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@@ -4,7 +4,7 @@
|
||||
|
||||
# Define the CANN base image for easier version updates later
|
||||
ARG CHIP_TYPE=910b
|
||||
ARG CANN_BASE_IMAGE=quay.io/ascend/cann:8.3.rc2-${CHIP_TYPE}-openeuler24.03-py3.11
|
||||
ARG CANN_BASE_IMAGE=quay.io/ascend/cann:8.5.0-${CHIP_TYPE}-openeuler24.03-py3.11
|
||||
|
||||
# ==============================================================================
|
||||
# BUILD STAGE
|
||||
|
||||
@@ -1,11 +1,13 @@
|
||||
ARG UBUNTU_VERSION=22.04
|
||||
ARG UBUNTU_VERSION=24.04
|
||||
|
||||
FROM ubuntu:$UBUNTU_VERSION AS build
|
||||
|
||||
ARG TARGETARCH
|
||||
|
||||
RUN apt-get update && \
|
||||
apt-get install -y build-essential git cmake libssl-dev
|
||||
apt-get install -y gcc-14 g++-14 build-essential git cmake libssl-dev
|
||||
|
||||
ENV CC=gcc-14 CXX=g++-14
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
@@ -34,7 +36,7 @@ RUN mkdir -p /app/full \
|
||||
FROM ubuntu:$UBUNTU_VERSION AS base
|
||||
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y libgomp1 curl\
|
||||
&& apt-get install -y libgomp1 curl \
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
&& rm -rf /tmp/* /var/tmp/* \
|
||||
@@ -55,8 +57,9 @@ RUN apt-get update \
|
||||
git \
|
||||
python3 \
|
||||
python3-pip \
|
||||
&& pip install --upgrade pip setuptools wheel \
|
||||
&& pip install -r requirements.txt \
|
||||
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/* \
|
||||
|
||||
@@ -1,95 +0,0 @@
|
||||
ARG UBUNTU_VERSION=24.04
|
||||
# This needs to generally match the container host's environment.
|
||||
ARG CUDA_VERSION=13.1.0
|
||||
# Target the CUDA build image
|
||||
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
|
||||
|
||||
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
|
||||
|
||||
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
|
||||
|
||||
# CUDA architecture to build for (defaults to all supported archs)
|
||||
ARG CUDA_DOCKER_ARCH=default
|
||||
|
||||
RUN apt-get update && \
|
||||
apt-get install -y build-essential cmake python3 python3-pip git libssl-dev libgomp1
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
COPY . .
|
||||
|
||||
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
|
||||
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
|
||||
fi && \
|
||||
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
|
||||
cmake --build build --config Release -j$(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 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 ${BASE_CUDA_RUN_CONTAINER} AS base
|
||||
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y libgomp1 curl\
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
&& rm -rf /tmp/* /var/tmp/* \
|
||||
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
|
||||
&& find /var/cache -type f -delete
|
||||
|
||||
COPY --from=build /app/lib/ /app
|
||||
|
||||
### Full
|
||||
FROM base AS full
|
||||
|
||||
COPY --from=build /app/full /app
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y \
|
||||
git \
|
||||
python3 \
|
||||
python3-pip \
|
||||
python3-wheel \
|
||||
&& pip install --break-system-packages --upgrade setuptools \
|
||||
&& pip install --break-system-packages -r requirements.txt \
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
&& rm -rf /tmp/* /var/tmp/* \
|
||||
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
|
||||
&& find /var/cache -type f -delete
|
||||
|
||||
|
||||
ENTRYPOINT ["/app/tools.sh"]
|
||||
|
||||
### Light, CLI only
|
||||
FROM base AS light
|
||||
|
||||
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
ENTRYPOINT [ "/app/llama-cli" ]
|
||||
|
||||
### Server, Server only
|
||||
FROM base AS server
|
||||
|
||||
ENV LLAMA_ARG_HOST=0.0.0.0
|
||||
|
||||
COPY --from=build /app/full/llama-server /app
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
|
||||
|
||||
ENTRYPOINT [ "/app/llama-server" ]
|
||||
@@ -1,6 +1,6 @@
|
||||
ARG UBUNTU_VERSION=22.04
|
||||
ARG UBUNTU_VERSION=24.04
|
||||
# This needs to generally match the container host's environment.
|
||||
ARG CUDA_VERSION=12.4.0
|
||||
ARG CUDA_VERSION=12.8.1
|
||||
# Target the CUDA build image
|
||||
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
|
||||
|
||||
@@ -12,7 +12,9 @@ FROM ${BASE_CUDA_DEV_CONTAINER} AS build
|
||||
ARG CUDA_DOCKER_ARCH=default
|
||||
|
||||
RUN apt-get update && \
|
||||
apt-get install -y build-essential cmake python3 python3-pip git libssl-dev libgomp1
|
||||
apt-get install -y gcc-14 g++-14 build-essential cmake python3 python3-pip git libssl-dev libgomp1
|
||||
|
||||
ENV CC=gcc-14 CXX=g++-14 CUDAHOSTCXX=g++-14
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
@@ -39,7 +41,7 @@ RUN mkdir -p /app/full \
|
||||
FROM ${BASE_CUDA_RUN_CONTAINER} AS base
|
||||
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y libgomp1 curl\
|
||||
&& apt-get install -y libgomp1 curl \
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
&& rm -rf /tmp/* /var/tmp/* \
|
||||
@@ -60,7 +62,8 @@ RUN apt-get update \
|
||||
git \
|
||||
python3 \
|
||||
python3-pip \
|
||||
&& pip install --upgrade pip setuptools wheel \
|
||||
python3-wheel \
|
||||
&& pip install --break-system-packages --upgrade setuptools \
|
||||
&& pip install --break-system-packages -r requirements.txt \
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
|
||||
@@ -33,8 +33,25 @@ RUN mkdir -p /app/full \
|
||||
|
||||
FROM intel/deep-learning-essentials:$ONEAPI_VERSION AS base
|
||||
|
||||
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 \
|
||||
&& wget https://github.com/intel/compute-runtime/releases/download/$COMPUTE_RUNTIME_VERSION/intel-ocloc-dbgsym_${COMPUTE_RUNTIME_VERSION_FULL}_amd64.ddeb \
|
||||
&& wget https://github.com/intel/compute-runtime/releases/download/$COMPUTE_RUNTIME_VERSION/intel-ocloc_${COMPUTE_RUNTIME_VERSION_FULL}_amd64.deb \
|
||||
&& wget https://github.com/intel/compute-runtime/releases/download/$COMPUTE_RUNTIME_VERSION/intel-opencl-icd-dbgsym_${COMPUTE_RUNTIME_VERSION_FULL}_amd64.ddeb \
|
||||
&& wget https://github.com/intel/compute-runtime/releases/download/$COMPUTE_RUNTIME_VERSION/intel-opencl-icd_${COMPUTE_RUNTIME_VERSION_FULL}_amd64.deb \
|
||||
&& wget https://github.com/intel/compute-runtime/releases/download/$COMPUTE_RUNTIME_VERSION/libigdgmm12_${IGDGMM_VERSION}_amd64.deb \
|
||||
&& wget https://github.com/intel/compute-runtime/releases/download/$COMPUTE_RUNTIME_VERSION/libze-intel-gpu1-dbgsym_${COMPUTE_RUNTIME_VERSION_FULL}_amd64.ddeb \
|
||||
&& wget https://github.com/intel/compute-runtime/releases/download/$COMPUTE_RUNTIME_VERSION/libze-intel-gpu1_${COMPUTE_RUNTIME_VERSION_FULL}_amd64.deb \
|
||||
&& dpkg --install *.deb
|
||||
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y libgomp1 curl\
|
||||
&& apt-get install -y libgomp1 curl \
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
&& rm -rf /tmp/* /var/tmp/* \
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
ARG ASCEND_VERSION=8.1.RC1.alpha001-910b-openeuler22.03-py3.10
|
||||
ARG ASCEND_VERSION=8.5.0-910b-openeuler22.03-py3.10
|
||||
|
||||
FROM ascendai/cann:$ASCEND_VERSION AS build
|
||||
|
||||
|
||||
@@ -46,7 +46,7 @@ RUN mkdir -p /app/full \
|
||||
FROM ${BASE_MUSA_RUN_CONTAINER} AS base
|
||||
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y libgomp1 curl\
|
||||
&& apt-get install -y libgomp1 curl \
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
&& rm -rf /tmp/* /var/tmp/* \
|
||||
|
||||
@@ -16,7 +16,7 @@
|
||||
rocmPackages,
|
||||
vulkan-headers,
|
||||
vulkan-loader,
|
||||
curl,
|
||||
openssl,
|
||||
shaderc,
|
||||
useBlas ?
|
||||
builtins.all (x: !x) [
|
||||
@@ -41,6 +41,7 @@
|
||||
effectiveStdenv ? if useCuda then cudaPackages.backendStdenv else stdenv,
|
||||
enableStatic ? effectiveStdenv.hostPlatform.isStatic,
|
||||
precompileMetalShaders ? false,
|
||||
useWebUi ? true,
|
||||
}:
|
||||
|
||||
let
|
||||
@@ -159,11 +160,13 @@ effectiveStdenv.mkDerivation (finalAttrs: {
|
||||
++ optionals useMpi [ mpi ]
|
||||
++ optionals useRocm rocmBuildInputs
|
||||
++ optionals useBlas [ blas ]
|
||||
++ optionals useVulkan vulkanBuildInputs;
|
||||
++ optionals useVulkan vulkanBuildInputs
|
||||
++ [ openssl ];
|
||||
|
||||
cmakeFlags =
|
||||
[
|
||||
(cmakeBool "LLAMA_BUILD_SERVER" true)
|
||||
(cmakeBool "LLAMA_BUILD_WEBUI" useWebUi)
|
||||
(cmakeBool "BUILD_SHARED_LIBS" (!enableStatic))
|
||||
(cmakeBool "CMAKE_SKIP_BUILD_RPATH" true)
|
||||
(cmakeBool "GGML_NATIVE" false)
|
||||
|
||||
@@ -78,7 +78,7 @@ ARG http_proxy
|
||||
ARG https_proxy
|
||||
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y libgomp1 libtbb12 curl\
|
||||
&& apt-get install -y libgomp1 libtbb12 curl \
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
&& rm -rf /tmp/* /var/tmp/* \
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
ARG UBUNTU_VERSION=24.04
|
||||
|
||||
# This needs to generally match the container host's environment.
|
||||
ARG ROCM_VERSION=7.2
|
||||
ARG AMDGPU_VERSION=7.2
|
||||
ARG ROCM_VERSION=7.2.1
|
||||
ARG AMDGPU_VERSION=7.2.1
|
||||
|
||||
# Target the ROCm build image
|
||||
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
|
||||
@@ -12,11 +12,11 @@ FROM ${BASE_ROCM_DEV_CONTAINER} AS build
|
||||
|
||||
# Unless otherwise specified, we make a fat build.
|
||||
# This is mostly tied to rocBLAS supported archs.
|
||||
# check https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.2.0/reference/system-requirements.html
|
||||
# check https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.2.1/reference/system-requirements.html
|
||||
# check https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/docs/compatibility/compatibilityrad/native_linux/native_linux_compatibility.html
|
||||
# check https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/docs/compatibility/compatibilityryz/native_linux/native_linux_compatibility.html
|
||||
|
||||
ARG ROCM_DOCKER_ARCH='gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1151;gfx1150;gfx1200;gfx1201'
|
||||
ARG ROCM_DOCKER_ARCH='gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1151;gfx1150;gfx1200;gfx1201'
|
||||
|
||||
# Set ROCm architectures
|
||||
ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}
|
||||
@@ -58,7 +58,7 @@ RUN mkdir -p /app/full \
|
||||
FROM ${BASE_ROCM_DEV_CONTAINER} AS base
|
||||
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y libgomp1 curl\
|
||||
&& apt-get install -y libgomp1 curl \
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
&& rm -rf /tmp/* /var/tmp/* \
|
||||
@@ -79,7 +79,7 @@ RUN apt-get update \
|
||||
git \
|
||||
python3-pip \
|
||||
python3 \
|
||||
python3-wheel\
|
||||
python3-wheel \
|
||||
&& pip install --break-system-packages --upgrade setuptools \
|
||||
&& pip install --break-system-packages -r requirements.txt \
|
||||
&& apt autoremove -y \
|
||||
|
||||
@@ -49,17 +49,20 @@ COPY --from=build /app/full /app
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
ENV PATH="/root/.venv/bin:/root/.local/bin:${PATH}"
|
||||
|
||||
# Flag for compatibility with pip
|
||||
ARG UV_INDEX_STRATEGY="unsafe-best-match"
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y \
|
||||
build-essential \
|
||||
curl \
|
||||
git \
|
||||
python3.13 \
|
||||
python3.13-dev \
|
||||
python3-pip \
|
||||
python3-wheel \
|
||||
&& update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.13 100 \
|
||||
&& pip install --break-system-packages --upgrade setuptools \
|
||||
&& pip install --break-system-packages -r requirements.txt \
|
||||
ca-certificates \
|
||||
&& curl -LsSf https://astral.sh/uv/install.sh | sh \
|
||||
&& uv python install 3.13 \
|
||||
&& uv venv --python 3.13 /root/.venv \
|
||||
&& uv pip install --python /root/.venv/bin/python -r requirements.txt \
|
||||
&& apt autoremove -y \
|
||||
&& apt clean -y \
|
||||
&& rm -rf /tmp/* /var/tmp/* \
|
||||
|
||||
@@ -21,14 +21,6 @@ indent_style = tab
|
||||
[prompts/*.txt]
|
||||
insert_final_newline = unset
|
||||
|
||||
[tools/server/public/*]
|
||||
indent_size = 2
|
||||
|
||||
[tools/server/public/deps_*]
|
||||
trim_trailing_whitespace = unset
|
||||
indent_style = unset
|
||||
indent_size = unset
|
||||
|
||||
[tools/server/deps_*]
|
||||
trim_trailing_whitespace = unset
|
||||
indent_style = unset
|
||||
@@ -61,6 +53,14 @@ charset = unset
|
||||
trim_trailing_whitespace = unset
|
||||
insert_final_newline = unset
|
||||
|
||||
[tools/server/public/**]
|
||||
indent_style = unset
|
||||
indent_size = unset
|
||||
end_of_line = unset
|
||||
charset = unset
|
||||
trim_trailing_whitespace = unset
|
||||
insert_final_newline = unset
|
||||
|
||||
[benches/**]
|
||||
indent_style = unset
|
||||
indent_size = unset
|
||||
|
||||
4
.gitattributes
vendored
Normal file
4
.gitattributes
vendored
Normal 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
|
||||
@@ -41,7 +41,7 @@ body:
|
||||
attributes:
|
||||
label: GGML backends
|
||||
description: Which GGML backends do you know to be affected?
|
||||
options: [AMX, BLAS, CANN, CPU, CUDA, Hexagon, HIP, Metal, Musa, OpenCL, RPC, SYCL, VirtGPU, Vulkan, WebGPU, zDNN, ZenDNN]
|
||||
options: [AMX, BLAS, CANN, CPU, CUDA, Hexagon, HIP, Metal, Musa, OpenCL, OpenVINO, RPC, SYCL, VirtGPU, Vulkan, WebGPU, zDNN, ZenDNN]
|
||||
multiple: true
|
||||
validations:
|
||||
required: true
|
||||
|
||||
2
.github/ISSUE_TEMPLATE/011-bug-results.yml
vendored
2
.github/ISSUE_TEMPLATE/011-bug-results.yml
vendored
@@ -42,7 +42,7 @@ body:
|
||||
attributes:
|
||||
label: GGML backends
|
||||
description: Which GGML backends do you know to be affected?
|
||||
options: [AMX, BLAS, CANN, CPU, CUDA, Hexagon, HIP, Metal, Musa, OpenCL, RPC, SYCL, VirtGPU, Vulkan, WebGPU, zDNN, ZenDNN]
|
||||
options: [AMX, BLAS, CANN, CPU, CUDA, Hexagon, HIP, Metal, Musa, OpenCL, OpenVINO, RPC, SYCL, VirtGPU, Vulkan, WebGPU, zDNN, ZenDNN]
|
||||
multiple: true
|
||||
validations:
|
||||
required: true
|
||||
|
||||
25
.github/labeler.yml
vendored
25
.github/labeler.yml
vendored
@@ -27,6 +27,11 @@ IBM zDNN:
|
||||
- any-glob-to-any-file:
|
||||
- ggml/include/ggml-zdnn.h
|
||||
- ggml/src/ggml-zdnn/**
|
||||
AMD ZenDNN:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- ggml/include/ggml-zendnn.h
|
||||
- ggml/src/ggml-zendnn/**
|
||||
documentation:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
@@ -68,10 +73,26 @@ android:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- examples/llama.android/**
|
||||
server/webui:
|
||||
- changed-files:
|
||||
- all:
|
||||
- any-glob-to-any-file:
|
||||
- tools/server/webui/**
|
||||
- tools/server/public/**
|
||||
- all-globs-to-all-files:
|
||||
- '!tools/server/webui/**'
|
||||
- '!tools/server/public/**'
|
||||
server:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- tools/server/**
|
||||
- all:
|
||||
- any-glob-to-any-file:
|
||||
- tools/server/**
|
||||
- all-globs-to-all-files:
|
||||
- '!tools/server/webui/**'
|
||||
- '!tools/server/public/**'
|
||||
|
||||
|
||||
|
||||
ggml:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
|
||||
85
.github/workflows/build-android.yml
vendored
85
.github/workflows/build-android.yml
vendored
@@ -40,13 +40,9 @@ jobs:
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v6
|
||||
|
||||
# Disabled due to size (400MB) and always 0 cache hits
|
||||
# - name: ccache
|
||||
# uses: ggml-org/ccache-action@v1.2.16
|
||||
# with:
|
||||
# key: android-build
|
||||
# evict-old-files: 1d
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: false
|
||||
|
||||
- name: Set up JDK
|
||||
uses: actions/setup-java@v5
|
||||
@@ -55,7 +51,7 @@ jobs:
|
||||
distribution: zulu
|
||||
|
||||
- name: Setup Android SDK
|
||||
uses: android-actions/setup-android@v3
|
||||
uses: android-actions/setup-android@9fc6c4e9069bf8d3d10b2204b1fb8f6ef7065407 # v3
|
||||
with:
|
||||
log-accepted-android-sdk-licenses: false
|
||||
|
||||
@@ -66,10 +62,11 @@ jobs:
|
||||
|
||||
android-ndk:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
env:
|
||||
OPENCL_VERSION: 2025.07.22
|
||||
|
||||
container:
|
||||
image: 'ghcr.io/snapdragon-toolchain/arm64-android:v0.3'
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
@@ -82,59 +79,23 @@ jobs:
|
||||
- name: Clone
|
||||
id: checkout
|
||||
uses: actions/checkout@v6
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: false
|
||||
|
||||
- name: Install OpenCL Headers and Libs
|
||||
id: install_opencl
|
||||
if: ${{ matrix.build == 'arm64-snapdragon' }}
|
||||
run: |
|
||||
mkdir opencl
|
||||
curl -L -o opencl/clhpp.tar.gz https://github.com/KhronosGroup/OpenCL-CLHPP/archive/refs/tags/v${OPENCL_VERSION}.tar.gz
|
||||
curl -L -o opencl/headers.tar.gz https://github.com/KhronosGroup/OpenCL-Headers/archive/refs/tags/v${OPENCL_VERSION}.tar.gz
|
||||
curl -L -o opencl/icd-loader.tar.gz https://github.com/KhronosGroup/OpenCL-ICD-Loader/archive/refs/tags/v${OPENCL_VERSION}.tar.gz
|
||||
tar -xaf opencl/headers.tar.gz -C opencl
|
||||
tar -xaf opencl/clhpp.tar.gz -C opencl
|
||||
tar -xaf opencl/icd-loader.tar.gz -C opencl
|
||||
sudo cp -r opencl/OpenCL-Headers-${OPENCL_VERSION}/CL ${ANDROID_NDK_ROOT}/toolchains/llvm/prebuilt/linux-x86_64/sysroot/usr/include
|
||||
sudo cp -r opencl/OpenCL-CLHPP-${OPENCL_VERSION}/include/CL/* ${ANDROID_NDK_ROOT}/toolchains/llvm/prebuilt/linux-x86_64/sysroot/usr/include/CL
|
||||
cd opencl/OpenCL-ICD-Loader-${OPENCL_VERSION}
|
||||
cmake -B build -G Ninja -DCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE=${ANDROID_NDK_ROOT}/build/cmake/android.toolchain.cmake -DOPENCL_ICD_LOADER_HEADERS_DIR=${ANDROID_NDK_ROOT}/toolchains/llvm/prebuilt/linux-x86_64/sysroot/usr/include -DANDROID_ABI=arm64-v8a -DANDROID_PLATFORM=31 -DANDROID_STL=c++_shared
|
||||
cmake --build build
|
||||
sudo cp build/libOpenCL.so ${ANDROID_NDK_ROOT}/toolchains/llvm/prebuilt/linux-x86_64/sysroot/usr/lib/aarch64-linux-android
|
||||
rm -rf opencl
|
||||
|
||||
- name: Install Hexagon SDK
|
||||
id: install_hexsdk
|
||||
if: ${{ matrix.build == 'arm64-snapdragon' }}
|
||||
env:
|
||||
HEXSDK_VER: 6.4.0.2
|
||||
HEXTLS_VER: 19.0.04
|
||||
run: |
|
||||
curl -L -o hex-sdk.tar.gz https://github.com/snapdragon-toolchain/hexagon-sdk/releases/download/v$HEXSDK_VER/hexagon-sdk-v$HEXSDK_VER-amd64-lnx.tar.xz
|
||||
mkdir hex-sdk
|
||||
tar -xaf hex-sdk.tar.gz -C hex-sdk
|
||||
ls -l hex-sdk
|
||||
sudo mv hex-sdk /opt/hexagon
|
||||
echo "HEXAGON_SDK_ROOT=/opt/hexagon/$HEXSDK_VER" >> "$GITHUB_ENV"
|
||||
echo "HEXAGON_TOOLS_ROOT=/opt/hexagon/$HEXSDK_VER/tools/HEXAGON_Tools/$HEXTLS_VER" >> "$GITHUB_ENV"
|
||||
echo "DEFAULT_HLOS_ARCH=64" >> "$GITHUB_ENV"
|
||||
echo "DEFAULT_TOOLS_VARIANT=toolv19" >> "$GITHUB_ENV"
|
||||
echo "DEFAULT_NO_QURT_INC=0" >> "$GITHUB_ENV"
|
||||
echo "DEFAULT_DSP_ARCH=v73" >> "$GITHUB_ENV"
|
||||
|
||||
- name: Update CMake presets
|
||||
id: update_presets
|
||||
if: ${{ matrix.build == 'arm64-snapdragon' }}
|
||||
run: |
|
||||
cp docs/backend/snapdragon/CMakeUserPresets.json .
|
||||
|
||||
- name: Build
|
||||
id: ndk_build
|
||||
- name: Build Llama.CPP for Hexagon Android
|
||||
id: build_llama_cpp_hexagon_android
|
||||
run: |
|
||||
if [[ "${{ matrix.build }}" == "arm64-snapdragon" ]]; then
|
||||
cp docs/backend/snapdragon/CMakeUserPresets.json .
|
||||
fi
|
||||
cmake ${{ matrix.defines }} -B build
|
||||
cmake --build build
|
||||
cmake --install build --prefix pkg-adb/llama.cpp
|
||||
|
||||
- name: Test
|
||||
id: cmake_test
|
||||
run: |
|
||||
echo "FIXME: test on devices"
|
||||
- name: Upload Llama.CPP Hexagon Android Build Artifact
|
||||
if: ${{ always() && steps.build_llama_cpp_hexagon_android.outcome == 'success' }}
|
||||
uses: actions/upload-artifact@v6
|
||||
with:
|
||||
name: llama-cpp-android-${{ matrix.build }}
|
||||
path: pkg-adb/llama.cpp
|
||||
|
||||
2
.github/workflows/build-cann.yml
vendored
2
.github/workflows/build-cann.yml
vendored
@@ -63,7 +63,7 @@ jobs:
|
||||
- name: Set container image
|
||||
id: cann-image
|
||||
run: |
|
||||
image="ascendai/cann:${{ matrix.chip_type == '910b' && '8.3.rc2-910b-openeuler24.03-py3.11' || '8.3.rc2-310p-openeuler24.03-py3.11' }}"
|
||||
image="ascendai/cann:${{ 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
|
||||
|
||||
2
.github/workflows/build-msys.yml
vendored
2
.github/workflows/build-msys.yml
vendored
@@ -43,7 +43,7 @@ jobs:
|
||||
# save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
|
||||
|
||||
- name: Setup ${{ matrix.sys }}
|
||||
uses: msys2/setup-msys2@v2
|
||||
uses: msys2/setup-msys2@cafece8e6baf9247cf9b1bf95097b0b983cc558d # v2
|
||||
with:
|
||||
update: true
|
||||
msystem: ${{matrix.sys}}
|
||||
|
||||
38
.github/workflows/build-riscv.yml
vendored
38
.github/workflows/build-riscv.yml
vendored
@@ -35,7 +35,7 @@ env:
|
||||
|
||||
jobs:
|
||||
ubuntu-riscv64-native-sanitizer:
|
||||
runs-on: RISCV64
|
||||
runs-on: ubuntu-24.04-riscv
|
||||
|
||||
continue-on-error: true
|
||||
|
||||
@@ -50,17 +50,18 @@ jobs:
|
||||
sudo apt-get update
|
||||
|
||||
# Install necessary packages
|
||||
sudo apt-get install -y libatomic1 libtsan2 gcc-14 g++-14 rustup cmake build-essential wget ccache git-lfs
|
||||
sudo apt-get install -y libatomic1 libtsan2 gcc-14 g++-14 cmake build-essential wget git-lfs
|
||||
|
||||
# Set gcc-14 and g++-14 as the default compilers
|
||||
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100
|
||||
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100
|
||||
sudo ln -sf /usr/bin/gcc-14 /usr/bin/gcc
|
||||
sudo ln -sf /usr/bin/g++-14 /usr/bin/g++
|
||||
|
||||
# Install Rust stable version
|
||||
rustup install stable
|
||||
rustup default stable
|
||||
if ! which rustc; then
|
||||
# Install Rust stable version
|
||||
sudo apt-get install -y rustup
|
||||
rustup install stable
|
||||
rustup default stable
|
||||
fi
|
||||
|
||||
git lfs install
|
||||
|
||||
@@ -73,23 +74,12 @@ jobs:
|
||||
id: checkout
|
||||
uses: actions/checkout@v6
|
||||
|
||||
- name: Setup ccache
|
||||
run: |
|
||||
# Unique cache directory per matrix combination
|
||||
export CCACHE_DIR="$HOME/.ccache/sanitizer-${{ matrix.sanitizer }}-${{ matrix.build_type }}"
|
||||
mkdir -p "$CCACHE_DIR"
|
||||
|
||||
# Configure ccache
|
||||
ccache --set-config=max_size=5G
|
||||
ccache --set-config=compression=true
|
||||
ccache --set-config=compression_level=6
|
||||
ccache --set-config=cache_dir="$CCACHE_DIR"
|
||||
ccache --set-config=sloppiness=file_macro,time_macros,include_file_mtime,include_file_ctime
|
||||
ccache --set-config=hash_dir=false
|
||||
|
||||
# Export for subsequent steps
|
||||
echo "CCACHE_DIR=$CCACHE_DIR" >> $GITHUB_ENV
|
||||
echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV
|
||||
# FIXME: Enable when ggml-org/ccache-action works on riscv64
|
||||
# - name: ccache
|
||||
# uses: ggml-org/ccache-action@v1.2.21
|
||||
# with:
|
||||
# key: ubuntu-riscv64-native-sanitizer-${{ matrix.sanytizer }}-${{ matrix.build_type }}
|
||||
# save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
|
||||
|
||||
- name: Build
|
||||
id: cmake_build
|
||||
|
||||
130
.github/workflows/build-self-hosted.yml
vendored
130
.github/workflows/build-self-hosted.yml
vendored
@@ -141,60 +141,61 @@ jobs:
|
||||
# amd-smi static
|
||||
# GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS="gfx1101" bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
|
||||
|
||||
ggml-ci-mac-metal:
|
||||
runs-on: [self-hosted, macOS, ARM64]
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
id: checkout
|
||||
uses: actions/checkout@v6
|
||||
|
||||
- name: Test
|
||||
id: ggml-ci
|
||||
run: |
|
||||
GG_BUILD_METAL=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
|
||||
|
||||
ggml-ci-mac-webgpu:
|
||||
runs-on: [self-hosted, macOS, ARM64]
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
id: checkout
|
||||
uses: actions/checkout@v6
|
||||
|
||||
- name: Dawn Dependency
|
||||
id: dawn-depends
|
||||
run: |
|
||||
DAWN_VERSION="v2.0.0"
|
||||
DAWN_OWNER="reeselevine"
|
||||
DAWN_REPO="dawn"
|
||||
DAWN_ASSET_NAME="Dawn-5e9a4865b1635796ccc77dd30057f2b4002a1355-macos-latest-Release"
|
||||
echo "Fetching release asset from https://github.com/${DAWN_OWNER}/${DAWN_REPO}/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.zip"
|
||||
curl -L -o artifact.zip \
|
||||
"https://github.com/${DAWN_OWNER}/${DAWN_REPO}/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.zip"
|
||||
mkdir dawn
|
||||
unzip artifact.zip
|
||||
tar -xvf ${DAWN_ASSET_NAME}.tar.gz -C dawn --strip-components=1
|
||||
|
||||
- name: Test
|
||||
id: ggml-ci
|
||||
run: |
|
||||
GG_BUILD_WEBGPU=1 GG_BUILD_WEBGPU_DAWN_PREFIX="$GITHUB_WORKSPACE/dawn" \
|
||||
bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
|
||||
|
||||
ggml-ci-mac-vulkan:
|
||||
runs-on: [self-hosted, macOS, ARM64]
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
id: checkout
|
||||
uses: actions/checkout@v6
|
||||
|
||||
- name: Test
|
||||
id: ggml-ci
|
||||
run: |
|
||||
vulkaninfo --summary
|
||||
GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
|
||||
# TODO: sandbox Mac runners
|
||||
# ggml-ci-mac-metal:
|
||||
# runs-on: [self-hosted, macOS, ARM64]
|
||||
#
|
||||
# steps:
|
||||
# - name: Clone
|
||||
# id: checkout
|
||||
# uses: actions/checkout@v6
|
||||
#
|
||||
# - name: Test
|
||||
# id: ggml-ci
|
||||
# run: |
|
||||
# GG_BUILD_METAL=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
|
||||
#
|
||||
# ggml-ci-mac-webgpu:
|
||||
# runs-on: [self-hosted, macOS, ARM64]
|
||||
#
|
||||
# steps:
|
||||
# - name: Clone
|
||||
# id: checkout
|
||||
# uses: actions/checkout@v6
|
||||
#
|
||||
# - name: Dawn Dependency
|
||||
# id: dawn-depends
|
||||
# run: |
|
||||
# DAWN_VERSION="v2.0.0"
|
||||
# DAWN_OWNER="reeselevine"
|
||||
# DAWN_REPO="dawn"
|
||||
# DAWN_ASSET_NAME="Dawn-5e9a4865b1635796ccc77dd30057f2b4002a1355-macos-latest-Release"
|
||||
# echo "Fetching release asset from https://github.com/${DAWN_OWNER}/${DAWN_REPO}/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.zip"
|
||||
# curl -L -o artifact.zip \
|
||||
# "https://github.com/${DAWN_OWNER}/${DAWN_REPO}/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.zip"
|
||||
# mkdir dawn
|
||||
# unzip artifact.zip
|
||||
# tar -xvf ${DAWN_ASSET_NAME}.tar.gz -C dawn --strip-components=1
|
||||
#
|
||||
# - name: Test
|
||||
# id: ggml-ci
|
||||
# run: |
|
||||
# GG_BUILD_WEBGPU=1 GG_BUILD_WEBGPU_DAWN_PREFIX="$GITHUB_WORKSPACE/dawn" \
|
||||
# bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
|
||||
#
|
||||
# ggml-ci-mac-vulkan:
|
||||
# runs-on: [self-hosted, macOS, ARM64]
|
||||
#
|
||||
# steps:
|
||||
# - name: Clone
|
||||
# id: checkout
|
||||
# uses: actions/checkout@v6
|
||||
#
|
||||
# - name: Test
|
||||
# id: ggml-ci
|
||||
# run: |
|
||||
# vulkaninfo --summary
|
||||
# GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
|
||||
|
||||
ggml-ci-linux-intel-vulkan:
|
||||
runs-on: [self-hosted, Linux, Intel]
|
||||
@@ -212,6 +213,27 @@ jobs:
|
||||
vulkaninfo --summary
|
||||
GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
|
||||
|
||||
ggml-ci-win-intel-vulkan:
|
||||
runs-on: [self-hosted, Windows, X64, Intel]
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
id: checkout
|
||||
uses: actions/checkout@v6
|
||||
|
||||
- name: Test
|
||||
id: ggml-ci
|
||||
shell: C:\msys64\usr\bin\bash.exe --noprofile --norc -eo pipefail "{0}"
|
||||
env:
|
||||
MSYSTEM: UCRT64
|
||||
CHERE_INVOKING: 1
|
||||
PATH: C:\msys64\ucrt64\bin;C:\msys64\usr\bin;C:\Windows\System32;${{ env.PATH }}
|
||||
run: |
|
||||
vulkaninfo --summary
|
||||
# Skip python related tests with GG_BUILD_LOW_PERF=1 since Windows MSYS2 UCRT64 currently fails to create
|
||||
# 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
|
||||
|
||||
ggml-ci-intel-openvino-gpu-low-perf:
|
||||
runs-on: [self-hosted, Linux, Intel, OpenVINO]
|
||||
|
||||
|
||||
2
.github/workflows/build-vulkan.yml
vendored
2
.github/workflows/build-vulkan.yml
vendored
@@ -72,7 +72,7 @@ jobs:
|
||||
|
||||
- name: Setup Vulkan SDK
|
||||
if: steps.cache-sdk.outputs.cache-hit != 'true'
|
||||
uses: ./.github/actions/linux-setup-vulkan-llvmpipe
|
||||
uses: ./.github/actions/linux-setup-vulkan
|
||||
with:
|
||||
path: ./vulkan_sdk
|
||||
version: ${{ env.VULKAN_SDK_VERSION }}
|
||||
|
||||
156
.github/workflows/build.yml
vendored
156
.github/workflows/build.yml
vendored
@@ -87,7 +87,7 @@ jobs:
|
||||
-DGGML_METAL_EMBED_LIBRARY=OFF \
|
||||
-DGGML_METAL_SHADER_DEBUG=ON \
|
||||
-DGGML_RPC=ON
|
||||
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
|
||||
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
|
||||
@@ -124,7 +124,7 @@ jobs:
|
||||
-DGGML_METAL=OFF \
|
||||
-DGGML_RPC=ON \
|
||||
-DCMAKE_OSX_DEPLOYMENT_TARGET=13.3
|
||||
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
|
||||
time cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
|
||||
|
||||
- name: Test
|
||||
id: cmake_test
|
||||
@@ -150,23 +150,22 @@ jobs:
|
||||
- name: Dawn Dependency
|
||||
id: dawn-depends
|
||||
run: |
|
||||
DAWN_VERSION="v2.0.0"
|
||||
DAWN_OWNER="reeselevine"
|
||||
DAWN_VERSION="v20260317.182325"
|
||||
DAWN_OWNER="google"
|
||||
DAWN_REPO="dawn"
|
||||
DAWN_ASSET_NAME="Dawn-5e9a4865b1635796ccc77dd30057f2b4002a1355-macos-latest-Release"
|
||||
echo "Fetching release asset from https://github.com/${DAWN_OWNER}/${DAWN_REPO}/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.zip"
|
||||
curl -L -o artifact.zip \
|
||||
"https://github.com/${DAWN_OWNER}/${DAWN_REPO}/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.zip"
|
||||
DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-macos-latest-Release"
|
||||
echo "Fetching release asset from https://github.com/google/dawn/releases/download/${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
|
||||
unzip artifact.zip
|
||||
tar -xvf ${DAWN_ASSET_NAME}.tar.gz -C dawn --strip-components=1
|
||||
tar -xvf artifact.tar.gz -C dawn --strip-components=1
|
||||
|
||||
- name: Build
|
||||
id: cmake_build
|
||||
run: |
|
||||
export CMAKE_PREFIX_PATH=dawn
|
||||
cmake -B build -DGGML_WEBGPU=ON -DGGML_METAL=OFF -DGGML_BLAS=OFF
|
||||
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
|
||||
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
|
||||
@@ -181,7 +180,7 @@ jobs:
|
||||
- build: 'x64'
|
||||
os: ubuntu-22.04
|
||||
- build: 'arm64'
|
||||
os: ubuntu-22.04-arm
|
||||
os: ubuntu-24.04-arm
|
||||
- build: 's390x'
|
||||
os: ubuntu-24.04-s390x
|
||||
- build: 'ppc64le'
|
||||
@@ -207,14 +206,22 @@ jobs:
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install -y --no-install-recommends \
|
||||
python3 python3-pip python3-dev \
|
||||
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: |
|
||||
python3 -m pip install --upgrade pip
|
||||
export PIP_BREAK_SYSTEM_PACKAGES="1"
|
||||
python3 -m pip install --upgrade pip setuptools
|
||||
pip3 install ./gguf-py
|
||||
|
||||
- name: Swap Endianness
|
||||
@@ -231,7 +238,7 @@ jobs:
|
||||
cmake -B build \
|
||||
-DLLAMA_FATAL_WARNINGS=ON \
|
||||
-DGGML_RPC=ON
|
||||
cmake --build build --config Release -j $(nproc)
|
||||
time cmake --build build --config Release -j $(nproc)
|
||||
|
||||
- name: Test
|
||||
id: cmake_test
|
||||
@@ -274,14 +281,16 @@ jobs:
|
||||
id: depends
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential libssl-dev
|
||||
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
|
||||
cmake --build build --config Release -j $(nproc)
|
||||
time cmake --build build --config Release -j $(nproc)
|
||||
|
||||
- name: Test
|
||||
id: cmake_test
|
||||
@@ -290,7 +299,15 @@ jobs:
|
||||
ctest -L main --verbose
|
||||
|
||||
ubuntu-24-vulkan:
|
||||
runs-on: ${{ 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
- build: 'x64'
|
||||
os: ubuntu-24.04
|
||||
- build: 'arm64'
|
||||
