Merge branch 'master' into xsn/common_json

.devops/nix/package.nix

@@ -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/";

.devops/openvino.Dockerfile

@@ -1,12 +1,12 @@
-ARG OPENVINO_VERSION_MAJOR=2026.3.1
-ARG OPENVINO_VERSION_FULL=2026.3.1.22476.56d9685302d
+ARG OPENVINO_VERSION_MAJOR=2026.3
+ARG OPENVINO_VERSION_FULL=2026.3.0.22451.bd8d6542e3c
 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=v2.38.2
+ARG IGC_VERSION_FULL=2_2.38.2+22051
+ARG COMPUTE_RUNTIME_VERSION=26.27.39122.11
+ARG COMPUTE_RUNTIME_VERSION_FULL=26.27.39122.11-0
 ARG IGDGMM_VERSION=22.10.0
 
 # Intel NPU driver versions. https://github.com/intel/linux-npu-driver/releases
@@ -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 "
 

.ecrc

@@ -1,5 +1,5 @@
 {
-  "Exclude": ["^\\.gitmodules$", "stb_image\\.h", "examples/test-cmake/build/", "examples/test-cmake/build-subdir/"],
+  "Exclude": ["^\\.gitmodules$", "stb_image\\.h"],
   "Disable": {
     "IndentSize": true
   }

.github/ISSUE_TEMPLATE/config.yml

@@ -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

.github/actions/ccache-buckets/action.yml

@@ -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

.github/actions/ccache-clear/action.yml

@@ -21,30 +21,68 @@ inputs:
 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
+      env:
+        CLEAR_KEY: ${{ inputs.key }}
+        CLEAR_OLDER: ${{ inputs.older }}
+        CLEAR_MIN: ${{ inputs.min }}
+        CLEAR_DRY_RUN: ${{ inputs.dry-run }}
       run: |
-        bash scripts/ccache-clear.sh \
-          --key "${{ inputs.key }}" \
-          --older "${{ inputs.older }}" \
-          --min "${{ inputs.min }}" \
-          ${{ inputs.dry-run == 'true' && '--dry-run' || '' }}
+        # Convert a duration (e.g. 90m, 1h, 1d, plain seconds) to seconds
+        to_seconds() {
+          local val="$1"
+          [[ "$val" =~ ^[0-9]+$ ]] && { echo "$val"; return 0; }
+          local num="${val%?}" unit="${val: -1}" mult
+          [[ "$num" =~ ^[0-9]+$ ]] || return 1
+          case "$unit" in
+            s) mult=1 ;;
+            m) mult=60 ;;
+            h) mult=3600 ;;
+            d) mult=86400 ;;
+            *) return 1 ;;
+          esac
+          echo $((num * mult))
+        }
+
+        [[ "$CLEAR_MIN" =~ ^[0-9]+$ ]] || { echo "Invalid min value: $CLEAR_MIN" >&2; exit 1; }
+        [[ "$CLEAR_DRY_RUN" =~ ^(true|false)$ ]] || { echo "Invalid dry-run value: $CLEAR_DRY_RUN" >&2; exit 1; }
+
+        CACHES=$(gh cache list --key "ccache-$CLEAR_KEY" --json id,key,createdAt --jq '.[] | [.createdAt, .id, .key] | @tsv' 2>/dev/null | LC_ALL=C sort)
+        if [ -z "$CACHES" ]; then
+          echo "No caches found with key prefix: $CLEAR_KEY"
+          exit 0
+        fi
+
+        TOTAL=$(( $(wc -l <<< "$CACHES") ))
+
+        echo "Found $TOTAL cache(s) with key prefix: $CLEAR_KEY (oldest first):"
+        while IFS=$'\t' read -r CREATED ID KEY; do
+          printf '  %s  %s  %s\n' "$CREATED" "$ID" "$KEY"
+        done <<< "$CACHES"
+
+        CUTOFF=""
+        if [ -n "$CLEAR_OLDER" ]; then
+          OLDER_SECONDS=$(to_seconds "$CLEAR_OLDER") || { echo "Invalid older value: $CLEAR_OLDER (expected e.g. 90m, 1h, 1d)" >&2; exit 1; }
+          CUTOFF=$(( $(date +%s) - OLDER_SECONDS ))
+        fi
+
+        # Caches are sorted oldest first
+        DELETED=0
+        while IFS=$'\t' read -r CREATED ID KEY; do
+          if [ -n "$CUTOFF" ] && [ "$(date -d "$CREATED" +%s)" -ge "$CUTOFF" ]; then
+            echo "Rest are not older than $CLEAR_OLDER, stopping"
+            break
+          fi
+          if [ $((TOTAL - DELETED - 1)) -lt "$CLEAR_MIN" ]; then
+            echo "Keeping at least $CLEAR_MIN cache(s), stopping"
+            break
+          fi
+          if [ "$CLEAR_DRY_RUN" = "true" ]; then
+            echo "Would delete cache: $ID ($KEY)"
+          else
+            echo "Deleting cache: $ID ($KEY)"
+            gh cache delete "$ID"
+          fi
+          DELETED=$((DELETED + 1))
+        done <<< "$CACHES"

.github/actions/get-tag-name/action.yml

@@ -14,7 +14,7 @@ runs:
       run: |
         BUILD_NUMBER="$(git rev-list --count HEAD)"
         SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-        if [[ "${{ env.BRANCH_NAME }}" == "master" || "${{ env.BRANCH_NAME }}" == "b${BUILD_NUMBER}" ]]; then
+        if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
           echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
         else
           SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')

.github/actions/windows-setup-cuda/action.yml

@@ -100,36 +100,36 @@ runs:
           echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
           echo "CUDA_PATH_V13_1=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
 
-    - name: Install Cuda Toolkit 13.4 for x64
-      if: ${{ inputs.cuda_version == '13.4' && inputs.cuda_arch == 'x64' }}
+    - name: Install Cuda Toolkit 13.3
+      if: ${{ inputs.cuda_version == '13.3' }}
       shell: pwsh
       run: |
-          mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4"
+          mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3"
           choco install unzip -y
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_crt/windows-x86_64/cuda_crt-windows-x86_64-13.4.59-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-13.4.49-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-13.4.59-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-13.4.59-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-13.7.0.27-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libnvvm/windows-x86_64/libnvvm-windows-x86_64-13.4.59-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-13.4.49-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_profiler_api/windows-x86_64/cuda_profiler_api-windows-x86_64-13.4.49-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-13.4.49-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cccl/windows-x86_64/cccl-windows-x86_64-13.3.4.2.1-archive.zip"
-          unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4"
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_crt-windows-x86_64-13.4.59-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_cudart-windows-x86_64-13.4.49-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_nvcc-windows-x86_64-13.4.59-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_nvrtc-windows-x86_64-13.4.59-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\libcublas-windows-x86_64-13.7.0.27-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\libnvvm-windows-x86_64-13.4.59-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_nvtx-windows-x86_64-13.4.49-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_profiler_api-windows-x86_64-13.4.49-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\visual_studio_integration-windows-x86_64-13.4.49-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cccl-windows-x86_64-13.3.4.2.1-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-          echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
-          echo "CUDA_PATH_V13_4=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_crt/windows-x86_64/cuda_crt-windows-x86_64-13.3.33-archive.zip"
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-13.3.29-archive.zip"
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-13.3.33-archive.zip"
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-13.3.33-archive.zip"
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-13.5.1.27-archive.zip"
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libnvvm/windows-x86_64/libnvvm-windows-x86_64-13.3.33-archive.zip"
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-13.3.29-archive.zip"
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_profiler_api/windows-x86_64/cuda_profiler_api-windows-x86_64-13.3.27-archive.zip"
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-13.3.27-archive.zip"
+          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cccl/windows-x86_64/cccl-windows-x86_64-13.3.3.3.1-archive.zip"
+          unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3"
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_crt-windows-x86_64-13.3.33-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_cudart-windows-x86_64-13.3.29-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_nvcc-windows-x86_64-13.3.33-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_nvrtc-windows-x86_64-13.3.33-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\libcublas-windows-x86_64-13.5.1.27-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\libnvvm-windows-x86_64-13.3.33-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_nvtx-windows-x86_64-13.3.29-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cuda_profiler_api-windows-x86_64-13.3.27-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\visual_studio_integration-windows-x86_64-13.3.27-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\cccl-windows-x86_64-13.3.3.3.1-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" /E /I /H /Y
+          echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
+          echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
+          echo "CUDA_PATH_V13_3=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.3" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
 
