Compare commits

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38 Commits

Author SHA1 Message Date
Georgi Gerganov c8f8e2364c cont : simplify 2026-05-11 10:54:07 +03:00
Aman Gupta c417ddfc74 fix batch size 2026-05-11 12:22:37 +08:00
Aman Gupta a428b010ab spec: support MTP 2026-05-11 11:28:30 +08:00
Georgi Gerganov db8e326913 spec : introduce common_speculative_process() 2026-05-09 17:12:24 +03:00
Georgi Gerganov 0d5dd61d66 spec : reset drafting flag at the end 2026-05-09 17:12:06 +03:00
Georgi Gerganov ec8bc44854 cont : minor 2026-05-09 16:38:17 +03:00
Georgi Gerganov b3bd3bd4cc cont : clean-up 2026-05-09 15:03:20 +03:00
Georgi Gerganov ce0acf03ea server, spec : clean-up 2026-05-09 10:21:57 +03:00
Georgi Gerganov 55b62bce15 llama : reuse device buffers when possible 2026-05-08 20:42:56 +03:00
Georgi Gerganov f1652197dd server : support parallel drafting 2026-05-08 19:30:31 +03:00
Georgi Gerganov f88c942861 spec : support parallel drafts 2026-05-08 18:53:33 +03:00
Georgi Gerganov 927d6635d3 cont : prepare params 2026-05-08 17:50:20 +03:00
Georgi Gerganov 8822c122be cont : prepare params 2026-05-08 17:06:24 +03:00
Georgi Gerganov 6582523eaa spec : refactor for multi-sequence speculative context 2026-05-08 15:43:36 +03:00
Georgi Gerganov efa2f8e5a7 naming : improve consistency 2026-05-08 12:24:57 +03:00
Georgi Gerganov 778f9e247e tools : update readme 2026-05-08 11:55:16 +03:00
Georgi Gerganov 1dbc054da5 server : fix slot ctx_drft ptr 2026-05-08 11:55:05 +03:00
Georgi Gerganov 161eae0adf spec : fix n_past type 2026-05-08 11:54:32 +03:00
Georgi Gerganov e5b1401318 speculative-simple : update 2026-05-08 11:09:34 +03:00
Georgi Gerganov 3b1a8df8fd server : clean-up + dry 2026-05-08 10:20:01 +03:00
Georgi Gerganov 233d1aee69 server : add comment
[no ci]
2026-05-08 08:50:23 +03:00
Georgi Gerganov 12c7cfbe83 server : fix URL for draft model 2026-05-08 08:03:49 +03:00
Georgi Gerganov 6a4b05a030 server : fix mtmd draft processing 2026-05-08 08:02:11 +03:00
Georgi Gerganov 8be14e40de spec : handle draft running out of context 2026-05-08 07:11:51 +03:00
Georgi Gerganov 7e118cdce0 cont : process images throught the draft context 2026-05-07 21:44:09 +03:00
Georgi Gerganov ae6703fa89 cont : pass correct n_past for drafting 2026-05-07 21:44:08 +03:00
Georgi Gerganov 0239f4c611 cont : handle non-ckpt models 2026-05-07 21:44:08 +03:00
Georgi Gerganov c7facb0fe1 cont : async drft eval when possible 2026-05-07 21:44:08 +03:00
Georgi Gerganov 08c8012bde cont : sync main and drft contexts 2026-05-07 21:44:08 +03:00
Georgi Gerganov de35b1255c server, spec : transition to unified spec context 2026-05-07 21:44:08 +03:00
Georgi Gerganov 1afee5b262 server : improve ctx names
[no ci]
2026-05-07 21:44:08 +03:00
Georgi Gerganov 11fd5e7272 server : draft prompt cache and checkpoints
[no ci]
2026-05-07 21:44:08 +03:00
Georgi Gerganov c97dc3605e server : sketch the ctx_dft decode loop
[no ci]
2026-05-07 21:44:08 +03:00
Georgi Gerganov 8a50f6f0b9 cont : dedup ctx_seq_rm_type
[no ci]
2026-05-07 21:44:07 +03:00
Georgi Gerganov 77269ad8a7 cont : pass seq_id
[no ci]
2026-05-07 21:44:07 +03:00
Georgi Gerganov 4550f0f08b spec : update common_speculative_init()
[no ci]
2026-05-07 21:44:07 +03:00
Georgi Gerganov befc7ef635 spec : drop support for incompatible vocabs
[no ci]
2026-05-07 21:44:07 +03:00
Georgi Gerganov 2c9a40849f spec : refactor
[no ci]
2026-05-07 21:44:07 +03:00
1233 changed files with 51777 additions and 82079 deletions
-17
View File
@@ -5,9 +5,6 @@
# Define the CANN base image for easier version updates later
ARG CHIP_TYPE=910b
ARG CANN_BASE_IMAGE=quay.io/ascend/cann:8.5.0-${CHIP_TYPE}-openeuler24.03-py3.11
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
# ==============================================================================
# BUILD STAGE
@@ -58,7 +55,6 @@ RUN mkdir -p /app/lib && \
RUN mkdir -p /app/full && \
cp build/bin/* /app/full/ && \
cp *.py /app/full/ && \
cp -r conversion /app/full/ && \
cp -r gguf-py /app/full/ && \
cp -r requirements /app/full/ && \
cp requirements.txt /app/full/
@@ -71,19 +67,6 @@ RUN mkdir -p /app/full && \
# ==============================================================================
FROM ${CANN_BASE_IMAGE} AS base
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
# -- Install runtime dependencies --
RUN yum install -y libgomp curl && \
yum clean all && \
-17
View File
@@ -1,7 +1,4 @@
ARG UBUNTU_VERSION=24.04
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
FROM ubuntu:$UBUNTU_VERSION AS build
@@ -30,7 +27,6 @@ RUN mkdir -p /app/lib && \
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
&& cp *.py /app/full \
&& cp -r conversion /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
@@ -39,19 +35,6 @@ RUN mkdir -p /app/full \
## Base image
FROM ubuntu:$UBUNTU_VERSION AS base
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
RUN apt-get update \
&& apt-get install -y libgomp1 curl \
&& apt autoremove -y \
-18
View File
@@ -6,10 +6,6 @@ ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VER
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# CUDA architecture to build for (defaults to all supported archs)
@@ -36,7 +32,6 @@ RUN mkdir -p /app/lib && \
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
&& cp *.py /app/full \
&& cp -r conversion /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
@@ -45,19 +40,6 @@ RUN mkdir -p /app/full \
## Base image
FROM ${BASE_CUDA_RUN_CONTAINER} AS base
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
RUN apt-get update \
&& apt-get install -y libgomp1 curl \
&& apt autoremove -y \
+7 -30
View File
@@ -1,22 +1,12 @@
ARG ONEAPI_VERSION=2025.3.3-0-devel-ubuntu24.04
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
## Build Image
FROM intel/deep-learning-essentials:$ONEAPI_VERSION AS build
ARG GGML_SYCL_F16=OFF
ARG LEVEL_ZERO_VERSION=1.28.2
ARG LEVEL_ZERO_UBUNTU_VERSION=u24.04
RUN apt-get update && \
apt-get install -y git libssl-dev wget ca-certificates && \
cd /tmp && \
wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero.deb && \
wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero-devel_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero-devel.deb && \
apt-get -o Dpkg::Options::="--force-overwrite" install -y ./level-zero.deb ./level-zero-devel.deb && \
rm -f /tmp/level-zero.deb /tmp/level-zero-devel.deb
apt-get install -y git libssl-dev
WORKDIR /app
@@ -36,7 +26,6 @@ RUN mkdir -p /app/lib && \
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
&& cp *.py /app/full \
&& cp -r conversion /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
@@ -44,24 +33,11 @@ RUN mkdir -p /app/full \
FROM intel/deep-learning-essentials:$ONEAPI_VERSION AS base
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
ARG IGC_VERSION=v2.20.5
ARG IGC_VERSION_FULL=2_2.20.5+19972
ARG COMPUTE_RUNTIME_VERSION=25.40.35563.10
ARG COMPUTE_RUNTIME_VERSION_FULL=25.40.35563.10-0
ARG IGDGMM_VERSION=22.8.2
ARG IGC_VERSION=v2.30.1
ARG IGC_VERSION_FULL=2_2.30.1+20950
ARG COMPUTE_RUNTIME_VERSION=26.09.37435.1
ARG COMPUTE_RUNTIME_VERSION_FULL=26.09.37435.1-0
ARG IGDGMM_VERSION=22.9.0
RUN mkdir /tmp/neo/ && cd /tmp/neo/ \
&& wget https://github.com/intel/intel-graphics-compiler/releases/download/$IGC_VERSION/intel-igc-core-${IGC_VERSION_FULL}_amd64.deb \
&& wget https://github.com/intel/intel-graphics-compiler/releases/download/$IGC_VERSION/intel-igc-opencl-${IGC_VERSION_FULL}_amd64.deb \
@@ -133,3 +109,4 @@ WORKDIR /app
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/app/llama-server" ]
-17
View File
@@ -1,7 +1,4 @@
ARG ASCEND_VERSION=8.5.0-910b-openeuler22.03-py3.10
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
FROM ascendai/cann:$ASCEND_VERSION AS build
@@ -31,20 +28,6 @@ RUN echo "Building with static libs" && \
# TODO: use image with NNRT
FROM ascendai/cann:$ASCEND_VERSION AS runtime
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
COPY --from=build /app/build/bin/llama-cli /app/build/bin/llama-completion /
ENV LC_ALL=C.utf8
-18
View File
@@ -6,10 +6,6 @@ ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_V
ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}-amd64
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
# MUSA architecture to build for (defaults to all supported archs)
@@ -41,7 +37,6 @@ RUN mkdir -p /app/lib && \
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
&& cp *.py /app/full \
&& cp -r conversion /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
@@ -50,19 +45,6 @@ RUN mkdir -p /app/full \
## Base image
FROM ${BASE_MUSA_RUN_CONTAINER} AS base
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
RUN apt-get update \
&& apt-get install -y libgomp1 curl \
&& apt autoremove -y \
+1 -1
View File
@@ -103,7 +103,6 @@ let
vulkan-headers
vulkan-loader
shaderc
spirv-headers
];
in
@@ -147,6 +146,7 @@ effectiveStdenv.mkDerivation (finalAttrs: {
ninja
pkg-config
git
spirv-headers
]
++ optionals useCuda [
cudaPackages.cuda_nvcc
-17
View File
@@ -18,10 +18,6 @@ ARG LIBZE1_VERSION=1.27.0-1~24.04~ppa2
ARG http_proxy=
ARG https_proxy=
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
## Build Image
FROM ubuntu:${UBUNTU_VERSION} AS build
@@ -81,7 +77,6 @@ RUN mkdir -p /app/lib && \
RUN mkdir -p /app/full \
&& cp build/ReleaseOV/bin/* /app/full/ \
&& cp *.py /app/full \
&& cp -r conversion /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
@@ -93,18 +88,6 @@ FROM ubuntu:${UBUNTU_VERSION} AS base
# Pass proxy args to runtime stage
ARG http_proxy
ARG https_proxy
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
RUN apt-get update \
&& apt-get install -y libgomp1 libtbb12 curl wget ocl-icd-libopencl1 \
-18
View File
@@ -7,10 +7,6 @@ ARG AMDGPU_VERSION=7.2.1
# Target the ROCm build image
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
### Build image
FROM ${BASE_ROCM_DEV_CONTAINER} AS build
@@ -53,7 +49,6 @@ RUN mkdir -p /app/lib \
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
&& cp *.py /app/full \
&& cp -r conversion /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
@@ -62,19 +57,6 @@ RUN mkdir -p /app/full \
## Base image
FROM ${BASE_ROCM_DEV_CONTAINER} AS base
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
RUN apt-get update \
&& apt-get install -y libgomp1 curl \
&& apt autoremove -y \
+3 -22
View File
@@ -1,8 +1,5 @@
ARG GCC_VERSION=15.2.0
ARG UBUNTU_VERSION=24.04
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
### Build Llama.cpp stage
FROM gcc:${GCC_VERSION} AS build
@@ -37,7 +34,6 @@ RUN --mount=type=cache,target=/root/.ccache \
COPY *.py /opt/llama.cpp/bin
COPY .devops/tools.sh /opt/llama.cpp/bin
COPY conversion /opt/llama.cpp/conversion
COPY gguf-py /opt/llama.cpp/gguf-py
COPY requirements.txt /opt/llama.cpp/gguf-py
@@ -48,28 +44,14 @@ COPY requirements /opt/llama.cpp/gguf-py/requirements
FROM scratch AS collector
# Copy llama.cpp binaries and libraries
COPY --from=build /opt/llama.cpp/bin /llama.cpp/bin
COPY --from=build /opt/llama.cpp/lib /llama.cpp/lib
COPY --from=build /opt/llama.cpp/gguf-py /llama.cpp/gguf-py
COPY --from=build /opt/llama.cpp/conversion /llama.cpp/conversion
COPY --from=build /opt/llama.cpp/bin /llama.cpp/bin
COPY --from=build /opt/llama.cpp/lib /llama.cpp/lib
COPY --from=build /opt/llama.cpp/gguf-py /llama.cpp/gguf-py
### Base image
FROM ubuntu:${UBUNTU_VERSION} AS base
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt/lists,sharing=locked \
apt update -y && \
@@ -109,7 +91,6 @@ RUN curl https://sh.rustup.rs -sSf | bash -s -- -y
COPY --from=collector /llama.cpp/bin /app
COPY --from=collector /llama.cpp/gguf-py /app/gguf-py
COPY --from=collector /llama.cpp/conversion /app/conversion
RUN pip install --no-cache-dir --break-system-packages \
-r /app/gguf-py/requirements.txt
-17
View File
@@ -1,7 +1,4 @@
ARG UBUNTU_VERSION=26.04
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
FROM ubuntu:$UBUNTU_VERSION AS build
@@ -26,7 +23,6 @@ RUN mkdir -p /app/lib && \
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
&& cp *.py /app/full \
&& cp -r conversion /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
@@ -35,19 +31,6 @@ RUN mkdir -p /app/full \
## Base image
FROM ubuntu:$UBUNTU_VERSION AS base
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
RUN apt-get update \
&& apt-get install -y libgomp1 curl libvulkan1 mesa-vulkan-drivers \
libglvnd0 libgl1 libglx0 libegl1 libgles2 \
-101
View File
@@ -1,101 +0,0 @@
ARG UBUNTU_VERSION=24.04
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
FROM ubuntu:$UBUNTU_VERSION AS build
RUN apt-get update && \
apt-get install -y gcc-13 g++-13 build-essential git cmake libssl-dev libomp-dev libnuma-dev python3 ca-certificates
ENV CC=gcc-13 CXX=g++-13
WORKDIR /app
COPY . .
RUN cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_ZENDNN=ON && \
cmake --build build -j $(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
&& cp *.py /app/full \
&& cp -r conversion /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
&& cp .devops/tools.sh /app/full/tools.sh
## Base image
FROM ubuntu:$UBUNTU_VERSION AS base
ARG BUILD_DATE=N/A
ARG APP_VERSION=N/A
ARG APP_REVISION=N/A
ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp
ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp
LABEL org.opencontainers.image.created=$BUILD_DATE \
org.opencontainers.image.version=$APP_VERSION \
org.opencontainers.image.revision=$APP_REVISION \
org.opencontainers.image.title="llama.cpp" \
org.opencontainers.image.description="LLM inference in C/C++" \
org.opencontainers.image.url=$IMAGE_URL \
org.opencontainers.image.source=$IMAGE_SOURCE
RUN apt-get update \
&& apt-get install -y libgomp1 libnuma1 curl \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
COPY --from=build /app/lib/ /app
### Full
FROM base AS full
COPY --from=build /app/full /app
WORKDIR /app
RUN apt-get update \
&& apt-get install -y \
git \
python3 \
python3-pip \
python3-wheel \
&& pip install --break-system-packages --upgrade setuptools \
&& pip install --break-system-packages -r requirements.txt \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
ENTRYPOINT ["/app/tools.sh"]
### Light, CLI only
FROM base AS light
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
WORKDIR /app
ENTRYPOINT [ "/app/llama-cli" ]
### Server, Server only
FROM base AS server
ENV LLAMA_ARG_HOST=0.0.0.0
COPY --from=build /app/full/llama-server /app
WORKDIR /app
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/app/llama-server" ]
+9 -1
View File
@@ -45,7 +45,15 @@ insert_final_newline = unset
trim_trailing_whitespace = unset
insert_final_newline = unset
[tools/ui/**]
[tools/server/webui/**]
indent_style = unset
indent_size = unset
end_of_line = unset
charset = unset
trim_trailing_whitespace = unset
insert_final_newline = unset
[tools/server/public/**]
indent_style = unset
indent_size = unset
end_of_line = unset
+4
View File
@@ -0,0 +1,4 @@
# Treat the generated single-file WebUI build as binary for diff purposes.
# Git's pack-file delta compression still works (byte-level), but this prevents
# git diff from printing the entire minified file on every change.
tools/server/public/index.html -diff
+2 -2
View File
@@ -100,8 +100,8 @@ body:
label: Relevant log output
description: >
Please copy and paste any relevant log output, including the command that you entered and any generated text.
For very long logs (thousands of lines), please upload them as files instead; the `--log-file` CLI argument can be used for this purpose.
On Linux you can alternatively redirect the console output of any command into a file by appending ` > llama.log 2>&1` to your command.
For very long logs (thousands of lines), preferably upload them as files instead.
On Linux you can redirect console output into a file by appending ` > llama.log 2>&1` to your command.
value: |
<details>
<summary>Logs</summary>
+2 -2
View File
@@ -88,8 +88,8 @@ body:
description: >
If applicable, please copy and paste any relevant log output, including any generated text.
If you are encountering problems specifically with the `llama_params_fit` module, always upload `--verbose` logs as well.
For very long logs (thousands of lines), please upload them as files instead; the `--log-file` CLI argument can be used for this purpose.
On Linux you can alternatively redirect the console output of any command into a file by appending ` > llama.log 2>&1` to your command.
For very long logs (thousands of lines), please upload them as files instead.
On Linux you can redirect console output into a file by appending ` > llama.log 2>&1` to your command.
value: |
<details>
<summary>Logs</summary>
@@ -15,6 +15,6 @@ runs:
id: setup
uses: ./.github/actions/unarchive-tar
with:
url: https://github.com/spacemit-com/toolchain/releases/download/v${{ inputs.version }}/spacemit-toolchain-linux-glibc-x86_64-v${{ inputs.version }}.tar.xz
url: https://archive.spacemit.com/toolchain/spacemit-toolchain-linux-glibc-x86_64-v${{ inputs.version }}.tar.xz
path: ${{ inputs.path }}
strip: 1
+1 -1
View File
@@ -24,4 +24,4 @@ runs:
run: |
mkdir -p ${{ inputs.path }}
cd ${{ inputs.path }}
curl --no-progress-meter -L ${{ inputs.url }} | tar -${{ inputs.type }}x --strip-components=${{ inputs.strip }}
curl --no-progress-meter ${{ inputs.url }} | tar -${{ inputs.type }}x --strip-components=${{ inputs.strip }}
@@ -96,34 +96,3 @@ runs:
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
echo "CUDA_PATH_V13_1=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
- name: Install Cuda Toolkit 13.3
if: ${{ inputs.cuda_version == '13.3' }}
shell: pwsh
run: |
mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3"
choco install unzip -y
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_crt/windows-x86_64/cuda_crt-windows-x86_64-13.3.33-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-13.3.29-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-13.3.33-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-13.3.33-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-13.5.1.27-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libnvvm/windows-x86_64/libnvvm-windows-x86_64-13.3.33-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-13.3.29-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_profiler_api/windows-x86_64/cuda_profiler_api-windows-x86_64-13.3.27-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-13.3.27-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cccl/windows-x86_64/cccl-windows-x86_64-13.3.3.3.1-archive.zip"
unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3"
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_crt-windows-x86_64-13.3.33-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_cudart-windows-x86_64-13.3.29-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_nvcc-windows-x86_64-13.3.33-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_nvrtc-windows-x86_64-13.3.33-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\libcublas-windows-x86_64-13.5.1.27-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\libnvvm-windows-x86_64-13.3.33-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_nvtx-windows-x86_64-13.3.29-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_profiler_api-windows-x86_64-13.3.27-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\visual_studio_integration-windows-x86_64-13.3.27-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cccl-windows-x86_64-13.3.3.3.1-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
echo "CUDA_PATH_V13_3=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
+3 -2
View File
@@ -73,10 +73,11 @@ android:
- changed-files:
- any-glob-to-any-file:
- examples/llama.android/**
server/ui:
server/webui:
- changed-files:
- any-glob-to-any-file:
- tools/ui/**
- tools/server/webui/**
- tools/server/public/**
server:
- changed-files:
- any-glob-to-any-file:
+3 -3
View File
@@ -22,9 +22,9 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
ubuntu-24-llguidance:
@@ -31,7 +31,7 @@ jobs:
android-ndk-snapdragon:
runs-on: ubuntu-latest
container:
image: 'ghcr.io/snapdragon-toolchain/arm64-android:v0.7'
image: 'ghcr.io/snapdragon-toolchain/arm64-android:v0.3'
defaults:
run:
shell: bash
@@ -58,45 +58,14 @@ jobs:
name: llama-cpp-android-arm64-snapdragon
path: pkg-snapdragon/llama.cpp
linux-iot-snapdragon:
runs-on: ubuntu-latest
container:
image: 'ghcr.io/snapdragon-toolchain/arm64-linux:v0.7'
defaults:
run:
shell: bash
steps:
- name: Clone
uses: actions/checkout@v6
with:
fetch-depth: 0
lfs: false
- name: Build Llama.CPP for Snapdragon Linux IoT
id: build_llama_cpp_snapdragon_linux
run: |
cp docs/backend/snapdragon/CMakeUserPresets.json .
cmake --preset arm64-linux-snapdragon-release -B build-snapdragon -DGGML_OPENCL=ON
cmake --build build-snapdragon -j $(nproc)
cmake --install build-snapdragon --prefix pkg-snapdragon/llama.cpp
- name: Upload Llama.CPP Snapdragon Linux IoT Build Artifact
if: ${{ always() && steps.build_llama_cpp_snapdragon_linux.outcome == 'success' }}
uses: actions/upload-artifact@v6
with:
name: llama-cpp-linux-arm64-snapdragon
path: pkg-snapdragon/llama.cpp
test-snapdragon-qdc:
name: Test on QDC Device (${{ matrix.device }})
needs: [android-ndk-snapdragon, linux-iot-snapdragon]
runs-on: ubuntu-24.04-arm
timeout-minutes: 90
name: Test on QDC Android Device (${{ matrix.device }})
needs: [android-ndk-snapdragon]
runs-on: ubuntu-slim
strategy:
fail-fast: false
matrix:
device: [SM8750, SM8850, QCS9075M]
device: [SM8750, SM8650, SM8850]
steps:
- name: Checkout
@@ -105,11 +74,11 @@ jobs:
- name: Download build artifact
uses: actions/download-artifact@v7
with:
name: ${{ startsWith(matrix.device, 'QCS') && 'llama-cpp-linux-arm64-snapdragon' || 'llama-cpp-android-arm64-snapdragon' }}
name: llama-cpp-android-arm64-snapdragon
path: pkg-snapdragon/llama.cpp
- name: Set up Python
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: '3.x'
cache: pip
@@ -138,8 +107,7 @@ jobs:
--test all \
--pkg-dir pkg-snapdragon/llama.cpp \
--model-url "https://huggingface.co/bartowski/Llama-3.2-1B-Instruct-GGUF/resolve/main/Llama-3.2-1B-Instruct-Q4_0.gguf" \
--device ${{ matrix.device }} \
${{ startsWith(matrix.device, 'QCS') && '--retries 2 --retry-delay 300' || '' }}
--device ${{ matrix.device }}
env:
QDC_API_KEY: ${{ secrets.QDC_API_KEY }}
+5 -66
View File
@@ -27,12 +27,12 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
default:
android:
runs-on: ubuntu-latest
steps:
@@ -58,7 +58,7 @@ jobs:
cd examples/llama.android
./gradlew build --no-daemon
ndk:
android-ndk:
runs-on: ubuntu-latest
container:
image: 'ghcr.io/snapdragon-toolchain/arm64-android:v0.3'
@@ -73,11 +73,6 @@ jobs:
fetch-depth: 0
lfs: false
- name: Dependencies
run: |
apt-get update
apt-get install -y build-essential
- name: Build
id: ndk_build
run: |
@@ -91,59 +86,3 @@ jobs:
with:
name: llama-cpp-android-arm64-cpu
path: pkg-adb/llama.cpp
arm64:
runs-on: ubuntu-latest
env:
NDK_VERSION: "29.0.14206865"
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
# note : disabled to spare some cache space (https://github.com/ggml-org/llama.cpp/pull/23789)
# for some reason, the ccache does not improve the build time in this case
# example:
# cache off: https://github.com/ggerganov/tmp2/actions/runs/26534713799/job/78160400831
# cache on: https://github.com/ggerganov/tmp2/actions/runs/26534713799/job/78224189394
#
#- name: ccache
# uses: ggml-org/ccache-action@v1.2.21
# with:
# key: android-ubuntu-arm64
# evict-old-files: 1d
# save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Set up JDK
uses: actions/setup-java@v5
with:
java-version: 17
distribution: temurin
- name: Setup Android SDK
uses: android-actions/setup-android@40fd30fb8d7440372e1316f5d1809ec01dcd3699 # v4.0.1
with:
log-accepted-android-sdk-licenses: false
- name: Install NDK
run: |
sdkmanager "ndk;${{ env.NDK_VERSION }}"
echo "ANDROID_NDK=${ANDROID_SDK_ROOT}/ndk/${{ env.NDK_VERSION }}" >> $GITHUB_ENV
- name: Build
id: cmake_build
run: |
cmake -B build \
-DCMAKE_TOOLCHAIN_FILE=${ANDROID_NDK}/build/cmake/android.toolchain.cmake \
-DANDROID_ABI=arm64-v8a \
-DANDROID_PLATFORM=android-28 \
-DLLAMA_FATAL_WARNINGS=ON \
-DGGML_BACKEND_DL=ON \
-DGGML_NATIVE=OFF \
-DGGML_CPU_ALL_VARIANTS=ON \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_BORINGSSL=ON \
-DGGML_RPC=ON
time cmake --build build --config Release -j $(nproc)
+10 -98
View File
@@ -32,12 +32,12 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
macos-latest-arm64:
macOS-latest-ios:
runs-on: macos-latest
steps:
@@ -48,80 +48,7 @@ jobs:
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-arm64
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
run: |
sysctl -a
cmake -B build \
-DCMAKE_BUILD_RPATH="@loader_path" \
-DLLAMA_FATAL_WARNINGS=ON \
-DLLAMA_BUILD_BORINGSSL=ON \
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=OFF \
-DGGML_METAL_SHADER_DEBUG=ON \
-DGGML_RPC=ON
time cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
leaks -atExit -- ./build/bin/test-thread-safety -hf ggml-org/gemma-3-270m-qat-GGUF -ngl 99 -p "$(printf 'hello %.0s' {1..128})" -n 16 -c 512 -ub 32 -np 2 -t 2 -lv 1
- name: Test
id: cmake_test
run: |
cd build
ctest -L main -E "test-llama-archs" --verbose --timeout 900
macos-latest-x64:
runs-on: macos-15-intel
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-x64
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
run: |
sysctl -a
# Metal is disabled due to intermittent failures with Github runners not having a GPU:
# https://github.com/ggml-org/llama.cpp/actions/runs/8635935781/job/23674807267#step:5:2313
cmake -B build \
-DCMAKE_BUILD_RPATH="@loader_path" \
-DLLAMA_FATAL_WARNINGS=ON \
-DLLAMA_BUILD_BORINGSSL=ON \
-DGGML_METAL=OFF \
-DGGML_RPC=ON \
-DCMAKE_OSX_DEPLOYMENT_TARGET=13.3
time cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: Test
id: cmake_test
run: |
cd build
ctest -L main --verbose --timeout 900
macos-latest-ios:
runs-on: macos-latest
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
# TODO: this likely does not do anything - if yes, remove it
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-ios
key: macOS-latest-ios
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
@@ -132,7 +59,6 @@ jobs:
cmake -B build -G Xcode \
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DLLAMA_BUILD_APP=OFF \
-DLLAMA_BUILD_COMMON=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF \
-DLLAMA_BUILD_TOOLS=OFF \
@@ -163,7 +89,6 @@ jobs:
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_BUILD_APP=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF \
-DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_TESTS=OFF \
@@ -190,7 +115,7 @@ jobs:
xcodebuild -downloadPlatform iOS
xcodebuild -project examples/llama.swiftui/llama.swiftui.xcodeproj -scheme llama.swiftui -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' FRAMEWORK_FOLDER_PATH=./build-ios build
macos-latest-tvos:
macOS-latest-tvos:
runs-on: macos-latest
steps:
@@ -198,11 +123,10 @@ jobs:
id: checkout
uses: actions/checkout@v6
# TODO: this likely does not do anything - if yes, remove it
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-tvos
key: macOS-latest-tvos
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
@@ -214,7 +138,6 @@ jobs:
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DLLAMA_BUILD_COMMON=OFF \
-DLLAMA_BUILD_APP=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF \
-DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_TESTS=OFF \
@@ -224,7 +147,7 @@ jobs:
-DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO
macos-latest-visionos:
macOS-latest-visionos:
runs-on: macos-latest
steps:
@@ -232,14 +155,6 @@ jobs:
id: checkout
uses: actions/checkout@v6
# TODO: this likely does not do anything - if yes, remove it
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-visionos
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
run: |
@@ -248,7 +163,6 @@ jobs:
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DLLAMA_BUILD_COMMON=OFF \
-DLLAMA_BUILD_APP=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF \
-DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_TESTS=OFF \
@@ -258,7 +172,7 @@ jobs:
-DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO
macos-latest-swift:
macOS-latest-swift:
runs-on: macos-latest
needs: macos-latest-ios-xcode
@@ -271,11 +185,10 @@ jobs:
id: checkout
uses: actions/checkout@v6
# TODO: this likely does not do anything - if yes, remove it
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-swift
key: macOS-latest-swift
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
@@ -293,7 +206,6 @@ jobs:
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_BUILD_APP=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF \
-DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_TESTS=OFF \
+4 -4
View File
@@ -28,7 +28,7 @@ jobs:
id: cache-sdk
with:
path: ./vulkan_sdk
key: cache-gha-vulkan-sdk-${{ env.VULKAN_SDK_VERSION }}-${{ runner.os }}
key: vulkan-sdk-${{ env.VULKAN_SDK_VERSION }}-${{ runner.os }}
- name: Setup Vulkan SDK
if: steps.cache-sdk.outputs.cache-hit != 'true'
@@ -54,7 +54,7 @@ jobs:
# id: cache-toolchain
# with:
# path: ./spacemit_toolchain
# key: cache-gha-spacemit-ime-toolchain-v${{ env.SPACEMIT_IME_TOOLCHAIN_VERSION }}-${{ runner.os }}
# key: spacemit-ime-toolchain-v${{ env.SPACEMIT_IME_TOOLCHAIN_VERSION }}-${{ runner.os }}
# - name: Setup SpacemiT Toolchain
# if: steps.cache-toolchain.outputs.cache-hit != 'true'
@@ -81,7 +81,7 @@ jobs:
id: cache-openvino
with:
path: ./openvino_toolkit
key: cache-gha-openvino-toolkit-v${{ env.OPENVINO_VERSION_FULL }}-${{ runner.os }}
key: openvino-toolkit-v${{ env.OPENVINO_VERSION_FULL }}-${{ runner.os }}
- name: Setup OpenVINO Toolkit
if: steps.cache-openvino.outputs.cache-hit != 'true'
@@ -108,7 +108,7 @@ jobs:
id: cache-rocm
with:
path: C:\Program Files\AMD\ROCm
key: cache-gha-rocm-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ runner.os }}
