jobs := make([]*schema.QuantizationJob, 0, len(records))
for i := range records {
jobs = append(jobs, recordToJob(&records[i]))
}
return jobs, nil
}
func (a *quantStoreAdapter) Upsert(_ context.Context, job *schema.QuantizationJob) error {
return a.store.Upsert(jobToRecord(job))
}
func (a *quantStoreAdapter) Delete(_ context.Context, id string) error {
return a.store.Delete(id)
}
// recordToJob maps a persisted DB record back to the API shape, reconstructing
// the structured Config / ExtraOptions from their JSON columns.
func recordToJob(r *distributed.QuantJobRecord) *schema.QuantizationJob {
job := &schema.QuantizationJob{
ID: r.ID,
UserID: r.UserID,
Model: r.Model,
Backend: r.Backend,
ModelID: r.ModelID,
QuantizationType: r.QuantizationType,
Status: r.Status,
Message: r.Message,
OutputDir: r.OutputDir,
OutputFile: r.OutputFile,
ImportStatus: r.ImportStatus,
ImportMessage: r.ImportMessage,
ImportModelName: r.ImportModelName,
CreatedAt: r.CreatedAt.UTC().Format(time.RFC3339),
}
if r.ExtraOptsJSON != "" {
// Best-effort: a malformed column must not drop the whole job from the API.
_ = json.Unmarshal([]byte(r.ExtraOptsJSON), &job.ExtraOptions)
}
if r.ConfigJSON != "" {
var cfg schema.QuantizationJobRequest
if err := json.Unmarshal([]byte(r.ConfigJSON), &cfg); err == nil {
job.Config = &cfg
}
}
return job
}
// jobToRecord maps the API shape to a DB record for write-through, serializing
// the structured Config / ExtraOptions into their JSON columns. CreatedAt is
// parsed back from the RFC3339 string the service stamps; an unparseable value is
// left zero so QuantStore.Upsert stamps "now".
func jobToRecord(job *schema.QuantizationJob) *distributed.QuantJobRecord {
rec := &distributed.QuantJobRecord{
ID: job.ID,
UserID: job.UserID,
Model: job.Model,
Backend: job.Backend,
ModelID: job.ModelID,
QuantizationType: job.QuantizationType,
Status: job.Status,
Message: job.Message,
OutputDir: job.OutputDir,
OutputFile: job.OutputFile,
ImportStatus: job.ImportStatus,
ImportMessage: job.ImportMessage,
ImportModelName: job.ImportModelName,
}
if job.Config != nil {
if data, err := json.Marshal(job.Config); err == nil {
rec.ConfigJSON = string(data)
}
}
if job.ExtraOptions != nil {
if data, err := json.Marshal(job.ExtraOptions); err == nil {
rec.ExtraOptsJSON = string(data)
}
}
if t, err := time.Parse(time.RFC3339, job.CreatedAt); err == nil {
rec.CreatedAt = t
}
return rec
}

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// Package syncstate provides SyncedMap, a reusable cross-replica in-memory map.
//
// LocalAI in distributed mode runs multiple frontend replicas behind a
// round-robin load balancer. Several features keep process-local in-memory state
// that is surfaced to the HTTP/UI API; without cross-replica sync a poll that
// lands on a replica which did not originate a change sees stale or missing data.
// SyncedMap collapses the three legs each feature otherwise hand-wires - an
// in-memory map, a NATS broadcast/apply path, and optional durable read-through -
// into one well-tested component so cross-replica consistency is a configuration
// choice rather than a bespoke re-implementation.
package syncstate
import (
"context"
"sync"
"time"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/xlog"
)
// Op values carried on the wire and passed to OnApply.
const (
opSet = "set"
opDelete = "delete"
)
// Store is optional durable backing for a SyncedMap. In distributed mode it is a
// single shared DB, so the apply path (a delta received from a peer) updates
// memory only and never re-writes the Store.
type Store[K comparable, V any] interface {
List(ctx context.Context) ([]V, error)
Upsert(ctx context.Context, v V) error
Delete(ctx context.Context, k K) error
}
// Config configures a SyncedMap.
type Config[K comparable, V any] struct {
Name string // subject namespace, e.g. "finetune.jobs"
Key func(V) K // extract the key from a value
Nats messaging.MessagingClient // nil => standalone: in-memory only, no broadcast/subscribe
Store Store[K, V] // optional read-through persistence
Loader func(ctx context.Context) ([]V, error) // source when there is no Store (e.g. disk reload)
OnApply func(op string, k K, v V) // optional hook after an applied change (e.g. ShutdownModel)
Reconcile time.Duration // optional periodic re-hydrate; 0 = off
}
// delta is the JSON wire envelope broadcast on every local mutation. Value is
// omitempty so a delete carries only op+key.