     - name: Install Cuda Toolkit 13.4 for ARM64
       if: ${{ inputs.cuda_version == '13.4' && inputs.cuda_arch == 'arm64' }}
@@ -137,19 +137,19 @@ runs:
       run: |
           mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4"
           choco install unzip -y
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cccl/windows-x86_64/cccl-windows-x86_64-13.3.4.2.1-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_crt/windows-x86_64/cuda_crt-windows-x86_64-13.4.59-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-13.4.59-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libnvvm/windows-x86_64/libnvvm-windows-x86_64-13.4.59-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-arm64/cuda_cudart-windows-arm64-13.4.49-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-arm64/libcublas-windows-arm64-13.7.0.27-archive.zip"
+          curl -O "https://packages.nvidia.com/bin-archive/pool/windows-x86_64/5B515474-7E78-11F1-8656-C51E4F4B317F/cccl-windows-x86_64-13.3.4.1.2-archive.zip"
+          curl -O "https://packages.nvidia.com/bin-archive/pool/windows-x86_64/5B515474-7E78-11F1-8656-C51E4F4B317F/cuda_crt-windows-x86_64-13.4.46-archive.zip"
+          curl -O "https://packages.nvidia.com/bin-archive/pool/windows-x86_64/5B515474-7E78-11F1-8656-C51E4F4B317F/cuda_nvcc-windows-x86_64-13.4.46-archive.zip"
+          curl -O "https://packages.nvidia.com/bin-archive/pool/windows-x86_64/5B515474-7E78-11F1-8656-C51E4F4B317F/libnvvm-windows-x86_64-13.4.46-archive.zip"
+          curl -O "https://packages.nvidia.com/bin-archive/pool/windows-arm64/5B515474-7E78-11F1-8656-C51E4F4B317F/cuda_cudart-windows-arm64-13.4.46-archive.zip"
+          curl -O "https://packages.nvidia.com/bin-archive/pool/windows-arm64/5B515474-7E78-11F1-8656-C51E4F4B317F/libcublas-windows-arm64-13.7.0.10-archive.zip"
           unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4"
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cccl-windows-x86_64-13.3.4.2.1-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_crt-windows-x86_64-13.4.59-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_nvcc-windows-x86_64-13.4.59-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\libnvvm-windows-x86_64-13.4.59-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_cudart-windows-arm64-13.4.49-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\libcublas-windows-arm64-13.7.0.27-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cccl-windows-x86_64-13.3.4.1.2-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_crt-windows-x86_64-13.4.46-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_nvcc-windows-x86_64-13.4.46-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\libnvvm-windows-x86_64-13.4.46-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\cuda_cudart-windows-arm64-13.4.46-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
+          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\libcublas-windows-arm64-13.7.0.10-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" /E /I /H /Y
           echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
           echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
           echo "CUDA_PATH_V13_4=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8

.github/actions/windows-setup-rocm/action.yml

@@ -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"

.github/workflows/build-android.yml

@@ -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

.github/workflows/build-apple.yml

@@ -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:

.github/workflows/build-cache.yml

@@ -41,8 +41,8 @@ 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: "2026.3"
+      OPENVINO_VERSION_FULL: "2026.3.0.22451.bd8d6542e3c"
 
     steps:
       - name: Clone
@@ -69,8 +69,8 @@ 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: "2026.3"
+      OPENVINO_VERSION_FULL: "2026.3.0.22451.bd8d6542e3c"
 
     steps:
       - name: Clone

.github/workflows/build-cpu.yml

@@ -62,10 +62,11 @@ 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
@@ -90,15 +91,6 @@ 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: |
@@ -108,18 +100,6 @@ jobs:
             -DGGML_RPC=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: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
-        with:
-          key: cpu-${{ matrix.os }}
-          folder: llama.cpp
-          evict-old-files: 1d
-          hf_bucket: ggml-org/cache
-          save: true
-
       - name: Test
         id: cmake_test
         run: |
@@ -137,6 +117,18 @@ jobs:
           ./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
           ./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
 
+      # note: real deletion only on push to master (same condition as the ccache save),
+      #       dry-run otherwise (the token is read-only on PRs from forks)
+      - name: ccache-clear
+        uses: ./.github/actions/ccache-clear
+        env:
+          GH_TOKEN: ${{ github.token }}
+        with:
+          key: cpu-${{ matrix.os }}
+          older: 1h
+          min: 1
+          dry-run: ${{ github.event_name != 'push' || github.ref != 'refs/heads/master' }}
+
   windows:
     name: windows / ${{ matrix.build }}
     runs-on: windows-2025
@@ -164,7 +156,7 @@ 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-${{ matrix.build }}
           variant: ccache
@@ -221,14 +213,5 @@ jobs:
       #     7z x "-o${env:RUNNER_TEMP}" $env:RUNNER_TEMP/sde.tar
       #     $sde = $(join-path $env:RUNNER_TEMP sde-external-${env:SDE_VERSION}-win/sde.exe)
       #     cd build
+      #     $env:LLAMA_SKIP_TESTS_SLOW_ON_EMULATOR = 1
       #     & $sde -future -- ctest -L main -C Release --verbose --timeout 900
-
-      - 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' }}

.github/workflows/build-cuda-ubuntu.yml

@@ -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
@@ -156,39 +116,18 @@ 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
         run: |
           cmake -B build -S . \
-            -DGGML_MUSA=ON \
-            -DMUSA_ARCHITECTURES=21
+            -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

.github/workflows/build-cuda-windows.yml

@@ -34,7 +34,7 @@ jobs:
           - cuda: '12.4'
             arch: x64
             defines: '-DGGML_CUDA_CUB_3DOT2=ON'
-          - cuda: '13.4'
+          - cuda: '13.3'
             arch: x64
             defines: ''
           - cuda: '13.4'
@@ -47,7 +47,7 @@ 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: release-windows-2022-${{ matrix.arch }}-cuda-${{ matrix.cuda }}
 
@@ -152,7 +152,7 @@ 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

.github/workflows/build-ibm.yml

@@ -34,14 +34,9 @@ env:
   LLAMA_ARG_LOG_TIMESTAMPS: 1
 
 jobs:
-  ubuntu-24-s390x:
-    name: ubuntu-24-s390x (VXE ${{ matrix.vxe }})
-    runs-on: ubuntu-24.04-s390x
 
-    strategy:
-      fail-fast: false
-      matrix:
-        vxe: ["ON", "OFF"]  # `-DGGML_VXE=ON/OFF`
+  ubuntu-24-s390x:
+    runs-on: ubuntu-24.04-s390x
 
     steps:
       - name: Clone
@@ -82,8 +77,7 @@ jobs:
         run: |
           cmake -B build \
             -DLLAMA_FATAL_WARNINGS=ON \
-            -DGGML_RPC=ON \
-            -DGGML_VXE=${{ matrix.vxe }}
+            -DGGML_RPC=ON
           time cmake --build build --config Release -j $(nproc)
 
       - name: Test

.github/workflows/build-msys.yml

@@ -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

.github/workflows/build-opencl.yml

@@ -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' }}

.github/workflows/build-openvino.yml

@@ -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-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: "2026.3"
+      OPENVINO_VERSION_FULL: "2026.3.0.22451.bd8d6542e3c"
 
     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|test-recurrent-state-rollback-nemotron-h" --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|test-recurrent-state-rollback-nemotron-h" --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: "2026.3"
+      OPENVINO_VERSION_FULL: "2026.3.0.22451.bd8d6542e3c"
 
     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|test-recurrent-state-rollback-nemotron-h" -C Release --verbose --timeout 3000

.github/workflows/build-riscv.yml

@@ -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
@@ -106,3 +106,83 @@ jobs:
           wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
           ./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
           ./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
+
+  ubuntu-riscv64-native-sanitizer:
+    runs-on: ubuntu-24.04-riscv
+
+    continue-on-error: true
+
+    strategy:
+      matrix:
+        sanitizer: [ADDRESS, THREAD, UNDEFINED]
+        build_type: [Debug]
+
+    steps:
+      - name: Install dependencies
+        run: |
+          # Set gcc-14 and g++-14 as the default compilers
+          sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-14 100
+          sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-14 100
+
+          git lfs install
+
+      - name: GCC version check
+        run: |
+          gcc --version
+          g++ --version
+
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      # note: sparing some ccache since these jobs run on dedicated runners that are not part of the organitzation
+      #- name: ccache
+      #  uses: ggml-org/ccache-action@afde29e5b5422e5da23cb1f639e8baecadeadfc3 # https://github.com/ggml-org/ccache-action/pull/1
+      #  with:
+      #    key: riscv-ubuntu-native-sanitizer-${{ matrix.sanitizer }}-${{ matrix.build_type }}
+      #    evict-old-files: 1d
+      #    save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+
+      - name: Build
+        id: cmake_build
+        if: ${{ matrix.sanitizer != 'THREAD' }}
+        run: |
+          cmake -B build \
+            -DLLAMA_OPENSSL=OFF \
+            -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
+            -DGGML_OPENMP=ON \
+            -DLLAMA_BUILD_EXAMPLES=ON \
+            -DLLAMA_BUILD_TOOLS=ON \
+            -DLLAMA_BUILD_TESTS=OFF \
+            -DCMAKE_C_COMPILER_LAUNCHER=ccache \
+            -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
+            -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
+            -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
+            -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14
+
+          cmake --build build --config ${{ matrix.build_type }} -j $(nproc)
+
+      - name: Build (no OpenMP)
+        id: cmake_build_no_openmp
+        if: ${{ matrix.sanitizer == 'THREAD' }}
+        run: |
+          cmake -B build \
+            -DLLAMA_OPENSSL=OFF \
+            -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
+            -DGGML_OPENMP=OFF \
+            -DLLAMA_BUILD_EXAMPLES=ON \
+            -DLLAMA_BUILD_TOOLS=ON \
+            -DLLAMA_BUILD_TESTS=OFF \
+            -DCMAKE_C_COMPILER_LAUNCHER=ccache \
+            -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
+            -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
+            -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
+            -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14
+
+          cmake --build build --config ${{ matrix.build_type }} -j $(nproc)
+
+      - name: Test
+        id: cmake_test
+        run: |
+          cd build
+          ctest -L main --verbose --timeout 900

.github/workflows/build-sanitize.yml

@@ -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
@@ -101,6 +101,8 @@ jobs:
 
       - name: Test
         id: cmake_test
+        # skip run in Debug - very slow
+        if: ${{ matrix.sanitizer != 'UNDEFINED' }}
         run: |
           cd build
           ctest -L main -E tokenizer --verbose --timeout 900

