Merge branch 'master' into compilade/refactor-kv-cache

This commit is contained in:
Francis Couture-Harpin 2025-07-02 21:41:39 -04:00
commit 2bcaf64e8e
1082 changed files with 318232 additions and 122225 deletions

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@ -13,12 +13,15 @@ Checks: >
-readability-magic-numbers, -readability-magic-numbers,
-readability-uppercase-literal-suffix, -readability-uppercase-literal-suffix,
-readability-simplify-boolean-expr, -readability-simplify-boolean-expr,
-readability-math-missing-parentheses,
clang-analyzer-*, clang-analyzer-*,
-clang-analyzer-security.insecureAPI.DeprecatedOrUnsafeBufferHandling, -clang-analyzer-security.insecureAPI.DeprecatedOrUnsafeBufferHandling,
performance-*, performance-*,
portability-*, portability-*,
-portability-simd-intrinsics,
misc-*, misc-*,
-misc-const-correctness, -misc-const-correctness,
-misc-non-private-member-variables-in-classes, -misc-non-private-member-variables-in-classes,
-misc-no-recursion, -misc-no-recursion,
-misc-use-anonymous-namespace,
FormatStyle: none FormatStyle: none

92
.devops/cpu.Dockerfile Normal file
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@ -0,0 +1,92 @@
ARG UBUNTU_VERSION=22.04
FROM ubuntu:$UBUNTU_VERSION AS build
ARG TARGETARCH
ARG GGML_CPU_ARM_ARCH=armv8-a
RUN apt-get update && \
apt-get install -y build-essential git cmake libcurl4-openssl-dev
WORKDIR /app
COPY . .
RUN if [ "$TARGETARCH" = "amd64" ]; then \
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON; \
elif [ "$TARGETARCH" = "arm64" ]; then \
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DGGML_CPU_ARM_ARCH=${GGML_CPU_ARM_ARCH}; \
else \
echo "Unsupported architecture"; \
exit 1; \
fi && \
cmake --build build -j $(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so" -exec cp {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
&& cp *.py /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
&& cp .devops/tools.sh /app/full/tools.sh
## Base image
FROM ubuntu:$UBUNTU_VERSION 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 \
&& pip install --upgrade pip setuptools wheel \
&& pip install -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
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" ]

94
.devops/cuda.Dockerfile Normal file
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@ -0,0 +1,94 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.4.0
# 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 ${BASE_CUDA_DEV_CONTAINER} AS build
# CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y build-essential cmake python3 python3-pip git libcurl4-openssl-dev libgomp1
WORKDIR /app
COPY . .
RUN if [ "${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 {} /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 \
&& pip install --upgrade pip setuptools wheel \
&& pip install -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
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" ]

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@ -1,33 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.6.0
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y build-essential cmake python3 python3-pip git libcurl4-openssl-dev libgomp1
COPY requirements.txt requirements.txt
COPY requirements requirements
RUN pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt
WORKDIR /app
COPY . .
# Use the default CUDA archs if not specified
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j$(nproc) && \
cp build/bin/* .
ENTRYPOINT ["/app/.devops/tools.sh"]

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@ -1,26 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG MUSA_VERSION=rc3.1.0
# Target the MUSA build image
ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
RUN apt-get update && \
apt-get install -y build-essential cmake python3 python3-pip git libcurl4-openssl-dev libgomp1
COPY requirements.txt requirements.txt
COPY requirements requirements
RUN pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_MUSA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j$(nproc) && \
cp build/bin/* .
ENTRYPOINT ["/app/.devops/tools.sh"]

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@ -1,50 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG ROCM_VERSION=5.6
# Target the CUDA build image
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
FROM ${BASE_ROCM_DEV_CONTAINER} AS build
# Unless otherwise specified, we make a fat build.
# List from https://github.com/ggerganov/llama.cpp/pull/1087#issuecomment-1682807878
# This is mostly tied to rocBLAS supported archs.
ARG ROCM_DOCKER_ARCH="\
gfx803 \
gfx900 \
gfx906 \
gfx908 \
gfx90a \
gfx1010 \
gfx1030 \
gfx1100 \
gfx1101 \
gfx1102"
COPY requirements.txt requirements.txt
COPY requirements requirements
RUN pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt
WORKDIR /app
COPY . .
# Set nvcc architecture
ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}
# Enable ROCm
ENV GGML_HIPBLAS=1
ENV CC=/opt/rocm/llvm/bin/clang
ENV CXX=/opt/rocm/llvm/bin/clang++
# Enable cURL
ENV LLAMA_CURL=1
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev
RUN make -j$(nproc)
ENTRYPOINT ["/app/.devops/tools.sh"]

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@ -1,25 +0,0 @@
ARG UBUNTU_VERSION=22.04
FROM ubuntu:$UBUNTU_VERSION AS build
RUN apt-get update && \
apt-get install -y build-essential python3 python3-pip git libcurl4-openssl-dev libgomp1
COPY requirements.txt requirements.txt
COPY requirements requirements
RUN pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt
WORKDIR /app
COPY . .
ENV LLAMA_CURL=1
RUN make -j$(nproc)
ENV LC_ALL=C.utf8
ENTRYPOINT ["/app/.devops/tools.sh"]

95
.devops/intel.Dockerfile Normal file
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@ -0,0 +1,95 @@
ARG ONEAPI_VERSION=2025.1.1-0-devel-ubuntu24.04
## Build Image
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS build
ARG GGML_SYCL_F16=OFF
RUN apt-get update && \
apt-get install -y git libcurl4-openssl-dev
WORKDIR /app
COPY . .
RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
echo "GGML_SYCL_F16 is set" \
&& export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
fi && \
echo "Building with dynamic libs" && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${OPT_SYCL_F16} && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so" -exec cp {} /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
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS base
RUN apt-get update \
&& apt-get install -y libgomp1 curl\
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
### Full
FROM base AS full
COPY --from=build /app/lib/ /app
COPY --from=build /app/full /app
WORKDIR /app
RUN apt-get update && \
apt-get install -y \
git \
python3 \
python3-pip \
python3-venv && \
python3 -m venv /opt/venv && \
. /opt/venv/bin/activate && \
pip install --upgrade pip setuptools wheel && \
pip install -r requirements.txt && \
apt autoremove -y && \
apt clean -y && \
rm -rf /tmp/* /var/tmp/* && \
find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete && \
find /var/cache -type f -delete
ENV PATH="/opt/venv/bin:$PATH"
ENTRYPOINT ["/app/tools.sh"]
### Light, CLI only
FROM base AS light
COPY --from=build /app/lib/ /app
COPY --from=build /app/full/llama-cli /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/lib/ /app
COPY --from=build /app/full/llama-server /app
WORKDIR /app
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/app/llama-server" ]

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@ -1,4 +1,4 @@
ARG ASCEND_VERSION=8.0.rc2.alpha003-910b-openeuler22.03-py3.8 ARG ASCEND_VERSION=8.1.RC1.alpha001-910b-openeuler22.03-py3.10
FROM ascendai/cann:$ASCEND_VERSION AS build FROM ascendai/cann:$ASCEND_VERSION AS build
@ -6,7 +6,7 @@ WORKDIR /app
COPY . . COPY . .
RUN yum install -y gcc g++ cmake make RUN yum install -y gcc g++ cmake make libcurl-devel
ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest
ENV LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:$LIBRARY_PATH ENV LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:$LIBRARY_PATH
ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/lib64/plugin/opskernel:${ASCEND_TOOLKIT_HOME}/lib64/plugin/nnengine:${ASCEND_TOOLKIT_HOME}/opp/built-in/op_impl/ai_core/tbe/op_tiling:${LD_LIBRARY_PATH} ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/lib64/plugin/opskernel:${ASCEND_TOOLKIT_HOME}/lib64/plugin/nnengine:${ASCEND_TOOLKIT_HOME}/opp/built-in/op_impl/ai_core/tbe/op_tiling:${LD_LIBRARY_PATH}
@ -22,7 +22,7 @@ ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/runtime/lib64/stub:$LD_LIBRARY_PATH
RUN echo "Building with static libs" && \ RUN echo "Building with static libs" && \
source /usr/local/Ascend/ascend-toolkit/set_env.sh --force && \ source /usr/local/Ascend/ascend-toolkit/set_env.sh --force && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CANN=ON -DBUILD_SHARED_LIBS=OFF && \ cmake -B build -DGGML_NATIVE=OFF -DGGML_CANN=ON -DBUILD_SHARED_LIBS=OFF -DLLAMA_BUILD_TESTS=OFF && \
cmake --build build --config Release --target llama-cli cmake --build build --config Release --target llama-cli
# TODO: use image with NNRT # TODO: use image with NNRT

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@ -1,38 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.6.0
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y build-essential git cmake
WORKDIR /app
COPY . .
# Use the default CUDA archs if not specified
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release --target llama-cli -j$(nproc) && \
mkdir -p /app/lib && \
find build -name "*.so" -exec cp {} /app/lib \;
FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
RUN apt-get update && \
apt-get install -y libgomp1
COPY --from=build /app/lib/ /
COPY --from=build /app/build/bin/llama-cli /
ENTRYPOINT [ "/llama-cli" ]

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@ -1,28 +0,0 @@
ARG ONEAPI_VERSION=2025.0.0-0-devel-ubuntu22.04
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS build
ARG GGML_SYCL_F16=OFF
RUN apt-get update && \
apt-get install -y git
WORKDIR /app
COPY . .
RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
echo "GGML_SYCL_F16 is set" && \
export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
fi && \
echo "Building with static libs" && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx \
${OPT_SYCL_F16} -DBUILD_SHARED_LIBS=OFF && \
cmake --build build --config Release --target llama-cli
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS runtime
COPY --from=build /app/build/bin/llama-cli /llama-cli
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/llama-cli" ]

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@ -1,31 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG MUSA_VERSION=rc3.1.0
# Target the MUSA build image
ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the MUSA runtime image
ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
RUN apt-get update && \
apt-get install -y build-essential git cmake
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_MUSA=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release --target llama-cli -j$(nproc) && \
mkdir -p /app/lib && \
find build -name "*.so" -exec cp {} /app/lib \;
FROM ${BASE_MUSA_RUN_CONTAINER} AS runtime
RUN apt-get update && \
apt-get install -y libgomp1
COPY --from=build /app/lib/ /
COPY --from=build /app/build/bin/llama-cli /llama-cli
ENTRYPOINT [ "/llama-cli" ]

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@ -1,45 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG ROCM_VERSION=5.6
# Target the CUDA build image
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
FROM ${BASE_ROCM_DEV_CONTAINER} AS build
# Unless otherwise specified, we make a fat build.
# List from https://github.com/ggerganov/llama.cpp/pull/1087#issuecomment-1682807878
# This is mostly tied to rocBLAS supported archs.
ARG ROCM_DOCKER_ARCH="\
gfx803 \
gfx900 \
gfx906 \
gfx908 \
gfx90a \
gfx1010 \
gfx1030 \
gfx1100 \
gfx1101 \
gfx1102"
COPY requirements.txt requirements.txt
COPY requirements requirements
RUN pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt
WORKDIR /app
COPY . .
# Set nvcc architecture
ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}
# Enable ROCm
ENV GGML_HIPBLAS=1
ENV CC=/opt/rocm/llvm/bin/clang
ENV CXX=/opt/rocm/llvm/bin/clang++
RUN make -j$(nproc) llama-cli
ENTRYPOINT [ "/app/llama-cli" ]

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@ -1,27 +0,0 @@
ARG UBUNTU_VERSION=jammy
FROM ubuntu:$UBUNTU_VERSION AS build
# Install build tools
RUN apt update && apt install -y git build-essential cmake wget libgomp1
# Install Vulkan SDK
RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt update -y && \
apt-get install -y vulkan-sdk
# Build it
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_VULKAN=1 && \
cmake --build build --config Release --target llama-cli
# Clean up
WORKDIR /
RUN cp /app/build/bin/llama-cli /llama-cli && \
rm -rf /app
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/llama-cli" ]

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@ -1,23 +0,0 @@
ARG UBUNTU_VERSION=22.04
FROM ubuntu:$UBUNTU_VERSION AS build
RUN apt-get update && \
apt-get install -y build-essential git
WORKDIR /app
COPY . .
RUN make -j$(nproc) llama-cli
FROM ubuntu:$UBUNTU_VERSION AS runtime
RUN apt-get update && \
apt-get install -y libgomp1
COPY --from=build /app/llama-cli /llama-cli
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/llama-cli" ]

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@ -17,10 +17,10 @@ Version: %( date "+%%Y%%m%%d" )
Release: 1%{?dist} Release: 1%{?dist}
Summary: CPU Inference of LLaMA model in pure C/C++ (no CUDA/OpenCL) Summary: CPU Inference of LLaMA model in pure C/C++ (no CUDA/OpenCL)
License: MIT License: MIT
Source0: https://github.com/ggerganov/llama.cpp/archive/refs/heads/master.tar.gz Source0: https://github.com/ggml-org/llama.cpp/archive/refs/heads/master.tar.gz
BuildRequires: coreutils make gcc-c++ git cuda-toolkit BuildRequires: coreutils make gcc-c++ git cuda-toolkit
Requires: cuda-toolkit Requires: cuda-toolkit
URL: https://github.com/ggerganov/llama.cpp URL: https://github.com/ggml-org/llama.cpp
%define debug_package %{nil} %define debug_package %{nil}
%define source_date_epoch_from_changelog 0 %define source_date_epoch_from_changelog 0

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@ -18,10 +18,10 @@ Version: %( date "+%%Y%%m%%d" )
Release: 1%{?dist} Release: 1%{?dist}
Summary: CPU Inference of LLaMA model in pure C/C++ (no CUDA/OpenCL) Summary: CPU Inference of LLaMA model in pure C/C++ (no CUDA/OpenCL)
License: MIT License: MIT
Source0: https://github.com/ggerganov/llama.cpp/archive/refs/heads/master.tar.gz Source0: https://github.com/ggml-org/llama.cpp/archive/refs/heads/master.tar.gz
BuildRequires: coreutils make gcc-c++ git libstdc++-devel BuildRequires: coreutils make gcc-c++ git libstdc++-devel
Requires: libstdc++ Requires: libstdc++
URL: https://github.com/ggerganov/llama.cpp URL: https://github.com/ggml-org/llama.cpp
%define debug_package %{nil} %define debug_package %{nil}
%define source_date_epoch_from_changelog 0 %define source_date_epoch_from_changelog 0

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@ -1,43 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=12.6.0
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y build-essential git cmake libcurl4-openssl-dev
WORKDIR /app
COPY . .
# Use the default CUDA archs if not specified
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release --target llama-server -j$(nproc) && \
mkdir -p /app/lib && \
find build -name "*.so" -exec cp {} /app/lib \;
FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev libgomp1 curl
COPY --from=build /app/lib/ /
COPY --from=build /app/build/bin/llama-server /llama-server
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

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@ -1,34 +0,0 @@
ARG ONEAPI_VERSION=2025.0.0-0-devel-ubuntu22.04
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS build
ARG GGML_SYCL_F16=OFF
RUN apt-get update && \
apt-get install -y git libcurl4-openssl-dev
WORKDIR /app
COPY . .
RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
echo "GGML_SYCL_F16 is set" && \
export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
fi && \
echo "Building with dynamic libs" && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \
cmake --build build --config Release --target llama-server
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev curl
COPY --from=build /app/build/bin/llama-server /llama-server
ENV LC_ALL=C.utf8
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

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@ -1,36 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG MUSA_VERSION=rc3.1.0
# Target the MUSA build image
ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the MUSA runtime image
ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
RUN apt-get update && \
apt-get install -y build-essential git cmake libcurl4-openssl-dev
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_MUSA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release --target llama-server -j$(nproc) && \
mkdir -p /app/lib && \
find build -name "*.so" -exec cp {} /app/lib \;
FROM ${BASE_MUSA_RUN_CONTAINER} AS runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev libgomp1 curl
COPY --from=build /app/lib/ /
COPY --from=build /app/build/bin/llama-server /llama-server
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

View File

@ -1,54 +0,0 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG ROCM_VERSION=5.6
# Target the CUDA build image
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
FROM ${BASE_ROCM_DEV_CONTAINER} AS build
# Unless otherwise specified, we make a fat build.
# List from https://github.com/ggerganov/llama.cpp/pull/1087#issuecomment-1682807878
# This is mostly tied to rocBLAS supported archs.
ARG ROCM_DOCKER_ARCH="\
gfx803 \
gfx900 \
gfx906 \
gfx908 \
gfx90a \
gfx1010 \
gfx1030 \
gfx1100 \
gfx1101 \
gfx1102"
COPY requirements.txt requirements.txt
COPY requirements requirements
RUN pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt
WORKDIR /app
COPY . .
# Set nvcc architecture
ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}
# Enable ROCm
ENV GGML_HIPBLAS=1
ENV CC=/opt/rocm/llvm/bin/clang
ENV CXX=/opt/rocm/llvm/bin/clang++
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
# Enable cURL
ENV LLAMA_CURL=1
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev curl
RUN make -j$(nproc) llama-server
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/app/llama-server" ]

View File

@ -1,31 +0,0 @@
ARG UBUNTU_VERSION=jammy
FROM ubuntu:$UBUNTU_VERSION AS build
# Install build tools
RUN apt update && apt install -y git build-essential cmake wget
# Install Vulkan SDK and cURL
RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt update -y && \
apt-get install -y vulkan-sdk libcurl4-openssl-dev curl
# Build it
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_VULKAN=1 -DLLAMA_CURL=1 && \
cmake --build build --config Release --target llama-server
# Clean up
WORKDIR /
RUN cp /app/build/bin/llama-server /llama-server && \
rm -rf /app
ENV LC_ALL=C.utf8
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

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@ -1,29 +0,0 @@
ARG UBUNTU_VERSION=22.04
FROM ubuntu:$UBUNTU_VERSION AS build
RUN apt-get update && \
apt-get install -y build-essential git libcurl4-openssl-dev
WORKDIR /app
COPY . .
ENV LLAMA_CURL=1
RUN make -j$(nproc) llama-server
FROM ubuntu:$UBUNTU_VERSION AS runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev libgomp1 curl
COPY --from=build /app/llama-server /llama-server
ENV LC_ALL=C.utf8
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/llama-server" ]

101
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@ -0,0 +1,101 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG MUSA_VERSION=rc4.0.1
# Target the MUSA build image
ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-mudnn-devel-ubuntu${UBUNTU_VERSION}
ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-mudnn-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
# MUSA architecture to build for (defaults to all supported archs)
ARG MUSA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y \
build-essential \
cmake \
python3 \
python3-pip \
git \
libcurl4-openssl-dev \
libgomp1
WORKDIR /app
COPY . .
RUN if [ "${MUSA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DMUSA_ARCHITECTURES=${MUSA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_MUSA=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 {} /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_MUSA_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 \
&& pip install --upgrade pip setuptools wheel \
&& pip install -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
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" ]

View File

@ -31,6 +31,7 @@
# Increases the runtime closure size by ~700M # Increases the runtime closure size by ~700M
useMpi ? false, useMpi ? false,
useRocm ? config.rocmSupport, useRocm ? config.rocmSupport,
rocmGpuTargets ? builtins.concatStringsSep ";" rocmPackages.clr.gpuTargets,
enableCurl ? true, enableCurl ? true,
useVulkan ? false, useVulkan ? false,
llamaVersion ? "0.0.0", # Arbitrary version, substituted by the flake llamaVersion ? "0.0.0", # Arbitrary version, substituted by the flake
@ -132,12 +133,12 @@ effectiveStdenv.mkDerivation (finalAttrs: {
--replace '[bundle pathForResource:@"default" ofType:@"metallib"];' "@\"$out/bin/default.metallib\";" --replace '[bundle pathForResource:@"default" ofType:@"metallib"];' "@\"$out/bin/default.metallib\";"
''; '';
# With PR#6015 https://github.com/ggerganov/llama.cpp/pull/6015, # With PR#6015 https://github.com/ggml-org/llama.cpp/pull/6015,
# `default.metallib` may be compiled with Metal compiler from XCode # `default.metallib` may be compiled with Metal compiler from XCode
# and we need to escape sandbox on MacOS to access Metal compiler. # and we need to escape sandbox on MacOS to access Metal compiler.
# `xcrun` is used find the path of the Metal compiler, which is varible # `xcrun` is used find the path of the Metal compiler, which is varible
# and not on $PATH # and not on $PATH
# see https://github.com/ggerganov/llama.cpp/pull/6118 for discussion # see https://github.com/ggml-org/llama.cpp/pull/6118 for discussion
__noChroot = effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders; __noChroot = effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders;
nativeBuildInputs = nativeBuildInputs =
@ -188,7 +189,7 @@ effectiveStdenv.mkDerivation (finalAttrs: {
] ]
++ optionals useRocm [ ++ optionals useRocm [
(cmakeFeature "CMAKE_HIP_COMPILER" "${rocmPackages.llvm.clang}/bin/clang") (cmakeFeature "CMAKE_HIP_COMPILER" "${rocmPackages.llvm.clang}/bin/clang")
(cmakeFeature "CMAKE_HIP_ARCHITECTURES" (builtins.concatStringsSep ";" rocmPackages.clr.gpuTargets)) (cmakeFeature "CMAKE_HIP_ARCHITECTURES" rocmGpuTargets)
] ]
++ optionals useMetalKit [ ++ optionals useMetalKit [
(lib.cmakeFeature "CMAKE_C_FLAGS" "-D__ARM_FEATURE_DOTPROD=1") (lib.cmakeFeature "CMAKE_C_FLAGS" "-D__ARM_FEATURE_DOTPROD=1")
@ -219,7 +220,7 @@ effectiveStdenv.mkDerivation (finalAttrs: {
broken = (useMetalKit && !effectiveStdenv.isDarwin); broken = (useMetalKit && !effectiveStdenv.isDarwin);
description = "Inference of LLaMA model in pure C/C++${descriptionSuffix}"; description = "Inference of LLaMA model in pure C/C++${descriptionSuffix}";
homepage = "https://github.com/ggerganov/llama.cpp/"; homepage = "https://github.com/ggml-org/llama.cpp/";
license = lib.licenses.mit; license = lib.licenses.mit;
# Accommodates `nix run` and `lib.getExe` # Accommodates `nix run` and `lib.getExe`

View File

@ -34,7 +34,7 @@ let
# server tests # server tests
openai openai
behave pytest
prometheus-client prometheus-client
]; ];
in in

113
.devops/rocm.Dockerfile Normal file
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@ -0,0 +1,113 @@
ARG UBUNTU_VERSION=24.04
# This needs to generally match the container host's environment.
ARG ROCM_VERSION=6.3
ARG AMDGPU_VERSION=6.3
# Target the CUDA build image
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
### Build image
FROM ${BASE_ROCM_DEV_CONTAINER} AS build
# Unless otherwise specified, we make a fat build.
# List from https://github.com/ggml-org/llama.cpp/pull/1087#issuecomment-1682807878
# This is mostly tied to rocBLAS supported archs.
# gfx803, gfx900, gfx1032, gfx1101, gfx1102,not officialy supported
# gfx906 is deprecated
#check https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.2.4/reference/system-requirements.html
ARG ROCM_DOCKER_ARCH='gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102'
#ARG ROCM_DOCKER_ARCH=gfx1100
# Set nvcc architectured
ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}
# Enable ROCm
# ENV CC=/opt/rocm/llvm/bin/clang
# ENV CXX=/opt/rocm/llvm/bin/clang++
RUN apt-get update \
&& apt-get install -y \
build-essential \
cmake \
git \
libcurl4-openssl-dev \
curl \
libgomp1
WORKDIR /app
COPY . .
RUN HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \
cmake -S . -B build -DGGML_HIP=ON -DAMDGPU_TARGETS=$ROCM_DOCKER_ARCH -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DCMAKE_BUILD_TYPE=Release -DLLAMA_BUILD_TESTS=OFF \
&& cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib \
&& find build -name "*.so" -exec cp {} /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_ROCM_DEV_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-pip \
python3 \
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
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" ]

View File

@ -1,4 +1,4 @@
#!/bin/bash #!/usr/bin/env bash
set -e set -e
# Read the first argument into a variable # Read the first argument into a variable
@ -8,28 +8,36 @@ arg1="$1"
shift shift
if [[ "$arg1" == '--convert' || "$arg1" == '-c' ]]; then if [[ "$arg1" == '--convert' || "$arg1" == '-c' ]]; then
python3 ./convert_hf_to_gguf.py "$@" exec python3 ./convert_hf_to_gguf.py "$@"
elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then
./llama-quantize "$@" exec ./llama-quantize "$@"
elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then
./llama-cli "$@" exec ./llama-cli "$@"
elif [[ "$arg1" == '--bench' || "$arg1" == '-b' ]]; then
exec ./llama-bench "$@"
elif [[ "$arg1" == '--perplexity' || "$arg1" == '-p' ]]; then
exec ./llama-perplexity "$@"
elif [[ "$arg1" == '--all-in-one' || "$arg1" == '-a' ]]; then elif [[ "$arg1" == '--all-in-one' || "$arg1" == '-a' ]]; then
echo "Converting PTH to GGML..." echo "Converting PTH to GGML..."
for i in `ls $1/$2/ggml-model-f16.bin*`; do for i in $(ls $1/$2/ggml-model-f16.bin*); do
if [ -f "${i/f16/q4_0}" ]; then if [ -f "${i/f16/q4_0}" ]; then
echo "Skip model quantization, it already exists: ${i/f16/q4_0}" echo "Skip model quantization, it already exists: ${i/f16/q4_0}"
else else
echo "Converting PTH to GGML: $i into ${i/f16/q4_0}..." echo "Converting PTH to GGML: $i into ${i/f16/q4_0}..."
./llama-quantize "$i" "${i/f16/q4_0}" q4_0 exec ./llama-quantize "$i" "${i/f16/q4_0}" q4_0
fi fi
done done
elif [[ "$arg1" == '--server' || "$arg1" == '-s' ]]; then elif [[ "$arg1" == '--server' || "$arg1" == '-s' ]]; then
./llama-server "$@" exec ./llama-server "$@"
else else
echo "Unknown command: $arg1" echo "Unknown command: $arg1"
echo "Available commands: " echo "Available commands: "
echo " --run (-r): Run a model previously converted into ggml" echo " --run (-r): Run a model previously converted into ggml"
echo " ex: -m /models/7B/ggml-model-q4_0.bin -p \"Building a website can be done in 10 simple steps:\" -n 512" echo " ex: -m /models/7B/ggml-model-q4_0.bin -p \"Building a website can be done in 10 simple steps:\" -n 512"
echo " --bench (-b): Benchmark the performance of the inference for various parameters."
echo " ex: -m model.gguf"
echo " --perplexity (-p): Measure the perplexity of a model over a given text."
echo " ex: -m model.gguf -f file.txt"
echo " --convert (-c): Convert a llama model into ggml" echo " --convert (-c): Convert a llama model into ggml"
echo " ex: --outtype f16 \"/models/7B/\" " echo " ex: --outtype f16 \"/models/7B/\" "
echo " --quantize (-q): Optimize with quantization process ggml" echo " --quantize (-q): Optimize with quantization process ggml"

89
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@ -0,0 +1,89 @@
ARG UBUNTU_VERSION=24.04
FROM ubuntu:$UBUNTU_VERSION AS build
# Install build tools
RUN apt update && apt install -y git build-essential cmake wget
# Install Vulkan SDK and cURL
RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-noble.list https://packages.lunarg.com/vulkan/lunarg-vulkan-noble.list && \
apt update -y && \
apt-get install -y vulkan-sdk libcurl4-openssl-dev curl
# Build it
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_VULKAN=1 -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so" -exec cp {} /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 ubuntu:$UBUNTU_VERSION AS base
RUN apt-get update \
&& apt-get install -y libgomp1 curl libvulkan-dev \
&& 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
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" ]

View File

@ -21,15 +21,15 @@ indent_style = tab
[prompts/*.txt] [prompts/*.txt]
insert_final_newline = unset insert_final_newline = unset
[examples/server/public/*] [tools/server/public/*]
indent_size = 2 indent_size = 2
[examples/server/public/deps_*] [tools/server/public/deps_*]
trim_trailing_whitespace = unset trim_trailing_whitespace = unset
indent_style = unset indent_style = unset
indent_size = unset indent_size = unset
[examples/server/deps_*] [tools/server/deps_*]
trim_trailing_whitespace = unset trim_trailing_whitespace = unset
indent_style = unset indent_style = unset
indent_size = unset indent_size = unset
@ -37,6 +37,18 @@ indent_size = unset
[examples/llama.swiftui/llama.swiftui.xcodeproj/*] [examples/llama.swiftui/llama.swiftui.xcodeproj/*]
indent_style = tab indent_style = tab
[examples/cvector-generator/*.txt] [tools/cvector-generator/*.txt]
trim_trailing_whitespace = unset
insert_final_newline = unset
[models/templates/*.jinja]
indent_style = unset
indent_size = unset
end_of_line = unset
charset = unset
trim_trailing_whitespace = unset
insert_final_newline = unset
[vendor/miniaudio/miniaudio.h]
trim_trailing_whitespace = unset trim_trailing_whitespace = unset
insert_final_newline = unset insert_final_newline = unset

View File

@ -2,8 +2,9 @@
max-line-length = 125 max-line-length = 125
ignore = E203,E211,E221,E225,E231,E241,E251,E261,E266,E501,E701,E704,W503 ignore = E203,E211,E221,E225,E231,E241,E251,E261,E266,E501,E701,E704,W503
exclude = exclude =
# Do not traverse examples # Do not traverse examples and tools
examples, examples,
tools,
# Do not include package initializers # Do not include package initializers
__init__.py, __init__.py,
# No need to traverse our git directory # No need to traverse our git directory

View File

@ -24,7 +24,8 @@ body:
- type: dropdown - type: dropdown
id: operating-system id: operating-system
attributes: attributes:
label: Which operating systems do you know to be affected? label: Operating systems
description: Which operating systems do you know to be affected?
multiple: true multiple: true
options: options:
- Linux - Linux
@ -39,16 +40,19 @@ body:
attributes: attributes:
label: GGML backends label: GGML backends
description: Which GGML backends do you know to be affected? description: Which GGML backends do you know to be affected?
options: [AMX, BLAS, CPU, CUDA, HIP, Kompute, Metal, Musa, RPC, SYCL, Vulkan] options: [AMX, BLAS, CPU, CUDA, HIP, Kompute, Metal, Musa, RPC, SYCL, Vulkan, OpenCL]
multiple: true multiple: true
validations:
required: true
- type: textarea - type: textarea
id: steps_to_reproduce id: info
attributes: attributes:
label: Steps to Reproduce label: Problem description & steps to reproduce
description: > description: >
Please tell us how to reproduce the bug and any additional information that you think could be useful for fixing it. Please give us a summary of the problem and tell us how to reproduce it.
If you can narrow down the bug to specific compile flags, that information would be very much appreciated by us. If you can narrow down the bug to specific compile flags, that information would be very much appreciated by us.
placeholder: > placeholder: >
I'm trying to compile llama.cpp with CUDA support on a fresh install of Ubuntu and get error XY.
Here are the exact commands that I used: ... Here are the exact commands that I used: ...
validations: validations:
required: true required: true
@ -61,12 +65,22 @@ body:
If possible, please do a git bisect and identify the exact commit that introduced the bug. If possible, please do a git bisect and identify the exact commit that introduced the bug.
validations: validations:
required: false required: false
- type: textarea
id: command
attributes:
label: Compile command
description: >
Please provide the exact command you used to compile llama.cpp. For example: `cmake -B ...`.
This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
- type: textarea - type: textarea
id: logs id: logs
attributes: attributes:
label: Relevant log output label: Relevant log output
description: > description: >
Please copy and paste any relevant log output, including the command that you entered and any generated text. Please copy and paste any relevant log output, including any generated text.
This will be automatically formatted into code, so no need for backticks. This will be automatically formatted into code, so no need for backticks.
render: shell render: shell
validations: validations:

View File

@ -26,7 +26,8 @@ body:
- type: dropdown - type: dropdown
id: operating-system id: operating-system
attributes: attributes:
label: Which operating systems do you know to be affected? label: Operating systems
description: Which operating systems do you know to be affected?
multiple: true multiple: true
options: options:
- Linux - Linux
@ -41,8 +42,10 @@ body:
attributes: attributes:
label: GGML backends label: GGML backends
description: Which GGML backends do you know to be affected? description: Which GGML backends do you know to be affected?
options: [AMX, BLAS, CPU, CUDA, HIP, Kompute, Metal, Musa, RPC, SYCL, Vulkan] options: [AMX, BLAS, CPU, CUDA, HIP, Kompute, Metal, Musa, RPC, SYCL, Vulkan, OpenCL]
multiple: true multiple: true
validations:
required: true
- type: textarea - type: textarea
id: hardware id: hardware
attributes: attributes:
@ -55,20 +58,20 @@ body:
- type: textarea - type: textarea
id: model id: model
attributes: attributes:
label: Model label: Models
description: > description: >
Which model at which quantization were you using when encountering the bug? Which model(s) at which quantization were you using when encountering the bug?
If you downloaded a GGUF file off of Huggingface, please provide a link. If you downloaded a GGUF file off of Huggingface, please provide a link.
placeholder: > placeholder: >
e.g. Meta LLaMA 3.1 Instruct 8b q4_K_M e.g. Meta LLaMA 3.1 Instruct 8b q4_K_M
validations: validations:
required: false required: false
- type: textarea - type: textarea
id: steps_to_reproduce id: info
attributes: attributes:
label: Steps to Reproduce label: Problem description & steps to reproduce
description: > description: >
Please tell us how to reproduce the bug and any additional information that you think could be useful for fixing it. Please give us a summary of the problem and tell us how to reproduce it.
If you can narrow down the bug to specific hardware, compile flags, or command line arguments, If you can narrow down the bug to specific hardware, compile flags, or command line arguments,
that information would be very much appreciated by us. that information would be very much appreciated by us.
placeholder: > placeholder: >

View File

@ -14,7 +14,7 @@ body:
id: version id: version
attributes: attributes:
label: Name and Version label: Name and Version
description: Which version of our software are you running? (use `--version` to get a version string) description: Which version of our software is affected? (You can use `--version` to get a version string.)
placeholder: | placeholder: |
$./llama-cli --version $./llama-cli --version
version: 2999 (42b4109e) version: 2999 (42b4109e)
@ -24,7 +24,8 @@ body:
- type: dropdown - type: dropdown
id: operating-system id: operating-system
attributes: attributes:
label: Which operating systems do you know to be affected? label: Operating systems
description: Which operating systems do you know to be affected?
multiple: true multiple: true
options: options:
- Linux - Linux
@ -33,28 +34,40 @@ body:
- BSD - BSD
- Other? (Please let us know in description) - Other? (Please let us know in description)
validations: validations:
required: true required: false
- type: dropdown - type: dropdown
id: module id: module
attributes: attributes:
label: Which llama.cpp modules do you know to be affected? label: Which llama.cpp modules do you know to be affected?
multiple: true multiple: true
options: options:
- Documentation/Github
- libllama (core library) - libllama (core library)
- llama-cli - llama-cli
- llama-server - llama-server
- llama-bench - llama-bench
- llama-quantize - llama-quantize
- Python/Bash scripts - Python/Bash scripts
- Test code
- Other (Please specify in the next section) - Other (Please specify in the next section)
validations: validations:
required: true required: false
- type: textarea - type: textarea
id: steps_to_reproduce id: command
attributes: attributes:
label: Steps to Reproduce label: Command line
description: > description: >
Please tell us how to reproduce the bug and any additional information that you think could be useful for fixing it. Please provide the exact commands you entered, if applicable. For example: `llama-server -m ... -c ...`, `llama-cli -m ...`, etc.
This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: false
- type: textarea
id: info
attributes:
label: Problem description & steps to reproduce
description: >
Please give us a summary of the problem and tell us how to reproduce it (if applicable).
validations: validations:
required: true required: true
- type: textarea - type: textarea
@ -62,7 +75,7 @@ body:
attributes: attributes:
label: First Bad Commit label: First Bad Commit
description: > description: >
If the bug was not present on an earlier version: when did it start appearing? If the bug was not present on an earlier version and it's not trivial to track down: when did it start appearing?
If possible, please do a git bisect and identify the exact commit that introduced the bug. If possible, please do a git bisect and identify the exact commit that introduced the bug.
validations: validations:
required: false required: false
@ -71,8 +84,8 @@ body:
attributes: attributes:
label: Relevant log output label: Relevant log output
description: > description: >
Please copy and paste any relevant log output, including the command that you entered and any generated text. If applicable, please copy and paste any relevant log output, including any generated text.
This will be automatically formatted into code, so no need for backticks. This will be automatically formatted into code, so no need for backticks.
render: shell render: shell
validations: validations:
required: true required: false

View File

@ -6,7 +6,7 @@ body:
- type: markdown - type: markdown
attributes: attributes:
value: | value: |
[Please post your idea first in Discussion if there is not yet a consensus for this enhancement request. This will help to keep this issue tracker focused on enhancements that the community has agreed needs to be implemented.](https://github.com/ggerganov/llama.cpp/discussions/categories/ideas) [Please post your idea first in Discussion if there is not yet a consensus for this enhancement request. This will help to keep this issue tracker focused on enhancements that the community has agreed needs to be implemented.](https://github.com/ggml-org/llama.cpp/discussions/categories/ideas)
- type: checkboxes - type: checkboxes
id: prerequisites id: prerequisites
@ -16,11 +16,11 @@ body:
options: options:
- label: I am running the latest code. Mention the version if possible as well. - label: I am running the latest code. Mention the version if possible as well.
required: true required: true
- label: I carefully followed the [README.md](https://github.com/ggerganov/llama.cpp/blob/master/README.md). - label: I carefully followed the [README.md](https://github.com/ggml-org/llama.cpp/blob/master/README.md).
required: true required: true
- label: I searched using keywords relevant to my issue to make sure that I am creating a new issue that is not already open (or closed). - label: I searched using keywords relevant to my issue to make sure that I am creating a new issue that is not already open (or closed).
required: true required: true
- label: I reviewed the [Discussions](https://github.com/ggerganov/llama.cpp/discussions), and have a new and useful enhancement to share. - label: I reviewed the [Discussions](https://github.com/ggml-org/llama.cpp/discussions), and have a new and useful enhancement to share.
required: true required: true
- type: textarea - type: textarea

View File

@ -6,7 +6,7 @@ body:
- type: markdown - type: markdown
attributes: attributes:
value: | value: |
Don't forget to check for any [duplicate research issue tickets](https://github.com/ggerganov/llama.cpp/issues?q=is%3Aopen+is%3Aissue+label%3A%22research+%F0%9F%94%AC%22) Don't forget to check for any [duplicate research issue tickets](https://github.com/ggml-org/llama.cpp/issues?q=is%3Aopen+is%3Aissue+label%3A%22research+%F0%9F%94%AC%22)
- type: checkboxes - type: checkboxes
id: research-stage id: research-stage

View File

@ -6,8 +6,8 @@ body:
- type: markdown - type: markdown
attributes: attributes:
value: | value: |
Don't forget to [check for existing refactor issue tickets](https://github.com/ggerganov/llama.cpp/issues?q=is%3Aopen+is%3Aissue+label%3Arefactoring) in case it's already covered. Don't forget to [check for existing refactor issue tickets](https://github.com/ggml-org/llama.cpp/issues?q=is%3Aopen+is%3Aissue+label%3Arefactoring) in case it's already covered.
Also you may want to check [Pull request refactor label as well](https://github.com/ggerganov/llama.cpp/pulls?q=is%3Aopen+is%3Apr+label%3Arefactoring) for duplicates too. Also you may want to check [Pull request refactor label as well](https://github.com/ggml-org/llama.cpp/pulls?q=is%3Aopen+is%3Apr+label%3Arefactoring) for duplicates too.
- type: textarea - type: textarea
id: background-description id: background-description

View File

@ -1,11 +1,11 @@
blank_issues_enabled: true blank_issues_enabled: true
contact_links: contact_links:
- name: Got an idea? - name: Got an idea?
url: https://github.com/ggerganov/llama.cpp/discussions/categories/ideas url: https://github.com/ggml-org/llama.cpp/discussions/categories/ideas
about: Pop it there. It may then become an enhancement ticket. about: Pop it there. It may then become an enhancement ticket.
- name: Got a question? - name: Got a question?
url: https://github.com/ggerganov/llama.cpp/discussions/categories/q-a url: https://github.com/ggml-org/llama.cpp/discussions/categories/q-a
about: Ask a question there! about: Ask a question there!
- name: Want to contribute? - name: Want to contribute?
url: https://github.com/ggerganov/llama.cpp/wiki/contribute url: https://github.com/ggml-org/llama.cpp/wiki/contribute
about: Head to the contribution guide page of the wiki for areas you can help with about: Head to the contribution guide page of the wiki for areas you can help with

22
.github/actions/get-tag-name/action.yml vendored Normal file
View File

@ -0,0 +1,22 @@
name: "Determine tag name"
description: "Determine the tag name to use for a release"
outputs:
name:
description: "The name of the tag"
value: ${{ steps.tag.outputs.name }}
runs:
using: "composite"
steps:
- name: Determine tag name
id: tag
shell: bash
run: |
BUILD_NUMBER="$(git rev-list --count HEAD)"
SHORT_HASH="$(git rev-parse --short=7 HEAD)"
if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
else
SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
fi

View File

@ -0,0 +1,67 @@
name: "Windows - Setup CUDA Toolkit"
description: "Setup CUDA Toolkit for Windows"
inputs:
cuda_version:
description: "CUDA toolkit version"
required: true
runs:
using: "composite"
steps:
- name: Install Cuda Toolkit 11.7
if: ${{ inputs.cuda_version == '11.7' }}
shell: pwsh
run: |
mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7"
choco install unzip -y
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-11.7.99-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-11.7.99-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-11.7.99-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-11.7.4.6-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-11.7.91-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-11.7.91-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvprof/windows-x86_64/cuda_nvprof-windows-x86_64-11.7.101-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-11.7.91-archive.zip"
unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7"
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_cudart-windows-x86_64-11.7.99-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvcc-windows-x86_64-11.7.99-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvrtc-windows-x86_64-11.7.99-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\libcublas-windows-x86_64-11.7.4.6-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvtx-windows-x86_64-11.7.91-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\visual_studio_integration-windows-x86_64-11.7.91-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvprof-windows-x86_64-11.7.101-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_cccl-windows-x86_64-11.7.91-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\libnvvp" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
echo "CUDA_PATH_V11_7=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
- name: Install Cuda Toolkit 12.4
if: ${{ inputs.cuda_version == '12.4' }}
shell: pwsh
run: |
mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4"
choco install unzip -y
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-12.4.131-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-12.4.5.8-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_profiler_api/windows-x86_64/cuda_profiler_api-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvprof/windows-x86_64/cuda_nvprof-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-12.4.127-archive.zip"
unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4"
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_cudart-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvcc-windows-x86_64-12.4.131-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvrtc-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\libcublas-windows-x86_64-12.4.5.8-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvtx-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_profiler_api-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\visual_studio_integration-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvprof-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_cccl-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\libnvvp" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
echo "CUDA_PATH_V12_4=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8

View File

@ -0,0 +1,30 @@
name: 'Windows - Setup CURL'
description: 'Composite action, to be reused in other workflow'
inputs:
curl_version:
description: 'CURL version'
required: false
default: '8.6.0_6'
architecture:
description: 'Architecture of the libcurl to download'
required: false
default: 'win64'
outputs:
curl_path:
description: "Path to the downloaded libcurl"
value: ${{ steps.get_libcurl.outputs.curl_path }}
runs:
using: "composite"
steps:
- name: libCURL
id: get_libcurl
shell: powershell
env:
CURL_VERSION: ${{ inputs.curl_version }}
ARCHITECTURE: ${{ inputs.architecture }}
run: |
curl.exe -o $env:RUNNER_TEMP/curl.zip -L "https://curl.se/windows/dl-${env:CURL_VERSION}/curl-${env:CURL_VERSION}-${env:ARCHITECTURE}-mingw.zip"
mkdir $env:RUNNER_TEMP/libcurl
tar.exe -xvf $env:RUNNER_TEMP/curl.zip --strip-components=1 -C $env:RUNNER_TEMP/libcurl
echo "curl_path=$env:RUNNER_TEMP/libcurl" >> $env:GITHUB_OUTPUT

33
.github/labeler.yml vendored
View File

@ -3,19 +3,18 @@ Kompute:
- changed-files: - changed-files:
- any-glob-to-any-file: - any-glob-to-any-file:
- ggml/include/ggml-kompute.h - ggml/include/ggml-kompute.h
- ggml/src/ggml-kompute.cpp - ggml/src/ggml-kompute/**
- README-kompute.md - README-kompute.md
Apple Metal: Apple Metal:
- changed-files: - changed-files:
- any-glob-to-any-file: - any-glob-to-any-file:
- ggml/include/ggml-metal.h - ggml/include/ggml-metal.h
- ggml/src/ggml-metal.cpp - ggml/src/ggml-metal/**
- README-metal.md - README-metal.md
SYCL: SYCL:
- changed-files: - changed-files:
- any-glob-to-any-file: - any-glob-to-any-file:
- ggml/include/ggml-sycl.h - ggml/include/ggml-sycl.h
- ggml/src/ggml-sycl.cpp
- ggml/src/ggml-sycl/** - ggml/src/ggml-sycl/**
- docs/backend/SYCL.md - docs/backend/SYCL.md
- examples/sycl/** - examples/sycl/**
@ -27,8 +26,8 @@ Nvidia GPU:
Vulkan: Vulkan:
- changed-files: - changed-files:
- any-glob-to-any-file: - any-glob-to-any-file:
- ggml/ggml_vk_generate_shaders.py - ggml/include/ggml-vulkan.h
- ggml/src/ggml-vulkan* - ggml/src/ggml-vulkan/**
documentation: documentation:
- changed-files: - changed-files:
- any-glob-to-any-file: - any-glob-to-any-file:
@ -46,7 +45,9 @@ build:
- CMakePresets.json - CMakePresets.json
examples: examples:
- changed-files: - changed-files:
- any-glob-to-any-file: examples/** - any-glob-to-any-file:
- examples/**
- tools/**
devops: devops:
- changed-files: - changed-files:
- any-glob-to-any-file: - any-glob-to-any-file:
@ -71,15 +72,11 @@ android:
server: server:
- changed-files: - changed-files:
- any-glob-to-any-file: - any-glob-to-any-file:
- examples/server/** - tools/server/**
ggml: ggml:
- changed-files: - changed-files:
- any-glob-to-any-file: - any-glob-to-any-file:
- ggml/include/ggml*.h - ggml/**
- ggml/src/ggml*.c
- ggml/src/ggml*.cpp
- ggml/src/ggml*.h
- ggml-cuda/**
nix: nix:
- changed-files: - changed-files:
- any-glob-to-any-file: - any-glob-to-any-file:
@ -89,3 +86,15 @@ nix:
embedding: embedding:
- changed-files: - changed-files:
- any-glob-to-any-file: examples/embedding/ - any-glob-to-any-file: examples/embedding/
Ascend NPU:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-cann.h
- ggml/src/ggml-cann/**
- docs/backend/CANN.md
OpenCL:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-opencl.h
- ggml/src/ggml-opencl/**

View File

@ -1,7 +1 @@
*Make sure to read the [contributing guidelines](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md) before submitting a PR*
- [x] I have read the [contributing guidelines](https://github.com/ggerganov/llama.cpp/blob/master/CONTRIBUTING.md)
- Self-reported review complexity:
- [ ] Low
- [ ] Medium
- [ ] High