key: rocm-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ runner.os }}
- name: Setup ROCm
if: steps.cache-rocm.outputs.cache-hit != 'true'
+69 -71
View File
@@ -29,76 +29,74 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
# TODO: this build is disabled to save Github Actions resources (https://github.com/ggml-org/llama.cpp/pull/23705)
# in order to enable it again, we have to provision dedicated runners to run it
# openEuler-latest-cann:
# defaults:
# run:
# shell: bash -el {0}
# strategy:
# matrix:
# arch: [x86, aarch64]
# chip_type: ['910b', '310p']
# build: ['Release']
# use_acl_graph: ['on', 'off']
# exclude:
# # 310P does not support USE_ACL_GRAPH=on
# - chip_type: '310p'
# use_acl_graph: 'on'
# runs-on: ${{ matrix.arch == 'aarch64' && 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
# steps:
# - name: Checkout
# uses: actions/checkout@v6
# with:
# fetch-depth: 0
#
# - name: Free up disk space
# uses: ggml-org/free-disk-space@v1.3.1
# with:
# tool-cache: true
#
# - name: Set container image
# id: cann-image
# run: |
# image="ascendai/cann:${{ matrix.chip_type == '910b' && '8.5.0-910b-openeuler24.03-py3.11' || '8.5.0-310p-openeuler24.03-py3.11' }}"
# echo "image=${image}" >> "${GITHUB_OUTPUT}"
#
# - name: Pull container image
# run: docker pull "${{ steps.cann-image.outputs.image }}"
#
# - name: Build
# env:
# BUILD_TYPE: ${{ matrix.build }}
# SOC_TYPE: ascend${{ matrix.chip_type }}
# USE_ACL_GRAPH: ${{ matrix.use_acl_graph }}
# run: |
# HOST_UID=$(id -u)
# HOST_GID=$(id -g)
#
# docker run --rm \
# -v "${PWD}:/workspace" \
# -w /workspace \
# -e SOC_TYPE=${SOC_TYPE} \
# -e BUILD_TYPE=${BUILD_TYPE} \
# -e USE_ACL_GRAPH=${USE_ACL_GRAPH} \
# "${{ steps.cann-image.outputs.image }}" \
# bash -lc '
# set -e
# yum install -y --setopt=install_weak_deps=False --setopt=tsflags=nodocs git gcc gcc-c++ make cmake openssl-devel
# yum clean all && rm -rf /var/cache/yum
# git config --global --add safe.directory "/workspace"
# export LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/$(uname -m)-linux/devlib/:${LD_LIBRARY_PATH}
# cmake -S . -B build \
# -DCMAKE_BUILD_TYPE=${BUILD_TYPE} \
# -DGGML_CANN=on \
# -DSOC_TYPE=${SOC_TYPE} \
# -DUSE_ACL_GRAPH=${USE_ACL_GRAPH}
# cmake --build build -j $(nproc)
#
# chown -R '"${HOST_UID}"':'"${HOST_GID}"' /workspace/build
# '
openEuler-latest-cann:
defaults:
run:
shell: bash -el {0}
strategy:
matrix:
arch: [x86, aarch64]
chip_type: ['910b', '310p']
build: ['Release']
use_acl_graph: ['on', 'off']
exclude:
# 310P does not support USE_ACL_GRAPH=on
- chip_type: '310p'
use_acl_graph: 'on'
runs-on: ${{ matrix.arch == 'aarch64' && 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Free up disk space
uses: ggml-org/free-disk-space@v1.3.1
with:
tool-cache: true
- name: Set container image
id: cann-image
run: |
image="ascendai/cann:${{ matrix.chip_type == '910b' && '8.5.0-910b-openeuler24.03-py3.11' || '8.5.0-310p-openeuler24.03-py3.11' }}"
echo "image=${image}" >> "${GITHUB_OUTPUT}"
- name: Pull container image
run: docker pull "${{ steps.cann-image.outputs.image }}"
- name: Build
env:
BUILD_TYPE: ${{ matrix.build }}
SOC_TYPE: ascend${{ matrix.chip_type }}
USE_ACL_GRAPH: ${{ matrix.use_acl_graph }}
run: |
HOST_UID=$(id -u)
HOST_GID=$(id -g)
docker run --rm \
-v "${PWD}:/workspace" \
-w /workspace \
-e SOC_TYPE=${SOC_TYPE} \
-e BUILD_TYPE=${BUILD_TYPE} \
-e USE_ACL_GRAPH=${USE_ACL_GRAPH} \
"${{ steps.cann-image.outputs.image }}" \
bash -lc '
set -e
yum install -y --setopt=install_weak_deps=False --setopt=tsflags=nodocs git gcc gcc-c++ make cmake openssl-devel
yum clean all && rm -rf /var/cache/yum
git config --global --add safe.directory "/workspace"
export LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/$(uname -m)-linux/devlib/:${LD_LIBRARY_PATH}
cmake -S . -B build \
-DCMAKE_BUILD_TYPE=${BUILD_TYPE} \
-DGGML_CANN=on \
-DSOC_TYPE=${SOC_TYPE} \
-DUSE_ACL_GRAPH=${USE_ACL_GRAPH}
cmake --build build -j $(nproc)
chown -R '"${HOST_UID}"':'"${HOST_GID}"' /workspace/build
'
+9 -9
View File
@@ -5,23 +5,23 @@ on:
jobs:
linux:
runs-on: [self-hosted, Linux, CPU]
runs-on: ubuntu-slim
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y build-essential tcl cmake
- name: Build
run: |
PREFIX="$(pwd)"/inst
cmake -S . -B build \
-DCMAKE_PREFIX_PATH="$PREFIX" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_BUILD_TESTS=OFF \
-DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF \
-DLLAMA_BUILD_APP=OFF \
-DCMAKE_BUILD_TYPE=Release
cmake -S . -B build -DCMAKE_PREFIX_PATH="$PREFIX" \
-DLLAMA_OPENSSL=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF -DCMAKE_BUILD_TYPE=Release
cmake --build build --config Release
cmake --install build --prefix "$PREFIX" --config Release
-231
View File
@@ -1,231 +0,0 @@
name: CI (cpu)
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
paths: [
'.github/workflows/build-cpu.yml',
'.github/workflows/build-cmake-pkg.yml',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
'**/*.hpp',
'**/*.c',
'**/*.cpp',
'**/*.cu',
'**/*.cuh',
'**/*.swift',
'**/*.m',
'**/*.metal',
'**/*.comp',
'**/*.glsl',
'**/*.wgsl'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/build-cpu.yml',
'.github/workflows/build-cmake-pkg.yml',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
'**/*.hpp',
'**/*.c',
'**/*.cpp',
'**/*.cu',
'**/*.cuh',
'**/*.swift',
'**/*.m',
'**/*.metal',
'**/*.comp',
'**/*.glsl',
'**/*.wgsl'
]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
jobs:
build-cmake-pkg:
uses: ./.github/workflows/build-cmake-pkg.yml
ubuntu:
strategy:
matrix:
include:
- build: 'x64'
os: ubuntu-22.04
- build: 'arm64'
os: ubuntu-24.04-arm
runs-on: ${{ matrix.os }}
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: cpu-${{ matrix.os }}
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build Dependencies
id: build_depends
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
python3 python3-pip python3-dev python3-wheel \
libjpeg-dev build-essential libssl-dev \
git-lfs
- name: Toolchain workaround (GCC 14)
if: ${{ contains(matrix.os, 'ubuntu-24.04') }}
run: |
sudo apt-get install -y gcc-14 g++-14
echo "CC=gcc-14" >> "$GITHUB_ENV"
echo "CXX=g++-14" >> "$GITHUB_ENV"
- name: Python Dependencies
id: python_depends
run: |
export PIP_BREAK_SYSTEM_PACKAGES="1"
python3 -m pip install --upgrade pip setuptools
pip3 install ./gguf-py
- name: Build
id: cmake_build
run: |
cmake -B build \
-DLLAMA_FATAL_WARNINGS=ON \
-DGGML_RPC=ON
time cmake --build build --config Release -j $(nproc)
- name: Test
id: cmake_test
run: |
cd build
ctest -L main --verbose --timeout 900
- name: Test llama2c conversion
id: llama2c_test
run: |
cd build
echo "Fetch tokenizer"
wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/tok512.bin
echo "Fetch llama2c model"
wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
windows:
runs-on: windows-2025
env:
OPENBLAS_VERSION: 0.3.23
SDE_VERSION: 9.33.0-2024-01-07
VULKAN_VERSION: 1.4.313.2
strategy:
matrix:
include:
- build: 'x64-cpu-static'
arch: 'x64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DBUILD_SHARED_LIBS=OFF'
- build: 'x64-openblas'
arch: 'x64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_OPENMP=OFF -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS -DBLAS_INCLUDE_DIRS="$env:RUNNER_TEMP/openblas/include" -DBLAS_LIBRARIES="$env:RUNNER_TEMP/openblas/lib/openblas.lib"'
- build: 'x64-vulkan'
arch: 'x64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_VULKAN=ON'
- build: 'arm64'
arch: 'arm64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON'
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: cpu-windows-2025-${{ matrix.build }}
variant: ccache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Download OpenBLAS
id: get_openblas
if: ${{ matrix.build == 'x64-openblas' }}
run: |
curl.exe -o $env:RUNNER_TEMP/openblas.zip -L "https://github.com/xianyi/OpenBLAS/releases/download/v${env:OPENBLAS_VERSION}/OpenBLAS-${env:OPENBLAS_VERSION}-x64.zip"
curl.exe -o $env:RUNNER_TEMP/OpenBLAS.LICENSE.txt -L "https://github.com/xianyi/OpenBLAS/raw/v${env:OPENBLAS_VERSION}/LICENSE"
mkdir $env:RUNNER_TEMP/openblas
tar.exe -xvf $env:RUNNER_TEMP/openblas.zip -C $env:RUNNER_TEMP/openblas
$vcdir = $(vswhere -latest -products * -requires Microsoft.VisualStudio.Component.VC.Tools.x86.x64 -property installationPath)
$msvc = $(join-path $vcdir $('VC\Tools\MSVC\'+$(gc -raw $(join-path $vcdir 'VC\Auxiliary\Build\Microsoft.VCToolsVersion.default.txt')).Trim()))
$lib = $(join-path $msvc 'bin\Hostx64\x64\lib.exe')
& $lib /machine:x64 "/def:${env:RUNNER_TEMP}/openblas/lib/libopenblas.def" "/out:${env:RUNNER_TEMP}/openblas/lib/openblas.lib" /name:openblas.dll
- name: Install Vulkan SDK
id: get_vulkan
if: ${{ matrix.build == 'x64-vulkan' }}
run: |
curl.exe -o $env:RUNNER_TEMP/VulkanSDK-Installer.exe -L "https://sdk.lunarg.com/sdk/download/${env:VULKAN_VERSION}/windows/vulkansdk-windows-X64-${env:VULKAN_VERSION}.exe"
& "$env:RUNNER_TEMP\VulkanSDK-Installer.exe" --accept-licenses --default-answer --confirm-command install
Add-Content $env:GITHUB_ENV "VULKAN_SDK=C:\VulkanSDK\${env:VULKAN_VERSION}"
Add-Content $env:GITHUB_PATH "C:\VulkanSDK\${env:VULKAN_VERSION}\bin"
- name: Install Ninja
id: install_ninja
run: |
choco install ninja
- name: Build
id: cmake_build
run: |
cmake -S . -B build ${{ matrix.defines }} `
-DLLAMA_BUILD_BORINGSSL=ON
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS}
- name: Add libopenblas.dll
id: add_libopenblas_dll
if: ${{ matrix.build == 'x64-openblas' }}
run: |
cp $env:RUNNER_TEMP/openblas/bin/libopenblas.dll ./build/bin/Release/openblas.dll
cp $env:RUNNER_TEMP/OpenBLAS.LICENSE.txt ./build/bin/Release/OpenBLAS-${env:OPENBLAS_VERSION}.txt
- name: Test
id: cmake_test
if: ${{ matrix.arch == 'x64' }}
run: |
cd build
ctest -L main -C Release --verbose --timeout 900
# TODO: disabled for now, consider adding tests for all CPU variants instead
# - name: Test (Intel SDE)
# id: cmake_test_sde
# if: ${{ matrix.build == 'avx512-x64' && env.HAS_AVX512F == '0' }} # use Intel SDE for AVX-512 emulation
# run: |
# curl.exe -o $env:RUNNER_TEMP/sde.tar.xz -L "https://downloadmirror.intel.com/813591/sde-external-${env:SDE_VERSION}-win.tar.xz"
# # for some weird reason windows tar doesn't like sde tar.xz
# 7z x "-o${env:RUNNER_TEMP}" $env:RUNNER_TEMP/sde.tar.xz
# 7z x "-o${env:RUNNER_TEMP}" $env:RUNNER_TEMP/sde.tar
# $sde = $(join-path $env:RUNNER_TEMP sde-external-${env:SDE_VERSION}-win/sde.exe)
# cd build
# $env:LLAMA_SKIP_TESTS_SLOW_ON_EMULATOR = 1
# & $sde -future -- ctest -L main -C Release --verbose --timeout 900
+4 -5
View File
@@ -277,7 +277,7 @@ jobs:
env:
# Make sure this is in sync with build-cache.yml
SPACEMIT_IME_TOOLCHAIN_VERSION: "1.2.4"
SPACEMIT_IME_TOOLCHAIN_VERSION: "1.1.2"
steps:
- uses: actions/checkout@v6
@@ -287,7 +287,7 @@ jobs:
# id: cache-toolchain
# with:
# path: ./spacemit_toolchain
# key: cache-gha-spacemit-ime-toolchain-v${{ env.SPACEMIT_IME_TOOLCHAIN_VERSION }}-${{ runner.os }}
# key: spacemit-ime-toolchain-v${{ env.SPACEMIT_IME_TOOLCHAIN_VERSION }}-${{ runner.os }}
- name: Setup SpacemiT Toolchain
#if: steps.cache-toolchain.outputs.cache-hit != 'true'
@@ -301,17 +301,16 @@ jobs:
export RISCV_ROOT_PATH=${PWD}/spacemit_toolchain
cmake -B build -DLLAMA_OPENSSL=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DGGML_CPU_REPACK=OFF \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DGGML_CPU_RISCV64_SPACEMIT=ON \
-DGGML_RVV=ON \
-DGGML_RV_ZVFH=ON \
-DGGML_RV_ZFH=ON \
-DGGML_RV_ZICBOP=ON \
-DGGML_RV_ZIHINTPAUSE=ON \
-DGGML_RV_ZBA=ON \
-DRISCV64_SPACEMIT_IME_SPEC=RISCV64_SPACEMIT_IME1 \
-DCMAKE_TOOLCHAIN_FILE=${PWD}/cmake/riscv64-spacemit-linux-gnu-gcc.cmake
cmake --build build --config Release -j $(nproc)
-134
View File
@@ -1,134 +0,0 @@
name: CI (CUDA, ubuntu)
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
paths: [
'.github/workflows/build-cuda-ubuntu.yml',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
'**/*.hpp',
'**/*.c',
'**/*.cpp',
'**/*.cu',
'**/*.cuh'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/build-cuda-ubuntu.yml',
'ggml/src/ggml-cuda/**'
]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
jobs:
cuda:
runs-on: ubuntu-24.04
container: nvidia/cuda:12.6.2-devel-ubuntu24.04
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Install dependencies
env:
DEBIAN_FRONTEND: noninteractive
run: |
apt update
apt install -y cmake build-essential ninja-build libgomp1 git libssl-dev
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: cuda-ubuntu-24.04-cuda
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build with CMake
# TODO: Remove GGML_CUDA_CUB_3DOT2 flag once CCCL 3.2 is bundled within CTK and that CTK version is used in this project
run: |
cmake -S . -B build -G Ninja \
-DLLAMA_FATAL_WARNINGS=ON \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_CUDA_ARCHITECTURES=89-real \
-DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined \
-DGGML_NATIVE=OFF \
-DGGML_CUDA=ON \
-DGGML_CUDA_CUB_3DOT2=ON
cmake --build build
hip:
runs-on: ubuntu-22.04
container: rocm/dev-ubuntu-22.04:6.1.2
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install -y build-essential git cmake rocblas-dev hipblas-dev libssl-dev rocwmma-dev
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: cuda-ubuntu-22.04-hip
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build with native CMake HIP support
id: cmake_build
run: |
cmake -B build -S . \
-DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" \
-DGGML_HIP_ROCWMMA_FATTN=ON \
-DGPU_TARGETS="gfx1030" \
-DGGML_HIP=ON
cmake --build build --config Release -j $(nproc)
musa:
runs-on: ubuntu-22.04
container: mthreads/musa:rc4.3.0-devel-ubuntu22.04-amd64
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Dependencies
id: depends
run: |
apt-get update
apt-get install -y build-essential git cmake libssl-dev
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: cuda-ubuntu-22.04-musa
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build with native CMake MUSA support
id: cmake_build
run: |
cmake -B build -S . \
-DGGML_MUSA=ON
time cmake --build build --config Release -j $(nproc)
-146
View File
@@ -1,146 +0,0 @@
name: CI (CUDA, windows)
# TODO: this workflow is only triggered manually because it is very heavy on the CI
# when we provision dedicated windows runners, we can enable it for pushes too
# note: running this workflow manually will populate the ccache for the release builds
# this can be used before merging a PR to speed up the release workflow
on:
workflow_dispatch: # allows manual triggering
# note: this will run in queue with the release workflow
concurrency:
group: release
queue: max
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
jobs:
cuda:
runs-on: windows-2022
strategy:
matrix:
cuda: ['12.4', '13.3']
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: release-windows-2022-x64-cuda-${{ matrix.cuda }}
append-timestamp: false # note: use this only with non-concurrent jobs!
- name: Install Cuda Toolkit
uses: ./.github/actions/windows-setup-cuda
with:
cuda_version: ${{ matrix.cuda }}
- name: Install Ninja
id: install_ninja
run: |
choco install ninja
- name: Build
id: cmake_build
shell: cmd
# TODO: Remove GGML_CUDA_CUB_3DOT2 flag once CCCL 3.2 is bundled within CTK and that CTK version is used in this project
run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64
cmake -S . -B build -G "Ninja Multi-Config" ^
-DLLAMA_BUILD_SERVER=ON ^
-DLLAMA_BUILD_BORINGSSL=ON ^
-DGGML_NATIVE=OFF ^
-DGGML_BACKEND_DL=ON ^
-DGGML_CPU_ALL_VARIANTS=ON ^
-DGGML_CUDA=ON ^
-DGGML_RPC=ON ^
-DGGML_CUDA_CUB_3DOT2=ON
set /A NINJA_JOBS=%NUMBER_OF_PROCESSORS%-1
cmake --build build --config Release -j %NINJA_JOBS% -t ggml
cmake --build build --config Release
hip:
runs-on: windows-2022
env:
# Make sure this is in sync with build-cache.yml
HIPSDK_INSTALLER_VERSION: "26.Q1"
strategy:
matrix:
include:
# sync with release.yml
- name: "radeon"
gpu_targets: "gfx1150;gfx1151;gfx1200;gfx1201;gfx1100;gfx1101;gfx1102;gfx1030;gfx1031;gfx1032"
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Grab rocWMMA package
id: grab_rocwmma
run: |
curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.2.1/pool/main/r/rocwmma-dev/rocwmma-dev_2.2.0.70201-81~24.04_amd64.deb"
7z x rocwmma.deb
7z x data.tar
- name: Use ROCm Installation Cache
uses: actions/cache@v5
id: cache-rocm
with:
path: C:\Program Files\AMD\ROCm
key: cache-gha-rocm-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ runner.os }}
- name: Setup ROCm
if: steps.cache-rocm.outputs.cache-hit != 'true'
uses: ./.github/actions/windows-setup-rocm
with:
version: ${{ env.HIPSDK_INSTALLER_VERSION }}
- name: Verify ROCm
id: verify
run: |
# Find and test ROCm installation
$clangPath = Get-ChildItem 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | Select-Object -First 1
if (-not $clangPath) {
Write-Error "ROCm installation not found"
exit 1
}
& $clangPath.FullName --version
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
# TODO: this build does not match the build in release.yml, so we use a different cache key
# ideally, the builds should match, similar to the CUDA build above so that we would be able
# to populate the ccache for the release with manual runs of this workflow
#key: release-windows-2022-x64-hip-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ matrix.name }}
key: cuda-windows-2022-x64-hip-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ matrix.name }}
append-timestamp: false # note: use this only with non-concurrent jobs!
- name: Build
id: cmake_build
run: |
$env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
$env:CMAKE_PREFIX_PATH="${env:HIP_PATH}"
cmake -G "Unix Makefiles" -B build -S . `
-DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
-DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
-DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.2.1/include/" `
-DCMAKE_BUILD_TYPE=Release `
-DLLAMA_BUILD_BORINGSSL=ON `
-DROCM_DIR="${env:HIP_PATH}" `
-DGGML_HIP=ON `
-DGGML_HIP_ROCWMMA_FATTN=ON `
-DGPU_TARGETS="gfx1100" `
-DGGML_RPC=ON
cmake --build build -j ${env:NUMBER_OF_PROCESSORS}
-150
View File
@@ -1,150 +0,0 @@
name: CI (ibm)
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
paths: [
'.github/workflows/build-ibm.yml',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
'**/*.hpp',
'**/*.c',
'**/*.cpp'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/build-ibm.yml',
'ggml/src/ggml-cpu/**'
]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
jobs:
ubuntu-24-s390x:
runs-on: ubuntu-24.04-s390x
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Build Dependencies
id: build_depends
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
python3 python3-pip python3-dev python3-wheel \
libjpeg-dev build-essential libssl-dev \
git-lfs
- name: Toolchain workaround (GCC 14)
run: |
sudo apt-get install -y gcc-14 g++-14
echo "CC=gcc-14" >> "$GITHUB_ENV"
echo "CXX=g++-14" >> "$GITHUB_ENV"
- name: Python Dependencies
id: python_depends
run: |
export PIP_BREAK_SYSTEM_PACKAGES="1"
python3 -m pip install --upgrade pip setuptools
pip3 install ./gguf-py
- name: Swap Endianness
id: endianness
run: |
for f in models/*.gguf; do
echo YES | python3 gguf-py/gguf/scripts/gguf_convert_endian.py $f big
done
- name: Build
id: cmake_build
run: |
cmake -B build \
-DLLAMA_FATAL_WARNINGS=ON \
-DGGML_RPC=ON
time cmake --build build --config Release -j $(nproc)
- name: Test
id: cmake_test
run: |
cd build
ctest -L main --verbose --timeout 900
- name: Test llama2c (s390x)
id: llama2c_test_s390x
run: |
cd build
echo "Fetch llama2c big-endian model"
wget https://huggingface.co/ggml-org/models/resolve/main/tinyllamas/stories260K-be.gguf
./bin/llama-completion -m stories260K-be.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
ubuntu-24-ppc64le:
runs-on: ubuntu-24.04-ppc64le
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Build Dependencies
id: build_depends
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
python3 python3-pip python3-dev python3-wheel \
libjpeg-dev build-essential libssl-dev \
git-lfs
- name: Toolchain workaround (GCC 14)
run: |
sudo apt-get install -y gcc-14 g++-14
echo "CC=gcc-14" >> "$GITHUB_ENV"
echo "CXX=g++-14" >> "$GITHUB_ENV"
- name: Python Dependencies
id: python_depends
run: |
export PIP_BREAK_SYSTEM_PACKAGES="1"
python3 -m pip install --upgrade pip setuptools
pip3 install ./gguf-py
- name: Build
id: cmake_build
run: |
cmake -B build \
-DLLAMA_FATAL_WARNINGS=ON \
-DGGML_RPC=ON
time cmake --build build --config Release -j $(nproc)
- name: Test
id: cmake_test
run: |
cd build
ctest -L main --verbose --timeout 900
- name: Test llama2c conversion
id: llama2c_test
run: |
cd build
echo "Fetch tokenizer"
wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/tok512.bin
echo "Fetch llama2c model"
wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
+4 -4
View File
@@ -15,9 +15,9 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
windows-msys2:
@@ -37,7 +37,7 @@ jobs:
#- name: ccache
# uses: ggml-org/ccache-action@v1.2.16
# with:
# key: msys-windows-2025-x64
# key: windows-msys2
# variant: ccache
# evict-old-files: 1d
# save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-82
View File
@@ -1,82 +0,0 @@
name: CI (opencl)
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
paths: [
'.github/workflows/build-opencl.yml',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
'**/*.hpp',
'**/*.c',
'**/*.cpp',
'**/*.cl'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/build-opencl.yml',
'ggml/src/ggml-opencl/**'
]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
jobs:
windows-2025-opencl-adreno:
runs-on: windows-2025
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: opencl-windows-2025-x64
variant: ccache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Install Ninja
id: install_ninja
run: |
choco install ninja
- name: Install OpenCL Headers and Libs
id: install_opencl
run: |
git clone https://github.com/KhronosGroup/OpenCL-Headers
cd OpenCL-Headers
cmake -B build `
-DBUILD_TESTING=OFF `
-DOPENCL_HEADERS_BUILD_TESTING=OFF `
-DOPENCL_HEADERS_BUILD_CXX_TESTS=OFF `
-DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
cmake --build build --target install
git clone https://github.com/KhronosGroup/OpenCL-ICD-Loader
cd OpenCL-ICD-Loader
cmake -B build-arm64-release `
-A arm64 `
-DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" `
-DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
cmake --build build-arm64-release --target install --config release
- name: Build
id: cmake_build
run: |
cmake -S . -B build -G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" -DGGML_OPENCL=ON -DGGML_OPENCL_USE_ADRENO_KERNELS=ON -DLLAMA_BUILD_BORINGSSL=ON
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS}
+5 -5
View File
@@ -29,9 +29,9 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
ubuntu-24-openvino:
@@ -67,7 +67,7 @@ jobs:
if: runner.environment == 'github-hosted'
uses: ggml-org/ccache-action@v1.2.21
with:
key: openvino-ubuntu-24.04-${{ matrix.variant }}-no-preset-v1
key: ubuntu-24-openvino-${{ matrix.variant }}-no-preset-v1
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
@@ -84,7 +84,7 @@ jobs:
id: cache-openvino
with:
path: ./openvino_toolkit
key: cache-gha-openvino-toolkit-v${{ env.OPENVINO_VERSION_FULL }}-${{ runner.os }}
key: openvino-toolkit-v${{ env.OPENVINO_VERSION_FULL }}-${{ runner.os }}
- name: Setup OpenVINO Toolkit
if: steps.cache-openvino.outputs.cache-hit != 'true'
+9 -83
View File
@@ -29,84 +29,11 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
ubuntu-cpu-riscv64-native:
runs-on: ubuntu-24.04-riscv
steps:
- name: Install dependencies
run: |
# Install necessary packages
sudo apt-get update
sudo apt-get install -y libssl-dev
# Set gcc-14 and g++-14 as the default compilers
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100
git lfs install
- name: Check environment
run: |
uname -a
gcc --version
g++ --version
ldd --version
cmake --version
rustc --version
env
echo "nproc=$(nproc)"
- name: Clone
id: checkout
uses: actions/checkout@v6
# note: sparing some ccache since these jobs run on dedicated runners that are not part of the organitzation
#- name: ccache
# uses: ggml-org/ccache-action@afde29e5b5422e5da23cb1f639e8baecadeadfc3 # https://github.com/ggml-org/ccache-action/pull/1
# with:
# key: riscv-ubuntu-native
# evict-old-files: 1d
# save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
run: |
cmake -B build \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=ON \
-DCMAKE_C_COMPILER_LAUNCHER=ccache \
-DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DGGML_RPC=ON \
-DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14
time cmake --build build --config Release -j $(nproc)
- name: Test
id: cmake_test
run: |
cd build
ctest -L main --verbose --timeout 900
- name: Test llama2c conversion
id: llama2c_test
run: |
cd build
echo "Fetch tokenizer"
wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/tok512.bin
echo "Fetch llama2c model"
wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
ubuntu-riscv64-native-sanitizer:
runs-on: ubuntu-24.04-riscv
@@ -135,13 +62,12 @@ jobs:
id: checkout
uses: actions/checkout@v6
# note: sparing some ccache since these jobs run on dedicated runners that are not part of the organitzation
#- name: ccache
# uses: ggml-org/ccache-action@afde29e5b5422e5da23cb1f639e8baecadeadfc3 # https://github.com/ggml-org/ccache-action/pull/1
# with:
# key: riscv-ubuntu-native-sanitizer-${{ matrix.sanitizer }}-${{ matrix.build_type }}
# evict-old-files: 1d
# save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: ccache
uses: ggml-org/ccache-action@afde29e5b5422e5da23cb1f639e8baecadeadfc3 # https://github.com/ggml-org/ccache-action/pull/1
with:
key: ubuntu-riscv64-native-sanitizer-${{ matrix.sanitizer }}-${{ matrix.build_type }}
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
-66
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@@ -1,66 +0,0 @@
name: CI (rpc)
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
paths: [
'.github/workflows/build-rpc.yml',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
'**/*.hpp',
'**/*.c',
'**/*.cpp'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/build-rpc.yml',
'ggml/src/ggml-rpc/**'
]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
jobs:
ubuntu-latest-rpc:
runs-on: ubuntu-latest
continue-on-error: true
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install build-essential libssl-dev ninja-build
- name: Build
id: cmake_build
run: |
cmake -B build \
-G "Ninja" \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_RPC=ON
time cmake --build build --config Release -j $(nproc)
- name: Test
id: cmake_test
run: |
cd build
ctest -L main --verbose
+26 -25
View File
@@ -22,65 +22,66 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
ctest:
runs-on: [self-hosted, X64, CPU, Linux]
ubuntu-latest-sanitizer:
runs-on: ubuntu-latest
continue-on-error: true
strategy:
matrix:
sanitizer: [ADDRESS, THREAD, UNDEFINED]
build_type: [Debug]
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
# with UNDEFINED sanitizer, we have to build in Debug to avoid GCC 13 false-positive warnings
- name: Build (undefined)
id: cmake_build_undefined
if: ${{ matrix.sanitizer == 'UNDEFINED' }}
run: |
cmake -B build \
-DCMAKE_BUILD_TYPE=Debug \
-DLLAMA_FATAL_WARNINGS=ON \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
-DGGML_SANITIZE_${{ matrix.sanitizer }}=ON
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: ubuntu-latest-sanitizer-${{ matrix.sanitizer }}
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
cmake --build build --config Debug -j $(nproc)
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install build-essential libssl-dev
- name: Build
id: cmake_build
if: ${{ matrix.sanitizer == 'ADDRESS' }}
if: ${{ matrix.sanitizer != 'THREAD' }}
run: |
cmake -B build \
-DCMAKE_BUILD_TYPE=RelWithDebInfo \
-DLLAMA_FATAL_WARNINGS=ON \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
-DGGML_SANITIZE_${{ matrix.sanitizer }}=ON
-DGGML_SANITIZE_${{ matrix.sanitizer }}=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }}
cmake --build build --config RelWithDebInfo -j $(nproc)
cmake --build build --config ${{ matrix.build_type }} -j $(nproc)
- name: Build (no OpenMP)
id: cmake_build_no_openmp
if: ${{ matrix.sanitizer == 'THREAD' }}
run: |
cmake -B build \
-DCMAKE_BUILD_TYPE=RelWithDebInfo \
-DLLAMA_FATAL_WARNINGS=ON \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
-DGGML_SANITIZE_${{ matrix.sanitizer }}=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DGGML_OPENMP=OFF
cmake --build build --config RelWithDebInfo -j $(nproc)
cmake --build build --config ${{ matrix.build_type }} -j $(nproc)
- name: Test
id: cmake_test
# skip run in Debug - very slow
if: ${{ matrix.sanitizer != 'UNDEFINED' }}
run: |
cd build
ctest -L main -E tokenizer --verbose --timeout 900
ctest -L main --verbose --timeout 900
+48 -153
View File
@@ -50,12 +50,12 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
gpu-cuda:
ggml-ci-nvidia-cuda:
runs-on: [self-hosted, Linux, NVIDIA]
steps:
@@ -67,9 +67,9 @@ jobs:
id: ggml-ci
run: |
nvidia-smi
GG_BUILD_CUDA=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
GG_BUILD_CUDA=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
gpu-vulkan-nvidia-cm:
ggml-ci-nvidia-vulkan-cm:
runs-on: [self-hosted, Linux, NVIDIA]
steps:
@@ -81,9 +81,9 @@ jobs:
id: ggml-ci
run: |
vulkaninfo --summary
GG_BUILD_VULKAN=1 GGML_VK_DISABLE_COOPMAT2=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
GG_BUILD_VULKAN=1 GGML_VK_DISABLE_COOPMAT2=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
gpu-vulkan-nvidia-cm2:
ggml-ci-nvidia-vulkan-cm2:
runs-on: [self-hosted, Linux, NVIDIA, COOPMAT2]
steps:
@@ -95,39 +95,40 @@ jobs:
id: ggml-ci
run: |
vulkaninfo --summary
GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
gpu-webgpu-nvidia:
runs-on: [self-hosted, Linux, NVIDIA, X64]