os: ubuntu-24.04-arm
|
||||
|
||||
runs-on: ${{ matrix.os }}
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
@@ -300,12 +317,16 @@ jobs:
|
||||
- name: Dependencies
|
||||
id: depends
|
||||
run: |
|
||||
sudo apt-get install -y glslc libvulkan-dev libssl-dev
|
||||
sudo apt-get update
|
||||
sudo apt-get install -y gcc-14 g++-14 build-essential glslc libvulkan-dev libssl-dev ninja-build
|
||||
echo "CC=gcc-14" >> "$GITHUB_ENV"
|
||||
echo "CXX=g++-14" >> "$GITHUB_ENV"
|
||||
|
||||
- name: Configure
|
||||
id: cmake_configure
|
||||
run: |
|
||||
cmake -B build \
|
||||
-G "Ninja" \
|
||||
-DCMAKE_BUILD_TYPE=RelWithDebInfo \
|
||||
-DGGML_BACKEND_DL=ON \
|
||||
-DGGML_CPU_ALL_VARIANTS=ON \
|
||||
@@ -314,7 +335,7 @@ jobs:
|
||||
- name: Build
|
||||
id: cmake_build
|
||||
run: |
|
||||
cmake --build build -j $(nproc)
|
||||
time cmake --build build -j $(nproc)
|
||||
|
||||
ubuntu-24-webgpu:
|
||||
runs-on: ubuntu-24.04
|
||||
@@ -336,7 +357,8 @@ jobs:
|
||||
run: |
|
||||
sudo add-apt-repository -y ppa:kisak/kisak-mesa
|
||||
sudo apt-get update -y
|
||||
sudo apt-get install -y build-essential mesa-vulkan-drivers libxcb-xinput0 libxcb-xinerama0 libxcb-cursor-dev libssl-dev
|
||||
sudo apt-get install -y build-essential mesa-vulkan-drivers \
|
||||
libxcb-xinput0 libxcb-xinerama0 libxcb-cursor-dev libssl-dev
|
||||
|
||||
- name: Get latest Vulkan SDK version
|
||||
id: vulkan_sdk_version
|
||||
@@ -361,16 +383,15 @@ jobs:
|
||||
id: dawn-depends
|
||||
run: |
|
||||
sudo apt-get install -y libxrandr-dev libxinerama-dev libxcursor-dev mesa-common-dev libx11-xcb-dev libxi-dev
|
||||
DAWN_VERSION="v2.0.0"
|
||||
DAWN_OWNER="reeselevine"
|
||||
DAWN_VERSION="v20260317.182325"
|
||||
DAWN_OWNER="google"
|
||||
DAWN_REPO="dawn"
|
||||
DAWN_ASSET_NAME="Dawn-5e9a4865b1635796ccc77dd30057f2b4002a1355-ubuntu-latest-Release"
|
||||
echo "Fetching release asset from https://github.com/${DAWN_OWNER}/${DAWN_REPO}/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.zip"
|
||||
curl -L -o artifact.zip \
|
||||
"https://github.com/${DAWN_OWNER}/${DAWN_REPO}/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.zip"
|
||||
DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
|
||||
echo "Fetching release asset from https://github.com/google/dawn/releases/download/${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
|
||||
unzip artifact.zip
|
||||
tar -xvf ${DAWN_ASSET_NAME}.tar.gz -C dawn --strip-components=1
|
||||
tar -xvf artifact.tar.gz -C dawn --strip-components=1
|
||||
|
||||
- name: Build
|
||||
id: cmake_build
|
||||
@@ -378,7 +399,7 @@ jobs:
|
||||
export Dawn_DIR=dawn/lib64/cmake/Dawn
|
||||
cmake -B build \
|
||||
-DGGML_WEBGPU=ON
|
||||
cmake --build build --config Release -j $(nproc)
|
||||
time cmake --build build --config Release -j $(nproc)
|
||||
|
||||
- name: Test
|
||||
id: cmake_test
|
||||
@@ -404,7 +425,7 @@ jobs:
|
||||
|
||||
- name: Fetch emdawnwebgpu
|
||||
run: |
|
||||
DAWN_TAG="v20251027.212519"
|
||||
DAWN_TAG="v20260317.182325"
|
||||
EMDAWN_PKG="emdawnwebgpu_pkg-${DAWN_TAG}.zip"
|
||||
echo "Downloading ${EMDAWN_PKG}"
|
||||
curl -L -o emdawn.zip \
|
||||
@@ -415,11 +436,13 @@ jobs:
|
||||
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
|
||||
|
||||
cmake --build build-wasm --target test-backend-ops -j $(nproc)
|
||||
time cmake --build build-wasm --config Release --target test-backend-ops -j $(nproc)
|
||||
|
||||
ubuntu-22-hip:
|
||||
runs-on: ubuntu-22.04
|
||||
@@ -449,6 +472,7 @@ jobs:
|
||||
cmake -B build -S . \
|
||||
-DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" \
|
||||
-DGGML_HIP_ROCWMMA_FATTN=ON \
|
||||
-DGPU_TARGETS="gfx1030" \
|
||||
-DGGML_HIP=ON
|
||||
cmake --build build --config Release -j $(nproc)
|
||||
|
||||
@@ -479,7 +503,7 @@ jobs:
|
||||
run: |
|
||||
cmake -B build -S . \
|
||||
-DGGML_MUSA=ON
|
||||
cmake --build build --config Release -j $(nproc)
|
||||
time cmake --build build --config Release -j $(nproc)
|
||||
|
||||
ubuntu-22-sycl:
|
||||
runs-on: ubuntu-22.04
|
||||
@@ -528,7 +552,7 @@ jobs:
|
||||
-DGGML_SYCL=ON \
|
||||
-DCMAKE_C_COMPILER=icx \
|
||||
-DCMAKE_CXX_COMPILER=icpx
|
||||
cmake --build build --config Release -j $(nproc)
|
||||
time cmake --build build --config Release -j $(nproc)
|
||||
|
||||
ubuntu-22-sycl-fp16:
|
||||
runs-on: ubuntu-22.04
|
||||
@@ -551,7 +575,7 @@ jobs:
|
||||
shell: bash
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install intel-oneapi-compiler-dpcpp-cpp libssl-dev
|
||||
sudo apt install intel-oneapi-compiler-dpcpp-cpp libssl-dev ninja-build
|
||||
|
||||
- name: install oneAPI MKL library
|
||||
shell: bash
|
||||
@@ -574,11 +598,13 @@ jobs:
|
||||
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 \
|
||||
-DGGML_SYCL_F16=ON
|
||||
cmake --build build --config Release -j $(nproc)
|
||||
time cmake --build build --config Release -j $(nproc)
|
||||
|
||||
ubuntu-24-openvino:
|
||||
name: ubuntu-24-openvino-${{ matrix.openvino_device }}
|
||||
@@ -648,7 +674,7 @@ jobs:
|
||||
cmake -B build/ReleaseOV -G Ninja \
|
||||
-DCMAKE_BUILD_TYPE=Release \
|
||||
-DGGML_OPENVINO=ON
|
||||
cmake --build build/ReleaseOV --config Release -j $(nproc)
|
||||
time cmake --build build/ReleaseOV --config Release -j $(nproc)
|
||||
|
||||
- name: Test
|
||||
id: cmake_test
|
||||
@@ -916,7 +942,7 @@ jobs:
|
||||
- name: Grab rocWMMA package
|
||||
id: grab_rocwmma
|
||||
run: |
|
||||
curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.2/pool/main/r/rocwmma-dev/rocwmma-dev_2.2.0.70200-43~24.04_amd64.deb"
|
||||
curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.2.1/pool/main/r/rocwmma-dev/rocwmma-dev_2.2.0.70201-81~24.04_amd64.deb"
|
||||
7z x rocwmma.deb
|
||||
7z x data.tar
|
||||
|
||||
@@ -959,17 +985,18 @@ jobs:
|
||||
cmake -G "Unix Makefiles" -B build -S . `
|
||||
-DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
|
||||
-DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
|
||||
-DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.2.0/include/" `
|
||||
-DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.2.1/include/" `
|
||||
-DCMAKE_BUILD_TYPE=Release `
|
||||
-DLLAMA_BUILD_BORINGSSL=ON `
|
||||
-DROCM_DIR="${env:HIP_PATH}" `
|
||||
-DGGML_HIP=ON `
|
||||
-DGGML_HIP_ROCWMMA_FATTN=ON `
|
||||
-DGPU_TARGETS="gfx1100" `
|
||||
-DGGML_RPC=ON
|
||||
cmake --build build -j ${env:NUMBER_OF_PROCESSORS}
|
||||
|
||||
ubuntu-cpu-riscv64-native:
|
||||
runs-on: RISCV64
|
||||
runs-on: ubuntu-24.04-riscv
|
||||
|
||||
steps:
|
||||
- name: Install dependencies
|
||||
@@ -977,24 +1004,21 @@ jobs:
|
||||
sudo apt-get update
|
||||
|
||||
# Install necessary packages
|
||||
sudo apt-get install -y libatomic1 libtsan2 gcc-14 g++-14 rustup cmake build-essential libssl-dev wget ccache git-lfs
|
||||
sudo apt-get install -y libatomic1 libtsan2 gcc-14 g++-14 cmake build-essential libssl-dev wget git-lfs
|
||||
|
||||
# Set gcc-14 and g++-14 as the default compilers
|
||||
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100
|
||||
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100
|
||||
sudo ln -sf /usr/bin/gcc-14 /usr/bin/gcc
|
||||
sudo ln -sf /usr/bin/g++-14 /usr/bin/g++
|
||||
|
||||
# Install Rust stable version
|
||||
rustup install stable
|
||||
rustup default stable
|
||||
if ! which rustc; then
|
||||
# Install Rust stable version
|
||||
sudo apt-get install -y rustup
|
||||
rustup install stable
|
||||
rustup default stable
|
||||
fi
|
||||
|
||||
git lfs install
|
||||
|
||||
- name: Clone
|
||||
id: checkout
|
||||
uses: actions/checkout@v6
|
||||
|
||||
- name: Check environment
|
||||
run: |
|
||||
uname -a
|
||||
@@ -1004,25 +1028,17 @@ jobs:
|
||||
cmake --version
|
||||
rustc --version
|
||||
|
||||
- name: Setup ccache
|
||||
run: |
|
||||
# Set unique cache directory for this job
|
||||
export CCACHE_DIR="$HOME/.ccache/cpu-cmake-rv64-native"
|
||||
mkdir -p "$CCACHE_DIR"
|
||||
- name: Clone
|
||||
id: checkout
|
||||
uses: actions/checkout@v6
|
||||
|
||||
# Configure ccache for optimal performance
|
||||
ccache --set-config=max_size=5G
|
||||
ccache --set-config=compression=true
|
||||
ccache --set-config=compression_level=6
|
||||
ccache --set-config=cache_dir="$CCACHE_DIR"
|
||||
|
||||
# Enable more aggressive caching
|
||||
ccache --set-config=sloppiness=file_macro,time_macros,include_file_mtime,include_file_ctime
|
||||
ccache --set-config=hash_dir=false
|
||||
|
||||
# Export for subsequent steps
|
||||
echo "CCACHE_DIR=$CCACHE_DIR" >> $GITHUB_ENV
|
||||
echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV
|
||||
# FIXME: Enable when ggml-org/ccache-action works on riscv64
|
||||
# - name: ccache
|
||||
# uses: ggml-org/ccache-action@v1.2.21
|
||||
# with:
|
||||
# key: ubuntu-cpu-riscv64-native
|
||||
# evict-old-files: 1d
|
||||
# save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
|
||||
|
||||
- name: Build
|
||||
id: cmake_build
|
||||
@@ -1039,7 +1055,7 @@ jobs:
|
||||
-DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
|
||||
-DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14
|
||||
|
||||
cmake --build build --config Release -j $(nproc)
|
||||
time cmake --build build --config Release -j $(nproc)
|
||||
|
||||
- name: Test
|
||||
id: cmake_test
|
||||
|
||||
1
.github/workflows/copilot-setup-steps.yml
vendored
1
.github/workflows/copilot-setup-steps.yml
vendored
@@ -54,4 +54,3 @@ jobs:
|
||||
python3 -m venv .venv
|
||||
source .venv/bin/activate
|
||||
pip install -r requirements/requirements-all.txt -r tools/server/tests/requirements.txt
|
||||
pip install flake8 pyright pre-commit
|
||||
|
||||
567
.github/workflows/docker.yml
vendored
567
.github/workflows/docker.yml
vendored
@@ -25,186 +25,13 @@ permissions:
|
||||
packages: write
|
||||
|
||||
jobs:
|
||||
push_to_registry:
|
||||
name: Push Docker image to Docker Hub
|
||||
|
||||
runs-on: ${{ matrix.config.runs_on }}
|
||||
env:
|
||||
COMMIT_SHA: ${{ github.sha }}
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
config:
|
||||
# Multi-stage build
|
||||
# Note: the arm64 images are failing, which prevents the amd64 images from being built
|
||||
# https://github.com/ggml-org/llama.cpp/issues/11888
|
||||
#- { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64,linux/arm64", full: true, light: true, server: true, free_disk_space: false }
|
||||
- { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false, runs_on: "ubuntu-22.04" }
|
||||
- { tag: "cuda cuda12", dockerfile: ".devops/cuda.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04", cuda_version: "12.4.0", ubuntu_version: "22.04" }
|
||||
- { tag: "cuda13", dockerfile: ".devops/cuda-new.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04", cuda_version: "13.1.0", ubuntu_version: "24.04" }
|
||||
- { tag: "musa", dockerfile: ".devops/musa.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04" }
|
||||
- { tag: "intel", dockerfile: ".devops/intel.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04" }
|
||||
- { tag: "vulkan", dockerfile: ".devops/vulkan.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false, runs_on: "ubuntu-22.04" }
|
||||
- { tag: "s390x", dockerfile: ".devops/s390x.Dockerfile", platforms: "linux/s390x", full: true, light: true, server: true, free_disk_space: false, runs_on: "ubuntu-22.04-s390x" }
|
||||
- { tag: "rocm", dockerfile: ".devops/rocm.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04" }
|
||||
- { tag: "openvino", dockerfile: ".devops/openvino.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false, runs_on: "ubuntu-22.04" }
|
||||
steps:
|
||||
- name: Check out the repo
|
||||
uses: actions/checkout@v6
|
||||
with:
|
||||
fetch-depth: 0 # preserve git history, so we can determine the build number
|
||||
|
||||
- name: Set up QEMU
|
||||
if: ${{ matrix.config.tag != 's390x' }}
|
||||
uses: docker/setup-qemu-action@v3
|
||||
with:
|
||||
image: tonistiigi/binfmt:qemu-v7.0.0-28
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
|
||||
- name: Log in to Docker Hub
|
||||
uses: docker/login-action@v3
|
||||
with:
|
||||
registry: ghcr.io
|
||||
username: ${{ github.repository_owner }}
|
||||
password: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Determine source tag name
|
||||
id: srctag
|
||||
uses: ./.github/actions/get-tag-name
|
||||
env:
|
||||
BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
|
||||
|
||||
- name: Determine image tag name
|
||||
id: tag
|
||||
shell: bash
|
||||
run: |
|
||||
REPO_OWNER="${GITHUB_REPOSITORY_OWNER@L}" # to lower case
|
||||
REPO_NAME="${{ github.event.repository.name }}"
|
||||
PREFIX="ghcr.io/${REPO_OWNER}/${REPO_NAME}:"
|
||||
|
||||
# list all tags possible
|
||||
tags="${{ matrix.config.tag }}"
|
||||
for tag in $tags; do
|
||||
if [[ "$tag" == "cpu" ]]; then
|
||||
TYPE=""
|
||||
else
|
||||
TYPE="-$tag"
|
||||
fi
|
||||
CACHETAGS="${PREFIX}buildcache${TYPE}"
|
||||
FULLTAGS="${FULLTAGS:+$FULLTAGS,}${PREFIX}full${TYPE},${PREFIX}full${TYPE}-${{ steps.srctag.outputs.name }}"
|
||||
LIGHTTAGS="${LIGHTTAGS:+$LIGHTTAGS,}${PREFIX}light${TYPE},${PREFIX}light${TYPE}-${{ steps.srctag.outputs.name }}"
|
||||
SERVERTAGS="${SERVERTAGS:+$SERVERTAGS,}${PREFIX}server${TYPE},${PREFIX}server${TYPE}-${{ steps.srctag.outputs.name }}"
|
||||
done
|
||||
echo "cache_output_tags=$CACHETAGS" >> $GITHUB_OUTPUT
|
||||
echo "full_output_tags=$FULLTAGS" >> $GITHUB_OUTPUT
|
||||
echo "light_output_tags=$LIGHTTAGS" >> $GITHUB_OUTPUT
|
||||
echo "server_output_tags=$SERVERTAGS" >> $GITHUB_OUTPUT
|
||||
echo "cache_output_tags=$CACHETAGS" # print out for debugging
|
||||
echo "full_output_tags=$FULLTAGS" # print out for debugging
|
||||
echo "light_output_tags=$LIGHTTAGS" # print out for debugging
|
||||
echo "server_output_tags=$SERVERTAGS" # print out for debugging
|
||||
env:
|
||||
GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}'
|
||||
|
||||
- name: Free Disk Space (Ubuntu)
|
||||
if: ${{ matrix.config.free_disk_space == true }}
|
||||
uses: ggml-org/free-disk-space@v1.3.1
|
||||
with:
|
||||
# this might remove tools that are actually needed,
|
||||
# if set to "true" but frees about 6 GB
|
||||
tool-cache: false
|
||||
|
||||
# all of these default to true, but feel free to set to
|
||||
# "false" if necessary for your workflow
|
||||
android: true
|
||||
dotnet: true
|
||||
haskell: true
|
||||
large-packages: true
|
||||
docker-images: true
|
||||
swap-storage: true
|
||||
|
||||
- name: Build and push Full Docker image (tagged + versioned)
|
||||
if: ${{ (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && matrix.config.full == true }}
|
||||
uses: docker/build-push-action@v6
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
platforms: ${{ matrix.config.platforms }}
|
||||
# tag list is generated from step above
|
||||
tags: ${{ steps.tag.outputs.full_output_tags }}
|
||||
file: ${{ matrix.config.dockerfile }}
|
||||
target: full
|
||||
provenance: false
|
||||
build-args: |
|
||||
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
|
||||
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
|
||||
# using github experimental cache
|
||||
#cache-from: type=gha
|
||||
#cache-to: type=gha,mode=max
|
||||
# return to this if the experimental github cache is having issues
|
||||
#cache-to: type=local,dest=/tmp/.buildx-cache
|
||||
#cache-from: type=local,src=/tmp/.buildx-cache
|
||||
# using registry cache (no storage limit)
|
||||
cache-from: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }}
|
||||
cache-to: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }},mode=max
|
||||
|
||||
- name: Build and push Light Docker image (tagged + versioned)
|
||||
if: ${{ (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && matrix.config.light == true }}
|
||||
uses: docker/build-push-action@v6
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
platforms: ${{ matrix.config.platforms }}
|
||||
# tag list is generated from step above
|
||||
tags: ${{ steps.tag.outputs.light_output_tags }}
|
||||
file: ${{ matrix.config.dockerfile }}
|
||||
target: light
|
||||
provenance: false
|
||||
build-args: |
|
||||
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
|
||||
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
|
||||
# using github experimental cache
|
||||
#cache-from: type=gha
|
||||
#cache-to: type=gha,mode=max
|
||||
# return to this if the experimental github cache is having issues
|
||||
#cache-to: type=local,dest=/tmp/.buildx-cache
|
||||
#cache-from: type=local,src=/tmp/.buildx-cache
|
||||
# using registry cache (no storage limit)
|
||||
cache-from: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }}
|
||||
cache-to: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }},mode=max
|
||||
|
||||
- name: Build and push Server Docker image (tagged + versioned)
|
||||
if: ${{ (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && matrix.config.server == true }}
|
||||
uses: docker/build-push-action@v6
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
platforms: ${{ matrix.config.platforms }}
|
||||
# tag list is generated from step above
|
||||
tags: ${{ steps.tag.outputs.server_output_tags }}
|
||||
file: ${{ matrix.config.dockerfile }}
|
||||
target: server
|
||||
provenance: false
|
||||
build-args: |
|
||||
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
|
||||
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
|
||||
# using github experimental cache
|
||||
#cache-from: type=gha
|
||||
#cache-to: type=gha,mode=max
|
||||
# return to this if the experimental github cache is having issues
|
||||
#cache-to: type=local,dest=/tmp/.buildx-cache
|
||||
#cache-from: type=local,src=/tmp/.buildx-cache
|
||||
# using registry cache (no storage limit)
|
||||
cache-from: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }}
|
||||
cache-to: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }},mode=max
|
||||
|
||||
create_tag:
|
||||
name: Create and push git tag
|
||||
runs-on: ubuntu-22.04
|
||||
runs-on: ubuntu-slim
|
||||
permissions:
|
||||
contents: write
|
||||
outputs:
|
||||
source_tag: ${{ steps.srctag.outputs.name }}
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
@@ -225,3 +52,391 @@ jobs:
|
||||
run: |
|
||||
git tag ${{ steps.srctag.outputs.name }} || exit 0
|
||||
git push origin ${{ steps.srctag.outputs.name }} || exit 0
|
||||
|
||||
prepare_matrices:
|
||||
name: Prepare Docker matrices
|
||||
runs-on: ubuntu-24.04
|
||||
outputs:
|
||||
build_matrix: ${{ steps.matrices.outputs.build_matrix }}
|
||||
merge_matrix: ${{ steps.matrices.outputs.merge_matrix }}
|
||||
|
||||
steps:
|
||||
- name: Generate build and merge matrices
|
||||
id: matrices
|
||||
shell: bash
|
||||
run: |
|
||||
set -euo pipefail
|
||||
|
||||
# Keep all build targets in one place and derive merge targets from it.
|
||||
cat > build-matrix.json <<'JSON'
|
||||
[
|
||||
{ "tag": "cpu", "dockerfile": ".devops/cpu.Dockerfile", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04" },
|
||||
{ "tag": "cpu", "dockerfile": ".devops/cpu.Dockerfile", "platforms": "linux/arm64", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04-arm" },
|
||||
{ "tag": "cpu", "dockerfile": ".devops/s390x.Dockerfile", "platforms": "linux/s390x", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04-s390x" },
|
||||
{ "tag": "cuda cuda12", "dockerfile": ".devops/cuda.Dockerfile", "cuda_version": "12.8.1", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04" },
|
||||
{ "tag": "cuda cuda12", "dockerfile": ".devops/cuda.Dockerfile", "cuda_version": "12.8.1", "platforms": "linux/arm64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04-arm" },
|
||||
{ "tag": "cuda13", "dockerfile": ".devops/cuda.Dockerfile", "cuda_version": "13.1.1", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04" },
|
||||
{ "tag": "cuda13", "dockerfile": ".devops/cuda.Dockerfile", "cuda_version": "13.1.1", "platforms": "linux/arm64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04-arm" },
|
||||
{ "tag": "musa", "dockerfile": ".devops/musa.Dockerfile", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04" },
|
||||
{ "tag": "intel", "dockerfile": ".devops/intel.Dockerfile", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04" },
|
||||
{ "tag": "vulkan", "dockerfile": ".devops/vulkan.Dockerfile", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04" },
|
||||
{ "tag": "vulkan", "dockerfile": ".devops/vulkan.Dockerfile", "platforms": "linux/arm64", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04-arm" },
|
||||
{ "tag": "rocm", "dockerfile": ".devops/rocm.Dockerfile", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": true, "runs_on": "ubuntu-24.04" },
|
||||
{ "tag": "openvino", "dockerfile": ".devops/openvino.Dockerfile", "platforms": "linux/amd64", "full": true, "light": true, "server": true, "free_disk_space": false, "runs_on": "ubuntu-24.04" }
|
||||
]
|
||||
JSON
|
||||
|
||||
BUILD_MATRIX="$(jq -c . build-matrix.json)"
|
||||
MERGE_MATRIX="$(jq -c '
|
||||
reduce .[] as $entry ({}; .[$entry.tag] |= (
|
||||
. // {
|
||||
tag: $entry.tag,
|
||||
arches: [],
|
||||
full: false,
|
||||
light: false,
|
||||
server: false
|
||||
}
|
||||
| .full = (.full or ($entry.full // false))
|
||||
| .light = (.light or ($entry.light // false))
|
||||
| .server = (.server or ($entry.server // false))
|
||||
| .arches += [($entry.platforms | sub("^linux/"; ""))]
|
||||
))
|
||||
# Backward compatibility: s390x tags are aliases of cpu for the linux/s390x platform.
|
||||
| if (has("cpu") and (((.cpu.arches // []) | index("s390x")) != null)) then
|
||||
. + {
|
||||
s390x: {
|
||||
tag: "s390x",
|
||||
arches: ["s390x"],
|
||||
full: .cpu.full,
|
||||
light: .cpu.light,
|
||||
server: .cpu.server
|
||||
}
|
||||
}
|
||||
else
|
||||
.
|
||||
end
|
||||
| [.[] | .arches = (.arches | unique | sort | join(" "))]
|
||||
' build-matrix.json)"
|
||||
|
||||
echo "build_matrix=$BUILD_MATRIX" >> "$GITHUB_OUTPUT"
|
||||
echo "merge_matrix=$MERGE_MATRIX" >> "$GITHUB_OUTPUT"
|
||||
|
||||
push_to_registry:
|
||||
name: Push Docker image to Docker Registry
|
||||
needs: [prepare_matrices, create_tag]
|
||||
|
||||
runs-on: ${{ matrix.config.runs_on }}
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
config: ${{ fromJSON(needs.prepare_matrices.outputs.build_matrix) }}
|
||||
steps:
|
||||
- name: Check out the repo
|
||||
uses: actions/checkout@v6
|
||||
with:
|
||||
fetch-depth: 0
|
||||
ref: ${{ needs.create_tag.outputs.source_tag }}
|
||||
|
||||
- name: Set up QEMU
|
||||
if: ${{ contains(matrix.config.platforms, 'linux/amd64') }}
|
||||
uses: docker/setup-qemu-action@ce360397dd3f832beb865e1373c09c0e9f86d70a # v4
|
||||
with:
|
||||
image: tonistiigi/binfmt:qemu-v10.2.1
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@4d04d5d9486b7bd6fa91e7baf45bbb4f8b9deedd # v4
|
||||
|
||||
- name: Log in to Docker Registry
|
||||
uses: docker/login-action@b45d80f862d83dbcd57f89517bcf500b2ab88fb2 # v4
|
||||
with:
|
||||
registry: ghcr.io
|
||||
username: ${{ github.repository_owner }}
|
||||
password: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Determine image metadata
|
||||
id: meta
|
||||
shell: bash
|
||||
run: |
|
||||
set -euo pipefail
|
||||
|
||||
REPO_OWNER="${GITHUB_REPOSITORY_OWNER@L}" # to lower case
|
||||
REPO_NAME="${{ github.event.repository.name }}"
|
||||
IMAGE_REPO="ghcr.io/${REPO_OWNER}/${REPO_NAME}"
|
||||
PREFIX="${IMAGE_REPO}:"
|
||||
PLATFORM="${{ matrix.config.platforms }}"
|
||||
ARCH_SUFFIX="${PLATFORM#linux/}"
|
||||
|
||||
# list all tags possible
|
||||
tags="${{ matrix.config.tag }}"
|
||||
for tag in $tags; do
|
||||
if [[ "$tag" == "cpu" ]]; then
|
||||
TYPE=""
|
||||
else
|
||||
TYPE="-$tag"
|
||||
fi
|
||||
CACHETAG="${PREFIX}buildcache${TYPE}-${ARCH_SUFFIX}"
|
||||
done
|
||||
|
||||
SAFE_TAGS="$(echo "$tags" | tr ' ' '_')"
|
||||
|
||||
echo "image_repo=$IMAGE_REPO" >> $GITHUB_OUTPUT
|
||||
echo "arch_suffix=$ARCH_SUFFIX" >> $GITHUB_OUTPUT
|
||||
echo "cache_output_tag=$CACHETAG" >> $GITHUB_OUTPUT
|
||||
echo "digest_artifact_suffix=${SAFE_TAGS}-${ARCH_SUFFIX}" >> $GITHUB_OUTPUT
|
||||
echo "cache_output_tag=$CACHETAG" # print out for debugging
|
||||
env:
|
||||
GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}'
|
||||
|
||||
- name: Free Disk Space (Ubuntu)
|
||||
if: ${{ matrix.config.free_disk_space == true }}
|
||||
uses: ggml-org/free-disk-space@v1.3.1
|
||||
with:
|
||||
# this might remove tools that are actually needed,
|
||||
# if set to "true" but frees about 6 GB
|
||||
tool-cache: false
|
||||
|
||||
# all of these default to true, but feel free to set to
|
||||
# "false" if necessary for your workflow
|
||||
android: true
|
||||
dotnet: true
|
||||
haskell: true
|
||||
large-packages: true
|
||||
docker-images: true
|
||||
swap-storage: true
|
||||
|
||||
- name: Build and push Full Docker image by digest
|
||||
id: build_full
|
||||
if: ${{ (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && matrix.config.full == true }}
|
||||
uses: docker/build-push-action@d08e5c354a6adb9ed34480a06d141179aa583294 # v7
|
||||
with:
|
||||
context: .
|
||||
platforms: ${{ matrix.config.platforms }}
|
||||
outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true
|
||||
file: ${{ matrix.config.dockerfile }}
|
||||
target: full
|
||||
provenance: false
|
||||
build-args: |
|
||||
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
|
||||
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
|
||||
# using github experimental cache
|
||||
#cache-from: type=gha
|
||||
#cache-to: type=gha,mode=max
|
||||
# return to this if the experimental github cache is having issues
|
||||
#cache-to: type=local,dest=/tmp/.buildx-cache
|
||||
#cache-from: type=local,src=/tmp/.buildx-cache
|
||||
# using registry cache (no storage limit)
|
||||
cache-from: type=registry,ref=${{ steps.meta.outputs.cache_output_tag }}
|
||||
cache-to: type=registry,ref=${{ steps.meta.outputs.cache_output_tag }},mode=max
|
||||
|
||||
- name: Build and push Light Docker image by digest
|
||||
id: build_light
|
||||
if: ${{ (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && matrix.config.light == true }}
|
||||
uses: docker/build-push-action@d08e5c354a6adb9ed34480a06d141179aa583294 # v7
|
||||
with:
|
||||
context: .
|
||||
platforms: ${{ matrix.config.platforms }}
|
||||
outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true
|
||||
file: ${{ matrix.config.dockerfile }}
|
||||
target: light
|
||||
provenance: false
|
||||
build-args: |
|
||||
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
|
||||
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
|
||||
# using github experimental cache
|
||||
#cache-from: type=gha
|
||||
#cache-to: type=gha,mode=max
|
||||
# return to this if the experimental github cache is having issues
|
||||
#cache-to: type=local,dest=/tmp/.buildx-cache
|
||||
#cache-from: type=local,src=/tmp/.buildx-cache
|
||||
# using registry cache (no storage limit)
|
||||
cache-from: type=registry,ref=${{ steps.meta.outputs.cache_output_tag }}
|
||||
cache-to: type=registry,ref=${{ steps.meta.outputs.cache_output_tag }},mode=max
|
||||
|
||||
- name: Build and push Server Docker image by digest
|
||||
id: build_server
|
||||
if: ${{ (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && matrix.config.server == true }}
|
||||
uses: docker/build-push-action@d08e5c354a6adb9ed34480a06d141179aa583294 # v7
|
||||
with:
|
||||
context: .
|
||||
platforms: ${{ matrix.config.platforms }}
|
||||
outputs: type=image,name=${{ steps.meta.outputs.image_repo }},push-by-digest=true,name-canonical=true,push=true
|
||||
file: ${{ matrix.config.dockerfile }}
|
||||
target: server
|
||||
provenance: false
|
||||
build-args: |
|
||||
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
|
||||
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
|
||||
# using github experimental cache
|
||||
#cache-from: type=gha
|
||||
#cache-to: type=gha,mode=max
|
||||
# return to this if the experimental github cache is having issues
|
||||
#cache-to: type=local,dest=/tmp/.buildx-cache
|
||||
#cache-from: type=local,src=/tmp/.buildx-cache
|
||||
# using registry cache (no storage limit)
|
||||
cache-from: type=registry,ref=${{ steps.meta.outputs.cache_output_tag }}
|
||||
cache-to: type=registry,ref=${{ steps.meta.outputs.cache_output_tag }},mode=max
|
||||
|
||||
- name: Export digest metadata
|
||||
shell: bash
|
||||
run: |
|
||||
set -euo pipefail
|
||||
|
||||
TAGS="${{ matrix.config.tag }}"
|
||||
ARCH_SUFFIX="${{ steps.meta.outputs.arch_suffix }}"
|
||||
DIGEST_FILE="/tmp/digests/${{ steps.meta.outputs.digest_artifact_suffix }}.tsv"
|
||||
mkdir -p /tmp/digests
|
||||
|
||||
add_digest_rows() {
|
||||
local image_type="$1"
|
||||
local digest="$2"
|
||||
|
||||
if [[ -z "$digest" ]]; then
|
||||
echo "Missing digest for image_type=${image_type}" >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
for tag in $TAGS; do
|
||||
printf '%s\t%s\t%s\t%s\n' "$tag" "$ARCH_SUFFIX" "$image_type" "$digest" >> "$DIGEST_FILE"
|
||||
done
|
||||
}
|
||||
|
||||
if [[ "${{ matrix.config.full }}" == "true" ]]; then
|
||||
add_digest_rows "full" "${{ steps.build_full.outputs.digest }}"
|
||||
fi
|
||||
|
||||
if [[ "${{ matrix.config.light }}" == "true" ]]; then
|
||||
add_digest_rows "light" "${{ steps.build_light.outputs.digest }}"
|
||||
fi
|
||||
|
||||
if [[ "${{ matrix.config.server }}" == "true" ]]; then
|
||||
add_digest_rows "server" "${{ steps.build_server.outputs.digest }}"
|
||||
fi
|
||||
|
||||
- name: Upload digest metadata
|
||||
uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7
|
||||
with:
|
||||
name: digests-${{ steps.meta.outputs.digest_artifact_suffix }}
|
||||
path: /tmp/digests/${{ steps.meta.outputs.digest_artifact_suffix }}.tsv
|
||||
if-no-files-found: error
|
||||
|
||||
merge_arch_tags:
|
||||
name: Create shared tags from digests
|
||||
needs: [prepare_matrices, push_to_registry, create_tag]
|
||||
runs-on: ubuntu-24.04
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
config: ${{ fromJSON(needs.prepare_matrices.outputs.merge_matrix) }}
|
||||
|
||||
steps:
|
||||
- name: Check out the repo
|
||||
uses: actions/checkout@v6
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Download digest metadata
|
||||
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8
|
||||
with:
|
||||
pattern: digests-*
|
||||
path: /tmp/digests
|
||||
merge-multiple: true
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@4d04d5d9486b7bd6fa91e7baf45bbb4f8b9deedd # v4
|
||||
|
||||
- name: Log in to Docker Registry
|
||||
uses: docker/login-action@b45d80f862d83dbcd57f89517bcf500b2ab88fb2 # v4
|
||||
with:
|
||||
registry: ghcr.io
|
||||
username: ${{ github.repository_owner }}
|
||||
password: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Create tags from digests
|
||||
shell: bash
|
||||
run: |
|
||||
set -euo pipefail
|
||||
|
||||
REPO_OWNER="${GITHUB_REPOSITORY_OWNER@L}" # to lower case
|
||||
REPO_NAME="${{ github.event.repository.name }}"
|
||||
IMAGE_REPO="ghcr.io/${REPO_OWNER}/${REPO_NAME}"
|
||||
PREFIX="${IMAGE_REPO}:"
|
||||
SRC_TAG="${{ needs.create_tag.outputs.source_tag }}"
|
||||
TAGS="${{ matrix.config.tag }}"
|
||||
ARCHES="${{ matrix.config.arches }}"
|
||||
DIGEST_GLOB="/tmp/digests/*.tsv"
|
||||
|
||||
if ! ls ${DIGEST_GLOB} >/dev/null 2>&1; then
|
||||
echo "No digest metadata found in /tmp/digests" >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [[ -z "$SRC_TAG" ]]; then
|
||||
echo "Missing source tag from create_tag" >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
find_digest() {
|
||||
local tag_name="$1"
|
||||
local arch="$2"
|
||||
local image_type="$3"
|
||||
local digest
|
||||
|
||||
digest="$(awk -F '\t' -v t="$tag_name" -v a="$arch" -v i="$image_type" '$1 == t && $2 == a && $3 == i { print $4; exit }' ${DIGEST_GLOB})"
