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53 Commits

Author SHA1 Message Date
LocalAI [bot]
0b085089b9 chore: ⬆️ Update ggml-org/llama.cpp to daf2dd788066b8b239cb7f68210e090c2124c199 (#5951)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-08-01 08:25:36 +02:00
LocalAI [bot]
624f3b1fc8 feat(swagger): update swagger (#5950)
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-07-31 21:04:23 +00:00
Richard Palethorpe
c07bc55fee fix(intel): Set GPU vendor on Intel images and cleanup (#5945)
Signed-off-by: Richard Palethorpe <io@richiejp.com>
2025-07-31 19:44:46 +02:00
Ettore Di Giacinto
173e0774c0 chore(model gallery): add flux.1-krea-dev-ggml (#5949)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-31 18:32:06 +02:00
Ettore Di Giacinto
8ece26ab7c chore(model gallery): add flux.1-dev-ggml-abliterated-v2-q8_0 (#5948)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-31 17:23:48 +02:00
Ettore Di Giacinto
d704cc7970 chore(model gallery): add flux.1-dev-ggml-q8_0 (#5947)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-31 17:13:19 +02:00
Ettore Di Giacinto
ab17baaae1 chore(capability): improve messages (#5944)
* chore(capability): improve messages

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

* chore: isolate to constants, do not detect from the first gpu

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-31 16:25:19 +02:00
Ettore Di Giacinto
ca358fcdca feat(stablediffusion-ggml): allow to load loras (#5943)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-31 16:25:05 +02:00
Ettore Di Giacinto
9aadfd485f chore: update swagger (#5946)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-31 16:22:27 +02:00
LocalAI [bot]
da3b0850de chore: ⬆️ Update ggml-org/whisper.cpp to f7502dca872866a310fe69d30b163fa87d256319 (#5941)
⬆️ 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>
2025-07-31 09:26:30 +02:00
LocalAI [bot]
8b1e8b4cda chore: ⬆️ Update ggml-org/llama.cpp to e9192bec564780bd4313ad6524d20a0ab92797db (#5940)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-07-31 09:26:02 +02:00
Ettore Di Giacinto
3d22bfc27c feat(stablediffusion-ggml): add support to ref images (flux Kontext) (#5935)
* feat(stablediffusion-ggml): add support to ref images

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

* Add it to the model gallery

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-30 22:42:34 +02:00
Ettore Di Giacinto
4438b4361e chore(model gallery): add qwen_qwen3-30b-a3b-thinking-2507 (#5939)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-30 21:18:56 +02:00
Ettore Di Giacinto
04bad9a2da chore(model gallery): add arcee-ai_afm-4.5b (#5938)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-30 15:37:07 +02:00
Ettore Di Giacinto
8235e53602 chore(model gallery): add qwen_qwen3-30b-a3b-instruct-2507 (#5936)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-30 15:29:34 +02:00
LocalAI [bot]
eb5c3670f1 chore: ⬆️ Update ggml-org/llama.cpp to aa79524c51fb014f8df17069d31d7c44b9ea6cb8 (#5934)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-07-29 21:05:00 +00:00
LocalAI [bot]
89e61fca90 chore: ⬆️ Update ggml-org/whisper.cpp to d0a9d8c7f8f7b91c51d77bbaa394b915f79cde6b (#5932)
⬆️ 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>
2025-07-29 08:02:01 +02:00
LocalAI [bot]
9d6efe8842 chore: ⬆️ Update leejet/stable-diffusion.cpp to f6b9aa1a4373e322ff12c15b8a0749e6dd6f0253 (#5930)
⬆️ 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>
2025-07-29 08:01:30 +02:00
LocalAI [bot]
60726d16f2 chore: ⬆️ Update ggml-org/llama.cpp to 8ad7b3e65b5834e5574c2f5640056c9047b5d93b (#5931)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-07-29 08:01:03 +02:00
LocalAI [bot]
9d7ec09ec0 docs: ⬆️ update docs version mudler/LocalAI (#5929)
⬆️ 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>
2025-07-28 21:03:44 +00:00
Ettore Di Giacinto
36179ffbed fix(backend gallery): intel images for python-based backends, re-add exllama2 (#5928)
chore(backend gallery): fix intel images for python-based backends

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-28 15:15:19 +02:00
LocalAI [bot]
d25145e641 chore: ⬆️ Update ggml-org/llama.cpp to bf78f5439ee8e82e367674043303ebf8e92b4805 (#5927)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-07-27 21:08:32 +00:00
Ettore Di Giacinto
949e5b9be8 feat(rfdetr): add object detection API (#5923)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-27 22:02:51 +02:00
Ettore Di Giacinto
73ecb7f90b chore: drop assistants endpoint (#5926)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-27 21:06:09 +02:00
Ettore Di Giacinto
053bed6e5f feat: normalize search (#5925)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-27 11:51:28 +02:00
LocalAI [bot]
932360bf7e chore: ⬆️ Update ggml-org/llama.cpp to 11dd5a44eb180e1d69fac24d3852b5222d66fb7f (#5921)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-07-27 09:50:56 +02:00
LocalAI [bot]
6d0b52843f chore: ⬆️ Update ggml-org/whisper.cpp to e7bf0294ec9099b5fc21f5ba969805dfb2108cea (#5922)
⬆️ 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>
2025-07-27 09:42:28 +02:00
LocalAI [bot]
078c22f485 docs: ⬆️ update docs version mudler/LocalAI (#5920)
⬆️ 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>
2025-07-26 20:58:54 +00:00
Ettore Di Giacinto
6ef3852de5 chore(docs): fixup tag
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-26 21:25:07 +02:00
Ettore Di Giacinto
a8057b952c fix(cuda): be consistent with image tag naming (#5916)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-26 08:30:59 +02:00
Ettore Di Giacinto
fd5c1d916f chore(docs): add documentation on backend detection override (#5915)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-26 08:18:31 +02:00
LocalAI [bot]
5ce982b9c9 chore: ⬆️ Update ggml-org/llama.cpp to c7f3169cd523140a288095f2d79befb20a0b73f4 (#5913)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-07-25 23:08:20 +02:00
Ettore Di Giacinto
47ccfccf7a fix(ci): add nvidia-l4t capability to l4t images (#5914)
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2025-07-25 22:45:09 +02:00
LocalAI [bot]
a760f7ff39 docs: ⬆️ update docs version mudler/LocalAI (#5912)
⬆️ 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>
2025-07-25 22:15:16 +02:00
Ettore Di Giacinto
facf7625f3 fix(vulkan): use correct image suffix (#5911)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-25 19:20:20 +02:00
Ettore Di Giacinto
b3600b3c50 feat(backend gallery): add mirrors (#5910)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-25 19:20:08 +02:00
Ettore Di Giacinto
f0b47cfe6a fix(backends gallery): trim string when reading cap from file (#5909)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-25 18:10:02 +02:00
Ettore Di Giacinto
ee625fc34e fix(backends gallery): pass-by backend galleries to the model service (#5906)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-25 16:38:09 +02:00
Ettore Di Giacinto
693aa0b5de Update README.md
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2025-07-25 11:51:23 +02:00
Ettore Di Giacinto
3973e6e5da fix(install.sh): update to use the new binary naming (#5903)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-25 10:43:22 +02:00
LocalAI [bot]
fb6ec68090 chore: ⬆️ Update ggml-org/whisper.cpp to 7de8dd783f7b2eab56bff6bbc5d3369e34f0e77f (#5902)
⬆️ 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>
2025-07-25 08:40:24 +02:00
LocalAI [bot]
0301fc7c46 chore: ⬆️ Update leejet/stable-diffusion.cpp to eed97a5e1d054f9c1e7ac01982ae480411d4157e (#5901)
⬆️ 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>
2025-07-25 08:40:06 +02:00
LocalAI [bot]
813cb4296d chore: ⬆️ Update ggml-org/llama.cpp to 3f4fc97f1d745f1d5d3c853949503136d419e6de (#5900)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-07-25 08:39:44 +02:00
Ettore Di Giacinto
deda3a4972 Update build documentation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-24 22:53:08 +02:00
Ettore Di Giacinto
a28f27604a Update backends.md
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2025-07-24 16:18:25 +02:00
Richard Palethorpe
8fe9fa98f2 fix(stablediffusion-cpp): Switch back to upstream and update (#5880)
* sync(stablediffusion-cpp): Switch back to upstream and update

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

* fix(stablediffusion-ggml): NULL terminate options array to prevent segfault

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

* fix(build): Add BUILD_TYPE and BASE_IMAGE to all backends

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

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2025-07-24 16:03:18 +02:00
Nathaniel Hyson
4db1b80278 Update quickstart.md (#5898)
Fixed spelling mistake

Signed-off-by: Nathaniel Hyson <Shinrai@users.noreply.github.com>
2025-07-24 15:04:02 +02:00
Dave
b3c2a3c257 fix: untangle pkg and core (#5896)
* migrate core/system to pkg/system - it has no dependencies FROM core, and IS USED in pkg

Signed-off-by: Dave Lee <dave@gray101.com>

* move pkg/templates up to core/templates -- nothing in pkg references it, but it does reference core.

Signed-off-by: Dave Lee <dave@gray101.com>

* remove extra check, len of nil is 0

Signed-off-by: Dave Lee <dave@gray101.com>

* move pkg/startup to core/startup -- it does have important and unfixable dependencies on core

Signed-off-by: Dave Lee <dave@gray101.com>

---------

Signed-off-by: Dave Lee <dave@gray101.com>
2025-07-24 15:03:41 +02:00
LocalAI [bot]
61c2304638 chore: ⬆️ Update ggml-org/llama.cpp to a86f52b2859dae4db5a7a0bbc0f1ad9de6b43ec6 (#5894)
⬆️ Update ggml-org/llama.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2025-07-24 15:02:37 +02:00
Ettore Di Giacinto
92c5ab97e2 chore(Makefile): drop unused targets (#5893)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-24 14:49:50 +02:00
LocalAI [bot]
76e471441c chore: ⬆️ Update richiejp/stable-diffusion.cpp to 10c6501bd05a697e014f1bee3a84e5664290c489 (#5732)
⬆️ Update richiejp/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>
2025-07-23 21:09:02 +00:00
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>
2025-07-23 21:33:26 +02:00
Ettore Di Giacinto
b7b3164736 chore: try to speedup build
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-23 21:21:23 +02:00
103 changed files with 2992 additions and 3394 deletions

View File

@@ -381,24 +381,12 @@ jobs:
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
# sycl builds
- build-type: 'sycl_f32'
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-rerankers'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "rerankers"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f16'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f16-rerankers'
tag-suffix: '-gpu-intel-rerankers'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
@@ -429,60 +417,36 @@ jobs:
backend: "llama-cpp"
dockerfile: "./backend/Dockerfile.llama-cpp"
context: "./"
- build-type: 'sycl_f32'
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-vllm'
tag-suffix: '-gpu-intel-vllm'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "vllm"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f16'
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f16-vllm'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "vllm"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f32'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-transformers'
tag-suffix: '-gpu-intel-transformers'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "transformers"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f16'
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f16-transformers'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "transformers"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f32'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-diffusers'
tag-suffix: '-gpu-intel-diffusers'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
@@ -490,96 +454,48 @@ jobs:
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
# SYCL additional backends
- build-type: 'sycl_f32'
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-kokoro'
tag-suffix: '-gpu-intel-kokoro'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "kokoro"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f16'
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f16-kokoro'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "kokoro"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f32'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-faster-whisper'
tag-suffix: '-gpu-intel-faster-whisper'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "faster-whisper"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f16'
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f16-faster-whisper'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "faster-whisper"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f32'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-coqui'
tag-suffix: '-gpu-intel-coqui'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "coqui"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f16'
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f16-coqui'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "coqui"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f32'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f32-bark'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "bark"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'sycl_f16'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-sycl-f16-bark'
tag-suffix: '-gpu-intel-bark'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
@@ -597,7 +513,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "piper"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
# bark-cpp
- build-type: ''
@@ -610,7 +526,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "bark-cpp"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: ''
cuda-major-version: ""
@@ -659,7 +575,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "stablediffusion-ggml"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'cublas'
cuda-major-version: "12"
@@ -671,7 +587,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "stablediffusion-ggml"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'cublas'
cuda-major-version: "11"
@@ -683,7 +599,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "stablediffusion-ggml"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'sycl_f32'
cuda-major-version: ""
@@ -695,7 +611,7 @@ jobs:
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "stablediffusion-ggml"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'sycl_f16'
cuda-major-version: ""
@@ -707,7 +623,7 @@ jobs:
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "stablediffusion-ggml"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'vulkan'
cuda-major-version: ""
@@ -719,7 +635,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "stablediffusion-ggml"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'cublas'
cuda-major-version: "12"
@@ -731,7 +647,7 @@ jobs:
base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
runs-on: 'ubuntu-24.04-arm'
backend: "stablediffusion-ggml"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
# whisper
- build-type: ''
@@ -744,7 +660,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "whisper"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'cublas'
cuda-major-version: "12"
@@ -756,7 +672,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "whisper"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'cublas'
cuda-major-version: "11"
@@ -768,7 +684,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "whisper"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'sycl_f32'
cuda-major-version: ""
@@ -780,7 +696,7 @@ jobs:
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "whisper"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'sycl_f16'
cuda-major-version: ""
@@ -792,7 +708,7 @@ jobs:
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "whisper"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'vulkan'
cuda-major-version: ""
@@ -804,7 +720,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "whisper"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'cublas'
cuda-major-version: "12"
@@ -816,7 +732,7 @@ jobs:
base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
runs-on: 'ubuntu-24.04-arm'
backend: "whisper"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
- build-type: 'hipblas'
cuda-major-version: ""
@@ -828,7 +744,7 @@ jobs:
runs-on: 'ubuntu-latest'
skip-drivers: 'false'
backend: "whisper"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
#silero-vad
- build-type: ''
@@ -841,7 +757,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "silero-vad"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
# local-store
- build-type: ''
@@ -854,7 +770,7 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "local-store"
dockerfile: "./backend/Dockerfile.go"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
# huggingface
- build-type: ''
@@ -867,8 +783,143 @@ jobs:
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "huggingface"
dockerfile: "./backend/Dockerfile.go"
context: "./"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
# rfdetr
- build-type: ''
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: '-cpu-rfdetr'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "rfdetr"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-12-rfdetr'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "rfdetr"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-11-rfdetr'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "rfdetr"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-rfdetr'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "rfdetr"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/arm64'
skip-drivers: 'true'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-arm64-rfdetr'
base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
runs-on: 'ubuntu-24.04-arm'
backend: "rfdetr"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
# exllama2
- build-type: ''
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-cpu-exllama2'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "exllama2"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-12-exllama2'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "exllama2"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-11-exllama2'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
backend: "exllama2"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'intel'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-intel-exllama2'
runs-on: 'ubuntu-latest'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
skip-drivers: 'false'
backend: "exllama2"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
- build-type: 'hipblas'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
skip-drivers: 'true'
tag-latest: 'auto'
tag-suffix: '-gpu-hipblas-exllama2'
base-image: "rocm/dev-ubuntu-22.04:6.1"
runs-on: 'ubuntu-latest'
backend: "exllama2"
dockerfile: "./backend/Dockerfile.python"
context: "./backend"
# runs out of space on the runner
# - build-type: 'hipblas'
# cuda-major-version: ""
# cuda-minor-version: ""
# platforms: 'linux/amd64'
# tag-latest: 'auto'
# tag-suffix: '-gpu-hipblas-rfdetr'
# base-image: "rocm/dev-ubuntu-22.04:6.1"
# runs-on: 'ubuntu-latest'
# skip-drivers: 'false'
# backend: "rfdetr"
# dockerfile: "./backend/Dockerfile.python"
# context: "./backend"
llama-cpp-darwin:
runs-on: macOS-14
strategy:

View File

@@ -21,7 +21,7 @@ jobs:
variable: "BARKCPP_VERSION"
branch: "main"
file: "Makefile"
- repository: "richiejp/stable-diffusion.cpp"
- repository: "leejet/stable-diffusion.cpp"
variable: "STABLEDIFFUSION_GGML_VERSION"
branch: "master"
file: "backend/go/stablediffusion-ggml/Makefile"

View File

@@ -39,7 +39,7 @@ jobs:
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-gpu-nvidia-cuda12'
tag-suffix: '-gpu-nvidia-cuda-12'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
@@ -51,12 +51,12 @@ jobs:
grpc-base-image: "ubuntu:22.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
- build-type: 'sycl'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: 'sycl-f16'
tag-suffix: 'sycl'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'vulkan'

View File

@@ -83,7 +83,7 @@ jobs:
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda11'
tag-suffix: '-gpu-nvidia-cuda-11'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
@@ -94,7 +94,7 @@ jobs:
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda12'
tag-suffix: '-gpu-nvidia-cuda-12'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
@@ -103,30 +103,21 @@ jobs:
- build-type: 'vulkan'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-vulkan'
tag-suffix: '-gpu-vulkan'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
aio: "-aio-gpu-vulkan"
- build-type: 'sycl_f16'
- build-type: 'sycl'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-gpu-intel-f16'
tag-suffix: '-gpu-intel'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
aio: "-aio-gpu-intel-f16"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-gpu-intel-f32'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
aio: "-aio-gpu-intel-f32"
aio: "-aio-gpu-intel"
gh-runner:
uses: ./.github/workflows/image_build.yml

1
.gitignore vendored
View File

@@ -12,6 +12,7 @@ prepare-sources
/backends
/backend-images
/result.yaml
protoc
*.log

View File

@@ -72,6 +72,12 @@ RUN <<EOT bash
fi
EOT
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
echo "nvidia-l4t" > /run/localai/capability
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
@@ -94,6 +100,11 @@ RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
ldconfig \
; fi
RUN expr "${BUILD_TYPE}" : sycl && \
echo "intel" > /run/localai/capability || \
echo "Not Intel"
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}

155
Makefile
View File

@@ -5,8 +5,6 @@ BINARY_NAME=local-ai
GORELEASER?=
ONEAPI_VERSION?=2025.2
export BUILD_TYPE?=
GO_TAGS?=
@@ -145,7 +143,7 @@ backends/stablediffusion-ggml: docker-build-stablediffusion-ggml docker-save-sta
backends/whisper: docker-build-whisper docker-save-whisper build
./local-ai backends install "ocifile://$(abspath ./backend-images/whisper.tar)"
backends/silero-vad: docker-build-silero-vad docker-save-silero-vad build
./local-ai backends install "ocifile://$(abspath ./backend-images/silero-vad.tar)"
@@ -155,6 +153,9 @@ backends/local-store: docker-build-local-store docker-save-local-store build
backends/huggingface: docker-build-huggingface docker-save-huggingface build
./local-ai backends install "ocifile://$(abspath ./backend-images/huggingface.tar)"
backends/rfdetr: docker-build-rfdetr docker-save-rfdetr build
./local-ai backends install "ocifile://$(abspath ./backend-images/rfdetr.tar)"
########################################################
## AIO tests
########################################################
@@ -242,10 +243,7 @@ help: ## Show this help.
########################################################
.PHONY: protogen
protogen: protogen-go protogen-python
.PHONY: protogen-clean
protogen-clean: protogen-go-clean protogen-python-clean
protogen: protogen-go
protoc:
@OS_NAME=$$(uname -s | tr '[:upper:]' '[:lower:]'); \
@@ -290,93 +288,6 @@ protogen-go-clean:
$(RM) pkg/grpc/proto/backend.pb.go pkg/grpc/proto/backend_grpc.pb.go
$(RM) bin/*
.PHONY: protogen-python
protogen-python: bark-protogen coqui-protogen chatterbox-protogen diffusers-protogen exllama2-protogen rerankers-protogen transformers-protogen kokoro-protogen vllm-protogen faster-whisper-protogen
.PHONY: protogen-python-clean
protogen-python-clean: bark-protogen-clean coqui-protogen-clean chatterbox-protogen-clean diffusers-protogen-clean exllama2-protogen-clean rerankers-protogen-clean transformers-protogen-clean kokoro-protogen-clean vllm-protogen-clean faster-whisper-protogen-clean
.PHONY: bark-protogen
bark-protogen:
$(MAKE) -C backend/python/bark protogen
.PHONY: bark-protogen-clean
bark-protogen-clean:
$(MAKE) -C backend/python/bark protogen-clean
.PHONY: coqui-protogen
coqui-protogen:
$(MAKE) -C backend/python/coqui protogen
.PHONY: coqui-protogen-clean
coqui-protogen-clean:
$(MAKE) -C backend/python/coqui protogen-clean
.PHONY: diffusers-protogen
diffusers-protogen:
$(MAKE) -C backend/python/diffusers protogen
.PHONY: chatterbox-protogen
chatterbox-protogen:
$(MAKE) -C backend/python/chatterbox protogen
.PHONY: diffusers-protogen-clean
diffusers-protogen-clean:
$(MAKE) -C backend/python/diffusers protogen-clean
.PHONY: chatterbox-protogen-clean
chatterbox-protogen-clean:
$(MAKE) -C backend/python/chatterbox protogen-clean
.PHONY: faster-whisper-protogen
faster-whisper-protogen:
$(MAKE) -C backend/python/faster-whisper protogen
.PHONY: faster-whisper-protogen-clean
faster-whisper-protogen-clean:
$(MAKE) -C backend/python/faster-whisper protogen-clean
.PHONY: exllama2-protogen
exllama2-protogen:
$(MAKE) -C backend/python/exllama2 protogen
.PHONY: exllama2-protogen-clean
exllama2-protogen-clean:
$(MAKE) -C backend/python/exllama2 protogen-clean
.PHONY: rerankers-protogen
rerankers-protogen:
$(MAKE) -C backend/python/rerankers protogen
.PHONY: rerankers-protogen-clean
rerankers-protogen-clean:
$(MAKE) -C backend/python/rerankers protogen-clean
.PHONY: transformers-protogen
transformers-protogen:
$(MAKE) -C backend/python/transformers protogen
.PHONY: transformers-protogen-clean
transformers-protogen-clean:
$(MAKE) -C backend/python/transformers protogen-clean
.PHONY: kokoro-protogen
kokoro-protogen:
$(MAKE) -C backend/python/kokoro protogen
.PHONY: kokoro-protogen-clean
kokoro-protogen-clean:
$(MAKE) -C backend/python/kokoro protogen-clean
.PHONY: vllm-protogen
vllm-protogen:
$(MAKE) -C backend/python/vllm protogen
.PHONY: vllm-protogen-clean
vllm-protogen-clean:
$(MAKE) -C backend/python/vllm protogen-clean
prepare-test-extra: protogen-python
$(MAKE) -C backend/python/transformers
$(MAKE) -C backend/python/diffusers
@@ -412,7 +323,7 @@ docker-cuda11:
--build-arg GO_TAGS="$(GO_TAGS)" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
--build-arg BUILD_TYPE=$(BUILD_TYPE) \
-t $(DOCKER_IMAGE)-cuda11 .
-t $(DOCKER_IMAGE)-cuda-11 .
docker-aio:
@echo "Building AIO image with base $(BASE_IMAGE) as $(DOCKER_AIO_IMAGE)"
@@ -427,19 +338,11 @@ docker-aio-all:
docker-image-intel:
docker build \
--build-arg BASE_IMAGE=intel/oneapi-basekit:${ONEAPI_VERSION}.0-0-devel-ubuntu24.04 \
--build-arg BASE_IMAGE=quay.io/go-skynet/intel-oneapi-base:latest \
--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
--build-arg GO_TAGS="$(GO_TAGS)" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
--build-arg BUILD_TYPE=sycl_f32 -t $(DOCKER_IMAGE) .
docker-image-intel-xpu:
docker build \
--build-arg BASE_IMAGE=intel/oneapi-basekit:${ONEAPI_VERSION}.0-0-devel-ubuntu22.04 \
--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
--build-arg GO_TAGS="$(GO_TAGS)" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
--build-arg BUILD_TYPE=sycl_f32 -t $(DOCKER_IMAGE) .
--build-arg BUILD_TYPE=sycl -t $(DOCKER_IMAGE) .
########################################################
## Backends
@@ -449,19 +352,25 @@ backend-images:
mkdir -p backend-images
docker-build-llama-cpp:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg IMAGE_BASE=$(IMAGE_BASE) -t local-ai-backend:llama-cpp -f backend/Dockerfile.llama-cpp .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:llama-cpp -f backend/Dockerfile.llama-cpp .
docker-build-bark-cpp:
docker build -t local-ai-backend:bark-cpp -f backend/Dockerfile.go --build-arg BACKEND=bark-cpp .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:bark-cpp -f backend/Dockerfile.golang --build-arg BACKEND=bark-cpp .
docker-build-piper:
docker build -t local-ai-backend:piper -f backend/Dockerfile.go --build-arg BACKEND=piper .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:piper -f backend/Dockerfile.golang --build-arg BACKEND=piper .
docker-build-local-store:
docker build -t local-ai-backend:local-store -f backend/Dockerfile.go --build-arg BACKEND=local-store .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:local-store -f backend/Dockerfile.golang --build-arg BACKEND=local-store .
docker-build-huggingface:
docker build -t local-ai-backend:huggingface -f backend/Dockerfile.go --build-arg BACKEND=huggingface .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:huggingface -f backend/Dockerfile.golang --build-arg BACKEND=huggingface .
docker-build-rfdetr:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:rfdetr -f backend/Dockerfile.python --build-arg BACKEND=rfdetr ./backend
docker-save-rfdetr: backend-images
docker save local-ai-backend:rfdetr -o backend-images/rfdetr.tar
docker-save-huggingface: backend-images
docker save local-ai-backend:huggingface -o backend-images/huggingface.tar
@@ -470,7 +379,7 @@ docker-save-local-store: backend-images
docker save local-ai-backend:local-store -o backend-images/local-store.tar
docker-build-silero-vad:
docker build -t local-ai-backend:silero-vad -f backend/Dockerfile.go --build-arg BACKEND=silero-vad .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:silero-vad -f backend/Dockerfile.golang --build-arg BACKEND=silero-vad .
docker-save-silero-vad: backend-images
docker save local-ai-backend:silero-vad -o backend-images/silero-vad.tar
@@ -485,46 +394,46 @@ docker-save-bark-cpp: backend-images
docker save local-ai-backend:bark-cpp -o backend-images/bark-cpp.tar
docker-build-stablediffusion-ggml:
docker build -t local-ai-backend:stablediffusion-ggml -f backend/Dockerfile.go --build-arg BACKEND=stablediffusion-ggml .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:stablediffusion-ggml -f backend/Dockerfile.golang --build-arg BACKEND=stablediffusion-ggml .
docker-save-stablediffusion-ggml: backend-images
docker save local-ai-backend:stablediffusion-ggml -o backend-images/stablediffusion-ggml.tar
docker-build-rerankers:
docker build -t local-ai-backend:rerankers -f backend/Dockerfile.python --build-arg BACKEND=rerankers .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:rerankers -f backend/Dockerfile.python --build-arg BACKEND=rerankers .
docker-build-vllm:
docker build -t local-ai-backend:vllm -f backend/Dockerfile.python --build-arg BACKEND=vllm .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:vllm -f backend/Dockerfile.python --build-arg BACKEND=vllm .
docker-build-transformers:
docker build -t local-ai-backend:transformers -f backend/Dockerfile.python --build-arg BACKEND=transformers .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:transformers -f backend/Dockerfile.python --build-arg BACKEND=transformers .
docker-build-diffusers:
docker build -t local-ai-backend:diffusers -f backend/Dockerfile.python --build-arg BACKEND=diffusers .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:diffusers -f backend/Dockerfile.python --build-arg BACKEND=diffusers .
docker-build-kokoro:
docker build -t local-ai-backend:kokoro -f backend/Dockerfile.python --build-arg BACKEND=kokoro .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:kokoro -f backend/Dockerfile.python --build-arg BACKEND=kokoro .
docker-build-whisper:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:whisper -f backend/Dockerfile.go --build-arg BACKEND=whisper .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:whisper -f backend/Dockerfile.golang --build-arg BACKEND=whisper .
docker-save-whisper: backend-images
docker save local-ai-backend:whisper -o backend-images/whisper.tar
docker-build-faster-whisper:
docker build -t local-ai-backend:faster-whisper -f backend/Dockerfile.python --build-arg BACKEND=faster-whisper .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:faster-whisper -f backend/Dockerfile.python --build-arg BACKEND=faster-whisper .
docker-build-coqui:
docker build -t local-ai-backend:coqui -f backend/Dockerfile.python --build-arg BACKEND=coqui .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:coqui -f backend/Dockerfile.python --build-arg BACKEND=coqui .
docker-build-bark:
docker build -t local-ai-backend:bark -f backend/Dockerfile.python --build-arg BACKEND=bark .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:bark -f backend/Dockerfile.python --build-arg BACKEND=bark .
docker-build-chatterbox:
docker build -t local-ai-backend:chatterbox -f backend/Dockerfile.python --build-arg BACKEND=chatterbox .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:chatterbox -f backend/Dockerfile.python --build-arg BACKEND=chatterbox .
docker-build-exllama2:
docker build -t local-ai-backend:exllama2 -f backend/Dockerfile.python --build-arg BACKEND=exllama2 .
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:exllama2 -f backend/Dockerfile.python --build-arg BACKEND=exllama2 .
docker-build-backends: docker-build-llama-cpp docker-build-rerankers docker-build-vllm docker-build-transformers docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-bark docker-build-chatterbox docker-build-exllama2