type delta[K comparable, V any] struct {
Op string `json:"op"`
Key K `json:"key"`
Value V `json:"value,omitempty"`
}
// SyncedMap is a cross-replica in-memory map. A local write (Set/Delete) updates
// memory, the optional durable Store, then broadcasts a delta to peers. A peer's
// delta updates memory only and fires OnApply - it never re-broadcasts and never
// writes the Store. That structural split is the echo-loop guard (same pattern as
// galleryop.mergeStatus / OpCache.applyStart): receiving your own broadcast just
// re-applies an idempotent value to memory, so there is no storm and no
// double-write.
type SyncedMap[K comparable, V any] struct {
cfg Config[K, V]
mu sync.RWMutex
data map[K]V
sub Subscription
// lifeCtx outlives Start's argument: a reconnect callback or reconcile tick
// can fire long after Start returns, so they must not be tied to a ctx the
// caller may cancel. Close cancels it.
lifeCtx context.Context
cancel context.CancelFunc
wg sync.WaitGroup
}
// Subscription is the subset of messaging.Subscription the component holds onto.
type Subscription = messaging.Subscription
// New constructs a SyncedMap. Call Start to hydrate and begin syncing.
func New[K comparable, V any](cfg Config[K, V]) *SyncedMap[K, V] {
return &SyncedMap[K, V]{cfg: cfg, data: make(map[K]V)}
}
func (m *SyncedMap[K, V]) subject() string {
return messaging.SubjectSyncStateDelta(m.cfg.Name)
}
// Start hydrates from the source, subscribes for peer deltas, registers a
// reconnect re-hydrate (when the client supports it), and starts the optional
// reconcile ticker.
func (m *SyncedMap[K, V]) Start(ctx context.Context) error {
if err := m.hydrate(ctx); err != nil {
return err
}
// The cancel func is stored on the struct and invoked in Close (covered by
// tests); lifeCtx must outlive Start to drive the reconnect/reconcile
// goroutines, so it cannot be cancelled or deferred within this scope.
m.lifeCtx, m.cancel = context.WithCancel(context.Background()) // #nosec G118 -- cancel is invoked in Close()
if m.cfg.Nats != nil {
sub, err := messaging.SubscribeJSON(m.cfg.Nats, m.subject(), m.apply)
if err != nil {
return err
}
m.sub = sub
// nats.go transparently resubscribes on reconnect, but it cannot know we
// kept derived in-memory state that may have drifted while the link was
// down, so re-hydrate from the durable source. Detected via an optional
// interface so MessagingClient itself stays minimal; standalone/test
// clients without the method simply fall back to the reconcile ticker.
if r, ok := m.cfg.Nats.(interface{ OnReconnect(func()) }); ok {
r.OnReconnect(func() {
if err := m.hydrate(m.lifeCtx); err != nil {
xlog.Warn("syncstate: reconnect re-hydrate failed", "name", m.cfg.Name, "error", err)
}
})
}
}
if m.cfg.Reconcile > 0 {
m.wg.Add(1)
go m.reconcileLoop()
}
return nil
}
// Close unsubscribes and stops the reconcile ticker.
func (m *SyncedMap[K, V]) Close() error {
if m.cancel != nil {
m.cancel()
}
m.wg.Wait()
if m.sub != nil {
return m.sub.Unsubscribe()
}
return nil
}
// Set updates the value locally, writes through the Store, then broadcasts.
// Per the data-flow contract the Store write happens under the lock so memory and
// durable state move together; the broadcast is best-effort after unlocking.
func (m *SyncedMap[K, V]) Set(ctx context.Context, v V) error {
k := m.cfg.Key(v)
m.mu.Lock()
m.data[k] = v
if m.cfg.Store != nil {
if err := m.cfg.Store.Upsert(ctx, v); err != nil {
m.mu.Unlock()
return err
}
}
m.mu.Unlock()
m.publish(opSet, k, v)
return nil
}
// Delete removes the key locally, deletes it from the Store, then broadcasts.
func (m *SyncedMap[K, V]) Delete(ctx context.Context, k K) error {
m.mu.Lock()
delete(m.data, k)
if m.cfg.Store != nil {
if err := m.cfg.Store.Delete(ctx, k); err != nil {
m.mu.Unlock()
return err
}
}
m.mu.Unlock()
var zero V
m.publish(opDelete, k, zero)
return nil
}
// Get returns the value for k and whether it was present.