View File

@ -1,5 +1,5 @@
# TODO: there have been some issues with the workflow, so disabling for now # TODO: there have been some issues with the workflow, so disabling for now
# https://github.com/ggerganov/llama.cpp/issues/7893 # https://github.com/ggml-org/llama.cpp/issues/7893
# #
# Benchmark # Benchmark
name: Benchmark name: Benchmark
@ -27,10 +27,10 @@ on:
push: push:
branches: branches:
- master - master
paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'examples/server/*.h*', 'examples/server/*.cpp'] paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'tools/server/*.h*', 'tools/server/*.cpp']
pull_request_target: pull_request_target:
types: [opened, synchronize, reopened] types: [opened, synchronize, reopened]
paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'examples/server/*.h*', 'examples/server/*.cpp'] paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'tools/server/*.h*', 'tools/server/*.cpp']
schedule: schedule:
- cron: '04 2 * * *' - cron: '04 2 * * *'
@ -57,17 +57,7 @@ jobs:
if: | if: |
inputs.gpu-series == 'Standard_NC4as_T4_v3' inputs.gpu-series == 'Standard_NC4as_T4_v3'
|| (
github.event_name == 'schedule'
&& github.ref_name == 'master'
&& github.repository_owner == 'ggerganov'
)
|| github.event_name == 'pull_request_target' || github.event_name == 'pull_request_target'
|| (
github.event_name == 'push'
&& github.event.ref == 'refs/heads/master'
&& github.repository_owner == 'ggerganov'
)
steps: steps:
- name: Clone - name: Clone
id: checkout id: checkout
@ -79,7 +69,7 @@ jobs:
- name: Install python env - name: Install python env
id: pipenv id: pipenv
run: | run: |
cd examples/server/bench cd tools/server/bench
python3 -m venv venv python3 -m venv venv
source venv/bin/activate source venv/bin/activate
pip install -r requirements.txt pip install -r requirements.txt
@ -89,7 +79,7 @@ jobs:
run: | run: |
wget --quiet https://github.com/prometheus/prometheus/releases/download/v2.51.0/prometheus-2.51.0.linux-amd64.tar.gz wget --quiet https://github.com/prometheus/prometheus/releases/download/v2.51.0/prometheus-2.51.0.linux-amd64.tar.gz
tar xzf prometheus*.tar.gz --strip-components=1 tar xzf prometheus*.tar.gz --strip-components=1
./prometheus --config.file=examples/server/bench/prometheus.yml & ./prometheus --config.file=tools/server/bench/prometheus.yml &
while ! nc -z localhost 9090; do while ! nc -z localhost 9090; do
sleep 0.1 sleep 0.1
done done
@ -102,7 +92,7 @@ jobs:
- name: Install k6 and xk6-sse - name: Install k6 and xk6-sse
id: k6_installation id: k6_installation
run: | run: |
cd examples/server/bench cd tools/server/bench
go install go.k6.io/xk6/cmd/xk6@latest go install go.k6.io/xk6/cmd/xk6@latest
xk6 build master \ xk6 build master \
--with github.com/phymbert/xk6-sse --with github.com/phymbert/xk6-sse
@ -114,7 +104,6 @@ jobs:
cmake -B build \ cmake -B build \
-DGGML_NATIVE=OFF \ -DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \ -DLLAMA_BUILD_SERVER=ON \
-DLLAMA_CURL=ON \
-DLLAMA_CUBLAS=ON \ -DLLAMA_CUBLAS=ON \
-DCUDAToolkit_ROOT=/usr/local/cuda \ -DCUDAToolkit_ROOT=/usr/local/cuda \
-DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc \ -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc \
@ -127,7 +116,7 @@ jobs:
- name: Download the dataset - name: Download the dataset
id: download_dataset id: download_dataset
run: | run: |
cd examples/server/bench cd tools/server/bench
wget --quiet https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json wget --quiet https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json
- name: Server bench - name: Server bench
@ -137,7 +126,7 @@ jobs:
run: | run: |
set -eux set -eux
cd examples/server/bench cd tools/server/bench
source venv/bin/activate source venv/bin/activate
python bench.py \ python bench.py \
--runner-label ${{ env.RUNNER_LABEL }} \ --runner-label ${{ env.RUNNER_LABEL }} \
@ -168,9 +157,9 @@ jobs:
name: bench-server-${{ github.job }}-${{ env.RUNNER_LABEL }}-${{ matrix.model }}-${{ matrix.ftype }} name: bench-server-${{ github.job }}-${{ env.RUNNER_LABEL }}-${{ matrix.model }}-${{ matrix.ftype }}
compression-level: 9 compression-level: 9
path: | path: |
examples/server/bench/*.jpg tools/server/bench/*.jpg
examples/server/bench/*.json tools/server/bench/*.json
examples/server/bench/*.log tools/server/bench/*.log
- name: Commit status - name: Commit status
uses: Sibz/github-status-action@v1 uses: Sibz/github-status-action@v1
@ -189,17 +178,17 @@ jobs:
with: with:
client_id: ${{secrets.IMGUR_CLIENT_ID}} client_id: ${{secrets.IMGUR_CLIENT_ID}}
path: | path: |
examples/server/bench/prompt_tokens_seconds.jpg tools/server/bench/prompt_tokens_seconds.jpg
examples/server/bench/predicted_tokens_seconds.jpg tools/server/bench/predicted_tokens_seconds.jpg
examples/server/bench/kv_cache_usage_ratio.jpg tools/server/bench/kv_cache_usage_ratio.jpg
examples/server/bench/requests_processing.jpg tools/server/bench/requests_processing.jpg
- name: Extract mermaid - name: Extract mermaid
id: set_mermaid id: set_mermaid
run: | run: |
set -eux set -eux
cd examples/server/bench cd tools/server/bench
PROMPT_TOKENS_SECONDS=$(cat prompt_tokens_seconds.mermaid) PROMPT_TOKENS_SECONDS=$(cat prompt_tokens_seconds.mermaid)
echo "PROMPT_TOKENS_SECONDS<<EOF" >> $GITHUB_ENV echo "PROMPT_TOKENS_SECONDS<<EOF" >> $GITHUB_ENV
echo "$PROMPT_TOKENS_SECONDS" >> $GITHUB_ENV echo "$PROMPT_TOKENS_SECONDS" >> $GITHUB_ENV

51
.github/workflows/build-cmake-pkg.yml vendored Normal file
View File

@ -0,0 +1,51 @@
name: Build relocatable cmake package
on:
workflow_dispatch:
workflow_call:
jobs:
linux:
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y build-essential tcl
- name: Build
run: |
PREFIX="$(pwd)"/inst
cmake -S . -B build -DCMAKE_PREFIX_PATH="$PREFIX" \
-DLLAMA_CURL=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF -DCMAKE_BUILD_TYPE=Release
cmake --build build --config Release
cmake --install build --prefix "$PREFIX" --config Release
export LLAMA_CONFIG="$PREFIX"/lib/cmake/llama/llama-config.cmake
tclsh <<'EOF'
set build(commit) [string trim [exec git rev-parse --short HEAD]]
set build(number) [string trim [exec git rev-list --count HEAD]]
set build(version) "0.0.$build(number)"
set llamaconfig [read [open "$env(LLAMA_CONFIG)" r]]
set checks [list "set\\(LLAMA_VERSION \\s+$build(version)\\)" \
"set\\(LLAMA_BUILD_COMMIT\\s+$build(commit)\\)" \
"set\\(LLAMA_BUILD_NUMBER\\s+$build(number)\\)"]
puts -nonewline "Checking llama-config.cmake version... "
foreach check $checks {
if {![regexp -expanded -- $check $llamaconfig]} {
puts "\"$check\" failed!"
exit 1
}
}
puts "success."
EOF
cd examples/simple-cmake-pkg
cmake -S . -B build -DCMAKE_PREFIX_PATH="$PREFIX"/lib/cmake
cmake --build build

346
.github/workflows/build-linux-cross.yml vendored Normal file
View File

@ -0,0 +1,346 @@
name: Build on Linux using cross-compiler
on:
workflow_dispatch:
workflow_call:
jobs:
ubuntu-24-riscv64-cpu-cross:
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v4
- name: Setup Riscv
run: |
sudo dpkg --add-architecture riscv64
# Add arch-specific repositories for non-amd64 architectures
cat << EOF | sudo tee /etc/apt/sources.list.d/riscv64-ports.list
deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble main universe
deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-updates main universe
deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-security main universe
deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-backports main universe
EOF
sudo apt-get update || true ;# Prevent failure due to missing URLs.
sudo apt-get install -y --no-install-recommends \
build-essential \
gcc-14-riscv64-linux-gnu \
g++-14-riscv64-linux-gnu
- name: Build
run: |
cmake -B build -DLLAMA_CURL=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=riscv64 \
-DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/riscv64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)
ubuntu-24-riscv64-vulkan-cross:
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v4
- name: Setup Riscv
run: |
sudo dpkg --add-architecture riscv64
# Add arch-specific repositories for non-amd64 architectures
cat << EOF | sudo tee /etc/apt/sources.list.d/riscv64-ports.list
deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble main universe
deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-updates main universe
deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-security main universe
deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-backports main universe
EOF
sudo apt-get update || true ;# Prevent failure due to missing URLs.
sudo apt-get install -y --no-install-recommends \
build-essential \
glslc \
gcc-14-riscv64-linux-gnu \
g++-14-riscv64-linux-gnu \
libvulkan-dev:riscv64
- name: Build
run: |
cmake -B build -DLLAMA_CURL=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_VULKAN=ON \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=riscv64 \
-DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/riscv64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)
ubuntu-24-arm64-vulkan-cross:
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v4
- name: Setup Arm64
run: |
sudo dpkg --add-architecture arm64
# Add arch-specific repositories for non-amd64 architectures
cat << EOF | sudo tee /etc/apt/sources.list.d/arm64-ports.list
deb [arch=arm64] http://ports.ubuntu.com/ubuntu-ports/ noble main universe
deb [arch=arm64] http://ports.ubuntu.com/ubuntu-ports/ noble-updates main universe
deb [arch=arm64] http://ports.ubuntu.com/ubuntu-ports/ noble-security main universe
deb [arch=arm64] http://ports.ubuntu.com/ubuntu-ports/ noble-backports main universe
EOF
sudo apt-get update || true ;# Prevent failure due to missing URLs.
sudo apt-get install -y --no-install-recommends \
build-essential \
glslc \
crossbuild-essential-arm64 \
libvulkan-dev:arm64
- name: Build
run: |
cmake -B build -DLLAMA_CURL=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_VULKAN=ON \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=aarch64 \
-DCMAKE_C_COMPILER=aarch64-linux-gnu-gcc \
-DCMAKE_CXX_COMPILER=aarch64-linux-gnu-g++ \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/aarch64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)
ubuntu-24-ppc64el-cpu-cross:
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v4
- name: Setup PowerPC64le
run: |
sudo dpkg --add-architecture ppc64el
# Add arch-specific repositories for non-amd64 architectures
cat << EOF | sudo tee /etc/apt/sources.list.d/ppc64el-ports.list
deb [arch=ppc64el] http://ports.ubuntu.com/ubuntu-ports/ noble main universe
deb [arch=ppc64el] http://ports.ubuntu.com/ubuntu-ports/ noble-updates main universe
deb [arch=ppc64el] http://ports.ubuntu.com/ubuntu-ports/ noble-security main universe
deb [arch=ppc64el] http://ports.ubuntu.com/ubuntu-ports/ noble-backports main universe
EOF
sudo apt-get update || true ;# Prevent failure due to missing URLs.
sudo apt-get install -y --no-install-recommends \
build-essential \
gcc-14-powerpc64le-linux-gnu \
g++-14-powerpc64le-linux-gnu
- name: Build
run: |
cmake -B build -DLLAMA_CURL=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=ppc64 \
-DCMAKE_C_COMPILER=powerpc64le-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=powerpc64le-linux-gnu-g++-14 \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/powerpc64le-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)
ubuntu-24-ppc64el-vulkan-cross:
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v4
- name: Setup PowerPC64le
run: |
sudo dpkg --add-architecture ppc64el
# Add arch-specific repositories for non-amd64 architectures
cat << EOF | sudo tee /etc/apt/sources.list.d/ppc64el-ports.list
deb [arch=ppc64el] http://ports.ubuntu.com/ubuntu-ports/ noble main universe
deb [arch=ppc64el] http://ports.ubuntu.com/ubuntu-ports/ noble-updates main universe
deb [arch=ppc64el] http://ports.ubuntu.com/ubuntu-ports/ noble-security main universe
deb [arch=ppc64el] http://ports.ubuntu.com/ubuntu-ports/ noble-backports main universe
EOF
sudo apt-get update || true ;# Prevent failure due to missing URLs.
sudo apt-get install -y --no-install-recommends \
build-essential \
glslc \
gcc-14-powerpc64le-linux-gnu \
g++-14-powerpc64le-linux-gnu \
libvulkan-dev:ppc64el
- name: Build
run: |
cmake -B build -DLLAMA_CURL=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_VULKAN=ON \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=ppc64 \
-DCMAKE_C_COMPILER=powerpc64le-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=powerpc64le-linux-gnu-g++-14 \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/powerpc64le-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)
debian-13-loongarch64-cpu-cross:
runs-on: ubuntu-24.04
container: debian@sha256:653dfb9f86c3782e8369d5f7d29bb8faba1f4bff9025db46e807fa4c22903671
steps:
- uses: actions/checkout@v4
- name: Setup LoongArch
run: |
rm -f /etc/apt/sources.list.d/*
cat << EOF | tee /etc/apt/sources.list.d/debian-ports.list
deb http://snapshot.debian.org/archive/debian/20250515T202920Z/ trixie main
EOF
( echo 'quiet "true";'; \
echo 'APT::Get::Assume-Yes "true";'; \
echo 'APT::Install-Recommends "false";'; \
echo 'Acquire::Check-Valid-Until "false";'; \
echo 'Acquire::Retries "5";'; \
) > /etc/apt/apt.conf.d/99snapshot-repos
apt-get update
apt-get install -y ca-certificates debian-ports-archive-keyring cmake git zip
dpkg --add-architecture loong64
# Add arch-specific repositories for non-amd64 architectures
cat << EOF | tee /etc/apt/sources.list.d/loong64-ports.list
deb [arch=loong64] http://snapshot.debian.org/archive/debian-ports/20250515T194251Z/ sid main
EOF
apt-get update || true ;# Prevent failure due to missing URLs.
apt-get install -y --no-install-recommends \
build-essential \
gcc-14-loongarch64-linux-gnu \
g++-14-loongarch64-linux-gnu
- name: Build
run: |
cmake -B build -DLLAMA_CURL=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=loongarch64 \
-DCMAKE_C_COMPILER=loongarch64-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=loongarch64-linux-gnu-g++-14 \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/loongarch64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)
debian-13-loongarch64-vulkan-cross:
runs-on: ubuntu-24.04
container: debian@sha256:653dfb9f86c3782e8369d5f7d29bb8faba1f4bff9025db46e807fa4c22903671
steps:
- uses: actions/checkout@v4
- name: Setup LoongArch
run: |
rm -f /etc/apt/sources.list.d/*
cat << EOF | tee /etc/apt/sources.list.d/debian-ports.list
deb http://snapshot.debian.org/archive/debian/20250515T202920Z/ trixie main
EOF
( echo 'quiet "true";'; \
echo 'APT::Get::Assume-Yes "true";'; \
echo 'APT::Install-Recommends "false";'; \
echo 'Acquire::Check-Valid-Until "false";'; \
echo 'Acquire::Retries "5";'; \
) > /etc/apt/apt.conf.d/99snapshot-repos
apt-get update
apt-get install -y ca-certificates debian-ports-archive-keyring cmake git zip
dpkg --add-architecture loong64
# Add arch-specific repositories for non-amd64 architectures
cat << EOF | tee /etc/apt/sources.list.d/loong64-ports.list
deb [arch=loong64] http://snapshot.debian.org/archive/debian-ports/20250515T194251Z/ sid main
EOF
apt-get update || true ;# Prevent failure due to missing URLs.
apt-get install -y --no-install-recommends \
build-essential \
glslc \
gcc-14-loongarch64-linux-gnu \
g++-14-loongarch64-linux-gnu \
libvulkan-dev:loong64
- name: Build
run: |
cmake -B build -DLLAMA_CURL=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_VULKAN=ON \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=loongarch64 \
-DCMAKE_C_COMPILER=loongarch64-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=loongarch64-linux-gnu-g++-14 \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/loongarch64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)

File diff suppressed because it is too large Load Diff

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@ -17,7 +17,7 @@ jobs:
steps: steps:
- uses: actions/stale@v5 - uses: actions/stale@v5
with: with:
exempt-issue-labels: "refactor,help wanted,good first issue,research,bug" exempt-issue-labels: "refactor,help wanted,good first issue,research,bug,roadmap"
days-before-issue-stale: 30 days-before-issue-stale: 30
days-before-issue-close: 14 days-before-issue-close: 14
stale-issue-label: "stale" stale-issue-label: "stale"

View File

@ -10,12 +10,10 @@
name: Publish Docker image name: Publish Docker image
on: on:
#pull_request: workflow_dispatch: # allows manual triggering
push: schedule:
branches: # Rebuild daily rather than on every push because it is expensive
- master - cron: '12 4 * * *'
paths: ['.github/workflows/docker.yml', '.devops/*.Dockerfile', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal']
workflow_dispatch: # allows manual triggering, useful for debugging
concurrency: concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }} group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
@ -29,29 +27,25 @@ permissions:
jobs: jobs:
push_to_registry: push_to_registry:
name: Push Docker image to Docker Hub name: Push Docker image to Docker Hub
#if: github.event.pull_request.draft == false
runs-on: ubuntu-latest runs-on: ubuntu-22.04
env: env:
COMMIT_SHA: ${{ github.sha }} COMMIT_SHA: ${{ github.sha }}
strategy: strategy:
fail-fast: false
matrix: matrix:
config: config:
- { tag: "light", dockerfile: ".devops/llama-cli.Dockerfile", platforms: "linux/amd64,linux/arm64" } # Multi-stage build
- { tag: "server", dockerfile: ".devops/llama-server.Dockerfile", platforms: "linux/amd64,linux/arm64" } # Note: the arm64 images are failing, which prevents the amd64 images from being built
- { tag: "full", dockerfile: ".devops/full.Dockerfile", platforms: "linux/amd64,linux/arm64" } # https://github.com/ggml-org/llama.cpp/issues/11888
- { tag: "light-cuda", dockerfile: ".devops/llama-cli-cuda.Dockerfile", platforms: "linux/amd64" } #- { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64,linux/arm64", full: true, light: true, server: true, free_disk_space: false }
- { tag: "server-cuda", dockerfile: ".devops/llama-server-cuda.Dockerfile", platforms: "linux/amd64" } - { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
- { tag: "full-cuda", dockerfile: ".devops/full-cuda.Dockerfile", platforms: "linux/amd64" } - { tag: "cuda", dockerfile: ".devops/cuda.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
- { tag: "light-musa", dockerfile: ".devops/llama-cli-musa.Dockerfile", platforms: "linux/amd64" } - { tag: "musa", dockerfile: ".devops/musa.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true }
- { tag: "server-musa", dockerfile: ".devops/llama-server-musa.Dockerfile", platforms: "linux/amd64" } - { tag: "intel", dockerfile: ".devops/intel.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true }
- { tag: "full-musa", dockerfile: ".devops/full-musa.Dockerfile", platforms: "linux/amd64" } - { tag: "vulkan", dockerfile: ".devops/vulkan.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
# Note: the rocm images are failing due to a compiler error and are disabled until this is fixed to allow the workflow to complete # Note: the rocm images are failing due to a compiler error and are disabled until this is fixed to allow the workflow to complete
#- { tag: "light-rocm", dockerfile: ".devops/llama-cli-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" } #- {tag: "rocm", dockerfile: ".devops/rocm.Dockerfile", platforms: "linux/amd64,linux/arm64", full: true, light: true, server: true, free_disk_space: true }
#- { tag: "server-rocm", dockerfile: ".devops/llama-server-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
#- { tag: "full-rocm", dockerfile: ".devops/full-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "light-intel", dockerfile: ".devops/llama-cli-intel.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-intel", dockerfile: ".devops/llama-server-intel.Dockerfile", platforms: "linux/amd64" }
steps: steps:
- name: Check out the repo - name: Check out the repo
uses: actions/checkout@v4 uses: actions/checkout@v4
@ -59,10 +53,12 @@ jobs:
fetch-depth: 0 # preserve git history, so we can determine the build number fetch-depth: 0 # preserve git history, so we can determine the build number
- name: Set up QEMU - name: Set up QEMU
uses: docker/setup-qemu-action@v2 uses: docker/setup-qemu-action@v3
with:
image: tonistiigi/binfmt:qemu-v7.0.0-28
- name: Set up Docker Buildx - name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2 uses: docker/setup-buildx-action@v3
- name: Log in to Docker Hub - name: Log in to Docker Hub
uses: docker/login-action@v2 uses: docker/login-action@v2
@ -82,26 +78,34 @@ jobs:
# determine tag name postfix (build number, commit hash) # determine tag name postfix (build number, commit hash)
if [[ "${{ env.GITHUB_BRANCH_NAME }}" == "master" ]]; then if [[ "${{ env.GITHUB_BRANCH_NAME }}" == "master" ]]; then
TAG_POSTFIX="b${BUILD_NUMBER}" TAG_POSTFIX="-b${BUILD_NUMBER}"
else else
SAFE_NAME=$(echo "${{ env.GITHUB_BRANCH_NAME }}" | tr '/' '-') SAFE_NAME=$(echo "${{ env.GITHUB_BRANCH_NAME }}" | tr '/' '-')
TAG_POSTFIX="${SAFE_NAME}-${SHORT_HASH}" TAG_POSTFIX="-${SAFE_NAME}-${SHORT_HASH}"
fi fi
# list all tags possible # list all tags possible
TAGS="" if [[ "${{ matrix.config.tag }}" == "cpu" ]]; then
TAGS="${TAGS}ghcr.io/${REPO_OWNER}/${REPO_NAME}:${{ matrix.config.tag }}," TYPE=""
TAGS="${TAGS}ghcr.io/${REPO_OWNER}/${REPO_NAME}:${{ matrix.config.tag }}-${TAG_POSTFIX}" else
TYPE="-${{ matrix.config.tag }}"
echo "output_tags=$TAGS" >> $GITHUB_OUTPUT fi
echo "output_tags=$TAGS" # print out for debugging PREFIX="ghcr.io/${REPO_OWNER}/${REPO_NAME}:"
FULLTAGS="${PREFIX}full${TYPE},${PREFIX}full${TYPE}${TAG_POSTFIX}"
LIGHTTAGS="${PREFIX}light${TYPE},${PREFIX}light${TYPE}${TAG_POSTFIX}"
SERVERTAGS="${PREFIX}server${TYPE},${PREFIX}server${TYPE}${TAG_POSTFIX}"
echo "full_output_tags=$FULLTAGS" >> $GITHUB_OUTPUT
echo "light_output_tags=$LIGHTTAGS" >> $GITHUB_OUTPUT
echo "server_output_tags=$SERVERTAGS" >> $GITHUB_OUTPUT
echo "full_output_tags=$FULLTAGS" # print out for debugging
echo "light_output_tags=$LIGHTTAGS" # print out for debugging
echo "server_output_tags=$SERVERTAGS" # print out for debugging
env: env:
GITHUB_BRANCH_NAME: ${{ github.head_ref || github.ref_name }} GITHUB_BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}' GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}'
# https://github.com/jlumbroso/free-disk-space/tree/54081f138730dfa15788a46383842cd2f914a1be#example
- name: Free Disk Space (Ubuntu) - name: Free Disk Space (Ubuntu)
uses: jlumbroso/free-disk-space@main if: ${{ matrix.config.free_disk_space == true }}
uses: ggml-org/free-disk-space@v1.3.1
with: with:
# this might remove tools that are actually needed, # this might remove tools that are actually needed,
# if set to "true" but frees about 6 GB # if set to "true" but frees about 6 GB
@ -116,13 +120,59 @@ jobs:
docker-images: true docker-images: true
swap-storage: true swap-storage: true
- name: Build and push Docker image (tagged + versioned) - name: Build and push Full Docker image (tagged + versioned)
if: github.event_name == 'push' if: ${{ (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && matrix.config.full == true }}
uses: docker/build-push-action@v6 uses: docker/build-push-action@v6
with: with:
context: . context: .
push: true push: true
platforms: ${{ matrix.config.platforms }} platforms: ${{ matrix.config.platforms }}
# tag list is generated from step above # tag list is generated from step above
tags: ${{ steps.tag.outputs.output_tags }} tags: ${{ steps.tag.outputs.full_output_tags }}
file: ${{ matrix.config.dockerfile }} file: ${{ matrix.config.dockerfile }}
target: full
provenance: false
# 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
- 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
# 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
- 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
# 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

View File

@ -23,5 +23,7 @@ jobs:
runs-on: ubuntu-latest runs-on: ubuntu-latest
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
- uses: editorconfig-checker/action-editorconfig-checker@main - uses: editorconfig-checker/action-editorconfig-checker@v2
with:
version: v3.0.3
- run: editorconfig-checker - run: editorconfig-checker

View File

@ -11,7 +11,7 @@ jobs:
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
with: with:
repository: "ggerganov/llama.cpp" repository: "ggml-org/llama.cpp"
- uses: actions/labeler@v5 - uses: actions/labeler@v5
with: with:
configuration-path: '.github/labeler.yml' configuration-path: '.github/labeler.yml'

View File

@ -1,72 +0,0 @@
name: Nix aarch64 builds
on:
workflow_dispatch: # allows manual triggering
schedule:
# Rebuild daily rather than on every push because QEMU is expensive (e.g.
# 1.5h instead of minutes with the cold cache).
#
# randint(0, 59), randint(0, 23)
- cron: '26 12 * * *'
# But also rebuild if we touched any of the Nix expressions:
push:
branches:
- master
paths: ['**/*.nix', 'flake.lock']
pull_request:
types: [opened, synchronize, reopened]
paths: ['**/*.nix', 'flake.lock']
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
# Fine-grant permission
# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
permissions:
# https://github.com/DeterminateSystems/nix-installer-action?tab=readme-ov-file#with-flakehub
id-token: write
contents: read
jobs:
nix-build-aarch64:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Install QEMU
# Copy-paste from https://github.com/orgs/community/discussions/8305#discussioncomment-5888654
run: |
sudo apt-get update
sudo apt-get install -y qemu-user-static qemu-system-aarch64
sudo usermod -a -G kvm $USER
- name: Install Nix
uses: DeterminateSystems/nix-installer-action@v9
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
extra-conf: |
extra-platforms = aarch64-linux
extra-system-features = nixos-test kvm
extra-substituters = https://llama-cpp.cachix.org https://cuda-maintainers.cachix.org
extra-trusted-public-keys = llama-cpp.cachix.org-1:H75X+w83wUKTIPSO1KWy9ADUrzThyGs8P5tmAbkWhQc= cuda-maintainers.cachix.org-1:0dq3bujKpuEPMCX6U4WylrUDZ9JyUG0VpVZa7CNfq5E=
- uses: DeterminateSystems/magic-nix-cache-action@v2
with:
upstream-cache: https://${{ matrix.cachixName }}.cachix.org
- name: Set-up cachix to push the results to
uses: cachix/cachix-action@v13
with:
authToken: '${{ secrets.CACHIX_AUTH_TOKEN }}'
name: llama-cpp
- name: Show all output paths
run: >
nix run github:nix-community/nix-eval-jobs
-- --gc-roots-dir gcroot
--flake
".#packages.aarch64-linux"
- name: Build
run: >
nix run github:Mic92/nix-fast-build
-- --skip-cached --no-nom
--systems aarch64-linux
--flake
".#checks.aarch64-linux"

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@ -1,79 +0,0 @@
name: Nix CI
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
pull_request:
types: [opened, synchronize, reopened]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
# Fine-grant permission
# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
permissions:
# https://github.com/DeterminateSystems/nix-installer-action?tab=readme-ov-file#with-flakehub
id-token: write
contents: read
jobs:
nix-eval:
strategy:
fail-fast: false
matrix:
os: [ ubuntu-latest, macos-latest ]
runs-on: ${{ matrix.os }}
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Install Nix
uses: DeterminateSystems/nix-installer-action@v9
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
extra-conf: |
extra-substituters = https://llama-cpp.cachix.org https://cuda-maintainers.cachix.org
extra-trusted-public-keys = llama-cpp.cachix.org-1:H75X+w83wUKTIPSO1KWy9ADUrzThyGs8P5tmAbkWhQc= cuda-maintainers.cachix.org-1:0dq3bujKpuEPMCX6U4WylrUDZ9JyUG0VpVZa7CNfq5E=
- uses: DeterminateSystems/magic-nix-cache-action@v2
with:
upstream-cache: https://${{ matrix.cachixName }}.cachix.org
- name: List all flake outputs
run: nix flake show --all-systems
- name: Show all output paths
run: >
nix run github:nix-community/nix-eval-jobs
-- --gc-roots-dir gcroot
--flake
".#packages.$(nix eval --raw --impure --expr builtins.currentSystem)"
nix-build:
strategy:
fail-fast: false
matrix:
os: [ ubuntu-latest, macos-latest ]
runs-on: ${{ matrix.os }}
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Install Nix
uses: DeterminateSystems/nix-installer-action@v9
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
extra-conf: |
extra-substituters = https://llama-cpp.cachix.org https://cuda-maintainers.cachix.org
extra-trusted-public-keys = llama-cpp.cachix.org-1:H75X+w83wUKTIPSO1KWy9ADUrzThyGs8P5tmAbkWhQc= cuda-maintainers.cachix.org-1:0dq3bujKpuEPMCX6U4WylrUDZ9JyUG0VpVZa7CNfq5E=
- uses: DeterminateSystems/magic-nix-cache-action@v2
with:
upstream-cache: https://${{ matrix.cachixName }}.cachix.org
- name: Set-up cachix to push the results to
uses: cachix/cachix-action@v13
with:
authToken: '${{ secrets.CACHIX_AUTH_TOKEN }}'
name: llama-cpp
- name: Build
run: >
nix run github:Mic92/nix-fast-build
-- --skip-cached --no-nom
--flake
".#checks.$(nix eval --raw --impure --expr builtins.currentSystem)"

View File

@ -1,22 +0,0 @@
name: update-flake-lock
on:
workflow_dispatch:
schedule:
- cron: '0 0 * * 0' # runs weekly on Sunday at 00:00
jobs:
lockfile:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Install Nix
uses: DeterminateSystems/nix-installer-action@main
- name: Update flake.lock
uses: DeterminateSystems/update-flake-lock@main
with:
pr-title: "nix: update flake.lock"
pr-labels: |
nix
pr-reviewers: philiptaron,SomeoneSerge
token: ${{ secrets.FLAKE_TOKEN }}

View File

@ -1,36 +0,0 @@
# Make the flake discoverable on https://flakestry.dev and https://flakehub.com/flakes
name: "Publish a flake to flakestry & flakehub"
on:
push:
tags:
- "*"
workflow_dispatch:
inputs:
tag:
description: "The existing tag to publish"
type: "string"
required: true
jobs:
flakestry-publish:
runs-on: ubuntu-latest
permissions:
id-token: "write"
contents: "read"
steps:
- uses: flakestry/flakestry-publish@main
with:
version: "${{ inputs.tag || github.ref_name }}"
flakehub-publish:
runs-on: "ubuntu-latest"
permissions:
id-token: "write"
contents: "read"
steps:
- uses: "actions/checkout@v4"
with:
ref: "${{ (inputs.tag != null) && format('refs/tags/{0}', inputs.tag) || '' }}"
- uses: "DeterminateSystems/nix-installer-action@main"
- uses: "DeterminateSystems/flakehub-push@main"
with:
visibility: "public"
tag: "${{ inputs.tag }}"

View File

@ -1,6 +1,13 @@
name: flake8 Lint name: flake8 Lint
on: [push, pull_request] on:
push:
branches:
- master
paths: ['.github/workflows/python-lint.yml', '**/*.py']
pull_request:
types: [opened, synchronize, reopened]
paths: ['.github/workflows/python-lint.yml', '**/*.py']
concurrency: concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }} group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}

755
.github/workflows/release.yml vendored Normal file
View File

@ -0,0 +1,755 @@
name: Release
on:
workflow_dispatch: # allows manual triggering
inputs:
create_release:
description: 'Create new release'
required: true
type: boolean
push:
branches:
- master
paths: ['.github/workflows/release.yml', '**/CMakeLists.txt', '**/.cmake', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal', '**/*.comp']
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
env:
BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
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
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: macOS-latest-cmake-arm64
evict-old-files: 1d
- name: Dependencies
id: depends
continue-on-error: true
run: |
brew update
brew install curl
- name: Build
id: cmake_build
run: |
sysctl -a
cmake -B build \
-DCMAKE_INSTALL_RPATH='@loader_path' \
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
-DLLAMA_FATAL_WARNINGS=ON \
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DGGML_RPC=ON \
${{ env.CMAKE_ARGS }}
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
cp LICENSE ./build/bin/
zip -r llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip ./build/bin/*
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip
name: llama-bin-macos-arm64.zip
macOS-x64:
runs-on: macos-13
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: macOS-latest-cmake-x64
evict-old-files: 1d
- name: Dependencies
id: depends
continue-on-error: true
run: |
brew update
brew install curl
- 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 \
-DGGML_METAL=OFF \
-DGGML_RPC=ON
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
cp LICENSE ./build/bin/
zip -r llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip ./build/bin/*
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip
name: llama-bin-macos-x64.zip
ubuntu-22-cpu:
strategy:
matrix:
include:
- build: 'x64'
os: ubuntu-22.04
# GGML_BACKEND_DL and GGML_CPU_ALL_VARIANTS are not currently supported on arm
# - build: 'arm64'
# os: ubuntu-22.04-arm
runs-on: ${{ matrix.os }}
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-cpu-cmake
evict-old-files: 1d
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install build-essential libcurl4-openssl-dev
- name: Build
id: cmake_build
run: |
cmake -B build \
-DCMAKE_INSTALL_RPATH='$ORIGIN' \
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
-DGGML_BACKEND_DL=ON \
-DGGML_NATIVE=OFF \
-DGGML_CPU_ALL_VARIANTS=ON \
-DLLAMA_FATAL_WARNINGS=ON \
${{ env.CMAKE_ARGS }}
cmake --build build --config Release -j $(nproc)
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
cp LICENSE ./build/bin/
zip -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip ./build/bin/*
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip
name: llama-bin-ubuntu-${{ matrix.build }}.zip
ubuntu-22-vulkan:
runs-on: ubuntu-22.04
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: ubuntu-22-cmake-vulkan
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 libcurl4-openssl-dev
- name: Build
id: cmake_build
run: |
cmake -B build \
-DCMAKE_INSTALL_RPATH='$ORIGIN' \
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
-DGGML_BACKEND_DL=ON \
-DGGML_NATIVE=OFF \
-DGGML_CPU_ALL_VARIANTS=ON \
-DGGML_VULKAN=ON \
${{ env.CMAKE_ARGS }}
cmake --build build --config Release -j $(nproc)
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
cp LICENSE ./build/bin/
zip -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip ./build/bin/*
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip
name: llama-bin-ubuntu-vulkan-x64.zip
windows-cpu:
runs-on: windows-2025
strategy:
matrix:
include:
- arch: 'x64'
- arch: 'arm64'
steps:
- name: Clone
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: windows-latest-cmake-cpu-${{ matrix.arch }}
variant: ccache
evict-old-files: 1d
- name: Install Ninja
run: |
choco install ninja
- name: libCURL
id: get_libcurl
uses: ./.github/actions/windows-setup-curl
with:
architecture: ${{ matrix.arch == 'x64' && 'win64' || 'win64a' }}
- name: Build
shell: cmd
env:
CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" ${{ matrix.arch == 'x64' && 'x64' || 'amd64_arm64' }}
cmake -S . -B build -G "Ninja Multi-Config" ^
-D CMAKE_TOOLCHAIN_FILE=cmake/${{ matrix.arch }}-windows-llvm.cmake ^
-DGGML_NATIVE=OFF ^
-DGGML_BACKEND_DL=ON ^
-DGGML_CPU_ALL_VARIANTS=${{ matrix.arch == 'x64' && 'ON' || 'OFF' }} ^
-DGGML_OPENMP=ON ^
-DCURL_LIBRARY="%CURL_PATH%/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="%CURL_PATH%/include" ^
${{ env.CMAKE_ARGS }}
cmake --build build --config Release
- name: Pack artifacts
id: pack_artifacts
env:
CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
run: |
Copy-Item $env:CURL_PATH\bin\libcurl-${{ matrix.arch }}.dll .\build\bin\Release\
Copy-Item "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Redist\MSVC\14.44.35112\debug_nonredist\${{ matrix.arch }}\Microsoft.VC143.OpenMP.LLVM\libomp140.${{ matrix.arch == 'x64' && 'x86_64' || 'aarch64' }}.dll" .\build\bin\Release\
7z a llama-bin-win-cpu-${{ matrix.arch }}.zip .\build\bin\Release\*
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: llama-bin-win-cpu-${{ matrix.arch }}.zip
name: llama-bin-win-cpu-${{ matrix.arch }}.zip
windows:
runs-on: windows-2025
env:
OPENBLAS_VERSION: 0.3.23
VULKAN_VERSION: 1.4.313.2
strategy:
matrix:
include:
- backend: 'vulkan'
arch: 'x64'
defines: '-DGGML_VULKAN=ON'
target: 'ggml-vulkan'
- backend: 'opencl-adreno'
arch: 'arm64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" -DGGML_OPENCL=ON -DGGML_OPENCL_USE_ADRENO_KERNELS=ON'
target: 'ggml-opencl'
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: windows-latest-cmake-${{ matrix.backend }}-${{ matrix.arch }}
variant: ccache
evict-old-files: 1d
- name: Install Vulkan SDK
id: get_vulkan
if: ${{ matrix.backend == 'vulkan' }}
run: |
curl.exe -o $env:RUNNER_TEMP/VulkanSDK-Installer.exe -L "https://sdk.lunarg.com/sdk/download/${env:VULKAN_VERSION}/windows/vulkansdk-windows-X64-${env:VULKAN_VERSION}.exe"
& "$env:RUNNER_TEMP\VulkanSDK-Installer.exe" --accept-licenses --default-answer --confirm-command install
Add-Content $env:GITHUB_ENV "VULKAN_SDK=C:\VulkanSDK\${env:VULKAN_VERSION}"
Add-Content $env:GITHUB_PATH "C:\VulkanSDK\${env:VULKAN_VERSION}\bin"
- name: Install Ninja
id: install_ninja
run: |
choco install ninja
- name: Install OpenCL Headers and Libs
id: install_opencl
if: ${{ matrix.backend == 'opencl-adreno' && matrix.arch == 'arm64' }}
run: |
git clone https://github.com/KhronosGroup/OpenCL-Headers
cd OpenCL-Headers
cmake -B build `
-DBUILD_TESTING=OFF `
-DOPENCL_HEADERS_BUILD_TESTING=OFF `
-DOPENCL_HEADERS_BUILD_CXX_TESTS=OFF `
-DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
cmake --build build --target install
git clone https://github.com/KhronosGroup/OpenCL-ICD-Loader
cd OpenCL-ICD-Loader
cmake -B build-arm64-release `
-A arm64 `
-DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" `
-DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
cmake --build build-arm64-release --target install --config release
- name: Build
id: cmake_build
run: |
cmake -S . -B build ${{ matrix.defines }} -DGGML_NATIVE=OFF -DGGML_CPU=OFF -DGGML_BACKEND_DL=ON -DLLAMA_CURL=OFF
cmake --build build --config Release --target ${{ matrix.target }}
- name: Pack artifacts
id: pack_artifacts
run: |
7z a llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip .\build\bin\Release\${{ matrix.target }}.dll
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip
name: llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip
windows-cuda:
runs-on: windows-2022
strategy:
matrix:
cuda: ['12.4']
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
- name: Install ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: windows-cuda-${{ matrix.cuda }}
variant: ccache
evict-old-files: 1d
- name: Install Cuda Toolkit
uses: ./.github/actions/windows-setup-cuda
with:
cuda_version: ${{ matrix.cuda }}
- name: Install Ninja
id: install_ninja
run: |
choco install ninja
- name: Build
id: cmake_build
shell: cmd
run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64
cmake -S . -B build -G "Ninja Multi-Config" ^
-DGGML_BACKEND_DL=ON ^
-DGGML_NATIVE=OFF ^
-DGGML_CPU=OFF ^
-DGGML_CUDA=ON ^
-DLLAMA_CURL=OFF
set /A NINJA_JOBS=%NUMBER_OF_PROCESSORS%-1
cmake --build build --config Release -j %NINJA_JOBS% --target ggml-cuda
- name: Pack artifacts
id: pack_artifacts
run: |
7z a llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip .\build\bin\Release\ggml-cuda.dll
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip
name: llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip
- name: Copy and pack Cuda runtime
run: |
echo "Cuda install location: ${{ env.CUDA_PATH }}"
$dst='.\build\bin\cudart\'
robocopy "${{env.CUDA_PATH}}\bin" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll
robocopy "${{env.CUDA_PATH}}\lib" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll
7z a cudart-llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip $dst\*
- name: Upload Cuda runtime
uses: actions/upload-artifact@v4
with:
path: cudart-llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip
name: cudart-llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip
windows-sycl:
runs-on: windows-2022
defaults:
run:
shell: bash
env:
WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/7cd9bba0-7aab-4e30-b3ae-2221006a4a05/intel-oneapi-base-toolkit-2025.1.1.34_offline.exe
WINDOWS_DPCPP_MKL: intel.oneapi.win.cpp-dpcpp-common:intel.oneapi.win.mkl.devel:intel.oneapi.win.dnnl:intel.oneapi.win.tbb.devel
ONEAPI_ROOT: "C:/Program Files (x86)/Intel/oneAPI"
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: windows-latest-cmake-sycl
variant: ccache
evict-old-files: 1d
- name: Install
run: |
scripts/install-oneapi.bat $WINDOWS_BASEKIT_URL $WINDOWS_DPCPP_MKL
- name: Build
id: cmake_build
shell: cmd
run: |
call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force
cmake -G "Ninja" -B build ^
-DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx ^
-DCMAKE_BUILD_TYPE=Release ^
-DGGML_BACKEND_DL=ON -DBUILD_SHARED_LIBS=ON ^
-DGGML_CPU=OFF -DGGML_SYCL=ON ^
-DLLAMA_CURL=OFF
cmake --build build --target ggml-sycl -j
- name: Build the release package
id: pack_artifacts
run: |
echo "cp oneAPI running time dll files in ${{ env.ONEAPI_ROOT }} to ./build/bin"
cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_sycl_blas.5.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_core.2.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_tbb_thread.2.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_level_zero.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_opencl.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_loader.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_win_proxy_loader.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/sycl8.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/svml_dispmd.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libmmd.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libiomp5md.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/dnnl/latest/bin/dnnl.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/tbb/latest/bin/tbb12.dll" ./build/bin
echo "cp oneAPI running time dll files to ./build/bin done"
7z a llama-bin-win-sycl-x64.zip ./build/bin/*
- name: Upload the release package
uses: actions/upload-artifact@v4
with:
path: llama-bin-win-sycl-x64.zip
name: llama-bin-win-sycl-x64.zip
windows-hip:
runs-on: windows-2022
strategy:
matrix:
include:
- name: "radeon"
gpu_targets: "gfx1100;gfx1101;gfx1102;gfx1030;gfx1031;gfx1032"
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
- name: Clone rocWMMA repository
id: clone_rocwmma
run: |
git clone https://github.com/rocm/rocwmma --branch rocm-6.2.4 --depth 1
- name: ccache
uses: hendrikmuhs/ccache-action@v1.2.16
with:
key: windows-latest-cmake-hip-${{ matrix.name }}-x64
evict-old-files: 1d
- name: Install
id: depends
run: |
$ErrorActionPreference = "Stop"
write-host "Downloading AMD HIP SDK Installer"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
write-host "Installing AMD HIP SDK"
Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
write-host "Completed AMD HIP SDK installation"
- name: Verify ROCm
id: verify
run: |
& 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
- name: Build
id: cmake_build
run: |
$env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
$env:CMAKE_PREFIX_PATH="${env:HIP_PATH}"
cmake -G "Unix Makefiles" -B build -S . `
-DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
-DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
-DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/rocwmma/library/include/ -Wno-ignored-attributes -Wno-nested-anon-types" `
-DCMAKE_BUILD_TYPE=Release `
-DGGML_BACKEND_DL=ON `
-DGGML_NATIVE=OFF `
-DGGML_CPU=OFF `
-DAMDGPU_TARGETS="${{ matrix.gpu_targets }}" `
-DGGML_HIP_ROCWMMA_FATTN=ON `
-DGGML_HIP=ON `
-DLLAMA_CURL=OFF
cmake --build build --target ggml-hip -j ${env:NUMBER_OF_PROCESSORS}
md "build\bin\rocblas\library\"
cp "${env:HIP_PATH}\bin\hipblas.dll" "build\bin\"
cp "${env:HIP_PATH}\bin\rocblas.dll" "build\bin\"
cp "${env:HIP_PATH}\bin\rocblas\library\*" "build\bin\rocblas\library\"
- name: Pack artifacts
id: pack_artifacts
run: |
7z a llama-bin-win-hip-${{ matrix.name }}-x64.zip .\build\bin\*
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: llama-bin-win-hip-${{ matrix.name }}-x64.zip
name: llama-bin-win-hip-${{ matrix.name }}-x64.zip
ios-xcode-build:
runs-on: macos-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Build
id: cmake_build
run: |
sysctl -a
cmake -B build -G Xcode \
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DLLAMA_CURL=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF \
-DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_TESTS=OFF \
-DLLAMA_BUILD_SERVER=OFF \
-DCMAKE_SYSTEM_NAME=iOS \
-DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 \
-DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO
- name: xcodebuild for swift package
id: xcodebuild
run: |
./build-xcframework.sh
- name: Build Xcode project
run: xcodebuild -project examples/llama.swiftui/llama.swiftui.xcodeproj -scheme llama.swiftui -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' FRAMEWORK_FOLDER_PATH=./build-ios build
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
zip --symlinks -r llama-${{ steps.tag.outputs.name }}-xcframework.zip build-apple/llama.xcframework
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: llama-${{ steps.tag.outputs.name }}-xcframework.zip
name: llama-${{ steps.tag.outputs.name }}-xcframework
release:
if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
# Fine-grant permission
# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
permissions:
contents: write # for creating release
runs-on: ubuntu-latest
needs:
- windows
- windows-cpu
- windows-cuda
- windows-sycl
- windows-hip
- ubuntu-22-cpu
- ubuntu-22-vulkan
- macOS-arm64
- macOS-x64
- ios-xcode-build
steps:
- name: Clone
id: checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Download artifacts
id: download-artifact
uses: actions/download-artifact@v4
with:
path: ./artifact
merge-multiple: true
- name: Move artifacts
id: move_artifacts
run: |
mkdir -p release
echo "Adding CPU backend files to existing zips..."
for arch in x64 arm64; do
cpu_zip="artifact/llama-bin-win-cpu-${arch}.zip"
temp_dir=$(mktemp -d)
echo "Extracting CPU backend for $arch..."
unzip "$cpu_zip" -d "$temp_dir"
echo "Adding CPU files to $arch zips..."
for target_zip in artifact/llama-bin-win-*-${arch}.zip; do
if [[ "$target_zip" == "$cpu_zip" ]]; then
continue
fi
echo "Adding CPU backend to $(basename "$target_zip")"
realpath_target_zip=$(realpath "$target_zip")
(cd "$temp_dir" && zip -r "$realpath_target_zip" .)
done
rm -rf "$temp_dir"
done
echo "Renaming and moving zips to release..."
for zip_file in artifact/llama-bin-win-*.zip; do
base_name=$(basename "$zip_file" .zip)
zip_name="llama-${{ steps.tag.outputs.name }}-${base_name#llama-}.zip"
echo "Moving $zip_file to release/$zip_name"
mv "$zip_file" "release/$zip_name"
done
echo "Moving other artifacts..."
mv -v artifact/*.zip release
- name: Create release
id: create_release
uses: ggml-org/action-create-release@v1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
tag_name: ${{ steps.tag.outputs.name }}
- name: Upload release
id: upload_release
uses: actions/github-script@v3
with:
github-token: ${{secrets.GITHUB_TOKEN}}
script: |
const path = require('path');
const fs = require('fs');
const release_id = '${{ steps.create_release.outputs.id }}';
for (let file of await fs.readdirSync('./release')) {
if (path.extname(file) === '.zip') {
console.log('uploadReleaseAsset', file);
await github.repos.uploadReleaseAsset({
owner: context.repo.owner,
repo: context.repo.repo,
release_id: release_id,
name: file,
data: await fs.readFileSync(`./release/${file}`)
});
}
}