.github/workflows/build-self-hosted.yml

@@ -7,7 +7,6 @@ on:
       - master
     paths: [
       '.github/workflows/build-self-hosted.yml',
-      'ci/run.sh',
       '**/CMakeLists.txt',
       '**/.cmake',
       '**/*.h',
@@ -28,7 +27,6 @@ on:
     types: [opened, synchronize, reopened]
     paths: [
       '.github/workflows/build-self-hosted.yml',
-      'ci/run.sh',
       '**/CMakeLists.txt',
       '**/.cmake',
       '**/*.h',
@@ -60,48 +58,18 @@ env:
 
 jobs:
   gpu-cuda:
-    runs-on: "hf-jobs-t4-small:cuda13"
+    runs-on: [self-hosted, Linux, NVIDIA]
 
     steps:
       - name: Clone
         id: checkout
         uses: actions/checkout@v6
 
-      - name: Install dependencies
-        run: |
-          sudo apt update
-          sudo apt install -y cmake libssl-dev time unzip wget 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-gpu-cuda
-          folder: llama.cpp
-          hf_bucket: ggml-org/cache
-
       - name: Test
         id: ggml-ci
         run: |
           nvidia-smi
-          GG_BUILD_CUDA=1 CUDACXX=/usr/local/cuda/bin/nvcc bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
-
-      - 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-gpu-cuda
-          folder: llama.cpp
-          evict-old-files: 1d
-          hf_bucket: ggml-org/cache
-          save: true
+          GG_BUILD_CUDA=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   gpu-rocm:
     runs-on: [self-hosted, Linux, AMD]
@@ -124,7 +92,6 @@ jobs:
           GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS=gfx1151 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   gpu-vulkan-nvidia-cm:
-    # runs-on: "hf-jobs-t4-small:ubuntu26_04"
     runs-on: [self-hosted, Linux, NVIDIA]
 
     steps:
@@ -132,44 +99,13 @@ jobs:
         id: checkout
         uses: actions/checkout@v6
 
-      # - name: Install dependencies
-      #   run: |
-      #     sudo apt update
-      #     sudo apt install -y build-essential cmake libxcb-xinput0 libxcb-xinerama0 libxcb-cursor-dev libvulkan-dev glslc spirv-headers vulkan-tools mesa-vulkan-drivers libglvnd0 libgl1 libglx0 libegl1 libgles2 libssl-dev time unzip wget 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-vulkan-nvidia-cm
-      #     folder: llama.cpp
-      #     hf_bucket: ggml-org/cache
-
       - name: Test
         id: ggml-ci
         run: |
           vulkaninfo --summary
           GG_BUILD_VULKAN=1 GGML_VK_DISABLE_COOPMAT2=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
-      # - 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-vulkan-nvidia-cm
-      #     folder: llama.cpp
-      #     evict-old-files: 1d
-      #     hf_bucket: ggml-org/cache
-      #     save: true
-
   gpu-vulkan-nvidia-cm2:
-    # runs-on: "hf-jobs-t4-small:ubuntu26_04"
     runs-on: [self-hosted, Linux, NVIDIA, COOPMAT2]
 
     steps:
@@ -177,75 +113,27 @@ jobs:
         id: checkout
         uses: actions/checkout@v6
 
-      # - name: Install dependencies
-      #   run: |
-      #     sudo apt update
-      #     sudo apt install -y build-essential cmake libxcb-xinput0 libxcb-xinerama0 libxcb-cursor-dev libvulkan-dev glslc spirv-headers vulkan-tools mesa-vulkan-drivers libglvnd0 libgl1 libglx0 libegl1 libgles2 libssl-dev time unzip wget 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-vulkan-nvidia-cm2
-      #     folder: llama.cpp
-      #     hf_bucket: ggml-org/cache
-
       - name: Test
         id: ggml-ci
         run: |
           vulkaninfo --summary
           GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
-      # - 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-vulkan-nvidia-cm2
-      #     folder: llama.cpp
-      #     evict-old-files: 1d
-      #     hf_bucket: ggml-org/cache
-      #     save: true
-
   gpu-webgpu-nvidia:
-    runs-on: "hf-jobs-t4-small:ubuntu26_04"
+    runs-on: [self-hosted, Linux, NVIDIA, X64]
 
     steps:
       - name: Clone
         id: checkout
         uses: actions/checkout@v6
 
-      - name: Install dependencies
-        run: |
-          sudo apt update
-          sudo apt install -y build-essential cmake libxcb-xinput0 libxcb-xinerama0 libxcb-cursor-dev libvulkan1 mesa-vulkan-drivers libglvnd0 libgl1 libglx0 libegl1 libgles2 libssl-dev time unzip wget 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-webgpu-nvidia
-          folder: llama.cpp
-          hf_bucket: ggml-org/cache
-
       - name: Dawn Dependency
         id: dawn-depends
         run: |
-          DAWN_VERSION="v20260908.214631"
+          DAWN_VERSION="v20260317.182325"
           DAWN_OWNER="google"
           DAWN_REPO="dawn"
-          DAWN_ASSET_NAME="Dawn-94c3c9cc0d5fb2e85aebb370fa8d37b71aa34655-ubuntu-latest-Release"
+          DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
           echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
           curl -L -o artifact.tar.gz \
             "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
@@ -260,18 +148,6 @@ jobs:
           GG_BUILD_WEBGPU_DAWN_DIR="$GITHUB_WORKSPACE/dawn/lib64/cmake/Dawn" \
             bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
-      - name: ccache-buckets-save
-        if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-        uses: ./.github/actions/ccache-buckets
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
-        with:
-          key: self-hosted-webgpu-nvidia
-          folder: llama.cpp
-          evict-old-files: 1d
-          hf_bucket: ggml-org/cache
-          save: true
-
   # TODO: provision AMX-compatible machine
   #cpu-amx:
   #  runs-on: [self-hosted, Linux, CPU, AMX]
@@ -340,10 +216,10 @@ jobs:
       - name: Dawn Dependency
         id: dawn-depends
         run: |
-          DAWN_VERSION="v20260908.214631"
+          DAWN_VERSION="v20260317.182325"
           DAWN_OWNER="google"
           DAWN_REPO="dawn"
-          DAWN_ASSET_NAME="Dawn-94c3c9cc0d5fb2e85aebb370fa8d37b71aa34655-macos-latest-Release"
+          DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-macos-latest-Release"
           echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
           curl -L -o artifact.tar.gz \
             "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
@@ -412,8 +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: "2026.3"
+      OPENVINO_VERSION_FULL: "2026.3.0.22451.bd8d6542e3c"
 
     steps:
       - name: Clone
@@ -453,7 +329,7 @@ jobs:
           LLAMA_ARG_THREADS=$(nproc) GG_BUILD_HIGH_PERF=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   cpu-arm64-high-perf-graviton4:
-    runs-on: ah-ubuntu_24_04-c8g_8x
+    runs-on: ah-ubuntu_22_04-c8g_8x
 
     steps:
       - name: Clone
@@ -489,14 +365,10 @@ jobs:
       - name: Test
         id: ggml-ci
         run: |
-          LLAMA_ARG_THREADS=$(nproc) \
-          GG_BUILD_HIGH_PERF=1 \
-          GG_BUILD_NO_BF16=1 \
-          GG_BUILD_EXTRA_TESTS_0=1 \
-          bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
+          LLAMA_ARG_THREADS=$(nproc) GG_BUILD_HIGH_PERF=1 GG_BUILD_NO_BF16=1 GG_BUILD_EXTRA_TESTS_0=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
 
   cpu-arm64-graviton4-kleidiai:
-    runs-on: ah-ubuntu_24_04-c8g_8x
+    runs-on: ah-ubuntu_22_04-c8g_8x
 
     steps:
       - name: Clone
@@ -532,8 +404,6 @@ jobs:
       - name: Test
         id: ggml-ci
         run: |
-          LLAMA_ARG_THREADS=$(nproc) \
           GG_BUILD_KLEIDIAI=1 \
           GG_BUILD_EXTRA_TESTS_0=1 \
-          GG_BUILD_HIGH_PERF=1 \
-          bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp
+          bash ./ci/run.sh ./tmp/results ./tmp/mnt

.github/workflows/build-sycl.yml

@@ -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' }}

.github/workflows/build-vulkan.yml

@@ -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
 
@@ -122,19 +102,11 @@ jobs:
           strip: 1
 
       - 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 +117,6 @@ 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: |
@@ -164,7 +124,9 @@ jobs:
           export GGML_VK_VISIBLE_DEVICES=0
           export GGML_VK_DISABLE_F16=1
           export GGML_VK_DISABLE_COOPMAT=1
-          ctest -L main --verbose --timeout 900
+          # 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
@@ -178,7 +140,7 @@ 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-x64-vulkan
           variant: ccache
@@ -218,13 +180,3 @@ jobs:
         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' }}

.github/workflows/build-wasm.yml

@@ -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: |
@@ -68,22 +69,13 @@ jobs:
 
       - name: Fetch emdawnwebgpu
         run: |
-          DAWN_TAG="v20260908.214631"
+          DAWN_TAG="v20260317.182325"
           EMDAWN_PKG="emdawnwebgpu_pkg-${DAWN_TAG}.zip"
           echo "Downloading ${EMDAWN_PKG}"
           curl -L -o emdawn.zip \
             "https://github.com/google/dawn/releases/download/${DAWN_TAG}/${EMDAWN_PKG}"
           unzip emdawn.zip
 