func (m *SyncedMap[K, V]) Get(k K) (V, bool) {
m.mu.RLock()
defer m.mu.RUnlock()
v, ok := m.data[k]
return v, ok
}
// List returns a snapshot slice of all values.
func (m *SyncedMap[K, V]) List() []V {
m.mu.RLock()
defer m.mu.RUnlock()
out := make([]V, 0, len(m.data))
for _, v := range m.data {
out = append(out, v)
}
return out
}
// Snapshot returns a copy of the underlying map.
func (m *SyncedMap[K, V]) Snapshot() map[K]V {
m.mu.RLock()
defer m.mu.RUnlock()
out := make(map[K]V, len(m.data))
for k, v := range m.data {
out[k] = v
}
return out
}
// publish broadcasts a delta. Standalone (nil Nats) is a strict no-op.
func (m *SyncedMap[K, V]) publish(op string, k K, v V) {
if m.cfg.Nats == nil {
return
}
if err := m.cfg.Nats.Publish(m.subject(), delta[K, V]{Op: op, Key: k, Value: v}); err != nil {
xlog.Warn("syncstate: failed to broadcast delta", "name", m.cfg.Name, "op", op, "error", err)
}
}
// apply handles a peer's delta: memory-only update plus OnApply. It deliberately
// never writes the Store nor re-publishes - that is the echo-loop guard.
func (m *SyncedMap[K, V]) apply(d delta[K, V]) {
switch d.Op {
case opSet:
m.mu.Lock()
m.data[d.Key] = d.Value
m.mu.Unlock()
case opDelete:
m.mu.Lock()
delete(m.data, d.Key)
m.mu.Unlock()
default:
xlog.Warn("syncstate: ignoring delta with unknown op", "name", m.cfg.Name, "op", d.Op)
return
}
if m.cfg.OnApply != nil {
m.cfg.OnApply(d.Op, d.Key, d.Value)
}
}
// hydrate replaces the whole map from the durable source: Store if present, else
// Loader. With neither, a late joiner starts empty and catches up via deltas
// (acceptable only for ephemeral state).
func (m *SyncedMap[K, V]) hydrate(ctx context.Context) error {
var (
vals []V
err error
)
switch {
case m.cfg.Store != nil:
vals, err = m.cfg.Store.List(ctx)
case m.cfg.Loader != nil:
vals, err = m.cfg.Loader(ctx)
default:
return nil
}
if err != nil {
return err
}
m.replaceAll(vals)
return nil
}
// replaceAll atomically swaps the map contents for the given values, keyed via
// cfg.Key.
func (m *SyncedMap[K, V]) replaceAll(vals []V) {
next := make(map[K]V, len(vals))
for _, v := range vals {
next[m.cfg.Key(v)] = v
}
m.mu.Lock()
m.data = next
m.mu.Unlock()
}
// reconcileLoop periodically re-hydrates to repair silent drift (missed deltas).
func (m *SyncedMap[K, V]) reconcileLoop() {
defer m.wg.Done()
t := time.NewTicker(m.cfg.Reconcile)
defer t.Stop()
for {
select {
case <-m.lifeCtx.Done():
return
case <-t.C:
if err := m.hydrate(m.lifeCtx); err != nil {
xlog.Warn("syncstate: reconcile re-hydrate failed", "name", m.cfg.Name, "error", err)
}
}
}
}

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@@ -0,0 +1,13 @@
package syncstate_test
import (
"testing"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestSyncstate(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "Syncstate Suite")
}

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package syncstate_test
import (
"context"
"sync"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"github.com/mudler/LocalAI/core/services/messaging"
"github.com/mudler/LocalAI/core/services/syncstate"
"github.com/mudler/LocalAI/core/services/testutil"
)
// job is a minimal JSON-serializable value stand-in for the real cross-replica
// records (finetune/quant/agent jobs) the component is built for.
type job struct {
ID string `json:"id"`
Status string `json:"status"`
}
func jobKey(j *job) string { return j.ID }
const stateName = "test.jobs"
func deltaSubject() string { return messaging.SubjectSyncStateDelta(stateName) }
// fakeStore is an in-memory Store that records call counts so specs can assert
// the write-through-vs-apply split (local writes hit the Store; applied deltas
// must not).