View File

@ -15,10 +15,10 @@ on:
push: push:
branches: branches:
- master - master
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/**.*'] paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'tools/server/**.*']
pull_request: pull_request:
types: [opened, synchronize, reopened] types: [opened, synchronize, reopened]
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/**.*'] paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'tools/server/**.*']
env: env:
LLAMA_LOG_COLORS: 1 LLAMA_LOG_COLORS: 1
@ -74,22 +74,51 @@ jobs:
- name: Tests dependencies - name: Tests dependencies
id: test_dependencies id: test_dependencies
run: | run: |
pip install -r examples/server/tests/requirements.txt pip install -r tools/server/tests/requirements.txt
- name: Verify server deps # Setup nodejs (to be used for verifying bundled index.html)
id: verify_server_deps - uses: actions/setup-node@v4
with:
node-version: '22.11.0'
- name: WebUI - Install dependencies
id: webui_lint
run: |
cd tools/server/webui
npm ci
- name: WebUI - Check code format
id: webui_format
run: | run: |
git config --global --add safe.directory $(realpath .) git config --global --add safe.directory $(realpath .)
cd examples/server cd tools/server/webui
git ls-files --others --modified
git status git status
./deps.sh
npm run format
git status git status
not_ignored_files="$(git ls-files --others --modified)" modified_files="$(git status -s)"
echo "Modified files: ${not_ignored_files}" echo "Modified files: ${modified_files}"
if [ -n "${not_ignored_files}" ]; then if [ -n "${modified_files}" ]; then
echo "Repository is dirty or server deps are not built as expected" echo "Files do not follow coding style. To fix: npm run format"
echo "${not_ignored_files}" echo "${modified_files}"
exit 1
fi
- name: Verify bundled index.html
id: verify_server_index_html
run: |
git config --global --add safe.directory $(realpath .)
cd tools/server/webui
git status
npm run build
git status
modified_files="$(git status -s)"
echo "Modified files: ${modified_files}"
if [ -n "${modified_files}" ]; then
echo "Repository is dirty or server/webui is not built as expected"
echo "Hint: You may need to follow Web UI build guide in server/README.md"
echo "${modified_files}"
exit 1 exit 1
fi fi
@ -100,40 +129,58 @@ jobs:
cmake -B build \ cmake -B build \
-DGGML_NATIVE=OFF \ -DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \ -DLLAMA_BUILD_SERVER=ON \
-DLLAMA_CURL=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \ -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \ -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
-DGGML_OPENMP=OFF ; -DGGML_OPENMP=OFF ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Build - name: Build (sanitizers)
id: cmake_build id: cmake_build_sanitizers
if: ${{ matrix.sanitizer != 'THREAD' }} if: ${{ matrix.sanitizer != '' && matrix.sanitizer != 'THREAD' }}
run: | run: |
cmake -B build \ cmake -B build \
-DGGML_NATIVE=OFF \ -DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \ -DLLAMA_BUILD_SERVER=ON \
-DLLAMA_CURL=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \ -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ; -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Build (sanitizers)
id: cmake_build
if: ${{ matrix.sanitizer == '' }}
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Tests - name: Tests
id: server_integration_tests id: server_integration_tests
if: ${{ matrix.sanitizer == '' }}
env:
GITHUB_ACTIONS: "true"
run: | run: |
cd examples/server/tests cd tools/server/tests
PORT=8888 ./tests.sh ./tests.sh
- name: Tests (sanitizers)
id: server_integration_tests_sanitizers
if: ${{ matrix.sanitizer != '' }}
run: |
cd tools/server/tests
LLAMA_SANITIZE=1 ./tests.sh
- name: Slow tests - name: Slow tests
id: server_integration_tests_slow id: server_integration_tests_slow
if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }} if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }}
run: | run: |
cd examples/server/tests cd tools/server/tests
PORT=8888 ./tests.sh --stop --no-skipped --no-capture --tags slow SLOW_TESTS=1 ./tests.sh
server-windows: server-windows:
runs-on: windows-2019 runs-on: windows-2022
steps: steps:
- name: Clone - name: Clone
@ -145,17 +192,14 @@ jobs:
- name: libCURL - name: libCURL
id: get_libcurl id: get_libcurl
env: uses: ./.github/actions/windows-setup-curl
CURL_VERSION: 8.6.0_6
run: |
curl.exe -o $env:RUNNER_TEMP/curl.zip -L "https://curl.se/windows/dl-${env:CURL_VERSION}/curl-${env:CURL_VERSION}-win64-mingw.zip"
mkdir $env:RUNNER_TEMP/libcurl
tar.exe -xvf $env:RUNNER_TEMP/curl.zip --strip-components=1 -C $env:RUNNER_TEMP/libcurl
- name: Build - name: Build
id: cmake_build id: cmake_build
env:
CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
run: | run: |
cmake -B build -DLLAMA_CURL=ON -DCURL_LIBRARY="$env:RUNNER_TEMP/libcurl/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:RUNNER_TEMP/libcurl/include" cmake -B build -DCURL_LIBRARY="$env:CURL_PATH/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:CURL_PATH/include"
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS} --target llama-server cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS} --target llama-server
- name: Python setup - name: Python setup
@ -167,24 +211,27 @@ jobs:
- name: Tests dependencies - name: Tests dependencies
id: test_dependencies id: test_dependencies
run: | run: |
pip install -r examples/server/tests/requirements.txt pip install -r tools/server/tests/requirements.txt
- name: Copy Libcurl - name: Copy Libcurl
id: prepare_libcurl id: prepare_libcurl
env:
CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
run: | run: |
cp $env:RUNNER_TEMP/libcurl/bin/libcurl-x64.dll ./build/bin/Release/libcurl-x64.dll cp $env:CURL_PATH/bin/libcurl-x64.dll ./build/bin/Release/libcurl-x64.dll
- name: Tests - name: Tests
id: server_integration_tests id: server_integration_tests
if: ${{ !matrix.disabled_on_pr || !github.event.pull_request }} if: ${{ !matrix.disabled_on_pr || !github.event.pull_request }}
run: | run: |
cd examples/server/tests cd tools/server/tests
$env:PYTHONIOENCODING = ":replace" $env:PYTHONIOENCODING = ":replace"
behave.exe --summary --stop --no-capture --exclude 'issues|wrong_usages|passkey' --tags llama.cpp pytest -v -x -m "not slow"
- name: Slow tests - name: Slow tests
id: server_integration_tests_slow id: server_integration_tests_slow
if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }} if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }}
run: | run: |
cd examples/server/tests cd tools/server/tests
behave.exe --stop --no-skipped --no-capture --tags slow $env:SLOW_TESTS = "1"
pytest -v -x

42
.github/workflows/winget.yml vendored Normal file
View File

@ -0,0 +1,42 @@
name: Update Winget Package
on:
workflow_dispatch: # allows manual triggering
schedule:
- cron: '28 5 * * *' # Update every day at 5:28 UTC
jobs:
update:
name: Update Winget Package
runs-on: ubuntu-latest
steps:
- name: Install cargo binstall
uses: cargo-bins/cargo-binstall@268643a6b5ea099f5718ee5cd3ff7dc89a5eb49b
- name: Install komac
run: |
cargo binstall komac@2.11.2 -y
- name: Find latest release
id: find_latest_release
uses: actions/github-script@v6
with:
script: |
const { data: releases } = await github.rest.repos.listReleases({
owner: context.repo.owner,
repo: context.repo.repo,
});
console.log("Latest release:", releases[0].tag_name);
return releases[0].tag_name;
- name: Update manifest
env:
VERSION: ${{ steps.find_latest_release.outputs.result }}
run: |
echo "Updating manifest..."
komac update --version ${{ env.VERSION }} \
--urls "https://github.com/ggml-org/llama.cpp/releases/download/${{ env.VERSION }}/llama-${{ env.VERSION }}-bin-win-vulkan-x64.zip" \
--token ${{ secrets.WINGET_GITHUB_TOKEN }} \
--submit \
ggml.llamacpp

16
.gitignore vendored
View File

@ -18,6 +18,7 @@
*.metallib *.metallib
*.o *.o
*.so *.so
*.swp
*.tmp *.tmp
# IDE / OS # IDE / OS
@ -44,6 +45,8 @@ lcov-report/
tags tags
.build/ .build/
build* build*
release
debug
!build-info.cmake !build-info.cmake
!build-info.cpp.in !build-info.cpp.in
!build-info.sh !build-info.sh
@ -93,10 +96,11 @@ perf-*.txt
# Examples # Examples
examples/jeopardy/results.txt examples/jeopardy/results.txt
examples/server/*.css.hpp tools/server/*.css.hpp
examples/server/*.html.hpp tools/server/*.html.hpp
examples/server/*.js.hpp tools/server/*.js.hpp
examples/server/*.mjs.hpp tools/server/*.mjs.hpp
tools/server/*.gz.hpp
!build_64.sh !build_64.sh
!examples/*.bat !examples/*.bat
!examples/*/*.kts !examples/*/*.kts
@ -104,6 +108,10 @@ examples/server/*.mjs.hpp
!examples/sycl/*.bat !examples/sycl/*.bat
!examples/sycl/*.sh !examples/sycl/*.sh
# Server Web UI temporary files
node_modules
tools/server/webui/dist
# Python # Python
/.venv /.venv

326
AUTHORS

File diff suppressed because it is too large Load Diff

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@ -16,6 +16,7 @@ endif()
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/") list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/")
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin) set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
if (CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR) if (CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
set(LLAMA_STANDALONE ON) set(LLAMA_STANDALONE ON)
@ -28,6 +29,8 @@ else()
set(LLAMA_STANDALONE OFF) set(LLAMA_STANDALONE OFF)
endif() endif()
option(LLAMA_USE_SYSTEM_GGML "Use system libggml" OFF)
if (EMSCRIPTEN) if (EMSCRIPTEN)
set(BUILD_SHARED_LIBS_DEFAULT OFF) set(BUILD_SHARED_LIBS_DEFAULT OFF)
@ -46,11 +49,11 @@ if (WIN32)
add_compile_definitions(_CRT_SECURE_NO_WARNINGS) add_compile_definitions(_CRT_SECURE_NO_WARNINGS)
endif() endif()
if ("${CMAKE_CXX_COMPILER_ID}" STREQUAL "MSVC") if (MSVC)
add_compile_options("$<$<COMPILE_LANGUAGE:C>:/source-charset:utf-8>") add_compile_options("$<$<COMPILE_LANGUAGE:C>:/utf-8>")
add_compile_options("$<$<COMPILE_LANGUAGE:CXX>:/source-charset:utf-8>") add_compile_options("$<$<COMPILE_LANGUAGE:CXX>:/utf-8>")
add_compile_options("$<$<COMPILE_LANGUAGE:C>:/execution-charset:utf-8>") add_compile_options("$<$<COMPILE_LANGUAGE:C>:/bigobj>")
add_compile_options("$<$<COMPILE_LANGUAGE:CXX>:/execution-charset:utf-8>") add_compile_options("$<$<COMPILE_LANGUAGE:CXX>:/bigobj>")
endif() endif()
# #
@ -74,31 +77,35 @@ option(LLAMA_BUILD_COMMON "llama: build common utils library" ${LLAMA_STANDALONE
# extra artifacts # extra artifacts
option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE}) 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_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_SERVER "llama: build server example" ${LLAMA_STANDALONE}) option(LLAMA_BUILD_SERVER "llama: build server example" ${LLAMA_STANDALONE})
# 3rd party libs # 3rd party libs
option(LLAMA_CURL "llama: use libcurl to download model from an URL" OFF) option(LLAMA_CURL "llama: use libcurl to download model from an URL" ON)
option(LLAMA_LLGUIDANCE "llama-common: include LLGuidance library for structured output in common utils" OFF)
# Required for relocatable CMake package # Required for relocatable CMake package
include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake) include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)
include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/common.cmake)
if (NOT DEFINED LLAMA_BUILD_NUMBER)
set(LLAMA_BUILD_NUMBER ${BUILD_NUMBER})
endif()
if (NOT DEFINED LLAMA_BUILD_COMMIT)
set(LLAMA_BUILD_COMMIT ${BUILD_COMMIT})
endif()
set(LLAMA_INSTALL_VERSION 0.0.${LLAMA_BUILD_NUMBER})
# override ggml options # override ggml options
set(GGML_SANITIZE_THREAD ${LLAMA_SANITIZE_THREAD}) set(GGML_ALL_WARNINGS ${LLAMA_ALL_WARNINGS})
set(GGML_SANITIZE_ADDRESS ${LLAMA_SANITIZE_ADDRESS}) set(GGML_FATAL_WARNINGS ${LLAMA_FATAL_WARNINGS})
set(GGML_SANITIZE_UNDEFINED ${LLAMA_SANITIZE_UNDEFINED})
set(GGML_ALL_WARNINGS ${LLAMA_ALL_WARNINGS})
set(GGML_FATAL_WARNINGS ${LLAMA_FATAL_WARNINGS})
# change the default for these ggml options # change the default for these ggml options
if (NOT DEFINED GGML_LLAMAFILE) if (NOT DEFINED GGML_LLAMAFILE)
set(GGML_LLAMAFILE_DEFAULT ON) set(GGML_LLAMAFILE_DEFAULT ON)
endif() endif()
if (NOT DEFINED GGML_AMX)
set(GGML_AMX ON)
endif()
if (NOT DEFINED GGML_CUDA_GRAPHS) if (NOT DEFINED GGML_CUDA_GRAPHS)
set(GGML_CUDA_GRAPHS_DEFAULT ON) set(GGML_CUDA_GRAPHS_DEFAULT ON)
endif() endif()
@ -122,16 +129,84 @@ llama_option_depr(WARNING LLAMA_SYCL GGML_SYCL)
llama_option_depr(WARNING LLAMA_SYCL_F16 GGML_SYCL_F16) llama_option_depr(WARNING LLAMA_SYCL_F16 GGML_SYCL_F16)
llama_option_depr(WARNING LLAMA_CANN GGML_CANN) llama_option_depr(WARNING LLAMA_CANN GGML_CANN)
if (NOT MSVC)
if (LLAMA_SANITIZE_THREAD)
message(STATUS "Using -fsanitize=thread")
add_compile_options(-fsanitize=thread)
link_libraries (-fsanitize=thread)
endif()
if (LLAMA_SANITIZE_ADDRESS)
message(STATUS "Using -fsanitize=address")
add_compile_options(-fsanitize=address -fno-omit-frame-pointer)
link_libraries (-fsanitize=address)
endif()
if (LLAMA_SANITIZE_UNDEFINED)
message(STATUS "Using -fsanitize=undefined")
add_compile_options(-fsanitize=undefined)
link_libraries (-fsanitize=undefined)
endif()
endif()
#
# 3rd-party
#
if (LLAMA_USE_SYSTEM_GGML)
message(STATUS "Using system-provided libggml, skipping ggml build")
find_package(ggml REQUIRED)
add_library(ggml ALIAS ggml::ggml)
endif()
if (NOT TARGET ggml AND NOT LLAMA_USE_SYSTEM_GGML)
set(GGML_BUILD_NUMBER ${LLAMA_BUILD_NUMBER})
set(GGML_BUILD_COMMIT ${LLAMA_BUILD_COMMIT})
add_subdirectory(ggml)
# ... otherwise assume ggml is added by a parent CMakeLists.txt
endif()
if (MINGW)
# Target Windows 8 for PrefetchVirtualMemory
add_compile_definitions(_WIN32_WINNT=${GGML_WIN_VER})
endif()
# #
# build the library # build the library
# #
if (NOT TARGET ggml)
add_subdirectory(ggml)
# ... otherwise assume ggml is added by a parent CMakeLists.txt
endif()
add_subdirectory(src) add_subdirectory(src)
#
# utils, programs, examples and tests
#
if (NOT LLAMA_BUILD_COMMON)
message(STATUS "LLAMA_BUILD_COMMON is OFF, disabling LLAMA_CURL")
set(LLAMA_CURL OFF)
endif()
if (LLAMA_BUILD_COMMON)
add_subdirectory(common)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TESTS AND NOT CMAKE_JS_VERSION)
include(CTest)
add_subdirectory(tests)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_EXAMPLES)
add_subdirectory(examples)
add_subdirectory(pocs)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TOOLS)
add_subdirectory(tools)
endif()
# #
# install # install
# #
@ -139,32 +214,18 @@ add_subdirectory(src)
include(GNUInstallDirs) include(GNUInstallDirs)
include(CMakePackageConfigHelpers) include(CMakePackageConfigHelpers)
set(LLAMA_BUILD_NUMBER ${BUILD_NUMBER})
set(LLAMA_BUILD_COMMIT ${BUILD_COMMIT})
set(LLAMA_INSTALL_VERSION 0.0.${BUILD_NUMBER})
set(LLAMA_INCLUDE_INSTALL_DIR ${CMAKE_INSTALL_INCLUDEDIR} CACHE PATH "Location of header files") set(LLAMA_INCLUDE_INSTALL_DIR ${CMAKE_INSTALL_INCLUDEDIR} CACHE PATH "Location of header files")
set(LLAMA_LIB_INSTALL_DIR ${CMAKE_INSTALL_LIBDIR} CACHE PATH "Location of library files") set(LLAMA_LIB_INSTALL_DIR ${CMAKE_INSTALL_LIBDIR} CACHE PATH "Location of library files")
set(LLAMA_BIN_INSTALL_DIR ${CMAKE_INSTALL_BINDIR} CACHE PATH "Location of binary files") set(LLAMA_BIN_INSTALL_DIR ${CMAKE_INSTALL_BINDIR} CACHE PATH "Location of binary files")
# At the moment some compile definitions are placed within the ggml/src set(LLAMA_PUBLIC_HEADERS
# directory but not exported on the `ggml` target. This could be improved by ${CMAKE_CURRENT_SOURCE_DIR}/include/llama.h
# determining _precisely_ which defines are necessary for the llama-config ${CMAKE_CURRENT_SOURCE_DIR}/include/llama-cpp.h)
# package.
# set_target_properties(llama
set(GGML_TRANSIENT_DEFINES) PROPERTIES
get_target_property(GGML_DIRECTORY ggml SOURCE_DIR) PUBLIC_HEADER "${LLAMA_PUBLIC_HEADERS}")
get_directory_property(GGML_DIR_DEFINES DIRECTORY ${GGML_DIRECTORY} COMPILE_DEFINITIONS)
if (GGML_DIR_DEFINES)
list(APPEND GGML_TRANSIENT_DEFINES ${GGML_DIR_DEFINES})
endif()
get_target_property(GGML_TARGET_DEFINES ggml COMPILE_DEFINITIONS)
if (GGML_TARGET_DEFINES)
list(APPEND GGML_TRANSIENT_DEFINES ${GGML_TARGET_DEFINES})
endif()
get_target_property(GGML_LINK_LIBRARIES ggml LINK_LIBRARIES)
set_target_properties(llama PROPERTIES PUBLIC_HEADER ${CMAKE_CURRENT_SOURCE_DIR}/include/llama.h)
install(TARGETS llama LIBRARY PUBLIC_HEADER) install(TARGETS llama LIBRARY PUBLIC_HEADER)
configure_package_config_file( configure_package_config_file(
@ -201,22 +262,4 @@ configure_file(cmake/llama.pc.in
@ONLY) @ONLY)
install(FILES "${CMAKE_CURRENT_BINARY_DIR}/llama.pc" install(FILES "${CMAKE_CURRENT_BINARY_DIR}/llama.pc"
DESTINATION lib/pkgconfig) DESTINATION ${CMAKE_INSTALL_LIBDIR}/pkgconfig)
#
# utils, programs, examples and tests
#
if (LLAMA_BUILD_COMMON)
add_subdirectory(common)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TESTS AND NOT CMAKE_JS_VERSION)
include(CTest)
add_subdirectory(tests)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_EXAMPLES)
add_subdirectory(examples)
add_subdirectory(pocs)
endif()

View File

@ -32,11 +32,9 @@
{ "name": "vulkan", "hidden": true, "cacheVariables": { "GGML_VULKAN": "ON" } }, { "name": "vulkan", "hidden": true, "cacheVariables": { "GGML_VULKAN": "ON" } },
{ {
"name": "arm64-windows-msvc", "hidden": true, "name": "x64-windows-llvm", "hidden": true,
"architecture": { "value": "arm64", "strategy": "external" },
"toolset": { "value": "host=x64", "strategy": "external" },
"cacheVariables": { "cacheVariables": {
"CMAKE_TOOLCHAIN_FILE": "${sourceDir}/cmake/arm64-windows-msvc.cmake" "CMAKE_TOOLCHAIN_FILE": "${sourceDir}/cmake/x64-windows-llvm.cmake"
} }
}, },
@ -66,9 +64,10 @@
{ "name": "arm64-apple-clang-release", "inherits": [ "base", "arm64-apple-clang", "reldbg" ] }, { "name": "arm64-apple-clang-release", "inherits": [ "base", "arm64-apple-clang", "reldbg" ] },
{ "name": "arm64-apple-clang+static-release", "inherits": [ "base", "arm64-apple-clang", "reldbg", "static" ] }, { "name": "arm64-apple-clang+static-release", "inherits": [ "base", "arm64-apple-clang", "reldbg", "static" ] },
{ "name": "arm64-windows-msvc-debug", "inherits": [ "base", "arm64-windows-msvc", "debug" ] }, { "name": "x64-windows-llvm-debug", "inherits": [ "base", "x64-windows-llvm", "debug" ] },
{ "name": "arm64-windows-msvc-release", "inherits": [ "base", "arm64-windows-msvc", "reldbg" ] }, { "name": "x64-windows-llvm-release", "inherits": [ "base", "x64-windows-llvm", "release" ] },
{ "name": "arm64-windows-msvc+static-release", "inherits": [ "base", "arm64-windows-msvc", "reldbg", "static" ] }, { "name": "x64-windows-llvm-reldbg", "inherits": [ "base", "x64-windows-llvm", "reldbg" ] },
{ "name": "x64-windows-llvm+static-release", "inherits": [ "base", "x64-windows-llvm", "reldbg", "static" ] },
{ "name": "x64-windows-msvc-debug", "inherits": [ "base", "debug" ] }, { "name": "x64-windows-msvc-debug", "inherits": [ "base", "debug" ] },
{ "name": "x64-windows-msvc-release", "inherits": [ "base", "reldbg" ] }, { "name": "x64-windows-msvc-release", "inherits": [ "base", "reldbg" ] },

11
CODEOWNERS Normal file
View File

@ -0,0 +1,11 @@
# collaborators can optionally add themselves here to indicate their availability for reviewing related PRs
/ci/ @ggerganov
/.devops/*.Dockerfile @ngxson
/tools/server/ @ngxson
/ggml/src/ggml-cuda/fattn* @JohannesGaessler
/ggml/src/ggml-cuda/mmq.* @JohannesGaessler
/ggml/src/ggml-cuda/mmv.* @JohannesGaessler
/ggml/src/ggml-cuda/mmvq.* @JohannesGaessler
/ggml/src/ggml-opt.cpp @JohannesGaessler
/ggml/src/gguf.cpp @JohannesGaessler

View File

@ -1,9 +1,12 @@
# Pull requests (for contributors) # Pull requests (for contributors)
- llama.cpp uses the ggml tensor library for model evaluation. If you are unfamiliar with ggml, consider taking a look at the [examples in the ggml repository](https://github.com/ggml-org/ggml/tree/master/examples/). [simple](https://github.com/ggml-org/ggml/tree/master/examples/simple) shows the bare minimum for using ggml. [gpt-2](https://github.com/ggml-org/ggml/tree/master/examples/gpt-2) has minimal implementations for language model inference using GPT-2. [mnist](https://github.com/ggml-org/ggml/tree/master/examples/mnist) demonstrates how to train and evaluate a simple image classifier
- Test your changes: - Test your changes:
- Using the commands in the [`tests`](tests) folder. For instance, running the `./tests/test-backend-ops` command tests different backend implementations of the `ggml` library - Execute [the full CI locally on your machine](ci/README.md) before publishing
- Execute [the full CI locally on your machine](ci/README.md) before publishing - Verify that the perplexity and the performance are not affected negatively by your changes (use `llama-perplexity` and `llama-bench`)
- Optionally rate the complexity of your PR (i.e. `Review Complexity : Low`, `Review Complexity : Medium`, `Review Complexity : High`). This makes it easier for maintainers to triage the PRs - If you modified the `ggml` source, run the `test-backend-ops` tool to check whether different backend implementations of the `ggml` operators produce consistent results (this requires access to at least two different `ggml` backends)
- If you modified a `ggml` operator or added a new one, add the corresponding test cases to `test-backend-ops`
- Create separate PRs for each feature or fix. Avoid combining unrelated changes in a single PR
- Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly - Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly
- If your PR becomes stale, don't hesitate to ping the maintainers in the comments - If your PR becomes stale, don't hesitate to ping the maintainers in the comments
@ -11,23 +14,114 @@
- Squash-merge PRs - Squash-merge PRs
- Use the following format for the squashed commit title: `<module> : <commit title> (#<issue_number>)`. For example: `utils : fix typo in utils.py (#1234)` - Use the following format for the squashed commit title: `<module> : <commit title> (#<issue_number>)`. For example: `utils : fix typo in utils.py (#1234)`
- Optionally pick a `<module>` from here: https://github.com/ggerganov/llama.cpp/wiki/Modules - Optionally pick a `<module>` from here: https://github.com/ggml-org/llama.cpp/wiki/Modules
- Consider adding yourself to [CODEOWNERS](CODEOWNERS)
# Coding guidelines # Coding guidelines
- Avoid adding third-party dependencies, extra files, extra headers, etc. - Avoid adding third-party dependencies, extra files, extra headers, etc.
- Always consider cross-compatibility with other operating systems and architectures - Always consider cross-compatibility with other operating systems and architectures
- Avoid fancy-looking modern STL constructs, use basic `for` loops, avoid templates, keep it simple - Avoid fancy-looking modern STL constructs, use basic `for` loops, avoid templates, keep it simple
- There are no strict rules for the code style, but try to follow the patterns in the code (indentation, spaces, etc.). Vertical alignment makes things more readable and easier to batch edit - Vertical alignment makes things more readable and easier to batch edit
- Clean-up any trailing whitespaces, use 4 spaces for indentation, brackets on the same line, `void * ptr`, `int & a` - Clean-up any trailing whitespaces, use 4 spaces for indentation, brackets on the same line, `void * ptr`, `int & a`
- Naming usually optimizes for common prefix (see https://github.com/ggerganov/ggml/pull/302#discussion_r1243240963) - Use sized integer types such as `int32_t` in the public API, e.g. `size_t` may also be appropriate for allocation sizes or byte offsets
- Declare structs with `struct foo {}` instead of `typedef struct foo {} foo`
- In C++ code omit optional `struct` and `enum` keyword whenever they are not necessary
```cpp
// OK
llama_context * ctx;
const llama_rope_type rope_type;
// not OK
struct llama_context * ctx;
const enum llama_rope_type rope_type;
```
_(NOTE: this guideline is yet to be applied to the `llama.cpp` codebase. New code should follow this guideline.)_
- Try to follow the existing patterns in the code (indentation, spaces, etc.). In case of doubt use `clang-format` (from clang-tools v15+) to format the added code
- For anything not covered in the current guidelines, refer to the [C++ Core Guidelines](https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines)
- Tensors store data in row-major order. We refer to dimension 0 as columns, 1 as rows, 2 as matrices - Tensors store data in row-major order. We refer to dimension 0 as columns, 1 as rows, 2 as matrices
- Matrix multiplication is unconventional: [`C = ggml_mul_mat(ctx, A, B)`](https://github.com/ggerganov/llama.cpp/blob/880e352277fc017df4d5794f0c21c44e1eae2b84/ggml.h#L1058-L1064) means $C^T = A B^T \Leftrightarrow C = B A^T.$ - Matrix multiplication is unconventional: [`C = ggml_mul_mat(ctx, A, B)`](https://github.com/ggml-org/llama.cpp/blob/880e352277fc017df4d5794f0c21c44e1eae2b84/ggml.h#L1058-L1064) means $C^T = A B^T \Leftrightarrow C = B A^T.$
![matmul](media/matmul.png) ![matmul](media/matmul.png)
# Naming guidelines
- Use `snake_case` for function, variable and type names
- Naming usually optimizes for longest common prefix (see https://github.com/ggml-org/ggml/pull/302#discussion_r1243240963)
```cpp
// not OK
int small_number;
int big_number;
// OK
int number_small;
int number_big;
```
- Enum values are always in upper case and prefixed with the enum name
```cpp
enum llama_vocab_type {
LLAMA_VOCAB_TYPE_NONE = 0,
LLAMA_VOCAB_TYPE_SPM = 1,
LLAMA_VOCAB_TYPE_BPE = 2,
LLAMA_VOCAB_TYPE_WPM = 3,
LLAMA_VOCAB_TYPE_UGM = 4,
LLAMA_VOCAB_TYPE_RWKV = 5,
};
```
- The general naming pattern is `<class>_<method>`, with `<method>` being `<action>_<noun>`
```cpp
llama_model_init(); // class: "llama_model", method: "init"
llama_sampler_chain_remove(); // class: "llama_sampler_chain", method: "remove"
llama_sampler_get_seed(); // class: "llama_sampler", method: "get_seed"
llama_set_embeddings(); // class: "llama_context", method: "set_embeddings"
llama_n_threads(); // class: "llama_context", method: "n_threads"
llama_adapter_lora_free(); // class: "llama_adapter_lora", method: "free"
```
- The `get` `<action>` can be omitted
- The `<noun>` can be omitted if not necessary
- The `_context` suffix of the `<class>` is optional. Use it to disambiguate symbols when needed
- Use `init`/`free` for constructor/destructor `<action>`
- Use the `_t` suffix when a type is supposed to be opaque to the user - it's not relevant to them if it is a struct or anything else
```cpp
typedef struct llama_context * llama_context_t;
enum llama_pooling_type llama_pooling_type(const llama_context_t ctx);
```
_(NOTE: this guideline is yet to be applied to the `llama.cpp` codebase. New code should follow this guideline)_
- C/C++ filenames are all lowercase with dashes. Headers use the `.h` extension. Source files use the `.c` or `.cpp` extension
- Python filenames are all lowercase with underscores
- _(TODO: abbreviations usage)_
# Preprocessor directives
- _(TODO: add guidelines with examples and apply them to the codebase)_
```cpp
#ifdef FOO
#endif // FOO
```
# Documentation
- Documentation is a community effort
- When you need to look into the source code to figure out how to use an API consider adding a short summary to the header file for future reference
- When you notice incorrect or outdated documentation, please update it
# Resources # Resources
The Github issues, PRs and discussions contain a lot of information that can be useful to get familiar with the codebase. For convenience, some of the more important information is referenced from Github projects: The Github issues, PRs and discussions contain a lot of information that can be useful to get familiar with the codebase. For convenience, some of the more important information is referenced from Github projects:
https://github.com/ggerganov/llama.cpp/projects https://github.com/ggml-org/llama.cpp/projects

192
Makefile
View File

@ -1,3 +1,7 @@
ifndef LLAMA_MAKEFILE
$(error The Makefile build is deprecated. Use the CMake build instead. For more details, see https://github.com/ggml-org/llama.cpp/blob/master/docs/build.md)
endif
# Define the default target now so that it is always the first target # Define the default target now so that it is always the first target
BUILD_TARGETS = \ BUILD_TARGETS = \
libllava.a \ libllava.a \
@ -18,6 +22,7 @@ BUILD_TARGETS = \
llama-infill \ llama-infill \
llama-llava-cli \ llama-llava-cli \
llama-minicpmv-cli\ llama-minicpmv-cli\
llama-qwen2vl-cli\
llama-lookahead \ llama-lookahead \
llama-lookup \ llama-lookup \
llama-lookup-create \ llama-lookup-create \
@ -34,6 +39,7 @@ BUILD_TARGETS = \
llama-server \ llama-server \
llama-simple \ llama-simple \
llama-simple-chat \ llama-simple-chat \
llama-run \
llama-speculative \ llama-speculative \
llama-tokenize \ llama-tokenize \
llama-vdot \ llama-vdot \
@ -46,6 +52,7 @@ TEST_TARGETS = \
tests/test-arg-parser \ tests/test-arg-parser \
tests/test-autorelease \ tests/test-autorelease \
tests/test-backend-ops \ tests/test-backend-ops \
tests/test-chat \
tests/test-chat-template \ tests/test-chat-template \
tests/test-double-float \ tests/test-double-float \
tests/test-grammar-integration \ tests/test-grammar-integration \
@ -250,11 +257,11 @@ endif
# Compile flags # Compile flags
# #
# keep standard at C11 and C++11 # keep standard at C11 and C++17
MK_CPPFLAGS = -Iggml/include -Iggml/src -Iinclude -Isrc -Icommon MK_CPPFLAGS = -Iggml/include -Iggml/src -Iinclude -Isrc -Icommon -DGGML_USE_CPU
MK_CFLAGS = -std=c11 -fPIC MK_CFLAGS = -std=c11 -fPIC
MK_CXXFLAGS = -std=c++11 -fPIC MK_CXXFLAGS = -std=c++17 -fPIC
MK_NVCCFLAGS = -std=c++11 MK_NVCCFLAGS = -std=c++17
ifdef LLAMA_NO_CCACHE ifdef LLAMA_NO_CCACHE
GGML_NO_CCACHE := 1 GGML_NO_CCACHE := 1
@ -290,6 +297,7 @@ endif
# some memory allocation are available on Linux through GNU extensions in libc # some memory allocation are available on Linux through GNU extensions in libc
ifeq ($(UNAME_S),Linux) ifeq ($(UNAME_S),Linux)
MK_CPPFLAGS += -D_GNU_SOURCE MK_CPPFLAGS += -D_GNU_SOURCE
MK_LDFLAGS += -ldl
endif endif
# RLIMIT_MEMLOCK came in BSD, is not specified in POSIX.1, # RLIMIT_MEMLOCK came in BSD, is not specified in POSIX.1,
@ -359,7 +367,7 @@ ifdef LLAMA_SERVER_SSL
endif endif
ifndef GGML_NO_CPU_AARCH64 ifndef GGML_NO_CPU_AARCH64
MK_CPPFLAGS += -DGGML_USE_CPU_AARCH64 MK_CPPFLAGS += -DGGML_USE_CPU_REPACK
endif endif
# warnings # warnings
@ -439,6 +447,10 @@ ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686 amd64))
MK_CFLAGS += -march=native -mtune=native MK_CFLAGS += -march=native -mtune=native
HOST_CXXFLAGS += -march=native -mtune=native HOST_CXXFLAGS += -march=native -mtune=native
# Usage AMX build test
#MK_CFLAGS += -march=graniterapids -mtune=graniterapids
#HOST_CXXFLAGS += -march=graniterapids -mtune=graniterapids
# Usage AVX-only # Usage AVX-only
#MK_CFLAGS += -mfma -mf16c -mavx #MK_CFLAGS += -mfma -mf16c -mavx
#MK_CXXFLAGS += -mfma -mf16c -mavx #MK_CXXFLAGS += -mfma -mf16c -mavx
@ -451,7 +463,7 @@ endif
ifneq '' '$(findstring mingw,$(shell $(CC) -dumpmachine))' ifneq '' '$(findstring mingw,$(shell $(CC) -dumpmachine))'
# The stack is only 16-byte aligned on Windows, so don't let gcc emit aligned moves. # The stack is only 16-byte aligned on Windows, so don't let gcc emit aligned moves.
# https://gcc.gnu.org/bugzilla/show_bug.cgi?id=54412 # https://gcc.gnu.org/bugzilla/show_bug.cgi?id=54412
# https://github.com/ggerganov/llama.cpp/issues/2922 # https://github.com/ggml-org/llama.cpp/issues/2922
MK_CFLAGS += -Xassembler -muse-unaligned-vector-move MK_CFLAGS += -Xassembler -muse-unaligned-vector-move
MK_CXXFLAGS += -Xassembler -muse-unaligned-vector-move MK_CXXFLAGS += -Xassembler -muse-unaligned-vector-move
@ -573,15 +585,18 @@ endif
ifndef GGML_NO_AMX ifndef GGML_NO_AMX
MK_CPPFLAGS += -DGGML_USE_AMX MK_CPPFLAGS += -DGGML_USE_AMX
OBJ_GGML_EXT += ggml/src/ggml-amx/ggml-amx.o ggml/src/ggml-amx/mmq.o OBJ_GGML_EXT += ggml/src/ggml-cpu/amx/amx.o ggml/src/ggml-cpu/amx/mmq.o
endif endif
# only necessary for the CPU backend files
MK_CPPFLAGS += -Iggml/src/ggml-cpu
ifdef GGML_RPC ifdef GGML_RPC
MK_CPPFLAGS += -DGGML_USE_RPC MK_CPPFLAGS += -DGGML_USE_RPC
OBJ_GGML_EXT += ggml/src/ggml-rpc.o OBJ_GGML_EXT += ggml/src/ggml-rpc.o
endif # GGML_RPC endif # GGML_RPC
OBJ_CUDA_TMPL = $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/fattn-wmma*.cu)) OBJ_CUDA_TMPL = $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/fattn-mma*.cu))
OBJ_CUDA_TMPL += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/mmq*.cu)) OBJ_CUDA_TMPL += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/template-instances/mmq*.cu))
ifdef GGML_CUDA_FA_ALL_QUANTS ifdef GGML_CUDA_FA_ALL_QUANTS
@ -665,6 +680,10 @@ ifdef GGML_CUDA_CCBIN
MK_NVCCFLAGS += -ccbin $(GGML_CUDA_CCBIN) MK_NVCCFLAGS += -ccbin $(GGML_CUDA_CCBIN)
endif # GGML_CUDA_CCBIN endif # GGML_CUDA_CCBIN
ifdef GGML_CUDA_NO_FA
MK_NVCCFLAGS += -DGGML_CUDA_NO_FA
endif # GGML_CUDA_NO_FA
ifdef GGML_CUDA_FA_ALL_QUANTS ifdef GGML_CUDA_FA_ALL_QUANTS
MK_NVCCFLAGS += -DGGML_CUDA_FA_ALL_QUANTS MK_NVCCFLAGS += -DGGML_CUDA_FA_ALL_QUANTS
endif # GGML_CUDA_FA_ALL_QUANTS endif # GGML_CUDA_FA_ALL_QUANTS
@ -750,7 +769,7 @@ vulkan-shaders-gen: ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
endif # GGML_VULKAN endif # GGML_VULKAN
ifdef GGML_HIPBLAS ifdef GGML_HIP
ifeq ($(wildcard /opt/rocm),) ifeq ($(wildcard /opt/rocm),)
ROCM_PATH ?= /usr ROCM_PATH ?= /usr
AMDGPU_TARGETS ?= $(shell $(shell which amdgpu-arch)) AMDGPU_TARGETS ?= $(shell $(shell which amdgpu-arch))
@ -761,10 +780,6 @@ ifdef GGML_HIPBLAS
MK_CPPFLAGS += -DGGML_USE_HIP -DGGML_USE_CUDA MK_CPPFLAGS += -DGGML_USE_HIP -DGGML_USE_CUDA
ifdef GGML_HIP_UMA
MK_CPPFLAGS += -DGGML_HIP_UMA
endif # GGML_HIP_UMA
MK_LDFLAGS += -L$(ROCM_PATH)/lib -Wl,-rpath=$(ROCM_PATH)/lib MK_LDFLAGS += -L$(ROCM_PATH)/lib -Wl,-rpath=$(ROCM_PATH)/lib
MK_LDFLAGS += -L$(ROCM_PATH)/lib64 -Wl,-rpath=$(ROCM_PATH)/lib64 MK_LDFLAGS += -L$(ROCM_PATH)/lib64 -Wl,-rpath=$(ROCM_PATH)/lib64
MK_LDFLAGS += -lhipblas -lamdhip64 -lrocblas MK_LDFLAGS += -lhipblas -lamdhip64 -lrocblas
@ -785,6 +800,10 @@ ifdef GGML_CUDA_NO_PEER_COPY
HIPFLAGS += -DGGML_CUDA_NO_PEER_COPY HIPFLAGS += -DGGML_CUDA_NO_PEER_COPY
endif # GGML_CUDA_NO_PEER_COPY endif # GGML_CUDA_NO_PEER_COPY
ifdef GGML_CUDA_NO_FA
HIPFLAGS += -DGGML_CUDA_NO_FA
endif # GGML_CUDA_NO_FA
OBJ_GGML_EXT += ggml/src/ggml-cuda/ggml-cuda.o OBJ_GGML_EXT += ggml/src/ggml-cuda/ggml-cuda.o
OBJ_GGML_EXT += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/*.cu)) OBJ_GGML_EXT += $(patsubst %.cu,%.o,$(wildcard ggml/src/ggml-cuda/*.cu))
OBJ_GGML_EXT += $(OBJ_CUDA_TMPL) OBJ_GGML_EXT += $(OBJ_CUDA_TMPL)
@ -805,7 +824,7 @@ ggml/src/ggml-cuda/%.o: \
ggml/src/ggml-common.h \ ggml/src/ggml-common.h \
ggml/src/ggml-cuda/common.cuh ggml/src/ggml-cuda/common.cuh
$(HIPCC) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $< $(HIPCC) $(CXXFLAGS) $(HIPFLAGS) -x hip -c -o $@ $<
endif # GGML_HIPBLAS endif # GGML_HIP
ifdef GGML_MUSA ifdef GGML_MUSA
ifeq ($(wildcard /opt/musa),) ifeq ($(wildcard /opt/musa),)
@ -813,7 +832,7 @@ ifdef GGML_MUSA
else else
MUSA_PATH ?= /opt/musa MUSA_PATH ?= /opt/musa
endif endif
MTGPU_TARGETS ?= mp_21 mp_22 MUSA_ARCHITECTURES ?= 21;22;31
MK_CPPFLAGS += -DGGML_USE_MUSA -DGGML_USE_CUDA MK_CPPFLAGS += -DGGML_USE_MUSA -DGGML_USE_CUDA
MK_LDFLAGS += -L$(MUSA_PATH)/lib -Wl,-rpath=$(MUSA_PATH)/lib MK_LDFLAGS += -L$(MUSA_PATH)/lib -Wl,-rpath=$(MUSA_PATH)/lib
@ -832,7 +851,8 @@ ifdef GGML_MUSA
CXX := $(MUSA_PATH)/bin/clang++ CXX := $(MUSA_PATH)/bin/clang++
MCC := $(CCACHE) $(MUSA_PATH)/bin/mcc MCC := $(CCACHE) $(MUSA_PATH)/bin/mcc
MUSAFLAGS += $(addprefix --cuda-gpu-arch=, $(MTGPU_TARGETS)) MUSAFLAGS = -fsigned-char -x musa -mtgpu
MUSAFLAGS += $(foreach arch,$(subst ;, ,$(MUSA_ARCHITECTURES)),--cuda-gpu-arch=mp_$(arch))
ifdef GGML_CUDA_FORCE_MMQ ifdef GGML_CUDA_FORCE_MMQ
MUSAFLAGS += -DGGML_CUDA_FORCE_MMQ MUSAFLAGS += -DGGML_CUDA_FORCE_MMQ
@ -860,6 +880,10 @@ ifdef GGML_CUDA_NO_PEER_COPY
MUSAFLAGS += -DGGML_CUDA_NO_PEER_COPY MUSAFLAGS += -DGGML_CUDA_NO_PEER_COPY
endif # GGML_CUDA_NO_PEER_COPY endif # GGML_CUDA_NO_PEER_COPY
ifdef GGML_CUDA_NO_FA
MUSAFLAGS += -DGGML_CUDA_NO_FA
endif # GGML_CUDA_NO_FA
ifdef GGML_CUDA_FA_ALL_QUANTS ifdef GGML_CUDA_FA_ALL_QUANTS
MUSAFLAGS += -DGGML_CUDA_FA_ALL_QUANTS MUSAFLAGS += -DGGML_CUDA_FA_ALL_QUANTS
endif # GGML_CUDA_FA_ALL_QUANTS endif # GGML_CUDA_FA_ALL_QUANTS
@ -876,14 +900,14 @@ ggml/src/ggml-cuda/ggml-cuda.o: \
ggml/src/ggml-backend-impl.h \ ggml/src/ggml-backend-impl.h \
ggml/src/ggml-common.h \ ggml/src/ggml-common.h \
$(wildcard ggml/src/ggml-cuda/*.cuh) $(wildcard ggml/src/ggml-cuda/*.cuh)
$(MCC) $(CXXFLAGS) $(MUSAFLAGS) -x musa -mtgpu -c -o $@ $< $(MCC) $(CXXFLAGS) $(MUSAFLAGS) -c -o $@ $<
ggml/src/ggml-cuda/%.o: \ ggml/src/ggml-cuda/%.o: \
ggml/src/ggml-cuda/%.cu \ ggml/src/ggml-cuda/%.cu \
ggml/include/ggml.h \ ggml/include/ggml.h \
ggml/src/ggml-common.h \ ggml/src/ggml-common.h \
ggml/src/ggml-cuda/common.cuh ggml/src/ggml-cuda/common.cuh
$(MCC) $(CXXFLAGS) $(MUSAFLAGS) -x musa -mtgpu -c -o $@ $< $(MCC) $(CXXFLAGS) $(MUSAFLAGS) -c -o $@ $<
endif # GGML_MUSA endif # GGML_MUSA
ifdef GGML_METAL ifdef GGML_METAL
@ -938,7 +962,6 @@ DIR_COMMON = common
OBJ_GGML = \ OBJ_GGML = \
$(DIR_GGML)/src/ggml.o \ $(DIR_GGML)/src/ggml.o \
$(DIR_GGML)/src/ggml-aarch64.o \
$(DIR_GGML)/src/ggml-alloc.o \ $(DIR_GGML)/src/ggml-alloc.o \
$(DIR_GGML)/src/ggml-backend.o \ $(DIR_GGML)/src/ggml-backend.o \
$(DIR_GGML)/src/ggml-backend-reg.o \ $(DIR_GGML)/src/ggml-backend-reg.o \
@ -946,9 +969,11 @@ OBJ_GGML = \
$(DIR_GGML)/src/ggml-quants.o \ $(DIR_GGML)/src/ggml-quants.o \
$(DIR_GGML)/src/ggml-threading.o \ $(DIR_GGML)/src/ggml-threading.o \
$(DIR_GGML)/src/ggml-cpu/ggml-cpu.o \ $(DIR_GGML)/src/ggml-cpu/ggml-cpu.o \
$(DIR_GGML)/src/ggml-cpu/ggml-cpu-cpp.o \ $(DIR_GGML)/src/ggml-cpu/ggml-cpu_cpp.o \
$(DIR_GGML)/src/ggml-cpu/ggml-cpu-aarch64.o \ $(DIR_GGML)/src/ggml-cpu/repack.o \
$(DIR_GGML)/src/ggml-cpu/ggml-cpu-hbm.o \
$(DIR_GGML)/src/ggml-cpu/ggml-cpu-quants.o \ $(DIR_GGML)/src/ggml-cpu/ggml-cpu-quants.o \
$(DIR_GGML)/src/ggml-cpu/ggml-cpu-traits.o \
$(OBJ_GGML_EXT) $(OBJ_GGML_EXT)
OBJ_LLAMA = \ OBJ_LLAMA = \
@ -966,6 +991,8 @@ OBJ_COMMON = \
$(DIR_COMMON)/console.o \ $(DIR_COMMON)/console.o \
$(DIR_COMMON)/ngram-cache.o \ $(DIR_COMMON)/ngram-cache.o \
$(DIR_COMMON)/sampling.o \ $(DIR_COMMON)/sampling.o \
$(DIR_COMMON)/speculative.o \
$(DIR_COMMON)/chat.o \
$(DIR_COMMON)/build-info.o \ $(DIR_COMMON)/build-info.o \
$(DIR_COMMON)/json-schema-to-grammar.o $(DIR_COMMON)/json-schema-to-grammar.o
@ -1059,8 +1086,8 @@ endif
ifdef REMOVE_WARNING ifdef REMOVE_WARNING
$(info !!! REMOVAL WARNING !!!) $(info !!! REMOVAL WARNING !!!)
$(info The following LLAMA_ options have been removed and are no longer supported) $(info The following LLAMA_ options have been removed and are no longer supported)
$(info - LLAMA_DISABLE_LOGS (https://github.com/ggerganov/llama.cpp/pull/9418)) $(info - LLAMA_DISABLE_LOGS (https://github.com/ggml-org/llama.cpp/pull/9418))
$(info - LLAMA_SERVER_VERBOSE (https://github.com/ggerganov/llama.cpp/pull/9418)) $(info - LLAMA_SERVER_VERBOSE (https://github.com/ggml-org/llama.cpp/pull/9418))
$(info ) $(info )
endif endif
@ -1087,17 +1114,10 @@ DEP_FILES = $(OBJ_GGML:.o=.d) $(OBJ_LLAMA:.o=.d) $(OBJ_COMMON:.o=.d)
# Default target # Default target
all: $(BUILD_TARGETS) all: $(BUILD_TARGETS)
# force c++ build for source file that have same name as c file
# Note: need this exception because `ggml-cpu.c` and `ggml-cpu.cpp` both produce the same obj/dep files # Note: need this exception because `ggml-cpu.c` and `ggml-cpu.cpp` both produce the same obj/dep files
# g++ -M -I ./ggml/include/ -I ./ggml/src ggml/src/ggml-cpu/ggml-cpu.cpp | grep ggml $(DIR_GGML)/%_cpp.o: $(DIR_GGML)/%.cpp
$(DIR_GGML)/src/ggml-cpu/ggml-cpu-cpp.o: \ $(CXX) $(CXXFLAGS) -MMD -c $< -o $@
ggml/src/ggml-cpu/ggml-cpu.cpp \
ggml/include/ggml-backend.h \
ggml/include/ggml.h \
ggml/include/ggml-alloc.h \
ggml/src/ggml-backend-impl.h \
ggml/include/ggml-cpu.h \
ggml/src/ggml-impl.h
$(CXX) $(CXXFLAGS) -c $< -o $@
# Rules for building object files # Rules for building object files
$(DIR_GGML)/%.o: $(DIR_GGML)/%.c $(DIR_GGML)/%.o: $(DIR_GGML)/%.c
@ -1134,8 +1154,15 @@ $(LIB_COMMON_S): $(OBJ_COMMON)
# Include dependency files # Include dependency files
-include $(DEP_FILES) -include $(DEP_FILES)
# Clean generated server assets
clean-server-assets:
find tools/server -type f -name "*.js.hpp" -delete
find tools/server -type f -name "*.mjs.hpp" -delete
find tools/server -type f -name "*.css.hpp" -delete
find tools/server -type f -name "*.html.hpp" -delete
# Clean rule # Clean rule
clean: clean: clean-server-assets
rm -vrf $(BUILD_TARGETS) $(TEST_TARGETS) rm -vrf $(BUILD_TARGETS) $(TEST_TARGETS)
rm -rvf *.a *.dll *.so *.dot rm -rvf *.a *.dll *.so *.dot
find ggml src common tests examples pocs -type f -name "*.o" -delete find ggml src common tests examples pocs -type f -name "*.o" -delete
@ -1152,7 +1179,7 @@ clean:
# Helper function that replaces .c, .cpp, and .cu file endings with .o: # Helper function that replaces .c, .cpp, and .cu file endings with .o:
GET_OBJ_FILE = $(patsubst %.c,%.o,$(patsubst %.cpp,%.o,$(patsubst %.cu,%.o,$(1)))) GET_OBJ_FILE = $(patsubst %.c,%.o,$(patsubst %.cpp,%.o,$(patsubst %.cu,%.o,$(1))))
llama-cli: examples/main/main.cpp \ llama-cli: tools/main/main.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@ -1160,7 +1187,7 @@ llama-cli: examples/main/main.cpp \
@echo '==== Run ./llama-cli -h for help. ====' @echo '==== Run ./llama-cli -h for help. ===='
@echo @echo
llama-infill: examples/infill/infill.cpp \ llama-run: tools/run/run.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@ -1175,7 +1202,7 @@ llama-simple-chat: examples/simple-chat/simple-chat.cpp \
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-tokenize: examples/tokenize/tokenize.cpp \ llama-tokenize: tools/tokenize/tokenize.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@ -1185,27 +1212,27 @@ llama-batched: examples/batched/batched.cpp \
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-batched-bench: examples/batched-bench/batched-bench.cpp \ llama-batched-bench: tools/batched-bench/batched-bench.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-quantize: examples/quantize/quantize.cpp \ llama-quantize: tools/quantize/quantize.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-quantize-stats: examples/quantize-stats/quantize-stats.cpp \ llama-quantize-stats: tools/quantize-stats/quantize-stats.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-perplexity: examples/perplexity/perplexity.cpp \ llama-perplexity: tools/perplexity/perplexity.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-imatrix: examples/imatrix/imatrix.cpp \ llama-imatrix: tools/imatrix/imatrix.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@ -1247,7 +1274,7 @@ llama-gguf-hash: examples/gguf-hash/gguf-hash.cpp examples/gguf-hash/deps/sha1/s
$(CXX) $(CXXFLAGS) -Iexamples/gguf-hash/deps -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -Iexamples/gguf-hash/deps -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-gguf-split: examples/gguf-split/gguf-split.cpp \ llama-gguf-split: tools/gguf-split/gguf-split.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@ -1257,7 +1284,7 @@ llama-eval-callback: examples/eval-callback/eval-callback.cpp \
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-cvector-generator: examples/cvector-generator/cvector-generator.cpp \ llama-cvector-generator: tools/cvector-generator/cvector-generator.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@ -1267,12 +1294,12 @@ llama-convert-llama2c-to-ggml: examples/convert-llama2c-to-ggml/convert-llama2c-
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-bench: examples/llama-bench/llama-bench.cpp \ llama-bench: tools/llama-bench/llama-bench.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-export-lora: examples/export-lora/export-lora.cpp \ llama-export-lora: tools/export-lora/export-lora.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@ -1328,30 +1355,28 @@ llama-gbnf-validator: examples/gbnf-validator/gbnf-validator.cpp \
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
ifdef GGML_RPC ifdef GGML_RPC
rpc-server: examples/rpc/rpc-server.cpp \ rpc-server: tools/rpc/rpc-server.cpp \
$(OBJ_GGML) $(OBJ_GGML)
$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
endif # GGML_RPC endif # GGML_RPC
llama-server: \ llama-server: \
examples/server/server.cpp \ tools/server/server.cpp \
examples/server/utils.hpp \ tools/server/utils.hpp \
examples/server/httplib.h \ tools/server/httplib.h \
examples/server/index.html.hpp \ tools/server/index.html.hpp \
examples/server/completion.js.hpp \ tools/server/loading.html.hpp \
examples/server/loading.html.hpp \ common/chat.cpp \
examples/server/deps_daisyui.min.css.hpp \ common/chat.h \
examples/server/deps_markdown-it.js.hpp \ common/chat-template.hpp \
examples/server/deps_tailwindcss.js.hpp \
examples/server/deps_vue.esm-browser.js.hpp \
common/json.hpp \ common/json.hpp \
common/stb_image.h \ common/minja.hpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h %.hpp $<,$^) -Iexamples/server $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(LWINSOCK2) $(CXX) $(CXXFLAGS) $(filter-out %.h %.hpp $<,$^) -Itools/server $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(LWINSOCK2)
# Portable equivalent of `cd examples/server/public && xxd -i $(notdir $<) ../$(notdir $<).hpp`: # Portable equivalent of `cd tools/server/public && xxd -i $(notdir $<) ../$(notdir $<).hpp`:
examples/server/%.hpp: examples/server/public/% Makefile tools/server/%.hpp: tools/server/public/% FORCE Makefile
@( export NAME=$(subst .,_,$(subst -,_,$(notdir $<))) && \ @( export NAME=$(subst .,_,$(subst -,_,$(notdir $<))) && \
echo "unsigned char $${NAME}[] = {" && \ echo "unsigned char $${NAME}[] = {" && \
cat $< | od -v -t x1 -An | sed -E 's/([0-9a-fA-F]+)/0x\1, /g' && \ cat $< | od -v -t x1 -An | sed -E 's/([0-9a-fA-F]+)/0x\1, /g' && \
@ -1364,28 +1389,36 @@ llama-gen-docs: examples/gen-docs/gen-docs.cpp \
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
libllava.a: examples/llava/llava.cpp \ libllava.a: tools/mtmd/llava.cpp \
examples/llava/llava.h \ tools/mtmd/llava.h \
examples/llava/clip.cpp \ tools/mtmd/clip.cpp \
examples/llava/clip.h \ tools/mtmd/clip.h \
common/stb_image.h \ common/stb_image.h \
common/base64.hpp \ common/base64.hpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -static -fPIC -c $< -o $@ -Wno-cast-qual $(CXX) $(CXXFLAGS) -static -fPIC -c $< -o $@ -Wno-cast-qual
llama-llava-cli: examples/llava/llava-cli.cpp \ llama-llava-cli: tools/mtmd/llava-cli.cpp \
examples/llava/llava.cpp \ tools/mtmd/llava.cpp \
examples/llava/llava.h \ tools/mtmd/llava.h \
examples/llava/clip.cpp \ tools/mtmd/clip.cpp \
examples/llava/clip.h \ tools/mtmd/clip.h \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) $< $(filter-out %.h $<,$^) -o $@ $(LDFLAGS) -Wno-cast-qual $(CXX) $(CXXFLAGS) $< $(filter-out %.h $<,$^) -o $@ $(LDFLAGS) -Wno-cast-qual
llama-minicpmv-cli: examples/llava/minicpmv-cli.cpp \ llama-minicpmv-cli: tools/mtmd/minicpmv-cli.cpp \
examples/llava/llava.cpp \ tools/mtmd/llava.cpp \
examples/llava/llava.h \ tools/mtmd/llava.h \
examples/llava/clip.cpp \ tools/mtmd/clip.cpp \
examples/llava/clip.h \ tools/mtmd/clip.h \
$(OBJ_ALL)
$(CXX) $(CXXFLAGS) $< $(filter-out %.h $<,$^) -o $@ $(LDFLAGS) -Wno-cast-qual
llama-qwen2vl-cli: tools/mtmd/qwen2vl-cli.cpp \
tools/mtmd/llava.cpp \
tools/mtmd/llava.h \
tools/mtmd/clip.cpp \
tools/mtmd/clip.h \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) $< $(filter-out %.h $<,$^) -o $@ $(LDFLAGS) -Wno-cast-qual $(CXX) $(CXXFLAGS) $< $(filter-out %.h $<,$^) -o $@ $(LDFLAGS) -Wno-cast-qual
@ -1442,7 +1475,12 @@ tests/test-double-float: tests/test-double-float.cpp
tests/test-json-schema-to-grammar: tests/test-json-schema-to-grammar.cpp \ tests/test-json-schema-to-grammar: tests/test-json-schema-to-grammar.cpp \
$(OBJ_ALL) $(OBJ_ALL)
$(CXX) $(CXXFLAGS) -Iexamples/server -c $< -o $(call GET_OBJ_FILE, $<) $(CXX) $(CXXFLAGS) -Itools/server -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
tests/test-chat: tests/test-chat.cpp \
$(OBJ_ALL)
$(CXX) $(CXXFLAGS) -Itools/server -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
tests/test-opt: tests/test-opt.cpp \ tests/test-opt: tests/test-opt.cpp \
@ -1526,7 +1564,7 @@ llama-q8dot: pocs/vdot/q8dot.cpp ggml/src/ggml.o \
# Deprecated binaries that we want to keep around long enough for people to migrate to the new filenames, then these can be removed. # Deprecated binaries that we want to keep around long enough for people to migrate to the new filenames, then these can be removed.
# #
# Mark legacy binary targets as .PHONY so that they are always checked. # Mark legacy binary targets as .PHONY so that they are always checked.
.PHONY: main quantize perplexity embedding server .PHONY: FORCE main quantize perplexity embedding server
# Define the object file target # Define the object file target
examples/deprecation-warning/deprecation-warning.o: examples/deprecation-warning/deprecation-warning.cpp examples/deprecation-warning/deprecation-warning.o: examples/deprecation-warning/deprecation-warning.cpp

