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Author SHA1 Message Date
Georgi Gerganov 04a134c70b ci : make release workflows use a deply key 2026-08-17 09:58:11 +03:00
1264 changed files with 43874 additions and 113690 deletions
+6 -6
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@@ -31,7 +31,7 @@
]
&& blas.meta.available,
useCuda ? config.cudaSupport,
useMetalKit ? stdenv.hostPlatform.isAarch64 && stdenv.hostPlatform.isDarwin,
useMetalKit ? stdenv.isAarch64 && stdenv.isDarwin,
# Increases the runtime closure size by ~700M
useMpi ? false,
useRocm ? config.rocmSupport,
@@ -92,7 +92,7 @@ let
cudaBuildInputs = with cudaPackages; [
cuda_cudart
cccl # <nv/target>
cuda_cccl # <nv/target>
libcublas
];
@@ -166,7 +166,7 @@ effectiveStdenv.mkDerivation (finalAttrs: {
# `xcrun` is used find the path of the Metal compiler, which is varible
# and not on $PATH
# see https://github.com/ggml-org/llama.cpp/pull/6118 for discussion
__noChroot = effectiveStdenv.hostPlatform.isDarwin && useMetalKit && precompileMetalShaders;
__noChroot = effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders;
nativeBuildInputs =
[
@@ -181,10 +181,10 @@ effectiveStdenv.mkDerivation (finalAttrs: {
autoAddDriverRunpath
]
++ optionals (effectiveStdenv.hostPlatform.isGnu && enableStatic) [ glibc.static ]
++ optionals (effectiveStdenv.hostPlatform.isDarwin && useMetalKit && precompileMetalShaders) [ xcrunHost ];
++ optionals (effectiveStdenv.isDarwin && useMetalKit && precompileMetalShaders) [ xcrunHost ];
buildInputs =
optionals effectiveStdenv.hostPlatform.isDarwin darwinBuildInputs
optionals effectiveStdenv.isDarwin darwinBuildInputs
++ optionals useCuda cudaBuildInputs
++ optionals useMpi [ mpi ]
++ optionals useRocm rocmBuildInputs
@@ -245,7 +245,7 @@ effectiveStdenv.mkDerivation (finalAttrs: {
# Configurations that are known to result in build failures. Can be
# overridden by importing Nixpkgs with `allowBroken = true`.
broken = (useMetalKit && !effectiveStdenv.hostPlatform.isDarwin);
broken = (useMetalKit && !effectiveStdenv.isDarwin);
description = "Inference of LLaMA model in pure C/C++${descriptionSuffix}";
homepage = "https://github.com/ggml-org/llama.cpp/";
+10 -13
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@@ -1,18 +1,18 @@
ARG OPENVINO_VERSION_MAJOR=2026.3.1
ARG OPENVINO_VERSION_FULL=2026.3.1.22476.56d9685302d
ARG OPENVINO_VERSION_MAJOR=2026.2.1
ARG OPENVINO_VERSION_FULL=2026.2.1.21919.ede283a88e3
ARG UBUNTU_VERSION=24.04
# Intel GPU driver versions. https://github.com/intel/compute-runtime/releases
ARG IGC_VERSION=v2.40.13
ARG IGC_VERSION_FULL=2_2.40.13+22418
ARG COMPUTE_RUNTIME_VERSION=26.31.39395.13
ARG COMPUTE_RUNTIME_VERSION_FULL=26.31.39395.13-0
ARG IGC_VERSION=v2.36.3
ARG IGC_VERSION_FULL=2_2.36.3+21719
ARG COMPUTE_RUNTIME_VERSION=26.22.38646.4
ARG COMPUTE_RUNTIME_VERSION_FULL=26.22.38646.4-0
ARG IGDGMM_VERSION=22.10.0
# Intel NPU driver versions. https://github.com/intel/linux-npu-driver/releases
ARG NPU_DRIVER_VERSION=v1.35.0
ARG NPU_DRIVER_FULL=v1.35.0.20260722-29947505341
ARG LIBZE1_VERSION=1.28.2-1~24.04~ppa1
ARG NPU_DRIVER_VERSION=v1.33.0
ARG NPU_DRIVER_FULL=v1.33.0.20260529-26625960453
ARG LIBZE1_VERSION=1.27.0-1~24.04~ppa2
# Optional proxy build arguments
ARG http_proxy=
@@ -90,9 +90,6 @@ RUN bash -c "source ${OpenVINO_DIR}/setupvars.sh && \
cmake -B build/ReleaseOV -G Ninja \
-DCMAKE_BUILD_TYPE=Release \
-DLLAMA_BUILD_TESTS=OFF \
-DGGML_NATIVE=OFF \
-DGGML_BACKEND_DL=ON \
-DGGML_CPU_ALL_VARIANTS=ON \
-DGGML_OPENVINO=ON && \
cmake --build build/ReleaseOV --parallel "
@@ -173,7 +170,7 @@ RUN --mount=type=cache,target=/var/cache/intel-npu,sharing=locked \
fi; \
DEB=/var/cache/intel-npu/libze1_${LIBZE1_VERSION}_amd64.deb; \
if [ ! -f "$DEB" ]; then \
wget -q -O "$DEB" https://snapshot.ppa.launchpadcontent.net/kobuk-team/intel-graphics/ubuntu/20260606T100000Z/pool/main/l/level-zero-loader/libze1_${LIBZE1_VERSION}_amd64.deb; \
wget -q -O "$DEB" https://snapshot.ppa.launchpadcontent.net/kobuk-team/intel-graphics/ubuntu/20260324T100000Z/pool/main/l/level-zero-loader/libze1_${LIBZE1_VERSION}_amd64.deb; \
fi; \
mkdir /tmp/npu/ && cd /tmp/npu/ && tar -xf "$TGZ" && cp "$DEB" .; \
apt-get update; \
+1 -1
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@@ -1,4 +1,4 @@
blank_issues_enabled: false
blank_issues_enabled: true
contact_links:
- name: Got an idea?
url: https://github.com/ggml-org/llama.cpp/discussions/categories/ideas
-95
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@@ -1,95 +0,0 @@
name: "ccache-buckets"
description: "Save/restore latest GitHub Actions ccache matching a key prefix to/from HF buckets"
inputs:
key:
description: "Cache key prefix to match and load"
required: true
folder:
description: "Bucket folder containing ccache files"
required: true
evict-old-files:
description: "Corresponds to the ccache --evict-older-than AGE option, where AGE is the number of seconds or days followed by the 's' or 'd' suffix respectively."
default: ''
save:
description: "Save ccache"
required: false
default: false
type: boolean
hf_bucket:
description: 'Hugging Face buckets path'
required: true
runs:
using: "composite"
steps:
- name: Install Hugging Face Hub CLI
shell: bash
run: |
python3 -m venv .venv-hf
.venv-hf/bin/pip install -U huggingface_hub==1.28.0
- name: Restore ccache from buckets
if: ${{ inputs.save != 'true' }}
shell: bash
run: |
set +e -uo pipefail
source .venv-hf/bin/activate
CCACHE_DIR=$(ccache -k cache_dir)
if [[ -d "$CCACHE_DIR" ]]; then
CACHE_PATH=$(hf buckets list "hf://buckets/${{ inputs.hf_bucket }}/${{ inputs.folder }}" --json | jq -r '[.[] | select(.type == "file") | select(.path | startswith("${{ inputs.folder }}/${{ inputs.key }}") and endswith(".tar.gz"))] | sort_by(.path) | last | .path // ""')
if [[ -n "$CACHE_PATH" ]]; then
echo "Restoring ccache from '$CACHE_PATH'."
hf buckets cp "hf://buckets/${{ inputs.hf_bucket }}/$CACHE_PATH" ccache_bucket.tar.gz
mkdir -p ccache_bucket
if tar -xzf ccache_bucket.tar.gz -C ccache_bucket; then
rm -rf "$CCACHE_DIR"
mv ccache_bucket "$CCACHE_DIR"
ccache -z
fi
rm ccache_bucket.tar.gz
else
echo "No ccache found."
fi
else
echo "'$CCACHE_DIR' not found."
fi
- name: Save ccache to buckets
if: ${{ inputs.save == 'true' }}
shell: bash
run: |
if [[ -n "$HF_TOKEN" ]]; then
set +e -uo pipefail
source .venv-hf/bin/activate
CCACHE_DIR=$(ccache -k cache_dir)
if [[ -d "$CCACHE_DIR" ]]; then
ccache -s
if [[ -n "${{ inputs.evict-old-files }}" ]]; then
ccache --evict-older-than "${{ inputs.evict-old-files }}"
fi
DATESTAMP=$(date -u +'%Y-%m-%dT%H:%M:%SZ')
CACHEFILE="${{ inputs.key }}-$DATESTAMP.tar.gz"
if tar -czf ccache_bucket.tar.gz -C "$CCACHE_DIR" .; then
hf buckets cp ccache_bucket.tar.gz "hf://buckets/${{ inputs.hf_bucket }}/${{ inputs.folder }}/$CACHEFILE"
fi
rm ccache_bucket.tar.gz
else
echo "'$CCACHE_DIR' not found."
fi
fi
- name: Remove old ccache files from buckets
if: ${{ inputs.save == 'true' }}
shell: bash
run: |
if [[ -n "$HF_TOKEN" ]]; then
set +e -uo pipefail
source .venv-hf/bin/activate
CACHE_FILES=$(hf buckets list "hf://buckets/${{ inputs.hf_bucket }}/${{ inputs.folder }}" --json | jq -r '[.[] | select(.type == "file") | select((.uploaded_at | .[:19]+"Z" | fromdateiso8601) < (now - 5 * 60)) | select(.path | startswith("${{ inputs.folder }}/${{ inputs.key }}") and endswith(".tar.gz"))] | sort_by(.path)[:-1] | .[] | [.path // ""] | @tsv')
if [[ -n "$CACHE_FILES" ]]; then
echo "Removing old ccache files..."
while IFS=$'\t' read -r CACHE_PATH; do
hf buckets rm "hf://buckets/${{ inputs.hf_bucket }}/$CACHE_PATH" -y
done <<< "$CACHE_FILES"
fi
fi
+10 -38
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@@ -1,50 +1,22 @@
# note: place this as the last step of the job, so the new cache is saved by "Post ccache" right after the old one is cleared
name: "ccache-clear"
description: "Delete GitHub Actions caches matching a key prefix, oldest first"
description: "Delete all GitHub Actions caches matching a key prefix"
inputs:
key:
description: "Cache key prefix to match and delete"
required: true
older:
description: "Only delete caches created more than this long ago (e.g. 90m, 1h, 1d). By default all matching caches are deleted"
required: false
default: ""
min:
description: "Stop deleting if fewer than this many caches would remain (e.g. 1). By default there is no minimum"
required: false
default: "0"
dry-run:
description: "Only print the caches that would be deleted, without deleting them"
required: false
default: "false"
runs:
using: "composite"
steps:
- name: Install GitHub CLI if missing
shell: bash
run: |
# e.g. in container jobs, where it is not preinstalled
if ! command -v gh >/dev/null 2>&1; then
echo "GitHub CLI not found, installing..."
if ! command -v curl >/dev/null 2>&1; then
apt-get update >/dev/null 2>&1 || true
apt-get install -y curl >/dev/null 2>&1 || true
fi
mkdir -p -m 755 /etc/apt/keyrings
curl -fsSL https://cli.github.com/packages/githubcli-archive-keyring.gpg | tee /etc/apt/keyrings/githubcli-archive-keyring.gpg >/dev/null
chmod go+r /etc/apt/keyrings/githubcli-archive-keyring.gpg
echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/githubcli-archive-keyring.gpg] https://cli.github.com/packages stable main" > /etc/apt/sources.list.d/github-cli.list
apt-get update >/dev/null 2>&1 || true
apt-get install -y gh || { echo "Failed to install GitHub CLI (gh)" >&2; exit 1; }
fi
command -v gh >/dev/null 2>&1 || { echo "GitHub CLI (gh) is required but could not be installed" >&2; exit 1; }
- name: Clear caches
shell: bash
run: |
bash scripts/ccache-clear.sh \
--key "${{ inputs.key }}" \
--older "${{ inputs.older }}" \
--min "${{ inputs.min }}" \
${{ inputs.dry-run == 'true' && '--dry-run' || '' }}
CACHES=$(gh cache list --key "ccache-${{ inputs.key }}" --json id,key --jq '.[] | "\(.id) \(.key)"' 2>/dev/null)
if [ -z "$CACHES" ]; then
echo "No caches found with key prefix: ${{ inputs.key }}"
exit 0
fi
while read -r id key; do
echo "Deleting cache: $id ($key)"
gh cache delete "$id"
done <<< "$CACHES"
@@ -0,0 +1,20 @@
name: "Linux - Setup Vulkan SDK"
description: "Setup Vulkan SDK for Linux"
inputs:
path:
description: "Installation path"
required: true
version:
description: "Vulkan SDK version"
required: true
runs:
using: "composite"
steps:
- name: Setup Vulkan SDK
id: setup
uses: ./.github/actions/unarchive-tar
with:
url: https://sdk.lunarg.com/sdk/download/${{ inputs.version }}/linux/vulkan_sdk.tar.xz
path: ${{ inputs.path }}
strip: 1
@@ -6,7 +6,8 @@ inputs:
required: true
cuda_arch:
description: "CUDA target architecture"
required: true
required: false
default: "x64"
runs:
using: "composite"
@@ -24,7 +24,7 @@ runs:
write-host "Installing ROCm wheels for multi-arch support"
# Install ROCm wheels for multi-arch support (this may take several minutes)
python -m pip install --index-url https://stable.repo.amd.com/rocm/whl-next/ "rocm[libraries,devel]==${{ inputs.version }}"
python -m pip install --index-url https://repo.amd.com/rocm/whl-multi-arch/ "rocm[libraries,devel]==${{ inputs.version }}"
# Pre-expand the devel tree so it is included in the cache
write-host "Initializing ROCm devel tree"
+1 -1
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@@ -110,7 +110,7 @@ jobs:
# cache on: https://github.com/ggerganov/tmp2/actions/runs/26534713799/job/78224189394
#
#- name: ccache
# uses: ggml-org/ccache-action@v1.2.24
# uses: ggml-org/ccache-action@v1.2.21
# with:
# key: android-ubuntu-arm64
# evict-old-files: 1d
+32 -55
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@@ -22,8 +22,7 @@ on:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/build-apple.yml',
'ggml/src/ggml-metal/**',
'ggml/src/ggml-rpc/**'
'ggml/src/ggml-metal/**'
]
concurrency:
@@ -47,19 +46,11 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-arm64
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: apple-arm64
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
@@ -74,25 +65,7 @@ jobs:
-DGGML_RPC=ON \
-DCMAKE_OSX_DEPLOYMENT_TARGET=13.3
time cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: apple-arm64
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
- name: Check for leaks
run: |
cmd=(./build/bin/test-thread-safety -hf ggml-org/gemma-3-270m-qat-GGUF -ngl 99 -p "$(printf 'hello %.0s' {1..128})" -n 16 -c 512 -ub 32 -np 2 -t 2 -lv 1)
leaks -atExit -- "${cmd[@]}"
# Graphics devices are leaked by Metal in Apple code sometimes, so we ignore those leaks
OBJC_DEBUG_MISSING_POOLS=YES "${cmd[@]}" 2>&1 | awk '{ print } index($0, "autoreleased with no pool in place") && !/class [a-zA-Z0-9]+Device autoreleased/ { found = 1 } END { exit found }'
leaks -atExit -- ./build/bin/test-thread-safety -hf ggml-org/gemma-3-270m-qat-GGUF -ngl 99 -p "$(printf 'hello %.0s' {1..128})" -n 16 -c 512 -ub 32 -np 2 -t 2 -lv 1
- name: Test
id: cmake_test
@@ -109,19 +82,11 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-x64
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: apple-x64
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
@@ -138,18 +103,6 @@ jobs:
-DCMAKE_OSX_DEPLOYMENT_TARGET=13.3
time cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: apple-x64
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
- name: Test
id: cmake_test
run: |
@@ -210,6 +163,14 @@ jobs:
id: checkout
uses: actions/checkout@v6
# TODO: this likely does not do anything - if yes, remove it
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-tvos
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
run: |
@@ -235,6 +196,14 @@ jobs:
id: checkout
uses: actions/checkout@v6
# TODO: this likely does not do anything - if yes, remove it
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-visionos
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
run: |
@@ -265,6 +234,14 @@ jobs:
id: checkout
uses: actions/checkout@v6
# TODO: this likely does not do anything - if yes, remove it
- name: ccache
uses: ggml-org/ccache-action@v1.2.21
with:
key: apple-swift
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Download xcframework artifact
uses: actions/download-artifact@v7
with:
+32 -5
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@@ -10,6 +10,33 @@ concurrency:
cancel-in-progress: true
jobs:
ubuntu-24-vulkan-cache:
runs-on: ubuntu-24.04
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Get latest Vulkan SDK version
id: vulkan_sdk_version
run: |
echo "VULKAN_SDK_VERSION=$(curl https://vulkan.lunarg.com/sdk/latest/linux.txt)" >> "$GITHUB_ENV"
- name: Setup Cache
uses: actions/cache@v5
id: cache-sdk
with:
path: ./vulkan_sdk
key: cache-gha-vulkan-sdk-${{ env.VULKAN_SDK_VERSION }}-${{ runner.os }}
- name: Setup Vulkan SDK
if: steps.cache-sdk.outputs.cache-hit != 'true'
uses: ./.github/actions/linux-setup-vulkan
with:
path: ./vulkan_sdk
version: ${{ env.VULKAN_SDK_VERSION }}
#ubuntu-24-spacemit-cache:
# runs-on: ubuntu-24.04
@@ -40,9 +67,9 @@ jobs:
runs-on: ubuntu-24.04
env:
# Sync versions in build-openvino.yml, build-self-hosted.yml, release.yml, build-cache.yml, .devops/openvino.Dockerfile
OPENVINO_VERSION_MAJOR: "2026.3.1"
OPENVINO_VERSION_FULL: "2026.3.1.22476.56d9685302d"
# Sync versions in build.yml, build-self-hosted.yml, release.yml, build-cache.yml, .devops/openvino.Dockerfile
OPENVINO_VERSION_MAJOR: "2026.2.1"
OPENVINO_VERSION_FULL: "2026.2.1.21919.ede283a88e3"
steps:
- name: Clone
@@ -69,8 +96,8 @@ jobs:
env:
# Sync versions in build.yml, build-self-hosted.yml, release.yml, build-cache.yml, .devops/openvino.Dockerfile
OPENVINO_VERSION_MAJOR: "2026.3.1"
OPENVINO_VERSION_FULL: "2026.3.1.22476.56d9685302d"
OPENVINO_VERSION_MAJOR: "2026.2.1"
OPENVINO_VERSION_FULL: "2026.2.1.21919.ede283a88e3"
steps:
- name: Clone
+20 -16
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@@ -27,26 +27,30 @@ jobs:
cmake --install build --prefix "$PREFIX" --config Release
export LLAMA_CONFIG="$PREFIX"/lib/cmake/llama/llama-config.cmake
build_commit=$(git rev-parse --short HEAD | xargs)
build_number=$(git rev-list --count HEAD | xargs)
tclsh <<'EOF'
set build(commit) [string trim [exec git rev-parse --short HEAD]]
set build(number) [string trim [exec git rev-list --count HEAD]]
major=$(grep -oE "set\(LLAMA_VERSION_MAJOR[[:space:]]+[0-9]+" CMakeLists.txt | grep -oE "[0-9]+$")
minor=$(grep -oE "set\(LLAMA_VERSION_MINOR[[:space:]]+[0-9]+" CMakeLists.txt | grep -oE "[0-9]+$")
patch=$(grep -oE "set\(LLAMA_VERSION_PATCH[[:space:]]+[0-9]+" CMakeLists.txt | grep -oE "[0-9]+$")
build_version="$major.$minor.$patch"
set cmakelists [read [open "CMakeLists.txt" r]]
regexp {set\(LLAMA_VERSION_MAJOR\s+(\d+)\)} $cmakelists -> major
regexp {set\(LLAMA_VERSION_MINOR\s+(\d+)\)} $cmakelists -> minor
regexp {set\(LLAMA_VERSION_PATCH\s+(\d+)\)} $cmakelists -> patch
set build(version) "$major.$minor.$patch"
checks=("set\(LLAMA_VERSION[[:space:]]+$build_version\)"
"set\(LLAMA_BUILD_COMMIT[[:space:]]+$build_commit\)"
"set\(LLAMA_BUILD_NUMBER[[:space:]]+$build_number\)")
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)\\)"]
for check in "${checks[@]}"; do
if ! grep -qE "$check" "$LLAMA_CONFIG"; then
echo "Checking llama-config.cmake version... \"$check\" failed!"
puts -nonewline "Checking llama-config.cmake version... "
foreach check $checks {
if {![regexp -expanded -- $check $llamaconfig]} {
puts "\"$check\" failed!"
exit 1
fi
done
echo "Checking llama-config.cmake version... success."
}
}
puts "success."
EOF
cd examples/simple-cmake-pkg
cmake -S . -B build -DCMAKE_PREFIX_PATH="$PREFIX"/lib/cmake
+21 -39
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@@ -21,7 +21,6 @@ on:
paths: [
'.github/workflows/build-cpu.yml',
'.github/workflows/build-cmake-pkg.yml',
'ggml/src/ggml-rpc/**',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
@@ -62,10 +61,11 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: cpu-${{ matrix.os }}
save: false
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build Dependencies
id: build_depends
@@ -90,36 +90,16 @@ jobs:
python3 -m pip install --upgrade pip setuptools
pip3 install ./gguf-py
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: cpu-${{ matrix.os }}
folder: llama.cpp
hf_bucket: ggml-org/cache
- name: Build
id: cmake_build
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_FATAL_WARNINGS=ON \
-DGGML_RPC=ON
-DGGML_RPC=ON \
-DGGML_NATIVE=OFF
time cmake --build build --config Release -j $(nproc)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: cpu-${{ matrix.os }}
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
- name: Test
id: cmake_test
run: |
@@ -138,25 +118,28 @@ jobs:
./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
windows:
name: windows / ${{ matrix.build }}
runs-on: windows-2025
env:
OPENBLAS_VERSION: 0.3.23
SDE_VERSION: 9.33.0-2024-01-07
VULKAN_VERSION: 1.4.357.0
strategy:
matrix:
include:
- build: 'x64-cpu-static'
arch: 'x64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DGGML_OPENMP_FETCH=ON -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DBUILD_SHARED_LIBS=OFF'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DBUILD_SHARED_LIBS=OFF'
- build: 'x64-openblas'
arch: 'x64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_OPENMP=OFF -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS -DBLAS_INCLUDE_DIRS="$env:RUNNER_TEMP/openblas/include" -DBLAS_LIBRARIES="$env:RUNNER_TEMP/openblas/lib/openblas.lib"'
- build: 'x64-vulkan'
arch: 'x64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_VULKAN=ON'
- build: 'arm64'
arch: 'arm64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DGGML_NATIVE=OFF -DGGML_OPENMP_FETCH=ON -DLLAMA_BUILD_SERVER=ON'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DGGML_NATIVE=OFF -DLLAMA_BUILD_SERVER=ON'
steps:
- name: Clone
@@ -164,7 +147,7 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: cpu-windows-2025-${{ matrix.build }}
variant: ccache
@@ -184,6 +167,15 @@ jobs:
$lib = $(join-path $msvc 'bin\Hostx64\x64\lib.exe')
& $lib /machine:x64 "/def:${env:RUNNER_TEMP}/openblas/lib/libopenblas.def" "/out:${env:RUNNER_TEMP}/openblas/lib/openblas.lib" /name:openblas.dll
- name: Install Vulkan SDK
id: get_vulkan
if: ${{ matrix.build == 'x64-vulkan' }}
run: |
curl.exe -o $env:RUNNER_TEMP/VulkanSDK-Installer.exe -L "https://sdk.lunarg.com/sdk/download/${env:VULKAN_VERSION}/windows/vulkansdk-windows-X64-${env:VULKAN_VERSION}.exe"
& "$env:RUNNER_TEMP\VulkanSDK-Installer.exe" --accept-licenses --default-answer --confirm-command install
Add-Content $env:GITHUB_ENV "VULKAN_SDK=C:\VulkanSDK\${env:VULKAN_VERSION}"
Add-Content $env:GITHUB_PATH "C:\VulkanSDK\${env:VULKAN_VERSION}\bin"
- name: Install Ninja
id: install_ninja
run: |
@@ -223,13 +215,3 @@ jobs:
# cd build
# $env:LLAMA_SKIP_TESTS_SLOW_ON_EMULATOR = 1
# & $sde -future -- ctest -L main -C Release --verbose --timeout 900
- name: ccache-clear
uses: ./.github/actions/ccache-clear
env:
GH_TOKEN: ${{ github.token }}
with:
key: cpu-windows-2025-${{ matrix.build }}
older: 5m
min: 1
dry-run: ${{ github.event_name != 'push' || github.ref != 'refs/heads/master' }}
+12 -72
View File
@@ -50,22 +50,14 @@ jobs:
DEBIAN_FRONTEND: noninteractive
run: |
apt update
apt install -y cmake build-essential ninja-build libgomp1 git libssl-dev jq python3 python3-venv python3-pip
apt install -y cmake build-essential ninja-build libgomp1 git libssl-dev
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: cuda-ubuntu-24.04-cuda
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: cuda-ubuntu-24.04-cuda
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build with CMake
# TODO: Remove GGML_CUDA_CUB_3DOT2 flag once CCCL 3.2 is bundled within CTK and that CTK version is used in this project
@@ -80,18 +72,6 @@ jobs:
-DGGML_CUDA_CUB_3DOT2=ON
cmake --build build
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: cuda-ubuntu-24.04-cuda
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
hip:
runs-on: ubuntu-22.04
container: rocm/dev-ubuntu-22.04:6.1.2
@@ -105,22 +85,14 @@ jobs:
id: depends
run: |
sudo apt-get update
sudo apt-get install -y build-essential git cmake rocblas-dev hipblas-dev libssl-dev rocwmma-dev jq python3-venv
sudo apt-get install -y build-essential git cmake rocblas-dev hipblas-dev libssl-dev rocwmma-dev
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: cuda-ubuntu-22.04-hip
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: cuda-ubuntu-22.04-hip
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build with native CMake HIP support
id: cmake_build
@@ -131,18 +103,6 @@ jobs:
-DGGML_HIP=ON
cmake --build build --config Release -j $(nproc)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: cuda-ubuntu-22.04-hip
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
musa:
runs-on: ubuntu-22.04
container: mthreads/musa:rc4.3.0-devel-ubuntu22.04-amd64
@@ -156,22 +116,14 @@ jobs:
id: depends
run: |
apt-get update
apt-get install -y build-essential git cmake libssl-dev jq
apt-get install -y build-essential git cmake libssl-dev
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: cuda-ubuntu-22.04-musa
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: cuda-ubuntu-22.04-musa
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build with native CMake MUSA support
id: cmake_build
@@ -179,15 +131,3 @@ jobs:
cmake -B build -S . \
-DGGML_MUSA=ON
time cmake --build build --config Release -j $(nproc)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: cuda-ubuntu-22.04-musa
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
+15 -21
View File
@@ -22,7 +22,6 @@ env:
jobs:
cuda:
name: windows-cuda (${{ matrix.cuda }}, ${{ matrix.arch }})
runs-on: windows-2022
permissions:
@@ -30,16 +29,7 @@ jobs:
strategy:
matrix:
include:
- cuda: '12.4'
arch: x64
defines: '-DGGML_CUDA_CUB_3DOT2=ON'
- cuda: '13.3'
arch: x64
defines: ''
- cuda: '13.4'
arch: arm64
defines: '-DCMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-msvc-cuda.cmake'
cuda: ['12.4', '13.3']
steps:
- name: Clone
@@ -47,15 +37,14 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: release-windows-2022-${{ matrix.arch }}-cuda-${{ matrix.cuda }}
key: release-windows-2022-x64-cuda-${{ matrix.cuda }}
- name: Install Cuda Toolkit
uses: ./.github/actions/windows-setup-cuda
with:
cuda_version: ${{ matrix.cuda }}
cuda_arch: ${{ matrix.arch }}
- name: Install Ninja
id: install_ninja
@@ -65,21 +54,26 @@ jobs:
- name: Build
id: cmake_build
shell: cmd
# TODO: Remove GGML_CUDA_CUB_3DOT2 flag once CCCL 3.2 is bundled within CTK and that CTK version is used in this project
run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" ${{ matrix.arch == 'x64' && 'x64' || 'amd64_arm64' }}
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 ^
-DLLAMA_BUILD_SERVER=ON ^
-DLLAMA_BUILD_BORINGSSL=ON ^
-DGGML_NATIVE=OFF ^
-DGGML_CPU=OFF ^
-DGGML_BACKEND_DL=ON ^
-DGGML_CPU_ALL_VARIANTS=ON ^
-DGGML_CUDA=ON ^
-DLLAMA_BUILD_BORINGSSL=ON ${{ matrix.defines }}
-DGGML_RPC=ON ^
-DGGML_CUDA_CUB_3DOT2=ON
set /A NINJA_JOBS=%NUMBER_OF_PROCESSORS%-1
cmake --build build --config Release -j %NINJA_JOBS% --target ggml-cuda
cmake --build build --config Release -j %NINJA_JOBS% -t ggml
cmake --build build --config Release
- name: ccache-clear
uses: ./.github/actions/ccache-clear
with:
key: release-windows-2022-${{ matrix.arch }}-cuda-${{ matrix.cuda }}
key: release-windows-2022-x64-cuda-${{ matrix.cuda }}
hip:
runs-on: windows-2022
@@ -152,7 +146,7 @@ jobs:
& "${env:HIP_PATH}\lib\llvm\bin\clang.exe" --version
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
# TODO: this build does not match the build in release.yml, so we use a different cache key
# ideally, the builds should match, similar to the CUDA build above so that we would be able
+1 -1
View File
@@ -35,7 +35,7 @@ jobs:
uses: actions/checkout@v6
#- name: ccache
# uses: ggml-org/ccache-action@v1.2.24
# uses: ggml-org/ccache-action@v1.2.16
# with:
# key: msys-windows-2025-x64
# variant: ccache
+1 -11
View File
@@ -44,7 +44,7 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: opencl-windows-2025-x64
variant: ccache
@@ -80,13 +80,3 @@ jobs:
run: |
cmake -S . -B build -G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" -DGGML_OPENCL=ON -DGGML_OPENCL_USE_ADRENO_KERNELS=ON -DLLAMA_BUILD_BORINGSSL=ON
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS}
- name: ccache-clear
uses: ./.github/actions/ccache-clear
env:
GH_TOKEN: ${{ github.token }}
with:
key: opencl-windows-2025-x64
older: 5m
min: 1
dry-run: ${{ github.event_name != 'push' || github.ref != 'refs/heads/master' }}
+11 -20
View File
@@ -32,8 +32,6 @@ env:
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
# TODO: fix failing tests on OpenVINO backend
CTEST_EXCLUDE: "test-llama-archs|^test-recurrent-state-|test-backend-ops|test-save-load-state"
jobs:
ubuntu-24-openvino:
@@ -41,8 +39,8 @@ jobs:
env:
# Sync versions in build-openvino.yml, build-self-hosted.yml, release.yml, build-cache.yml, .devops/openvino.Dockerfile
OPENVINO_VERSION_MAJOR: "2026.3.1"
OPENVINO_VERSION_FULL: "2026.3.1.22476.56d9685302d"
OPENVINO_VERSION_MAJOR: "2026.2.1"
OPENVINO_VERSION_FULL: "2026.2.1.21919.ede283a88e3"
steps:
- name: Clone
@@ -80,24 +78,26 @@ jobs:
- name: Test (CPU)
id: cmake_test_cpu
# TODO: fix and re-enable the `test-llama-archs` test below
run: |
cd ${{ github.workspace }}
ctest --test-dir build/ReleaseOV -L main -E "${{ env.CTEST_EXCLUDE }}" --verbose --timeout 3000
ctest --test-dir build/ReleaseOV -L main -E "test-llama-archs" --verbose --timeout 2000
- name: Test (GPU)
id: cmake_test_gpu
# TODO: fix and re-enable the `test-llama-archs` test below
run: |
cd ${{ github.workspace }}
export GGML_OPENVINO_DEVICE=GPU
ctest --test-dir build/ReleaseOV -L main -E "${{ env.CTEST_EXCLUDE }}" --verbose --timeout 3000
ctest --test-dir build/ReleaseOV -L main -E "test-llama-archs" --verbose --timeout 3000
openvino-windows-2022:
runs-on: windows-2022
env:
# Sync versions in build-openvino.yml, build-self-hosted.yml, release.yml, build-cache.yml, .devops/openvino.Dockerfile
OPENVINO_VERSION_MAJOR: "2026.3.1"
OPENVINO_VERSION_FULL: "2026.3.1.22476.56d9685302d"
OPENVINO_VERSION_MAJOR: "2026.2.1"
OPENVINO_VERSION_FULL: "2026.2.1.21919.ede283a88e3"
steps:
- name: Clone
@@ -105,7 +105,7 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: openvino-windows-2022
variant: ccache
@@ -159,20 +159,11 @@ jobs:
- name: Test (CPU)
id: cmake_test_cpu
shell: cmd
# TODO: fix and re-enable the `test-llama-archs` test below
run: |
REM Find extracted OpenVINO folder dynamically
for /d %%i in (openvino_toolkit\*) do set OPENVINO_ROOT=%%i
