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18 Commits
| Author | SHA1 | Message | Date | |
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LocalAI [bot]
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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> |
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Richard Palethorpe
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606128e4e9 |
feat(vulkan): make Vulkan backends self-contained on the GPU (#10404)
Vulkan backends bundled their own loader and ICD manifests but neither the Mesa driver the manifests point at nor a way to make the loader find them, so on a runtime base image without Mesa the loader enumerated zero devices and the GPU silently fell back to CPU (only NVIDIA worked, since its ICD is injected by the container toolkit). - scripts/build/package-gpu-libs.sh: for each installed ICD manifest, bundle the driver .so its library_path names — no hard-coded, platform-dependent soname list — plus that driver's ldd dependencies, skipping manifests whose driver isn't installed. Rewrite each library_path to a bare soname so the bundled driver resolves via the LD_LIBRARY_PATH run.sh already sets. - .docker/install-base-deps.sh, backend/Dockerfile.golang, backend/Dockerfile.python: install mesa-vulkan-drivers in every Vulkan builder so the driver + manifests exist to be packaged (the LunarG SDK ships only the loader and shader tooling). - pkg/model/process.go: when a backend ships vulkan/icd.d/, point the loader at it via VK_DRIVER_FILES/VK_ICD_FILENAMES at launch (no-op otherwise). Covered by pkg/model/process_vulkan_test.go. - backend/go/parakeet-cpp/package.sh: complete the L0 stub (was missing the libc-family ldd walk + GPU-lib packaging) by mirroring whisper, so the vulkan-parakeet image actually bundles its GPU runtime. Assisted-by: Claude Code:claude-opus-4-8 Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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LocalAI [bot]
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50dea8c983 |
feat(crispasr): bundle espeak-ng and add piper TTS voices to the gallery (#10283)
CrispASR's piper backend phonemizes non-English text via espeak-ng (dlopen, the MIT-clean path; English uses a built-in G2P). The FROM scratch crispasr image shipped none of it, so non-English piper voices loaded but failed synthesis with "phonemization failed". Bundle the espeak-ng runtime so they work: - Dockerfile.golang: install espeak-ng-data + libespeak-ng1 and its libpcaudio0 / libsonic0 deps in the crispasr builder (espeak's dlopen fails without the latter two). - package.sh: copy libespeak-ng.so.1, libpcaudio.so.0, libsonic.so.0 into package/lib/ and the espeak-ng-data dir into the package root. - run.sh: export CRISPASR_ESPEAK_DATA_PATH so the bundled data is found. Add 9 single-speaker piper voices (de/en/it, incl. Italian paola + riccardo) to the gallery, run through backend:piper, hosted at LocalAI-Community/piper-voices-GGUF (converted from rhasspy/piper-voices with CrispASR's convert-piper-to-gguf.py). Only single-speaker low/medium voices are included; the engine does not yet support multi-speaker or high-quality piper decoders. All 9 verified end-to-end: each synthesizes a WAV at the model's native sample rate using only the image-bundled espeak payload. 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> |
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Ettore Di Giacinto
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e86ade54a6 |
feat(api): add /v1/audio/diarization endpoint with sherpa-onnx + vibevoice.cpp (#9654)
* feat(api): add /v1/audio/diarization endpoint with sherpa-onnx + vibevoice.cpp
Closes #1648.
OpenAI-style multipart endpoint that returns "who spoke when". Single
endpoint instead of the issue's three-endpoint sketch (refactor /vad,
/vad/embedding, /diarization) — the typical client wants one call, and
embeddings can land later as a sibling without breaking this surface.
Response shape borrows from Pyannote/Deepgram: segments carry a
normalised SPEAKER_NN id (zero-padded, stable across the response) plus
the raw backend label, optional per-segment text when the backend bundles
ASR, and a speakers summary in verbose_json. response_format also accepts
rttm so consumers can pipe straight into pyannote.metrics / dscore.