View File

@ -1,89 +0,0 @@
// swift-tools-version:5.5
import PackageDescription
var sources = [
"src/llama.cpp",
"src/llama-vocab.cpp",
"src/llama-grammar.cpp",
"src/llama-sampling.cpp",
"src/unicode.cpp",
"src/unicode-data.cpp",
"ggml/src/ggml.c",
"ggml/src/ggml-aarch64.c",
"ggml/src/ggml-alloc.c",
"ggml/src/ggml-backend.cpp",
"ggml/src/ggml-backend-reg.cpp",
"ggml/src/ggml-cpu/ggml-cpu.c",
"ggml/src/ggml-cpu/ggml-cpu.cpp",
"ggml/src/ggml-cpu/ggml-cpu-aarch64.c",
"ggml/src/ggml-cpu/ggml-cpu-quants.c",
"ggml/src/ggml-threading.cpp",
"ggml/src/ggml-quants.c",
]
var resources: [Resource] = []
var linkerSettings: [LinkerSetting] = []
var cSettings: [CSetting] = [
.unsafeFlags(["-Wno-shorten-64-to-32", "-O3", "-DNDEBUG"]),
.unsafeFlags(["-fno-objc-arc"]),
.headerSearchPath("ggml/src"),
// NOTE: NEW_LAPACK will required iOS version 16.4+
// We should consider add this in the future when we drop support for iOS 14
// (ref: ref: https://developer.apple.com/documentation/accelerate/1513264-cblas_sgemm?language=objc)
// .define("ACCELERATE_NEW_LAPACK"),
// .define("ACCELERATE_LAPACK_ILP64")
]
#if canImport(Darwin)
sources.append("ggml/src/ggml-common.h")
sources.append("ggml/src/ggml-metal/ggml-metal.m")
resources.append(.process("ggml/src/ggml-metal/ggml-metal.metal"))
linkerSettings.append(.linkedFramework("Accelerate"))
cSettings.append(
contentsOf: [
.define("GGML_USE_ACCELERATE"),
.define("GGML_USE_METAL")
]
)
#endif
#if os(Linux)
cSettings.append(.define("_GNU_SOURCE"))
#endif
let package = Package(
name: "llama",
platforms: [
.macOS(.v12),
.iOS(.v14),
.watchOS(.v4),
.tvOS(.v14)
],
products: [
.library(name: "llama", targets: ["llama"]),
],
targets: [
.target(
name: "llama",
path: ".",
exclude: [
"build",
"cmake",
"examples",
"scripts",
"models",
"tests",
"CMakeLists.txt",
"Makefile",
"ggml/src/ggml-metal-embed.metal"
],
sources: sources,
resources: resources,
publicHeadersPath: "spm-headers",
cSettings: cSettings,
linkerSettings: linkerSettings
)
],
cxxLanguageStandard: .cxx11
)