View File

@@ -140,11 +140,7 @@ docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri
### Intel GPU Images (oneAPI):
```bash
# Intel GPU with FP16 support
docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel-f16
# Intel GPU with FP32 support
docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel-f32
docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel
```
### Vulkan GPU Images:
@@ -166,7 +162,7 @@ docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-ai
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-11
# Intel GPU version
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-gpu-intel-f16
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-gpu-intel
# AMD GPU version
docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-aio-gpu-hipblas
@@ -189,10 +185,14 @@ local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
local-ai run oci://localai/phi-2:latest
```
> ⚡ **Automatic Backend Detection**: When you install models from the gallery or YAML files, LocalAI automatically detects your system's GPU capabilities (NVIDIA, AMD, Intel) and downloads the appropriate backend. For advanced configuration options, see [GPU Acceleration](https://localai.io/features/gpu-acceleration/#automatic-backend-detection).
For more information, see [💻 Getting started](https://localai.io/basics/getting_started/index.html)
## 📰 Latest project news
- July/August 2025: 🔍 [Object Detection](https://localai.io/features/object-detection/) added to the API featuring [rf-detr](https://github.com/roboflow/rf-detr)
- July 2025: All backends migrated outside of the main binary. LocalAI is now more lightweight, small, and automatically downloads the required backend to run the model. [Read the release notes](https://github.com/mudler/LocalAI/releases/tag/v3.2.0)
- June 2025: [Backend management](https://github.com/mudler/LocalAI/pull/5607) has been added. Attention: extras images are going to be deprecated from the next release! Read [the backend management PR](https://github.com/mudler/LocalAI/pull/5607).
- May 2025: [Audio input](https://github.com/mudler/LocalAI/pull/5466) and [Reranking](https://github.com/mudler/LocalAI/pull/5396) in llama.cpp backend, [Realtime API](https://github.com/mudler/LocalAI/pull/5392), Support to Gemma, SmollVLM, and more multimodal models (available in the gallery).
- May 2025: Important: image name changes [See release](https://github.com/mudler/LocalAI/releases/tag/v2.29.0)
@@ -225,6 +225,7 @@ Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3A
- ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/)
- 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
- 🥽 [Vision API](https://localai.io/features/gpt-vision/)
- 🔍 [Object Detection](https://localai.io/features/object-detection/)
- 📈 [Reranker API](https://localai.io/features/reranker/)
- 🆕🖧 [P2P Inferencing](https://localai.io/features/distribute/)
- [Agentic capabilities](https://github.com/mudler/LocalAGI)

View File

@@ -96,17 +96,6 @@ RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
ldconfig \
; fi
# Intel oneAPI requirements
RUN <<EOT bash
if [[ "${BUILD_TYPE}" == sycl* ]] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
intel-oneapi-runtime-libs && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin:/usr/local/bin

View File

@@ -20,6 +20,7 @@ service Backend {
rpc SoundGeneration(SoundGenerationRequest) returns (Result) {}
rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
rpc Status(HealthMessage) returns (StatusResponse) {}
rpc Detect(DetectOptions) returns (DetectResponse) {}
rpc StoresSet(StoresSetOptions) returns (Result) {}
rpc StoresDelete(StoresDeleteOptions) returns (Result) {}
@@ -304,6 +305,9 @@ message GenerateImageRequest {
// Diffusers
string EnableParameters = 10;
int32 CLIPSkip = 11;
// Reference images for models that support them (e.g., Flux Kontext)
repeated string ref_images = 12;
}
message GenerateVideoRequest {
@@ -376,3 +380,20 @@ message Message {
string role = 1;
string content = 2;
}
message DetectOptions {
string src = 1;
}
message Detection {
float x = 1;
float y = 2;
float width = 3;
float height = 4;
float confidence = 5;
string class_name = 6;
}
message DetectResponse {
repeated Detection Detections = 1;
}

View File

@@ -1,5 +1,5 @@
LLAMA_VERSION?=acd6cb1c41676f6bbb25c2a76fa5abeb1719301e
LLAMA_VERSION?=daf2dd788066b8b239cb7f68210e090c2124c199
LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
CMAKE_ARGS?=
@@ -7,6 +7,7 @@ BUILD_TYPE?=
NATIVE?=false
ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
TARGET?=--target grpc-server
JOBS?=$(shell nproc)
# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF -DLLAMA_CURL=OFF
@@ -25,7 +26,7 @@ else ifeq ($(BUILD_TYPE),openblas)
# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
else ifeq ($(BUILD_TYPE),clblas)
CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
else ifeq ($(BUILD_TYPE),hipblas)
ROCM_HOME ?= /opt/rocm
ROCM_PATH ?= /opt/rocm
@@ -160,8 +161,8 @@ grpc-server: llama.cpp llama.cpp/tools/grpc-server
@echo "Building grpc-server with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
ifneq (,$(findstring sycl,$(BUILD_TYPE)))
+bash -c "source $(ONEAPI_VARS); \
cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release $(TARGET)"
cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release -j $(JOBS) $(TARGET)"
else
+cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release $(TARGET)
+cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release -j $(JOBS) $(TARGET)
endif
cp llama.cpp/build/bin/grpc-server .

View File

@@ -18,8 +18,8 @@ GO_TAGS?=
LD_FLAGS?=
# stablediffusion.cpp (ggml)
STABLEDIFFUSION_GGML_REPO?=https://github.com/richiejp/stable-diffusion.cpp
STABLEDIFFUSION_GGML_VERSION?=53e3b17eb3d0b5760ced06a1f98320b68b34aaae
STABLEDIFFUSION_GGML_REPO?=https://github.com/leejet/stable-diffusion.cpp
STABLEDIFFUSION_GGML_VERSION?=f6b9aa1a4373e322ff12c15b8a0749e6dd6f0253
# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
@@ -91,23 +91,18 @@ endif
# (ggml can have different backends cpu, cuda, etc., each backend generates a .a archive)
GGML_ARCHIVE_DIR := build/ggml/src/
ALL_ARCHIVES := $(shell find $(GGML_ARCHIVE_DIR) -type f -name '*.a')
ALL_OBJS := $(shell find $(GGML_ARCHIVE_DIR) -type f -name '*.o')
# Name of the single merged library
COMBINED_LIB := libggmlall.a
# Rule to merge all the .a files into one
# Instead of using the archives generated by GGML, use the object files directly to avoid overwriting objects with the same base name
$(COMBINED_LIB): $(ALL_ARCHIVES)
@echo "Merging all .a into $(COMBINED_LIB)"
@echo "Merging all .o into $(COMBINED_LIB): $(ALL_OBJS)"
rm -f $@
mkdir -p merge-tmp
for a in $(ALL_ARCHIVES); do \
( cd merge-tmp && ar x ../$$a ); \
done
( cd merge-tmp && ar rcs ../$@ *.o )
ar -qc $@ $(ALL_OBJS)
# Ensure we have a proper index
ranlib $@
# Clean up
rm -rf merge-tmp
build/libstable-diffusion.a:
@echo "Building SD with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"

View File

@@ -5,6 +5,7 @@
#include <random>
#include <string>
#include <vector>
#include <filesystem>
#include "gosd.h"
// #include "preprocessing.hpp"
@@ -53,9 +54,43 @@ sd_ctx_t* sd_c;
sample_method_t sample_method;
int load_model(char *model, char* options[], int threads, int diff) {
// Copied from the upstream CLI
void sd_log_cb(enum sd_log_level_t level, const char* log, void* data) {
//SDParams* params = (SDParams*)data;
const char* level_str;
if (!log /*|| (!params->verbose && level <= SD_LOG_DEBUG)*/) {
return;
}
switch (level) {
case SD_LOG_DEBUG:
level_str = "DEBUG";
break;
case SD_LOG_INFO:
level_str = "INFO";
break;
case SD_LOG_WARN:
level_str = "WARN";
break;
case SD_LOG_ERROR:
level_str = "ERROR";
break;
default: /* Potential future-proofing */
level_str = "?????";
break;
}
fprintf(stderr, "[%-5s] ", level_str);
fputs(log, stderr);
fflush(stderr);
}
int load_model(char *model, char *model_path, char* options[], int threads, int diff) {
fprintf (stderr, "Loading model!\n");
sd_set_log_callback(sd_log_cb, NULL);
char *stableDiffusionModel = "";
if (diff == 1 ) {
stableDiffusionModel = model;
@@ -69,6 +104,10 @@ int load_model(char *model, char* options[], int threads, int diff) {
char *vae_path = "";
char *scheduler = "";
char *sampler = "";
char *lora_dir = model_path;
bool lora_dir_allocated = false;
fprintf(stderr, "parsing options\n");
// If options is not NULL, parse options
for (int i = 0; options[i] != NULL; i++) {
@@ -96,12 +135,29 @@ int load_model(char *model, char* options[], int threads, int diff) {
if (!strcmp(optname, "sampler")) {
sampler = optval;
}
if (!strcmp(optname, "lora_dir")) {
// Path join with model dir
if (model_path && strlen(model_path) > 0) {
std::filesystem::path model_path_str(model_path);
std::filesystem::path lora_path(optval);
std::filesystem::path full_lora_path = model_path_str / lora_path;
lora_dir = strdup(full_lora_path.string().c_str());
lora_dir_allocated = true;
fprintf(stderr, "Lora dir resolved to: %s\n", lora_dir);
} else {
lora_dir = optval;
fprintf(stderr, "No model path provided, using lora dir as-is: %s\n", lora_dir);
}
}
}
fprintf(stderr, "parsed options\n");
int sample_method_found = -1;
for (int m = 0; m < N_SAMPLE_METHODS; m++) {
for (int m = 0; m < SAMPLE_METHOD_COUNT; m++) {
if (!strcmp(sampler, sample_method_str[m])) {
sample_method_found = m;
fprintf(stderr, "Found sampler: %s\n", sampler);
}
}
if (sample_method_found == -1) {
@@ -111,7 +167,7 @@ int load_model(char *model, char* options[], int threads, int diff) {
sample_method = (sample_method_t)sample_method_found;
int schedule_found = -1;
for (int d = 0; d < N_SCHEDULES; d++) {
for (int d = 0; d < SCHEDULE_COUNT; d++) {
if (!strcmp(scheduler, schedule_str[d])) {
schedule_found = d;
fprintf (stderr, "Found scheduler: %s\n", scheduler);
@@ -125,43 +181,50 @@ int load_model(char *model, char* options[], int threads, int diff) {
}
schedule_t schedule = (schedule_t)schedule_found;
fprintf (stderr, "Creating context\n");
sd_ctx_t* sd_ctx = new_sd_ctx(model,
clip_l_path,
clip_g_path,
t5xxl_path,
stableDiffusionModel,
vae_path,
"",
"",
"",
"",
"",
false,
false,
false,
threads,
SD_TYPE_COUNT,
STD_DEFAULT_RNG,
schedule,
false,
false,
false,
false);
sd_ctx_params_t ctx_params;
sd_ctx_params_init(&ctx_params);
ctx_params.model_path = model;
ctx_params.clip_l_path = clip_l_path;
ctx_params.clip_g_path = clip_g_path;
ctx_params.t5xxl_path = t5xxl_path;
ctx_params.diffusion_model_path = stableDiffusionModel;
ctx_params.vae_path = vae_path;
ctx_params.taesd_path = "";
ctx_params.control_net_path = "";
ctx_params.lora_model_dir = lora_dir;
ctx_params.embedding_dir = "";
ctx_params.stacked_id_embed_dir = "";
ctx_params.vae_decode_only = false;
ctx_params.vae_tiling = false;
ctx_params.free_params_immediately = false;
ctx_params.n_threads = threads;
ctx_params.rng_type = STD_DEFAULT_RNG;
ctx_params.schedule = schedule;
sd_ctx_t* sd_ctx = new_sd_ctx(&ctx_params);
if (sd_ctx == NULL) {
fprintf (stderr, "failed loading model (generic error)\n");
// Clean up allocated memory
if (lora_dir_allocated && lora_dir) {
free(lora_dir);
}
return 1;
}
fprintf (stderr, "Created context: OK\n");
sd_c = sd_ctx;
// Clean up allocated memory
if (lora_dir_allocated && lora_dir) {
free(lora_dir);
}
return 0;
}
int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed , char *dst, float cfg_scale) {
int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed , char *dst, float cfg_scale, char *src_image, float strength, char *mask_image, char **ref_images, int ref_images_count) {
sd_image_t* results;
@@ -169,37 +232,202 @@ int gen_image(char *text, char *negativeText, int width, int height, int steps,
fprintf (stderr, "Generating image\n");
results = txt2img(sd_c,
text,
negativeText,
-1, //clip_skip
cfg_scale, // sfg_scale
3.5f,
0, // eta
width,
height,
sample_method,
steps,
seed,
1,
NULL,
0.9f,
20.f,
false,
"",
skip_layers.data(),
skip_layers.size(),
0,
0.01,
0.2);
sd_img_gen_params_t p;
sd_img_gen_params_init(&p);
p.prompt = text;
p.negative_prompt = negativeText;
p.guidance.txt_cfg = cfg_scale;
p.guidance.slg.layers = skip_layers.data();
p.guidance.slg.layer_count = skip_layers.size();
p.width = width;
p.height = height;
p.sample_method = sample_method;
p.sample_steps = steps;
p.seed = seed;
p.input_id_images_path = "";
// Handle input image for img2img
bool has_input_image = (src_image != NULL && strlen(src_image) > 0);
bool has_mask_image = (mask_image != NULL && strlen(mask_image) > 0);
uint8_t* input_image_buffer = NULL;
uint8_t* mask_image_buffer = NULL;
std::vector<uint8_t> default_mask_image_vec;
if (has_input_image) {
fprintf(stderr, "Loading input image: %s\n", src_image);
int c = 0;
int img_width = 0;
int img_height = 0;
input_image_buffer = stbi_load(src_image, &img_width, &img_height, &c, 3);
if (input_image_buffer == NULL) {
fprintf(stderr, "Failed to load input image from '%s'\n", src_image);
return 1;
}
if (c < 3) {
fprintf(stderr, "Input image must have at least 3 channels, got %d\n", c);
free(input_image_buffer);
return 1;
}
// Resize input image if dimensions don't match
if (img_width != width || img_height != height) {
fprintf(stderr, "Resizing input image from %dx%d to %dx%d\n", img_width, img_height, width, height);
uint8_t* resized_image_buffer = (uint8_t*)malloc(height * width * 3);
if (resized_image_buffer == NULL) {
fprintf(stderr, "Failed to allocate memory for resized image\n");
free(input_image_buffer);
return 1;
}
stbir_resize(input_image_buffer, img_width, img_height, 0,
resized_image_buffer, width, height, 0, STBIR_TYPE_UINT8,
3, STBIR_ALPHA_CHANNEL_NONE, 0,
STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP,
STBIR_FILTER_BOX, STBIR_FILTER_BOX,
STBIR_COLORSPACE_SRGB, nullptr);
free(input_image_buffer);
input_image_buffer = resized_image_buffer;
}
p.init_image = {(uint32_t)width, (uint32_t)height, 3, input_image_buffer};
p.strength = strength;
fprintf(stderr, "Using img2img with strength: %.2f\n", strength);
} else {
// No input image, use empty image for text-to-image
p.init_image = {(uint32_t)width, (uint32_t)height, 3, NULL};
p.strength = 0.0f;
}
// Handle mask image for inpainting
if (has_mask_image) {
fprintf(stderr, "Loading mask image: %s\n", mask_image);
int c = 0;
int mask_width = 0;
int mask_height = 0;
mask_image_buffer = stbi_load(mask_image, &mask_width, &mask_height, &c, 1);
if (mask_image_buffer == NULL) {
fprintf(stderr, "Failed to load mask image from '%s'\n", mask_image);
if (input_image_buffer) free(input_image_buffer);
return 1;
}
// Resize mask if dimensions don't match
if (mask_width != width || mask_height != height) {
fprintf(stderr, "Resizing mask image from %dx%d to %dx%d\n", mask_width, mask_height, width, height);
uint8_t* resized_mask_buffer = (uint8_t*)malloc(height * width);
if (resized_mask_buffer == NULL) {
fprintf(stderr, "Failed to allocate memory for resized mask\n");
free(mask_image_buffer);
if (input_image_buffer) free(input_image_buffer);
return 1;
}
stbir_resize(mask_image_buffer, mask_width, mask_height, 0,
resized_mask_buffer, width, height, 0, STBIR_TYPE_UINT8,
1, STBIR_ALPHA_CHANNEL_NONE, 0,
STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP,
STBIR_FILTER_BOX, STBIR_FILTER_BOX,
STBIR_COLORSPACE_SRGB, nullptr);
free(mask_image_buffer);
mask_image_buffer = resized_mask_buffer;
}
p.mask_image = {(uint32_t)width, (uint32_t)height, 1, mask_image_buffer};
fprintf(stderr, "Using inpainting with mask\n");
} else {
// No mask image, create default full mask
default_mask_image_vec.resize(width * height, 255);
p.mask_image = {(uint32_t)width, (uint32_t)height, 1, default_mask_image_vec.data()};
}
// Handle reference images
std::vector<sd_image_t> ref_images_vec;
std::vector<uint8_t*> ref_image_buffers;
if (ref_images_count > 0 && ref_images != NULL) {
fprintf(stderr, "Loading %d reference images\n", ref_images_count);
for (int i = 0; i < ref_images_count; i++) {
if (ref_images[i] == NULL || strlen(ref_images[i]) == 0) {
continue;
}
fprintf(stderr, "Loading reference image %d: %s\n", i + 1, ref_images[i]);
int c = 0;
int ref_width = 0;
int ref_height = 0;
uint8_t* ref_image_buffer = stbi_load(ref_images[i], &ref_width, &ref_height, &c, 3);
if (ref_image_buffer == NULL) {
fprintf(stderr, "Failed to load reference image from '%s'\n", ref_images[i]);
continue;
}
if (c < 3) {
fprintf(stderr, "Reference image must have at least 3 channels, got %d\n", c);
free(ref_image_buffer);
continue;
}
// Resize reference image if dimensions don't match
if (ref_width != width || ref_height != height) {
fprintf(stderr, "Resizing reference image from %dx%d to %dx%d\n", ref_width, ref_height, width, height);
uint8_t* resized_ref_buffer = (uint8_t*)malloc(height * width * 3);
if (resized_ref_buffer == NULL) {
fprintf(stderr, "Failed to allocate memory for resized reference image\n");
free(ref_image_buffer);
continue;
}
stbir_resize(ref_image_buffer, ref_width, ref_height, 0,
resized_ref_buffer, width, height, 0, STBIR_TYPE_UINT8,
3, STBIR_ALPHA_CHANNEL_NONE, 0,
STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP,
STBIR_FILTER_BOX, STBIR_FILTER_BOX,
STBIR_COLORSPACE_SRGB, nullptr);
free(ref_image_buffer);
ref_image_buffer = resized_ref_buffer;
}
ref_image_buffers.push_back(ref_image_buffer);
ref_images_vec.push_back({(uint32_t)width, (uint32_t)height, 3, ref_image_buffer});
}
if (!ref_images_vec.empty()) {
p.ref_images = ref_images_vec.data();
p.ref_images_count = ref_images_vec.size();
fprintf(stderr, "Using %zu reference images\n", ref_images_vec.size());
}
}
results = generate_image(sd_c, &p);
if (results == NULL) {
fprintf (stderr, "NO results\n");
if (input_image_buffer) free(input_image_buffer);
if (mask_image_buffer) free(mask_image_buffer);
for (auto buffer : ref_image_buffers) {
if (buffer) free(buffer);
}
return 1;
}
if (results[0].data == NULL) {
fprintf (stderr, "Results with no data\n");
if (input_image_buffer) free(input_image_buffer);
if (mask_image_buffer) free(mask_image_buffer);
for (auto buffer : ref_image_buffers) {
if (buffer) free(buffer);
}
return 1;
}
@@ -215,11 +443,15 @@ int gen_image(char *text, char *negativeText, int width, int height, int steps,
results[0].data, 0, NULL);
fprintf (stderr, "Saved resulting image to '%s'\n", dst);
// TODO: free results. Why does it crash?
// Clean up
free(results[0].data);
results[0].data = NULL;
free(results);
if (input_image_buffer) free(input_image_buffer);
if (mask_image_buffer) free(mask_image_buffer);
for (auto buffer : ref_image_buffers) {
if (buffer) free(buffer);
}
fprintf (stderr, "gen_image is done", dst);
return 0;

View File

@@ -29,16 +29,21 @@ func (sd *SDGGML) Load(opts *pb.ModelOptions) error {
sd.threads = int(opts.Threads)
modelPath := opts.ModelPath
modelFile := C.CString(opts.ModelFile)
defer C.free(unsafe.Pointer(modelFile))
modelPathC := C.CString(modelPath)
defer C.free(unsafe.Pointer(modelPathC))
var options **C.char
// prepare the options array to pass to C
size := C.size_t(unsafe.Sizeof((*C.char)(nil)))
length := C.size_t(len(opts.Options))
options = (**C.char)(C.malloc(length * size))
view := (*[1 << 30]*C.char)(unsafe.Pointer(options))[0:len(opts.Options):len(opts.Options)]
options = (**C.char)(C.malloc((length + 1) * size))
view := (*[1 << 30]*C.char)(unsafe.Pointer(options))[0 : len(opts.Options)+1 : len(opts.Options)+1]
var diffusionModel int
@@ -66,10 +71,11 @@ func (sd *SDGGML) Load(opts *pb.ModelOptions) error {
for i, x := range oo {
view[i] = C.CString(x)
}
view[len(oo)] = nil
sd.cfgScale = opts.CFGScale
ret := C.load_model(modelFile, options, C.int(opts.Threads), C.int(diffusionModel))
ret := C.load_model(modelFile, modelPathC, options, C.int(opts.Threads), C.int(diffusionModel))
if ret != 0 {
return fmt.Errorf("could not load model")
}
@@ -87,7 +93,56 @@ func (sd *SDGGML) GenerateImage(opts *pb.GenerateImageRequest) error {
negative := C.CString(opts.NegativePrompt)
defer C.free(unsafe.Pointer(negative))
ret := C.gen_image(t, negative, C.int(opts.Width), C.int(opts.Height), C.int(opts.Step), C.int(opts.Seed), dst, C.float(sd.cfgScale))
// Handle source image path
var srcImage *C.char
if opts.Src != "" {
srcImage = C.CString(opts.Src)
defer C.free(unsafe.Pointer(srcImage))
}
// Handle mask image path
var maskImage *C.char
if opts.EnableParameters != "" {
// Parse EnableParameters for mask path if provided
// This is a simple approach - in a real implementation you might want to parse JSON
if strings.Contains(opts.EnableParameters, "mask:") {
parts := strings.Split(opts.EnableParameters, "mask:")
if len(parts) > 1 {
maskPath := strings.TrimSpace(parts[1])
if maskPath != "" {
maskImage = C.CString(maskPath)
defer C.free(unsafe.Pointer(maskImage))
}
}
}
}
// Handle reference images
var refImages **C.char
var refImagesCount C.int
if len(opts.RefImages) > 0 {
refImagesCount = C.int(len(opts.RefImages))
// Allocate array of C strings
size := C.size_t(unsafe.Sizeof((*C.char)(nil)))
refImages = (**C.char)(C.malloc((C.size_t(len(opts.RefImages)) + 1) * size))
view := (*[1 << 30]*C.char)(unsafe.Pointer(refImages))[0 : len(opts.RefImages)+1 : len(opts.RefImages)+1]
for i, refImagePath := range opts.RefImages {
view[i] = C.CString(refImagePath)
defer C.free(unsafe.Pointer(view[i]))
}
view[len(opts.RefImages)] = nil
}
// Default strength for img2img (0.75 is a good default)
strength := C.float(0.75)
if opts.Src != "" {
// If we have a source image, use img2img mode
// You could also parse strength from EnableParameters if needed
strength = C.float(0.75)
}
ret := C.gen_image(t, negative, C.int(opts.Width), C.int(opts.Height), C.int(opts.Step), C.int(opts.Seed), dst, C.float(sd.cfgScale), srcImage, strength, maskImage, refImages, refImagesCount)
if ret != 0 {
return fmt.Errorf("inference failed")
}

View File

@@ -1,8 +1,8 @@
#ifdef __cplusplus
extern "C" {
#endif
int load_model(char *model, char* options[], int threads, int diffusionModel);
int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed, char *dst, float cfg_scale);
int load_model(char *model, char *model_path, char* options[], int threads, int diffusionModel);
int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed, char *dst, float cfg_scale, char *src_image, float strength, char *mask_image, char **ref_images, int ref_images_count);
#ifdef __cplusplus
}
#endif

View File

@@ -6,7 +6,7 @@ CMAKE_ARGS?=
# whisper.cpp version
WHISPER_REPO?=https://github.com/ggml-org/whisper.cpp
WHISPER_CPP_VERSION?=1f5cf0b2888402d57bb17b2029b2caa97e5f3baf
WHISPER_CPP_VERSION?=f7502dca872866a310fe69d30b163fa87d256319
export WHISPER_CMAKE_ARGS?=-DBUILD_SHARED_LIBS=OFF
export WHISPER_DIR=$(abspath ./sources/whisper.cpp)

View File

@@ -73,6 +73,28 @@
nvidia-l4t: "nvidia-l4t-arm64-stablediffusion-ggml"
# metal: "metal-stablediffusion-ggml"
# darwin-x86: "darwin-x86-stablediffusion-ggml"
- &rfdetr
name: "rfdetr"
alias: "rfdetr"
license: apache-2.0
icon: https://avatars.githubusercontent.com/u/53104118?s=200&v=4
description: |
RF-DETR is a real-time, transformer-based object detection model architecture developed by Roboflow and released under the Apache 2.0 license.
RF-DETR is the first real-time model to exceed 60 AP on the Microsoft COCO benchmark alongside competitive performance at base sizes. It also achieves state-of-the-art performance on RF100-VL, an object detection benchmark that measures model domain adaptability to real world problems. RF-DETR is fastest and most accurate for its size when compared current real-time objection models.
RF-DETR is small enough to run on the edge using Inference, making it an ideal model for deployments that need both strong accuracy and real-time performance.
urls:
- https://github.com/roboflow/rf-detr
tags:
- object-detection
- rfdetr
- gpu
- cpu
capabilities:
nvidia: "cuda12-rfdetr"
intel: "intel-rfdetr"
#amd: "rocm-rfdetr"
nvidia-l4t: "nvidia-l4t-arm64-rfdetr"
default: "cpu-rfdetr"
- &vllm
name: "vllm"
license: apache-2.0
@@ -104,13 +126,13 @@
capabilities:
nvidia: "cuda12-vllm"
amd: "rocm-vllm"
intel: "intel-sycl-f16-vllm"
intel: "intel-vllm"
- &rerankers
name: "rerankers"
alias: "rerankers"
capabilities:
nvidia: "cuda12-rerankers"
intel: "intel-sycl-f16-rerankers"
intel: "intel-rerankers"
amd: "rocm-rerankers"
- &transformers
name: "transformers"
@@ -127,7 +149,7 @@
- multimodal
capabilities:
nvidia: "cuda12-transformers"
intel: "intel-sycl-f16-transformers"
intel: "intel-transformers"
amd: "rocm-transformers"
- &diffusers
name: "diffusers"
@@ -144,7 +166,7 @@
alias: "diffusers"
capabilities:
nvidia: "cuda12-diffusers"
intel: "intel-sycl-f32-diffusers"
intel: "intel-diffusers"
amd: "rocm-diffusers"
- &exllama2
name: "exllama2"
@@ -160,8 +182,7 @@
alias: "exllama2"
capabilities:
nvidia: "cuda12-exllama2"
intel: "intel-sycl-f32-exllama2"
amd: "rocm-exllama2"
intel: "intel-exllama2"
- &faster-whisper
icon: https://avatars.githubusercontent.com/u/1520500?s=200&v=4
description: |
@@ -176,7 +197,7 @@
name: "faster-whisper"
capabilities:
nvidia: "cuda12-faster-whisper"
intel: "intel-sycl-f32-faster-whisper"
intel: "intel-faster-whisper"
amd: "rocm-faster-whisper"
- &kokoro
icon: https://avatars.githubusercontent.com/u/166769057?v=4
@@ -194,7 +215,7 @@
name: "kokoro"
capabilities:
nvidia: "cuda12-kokoro"
intel: "intel-sycl-f32-kokoro"
intel: "intel-kokoro"
amd: "rocm-kokoro"
- &coqui
urls:
@@ -215,7 +236,7 @@
alias: "coqui"
capabilities:
nvidia: "cuda12-coqui"
intel: "intel-sycl-f32-coqui"
intel: "intel-coqui"
amd: "rocm-coqui"
icon: https://avatars.githubusercontent.com/u/1338804?s=200&v=4
- &bark
@@ -231,7 +252,7 @@
alias: "bark"
capabilities:
cuda: "cuda12-bark"
intel: "intel-sycl-f32-bark"
intel: "intel-bark"
rocm: "rocm-bark"
icon: https://avatars.githubusercontent.com/u/99442120?s=200&v=4
- &barkcpp
@@ -258,6 +279,8 @@
icon: https://github.com/PABannier/bark.cpp/raw/main/assets/banner.png
name: "bark-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-bark-cpp"
mirrors:
- localai/localai-backends:latest-bark-cpp
alias: "bark-cpp"
- &chatterbox
urls:
@@ -280,6 +303,8 @@
urls:
- https://github.com/rhasspy/piper
- https://github.com/mudler/go-piper
mirrors:
- localai/localai-backends:latest-piper
license: MIT
description: |
A fast, local neural text to speech system
@@ -292,6 +317,8 @@
icon: https://user-images.githubusercontent.com/12515440/89997349-b3523080-dc94-11ea-9906-ca2e8bc50535.png
urls:
- https://github.com/snakers4/silero-vad
mirrors:
- localai/localai-backends:latest-cpu-silero-vad
description: |
Silero VAD: pre-trained enterprise-grade Voice Activity Detector.
Silero VAD is a voice activity detection model that can be used to detect whether a given audio contains speech or not.
@@ -303,6 +330,8 @@
- &local-store
name: "local-store"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-local-store"
mirrors:
- localai/localai-backends:latest-cpu-local-store
urls:
- https://github.com/mudler/LocalAI
description: |
@@ -316,6 +345,8 @@
- &huggingface
name: "huggingface"
uri: "quay.io/go-skynet/local-ai-backends:latest-huggingface"
mirrors:
- localai/localai-backends:latest-huggingface
icon: https://huggingface.co/front/assets/huggingface_logo-noborder.svg
urls:
- https://huggingface.co/docs/hub/en/api
@@ -328,469 +359,721 @@
- !!merge <<: *huggingface
name: "huggingface-development"
uri: "quay.io/go-skynet/local-ai-backends:master-huggingface"
mirrors:
- localai/localai-backends:master-huggingface
- !!merge <<: *local-store
name: "local-store-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-local-store"
mirrors:
- localai/localai-backends:master-cpu-local-store
- !!merge <<: *silero-vad
name: "silero-vad-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-silero-vad"
mirrors:
- localai/localai-backends:master-cpu-silero-vad
- !!merge <<: *piper
name: "piper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-piper"
mirrors:
- localai/localai-backends:master-piper
## llama-cpp
- !!merge <<: *llamacpp
name: "darwin-x86-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-darwin-x86-llama-cpp"
mirrors:
- localai/localai-backends:latest-darwin-x86-llama-cpp
- !!merge <<: *llamacpp
name: "darwin-x86-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-darwin-x86-llama-cpp"
mirrors:
- localai/localai-backends:master-darwin-x86-llama-cpp
- !!merge <<: *llamacpp
name: "nvidia-l4t-arm64-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-llama-cpp"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-arm64-llama-cpp
- !!merge <<: *llamacpp
name: "nvidia-l4t-arm64-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-arm64-llama-cpp"
mirrors:
- localai/localai-backends:master-nvidia-l4t-arm64-llama-cpp
- !!merge <<: *llamacpp
name: "cpu-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-llama-cpp"
mirrors:
- localai/localai-backends:latest-cpu-llama-cpp
- !!merge <<: *llamacpp
name: "cpu-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-llama-cpp"
mirrors:
- localai/localai-backends:master-cpu-llama-cpp
- !!merge <<: *llamacpp
name: "cuda11-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-llama-cpp"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-llama-cpp
- !!merge <<: *llamacpp
name: "cuda12-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-llama-cpp"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-llama-cpp
- !!merge <<: *llamacpp
name: "rocm-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-llama-cpp"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-llama-cpp
- !!merge <<: *llamacpp
name: "intel-sycl-f32-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-llama-cpp"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f32-llama-cpp
- !!merge <<: *llamacpp
name: "intel-sycl-f16-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-llama-cpp"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f16-llama-cpp
- !!merge <<: *llamacpp
name: "vulkan-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-vulkan-llama-cpp"
mirrors:
- localai/localai-backends:latest-gpu-vulkan-llama-cpp
- !!merge <<: *llamacpp
name: "vulkan-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-vulkan-llama-cpp"
mirrors:
- localai/localai-backends:master-gpu-vulkan-llama-cpp
- !!merge <<: *llamacpp
name: "metal-llama-cpp"
uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-llama-cpp"
mirrors:
- localai/localai-backends:latest-metal-darwin-arm64-llama-cpp
- !!merge <<: *llamacpp
name: "metal-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-llama-cpp"
mirrors:
- localai/localai-backends:master-metal-darwin-arm64-llama-cpp
- !!merge <<: *llamacpp
name: "cuda11-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-llama-cpp"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-llama-cpp
- !!merge <<: *llamacpp
name: "cuda12-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-llama-cpp"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-llama-cpp
- !!merge <<: *llamacpp
name: "rocm-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-llama-cpp"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-llama-cpp
- !!merge <<: *llamacpp
name: "intel-sycl-f32-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-llama-cpp"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f32-llama-cpp
- !!merge <<: *llamacpp
name: "intel-sycl-f16-llama-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-llama-cpp"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f16-llama-cpp
## whisper
- !!merge <<: *whispercpp
name: "nvidia-l4t-arm64-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-whisper"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-arm64-whisper
- !!merge <<: *whispercpp
name: "nvidia-l4t-arm64-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-arm64-whisper"
mirrors:
- localai/localai-backends:master-nvidia-l4t-arm64-whisper
- !!merge <<: *whispercpp
name: "cpu-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-whisper"
mirrors:
- localai/localai-backends:latest-cpu-whisper
- !!merge <<: *whispercpp
name: "cpu-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-whisper"
mirrors:
- localai/localai-backends:master-cpu-whisper
- !!merge <<: *whispercpp
name: "cuda11-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-whisper"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-whisper
- !!merge <<: *whispercpp
name: "cuda12-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-whisper"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-whisper
- !!merge <<: *whispercpp
name: "rocm-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-whisper"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-whisper
- !!merge <<: *whispercpp
name: "intel-sycl-f32-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-whisper"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f32-whisper
- !!merge <<: *whispercpp
name: "intel-sycl-f16-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-whisper"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f16-whisper
- !!merge <<: *whispercpp
name: "vulkan-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-vulkan-whisper"
mirrors:
- localai/localai-backends:latest-gpu-vulkan-whisper
- !!merge <<: *whispercpp
name: "vulkan-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-vulkan-whisper"
mirrors:
- localai/localai-backends:master-gpu-vulkan-whisper
- !!merge <<: *whispercpp
name: "metal-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-whisper"
mirrors:
- localai/localai-backends:latest-metal-darwin-arm64-whisper
- !!merge <<: *whispercpp
name: "metal-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-whisper"
mirrors:
- localai/localai-backends:master-metal-darwin-arm64-whisper
- !!merge <<: *whispercpp
name: "cuda11-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-whisper"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-whisper
- !!merge <<: *whispercpp
name: "cuda12-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-whisper"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-whisper
- !!merge <<: *whispercpp
name: "rocm-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-whisper"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-whisper
- !!merge <<: *whispercpp
name: "intel-sycl-f32-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-whisper"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f32-whisper
- !!merge <<: *whispercpp