-      - name: 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

.github/workflows/build-webgpu.yml

@@ -69,33 +69,25 @@ 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
         run: |
-          DAWN_VERSION="v20260908.214631"
+          DAWN_VERSION="v20260317.182325"
           DAWN_OWNER="google"
           DAWN_REPO="dawn"
-          DAWN_ASSET_NAME="Dawn-94c3c9cc0d5fb2e85aebb370fa8d37b71aa34655-macos-latest-Release"
+          DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-macos-latest-Release"
           echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
           curl -L -o artifact.tar.gz \
             "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
           mkdir dawn
           tar -xvf artifact.tar.gz -C dawn --strip-components=1
 
-      - name: 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
@@ -147,25 +128,16 @@ jobs:
         id: dawn-depends
         run: |
           sudo apt-get install -y libxrandr-dev libxinerama-dev libxcursor-dev mesa-common-dev libx11-xcb-dev libxi-dev
-          DAWN_VERSION="v20260908.214631"
+          DAWN_VERSION="v20260317.182325"
           DAWN_OWNER="google"
           DAWN_REPO="dawn"
-          DAWN_ASSET_NAME="Dawn-94c3c9cc0d5fb2e85aebb370fa8d37b71aa34655-ubuntu-latest-Release"
+          DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
           echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
           curl -L -o artifact.tar.gz \
             "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
           mkdir dawn
           tar -xvf artifact.tar.gz -C dawn --strip-components=1
 
-      - name: 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: |
@@ -174,20 +146,10 @@ 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: |
           cd build
-          ctest -L main --verbose --timeout 900
+          # 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

.github/workflows/code-style.yml

@@ -15,7 +15,7 @@ concurrency:
 
 jobs:
   model-naming:
-    runs-on: ubuntu-slim
+    runs-on: [self-hosted, fast]
     steps:
       - uses: actions/checkout@v6
       - name: Check model naming conventions

.github/workflows/copilot-setup-steps.yml

@@ -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

.github/workflows/docker.yml

@@ -64,7 +64,7 @@ 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 +162,7 @@ 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

.github/workflows/editorconfig.yml

@@ -15,7 +15,7 @@ concurrency:
 
 jobs:
   editorconfig:
-    runs-on: ubuntu-slim
+    runs-on: [self-hosted, fast]
     steps:
       - uses: actions/checkout@v6
       - uses: editorconfig-checker/action-editorconfig-checker@840e866d93b8e032123c23bac69dece044d4d84c # v2.2.0

.github/workflows/fusion.yml

@@ -1,71 +0,0 @@
-name: Fusion
-
-on:
-  workflow_dispatch: # allows manual triggering
-  push:
-    branches:
-      - master
-    paths: [
-      '.github/workflows/fusion.yml',
-      'ggml/**',
-      'tests/fusion/**',
-      'tests/test-fusion.cpp',
-      'tests/test-llama-archs.cpp',
-      'src/models/**'
-    ]
-
-  pull_request:
-    types: [opened, synchronize, reopened]
-    paths: [
-      '.github/workflows/fusion.yml',
-      'ggml/**',
-      'tests/fusion/**',
-      'tests/test-fusion.cpp',
-      'tests/test-llama-archs.cpp',
-      'src/models/**'
-    ]
-
-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:
-  # TODO: add jobs for other backends as they adopt the fusion debug API
-  metal:
-    runs-on: [self-hosted, macOS, ARM64]
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-
-      - name: Build
-        id: cmake_build
-        run: |
-          cmake -B build \
-            -DCMAKE_BUILD_TYPE=Release \
-            -DLLAMA_FATAL_WARNINGS=ON \
-            -DLLAMA_OPENSSL=OFF \
-            -DGGML_SCHED_NO_REALLOC=ON \
-            -DGGML_BLAS=OFF \
-            -DGGML_METAL=ON
-          time cmake --build build --config Release --target test-llama-archs -j $(sysctl -n hw.logicalcpu)
-          time cmake --build build --config Release --target test-fusion -j $(sysctl -n hw.logicalcpu)
-
-      - name: Generate models
-        id: generate_models
-        run: |
-          rm -rf build-ci-models && mkdir -p build-ci-models
-          ./build/bin/test-llama-archs -o build-ci-models
-
-      - name: Test fusion
-        id: test_fusion
-        run: |
-          ./build/bin/test-fusion --models build-ci-models --device MTL0 --check tests/fusion/MTL.csv

.github/workflows/hip-quality-check.yml

@@ -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

.github/workflows/make-release.yml

@@ -19,7 +19,6 @@ env:
 
 permissions:
   contents: write
-  packages: write
 
 jobs:
   make-release:
@@ -85,13 +84,11 @@ jobs:
 
             New version has been released.
 
-            ## Assets
-
             ${{ steps.desc.outputs.nightly }}
 
-            ## More info
+            **Web UI:** the `nightly-tag.txt` asset contains the tag of the corresponding nightly release
 
-            - [Releases and versioning of `ggml-org` projects](https://github.com/ggml-org/ggml/discussions/1579)
+            **More info:** [dist : releases and versioning of ggml-org projects](https://github.com/ggml-org/ggml/discussions/1579)
 
             ## ${{ steps.desc.outputs.changelog_title }}
 
@@ -114,29 +111,6 @@ jobs:
               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: |

.github/workflows/python-type-check.yml

@@ -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

.github/workflows/release.yml

@@ -61,8 +61,31 @@ jobs:
             echo "should_release=false" >> $GITHUB_OUTPUT
           fi
 
+  get-version:
+    runs-on: ubuntu-slim
+    outputs:
+      ui_version: ${{ steps.version.outputs.ui_version }}
+    steps:
+      - uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+      - id: version
+        run: |
+          # Resolve UI version: BUILD_NUMBER from cmake/build-info.cmake > git hash + epoch > fallback
+          version=""
+          if grep -q "BUILD_NUMBER" cmake/build-info.cmake; then
+            build_number=$(grep "set(BUILD_NUMBER" cmake/build-info.cmake | grep -oP '\d+')
+            if [ -n "$build_number" ] && [ "$build_number" -gt 0 ]; then
+              version="b${build_number}"
+            fi
+          fi
+          if [ -z "$version" ]; then
+            version=$(git rev-parse --short HEAD)-$(date +%s)
+          fi
+          echo "ui_version=${version}" >> $GITHUB_OUTPUT
+
   macos-cpu:
-    needs: [check-release, ui-build]
+    needs: [check-release, get-version]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
     strategy:
       matrix:
@@ -96,14 +119,15 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Download UI build
-        uses: actions/download-artifact@v7
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          name: llama-ui.zip
-          path: tools/ui/dist
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
           key: release-${{ matrix.os }}-${{ matrix.arch }}
 
@@ -117,6 +141,7 @@ jobs:
             -DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
             -DLLAMA_FATAL_WARNINGS=ON \
             -DLLAMA_BUILD_BORINGSSL=ON \
+            -DHF_UI_VERSION=${{ needs.get-version.outputs.ui_version }} \
             ${{ env.CMAKE_ARGS }}
           cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
 
@@ -142,7 +167,7 @@ jobs:
           key: release-${{ matrix.os }}-${{ matrix.arch }}
 
   ubuntu-cpu:
-    needs: [check-release, ui-build]
+    needs: [check-release, get-version]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
     strategy:
       matrix:
@@ -166,11 +191,12 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Download UI build
-        uses: actions/download-artifact@v7
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          name: llama-ui.zip
-          path: tools/ui/dist
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Dependencies
         id: depends
@@ -187,7 +213,7 @@ jobs:
 
       - name: ccache
         if: ${{ matrix.build != 's390x' }}
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
           key: release-${{ matrix.os }}-cpu
 
@@ -201,6 +227,7 @@ jobs:
             -DGGML_NATIVE=OFF \
             -DGGML_CPU_ALL_VARIANTS=ON \
             -DLLAMA_FATAL_WARNINGS=ON \
+            -DHF_UI_VERSION=${{ needs.get-version.outputs.ui_version }} \
             ${{ env.CMAKE_ARGS }}
           cmake --build build --config Release -j $(nproc)
 
@@ -227,7 +254,7 @@ jobs:
           key: release-${{ matrix.os }}-cpu
 
   ubuntu-vulkan:
-    needs: [check-release, ui-build]
+    needs: [check-release, get-version]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
 
     strategy:
@@ -250,11 +277,12 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Download UI build
-        uses: actions/download-artifact@v7
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          name: llama-ui.zip
-          path: tools/ui/dist
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Dependencies
         id: depends
@@ -272,7 +300,7 @@ jobs:
           fi
 
       - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
           key: release-${{ matrix.os }}-vulkan
 
@@ -286,6 +314,7 @@ jobs:
             -DGGML_NATIVE=OFF \
             -DGGML_CPU_ALL_VARIANTS=ON \
             -DGGML_VULKAN=ON \
+            -DHF_UI_VERSION=${{ needs.get-version.outputs.ui_version }} \
             ${{ env.CMAKE_ARGS }}
           cmake --build build --config Release -j $(nproc)
 
@@ -310,147 +339,8 @@ jobs:
         with:
           key: release-${{ matrix.os }}-vulkan
 