# TODO: investigate slight precision issues in some operations for test-backend-ops on the WebGPU backend.
#ggml-ci-nvidia-webgpu:
# runs-on: [self-hosted, Linux, NVIDIA]
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
# steps:
# - name: Clone
# id: checkout
# uses: actions/checkout@v6
- name: Dawn Dependency
id: dawn-depends
run: |
DAWN_VERSION="v20260317.182325"
DAWN_OWNER="google"
DAWN_REPO="dawn"
DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
curl -L -o artifact.tar.gz \
"https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
mkdir dawn
tar -xvf artifact.tar.gz -C dawn --strip-components=1
# - name: Dawn Dependency
# id: dawn-depends
# run: |
# DAWN_VERSION="v20260317.182325"
# DAWN_OWNER="google"
# DAWN_REPO="dawn"
# DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
# echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
# curl -L -o artifact.tar.gz \
# "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
# mkdir dawn
# tar -xvf artifact.tar.gz -C dawn --strip-components=1
- name: Test
id: ggml-ci
run: |
GG_BUILD_WEBGPU=1 \
GG_BUILD_WEBGPU_DAWN_PREFIX="$GITHUB_WORKSPACE/dawn" \
GG_BUILD_WEBGPU_DAWN_DIR="$GITHUB_WORKSPACE/dawn/lib64/cmake/Dawn" \
bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
# - name: Test
# id: ggml-ci
# run: |
# GG_BUILD_WEBGPU=1 \
# GG_BUILD_WEBGPU_DAWN_PREFIX="$GITHUB_WORKSPACE/dawn" \
# GG_BUILD_WEBGPU_DAWN_DIR="$GITHUB_WORKSPACE/dawn/lib64/cmake/Dawn" \
# bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
# TODO: provision AMX-compatible machine
#cpu-amx:
#ggml-ci-cpu-amx:
# runs-on: [self-hosted, Linux, CPU, AMX]
# steps:
@@ -138,10 +139,10 @@ jobs:
# - name: Test
# id: ggml-ci
# run: |
# bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
# bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
# TODO: provision AMD GPU machine
# amd-vulkan:
# ggml-ci-amd-vulkan:
# runs-on: [self-hosted, Linux, AMD]
# steps:
@@ -153,10 +154,10 @@ jobs:
# id: ggml-ci
# run: |
# vulkaninfo --summary
# GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
# GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
# TODO: provision AMD GPU machine
# amd-rocm:
# ggml-ci-amd-rocm:
# runs-on: [self-hosted, Linux, AMD]
# steps:
@@ -168,9 +169,9 @@ jobs:
# id: ggml-ci
# run: |
# amd-smi static
# GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS="gfx1101" bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
# GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS="gfx1101" bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
gpu-metal:
ggml-ci-mac-metal:
runs-on: [self-hosted, macOS, ARM64]
steps:
@@ -183,7 +184,7 @@ jobs:
run: |
GG_BUILD_METAL=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
gpu-webgpu-apple:
ggml-ci-mac-webgpu:
runs-on: [self-hosted, macOS, ARM64]
steps:
@@ -210,7 +211,7 @@ jobs:
GG_BUILD_WEBGPU=1 GG_BUILD_WEBGPU_DAWN_PREFIX="$GITHUB_WORKSPACE/dawn" \
bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
gpu-vulkan:
ggml-ci-mac-vulkan:
runs-on: [self-hosted, macOS, ARM64]
steps:
@@ -224,7 +225,7 @@ jobs:
vulkaninfo --summary
GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
gpu-vulkan-intel-linux:
ggml-ci-linux-intel-vulkan:
runs-on: [self-hosted, Linux, Intel]
steps:
@@ -240,7 +241,7 @@ jobs:
vulkaninfo --summary
GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
gpu-vulkan-intel-windows:
ggml-ci-win-intel-vulkan:
runs-on: [self-hosted, Windows, X64, Intel]
steps:
@@ -261,7 +262,7 @@ jobs:
# a valid python environment for testing
LLAMA_FATAL_WARNINGS=OFF GG_BUILD_NINJA=1 GG_BUILD_VULKAN=1 GG_BUILD_LOW_PERF=1 ./ci/run.sh ./results/llama.cpp ./mnt/llama.cpp
cpu-openvino-low-perf:
ggml-ci-intel-openvino-gpu-low-perf:
runs-on: [self-hosted, Linux, Intel, OpenVINO]
concurrency:
@@ -295,110 +296,4 @@ jobs:
id: ggml-ci
run: |
source ./openvino_toolkit/setupvars.sh
GG_BUILD_OPENVINO=1 GGML_OPENVINO_DEVICE=GPU GG_BUILD_LOW_PERF=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
cpu-any-low-perf:
runs-on: [self-hosted, CPU]
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Test
id: ggml-ci
run: |
LLAMA_ARG_THREADS=$(nproc) GG_BUILD_LOW_PERF=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
cpu-any-high-perf:
runs-on: [self-hosted, CPU]
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Test
id: ggml-ci
run: |
LLAMA_ARG_THREADS=$(nproc) GG_BUILD_HIGH_PERF=1 GG_BUILD_NO_SVE=1 GG_BUILD_NO_BF16=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
cpu-arm64-graviton4:
runs-on: ah-ubuntu_22_04-c8g_8x
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Dependencies
id: depends
run: |
set -euxo pipefail
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive NEEDRESTART_MODE=a \
apt-get install -y \
build-essential \
python3-venv \
gpg \
wget \
time \
git-lfs
git lfs install
# install the latest cmake
sudo install -d /usr/share/keyrings
wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc \
| gpg --dearmor \
| sudo tee /usr/share/keyrings/kitware-archive-keyring.gpg >/dev/null
echo 'deb [signed-by=/usr/share/keyrings/kitware-archive-keyring.gpg] https://apt.kitware.com/ubuntu/ jammy main' \
| sudo tee /etc/apt/sources.list.d/kitware.list
sudo apt-get update
sudo apt-get install -y cmake
- name: Test
id: ggml-ci
run: |
LLAMA_ARG_THREADS=$(nproc) GG_BUILD_NO_BF16=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
cpu-arm64-graviton4-kleidiai:
runs-on: ah-ubuntu_22_04-c8g_8x
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Dependencies
id: depends
run: |
set -euxo pipefail
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive NEEDRESTART_MODE=a \
apt-get install -y \
build-essential \
python3-venv \
gpg \
wget \
time \
git-lfs
git lfs install
# install the latest cmake
sudo install -d /usr/share/keyrings
wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc \
| gpg --dearmor \
| sudo tee /usr/share/keyrings/kitware-archive-keyring.gpg >/dev/null
echo 'deb [signed-by=/usr/share/keyrings/kitware-archive-keyring.gpg] https://apt.kitware.com/ubuntu/ jammy main' \
| sudo tee /etc/apt/sources.list.d/kitware.list
sudo apt-get update
sudo apt-get install -y cmake
- name: Test
id: ggml-ci
run: |
GG_BUILD_KLEIDIAI=1 \
GG_BUILD_EXTRA_TESTS_0=1 \
bash ./ci/run.sh ./tmp/results ./tmp/mnt
GG_BUILD_OPENVINO=1 GGML_OPENVINO_DEVICE=GPU GG_BUILD_LOW_PERF=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
+107 -127
View File
@@ -29,134 +29,114 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
# TODO: this build is disabled to save Github Actions resources (https://github.com/ggml-org/llama.cpp/pull/23705)
# in order to enable it again, we have to provision dedicated runners to run it
# ubuntu-24-sycl:
# strategy:
# matrix:
# build: [fp32]
# include:
# - build: fp32
# fp16: OFF
#
# runs-on: ubuntu-24.04
#
# env:
# ONEAPI_ROOT: /opt/intel/oneapi/
# ONEAPI_INSTALLER_VERSION: "2025.3.3"
# LEVEL_ZERO_VERSION: "1.28.2"
# LEVEL_ZERO_UBUNTU_VERSION: "u24.04"
#
# continue-on-error: true
#
# steps:
# - uses: actions/checkout@v6
#
# - name: Use oneAPI Installation Cache
# uses: actions/cache@v5
# id: cache-sycl
# with:
# path: ${{ env.ONEAPI_ROOT }}
# key: cache-gha-oneAPI-${{ env.ONEAPI_INSTALLER_VERSION }}-${{ runner.os }}
#
# - name: Download & Install oneAPI
# shell: bash
# if: steps.cache-sycl.outputs.cache-hit != 'true'
# run: |
# cd /tmp
# wget https://registrationcenter-download.intel.com/akdlm/IRC_NAS/56f7923a-adb8-43f3-8b02-2b60fcac8cab/intel-deep-learning-essentials-2025.3.3.16_offline.sh -O intel-deep-learning-essentials_offline.sh
# sudo bash intel-deep-learning-essentials_offline.sh -s -a --silent --eula accept
#
# - name: Install Level Zero SDK
# shell: bash
# run: |
# cd /tmp
# wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero.deb
# wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero-devel_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero-devel.deb
# sudo apt-get install -y ./level-zero.deb ./level-zero-devel.deb
#
# - name: Clone
# id: checkout
# uses: actions/checkout@v6
#
# - name: ccache
# uses: ggml-org/ccache-action@v1.2.21
# with:
# key: sycl-ubuntu-24-${{ matrix.build }}
# evict-old-files: 1d
# save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
#
# - name: Build
# id: cmake_build
# run: |
# source /opt/intel/oneapi/setvars.sh
# cmake -B build \
# -G "Ninja" \
# -DCMAKE_BUILD_TYPE=Release \
# -DGGML_SYCL=ON \
# -DCMAKE_C_COMPILER=icx \
# -DCMAKE_CXX_COMPILER=icpx \
# -DLLAMA_OPENSSL=OFF \
# -DGGML_NATIVE=OFF \
# -DGGML_SYCL_F16=${{ matrix.fp16 }}
# time cmake --build build --config Release -j $(nproc)
ubuntu-24-sycl:
strategy:
matrix:
build: [fp32, fp16]
include:
- build: fp32
fp16: OFF
- build: fp16
fp16: ON
# TODO: this build is disabled to save Github Actions resources (https://github.com/ggml-org/llama.cpp/pull/23705)
# in order to enable it again, we have to provision dedicated runners to run it
# windows-latest-sycl:
# runs-on: windows-2022
#
# defaults:
# run:
# shell: bash
#
# env:
# WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/b60765d1-2b85-4e85-86b6-cb0e9563a699/intel-deep-learning-essentials-2025.3.3.18_offline.exe
# WINDOWS_DPCPP_MKL: intel.oneapi.win.cpp-dpcpp-common:intel.oneapi.win.mkl.devel:intel.oneapi.win.dnnl:intel.oneapi.win.tbb.devel
# LEVEL_ZERO_SDK_URL: https://github.com/oneapi-src/level-zero/releases/download/v1.28.2/level-zero-win-sdk-1.28.2.zip
# ONEAPI_ROOT: "C:/Program Files (x86)/Intel/oneAPI"
# ONEAPI_INSTALLER_VERSION: "2025.3.3"
# steps:
# - name: Clone
# id: checkout
# uses: actions/checkout@v6
#
# - name: Use oneAPI Installation Cache
# uses: actions/cache@v5
# id: cache-sycl
# with:
# path: ${{ env.ONEAPI_ROOT }}
# key: cache-gha-oneAPI-${{ env.ONEAPI_INSTALLER_VERSION }}-${{ runner.os }}
#
# - name: Download & Install oneAPI
# shell: bash
# if: steps.cache-sycl.outputs.cache-hit != 'true'
# run: |
# scripts/install-oneapi.bat $WINDOWS_BASEKIT_URL $WINDOWS_DPCPP_MKL
#
# - name: Install Level Zero SDK
# shell: pwsh
# run: |
# Invoke-WebRequest -Uri "${{ env.LEVEL_ZERO_SDK_URL }}" -OutFile "level-zero-win-sdk.zip"
# Expand-Archive -Path "level-zero-win-sdk.zip" -DestinationPath "C:/level-zero-sdk" -Force
# "LEVEL_ZERO_V1_SDK_PATH=C:/level-zero-sdk" | Out-File -FilePath $env:GITHUB_ENV -Append
#
# - name: ccache
# uses: ggml-org/ccache-action@v1.2.21
# with:
# key: sycl-windows-latest
# variant: ccache
# evict-old-files: 1d
# save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
#
# # TODO: add ssl support ; we will also need to modify win-build-sycl.bat to accept user-specified args
#
# - name: Build
# id: cmake_build
# run: examples/sycl/win-build-sycl.bat
runs-on: ubuntu-24.04
env:
ONEAPI_ROOT: /opt/intel/oneapi/
ONEAPI_INSTALLER_VERSION: "2025.3.3"
continue-on-error: true
steps:
- uses: actions/checkout@v6
- name: Use oneAPI Installation Cache
uses: actions/cache@v5
id: cache-sycl
with:
path: ${{ env.ONEAPI_ROOT }}
key: oneAPI-${{ env.ONEAPI_INSTALLER_VERSION }}-${{ runner.os }}
- name: Download & Install oneAPI
shell: bash
if: steps.cache-sycl.outputs.cache-hit != 'true'
run: |
cd /tmp
wget https://registrationcenter-download.intel.com/akdlm/IRC_NAS/56f7923a-adb8-43f3-8b02-2b60fcac8cab/intel-deep-learning-essentials-2025.3.3.16_offline.sh -O intel-deep-learning-essentials_offline.sh
sudo bash intel-deep-learning-essentials_offline.sh -s -a --silent --eula accept
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: ubuntu-24-sycl-${{ matrix.build }}
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
run: |
source /opt/intel/oneapi/setvars.sh
cmake -B build \
-G "Ninja" \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_SYCL=ON \
-DCMAKE_C_COMPILER=icx \
-DCMAKE_CXX_COMPILER=icpx \
-DLLAMA_OPENSSL=OFF \
-DGGML_NATIVE=OFF \
-DGGML_SYCL_F16=${{ matrix.fp16 }}
time cmake --build build --config Release -j $(nproc)
windows-latest-sycl:
runs-on: windows-2022
defaults:
run:
shell: bash
env:
WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/b60765d1-2b85-4e85-86b6-cb0e9563a699/intel-deep-learning-essentials-2025.3.3.18_offline.exe
WINDOWS_DPCPP_MKL: intel.oneapi.win.cpp-dpcpp-common:intel.oneapi.win.mkl.devel:intel.oneapi.win.dnnl:intel.oneapi.win.tbb.devel
ONEAPI_ROOT: "C:/Program Files (x86)/Intel/oneAPI"
ONEAPI_INSTALLER_VERSION: "2025.3.3"
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Use oneAPI Installation Cache
uses: actions/cache@v5
id: cache-sycl
with:
path: ${{ env.ONEAPI_ROOT }}
key: oneAPI-${{ env.ONEAPI_INSTALLER_VERSION }}-${{ runner.os }}
- name: Download & Install oneAPI
shell: bash
if: steps.cache-sycl.outputs.cache-hit != 'true'
run: |
scripts/install-oneapi.bat $WINDOWS_BASEKIT_URL $WINDOWS_DPCPP_MKL
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: windows-latest-sycl
variant: ccache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
# TODO: add ssl support ; we will also need to modify win-build-sycl.bat to accept user-specified args
- name: Build
id: cmake_build
run: examples/sycl/win-build-sycl.bat
-50
View File
@@ -1,50 +0,0 @@
name: CI (virtgpu)
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
paths: [
'.github/workflows/build-virtgpu.yml',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
'**/*.hpp',
'**/*.c',
'**/*.cpp'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/build-virtgpu.yml',
'ggml/src/ggml-virtgpu/**'
]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
jobs:
ubuntu-24-virtgpu:
runs-on: ${{ 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install -y build-essential libdrm-dev pkg-config libssl-dev
- name: Build
id: cmake_build
run: |
cmake -B build \
-DGGML_VIRTGPU=ON \
-DGGML_VIRTGPU_BACKEND=ON
cmake --build build --config Release -j $(nproc)
+12 -57
View File
@@ -31,57 +31,12 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
ubuntu:
strategy:
matrix:
include:
- build: 'x64'
os: ubuntu-24.04
- build: 'arm64'
os: ubuntu-24.04-arm
runs-on: ${{ matrix.os }}
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install -y gcc-14 g++-14 build-essential glslc libvulkan-dev spirv-headers libssl-dev ninja-build
echo "CC=gcc-14" >> "$GITHUB_ENV"
echo "CXX=g++-14" >> "$GITHUB_ENV"
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: vulkan-${{ matrix.os }}-new
variant: ccache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Configure
id: cmake_configure
run: |
cmake -B build \
-G "Ninja" \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_VULKAN=ON
- name: Build
id: cmake_build
run: |
time cmake --build build -j $(nproc)
ubuntu-llvmpipe:
ubuntu-24-vulkan-llvmpipe:
runs-on: ubuntu-24.04
steps:
@@ -89,6 +44,13 @@ jobs:
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: ubuntu-24-vulkan-llvmpipe
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Dependencies
id: depends
run: |
@@ -106,7 +68,7 @@ jobs:
id: cache-sdk
with:
path: ./vulkan_sdk
key: cache-gha-vulkan-sdk-${{ env.VULKAN_SDK_VERSION }}-${{ runner.os }}
key: vulkan-sdk-${{ env.VULKAN_SDK_VERSION }}-${{ runner.os }}
- name: Setup Vulkan SDK
if: steps.cache-sdk.outputs.cache-hit != 'true'
@@ -115,13 +77,6 @@ jobs:
path: ./vulkan_sdk
version: ${{ env.VULKAN_SDK_VERSION }}
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: vulkan-ubuntu-24.04-llvmpipe
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
run: |
-181
View File
@@ -1,181 +0,0 @@
name: CI (webgpu)
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
paths: [
'.github/workflows/build-webgpu.yml',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
'**/*.hpp',
'**/*.c',
'**/*.cpp',
'**/*.wgsl'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/build-webgpu.yml',
'ggml/src/ggml-webgpu/**'
]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
jobs:
macos:
runs-on: macos-latest
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: webgpu-macos-latest
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Dawn Dependency
id: dawn-depends
run: |
DAWN_VERSION="v20260317.182325"
DAWN_OWNER="google"
DAWN_REPO="dawn"
DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-macos-latest-Release"
echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
curl -L -o artifact.tar.gz \
"https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
mkdir dawn
tar -xvf artifact.tar.gz -C dawn --strip-components=1
- name: Build
id: cmake_build
run: |
export CMAKE_PREFIX_PATH=dawn
cmake -B build -G "Ninja" -DCMAKE_BUILD_TYPE=Release -DGGML_WEBGPU=ON -DGGML_METAL=OFF -DGGML_BLAS=OFF
time cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: Test
id: cmake_test
run: |
cd build
ctest -L main --verbose --timeout 900
ubuntu:
runs-on: ubuntu-24.04
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: webgpu-ubuntu-24.04
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Dependencies
id: depends
run: |
sudo add-apt-repository -y ppa:kisak/kisak-mesa
sudo apt-get update -y
sudo apt-get install -y build-essential mesa-vulkan-drivers \
libxcb-xinput0 libxcb-xinerama0 libxcb-cursor-dev libssl-dev
- name: Dawn Dependency
id: dawn-depends
run: |
sudo apt-get install -y libxrandr-dev libxinerama-dev libxcursor-dev mesa-common-dev libx11-xcb-dev libxi-dev
DAWN_VERSION="v20260317.182325"
DAWN_OWNER="google"
DAWN_REPO="dawn"
DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
curl -L -o artifact.tar.gz \
"https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
mkdir dawn
tar -xvf artifact.tar.gz -C dawn --strip-components=1
- name: Build
id: cmake_build
run: |
export Dawn_DIR=dawn/lib64/cmake/Dawn
cmake -B build \
-DGGML_WEBGPU=ON
time cmake --build build --config Release -j $(nproc)
- name: Test
id: cmake_test
run: |
cd build
# This is using llvmpipe and runs slower than other backends
# test-backend-ops is too slow on llvmpipe, skip it
ctest -L main -E test-backend-ops --verbose --timeout 900
ubuntu-wasm:
strategy:
matrix:
include:
- build: 'x64'
os: ubuntu-24.04
- build: 'arm64'
os: ubuntu-24.04-arm
runs-on: ${{ matrix.os }}
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: webgpu-${{ matrix.os }}-wasm
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Install Emscripten
run: |
git clone https://github.com/emscripten-core/emsdk.git
cd emsdk
./emsdk install latest
./emsdk activate latest
- name: Fetch emdawnwebgpu
run: |
DAWN_TAG="v20260317.182325"
EMDAWN_PKG="emdawnwebgpu_pkg-${DAWN_TAG}.zip"
echo "Downloading ${EMDAWN_PKG}"
curl -L -o emdawn.zip \
"https://github.com/google/dawn/releases/download/${DAWN_TAG}/${EMDAWN_PKG}"
unzip emdawn.zip
- name: Build WASM WebGPU
run: |
source emsdk/emsdk_env.sh
emcmake cmake -B build-wasm \
-G "Ninja" \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_WEBGPU=ON \
-DLLAMA_OPENSSL=OFF \
-DEMDAWNWEBGPU_DIR=emdawnwebgpu_pkg
time cmake --build build-wasm --config Release --target test-backend-ops -j $(nproc)
File diff suppressed because it is too large Load Diff
+1 -1
View File
@@ -19,7 +19,7 @@ on:
jobs:
check-vendor:
runs-on: [self-hosted, fast]
runs-on: ubuntu-slim
steps:
- name: Checkout
-51
View File
@@ -1,51 +0,0 @@
name: Code Style Checker
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
pull_request:
branches:
- master
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
jobs:
model-naming:
runs-on: [self-hosted, fast]
steps:
- uses: actions/checkout@v6
- name: Check model naming conventions
run: |
python3 - << 'EOF'
import re, os, sys
pairs = re.findall(
r'case\s+(LLM_ARCH_\w+)\s*:\s*\n\s+return new (llama_model_\w+)\s*\(',
open("src/llama-model.cpp").read())
errors = []
for arch, cls in pairs:
suffix = arch[len("LLM_ARCH_"):]
csuffix = cls[len("llama_model_"):]
fname = csuffix.replace("_", "-") + ".cpp"
if not re.fullmatch(r'[A-Z][A-Z0-9_]*', suffix):
errors.append(f"{arch}: suffix not upper snake case, example: LLM_ARCH_MY_MODEL")
if not re.fullmatch(r'[a-z][a-z0-9_]*', csuffix):
errors.append(f"{arch}: class suffix not lower snake case, example: llama_model_my_model")
elif suffix.lower() != csuffix:
errors.append(f"{arch}: arch/class name mismatch, expected class 'llama_model_{suffix.lower()}' but got '{cls}'")
elif not os.path.isfile(f"src/models/{fname}"):
errors.append(f"{arch}: expects model file name to be src/models/{fname}, but not found")
if errors:
print('\n'.join(f" - {e}" for e in errors)); sys.exit(1)
print(f"OK: {len(pairs)} mappings validated.")
EOF
+5 -78
View File
@@ -11,11 +11,6 @@ name: Publish Docker image
on:
workflow_dispatch: # allows manual triggering
inputs:
skip_s390x:
description: "Skip the s390x build target (useful for fast test runs that do not need the IBM Z runner)"
type: boolean
default: false
schedule:
# Rebuild daily rather than on every push because it is expensive
- cron: '12 4 * * *'
@@ -69,8 +64,6 @@ jobs:
- name: Generate build and merge matrices
id: matrices
shell: bash
env:
SKIP_S390X: ${{ inputs.skip_s390x || 'false' }}
run: |
set -euo pipefail
@@ -93,11 +86,6 @@ jobs:
]
JSON
if [ "${SKIP_S390X}" = "true" ]; then
jq 'map(select(.platforms != "linux/s390x"))' build-matrix.json > build-matrix.json.tmp
mv build-matrix.json.tmp build-matrix.json
fi
BUILD_MATRIX="$(jq -c . build-matrix.json)"
MERGE_MATRIX="$(jq -c '
reduce .[] as $entry ({}; .[$entry.tag] |= (
@@ -144,7 +132,6 @@ jobs:
config: ${{ fromJSON(needs.prepare_matrices.outputs.build_matrix) }}
steps:
- name: Check out the repo
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
@@ -200,10 +187,6 @@ jobs:
env:
GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}'
- name: Get build date
id: build_date
run: echo "date=$(date -u +"%Y-%m-%dT%H:%M:%SZ")" >> $GITHUB_OUTPUT
- name: Free Disk Space (Ubuntu)
if: ${{ matrix.config.free_disk_space == true }}
uses: ggml-org/free-disk-space@v1.3.1
@@ -228,26 +211,13 @@ jobs:
with:
context: .
platforms: ${{ matrix.config.platforms }}
outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true,oci-mediatypes=true
outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true
file: ${{ matrix.config.dockerfile }}
target: full
provenance: false
build-args: |
BUILD_DATE=${{ steps.build_date.outputs.date }}
APP_VERSION=${{ needs.create_tag.outputs.source_tag }}
APP_REVISION=${{ steps.checkout.outputs.commit }}
IMAGE_URL=${{ github.server_url }}/${{ github.repository }}
IMAGE_SOURCE=${{ github.server_url }}/${{ github.repository }}
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
annotations: |
manifest:org.opencontainers.image.created=${{ steps.build_date.outputs.date }}
manifest:org.opencontainers.image.version=${{ needs.create_tag.outputs.source_tag }}
manifest:org.opencontainers.image.revision=${{ steps.checkout.outputs.commit }}
manifest:org.opencontainers.image.title=llama.cpp
manifest:org.opencontainers.image.description=LLM inference in C/C++
manifest:org.opencontainers.image.url=${{ github.server_url }}/${{ github.repository }}
manifest:org.opencontainers.image.source=${{ github.server_url }}/${{ github.repository }}
# using github experimental cache
#cache-from: type=gha
#cache-to: type=gha,mode=max
@@ -265,26 +235,13 @@ jobs:
with:
context: .
platforms: ${{ matrix.config.platforms }}
outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true,oci-mediatypes=true
outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true
file: ${{ matrix.config.dockerfile }}
target: light
provenance: false
build-args: |
BUILD_DATE=${{ steps.build_date.outputs.date }}
APP_VERSION=${{ needs.create_tag.outputs.source_tag }}
APP_REVISION=${{ steps.checkout.outputs.commit }}
IMAGE_URL=${{ github.server_url }}/${{ github.repository }}
IMAGE_SOURCE=${{ github.server_url }}/${{ github.repository }}
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
annotations: |
manifest:org.opencontainers.image.created=${{ steps.build_date.outputs.date }}
manifest:org.opencontainers.image.version=${{ needs.create_tag.outputs.source_tag }}
manifest:org.opencontainers.image.revision=${{ steps.checkout.outputs.commit }}
manifest:org.opencontainers.image.title=llama.cpp
manifest:org.opencontainers.image.description=LLM inference in C/C++
manifest:org.opencontainers.image.url=${{ github.server_url }}/${{ github.repository }}
manifest:org.opencontainers.image.source=${{ github.server_url }}/${{ github.repository }}
# using github experimental cache
#cache-from: type=gha
#cache-to: type=gha,mode=max
@@ -302,26 +259,13 @@ jobs:
with:
context: .
platforms: ${{ matrix.config.platforms }}
outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true,oci-mediatypes=true
outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true
file: ${{ matrix.config.dockerfile }}
target: server
provenance: false
build-args: |
BUILD_DATE=${{ steps.build_date.outputs.date }}
APP_VERSION=${{ needs.create_tag.outputs.source_tag }}
APP_REVISION=${{ steps.checkout.outputs.commit }}
IMAGE_URL=${{ github.server_url }}/${{ github.repository }}
IMAGE_SOURCE=${{ github.server_url }}/${{ github.repository }}
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
annotations: |
manifest:org.opencontainers.image.created=${{ steps.build_date.outputs.date }}
manifest:org.opencontainers.image.version=${{ needs.create_tag.outputs.source_tag }}
manifest:org.opencontainers.image.revision=${{ steps.checkout.outputs.commit }}
manifest:org.opencontainers.image.title=llama.cpp
manifest:org.opencontainers.image.description=LLM inference in C/C++
manifest:org.opencontainers.image.url=${{ github.server_url }}/${{ github.repository }}
manifest:org.opencontainers.image.source=${{ github.server_url }}/${{ github.repository }}
# using github experimental cache
#cache-from: type=gha
#cache-to: type=gha,mode=max
@@ -386,15 +330,10 @@ jobs:
steps:
- name: Check out the repo
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Get build date
id: build_date
run: echo "date=$(date -u +"%Y-%m-%dT%H:%M:%SZ")" >> $GITHUB_OUTPUT
- name: Download digest metadata
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8
with:
@@ -422,8 +361,6 @@ jobs:
IMAGE_REPO="ghcr.io/${REPO_OWNER}/${REPO_NAME}"
PREFIX="${IMAGE_REPO}:"
SRC_TAG="${{ needs.create_tag.outputs.source_tag }}"
BUILD_DATE="${{ steps.build_date.outputs.date }}"
COMMIT_SHA="${{ steps.checkout.outputs.commit }}"
TAGS="${{ matrix.config.tag }}"
ARCHES="${{ matrix.config.arches }}"
DIGEST_GLOB="/tmp/digests/*.tsv"
@@ -475,21 +412,11 @@ jobs:
refs+=("${IMAGE_REPO}@${digest}")
done
local annotations=(
--annotation "index:org.opencontainers.image.created=${BUILD_DATE}"
--annotation "index:org.opencontainers.image.version=${SRC_TAG}"
--annotation "index:org.opencontainers.image.revision=${COMMIT_SHA}"
--annotation "index:org.opencontainers.image.title=llama.cpp"
--annotation "index:org.opencontainers.image.description=LLM inference in C/C++"
--annotation "index:org.opencontainers.image.url=${{ github.server_url }}/${{ github.repository }}"
--annotation "index:org.opencontainers.image.source=${{ github.server_url }}/${{ github.repository }}"
)
echo "Creating ${merged_tag} from ${refs[*]}"
docker buildx imagetools create "${annotations[@]}" --tag "${merged_tag}" "${refs[@]}"
docker buildx imagetools create --tag "${merged_tag}" "${refs[@]}"
echo "Creating ${merged_versioned_tag} from ${refs[*]}"
docker buildx imagetools create "${annotations[@]}" --tag "${merged_versioned_tag}" "${refs[@]}"
docker buildx imagetools create --tag "${merged_versioned_tag}" "${refs[@]}"
}
for tag in $TAGS; do
+6 -1
View File
@@ -2,6 +2,11 @@ name: EditorConfig Checker
on:
workflow_dispatch: # allows manual triggering
inputs:
create_release:
description: 'Create new release'
required: true
type: boolean
push:
branches:
- master
@@ -15,7 +20,7 @@ concurrency:
jobs:
editorconfig:
runs-on: [self-hosted, fast]
runs-on: ubuntu-slim
steps:
- uses: actions/checkout@v6
- uses: editorconfig-checker/action-editorconfig-checker@840e866d93b8e032123c23bac69dece044d4d84c # v2.2.0
+4 -4
View File
@@ -28,9 +28,9 @@ concurrency:
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
jobs:
ubuntu-22-hip-quality-check:
@@ -50,7 +50,7 @@ jobs:
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: hip-quality-check-ubuntu-22.04
key: ubuntu-22-hip-quality-check
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+8 -8
View File
@@ -3,16 +3,16 @@ name: Check Pre-Tokenizer Hashes
on:
push:
paths:
- 'conversion/base.py'
- 'convert_hf_to_gguf.py'
- 'convert_hf_to_gguf_update.py'
pull_request:
paths:
- 'conversion/base.py'
- 'convert_hf_to_gguf.py'
- 'convert_hf_to_gguf_update.py'
jobs:
pre-tokenizer-hashes:
runs-on: [self-hosted, fast]
runs-on: ubuntu-slim
steps:
- name: Checkout repository
@@ -30,16 +30,16 @@ jobs:
- name: Update pre-tokenizer hashes
run: |
cp conversion/base.py /tmp
cp convert_hf_to_gguf.py /tmp
.venv/bin/python convert_hf_to_gguf_update.py --check-missing
- name: Check if committed pre-tokenizer hashes matches generated version
run: |
if ! diff -q conversion/base.py /tmp/base.py; then
echo "Model pre-tokenizer hashes (in conversion/base.py) do not match generated hashes (from convert_hf_to_gguf_update.py)."
echo "To fix: run ./convert_hf_to_gguf_update.py and commit the updated conversion/base.py along with your changes"
if ! diff -q convert_hf_to_gguf.py /tmp/convert_hf_to_gguf.py; then
echo "Model pre-tokenizer hashes (in convert_hf_to_gguf.py) do not match generated hashes (from convert_hf_to_gguf_update.py)."
echo "To fix: run ./convert_hf_to_gguf_update.py and commit the updated convert_hf_to_gguf.py along with your changes"
echo "Differences found:"
diff conversion/base.py /tmp/base.py || true
diff convert_hf_to_gguf.py /tmp/convert_hf_to_gguf.py || true
exit 1
fi
echo "Model pre-tokenizer hashes are up to date."