name: "intel-sycl-f16-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-whisper"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f16-whisper
## stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "cpu-stablediffusion-ggml"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-stablediffusion-ggml"
mirrors:
- localai/localai-backends:latest-cpu-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "cpu-stablediffusion-ggml-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-stablediffusion-ggml"
mirrors:
- localai/localai-backends:master-cpu-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "vulkan-stablediffusion-ggml"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-vulkan-stablediffusion-ggml"
mirrors:
- localai/localai-backends:latest-gpu-vulkan-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "vulkan-stablediffusion-ggml-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-vulkan-stablediffusion-ggml"
mirrors:
- localai/localai-backends:master-gpu-vulkan-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "cuda12-stablediffusion-ggml"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-stablediffusion-ggml"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "intel-sycl-f32-stablediffusion-ggml"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-stablediffusion-ggml"
- !!merge <<: *stablediffusionggml
name: "intel-sycl-f16-stablediffusion-ggml"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-stablediffusion-ggml"
mirrors:
- localai/localai-backends:latest-gpu-intel-sycl-f16-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "cuda11-stablediffusion-ggml"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-stablediffusion-ggml"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "cuda12-stablediffusion-ggml-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-stablediffusion-ggml"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "intel-sycl-f32-stablediffusion-ggml-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-stablediffusion-ggml"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f32-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "intel-sycl-f16-stablediffusion-ggml-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-stablediffusion-ggml"
mirrors:
- localai/localai-backends:master-gpu-intel-sycl-f16-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "cuda11-stablediffusion-ggml-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-stablediffusion-ggml"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "nvidia-l4t-arm64-stablediffusion-ggml-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-arm64-stablediffusion-ggml"
mirrors:
- localai/localai-backends:master-nvidia-l4t-arm64-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "nvidia-l4t-arm64-stablediffusion-ggml"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-stablediffusion-ggml"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-arm64-stablediffusion-ggml
# vllm
- !!merge <<: *vllm
name: "vllm-development"
capabilities:
nvidia: "cuda12-vllm-development"
amd: "rocm-vllm-development"
intel: "intel-sycl-f16-vllm-development"
intel: "intel-vllm-development"
- !!merge <<: *vllm
name: "cuda12-vllm"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-vllm"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-vllm
- !!merge <<: *vllm
name: "rocm-vllm"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-vllm"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-vllm
- !!merge <<: *vllm
name: "intel-sycl-f32-vllm"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-vllm"
- !!merge <<: *vllm
name: "intel-sycl-f16-vllm"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-vllm"
name: "intel-vllm"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-vllm"
mirrors:
- localai/localai-backends:latest-gpu-intel-vllm
- !!merge <<: *vllm
name: "cuda12-vllm-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-vllm"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-vllm
- !!merge <<: *vllm
name: "rocm-vllm-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-vllm"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-vllm
- !!merge <<: *vllm
name: "intel-sycl-f32-vllm-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-vllm"
- !!merge <<: *vllm
name: "intel-sycl-f16-vllm-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-vllm"
name: "intel-vllm-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-vllm"
mirrors:
- localai/localai-backends:master-gpu-intel-vllm
# rfdetr
- !!merge <<: *rfdetr
name: "rfdetr-development"
capabilities:
nvidia: "cuda12-rfdetr-development"
intel: "intel-rfdetr-development"
#amd: "rocm-rfdetr-development"
nvidia-l4t: "nvidia-l4t-arm64-rfdetr-development"
default: "cpu-rfdetr-development"
- !!merge <<: *rfdetr
name: "cuda12-rfdetr"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-rfdetr"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-rfdetr
- !!merge <<: *rfdetr
name: "intel-rfdetr"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-rfdetr"
mirrors:
- localai/localai-backends:latest-gpu-intel-rfdetr
# - !!merge <<: *rfdetr
# name: "rocm-rfdetr"
# uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-hipblas-rfdetr"
# mirrors:
# - localai/localai-backends:latest-gpu-hipblas-rfdetr
- !!merge <<: *rfdetr
name: "nvidia-l4t-arm64-rfdetr"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-rfdetr"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-arm64-rfdetr
- !!merge <<: *rfdetr
name: "cpu-rfdetr"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-rfdetr"
mirrors:
- localai/localai-backends:latest-cpu-rfdetr
- !!merge <<: *rfdetr
name: "cuda12-rfdetr-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-rfdetr"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-rfdetr
- !!merge <<: *rfdetr
name: "intel-rfdetr-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-rfdetr"
mirrors:
- localai/localai-backends:master-gpu-intel-rfdetr
# - !!merge <<: *rfdetr
# name: "rocm-rfdetr-development"
# uri: "quay.io/go-skynet/local-ai-backends:master-gpu-hipblas-rfdetr"
# mirrors:
# - localai/localai-backends:master-gpu-hipblas-rfdetr
- !!merge <<: *rfdetr
name: "cpu-rfdetr-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-rfdetr"
mirrors:
- localai/localai-backends:master-cpu-rfdetr
- !!merge <<: *rfdetr
name: "intel-rfdetr"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-rfdetr"
mirrors:
- localai/localai-backends:latest-gpu-intel-rfdetr
## Rerankers
- !!merge <<: *rerankers
name: "rerankers-development"
capabilities:
nvidia: "cuda12-rerankers-development"
intel: "intel-sycl-f16-rerankers-development"
intel: "intel-rerankers-development"
amd: "rocm-rerankers-development"
- !!merge <<: *rerankers
name: "cuda11-rerankers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-rerankers"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-rerankers
- !!merge <<: *rerankers
name: "cuda12-rerankers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-rerankers"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-rerankers
- !!merge <<: *rerankers
name: "intel-sycl-f32-rerankers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-rerankers"
- !!merge <<: *rerankers
name: "intel-sycl-f16-rerankers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-rerankers"
name: "intel-rerankers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-rerankers"
mirrors:
- localai/localai-backends:latest-gpu-intel-rerankers
- !!merge <<: *rerankers
name: "rocm-rerankers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-rerankers"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-rerankers
- !!merge <<: *rerankers
name: "cuda11-rerankers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-rerankers"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-rerankers
- !!merge <<: *rerankers
name: "cuda12-rerankers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-rerankers"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-rerankers
- !!merge <<: *rerankers
name: "rocm-rerankers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-rerankers"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-rerankers
- !!merge <<: *rerankers
name: "intel-sycl-f32-rerankers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-rerankers"
- !!merge <<: *rerankers
name: "intel-sycl-f16-rerankers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-rerankers"
name: "intel-rerankers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-rerankers"
mirrors:
- localai/localai-backends:master-gpu-intel-rerankers
## Transformers
- !!merge <<: *transformers
name: "transformers-development"
capabilities:
nvidia: "cuda12-transformers-development"
intel: "intel-sycl-f16-transformers-development"
intel: "intel-transformers-development"
amd: "rocm-transformers-development"
- !!merge <<: *transformers
name: "cuda12-transformers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-transformers"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-transformers
- !!merge <<: *transformers
name: "rocm-transformers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-transformers"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-transformers
- !!merge <<: *transformers
name: "intel-sycl-f32-transformers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-transformers"
- !!merge <<: *transformers
name: "intel-sycl-f16-transformers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-transformers"
name: "intel-transformers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-transformers"
mirrors:
- localai/localai-backends:latest-gpu-intel-transformers
- !!merge <<: *transformers
name: "cuda11-transformers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-transformers"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-transformers
- !!merge <<: *transformers
name: "cuda11-transformers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-transformers"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-transformers
- !!merge <<: *transformers
name: "cuda12-transformers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-transformers"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-transformers
- !!merge <<: *transformers
name: "rocm-transformers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-transformers"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-transformers
- !!merge <<: *transformers
name: "intel-sycl-f32-transformers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-transformers"
- !!merge <<: *transformers
name: "intel-sycl-f16-transformers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-transformers"
name: "intel-transformers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-transformers"
mirrors:
- localai/localai-backends:master-gpu-intel-transformers
## Diffusers
- !!merge <<: *diffusers
name: "diffusers-development"
capabilities:
nvidia: "cuda12-diffusers-development"
intel: "intel-sycl-f32-diffusers-development"
intel: "intel-diffusers-development"
amd: "rocm-diffusers-development"
- !!merge <<: *diffusers
name: "cuda12-diffusers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-diffusers"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-diffusers
- !!merge <<: *diffusers
name: "rocm-diffusers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-diffusers"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-diffusers
- !!merge <<: *diffusers
name: "cuda11-diffusers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-diffusers"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-diffusers
- !!merge <<: *diffusers
name: "intel-sycl-f32-diffusers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-diffusers"
name: "intel-diffusers"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-diffusers"
mirrors:
- localai/localai-backends:latest-gpu-intel-diffusers
- !!merge <<: *diffusers
name: "cuda11-diffusers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-diffusers"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-diffusers
- !!merge <<: *diffusers
name: "cuda12-diffusers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-diffusers"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-diffusers
- !!merge <<: *diffusers
name: "rocm-diffusers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-diffusers"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-diffusers
- !!merge <<: *diffusers
name: "intel-sycl-f32-diffusers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-diffusers"
name: "intel-diffusers-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-diffusers"
mirrors:
- localai/localai-backends:master-gpu-intel-diffusers
## exllama2
- !!merge <<: *exllama2
name: "exllama2-development"
capabilities:
nvidia: "cuda12-exllama2-development"
intel: "intel-sycl-f32-exllama2-development"
amd: "rocm-exllama2-development"
intel: "intel-exllama2-development"
- !!merge <<: *exllama2
name: "cuda11-exllama2"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-exllama2"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-exllama2
- !!merge <<: *exllama2
name: "cuda12-exllama2"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-exllama2"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-exllama2
- !!merge <<: *exllama2
name: "cuda11-exllama2-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-exllama2"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-exllama2
- !!merge <<: *exllama2
name: "cuda12-exllama2-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-exllama2"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-exllama2
## kokoro
- !!merge <<: *kokoro
name: "kokoro-development"
capabilities:
nvidia: "cuda12-kokoro-development"
intel: "intel-sycl-f32-kokoro-development"
intel: "intel-kokoro-development"
amd: "rocm-kokoro-development"
- !!merge <<: *kokoro
name: "cuda11-kokoro-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-kokoro"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-kokoro
- !!merge <<: *kokoro
name: "cuda12-kokoro-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-kokoro"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-kokoro
- !!merge <<: *kokoro
name: "rocm-kokoro-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-kokoro"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-kokoro
- !!merge <<: *kokoro
name: "sycl-f32-kokoro"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-kokoro"
name: "intel-kokoro"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-kokoro"
mirrors:
- localai/localai-backends:latest-gpu-intel-kokoro
- !!merge <<: *kokoro
name: "sycl-f16-kokoro"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-kokoro"
- !!merge <<: *kokoro
name: "sycl-f16-kokoro-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-kokoro"
- !!merge <<: *kokoro
name: "sycl-f32-kokoro-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-kokoro"
name: "intel-kokoro-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-kokoro"
mirrors:
- localai/localai-backends:master-gpu-intel-kokoro
- !!merge <<: *kokoro
name: "cuda11-kokoro"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-kokoro"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-kokoro
- !!merge <<: *kokoro
name: "cuda12-kokoro"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-kokoro"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-kokoro
- !!merge <<: *kokoro
name: "rocm-kokoro"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-kokoro"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-kokoro
## faster-whisper
- !!merge <<: *faster-whisper
name: "faster-whisper-development"
capabilities:
nvidia: "cuda12-faster-whisper-development"
intel: "intel-sycl-f32-faster-whisper-development"
intel: "intel-faster-whisper-development"
amd: "rocm-faster-whisper-development"
- !!merge <<: *faster-whisper
name: "cuda11-faster-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-faster-whisper"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-faster-whisper
- !!merge <<: *faster-whisper
name: "cuda12-faster-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-faster-whisper"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-faster-whisper
- !!merge <<: *faster-whisper
name: "rocm-faster-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-faster-whisper"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-faster-whisper
- !!merge <<: *faster-whisper
name: "sycl-f32-faster-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-faster-whisper"
name: "intel-faster-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-faster-whisper"
mirrors:
- localai/localai-backends:latest-gpu-intel-faster-whisper
- !!merge <<: *faster-whisper
name: "sycl-f16-faster-whisper"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-faster-whisper"
- !!merge <<: *faster-whisper
name: "sycl-f32-faster-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-faster-whisper"
- !!merge <<: *faster-whisper
name: "sycl-f16-faster-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-faster-whisper"
name: "intel-faster-whisper-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-faster-whisper"
mirrors:
- localai/localai-backends:master-gpu-intel-faster-whisper
## coqui
- !!merge <<: *coqui
name: "coqui-development"
capabilities:
nvidia: "cuda12-coqui-development"
intel: "intel-sycl-f32-coqui-development"
intel: "intel-coqui-development"
amd: "rocm-coqui-development"
- !!merge <<: *coqui
name: "cuda11-coqui"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-coqui"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-coqui
- !!merge <<: *coqui
name: "cuda12-coqui"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-coqui"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-coqui
- !!merge <<: *coqui
name: "cuda11-coqui-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-coqui"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-coqui
- !!merge <<: *coqui
name: "cuda12-coqui-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-coqui"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-coqui
- !!merge <<: *coqui
name: "rocm-coqui-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-coqui"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-coqui
- !!merge <<: *coqui
name: "sycl-f32-coqui"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-coqui"
name: "intel-coqui"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-coqui"
mirrors:
- localai/localai-backends:latest-gpu-intel-coqui
- !!merge <<: *coqui
name: "sycl-f16-coqui"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-coqui"
- !!merge <<: *coqui
name: "sycl-f32-coqui-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-coqui"
- !!merge <<: *coqui
name: "sycl-f16-coqui-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-coqui"
name: "intel-coqui-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-coqui"
mirrors:
- localai/localai-backends:master-gpu-intel-coqui
- !!merge <<: *coqui
name: "rocm-coqui"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-coqui"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-coqui
## bark
- !!merge <<: *bark
name: "bark-development"
capabilities:
nvidia: "cuda12-bark-development"
intel: "intel-sycl-f32-bark-development"
intel: "intel-bark-development"
amd: "rocm-bark-development"
- !!merge <<: *bark
name: "cuda11-bark-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-bark"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-bark
- !!merge <<: *bark
name: "cuda11-bark"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-bark"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-bark
- !!merge <<: *bark
name: "rocm-bark-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-bark"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-bark
- !!merge <<: *bark
name: "sycl-f32-bark"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-bark"
name: "intel-bark"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-bark"
mirrors:
- localai/localai-backends:latest-gpu-intel-bark
- !!merge <<: *bark
name: "sycl-f16-bark"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-bark"
- !!merge <<: *bark
name: "sycl-f32-bark-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-bark"
- !!merge <<: *bark
name: "sycl-f16-bark-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f16-bark"
name: "intel-bark-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-bark"
mirrors:
- localai/localai-backends:master-gpu-intel-bark
- !!merge <<: *bark
name: "cuda12-bark"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-bark"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-bark
- !!merge <<: *bark
name: "rocm-bark"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-bark"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-bark
- !!merge <<: *bark
name: "cuda12-bark-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-bark"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-bark
- !!merge <<: *barkcpp
name: "bark-cpp-development"
uri: "quay.io/go-skynet/local-ai-backends:master-bark-cpp"
@@ -803,12 +1086,20 @@
- !!merge <<: *chatterbox
name: "cuda12-chatterbox-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-chatterbox"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-chatterbox
- !!merge <<: *chatterbox
name: "cuda11-chatterbox"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-chatterbox"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-11-chatterbox
- !!merge <<: *chatterbox
name: "cuda11-chatterbox-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-chatterbox"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-11-chatterbox
- !!merge <<: *chatterbox
name: "cuda12-chatterbox"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-chatterbox"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-chatterbox

View File

@@ -111,7 +111,7 @@ function ensureVenv() {
# - requirements-${BUILD_TYPE}.txt
# - requirements-${BUILD_PROFILE}.txt
#
# BUILD_PROFILE is a pore specific version of BUILD_TYPE, ex: cuda11 or cuda12
# BUILD_PROFILE is a pore specific version of BUILD_TYPE, ex: cuda-11 or cuda-12
# it can also include some options that we do not have BUILD_TYPES for, ex: intel
#
# NOTE: for BUILD_PROFILE==intel, this function does NOT automatically use the Intel python package index.

View File

@@ -8,4 +8,6 @@ else
source $backend_dir/../common/libbackend.sh
fi
ensureVenv
python3 -m grpc_tools.protoc -I../.. -I./ --python_out=. --grpc_python_out=. backend.proto

View File

@@ -0,0 +1,20 @@
.DEFAULT_GOAL := install
.PHONY: install
install:
bash install.sh
$(MAKE) protogen
.PHONY: protogen
protogen: backend_pb2_grpc.py backend_pb2.py
.PHONY: protogen-clean
protogen-clean:
$(RM) backend_pb2_grpc.py backend_pb2.py
backend_pb2_grpc.py backend_pb2.py:
bash protogen.sh
.PHONY: clean
clean: protogen-clean
rm -rf venv __pycache__

174
backend/python/rfdetr/backend.py Executable file
View File

@@ -0,0 +1,174 @@
#!/usr/bin/env python3
"""
gRPC server for RFDETR object detection models.
"""
from concurrent import futures
import argparse
import signal
import sys
import os
import time
import base64
import backend_pb2
import backend_pb2_grpc
import grpc
import requests
import supervision as sv
from inference import get_model
from PIL import Image
from io import BytesIO
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
# Implement the BackendServicer class with the service methods
class BackendServicer(backend_pb2_grpc.BackendServicer):
"""
A gRPC servicer for the RFDETR backend service.
This class implements the gRPC methods for object detection using RFDETR models.
"""
def __init__(self):
self.model = None
self.model_name = None
def Health(self, request, context):
"""
A gRPC method that returns the health status of the backend service.
Args:
request: A HealthMessage object that contains the request parameters.
context: A grpc.ServicerContext object that provides information about the RPC.
Returns:
A Reply object that contains the health status of the backend service.
"""
return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
def LoadModel(self, request, context):
"""
A gRPC method that loads a RFDETR model into memory.
Args:
request: A ModelOptions object that contains the model parameters.
context: A grpc.ServicerContext object that provides information about the RPC.
Returns:
A Result object that contains the result of the LoadModel operation.
"""
model_name = request.Model
try:
# Load the RFDETR model
self.model = get_model(model_name)
self.model_name = model_name
print(f'Loaded RFDETR model: {model_name}')
except Exception as err:
return backend_pb2.Result(success=False, message=f"Failed to load model: {err}")
return backend_pb2.Result(message="Model loaded successfully", success=True)
def Detect(self, request, context):
"""
A gRPC method that performs object detection on an image.
Args:
request: A DetectOptions object that contains the image source.
context: A grpc.ServicerContext object that provides information about the RPC.
Returns:
A DetectResponse object that contains the detection results.
"""
if self.model is None:
print(f"Model is None")
return backend_pb2.DetectResponse()
print(f"Model is not None")
try:
print(f"Decoding image")
# Decode the base64 image
print(f"Image data: {request.src}")
image_data = base64.b64decode(request.src)
image = Image.open(BytesIO(image_data))
# Perform inference
predictions = self.model.infer(image, confidence=0.5)[0]
# Convert to proto format
proto_detections = []
for i in range(len(predictions.predictions)):
pred = predictions.predictions[i]
print(f"Prediction: {pred}")
proto_detection = backend_pb2.Detection(
x=float(pred.x),
y=float(pred.y),
width=float(pred.width),
height=float(pred.height),
confidence=float(pred.confidence),
class_name=pred.class_name
)
proto_detections.append(proto_detection)
return backend_pb2.DetectResponse(Detections=proto_detections)
except Exception as err:
print(f"Detection error: {err}")
return backend_pb2.DetectResponse()
def Status(self, request, context):
"""
A gRPC method that returns the status of the backend service.
Args:
request: A HealthMessage object that contains the request parameters.
context: A grpc.ServicerContext object that provides information about the RPC.
Returns:
A StatusResponse object that contains the status information.
"""
state = backend_pb2.StatusResponse.READY if self.model is not None else backend_pb2.StatusResponse.UNINITIALIZED
return backend_pb2.StatusResponse(state=state)
def serve(address):
server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS),
options=[
('grpc.max_message_length', 50 * 1024 * 1024), # 50MB
('grpc.max_send_message_length', 50 * 1024 * 1024), # 50MB
('grpc.max_receive_message_length', 50 * 1024 * 1024), # 50MB
])
backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
server.add_insecure_port(address)
server.start()
print("[RFDETR] Server started. Listening on: " + address, file=sys.stderr)
# Define the signal handler function
def signal_handler(sig, frame):
print("[RFDETR] Received termination signal. Shutting down...")
server.stop(0)
sys.exit(0)
# Set the signal handlers for SIGINT and SIGTERM
signal.signal(signal.SIGINT, signal_handler)
signal.signal(signal.SIGTERM, signal_handler)
try:
while True:
time.sleep(_ONE_DAY_IN_SECONDS)
except KeyboardInterrupt:
server.stop(0)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run the RFDETR gRPC server.")
parser.add_argument(
"--addr", default="localhost:50051", help="The address to bind the server to."
)
args = parser.parse_args()
print(f"[RFDETR] startup: {args}", file=sys.stderr)
serve(args.addr)

View File

@@ -0,0 +1,19 @@
#!/bin/bash
set -e
backend_dir=$(dirname $0)
if [ -d $backend_dir/common ]; then
source $backend_dir/common/libbackend.sh
else
source $backend_dir/../common/libbackend.sh
fi
# This is here because the Intel pip index is broken and returns 200 status codes for every package name, it just doesn't return any package links.
# This makes uv think that the package exists in the Intel pip index, and by default it stops looking at other pip indexes once it finds a match.
# We need uv to continue falling through to the pypi default index to find optimum[openvino] in the pypi index
# the --upgrade actually allows us to *downgrade* torch to the version provided in the Intel pip index
if [ "x${BUILD_PROFILE}" == "xintel" ]; then
EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
fi
installRequirements

View File

@@ -0,0 +1,13 @@
#!/bin/bash
set -e
backend_dir=$(dirname $0)
if [ -d $backend_dir/common ]; then
source $backend_dir/common/libbackend.sh
else
source $backend_dir/../common/libbackend.sh
fi
ensureVenv
python3 -m grpc_tools.protoc -I../.. -I./ --python_out=. --grpc_python_out=. backend.proto

View File

@@ -0,0 +1,7 @@
rfdetr
opencv-python
accelerate
peft
inference
torch==2.7.1
optimum-quanto

View File

@@ -0,0 +1,8 @@
--extra-index-url https://download.pytorch.org/whl/cu118
torch==2.7.1+cu118
rfdetr
opencv-python
accelerate
inference
peft
optimum-quanto

View File

@@ -0,0 +1,7 @@
torch==2.7.1
rfdetr
opencv-python
accelerate
inference
peft
optimum-quanto

View File

@@ -0,0 +1,9 @@
--extra-index-url https://download.pytorch.org/whl/rocm6.3
torch==2.7.1+rocm6.3
torchvision==0.22.1+rocm6.3
rfdetr
opencv-python
accelerate
inference
peft
optimum-quanto

View File

@@ -0,0 +1,13 @@
--extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
intel-extension-for-pytorch==2.3.110+xpu
torch==2.3.1+cxx11.abi
torchvision==0.18.1+cxx11.abi
oneccl_bind_pt==2.3.100+xpu
optimum[openvino]
setuptools
rfdetr
inference
opencv-python
accelerate
peft
optimum-quanto

View File

@@ -0,0 +1,3 @@
grpcio==1.71.0
protobuf
grpcio-tools

9
backend/python/rfdetr/run.sh Executable file
View File

@@ -0,0 +1,9 @@
#!/bin/bash
backend_dir=$(dirname $0)
if [ -d $backend_dir/common ]; then
source $backend_dir/common/libbackend.sh
else
source $backend_dir/../common/libbackend.sh
fi
startBackend $@

11
backend/python/rfdetr/test.sh Executable file
View File

@@ -0,0 +1,11 @@
#!/bin/bash
set -e
backend_dir=$(dirname $0)
if [ -d $backend_dir/common ]; then
source $backend_dir/common/libbackend.sh
else
source $backend_dir/../common/libbackend.sh
fi
runUnittests

View File

@@ -2,8 +2,8 @@ package application
import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/templates"
)
type Application struct {

View File

@@ -10,8 +10,8 @@ import (
"github.com/mudler/LocalAI/core/services"
"github.com/mudler/LocalAI/internal"
coreStartup "github.com/mudler/LocalAI/core/startup"
"github.com/mudler/LocalAI/pkg/model"
pkgStartup "github.com/mudler/LocalAI/pkg/startup"
"github.com/mudler/LocalAI/pkg/xsysinfo"
"github.com/rs/zerolog/log"
)
@@ -55,11 +55,11 @@ func New(opts ...config.AppOption) (*Application, error) {
}
}
if err := pkgStartup.InstallModels(options.Galleries, options.BackendGalleries, options.ModelPath, options.BackendsPath, options.EnforcePredownloadScans, options.AutoloadBackendGalleries, nil, options.ModelsURL...); err != nil {
if err := coreStartup.InstallModels(options.Galleries, options.BackendGalleries, options.ModelPath, options.BackendsPath, options.EnforcePredownloadScans, options.AutoloadBackendGalleries, nil, options.ModelsURL...); err != nil {
log.Error().Err(err).Msg("error installing models")
}
if err := pkgStartup.InstallExternalBackends(options.BackendGalleries, options.BackendsPath, nil, options.ExternalBackends...); err != nil {
if err := coreStartup.InstallExternalBackends(options.BackendGalleries, options.BackendsPath, nil, options.ExternalBackends...); err != nil {
log.Error().Err(err).Msg("error installing external backends")
}

34
core/backend/detection.go Normal file
View File

@@ -0,0 +1,34 @@
package backend
import (
"context"
"fmt"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/model"
)
func Detection(
sourceFile string,
loader *model.ModelLoader,
appConfig *config.ApplicationConfig,
backendConfig config.BackendConfig,
) (*proto.DetectResponse, error) {
opts := ModelOptions(backendConfig, appConfig)
detectionModel, err := loader.Load(opts...)
if err != nil {
return nil, err
}
defer loader.Close()
if detectionModel == nil {
return nil, fmt.Errorf("could not load detection model")
}
res, err := detectionModel.Detect(context.Background(), &proto.DetectOptions{
Src: sourceFile,
})
return res, err
}

View File

@@ -7,7 +7,7 @@ import (
model "github.com/mudler/LocalAI/pkg/model"
)
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, src, dst string, loader *model.ModelLoader, backendConfig config.BackendConfig, appConfig *config.ApplicationConfig) (func() error, error) {
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, src, dst string, loader *model.ModelLoader, backendConfig config.BackendConfig, appConfig *config.ApplicationConfig, refImages []string) (func() error, error) {
opts := ModelOptions(backendConfig, appConfig)
inferenceModel, err := loader.Load(
@@ -33,6 +33,7 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
Dst: dst,
Src: src,
EnableParameters: backendConfig.Diffusers.EnableParameters,
RefImages: refImages,
})
return err
}

View File

@@ -8,7 +8,7 @@ import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/gallery"
"github.com/mudler/LocalAI/pkg/startup"
"github.com/mudler/LocalAI/core/startup"
"github.com/rs/zerolog/log"
"github.com/schollz/progressbar/v3"
)

View File

@@ -9,8 +9,8 @@ import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/gallery"
"github.com/mudler/LocalAI/core/startup"
"github.com/mudler/LocalAI/pkg/downloader"
"github.com/mudler/LocalAI/pkg/startup"
"github.com/rs/zerolog/log"
"github.com/schollz/progressbar/v3"
)

View File

@@ -25,7 +25,6 @@ type RunCMD struct {
ModelsPath string `env:"LOCALAI_MODELS_PATH,MODELS_PATH" type:"path" default:"${basepath}/models" help:"Path containing models used for inferencing" group:"storage"`
GeneratedContentPath string `env:"LOCALAI_GENERATED_CONTENT_PATH,GENERATED_CONTENT_PATH" type:"path" default:"/tmp/generated/content" help:"Location for generated content (e.g. images, audio, videos)" group:"storage"`
UploadPath string `env:"LOCALAI_UPLOAD_PATH,UPLOAD_PATH" type:"path" default:"/tmp/localai/upload" help:"Path to store uploads from files api" group:"storage"`
ConfigPath string `env:"LOCALAI_CONFIG_PATH,CONFIG_PATH" default:"/tmp/localai/config" group:"storage"`