Backends:
* vibevoice-cpp — Diarize() reuses the existing vv_capi_asr pass.
vibevoice's ASR prompt asks the model to emit
[{Start,End,Speaker,Content}] natively, so diarization is a by-product
of the same pass; include_text=true preserves the transcript per
segment, otherwise we drop it.
* sherpa-onnx — wraps the upstream SherpaOnnxOfflineSpeakerDiarization
C API (pyannote segmentation + speaker-embedding extractor + fast
clustering). libsherpa-shim grew config builders, a SetClustering
wrapper for per-call num_clusters/threshold overrides, and a
segment_at accessor (purego can't read field arrays out of
SherpaOnnxOfflineSpeakerDiarizationSegment[] directly).
Plumbing: new Diarize gRPC RPC + DiarizeRequest / DiarizeSegment /
DiarizeResponse messages, threaded through interface.go, base, server,
client, embed. Default Base impl returns unimplemented.
Capability surfaces all updated: FLAG_DIARIZATION usecase,
FeatureAudioDiarization permission (default-on), RouteFeatureRegistry
entries for /v1/audio/diarization and /audio/diarization, audio
instruction-def description widened, CAP_DIARIZATION JS symbol,
swagger regenerated, /api/instructions discovery map updated.
Tests:
* core/backend: speaker-label normalisation (first-seen → SPEAKER_NN,
per-speaker totals, nil-safety, fallback to backend NumSpeakers when
no segments).
* core/http/endpoints/openai: RTTM rendering (file-id basename, negative
duration clamping, fallback id).
* tests/e2e: mock-backend grew a deterministic Diarize that emits
raw labels "5","2","5" so the e2e suite verifies SPEAKER_NN
remapping, verbose_json speakers summary + transcript pass-through
(gated by include_text), RTTM bytes content-type, and rejection of
unknown response_format. mock-diarize model config registered with
known_usecases=[FLAG_DIARIZATION] to bypass the backend-name guard.
Docs: new features/audio-diarization.md (request/response, RTTM example,
sherpa-onnx + vibevoice setup), cross-link from audio-to-text.md, entry
in whats-new.md.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
* fix(diarization): correct sherpa-onnx symbol name + lint cleanup
CI failures on #9654:
* sherpa-onnx-grpc-{tts,transcription} and sherpa-onnx-realtime panicked
at backend startup with `undefined symbol: SherpaOnnxDestroyOfflineSpeakerDiarizationResult`.
Upstream's actual symbol is SherpaOnnxOfflineSpeakerDiarizationDestroyResult
(Destroy in the middle, not the prefix); the rest of the diarization
surface follows the same naming pattern. The mismatched name made
purego.RegisterLibFunc fail at dlopen time and crashed the gRPC server
before the BeforeAll could probe Health, taking down every sherpa-onnx
test job — not just the diarization-related ones.
* golangci-lint flagged 5 errcheck violations on new defer cleanups
(os.RemoveAll / Close / conn.Close); wrap each in a `defer func() { _ = X() }()`
closure (matches the pattern other LocalAI files use for new code, since
pre-existing bare defers are grandfathered in via new-from-merge-base).
* golangci-lint also flagged forbidigo violations: the new
diarization_test.go files used testing.T-style `t.Errorf` / `t.Fatalf`,
which are forbidden by the project's coding-style policy
(.agents/coding-style.md). Convert both files to Ginkgo/Gomega
Describe/It with Expect(...) — they get picked up by the existing
TestBackend / TestOpenAI suites, no new suite plumbing needed.
* modernize linter: tightened the diarization segment loop to
`for i := range int(numSegments)` (Go 1.22+ idiom).
Verified locally: golangci-lint with new-from-merge-base=origin/master
reports 0 issues across all touched packages, and the four mocked
diarization e2e specs in tests/e2e/mock_backend_test.go still pass.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
* fix(vibevoice-cpp): convert non-WAV input via ffmpeg + raise ASR token budget
Confirmed end-to-end against a real LocalAI instance with vibevoice-asr-q4_k
loaded and the multi-speaker MP3 sample at vibevoice.cpp/samples/2p_argument.mp3:
both /v1/audio/transcriptions and /v1/audio/diarization now succeed and
return correctly attributed speaker turns for the full clip.