call "%OPENVINO_ROOT%\setupvars.bat"
cd build
ctest --test-dir ReleaseOV -L main -E "${{ env.CTEST_EXCLUDE }}" -C Release --verbose --timeout 3000
- name: ccache-clear
uses: ./.github/actions/ccache-clear
env:
GH_TOKEN: ${{ github.token }}
with:
key: openvino-windows-2022
older: 5m
min: 1
dry-run: ${{ github.event_name != 'push' || github.ref != 'refs/heads/master' }}
ctest --test-dir ReleaseOV -L main -E "test-llama-archs" -C Release --verbose --timeout 3000
+2 -2
View File
@@ -67,7 +67,7 @@ jobs:
# note: sparing some ccache since these jobs run on dedicated runners that are not part of the organitzation
#- name: ccache
# uses: ggml-org/ccache-action@v1.2.24
# uses: ggml-org/ccache-action@afde29e5b5422e5da23cb1f639e8baecadeadfc3 # https://github.com/ggml-org/ccache-action/pull/1
# with:
# key: riscv-ubuntu-native
# evict-old-files: 1d
@@ -137,7 +137,7 @@ jobs:
# note: sparing some ccache since these jobs run on dedicated runners that are not part of the organitzation
#- name: ccache
# uses: ggml-org/ccache-action@v1.2.24
# uses: ggml-org/ccache-action@afde29e5b5422e5da23cb1f639e8baecadeadfc3 # https://github.com/ggml-org/ccache-action/pull/1
# with:
# key: riscv-ubuntu-native-sanitizer-${{ matrix.sanitizer }}-${{ matrix.build_type }}
# evict-old-files: 1d
+66
View File
@@ -0,0 +1,66 @@
name: CI (rpc)
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
paths: [
'.github/workflows/build-rpc.yml',
'**/CMakeLists.txt',
'**/.cmake',
'**/*.h',
'**/*.hpp',
'**/*.c',
'**/*.cpp'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'.github/workflows/build-rpc.yml',
'ggml/src/ggml-rpc/**'
]
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
env:
GGML_NLOOP: 3
GGML_N_THREADS: 1
LLAMA_ARG_LOG_COLORS: 1
LLAMA_ARG_LOG_PREFIX: 1
LLAMA_ARG_LOG_TIMESTAMPS: 1
jobs:
ubuntu-24-rpc:
runs-on: ${{ 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
continue-on-error: true
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install build-essential libssl-dev ninja-build
- name: Build
id: cmake_build
run: |
cmake -B build \
-G "Ninja" \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_RPC=ON
time cmake --build build --config Release -j $(nproc)
- name: Test
id: cmake_test
run: |
cd build
ctest -L main --verbose
+1 -1
View File
@@ -55,7 +55,7 @@ jobs:
uses: actions/checkout@v6
# - name: ccache
# uses: ggml-org/ccache-action@v1.2.24
# uses: ggml-org/ccache-action@v1.2.21
# if: ${{ matrix.sanitizer != 'UNDEFINED' }}
# with:
# key: ctest-${{ matrix.sanitizer }}-ubuntu-24.04
+2 -2
View File
@@ -288,8 +288,8 @@ jobs:
env:
# Sync versions in build.yml, build-self-hosted.yml, release.yml, build-cache.yml, .devops/openvino.Dockerfile
OPENVINO_VERSION_MAJOR: "2026.3.1"
OPENVINO_VERSION_FULL: "2026.3.1.22476.56d9685302d"
OPENVINO_VERSION_MAJOR: "2026.2.1"
OPENVINO_VERSION_FULL: "2026.2.1.21919.ede283a88e3"
steps:
- name: Clone
+4 -34
View File
@@ -75,19 +75,11 @@ jobs:
sudo apt-get install -y ./level-zero.deb ./level-zero-devel.deb
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: sycl-ubuntu-24-${{ matrix.build }}
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: sycl-ubuntu-24-${{ matrix.build }}
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
@@ -104,18 +96,6 @@ jobs:
-DGGML_SYCL_F16=${{ matrix.fp16 }}
time cmake --build build --config Release -j $(nproc)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: sycl-ubuntu-24-${{ matrix.build }}
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
windows-latest-sycl:
runs-on: windows-2022
@@ -147,7 +127,7 @@ jobs:
"LEVEL_ZERO_V1_SDK_PATH=C:/level-zero-sdk" | Out-File -FilePath $env:GITHUB_ENV -Append
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: sycl-windows-latest
variant: ccache
@@ -159,13 +139,3 @@ jobs:
- name: Build
id: cmake_build
run: examples/sycl/win-build-sycl.bat
- name: ccache-clear
uses: ./.github/actions/ccache-clear
env:
GH_TOKEN: ${{ github.token }}
with:
key: sycl-windows-latest
older: 5m
min: 1
dry-run: ${{ github.event_name != 'push' || github.ref != 'refs/heads/master' }}
+18 -115
View File
@@ -53,20 +53,12 @@ jobs:
echo "CXX=g++-14" >> "$GITHUB_ENV"
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: vulkan-ubuntu-24.04-arm
key: vulkan-ubuntu-24.04-arm-new
variant: ccache
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: vulkan-ubuntu-24.04-arm
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Configure
id: cmake_configure
@@ -81,18 +73,6 @@ jobs:
run: |
time cmake --build build -j $(nproc)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: vulkan-ubuntu-24.04-arm
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
ubuntu-llvmpipe:
runs-on: ubuntu-24.04
@@ -113,28 +93,26 @@ jobs:
run: |
echo "VULKAN_SDK_VERSION=$(curl https://vulkan.lunarg.com/sdk/latest/linux.txt)" >> "$GITHUB_ENV"
- name: Setup Vulkan SDK
id: setup
uses: ./.github/actions/unarchive-tar
- name: Use Vulkan SDK Cache
uses: actions/cache@v5
id: cache-sdk
with:
url: https://sdk.lunarg.com/sdk/download/${{ env.VULKAN_SDK_VERSION }}/linux/vulkan_sdk.tar.xz
path: ./vulkan_sdk
strip: 1
key: cache-gha-vulkan-sdk-${{ env.VULKAN_SDK_VERSION }}-${{ runner.os }}
- name: Setup Vulkan SDK
if: steps.cache-sdk.outputs.cache-hit != 'true'
uses: ./.github/actions/linux-setup-vulkan
with:
path: ./vulkan_sdk
version: ${{ env.VULKAN_SDK_VERSION }}
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: vulkan-ubuntu-24.04-llvmpipe
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: vulkan-ubuntu-24.04-llvmpipe
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
@@ -145,18 +123,6 @@ jobs:
-DGGML_VULKAN=ON
cmake --build build --config Release -j $(nproc)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: vulkan-ubuntu-24.04-llvmpipe
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
- name: Test
id: cmake_test
run: |
@@ -167,66 +133,3 @@ jobs:
# This is using llvmpipe and runs slower than other backends
# test-backend-ops is too slow on llvmpipe, skip it
ctest -L main -E test-backend-ops --verbose --timeout 900
windows:
runs-on: windows-2025
env:
VULKAN_VERSION: 1.4.357.0
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
with:
key: cpu-windows-2025-x64-vulkan
variant: ccache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Install Vulkan SDK
id: get_vulkan
run: |
curl.exe -o $env:RUNNER_TEMP/VulkanSDK-Installer.exe -L "https://sdk.lunarg.com/sdk/download/${env:VULKAN_VERSION}/windows/vulkansdk-windows-X64-${env:VULKAN_VERSION}.exe"
& "$env:RUNNER_TEMP\VulkanSDK-Installer.exe" --accept-licenses --default-answer --confirm-command install
Add-Content $env:GITHUB_ENV "VULKAN_SDK=C:\VulkanSDK\${env:VULKAN_VERSION}"
Add-Content $env:GITHUB_PATH "C:\VulkanSDK\${env:VULKAN_VERSION}\bin"
- name: Install Ninja
id: install_ninja
run: |
choco install ninja
- name: Build
id: cmake_build
run: |
cmake -S . -B build -G "Ninja Multi-Config" `
-D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake `
-DCMAKE_BUILD_TYPE=Release `
-DGGML_NATIVE=OFF `
-DLLAMA_BUILD_SERVER=ON `
-DGGML_RPC=ON `
-DGGML_BACKEND_DL=ON `
-DGGML_CPU_ALL_VARIANTS=ON `
-DGGML_VULKAN=ON `
-DLLAMA_BUILD_BORINGSSL=ON
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS}
- name: Test
id: cmake_test
run: |
cd build
ctest -L main -C Release --verbose --timeout 900
- name: ccache-clear
uses: ./.github/actions/ccache-clear
env:
GH_TOKEN: ${{ github.token }}
with:
key: cpu-windows-2025-x64-vulkan
older: 5m
min: 1
dry-run: ${{ github.event_name != 'push' || github.ref != 'refs/heads/master' }}
+3 -23
View File
@@ -54,10 +54,11 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: webgpu-ubuntu-24.04-arm-wasm
save: false
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Install Emscripten
run: |
@@ -75,15 +76,6 @@ jobs:
"https://github.com/google/dawn/releases/download/${DAWN_TAG}/${EMDAWN_PKG}"
unzip emdawn.zip
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: webgpu-ubuntu-24.04-arm-wasm
folder: llama.cpp
hf_bucket: ggml-org/cache
- name: Build WASM WebGPU
run: |
source emsdk/emsdk_env.sh
@@ -96,15 +88,3 @@ jobs:
-DEMDAWNWEBGPU_DIR=emdawnwebgpu_pkg
time cmake --build build-wasm --config Release --target test-backend-ops -j $(nproc)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: webgpu-ubuntu-24.04-arm-wasm
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
+6 -46
View File
@@ -69,10 +69,11 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: webgpu-macos-latest
save: false
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Dawn Dependency
id: dawn-depends
@@ -87,15 +88,6 @@ jobs:
mkdir dawn
tar -xvf artifact.tar.gz -C dawn --strip-components=1
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: webgpu-macos-latest
folder: llama.cpp
hf_bucket: ggml-org/cache
- name: Build
id: cmake_build
run: |
@@ -103,18 +95,6 @@ jobs:
cmake -B build -G "Ninja" -DCMAKE_BUILD_TYPE=Release -DGGML_WEBGPU=ON -DGGML_METAL=OFF -DGGML_BLAS=OFF
time cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: webgpu-macos-latest
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
- name: Test
id: cmake_test
run: |
@@ -130,10 +110,11 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: webgpu-ubuntu-24.04
save: false
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Dependencies
id: depends
@@ -157,15 +138,6 @@ jobs:
mkdir dawn
tar -xvf artifact.tar.gz -C dawn --strip-components=1
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: webgpu-ubuntu-24.04
folder: llama.cpp
hf_bucket: ggml-org/cache
- name: Build
id: cmake_build
run: |
@@ -174,18 +146,6 @@ jobs:
-DGGML_WEBGPU=ON
time cmake --build build --config Release -j $(nproc)
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: webgpu-ubuntu-24.04
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
- name: Test
id: cmake_test
run: |
+1 -1
View File
@@ -29,7 +29,7 @@ jobs:
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: copilot-setup-steps
evict-old-files: 1d
+2 -41
View File
@@ -44,7 +44,6 @@ jobs:
uses: actions/checkout@v6
with:
fetch-depth: 0
ssh-key: ${{ secrets.DEPLOY_KEY_RELEASE }}
- name: Determine source tag name
id: srctag
@@ -64,7 +63,7 @@ jobs:
needs: create_tag
uses: ./.github/workflows/ui-build.yml
with:
ui_version: ${{ needs.create_tag.outputs.source_tag }}
hf_ui_version: ${{ needs.create_tag.outputs.source_tag }}
prepare_matrices:
name: Prepare Docker matrices
@@ -162,7 +161,7 @@ jobs:
if: ${{ matrix.config.prebuilt_ui == true }}
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8
with:
name: llama-ui.zip
name: ui-build
path: tools/ui/dist
- name: Set up QEMU
@@ -394,11 +393,6 @@ jobs:
name: Create shared tags from digests
needs: [prepare_matrices, push_to_registry, create_tag]
runs-on: ubuntu-24.04
permissions:
contents: read
packages: write
id-token: write
attestations: write
strategy:
fail-fast: false
matrix:
@@ -433,7 +427,6 @@ jobs:
password: ${{ secrets.GITHUB_TOKEN }}
- name: Create tags from digests
id: create_tags
shell: bash
run: |
set -euo pipefail
@@ -445,7 +438,6 @@ jobs:
SRC_TAG="${{ needs.create_tag.outputs.source_tag }}"
BUILD_DATE="${{ steps.build_date.outputs.date }}"
COMMIT_SHA="${{ steps.checkout.outputs.commit }}"
echo "image_repo=${IMAGE_REPO}" >> "$GITHUB_OUTPUT"
TAGS="${{ matrix.config.tag }}"
ARCHES="${{ matrix.config.arches }}"
DIGEST_GLOB="/tmp/digests/*.tsv"
@@ -512,16 +504,6 @@ jobs:
echo "Creating ${merged_versioned_tag} from ${refs[*]}"
docker buildx imagetools create "${annotations[@]}" --tag "${merged_versioned_tag}" "${refs[@]}"
if [[ "$tag_name" == "${TAGS%% *}" ]]; then
local digest
digest="$(docker buildx imagetools inspect "${merged_versioned_tag}" --format '{{.Manifest.Digest}}')"
if [[ ! "$digest" =~ ^sha256:[0-9a-f]{64}$ ]]; then
echo "Invalid digest for ${merged_versioned_tag}: ${digest}" >&2
exit 1
fi
echo "${image_type}_digest=${digest}" >> "$GITHUB_OUTPUT"
fi
}
for tag in $TAGS; do
@@ -545,24 +527,3 @@ jobs:
done
env:
GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}'
- name: Attest full image
if: ${{ matrix.config.full }}
uses: actions/attest@v4
with:
subject-name: ${{ steps.create_tags.outputs.image_repo }}
subject-digest: ${{ steps.create_tags.outputs.full_digest }}
- name: Attest light image
if: ${{ matrix.config.light }}
uses: actions/attest@v4
with:
subject-name: ${{ steps.create_tags.outputs.image_repo }}
subject-digest: ${{ steps.create_tags.outputs.light_digest }}
- name: Attest server image
if: ${{ matrix.config.server }}
uses: actions/attest@v4
with:
subject-name: ${{ steps.create_tags.outputs.image_repo }}
subject-digest: ${{ steps.create_tags.outputs.server_digest }}
+4 -24
View File
@@ -49,22 +49,14 @@ jobs:
id: depends
run: |
sudo apt-get update
sudo apt-get install -y build-essential git cmake rocblas-dev hipblas-dev libssl-dev python3 python3-venv python3-pip jq
sudo apt-get install -y build-essential git cmake rocblas-dev hipblas-dev libssl-dev python3
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: hip-quality-check-ubuntu-22.04
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: hip-quality-check-ubuntu-22.04
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build with Werror
id: cmake_build
@@ -92,15 +84,3 @@ jobs:
cd build
make -j $(nproc) 2>&1 | tee metrics.log | grep -v 'Rpass-analysis=kernel-resource-usage\|remark:\|^$'
python3 ../scripts/hip/gcn-cdna-vgpr-check.py metrics.log
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: hip-quality-check-ubuntu-22.04
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
-99
View File
@@ -3,11 +3,6 @@ name: Make Release
on:
workflow_dispatch:
inputs:
commit:
description: 'Commit SHA to release (empty = branch HEAD)'
required: false
default: ''
type: string
dry_run:
description: 'Dry run - validate without creating the tag'
required: true
@@ -19,7 +14,6 @@ env:
permissions:
contents: write
packages: write
jobs:
make-release:
@@ -30,15 +24,12 @@ jobs:
uses: actions/checkout@v6
with:
ssh-key: ${{ secrets.DEPLOY_KEY_RELEASE }}
ref: ${{ inputs.commit != '' && inputs.commit || github.ref_name }}
fetch-depth: 0
- name: Run release checks
id: checks
run: bash scripts/make-release-checks.sh ${{ github.event.inputs.dry_run == 'true' && '--dry-run' || '' }}
env:
GITHUB_REPOSITORY: ${{ github.repository }}
RELEASE_BRANCH: ${{ github.ref_name }}
- name: Create release tag
if: ${{ github.event.inputs.dry_run == 'false' }}
@@ -50,102 +41,12 @@ jobs:
git push origin "${VERSION}"
echo "Created and pushed tag ${VERSION}"
- name: Generate release description
id: desc
run: bash scripts/make-release-desc.sh "${{ steps.checks.outputs.version }}"
env:
GITHUB_REPOSITORY: ${{ github.repository }}
- name: Create nightly-tag.txt
id: nightly_tag_file
run: |
NIGHTLY_TAG="${{ steps.desc.outputs.nightly_tag }}"
if [[ -z "${NIGHTLY_TAG}" ]]; then
echo "Warning: no nightly tag found for the release commit - nightly-tag.txt will not be created"
echo "create=false" >> "$GITHUB_OUTPUT"
exit 0
fi
echo "${NIGHTLY_TAG}" > nightly-tag.txt
echo "create=true" >> "$GITHUB_OUTPUT"
echo "nightly-tag.txt:"
cat nightly-tag.txt
- name: Create release
id: create_release
if: ${{ github.event.inputs.dry_run == 'false' }}
uses: ggml-org/action-create-release@v1
env:
GITHUB_TOKEN: ${{ github.token }}
with:
tag_name: ${{ steps.checks.outputs.version }}
prerelease: false
# TODO: enrich the body of the release with more information
body: |
## Overview
New version has been released.
## Assets
${{ steps.desc.outputs.nightly }}
## More info
- [Releases and versioning of `ggml-org` projects](https://github.com/ggml-org/ggml/discussions/1579)
## ${{ steps.desc.outputs.changelog_title }}
${{ steps.desc.outputs.changelog }}
- name: Upload nightly-tag.txt
if: ${{ github.event.inputs.dry_run == 'false' && steps.nightly_tag_file.outputs.create == 'true' }}
uses: actions/github-script@v8
with:
github-token: ${{secrets.GITHUB_TOKEN}}
script: |
const fs = require('fs');
const release_id = '${{ steps.create_release.outputs.id }}';
console.log('uploadReleaseAsset', 'nightly-tag.txt');
await github.rest.repos.uploadReleaseAsset({
owner: context.repo.owner,
repo: context.repo.repo,
release_id: release_id,
name: 'nightly-tag.txt',
data: await fs.readFileSync('./nightly-tag.txt')
});
- name: Re-tag container images with release version
if: ${{ github.event.inputs.dry_run == 'false' && steps.desc.outputs.nightly_tag != '' }}
env:
GITHUB_REPOSITORY_OWNER: ${{ github.repository_owner }}
run: |
VERSION="${{ steps.checks.outputs.version }}"
NIGHTLY_TAG="${{ steps.desc.outputs.nightly_tag }}"
REPO_OWNER="${GITHUB_REPOSITORY_OWNER,,}"
IMAGE_REPO="ghcr.io/${REPO_OWNER}/${{ github.event.repository.name }}"
echo "${{ secrets.GITHUB_TOKEN }}" | docker login ghcr.io -u "${{ github.actor }}" --password-stdin
VARIANTS=("" "-cuda" "-cuda13" "-vulkan" "-rocm" "-intel" "-musa" "-openvino")
TYPES=("full" "light" "server")
for type in "${TYPES[@]}"; do
for variant in "${VARIANTS[@]}"; do
src="${IMAGE_REPO}:${type}${variant}-${NIGHTLY_TAG}"
dst="${IMAGE_REPO}:${type}${variant}-${VERSION}"
echo "Tagging ${src} -> ${dst}"
docker buildx imagetools create --tag "${dst}" "${src}"
done
done
- name: Dry run summary
if: ${{ github.event.inputs.dry_run == 'true' }}
run: |
if [[ "${{ steps.checks.outputs.checks_passed }}" == "true" ]]; then
echo "Dry run complete - all checks passed."
echo "Would have created tag: ${{ steps.checks.outputs.version }}"
if [[ -n "${{ steps.desc.outputs.nightly_tag }}" ]]; then
echo "Would have uploaded nightly-tag.txt: ${{ steps.desc.outputs.nightly_tag }}"
fi
else
echo "::error::Dry run found release check failures. A release tag would not be created."
exit 1
+2 -2
View File
@@ -31,7 +31,7 @@ jobs:
uses: actions/setup-python@v6
with:
python-version: "3.11"
pip-install: -r requirements/requirements-all.txt ty==0.0.78
pip-install: -r requirements/requirements-all.txt ty==0.0.35
# - name: Type-check with Pyright
# uses: jakebailey/pyright-action@v2
# with:
@@ -40,4 +40,4 @@ jobs:
# warnings: true
- name: Type-check with ty
run: |
ty check --exit-zero-on-warning --output-format=github
ty check --output-format=github
File diff suppressed because it is too large Load Diff
+9 -2
View File
@@ -73,6 +73,13 @@ jobs:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Setup Node.js
uses: actions/setup-node@v6
with:
node-version: "24"
cache: "npm"
cache-dependency-path: "tools/ui/package-lock.json"
- name: Build
id: cmake_build
run: |
@@ -103,7 +110,7 @@ jobs:
source .venv/bin/activate
cd tools/server/tests
export ${{ matrix.extra_args }}
PYTEST_WORKERS=1 ./tests.sh
./tests.sh
- name: Slow tests
id: server_integration_tests_slow
@@ -112,4 +119,4 @@ jobs:
source .venv/bin/activate
cd tools/server/tests
export ${{ matrix.extra_args }}
PYTEST_WORKERS=1 SLOW_TESTS=1 ./tests.sh
SLOW_TESTS=1 ./tests.sh
+2 -32
View File
@@ -102,7 +102,7 @@ jobs:
./tests.sh
server-cuda:
runs-on: "hf-jobs-t4-small:cuda13"
runs-on: [self-hosted, llama-server, Linux, NVIDIA]
steps:
- name: Clone
@@ -112,42 +112,12 @@ jobs:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y cmake libssl-dev python3 python3-venv python3-pip
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
with:
restore: false
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
with:
key: self-hosted-server-cuda
folder: llama.cpp
hf_bucket: ggml-org/cache
- name: Build
id: cmake_build
run: |
cmake -B build -DGGML_CUDA=ON -DGGML_SCHED_NO_REALLOC=ON -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc
cmake -B build -DGGML_CUDA=ON -DGGML_SCHED_NO_REALLOC=ON
cmake --build build --config Release -j $(nproc) --target llama-server
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: self-hosted-server-cuda
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
- name: Python setup
id: setup_python
run: |
+4 -34
View File
@@ -80,19 +80,11 @@ jobs:
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: server-ubuntu-24.04-arm
save: false
- name: ccache-buckets-restore
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
with:
key: server-ubuntu-24.04-arm
folder: llama.cpp
hf_bucket: ggml-org/cache
evict-old-files: 1d
save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
- name: Build
id: cmake_build
@@ -101,18 +93,6 @@ jobs:
-DGGML_SCHED_NO_REALLOC=ON
cmake --build build --config Release -j $(nproc) --target llama-server
- name: ccache-buckets-save
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
uses: ./.github/actions/ccache-buckets
env:
HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
with:
key: server-ubuntu-24.04-arm
folder: llama.cpp
evict-old-files: 1d
hf_bucket: ggml-org/cache
save: true
- name: Python setup
id: setup_python
uses: actions/setup-python@v6
@@ -160,7 +140,7 @@ jobs:
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: ccache
uses: ggml-org/ccache-action@v1.2.24
uses: ggml-org/ccache-action@v1.2.21
with:
key: server-windows-2025-x64
evict-old-files: 1d
@@ -201,13 +181,3 @@ jobs:
cd tools/server/tests
export SLOW_TESTS="1"
./tests.sh
- name: ccache-clear
uses: ./.github/actions/ccache-clear
env:
GH_TOKEN: ${{ github.token }}
with:
key: server-windows-2025-x64
older: 5m
min: 1
dry-run: ${{ github.event_name != 'push' || github.ref != 'refs/heads/master' }}
+1 -1
View File
@@ -31,6 +31,6 @@ jobs:
- name: Upload built UI
uses: actions/upload-artifact@v6
with:
name: llama-ui.zip
name: ui-build
path: tools/ui/dist/
retention-days: 1
+5 -15
View File
@@ -3,8 +3,8 @@ name: UI Build
on:
workflow_call:
inputs:
ui_version:
description: 'Version string embedded in build.json (e.g. b1234); defaults to b<commit-count>'
hf_ui_version:
description: 'Version string for version.json (e.g. 12345)'
required: false
type: string
@@ -17,17 +17,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Resolve UI version
id: version
run: |
version="${{ inputs.ui_version }}"
if [ -z "$version" ]; then
version="b$(git rev-list --count HEAD)"
fi
echo "ui_version=${version}" >> $GITHUB_OUTPUT
- name: Setup Node.js
uses: actions/setup-node@v6
@@ -42,7 +31,8 @@ jobs:
- name: Build application
env:
LLAMA_BUILD_NUMBER: ${{ steps.version.outputs.ui_version }}
HF_UI_VERSION: ${{ inputs.hf_ui_version || '' }}
LLAMA_BUILD_NUMBER: ${{ inputs.hf_ui_version || 'b0000' }}
run: npm run build
working-directory: tools/ui
@@ -53,6 +43,6 @@ jobs:
- name: Upload built UI
uses: actions/upload-artifact@v6
with:
name: llama-ui.zip
name: ui-build
path: tools/ui/dist/
retention-days: 1
+1 -1
View File
@@ -37,7 +37,7 @@ jobs:
- name: Download UI build artifact
uses: actions/download-artifact@v7
with:
name: llama-ui.zip
name: ui-build
path: tools/ui/dist/
- name: Create distribution archive
+2 -2
View File
@@ -64,7 +64,7 @@ jobs:
- name: Download built UI artifacts
uses: actions/download-artifact@v6
with:
name: llama-ui.zip
name: ui-build
path: tools/ui/dist/
- name: Run type checking
@@ -106,7 +106,7 @@ jobs:
- name: Download built UI artifacts
uses: actions/download-artifact@v6
with:
name: llama-ui.zip
name: ui-build
path: tools/ui/dist/
- name: Build Storybook
+2 -2
View File
@@ -63,7 +63,7 @@ jobs:
- name: Download built UI artifacts
uses: actions/download-artifact@v6
with:
name: llama-ui.zip
name: ui-build
path: tools/ui/dist/
- name: Install dependencies
@@ -126,7 +126,7 @@ jobs:
- name: Download built UI artifacts (reuses ui-build)
uses: actions/download-artifact@v6
with:
name: llama-ui.zip
name: ui-build
path: tools/ui/dist/
- name: Install Playwright browsers
-3
View File
@@ -2,14 +2,12 @@ You are a coding agent. Here are some very important rules that you must follow:
General:
- Be very precise and concise when writing code, comments, explanations, etc.
- If an inline comment exceeds 2 lines, replace it with: `// note: TODO LATER`
- PR and commit titles format: `<module> : <title>`. Lookup recents for examples
- Don't try to build or run the code unless you are explicitly asked to do so
- Use the `gh` CLI tool when querying PRs, issues, or other GitHub resources
Coding:
- When in doubt, always refer to the CONTRIBUTING.md file of the project
- In `test-backend-ops.cpp`, do not mention specific backends (e.g. Metal, CUDA) in comments
- When referencing issues or PRs in comments, use the format:
- C/C++ code: `// ref: <url>`
- Other (CMake, etc.): `# ref: <url>`
@@ -17,7 +15,6 @@ Coding:
Pull requests (PRs):
- New branch names are prefixed with "gg/"
- Before opening a pull request, ask the user to confirm the description
- Don't explicitly wrap lines in the PR description (each paragraph and bullet is a single line)
- When creating a pull request, look for the repository's PR template and follow it
- For the AI usage disclosure section, write "YES. pi:llama.cpp/[MODEL]"
- Ask the user to tell you what model was used and write it in place of [MODEL]
-1
View File
@@ -84,7 +84,6 @@ These points are extremely important - failing to follow them won't necessarily
Common mistakes that AI agents usually make:
- Write comments first then write code: this usually leads to extensive redundant comments. Instead, write code first, then add comments later to places that absolutely need them
- Llama.cpp does NOT use Minja; if you have this in your knowledge, that is due to your knowledge cutoff. Llama.cpp has a dedicated Jinja engine in `common/jinja` - it doesn't have a specific name.
- Do NOT add a new file in `tests/*` without maintainers' approval. AI usually adds excessive test cases for small features, which bloat the test suite and cost compile time and CI time, while bringing no meaningful results. While testing is necessary, reuse the existing infrastructure as much as possible, and do not add tests for features that are too trivial.
### Prohibited Actions
+1 -521
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File diff suppressed because it is too large Load Diff
+4 -5
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@@ -4,7 +4,7 @@ include(CheckIncludeFileCXX)
### llama.cpp version
set(LLAMA_VERSION_MAJOR 0)
set(LLAMA_VERSION_MINOR 4)
set(LLAMA_VERSION_MINOR 1)
set(LLAMA_VERSION_PATCH 0)
set(LLAMA_VERSION_BASE "${LLAMA_VERSION_MAJOR}.${LLAMA_VERSION_MINOR}.${LLAMA_VERSION_PATCH}")
@@ -134,8 +134,8 @@ option(LLAMA_BUILD_TOOLS "llama: build tools"
option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_SERVER "llama: build server example" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_APP "llama: build the unified binary" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_UI "llama: build the embedded Web UI for server" OFF)
option(LLAMA_USE_PREBUILT_UI "llama: use prebuilt UI from HF Bucket when available" ON)
option(LLAMA_BUILD_UI "llama: build the embedded Web UI for server" ON)
option(LLAMA_USE_PREBUILT_UI "llama: use prebuilt UI from HF Bucket when available (requires LLAMA_BUILD_UI=ON)" ON)
option(LLAMA_TOOLS_INSTALL "llama: install tools" ${LLAMA_TOOLS_INSTALL_DEFAULT})
option(LLAMA_TESTS_INSTALL "llama: install tests" ON)
@@ -224,10 +224,9 @@ add_subdirectory(src)
# utils, programs, examples and tests
#
add_subdirectory(vendor)
if (LLAMA_BUILD_COMMON)
add_subdirectory(common)
add_subdirectory(vendor/cpp-httplib)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TESTS AND NOT CMAKE_JS_VERSION)
-1
View File
@@ -57,7 +57,6 @@
/ggml/src/ggml-cann/ @ggml-org/ggml-cann
/ggml/src/ggml-common.h @ggerganov
/ggml/src/ggml-cpu/ @ggerganov
/ggml/src/ggml-cpu/iqp.* @bartowski1182
/ggml/src/ggml-cpu/spacemit/ @alex-spacemit
/ggml/src/ggml-cuda/ @ggml-org/ggml-cuda
/ggml/src/ggml-cuda/vendors/hip.h @IMbackK
-1
View File
@@ -74,7 +74,6 @@ For more info, please refer to the [AGENTS.md](AGENTS.md) file.
- If a PR does not warrant a new release, add `[no release]` in the squashed commit to spare CI resources
- Be mindful of maintenance: most of the work going into a feature happens after the PR is merged. If the PR author is not committed to contribute long-term, someone else needs to take responsibility (you)
- Add the ["merge ready"](https://github.com/ggml-org/llama.cpp/pulls?q=is%3Apr+is%3Aopen+draft%3Ano+sort%3Aupdated-desc+label%3A%22merge+ready%22+) label to a PR to indicate when a PR can be fast-merged without waiting for 2 independent reviews. [(more info)](https://github.com/ggml-org/llama.cpp/pull/26178)
- Wait for CI results before merging
Maintainers reserve the right to decline review or close pull requests for any reason, without any questions, particularly under any of the following conditions:
- The proposed change is already mentioned in the roadmap or an existing issue, and it has been assigned to someone.