748
README.md
View File

@ -3,47 +3,79 @@
![llama](https://user-images.githubusercontent.com/1991296/230134379-7181e485-c521-4d23-a0d6-f7b3b61ba524.png) ![llama](https://user-images.githubusercontent.com/1991296/230134379-7181e485-c521-4d23-a0d6-f7b3b61ba524.png)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT) [![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![Server](https://github.com/ggerganov/llama.cpp/actions/workflows/server.yml/badge.svg)](https://github.com/ggerganov/llama.cpp/actions/workflows/server.yml) [![Release](https://img.shields.io/github/v/release/ggml-org/llama.cpp)](https://github.com/ggml-org/llama.cpp/releases)
[![Conan Center](https://shields.io/conan/v/llama-cpp)](https://conan.io/center/llama-cpp) [![Server](https://github.com/ggml-org/llama.cpp/actions/workflows/server.yml/badge.svg)](https://github.com/ggml-org/llama.cpp/actions/workflows/server.yml)
[Roadmap](https://github.com/users/ggerganov/projects/7) / [Project status](https://github.com/ggerganov/llama.cpp/discussions/3471) / [Manifesto](https://github.com/ggerganov/llama.cpp/discussions/205) / [ggml](https://github.com/ggerganov/ggml) [Roadmap](https://github.com/users/ggerganov/projects/7) / [Manifesto](https://github.com/ggml-org/llama.cpp/discussions/205) / [ggml](https://github.com/ggml-org/ggml)
Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others) in pure C/C++ Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others) in pure C/C++
## Recent API changes ## Recent API changes
- [Changelog for `libllama` API](https://github.com/ggerganov/llama.cpp/issues/9289) - [Changelog for `libllama` API](https://github.com/ggml-org/llama.cpp/issues/9289)
- [Changelog for `llama-server` REST API](https://github.com/ggerganov/llama.cpp/issues/9291) - [Changelog for `llama-server` REST API](https://github.com/ggml-org/llama.cpp/issues/9291)
## Hot topics ## Hot topics
- **Introducing GGUF-my-LoRA** https://github.com/ggerganov/llama.cpp/discussions/10123 - 🔥 Multimodal support arrived in `llama-server`: [#12898](https://github.com/ggml-org/llama.cpp/pull/12898) | [documentation](./docs/multimodal.md)
- Hugging Face Inference Endpoints now support GGUF out of the box! https://github.com/ggerganov/llama.cpp/discussions/9669 - A new binary `llama-mtmd-cli` is introduced to replace `llava-cli`, `minicpmv-cli`, `gemma3-cli` ([#13012](https://github.com/ggml-org/llama.cpp/pull/13012)) and `qwen2vl-cli` ([#13141](https://github.com/ggml-org/llama.cpp/pull/13141)), `libllava` will be deprecated
- Hugging Face GGUF editor: [discussion](https://github.com/ggerganov/llama.cpp/discussions/9268) | [tool](https://huggingface.co/spaces/CISCai/gguf-editor) - VS Code extension for FIM completions: https://github.com/ggml-org/llama.vscode
- Universal [tool call support](./docs/function-calling.md) in `llama-server` https://github.com/ggml-org/llama.cpp/pull/9639
- Vim/Neovim plugin for FIM completions: https://github.com/ggml-org/llama.vim
- Introducing GGUF-my-LoRA https://github.com/ggml-org/llama.cpp/discussions/10123
- Hugging Face Inference Endpoints now support GGUF out of the box! https://github.com/ggml-org/llama.cpp/discussions/9669
- Hugging Face GGUF editor: [discussion](https://github.com/ggml-org/llama.cpp/discussions/9268) | [tool](https://huggingface.co/spaces/CISCai/gguf-editor)
---- ----
## Quick start
Getting started with llama.cpp is straightforward. Here are several ways to install it on your machine:
- Install `llama.cpp` using [brew, nix or winget](docs/install.md)
- Run with Docker - see our [Docker documentation](docs/docker.md)
- Download pre-built binaries from the [releases page](https://github.com/ggml-org/llama.cpp/releases)
- Build from source by cloning this repository - check out [our build guide](docs/build.md)
Once installed, you'll need a model to work with. Head to the [Obtaining and quantizing models](#obtaining-and-quantizing-models) section to learn more.
Example command:
```sh
# Use a local model file
llama-cli -m my_model.gguf
# Or download and run a model directly from Hugging Face
llama-cli -hf ggml-org/gemma-3-1b-it-GGUF
# Launch OpenAI-compatible API server
llama-server -hf ggml-org/gemma-3-1b-it-GGUF
```
## Description ## Description
The main goal of `llama.cpp` is to enable LLM inference with minimal setup and state-of-the-art performance on a wide The main goal of `llama.cpp` is to enable LLM inference with minimal setup and state-of-the-art performance on a wide
variety of hardware - locally and in the cloud. range of hardware - locally and in the cloud.
- Plain C/C++ implementation without any dependencies - Plain C/C++ implementation without any dependencies
- Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks - Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks
- AVX, AVX2, AVX512 and AMX support for x86 architectures - AVX, AVX2, AVX512 and AMX support for x86 architectures
- 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use - 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use
- Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads MTT GPUs via MUSA) - Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads GPUs via MUSA)
- Vulkan and SYCL backend support - Vulkan and SYCL backend support
- CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity - CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity
Since its [inception](https://github.com/ggerganov/llama.cpp/issues/33#issuecomment-1465108022), the project has The `llama.cpp` project is the main playground for developing new features for the [ggml](https://github.com/ggml-org/ggml) library.
improved significantly thanks to many contributions. It is the main playground for developing new features for the
[ggml](https://github.com/ggerganov/ggml) library.
**Supported models:** <details>
<summary>Models</summary>
Typically finetunes of the base models below are supported as well. Typically finetunes of the base models below are supported as well.
Instructions for adding support for new models: [HOWTO-add-model.md](docs/development/HOWTO-add-model.md)
#### Text-only
- [X] LLaMA 🦙 - [X] LLaMA 🦙
- [x] LLaMA 2 🦙🦙 - [x] LLaMA 2 🦙🦙
- [x] LLaMA 3 🦙🦙🦙 - [x] LLaMA 3 🦙🦙🦙
@ -53,22 +85,23 @@ Typically finetunes of the base models below are supported as well.
- [X] [Falcon](https://huggingface.co/models?search=tiiuae/falcon) - [X] [Falcon](https://huggingface.co/models?search=tiiuae/falcon)
- [X] [Chinese LLaMA / Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca) and [Chinese LLaMA-2 / Alpaca-2](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2) - [X] [Chinese LLaMA / Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca) and [Chinese LLaMA-2 / Alpaca-2](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2)
- [X] [Vigogne (French)](https://github.com/bofenghuang/vigogne) - [X] [Vigogne (French)](https://github.com/bofenghuang/vigogne)
- [X] [BERT](https://github.com/ggerganov/llama.cpp/pull/5423) - [X] [BERT](https://github.com/ggml-org/llama.cpp/pull/5423)
- [X] [Koala](https://bair.berkeley.edu/blog/2023/04/03/koala/) - [X] [Koala](https://bair.berkeley.edu/blog/2023/04/03/koala/)
- [X] [Baichuan 1 & 2](https://huggingface.co/models?search=baichuan-inc/Baichuan) + [derivations](https://huggingface.co/hiyouga/baichuan-7b-sft) - [X] [Baichuan 1 & 2](https://huggingface.co/models?search=baichuan-inc/Baichuan) + [derivations](https://huggingface.co/hiyouga/baichuan-7b-sft)
- [X] [Aquila 1 & 2](https://huggingface.co/models?search=BAAI/Aquila) - [X] [Aquila 1 & 2](https://huggingface.co/models?search=BAAI/Aquila)
- [X] [Starcoder models](https://github.com/ggerganov/llama.cpp/pull/3187) - [X] [Starcoder models](https://github.com/ggml-org/llama.cpp/pull/3187)
- [X] [Refact](https://huggingface.co/smallcloudai/Refact-1_6B-fim) - [X] [Refact](https://huggingface.co/smallcloudai/Refact-1_6B-fim)
- [X] [MPT](https://github.com/ggerganov/llama.cpp/pull/3417) - [X] [MPT](https://github.com/ggml-org/llama.cpp/pull/3417)
- [X] [Bloom](https://github.com/ggerganov/llama.cpp/pull/3553) - [X] [Bloom](https://github.com/ggml-org/llama.cpp/pull/3553)
- [x] [Yi models](https://huggingface.co/models?search=01-ai/Yi) - [x] [Yi models](https://huggingface.co/models?search=01-ai/Yi)
- [X] [StableLM models](https://huggingface.co/stabilityai) - [X] [StableLM models](https://huggingface.co/stabilityai)
- [x] [Deepseek models](https://huggingface.co/models?search=deepseek-ai/deepseek) - [x] [Deepseek models](https://huggingface.co/models?search=deepseek-ai/deepseek)
- [x] [Qwen models](https://huggingface.co/models?search=Qwen/Qwen) - [x] [Qwen models](https://huggingface.co/models?search=Qwen/Qwen)
- [x] [PLaMo-13B](https://github.com/ggerganov/llama.cpp/pull/3557) - [x] [PLaMo-13B](https://github.com/ggml-org/llama.cpp/pull/3557)
- [x] [Phi models](https://huggingface.co/models?search=microsoft/phi) - [x] [Phi models](https://huggingface.co/models?search=microsoft/phi)
- [x] [PhiMoE](https://github.com/ggml-org/llama.cpp/pull/11003)
- [x] [GPT-2](https://huggingface.co/gpt2) - [x] [GPT-2](https://huggingface.co/gpt2)
- [x] [Orion 14B](https://github.com/ggerganov/llama.cpp/pull/5118) - [x] [Orion 14B](https://github.com/ggml-org/llama.cpp/pull/5118)
- [x] [InternLM2](https://huggingface.co/models?search=internlm2) - [x] [InternLM2](https://huggingface.co/models?search=internlm2)
- [x] [CodeShell](https://github.com/WisdomShell/codeshell) - [x] [CodeShell](https://github.com/WisdomShell/codeshell)
- [x] [Gemma](https://ai.google.dev/gemma) - [x] [Gemma](https://ai.google.dev/gemma)
@ -79,6 +112,7 @@ Typically finetunes of the base models below are supported as well.
- [x] [SEA-LION](https://huggingface.co/models?search=sea-lion) - [x] [SEA-LION](https://huggingface.co/models?search=sea-lion)
- [x] [GritLM-7B](https://huggingface.co/GritLM/GritLM-7B) + [GritLM-8x7B](https://huggingface.co/GritLM/GritLM-8x7B) - [x] [GritLM-7B](https://huggingface.co/GritLM/GritLM-7B) + [GritLM-8x7B](https://huggingface.co/GritLM/GritLM-8x7B)
- [x] [OLMo](https://allenai.org/olmo) - [x] [OLMo](https://allenai.org/olmo)
- [x] [OLMo 2](https://allenai.org/olmo)
- [x] [OLMoE](https://huggingface.co/allenai/OLMoE-1B-7B-0924) - [x] [OLMoE](https://huggingface.co/allenai/OLMoE-1B-7B-0924)
- [x] [Granite models](https://huggingface.co/collections/ibm-granite/granite-code-models-6624c5cec322e4c148c8b330) - [x] [Granite models](https://huggingface.co/collections/ibm-granite/granite-code-models-6624c5cec322e4c148c8b330)
- [x] [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) + [Pythia](https://github.com/EleutherAI/pythia) - [x] [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) + [Pythia](https://github.com/EleutherAI/pythia)
@ -88,17 +122,20 @@ Typically finetunes of the base models below are supported as well.
- [x] [Bitnet b1.58 models](https://huggingface.co/1bitLLM) - [x] [Bitnet b1.58 models](https://huggingface.co/1bitLLM)
- [x] [Flan T5](https://huggingface.co/models?search=flan-t5) - [x] [Flan T5](https://huggingface.co/models?search=flan-t5)
- [x] [Open Elm models](https://huggingface.co/collections/apple/openelm-instruct-models-6619ad295d7ae9f868b759ca) - [x] [Open Elm models](https://huggingface.co/collections/apple/openelm-instruct-models-6619ad295d7ae9f868b759ca)
- [x] [ChatGLM3-6b](https://huggingface.co/THUDM/chatglm3-6b) + [ChatGLM4-9b](https://huggingface.co/THUDM/glm-4-9b) - [x] [ChatGLM3-6b](https://huggingface.co/THUDM/chatglm3-6b) + [ChatGLM4-9b](https://huggingface.co/THUDM/glm-4-9b) + [GLMEdge-1.5b](https://huggingface.co/THUDM/glm-edge-1.5b-chat) + [GLMEdge-4b](https://huggingface.co/THUDM/glm-edge-4b-chat)
- [x] [GLM-4-0414](https://huggingface.co/collections/THUDM/glm-4-0414-67f3cbcb34dd9d252707cb2e)
- [x] [SmolLM](https://huggingface.co/collections/HuggingFaceTB/smollm-6695016cad7167254ce15966) - [x] [SmolLM](https://huggingface.co/collections/HuggingFaceTB/smollm-6695016cad7167254ce15966)
- [x] [EXAONE-3.0-7.8B-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct) - [x] [EXAONE-3.0-7.8B-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct)
- [x] [FalconMamba Models](https://huggingface.co/collections/tiiuae/falconmamba-7b-66b9a580324dd1598b0f6d4a) - [x] [FalconMamba Models](https://huggingface.co/collections/tiiuae/falconmamba-7b-66b9a580324dd1598b0f6d4a)
- [x] [Jais](https://huggingface.co/inceptionai/jais-13b-chat) - [x] [Jais](https://huggingface.co/inceptionai/jais-13b-chat)
- [x] [Bielik-11B-v2.3](https://huggingface.co/collections/speakleash/bielik-11b-v23-66ee813238d9b526a072408a) - [x] [Bielik-11B-v2.3](https://huggingface.co/collections/speakleash/bielik-11b-v23-66ee813238d9b526a072408a)
- [x] [RWKV-6](https://github.com/BlinkDL/RWKV-LM) - [x] [RWKV-6](https://github.com/BlinkDL/RWKV-LM)
- [x] [QRWKV-6](https://huggingface.co/recursal/QRWKV6-32B-Instruct-Preview-v0.1)
- [x] [GigaChat-20B-A3B](https://huggingface.co/ai-sage/GigaChat-20B-A3B-instruct)
- [X] [Trillion-7B-preview](https://huggingface.co/trillionlabs/Trillion-7B-preview)
- [x] [Ling models](https://huggingface.co/collections/inclusionAI/ling-67c51c85b34a7ea0aba94c32)
(instructions for supporting more models: [HOWTO-add-model.md](./docs/development/HOWTO-add-model.md)) #### Multimodal
**Multimodal models:**
- [x] [LLaVA 1.5 models](https://huggingface.co/collections/liuhaotian/llava-15-653aac15d994e992e2677a7e), [LLaVA 1.6 models](https://huggingface.co/collections/liuhaotian/llava-16-65b9e40155f60fd046a5ccf2) - [x] [LLaVA 1.5 models](https://huggingface.co/collections/liuhaotian/llava-15-653aac15d994e992e2677a7e), [LLaVA 1.6 models](https://huggingface.co/collections/liuhaotian/llava-16-65b9e40155f60fd046a5ccf2)
- [x] [BakLLaVA](https://huggingface.co/models?search=SkunkworksAI/Bakllava) - [x] [BakLLaVA](https://huggingface.co/models?search=SkunkworksAI/Bakllava)
@ -109,9 +146,15 @@ Typically finetunes of the base models below are supported as well.
- [x] [Mini CPM](https://huggingface.co/models?search=MiniCPM) - [x] [Mini CPM](https://huggingface.co/models?search=MiniCPM)
- [x] [Moondream](https://huggingface.co/vikhyatk/moondream2) - [x] [Moondream](https://huggingface.co/vikhyatk/moondream2)
- [x] [Bunny](https://github.com/BAAI-DCAI/Bunny) - [x] [Bunny](https://github.com/BAAI-DCAI/Bunny)
- [x] [GLM-EDGE](https://huggingface.co/models?search=glm-edge)
- [x] [Qwen2-VL](https://huggingface.co/collections/Qwen/qwen2-vl-66cee7455501d7126940800d)
**Bindings:** </details>
<details>
<summary>Bindings</summary>
- Python: [ddh0/easy-llama](https://github.com/ddh0/easy-llama)
- Python: [abetlen/llama-cpp-python](https://github.com/abetlen/llama-cpp-python) - Python: [abetlen/llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
- Go: [go-skynet/go-llama.cpp](https://github.com/go-skynet/go-llama.cpp) - Go: [go-skynet/go-llama.cpp](https://github.com/go-skynet/go-llama.cpp)
- Node.js: [withcatai/node-llama-cpp](https://github.com/withcatai/node-llama-cpp) - Node.js: [withcatai/node-llama-cpp](https://github.com/withcatai/node-llama-cpp)
@ -123,6 +166,7 @@ Typically finetunes of the base models below are supported as well.
- Rust (more features): [edgenai/llama_cpp-rs](https://github.com/edgenai/llama_cpp-rs) - Rust (more features): [edgenai/llama_cpp-rs](https://github.com/edgenai/llama_cpp-rs)
- Rust (nicer API): [mdrokz/rust-llama.cpp](https://github.com/mdrokz/rust-llama.cpp) - Rust (nicer API): [mdrokz/rust-llama.cpp](https://github.com/mdrokz/rust-llama.cpp)
- Rust (more direct bindings): [utilityai/llama-cpp-rs](https://github.com/utilityai/llama-cpp-rs) - Rust (more direct bindings): [utilityai/llama-cpp-rs](https://github.com/utilityai/llama-cpp-rs)
- Rust (automated build from crates.io): [ShelbyJenkins/llm_client](https://github.com/ShelbyJenkins/llm_client)
- C#/.NET: [SciSharp/LLamaSharp](https://github.com/SciSharp/LLamaSharp) - C#/.NET: [SciSharp/LLamaSharp](https://github.com/SciSharp/LLamaSharp)
- C#/VB.NET (more features - community license): [LM-Kit.NET](https://docs.lm-kit.com/lm-kit-net/index.html) - C#/VB.NET (more features - community license): [LM-Kit.NET](https://docs.lm-kit.com/lm-kit-net/index.html)
- Scala 3: [donderom/llm4s](https://github.com/donderom/llm4s) - Scala 3: [donderom/llm4s](https://github.com/donderom/llm4s)
@ -132,321 +176,341 @@ Typically finetunes of the base models below are supported as well.
- Zig: [deins/llama.cpp.zig](https://github.com/Deins/llama.cpp.zig) - Zig: [deins/llama.cpp.zig](https://github.com/Deins/llama.cpp.zig)
- Flutter/Dart: [netdur/llama_cpp_dart](https://github.com/netdur/llama_cpp_dart) - Flutter/Dart: [netdur/llama_cpp_dart](https://github.com/netdur/llama_cpp_dart)
- Flutter: [xuegao-tzx/Fllama](https://github.com/xuegao-tzx/Fllama) - Flutter: [xuegao-tzx/Fllama](https://github.com/xuegao-tzx/Fllama)
- PHP (API bindings and features built on top of llama.cpp): [distantmagic/resonance](https://github.com/distantmagic/resonance) [(more info)](https://github.com/ggerganov/llama.cpp/pull/6326) - PHP (API bindings and features built on top of llama.cpp): [distantmagic/resonance](https://github.com/distantmagic/resonance) [(more info)](https://github.com/ggml-org/llama.cpp/pull/6326)
- Guile Scheme: [guile_llama_cpp](https://savannah.nongnu.org/projects/guile-llama-cpp) - Guile Scheme: [guile_llama_cpp](https://savannah.nongnu.org/projects/guile-llama-cpp)
- Swift [srgtuszy/llama-cpp-swift](https://github.com/srgtuszy/llama-cpp-swift) - Swift [srgtuszy/llama-cpp-swift](https://github.com/srgtuszy/llama-cpp-swift)
- Swift [ShenghaiWang/SwiftLlama](https://github.com/ShenghaiWang/SwiftLlama) - Swift [ShenghaiWang/SwiftLlama](https://github.com/ShenghaiWang/SwiftLlama)
- Delphi [Embarcadero/llama-cpp-delphi](https://github.com/Embarcadero/llama-cpp-delphi)
**UI:** </details>
Unless otherwise noted these projects are open-source with permissive licensing: <details>
<summary>UIs</summary>
- [MindWorkAI/AI-Studio](https://github.com/MindWorkAI/AI-Studio) (FSL-1.1-MIT)
- [iohub/collama](https://github.com/iohub/coLLaMA)
- [janhq/jan](https://github.com/janhq/jan) (AGPL)
- [nat/openplayground](https://github.com/nat/openplayground)
- [Faraday](https://faraday.dev/) (proprietary)
- [LMStudio](https://lmstudio.ai/) (proprietary)
- [Layla](https://play.google.com/store/apps/details?id=com.laylalite) (proprietary)
- [ramalama](https://github.com/containers/ramalama) (MIT)
- [LocalAI](https://github.com/mudler/LocalAI) (MIT)
- [LostRuins/koboldcpp](https://github.com/LostRuins/koboldcpp) (AGPL)
- [Mozilla-Ocho/llamafile](https://github.com/Mozilla-Ocho/llamafile)
- [nomic-ai/gpt4all](https://github.com/nomic-ai/gpt4all)
- [ollama/ollama](https://github.com/ollama/ollama)
- [oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui) (AGPL)
- [psugihara/FreeChat](https://github.com/psugihara/FreeChat)
- [cztomsik/ava](https://github.com/cztomsik/ava) (MIT)
- [ptsochantaris/emeltal](https://github.com/ptsochantaris/emeltal)
- [pythops/tenere](https://github.com/pythops/tenere) (AGPL)
- [RAGNA Desktop](https://ragna.app/) (proprietary)
- [RecurseChat](https://recurse.chat/) (proprietary)
- [semperai/amica](https://github.com/semperai/amica)
- [withcatai/catai](https://github.com/withcatai/catai)
- [Mobile-Artificial-Intelligence/maid](https://github.com/Mobile-Artificial-Intelligence/maid) (MIT)
- [Msty](https://msty.app) (proprietary)
- [LLMFarm](https://github.com/guinmoon/LLMFarm?tab=readme-ov-file) (MIT)
- [KanTV](https://github.com/zhouwg/kantv?tab=readme-ov-file)(Apachev2.0 or later)
- [Dot](https://github.com/alexpinel/Dot) (GPL)
- [MindMac](https://mindmac.app) (proprietary)
- [KodiBot](https://github.com/firatkiral/kodibot) (GPL)
- [eva](https://github.com/ylsdamxssjxxdd/eva) (MIT)
- [AI Sublime Text plugin](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (MIT)
- [AIKit](https://github.com/sozercan/aikit) (MIT)
- [LARS - The LLM & Advanced Referencing Solution](https://github.com/abgulati/LARS) (AGPL)
- [LLMUnity](https://github.com/undreamai/LLMUnity) (MIT)
- [Llama Assistant](https://github.com/vietanhdev/llama-assistant) (GPL)
- [PocketPal AI - An iOS and Android App](https://github.com/a-ghorbani/pocketpal-ai) (MIT)
*(to have a project listed here, it should clearly state that it depends on `llama.cpp`)* *(to have a project listed here, it should clearly state that it depends on `llama.cpp`)*
**Tools:** - [AI Sublime Text plugin](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (MIT)
- [cztomsik/ava](https://github.com/cztomsik/ava) (MIT)
- [Dot](https://github.com/alexpinel/Dot) (GPL)
- [eva](https://github.com/ylsdamxssjxxdd/eva) (MIT)
- [iohub/collama](https://github.com/iohub/coLLaMA) (Apache-2.0)
- [janhq/jan](https://github.com/janhq/jan) (AGPL)
- [johnbean393/Sidekick](https://github.com/johnbean393/Sidekick) (MIT)
- [KanTV](https://github.com/zhouwg/kantv?tab=readme-ov-file) (Apache-2.0)
- [KodiBot](https://github.com/firatkiral/kodibot) (GPL)
- [llama.vim](https://github.com/ggml-org/llama.vim) (MIT)
- [LARS](https://github.com/abgulati/LARS) (AGPL)
- [Llama Assistant](https://github.com/vietanhdev/llama-assistant) (GPL)
- [LLMFarm](https://github.com/guinmoon/LLMFarm?tab=readme-ov-file) (MIT)
- [LLMUnity](https://github.com/undreamai/LLMUnity) (MIT)
- [LMStudio](https://lmstudio.ai/) (proprietary)
- [LocalAI](https://github.com/mudler/LocalAI) (MIT)
- [LostRuins/koboldcpp](https://github.com/LostRuins/koboldcpp) (AGPL)
- [MindMac](https://mindmac.app) (proprietary)
- [MindWorkAI/AI-Studio](https://github.com/MindWorkAI/AI-Studio) (FSL-1.1-MIT)
- [Mobile-Artificial-Intelligence/maid](https://github.com/Mobile-Artificial-Intelligence/maid) (MIT)
- [Mozilla-Ocho/llamafile](https://github.com/Mozilla-Ocho/llamafile) (Apache-2.0)
- [nat/openplayground](https://github.com/nat/openplayground) (MIT)
- [nomic-ai/gpt4all](https://github.com/nomic-ai/gpt4all) (MIT)
- [ollama/ollama](https://github.com/ollama/ollama) (MIT)
- [oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui) (AGPL)
- [PocketPal AI](https://github.com/a-ghorbani/pocketpal-ai) (MIT)
- [psugihara/FreeChat](https://github.com/psugihara/FreeChat) (MIT)
- [ptsochantaris/emeltal](https://github.com/ptsochantaris/emeltal) (MIT)
- [pythops/tenere](https://github.com/pythops/tenere) (AGPL)
- [ramalama](https://github.com/containers/ramalama) (MIT)
- [semperai/amica](https://github.com/semperai/amica) (MIT)
- [withcatai/catai](https://github.com/withcatai/catai) (MIT)
- [Autopen](https://github.com/blackhole89/autopen) (GPL)
</details>
<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 HuggingFace 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 - [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 - [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 - [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
- [Styled Lines](https://marketplace.unity.com/packages/tools/generative-ai/styled-lines-llama-cpp-model-292902) (proprietary licensed, async wrapper of inference part for game development in Unity3d with prebuild Mobile and Web platform wrappers and a model example) - [Styled Lines](https://marketplace.unity.com/packages/tools/generative-ai/styled-lines-llama-cpp-model-292902) (proprietary licensed, async wrapper of inference part for game development in Unity3d with pre-built Mobile and Web platform wrappers and a model example)
**Infrastructure:** </details>
<details>
<summary>Infrastructure</summary>
- [Paddler](https://github.com/distantmagic/paddler) - Stateful load balancer custom-tailored for llama.cpp - [Paddler](https://github.com/distantmagic/paddler) - Stateful load balancer custom-tailored for llama.cpp
- [GPUStack](https://github.com/gpustack/gpustack) - Manage GPU clusters for running LLMs - [GPUStack](https://github.com/gpustack/gpustack) - Manage GPU clusters for running LLMs
- [llama_cpp_canister](https://github.com/onicai/llama_cpp_canister) - llama.cpp as a smart contract on the Internet Computer, using WebAssembly - [llama_cpp_canister](https://github.com/onicai/llama_cpp_canister) - llama.cpp as a smart contract on the Internet Computer, using WebAssembly
- [llama-swap](https://github.com/mostlygeek/llama-swap) - transparent proxy that adds automatic model switching with llama-server
- [Kalavai](https://github.com/kalavai-net/kalavai-client) - Crowdsource end to end LLM deployment at any scale
- [llmaz](https://github.com/InftyAI/llmaz) - ☸️ Easy, advanced inference platform for large language models on Kubernetes.
</details>
<details>
<summary>Games</summary>
**Games:**
- [Lucy's Labyrinth](https://github.com/MorganRO8/Lucys_Labyrinth) - A simple maze game where agents controlled by an AI model will try to trick you. - [Lucy's Labyrinth](https://github.com/MorganRO8/Lucys_Labyrinth) - A simple maze game where agents controlled by an AI model will try to trick you.
## Demo
<details>
<summary>Typical run using LLaMA v2 13B on M2 Ultra</summary>
```
$ make -j && ./llama-cli -m models/llama-13b-v2/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e
I llama.cpp build info:
I UNAME_S: Darwin
I UNAME_P: arm
I UNAME_M: arm64
I CFLAGS: -I. -O3 -std=c11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -Wmissing-prototypes -pthread -DGGML_USE_K_QUANTS -DGGML_USE_ACCELERATE
I CXXFLAGS: -I. -I./common -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -DGGML_USE_K_QUANTS
I LDFLAGS: -framework Accelerate
I CC: Apple clang version 14.0.3 (clang-1403.0.22.14.1)
I CXX: Apple clang version 14.0.3 (clang-1403.0.22.14.1)
make: Nothing to be done for `default'.
main: build = 1041 (cf658ad)
main: seed = 1692823051
llama_model_loader: loaded meta data with 16 key-value pairs and 363 tensors from models/llama-13b-v2/ggml-model-q4_0.gguf (version GGUF V1 (latest))
llama_model_loader: - type f32: 81 tensors
llama_model_loader: - type q4_0: 281 tensors
llama_model_loader: - type q6_K: 1 tensors
llm_load_print_meta: format = GGUF V1 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 32000
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 4096
llm_load_print_meta: n_ctx = 512
llm_load_print_meta: n_embd = 5120
llm_load_print_meta: n_head = 40
llm_load_print_meta: n_head_kv = 40
llm_load_print_meta: n_layer = 40
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_gqa = 1
llm_load_print_meta: f_norm_eps = 1.0e-05
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
llm_load_print_meta: n_ff = 13824
llm_load_print_meta: freq_base = 10000.0
llm_load_print_meta: freq_scale = 1
llm_load_print_meta: model type = 13B
llm_load_print_meta: model ftype = mostly Q4_0
llm_load_print_meta: model size = 13.02 B
llm_load_print_meta: general.name = LLaMA v2
llm_load_print_meta: BOS token = 1 '<s>'
llm_load_print_meta: EOS token = 2 '</s>'
llm_load_print_meta: UNK token = 0 '<unk>'
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.11 MB
llm_load_tensors: mem required = 7024.01 MB (+ 400.00 MB per state)
...................................................................................................
llama_new_context_with_model: kv self size = 400.00 MB
llama_new_context_with_model: compute buffer total size = 75.41 MB
system_info: n_threads = 16 / 24 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | VSX = 0 |
sampling: repeat_last_n = 64, repeat_penalty = 1.100000, presence_penalty = 0.000000, frequency_penalty = 0.000000, top_k = 40, tfs_z = 1.000000, top_p = 0.950000, typical_p = 1.000000, temp = 0.800000, mirostat = 0, mirostat_lr = 0.100000, mirostat_ent = 5.000000
generate: n_ctx = 512, n_batch = 512, n_predict = 400, n_keep = 0
Building a website can be done in 10 simple steps:
Step 1: Find the right website platform.
Step 2: Choose your domain name and hosting plan.
Step 3: Design your website layout.
Step 4: Write your website content and add images.
Step 5: Install security features to protect your site from hackers or spammers
Step 6: Test your website on multiple browsers, mobile devices, operating systems etc…
Step 7: Test it again with people who are not related to you personally friends or family members will work just fine!
Step 8: Start marketing and promoting the website via social media channels or paid ads
Step 9: Analyze how many visitors have come to your site so far, what type of people visit more often than others (e.g., men vs women) etc…
Step 10: Continue to improve upon all aspects mentioned above by following trends in web design and staying up-to-date on new technologies that can enhance user experience even further!
How does a Website Work?
A website works by having pages, which are made of HTML code. This code tells your computer how to display the content on each page you visit whether its an image or text file (like PDFs). In order for someone elses browser not only be able but also want those same results when accessing any given URL; some additional steps need taken by way of programming scripts that will add functionality such as making links clickable!
The most common type is called static HTML pages because they remain unchanged over time unless modified manually (either through editing files directly or using an interface such as WordPress). They are usually served up via HTTP protocols this means anyone can access them without having any special privileges like being part of a group who is allowed into restricted areas online; however, there may still exist some limitations depending upon where one lives geographically speaking.
How to
llama_print_timings: load time = 576.45 ms
llama_print_timings: sample time = 283.10 ms / 400 runs ( 0.71 ms per token, 1412.91 tokens per second)
llama_print_timings: prompt eval time = 599.83 ms / 19 tokens ( 31.57 ms per token, 31.68 tokens per second)
llama_print_timings: eval time = 24513.59 ms / 399 runs ( 61.44 ms per token, 16.28 tokens per second)
llama_print_timings: total time = 25431.49 ms
```
</details> </details>
<details>
<summary>Demo of running both LLaMA-7B and whisper.cpp on a single M1 Pro MacBook</summary>
And here is another demo of running both LLaMA-7B and [whisper.cpp](https://github.com/ggerganov/whisper.cpp) on a single M1 Pro MacBook:
https://user-images.githubusercontent.com/1991296/224442907-7693d4be-acaa-4e01-8b4f-add84093ffff.mp4
</details>
## Usage
Here are the end-to-end binary build and model conversion steps for most supported models.
### Basic usage
Firstly, you need to get the binary. There are different methods that you can follow:
- Method 1: Clone this repository and build locally, see [how to build](./docs/build.md)
- Method 2: If you are using MacOS or Linux, you can install llama.cpp via [brew, flox or nix](./docs/install.md)
- Method 3: Use a Docker image, see [documentation for Docker](./docs/docker.md)
- Method 4: Download pre-built binary from [releases](https://github.com/ggerganov/llama.cpp/releases)
You can run a basic completion using this command:
```bash
llama-cli -m your_model.gguf -p "I believe the meaning of life is" -n 128
# Output:
# I believe the meaning of life is to find your own truth and to live in accordance with it. For me, this means being true to myself and following my passions, even if they don't align with societal expectations. I think that's what I love about yoga it's not just a physical practice, but a spiritual one too. It's about connecting with yourself, listening to your inner voice, and honoring your own unique journey.
```
See [this page](./examples/main/README.md) for a full list of parameters.
### Conversation mode
If you want a more ChatGPT-like experience, you can run in conversation mode by passing `-cnv` as a parameter:
```bash
llama-cli -m your_model.gguf -p "You are a helpful assistant" -cnv
# Output:
# > hi, who are you?
# Hi there! I'm your helpful assistant! I'm an AI-powered chatbot designed to assist and provide information to users like you. I'm here to help answer your questions, provide guidance, and offer support on a wide range of topics. I'm a friendly and knowledgeable AI, and I'm always happy to help with anything you need. What's on your mind, and how can I assist you today?
#
# > what is 1+1?
# Easy peasy! The answer to 1+1 is... 2!
```
By default, the chat template will be taken from the input model. If you want to use another chat template, pass `--chat-template NAME` as a parameter. See the list of [supported templates](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template)
```bash
./llama-cli -m your_model.gguf -p "You are a helpful assistant" -cnv --chat-template chatml
```
You can also use your own template via in-prefix, in-suffix and reverse-prompt parameters:
```bash
./llama-cli -m your_model.gguf -p "You are a helpful assistant" -cnv --in-prefix 'User: ' --reverse-prompt 'User:'
```
### Web server
[llama.cpp web server](./examples/server/README.md) is a lightweight [OpenAI API](https://github.com/openai/openai-openapi) compatible HTTP server that can be used to serve local models and easily connect them to existing clients.
Example usage:
```bash
./llama-server -m your_model.gguf --port 8080
# Basic web UI can be accessed via browser: http://localhost:8080
# Chat completion endpoint: http://localhost:8080/v1/chat/completions
```
### Interactive mode
> [!NOTE]
> If you prefer basic usage, please consider using conversation mode instead of interactive mode
In this mode, you can always interrupt generation by pressing Ctrl+C and entering one or more lines of text, which will be converted into tokens and appended to the current context. You can also specify a *reverse prompt* with the parameter `-r "reverse prompt string"`. This will result in user input being prompted whenever the exact tokens of the reverse prompt string are encountered in the generation. A typical use is to use a prompt that makes LLaMA emulate a chat between multiple users, say Alice and Bob, and pass `-r "Alice:"`.
Here is an example of a few-shot interaction, invoked with the command
```bash
# default arguments using a 7B model
./examples/chat.sh
# advanced chat with a 13B model
./examples/chat-13B.sh
# custom arguments using a 13B model
./llama-cli -m ./models/13B/ggml-model-q4_0.gguf -n 256 --repeat_penalty 1.0 --color -i -r "User:" -f prompts/chat-with-bob.txt
```
Note the use of `--color` to distinguish between user input and generated text. Other parameters are explained in more detail in the [README](examples/main/README.md) for the `llama-cli` example program.
![image](https://user-images.githubusercontent.com/1991296/224575029-2af3c7dc-5a65-4f64-a6bb-517a532aea38.png)
### Persistent Interaction
The prompt, user inputs, and model generations can be saved and resumed across calls to `./llama-cli` by leveraging `--prompt-cache` and `--prompt-cache-all`. The `./examples/chat-persistent.sh` script demonstrates this with support for long-running, resumable chat sessions. To use this example, you must provide a file to cache the initial chat prompt and a directory to save the chat session, and may optionally provide the same variables as `chat-13B.sh`. The same prompt cache can be reused for new chat sessions. Note that both prompt cache and chat directory are tied to the initial prompt (`PROMPT_TEMPLATE`) and the model file.
```bash
# Start a new chat
PROMPT_CACHE_FILE=chat.prompt.bin CHAT_SAVE_DIR=./chat/default ./examples/chat-persistent.sh
# Resume that chat
PROMPT_CACHE_FILE=chat.prompt.bin CHAT_SAVE_DIR=./chat/default ./examples/chat-persistent.sh
# Start a different chat with the same prompt/model
PROMPT_CACHE_FILE=chat.prompt.bin CHAT_SAVE_DIR=./chat/another ./examples/chat-persistent.sh
# Different prompt cache for different prompt/model
PROMPT_TEMPLATE=./prompts/chat-with-bob.txt PROMPT_CACHE_FILE=bob.prompt.bin \
CHAT_SAVE_DIR=./chat/bob ./examples/chat-persistent.sh
```
### Constrained output with grammars
`llama.cpp` supports grammars to constrain model output. For example, you can force the model to output JSON only:
```bash
./llama-cli -m ./models/13B/ggml-model-q4_0.gguf -n 256 --grammar-file grammars/json.gbnf -p 'Request: schedule a call at 8pm; Command:'
```
The `grammars/` folder contains a handful of sample grammars. To write your own, check out the [GBNF Guide](./grammars/README.md).
For authoring more complex JSON grammars, you can also check out https://grammar.intrinsiclabs.ai/, a browser app that lets you write TypeScript interfaces which it compiles to GBNF grammars that you can save for local use. Note that the app is built and maintained by members of the community, please file any issues or FRs on [its repo](http://github.com/intrinsiclabsai/gbnfgen) and not this one.
## Build
Please refer to [Build llama.cpp locally](./docs/build.md)
## Supported backends ## Supported backends
| Backend | Target devices | | Backend | Target devices |
| --- | --- | | --- | --- |
| [Metal](./docs/build.md#metal-build) | Apple Silicon | | [Metal](docs/build.md#metal-build) | Apple Silicon |
| [BLAS](./docs/build.md#blas-build) | All | | [BLAS](docs/build.md#blas-build) | All |
| [BLIS](./docs/backend/BLIS.md) | All | | [BLIS](docs/backend/BLIS.md) | All |
| [SYCL](./docs/backend/SYCL.md) | Intel and Nvidia GPU | | [SYCL](docs/backend/SYCL.md) | Intel and Nvidia GPU |
| [MUSA](./docs/build.md#musa) | Moore Threads MTT GPU | | [MUSA](docs/build.md#musa) | Moore Threads GPU |
| [CUDA](./docs/build.md#cuda) | Nvidia GPU | | [CUDA](docs/build.md#cuda) | Nvidia GPU |
| [hipBLAS](./docs/build.md#hipblas) | AMD GPU | | [HIP](docs/build.md#hip) | AMD GPU |
| [Vulkan](./docs/build.md#vulkan) | GPU | | [Vulkan](docs/build.md#vulkan) | GPU |
| [CANN](./docs/build.md#cann) | Ascend NPU | | [CANN](docs/build.md#cann) | Ascend NPU |
| [OpenCL](docs/backend/OPENCL.md) | Adreno GPU |
| [RPC](https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc) | All |
## Tools ## Obtaining and quantizing models
### Prepare and Quantize The [Hugging Face](https://huggingface.co) platform hosts a [number of LLMs](https://huggingface.co/models?library=gguf&sort=trending) compatible with `llama.cpp`:
> [!NOTE] - [Trending](https://huggingface.co/models?library=gguf&sort=trending)
> You can use the [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space on Hugging Face to quantise your model weights without any setup too. It is synced from `llama.cpp` main every 6 hours. - [LLaMA](https://huggingface.co/models?sort=trending&search=llama+gguf)
To obtain the official LLaMA 2 weights please see the <a href="#obtaining-and-using-the-facebook-llama-2-model">Obtaining and using the Facebook LLaMA 2 model</a> section. There is also a large selection of pre-quantized `gguf` models available on Hugging Face. 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:
Note: `convert.py` has been moved to `examples/convert_legacy_llama.py` and shouldn't be used for anything other than `Llama/Llama2/Mistral` models and their derivatives. ```sh
It does not support LLaMA 3, you can use `convert_hf_to_gguf.py` with LLaMA 3 downloaded from Hugging Face. llama-cli -hf ggml-org/gemma-3-1b-it-GGUF
```
To learn more about quantizing model, [read this documentation](./examples/quantize/README.md) 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/`.
### Perplexity (measuring model quality) After downloading a model, use the CLI tools to run it locally - see below.
You can use the `perplexity` example to measure perplexity over a given prompt (lower perplexity is better). `llama.cpp` requires the model to be stored in the [GGUF](https://github.com/ggml-org/ggml/blob/master/docs/gguf.md) file format. Models in other data formats can be converted to GGUF using the `convert_*.py` Python scripts in this repo.
For more information, see [https://huggingface.co/docs/transformers/perplexity](https://huggingface.co/docs/transformers/perplexity).
The Hugging Face platform provides a variety of online tools for converting, quantizing and hosting models with `llama.cpp`:
- Use the [GGUF-my-repo space](https://huggingface.co/spaces/ggml-org/gguf-my-repo) to convert to GGUF format and quantize model weights to smaller sizes
- Use the [GGUF-my-LoRA space](https://huggingface.co/spaces/ggml-org/gguf-my-lora) to convert LoRA adapters to GGUF format (more info: https://github.com/ggml-org/llama.cpp/discussions/10123)
- Use the [GGUF-editor space](https://huggingface.co/spaces/CISCai/gguf-editor) to edit GGUF meta data in the browser (more info: https://github.com/ggml-org/llama.cpp/discussions/9268)
- Use the [Inference Endpoints](https://ui.endpoints.huggingface.co/) to directly host `llama.cpp` in the cloud (more info: https://github.com/ggml-org/llama.cpp/discussions/9669)
To learn more about model quantization, [read this documentation](tools/quantize/README.md)
## [`llama-cli`](tools/main)
#### A CLI tool for accessing and experimenting with most of `llama.cpp`'s functionality.
- <details open>
<summary>Run in conversation mode</summary>
Models with a built-in chat template will automatically activate conversation mode. If this doesn't occur, you can manually enable it by adding `-cnv` and specifying a suitable chat template with `--chat-template NAME`
```bash
llama-cli -m model.gguf
# > hi, who are you?
# Hi there! I'm your helpful assistant! I'm an AI-powered chatbot designed to assist and provide information to users like you. I'm here to help answer your questions, provide guidance, and offer support on a wide range of topics. I'm a friendly and knowledgeable AI, and I'm always happy to help with anything you need. What's on your mind, and how can I assist you today?
#
# > what is 1+1?
# Easy peasy! The answer to 1+1 is... 2!
```
</details>
- <details>
<summary>Run in conversation mode with custom chat template</summary>
```bash
# use the "chatml" template (use -h to see the list of supported templates)
llama-cli -m model.gguf -cnv --chat-template chatml
# use a custom template
llama-cli -m model.gguf -cnv --in-prefix 'User: ' --reverse-prompt 'User:'
```
</details>
- <details>
<summary>Run simple text completion</summary>
To disable conversation mode explicitly, use `-no-cnv`
```bash
llama-cli -m model.gguf -p "I believe the meaning of life is" -n 128 -no-cnv
# I believe the meaning of life is to find your own truth and to live in accordance with it. For me, this means being true to myself and following my passions, even if they don't align with societal expectations. I think that's what I love about yoga it's not just a physical practice, but a spiritual one too. It's about connecting with yourself, listening to your inner voice, and honoring your own unique journey.
```
</details>
- <details>
<summary>Constrain the output with a custom grammar</summary>
```bash
llama-cli -m model.gguf -n 256 --grammar-file grammars/json.gbnf -p 'Request: schedule a call at 8pm; Command:'
# {"appointmentTime": "8pm", "appointmentDetails": "schedule a a call"}
```
The [grammars/](grammars/) folder contains a handful of sample grammars. To write your own, check out the [GBNF Guide](grammars/README.md).
For authoring more complex JSON grammars, check out https://grammar.intrinsiclabs.ai/
</details>
## [`llama-server`](tools/server)
#### A lightweight, [OpenAI API](https://github.com/openai/openai-openapi) compatible, HTTP server for serving LLMs.
- <details open>
<summary>Start a local HTTP server with default configuration on port 8080</summary>
```bash
llama-server -m model.gguf --port 8080
# Basic web UI can be accessed via browser: http://localhost:8080
# Chat completion endpoint: http://localhost:8080/v1/chat/completions
```
</details>
- <details>
<summary>Support multiple-users and parallel decoding</summary>
```bash
# up to 4 concurrent requests, each with 4096 max context
llama-server -m model.gguf -c 16384 -np 4
```
</details>
- <details>
<summary>Enable speculative decoding</summary>
```bash
# the draft.gguf model should be a small variant of the target model.gguf
llama-server -m model.gguf -md draft.gguf
```
</details>
- <details>
<summary>Serve an embedding model</summary>
```bash
# use the /embedding endpoint
llama-server -m model.gguf --embedding --pooling cls -ub 8192
```
</details>
- <details>
<summary>Serve a reranking model</summary>
```bash
# use the /reranking endpoint
llama-server -m model.gguf --reranking
```
</details>
- <details>
<summary>Constrain all outputs with a grammar</summary>
```bash
# custom grammar
llama-server -m model.gguf --grammar-file grammar.gbnf
# JSON
llama-server -m model.gguf --grammar-file grammars/json.gbnf
```
</details>
## [`llama-perplexity`](tools/perplexity)
#### A tool for measuring the perplexity [^1][^2] (and other quality metrics) of a model over a given text.
- <details open>
<summary>Measure the perplexity over a text file</summary>
```bash
llama-perplexity -m model.gguf -f file.txt
# [1]15.2701,[2]5.4007,[3]5.3073,[4]6.2965,[5]5.8940,[6]5.6096,[7]5.7942,[8]4.9297, ...
# Final estimate: PPL = 5.4007 +/- 0.67339
```
</details>
- <details>
<summary>Measure KL divergence</summary>
```bash
# TODO
```
</details>
[^1]: [tools/perplexity/README.md](./tools/perplexity/README.md)
[^2]: [https://huggingface.co/docs/transformers/perplexity](https://huggingface.co/docs/transformers/perplexity)
## [`llama-bench`](tools/llama-bench)
#### Benchmark the performance of the inference for various parameters.
- <details open>
<summary>Run default benchmark</summary>
```bash
llama-bench -m model.gguf
# Output:
# | model | size | params | backend | threads | test | t/s |
# | ------------------- | ---------: | ---------: | ---------- | ------: | ------------: | -------------------: |
# | qwen2 1.5B Q4_0 | 885.97 MiB | 1.54 B | Metal,BLAS | 16 | pp512 | 5765.41 ± 20.55 |
# | qwen2 1.5B Q4_0 | 885.97 MiB | 1.54 B | Metal,BLAS | 16 | tg128 | 197.71 ± 0.81 |
#
# build: 3e0ba0e60 (4229)
```
</details>
## [`llama-run`](tools/run)
#### A comprehensive example for running `llama.cpp` models. Useful for inferencing. Used with RamaLama [^3].
- <details>
<summary>Run a model with a specific prompt (by default it's pulled from Ollama registry)</summary>
```bash
llama-run granite-code
```
</details>
[^3]: [RamaLama](https://github.com/containers/ramalama)
## [`llama-simple`](examples/simple)
#### A minimal example for implementing apps with `llama.cpp`. Useful for developers.
- <details>
<summary>Basic text completion</summary>
```bash
llama-simple -m model.gguf
# Hello my name is Kaitlyn and I am a 16 year old girl. I am a junior in high school and I am currently taking a class called "The Art of
```
</details>
To learn more how to measure perplexity using llama.cpp, [read this documentation](./examples/perplexity/README.md)
## Contributing ## Contributing
@ -454,27 +518,26 @@ To learn more how to measure perplexity using llama.cpp, [read this documentatio
- Collaborators can push to branches in the `llama.cpp` repo and merge PRs into the `master` branch - Collaborators can push to branches in the `llama.cpp` repo and merge PRs into the `master` branch
- Collaborators will be invited based on contributions - Collaborators will be invited based on contributions
- Any help with managing issues, PRs and projects is very appreciated! - Any help with managing issues, PRs and projects is very appreciated!
- See [good first issues](https://github.com/ggerganov/llama.cpp/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) for tasks suitable for first contributions - See [good first issues](https://github.com/ggml-org/llama.cpp/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) for tasks suitable for first contributions
- Read the [CONTRIBUTING.md](CONTRIBUTING.md) for more information - Read the [CONTRIBUTING.md](CONTRIBUTING.md) for more information
- Make sure to read this: [Inference at the edge](https://github.com/ggerganov/llama.cpp/discussions/205) - Make sure to read this: [Inference at the edge](https://github.com/ggml-org/llama.cpp/discussions/205)
- A bit of backstory for those who are interested: [Changelog podcast](https://changelog.com/podcast/532) - A bit of backstory for those who are interested: [Changelog podcast](https://changelog.com/podcast/532)
## Other documentation ## Other documentation
- [main (cli)](./examples/main/README.md) - [main (cli)](tools/main/README.md)
- [server](./examples/server/README.md) - [server](tools/server/README.md)
- [jeopardy](./examples/jeopardy/README.md) - [GBNF grammars](grammars/README.md)
- [GBNF grammars](./grammars/README.md)
**Development documentation** #### Development documentation
- [How to build](./docs/build.md) - [How to build](docs/build.md)
- [Running on Docker](./docs/docker.md) - [Running on Docker](docs/docker.md)
- [Build on Android](./docs/android.md) - [Build on Android](docs/android.md)
- [Performance troubleshooting](./docs/development/token_generation_performance_tips.md) - [Performance troubleshooting](docs/development/token_generation_performance_tips.md)
- [GGML tips & tricks](https://github.com/ggerganov/llama.cpp/wiki/GGML-Tips-&-Tricks) - [GGML tips & tricks](https://github.com/ggml-org/llama.cpp/wiki/GGML-Tips-&-Tricks)
**Seminal papers and background on the models** #### Seminal papers and background on the models
If your issue is with model generation quality, then please at least scan the following links and papers to understand the limitations of LLaMA models. This is especially important when choosing an appropriate model size and appreciating both the significant and subtle differences between LLaMA models and ChatGPT: If your issue is with model generation quality, then please at least scan the following links and papers to understand the limitations of LLaMA models. This is especially important when choosing an appropriate model size and appreciating both the significant and subtle differences between LLaMA models and ChatGPT:
- LLaMA: - LLaMA:
@ -485,3 +548,56 @@ If your issue is with model generation quality, then please at least scan the fo
- GPT-3.5 / InstructGPT / ChatGPT: - GPT-3.5 / InstructGPT / ChatGPT:
- [Aligning language models to follow instructions](https://openai.com/research/instruction-following) - [Aligning language models to follow instructions](https://openai.com/research/instruction-following)
- [Training language models to follow instructions with human feedback](https://arxiv.org/abs/2203.02155) - [Training language models to follow instructions with human feedback](https://arxiv.org/abs/2203.02155)
## XCFramework
The XCFramework is a precompiled version of the library for iOS, visionOS, tvOS,
and macOS. It can be used in Swift projects without the need to compile the
library from source. For example:
```swift
// swift-tools-version: 5.10
// The swift-tools-version declares the minimum version of Swift required to build this package.
import PackageDescription
let package = Package(
name: "MyLlamaPackage",
targets: [
.executableTarget(
name: "MyLlamaPackage",
dependencies: [
"LlamaFramework"
]),
.binaryTarget(
name: "LlamaFramework",
url: "https://github.com/ggml-org/llama.cpp/releases/download/b5046/llama-b5046-xcframework.zip",
checksum: "c19be78b5f00d8d29a25da41042cb7afa094cbf6280a225abe614b03b20029ab"
)
]
)
```
The above example is using an intermediate build `b5046` of the library. This can be modified
to use a different version by changing the URL and checksum.
## Completions
Command-line completion is available for some environments.
#### Bash Completion
```bash
$ build/bin/llama-cli --completion-bash > ~/.llama-completion.bash
$ source ~/.llama-completion.bash
```
Optionally this can be added to your `.bashrc` or `.bash_profile` to load it
automatically. For example:
```console
$ echo "source ~/.llama-completion.bash" >> ~/.bashrc
```
## Dependencies
- [yhirose/cpp-httplib](https://github.com/yhirose/cpp-httplib) - Single-header HTTP server, used by `llama-server` - MIT license
- [stb-image](https://github.com/nothings/stb) - Single-header image format decoder, used by multimodal subsystem - Public domain
- [nlohmann/json](https://github.com/nlohmann/json) - Single-header JSON library, used by various tools/examples - MIT License
- [minja](https://github.com/google/minja) - Minimal Jinja parser in C++, used by various tools/examples - MIT License
- [linenoise.cpp](./tools/run/linenoise.cpp/linenoise.cpp) - C++ library that provides readline-like line editing capabilities, used by `llama-run` - BSD 2-Clause License
- [curl](https://curl.se/) - Client-side URL transfer library, used by various tools/examples - [CURL License](https://curl.se/docs/copyright.html)
- [miniaudio.h](https://github.com/mackron/miniaudio) - Single-header audio format decoder, used by multimodal subsystem - Public domain

View File

@ -40,7 +40,8 @@ To protect sensitive data from potential leaks or unauthorized access, it is cru
### Untrusted environments or networks ### Untrusted environments or networks
If you can't run your models in a secure and isolated environment or if it must be exposed to an untrusted network, make sure to take the following security precautions: If you can't run your models in a secure and isolated environment or if it must be exposed to an untrusted network, make sure to take the following security precautions:
* Confirm the hash of any downloaded artifact (e.g. pre-trained model weights) matches a known-good value * Do not use the RPC backend, [rpc-server](https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc) and [llama-server](https://github.com/ggml-org/llama.cpp/tree/master/tools/server) functionality (see https://github.com/ggml-org/llama.cpp/pull/13061).
* Confirm the hash of any downloaded artifact (e.g. pre-trained model weights) matches a known-good value.
* Encrypt your data if sending it over the network. * Encrypt your data if sending it over the network.
### Multi-Tenant environments ### Multi-Tenant environments
@ -62,6 +63,6 @@ Beware that none of the topics under [Using llama.cpp securely](#using-llamacpp-
<!-- normal version --> <!-- normal version -->
However, If you have discovered a security vulnerability in this project, please report it privately. **Do not disclose it as a public issue.** This gives us time to work with you to fix the issue before public exposure, reducing the chance that the exploit will be used before a patch is released. However, If you have discovered a security vulnerability in this project, please report it privately. **Do not disclose it as a public issue.** This gives us time to work with you to fix the issue before public exposure, reducing the chance that the exploit will be used before a patch is released.
Please disclose it as a private [security advisory](https://github.com/ggerganov/llama.cpp/security/advisories/new). Please disclose it as a private [security advisory](https://github.com/ggml-org/llama.cpp/security/advisories/new).
A team of volunteers on a reasonable-effort basis maintains this project. As such, please give us at least 90 days to work on a fix before public exposure. A team of volunteers on a reasonable-effort basis maintains this project. As such, please give us at least 90 days to work on a fix before public exposure.

541
build-xcframework.sh Executable file
View File

@ -0,0 +1,541 @@
#!/usr/bin/env bash
#
# Options
IOS_MIN_OS_VERSION=16.4
MACOS_MIN_OS_VERSION=13.3
VISIONOS_MIN_OS_VERSION=1.0
TVOS_MIN_OS_VERSION=16.4
BUILD_SHARED_LIBS=OFF
LLAMA_BUILD_EXAMPLES=OFF
LLAMA_BUILD_TOOLS=OFF
LLAMA_BUILD_TESTS=OFF
LLAMA_BUILD_SERVER=OFF
GGML_METAL=ON
GGML_METAL_EMBED_LIBRARY=ON
GGML_BLAS_DEFAULT=ON
GGML_METAL_USE_BF16=ON
GGML_OPENMP=OFF
COMMON_C_FLAGS="-Wno-macro-redefined -Wno-shorten-64-to-32 -Wno-unused-command-line-argument -g"
COMMON_CXX_FLAGS="-Wno-macro-redefined -Wno-shorten-64-to-32 -Wno-unused-command-line-argument -g"
# Common options for all builds
COMMON_CMAKE_ARGS=(
-DCMAKE_XCODE_ATTRIBUTE_CODE_SIGNING_REQUIRED=NO
-DCMAKE_XCODE_ATTRIBUTE_CODE_SIGN_IDENTITY=""
-DCMAKE_XCODE_ATTRIBUTE_CODE_SIGNING_ALLOWED=NO
-DCMAKE_XCODE_ATTRIBUTE_DEBUG_INFORMATION_FORMAT="dwarf-with-dsym"
-DCMAKE_XCODE_ATTRIBUTE_GCC_GENERATE_DEBUGGING_SYMBOLS=YES
-DCMAKE_XCODE_ATTRIBUTE_COPY_PHASE_STRIP=NO
-DCMAKE_XCODE_ATTRIBUTE_STRIP_INSTALLED_PRODUCT=NO
-DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
-DBUILD_SHARED_LIBS=${BUILD_SHARED_LIBS}
-DLLAMA_BUILD_EXAMPLES=${LLAMA_BUILD_EXAMPLES}
-DLLAMA_BUILD_TOOLS=${LLAMA_BUILD_TOOLS}
-DLLAMA_BUILD_TESTS=${LLAMA_BUILD_TESTS}
-DLLAMA_BUILD_SERVER=${LLAMA_BUILD_SERVER}
-DGGML_METAL_EMBED_LIBRARY=${GGML_METAL_EMBED_LIBRARY}
-DGGML_BLAS_DEFAULT=${GGML_BLAS_DEFAULT}
-DGGML_METAL=${GGML_METAL}
-DGGML_METAL_USE_BF16=${GGML_METAL_USE_BF16}
-DGGML_NATIVE=OFF
-DGGML_OPENMP=${GGML_OPENMP}
)
XCODE_VERSION=$(xcodebuild -version 2>/dev/null | head -n1 | awk '{ print $2 }')
MAJOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f1)
MINOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f2)
echo "Detected Xcode version: $XCODE_VERSION"
check_required_tool() {
local tool=$1
local install_message=$2
if ! command -v $tool &> /dev/null; then
echo "Error: $tool is required but not found."
echo "$install_message"
exit 1
fi
}
echo "Checking for required tools..."
check_required_tool "cmake" "Please install CMake 3.28.0 or later (brew install cmake)"
check_required_tool "xcodebuild" "Please install Xcode and Xcode Command Line Tools (xcode-select --install)"
check_required_tool "libtool" "Please install libtool which should be available with Xcode Command Line Tools (CLT). Make sure Xcode CLT is installed (xcode-select --install)"
check_required_tool "dsymutil" "Please install Xcode and Xcode Command Line Tools (xcode-select --install)"
set -e
## Clean up previous builds
rm -rf build-apple
rm -rf build-ios-sim
rm -rf build-ios-device
rm -rf build-macos
rm -rf build-visionos
rm -rf build-visionos-sim
rm -rf build-tvos-sim
rm -rf build-tvos-device
# Setup the xcframework build directory structure
setup_framework_structure() {
local build_dir=$1
local min_os_version=$2
local platform=$3 # "ios", "macos", "visionos", or "tvos"
local framework_name="llama"
echo "Creating ${platform}-style framework structure for ${build_dir}"
if [[ "$platform" == "macos" ]]; then
# macOS versioned structure uses versioned directories
mkdir -p ${build_dir}/framework/${framework_name}.framework/Versions/A/Headers
mkdir -p ${build_dir}/framework/${framework_name}.framework/Versions/A/Modules
mkdir -p ${build_dir}/framework/${framework_name}.framework/Versions/A/Resources
# Create symbolic links
ln -sf A ${build_dir}/framework/${framework_name}.framework/Versions/Current
ln -sf Versions/Current/Headers ${build_dir}/framework/${framework_name}.framework/Headers
ln -sf Versions/Current/Modules ${build_dir}/framework/${framework_name}.framework/Modules
ln -sf Versions/Current/Resources ${build_dir}/framework/${framework_name}.framework/Resources
ln -sf Versions/Current/${framework_name} ${build_dir}/framework/${framework_name}.framework/${framework_name}
# Set header and module paths
local header_path=${build_dir}/framework/${framework_name}.framework/Versions/A/Headers/
local module_path=${build_dir}/framework/${framework_name}.framework/Versions/A/Modules/
else
# iOS/VisionOS/tvOS use a flat structure
mkdir -p ${build_dir}/framework/${framework_name}.framework/Headers
mkdir -p ${build_dir}/framework/${framework_name}.framework/Modules
# Remove any existing structure to ensure clean build
rm -rf ${build_dir}/framework/${framework_name}.framework/Versions
# Set header and module paths
local header_path=${build_dir}/framework/${framework_name}.framework/Headers/
local module_path=${build_dir}/framework/${framework_name}.framework/Modules/
fi
# Copy all required headers (common for all platforms)
cp include/llama.h ${header_path}
cp ggml/include/ggml.h ${header_path}
cp ggml/include/ggml-opt.h ${header_path}
cp ggml/include/ggml-alloc.h ${header_path}
cp ggml/include/ggml-backend.h ${header_path}
cp ggml/include/ggml-metal.h ${header_path}
cp ggml/include/ggml-cpu.h ${header_path}
cp ggml/include/ggml-blas.h ${header_path}
cp ggml/include/gguf.h ${header_path}
# Create module map (common for all platforms)
cat > ${module_path}module.modulemap << EOF
framework module llama {
header "llama.h"
header "ggml.h"
header "ggml-alloc.h"
header "ggml-backend.h"
header "ggml-metal.h"
header "ggml-cpu.h"
header "ggml-blas.h"
header "gguf.h"
link "c++"
link framework "Accelerate"
link framework "Metal"
link framework "Foundation"
export *
}
EOF
# Platform-specific settings for Info.plist
local platform_name=""
local sdk_name=""
local supported_platform=""
case "$platform" in
"ios")
platform_name="iphoneos"
sdk_name="iphoneos${min_os_version}"
supported_platform="iPhoneOS"
local plist_path="${build_dir}/framework/${framework_name}.framework/Info.plist"
local device_family=' <key>UIDeviceFamily</key>
<array>
<integer>1</integer>
<integer>2</integer>
</array>'
;;
"macos")
platform_name="macosx"
sdk_name="macosx${min_os_version}"
supported_platform="MacOSX"
local plist_path="${build_dir}/framework/${framework_name}.framework/Versions/A/Resources/Info.plist"
local device_family=""
;;
"visionos")
platform_name="xros"
sdk_name="xros${min_os_version}"
supported_platform="XRPlatform"
local plist_path="${build_dir}/framework/${framework_name}.framework/Info.plist"
local device_family=""
;;
"tvos")
platform_name="appletvos"
sdk_name="appletvos${min_os_version}"
supported_platform="AppleTVOS"
local plist_path="${build_dir}/framework/${framework_name}.framework/Info.plist"
local device_family=' <key>UIDeviceFamily</key>
<array>
<integer>3</integer>
</array>'
;;
esac
# Create Info.plist
cat > ${plist_path} << EOF
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>en</string>
<key>CFBundleExecutable</key>
<string>llama</string>
<key>CFBundleIdentifier</key>
<string>org.ggml.llama</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>llama</string>
<key>CFBundlePackageType</key>
<string>FMWK</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleVersion</key>
<string>1</string>
<key>MinimumOSVersion</key>
<string>${min_os_version}</string>
<key>CFBundleSupportedPlatforms</key>
<array>
<string>${supported_platform}</string>
</array>${device_family}
<key>DTPlatformName</key>
<string>${platform_name}</string>
<key>DTSDKName</key>
<string>${sdk_name}</string>
</dict>
</plist>
EOF
}
# Create dynamic libraries from static libraries.
combine_static_libraries() {
local build_dir="$1"
local release_dir="$2"
local platform="$3" # "ios", "macos", "visionos", or "tvos"
local is_simulator="$4"
local base_dir="$(pwd)"
local framework_name="llama"
# Determine output path based on platform
local output_lib=""
if [[ "$platform" == "macos" ]]; then
# macOS uses versioned structure
output_lib="${build_dir}/framework/${framework_name}.framework/Versions/A/${framework_name}"
else
# iOS, visionOS, and tvOS use a directory flat structure
output_lib="${build_dir}/framework/${framework_name}.framework/${framework_name}"
fi
local libs=(
"${base_dir}/${build_dir}/src/${release_dir}/libllama.a"
"${base_dir}/${build_dir}/ggml/src/${release_dir}/libggml.a"
"${base_dir}/${build_dir}/ggml/src/${release_dir}/libggml-base.a"
"${base_dir}/${build_dir}/ggml/src/${release_dir}/libggml-cpu.a"
"${base_dir}/${build_dir}/ggml/src/ggml-metal/${release_dir}/libggml-metal.a"
"${base_dir}/${build_dir}/ggml/src/ggml-blas/${release_dir}/libggml-blas.a"
)
# Create temporary directory for processing
local temp_dir="${base_dir}/${build_dir}/temp"
mkdir -p "${temp_dir}"
# Since we have multiple architectures libtool will find object files that do not
# match the target architecture. We suppress these warnings.
libtool -static -o "${temp_dir}/combined.a" "${libs[@]}" 2> /dev/null
# Determine SDK, architectures, and install_name based on platform and simulator flag.
local sdk=""
local archs=""
local min_version_flag=""
local install_name=""
case "$platform" in
"ios")
if [[ "$is_simulator" == "true" ]]; then
sdk="iphonesimulator"
archs="arm64 x86_64"
min_version_flag="-mios-simulator-version-min=${IOS_MIN_OS_VERSION}"
else
sdk="iphoneos"
archs="arm64"
min_version_flag="-mios-version-min=${IOS_MIN_OS_VERSION}"
fi
install_name="@rpath/llama.framework/llama"
;;
"macos")
sdk="macosx"
archs="arm64 x86_64"
min_version_flag="-mmacosx-version-min=${MACOS_MIN_OS_VERSION}"
install_name="@rpath/llama.framework/Versions/Current/llama"
;;
"visionos")
if [[ "$is_simulator" == "true" ]]; then
sdk="xrsimulator"
archs="arm64 x86_64"
min_version_flag="-mtargetos=xros${VISIONOS_MIN_OS_VERSION}-simulator"
else
sdk="xros"
archs="arm64"
min_version_flag="-mtargetos=xros${VISIONOS_MIN_OS_VERSION}"
fi
# Use flat structure for visionOS, same as iOS
install_name="@rpath/llama.framework/llama"
;;
"tvos")
if [[ "$is_simulator" == "true" ]]; then
sdk="appletvsimulator"
archs="arm64 x86_64"
min_version_flag="-mtvos-simulator-version-min=${TVOS_MIN_OS_VERSION}"
else
sdk="appletvos"
archs="arm64"
min_version_flag="-mtvos-version-min=${TVOS_MIN_OS_VERSION}"
fi
install_name="@rpath/llama.framework/llama"
;;
esac
# Build architecture flags
local arch_flags=""
for arch in $archs; do
arch_flags+=" -arch $arch"
done
# Create dynamic library
echo "Creating dynamic library for ${platform}."
xcrun -sdk $sdk clang++ -dynamiclib \
-isysroot $(xcrun --sdk $sdk --show-sdk-path) \
$arch_flags \
$min_version_flag \
-Wl,-force_load,"${temp_dir}/combined.a" \
-framework Foundation -framework Metal -framework Accelerate \
-install_name "$install_name" \
-o "${base_dir}/${output_lib}"
# Platform-specific post-processing for device builds
if [[ "$is_simulator" == "false" ]]; then
if command -v xcrun vtool &>/dev/null; then
case "$platform" in
"ios")
echo "Marking binary as a framework binary for iOS..."
xcrun vtool -set-build-version ios ${IOS_MIN_OS_VERSION} ${IOS_MIN_OS_VERSION} -replace \
-output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
;;
"visionos")
echo "Marking binary as a framework binary for visionOS..."
if [[ "$MAJOR_VERSION" -gt 16 ]] || [[ "$MAJOR_VERSION" -eq 16 && "$MINOR_VERSION" -gt 2 ]]; then
echo "Xcode version greater than 16.2, using visionOS."
VISION_OS_BUILD_VERSION="visionos"
else
echo "Xcode version less than or equal to 16.2, using xros."
VISION_OS_BUILD_VERSION="xros"
fi
xcrun vtool -set-build-version ${VISION_OS_BUILD_VERSION} ${VISIONOS_MIN_OS_VERSION} ${VISIONOS_MIN_OS_VERSION} -replace \
-output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
;;
"tvos")
echo "Marking binary as a framework binary for tvOS..."
xcrun vtool -set-build-version tvos ${TVOS_MIN_OS_VERSION} ${TVOS_MIN_OS_VERSION} -replace \
-output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
;;
esac
else
echo "Warning: vtool not found. Binary may not pass App Store validation."
fi
fi
echo "Creating properly formatted dSYM..."
# Create a separate directory for dSYMs for all platforms
mkdir -p "${base_dir}/${build_dir}/dSYMs"
# iOS and visionOS style dSYM (flat structure)
if [[ "$platform" == "ios" || "$platform" == "visionos" || "$platform" == "tvos" ]]; then
# Generate dSYM in the dSYMs directory
xcrun dsymutil "${base_dir}/${output_lib}" -o "${base_dir}/${build_dir}/dSYMs/llama.dSYM"
# Create a copy of the binary that will be stripped
cp "${base_dir}/${output_lib}" "${temp_dir}/binary_to_strip"
# Strip debug symbols from the copy
xcrun strip -S "${temp_dir}/binary_to_strip" -o "${temp_dir}/stripped_lib"
# Replace the original with the stripped version
mv "${temp_dir}/stripped_lib" "${base_dir}/${output_lib}"
else
# macOS style dSYM
# First strip debug info to a separate file
xcrun strip -S "${base_dir}/${output_lib}" -o "${temp_dir}/stripped_lib"
# Generate dSYM in the dSYMs directory
xcrun dsymutil "${base_dir}/${output_lib}" -o "${base_dir}/${build_dir}/dSYMs/llama.dSYM"
# Replace original binary with stripped version
mv "${temp_dir}/stripped_lib" "${base_dir}/${output_lib}"
fi
# Remove any automatically generated dSYM files in the framework structure as they will
# otherwise case Invalid Bundle Structure validation errors.
if [ -d "${base_dir}/${output_lib}.dSYM" ]; then
echo "Removing generated dSYM file in framework structure: ${base_dir}/${output_lib}.dSYM"
rm -rf "${base_dir}/${output_lib}.dSYM"
fi
# Clean up
rm -rf "${temp_dir}"
}
echo "Building for iOS simulator..."
cmake -B build-ios-sim -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${IOS_MIN_OS_VERSION} \
-DIOS=ON \
-DCMAKE_SYSTEM_NAME=iOS \
-DCMAKE_OSX_SYSROOT=iphonesimulator \
-DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=iphonesimulator \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-ios-sim --config Release -- -quiet
echo "Building for iOS devices..."
cmake -B build-ios-device -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${IOS_MIN_OS_VERSION} \
-DCMAKE_OSX_SYSROOT=iphoneos \
-DCMAKE_OSX_ARCHITECTURES="arm64" \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=iphoneos \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-ios-device --config Release -- -quiet
echo "Building for macOS..."
cmake -B build-macos -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${MACOS_MIN_OS_VERSION} \
-DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-macos --config Release -- -quiet
echo "Building for visionOS..."
cmake -B build-visionos -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${VISIONOS_MIN_OS_VERSION} \
-DCMAKE_OSX_ARCHITECTURES="arm64" \
-DCMAKE_SYSTEM_NAME=visionOS \
-DCMAKE_OSX_SYSROOT=xros \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xros \
-DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_CXX_FLAGS}" \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-visionos --config Release -- -quiet
echo "Building for visionOS simulator..."
cmake -B build-visionos-sim -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${VISIONOS_MIN_OS_VERSION} \
-DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
-DCMAKE_SYSTEM_NAME=visionOS \
-DCMAKE_OSX_SYSROOT=xrsimulator \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xrsimulator \
-DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_CXX_FLAGS}" \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-visionos-sim --config Release -- -quiet
# Add tvOS builds (might need the same u_int definitions as watchOS and visionOS)
echo "Building for tvOS simulator..."
cmake -B build-tvos-sim -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${TVOS_MIN_OS_VERSION} \
-DCMAKE_SYSTEM_NAME=tvOS \
-DCMAKE_OSX_SYSROOT=appletvsimulator \
-DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
-DGGML_METAL=ON \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=appletvsimulator \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-tvos-sim --config Release -- -quiet
echo "Building for tvOS devices..."
cmake -B build-tvos-device -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${TVOS_MIN_OS_VERSION} \
-DCMAKE_SYSTEM_NAME=tvOS \
-DCMAKE_OSX_SYSROOT=appletvos \
-DCMAKE_OSX_ARCHITECTURES="arm64" \
-DGGML_METAL=ON \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=appletvos \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-tvos-device --config Release -- -quiet
# Setup frameworks and copy binaries and headers
echo "Setting up framework structures..."
setup_framework_structure "build-ios-sim" ${IOS_MIN_OS_VERSION} "ios"
setup_framework_structure "build-ios-device" ${IOS_MIN_OS_VERSION} "ios"
setup_framework_structure "build-macos" ${MACOS_MIN_OS_VERSION} "macos"
setup_framework_structure "build-visionos" ${VISIONOS_MIN_OS_VERSION} "visionos"
setup_framework_structure "build-visionos-sim" ${VISIONOS_MIN_OS_VERSION} "visionos"
setup_framework_structure "build-tvos-sim" ${TVOS_MIN_OS_VERSION} "tvos"
setup_framework_structure "build-tvos-device" ${TVOS_MIN_OS_VERSION} "tvos"
# Create dynamic libraries from static libraries
echo "Creating dynamic libraries from static libraries..."
combine_static_libraries "build-ios-sim" "Release-iphonesimulator" "ios" "true"
combine_static_libraries "build-ios-device" "Release-iphoneos" "ios" "false"
combine_static_libraries "build-macos" "Release" "macos" "false"
combine_static_libraries "build-visionos" "Release-xros" "visionos" "false"
combine_static_libraries "build-visionos-sim" "Release-xrsimulator" "visionos" "true"
combine_static_libraries "build-tvos-sim" "Release-appletvsimulator" "tvos" "true"
combine_static_libraries "build-tvos-device" "Release-appletvos" "tvos" "false"
# Create XCFramework with correct debug symbols paths
echo "Creating XCFramework..."
xcodebuild -create-xcframework \
-framework $(pwd)/build-ios-sim/framework/llama.framework \
-debug-symbols $(pwd)/build-ios-sim/dSYMs/llama.dSYM \
-framework $(pwd)/build-ios-device/framework/llama.framework \
-debug-symbols $(pwd)/build-ios-device/dSYMs/llama.dSYM \
-framework $(pwd)/build-macos/framework/llama.framework \
-debug-symbols $(pwd)/build-macos/dSYMS/llama.dSYM \
-framework $(pwd)/build-visionos/framework/llama.framework \
-debug-symbols $(pwd)/build-visionos/dSYMs/llama.dSYM \
-framework $(pwd)/build-visionos-sim/framework/llama.framework \
-debug-symbols $(pwd)/build-visionos-sim/dSYMs/llama.dSYM \
-framework $(pwd)/build-tvos-device/framework/llama.framework \
-debug-symbols $(pwd)/build-tvos-device/dSYMs/llama.dSYM \
-framework $(pwd)/build-tvos-sim/framework/llama.framework \
-debug-symbols $(pwd)/build-tvos-sim/dSYMs/llama.dSYM \
-output $(pwd)/build-apple/llama.xcframework

View File

@ -1,11 +1,11 @@
# CI # CI
In addition to [Github Actions](https://github.com/ggerganov/llama.cpp/actions) `llama.cpp` uses a custom CI framework: In addition to [Github Actions](https://github.com/ggml-org/llama.cpp/actions) `llama.cpp` uses a custom CI framework:
https://github.com/ggml-org/ci https://github.com/ggml-org/ci
It monitors the `master` branch for new commits and runs the It monitors the `master` branch for new commits and runs the
[ci/run.sh](https://github.com/ggerganov/llama.cpp/blob/master/ci/run.sh) script on dedicated cloud instances. This allows us [ci/run.sh](https://github.com/ggml-org/llama.cpp/blob/master/ci/run.sh) script on dedicated cloud instances. This allows us
to execute heavier workloads compared to just using Github Actions. Also with time, the cloud instances will be scaled to execute heavier workloads compared to just using Github Actions. Also with time, the cloud instances will be scaled
to cover various hardware architectures, including GPU and Apple Silicon instances. to cover various hardware architectures, including GPU and Apple Silicon instances.
@ -26,4 +26,43 @@ GG_BUILD_CUDA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
# with SYCL support # with SYCL support
source /opt/intel/oneapi/setvars.sh source /opt/intel/oneapi/setvars.sh
GG_BUILD_SYCL=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt GG_BUILD_SYCL=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
# with MUSA support
GG_BUILD_MUSA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
``` ```
## Running MUSA CI in a Docker Container
Assuming `$PWD` is the root of the `llama.cpp` repository, follow these steps to set up and run MUSA CI in a Docker container:
### 1. Create a local directory to store cached models, configuration files and venv:
```bash
mkdir -p $HOME/llama.cpp/ci-cache
```
### 2. Create a local directory to store CI run results:
```bash
mkdir -p $HOME/llama.cpp/ci-results
```
### 3. Start a Docker container and run the CI:
```bash
docker run --privileged -it \
-v $HOME/llama.cpp/ci-cache:/ci-cache \
-v $HOME/llama.cpp/ci-results:/ci-results \
-v $PWD:/ws -w /ws \
mthreads/musa:rc4.0.1-mudnn-devel-ubuntu22.04
```
Inside the container, execute the following commands:
```bash
apt update -y && apt install -y bc cmake ccache git python3.10-venv time unzip wget
git config --global --add safe.directory /ws
GG_BUILD_MUSA=1 bash ./ci/run.sh /ci-results /ci-cache
```
This setup ensures that the CI runs within an isolated Docker environment while maintaining cached files and results across runs.