|
||||
|
||||
# Backward compatibility: s390x tags are aliases of cpu for the linux/s390x platform.
|
||||
if [[ -z "$digest" && "$tag_name" == "s390x" && "$arch" == "s390x" ]]; then
|
||||
digest="$(awk -F '\t' -v t="cpu" -v a="$arch" -v i="$image_type" '$1 == t && $2 == a && $3 == i { print $4; exit }' ${DIGEST_GLOB})"
|
||||
fi
|
||||
|
||||
if [[ -z "$digest" ]]; then
|
||||
echo "Missing digest for tag=${tag_name} arch=${arch} image_type=${image_type}" >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
echo "$digest"
|
||||
}
|
||||
|
||||
create_manifest_tags() {
|
||||
local image_type="$1"
|
||||
local tag_name="$2"
|
||||
local suffix="$3"
|
||||
|
||||
local merged_tag="${PREFIX}${image_type}${suffix}"
|
||||
local merged_versioned_tag="${merged_tag}-${SRC_TAG}"
|
||||
|
||||
local refs=()
|
||||
|
||||
for arch in $ARCHES; do
|
||||
local digest
|
||||
digest="$(find_digest "$tag_name" "$arch" "$image_type")"
|
||||
refs+=("${IMAGE_REPO}@${digest}")
|
||||
done
|
||||
|
||||
echo "Creating ${merged_tag} from ${refs[*]}"
|
||||
docker buildx imagetools create --tag "${merged_tag}" "${refs[@]}"
|
||||
|
||||
echo "Creating ${merged_versioned_tag} from ${refs[*]}"
|
||||
docker buildx imagetools create --tag "${merged_versioned_tag}" "${refs[@]}"
|
||||
}
|
||||
|
||||
for tag in $TAGS; do
|
||||
if [[ "$tag" == "cpu" ]]; then
|
||||
TYPE=""
|
||||
else
|
||||
TYPE="-$tag"
|
||||
fi
|
||||
|
||||
if [[ "${{ matrix.config.full }}" == "true" ]]; then
|
||||
create_manifest_tags "full" "$tag" "$TYPE"
|
||||
fi
|
||||
|
||||
if [[ "${{ matrix.config.light }}" == "true" ]]; then
|
||||
create_manifest_tags "light" "$tag" "$TYPE"
|
||||
fi
|
||||
|
||||
if [[ "${{ matrix.config.server }}" == "true" ]]; then
|
||||
create_manifest_tags "server" "$tag" "$TYPE"
|
||||
fi
|
||||
done
|
||||
env:
|
||||
GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}'
|
||||
|
||||
2
.github/workflows/editorconfig.yml
vendored
2
.github/workflows/editorconfig.yml
vendored
@@ -23,7 +23,7 @@ jobs:
|
||||
runs-on: ubuntu-slim
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: editorconfig-checker/action-editorconfig-checker@v2
|
||||
- uses: editorconfig-checker/action-editorconfig-checker@840e866d93b8e032123c23bac69dece044d4d84c # v2.2.0
|
||||
with:
|
||||
version: v3.0.3
|
||||
- run: editorconfig-checker
|
||||
|
||||
6
.github/workflows/gguf-publish.yml
vendored
6
.github/workflows/gguf-publish.yml
vendored
@@ -28,17 +28,17 @@ jobs:
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v6
|
||||
with:
|
||||
python-version: '3.9.x'
|
||||
python-version: '3.11'
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
cd gguf-py
|
||||
python -m pip install poetry
|
||||
python -m pip install poetry==2.3.2
|
||||
poetry install
|
||||
|
||||
- name: Build package
|
||||
run: cd gguf-py && poetry build
|
||||
- name: Publish package
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
uses: pypa/gh-action-pypi-publish@ed0c53931b1dc9bd32cbe73a98c7f6766f8a527e # release/v1
|
||||
with:
|
||||
password: ${{ secrets.PYPI_API_TOKEN }}
|
||||
packages-dir: gguf-py/dist
|
||||
|
||||
10
.github/workflows/hip-quality-check.yml
vendored
10
.github/workflows/hip-quality-check.yml
vendored
@@ -8,7 +8,8 @@ on:
|
||||
paths: [
|
||||
'.github/workflows/hip-quality-check.yml',
|
||||
'**/*.cu',
|
||||
'**/*.cuh'
|
||||
'**/*.cuh',
|
||||
'scripts/hip/gcn-cdna-vgpr-check.py'
|
||||
]
|
||||
|
||||
pull_request:
|
||||
@@ -16,7 +17,8 @@ on:
|
||||
paths: [
|
||||
'.github/workflows/hip-quality-check.yml',
|
||||
'**/*.cu',
|
||||
'**/*.cuh'
|
||||
'**/*.cuh',
|
||||
'scripts/hip/gcn-cdna-vgpr-check.py'
|
||||
]
|
||||
|
||||
concurrency:
|
||||
@@ -33,7 +35,7 @@ env:
|
||||
jobs:
|
||||
ubuntu-22-hip-quality-check:
|
||||
runs-on: ubuntu-22.04
|
||||
container: rocm/dev-ubuntu-22.04:7.2
|
||||
container: rocm/dev-ubuntu-22.04:7.2.1
|
||||
steps:
|
||||
- name: Clone
|
||||
id: checkout
|
||||
@@ -57,7 +59,7 @@ jobs:
|
||||
run: |
|
||||
cmake -B build -S . \
|
||||
-DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" \
|
||||
-DGPU_TARGETS=gfx908 \
|
||||
-DGPU_TARGETS=gfx942 \
|
||||
-DGGML_HIP=ON \
|
||||
-DGGML_HIP_EXPORT_METRICS=Off \
|
||||
-DCMAKE_HIP_FLAGS="-Werror -Wno-tautological-compare" \
|
||||
|
||||
2
.github/workflows/python-lint.yml
vendored
2
.github/workflows/python-lint.yml
vendored
@@ -31,6 +31,6 @@ jobs:
|
||||
with:
|
||||
python-version: "3.11"
|
||||
- name: flake8 Lint
|
||||
uses: py-actions/flake8@v2
|
||||
uses: py-actions/flake8@84ec6726560b6d5bd68f2a5bed83d62b52bb50ba # v2
|
||||
with:
|
||||
plugins: "flake8-no-print"
|
||||
|
||||
2
.github/workflows/python-type-check.yml
vendored
2
.github/workflows/python-type-check.yml
vendored
@@ -31,7 +31,7 @@ jobs:
|
||||
uses: actions/setup-python@v6
|
||||
with:
|
||||
python-version: "3.11"
|
||||
pip-install: -r requirements/requirements-all.txt ty==0.0.24
|
||||
pip-install: -r requirements/requirements-all.txt ty==0.0.26
|
||||
# - name: Type-check with Pyright
|
||||
# uses: jakebailey/pyright-action@v2
|
||||
# with:
|
||||
|
||||
169
.github/workflows/release.yml
vendored
169
.github/workflows/release.yml
vendored
@@ -36,8 +36,26 @@ env:
|
||||
CMAKE_ARGS: "-DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_TOOLS=ON -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON"
|
||||
|
||||
jobs:
|
||||
macOS-arm64:
|
||||
runs-on: macos-14
|
||||
macOS-cpu:
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
- build: 'arm64'
|
||||
arch: 'arm64'
|
||||
os: macos-14
|
||||
defines: "-DGGML_METAL_USE_BF16=ON -DGGML_METAL_EMBED_LIBRARY=ON"
|
||||
- build: 'arm64-kleidiai'
|
||||
arch: 'arm64'
|
||||
os: macos-14
|
||||
defines: "-DGGML_METAL_USE_BF16=ON -DGGML_METAL_EMBED_LIBRARY=ON -DGGML_CPU_KLEIDIAI=ON"
|
||||
- build: 'x64'
|
||||
arch: 'x64'
|
||||
os: macos-15-intel
|
||||
# Metal is disabled on x64 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
|
||||
defines: "-DGGML_METAL=OFF -DCMAKE_OSX_DEPLOYMENT_TARGET=13.3"
|
||||
|
||||
runs-on: ${{ matrix.os }}
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
@@ -49,7 +67,7 @@ jobs:
|
||||
- name: ccache
|
||||
uses: ggml-org/ccache-action@v1.2.21
|
||||
with:
|
||||
key: macOS-latest-arm64
|
||||
key: macOS-latest-${{ matrix.arch }}
|
||||
evict-old-files: 1d
|
||||
|
||||
- name: Build
|
||||
@@ -57,13 +75,11 @@ jobs:
|
||||
run: |
|
||||
sysctl -a
|
||||
cmake -B build \
|
||||
${{ matrix.defines }} \
|
||||
-DCMAKE_INSTALL_RPATH='@loader_path' \
|
||||
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
|
||||
-DLLAMA_FATAL_WARNINGS=ON \
|
||||
-DLLAMA_BUILD_BORINGSSL=ON \
|
||||
-DGGML_METAL_USE_BF16=ON \
|
||||
-DGGML_METAL_EMBED_LIBRARY=ON \
|
||||
-DGGML_RPC=ON \
|
||||
${{ env.CMAKE_ARGS }}
|
||||
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
|
||||
|
||||
@@ -75,73 +91,24 @@ jobs:
|
||||
id: pack_artifacts
|
||||
run: |
|
||||
cp LICENSE ./build/bin/
|
||||
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
|
||||
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-${{ matrix.build }}.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v6
|
||||
with:
|
||||
path: llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz
|
||||
name: llama-bin-macos-arm64.tar.gz
|
||||
path: llama-${{ steps.tag.outputs.name }}-bin-macos-${{ matrix.build }}.tar.gz
|
||||
name: llama-bin-macos-${{ matrix.build }}.tar.gz
|
||||
|
||||
macOS-x64:
|
||||
runs-on: macos-15-intel
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
id: checkout
|
||||
uses: actions/checkout@v6
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: ccache
|
||||
uses: ggml-org/ccache-action@v1.2.21
|
||||
with:
|
||||
key: macOS-latest-x64
|
||||
evict-old-files: 1d
|
||||
|
||||
- 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_INSTALL_RPATH='@loader_path' \
|
||||
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
|
||||
-DLLAMA_FATAL_WARNINGS=ON \
|
||||
-DLLAMA_BUILD_BORINGSSL=ON \
|
||||
-DGGML_METAL=OFF \
|
||||
-DGGML_RPC=ON \
|
||||
-DCMAKE_OSX_DEPLOYMENT_TARGET=13.3
|
||||
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
|
||||
|
||||
- name: Determine tag name
|
||||
id: tag
|
||||
uses: ./.github/actions/get-tag-name
|
||||
|
||||
- name: Pack artifacts
|
||||
id: pack_artifacts
|
||||
run: |
|
||||
cp LICENSE ./build/bin/
|
||||
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v6
|
||||
with:
|
||||
path: llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz
|
||||
name: llama-bin-macos-x64.tar.gz
|
||||
|
||||
ubuntu-22-cpu:
|
||||
ubuntu-cpu:
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
- build: 'x64'
|
||||
os: ubuntu-22.04
|
||||
- build: 'arm64'
|
||||
os: ubuntu-24.04-arm
|
||||
- build: 's390x'
|
||||
os: ubuntu-24.04-s390x
|
||||
# GGML_BACKEND_DL and GGML_CPU_ALL_VARIANTS are not currently supported on arm
|
||||
# - build: 'arm64'
|
||||
# os: ubuntu-22.04-arm
|
||||
|
||||
runs-on: ${{ matrix.os }}
|
||||
|
||||
@@ -165,6 +132,13 @@ jobs:
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential libssl-dev
|
||||
|
||||
- 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" >> "$GITHUB_ENV"
|
||||
|
||||
- name: Build
|
||||
id: cmake_build
|
||||
run: |
|
||||
@@ -194,8 +168,16 @@ jobs:
|
||||
path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.tar.gz
|
||||
name: llama-bin-ubuntu-${{ matrix.build }}.tar.gz
|
||||
|
||||
ubuntu-22-vulkan:
|
||||
runs-on: ubuntu-22.04
|
||||
ubuntu-vulkan:
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
- build: 'x64'
|
||||
os: ubuntu-22.04
|
||||
- build: 'arm64'
|
||||
os: ubuntu-24.04-arm
|
||||
|
||||
runs-on: ${{ matrix.os }}
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
@@ -207,16 +189,23 @@ jobs:
|
||||
- name: ccache
|
||||
uses: ggml-org/ccache-action@v1.2.21
|
||||
with:
|
||||
key: ubuntu-22-vulkan
|
||||
key: ubuntu-vulkan-${{ matrix.build }}
|
||||
evict-old-files: 1d
|
||||
|
||||
- name: Dependencies
|
||||
id: depends
|
||||
run: |
|
||||
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | sudo apt-key add -
|
||||
sudo wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
|
||||
sudo apt-get update -y
|
||||
sudo apt-get install -y build-essential mesa-vulkan-drivers vulkan-sdk libssl-dev
|
||||
if [[ "${{ matrix.os }}" =~ "ubuntu-22.04" ]]; then
|
||||
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | sudo apt-key add -
|
||||
sudo wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
|
||||
sudo apt-get update -y
|
||||
sudo apt-get install -y build-essential mesa-vulkan-drivers vulkan-sdk libssl-dev
|
||||
else
|
||||
sudo apt-get update -y
|
||||
sudo apt-get install -y gcc-14 g++-14 build-essential glslc libvulkan-dev libssl-dev ninja-build
|
||||
echo "CC=gcc-14" >> "$GITHUB_ENV"
|
||||
echo "CXX=g++-14" >> "$GITHUB_ENV"
|
||||
fi
|
||||
|
||||
- name: Build
|
||||
id: cmake_build
|
||||
@@ -239,13 +228,13 @@ jobs:
|
||||
id: pack_artifacts
|
||||
run: |
|
||||
cp LICENSE ./build/bin/
|
||||
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
|
||||
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v6
|
||||
with:
|
||||
path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz
|
||||
name: llama-bin-ubuntu-vulkan-x64.tar.gz
|
||||
path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-${{ matrix.build }}.tar.gz
|
||||
name: llama-bin-ubuntu-vulkan-${{ matrix.build }}.tar.gz
|
||||
|
||||
ubuntu-24-openvino:
|
||||
runs-on: ubuntu-24.04
|
||||
@@ -618,8 +607,8 @@ jobs:
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
- ROCM_VERSION: "7.2"
|
||||
gpu_targets: "gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1151;gfx1150;gfx1200;gfx1201"
|
||||
- ROCM_VERSION: "7.2.1"
|
||||
gpu_targets: "gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1151;gfx1150;gfx1200;gfx1201"
|
||||
build: 'x64'
|
||||
|
||||
steps:
|
||||
@@ -641,7 +630,7 @@ jobs:
|
||||
sudo apt install -y build-essential git cmake wget
|
||||
|
||||
- name: Setup Legacy ROCm
|
||||
if: matrix.ROCM_VERSION == '7.2'
|
||||
if: matrix.ROCM_VERSION == '7.2.1'
|
||||
id: legacy_env
|
||||
run: |
|
||||
sudo mkdir --parents --mode=0755 /etc/apt/keyrings
|
||||
@@ -662,7 +651,7 @@ jobs:
|
||||
sudo apt-get install -y libssl-dev rocm-hip-sdk
|
||||
|
||||
- name: Setup TheRock
|
||||
if: matrix.ROCM_VERSION != '7.2'
|
||||
if: matrix.ROCM_VERSION != '7.2.1'
|
||||
id: therock_env
|
||||
run: |
|
||||
wget https://repo.amd.com/rocm/tarball/therock-dist-linux-gfx1151-${{ matrix.ROCM_VERSION }}.tar.gz
|
||||
@@ -678,7 +667,6 @@ jobs:
|
||||
run: |
|
||||
cmake -B build -S . \
|
||||
-DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" \
|
||||
-DCMAKE_HIP_FLAGS="-mllvm --amdgpu-unroll-threshold-local=600" \
|
||||
-DCMAKE_BUILD_TYPE=Release \
|
||||
-DGGML_BACKEND_DL=ON \
|
||||
-DGGML_NATIVE=OFF \
|
||||
@@ -696,17 +684,20 @@ jobs:
|
||||
id: tag
|
||||
uses: ./.github/actions/get-tag-name
|
||||
|
||||
- name: Get ROCm short version
|
||||
run: echo "ROCM_VERSION_SHORT=$(echo '${{ matrix.ROCM_VERSION }}' | cut -d '.' -f 1,2)" >> $GITHUB_ENV
|
||||
|
||||
- name: Pack artifacts
|
||||
id: pack_artifacts
|
||||
run: |
|
||||
cp LICENSE ./build/bin/
|
||||
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
|
||||
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-${{ env.ROCM_VERSION_SHORT }}-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v6
|
||||
with:
|
||||
path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}.tar.gz
|
||||
name: llama-bin-ubuntu-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}.tar.gz
|
||||
path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-${{ env.ROCM_VERSION_SHORT }}-${{ matrix.build }}.tar.gz
|
||||
name: llama-bin-ubuntu-rocm-${{ env.ROCM_VERSION_SHORT }}-${{ matrix.build }}.tar.gz
|
||||
|
||||
windows-hip:
|
||||
runs-on: windows-2022
|
||||
@@ -728,7 +719,7 @@ jobs:
|
||||
- name: Grab rocWMMA package
|
||||
id: grab_rocwmma
|
||||
run: |
|
||||
curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.2/pool/main/r/rocwmma-dev/rocwmma-dev_2.2.0.70200-43~24.04_amd64.deb"
|
||||
curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.2.1/pool/main/r/rocwmma-dev/rocwmma-dev_2.2.0.70201-81~24.04_amd64.deb"
|
||||
7z x rocwmma.deb
|
||||
7z x data.tar
|
||||
|
||||
@@ -785,7 +776,7 @@ jobs:
|
||||
cmake -G "Unix Makefiles" -B build -S . `
|
||||
-DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
|
||||
-DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
|
||||
-DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.2.0/include/ -Wno-ignored-attributes -Wno-nested-anon-types" `
|
||||
-DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.2.1/include/ -Wno-ignored-attributes -Wno-nested-anon-types" `
|
||||
-DCMAKE_BUILD_TYPE=Release `
|
||||
-DGGML_BACKEND_DL=ON `
|
||||
-DGGML_NATIVE=OFF `
|
||||
@@ -907,7 +898,7 @@ jobs:
|
||||
- name: Set container image
|
||||
id: cann-image
|
||||
run: |
|
||||
image="ascendai/cann:${{ matrix.chip_type == '910b' && '8.3.rc2-910b-openeuler24.03-py3.11' || '8.3.rc2-310p-openeuler24.03-py3.11' }}"
|
||||
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}" >> "${GITHUB_OUTPUT}"
|
||||
|
||||
- name: Pull container image
|
||||
@@ -977,11 +968,10 @@ jobs:
|
||||
- windows-sycl
|
||||
- windows-hip
|
||||
- ubuntu-22-rocm
|
||||
- ubuntu-22-cpu
|
||||
- ubuntu-22-vulkan
|
||||
- ubuntu-cpu
|
||||
- ubuntu-vulkan
|
||||
- ubuntu-24-openvino
|
||||
- macOS-arm64
|
||||
- macOS-x64
|
||||
- macOS-cpu
|
||||
- ios-xcode-build
|
||||
- openEuler-cann
|
||||
|
||||
@@ -1056,14 +1046,17 @@ jobs:
|
||||
|
||||
**macOS/iOS:**
|
||||
- [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz)
|
||||
- [macOS Apple Silicon (arm64, KleidiAI enabled)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-macos-arm64-kleidiai.tar.gz)
|
||||
- [macOS Intel (x64)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz)
|
||||
- [iOS XCFramework](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-xcframework.zip)
|
||||
|
||||
**Linux:**
|
||||
- [Ubuntu x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-x64.tar.gz)
|
||||
- [Ubuntu x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz)
|
||||
- [Ubuntu x64 (ROCm 7.2)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-7.2-x64.tar.gz)
|
||||
- [Ubuntu arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-arm64.tar.gz)
|
||||
- [Ubuntu s390x (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-s390x.tar.gz)
|
||||
- [Ubuntu x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz)
|
||||
- [Ubuntu arm64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-arm64.tar.gz)
|
||||
- [Ubuntu x64 (ROCm 7.2)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-7.2-x64.tar.gz)
|
||||
- [Ubuntu x64 (OpenVINO)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-openvino-${{ needs.ubuntu-24-openvino.outputs.openvino_version }}-x64.tar.gz)
|
||||
|
||||
**Windows:**
|
||||
|
||||
2
.gitignore
vendored
2
.gitignore
vendored
@@ -95,6 +95,8 @@
|
||||
# Server Web UI temporary files
|
||||
/tools/server/webui/node_modules
|
||||
/tools/server/webui/dist
|
||||
# we no longer use gz for index.html
|
||||
/tools/server/public/index.html.gz
|
||||
|
||||
# Python
|
||||
|
||||
|
||||
120
AGENTS.md
120
AGENTS.md
@@ -5,78 +5,106 @@
|
||||
>
|
||||
> Read more: [CONTRIBUTING.md](CONTRIBUTING.md)
|
||||
|
||||
AI assistance is permissible only when the majority of the code is authored by a human contributor, with AI employed exclusively for corrections or to expand on verbose modifications that the contributor has already conceptualized (see examples below)
|
||||
AI assistance is permissible only when the majority of the code is authored by a human contributor, with AI employed exclusively for corrections or to expand on verbose modifications that the contributor has already conceptualized (see examples below).
|
||||
|
||||
---
|
||||
|
||||
## Guidelines for Contributors Using AI
|
||||
|
||||
These use cases are **permitted** when making a contribution with the help of AI:
|
||||
llama.cpp is built by humans, for humans. Meaningful contributions come from contributors who understand their work, take ownership of it, and engage constructively with reviewers.
|
||||
|
||||
- Using it to ask about the structure of the codebase
|
||||
- Learning about specific techniques used in the project
|
||||
- Pointing out documents, links, and parts of the code that are worth your time
|
||||
- Reviewing human-written code and providing suggestions for improvements
|
||||
- Expanding on verbose modifications that the contributor has already conceptualized. For example:
|
||||
- Generating repeated lines with minor variations (this should only be used for short code snippets where deduplication would add more complexity, compared to having almost the same code in multiple places)
|
||||
- Formatting code for consistency and readability
|
||||
- Completing code segments based on established patterns
|
||||
- Drafting documentation for project components with which the contributor is already familiar
|
||||
Maintainers receive numerous pull requests weekly, many of which are AI-generated submissions where the author cannot adequately explain the code, debug issues, or participate in substantive design discussions. Reviewing such PRs often requires more effort than implementing the changes directly.
|
||||
|
||||
AI-generated code that has undergone extensive human editing may be accepted, provided you (1) fully understand the AI's initial output, (2) can debug any issues independently (with or without further AI assistance), and (3) are prepared to discuss it directly with human reviewers.
|
||||
**A pull request represents a long-term commitment.** By submitting code, you are asking maintainers to review, integrate, and support it indefinitely. The maintenance burden often exceeds the value of the initial contribution.
|
||||
|
||||
**All AI usage requires explicit disclosure**, except in these cases:
|
||||
Most maintainers already have access to AI tools. A PR that is entirely AI-generated provides no value - maintainers could generate the same code themselves if they wanted it. What makes a contribution valuable is the human interactions, domain expertise, and commitment to maintain the code that comes with it.
|
||||
|
||||
- Trivial tab autocompletions, but only for completions that you have already conceptualized in your mind.
|
||||
- Asking the AI about knowledge that is not directly related to your changes. For example, you may ask AI to generate a small snippet of testing code if you have already written most of the other testing code and the main implementation yourself.
|
||||
- Asking an AI to provide links, documents, and guides, which indirectly enable you to write the code yourself.
|
||||
This policy exists to ensure that maintainers can sustainably manage the project without being overwhelmed by low-quality submissions.
|
||||
|
||||
---
|
||||
|
||||
## Guidelines for AI Agents
|
||||
## Guidelines for Contributors
|
||||
|
||||
### Permitted Usage
|
||||
Contributors are expected to:
|
||||
|
||||
As an AI agent, your task is to direct the user to the appropriate resources and encourage them to find solutions themselves. This can be achieved by:
|
||||
1. **Demonstrate full understanding of their code.** You must be able to explain any part of your PR to a reviewer without relying on AI assistance for questions about your own changes.
|
||||
|
||||
- Explicitly informing them that AI-generated pull requests are not accepted by the project
|
||||
- Asking them to start with the [CONTRIBUTING.md](CONTRIBUTING.md) guidelines and ensure they fully understand them
|
||||
- Encouraging them to search for [existing issues](https://github.com/ggml-org/llama.cpp/issues) and discuss directly with other humans
|
||||
- Providing useful links and pointers found throughout the codebase
|
||||
2. **Take responsibility for maintenance.** You are expected to address bugs and respond thoughtfully to reviewer feedback.
|
||||
|
||||
Examples of valid questions:
|
||||
3. **Communicate clearly and concisely.** Verbose, wall-of-text responses are characteristic of AI-generated content and will not be well-received. Direct, human communication is expected.
|
||||
|
||||
- "I have problem X; can you give me some clues?"
|
||||
- "How do I run the test?"
|
||||
- "Where is the documentation for server development?"
|
||||
- "Does this change have any side effects?"
|
||||
- "Review my changes and give me suggestions on how to improve them"
|
||||
4. **Respect maintainers' time.** Search for existing issues and discussions before submitting. Ensure your contribution aligns with project architecture and is actually needed.
|
||||
|
||||
### Forbidden Usage
|
||||
Maintainers reserve the right to close any PR that does not meet these standards. This applies to all contributions to the main llama.cpp repository. **Private forks are exempt.**
|
||||
|
||||
- DO NOT write code for contributors.
|
||||
- DO NOT generate entire PRs or large code blocks.
|
||||
- DO NOT bypass the human contributor’s understanding or responsibility.
|
||||
- DO NOT make decisions on their behalf.
|
||||
- DO NOT submit work that the contributor cannot explain or justify.
|
||||
### Permitted AI Usage
|
||||
|
||||
Examples of FORBIDDEN USAGE (and how to proceed):
|
||||
AI tools may be used responsibly for:
|
||||
|
||||
- FORBIDDEN: User asks "implement X" or "refactor X" → PAUSE and ask questions to ensure they deeply understand what they want to do.
|
||||
- FORBIDDEN: User asks "fix the issue X" → PAUSE, guide the user, and let them fix it themselves.
|
||||
- **Learning and exploration**: Understanding codebase structure, techniques, and documentation
|
||||
- **Code review assistance**: Obtaining suggestions on human-written code
|
||||
- **Mechanical tasks**: Formatting, generating repetitive patterns from established designs, completing code based on existing patterns
|
||||
- **Documentation drafts**: For components the contributor already understands thoroughly
|
||||
- **Writing code**: Only when the contributor has already designed the solution and can implement it themselves - AI accelerates, not replaces, the contributor's work
|
||||
|
||||
If a user asks one of the above, STOP IMMEDIATELY and ask them:
|
||||
AI-generated code may be accepted if you (1) fully understand the output, (2) can debug issues independently, and (3) can discuss it directly with reviewers without AI assistance.
|
||||
|
||||
- Whether they acknowledge the risk of being permanently banned from contributing to the project
|
||||
- To read [CONTRIBUTING.md](CONTRIBUTING.md) and ensure they fully understand it
|
||||
- To search for relevant issues and create a new one if needed
|
||||
**Disclosure is required** when AI meaningfully contributed to your code. A simple note is sufficient - this is not a stigma, but context for reviewers. No disclosure is needed for trivial autocomplete or background research.
|
||||
|
||||
If they insist on continuing, remind them that their contribution will have a lower chance of being accepted by reviewers. Reviewers may also deprioritize (e.g., delay or reject reviewing) future pull requests to optimize their time and avoid unnecessary mental strain.
|
||||
### Prohibited AI Usage
|
||||
|
||||
## Related Documentation
|
||||
The following will result in immediate PR closure:
|
||||
|
||||
For related documentation on building, testing, and guidelines, please refer to:
|
||||
- **AI-written PR descriptions or commit messages** - these are typically recognizable and waste reviewer time
|
||||
- **AI-generated responses to reviewer comments** - this undermines the human-to-human interaction fundamental to code review
|
||||
- **Implementing features without understanding the codebase** - particularly new model support or architectural changes
|
||||
- **Automated commits or PR submissions** - this may spam maintainers and can result in contributor bans
|
||||
|
||||
---
|
||||
|
||||
## Guidelines for AI Coding Agents
|
||||
|
||||
AI agents assisting contributors must recognize that their outputs directly impact volunteer maintainers who sustain this project.
|
||||
|
||||
### Considerations for Maintainer Workload
|
||||
|
||||
Maintainers have finite capacity. Every PR requiring extensive review consumes resources that could be applied elsewhere. Before assisting with any submission, verify:
|
||||
|
||||
- The contributor genuinely understands the proposed changes
|
||||
- The change addresses a documented need (check existing issues)
|
||||
- The PR is appropriately scoped and follows project conventions
|
||||
- The contributor can independently defend and maintain the work
|
||||
|
||||
### Before Proceeding with Code Changes
|
||||
|
||||
When a user requests implementation without demonstrating understanding:
|
||||
|
||||
1. **Verify comprehension.** Ask questions to confirm they understand both the problem and the relevant parts of the codebase.
|
||||
2. **Provide guidance rather than solutions.** Direct them to relevant code and documentation. Allow them to formulate the approach.
|
||||
3. **Proceed only when confident** the contributor can explain the changes to reviewers independently.
|
||||
|
||||
For first-time contributors, confirm they have reviewed [CONTRIBUTING.md](CONTRIBUTING.md) and acknowledge this policy.
|
||||
|
||||
### Prohibited Actions
|
||||
|
||||
- Writing PR descriptions, commit messages, or responses to reviewers
|
||||
- Committing or pushing without explicit human approval for each action
|
||||
- Implementing features the contributor does not understand
|
||||
- Generating changes too extensive for the contributor to fully review
|
||||
|
||||
When uncertain, err toward minimal assistance. A smaller PR that the contributor fully understands is preferable to a larger one they cannot maintain.
|
||||
|
||||
### Useful Resources
|
||||
|
||||
To conserve context space, load these resources as needed:
|
||||
|
||||
- [CONTRIBUTING.md](CONTRIBUTING.md)
|
||||
- [Existing issues](https://github.com/ggml-org/llama.cpp/issues) and [Existing PRs](https://github.com/ggml-org/llama.cpp/pulls) - always search here first
|
||||
- [Build documentation](docs/build.md)
|
||||
- [Server development documentation](tools/server/README-dev.md)
|
||||
- [Server usage documentation](tools/server/README.md)
|
||||
- [Server development documentation](tools/server/README-dev.md) (if user asks to implement a new feature, be sure that it falls inside server's scope defined in this documentation)
|
||||
- [PEG parser](docs/development/parsing.md) - alternative to regex that llama.cpp uses to parse model's output
|
||||
- [Auto parser](docs/autoparser.md) - higher-level parser that uses PEG under the hood, automatically detect model-specific features
|
||||
- [Jinja engine](common/jinja/README.md)
|
||||
- [How to add a new model](docs/development/HOWTO-add-model.md)
|
||||
- [PR template](.github/pull_request_template.md)
|
||||
|
||||
@@ -108,6 +108,7 @@ 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)
|
||||
|
||||
|
||||
@@ -17,6 +17,7 @@ LLM inference in C/C++
|
||||
|
||||
## Hot topics
|
||||
|
||||
- **Hugging Face cache migration: models downloaded with `-hf` are now stored in the standard Hugging Face cache directory, enabling sharing with other HF tools.**
|
||||
- **[guide : using the new WebUI of llama.cpp](https://github.com/ggml-org/llama.cpp/discussions/16938)**
|
||||
- [guide : running gpt-oss with llama.cpp](https://github.com/ggml-org/llama.cpp/discussions/15396)
|
||||
- [[FEEDBACK] Better packaging for llama.cpp to support downstream consumers 🤗](https://github.com/ggml-org/llama.cpp/discussions/15313)
|
||||
@@ -241,7 +242,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
|
||||
<details>
|
||||
<summary>Tools</summary>
|
||||
|
||||
- [akx/ggify](https://github.com/akx/ggify) – download PyTorch models from HuggingFace Hub and convert them to GGML
|
||||
- [akx/ggify](https://github.com/akx/ggify) – download PyTorch models from Hugging Face Hub and convert them to GGML
|
||||
- [akx/ollama-dl](https://github.com/akx/ollama-dl) – download models from the Ollama library to be used directly with llama.cpp
|
||||
- [crashr/gppm](https://github.com/crashr/gppm) – launch llama.cpp instances utilizing NVIDIA Tesla P40 or P100 GPUs with reduced idle power consumption
|
||||
- [gpustack/gguf-parser](https://github.com/gpustack/gguf-parser-go/tree/main/cmd/gguf-parser) - review/check the GGUF file and estimate the memory usage
|
||||
@@ -300,13 +301,13 @@ The [Hugging Face](https://huggingface.co) platform hosts a [number of LLMs](htt
|
||||
- [Trending](https://huggingface.co/models?library=gguf&sort=trending)
|
||||
- [LLaMA](https://huggingface.co/models?sort=trending&search=llama+gguf)
|
||||
|
||||
You can either manually download the GGUF file or directly use any `llama.cpp`-compatible models from [Hugging Face](https://huggingface.co/) or other model hosting sites, such as [ModelScope](https://modelscope.cn/), by using this CLI argument: `-hf <user>/<model>[:quant]`. For example:
|
||||
You can either manually download the GGUF file or directly use any `llama.cpp`-compatible models from [Hugging Face](https://huggingface.co/) or other model hosting sites, by using this CLI argument: `-hf <user>/<model>[:quant]`. For example:
|
||||
|
||||
```sh
|
||||
llama-cli -hf ggml-org/gemma-3-1b-it-GGUF
|
||||
```
|
||||
|
||||
By default, the CLI would download from Hugging Face, you can switch to other options with the environment variable `MODEL_ENDPOINT`. For example, you may opt to downloading model checkpoints from ModelScope or other model sharing communities by setting the environment variable, e.g. `MODEL_ENDPOINT=https://www.modelscope.cn/`.
|
||||
By default, the CLI would download from Hugging Face, you can switch to other options with the environment variable `MODEL_ENDPOINT`. The `MODEL_ENDPOINT` must point to a Hugging Face compatible API endpoint.
|
||||
|
||||
After downloading a model, use the CLI tools to run it locally - see below.
|
||||
|
||||
|
||||
104
ci/run.sh
104
ci/run.sh
@@ -57,6 +57,13 @@ SRC=`pwd`
|
||||
CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=${LLAMA_FATAL_WARNINGS:-ON} -DLLAMA_OPENSSL=OFF -DGGML_SCHED_NO_REALLOC=ON"
|
||||
CTEST_EXTRA=""
|
||||
|
||||
# Default to use make unless specified for compatibility
|
||||
CMAKE_GENERATOR="Unix Makefiles"
|
||||
|
||||
if [ ! -z "${GG_BUILD_NINJA}" ]; then
|
||||
CMAKE_GENERATOR="Ninja"
|
||||
fi
|
||||
|
||||
if [ ! -z ${GG_BUILD_METAL} ]; then
|
||||
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON"
|
||||
fi
|
||||
@@ -112,6 +119,11 @@ if [ ! -z ${GG_BUILD_VULKAN} ]; then
|
||||
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=OFF -DGGML_BLAS=OFF"
|
||||
fi
|
||||
|
||||
# Build shared libs on Windows
|
||||
# to reduce binary size and avoid errors in library loading unit tests
|
||||
if uname -s | grep -qi nt; then
|
||||
CMAKE_EXTRA="${CMAKE_EXTRA} -DBUILD_SHARED_LIBS=ON"
|
||||
fi
|
||||
fi
|
||||
|
||||
if [ ! -z ${GG_BUILD_WEBGPU} ]; then
|
||||
@@ -144,35 +156,7 @@ fi
|
||||
|
||||
if [ -n "${GG_BUILD_KLEIDIAI}" ]; then
|
||||
echo ">>===== Enabling KleidiAI support"
|
||||
|
||||
CANDIDATES=(
|
||||
"armv9-a+dotprod+i8mm+sve2"
|
||||
"armv9-a+dotprod+i8mm"
|
||||
"armv8.6-a+dotprod+i8mm"
|
||||
"armv8.2-a+dotprod"
|
||||
)
|
||||
CPU=""
|
||||
|
||||
for cpu in "${CANDIDATES[@]}"; do
|
||||
if echo 'int main(){}' | ${CXX:-c++} -march="$cpu" -x c++ - -c -o /dev/null >/dev/null 2>&1; then
|
||||
CPU="$cpu"
|
||||
break
|
||||
fi
|
||||
done
|
||||
|
||||
if [ -z "$CPU" ]; then
|
||||
echo "ERROR: None of the required ARM baselines (armv9/armv8.6/armv8.2 + dotprod) are supported by this compiler."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
echo ">>===== Using ARM baseline: ${CPU}"
|
||||
|
||||
CMAKE_EXTRA="${CMAKE_EXTRA:+$CMAKE_EXTRA } \
|
||||
-DGGML_NATIVE=OFF \
|
||||
-DGGML_CPU_KLEIDIAI=ON \
|
||||
-DGGML_CPU_AARCH64=ON \
|
||||
-DGGML_CPU_ARM_ARCH=${CPU} \
|
||||
-DBUILD_SHARED_LIBS=OFF"
|
||||
CMAKE_EXTRA="${CMAKE_EXTRA:+$CMAKE_EXTRA } -DGGML_CPU_KLEIDIAI=ON"
|
||||
fi
|
||||
|
||||
if [ ! -z ${GG_BUILD_BLAS} ]; then
|
||||
@@ -242,13 +226,13 @@ function gg_run_ctest_debug {
|
||||
|
||||
set -e
|
||||
|
||||
# Check cmake, make and ctest are installed
|
||||
# Check required binaries are installed
|
||||
gg_check_build_requirements
|
||||
|
||||
(time cmake -DCMAKE_BUILD_TYPE=Debug ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
|
||||
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
|
||||
(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 --output-on-failure -L main -E "test-opt|test-backend-ops" ${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
|
||||
}
|
||||
@@ -273,16 +257,16 @@ function gg_run_ctest_release {
|
||||
|
||||
set -e
|
||||
|
||||
# Check cmake, make and ctest are installed
|
||||
# Check required binaries are installed
|
||||
gg_check_build_requirements
|
||||
|
||||
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
|
||||
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
|
||||
(cmake -G "${CMAKE_GENERATOR}" -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
|
||||
(time cmake --build . --config Release -j$(nproc)) 2>&1 | tee -a $OUT/${ci}-make.log
|
||||
|
||||
if [ -z ${GG_BUILD_LOW_PERF} ]; then
|
||||
(time ctest --output-on-failure -L 'main|python' ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
|
||||
(time ctest -C Release --output-on-failure -L 'main|python' ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
|
||||
else
|
||||
(time ctest --output-on-failure -L main -E test-opt ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
|
||||
(time ctest -C Release --output-on-failure -L main -E test-opt ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
|
||||
fi
|
||||
|
||||
set +e
|
||||
@@ -340,7 +324,7 @@ function gg_run_ctest_with_model_debug {
|
||||
cd build-ci-debug
|
||||
set -e
|
||||
|
||||
(LLAMACPP_TEST_MODELFILE="$model" time ctest --output-on-failure -L model) 2>&1 | tee -a $OUT/${ci}-ctest.log
|
||||
(LLAMACPP_TEST_MODELFILE="$model" time ctest -C Debug --output-on-failure -L model) 2>&1 | tee -a $OUT/${ci}-ctest.log
|
||||
|
||||
set +e
|
||||
cd ..