-  ubuntu-cuda:
-    name: ubuntu-cuda (${{ matrix.label }}, ${{ matrix.build }})
-    needs: [check-release, ui-build]
-    if: ${{ needs.check-release.outputs.should_release == 'true' }}
-
-    strategy:
-      matrix:
-        include:
-          # label = short version used in artifact names / release body
-          # cuda  = full container image tag
-          - build: 'x64'
-            os: ubuntu-24.04
-            cuda: '12.8.2'
-            label: '12.8'
-            defines: '-DGGML_CUDA_CUB_3DOT2=ON'
-          - build: 'x64'
-            os: ubuntu-24.04
-            cuda: '13.3.1'
-            label: '13.3'
-            defines: ''
-          - build: 'arm64'
-            os: ubuntu-24.04-arm
-            cuda: '13.3.1'
-            label: '13.3'
-            defines: ''
-
-    runs-on: ${{ matrix.os }}
-    container: nvidia/cuda:${{ matrix.cuda }}-devel-ubuntu24.04
-
-    permissions:
-      actions: write
-
-    steps:
-      # the container has no git; install it before checkout so that a real git
-      # repository is created (the get-tag-name action and the build both need it)
-      - name: Install git
-        run: |
-          apt-get update
-          apt-get install -y --no-install-recommends git
-
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v6
-        with:
-          fetch-depth: 0
-
-      # checkout runs as the host user; in-container steps run as root, so git
-      # refuses to touch a repo it does not own. Mark the workspace as safe.
-      # use the env var: the github.workspace context holds the HOST path,
-      # GITHUB_WORKSPACE the container path
-      - name: Git safe directory
-        run: git config --global --add safe.directory "$GITHUB_WORKSPACE"
-
-      - name: Download UI build
-        uses: actions/download-artifact@v7
-        with:
-          name: llama-ui.zip
-          path: tools/ui/dist
-
-      - name: Dependencies
-        id: depends
-        # container jobs default to sh (dash); need bash for the [[ ]] below
-        shell: bash
-        run: |
-          apt-get update
-          apt-get install -y --no-install-recommends build-essential cmake ninja-build libssl-dev jq python3-venv
-          # the container ships GCC 13, which does not know the 'sme' march
-          # feature used by the armv9.2 CPU variant of GGML_CPU_ALL_VARIANTS
-          if [[ "${{ matrix.build }}" == "arm64" ]]; then
-            apt-get install -y --no-install-recommends gcc-14 g++-14
-            echo "CC=gcc-14" >> "$GITHUB_ENV"
-            echo "CXX=g++-14" >> "$GITHUB_ENV"
-          fi
-
-      - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
-        with:
-          key: release-ubuntu-${{ matrix.os }}-cuda-${{ matrix.label }}-${{ matrix.build }}
-          evict-old-files: 1d
-          max-size: "1G"
-
-      - name: Build
-        id: cmake_build
-        # no CMAKE_CUDA_ARCHITECTURES: use the broad default arch set from
-        # ggml/src/ggml-cuda/CMakeLists.txt so the release binary covers many GPUs
-        run: |
-          cmake -B build \
-            -DCMAKE_INSTALL_RPATH='$ORIGIN' \
-            -DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
-            -DGGML_BACKEND_DL=ON \
-            -DGGML_NATIVE=OFF \
-            -DGGML_CPU_ALL_VARIANTS=ON \
-            -DGGML_CUDA=ON \
-            -DGGML_CUDA_NCCL=OFF \
-            ${{ env.CMAKE_ARGS }} ${{ matrix.defines }}
-          cmake --build build --config Release -j $(nproc)
-
-      - name: Determine tag name
-        id: tag
-        uses: ./.github/actions/get-tag-name
-
-      - name: Pack artifacts
-        id: pack_artifacts
-        run: |
-          cp LICENSE ./build/bin/
-          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-${{ matrix.label }}-${{ matrix.build }}.tar.gz --transform "s,^\.,llama-${{ steps.tag.outputs.name }}," -C ./build/bin .
-
-      - name: Upload artifacts
-        uses: actions/upload-artifact@v6
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-${{ matrix.label }}-${{ matrix.build }}.tar.gz
-          name: llama-bin-ubuntu-cuda-${{ matrix.label }}-${{ matrix.build }}.tar.gz
-
-      # ship the CUDA runtime libraries the backend links against, mirroring
-      # the windows-cuda cudart zip - extract next to the binaries ($ORIGIN rpath)
-      - name: Pack CUDA runtime
-        id: pack_cuda_runtime
-        run: |
-          major="${{ matrix.label }}"
-          major="${major%%.*}"
-          mkdir -p ./cudart
-          # cp -L dereferences the SONAME symlinks into plain files, so the
-          # tarball holds exactly 3 files with no versioned duplicates
-          cp -L /usr/local/cuda/lib64/libcudart.so.${major} ./cudart/
-          cp -L /usr/local/cuda/lib64/libcublas.so.${major} ./cudart/
-          cp -L /usr/local/cuda/lib64/libcublasLt.so.${major} ./cudart/
-          tar -czvf cudart-llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-${{ matrix.label }}-${{ matrix.build }}.tar.gz --transform "s,^\.,cudart-llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-${{ matrix.label }}-${{ matrix.build }}," -C ./cudart .
-
-      - name: Upload CUDA runtime
-        uses: actions/upload-artifact@v6
-        with:
-          path: cudart-llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-${{ matrix.label }}-${{ matrix.build }}.tar.gz
-          name: cudart-llama-bin-ubuntu-cuda-${{ matrix.label }}-${{ matrix.build }}.tar.gz
-
-      - name: ccache-clear
-        uses: ./.github/actions/ccache-clear
-        with:
-          key: release-ubuntu-${{ matrix.os }}-cuda-${{ matrix.label }}-${{ matrix.build }}
-
   android-arm64:
-    needs: [check-release, ui-build]
+    needs: [check-release, get-version]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
 
     runs-on: ubuntu-latest
@@ -468,11 +358,12 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Download UI build
-        uses: actions/download-artifact@v7
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          name: llama-ui.zip
-          path: tools/ui/dist
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Set up JDK
         uses: actions/setup-java@v5
@@ -484,7 +375,6 @@ jobs:
         uses: android-actions/setup-android@40fd30fb8d7440372e1316f5d1809ec01dcd3699 # v4.0.1
         with:
           log-accepted-android-sdk-licenses: false
-          packages: 'platform-tools'
 
       - name: Install NDK
         run: |
@@ -498,7 +388,7 @@ 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: release-android-arm64
 
@@ -517,6 +407,7 @@ jobs:
             -DLLAMA_FATAL_WARNINGS=ON \
             -DGGML_OPENMP=OFF \
             -DLLAMA_BUILD_BORINGSSL=ON \
+            -DHF_UI_VERSION=${{ needs.get-version.outputs.ui_version }} \
             ${{ env.CMAKE_ARGS }}
           cmake --build build --config Release -j $(nproc)
 
@@ -542,7 +433,7 @@ jobs:
           name: llama-bin-android-arm64.tar.gz
 
   ubuntu-24-openvino:
-    needs: [check-release, ui-build]
+    needs: [check-release, get-version]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
 
     runs-on: ubuntu-24.04
@@ -555,8 +446,8 @@ 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: "2026.3"
+      OPENVINO_VERSION_FULL: "2026.3.0.22451.bd8d6542e3c"
 
     steps:
       - name: Set OpenVINO version output
@@ -569,14 +460,15 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Download UI build
-        uses: actions/download-artifact@v7
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          name: llama-ui.zip
-          path: tools/ui/dist
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
           key: release-ubuntu-24.04-openvino-release-no-preset-v1
 
@@ -616,6 +508,7 @@ jobs:
             -DGGML_OPENVINO=ON \
             -DCMAKE_INSTALL_RPATH='$ORIGIN' \
             -DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
+            -DHF_UI_VERSION=${{ needs.get-version.outputs.ui_version }} \
             ${{ env.CMAKE_ARGS }}
           cmake --build build/ReleaseOV --config Release --parallel
 
@@ -659,7 +552,7 @@ jobs:
           key: release-ubuntu-24.04-openvino-release-no-preset-v1
 
   windows-openvino:
-    needs: [check-release, ui-build]
+    needs: [check-release]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
 
     runs-on: windows-2022
@@ -669,8 +562,8 @@ 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: "2026.3"
+      OPENVINO_VERSION_FULL: "2026.3.0.22451.bd8d6542e3c"
 
     steps:
       - name: Set OpenVINO version output
@@ -684,14 +577,15 @@ jobs:
         with:
             fetch-depth: 0
 
-      - name: Download UI build
-        uses: actions/download-artifact@v7
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          name: llama-ui.zip
-          path: tools/ui/dist
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
           key: release-windows-2022-openvino
           variant: ccache
@@ -788,7 +682,7 @@ jobs:
 
   windows-cpu:
     name: windows-cpu / ${{ matrix.arch }}
-    needs: [check-release, ui-build]
+    needs: [check-release]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
 
     runs-on: windows-2025-vs2026
@@ -808,18 +702,19 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Download UI build
-        uses: actions/download-artifact@v7
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          name: llama-ui.zip
-          path: tools/ui/dist
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Install Ninja
         run: |
           choco install ninja
 
       - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
           key: release-windows-2025-vs2026-${{ matrix.arch }}-cpu
 
@@ -854,8 +749,6 @@ jobs:
         with:
           key: release-windows-2025-vs2026-${{ matrix.arch }}-cpu
 
-  # note: builds only the ggml-hip backend - llama-server is injected from the
-  #       windows-cpu zip during the release "Merge artifacts" step
   windows-rocm:
     needs: [check-release]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
@@ -865,7 +758,7 @@ jobs:
     strategy:
       matrix:
         include:
-          - ROCM_VERSION: "10.0.0"
+          - ROCM_VERSION: "7.14.0"
             gpu_targets: "gfx1010;gfx1011;gfx1012;gfx1030;gfx1031;gfx1032;gfx1033;gfx1034;gfx1035;gfx1036;gfx1100;gfx1101;gfx1102;gfx1103;gfx1150;gfx1151;gfx1152;gfx1153;gfx1200;gfx1201"
             build: x64
 
@@ -876,12 +769,8 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Install Ninja
-        run: |
-          choco install ninja
-
       - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
           key: windows-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}
           evict-old-files: 1d
@@ -933,28 +822,33 @@ jobs:
 