type fakeStore struct {
mu sync.Mutex
data map[string]*job
upsertCalls int
deleteCalls int
listCalls int
}
func newFakeStore(seed ...*job) *fakeStore {
s := &fakeStore{data: map[string]*job{}}
for _, j := range seed {
s.data[j.ID] = j
}
return s
}
func (s *fakeStore) List(_ context.Context) ([]*job, error) {
s.mu.Lock()
defer s.mu.Unlock()
s.listCalls++
out := make([]*job, 0, len(s.data))
for _, j := range s.data {
out = append(out, j)
}
return out, nil
}
func (s *fakeStore) Upsert(_ context.Context, j *job) error {
s.mu.Lock()
defer s.mu.Unlock()
s.upsertCalls++
s.data[j.ID] = j
return nil
}
func (s *fakeStore) Delete(_ context.Context, k string) error {
s.mu.Lock()
defer s.mu.Unlock()
s.deleteCalls++
delete(s.data, k)
return nil
}
// add simulates a peer replica writing to the shared DB out-of-band (e.g. while
// this replica was partitioned), so a re-hydrate can be observed to pick it up.
func (s *fakeStore) add(j *job) {
s.mu.Lock()
defer s.mu.Unlock()
s.data[j.ID] = j
}
func (s *fakeStore) counts() (upsert, del, list int) {
s.mu.Lock()
defer s.mu.Unlock()
return s.upsertCalls, s.deleteCalls, s.listCalls
}
var _ = Describe("SyncedMap", func() {
ctx := context.Background()
Describe("cross-replica delta propagation", func() {
var (
bus *testutil.FakeBus
a, b *syncstate.SyncedMap[string, *job]
)
BeforeEach(func() {
bus = testutil.NewFakeBus()
a = syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey, Nats: bus})
b = syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey, Nats: bus})
Expect(a.Start(ctx)).To(Succeed())
Expect(b.Start(ctx)).To(Succeed())
})
AfterEach(func() {
Expect(a.Close()).To(Succeed())
Expect(b.Close()).To(Succeed())
})
It("propagates a Set on A to B", func() {
Expect(a.Set(ctx, &job{ID: "1", Status: "running"})).To(Succeed())
got, ok := b.Get("1")
Expect(ok).To(BeTrue(), "replica B should see the value A just set")
Expect(got.Status).To(Equal("running"))
})
It("prunes a Delete on A from B", func() {
Expect(a.Set(ctx, &job{ID: "1", Status: "running"})).To(Succeed())
_, present := b.Get("1")
Expect(present).To(BeTrue(), "precondition: B must have the value before the delete")
Expect(a.Delete(ctx, "1")).To(Succeed())
_, ok := b.Get("1")
Expect(ok).To(BeFalse(), "a delete on A must remove the key from B")
})
})
Describe("hydration", func() {
It("hydrates on Start from a preloaded Store", func() {
store := newFakeStore(&job{ID: "x", Status: "done"})
m := syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey, Store: store})
Expect(m.Start(ctx)).To(Succeed())
got, ok := m.Get("x")
Expect(ok).To(BeTrue(), "Start must populate the map from the Store")
Expect(got.Status).To(Equal("done"))
})
It("uses the Loader when Store is nil", func() {
m := syncstate.New(syncstate.Config[string, *job]{
Name: stateName,
Key: jobKey,
Loader: func(_ context.Context) ([]*job, error) {
return []*job{{ID: "l", Status: "loaded"}}, nil
},
})
Expect(m.Start(ctx)).To(Succeed())
got, ok := m.Get("l")
Expect(ok).To(BeTrue(), "Loader output must hydrate the map when there is no Store")
Expect(got.Status).To(Equal("loaded"))
})
})
Describe("echo-loop guard", func() {
It("applies its own broadcast once and does not re-publish", func() {
bus := testutil.NewFakeBus()
a := syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey, Nats: bus})
b := syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey, Nats: bus})
Expect(a.Start(ctx)).To(Succeed())
Expect(b.Start(ctx)).To(Succeed())
defer func() {
Expect(a.Close()).To(Succeed())
Expect(b.Close()).To(Succeed())
}()
Expect(a.Set(ctx, &job{ID: "e", Status: "running"})).To(Succeed())
// One local write must produce exactly one broadcast: A and B both
// receive it and apply to memory, but the apply path never re-publishes.