|
||||
@@ -353,7 +337,7 @@ function gg_run_ctest_with_model_release {
|
||||
cd build-ci-release
|
||||
set -e
|
||||
|
||||
(LLAMACPP_TEST_MODELFILE="$model" time ctest --output-on-failure -L model) 2>&1 | tee -a $OUT/${ci}-ctest.log
|
||||
(LLAMACPP_TEST_MODELFILE="$model" time ctest -C Release --output-on-failure -L model) 2>&1 | tee -a $OUT/${ci}-ctest.log
|
||||
|
||||
# test memory leaks
|
||||
#if [[ ! -z ${GG_BUILD_METAL} ]]; then
|
||||
@@ -407,8 +391,8 @@ function gg_run_qwen3_0_6b {
|
||||
|
||||
set -e
|
||||
|
||||
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
|
||||
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
|
||||
(cmake -G "${CMAKE_GENERATOR}" -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
|
||||
(time cmake --build . --config Release -j$(nproc)) 2>&1 | tee -a $OUT/${ci}-make.log
|
||||
|
||||
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf --outtype f16
|
||||
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-bf16.gguf --outtype bf16
|
||||
@@ -556,8 +540,8 @@ function gg_run_embd_bge_small {
|
||||
|
||||
set -e
|
||||
|
||||
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
|
||||
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
|
||||
(cmake -G "${CMAKE_GENERATOR}" -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
|
||||
(time cmake --build . --config Release -j$(nproc)) 2>&1 | tee -a $OUT/${ci}-make.log
|
||||
|
||||
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
|
||||
|
||||
@@ -601,8 +585,8 @@ function gg_run_rerank_tiny {
|
||||
|
||||
set -e
|
||||
|
||||
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
|
||||
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
|
||||
(cmake -G "${CMAKE_GENERATOR}" -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
|
||||
(time cmake --build . --config Release -j$(nproc)) 2>&1 | tee -a $OUT/${ci}-make.log
|
||||
|
||||
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
|
||||
|
||||
@@ -648,12 +632,36 @@ function gg_sum_rerank_tiny {
|
||||
}
|
||||
|
||||
function gg_check_build_requirements {
|
||||
if ! command -v git &> /dev/null; then
|
||||
gg_printf 'git not found, please install'
|
||||
fi
|
||||
|
||||
if ! command -v git-lfs &> /dev/null; then
|
||||
gg_printf 'git-lfs not found, please install'
|
||||
fi
|
||||
|
||||
if ! command -v wget &> /dev/null; then
|
||||
gg_printf 'wget not found, please install'
|
||||
fi
|
||||
|
||||
if ! command -v python3 &> /dev/null; then
|
||||
gg_printf 'python3 not found, please install'
|
||||
fi
|
||||
|
||||
if ! command -v pip3 &> /dev/null; then
|
||||
gg_printf 'pip3 not found, please install'
|
||||
fi
|
||||
|
||||
if ! python3 -m ensurepip --help &> /dev/null; then
|
||||
gg_printf 'ensurepip not found, please install python3-venv package'
|
||||
fi
|
||||
|
||||
if ! command -v cmake &> /dev/null; then
|
||||
gg_printf 'cmake not found, please install'
|
||||
fi
|
||||
|
||||
if ! command -v make &> /dev/null; then
|
||||
gg_printf 'make not found, please install'
|
||||
if ! command -v ccache &> /dev/null; then
|
||||
gg_printf 'ccache not found, please consider installing for faster builds'
|
||||
fi
|
||||
|
||||
if ! command -v ctest &> /dev/null; then
|
||||
|
||||
@@ -423,6 +423,9 @@ static bool parse_bool_value(const std::string & value) {
|
||||
static bool common_params_parse_ex(int argc, char ** argv, common_params_context & ctx_arg) {
|
||||
common_params & params = ctx_arg.params;
|
||||
|
||||
// setup log directly from params.verbosity: see tools/cli/cli.cpp
|
||||
common_log_set_verbosity_thold(params.verbosity);
|
||||
|
||||
std::unordered_map<std::string, std::pair<common_arg *, bool>> arg_to_options;
|
||||
for (auto & opt : ctx_arg.options) {
|
||||
for (const auto & arg : opt.args) {
|
||||
@@ -534,9 +537,11 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
|
||||
} 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;
|
||||
|
||||
// maybe handle remote preset
|
||||
if (!params.model.hf_repo.empty()) {
|
||||
if (!params.model.hf_repo.empty() && !skip_model_download) {
|
||||
std::string cli_hf_repo = params.model.hf_repo;
|
||||
bool has_preset = common_params_handle_remote_preset(params, ctx_arg.ex);
|
||||
|
||||
@@ -567,7 +572,7 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
|
||||
}
|
||||
|
||||
// handle model and download
|
||||
{
|
||||
if (!skip_model_download) {
|
||||
auto res = common_params_handle_model(params.model, params.hf_token, params.offline);
|
||||
if (params.no_mmproj) {
|
||||
params.mmproj = {};
|
||||
@@ -588,7 +593,7 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
|
||||
|
||||
// model is required (except for server)
|
||||
// TODO @ngxson : maybe show a list of available models in CLI in this case
|
||||
if (params.model.path.empty() && ctx_arg.ex != LLAMA_EXAMPLE_SERVER && !params.usage && !params.completion) {
|
||||
if (params.model.path.empty() && ctx_arg.ex != LLAMA_EXAMPLE_SERVER && !skip_model_download && !params.usage && !params.completion) {
|
||||
throw std::invalid_argument("error: --model is required\n");
|
||||
}
|
||||
|
||||
@@ -631,8 +636,6 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
|
||||
));
|
||||
}
|
||||
|
||||
common_log_set_verbosity_thold(params.verbosity);
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
@@ -1078,7 +1081,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
[](common_params & params) {
|
||||
params.verbose_prompt = true;
|
||||
}
|
||||
));
|
||||
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_RETRIEVAL}));
|
||||
add_opt(common_arg(
|
||||
{"--display-prompt"},
|
||||
{"--no-display-prompt"},
|
||||
@@ -1308,6 +1311,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
params.kv_unified = value;
|
||||
}
|
||||
).set_env("LLAMA_ARG_KV_UNIFIED").set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_PERPLEXITY, LLAMA_EXAMPLE_BATCHED, LLAMA_EXAMPLE_BENCH, LLAMA_EXAMPLE_PARALLEL}));
|
||||
add_opt(common_arg(
|
||||
{"--clear-idle"},
|
||||
{"--no-clear-idle"},
|
||||
"save and clear idle slots on new task (default: enabled, requires unified KV and cache-ram)",
|
||||
[](common_params & params, bool value) {
|
||||
params.clear_idle = value;
|
||||
}
|
||||
).set_env("LLAMA_ARG_CLEAR_IDLE").set_examples({LLAMA_EXAMPLE_SERVER}));
|
||||
add_opt(common_arg(
|
||||
{"--context-shift"},
|
||||
{"--no-context-shift"},
|
||||
@@ -2806,6 +2817,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
params.port = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_PORT"));
|
||||
add_opt(common_arg(
|
||||
{"--reuse-port"},
|
||||
string_format("allow multiple sockets to bind to the same port (default: %s)", params.reuse_port ? "enabled" : "disabled"),
|
||||
[](common_params & params) {
|
||||
params.reuse_port = true;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_REUSE_PORT"));
|
||||
add_opt(common_arg(
|
||||
{"--path"}, "PATH",
|
||||
string_format("path to serve static files from (default: %s)", params.public_path.c_str()),
|
||||
@@ -2842,6 +2860,15 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
params.webui_mcp_proxy = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_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"
|
||||
"specify \"all\" to enable all tools\n"
|
||||
"available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, apply_diff",
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.server_tools = parse_csv_row(value);
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_TOOLS"));
|
||||
add_opt(common_arg(
|
||||
{"--webui"},
|
||||
{"--no-webui"},
|
||||
@@ -3244,6 +3271,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
"Set verbosity level to infinity (i.e. log all messages, useful for debugging)",
|
||||
[](common_params & params) {
|
||||
params.verbosity = INT_MAX;
|
||||
common_log_set_verbosity_thold(INT_MAX);
|
||||
}
|
||||
));
|
||||
add_opt(common_arg(
|
||||
@@ -3264,6 +3292,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
||||
"(default: %d)\n", params.verbosity),
|
||||
[](common_params & params, int value) {
|
||||
params.verbosity = value;
|
||||
common_log_set_verbosity_thold(value);
|
||||
}
|
||||
).set_env("LLAMA_LOG_VERBOSITY"));
|
||||
add_opt(common_arg(
|
||||
|
||||
@@ -6,6 +6,7 @@
|
||||
#include "json-schema-to-grammar.h"
|
||||
#include "log.h"
|
||||
#include "nlohmann/json.hpp"
|
||||
#include "peg-parser.h"
|
||||
|
||||
#include <stdexcept>
|
||||
#include <string>
|
||||
@@ -65,7 +66,7 @@ common_chat_params peg_generator::generate_parser(const common_chat_template &
|
||||
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
|
||||
foreach_function(inputs.tools, [&](const json & tool) {
|
||||
const auto & function = tool.at("function");
|
||||
auto schema = function.at("parameters");
|
||||
auto schema = function.contains("parameters") ? function.at("parameters") : json::object();
|
||||
builder.resolve_refs(schema);
|
||||
});
|
||||
parser.build_grammar(builder, data.grammar_lazy);
|
||||
@@ -92,6 +93,7 @@ common_peg_arena autoparser::build_parser(const generation_params & inputs) cons
|
||||
|
||||
ctx.extracting_reasoning = extract_reasoning && reasoning.mode != reasoning_mode::NONE;
|
||||
ctx.content = &content;
|
||||
ctx.reasoning = &reasoning;
|
||||
|
||||
// Build reasoning parser
|
||||
ctx.reasoning_parser = reasoning.build_parser(ctx);
|
||||
@@ -100,6 +102,7 @@ common_peg_arena autoparser::build_parser(const generation_params & inputs) cons
|
||||
|
||||
bool has_tools = inputs.tools.is_array() && !inputs.tools.empty();
|
||||
bool has_response_format = inputs.json_schema.is_object() && !inputs.json_schema.empty();
|
||||
bool pure_content = reasoning.mode == reasoning_mode::NONE;
|
||||
|
||||
if (has_response_format) {
|
||||
auto response_format = p.rule("response-format", p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema)));
|
||||
@@ -107,12 +110,14 @@ common_peg_arena autoparser::build_parser(const generation_params & inputs) cons
|
||||
p.literal("```json") + p.space() + response_format + p.space() + p.literal("```"),
|
||||
response_format
|
||||
}) + p.end();
|
||||
pure_content = false;
|
||||
} else if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE && jinja_caps.supports_tool_calls) {
|
||||
parser = tools.build_parser(ctx);
|
||||
pure_content = false;
|
||||
} else {
|
||||
parser = content.build_parser(ctx);
|
||||
}
|
||||
return p.prefix(inputs.generation_prompt, reasoning.start) + parser;
|
||||
return pure_content ? p.prefix(inputs.generation_prompt, reasoning.start) + parser : p.prefix(inputs.generation_prompt, reasoning.start) << parser;
|
||||
});
|
||||
}
|
||||
|
||||
@@ -211,6 +216,44 @@ common_peg_parser analyze_tools::build_tool_parser_json_native(parser_build_cont
|
||||
p.end();
|
||||
}
|
||||
|
||||
common_peg_parser analyze_tools::build_func_parser(common_chat_peg_builder & p, const std::string & name,
|
||||
const common_peg_parser & call_id_section, bool have_call_id,
|
||||
const common_peg_parser & args,
|
||||
std::optional<common_peg_parser> atomic_peek) const {
|
||||
auto open = p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix);
|
||||
bool matched_atomic = false;
|
||||
common_peg_parser func_parser = p.eps();
|
||||
|
||||
if (!function.name_suffix.empty()) {
|
||||
func_parser = open + call_id_section + p.space() + args;
|
||||
matched_atomic = true;
|
||||
} else if (have_call_id) {
|
||||
func_parser = p.atomic(open + call_id_section) + p.space() + args;
|
||||
matched_atomic = true;
|
||||
} else if (atomic_peek.has_value()) {
|
||||
func_parser = p.atomic(open + call_id_section + p.space() + *atomic_peek) + args;
|
||||
matched_atomic = true;
|
||||
} else {
|
||||
func_parser = open + call_id_section + p.space() + args;
|
||||
}
|
||||
|
||||
if (!function.close.empty()) {
|
||||
func_parser = func_parser + p.space() + p.tool_close(p.literal(function.close));
|
||||
} else if (!format.per_call_end.empty()) {
|
||||
// When there's no func_close but there is a per_call_end marker, use peek() to ensure
|
||||
// we only emit tool_close when we can actually see the closing marker. This prevents
|
||||
// premature closing during partial parsing when we've seen e.g. "</" which could be
|
||||
// either "</tool_call>" (end) or "<arg_key>" prefix that failed to match.
|
||||
func_parser = func_parser + p.tool_close(p.peek(p.literal(format.per_call_end)));
|
||||
} else {
|
||||
func_parser = func_parser + p.tool_close(p.space()); // force this to process tool closing callbacks in mapper
|
||||
}
|
||||
if (!matched_atomic) {
|
||||
func_parser = p.atomic(func_parser);
|
||||
}
|
||||
return func_parser;
|
||||
}
|
||||
|
||||
common_peg_parser analyze_tools::build_tool_parser_tag_json(parser_build_context & ctx) const {
|
||||
auto & p = ctx.p;
|
||||
const auto & inputs = ctx.inputs;
|
||||
@@ -221,20 +264,30 @@ common_peg_parser analyze_tools::build_tool_parser_tag_json(parser_build_context
|
||||
foreach_function(inputs.tools, [&](const json & tool) {
|
||||
const auto & func = tool.at("function");
|
||||
std::string name = func.at("name");
|
||||
const auto & schema = func.at("parameters");
|
||||
const auto & schema = func.contains("parameters") ? func.at("parameters") : json::object();
|
||||
|
||||
// Build call_id parser based on position (if supported)
|
||||
bool have_call_id = false;
|
||||
common_peg_parser call_id_section = p.eps();
|
||||
if (call_id.pos == call_id_position::BETWEEN_FUNC_AND_ARGS && !call_id.prefix.empty() &&
|
||||
!call_id.suffix.empty()) {
|
||||
call_id_section = p.optional(call_id.prefix + p.tool_id(p.until(call_id.suffix))) + call_id.suffix;
|
||||
(!call_id.suffix.empty() || !arguments.start.empty())) {
|
||||
if (!call_id.suffix.empty()) {
|
||||
call_id_section = p.optional(call_id.prefix + p.tool_id(p.until(call_id.suffix))) + call_id.suffix;
|
||||
} else {
|
||||
call_id_section = p.optional(call_id.prefix + p.tool_id(p.until(arguments.start)));
|
||||
}
|
||||
have_call_id = true;
|
||||
}
|
||||
auto args_parser = p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema));
|
||||
if (!arguments.start.empty()) {
|
||||
args_parser = p.literal(arguments.start) + args_parser;
|
||||
}
|
||||
if (!arguments.end.empty()) {
|
||||
args_parser = args_parser + p.literal(arguments.end);
|
||||
}
|
||||
|
||||
auto func_parser = p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
|
||||
call_id_section + p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema));
|
||||
if (!function.close.empty()) {
|
||||
func_parser = func_parser + function.close;
|
||||
}
|
||||
auto atomic_peek = !arguments.start.empty() ? std::optional(p.peek(p.literal(arguments.start))) : std::nullopt;
|
||||
auto func_parser = build_func_parser(p, name, call_id_section, have_call_id, args_parser, atomic_peek);
|
||||
tool_choice |= p.rule("tool-" + name, func_parser);
|
||||
});
|
||||
|
||||
@@ -282,19 +335,11 @@ common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_conte
|
||||
common_peg_parser tool_choice = p.choice();
|
||||
|
||||
foreach_function(inputs.tools, [&](const json & tool) {
|
||||
const auto & func = tool.at("function");
|
||||
std::string name = func.at("name");
|
||||
const auto & params = func.at("parameters");
|
||||
|
||||
if (!params.contains("properties") || !params.at("properties").is_object()) {
|
||||
return;
|
||||
}
|
||||
|
||||
const auto & properties = params.at("properties");
|
||||
const auto & func = tool.at("function");
|
||||
std::string name = func.at("name");
|
||||
const auto & params = func.contains("parameters") ? func.at("parameters") : json::object();
|
||||
const auto & properties = params.contains("properties") ? params.at("properties") : json::object();
|
||||
std::set<std::string> required;
|
||||
if (params.contains("required") && params.at("required").is_array()) {
|
||||
params.at("required").get_to(required);
|
||||
}
|
||||
|
||||
// Build parser for each argument, separating required and optional
|
||||
std::vector<common_peg_parser> required_parsers;
|
||||
@@ -302,26 +347,49 @@ common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_conte
|
||||
for (const auto & [param_name, param_schema] : properties.items()) {
|
||||
bool is_required = required.find(param_name) != required.end();
|
||||
std::string type = "object";
|
||||
auto type_obj = param_schema.contains("type") ? param_schema.at("type") : json::object();
|
||||
if (type_obj.is_string()) {
|
||||
type_obj.get_to(type);
|
||||
} else if (type_obj.is_object()) {
|
||||
if (type_obj.contains("type") && type_obj.at("type").is_string()) {
|
||||
type_obj.at("type").get_to(type);
|
||||
if (param_schema.contains("type")) {
|
||||
const auto & type_obj = param_schema.at("type");
|
||||
if (type_obj.is_string()) {
|
||||
type_obj.get_to(type);
|
||||
} else if (type_obj.is_array()) {
|
||||
// Handle nullable types like ["string", "null"]
|
||||
for (const auto & t : type_obj) {
|
||||
if (t.is_string() && t.get<std::string>() != "null") {
|
||||
type = t.get<std::string>();
|
||||
break;
|
||||
}
|
||||
}
|
||||
} else if (type_obj.is_object()) {
|
||||
if (type_obj.contains("type") && type_obj.at("type").is_string()) {
|
||||
type_obj.at("type").get_to(type);
|
||||
}
|
||||
}
|
||||
}
|
||||
// Infer string type from enum values when type is unspecified
|
||||
if (type == "object" && param_schema.contains("enum")) {
|
||||
const auto & enum_vals = param_schema.at("enum");
|
||||
if (enum_vals.is_array()) {
|
||||
for (const auto & v : enum_vals) {
|
||||
if (v.is_string()) {
|
||||
type = "string";
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
auto arg = p.tool_arg(
|
||||
p.tool_arg_open(arguments.name_prefix + p.tool_arg_name(p.literal(param_name)) +
|
||||
arguments.name_suffix) +
|
||||
arguments.value_prefix +
|
||||
(type == "string" ? p.tool_arg_string_value(p.schema(p.until(arguments.value_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()) +
|
||||
p.tool_arg_close(p.literal(arguments.value_suffix)));
|
||||
auto arg =
|
||||
p.tool_arg(p.tool_arg_open(arguments.name_prefix + p.tool_arg_name(p.literal(param_name)) +
|
||||
arguments.name_suffix) +
|
||||
arguments.value_prefix +
|
||||
(type == "string" ?
|
||||
p.tool_arg_string_value(p.schema(p.until(arguments.value_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()) +
|
||||
p.tool_arg_close(p.literal(arguments.value_suffix)));
|
||||
|
||||
auto named_arg = p.rule("tool-" + name + "-arg-" + param_name, arg);
|
||||
if (is_required) {
|
||||
@@ -349,52 +417,31 @@ common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_conte
|
||||
args_seq = args_seq + p.repeat(p.space() + any_opt, 0, (int) optional_parsers.size());
|
||||
}
|
||||
|
||||
if (!arguments.start.empty()) {
|
||||
args_seq = p.literal(arguments.start) + args_seq;
|
||||
}
|
||||
if (!arguments.end.empty()) {
|
||||
args_seq = args_seq + p.literal(arguments.end);
|
||||
}
|
||||
|
||||
// Build call_id parser based on position (if supported)
|
||||
common_peg_parser call_id_section = p.eps();
|
||||
bool have_call_id = false;
|
||||
if (call_id.pos == call_id_position::BETWEEN_FUNC_AND_ARGS && !call_id.prefix.empty() &&
|
||||
!call_id.suffix.empty()) {
|
||||
(!call_id.suffix.empty() || !arguments.start.empty())) {
|
||||
have_call_id = true;
|
||||
call_id_section = p.optional(call_id.prefix + p.tool_id(p.until(call_id.suffix)) + call_id.suffix);
|
||||
}
|
||||
|
||||
bool matched_atomic = false;
|
||||
common_peg_parser func_parser = p.eps();
|
||||
if (!function.name_suffix.empty()) {
|
||||
func_parser = p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
|
||||
call_id_section + p.space() + args_seq;
|
||||
matched_atomic = true;
|
||||
} else if (have_call_id) {
|
||||
func_parser = p.atomic(p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
|
||||
call_id_section) + p.space() + args_seq;
|
||||
matched_atomic = true;
|
||||
} else if (!arguments.name_prefix.empty() && !required_parsers.empty()) {
|
||||
// Only peek for an arg tag when there are required args that must follow.
|
||||
// When all args are optional, the model may emit no arg tags at all (#20650).
|
||||
func_parser = p.atomic(p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
|
||||
call_id_section + p.space() + p.peek(p.literal(arguments.name_prefix))) + args_seq;
|
||||
matched_atomic = true;
|
||||
} else {
|
||||
func_parser = p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
|
||||
call_id_section + p.space() + args_seq;
|
||||
}
|
||||
|
||||
if (!function.close.empty()) {
|
||||
func_parser = func_parser + p.space() + p.tool_close(p.literal(function.close));
|
||||
} else if (!format.per_call_end.empty()) {
|
||||
// When there's no func_close but there is a per_call_end marker, use peek() to ensure
|
||||
// we only emit tool_close when we can actually see the closing marker. This prevents
|
||||
// premature closing during partial parsing when we've seen e.g. "</" which could be
|
||||
// either "</tool_call>" (end) or "<arg_key>" prefix that failed to match.
|
||||
func_parser = func_parser + p.tool_close(p.peek(p.literal(format.per_call_end)));
|
||||
} else {
|
||||
func_parser =
|
||||
func_parser + p.tool_close(p.space()); // force this to process tool closing callbacks in mapper
|
||||
}
|
||||
if (!matched_atomic) {
|
||||
func_parser = p.atomic(func_parser);
|
||||
if (!call_id.suffix.empty()) {
|
||||
call_id_section = p.optional(call_id.prefix + p.tool_id(p.until(call_id.suffix)) + call_id.suffix);
|
||||
} else {
|
||||
call_id_section = p.optional(call_id.prefix + p.tool_id(p.until(arguments.start)));
|
||||
}
|
||||
}
|
||||
|
||||
// Only peek for an arg tag when there are required args that must follow.
|
||||
// When all args are optional, the model may emit no arg tags at all (#20650).
|
||||
auto atomic_peek = (!arguments.name_prefix.empty() && !required_parsers.empty()) ?
|
||||
std::optional(p.peek(p.literal(arguments.name_prefix))) : std::nullopt;
|
||||
auto func_parser = build_func_parser(p, name, call_id_section, have_call_id, args_seq, atomic_peek);
|
||||
tool_choice |= p.rule("tool-" + name, func_parser);
|
||||
});
|
||||
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
#pragma once
|
||||
|
||||
#include "chat-auto-parser.h"
|
||||
#include "peg-parser.h"
|
||||
|
||||
#include <functional>
|
||||
#include <optional>
|
||||
#include <string>
|
||||
|
||||
@@ -4,6 +4,7 @@
|
||||
#include "common.h"
|
||||
#include "jinja/caps.h"
|
||||
#include "peg-parser.h"
|
||||
#include "nlohmann/json.hpp"
|
||||
|
||||
#include <chrono>
|
||||
#include <optional>
|
||||
@@ -212,12 +213,14 @@ struct tool_id_analysis {
|
||||
// ============================================================================
|
||||
|
||||
struct analyze_content;
|
||||
struct analyze_reasoning;
|
||||
|
||||
struct parser_build_context {
|
||||
common_chat_peg_builder & p;
|
||||
const generation_params & inputs;
|
||||
const generation_params & inputs;
|
||||
common_peg_parser reasoning_parser;
|
||||
bool extracting_reasoning = false;
|
||||
const analyze_reasoning * reasoning = nullptr;
|
||||
const analyze_content * content = nullptr;
|
||||
|
||||
parser_build_context(common_chat_peg_builder & p, const generation_params & inputs);
|
||||
@@ -350,6 +353,13 @@ struct analyze_tools : analyze_base {
|
||||
common_peg_parser build_tool_parser_json_native(parser_build_context & ctx) const;
|
||||
common_peg_parser build_tool_parser_tag_json(parser_build_context & ctx) const;
|
||||
common_peg_parser build_tool_parser_tag_tagged(parser_build_context & ctx) const;
|
||||
|
||||
// Shared helper: builds func_parser from open+call_id+args, handling atomic wrapping and close.
|
||||
// atomic_peek: if present, used as the peek expression in the third atomicity branch.
|
||||
common_peg_parser build_func_parser(common_chat_peg_builder & p, const std::string & name,
|
||||
const common_peg_parser & call_id_section, bool have_call_id,
|
||||
const common_peg_parser & args,
|
||||
std::optional<common_peg_parser> atomic_peek) const;
|
||||
};
|
||||
|
||||
// ============================================================================
|
||||
|
||||
@@ -25,6 +25,9 @@ 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 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";
|
||||
static const std::string CALL_ID_002 = "call00002";
|
||||
static const std::string CALL_ID_999 = "call99999";
|
||||
|
||||
static std::vector<std::function<void(const common_chat_template & tmpl, autoparser &)>> workarounds(
|
||||
{ // Old reasoning Qwen templates - they don't really display reasoning content, but we still want to
|
||||
@@ -103,6 +106,7 @@ static std::vector<std::function<void(const common_chat_template & tmpl, autopar
|
||||
analysis.tools.function.name_prefix = "<|tool▁sep|>";
|
||||
analysis.tools.format.per_call_end = "<|tool▁call▁end|>";
|
||||
analysis.tools.function.close = "```";
|
||||
LOG_DBG(ANSI_ORANGE "[Patch: DeepSeek-R1-Distill-Qwen]\n" ANSI_RESET);
|
||||
}
|
||||
}
|
||||
});
|
||||
@@ -130,7 +134,7 @@ static json user_msg = json{
|
||||
{ "content", USER_MSG }
|
||||
};
|
||||
|
||||
static json build_tool_call(const std::string & name, const json & args, const std::string & id = "call00001") {
|
||||
static json build_tool_call(const std::string & name, const json & args, const std::string & id = CALL_ID_001) {
|
||||
return json{
|
||||
{ "id", id },
|
||||
{ "type", "function" },
|
||||
@@ -138,17 +142,17 @@ static json build_tool_call(const std::string & name, const json & args, const s
|
||||
};
|
||||
}
|
||||
|
||||
static json first_tool_call_zero_args = build_tool_call(FUN_FIRST, json::object(), "call00001");
|
||||
static json first_tool_call_one_arg = build_tool_call(FUN_FIRST, {{ ARG_FIRST, "XXXX" }}, "call00001");
|
||||
static json first_tool_call_one_arg_other_val = build_tool_call(FUN_FIRST, {{ ARG_FIRST, "YYYY" }}, "call00001");
|
||||
static json first_tool_call_other_arg = build_tool_call(FUN_FIRST, {{ ARG_SECOND, "YYYY" }}, "call00001");
|
||||
static json first_tool_call_zero_args = build_tool_call(FUN_FIRST, json::object(), CALL_ID_001);
|
||||
static json first_tool_call_one_arg = build_tool_call(FUN_FIRST, {{ ARG_FIRST, "XXXX" }}, CALL_ID_001);
|
||||
static json first_tool_call_one_arg_other_val = build_tool_call(FUN_FIRST, {{ ARG_FIRST, "YYYY" }}, CALL_ID_001);
|
||||
static json first_tool_call_other_arg = build_tool_call(FUN_FIRST, {{ ARG_SECOND, "YYYY" }}, CALL_ID_001);
|
||||
|
||||
static json first_tool_call =
|
||||
build_tool_call(FUN_FIRST, json{{ ARG_FIRST, "XXXX" }, { ARG_SECOND, "YYYY" }}, "call00001");
|
||||
build_tool_call(FUN_FIRST, json{{ ARG_FIRST, "XXXX" }, { ARG_SECOND, "YYYY" }}, CALL_ID_001);
|
||||
static json second_tool_call =
|
||||
build_tool_call(FUN_SECOND, json{ { ARG_FIRST, "XXXX" }, { ARG_SECOND, "YYYY" }}, "call00002");
|
||||
build_tool_call(FUN_SECOND, json{ { ARG_FIRST, "XXXX" }, { ARG_SECOND, "YYYY" }}, CALL_ID_002);
|
||||
static json first_tool_call_alt_id =
|
||||
build_tool_call(FUN_FIRST, json{{ ARG_FIRST, "XXXX" }, { ARG_SECOND, "YYYY" }}, "call99999");
|
||||
build_tool_call(FUN_FIRST, json{{ ARG_FIRST, "XXXX" }, { ARG_SECOND, "YYYY" }}, CALL_ID_999);
|
||||
|
||||
template <typename T>
|
||||
static std::string mode_to_str(T mode) {
|
||||
@@ -187,6 +191,11 @@ void autoparser::analyze_template(const common_chat_template & tmpl) {
|
||||
LOG_DBG("func_name_prefix: '%s'\n", tools.function.name_prefix.c_str());
|
||||
LOG_DBG("func_name_suffix: '%s'\n", tools.function.name_suffix.c_str());
|
||||
LOG_DBG("func_close: '%s'\n", tools.function.close.c_str());
|
||||
LOG_DBG("call_id_prefix: '%s'\n", tools.call_id.prefix.c_str());
|
||||
LOG_DBG("call_id_suffix: '%s'\n", tools.call_id.suffix.c_str());
|
||||
LOG_DBG("call_id_pos: '%s'\n", mode_to_str(tools.call_id.pos).c_str());
|
||||
LOG_DBG("args_start: '%s'\n", tools.arguments.start.c_str());
|
||||
LOG_DBG("args_end: '%s'\n", tools.arguments.end.c_str());
|
||||
LOG_DBG("arg_name_prefix: '%s'\n", tools.arguments.name_prefix.c_str());
|
||||
LOG_DBG("arg_name_suffix: '%s'\n", tools.arguments.name_suffix.c_str());
|
||||
LOG_DBG("arg_value_prefix: '%s'\n", tools.arguments.value_prefix.c_str());
|
||||
@@ -287,7 +296,7 @@ void analyze_reasoning::compare_reasoning_presence() {
|
||||
return p.literal(reasoning_content) + p.space() + p.optional(p.tag("post", (p.marker() + p.space())) + p.rest());
|
||||
});
|
||||
auto parser_wrapped = build_tagged_peg_parser([&](common_peg_parser_builder &p) {
|
||||
return p.tag("pre", p.marker()) + p.space() + p.literal(reasoning_content) + p.space() + p.tag("post", (p.marker() + p.space())) + p.rest();
|
||||
return p.tag("pre", p.marker() + p.space()) + p.literal(reasoning_content) + p.space() + p.tag("post", (p.marker() + p.space())) + p.rest();
|
||||
});
|
||||
// try the more aggressive parse first, if it fails, fall back to the delimiter one
|
||||
auto result = parser_wrapped.parse_anywhere_and_extract(comparison->output_B);
|
||||
@@ -297,7 +306,7 @@ void analyze_reasoning::compare_reasoning_presence() {
|
||||
if (result.result.success()) {
|
||||
if (!result.tags["pre"].empty() && !result.tags["post"].empty()) {
|
||||
mode = reasoning_mode::TAG_BASED;
|
||||
start = trim_whitespace(result.tags["pre"]);
|
||||
start = trim_leading_whitespace(result.tags["pre"]);
|
||||
end = trim_trailing_whitespace(result.tags["post"]);
|
||||
} else if (!result.tags["post"].empty()) {
|
||||
mode = reasoning_mode::TAG_BASED;
|
||||
@@ -333,7 +342,7 @@ void analyze_reasoning::compare_thinking_enabled() {
|
||||
if (left_trimmed.empty() && !diff.right.empty()) {
|
||||
if (!right_trimmed.empty() && string_ends_with(comparison->output_B, right_trimmed)) {
|
||||
if (start.empty()) {
|
||||
start = right_trimmed;
|
||||
start = trim_leading_whitespace(diff.right);
|
||||
mode = reasoning_mode::TAG_BASED;
|
||||
}
|
||||
}
|
||||
@@ -344,7 +353,7 @@ void analyze_reasoning::compare_thinking_enabled() {
|
||||
if (seg.size() >= 2 && seg[seg.size() - 1].value == left_trimmed && seg[seg.size() - 2].type == segment_type::MARKER) {
|
||||
start = seg[seg.size() - 2].value;
|
||||
}
|
||||
end = left_trimmed;
|
||||
end = trim_trailing_whitespace(diff.left);
|
||||
mode = reasoning_mode::TAG_BASED;
|
||||
}
|
||||
}
|
||||
@@ -363,15 +372,23 @@ void analyze_reasoning::compare_thinking_enabled() {
|
||||
size_t len = std::min(base.size(), anchor_len);
|
||||
std::string anchor = base.substr(base.size() - len);
|
||||
auto pos = extended.rfind(anchor);
|
||||
if (pos == std::string::npos || pos + len >= extended.size()) continue;
|
||||
if (pos == std::string::npos || pos + len >= extended.size()) {
|
||||
continue;
|
||||
}
|
||||
|
||||
std::string extra = trim_whitespace(extended.substr(pos + len));
|
||||
if (extra.empty()) continue;
|
||||
if (extra.empty()) {
|
||||
continue;
|
||||
}
|
||||
|
||||
auto seg = prune_whitespace_segments(segmentize_markers(extra));
|
||||
if (seg.size() == 2 && seg[0].type == segment_type::MARKER && seg[1].type == segment_type::MARKER) {
|
||||
if (start.empty()) start = seg[0].value;
|
||||
if (end.empty()) end = seg[1].value;
|
||||
if (start.empty()) {
|
||||
start = seg[0].value;
|
||||
}
|
||||
if (end.empty()) {
|
||||
end = seg[1].value;
|
||||
}
|
||||
mode = reasoning_mode::TAG_BASED;
|
||||
break;
|
||||
}
|
||||
@@ -423,7 +440,7 @@ void analyze_reasoning::compare_reasoning_scope() {
|
||||
LOG_DBG(ANSI_ORANGE "%s: Detected TOOLS_ONLY reasoning mode\n" ANSI_RESET, __func__);
|
||||
|
||||
auto parser_wrapped = build_tagged_peg_parser([&](common_peg_parser_builder &p) {
|
||||
return p.tag("pre", p.marker()) + p.space() + p.literal(reasoning_content) + p.space() + p.tag("post", (p.marker() + p.space()));
|
||||
return p.tag("pre", p.marker() + p.space()) + p.literal(reasoning_content) + p.space() + p.tag("post", (p.marker() + p.space()));
|
||||
});
|
||||
auto result = parser_wrapped.parse_anywhere_and_extract(comparison->output_B);
|
||||
if (result.result.success()) {
|
||||
@@ -516,7 +533,7 @@ analyze_content::analyze_content(const common_chat_template & tmpl, const analyz
|
||||
// Take the more promising diff
|
||||
std::string pure_content = rdiff.length() > diff_tools.left.length() ? rdiff : diff_tools.left;
|
||||
auto parser_wrapped = build_tagged_peg_parser([&](common_peg_parser_builder &p) {
|
||||
return p.tag("pre", p.marker()) + p.space() + p.literal(response) + p.space() + p.tag("post", (p.marker() + p.space())) + p.rest();
|
||||
return p.tag("pre", p.marker() + p.space()) + p.literal(response) + p.space() + p.tag("post", (p.marker() + p.space())) + p.rest();
|
||||
});
|
||||
auto result = parser_wrapped.parse_anywhere_and_extract(pure_content);
|
||||
start = result.tags["pre"];
|
||||
@@ -547,12 +564,15 @@ analyze_tools::analyze_tools(const common_chat_template & tmpl,
|
||||
if (caps.supports_parallel_tool_calls) {
|
||||
check_per_call_markers();
|
||||
}
|
||||
LOG_DBG(ANSI_ORANGE "Phase 3a: Function call analysis\n" ANSI_RESET);
|
||||
extract_function_markers();
|
||||
LOG_DBG(ANSI_ORANGE "Phase 3b: Argument analysis\n" ANSI_RESET);
|
||||
if (format.mode == tool_format::TAG_WITH_TAGGED) {
|
||||
analyze_arguments();
|
||||
}
|
||||
extract_argument_separator();
|
||||
extract_args_markers();
|
||||
LOG_DBG(ANSI_ORANGE "Phase 3c: Call id analysis\n" ANSI_RESET);
|
||||
extract_call_id_markers();
|
||||
}
|
||||
}
|
||||
@@ -943,8 +963,6 @@ void analyze_tools::extract_function_markers() {
|
||||
}
|
||||
|
||||
void analyze_tools::analyze_arguments() {
|
||||
LOG_DBG(ANSI_ORANGE "Phase 4: Argument analysis\n" ANSI_RESET);
|
||||
|
||||
extract_argument_name_markers();
|
||||
extract_argument_value_markers();
|
||||
}
|
||||
@@ -1153,7 +1171,7 @@ void analyze_tools::extract_args_markers() {
|
||||
|
||||
const auto & diff = comparison->diff;
|
||||
|
||||
if (format.mode != tool_format::JSON_NATIVE) {
|
||||
if (format.mode == tool_format::JSON_NATIVE) {
|
||||
std::string prefix_marker = !format.section_start.empty() ? format.section_start : format.per_call_start;
|
||||
std::string suffix_marker = !format.section_end.empty() ? format.section_end : format.per_call_end;
|
||||
// these might happen earlier in the tools section as an example or somewhere else, so we need to find the closest ones
|
||||
@@ -1175,6 +1193,10 @@ void analyze_tools::extract_args_markers() {
|
||||
if (find_fun != std::string::npos) {
|
||||
args_start = args_start.substr(find_fun + FUN_FIRST.size(), args_start.size() - find_fun - FUN_FIRST.size());
|
||||
}
|
||||
size_t find_call_id = args_start.find(CALL_ID_001);
|
||||
if (find_call_id != std::string::npos) {
|
||||
args_start = args_start.substr(find_call_id + CALL_ID_001.size(), args_start.size() - find_call_id - CALL_ID_001.size());
|
||||
}
|
||||
arguments.start = args_start;
|
||||
arguments.end = args_end;
|
||||
}
|
||||
@@ -1214,8 +1236,8 @@ void analyze_tools::extract_call_id_markers() {
|
||||
return;
|
||||
}
|
||||
|
||||
std::string id_value_1 = "call00001";
|
||||
std::string id_value_2 = "call99999";
|
||||
std::string id_value_1 = CALL_ID_001;
|
||||
std::string id_value_2 = CALL_ID_999;
|
||||
|
||||
size_t common_id_prefix_len = 0;
|
||||
for (size_t i = 0; i < std::min(id_value_1.length(), id_value_2.length()); i++) {
|
||||
@@ -1314,6 +1336,14 @@ void analyze_tools::extract_call_id_markers() {
|
||||
call_id.suffix = find_first_marker(before_func);
|
||||
}
|
||||
|
||||
if (call_id.prefix == arguments.end) {
|
||||
call_id.prefix = "";
|
||||
}
|
||||
|
||||
if (call_id.suffix == arguments.start) {
|
||||
call_id.suffix = "";
|
||||
}
|
||||
|
||||
// When call_id is detected, per_call_end may have been incorrectly set to include
|
||||
// the call_id_suffix and sample args. Clear it if it starts with call_id_suffix.