Two latent issues surfaced once the diarization endpoint actually exercised
the backend with a non-trivial input:
1. vv_capi_asr only accepts WAV via load_wav_24k_mono. The previous code
passed the uploaded path straight through, so anything that wasn't
already a 24 kHz mono s16le WAV failed at the C side with rc=-8 and
the very unhelpful "vv_capi_asr failed". prepareWavInput shells out
to ffmpeg ("-ar 24000 -ac 1 -acodec pcm_s16le") in a per-call temp
dir, matching the rate the model was trained on; both AudioTranscription
and Diarize now route through it. This is the same shape sherpa-onnx
uses (utils.AudioToWav), but vibevoice needs 24 kHz rather than 16 kHz
so we don't reuse that helper.
2. The C ABI's max_new_tokens defaults to 256 when 0 is passed. That's
fine for a five-second clip but not for anything past ~10 s — vibevoice
stops mid-JSON, the parse fails, and the caller sees a hard error.
Pass a much larger budget (16 384 ≈ ~9 minutes of speech at the
model's ~30 tok/s rate); generation stops at EOS so this is a cap
rather than a target.
3. As a defensive belt-and-braces, mirror AudioTranscription's existing
"fall back to a single segment if the model emits non-JSON text"
pattern in Diarize, so partial / unusual model output never produces
a 500. This kept the endpoint usable while diagnosing (1) and (2),
and is the right behaviour to keep.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
* fix(vibevoice-cpp): pass valid WAVs through directly so ffmpeg is not required at runtime
Spotted by tests-e2e-backend (1.25.x): the previous fix forced every
incoming audio file through `ffmpeg -ar 24000 ...`, which meant the
backend container — which does not ship ffmpeg — failed even for the
existing happy path where the caller already uploads a WAV. The
container-side error was:
rpc error: code = Unknown desc = vibevoice-cpp: ffmpeg convert to
24k mono wav: exec: "ffmpeg": executable file not found in $PATH
Reading vibevoice.cpp's audio_io.cpp, `load_wav_24k_mono` uses drwav and
already accepts any PCM/IEEE-float WAV at any sample rate, downmixes
multi-channel input to mono, and resamples to 24 kHz internally. So the
only inputs that genuinely need an external converter are non-WAV
formats (MP3, OGG, FLAC, ...).
Detect WAVs by RIFF/WAVE magic at bytes 0..3 / 8..11 and pass them
straight through with a no-op cleanup; everything else still goes
through ffmpeg with the same 24 kHz mono s16le target. The result:
* Container builds without ffmpeg keep working for WAV uploads
(the e2e-backends fixture is jfk.wav at 16 kHz mono s16le).
* MP3 and other non-WAV inputs still get the new ffmpeg conversion
path so the diarization endpoint stays useful.
* If the caller uploads a non-WAV but ffmpeg isn't on PATH, the
surfaced error is still descriptive enough to act on.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
* fix(ci): make gcc-14 install in Dockerfile.golang best-effort for jammy bases
The LocalVQE PR (
|
||
|
Richard Palethorpe
|
bb033b16a9 |
feat: add LocalVQE backend and audio transformations UI (#9640)
feat(audio-transform): add LocalVQE backend, bidi gRPC RPC, Studio UI
Introduce a generic "audio transform" capability for any audio-in / audio-out
operation (echo cancellation, noise suppression, dereverberation, voice
conversion, etc.) and ship LocalVQE as the first backend implementation.
Backend protocol:
- Two new gRPC RPCs in backend.proto: unary AudioTransform for batch and
bidirectional AudioTransformStream for low-latency frame-by-frame use.