140
ci/run.sh
View File

@ -1,4 +1,4 @@
#!/bin/bash #!/usr/bin/env bash
# #
# sample usage: # sample usage:
# #
@ -16,6 +16,9 @@
# # with VULKAN support # # with VULKAN support
# GG_BUILD_VULKAN=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt # GG_BUILD_VULKAN=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
# #
# # with MUSA support
# GG_BUILD_MUSA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
#
if [ -z "$2" ]; then if [ -z "$2" ]; then
echo "usage: $0 <output-dir> <mnt-dir>" echo "usage: $0 <output-dir> <mnt-dir>"
@ -36,14 +39,27 @@ sd=`dirname $0`
cd $sd/../ cd $sd/../
SRC=`pwd` SRC=`pwd`
CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=ON" CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=ON -DLLAMA_CURL=ON"
if [ ! -z ${GG_BUILD_METAL} ]; then if [ ! -z ${GG_BUILD_METAL} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON -DGGML_METAL_USE_BF16=ON" CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON -DGGML_METAL_USE_BF16=ON"
fi fi
if [ ! -z ${GG_BUILD_CUDA} ]; then if [ ! -z ${GG_BUILD_CUDA} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=native" CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_CUDA=ON"
if command -v nvidia-smi >/dev/null 2>&1; then
CUDA_ARCH=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader,nounits 2>/dev/null | head -1 | tr -d '.')
if [[ -n "$CUDA_ARCH" && "$CUDA_ARCH" =~ ^[0-9]+$ ]]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH}"
else
echo "Warning: Using fallback CUDA architectures"
CMAKE_EXTRA="${CMAKE_EXTRA} -DCMAKE_CUDA_ARCHITECTURES=61;70;75;80;86;89"
fi
else
echo "Error: nvidia-smi not found, cannot build with CUDA"
exit 1
fi
fi fi
if [ ! -z ${GG_BUILD_SYCL} ]; then if [ ! -z ${GG_BUILD_SYCL} ]; then
@ -52,13 +68,24 @@ if [ ! -z ${GG_BUILD_SYCL} ]; then
echo "source /opt/intel/oneapi/setvars.sh" echo "source /opt/intel/oneapi/setvars.sh"
exit 1 exit 1
fi fi
# Use only main GPU
export ONEAPI_DEVICE_SELECTOR="level_zero:0"
# Enable sysman for correct memory reporting
export ZES_ENABLE_SYSMAN=1
# to circumvent precision issues on CPY operations
export SYCL_PROGRAM_COMPILE_OPTIONS="-cl-fp32-correctly-rounded-divide-sqrt"
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_SYCL=1 -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON" CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_SYCL=1 -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON"
fi fi
if [ ! -z ${GG_BUILD_VULKAN} ]; then if [ ! -z ${GG_BUILD_VULKAN} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_VULKAN=1" CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_VULKAN=1"
fi fi
if [ ! -z ${GG_BUILD_MUSA} ]; then
# Use qy1 by default (MTT S80)
MUSA_ARCH=${MUSA_ARCH:-21}
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_MUSA=ON -DMUSA_ARCHITECTURES=${MUSA_ARCH}"
fi
## helpers ## helpers
# download a file if it does not exist or if it is outdated # download a file if it does not exist or if it is outdated
@ -173,8 +200,8 @@ function gg_run_test_scripts_debug {
set -e set -e
(cd ./examples/gguf-split && time bash tests.sh "$SRC/build-ci-debug/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log (cd ./tools/gguf-split && time bash tests.sh "$SRC/build-ci-debug/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
(cd ./examples/quantize && time bash tests.sh "$SRC/build-ci-debug/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log (cd ./tools/quantize && time bash tests.sh "$SRC/build-ci-debug/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
set +e set +e
} }
@ -197,8 +224,8 @@ function gg_run_test_scripts_release {
set -e set -e
(cd ./examples/gguf-split && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log (cd ./tools/gguf-split && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
(cd ./examples/quantize && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log (cd ./tools/quantize && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
set +e set +e
} }
@ -326,17 +353,17 @@ function gg_run_open_llama_7b_v2 {
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k ./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k ./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/llama-cli --model ${model_f16} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log (time ./bin/llama-cli -no-cnv --model ${model_f16} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log (time ./bin/llama-cli -no-cnv --model ${model_q8_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log (time ./bin/llama-cli -no-cnv --model ${model_q4_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log (time ./bin/llama-cli -no-cnv --model ${model_q4_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log (time ./bin/llama-cli -no-cnv --model ${model_q5_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log (time ./bin/llama-cli -no-cnv --model ${model_q5_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log (time ./bin/llama-cli -no-cnv --model ${model_q2_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log (time ./bin/llama-cli -no-cnv --model ${model_q3_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log (time ./bin/llama-cli -no-cnv --model ${model_q4_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log (time ./bin/llama-cli -no-cnv --model ${model_q5_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log (time ./bin/llama-cli -no-cnv --model ${model_q6_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log (time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log (time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
@ -352,10 +379,10 @@ function gg_run_open_llama_7b_v2 {
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log (time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state--model ${model_q4_0} -ngl 10 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log (time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state--model ${model_q4_0} -ngl 10 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log (time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state--model ${model_q4_0} -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log (time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state--model ${model_q4_0} -ngl 99 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log (time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl { function check_ppl {
qnt="$1" qnt="$1"
@ -460,17 +487,17 @@ function gg_run_pythia_1_4b {
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k ./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k ./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/llama-cli --model ${model_f16} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log (time ./bin/llama-cli -no-cnv --model ${model_f16} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log (time ./bin/llama-cli -no-cnv --model ${model_q8_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log (time ./bin/llama-cli -no-cnv --model ${model_q4_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log (time ./bin/llama-cli -no-cnv --model ${model_q4_1} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log (time ./bin/llama-cli -no-cnv --model ${model_q5_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log (time ./bin/llama-cli -no-cnv --model ${model_q5_1} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log (time ./bin/llama-cli -no-cnv --model ${model_q2_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log (time ./bin/llama-cli -no-cnv --model ${model_q3_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log (time ./bin/llama-cli -no-cnv --model ${model_q4_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log (time ./bin/llama-cli -no-cnv --model ${model_q5_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log (time ./bin/llama-cli -no-cnv --model ${model_q6_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log (time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log (time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
@ -591,17 +618,17 @@ function gg_run_pythia_2_8b {
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k ./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k ./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/llama-cli --model ${model_f16} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log (time ./bin/llama-cli -no-cnv --model ${model_f16} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log (time ./bin/llama-cli -no-cnv --model ${model_q8_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log (time ./bin/llama-cli -no-cnv --model ${model_q4_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log (time ./bin/llama-cli -no-cnv --model ${model_q4_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log (time ./bin/llama-cli -no-cnv --model ${model_q5_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log (time ./bin/llama-cli -no-cnv --model ${model_q5_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log (time ./bin/llama-cli -no-cnv --model ${model_q2_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log (time ./bin/llama-cli -no-cnv --model ${model_q3_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log (time ./bin/llama-cli -no-cnv --model ${model_q4_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log (time ./bin/llama-cli -no-cnv --model ${model_q5_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log (time ./bin/llama-cli -no-cnv --model ${model_q6_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log (time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log (time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
@ -752,7 +779,7 @@ function gg_run_rerank_tiny {
model_f16="${path_models}/ggml-model-f16.gguf" model_f16="${path_models}/ggml-model-f16.gguf"
# for this model, the SEP token is "</s>" # for this model, the SEP token is "</s>"
(time ./bin/llama-embedding --model ${model_f16} -p "what is panda?</s></s>hi\nwhat is panda?</s></s>it's a bear\nwhat is panda?</s></s>The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China." -ngl 99 -c 0 --pooling rank --embd-normalize -1 --verbose-prompt) 2>&1 | tee -a $OUT/${ci}-rk-f16.log (time ./bin/llama-embedding --model ${model_f16} -p "what is panda?\thi\nwhat is panda?\tit's a bear\nwhat is panda?\tThe giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China." -ngl 99 -c 0 --pooling rank --embd-normalize -1 --verbose-prompt) 2>&1 | tee -a $OUT/${ci}-rk-f16.log
# sample output # sample output
# rerank score 0: 0.029 # rerank score 0: 0.029
@ -808,14 +835,17 @@ export LLAMA_LOG_PREFIX=1
export LLAMA_LOG_TIMESTAMPS=1 export LLAMA_LOG_TIMESTAMPS=1
if [ -z ${GG_BUILD_LOW_PERF} ]; then if [ -z ${GG_BUILD_LOW_PERF} ]; then
# Create symlink: ./llama.cpp/models-mnt -> $MNT/models/models-mnt # Create symlink: ./llama.cpp/models-mnt -> $MNT/models
rm -rf ${SRC}/models-mnt rm -rf ${SRC}/models-mnt
mnt_models=${MNT}/models mnt_models=${MNT}/models
mkdir -p ${mnt_models} mkdir -p ${mnt_models}
ln -sfn ${mnt_models} ${SRC}/models-mnt ln -sfn ${mnt_models} ${SRC}/models-mnt
# Create a fresh python3 venv and enter it # Create a fresh python3 venv and enter it
python3 -m venv "$MNT/venv" if ! python3 -m venv "$MNT/venv"; then
echo "Error: Failed to create Python virtual environment at $MNT/venv."
exit 1
fi
source "$MNT/venv/bin/activate" source "$MNT/venv/bin/activate"
pip install -r ${SRC}/requirements.txt --disable-pip-version-check pip install -r ${SRC}/requirements.txt --disable-pip-version-check
@ -823,8 +853,10 @@ if [ -z ${GG_BUILD_LOW_PERF} ]; then
fi fi
ret=0 ret=0
if [ -z ${GG_BUILD_SYCL} ]; then
test $ret -eq 0 && gg_run ctest_debug # SYCL build breaks with debug build flags
test $ret -eq 0 && gg_run ctest_debug
fi
test $ret -eq 0 && gg_run ctest_release test $ret -eq 0 && gg_run ctest_release
if [ -z ${GG_BUILD_LOW_PERF} ]; then if [ -z ${GG_BUILD_LOW_PERF} ]; then
@ -832,7 +864,9 @@ if [ -z ${GG_BUILD_LOW_PERF} ]; then
test $ret -eq 0 && gg_run rerank_tiny test $ret -eq 0 && gg_run rerank_tiny
if [ -z ${GG_BUILD_CLOUD} ] || [ ${GG_BUILD_EXTRA_TESTS_0} ]; then if [ -z ${GG_BUILD_CLOUD} ] || [ ${GG_BUILD_EXTRA_TESTS_0} ]; then
test $ret -eq 0 && gg_run test_scripts_debug if [ -z ${GG_BUILD_SYCL} ]; then
test $ret -eq 0 && gg_run test_scripts_debug
fi
test $ret -eq 0 && gg_run test_scripts_release test $ret -eq 0 && gg_run test_scripts_release
fi fi
@ -843,7 +877,9 @@ if [ -z ${GG_BUILD_LOW_PERF} ]; then
test $ret -eq 0 && gg_run pythia_2_8b test $ret -eq 0 && gg_run pythia_2_8b
#test $ret -eq 0 && gg_run open_llama_7b_v2 #test $ret -eq 0 && gg_run open_llama_7b_v2
fi fi
test $ret -eq 0 && gg_run ctest_with_model_debug if [ -z ${GG_BUILD_SYCL} ]; then
test $ret -eq 0 && gg_run ctest_with_model_debug
fi
test $ret -eq 0 && gg_run ctest_with_model_release test $ret -eq 0 && gg_run ctest_with_model_release
fi fi
fi fi

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@ -1,6 +0,0 @@
set( CMAKE_SYSTEM_NAME Windows )
set( CMAKE_SYSTEM_PROCESSOR arm64 )
set( target arm64-pc-windows-msvc )
set( CMAKE_C_COMPILER_TARGET ${target} )
set( CMAKE_CXX_COMPILER_TARGET ${target} )

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@ -41,14 +41,20 @@ endif()
if(MSVC) if(MSVC)
set(BUILD_COMPILER "${CMAKE_C_COMPILER_ID} ${CMAKE_C_COMPILER_VERSION}") set(BUILD_COMPILER "${CMAKE_C_COMPILER_ID} ${CMAKE_C_COMPILER_VERSION}")
set(BUILD_TARGET ${CMAKE_VS_PLATFORM_NAME}) if (CMAKE_VS_PLATFORM_NAME)
set(BUILD_TARGET ${CMAKE_VS_PLATFORM_NAME})
else()
set(BUILD_TARGET "${CMAKE_SYSTEM_NAME} ${CMAKE_SYSTEM_PROCESSOR}")
endif()
else() else()
execute_process( execute_process(
COMMAND sh -c "$@ --version | head -1" _ ${CMAKE_C_COMPILER} COMMAND ${CMAKE_C_COMPILER} --version
OUTPUT_VARIABLE OUT OUTPUT_VARIABLE OUT
OUTPUT_STRIP_TRAILING_WHITESPACE OUTPUT_STRIP_TRAILING_WHITESPACE
) )
string(REGEX REPLACE " *\n.*" "" OUT "${OUT}")
set(BUILD_COMPILER ${OUT}) set(BUILD_COMPILER ${OUT})
execute_process( execute_process(
COMMAND ${CMAKE_C_COMPILER} -dumpmachine COMMAND ${CMAKE_C_COMPILER} -dumpmachine
OUTPUT_VARIABLE OUT OUTPUT_VARIABLE OUT

35
cmake/common.cmake Normal file
View File

@ -0,0 +1,35 @@
include("ggml/cmake/common.cmake")
function(llama_add_compile_flags)
if (LLAMA_FATAL_WARNINGS)
if (CMAKE_CXX_COMPILER_ID MATCHES "GNU" OR CMAKE_CXX_COMPILER_ID MATCHES "Clang")
list(APPEND C_FLAGS -Werror)
list(APPEND CXX_FLAGS -Werror)
elseif (CMAKE_CXX_COMPILER_ID STREQUAL "MSVC")
add_compile_options(/WX)
endif()
endif()
if (LLAMA_ALL_WARNINGS)
if (NOT MSVC)
list(APPEND C_FLAGS -Wshadow -Wstrict-prototypes -Wpointer-arith -Wmissing-prototypes
-Werror=implicit-int -Werror=implicit-function-declaration)
list(APPEND CXX_FLAGS -Wmissing-declarations -Wmissing-noreturn)
list(APPEND WARNING_FLAGS -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function)
list(APPEND C_FLAGS ${WARNING_FLAGS})
list(APPEND CXX_FLAGS ${WARNING_FLAGS})
ggml_get_flags(${CMAKE_CXX_COMPILER_ID} ${CMAKE_CXX_COMPILER_VERSION})
add_compile_options("$<$<COMPILE_LANGUAGE:C>:${C_FLAGS};${GF_C_FLAGS}>"
"$<$<COMPILE_LANGUAGE:CXX>:${CXX_FLAGS};${GF_CXX_FLAGS}>")
else()
# todo : msvc
set(C_FLAGS "" PARENT_SCOPE)
set(CXX_FLAGS "" PARENT_SCOPE)
endif()
endif()
endfunction()

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@ -3,159 +3,13 @@ set(LLAMA_BUILD_COMMIT @LLAMA_BUILD_COMMIT@)
set(LLAMA_BUILD_NUMBER @LLAMA_BUILD_NUMBER@) set(LLAMA_BUILD_NUMBER @LLAMA_BUILD_NUMBER@)
set(LLAMA_SHARED_LIB @BUILD_SHARED_LIBS@) set(LLAMA_SHARED_LIB @BUILD_SHARED_LIBS@)
set(GGML_STATIC @GGML_STATIC@)
set(GGML_NATIVE @GGML_NATIVE@)
set(GGML_LTO @GGML_LTO@)
set(GGML_CCACHE @GGML_CCACHE@)
set(GGML_AVX @GGML_AVX@)
set(GGML_AVX2 @GGML_AVX2@)
set(GGML_AVX512 @GGML_AVX512@)
set(GGML_AVX512_VBMI @GGML_AVX512_VBMI@)
set(GGML_AVX512_VNNI @GGML_AVX512_VNNI@)
set(GGML_AVX512_BF16 @GGML_AVX512_BF16@)
set(GGML_AMX_TILE @GGML_AMX_TILE@)
set(GGML_AMX_INT8 @GGML_AMX_INT8@)
set(GGML_AMX_BF16 @GGML_AMX_BF16@)
set(GGML_FMA @GGML_FMA@)
set(GGML_LASX @GGML_LASX@)
set(GGML_LSX @GGML_LSX@)
set(GGML_RVV @GGML_RVV@)
set(GGML_SVE @GGML_SVE@)
set(GGML_ACCELERATE @GGML_ACCELERATE@)
set(GGML_OPENMP @GGML_OPENMP@)
set(GGML_CPU_HBM @GGML_CPU_HBM@)
set(GGML_BLAS_VENDOR @GGML_BLAS_VENDOR@)
set(GGML_CUDA_FORCE_MMQ @GGML_CUDA_FORCE_MMQ@)
set(GGML_CUDA_FORCE_CUBLAS @GGML_CUDA_FORCE_CUBLAS@)
set(GGML_CUDA_F16 @GGML_CUDA_F16@)
set(GGML_CUDA_PEER_MAX_BATCH_SIZE @GGML_CUDA_PEER_MAX_BATCH_SIZE@)
set(GGML_CUDA_NO_PEER_COPY @GGML_CUDA_NO_PEER_COPY@)
set(GGML_CUDA_NO_VMM @GGML_CUDA_NO_VMM@)
set(GGML_CUDA_FA_ALL_QUANTS @GGML_CUDA_FA_ALL_QUANTS@)
set(GGML_CUDA_GRAPHS @GGML_CUDA_GRAPHS@)
set(GGML_HIP_UMA @GGML_HIP_UMA@)
set(GGML_VULKAN_CHECK_RESULTS @GGML_VULKAN_CHECK_RESULTS@)
set(GGML_VULKAN_DEBUG @GGML_VULKAN_DEBUG@)
set(GGML_VULKAN_MEMORY_DEBUG @GGML_VULKAN_MEMORY_DEBUG@)
set(GGML_VULKAN_SHADER_DEBUG_INFO @GGML_VULKAN_SHADER_DEBUG_INFO@)
set(GGML_VULKAN_PERF @GGML_VULKAN_PERF@)
set(GGML_VULKAN_VALIDATE @GGML_VULKAN_VALIDATE@)
set(GGML_VULKAN_RUN_TESTS @GGML_VULKAN_RUN_TESTS@)
set(GGML_METAL_USE_BF16 @GGML_METAL_USE_BF16@)
set(GGML_METAL_NDEBUG @GGML_METAL_NDEBUG@)
set(GGML_METAL_SHADER_DEBUG @GGML_METAL_SHADER_DEBUG@)
set(GGML_METAL_EMBED_LIBRARY @GGML_METAL_EMBED_LIBRARY@)
set(GGML_METAL_MACOSX_VERSION_MIN @GGML_METAL_MACOSX_VERSION_MIN@)
set(GGML_METAL_STD @GGML_METAL_STD@)
set(GGML_SYCL_F16 @GGML_SYCL_F16@)
set(GGML_SYCL_TARGET @GGML_SYCL_TARGET@)
set(GGML_SYCL_DEVICE_ARCH @GGML_SYCL_DEVICE_ARCH@)
@PACKAGE_INIT@ @PACKAGE_INIT@
set_and_check(LLAMA_INCLUDE_DIR "@PACKAGE_LLAMA_INCLUDE_INSTALL_DIR@") set_and_check(LLAMA_INCLUDE_DIR "@PACKAGE_LLAMA_INCLUDE_INSTALL_DIR@")
set_and_check(LLAMA_LIB_DIR "@PACKAGE_LLAMA_LIB_INSTALL_DIR@") set_and_check(LLAMA_LIB_DIR "@PACKAGE_LLAMA_LIB_INSTALL_DIR@")
set_and_check(LLAMA_BIN_DIR "@PACKAGE_LLAMA_BIN_INSTALL_DIR@") set_and_check(LLAMA_BIN_DIR "@PACKAGE_LLAMA_BIN_INSTALL_DIR@")
find_package(Threads REQUIRED) find_package(ggml REQUIRED HINTS ${LLAMA_LIB_DIR}/cmake)
set(_llama_transient_defines "@GGML_TRANSIENT_DEFINES@")
set(_llama_link_deps "")
set(_llama_link_opts "")
foreach(_ggml_lib ggml ggml-base)
string(REPLACE "-" "_" _ggml_lib_var "${_ggml_lib}_LIBRARY")
find_library(${_ggml_lib_var} ${_ggml_lib}
REQUIRED
HINTS ${LLAMA_LIB_DIR}
NO_CMAKE_FIND_ROOT_PATH
)
list(APPEND _llama_link_deps "${${_ggml_lib_var}}")
message(STATUS "Found ${${_ggml_lib_var}}")
endforeach()
foreach(backend amx blas cann cpu cuda hip kompute metal musa rpc sycl vulkan)
string(TOUPPER "GGML_${backend}" backend_id)
set(_ggml_lib "ggml-${backend}")
string(REPLACE "-" "_" _ggml_lib_var "${_ggml_lib}_LIBRARY")
find_library(${_ggml_lib_var} ${_ggml_lib}
HINTS ${LLAMA_LIB_DIR}
NO_CMAKE_FIND_ROOT_PATH
)
if(${_ggml_lib_var})
list(APPEND _llama_link_deps "${${_ggml_lib_var}}")
set(${backend_id} ON)
message(STATUS "Found backend ${${_ggml_lib_var}}")
else()
set(${backend_id} OFF)
endif()
endforeach()
if (NOT LLAMA_SHARED_LIB)
if (APPLE AND GGML_ACCELERATE)
find_library(ACCELERATE_FRAMEWORK Accelerate REQUIRED)
list(APPEND _llama_link_deps ${ACCELERATE_FRAMEWORK})
endif()
if (GGML_OPENMP)
find_package(OpenMP REQUIRED)
list(APPEND _llama_link_deps OpenMP::OpenMP_C OpenMP::OpenMP_CXX)
endif()
if (GGML_CPU_HBM)
find_library(memkind memkind REQUIRED)
list(APPEND _llama_link_deps memkind)
endif()
if (GGML_BLAS)
find_package(BLAS REQUIRED)
list(APPEND _llama_link_deps ${BLAS_LIBRARIES})
list(APPEND _llama_link_opts ${BLAS_LINKER_FLAGS})
endif()
if (GGML_CUDA)
find_package(CUDAToolkit REQUIRED)
endif()
if (GGML_METAL)
find_library(FOUNDATION_LIBRARY Foundation REQUIRED)
find_library(METAL_FRAMEWORK Metal REQUIRED)
find_library(METALKIT_FRAMEWORK MetalKit REQUIRED)
list(APPEND _llama_link_deps ${FOUNDATION_LIBRARY}
${METAL_FRAMEWORK} ${METALKIT_FRAMEWORK})
endif()
if (GGML_VULKAN)
find_package(Vulkan REQUIRED)
list(APPEND _llama_link_deps Vulkan::Vulkan)
endif()
if (GGML_HIP)
find_package(hip REQUIRED)
find_package(hipblas REQUIRED)
find_package(rocblas REQUIRED)
list(APPEND _llama_link_deps hip::host roc::rocblas roc::hipblas)
endif()
if (GGML_SYCL)
find_package(DNNL)
if (${DNNL_FOUND} AND GGML_SYCL_TARGET STREQUAL "INTEL")
list(APPEND _llama_link_deps DNNL::dnnl)
endif()
if (WIN32)
find_package(IntelSYCL REQUIRED)
find_package(MKL REQUIRED)
list(APPEND _llama_link_deps IntelSYCL::SYCL_CXX MKL::MKL MKL::MKL_SYCL)
endif()
endif()
endif()
find_library(llama_LIBRARY llama find_library(llama_LIBRARY llama
REQUIRED REQUIRED
@ -167,12 +21,10 @@ add_library(llama UNKNOWN IMPORTED)
set_target_properties(llama set_target_properties(llama
PROPERTIES PROPERTIES
INTERFACE_INCLUDE_DIRECTORIES "${LLAMA_INCLUDE_DIR}" INTERFACE_INCLUDE_DIRECTORIES "${LLAMA_INCLUDE_DIR}"
INTERFACE_LINK_LIBRARIES "${_llama_link_deps}" INTERFACE_LINK_LIBRARIES "ggml::ggml;ggml::ggml-base;"
INTERFACE_LINK_OPTIONS "${_llama_link_opts}"
INTERFACE_COMPILE_DEFINITIONS "${_llama_transient_defines}"
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX" IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${llama_LIBRARY}" IMPORTED_LOCATION "${llama_LIBRARY}"
INTERFACE_COMPILE_FEATURES cxx_std_11 INTERFACE_COMPILE_FEATURES c_std_90
POSITION_INDEPENDENT_CODE ON ) POSITION_INDEPENDENT_CODE ON)
check_required_components(Llama) check_required_components(Llama)

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@ -1,10 +1,10 @@
prefix=@CMAKE_INSTALL_PREFIX@ prefix=@CMAKE_INSTALL_PREFIX@
exec_prefix=${prefix} exec_prefix=@CMAKE_INSTALL_PREFIX@
libdir=${exec_prefix}/lib libdir=@CMAKE_INSTALL_FULL_LIBDIR@
includedir=${prefix}/include includedir=@CMAKE_INSTALL_FULL_INCLUDEDIR@
Name: llama Name: llama
Description: Port of Facebook's LLaMA model in C/C++ Description: Port of Facebook's LLaMA model in C/C++
Version: @PROJECT_VERSION@ Version: @LLAMA_INSTALL_VERSION@
Libs: -L${libdir} -lllama Libs: -L${libdir} -lggml -lggml-base -lllama
Cflags: -I${includedir} Cflags: -I${includedir}

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@ -0,0 +1,5 @@
set( CMAKE_SYSTEM_NAME Windows )
set( CMAKE_SYSTEM_PROCESSOR x86_64 )
set( CMAKE_C_COMPILER clang )
set( CMAKE_CXX_COMPILER clang++ )

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@ -2,11 +2,13 @@
find_package(Threads REQUIRED) find_package(Threads REQUIRED)
llama_add_compile_flags()
# Build info header # Build info header
# #
if(EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/../.git") if(EXISTS "${PROJECT_SOURCE_DIR}/.git")
set(GIT_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../.git") set(GIT_DIR "${PROJECT_SOURCE_DIR}/.git")
# Is git submodule # Is git submodule
if(NOT IS_DIRECTORY "${GIT_DIR}") if(NOT IS_DIRECTORY "${GIT_DIR}")
@ -16,34 +18,26 @@ if(EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/../.git")
if (SLASH_POS EQUAL 0) if (SLASH_POS EQUAL 0)
set(GIT_DIR "${REAL_GIT_DIR}") set(GIT_DIR "${REAL_GIT_DIR}")
else() else()
set(GIT_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../${REAL_GIT_DIR}") set(GIT_DIR "${PROJECT_SOURCE_DIR}/${REAL_GIT_DIR}")
endif() endif()
endif() endif()
if(EXISTS "${GIT_DIR}/index") if(EXISTS "${GIT_DIR}/index")
set(GIT_INDEX "${GIT_DIR}/index") # For build-info.cpp below
set_property(DIRECTORY APPEND PROPERTY CMAKE_CONFIGURE_DEPENDS "${GIT_DIR}/index")
else() else()
message(WARNING "Git index not found in git repository.") message(WARNING "Git index not found in git repository.")
set(GIT_INDEX "")
endif() endif()
else() else()
message(WARNING "Git repository not found; to enable automatic generation of build info, make sure Git is installed and the project is a Git repository.") message(WARNING "Git repository not found; to enable automatic generation of build info, make sure Git is installed and the project is a Git repository.")
set(GIT_INDEX "")
endif() endif()
# Add a custom command to rebuild build-info.cpp when .git/index changes set(TEMPLATE_FILE "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp.in")
add_custom_command( set(OUTPUT_FILE "${CMAKE_CURRENT_BINARY_DIR}/build-info.cpp")
OUTPUT "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp" configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
COMMENT "Generating build details from Git"
COMMAND ${CMAKE_COMMAND} -DMSVC=${MSVC} -DCMAKE_C_COMPILER_VERSION=${CMAKE_C_COMPILER_VERSION}
-DCMAKE_C_COMPILER_ID=${CMAKE_C_COMPILER_ID} -DCMAKE_VS_PLATFORM_NAME=${CMAKE_VS_PLATFORM_NAME}
-DCMAKE_C_COMPILER=${CMAKE_C_COMPILER} -P "${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info-gen-cpp.cmake"
WORKING_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/.."
DEPENDS "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp.in" ${GIT_INDEX}
VERBATIM
)
set(TARGET build_info) set(TARGET build_info)
add_library(${TARGET} OBJECT build-info.cpp) add_library(${TARGET} OBJECT ${OUTPUT_FILE})
if (BUILD_SHARED_LIBS) if (BUILD_SHARED_LIBS)
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON) set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
endif() endif()
@ -54,18 +48,28 @@ add_library(${TARGET} STATIC
arg.cpp arg.cpp
arg.h arg.h
base64.hpp base64.hpp
chat-parser.cpp
chat-parser.h
chat.cpp
chat.h
common.cpp common.cpp
common.h common.h
console.cpp console.cpp
console.h console.h
json-partial.cpp
json-partial.h
json-schema-to-grammar.cpp json-schema-to-grammar.cpp
json.hpp llguidance.cpp
log.cpp log.cpp
log.h log.h
ngram-cache.cpp ngram-cache.cpp
ngram-cache.h ngram-cache.h
regex-partial.cpp
regex-partial.h
sampling.cpp sampling.cpp
sampling.h sampling.h
speculative.cpp
speculative.h
) )
if (BUILD_SHARED_LIBS) if (BUILD_SHARED_LIBS)
@ -76,13 +80,84 @@ set(LLAMA_COMMON_EXTRA_LIBS build_info)
# Use curl to download model url # Use curl to download model url
if (LLAMA_CURL) if (LLAMA_CURL)
find_package(CURL REQUIRED) find_package(CURL)
add_definitions(-DLLAMA_USE_CURL) if (NOT CURL_FOUND)
message(FATAL_ERROR "Could NOT find CURL. Hint: to disable this feature, set -DLLAMA_CURL=OFF")
endif()
target_compile_definitions(${TARGET} PUBLIC LLAMA_USE_CURL)
include_directories(${CURL_INCLUDE_DIRS}) include_directories(${CURL_INCLUDE_DIRS})
find_library(CURL_LIBRARY curl REQUIRED) find_library(CURL_LIBRARY curl REQUIRED)
set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} ${CURL_LIBRARY}) set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} ${CURL_LIBRARY})
endif () endif ()
target_include_directories(${TARGET} PUBLIC .) if (LLAMA_LLGUIDANCE)
target_compile_features (${TARGET} PUBLIC cxx_std_11) include(ExternalProject)
set(LLGUIDANCE_SRC ${CMAKE_BINARY_DIR}/llguidance/source)
set(LLGUIDANCE_PATH ${LLGUIDANCE_SRC}/target/release)
# Set the correct library file extension based on platform
if (WIN32)
set(LLGUIDANCE_LIB_NAME "llguidance.lib")
# Add Windows-specific libraries
set(LLGUIDANCE_PLATFORM_LIBS
ws2_32 # Windows Sockets API
userenv # For GetUserProfileDirectoryW
ntdll # For NT functions
bcrypt # For BCryptGenRandom
)
else()
set(LLGUIDANCE_LIB_NAME "libllguidance.a")
set(LLGUIDANCE_PLATFORM_LIBS "")
endif()
ExternalProject_Add(llguidance_ext
GIT_REPOSITORY https://github.com/guidance-ai/llguidance
# v0.7.20 (+ fix to build on GCC 15):
GIT_TAG b5b8b64dba11c4e4ee6b1d1450d3a3ae279891e8
PREFIX ${CMAKE_BINARY_DIR}/llguidance
SOURCE_DIR ${LLGUIDANCE_SRC}
BUILD_IN_SOURCE TRUE
CONFIGURE_COMMAND ""
BUILD_COMMAND cargo build --release
INSTALL_COMMAND ""
BUILD_BYPRODUCTS ${LLGUIDANCE_PATH}/${LLGUIDANCE_LIB_NAME} ${LLGUIDANCE_PATH}/llguidance.h
UPDATE_COMMAND ""
)
target_compile_definitions(${TARGET} PUBLIC LLAMA_USE_LLGUIDANCE)
add_library(llguidance STATIC IMPORTED)
set_target_properties(llguidance PROPERTIES IMPORTED_LOCATION ${LLGUIDANCE_PATH}/${LLGUIDANCE_LIB_NAME})
add_dependencies(llguidance llguidance_ext)
target_include_directories(${TARGET} PRIVATE ${LLGUIDANCE_PATH})
# Add platform libraries to the main target
set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} llguidance ${LLGUIDANCE_PLATFORM_LIBS})
endif ()
target_include_directories(${TARGET} PUBLIC . ../vendor)
target_compile_features (${TARGET} PUBLIC cxx_std_17)
target_link_libraries (${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads) target_link_libraries (${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads)
#
# copy the license files
#
# Check if running in GitHub Actions
if (DEFINED ENV{GITHUB_ACTIONS} AND "$ENV{GITHUB_ACTIONS}" STREQUAL "true")
message(STATUS "Running inside GitHub Actions - copying license files")
# Copy all files from licenses/ to build/bin/
file(GLOB LICENSE_FILES "${CMAKE_SOURCE_DIR}/licenses/*")
foreach(LICENSE_FILE ${LICENSE_FILES})
get_filename_component(FILENAME ${LICENSE_FILE} NAME)
add_custom_command(
POST_BUILD
TARGET ${TARGET}
COMMAND ${CMAKE_COMMAND} -E copy_if_different
"${LICENSE_FILE}"
"$<TARGET_FILE_DIR:llama>/${FILENAME}"
COMMENT "Copying ${FILENAME} to ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}")
message(STATUS "Copying ${LICENSE_FILE} to ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${FILENAME}")
endforeach()
endif()

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@ -12,6 +12,7 @@
struct common_arg { struct common_arg {
std::set<enum llama_example> examples = {LLAMA_EXAMPLE_COMMON}; std::set<enum llama_example> examples = {LLAMA_EXAMPLE_COMMON};
std::set<enum llama_example> excludes = {};
std::vector<const char *> args; std::vector<const char *> args;
const char * value_hint = nullptr; // help text or example for arg value const char * value_hint = nullptr; // help text or example for arg value
const char * value_hint_2 = nullptr; // for second arg value const char * value_hint_2 = nullptr; // for second arg value
@ -53,9 +54,11 @@ struct common_arg {
) : args(args), value_hint(value_hint), value_hint_2(value_hint_2), help(help), handler_str_str(handler) {} ) : args(args), value_hint(value_hint), value_hint_2(value_hint_2), help(help), handler_str_str(handler) {}
common_arg & set_examples(std::initializer_list<enum llama_example> examples); common_arg & set_examples(std::initializer_list<enum llama_example> examples);
common_arg & set_excludes(std::initializer_list<enum llama_example> excludes);
common_arg & set_env(const char * env); common_arg & set_env(const char * env);
common_arg & set_sparam(); common_arg & set_sparam();
bool in_example(enum llama_example ex); bool in_example(enum llama_example ex);
bool is_exclude(enum llama_example ex);
bool get_value_from_env(std::string & output); bool get_value_from_env(std::string & output);
bool has_value_from_env(); bool has_value_from_env();
std::string to_string(); std::string to_string();
@ -75,3 +78,12 @@ bool common_params_parse(int argc, char ** argv, common_params & params, llama_e
// function to be used by test-arg-parser // function to be used by test-arg-parser
common_params_context common_params_parser_init(common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr); common_params_context common_params_parser_init(common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr);
bool common_has_curl();
struct common_remote_params {
std::vector<std::string> headers;
long timeout = 0; // CURLOPT_TIMEOUT, in seconds ; 0 means no timeout
long max_size = 0; // max size of the response ; unlimited if 0 ; max is 2GB
};
// get remote file content, returns <http_code, raw_response_body>
std::pair<long, std::vector<char>> common_remote_get_content(const std::string & url, const common_remote_params & params);

View File

@ -1,4 +1,4 @@
int LLAMA_BUILD_NUMBER = @BUILD_NUMBER@; int LLAMA_BUILD_NUMBER = @LLAMA_BUILD_NUMBER@;
char const *LLAMA_COMMIT = "@BUILD_COMMIT@"; char const *LLAMA_COMMIT = "@LLAMA_BUILD_COMMIT@";
char const *LLAMA_COMPILER = "@BUILD_COMPILER@"; char const *LLAMA_COMPILER = "@BUILD_COMPILER@";
char const *LLAMA_BUILD_TARGET = "@BUILD_TARGET@"; char const *LLAMA_BUILD_TARGET = "@BUILD_TARGET@";

385
common/chat-parser.cpp Normal file
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@ -0,0 +1,385 @@
#include "chat-parser.h"
#include "common.h"
#include "log.h"
#include "regex-partial.h"
#include <optional>
#include <stdexcept>
#include <string>
#include <vector>
using json = nlohmann::ordered_json;
common_chat_msg_parser::common_chat_msg_parser(const std::string & input, bool is_partial, const common_chat_syntax & syntax)
: input_(input), is_partial_(is_partial), syntax_(syntax)
{
result_.role = "assistant";
while (true) {
std::string id = std::to_string(std::rand());
if (input.find(id) == std::string::npos) {
healing_marker_ = id;
break;
}
}
}
std::string common_chat_msg_parser::str(const common_string_range & rng) const {
GGML_ASSERT(rng.begin <= rng.end);
return input_.substr(rng.begin, rng.end - rng.begin);
}
void common_chat_msg_parser::add_content(const std::string &content) {
result_.content += content;
}
void common_chat_msg_parser::add_reasoning_content(const std::string &reasoning_content) {
result_.reasoning_content += reasoning_content;
}
bool common_chat_msg_parser::add_tool_call(const std::string & name, const std::string & id, const std::string & arguments) {
if (name.empty()) {
return false;
}
common_chat_tool_call tool_call;
tool_call.name = name;
tool_call.arguments = arguments;
tool_call.id = id;
// LOG_DBG("Tool call arguments:\n\traw: %s\n\tresult: %s\n", arguments.c_str(), tool_call.arguments.c_str());
result_.tool_calls.emplace_back(tool_call);
return true;
}
bool common_chat_msg_parser::add_tool_call(const json & tool_call) {
std::string name = tool_call.contains("name") ? tool_call.at("name") : "";
std::string id = tool_call.contains("id") ? tool_call.at("id") : "";
std::string arguments = tool_call.contains("arguments") ? tool_call.at("arguments") : "";
return add_tool_call(name, id, arguments);
}
bool common_chat_msg_parser::add_tool_calls(const json & arr) {
for (const auto & item : arr) {
if (!add_tool_call(item)) {
return false;
}
}
return true;
}
void common_chat_msg_parser::finish() {
if (!is_partial_ && pos_ != input_.size()) {
throw std::runtime_error("Unexpected content at end of input");// + input_.substr(pos_));
}
}
bool common_chat_msg_parser::consume_spaces() {
const auto length = input_.size();
auto consumed = false;
while (pos_ < length && std::isspace(input_[pos_])) {
++pos_;
consumed = true;
}
return consumed;
}
bool common_chat_msg_parser::try_consume_literal(const std::string & literal) {
auto pos = pos_;
for (auto i = 0u; i < literal.size(); ++i) {
if (pos >= input_.size()) {
return false;
}
if (input_[pos] != literal[i]) {
return false;
}
++pos;
}
pos_ = pos;
return true;
}
std::optional<common_chat_msg_parser::find_regex_result> common_chat_msg_parser::try_find_literal(const std::string & literal) {
auto idx = input_.find(literal, pos_);
if (idx != std::string::npos) {
find_regex_result res;
res.prelude = input_.substr(pos_, idx - pos_);
auto end = idx + literal.size();
res.groups.emplace_back(common_string_range{idx, end});
move_to(end);
return res;
}
if (is_partial_) {
idx = string_find_partial_stop(input_, literal);
if (idx != std::string::npos && idx >= pos_) {
find_regex_result res;
res.prelude = input_.substr(pos_, idx - pos_);
auto end = input_.size();
res.groups.emplace_back(common_string_range{idx, end});
move_to(end);
return res;
}
}
return std::nullopt;
}
void common_chat_msg_parser::consume_literal(const std::string & literal) {
if (!try_consume_literal(literal)) {
throw common_chat_msg_partial_exception(literal);
}
}
bool common_chat_msg_parser::try_parse_reasoning(const std::string & start_think, const std::string & end_think) {
auto handle_reasoning = [&](const std::string & reasoning, bool closed) {
auto stripped_reasoning = string_strip(reasoning);
if (stripped_reasoning.empty()) {
return;
}
if (syntax_.reasoning_in_content) {
add_content(syntax_.reasoning_format == COMMON_REASONING_FORMAT_DEEPSEEK ? "<think>" : start_think);
add_content(stripped_reasoning);
if (closed) {
add_content(syntax_.reasoning_format == COMMON_REASONING_FORMAT_DEEPSEEK ? "</think>" : end_think);
}
} else {
add_reasoning_content(stripped_reasoning);
}
};
if (syntax_.reasoning_format != COMMON_REASONING_FORMAT_NONE) {
if (syntax_.thinking_forced_open || try_consume_literal(start_think)) {
if (auto res = try_find_literal(end_think)) {
handle_reasoning(res->prelude, /* closed */ true);
consume_spaces();
return true;
}
auto rest = consume_rest();
if (!rest.empty()) {
handle_reasoning(rest, /* closed */ !is_partial());
}
// Allow unclosed thinking tags, for now (https://github.com/ggml-org/llama.cpp/issues/13812, https://github.com/ggml-org/llama.cpp/issues/13877)
// if (!syntax_.thinking_forced_open) {
// throw common_chat_msg_partial_exception(end_think);
// }
return true;
}
}
return false;
}
std::string common_chat_msg_parser::consume_rest() {
auto rest = input_.substr(pos_);
pos_ = input_.size();
return rest;
}
// Tries to find the regex, consumes it (pos right after it) and gives the prelude (right before it) and the groups to the callback.
std::optional<common_chat_msg_parser::find_regex_result> common_chat_msg_parser::try_find_regex(const common_regex & regex, size_t from, bool add_prelude_to_content) {
auto m = regex.search(input_, from == std::string::npos ? pos_ : from);
if (m.type == COMMON_REGEX_MATCH_TYPE_NONE) {
return std::nullopt;
}
auto prelude = input_.substr(pos_, m.groups[0].begin - pos_);
pos_ = m.groups[0].end;
if (add_prelude_to_content) {
add_content(prelude);
}
if (m.type == COMMON_REGEX_MATCH_TYPE_PARTIAL) {
if (is_partial()) {
throw common_chat_msg_partial_exception(regex.str());
}
return std::nullopt;
}
return find_regex_result{prelude, m.groups};
}
common_chat_msg_parser::find_regex_result common_chat_msg_parser::consume_regex(const common_regex & regex) {
if (auto result = try_consume_regex(regex)) {
return *result;
}
throw common_chat_msg_partial_exception(regex.str());
}
std::optional<common_chat_msg_parser::find_regex_result> common_chat_msg_parser::try_consume_regex(const common_regex & regex) {
auto m = regex.search(input_, pos_);
if (m.type == COMMON_REGEX_MATCH_TYPE_NONE) {
return std::nullopt;
}
if (m.type == COMMON_REGEX_MATCH_TYPE_PARTIAL) {
if (is_partial()) {
throw common_chat_msg_partial_exception(regex.str());
}
return std::nullopt;
}
if (m.groups[0].begin != pos_) {
// Didn't match at the current position.
return std::nullopt;
}
pos_ = m.groups[0].end;
return find_regex_result {
/* .prelude = */ "",
m.groups,
};
}
std::optional<common_json> common_chat_msg_parser::try_consume_json() {
auto it = input_.cbegin() + pos_;
const auto end = input_.cend();
common_json result;
if (!common_json_parse(it, end, healing_marker_, result)) {
return std::nullopt;
}
pos_ = std::distance(input_.cbegin(), it);
if (result.healing_marker.marker.empty()) {
// No healing marker, just return the parsed json
return result;
}
if (!is_partial()) {
throw common_chat_msg_partial_exception("JSON");
}
return result;
}
common_json common_chat_msg_parser::consume_json() {
if (auto result = try_consume_json()) {
return *result;
}
throw common_chat_msg_partial_exception("JSON");
}
common_chat_msg_parser::consume_json_result common_chat_msg_parser::consume_json_with_dumped_args(
const std::vector<std::vector<std::string>> & args_paths,
const std::vector<std::vector<std::string>> & content_paths
) {
if (auto result = try_consume_json_with_dumped_args(args_paths, content_paths)) {
return *result;
}
throw common_chat_msg_partial_exception("JSON");
}
std::optional<common_chat_msg_parser::consume_json_result> common_chat_msg_parser::try_consume_json_with_dumped_args(
const std::vector<std::vector<std::string>> & args_paths,
const std::vector<std::vector<std::string>> & content_paths
) {
auto partial = try_consume_json();
if (!partial) {
return std::nullopt;
}
auto is_arguments_path = [&](const std::vector<std::string> & path) {
return std::find(args_paths.begin(), args_paths.end(), path) != args_paths.end();
};
auto is_content_path = [&](const std::vector<std::string> & path) {
return std::find(content_paths.begin(), content_paths.end(), path) != content_paths.end();
};
if (partial->healing_marker.marker.empty()) {
if (args_paths.empty()) {
// No arguments to dump, and JSON was parsed fully.
return consume_json_result {
partial->json,
/* .is_partial = */ false,
};
}
if (is_arguments_path({})) {
// Entire JSON is the arguments and was parsed fully.
return consume_json_result {
partial->json.dump(),
/* .is_partial = */ false,
};
}
}
LOG_DBG("Parsed partial JSON: %s (json_healing_marker: %s)\n", partial->json.dump().c_str(), partial->healing_marker.json_dump_marker.c_str());
auto found_healing_marker = false;
std::vector<std::string> path;
std::function<json(const json &)> remove_unsupported_healings_and_dump_args = [&](const json & j) -> json {
if (is_arguments_path(path)) {
auto arguments = j.dump();
if (is_partial() && !partial->healing_marker.marker.empty()) {
auto idx = arguments.find(partial->healing_marker.json_dump_marker);
if (idx != std::string::npos) {
arguments.resize(idx);
found_healing_marker = true;
}
if (arguments == "\"") {
// This happens because of completing `:"$magic` after `"arguments"`
arguments = "";
}
}
return arguments;
}
if (is_content_path(path)) {
if (!j.is_string()) {
throw std::runtime_error("Content path must be a string");
}
std::string str = j;
auto idx = str.find(partial->healing_marker.marker); // not using json_dump_marker as we're inside a string
if (idx != std::string::npos) {
str.resize(idx);
found_healing_marker = true;
}
return str;
}
if (j.is_object()) {
auto obj = json::object();
for (const auto & p : j.items()) {
const auto & key = p.key();
const auto & value = p.value();
const std::string key_str = key; // NOLINT
auto idx = key_str.find(healing_marker_);
if (idx != std::string::npos) {
found_healing_marker = true;
break;
}
path.push_back(key_str);
if (value.is_string()) {
const std::string value_str = value;
if (value_str.find(healing_marker_) != std::string::npos) {
found_healing_marker = true;
if (is_content_path(path)) {
if (partial->healing_marker.marker == partial->healing_marker.json_dump_marker) {
// The healing occurred inside the string: good. Otherwise we just ditch the entire key/value pair.
obj[key] = remove_unsupported_healings_and_dump_args(value);
}
}
break;
}
obj[key] = value;
} else {
obj[key] = remove_unsupported_healings_and_dump_args(value);
}
path.pop_back();
}
return obj;
}
if (j.is_array()) {
auto arr = json::array();
for (const auto & value : j) {
if (value.is_string()) {
std::string str = value;
auto idx = str.find(healing_marker_);
if (idx != std::string::npos) {
// Don't heal array values that aren't in the arguments.
found_healing_marker = true;
break;
}
}
arr.push_back(remove_unsupported_healings_and_dump_args(value));
}
return arr;
}
return j;
};
auto cleaned = remove_unsupported_healings_and_dump_args(partial->json);
LOG_DBG("Cleaned up JSON %s to %s (json_healing_marker : '%s')\n", partial->json.dump().c_str(), cleaned.dump().c_str(), partial->healing_marker.json_dump_marker.c_str());
return consume_json_result {
cleaned,
/* .is_partial = */ found_healing_marker,
};
}
void common_chat_msg_parser::clear_tools() {
result_.tool_calls.clear();
}