|
||||
if (call_id.pos != call_id_position::NONE && !call_id.suffix.empty() &&
|
||||
|
||||
@@ -214,6 +214,10 @@ std::string & common_chat_peg_mapper::args_target() {
|
||||
return (current_tool && !current_tool->name.empty()) ? current_tool->arguments : args_buffer;
|
||||
}
|
||||
|
||||
std::string common_chat_peg_mapper::normalize_container_value(const std::string & input) {
|
||||
return normalize_quotes_to_json(input);
|
||||
}
|
||||
|
||||
void common_chat_peg_mapper::from_ast(const common_peg_ast_arena & arena,
|
||||
const common_peg_parse_result & parse_result_arg) {
|
||||
arena.visit(parse_result_arg, [this](const common_peg_ast_node & node) { map(node); });
|
||||
@@ -352,7 +356,7 @@ void common_chat_peg_mapper::map(const common_peg_ast_node & node) {
|
||||
// For potential containers, normalize Python-style single quotes to JSON double quotes
|
||||
bool is_potential_container = value_content[0] == '[' || value_content[0] == '{';
|
||||
if (is_potential_container) {
|
||||
value_content = normalize_quotes_to_json(value_content);
|
||||
value_content = normalize_container_value(value_content);
|
||||
}
|
||||
|
||||
// Try to parse as JSON value (number, bool, null, object, array)
|
||||
@@ -861,3 +865,143 @@ common_peg_parser common_chat_peg_builder::standard_json_tools(
|
||||
|
||||
return force_tool_calls ? section : optional(section);
|
||||
}
|
||||
|
||||
void common_chat_peg_gemma4_mapper::from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result) {
|
||||
for (const auto & node : result.nodes) {
|
||||
visit(arena, node);
|
||||
}
|
||||
}
|
||||
|
||||
static std::string gemma4_to_json(const common_peg_ast_arena & arena, common_peg_ast_id id) {
|
||||
const auto & node = arena.get(id);
|
||||
|
||||
if (node.text.empty()) {
|
||||
return "";
|
||||
}
|
||||
|
||||
if (node.rule == "gemma4-number" || node.rule == "gemma4-bool" || node.rule == "gemma4-null") {
|
||||
return std::string(node.text);
|
||||
}
|
||||
|
||||
if (node.rule == "gemma4-string-content") {
|
||||
return escape_json_string_inner(std::string(node.text));
|
||||
}
|
||||
|
||||
if (node.rule == "gemma4-string") {
|
||||
std::string result = "\"";
|
||||
if (!node.children.empty()) {
|
||||
result += gemma4_to_json(arena, node.children[0]);
|
||||
if (!node.is_partial) {
|
||||
result += "\"";
|
||||
}
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
if (node.rule == "gemma4-array") {
|
||||
std::string result = "[";
|
||||
|
||||
bool add_comma = false;
|
||||
for (auto child_id : node.children) {
|
||||
if (add_comma) {
|
||||
result += ',';
|
||||
}
|
||||
add_comma = true;
|
||||
result += gemma4_to_json(arena, child_id);
|
||||
}
|
||||
|
||||
if (!node.is_partial) {
|
||||
result += ']';
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
if (node.rule == "gemma4-dict-key-name") {
|
||||
return std::string(node.text);
|
||||
}
|
||||
|
||||
if (node.rule == "gemma4-dict-key") {
|
||||
std::string result = "\"";
|
||||
if (!node.children.empty()) {
|
||||
result += escape_json_string_inner(gemma4_to_json(arena, node.children[0]));
|
||||
}
|
||||
if (!node.is_partial) {
|
||||
result += "\":";
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
if (node.rule == "gemma4-dict-kv") {
|
||||
std::string result;
|
||||
for (auto child_id : node.children) {
|
||||
result += gemma4_to_json(arena, child_id);
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
if (node.rule == "gemma4-dict") {
|
||||
std::string result = "{";
|
||||
|
||||
bool add_comma = false;
|
||||
for (auto child_id : node.children) {
|
||||
if (add_comma) {
|
||||
result += ',';
|
||||
}
|
||||
add_comma = true;
|
||||
result += gemma4_to_json(arena, child_id);
|
||||
}
|
||||
|
||||
if (!node.is_partial) {
|
||||
result += '}';
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
if (node.rule == "gemma4-value") {
|
||||
if (!node.children.empty()) {
|
||||
return gemma4_to_json(arena, node.children[0]);
|
||||
}
|
||||
return "";
|
||||
}
|
||||
|
||||
return "";
|
||||
}
|
||||
|
||||
void common_chat_peg_gemma4_mapper::visit(const common_peg_ast_arena & arena, common_peg_ast_id id) {
|
||||
const auto & node = arena.get(id);
|
||||
|
||||
if (node.tag == "reasoning") {
|
||||
result.reasoning_content += std::string(node.text);
|
||||
return;
|
||||
}
|
||||
|
||||
if (node.tag == "content") {
|
||||
result.content += std::string(node.text);
|
||||
return;
|
||||
}
|
||||
|
||||
if (node.tag == "tool") {
|
||||
auto name_id = arena.find_by_tag(node, "tool-name");
|
||||
auto args_id = arena.find_by_tag(node, "tool-args");
|
||||
|
||||
if (name_id != COMMON_PEG_INVALID_AST_ID && args_id != COMMON_PEG_INVALID_AST_ID) {
|
||||
const auto & name_node = arena.get(name_id);
|
||||
const auto & args_node = arena.get(args_id);
|
||||
|
||||
if (!name_node.is_partial) {
|
||||
common_chat_tool_call call;
|
||||
call.name = std::string(name_node.text);
|
||||
if (!args_node.children.empty()) {
|
||||
call.arguments = gemma4_to_json(arena, args_node.children[0]);
|
||||
}
|
||||
result.tool_calls.push_back(call);
|
||||
}
|
||||
}
|
||||
|
||||
return;
|
||||
}
|
||||
|
||||
for (auto child_id : node.children) {
|
||||
visit(arena, child_id);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -17,7 +17,9 @@ class common_chat_peg_mapper {
|
||||
|
||||
virtual void from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result);
|
||||
virtual void map(const common_peg_ast_node & node);
|
||||
private:
|
||||
protected:
|
||||
virtual std::string normalize_container_value(const std::string & input);
|
||||
private:
|
||||
// Tool call handling state
|
||||
std::optional<common_chat_tool_call> pending_tool_call; // Tool call waiting for name
|
||||
common_chat_tool_call * current_tool = nullptr;
|
||||
@@ -30,6 +32,14 @@ class common_chat_peg_mapper {
|
||||
std::string & args_target();
|
||||
};
|
||||
|
||||
class common_chat_peg_gemma4_mapper : public common_chat_peg_mapper {
|
||||
public:
|
||||
common_chat_peg_gemma4_mapper(common_chat_msg & msg) : common_chat_peg_mapper(msg) {}
|
||||
virtual void from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result);
|
||||
private:
|
||||
void visit(const common_peg_ast_arena & arena, common_peg_ast_id id);
|
||||
};
|
||||
|
||||
struct content_structure;
|
||||
struct tool_call_structure;
|
||||
|
||||
|
||||
467
common/chat.cpp
467
common/chat.cpp
@@ -13,6 +13,8 @@
|
||||
#include "jinja/caps.h"
|
||||
#include "peg-parser.h"
|
||||
|
||||
#include "nlohmann/json.hpp"
|
||||
|
||||
#include <cstdio>
|
||||
#include <cstdlib>
|
||||
#include <ctime>
|
||||
@@ -221,7 +223,7 @@ using chat_template_caps = jinja::caps;
|
||||
struct common_chat_templates {
|
||||
bool add_bos;
|
||||
bool add_eos;
|
||||
bool has_explicit_template; // Model had builtin template or template overridde was specified.
|
||||
bool has_explicit_template; // Model had builtin template or template overridden was specified.
|
||||
std::unique_ptr<common_chat_template> template_default; // always set (defaults to chatml)
|
||||
std::unique_ptr<common_chat_template> template_tool_use;
|
||||
};
|
||||
@@ -694,6 +696,8 @@ const char * common_chat_format_name(common_chat_format format) {
|
||||
return "peg-simple";
|
||||
case COMMON_CHAT_FORMAT_PEG_NATIVE:
|
||||
return "peg-native";
|
||||
case COMMON_CHAT_FORMAT_PEG_GEMMA4:
|
||||
return "peg-gemma4";
|
||||
default:
|
||||
throw std::runtime_error("Unknown chat format");
|
||||
}
|
||||
@@ -760,12 +764,12 @@ static void foreach_parameter(const json &
|
||||
}
|
||||
}
|
||||
|
||||
std::string common_chat_template_direct_apply(
|
||||
static std::string common_chat_template_direct_apply_impl(
|
||||
const common_chat_template & tmpl,
|
||||
const autoparser::generation_params & inputs,
|
||||
const std::optional<json> & messages_override,
|
||||
const std::optional<json> & tools_override,
|
||||
const std::optional<json> & additional_context) {
|
||||
const std::optional<json> & messages_override = std::nullopt,
|
||||
const std::optional<json> & tools_override = std::nullopt,
|
||||
const std::optional<json> & additional_context = std::nullopt) {
|
||||
jinja::context ctx(tmpl.source());
|
||||
|
||||
nlohmann::ordered_json inp = nlohmann::ordered_json{
|
||||
@@ -812,6 +816,12 @@ std::string common_chat_template_direct_apply(
|
||||
return result;
|
||||
}
|
||||
|
||||
std::string common_chat_template_direct_apply(
|
||||
const common_chat_template & tmpl,
|
||||
const autoparser::generation_params & inputs) {
|
||||
return common_chat_template_direct_apply_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;
|
||||
@@ -862,7 +872,7 @@ static common_chat_params common_chat_params_init_ministral_3(const common_chat_
|
||||
data.supports_thinking = true;
|
||||
data.thinking_start_tag = "[THINK]";
|
||||
data.thinking_end_tag = "[/THINK]";
|
||||
data.prompt = common_chat_template_direct_apply(tmpl, inputs, /* messages_override = */ adjusted_messages);
|
||||
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs, /* messages_override = */ adjusted_messages);
|
||||
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
|
||||
data.preserved_tokens = {
|
||||
"[THINK]",
|
||||
@@ -945,7 +955,7 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
|
||||
adjusted_messages.push_back(msg);
|
||||
}
|
||||
|
||||
auto prompt = common_chat_template_direct_apply(tmpl, inputs, /* messages_override= */ adjusted_messages);
|
||||
auto prompt = common_chat_template_direct_apply_impl(tmpl, inputs, /* messages_override= */ adjusted_messages);
|
||||
|
||||
// Check if we need to replace the return token with end token during
|
||||
// inference and without generation prompt. For more details see:
|
||||
@@ -971,6 +981,7 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
|
||||
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.literal("<|start|>assistant"));
|
||||
@@ -979,13 +990,27 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
|
||||
auto channel = p.literal("<|channel|>") + (p.literal("commentary") | p.literal("analysis"));
|
||||
auto constrain_type = p.chars("[A-Za-z0-9_-]", 1, -1);
|
||||
|
||||
auto analysis = p.rule("analysis", p.literal("<|channel|>analysis<|message|>") + p.reasoning(content) + end);
|
||||
// Occasionally, gpt-oss-20b will prefix channels with this commentary
|
||||
auto stray_commentary = p.optional(p.literal("<|channel|>commentary") + p.optional(p.literal(" to=assistant")));
|
||||
auto start_analysis = stray_commentary + p.literal("<|channel|>analysis<|message|>");
|
||||
|
||||
if (extract_reasoning) {
|
||||
p.rule("analysis", start_analysis + p.reasoning(content) + end);
|
||||
} else {
|
||||
p.rule("analysis", p.content(start_analysis + content + end));
|
||||
}
|
||||
|
||||
auto analysis = p.ref("analysis");
|
||||
auto preamble = p.rule("preamble", p.literal("<|channel|>commentary<|message|>") + p.content(content) + end);
|
||||
auto final_msg = p.rule("final", p.literal("<|channel|>final<|message|>") + p.content(content));
|
||||
auto final_msg = p.rule("final", stray_commentary + p.literal("<|channel|>final<|message|>") + p.content(content));
|
||||
|
||||
// Consume any unsolicited tool calls, e.g. builtin functions
|
||||
auto unsolicited = p.rule("unsolicited", p.atomic(p.optional(channel) + p.literal(" to=") + content + end));
|
||||
|
||||
auto any = p.rule("any", preamble | analysis);
|
||||
|
||||
if (has_response_format) {
|
||||
auto constraint = p.optional(p.space() + p.literal("<|constrain|>") + constrain_type);
|
||||
auto constraint = p.optional(p.space() + p.optional(p.literal("<|constrain|>")) + constrain_type);
|
||||
auto response_format = p.rule("response-format",
|
||||
p.literal("<|channel|>final") + constraint + p.literal("<|message|>") +
|
||||
p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema)));
|
||||
@@ -1002,7 +1027,7 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
|
||||
const auto & params = function.at("parameters");
|
||||
|
||||
auto func_name = p.literal(" to=functions.") + p.tool_name(p.literal(name));
|
||||
auto constraint = p.optional(p.space() + p.literal("<|constrain|>") + constrain_type);
|
||||
auto constraint = p.optional(p.space() + p.optional(p.literal("<|constrain|>")) + constrain_type);
|
||||
auto args = p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", params));
|
||||
|
||||
// recipient in role header
|
||||
@@ -1025,7 +1050,7 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
|
||||
return p.zero_or_more(start + any) + start + (tool_call | final_msg);
|
||||
}
|
||||
|
||||
return p.zero_or_more(start + any) + start + final_msg;
|
||||
return p.zero_or_more(start + any) + start + (final_msg | unsolicited);
|
||||
});
|
||||
|
||||
data.parser = parser.save();
|
||||
@@ -1043,6 +1068,7 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
|
||||
|
||||
data.grammar_triggers = {
|
||||
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN, "^\\s+to$" },
|
||||
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN, "^<\\|channel\\|>(?:commentary|analysis)\\s+to=functions$" },
|
||||
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN, "<\\|start\\|>assistant(\\s+to)" },
|
||||
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN, "<\\|start\\|>assistant(<\\|channel\\|>(?:commentary|analysis)\\s+to)" }
|
||||
};
|
||||
@@ -1051,12 +1077,137 @@ static common_chat_params common_chat_params_init_gpt_oss(const common_chat_temp
|
||||
return data;
|
||||
}
|
||||
|
||||
static common_chat_params common_chat_params_init_gemma4(const common_chat_template & tmpl,
|
||||
const autoparser::generation_params & inputs) {
|
||||
common_chat_params data;
|
||||
|
||||
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
|
||||
data.format = COMMON_CHAT_FORMAT_PEG_GEMMA4;
|
||||
data.supports_thinking = true;
|
||||
|
||||
data.preserved_tokens = {
|
||||
"<|channel>",
|
||||
"<channel|>",
|
||||
"<|tool_call>",
|
||||
"<tool_call|>",
|
||||
"<|turn>",
|
||||
};
|
||||
|
||||
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.prefix(inputs.generation_prompt, "<|channel>"));
|
||||
|
||||
if (extract_reasoning) {
|
||||
p.rule("thought", p.literal("<|channel>thought\n") + p.reasoning(p.until("<channel|>")) + p.literal("<channel|>"));
|
||||
} else {
|
||||
p.rule("thought", p.content(p.literal("<|channel>thought\n") + p.until("<channel|>") + p.literal("<channel|>")));
|
||||
}
|
||||
|
||||
auto thought = (p.peek(p.literal("<|channel>")) + p.ref("thought")) | p.negate(p.literal("<|channel>"));
|
||||
|
||||
if (has_response_format) {
|
||||
auto response_format = p.literal("```json") <<
|
||||
p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema)) <<
|
||||
p.literal("```");
|
||||
return start + p.optional(thought) + response_format;
|
||||
}
|
||||
|
||||
if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) {
|
||||
// Gemma4 tool calling syntax
|
||||
// Rules should match traversal logic in gemma4_to_json()
|
||||
p.rule("gemma4-string-content", p.until("<|\"|>"));
|
||||
p.rule("gemma4-string", p.literal("<|\"|>") + p.ref("gemma4-string-content") + p.literal("<|\"|>"));
|
||||
p.rule("gemma4-bool", p.json_bool());
|
||||
p.rule("gemma4-null", p.json_null());
|
||||
p.rule("gemma4-number", p.json_number());
|
||||
p.rule("gemma4-dict-key", p.rule("gemma4-dict-key-name", p.until(":")) + p.literal(":"));
|
||||
p.rule("gemma4-dict-kv", p.ref("gemma4-dict-key") + p.space() + p.ref("gemma4-value"));
|
||||
p.rule("gemma4-dict", [&]() {
|
||||
auto ws = p.space();
|
||||
auto member = p.ref("gemma4-dict-kv");
|
||||
auto members = p.sequence({member, p.zero_or_more(p.sequence({p.literal(","), ws, member}))});
|
||||
return p.sequence({
|
||||
p.literal("{"), ws,
|
||||
p.choice({p.literal("}"), p.sequence({members, ws, p.literal("}")})})
|
||||
});
|
||||
});
|
||||
p.rule("gemma4-array", [&]() {
|
||||
auto ws = p.space();
|
||||
auto value = p.ref("gemma4-value");
|
||||
auto elements = p.sequence({value, p.zero_or_more(p.sequence({p.literal(","), ws, value}))});
|
||||
return p.sequence({
|
||||
p.literal("["), ws,
|
||||
p.choice({p.literal("]"), p.sequence({elements, ws, p.literal("]")})})
|
||||
});
|
||||
});
|
||||
p.rule("gemma4-value", [&]() {
|
||||
return p.choice({
|
||||
p.ref("gemma4-string"), p.ref("gemma4-dict"), p.ref("gemma4-array"),
|
||||
p.ref("gemma4-number"), p.ref("gemma4-bool"), p.ref("gemma4-null")
|
||||
});
|
||||
});
|
||||
|
||||
auto tool_choice = p.choice();
|
||||
|
||||
foreach_function(inputs.tools, [&](const json & tool) {
|
||||
const auto & function = tool.at("function");
|
||||
std::string name = function.at("name");
|
||||
// TODO @aldehir : need to extend json-schema-to-grammar to produce more than JSON rules
|
||||
// const auto & params = function.at("parameters");
|
||||
|
||||
tool_choice |= p.rule("tool-" + name, p.tool(p.sequence({
|
||||
p.tool_open(p.tool_name(p.literal(name)) + p.peek(p.literal("{"))),
|
||||
p.tool_args(p.ref("gemma4-dict")),
|
||||
})));
|
||||
});
|
||||
|
||||
auto tool_call = p.trigger_rule("tool-call", p.repeat(
|
||||
"<|tool_call>call:" + tool_choice + "<tool_call|>",
|
||||
/* min = */ inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? 1 : 0,
|
||||
/* max = */ inputs.parallel_tool_calls ? -1 : 1
|
||||
));
|
||||
|
||||
auto content = p.rule("content", p.content(p.until_one_of({"<|channel>", "<|tool_call>"})));
|
||||
auto message = p.rule("message", thought + content);
|
||||
return start + p.zero_or_more(message) + tool_call;
|
||||
}
|
||||
|
||||
auto content = p.rule("content", p.content(p.until("<|channel>")));
|
||||
auto message = p.rule("message", thought + content);
|
||||
return start + p.one_or_more(message);
|
||||
});
|
||||
|
||||
data.parser = parser.save();
|
||||
|
||||
if (include_grammar) {
|
||||
data.grammar_lazy = !(has_response_format || (has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED));
|
||||
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
|
||||
foreach_function(inputs.tools, [&](const json & tool) {
|
||||
const auto & function = tool.at("function");
|
||||
auto schema = function.at("parameters");
|
||||
builder.resolve_refs(schema);
|
||||
});
|
||||
parser.build_grammar(builder, data.grammar_lazy);
|
||||
});
|
||||
|
||||
data.grammar_triggers = {
|
||||
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "<|tool_call>" },
|
||||
};
|
||||
}
|
||||
|
||||
return data;
|
||||
}
|
||||
|
||||
// Functionary v3.2 - uses recipient-based format: >>>recipient\n{content}
|
||||
static common_chat_params common_chat_params_init_functionary_v3_2(const common_chat_template & tmpl,
|
||||
const autoparser::generation_params & inputs) {
|
||||
common_chat_params data;
|
||||
|
||||
data.prompt = common_chat_template_direct_apply(tmpl, inputs);
|
||||
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
|
||||
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
|
||||
data.preserved_tokens = {
|
||||
">>>all",
|
||||
@@ -1150,7 +1301,7 @@ 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(tmpl, inputs);
|
||||
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
|
||||
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
|
||||
data.supports_thinking = true;
|
||||
data.preserved_tokens = {
|
||||
@@ -1263,16 +1414,17 @@ static common_chat_params common_chat_params_init_kimi_k2(const common_chat_temp
|
||||
return data;
|
||||
}
|
||||
|
||||
// LFM2 format:
|
||||
// - Reasoning: <think>{reasoning}</think> (optional, only if enable_thinking is true)
|
||||
// - Content: text after reasoning (optional)
|
||||
// - Tool calls: <|tool_call_start|>[function_name(arg1="value1", arg2="value2")]<|tool_call_end|>
|
||||
// Tool calls can appear multiple times (parallel tool calls)
|
||||
// LFM2 format: uses <|tool_list_start|>[...]<|tool_list_end|> in system prompt
|
||||
// and <|tool_call_start|>[name(arg="val")]<|tool_call_end|> for tool calls.
|
||||
// - Reasoning: <think>{reasoning}</think> (optional)
|
||||
// - Content: text before a tool call (optional)
|
||||
// - Tool calls: Python-style, e.g. [function_name(arg1="value1", arg2="value2")]
|
||||
// Tool calls can appear multiple times (parallel tool calls supported)
|
||||
static common_chat_params common_chat_params_init_lfm2(const common_chat_template & tmpl,
|
||||
const autoparser::generation_params & inputs) {
|
||||
common_chat_params data;
|
||||
|
||||
data.prompt = common_chat_template_direct_apply(tmpl, inputs);
|
||||
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
|
||||
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
|
||||
data.supports_thinking = true;
|
||||
data.preserved_tokens = {
|
||||
@@ -1308,9 +1460,9 @@ static common_chat_params common_chat_params_init_lfm2(const common_chat_templat
|
||||
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
|
||||
return generation_prompt + reasoning + p.content(p.rest()) + end;
|
||||
}
|
||||
|
||||
auto tool_calls = p.rule("tool-calls",
|
||||
p.trigger_rule("tool-call", p.literal(TOOL_CALL_START) +
|
||||
p.trigger_rule("tool-call",
|
||||
p.literal(TOOL_CALL_START) +
|
||||
p.python_style_tool_calls(inputs.tools, inputs.parallel_tool_calls) +
|
||||
p.literal(TOOL_CALL_END)
|
||||
)
|
||||
@@ -1338,6 +1490,80 @@ static common_chat_params common_chat_params_init_lfm2(const common_chat_templat
|
||||
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, TOOL_CALL_START }
|
||||
};
|
||||
}
|
||||
return data;
|
||||
}
|
||||
|
||||
// LFM2.5 format: uses plain "List of tools: [...]" in system prompt, no wrapper tokens.
|
||||
// Tool calls are bare [name(arg="val")], though model may optionally emit <|tool_call_start|>.
|
||||
// - Reasoning: <think>{reasoning}</think> (optional)
|
||||
// - Content: text before a tool call (optional)
|
||||
// - Tool calls: Python-style, e.g. [function_name(arg1="value1", arg2="value2")]
|
||||
// Tool calls can appear multiple times (parallel tool calls supported)
|
||||
static common_chat_params common_chat_params_init_lfm2_5(const common_chat_template & tmpl,
|
||||
const autoparser::generation_params & inputs) {
|
||||
common_chat_params data;
|
||||
|
||||
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_call_start|>",
|
||||
"<|tool_call_end|>",
|
||||
"<think>",
|
||||
"</think>",
|
||||
};
|
||||
|
||||
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
|
||||
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
|
||||
auto include_grammar = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
|
||||
|
||||
const std::string THINK_START = "<think>";
|
||||
const std::string THINK_END = "</think>";
|
||||
|
||||
data.thinking_start_tag = THINK_START;
|
||||
data.thinking_end_tag = THINK_END;
|
||||
|
||||
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
|
||||
auto generation_prompt = p.prefix(inputs.generation_prompt, THINK_START);
|
||||
auto end = p.end();
|
||||
|
||||
auto reasoning = p.eps();
|
||||
if (extract_reasoning && inputs.enable_thinking) {
|
||||
reasoning = p.optional(THINK_START + p.reasoning(p.until(THINK_END)) + THINK_END);
|
||||
}
|
||||
|
||||
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
|
||||
return generation_prompt + reasoning + p.content(p.rest()) + end;
|
||||
}
|
||||
|
||||
auto tool_calls = p.rule("tool-calls",
|
||||
p.trigger_rule("tool-call",
|
||||
p.python_style_tool_calls(inputs.tools, inputs.parallel_tool_calls)
|
||||
)
|
||||
);
|
||||
|
||||
auto content = p.content(p.until_one_of({"<|tool_call_start|>", "["}));
|
||||
auto maybe_start = p.optional(p.literal("<|tool_call_start|>"));
|
||||
return generation_prompt + reasoning + content + maybe_start + tool_calls + end;
|
||||
});
|
||||
|
||||
data.parser = parser.save();
|
||||
|
||||
if (include_grammar) {
|
||||
data.grammar_lazy = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
|
||||
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
|
||||
foreach_function(inputs.tools, [&](const json & tool) {
|
||||
const auto & function = tool.at("function");
|
||||
auto schema = function.at("parameters");
|
||||
builder.resolve_refs(schema);
|
||||
});
|
||||
parser.build_grammar(builder, data.grammar_lazy);
|
||||
});
|
||||
foreach_function(inputs.tools, [&](const json & tool) {
|
||||
const std::string name = tool.at("function").at("name");
|
||||
data.grammar_triggers.push_back({ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "[" + name + "(" });
|
||||
});
|
||||
}
|
||||
|
||||
return data;
|
||||
}
|
||||
@@ -1348,7 +1574,7 @@ static common_chat_params common_chat_params_init_gigachat_v3(
|
||||
|
||||
common_chat_params data;
|
||||
|
||||
data.prompt = common_chat_template_direct_apply(tmpl, inputs);
|
||||
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
|
||||
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
|
||||
data.supports_thinking = false;
|
||||
data.preserved_tokens = {
|
||||
@@ -1454,6 +1680,150 @@ static void requires_non_null_content(json & messages) {
|
||||
}
|
||||
}
|
||||
|
||||
// Gemma4 uses a custom tool_responses field instead of role:tool messages.
|
||||
//
|
||||
// This will transform a sequence of messages:
|
||||
// assistant(tool_call+) -> tool+ -> assistant(content)
|
||||
//
|
||||
// Into a single assistant message containing a tool_responses field:
|
||||
// assistant(content + tool_call + tool_responses)
|
||||
//
|
||||
// This is necessary for the Gemma4 chat template to properly format the prompt.
|
||||
// See https://ai.google.dev/gemma/docs/core/prompt-formatting-gemma4
|
||||
struct gemma4_model_turn_builder {
|
||||
json & messages;
|
||||
size_t pos;
|
||||
json tool_calls = json::array();
|
||||
json tool_responses = json::array();
|
||||
json content;
|
||||
json reasoning_content;
|
||||
|
||||
gemma4_model_turn_builder(json & msgs, size_t pos) : messages(msgs), pos(pos) {}
|
||||
|
||||
void collect() {
|
||||
// Collect the first assistant message
|
||||
auto & msg = messages[pos];
|
||||
if (msg.contains("reasoning_content") && msg.at("reasoning_content").is_string()) {
|
||||
// According to the prompt formatting guide, we need to preserve reasoning_content
|
||||
// between function calls. The current chat templates do not support this, but we will do it anyway.