LocalaiConfigDir string `env:"LOCALAI_CONFIG_DIR" type:"path" default:"${basepath}/configuration" help:"Directory for dynamic loading of certain configuration files (currently api_keys.json and external_backends.json)" group:"storage"`
LocalaiConfigDirPollInterval time.Duration `env:"LOCALAI_CONFIG_DIR_POLL_INTERVAL" help:"Typically the config path picks up changes automatically, but if your system has broken fsnotify events, set this to an interval to poll the LocalAI Config Dir (example: 1m)" group:"storage"`
// The alias on this option is there to preserve functionality with the old `--config-file` parameter
@@ -88,7 +87,6 @@ func (r *RunCMD) Run(ctx *cliContext.Context) error {
config.WithDebug(zerolog.GlobalLevel() <= zerolog.DebugLevel),
config.WithGeneratedContentDir(r.GeneratedContentPath),
config.WithUploadDir(r.UploadPath),
config.WithConfigsDir(r.ConfigPath),
config.WithDynamicConfigDir(r.LocalaiConfigDir),
config.WithDynamicConfigDirPollInterval(r.LocalaiConfigDirPollInterval),
config.WithF16(r.F16),

View File

@@ -72,7 +72,7 @@ func (u *CreateOCIImageCMD) Run(ctx *cliContext.Context) error {
}
func (u *GGUFInfoCMD) Run(ctx *cliContext.Context) error {
if u.Args == nil || len(u.Args) == 0 {
if len(u.Args) == 0 {
return fmt.Errorf("no GGUF file provided")
}
// We try to guess only if we don't have a template defined already

View File

@@ -21,8 +21,7 @@ type ApplicationConfig struct {
Debug bool
GeneratedContentDir string
ConfigsDir string
UploadDir string
UploadDir string
DynamicConfigsDir string
DynamicConfigsDirPollInterval time.Duration
@@ -302,12 +301,6 @@ func WithUploadDir(uploadDir string) AppOption {
}
}
func WithConfigsDir(configsDir string) AppOption {
return func(o *ApplicationConfig) {
o.ConfigsDir = configsDir
}
}
func WithDynamicConfigDir(dynamicConfigsDir string) AppOption {
return func(o *ApplicationConfig) {
o.DynamicConfigsDir = dynamicConfigsDir

View File

@@ -458,6 +458,7 @@ const (
FLAG_TOKENIZE BackendConfigUsecases = 0b001000000000
FLAG_VAD BackendConfigUsecases = 0b010000000000
FLAG_VIDEO BackendConfigUsecases = 0b100000000000
FLAG_DETECTION BackendConfigUsecases = 0b1000000000000
// Common Subsets
FLAG_LLM BackendConfigUsecases = FLAG_CHAT | FLAG_COMPLETION | FLAG_EDIT
@@ -479,6 +480,7 @@ func GetAllBackendConfigUsecases() map[string]BackendConfigUsecases {
"FLAG_VAD": FLAG_VAD,
"FLAG_LLM": FLAG_LLM,
"FLAG_VIDEO": FLAG_VIDEO,
"FLAG_DETECTION": FLAG_DETECTION,
}
}
@@ -572,6 +574,12 @@ func (c *BackendConfig) GuessUsecases(u BackendConfigUsecases) bool {
}
}
if (u & FLAG_DETECTION) == FLAG_DETECTION {
if c.Backend != "rfdetr" {
return false
}
}
if (u & FLAG_SOUND_GENERATION) == FLAG_SOUND_GENERATION {
if c.Backend != "transformers-musicgen" {
return false

View File

@@ -2,7 +2,8 @@ package gallery
import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/system"
"github.com/mudler/LocalAI/pkg/system"
"github.com/rs/zerolog/log"
)
// BackendMetadata represents the metadata stored in a JSON file for each installed backend
@@ -23,6 +24,7 @@ type GalleryBackend struct {
Metadata `json:",inline" yaml:",inline"`
Alias string `json:"alias,omitempty" yaml:"alias,omitempty"`
URI string `json:"uri,omitempty" yaml:"uri,omitempty"`
Mirrors []string `json:"mirrors,omitempty" yaml:"mirrors,omitempty"`
CapabilitiesMap map[string]string `json:"capabilities,omitempty" yaml:"capabilities,omitempty"`
}
@@ -33,9 +35,11 @@ func (backend *GalleryBackend) FindBestBackendFromMeta(systemState *system.Syste
realBackend := backend.CapabilitiesMap[systemState.Capability(backend.CapabilitiesMap)]
if realBackend == "" {
log.Debug().Str("backend", backend.Name).Str("reportedCapability", systemState.Capability(backend.CapabilitiesMap)).Msg("No backend found for reported capability")
return nil
}
log.Debug().Str("backend", backend.Name).Str("reportedCapability", systemState.Capability(backend.CapabilitiesMap)).Msg("Found backend for reported capability")
return backends.FindByName(realBackend)
}

View File

@@ -8,9 +8,9 @@ import (
"time"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/system"
"github.com/mudler/LocalAI/pkg/downloader"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/system"
"github.com/rs/zerolog/log"
)
@@ -146,7 +146,18 @@ func InstallBackend(basePath string, config *GalleryBackend, downloadStatus func
uri := downloader.URI(config.URI)
if err := uri.DownloadFile(backendPath, "", 1, 1, downloadStatus); err != nil {
return fmt.Errorf("failed to download backend %q: %v", config.URI, err)
success := false
// Try to download from mirrors
for _, mirror := range config.Mirrors {
if err := downloader.URI(mirror).DownloadFile(backendPath, "", 1, 1, downloadStatus); err == nil {
success = true
break
}
}
if !success {
return fmt.Errorf("failed to download backend %q: %v", config.URI, err)
}
}
// Create metadata for the backend

View File

@@ -7,7 +7,7 @@ import (
"runtime"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/system"
"github.com/mudler/LocalAI/pkg/system"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"gopkg.in/yaml.v2"

View File

@@ -95,7 +95,7 @@ func FindGalleryElement[T GalleryElement](models []T, name string, basePath stri
if !strings.Contains(name, "@") {
for _, m := range models {
if strings.EqualFold(m.GetName(), name) {
if strings.EqualFold(strings.ToLower(m.GetName()), strings.ToLower(name)) {
model = m
break
}
@@ -103,7 +103,7 @@ func FindGalleryElement[T GalleryElement](models []T, name string, basePath stri
} else {
for _, m := range models {
if strings.EqualFold(name, fmt.Sprintf("%s@%s", m.GetGallery().Name, m.GetName())) {
if strings.EqualFold(strings.ToLower(name), strings.ToLower(fmt.Sprintf("%s@%s", m.GetGallery().Name, m.GetName()))) {
model = m
break
}

View File

@@ -10,8 +10,8 @@ import (
"dario.cat/mergo"
"github.com/mudler/LocalAI/core/config"
lconfig "github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/system"
"github.com/mudler/LocalAI/pkg/downloader"
"github.com/mudler/LocalAI/pkg/system"
"github.com/mudler/LocalAI/pkg/utils"
"github.com/rs/zerolog/log"

View File

@@ -10,10 +10,8 @@ import (
"github.com/dave-gray101/v2keyauth"
"github.com/gofiber/websocket/v2"
"github.com/mudler/LocalAI/pkg/utils"
"github.com/mudler/LocalAI/core/http/endpoints/localai"
"github.com/mudler/LocalAI/core/http/endpoints/openai"
"github.com/mudler/LocalAI/core/http/middleware"
"github.com/mudler/LocalAI/core/http/routes"
@@ -199,11 +197,6 @@ func API(application *application.Application) (*fiber.App, error) {
router.Use(csrf.New())
}
// Load config jsons
utils.LoadConfig(application.ApplicationConfig().UploadDir, openai.UploadedFilesFile, &openai.UploadedFiles)
utils.LoadConfig(application.ApplicationConfig().ConfigsDir, openai.AssistantsConfigFile, &openai.Assistants)
utils.LoadConfig(application.ApplicationConfig().ConfigsDir, openai.AssistantsFileConfigFile, &openai.AssistantFiles)
galleryService := services.NewGalleryService(application.ApplicationConfig(), application.ModelLoader())
err = galleryService.Start(application.ApplicationConfig().Context, application.BackendLoader())
if err != nil {

View File

@@ -34,7 +34,7 @@ func CreateBackendEndpointService(galleries []config.Gallery, backendPath string
// GetOpStatusEndpoint returns the job status
// @Summary Returns the job status
// @Success 200 {object} services.BackendOpStatus "Response"
// @Success 200 {object} services.GalleryOpStatus "Response"
// @Router /backends/jobs/{uuid} [get]
func (mgs *BackendEndpointService) GetOpStatusEndpoint() func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
@@ -48,7 +48,7 @@ func (mgs *BackendEndpointService) GetOpStatusEndpoint() func(c *fiber.Ctx) erro
// GetAllStatusEndpoint returns all the jobs status progress
// @Summary Returns all the jobs status progress
// @Success 200 {object} map[string]services.BackendOpStatus "Response"
// @Success 200 {object} map[string]services.GalleryOpStatus "Response"
// @Router /backends/jobs [get]
func (mgs *BackendEndpointService) GetAllStatusEndpoint() func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
@@ -58,7 +58,7 @@ func (mgs *BackendEndpointService) GetAllStatusEndpoint() func(c *fiber.Ctx) err
// ApplyBackendEndpoint installs a new backend to a LocalAI instance
// @Summary Install backends to LocalAI.
// @Param request body BackendModel true "query params"
// @Param request body GalleryBackend true "query params"
// @Success 200 {object} schema.BackendResponse "Response"
// @Router /backends/apply [post]
func (mgs *BackendEndpointService) ApplyBackendEndpoint() func(c *fiber.Ctx) error {

View File

@@ -0,0 +1,59 @@
package localai
import (
"github.com/gofiber/fiber/v2"
"github.com/mudler/LocalAI/core/backend"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/http/middleware"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/utils"
"github.com/rs/zerolog/log"
)
// DetectionEndpoint is the LocalAI Detection endpoint https://localai.io/docs/api-reference/detection
// @Summary Detects objects in the input image.
// @Param request body schema.DetectionRequest true "query params"
// @Success 200 {object} schema.DetectionResponse "Response"
// @Router /v1/detection [post]
func DetectionEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
input, ok := c.Locals(middleware.CONTEXT_LOCALS_KEY_LOCALAI_REQUEST).(*schema.DetectionRequest)
if !ok || input.Model == "" {
return fiber.ErrBadRequest
}
cfg, ok := c.Locals(middleware.CONTEXT_LOCALS_KEY_MODEL_CONFIG).(*config.BackendConfig)
if !ok || cfg == nil {
return fiber.ErrBadRequest
}
log.Debug().Str("image", input.Image).Str("modelFile", "modelFile").Str("backend", cfg.Backend).Msg("Detection")
image, err := utils.GetContentURIAsBase64(input.Image)
if err != nil {
return err
}
res, err := backend.Detection(image, ml, appConfig, *cfg)
if err != nil {
return err
}
response := schema.DetectionResponse{
Detections: make([]schema.Detection, len(res.Detections)),
}
for i, detection := range res.Detections {
response.Detections[i] = schema.Detection{
X: detection.X,
Y: detection.Y,
Width: detection.Width,
Height: detection.Height,
ClassName: detection.ClassName,
}
}
return c.JSON(response)
}
}

View File

@@ -15,9 +15,10 @@ import (
)
type ModelGalleryEndpointService struct {
galleries []config.Gallery
modelPath string
galleryApplier *services.GalleryService
galleries []config.Gallery
backendGalleries []config.Gallery
modelPath string
galleryApplier *services.GalleryService
}
type GalleryModel struct {
@@ -25,11 +26,12 @@ type GalleryModel struct {
gallery.GalleryModel
}
func CreateModelGalleryEndpointService(galleries []config.Gallery, modelPath string, galleryApplier *services.GalleryService) ModelGalleryEndpointService {
func CreateModelGalleryEndpointService(galleries []config.Gallery, backendGalleries []config.Gallery, modelPath string, galleryApplier *services.GalleryService) ModelGalleryEndpointService {
return ModelGalleryEndpointService{
galleries: galleries,
modelPath: modelPath,
galleryApplier: galleryApplier,
galleries: galleries,
backendGalleries: backendGalleries,
modelPath: modelPath,
galleryApplier: galleryApplier,
}
}
@@ -79,6 +81,7 @@ func (mgs *ModelGalleryEndpointService) ApplyModelGalleryEndpoint() func(c *fibe
ID: uuid.String(),
GalleryElementName: input.ID,
Galleries: mgs.galleries,
BackendGalleries: mgs.backendGalleries,
}
return c.JSON(schema.GalleryResponse{ID: uuid.String(), StatusURL: fmt.Sprintf("%smodels/jobs/%s", utils.BaseURL(c), uuid.String())})

View File

@@ -1,522 +0,0 @@
package openai
import (
"fmt"
"net/http"
"sort"
"strconv"
"strings"
"sync/atomic"
"time"
"github.com/gofiber/fiber/v2"
"github.com/microcosm-cc/bluemonday"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services"
model "github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/utils"
"github.com/rs/zerolog/log"
)
// ToolType defines a type for tool options
type ToolType string
const (
CodeInterpreter ToolType = "code_interpreter"
Retrieval ToolType = "retrieval"
Function ToolType = "function"
MaxCharacterInstructions = 32768
MaxCharacterDescription = 512
MaxCharacterName = 256
MaxToolsSize = 128
MaxFileIdSize = 20
MaxCharacterMetadataKey = 64
MaxCharacterMetadataValue = 512
)
type Tool struct {
Type ToolType `json:"type"`
}
// Assistant represents the structure of an assistant object from the OpenAI API.
type Assistant struct {
ID string `json:"id"` // The unique identifier of the assistant.
Object string `json:"object"` // Object type, which is "assistant".
Created int64 `json:"created"` // The time at which the assistant was created.
Model string `json:"model"` // The model ID used by the assistant.
Name string `json:"name,omitempty"` // The name of the assistant.
Description string `json:"description,omitempty"` // The description of the assistant.
Instructions string `json:"instructions,omitempty"` // The system instructions that the assistant uses.
Tools []Tool `json:"tools,omitempty"` // A list of tools enabled on the assistant.
FileIDs []string `json:"file_ids,omitempty"` // A list of file IDs attached to this assistant.
Metadata map[string]string `json:"metadata,omitempty"` // Set of key-value pairs attached to the assistant.
}
var (
Assistants = []Assistant{} // better to return empty array instead of "null"
AssistantsConfigFile = "assistants.json"
)
type AssistantRequest struct {
Model string `json:"model"`
Name string `json:"name,omitempty"`
Description string `json:"description,omitempty"`
Instructions string `json:"instructions,omitempty"`
Tools []Tool `json:"tools,omitempty"`
FileIDs []string `json:"file_ids,omitempty"`
Metadata map[string]string `json:"metadata,omitempty"`
}
// CreateAssistantEndpoint is the OpenAI Assistant API endpoint https://platform.openai.com/docs/api-reference/assistants/createAssistant
// @Summary Create an assistant with a model and instructions.
// @Param request body AssistantRequest true "query params"
// @Success 200 {object} Assistant "Response"
// @Router /v1/assistants [post]
func CreateAssistantEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
request := new(AssistantRequest)
if err := c.BodyParser(request); err != nil {
log.Warn().AnErr("Unable to parse AssistantRequest", err)
return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "Cannot parse JSON"})
}
if !modelExists(cl, ml, request.Model) {
log.Warn().Msgf("Model: %s was not found in list of models.", request.Model)
return c.Status(fiber.StatusBadRequest).SendString(bluemonday.StrictPolicy().Sanitize(fmt.Sprintf("Model %q not found", request.Model)))
}
if request.Tools == nil {
request.Tools = []Tool{}
}
if request.FileIDs == nil {
request.FileIDs = []string{}
}
if request.Metadata == nil {
request.Metadata = make(map[string]string)
}
id := "asst_" + strconv.FormatInt(generateRandomID(), 10)
assistant := Assistant{
ID: id,
Object: "assistant",
Created: time.Now().Unix(),
Model: request.Model,
Name: request.Name,
Description: request.Description,
Instructions: request.Instructions,
Tools: request.Tools,
FileIDs: request.FileIDs,
Metadata: request.Metadata,
}
Assistants = append(Assistants, assistant)
utils.SaveConfig(appConfig.ConfigsDir, AssistantsConfigFile, Assistants)
return c.Status(fiber.StatusOK).JSON(assistant)
}
}
var currentId int64 = 0
func generateRandomID() int64 {
atomic.AddInt64(&currentId, 1)
return currentId
}
// ListAssistantsEndpoint is the OpenAI Assistant API endpoint to list assistents https://platform.openai.com/docs/api-reference/assistants/listAssistants
// @Summary List available assistents
// @Param limit query int false "Limit the number of assistants returned"
// @Param order query string false "Order of assistants returned"
// @Param after query string false "Return assistants created after the given ID"
// @Param before query string false "Return assistants created before the given ID"
// @Success 200 {object} []Assistant "Response"
// @Router /v1/assistants [get]
func ListAssistantsEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
// Because we're altering the existing assistants list we should just duplicate it for now.
returnAssistants := Assistants
// Parse query parameters
limitQuery := c.Query("limit", "20")
orderQuery := c.Query("order", "desc")
afterQuery := c.Query("after")
beforeQuery := c.Query("before")
// Convert string limit to integer
limit, err := strconv.Atoi(limitQuery)
if err != nil {
return c.Status(http.StatusBadRequest).SendString(bluemonday.StrictPolicy().Sanitize(fmt.Sprintf("Invalid limit query value: %s", limitQuery)))
}
// Sort assistants
sort.SliceStable(returnAssistants, func(i, j int) bool {
if orderQuery == "asc" {
return returnAssistants[i].Created < returnAssistants[j].Created
}
return returnAssistants[i].Created > returnAssistants[j].Created
})
// After and before cursors
if afterQuery != "" {
returnAssistants = filterAssistantsAfterID(returnAssistants, afterQuery)
}
if beforeQuery != "" {
returnAssistants = filterAssistantsBeforeID(returnAssistants, beforeQuery)
}
// Apply limit
if limit < len(returnAssistants) {
returnAssistants = returnAssistants[:limit]
}
return c.JSON(returnAssistants)
}
}
// FilterAssistantsBeforeID filters out those assistants whose ID comes before the given ID
// We assume that the assistants are already sorted
func filterAssistantsBeforeID(assistants []Assistant, id string) []Assistant {
idInt, err := strconv.Atoi(id)
if err != nil {
return assistants // Return original slice if invalid id format is provided
}
var filteredAssistants []Assistant
for _, assistant := range assistants {
aid, err := strconv.Atoi(strings.TrimPrefix(assistant.ID, "asst_"))
if err != nil {
continue // Skip if invalid id in assistant
}
if aid < idInt {
filteredAssistants = append(filteredAssistants, assistant)
}
}
return filteredAssistants
}
// FilterAssistantsAfterID filters out those assistants whose ID comes after the given ID
// We assume that the assistants are already sorted
func filterAssistantsAfterID(assistants []Assistant, id string) []Assistant {
idInt, err := strconv.Atoi(id)
if err != nil {
return assistants // Return original slice if invalid id format is provided
}
var filteredAssistants []Assistant
for _, assistant := range assistants {
aid, err := strconv.Atoi(strings.TrimPrefix(assistant.ID, "asst_"))
if err != nil {
continue // Skip if invalid id in assistant
}
if aid > idInt {
filteredAssistants = append(filteredAssistants, assistant)
}
}
return filteredAssistants
}
func modelExists(cl *config.BackendConfigLoader, ml *model.ModelLoader, modelName string) (found bool) {
found = false
models, err := services.ListModels(cl, ml, config.NoFilterFn, services.SKIP_IF_CONFIGURED)
if err != nil {
return
}
for _, model := range models {
if model == modelName {
found = true
return
}
}
return
}
// DeleteAssistantEndpoint is the OpenAI Assistant API endpoint to delete assistents https://platform.openai.com/docs/api-reference/assistants/deleteAssistant
// @Summary Delete assistents
// @Success 200 {object} schema.DeleteAssistantResponse "Response"
// @Router /v1/assistants/{assistant_id} [delete]
func DeleteAssistantEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
assistantID := c.Params("assistant_id")
if assistantID == "" {
return c.Status(fiber.StatusBadRequest).SendString("parameter assistant_id is required")
}
for i, assistant := range Assistants {
if assistant.ID == assistantID {
Assistants = append(Assistants[:i], Assistants[i+1:]...)
utils.SaveConfig(appConfig.ConfigsDir, AssistantsConfigFile, Assistants)
return c.Status(fiber.StatusOK).JSON(schema.DeleteAssistantResponse{
ID: assistantID,
Object: "assistant.deleted",
Deleted: true,
})
}
}
log.Warn().Msgf("Unable to find assistant %s for deletion", assistantID)
return c.Status(fiber.StatusNotFound).JSON(schema.DeleteAssistantResponse{
ID: assistantID,
Object: "assistant.deleted",
Deleted: false,
})
}
}
// GetAssistantEndpoint is the OpenAI Assistant API endpoint to get assistents https://platform.openai.com/docs/api-reference/assistants/getAssistant
// @Summary Get assistent data
// @Success 200 {object} Assistant "Response"
// @Router /v1/assistants/{assistant_id} [get]
func GetAssistantEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
assistantID := c.Params("assistant_id")
if assistantID == "" {
return c.Status(fiber.StatusBadRequest).SendString("parameter assistant_id is required")
}
for _, assistant := range Assistants {
if assistant.ID == assistantID {
return c.Status(fiber.StatusOK).JSON(assistant)
}
}
return c.Status(fiber.StatusNotFound).SendString(bluemonday.StrictPolicy().Sanitize(fmt.Sprintf("Unable to find assistant with id: %s", assistantID)))
}
}
type AssistantFile struct {
ID string `json:"id"`
Object string `json:"object"`
CreatedAt int64 `json:"created_at"`
AssistantID string `json:"assistant_id"`
}
var (
AssistantFiles []AssistantFile
AssistantsFileConfigFile = "assistantsFile.json"
)
func CreateAssistantFileEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
request := new(schema.AssistantFileRequest)
if err := c.BodyParser(request); err != nil {
return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "Cannot parse JSON"})
}
assistantID := c.Params("assistant_id")
if assistantID == "" {
return c.Status(fiber.StatusBadRequest).SendString("parameter assistant_id is required")
}
for _, assistant := range Assistants {
if assistant.ID == assistantID {
if len(assistant.FileIDs) > MaxFileIdSize {
return c.Status(fiber.StatusBadRequest).SendString(fmt.Sprintf("Max files %d for assistant %s reached.", MaxFileIdSize, assistant.Name))
}
for _, file := range UploadedFiles {
if file.ID == request.FileID {
assistant.FileIDs = append(assistant.FileIDs, request.FileID)
assistantFile := AssistantFile{
ID: file.ID,
Object: "assistant.file",
CreatedAt: time.Now().Unix(),
AssistantID: assistant.ID,
}
AssistantFiles = append(AssistantFiles, assistantFile)
utils.SaveConfig(appConfig.ConfigsDir, AssistantsFileConfigFile, AssistantFiles)
return c.Status(fiber.StatusOK).JSON(assistantFile)
}
}
return c.Status(fiber.StatusNotFound).SendString(bluemonday.StrictPolicy().Sanitize(fmt.Sprintf("Unable to find file_id: %s", request.FileID)))
}
}
return c.Status(fiber.StatusNotFound).SendString(bluemonday.StrictPolicy().Sanitize(fmt.Sprintf("Unable to find %q", assistantID)))
}
}
func ListAssistantFilesEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
type ListAssistantFiles struct {
Data []schema.File
Object string
}
return func(c *fiber.Ctx) error {
assistantID := c.Params("assistant_id")
if assistantID == "" {
return c.Status(fiber.StatusBadRequest).SendString("parameter assistant_id is required")
}
limitQuery := c.Query("limit", "20")
order := c.Query("order", "desc")
limit, err := strconv.Atoi(limitQuery)
if err != nil || limit < 1 || limit > 100 {
limit = 20 // Default to 20 if there's an error or the limit is out of bounds
}
// Sort files by CreatedAt depending on the order query parameter
if order == "asc" {
sort.Slice(AssistantFiles, func(i, j int) bool {
return AssistantFiles[i].CreatedAt < AssistantFiles[j].CreatedAt
})
} else { // default to "desc"
sort.Slice(AssistantFiles, func(i, j int) bool {
return AssistantFiles[i].CreatedAt > AssistantFiles[j].CreatedAt
})
}
// Limit the number of files returned
var limitedFiles []AssistantFile
hasMore := false
if len(AssistantFiles) > limit {
hasMore = true
limitedFiles = AssistantFiles[:limit]
} else {
limitedFiles = AssistantFiles
}
response := map[string]interface{}{
"object": "list",
"data": limitedFiles,
"first_id": func() string {
if len(limitedFiles) > 0 {
return limitedFiles[0].ID
}
return ""
}(),
"last_id": func() string {
if len(limitedFiles) > 0 {
return limitedFiles[len(limitedFiles)-1].ID
}
return ""
}(),
"has_more": hasMore,
}
return c.Status(fiber.StatusOK).JSON(response)
}
}
func ModifyAssistantEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
request := new(AssistantRequest)
if err := c.BodyParser(request); err != nil {
log.Warn().AnErr("Unable to parse AssistantRequest", err)
return c.Status(fiber.StatusBadRequest).JSON(fiber.Map{"error": "Cannot parse JSON"})
}
assistantID := c.Params("assistant_id")
if assistantID == "" {
return c.Status(fiber.StatusBadRequest).SendString("parameter assistant_id is required")
}
for i, assistant := range Assistants {
if assistant.ID == assistantID {
newAssistant := Assistant{
ID: assistantID,
Object: assistant.Object,
Created: assistant.Created,
Model: request.Model,
Name: request.Name,
Description: request.Description,
Instructions: request.Instructions,
Tools: request.Tools,
FileIDs: request.FileIDs, // todo: should probably verify fileids exist
Metadata: request.Metadata,
}
// Remove old one and replace with new one
Assistants = append(Assistants[:i], Assistants[i+1:]...)
Assistants = append(Assistants, newAssistant)
utils.SaveConfig(appConfig.ConfigsDir, AssistantsConfigFile, Assistants)
return c.Status(fiber.StatusOK).JSON(newAssistant)
}
}
return c.Status(fiber.StatusNotFound).SendString(bluemonday.StrictPolicy().Sanitize(fmt.Sprintf("Unable to find assistant with id: %s", assistantID)))
}
}
func DeleteAssistantFileEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
assistantID := c.Params("assistant_id")
fileId := c.Params("file_id")
if assistantID == "" {
return c.Status(fiber.StatusBadRequest).SendString("parameter assistant_id and file_id are required")
}
// First remove file from assistant
for i, assistant := range Assistants {
if assistant.ID == assistantID {
for j, fileId := range assistant.FileIDs {
Assistants[i].FileIDs = append(Assistants[i].FileIDs[:j], Assistants[i].FileIDs[j+1:]...)
// Check if the file exists in the assistantFiles slice
for i, assistantFile := range AssistantFiles {
if assistantFile.ID == fileId {
// Remove the file from the assistantFiles slice
AssistantFiles = append(AssistantFiles[:i], AssistantFiles[i+1:]...)
utils.SaveConfig(appConfig.ConfigsDir, AssistantsFileConfigFile, AssistantFiles)
return c.Status(fiber.StatusOK).JSON(schema.DeleteAssistantFileResponse{
ID: fileId,
Object: "assistant.file.deleted",
Deleted: true,
})
}
}
}
log.Warn().Msgf("Unable to locate file_id: %s in assistants: %s. Continuing to delete assistant file.", fileId, assistantID)
for i, assistantFile := range AssistantFiles {
if assistantFile.AssistantID == assistantID {
AssistantFiles = append(AssistantFiles[:i], AssistantFiles[i+1:]...)
utils.SaveConfig(appConfig.ConfigsDir, AssistantsFileConfigFile, AssistantFiles)
return c.Status(fiber.StatusNotFound).JSON(schema.DeleteAssistantFileResponse{
ID: fileId,
Object: "assistant.file.deleted",
Deleted: true,
})
}
}
}
}
log.Warn().Msgf("Unable to find assistant: %s", assistantID)
return c.Status(fiber.StatusNotFound).JSON(schema.DeleteAssistantFileResponse{
ID: fileId,
Object: "assistant.file.deleted",
Deleted: false,
})
}
}
func GetAssistantFileEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
assistantID := c.Params("assistant_id")
fileId := c.Params("file_id")
if assistantID == "" {
return c.Status(fiber.StatusBadRequest).SendString("parameter assistant_id and file_id are required")
}
for _, assistantFile := range AssistantFiles {
if assistantFile.AssistantID == assistantID {
if assistantFile.ID == fileId {
return c.Status(fiber.StatusOK).JSON(assistantFile)
}
return c.Status(fiber.StatusNotFound).SendString(bluemonday.StrictPolicy().Sanitize(fmt.Sprintf("Unable to find assistant file with file_id: %s", fileId)))
}
}
return c.Status(fiber.StatusNotFound).SendString(bluemonday.StrictPolicy().Sanitize(fmt.Sprintf("Unable to find assistant file with assistant_id: %s", assistantID)))
}
}

View File

@@ -1,460 +0,0 @@
package openai
import (
"encoding/json"
"fmt"
"io"
"net/http"
"net/http/httptest"
"os"
"path/filepath"
"strings"
"testing"
"time"
"github.com/gofiber/fiber/v2"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/pkg/model"
"github.com/stretchr/testify/assert"
)
var configsDir string = "/tmp/localai/configs"
type MockLoader struct {
models []string
}
func tearDown() func() {
return func() {
UploadedFiles = []schema.File{}
Assistants = []Assistant{}
AssistantFiles = []AssistantFile{}
_ = os.Remove(filepath.Join(configsDir, AssistantsConfigFile))
_ = os.Remove(filepath.Join(configsDir, AssistantsFileConfigFile))
}
}
func TestAssistantEndpoints(t *testing.T) {
// Preparing the mocked objects
cl := &config.BackendConfigLoader{}
//configsDir := "/tmp/localai/configs"
modelPath := "/tmp/localai/model"
var ml = model.NewModelLoader(modelPath, false)
appConfig := &config.ApplicationConfig{
ConfigsDir: configsDir,
UploadLimitMB: 10,
UploadDir: "test_dir",
ModelPath: modelPath,
}
_ = os.RemoveAll(appConfig.ConfigsDir)
_ = os.MkdirAll(appConfig.ConfigsDir, 0750)
_ = os.MkdirAll(modelPath, 0750)
os.Create(filepath.Join(modelPath, "ggml-gpt4all-j"))
app := fiber.New(fiber.Config{
BodyLimit: 20 * 1024 * 1024, // sets the limit to 20MB.
})
// Create a Test Server
app.Get("/assistants", ListAssistantsEndpoint(cl, ml, appConfig))
app.Post("/assistants", CreateAssistantEndpoint(cl, ml, appConfig))
app.Delete("/assistants/:assistant_id", DeleteAssistantEndpoint(cl, ml, appConfig))
app.Get("/assistants/:assistant_id", GetAssistantEndpoint(cl, ml, appConfig))
app.Post("/assistants/:assistant_id", ModifyAssistantEndpoint(cl, ml, appConfig))
app.Post("/files", UploadFilesEndpoint(cl, appConfig))
app.Get("/assistants/:assistant_id/files", ListAssistantFilesEndpoint(cl, ml, appConfig))
app.Post("/assistants/:assistant_id/files", CreateAssistantFileEndpoint(cl, ml, appConfig))
app.Delete("/assistants/:assistant_id/files/:file_id", DeleteAssistantFileEndpoint(cl, ml, appConfig))
app.Get("/assistants/:assistant_id/files/:file_id", GetAssistantFileEndpoint(cl, ml, appConfig))
t.Run("CreateAssistantEndpoint", func(t *testing.T) {
t.Cleanup(tearDown())
ar := &AssistantRequest{
Model: "ggml-gpt4all-j",
Name: "3.5-turbo",
Description: "Test Assistant",
Instructions: "You are computer science teacher answering student questions",
Tools: []Tool{{Type: Function}},
FileIDs: nil,
Metadata: nil,
}
resultAssistant, resp, err := createAssistant(app, *ar)
assert.NoError(t, err)
assert.Equal(t, fiber.StatusOK, resp.StatusCode)
assert.Equal(t, 1, len(Assistants))
//t.Cleanup(cleanupAllAssistants(t, app, []string{resultAssistant.ID}))
assert.Equal(t, ar.Name, resultAssistant.Name)
assert.Equal(t, ar.Model, resultAssistant.Model)
assert.Equal(t, ar.Tools, resultAssistant.Tools)
assert.Equal(t, ar.Description, resultAssistant.Description)
assert.Equal(t, ar.Instructions, resultAssistant.Instructions)
assert.Equal(t, ar.FileIDs, resultAssistant.FileIDs)
assert.Equal(t, ar.Metadata, resultAssistant.Metadata)
})
t.Run("ListAssistantsEndpoint", func(t *testing.T) {
var ids []string
var resultAssistant []Assistant
for i := 0; i < 4; i++ {
ar := &AssistantRequest{
Model: "ggml-gpt4all-j",
Name: fmt.Sprintf("3.5-turbo-%d", i),
Description: fmt.Sprintf("Test Assistant - %d", i),
Instructions: fmt.Sprintf("You are computer science teacher answering student questions - %d", i),
Tools: []Tool{{Type: Function}},
FileIDs: []string{"fid-1234"},
Metadata: map[string]string{"meta": "data"},
}
//var err error
ra, _, err := createAssistant(app, *ar)
// Because we create the assistants so fast all end up with the same created time.
time.Sleep(time.Second)
resultAssistant = append(resultAssistant, ra)
assert.NoError(t, err)
ids = append(ids, resultAssistant[i].ID)
}
t.Cleanup(cleanupAllAssistants(t, app, ids))
tests := []struct {
name string
reqURL string
expectedStatus int
expectedResult []Assistant
expectedStringResult string
}{
{
name: "Valid Usage - limit only",
reqURL: "/assistants?limit=2",
expectedStatus: http.StatusOK,
expectedResult: Assistants[:2], // Expecting the first two assistants
},
{
name: "Valid Usage - order asc",
reqURL: "/assistants?order=asc",
expectedStatus: http.StatusOK,
expectedResult: Assistants, // Expecting all assistants in ascending order
},
{
name: "Valid Usage - order desc",
reqURL: "/assistants?order=desc",
expectedStatus: http.StatusOK,
expectedResult: []Assistant{Assistants[3], Assistants[2], Assistants[1], Assistants[0]}, // Expecting all assistants in descending order
},
{
name: "Valid Usage - after specific ID",
reqURL: "/assistants?after=2",
expectedStatus: http.StatusOK,
// Note this is correct because it's put in descending order already
expectedResult: Assistants[:3], // Expecting assistants after (excluding) ID 2
},
{
name: "Valid Usage - before specific ID",
reqURL: "/assistants?before=4",
expectedStatus: http.StatusOK,
expectedResult: Assistants[2:], // Expecting assistants before (excluding) ID 3.
},
{
name: "Invalid Usage - non-integer limit",
reqURL: "/assistants?limit=two",
expectedStatus: http.StatusBadRequest,
expectedStringResult: "Invalid limit query value: two",
},
{
name: "Invalid Usage - non-existing id in after",
reqURL: "/assistants?after=100",
expectedStatus: http.StatusOK,
expectedResult: []Assistant(nil), // Expecting empty list as there are no IDs above 100
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
request := httptest.NewRequest(http.MethodGet, tt.reqURL, nil)
response, err := app.Test(request)
assert.NoError(t, err)
assert.Equal(t, tt.expectedStatus, response.StatusCode)
if tt.expectedStatus != fiber.StatusOK {
all, _ := io.ReadAll(response.Body)
assert.Equal(t, tt.expectedStringResult, string(all))
} else {
var result []Assistant
err = json.NewDecoder(response.Body).Decode(&result)
assert.NoError(t, err)
assert.Equal(t, tt.expectedResult, result)
}
})
}
})
t.Run("DeleteAssistantEndpoint", func(t *testing.T) {
ar := &AssistantRequest{
Model: "ggml-gpt4all-j",
Name: "3.5-turbo",
Description: "Test Assistant",
Instructions: "You are computer science teacher answering student questions",
Tools: []Tool{{Type: Function}},
FileIDs: nil,
Metadata: nil,
}
resultAssistant, _, err := createAssistant(app, *ar)
assert.NoError(t, err)
target := fmt.Sprintf("/assistants/%s", resultAssistant.ID)
deleteReq := httptest.NewRequest(http.MethodDelete, target, nil)
_, err = app.Test(deleteReq)
assert.NoError(t, err)
assert.Equal(t, 0, len(Assistants))
})
t.Run("GetAssistantEndpoint", func(t *testing.T) {
ar := &AssistantRequest{
Model: "ggml-gpt4all-j",
Name: "3.5-turbo",
Description: "Test Assistant",