@@ -20,7 +20,7 @@ concurrency:
jobs:
python-check-requirements:
runs-on: [self-hosted, CPU, fast]
runs-on: ubuntu-slim
name: check-requirements
steps:
- name: Check out source repository
+1 -1
View File
@@ -21,7 +21,7 @@ concurrency:
jobs:
flake8-lint:
runs-on: [self-hosted, fast]
runs-on: ubuntu-slim
name: Lint
steps:
- name: Check out source repository
+2 -2
View File
@@ -22,7 +22,7 @@ concurrency:
jobs:
python-type-check:
runs-on: [self-hosted, fast]
runs-on: ubuntu-slim
name: python type-check
steps:
- name: Check out source repository
@@ -31,7 +31,7 @@ jobs:
uses: actions/setup-python@v6
with:
python-version: "3.11"
pip-install: -r requirements/requirements-all.txt ty==0.0.35
pip-install: -r requirements/requirements-all.txt ty==0.0.33
# - name: Type-check with Pyright
# uses: jakebailey/pyright-action@v2
# with:
File diff suppressed because it is too large Load Diff
+18 -25
View File
@@ -26,10 +26,10 @@ on:
]
env:
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_ARG_LOG_VERBOSITY: 10
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
LLAMA_LOG_VERBOSITY: 10
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}
@@ -37,7 +37,7 @@ concurrency:
jobs:
server:
runs-on: [self-hosted, CPU, Linux, llama-server]
runs-on: ubuntu-latest
strategy:
matrix:
@@ -46,19 +46,19 @@ jobs:
fail-fast: false
steps:
#- name: Dependencies
# id: depends
# run: |
# sudo apt-get update
# sudo apt-get -y install \
# build-essential \
# xxd \
# git \
# cmake \
# curl \
# wget \
# language-pack-en \
# libssl-dev
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get -y install \
build-essential \
xxd \
git \
cmake \
curl \
wget \
language-pack-en \
libssl-dev
- name: Clone
id: checkout
@@ -67,13 +67,6 @@ jobs:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Setup Node.js
uses: actions/setup-node@v6
with:
node-version: "24"
cache: "npm"
cache-dependency-path: "tools/ui/package-lock.json"
- name: Build
id: cmake_build
run: |
+43 -114
View File
@@ -29,10 +29,10 @@ on:
]
env:
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_ARG_LOG_VERBOSITY: 10
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
LLAMA_LOG_VERBOSITY: 10
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}
@@ -67,13 +67,6 @@ jobs:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Setup Node.js
uses: actions/setup-node@v6
with:
node-version: "24"
cache: "npm"
cache-dependency-path: "tools/ui/package-lock.json"
- name: Build
id: cmake_build
run: |
@@ -91,106 +84,42 @@ jobs:
export ${{ matrix.extra_args }}
pytest -v -x -m "not slow"
server-cuda:
runs-on: [self-hosted, llama-server, Linux, NVIDIA]
name: server-cuda (${{ matrix.wf_name }})
strategy:
matrix:
build_type: [Release]
wf_name: ["GPUx1"]
include:
- build_type: Release
extra_args: "LLAMA_ARG_BACKEND_SAMPLING=1"
wf_name: "GPUx1, backend-sampling"
fail-fast: false
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Build
id: cmake_build
run: |
cmake -B build -DGGML_CUDA=ON -DGGML_SCHED_NO_REALLOC=ON
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Tests
id: server_integration_tests
if: ${{ (!matrix.disabled_on_pr || !github.event.pull_request) }}
run: |
cd tools/server/tests
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
export ${{ matrix.extra_args }}
pytest -v -x -m "not slow"
server-kleidiai:
runs-on: ah-ubuntu_22_04-c8g_8x
name: server-kleidiai (${{ matrix.wf_name }})
strategy:
matrix:
include:
- build_type: Release
extra_build_flags: "-DGGML_CPU_KLEIDIAI=ON"
extra_args: ""
wf_name: "CPUx1, kleidiai"
fail-fast: false
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Dependencies
id: depends
run: |
set -euxo pipefail
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive NEEDRESTART_MODE=a \
apt-get install -y \
build-essential \
libssl-dev \
python3-venv \
gpg \
wget \
time \
git-lfs
git lfs install
# install the latest cmake
sudo install -d /usr/share/keyrings
wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc \
| gpg --dearmor \
| sudo tee /usr/share/keyrings/kitware-archive-keyring.gpg >/dev/null
echo 'deb [signed-by=/usr/share/keyrings/kitware-archive-keyring.gpg] https://apt.kitware.com/ubuntu/ jammy main' \
| sudo tee /etc/apt/sources.list.d/kitware.list
sudo apt-get update
sudo apt-get install -y cmake
- name: Build
id: cmake_build
run: |
cmake -B build -DGGML_SCHED_NO_REALLOC=ON ${{ matrix.extra_build_flags }}
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Tests
id: server_integration_tests
if: ${{ (!matrix.disabled_on_pr || !github.event.pull_request) }}
run: |
cd tools/server/tests
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
export ${{ matrix.extra_args }}
pytest -v -x -m "not slow"
# TODO: provision CUDA runner
# server-cuda:
# runs-on: [self-hosted, llama-server, Linux, NVIDIA]
#
# name: server-cuda (${{ matrix.wf_name }})
# strategy:
# matrix:
# build_type: [Release]
# wf_name: ["GPUx1"]
# include:
# - build_type: Release
# extra_args: "LLAMA_ARG_BACKEND_SAMPLING=1"
# wf_name: "GPUx1, backend-sampling"
# fail-fast: false
#
# steps:
# - name: Clone
# id: checkout
# uses: actions/checkout@v6
# with:
# fetch-depth: 0
# ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
#
# - name: Build
# id: cmake_build
# run: |
# cmake -B build -DGGML_SCHED_NO_REALLOC=ON
# cmake --build build --config ${{ matrix.build_type }} -j $(sysctl -n hw.logicalcpu) --target llama-server
#
# - name: Tests
# id: server_integration_tests
# if: ${{ (!matrix.disabled_on_pr || !github.event.pull_request) }}
# run: |
# cd tools/server/tests
# python3 -m venv venv
# source venv/bin/activate
# pip install -r requirements.txt
# export ${{ matrix.extra_args }}
# pytest -v -x -m "not slow"
@@ -1,7 +1,7 @@
name: UI
name: Server WebUI
on:
workflow_dispatch:
workflow_dispatch: # allows manual triggering
inputs:
sha:
description: 'Commit SHA1 to build'
@@ -11,39 +11,34 @@ on:
branches:
- master
paths: [
'.github/workflows/ui.yml',
'.github/workflows/ui-build.yml',
'tools/ui/**.*',
'tools/server/tests/**.*'
'.github/workflows/server-webui.yml',
'tools/server/webui/**.*',
'tools/server/tests/**.*',
'tools/server/public/**'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/ui.yml',
'.github/workflows/ui-build.yml',
'tools/ui/**.*',
'tools/server/tests/**.*'
'.github/workflows/server-webui.yml',
'tools/server/webui/**.*',
'tools/server/tests/**.*',
'tools/server/public/**'
]
env:
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_ARG_LOG_VERBOSITY: 10
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
LLAMA_LOG_VERBOSITY: 10
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
ui-build:
name: Build static output
uses: ./.github/workflows/ui-build.yml
ui-checks:
name: Checks
needs: ui-build
runs-on: ubuntu-latest
webui-check:
name: WebUI Checks
runs-on: ${{ 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
continue-on-error: true
steps:
- name: Checkout code
@@ -56,89 +51,58 @@ jobs:
id: node
uses: actions/setup-node@v6
with:
node-version: "24"
node-version: "22"
cache: "npm"
cache-dependency-path: "tools/ui/package-lock.json"
cache-dependency-path: "tools/server/webui/package-lock.json"
- name: Install dependencies
id: setup
if: ${{ steps.node.conclusion == 'success' }}
run: npm ci
working-directory: tools/ui
working-directory: tools/server/webui
- name: Run type checking
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npm run check
working-directory: tools/ui
working-directory: tools/server/webui
- name: Run linting
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npm run lint
working-directory: tools/ui
- name: Install Playwright browsers
id: playwright
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npx playwright install --with-deps
working-directory: tools/ui
- name: Run Client tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:client
working-directory: tools/ui
- name: Run Unit tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:unit
working-directory: tools/ui
e2e-tests:
name: E2E Tests
needs: ui-build
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Setup Node.js
id: node
uses: actions/setup-node@v6
with:
node-version: "24"
cache: "npm"
cache-dependency-path: "tools/ui/package-lock.json"
- name: Install dependencies
id: setup
if: ${{ steps.node.conclusion == 'success' }}
run: npm ci
working-directory: tools/ui
working-directory: tools/server/webui
- name: Build application
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npm run build
working-directory: tools/ui
working-directory: tools/server/webui
- name: Install Playwright browsers
id: playwright
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npx playwright install --with-deps
working-directory: tools/ui
working-directory: tools/server/webui
- name: Build Storybook
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run build-storybook
working-directory: tools/ui
working-directory: tools/server/webui
- name: Run Client tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:client
working-directory: tools/server/webui
- name: Run Unit tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:unit
working-directory: tools/server/webui
- name: Run UI tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:ui -- --testTimeout=60000
working-directory: tools/ui
working-directory: tools/server/webui
- name: Run E2E tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:e2e
working-directory: tools/ui
working-directory: tools/server/webui
+12 -31
View File
@@ -44,20 +44,20 @@ on:
]
env:
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_ARG_LOG_VERBOSITY: 10
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
LLAMA_LOG_VERBOSITY: 10
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
ubuntu:
runs-on: ubuntu-24.04
server:
runs-on: ubuntu-latest
name: ubuntu (${{ matrix.wf_name }})
name: server (${{ matrix.wf_name }})
strategy:
matrix:
build_type: [Release]
@@ -93,17 +93,11 @@ jobs:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: server-ubuntu-24.04-x64
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
run: |
cmake -B build \
-DLLAMA_BUILD_BORINGSSL=ON \
-DGGML_SCHED_NO_REALLOC=ON
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
@@ -130,8 +124,8 @@ jobs:
export ${{ matrix.extra_args }}
SLOW_TESTS=1 pytest -v -x
windows:
runs-on: windows-2025
server-windows:
runs-on: windows-2022
steps:
- name: Clone
@@ -141,24 +135,11 @@ jobs:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: server-windows-2025-x64
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
shell: cmd
run: |
cmake -B build -G "Ninja Multi-Config" ^
-DCMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake ^
-DCMAKE_BUILD_TYPE=Release ^
-DLLAMA_BUILD_BORINGSSL=ON ^
-DGGML_SCHED_NO_REALLOC=ON
set /A NINJA_JOBS=%NUMBER_OF_PROCESSORS%-1
cmake --build build --config Release -j %NINJA_JOBS% --target llama-server
cmake -B build -DLLAMA_BUILD_BORINGSSL=ON -DGGML_SCHED_NO_REALLOC=ON
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS} --target llama-server
- name: Python setup
id: setup_python
@@ -1,43 +0,0 @@
name: UI Build (self-hosted)
on:
workflow_call:
jobs:
build:
runs-on: [self-hosted, fast]
env:
BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
steps:
- name: Checkout code
uses: actions/checkout@v6
- name: Setup Node.js
uses: actions/setup-node@v6
with:
node-version: "24"
cache: "npm"
cache-dependency-path: "tools/ui/package-lock.json"
- name: Install dependencies
run: npm ci
working-directory: tools/ui
- name: Build application
run: npm run build
working-directory: tools/ui
- name: Generate checksums
run: |
cd tools/ui/dist
for f in *; do
sha256sum "$f" | awk '{print $1, $2}' >> checksums.txt
done
- name: Upload built UI
uses: actions/upload-artifact@v6
with:
name: ui-build
path: tools/ui/dist/
retention-days: 1
-43
View File
@@ -1,43 +0,0 @@
name: UI Build
on:
workflow_call:
jobs:
build:
runs-on: ubuntu-slim
env:
BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
steps:
- name: Checkout code
uses: actions/checkout@v6
- name: Setup Node.js
uses: actions/setup-node@v6
with:
node-version: "24"
cache: "npm"
cache-dependency-path: "tools/ui/package-lock.json"
- name: Install dependencies
run: npm ci
working-directory: tools/ui
- name: Build application
run: npm run build
working-directory: tools/ui
- name: Generate checksums
run: |
cd tools/ui/dist
for f in *; do
sha256sum "$f" | awk '{print $1, $2}' >> checksums.txt
done
- name: Upload built UI
uses: actions/upload-artifact@v6
with:
name: ui-build
path: tools/ui/dist/
retention-days: 1
-70
View File
@@ -1,70 +0,0 @@
name: UI Publish
on:
workflow_call:
inputs:
version_tag:
description: 'Version tag to publish under (e.g., b1234)'
required: true
type: string
secrets:
hf_token:
description: 'Hugging Face token with write access'
required: true
jobs:
build:
name: Build static output
uses: ./.github/workflows/ui-build.yml
publish:
name: Publish UI Static Output
needs: build
runs-on: ubuntu-slim
permissions:
contents: read
env:
HF_BUCKET_NAME: ${{ vars.HF_BUCKET_UI_STATIC_OUTPUT }}
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 1
- name: Download UI build artifact
uses: actions/download-artifact@v7
with:
name: ui-build
path: tools/ui/dist/
- name: Install Hugging Face Hub CLI
run: pip install -U huggingface_hub
- name: Authenticate with Hugging Face
run: hf auth login --token ${{ secrets.hf_token }}
- name: Sync built files to Hugging Face bucket (version tag)
run: |
# Upload the built files to the Hugging Face bucket under the release version
hf buckets sync tools/ui/dist hf://buckets/ggml-org/${{ env.HF_BUCKET_NAME }}/${{ inputs.version_tag }} --delete --quiet
- name: Sync built files to Hugging Face bucket (latest)
run: |
# Also upload to the 'latest' directory for fallback downloads
hf buckets sync tools/ui/dist hf://buckets/ggml-org/${{ env.HF_BUCKET_NAME }}/latest --delete --quiet
- name: Verify upload
run: |
# List the files in the bucket to verify the upload
hf buckets list hf://buckets/ggml-org/${{ env.HF_BUCKET_NAME }}/${{ inputs.version_tag }} -R -h
- name: Clean up root-level files
run: |
# Clean up any old root-level files from previous non-versioned deployments
hf buckets rm ggml-org/${{ env.HF_BUCKET_NAME }}/index.html --yes 2>/dev/null || true
hf buckets rm ggml-org/${{ env.HF_BUCKET_NAME }}/bundle.js --yes 2>/dev/null || true
hf buckets rm ggml-org/${{ env.HF_BUCKET_NAME }}/bundle.css --yes 2>/dev/null || true
hf buckets rm ggml-org/${{ env.HF_BUCKET_NAME }}/loading.html --yes 2>/dev/null || true
-118
View File
@@ -1,118 +0,0 @@
name: UI (self-hosted)
# these are the same as ui.yml, but with self-hosted runners
# the runners come with pre-installed Playwright browsers version: 1.56.1
# the jobs are much lighter because they don't need to install node and playwright browsers
on:
workflow_dispatch:
inputs:
sha:
description: 'Commit SHA1 to build'
required: false
type: string
push:
branches:
- master
paths: [
'.github/workflows/ui-self-hosted.yml',
'.github/workflows/ui-build-self-hosted.yml',
'tools/ui/**.*',
'tools/server/tests/**.*'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/ui-self-hosted.yml',
'.github/workflows/ui-build-self-hosted.yml',
'tools/ui/**.*',
'tools/server/tests/**.*'
]
env:
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
LLAMA_ARG_LOG_VERBOSITY: 10
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
ui-build:
name: Build static output
uses: ./.github/workflows/ui-build-self-hosted.yml
ui-checks:
name: Checks
needs: ui-build
runs-on: [self-hosted, PLAYWRIGHT]
continue-on-error: true
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Install dependencies
id: setup
run: npm ci
working-directory: tools/ui
- name: Run type checking
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npm run check
working-directory: tools/ui
- name: Run linting
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npm run lint
working-directory: tools/ui
- name: Run Client tests
if: ${{ always() }}
run: npm run test:client
working-directory: tools/ui
- name: Run Unit tests
if: ${{ always() }}
run: npm run test:unit
working-directory: tools/ui
e2e-tests:
name: E2E Tests
needs: ui-build
runs-on: [self-hosted, PLAYWRIGHT]
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Install dependencies
id: setup
run: npm ci
working-directory: tools/ui
- name: Build application
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npm run build
working-directory: tools/ui
- name: Build Storybook
if: ${{ always() }}
run: npm run build-storybook
working-directory: tools/ui
- name: Run UI tests
if: ${{ always() }}
run: npm run test:ui -- --testTimeout=60000
working-directory: tools/ui
- name: Run E2E tests
if: ${{ always() }}
run: npm run test:e2e
working-directory: tools/ui
+1 -3
View File
@@ -3,20 +3,18 @@ name: Update Operations Documentation
on:
push:
paths:
- '.github/workflows/update-ops-docs.yml'
- 'docs/ops.md'
- 'docs/ops/**'
- 'scripts/create_ops_docs.py'
pull_request:
paths:
- '.github/workflows/update-ops-docs.yml'
- 'docs/ops.md'
- 'docs/ops/**'
- 'scripts/create_ops_docs.py'
jobs:
update-ops-docs:
runs-on: [self-hosted, fast, ARM64]
runs-on: ubuntu-slim
steps:
- name: Checkout repository
+3 -4
View File
@@ -92,12 +92,12 @@
!/examples/sycl/*.bat
!/examples/sycl/*.sh
# Server Web UI temporary files (+ legacy directory)
# Server Web UI temporary files
/tools/server/webui/node_modules
/tools/server/webui/dist
/tools/ui/node_modules
/tools/ui/dist
# we no longer use gz for index.html
/tools/server/public/index.html.gz
# Python
@@ -110,7 +110,6 @@ uv.lock
# Nix
flake.lock
/result
# Test binaries
+2 -5
View File
@@ -1,7 +1,7 @@
You are a coding agent. Here are some very important rules that you must follow:
General:
- Be very precise and concise when writing code, comments, explanations, etc.
- By very precise and concise when writing code, comments, explanations, etc.
- PR and commit titles format: `<module> : <title>`. Lookup recents for examples
- Don't try to build or run the code unless you are explicitly asked to do so
- Use the `gh` CLI tool when querying PRs, issues, or other GitHub resources
@@ -16,15 +16,12 @@ Pull requests (PRs):
- New branch names are prefixed with "gg/"
- Before opening a pull request, ask the user to confirm the description
- When creating a pull request, look for the repository's PR template and follow it
- For the AI usage disclosure section, write "YES. llama.cpp + pi + [MODEL]"
- Ask the user to tell you what model was used and write it in place of [MODEL]
- For the AI usage disclosure section, write "YES. llama.cpp + pi"
- Always create the pull requests in draft mode
Commits:
- On every commit that you make, include a "Assisted-by: llama.cpp:local pi" tag
- Do not explicitly set the git author in commits - rely on the default git config
- Always use `--no-gpg-sign` when committing
- Never `git push` without explicit confirmation from the user
Resources (read on demand):
- [CONTRIBUTING.md](CONTRIBUTING.md)
+19 -14
View File
@@ -104,16 +104,13 @@ option(LLAMA_SANITIZE_UNDEFINED "llama: enable undefined sanitizer" OFF)
option(LLAMA_BUILD_COMMON "llama: build common utils library" ${LLAMA_STANDALONE})
# extra artifacts
option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_TOOLS "llama: build tools" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_SERVER "llama: build server example" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_APP "llama: build the unified binary" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_UI "llama: build the embedded Web UI for server" ON)
option(LLAMA_USE_PREBUILT_UI "llama: use prebuilt UI from HF Bucket when available (requires LLAMA_BUILD_UI=ON)" ON)
option(LLAMA_TOOLS_INSTALL "llama: install tools" ${LLAMA_TOOLS_INSTALL_DEFAULT})
option(LLAMA_TESTS_INSTALL "llama: install tests" ON)
option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_TOOLS "llama: build tools" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_SERVER "llama: build server example" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_WEBUI "llama: build the embedded Web UI for server" ON)
option(LLAMA_TOOLS_INSTALL "llama: install tools" ${LLAMA_TOOLS_INSTALL_DEFAULT})
option(LLAMA_TESTS_INSTALL "llama: install tests" ON)
# 3rd party libs
option(LLAMA_OPENSSL "llama: use openssl to support HTTPS" ON)
@@ -218,10 +215,6 @@ if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TOOLS)
add_subdirectory(tools)
endif()
if (LLAMA_BUILD_APP)
add_subdirectory(app)
endif()
# Automatically add all files from the 'licenses' directory
file(GLOB EXTRA_LICENSES "${CMAKE_SOURCE_DIR}/licenses/LICENSE-*")
@@ -277,6 +270,18 @@ install(FILES ${CMAKE_CURRENT_BINARY_DIR}/llama-config.cmake
${CMAKE_CURRENT_BINARY_DIR}/llama-version.cmake
DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/llama)
install(
FILES convert_hf_to_gguf.py
PERMISSIONS
OWNER_READ
OWNER_WRITE
OWNER_EXECUTE
GROUP_READ
GROUP_EXECUTE
WORLD_READ
WORLD_EXECUTE
DESTINATION ${CMAKE_INSTALL_BINDIR})
configure_file(cmake/llama.pc.in
"${CMAKE_CURRENT_BINARY_DIR}/llama.pc"
@ONLY)
+3 -3
View File
@@ -15,7 +15,7 @@
# ggml-org/llama-common : ggerganov, aldehir, angt, danbev, ngxson, pwilkin
# ggml-org/llama-mtmd : ngxson
# ggml-org/llama-server : ggerganov, ngxson, allozaur, angt, ServeurpersoCom
# ggml-org/llama-ui : allozaur
# ggml-org/llama-webui : allozaur
/.devops/*.Dockerfile @ngxson
/.github/actions/ @ggml-org/ci
@@ -26,7 +26,6 @@
/common/fit.* @JohannesGaessler
/common/jinja/ @CISC
/common/ngram-map.* @srogmann
/conversion/ @CISC
/convert_*.py @CISC
/docs/backend/snapdragon/ @ggml-org/ggml-hexagon
/examples/batched.swift/ @ggerganov
@@ -49,6 +48,7 @@
/examples/parallel/ @ggerganov
/examples/passkey/ @ggerganov
/examples/retrieval/ @ggerganov
/examples/save-load-state/ @ggerganov
/examples/speculative-simple/ @ggerganov
/examples/speculative/ @ggerganov
/ggml/cmake/ @ggerganov
@@ -107,7 +107,7 @@
/tools/rpc/ @ggml-org/ggml-rpc
/tools/server/* @ggml-org/llama-server # no subdir
/tools/server/tests/ @ggml-org/llama-server
/tools/ui/ @ggml-org/llama-ui
/tools/server/webui/ @ggml-org/llama-webui
/tools/tokenize/ @ggerganov
/tools/tts/ @ggerganov
/vendor/ @ggerganov
+1 -4
View File
@@ -46,9 +46,7 @@ Before submitting your PR:
- provide KL divergence data calculated vs. the FP16/BF16 (whichever is the native precision) version for both the new type as well as types of similar size
- provide [performance data](https://github.com/ggml-org/llama.cpp/tree/master/tools/llama-bench) for the new type in comparison to types of similar size on pure CPU
- Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly
- If you are a new contributor
- Limit your open PRs to 1
- Do not submit trivial fixes (e.g. typos, formatting changes)
- If you are a new contributor, limit your open PRs to 1.
After submitting your PR:
- Expect requests for modifications to ensure the code meets llama.cpp's standards for quality and long-term maintainability
@@ -63,7 +61,6 @@ After submitting your PR:
- Optionally pick a `<module>` from here: https://github.com/ggml-org/llama.cpp/wiki/Modules
- Let other maintainers merge their own PRs
- When merging a PR, make sure you have a good understanding of the changes
- If a PR does not warrant a new release, add `[no release]` in the squashed commit to spare CI resources
- Be mindful of maintenance: most of the work going into a feature happens after the PR is merged. If the PR author is not committed to contribute long-term, someone else needs to take responsibility (you)
Maintainers reserve the right to decline review or close pull requests for any reason, without any questions, particularly under any of the following conditions:
+2 -4
View File
@@ -27,7 +27,6 @@ LLM inference in C/C++
- Vim/Neovim plugin for FIM completions: https://github.com/ggml-org/llama.vim
- Hugging Face Inference Endpoints now support GGUF out of the box! https://github.com/ggml-org/llama.cpp/discussions/9669
- Hugging Face GGUF editor: [discussion](https://github.com/ggml-org/llama.cpp/discussions/9268) | [tool](https://huggingface.co/spaces/CISCai/gguf-editor)
- WebGPU support is now available in the browser, see a blog/demo introducing it [here](https://reeselevine.github.io/llamas-on-the-web/).