|
||||
reasoning_content = msg.at("reasoning_content");
|
||||
}
|
||||
for (auto & tc : msg.at("tool_calls")) {
|
||||
tool_calls.push_back(tc);
|
||||
}
|
||||
pos++;
|
||||
|
||||
// Collect tool call results
|
||||
while (pos < messages.size() && messages[pos].value("role", "") == "tool") {
|
||||
collect_result(messages[pos]);
|
||||
pos++;
|
||||
}
|
||||
|
||||
// Check if the next assistant message is the final message
|
||||
if (pos < messages.size() && messages[pos].value("role", "") == "assistant") {
|
||||
auto & next = messages[pos];
|
||||
if (!has_tool_calls(next) && has_content(next)) {
|
||||
content = next.at("content");
|
||||
pos++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void collect_result(const json & curr) {
|
||||
json response;
|
||||
if (curr.contains("content")) {
|
||||
const auto & content = curr.at("content");
|
||||
if (content.is_string()) {
|
||||
// Try to parse the content as JSON; fall back to raw string
|
||||
try {
|
||||
response = json::parse(content.get<std::string>());
|
||||
} catch (...) {
|
||||
response = content;
|
||||
}
|
||||
} else {
|
||||
response = content;
|
||||
}
|
||||
}
|
||||
|
||||
std::string name;
|
||||
|
||||
// Match name with corresponding tool call
|
||||
size_t idx = tool_responses.size();
|
||||
if (idx < tool_calls.size()) {
|
||||
auto & tc = tool_calls[idx];
|
||||
if (tc.contains("function")) {
|
||||
name = tc.at("function").value("name", "");
|
||||
}
|
||||
}
|
||||
|
||||
// Fallback to the tool call id
|
||||
if (name.empty()) {
|
||||
name = curr.value("tool_call_id", "");
|
||||
}
|
||||
|
||||
tool_responses.push_back({{"name", name}, {"response", response}});
|
||||
}
|
||||
|
||||
json build() {
|
||||
collect();
|
||||
|
||||
json msg = {
|
||||
{"role", "assistant"},
|
||||
{"tool_calls", tool_calls},
|
||||
};
|
||||
if (!tool_responses.empty()) {
|
||||
msg["tool_responses"] = tool_responses;
|
||||
}
|
||||
if (!content.is_null()) {
|
||||
msg["content"] = content;
|
||||
}
|
||||
if (!reasoning_content.is_null()) {
|
||||
msg["reasoning_content"] = reasoning_content;
|
||||
}
|
||||
return msg;
|
||||
}
|
||||
|
||||
static bool has_content(const json & msg) {
|
||||
if (!msg.contains("content") || msg.at("content").is_null()) {
|
||||
return false;
|
||||
}
|
||||
const auto & content = msg.at("content");
|
||||
if (content.is_string() && !content.get<std::string>().empty()) {
|
||||
return true;
|
||||
}
|
||||
if (content.is_array() && !content.empty()) {
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
static bool has_tool_calls(const json & msg) {
|
||||
return msg.contains("tool_calls") && msg.at("tool_calls").is_array() && !msg.at("tool_calls").empty();
|
||||
}
|
||||
};
|
||||
|
||||
static void convert_tool_responses_gemma4(json & messages) {
|
||||
json result = json::array();
|
||||
size_t i = 0;
|
||||
|
||||
while (i < messages.size()) {
|
||||
auto & msg = messages[i];
|
||||
|
||||
if (msg.value("role", "") != "assistant" || !msg.contains("tool_calls") ||
|
||||
!msg.at("tool_calls").is_array() || msg.at("tool_calls").empty()) {
|
||||
result.push_back(msg);
|
||||
i++;
|
||||
continue;
|
||||
}
|
||||
|
||||
gemma4_model_turn_builder builder(messages, i);
|
||||
result.push_back(builder.build());
|
||||
i = builder.pos;
|
||||
}
|
||||
|
||||
messages = result;
|
||||
}
|
||||
|
||||
static void func_args_not_string(json & messages) {
|
||||
GGML_ASSERT(messages.is_array());
|
||||
for (auto & message : messages) {
|
||||
@@ -1486,10 +1856,10 @@ static json common_chat_extra_context() {
|
||||
return ctx;
|
||||
}
|
||||
|
||||
static std::optional<common_chat_params> try_specialized_template(
|
||||
std::optional<common_chat_params> common_chat_try_specialized_template(
|
||||
const common_chat_template & tmpl,
|
||||
const std::string & src,
|
||||
const autoparser::generation_params & params) {
|
||||
autoparser::generation_params & params) {
|
||||
// Ministral/Mistral Large 3 - uses special reasoning structure fixes, can't use autoparser
|
||||
// Note: Mistral Small 3.2 uses [CALL_ID] which Ministral doesn't have, so we can distinguish them
|
||||
if (src.find("[SYSTEM_PROMPT]") != std::string::npos && src.find("[TOOL_CALLS]") != std::string::npos &&
|
||||
@@ -1519,14 +1889,21 @@ static std::optional<common_chat_params> try_specialized_template(
|
||||
return common_chat_params_init_kimi_k2(tmpl, params);
|
||||
}
|
||||
|
||||
// LFM2 - uses <|tool_list_start|>/<|tool_list_end|> markers and <|tool_call_start|>[name(args)]<|tool_call_end|> format
|
||||
// Detection: template has "<|tool_list_start|>" and "<|tool_list_end|>" markers
|
||||
// LFM2 format detection: template uses <|tool_list_start|>[...]<|tool_list_end|> around the tool list
|
||||
// and <|tool_call_start|>[...]<|tool_call_end|> around each tool call
|
||||
if (src.find("<|tool_list_start|>") != std::string::npos &&
|
||||
src.find("<|tool_list_end|>") != std::string::npos) {
|
||||
LOG_DBG("Using specialized template: LFM2\n");
|
||||
return common_chat_params_init_lfm2(tmpl, params);
|
||||
}
|
||||
|
||||
// LFM2.5 format detection: template uses plain "List of tools: [...]" with no special tokens
|
||||
if (src.find("List of tools: [") != std::string::npos &&
|
||||
src.find("<|tool_list_start|>") == std::string::npos) {
|
||||
LOG_DBG("Using specialized template: LFM2.5\n");
|
||||
return common_chat_params_init_lfm2_5(tmpl, params);
|
||||
}
|
||||
|
||||
// GigaChatV3 format detection
|
||||
if (src.find("<|role_sep|>") != std::string::npos &&
|
||||
src.find("<|message_sep|>") != std::string::npos &&
|
||||
@@ -1535,6 +1912,12 @@ static std::optional<common_chat_params> try_specialized_template(
|
||||
return common_chat_params_init_gigachat_v3(tmpl, params);
|
||||
}
|
||||
|
||||
// Gemma4 format detection
|
||||
if (src.find("'<|tool_call>call:'") != std::string::npos) {
|
||||
workaround::convert_tool_responses_gemma4(params.messages);
|
||||
return common_chat_params_init_gemma4(tmpl, params);
|
||||
}
|
||||
|
||||
return std::nullopt;
|
||||
}
|
||||
|
||||
@@ -1576,11 +1959,11 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
|
||||
}
|
||||
|
||||
params.add_generation_prompt = false;
|
||||
std::string no_gen_prompt = common_chat_template_direct_apply(tmpl, params);
|
||||
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(tmpl, params);
|
||||
std::string gen_prompt = common_chat_template_direct_apply_impl(tmpl, params);
|
||||
auto diff = calculate_diff_split(no_gen_prompt, gen_prompt);
|
||||
params.generation_prompt = diff.right;
|
||||
params.generation_prompt = diff.right + diff.suffix;
|
||||
|
||||
params.add_generation_prompt = inputs.add_generation_prompt;
|
||||
|
||||
@@ -1612,17 +1995,17 @@ static common_chat_params common_chat_templates_apply_jinja(const struct common_
|
||||
common_chat_params data;
|
||||
auto params_copy = params;
|
||||
params_copy.reasoning_format = COMMON_REASONING_FORMAT_NONE;
|
||||
data.prompt = common_chat_template_direct_apply(tmpl, params_copy);
|
||||
data.prompt = common_chat_template_direct_apply_impl(tmpl, params_copy);
|
||||
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
|
||||
data.generation_prompt = params.generation_prompt;
|
||||
auto parser = build_chat_peg_parser([¶ms](common_chat_peg_builder &p) {
|
||||
return p.prefix(params.generation_prompt) + p.content(p.rest());
|
||||
return p.prefix(params.generation_prompt) << p.content(p.rest());
|
||||
});
|
||||
data.parser = parser.save();
|
||||
return data;
|
||||
}
|
||||
|
||||
if (auto result = try_specialized_template(tmpl, src, params)) {
|
||||
if (auto result = common_chat_try_specialized_template(tmpl, src, params)) {
|
||||
result->generation_prompt = params.generation_prompt;
|
||||
return *result;
|
||||
}
|
||||
@@ -1759,8 +2142,13 @@ common_chat_msg common_chat_peg_parse(const common_peg_arena & src_pars
|
||||
// Try to extract any partial results from what was successfully parsed
|
||||
common_chat_msg msg;
|
||||
msg.role = "assistant";
|
||||
auto mapper = common_chat_peg_mapper(msg);
|
||||
mapper.from_ast(ctx.ast, result);
|
||||
std::unique_ptr<common_chat_peg_mapper> mapper;
|
||||
if (params.format == COMMON_CHAT_FORMAT_PEG_GEMMA4) {
|
||||
mapper = std::make_unique<common_chat_peg_gemma4_mapper>(msg);
|
||||
} else {
|
||||
mapper = std::make_unique<common_chat_peg_mapper>(msg);
|
||||
}
|
||||
mapper->from_ast(ctx.ast, result);
|
||||
|
||||
if (ctx.is_debug()) {
|
||||
fprintf(stderr, "\nAST for partial parse (fail):\n%s\n", ctx.ast.dump().c_str());
|
||||
@@ -1775,8 +2163,13 @@ common_chat_msg common_chat_peg_parse(const common_peg_arena & src_pars
|
||||
common_chat_msg msg;
|
||||
msg.role = "assistant";
|
||||
|
||||
auto mapper = common_chat_peg_mapper(msg);
|
||||
mapper.from_ast(ctx.ast, result);
|
||||
std::unique_ptr<common_chat_peg_mapper> mapper;
|
||||
if (params.format == COMMON_CHAT_FORMAT_PEG_GEMMA4) {
|
||||
mapper = std::make_unique<common_chat_peg_gemma4_mapper>(msg);
|
||||
} else {
|
||||
mapper = std::make_unique<common_chat_peg_mapper>(msg);
|
||||
}
|
||||
mapper->from_ast(ctx.ast, result);
|
||||
|
||||
if (ctx.is_debug()) {
|
||||
fprintf(stderr, "\nAST for %s parse:\n%s\n", is_partial ? "partial" : "full", ctx.ast.dump().c_str());
|
||||
|
||||
@@ -3,12 +3,12 @@
|
||||
#pragma once
|
||||
|
||||
#include "common.h"
|
||||
#include "jinja/parser.h"
|
||||
#include "nlohmann/json_fwd.hpp"
|
||||
#include "peg-parser.h"
|
||||
#include "jinja/parser.h"
|
||||
#include "jinja/runtime.h"
|
||||
#include "jinja/caps.h"
|
||||
#include "nlohmann/json.hpp"
|
||||
|
||||
#include "nlohmann/json_fwd.hpp"
|
||||
|
||||
#include <chrono>
|
||||
#include <functional>
|
||||
@@ -19,8 +19,6 @@
|
||||
using chat_template_caps = jinja::caps;
|
||||
using json = nlohmann::ordered_json;
|
||||
|
||||
#include <nlohmann/json_fwd.hpp>
|
||||
|
||||
struct common_chat_templates;
|
||||
|
||||
namespace autoparser {
|
||||
@@ -75,41 +73,9 @@ struct common_chat_template {
|
||||
const std::string & bos_token() const { return bos_tok; }
|
||||
const std::string & eos_token() const { return eos_tok; }
|
||||
|
||||
// TODO: this is ugly, refactor it somehow
|
||||
json add_system(const json & messages, const std::string & system_prompt) const {
|
||||
GGML_ASSERT(messages.is_array());
|
||||
auto msgs_copy = messages;
|
||||
if (!caps.supports_system_role) {
|
||||
if (msgs_copy.empty()) {
|
||||
msgs_copy.insert(msgs_copy.begin(), json{
|
||||
{"role", "user"},
|
||||
{"content", system_prompt}
|
||||
});
|
||||
} else {
|
||||
auto & first_msg = msgs_copy[0];
|
||||
if (!first_msg.contains("content")) {
|
||||
first_msg["content"] = "";
|
||||
}
|
||||
first_msg["content"] = system_prompt + "\n\n"
|
||||
+ first_msg["content"].get<std::string>();
|
||||
}
|
||||
} else {
|
||||
if (msgs_copy.empty() || msgs_copy[0].at("role") != "system") {
|
||||
msgs_copy.insert(msgs_copy.begin(), json{
|
||||
{"role", "system"},
|
||||
{"content", system_prompt}
|
||||
});
|
||||
} else if (msgs_copy[0].at("role") == "system") {
|
||||
msgs_copy[0]["content"] = system_prompt;
|
||||
}
|
||||
}
|
||||
return msgs_copy;
|
||||
}
|
||||
|
||||
chat_template_caps original_caps() const {
|
||||
return caps;
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
struct common_chat_msg {
|
||||
@@ -184,6 +150,7 @@ enum common_chat_format {
|
||||
// These are intended to be parsed by the PEG parser
|
||||
COMMON_CHAT_FORMAT_PEG_SIMPLE,
|
||||
COMMON_CHAT_FORMAT_PEG_NATIVE,
|
||||
COMMON_CHAT_FORMAT_PEG_GEMMA4,
|
||||
|
||||
COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats
|
||||
};
|
||||
@@ -256,8 +223,8 @@ common_chat_templates_ptr common_chat_templates_init(const struct llama_model *
|
||||
const std::string & bos_token_override = "",
|
||||
const std::string & eos_token_override = "");
|
||||
|
||||
bool common_chat_templates_was_explicit(const struct common_chat_templates * tmpls);
|
||||
std::string common_chat_templates_source(const struct common_chat_templates * tmpls, const std::string & variant = "");
|
||||
bool common_chat_templates_was_explicit(const struct common_chat_templates * tmpls);
|
||||
std::string common_chat_templates_source(const struct common_chat_templates * tmpls, const std::string & variant = "");
|
||||
|
||||
struct common_chat_params common_chat_templates_apply(const struct common_chat_templates * tmpls,
|
||||
const struct common_chat_templates_inputs & inputs);
|
||||
@@ -274,9 +241,9 @@ std::string common_chat_format_example(const struct common_chat_templates *
|
||||
bool use_jinja,
|
||||
const std::map<std::string, std::string> & chat_template_kwargs);
|
||||
|
||||
const char * common_chat_format_name(common_chat_format format);
|
||||
common_chat_msg common_chat_parse(const std::string & input, bool is_partial, const common_chat_parser_params & params);
|
||||
common_chat_msg common_chat_peg_parse(const common_peg_arena & src_parser, const std::string & input, bool is_partial, const common_chat_parser_params & params);
|
||||
const char * common_chat_format_name(common_chat_format format);
|
||||
common_chat_msg common_chat_parse(const std::string & input, bool is_partial, const common_chat_parser_params & params);
|
||||
common_chat_msg common_chat_peg_parse(const common_peg_arena & src_parser, const std::string & input, bool is_partial, const common_chat_parser_params & params);
|
||||
|
||||
// used by arg and server
|
||||
const char * common_reasoning_format_name(common_reasoning_format format);
|
||||
@@ -302,7 +269,9 @@ std::map<std::string, bool> common_chat_templates_get_caps(const common_chat_tem
|
||||
|
||||
std::string common_chat_template_direct_apply(
|
||||
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);
|
||||
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);
|
||||
|
||||
@@ -359,6 +359,11 @@ bool parse_cpu_mask(const std::string & mask, bool (&boolmask)[GGML_MAX_N_THREAD
|
||||
}
|
||||
|
||||
void common_init() {
|
||||
#if defined(_WIN32)
|
||||
SetConsoleOutputCP(CP_UTF8);
|
||||
SetConsoleCP(CP_UTF8);
|
||||
#endif
|
||||
|
||||
llama_log_set(common_log_default_callback, NULL);
|
||||
|
||||
#ifdef NDEBUG
|
||||
@@ -367,7 +372,7 @@ void common_init() {
|
||||
const char * build_type = " (debug)";
|
||||
#endif
|
||||
|
||||
LOG_INF("build: %d (%s) with %s for %s%s\n", LLAMA_BUILD_NUMBER, LLAMA_COMMIT, LLAMA_COMPILER, LLAMA_BUILD_TARGET, build_type);
|
||||
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) {
|
||||
@@ -656,6 +661,97 @@ bool string_parse_kv_override(const char * data, std::vector<llama_model_kv_over
|
||||
return true;
|
||||
}
|
||||
|
||||
static inline bool glob_class_match(const char c, const char * pattern, const char * class_end) {
|
||||
const char * class_start = pattern;
|
||||
bool negated = false;
|
||||
|
||||
if (*class_start == '!') {
|
||||
negated = true;
|
||||
class_start++;
|
||||
}
|
||||
|
||||
// If first character after negation is ']' or '-', treat it as literal
|
||||
if (*class_start == ']' || *class_start == '-') {
|
||||
if (class_start < class_end && *class_start == c) {
|
||||
return !negated;
|
||||
}
|
||||
class_start++;
|
||||
}
|
||||
|
||||
bool matched = false;
|
||||
|
||||
while (class_start < class_end) {
|
||||
if (class_start + 2 < class_end && class_start[1] == '-' && class_start[2] != ']') {
|
||||
char start_char = *class_start;
|
||||
char end_char = class_start[2];
|
||||
if (c >= start_char && c <= end_char) {
|
||||
matched = true;
|
||||
break;
|
||||
}
|
||||
class_start += 3;
|
||||
} else {
|
||||
if (*class_start == c) {
|
||||
matched = true;
|
||||
break;
|
||||
}
|
||||
class_start++;
|
||||
}
|
||||
}
|
||||
|
||||
return negated ? !matched : matched;
|
||||
}
|
||||
|
||||
// simple glob: * matches non-/ chars, ** matches anything including /, [] matches character class
|
||||
static inline bool glob_match(const char * pattern, const char * str) {
|
||||
if (*pattern == '\0') {
|
||||
return *str == '\0';
|
||||
}
|
||||
if (pattern[0] == '*' && pattern[1] == '*') {
|
||||
const char * p = pattern + 2;
|
||||
if (glob_match(p, str)) return true;
|
||||
if (*str != '\0') return glob_match(pattern, str + 1);
|
||||
return false;
|
||||
}
|
||||
if (*pattern == '*') {
|
||||
const char * p = pattern + 1;
|
||||
for (; *str != '\0' && *str != '/'; str++) {
|
||||
if (glob_match(p, str)) return true;
|
||||
}
|
||||
return glob_match(p, str);
|
||||
}
|
||||
if (*pattern == '?' && *str != '\0' && *str != '/') {
|
||||
return glob_match(pattern + 1, str + 1);
|
||||
}
|
||||
if (*pattern == '[') {
|
||||
const char * class_end = pattern + 1;
|
||||
// If first character after '[' is ']' or '-', treat it as literal
|
||||
if (*class_end == ']' || *class_end == '-') {
|
||||
class_end++;
|
||||
}
|
||||
while (*class_end != '\0' && *class_end != ']') {
|
||||
class_end++;
|
||||
}
|
||||
if (*class_end == ']') {
|
||||
if (*str == '\0') return false;
|
||||
bool matched = glob_class_match(*str, pattern + 1, class_end);
|
||||
return matched && glob_match(class_end + 1, str + 1);
|
||||
} else {
|
||||
if (*str == '[') {
|
||||
return glob_match(pattern + 1, str + 1);
|
||||
}
|
||||
return false;
|
||||
}
|
||||
}
|
||||
if (*pattern == *str) {
|
||||
return glob_match(pattern + 1, str + 1);
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
bool glob_match(const std::string & pattern, const std::string & str) {
|
||||
return glob_match(pattern.c_str(), str.c_str());
|
||||
}
|
||||
|
||||
//
|
||||
// Filesystem utils
|
||||
//
|
||||
@@ -1152,6 +1248,9 @@ llama_context * common_init_result::context() {
|
||||
}
|
||||
|
||||
common_sampler * common_init_result::sampler(llama_seq_id seq_id) {
|
||||
if (seq_id < 0 || seq_id >= (int) pimpl->samplers.size()) {
|
||||
return nullptr;
|
||||
}
|
||||
return pimpl->samplers[seq_id].get();
|
||||
}
|
||||
|
||||
@@ -1343,6 +1442,7 @@ struct llama_model_params common_model_params_to_llama(common_params & params) {
|
||||
|
||||
mparams.progress_callback = params.load_progress_callback;
|
||||
mparams.progress_callback_user_data = params.load_progress_callback_user_data;
|
||||
mparams.no_alloc = params.no_alloc;
|
||||
|
||||
return mparams;
|
||||
}
|
||||
|
||||
@@ -573,13 +573,15 @@ struct common_params {
|
||||
|
||||
// server params
|
||||
int32_t port = 8080; // server listens on this network port
|
||||
bool reuse_port = false; // allow multiple sockets to bind to the same port
|
||||
int32_t timeout_read = 600; // http read timeout in seconds
|
||||
int32_t timeout_write = timeout_read; // http write timeout in seconds
|
||||
int32_t n_threads_http = -1; // number of threads to process HTTP requests (TODO: support threadpool)
|
||||
int32_t n_cache_reuse = 0; // min chunk size to reuse from the cache via KV shifting
|
||||
bool cache_prompt = true; // whether to enable prompt caching
|
||||
int32_t n_ctx_checkpoints = 32; // max number of context checkpoints per slot
|
||||
int32_t checkpoint_every_nt = 8192; // make a checkpoint every n tokens during prefill
|
||||
bool clear_idle = 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_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";
|
||||
@@ -613,6 +615,9 @@ struct common_params {
|
||||
bool endpoint_props = false; // only control POST requests, not GET
|
||||
bool endpoint_metrics = false;
|
||||
|
||||
// enable built-in tools
|
||||
std::vector<std::string> server_tools;
|
||||
|
||||
// router server configs
|
||||
std::string models_dir = ""; // directory containing models for the router server
|
||||
std::string models_preset = ""; // directory containing model presets for the router server
|
||||
@@ -675,6 +680,7 @@ struct common_params {
|
||||
// return false from callback to abort model loading or true to continue
|
||||
llama_progress_callback load_progress_callback = NULL;
|
||||
void * load_progress_callback_user_data = NULL;
|
||||
bool no_alloc = false; // Don't allocate model buffers
|
||||
};
|
||||
|
||||
// call once at the start of a program if it uses libcommon
|
||||
@@ -790,6 +796,8 @@ std::string string_from(const std::vector<int> & values);
|
||||
std::string string_from(const struct llama_context * ctx, const std::vector<llama_token> & tokens);
|
||||
std::string string_from(const struct llama_context * ctx, const struct llama_batch & batch);
|
||||
|
||||
bool glob_match(const std::string & pattern, const std::string & str);
|
||||
|
||||
//
|
||||
// Filesystem utils
|
||||
//
|
||||
|
||||
@@ -700,13 +700,13 @@ namespace console {
|
||||
std::vector<std::string> entries;
|
||||
size_t viewing_idx = SIZE_MAX;
|
||||
std::string backup_line; // current line before viewing history
|
||||
void add(const std::string & line) {
|
||||
void add(std::string_view line) {
|
||||
if (line.empty()) {
|
||||
return;
|
||||
}
|
||||
// avoid duplicates with the last entry
|
||||
if (entries.empty() || entries.back() != line) {
|
||||
entries.push_back(line);
|
||||
entries.emplace_back(line);
|
||||
}
|
||||
// also clear viewing state
|
||||
end_viewing();
|
||||
@@ -1031,11 +1031,12 @@ namespace console {
|
||||
|
||||
if (!end_of_stream && !line.empty()) {
|
||||
// remove the trailing newline for history storage
|
||||
std::string_view hline = line;
|
||||
if (!line.empty() && line.back() == '\n') {
|
||||
line.pop_back();
|
||||
hline.remove_suffix(1);
|
||||
}
|
||||
// TODO: maybe support multiline history entries?
|
||||
history.add(line);
|
||||
history.add(hline);
|
||||
}
|
||||
|
||||
fflush(out);
|
||||
|
||||
@@ -119,6 +119,9 @@ class ProgressBar {
|
||||
static inline std::map<const ProgressBar *, int> lines;
|
||||
static inline int max_line = 0;
|
||||
|
||||
std::string filename;
|
||||
size_t len = 0;
|
||||
|
||||
static void cleanup(const ProgressBar * line) {
|
||||
lines.erase(line);
|
||||
if (lines.empty()) {
|
||||
@@ -135,7 +138,23 @@ class ProgressBar {
|
||||
}
|
||||
|
||||
public:
|
||||
ProgressBar() = default;
|
||||
ProgressBar(const std::string & url = "") : filename(url) {
|
||||
if (auto pos = filename.rfind('/'); pos != std::string::npos) {
|
||||
filename = filename.substr(pos + 1);
|
||||
}
|
||||
if (auto pos = filename.find('?'); pos != std::string::npos) {
|
||||
filename = filename.substr(0, pos);
|
||||
}
|
||||
for (size_t i = 0; i < filename.size(); ++i) {
|
||||
if ((filename[i] & 0xC0) != 0x80) {
|
||||
if (len++ == 39) {
|
||||
filename.resize(i);
|
||||
filename += "…";
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
~ProgressBar() {
|
||||
std::lock_guard<std::mutex> lock(mutex);
|
||||
@@ -143,11 +162,7 @@ public:
|
||||
}
|
||||
|
||||
void update(size_t current, size_t total) {
|
||||
if (!is_output_a_tty()) {
|
||||
return;
|
||||
}
|
||||
|
||||
if (!total) {
|
||||
if (!total || !is_output_a_tty()) {
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -159,28 +174,27 @@ public:
|
||||
}
|
||||
int lines_up = max_line - lines[this];
|
||||
|
||||
size_t width = 50;
|
||||
size_t bar = 55 - len;
|
||||
size_t pct = (100 * current) / total;
|
||||
size_t pos = (width * current) / total;
|
||||
|
||||
std::cout << "\033[s";
|
||||
size_t pos = (bar * current) / total;
|
||||
|
||||
if (lines_up > 0) {
|
||||
std::cout << "\033[" << lines_up << "A";
|
||||
}
|
||||
std::cout << "\033[2K\r["
|
||||
<< std::string(pos, '=')
|
||||
<< (pos < width ? ">" : "")
|
||||
<< std::string(width - pos, ' ')
|
||||
<< "] " << std::setw(3) << pct << "% ("
|
||||
<< current / (1024 * 1024) << " MB / "
|
||||
<< total / (1024 * 1024) << " MB) "
|
||||
<< "\033[u";
|
||||
std::cout << '\r' << "Downloading " << filename << " ";
|
||||
|
||||
std::cout.flush();
|
||||
for (size_t i = 0; i < bar; ++i) {
|
||||
std::cout << (i < pos ? "—" : " ");
|
||||
}
|
||||
std::cout << std::setw(4) << pct << "%\033[K";
|
||||
|
||||
if (lines_up > 0) {
|
||||
std::cout << "\033[" << lines_up << "B";
|
||||
}
|
||||
std::cout << '\r' << std::flush;
|
||||
|
||||
if (current == total) {
|
||||
cleanup(this);
|
||||
cleanup(this);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -208,7 +222,7 @@ static bool common_pull_file(httplib::Client & cli,
|
||||
const char * func = __func__; // avoid __func__ inside a lambda
|
||||
size_t downloaded = existing_size;
|
||||
size_t progress_step = 0;
|
||||
ProgressBar bar;
|
||||
ProgressBar bar(resolve_path);
|
||||
|
||||
auto res = cli.Get(resolve_path, headers,
|
||||
[&](const httplib::Response &response) {
|
||||
@@ -286,7 +300,7 @@ static int common_download_file_single_online(const std::string & url,
|
||||
const bool file_exists = std::filesystem::exists(path);
|
||||
|
||||
if (file_exists && skip_etag) {
|
||||
LOG_INF("%s: using cached file: %s\n", __func__, path.c_str());
|
||||
LOG_DBG("%s: using cached file: %s\n", __func__, path.c_str());
|
||||
return 304; // 304 Not Modified - fake cached response
|
||||
}
|
||||
|
||||
@@ -294,7 +308,7 @@ static int common_download_file_single_online(const std::string & url,
|
||||
if (file_exists) {
|
||||
last_etag = read_etag(path);
|
||||
} else {
|
||||
LOG_INF("%s: no previous model file found %s\n", __func__, path.c_str());
|
||||
LOG_DBG("%s: no previous model file found %s\n", __func__, path.c_str());
|
||||
}
|
||||
|
||||
auto head = cli.Head(parts.path);
|
||||
@@ -328,11 +342,11 @@ static int common_download_file_single_online(const std::string & url,
|
||||
|
||||
if (file_exists) {
|
||||
if (etag.empty()) {
|
||||
LOG_INF("%s: using cached file (no server etag): %s\n", __func__, path.c_str());
|
||||
LOG_DBG("%s: using cached file (no server etag): %s\n", __func__, path.c_str());
|
||||
return 304; // 304 Not Modified - fake cached response
|
||||
}
|
||||
if (!last_etag.empty() && last_etag == etag) {
|
||||
LOG_INF("%s: using cached file (same etag): %s\n", __func__, path.c_str());
|
||||
LOG_DBG("%s: using cached file (same etag): %s\n", __func__, path.c_str());
|
||||
return 304; // 304 Not Modified - fake cached response
|
||||
}
|
||||
if (remove(path.c_str()) != 0) {
|
||||
@@ -368,7 +382,7 @@ static int common_download_file_single_online(const std::string & url,
|
||||
}
|
||||
}
|
||||
|
||||
LOG_INF("%s: downloading from %s to %s (etag:%s)...\n",
|
||||
LOG_DBG("%s: downloading from %s to %s (etag:%s)...\n",
|
||||
__func__, common_http_show_masked_url(parts).c_str(),
|
||||
path_temporary.c_str(), etag.c_str());
|
||||
|
||||
@@ -437,7 +451,7 @@ int common_download_file_single(const std::string & url,
|
||||
return -1;
|
||||
}
|
||||
|
||||
LOG_INF("%s: using cached file (offline mode): %s\n", __func__, path.c_str());
|
||||
LOG_DBG("%s: using cached file (offline mode): %s\n", __func__, path.c_str());
|
||||
return 304; // Not Modified - fake cached response
|
||||
}
|
||||
|
||||
@@ -454,15 +468,17 @@ static gguf_split_info get_gguf_split_info(const std::string & path) {
|
||||
std::smatch m;
|
||||
|
||||
std::string prefix = path;
|
||||
string_remove_suffix(prefix, ".gguf");
|
||||
if (!string_remove_suffix(prefix, ".gguf")) {
|
||||
return {};
|
||||
}
|
||||
|
||||
int index = 1;
|
||||
int count = 1;
|
||||
|
||||
if (std::regex_match(prefix, m, re_split)) {
|
||||
prefix = m[1].str();
|
||||
index = std::stoi(m[2].str());
|
||||
count = std::stoi(m[3].str());
|
||||
prefix = m[1].str();
|
||||
}
|
||||
|
||||
std::string tag;
|
||||
@@ -546,6 +562,20 @@ static hf_cache::hf_file find_best_mmproj(const hf_cache::hf_files & files,
|
||||
return best;
|
||||
}
|
||||
|
||||
static bool gguf_filename_is_model(const std::string & filepath) {
|
||||
if (!string_ends_with(filepath, ".gguf")) {
|
||||
return false;
|
||||
}
|
||||
|
||||
std::string filename = filepath;
|
||||
if (auto pos = filename.rfind('/'); pos != std::string::npos) {
|
||||
filename = filename.substr(pos + 1);
|
||||
}
|
||||
|
||||
return filename.find("mmproj") == std::string::npos &&
|
||||
filename.find("imatrix") == std::string::npos;
|
||||
}
|
||||
|
||||
static hf_cache::hf_file find_best_model(const hf_cache::hf_files & files,
|
||||
const std::string & tag) {
|
||||
std::vector<std::string> tags;
|
||||
@@ -559,18 +589,27 @@ static hf_cache::hf_file find_best_model(const hf_cache::hf_files & files,
|
||||
for (const auto & t : tags) {
|
||||
std::regex pattern(t + "[.-]", std::regex::icase);
|
||||
for (const auto & f : files) {
|
||||
if (string_ends_with(f.path, ".gguf") &&
|
||||
f.path.find("mmproj") == std::string::npos &&
|
||||
if (gguf_filename_is_model(f.path) &&
|
||||
std::regex_search(f.path, pattern)) {
|
||||
auto split = get_gguf_split_info(f.path);
|
||||
if (split.count > 1 && split.index != 1) {
|
||||
continue;
|
||||
}
|
||||
return f;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
for (const auto & f : files) {
|
||||
if (string_ends_with(f.path, ".gguf") &&
|
||||
f.path.find("mmproj") == std::string::npos) {
|
||||
return f;
|
||||
// fallback to first available model only if tag is empty
|
||||
if (tag.empty()) {
|
||||
for (const auto & f : files) {
|
||||
if (gguf_filename_is_model(f.path)) {
|
||||
auto split = get_gguf_split_info(f.path);
|
||||
if (split.count > 1 && split.index != 1) {
|
||||
continue;
|
||||
}
|
||||
return f;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -587,6 +626,7 @@ static void list_available_gguf_files(const hf_cache::hf_files & files) {
|
||||
}
|
||||
|
||||
struct hf_plan {
|
||||
hf_cache::hf_file primary;
|
||||
hf_cache::hf_files model_files;
|
||||
hf_cache::hf_file mmproj;
|
||||
};
|
||||
@@ -632,6 +672,7 @@ static hf_plan get_hf_plan(const common_params_model & model,
|
||||
}
|
||||
}
|
||||
|
||||
plan.primary = primary;
|
||||
plan.model_files = get_split_files(all, primary);
|
||||
|
||||
if (opts.download_mmproj) {
|
||||
@@ -718,7 +759,7 @@ common_download_model_result common_download_model(const common_params_model
|
||||
for (const auto & f : hf.model_files) {
|
||||
hf_cache::finalize_file(f);
|
||||
}
|
||||
result.model_path = hf.model_files[0].final_path;
|
||||
result.model_path = hf.primary.final_path;
|
||||
|
||||
if (!hf.mmproj.path.empty()) {
|
||||
result.mmproj_path = hf_cache::finalize_file(hf.mmproj);
|
||||
|
||||
@@ -26,6 +26,8 @@ namespace nl = nlohmann;
|
||||
#include <windows.h>
|
||||
#else
|
||||
#define HOME_DIR "HOME"
|
||||
#include <unistd.h>
|
||||
#include <pwd.h>
|
||||
#endif
|
||||
|
||||
namespace hf_cache {
|
||||
@@ -38,6 +40,7 @@ static fs::path get_cache_directory() {
|
||||
const char * var;
|
||||
fs::path path;
|
||||
} entries[] = {
|
||||
{"LLAMA_CACHE", fs::path()},
|
||||
{"HF_HUB_CACHE", fs::path()},
|
||||
{"HUGGINGFACE_HUB_CACHE", fs::path()},
|
||||
{"HF_HOME", fs::path("hub")},
|
||||
@@ -50,6 +53,13 @@ static fs::path get_cache_directory() {
|
||||
return entry.path.empty() ? base : base / entry.path;
|
||||
}
|
||||
}
|
||||
#ifndef _WIN32
|
||||
const struct passwd * pw = getpwuid(getuid());
|
||||
|
||||
if (pw->pw_dir && *pw->pw_dir) {
|
||||
return fs::path(pw->pw_dir) / ".cache" / "huggingface" / "hub";
|
||||
}
|
||||
#endif
|
||||
throw std::runtime_error("Failed to determine HF cache directory");
|
||||
}();
|
||||
|
||||
@@ -325,9 +335,15 @@ 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());
|
||||
@@ -487,6 +503,34 @@ std::string finalize_file(const hf_file & file) {
|
||||
|
||||
// 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;
|
||||
@@ -504,25 +548,30 @@ static std::string make_old_cache_filename(const std::string & owner,
|
||||
return result;
|
||||
}
|
||||
|
||||
static bool migrate_single_file(const fs::path & old_cache,
|
||||
const std::string & owner,
|
||||
const std::string & repo,
|
||||
const nl::json & node,
|
||||
const hf_files & files) {
|
||||
struct migrate_file {
|
||||
std::string path;
|
||||
std::string sha256;
|
||||
size_t size;
|
||||
fs::path old_path;
|
||||
fs::path etag_path;
|
||||
const hf_file * file;
|
||||
};
|
||||
|
||||
if (!node.contains("rfilename") ||
|
||||
!node.contains("lfs") ||
|
||||
!node["lfs"].contains("sha256")) {
|
||||
return false;
|
||||
}
|
||||
using migrate_files = std::vector<migrate_file>;
|
||||
|
||||
std::string path = node["rfilename"];
|
||||
std::string sha256 = node["lfs"]["sha256"];
|
||||
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;
|
||||
|
||||
const hf_file * file_info = nullptr;
|
||||
for (const auto & f : files) {
|
||||
if (f.path == path) {
|
||||
file_info = &f;
|
||||
file = &f;
|
||||
break;
|
||||
}
|
||||
}
|
||||
@@ -532,50 +581,104 @@ static bool migrate_single_file(const fs::path & old_cache,
|
||||
fs::path etag_path = old_path.string() + ".etag";
|
||||
|
||||
if (!fs::exists(old_path)) {
|
||||
if (fs::exists(etag_path)) {
|
||||
LOG_WRN("%s: %s is orphan, deleting...\n", __func__, etag_path.string().c_str());
|
||||
fs::remove(etag_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;
|
||||
}
|
||||
|
||||
bool delete_old_path = false;
|
||||
|
||||
if (!file_info) {
|
||||
LOG_WRN("%s: %s not found in current repo, deleting...\n", __func__, old_filename.c_str());
|
||||
delete_old_path = true;
|
||||
} else if (!sha256.empty() && !file_info->oid.empty() && sha256 != file_info->oid) {
|
||||
LOG_WRN("%s: %s is not up to date (sha256 mismatch), deleting...\n", __func__, old_filename.c_str());
|
||||
delete_old_path = true;
|
||||
if (!file) {
|
||||
LOG_WRN("%s: %s not found in current repo\n", __func__, old_filename.c_str());
|
||||
return false;
|
||||
}
|
||||
|
||||
std::error_code ec;
|
||||
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 (delete_old_path) {
|
||||
fs::remove(old_path, ec);
|
||||
fs::remove(etag_path, ec);
|
||||
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;
|
||||
}
|
||||
|
||||
fs::path new_path(file_info->local_path);
|
||||
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(old_path, new_path, ec);
|
||||
fs::rename(file.old_path, new_path, ec);
|
||||
if (ec) {
|
||||
fs::copy_file(old_path, new_path, ec);
|
||||
fs::copy_file(file.old_path, new_path, ec);
|
||||
if (ec) {
|
||||
LOG_WRN("%s: failed to move/copy %s: %s\n", __func__, old_path.string().c_str(), ec.message().c_str());
|
||||
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(old_path, ec);
|
||||
fs::remove(file.old_path, ec);
|
||||
}
|
||||
fs::remove(etag_path, ec);
|
||||
|
||||
std::string filename = finalize_file(*file_info);
|
||||
LOG_INF("%s: migrated %s -> %s\n", __func__, old_filename.c_str(), filename.c_str());
|
||||
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;
|
||||
}
|
||||
|
||||
@@ -590,6 +693,8 @@ void migrate_old_cache_to_hf_cache(const std::string & token, bool offline) {
|
||||
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;
|
||||
@@ -601,6 +706,19 @@ void migrate_old_cache_to_hf_cache(const std::string & token, bool offline) {
|
||||
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);
|
||||
|
||||
@@ -609,19 +727,43 @@ void migrate_old_cache_to_hf_cache(const std::string & token, bool offline) {
|
||||
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)) {
|
||||
migrate_single_file(old_cache, owner, repo, json[key], files);
|
||||
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());
|
||||
}
|
||||
}
|
||||
|
||||
@@ -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>;
|
||||
|
||||
@@ -539,6 +539,9 @@ private:
|
||||
statement_ptr step = slices.size() > 2 ? std::move(slices[2]) : nullptr;
|
||||
return mk_stmt<slice_expression>(start_pos, std::move(start), std::move(stop), std::move(step));
|
||||
}
|
||||
if (slices.empty()) {
|
||||
return mk_stmt<blank_expression>(start_pos);
|
||||
}
|
||||
return std::move(slices[0]);
|
||||
}
|
||||
|
||||
|
||||
@@ -306,6 +306,19 @@ value filter_expression::execute_impl(context & ctx) {
|
||||
filter_id = "strip"; // alias
|
||||
}
|
||||
JJ_DEBUG("Applying filter '%s' to %s", filter_id.c_str(), input->type().c_str());
|
||||
// TODO: Refactor filters so this coercion can be done automatically
|
||||
if (!input->is_undefined() && !is_val<value_string>(input) && (
|
||||
filter_id == "capitalize" ||
|
||||
filter_id == "lower" ||
|
||||
filter_id == "replace" ||
|
||||
filter_id == "strip" ||
|
||||
filter_id == "title" ||
|
||||
filter_id == "upper" ||
|
||||
filter_id == "wordcount"
|
||||
)) {
|
||||
JJ_DEBUG("Coercing %s to String for '%s' filter", input->type().c_str(), filter_id.c_str());
|
||||
input = mk_val<value_string>(input->as_string());
|
||||
}
|
||||
return try_builtin_func(ctx, filter_id, input)->invoke(func_args(ctx));
|
||||
|
||||
} else if (is_stmt<call_expression>(filter)) {
|
||||
@@ -667,8 +680,9 @@ value macro_statement::execute_impl(context & ctx) {
|
||||
if (is_stmt<identifier>(this->args[i])) {
|
||||
// normal parameter
|
||||
std::string param_name = cast_stmt<identifier>(this->args[i])->val;
|
||||
JJ_DEBUG(" Binding parameter '%s' to argument of type %s", param_name.c_str(), args.get_pos(i)->type().c_str());
|
||||
macro_ctx.set_val(param_name, args.get_pos(i));
|
||||
value param_value = args.get_kwarg_or_pos(param_name, i);
|
||||
JJ_DEBUG(" Binding parameter '%s' to argument of type %s", param_name.c_str(), param_value->type().c_str());
|
||||
macro_ctx.set_val(param_name, param_value);
|
||||
} else if (is_stmt<keyword_argument_expression>(this->args[i])) {
|
||||
// default argument used as normal parameter
|
||||
auto kwarg = cast_stmt<keyword_argument_expression>(this->args[i]);
|
||||
@@ -676,8 +690,9 @@ value macro_statement::execute_impl(context & ctx) {
|
||||
throw std::runtime_error("Keyword argument key must be an identifier in macro '" + name + "'");
|
||||
}
|
||||
std::string param_name = cast_stmt<identifier>(kwarg->key)->val;
|
||||
JJ_DEBUG(" Binding parameter '%s' to argument of type %s", param_name.c_str(), args.get_pos(i)->type().c_str());
|
||||
macro_ctx.set_val(param_name, args.get_pos(i));
|
||||
value param_value = args.get_kwarg_or_pos(param_name, i);
|
||||
JJ_DEBUG(" Binding parameter '%s' to argument of type %s", param_name.c_str(), param_value->type().c_str());
|
||||
macro_ctx.set_val(param_name, param_value);
|
||||
} else {
|
||||
throw std::runtime_error("Invalid parameter type in macro '" + name + "'");
|
||||
}
|
||||
@@ -769,10 +784,15 @@ value member_expression::execute_impl(context & ctx) {
|
||||
}
|
||||
|
||||
JJ_DEBUG("Member expression on object type %s, property type %s", object->type().c_str(), property->type().c_str());
|
||||
ensure_key_type_allowed(property);
|
||||
|
||||
value val = mk_val<value_undefined>("object_property");
|
||||
|
||||
if (property->is_undefined()) {
|
||||
JJ_DEBUG("%s", "Member expression property is undefined, returning undefined");
|
||||
return val;
|
||||
}
|
||||
|
||||
ensure_key_type_allowed(property);
|
||||
|
||||
if (is_val<value_undefined>(object)) {
|
||||
JJ_DEBUG("%s", "Accessing property on undefined object, returning undefined");
|
||||
return val;
|
||||
|
||||
@@ -263,6 +263,14 @@ struct comment_statement : public statement {
|
||||
|
||||
// Expressions
|
||||
|
||||
// Represents an omitted expression in a computed member, e.g. `a[]`.