Instructions: "You are computer science teacher answering student questions",
Tools: []Tool{{Type: Function}},
FileIDs: nil,
Metadata: nil,
}
resultAssistant, _, err := createAssistant(app, *ar)
assert.NoError(t, err)
t.Cleanup(cleanupAllAssistants(t, app, []string{resultAssistant.ID}))
target := fmt.Sprintf("/assistants/%s", resultAssistant.ID)
request := httptest.NewRequest(http.MethodGet, target, nil)
response, err := app.Test(request)
assert.NoError(t, err)
var getAssistant Assistant
err = json.NewDecoder(response.Body).Decode(&getAssistant)
assert.NoError(t, err)
assert.Equal(t, resultAssistant.ID, getAssistant.ID)
})
t.Run("ModifyAssistantEndpoint", func(t *testing.T) {
ar := &AssistantRequest{
Model: "ggml-gpt4all-j",
Name: "3.5-turbo",
Description: "Test Assistant",
Instructions: "You are computer science teacher answering student questions",
Tools: []Tool{{Type: Function}},
FileIDs: nil,
Metadata: nil,
}
resultAssistant, _, err := createAssistant(app, *ar)
assert.NoError(t, err)
modifiedAr := &AssistantRequest{
Model: "ggml-gpt4all-j",
Name: "4.0-turbo",
Description: "Modified Test Assistant",
Instructions: "You are math teacher answering student questions",
Tools: []Tool{{Type: CodeInterpreter}},
FileIDs: nil,
Metadata: nil,
}
modifiedArJson, err := json.Marshal(modifiedAr)
assert.NoError(t, err)
target := fmt.Sprintf("/assistants/%s", resultAssistant.ID)
request := httptest.NewRequest(http.MethodPost, target, strings.NewReader(string(modifiedArJson)))
request.Header.Set(fiber.HeaderContentType, "application/json")
modifyResponse, err := app.Test(request)
assert.NoError(t, err)
var getAssistant Assistant
err = json.NewDecoder(modifyResponse.Body).Decode(&getAssistant)
assert.NoError(t, err)
t.Cleanup(cleanupAllAssistants(t, app, []string{getAssistant.ID}))
assert.Equal(t, resultAssistant.ID, getAssistant.ID) // IDs should match even if contents change
assert.Equal(t, modifiedAr.Tools, getAssistant.Tools)
assert.Equal(t, modifiedAr.Name, getAssistant.Name)
assert.Equal(t, modifiedAr.Instructions, getAssistant.Instructions)
assert.Equal(t, modifiedAr.Description, getAssistant.Description)
})
t.Run("CreateAssistantFileEndpoint", func(t *testing.T) {
t.Cleanup(tearDown())
file, assistant, err := createFileAndAssistant(t, app, appConfig)
assert.NoError(t, err)
afr := schema.AssistantFileRequest{FileID: file.ID}
af, _, err := createAssistantFile(app, afr, assistant.ID)
assert.NoError(t, err)
assert.Equal(t, assistant.ID, af.AssistantID)
})
t.Run("ListAssistantFilesEndpoint", func(t *testing.T) {
t.Cleanup(tearDown())
file, assistant, err := createFileAndAssistant(t, app, appConfig)
assert.NoError(t, err)
afr := schema.AssistantFileRequest{FileID: file.ID}
af, _, err := createAssistantFile(app, afr, assistant.ID)
assert.NoError(t, err)
assert.Equal(t, assistant.ID, af.AssistantID)
})
t.Run("GetAssistantFileEndpoint", func(t *testing.T) {
t.Cleanup(tearDown())
file, assistant, err := createFileAndAssistant(t, app, appConfig)
assert.NoError(t, err)
afr := schema.AssistantFileRequest{FileID: file.ID}
af, _, err := createAssistantFile(app, afr, assistant.ID)
assert.NoError(t, err)
t.Cleanup(cleanupAssistantFile(t, app, af.ID, af.AssistantID))
target := fmt.Sprintf("/assistants/%s/files/%s", assistant.ID, file.ID)
request := httptest.NewRequest(http.MethodGet, target, nil)
response, err := app.Test(request)
assert.NoError(t, err)
var assistantFile AssistantFile
err = json.NewDecoder(response.Body).Decode(&assistantFile)
assert.NoError(t, err)
assert.Equal(t, af.ID, assistantFile.ID)
assert.Equal(t, af.AssistantID, assistantFile.AssistantID)
})
t.Run("DeleteAssistantFileEndpoint", func(t *testing.T) {
t.Cleanup(tearDown())
file, assistant, err := createFileAndAssistant(t, app, appConfig)
assert.NoError(t, err)
afr := schema.AssistantFileRequest{FileID: file.ID}
af, _, err := createAssistantFile(app, afr, assistant.ID)
assert.NoError(t, err)
cleanupAssistantFile(t, app, af.ID, af.AssistantID)()
assert.Empty(t, AssistantFiles)
})
}
func createFileAndAssistant(t *testing.T, app *fiber.App, o *config.ApplicationConfig) (schema.File, Assistant, error) {
ar := &AssistantRequest{
Model: "ggml-gpt4all-j",
Name: "3.5-turbo",
Description: "Test Assistant",
Instructions: "You are computer science teacher answering student questions",
Tools: []Tool{{Type: Function}},
FileIDs: nil,
Metadata: nil,
}
assistant, _, err := createAssistant(app, *ar)
if err != nil {
return schema.File{}, Assistant{}, err
}
t.Cleanup(cleanupAllAssistants(t, app, []string{assistant.ID}))
file := CallFilesUploadEndpointWithCleanup(t, app, "test.txt", "file", "fine-tune", 5, o)
t.Cleanup(func() {
_, err := CallFilesDeleteEndpoint(t, app, file.ID)
assert.NoError(t, err)
})
return file, assistant, nil
}
func createAssistantFile(app *fiber.App, afr schema.AssistantFileRequest, assistantId string) (AssistantFile, *http.Response, error) {
afrJson, err := json.Marshal(afr)
if err != nil {
return AssistantFile{}, nil, err
}
target := fmt.Sprintf("/assistants/%s/files", assistantId)
request := httptest.NewRequest(http.MethodPost, target, strings.NewReader(string(afrJson)))
request.Header.Set(fiber.HeaderContentType, "application/json")
request.Header.Set("OpenAi-Beta", "assistants=v1")
resp, err := app.Test(request)
if err != nil {
return AssistantFile{}, resp, err
}
var assistantFile AssistantFile
all, err := io.ReadAll(resp.Body)
if err != nil {
return AssistantFile{}, resp, err
}
err = json.NewDecoder(strings.NewReader(string(all))).Decode(&assistantFile)
if err != nil {
return AssistantFile{}, resp, err
}
return assistantFile, resp, nil
}
func createAssistant(app *fiber.App, ar AssistantRequest) (Assistant, *http.Response, error) {
assistant, err := json.Marshal(ar)
if err != nil {
return Assistant{}, nil, err
}
request := httptest.NewRequest(http.MethodPost, "/assistants", strings.NewReader(string(assistant)))
request.Header.Set(fiber.HeaderContentType, "application/json")
request.Header.Set("OpenAi-Beta", "assistants=v1")
resp, err := app.Test(request)
if err != nil {
return Assistant{}, resp, err
}
bodyString, err := io.ReadAll(resp.Body)
if err != nil {
return Assistant{}, resp, err
}
var resultAssistant Assistant
err = json.NewDecoder(strings.NewReader(string(bodyString))).Decode(&resultAssistant)
return resultAssistant, resp, err
}
func cleanupAllAssistants(t *testing.T, app *fiber.App, ids []string) func() {
return func() {
for _, assistant := range ids {
target := fmt.Sprintf("/assistants/%s", assistant)
deleteReq := httptest.NewRequest(http.MethodDelete, target, nil)
_, err := app.Test(deleteReq)
if err != nil {
t.Fatalf("Failed to delete assistant %s: %v", assistant, err)
}
}
}
}
func cleanupAssistantFile(t *testing.T, app *fiber.App, fileId, assistantId string) func() {
return func() {
target := fmt.Sprintf("/assistants/%s/files/%s", assistantId, fileId)
request := httptest.NewRequest(http.MethodDelete, target, nil)
request.Header.Set(fiber.HeaderContentType, "application/json")
request.Header.Set("OpenAi-Beta", "assistants=v1")
resp, err := app.Test(request)
assert.NoError(t, err)
var dafr schema.DeleteAssistantFileResponse
err = json.NewDecoder(resp.Body).Decode(&dafr)
assert.NoError(t, err)
assert.True(t, dafr.Deleted)
}
}

View File

@@ -15,8 +15,8 @@ import (
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/pkg/functions"
"github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/templates"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
@@ -175,7 +175,7 @@ func ChatEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, evaluat
textContentToReturn = ""
id = uuid.New().String()
created = int(time.Now().Unix())
input, ok := c.Locals(middleware.CONTEXT_LOCALS_KEY_LOCALAI_REQUEST).(*schema.OpenAIRequest)
if !ok || input.Model == "" {
return fiber.ErrBadRequest

View File

@@ -15,9 +15,9 @@ import (
"github.com/gofiber/fiber/v2"
"github.com/google/uuid"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/functions"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/templates"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)

View File

@@ -12,8 +12,8 @@ import (
"github.com/google/uuid"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/templates"
"github.com/rs/zerolog/log"
)

View File

@@ -1,194 +0,0 @@
package openai
import (
"errors"
"fmt"
"os"
"path/filepath"
"sync/atomic"
"time"
"github.com/microcosm-cc/bluemonday"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/gofiber/fiber/v2"
"github.com/mudler/LocalAI/pkg/utils"
)
var UploadedFiles []schema.File
const UploadedFilesFile = "uploadedFiles.json"
// UploadFilesEndpoint https://platform.openai.com/docs/api-reference/files/create
func UploadFilesEndpoint(cm *config.BackendConfigLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
file, err := c.FormFile("file")
if err != nil {
return err
}
// Check the file size
if file.Size > int64(appConfig.UploadLimitMB*1024*1024) {
return c.Status(fiber.StatusBadRequest).SendString(fmt.Sprintf("File size %d exceeds upload limit %d", file.Size, appConfig.UploadLimitMB))
}
purpose := c.FormValue("purpose", "") //TODO put in purpose dirs
if purpose == "" {
return c.Status(fiber.StatusBadRequest).SendString("Purpose is not defined")
}
// Sanitize the filename to prevent directory traversal
filename := utils.SanitizeFileName(file.Filename)
savePath := filepath.Join(appConfig.UploadDir, filename)
// Check if file already exists
if _, err := os.Stat(savePath); !os.IsNotExist(err) {
return c.Status(fiber.StatusBadRequest).SendString("File already exists")
}
err = c.SaveFile(file, savePath)
if err != nil {
return c.Status(fiber.StatusInternalServerError).SendString("Failed to save file: " + bluemonday.StrictPolicy().Sanitize(err.Error()))
}
f := schema.File{
ID: fmt.Sprintf("file-%d", getNextFileId()),
Object: "file",
Bytes: int(file.Size),
CreatedAt: time.Now(),
Filename: file.Filename,
Purpose: purpose,
}
UploadedFiles = append(UploadedFiles, f)
utils.SaveConfig(appConfig.UploadDir, UploadedFilesFile, UploadedFiles)
return c.Status(fiber.StatusOK).JSON(f)
}
}
var currentFileId int64 = 0
func getNextFileId() int64 {
atomic.AddInt64(&currentId, 1)
return currentId
}
// ListFilesEndpoint https://platform.openai.com/docs/api-reference/files/list
// @Summary List files.
// @Success 200 {object} schema.ListFiles "Response"
// @Router /v1/files [get]
func ListFilesEndpoint(cm *config.BackendConfigLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
var listFiles schema.ListFiles
purpose := c.Query("purpose")
if purpose == "" {
listFiles.Data = UploadedFiles
} else {
for _, f := range UploadedFiles {
if purpose == f.Purpose {
listFiles.Data = append(listFiles.Data, f)
}
}
}
listFiles.Object = "list"
return c.Status(fiber.StatusOK).JSON(listFiles)
}
}
func getFileFromRequest(c *fiber.Ctx) (*schema.File, error) {
id := c.Params("file_id")
if id == "" {
return nil, fmt.Errorf("file_id parameter is required")
}
for _, f := range UploadedFiles {
if id == f.ID {
return &f, nil
}
}
return nil, fmt.Errorf("unable to find file id %s", id)
}
// GetFilesEndpoint is the OpenAI API endpoint to get files https://platform.openai.com/docs/api-reference/files/retrieve
// @Summary Returns information about a specific file.
// @Success 200 {object} schema.File "Response"
// @Router /v1/files/{file_id} [get]
func GetFilesEndpoint(cm *config.BackendConfigLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
file, err := getFileFromRequest(c)
if err != nil {
return c.Status(fiber.StatusInternalServerError).SendString(bluemonday.StrictPolicy().Sanitize(err.Error()))
}
return c.JSON(file)
}
}
type DeleteStatus struct {
Id string
Object string
Deleted bool
}
// DeleteFilesEndpoint is the OpenAI API endpoint to delete files https://platform.openai.com/docs/api-reference/files/delete
// @Summary Delete a file.
// @Success 200 {object} DeleteStatus "Response"
// @Router /v1/files/{file_id} [delete]
func DeleteFilesEndpoint(cm *config.BackendConfigLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
file, err := getFileFromRequest(c)
if err != nil {
return c.Status(fiber.StatusInternalServerError).SendString(bluemonday.StrictPolicy().Sanitize(err.Error()))
}
err = os.Remove(filepath.Join(appConfig.UploadDir, file.Filename))
if err != nil {
// If the file doesn't exist then we should just continue to remove it
if !errors.Is(err, os.ErrNotExist) {
return c.Status(fiber.StatusInternalServerError).SendString(bluemonday.StrictPolicy().Sanitize(fmt.Sprintf("Unable to delete file: %s, %v", file.Filename, err)))
}
}
// Remove upload from list
for i, f := range UploadedFiles {
if f.ID == file.ID {
UploadedFiles = append(UploadedFiles[:i], UploadedFiles[i+1:]...)
break
}
}
utils.SaveConfig(appConfig.UploadDir, UploadedFilesFile, UploadedFiles)
return c.JSON(DeleteStatus{
Id: file.ID,
Object: "file",
Deleted: true,
})
}
}
// GetFilesContentsEndpoint is the OpenAI API endpoint to get files content https://platform.openai.com/docs/api-reference/files/retrieve-contents
// @Summary Returns information about a specific file.
// @Success 200 {string} binary "file"
// @Router /v1/files/{file_id}/content [get]
// GetFilesContentsEndpoint
func GetFilesContentsEndpoint(cm *config.BackendConfigLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
file, err := getFileFromRequest(c)
if err != nil {
return c.Status(fiber.StatusInternalServerError).SendString(bluemonday.StrictPolicy().Sanitize(err.Error()))
}
fileContents, err := os.ReadFile(filepath.Join(appConfig.UploadDir, file.Filename))
if err != nil {
return c.Status(fiber.StatusInternalServerError).SendString(bluemonday.StrictPolicy().Sanitize(err.Error()))
}
return c.Send(fileContents)
}
}

View File

@@ -1,301 +0,0 @@
package openai
import (
"encoding/json"
"fmt"
"io"
"mime/multipart"
"net/http"
"net/http/httptest"
"os"
"path/filepath"
"strings"
"github.com/rs/zerolog/log"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/gofiber/fiber/v2"
utils2 "github.com/mudler/LocalAI/pkg/utils"
"github.com/stretchr/testify/assert"
"testing"
)
func startUpApp() (app *fiber.App, option *config.ApplicationConfig, loader *config.BackendConfigLoader) {
// Preparing the mocked objects
loader = &config.BackendConfigLoader{}
option = &config.ApplicationConfig{
UploadLimitMB: 10,
UploadDir: "test_dir",
}
_ = os.RemoveAll(option.UploadDir)
app = fiber.New(fiber.Config{
BodyLimit: 20 * 1024 * 1024, // sets the limit to 20MB.
})
// Create a Test Server
app.Post("/files", UploadFilesEndpoint(loader, option))
app.Get("/files", ListFilesEndpoint(loader, option))
app.Get("/files/:file_id", GetFilesEndpoint(loader, option))
app.Delete("/files/:file_id", DeleteFilesEndpoint(loader, option))
app.Get("/files/:file_id/content", GetFilesContentsEndpoint(loader, option))
return
}
func TestUploadFileExceedSizeLimit(t *testing.T) {
// Preparing the mocked objects
loader := &config.BackendConfigLoader{}
option := &config.ApplicationConfig{
UploadLimitMB: 10,
UploadDir: "test_dir",
}
_ = os.RemoveAll(option.UploadDir)
app := fiber.New(fiber.Config{
BodyLimit: 20 * 1024 * 1024, // sets the limit to 20MB.
})
// Create a Test Server
app.Post("/files", UploadFilesEndpoint(loader, option))
app.Get("/files", ListFilesEndpoint(loader, option))
app.Get("/files/:file_id", GetFilesEndpoint(loader, option))
app.Delete("/files/:file_id", DeleteFilesEndpoint(loader, option))
app.Get("/files/:file_id/content", GetFilesContentsEndpoint(loader, option))
t.Run("UploadFilesEndpoint file size exceeds limit", func(t *testing.T) {
t.Cleanup(tearDown())
resp, err := CallFilesUploadEndpoint(t, app, "foo.txt", "file", "fine-tune", 11, option)
assert.NoError(t, err)
assert.Equal(t, fiber.StatusBadRequest, resp.StatusCode)
assert.Contains(t, bodyToString(resp, t), "exceeds upload limit")
})
t.Run("UploadFilesEndpoint purpose not defined", func(t *testing.T) {
t.Cleanup(tearDown())
resp, _ := CallFilesUploadEndpoint(t, app, "foo.txt", "file", "", 5, option)
assert.Equal(t, fiber.StatusBadRequest, resp.StatusCode)
assert.Contains(t, bodyToString(resp, t), "Purpose is not defined")
})
t.Run("UploadFilesEndpoint file already exists", func(t *testing.T) {
t.Cleanup(tearDown())
f1 := CallFilesUploadEndpointWithCleanup(t, app, "foo.txt", "file", "fine-tune", 5, option)
resp, err := CallFilesUploadEndpoint(t, app, "foo.txt", "file", "fine-tune", 5, option)
fmt.Println(f1)
fmt.Printf("ERror: %v\n", err)
fmt.Printf("resp: %+v\n", resp)
assert.Equal(t, fiber.StatusBadRequest, resp.StatusCode)
assert.Contains(t, bodyToString(resp, t), "File already exists")
})
t.Run("UploadFilesEndpoint file uploaded successfully", func(t *testing.T) {
t.Cleanup(tearDown())
file := CallFilesUploadEndpointWithCleanup(t, app, "test.txt", "file", "fine-tune", 5, option)
// Check if file exists in the disk
testName := strings.Split(t.Name(), "/")[1]
fileName := testName + "-test.txt"
filePath := filepath.Join(option.UploadDir, utils2.SanitizeFileName(fileName))
_, err := os.Stat(filePath)
assert.False(t, os.IsNotExist(err))
assert.Equal(t, file.Bytes, 5242880)
assert.NotEmpty(t, file.CreatedAt)
assert.Equal(t, file.Filename, fileName)
assert.Equal(t, file.Purpose, "fine-tune")
})
t.Run("ListFilesEndpoint without purpose parameter", func(t *testing.T) {
t.Cleanup(tearDown())
resp, err := CallListFilesEndpoint(t, app, "")
assert.NoError(t, err)
assert.Equal(t, 200, resp.StatusCode)
listFiles := responseToListFile(t, resp)
if len(listFiles.Data) != len(UploadedFiles) {
t.Errorf("Expected %v files, got %v files", len(UploadedFiles), len(listFiles.Data))
}
})
t.Run("ListFilesEndpoint with valid purpose parameter", func(t *testing.T) {
t.Cleanup(tearDown())
_ = CallFilesUploadEndpointWithCleanup(t, app, "test.txt", "file", "fine-tune", 5, option)
resp, err := CallListFilesEndpoint(t, app, "fine-tune")
assert.NoError(t, err)
listFiles := responseToListFile(t, resp)
if len(listFiles.Data) != 1 {
t.Errorf("Expected 1 file, got %v files", len(listFiles.Data))
}
})
t.Run("ListFilesEndpoint with invalid query parameter", func(t *testing.T) {
t.Cleanup(tearDown())
resp, err := CallListFilesEndpoint(t, app, "not-so-fine-tune")
assert.NoError(t, err)
assert.Equal(t, 200, resp.StatusCode)
listFiles := responseToListFile(t, resp)
if len(listFiles.Data) != 0 {
t.Errorf("Expected 0 file, got %v files", len(listFiles.Data))
}
})
t.Run("GetFilesContentsEndpoint get file content", func(t *testing.T) {
t.Cleanup(tearDown())
req := httptest.NewRequest("GET", "/files", nil)
resp, _ := app.Test(req)
assert.Equal(t, 200, resp.StatusCode)
var listFiles schema.ListFiles
if err := json.Unmarshal(bodyToByteArray(resp, t), &listFiles); err != nil {
t.Errorf("Failed to decode response: %v", err)
return
}
if len(listFiles.Data) != 0 {
t.Errorf("Expected 0 file, got %v files", len(listFiles.Data))
}
})
}
func CallListFilesEndpoint(t *testing.T, app *fiber.App, purpose string) (*http.Response, error) {
var target string
if purpose != "" {
target = fmt.Sprintf("/files?purpose=%s", purpose)
} else {
target = "/files"
}
req := httptest.NewRequest("GET", target, nil)
return app.Test(req)
}
func CallFilesContentEndpoint(t *testing.T, app *fiber.App, fileId string) (*http.Response, error) {
request := httptest.NewRequest("GET", "/files?file_id="+fileId, nil)
return app.Test(request)
}
func CallFilesUploadEndpoint(t *testing.T, app *fiber.App, fileName, tag, purpose string, fileSize int, appConfig *config.ApplicationConfig) (*http.Response, error) {
testName := strings.Split(t.Name(), "/")[1]
// Create a file that exceeds the limit
file := createTestFile(t, testName+"-"+fileName, fileSize, appConfig)
// Creating a new HTTP Request
body, writer := newMultipartFile(file.Name(), tag, purpose)
req := httptest.NewRequest(http.MethodPost, "/files", body)
req.Header.Set(fiber.HeaderContentType, writer.FormDataContentType())
return app.Test(req)
}
func CallFilesUploadEndpointWithCleanup(t *testing.T, app *fiber.App, fileName, tag, purpose string, fileSize int, appConfig *config.ApplicationConfig) schema.File {
// Create a file that exceeds the limit
testName := strings.Split(t.Name(), "/")[1]
file := createTestFile(t, testName+"-"+fileName, fileSize, appConfig)
// Creating a new HTTP Request
body, writer := newMultipartFile(file.Name(), tag, purpose)
req := httptest.NewRequest(http.MethodPost, "/files", body)
req.Header.Set(fiber.HeaderContentType, writer.FormDataContentType())
resp, err := app.Test(req)
assert.NoError(t, err)
f := responseToFile(t, resp)
//id := f.ID
//t.Cleanup(func() {
// _, err := CallFilesDeleteEndpoint(t, app, id)
// assert.NoError(t, err)
// assert.Empty(t, UploadedFiles)
//})
return f
}
func CallFilesDeleteEndpoint(t *testing.T, app *fiber.App, fileId string) (*http.Response, error) {
target := fmt.Sprintf("/files/%s", fileId)
req := httptest.NewRequest(http.MethodDelete, target, nil)
return app.Test(req)
}
// Helper to create multi-part file
func newMultipartFile(filePath, tag, purpose string) (*strings.Reader, *multipart.Writer) {
body := new(strings.Builder)
writer := multipart.NewWriter(body)
file, _ := os.Open(filePath)
defer file.Close()
part, _ := writer.CreateFormFile(tag, filepath.Base(filePath))
io.Copy(part, file)
if purpose != "" {
_ = writer.WriteField("purpose", purpose)
}
writer.Close()
return strings.NewReader(body.String()), writer
}
// Helper to create test files
func createTestFile(t *testing.T, name string, sizeMB int, option *config.ApplicationConfig) *os.File {
err := os.MkdirAll(option.UploadDir, 0750)
if err != nil {
t.Fatalf("Error MKDIR: %v", err)
}
file, err := os.Create(name)
assert.NoError(t, err)
file.WriteString(strings.Repeat("a", sizeMB*1024*1024)) // sizeMB MB File
t.Cleanup(func() {
os.Remove(name)
os.RemoveAll(option.UploadDir)
})
return file
}
func bodyToString(resp *http.Response, t *testing.T) string {
return string(bodyToByteArray(resp, t))
}
func bodyToByteArray(resp *http.Response, t *testing.T) []byte {
bodyBytes, err := io.ReadAll(resp.Body)
if err != nil {
t.Fatal(err)
}
return bodyBytes
}
func responseToFile(t *testing.T, resp *http.Response) schema.File {
var file schema.File
responseToString := bodyToString(resp, t)
err := json.NewDecoder(strings.NewReader(responseToString)).Decode(&file)
if err != nil {
t.Errorf("Failed to decode response: %s", err)
}
return file
}
func responseToListFile(t *testing.T, resp *http.Response) schema.ListFiles {
var listFiles schema.ListFiles
responseToString := bodyToString(resp, t)
err := json.NewDecoder(strings.NewReader(responseToString)).Decode(&listFiles)
if err != nil {
log.Error().Err(err).Msg("failed to decode response")
}
return listFiles
}

View File

@@ -79,49 +79,37 @@ func ImageEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appCon
return fiber.ErrBadRequest
}
// Process input images (for img2img/inpainting)
src := ""
if input.File != "" {
src = processImageFile(input.File, appConfig.GeneratedContentDir)
if src != "" {
defer os.RemoveAll(src)
}
}
fileData := []byte{}
var err error
// check if input.File is an URL, if so download it and save it
// to a temporary file
if strings.HasPrefix(input.File, "http://") || strings.HasPrefix(input.File, "https://") {
out, err := downloadFile(input.File)
if err != nil {
return fmt.Errorf("failed downloading file:%w", err)
}
defer os.RemoveAll(out)
fileData, err = os.ReadFile(out)
if err != nil {
return fmt.Errorf("failed reading file:%w", err)
}
} else {
// base 64 decode the file and write it somewhere
// that we will cleanup
fileData, err = base64.StdEncoding.DecodeString(input.File)
if err != nil {
return err
// Process multiple input images
var inputImages []string
if len(input.Files) > 0 {
for _, file := range input.Files {
processedFile := processImageFile(file, appConfig.GeneratedContentDir)
if processedFile != "" {
inputImages = append(inputImages, processedFile)
defer os.RemoveAll(processedFile)
}
}
}
// Create a temporary file
outputFile, err := os.CreateTemp(appConfig.GeneratedContentDir, "b64")
if err != nil {
return err
// Process reference images
var refImages []string
if len(input.RefImages) > 0 {
for _, file := range input.RefImages {
processedFile := processImageFile(file, appConfig.GeneratedContentDir)
if processedFile != "" {
refImages = append(refImages, processedFile)
defer os.RemoveAll(processedFile)
}
}
// write the base64 result
writer := bufio.NewWriter(outputFile)
_, err = writer.Write(fileData)
if err != nil {
outputFile.Close()
return err
}
outputFile.Close()
src = outputFile.Name()
defer os.RemoveAll(src)
}
log.Debug().Msgf("Parameter Config: %+v", config)
@@ -202,7 +190,13 @@ func ImageEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appCon
baseURL := c.BaseURL()
fn, err := backend.ImageGeneration(height, width, mode, step, *config.Seed, positive_prompt, negative_prompt, src, output, ml, *config, appConfig)
// Use the first input image as src if available, otherwise use the original src
inputSrc := src
if len(inputImages) > 0 {
inputSrc = inputImages[0]
}
fn, err := backend.ImageGeneration(height, width, mode, step, *config.Seed, positive_prompt, negative_prompt, inputSrc, output, ml, *config, appConfig, refImages)
if err != nil {
return err
}
@@ -243,3 +237,51 @@ func ImageEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appCon
return c.JSON(resp)
}
}
// processImageFile handles a single image file (URL or base64) and returns the path to the temporary file
func processImageFile(file string, generatedContentDir string) string {
fileData := []byte{}
var err error
// check if file is an URL, if so download it and save it to a temporary file
if strings.HasPrefix(file, "http://") || strings.HasPrefix(file, "https://") {
out, err := downloadFile(file)
if err != nil {
log.Error().Err(err).Msgf("Failed downloading file: %s", file)
return ""
}
defer os.RemoveAll(out)
fileData, err = os.ReadFile(out)
if err != nil {
log.Error().Err(err).Msgf("Failed reading downloaded file: %s", out)
return ""
}
} else {
// base 64 decode the file and write it somewhere that we will cleanup
fileData, err = base64.StdEncoding.DecodeString(file)
if err != nil {
log.Error().Err(err).Msgf("Failed decoding base64 file")
return ""
}
}
// Create a temporary file
outputFile, err := os.CreateTemp(generatedContentDir, "b64")
if err != nil {
log.Error().Err(err).Msg("Failed creating temporary file")
return ""
}
// write the base64 result
writer := bufio.NewWriter(outputFile)
_, err = writer.Write(fileData)
if err != nil {
outputFile.Close()
log.Error().Err(err).Msg("Failed writing to temporary file")
return ""
}
outputFile.Close()
return outputFile.Name()
}

View File

@@ -16,12 +16,12 @@ import (
"github.com/mudler/LocalAI/core/application"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/http/endpoints/openai/types"
"github.com/mudler/LocalAI/core/templates"
laudio "github.com/mudler/LocalAI/pkg/audio"
"github.com/mudler/LocalAI/pkg/functions"
"github.com/mudler/LocalAI/pkg/grpc/proto"
model "github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/sound"
"github.com/mudler/LocalAI/pkg/templates"
"google.golang.org/grpc"
@@ -29,8 +29,8 @@ import (
)
const (
localSampleRate = 16000
remoteSampleRate = 24000
localSampleRate = 16000
remoteSampleRate = 24000
)
// A model can be "emulated" that is: transcribe audio to text -> feed text to the LLM -> generate audio as result
@@ -210,9 +210,9 @@ func registerRealtime(application *application.Application) func(c *websocket.Co
// TODO: Need some way to pass this to the backend
Threshold: 0.5,
// TODO: This is ignored and the amount of padding is random at present
PrefixPaddingMs: 30,
PrefixPaddingMs: 30,
SilenceDurationMs: 500,
CreateResponse: func() *bool { t := true; return &t }(),
CreateResponse: func() *bool { t := true; return &t }(),
},
},
InputAudioTranscription: &types.InputAudioTranscription{
@@ -233,7 +233,7 @@ func registerRealtime(application *application.Application) func(c *websocket.Co
// TODO: The API has no way to configure the VAD model or other models that make up a pipeline to fake any-to-any
// So possibly we could have a way to configure a composite model that can be used in situations where any-to-any is expected
pipeline := config.Pipeline{
VAD: "silero-vad",
VAD: "silero-vad",
Transcription: session.InputAudioTranscription.Model,
}
@@ -567,8 +567,8 @@ func updateTransSession(session *Session, update *types.ClientSession, cl *confi
trCur := session.InputAudioTranscription
if trUpd != nil && trUpd.Model != "" && trUpd.Model != trCur.Model {
pipeline := config.Pipeline {
VAD: "silero-vad",
pipeline := config.Pipeline{
VAD: "silero-vad",
Transcription: trUpd.Model,
}
@@ -684,7 +684,7 @@ func handleVAD(cfg *config.BackendConfig, evaluator *templates.Evaluator, sessio
sendEvent(c, types.InputAudioBufferClearedEvent{
ServerEventBase: types.ServerEventBase{
EventID: "event_TODO",
Type: types.ServerEventTypeInputAudioBufferCleared,
Type: types.ServerEventTypeInputAudioBufferCleared,
},
})
@@ -697,7 +697,7 @@ func handleVAD(cfg *config.BackendConfig, evaluator *templates.Evaluator, sessio
sendEvent(c, types.InputAudioBufferSpeechStartedEvent{
ServerEventBase: types.ServerEventBase{
EventID: "event_TODO",
Type: types.ServerEventTypeInputAudioBufferSpeechStarted,
Type: types.ServerEventTypeInputAudioBufferSpeechStarted,
},
AudioStartMs: time.Now().Sub(startTime).Milliseconds(),
})
@@ -719,7 +719,7 @@ func handleVAD(cfg *config.BackendConfig, evaluator *templates.Evaluator, sessio
sendEvent(c, types.InputAudioBufferSpeechStoppedEvent{
ServerEventBase: types.ServerEventBase{
EventID: "event_TODO",
Type: types.ServerEventTypeInputAudioBufferSpeechStopped,
Type: types.ServerEventTypeInputAudioBufferSpeechStopped,
},
AudioEndMs: time.Now().Sub(startTime).Milliseconds(),
})
@@ -728,9 +728,9 @@ func handleVAD(cfg *config.BackendConfig, evaluator *templates.Evaluator, sessio
sendEvent(c, types.InputAudioBufferCommittedEvent{
ServerEventBase: types.ServerEventBase{
EventID: "event_TODO",
Type: types.ServerEventTypeInputAudioBufferCommitted,
Type: types.ServerEventTypeInputAudioBufferCommitted,
},
ItemID: generateItemID(),
ItemID: generateItemID(),
PreviousItemID: "TODO",
})
@@ -833,9 +833,9 @@ func commitUtterance(ctx context.Context, utt []byte, cfg *config.BackendConfig,
func runVAD(ctx context.Context, session *Session, adata []int16) ([]*proto.VADSegment, error) {
soundIntBuffer := &audio.IntBuffer{
Format: &audio.Format{SampleRate: localSampleRate, NumChannels: 1},
Format: &audio.Format{SampleRate: localSampleRate, NumChannels: 1},
SourceBitDepth: 16,
Data: sound.ConvertInt16ToInt(adata),
Data: sound.ConvertInt16ToInt(adata),
}
float32Data := soundIntBuffer.AsFloat32Buffer().Data

View File

@@ -11,9 +11,9 @@ import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services"
"github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/functions"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/templates"
"github.com/mudler/LocalAI/pkg/utils"
"github.com/gofiber/fiber/v2"

View File

@@ -23,7 +23,7 @@ func RegisterLocalAIRoutes(router *fiber.App,
// LocalAI API endpoints
if !appConfig.DisableGalleryEndpoint {
modelGalleryEndpointService := localai.CreateModelGalleryEndpointService(appConfig.Galleries, appConfig.ModelPath, galleryService)
modelGalleryEndpointService := localai.CreateModelGalleryEndpointService(appConfig.Galleries, appConfig.BackendGalleries, appConfig.ModelPath, galleryService)
router.Post("/models/apply", modelGalleryEndpointService.ApplyModelGalleryEndpoint())
router.Post("/models/delete/:name", modelGalleryEndpointService.DeleteModelGalleryEndpoint())
@@ -41,6 +41,11 @@ func RegisterLocalAIRoutes(router *fiber.App,
router.Get("/backends/jobs/:uuid", backendGalleryEndpointService.GetOpStatusEndpoint())
}
router.Post("/v1/detection",
requestExtractor.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_DETECTION)),
requestExtractor.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.DetectionRequest) }),
localai.DetectionEndpoint(cl, ml, appConfig))
router.Post("/tts",
requestExtractor.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_TTS)),
requestExtractor.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.TTSRequest) }),

View File

@@ -54,38 +54,6 @@ func RegisterOpenAIRoutes(app *fiber.App,
app.Post("/completions", completionChain...)
app.Post("/v1/engines/:model/completions", completionChain...)
// assistant
app.Get("/v1/assistants", openai.ListAssistantsEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/assistants", openai.ListAssistantsEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/assistants", openai.CreateAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/assistants", openai.CreateAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Delete("/v1/assistants/:assistant_id", openai.DeleteAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Delete("/assistants/:assistant_id", openai.DeleteAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/v1/assistants/:assistant_id", openai.GetAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/assistants/:assistant_id", openai.GetAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/assistants/:assistant_id", openai.ModifyAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/assistants/:assistant_id", openai.ModifyAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/v1/assistants/:assistant_id/files", openai.ListAssistantFilesEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/assistants/:assistant_id/files", openai.ListAssistantFilesEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/assistants/:assistant_id/files", openai.CreateAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/assistants/:assistant_id/files", openai.CreateAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Delete("/v1/assistants/:assistant_id/files/:file_id", openai.DeleteAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Delete("/assistants/:assistant_id/files/:file_id", openai.DeleteAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/v1/assistants/:assistant_id/files/:file_id", openai.GetAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/assistants/:assistant_id/files/:file_id", openai.GetAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
// files