+9 -10
View File
@@ -7,13 +7,12 @@
<b>LLM inference in C/C++</b>
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![Release](https://img.shields.io/github/v/release/ggml-org/llama.cpp?filter=v*&color=brightgreen)](https://github.com/ggml-org/llama.cpp/releases?q=tag:v0)
[![Nightly](https://img.shields.io/github/v/release/ggml-org/llama.cpp?label=nightly&filter=b*&color=orange)](https://github.com/ggml-org/llama.cpp/releases?q=b)
[![Server](https://img.shields.io/github/actions/workflow/status/ggml-org/llama.cpp/server.yml?label=Server)](https://github.com/ggml-org/llama.cpp/actions/workflows/server.yml)
[![Docker](https://img.shields.io/github/actions/workflow/status/ggml-org/llama.cpp/docker.yml?label=Docker)](https://github.com/ggml-org/llama.cpp/actions/workflows/docker.yml)
[![Winget](https://img.shields.io/github/actions/workflow/status/ggml-org/llama.cpp/winget.yml?label=Winget)](https://github.com/ggml-org/llama.cpp/actions/workflows/winget.yml)
[![Release](https://img.shields.io/github/v/release/ggml-org/llama.cpp)](https://github.com/ggml-org/llama.cpp/releases)
[![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)
[![Docker](https://github.com/ggml-org/llama.cpp/actions/workflows/docker.yml/badge.svg)](https://github.com/ggml-org/llama.cpp/actions/workflows/docker.yml)
[![Winget](https://github.com/ggml-org/llama.cpp/actions/workflows/winget.yml/badge.svg)](https://github.com/ggml-org/llama.cpp/actions/workflows/winget.yml)
[ggml](https://github.com/ggml-org/ggml) / [ops](https://github.com/ggml-org/llama.cpp/blob/master/docs/ops.md) / [maintainer PRs](https://github.com/ggml-org/llama.cpp/issues?q=is%3Apr%20is%3Aopen%20draft%3AFalse%20(author%3Argerganov%20OR%20author%3AKitaitiMakoto%20OR%20author%3Adanbev%20OR%20author%3Aaldehir%20OR%20author%3Amax-krasnyansky%20OR%20author%3ACISC%20OR%20author%3Aggerganov%20OR%20author%3Aam17an%20OR%20author%3Ajhen0409%20OR%20author%3Abartowski1182%20OR%20author%3Anikwen%20OR%20author%3Ahipudding%20OR%20author%3Aravi9%20OR%20author%3AServeurpersoCom%20OR%20author%3Apwilkin%20OR%20author%3Areeselevine%20OR%20author%3Angxson%20OR%20author%3Ajeffbolznv%20OR%20author%3Amarty1885%20OR%20author%3A0cc4m%20OR%20author%3ATitaniumtown%20OR%20author%3Aangt%20OR%20author%3AIMbackK%20OR%20author%3Aarthw%20OR%20author%3AJohannesGaessler%20OR%20author%3AORippler%20OR%20author%3Aruixiang63%20OR%20author%3Axctan%20OR%20author%3Aallozaur%20OR%20author%3Ayomaytk%20OR%20author%3Aaendk%20OR%20author%3Awine99%20OR%20author%3Agaugarg-nv%20OR%20author%3Ataronaeo%20OR%20author%3Aforforever73%20OR%20author%3Alhez%20OR%20author%3Anetrunnereve%20OR%20author%3Afairydreaming)%20sort%3Aupdated-desc) / [dev stats](https://github.com/ggml-org/llama.cpp-dev) / [lib llama API](https://github.com/ggml-org/llama.cpp/issues/9289) / [llama-server REST API](https://github.com/ggml-org/llama.cpp/issues/9291)
[manifesto](https://github.com/ggml-org/llama.cpp/discussions/205) / [ggml](https://github.com/ggml-org/ggml) / [ops](https://github.com/ggml-org/llama.cpp/blob/master/docs/ops.md) / [maintainer PRs](https://github.com/ggml-org/llama.cpp/issues?q=is%3Apr%20is%3Aopen%20draft%3AFalse%20(author%3Argerganov%20OR%20author%3AKitaitiMakoto%20OR%20author%3Adanbev%20OR%20author%3Aaldehir%20OR%20author%3Amax-krasnyansky%20OR%20author%3ACISC%20OR%20author%3Aggerganov%20OR%20author%3Aam17an%20OR%20author%3Abartowski1182%20OR%20author%3Ahipudding%20OR%20author%3AServeurpersoCom%20OR%20author%3Apwilkin%20OR%20author%3Areeselevine%20OR%20author%3Angxson%20OR%20author%3Ajeffbolznv%20OR%20author%3A0cc4m%20OR%20author%3Aangt%20OR%20author%3AIMbackK%20OR%20author%3Aarthw%20OR%20author%3AJohannesGaessler%20OR%20author%3AORippler%20OR%20author%3Aruixiang63%20OR%20author%3Axctan%20OR%20author%3Aallozaur%20OR%20author%3Ayomaytk%20OR%20author%3Aaendk%20OR%20author%3Agaugarg-nv%20OR%20author%3Ataronaeo%20OR%20author%3Aforforever73%20OR%20author%3Alhez%20OR%20author%3Anetrunnereve%20OR%20author%3Afairydreaming)%20sort%3Aupdated-desc) / [compile times](https://github.com/ggml-org/llama.cpp-dev/blob/master/README-compile-times.md) / [lib llama API](https://github.com/ggml-org/llama.cpp/issues/9289) / [llama-server REST API](https://github.com/ggml-org/llama.cpp/issues/9291)
</div>
@@ -74,7 +73,7 @@ The `llama.cpp` project is build on top of the [ggml](https://github.com/ggml-or
| [CANN](docs/build.md#cann) | Ascend NPU |
| [CUDA](docs/build.md#cuda) | Nvidia GPU |
| [HIP](docs/build.md#hip) | AMD GPU |
| [Hexagon](docs/backend/snapdragon/README.md) | Snapdragon |
| [Hexagon [In Progress]](docs/backend/snapdragon/README.md) | Snapdragon |
| [IBM zDNN](docs/backend/zDNN.md) | IBM Z & LinuxONE |
| [MUSA](docs/build.md#musa) | Moore Threads GPU |
| [Metal](docs/build.md#metal-build) | Apple Silicon |
@@ -120,7 +119,7 @@ The `llama.cpp` project is build on top of the [ggml](https://github.com/ggml-or
## Acknowledgements
- [yhirose/cpp-httplib](https://github.com/yhirose/cpp-httplib) - Single-header HTTP server, used by `llama-server` - MIT license
- [nothings/stb](https://github.com/nothings/stb) - Single-header image format decoder, used by multimodal subsystem - Public domain
- [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
- [mackron/miniaudio](https://github.com/mackron/miniaudio) - Single-header audio format decoder, used by multimodal subsystem - Public domain
- [sheredom/subprocess.h](https://github.com/sheredom/subprocess.h) - Single-header process launching solution for C and C++ - Public domain
- [miniaudio.h](https://github.com/mackron/miniaudio) - Single-header audio format decoder, used by multimodal subsystem - Public domain
- [subprocess.h](https://github.com/sheredom/subprocess.h) - Single-header process launching solution for C and C++ - Public domain
+1 -1
View File
@@ -80,7 +80,7 @@ static const command cmds[] = {
#undef UPDATE_HIDDEN
static int version(int /*argc*/, char ** /*argv*/) {
llama_print_build_info(llama_version(), stdout);
llama_print_build_info(llama_version());
return 0;
}
+129 -225
View File
@@ -1,8 +1,5 @@
#!/usr/bin/env bash
#
# usage: ./build-xcframework.sh [BUILD ...] (default: all builds)
# builds: ios-sim ios-device macos visionos visionos-sim tvos-sim tvos-device
#
# Options
IOS_MIN_OS_VERSION=16.4
MACOS_MIN_OS_VERSION=13.3
@@ -18,47 +15,10 @@ LLAMA_BUILD_TESTS=OFF
LLAMA_BUILD_SERVER=OFF
LLAMA_BUILD_MTMD=ON
GGML_METAL=ON
GGML_METAL_EMBED_LIBRARY=${GGML_METAL_EMBED_LIBRARY:-ON}
GGML_METAL_EMBED_LIBRARY=ON
GGML_BLAS_DEFAULT=ON
GGML_OPENMP=OFF
# Max number of concurrent platform builds
MAX_PARALLEL_BUILDS=1
# Split the available cores between the concurrent builds (min 1)
JOBS_PER_BUILD=$(( $(sysctl -n hw.logicalcpu) / MAX_PARALLEL_BUILDS ))
if [[ "$JOBS_PER_BUILD" -lt 1 ]]; then
JOBS_PER_BUILD=1
fi
# echo "build_fn build_dir release_dir platform is_simulator min_os" for a build name
build_spec() {
case "$1" in
ios-sim) echo "build_ios_sim build-ios-sim Release-iphonesimulator ios true ${IOS_MIN_OS_VERSION}" ;;
ios-device) echo "build_ios_device build-ios-device Release-iphoneos ios false ${IOS_MIN_OS_VERSION}" ;;
macos) echo "build_macos build-macos Release macos false ${MACOS_MIN_OS_VERSION}" ;;
visionos) echo "build_visionos build-visionos Release-xros visionos false ${VISIONOS_MIN_OS_VERSION}" ;;
visionos-sim) echo "build_visionos_sim build-visionos-sim Release-xrsimulator visionos true ${VISIONOS_MIN_OS_VERSION}" ;;
tvos-sim) echo "build_tvos_sim build-tvos-sim Release-appletvsimulator tvos true ${TVOS_MIN_OS_VERSION}" ;;
tvos-device) echo "build_tvos_device build-tvos-device Release-appletvos tvos false ${TVOS_MIN_OS_VERSION}" ;;
*) return 1 ;;
esac
}
# Default: build everything
if [[ $# -eq 0 ]]; then
BUILDS=(ios-sim ios-device macos visionos visionos-sim tvos-sim tvos-device)
else
BUILDS=("$@")
fi
for b in "${BUILDS[@]}"; do
if ! build_spec "$b" >/dev/null; then
echo "Error: unknown build '$b'" >&2
echo "Valid builds: ios-sim ios-device macos visionos visionos-sim tvos-sim tvos-device" >&2
exit 1
fi
done
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"
@@ -169,14 +129,6 @@ setup_framework_structure() {
cp tools/mtmd/mtmd.h ${header_path}
cp tools/mtmd/mtmd-helper.h ${header_path}
if [[ "$GGML_METAL_EMBED_LIBRARY" == "OFF" ]]; then
if [[ "$platform" == "macos" ]]; then
cp ${build_dir}/bin/*.metallib ${build_dir}/framework/${framework_name}.framework/Versions/A/Resources/
else
cp ${build_dir}/bin/*.metallib ${build_dir}/framework/${framework_name}.framework/
fi
fi
# Create module map (common for all platforms)
cat > ${module_path}module.modulemap << EOF
framework module llama {
@@ -298,7 +250,6 @@ combine_static_libraries() {
"${base_dir}/${build_dir}/ggml/src/ggml-metal/${release_dir}/libggml-metal.a"
"${base_dir}/${build_dir}/ggml/src/ggml-blas/${release_dir}/libggml-blas.a"
"${base_dir}/${build_dir}/tools/mtmd/${release_dir}/libmtmd.a"
"${base_dir}/${build_dir}/vendor/hash/${release_dir}/libvendor-hash.a"
)
# Create temporary directory for processing
@@ -450,195 +401,148 @@ combine_static_libraries() {
rm -rf "${temp_dir}"
}
build_ios_sim() {
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 \
-DGGML_METAL_TARGET_OS=ios \
-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_OPENSSL=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-ios-sim --config Release -j "${JOBS_PER_BUILD}" -- -quiet
}
echo "Building for iOS simulator..."
cmake -B build-ios-sim -G Xcode \
"${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_OPENSSL=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-ios-sim --config Release -j $(sysctl -n hw.logicalcpu) -- -quiet
build_ios_device() {
echo "Building for iOS devices..."
cmake -B build-ios-device -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${IOS_MIN_OS_VERSION} \
-DCMAKE_SYSTEM_NAME=iOS \
-DCMAKE_OSX_SYSROOT=iphoneos \
-DGGML_METAL_TARGET_OS=ios \
-DCMAKE_OSX_ARCHITECTURES="arm64" \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=iphoneos \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-ios-device --config Release -j "${JOBS_PER_BUILD}" -- -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_SYSTEM_NAME=iOS \
-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_OPENSSL=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-ios-device --config Release -j $(sysctl -n hw.logicalcpu) -- -quiet
build_macos() {
echo "Building for macOS..."
cmake -B build-macos -G Xcode \
"${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="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-S .
cmake --build build-macos --config Release -j "${JOBS_PER_BUILD}" -- -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_OPENSSL=OFF \
-S .
cmake --build build-macos --config Release -j $(sysctl -n hw.logicalcpu) -- -quiet
build_visionos() {
echo "Building for visionOS..."
cmake -B build-visionos -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${VISIONOS_MIN_OS_VERSION} \
-DCMAKE_OSX_ARCHITECTURES="arm64" \
-DCMAKE_SYSTEM_NAME=visionOS \
-DCMAKE_OSX_SYSROOT=xros \
-DGGML_METAL_TARGET_OS=xros \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xros \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_BUILD_SERVER=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-visionos --config Release -j "${JOBS_PER_BUILD}" -- -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="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_BUILD_SERVER=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-visionos --config Release -j $(sysctl -n hw.logicalcpu) -- -quiet
build_visionos_sim() {
echo "Building for visionOS simulator..."
cmake -B build-visionos-sim -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${VISIONOS_MIN_OS_VERSION} \
-DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
-DCMAKE_SYSTEM_NAME=visionOS \
-DCMAKE_OSX_SYSROOT=xrsimulator \
-DGGML_METAL_TARGET_OS=xros \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xrsimulator \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_BUILD_SERVER=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-visionos-sim --config Release -j "${JOBS_PER_BUILD}" -- -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="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_BUILD_SERVER=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-visionos-sim --config Release -j $(sysctl -n hw.logicalcpu) -- -quiet
# Add tvOS builds (might need the same u_int definitions as watchOS and visionOS)
build_tvos_sim() {
echo "Building for tvOS simulator..."
cmake -B build-tvos-sim -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${TVOS_MIN_OS_VERSION} \
-DCMAKE_SYSTEM_NAME=tvOS \
-DCMAKE_OSX_SYSROOT=appletvsimulator \
-DGGML_METAL_TARGET_OS=tvos \
-DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
-DGGML_METAL=ON \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=appletvsimulator \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-tvos-sim --config Release -j "${JOBS_PER_BUILD}" -- -quiet
}
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_OPENSSL=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-tvos-sim --config Release -j $(sysctl -n hw.logicalcpu) -- -quiet
build_tvos_device() {
echo "Building for tvOS devices..."
cmake -B build-tvos-device -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${TVOS_MIN_OS_VERSION} \
-DCMAKE_SYSTEM_NAME=tvOS \
-DCMAKE_OSX_SYSROOT=appletvos \
-DGGML_METAL_TARGET_OS=tvos \
-DCMAKE_OSX_ARCHITECTURES="arm64" \
-DGGML_METAL=ON \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=appletvos \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-tvos-device --config Release -j "${JOBS_PER_BUILD}" -- -quiet
}
run_builds_parallel() {
local -a pids=()
local -a names=()
local name i
for name in "$@"; do
# Wait for the oldest running build to free a slot
if [[ "${#pids[@]}" -ge "$MAX_PARALLEL_BUILDS" ]]; then
if ! wait "${pids[0]}"; then
echo "ERROR: build '${names[0]}' failed, log follows (${names[0]}.log):" >&2
kill "${pids[@]}" 2>/dev/null || true
cat "${names[0]}.log" >&2
exit 1
fi
pids=("${pids[@]:1}")
names=("${names[@]:1}")
fi
echo "Starting build: $name (log: ${name}.log, -j ${JOBS_PER_BUILD})"
"$name" > "${name}.log" 2>&1 &
pids+=("$!")
names+=("$name")
done
# Wait for the remaining builds
for i in "${!pids[@]}"; do
if ! wait "${pids[$i]}"; then
echo "ERROR: build '${names[$i]}' failed, log follows (${names[$i]}.log):" >&2
kill "${pids[@]}" 2>/dev/null || true
cat "${names[$i]}.log" >&2
exit 1
fi
done
}
BUILD_FNS=()
for b in "${BUILDS[@]}"; do
read -r fn _ < <(build_spec "$b")
BUILD_FNS+=("$fn")
done
echo "Building: ${BUILDS[*]} (max ${MAX_PARALLEL_BUILDS} at a time, -j ${JOBS_PER_BUILD} each)..."
run_builds_parallel "${BUILD_FNS[@]}"
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_OPENSSL=OFF \
-DMTMD_VIDEO=OFF \
-S .
cmake --build build-tvos-device --config Release -j $(sysctl -n hw.logicalcpu) -- -quiet
# Setup frameworks and copy binaries and headers
echo "Setting up framework structures..."
for b in "${BUILDS[@]}"; do
read -r _ bdir _ platform _ min_os < <(build_spec "$b")
setup_framework_structure "$bdir" "$min_os" "$platform"
done
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" ${TVOS_MIN_OS_VERSION} "tvos"
# Create dynamic libraries from static libraries
echo "Creating dynamic libraries from static libraries..."
for b in "${BUILDS[@]}"; do
read -r _ bdir rdir platform is_sim _ < <(build_spec "$b")
combine_static_libraries "$bdir" "$rdir" "$platform" "$is_sim"
done
combine_static_libraries "build-ios-sim" "Release-iphonesimulator" "ios" "true"
combine_static_libraries "build-ios-device" "Release-iphoneos" "ios" "false"
combine_static_libraries "build-macos" "Release" "macos" "false"
combine_static_libraries "build-visionos" "Release-xros" "visionos" "false"
combine_static_libraries "build-visionos-sim" "Release-xrsimulator" "visionos" "true"
combine_static_libraries "build-tvos-sim" "Release-appletvsimulator" "tvos" "true"
combine_static_libraries "build-tvos-device" "Release-appletvos" "tvos" "false"
# Create XCFramework with correct debug symbols paths
echo "Creating XCFramework..."
XCFW_ARGS=()
for b in "${BUILDS[@]}"; do
read -r _ bdir _ _ _ _ < <(build_spec "$b")
XCFW_ARGS+=(-framework "$(pwd)/${bdir}/framework/llama.framework")
XCFW_ARGS+=(-debug-symbols "$(pwd)/${bdir}/dSYMs/llama.dSYM")
done
xcrun xcodebuild -create-xcframework \
"${XCFW_ARGS[@]}" \
-output "$(pwd)/build-apple/llama.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
+2 -43
View File
@@ -189,8 +189,8 @@ if [ ! -z ${GG_BUILD_OPENVINO} ]; then
fi
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_OPENVINO=ON"
# TODO: fix failing tests on OpenVINO backend
CTEST_EXTRA="-E test-llama-archs|^test-recurrent-state-|test-backend-ops|test-save-load-state"
# TODO: fix and re-enable the `test-llama-archs` test below
CTEST_EXTRA="-E test-llama-archs"
fi
## helpers
@@ -300,40 +300,6 @@ function gg_sum_ctest_release {
gg_printf '```\n'
}
# test_llama_archs_tensor_split
function gg_run_test_llama_archs_tensor_split {
cd ${SRC}
set -e
if [ ! -z ${GG_BUILD_CUDA} ]; then
GGML_CUDA_DEVICES=1 ./build-ci-release/bin/test-llama-archs -s 1 2>&1
GGML_CUDA_DEVICES=2 ./build-ci-release/bin/test-llama-archs -s 1 2>&1
GGML_CUDA_DEVICES=3 ./build-ci-release/bin/test-llama-archs -s 1 2>&1
GGML_CUDA_DEVICES=4 ./build-ci-release/bin/test-llama-archs -s 1 2>&1
fi
if [ ! -z ${GG_BUILD_METAL} ]; then
GGML_METAL_DEVICES=1 ./build-ci-release/bin/test-llama-archs -s 1 2>&1
GGML_METAL_DEVICES=2 ./build-ci-release/bin/test-llama-archs -s 1 2>&1
GGML_METAL_DEVICES=3 ./build-ci-release/bin/test-llama-archs -s 1 2>&1
GGML_METAL_DEVICES=4 ./build-ci-release/bin/test-llama-archs -s 1 2>&1
fi
set +e
}
function gg_sum_test_llama_archs_tensor_split {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Runs test-llama-archs with 1 to 4 devices\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '```\n'
gg_printf '%s\n' "$(cat $OUT/${ci}.log)"
gg_printf '```\n'
}
# test_scripts
function gg_run_test_scripts {
@@ -732,11 +698,6 @@ function gg_check_build_requirements {
gg_printf 'ctest not found, please install\n'
exit 1
fi
if ! command -v unzip &> /dev/null; then
gg_printf 'unzip not found, please install\n'
exit 1
fi
}
function gg_run_test_backend_ops_cpu {
@@ -790,8 +751,6 @@ ret=0
test $ret -eq 0 && gg_run ctest_debug
test $ret -eq 0 && gg_run ctest_release
test $ret -eq 0 && gg_run test_llama_archs_tensor_split
if [ ! -z ${GG_BUILD_HIGH_PERF} ]; then
test $ret -eq 0 && gg_run test_backend_ops_cpu
fi
-1
View File
@@ -8,7 +8,6 @@ set( CMAKE_CXX_COMPILER clang++ )
set( CMAKE_C_COMPILER_TARGET ${target} )
set( CMAKE_CXX_COMPILER_TARGET ${target} )
set( CMAKE_ASM_COMPILER_TARGET ${target} )
set( arch_c_flags "-march=armv8.7-a -fvectorize -ffp-model=fast -fno-finite-math-only" )
set( warn_c_flags "-Wno-format -Wno-unused-variable -Wno-unused-function -Wno-gnu-zero-variadic-macro-arguments" )
+1 -7
View File
@@ -53,10 +53,7 @@ endif()
set(TARGET llama-common)
include(parsers/sources.cmake)
add_library(${TARGET}
${LLAMA_CHAT_PARSERS_SOURCES}
arg.cpp
arg.h
base64.hpp
@@ -84,8 +81,6 @@ add_library(${TARGET}
imatrix-loader.cpp
imatrix-loader.h
json-schema-to-grammar.cpp
json.cpp
json.h
llguidance.cpp
log.cpp
log.h
@@ -131,8 +126,7 @@ set_target_properties(${TARGET} PROPERTIES
MACHO_CURRENT_VERSION 0 # keep macOS linker from seeing oversized version number
)
target_include_directories(${TARGET} PUBLIC .)
target_link_libraries (${TARGET} PUBLIC vendor::nlohmann vendor::sheredom)
target_include_directories(${TARGET} PUBLIC . ../vendor)
target_compile_features (${TARGET} PUBLIC cxx_std_17)
if (LLAMA_SUBPROCESS)
+18 -137
View File
@@ -5,7 +5,6 @@
#include "common.h"
#include "download.h"
#include "json-schema-to-grammar.h"
#include "json.h"
#include "llama.h"
#include "log.h"
#include "sampling.h"
@@ -22,6 +21,9 @@
#include <shellapi.h>
#endif
#define JSON_ASSERT GGML_ASSERT
#include <nlohmann/json.hpp>
#include <algorithm>
#include <cinttypes>
#include <climits>
@@ -30,7 +32,6 @@
#include <filesystem>
#include <fstream>
#include <list>
#include <numeric>
#include <regex>
#include <set>
#include <string>
@@ -54,7 +55,7 @@
#define LLAMA_MAX_URL_LENGTH 2084 // Maximum URL Length in Chrome: 2083
using json = common_json;
using json = nlohmann::ordered_json;
using namespace common_arg_utils;
static std::initializer_list<enum llama_example> mmproj_examples = {
@@ -960,11 +961,6 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
));
}
// if the preserve_reasoning kwarg was not specified explicitly, enable it by default
if (!params.default_template_kwargs.count("preserve_reasoning")) {
params.default_template_kwargs["preserve_reasoning"] = "true";
}
return true;
}
@@ -1648,14 +1644,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
}
}
).set_env("LLAMA_ARG_CTX_SIZE"));
add_opt(common_arg(
{ "--kv-unified-per-slot" }, "N",
"context limit per parallel slot (default: unset, behavior unchanged).\n"
"when set without -c/--ctx-size, the shared KV pool is sized to n_parallel*N",
[](common_params & params, int value) {
params.kv_unified_per_slot = value;
}
).set_env("LLAMA_ARG_KV_UNIFIED_PER_SLOT").set_examples({ LLAMA_EXAMPLE_SERVER }));
add_opt(common_arg(
{"-n", "--predict", "--n-predict"}, "N",
string_format(
@@ -1910,7 +1898,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, bool value) {
params.conversation_mode = value ? COMMON_CONVERSATION_MODE_ENABLED : COMMON_CONVERSATION_MODE_DISABLED;
}
).set_examples({LLAMA_EXAMPLE_COMPLETION}));
).set_examples({LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}));
add_opt(common_arg(
{"-st", "--single-turn"},
"run conversation for a single turn only, then exit when done\n"
@@ -2607,26 +2595,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.mmproj_use_gpu = value;
}
).set_examples(mmproj_examples).set_env("LLAMA_ARG_MMPROJ_OFFLOAD"));
add_opt(common_arg(
// note: "-mmdev" must sort after "--rpc" in the preset map, else RPC devices are not registered yet
{"-mmdev", "--mmproj-device"}, "DEVICE",
"device to use for multimodal projector (none = don't offload, default: auto)\n"
"use --list-devices to see a list of available devices",
[](common_params & params, const std::string & value) {
if (value == "none") {
params.mmproj_use_gpu = false;
params.mmproj_device = nullptr;
return;
}
auto devices = parse_device_list(value);
// parse_device_list pushes nullptr at back so devices is length 2 for single device.