       - name: Build
         run: |
-          cmake -S . -B build `
-            -G "Ninja Multi-Config" `
+          mkdir build
+          cd build
+          cmake .. `
+            -G "Unix Makefiles" `
             -DCMAKE_PREFIX_PATH="${env:HIP_PATH}" `
+            -DCMAKE_BUILD_TYPE=Release `
             -DGGML_BACKEND_DL=ON `
             -DGGML_NATIVE=OFF `
-            -DGGML_CPU=OFF `
+            -DGGML_CPU=ON `
+            -DGGML_CPU_ALL_VARIANTS=ON `
             -DGGML_HIP=ON `
             -DCMAKE_C_COMPILER="${env:HIP_PATH}\lib\llvm\bin\clang.exe" `
             -DCMAKE_CXX_COMPILER="${env:HIP_PATH}\lib\llvm\bin\clang++.exe" `
             -DCMAKE_C_FLAGS="-Wno-error=incompatible-pointer-types" `
             -DCMAKE_HIP_COMPILER="${env:HIP_PATH}\lib\llvm\bin\clang.exe" `
             -DHIP_PATH="${env:HIP_PATH}" `
+            -DGGML_HIP_ROCWMMA_FATTN=ON `
             -DAMDGPU_TARGETS="${{ matrix.gpu_targets }}"
-          cmake --build build --config Release --parallel ${env:NUMBER_OF_PROCESSORS} --target ggml-hip
+          cmake --build . --config Release --parallel ${env:NUMBER_OF_PROCESSORS}
 
       - name: Verify HIP backend was built
         run: |
-          $hipDll = Get-ChildItem -Path build\bin\Release -Filter "ggml-hip*.dll" -ErrorAction SilentlyContinue
+          $hipDll = Get-ChildItem -Path build\bin -Filter "ggml-hip*.dll" -ErrorAction SilentlyContinue
           if (-not $hipDll) {
             Write-Host "##[error]ggml-hip*.dll was NOT produced. The HIP backend silently failed to build."
-            Write-Host "Contents of build\bin\Release:"
-            Get-ChildItem build\bin\Release | Format-Table -AutoSize
+            Write-Host "Contents of build\bin:"
+            Get-ChildItem build\bin | Format-Table -AutoSize
             exit 1
           }
           Write-Host "HIP backend artifact found:"
@@ -969,40 +863,10 @@ jobs:
           $rocmVersionShort = ('${{ matrix.ROCM_VERSION }}'.Split('.')[0..1] -join '.')
           echo "ROCM_VERSION_SHORT=$rocmVersionShort" >> $env:GITHUB_ENV
 
-      - name: Bundle HIP runtime DLLs (amdhip64_7.dll, rocm_kpack.dll, amd_comgr.dll)
-        run: |
-          $ErrorActionPreference = "Stop"
-          # See issue https://github.com/ggml-org/llama.cpp/issues/26929.
-          # ggml-hip.dll loads amdhip64_7.dll at run time. The Adrenalin driver
-          # ships an amdhip64_7.dll in System32, which the loader searches before PATH,
-          # so a matching DLL from PATH cannot win. Copy amdhip64 next to the
-          # binaries (exe directory is searched before System32) so the correct
-          # runtime is used. rocm_kpack.dll is amdhip64_7's direct dependency, so
-          # copy the matching version too. amd_comgr is copied as well to keep it
-          # in sync with the bundled amdhip64, avoiding a version mismatch with a
-          # amd_comgr from System32.
-          # rocblas/hipblaslt kernels resolve fine via PATH and are not copied.
-          $binPath = (rocm-sdk path --bin).Trim()
-          if (-not $binPath) { throw "rocm-sdk path --bin returned empty" }
-          write-host "ROCm bin path: $binPath"
-
-          $patterns = @("amdhip64_7.dll", "rocm_kpack.dll", "amd_comgr.dll")
-          foreach ($pattern in $patterns) {
-            $files = Get-ChildItem -Path $binPath -Filter $pattern -ErrorAction SilentlyContinue
-            if (-not $files) { throw "no match for $pattern in $binPath" }
-            foreach ($f in $files) {
-              Copy-Item $f.FullName -Destination build\bin\Release -Force
-              write-host "  copied $($f.Name)"
-            }
-          }
-
       - name: Pack artifacts
         run: |
-          7z a -snl llama-bin-win-rocm-${{ env.ROCM_VERSION_SHORT }}-${{ matrix.build }}.zip `
-            .\build\bin\Release\ggml-hip.dll `
-            .\build\bin\Release\amdhip64_7.dll `
-            .\build\bin\Release\rocm_kpack.dll `
-            .\build\bin\Release\amd_comgr.dll
+          cp "LICENSE" "build\bin\"
+          7z a -snl llama-bin-win-rocm-${{ env.ROCM_VERSION_SHORT }}-${{ matrix.build }}.zip .\build\bin\*
 
       - name: Upload artifacts
         uses: actions/upload-artifact@v6
@@ -1015,8 +879,6 @@ jobs:
         with:
           key: windows-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}
 
-  # note: builds only the backend library - llama-server (with the embedded UI)
-  #       is injected from the windows-cpu zip during the release "Merge artifacts" step
   windows:
     needs: [check-release]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
@@ -1047,6 +909,13 @@ jobs:
         id: checkout
         uses: actions/checkout@v6
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: Install Vulkan SDK
         id: get_vulkan
         if: ${{ matrix.backend == 'vulkan' }}
@@ -1063,7 +932,7 @@ jobs:
 
       # TODO: these jobs need to use llvm toolchain in order to utilize the ccache
       #- name: ccache
-      #  uses: ggml-org/ccache-action@v1.2.24
+      #  uses: ggml-org/ccache-action@v1.2.21
       #  with:
       #    key: release-windows-2025-${{ matrix.arch }}-${{ matrix.backend }}
 
@@ -1109,8 +978,6 @@ jobs:
           path: llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip
           name: llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip
 
-  # note: builds only the ggml-cuda backend - llama-server is injected from the
-  #       windows-cpu zip during the release "Merge artifacts" step
   windows-cuda:
     name: windows-cuda (${{ matrix.cuda }}, ${{ matrix.arch }})
     needs: [check-release]
@@ -1127,7 +994,7 @@ jobs:
           - cuda: '12.4'
             arch: x64
             defines: '-DGGML_CUDA_CUB_3DOT2=ON'
-          - cuda: '13.4'
+          - cuda: '13.3'
             arch: x64
             defines: ''
           - cuda: '13.4'
@@ -1139,6 +1006,13 @@ jobs:
         id: checkout
         uses: actions/checkout@v6
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: Install Cuda Toolkit
         uses: ./.github/actions/windows-setup-cuda
         with:
@@ -1151,7 +1025,7 @@ jobs:
           choco install ninja
 
       - 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 }}
 
@@ -1210,8 +1084,6 @@ jobs:
         with:
           key: release-windows-2022-${{ matrix.arch }}-cuda-${{ matrix.cuda }}
 
-  # note: builds only the ggml-sycl backend - llama-server is injected from the
-  #       windows-cpu zip during the release "Merge artifacts" step
   windows-sycl:
     needs: [check-release]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
@@ -1246,8 +1118,15 @@ jobs:
           Expand-Archive -Path "level-zero-win-sdk.zip" -DestinationPath "C:/level-zero-sdk" -Force
           "LEVEL_ZERO_V1_SDK_PATH=C:/level-zero-sdk" | Out-File -FilePath $env:GITHUB_ENV -Append
 
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
+
       - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
           key: release-windows-2022-x64-sycl
 
@@ -1316,7 +1195,7 @@ jobs:
           key: release-windows-2022-x64-sycl
 
   ubuntu-24-sycl:
-    needs: [check-release, ui-build]
+    needs: [check-release]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
 
     strategy:
@@ -1358,14 +1237,15 @@ jobs:
           wget -q "https://github.com/oneapi-src/level-zero/releases/download/v${LEVEL_ZERO_VERSION}/level-zero-devel_${LEVEL_ZERO_VERSION}%2B${LEVEL_ZERO_UBUNTU_VERSION}_amd64.deb" -O level-zero-devel.deb
           sudo apt-get install -y ./level-zero.deb ./level-zero-devel.deb
 
-      - name: Download UI build
-        uses: actions/download-artifact@v7
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          name: llama-ui.zip
-          path: tools/ui/dist
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
           key: release-ubuntu-24.04-sycl-${{ matrix.build }}
 
@@ -1407,11 +1287,11 @@ jobs:
         with:
           key: release-ubuntu-24.04-sycl-${{ matrix.build }}
 
-  ubuntu-24-rocm:
-    needs: [check-release, ui-build]
+  ubuntu-22-rocm:
+    needs: [check-release, get-version]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
 
-    runs-on: ubuntu-24.04
+    runs-on: ubuntu-22.04
 
     permissions:
       actions: write
@@ -1419,8 +1299,8 @@ jobs:
     strategy:
       matrix:
         include:
-          - ROCM_VERSION: "10.0.0"
-            gpu_targets: "gfx908;gfx90a;gfx942;gfx950;gfx1010;gfx1011;gfx1012;gfx1030;gfx1031;gfx1032;gfx1033;gfx1034;gfx1035;gfx1036;gfx1100;gfx1101;gfx1102;gfx1103;gfx1150;gfx1151;gfx1152;gfx1200;gfx1201"
+          - ROCM_VERSION: "7.14.0"
+            gpu_targets: "gfx908;gfx90a;gfx942;gfx950;gfx1010;gfx1011;gfx1012;gfx1030;gfx1031;gfx1032;gfx1033;gfx1034;gfx1035;gfx1036;gfx1100;gfx1101;gfx1102;gfx1150;gfx1151;gfx1152;gfx1200;gfx1201"
             build: 'x64'
 
     steps:
@@ -1430,11 +1310,12 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Download UI build
-        uses: actions/download-artifact@v7
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          name: llama-ui.zip
-          path: tools/ui/dist
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Free up disk space
         uses: ggml-org/free-disk-space@v1.3.1
@@ -1442,9 +1323,9 @@ jobs:
           tool-cache: true
 
       - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+        uses: ggml-org/ccache-action@v1.2.21
         with:
-          key: release-ubuntu-24.04-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}
+          key: release-ubuntu-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}
           evict-old-files: 1d
           max-size: "1G"
 
@@ -1473,7 +1354,7 @@ jobs:
           # libraries = HIP runtime and CMake configs needed for linking
           # devel = compilers, headers, static libs
           python -m pip install --upgrade pip
-          python -m pip install --index-url https://stable.repo.amd.com/rocm/whl-next/ "rocm[libraries,devel]==${{ matrix.ROCM_VERSION }}"
+          python -m pip install --index-url https://repo.amd.com/rocm/whl-multi-arch/ "rocm[libraries,devel]==${{ matrix.ROCM_VERSION }}"
 
           # Get ROCm installation paths using the rocm-sdk CLI tool
           ROCM_PATH=$(rocm-sdk path --root)
@@ -1507,6 +1388,7 @@ jobs:
             -DGPU_TARGETS="${{ matrix.gpu_targets }}" \
             -DGGML_HIP=ON \
             -DHIP_PLATFORM=amd \
+            -DHF_UI_VERSION=${{ needs.get-version.outputs.ui_version }} \
             ${{ env.CMAKE_ARGS }}
           cmake --build build --config Release -j $(nproc)
 
@@ -1532,10 +1414,10 @@ jobs:
       - name: ccache-clear
         uses: ./.github/actions/ccache-clear
         with:
-          key: release-ubuntu-24.04-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}
+          key: release-ubuntu-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}
 
   ios-xcode:
-    needs: [check-release]
+    needs: [check-release, get-version]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
     runs-on: macos-26
 
@@ -1563,7 +1445,8 @@ jobs:
             -DLLAMA_BUILD_SERVER=OFF \
             -DCMAKE_SYSTEM_NAME=iOS \
             -DCMAKE_OSX_DEPLOYMENT_TARGET=16.0 \
-            -DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
+            -DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml \
+            -DHF_UI_VERSION=${{ needs.get-version.outputs.ui_version }}
           cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO
 
       - name: xcodebuild for swift package
@@ -1686,9 +1569,11 @@ jobs:
 #          name: llama-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}${{ matrix.use_acl_graph == 'on' && '-aclgraph' || '' }}.tar.gz
 
   ui-build:
-    needs: [check-release]
+    needs: [check-release, get-version]
     if: ${{ needs.check-release.outputs.should_release == 'true' }}
     uses: ./.github/workflows/ui-build.yml
+    with:
+      hf_ui_version: ${{ needs.get-version.outputs.ui_version }}
 
   release:
     if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
@@ -1703,16 +1588,16 @@ jobs:
     runs-on: ubuntu-slim
 
     needs:
+      - get-version
       - windows
       - windows-cpu
       - windows-cuda
       - windows-sycl
       - windows-rocm
       - windows-openvino
-      - ubuntu-24-rocm
+      - ubuntu-22-rocm
       - ubuntu-cpu
       - ubuntu-vulkan
-      - ubuntu-cuda
       - ubuntu-24-openvino
       - ubuntu-24-sycl
       - android-arm64
@@ -1743,27 +1628,24 @@ jobs:
           path: ./artifact
           merge-multiple: true
 
-      - name: Merge artifacts
+      - name: Move artifacts
         id: move_artifacts
         run: |
           mkdir -p release
 
-          # the windows-cpu zip contains the full toolset (llama-server with the embedded
-          # UI, ggml-cpu) - inject it into the other windows zips so that every archive
-          # ships the same binaries, only with a different backend library on top
-          echo "Injecting windows-cpu binaries (llama-server + CPU backend) into the backend zips..."
+          echo "Adding CPU backend files to existing zips..."
           for arch in x64 arm64; do
             cpu_zip="artifact/llama-bin-win-cpu-${arch}.zip"
             temp_dir=$(mktemp -d)
-            echo "Extracting windows-cpu-${arch} package..."
+            echo "Extracting CPU backend for $arch..."
             unzip "$cpu_zip" -d "$temp_dir"
 
-            echo "Merging into $arch zips..."
+            echo "Adding CPU files to $arch zips..."
             for target_zip in artifact/llama-bin-win-*-${arch}.zip; do
               if [[ "$target_zip" == "$cpu_zip" ]]; then
                 continue
               fi
-              echo "Injecting into $(basename "$target_zip")"
+              echo "Adding CPU backend to $(basename "$target_zip")"
               realpath_target_zip=$(realpath "$target_zip")
               (cd "$temp_dir" && zip -r "$realpath_target_zip" .)
             done
@@ -1787,7 +1669,7 @@ jobs:
         id: download_ui
         uses: actions/download-artifact@v7
         with:
-          name: llama-ui.zip
+          name: ui-build
           path: ./ui-dist
 
       - name: Package UI
@@ -1844,10 +1726,7 @@ jobs:
             - [Ubuntu s390x (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-s390x.tar.gz)
             - [Ubuntu x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz)
             - [Ubuntu arm64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-arm64.tar.gz)
-            - [Ubuntu x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-12.8-x64.tar.gz) - [CUDA 12.8 libraries](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-12.8-x64.tar.gz)
-            - [Ubuntu x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-13.3-x64.tar.gz) - [CUDA 13.3 libraries](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-13.3-x64.tar.gz)
-            - [Ubuntu arm64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-13.3-arm64.tar.gz) - [CUDA 13.3 libraries](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-${{ steps.tag.outputs.name }}-bin-ubuntu-cuda-13.3-arm64.tar.gz)
-            - [Ubuntu x64 (ROCm 10.0)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-10.0-x64.tar.gz)
+            - [Ubuntu x64 (ROCm 7.14)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-7.14-x64.tar.gz)
             - [Ubuntu x64 (OpenVINO)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-openvino-${{ needs.ubuntu-24-openvino.outputs.openvino_version }}-x64.tar.gz)
             - [Ubuntu x64 (SYCL FP32)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-sycl-fp32-x64.tar.gz)
             - [Ubuntu x64 (SYCL FP16)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-sycl-fp16-x64.tar.gz)
@@ -1860,12 +1739,12 @@ jobs:
             - [Windows arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cpu-arm64.zip)
             - [Windows arm64 (OpenCL Adreno)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-opencl-adreno-arm64.zip)
             - [Windows x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-12.4-x64.zip) - [CUDA 12.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-12.4-x64.zip)
-            - [Windows x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-13.4-x64.zip) - [CUDA 13.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-13.4-x64.zip)
-            - [Windows arm64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-13.4-arm64.zip) - [CUDA 13.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-13.4-arm64.zip)
+            - [Windows x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-13.3-x64.zip) - [CUDA 13.3 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-13.3-x64.zip)
+            - [Windows arm64 (CUDA 13) (preview)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-13.4-arm64.zip) - [CUDA 13.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-13.4-arm64.zip)
             - [Windows x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-vulkan-x64.zip)
             - [Windows x64 (OpenVINO)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-openvino-${{ needs.windows-openvino.outputs.openvino_version }}-x64.zip)
             - [Windows x64 (SYCL)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-sycl-x64.zip)
-            - [Windows x64 (ROCm 10.0)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-rocm-10.0-x64.zip)
+            - [Windows x64 (ROCm 7.14)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-rocm-7.14-x64.zip)
 
             **openEuler:**
             - [DISABLED](https://github.com/ggml-org/llama.cpp/pull/23705)

.github/workflows/server-sanitize.yml

@@ -32,8 +32,6 @@ on:
     ]
 
 env:
-  # note: this is dud token to avoid rate limiting (https://github.com/ggml-org/llama.cpp/pull/25706#issuecomment-4979941302)
-  HF_TOKEN: ${{ secrets.HF_TOKEN_CI }}
   LLAMA_ARG_LOG_COLORS: 1
   LLAMA_ARG_LOG_PREFIX: 1
   LLAMA_ARG_LOG_TIMESTAMPS: 1
@@ -45,7 +43,7 @@ concurrency:
 
 jobs:
   server:
-    runs-on: hf-jobs-cpu-upgrade
+    runs-on: [self-hosted, CPU, Linux, llama-server]
 
     strategy:
       matrix:
@@ -54,6 +52,20 @@ jobs:
       fail-fast: false
 
     steps:
+      #- name: Dependencies
+      #  id: depends
+      #  run: |
+      #    sudo apt-get update
+      #    sudo apt-get -y install \
+      #      build-essential \
+      #      xxd \
+      #      git \
+      #      cmake \
+      #      curl \
+      #      wget \
+      #      language-pack-en \
+      #      libssl-dev
+
       - name: Clone
         id: checkout
         uses: actions/checkout@v6
@@ -61,23 +73,12 @@ 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 build-essential cmake python3-full
-
-      - name: ccache
-        uses: ggml-org/ccache-action@v1.2.24
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
         with:
-          restore: false
-          save: false
-
-      - name: ccache-buckets-restore
-        uses: ./.github/actions/ccache-buckets
-        with:
-          key: server-sanitize-${{ matrix.sanitizer }}
-          folder: llama.cpp
-          hf_bucket: ggml-org/cache
+          node-version: "24"
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Build
         id: cmake_build
@@ -93,17 +94,9 @@ jobs:
             -DLLAMA_SANITIZE_UNDEFINED=${{ matrix.sanitizer == 'UNDEFINED' }}
           cmake --build build --config ${{ matrix.build_type }} -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: ${{ secrets.HF_TOKEN_CACHE_OUTPUT }}
-        with:
-          key: server-sanitize-${{ matrix.sanitizer }}
-          folder: llama.cpp
-          evict-old-files: 1d
-          hf_bucket: ggml-org/cache
-          save: true
+      - name: Python setup
+        id: setup_python
+        uses: actions/setup-python@v7
 