Expect(bus.PublishCount(deltaSubject())).To(Equal(1),
"the apply path must not re-broadcast, otherwise replicas storm")
Expect(a.List()).To(HaveLen(1), "A must not double-store its own echo")
_, ok := b.Get("e")
Expect(ok).To(BeTrue())
})
})
Describe("Store write-through vs apply", func() {
It("writes the Store on local Set/Delete but not on an applied delta", func() {
bus := testutil.NewFakeBus()
storeA := newFakeStore()
storeB := newFakeStore()
a := syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey, Nats: bus, Store: storeA})
b := syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey, Nats: bus, Store: storeB})
Expect(a.Start(ctx)).To(Succeed())
Expect(b.Start(ctx)).To(Succeed())
defer func() {
Expect(a.Close()).To(Succeed())
Expect(b.Close()).To(Succeed())
}()
Expect(a.Set(ctx, &job{ID: "w", Status: "running"})).To(Succeed())
upA, _, _ := storeA.counts()
upB, _, _ := storeB.counts()
Expect(upA).To(Equal(1), "local Set must write through to its own Store")
Expect(upB).To(Equal(0), "the apply path must never write the peer's Store")
Expect(a.Delete(ctx, "w")).To(Succeed())
_, delA, _ := storeA.counts()
_, delB, _ := storeB.counts()
Expect(delA).To(Equal(1), "local Delete must delete from its own Store")
Expect(delB).To(Equal(0), "the apply path must never delete from the peer's Store")
})
})
Describe("OnApply hook", func() {
It("fires with the correct op and key on an applied delta", func() {
bus := testutil.NewFakeBus()
var (
mu sync.Mutex
ops []string
keys []string
)
a := syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey, Nats: bus})
b := syncstate.New(syncstate.Config[string, *job]{
Name: stateName, Key: jobKey, Nats: bus,
OnApply: func(op string, k string, _ *job) {
mu.Lock()
ops = append(ops, op)
keys = append(keys, k)
mu.Unlock()
},
})
Expect(a.Start(ctx)).To(Succeed())
Expect(b.Start(ctx)).To(Succeed())
defer func() {
Expect(a.Close()).To(Succeed())
Expect(b.Close()).To(Succeed())
}()
Expect(a.Set(ctx, &job{ID: "o", Status: "running"})).To(Succeed())
Expect(a.Delete(ctx, "o")).To(Succeed())
mu.Lock()
defer mu.Unlock()
Expect(ops).To(Equal([]string{"set", "delete"}))
Expect(keys).To(Equal([]string{"o", "o"}))
})
})
Describe("standalone (nil Nats)", func() {
It("works in-memory with no panic and nothing to broadcast", func() {
m := syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey})
Expect(m.Start(ctx)).To(Succeed())
defer func() { Expect(m.Close()).To(Succeed()) }()
Expect(func() {
Expect(m.Set(ctx, &job{ID: "s", Status: "running"})).To(Succeed())
}).ToNot(Panic())
got, ok := m.Get("s")
Expect(ok).To(BeTrue())
Expect(got.Status).To(Equal("running"))
Expect(m.List()).To(HaveLen(1))
Expect(m.Snapshot()).To(HaveKey("s"))
Expect(m.Delete(ctx, "s")).To(Succeed())
_, ok = m.Get("s")
Expect(ok).To(BeFalse())
})
})
Describe("reconnect re-hydrate", func() {
It("re-reads the source when the messaging client reconnects", func() {
bus := testutil.NewFakeBus()
store := newFakeStore(&job{ID: "init", Status: "running"})
m := syncstate.New(syncstate.Config[string, *job]{Name: stateName, Key: jobKey, Nats: bus, Store: store})
Expect(m.Start(ctx)).To(Succeed())
defer func() { Expect(m.Close()).To(Succeed()) }()
_, ok := m.Get("init")
Expect(ok).To(BeTrue())
// A peer writes to the shared DB while we are unaware (no delta seen).
store.add(&job{ID: "late", Status: "running"})
_, ok = m.Get("late")
Expect(ok).To(BeFalse(), "the new row should not appear before a re-hydrate")
bus.TriggerReconnect()
_, ok = m.Get("late")
Expect(ok).To(BeTrue(), "reconnect must re-hydrate from the source and pick up drift")
_, _, list := store.counts()
Expect(list).To(Equal(2), "exactly one Start hydrate plus one reconnect re-hydrate")
})
})
})

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package testutil
import (
"encoding/json"
"strings"
"sync"
"time"
"github.com/mudler/LocalAI/core/services/messaging"
)
// FakeBus is an in-memory messaging.MessagingClient that delivers each published
// message synchronously to every registered subscriber whose subject filter
// matches, including NATS-style wildcard subjects (`*` matches exactly one
// token).