This is the first bidi stream in the proto; per-frame unary at LocalVQE's
16 ms hop would be RTT-bound. Wire it through pkg/grpc/{client,server,
embed,interface,base} with paired-channel ergonomics.
LocalVQE backend (backend/go/localvqe/):
- Go-Purego wrapper around upstream liblocalvqe.so. CMake builds the upstream
shared lib + its libggml-cpu-*.so runtime variants directly — no MODULE
wrapper needed because LocalVQE handles CPU feature selection internally
via GGML_BACKEND_DL.
- Sets GGML_NTHREADS from opts.Threads (or runtime.NumCPU()-1) — without it
LocalVQE runs single-threaded at ~1× realtime instead of the documented
~9.6×.
- Reference-length policy: zero-pad short refs, truncate long ones (the
trailing portion can't have leaked into a mic that wasn't recording).
- Ginkgo test suite (9 always-on specs + 2 model-gated).
HTTP layer:
- POST /audio/transformations (alias /audio/transform): multipart batch
endpoint, accepts audio + optional reference + params[*]=v form fields.
Persists inputs alongside the output in GeneratedContentDir/audio so the
React UI history can replay past (audio, reference, output) triples.
- GET /audio/transformations/stream: WebSocket bidi, 16 ms PCM frames
(interleaved stereo mic+ref in, mono out). JSON session.update envelope
for config; constants hoisted in core/schema/audio_transform.go.
- ffmpeg-based input normalisation to 16 kHz mono s16 WAV via the existing
utils.AudioToWav (with passthrough fast-path), so the user can upload any
format / rate without seeing the model's strict 16 kHz constraint.
- BackendTraceAudioTransform integration so /api/backend-traces and the
Traces UI light up with audio_snippet base64 and timing.
- Routes registered under routes/localai.go (LocalAI extension; OpenAI has
no /audio/transformations endpoint), traced via TraceMiddleware.
Auth + capability + importer:
- FLAG_AUDIO_TRANSFORM (model_config.go), FeatureAudioTransform (default-on,
in APIFeatures), three RouteFeatureRegistry rows.
- localvqe added to knownPrefOnlyBackends with modality "audio-transform".
- Gallery entry localvqe-v1-1.3m (sha256-pinned, hosted on
huggingface.co/LocalAI-io/LocalVQE).
React UI:
- New /app/transform page surfaced via a dedicated "Enhance" sidebar
section (sibling of Tools / Biometrics) — the page is enhancement, not
generation, so it lives outside Studio. Two AudioInput components
(Upload + Record tabs, drag-drop, mic capture).
- Echo-test button: records mic while playing the loaded reference through
the speakers — the mic naturally picks up speaker bleed, giving a real
(mic, ref) pair for AEC testing without leaving the UI.
- Reusable WaveformPlayer (canvas peaks + click-to-seek + audio controls)
and useAudioPeaks hook (shared module-scoped AudioContext to avoid
hitting browser context limits with three players on one page); migrated
TTS, Sound, Traces audio blocks to use it.
- Past runs saved in localStorage via useMediaHistory('audio-transform') —
the history entry stores all three URLs so clicking re-renders the full
triple, not just the output.
Build + e2e:
- 11 matrix entries removed from .github/workflows/backend.yml (CUDA, ROCm,
SYCL, Metal, L4T): upstream supports only CPU + Vulkan, so we ship those
two and let GPU-class hardware route through Vulkan in the gallery
capabilities map.
- tests-localvqe-grpc-transform job in test-extra.yml (gated on
detect-changes.outputs.localvqe).
- New audio_transform capability + 4 specs in tests/e2e-backends.
- Playwright spec suite in core/http/react-ui/e2e/audio-transform.spec.js
(8 specs covering tabs, file upload, multipart shape, history, errors).
Docs:
- New docs/content/features/audio-transform.md covering the (audio,
reference) mental model, batch + WebSocket wire formats, LocalVQE param
keys, and a YAML config example. Cross-links from text-to-audio and
audio-to-text feature pages.
Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit Write Agent TaskCreate]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
|
||
|
Ettore Di Giacinto
|
8edac61e57 |
feat(ci): allow routing apt traffic through an alternate Ubuntu mirror (#9650)
* feat(ci): allow routing apt traffic through an alternate Ubuntu mirror
Adds opt-in APT_MIRROR / APT_PORTS_MIRROR knobs to all Dockerfiles, the
Makefile, and CI workflows so we can fail over to a non-canonical Ubuntu
mirror when archive.ubuntu.com / security.ubuntu.com / ports.ubuntu.com
are degraded (recently observed: multi-day DDoS against the default pool).
Defaults are empty everywhere — behavior is unchanged unless a mirror is
configured. To enable in CI, set the repo-level GitHub Actions variables
APT_MIRROR (and APT_PORTS_MIRROR for arm64 builds). Locally:
make docker APT_MIRROR=http://azure.archive.ubuntu.com
A small POSIX-sh helper in .docker/apt-mirror.sh rewrites both DEB822
(/etc/apt/sources.list.d/ubuntu.sources, Ubuntu 24.04+) and the legacy
/etc/apt/sources.list before the first apt-get update. Dockerfile stages
load it via RUN --mount=type=bind, so there is no extra layer and no
cache invalidation when the script is unchanged. Reusable workflows also
rewrite the runner's own /etc/apt sources before any sudo apt-get call.
Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci(apt-mirror): default to the Azure mirror, visible in the workflow source
Bakes Azure (http://azure.archive.ubuntu.com / http://azure.ports.ubuntu.com)
in as the default for both Docker builds and runner-side apt — rather than
hiding the URL behind a GitHub Actions repo variable that's not visible
from the source tree.
A new composite action at .github/actions/configure-apt-mirror is the
single source of truth for runner-side rewrites. Five standalone
workflows (build-test, release, tests-e2e, tests-ui-e2e, update_swagger)
just `uses: ./.github/actions/configure-apt-mirror`.
Three workflows (image_build, backend_build, checksum_checker) keep an
inline bash rewrite, because they install/upgrade git via apt *before*
the checkout step (so the local composite action isn't loadable yet).
The Azure URL is visible in those files too.
The `apt-mirror` / `apt-ports-mirror` inputs of the reusable workflows
keep their now-Azure defaults — they still feed the Docker build-args
block in addition to the inline runner-side rewrite. Callers (image.yml,
image-pr.yml, backend.yml, backend_pr.yml) drop the previous
`vars.APT_MIRROR` plumbing and rely on those defaults.
Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci(apt-mirror): drop Force Install GIT, consolidate on the composite action
The PPA git upgrade ran add-apt-repository ppa:git-core/ppa, which talks
to api.launchpad.net — also part of Canonical's infrastructure and
currently returning HTTP 504. The Azure mirror only covers
archive.ubuntu.com / security.ubuntu.com / ports.ubuntu.com, not PPAs.
The system git that ubuntu-latest already ships is sufficient for
actions/checkout and the build pipeline, so just drop the upgrade. With
that gone, the apt-before-checkout constraint disappears too — all three
holdouts (image_build, backend_build, checksum_checker) can now switch
to ./.github/actions/configure-apt-mirror like the other five.
Net: 0 inline apt-mirror blocks, all 8 workflows route through the
composite action.
Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
|
||
|
Russell Sim
|
18e039f305 |
fix(ci): fix AMDGPU_TARGETS empty-string bypass in hipblas builds (#9626)
* fix(ci): fix AMDGPU_TARGETS empty-string bypass in hipblas builds
|
||
|
Andreas Egli
|
1d0de757c3 |
fix: add hipblaslt library (#9541)
Signed-off-by: Andreas Egli <github@kharan.ch> |
||
|
Richard Palethorpe
|
f9a850c02a |
feat(realtime): WebRTC support (#8790)
* feat(realtime): WebRTC support Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(tracing): Show full LLM opts and deltas Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
||
|
Ettore Di Giacinto
|
bf5a1dd840 |
feat(voxtral): add voxtral backend (#8451)
* feat(voxtral): add voxtral backend Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * simplify Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Ettore Di Giacinto
|
7891c33cb1 |
chore(vulkan): bump vulkan-sdk to 1.4.335.0 (#7981)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Ettore Di Giacinto
|
917c7aa9f3 |
chore(ci): roll back l4t-cuda12 configurations (#7935)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Copilot
|
b2ff1cea2a |
feat: enable Vulkan arm64 image builds (#7912)
* Initial plan * Add arm64 support for Vulkan builds in Dockerfiles and workflows Co-authored-by: mudler <2420543+mudler@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: mudler <2420543+mudler@users.noreply.github.com> |
||
|
Richard Palethorpe
|
e6ba26c3e7 |
chore: Update to Ubuntu24.04 (cont #7423) (#7769)
* ci(workflows): bump GitHub Actions images to Ubuntu 24.04 Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * ci(workflows): remove CUDA 11.x support from GitHub Actions (incompatible with ubuntu:24.04) Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * ci(workflows): bump GitHub Actions CUDA support to 12.9 Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * build(docker): bump base image to ubuntu:24.04 and adjust Vulkan SDK/packages Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * fix(backend): correct context paths for Python backends in workflows, Makefile and Dockerfile Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * chore(make): disable parallel backend builds to avoid race conditions Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * chore(make): export CUDA_MAJOR_VERSION and CUDA_MINOR_VERSION for override Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * build(backend): update backend Dockerfiles to Ubuntu 24.04 Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * chore(backend): add ROCm env vars and default AMDGPU_TARGETS for hipBLAS builds Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * chore(chatterbox): bump ROCm PyTorch to 2.9.1+rocm6.4 and update index URL; align hipblas requirements Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * chore: add local-ai-launcher to .gitignore Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * ci(workflows): fix backends GitHub Actions workflows after rebase Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * build(docker): use build-time UBUNTU_VERSION variable Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * chore(docker): remove libquadmath0 from requirements-stage base image Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * chore(make): add backends/vllm to .NOTPARALLEL to prevent parallel builds Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * fix(docker): correct CUDA installation steps in backend Dockerfiles Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * chore(backend): update ROCm to 6.4 and align Python hipblas requirements Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * ci(workflows): switch GitHub Actions runners to Ubuntu-24.04 for CUDA on arm64 builds Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * build(docker): update base image and backend Dockerfiles for Ubuntu 24.04 compatibility on arm64 Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * build(backend): increase timeout for uv installs behind slow networks on backend/Dockerfile.python Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * ci(workflows): switch GitHub Actions runners to Ubuntu-24.04 for vibevoice backend Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * ci(workflows): fix failing GitHub Actions runners Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> * fix: Allow FROM_SOURCE to be unset, use upstream Intel images etc. Signed-off-by: Richard Palethorpe <io@richiejp.com> * chore(build): rm all traces of CUDA 11 Signed-off-by: Richard Palethorpe <io@richiejp.com> * chore(build): Add Ubuntu codename as an argument Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> Signed-off-by: Richard Palethorpe <io@richiejp.com> Co-authored-by: Alessandro Sturniolo <alessandro.sturniolo@gmail.com> |
||
|
Ettore Di Giacinto
|
edcbf82b31 | chore(ci): add wget | ||
|
Ettore Di Giacinto
|
6558caca85 | chore(ci): adapt also golang-based backends docker images | ||
|
Richard Palethorpe
|
c07bc55fee |
fix(intel): Set GPU vendor on Intel images and cleanup (#5945)
Signed-off-by: Richard Palethorpe <io@richiejp.com> |
||
|
Dave
|
9cecf5e7ac |
fix: rename Dockerfile.go --> Dockerfile.golang to avoid IDE errors (#5892)
extract up and out Dockerfile.go --> Dockerfile.golang rename. Prevents syntax highlighting and IDE errors Signed-off-by: Dave Lee <dave@gray101.com> |