120
common/chat-parser.h Normal file
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@ -0,0 +1,120 @@
#pragma once
#include "chat.h"
#include "json-partial.h"
#include "regex-partial.h"
#include <nlohmann/json.hpp>
#include <optional>
#include <string>
#include <vector>
class common_chat_msg_partial_exception : public std::runtime_error {
public:
common_chat_msg_partial_exception(const std::string & message) : std::runtime_error(message) {}
};
class common_chat_msg_parser {
std::string input_;
bool is_partial_;
common_chat_syntax syntax_;
std::string healing_marker_;
size_t pos_ = 0;
common_chat_msg result_;
public:
common_chat_msg_parser(const std::string & input, bool is_partial, const common_chat_syntax & syntax);
const std::string & input() const { return input_; }
size_t pos() const { return pos_; }
const std::string & healing_marker() const { return healing_marker_; }
const bool & is_partial() const { return is_partial_; }
const common_chat_msg & result() const { return result_; }
const common_chat_syntax & syntax() const { return syntax_; }
void move_to(size_t pos) {
if (pos > input_.size()) {
throw std::runtime_error("Invalid position!");
}
pos_ = pos;
}
void move_back(size_t n) {
if (pos_ < n) {
throw std::runtime_error("Can't move back that far!");
}
pos_ -= n;
}
// Get the substring of the input at the given range
std::string str(const common_string_range & rng) const;
// Appends to the result.content field
void add_content(const std::string & content);
// Appends to the result.reasoning_content field
void add_reasoning_content(const std::string & reasoning_content);
// Adds a tool call to the result. If the tool call is too incomplete (e.g. name empty), it won't add anything.
bool add_tool_call(const std::string & name, const std::string & id, const std::string & arguments);
// Adds a tool call using the "name", "id" and "arguments" fields of the json object
bool add_tool_call(const nlohmann::ordered_json & tool_call);
// Adds an array of tool calls using their "name", "id" and "arguments" fields.
bool add_tool_calls(const nlohmann::ordered_json & arr);
void finish();
bool consume_spaces();
void consume_literal(const std::string & literal);
bool try_parse_reasoning(const std::string & start_think, const std::string & end_think);
std::string consume_rest();
struct find_regex_result {
std::string prelude;
std::vector<common_string_range> groups;
};
std::optional<find_regex_result> try_find_regex(const common_regex & regex, size_t from = std::string::npos, bool add_prelude_to_content = true);
bool try_consume_literal(const std::string & literal);
std::optional<find_regex_result> try_find_literal(const std::string & literal);
find_regex_result consume_regex(const common_regex & regex);
std::optional<find_regex_result> try_consume_regex(const common_regex & regex);
std::optional<common_json> try_consume_json();
common_json consume_json();
struct consume_json_result {
nlohmann::ordered_json value;
bool is_partial;
};
/*
Consume (possibly partial) json and converts specific subtrees to (possibly truncated) JSON strings.
By default, object keys can't be truncated, nor can string values (their corresponding key is removed,
e.g. `{"foo": "bar", "baz": "b` -> `{"foo": "bar"}`
But one can allow subpaths to be kept truncated, and possibly json-dumped to truncated json strings
- with `content_paths={{"foo"}}` -> `{"foo": "b` -> {"foo": "b"}`
- with `args_paths={{"foo"}}` -> `{"foo": {"b` -> `{"foo": "{b"}`
*/
consume_json_result consume_json_with_dumped_args(
const std::vector<std::vector<std::string>> & args_paths = {},
const std::vector<std::vector<std::string>> & content_paths = {}
);
std::optional<consume_json_result> try_consume_json_with_dumped_args(
const std::vector<std::vector<std::string>> & args_paths = {},
const std::vector<std::vector<std::string>> & content_paths = {}
);
void clear_tools();
};

1949
common/chat.cpp Normal file

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204
common/chat.h Normal file
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@ -0,0 +1,204 @@
// Chat support (incl. tool call grammar constraining & output parsing) w/ generic & custom template handlers.
#pragma once
#include "common.h"
#include <functional>
#include <chrono>
#include <string>
#include <vector>
#include <map>
struct common_chat_templates;
struct common_chat_tool_call {
std::string name;
std::string arguments;
std::string id;
bool operator==(const common_chat_tool_call & other) const {
return name == other.name && arguments == other.arguments && id == other.id;
}
};
struct common_chat_msg_content_part {
std::string type;
std::string text;
bool operator==(const common_chat_msg_content_part & other) const {
return type == other.type && text == other.text;
}
};
struct common_chat_msg {
std::string role;
std::string content;
std::vector<common_chat_msg_content_part> content_parts = {};
std::vector<common_chat_tool_call> tool_calls = {};
std::string reasoning_content;
std::string tool_name;
std::string tool_call_id;
template <class T> T to_json_oaicompat() const;
bool empty() const {
return content.empty() && content_parts.empty() && tool_calls.empty() && reasoning_content.empty() && tool_name.empty() && tool_call_id.empty();
}
void ensure_tool_call_ids_set(std::vector<std::string> & ids_cache, const std::function<std::string()> & gen_tool_call_id) {
for (auto i = 0u; i < tool_calls.size(); i++) {
if (ids_cache.size() <= i) {
auto id = tool_calls[i].id;
if (id.empty()) {
id = gen_tool_call_id();
}
ids_cache.push_back(id);
}
tool_calls[i].id = ids_cache[i];
}
}
bool operator==(const common_chat_msg & other) const {
return role == other.role
&& content == other.content
&& content_parts == other.content_parts
&& tool_calls == other.tool_calls
&& reasoning_content == other.reasoning_content
&& tool_name == other.tool_name
&& tool_call_id == other.tool_call_id;
}
bool operator!=(const common_chat_msg & other) const {
return !(*this == other);
}
};
struct common_chat_msg_diff {
std::string reasoning_content_delta;
std::string content_delta;
size_t tool_call_index = std::string::npos;
common_chat_tool_call tool_call_delta;
static std::vector<common_chat_msg_diff> compute_diffs(const common_chat_msg & previous_msg, const common_chat_msg & new_msg);
bool operator==(const common_chat_msg_diff & other) const {
return content_delta == other.content_delta
&& tool_call_index == other.tool_call_index
&& tool_call_delta == other.tool_call_delta;
}
};
struct common_chat_tool {
std::string name;
std::string description;
std::string parameters;
};
enum common_chat_tool_choice {
COMMON_CHAT_TOOL_CHOICE_AUTO,
COMMON_CHAT_TOOL_CHOICE_REQUIRED,
COMMON_CHAT_TOOL_CHOICE_NONE,
};
enum common_chat_format {
COMMON_CHAT_FORMAT_CONTENT_ONLY,
COMMON_CHAT_FORMAT_GENERIC,
COMMON_CHAT_FORMAT_MISTRAL_NEMO,
COMMON_CHAT_FORMAT_LLAMA_3_X,
COMMON_CHAT_FORMAT_LLAMA_3_X_WITH_BUILTIN_TOOLS,
COMMON_CHAT_FORMAT_DEEPSEEK_R1,
COMMON_CHAT_FORMAT_FIREFUNCTION_V2,
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2,
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1,
COMMON_CHAT_FORMAT_HERMES_2_PRO,
COMMON_CHAT_FORMAT_COMMAND_R7B,
COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats
};
struct common_chat_templates_inputs {
std::vector<common_chat_msg> messages;
std::string grammar;
std::string json_schema;
bool add_generation_prompt = true;
bool use_jinja = true;
// Parameters below only supported when use_jinja is true
std::vector<common_chat_tool> tools;
common_chat_tool_choice tool_choice = COMMON_CHAT_TOOL_CHOICE_AUTO;
bool parallel_tool_calls = false;
common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_NONE;
bool enable_thinking = true;
std::chrono::system_clock::time_point now = std::chrono::system_clock::now();
std::map<std::string, std::string> chat_template_kwargs;
};
struct common_chat_params {
common_chat_format format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
std::string prompt;
std::string grammar;
bool grammar_lazy = false;
bool thinking_forced_open = false;
std::vector<common_grammar_trigger> grammar_triggers;
std::vector<std::string> preserved_tokens;
std::vector<std::string> additional_stops;
};
struct common_chat_syntax {
common_chat_format format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_NONE;
// Whether reasoning_content should be inlined in the content (e.g. for reasoning_format=deepseek in stream mode)
bool reasoning_in_content = false;
bool thinking_forced_open = false;
bool parse_tool_calls = true;
};
// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
bool common_chat_verify_template(const std::string & tmpl, bool use_jinja);
void common_chat_templates_free(struct common_chat_templates * tmpls);
struct common_chat_templates_deleter { void operator()(common_chat_templates * tmpls) { common_chat_templates_free(tmpls); } };
typedef std::unique_ptr<struct common_chat_templates, common_chat_templates_deleter> common_chat_templates_ptr;
common_chat_templates_ptr common_chat_templates_init(
const struct llama_model * model,
const std::string & chat_template_override,
const std::string & bos_token_override = "",
const std::string & eos_token_override = "");
bool common_chat_templates_was_explicit(const struct common_chat_templates * tmpls);
const char * common_chat_templates_source(const struct common_chat_templates * tmpls, const char * variant = nullptr);
struct common_chat_params common_chat_templates_apply(
const struct common_chat_templates * tmpls,
const struct common_chat_templates_inputs & inputs);
// Format single message, while taking into account the position of that message in chat history
std::string common_chat_format_single(
const struct common_chat_templates * tmpls,
const std::vector<common_chat_msg> & past_msg,
const common_chat_msg & new_msg,
bool add_ass,
bool use_jinja);
// Returns an example of formatted chat
std::string common_chat_format_example(
const struct common_chat_templates * tmpls,
bool use_jinja);
const char* common_chat_format_name(common_chat_format format);
const char* common_reasoning_format_name(common_reasoning_format format);
common_chat_msg common_chat_parse(const std::string & input, bool is_partial, const common_chat_syntax & syntax);
common_chat_tool_choice common_chat_tool_choice_parse_oaicompat(const std::string & tool_choice);
// Parses a JSON array of messages in OpenAI's chat completion API format.
// T can be std::string containing JSON or nlohmann::ordered_json
template <class T> std::vector<common_chat_msg> common_chat_msgs_parse_oaicompat(const T & messages);
template <class T> T common_chat_msgs_to_json_oaicompat(const std::vector<common_chat_msg> & msgs, bool concat_typed_text = false);
// Parses a JSON array of tools in OpenAI's chat completion tool call API format.
// T can be std::string containing JSON or nlohmann::ordered_json
template <class T> std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const T & tools);
template <class T> T common_chat_tools_to_json_oaicompat(const std::vector<common_chat_tool> & tools);
template <class T> T common_chat_msg_diff_to_json_oaicompat(const common_chat_msg_diff & diff);

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@ -1,24 +0,0 @@
include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)
set(TEMPLATE_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp.in")
set(OUTPUT_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp")
# Only write the build info if it changed
if(EXISTS ${OUTPUT_FILE})
file(READ ${OUTPUT_FILE} CONTENTS)
string(REGEX MATCH "LLAMA_COMMIT = \"([^\"]*)\";" _ ${CONTENTS})
set(OLD_COMMIT ${CMAKE_MATCH_1})
string(REGEX MATCH "LLAMA_COMPILER = \"([^\"]*)\";" _ ${CONTENTS})
set(OLD_COMPILER ${CMAKE_MATCH_1})
string(REGEX MATCH "LLAMA_BUILD_TARGET = \"([^\"]*)\";" _ ${CONTENTS})
set(OLD_TARGET ${CMAKE_MATCH_1})
if (
NOT OLD_COMMIT STREQUAL BUILD_COMMIT OR
NOT OLD_COMPILER STREQUAL BUILD_COMPILER OR
NOT OLD_TARGET STREQUAL BUILD_TARGET
)
configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
endif()
else()
configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
endif()

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@ -2,10 +2,13 @@
#pragma once #pragma once
#include "llama.h" #include "llama-cpp.h"
#include <set>
#include <string> #include <string>
#include <string_view>
#include <vector> #include <vector>
#include <map>
#include <sstream> #include <sstream>
#ifdef _WIN32 #ifdef _WIN32
@ -24,20 +27,20 @@
#define DEFAULT_MODEL_PATH "models/7B/ggml-model-f16.gguf" #define DEFAULT_MODEL_PATH "models/7B/ggml-model-f16.gguf"
struct common_lora_adapter_info { struct common_adapter_lora_info {
std::string path; std::string path;
float scale; float scale;
struct llama_adapter_lora * ptr;
}; };
struct common_lora_adapter_container : common_lora_adapter_info { using llama_tokens = std::vector<llama_token>;
struct llama_lora_adapter * adapter;
};
// build info // build info
extern int LLAMA_BUILD_NUMBER; extern int LLAMA_BUILD_NUMBER;
extern char const * LLAMA_COMMIT; extern const char * LLAMA_COMMIT;
extern char const * LLAMA_COMPILER; extern const char * LLAMA_COMPILER;
extern char const * LLAMA_BUILD_TARGET; extern const char * LLAMA_BUILD_TARGET;
struct common_control_vector_load_info; struct common_control_vector_load_info;
@ -65,7 +68,6 @@ enum llama_example {
LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_COMMON,
LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SPECULATIVE,
LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_MAIN,
LLAMA_EXAMPLE_INFILL,
LLAMA_EXAMPLE_EMBEDDING, LLAMA_EXAMPLE_EMBEDDING,
LLAMA_EXAMPLE_PERPLEXITY, LLAMA_EXAMPLE_PERPLEXITY,
LLAMA_EXAMPLE_RETRIEVAL, LLAMA_EXAMPLE_RETRIEVAL,
@ -75,9 +77,10 @@ enum llama_example {
LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_SERVER,
LLAMA_EXAMPLE_CVECTOR_GENERATOR, LLAMA_EXAMPLE_CVECTOR_GENERATOR,
LLAMA_EXAMPLE_EXPORT_LORA, LLAMA_EXAMPLE_EXPORT_LORA,
LLAMA_EXAMPLE_LLAVA, LLAMA_EXAMPLE_MTMD,
LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_LOOKUP,
LLAMA_EXAMPLE_PARALLEL, LLAMA_EXAMPLE_PARALLEL,
LLAMA_EXAMPLE_TTS,
LLAMA_EXAMPLE_COUNT, LLAMA_EXAMPLE_COUNT,
}; };
@ -93,6 +96,8 @@ enum common_sampler_type {
COMMON_SAMPLER_TYPE_TEMPERATURE = 7, COMMON_SAMPLER_TYPE_TEMPERATURE = 7,
COMMON_SAMPLER_TYPE_XTC = 8, COMMON_SAMPLER_TYPE_XTC = 8,
COMMON_SAMPLER_TYPE_INFILL = 9, COMMON_SAMPLER_TYPE_INFILL = 9,
COMMON_SAMPLER_TYPE_PENALTIES = 10,
COMMON_SAMPLER_TYPE_TOP_N_SIGMA = 11,
}; };
// dimensionality reduction methods, used by cvector-generator // dimensionality reduction methods, used by cvector-generator
@ -101,8 +106,27 @@ enum dimre_method {
DIMRE_METHOD_MEAN, DIMRE_METHOD_MEAN,
}; };
// sampler parameters enum common_conversation_mode {
struct common_sampler_params { COMMON_CONVERSATION_MODE_DISABLED = 0,
COMMON_CONVERSATION_MODE_ENABLED = 1,
COMMON_CONVERSATION_MODE_AUTO = 2,
};
enum common_grammar_trigger_type {
COMMON_GRAMMAR_TRIGGER_TYPE_TOKEN,
COMMON_GRAMMAR_TRIGGER_TYPE_WORD,
COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN,
COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN_FULL,
};
struct common_grammar_trigger {
common_grammar_trigger_type type;
std::string value;
llama_token token = LLAMA_TOKEN_NULL;
};
// sampling parameters
struct common_params_sampling {
uint32_t seed = LLAMA_DEFAULT_SEED; // the seed used to initialize llama_sampler uint32_t seed = LLAMA_DEFAULT_SEED; // the seed used to initialize llama_sampler
int32_t n_prev = 64; // number of previous tokens to remember int32_t n_prev = 64; // number of previous tokens to remember
@ -126,17 +150,20 @@ struct common_sampler_params {
int32_t dry_allowed_length = 2; // tokens extending repetitions beyond this receive penalty int32_t dry_allowed_length = 2; // tokens extending repetitions beyond this receive penalty
int32_t dry_penalty_last_n = -1; // how many tokens to scan for repetitions (0 = disable penalty, -1 = context size) int32_t dry_penalty_last_n = -1; // how many tokens to scan for repetitions (0 = disable penalty, -1 = context size)
int32_t mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0 int32_t mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0
float top_n_sigma = -1.00f;// -1.0 = disabled
float mirostat_tau = 5.00f; // target entropy float mirostat_tau = 5.00f; // target entropy
float mirostat_eta = 0.10f; // learning rate float mirostat_eta = 0.10f; // learning rate
bool penalize_nl = false; // consider newlines as a repeatable token
bool ignore_eos = false; bool ignore_eos = false;
bool no_perf = false; // disable performance metrics bool no_perf = false; // disable performance metrics
bool timing_per_token = false;
std::vector<std::string> dry_sequence_breakers = {"\n", ":", "\"", "*"}; // default sequence breakers for DRY std::vector<std::string> dry_sequence_breakers = {"\n", ":", "\"", "*"}; // default sequence breakers for DRY
std::vector<enum common_sampler_type> samplers = { std::vector<enum common_sampler_type> samplers = {
COMMON_SAMPLER_TYPE_PENALTIES,
COMMON_SAMPLER_TYPE_DRY, COMMON_SAMPLER_TYPE_DRY,
COMMON_SAMPLER_TYPE_TOP_N_SIGMA,
COMMON_SAMPLER_TYPE_TOP_K, COMMON_SAMPLER_TYPE_TOP_K,
COMMON_SAMPLER_TYPE_TYPICAL_P, COMMON_SAMPLER_TYPE_TYPICAL_P,
COMMON_SAMPLER_TYPE_TOP_P, COMMON_SAMPLER_TYPE_TOP_P,
@ -145,7 +172,10 @@ struct common_sampler_params {
COMMON_SAMPLER_TYPE_TEMPERATURE, COMMON_SAMPLER_TYPE_TEMPERATURE,
}; };
std::string grammar; // optional BNF-like grammar to constrain sampling std::string grammar; // optional BNF-like grammar to constrain sampling
bool grammar_lazy = false;
std::vector<common_grammar_trigger> grammar_triggers; // optional triggers (for lazy grammars)
std::set<llama_token> preserved_tokens;
std::vector<llama_logit_bias> logit_bias; // logit biases to apply std::vector<llama_logit_bias> logit_bias; // logit biases to apply
@ -153,21 +183,55 @@ struct common_sampler_params {
std::string print() const; std::string print() const;
}; };
struct common_params_model {
std::string path = ""; // model local path // NOLINT
std::string url = ""; // model url to download // NOLINT
std::string hf_repo = ""; // HF repo // NOLINT
std::string hf_file = ""; // HF file // NOLINT
};
struct common_params_speculative {
std::vector<ggml_backend_dev_t> devices; // devices to use for offloading
int32_t n_ctx = 0; // draft context size
int32_t n_max = 16; // maximum number of tokens to draft during speculative decoding
int32_t n_min = 0; // minimum number of draft tokens to use for speculative decoding
int32_t n_gpu_layers = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
float p_split = 0.1f; // speculative decoding split probability
float p_min = 0.75f; // minimum speculative decoding probability (greedy)
ggml_type cache_type_k = GGML_TYPE_F16; // KV cache data type for the K
ggml_type cache_type_v = GGML_TYPE_F16; // KV cache data type for the V
struct cpu_params cpuparams;
struct cpu_params cpuparams_batch;
struct common_params_model model;
};
struct common_params_vocoder {
struct common_params_model model;
std::string speaker_file = ""; // speaker file path // NOLINT
bool use_guide_tokens = false; // enable guide tokens to improve TTS accuracy // NOLINT
};
enum common_reasoning_format {
COMMON_REASONING_FORMAT_NONE,
COMMON_REASONING_FORMAT_DEEPSEEK_LEGACY, // Extract thinking tag contents and return as `message.reasoning_content`, or leave inline in <think> tags in stream mode
COMMON_REASONING_FORMAT_DEEPSEEK, // Extract thinking tag contents and return as `message.reasoning_content`, including in streaming deltas.
};
struct common_params { struct common_params {
int32_t n_predict = -1; // new tokens to predict int32_t n_predict = -1; // new tokens to predict
int32_t n_ctx = 4096; // context size int32_t n_ctx = 4096; // context size
int32_t n_batch = 2048; // logical batch size for prompt processing (must be >=32 to use BLAS) int32_t n_batch = 2048; // logical batch size for prompt processing (must be >=32 to use BLAS)
int32_t n_ubatch = 512; // physical batch size for prompt processing (must be >=32 to use BLAS) int32_t n_ubatch = 512; // physical batch size for prompt processing (must be >=32 to use BLAS)
int32_t n_keep = 0; // number of tokens to keep from initial prompt int32_t n_keep = 0; // number of tokens to keep from initial prompt
int32_t n_draft = 5; // number of tokens to draft during speculative decoding
int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited) int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
int32_t n_parallel = 1; // number of parallel sequences to decode int32_t n_parallel = 1; // number of parallel sequences to decode
int32_t n_sequences = 1; // number of sequences to decode int32_t n_sequences = 1; // number of sequences to decode
float p_split = 0.1f; // speculative decoding split probability
int32_t n_gpu_layers = -1; // number of layers to store in VRAM (-1 - use default)
int32_t n_gpu_layers_draft = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
float tensor_split[128] = {0}; // how split tensors should be distributed across GPUs
int32_t grp_attn_n = 1; // group-attention factor int32_t grp_attn_n = 1; // group-attention factor
int32_t grp_attn_w = 512; // group-attention width int32_t grp_attn_w = 512; // group-attention width
int32_t n_print = -1; // print token count every n tokens (-1 = disabled) int32_t n_print = -1; // print token count every n tokens (-1 = disabled)
@ -180,31 +244,37 @@ struct common_params {
int32_t yarn_orig_ctx = 0; // YaRN original context length int32_t yarn_orig_ctx = 0; // YaRN original context length
float defrag_thold = 0.1f; // KV cache defragmentation threshold float defrag_thold = 0.1f; // KV cache defragmentation threshold
// offload params
std::vector<ggml_backend_dev_t> devices; // devices to use for offloading
int32_t n_gpu_layers = -1; // number of layers to store in VRAM (-1 - use default)
int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
float tensor_split[128] = {0}; // how split tensors should be distributed across GPUs
enum llama_split_mode split_mode = LLAMA_SPLIT_MODE_LAYER; // how to split the model across GPUs
struct cpu_params cpuparams; struct cpu_params cpuparams;
struct cpu_params cpuparams_batch; struct cpu_params cpuparams_batch;
struct cpu_params draft_cpuparams;
struct cpu_params draft_cpuparams_batch;
ggml_backend_sched_eval_callback cb_eval = nullptr; ggml_backend_sched_eval_callback cb_eval = nullptr;
void * cb_eval_user_data = nullptr; void * cb_eval_user_data = nullptr;
ggml_numa_strategy numa = GGML_NUMA_STRATEGY_DISABLED; ggml_numa_strategy numa = GGML_NUMA_STRATEGY_DISABLED;
enum llama_split_mode split_mode = LLAMA_SPLIT_MODE_LAYER; // how to split the model across GPUs
enum llama_rope_scaling_type rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_UNSPECIFIED; enum llama_rope_scaling_type rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_UNSPECIFIED;
enum llama_pooling_type pooling_type = LLAMA_POOLING_TYPE_UNSPECIFIED; // pooling type for embeddings enum llama_pooling_type pooling_type = LLAMA_POOLING_TYPE_UNSPECIFIED; // pooling type for embeddings
enum llama_attention_type attention_type = LLAMA_ATTENTION_TYPE_UNSPECIFIED; // attention type for embeddings enum llama_attention_type attention_type = LLAMA_ATTENTION_TYPE_UNSPECIFIED; // attention type for embeddings
struct common_sampler_params sparams; struct common_params_sampling sampling;
struct common_params_speculative speculative;
struct common_params_vocoder vocoder;
std::string model = ""; // model path // NOLINT struct common_params_model model;
std::string model_draft = ""; // draft model for speculative decoding // NOLINT
std::string model_alias = "unknown"; // model alias // NOLINT std::string model_alias = ""; // model alias // NOLINT
std::string model_url = ""; // model url to download // NOLINT
std::string hf_token = ""; // HF token // NOLINT std::string hf_token = ""; // HF token // NOLINT
std::string hf_repo = ""; // HF repo // NOLINT
std::string hf_file = ""; // HF file // NOLINT
std::string prompt = ""; // NOLINT std::string prompt = ""; // NOLINT
std::string system_prompt = ""; // NOLINT
std::string prompt_file = ""; // store the external prompt file name // NOLINT std::string prompt_file = ""; // store the external prompt file name // NOLINT
std::string path_prompt_cache = ""; // path to file for saving/loading prompt eval state // NOLINT std::string path_prompt_cache = ""; // path to file for saving/loading prompt eval state // NOLINT
std::string input_prefix = ""; // string to prefix user inputs with // NOLINT std::string input_prefix = ""; // string to prefix user inputs with // NOLINT
@ -212,20 +282,21 @@ struct common_params {
std::string lookup_cache_static = ""; // path of static ngram cache file for lookup decoding // NOLINT std::string lookup_cache_static = ""; // path of static ngram cache file for lookup decoding // NOLINT
std::string lookup_cache_dynamic = ""; // path of dynamic ngram cache file for lookup decoding // NOLINT std::string lookup_cache_dynamic = ""; // path of dynamic ngram cache file for lookup decoding // NOLINT
std::string logits_file = ""; // file for saving *all* logits // NOLINT std::string logits_file = ""; // file for saving *all* logits // NOLINT
std::string rpc_servers = ""; // comma separated list of RPC servers // NOLINT
std::vector<std::string> in_files; // all input files std::vector<std::string> in_files; // all input files
std::vector<std::string> antiprompt; // strings upon which more user input is prompted (a.k.a. reverse prompts) std::vector<std::string> antiprompt; // strings upon which more user input is prompted (a.k.a. reverse prompts)
std::vector<llama_model_kv_override> kv_overrides; std::vector<llama_model_kv_override> kv_overrides;
std::vector<llama_model_tensor_buft_override> tensor_buft_overrides;
bool lora_init_without_apply = false; // only load lora to memory, but do not apply it to ctx (user can manually apply lora later using llama_lora_adapter_apply) bool lora_init_without_apply = false; // only load lora to memory, but do not apply it to ctx (user can manually apply lora later using llama_adapter_lora_apply)
std::vector<common_lora_adapter_info> lora_adapters; // lora adapter path with user defined scale std::vector<common_adapter_lora_info> lora_adapters; // lora adapter path with user defined scale
std::vector<common_control_vector_load_info> control_vectors; // control vector with user defined scale std::vector<common_control_vector_load_info> control_vectors; // control vector with user defined scale
int32_t verbosity = 0; int32_t verbosity = 0;
int32_t control_vector_layer_start = -1; // layer range for control vector int32_t control_vector_layer_start = -1; // layer range for control vector
int32_t control_vector_layer_end = -1; // layer range for control vector int32_t control_vector_layer_end = -1; // layer range for control vector
bool offline = false;
int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used.
int32_t ppl_output_type = 0; // = 0 -> ppl output is as usual, = 1 -> ppl output is num_tokens, ppl, one per line int32_t ppl_output_type = 0; // = 0 -> ppl output is as usual, = 1 -> ppl output is num_tokens, ppl, one per line
@ -243,11 +314,11 @@ struct common_params {
bool kl_divergence = false; // compute KL divergence bool kl_divergence = false; // compute KL divergence
bool usage = false; // print usage bool usage = false; // print usage
bool completion = false; // print source-able completion script
bool use_color = false; // use color to distinguish generations and inputs bool use_color = false; // use color to distinguish generations and inputs
bool special = false; // enable special token output bool special = false; // enable special token output
bool interactive = false; // interactive mode bool interactive = false; // interactive mode
bool interactive_first = false; // wait for user input immediately bool interactive_first = false; // wait for user input immediately
bool conversation = false; // conversation mode (does not print special tokens and suffix/prefix)
bool prompt_cache_all = false; // save user input and generations to prompt cache bool prompt_cache_all = false; // save user input and generations to prompt cache
bool prompt_cache_ro = false; // open the prompt cache read-only and do not update it bool prompt_cache_ro = false; // open the prompt cache read-only and do not update it
@ -258,23 +329,29 @@ struct common_params {
bool flash_attn = false; // flash attention bool flash_attn = false; // flash attention
bool no_perf = false; // disable performance metrics bool no_perf = false; // disable performance metrics
bool ctx_shift = true; // context shift on inifinite text generation bool ctx_shift = true; // context shift on inifinite text generation
bool swa_full = false; // use full-size SWA cache (https://github.com/ggml-org/llama.cpp/pull/13194#issuecomment-2868343055)
bool input_prefix_bos = false; // prefix BOS to user inputs, preceding input_prefix bool input_prefix_bos = false; // prefix BOS to user inputs, preceding input_prefix
bool logits_all = false; // return logits for all tokens in the batch
bool use_mmap = true; // use mmap for faster loads bool use_mmap = true; // use mmap for faster loads
bool use_mlock = false; // use mlock to keep model in memory bool use_mlock = false; // use mlock to keep model in memory
bool verbose_prompt = false; // print prompt tokens before generation bool verbose_prompt = false; // print prompt tokens before generation
bool display_prompt = true; // print prompt before generation bool display_prompt = true; // print prompt before generation
bool dump_kv_cache = false; // dump the KV cache contents for debugging purposes
bool no_kv_offload = false; // disable KV offloading bool no_kv_offload = false; // disable KV offloading
bool warmup = true; // warmup run bool warmup = true; // warmup run
bool check_tensors = false; // validate tensor data bool check_tensors = false; // validate tensor data
bool no_op_offload = false; // globally disable offload host tensor operations to device
std::string cache_type_k = "f16"; // KV cache data type for the K bool single_turn = false; // single turn chat conversation
std::string cache_type_v = "f16"; // KV cache data type for the V
// multimodal models (see examples/llava) ggml_type cache_type_k = GGML_TYPE_F16; // KV cache data type for the K
std::string mmproj = ""; // path to multimodal projector // NOLINT ggml_type cache_type_v = GGML_TYPE_F16; // KV cache data type for the V
common_conversation_mode conversation_mode = COMMON_CONVERSATION_MODE_AUTO;
// multimodal models (see tools/mtmd)
struct common_params_model mmproj;
bool mmproj_use_gpu = true; // use GPU for multimodal model
bool no_mmproj = false; // explicitly disable multimodal model
std::vector<std::string> image; // path to image file(s) std::vector<std::string> image; // path to image file(s)
// embedding // embedding
@ -282,7 +359,7 @@ struct common_params {
int32_t embd_normalize = 2; // normalisation for embeddings (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm) int32_t embd_normalize = 2; // normalisation for embeddings (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)
std::string embd_out = ""; // empty = default, "array" = [[],[]...], "json" = openai style, "json+" = same "json" + cosine similarity matrix std::string embd_out = ""; // empty = default, "array" = [[],[]...], "json" = openai style, "json+" = same "json" + cosine similarity matrix
std::string embd_sep = "\n"; // separator of embeddings std::string embd_sep = "\n"; // separator of embeddings
bool reranking = false; // enable reranking support on server std::string cls_sep = "\t"; // separator of classification sequences
// server params // server params
int32_t port = 8080; // server listens on this network port int32_t port = 8080; // server listens on this network port
@ -294,13 +371,19 @@ struct common_params {
std::string hostname = "127.0.0.1"; std::string hostname = "127.0.0.1";
std::string public_path = ""; // NOLINT std::string public_path = ""; // NOLINT
std::string chat_template = ""; // NOLINT std::string chat_template = ""; // NOLINT
bool use_jinja = false; // NOLINT
bool enable_chat_template = true; bool enable_chat_template = true;
common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_DEEPSEEK;
int reasoning_budget = -1;
bool prefill_assistant = true; // if true, any trailing assistant message will be prefilled into the response
std::vector<std::string> api_keys; std::vector<std::string> api_keys;
std::string ssl_file_key = ""; // NOLINT std::string ssl_file_key = ""; // NOLINT
std::string ssl_file_cert = ""; // NOLINT std::string ssl_file_cert = ""; // NOLINT
std::map<std::string, std::string> default_template_kwargs;
// "advanced" endpoints are disabled by default for better security // "advanced" endpoints are disabled by default for better security
bool webui = true; bool webui = true;
bool endpoint_slots = false; bool endpoint_slots = false;
@ -332,29 +415,33 @@ struct common_params {
int32_t i_pos = -1; // position of the passkey in the junk text int32_t i_pos = -1; // position of the passkey in the junk text
// imatrix params // imatrix params
std::string out_file = "imatrix.dat"; // save the resulting imatrix to this file
int32_t n_out_freq = 10; // output the imatrix every n_out_freq iterations int32_t n_out_freq = 10; // output the imatrix every n_out_freq iterations
int32_t n_save_freq = 0; // save the imatrix every n_save_freq iterations int32_t n_save_freq = 0; // save the imatrix every n_save_freq iterations
int32_t i_chunk = 0; // start processing from this chunk int32_t i_chunk = 0; // start processing from this chunk
bool process_output = false; // collect data for the output tensor bool process_output = false; // collect data for the output tensor
bool compute_ppl = true; // whether to compute perplexity bool compute_ppl = true; // whether to compute perplexity
bool parse_special = false; // whether to parse special tokens during imatrix tokenization
// cvector-generator params // cvector-generator params
int n_pca_batch = 100; int n_pca_batch = 100;
int n_pca_iterations = 1000; int n_pca_iterations = 1000;
dimre_method cvector_dimre_method = DIMRE_METHOD_PCA; dimre_method cvector_dimre_method = DIMRE_METHOD_PCA;
std::string cvector_outfile = "control_vector.gguf"; std::string cvector_positive_file = "tools/cvector-generator/positive.txt";
std::string cvector_positive_file = "examples/cvector-generator/positive.txt"; std::string cvector_negative_file = "tools/cvector-generator/negative.txt";
std::string cvector_negative_file = "examples/cvector-generator/negative.txt";
bool spm_infill = false; // suffix/prefix/middle pattern for infill bool spm_infill = false; // suffix/prefix/middle pattern for infill
std::string lora_outfile = "ggml-lora-merged-f16.gguf";
// batched-bench params // batched-bench params
bool batched_bench_output_jsonl = false; bool batched_bench_output_jsonl = false;
// common params
std::string out_file; // output filename for all example programs
// optional callback for model loading progress and cancellation:
// called with a progress value between 0.0 and 1.0.
// 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;
}; };
// call once at the start of a program if it uses libcommon // call once at the start of a program if it uses libcommon
@ -373,13 +460,13 @@ bool set_process_priority(enum ggml_sched_priority prio);
// //
#ifdef __GNUC__ #ifdef __GNUC__
#ifdef __MINGW32__ # if defined(__MINGW32__) && !defined(__clang__)
#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(gnu_printf, __VA_ARGS__))) # define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(gnu_printf, __VA_ARGS__)))
# else
# define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__)))
# endif
#else #else
#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__))) # define LLAMA_COMMON_ATTRIBUTE_FORMAT(...)
#endif
#else
#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...)
#endif #endif
LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2) LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2)
@ -388,8 +475,14 @@ std::string string_format(const char * fmt, ...);
std::string string_strip(const std::string & str); std::string string_strip(const std::string & str);
std::string string_get_sortable_timestamp(); std::string string_get_sortable_timestamp();
std::string string_join(const std::vector<std::string> & values, const std::string & separator);
std::vector<std::string> string_split(const std::string & str, const std::string & delimiter);
std::string string_repeat(const std::string & str, size_t n);
void string_replace_all(std::string & s, const std::string & search, const std::string & replace); void string_replace_all(std::string & s, const std::string & search, const std::string & replace);
std::string regex_escape(const std::string & s);
template<class T> template<class T>
static std::vector<T> string_split(const std::string & str, char delim) { static std::vector<T> string_split(const std::string & str, char delim) {
static_assert(!std::is_same<T, std::string>::value, "Please use the specialized version for std::string"); static_assert(!std::is_same<T, std::string>::value, "Please use the specialized version for std::string");
@ -421,6 +514,15 @@ std::vector<std::string> string_split<std::string>(const std::string & input, ch
return parts; return parts;
} }
static bool string_starts_with(const std::string & str,
const std::string & prefix) { // While we wait for C++20's std::string::starts_with...
return str.rfind(prefix, 0) == 0;
}
// While we wait for C++20's std::string::ends_with...
bool string_ends_with(const std::string_view & str, const std::string_view & suffix);
size_t string_find_partial_stop(const std::string_view & str, const std::string_view & stop);
bool string_parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides); bool string_parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides);
void string_process_escapes(std::string & input); void string_process_escapes(std::string & input);
@ -443,25 +545,28 @@ std::string fs_get_cache_file(const std::string & filename);
// Model utils // Model utils
// //
// note: defines object's lifetime
struct common_init_result { struct common_init_result {
struct llama_model * model = nullptr; llama_model_ptr model;
struct llama_context * context = nullptr; llama_context_ptr context;
std::vector<common_lora_adapter_container> lora_adapters;
std::vector<llama_adapter_lora_ptr> lora;
}; };
struct common_init_result common_init_from_params(common_params & params); struct common_init_result common_init_from_params(common_params & params);
struct llama_model_params common_model_params_to_llama (const common_params & params); struct llama_model_params common_model_params_to_llama ( common_params & params);
struct llama_context_params common_context_params_to_llama(const common_params & params); struct llama_context_params common_context_params_to_llama(const common_params & params);
struct ggml_threadpool_params ggml_threadpool_params_from_cpu_params(const cpu_params & params); struct ggml_threadpool_params ggml_threadpool_params_from_cpu_params(const cpu_params & params);
struct llama_model * common_load_model_from_url(const char * model_url, const char * path_model, const char * hf_token, const struct llama_model_params & params);
struct llama_model * common_load_model_from_hf(const char * repo, const char * file, const char * path_model, const char * hf_token, const struct llama_model_params & params);
// clear LoRA adapters from context, then apply new list of adapters // clear LoRA adapters from context, then apply new list of adapters
void common_lora_adapters_apply(struct llama_context * ctx, std::vector<common_lora_adapter_container> & lora_adapters); void common_set_adapter_lora(struct llama_context * ctx, std::vector<common_adapter_lora_info> & lora);
std::string get_model_endpoint();
//
// Batch utils // Batch utils
//
void common_batch_clear(struct llama_batch & batch); void common_batch_clear(struct llama_batch & batch);
@ -472,6 +577,16 @@ void common_batch_add(
const std::vector<llama_seq_id> & seq_ids, const std::vector<llama_seq_id> & seq_ids,
bool logits); bool logits);
//
// Token utils
//
// longest common prefix
size_t common_lcp(const llama_tokens & a, const llama_tokens & b);
// longet common subsequence
size_t common_lcs(const llama_tokens & a, const llama_tokens & b);
// //
// Vocab utils // Vocab utils
// //
@ -485,7 +600,7 @@ std::vector<llama_token> common_tokenize(
bool parse_special = false); bool parse_special = false);
std::vector<llama_token> common_tokenize( std::vector<llama_token> common_tokenize(
const struct llama_model * model, const struct llama_vocab * vocab,
const std::string & text, const std::string & text,
bool add_special, bool add_special,
bool parse_special = false); bool parse_special = false);
@ -497,61 +612,30 @@ std::string common_token_to_piece(
llama_token token, llama_token token,
bool special = true); bool special = true);
std::string common_token_to_piece(
const struct llama_vocab * vocab,
llama_token token,
bool special = true);
// detokenizes a vector of tokens into a string // detokenizes a vector of tokens into a string
// should work similar to Python's `tokenizer.decode` // should work similar to Python's `tokenizer.decode`
// optionally renders special/control tokens // optionally renders special/control tokens
std::string common_detokenize( std::string common_detokenize(
llama_context * ctx, const struct llama_context * ctx,
const std::vector<llama_token> & tokens, const std::vector<llama_token> & tokens,
bool special = true); bool special = true);
// std::string common_detokenize(
// Chat template utils const struct llama_vocab * vocab,
// const std::vector<llama_token> & tokens,
bool special = true);
// same with llama_chat_message, but uses std::string
struct common_chat_msg {
std::string role;
std::string content;
};
// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
bool common_chat_verify_template(const std::string & tmpl);
// CPP wrapper for llama_chat_apply_template
// If the built-in template is not supported, we default to chatml
// If the custom "tmpl" is not supported, we throw an error
std::string common_chat_apply_template(const struct llama_model * model,
const std::string & tmpl,
const std::vector<common_chat_msg> & chat,
bool add_ass);
// Format single message, while taking into account the position of that message in chat history
std::string common_chat_format_single(const struct llama_model * model,
const std::string & tmpl,
const std::vector<common_chat_msg> & past_msg,
const common_chat_msg & new_msg,
bool add_ass);
// Returns an example of formatted chat
std::string common_chat_format_example(const struct llama_model * model,
const std::string & tmpl);
//
// KV cache utils
//
// Dump the KV cache view with the number of sequences per cell.
void common_kv_cache_dump_view(const llama_kv_cache_view & view, int row_size = 80);
// Dump the KV cache view showing individual sequences in each cell (long output).
void common_kv_cache_dump_view_seqs(const llama_kv_cache_view & view, int row_size = 40);
// //
// Embedding utils // Embedding utils
// //
void common_embd_normalize(const float * inp, float * out, int n, int embd_norm = 2); // TODO: repace embd_norm with an enum
void common_embd_normalize(const float * inp, float * out, int n, int embd_norm);
float common_embd_similarity_cos(const float * embd1, const float * embd2, int n); float common_embd_similarity_cos(const float * embd1, const float * embd2, int n);
@ -580,6 +664,16 @@ common_control_vector_data common_control_vector_load(const std::vector<common_c
// Split utils // Split utils
// //
static const char * const LLM_KV_SPLIT_NO = "split.no"; namespace {
static const char * const LLM_KV_SPLIT_COUNT = "split.count";
static const char * const LLM_KV_SPLIT_TENSORS_COUNT = "split.tensors.count"; const char * const LLM_KV_SPLIT_NO = "split.no";
const char * const LLM_KV_SPLIT_COUNT = "split.count";
const char * const LLM_KV_SPLIT_TENSORS_COUNT = "split.tensors.count";
}
//
// training utils
//
ggml_opt_dataset_t common_opt_dataset_init(struct llama_context * ctx, const std::vector<llama_token> & tokens, int64_t stride);