----
@@ -173,7 +172,6 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
- JavaScript/Wasm (works in browser): [tangledgroup/llama-cpp-wasm](https://github.com/tangledgroup/llama-cpp-wasm)
- Typescript/Wasm (nicer API, available on npm): [ngxson/wllama](https://github.com/ngxson/wllama)
- Ruby: [yoshoku/llama_cpp.rb](https://github.com/yoshoku/llama_cpp.rb)
- Ruby: [docusealco/rllama](https://github.com/docusealco/rllama)
- Rust (more features): [edgenai/llama_cpp-rs](https://github.com/edgenai/llama_cpp-rs)
- Rust (nicer API): [mdrokz/rust-llama.cpp](https://github.com/mdrokz/rust-llama.cpp)
- Rust (more direct bindings): [utilityai/llama-cpp-rs](https://github.com/utilityai/llama-cpp-rs)
@@ -281,7 +279,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
| [Metal](docs/build.md#metal-build) | Apple Silicon |
| [BLAS](docs/build.md#blas-build) | All |
| [BLIS](docs/backend/BLIS.md) | All |
| [SYCL](docs/backend/SYCL.md) | Intel GPU |
| [SYCL](docs/backend/SYCL.md) | Intel and Nvidia GPU |
| [OpenVINO [In Progress]](docs/backend/OPENVINO.md) | Intel CPUs, GPUs, and NPUs |
| [MUSA](docs/build.md#musa) | Moore Threads GPU |
| [CUDA](docs/build.md#cuda) | Nvidia GPU |
@@ -291,7 +289,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
| [CANN](docs/build.md#cann) | Ascend NPU |
| [OpenCL](docs/backend/OPENCL.md) | Adreno GPU |
| [IBM zDNN](docs/backend/zDNN.md) | IBM Z & LinuxONE |
| [WebGPU](docs/build.md#webgpu) | All |
| [WebGPU [In Progress]](docs/build.md#webgpu) | All |
| [RPC](https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc) | All |
| [Hexagon [In Progress]](docs/backend/snapdragon/README.md) | Snapdragon |
| [VirtGPU](docs/backend/VirtGPU.md) | VirtGPU APIR |
-20
View File
@@ -1,20 +0,0 @@
set(TARGET llama-app)
add_executable(${TARGET} llama.cpp)
set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME llama)
target_link_libraries(${TARGET} PRIVATE
llama-server-impl
llama-cli-impl
llama-completion-impl
llama-bench-impl
llama-batched-bench-impl
llama-fit-params-impl
llama-quantize-impl
llama-perplexity-impl
)
target_compile_features(${TARGET} PRIVATE cxx_std_17)
if(LLAMA_TOOLS_INSTALL)
install(TARGETS ${TARGET} RUNTIME)
endif()
-101
View File
@@ -1,101 +0,0 @@
#include "build-info.h"
#include <cstdio>
#include <cstdlib>
#include <string>
#include <vector>
// visible
int llama_server(int argc, char ** argv);
int llama_cli(int argc, char ** argv);
// hidden
int llama_completion(int argc, char ** argv);
int llama_bench(int argc, char ** argv);
int llama_batched_bench(int argc, char ** argv);
int llama_fit_params(int argc, char ** argv);
int llama_quantize(int argc, char ** argv);
int llama_perplexity(int argc, char ** argv);
static const char * progname;
static int help(int argc, char ** argv);
static int version(int argc, char ** argv);
struct command {
const char * name;
const char * desc;
std::vector<std::string> aliases;
bool hidden;
int (*func)(int, char **);
};
static const command cmds[] = {
{"serve", "HTTP API server", {"server"}, false, llama_server },
{"cli", "Command-line interactive interface", {"client"}, false, llama_cli },
{"completion", "Text completion", {"complete"}, true, llama_completion },
{"bench", "Benchmark prompt processing and text generation", {}, true, llama_bench },
{"batched-bench", "Benchmark batched decoding performance", {}, true, llama_batched_bench},
{"fit-params", "Compute parameters to fit a model in device memory", {}, true, llama_fit_params },
{"quantize", "Quantize a model", {}, true, llama_quantize },
{"perplexity", "Compute model perplexity and KL divergence", {}, true, llama_perplexity },
{"version", "Show version", {}, false, version },
{"help", "Show available commands", {}, false, help },
};
static int version(int argc, char ** argv) {
printf("%s\n", llama_build_info());
return 0;
}
static int help(int argc, char ** argv) {
const bool show_all = argc >= 2 && std::string(argv[1]) == "all";
printf("Usage: %s <command> [options]\n\nAvailable commands:\n", progname);
for (const auto & cmd : cmds) {
if (show_all || !cmd.hidden) {
printf(" %-15s %s\n", cmd.name, cmd.desc);
}
}
printf("\n");
if (!show_all) {
printf("Run '%s help all' to show additional commands.\n", progname);
}
printf("Run '%s <command> --help' for command-specific usage.\n", progname);
return 0;
}
static bool matches(const std::string & arg, const command & cmd) {
if (arg == cmd.name) {
return true;
}
for (const auto & alias : cmd.aliases) {
if (arg == alias) {
return true;
}
}
return false;
}
int main(int argc, char ** argv) {
progname = argv[0];
const std::string arg = argc >= 2 ? argv[1] : "help";
for (const auto & cmd : cmds) {
if (matches(arg, cmd)) {
// keep cmd.name so the router's child processes re-invoke correctly
#ifdef _WIN32
_putenv_s("LLAMA_APP_CMD", cmd.name);
#else
setenv("LLAMA_APP_CMD", cmd.name, 1);
#endif
return cmd.func(argc - 1, argv + 1);
}
}
fprintf(stderr, "error: unknown command '%s'\n", arg.c_str());
return 1;
}
-2
View File
@@ -7,7 +7,6 @@ VISIONOS_MIN_OS_VERSION=1.0
TVOS_MIN_OS_VERSION=16.4
BUILD_SHARED_LIBS=OFF
LLAMA_BUILD_APP=OFF
LLAMA_BUILD_EXAMPLES=OFF
LLAMA_BUILD_TOOLS=OFF
LLAMA_BUILD_TESTS=OFF
@@ -32,7 +31,6 @@ COMMON_CMAKE_ARGS=(
-DCMAKE_XCODE_ATTRIBUTE_STRIP_INSTALLED_PRODUCT=NO
-DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
-DBUILD_SHARED_LIBS=${BUILD_SHARED_LIBS}
-DLLAMA_BUILD_APP=${LLAMA_BUILD_APP}
-DLLAMA_BUILD_EXAMPLES=${LLAMA_BUILD_EXAMPLES}
-DLLAMA_BUILD_TOOLS=${LLAMA_BUILD_TOOLS}
-DLLAMA_BUILD_TESTS=${LLAMA_BUILD_TESTS}
+10 -17
View File
@@ -66,8 +66,6 @@ fi
if [ ! -z ${GG_BUILD_METAL} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON"
else
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=OFF"
fi
if [ ! -z ${GG_BUILD_CUDA} ]; then
@@ -116,12 +114,9 @@ fi
if [ ! -z ${GG_BUILD_VULKAN} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_VULKAN=1"
# if on Mac, disable METAL
if [[ "$OSTYPE" == "darwin"* ]]; then
MACOS_RUNNER_CUSTOM_VULKAN_CMAKE_LOCATION="/usr/local/lib/cmake/vulkan"
MACOS_RUNNER_CUSTOM_SPIRV_HEADERS_LOCATION="${MACOS_RUNNER_CUSTOM_VULKAN_CMAKE_LOCATION}/SPIRV-Headers/SPIRV-HeadersConfig.cmake"
if [[ -f "${MACOS_RUNNER_CUSTOM_SPIRV_HEADERS_LOCATION}" || -h "${MACOS_RUNNER_CUSTOM_SPIRV_HEADERS_LOCATION}" ]]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DSPIRV-Headers_DIR=${MACOS_RUNNER_CUSTOM_VULKAN_CMAKE_LOCATION}/SPIRV-Headers"
fi
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=OFF -DGGML_BLAS=OFF"
fi
# Build shared libs on Windows
@@ -132,7 +127,7 @@ if [ ! -z ${GG_BUILD_VULKAN} ]; then
fi
if [ ! -z ${GG_BUILD_WEBGPU} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_WEBGPU=1"
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_WEBGPU=1 -DGGML_METAL=OFF -DGGML_BLAS=OFF"
if [ ! -z "${GG_BUILD_WEBGPU_DAWN_PREFIX}" ]; then
if [ -z "${CMAKE_PREFIX_PATH}" ]; then
@@ -166,8 +161,6 @@ fi
if [ ! -z ${GG_BUILD_BLAS} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=${GG_BUILD_BLAS_VENDOR:-OpenBLAS}"
else
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_BLAS=OFF"
fi
if [ ! -z ${GG_BUILD_OPENVINO} ]; then
@@ -239,7 +232,7 @@ function gg_run_ctest_debug {
(cmake -G "${CMAKE_GENERATOR}" -DCMAKE_BUILD_TYPE=Debug ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time cmake --build . --config Debug -j$(nproc)) 2>&1 | tee -a $OUT/${ci}-make.log
(time ctest -C Debug --output-on-failure -L main -E "test-opt|test-backend-ops|test-llama-archs" ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
(time ctest -C Debug --output-on-failure -L main -E "test-opt|test-backend-ops" ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
set +e
}
@@ -462,10 +455,10 @@ function gg_run_qwen3_0_6b {
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/test-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa off --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/test-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa on --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/test-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa off ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/test-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa on ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa off --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa on --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa off ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa on ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@@ -701,8 +694,8 @@ function gg_sum_test_backend_ops_cpu {
## main
export LLAMA_ARG_LOG_PREFIX=1
export LLAMA_ARG_LOG_TIMESTAMPS=1
export LLAMA_LOG_PREFIX=1
export LLAMA_LOG_TIMESTAMPS=1
if [ -z ${GG_BUILD_LOW_PERF} ]; then
# Create symlink: ./llama.cpp/models-mnt -> $MNT/models
+1 -1
View File
@@ -7,7 +7,7 @@ set(LLAMA_SHARED_LIB @BUILD_SHARED_LIBS@)
set_and_check(LLAMA_INCLUDE_DIR "@PACKAGE_LLAMA_INCLUDE_INSTALL_DIR@")
set_and_check(LLAMA_LIB_DIR "@PACKAGE_LLAMA_LIB_INSTALL_DIR@")
set(LLAMA_BIN_DIR "@PACKAGE_LLAMA_BIN_INSTALL_DIR@")
set_and_check(LLAMA_BIN_DIR "@PACKAGE_LLAMA_BIN_INSTALL_DIR@")
find_package(ggml REQUIRED HINTS ${LLAMA_LIB_DIR}/cmake)
+2 -2
View File
@@ -24,6 +24,6 @@ set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)
set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY)
set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY)
set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY)
set(CMAKE_C_FLAGS "-march=rv64gcv_zfh_zvfh_zba_zicbop -mabi=lp64d -fno-tree-vectorize -fno-tree-loop-vectorize ${CMAKE_C_FLAGS}")
set(CMAKE_CXX_FLAGS "-march=rv64gcv_zfh_zvfh_zba_zicbop -mabi=lp64d -fno-tree-vectorize -fno-tree-loop-vectorize ${CMAKE_CXX_FLAGS}")
set(CMAKE_C_FLAGS "-march=rv64gcv_zfh_zba_zicbop -mabi=lp64d ${CMAKE_C_FLAGS}")
set(CMAKE_CXX_FLAGS "-march=rv64gcv_zfh_zba_zicbop -mabi=lp64d ${CXX_FLAGS}")
set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -latomic")
+78 -159
View File
@@ -4,6 +4,7 @@
#include "chat.h"
#include "common.h"
#include "download.h"
#include "hf-cache.h"
#include "json-schema-to-grammar.h"
#include "log.h"
#include "sampling.h"
@@ -307,14 +308,12 @@ static bool common_params_handle_remote_preset(common_params & params, llama_exa
common_download_opts opts;
opts.bearer_token = params.hf_token;
opts.offline = params.offline;
LOG_TRC("%s: looking for remote preset at %s\n", __func__, preset_url.c_str());
const int status = common_download_file_single(preset_url, preset_path, opts);
const bool has_preset = status >= 200 && status < 400;
// remote preset is optional, so we don't error out if not found
if (has_preset) {
LOG_TRC("%s: applying remote preset from %s\n", __func__, preset_url.c_str());
LOG_INF("applying remote preset from %s\n", preset_url.c_str());
common_preset_context ctx(ex, /* only_remote_allowed */ true);
common_preset global;
auto remote_presets = ctx.load_from_ini(preset_path, global);
@@ -327,7 +326,7 @@ static bool common_params_handle_remote_preset(common_params & params, llama_exa
throw std::runtime_error("Remote preset.ini does not contain [" + std::string(hf_tag) + "] section");
}
} else {
LOG_TRC("%s: no remote preset found, skipping\n", __func__);
LOG_INF("%s", "no remote preset found, skipping\n");
}
return has_preset;
@@ -336,15 +335,11 @@ static bool common_params_handle_remote_preset(common_params & params, llama_exa
struct handle_model_result {
bool found_mmproj = false;
common_params_model mmproj;
bool found_mtp = false;
common_params_model mtp;
};
static handle_model_result common_params_handle_model(struct common_params_model & model,
const std::string & bearer_token,
bool offline,
bool search_mtp = false) {
bool offline) {
handle_model_result result;
if (!model.docker_repo.empty()) {
@@ -359,10 +354,11 @@ static handle_model_result common_params_handle_model(struct common_params_model
common_download_opts opts;
opts.bearer_token = bearer_token;
opts.offline = offline;
auto download_result = common_download_model(model, opts, true, search_mtp);
auto download_result = common_download_model(model, opts, true);
if (download_result.model_path.empty()) {
throw std::runtime_error("failed to download model from Hugging Face");
LOG_ERR("error: failed to download model from Hugging Face\n");
exit(1);
}
model.name = model.hf_repo;
@@ -372,11 +368,6 @@ static handle_model_result common_params_handle_model(struct common_params_model
result.found_mmproj = true;
result.mmproj.path = download_result.mmproj_path;
}
if (!download_result.mtp_path.empty()) {
result.found_mtp = true;
result.mtp.path = download_result.mtp_path;
}
} else if (!model.url.empty()) {
if (model.path.empty()) {
auto f = string_split<std::string>(model.url, '#').front();
@@ -389,7 +380,8 @@ static handle_model_result common_params_handle_model(struct common_params_model
opts.offline = offline;
auto download_result = common_download_model(model, opts);
if (download_result.model_path.empty()) {
throw std::runtime_error("failed to download model from " + model.url);
LOG_ERR("error: failed to download model from %s\n", model.url.c_str());
exit(1);
}
}
@@ -443,37 +435,6 @@ static bool parse_bool_value(const std::string & value) {
// CLI argument parsing functions
//
void common_params_handle_models(common_params & params, llama_example curr_ex) {
const bool spec_type_draft_mtp = std::find(params.speculative.types.begin(),
params.speculative.types.end(),
COMMON_SPECULATIVE_TYPE_DRAFT_MTP) != params.speculative.types.end();
auto res = common_params_handle_model(params.model, params.hf_token, params.offline, spec_type_draft_mtp);
if (params.no_mmproj) {
params.mmproj = {};
} else if (res.found_mmproj && params.mmproj.path.empty() && params.mmproj.url.empty()) {
// optionally, handle mmproj model when -hf is specified
params.mmproj = res.mmproj;
}
// only download mmproj if the current example is using it
for (const auto & ex : mmproj_examples) {
if (curr_ex == ex) {
common_params_handle_model(params.mmproj, params.hf_token, params.offline);
break;
}
}
// when --spec-type mtp is set and no draft model was provided explicitly,
// fall back to the MTP head discovered alongside the -hf model
if (spec_type_draft_mtp && res.found_mtp &&
params.speculative.draft.mparams.path.empty() &&
params.speculative.draft.mparams.hf_repo.empty() &&
params.speculative.draft.mparams.url.empty()) {
params.speculative.draft.mparams.path = res.mtp.path;
}
common_params_handle_model(params.speculative.draft.mparams, params.hf_token, params.offline);
common_params_handle_model(params.vocoder.model, params.hf_token, params.offline);
}
static bool common_params_parse_ex(int argc, char ** argv, common_params_context & ctx_arg) {
common_params & params = ctx_arg.params;
@@ -536,11 +497,7 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
throw std::invalid_argument(string_format("error: invalid argument: %s", arg.c_str()));
}
if (!seen_args.insert(arg).second) {
const bool skip = (arg == "--spec-type");
if (!skip) {
LOG_WRN("DEPRECATED: argument '%s' specified multiple times, use comma-separated values instead (only last value will be used)\n", arg.c_str());
}
LOG_WRN("DEPRECATED: argument '%s' specified multiple times, use comma-separated values instead (only last value will be used)\n", arg.c_str());
}
auto & tmp = arg_to_options[arg];
auto opt = *tmp.first;
@@ -589,6 +546,12 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
// parse the first time to get -hf option (used for remote preset)
parse_cli_args();
// TODO: Remove later
try {
hf_cache::migrate_old_cache_to_hf_cache(params.hf_token, params.offline);
} catch (const std::exception & e) {
LOG_WRN("HF cache migration failed: %s\n", e.what());
}
// export_graph_ops loads only metadata
const bool skip_model_download = ctx_arg.ex == LLAMA_EXAMPLE_EXPORT_GRAPH_OPS;
@@ -625,7 +588,22 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
// handle model and download
if (!skip_model_download) {
common_params_handle_models(params, ctx_arg.ex);
auto res = common_params_handle_model(params.model, params.hf_token, params.offline);
if (params.no_mmproj) {
params.mmproj = {};
} else if (res.found_mmproj && params.mmproj.path.empty() && params.mmproj.url.empty()) {
// optionally, handle mmproj model when -hf is specified
params.mmproj = res.mmproj;
}
// only download mmproj if the current example is using it
for (const auto & ex : mmproj_examples) {
if (ctx_arg.ex == ex) {
common_params_handle_model(params.mmproj, params.hf_token, params.offline);
break;
}
}
common_params_handle_model(params.speculative.draft.mparams, params.hf_token, params.offline);
common_params_handle_model(params.vocoder.model, params.hf_token, params.offline);
}
// model is required (except for server)
@@ -897,11 +875,7 @@ bool common_params_to_map(int argc, char ** argv, llama_example ex, std::map<com
throw std::invalid_argument(string_format("error: invalid argument: %s", arg.c_str()));
}
if (!seen_args.insert(arg).second) {
const bool skip = (arg == "--spec-type");
if (!skip) {
LOG_WRN("DEPRECATED: argument '%s' specified multiple times, use comma-separated values instead (only last value will be used)\n", arg.c_str());
}
LOG_WRN("DEPRECATED: argument '%s' specified multiple times, use comma-separated values instead (only last value will be used)\n", arg.c_str());
}
auto opt = *arg_to_options[arg];
std::string val;
@@ -1334,15 +1308,12 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
}
).set_env("LLAMA_ARG_CTX_CHECKPOINTS").set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"-cms", "--checkpoint-min-step"}, "N",
string_format("minimum spacing between context checkpoints in tokens (default: %d, 0 = no minimum)", params.checkpoint_min_step),
{"-cpent", "--checkpoint-every-n-tokens"}, "N",
string_format("create a checkpoint every n tokens during prefill (processing), -1 to disable (default: %d)", params.checkpoint_every_nt),
[](common_params & params, int value) {
if (value < 0) {
throw std::invalid_argument("checkpoint-min-step must be non-negative");
}
params.checkpoint_min_step = value;
params.checkpoint_every_nt = value;
}
).set_env("LLAMA_ARG_CHECKPOINT_MIN_SPACING_NT").set_examples({LLAMA_EXAMPLE_SERVER}));
).set_env("LLAMA_ARG_CHECKPOINT_EVERY_NT").set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"-cram", "--cache-ram"}, "N",
string_format("set the maximum cache size in MiB (default: %d, -1 - no limit, 0 - disable)"
@@ -2248,7 +2219,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
if (llama_supports_rpc()) {
add_opt(common_arg(
{"--rpc"}, "SERVERS",
"comma-separated list of RPC servers (host:port)",
"comma separated list of RPC servers (host:port)",
[](common_params & params, const std::string & value) {
add_rpc_devices(value);
GGML_UNUSED(params);
@@ -2812,7 +2783,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, int value) {
params.embd_normalize = value;
}
).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_DEBUG}));
).set_examples({LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_DEBUG}));
add_opt(common_arg(
{"--embd-output-format"}, "FORMAT",
"empty = default, \"array\" = [[],[]...], \"json\" = openai style, \"json+\" = same \"json\" + cosine similarity matrix, \"raw\" = plain whitespace-delimited output (one embedding per line)",
@@ -2869,64 +2840,28 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.api_prefix = value;
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_API_PREFIX"));
// Deprecated: use --ui-config instead (kept for backward compat)
add_opt(common_arg(
{"--webui-config"}, "JSON",
"[DEPRECATED: use --ui-config] JSON that provides default WebUI settings (overrides WebUI defaults)",
"JSON that provides default WebUI settings (overrides WebUI defaults)",
[](common_params & params, const std::string & value) {
params.ui_config_json = value;
params.webui_config_json = value;
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_CONFIG"));
add_opt(common_arg(
{"--ui-config"}, "JSON",
"JSON that provides default UI settings (overrides UI defaults)",
[](common_params & params, const std::string & value) {
params.ui_config_json = value;
params.webui_config_json = value;
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI_CONFIG"));
// Deprecated: use --ui-config-file instead (kept for backward compat)
add_opt(common_arg(
{"--webui-config-file"}, "PATH",
"[DEPRECATED: use --ui-config-file] JSON file that provides default WebUI settings (overrides WebUI defaults)",
"JSON file that provides default WebUI settings (overrides WebUI defaults)",
[](common_params & params, const std::string & value) {
params.ui_config_json = read_file(value);
params.webui_config_json = params.ui_config_json;
params.webui_config_json = read_file(value);
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_CONFIG_FILE"));
add_opt(common_arg(
{"--ui-config-file"}, "PATH",
"JSON file that provides default UI settings (overrides UI defaults)",
[](common_params & params, const std::string & value) {
params.ui_config_json = read_file(value);
params.webui_config_json = params.ui_config_json;
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI_CONFIG_FILE"));
// Deprecated: use --ui-mcp-proxy instead (kept for backward compat)
add_opt(common_arg(
{"--webui-mcp-proxy"},
{"--no-webui-mcp-proxy"},
"[DEPRECATED: use --ui-mcp-proxy/--no-ui-mcp-proxy] experimental: whether to enable MCP CORS proxy",
string_format("experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: %s)", params.webui_mcp_proxy ? "enabled" : "disabled"),
[](common_params & params, bool value) {
params.ui_mcp_proxy = value;
params.webui_mcp_proxy = value;
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_MCP_PROXY"));
add_opt(common_arg(
{"--ui-mcp-proxy"},
{"--no-ui-mcp-proxy"},
"experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: disabled)",
[](common_params & params, bool value) {
params.ui_mcp_proxy = value;
params.webui_mcp_proxy = value;
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI_MCP_PROXY"));
add_opt(common_arg(
{"--tools"}, "TOOL1,TOOL2,...",
"experimental: whether to enable built-in tools for AI agents - do not enable in untrusted environments (default: no tools)\n"
@@ -2936,26 +2871,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.server_tools = parse_csv_row(value);
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_TOOLS"));
// Deprecated: use --ui/--no-ui instead (kept for backward compat)
add_opt(common_arg(
{"--webui"},
{"--no-webui"},
"[DEPRECATED: use --ui/--no-ui] whether to enable the Web UI",
string_format("whether to enable the Web UI (default: %s)", params.webui ? "enabled" : "disabled"),
[](common_params & params, bool value) {
params.ui = value;
params.webui = value;
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI"));
add_opt(common_arg(
{"--ui"},
{"--no-ui"},
string_format("whether to enable the Web UI (default: %s)", params.ui ? "enabled" : "disabled"),
[](common_params & params, bool value) {
params.ui = value;
params.webui = value;
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_UI"));
add_opt(common_arg(
{"--embedding", "--embeddings"},
string_format("restrict to only support embedding use case; use only with dedicated embedding models (default: %s)", params.embedding ? "enabled" : "disabled"),
@@ -2998,7 +2921,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
}
key_file.close();
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_API_KEY_FILE"));
).set_examples({LLAMA_EXAMPLE_SERVER}));
add_opt(common_arg(
{"--ssl-key-file"}, "FNAME",
"path to file a PEM-encoded SSL private key",
@@ -3026,7 +2949,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.default_template_kwargs[item.key()] = item.value().dump();
}
}
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_CHAT_TEMPLATE_KWARGS"));
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_CHAT_TEMPLATE_KWARGS"));
add_opt(common_arg(
{"-to", "--timeout"}, "N",
string_format("server read/write timeout in seconds (default: %d)", params.timeout_read),
@@ -3327,7 +3250,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params &, const std::string & value) {
common_log_set_file(common_log_main(), value.c_str());
}
).set_env("LLAMA_ARG_LOG_FILE"));
).set_env("LLAMA_LOG_FILE"));
add_opt(common_arg(
{"--log-colors"}, "[on|off|auto]",
"Set colored logging ('on', 'off', or 'auto', default: 'auto')\n"
@@ -3344,7 +3267,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
string_format("error: unknown value for --log-colors: '%s'\n", value.c_str()));
}
}
).set_env("LLAMA_ARG_LOG_COLORS"));
).set_env("LLAMA_LOG_COLORS"));
add_opt(common_arg(
{"-v", "--verbose", "--log-verbose"},
"Set verbosity level to infinity (i.e. log all messages, useful for debugging)",
@@ -3359,7 +3282,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params) {
params.offline = true;
}
).set_env("LLAMA_ARG_OFFLINE"));
).set_env("LLAMA_OFFLINE"));
add_opt(common_arg(
{"-lv", "--verbosity", "--log-verbosity"}, "N",
string_format("Set the verbosity threshold. Messages with a higher verbosity will be ignored. Values:\n"
@@ -3367,30 +3290,27 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
" - 1: error\n"
" - 2: warning\n"
" - 3: info\n"
" - 4: trace (more info)\n"
" - 5: debug\n"
" - 4: debug\n"
"(default: %d)\n", params.verbosity),
[](common_params & params, int value) {
params.verbosity = value;
common_log_set_verbosity_thold(value);
}
).set_env("LLAMA_ARG_LOG_VERBOSITY"));
).set_env("LLAMA_LOG_VERBOSITY"));
add_opt(common_arg(
{"--log-prefix"},
{"--no-log-prefix"},
"Enable prefix in log messages",
[](common_params &, bool value) {
common_log_set_prefix(common_log_main(), value);
[](common_params &) {
common_log_set_prefix(common_log_main(), true);
}
).set_env("LLAMA_ARG_LOG_PREFIX"));
).set_env("LLAMA_LOG_PREFIX"));
add_opt(common_arg(
{"--log-timestamps"},
{"--no-log-timestamps"},
"Enable timestamps in log messages",
[](common_params &, bool value) {
common_log_set_timestamps(common_log_main(), value);
[](common_params &) {
common_log_set_timestamps(common_log_main(), true);
}
).set_env("LLAMA_ARG_LOG_TIMESTAMPS"));
).set_env("LLAMA_LOG_TIMESTAMPS"));
//
// speculative parameters
@@ -3594,15 +3514,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.speculative.draft.p_min = std::stof(value);
}
).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_P_MIN"));
add_opt(common_arg(
{"--spec-draft-backend-sampling"},
{"--no-spec-draft-backend-sampling"},
string_format("offload draft sampling to the backend (default: %s)",
params.speculative.draft.backend_sampling ? "enabled" : "disabled"),
[](common_params & params, bool value) {
params.speculative.draft.backend_sampling = value;
}
).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_BACKEND_SAMPLING"));
add_opt(common_arg(
{"--spec-draft-device", "-devd", "--device-draft"}, "<dev1,dev2,..>",
"comma-separated list of devices to use for offloading the draft model (none = don't offload)\n"
@@ -3639,13 +3550,27 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
}
).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_MODEL"));
add_opt(common_arg(
{"--spec-type"}, common_speculative_all_types_str(),
string_format("comma-separated list of types of speculative decoding to use (default: %s)\n",
common_speculative_type_name_str(params.speculative.types).c_str()),
{"--spec-type"}, "[none|mtp|ngram-cache|ngram-simple|ngram-map-k|ngram-map-k4v|ngram-mod]",
string_format("type of speculative decoding to use when no draft model is provided (default: %s)\n",
common_speculative_type_to_str(params.speculative.type).c_str()),
[](common_params & params, const std::string & value) {
const auto types_str = string_split<std::string>(value, ',');
auto types = common_speculative_types_from_names(types_str);
params.speculative.types.insert(params.speculative.types.end(), types.begin(), types.end());
if (value == "none") {
params.speculative.type = COMMON_SPECULATIVE_TYPE_NONE;
} else if (value == "mtp") {
params.speculative.type = COMMON_SPECULATIVE_TYPE_MTP;
} else if (value == "ngram-cache") {
params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_CACHE;
} else if (value == "ngram-simple") {
params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_SIMPLE;
} else if (value == "ngram-map-k") {
params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K;
} else if (value == "ngram-map-k4v") {
params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K4V;
} else if (value == "ngram-mod") {
params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MOD;
} else {
throw std::invalid_argument("unknown speculative decoding type without draft model");
}
}
).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_TYPE"));
add_opt(common_arg(
@@ -4134,16 +4059,10 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
{"--spec-default"},
string_format("enable default speculative decoding config"),
[](common_params & params) {
params.speculative.types.push_back(COMMON_SPECULATIVE_TYPE_NGRAM_MOD);
params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MOD;
params.speculative.ngram_mod.n_match = 24;
params.speculative.ngram_mod.n_min = 48;
params.speculative.ngram_mod.n_max = 64;
// TODO: not sure if this is a good config - explore more settings and potentially enable it
//params.speculative.types.push_back(COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K4V);
//params.speculative.ngram_map_k4v.size_n = 8;
//params.speculative.ngram_map_k4v.size_m = 24;
//params.speculative.ngram_map_k4v.min_hits = 2;
}
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
-3
View File
@@ -129,8 +129,5 @@ bool common_params_to_map(int argc, char ** argv, llama_example ex, std::map<com
// see: https://github.com/ggml-org/llama.cpp/issues/18163
void common_params_add_preset_options(std::vector<common_arg> & args);
// Populate model paths (main model, mmproj, etc) from -hf if necessary
void common_params_handle_models(common_params & params, llama_example curr_ex);
// initialize argument parser context - used by test-arg-parser and preset
common_params_context common_params_parser_init(common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr);
+9 -29
View File
@@ -43,33 +43,11 @@ common_chat_params peg_generator::generate_parser(const common_chat_template &
const autoparser & autoparser) {
// Create the result structure
common_chat_params data;
data.prompt = common_chat_template_direct_apply(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.preserved_tokens = autoparser.preserved_tokens;
data.prompt = common_chat_template_direct_apply(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.preserved_tokens = autoparser.preserved_tokens;
std::string parser_generation_prompt = data.generation_prompt;
if (inputs.continue_final_message != COMMON_CHAT_CONTINUATION_NONE && !inputs.continue_msg.empty()) {
// Build up generation prompt manually
const auto & msg = inputs.continue_msg;
if (!autoparser.reasoning.start.empty()) {
data.generation_prompt = data.generation_prompt.substr(0, data.generation_prompt.find(autoparser.reasoning.start));
data.generation_prompt += autoparser.reasoning.start + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += autoparser.reasoning.end;
}
}
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = autoparser.build_parser(inputs, parser_generation_prompt);
auto parser = autoparser.build_parser(inputs);
data.parser = parser.save();
// Build grammar if tools are present
@@ -109,7 +87,7 @@ common_chat_params peg_generator::generate_parser(const common_chat_template &
return data;
}
common_peg_arena autoparser::build_parser(const generation_params & inputs, const std::string & generation_prompt) const {
common_peg_arena autoparser::build_parser(const generation_params & inputs) const {
if (!analysis_complete) {
throw std::invalid_argument("Cannot call build_parser on autoparser without performing analysis first, call analyze_template(...)");
}
@@ -143,7 +121,7 @@ common_peg_arena autoparser::build_parser(const generation_params & inputs, cons
} else {
parser = content.build_parser(ctx);
}
return pure_content ? p.prefix(generation_prompt, reasoning.start) + parser : p.prefix(generation_prompt, reasoning.start) << parser;
return pure_content ? p.prefix(inputs.generation_prompt, reasoning.start) + parser : p.prefix(inputs.generation_prompt, reasoning.start) << parser;
});
}
@@ -391,7 +369,9 @@ common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_conte
arguments.name_suffix) +
arguments.value_prefix +
(schema_info.resolves_to_string(param_schema) ?