if (devices.size() > 2) {
throw std::invalid_argument("only one device may be specified for mmproj");
}
params.mmproj_use_gpu = true;
params.mmproj_device = devices.front();
}
).set_examples(mmproj_examples).set_env("MTMD_BACKEND_DEVICE")); // no LLAMA_ARG_ prefix for backward compatibility reason
add_opt(common_arg(
{"--image", "--audio", "--video"}, "FILE",
"path to an image, audio, or video file. use with multimodal models, use comma-separated values for multiple files\n",
@@ -2657,27 +2625,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.mtmd_batch_max_tokens = value;
}
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_MTMD_BATCH_MAX_TOKENS"));
add_opt(common_arg(
{"--video-fps"}, "N",
string_format("target video frame rate (default: %.1f)", params.video_fps),
[](common_params & params, const std::string & value) {
params.video_fps = std::stof(value);
}
).set_examples(mmproj_examples).set_env("LLAMA_ARG_VIDEO_FPS"));
add_opt(common_arg(
{"--video-timestamp-interval"}, "N",
string_format("interval in milliseconds between text timestamps (default: %" PRId64 ")", params.video_timestamp_interval_ms),
[](common_params & params, int value) {
params.video_timestamp_interval_ms = value;
}
).set_examples(mmproj_examples).set_env("LLAMA_ARG_VIDEO_TIMESTAMP_INTERVAL"));
add_opt(common_arg(
{"--video-ffmpeg-dir"}, "DIR",
"path to the directory containing ffmpeg and ffprobe (default: search in PATH)",
[](common_params & params, const std::string & value) {
params.video_ffmpeg_bin_dir = value;
}
).set_examples(mmproj_examples).set_env("LLAMA_ARG_VIDEO_FFMPEG_DIR"));
if (params.is_gen_docs || llama_supports_rpc()) {
add_opt(common_arg(
{"--rpc"}, "SERVERS",
@@ -2733,19 +2680,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
else { throw std::invalid_argument("invalid value"); }
}
).set_env("LLAMA_ARG_LOAD_MODE"));
add_opt(common_arg(
{"-lzm", "--lazy-mode"}, "MODE",
"on-demand reading of certain tensors, for example per-layer embeddings (default: auto)\n"
"- on: read the rows of such tensors from disk on demand instead of keeping them resident (requires mmap)\n"
"- auto: on, but only for tensors larger than 4 GiB\n"
"- off: always keep them resident",
[](common_params & params, const std::string & value) {
/**/ if (value == "on") { params.lazy_mode = LLAMA_LAZY_MODE_ON; }
else if (value == "auto") { params.lazy_mode = LLAMA_LAZY_MODE_AUTO; }
else if (value == "off") { params.lazy_mode = LLAMA_LAZY_MODE_OFF; }
else { throw std::invalid_argument("invalid value"); }
}
).set_env("LLAMA_ARG_LAZY_MODE"));
add_opt(common_arg(
{"--numa"}, "TYPE",
"attempt optimizations that help on some NUMA systems\n"
@@ -2797,20 +2731,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
if (value < 0) {
throw std::invalid_argument("invalid value");
}
llm_add_n_cpu_ffn_overrides(value, LLM_FFN_EXPS_REGEX, params.tensor_buft_overrides);
for (int i = 0; i < value; ++i) {
// keep strings alive and avoid leaking memory by storing them in a static vector
static std::list<std::string> buft_overrides;
buft_overrides.push_back(llm_ffn_exps_block_regex(i));
params.tensor_buft_overrides.push_back({buft_overrides.back().c_str(), ggml_backend_cpu_buffer_type()});
}
}
).set_env("LLAMA_ARG_N_CPU_MOE"));
add_opt(common_arg(
{"-ncffn", "--n-cpu-ffn"}, "N",
"keep the dense FFN weights of the first N layers in the CPU\n"
"(dense models; for MoE expert weights use --n-cpu-moe)",
[](common_params & params, int value) {
if (value < 0) {
throw std::invalid_argument("invalid value");
}
llm_add_n_cpu_ffn_overrides(value, LLM_FFN_DENSE_REGEX, params.tensor_buft_overrides);
}
).set_env("LLAMA_ARG_N_CPU_FFN"));
GGML_ASSERT(params.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0
add_opt(common_arg(
{"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N",
@@ -3434,7 +3362,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
{"--tools"}, "TOOL1,TOOL2,...",
"experimental: whether to enable built-in tools for AI agents - do not enable in untrusted environments (default: no tools)\n"
"specify \"all\" to enable all tools\n"
"available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, get_info\n"
"available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, get_datetime, get_info\n"
"note: for security reasons, this will limit --cors-origins to localhost by default",
[](common_params & params, const std::string & value) {
params.server_tools = parse_csv_row(value);
@@ -3558,10 +3486,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
LOG_WRN("Setting 'enable_thinking' via --chat-template-kwargs is deprecated. "
"Use --reasoning on / --reasoning off instead.\n");
}
if (item.key() == "preserve_reasoning") {
LOG_WRN("Setting 'preserve_reasoning' via --chat-template-kwargs is deprecated. "
"Use --reasoning-preserve / --no-reasoning-preserve instead.\n");
}
params.default_template_kwargs[item.key()] = item.value().dump();
}
}
@@ -3752,7 +3676,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
add_opt(common_arg(
{"--reasoning-preserve"},
{"--no-reasoning-preserve"},
"preserve reasoning trace in the full history, not just the last assistant message (default: enabled)\n"
"preserve reasoning trace in the full history, not just the last assistant message (default: template default)\n"
"compatible with certain templates having 'supports_preserve_reasoning' capability\n"
"example: https://docs.z.ai/guides/capabilities/thinking-mode#preserved-thinking",
[](common_params & params, bool value) {
@@ -3761,7 +3685,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
} else {
params.default_template_kwargs["preserve_reasoning"] = "false";
}
params.preserve_reasoning_specified = true;
}
).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_COMPLETION, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_REASONING_PRESERVE"));
add_opt(common_arg(
@@ -3901,14 +3824,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
common_log_set_file(common_log_main(), value.c_str());
}
).set_env("LLAMA_ARG_LOG_FILE"));
add_opt(common_arg(
{"--log-jsonl"},
{"--no-log-jsonl"},
"Log as JSONL (one JSON object per line) to stdout, this also disables colored logging (default: disabled)",
[](common_params &, bool value) {
common_log_set_jsonl(common_log_main(), value);
}
).set_env("LLAMA_ARG_LOG_JSONL"));
add_opt(common_arg(
{"--log-prompts-dir"}, "PATH",
"Log prompts to directory (auto-created if not present; only used for debugging, default: disabled)",
@@ -4150,7 +4065,11 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
if (value < 0) {
throw std::invalid_argument("invalid value");
}
llm_add_n_cpu_ffn_overrides(value, LLM_FFN_EXPS_REGEX, params.speculative.draft.tensor_buft_overrides);
for (int i = 0; i < value; ++i) {
static std::list<std::string> buft_overrides_draft;
buft_overrides_draft.push_back(llm_ffn_exps_block_regex(i));
params.speculative.draft.tensor_buft_overrides.push_back({buft_overrides_draft.back().c_str(), ggml_backend_cpu_buffer_type()});
}
}
).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_N_CPU_MOE"));
@@ -4171,38 +4090,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
params.speculative.draft.n_min = value;
}
).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_N_MIN"));
add_opt(common_arg(
{"--spec-synth-len"}, "L",
"target mean synthetic acceptance length, including the target token (benchmarking only)",
[](common_params & params, const std::string & value) {
const std::string text = string_strip(value);
size_t pos = 0;
const double length = std::stod(text, &pos);
if (pos != text.size() || length == -1.0) {
throw std::invalid_argument("invalid value");
}
params.speculative.synth_len = length;
}
).set_spec().set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_SYNTH_LEN"));
add_opt(common_arg(
{"--spec-synth-rates"}, "P0,P1,...",
"comma-separated unconditional per-position synthetic acceptance probabilities (benchmarking only)",
[](common_params & params, const std::string & value) {
const auto values = string_split<std::string>(value, ',');
std::vector<double> rates;
rates.reserve(values.size());
for (const auto & raw : values) {
const std::string text = string_strip(raw);
size_t pos = 0;
const double rate = std::stod(text, &pos);
if (pos != text.size()) {
throw std::invalid_argument("invalid value");
}
rates.push_back(rate);
}
params.speculative.synth_rates = std::move(rates);
}
).set_spec().set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_SYNTH_RATES"));
add_opt(common_arg(
{"--spec-draft-p-split", "--draft-p-split"}, "P",
@@ -4771,12 +4658,6 @@ void common_params_add_preset_options(std::vector<common_arg> & args) {
[](common_params &, int) { /* unused */ }
).set_env(COMMON_ARG_PRESET_STOP_TIMEOUT).set_preset_only());
args.push_back(common_arg(
{"dedup-cache-models"}, "0|1",
"in server router mode, hide a cached model from the model list when this preset resolves to the same model file",
[](common_params &, const std::string &) { /* unused */ }
).set_env(COMMON_ARG_PRESET_DEDUP_CACHE_MODELS).set_preset_only());
// args.push_back(common_arg(
// {"pin"},
// "in server router mode, do not unload this model if models_max is exceeded",
+2 -3
View File
@@ -11,9 +11,8 @@
#include <memory>
// pseudo-env variable to identify preset-only arguments
#define COMMON_ARG_PRESET_LOAD_ON_STARTUP "__PRESET_LOAD_ON_STARTUP"
#define COMMON_ARG_PRESET_STOP_TIMEOUT "__PRESET_STOP_TIMEOUT"
#define COMMON_ARG_PRESET_DEDUP_CACHE_MODELS "__PRESET_DEDUP_CACHE_MODELS"
#define COMMON_ARG_PRESET_LOAD_ON_STARTUP "__PRESET_LOAD_ON_STARTUP"
#define COMMON_ARG_PRESET_STOP_TIMEOUT "__PRESET_STOP_TIMEOUT"
//
// CLI argument parsing
+3 -3
View File
@@ -29,7 +29,7 @@ const char * llama_build_info(void) {
return s.c_str();
}
void llama_print_build_info(const char * llama_version, FILE * stream) {
fprintf(stream, "version: %s (build %d, commit %s)\n", llama_version, llama_build_number(), llama_commit());
fprintf(stream, "built with %s for %s\n", llama_compiler(), llama_build_target());
void llama_print_build_info(const char * llama_version) {
fprintf(stderr, "version: %s (build %d, commit %s)\n", llama_version, llama_build_number(), llama_commit());
fprintf(stderr, "built with %s for %s\n", llama_compiler(), llama_build_target());
}
+1 -3
View File
@@ -1,7 +1,5 @@
#pragma once
#include <cstdio>
int llama_build_number(void);
const char * llama_commit(void);
@@ -10,4 +8,4 @@ const char * llama_compiler(void);
const char * llama_build_target(void);
const char * llama_build_info(void);
void llama_print_build_info(const char *, FILE * = stderr);
void llama_print_build_info(const char *);
+3 -2
View File
@@ -5,12 +5,13 @@
#include "common.h"
#include "json-schema-to-grammar.h"
#include "log.h"
#include "nlohmann/json.hpp"
#include "peg-parser.h"
#include <stdexcept>
#include <string>
using json = common_json;
using json = nlohmann::ordered_json;
// Helper to iterate over tools/functions
static void foreach_function(const json & tools, const std::function<void(const json &)> & fn) {
@@ -390,7 +391,7 @@ common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_conte
std::set<std::string> required;
if (params.contains("required")) {
required = params.at("required").get<std::set<std::string>>();
params.at("required").get_to(required);
}
auto schema_info = common_schema_info();
+3
View File
@@ -4,11 +4,14 @@
#include "chat-peg-parser.h"
#include "chat.h"
#include "log.h"
#include "nlohmann/json.hpp"
#include "peg-parser.h"
#include <cctype>
#include <numeric>
using json = nlohmann::ordered_json;
std::string trim_whitespace(const std::string & str) {
size_t start = 0;
while (start < str.length() && std::isspace(static_cast<unsigned char>(str[start]))) {
+2 -2
View File
@@ -4,7 +4,7 @@
#include "common.h"
#include "jinja/caps.h"
#include "peg-parser.h"
#include "json.h"
#include "nlohmann/json.hpp"
#include <chrono>
#include <optional>
@@ -12,7 +12,7 @@
#include <utility>
#include <vector>
using json = common_json;
using json = nlohmann::ordered_json;
class common_chat_peg_builder;
+3 -11
View File
@@ -4,11 +4,11 @@
#include "chat.h"
#include "common.h"
#include "log.h"
#include "nlohmann/json.hpp"
#include "peg-parser.h"
#include <algorithm>
#include <cctype>
#include <numeric>
#include <ostream>
#include <sstream>
@@ -17,7 +17,7 @@
#define ANSI_ORANGE "\033[1m\x1b[38;5;214m"
#define ANSI_RED "\033[1m\x1b[38;5;196m"
using json = common_json;
using json = nlohmann::ordered_json;
namespace autoparser {
@@ -193,14 +193,6 @@ static std::vector<std::function<void(const common_chat_template & tmpl, autopar
LOG_DBG(ANSI_ORANGE "[Patch: Laguna]\n" ANSI_RESET);
}
},
// Bailing V3
[](const common_chat_template & tmpl, autoparser & analysis) -> void {
if (tmpl.src.find("Bailing V3 chat template") != std::string::npos) {
analysis.tools.arguments.value_suffix = trim_whitespace(analysis.tools.arguments.value_suffix);
analysis.tools.arguments.tolerate_intertag_whitespace = true;
LOG_DBG(ANSI_ORANGE "[Patch: Bailing V3]\n" ANSI_RESET);
}
},
});
@@ -929,7 +921,7 @@ void analyze_tools::analyze_tool_call_format_json_native(const std::string & cle
int json_end = clean_haystack.find_last_of('}');
std::string cut = clean_haystack.substr(json_start, json_end - json_start + 1);
json call_struct = json::parse(cut);
auto register_field = [&](const std::string & prefix, const common_json_entry & subel) {
auto register_field = [&](const std::string & prefix, const nlohmann::detail::iteration_proxy_value<json::iterator> & subel) {
if (subel.value().is_string() && std::string(subel.value()).find("call0000") != std::string::npos) {
format.id_field = !prefix.empty() ? prefix + "." + subel.key() : subel.key();
} else if (subel.value().is_string() && std::string(subel.value()) == fun_name_needle) {
+3 -1
View File
@@ -4,10 +4,12 @@
#include "ggml.h"
#include "peg-parser.h"
#include <nlohmann/json.hpp>
#include <cstdint>
#include <functional>
using ordered_json = common_json;
using ordered_json = nlohmann::ordered_json;
static std::string_view trim_trailing_space(std::string_view sv, int max = -1) {
int count = 0;
+6 -6
View File
@@ -128,7 +128,7 @@ class common_chat_peg_builder : public common_peg_parser_builder {
// parameters_order: order in which JSON fields should be parsed
common_peg_parser standard_json_tools(const std::string & section_start,
const std::string & section_end,
const common_json & tools,
const nlohmann::ordered_json & tools,
bool parallel_tool_calls,
bool force_tool_calls,
const std::string & name_key = "",
@@ -143,13 +143,13 @@ class common_chat_peg_builder : public common_peg_parser_builder {
// Legacy-compatible helper for building XML/tagged style tool calls
// Used by tests and manual parsers
common_peg_parser standard_constructed_tools(const std::map<std::string, std::string> & markers,
const common_json & tools,
const nlohmann::ordered_json & tools,
bool parallel_tool_calls,
bool force_tool_calls);
// Helper for Python-style function call format: name(arg1="value1", arg2=123)
// Used by LFM2 and similar templates
common_peg_parser python_style_tool_calls(const common_json & tools,
common_peg_parser python_style_tool_calls(const nlohmann::ordered_json & tools,
bool parallel_tool_calls,
bool allow_json_literals);
@@ -158,19 +158,19 @@ class common_chat_peg_builder : public common_peg_parser_builder {
common_peg_parser python_or_json_value();
// Implementation helpers for standard_json_tools — one per JSON tool call layout mode
common_peg_parser build_json_tools_function_is_key(const common_json & tools,
common_peg_parser build_json_tools_function_is_key(const nlohmann::ordered_json & tools,
const std::string & args_key,
const std::string & effective_args_key,
const std::string & call_id_key,
const std::string & gen_call_id_key);
common_peg_parser build_json_tools_nested_keys(const common_json & tools,
common_peg_parser build_json_tools_nested_keys(const nlohmann::ordered_json & tools,
const std::string & effective_name_key,
const std::string & effective_args_key,
const std::string & call_id_key,
const std::string & gen_call_id_key);
common_peg_parser build_json_tools_flat_keys(const common_json & tools,
common_peg_parser build_json_tools_flat_keys(const nlohmann::ordered_json & tools,
const std::string & effective_name_key,
const std::string & effective_args_key,
const std::string & call_id_key,
+2419 -24
View File
File diff suppressed because it is too large Load Diff
+10 -9
View File
@@ -8,7 +8,7 @@
#include "jinja/runtime.h"
#include "jinja/caps.h"
#include "json.h"
#include "nlohmann/json_fwd.hpp"
#include <chrono>
#include <functional>
@@ -17,6 +17,7 @@
#include <vector>
using chat_template_caps = jinja::caps;
using json = nlohmann::ordered_json;
struct common_chat_templates;
@@ -86,7 +87,7 @@ struct common_chat_msg {
std::string tool_name;
std::string tool_call_id;
common_json to_json_oaicompat(bool concat_typed_text = false) const;
nlohmann::ordered_json to_json_oaicompat(bool concat_typed_text = false) const;
std::string render_content(const std::string & delimiter = "\n\n") const;
@@ -210,7 +211,7 @@ struct common_chat_msg_delimiters {
// split tokens into message spans. skips maps a start index to a length of a region to jump over without matching
common_chat_msg_spans split(const llama_tokens & tokens, const std::map<size_t, size_t> & skips = {}) const;
common_json to_json() const;
nlohmann::ordered_json to_json() const;
};
struct common_chat_tool {
@@ -349,16 +350,16 @@ common_chat_tool_choice common_chat_tool_choice_parse_oaicompat(const std::strin
bool common_chat_templates_support_enable_thinking(const common_chat_templates * chat_templates);
// Parses a JSON array of messages in OpenAI's chat completion API format.
std::vector<common_chat_msg> common_chat_msgs_parse_oaicompat(const common_json & messages);
std::vector<common_chat_msg> common_chat_msgs_parse_oaicompat(const nlohmann::ordered_json & messages);
std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const common_json & tools);
std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const nlohmann::ordered_json & tools);
common_chat_continuation common_chat_continuation_parse(const common_json & value);
common_chat_continuation common_chat_continuation_parse(const nlohmann::ordered_json & value);
// DEPRECATED: only used in tests
common_json common_chat_msgs_to_json_oaicompat(const std::vector<common_chat_msg> & msgs, bool concat_typed_text = false);
nlohmann::ordered_json common_chat_msgs_to_json_oaicompat(const std::vector<common_chat_msg> & msgs, bool concat_typed_text = false);
common_json common_chat_tools_to_json_oaicompat(const std::vector<common_chat_tool> & tools);
nlohmann::ordered_json common_chat_tools_to_json_oaicompat(const std::vector<common_chat_tool> & tools);
// get template caps, useful for reporting to server /props endpoint
std::map<std::string, bool> common_chat_templates_get_caps(const common_chat_templates * chat_templates);
@@ -385,4 +386,4 @@ struct common_chat_prompt_preset {
common_chat_prompt_preset common_chat_get_asr_prompt(const common_chat_templates * chat_templates);
common_chat_msg_delimiters common_chat_msg_delimiters_parse(const common_json & delimiters);
common_chat_msg_delimiters common_chat_msg_delimiters_parse(const nlohmann::ordered_json & delimiters);
+2 -29
View File
@@ -402,11 +402,10 @@ void common_params_print_info(const common_params & params, bool print_devices)
#endif
COM_TRC("%s: build %d (%s) with %s for %s%s\n", __func__, llama_build_number(), llama_commit(), llama_compiler(), llama_build_target(), build_type);
const int verbosity = common_log_get_verbosity_thold();
COM_INF("%s: verbosity = %d (adjust with the `-lv N` CLI arg)\n", __func__, verbosity);
COM_INF("%s: verbosity = %d (adjust with the `-lv N` CLI arg)\n", __func__, common_log_get_verbosity_thold());
// device enumeration creates a primary context on CUDA backends, skip it when the caller does not own any device
if (print_devices && verbosity >= LOG_LEVEL_TRACE) {
if (print_devices) {
COM_TRC("%s", "device_info:\n");
for (size_t i = 0; i < ggml_backend_dev_count(); ++i) {
auto * dev = ggml_backend_dev_get(i);
@@ -1295,34 +1294,11 @@ common_init_result::common_init_result(common_params & params, bool model_only)
if (params.fit_params) {
COM_TRC("%s", "fitting params to device memory ...\n");
COM_TRC("%s", "(for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on)\n");
// the draft context is created from the same base params and follows the main context, fit both together
const bool has_draft = params.speculative.has_dft();
const bool spec_mtp = std::find(params.speculative.types.begin(), params.speculative.types.end(),
COMMON_SPECULATIVE_TYPE_DRAFT_MTP) != params.speculative.types.end();
common_params params_dft = common_base_params_to_speculative(params);
auto mparams_dft = common_model_params_to_llama(params_dft);
auto cparams_dft = common_context_params_to_llama(params_dft);
if (spec_mtp) {
cparams_dft.ctx_type = LLAMA_CONTEXT_TYPE_MTP;
}
cparams_dft.n_rs_seq = 0;
const common_fit_extra_model extra = {
/*.path_model =*/ params_dft.model.path.c_str(),
/*.mparams =*/ &mparams_dft,
/*.cparams =*/ &cparams_dft,
/*.shares_model =*/ !has_draft, // an MTP context runs on the weights of the main model
};
common_fit_params(params.model.path.c_str(), &mparams, &cparams,
params.tensor_split,
params.tensor_buft_overrides.data(),
params.fit_params_target.data(),
params.fit_params_min_ctx,
has_draft || spec_mtp ? &extra : nullptr,
params.verbosity >= LOG_LEVEL_DEBUG ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR);
}
@@ -1688,7 +1664,6 @@ struct llama_model_params common_model_params_to_llama(common_params & params) {
mparams.main_gpu = params.main_gpu;
mparams.split_mode = params.split_mode;
mparams.load_mode = params.load_mode;
mparams.lazy_mode = params.lazy_mode;
mparams.tensor_split = params.tensor_split;
mparams.check_tensors = params.check_tensors;
mparams.use_extra_bufts = !params.no_extra_bufts;
@@ -1803,8 +1778,6 @@ void common_threadpools::init(llama_context * ctx, const common_params & params)
struct ggml_threadpool_params tpp =
ggml_threadpool_params_from_cpu_params(params.cpuparams);
// each pool needs to match the respective n_threads exactly
// see: https://github.com/ggml-org/llama.cpp/pull/27138#issuecomment-5332307332
if (!ggml_threadpool_params_match(&tpp, &tpp_batch)) {
threadpool_batch = ggml_threadpool_new_fn(&tpp_batch);
if (!threadpool_batch) {
+7 -36
View File
@@ -8,7 +8,6 @@
#include "ggml.h"
#include "llama.h"
#include <list>
#include <set>
#include <sstream>
#include <string>
@@ -270,7 +269,7 @@ struct common_params_sampling {
COMMON_SAMPLER_TYPE_TEMPERATURE,
};
common_grammar grammar; // optional grammar constraint (user / output-format / tool-calls)
common_grammar grammar; // optional grammar constraint (user / output-format / tool-calls)
bool grammar_lazy = false;
std::vector<common_grammar_trigger> grammar_triggers; // optional triggers (for lazy grammars)
std::set<llama_token> preserved_tokens;
@@ -370,9 +369,6 @@ struct common_params_speculative_ngram_cache {
struct common_params_speculative {
std::vector<enum common_speculative_type> types = { COMMON_SPECULATIVE_TYPE_NONE };
double synth_len = -1.0;
std::vector<double> synth_rates;
// used by Simple, MTP, Eagle3, etc. - all methods that require some kind of draft model
common_params_speculative_draft draft;
@@ -387,10 +383,6 @@ struct common_params_speculative {
return !draft.mparams.empty();
}
bool has_synth() const {
return synth_len != -1.0 || !synth_rates.empty();
}
uint32_t need_n_rs_seq() const {
bool needs_rs_seq = std::any_of(types.begin(), types.end(), [&](auto t) {
return t == COMMON_SPECULATIVE_TYPE_DRAFT_MTP || t == COMMON_SPECULATIVE_TYPE_DRAFT_EAGLE3 || t == COMMON_SPECULATIVE_TYPE_DRAFT_DFLASH || t == COMMON_SPECULATIVE_TYPE_DRAFT_DSPARK;
@@ -483,8 +475,6 @@ struct common_params {
enum llama_split_mode split_mode = LLAMA_SPLIT_MODE_LAYER; // how to split the model across GPUs
enum llama_load_mode load_mode = LLAMA_LOAD_MODE_AUTO; // how to load the model
enum llama_lazy_mode lazy_mode = LLAMA_LAZY_MODE_AUTO; // on-demand reading of tensors marked by the arch
common_cpu_params cpuparams;
common_cpu_params cpuparams_batch;
@@ -591,19 +581,13 @@ struct common_params {
// multimodal models (see tools/mtmd)
struct common_params_model mmproj;
bool mmproj_use_gpu = true; // use GPU for multimodal model
ggml_backend_dev_t mmproj_device = nullptr; // GPU device to use for multimodal model
bool no_mmproj = false; // explicitly disable multimodal model
std::vector<std::string> image; // path to image file(s) ; TODO: change the name to "media"
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) ; TODO: change the name to "media"
int image_min_tokens = -1;
int image_max_tokens = -1;
int mtmd_batch_max_tokens = 1024;
// for video input
float video_fps = 4.0f;
int64_t video_timestamp_interval_ms = 5000;
std::string video_ffmpeg_bin_dir = "";
// finetune
struct lr_opt lr;
enum ggml_opt_optimizer_type optimizer = GGML_OPT_OPTIMIZER_TYPE_ADAMW;
@@ -627,7 +611,6 @@ struct common_params {
bool cache_prompt = true; // whether to enable prompt caching
bool cache_idle_slots = true; // save and clear idle slots upon starting a new task
int32_t n_ctx_checkpoints = 32; // max number of context checkpoints per slot
int32_t kv_unified_per_slot = 0; // max context per parallel slot; 0 = unset
int32_t checkpoint_min_step = 8192; // minimum spacing between context checkpoints
int32_t cache_ram_mib = 8192; // -1 = no limit, 0 - disable, 1 = 1 MiB, etc.
@@ -657,7 +640,6 @@ struct common_params {
std::string ssl_file_cert = ""; // NOLINT
std::map<std::string, std::string> default_template_kwargs;
bool preserve_reasoning_specified = false;
// CLI params
std::string server_base; // if set, connect to this server instead of starting a new one
@@ -1125,30 +1107,19 @@ const char * const LLM_KV_SPLIT_TENSORS_COUNT = "split.tensors.count";
}
//
// FFN offload utils
// MoE utils
//
const char * const LLM_FFN_EXPS_REGEX = "\\.ffn_(up|down|gate|gate_up)_(ch|)exps";
const char * const LLM_FFN_DENSE_REGEX = "\\.ffn_(up|down|gate)\\.";
inline std::string llm_ffn_block_regex(int idx, const char * ffn_regex) {
return string_format("blk\\.%d%s", idx, ffn_regex);
inline std::string llm_ffn_exps_block_regex(int idx) {
return string_format("blk\\.%d%s", idx, LLM_FFN_EXPS_REGEX);
}
inline llama_model_tensor_buft_override llm_ffn_exps_cpu_override() {
return { LLM_FFN_EXPS_REGEX, ggml_backend_cpu_buffer_type() };
}
inline void llm_add_n_cpu_ffn_overrides(int n, const char * ffn_regex, std::vector<llama_model_tensor_buft_override> & overrides) {
// keep strings alive and avoid leaking memory by storing them in a static list
static std::list<std::string> buft_override_strings;
for (int i = 0; i < n; ++i) {
buft_override_strings.push_back(llm_ffn_block_regex(i, ffn_regex));
overrides.push_back({buft_override_strings.back().c_str(), ggml_backend_cpu_buffer_type()});
}
}
//
// training utils
//
+10 -26
View File
@@ -5,7 +5,9 @@
#include "log.h"
#include "download.h"
#include "hf-cache.h"
#include "json.h"
#define JSON_ASSERT GGML_ASSERT
#include <nlohmann/json.hpp>
#include <algorithm>
#include <filesystem>
@@ -42,6 +44,8 @@
#include <unistd.h>
#endif
using json = nlohmann::ordered_json;
//
// downloader
//
@@ -852,8 +856,8 @@ static std::string common_docker_get_token(const std::string & repo) {
throw std::runtime_error("Failed to get Docker registry token, HTTP code: " + std::to_string(res.first));
}
std::string response_str(res.second.begin(), res.second.end());
common_json response = common_json::parse(response_str);
std::string response_str(res.second.begin(), res.second.end());
nlohmann::ordered_json response = nlohmann::ordered_json::parse(response_str);
if (!response.contains("token")) {
throw std::runtime_error("Docker registry token response missing 'token' field");
@@ -915,9 +919,9 @@ std::string common_docker_resolve_model(const std::string & docker) {
throw std::runtime_error("Failed to get Docker manifest, HTTP code: " + std::to_string(manifest_res.first));
}
std::string manifest_str(manifest_res.second.begin(), manifest_res.second.end());
common_json manifest = common_json::parse(manifest_str);
std::string gguf_digest; // Find the GGUF layer
std::string manifest_str(manifest_res.second.begin(), manifest_res.second.end());
nlohmann::ordered_json manifest = nlohmann::ordered_json::parse(manifest_str);
std::string gguf_digest; // Find the GGUF layer
if (manifest.contains("layers")) {
for (const auto & layer : manifest["layers"]) {
if (layer.contains("mediaType")) {
@@ -985,26 +989,6 @@ std::vector<common_cached_model_info> common_list_cached_models() {
return result;
}
std::string common_download_resolve_path(const std::string & hf_repo_with_tag, const std::string & hf_file) {
auto [repo, tag] = common_download_split_repo_tag(hf_repo_with_tag);
auto files = hf_cache::get_cached_files(repo);
if (files.empty()) {
return "";
}
if (!hf_file.empty()) {
for (const auto & f : files) {
if (f.path == hf_file) {
return f.local_path;
}
}
return "";
}
return find_best_model(files, tag).local_path;
}
bool common_download_remove(const std::string & hf_repo_with_tag) {
namespace fs = std::filesystem;
-4
View File
@@ -85,10 +85,6 @@ std::vector<std::string> common_download_get_all_parts(const std::string & url);
// returns list of cached models
std::vector<common_cached_model_info> common_list_cached_models();
// resolve the local cached file path for a HF repo without network access (hf_file, if given, must match exactly)
// returns an empty string if the model is not present in the cache
std::string common_download_resolve_path(const std::string & hf_repo_with_tag, const std::string & hf_file = "");
// download single file from url to local path
// returns status code or -1 on error
// skip_etag: if true, don't read/write .etag files (for HF cache where filename is the hash)
+17 -105
View File
@@ -178,7 +178,7 @@ common_device_memory_data_vec common_get_device_memory_data(
static void common_params_fit_impl(
const char * path_model, struct llama_model_params * mparams, struct llama_context_params * cparams,
float * tensor_split, struct llama_model_tensor_buft_override * tensor_buft_overrides,
size_t * margins_s, uint32_t n_ctx_min, const common_fit_extra_model * extra, enum ggml_log_level log_level) {
size_t * margins_s, uint32_t n_ctx_min, enum ggml_log_level log_level) {
if (mparams->split_mode == LLAMA_SPLIT_MODE_TENSOR) {
throw common_params_fit_exception("llama_params_fit is not implemented for SPLIT_MODE_TENSOR, abort");
}
@@ -191,92 +191,10 @@ static void common_params_fit_impl(
uint32_t hp_nct = 0; // hparams.n_ctx_train
uint32_t hp_nex = 0; // hparams.n_expert
// with non-unified kv, we need to take into account n_streams
// for example, if memory can hold more than model's trained context size, we must extend the n_ctx to hold enough n_streams
const uint32_t n_streams = cparams->kv_unified ? 1 : std::max<uint32_t>(1, cparams->n_seq_max);
const bool n_ctx_auto = cparams->n_ctx == 0;
dmds_t dmds_extra; // memory of the extra model, laid out on the devices of the main model
uint32_t n_ctx_extra = 0; // context that memory was measured at
// the extra model competes for the same memory as the main model, add it to every measurement
// its memory is measured again whenever the context it follows changes
auto add_extra_memory = [&](dmds_t & dmds) {
if (extra == nullptr) {
return;
}
if (dmds_extra.empty() || n_ctx_extra != cparams->n_ctx) {
std::vector<ggml_backend_dev_t> devs_extra;
uint32_t ngl_extra = 0;
uint32_t nct_extra = 0;
uint32_t nex_extra = 0;
extra->cparams->n_ctx = cparams->n_ctx;
LOG_TRC("%s: getting device memory data for the extra model at a context size of %" PRIu32 ":\n",
__func__, cparams->n_ctx);
dmds_t measured;
try {
measured = common_get_device_memory_data_impl(
extra->path_model, extra->mparams, extra->cparams, devs_extra, ngl_extra, nct_extra, nex_extra, log_level);
} catch (const std::runtime_error & e) {
// the extra model is optional, fit the main model alone rather than giving up
LOG_WRN("%s: failed to measure the memory of the extra model, fitting without it: %s\n", __func__, e.what());
dmds_extra = dmds_t(devs.size() + 1);
n_ctx_extra = cparams->n_ctx;
return;
}
dmds_extra = dmds_t(devs.size() + 1);
dmds_extra.back().mb = measured.back().mb;
for (size_t je = 0; je < devs_extra.size(); je++) {
for (size_t id = 0; id < devs.size(); id++) {
if (devs_extra[je] == devs[id]) {
dmds_extra[id].mb.model += measured[je].mb.model;
dmds_extra[id].mb.context += measured[je].mb.context;
dmds_extra[id].mb.compute += measured[je].mb.compute;
break;
}
}
}
if (extra->shares_model) {
for (llama_device_memory_data & dmd : dmds_extra) {
dmd.mb.model = 0;
}
}
n_ctx_extra = cparams->n_ctx;
}
for (size_t id = 0; id < dmds.size(); id++) {
dmds[id].mb.model += dmds_extra[id].mb.model;
dmds[id].mb.context += dmds_extra[id].mb.context;
dmds[id].mb.compute += dmds_extra[id].mb.compute;
}
};
// step 1: get data for default parameters and check whether any changes are necessary in the first place
LOG_TRC("%s: getting device memory data for initial parameters:\n", __func__);
dmds_t dmds_full = common_get_device_memory_data_impl(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
// saturate instead of overflowing, this also preserves the UINT32_MAX sentinel of n_ctx_min:
const uint32_t n_ctx_max = (uint32_t) std::min<uint64_t>(uint64_t(hp_nct) * n_streams, UINT32_MAX);
const uint32_t n_ctx_min_total = (uint32_t) std::min<uint64_t>(uint64_t(n_ctx_min) * n_streams, UINT32_MAX);
// llama_context would use only hp_nct in total for n_ctx == 0, resolve the context before measuring anything else:
if (n_ctx_auto) {
cparams->n_ctx = n_ctx_max;
if (n_streams > 1) {
LOG_TRC("%s: context size unset and KV cache not unified -> using %" PRIu32 " for %" PRIu32 " sequences:\n",
__func__, n_ctx_max, n_streams);
dmds_full = common_get_device_memory_data_impl(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
}
}
add_extra_memory(dmds_full);
const dmds_t dmds_full = common_get_device_memory_data_impl(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
const size_t nd = devs.size(); // number of devices
std::vector<int64_t> margins; // this function uses int64_t rather than size_t for memory sizes to more conveniently handle deficits
@@ -389,8 +307,8 @@ static void common_params_fit_impl(
"%s: cannot meet free memory targets on all devices, need to use %" PRId64 " MiB less in total\n",
__func__, -global_surplus/MiB);
}
if (n_ctx_auto) {
if (n_ctx_max > n_ctx_min_total) {
if (cparams->n_ctx == 0) {
if (hp_nct > n_ctx_min) {
int64_t sum_used_target = sum_free;
if (nd == 0) {
sum_used_target -= margins[0];
@@ -410,9 +328,8 @@ static void common_params_fit_impl(
}
int64_t sum_projected_used_min_ctx = 0;
cparams->n_ctx = n_ctx_min_total;
dmds_t dmds_min_ctx = common_get_device_memory_data_impl(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
add_extra_memory(dmds_min_ctx);
cparams->n_ctx = n_ctx_min;
const dmds_t dmds_min_ctx = common_get_device_memory_data_impl(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
if (nd == 0) {
sum_projected_used_min_ctx = dmds_min_ctx.back().mb.total();
} else {
@@ -422,16 +339,14 @@ static void common_params_fit_impl(
}
if (sum_used_target > sum_projected_used_min_ctx) {
// linear interpolation between minimum and maximum context size:
cparams->n_ctx += (n_ctx_max - n_ctx_min_total) * (sum_used_target - sum_projected_used_min_ctx)
cparams->n_ctx += (hp_nct - n_ctx_min) * (sum_used_target - sum_projected_used_min_ctx)
/ (sum_projected_used - sum_projected_used_min_ctx);
// round down context for CUDA backend, keep it divisible by the number of streams:
const uint32_t align = 256 * n_streams;
cparams->n_ctx = std::max(cparams->n_ctx - cparams->n_ctx % align, n_ctx_min_total);
cparams->n_ctx = std::max(cparams->n_ctx - cparams->n_ctx % 256, n_ctx_min); // round down context for CUDA backend
const int64_t bytes_per_ctx = (sum_projected_used - sum_projected_used_min_ctx) / (n_ctx_max - n_ctx_min_total);
const int64_t memory_reduction = (n_ctx_max - cparams->n_ctx) * bytes_per_ctx;
const int64_t bytes_per_ctx = (sum_projected_used - sum_projected_used_min_ctx) / (hp_nct - n_ctx_min);
const int64_t memory_reduction = (hp_nct - cparams->n_ctx) * bytes_per_ctx;
LOG_TRC("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
__func__, n_ctx_max, cparams->n_ctx, memory_reduction/MiB);
__func__, hp_nct, cparams->n_ctx, memory_reduction/MiB);
if (nd <= 1) {
LOG_TRC("%s: entire model can be fit by reducing context\n", __func__);
return;
@@ -440,14 +355,14 @@ static void common_params_fit_impl(
} else {
const int64_t memory_reduction = sum_projected_used - sum_projected_used_min_ctx;
LOG_TRC("%s: context size reduced from %" PRIu32 " to %" PRIu32 " -> need %" PRId64 " MiB less memory in total\n",
__func__, n_ctx_max, cparams->n_ctx, memory_reduction/MiB);
__func__, hp_nct, cparams->n_ctx, memory_reduction/MiB);
}
} else {
if (n_ctx_min == UINT32_MAX) {
LOG_TRC("%s: user has requested full context size of %" PRIu32 " -> no change\n", __func__, n_ctx_max);
LOG_TRC("%s: user has requested full context size of %" PRIu32 " -> no change\n", __func__, hp_nct);
} else {
LOG_TRC("%s: default model context size is %" PRIu32 " which is <= the min. context size of %" PRIu32 " -> no change\n",
__func__, n_ctx_max, n_ctx_min_total);
__func__, hp_nct, n_ctx_min);
}
}
} else {
@@ -592,9 +507,8 @@ static void common_params_fit_impl(
llama_model_params mparams_copy = *mparams;
set_ngl_tensor_split_tbo(ngl_per_device, overflow_bufts, mparams_copy);
dmds_t dmd_nl = common_get_device_memory_data_impl(
const dmds_t dmd_nl = common_get_device_memory_data_impl(
path_model, &mparams_copy, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
add_extra_memory(dmd_nl);
LOG_TRC("%s: memory for test allocation by device:\n", func_name);
for (size_t id = 0; id < nd; id++) {
@@ -621,9 +535,8 @@ static void common_params_fit_impl(
mparams->tensor_buft_overrides = tensor_buft_overrides;
LOG_TRC("%s: getting device memory data with all MoE tensors moved to system memory:\n", __func__);
dmds_t dmds_cpu_moe = common_get_device_memory_data_impl(
const dmds_t dmds_cpu_moe = common_get_device_memory_data_impl(
path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
add_extra_memory(dmds_cpu_moe);
for (size_t id = 0; id < nd; id++) {
global_surplus_cpu_moe += dmds_cpu_moe[id].free;
@@ -883,12 +796,11 @@ enum common_params_fit_status common_fit_params(
llama_model_tensor_buft_override * tensor_buft_overrides,
size_t * margins,
uint32_t n_ctx_min,
const common_fit_extra_model * extra,
ggml_log_level log_level) {
const int64_t t0_us = llama_time_us();
common_params_fit_status status = COMMON_PARAMS_FIT_STATUS_SUCCESS;
try {
common_params_fit_impl(path_model, mparams, cparams, tensor_split, tensor_buft_overrides, margins, n_ctx_min, extra, log_level);
common_params_fit_impl(path_model, mparams, cparams, tensor_split, tensor_buft_overrides, margins, n_ctx_min, log_level);
LOG_TRC("%s: successfully fit params to free device memory\n", __func__);
} catch (const common_params_fit_exception & e) {
LOG_WRN("%s: failed to fit params to free device memory: %s\n", __func__, e.what());
-11
View File
@@ -11,16 +11,6 @@ enum common_params_fit_status {
COMMON_PARAMS_FIT_STATUS_ERROR = 2, // a hard error occurred, e.g. because no model could be found at the specified path
};
// a second model that shares the devices of the main model, e.g. a draft model
// - its context follows the context of the main model, so its memory is measured again whenever that context changes
// - shares_model tells the fit that the weights are already counted in the main model, as for an MTP context
struct common_fit_extra_model {
const char * path_model;
llama_model_params * mparams;
llama_context_params * cparams;
bool shares_model;
};
// fits mparams and cparams to free device memory (assumes system memory is unlimited)
// - returns true if the parameters could be successfully modified to fit device memory
// - this function is NOT thread safe because it modifies the global llama logger state
@@ -34,7 +24,6 @@ common_params_fit_status common_fit_params(
llama_model_tensor_buft_override * tensor_buft_overrides, // writable buffer for overrides, needs at least llama_max_tensor_buft_overrides elements
size_t * margins, // margins of memory to leave per device in bytes
uint32_t n_ctx_min, // minimum context size to set when trying to reduce memory use
const common_fit_extra_model * extra, // model to fit alongside the main one, nullptr if there is none
ggml_log_level log_level); // minimum log level to print during fitting, lower levels go to debug log
// print estimated memory to stdout
+11 -7
View File
@@ -4,7 +4,9 @@
#include "common.h"
#include "log.h"
#include "http.h"
#include "json.h"
#define JSON_ASSERT GGML_ASSERT
#include <nlohmann/json.hpp>
#include <filesystem>
#include <fstream>
@@ -13,6 +15,8 @@
#include <string_view>
#include <stdexcept>
namespace nl = nlohmann;
#if defined(_WIN32)
#define WIN32_LEAN_AND_MEAN
#ifndef NOMINMAX
@@ -191,8 +195,8 @@ static void safe_write_file(const fs::path & path, const std::string & data) {
}
}
static common_json api_get(const std::string & url,
const std::string & token) {
static nl::json api_get(const std::string & url,
const std::string & token) {
auto [cli, parts] = common_http_client(url);
httplib::Headers headers = {
@@ -210,10 +214,10 @@ static common_json api_get(const std::string & url,
auto body = res->body;
if (res->status == 200) {
return common_json::parse(res->body);
return nl::json::parse(res->body);
}
try {
body = common_json::parse(res->body)["error"].get<std::string>();
body = nl::json::parse(res->body)["error"].get<std::string>();
} catch (...) { }
throw std::runtime_error("GET failed (" + std::to_string(res->status) + "): " + body);
@@ -276,7 +280,7 @@ static std::string get_repo_commit(const std::string & repo_id,
safe_write_file(refs_path / name, commit);
return commit;
} catch (const common_json_error & e) {
} catch (const nl::json::exception & e) {
LOG_ERR("%s: JSON error: %s\n", __func__, e.what());
} catch (const std::exception & e) {
LOG_ERR("%s: error: %s\n", __func__, e.what());
@@ -354,7 +358,7 @@ hf_files get_repo_files(const std::string & repo_id,
files.push_back(file);
}
} catch (const common_json_error & e) {
} catch (const nl::json::exception & e) {
LOG_ERR("%s: JSON error: %s\n", __func__, e.what());
} catch (const std::exception & e) {
LOG_ERR("%s: error: %s\n", __func__, e.what());
+1 -1
View File
@@ -7,7 +7,7 @@ The implementation can be found in the `common/jinja` directory.