//
// Synchronous delivery keeps specs deterministic: the moment Publish returns,
// every matching subscriber's handler has already run, so the spec body can read
// the resulting state without polling. It is the shared test double for every
// cross-replica-sync adopter (gallery, syncstate, ...) so they exercise the same
// delivery semantics. It deliberately depends only on the standard library and
// the messaging package — no test framework — so it is importable anywhere.
type FakeBus struct {
mu sync.Mutex
subs []fakeBusSub
// publishCounts records how many messages were published per subject, so a
// spec can assert the echo-loop guard (an applied delta must not re-publish).
publishCounts map[string]int
// reconnectCbs back the optional OnReconnect/TriggerReconnect pair, letting a
// spec exercise the component's reconnect re-hydrate path without a real
// NATS server.
reconnectCbs []func()
}
type fakeBusSub struct {
subject string
handler func([]byte)
}
// NewFakeBus returns a ready-to-use in-memory bus.
func NewFakeBus() *FakeBus {
return &FakeBus{publishCounts: map[string]int{}}
}
// subjectMatches reports whether a subscription filter matches a concrete
// subject, honoring the single-token `*` wildcard used by NATS.
func subjectMatches(filter, subject string) bool {
if filter == subject {
return true
}
fp := strings.Split(filter, ".")
sp := strings.Split(subject, ".")
if len(fp) != len(sp) {
return false
}
for i := range fp {
if fp[i] == "*" {
continue
}
if fp[i] != sp[i] {
return false
}
}
return true
}
// Publish marshals data as JSON and delivers it synchronously to every matching
// subscriber.
func (b *FakeBus) Publish(subject string, data any) error {
payload, err := json.Marshal(data)
if err != nil {
return err
}
b.mu.Lock()
b.publishCounts[subject]++
subs := append([]fakeBusSub(nil), b.subs...)
b.mu.Unlock()
for _, s := range subs {
if subjectMatches(s.subject, subject) {
s.handler(payload)
}
}
return nil
}
// PublishCount returns how many messages were published on the exact subject.
func (b *FakeBus) PublishCount(subject string) int {
b.mu.Lock()
defer b.mu.Unlock()
return b.publishCounts[subject]
}
type fakeBusSubscription struct {
bus *FakeBus
subRef fakeBusSub
}
func (s *fakeBusSubscription) Unsubscribe() error {
s.bus.mu.Lock()
defer s.bus.mu.Unlock()
for i, candidate := range s.bus.subs {
if candidate.subject == s.subRef.subject {
s.bus.subs = append(s.bus.subs[:i], s.bus.subs[i+1:]...)
return nil
}
}
return nil
}
func (b *FakeBus) Subscribe(subject string, handler func([]byte)) (messaging.Subscription, error) {
sub := fakeBusSub{subject: subject, handler: handler}
b.mu.Lock()
b.subs = append(b.subs, sub)
b.mu.Unlock()
return &fakeBusSubscription{bus: b, subRef: sub}, nil
}
func (b *FakeBus) QueueSubscribe(subject, _ string, handler func([]byte)) (messaging.Subscription, error) {
return b.Subscribe(subject, handler)
}
func (b *FakeBus) QueueSubscribeReply(string, string, func([]byte, func([]byte))) (messaging.Subscription, error) {
return &fakeBusSubscription{bus: b}, nil
}
func (b *FakeBus) SubscribeReply(string, func([]byte, func([]byte))) (messaging.Subscription, error) {
return &fakeBusSubscription{bus: b}, nil
}
func (b *FakeBus) Request(string, []byte, time.Duration) ([]byte, error) {
return nil, nil
}
func (b *FakeBus) IsConnected() bool { return true }
func (b *FakeBus) Close() {}
// OnReconnect mirrors *messaging.Client.OnReconnect so a spec can drive the
// component's reconnect re-hydrate path. The component detects this method via an
// optional interface assertion; implementing it here keeps the fake a faithful
// stand-in for the concrete client.
func (b *FakeBus) OnReconnect(cb func()) {
if cb == nil {
return
}
b.mu.Lock()
b.reconnectCbs = append(b.reconnectCbs, cb)
b.mu.Unlock()
}
// TriggerReconnect runs every registered reconnect callback, simulating a NATS
// reconnect event.
func (b *FakeBus) TriggerReconnect() {
b.mu.Lock()
cbs := append([]func(){}, b.reconnectCbs...)
b.mu.Unlock()
for _, cb := range cbs {
cb()
}
}

View File

@@ -57,6 +57,11 @@ services:
LOCALAI_AGENT_POOL_VECTOR_ENGINE: "postgres"
LOCALAI_AGENT_POOL_DATABASE_URL: "postgresql://localai:localai@postgres:5432/localai?sslmode=disable"
LOCALAI_REGISTRATION_TOKEN: "changeme" # Change this in production!