p.tool_arg_string_value(until_suffix) :
p.tool_arg_string_value(p.schema(until_suffix,
"tool-" + name + "-arg-" + param_name + "-schema",
param_schema, true)) :
p.tool_arg_json_value(p.schema(
p.json(), "tool-" + name + "-arg-" + param_name + "-schema", param_schema, false)) +
p.space()) +
+2 -4
View File
@@ -310,8 +310,6 @@ std::vector<segment> prune_whitespace_segments(const std::vector<segment> & segm
namespace autoparser {
static const std::string ERR_TMPL = "#**ERROR**#";
std::string apply_template(const common_chat_template & tmpl, const template_params & params) {
generation_params tmpl_params;
tmpl_params.messages = params.messages;
@@ -328,7 +326,7 @@ std::string apply_template(const common_chat_template & tmpl, const template_par
return common_chat_template_direct_apply(tmpl, tmpl_params);
} catch (const std::exception & e) {
LOG_DBG("Template application failed: %s\n", e.what());
return ERR_TMPL;
return "";
}
}
@@ -349,7 +347,7 @@ std::optional<compare_variants_result> compare_variants(
std::string output_B = apply_template(tmpl, params_B);
// Check for template application failures
if (output_A == ERR_TMPL || output_B == ERR_TMPL) {
if (output_A.empty() || output_B.empty()) {
return std::nullopt;
}
+5 -16
View File
@@ -60,21 +60,16 @@ struct generation_params {
common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_AUTO;
bool stream = true;
std::string grammar;
bool add_generation_prompt = false;
common_chat_continuation continue_final_message = COMMON_CHAT_CONTINUATION_NONE;
common_chat_msg continue_msg;
bool enable_thinking = true;
std::chrono::system_clock::time_point now = std::chrono::system_clock::now();
bool add_generation_prompt = false;
bool enable_thinking = true;
std::chrono::system_clock::time_point now = std::chrono::system_clock::now();
std::string generation_prompt;
json extra_context;
bool add_bos = false;
bool add_eos = false;
bool is_inference = true;
bool add_inference = false;
bool mark_input = true; // whether to mark input strings in the jinja context
bool has_continuation() const {
return continue_final_message != COMMON_CHAT_CONTINUATION_NONE && !continue_msg.empty();
}
};
// ============================================================================
@@ -377,8 +372,6 @@ struct analyze_tools : analyze_base {
struct autoparser {
jinja::caps jinja_caps;
std::string user_start;
std::string assistant_start;
analyze_reasoning reasoning;
analyze_content content;
analyze_tools tools;
@@ -389,15 +382,11 @@ struct autoparser {
autoparser() = default;
// Find the starting marker for the user message and assistant message
std::string detect_user_start_marker(const common_chat_template & tmpl);
std::string detect_assistant_start_marker(const common_chat_template & tmpl);
// Run full differential analysis on a template
void analyze_template(const common_chat_template & tmpl);
// Build the PEG parser for this template
common_peg_arena build_parser(const generation_params & inputs, const std::string & generation_prompt) const;
common_peg_arena build_parser(const generation_params & inputs) const;
private:
// Collect tokens from entire analysis to preserve
+1 -176
View File
@@ -8,9 +8,6 @@
#include "peg-parser.h"
#include <algorithm>
#include <cctype>
#include <ostream>
#include <sstream>
#define ANSI_RESET "\033[0m"
#define ANSI_PURPLE "\033[1m\x1b[38;5;126m"
@@ -26,7 +23,6 @@ static const std::string FUN_SECOND = "SSS_SECOND_FUN_S";
static const std::string ARG_FIRST = "AA_ARG_FST_AA";
static const std::string ARG_SECOND = "BB_ARG_SND_BB";
static const std::string USER_MSG = "U_USER_MSG Hello END_U";
static const std::string USER_MSG_TWO = "V_USER_MSG Hello END_V";
static const std::string ASSISTANT_MSG = "A_ASST_MSG I can help END_A";
static const std::string THINKING_CONTENT = "REASON_PART I am thinking END_R";
static const std::string CALL_ID_001 = "call00001";
@@ -75,7 +71,6 @@ static std::vector<std::function<void(const common_chat_template & tmpl, autopar
analysis.content.end = "<|END_OF_TURN_TOKEN|>";
analysis.preserved_tokens.push_back("<|CHATBOT_TOKEN|>");
analysis.preserved_tokens.push_back("<|END_OF_TURN_TOKEN|>");
analysis.user_start = "<|START_OF_TURN_TOKEN|><|USER_TOKEN|>";
LOG_DBG(ANSI_ORANGE "[Patch: Cohere Command R+]\n" ANSI_RESET);
}
},
@@ -113,59 +108,7 @@ static std::vector<std::function<void(const common_chat_template & tmpl, autopar
analysis.tools.function.close = "```";
LOG_DBG(ANSI_ORANGE "[Patch: DeepSeek-R1-Distill-Qwen]\n" ANSI_RESET);
}
},
// Nemotron Nano v2
[](const common_chat_template & tmpl, autoparser & analysis) -> void {
if (tmpl.src.find("<SPECIAL_10>") != std::string::npos && tmpl.src.find("<SPECIAL_11>") != std::string::npos &&
tmpl.src.find("<SPECIAL_12>") != std::string::npos && tmpl.src.find("<TOOL_RESPONSE>") != std::string::npos) {
analysis.tools.format.mode = tool_format::JSON_NATIVE;
analysis.tools.format.section_start = "";
analysis.tools.format.section_end = "";
analysis.tools.format.per_call_start = "<TOOLCALL>";
analysis.tools.format.per_call_end = "</TOOLCALL>";
analysis.content.mode = content_mode::PLAIN;
analysis.content.start = "";
analysis.content.end = "";
analysis.reasoning.mode = reasoning_mode::TAG_BASED;
analysis.reasoning.start = "<think>\n\n";
analysis.reasoning.end = "</think>";
analysis.assistant_start = "<SPECIAL_11>Assistant";
analysis.user_start = "<SPECIAL_11>User";
analysis.preserved_tokens.clear();
analysis.preserved_tokens.push_back("<SPECIAL_12>");
analysis.preserved_tokens.push_back("<SPECIAL_11>");
analysis.preserved_tokens.push_back("</think>");
analysis.preserved_tokens.push_back("<TOOLCALL>");
analysis.preserved_tokens.push_back("</TOOLCALL>");
LOG_DBG(ANSI_ORANGE "[Patch: Nemotron Nano v2]\n" ANSI_RESET);
}
},
// Fireworks
[](const common_chat_template & tmpl, autoparser & analysis) -> void {
if (tmpl.src.find("{%- set system_prompt = '<|start_header_id|>' + 'system' + '<|end_header_id|>\\n\\n'"
" + message['content'] | trim + '\\n' + system_prompt_suffix + '<|eot_id|>' -%}") != std::string::npos) {
analysis.assistant_start = "<|start_header_id|>assistant<|end_header_id|>";
analysis.user_start = "<|start_header_id|>user<|end_header_id|>";
LOG_DBG(ANSI_ORANGE "[Patch: Fireworks v2]\n" ANSI_RESET);
}
},
// Solar Open
[](const common_chat_template & tmpl, autoparser & analysis) -> void {
if (tmpl.src.find("<|begin|>assistant<|think|><|end|>") != std::string::npos) {
analysis.assistant_start = "<|begin|>assistant";
LOG_DBG(ANSI_ORANGE "[Patch: Solar Open]\n" ANSI_RESET);
}
},
// Apriel 1.6
[](const common_chat_template & tmpl, autoparser & analysis) -> void {
if (tmpl.src.find("if not loop.last and '[BEGIN FINAL RESPONSE]' in asst_text") != std::string::npos) {
analysis.user_start = "<|begin_user|>";
analysis.assistant_start = "<|begin_assistant|>";
LOG_DBG(ANSI_ORANGE "[Patch: Apriel 1.6]\n" ANSI_RESET);
}
},
}
});
// Common JSON structures
@@ -223,8 +166,6 @@ void autoparser::analyze_template(const common_chat_template & tmpl) {
reasoning = analyze_reasoning(tmpl, jinja_caps.supports_tool_calls);
content = analyze_content(tmpl, reasoning);
tools = analyze_tools(jinja_caps.supports_tool_calls ? analyze_tools(tmpl, jinja_caps, reasoning) : analyze_tools());
assistant_start = detect_assistant_start_marker(tmpl);
user_start = detect_user_start_marker(tmpl);
collect_preserved_tokens();
for (auto & workaround : workarounds) {
@@ -232,8 +173,6 @@ void autoparser::analyze_template(const common_chat_template & tmpl) {
}
LOG_DBG("\n--- Reasoning & Content Structure ---\n");
LOG_DBG("user_msg_start: %s\n", user_start.c_str());
LOG_DBG("assistant_msg_start: %s\n", assistant_start.c_str());
LOG_DBG("reasoning_mode: %s\n", mode_to_str(reasoning.mode).c_str());
LOG_DBG("reasoning_start: '%s'\n", reasoning.start.c_str());
LOG_DBG("reasoning_end: '%s'\n", reasoning.end.c_str());
@@ -306,120 +245,6 @@ void autoparser::collect_preserved_tokens() {
add_token(tools.call_id.suffix);
}
std::string autoparser::detect_assistant_start_marker(const common_chat_template & tmpl) {
json user_msg = json{
{ "role", "user" },
{ "content", USER_MSG }
};
json assistant_no_reasoning = json{
{ "role", "assistant" },
{ "content", ASSISTANT_MSG }
};
template_params params;
params.messages = json::array({ user_msg });
params.add_generation_prompt = false;
params.enable_thinking = true;
auto comparison = compare_variants(
tmpl, params, [&](template_params & p) {
p.messages = json::array({ user_msg, assistant_no_reasoning });
}
);
if (!comparison) {
LOG_DBG(ANSI_ORANGE "%s: Template application failed, skipping assistant start detection\n" ANSI_RESET, __func__);
return "";
}
auto usermsg = comparison->diff.right;
if (usermsg.find(ASSISTANT_MSG) == std::string::npos) {
LOG_DBG(ANSI_ORANGE "%s: Did not find assistant message in assistant message block, skipping detection\n" ANSI_RESET, __func__);
}
auto ast_prefix = usermsg.substr(0, usermsg.find(ASSISTANT_MSG));
if (!reasoning.start.empty() && ast_prefix.find(trim_whitespace(reasoning.start)) != std::string::npos) {
ast_prefix = ast_prefix.substr(0, ast_prefix.find(trim_whitespace(reasoning.start)));
}
if (!reasoning.end.empty() && ast_prefix.find(trim_whitespace(reasoning.end)) != std::string::npos) {
ast_prefix = ast_prefix.substr(0, ast_prefix.find(trim_whitespace(reasoning.end)));
}
return trim_whitespace(ast_prefix);
}
std::string autoparser::detect_user_start_marker(const common_chat_template & tmpl) {
json user_msg = json{
{ "role", "user" },
{ "content", USER_MSG }
};
json assistant = json{
{ "role", "assistant" },
{ "content", ASSISTANT_MSG }
};
json user_msg_two = json{
{ "role", "user" },
{ "content", USER_MSG_TWO }
};
template_params params;
params.messages = json::array({});
params.add_generation_prompt = false;
params.enable_thinking = true;
auto comparison = compare_variants(
tmpl, params, [&](template_params & p) {
p.messages = json::array({ user_msg });
}
);
if (!comparison) {
LOG_DBG(ANSI_ORANGE "%s: Template application failed, unsupported empty messages? trying complex variant\n" ANSI_RESET, __func__);
params.messages = json::array({ user_msg_two, assistant });
comparison = compare_variants(
tmpl, params, [&](template_params & p) {
p.messages = json::array({ user_msg_two, assistant, user_msg });
}
);
if (!comparison) {
LOG_DBG(ANSI_ORANGE "%s: Template application failed for reserve variant, aborting\n" ANSI_RESET, __func__);
return "";
}
}
auto usermsg = comparison->diff.right;
if (usermsg.find(USER_MSG) == std::string::npos) {
LOG_DBG(ANSI_ORANGE "%s: Did not find user message in user message block, aborting detection\n" ANSI_RESET, __func__);
}
if (usermsg.find(ASSISTANT_MSG) != std::string::npos) {
usermsg = usermsg.substr(usermsg.find(ASSISTANT_MSG) + ASSISTANT_MSG.size());
}
auto candidate = usermsg.substr(0, usermsg.find(USER_MSG));
auto candidate_split = segmentize_markers(candidate);
std::stringstream result;
bool encountered_marker = false;
for (const auto & mrk : candidate_split) {
std::string lower_mrk = std::string(mrk.value);
std::transform(lower_mrk.begin(), lower_mrk.end(), lower_mrk.begin(),
[](unsigned char c) { return std::tolower(c); });
// heuristic to weed out potential end markers, but only at the start
if (mrk.type == segment_type::MARKER && !encountered_marker &&
(lower_mrk.find("end") != std::string::npos || lower_mrk.find("close") != std::string::npos)) {
continue;
}
if (mrk.type == segment_type::TEXT && !encountered_marker && trim_whitespace(mrk.value).empty()) {
continue;
}
encountered_marker |= mrk.type == segment_type::MARKER;
result << mrk.value;
}
return trim_whitespace(result.str());
}
analyze_reasoning::analyze_reasoning(const common_chat_template & tmpl, bool supports_tools)
: analyze_base(tmpl) {
LOG_DBG(ANSI_PURPLE "=== Starting differential analysis ===\n" ANSI_RESET);
+30 -2
View File
@@ -358,7 +358,35 @@ void common_chat_peg_mapper::map(const common_peg_ast_node & node) {
if (is_potential_container) {
value_content = normalize_container_value(value_content);
}
value_to_add += value_content;
// Try to parse as JSON value (number, bool, null, object, array)
try {
ordered_json parsed = ordered_json::parse(value_content);
if (parsed.is_string()) {
// Don't add closing quote yet (added by arg_close) for monotonic streaming
std::string escaped = parsed.dump();
if (!escaped.empty() && escaped.back() == '"') {
escaped.pop_back();
}
value_to_add = escaped;
closing_quote_pending = true;
} else {
// Non-string values: use raw content to preserve whitespace for monotonicity
value_to_add = value_content;
}
} catch (...) {
if (node.is_partial && is_potential_container) {
// Partial container: pass through the already-normalized content
value_to_add = value_content;
} else {
// Not valid JSON - treat as string value
if (!closing_quote_pending) {
value_to_add = "\"";
closing_quote_pending = true;
}
value_to_add += escape_json_string_inner(value_content);
}
}
}
args_target() += value_to_add;
@@ -785,7 +813,7 @@ common_peg_parser common_chat_peg_builder::prefix(const std::string & s, const s
if (delimiter.empty()) {
return literal(s);
}
return literal(s.substr(0, s.find(delimiter)));
return literal(s.substr(0, s.rfind(delimiter)));
}
common_peg_parser common_chat_peg_builder::optspace(const std::string & tag) {
+1 -1
View File
@@ -90,7 +90,7 @@ class common_chat_peg_builder : public common_peg_parser_builder {
// Use for schema-declared string types - won't be treated as potential JSON container
common_peg_parser tool_arg_string_value(const common_peg_parser & p) { return tag(TOOL_ARG_STRING_VALUE, p); }
common_peg_parser tool_arg_json_value(const common_peg_parser & p) { return tag(TOOL_ARG_VALUE, p); }
common_peg_parser tool_arg_json_value(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_VALUE, p)); }
// Return a parser that parses the prefix of a string, up to a given delimiter.
+41 -279
View File
@@ -70,65 +70,6 @@ static bool has_content_or_tool_calls(const common_chat_msg & msg) {
return !msg.content.empty() || !msg.tool_calls.empty();
}
std::string common_chat_msg::render_content(const std::string & delimiter) const {
if (!content.empty() && !content_parts.empty()) {
throw std::runtime_error("Cannot specify both content and content_parts");
}
if (!content.empty()) {
return content;
}
std::string text;
for (const auto & part : content_parts) {
if (part.type == "text") {
if (!text.empty()) {
text += delimiter;
}
text += part.text;
}
}
return text;
}
std::vector<common_chat_msg_span> common_chat_split_by_role(const std::string & prompt, const std::vector<common_chat_msg_delimiter> & delims) {
if (delims.empty() || prompt.empty()) {
return {};
}
auto parser = build_peg_parser([&](common_peg_parser_builder & p) {
std::vector<std::string> all_delims;
std::vector<common_peg_parser> tagged_messages;
all_delims.reserve(delims.size());
tagged_messages.reserve(delims.size());
for (const auto & d : delims) {
all_delims.push_back(d.delimiter);
}
auto any_delim = p.until_one_of(all_delims);
for (const auto & d : delims) {
tagged_messages.push_back(p.tag(d.role, p.literal(d.delimiter) + any_delim));
}
return any_delim + p.zero_or_more(p.choice(tagged_messages)) + p.end();
});
common_peg_parse_context ctx(prompt);
const auto result = parser.parse(ctx);
if (!result.success()) {
return {};
}
std::vector<common_chat_msg_span> spans;
ctx.ast.visit(result, [&](const common_peg_ast_node & node) {
if (!node.tag.empty()) {
spans.push_back({ node.tag, node.start, node.end - node.start });
}
});
return spans;
}
json common_chat_msg::to_json_oaicompat(bool concat_typed_text) const {
if (!content.empty() && !content_parts.empty()) {
throw std::runtime_error("Cannot specify both content and content_parts");
@@ -510,22 +451,6 @@ std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const json & too
return result;
}
common_chat_continuation common_chat_continuation_parse(const nlohmann::ordered_json & value) {
if (value.is_boolean() && value.get<bool>()) {
return COMMON_CHAT_CONTINUATION_AUTO;
}
if (value.is_string()) {
auto value_str = value.get<std::string>();
if (value_str == "reasoning_content") {
return COMMON_CHAT_CONTINUATION_REASONING;
}
if (value_str == "content") {
return COMMON_CHAT_CONTINUATION_CONTENT;
}
}
return COMMON_CHAT_CONTINUATION_NONE;
}
bool common_chat_verify_template(const std::string & tmpl, bool use_jinja) {
if (use_jinja) {
try {
@@ -886,36 +811,6 @@ std::string common_chat_template_direct_apply(
return common_chat_template_direct_apply_impl(tmpl, inputs, std::nullopt, std::nullopt, std::nullopt);
}
static std::string common_chat_template_generation_prompt_impl(
const common_chat_template & tmpl,
const autoparser::generation_params & inputs,
const std::optional<json> & messages_override = std::nullopt,
const std::optional<json> & tools_override = std::nullopt,
const std::optional<json> & additional_context = std::nullopt) {
auto adjusted_messages = messages_override ? *messages_override : inputs.messages;
autoparser::generation_params params = inputs;
params.add_generation_prompt = false;
params.continue_final_message = COMMON_CHAT_CONTINUATION_NONE;
std::string no_gen_prompt = common_chat_template_direct_apply_impl(tmpl, params, adjusted_messages, tools_override, additional_context);
params.add_generation_prompt = true;
std::string gen_prompt = common_chat_template_direct_apply_impl(tmpl, params, adjusted_messages, tools_override, additional_context);
size_t prefix_len = 0;
size_t min_size = std::min(no_gen_prompt.size(), gen_prompt.size());
while (prefix_len < min_size && no_gen_prompt[prefix_len] == gen_prompt[prefix_len]) {
prefix_len++;
}
return gen_prompt.substr(prefix_len);
}
std::string common_chat_template_generation_prompt(
const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
return common_chat_template_generation_prompt_impl(tmpl, inputs, std::nullopt, std::nullopt, std::nullopt);
}
static common_chat_params common_chat_params_init_ministral_3(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
@@ -968,7 +863,6 @@ static common_chat_params common_chat_params_init_ministral_3(const common_chat_
data.thinking_start_tag = "[THINK]";
data.thinking_end_tag = "[/THINK]";
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs, /* messages_override = */ adjusted_messages);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs, /* messages_override = */ adjusted_messages);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.preserved_tokens = {
"[THINK]",
@@ -977,19 +871,8 @@ static common_chat_params common_chat_params_init_ministral_3(const common_chat_
"[ARGS]",
};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "[THINK]" + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += "[/THINK]" + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.eps();
auto generation_prompt = p.prefix(inputs.generation_prompt, "[THINK]");
auto reasoning =
extract_reasoning ? p.optional("[THINK]" + p.reasoning(p.until("[/THINK]")) + "[/THINK]") : p.eps();
@@ -1080,15 +963,6 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
}
data.prompt = prompt;
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs, /* messages_override= */ adjusted_messages);
data.message_spans = common_chat_split_by_role(prompt, {
{ "assistant", "<|start|>assistant" },
{ "user", "<|start|>user" },
{ "system", "<|start|>developer" },
{ "system", "<|start|>system" },
{ "tool", "<|start|>functions" },
});
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
@@ -1098,18 +972,6 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
"<|channel|>", "<|constrain|>", "<|message|>", "<|start|>", "<|end|>",
};
// Adjust prompt for continuation
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "<|start|>assistant<|channel|>analysis<|message|>" + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += "<|end|><|start|>assistant<|channel|>final<|message|>" + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = !inputs.json_schema.is_null() && inputs.json_schema.is_object();
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
@@ -1218,21 +1080,14 @@ static common_chat_params common_chat_params_init_gemma4(const common_chat_templ
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
if (inputs.add_generation_prompt && string_ends_with(data.prompt, "<turn|>\n")) {
// This may happen if the model generates content + tool_call, the
// template does not add the model's next turn and confuses the model
// from emitting its proper reasoning token sequence.
data.generation_prompt = "<|turn>model\n";
data.prompt += data.generation_prompt;
data.prompt += "<|turn>model\n";
}
data.message_spans = common_chat_split_by_role(data.prompt, {
{ "user", "<|turn>user\n" },
{ "assistant", "<|turn>model\n" },
});
data.format = COMMON_CHAT_FORMAT_PEG_GEMMA4;
data.supports_thinking = true;
data.thinking_start_tag = "<|channel>thought";
@@ -1246,25 +1101,13 @@ static common_chat_params common_chat_params_init_gemma4(const common_chat_templ
"<|turn>",
};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = string_ends_with(data.prompt, "<turn|>\n") ? "<|turn>model\n" : "";
data.generation_prompt += "<|channel>thought\n" + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += "<channel|>" + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = !inputs.json_schema.is_null() && inputs.json_schema.is_object();
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto start = p.rule("start", p.optional(p.literal("<|turn>model\n")));
auto start = p.rule("start", p.prefix(inputs.generation_prompt, "<|channel>"));
if (extract_reasoning) {
p.rule("thought", p.literal("<|channel>thought") + p.space() + p.reasoning(p.until("<channel|>")) + p.literal("<channel|>"));
@@ -1381,22 +1224,15 @@ static common_chat_params common_chat_params_init_functionary_v3_2(const common_
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.preserved_tokens = {
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.preserved_tokens = {
">>>all",
};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto include_grammar = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "<|start_header_id|>assistant<|end_header_id|>\n\n>>>all\n" + msg.render_content();
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
// Functionary v3.2 format:
// - Normal content: >>>all\n{content}
@@ -1408,7 +1244,7 @@ static common_chat_params common_chat_params_init_functionary_v3_2(const common_
// When no tools, content goes until end
auto content_until_tool = p.literal("all\n") + p.content(p.until(">>>"));
auto content_until_end = p.literal("all\n") + p.content(p.rest());
auto generation_prompt = p.literal("<|start_header_id|>assistant<|end_header_id|>\n\n>>>");
auto generation_prompt = p.literal(inputs.generation_prompt);
// If no tools or tool_choice is NONE, just parse content
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
@@ -1482,10 +1318,9 @@ static common_chat_params common_chat_params_init_kimi_k2(const common_chat_temp
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.preserved_tokens = {
"<|tool_calls_section_begin|>",
"<|tool_calls_section_end|>",
@@ -1508,22 +1343,10 @@ static common_chat_params common_chat_params_init_kimi_k2(const common_chat_temp
const std::string THINK_START = "<think>";
const std::string THINK_END = "</think>";
const std::string GEN_PROMPT = "<|im_assistant|>assistant<|im_middle|>";
data.thinking_start_tag = THINK_START;
data.thinking_end_tag = THINK_END;
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
// Kimi K2 Thinking format:
// - Reasoning: <think>{reasoning}</think>
@@ -1543,7 +1366,7 @@ static common_chat_params common_chat_params_init_kimi_k2(const common_chat_temp
auto reasoning = extract_reasoning ? p.optional(THINK_START + p.reasoning(
p.until_one_of({ THINK_END, "<|tool_calls_section_begin|>", "<|tool_call_begin|>" })) +
p.optional(p.literal(THINK_END))) : p.eps();
auto generation_prompt = p.literal(GEN_PROMPT);
auto generation_prompt = p.prefix(inputs.generation_prompt, THINK_START);
// Content only parser (no tools)
@@ -1619,7 +1442,6 @@ static common_chat_params common_chat_params_init_lfm2(const common_chat_templat
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.preserved_tokens = {
@@ -1639,24 +1461,12 @@ static common_chat_params common_chat_params_init_lfm2(const common_chat_templat
const std::string TOOL_CALL_END = "<|tool_call_end|>";
const std::string THINK_START = "<think>";
const std::string THINK_END = "</think>";
const std::string GEN_PROMPT = "<|im_start|>assistant\n";
data.thinking_start_tag = THINK_START;
data.thinking_end_tag = THINK_END;
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.literal(GEN_PROMPT);
auto generation_prompt = p.prefix(inputs.generation_prompt, THINK_START);
auto end = p.end();
auto reasoning = p.eps();
@@ -1711,7 +1521,6 @@ static common_chat_params common_chat_params_init_lfm2_5(const common_chat_templ
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.preserved_tokens = {
@@ -1727,24 +1536,12 @@ static common_chat_params common_chat_params_init_lfm2_5(const common_chat_templ
const std::string THINK_START = "<think>";
const std::string THINK_END = "</think>";
const std::string GEN_PROMPT = "<|im_start|>assistant\n";
data.thinking_start_tag = THINK_START;
data.thinking_end_tag = THINK_END;
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.literal(GEN_PROMPT);
auto generation_prompt = p.prefix(inputs.generation_prompt, THINK_START);
auto end = p.end();
auto reasoning = p.eps();
@@ -1795,7 +1592,6 @@ static common_chat_params common_chat_params_init_gigachat_v3(
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = false;
data.preserved_tokens = {
@@ -1803,12 +1599,6 @@ static common_chat_params common_chat_params_init_gigachat_v3(
"<|role_sep|>\n",
};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "assistant<|role_sep|>\n" + msg.render_content();
data.prompt += data.generation_prompt;
}
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto include_grammar = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
const auto *tool_call_start_prefix = "<|message_sep|>\n\nfunction call<|role_sep|>\n";
@@ -1844,7 +1634,7 @@ static common_chat_params common_chat_params_init_gigachat_v3(
ret = p.content(p.rest());
}
return p.literal("assistant<|role_sep|>\n") + ret;
return p.literal(inputs.generation_prompt) + ret;
});
data.parser = parser.save();
@@ -1872,13 +1662,12 @@ static common_chat_params common_chat_params_init_deepseek_v3_2(const common_cha
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.thinking_start_tag = "<think>";
data.thinking_end_tag = "</think>";
data.preserved_tokens = {
data.preserved_tokens = {
"DSML",
"<think>",
"</think>",
@@ -1898,21 +1687,9 @@ static common_chat_params common_chat_params_init_deepseek_v3_2(const common_cha
const std::string INVOKE_END = "</" + DSML + "invoke>";
const std::string PARAM_START = "<" + DSML + "parameter";
const std::string PARAM_END = "</" + DSML + "parameter>";
const std::string GEN_PROMPT = "<Assistant>";
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.literal(GEN_PROMPT);
auto generation_prompt = p.prefix(inputs.generation_prompt, THINK_START);
auto end = p.end();
auto reasoning = p.eps();
@@ -2339,6 +2116,21 @@ std::optional<common_chat_params> common_chat_try_specialized_template(
return std::nullopt;
}
static std::string common_chat_templates_generation_prompt(const common_chat_template & tmpl, const autoparser::generation_params & inputs) {
autoparser::generation_params params = inputs;
params.add_generation_prompt = false;
std::string no_gen_prompt = common_chat_template_direct_apply_impl(tmpl, params);
params.add_generation_prompt = true;
std::string gen_prompt = common_chat_template_direct_apply_impl(tmpl, params);
size_t prefix_len = 0;
size_t min_size = std::min(no_gen_prompt.size(), gen_prompt.size());
while (prefix_len < min_size && no_gen_prompt[prefix_len] == gen_prompt[prefix_len]) {
prefix_len++;
}
return gen_prompt.substr(prefix_len);
}
static common_chat_params common_chat_templates_apply_jinja(const struct common_chat_templates * tmpls,
const struct common_chat_templates_inputs & inputs) {
autoparser::generation_params params;
@@ -2357,27 +2149,6 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
params.add_bos = tmpls->add_bos;
params.add_eos = tmpls->add_eos;
params.continue_final_message = inputs.continue_final_message;
if (params.continue_final_message != COMMON_CHAT_CONTINUATION_NONE) {
params.add_generation_prompt = false;
if (!inputs.messages.empty()) {
// Render messages[:-1] and store continuation message separately
params.continue_msg = inputs.messages.back();
params.messages.erase(params.messages.size() - 1);
}
if (params.continue_final_message == COMMON_CHAT_CONTINUATION_AUTO && !inputs.messages.empty()) {
// Resolve based on message content
params.continue_final_message = COMMON_CHAT_CONTINUATION_CONTENT;
if (!params.continue_msg.reasoning_content.empty() &&
params.continue_msg.content.empty() &&
params.continue_msg.content_parts.empty()) {
params.continue_final_message = COMMON_CHAT_CONTINUATION_REASONING;
}
}
}
if (src.find("<|channel|>") == std::string::npos) {
// map developer to system for all models except for GPT-OSS
workaround::map_developer_role_to_system(params.messages);
@@ -2398,6 +2169,8 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
workaround::func_args_not_string(params.messages);
}
params.generation_prompt = common_chat_templates_generation_prompt(tmpl, params);
params.extra_context = common_chat_extra_context();
for (auto el : inputs.chat_template_kwargs) {
params.extra_context[el.first] = json::parse(el.second);
@@ -2427,16 +2200,17 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
auto params_copy = params;
params_copy.reasoning_format = COMMON_REASONING_FORMAT_NONE;