## Key Features
- Input marking: security against special token injection
- Decoupled from the JSON library: `common_json` is only used for JSON-to-internal type translation and is completely optional
- Decoupled from `nlohmann::json`: this dependency is only used for JSON-to-internal type translation and is completely optional
- Minimal primitive types: int, float, bool, string, array, object, none, undefined
- Detailed logging: allow source tracing on error
- Clean architecture: workarounds are applied to input data before entering the runtime (see `common/chat.cpp`)
+2 -34
View File
@@ -4,14 +4,14 @@
// note: the json dependency is only for defining input in a convenient way
// we can remove it in the future when we figure out a better way to define inputs using jinja::value
#include "json.h"
#include <nlohmann/json.hpp>
#include <functional>
#include <sstream>
#define FILENAME "jinja-caps"
using json = common_json;
using json = nlohmann::ordered_json;
namespace jinja {
@@ -117,7 +117,6 @@ caps caps_get(jinja::program & prog) {
JJ_DEBUG("%s\n", ">>> Running capability check: typed content");
bool checks_for_string = false;
static const std::string content_marker = "STRING_MARKER";
// case: typed content support
@@ -137,10 +136,6 @@ caps caps_get(jinja::program & prog) {
[&](context &, bool success, value & messages, value &, const std::string & rendered) {
auto & content = messages->at(0)->at("content");
caps_print_stats(content, "messages[0].content");
if (has_op(content, "test_is_string")) {
// checked if content is string
checks_for_string = true;
}
bool used_as_array = has_op(content, "selectattr") || has_op(content, "array_access");
if (used_as_array) {
// accessed as an array
@@ -156,33 +151,6 @@ caps caps_get(jinja::program & prog) {
}
);
if (checks_for_string) {
caps_try_execute(
prog,
[&]() {
// messages
return json::array({
{
{"role", "user"},
{"content", json::array({
})}
}
});
},
nullptr, // ctx_fn
nullptr, // tools_fn
[&](context &, bool success, value & messages, value &, const std::string &) {
auto & content = messages->at(0)->at("content");
caps_print_stats(content, "messages[0].content");
bool used_as_array = has_op(content, "selectattr") || has_op(content, "array_access");
if (used_as_array && success) {
// accessed as an array
result.supports_typed_content = true;
}
}
);
}
JJ_DEBUG("%s\n", ">>> Running capability check: system prompt");
// case: system prompt support
+2 -8
View File
@@ -412,18 +412,12 @@ value test_expression::execute_impl(context & ctx) {
throw std::runtime_error("Invalid test expression");
}
const std::string test_name = "test_is_" + test_id;
auto it = builtins.find(test_name);
JJ_DEBUG("Test expression %s '%s' %s (using function '%s')", operand->type().c_str(), test_id.c_str(), negate ? "(negate)" : "", test_name.c_str());
auto it = builtins.find("test_is_" + test_id);
JJ_DEBUG("Test expression %s '%s' %s (using function 'test_is_%s')", operand->type().c_str(), test_id.c_str(), negate ? "(negate)" : "", test_id.c_str());
if (it == builtins.end()) {
throw std::runtime_error("Unknown test '" + test_id + "'");
}
if (ctx.is_get_stats) {
value_t::stats_t::mark_used(input);
input->stats.ops.insert(test_name);
}
auto res = it->second(args);
if (negate) {
+3 -3
View File
@@ -3,7 +3,7 @@
#include "value.h"
// for converting from JSON to jinja values
#include "json.h"
#include <nlohmann/json.hpp>
#include <sstream>
#include <string>
@@ -1355,7 +1355,7 @@ const func_builtins & value_undefined_t::get_builtins() const {
//////////////////////////////////
static value from_json(const common_json & j, bool mark_input) {
static value from_json(const nlohmann::ordered_json & j, bool mark_input) {
if (j.is_null()) {
return mk_val<value_none>();
} else if (j.is_boolean()) {
@@ -1452,7 +1452,7 @@ bool value_compare(const value & a, const value & b, value_compare_op op) {
}
template<>
void global_from_json(context & ctx, const common_json & json_obj, bool mark_input) {
void global_from_json(context & ctx, const nlohmann::ordered_json & json_obj, bool mark_input) {
// printf("global_from_json: %s\n" , json_obj.dump(2).c_str());
if (json_obj.is_null() || !json_obj.is_object()) {
throw std::runtime_error("global_from_json: input JSON value must be an object");
+1 -1
View File
@@ -86,7 +86,7 @@ struct context; // forward declaration
// marking input can be useful for tracking data provenance
// and preventing template injection attacks
//
// Note: T_JSON can be common_json
// Note: T_JSON can be nlohmann::ordered_json
template<typename T_JSON>
void global_from_json(context & ctx, const T_JSON & json_obj, bool mark_input);
+44 -123
View File
@@ -1,8 +1,9 @@
#include "json-schema-to-grammar.h"
#include "common.h"
#include <nlohmann/json.hpp>
#include <algorithm>
#include <limits>
#include <map>
#include <regex>
#include <sstream>
@@ -11,7 +12,7 @@
#include <unordered_set>
#include <vector>
using json = common_json;
using json = nlohmann::ordered_json;
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();
@@ -277,9 +278,7 @@ static std::unordered_map<char, std::string> GRAMMAR_LITERAL_ESCAPES = {
{'\r', "\\r"}, {'\n', "\\n"}, {'"', "\\\""}, {'-', "\\-"}, {']', "\\]"}, {'\\', "\\\\"}
};
static const int MAX_PATTERN_DEPTH = 100;
static std::unordered_set<char> NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?', '^', '$'};
static std::unordered_set<char> NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?'};
static std::unordered_set<char> ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'^', '$', '.', '[', ']', '(', ')', '|', '{', '}', '*', '+', '?'};
static std::string replacePattern(const std::string & input, const std::regex & regex, const std::function<std::string(const std::smatch &)> & replacement) {
@@ -310,32 +309,6 @@ static std::string format_literal(const std::string & literal) {
std::string gbnf_format_literal(const std::string & literal) { return format_literal(literal); }
static size_t gbnf_escape_length(const std::string & pattern, size_t pos) {
if (pos + 1 >= pattern.length() || pattern[pos] != '\\') {
return 0;
}
size_t n_hex = 0;
switch (pattern[pos + 1]) {
case 'x': n_hex = 2; break;
case 'u': n_hex = 4; break;
case 'U': n_hex = 8; break;
case 't': case 'r': case 'n': case '\\': case '"': case '[': case ']':
return 2;
default:
return 0;
}
if (pos + 2 + n_hex > pattern.length()) {
return 0;
}
for (size_t i = pos + 2; i < pos + 2 + n_hex; i++) {
char h = pattern[i];
if (!((h >= '0' && h <= '9') || (h >= 'a' && h <= 'f') || (h >= 'A' && h <= 'F'))) {
return 0;
}
}
return 2 + n_hex;
}
class common_schema_converter {
private:
friend class common_schema_info;
@@ -372,42 +345,16 @@ private:
return string_join(rules, " | ");
}
// thrown when the pattern is a valid regex with no grammar equivalent
struct unsupported_pattern : public std::runtime_error {
using std::runtime_error::runtime_error;
};
// thrown when the pattern is not a valid regex
struct invalid_pattern : public std::runtime_error {
using std::runtime_error::runtime_error;
};
std::string _visit_pattern(const std::string & pattern, const std::string & name) {
auto rules_snapshot = _rules;
try {
return _pattern_to_rule(pattern, name);
} catch (const unsupported_pattern & err) {
// revert rules
_rules = std::move(rules_snapshot);
_warnings.push_back("pattern " + pattern + " is not supported (" + err.what() + "), accepting any string");
return _add_rule(name, _add_primitive("string", PRIMITIVE_RULES.at("string")));
} catch (const invalid_pattern & err) {
_rules = std::move(rules_snapshot);
_errors.push_back("Invalid pattern " + pattern + ": " + err.what());
if (!(pattern.front() == '^' && pattern.back() == '$')) {
_errors.push_back("Pattern must start with '^' and end with '$'");
return "";
}
}
std::string _pattern_to_rule(const std::string & pattern, const std::string & name) {
if (pattern.length() < 2 || pattern.front() != '^' || pattern.back() != '$') {
throw unsupported_pattern("not anchored with '^' and '$'");
}
std::string sub_pattern = pattern.substr(1, pattern.length() - 2);
std::unordered_map<std::string, std::string> sub_rule_ids;
size_t i = 0;
size_t length = sub_pattern.length();
int paren_depth = 0;
using literal_or_rule = std::pair<std::string, bool>;
auto to_rule = [&](const literal_or_rule & ls) {
@@ -416,6 +363,7 @@ private:
return is_literal ? "\"" + s + "\"" : s;
};
std::function<literal_or_rule()> transform = [&]() -> literal_or_rule {
size_t start = i;
std::vector<literal_or_rule> seq;
auto get_dot = [&]() {
@@ -472,42 +420,43 @@ private:
if (i + 1 < length && sub_pattern[i + 1] == ':') {
i += 2; // skip "?:" for non-capturing group, treat as regular group
} else {
// lookaround, named group, inline flags, ...
throw unsupported_pattern("unsupported group syntax");
// lookahead/lookbehind (?=, ?!, ?<=, ?<!) - not supported
_warnings.push_back("Unsupported pattern syntax");
// skip to matching ')' to avoid UB on empty seq
int depth = 1;
while (i < length && depth > 0) {
if (sub_pattern[i] == '\\' && i + 1 < length) {
i += 2; // skip escaped character
} else {
if (sub_pattern[i] == '(') depth++;
else if (sub_pattern[i] == ')') depth--;
i++;
}
}
continue;
}
}
paren_depth++;
if (paren_depth > MAX_PATTERN_DEPTH) {
throw unsupported_pattern("pattern nesting too deep");
}
seq.emplace_back("(" + to_rule(transform()) + ")", false);
} else if (c == ')') {
i++;
if (paren_depth == 0) {
throw invalid_pattern("unbalanced parentheses");
if (start > 0 && sub_pattern[start - 1] != '(' && (start < 2 || sub_pattern[start - 2] != '?' || sub_pattern[start - 1] != ':')) {
_errors.push_back("Unbalanced parentheses");
}
paren_depth--;
return join_seq();
} else if (c == '^' || c == '$') {
throw unsupported_pattern("anchor inside the pattern");
} else if (c == '[') {
std::string square_brackets = std::string(1, c);
i++;
while (i < length && sub_pattern[i] != ']') {
if (sub_pattern[i] == '\\') {
auto escape_length = gbnf_escape_length(sub_pattern, i);
if (escape_length == 0) {
throw unsupported_pattern("unsupported escape in character class: " + sub_pattern.substr(i, 2));
}
square_brackets += sub_pattern.substr(i, escape_length);
i += escape_length;
square_brackets += sub_pattern.substr(i, 2);
i += 2;
} else {
square_brackets += sub_pattern[i];
i++;
}
}
if (i >= length) {
throw invalid_pattern("unterminated character class");
_errors.push_back("Unbalanced square brackets");
}
square_brackets += ']';
i++;
@@ -516,9 +465,6 @@ private:
seq.emplace_back("|", false);
i++;
} else if (c == '*' || c == '+' || c == '?') {
if (seq.empty()) {
throw invalid_pattern("nothing to repeat");
}
seq.back() = std::make_pair(to_rule(seq.back()) + c, false);
i++;
} else if (c == '{') {
@@ -529,19 +475,18 @@ private:
i++;
}
if (i >= length) {
throw unsupported_pattern("unterminated curly brackets");
_errors.push_back("Unbalanced curly brackets");
}
curly_brackets += '}';
i++;
auto nums = string_split(curly_brackets.substr(1, curly_brackets.length() - 2), ",");
int min_times = 0;
int max_times = std::numeric_limits<int>::max();
if (nums.size() != 1 && nums.size() != 2) {
throw unsupported_pattern("wrong number of values in curly brackets");
}
try {
if (nums.size() == 1) {
min_times = max_times = std::stoi(nums[0]);
} else if (nums.size() != 2) {
_errors.push_back("Wrong number of values in curly brackets");
} else {
if (!nums[0].empty()) {
min_times = std::stoi(nums[0]);
@@ -550,11 +495,9 @@ private:
max_times = std::stoi(nums[1]);
}
}
} catch (const std::logic_error &) {
throw unsupported_pattern("invalid number in curly brackets");
}
if (seq.empty()) {
throw invalid_pattern("nothing to repeat");
} catch (const std::invalid_argument & e) {
_errors.push_back("Invalid number in curly brackets");
return std::make_pair("", false);
}
auto &last = seq.back();
auto &sub = last.first;
@@ -580,22 +523,15 @@ private:
return NON_LITERAL_SET.find(c) != NON_LITERAL_SET.end();
};
while (i < length) {
if (sub_pattern[i] == '\\') {
if (i == length - 1) {
throw invalid_pattern("trailing backslash");
}
if (sub_pattern[i] == '\\' && i < length - 1) {
char next = sub_pattern[i + 1];
if (ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS.find(next) != ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS.end()) {
i++;
literal += sub_pattern[i];
i++;
} else {
auto escape_length = gbnf_escape_length(sub_pattern, i);
if (escape_length == 0) {
throw unsupported_pattern("unsupported escape: " + sub_pattern.substr(i, 2));
}
literal += sub_pattern.substr(i, escape_length);
i += escape_length;
literal += sub_pattern.substr(i, 2);
i += 2;
}
} else if (sub_pattern[i] == '"') {
literal += "\\\"";
@@ -608,21 +544,14 @@ private:
break;
}
}
if (literal.empty()) { // nothing was consumed, ex. a stray ']' or '}'
throw unsupported_pattern(std::string("unsupported character: ") + c);
if (!literal.empty()) {
seq.emplace_back(literal, true);
}
seq.emplace_back(literal, true);
}
}
return join_seq();
};
auto rule = to_rule(transform());
if (paren_depth != 0) {
throw invalid_pattern("unbalanced parentheses");
}
return _add_rule(name, "\"\\\"\" (" + rule + ") \"\\\"\"");
return _add_rule(name, "\"\\\"\" (" + to_rule(transform()) + ") \"\\\"\"");
}
/*
@@ -748,10 +677,6 @@ private:
optional_props.push_back("*");
}
if (required_props.empty() && optional_props.empty()) {
return "\"{\" space \"}\"";
}
std::string rule = "\"{\" space ";
for (size_t i = 0; i < required_props.size(); i++) {
if (i > 0) {
@@ -920,11 +845,7 @@ public:
return _add_rule(rule_name, _resolve_ref(schema["$ref"]));
}
if (schema.contains("oneOf") || schema.contains("anyOf")) {
const json & alts = schema.contains("oneOf") ? schema.at("oneOf") : schema.at("anyOf");
std::vector<json> alt_schemas;
for (const auto & alt : alts) {
alt_schemas.push_back(alt);
}
std::vector<json> alt_schemas = schema.contains("oneOf") ? schema["oneOf"].get<std::vector<json>>() : schema["anyOf"].get<std::vector<json>>();
return _add_rule(rule_name, _generate_union_rule(name, alt_schemas));
}
if (schema_type.is_array()) {
@@ -1118,7 +1039,7 @@ common_schema_info::~common_schema_info() = default;
common_schema_info::common_schema_info(common_schema_info &&) noexcept = default;
common_schema_info & common_schema_info::operator=(common_schema_info &&) noexcept = default;
void common_schema_info::resolve_refs(common_json & schema) {
void common_schema_info::resolve_refs(nlohmann::ordered_json & schema) {
impl_->resolve_refs(schema, "");
}
@@ -1126,7 +1047,7 @@ void common_schema_info::resolve_refs(common_json & schema) {
// Some models emit raw string values rather than JSON-encoded strings for string parameters.
// If any branch of the schema (via oneOf, anyOf, $ref, etc.) permits a string, this returns
// true, allowing callers to handle the value as a raw string for simplicity.
bool common_schema_info::resolves_to_string(const common_json & schema) {
bool common_schema_info::resolves_to_string(const nlohmann::ordered_json & schema) {
std::unordered_set<std::string> visited_refs;
std::function<bool(const json &)> check = [&](const json & s) -> bool {
@@ -1234,7 +1155,7 @@ bool common_schema_info::resolves_to_string(const common_json & schema) {
return check(schema);
}
std::string json_schema_to_grammar(const common_json & schema, bool force_gbnf) {
std::string json_schema_to_grammar(const json & schema, bool force_gbnf) {
#ifdef LLAMA_USE_LLGUIDANCE
if (!force_gbnf) {
return "%llguidance {}\nstart: %json " + schema.dump();
@@ -1255,10 +1176,10 @@ std::string build_grammar(const std::function<void(const common_grammar_builder
/* .add_rule = */ [&](const std::string & name, const std::string & rule) {
return converter._add_rule(name, rule);
},
/* .add_schema = */ [&](const std::string & name, const common_json & schema) {
/* .add_schema = */ [&](const std::string & name, const nlohmann::ordered_json & schema) {
return converter.visit(schema, name == "root" ? "" : name);
},
/* .resolve_refs = */ [&](common_json & schema) {
/* .resolve_refs = */ [&](nlohmann::ordered_json & schema) {
converter.resolve_refs(schema, "");
}
};
+6 -6
View File
@@ -1,12 +1,12 @@
#pragma once
#include "json.h"
#include <nlohmann/json_fwd.hpp>
#include <functional>
#include <memory>
#include <string>
std::string json_schema_to_grammar(const common_json & schema,
std::string json_schema_to_grammar(const nlohmann::ordered_json & schema,
bool force_gbnf = false);
class common_schema_converter;
@@ -24,14 +24,14 @@ class common_schema_info {
common_schema_info(common_schema_info &&) noexcept;
common_schema_info & operator=(common_schema_info &&) noexcept;
void resolve_refs(common_json & schema);
bool resolves_to_string(const common_json & schema);
void resolve_refs(nlohmann::ordered_json & schema);
bool resolves_to_string(const nlohmann::ordered_json & schema);
};
struct common_grammar_builder {
std::function<std::string(const std::string &, const std::string &)> add_rule;
std::function<std::string(const std::string &, const common_json &)> add_schema;
std::function<void(common_json &)> resolve_refs;
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 {
-433
View File
@@ -1,433 +0,0 @@
#include "json.h"
#include "ggml.h"
#define JSON_ASSERT GGML_ASSERT
#include <nlohmann/json.hpp>
#include <iterator>
#include <new>
#include <set>
#include <unordered_map>
#include <vector>
using nlohmann::ordered_json;
// a common_json is the backing value, so any value of a tree can be used as a common_json
static_assert(sizeof(ordered_json) <= sizeof(common_json), "common_json storage is too small");
static_assert(alignof(ordered_json) <= alignof(common_json), "common_json alignment is too weak");
// runs fn and gives every error of the backing library as a common_json_error
template <typename F>
static decltype(auto) guard(F && fn) {
try {
return fn();
} catch (const ordered_json::exception & e) {
throw common_json_error(e.what());
}
}
static ordered_json & as_json(common_json * self) {
return *reinterpret_cast<ordered_json *>(self);
}
static const ordered_json & as_json(const common_json * self) {
return *reinterpret_cast<const ordered_json *>(self);
}
static common_json & as_common(ordered_json & json) {
return *reinterpret_cast<common_json *>(&json);
}
static const common_json & as_common(const ordered_json & json) {
return *reinterpret_cast<const common_json *>(&json);
}
static ordered_json to_json(const common_json_value & val) {
switch (val.type) {
case common_json_value::VAL_NULL: return nullptr;
case common_json_value::VAL_BOOL: return val.val_bool;
case common_json_value::VAL_INT: return val.val_int;
case common_json_value::VAL_UINT: return val.val_uint;
case common_json_value::VAL_DOUBLE: return val.val_double;
case common_json_value::VAL_STRING: return val.val_string;
case common_json_value::VAL_JSON:
// one owner means no one else can see this tree, so it is safe to move it out
// note: this makes a value single use, same as the json_ref of the backing library
if (val.val_json.use_count() == 1) {
return std::move(as_json(val.val_json.get()));
}
return as_json(val.val_json.get());
}
return nullptr;
}
common_json_value::common_json_value(const char * val) {
if (val) {
type = VAL_STRING;
val_string = val;
} else {
type = VAL_NULL;
}
}
common_json_value::common_json_value(const common_json & val) :
type(VAL_JSON), val_json(std::make_shared<common_json>(val)) {}
common_json_value::common_json_value(common_json && val) :
type(VAL_JSON), val_json(std::make_shared<common_json>(std::move(val))) {}
// the ctors and get<T>() below are explicit specializations, giving strong symbols
// an explicit instantiation is a weak symbol, dropped by some LTO builds (clang-cl)
template <typename T>
static std::shared_ptr<common_json> set_json(const std::set<T> & vals) {
common_json out = common_json::array();
for (const auto & val : vals) {
out.push_back(val);
}
return std::make_shared<common_json>(std::move(out));
}
// a set value is usable only for the types below
#define COMMON_JSON_SET(...) template <> common_json_value::common_json_value(const std::set<__VA_ARGS__> & vals) : type(VAL_JSON), val_json(set_json(vals)) {}
COMMON_JSON_SET(int)
COMMON_JSON_SET(std::string)
#undef COMMON_JSON_SET
template <typename T>
static std::shared_ptr<common_json> map_json(const T & vals) {
common_json out = common_json::object();
for (const auto & val : vals) {
out.set({ val.first, val.second });
}
return std::make_shared<common_json>(std::move(out));
}
// a map value is usable only for the types below
#define COMMON_JSON_MAP(...) template <> common_json_value::common_json_value(const std::map<std::string, __VA_ARGS__> & vals) : type(VAL_JSON), val_json(map_json(vals)) {}
COMMON_JSON_MAP(bool)
COMMON_JSON_MAP(std::string)
#undef COMMON_JSON_MAP
// an unordered map value is usable only for the types below
#define COMMON_JSON_UMAP(...) template <> common_json_value::common_json_value(const std::unordered_map<std::string, __VA_ARGS__> & vals) : type(VAL_JSON), val_json(map_json(vals)) {}
COMMON_JSON_UMAP(size_t)
#undef COMMON_JSON_UMAP
template <typename T>
static std::shared_ptr<common_json> vec_json(const std::vector<T> & vals) {
common_json out = common_json::array();
for (const auto & val : vals) {
out.push_back(val);
}
return std::make_shared<common_json>(std::move(out));
}
// a vector value is usable only for the types below
// note: std::vector<bool> is not here, its proxy reference does not convert
#define COMMON_JSON_VEC(...) template <> common_json_value::common_json_value(const std::vector<__VA_ARGS__> & vals) : type(VAL_JSON), val_json(vec_json(vals)) {}
COMMON_JSON_VEC(int)
COMMON_JSON_VEC(unsigned char)
COMMON_JSON_VEC(unsigned int)
COMMON_JSON_VEC(long)
COMMON_JSON_VEC(unsigned long)
COMMON_JSON_VEC(long long)
COMMON_JSON_VEC(unsigned long long)
COMMON_JSON_VEC(float)
COMMON_JSON_VEC(double)
COMMON_JSON_VEC(std::string)
COMMON_JSON_VEC(std::vector<float>)
COMMON_JSON_VEC(common_json)
#undef COMMON_JSON_VEC
common_json_value::common_json_value(std::initializer_list<common_json_item> items) :
type(VAL_JSON), val_json(std::make_shared<common_json>(items)) {}
// null, same as the backing library
// operator[] turns it into an object, push_back() into an array
common_json::common_json() {
new (storage) ordered_json();
}
common_json::common_json(const common_json & other) {
new (storage) ordered_json(as_json(&other));
}
common_json::common_json(common_json && other) noexcept {
new (storage) ordered_json(std::move(as_json(&other)));
}
common_json::common_json(std::initializer_list<common_json_item> items) {
new (storage) ordered_json(ordered_json::object());
for (const auto & item : items) {
set(item);
}
}
common_json::common_json(const common_json_value & val) {
new (storage) ordered_json(to_json(val));
}
common_json::common_json(std::nullptr_t) {
new (storage) ordered_json(nullptr);
}
common_json & common_json::operator=(common_json other) noexcept {
as_json(this).swap(as_json(&other));
return *this;
}
common_json::~common_json() {
as_json(this).~basic_json();
}
common_json common_json::parse(const std::string & text) {
try {
// the assignment moves the parsed tree in, it does not copy
common_json out;
as_json(&out) = ordered_json::parse(text);
return out;
} catch (const std::exception & e) {
throw common_json_error(e.what());
}
}
common_json common_json::parse_no_throw(const std::string & text) {
common_json out;
as_json(&out) = ordered_json::parse(text, nullptr, false);
return out;
}
bool common_json::is_discarded() const {
return as_json(this).is_discarded();
}
common_json common_json::array() {
common_json out;
as_json(&out) = ordered_json::array();
return out;
}
common_json common_json::array(std::initializer_list<common_json_value> vals) {
common_json out;
ordered_json & arr = as_json(&out);
arr = ordered_json::array();
for (const auto & val : vals) {
arr.push_back(to_json(val));
}
return out;
}
common_json common_json::object() {
common_json out;
as_json(&out) = ordered_json::object();
return out;
}
common_json common_json::object(std::initializer_list<common_json_item> items) {
return common_json(items);
}
common_json common_json::make(const common_json_value & val) {
return common_json(val);
}
bool common_json::is_null() const { return as_json(this).is_null(); }
bool common_json::is_object() const { return as_json(this).is_object(); }
bool common_json::is_array() const { return as_json(this).is_array(); }
bool common_json::is_string() const { return as_json(this).is_string(); }
bool common_json::is_boolean() const { return as_json(this).is_boolean(); }
bool common_json::is_number() const { return as_json(this).is_number(); }
bool common_json::is_number_integer() const { return as_json(this).is_number_integer(); }
bool common_json::is_number_float() const { return as_json(this).is_number_float(); }
bool common_json::empty() const { return as_json(this).empty(); }
size_t common_json::size() const { return as_json(this).size(); }
bool common_json::contains(const std::string & key) const {
return as_json(this).contains(key);
}
bool common_json::operator==(const common_json_value & val) const {
// compare a tree in place, to_json() would copy it
if (val.type == common_json_value::VAL_JSON) {
return as_json(this) == as_json(val.val_json.get());
}
return as_json(this) == to_json(val);
}
bool common_json::operator!=(const common_json_value & val) const {
return !(*this == val);
}
common_json & common_json::at(const std::string & key) { return guard([&]() -> common_json & { return as_common(as_json(this).at(key)); }); }
const common_json & common_json::at(const std::string & key) const { return guard([&]() -> const common_json & { return as_common(as_json(this).at(key)); }); }
common_json & common_json::at(size_t idx) { return guard([&]() -> common_json & { return as_common(as_json(this).at(idx)); }); }
const common_json & common_json::at(size_t idx) const { return guard([&]() -> const common_json & { return as_common(as_json(this).at(idx)); }); }
common_json & common_json::operator[](const std::string & key) { return guard([&]() -> common_json & { return as_common(as_json(this)[key]); }); }
const common_json & common_json::operator[](const std::string & key) const { return guard([&]() -> const common_json & { return as_common(as_json(this).at(key)); }); }
common_json & common_json::operator[](size_t idx) { return guard([&]() -> common_json & { return as_common(as_json(this)[idx]); }); }
const common_json & common_json::operator[](size_t idx) const { return guard([&]() -> const common_json & { return as_common(as_json(this).at(idx)); }); }
common_json & common_json::front() { return as_common(as_json(this).front()); }
const common_json & common_json::front() const { return as_common(as_json(this).front()); }
common_json & common_json::back() { return as_common(as_json(this).back()); }
const common_json & common_json::back() const { return as_common(as_json(this).back()); }
void common_json::clear() {
as_json(this).clear();
}
void common_json::erase(const std::string & key) {
guard([&] { as_json(this).erase(key); });
}
void common_json::erase(size_t idx) {
guard([&] { as_json(this).erase(idx); });
}
void common_json::assign(const common_json_value & val) {
as_json(this) = to_json(val);
}
void common_json::set(const common_json_item & item) {
guard([&] { as_json(this)[item.key] = to_json(item.val); });
}
void common_json::push_back(const common_json_value & val) {
guard([&] { as_json(this).push_back(to_json(val)); });
}
void common_json::push_back(std::initializer_list<common_json_item> items) {
common_json val(items);
guard([&] { as_json(this).push_back(std::move(as_json(&val))); });
}
size_t common_json::count(const std::string & key) const {
return as_json(this).count(key);
}
void common_json::insert(const common_json & vals) {
guard([&] {
ordered_json & self = as_json(this);
self.insert(self.end(), as_json(&vals).begin(), as_json(&vals).end());
});
}
std::string common_json::dump(int indent) const {
return guard([&] { return as_json(this).dump(indent); });
}
std::string common_json::dump_safe(int indent) const {
return as_json(this).dump(indent, ' ', false, ordered_json::error_handler_t::replace);
}
// an array is indexed directly, an object needs a walk from the start
common_json & common_json::iterator::operator*() const {
return guard([&]() -> common_json & {
ordered_json & j = as_json(node);
if (j.is_object()) {
return as_common(std::next(j.begin(), idx).value());
}
if (j.is_array()) {
return as_common(j[idx]);
}
// a plain value gives itself once, same as the backing library
return *node;
});
}
std::string common_json::iterator::key() const {
return guard([&] { return std::next(as_json(node).begin(), idx).key(); });
}
common_json::iterator common_json::begin() const {
return iterator(const_cast<common_json *>(this), 0);
}
common_json::iterator common_json::end() const {
return iterator(const_cast<common_json *>(this), size());
}
// the keys follow the backing library: the index for an array, "" for a plain value
common_json::items_view::entry common_json::items_view::iterator::operator*() const {
return guard([&]() -> entry {
ordered_json & j = as_json(node);
if (j.is_object()) {
auto it = std::next(j.begin(), idx);
return { it.key(), as_common(it.value()) };
}
if (j.is_array()) {
return { std::to_string(idx), as_common(j[idx]) };
}
return { std::string(), *node };
});
}
common_json::items_view common_json::items() const {
return items_view(const_cast<common_json *>(this), size());
}
// the backing library cannot build a common_json, so this one is just a copy
template <> common_json common_json::get<common_json>() const {
return *this;
}
// get<T>() is usable only for the types below
#define COMMON_JSON_GET(...) template <> __VA_ARGS__ common_json::get<__VA_ARGS__>() const { return guard([&] { return as_json(this).get<__VA_ARGS__>(); }); }
COMMON_JSON_GET(bool)
COMMON_JSON_GET(int)
COMMON_JSON_GET(unsigned int)
COMMON_JSON_GET(long)
COMMON_JSON_GET(unsigned long)
COMMON_JSON_GET(long long)
COMMON_JSON_GET(unsigned long long)
COMMON_JSON_GET(float)
COMMON_JSON_GET(double)
COMMON_JSON_GET(std::string)
COMMON_JSON_GET(std::vector<float>)
COMMON_JSON_GET(std::vector<std::string>)
COMMON_JSON_GET(std::set<std::string>)
COMMON_JSON_GET(std::vector<int>)
COMMON_JSON_GET(std::vector<size_t>)
COMMON_JSON_GET(std::unordered_map<std::string, size_t>)
#undef COMMON_JSON_GET
// must stay below the get<std::string> specialization
common_json::operator std::string() const {
return get<std::string>();
}
std::string common_json::value(const std::string & key, const char * def) const {
return contains(key) ? at(key).get<std::string>() : std::string(def);
}
-352
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@@ -1,352 +0,0 @@
#pragma once
#include <cstddef>
#include <cstdint>
#include <initializer_list>
#include <iterator>
#include <map>
#include <memory>
#include <set>
#include <stdexcept>
#include <string>
#include <string_view>
#include <type_traits>
#include <unordered_map>
#include <utility>
#include <vector>
// common_json, a thin wrapper around vendor json library
// the underlay library is pimpl, we are using nlohmann::json for now
//
// many features of the library are deliberately left out, to keep this interface small and generic and to keep compile time down
//
// some main differences compared to nlohmann::json :
// - object keys keep the order in which they are added
// - errors are always throw as common_json_error
// - obj.push_back({key, val}) is intentionally unsupported to avoid confusion with push_back on a vector; write it as obj[key] = val for clarity
// - a braced pair in value position does not build, e.g. {"key", {"a", "b"}}; write array({"a", "b"}) where nlohmann made an array
//
// in doubt, search the code base for an existing usage example; do not add anything to this header unless absolutely necessary