# Shared-models mode (optional): set when every node mounts the SAME
# models directory at the SAME path (see "Shared Volume Mode" below).
# The router then skips gRPC file staging and workers load models
# directly from the shared volume instead of re-downloading them.
# LOCALAI_DISTRIBUTED_SHARED_MODELS: "true"
# Auth (required for distributed mode — must use PostgreSQL)
LOCALAI_AUTH: "true"
LOCALAI_AUTH_DATABASE_URL: "postgresql://localai:localai@postgres:5432/localai?sslmode=disable"
@@ -157,8 +162,11 @@ services:
# Then add to the volumes section:
# shared_models:
#
# With shared volumes, model files are already available on the backend —
# gRPC file staging becomes a no-op (paths match).
# With shared volumes the model files are already present on every worker at
# the same path. Set LOCALAI_DISTRIBUTED_SHARED_MODELS=true on the frontend
# (see its environment above) so the router skips gRPC file staging and the
# worker loads the model directly from the shared path instead of
# re-downloading it into a per-model subdirectory.
# --- Adding More Workers ---
# Copy the worker-1 service above and change:

View File

@@ -67,6 +67,7 @@ The frontend is a standard LocalAI instance with distributed mode enabled. These
| `--registration-require-auth` | `LOCALAI_REGISTRATION_REQUIRE_AUTH` | `false` | Fail startup when distributed mode is enabled but the registration token is empty (node endpoints and worker file-transfer would otherwise be unauthenticated) |
| `--distributed-require-auth` | `LOCALAI_DISTRIBUTED_REQUIRE_AUTH` | `false` | **Umbrella switch.** Implies both `--nats-require-auth` and `--registration-require-auth` — one knob to lock down the NATS bus *and* the registration/file-transfer layer. Set this in production instead of the two granular flags. |
| `--auto-approve-nodes` | `LOCALAI_AUTO_APPROVE_NODES` | `false` | Auto-approve new worker nodes (skip admin approval) |
| `--distributed-shared-models` | `LOCALAI_DISTRIBUTED_SHARED_MODELS` | `false` | Assert that every node mounts the **same** models directory at the **same** path (a shared volume). When `true`, the router skips file staging entirely and workers load models directly from the shared path instead of re-downloading them. See [Shared models directory](#shared-models-directory). |
| `--auth` | `LOCALAI_AUTH` | `false` | **Must be `true`** for distributed mode |
| `--auth-database-url` | `LOCALAI_AUTH_DATABASE_URL` | *(required)* | PostgreSQL connection URL |
| `--backend-install-timeout` | `LOCALAI_NATS_BACKEND_INSTALL_TIMEOUT` | `15m` | How long the frontend waits for a worker to acknowledge a backend install before considering the request stalled. Raise it when workers pull large backend images over slow links. If a worker takes longer than this, the operation shows as "still installing in background" in the admin UI and clears once the worker finishes. |
@@ -133,6 +134,14 @@ When S3 is not configured, model files are transferred directly from the fronten
For high-throughput or very large model files, S3 can be more efficient since it avoids streaming through the frontend.
### Shared models directory
If every node (frontend and workers) mounts the **same** models directory at the **same** path - for example a shared volume or network filesystem, as shown in the "Shared Volume Mode" section of `docker-compose.distributed.yaml` - the model files are already present on each worker at their canonical path. In that case staging is wasted work: it copies files that already exist into a per-model subdirectory the worker then loads from, which shows up as a re-download of a model you already have.
Set `LOCALAI_DISTRIBUTED_SHARED_MODELS=true` (or `--distributed-shared-models`) on the frontend to skip staging entirely. The router then leaves the model's absolute paths untouched and the worker loads them directly from the shared volume.
This flag is a contract you assert: all nodes must mount identical paths. Leave it off (the default) when workers have independent models directories - the frontend stages files to them over HTTP (or S3) as described above.
{{% notice warning %}}
The worker HTTP file transfer server is authenticated by `LOCALAI_REGISTRATION_TOKEN`. If the token is **empty**, the server **fails open** — anyone who can reach the port gets read/write access to the worker's models/staging/data directories (a remote model-poisoning / exfiltration vector). The worker logs a loud warning at startup in this case. Always set `LOCALAI_REGISTRATION_TOKEN` in distributed mode, and set `LOCALAI_DISTRIBUTED_REQUIRE_AUTH=true` (frontend **and** workers) to make a missing token *or* missing NATS credentials a hard startup error rather than a silent fail-open. Firewall the file-transfer port (gRPC base 1) so only the frontend can reach it.