|
||||
struct blank_expression : public expression {
|
||||
std::string type() const override { return "BlankExpression"; }
|
||||
value execute_impl(context &) override {
|
||||
return mk_val<value_undefined>();
|
||||
}
|
||||
};
|
||||
|
||||
struct member_expression : public expression {
|
||||
statement_ptr object;
|
||||
statement_ptr property;
|
||||
|
||||
@@ -465,8 +465,9 @@ const func_builtins & value_int_t::get_builtins() const {
|
||||
double val = static_cast<double>(args.get_pos(0)->as_int());
|
||||
return mk_val<value_float>(val);
|
||||
}},
|
||||
{"tojson", tojson},
|
||||
{"safe", tojson},
|
||||
{"string", tojson},
|
||||
{"tojson", tojson},
|
||||
};
|
||||
return builtins;
|
||||
}
|
||||
@@ -485,8 +486,9 @@ const func_builtins & value_float_t::get_builtins() const {
|
||||
int64_t val = static_cast<int64_t>(args.get_pos(0)->as_float());
|
||||
return mk_val<value_int>(val);
|
||||
}},
|
||||
{"tojson", tojson},
|
||||
{"safe", tojson},
|
||||
{"string", tojson},
|
||||
{"tojson", tojson},
|
||||
};
|
||||
return builtins;
|
||||
}
|
||||
@@ -771,6 +773,11 @@ const func_builtins & value_string_t::get_builtins() const {
|
||||
|
||||
|
||||
const func_builtins & value_bool_t::get_builtins() const {
|
||||
static const func_handler tostring = [](const func_args & args) -> value {
|
||||
args.ensure_vals<value_bool>();
|
||||
bool val = args.get_pos(0)->as_bool();
|
||||
return mk_val<value_string>(val ? "True" : "False");
|
||||
};
|
||||
static const func_builtins builtins = {
|
||||
{"default", default_value},
|
||||
{"int", [](const func_args & args) -> value {
|
||||
@@ -783,11 +790,8 @@ const func_builtins & value_bool_t::get_builtins() const {
|
||||
bool val = args.get_pos(0)->as_bool();
|
||||
return mk_val<value_float>(val ? 1.0 : 0.0);
|
||||
}},
|
||||
{"string", [](const func_args & args) -> value {
|
||||
args.ensure_vals<value_bool>();
|
||||
bool val = args.get_pos(0)->as_bool();
|
||||
return mk_val<value_string>(val ? "True" : "False");
|
||||
}},
|
||||
{"safe", tostring},
|
||||
{"string", tostring},
|
||||
{"tojson", tojson},
|
||||
};
|
||||
return builtins;
|
||||
@@ -1100,18 +1104,14 @@ const func_builtins & value_object_t::get_builtins() const {
|
||||
}
|
||||
|
||||
const func_builtins & value_none_t::get_builtins() const {
|
||||
static const func_handler tostring = [](const func_args &) -> value {
|
||||
return mk_val<value_string>("None");
|
||||
};
|
||||
static const func_builtins builtins = {
|
||||
{"default", default_value},
|
||||
{"tojson", tojson},
|
||||
{"string", [](const func_args &) -> value {
|
||||
return mk_val<value_string>("None");
|
||||
}},
|
||||
{"safe", [](const func_args &) -> value {
|
||||
return mk_val<value_string>("None");
|
||||
}},
|
||||
{"strip", [](const func_args &) -> value {
|
||||
return mk_val<value_string>("None");
|
||||
}},
|
||||
{"string", tostring},
|
||||
{"safe", tostring},
|
||||
{"items", empty_value_fn<value_array>},
|
||||
{"map", empty_value_fn<value_array>},
|
||||
{"reject", empty_value_fn<value_array>},
|
||||
|
||||
@@ -416,15 +416,30 @@ private:
|
||||
i++;
|
||||
} else if (c == '(') {
|
||||
i++;
|
||||
if (i < length) {
|
||||
if (sub_pattern[i] == '?') {
|
||||
if (i < length && sub_pattern[i] == '?') {
|
||||
if (i + 1 < length && sub_pattern[i + 1] == ':') {
|
||||
i += 2; // skip "?:" for non-capturing group, treat as regular group
|
||||
} else {
|
||||
// lookahead/lookbehind (?=, ?!, ?<=, ?<!) - not supported
|
||||
_warnings.push_back("Unsupported pattern syntax");
|
||||
// skip to matching ')' to avoid UB on empty seq
|
||||
int depth = 1;
|
||||
while (i < length && depth > 0) {
|
||||
if (sub_pattern[i] == '\\' && i + 1 < length) {
|
||||
i += 2; // skip escaped character
|
||||
} else {
|
||||
if (sub_pattern[i] == '(') depth++;
|
||||
else if (sub_pattern[i] == ')') depth--;
|
||||
i++;
|
||||
}
|
||||
}
|
||||
continue;
|
||||
}
|
||||
}
|
||||
seq.emplace_back("(" + to_rule(transform()) + ")", false);
|
||||
} else if (c == ')') {
|
||||
i++;
|
||||
if (start > 0 && sub_pattern[start - 1] != '(') {
|
||||
if (start > 0 && sub_pattern[start - 1] != '(' && (start < 2 || sub_pattern[start - 2] != '?' || sub_pattern[start - 1] != ':')) {
|
||||
_errors.push_back("Unbalanced parentheses");
|
||||
}
|
||||
return join_seq();
|
||||
|
||||
@@ -51,7 +51,7 @@ struct common_ngram_map_value {
|
||||
// statistics of a n-gram
|
||||
struct common_ngram_map_key {
|
||||
size_t key_idx; // index of key n-gram in token-history
|
||||
size_t stat_idx; // index of last token of stastistics computation (key_num, values)
|
||||
size_t stat_idx; // index of last token of statistics computation (key_num, values)
|
||||
|
||||
uint16_t key_num; // number of occurrences of this key n-gram in token-history
|
||||
common_ngram_map_value values[COMMON_NGRAM_MAX_VALUES]; // some known values after the key
|
||||
|
||||
@@ -256,6 +256,38 @@ static std::pair<std::vector<common_peg_chars_parser::char_range>, bool> parse_c
|
||||
return {ranges, negated};
|
||||
}
|
||||
|
||||
common_peg_ast_id common_peg_ast_arena::find_by_tag(const common_peg_ast_node & parent, const std::string & tag, int max_depth) const {
|
||||
for (auto child_id : parent.children) {
|
||||
const auto & child = get(child_id);
|
||||
if (child.tag == tag) {
|
||||
return child_id;
|
||||
}
|
||||
if (max_depth > 1) {
|
||||
auto result = find_by_tag(child, tag, max_depth - 1);
|
||||
if (result != COMMON_PEG_INVALID_AST_ID) {
|
||||
return result;
|
||||
}
|
||||
}
|
||||
}
|
||||
return COMMON_PEG_INVALID_AST_ID;
|
||||
}
|
||||
|
||||
common_peg_ast_id common_peg_ast_arena::find_by_rule(const common_peg_ast_node & parent, const std::string & rule, int max_depth) const {
|
||||
for (auto child_id : parent.children) {
|
||||
const auto & child = get(child_id);
|
||||
if (child.rule == rule) {
|
||||
return child_id;
|
||||
}
|
||||
if (max_depth > 1) {
|
||||
auto result = find_by_rule(child, rule, max_depth - 1);
|
||||
if (result != COMMON_PEG_INVALID_AST_ID) {
|
||||
return result;
|
||||
}
|
||||
}
|
||||
}
|
||||
return COMMON_PEG_INVALID_AST_ID;
|
||||
}
|
||||
|
||||
void common_peg_ast_arena::visit(common_peg_ast_id id, const common_peg_ast_visitor & visitor) const {
|
||||
if (id == COMMON_PEG_INVALID_AST_ID) {
|
||||
return;
|
||||
@@ -1557,6 +1589,52 @@ static std::unordered_set<std::string> collect_reachable_rules(
|
||||
|
||||
// GBNF generation implementation
|
||||
void common_peg_arena::build_grammar(const common_grammar_builder & builder, bool lazy) const {
|
||||
auto schema_delegates = [](const common_peg_schema_parser & s) -> bool {
|
||||
if (!s.schema) {
|
||||
return true;
|
||||
}
|
||||
if (s.raw && s.schema->contains("type")) {
|
||||
const auto & type_val = s.schema->at("type");
|
||||
if (type_val.is_string() && type_val == "string") {
|
||||
return true;
|
||||
}
|
||||
// Handle nullable types like ["string", "null"] - delegate when the
|
||||
// non-null type is string, since the tagged format uses raw text
|
||||
if (type_val.is_array()) {
|
||||
for (const auto & t : type_val) {
|
||||
if (t.is_string() && t.get<std::string>() != "null") {
|
||||
return t.get<std::string>() == "string";
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
// Delegate for enum schemas in raw mode - enum values are literal strings
|
||||
if (s.raw && !s.schema->contains("type") && s.schema->contains("enum")) {
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
};
|
||||
|
||||
// Unwrap the parser so we can properly check if it's a sequence or choice
|
||||
auto effective_parser = [&](common_peg_parser_id id) -> const common_peg_parser_variant & {
|
||||
while (true) {
|
||||
const auto & p = parsers_.at(id);
|
||||
if (const auto * tag = std::get_if<common_peg_tag_parser>(&p)) {
|
||||
id = tag->child;
|
||||
} else if (const auto * atomic = std::get_if<common_peg_atomic_parser>(&p)) {
|
||||
id = atomic->child;
|
||||
} else if (const auto * schema = std::get_if<common_peg_schema_parser>(&p)) {
|
||||
if (schema_delegates(*schema)) {
|
||||
id = schema->child;
|
||||
} else {
|
||||
return p;
|
||||
}
|
||||
} else {
|
||||
return p;
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// Generate GBNF for a parser
|
||||
std::function<std::string(common_peg_parser_id)> to_gbnf = [&](common_peg_parser_id id) -> std::string {
|
||||
const auto & parser = parsers_.at(id);
|
||||
@@ -1577,7 +1655,7 @@ void common_peg_arena::build_grammar(const common_grammar_builder & builder, boo
|
||||
s += " ";
|
||||
}
|
||||
auto child_gbnf = to_gbnf(child);
|
||||
const auto & child_parser = parsers_.at(child);
|
||||
const auto & child_parser = effective_parser(child);
|
||||
if (std::holds_alternative<common_peg_choice_parser>(child_parser) ||
|
||||
std::holds_alternative<common_peg_sequence_parser>(child_parser)) {
|
||||
s += "(" + child_gbnf + ")";
|
||||
@@ -1593,7 +1671,7 @@ void common_peg_arena::build_grammar(const common_grammar_builder & builder, boo
|
||||
s += " | ";
|
||||
}
|
||||
auto child_gbnf = to_gbnf(child);
|
||||
const auto & child_parser = parsers_.at(child);
|
||||
const auto & child_parser = effective_parser(child);
|
||||
if (std::holds_alternative<common_peg_choice_parser>(child_parser)) {
|
||||
s += "(" + child_gbnf + ")";
|
||||
} else {
|
||||
@@ -1603,7 +1681,7 @@ void common_peg_arena::build_grammar(const common_grammar_builder & builder, boo
|
||||
return s;
|
||||
} else if constexpr (std::is_same_v<T, common_peg_repetition_parser>) {
|
||||
auto child_gbnf = to_gbnf(p.child);
|
||||
const auto & child_parser = parsers_.at(p.child);
|
||||
const auto & child_parser = effective_parser(p.child);
|
||||
if (std::holds_alternative<common_peg_choice_parser>(child_parser) ||
|
||||
std::holds_alternative<common_peg_sequence_parser>(child_parser)) {
|
||||
child_gbnf = "(" + child_gbnf + ")";
|
||||
@@ -1663,15 +1741,10 @@ void common_peg_arena::build_grammar(const common_grammar_builder & builder, boo
|
||||
}
|
||||
return gbnf_excluding_pattern(p.delimiters);
|
||||
} else if constexpr (std::is_same_v<T, common_peg_schema_parser>) {
|
||||
if (p.schema) {
|
||||
if (p.raw && p.schema->contains("type") && p.schema->at("type").is_string() && p.schema->at("type") == "string") {
|
||||
// TODO: Implement more comprehensive grammar generation for raw strings.
|
||||
// For now, use the grammar emitted from the underlying parser.
|
||||
return to_gbnf(p.child);
|
||||
}
|
||||
return builder.add_schema(p.name, *p.schema);
|
||||
if (schema_delegates(p)) {
|
||||
return to_gbnf(p.child);
|
||||
}
|
||||
return to_gbnf(p.child);
|
||||
return builder.add_schema(p.name, *p.schema);
|
||||
} else if constexpr (std::is_same_v<T, common_peg_rule_parser>) {
|
||||
return p.name;
|
||||
} else if constexpr (std::is_same_v<T, common_peg_ref_parser>) {
|
||||
|
||||
@@ -106,6 +106,9 @@ class common_peg_ast_arena {
|
||||
|
||||
const common_peg_ast_node & get(common_peg_ast_id id) const { return nodes_.at(id); }
|
||||
|
||||
common_peg_ast_id find_by_tag(const common_peg_ast_node & parent, const std::string & tag, int max_depth = 3) const;
|
||||
common_peg_ast_id find_by_rule(const common_peg_ast_node & parent, const std::string & tag, int max_depth = 3) const;
|
||||
|
||||
size_t size() const { return nodes_.size(); }
|
||||
|
||||
void clear() { nodes_.clear(); }
|
||||
|
||||
@@ -115,9 +115,11 @@ static void common_reasoning_budget_accept(struct llama_sampler * smpl, llama_to
|
||||
break;
|
||||
}
|
||||
case REASONING_BUDGET_FORCING:
|
||||
// force_pos is advanced in apply(), not here.
|
||||
// This ensures the first forced token isn't skipped when the sampler
|
||||
// is initialized directly in FORCING state (e.g. COUNTING + budget=0)
|
||||
ctx->force_pos++;
|
||||
if (ctx->force_pos >= ctx->forced_tokens.size()) {
|
||||
ctx->state = REASONING_BUDGET_DONE;
|
||||
LOG_INF("reasoning-budget: forced sequence complete, done\n");
|
||||
}
|
||||
break;
|
||||
case REASONING_BUDGET_DONE:
|
||||
break;
|
||||
@@ -144,14 +146,6 @@ static void common_reasoning_budget_apply(struct llama_sampler * smpl, llama_tok
|
||||
cur_p->data[i].logit = -INFINITY;
|
||||
}
|
||||
}
|
||||
|
||||
// advance to next forced token (done here rather than in accept so that
|
||||
// the first forced token isn't skipped when starting in FORCING state)
|
||||
ctx->force_pos++;
|
||||
if (ctx->force_pos >= ctx->forced_tokens.size()) {
|
||||
ctx->state = REASONING_BUDGET_DONE;
|
||||
LOG_INF("reasoning-budget: forced sequence complete, done\n");
|
||||
}
|
||||
}
|
||||
|
||||
static void common_reasoning_budget_reset(struct llama_sampler * smpl) {
|
||||
@@ -261,3 +255,10 @@ struct llama_sampler * common_reasoning_budget_init(
|
||||
common_reasoning_budget_state initial_state) {
|
||||
return common_reasoning_budget_init_state(vocab, start_tokens, end_tokens, forced_tokens, budget, initial_state);
|
||||
}
|
||||
|
||||
common_reasoning_budget_state common_reasoning_budget_get_state(const struct llama_sampler * smpl) {
|
||||
if (!smpl) {
|
||||
return REASONING_BUDGET_IDLE;
|
||||
}
|
||||
return ((const common_reasoning_budget_ctx *)smpl->ctx)->state;
|
||||
}
|
||||
|
||||
@@ -51,3 +51,5 @@ struct llama_sampler * common_reasoning_budget_init(
|
||||
const std::vector<llama_token> & forced_tokens,
|
||||
int32_t budget,
|
||||
common_reasoning_budget_state initial_state);
|
||||
|
||||
common_reasoning_budget_state common_reasoning_budget_get_state(const struct llama_sampler * smpl);
|
||||
|
||||
@@ -7,6 +7,7 @@
|
||||
|
||||
#include <algorithm>
|
||||
#include <cctype>
|
||||
#include <climits>
|
||||
#include <cmath>
|
||||
#include <cstring>
|
||||
#include <unordered_map>
|
||||
@@ -109,6 +110,7 @@ struct common_sampler {
|
||||
common_params_sampling params;
|
||||
|
||||
struct llama_sampler * grmr;
|
||||
struct llama_sampler * rbudget;
|
||||
struct llama_sampler * chain;
|
||||
|
||||
ring_buffer<llama_token> prev;
|
||||
@@ -188,6 +190,7 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, st
|
||||
lparams.no_perf = params.no_perf;
|
||||
|
||||
llama_sampler * grmr = nullptr;
|
||||
llama_sampler * rbudget = nullptr;
|
||||
llama_sampler * chain = llama_sampler_chain_init(lparams);
|
||||
|
||||
std::vector<llama_sampler *> samplers;
|
||||
@@ -270,7 +273,7 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, st
|
||||
}
|
||||
}
|
||||
|
||||
if (grmr) {
|
||||
if (grmr && !params.grammar_lazy) {
|
||||
try {
|
||||
for (const auto & token : prefill_tokens) {
|
||||
llama_sampler_accept(grmr, token);
|
||||
@@ -284,15 +287,15 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, st
|
||||
}
|
||||
}
|
||||
|
||||
// reasoning budget sampler — added first so it can force tokens before other samplers
|
||||
if (params.reasoning_budget_tokens >= 0 && !params.reasoning_budget_forced.empty()) {
|
||||
samplers.push_back(common_reasoning_budget_init(
|
||||
// reasoning budget sampler
|
||||
if (!params.reasoning_budget_start.empty() && !params.reasoning_budget_end.empty()) {
|
||||
rbudget = common_reasoning_budget_init(
|
||||
vocab,
|
||||
params.reasoning_budget_start,
|
||||
params.reasoning_budget_end,
|
||||
params.reasoning_budget_forced,
|
||||
params.reasoning_budget_tokens,
|
||||
prefill_tokens));
|
||||
params.reasoning_budget_tokens < 0 ? INT_MAX : params.reasoning_budget_tokens,
|
||||
prefill_tokens);
|
||||
}
|
||||
|
||||
if (params.has_logit_bias()) {
|
||||
@@ -380,9 +383,16 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, st
|
||||
params.backend_sampling = false;
|
||||
}
|
||||
|
||||
if (rbudget && params.backend_sampling) {
|
||||
LOG_WRN("%s: backend sampling is not compatible with reasoning budget, disabling\n", __func__);
|
||||
|
||||
params.backend_sampling = false;
|
||||
}
|
||||
|
||||
auto * result = new common_sampler {
|
||||
/* .params = */ params,
|
||||
/* .grmr = */ grmr,
|
||||
/* .rbudget = */ rbudget,
|
||||
/* .chain = */ chain,
|
||||
/* .prev = */ ring_buffer<llama_token>(std::max(32, params.n_prev)),
|
||||
/* .cur = */ {},
|
||||
@@ -398,11 +408,27 @@ void common_sampler_free(struct common_sampler * gsmpl) {
|
||||
}
|
||||
|
||||
llama_sampler_free(gsmpl->grmr);
|
||||
llama_sampler_free(gsmpl->rbudget);
|
||||
llama_sampler_free(gsmpl->chain);
|
||||
|
||||
delete gsmpl;
|
||||
}
|
||||
|
||||
static bool grammar_should_apply(struct common_sampler * gsmpl) {
|
||||
if (!gsmpl->grmr) {
|
||||
return false;
|
||||
}
|
||||
if (!gsmpl->rbudget) {
|
||||
return true;
|
||||
}
|
||||
if (gsmpl->params.grammar_lazy) {
|
||||
// if grammar is lazy, only apply when reasoning budget is not active
|
||||
const auto state = common_reasoning_budget_get_state(gsmpl->rbudget);
|
||||
return state == REASONING_BUDGET_IDLE || state == REASONING_BUDGET_DONE;
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
void common_sampler_accept(struct common_sampler * gsmpl, llama_token token, bool accept_grammar) {
|
||||
if (!gsmpl) {
|
||||
return;
|
||||
@@ -410,6 +436,11 @@ void common_sampler_accept(struct common_sampler * gsmpl, llama_token token, boo
|
||||
|
||||
const auto tm = gsmpl->tm();
|
||||
|
||||
// grammar_should_apply() checks the reasoning budget state, so calculate this before we accept
|
||||
accept_grammar = accept_grammar && grammar_should_apply(gsmpl);
|
||||
|
||||
llama_sampler_accept(gsmpl->rbudget, token);
|
||||
|
||||
if (gsmpl->grmr && accept_grammar) {
|
||||
llama_sampler_accept(gsmpl->grmr, token);
|
||||
}
|
||||
@@ -431,6 +462,7 @@ struct common_sampler * common_sampler_clone(common_sampler * gsmpl) {
|
||||
return new common_sampler {
|
||||
/* .params = */ gsmpl->params,
|
||||
/* .grmr = */ llama_sampler_clone(gsmpl->grmr),
|
||||
/* .rbudget = */ llama_sampler_clone(gsmpl->rbudget),
|
||||
/* .chain = */ llama_sampler_clone(gsmpl->chain),
|
||||
/* .prev = */ gsmpl->prev,
|
||||
/* .cur = */ gsmpl->cur,
|
||||
@@ -500,6 +532,7 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
|
||||
llama_token id = LLAMA_TOKEN_NULL;
|
||||
|
||||
auto & grmr = gsmpl->grmr;
|
||||
auto & rbudget = gsmpl->rbudget;
|
||||
auto & chain = gsmpl->chain;
|
||||
auto & cur_p = gsmpl->cur_p; // initialized by set_logits
|
||||
|
||||
@@ -511,7 +544,8 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
|
||||
if (id != LLAMA_TOKEN_NULL) {
|
||||
LOG_DBG("%s: Backend sampler selected token: '%d'. Will not run any CPU samplers\n", __func__, id);
|
||||
|
||||
GGML_ASSERT(!gsmpl->grmr && "using grammar in combination with backend sampling is not supported");
|
||||
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");
|
||||
|
||||
// TODO: simplify
|
||||
gsmpl->cur.resize(1);
|
||||
@@ -524,7 +558,10 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
|
||||
|
||||
gsmpl->set_logits(ctx, idx);
|
||||
|
||||
if (grammar_first) {
|
||||
// apply reasoning budget first
|
||||
llama_sampler_apply(rbudget, &cur_p);
|
||||
|
||||
if (grammar_first && grammar_should_apply(gsmpl)) {
|
||||
llama_sampler_apply(grmr, &cur_p);
|
||||
}
|
||||
|
||||
@@ -532,7 +569,7 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
|
||||
|
||||
id = cur_p.data[cur_p.selected].id;
|
||||
|
||||
if (grammar_first) {
|
||||
if (grammar_first || !grammar_should_apply(gsmpl)) {
|
||||
return id;
|
||||
}
|
||||
|
||||
@@ -553,7 +590,12 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
|
||||
// if the token is not valid, sample again, but first apply the grammar sampler and then the sampling chain
|
||||
gsmpl->set_logits(ctx, idx);
|
||||
|
||||
llama_sampler_apply(grmr, &cur_p);
|
||||
llama_sampler_apply(rbudget, &cur_p);
|
||||
|
||||
if (grammar_should_apply(gsmpl)) {
|
||||
llama_sampler_apply(grmr, &cur_p);
|
||||
}
|
||||
|
||||
llama_sampler_apply(chain, &cur_p);
|
||||
|
||||
GGML_ASSERT(cur_p.selected != -1 && "no selected token during sampling - check your sampling configuration");
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -154,6 +154,7 @@ models = [
|
||||
{"name": "qwen35", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Qwen/Qwen3.5-9B-Instruct", },
|
||||
{"name": "joyai-llm", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jdopensource/JoyAI-LLM-Flash", },
|
||||
{"name": "kanana2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/kakaocorp/kanana-2-30b-a3b-instruct-2601", },
|
||||
{"name": "f2llmv2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/codefuse-ai/F2LLM-v2-4B", },
|
||||
]
|
||||
|
||||
# some models are known to be broken upstream, so we will skip them as exceptions
|
||||
@@ -177,6 +178,7 @@ pre_computed_hashes = [
|
||||
{"name": "grok-2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/alvarobartt/grok-2-tokenizer", "chkhsh": "66b8d4e19ab16c3bfd89bce5d785fb7e0155e8648708a1f42077cb9fe002c273"},
|
||||
# jina-v2-de variants
|
||||
{"name": "jina-v2-de", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/aari1995/German_Semantic_V3", "chkhsh": "b3d1dd861f1d4c5c0d2569ce36baf3f90fe8a102db3de50dd71ff860d91be3df"},
|
||||
{"name": "gpt-2", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/evilfreelancer/ruGPT3XL", "chkhsh": "0fe1cf6eda062318a1af7270f3331a85c539a01778ff948e24388e949c5282f4"},
|
||||
]
|
||||
|
||||
|
||||
|
||||
@@ -42,12 +42,22 @@ The llama.cpp CANN backend is designed to support Ascend NPU. It utilize the abi
|
||||
|
||||
### Ascend NPU
|
||||
|
||||
**Verified devices**
|
||||
You can retrieve your Ascend device IDs using the following command:
|
||||
|
||||
| Ascend NPU | Status |
|
||||
|:-----------------------------:|:-------:|
|
||||
| Atlas 300T A2 | Support |
|
||||
| Atlas 300I Duo | Support |
|
||||
```sh
|
||||
lspci -n | grep -Eo '19e5:d[0-9a-f]{3}' | cut -d: -f2
|
||||
```
|
||||
|
||||
**Devices**
|
||||
|
||||
| Device Id | Product Series | Product Models | Chip Model | Verified Status |
|
||||
|:---------:|----------------|----------------|:----------:|:---------------:|
|
||||
| d803 | Atlas A3 Train | | 910C | |
|
||||
| d803 | Atlas A3 Infer | | 910C | |
|
||||
| d802 | Atlas A2 Train | | 910B | |
|
||||
| d802 | Atlas A2 Infer | Atlas 300I A2 | 910B | Support |
|
||||
| d801 | Atlas Train | | 910 | |
|
||||
| d500 | Atlas Infer | Atlas 300I Duo | 310P | Support |
|
||||
|
||||
*Notes:*
|
||||
|
||||
@@ -57,6 +67,9 @@ The llama.cpp CANN backend is designed to support Ascend NPU. It utilize the abi
|
||||
|
||||
## Model Supports
|
||||
|
||||
<details>
|
||||
<summary>Text-only</summary>
|
||||
|
||||
| Model Name | FP16 | Q4_0 | Q8_0 |
|
||||
|:----------------------------|:-----:|:----:|:----:|
|
||||
| Llama-2 | √ | √ | √ |
|
||||
@@ -118,8 +131,11 @@ The llama.cpp CANN backend is designed to support Ascend NPU. It utilize the abi
|
||||
| Trillion-7B-preview | √ | √ | √ |
|
||||
| Ling models | √ | √ | √ |
|
||||
|
||||
</details>
|
||||
|
||||
<details>
|
||||
<summary>Multimodal</summary>
|
||||
|
||||
**Multimodal**
|
||||
| Model Name | FP16 | Q4_0 | Q8_0 |
|
||||
|:----------------------------|:-----:|:----:|:----:|
|
||||
| LLaVA 1.5 models, LLaVA 1.6 models | x | x | x |
|
||||
@@ -134,15 +150,22 @@ The llama.cpp CANN backend is designed to support Ascend NPU. It utilize the abi
|
||||
| GLM-EDGE | √ | √ | √ |
|
||||
| Qwen2-VL | √ | √ | √ |
|
||||
|
||||
</details>
|
||||
|
||||
|
||||
|
||||
## DataType Supports
|
||||
|
||||
| DataType | Status |
|
||||
|:----------------------:|:-------:|
|
||||
| FP16 | Support |
|
||||
| Q8_0 | Support |
|
||||
| Q4_0 | Support |
|
||||
| DataType | 910B | 310P |
|
||||
|:----------------------:|:-------:|:-------:|
|
||||
| FP16 | Support | Support |
|
||||
| Q8_0 | Support | Partial |
|
||||
| Q4_0 | Support | Partial |
|
||||
| BF16 | Support | |
|
||||
|
||||
> **310P note**
|
||||
> - `Q8_0`: data transform / buffer path is implemented, and `GET_ROWS` is supported, but quantized `MUL_MAT` / `MUL_MAT_ID` are not supported.
|
||||
> - `Q4_0`: data transform / buffer path is implemented, but quantized `MUL_MAT` / `MUL_MAT_ID` are not supported.
|
||||
|
||||
## Docker
|
||||
|
||||
@@ -160,7 +183,20 @@ npu-smi info
|
||||
|
||||
# Select the cards that you want to use, make sure these cards are not used by someone.
|
||||
# Following using cards of device0.
|
||||
docker run --name llamacpp --device /dev/davinci0 --device /dev/davinci_manager --device /dev/devmm_svm --device /dev/hisi_hdc -v /usr/local/dcmi:/usr/local/dcmi -v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi -v /usr/local/Ascend/driver/lib64/:/usr/local/Ascend/driver/lib64/ -v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info -v /PATH_TO_YOUR_MODELS/:/app/models -it llama-cpp-cann -m /app/models/MODEL_PATH -ngl 32 -p "Building a website can be done in 10 simple steps:"
|
||||
docker run --name llamacpp \
|
||||
--device /dev/davinci0 \
|
||||
--device /dev/davinci_manager \
|
||||
--device /dev/devmm_svm \
|
||||
--device /dev/hisi_hdc \
|
||||
-v /usr/local/dcmi:/usr/local/dcmi \
|
||||
-v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
|
||||
-v /usr/local/Ascend/driver/lib64/:/usr/local/Ascend/driver/lib64/ \
|
||||
-v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
|
||||
-v /PATH_TO_YOUR_MODELS/:/app/models \
|
||||
-it llama-cpp-cann \
|
||||
-m /app/models/MODEL_PATH \
|
||||
-ngl 32 \
|
||||
-p "Building a website can be done in 10 simple steps:"
|
||||
```
|
||||
|
||||
*Notes:*
|
||||
@@ -171,69 +207,57 @@ docker run --name llamacpp --device /dev/davinci0 --device /dev/davinci_manager
|
||||
|
||||
### I. Setup Environment
|
||||
|
||||
1. **Install Ascend Driver and firmware**
|
||||
1. **Configure Ascend user and group**
|
||||
|
||||
```sh
|
||||
# create driver running user.
|
||||
sudo groupadd -g HwHiAiUser
|
||||
sudo groupadd HwHiAiUser
|
||||
sudo useradd -g HwHiAiUser -d /home/HwHiAiUser -m HwHiAiUser -s /bin/bash
|
||||
sudo usermod -aG HwHiAiUser $USER
|
||||
|
||||
# download driver from https://www.hiascend.com/hardware/firmware-drivers/community according to your system
|
||||
# and install driver.
|
||||
sudo sh Ascend-hdk-910b-npu-driver_x.x.x_linux-{arch}.run --full --install-for-all
|
||||
```
|
||||
|
||||
Once installed, run `npu-smi info` to check whether driver is installed successfully.
|
||||
2. **Install dependencies**
|
||||
|
||||
**Ubuntu/Debian:**
|
||||
```sh
|
||||
+-------------------------------------------------------------------------------------------+
|
||||
| npu-smi 24.1.rc2 Version: 24.1.rc2 |
|
||||
+----------------------+---------------+----------------------------------------------------+
|
||||
| NPU Name | Health | Power(W) Temp(C) Hugepages-Usage(page)|
|
||||
| Chip | Bus-Id | AICore(%) Memory-Usage(MB) HBM-Usage(MB) |
|
||||
+======================+===============+====================================================+
|
||||
| 2 xxx | OK | 64.4 51 15 / 15 |
|
||||
| 0 | 0000:01:00.0 | 0 1873 / 15077 0 / 32768 |
|
||||
+======================+===============+====================================================+
|
||||
| 5 xxx | OK | 64.0 52 15 / 15 |
|
||||
| 0 | 0000:81:00.0 | 0 1874 / 15077 0 / 32768 |
|
||||
+======================+===============+====================================================+
|
||||
| No running processes found in NPU 2 |
|
||||
+======================+===============+====================================================+
|
||||
| No running processes found in NPU 5 |
|
||||
+======================+===============+====================================================+
|
||||
sudo apt-get update
|
||||
sudo apt-get install -y gcc python3 python3-pip linux-headers-$(uname -r)
|
||||
```
|
||||
|
||||
2. **Install Ascend Firmware**
|
||||
**RHEL/CentOS:**
|
||||
```sh
|
||||
# download driver from https://www.hiascend.com/hardware/firmware-drivers/community according to your system
|
||||
# and install driver.
|
||||
sudo sh Ascend-hdk-910b-npu-firmware_x.x.x.x.X.run --full
|
||||
sudo yum makecache
|
||||
sudo yum install -y gcc python3 python3-pip kernel-headers-$(uname -r) kernel-devel-$(uname -r)
|
||||
```
|
||||
If the following message appears, firmware is installed successfully.
|
||||
|
||||
3. **Install CANN (driver + toolkit)**
|
||||
|
||||
> The `Ascend-cann` package includes both the driver and toolkit.
|
||||
> `$ARCH` can be `x86_64` or `aarch64`, `$CHIP` can be `910b` or `310p`.
|
||||
|
||||
```sh
|
||||
Firmware package installed successfully!
|
||||
wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/CANN/CANN%208.5.T63/Ascend-cann_8.5.0_linux-$ARCH.run
|
||||
sudo bash ./Ascend-cann_8.5.0_linux-$ARCH.run --install
|
||||
|
||||
wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/CANN/CANN%208.5.T63/Ascend-cann-$CHIP-ops_8.5.0_linux-$ARCH.run
|
||||
sudo bash ./Ascend-cann-$CHIP-ops_8.5.0_linux-$ARCH.run --install
|
||||
```
|
||||
|
||||
4. **Verify installation**
|
||||
|
||||
3. **Install CANN toolkit and kernels**
|
||||
|
||||
CANN toolkit and kernels can be obtained from the official [CANN Toolkit](https://www.hiascend.com/zh/developer/download/community/result?module=cann) page.
|
||||
|
||||
Please download the corresponding version that satified your system. The minimum version required is 8.0.RC2.alpha002 and here is the install command.
|
||||
```sh
|
||||
pip3 install attrs numpy decorator sympy cffi pyyaml pathlib2 psutil protobuf scipy requests absl-py wheel typing_extensions
|
||||
sh Ascend-cann-toolkit_8.0.RC2.alpha002_linux-aarch64.run --install
|
||||
sh Ascend-cann-kernels-910b_8.0.RC2.alpha002_linux.run --install
|
||||
npu-smi info
|
||||
```
|
||||
|
||||
Set Ascend Variables:
|
||||
If device information is displayed correctly, the driver is functioning properly.
|
||||
|
||||
```sh
|
||||
echo "source ~/Ascend/ascend-toolkit/set_env.sh" >> ~/.bashrc
|
||||
source ~/.bashrc
|
||||
# Set environment variables (adjust path if needed)
|
||||
source /usr/local/Ascend/cann/set_env.sh
|
||||
|
||||
python3 -c "import acl; print(acl.get_soc_name())"
|
||||
```
|
||||
|
||||
Upon a successful installation, CANN is enabled for the available ascend devices.
|
||||
If the command outputs the chip model, the installation was successful.
|
||||
|
||||
### II. Build llama.cpp
|
||||
|
||||
|
||||
@@ -1,6 +1,9 @@
|
||||
# OpenVINO Backend for llama.cpp
|
||||
[OpenVINO](https://docs.openvino.ai/) is an open-source toolkit for optimizing and deploying high-performance AI inference, specifically designed for Intel hardware, including CPUs, GPUs, and NPUs, in the cloud, on-premises, and on the edge.
|
||||
This document describes the [OpenVINO backend for llama.cpp](../../src/ggml-openvino), which enables hardware-accelerated inference on **Intel® CPUs, GPUs, and NPUs** while remaining compatible with the existing **GGUF model ecosystem**. The backend translates GGML compute graphs into OpenVINO graphs and leverages graph compilation, kernel fusion, and device-specific optimizations to improve inference performance on supported Intel hardware.
|
||||
|
||||
> [!NOTE]
|
||||
> Performance and memory optimizations, accuracy validation, broader quantization coverage, broader operator and model support are work in progress.
|
||||
|
||||
[OpenVINO](https://docs.openvino.ai/) is an open-source toolkit for optimizing and deploying high-performance AI inference, specifically designed for Intel hardware, including CPUs, GPUs, and NPUs, in the cloud, on-premises, and on the edge. [OpenVINO backend for llama.cpp](../../src/ggml-openvino) enables hardware-accelerated inference on **Intel® CPUs, GPUs, and NPUs** while remaining compatible with the existing **GGUF model ecosystem**. The backend translates GGML compute graphs into OpenVINO graphs and leverages graph compilation, kernel fusion, and device-specific optimizations to improve inference performance on supported Intel hardware.
|
||||
|
||||
The OpenVINO backend is implemented in `ggml/src/ggml-openvino` and provides a translation layer for core GGML operations. The OpenVINO backend replaces the standard GGML graph execution path with Intel's OpenVINO inference engine. This approach allows the same GGUF model file to run on Intel CPUs, Intel GPUs (integrated and discrete), and Intel NPUs without changes to the model or the rest of the llama.cpp stack. When a `ggml_cgraph` is dispatched to OpenVINO backend, it:
|
||||
|
||||
@@ -179,31 +182,73 @@ curl -L https://huggingface.co/unsloth/Llama-3.2-1B-Instruct-GGUF/resolve/main/L
|
||||
|
||||
When using the OpenVINO backend, the first inference token may have slightly higher latency due to on-the-fly conversion to the OpenVINO graph. Subsequent tokens and runs will be faster.
|
||||
|
||||
> [!NOTE]
|
||||
> Default context size is set to the model training context, which may be very large. For example, 131072 for Llama 3.2 1B, which may result in lower performance, especially on edge/laptop devices. Use `-c` to limit context size in supported llama.cpp tools for better performance. For example, `-c 512`.
|
||||
|
||||
```bash
|
||||
# If device is unset or unavailable, defaults to CPU.
|
||||
# If the system has multiple GPUs, use GPU.0 or GPU.1 to explicitly target a specific GPU.
|
||||
|
||||
# Linux
|
||||
export GGML_OPENVINO_DEVICE=GPU
|
||||
# Enable stateful execution with GPU device to avoid known stateless execution failures.
|
||||
export GGML_OPENVINO_STATEFUL_EXECUTION=1
|
||||
# To run llama-simple:
|
||||
./build/ReleaseOV/bin/llama-simple -m ~/models/Llama-3.2-1B-Instruct-Q4_0.gguf -n 50 "The story of AI is "
|
||||
# To run in chat mode:
|
||||
./build/ReleaseOV/bin/llama-cli -m ~/models/Llama-3.2-1B-Instruct-Q4_0.gguf
|
||||
./build/ReleaseOV/bin/llama-cli -m ~/models/Llama-3.2-1B-Instruct-Q4_0.gguf -c 1024
|
||||
# To run llama-bench, -fa 1 is needed
|
||||
GGML_OPENVINO_STATEFUL_EXECUTION=1 GGML_OPENVINO_DEVICE=GPU ./build/ReleaseOV/bin/llama-bench -m ~/models/Llama-3.2-1B-Instruct-Q4_0.gguf -fa 1
|
||||
|
||||
# NPU: keep context small to avoid failures from very large model context windows.
|
||||
export GGML_OPENVINO_DEVICE=NPU
|
||||
./build/ReleaseOV/bin/llama-cli -m ~/models/Llama-3.2-1B-Instruct-Q4_0.gguf -c 512
|
||||
|
||||
# Windows Command Line
|
||||
set GGML_OPENVINO_DEVICE=GPU
|
||||
# Enable stateful execution with GPU device to avoid known stateless execution failures.
|
||||
set GGML_OPENVINO_STATEFUL_EXECUTION=1
|
||||
# Windows PowerShell
|
||||
$env:GGML_OPENVINO_DEVICE = "GPU"
|
||||
$env:GGML_OPENVINO_STATEFUL_EXECUTION = "1"
|
||||
|
||||
# To run llama-simple
|
||||
build\ReleaseOV\bin\llama-simple.exe -m "C:\models\Llama-3.2-1B-Instruct-Q4_0.gguf" -n 50 "The story of AI is "
|
||||
# To run in chat mode:
|
||||
build\ReleaseOV\bin\llama-cli.exe -m "C:\models\Llama-3.2-1B-Instruct-Q4_0.gguf"
|
||||
build\ReleaseOV\bin\llama-cli.exe -m "C:\models\Llama-3.2-1B-Instruct-Q4_0.gguf" -c 1024
|
||||
# To run llama-bench, -fa 1 is needed
|
||||
build\ReleaseOV\bin\llama-bench.exe -m "C:\models\Llama-3.2-1B-Instruct-Q4_0.gguf" -fa 1
|
||||
|
||||
# NPU: keep context small to avoid failures from very large model context windows.
|
||||
# Windows Command Line
|
||||
set GGML_OPENVINO_DEVICE=NPU
|
||||
# Windows PowerShell
|
||||
$env:GGML_OPENVINO_DEVICE = "NPU"
|
||||
build\ReleaseOV\bin\llama-cli.exe -m "C:\models\Llama-3.2-1B-Instruct-Q4_0.gguf" -c 512
|
||||
```
|
||||
> [!NOTE]
|
||||
> On systems with multiple GPUs, use `GPU.0` or `GPU.1` to explicitly target specific GPU. See [OpenVINO GPU Device](https://docs.openvino.ai/2026/openvino-workflow/running-inference/inference-devices-and-modes/gpu-device.html) for more details.