class common_json;
// common_json_value holds a list of these, and each of them holds a value, so one must come first
struct common_json_item;
struct common_json_error : std::runtime_error {
using std::runtime_error::runtime_error;
};
// one value, tagged so that this header stays free of the backing library
// note: a value that holds a tree is single use, the second use gives null
struct common_json_value {
enum value_type {
VAL_NULL,
VAL_BOOL,
VAL_INT,
VAL_UINT,
VAL_DOUBLE,
VAL_STRING,
VAL_JSON,
};
value_type type = VAL_NULL;
union {
bool val_bool;
int64_t val_int;
uint64_t val_uint = 0;
double val_double;
};
std::string val_string;
std::shared_ptr<common_json> val_json;
common_json_value(std::nullptr_t = nullptr) : type(VAL_NULL) {}
common_json_value(bool val) : type(VAL_BOOL), val_bool(val) {}
common_json_value(std::string val) : type(VAL_STRING), val_string(std::move(val)) {}
// without this a string_view lands on the common_json ctor below and recurses
common_json_value(std::string_view val) : type(VAL_STRING), val_string(val) {}
common_json_value(const char * val);
common_json_value(const common_json & val);
common_json_value(common_json && val);
// only for the types instantiated in json.cpp, the rest fails at link time
template <typename T> common_json_value(const std::vector<T> & vals);
// a set becomes an array, in the set's own order
template <typename T> common_json_value(const std::set<T> & vals);
// a map becomes an object, keyed in the map's own order
template <typename T> common_json_value(const std::map<std::string, T> & vals);
template <typename T> common_json_value(const std::unordered_map<std::string, T> & vals);
// nested object, e.g. {"fn", {{"name", "x"}}}
// note: a nested pair {"a", "b"} does not build, use common_json::array({"a", "b"}) for an array
common_json_value(std::initializer_list<common_json_item> items);
template <typename T, typename std::enable_if<std::is_integral<T>::value && !std::is_same<T, bool>::value, int>::type = 0>
common_json_value(T val) : type(std::is_signed<T>::value ? VAL_INT : VAL_UINT) {
if (std::is_signed<T>::value) {
val_int = (int64_t) val;
} else {
val_uint = (uint64_t) val;
}
}
template <typename T, typename std::enable_if<std::is_floating_point<T>::value, int>::type = 0>
common_json_value(T val) : type(VAL_DOUBLE), val_double((double) val) {}
};
struct common_json_item {
std::string key;
common_json_value val;
template <typename T>
common_json_item(std::string key, T && val) :
key(std::move(key)), val(std::forward<T>(val)) {}
// a braced list cannot deduce T, so it needs its own overload
common_json_item(std::string key, std::initializer_list<common_json_item> items) :
key(std::move(key)), val(items) {}
};
// the types common_json_value holds on its own
// anything else reaches its common_json ctor and recurses forever
template <typename T> struct common_json_is_value : std::integral_constant<bool,
std::is_arithmetic<T>::value ||
std::is_same<T, std::nullptr_t>::value ||
std::is_same<T, std::string>::value ||
std::is_same<T, std::string_view>::value ||
std::is_same<T, char *>::value ||
std::is_same<T, const char *>::value ||
std::is_same<T, common_json>::value> {};
template <typename T, typename A>
struct common_json_is_value<std::vector<T, A>> : std::true_type {};
template <typename T, typename C, typename A>
struct common_json_is_value<std::set<T, C, A>> : std::true_type {};
template <typename V, typename C, typename A>
struct common_json_is_value<std::map<std::string, V, C, A>> : std::true_type {};
template <typename V, typename H, typename E, typename A>
struct common_json_is_value<std::unordered_map<std::string, V, H, E, A>> : std::true_type {};
class common_json {
public:
common_json();
common_json(const common_json & other);
common_json(common_json && other) noexcept;
common_json(std::initializer_list<common_json_item> items);
common_json(const common_json_value & val);
// direct, a value would need two conversions in a row
common_json(std::nullptr_t);
// one step, so that "abc" or a vector can go straight into a common_json
template <typename T, typename std::enable_if<!std::is_same<typename std::decay<T>::type, common_json>::value &&
!std::is_same<typename std::decay<T>::type, common_json_value>::value, int>::type = 0>
common_json(T && val) : common_json(common_json_value(std::forward<T>(val))) {
static_assert(common_json_is_value<typename std::decay<T>::type>::value,
"no common_json_value ctor holds this type, add one instead of letting it recurse");
}
// by value, same as the backing library
// the right side is copied before the left side can invalidate it, e.g. msg["a"] = msg.at("b")
common_json & operator=(common_json other) noexcept;
~common_json();
// throws common_json_error if the text is not valid JSON
static common_json parse(const std::string & text);
// gives a discarded value instead of throwing, check it with is_discarded()
static common_json parse_no_throw(const std::string & text);
bool is_discarded() const;
static common_json array();
static common_json array(std::initializer_list<common_json_value> vals);
static common_json object();
static common_json object(std::initializer_list<common_json_item> items);
// holds a single value, e.g. make("abc").dump() gives "\"abc\""
static common_json make(const common_json_value & val);
bool is_null() const;
bool is_object() const;
bool is_array() const;
bool is_string() const;
bool is_boolean() const;
bool is_number() const;
bool is_number_integer() const;
bool is_number_float() const;
bool empty() const;
size_t size() const;
bool contains(const std::string & key) const;
bool operator==(const common_json_value & val) const;
bool operator!=(const common_json_value & val) const;
// at() throws common_json_error if the key is missing, operator[] adds a null value instead
// note: a const operator[] cannot add, it throws like at()
common_json & at(const std::string & key);
const common_json & at(const std::string & key) const;
common_json & at(size_t idx);
const common_json & at(size_t idx) const;
common_json & operator[](const std::string & key);
const common_json & operator[](const std::string & key) const;
common_json & operator[](const char * key) { return (*this)[std::string(key)]; }
const common_json & operator[](const char * key) const { return (*this)[std::string(key)]; }
common_json & operator[](int idx) { return (*this)[to_idx(idx)]; }
const common_json & operator[](int idx) const { return (*this)[to_idx(idx)]; }
common_json & operator[](size_t idx);
const common_json & operator[](size_t idx) const;
common_json & front();
const common_json & front() const;
common_json & back();
const common_json & back() const;
void clear();
void erase(const std::string & key);
void erase(size_t idx);
// only for the types instantiated in json.cpp, the rest fails at link time
template <typename T> T get() const;
// implicit get<T>() for plain values, so they can be assigned to their C++ type directly
// note: kept to this short list on purpose, a wider one makes j["key"] ambiguous
// note: a numeric one would make "str = json;" ambiguous, a number converts to char too
operator std::string() const;
template <typename T>
T value(const std::string & key, T def) const {
return contains(key) ? at(key).get<T>() : def;
}
std::string value(const std::string & key, const char * def) const;
// a JSON default needs no get<T>(), it is already the right type
common_json value(const std::string & key, const common_json & def) const {
return contains(key) ? at(key) : def;
}
void assign(const common_json_value & val);
void set(const common_json_item & item);
void push_back(const common_json_value & val);
// appends one object, e.g. push_back({{"a", 1}})
void push_back(std::initializer_list<common_json_item> items);
// 1 if the key is there, 0 if not
size_t count(const std::string & key) const;
// appends every value of another array; inserting an array into itself throws
void insert(const common_json & vals);
// a common_json goes through the copy assignment above, everything else becomes a value
template <typename T, typename std::enable_if<!std::is_same<typename std::decay<T>::type, common_json>::value, int>::type = 0>
common_json & operator=(T && val) {
assign(common_json_value(std::forward<T>(val)));
return *this;
}
std::string dump(int indent = -1) const;
// same as dump(), but bad UTF-8 gets replaced instead of throwing
std::string dump_safe(int indent = -1) const;
// walks an array by index, or an object in insertion order
// a plain value gives itself once, same as the backing library
class iterator {
public:
using iterator_category = std::forward_iterator_tag;
using value_type = common_json;
using difference_type = std::ptrdiff_t;
using pointer = common_json *;
using reference = common_json &;
iterator(common_json * node, size_t idx) : node(node), idx(idx) {}
common_json & operator*() const;
common_json & value() const { return **this; }
std::string key() const;
iterator & operator++() {
idx++;
return *this;
}
bool operator!=(const iterator & other) const { return idx != other.idx; }
bool operator==(const iterator & other) const { return idx == other.idx; }
private:
common_json * node;
size_t idx;
};
iterator begin() const;
iterator end() const;
// allows: for (const auto & [key, val] : obj.items())
class items_view {
public:
// the members are public, so an entry also works with structured bindings
struct entry {
std::string k;
common_json & v;
const std::string & key() const { return k; }
common_json & value() const { return v; }
};
items_view(common_json * node, size_t n) : node(node), n(n) {}
class iterator {
public:
iterator(common_json * node, size_t idx) : node(node), idx(idx) {}
entry operator*() const;
iterator & operator++() {
idx++;
return *this;
}
bool operator!=(const iterator & other) const { return idx != other.idx; }
private:
common_json * node;
size_t idx;
};
iterator begin() const { return iterator(node, 0); }
iterator end() const { return iterator(node, n); }
private:
common_json * node;
size_t n;
};
items_view items() const;
private:
// a negative index must not turn into a huge size_t
static size_t to_idx(int idx) {
if (idx < 0) {
throw common_json_error("negative array index");
}
return (size_t) idx;
}
// the backing value is built here, json.cpp checks that it fits
// it cannot be a pointer: a value inside a tree would then not be a common_json
// at() could then only give back a copy instead of a real reference
alignas(8) unsigned char storage[32];
};
using common_json_entry = common_json::items_view::entry;
+3 -41
View File
@@ -1,6 +1,5 @@
#include "common.h"
#include "log.h"
#include "json.h"
#include <chrono>
#include <condition_variable>
@@ -67,17 +66,6 @@ static const char* g_col[] = {
"",
};
static const char * level_str(enum ggml_log_level level) {
switch (level) {
case GGML_LOG_LEVEL_DEBUG: return "debug";
case GGML_LOG_LEVEL_INFO: return "info";
case GGML_LOG_LEVEL_WARN: return "warn";
case GGML_LOG_LEVEL_ERROR: return "error";
case GGML_LOG_LEVEL_CONT: return "cont";
default: return "none";
}
}
struct common_log_entry {
enum ggml_log_level level {GGML_LOG_LEVEL_INFO};
@@ -86,7 +74,6 @@ struct common_log_entry {
int64_t timestamp { 0 };
bool is_end { false }; // signals the worker thread to stop
bool prefix { false };
bool jsonl { false };
common_log_entry(size_t size = 256) : msg(size) { }
@@ -101,23 +88,11 @@ struct common_log_entry {
fcur = stdout;
if (level != GGML_LOG_LEVEL_NONE && !jsonl) {
if (level != GGML_LOG_LEVEL_NONE) {
fcur = stderr;
}
}
if (jsonl) {
common_json obj = {
{"type", "log"},
{"time", timestamp},
{"level", level_str(level)},
{"msg", msg.data()},
};
fprintf(fcur, "%s\n", obj.dump_safe().c_str());
fflush(fcur);
return;
}
if (level != GGML_LOG_LEVEL_NONE && level != GGML_LOG_LEVEL_CONT && prefix) {
if (timestamp) {
// [M.s.ms.us]
@@ -156,7 +131,6 @@ struct common_log {
file = nullptr;
prefix = false;
timestamps = false;
jsonl = false;
running = false;
t_start = t_us();
@@ -184,7 +158,6 @@ private:
bool prefix;
bool timestamps;
bool jsonl;
bool running;
int64_t t_start;
@@ -273,7 +246,6 @@ public:
entry.is_end = false;
entry.level = level;
entry.prefix = prefix;
entry.jsonl = jsonl;
entry.timestamp = 0;
if (timestamps) {
entry.timestamp = t_us() - t_start;
@@ -388,12 +360,6 @@ public:
this->timestamps = timestamps;
}
void set_jsonl(bool jsonl) {
std::lock_guard<std::mutex> lock(mtx);
this->jsonl = jsonl;
}
};
//
@@ -467,16 +433,12 @@ void common_log_set_timestamps(struct common_log * log, bool timestamps) {
log->set_timestamps(timestamps);
}
void common_log_set_jsonl(struct common_log * log, bool jsonl) {
log->set_jsonl(jsonl);
}
void common_log_flush(struct common_log * log) {
log->pause();
log->resume();
}
int common_log_get_verbosity(enum ggml_log_level level) {
static int common_get_verbosity(enum ggml_log_level level) {
switch (level) {
case GGML_LOG_LEVEL_DEBUG: return LOG_LEVEL_DEBUG;
case GGML_LOG_LEVEL_INFO: return LOG_LEVEL_TRACE;
@@ -490,7 +452,7 @@ int common_log_get_verbosity(enum ggml_log_level level) {
}
void common_log_default_callback(enum ggml_log_level level, const char * text, void * /*user_data*/) {
auto verbosity = common_log_get_verbosity(level);
auto verbosity = common_get_verbosity(level);
if (verbosity <= common_log_verbosity_thold) {
common_log_add(common_log_main(), level, "%s", text);
}
-3
View File
@@ -43,8 +43,6 @@ int common_log_get_verbosity_thold(void);
void common_log_set_verbosity_thold(int verbosity); // not thread-safe
int common_log_get_verbosity(enum ggml_log_level level);
void common_log_default_callback(enum ggml_log_level level, const char * text, void * user_data);
// the common_log uses an internal worker thread to print/write log messages
@@ -91,7 +89,6 @@ void common_log_set_file (struct common_log * log, const char * file); // n
void common_log_set_colors (struct common_log * log, log_colors colors); // not thread-safe
void common_log_set_prefix (struct common_log * log, bool prefix); // whether to output prefix to each log
void common_log_set_timestamps(struct common_log * log, bool timestamps); // whether to output timestamps in the prefix
void common_log_set_jsonl (struct common_log * log, bool jsonl); // print each log as a JSON object on one line, not thread-safe
void common_log_flush (struct common_log * log); // flush all pending log messages
// helper macros for logging
-150
View File
@@ -1,150 +0,0 @@
#include "parsers.h"
// Cohere2 MoE (a.k.a. "North Code") parser.
//
// The assistant turn is fully marker-wrapped:
// <|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>
// <|START_THINKING|>{reasoning}<|END_THINKING|>
// then EITHER content: <|START_TEXT|>{content}<|END_TEXT|>
// OR tool calls: <|START_ACTION|>[
// {"tool_call_id": "0", "tool_name": "f", "parameters": {...}}, ...
// ]<|END_ACTION|>
// <|END_OF_TURN_TOKEN|>
//
// The generation prompt forces a leading <|START_THINKING|> (when reasoning is enabled, which is
// the template default), so the model's output continues from *inside* the thinking block. The
// parser literal therefore only covers the stable <|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|> prefix
// and the reasoning rule consumes the <|START_THINKING|> ... <|END_THINKING|> markers itself,
// regardless of whether they came from the generation prompt or the generated text.
common_chat_params common_chat_params_init_cohere2moe(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
const std::string TURN_START = "<|START_OF_TURN_TOKEN|>";
const std::string TURN_END = "<|END_OF_TURN_TOKEN|>";
const std::string CHATBOT = "<|CHATBOT_TOKEN|>";
const std::string USER = "<|USER_TOKEN|>";
const std::string SYSTEM = "<|SYSTEM_TOKEN|>";
const std::string THINK_START = "<|START_THINKING|>";
const std::string THINK_END = "<|END_THINKING|>";
const std::string TEXT_START = "<|START_TEXT|>";
const std::string TEXT_END = "<|END_TEXT|>";
const std::string ACTION_START = "<|START_ACTION|>";
const std::string ACTION_END = "<|END_ACTION|>";
const std::string RESULT_START = "<|START_TOOL_RESULT|>";
const std::string RESULT_END = "<|END_TOOL_RESULT|>";
// Stable prefix of the generation prompt that precedes the (forced) <|START_THINKING|> marker.
const std::string GEN_PREFIX = TURN_START + CHATBOT;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.thinking_start_tag = THINK_START;
data.thinking_end_tags = {THINK_END};
data.preserved_tokens = {
TURN_START, TURN_END, CHATBOT, USER, SYSTEM,
THINK_START, THINK_END,
TEXT_START, TEXT_END,
ACTION_START, ACTION_END,
RESULT_START, RESULT_END,
};
// Declare per-role message delimiters. Tool results are rendered with the
// system token followed by <|START_TOOL_RESULT|>, so the "tool" delimiter must be listed before
// the plain "system" one (it is a strict superset, and the role split tries delimiters in order).
data.message_delimiters = {
{ COMMON_CHAT_ROLE_ASSISTANT, GEN_PREFIX },
{ COMMON_CHAT_ROLE_USER, TURN_START + USER },
{ COMMON_CHAT_ROLE_TOOL, TURN_START + SYSTEM + RESULT_START },
{ COMMON_CHAT_ROLE_SYSTEM, TURN_START + SYSTEM },
};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = inputs.json_schema.is_object() && !inputs.json_schema.empty();
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PREFIX + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + TEXT_START + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.literal(GEN_PREFIX);
auto end = p.end();
// The thinking block is always present (the generation prompt forces <|START_THINKING|>).
// When extracting reasoning, capture its body; otherwise keep the whole block (markers
// included) inline as content, matching reasoning_format=NONE conventions.
common_peg_parser reasoning = p.eps();
if (extract_reasoning) {
reasoning = p.optional(p.literal(THINK_START) +
p.reasoning(p.until_one_of({ THINK_END, TEXT_START, ACTION_START })) +
p.optional(p.literal(THINK_END)));
} else {
reasoning = p.optional(p.content(p.literal(THINK_START) +
p.until_one_of({ THINK_END, TEXT_START, ACTION_START }) +
p.optional(p.literal(THINK_END))));
}
auto text_content = has_response_format
? p.literal(TEXT_START) +
p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema)) +
p.optional(p.literal(TEXT_END))
: p.literal(TEXT_START) + p.content(p.until(TEXT_END)) + p.optional(p.literal(TEXT_END));
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
return generation_prompt + reasoning + text_content + p.optional(p.literal(TURN_END)) + end;
}
auto require_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
// <|START_ACTION|>[ {"tool_call_id": "0", "tool_name": "f", "parameters": {...}}, ... ]<|END_ACTION|>
auto tool_calls = p.standard_json_tools(ACTION_START, ACTION_END, inputs.tools, inputs.parallel_tool_calls,
/* force_tool_calls = */ true,
/* name_key = */ "tool_name",
/* args_key = */ "parameters",
/* array_wrapped = */ true,
/* function_is_key = */ false,
/* call_id_key = */ "",
/* gen_call_id_key = */ "tool_call_id",
/* parameters_order = */ { "tool_call_id", "tool_name", "parameters" });
// Content and tool calls are mutually exclusive in this format.
common_peg_parser body = require_tools ? tool_calls : p.choice({ tool_calls, text_content });
return generation_prompt + reasoning + body + p.optional(p.literal(TURN_END)) + end;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = !has_response_format && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.at("parameters");
builder.resolve_refs(schema);
});
if (has_response_format) {
auto schema = inputs.json_schema;
builder.resolve_refs(schema);
}
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, ACTION_START }
};
}
return data;
}
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#include "parsers.h"
// The DeepSeek V4 reference implementation renders consecutive tool results into a single
// user block, ordered by the tool call order of the preceding assistant message (matched
// by tool call id) rather than by the order they appear in the conversation.
static json deepseek_v4_sort_tool_results(const json & messages) {
json adjusted = messages;
std::map<std::string, size_t> call_order;
for (size_t i = 0; i < adjusted.size();) {
const auto & msg = adjusted[i];
const auto role = msg.value("role", "");
if (role == "assistant" && msg.contains("tool_calls") &&
msg.at("tool_calls").is_array() && !msg.at("tool_calls").empty()) {
call_order.clear();
const auto & tool_calls = msg.at("tool_calls");
for (size_t idx = 0; idx < tool_calls.size(); idx++) {
auto id = tool_calls[idx].value("id", "");
if (!id.empty()) {
call_order[id] = idx;
}
}
i++;
continue;
}
if (role != "user" && role != "tool") {
i++;
continue;
}
// collect a maximal run of user/tool messages - they render into one user block
std::vector<size_t> tool_positions;
size_t run_end = i;
for (; run_end < adjusted.size(); run_end++) {
const auto r = adjusted[run_end].value("role", "");
if (r == "tool") {
tool_positions.push_back(run_end);
} else if (r != "user") {
break;
}
}
if (tool_positions.size() > 1 && !call_order.empty()) {
std::vector<json> results;
results.reserve(tool_positions.size());
for (auto pos : tool_positions) {
results.push_back(adjusted[pos]);
}
std::stable_sort(results.begin(), results.end(), [&](const json & a, const json & b) {
const auto order = [&](const json & m) {
auto it = call_order.find(m.value("tool_call_id", ""));
return it == call_order.end() ? (size_t) 0 : it->second;
};
return order(a) < order(b);
});
for (size_t k = 0; k < tool_positions.size(); k++) {
adjusted[tool_positions[k]] = std::move(results[k]);
}
}
i = run_end;
}
return adjusted;
}
common_chat_params common_chat_params_init_deepseek_v3_2(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
// V4 uses the same DSML markup as V3.2, but names the tool call block "tool_calls"
// instead of "function_calls", renders tool results in tool call order and its
// non-thinking generation prompt ends with a bare </think> instead of an empty
// <think></think> pair.
const bool is_v4 = tmpl.source().find("function_calls") == std::string::npos;
std::optional<json> adjusted_messages;
if (is_v4) {
adjusted_messages = deepseek_v4_sort_tool_results(inputs.messages);
}
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = !inputs.json_schema.is_null() && inputs.json_schema.is_object();
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
std::optional<json> additional_context;
if (is_v4 && has_response_format) {
additional_context = json{ { "response_format", inputs.json_schema } };
}
const std::string DSML = "DSML";
const std::string THINK_START = "<think>";
const std::string THINK_END = "</think>";
const std::string TC_BLOCK = is_v4 ? "tool_calls" : "function_calls";
const std::string FC_START = "<" + DSML + TC_BLOCK + ">";
const std::string FC_END = "</" + DSML + TC_BLOCK + ">";
const std::string INVOKE_START = "<" + DSML + "invoke";
const std::string INVOKE_END = "</" + DSML + "invoke>";
const std::string PARAM_START = "<" + DSML + "parameter";
const std::string PARAM_END = "</" + DSML + "parameter>";
const std::string GEN_PROMPT = "<Assistant>";
const std::string TC_SEPARATOR = "\n\n";
data.prompt = common_chat_template_direct_apply_impl(
tmpl, inputs, adjusted_messages, std::nullopt, additional_context);
data.generation_prompt = common_chat_template_generation_prompt_impl(
tmpl, inputs, adjusted_messages, std::nullopt, additional_context);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.thinking_start_tag = THINK_START;
data.thinking_end_tags = {THINK_END, FC_START};
data.preserved_tokens = {
DSML,
THINK_START,
THINK_END,
};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
if (is_v4 && msg.reasoning_content.empty()) {
data.generation_prompt = GEN_PROMPT + THINK_END;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += msg.render_content();
}
} else {
data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + msg.render_content();
}
}
data.prompt += data.generation_prompt;
}
bool require_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
bool has_tool_calls = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.literal(GEN_PROMPT);
auto end = p.end();
// build tool call section first since we might need it in reasoning
auto tool_choice = p.choice();
if (has_tool_calls) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
auto params = function.contains("parameters") ? function.at("parameters") : json::object();
const auto & props = params.contains("properties") ? params.at("properties") : json::object();
std::set<std::string> required;
if (params.contains("required")) {
required = params.at("required").get<std::set<std::string>>();
}
auto schema_info = common_schema_info();
schema_info.resolve_refs(params);
std::vector<common_peg_parser> required_parsers;
std::vector<common_peg_parser> optional_parsers;
for (const auto & [param_name, param_schema] : props.items()) {
bool is_required = required.find(param_name) != required.end();
bool is_string = schema_info.resolves_to_string(param_schema);
auto arg = p.tool_arg(
p.tool_arg_open(p.literal(PARAM_START + " name=\"") + p.tool_arg_name(p.literal(param_name)) +
p.literal("\" string=\"" + std::string(is_string ? "true" : "false") + "\">")) +
(is_string ?
p.tool_arg_string_value(p.until(PARAM_END)) :
p.tool_arg_json_value(p.schema(p.json(), "tool-" + name + "-arg-" + param_name + "-schema",
param_schema, false))) +
p.tool_arg_close(p.literal(PARAM_END)));
auto named_arg = p.rule("tool-" + name + "-arg-" + param_name, arg);
if (is_required) {
required_parsers.push_back(named_arg);
} else {
optional_parsers.push_back(named_arg);
}
}
common_peg_parser args_seq = p.eps();
for (size_t i = 0; i < required_parsers.size(); i++) {
if (i > 0) {
args_seq = args_seq + p.space();
}
args_seq = args_seq + required_parsers[i];
}
if (!optional_parsers.empty()) {
common_peg_parser any_opt = p.choice();
for (const auto & opt : optional_parsers) {
any_opt |= opt;
}
args_seq = args_seq + p.repeat(p.space() + any_opt, 0, -1);
}
common_peg_parser invoke_body = args_seq;
auto func_parser = p.tool(p.tool_open(p.literal(INVOKE_START + " name=\"") +
p.tool_name(p.literal(name)) + p.literal("\">\n")) +
invoke_body + p.space() + p.tool_close(p.literal(INVOKE_END)));
tool_choice |= p.rule("tool-" + name, func_parser);
});
}
common_peg_parser tool_calls = p.eps();
if (inputs.parallel_tool_calls) {
tool_calls = p.trigger_rule("tool-call",
p.literal(FC_START) + p.space() + tool_choice +
p.zero_or_more(p.space() + tool_choice) + p.space() + p.literal(FC_END));
} else {
tool_calls = p.trigger_rule("tool-call",
p.literal(FC_START) + p.space() + tool_choice + p.space() + p.literal(FC_END));
}
auto reasoning = p.eps();
auto reasoning_with_tc = p.eps();
auto obligatory_tool_calls = tool_calls;
bool allow_reasoning_with_tc = false;
if (!require_tools) {
tool_calls = p.optional(tool_calls);
}
if (extract_reasoning && inputs.enable_thinking) {
reasoning = p.optional(THINK_START + p.reasoning(p.until(THINK_END)) + THINK_END);
reasoning_with_tc = THINK_START +
p.reasoning(p.until_one_of({ TC_SEPARATOR + FC_START, FC_START, THINK_END })) +
p.space() + obligatory_tool_calls;
allow_reasoning_with_tc = true;
} else if (extract_reasoning) {
// Thinking disabled but reasoning extraction requested: the generation prompt
// contains an empty <think></think> pair (V3.2) or a bare </think> (V4) that
// must still be consumed.
reasoning = is_v4
? p.optional(p.literal(THINK_END))
: p.optional(p.literal(THINK_START) + p.until(THINK_END) + p.literal(THINK_END));
}
if (has_response_format) {
auto response_format = p.rule("response-format",
p.literal("```json") + p.space() +
p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema)) +
p.space() + p.literal("```"));
return generation_prompt + reasoning + response_format + end;
}
if (!has_tool_calls) {
return generation_prompt + reasoning + p.content(p.rest()) + end;
}
auto content_before_tools = p.negate(p.literal(THINK_START)) +
p.content(p.until_one_of({ TC_SEPARATOR + FC_START, FC_START })) +
p.space();
return allow_reasoning_with_tc ? generation_prompt + (reasoning_with_tc | (reasoning + content_before_tools + tool_calls)) + end :
generation_prompt + reasoning + content_before_tools + tool_calls + end;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = has_tools && !require_tools;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.contains("parameters") ? function.at("parameters") : json::object();
builder.resolve_refs(schema);
});
if (has_response_format) {
auto schema = inputs.json_schema;
builder.resolve_refs(schema);
}
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, FC_START },
};
}
return data;
}
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#include "parsers.h"
// Functionary v3.2 - uses recipient-based format: >>>recipient\n{content}
common_chat_params common_chat_params_init_functionary_v3_2(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.preserved_tokens = {
">>>all",
};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto include_grammar = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "<|start_header_id|>assistant<|end_header_id|>\n\n>>>all\n" + msg.render_content();
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
// Functionary v3.2 format:
// - Normal content: >>>all\n{content}
// - Tool calls: >>>function_name\n{json_args}
// Generation prompt ends with ">>>" so model outputs recipient immediately
// Build content parser for >>>all\n{content}
// When tools are present, content stops before the next ">>>" (tool call)
// When no tools, content goes until end
auto content_until_tool = p.literal("all\n") + p.content(p.until(">>>"));
auto content_until_end = p.literal("all\n") + p.content(p.rest());
auto generation_prompt = p.literal("<|start_header_id|>assistant<|end_header_id|>\n\n>>>");
// If no tools or tool_choice is NONE, just parse content
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
// When no tools, just match the prefix and capture everything after
return generation_prompt + content_until_end + p.end();
}
// Build tool call parsers for each available function
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
const auto & schema = function.at("parameters");
// Tool format: >>>function_name\n{json_args}
auto tool_parser = p.tool(
p.tool_open(p.tool_name(p.literal(name)) + p.literal("\n")) +
p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema))
);
tool_choice |= p.rule("tool-" + name, tool_parser);
});
auto content_only = content_until_end;
auto tools_only = p.trigger_rule("tools", p.one_or_more(tool_choice));
auto content_and_tools = content_until_tool + tools_only;
auto ret = p.eps();
if (inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED) {
if (inputs.parallel_tool_calls) {
ret = p.choice({ content_and_tools, tools_only }) + p.end();
} else {
ret = p.choice({ content_until_tool + tool_choice, tools_only }) + p.end();
}
} else if (inputs.parallel_tool_calls) {
ret = p.choice({ content_and_tools, content_only, tools_only }) + p.end();
} else {
auto content_and_tool = content_until_tool + tool_choice;
ret = p.choice({ content_and_tool, content_only, tool_choice }) + p.end();
}
return generation_prompt + ret;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.at("parameters");
builder.resolve_refs(schema);
});
parser.build_grammar(builder, data.grammar_lazy);
});
// Grammar trigger for when the model starts outputting a tool call
// (after the initial ">>>" in the generation prompt but recipient other than "all")
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN, ">>>(?!all)" }
};
}
return data;
}
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#include "parsers.h"
namespace workaround {
// Gemma4 uses a custom tool_responses field instead of role:tool messages.