{{% /notice %}}

View File

@@ -7,16 +7,93 @@ url = "/features/face-recognition/"
![Face recognition: 1:N match against a vector store, with an anti-spoofing liveness gate that can veto a verification](/images/diagrams/face-recognition-flow.png)
LocalAI supports face recognition through the `insightface` backend:
face verification (1:1), face identification (1:N) against a built-in
vector store, face embedding, face detection, demographic analysis
(age / gender), and antispoofing / liveness detection.
LocalAI supports face recognition: face verification (1:1), face
identification (1:N) against a built-in vector store, face embedding,
face detection, demographic analysis (age / gender), and antispoofing /
liveness detection.
The backend ships **two interchangeable engines** under one image, each
paired with a distinct gallery entry so users can pick by license and
accuracy needs.
The same `/v1/face/*` HTTP API is served by two backends:
## Licensing — read this first
- **`face-detect` (recommended, default).** A standalone C++/ggml
engine ([face-detect.cpp](https://github.com/mudler/face-detect.cpp)):
no Python, no onnxruntime, no torch runtime. Each gallery entry is a
single self-describing GGUF. This is the recommended option for new
deployments.
- **`insightface` (Python).** The original ONNX Runtime backend. Still
supported; see [the Python backend](#insightface-python-backend) below.
Both backends expose the identical wire format, so the API examples in
this page work with either - only the gallery entry name (the `model`
field) changes.
## face-detect (ggml) backend
The `face-detect` backend reads the detector and recognizer architecture
(`facedetect.arch`) directly from the GGUF metadata, so installing a
gallery entry is all that is needed to select an engine. It drives the
Embeddings / Detect / FaceVerify / FaceAnalyze gRPC rpcs behind the
`/v1/face/{embed,verify,analyze,detect,register,identify,forget}`
endpoints.
### Licensing - read this first
| Gallery entry | Detector + recognizer | Embedding dim | License |
|---|---|---|---|
| `face-detect-buffalo-l` | SCRFD-10GF + ArcFace R50 + GenderAge | 512 | **Non-commercial research only** (upstream insightface weights) |
| `face-detect-buffalo-m` | SCRFD-2.5GF + ArcFace R50 + GenderAge | 512 | **Non-commercial research only** |
| `face-detect-buffalo-s` | SCRFD-500MF + MBF + GenderAge | 512 | **Non-commercial research only** |
| `face-detect-yunet-sface` | YuNet + SFace (OpenCV Zoo) | 128 | **Apache 2.0 - commercial-safe** |
The insightface buffalo packs (buffalo_l / buffalo_m / buffalo_s) are
released by the upstream maintainers for **non-commercial research use
only**. Pick the `face-detect-yunet-sface` entry for production /
commercial deployments.
### Quickstart
Install the commercial-safe entry (recommended for copy-paste):
```bash
local-ai models install face-detect-yunet-sface
```
Verify that two images depict the same person:
```bash
curl -sX POST http://localhost:8080/v1/face/verify \
-H "Content-Type: application/json" \
-d '{
"model": "face-detect-yunet-sface",
"img1": "https://example.com/alice_1.jpg",
"img2": "https://example.com/alice_2.jpg"
}'
```
Detect faces and analyze demographics (buffalo entries populate
age / gender; YuNet + SFace returns regions only):
```bash
curl -sX POST http://localhost:8080/v1/face/detect \
-H "Content-Type: application/json" \
-d '{"model": "face-detect-buffalo-l", "img": "https://example.com/group.jpg"}'
curl -sX POST http://localhost:8080/v1/face/analyze \
-H "Content-Type: application/json" \
-d '{"model": "face-detect-buffalo-l", "img": "https://example.com/alice.jpg"}'
```
The 1:N register / identify / forget workflow and the rest of the API
are identical to the [API reference](#api-reference) below - just pass a
`face-detect-*` model name. The per-engine verify thresholds are ~0.35
for the buffalo ArcFace/MBF recognizers and ~0.363 for SFace.
## insightface (Python) backend
The `insightface` backend ships **two interchangeable engines** under
one image, each paired with a distinct gallery entry so users can pick
by license and accuracy needs.
### Licensing - read this first
| Gallery entry | Detector + recognizer | Size | License |
|---|---|---|---|

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