|
||||
|
||||
### Known Issues and Current Workarounds
|
||||
|
||||
- GPU stateless execution is currently affected by a known issue.
|
||||
- Workaround: set `GGML_OPENVINO_STATEFUL_EXECUTION=1` when using GPU device.
|
||||
- NPU failures can happen when context size is too large. Recent llama.cpp behavior may resolve context size to the model training context (for example, 131072 for Llama 3.2 1B), which is too large for current NPU usage and can also stress laptop CPU/GPU on larger models. To inspect the selected context size, run `llama-cli` or `llama-server` with `-lv 3`.
|
||||
- Workaround: explicitly set context size, for ex. `-c 1024` for NPU runs. Performance will be better with lower context size.
|
||||
- Additional NPU limitations:
|
||||
- Model caching is not yet supported.
|
||||
- `llama-server -np > 1` (multiple parallel sequences) is not supported.
|
||||
- `llama-perplexity` is only supported with `-b 512` or smaller.
|
||||
- `--context-shift` with `llama-cli` is currently not supported with OpenVINO backend across CPU, GPU, and NPU devices.
|
||||
- Encoder models (embedding, reranking) are not supported with the current OpenVINO backend implementation.
|
||||
- `-fa 1` is required when running llama-bench with the OpenVINO backend.
|
||||
- `GGML_OPENVINO_STATEFUL_EXECUTION=1 GGML_OPENVINO_DEVICE=GPU ./llama-bench -fa 1`
|
||||
- `llama-server` with OpenVINO backend supports only one chat session/thread, when `GGML_OPENVINO_STATEFUL_EXECUTION=1` is enabled.
|
||||
- For Intel GPU, NPU detection in containers, GPU, NPU user-space drivers/libraries must be present inside the image. We will include in a future PR. Until then, you can use this reference Dockerfile: [openvino.Dockerfile](https://github.com/ravi9/llama.cpp/blob/ov-docker-update/.devops/openvino.Dockerfile)
|
||||
|
||||
> [!NOTE]
|
||||
> The OpenVINO backend is actively under development. Fixes are underway, and this document will continue to be updated as issues are resolved.
|
||||
|
||||
|
||||
### Docker Build
|
||||
|
||||
@@ -229,31 +274,42 @@ docker build --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_p
|
||||
Run llama.cpp with OpenVINO backend Docker container.
|
||||
Save sample models in `~/models` as [shown above](#3-download-sample-model). It will be mounted to the container in the examples below.
|
||||
|
||||
> [!NOTE]
|
||||
> Intel GPU, NPU detection in containers will be included in a future PR. Until then, you can use this reference Dockerfile: [openvino.Dockerfile](https://github.com/ravi9/llama.cpp/blob/ov-docker-update/.devops/openvino.Dockerfile).
|
||||
|
||||
```bash
|
||||
# Run Docker container
|
||||
docker run --rm -it -v ~/models:/models llama-openvino:light --no-warmup -m /models/Llama-3.2-1B-Instruct-Q4_0.gguf
|
||||
docker run --rm -it -v ~/models:/models llama-openvino:light --no-warmup -c 1024 -m /models/Llama-3.2-1B-Instruct-Q4_0.gguf
|
||||
|
||||
# With Intel GPU access (iGPU or dGPU)
|
||||
docker run --rm -it -v ~/models:/models \
|
||||
--device=/dev/dri --group-add=$(stat -c "%g" /dev/dri/render* | head -n 1) -u $(id -u):$(id -g) \
|
||||
llama-openvino:light --no-warmup -m /models/Llama-3.2-1B-Instruct-Q4_0.gguf
|
||||
--env=GGML_OPENVINO_DEVICE=GPU --env=GGML_OPENVINO_STATEFUL_EXECUTION=1 \
|
||||
llama-openvino:light --no-warmup -c 1024 -m /models/Llama-3.2-1B-Instruct-Q4_0.gguf
|
||||
|
||||
# With Intel NPU access
|
||||
docker run --rm -it --env GGML_OPENVINO_DEVICE=NPU -v ~/models:/models \
|
||||
docker run --rm -it -v ~/models:/models \
|
||||
--device=/dev/accel --group-add=$(stat -c "%g" /dev/dri/render* | head -n 1) -u $(id -u):$(id -g) \
|
||||
llama-openvino:light --no-warmup -m /models/Llama-3.2-1B-Instruct-Q4_0.gguf
|
||||
--env=GGML_OPENVINO_DEVICE=NPU \
|
||||
llama-openvino:light --no-warmup -c 1024 -m /models/Llama-3.2-1B-Instruct-Q4_0.gguf
|
||||
```
|
||||
|
||||
Run Llama.cpp Server with OpenVINO Backend:
|
||||
Run Llama.cpp Server with OpenVINO Backend.
|
||||
> [!NOTE]
|
||||
> `llama-server` with OpenVINO backend supports only one chat session/thread, when `GGML_OPENVINO_STATEFUL_EXECUTION=1` is enabled.
|
||||
|
||||
```bash
|
||||
# Run the Server Docker container
|
||||
docker run --rm -it -p 8080:8080 -v ~/models:/models llama-openvino:server --no-warmup -m /models/Llama-3.2-1B-Instruct-Q4_0.gguf
|
||||
|
||||
# In a NEW terminal, test the server with curl
|
||||
docker run --rm -it -p 8080:8080 -v ~/models:/models llama-openvino:server --no-warmup -m /models/Llama-3.2-1B-Instruct-Q4_0.gguf -c 1024
|
||||
# Or Using llama-server executable
|
||||
./build/ReleaseOV/bin/llama-server -m ~/models/Llama-3.2-1B-Instruct-Q4_0.gguf --port 8080 -c 1024
|
||||
|
||||
# If you are behind a proxy, make sure to set NO_PROXY to avoid proxy for localhost
|
||||
export NO_PROXY=localhost,127.0.0.1
|
||||
|
||||
# Option 1: Open your browser to http://localhost:8080 to access the web UI for the llama.cpp server.
|
||||
# Option 2: In a NEW terminal, test the server with curl
|
||||
|
||||
# Test health endpoint
|
||||
curl -f http://localhost:8080/health
|
||||
|
||||
@@ -295,6 +351,7 @@ The OpenVINO backend can be configured using the following environment variables
|
||||
export GGML_OPENVINO_CACHE_DIR=/tmp/ov_cache
|
||||
export GGML_OPENVINO_PROFILING=1
|
||||
export GGML_OPENVINO_DEVICE=GPU
|
||||
export GGML_OPENVINO_STATEFUL_EXECUTION=1
|
||||
|
||||
./build/ReleaseOV/bin/llama-simple -m ~/models/Llama-3.2-1B-Instruct-Q4_0.gguf -n 50 "The story of AI is "
|
||||
|
||||
@@ -302,38 +359,27 @@ export GGML_OPENVINO_DEVICE=GPU
|
||||
set GGML_OPENVINO_CACHE_DIR=C:\tmp\ov_cache
|
||||
set GGML_OPENVINO_PROFILING=1
|
||||
set GGML_OPENVINO_DEVICE=GPU
|
||||
set GGML_OPENVINO_STATEFUL_EXECUTION=1
|
||||
|
||||
# Windows PowerShell
|
||||
$env:GGML_OPENVINO_CACHE_DIR = "C:\tmp\ov_cache"
|
||||
$env:GGML_OPENVINO_PROFILING = "1"
|
||||
$env:GGML_OPENVINO_DEVICE = "GPU"
|
||||
$env:GGML_OPENVINO_STATEFUL_EXECUTION = "1"
|
||||
|
||||
build\ReleaseOV\bin\llama-simple.exe -m "C:\models\Llama-3.2-1B-Instruct-Q4_0.gguf" -n 50 "The story of AI is "
|
||||
|
||||
```
|
||||
|
||||
#### llama-bench
|
||||
|
||||
```bash
|
||||
# -fa 1 is required when running llama-bench with the OpenVINO backend.
|
||||
GGML_OPENVINO_DEVICE=GPU ./llama-bench -fa 1
|
||||
```
|
||||
|
||||
### NPU Notes
|
||||
|
||||
- Model caching is not yet supported
|
||||
- Does not support llama-server -np > 1 (multiple parallel sequences)
|
||||
- Only supports llama-perplexity -b 512 or smaller
|
||||
|
||||
## Llama.cpp Tools
|
||||
|
||||
The following tools work with the OpenVINO backend on CPU, GPU, NPU:
|
||||
- llama-simple
|
||||
- llama-run
|
||||
- llama-cli
|
||||
- llama-server
|
||||
- llama-bench
|
||||
- llama-cli
|
||||
- llama-completion
|
||||
- llama-perplexity
|
||||
- llama-server
|
||||
- llama-simple
|
||||
|
||||
## Work in Progress
|
||||
|
||||
|
||||
@@ -57,13 +57,14 @@ ZenDNN is optimized for AMD EPYC™ processors and AMD Ryzen™ processors based
|
||||
|
||||
## Supported Operations
|
||||
|
||||
The ZenDNN backend currently accelerates **matrix multiplication (MUL_MAT)** operations only. Other operations are handled by the standard CPU backend.
|
||||
The ZenDNN backend accelerates **matrix multiplication (MUL_MAT)** and **expert-based matrix multiplication (MUL_MAT_ID)** operations. Other operations are handled by the standard CPU backend.
|
||||
|
||||
| Operation | Status | Notes |
|
||||
|:-------------|:-------:|:----------------------------------------------:|
|
||||
| MUL_MAT | Support | Accelerated via ZenDNN LowOHA MatMul |
|
||||
| MUL_MAT_ID | Support | Accelerated via ZenDNN LowOHA MatMul (MoE) |
|
||||
|
||||
*Note:* Since only MUL_MAT is accelerated, models will benefit most from ZenDNN when matrix multiplications dominate the computational workload (which is typical for transformer-based LLMs).
|
||||
*Note:* Since MUL_MAT and MUL_MAT_ID are accelerated, models will benefit most from ZenDNN when matrix multiplications dominate the computational workload (which is typical for transformer-based LLMs and Mixture-of-Experts models).
|
||||
|
||||
## DataType Supports
|
||||
|
||||
@@ -181,7 +182,7 @@ For detailed profiling and logging options, refer to the [ZenDNN Logging Documen
|
||||
|
||||
## Known Issues
|
||||
|
||||
- **Limited operation support**: Currently only matrix multiplication (MUL_MAT) is accelerated via ZenDNN. Other operations fall back to the standard CPU backend.
|
||||
- **Limited operation support**: Currently matrix multiplication (MUL_MAT) and expert-based matrix multiplication (MUL_MAT_ID) are accelerated via ZenDNN. Other operations fall back to the standard CPU backend. Future updates may expand supported operations.
|
||||
- **BF16 support**: BF16 operations require AMD Zen 4 or Zen 5 architecture (EPYC 9004/9005 series). On older CPUs, operations will use FP32.
|
||||
- **NUMA awareness**: For multi-socket systems, manual NUMA binding may be required for optimal performance.
|
||||
|
||||
@@ -216,4 +217,4 @@ Please add the **[ZenDNN]** prefix/tag in issues/PRs titles to help the ZenDNN-t
|
||||
|
||||
## TODO
|
||||
|
||||
- Expand operation support beyond MUL_MAT (attention operations, activations, etc.)
|
||||
- Expand operation support beyond MUL_MAT and MUL_MAT_ID (attention operations, activations, etc.)
|
||||
|
||||
@@ -389,7 +389,7 @@ You can download it from your Linux distro's package manager or from here: [ROCm
|
||||
|
||||
|
||||
The environment variable [`HIP_VISIBLE_DEVICES`](https://rocm.docs.amd.com/en/latest/understand/gpu_isolation.html#hip-visible-devices) can be used to specify which GPU(s) will be used.
|
||||
If your GPU is not officially supported you can use the environment variable [`HSA_OVERRIDE_GFX_VERSION`] set to a similar GPU, for example 10.3.0 on RDNA2 (e.g. gfx1030, gfx1031, or gfx1035) or 11.0.0 on RDNA3.
|
||||
If your GPU is not officially supported you can use the environment variable [`HSA_OVERRIDE_GFX_VERSION`] set to a similar GPU, for example 10.3.0 on RDNA2 (e.g. gfx1030, gfx1031, or gfx1035) or 11.0.0 on RDNA3. Note that [`HSA_OVERRIDE_GFX_VERSION`] is [not supported on Windows](https://github.com/ROCm/ROCm/issues/2654)
|
||||
|
||||
### Unified Memory
|
||||
|
||||
@@ -728,7 +728,7 @@ To read documentation for how to build on Android, [click here](./android.md)
|
||||
|
||||
## WebGPU [In Progress]
|
||||
|
||||
The WebGPU backend relies on [Dawn](https://dawn.googlesource.com/dawn). Follow the instructions [here](https://dawn.googlesource.com/dawn/+/refs/heads/main/docs/quickstart-cmake.md) to install Dawn locally so that llama.cpp can find it using CMake. The current implementation is up-to-date with Dawn commit `bed1a61`.
|
||||
The WebGPU backend relies on [Dawn](https://dawn.googlesource.com/dawn). Follow the instructions [here](https://dawn.googlesource.com/dawn/+/refs/heads/main/docs/quickstart-cmake.md) to install Dawn locally so that llama.cpp can find it using CMake. The current implementation is up-to-date with Dawn commit `18eb229`.
|
||||
|
||||
In the llama.cpp directory, build with CMake:
|
||||
|
||||
@@ -741,7 +741,7 @@ cmake --build build --config Release
|
||||
|
||||
WebGPU allows cross-platform access to the GPU from supported browsers. We utilize [Emscripten](https://emscripten.org/) to compile ggml's WebGPU backend to WebAssembly. Emscripten does not officially support WebGPU bindings yet, but Dawn currently maintains its own WebGPU bindings called emdawnwebgpu.
|
||||
|
||||
Follow the instructions [here](https://dawn.googlesource.com/dawn/+/refs/heads/main/src/emdawnwebgpu/) to download or build the emdawnwebgpu package (Note that it might be safer to build the emdawbwebgpu package locally, so that it stays in sync with the version of Dawn you have installed above). When building using CMake, the path to the emdawnwebgpu port file needs to be set with the flag `EMDAWNWEBGPU_DIR`.
|
||||
Follow the instructions [here](https://dawn.googlesource.com/dawn/+/refs/heads/main/src/emdawnwebgpu/) to download or build the emdawnwebgpu package (Note that it might be safer to build the emdawnwebgpu package locally, so that it stays in sync with the version of Dawn you have installed above). When building using CMake, the path to the emdawnwebgpu port file needs to be set with the flag `EMDAWNWEBGPU_DIR`.
|
||||
|
||||
## IBM Z & LinuxONE
|
||||
|
||||
|
||||
@@ -13,24 +13,30 @@ We have three Docker images available for this project:
|
||||
|
||||
Additionally, there the following images, similar to the above:
|
||||
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-cuda`: Same as `full` but compiled with CUDA support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-cuda`: Same as `light` but compiled with CUDA support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-cuda`: Same as `server` but compiled with CUDA support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-rocm`: Same as `full` but compiled with ROCm support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-rocm`: Same as `light` but compiled with ROCm support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-rocm`: Same as `server` but compiled with ROCm support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-cuda`: Same as `full` but compiled with CUDA 12 support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-cuda13`: Same as `full` but compiled with CUDA 13 support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-cuda`: Same as `light` but compiled with CUDA 12 support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-cuda13`: Same as `light` but compiled with CUDA 13 support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-cuda`: Same as `server` but compiled with CUDA 12 support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-cuda13`: Same as `server` but compiled with CUDA 13 support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-rocm`: Same as `full` but compiled with ROCm support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-rocm`: Same as `light` but compiled with ROCm support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-rocm`: Same as `server` but compiled with ROCm support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-musa`: Same as `full` but compiled with MUSA support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-musa`: Same as `light` but compiled with MUSA support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-musa`: Same as `server` but compiled with MUSA support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-intel`: Same as `full` but compiled with SYCL support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-intel`: Same as `light` but compiled with SYCL support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-intel`: Same as `server` but compiled with SYCL support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-vulkan`: Same as `full` but compiled with Vulkan support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-vulkan`: Same as `light` but compiled with Vulkan support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-vulkan`: Same as `server` but compiled with Vulkan support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-vulkan`: Same as `full` but compiled with Vulkan support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-vulkan`: Same as `light` but compiled with Vulkan support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-vulkan`: Same as `server` but compiled with Vulkan support. (platforms: `linux/amd64`, `linux/arm64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-openvino`: Same as `full` but compiled with OpenVino support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-openvino`: Same as `light` but compiled with OpenVino support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-openvino`: Same as `server` but compiled with OpenVino support. (platforms: `linux/amd64`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:full-s390x`: Identical to `full`, an alias for the `s390x` platform. (platforms: `linux/s390x`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:light-s390x`: Identical to `light`, an alias for the `s390x` platform. (platforms: `linux/s390x`)
|
||||
- `ghcr.io/ggml-org/llama.cpp:server-s390x`: Identical to `server`, an alias for the `s390x` platform. (platforms: `linux/s390x`)
|
||||
|
||||
The GPU enabled images are not currently tested by CI beyond being built. They are not built with any variation from the ones in the Dockerfiles defined in [.devops/](../.devops/) and the GitHub Action defined in [.github/workflows/docker.yml](../.github/workflows/docker.yml). If you need different settings (for example, a different CUDA, ROCm or MUSA library, you'll need to build the images locally for now).
|
||||
|
||||
@@ -82,7 +88,7 @@ You may want to pass in some different `ARGS`, depending on the CUDA environment
|
||||
|
||||
The defaults are:
|
||||
|
||||
- `CUDA_VERSION` set to `12.4.0`
|
||||
- `CUDA_VERSION` set to `12.8.1`
|
||||
- `CUDA_DOCKER_ARCH` set to the cmake build default, which includes all the supported architectures
|
||||
|
||||
The resulting images, are essentially the same as the non-CUDA images:
|
||||
|
||||
@@ -31,6 +31,14 @@ llama-server -m gemma-3-4b-it-Q4_K_M.gguf --mmproj mmproj-gemma-3-4b-it-Q4_K_M.g
|
||||
llama-server -hf ggml-org/gemma-3-4b-it-GGUF --no-mmproj-offload
|
||||
```
|
||||
|
||||
> [!IMPORTANT]
|
||||
>
|
||||
> OCR models are trained with specific prompt and input structure, please refer to these discussions for more info:
|
||||
> - PaddleOCR-VL: https://github.com/ggml-org/llama.cpp/pull/18825
|
||||
> - GLM-OCR: https://github.com/ggml-org/llama.cpp/pull/19677
|
||||
> - Deepseek-OCR: https://github.com/ggml-org/llama.cpp/pull/17400
|
||||
> - HunyuanOCR: https://github.com/ggml-org/llama.cpp/pull/21395
|
||||
|
||||
## Pre-quantized models
|
||||
|
||||
These are ready-to-use models, most of them come with `Q4_K_M` quantization by default. They can be found at the Hugging Face page of the ggml-org: https://huggingface.co/collections/ggml-org/multimodal-ggufs-68244e01ff1f39e5bebeeedc
|
||||
|
||||
@@ -68,7 +68,7 @@ Legend:
|
||||
| MEAN | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
|
||||
| MUL | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
|
||||
| MUL_MAT | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 |
|
||||
| MUL_MAT_ID | ❌ | 🟡 | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | ❌ | ❌ | ❌ |
|
||||
| MUL_MAT_ID | ❌ | 🟡 | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | 🟡 | ❌ |
|
||||
| NEG | ❌ | ✅ | ✅ | 🟡 | ✅ | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
|
||||
| NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 🟡 | ❌ | ❌ | ❌ |
|
||||
| OPT_STEP_ADAMW | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
|
||||
|
||||
1145
docs/ops/WebGPU.csv
1145
docs/ops/WebGPU.csv
File diff suppressed because it is too large
Load Diff
9986
docs/ops/ZenDNN.csv
9986
docs/ops/ZenDNN.csv
File diff suppressed because it is too large
Load Diff
@@ -24,12 +24,12 @@ int main(int argc, char ** argv) {
|
||||
params.prompt = "Hello my name is";
|
||||
params.n_predict = 32;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_BATCHED, print_usage)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
// number of parallel batches
|
||||
int n_parallel = params.n_parallel;
|
||||
|
||||
|
||||
@@ -9,6 +9,7 @@
|
||||
#include <vector>
|
||||
#include <filesystem>
|
||||
#include <fstream>
|
||||
#include <optional>
|
||||
#include <regex>
|
||||
|
||||
static void print_usage(int /*argc*/, char ** argv) {
|
||||
@@ -213,16 +214,19 @@ static bool run(llama_context * ctx, const common_params & params) {
|
||||
int main(int argc, char ** argv) {
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_DEBUG, print_usage)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
llama_backend_init();
|
||||
llama_numa_init(params.numa);
|
||||
|
||||
base_callback_data cb_data(params, params.tensor_filter);
|
||||
std::optional<base_callback_data> cb_data;
|
||||
if (!params.save_logits) {
|
||||
cb_data.emplace(params, params.tensor_filter);
|
||||
}
|
||||
|
||||
auto llama_init = common_init_from_params(params);
|
||||
|
||||
|
||||
@@ -545,11 +545,12 @@ int main(int argc, char ** argv) {
|
||||
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_DIFFUSION)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
llama_backend_init();
|
||||
|
||||
llama_model_params model_params = llama_model_default_params();
|
||||
|
||||
@@ -99,12 +99,12 @@ int main(int argc, char ** argv) {
|
||||
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_EMBEDDING)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
params.embedding = true;
|
||||
|
||||
// get max number of sequences per batch
|
||||
|
||||
@@ -15,13 +15,18 @@ static bool run(llama_context * ctx, const common_params & params) {
|
||||
|
||||
const bool add_bos = llama_vocab_get_add_bos(vocab);
|
||||
|
||||
std::vector<llama_token> tokens = common_tokenize(ctx, params.prompt, add_bos);
|
||||
std::vector<llama_token> tokens = common_tokenize(ctx, params.prompt, add_bos, true);
|
||||
|
||||
if (tokens.empty()) {
|
||||
LOG_ERR("%s : there are not input tokens to process - (try to provide a prompt with '-p')\n", __func__);
|
||||
return false;
|
||||
}
|
||||
|
||||
LOG_INF("number of input tokens = %zu\n", tokens.size());
|
||||
for (size_t i = 0; i < tokens.size(); ++i) {
|
||||
LOG_INF(" %d\n", tokens[i]);
|
||||
}
|
||||
|
||||
if (llama_decode(ctx, llama_batch_get_one(tokens.data(), tokens.size()))) {
|
||||
LOG_ERR("%s : failed to eval\n", __func__);
|
||||
return false;
|
||||
@@ -37,12 +42,12 @@ int main(int argc, char ** argv) {
|
||||
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
llama_backend_init();
|
||||
llama_numa_init(params.numa);
|
||||
|
||||
|
||||
@@ -19,12 +19,12 @@ static void print_usage(int /*argc*/, char ** argv) {
|
||||
int main(int argc, char ** argv) {
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON, print_usage)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
// init LLM
|
||||
|
||||
llama_backend_init();
|
||||
|
||||
@@ -365,13 +365,13 @@ Java_com_arm_aichat_internal_InferenceEngineImpl_processSystemPrompt(
|
||||
const auto *system_prompt = env->GetStringUTFChars(jsystem_prompt, nullptr);
|
||||
LOGd("%s: System prompt received: \n%s", __func__, system_prompt);
|
||||
std::string formatted_system_prompt(system_prompt);
|
||||
env->ReleaseStringUTFChars(jsystem_prompt, system_prompt);
|
||||
|
||||
// Format system prompt if applicable
|
||||
const bool has_chat_template = common_chat_templates_was_explicit(g_chat_templates.get());
|
||||
if (has_chat_template) {
|
||||
formatted_system_prompt = chat_add_and_format(ROLE_SYSTEM, system_prompt);
|
||||
}
|
||||
env->ReleaseStringUTFChars(jsystem_prompt, system_prompt);
|
||||
|
||||
// Tokenize system prompt
|
||||
const auto system_tokens = common_tokenize(g_context, formatted_system_prompt,
|
||||
@@ -414,13 +414,13 @@ Java_com_arm_aichat_internal_InferenceEngineImpl_processUserPrompt(
|
||||
const auto *const user_prompt = env->GetStringUTFChars(juser_prompt, nullptr);
|
||||
LOGd("%s: User prompt received: \n%s", __func__, user_prompt);
|
||||
std::string formatted_user_prompt(user_prompt);
|
||||
env->ReleaseStringUTFChars(juser_prompt, user_prompt);
|
||||
|
||||
// Format user prompt if applicable
|
||||
const bool has_chat_template = common_chat_templates_was_explicit(g_chat_templates.get());
|
||||
if (has_chat_template) {
|
||||
formatted_user_prompt = chat_add_and_format(ROLE_USER, user_prompt);
|
||||
}
|
||||
env->ReleaseStringUTFChars(juser_prompt, user_prompt);
|
||||
|
||||
// Decode formatted user prompts
|
||||
auto user_tokens = common_tokenize(g_context, formatted_user_prompt, has_chat_template, has_chat_template);
|
||||
|
||||
@@ -43,12 +43,12 @@ int main(int argc, char ** argv) {
|
||||
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
const int W = 15; // lookahead window
|
||||
const int N = 5; // n-gram size
|
||||
const int G = 15; // max verification n-grams
|
||||
|
||||
@@ -12,6 +12,8 @@ int main(int argc, char ** argv){
|
||||
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_LOOKUP)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
@@ -18,12 +18,12 @@ int main(int argc, char ** argv){
|
||||
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_LOOKUP)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
const int n_draft = params.speculative.n_max;
|
||||
|
||||
// init llama.cpp
|
||||
|
||||
@@ -18,12 +18,12 @@ int main(int argc, char ** argv){
|
||||
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_LOOKUP)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
// max. number of additional tokens to draft if match is found
|
||||
const int n_draft = params.speculative.n_max;
|
||||
|
||||
|
||||
@@ -7,7 +7,7 @@ import os
|
||||
|
||||
# Add utils directory to path for direct script execution
|
||||
sys.path.insert(0, str(Path(__file__).parent.parent / "utils"))
|
||||
from common import get_model_name_from_env_path, compare_tokens, exit_with_warning # type: ignore[import-not-found]
|
||||
from common import get_model_name_from_env_path, compare_tokens, exit_with_warning # type: ignore[import-not-found, ty:unresolved-import]
|
||||
|
||||
def quick_logits_check(pytorch_file, llamacpp_file):
|
||||
"""Lightweight sanity check before NMSE"""
|
||||
|
||||
@@ -5,7 +5,7 @@ import sys
|
||||
import os
|
||||
import argparse
|
||||
from pathlib import Path
|
||||
from common import get_model_name_from_env_path # type: ignore[import-not-found]
|
||||
from common import get_model_name_from_env_path # type: ignore[import-not-found, ty:unresolved-import]
|
||||
|
||||
def calculate_nmse(reference, test):
|
||||
mse = np.mean((test - reference) ** 2)
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
import argparse
|
||||
import sys
|
||||
from common import compare_tokens # type: ignore[import-not-found]
|
||||
from common import compare_tokens # type: ignore[import-not-found, ty:unresolved-import]
|
||||
|
||||
|
||||
def parse_arguments():
|
||||
|
||||
@@ -7,7 +7,7 @@ import importlib
|
||||
from pathlib import Path
|
||||
|
||||
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, AutoModel
|
||||
from common import compare_tokens, exit_with_warning # type: ignore[import-not-found]
|
||||
from common import compare_tokens, exit_with_warning # type: ignore[import-not-found, ty:unresolved-import]
|
||||
|
||||
unreleased_model_name = os.getenv('UNRELEASED_MODEL_NAME')
|
||||
|
||||
|
||||
@@ -163,12 +163,12 @@ int main(int argc, char ** argv) {
|
||||
params.n_predict = 128;
|
||||
params.n_junk = 1;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_PARALLEL)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
// number of simultaneous "clients" to simulate
|
||||
const int32_t n_clients = params.n_parallel;
|
||||
|
||||
|
||||
@@ -25,12 +25,12 @@ int main(int argc, char ** argv) {
|
||||
params.n_keep = 32;
|
||||
params.i_pos = -1;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_PASSKEY, print_usage)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
int n_junk = params.n_junk;
|
||||
int n_keep = params.n_keep;
|
||||
int n_grp = params.grp_attn_n;
|
||||
|
||||
@@ -117,12 +117,12 @@ int main(int argc, char ** argv) {
|
||||
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_RETRIEVAL, print_usage)) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
// For BERT models, batch size must be equal to ubatch size
|
||||
params.n_ubatch = params.n_batch;
|
||||
params.embedding = true;
|
||||
|
||||
@@ -17,6 +17,8 @@ int main(int argc, char ** argv) {
|
||||
|
||||
const std::string_view state_file = "dump_state.bin";
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON)) {
|
||||
return 1;
|
||||
}
|
||||
@@ -27,8 +29,6 @@ int main(int argc, char ** argv) {
|
||||
params.kv_unified = true;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
if (params.n_predict < 0) {
|
||||
params.n_predict = 16;
|
||||
}
|
||||
|
||||
@@ -16,6 +16,8 @@ int main(int argc, char ** argv) {
|
||||
|
||||
common_params params;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_SPECULATIVE)) {
|
||||
return 1;
|
||||
}
|
||||
@@ -25,8 +27,6 @@ int main(int argc, char ** argv) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
if (params.speculative.mparams_dft.path.empty()) {
|
||||
LOG_ERR("%s: --model-draft is required\n", __func__);
|
||||
return 1;
|
||||
|
||||
@@ -38,6 +38,8 @@ int main(int argc, char ** argv) {
|
||||
// needed to get candidate probs even for temp <= 0.0
|
||||
params.sampling.n_probs = 128;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_SPECULATIVE)) {
|
||||
return 1;
|
||||
}
|
||||
@@ -47,8 +49,6 @@ int main(int argc, char ** argv) {
|
||||
return 1;
|
||||
}
|
||||
|
||||
common_init();
|
||||
|
||||
if (params.speculative.mparams_dft.path.empty()) {
|
||||
LOG_ERR("%s: --model-draft is required\n", __func__);
|
||||
return 1;
|
||||
|
||||
@@ -20,4 +20,4 @@ cmake .. -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA
|
||||
#cmake --build . --config Release --target llama-bench
|
||||
|
||||
#build all binary
|
||||
cmake --build . --config Release -j -v
|
||||
cmake --build . --config Release -j$((($(nproc)+1)/2)) -v
|
||||
|
||||
@@ -23,9 +23,9 @@ if [ $# -gt 0 ]; then
|
||||
GGML_SYCL_DEVICE=$1
|
||||
echo "use $GGML_SYCL_DEVICE as main GPU"
|
||||
#use signle GPU only
|
||||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-completion -m ${MODEL_FILE} -no-cnv -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -s 0 -c ${CONTEXT} -mg $GGML_SYCL_DEVICE -sm none ${LOAD_MODE}
|
||||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-completion -m ${MODEL_FILE} -no-cnv -p "${INPUT_PROMPT}" -n 200 -e -ngl ${NGL} -s 0 -c ${CONTEXT} -mg $GGML_SYCL_DEVICE -sm none ${LOAD_MODE}
|
||||
|
||||
else
|
||||
#use multiple GPUs with same max compute units
|
||||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-completion -m ${MODEL_FILE} -no-cnv -p "${INPUT_PROMPT}" -n 400 -e -ngl ${NGL} -s 0 -c ${CONTEXT} ${LOAD_MODE}
|
||||
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-completion -m ${MODEL_FILE} -no-cnv -p "${INPUT_PROMPT}" -n 200 -e -ngl ${NGL} -s 0 -c ${CONTEXT} ${LOAD_MODE}
|
||||
fi
|
||||
|
||||
@@ -20,6 +20,8 @@ int main(int argc, char ** argv) {
|
||||
common_params params;
|
||||
params.escape = false;
|
||||
|
||||
common_init();
|
||||
|
||||
if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_FINETUNE)) {
|
||||
return 1;
|
||||
}
|
||||
@@ -38,7 +40,6 @@ int main(int argc, char ** argv) {
|
||||
params.cache_type_v = GGML_TYPE_F32;
|
||||
}
|
||||
|
||||
common_init();
|
||||
llama_backend_init();
|
||||
llama_numa_init(params.numa);
|
||||
// load the model and apply lora adapter, if any
|
||||
|
||||
@@ -4,7 +4,7 @@ project("ggml" C CXX ASM)
|
||||
### GGML Version
|
||||
set(GGML_VERSION_MAJOR 0)
|
||||
set(GGML_VERSION_MINOR 9)
|
||||
set(GGML_VERSION_PATCH 8)
|
||||
set(GGML_VERSION_PATCH 11)
|
||||
set(GGML_VERSION_BASE "${GGML_VERSION_MAJOR}.${GGML_VERSION_MINOR}.${GGML_VERSION_PATCH}")
|
||||
|
||||
find_program(GIT_EXE NAMES git git.exe NO_CMAKE_FIND_ROOT_PATH)
|
||||
@@ -166,15 +166,16 @@ if (NOT MSVC)
|
||||
option(GGML_AMX_INT8 "ggml: enable AMX-INT8" OFF)
|
||||
option(GGML_AMX_BF16 "ggml: enable AMX-BF16" OFF)
|
||||
endif()
|
||||
option(GGML_LASX "ggml: enable lasx" ON)
|
||||
option(GGML_LSX "ggml: enable lsx" ON)
|
||||
option(GGML_RVV "ggml: enable rvv" ON)
|
||||
option(GGML_RV_ZFH "ggml: enable riscv zfh" ON)
|
||||
option(GGML_RV_ZVFH "ggml: enable riscv zvfh" ON)
|
||||
option(GGML_RV_ZICBOP "ggml: enable riscv zicbop" ON)
|
||||
option(GGML_RV_ZIHINTPAUSE "ggml: enable riscv zihintpause " ON)
|
||||
option(GGML_XTHEADVECTOR "ggml: enable xtheadvector" OFF)
|
||||
option(GGML_VXE "ggml: enable vxe" ${GGML_NATIVE})
|
||||
option(GGML_LASX "ggml: enable lasx" ON)
|
||||
option(GGML_LSX "ggml: enable lsx" ON)
|
||||
option(GGML_RVV "ggml: enable rvv" ON)
|
||||
option(GGML_RV_ZFH "ggml: enable riscv zfh" ON)
|
||||
option(GGML_RV_ZVFH "ggml: enable riscv zvfh" ON)
|
||||
option(GGML_RV_ZICBOP "ggml: enable riscv zicbop" ON)
|
||||
option(GGML_RV_ZIHINTPAUSE "ggml: enable riscv zihintpause" ON)
|
||||
option(GGML_RV_ZVFBFWMA "ggml: enable riscv zvfbfwma" OFF)
|
||||
option(GGML_XTHEADVECTOR "ggml: enable xtheadvector" OFF)
|
||||
option(GGML_VXE "ggml: enable vxe" ${GGML_NATIVE})
|
||||
|
||||
option(GGML_CPU_ALL_VARIANTS "ggml: build all variants of the CPU backend (requires GGML_BACKEND_DL)" OFF)
|
||||
set(GGML_CPU_ARM_ARCH "" CACHE STRING "ggml: CPU architecture for ARM")
|
||||
|
||||
@@ -428,7 +428,8 @@ extern "C" {
|
||||
// GGML_TYPE_IQ4_NL_8_8 = 38,
|
||||
GGML_TYPE_MXFP4 = 39, // MXFP4 (1 block)
|
||||
GGML_TYPE_NVFP4 = 40, // NVFP4 (4 blocks, E4M3 scale)
|
||||
GGML_TYPE_COUNT = 41,
|
||||
GGML_TYPE_Q1_0 = 41,
|
||||
GGML_TYPE_COUNT = 42,
|
||||
};
|
||||
|
||||
// precision
|
||||
@@ -465,6 +466,7 @@ extern "C" {
|
||||
GGML_FTYPE_MOSTLY_BF16 = 24, // except 1d tensors
|
||||
GGML_FTYPE_MOSTLY_MXFP4 = 25, // except 1d tensors
|
||||
GGML_FTYPE_MOSTLY_NVFP4 = 26, // except 1d tensors
|
||||
GGML_FTYPE_MOSTLY_Q1_0 = 27, // except 1d tensors
|
||||
};
|
||||
|
||||
// available tensor operations:
|
||||
@@ -900,15 +902,17 @@ extern "C" {
|
||||
struct ggml_tensor * b,
|
||||
struct ggml_tensor * ids);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_add1(
|
||||
GGML_DEPRECATED(GGML_API struct ggml_tensor * ggml_add1(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b);
|
||||
struct ggml_tensor * b),
|
||||
"use ggml_add instead");
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_add1_inplace(
|
||||
GGML_DEPRECATED(GGML_API struct ggml_tensor * ggml_add1_inplace(
|
||||
struct ggml_context * ctx,
|
||||
struct ggml_tensor * a,
|
||||
struct ggml_tensor * b);
|
||||
struct ggml_tensor * b),
|
||||
"use ggml_add_inplace instead");
|
||||
|
||||
// dst = a
|
||||
// view(dst, nb1, nb2, nb3, offset) += b
|
||||
|
||||
@@ -77,6 +77,7 @@ extern "C" {
|
||||
};
|
||||
|
||||
GGML_API struct gguf_context * gguf_init_empty(void);
|
||||
GGML_API struct gguf_context * gguf_init_from_file_ptr(FILE * file, struct gguf_init_params params);
|
||||
GGML_API struct gguf_context * gguf_init_from_file(const char * fname, struct gguf_init_params params);
|
||||
//GGML_API struct gguf_context * gguf_init_from_buffer(..);
|
||||
|
||||
@@ -189,6 +190,7 @@ extern "C" {
|
||||
//
|
||||
|
||||
// write the entire context to a binary file
|
||||
GGML_API bool gguf_write_to_file_ptr(const struct gguf_context * ctx, FILE * file, bool only_meta);
|
||||
GGML_API bool gguf_write_to_file(const struct gguf_context * ctx, const char * fname, bool only_meta);
|
||||
|
||||
// get the size in bytes of the meta data (header, kv pairs, tensor info) including padding
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user