//
// This will transform a sequence of messages:
// assistant(tool_call+) -> tool+ -> assistant(content)
//
// Into a single assistant message containing a tool_responses field:
// assistant(content + tool_call + tool_responses)
//
// This is necessary for the Gemma4 chat template to properly format the prompt.
// See https://ai.google.dev/gemma/docs/core/prompt-formatting-gemma4
struct gemma4_model_turn_builder {
json & messages;
size_t pos;
json tool_calls = json::array();
json tool_responses = json::array();
json content;
json reasoning_content;
gemma4_model_turn_builder(json & msgs, size_t pos) : messages(msgs), pos(pos) {}
void collect() {
// Collect the first assistant message
auto & msg = messages[pos];
if (msg.contains("reasoning_content") && msg.at("reasoning_content").is_string()) {
// According to the prompt formatting guide, we need to preserve reasoning_content
// between function calls. The current chat templates do not support this, but we will do it anyway.
reasoning_content = msg.at("reasoning_content");
}
for (auto & tc : msg.at("tool_calls")) {
tool_calls.push_back(tc);
}
pos++;
// Collect tool call results
while (pos < messages.size() && messages[pos].value("role", "") == "tool") {
collect_result(messages[pos]);
pos++;
}
// Check if the next assistant message is the final message
if (pos < messages.size() && messages[pos].value("role", "") == "assistant") {
auto & next = messages[pos];
if (!has_tool_calls(next) && has_content(next)) {
content = next.at("content");
pos++;
}
}
}
void collect_result(const json & curr) {
json response;
if (curr.contains("content")) {
const auto & content = curr.at("content");
if (content.is_string()) {
// Try to parse the content as JSON; fall back to raw string
try {
response = json::parse(content.get<std::string>());
} catch (...) {
response = content;
}
} else {
response = content;
}
}
std::string name;
// Match name with corresponding tool call
size_t idx = tool_responses.size();
if (idx < tool_calls.size()) {
auto & tc = tool_calls[idx];
if (tc.contains("function")) {
name = tc.at("function").value("name", "");
}
}
// Fallback to the tool call id
if (name.empty()) {
name = curr.value("tool_call_id", "");
}
tool_responses.push_back({{"name", name}, {"response", response}});
}
json build() {
collect();
json msg = {
{"role", "assistant"},
{"tool_calls", tool_calls},
};
if (!tool_responses.empty()) {
msg["tool_responses"] = tool_responses;
}
if (!content.is_null()) {
msg["content"] = content;
}
if (!reasoning_content.is_null()) {
msg["reasoning_content"] = reasoning_content;
}
return msg;
}
static bool has_content(const json & msg) {
if (!msg.contains("content") || msg.at("content").is_null()) {
return false;
}
const auto & content = msg.at("content");
if (content.is_string() && !content.get<std::string>().empty()) {
return true;
}
if (content.is_array() && !content.empty()) {
return true;
}
return false;
}
static bool has_tool_calls(const json & msg) {
return msg.contains("tool_calls") && msg.at("tool_calls").is_array() && !msg.at("tool_calls").empty();
}
};
void convert_tool_responses_gemma4(json & messages) {
json result = json::array();
size_t i = 0;
while (i < messages.size()) {
auto & msg = messages[i];
if (msg.value("role", "") != "assistant" || !msg.contains("tool_calls") ||
!msg.at("tool_calls").is_array() || msg.at("tool_calls").empty()) {
result.push_back(msg);
i++;
continue;
}
gemma4_model_turn_builder builder(messages, i);
result.push_back(builder.build());
i = builder.pos;
}
messages = result;
}
}
common_chat_params common_chat_params_init_gemma4(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
if (inputs.add_generation_prompt && string_ends_with(data.prompt, "<turn|>\n")) {
// This may happen if the model generates content + tool_call, the
// template does not add the model's next turn and confuses the model
// from emitting its proper reasoning token sequence.
data.generation_prompt = "<|turn>model\n";
data.prompt += data.generation_prompt;
}
data.message_delimiters = {
{ COMMON_CHAT_ROLE_USER, "<|turn>user" },
{ COMMON_CHAT_ROLE_ASSISTANT, "<|turn>model" },
};
data.format = COMMON_CHAT_FORMAT_PEG_GEMMA4;
data.supports_thinking = true;
data.thinking_start_tag = "<|channel>thought";
data.thinking_end_tags = {"<channel|>"};
data.preserved_tokens = {
"<|channel>",
"<channel|>",
"<|tool_call>",
"<tool_call|>",
"<|turn>",
};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = string_ends_with(data.prompt, "<turn|>\n") ? "<|turn>model\n" : "";
data.generation_prompt += "<|channel>thought\n" + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += "<channel|>" + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = !inputs.json_schema.is_null() && inputs.json_schema.is_object();
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto start = p.rule("start", p.optional(p.literal("<|turn>model\n")));
if (extract_reasoning) {
p.rule("thought", p.literal("<|channel>thought") + p.space() + p.reasoning(p.until("<channel|>")) + p.literal("<channel|>"));
} else {
p.rule("thought", p.content(p.literal("<|channel>thought") + p.space() + p.until("<channel|>") + p.literal("<channel|>")));
}
auto consume_empty_channels = p.gbnf(p.zero_or_more(p.literal("<|channel>") + p.negate(p.literal("thought"))), "");
auto thought = (p.peek(p.literal("<|channel>")) + consume_empty_channels + p.ref("thought")) | p.negate(p.literal("<|channel>"));
if (has_response_format) {
auto response_format = p.literal("```json") <<
p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema)) <<
p.literal("```");
return start + p.optional(thought) + response_format;
}
if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) {
// Gemma4 tool calling syntax
// Rules should match traversal logic in gemma4_to_json()
p.rule("gemma4-string-content", p.until("<|\"|>"));
p.rule("gemma4-string", p.literal("<|\"|>") + p.ref("gemma4-string-content") + p.literal("<|\"|>"));
p.rule("gemma4-bool", p.json_bool());
p.rule("gemma4-null", p.json_null());
p.rule("gemma4-number", p.json_number());
p.rule("gemma4-dict-key", p.rule("gemma4-dict-key-name", p.chars("[^:}]", 1, -1)) + p.literal(":"));
p.rule("gemma4-dict-kv", p.ref("gemma4-dict-key") + p.space() + p.ref("gemma4-value"));
p.rule("gemma4-dict", [&]() {
auto ws = p.space();
auto member = p.ref("gemma4-dict-kv");
auto members = p.sequence({member, p.zero_or_more(p.sequence({p.literal(","), ws, member}))});
return p.sequence({
p.literal("{"), ws,
p.choice({p.literal("}"), p.sequence({members, ws, p.literal("}")})})
});
});
p.rule("gemma4-array", [&]() {
auto ws = p.space();
auto value = p.ref("gemma4-value");
auto elements = p.sequence({value, p.zero_or_more(p.sequence({p.literal(","), ws, value}))});
return p.sequence({
p.literal("["), ws,
p.choice({p.literal("]"), p.sequence({elements, ws, p.literal("]")})})
});
});
p.rule("gemma4-value", [&]() {
return p.choice({
p.ref("gemma4-string"), p.ref("gemma4-dict"), p.ref("gemma4-array"),
p.ref("gemma4-number"), p.ref("gemma4-bool"), p.ref("gemma4-null")
});
});
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
// TODO @aldehir : need to extend json-schema-to-grammar to produce more than JSON rules
// const auto & params = function.at("parameters");
tool_choice |= p.rule("tool-" + name, p.tool(p.sequence({
p.tool_open(p.tool_name(p.literal(name)) + p.peek(p.literal("{"))),
p.tool_args(p.ref("gemma4-dict")),
})));
});
auto tool_call = p.trigger_rule("tool-call", p.repeat(
"<|tool_call>call:" + tool_choice + "<tool_call|>",
/* min = */ inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? 1 : 0,
/* max = */ inputs.parallel_tool_calls ? -1 : 1
));
auto scan_to_toolcall = p.rule("scan-to-toolcall", p.until("<|tool_call>"));
auto content = p.rule("content", p.content(p.until_one_of({"<|channel>", "<channel|>", "<|tool_call>"})));
auto message = p.rule("message", thought + content);
return start + p.zero_or_more(message) + scan_to_toolcall + tool_call;
}
// Gemma 4 may emit an extra <|channel>thought\n<channel|> at the end of the content. It may
// also emit a single trailing <channel|> token. Consume all complete reasoning blocks and
// then stop at the first unmatched <channel|> token.
auto content = p.rule("content", p.content(p.until_one_of({"<|channel>", "<channel|>"})));
auto message = p.rule("message", thought + content);
return start + p.one_or_more(message);
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = !(has_response_format || (has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED));
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.at("parameters");
builder.resolve_refs(schema);
});
if (has_response_format) {
auto schema = inputs.json_schema;
builder.resolve_refs(schema);
}
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "<|tool_call>" },
};
}
return data;
}
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#include "parsers.h"
common_chat_params common_chat_params_init_gigachat_v3(
const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = false;
data.preserved_tokens = {
"<|message_sep|>\n\n",
"<|role_sep|>\n",
};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "assistant<|role_sep|>\n" + msg.render_content();
data.prompt += data.generation_prompt;
}
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto include_grammar = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
const auto *tool_call_start_prefix = "<|message_sep|>\n\nfunction call<|role_sep|>\n";
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto ret = p.eps();
if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) {
// Build a choice of all available tools
auto tool_choice = p.choice();
for (const auto & tool : inputs.tools) {
const auto & function = tool.at("function");
std::string name = function.at("name");
const auto & schema = function.at("parameters");
auto tool_name = p.json_member("name", "\"" + p.tool_name(p.literal(name)) + "\"");
auto tool_args = p.json_member("arguments", p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema)));
auto tool_open = p.tool_open(p.literal("{") << tool_name);
tool_choice |= p.rule("tool-" + name, tool_open << "," << tool_args << "}");
}
// Define the tool call structure
auto min_calls = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? 1 : 0;
auto max_calls = 1; // parallel toolcalls are not supported
auto tool_call = p.rule("tool-call", p.literal(tool_call_start_prefix) + tool_choice);
auto tool_calls = p.trigger_rule("tool-call-root", p.repeat(tool_call, /* min = */ min_calls, /* max = */ max_calls));
ret = p.content(p.until("<|message_sep|>\n\n")) << tool_calls;
} else {
// Content only parser
include_grammar = false;
ret = p.content(p.rest());
}
return p.literal("assistant<|role_sep|>\n") + ret;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.at("parameters");
builder.resolve_refs(schema);
});
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{COMMON_GRAMMAR_TRIGGER_TYPE_WORD, tool_call_start_prefix}
};
}
return data;
}
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#include "parsers.h"
common_chat_params common_chat_params_init_gpt_oss(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
// Copy reasoning to the "thinking" field as expected by the gpt-oss template
auto adjusted_messages = json::array();
for (auto msg : inputs.messages) {
if (msg.contains("reasoning_content") && msg.at("reasoning_content").is_string()) {
msg["thinking"] = msg.at("reasoning_content");
if (msg.contains("tool_calls") && msg.at("tool_calls").is_array() && !msg.at("tool_calls").empty()) {
msg.erase("content");
}
}
adjusted_messages.push_back(msg);
}
auto prompt = common_chat_template_direct_apply_impl(tmpl, inputs, /* messages_override= */ adjusted_messages);
// Check if we need to replace the return token with end token during
// inference and without generation prompt. For more details see:
// https://github.com/ggml-org/llama.cpp/issues/15417
if (inputs.is_inference && !inputs.add_generation_prompt) {
static constexpr std::string_view return_token = "<|return|>";
static constexpr std::string_view end_token = "<|end|>";
if (size_t pos = prompt.rfind(return_token); pos != std::string::npos) {
prompt.replace(pos, return_token.length(), end_token);
}
}
data.prompt = prompt;
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs, /* messages_override= */ adjusted_messages);
data.message_delimiters = {
{ COMMON_CHAT_ROLE_ASSISTANT, "<|start|>assistant" },
{ COMMON_CHAT_ROLE_USER, "<|start|>user" },
{ COMMON_CHAT_ROLE_SYSTEM, "<|start|>developer" },
{ COMMON_CHAT_ROLE_SYSTEM, "<|start|>system" },
{ COMMON_CHAT_ROLE_TOOL, "<|start|>functions" },
};
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.thinking_start_tag = "<|channel|>analysis<|message|>";
data.thinking_end_tags = {"<|end|>"};
// These special tokens are required to parse properly, so we include them
// even if parse_tool_calls is false.
data.preserved_tokens = {
"<|channel|>", "<|constrain|>", "<|message|>", "<|start|>", "<|end|>",
};
// Adjust prompt for continuation
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "<|start|>assistant<|channel|>analysis<|message|>" + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += "<|end|><|start|>assistant<|channel|>final<|message|>" + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = !inputs.json_schema.is_null() && inputs.json_schema.is_object();
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto start = p.rule("start", p.literal("<|start|>assistant"));
auto end = p.rule("end", p.literal("<|end|>"));
auto content = p.rule("message-content", p.until("<|end|>"));
auto channel = p.literal("<|channel|>") + (p.literal("commentary") | p.literal("analysis"));
auto constrain_type = p.chars("[A-Za-z0-9_-]", 1, -1);
// Occasionally, gpt-oss-20b will prefix channels with this commentary
auto stray_commentary = p.optional(p.literal("<|channel|>commentary") + p.optional(p.literal(" to=assistant")));
auto start_analysis = stray_commentary + p.literal("<|channel|>analysis<|message|>");
if (extract_reasoning) {
p.rule("analysis", start_analysis + p.reasoning(content) + end);
} else {
p.rule("analysis", p.content(start_analysis + content + end));
}
auto analysis = p.ref("analysis");
auto preamble = p.rule("preamble", p.literal("<|channel|>commentary<|message|>") + p.content(content) + end);
auto final_msg = p.rule("final", stray_commentary + p.literal("<|channel|>final<|message|>") + p.content(content));
// Consume any unsolicited tool calls, e.g. builtin functions
auto unsolicited = p.rule("unsolicited", p.atomic(p.optional(channel) + p.literal(" to=") + content + end));
auto any = p.rule("any", preamble | analysis);
if (has_response_format) {
auto constraint = p.optional(p.space() + p.optional(p.literal("<|constrain|>")) + constrain_type);
auto response_format = p.rule("response-format",
p.literal("<|channel|>final") + constraint + p.literal("<|message|>") +
p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema)));
return p.zero_or_more(start + analysis) + start + response_format;
}
if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) {
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
const auto & params = function.at("parameters");
auto func_name = p.literal(" to=functions.") + p.tool_name(p.literal(name));
auto constraint = p.optional(p.space() + p.optional(p.literal("<|constrain|>")) + constrain_type);
auto args = p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", params));
// recipient in role header
// <|start|>assistant to=functions.NAME<|channel|>(commentary|analysis)[constraint]<|message|>ARGS
auto tool_in_role = p.tool(p.tool_open(func_name + channel + constraint + p.literal("<|message|>")) + args);
// recipient in channel header
// <|channel|>(commentary|analysis) to=functions.NAME[constraint]<|message|>ARGS
auto tool_in_channel = p.tool(p.tool_open(channel + func_name + constraint + p.literal("<|message|>")) + args);
tool_choice |= p.rule("tool-" + name, tool_in_role | tool_in_channel);
});
auto tool_call = p.trigger_rule("tool-call", tool_choice);
if (inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED) {
return p.zero_or_more(start + any) + start + tool_call;
}
return p.zero_or_more(start + any) + start + (tool_call | final_msg);
}
return p.zero_or_more(start + any) + start + (final_msg | unsolicited);
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = !(has_response_format || (has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED));
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.at("parameters");
builder.resolve_refs(schema);
});
if (has_response_format) {
auto schema = inputs.json_schema;
builder.resolve_refs(schema);
}
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN, "^\\s+to$" },
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN, "^<\\|channel\\|>(?:commentary|analysis)\\s+to=functions$" },
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN, "<\\|start\\|>assistant(\\s+to)" },
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN, "<\\|start\\|>assistant(<\\|channel\\|>(?:commentary|analysis)\\s+to)" }
};
}
return data;
}
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#include "parsers.h"
// Kimi K2 Thinking - uses unique tool call ID format: functions.<name>:<index>
// The ID contains both the function name and an incrementing counter
common_chat_params common_chat_params_init_kimi_k2(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.preserved_tokens = {
"<|tool_calls_section_begin|>",
"<|tool_calls_section_end|>",
"<|tool_call_begin|>",
"<|tool_call_argument_begin|>",
"<|tool_call_end|>",
"<think>",
"</think>",
};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto include_grammar = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
const std::string SECTION_BEGIN = "<|tool_calls_section_begin|>";
const std::string SECTION_END = "<|tool_calls_section_end|>";
const std::string CALL_BEGIN = "<|tool_call_begin|>";
const std::string ARGS_BEGIN = "<|tool_call_argument_begin|>";
const std::string CALL_END = "<|tool_call_end|>";
const std::string THINK_START = "<think>";
const std::string THINK_END = "</think>";
const std::string GEN_PROMPT = "<|im_assistant|>assistant<|im_middle|>";
data.thinking_start_tag = THINK_START;
data.thinking_end_tags = {THINK_END};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
// Kimi K2 Thinking format:
// - Reasoning: <think>{reasoning}</think>
// - Content: text after reasoning
// - Tool calls section:
// <|tool_calls_section_begin|>
// <|tool_call_begin|>functions.<name>:<index><|tool_call_argument_begin|>{json_args}<|tool_call_end|>
// ...
// <|tool_calls_section_end|>
// The ID format is: functions.<function_name>:<counter> where counter is 0, 1, 2, ...
// Tool call markers
auto end = p.end();
// Note: this model is CRAZY. It can diverge from its supposed tool calling pattern in so many ways it's not funny.
// For example, it can call tools at the end of reasoning without closing reasoning...
auto reasoning = extract_reasoning ? p.optional(THINK_START + p.reasoning(
p.until_one_of({ THINK_END, "<|tool_calls_section_begin|>", "<|tool_call_begin|>" })) +
p.optional(p.literal(THINK_END))) : p.eps();
auto generation_prompt = p.literal(GEN_PROMPT);
// Content only parser (no tools)
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
return generation_prompt + reasoning + p.content(p.rest()) + end;
}
// Build tool call parsers for each available function
// The ID format is: functions.<name>:<index>
// We need to match: functions.<name>:<digits>
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
const auto & schema = function.at("parameters");
// Match: functions.<name>:<digits>
// Capture the full call id (functions.<name>:<digits>) using tool_id tag
auto tool_id = p.tool_id(p.literal("functions.") + p.tool_name(p.literal(name)) + p.literal(":") + p.chars("[0-9]", 1, -1));
auto tool_parser = p.tool(
p.tool_open(tool_id + p.literal(ARGS_BEGIN)) +
p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema)) +
p.tool_close(p.optional((p.literal(CALL_END))))
);
tool_choice |= p.rule("tool-" + name, tool_parser);
});
// Tool calls section: <|tool_calls_section_begin|> tool_calls <|tool_calls_section_end|>
auto min_calls = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? 1 : 0;
auto max_calls = inputs.parallel_tool_calls ? -1 : 1;
// Use trigger_rule so grammar generator knows where to start generating rules
auto tool_calls = p.rule("tool-calls",
p.optional(p.literal(SECTION_BEGIN)) +
p.trigger_rule("tool-call", p.repeat(CALL_BEGIN + tool_choice, min_calls, max_calls) +
p.optional(p.literal(SECTION_END)))
);
auto content_before_tools = p.content(p.until_one_of({ SECTION_BEGIN, CALL_BEGIN }));
return generation_prompt + reasoning + content_before_tools + tool_calls + end;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.at("parameters");
builder.resolve_refs(schema);
});
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "<|tool_call_begin|>" }
};
}
return data;
}
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#include "parsers.h"
// Kimi K3 - XTML tagged format, built by open_tag/close_tag macros:
// open_tag(t, attrs) = <|open|>t k="v"...<|sep|> close_tag(t) = <|close|>t<|sep|>
// assistant := [think] [response] [tools] close_tag(message) <|end_of_msg|>
// the generation prompt already opens the think (or response) section, so the
// section opener is optional here - same as Kimi K2 Thinking
common_chat_params common_chat_params_init_kimi_k3(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
const std::string SEP = "<|sep|>";
const std::string MSG_START = "<|open|>message role=\"assistant\"<|sep|>";
const std::string THINK_START = "<|open|>think<|sep|>";
const std::string THINK_END = "<|close|>think<|sep|>";
const std::string RESP_START = "<|open|>response<|sep|>";
const std::string RESP_END = "<|close|>response<|sep|>";
const std::string TOOLS_START = "<|open|>tools<|sep|>";
const std::string TOOLS_END = "<|close|>tools<|sep|>";
const std::string CALL_START = "<|open|>call tool=\"";
const std::string CALL_END = "<|close|>call<|sep|>";
const std::string ARG_START = "<|open|>argument key=\"";
const std::string ARG_END = "<|close|>argument<|sep|>";
const std::string MSG_END = "<|close|>message<|sep|>";
const std::string EOM_TOKEN = "<|end_of_msg|>";
// only the markers are special tokens. tag names ("think", "response", ...) are
// normal tokens and must not be preserved, or prose with those words is broken
data.preserved_tokens = {
"<|open|>",
"<|close|>",
"<|sep|>",
"<|end_of_msg|>",
};
data.thinking_start_tag = THINK_START;
data.thinking_end_tags = { THINK_END };
// per-role message-start delimiters. user/assistant messages only have the role
// attribute, so the full opener is used. system and tool messages have more
// attributes, so those delimiters stop after the closing quote of the role
data.message_delimiters = {
{ COMMON_CHAT_ROLE_ASSISTANT, "<|open|>message role=\"assistant\"<|sep|>" },
{ COMMON_CHAT_ROLE_USER, "<|open|>message role=\"user\"<|sep|>" },
{ COMMON_CHAT_ROLE_TOOL, "<|open|>message role=\"tool\"" },
{ COMMON_CHAT_ROLE_SYSTEM, "<|open|>message role=\"system\"" },
};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto include_grammar = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = MSG_START + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + RESP_START + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto end = p.end();
auto start = p.optional(p.literal(MSG_START));
// the think section is always consumed, even with reasoning extraction off:
// the generation prompt ends with open_tag('think'), so it is always present.
// reasoning stops at its own closer, or at the response opener if the model
// skips the closer
auto think_body = extract_reasoning ? p.reasoning(p.until_one_of({ THINK_END, RESP_START })) :
p.content(p.until_one_of({ THINK_END, RESP_START }));
auto reasoning = p.optional(p.optional(p.literal(THINK_START)) + think_body +
p.optional(p.literal(THINK_END)));
// content runs to the response closer, or to the next section if truncated
auto response = p.optional(p.literal(RESP_START)) +
p.content(p.until_one_of({ RESP_END, TOOLS_START, MSG_END })) +
p.optional(p.literal(RESP_END));
// the EOG token after the message closer reaches the parser as text,
// so it must be consumed or the parse stays incomplete
auto trailer = p.optional(p.literal(MSG_END)) + p.optional(p.literal(EOM_TOKEN));
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
return start + reasoning + response + trailer + end;
}
auto tool_choices = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
const json schema = function.contains("parameters") ? function.at("parameters") : json::object();
// arguments come one tag per key, with the JSON type in a type="..."
// attribute. the type is taken from the tool schema instead, as it tells
// us if the value is JSON or a literal string
auto args = p.eps();
if (schema.contains("properties") && !schema.at("properties").empty()) {
auto arg_choices = p.choice();
for (const auto & prop : schema.at("properties").items()) {
const std::string & key = prop.key();
std::string type = "string";
if (prop.value().is_object() && prop.value().contains("type") &&
prop.value().at("type").is_string()) {
type = prop.value().at("type").get<std::string>();
}
auto value = type == "string" ? p.tool_arg_string_value(p.until(ARG_END)) :
p.tool_arg_value(p.until(ARG_END));
// skip the trailing type="..." attribute: anything up to <|sep|>
arg_choices |= p.rule("kimi-k3-arg-" + name + "-" + key,
p.tool_arg(p.tool_arg_open(p.literal(ARG_START)) +
p.tool_arg_name(p.literal(key)) + p.literal("\"") +
p.until(SEP) + p.literal(SEP) + value +
p.tool_arg_close(p.literal(ARG_END))));
}
args = p.zero_or_more(arg_choices);
}
// skip the trailing index="N" attribute the same way
auto call = p.tool(p.tool_open(p.literal(CALL_START) + p.tool_name(p.literal(name)) + p.literal("\"") +
p.until(SEP) + p.literal(SEP)) +
p.tool_args(args) + p.tool_close(p.literal(CALL_END)));
tool_choices |= p.rule("kimi-k3-tool-" + name, call);
});
// all calls go inside one tools section, then the message is closed. the
// message closer is part of the trigger rule, or else the lazy grammar
// rejects it once tool calls have started
auto tools_section =
p.trigger_rule("kimi-k3-tool-call", p.literal(TOOLS_START) + p.one_or_more(tool_choices) +
p.literal(TOOLS_END) + p.optional(p.literal(MSG_END)) +
p.optional(p.literal(EOM_TOKEN)));
auto tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? tools_section :
p.optional(tools_section);
return start + reasoning + response + tools + trailer + end;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_REQUIRED;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
if (function.contains("parameters")) {
auto schema = function.at("parameters");
builder.resolve_refs(schema);
}
});
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, TOOLS_START },
};
}
return data;
}
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#include "parsers.h"
// LFM2 format detection: template uses <|tool_list_start|>[...]<|tool_list_end|> around the tool list
// and <|tool_call_start|>[...]<|tool_call_end|> around each tool call
bool is_lfm2_template(const std::string & src) {
return src.find("<|tool_list_start|>") != std::string::npos &&
src.find("<|tool_list_end|>") != std::string::npos;
}
// LFM2/LFM2.5 parser. Tool calls are almost Python-style and parallel-capable
// (except dotted names and JSON literals true/false/null).
// Always wrapped in <|tool_call_start|>[name(args)]<|tool_call_end|> with optional <think> reasoning.
// tool_list_tokens preserves LFM2 system tool-list markers.
common_chat_params common_chat_params_init_lfm2(const common_chat_template & tmpl,
const autoparser::generation_params & inputs,
bool tool_list_tokens) {
common_chat_params data;
const std::string TOOL_CALL_START = "<|tool_call_start|>";
const std::string TOOL_CALL_END = "<|tool_call_end|>";
const std::string TOOL_LIST_START = "<|tool_list_start|>";
const std::string TOOL_LIST_END = "<|tool_list_end|>";
const std::string THINK_START = "<think>";
const std::string THINK_END = "</think>";
const std::string GEN_PROMPT = "<|im_start|>assistant\n";
// Copy reasoning to the "thinking" field the template expects
auto adjusted_messages = json::array();
for (auto msg : inputs.messages) {
if (msg.contains("reasoning_content") && msg.at("reasoning_content").is_string()) {
msg["thinking"] = msg.at("reasoning_content");
}
adjusted_messages.push_back(msg);
}
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs, adjusted_messages);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs, adjusted_messages);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.preserved_tokens = { TOOL_CALL_START, TOOL_CALL_END, THINK_START, THINK_END };
if (tool_list_tokens) {
data.preserved_tokens.push_back(TOOL_LIST_START);
data.preserved_tokens.push_back(TOOL_LIST_END);
}
data.thinking_start_tag = THINK_START;
data.thinking_end_tags = {THINK_END};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = !inputs.json_schema.is_null() && inputs.json_schema.is_object();
// Gate by reasoning format and whether the template supports <think>
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE &&
tmpl.source().find(THINK_START) != std::string::npos;
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.literal(GEN_PROMPT);
auto end = p.end();
auto reasoning = p.eps();
if (extract_reasoning) {
reasoning = p.optional(THINK_START + p.reasoning(p.until(THINK_END)) + THINK_END);
}
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
if (has_response_format) {
auto response_format = p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema));
return generation_prompt + reasoning + response_format + end;
}
return generation_prompt + reasoning + p.content(p.rest()) + end;
}
auto tool_calls = p.rule("tool-calls",
p.trigger_rule("tool-call",
p.literal(TOOL_CALL_START) +
p.python_style_tool_calls(inputs.tools, inputs.parallel_tool_calls, /* allow_json_literals = */ true) +
p.literal(TOOL_CALL_END)
)
);
auto content = p.content(p.until(TOOL_CALL_START));
return generation_prompt + reasoning + content + tool_calls + end;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = !(has_response_format || (has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED));
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.at("parameters");
builder.resolve_refs(schema);
});
if (has_response_format) {
auto schema = inputs.json_schema;
builder.resolve_refs(schema);
}
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, TOOL_CALL_START }
};
}
return data;
}
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#include "parsers.h"
// MiniCPM5 format:
// - Reasoning: <think>{reasoning}</think> (optional)
// - Tool calls: <function name="foo"><param name="bar">value</param></function>
common_chat_params common_chat_params_init_minicpm5(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.preserved_tokens = {
"<function",
"<param",
"</function>",
"</param>",
"<think>",
"</think>",
};
data.thinking_start_tag = "<think>";
data.thinking_end_tags = {"</think>"};
data.message_delimiters = {
{ COMMON_CHAT_ROLE_ASSISTANT, "<|im_start|>assistant" },
{ COMMON_CHAT_ROLE_TOOL, "<|im_start|>user\n<tool_response>" },
{ COMMON_CHAT_ROLE_USER, "<|im_start|>user" },
{ COMMON_CHAT_ROLE_SYSTEM, "<|im_start|>system" },
};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = inputs.json_schema.is_object() && !inputs.json_schema.empty();
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "<|im_start|>assistant\n<think>\n" + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += "\n</think>\n\n" + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.literal("<|im_start|>assistant\n");
auto reasoning = p.eps();
if (extract_reasoning) {
reasoning = ("<think>" << p.reasoning(p.until("</think>")) << "</think>") + p.space();
}
// Response format parser
if (has_response_format) {
return generation_prompt + reasoning + p.content(p.schema(p.json(), "response-format", inputs.json_schema));
}
if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) {
// CDATA lets a value carry characters that would otherwise close the tag (e.g.