app.Post("/v1/files", openai.UploadFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Post("/files", openai.UploadFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/v1/files", openai.ListFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/files", openai.ListFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/v1/files/:file_id", openai.GetFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/files/:file_id", openai.GetFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Delete("/v1/files/:file_id", openai.DeleteFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Delete("/files/:file_id", openai.DeleteFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/v1/files/:file_id/content", openai.GetFilesContentsEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/files/:file_id/content", openai.GetFilesContentsEndpoint(application.BackendLoader(), application.ApplicationConfig()))
// embeddings
embeddingChain := []fiber.Handler{
re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_EMBEDDINGS)),

View File

@@ -180,6 +180,7 @@ func registerGalleryRoutes(app *fiber.App, cl *config.BackendConfigLoader, appCo
ID: uid,
GalleryElementName: galleryID,
Galleries: appConfig.Galleries,
BackendGalleries: appConfig.BackendGalleries,
}
go func() {
galleryService.ModelGalleryChannel <- op
@@ -219,6 +220,7 @@ func registerGalleryRoutes(app *fiber.App, cl *config.BackendConfigLoader, appCo
Delete: true,
GalleryElementName: galleryName,
Galleries: appConfig.Galleries,
BackendGalleries: appConfig.BackendGalleries,
}
go func() {
galleryService.ModelGalleryChannel <- op

View File

@@ -90,6 +90,14 @@
hx-indicator=".htmx-indicator">
<i class="fas fa-headphones mr-2"></i>Whisper
</button>
<button hx-post="browse/search/backends"
class="inline-flex items-center rounded-full px-4 py-2 text-sm font-medium bg-red-900/60 text-red-200 border border-red-700/50 hover:bg-red-800 transition duration-200 ease-in-out"
hx-target="#search-results"
hx-vals='{"search": "object-detection"}'
onclick="hidePagination()"
hx-indicator=".htmx-indicator">
<i class="fas fa-eye mr-2"></i>Object detection
</button>
</div>
</div>
</div>

View File

@@ -115,6 +115,14 @@
hx-indicator=".htmx-indicator">
<i class="fas fa-headphones mr-2"></i>Audio transcription
</button>
<button hx-post="browse/search/models"
class="inline-flex items-center rounded-full px-4 py-2 text-sm font-medium bg-red-900/60 text-red-200 border border-red-700/50 hover:bg-red-800 transition duration-200 ease-in-out"
hx-target="#search-results"
hx-vals='{"search": "object-detection"}'
onclick="hidePagination()"
hx-indicator=".htmx-indicator">
<i class="fas fa-eye mr-2"></i>Object detection
</button>
</div>
</div>

View File

@@ -278,6 +278,7 @@ func ensureService(ctx context.Context, n *node.Node, nd *NodeData, sserv string
port, err := freeport.GetFreePort()
if err != nil {
zlog.Error().Err(err).Msgf("Could not allocate a free port for %s", nd.ID)
cancel()
return
}

View File

@@ -120,3 +120,20 @@ type SystemInformationResponse struct {
Backends []string `json:"backends"`
Models []SysInfoModel `json:"loaded_models"`
}
type DetectionRequest struct {
BasicModelRequest
Image string `json:"image"`
}
type DetectionResponse struct {
Detections []Detection `json:"detections"`
}
type Detection struct {
X float32 `json:"x"`
Y float32 `json:"y"`
Width float32 `json:"width"`
Height float32 `json:"height"`
ClassName string `json:"class_name"`
}

View File

@@ -2,7 +2,6 @@ package schema
import (
"context"
"time"
functions "github.com/mudler/LocalAI/pkg/functions"
)
@@ -115,37 +114,6 @@ type OpenAIModel struct {
Object string `json:"object"`
}
type DeleteAssistantResponse struct {
ID string `json:"id"`
Object string `json:"object"`
Deleted bool `json:"deleted"`
}
// File represents the structure of a file object from the OpenAI API.
type File struct {
ID string `json:"id"` // Unique identifier for the file
Object string `json:"object"` // Type of the object (e.g., "file")
Bytes int `json:"bytes"` // Size of the file in bytes
CreatedAt time.Time `json:"created_at"` // The time at which the file was created
Filename string `json:"filename"` // The name of the file
Purpose string `json:"purpose"` // The purpose of the file (e.g., "fine-tune", "classifications", etc.)
}
type ListFiles struct {
Data []File
Object string
}
type AssistantFileRequest struct {
FileID string `json:"file_id"`
}
type DeleteAssistantFileResponse struct {
ID string `json:"id"`
Object string `json:"object"`
Deleted bool `json:"deleted"`
}
type ImageGenerationResponseFormat string
type ChatCompletionResponseFormatType string
@@ -173,6 +141,10 @@ type OpenAIRequest struct {
// whisper
File string `json:"file" validate:"required"`
// Multiple input images for img2img or inpainting
Files []string `json:"files,omitempty"`
// Reference images for models that support them (e.g., Flux Kontext)
RefImages []string `json:"ref_images,omitempty"`
//whisper/image
ResponseFormat interface{} `json:"response_format,omitempty"`
// image

View File

@@ -2,7 +2,7 @@ package services
import (
"github.com/mudler/LocalAI/core/gallery"
"github.com/mudler/LocalAI/core/system"
"github.com/mudler/LocalAI/pkg/system"
"github.com/mudler/LocalAI/pkg/utils"
"github.com/rs/zerolog/log"
@@ -24,6 +24,7 @@ func (g *GalleryService) backendHandler(op *GalleryOp[gallery.GalleryBackend], s
g.modelLoader.DeleteExternalBackend(op.GalleryElementName)
} else {
log.Warn().Msgf("installing backend %s", op.GalleryElementName)
log.Debug().Msgf("backend galleries: %v", g.appConfig.BackendGalleries)
err = gallery.InstallBackendFromGallery(g.appConfig.BackendGalleries, systemState, op.GalleryElementName, g.appConfig.BackendsPath, progressCallback, true)
if err == nil {
err = gallery.RegisterBackends(g.appConfig.BackendsPath, g.modelLoader)

View File

@@ -7,8 +7,8 @@ import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/gallery"
"github.com/mudler/LocalAI/core/system"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/system"
"github.com/rs/zerolog/log"
)

View File

@@ -7,7 +7,7 @@ import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/gallery"
"github.com/mudler/LocalAI/core/system"
"github.com/mudler/LocalAI/pkg/system"
"github.com/mudler/LocalAI/pkg/utils"
"gopkg.in/yaml.v2"
)

View File

@@ -8,8 +8,8 @@ import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/gallery"
"github.com/mudler/LocalAI/core/system"
"github.com/mudler/LocalAI/pkg/downloader"
"github.com/mudler/LocalAI/pkg/system"
"github.com/rs/zerolog/log"
)

View File

@@ -10,8 +10,8 @@ import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/gallery"
"github.com/mudler/LocalAI/core/system"
"github.com/mudler/LocalAI/pkg/downloader"
"github.com/mudler/LocalAI/pkg/system"
"github.com/mudler/LocalAI/pkg/utils"
"github.com/rs/zerolog/log"
"gopkg.in/yaml.v2"

View File

@@ -6,7 +6,7 @@ import (
"path/filepath"
"github.com/mudler/LocalAI/core/config"
. "github.com/mudler/LocalAI/pkg/startup"
. "github.com/mudler/LocalAI/core/startup"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"

View File

@@ -3,8 +3,8 @@ package templates_test
import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
. "github.com/mudler/LocalAI/core/templates"
"github.com/mudler/LocalAI/pkg/functions"
. "github.com/mudler/LocalAI/pkg/templates"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"

View File

@@ -1,7 +1,7 @@
package templates_test
import (
. "github.com/mudler/LocalAI/pkg/templates" // Update with your module path
. "github.com/mudler/LocalAI/core/templates" // Update with your module path
// Update with your module path
. "github.com/onsi/ginkgo/v2"

View File

@@ -448,7 +448,7 @@ there are additional environment variables available that modify the behavior of
| Environment variable | Default | Description |
|----------------------------|---------|------------------------------------------------------------------------------------------------------------|
| `REBUILD` | `false` | Rebuild LocalAI on startup |
| `BUILD_TYPE` | | Build type. Available: `cublas`, `openblas`, `clblas` |
| `BUILD_TYPE` | | Build type. Available: `cublas`, `openblas`, `clblas`, `intel` (intel core), `sycl_f16`, `sycl_f32` (intel backends) |
| `GO_TAGS` | | Go tags. Available: `stablediffusion` |
| `HUGGINGFACEHUB_API_TOKEN` | | Special token for interacting with HuggingFace Inference API, required only when using the `langchain-huggingface` backend |
| `EXTRA_BACKENDS` | | A space separated list of backends to prepare. For example `EXTRA_BACKENDS="backend/python/diffusers backend/python/transformers"` prepares the python environment on start |

View File

@@ -15,6 +15,16 @@ This section contains instruction on how to use LocalAI with GPU acceleration.
For acceleration for AMD or Metal HW is still in development, for additional details see the [build]({{%relref "docs/getting-started/build#Acceleration" %}})
{{% /alert %}}
## Automatic Backend Detection
When you install a model from the gallery (or a YAML file), LocalAI intelligently detects the required backend and your system's capabilities, then downloads the correct version for you. Whether you're running on a standard CPU, an NVIDIA GPU, an AMD GPU, or an Intel GPU, LocalAI handles it automatically.
For advanced use cases or to override auto-detection, you can use the `LOCALAI_FORCE_META_BACKEND_CAPABILITY` environment variable. Here are the available options:
- `default`: Forces CPU-only backend. This is the fallback if no specific hardware is detected.
- `nvidia`: Forces backends compiled with CUDA support for NVIDIA GPUs.
- `amd`: Forces backends compiled with ROCm support for AMD GPUs.
- `intel`: Forces backends compiled with SYCL/oneAPI support for Intel GPUs.
## Model configuration
@@ -71,8 +81,8 @@ To use CUDA, use the images with the `cublas` tag, for example.
The image list is on [quay](https://quay.io/repository/go-skynet/local-ai?tab=tags):
- CUDA `11` tags: `master-gpu-nvidia-cuda11`, `v1.40.0-gpu-nvidia-cuda11`, ...
- CUDA `12` tags: `master-gpu-nvidia-cuda12`, `v1.40.0-gpu-nvidia-cuda12`, ...
- CUDA `11` tags: `master-gpu-nvidia-cuda-11`, `v1.40.0-gpu-nvidia-cuda-11`, ...
- CUDA `12` tags: `master-gpu-nvidia-cuda-12`, `v1.40.0-gpu-nvidia-cuda-12`, ...
In addition to the commands to run LocalAI normally, you need to specify `--gpus all` to docker, for example:
@@ -257,7 +267,7 @@ If building from source, you need to install [Intel oneAPI Base Toolkit](https:/
### Container images
To use SYCL, use the images with the `gpu-intel-f16` or `gpu-intel-f32` tag, for example `{{< version >}}-gpu-intel-f32-core`, `{{< version >}}-gpu-intel-f16`, ...
To use SYCL, use the images with `gpu-intel` in the tag, for example `{{< version >}}-gpu-intel`, ...
The image list is on [quay](https://quay.io/repository/go-skynet/local-ai?tab=tags).
@@ -266,7 +276,7 @@ The image list is on [quay](https://quay.io/repository/go-skynet/local-ai?tab=ta
To run LocalAI with Docker and sycl starting `phi-2`, you can use the following command as an example:
```bash
docker run -e DEBUG=true --privileged -ti -v $PWD/models:/models -p 8080:8080 -v /dev/dri:/dev/dri --rm quay.io/go-skynet/local-ai:master-gpu-intel-f32 phi-2
docker run -e DEBUG=true --privileged -ti -v $PWD/models:/models -p 8080:8080 -v /dev/dri:/dev/dri --rm quay.io/go-skynet/local-ai:master-gpu-intel phi-2
```
### Notes
@@ -274,7 +284,7 @@ docker run -e DEBUG=true --privileged -ti -v $PWD/models:/models -p 8080:8080 -
In addition to the commands to run LocalAI normally, you need to specify `--device /dev/dri` to docker, for example:
```bash
docker run --rm -ti --device /dev/dri -p 8080:8080 -e DEBUG=true -e MODELS_PATH=/models -e THREADS=1 -v $PWD/models:/models quay.io/go-skynet/local-ai:{{< version >}}-gpu-intel-f16
docker run --rm -ti --device /dev/dri -p 8080:8080 -e DEBUG=true -e MODELS_PATH=/models -e THREADS=1 -v $PWD/models:/models quay.io/go-skynet/local-ai:{{< version >}}-gpu-intel
```
Note also that sycl does have a known issue to hang with `mmap: true`. You have to disable it in the model configuration if explicitly enabled.

View File

@@ -96,8 +96,8 @@ Your backend container should:
For getting started, see the available backends in LocalAI here: https://github.com/mudler/LocalAI/tree/master/backend .
- For Python based backends there is a template that can be used as starting point: https://github.com/mudler/LocalAI/tree/master/backend/python/common/template .
- For Golang based backends, you can see the `bark-cpp` backend as an example: https://github.com/mudler/LocalAI/tree/master/backend/go/bark
- For C++ based backends, you can see the `llama-cpp` backend as an example: https://github.com/mudler/LocalAI/tree/master/backend/cpp/llama
- For Golang based backends, you can see the `bark-cpp` backend as an example: https://github.com/mudler/LocalAI/tree/master/backend/go/bark-cpp
- For C++ based backends, you can see the `llama-cpp` backend as an example: https://github.com/mudler/LocalAI/tree/master/backend/cpp/llama-cpp
### Publishing Your Backend

View File

@@ -0,0 +1,193 @@
+++
disableToc = false
title = "🔍 Object detection"
weight = 13
url = "/features/object-detection/"
+++
LocalAI supports object detection through various backends. This feature allows you to identify and locate objects within images with high accuracy and real-time performance. Currently, [RF-DETR](https://github.com/roboflow/rf-detr) is available as an implementation.
## Overview
Object detection in LocalAI is implemented through dedicated backends that can identify and locate objects within images. Each backend provides different capabilities and model architectures.
**Key Features:**
- Real-time object detection
- High accuracy detection with bounding boxes
- Support for multiple hardware accelerators (CPU, NVIDIA GPU, Intel GPU, AMD GPU)
- Structured detection results with confidence scores
- Easy integration through the `/v1/detection` endpoint
## Usage
### Detection Endpoint
LocalAI provides a dedicated `/v1/detection` endpoint for object detection tasks. This endpoint is specifically designed for object detection and returns structured detection results with bounding boxes and confidence scores.
### API Reference
To perform object detection, send a POST request to the `/v1/detection` endpoint:
```bash
curl -X POST http://localhost:8080/v1/detection \
-H "Content-Type: application/json" \
-d '{
"model": "rfdetr-base",
"image": "https://media.roboflow.com/dog.jpeg"
}'
```
### Request Format
The request body should contain:
- `model`: The name of the object detection model (e.g., "rfdetr-base")
- `image`: The image to analyze, which can be:
- A URL to an image
- A base64-encoded image
### Response Format
The API returns a JSON response with detected objects:
```json
{
"detections": [
{
"x": 100.5,
"y": 150.2,
"width": 200.0,
"height": 300.0,
"confidence": 0.95,
"class_name": "dog"
},
{
"x": 400.0,
"y": 200.0,
"width": 150.0,
"height": 250.0,
"confidence": 0.87,
"class_name": "person"
}
]
}
```
Each detection includes:
- `x`, `y`: Coordinates of the bounding box top-left corner
- `width`, `height`: Dimensions of the bounding box
- `confidence`: Detection confidence score (0.0 to 1.0)
- `class_name`: The detected object class
## Backends
### RF-DETR Backend
The RF-DETR backend is implemented as a Python-based gRPC service that integrates seamlessly with LocalAI. It provides object detection capabilities using the RF-DETR model architecture and supports multiple hardware configurations:
- **CPU**: Optimized for CPU inference
- **NVIDIA GPU**: CUDA acceleration for NVIDIA GPUs
- **Intel GPU**: Intel oneAPI optimization
- **AMD GPU**: ROCm acceleration for AMD GPUs
- **NVIDIA Jetson**: Optimized for ARM64 NVIDIA Jetson devices
#### Setup
1. **Using the Model Gallery (Recommended)**
The easiest way to get started is using the model gallery. The `rfdetr-base` model is available in the official LocalAI gallery:
```bash
# Install and run the rfdetr-base model
local-ai run rfdetr-base
```
You can also install it through the web interface by navigating to the Models section and searching for "rfdetr-base".
2. **Manual Configuration**
Create a model configuration file in your `models` directory:
```yaml
name: rfdetr
backend: rfdetr
parameters:
model: rfdetr-base
```
#### Available Models
Currently, the following model is available in the [Model Gallery]({{%relref "docs/features/model-gallery" %}}):
- **rfdetr-base**: Base model with balanced performance and accuracy
You can browse and install this model through the LocalAI web interface or using the command line.
## Examples
### Basic Object Detection
```bash
# Detect objects in an image from URL
curl -X POST http://localhost:8080/v1/detection \
-H "Content-Type: application/json" \
-d '{
"model": "rfdetr-base",
"image": "https://example.com/image.jpg"
}'
```
### Base64 Image Detection
```bash
# Convert image to base64 and send
base64_image=$(base64 -w 0 image.jpg)
curl -X POST http://localhost:8080/v1/detection \
-H "Content-Type: application/json" \
-d "{
\"model\": \"rfdetr-base\",
\"image\": \"data:image/jpeg;base64,$base64_image\"
}"
```
## Troubleshooting
### Common Issues
1. **Model Loading Errors**
- Ensure the model file is properly downloaded
- Check available disk space
- Verify model compatibility with your backend version
2. **Low Detection Accuracy**
- Ensure good image quality and lighting
- Check if objects are clearly visible
- Consider using a larger model for better accuracy
3. **Slow Performance**
- Enable GPU acceleration if available
- Use a smaller model for faster inference
- Optimize image resolution
### Debug Mode
Enable debug logging for troubleshooting:
```bash
local-ai run --debug rfdetr-base
```
## Object Detection Category
LocalAI includes a dedicated **object-detection** category for models and backends that specialize in identifying and locating objects within images. This category currently includes:
- **RF-DETR**: Real-time transformer-based object detection
Additional object detection models and backends will be added to this category in the future. You can filter models by the `object-detection` tag in the model gallery to find all available object detection models.
## Related Features
- [🎨 Image generation]({{%relref "docs/features/image-generation" %}}): Generate images with AI
- [📖 Text generation]({{%relref "docs/features/text-generation" %}}): Generate text with language models
- [🔍 GPT Vision]({{%relref "docs/features/gpt-vision" %}}): Analyze images with language models
- [🚀 GPU acceleration]({{%relref "docs/features/GPU-acceleration" %}}): Optimize performance with GPU acceleration

View File

@@ -9,13 +9,11 @@ ico = "rocket_launch"
### Build
LocalAI can be built as a container image or as a single, portable binary. Note that some model architectures might require Python libraries, which are not included in the binary. The binary contains only the core backends written in Go and C++.
LocalAI can be built as a container image or as a single, portable binary. Note that some model architectures might require Python libraries, which are not included in the binary.
LocalAI's extensible architecture allows you to add your own backends, which can be written in any language, and as such the container images contains also the Python dependencies to run all the available backends (for example, in order to run backends like __Diffusers__ that allows to generate images and videos from text).
In some cases you might want to re-build LocalAI from source (for instance to leverage Apple Silicon acceleration), or to build a custom container image with your own backends. This section contains instructions on how to build LocalAI from source.
This section contains instructions on how to build LocalAI from source.
#### Build LocalAI locally
@@ -24,7 +22,6 @@ In some cases you might want to re-build LocalAI from source (for instance to le
In order to build LocalAI locally, you need the following requirements:
- Golang >= 1.21
- Cmake/make
- GCC
- GRPC
@@ -36,20 +33,14 @@ To install the dependencies follow the instructions below:
Install `xcode` from the App Store
```bash
brew install abseil cmake go grpc protobuf protoc-gen-go protoc-gen-go-grpc python wget
```
After installing the above dependencies, you need to install grpcio-tools from PyPI. You could do this via a pip --user install or a virtualenv.
```bash
pip install --user grpcio-tools
brew install go protobuf protoc-gen-go protoc-gen-go-grpc wget
```
{{% /tab %}}
{{% tab tabName="Debian" %}}
```bash
apt install cmake golang libgrpc-dev make protobuf-compiler-grpc python3-grpc-tools
apt install golang make protobuf-compiler-grpc
```
After you have golang installed and working, you can install the required binaries for compiling the golang protobuf components via the following commands
@@ -63,10 +54,8 @@ go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f1
{{% /tab %}}
{{% tab tabName="From source" %}}
Specify `BUILD_GRPC_FOR_BACKEND_LLAMA=true` to build automatically the gRPC dependencies
```bash
make ... BUILD_GRPC_FOR_BACKEND_LLAMA=true build
make build
```
{{% /tab %}}
@@ -83,36 +72,6 @@ make build
This should produce the binary `local-ai`
Here is the list of the variables available that can be used to customize the build:
| Variable | Default | Description |
| ---------------------| ------- | ----------- |
| `BUILD_TYPE` | None | Build type. Available: `cublas`, `openblas`, `clblas`, `metal`,`hipblas`, `sycl_f16`, `sycl_f32` |
| `GO_TAGS` | `tts stablediffusion` | Go tags. Available: `stablediffusion`, `tts` |
| `CLBLAST_DIR` | | Specify a CLBlast directory |
| `CUDA_LIBPATH` | | Specify a CUDA library path |
| `BUILD_API_ONLY` | false | Set to true to build only the API (no backends will be built) |
{{% alert note %}}
#### CPU flagset compatibility
LocalAI uses different backends based on ggml and llama.cpp to run models. If your CPU doesn't support common instruction sets, you can disable them during build:
```
CMAKE_ARGS="-DGGML_F16C=OFF -DGGML_AVX512=OFF -DGGML_AVX2=OFF -DGGML_AVX=OFF -DGGML_FMA=OFF" make build
```
To have effect on the container image, you need to set `REBUILD=true`:
```
docker run quay.io/go-skynet/localai
docker run --rm -ti -p 8080:8080 -e DEBUG=true -e MODELS_PATH=/models -e THREADS=1 -e REBUILD=true -e CMAKE_ARGS="-DGGML_F16C=OFF -DGGML_AVX512=OFF -DGGML_AVX2=OFF -DGGML_AVX=OFF -DGGML_FMA=OFF" -v $PWD/models:/models quay.io/go-skynet/local-ai:latest
```
{{% /alert %}}
#### Container image
Requirements:
@@ -153,6 +112,9 @@ wget https://huggingface.co/TheBloke/phi-2-GGUF/resolve/main/phi-2.Q2_K.gguf -O
# Use a template from the examples
cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/phi-2.Q2_K.tmpl
# Install the llama-cpp backend
./local-ai backends install llama-cpp
# Run LocalAI
./local-ai --models-path=./models/ --debug=true
@@ -186,131 +148,53 @@ sudo xcode-select --switch /Applications/Xcode.app/Contents/Developer
```
# reinstall build dependencies
brew reinstall abseil cmake go grpc protobuf wget
brew reinstall go grpc protobuf wget
make clean
make build
```
**Requirements**: OpenCV, Gomp
## Build backends
Image generation requires `GO_TAGS=stablediffusion` to be set during build:
LocalAI have several backends available for installation in the backend gallery. The backends can be also built by source. As backends might vary from language and dependencies that they require, the documentation will provide generic guidance for few of the backends, which can be applied with some slight modifications also to the others.
### Manually
Typically each backend include a Makefile which allow to package the backend.
In the LocalAI repository, for instance you can build `bark-cpp` by doing:
```
make GO_TAGS=stablediffusion build
git clone https://github.com/go-skynet/LocalAI.git
# Build the bark-cpp backend (requires cmake)
make -C LocalAI/backend/go/bark-cpp build package
# Build vllm backend (requires python)
make -C LocalAI/backend/python/vllm
```
### Build with Text to audio support
### With Docker
**Requirements**: piper-phonemize
Building with docker is simpler as abstracts away all the requirement, and focuses on building the final OCI images that are available in the gallery. This allows for instance also to build locally a backend and install it with LocalAI. You can refer to [Backends](https://localai.io/backends/) for general guidance on how to install and develop backends.
Text to audio support is experimental and requires `GO_TAGS=tts` to be set during build:
In the LocalAI repository, you can build `bark-cpp` by doing:
```
make GO_TAGS=tts build
git clone https://github.com/go-skynet/LocalAI.git
# Build the bark-cpp backend (requires docker)
make docker-build-bark-cpp
```
### Acceleration
#### OpenBLAS
Software acceleration.
Requirements: OpenBLAS
```
make BUILD_TYPE=openblas build
```
#### CuBLAS
Nvidia Acceleration.
Requirement: Nvidia CUDA toolkit
Note: CuBLAS support is experimental, and has not been tested on real HW. please report any issues you find!
```
make BUILD_TYPE=cublas build
```
More informations available in the upstream PR: https://github.com/ggerganov/llama.cpp/pull/1412
#### Hipblas (AMD GPU with ROCm on Arch Linux)
Packages:
```
pacman -S base-devel git rocm-hip-sdk rocm-opencl-sdk opencv clblast grpc
```
Library links:
```
export CGO_CFLAGS="-I/usr/include/opencv4"
export CGO_CXXFLAGS="-I/usr/include/opencv4"
export CGO_LDFLAGS="-L/opt/rocm/hip/lib -lamdhip64 -L/opt/rocm/lib -lOpenCL -L/usr/lib -lclblast -lrocblas -lhipblas -lrocrand -lomp -O3 --rtlib=compiler-rt -unwindlib=libgcc -lhipblas -lrocblas --hip-link"
```
Build:
```
make BUILD_TYPE=hipblas GPU_TARGETS=gfx1030
```
#### ClBLAS
AMD/Intel GPU acceleration.
Requirement: OpenCL, CLBlast
```
make BUILD_TYPE=clblas build
```
To specify a clblast dir set: `CLBLAST_DIR`
#### Intel GPU acceleration
Intel GPU acceleration is supported via SYCL.
Requirements: [Intel oneAPI Base Toolkit](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html) (see also [llama.cpp setup installations instructions](https://github.com/ggerganov/llama.cpp/blob/d71ac90985854b0905e1abba778e407e17f9f887/README-sycl.md?plain=1#L56))
```
make BUILD_TYPE=sycl_f16 build # for float16
make BUILD_TYPE=sycl_f32 build # for float32
```
#### Metal (Apple Silicon)
```
make build
# correct build type is automatically used on mac (BUILD_TYPE=metal)
# Set `gpu_layers: 256` (or equal to the number of model layers) to your YAML model config file and `f16: true`
```
### Windows compatibility
Make sure to give enough resources to the running container. See https://github.com/go-skynet/LocalAI/issues/2
### Examples
More advanced build options are available, for instance to build only a single backend.
#### Build only a single backend
You can control the backends that are built by setting the `GRPC_BACKENDS` environment variable. For instance, to build only the `llama-cpp` backend only:
Note that `make` is only by convenience, in reality it just runs a simple `docker` command as:
```bash
make GRPC_BACKENDS=backend-assets/grpc/llama-cpp build
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:bark-cpp -f LocalAI/backend/Dockerfile.golang --build-arg BACKEND=bark-cpp .
```
By default, all the backends are built.
Note:
#### Specific llama.cpp version
To build with a specific version of llama.cpp, set `CPPLLAMA_VERSION` to the tag or wanted sha:
```
CPPLLAMA_VERSION=<sha> make build
```
- BUILD_TYPE can be either: `cublas`, `hipblas`, `sycl_f16`, `sycl_f32`, `metal`.
- BASE_IMAGE is tested on `ubuntu:22.04` (and defaults to it) and `quay.io/go-skynet/intel-oneapi-base:latest` for intel/sycl

View File

@@ -131,8 +131,7 @@ docker run -p 8080:8080 --name local-ai -ti -v localai-models:/models localai/lo
| Latest images for Nvidia GPU (CUDA11) | `quay.io/go-skynet/local-ai:latest-aio-gpu-nvidia-cuda-11` | `localai/localai:latest-aio-gpu-nvidia-cuda-11` |
| Latest images for Nvidia GPU (CUDA12) | `quay.io/go-skynet/local-ai:latest-aio-gpu-nvidia-cuda-12` | `localai/localai:latest-aio-gpu-nvidia-cuda-12` |
| Latest images for AMD GPU | `quay.io/go-skynet/local-ai:latest-aio-gpu-hipblas` | `localai/localai:latest-aio-gpu-hipblas` |
| Latest images for Intel GPU (sycl f16) | `quay.io/go-skynet/local-ai:latest-aio-gpu-intel-f16` | `localai/localai:latest-aio-gpu-intel-f16` |
| Latest images for Intel GPU (sycl f32) | `quay.io/go-skynet/local-ai:latest-aio-gpu-intel-f32` | `localai/localai:latest-aio-gpu-intel-f32` |
| Latest images for Intel GPU | `quay.io/go-skynet/local-ai:latest-aio-gpu-intel` | `localai/localai:latest-aio-gpu-intel` |
### Available environment variables
@@ -163,9 +162,9 @@ Standard container images do not have pre-installed models.
| Description | Quay | Docker Hub |
| --- | --- |-------------------------------------------------------------|
| Latest images from the branch (development) | `quay.io/go-skynet/local-ai:master-gpu-nvidia-cuda11` | `localai/localai:master-gpu-nvidia-cuda11` |
| Latest images from the branch (development) | `quay.io/go-skynet/local-ai:master-gpu-nvidia-cuda-11` | `localai/localai:master-gpu-nvidia-cuda-11` |
| Latest tag | `quay.io/go-skynet/local-ai:latest-gpu-nvidia-cuda-11` | `localai/localai:latest-gpu-nvidia-cuda-11` |
| Versioned image | `quay.io/go-skynet/local-ai:{{< version >}}-gpu-nvidia-cuda11` | `localai/localai:{{< version >}}-gpu-nvidia-cuda11` |
| Versioned image | `quay.io/go-skynet/local-ai:{{< version >}}-gpu-nvidia-cuda-11` | `localai/localai:{{< version >}}-gpu-nvidia-cuda-11` |
{{% /tab %}}
@@ -173,29 +172,19 @@ Standard container images do not have pre-installed models.
| Description | Quay | Docker Hub |
| --- | --- |-------------------------------------------------------------|
| Latest images from the branch (development) | `quay.io/go-skynet/local-ai:master-gpu-nvidia-cuda12` | `localai/localai:master-gpu-nvidia-cuda12` |
| Latest images from the branch (development) | `quay.io/go-skynet/local-ai:master-gpu-nvidia-cuda-12` | `localai/localai:master-gpu-nvidia-cuda-12` |
| Latest tag | `quay.io/go-skynet/local-ai:latest-gpu-nvidia-cuda-12` | `localai/localai:latest-gpu-nvidia-cuda-12` |
| Versioned image | `quay.io/go-skynet/local-ai:{{< version >}}-gpu-nvidia-cuda12` | `localai/localai:{{< version >}}-gpu-nvidia-cuda12` |
| Versioned image | `quay.io/go-skynet/local-ai:{{< version >}}-gpu-nvidia-cuda-12` | `localai/localai:{{< version >}}-gpu-nvidia-cuda-12` |
{{% /tab %}}
{{% tab tabName="Intel GPU (sycl f16)" %}}
{{% tab tabName="Intel GPU" %}}
| Description | Quay | Docker Hub |
| --- | --- |-------------------------------------------------------------|
| Latest images from the branch (development) | `quay.io/go-skynet/local-ai:master-gpu-intel-f16` | `localai/localai:master-gpu-intel-f16` |
| Latest tag | `quay.io/go-skynet/local-ai:latest-gpu-intel-f16` | `localai/localai:latest-gpu-intel-f16` |
| Versioned image | `quay.io/go-skynet/local-ai:{{< version >}}-gpu-intel-f16` | `localai/localai:{{< version >}}-gpu-intel-f16` |
{{% /tab %}}
{{% tab tabName="Intel GPU (sycl f32)" %}}
| Description | Quay | Docker Hub |
| --- | --- |-------------------------------------------------------------|
| Latest images from the branch (development) | `quay.io/go-skynet/local-ai:master-gpu-intel-f32` | `localai/localai:master-gpu-intel-f32` |
| Latest tag | `quay.io/go-skynet/local-ai:latest-gpu-intel-f32` | `localai/localai:latest-gpu-intel-f32` |
| Versioned image | `quay.io/go-skynet/local-ai:{{< version >}}-gpu-intel-f32` | `localai/localai:{{< version >}}-gpu-intel-f32` |
| Latest images from the branch (development) | `quay.io/go-skynet/local-ai:master-gpu-intel` | `localai/localai:master-gpu-intel` |
| Latest tag | `quay.io/go-skynet/local-ai:latest-gpu-intel` | `localai/localai:latest-gpu-intel` |
| Versioned image | `quay.io/go-skynet/local-ai:{{< version >}}-gpu-intel` | `localai/localai:{{< version >}}-gpu-intel` |
{{% /tab %}}

View File

@@ -59,11 +59,7 @@ docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri
#### Intel GPU Images (oneAPI):
```bash
# Intel GPU with FP16 support
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-intel-f16
# Intel GPU with FP32 support
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-intel-f32
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-intel
```
#### Vulkan GPU Images:
@@ -85,7 +81,7 @@ docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-ai
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-11
# Intel GPU version
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-gpu-intel-f16
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-gpu-intel
# AMD GPU version
docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-aio-gpu-hipblas
@@ -106,6 +102,9 @@ local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
local-ai run oci://localai/phi-2:latest
```
{{% alert icon="⚡" %}}
**Automatic Backend Detection**: When you install models from the gallery or YAML files, LocalAI automatically detects your system's GPU capabilities (NVIDIA, AMD, Intel) and downloads the appropriate backend. For advanced configuration options, see [GPU Acceleration]({{% relref "docs/features/gpu-acceleration#automatic-backend-detection" %}}).
{{% /alert %}}
For a full list of options, refer to the [Installer Options]({{% relref "docs/advanced/installer" %}}) documentation.
@@ -154,7 +153,7 @@ For instructions on using AIO images, see [Using container images]({{% relref "d
LocalAI is part of the Local family stack, along with LocalAGI and LocalRecall.
[LocalAGI](https://github.com/mudler/LocalAGI) is a powerful, self-hostable AI Agent platform designed for maximum privacy and flexibility which encompassess and uses all the softwre stack. It provides a complete drop-in replacement for OpenAI's Responses APIs with advanced agentic capabilities, working entirely locally on consumer-grade hardware (CPU and GPU).
[LocalAGI](https://github.com/mudler/LocalAGI) is a powerful, self-hostable AI Agent platform designed for maximum privacy and flexibility which encompassess and uses all the software stack. It provides a complete drop-in replacement for OpenAI's Responses APIs with advanced agentic capabilities, working entirely locally on consumer-grade hardware (CPU and GPU).
### Quick Start