256
common/json-partial.cpp Normal file
View File

@ -0,0 +1,256 @@
#include "json-partial.h"
#include "log.h"
#include <nlohmann/json.hpp>
#include <string>
using json = nlohmann::ordered_json;
enum common_json_stack_element_type {
COMMON_JSON_STACK_ELEMENT_OBJECT,
COMMON_JSON_STACK_ELEMENT_KEY,
COMMON_JSON_STACK_ELEMENT_ARRAY,
};
struct common_json_stack_element {
common_json_stack_element_type type;
std::string key;
};
bool common_json_parse(
const std::string & input,
const std::string & healing_marker,
common_json & out)
{
std::string::const_iterator it = input.begin();
const auto end = input.end();
return common_json_parse(it, end, healing_marker, out);
}
bool common_json_parse(
std::string::const_iterator & it,
const std::string::const_iterator & end,
const std::string & healing_marker,
common_json & out)
{
// // https://json.nlohmann.me/features/parsing/sax_interface/
struct json_error_locator : public nlohmann::json_sax<json> {
std::size_t position;
bool found_error;
std::string last_token;
std::string exception_message;
std::vector<common_json_stack_element> stack;
json_error_locator() : position(0), found_error(false) {}
bool parse_error(std::size_t position, const std::string & last_token, const json::exception & ex) override { // NOLINT
this->position = position - 1;
this->found_error = true;
this->last_token = last_token;
this->exception_message = ex.what();
return false;
}
void close_value() {
if (!stack.empty() && (stack.back().type == COMMON_JSON_STACK_ELEMENT_KEY)) {
stack.pop_back();
}
}
bool null() override { // NOLINT
close_value();
return true;
}
bool boolean(bool) override { // NOLINT
close_value();
return true;
}
bool number_integer(number_integer_t) override { // NOLINT
close_value();
return true;
}
bool number_unsigned(number_unsigned_t) override { // NOLINT
close_value();
return true;
}
bool number_float(number_float_t, const string_t &) override { // NOLINT
close_value();
return true;
}
bool string(string_t &) override { // NOLINT
close_value();
return true;
}
bool binary(binary_t &) override { // NOLINT
close_value();
return true;
}
bool start_object(std::size_t) override { // NOLINT
stack.push_back({COMMON_JSON_STACK_ELEMENT_OBJECT, ""});
return true;
}
bool end_object() override {
GGML_ASSERT(!stack.empty() && stack.back().type == COMMON_JSON_STACK_ELEMENT_OBJECT);
stack.pop_back();
close_value();
return true;
}
bool key(string_t & key) override { // NOLINT
stack.push_back({COMMON_JSON_STACK_ELEMENT_KEY, key});
return true;
}
bool start_array(std::size_t) override { // NOLINT
stack.push_back({COMMON_JSON_STACK_ELEMENT_ARRAY, ""});
return true;
}
bool end_array() override {
GGML_ASSERT(!stack.empty() && stack.back().type == COMMON_JSON_STACK_ELEMENT_ARRAY);
stack.pop_back();
close_value();
return true;
}
};
json_error_locator err_loc;
auto start = it;
json::sax_parse(it, end, &err_loc);
if (err_loc.found_error) {
it = start;
auto temptative_end = it + err_loc.position;
// LOG_DBG("Error at position %zu (is_end = %s): %s\n", err_loc.position, temptative_end == end ? "true" : "false", err_loc.exception_message.c_str());
auto input = std::string(it, temptative_end);
try {
out.json = json::parse(input);
// out.json = json::parse(it, temptative_end);
it = temptative_end;
return true;
} catch (const std::exception & ex) {
// No, needs healing.
LOG_DBG("Failed to parse up to error: %s: <<<%s>>>\n", ex.what(), std::string(it, temptative_end).c_str());
}
auto can_parse = [](const std::string & str) {
try {
auto _ = json::parse(str); // NOLINT
return true;
} catch (const std::exception &) {
return false;
}
};
if (!healing_marker.empty() && !err_loc.stack.empty()) {
std::string str(it, temptative_end);
auto last_non_sp_pos = str.find_last_not_of(" \n\r\t");
if (last_non_sp_pos == std::string::npos) {
throw std::runtime_error("Cannot heal a truncated JSON that stopped in an unknown location");
}
auto last_non_sp_char = str[last_non_sp_pos];
// Used to detect stops on a number, which may not be complete.
auto was_maybe_number = [&]() {
if (!str.empty() && std::isspace(str.back())) {
return false;
}
return std::isdigit(last_non_sp_char) ||
last_non_sp_char == '.' ||
last_non_sp_char == 'e' ||
last_non_sp_char == 'E' ||
last_non_sp_char == '-';
};
std::string closing;
for (size_t i = err_loc.stack.size(); i > 0; i--) {
auto & el = err_loc.stack[i - 1];
if (el.type == COMMON_JSON_STACK_ELEMENT_OBJECT) {
closing += "}";
} else if (el.type == COMMON_JSON_STACK_ELEMENT_ARRAY) {
closing += "]";
} else if (el.type != COMMON_JSON_STACK_ELEMENT_KEY) {
throw std::runtime_error("Unexpected stack element type");
}
}
const auto & magic_seed = out.healing_marker.marker = healing_marker;//"$llama.cpp.json$";
if (err_loc.stack.back().type == COMMON_JSON_STACK_ELEMENT_KEY) {
// We're inside an object value
if (last_non_sp_char == ':' && can_parse(str + "1" + closing)) {
// Was about to create an object value
str += (out.healing_marker.json_dump_marker = "\"" + magic_seed) + "\"" + closing;
} else if (can_parse(str + ": 1" + closing)) {
str += (out.healing_marker.json_dump_marker = ":\"" + magic_seed) + "\"" + closing;
} else if (last_non_sp_char == '{' && can_parse(str + closing)) {
// Was about to create an object
str += (out.healing_marker.json_dump_marker = "\"" + magic_seed) + "\": 1" + closing;
} else if (can_parse(str + "\"" + closing)) {
// Was inside an object value string
str += (out.healing_marker.json_dump_marker = magic_seed) + "\"" + closing;
} else if (str[str.length() - 1] == '\\' && can_parse(str + "\\\"" + closing)) {
// Was inside an object value string after an escape
str += (out.healing_marker.json_dump_marker = "\\" + magic_seed) + "\"" + closing;
} else {
// find last :
auto last_pos = str.find_last_of(':');
if (last_pos == std::string::npos) {
throw std::runtime_error("Cannot heal a truncated JSON that stopped in an unknown location");
}
// Cutting back to opening : for object value
str = str.substr(0, last_pos + 1) + (out.healing_marker.json_dump_marker = "\"" + magic_seed) + "\"" + closing;
}
} else if (err_loc.stack.back().type == COMMON_JSON_STACK_ELEMENT_ARRAY) {
if ((last_non_sp_char == ',' || last_non_sp_char == '[') && can_parse(str + "1" + closing)) {
// Was about to create an array value
str += (out.healing_marker.json_dump_marker = "\"" + magic_seed) + "\"" + closing;
} else if (can_parse(str + "\"" + closing)) {
// Was inside an array value string
str += (out.healing_marker.json_dump_marker = magic_seed) + "\"" + closing;
} else if (str[str.length() - 1] == '\\' && can_parse(str + "\\\"" + closing)) {
// Was inside an array value string after an escape
str += (out.healing_marker.json_dump_marker = "\\" + magic_seed) + "\"" + closing;
} else if (!was_maybe_number() && can_parse(str + ", 1" + closing)) {
// Had just finished a value
str += (out.healing_marker.json_dump_marker = ",\"" + magic_seed) + "\"" + closing;
} else {
auto last_pos = str.find_last_of("[,");
if (last_pos == std::string::npos) {
throw std::runtime_error("Cannot heal a truncated JSON array stopped in an unknown location");
}
// Cutting back to last [ or , for array value
str = str.substr(0, last_pos + 1) + (out.healing_marker.json_dump_marker = "\"" + magic_seed) + "\"" + closing;
}
} else if (err_loc.stack.back().type == COMMON_JSON_STACK_ELEMENT_OBJECT) {
if ((last_non_sp_char == '{' && can_parse(str + closing)) ||
(last_non_sp_char == ',' && can_parse(str + "\"\": 1" + closing))) {
// Was about to create an object key+value
str += (out.healing_marker.json_dump_marker = "\"" + magic_seed) + "\": 1" + closing;
} else if (!was_maybe_number() && can_parse(str + ",\"\": 1" + closing)) {
// Was about to create an object key+value
str += (out.healing_marker.json_dump_marker = ",\"" + magic_seed) + "\": 1" + closing;
} else if (can_parse(str + "\": 1" + closing)) {
// Was inside an object key string
str += (out.healing_marker.json_dump_marker = magic_seed) + "\": 1" + closing;
} else if (str[str.length() - 1] == '\\' && can_parse(str + "\\\": 1" + closing)) {
// Was inside an object key string after an escape
str += (out.healing_marker.json_dump_marker = "\\" + magic_seed) + "\": 1" + closing;
} else {
auto last_pos = str.find_last_of(':');
if (last_pos == std::string::npos) {
throw std::runtime_error("Cannot heal a truncated JSON object stopped in an unknown location");
}
// fprintf(stderr, "Cutting back to last : for object key+value\n");
str = str.substr(0, last_pos + 1) + (out.healing_marker.json_dump_marker = "\"" + magic_seed) + "\"" + closing;
}
} else {
throw std::runtime_error("Cannot heal a truncated JSON object stopped in an unknown location");
}
// fprintf(stderr, "HEALED:\nSTRING <<<\n%s\n>>>\n\nmagic_cut: <<<\n%s\n>>>\n\n", str.c_str(), out.healing_marker.json_dump_marker.c_str());
out.json = json::parse(str);
it = temptative_end;
return true;
}
// TODO: handle unclosed top-level primitive if the stack was empty but we got an error (e.g. "tru", "\"", etc...)
// fprintf(stderr, "Closing: TODO\n");
return false;
}
out.json = json::parse(it, end);
it = end;
return true;
}

38
common/json-partial.h Normal file
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@ -0,0 +1,38 @@
#pragma once
#include <nlohmann/json.hpp>
// Healing marker (empty if the JSON was fully parsed / wasn't healed).
struct common_healing_marker {
// Raw marker.
std::string marker;
// Cutting the `common_json.json.dump()` string at the (only) occurrence of this marker should yield the original partial JSON string (modulo spaces / if it had the same dump format).
std::string json_dump_marker;
};
// Represents a parsed JSON object, with its optional healing marker (a JSON dump fragment that can be used to find the position of healing in the JSON dump string)
struct common_json {
nlohmann::ordered_json json;
common_healing_marker healing_marker;
};
// Parse the JSON string, healing (closing) any partial JSON if `healing_marker` is not empty.
//
// Healing completes partial JSON strings by adding a (possibly modified) healing marker, then whatever is needed to close the JSON.
// This allows to parse the resulting healed JSON string, yet be able to cut it again if needed at the healing marker.
// (this is used when parsing JSON outputs from the models, then crafting partial JSONs for the partial tool calls in OAI format).
//
// For instance, parsing `{` with a healing marker `foo` will produce a healed JSON `{"foo":1}`, w/ json_dump_marker = `"foo"` (which can be used to break the JSON again).
bool common_json_parse(
const std::string & input,
const std::string & healing_marker,
common_json & out);
// Parse the JSON string (see overload above), but advancing an iterator to the end of the input when the (potentially partial) parsing succeeds.
bool common_json_parse(
std::string::const_iterator & it,
const std::string::const_iterator & end,
const std::string & healing_marker,
common_json & out);

View File

@ -1,6 +1,9 @@
#include "json-schema-to-grammar.h" #include "json-schema-to-grammar.h"
#include "common.h"
#include <nlohmann/json.hpp>
#include <algorithm> #include <algorithm>
#include <fstream>
#include <map> #include <map>
#include <regex> #include <regex>
#include <sstream> #include <sstream>
@ -11,14 +14,12 @@
using json = nlohmann::ordered_json; using json = nlohmann::ordered_json;
template <typename Iterator>
static std::string join(Iterator begin, Iterator end, const std::string & separator);
static std::string repeat(const std::string & str, size_t n);
static std::string build_repetition(const std::string & item_rule, int min_items, int max_items, const std::string & separator_rule = "") { static std::string build_repetition(const std::string & item_rule, int min_items, int max_items, const std::string & separator_rule = "") {
auto has_max = max_items != std::numeric_limits<int>::max(); auto has_max = max_items != std::numeric_limits<int>::max();
if (max_items == 0) {
return "";
}
if (min_items == 0 && max_items == 1) { if (min_items == 0 && max_items == 1) {
return item_rule + "?"; return item_rule + "?";
} }
@ -40,49 +41,6 @@ static std::string build_repetition(const std::string & item_rule, int min_items
return result; return result;
} }
/* Minimalistic replacement for std::string_view, which is only available from C++17 onwards */
class string_view {
const std::string & _str;
const size_t _start;
const size_t _end;
public:
string_view(const std::string & str, size_t start = 0, size_t end = std::string::npos) : _str(str), _start(start), _end(end == std::string::npos ? str.length() : end) {}
size_t size() const {
return _end - _start;
}
size_t length() const {
return size();
}
operator std::string() const {
return str();
}
std::string str() const {
return _str.substr(_start, _end - _start);
}
string_view substr(size_t pos, size_t len = std::string::npos) const {
return string_view(_str, _start + pos, len == std::string::npos ? _end : _start + pos + len);
}
char operator[](size_t pos) const {
auto index = _start + pos;
if (index >= _end) {
throw std::out_of_range("string_view index out of range");
}
return _str[_start + pos];
}
bool operator==(const string_view & other) const {
std::string this_str = *this;
std::string other_str = other;
return this_str == other_str;
}
};
static void _build_min_max_int(int min_value, int max_value, std::stringstream & out, int decimals_left = 16, bool top_level = true) { static void _build_min_max_int(int min_value, int max_value, std::stringstream & out, int decimals_left = 16, bool top_level = true) {
auto has_min = min_value != std::numeric_limits<int>::min(); auto has_min = min_value != std::numeric_limits<int>::min();
auto has_max = max_value != std::numeric_limits<int>::max(); auto has_max = max_value != std::numeric_limits<int>::max();
@ -111,14 +69,14 @@ static void _build_min_max_int(int min_value, int max_value, std::stringstream &
} }
out << "}"; out << "}";
}; };
std::function<void(const string_view &, const string_view &)> uniform_range = std::function<void(const std::string_view &, const std::string_view &)> uniform_range =
[&](const string_view & from, const string_view & to) { [&](const std::string_view & from, const std::string_view & to) {
size_t i = 0; size_t i = 0;
while (i < from.length() && i < to.length() && from[i] == to[i]) { while (i < from.length() && i < to.length() && from[i] == to[i]) {
i++; i++;
} }
if (i > 0) { if (i > 0) {
out << "\"" << from.substr(0, i).str() << "\""; out << "\"" << from.substr(0, i) << "\"";
} }
if (i < from.length() && i < to.length()) { if (i < from.length() && i < to.length()) {
if (i > 0) { if (i > 0) {
@ -128,8 +86,8 @@ static void _build_min_max_int(int min_value, int max_value, std::stringstream &
if (sub_len > 0) { if (sub_len > 0) {
auto from_sub = from.substr(i + 1); auto from_sub = from.substr(i + 1);
auto to_sub = to.substr(i + 1); auto to_sub = to.substr(i + 1);
auto sub_zeros = repeat("0", sub_len); auto sub_zeros = string_repeat("0", sub_len);
auto sub_nines = repeat("9", sub_len); auto sub_nines = string_repeat("9", sub_len);
auto to_reached = false; auto to_reached = false;
out << "("; out << "(";
@ -188,8 +146,8 @@ static void _build_min_max_int(int min_value, int max_value, std::stringstream &
auto max_digits = max_s.length(); auto max_digits = max_s.length();
for (auto digits = min_digits; digits < max_digits; digits++) { for (auto digits = min_digits; digits < max_digits; digits++) {
uniform_range(min_s, repeat("9", digits)); uniform_range(min_s, string_repeat("9", digits));
min_s = "1" + repeat("0", digits); min_s = "1" + string_repeat("0", digits);
out << " | "; out << " | ";
} }
uniform_range(min_s, max_s); uniform_range(min_s, max_s);
@ -267,7 +225,7 @@ static void _build_min_max_int(int min_value, int max_value, std::stringstream &
throw std::runtime_error("At least one of min_value or max_value must be set"); throw std::runtime_error("At least one of min_value or max_value must be set");
} }
const std::string SPACE_RULE = "| \" \" | \"\\n\" [ \\t]{0,20}"; const std::string SPACE_RULE = "| \" \" | \"\\n\"{1,2} [ \\t]{0,20}";
struct BuiltinRule { struct BuiltinRule {
std::string content; std::string content;
@ -318,49 +276,6 @@ std::unordered_map<char, std::string> GRAMMAR_LITERAL_ESCAPES = {
std::unordered_set<char> NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?'}; std::unordered_set<char> NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?'};
std::unordered_set<char> ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'^', '$', '.', '[', ']', '(', ')', '|', '{', '}', '*', '+', '?'}; std::unordered_set<char> ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'^', '$', '.', '[', ']', '(', ')', '|', '{', '}', '*', '+', '?'};
template <typename Iterator>
std::string join(Iterator begin, Iterator end, const std::string & separator) {
std::ostringstream result;
if (begin != end) {
result << *begin;
for (Iterator it = begin + 1; it != end; ++it) {
result << separator << *it;
}
}
return result.str();
}
static std::vector<std::string> split(const std::string & str, const std::string & delimiter) {
std::vector<std::string> tokens;
size_t start = 0;
size_t end = str.find(delimiter);
while (end != std::string::npos) {
tokens.push_back(str.substr(start, end - start));
start = end + delimiter.length();
end = str.find(delimiter, start);
}
tokens.push_back(str.substr(start));
return tokens;
}
static std::string repeat(const std::string & str, size_t n) {
if (n == 0) {
return "";
}
std::string result;
result.reserve(str.length() * n);
for (size_t i = 0; i < n; ++i) {
result += str;
}
return result;
}
static std::string replacePattern(const std::string & input, const std::regex & regex, const std::function<std::string(const std::smatch &)> & replacement) { static std::string replacePattern(const std::string & input, const std::regex & regex, const std::function<std::string(const std::smatch &)> & replacement) {
std::smatch match; std::smatch match;
std::string result; std::string result;
@ -389,6 +304,7 @@ static std::string format_literal(const std::string & literal) {
class SchemaConverter { class SchemaConverter {
private: private:
friend std::string build_grammar(const std::function<void(const common_grammar_builder &)> & cb, const common_grammar_options & options);
std::function<json(const std::string &)> _fetch_json; std::function<json(const std::string &)> _fetch_json;
bool _dotall; bool _dotall;
std::map<std::string, std::string> _rules; std::map<std::string, std::string> _rules;
@ -418,7 +334,7 @@ private:
for (size_t i = 0; i < alt_schemas.size(); i++) { for (size_t i = 0; i < alt_schemas.size(); i++) {
rules.push_back(visit(alt_schemas[i], name + (name.empty() ? "alternative-" : "-") + std::to_string(i))); rules.push_back(visit(alt_schemas[i], name + (name.empty() ? "alternative-" : "-") + std::to_string(i)));
} }
return join(rules.begin(), rules.end(), " | "); return string_join(rules, " | ");
} }
std::string _visit_pattern(const std::string & pattern, const std::string & name) { std::string _visit_pattern(const std::string & pattern, const std::string & name) {
@ -481,7 +397,7 @@ private:
for (const auto & item : ret) { for (const auto & item : ret) {
results.push_back(to_rule(item)); results.push_back(to_rule(item));
} }
return std::make_pair(join(results.begin(), results.end(), " "), false); return std::make_pair(string_join(results, " "), false);
}; };
while (i < length) { while (i < length) {
@ -539,7 +455,7 @@ private:
} }
curly_brackets += '}'; curly_brackets += '}';
i++; i++;
auto nums = split(curly_brackets.substr(1, curly_brackets.length() - 2), ","); auto nums = string_split(curly_brackets.substr(1, curly_brackets.length() - 2), ",");
int min_times = 0; int min_times = 0;
int max_times = std::numeric_limits<int>::max(); int max_times = std::numeric_limits<int>::max();
try { try {
@ -854,7 +770,7 @@ public:
return; return;
} }
std::string pointer = ref.substr(ref.find('#') + 1); std::string pointer = ref.substr(ref.find('#') + 1);
std::vector<std::string> tokens = split(pointer, "/"); std::vector<std::string> tokens = string_split(pointer, "/");
for (size_t i = 1; i < tokens.size(); ++i) { for (size_t i = 1; i < tokens.size(); ++i) {
std::string sel = tokens[i]; std::string sel = tokens[i];
if (target.is_null() || !target.contains(sel)) { if (target.is_null() || !target.contains(sel)) {
@ -905,7 +821,7 @@ public:
for (const auto & v : schema["enum"]) { for (const auto & v : schema["enum"]) {
enum_values.push_back(_generate_constant_rule(v)); enum_values.push_back(_generate_constant_rule(v));
} }
return _add_rule(rule_name, "(" + join(enum_values.begin(), enum_values.end(), " | ") + ") space"); return _add_rule(rule_name, "(" + string_join(enum_values, " | ") + ") space");
} else if ((schema_type.is_null() || schema_type == "object") } else if ((schema_type.is_null() || schema_type == "object")
&& (schema.contains("properties") || && (schema.contains("properties") ||
(schema.contains("additionalProperties") && schema["additionalProperties"] != true))) { (schema.contains("additionalProperties") && schema["additionalProperties"] != true))) {
@ -1019,10 +935,10 @@ public:
void check_errors() { void check_errors() {
if (!_errors.empty()) { if (!_errors.empty()) {
throw std::runtime_error("JSON schema conversion failed:\n" + join(_errors.begin(), _errors.end(), "\n")); throw std::runtime_error("JSON schema conversion failed:\n" + string_join(_errors, "\n"));
} }
if (!_warnings.empty()) { if (!_warnings.empty()) {
fprintf(stderr, "WARNING: JSON schema conversion was incomplete: %s\n", join(_warnings.begin(), _warnings.end(), "; ").c_str()); fprintf(stderr, "WARNING: JSON schema conversion was incomplete: %s\n", string_join(_warnings, "; ").c_str());
} }
} }
@ -1035,11 +951,35 @@ public:
} }
}; };
std::string json_schema_to_grammar(const json & schema) { std::string json_schema_to_grammar(const json & schema, bool force_gbnf) {
SchemaConverter converter([](const std::string &) { return json::object(); }, /* dotall= */ false); #ifdef LLAMA_USE_LLGUIDANCE
auto copy = schema; if (!force_gbnf) {
converter.resolve_refs(copy, "input"); return "%llguidance {}\nstart: %json " + schema.dump();
converter.visit(copy, ""); }
#else
(void)force_gbnf;
#endif // LLAMA_USE_LLGUIDANCE
return build_grammar([&](const common_grammar_builder & callbacks) {
auto copy = schema;
callbacks.resolve_refs(copy);
callbacks.add_schema("", copy);
});
}
std::string build_grammar(const std::function<void(const common_grammar_builder &)> & cb, const common_grammar_options & options) {
SchemaConverter converter([&](const std::string &) { return json(); }, options.dotall);
common_grammar_builder builder {
/* .add_rule = */ [&](const std::string & name, const std::string & rule) {
return converter._add_rule(name, rule);
},
/* .add_schema = */ [&](const std::string & name, const nlohmann::ordered_json & schema) {
return converter.visit(schema, name == "root" ? "" : name);
},
/* .resolve_refs = */ [&](nlohmann::ordered_json & schema) {
converter.resolve_refs(schema, "");
}
};
cb(builder);
converter.check_errors(); converter.check_errors();
return converter.format_grammar(); return converter.format_grammar();
} }

View File

@ -1,8 +1,21 @@
#pragma once #pragma once
#include "ggml.h" #include <nlohmann/json_fwd.hpp>
// Change JSON_ASSERT from assert() to GGML_ASSERT:
#define JSON_ASSERT GGML_ASSERT
#include "json.hpp"
std::string json_schema_to_grammar(const nlohmann::ordered_json& schema); #include <functional>
#include <string>
std::string json_schema_to_grammar(const nlohmann::ordered_json & schema,
bool force_gbnf = false);
struct common_grammar_builder {
std::function<std::string(const std::string &, const std::string &)> add_rule;
std::function<std::string(const std::string &, const nlohmann::ordered_json &)> add_schema;
std::function<void(nlohmann::ordered_json &)> resolve_refs;
};
struct common_grammar_options {
bool dotall = false;
};
std::string build_grammar(const std::function<void(const common_grammar_builder &)> & cb, const common_grammar_options & options = {});

254
common/llguidance.cpp Normal file
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@ -0,0 +1,254 @@
#include "sampling.h"
#include "log.h"
#ifdef LLAMA_USE_LLGUIDANCE
# include "llguidance.h"
# include <cmath>
struct llama_sampler_llg {
const llama_vocab * vocab;
std::string grammar_kind;
std::string grammar_data;
LlgTokenizer * tokenizer;
LlgMatcher * grammar;
};
static LlgMatcher * llama_sampler_llg_new(LlgTokenizer * tokenizer, const char * grammar_kind,
const char * grammar_data) {
LlgConstraintInit cinit;
llg_constraint_init_set_defaults(&cinit, tokenizer);
const char * log_level = getenv("LLGUIDANCE_LOG_LEVEL");
if (log_level && *log_level) {
cinit.log_stderr_level = atoi(log_level);
}
auto c = llg_new_matcher(&cinit, grammar_kind, grammar_data);
if (llg_matcher_get_error(c)) {
LOG_ERR("llg error: %s\n", llg_matcher_get_error(c));
llg_free_matcher(c);
return nullptr;
}
return c;
}
static const char * llama_sampler_llg_name(const llama_sampler * /*smpl*/) {
return "llguidance";
}
static void llama_sampler_llg_accept_impl(llama_sampler * smpl, llama_token token) {
auto * ctx = (llama_sampler_llg *) smpl->ctx;
if (ctx->grammar) {
llg_matcher_consume_token(ctx->grammar, token);
}
}
static void llama_sampler_llg_apply(llama_sampler * smpl, llama_token_data_array * cur_p) {
auto * ctx = (llama_sampler_llg *) smpl->ctx;
if (ctx->grammar) {
const uint32_t * mask = llg_matcher_get_mask(ctx->grammar);
if (mask == nullptr) {
if (llg_matcher_compute_mask(ctx->grammar) == 0) {
mask = llg_matcher_get_mask(ctx->grammar);
} else {
LOG_ERR("llg error: %s\n", llg_matcher_get_error(ctx->grammar));
llg_free_matcher(ctx->grammar);
ctx->grammar = nullptr;
return;
}
}
for (size_t i = 0; i < cur_p->size; ++i) {
auto token = cur_p->data[i].id;
if ((mask[token / 32] & (1 << (token % 32))) == 0) {
cur_p->data[i].logit = -INFINITY;
}
}
}
}
static void llama_sampler_llg_reset(llama_sampler * smpl) {
auto * ctx = (llama_sampler_llg *) smpl->ctx;
if (ctx->grammar) {
llg_matcher_reset(ctx->grammar);
}
}
static llama_sampler * llama_sampler_llg_clone(const llama_sampler * smpl) {
const auto * ctx = (const llama_sampler_llg *) smpl->ctx;
auto * result = llama_sampler_init_llg(ctx->vocab, nullptr, nullptr);
// copy the state
{
auto * result_ctx = (llama_sampler_llg *) result->ctx;
if (ctx->grammar) {
result_ctx->grammar_kind = ctx->grammar_kind;
result_ctx->grammar_data = ctx->grammar_data;
result_ctx->grammar = llg_clone_matcher(ctx->grammar);
result_ctx->tokenizer = llg_clone_tokenizer(ctx->tokenizer);
}
}
return result;
}
static void llama_sampler_llg_free(llama_sampler * smpl) {
const auto * ctx = (llama_sampler_llg *) smpl->ctx;
if (ctx->grammar) {
llg_free_matcher(ctx->grammar);
llg_free_tokenizer(ctx->tokenizer);
}
delete ctx;
}
static llama_sampler_i llama_sampler_llg_i = {
/* .name = */ llama_sampler_llg_name,
/* .accept = */ llama_sampler_llg_accept_impl,
/* .apply = */ llama_sampler_llg_apply,
/* .reset = */ llama_sampler_llg_reset,
/* .clone = */ llama_sampler_llg_clone,
/* .free = */ llama_sampler_llg_free,
};
static size_t llama_sampler_llg_tokenize_fn(const void * user_data, const uint8_t * bytes, size_t bytes_len,
uint32_t * output_tokens, size_t output_tokens_len) {
const llama_vocab * vocab = (const llama_vocab *) user_data;
int r = 0;
try {
r = llama_tokenize(vocab, (const char *) bytes, bytes_len, (int32_t *) output_tokens, output_tokens_len, false,
true);
} catch (const std::exception & e) {
GGML_ABORT("llama_tokenize failed: %s\n", e.what());
}
if (r < 0) {
return -r;
}
return r;
}
static LlgTokenizer * llama_sampler_llg_new_tokenizer(const llama_vocab * vocab) {
// TODO store the tokenizer in the vocab somehow
static const llama_vocab * vocab_cache;
static LlgTokenizer * tokenizer_cache;
if (vocab_cache == vocab) {
return llg_clone_tokenizer(tokenizer_cache);
}
auto tok_eos = llama_vocab_eot(vocab);
if (tok_eos == LLAMA_TOKEN_NULL) {
tok_eos = llama_vocab_eos(vocab);
}
size_t vocab_size = llama_vocab_n_tokens(vocab);
auto token_lens = new uint32_t[vocab_size];
// we typically have ~7 bytes per token; let's go on the safe side here
auto token_bytes_size = vocab_size * 16 + 1024 * 1024;
auto token_bytes = new uint8_t[token_bytes_size];
size_t offset = 0;
for (size_t i = 0; i < vocab_size; i++) {
size_t max_token = 1024;
if (token_bytes_size - offset < max_token) {
GGML_ABORT("token_bytes buffer too small\n");
}
llama_token token = i;
auto dp = (char *) token_bytes + offset;
auto size = llama_detokenize(vocab, &token, 1, dp, max_token, false, false);
if (size < 0) {
GGML_ABORT("llama_detokenize failed\n");
}
if (size == 0) {
size = llama_detokenize(vocab, &token, 1, dp + 1, max_token - 1, false, true);
if (size < 0) {
GGML_ABORT("llama_detokenize failed\n");
}
if (size != 0) {
*dp = '\xff'; // special token prefix marker
size += 1;
}
}
token_lens[i] = size;
offset += size;
}
LlgTokenizerInit tinit = {
/* .vocab_size = */ (uint32_t) vocab_size,
/* .tok_eos = */ (uint32_t) tok_eos,
/* .token_lens = */ token_lens,
/* .token_bytes = */ token_bytes,
/* .tokenizer_json = */ nullptr,
/* .tokenize_assumes_string = */ true,
/* .tokenize_fn = */ llama_sampler_llg_tokenize_fn,
/* .use_approximate_greedy_tokenize_fn = */ false,
/* .tokenize_user_data = */ vocab,
/* .slices = */ nullptr,
};
char error_buffer[1024];
LlgTokenizer * tokenizer = llg_new_tokenizer(&tinit, error_buffer, sizeof(error_buffer));
delete[] token_bytes;
delete[] token_lens;
if (tokenizer == nullptr) {
LOG_ERR("llg tokenizer error: %s\n", error_buffer);
return tokenizer;
}
if (tokenizer_cache) {
llg_free_tokenizer(tokenizer_cache);
}
vocab_cache = vocab;
tokenizer_cache = tokenizer;
return llg_clone_tokenizer(tokenizer_cache);
}
llama_sampler * llama_sampler_init_llg(const llama_vocab * vocab, const char * grammar_kind,
const char * grammar_data) {
auto * ctx = new llama_sampler_llg;
if (grammar_kind != nullptr && grammar_kind[0] != '\0') {
auto tokenizer = llama_sampler_llg_new_tokenizer(vocab);
*ctx = {
/* .vocab = */ vocab,
/* .grammar_kind = */ grammar_kind,
/* .grammar_data = */ grammar_data,
/* .tokenizer = */ tokenizer,
/* .grammar = */ llama_sampler_llg_new(tokenizer, grammar_kind, grammar_data),
};
if (ctx->grammar) {
GGML_ASSERT(((size_t) llama_vocab_n_tokens(vocab) + 31) / 32 * 4 ==
llg_matcher_get_mask_byte_size(ctx->grammar));
}
} else {
*ctx = {
/* .vocab = */ vocab,
/* .grammar_kind = */ {},
/* .grammar_data = */ {},
/* .tokenizer = */ nullptr,
/* .grammar = */ nullptr,
};
}
return llama_sampler_init(
/* .iface = */ &llama_sampler_llg_i,
/* .ctx = */ ctx);
}
#else
llama_sampler * llama_sampler_init_llg(const llama_vocab *, const char *, const char *) {
LOG_WRN("llguidance (cmake -DLLAMA_LLGUIDANCE=ON) is not enabled");
return nullptr;
}
#endif // LLAMA_USE_LLGUIDANCE

View File

@ -1,5 +1,6 @@
#include "log.h" #include "log.h"
#include <chrono>
#include <condition_variable> #include <condition_variable>
#include <cstdarg> #include <cstdarg>
#include <cstdio> #include <cstdio>
@ -14,16 +15,6 @@ void common_log_set_verbosity_thold(int verbosity) {
common_log_verbosity_thold = verbosity; common_log_verbosity_thold = verbosity;
} }
#define LOG_COL_DEFAULT "\033[0m"
#define LOG_COL_BOLD "\033[1m"
#define LOG_COL_RED "\033[31m"
#define LOG_COL_GREEN "\033[32m"
#define LOG_COL_YELLOW "\033[33m"
#define LOG_COL_BLUE "\033[34m"
#define LOG_COL_MAGENTA "\033[35m"
#define LOG_COL_CYAN "\033[36m"
#define LOG_COL_WHITE "\033[37m"
static int64_t t_us() { static int64_t t_us() {
return std::chrono::duration_cast<std::chrono::microseconds>(std::chrono::system_clock::now().time_since_epoch()).count(); return std::chrono::duration_cast<std::chrono::microseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
} }
@ -206,6 +197,7 @@ public:
vsnprintf(entry.msg.data(), entry.msg.size(), ss.str().c_str(), args_copy); vsnprintf(entry.msg.data(), entry.msg.size(), ss.str().c_str(), args_copy);
} }
#endif #endif
va_end(args_copy);
} }
entry.level = level; entry.level = level;

View File

@ -2,9 +2,20 @@
#include "ggml.h" // for ggml_log_level #include "ggml.h" // for ggml_log_level
#define LOG_CLR_TO_EOL "\033[K\r"
#define LOG_COL_DEFAULT "\033[0m"
#define LOG_COL_BOLD "\033[1m"
#define LOG_COL_RED "\033[31m"
#define LOG_COL_GREEN "\033[32m"
#define LOG_COL_YELLOW "\033[33m"
#define LOG_COL_BLUE "\033[34m"
#define LOG_COL_MAGENTA "\033[35m"
#define LOG_COL_CYAN "\033[36m"
#define LOG_COL_WHITE "\033[37m"
#ifndef __GNUC__ #ifndef __GNUC__
# define LOG_ATTRIBUTE_FORMAT(...) # define LOG_ATTRIBUTE_FORMAT(...)
#elif defined(__MINGW32__) #elif defined(__MINGW32__) && !defined(__clang__)
# define LOG_ATTRIBUTE_FORMAT(...) __attribute__((format(gnu_printf, __VA_ARGS__))) # define LOG_ATTRIBUTE_FORMAT(...) __attribute__((format(gnu_printf, __VA_ARGS__)))
#else #else
# define LOG_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__))) # define LOG_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__)))

View File

@ -7,6 +7,7 @@
#include <cstdio> #include <cstdio>
#include <fstream> #include <fstream>
#include <thread> #include <thread>
#include <algorithm>
void common_ngram_cache_update(common_ngram_cache & ngram_cache, int ngram_min, int ngram_max, void common_ngram_cache_update(common_ngram_cache & ngram_cache, int ngram_min, int ngram_max,
std::vector<llama_token> & inp, int nnew, bool print_progress) { std::vector<llama_token> & inp, int nnew, bool print_progress) {
@ -65,13 +66,13 @@ constexpr int draft_min_percent_strict[LLAMA_NGRAM_MAX] = {75, 66, 66, 66};
static llama_token try_draft(common_ngram_cache & nc_static, const common_ngram ngram_static) { static llama_token try_draft(common_ngram_cache & nc_static, const common_ngram ngram_static) {
common_ngram_cache::iterator part_static_it = nc_static.find(ngram_static); common_ngram_cache::iterator part_static_it = nc_static.find(ngram_static);
if (part_static_it == nc_static.end()) { if (part_static_it == nc_static.end()) {
return -1; return LLAMA_TOKEN_NULL;
} }
const common_ngram_cache_part part_static = part_static_it->second; const common_ngram_cache_part part_static = part_static_it->second;
int max_count_static = 0; int max_count_static = 0;
int sum_count_static = 0; int sum_count_static = 0;
llama_token max_token = -1; llama_token max_token = LLAMA_TOKEN_NULL;
for (std::pair<llama_token, int> token_count_static : part_static) { for (std::pair<llama_token, int> token_count_static : part_static) {
const llama_token token = token_count_static.first; const llama_token token = token_count_static.first;
@ -85,10 +86,10 @@ static llama_token try_draft(common_ngram_cache & nc_static, const common_ngram
} }
if (sum_count_static < draft_min_sample_size_lax[LLAMA_NGRAM_STATIC-1]) { if (sum_count_static < draft_min_sample_size_lax[LLAMA_NGRAM_STATIC-1]) {
return -1; return LLAMA_TOKEN_NULL;
} }
if (100*max_count_static < draft_min_percent_lax[LLAMA_NGRAM_STATIC-1]*sum_count_static) { if (100*max_count_static < draft_min_percent_lax[LLAMA_NGRAM_STATIC-1]*sum_count_static) {
return -1; return LLAMA_TOKEN_NULL;
} }
return max_token; return max_token;
} }
@ -98,9 +99,9 @@ static llama_token try_draft(
common_ngram_cache & nc_primary, const std::vector<common_ngram> & ngrams_primary, common_ngram_cache_part & part_static, common_ngram_cache & nc_primary, const std::vector<common_ngram> & ngrams_primary, common_ngram_cache_part & part_static,
const int * min_sample_size, const int * min_percent) { const int * min_sample_size, const int * min_percent) {
llama_token drafted_token = -1; llama_token drafted_token = LLAMA_TOKEN_NULL;
for (int i = ngrams_primary.size()-1; i >= 0 && drafted_token == -1; --i) { for (int i = ngrams_primary.size()-1; i >= 0 && drafted_token == LLAMA_TOKEN_NULL; --i) {
const common_ngram ngram_primary = ngrams_primary[i]; const common_ngram ngram_primary = ngrams_primary[i];
common_ngram_cache::iterator part_primary_it = nc_primary.find(ngram_primary); common_ngram_cache::iterator part_primary_it = nc_primary.find(ngram_primary);
@ -112,7 +113,7 @@ static llama_token try_draft(
int max_count_primary = 0; int max_count_primary = 0;
int max_count_static = 0; int max_count_static = 0;
int sum_count_primary = 0; int sum_count_primary = 0;
llama_token max_token = -1; llama_token max_token = LLAMA_TOKEN_NULL;
for (std::pair<llama_token, int> token_count_primary : part_primary) { for (std::pair<llama_token, int> token_count_primary : part_primary) {
const llama_token token = token_count_primary.first; const llama_token token = token_count_primary.first;
@ -154,7 +155,7 @@ void common_ngram_cache_draft(
} }
while ((int) draft.size()-1 < n_draft) { while ((int) draft.size()-1 < n_draft) {
llama_token drafted_token = -1; llama_token drafted_token = LLAMA_TOKEN_NULL;
const int ngram_start_static = inp_size-LLAMA_NGRAM_STATIC + draft.size()-1; const int ngram_start_static = inp_size-LLAMA_NGRAM_STATIC + draft.size()-1;
common_ngram ngram_static; common_ngram ngram_static;
@ -177,17 +178,17 @@ void common_ngram_cache_draft(
} }
ngrams_cd.push_back(ngram_cd); ngrams_cd.push_back(ngram_cd);
} }
if (drafted_token == -1) { if (drafted_token == LLAMA_TOKEN_NULL) {
drafted_token = try_draft(nc_context, ngrams_cd, part_static, draft_min_sample_size_lax, draft_min_percent_lax); drafted_token = try_draft(nc_context, ngrams_cd, part_static, draft_min_sample_size_lax, draft_min_percent_lax);
} }
if (drafted_token == -1) { if (drafted_token == LLAMA_TOKEN_NULL) {
drafted_token = try_draft(nc_dynamic, ngrams_cd, part_static, draft_min_sample_size_strict, draft_min_percent_strict); drafted_token = try_draft(nc_dynamic, ngrams_cd, part_static, draft_min_sample_size_strict, draft_min_percent_strict);
} }
if (drafted_token == -1) { if (drafted_token == LLAMA_TOKEN_NULL) {
drafted_token = try_draft(nc_static, ngram_static); drafted_token = try_draft(nc_static, ngram_static);
} }
if (drafted_token == -1) { if (drafted_token == LLAMA_TOKEN_NULL) {
break; break;
} }

View File

@ -17,13 +17,13 @@ struct common_ngram {
common_ngram() { common_ngram() {
for (int i = 0; i < LLAMA_NGRAM_MAX; ++i) { for (int i = 0; i < LLAMA_NGRAM_MAX; ++i) {
tokens[i] = -1; tokens[i] = LLAMA_TOKEN_NULL;
} }
} }
common_ngram(const llama_token * input, const int ngram_size) { common_ngram(const llama_token * input, const int ngram_size) {
for (int i = 0; i < LLAMA_NGRAM_MAX; ++i) { for (int i = 0; i < LLAMA_NGRAM_MAX; ++i) {
tokens[i] = i < ngram_size ? input[i] : -1; tokens[i] = i < ngram_size ? input[i] : LLAMA_TOKEN_NULL;
} }
} }

204
common/regex-partial.cpp Normal file
View File

@ -0,0 +1,204 @@
#include "regex-partial.h"
#include "common.h"
#include <functional>
#include <optional>
common_regex::common_regex(const std::string & pattern) :
pattern(pattern),
rx(pattern),
rx_reversed_partial(regex_to_reversed_partial_regex(pattern)) {}
common_regex_match common_regex::search(const std::string & input, size_t pos, bool as_match) const {
std::smatch match;
if (pos > input.size()) {
throw std::runtime_error("Position out of bounds");
}
auto start = input.begin() + pos;
auto found = as_match
? std::regex_match(start, input.end(), match, rx)
: std::regex_search(start, input.end(), match, rx);
if (found) {
common_regex_match res;
res.type = COMMON_REGEX_MATCH_TYPE_FULL;
for (size_t i = 0; i < match.size(); ++i) {
auto begin = pos + match.position(i);
res.groups.emplace_back(begin, begin + match.length(i));
}
return res;
}
std::match_results<std::string::const_reverse_iterator> srmatch;
if (std::regex_match(input.rbegin(), input.rend() - pos, srmatch, rx_reversed_partial)) {
auto group = srmatch[1].str();
if (group.length() != 0) {
auto it = srmatch[1].second.base();
// auto position = static_cast<size_t>(std::distance(input.begin(), it));
if ((!as_match) || it == input.begin()) {
common_regex_match res;
res.type = COMMON_REGEX_MATCH_TYPE_PARTIAL;
const size_t begin = std::distance(input.begin(), it);
const size_t end = input.size();
if (begin == std::string::npos || end == std::string::npos || begin > end) {
throw std::runtime_error("Invalid range");
}
res.groups.push_back({begin, end});
return res;
}
}
}
return {};
}
/*
Transforms a regex pattern to a partial match pattern that operates on a reversed input string to find partial final matches of the original pattern.
Ideally we'd like to use boost::match_partial (https://beta.boost.org/doc/libs/1_59_0/libs/regex/doc/html/boost_regex/partial_matches.html)
to see if a string ends with a partial regex match, but but it's not in std::regex yet.
Instead, we'll the regex into a partial match regex operating as a full match on the reverse iterators of the input.
- /abcd/ -> (dcba|cba|ba|a).* -> ((?:(?:(?:(?:d)?c)?b)?a).*
- /a|b/ -> (a|b).*
- /a*?/ -> error, could match ""
- /a*b/ -> ((?:b)?a*+).* (final repetitions become eager)
- /.*?ab/ -> ((?:b)?a).* (merge .*)
- /a.*?b/ -> ((?:b)?.*?a).* (keep reluctant matches)
- /a(bc)d/ -> ((?:(?:d)?(?:(?:c)?b))?a).*
- /a(bc|de)/ -> ((?:(?:(?:e)?d)?|(?:(?:c)?b)?)?a).*
- /ab{2,4}c/ -> abbb?b?c -> ((?:(?:(?:(?:(?:c)?b)?b)?b?)?b?)?a).*
The regex will match a reversed string fully, and the end of the first (And only) capturing group will indicate the reversed start of the original partial pattern
(i.e. just where the final .* starts in the inverted pattern; all other groups are turned into non-capturing groups, and reluctant quantifiers are ignored)
*/
std::string regex_to_reversed_partial_regex(const std::string & pattern) {
auto it = pattern.begin();
const auto end = pattern.end();
std::function<std::string()> process = [&]() {
std::vector<std::vector<std::string>> alternatives(1);
std::vector<std::string> * sequence = &alternatives.back();
while (it != end) {
if (*it == '[') {
auto start = it;
++it;
while (it != end) {
if ((*it == '\\') && (++it != end)) {
++it;
} else if ((it != end) && (*it == ']')) {
break;
} else {
++it;
}
}
if (it == end) {
throw std::runtime_error("Unmatched '[' in pattern");
}
++it;
sequence->push_back(std::string(start, it));
} else if (*it == '*' || *it == '?' || *it == '+') {
if (sequence->empty()) {
throw std::runtime_error("Quantifier without preceding element");
}
sequence->back() += *it;
auto is_star = *it == '*';
++it;
if (is_star) {
if (*it == '?') {
++it;
}
}
} else if (*it == '{') {
if (sequence->empty()) {
throw std::runtime_error("Repetition without preceding element");
}
++it;
auto start = it;
while (it != end && *it != '}') {
++it;
}
if (it == end) {
throw std::runtime_error("Unmatched '{' in pattern");
}
auto parts = string_split(std::string(start, it), ",");
++it;
if (parts.size() > 2) {
throw std::runtime_error("Invalid repetition range in pattern");
}
auto parseOptInt = [&](const std::string & s, const std::optional<int> & def = std::nullopt) -> std::optional<int> {
if (s.empty()) {
return def;
}
return std::stoi(s);
};
auto min = parseOptInt(parts[0], 0);
auto max = parts.size() == 1 ? min : parseOptInt(parts[1]);
if (min && max && *max < *min) {
throw std::runtime_error("Invalid repetition range in pattern");
}
// Brutal but... let's repeat at least min times, then ? for the delta between min & max (or * for unbounded)
auto part = sequence->back();
sequence->pop_back();
for (int i = 0; i < *min; i++) {
sequence->push_back(part);
}
if (max) {
for (int i = *min; i < *max; i++) {
sequence->push_back(part + "?");
}
} else {
sequence->push_back(part + "*");
}
} else if (*it == '(') {
++it;
if (it != end && *it == '?' && (it + 1 != end) && *(it + 1) == ':') {
it += 2;
}
auto sub = process();
if (*it != ')') {
throw std::runtime_error("Unmatched '(' in pattern");
}
++it;
auto & part = sequence->emplace_back("(?:");
part += sub;
part += ")";
} else if (*it == ')') {
break;
} else if (*it == '|') {
++it;
alternatives.emplace_back();
sequence = &alternatives.back();
} else if (*it == '\\' && (++it != end)) {
auto str = std::string("\\") + *it;
sequence->push_back(str);
++it;
} else if (it != end) {
sequence->push_back(std::string(1, *it));
++it;
}
}
// /abcd/ -> (dcba|cba|ba|a).* -> ((?:(?:(?:d)?c)?b)?a).*
// if n(=4) parts, opening n-1(=3) non-capturing groups after the 1 capturing group
// We'll do the outermost capturing group and final .* in the enclosing function.
std::vector<std::string> res_alts;
for (const auto & parts : alternatives) {
auto & res = res_alts.emplace_back();
for (size_t i = 0; i < parts.size() - 1; i++) {
res += "(?:";
}
for (auto it = parts.rbegin(); it != parts.rend(); ++it) {
res += *it;
if (it != parts.rend() - 1) {
res += ")?";
}
}
}
return string_join(res_alts, "|");
};
auto res = process();
if (it != end) {
throw std::runtime_error("Unmatched '(' in pattern");
}
return "(" + res + ")[\\s\\S]*";
}

56
common/regex-partial.h Normal file
View File

@ -0,0 +1,56 @@
#pragma once
#include <regex>
#include <string>
enum common_regex_match_type {
COMMON_REGEX_MATCH_TYPE_NONE,
COMMON_REGEX_MATCH_TYPE_PARTIAL,
COMMON_REGEX_MATCH_TYPE_FULL,
};
struct common_string_range {
size_t begin;
size_t end;
common_string_range(size_t begin, size_t end) : begin(begin), end(end) {
if (begin > end) {
throw std::runtime_error("Invalid range");
}
}
// prevent default ctor
common_string_range() = delete;
bool empty() const {
return begin == end;
}
bool operator==(const common_string_range & other) const {
return begin == other.begin && end == other.end;
}
};
struct common_regex_match {
common_regex_match_type type = COMMON_REGEX_MATCH_TYPE_NONE;
std::vector<common_string_range> groups;
bool operator==(const common_regex_match & other) const {
return type == other.type && groups == other.groups;
}
bool operator!=(const common_regex_match & other) const {
return !(*this == other);
}
};
class common_regex {
std::string pattern;
std::regex rx;
std::regex rx_reversed_partial;
public:
explicit common_regex(const std::string & pattern);
common_regex_match search(const std::string & input, size_t pos, bool as_match = false) const;
const std::string & str() const { return pattern; }
};
// For testing only (pretty print of failures).
std::string regex_to_reversed_partial_regex(const std::string & pattern);

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