// </param>); capture the inner text only, excluding the CDATA markers.
auto string_value = p.choice({
p.literal("<![CDATA[") + p.ac(p.tool_arg_string_value(p.until("]]>")) + p.literal("]]>"), "]]>") + p.tool_arg_close(p.literal("</param>")),
p.negate(p.literal("<![CDATA[")) + p.ac(p.tool_arg_string_value(p.until("</param>")) + p.tool_arg_close(p.literal("</param>")), "</param>")
});
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
const std::string name = function.at("name");
auto params = function.contains("parameters") ? function.at("parameters") : json::object();
auto args = p.eps();
if (params.contains("properties") && params.at("properties").is_object() && !params.at("properties").empty()) {
auto schema_info = common_schema_info();
schema_info.resolve_refs(params);
auto arg_choice = p.choice();
for (const auto & [prop_name, prop_schema] : params.at("properties").items()) {
auto value_parser = p.eps();
if (schema_info.resolves_to_string(prop_schema)) {
value_parser = string_value;
} else {
value_parser = p.tool_arg_json_value(
p.schema(p.json(), "tool-" + name + "-arg-" + prop_name + "-schema", prop_schema, false)
) + p.tool_arg_close(p.literal("</param>"));
}
auto arg_rule = p.tool_arg(
p.tool_arg_open(p.literal("<param name=\"") + p.tool_arg_name(p.literal(prop_name)) + p.literal("\">")) +
value_parser
);
arg_choice |= arg_rule;
}
args = p.zero_or_more(arg_choice + p.space());
}
auto tool_parser = p.tool(
p.tool_open(p.literal("<function name=\"") + p.tool_name(p.literal(name)) + p.literal("\">"))
<< p.tool_args(args)
<< p.tool_close(p.literal("</function>")));
tool_choice |= p.rule("tool-" + name, tool_parser);
});
auto max_calls = inputs.parallel_tool_calls ? -1 : 1;
auto tool_calls = p.trigger_rule("tool-call", p.repeat(tool_choice + p.space(), 1, max_calls));
auto content = p.content(p.until("<function"));
return generation_prompt + reasoning + content + tool_calls + p.end();
}
return generation_prompt + reasoning + p.content(p.rest()) + p.end();
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = !(has_response_format || (has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED));
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.contains("parameters") ? function.at("parameters") : json::object();
builder.resolve_refs(schema);
});
if (has_response_format) {
auto schema = inputs.json_schema;
builder.resolve_refs(schema);
}
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "<function" },
};
}
return data;
}
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#include "parsers.h"
common_chat_params common_chat_params_init_minimax_m3(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_MINIMAX_M3;
data.supports_thinking = true;
data.thinking_start_tag = "<mm:think>";
data.thinking_end_tags = {"</mm:think>"};
// M3 prefixes every tool tag with the namespace token "]<]minimax[>[";
// params use the parameter name as the tag (<file_path>...</file_path>).
const std::string NS = "]<]minimax[>[";
const std::string THINK_START = "<mm:think>";
const std::string THINK_END = "</mm:think>";
const std::string FC_START = NS + "<tool_call>";
const std::string FC_END = NS + "</tool_call>";
const std::string INVOKE_END = NS + "</invoke>";
data.preserved_tokens = {
NS,
"<tool_call>",
"</tool_call>",
THINK_START,
THINK_END,
};
data.message_delimiters = {
{ COMMON_CHAT_ROLE_ASSISTANT, "]~b]ai" },
{ COMMON_CHAT_ROLE_USER, "]~b]user" },
{ COMMON_CHAT_ROLE_TOOL, "]~b]tool" },
{ COMMON_CHAT_ROLE_SYSTEM, "]~b]developer" },
{ COMMON_CHAT_ROLE_SYSTEM, "]~b]system" },
};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = !inputs.json_schema.is_null() && inputs.json_schema.is_object();
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
const std::string GEN_PROMPT = data.generation_prompt;
using mm3 = common_chat_peg_minimax_m3_mapper;
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PROMPT + THINK_START + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += THINK_END + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.prefix(GEN_PROMPT, THINK_START);
auto end = p.end();
auto reasoning = p.eps();
if (extract_reasoning) {
auto block = inputs.enable_thinking
? p.literal(THINK_START) + p.space() +
p.ac(p.reasoning(p.until(THINK_END)) + p.literal(THINK_END), THINK_END)
: p.literal(THINK_START) + p.ac(p.until(THINK_END) + p.literal(THINK_END), THINK_END);
// A turn without reasoning is prefixed with a bare </mm:think>, written either by the
// generation prompt (thinking_mode = "disabled") or by the model itself.
reasoning = p.optional(p.choice({ block, p.literal(THINK_END) }));
}
if (has_response_format) {
auto response_format = p.rule("response-format",
p.literal("```json") + p.space() +
p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema)) +
p.space() + p.literal("```"));
return generation_prompt + reasoning + response_format + end;
}
if (!has_tools || inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_NONE) {
return generation_prompt + reasoning + p.content(p.rest()) + end;
}
auto alternatives_of = [](const json & schema) -> std::optional<json> {
for (const auto * keyword : { "oneOf", "anyOf" }) {
if (schema.contains(keyword) && schema.at(keyword).is_array() && !schema.at(keyword).empty()) {
return schema.at(keyword);
}
}
return std::nullopt;
};
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
auto params = function.contains("parameters") ? function.at("parameters") : json::object();
auto schema_info = common_schema_info();
schema_info.resolve_refs(params);
// The template expands argument values recursively in XML (see the to_xml() macro)
std::function<common_peg_parser(const json &, const std::string &, const std::string &)> value_of;
std::function<common_peg_parser(const json &, const std::string &)> members_of;
auto element_of = [&](const std::string & tag, const json & schema, const std::string & rule_name) {
const std::string close = NS + "</" + tag + ">";
return p.rule(rule_name,
p.tool_arg(
p.tool_arg_open(
p.literal(NS + "<") +
p.tool_arg_name(p.literal(tag)) +
p.literal(">")) +
value_of(schema, rule_name, close)));
};
value_of = [&](const json & schema,
const std::string & rule_name,
const std::string & close) -> common_peg_parser {
auto close_tag = p.tool_arg_close(p.literal(close));
// A string accepts anything, so a union with a string alternative is a string
if (schema_info.resolves_to_string(schema)) {
return p.ac(p.tool_arg_string_value(p.until(close)) + close_tag, close);
}
if (auto alternatives = alternatives_of(schema)) {
std::vector<common_peg_parser> choices;
size_t index = 0;
for (const auto & alternative : *alternatives) {
const std::string alt_name = rule_name + "-" + std::to_string(index++);
// There is a risk that this breaks streaming deltas, but that's a risk we
// assume to provide tool arg streaming.
choices.push_back(value_of(alternative, alt_name, close));
}
return p.choice(choices);
}
const std::string type = schema.contains("type") && schema.at("type").is_string()
? schema.at("type").get<std::string>()
: "";
if (type == "object" && schema.contains("properties")) {
return p.tag(mm3::TOOL_ARG_OBJECT, members_of(schema, rule_name)) + p.space() + close_tag;
}
if (type == "array" && schema.contains("items")) {
const std::string item_close = NS + "</item>";
auto item = p.rule(rule_name + "-item",
p.tag(mm3::TOOL_ARG_ITEM,
p.literal(NS + "<item>") +
value_of(schema.at("items"), rule_name + "-item", item_close)));
return p.tag(mm3::TOOL_ARG_ARRAY, p.repeat(p.space() + item, 0, -1)) + p.space() + close_tag;
}
return p.tool_arg_json_value(p.schema(p.json(), rule_name + "-schema", schema, false)) + close_tag;
};
// Required properties in schema order, then any number of optional ones in any order.
members_of = [&](const json & schema, const std::string & rule_prefix) -> common_peg_parser {
const auto & props = schema.at("properties");
std::set<std::string> required;
if (schema.contains("required")) {
required = schema.at("required").get<std::set<std::string>>();
}
std::vector<common_peg_parser> required_elements;
std::vector<common_peg_parser> optional_elements;
for (const auto & [key, key_schema] : props.items()) {
auto element = element_of(key, key_schema, rule_prefix + "-" + key);
if (required.find(key) != required.end()) {
required_elements.push_back(element);
} else {
optional_elements.push_back(element);
}
}
common_peg_parser members = p.eps();
for (size_t i = 0; i < required_elements.size(); i++) {
if (i > 0) {
members = members + p.space();
}
members = members + required_elements[i];
}
if (!optional_elements.empty()) {
common_peg_parser any_optional = p.choice();
for (const auto & element : optional_elements) {
any_optional |= element;
}
members = members + p.repeat(p.space() + any_optional, 0, -1);
}
return members;
};
common_peg_parser invoke_body =
params.contains("properties") ? members_of(params, "tool-" + name + "-arg") : p.eps();
auto func_parser = p.tool(
p.tool_open(p.literal(NS + "<invoke name=\"") +
p.tool_name(p.literal(name)) + p.literal("\">")) +
p.space() + invoke_body + p.space() +
p.tool_close(p.literal(INVOKE_END)));
tool_choice |= p.rule("tool-" + name, func_parser);
});
auto require_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
common_peg_parser tool_calls = p.eps();
if (inputs.parallel_tool_calls) {
tool_calls = p.trigger_rule("tool-call",
p.literal(FC_START) + p.space() + tool_choice +
p.zero_or_more(p.space() + tool_choice) + p.space() + p.literal(FC_END));
} else {
tool_calls = p.trigger_rule("tool-call",
p.literal(FC_START) + p.space() + tool_choice + p.space() + p.literal(FC_END));
}
if (!require_tools) {
tool_calls = p.optional(tool_calls);
}
auto content_before_tools = p.content(p.until(FC_START));
return generation_prompt + reasoning + content_before_tools + tool_calls + end;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = !(has_response_format || (has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED));
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.contains("parameters") ? function.at("parameters") : json::object();
builder.resolve_refs(schema);
});
if (has_response_format) {
auto schema = inputs.json_schema;
builder.resolve_refs(schema);
}
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, FC_START },
};
}
return data;
}
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#include "parsers.h"
common_chat_params common_chat_params_init_ministral_3(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
// Build up messages to follow the format: https://huggingface.co/mistralai/Ministral-3-14B-Reasoning-2512/blob/main/chat_template.jinja
auto adjusted_messages = json::array();
for (const auto & msg : inputs.messages) {
auto role = msg.value("role", "");
if (role != "system" && role != "assistant") {
// Only adjust system and assistant messages. Interestingly, the system message may contain thinking.
adjusted_messages.push_back(msg);
continue;
}
auto content = json::array();
// If message contains `reasoning_content`, add it as a block of type `thinking`
if (msg.contains("reasoning_content") && msg.at("reasoning_content").is_string()) {
content.push_back({
{ "type", "thinking" },
{ "thinking", msg.at("reasoning_content").get<std::string>() },
});
}
// If message contains `content`, add it as a block of type `text`
if (msg.contains("content")) {
if (msg.at("content").is_string()) {
content.push_back({
{ "type", "text" },
{ "text", msg.at("content").get<std::string>() },
});
} else if (msg.at("content").is_array()) {
auto blocks = msg.at("content");
content.insert(blocks);
}
}
auto adjusted = msg;
adjusted["content"] = content;
adjusted.erase("reasoning_content");
adjusted_messages.push_back(adjusted);
}
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = inputs.json_schema.is_object() && !inputs.json_schema.empty();
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto include_grammar = true;
data.supports_thinking = true;
data.thinking_start_tag = "[THINK]";
data.thinking_end_tags = {"[/THINK]"};
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs, /* messages_override = */ adjusted_messages);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs, /* messages_override = */ adjusted_messages);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.preserved_tokens = {
"[THINK]",
"[/THINK]",
"[TOOL_CALLS]",
"[ARGS]",
};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "[THINK]" + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += "[/THINK]" + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.eps();
auto reasoning =
extract_reasoning ? p.optional("[THINK]" + p.reasoning(p.until("[/THINK]")) + "[/THINK]") : p.eps();
// Response format parser
if (has_response_format) {
// Ministral wants to emit json surrounded by code fences
return generation_prompt + (reasoning << "```json" << p.content(p.schema(p.json(), "response-format", inputs.json_schema)) << "```");
}
// Tool call parser
if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) {
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
const auto & schema = function.at("parameters");
tool_choice |=
p.rule("tool-" + name, p.tool_open(p.tool_name(p.literal(name)) + "[ARGS]") +
p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema)));
});
auto min_calls = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? 1 : 0;
auto max_calls = inputs.parallel_tool_calls ? -1 : 1;
auto tool_calls = p.trigger_rule("tool-call", p.repeat("[TOOL_CALLS]" + tool_choice, min_calls, max_calls));
return generation_prompt + (reasoning << p.content(p.until("[TOOL_CALLS]")) << tool_calls);
}
// Content only parser
include_grammar = false;
return generation_prompt + (reasoning << p.content(p.rest()));
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.at("parameters");
builder.resolve_refs(schema);
});
if (has_response_format) {
auto schema = inputs.json_schema;
builder.resolve_refs(schema);
}
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "[TOOL_CALLS]" }
};
}
return data;
}
-148
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@@ -1,148 +0,0 @@
#include "parsers.h"
// An assistant turn is rendered as one or more messages, each
// "<|start|>assistant to=<recipient><|message|>{content}{END}" where END is
// <|eom|> (more messages follow) or <|eot|> (end of turn):
// - chain-of-thought: to=self, terminated by <|eom|>
// - final answer: to=user, terminated by <|eot|>
// The generation prompt is just "<|start|>assistant"; the model emits its own
// " to=...<|message|>".
common_chat_params common_chat_params_init_muse_glimmer(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = "<|start|>assistant";
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
data.supports_thinking = true;
data.preserved_tokens = {
"<|start|>", "<|message|>", "<|eom|>", "<|eot|>",
// ATEM tool-call markup emitted on " to=<tool>" turns.
"<atem:function_calls>", "<atem:invoke", "<atem:parameter", "</atem:parameter>",
"</atem:invoke>", "</atem:function_calls>",
};
data.message_delimiters = {
{ COMMON_CHAT_ROLE_ASSISTANT, "<|start|>assistant" },
{ COMMON_CHAT_ROLE_USER, "<|start|>user" },
{ COMMON_CHAT_ROLE_SYSTEM, "<|start|>system" },
{ COMMON_CHAT_ROLE_TOOL, "<|start|>tool" },
};
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = "<|start|>assistant to=self<|message|>" + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += "<|eom|><|start|>assistant to=user<|message|>" + msg.render_content();
}
data.prompt += data.generation_prompt;
}
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
// Constrained grammar whenever tools are offered.
auto include_grammar = has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE;
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto start = p.rule("start", p.literal("<|start|>assistant"));
if (!extract_reasoning && !include_grammar) {
return start + p.content(p.rest());
}
if (extract_reasoning) {
p.rule("analysis", p.literal(" to=self<|message|>") + p.reasoning(p.until("<|eom|>")) + p.literal("<|eom|>"));
} else {
p.rule("analysis", p.literal(" to=self<|message|>") + p.content(p.until("<|eom|>")) + p.literal("<|eom|>"));
}
auto analysis = p.ref("analysis");
auto recipient = p.optional(p.literal(" to=user"));
auto final_msg = p.rule("final", recipient + p.literal("<|message|>") +
p.content(p.until_one_of({ "<|eot|>", "<|eom|>" })));
if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) {
auto string_value = p.ac(
p.tool_arg_string_value(p.until("</atem:parameter>")) + p.tool_arg_close(p.literal("</atem:parameter>")),
"</atem:parameter>");
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
const std::string name = function.at("name");
auto params = function.contains("parameters") ? function.at("parameters") : json::object();
auto args = p.eps();
if (params.contains("properties") && params.at("properties").is_object() && !params.at("properties").empty()) {
auto schema_info = common_schema_info();
schema_info.resolve_refs(params);
auto arg_choice = p.choice();
for (const auto & [prop_name, prop_schema] : params.at("properties").items()) {
auto value_parser = p.eps();
if (schema_info.resolves_to_string(prop_schema)) {
value_parser = string_value;
} else {
value_parser = p.tool_arg_json_value(
p.schema(p.json(), "tool-" + name + "-arg-" + prop_name + "-schema", prop_schema, false))
+ p.tool_arg_close(p.literal("</atem:parameter>"));
}
auto arg_rule = p.tool_arg(
p.tool_arg_open(p.literal("<atem:parameter name=\"") + p.tool_arg_name(p.literal(prop_name)) + p.literal("\">")) +
value_parser);
arg_choice |= arg_rule;
}
args = p.zero_or_more(arg_choice + p.space());
}
auto tool_parser = p.tool(
p.tool_open(p.literal(" to=") + p.until("<|message|>") +
p.literal("<|message|><atem:function_calls>") + p.space() +
p.literal("<atem:invoke name=\"") + p.tool_name(p.literal(name)) + p.literal("\">") + p.space())
<< p.tool_args(args)
<< p.tool_close(p.literal("</atem:invoke>") + p.space() + p.literal("</atem:function_calls>")));
tool_choice |= p.rule("tool-" + name, tool_parser);
});
auto tool_calls = inputs.parallel_tool_calls
? p.trigger_rule("tool-call", tool_choice + p.zero_or_more(p.literal("<|eom|>") + start + tool_choice))
: p.trigger_rule("tool-call", tool_choice);
if (inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED) {
return p.zero_or_more(start + analysis) + start + tool_calls;
}
auto trailing_calls = p.optional(p.literal("<|eom|>") + start + tool_calls);
return p.zero_or_more(start + analysis) + start + (tool_calls | (final_msg + trailing_calls));
}
return p.zero_or_more(start + analysis) + start + final_msg;
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_REQUIRED;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.contains("parameters") ? function.at("parameters") : json::object();
builder.resolve_refs(schema);
});
parser.build_grammar(builder, data.grammar_lazy);
});
data.grammar_triggers = {
{ COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN,
"<\\|start\\|>assistant( to=(?!self<\\|message\\|>)(?!user<\\|message\\|>)[^<]*?<\\|message\\|>)" },
};
}
return data;
}
-34
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@@ -1,34 +0,0 @@
#include "parsers.h"
#include "log.h"
#include <set>
void foreach_function(const json & tools, const std::function<void(const json &)> & fn) {
for (const auto & tool : tools) {
if (!tool.contains("type") || tool.at("type") != "function" || !tool.contains("function")) {
LOG_INF("Skipping tool without function: %s", tool.dump(2).c_str());
continue;
}
fn(tool);
}
}
void foreach_parameter(const json & function, const std::function<void(const std::string &, const json &, bool)> & fn) {
if (!function.contains("parameters") || !function.at("parameters").is_object()) {
return;
}
const auto & params = function.at("parameters");
if (!params.contains("properties") || !params.at("properties").is_object()) {
return;
}
const auto & props = params.at("properties");
std::set<std::string> required;
if (params.contains("required") && params.at("required").is_array()) {
required = params.at("required").get<std::set<std::string>>();
}
for (const auto & [name, prop] : props.items()) {
bool is_required = (required.find(name) != required.end());
fn(name, prop, is_required);
}
}
-77
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@@ -1,77 +0,0 @@
#pragma once
#include "chat.h"
#include "chat-auto-parser.h"
#include "chat-auto-parser-helpers.h"
#include "chat-peg-parser.h"
#include "common.h"
#include "ggml.h"
#include "json-schema-to-grammar.h"
#include "json.h"
#include <functional>
#include <optional>
#include <set>
#include <string>
#include <vector>
using json = common_json;
// iterate over the function tools of an OpenAI-style tools array
void foreach_function(const json & tools, const std::function<void(const json &)> & fn);
// iterate over the parameters of a function tool, flagging the ones listed as required
void foreach_parameter(const json & function, const std::function<void(const std::string &, const json &, bool)> & fn);
// render a template; the override arguments let a parser feed in messages, tools or context it has rewritten
std::string common_chat_template_direct_apply_impl(
const common_chat_template & tmpl,
const autoparser::generation_params & inputs,
const std::optional<json> & messages_override = std::nullopt,
const std::optional<json> & tools_override = std::nullopt,
const std::optional<json> & additional_context = std::nullopt);
// the suffix a template appends when add_generation_prompt is set
std::string common_chat_template_generation_prompt_impl(
const common_chat_template & tmpl,
const autoparser::generation_params & inputs,
const std::optional<json> & messages_override = std::nullopt,
const std::optional<json> & tools_override = std::nullopt,
const std::optional<json> & additional_context = std::nullopt);
bool is_lfm2_template(const std::string & src);
namespace workaround {
void convert_tool_responses_gemma4(json & messages);
}
common_chat_params common_chat_params_init_cohere2moe(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_deepseek_v3_2(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_functionary_v3_2(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_gemma4(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_gigachat_v3(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_gpt_oss(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_kimi_k2(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_kimi_k3(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
// tool_list_tokens preserves the LFM2 system tool-list markers; LFM2.5 renders without them
common_chat_params common_chat_params_init_lfm2(const common_chat_template & tmpl, const autoparser::generation_params & inputs, bool tool_list_tokens);
common_chat_params common_chat_params_init_minicpm5(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_minimax_m3(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_ministral_3(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_muse_glimmer(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
common_chat_params common_chat_params_init_qwen3_coder(const common_chat_template & tmpl, const autoparser::generation_params & inputs);
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@@ -1,181 +0,0 @@
#include "parsers.h"
common_chat_params common_chat_params_init_qwen3_coder(const common_chat_template & tmpl,
const autoparser::generation_params & inputs) {
common_chat_params data;
const std::string GEN_PREFIX = "<|im_start|>assistant\n";
data.prompt = common_chat_template_direct_apply_impl(tmpl, inputs);
data.generation_prompt = common_chat_template_generation_prompt_impl(tmpl, inputs);
data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
auto supports_reasoning = tmpl.source().find("<think>") != std::string::npos;
data.supports_thinking = supports_reasoning;
data.preserved_tokens = {
"<tool_call>",
"</tool_call>",
};
auto is_qwen3_coder = !supports_reasoning;
if (supports_reasoning) {
data.thinking_start_tag = "<think>";
// Support both </think> and <tool_call> as reasoning end sequences.
// <function= is omitted, as it is a workaround for Qwen3-Coder which is not a thinking model
data.thinking_end_tags = { "</think>", "<tool_call>" };
data.preserved_tokens.insert(data.preserved_tokens.end(), { "<think>", "</think>" });
}
data.message_delimiters = {
{ COMMON_CHAT_ROLE_ASSISTANT, "<|im_start|>assistant" },
{ COMMON_CHAT_ROLE_TOOL, "<|im_start|>user\n<tool_response>" }, // Qwen3-Coder, Qwen3.5, Nemotron Nano 3
{ COMMON_CHAT_ROLE_TOOL, "<|im_start|>tool_response" }, // StepFun-3.5-Flash
{ COMMON_CHAT_ROLE_USER, "<|im_start|>user" },
{ COMMON_CHAT_ROLE_SYSTEM, "<|im_start|>system" },
};
auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
auto has_response_format = inputs.json_schema.is_object() && !inputs.json_schema.empty();
auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
auto include_grammar = has_response_format || (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE);
if (inputs.has_continuation()) {
const auto & msg = inputs.continue_msg;
data.generation_prompt = GEN_PREFIX;
if (supports_reasoning) {
data.generation_prompt += "<think>\n" + msg.reasoning_content;
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += "\n</think>\n\n";
}
}
if (inputs.continue_final_message == COMMON_CHAT_CONTINUATION_CONTENT) {
data.generation_prompt += msg.render_content();
}
data.prompt += data.generation_prompt;
}
std::vector<std::string> tool_call_starts = { "<tool_call>" };
if (is_qwen3_coder) {
// Match complete <function=name> opener for Qwen3-Coder models that occasionally omit the
// starting <tool_call>. The model may hallucinate a tool name, but it is preferable over
// constraining on <function which may occur in valid content generation, e.g. #include <functional>
foreach_function(inputs.tools, [&](const json & tool) {
const std::string name = tool.at("function").at("name");
tool_call_starts.push_back("<function=" + name + ">");
});
}
auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
auto generation_prompt = p.literal(GEN_PREFIX);
auto reasoning = p.eps();
if (supports_reasoning && extract_reasoning) {
reasoning = p.optional("<think>" + p.space() +
p.reasoning(p.until_one_of({ "</think>", "<tool_call>" })) +
(p.literal("</think>") | p.peek(p.literal("<tool_call>"))));
}
// Response format parser
if (has_response_format) {
return generation_prompt + (reasoning << p.content(p.schema(p.json(), "response-format", inputs.json_schema)));
}
// Tool call parser
if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) {
auto arg_close = p.tool_arg_close(p.literal("\n</parameter>\n"));
auto arg_string = p.rule("xml-arg-string",
p.ac(p.tool_arg_string_value(p.until("\n</parameter>\n")) + arg_close, "\n</parameter>\n"));
auto tool_choice = p.choice();
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
std::string name = function.at("name");
auto parameters = function.contains("parameters") ? function.at("parameters") : json::object();
auto schema_info = common_schema_info();
schema_info.resolve_refs(parameters);
std::vector<common_peg_parser> required_args;
std::vector<common_peg_parser> optional_args;
foreach_parameter(function, [&](const std::string & param_name, const json & param_schema, bool is_required) {
auto rule_name = "tool-" + name + "-arg-" + param_name;
auto arg_open = p.tool_arg_open("<parameter=" + p.tool_arg_name(p.literal(param_name)) + ">\n");
auto arg_value = schema_info.resolves_to_string(param_schema) ?
arg_string :
p.tool_arg_json_value(p.schema(p.json(), rule_name + "-schema", param_schema)) + arg_close;
auto arg_rule = p.rule(rule_name, p.tool_arg(arg_open + arg_value));
(is_required ? required_args : optional_args).push_back(arg_rule);
});
// Accept required arguments in any order, as Qwen does not always adhere to the
// order provided.
auto args = p.permute("tool-" + name + "-args", required_args);
if (!optional_args.empty()) {
args = args + p.zero_or_more(p.choice(optional_args));
}
auto func = p.tool(p.tool_open("<function=" + p.tool_name(p.literal(name)) + ">\n") +
p.tool_args(args) +
p.tool_close(p.literal("</function>\n")));
tool_choice |= p.rule("tool-" + name, func);
});
auto min_calls = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? 1 : 0;
auto tool_call_body = tool_choice + "</tool_call>" + p.space();
auto tool_call = p.rule("tool-call", "<tool_call>\n" + tool_call_body);
// Qwen3-Coder models may occasionally omit the <tool_call> token.
auto tool_call_first = is_qwen3_coder ?
p.rule("tool-call-first", p.optional(p.literal("<tool_call>\n")) + tool_call_body) :
tool_call;
auto calls = inputs.parallel_tool_calls ? tool_call_first + p.zero_or_more(tool_call) : tool_call_first;
auto tool_calls = p.trigger_rule("tool-call-root", p.repeat(calls, min_calls, 1));
return generation_prompt +
(reasoning << p.content(p.until_one_of(tool_call_starts)) << tool_calls);
}
// Content only parser
return generation_prompt + (reasoning << p.content(p.rest()));
});
data.parser = parser.save();
if (include_grammar) {
data.grammar_lazy = has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
data.grammar = build_grammar([&](const common_grammar_builder & builder) {
foreach_function(inputs.tools, [&](const json & tool) {
const auto & function = tool.at("function");
auto schema = function.contains("parameters") ? function.at("parameters") : json::object();
builder.resolve_refs(schema);
});
if (has_response_format) {
auto schema = inputs.json_schema;
builder.resolve_refs(schema);
}
parser.build_grammar(builder, data.grammar_lazy);
});
if (data.grammar_lazy) {
for (const auto & start : tool_call_starts) {
data.grammar_triggers.push_back({ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, start });
}
}
}
return data;
}
-20
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@@ -1,20 +0,0 @@
# Specialized chat template parsers, listed explicitly so that adding or removing one re-runs CMake instead of leaving an incremental build stale.
set(LLAMA_CHAT_PARSERS_SOURCES
${CMAKE_CURRENT_LIST_DIR}/parsers.cpp
${CMAKE_CURRENT_LIST_DIR}/parsers.h
${CMAKE_CURRENT_LIST_DIR}/cohere2moe.cpp
${CMAKE_CURRENT_LIST_DIR}/deepseek.cpp
${CMAKE_CURRENT_LIST_DIR}/functionary-v3-2.cpp
${CMAKE_CURRENT_LIST_DIR}/gemma4.cpp
${CMAKE_CURRENT_LIST_DIR}/gigachat-v3.cpp
${CMAKE_CURRENT_LIST_DIR}/gpt-oss.cpp
${CMAKE_CURRENT_LIST_DIR}/kimi-k2.cpp
${CMAKE_CURRENT_LIST_DIR}/kimi-k3.cpp
${CMAKE_CURRENT_LIST_DIR}/lfm2.cpp
${CMAKE_CURRENT_LIST_DIR}/minicpm5.cpp
${CMAKE_CURRENT_LIST_DIR}/minimax-m3.cpp
${CMAKE_CURRENT_LIST_DIR}/ministral3.cpp
${CMAKE_CURRENT_LIST_DIR}/muse-glimmer.cpp
${CMAKE_CURRENT_LIST_DIR}/qwen3-coder.cpp
)
+16 -15
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@@ -10,6 +10,7 @@
#include <initializer_list>
#include <map>
#include <memory>
#include <nlohmann/json.hpp>
#include <regex>
#include <set>
#include <stdexcept>
@@ -1119,8 +1120,8 @@ common_peg_parser common_peg_parser_builder::chars(const std::string & classes,
return wrap(arena_.add_parser(common_peg_chars_parser{classes, ranges, negated, min, max}));
}
common_peg_parser common_peg_parser_builder::schema(const common_peg_parser & p, const std::string & name, const common_json & schema, bool raw) {
return wrap(arena_.add_parser(common_peg_schema_parser{p.id(), name, std::make_shared<common_json>(schema), raw}));
common_peg_parser common_peg_parser_builder::schema(const common_peg_parser & p, const std::string & name, const nlohmann::ordered_json & schema, bool raw) {
return wrap(arena_.add_parser(common_peg_schema_parser{p.id(), name, std::make_shared<nlohmann::ordered_json>(schema), raw}));
}
common_peg_parser common_peg_parser_builder::rule(const std::string & name, const common_peg_parser & p, bool trigger) {
@@ -1804,8 +1805,8 @@ void common_peg_arena::build_grammar(const common_grammar_builder & builder, boo
}
}
static common_json serialize_parser_variant(const common_peg_parser_variant & variant) {
using json = common_json;
static nlohmann::json serialize_parser_variant(const common_peg_parser_variant & variant) {
using json = nlohmann::json;
return std::visit([](const auto & p) -> json {
using T = std::decay_t<decltype(p)>;
@@ -1859,7 +1860,7 @@ static common_json serialize_parser_variant(const common_peg_parser_variant & va
{"type", "schema"},
{"child", p.child},
{"name", p.name},
{"schema", p.schema ? *p.schema : json(nullptr)},
{"schema", p.schema ? *p.schema : nullptr},
{"raw", p.raw}
};
} else if constexpr (std::is_same_v<T, common_peg_rule_parser>) {
@@ -1887,19 +1888,19 @@ static common_json serialize_parser_variant(const common_peg_parser_variant & va
}, variant);
}
common_json common_peg_arena::to_json() const {
auto parsers = common_json::array();
nlohmann::json common_peg_arena::to_json() const {
auto parsers = nlohmann::json::array();
for (const auto & parser : parsers_) {
parsers.push_back(serialize_parser_variant(parser));
}
return common_json{
return nlohmann::json{
{"parsers", parsers},
{"rules", rules_},
{"root", root_}
};
}
static common_peg_parser_variant deserialize_parser_variant(const common_json & j) {
static common_peg_parser_variant deserialize_parser_variant(const nlohmann::json & j) {
if (!j.contains("type") || !j["type"].is_string()) {
throw std::runtime_error("Parser variant JSON missing or invalid 'type' field");
}
@@ -1968,9 +1969,9 @@ static common_peg_parser_variant deserialize_parser_variant(const common_json &
}
common_peg_chars_parser parser;
parser.pattern = j["pattern"];
parser.negated = j["negated"].get<bool>();
parser.min_count = j["min_count"].get<int>();
parser.max_count = j["max_count"].get<int>();
parser.negated = j["negated"];
parser.min_count = j["min_count"];
parser.max_count = j["max_count"];
for (const auto & range_json : j["ranges"]) {
if (!range_json.contains("start") || !range_json.contains("end")) {
throw std::runtime_error("char_range missing 'start' or 'end' field");
@@ -2006,7 +2007,7 @@ static common_peg_parser_variant deserialize_parser_variant(const common_json &
parser.child = j["child"].get<common_peg_parser_id>();
parser.name = j["name"];
if (!j["schema"].is_null()) {
parser.schema = std::make_shared<common_json>(j["schema"]);
parser.schema = std::make_shared<nlohmann::ordered_json>(j["schema"]);
}
parser.raw = j["raw"].get<bool>();
return parser;
@@ -2068,7 +2069,7 @@ static common_peg_parser_variant deserialize_parser_variant(const common_json &
throw std::runtime_error("Unknown parser type: " + type);
}
common_peg_arena common_peg_arena::from_json(const common_json & j) {
common_peg_arena common_peg_arena::from_json(const nlohmann::json & j) {
if (!j.contains("parsers") || !j["parsers"].is_array()) {
throw std::runtime_error("JSON missing or invalid 'parsers' array");
}
@@ -2108,7 +2109,7 @@ std::string common_peg_arena::save() const {
}
void common_peg_arena::load(const std::string & data) {
*this = from_json(common_json::parse(data));
*this = from_json(nlohmann::json::parse(data));
}
common_peg_arena build_peg_parser(const std::function<common_peg_parser(common_peg_parser_builder & builder)> & fn) {

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