View File

@@ -1,3 +1,3 @@
{
"version": "v3.1.1"
"version": "v3.3.0"
}

View File

@@ -660,7 +660,7 @@ install_docker() {
IMAGE_TAG=
if [ "$USE_VULKAN" = true ]; then
IMAGE_TAG=${LOCALAI_VERSION}-vulkan
IMAGE_TAG=${LOCALAI_VERSION}-gpu-vulkan
info "Starting LocalAI Docker container..."
$SUDO docker run -v local-ai-data:/models \
@@ -672,7 +672,7 @@ install_docker() {
-d -p $PORT:8080 --name local-ai localai/localai:$IMAGE_TAG $STARTCOMMAND
elif [ "$HAS_CUDA" ]; then
# Default to CUDA 12
IMAGE_TAG=${LOCALAI_VERSION}-gpu-nvidia-cuda12
IMAGE_TAG=${LOCALAI_VERSION}-gpu-nvidia-cuda-12
# AIO
if [ "$USE_AIO" = true ]; then
IMAGE_TAG=${LOCALAI_VERSION}-aio-gpu-nvidia-cuda-12
@@ -715,11 +715,10 @@ install_docker() {
$envs \
-d -p $PORT:8080 --name local-ai localai/localai:$IMAGE_TAG $STARTCOMMAND
elif [ "$HAS_INTEL" ]; then
# Default to FP32 for better compatibility
IMAGE_TAG=${LOCALAI_VERSION}-gpu-intel-f32
IMAGE_TAG=${LOCALAI_VERSION}-gpu-intel
# AIO
if [ "$USE_AIO" = true ]; then
IMAGE_TAG=${LOCALAI_VERSION}-aio-gpu-intel-f32
IMAGE_TAG=${LOCALAI_VERSION}-aio-gpu-intel
fi
info "Starting LocalAI Docker container..."
@@ -757,7 +756,7 @@ install_binary_darwin() {
[ "$(uname -s)" = "Darwin" ] || fatal 'This script is intended to run on macOS only.'
info "Downloading LocalAI ${LOCALAI_VERSION}..."
curl --fail --show-error --location --progress-bar -o $TEMP_DIR/local-ai "https://github.com/mudler/LocalAI/releases/download/${LOCALAI_VERSION}/local-ai-Darwin-${ARCH}"
curl --fail --show-error --location --progress-bar -o $TEMP_DIR/local-ai "https://github.com/mudler/LocalAI/releases/download/${LOCALAI_VERSION}/local-ai-${LOCALAI_VERSION}-darwin-${ARCH}"
info "Installing to /usr/local/bin/local-ai"
install -o0 -g0 -m755 $TEMP_DIR/local-ai /usr/local/bin/local-ai
@@ -789,7 +788,7 @@ install_binary() {
fi
info "Downloading LocalAI ${LOCALAI_VERSION}..."
curl --fail --location --progress-bar -o $TEMP_DIR/local-ai "https://github.com/mudler/LocalAI/releases/download/${LOCALAI_VERSION}/local-ai-Linux-${ARCH}"
curl --fail --location --progress-bar -o $TEMP_DIR/local-ai "https://github.com/mudler/LocalAI/releases/download/${LOCALAI_VERSION}/local-ai-${LOCALAI_VERSION}-linux-${ARCH}"
for BINDIR in /usr/local/bin /usr/bin /bin; do
echo $PATH | grep -q $BINDIR && break || continue
@@ -868,7 +867,7 @@ OS="$(uname -s)"
ARCH=$(uname -m)
case "$ARCH" in
x86_64) ARCH="x86_64" ;;
x86_64) ARCH="amd64" ;;
aarch64|arm64) ARCH="arm64" ;;
*) fatal "Unsupported architecture: $ARCH" ;;
esac