data.prompt = common_chat_template_direct_apply_impl(tmpl, params_copy);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, params);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
auto parser = build_chat_peg_parser([&data](common_chat_peg_builder &p) {
return p.literal(data.generation_prompt) << p.content(p.rest());
data.generation_prompt = params.generation_prompt;
auto parser = build_chat_peg_parser([&params](common_chat_peg_builder &p) {
return p.prefix(params.generation_prompt) << p.content(p.rest());
});
data.parser = parser.save();
return data;
}
if (auto result = common_chat_try_specialized_template(tmpl, src, params)) {
result->generation_prompt = params.generation_prompt;
return *result;
}
@@ -2445,24 +2219,12 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
struct autoparser::autoparser autoparser;
autoparser.analyze_template(tmpl);
auto auto_params = autoparser::peg_generator::generate_parser(tmpl, params, autoparser);
std::vector<common_chat_msg_delimiter> delimiters;
if (!autoparser.assistant_start.empty()) {
delimiters.push_back({ "assistant", autoparser.assistant_start });
}
if (!autoparser.user_start.empty()) {
delimiters.push_back({ "user", autoparser.user_start });
}
if (!delimiters.empty()) {
auto_params.message_spans = common_chat_split_by_role(auto_params.prompt, delimiters);
}
auto_params.supports_thinking = autoparser.reasoning.mode != autoparser::reasoning_mode::NONE;
if (auto_params.supports_thinking) {
auto_params.thinking_start_tag = trim_whitespace(autoparser.reasoning.start);
auto_params.thinking_end_tag = trim_whitespace(autoparser.reasoning.end);
}
auto_params.generation_prompt = params.generation_prompt;
common_peg_arena arena;
arena.load(auto_params.parser);
LOG_DBG("%s: generated parser:\n%s\n\nparser generation prompt: %s\n", __func__, arena.dump(arena.root()).c_str(), auto_params.generation_prompt.c_str());
+2 -38
View File
@@ -89,8 +89,6 @@ struct common_chat_msg {
nlohmann::ordered_json to_json_oaicompat(bool concat_typed_text = false) const;
std::string render_content(const std::string & delimiter = "\n\n") const;
bool empty() const {
return content.empty() && content_parts.empty() && tool_calls.empty() && reasoning_content.empty() &&
tool_name.empty() && tool_call_id.empty();
@@ -143,17 +141,6 @@ struct common_chat_msg_diff {
}
};
struct common_chat_msg_span {
std::string role;
std::size_t pos = 0;
std::size_t len = 0;
};
struct common_chat_msg_delimiter {
std::string role;
std::string delimiter;
};
struct common_chat_tool {
std::string name;
std::string description;
@@ -177,22 +164,12 @@ enum common_chat_format {
COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats
};
// Continuation method provided via `continue_final_message`
enum common_chat_continuation {
COMMON_CHAT_CONTINUATION_NONE,
COMMON_CHAT_CONTINUATION_AUTO,
COMMON_CHAT_CONTINUATION_REASONING,
COMMON_CHAT_CONTINUATION_CONTENT,
};
struct common_chat_templates_inputs {
std::vector<common_chat_msg> messages;
std::string grammar;
std::string json_schema;
bool add_generation_prompt = true;
common_chat_continuation continue_final_message = COMMON_CHAT_CONTINUATION_NONE;
bool use_jinja = true;
bool add_generation_prompt = true;
bool use_jinja = true;
// Parameters below only supported when use_jinja is true
std::vector<common_chat_tool> tools;
common_chat_tool_choice tool_choice = COMMON_CHAT_TOOL_CHOICE_AUTO;
@@ -219,7 +196,6 @@ struct common_chat_params {
std::vector<std::string> preserved_tokens;
std::vector<std::string> additional_stops;
std::string parser;
std::vector<common_chat_msg_span> message_spans;
};
// per-message parsing syntax
@@ -231,8 +207,6 @@ struct common_chat_parser_params {
bool reasoning_in_content = false;
std::string generation_prompt;
bool parse_tool_calls = true;
bool is_continuation = false;
bool echo = false; // Include assistant prefilled msg in output
bool debug = false; // Enable debug output for PEG parser
common_peg_arena parser = {};
common_chat_parser_params() = default;
@@ -293,8 +267,6 @@ std::vector<common_chat_msg> common_chat_msgs_parse_oaicompat(const nlohmann::or
std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const nlohmann::ordered_json & tools);
common_chat_continuation common_chat_continuation_parse(const nlohmann::ordered_json & value);
// DEPRECATED: only used in tests
nlohmann::ordered_json common_chat_msgs_to_json_oaicompat(const std::vector<common_chat_msg> & msgs, bool concat_typed_text = false);
@@ -307,16 +279,11 @@ std::string common_chat_template_direct_apply(
const common_chat_template & tmpl,
const autoparser::generation_params & inputs);
std::string common_chat_template_generation_prompt(
const common_chat_template & tmpl,
const autoparser::generation_params & inputs);
std::optional<common_chat_params> common_chat_try_specialized_template(
const common_chat_template & tmpl,
const std::string & src,
autoparser::generation_params & params);
// specialized per-task preset
struct common_chat_prompt_preset {
std::string system;
@@ -324,6 +291,3 @@ struct common_chat_prompt_preset {
};
common_chat_prompt_preset common_chat_get_asr_prompt(const common_chat_templates * chat_templates);
std::vector<common_chat_msg_span> common_chat_split_by_role(const std::string & prompt, const std::vector<common_chat_msg_delimiter> & delims);
+11 -92
View File
@@ -7,7 +7,6 @@
#include "log.h"
#include "llama.h"
#include "sampling.h"
#include "speculative.h"
#include "unicode.h"
#include <algorithm>
@@ -367,33 +366,15 @@ void common_init() {
SetConsoleCP(CP_UTF8);
#endif
common_log_set_prefix(common_log_main(), true);
common_log_set_timestamps(common_log_main(), true);
llama_log_set(common_log_default_callback, NULL);
}
void common_params_print_info(const common_params & params, bool print_devices) {
#ifdef NDEBUG
const char * build_type = "";
#else
const char * build_type = " (debug)";
#endif
LOG_TRC("%s: build %d (%s) with %s for %s%s\n", __func__, llama_build_number(), llama_commit(), llama_compiler(), llama_build_target(), build_type);
LOG_INF("log_info: verbosity = %d (adjust with the `-lv N` CLI arg)\n", common_log_get_verbosity_thold());
// device enumeration creates a primary context on CUDA backends, skip it when the caller does not own any device
if (print_devices) {
LOG_INF("device_info:\n");
for (size_t i = 0; i < ggml_backend_dev_count(); ++i) {
auto * dev = ggml_backend_dev_get(i);
size_t free, total;
ggml_backend_dev_memory(dev, &free, &total);
LOG_INF(" - %-8s: %s (%zu MiB, %zu MiB free)\n", ggml_backend_dev_name(dev), ggml_backend_dev_description(dev), total / 1024 / 1024, free / 1024 / 1024);
}
}
LOG_INF("%s\n", common_params_get_system_info(params).c_str());
LOG_DBG("build: %d (%s) with %s for %s%s\n", llama_build_number(), llama_commit(), llama_compiler(), llama_build_target(), build_type);
}
std::string common_params_get_system_info(const common_params & params) {
@@ -445,27 +426,6 @@ std::string string_strip(const std::string & str) {
return str.substr(start, end - start);
}
std::string string_lcs(std::string_view a, std::string_view b) {
if (a.empty() || b.empty()) return {};
std::vector<std::vector<size_t>> dp(a.size() + 1, std::vector<size_t>(b.size() + 1, 0));
size_t best_len = 0;
size_t best_end_a = 0;
for (size_t i = 1; i <= a.size(); ++i) {
for (size_t j = 1; j <= b.size(); ++j) {
if (a[i - 1] == b[j - 1]) {
dp[i][j] = dp[i - 1][j - 1] + 1;
if (dp[i][j] > best_len) {
best_len = dp[i][j];
best_end_a = i;
}
}
}
}
return std::string(a.substr(best_end_a - best_len, best_len));
}
std::string string_get_sortable_timestamp() {
using clock = std::chrono::system_clock;
@@ -1181,20 +1141,19 @@ struct common_init_result::impl {
std::vector<llama_sampler_seq_config> samplers_seq_config;
};
common_init_result::common_init_result(common_params & params, bool model_only) :
common_init_result::common_init_result(common_params & params) :
pimpl(new impl{}) {
auto mparams = common_model_params_to_llama(params);
auto cparams = common_context_params_to_llama(params);
if (params.fit_params) {
LOG_INF("%s: fitting params to device memory ...\n", __func__);
LOG_INF("%s: (for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on)\n", __func__);
LOG_INF("%s: fitting params to device memory, for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on\n", __func__);
common_fit_params(params.model.path.c_str(), &mparams, &cparams,
params.tensor_split,
params.tensor_buft_overrides.data(),
params.fit_params_target.data(),
params.fit_params_min_ctx,
params.verbosity >= LOG_LEVEL_DEBUG ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR);
params.verbosity >= 4 ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR);
}
llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams);
@@ -1204,10 +1163,6 @@ common_init_result::common_init_result(common_params & params, bool model_only)
pimpl->model.reset(model);
if (model_only) {
return;
}
const llama_vocab * vocab = llama_model_get_vocab(model);
// load and optionally apply lora adapters
@@ -1241,7 +1196,7 @@ common_init_result::common_init_result(common_params & params, bool model_only)
// initialize once
for (llama_token i = 0; i < llama_vocab_n_tokens(vocab); i++) {
if (llama_vocab_is_eog(vocab, i)) {
LOG_TRC("%s: added %s logit bias = %f\n", __func__, common_token_to_piece(vocab, i).c_str(), -INFINITY);
LOG_INF("%s: added %s logit bias = %f\n", __func__, common_token_to_piece(vocab, i).c_str(), -INFINITY);
params.sampling.logit_bias_eog.push_back({i, -INFINITY});
}
}
@@ -1254,12 +1209,12 @@ common_init_result::common_init_result(common_params & params, bool model_only)
}
//if (params.sampling.penalty_last_n == -1) {
// LOG_TRC("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
// LOG_INF("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
// params.sampling.penalty_last_n = llama_n_ctx(lctx);
//}
//if (params.sampling.dry_penalty_last_n == -1) {
// LOG_TRC("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
// LOG_INF("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
// params.sampling.dry_penalty_last_n = llama_n_ctx(lctx);
//}
@@ -1311,8 +1266,8 @@ std::vector<llama_adapter_lora_ptr> & common_init_result::lora() {
return pimpl->lora;
}
common_init_result_ptr common_init_from_params(common_params & params, bool model_only) {
common_init_result_ptr res(new common_init_result(params, model_only));
common_init_result_ptr common_init_from_params(common_params & params) {
common_init_result_ptr res(new common_init_result(params));
llama_model * model = res->model();
if (model == NULL) {
@@ -1320,10 +1275,6 @@ common_init_result_ptr common_init_from_params(common_params & params, bool mode
return res;
}
if (model_only) {
return res;
}
llama_context * lctx = res->context();
if (lctx == NULL) {
LOG_ERR("%s: failed to create context with model '%s'\n", __func__, params.model.path.c_str());
@@ -1387,7 +1338,7 @@ common_init_result_ptr common_init_from_params(common_params & params, bool mode
}
if (params.warmup) {
LOG_INF("%s: warming up the model with an empty run - please wait ... (--no-warmup to disable)\n", __func__);
LOG_WRN("%s: warming up the model with an empty run - please wait ... (--no-warmup to disable)\n", __func__);
llama_set_warmup(lctx, true);
@@ -1469,15 +1420,9 @@ common_context_seq_rm_type common_context_can_seq_rm(llama_context * ctx) {
goto done;
}
if (llama_n_rs_seq(ctx) > 0) {
LOG_INF("%s: the context supports bounded partial sequence removal\n", __func__);
res = COMMON_CONTEXT_SEQ_RM_TYPE_RS;
goto done;
}
// try to remove the last tokens
if (!llama_memory_seq_rm(mem, 0, 1, -1)) {
LOG_TRC("%s: the context does not support partial sequence removal\n", __func__);
LOG_WRN("%s: the context does not support partial sequence removal\n", __func__);
res = COMMON_CONTEXT_SEQ_RM_TYPE_FULL;
goto done;
}
@@ -1489,23 +1434,6 @@ done:
return res;
}
void common_context_seq_rm(llama_context * ctx, llama_seq_id seq_id, llama_pos p0, llama_pos p1) {
auto * mem = llama_get_memory(ctx);
if (!llama_memory_seq_rm(mem, seq_id, p0, p1)) {
GGML_ABORT("%s", string_format("failed to remove sequence %d with p0=%d, p1=%d\n", seq_id, p0, p1).c_str());
}
}
void common_context_seq_cp(llama_context * ctx, llama_seq_id seq_id_src, llama_seq_id seq_id_dst, llama_pos p0, llama_pos p1) {
auto * mem = llama_get_memory(ctx);
llama_memory_seq_cp(mem, seq_id_src, seq_id_dst, p0, p1);
}
void common_context_seq_add(llama_context * ctx, llama_seq_id seq_id, llama_pos p0, llama_pos p1, llama_pos delta) {
auto * mem = llama_get_memory(ctx);
llama_memory_seq_add(mem, seq_id, p0, p1, delta);
}
void common_set_adapter_lora(struct llama_context * ctx, std::vector<common_adapter_lora_info> & lora) {
std::vector<llama_adapter_lora *> loras;
std::vector<float> scales;
@@ -1562,7 +1490,6 @@ struct llama_context_params common_context_params_to_llama(const common_params &
cparams.n_ctx = params.n_ctx;
cparams.n_seq_max = params.n_parallel;
cparams.n_rs_seq = params.speculative.need_n_rs_seq();
cparams.n_batch = params.n_batch;
cparams.n_ubatch = params.n_ubatch;
cparams.n_threads = params.cpuparams.n_threads;
@@ -2132,11 +2059,3 @@ void common_prompt_checkpoint::load_dft(
GGML_ABORT("checkpoint size mismatch: expected %zu, got %zu\n", data_dft.size(), n);
}
}
void common_prompt_checkpoint::clear_tgt() {
data_tgt.clear();
}
void common_prompt_checkpoint::clear_dft() {
data_dft.clear();
}
+18 -45
View File
@@ -13,7 +13,6 @@
#include <string_view>
#include <vector>
#include <map>
#include <algorithm>
#if defined(_WIN32) && !defined(_WIN32_WINNT)
#define _WIN32_WINNT 0x0A00
@@ -158,10 +157,10 @@ enum common_params_sampling_config : uint64_t {
enum common_speculative_type {
COMMON_SPECULATIVE_TYPE_NONE, // no speculative decoding
COMMON_SPECULATIVE_TYPE_DRAFT_SIMPLE, // standalone draft model speculative decoding
COMMON_SPECULATIVE_TYPE_DRAFT_EAGLE3, // Eagle3 speculative decoding
COMMON_SPECULATIVE_TYPE_DRAFT_MTP, // Multi-token prediction
COMMON_SPECULATIVE_TYPE_NGRAM_SIMPLE, // simple self-speculative decoding based on n-grams
COMMON_SPECULATIVE_TYPE_DRAFT, // draft model
COMMON_SPECULATIVE_TYPE_EAGLE3, // eagle draft model
COMMON_SPECULATIVE_TYPE_MTP, // multi-token prediction head loaded from the target GGUF
COMMON_SPECULATIVE_TYPE_NGRAM_SIMPLE, // simple self-speculative decoding
COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K, // self-speculative decoding with n-gram keys only
COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K4V, // self-speculative decoding with n-gram keys and 4 m-gram values
COMMON_SPECULATIVE_TYPE_NGRAM_MOD,
@@ -299,13 +298,11 @@ struct common_params_model {
// draft-model-based speculative decoding parameters
struct common_params_speculative_draft {
int32_t n_max = 3; // maximum number of tokens to draft during speculative decoding
int32_t n_min = 0; // minimum number of draft tokens to use for speculative decoding
int32_t n_max = 16; // maximum number of tokens to draft during speculative decoding
int32_t n_min = 0; // minimum number of draft tokens to use for speculative decoding
float p_split = 0.1f; // speculative decoding split probability
float p_min = 0.0f; // minimum speculative decoding probability (greedy)
bool backend_sampling = true; // offload draft sampling to the backend (default: on)
float p_split = 0.1f; // speculative decoding split probability
float p_min = 0.75f; // minimum speculative decoding probability (greedy)
common_params_model mparams;
@@ -344,9 +341,9 @@ struct common_params_speculative_ngram_cache {
};
struct common_params_speculative {
std::vector<enum common_speculative_type> types = { COMMON_SPECULATIVE_TYPE_NONE };
// TODO: become a vector in order to support "chains of speculators"
common_speculative_type type = COMMON_SPECULATIVE_TYPE_NONE;
// used by Simple, MTP, Eagle3, etc. - all methods that require some kind of draft model
common_params_speculative_draft draft;
common_params_speculative_ngram_mod ngram_mod;
@@ -359,14 +356,6 @@ struct common_params_speculative {
bool has_dft() const {
return !draft.mparams.path.empty() || !draft.mparams.hf_repo.empty();
}
uint32_t need_n_rs_seq() const {
bool needs_rs_seq = std::any_of(types.begin(), types.end(), [&](auto t) {
return t == COMMON_SPECULATIVE_TYPE_DRAFT_MTP;
});
return needs_rs_seq ? draft.n_max : 0u;
}
};
struct common_params_vocoder {
@@ -594,7 +583,7 @@ struct common_params {
bool cache_prompt = true; // whether to enable prompt caching
bool cache_idle_slots = true; // save and clear idle slots upon starting a new task
int32_t n_ctx_checkpoints = 32; // max number of context checkpoints per slot
int32_t checkpoint_min_step = 256; // minimum spacing between context checkpoints
int32_t checkpoint_every_nt = 8192; // make a checkpoint every n tokens during prefill
int32_t cache_ram_mib = 8192; // -1 = no limit, 0 - disable, 1 = 1 MiB, etc.
std::string hostname = "127.0.0.1";
@@ -616,17 +605,11 @@ struct common_params {
std::map<std::string, std::string> default_template_kwargs;
// UI configs
bool ui = true;
// Deprecated: use ui, ui_mcp_proxy, ui_config_json instead
bool webui = ui;
// webui configs
bool webui = true;
bool webui_mcp_proxy = false;
std::string webui_config_json;
bool ui_mcp_proxy = false;
std::string ui_config_json;
// "advanced" endpoints are disabled by default for better security
bool endpoint_slots = true;
bool endpoint_props = false; // only control POST requests, not GET
@@ -704,7 +687,6 @@ struct common_params {
// initializes the logging system and prints info about the build
void common_init();
void common_params_print_info(const common_params & params, bool print_devices = true);
std::string common_params_get_system_info(const common_params & params);
bool parse_cpu_range(const std::string & range, bool(&boolmask)[GGML_MAX_N_THREADS]);
@@ -731,7 +713,6 @@ std::string string_format(const char * fmt, ...);
std::string string_strip(const std::string & str);
std::string string_get_sortable_timestamp();
std::string string_lcs(std::string_view a, std::string_view b);
std::string string_join(const std::vector<std::string> & values, const std::string & separator);
std::vector<std::string> string_split(const std::string & str, const std::string & delimiter);
@@ -856,7 +837,7 @@ struct common_sampler;
// note: defines the model, context, samplers, ets. lifetimes
struct common_init_result {
common_init_result(common_params & params, bool model_only = false);
common_init_result(common_params & params);
~common_init_result();
llama_model * model();
@@ -874,7 +855,7 @@ private:
using common_init_result_ptr = std::unique_ptr<common_init_result>;
common_init_result_ptr common_init_from_params(common_params & params, bool model_only = false);
common_init_result_ptr common_init_from_params(common_params & params);
struct llama_model_params common_model_params_to_llama ( common_params & params);
struct llama_context_params common_context_params_to_llama(const common_params & params);
@@ -891,20 +872,15 @@ std::string common_get_model_endpoint();
//
enum common_context_seq_rm_type {
COMMON_CONTEXT_SEQ_RM_TYPE_NO = 0, // seq_rm not supported (e.g. no memory module)
COMMON_CONTEXT_SEQ_RM_TYPE_PART = 1, // can seq_rm partial sequences
COMMON_CONTEXT_SEQ_RM_TYPE_FULL = 2, // can seq_rm full sequences only
COMMON_CONTEXT_SEQ_RM_TYPE_RS = 3, // can seq_rm partial sequences, bounded by n_rs_seq
COMMON_CONTEXT_SEQ_RM_TYPE_NO = 0, // seq_rm not supported (e.g. no memory module)
COMMON_CONTEXT_SEQ_RM_TYPE_PART = 1, // can seq_rm partial sequences
COMMON_CONTEXT_SEQ_RM_TYPE_FULL = 2, // can seq_rm full sequences only
};
// check if the llama_context can remove sequences
// note: clears the memory of the context
common_context_seq_rm_type common_context_can_seq_rm(llama_context * ctx);
// aborts execution on failure
void common_context_seq_rm (llama_context * ctx, llama_seq_id seq_id, llama_pos p0, llama_pos p1);
void common_context_seq_add(llama_context * ctx, llama_seq_id seq_id, llama_pos p0, llama_pos p1, llama_pos delta);
void common_context_seq_cp (llama_context * ctx, llama_seq_id seq_id_src, llama_seq_id seq_id_dst, llama_pos p0, llama_pos p1);
//
// Batch utils
@@ -1086,7 +1062,4 @@ struct common_prompt_checkpoint {
llama_context * ctx,
llama_seq_id seq_id,
llama_state_seq_flags flags) const;
void clear_tgt();
void clear_dft();
};
+15 -44
View File
@@ -320,9 +320,9 @@ static int common_download_file_single_online(const std::string & url,
auto head = cli.Head(parts.path);
if (!head || head->status < 200 || head->status >= 300) {
LOG_TRC("%s: HEAD failed, status: %d\n", __func__, head ? head->status : -1);
LOG_WRN("%s: HEAD failed, status: %d\n", __func__, head ? head->status : -1);
if (file_exists) {
LOG_TRC("%s: using cached file (HEAD failed): %s\n", __func__, path.c_str());
LOG_INF("%s: using cached file (HEAD failed): %s\n", __func__, path.c_str());
return 304; // 304 Not Modified - fake cached response
}
return head ? head->status : -1;
@@ -566,11 +566,8 @@ static hf_cache::hf_files get_split_files(const hf_cache::hf_files & files,
return result;
}
// pick the best sibling GGUF whose filename contains `keyword` (e.g. "mmproj" / "mtp"),
// preferring deeper shared directory prefix with the model, then closest quantization
static hf_cache::hf_file find_best_sibling(const hf_cache::hf_files & files,
const std::string & model,
const std::string & keyword) {
static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
const std::string & model) {
hf_cache::hf_file best;
size_t best_depth = 0;
int best_diff = 0;
@@ -582,20 +579,20 @@ static hf_cache::hf_file find_best_sibling(const hf_cache::hf_files & files,
for (const auto & f : files) {
if (!string_ends_with(f.path, ".gguf") ||
f.path.find(keyword) == std::string::npos) {
f.path.find("mmproj") == std::string::npos) {
continue;
}
auto sib_parts = string_split<std::string>(f.path, '/');
auto sib_dir = sib_parts.end() - 1;
auto mmproj_parts = string_split<std::string>(f.path, '/');
auto mmproj_dir = mmproj_parts.end() - 1;
auto [_, dir] = std::mismatch(model_parts.begin(), model_dir,
sib_parts.begin(), sib_dir);
if (dir != sib_dir) {
mmproj_parts.begin(), mmproj_dir);
if (dir != mmproj_dir) {
continue;
}
size_t depth = dir - sib_parts.begin();
size_t depth = dir - mmproj_parts.begin();
auto bits = extract_quant_bits(f.path);
auto diff = std::abs(bits - model_bits);
@@ -609,16 +606,6 @@ static hf_cache::hf_file find_best_sibling(const hf_cache::hf_files & files,
return best;
}
static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
const std::string & model) {
return find_best_sibling(files, model, "mmproj");
}
static hf_cache::hf_file find_best_mtp(const hf_cache::hf_files & files,
const std::string & model) {
return find_best_sibling(files, model, "mtp-");
}
static bool gguf_filename_is_model(const std::string & filepath) {
if (!string_ends_with(filepath, ".gguf")) {
return false;
@@ -630,8 +617,7 @@ static bool gguf_filename_is_model(const std::string & filepath) {
}
return filename.find("mmproj") == std::string::npos &&
filename.find("imatrix") == std::string::npos &&
filename.find("mtp-") == std::string::npos;
filename.find("imatrix") == std::string::npos;
}
static hf_cache::hf_file find_best_model(const hf_cache::hf_files & files,
@@ -687,13 +673,11 @@ struct hf_plan {
hf_cache::hf_file primary;
hf_cache::hf_files model_files;
hf_cache::hf_file mmproj;
hf_cache::hf_file mtp;
};
static hf_plan get_hf_plan(const common_params_model & model,
const common_download_opts & opts,
bool download_mmproj,
bool download_mtp) {
bool download_mmproj) {
hf_plan plan;
hf_cache::hf_files all;
@@ -739,10 +723,6 @@ static hf_plan get_hf_plan(const common_params_model & model,
plan.mmproj = find_best_mmproj(all, primary.path);
}
if (download_mtp) {
plan.mtp = find_best_mtp(all, primary.path);
}
return plan;
}
@@ -776,8 +756,7 @@ static std::vector<download_task> get_url_tasks(const common_params_model & mode
common_download_model_result common_download_model(const common_params_model & model,
const common_download_opts & opts,
bool download_mmproj,
bool download_mtp) {
bool download_mmproj) {
common_download_model_result result;
std::vector<download_task> tasks;
hf_plan hf;
@@ -785,16 +764,13 @@ common_download_model_result common_download_model(const common_params_model &
bool is_hf = !model.hf_repo.empty();
if (is_hf) {
hf = get_hf_plan(model, opts, download_mmproj, download_mtp);
hf = get_hf_plan(model, opts, download_mmproj);
for (const auto & f : hf.model_files) {
tasks.push_back({f.url, f.local_path});
}
if (!hf.mmproj.path.empty()) {
tasks.push_back({hf.mmproj.url, hf.mmproj.local_path});
}
if (!hf.mtp.path.empty()) {
tasks.push_back({hf.mtp.url, hf.mtp.local_path});
}
} else if (!model.url.empty()) {
tasks = get_url_tasks(model);
} else {
@@ -831,10 +807,6 @@ common_download_model_result common_download_model(const common_params_model &
if (!hf.mmproj.path.empty()) {
result.mmproj_path = hf_cache::finalize_file(hf.mmproj);
}
if (!hf.mtp.path.empty()) {
result.mtp_path = hf_cache::finalize_file(hf.mtp);
}
} else {
result.model_path = model.path;
}
@@ -974,8 +946,7 @@ std::vector<common_cached_model_info> common_list_cached_models() {
for (const auto & f : files) {
auto split = get_gguf_split_info(f.path);
if (split.index != 1 || split.tag.empty() ||
split.prefix.find("mmproj") != std::string::npos ||
split.prefix.find("mtp-") != std::string::npos) {
split.prefix.find("mmproj") != std::string::npos) {
continue;
}
if (seen.insert(f.repo_id + ":" + split.tag).second) {
+2 -5
View File
@@ -59,7 +59,6 @@ struct common_download_opts {
struct common_download_model_result {
std::string model_path;
std::string mmproj_path;
std::string mtp_path;
};
// Download model from HuggingFace repo or URL
@@ -84,14 +83,12 @@ struct common_download_model_result {
// when opts.offline=true, no network requests are made
// when download_mmproj=true, searches for mmproj in same directory as model or any parent directory
// then with the closest quantization bits
// when download_mtp=true, applies the same sibling search for an MTP-head GGUF
//
// returns result with model_path, mmproj_path and mtp_path (empty when not found / on failure)
// returns result with model_path and mmproj_path (empty on failure)
common_download_model_result common_download_model(
const common_params_model & model,
const common_download_opts & opts = {},
bool download_mmproj = false,
bool download_mtp = false
bool download_mmproj = false
);
// returns list of cached models
+45 -45
View File
@@ -26,7 +26,7 @@ class common_params_fit_exception : public std::runtime_error {
using std::runtime_error::runtime_error;
};
std::vector<llama_device_memory_data> common_get_device_memory_data(
static std::vector<llama_device_memory_data> common_get_device_memory_data(
const char * path_model,
const llama_model_params * mparams,
const llama_context_params * cparams,
@@ -168,7 +168,7 @@ static void common_params_fit_impl(
// step 1: get data for default parameters and check whether any changes are necessary in the first place
LOG_TRC("%s: getting device memory data for initial parameters:\n", __func__);
LOG_INF("%s: getting device memory data for initial parameters:\n", __func__);
const dmds_t dmds_full = common_get_device_memory_data(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
const size_t nd = devs.size(); // number of devices
@@ -213,13 +213,13 @@ static void common_params_fit_impl(
LOG_INF("%s: projected to use %" PRId64 " MiB of host memory vs. %" PRId64 " MiB of total host memory\n",
__func__, sum_projected_used/MiB, sum_free/MiB);
if (sum_projected_free >= margins[0]) {
LOG_TRC("%s: will leave %" PRId64 " >= %" PRId64 " MiB of system memory, no changes needed\n",
LOG_INF("%s: will leave %" PRId64 " >= %" PRId64 " MiB of system memory, no changes needed\n",
__func__, sum_projected_free/MiB, margins[0]/MiB);
return;
}
} else {
if (nd > 1) {
LOG_TRC("%s: projected memory use with initial parameters [MiB]:\n", __func__);
LOG_INF("%s: projected memory use with initial parameters [MiB]:\n", __func__);
}
for (size_t id = 0; id < nd; id++) {
const llama_device_memory_data & dmd = dmds_full[id];
@@ -234,16 +234,16 @@ static void common_params_fit_impl(
sum_projected_model += dmd.mb.model;
if (nd > 1) {
LOG_TRC("%s: - %s: %6" PRId64 " total, %6" PRId64 " used, %6" PRId64 " free vs. target of %6" PRId64 "\n",
LOG_INF("%s: - %s: %6" PRId64 " total, %6" PRId64 " used, %6" PRId64 " free vs. target of %6" PRId64 "\n",
__func__, dev_names[id].c_str(), dmd.total/MiB, projected_used/MiB, projected_free/MiB, margins[id]/MiB);
}
}
assert(sum_free >= 0 && sum_projected_used >= 0);
LOG_TRC("%s: projected to use %" PRId64 " MiB of device memory vs. %" PRId64 " MiB of free device memory\n",
LOG_INF("%s: projected to use %" PRId64 " MiB of device memory vs. %" PRId64 " MiB of free device memory\n",
__func__, sum_projected_used/MiB, sum_free/MiB);
if (nd == 1) {
if (projected_free_per_device[0] >= margins[0]) {
LOG_TRC("%s: will leave %" PRId64 " >= %" PRId64 " MiB of free device memory, no changes needed\n",
LOG_INF("%s: will leave %" PRId64 " >= %" PRId64 " MiB of free device memory, no changes needed\n",
__func__, projected_free_per_device[0]/MiB, margins[0]/MiB);
return;
}
@@ -256,7 +256,7 @@ static void common_params_fit_impl(
}
}
if (!changes_needed) {
LOG_TRC("%s: targets for free memory can be met on all devices, no changes needed\n", __func__);
LOG_INF("%s: targets for free memory can be met on all devices, no changes needed\n", __func__);
return;
}
}
@@ -275,10 +275,10 @@ static void common_params_fit_impl(
}
if (global_surplus < 0) {
if (nd <= 1) {
LOG_TRC("%s: cannot meet free memory target of %" PRId64 " MiB, need to reduce device memory by %" PRId64 " MiB\n",
LOG_INF("%s: cannot meet free memory target of %" PRId64 " MiB, need to reduce device memory by %" PRId64 " MiB\n",