View File

@@ -1,4 +1,54 @@
---
- &afm
name: "arcee-ai_afm-4.5b"
url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
icon: https://cdn-uploads.huggingface.co/production/uploads/6435718aaaef013d1aec3b8b/Lj9YVLIKKdImV_jID0A1g.png
license: aml
urls:
- https://huggingface.co/arcee-ai/AFM-4.5B
- https://huggingface.co/bartowski/arcee-ai_AFM-4.5B-GGUF
tags:
- gguf
- gpu
- gpu
- text-generation
description: |
AFM-4.5B is a 4.5 billion parameter instruction-tuned model developed by Arcee.ai, designed for enterprise-grade performance across diverse deployment environments from cloud to edge. The base model was trained on a dataset of 8 trillion tokens, comprising 6.5 trillion tokens of general pretraining data followed by 1.5 trillion tokens of midtraining data with enhanced focus on mathematical reasoning and code generation. Following pretraining, the model underwent supervised fine-tuning on high-quality instruction datasets. The instruction-tuned model was further refined through reinforcement learning on verifiable rewards as well as for human preference. We use a modified version of TorchTitan for pretraining, Axolotl for supervised fine-tuning, and a modified version of Verifiers for reinforcement learning.
The development of AFM-4.5B prioritized data quality as a fundamental requirement for achieving robust model performance. We collaborated with DatologyAI, a company specializing in large-scale data curation. DatologyAI's curation pipeline integrates a suite of proprietary algorithms—model-based quality filtering, embedding-based curation, target distribution-matching, source mixing, and synthetic data. Their expertise enabled the creation of a curated dataset tailored to support strong real-world performance.
The model architecture follows a standard transformer decoder-only design based on Vaswani et al., incorporating several key modifications for enhanced performance and efficiency. Notable architectural features include grouped query attention for improved inference efficiency and ReLU^2 activation functions instead of SwiGLU to enable sparsification while maintaining or exceeding performance benchmarks.
The model available in this repo is the instruct model following supervised fine-tuning and reinforcement learning.
overrides:
parameters:
model: arcee-ai_AFM-4.5B-Q4_K_M.gguf
files:
- filename: arcee-ai_AFM-4.5B-Q4_K_M.gguf
sha256: f05516b323f581bebae1af2cbf900d83a2569b0a60c54366daf4a9c15ae30d4f
uri: huggingface://bartowski/arcee-ai_AFM-4.5B-GGUF/arcee-ai_AFM-4.5B-Q4_K_M.gguf
- &rfdetr
name: "rfdetr-base"
url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
icon: https://avatars.githubusercontent.com/u/53104118?s=200&v=4
license: apache-2.0
description: |
RF-DETR is a real-time, transformer-based object detection model architecture developed by Roboflow and released under the Apache 2.0 license.
RF-DETR is the first real-time model to exceed 60 AP on the Microsoft COCO benchmark alongside competitive performance at base sizes. It also achieves state-of-the-art performance on RF100-VL, an object detection benchmark that measures model domain adaptability to real world problems. RF-DETR is fastest and most accurate for its size when compared current real-time objection models.
RF-DETR is small enough to run on the edge using Inference, making it an ideal model for deployments that need both strong accuracy and real-time performance.
tags:
- object-detection
- rfdetr
- gpu
- cpu
urls:
- https://github.com/roboflow/rf-detr
overrides:
backend: rfdetr
parameters:
model: rfdetr-base
known_usecases:
- detection
- name: "dream-org_dream-v0-instruct-7b"
# chatml
url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
@@ -1856,6 +1906,43 @@
- filename: Menlo_Lucy-128k-Q4_K_M.gguf
sha256: fb3e591cccc5d2821f3c615fd6dc2ca86d409f56fbc124275510a9612a90e61f
uri: huggingface://bartowski/Menlo_Lucy-128k-GGUF/Menlo_Lucy-128k-Q4_K_M.gguf
- !!merge <<: *qwen3
name: "qwen_qwen3-30b-a3b-instruct-2507"
urls:
- https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507
- https://huggingface.co/bartowski/Qwen_Qwen3-30B-A3B-Instruct-2507-GGUF
description: |
We introduce the updated version of the Qwen3-30B-A3B non-thinking mode, named Qwen3-30B-A3B-Instruct-2507, featuring the following key enhancements:
Significant improvements in general capabilities, including instruction following, logical reasoning, text comprehension, mathematics, science, coding and tool usage.
Substantial gains in long-tail knowledge coverage across multiple languages.
Markedly better alignment with user preferences in subjective and open-ended tasks, enabling more helpful responses and higher-quality text generation.
Enhanced capabilities in 256K long-context understanding.
overrides:
parameters:
model: Qwen_Qwen3-30B-A3B-Instruct-2507-Q4_K_M.gguf
files:
- filename: Qwen_Qwen3-30B-A3B-Instruct-2507-Q4_K_M.gguf
sha256: 382b4f5a164d200f93790ee0e339fae12852896d23485cfb203ce868fea33a95
uri: huggingface://bartowski/Qwen_Qwen3-30B-A3B-Instruct-2507-GGUF/Qwen_Qwen3-30B-A3B-Instruct-2507-Q4_K_M.gguf
- !!merge <<: *qwen3
name: "qwen_qwen3-30b-a3b-thinking-2507"
urls:
- https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507
- https://huggingface.co/bartowski/Qwen_Qwen3-30B-A3B-Thinking-2507-GGUF
description: |
Over the past three months, we have continued to scale the thinking capability of Qwen3-30B-A3B, improving both the quality and depth of reasoning. We are pleased to introduce Qwen3-30B-A3B-Thinking-2507, featuring the following key enhancements:
Significantly improved performance on reasoning tasks, including logical reasoning, mathematics, science, coding, and academic benchmarks that typically require human expertise.
Markedly better general capabilities, such as instruction following, tool usage, text generation, and alignment with human preferences.
Enhanced 256K long-context understanding capabilities.
NOTE: This version has an increased thinking length. We strongly recommend its use in highly complex reasoning tasks.
overrides:
parameters:
model: Qwen_Qwen3-30B-A3B-Thinking-2507-Q4_K_M.gguf
files:
- filename: Qwen_Qwen3-30B-A3B-Thinking-2507-Q4_K_M.gguf
sha256: 1359aa08e2f2dfe7ce4b5ff88c4c996e6494c9d916b1ebacd214bb74bbd5a9db
uri: huggingface://bartowski/Qwen_Qwen3-30B-A3B-Thinking-2507-GGUF/Qwen_Qwen3-30B-A3B-Thinking-2507-Q4_K_M.gguf
- &gemma3
url: "github:mudler/LocalAI/gallery/gemma.yaml@master"
name: "gemma-3-27b-it"
@@ -19057,6 +19144,148 @@
overrides:
parameters:
model: SicariusSicariiStuff/flux.1dev-abliteratedv2
- name: flux.1-kontext-dev
license: flux-1-dev-non-commercial-license
url: "github:mudler/LocalAI/gallery/flux-ggml.yaml@master"
icon: https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev/media/main/teaser.png
description: |
FLUX.1 Kontext [dev] is a 12 billion parameter rectified flow transformer capable of editing images based on text instructions. For more information, please read our blog post and our technical report. You can find information about the [pro] version in here.
Key Features
Change existing images based on an edit instruction.
Have character, style and object reference without any finetuning.
Robust consistency allows users to refine an image through multiple successive edits with minimal visual drift.
Trained using guidance distillation, making FLUX.1 Kontext [dev] more efficient.
Open weights to drive new scientific research, and empower artists to develop innovative workflows.
Generated outputs can be used for personal, scientific, and commercial purposes, as described in the FLUX.1 [dev] Non-Commercial License.
urls:
- https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev
- https://huggingface.co/QuantStack/FLUX.1-Kontext-dev-GGUF
tags:
- image-to-image
- flux
- gpu
- cpu
overrides:
parameters:
model: flux1-kontext-dev-Q8_0.gguf
files:
- filename: "flux1-kontext-dev-Q8_0.gguf"
sha256: "ff2ff71c3755c8ab394398a412252c23382a83138b65190b16e736d457b80f73"
uri: "huggingface://QuantStack/FLUX.1-Kontext-dev-GGUF/flux1-kontext-dev-Q8_0.gguf"
- filename: ae.safetensors
sha256: afc8e28272cd15db3919bacdb6918ce9c1ed22e96cb12c4d5ed0fba823529e38
uri: https://huggingface.co/ChuckMcSneed/FLUX.1-dev/resolve/main/ae.safetensors
- filename: clip_l.safetensors
sha256: 660c6f5b1abae9dc498ac2d21e1347d2abdb0cf6c0c0c8576cd796491d9a6cdd
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors
- filename: t5xxl_fp16.safetensors
sha256: 6e480b09fae049a72d2a8c5fbccb8d3e92febeb233bbe9dfe7256958a9167635
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors
- !!merge <<: *flux
name: flux.1-dev-ggml-q8_0
license: flux-1-dev-non-commercial-license
url: "github:mudler/LocalAI/gallery/flux-ggml.yaml@master"
urls:
- https://huggingface.co/black-forest-labs/FLUX.1-dev
- https://huggingface.co/city96/FLUX.1-dev-gguf
overrides:
parameters:
model: flux1-dev-Q8_0.gguf
files:
- filename: "flux1-dev-Q8_0.gguf"
sha256: "129032f32224bf7138f16e18673d8008ba5f84c1ec74063bf4511a8bb4cf553d"
uri: "huggingface://city96/FLUX.1-dev-gguf/flux1-dev-Q8_0.gguf"
- filename: ae.safetensors
sha256: afc8e28272cd15db3919bacdb6918ce9c1ed22e96cb12c4d5ed0fba823529e38
uri: https://huggingface.co/ChuckMcSneed/FLUX.1-dev/resolve/main/ae.safetensors
- filename: clip_l.safetensors
sha256: 660c6f5b1abae9dc498ac2d21e1347d2abdb0cf6c0c0c8576cd796491d9a6cdd
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors
- filename: t5xxl_fp16.safetensors
sha256: 6e480b09fae049a72d2a8c5fbccb8d3e92febeb233bbe9dfe7256958a9167635
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors
- !!merge <<: *flux
name: flux.1-dev-ggml-abliterated-v2-q8_0
url: "github:mudler/LocalAI/gallery/flux-ggml.yaml@master"
description: |
FLUX.1 [dev] is an abliterated version of FLUX.1 [dev]
urls:
- https://huggingface.co/black-forest-labs/FLUX.1-dev
- https://huggingface.co/t8star/flux.1-dev-abliterated-V2-GGUF
overrides:
parameters:
model: T8-flux.1-dev-abliterated-V2-GGUF-Q8_0.gguf
files:
- filename: "T8-flux.1-dev-abliterated-V2-GGUF-Q8_0.gguf"
sha256: "aba8163ff644018da195212a1c33aeddbf802a0c2bba96abc584a2d0b6b42272"
uri: "huggingface://t8star/flux.1-dev-abliterated-V2-GGUF/T8-flux.1-dev-abliterated-V2-GGUF-Q8_0.gguf"
- filename: ae.safetensors
sha256: afc8e28272cd15db3919bacdb6918ce9c1ed22e96cb12c4d5ed0fba823529e38
uri: https://huggingface.co/ChuckMcSneed/FLUX.1-dev/resolve/main/ae.safetensors
- filename: clip_l.safetensors
sha256: 660c6f5b1abae9dc498ac2d21e1347d2abdb0cf6c0c0c8576cd796491d9a6cdd
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors
- filename: t5xxl_fp16.safetensors
sha256: 6e480b09fae049a72d2a8c5fbccb8d3e92febeb233bbe9dfe7256958a9167635
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors
- !!merge <<: *flux
name: flux.1-krea-dev-ggml
url: "github:mudler/LocalAI/gallery/flux-ggml.yaml@master"
description: |
FLUX.1 Krea [dev] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post and Krea's blog post.
Cutting-edge output quality, with a focus on aesthetic photography.
Competitive prompt following, matching the performance of closed source alternatives.
Trained using guidance distillation, making FLUX.1 Krea [dev] more efficient.
Open weights to drive new scientific research, and empower artists to develop innovative workflows.
Generated outputs can be used for personal, scientific, and commercial purposes, as described in the flux-1-dev-non-commercial-license.
urls:
- https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev
- https://huggingface.co/QuantStack/FLUX.1-Krea-dev-GGUF
overrides:
parameters:
model: flux1-krea-dev-Q4_K_M.gguf
files:
- filename: "flux1-krea-dev-Q4_K_M.gguf"
sha256: "cf199b88509be2b3476a3372ff03eaaa662cb2b5d3710abf939ebb4838dbdcaf"
uri: "huggingface://QuantStack/FLUX.1-Krea-dev-GGUF/flux1-krea-dev-Q4_K_M.gguf"
- filename: ae.safetensors
sha256: afc8e28272cd15db3919bacdb6918ce9c1ed22e96cb12c4d5ed0fba823529e38
uri: https://huggingface.co/ChuckMcSneed/FLUX.1-dev/resolve/main/ae.safetensors
- filename: clip_l.safetensors
sha256: 660c6f5b1abae9dc498ac2d21e1347d2abdb0cf6c0c0c8576cd796491d9a6cdd
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors
- filename: t5xxl_fp16.safetensors
sha256: 6e480b09fae049a72d2a8c5fbccb8d3e92febeb233bbe9dfe7256958a9167635
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors
- !!merge <<: *flux
name: flux.1-krea-dev-ggml-q8_0
url: "github:mudler/LocalAI/gallery/flux-ggml.yaml@master"
description: |
FLUX.1 Krea [dev] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post and Krea's blog post.
Cutting-edge output quality, with a focus on aesthetic photography.
Competitive prompt following, matching the performance of closed source alternatives.
Trained using guidance distillation, making FLUX.1 Krea [dev] more efficient.
Open weights to drive new scientific research, and empower artists to develop innovative workflows.
Generated outputs can be used for personal, scientific, and commercial purposes, as described in the flux-1-dev-non-commercial-license.
urls:
- https://huggingface.co/black-forest-labs/FLUX.1-Krea-dev
- https://huggingface.co/markury/FLUX.1-Krea-dev-gguf
overrides:
parameters:
model: flux1-krea-dev-Q8_0.gguf
files:
- filename: "flux1-krea-dev-Q8_0.gguf"
sha256: "0d085b1e3ae0b90e5dbf74da049a80a565617de622a147d28ee37a07761fbd90"
uri: "huggingface://markury/FLUX.1-Krea-dev-gguf/flux1-krea-dev-Q8_0.gguf"
- filename: ae.safetensors
sha256: afc8e28272cd15db3919bacdb6918ce9c1ed22e96cb12c4d5ed0fba823529e38
uri: https://huggingface.co/ChuckMcSneed/FLUX.1-dev/resolve/main/ae.safetensors
- filename: clip_l.safetensors
sha256: 660c6f5b1abae9dc498ac2d21e1347d2abdb0cf6c0c0c8576cd796491d9a6cdd
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors
- filename: t5xxl_fp16.safetensors
sha256: 6e480b09fae049a72d2a8c5fbccb8d3e92febeb233bbe9dfe7256958a9167635
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors
- &whisper
url: "github:mudler/LocalAI/gallery/whisper-base.yaml@master" ## Whisper
name: "whisper-1"

View File

@@ -9,7 +9,7 @@ import (
var embeds = map[string]*embedBackend{}
func Provide(addr string, llm LLM) {
func Provide(addr string, llm AIModel) {
embeds[addr] = &embedBackend{s: &server{llm: llm}}
}
@@ -42,6 +42,7 @@ type Backend interface {
GenerateVideo(ctx context.Context, in *pb.GenerateVideoRequest, opts ...grpc.CallOption) (*pb.Result, error)
TTS(ctx context.Context, in *pb.TTSRequest, opts ...grpc.CallOption) (*pb.Result, error)
SoundGeneration(ctx context.Context, in *pb.SoundGenerationRequest, opts ...grpc.CallOption) (*pb.Result, error)
Detect(ctx context.Context, in *pb.DetectOptions, opts ...grpc.CallOption) (*pb.DetectResponse, error)
AudioTranscription(ctx context.Context, in *pb.TranscriptRequest, opts ...grpc.CallOption) (*pb.TranscriptResult, error)
TokenizeString(ctx context.Context, in *pb.PredictOptions, opts ...grpc.CallOption) (*pb.TokenizationResponse, error)
Status(ctx context.Context) (*pb.StatusResponse, error)

View File

@@ -69,6 +69,10 @@ func (llm *Base) SoundGeneration(*pb.SoundGenerationRequest) error {
return fmt.Errorf("unimplemented")
}
func (llm *Base) Detect(*pb.DetectOptions) (pb.DetectResponse, error) {
return pb.DetectResponse{}, fmt.Errorf("unimplemented")
}
func (llm *Base) TokenizeString(opts *pb.PredictOptions) (pb.TokenizationResponse, error) {
return pb.TokenizationResponse{}, fmt.Errorf("unimplemented")
}

View File

@@ -504,3 +504,25 @@ func (c *Client) VAD(ctx context.Context, in *pb.VADRequest, opts ...grpc.CallOp
client := pb.NewBackendClient(conn)
return client.VAD(ctx, in, opts...)
}
func (c *Client) Detect(ctx context.Context, in *pb.DetectOptions, opts ...grpc.CallOption) (*pb.DetectResponse, error) {
if !c.parallel {
c.opMutex.Lock()
defer c.opMutex.Unlock()
}
c.setBusy(true)
defer c.setBusy(false)
c.wdMark()
defer c.wdUnMark()
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()),
grpc.WithDefaultCallOptions(
grpc.MaxCallRecvMsgSize(50*1024*1024), // 50MB
grpc.MaxCallSendMsgSize(50*1024*1024), // 50MB
))
if err != nil {
return nil, err
}
defer conn.Close()
client := pb.NewBackendClient(conn)
return client.Detect(ctx, in, opts...)
}

View File

@@ -59,6 +59,10 @@ func (e *embedBackend) SoundGeneration(ctx context.Context, in *pb.SoundGenerati
return e.s.SoundGeneration(ctx, in)
}
func (e *embedBackend) Detect(ctx context.Context, in *pb.DetectOptions, opts ...grpc.CallOption) (*pb.DetectResponse, error) {
return e.s.Detect(ctx, in)
}
func (e *embedBackend) AudioTranscription(ctx context.Context, in *pb.TranscriptRequest, opts ...grpc.CallOption) (*pb.TranscriptResult, error) {
return e.s.AudioTranscription(ctx, in)
}

View File

@@ -4,7 +4,7 @@ import (
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
type LLM interface {
type AIModel interface {
Busy() bool
Lock()
Unlock()
@@ -15,6 +15,7 @@ type LLM interface {
Embeddings(*pb.PredictOptions) ([]float32, error)
GenerateImage(*pb.GenerateImageRequest) error
GenerateVideo(*pb.GenerateVideoRequest) error
Detect(*pb.DetectOptions) (pb.DetectResponse, error)
AudioTranscription(*pb.TranscriptRequest) (pb.TranscriptResult, error)
TTS(*pb.TTSRequest) error
SoundGeneration(*pb.SoundGenerationRequest) error

View File

@@ -22,7 +22,7 @@ import (
// server is used to implement helloworld.GreeterServer.
type server struct {
pb.UnimplementedBackendServer
llm LLM
llm AIModel
}
func (s *server) Health(ctx context.Context, in *pb.HealthMessage) (*pb.Reply, error) {
@@ -111,6 +111,18 @@ func (s *server) SoundGeneration(ctx context.Context, in *pb.SoundGenerationRequ
return &pb.Result{Message: "Sound Generation audio generated", Success: true}, nil
}
func (s *server) Detect(ctx context.Context, in *pb.DetectOptions) (*pb.DetectResponse, error) {
if s.llm.Locking() {
s.llm.Lock()
defer s.llm.Unlock()
}
res, err := s.llm.Detect(in)
if err != nil {
return nil, err
}
return &res, nil
}
func (s *server) AudioTranscription(ctx context.Context, in *pb.TranscriptRequest) (*pb.TranscriptResult, error) {
if s.llm.Locking() {
s.llm.Lock()
@@ -251,7 +263,7 @@ func (s *server) VAD(ctx context.Context, in *pb.VADRequest) (*pb.VADResponse, e
return &res, nil
}
func StartServer(address string, model LLM) error {
func StartServer(address string, model AIModel) error {
lis, err := net.Listen("tcp", address)
if err != nil {
return err
@@ -269,7 +281,7 @@ func StartServer(address string, model LLM) error {
return nil
}
func RunServer(address string, model LLM) (func() error, error) {
func RunServer(address string, model AIModel) (func() error, error) {
lis, err := net.Listen("tcp", address)
if err != nil {
return nil, err

View File

@@ -18,6 +18,13 @@ const (
nvidiaL4T = "nvidia-l4t"
darwinX86 = "darwin-x86"
metal = "metal"
nvidia = "nvidia"
amd = "amd"
intel = "intel"
capabilityEnv = "LOCALAI_FORCE_META_BACKEND_CAPABILITY"
capabilityRunFileEnv = "LOCALAI_FORCE_META_BACKEND_CAPABILITY_RUN_FILE"
defaultRunFile = "/run/localai/capability"
)
func (s *SystemState) Capability(capMap map[string]string) string {
@@ -25,21 +32,26 @@ func (s *SystemState) Capability(capMap map[string]string) string {
// Check if the reported capability is in the map
if _, exists := capMap[reportedCapability]; exists {
log.Debug().Str("reportedCapability", reportedCapability).Any("capMap", capMap).Msg("Using reported capability")
return reportedCapability
}
log.Debug().Str("reportedCapability", reportedCapability).Any("capMap", capMap).Msg("The requested capability was not found, using default capability")
// Otherwise, return the default capability (catch-all)
return defaultCapability
}
func (s *SystemState) getSystemCapabilities() string {
if os.Getenv("LOCALAI_FORCE_META_BACKEND_CAPABILITY") != "" {
return os.Getenv("LOCALAI_FORCE_META_BACKEND_CAPABILITY")
capability := os.Getenv(capabilityEnv)
if capability != "" {
log.Info().Str("capability", capability).Msgf("Using forced capability from environment variable (%s)", capabilityEnv)
return capability
}
capabilityRunFile := "/run/localai/capability"
if os.Getenv("LOCALAI_FORCE_META_BACKEND_CAPABILITY_RUN_FILE") != "" {
capabilityRunFile = os.Getenv("LOCALAI_FORCE_META_BACKEND_CAPABILITY_RUN_FILE")
capabilityRunFile := defaultRunFile
capabilityRunFileEnv := os.Getenv(capabilityRunFileEnv)
if capabilityRunFileEnv != "" {
capabilityRunFile = capabilityRunFileEnv
}
// Check if /run/localai/capability exists and use it
@@ -48,31 +60,37 @@ func (s *SystemState) getSystemCapabilities() string {
if _, err := os.Stat(capabilityRunFile); err == nil {
capability, err := os.ReadFile(capabilityRunFile)
if err == nil {
return string(capability)
log.Info().Str("capabilityRunFile", capabilityRunFile).Str("capability", string(capability)).Msgf("Using forced capability run file (%s)", capabilityRunFileEnv)
return strings.Trim(strings.TrimSpace(string(capability)), "\n")
}
}
// If we are on mac and arm64, we will return metal
if runtime.GOOS == "darwin" && runtime.GOARCH == "arm64" {
log.Info().Msgf("Using metal capability (arm64 on mac), set %s to override", capabilityEnv)
return metal
}
// If we are on mac and x86, we will return darwin-x86
if runtime.GOOS == "darwin" && runtime.GOARCH == "amd64" {
log.Info().Msgf("Using darwin-x86 capability (amd64 on mac), set %s to override", capabilityEnv)
return darwinX86
}
// If arm64 on linux and a nvidia gpu is detected, we will return nvidia-l4t
if runtime.GOOS == "linux" && runtime.GOARCH == "arm64" {
if s.GPUVendor == "nvidia" {
log.Info().Msgf("Using nvidia-l4t capability (arm64 on linux), set %s to override", capabilityEnv)
return nvidiaL4T
}
}
if s.GPUVendor == "" {
log.Info().Msgf("Default capability (no GPU detected), set %s to override", capabilityEnv)
return defaultCapability
}
log.Info().Str("Capability", s.GPUVendor).Msgf("Capability automatically detected, set %s to override", capabilityEnv)
return s.GPUVendor
}
@@ -96,18 +114,16 @@ func detectGPUVendor() (string, error) {
if gpu.DeviceInfo.Vendor != nil {
gpuVendorName := strings.ToUpper(gpu.DeviceInfo.Vendor.Name)
if strings.Contains(gpuVendorName, "NVIDIA") {
return "nvidia", nil
return nvidia, nil
}
if strings.Contains(gpuVendorName, "AMD") {
return "amd", nil
return amd, nil
}
if strings.Contains(gpuVendorName, "INTEL") {
return "intel", nil
return intel, nil
}
return "nvidia", nil
}
}
}
return "", nil

View File

@@ -20,7 +20,7 @@ var dataURIPattern = regexp.MustCompile(`^data:([^;]+);base64,`)
// GetContentURIAsBase64 checks if the string is an URL, if it's an URL downloads the content in memory encodes it in base64 and returns the base64 string, otherwise returns the string by stripping base64 data headers
func GetContentURIAsBase64(s string) (string, error) {
if strings.HasPrefix(s, "http") {
if strings.HasPrefix(s, "http") || strings.HasPrefix(s, "https") {
// download the image
resp, err := base64DownloadClient.Get(s)
if err != nil {

View File

@@ -1,42 +0,0 @@
package utils
import (
"encoding/json"
"os"
"path/filepath"
"github.com/rs/zerolog/log"
)
func SaveConfig(filePath, fileName string, obj any) {
file, err := json.MarshalIndent(obj, "", " ")
if err != nil {
log.Error().Err(err).Msg("failed to JSON marshal the uploadedFiles")
}
absolutePath := filepath.Join(filePath, fileName)
err = os.WriteFile(absolutePath, file, 0600)
if err != nil {
log.Error().Err(err).Str("filepath", absolutePath).Msg("failed to save configuration file")
}
}
func LoadConfig(filePath, fileName string, obj interface{}) {
uploadFilePath := filepath.Join(filePath, fileName)
_, err := os.Stat(uploadFilePath)
if os.IsNotExist(err) {
log.Debug().Msgf("No configuration file found at %s", uploadFilePath)
return
}
file, err := os.ReadFile(uploadFilePath)
if err != nil {
log.Error().Err(err).Str("filepath", uploadFilePath).Msg("failed to read file")
} else {
err = json.Unmarshal(file, &obj)
if err != nil {
log.Error().Err(err).Str("filepath", uploadFilePath).Msg("failed to parse file as JSON")
}
}
}

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