__func__, margins[0]/MiB, -global_surplus/MiB);
} else {
LOG_TRC(
LOG_INF(
"%s: cannot meet free memory targets on all devices, need to use %" PRId64 " MiB less in total\n",
__func__, -global_surplus/MiB);
}
@@ -320,28 +320,28 @@ static void common_params_fit_impl(
const int64_t bytes_per_ctx = (sum_projected_used - sum_projected_used_min_ctx) / (hp_nct - n_ctx_min);
const int64_t memory_reduction = (hp_nct - cparams->n_ctx) * bytes_per_ctx;
LOG_TRC("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
LOG_INF("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
__func__, hp_nct, cparams->n_ctx, memory_reduction/MiB);
if (nd <= 1) {
LOG_TRC("%s: entire model can be fit by reducing context\n", __func__);
LOG_INF("%s: entire model can be fit by reducing context\n", __func__);
return;
}
LOG_TRC("%s: entire model should be fit across devices by reducing context\n", __func__);
LOG_INF("%s: entire model should be fit across devices by reducing context\n", __func__);
} else {
const int64_t memory_reduction = sum_projected_used - sum_projected_used_min_ctx;
LOG_TRC("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
LOG_INF("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
__func__, hp_nct, cparams->n_ctx, memory_reduction/MiB);
}
} else {
if (n_ctx_min == UINT32_MAX) {
LOG_TRC("%s: user has requested full context size of %" PRIu32 " -> no change\n", __func__, hp_nct);
LOG_INF("%s: user has requested full context size of %" PRIu32 " -> no change\n", __func__, hp_nct);
} else {
LOG_TRC("%s: default model context size is %" PRIu32 " which is <= the min. context size of %" PRIu32 " -> no change\n",
LOG_INF("%s: default model context size is %" PRIu32 " which is <= the min. context size of %" PRIu32 " -> no change\n",
__func__, hp_nct, n_ctx_min);
}
}
} else {
LOG_TRC("%s: context size set by user to %" PRIu32 " -> no change\n", __func__, cparams->n_ctx);
LOG_INF("%s: context size set by user to %" PRIu32 " -> no change\n", __func__, cparams->n_ctx);
}
}
}
@@ -485,10 +485,10 @@ static void common_params_fit_impl(
const dmds_t dmd_nl = common_get_device_memory_data(
path_model, &mparams_copy, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
LOG_TRC("%s: memory for test allocation by device:\n", func_name);
LOG_INF("%s: memory for test allocation by device:\n", func_name);
for (size_t id = 0; id < nd; id++) {
const ngl_t & n = ngl_per_device[id];
LOG_TRC(
LOG_INF(
"%s: id=%zu, n_layer=%2" PRIu32 ", n_part=%2" PRIu32 ", overflow_type=%d, mem=%6" PRId64 " MiB\n",
func_name, id, n.n_layer, n.n_part, int(n.overflow_type), dmd_nl[id].mb.total()/MiB);
}
@@ -509,7 +509,7 @@ static void common_params_fit_impl(
tensor_buft_overrides[1] = {nullptr, nullptr};
mparams->tensor_buft_overrides = tensor_buft_overrides;
LOG_TRC("%s: getting device memory data with all MoE tensors moved to system memory:\n", __func__);
LOG_INF("%s: getting device memory data with all MoE tensors moved to system memory:\n", __func__);
const dmds_t dmds_cpu_moe = common_get_device_memory_data(
path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
@@ -519,10 +519,10 @@ static void common_params_fit_impl(
}
if (global_surplus_cpu_moe > 0) {
LOG_TRC("%s: with only dense weights in device memory there is a total surplus of %" PRId64 " MiB\n",
LOG_INF("%s: with only dense weights in device memory there is a total surplus of %" PRId64 " MiB\n",
__func__, global_surplus_cpu_moe/MiB);
} else {
LOG_TRC("%s: with only dense weights in device memory there is still a total deficit of %" PRId64 " MiB\n",
LOG_INF("%s: with only dense weights in device memory there is still a total deficit of %" PRId64 " MiB\n",
__func__, -global_surplus_cpu_moe/MiB);
}
@@ -535,7 +535,7 @@ static void common_params_fit_impl(
targets.reserve(nd);
for (size_t id = 0; id < nd; id++) {
targets.push_back(dmds_full[id].free - margins[id]);
LOG_TRC("%s: id=%zu, target=%" PRId64 " MiB\n", __func__, id, targets[id]/MiB);
LOG_INF("%s: id=%zu, target=%" PRId64 " MiB\n", __func__, id, targets[id]/MiB);
}
std::vector<ggml_backend_buffer_type_t> overflow_bufts; // which bufts the first partial layer of a device overflows to:
@@ -555,9 +555,9 @@ static void common_params_fit_impl(
// - once we only have a difference of a single layer, stop and return the lower bound that just barely still fits
// - the last device has the output layer, which cannot be a partial layer
if (hp_nex == 0) {
LOG_TRC("%s: filling dense layers back-to-front:\n", __func__);
LOG_INF("%s: filling dense layers back-to-front:\n", __func__);
} else {
LOG_TRC("%s: filling dense-only layers back-to-front:\n", __func__);
LOG_INF("%s: filling dense-only layers back-to-front:\n", __func__);
}
for (int id = nd - 1; id >= 0; id--) {
uint32_t n_unassigned = hp_ngl + 1;
@@ -576,7 +576,7 @@ static void common_params_fit_impl(
if (mem_high[id] > targets[id]) {
assert(ngl_per_device_high[id].n_layer > ngl_per_device[id].n_layer);
uint32_t delta = ngl_per_device_high[id].n_layer - ngl_per_device[id].n_layer;
LOG_TRC("%s: start filling device %" PRIu32 ", delta=%" PRIu32 "\n", __func__, id, delta);
LOG_INF("%s: start filling device %" PRIu32 ", delta=%" PRIu32 "\n", __func__, id, delta);
while (delta > 1) {
uint32_t step_size = int64_t(delta) * (targets[id] - mem[id]) / (mem_high[id] - mem[id]);
step_size = std::max(step_size, uint32_t(1));
@@ -593,11 +593,11 @@ static void common_params_fit_impl(
if (mem_test[id] <= targets[id]) {
ngl_per_device = ngl_per_device_test;
mem = mem_test;
LOG_TRC("%s: set ngl_per_device[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device[id].n_layer);
LOG_INF("%s: set ngl_per_device[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device[id].n_layer);
} else {
ngl_per_device_high = ngl_per_device_test;
mem_high = mem_test;
LOG_TRC("%s: set ngl_per_device_high[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device_high[id].n_layer);
LOG_INF("%s: set ngl_per_device_high[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device_high[id].n_layer);
}
delta = ngl_per_device_high[id].n_layer - ngl_per_device[id].n_layer;
}
@@ -605,12 +605,12 @@ static void common_params_fit_impl(
assert(ngl_per_device_high[id].n_layer == n_unassigned);
ngl_per_device = ngl_per_device_high;
mem = mem_high;
LOG_TRC("%s: set ngl_per_device[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device[id].n_layer);
LOG_INF("%s: set ngl_per_device[%d].n_layer=%" PRIu32 "\n", __func__, id, ngl_per_device[id].n_layer);
}
}
const int64_t projected_margin = dmds_full[id].free - mem[id];
LOG_TRC(
LOG_INF(
"%s: - %s: %2" PRIu32 " layers, %6" PRId64 " MiB used, %6" PRId64 " MiB free\n",
__func__, dev_names[id].c_str(), ngl_per_device[id].n_layer, mem[id]/MiB, projected_margin/MiB);
}
@@ -634,7 +634,7 @@ static void common_params_fit_impl(
}
assert(id_dense_start < nd);
LOG_TRC("%s: converting dense-only layers to full layers and filling them front-to-back with overflow to next device/system memory:\n", __func__);
LOG_INF("%s: converting dense-only layers to full layers and filling them front-to-back with overflow to next device/system memory:\n", __func__);
for (size_t id = 0; id <= id_dense_start && id_dense_start < nd; id++) {
std::vector<ngl_t> ngl_per_device_high = ngl_per_device;
for (size_t jd = id_dense_start; jd < nd; jd++) {
@@ -674,13 +674,13 @@ static void common_params_fit_impl(
ngl_per_device = ngl_per_device_test;
mem = mem_test;
id_dense_start = id_dense_start_test;
LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start=%zu\n",
LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start=%zu\n",
__func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
} else {
ngl_per_device_high = ngl_per_device_test;
mem_high = mem_test;
id_dense_start_high = id_dense_start_test;
LOG_TRC("%s: set ngl_per_device_high[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start_high=%zu\n",
LOG_INF("%s: set ngl_per_device_high[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start_high=%zu\n",
__func__, id, ngl_per_device_high[id].n_layer, ngl_per_device_high[id].n_part, id_dense_start_high);
}
assert(ngl_per_device_high[id].n_full() >= ngl_per_device[id].n_full());
@@ -690,7 +690,7 @@ static void common_params_fit_impl(
ngl_per_device = ngl_per_device_high;
mem = mem_high;
id_dense_start = id_dense_start_high;
LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start=%zu\n",
LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part)=(%" PRIu32 ", %" PRIu32 "), id_dense_start=%zu\n",
__func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
}
@@ -710,44 +710,44 @@ static void common_params_fit_impl(
if (id < nd - 1) {
overflow_bufts_test[id] = ggml_backend_dev_buffer_type(devs[id + 1]);
}
LOG_TRC("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_UP\n", __func__);
LOG_INF("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_UP\n", __func__);
std::vector<int64_t> mem_test = get_memory_for_layers(__func__, ngl_per_device_test, overflow_bufts_test);
if (mem_test[id] < targets[id] && (id + 1 == nd || mem_test[id + 1] < targets[id + 1])) {
ngl_per_device = ngl_per_device_test;
overflow_bufts = overflow_bufts_test;
mem = mem_test;
id_dense_start = id_dense_start_test;
LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", UP), id_dense_start=%zu\n",
LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", UP), id_dense_start=%zu\n",
__func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
ngl_per_device_test[id].overflow_type = LAYER_FRACTION_GATE;
LOG_TRC("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_GATE\n", __func__);
LOG_INF("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_GATE\n", __func__);
mem_test = get_memory_for_layers(__func__, ngl_per_device_test, overflow_bufts_test);
if (mem_test[id] < targets[id] && (id + 1 == nd || mem_test[id + 1] < targets[id + 1])) {
ngl_per_device = ngl_per_device_test;
overflow_bufts = overflow_bufts_test;
mem = mem_test;
id_dense_start = id_dense_start_test;
LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", GATE), id_dense_start=%zu\n",
LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", GATE), id_dense_start=%zu\n",
__func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
}
} else {
ngl_per_device_test[id].overflow_type = LAYER_FRACTION_ATTN;
LOG_TRC("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_ATTN\n", __func__);
LOG_INF("%s: trying to fit one extra layer with overflow_type=LAYER_FRACTION_ATTN\n", __func__);
mem_test = get_memory_for_layers(__func__, ngl_per_device_test, overflow_bufts_test);
if (mem_test[id] < targets[id] && (id + 1 == nd || mem_test[id + 1] < targets[id + 1])) {
ngl_per_device = ngl_per_device_test;
overflow_bufts = overflow_bufts_test;
mem = mem_test;
id_dense_start = id_dense_start_test;
LOG_TRC("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", ATTN), id_dense_start=%zu\n",
LOG_INF("%s: set ngl_per_device[%zu].(n_layer, n_part, overflow_type)=(%" PRIu32 ", %" PRIu32 ", ATTN), id_dense_start=%zu\n",
__func__, id, ngl_per_device[id].n_layer, ngl_per_device[id].n_part, id_dense_start);
}
}
}
const int64_t projected_margin = dmds_full[id].free - mem[id];
LOG_TRC(
LOG_INF(
"%s: - %s: %2" PRIu32 " layers (%2" PRIu32 " overflowing), %6" PRId64 " MiB used, %6" PRId64 " MiB free\n",
__func__, dev_names[id].c_str(), ngl_per_device[id].n_layer, ngl_per_device[id].n_part, mem[id]/MiB, projected_margin/MiB);
}
@@ -755,7 +755,7 @@ static void common_params_fit_impl(
// print info for devices that were not changed during the conversion from dense only to full layers:
for (size_t id = id_dense_start + 1; id < nd; id++) {
const int64_t projected_margin = dmds_full[id].free - mem[id];
LOG_TRC(
LOG_INF(
"%s: - %s: %2" PRIu32 " layers (%2" PRIu32 " overflowing), %6" PRId64 " MiB used, %6" PRId64 " MiB free\n",
__func__, dev_names[id].c_str(), ngl_per_device[id].n_layer, ngl_per_device[id].n_part, mem[id]/MiB, projected_margin/MiB);
}
@@ -776,7 +776,7 @@ enum common_params_fit_status common_fit_params(
common_params_fit_status status = COMMON_PARAMS_FIT_STATUS_SUCCESS;
try {
common_params_fit_impl(path_model, mparams, cparams, tensor_split, tensor_buft_overrides, margins, n_ctx_min, log_level);
LOG_TRC("%s: successfully fit params to free device memory\n", __func__);
LOG_INF("%s: successfully fit params to free device memory\n", __func__);
} catch (const common_params_fit_exception & e) {
LOG_WRN("%s: failed to fit params to free device memory: %s\n", __func__, e.what());
status = COMMON_PARAMS_FIT_STATUS_FAILURE;
@@ -785,7 +785,7 @@ enum common_params_fit_status common_fit_params(
status = COMMON_PARAMS_FIT_STATUS_ERROR;
}
const int64_t t1_us = llama_time_us();
LOG_TRC("%s: fitting params to free memory took %.2f seconds\n", __func__, (t1_us - t0_us) * 1e-6);
LOG_INF("%s: fitting params to free memory took %.2f seconds\n", __func__, (t1_us - t0_us) * 1e-6);
return status;
}
@@ -925,7 +925,7 @@ void common_memory_breakdown_print(const struct llama_context * ctx) {
}
}
for (const auto & td : table_data) {
LOG_TRC(td[0].c_str(),
LOG_INF(td[0].c_str(),
__func__, td[1].c_str(), td[2].c_str(), td[3].c_str(), td[4].c_str(), td[5].c_str(),
td[6].c_str(), td[7].c_str(), td[8].c_str());
}
-16
View File
@@ -1,11 +1,6 @@
#pragma once
#include "ggml.h"
#include "ggml-backend.h"
#include "llama.h"
#include "../src/llama-ext.h"
#include <vector>
enum common_params_fit_status {
COMMON_PARAMS_FIT_STATUS_SUCCESS = 0, // found allocations that are projected to fit
@@ -35,14 +30,3 @@ void common_fit_print(
struct llama_context_params * cparams);
void common_memory_breakdown_print(const struct llama_context * ctx);
// Load a model + context with no_alloc and return the per-device memory breakdown.
std::vector<llama_device_memory_data> common_get_device_memory_data(
const char * path_model,
const struct llama_model_params * mparams,
const struct llama_context_params * cparams,
std::vector<ggml_backend_dev_t> & devs,
uint32_t & hp_ngl,
uint32_t & hp_n_ctx_train,
uint32_t & hp_n_expert,
enum ggml_log_level log_level);
+274
View File
@@ -11,6 +11,7 @@
#include <filesystem>
#include <fstream>
#include <atomic>
#include <regex> // migration only
#include <string>
#include <string_view>
#include <stdexcept>
@@ -335,9 +336,15 @@ hf_files get_repo_files(const std::string & repo_id,
if (item["lfs"].contains("oid") && item["lfs"]["oid"].is_string()) {
file.oid = item["lfs"]["oid"].get<std::string>();
}
if (item["lfs"].contains("size") && item["lfs"]["size"].is_number()) {
file.size = item["lfs"]["size"].get<size_t>();
}
} else if (item.contains("oid") && item["oid"].is_string()) {
file.oid = item["oid"].get<std::string>();
}
if (file.size == 0 && item.contains("size") && item["size"].is_number()) {
file.size = item["size"].get<size_t>();
}
if (!file.oid.empty() && !is_valid_oid(file.oid)) {
LOG_WRN("%s: skip invalid oid: %s\n", __func__, file.oid.c_str());
@@ -495,4 +502,271 @@ std::string finalize_file(const hf_file & file) {
return file.final_path;
}
// delete everything after this line, one day
// copied from download.cpp without the tag part
struct gguf_split_info {
std::string prefix; // tag included
int index;
int count;
};
static gguf_split_info get_gguf_split_info(const std::string & path) {
static const std::regex re_split("^(.+)-([0-9]{5})-of-([0-9]{5})$", std::regex::icase);
std::smatch m;
std::string prefix = path;
if (!string_remove_suffix(prefix, ".gguf")) {
return {};
}
int index = 1;
int count = 1;
if (std::regex_match(prefix, m, re_split)) {
index = std::stoi(m[2].str());
count = std::stoi(m[3].str());
prefix = m[1].str();
}
return {std::move(prefix), index, count};
}
static std::pair<std::string, std::string> parse_manifest_name(std::string & filename) {
static const std::regex re(R"(^manifest=([^=]+)=([^=]+)=.*\.json$)");
std::smatch match;
if (std::regex_match(filename, match, re)) {
return {match[1].str(), match[2].str()};
}
return {};
}
static std::string make_old_cache_filename(const std::string & owner,
const std::string & repo,
const std::string & filename) {
auto result = owner + "_" + repo + "_" + filename;
string_replace_all(result, "/", "_");
return result;
}
struct migrate_file {
std::string path;
std::string sha256;
size_t size;
fs::path old_path;
fs::path etag_path;
const hf_file * file;
};
using migrate_files = std::vector<migrate_file>;
static bool collect_file(const fs::path & old_cache,
const std::string & owner,
const std::string & repo,
const std::string & path,
const std::string & sha256,
const hf_files & files,
migrate_files & to_migrate) {
const hf_file * file = nullptr;
for (const auto & f : files) {
if (f.path == path) {
file = &f;
break;
}
}
std::string old_filename = make_old_cache_filename(owner, repo, path);
fs::path old_path = old_cache / old_filename;
fs::path etag_path = old_path.string() + ".etag";
if (!fs::exists(old_path)) {
if (file && fs::exists(file->final_path)) {
return true;
}
LOG_WRN("%s: %s not found in old cache or HF cache\n", __func__, old_filename.c_str());
return false;
}
if (!file) {
LOG_WRN("%s: %s not found in current repo\n", __func__, old_filename.c_str());
return false;
}
if (!sha256.empty() && !file->oid.empty() && sha256 != file->oid) {
LOG_WRN("%s: %s is not up to date (sha256 mismatch)\n", __func__, old_filename.c_str());
return false;
}
if (file->size > 0) {
size_t size = fs::file_size(old_path);
if (size != file->size) {
LOG_WRN("%s: %s has wrong size %zu (expected %zu)\n", __func__, old_filename.c_str(), size, file->size);
return false;
}
}
to_migrate.push_back({path, sha256, file->size, old_path, etag_path, file});
return true;
}
static bool collect_files(const fs::path & old_cache,
const std::string & owner,
const std::string & repo,
const nl::json & node,
const hf_files & files,
migrate_files & to_migrate) {
if (!node.contains("rfilename") ||
!node.contains("lfs") ||
!node["lfs"].contains("sha256")) {
return true;
}
std::string path = node["rfilename"];
std::string sha256 = node["lfs"]["sha256"];
auto split = get_gguf_split_info(path);
if (split.count <= 1) {
return collect_file(old_cache, owner, repo, path, sha256, files, to_migrate);
}
std::vector<std::pair<std::string, std::string>> splits;
for (const auto & f : files) {
auto split_f = get_gguf_split_info(f.path);
if (split_f.count == split.count && split_f.prefix == split.prefix) {
// sadly the manifest only provides the sha256 of the first file (index == 1)
// the rest will be verified using the size...
std::string f_sha256 = (split_f.index == 1) ? sha256 : "";
splits.emplace_back(f.path, f_sha256);
}
}
if ((int)splits.size() != split.count) {
LOG_WRN("%s: expected %d split files but found %d in repo\n", __func__, split.count, (int)splits.size());
return false;
}
for (const auto & [f_path, f_sha256] : splits) {
if (!collect_file(old_cache, owner, repo, f_path, f_sha256, files, to_migrate)) {
return false;
}
}
return true;
}
static bool migrate_file(const migrate_file & file) {
std::error_code ec;
fs::path new_path(file.file->local_path);
fs::create_directories(new_path.parent_path(), ec);
if (!fs::exists(new_path, ec)) {
fs::rename(file.old_path, new_path, ec);
if (ec) {
fs::copy_file(file.old_path, new_path, ec);
if (ec) {
LOG_ERR("%s: failed to move/copy %s: %s\n", __func__, file.old_path.string().c_str(), ec.message().c_str());
return false;
}
}
fs::remove(file.old_path, ec);
}
fs::remove(file.etag_path, ec);
std::string filename = finalize_file(*file.file);
LOG_INF("%s: migrated %s -> %s\n", __func__, file.old_path.filename().string().c_str(), filename.c_str());
return true;
}
void migrate_old_cache_to_hf_cache(const std::string & token, bool offline) {
fs::path old_cache = fs_get_cache_directory();
if (!fs::exists(old_cache)) {
return;
}
if (offline) {
LOG_WRN("%s: skipping migration in offline mode (will run when online)\n", __func__);
return; // -hf is not going to work
}
bool warned = false;
for (const auto & entry : fs::directory_iterator(old_cache)) {
if (!entry.is_regular_file()) {
continue;
}
auto filename = entry.path().filename().string();
auto [owner, repo] = parse_manifest_name(filename);
if (owner.empty() || repo.empty()) {
continue;
}
if (!warned) {
warned = true;
LOG_WRN("================================================================================\n"
"WARNING: Migrating cache to HuggingFace cache directory\n"
" Old cache: %s\n"
" New cache: %s\n"
"This one-time migration moves models previously downloaded with -hf\n"
"from the legacy llama.cpp cache to the standard HuggingFace cache.\n"
"Models downloaded with --model-url are not affected.\n"
"================================================================================\n",
old_cache.string().c_str(), get_cache_directory().string().c_str());
}
auto repo_id = owner + "/" + repo;
auto files = get_repo_files(repo_id, token);
if (files.empty()) {
LOG_WRN("%s: could not get repo files for %s, skipping\n", __func__, repo_id.c_str());
continue;
}
migrate_files to_migrate;
bool ok = true;
try {
std::ifstream manifest(entry.path());
auto json = nl::json::parse(manifest);
for (const char * key : {"ggufFile", "mmprojFile"}) {
if (json.contains(key)) {
if (!collect_files(old_cache, owner, repo, json[key], files, to_migrate)) {
ok = false;
break;
}
}
}
} catch (const std::exception & e) {
LOG_WRN("%s: failed to parse manifest %s: %s\n", __func__, filename.c_str(), e.what());
continue;
}
if (!ok) {
LOG_WRN("%s: migration skipped: one or more files failed validation\n", __func__);
continue;
}
for (const auto & file : to_migrate) {
if (!migrate_file(file)) {
ok = false;
break;
}
}
if (!ok) {
LOG_WRN("%s: migration failed: could not migrate all files\n", __func__);
continue;
}
LOG_INF("%s: migration complete, deleting manifest: %s\n", __func__, entry.path().string().c_str());
fs::remove(entry.path());
}
}
} // namespace hf_cache
+4
View File
@@ -14,6 +14,7 @@ struct hf_file {
std::string final_path;
std::string oid;
std::string repo_id;
size_t size = 0; // only for the migration
};
using hf_files = std::vector<hf_file>;
@@ -29,4 +30,7 @@ hf_files get_cached_files(const std::string & repo_id = {});
// Create snapshot path (link or move/copy) and return it
std::string finalize_file(const hf_file & file);
// TODO: Remove later
void migrate_old_cache_to_hf_cache(const std::string & token, bool offline = false);
} // namespace hf_cache
+2 -2
View File
@@ -435,10 +435,10 @@ void common_log_flush(struct common_log * log) {
static int common_get_verbosity(enum ggml_log_level level) {
switch (level) {
case GGML_LOG_LEVEL_DEBUG: return LOG_LEVEL_DEBUG;
case GGML_LOG_LEVEL_INFO: return LOG_LEVEL_TRACE;
case GGML_LOG_LEVEL_INFO: return LOG_LEVEL_INFO;
case GGML_LOG_LEVEL_WARN: return LOG_LEVEL_WARN;
case GGML_LOG_LEVEL_ERROR: return LOG_LEVEL_ERROR;
case GGML_LOG_LEVEL_CONT: return LOG_LEVEL_TRACE;
case GGML_LOG_LEVEL_CONT: return LOG_LEVEL_INFO; // same as INFO
case GGML_LOG_LEVEL_NONE:
default:
return LOG_LEVEL_OUTPUT;
+2 -5
View File
@@ -21,8 +21,7 @@
# define LOG_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__)))
#endif
#define LOG_LEVEL_DEBUG 5
#define LOG_LEVEL_TRACE 4
#define LOG_LEVEL_DEBUG 4
#define LOG_LEVEL_INFO 3
#define LOG_LEVEL_WARN 2
#define LOG_LEVEL_ERROR 1
@@ -112,15 +111,13 @@ void common_log_flush (struct common_log * log); // f
#define LOGV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_NONE, verbosity, __VA_ARGS__)
#define LOG_DBG(...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, LOG_LEVEL_DEBUG, __VA_ARGS__)
#define LOG_TRC(...) LOG_TMPL(GGML_LOG_LEVEL_INFO, LOG_LEVEL_TRACE, __VA_ARGS__)
#define LOG_INF(...) LOG_TMPL(GGML_LOG_LEVEL_INFO, LOG_LEVEL_INFO, __VA_ARGS__)
#define LOG_WRN(...) LOG_TMPL(GGML_LOG_LEVEL_WARN, LOG_LEVEL_WARN, __VA_ARGS__)
#define LOG_ERR(...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, LOG_LEVEL_ERROR, __VA_ARGS__)
#define LOG_CNT(...) LOG_TMPL(GGML_LOG_LEVEL_CONT, LOG_LEVEL_INFO, __VA_ARGS__) // same as INFO
#define LOG_DBGV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, verbosity, __VA_ARGS__)
#define LOG_TRCV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_TRACE, verbosity, __VA_ARGS__)
#define LOG_INFV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_INFO, verbosity, __VA_ARGS__)
#define LOG_WRNV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_WARN, verbosity, __VA_ARGS__)
#define LOG_ERRV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, verbosity, __VA_ARGS__)
#define LOG_DBGV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_DEBUG, verbosity, __VA_ARGS__)
#define LOG_CNTV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_CONT, verbosity, __VA_ARGS__)
+3 -3
View File
@@ -471,7 +471,7 @@ void common_ngram_map_draft(common_ngram_map & map,
sum_occur += curr_occur;
}
LOG_DBG("%s: key_offset = %zu, max_occur = %d, sum_occur = %d, slot_max = %d [%zu/%d, %zu/%d, %zu/%d, %zu/%d]\n", __func__,
LOG_INF("%s: key_offset = %zu, max_occur = %d, sum_occur = %d, slot_max = %d [%zu/%d, %zu/%d, %zu/%d, %zu/%d]\n", __func__,
key_offset,
max_occur, sum_occur, slot_max,
curr_key.values[0].value_idx, curr_key.values[0].value_num,
@@ -482,7 +482,7 @@ void common_ngram_map_draft(common_ngram_map & map,
// Print the tokens of the four values (if idx != 0), use LOG_INF
for (int v = 0; v < COMMON_NGRAM_MAX_VALUES; ++v) {
if (curr_key.values[v].value_idx != 0) {
LOG_DBG("%s: value[%d] = %s\n", __func__, v, common_tokens_to_str(inp, curr_key.values[v].value_idx, m).c_str());
LOG_INF("%s: value[%d] = %s\n", __func__, v, common_tokens_to_str(inp, curr_key.values[v].value_idx, m).c_str());
}
}
@@ -500,7 +500,7 @@ void common_ngram_map_draft(common_ngram_map & map,
draft.push_back(inp[match_pos + n + i]);
}
LOG_DBG("%s: key_offset = %zu, slot_max = %d, key_num = %d, draft.size = %zu\n", __func__,
LOG_INF("%s: key_offset = %zu, slot_max = %d, key_num = %d, draft.size = %zu\n", __func__,
key_offset, slot_max,
curr_key.key_num, draft.size());
+1 -6
View File
@@ -163,13 +163,8 @@ void common_preset::merge(const common_preset & other) {
}
}
void common_preset::apply_to_params(common_params & params, const std::set<std::string> & handled_keys) const {
void common_preset::apply_to_params(common_params & params) const {
for (const auto & [opt, val] : options) {
if (!handled_keys.empty()) {
if (!opt.env || handled_keys.find(opt.env) == handled_keys.end()) {
continue;
}
}
// apply each option to params
if (opt.handler_string) {
opt.handler_string(params, val);
+1 -2
View File
@@ -43,8 +43,7 @@ struct common_preset {
void merge(const common_preset & other);
// apply preset options to common_params
// optionally specify handled_keys to only apply a subset of options (identified by their env), if empty, apply all options
void apply_to_params(common_params & params, const std::set<std::string> & handled_keys = std::set<std::string>()) const;
void apply_to_params(common_params & params) const;
};
// interface for multiple presets in one file
+13 -10
View File
@@ -158,6 +158,8 @@ static void common_reasoning_budget_apply(struct llama_sampler * smpl, llama_tok
for (size_t i = 0; i < cur_p->size; i++) {
if (cur_p->data[i].id != forced) {
cur_p->data[i].logit = -INFINITY;
} else {
cur_p->data[i].logit = +INFINITY; // force the token
}
}
}
@@ -171,12 +173,22 @@ static void common_reasoning_budget_reset(struct llama_sampler * smpl) {
ctx->force_pos = 0;
}
// forward declaration for use in clone
static struct llama_sampler * common_reasoning_budget_init_state(
const struct llama_vocab * vocab, const std::vector<llama_token> & start_tokens,
const std::vector<llama_token> & end_tokens, const std::vector<llama_token> & forced_tokens,
int32_t budget, common_reasoning_budget_state initial_state);
static struct llama_sampler * common_reasoning_budget_clone(const struct llama_sampler * smpl);
static struct llama_sampler * common_reasoning_budget_clone(const struct llama_sampler * smpl) {
const auto * ctx = (const common_reasoning_budget_ctx *) smpl->ctx;
return common_reasoning_budget_init_state(
ctx->vocab,
ctx->start_matcher.tokens,
ctx->end_matcher.tokens,
ctx->forced_tokens,
ctx->budget,
ctx->state);
}
static void common_reasoning_budget_free(struct llama_sampler * smpl) {
delete (common_reasoning_budget_ctx *) smpl->ctx;
@@ -195,15 +207,6 @@ static struct llama_sampler_i common_reasoning_budget_i = {
/* .backend_set_input = */ nullptr,
};
static struct llama_sampler * common_reasoning_budget_clone(const struct llama_sampler * smpl) {
const auto * ctx = (const common_reasoning_budget_ctx *) smpl->ctx;
return llama_sampler_init(
/* .iface = */ &common_reasoning_budget_i,
/* .ctx = */ new common_reasoning_budget_ctx(*ctx)
);
}
static struct llama_sampler * common_reasoning_budget_init_state(
const struct llama_vocab * vocab,
const std::vector<llama_token> & start_tokens,
+6 -8
View File
@@ -547,8 +547,6 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
auto & chain = gsmpl->chain;
auto & cur_p = gsmpl->cur_p; // initialized by set_logits
gsmpl->set_logits(ctx, idx);
// Check if a backend sampler has already sampled a token in which case we
// return that token id directly.
{
@@ -560,17 +558,17 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
GGML_ASSERT(!gsmpl->grmr && "using grammar in combination with backend sampling is not supported");
GGML_ASSERT(!gsmpl->rbudget && "using reasoning budget in combination with backend sampling is not supported");
for (size_t i = 0; i < cur_p.size; ++i) {
if (cur_p.data[i].id == id) {
cur_p.selected = i;
break;
}
}
// TODO: simplify
gsmpl->cur.resize(1);
gsmpl->cur[0] = { id, 0.0f, 1.0f };
cur_p = { gsmpl->cur.data(), gsmpl->cur.size(), 0, true };
return id;
}
}
gsmpl->set_logits(ctx, idx);
// apply reasoning budget first
llama_sampler_apply(rbudget, &cur_p);

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