       - name: Install Python dependencies
         run: |
@@ -116,7 +109,8 @@ jobs:
         run: |
           source .venv/bin/activate
           cd tools/server/tests
-          PYTEST_WORKERS=1 ./tests.sh
+          export ${{ matrix.extra_args }}
+          ./tests.sh
 
       - name: Slow tests
         id: server_integration_tests_slow
@@ -124,4 +118,5 @@ jobs:
         run: |
           source .venv/bin/activate
           cd tools/server/tests
-          PYTEST_WORKERS=1 SLOW_TESTS=1 ./tests.sh
+          export ${{ matrix.extra_args }}
+          SLOW_TESTS=1 ./tests.sh

.github/workflows/server-self-hosted.yml

@@ -72,7 +72,7 @@ jobs:
         run: |
           cd tools/server/tests
           source venv/bin/activate
-          PYTEST_WORKERS=1 ./tests.sh
+          ./tests.sh
 
       - name: Tests (GPUx1, backend-sampling)
         id: server_integration_tests_backend_sampling
@@ -81,7 +81,7 @@ jobs:
           cd tools/server/tests
           source venv/bin/activate
           export LLAMA_ARG_BACKEND_SAMPLING=1
-          PYTEST_WORKERS=1 ./tests.sh
+          ./tests.sh
 
       - name: Tests (GPUx2)
         id: server_integration_tests_gpu2
@@ -90,7 +90,7 @@ jobs:
           cd tools/server/tests
           source venv/bin/activate
           export GGML_METAL_DEVICES=2
-          PYTEST_WORKERS=1 ./tests.sh
+          ./tests.sh
 
       - name: Tests (GPUx2, backend-sampling)
         id: server_integration_tests_gpu2_backend_sampling
@@ -99,10 +99,10 @@ jobs:
           cd tools/server/tests
           source venv/bin/activate
           export GGML_METAL_DEVICES=2 LLAMA_ARG_BACKEND_SAMPLING=1
-          PYTEST_WORKERS=1 ./tests.sh
+          ./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: |
@@ -162,7 +132,7 @@ jobs:
         run: |
           cd tools/server/tests
           source venv/bin/activate
-          PYTEST_WORKERS=1 ./tests.sh
+          ./tests.sh
 
       - name: Tests (GPUx1, backend-sampling)
         id: server_integration_tests_backend_sampling
@@ -171,7 +141,7 @@ jobs:
           cd tools/server/tests
           source venv/bin/activate
           export LLAMA_ARG_BACKEND_SAMPLING=1
-          PYTEST_WORKERS=1 ./tests.sh
+          ./tests.sh
 
       - name: Tests (GPUx2)
         id: server_integration_tests_gpu2
@@ -180,7 +150,7 @@ jobs:
           cd tools/server/tests
           source venv/bin/activate
           export GGML_CUDA_DEVICES=2
-          PYTEST_WORKERS=1 ./tests.sh
+          ./tests.sh
 
       - name: Tests (GPUx2, backend-sampling)
         id: server_integration_tests_gpu2_backend_sampling
@@ -189,10 +159,10 @@ jobs:
           cd tools/server/tests
           source venv/bin/activate
           export GGML_CUDA_DEVICES=2 LLAMA_ARG_BACKEND_SAMPLING=1
-          PYTEST_WORKERS=1 ./tests.sh
+          ./tests.sh
 
   server-kleidiai:
-    runs-on: ah-ubuntu_24_04-c8g_8x
+    runs-on: ah-ubuntu_22_04-c8g_8x
 
     steps:
       - name: Clone
@@ -232,7 +202,7 @@ jobs:
       - name: Build
         id: cmake_build
         run: |
-          cmake -B build -DGGML_SCHED_NO_REALLOC=ON -DGGML_CPU_KLEIDIAI=ON -DLLAMA_FATAL_WARNINGS=ON
+          cmake -B build -DGGML_SCHED_NO_REALLOC=ON -DGGML_CPU_KLEIDIAI=ON
           cmake --build build --config Release -j $(nproc) --target llama-server
 
       - name: Python setup

.github/workflows/server.yml

@@ -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' }}

.github/workflows/ui-build-self-hosted.yml

@@ -17,9 +17,8 @@ jobs:
         uses: actions/setup-node@v6
         with:
           node-version: "24"
-          # cache: "npm"
-          # cache-dependency-path: "tools/ui/package-lock.json"
-          package-manager-cache: false
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Install dependencies
         run: npm ci
@@ -32,6 +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

.github/workflows/ui-build.yml

@@ -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
 
@@ -17,25 +17,13 @@ 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
         with:
           node-version: "24"
-          # cache: "npm"
-          # cache-dependency-path: "tools/ui/package-lock.json"
-          package-manager-cache: false
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Install dependencies
         run: npm ci
@@ -43,7 +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
 
@@ -54,6 +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

.github/workflows/ui-publish.yml

@@ -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

.github/workflows/ui-self-hosted.yml

@@ -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

.github/workflows/ui.yml

@@ -57,14 +57,13 @@ jobs:
         uses: actions/setup-node@v6
         with:
           node-version: "24"
-          # cache: "npm"
-          # cache-dependency-path: "tools/ui/package-lock.json"
-          package-manager-cache: false
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - 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
@@ -115,9 +114,8 @@ jobs:
         uses: actions/setup-node@v6
         with:
           node-version: "24"
-          # cache: "npm"
-          # cache-dependency-path: "tools/ui/package-lock.json"
-          package-manager-cache: false
+          cache: "npm"
+          cache-dependency-path: "tools/ui/package-lock.json"
 
       - name: Install dependencies
         id: setup
@@ -128,7 +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

.pi/gg/SYSTEM.md

@@ -6,7 +6,6 @@ General:
 - 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
-- When [MODEL] is needed, first try to get it from the `PI_MODEL_NAME` env var before asking the user
 
 Coding:
 - When in doubt, always refer to the CONTRIBUTING.md file of the project
@@ -21,9 +20,8 @@ Pull requests (PRs):
 - 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]"
-- If `PI_MODEL_NAME` env var is not set, ask the user to tell you what model was used and write it in place of [MODEL]
+- Ask the user to tell you what model was used and write it in place of [MODEL]
 - Always create the pull requests in draft mode
-- Never reply to review comments or post comments on issues/PRs without explicit permission from the user
 
 Commits:
 - On every commit that you make, include a "Assisted-by: pi:llama.cpp/[MODEL]" tag

AUTHORS

@@ -1,4 +1,4 @@
-# date: Fri Sep  4 10:06:46 EEST 2026
+# date: Tue Aug 18 14:32:43 EEST 2026
 # this file is auto-generated by scripts/gen-authors.sh
 
 Нияз Гарифзянов <112617865+garrnizon@users.noreply.github.com>
@@ -46,7 +46,6 @@ Abhijit Ramesh <abhijitramesh2k@gmail.com>
 abhijitb11 <113058133+abhijitb11@users.noreply.github.com>
 Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
 Abhinay Krishna <abhinaykrishna60@gmail.com>
-Abhiram <78226909+geckguy@users.noreply.github.com>
 Abhishek Gopinath K <31348521+overtunned@users.noreply.github.com>
 abotsis <github@bots.is>
 Abraham Gonzalez <theabecaster0@gmail.com>
@@ -88,7 +87,6 @@ akleine <alb.kleine@gmx.de>
 Al G <toasting@gmail.com>
 Al Mochkin <14274697+amochkin@users.noreply.github.com>
 Alan Gray <agray3@users.noreply.github.com>
-Alan Tseng <alanhc.tseng1999@gmail.com>
 Alawode Oluwandabira <dabiraalawode@yahoo.com>
 Albert Jin <albert.jin@gmail.com>
 Alberto <57916483+albbus-stack@users.noreply.github.com>
@@ -138,9 +136,7 @@ alonfaraj <alonfaraj@gmail.com>
 AlpinDale <52078762+AlpinDale@users.noreply.github.com>
 alwqx <kenan3015@gmail.com>
 Aman <amangupta052@gmail.com>
-Aman Chadha(IVIXMMI) <79802170+ac-mmi@users.noreply.github.com>
 Aman Gupta <amangupta052@gmail.com>
-Aman Karki <itsamankarki@gmail.com>
 amd-dwang <dong.wang@amd.com>
 amd-lalithnc <lalithnc@amd.com>
 Amir <amir_zia@outlook.com>
@@ -191,7 +187,6 @@ Anton Mitkov <anton.mitkov@codeplay.com>
 Antonis Makropoulos <benuix@gmail.com>
 Anudit Nagar <nagaranudit@gmail.com>
 Anuj Attri <anujattri01@gmail.com>
-anujj <ajalota@nvidia.com>
 anzz1 <anzz1@live.com>
 Aparna M P <aparmp@qti.qualcomm.com>
 Aparna M P <quic_aparmp@quicinc.com>
@@ -201,7 +196,6 @@ arch-btw <57669023+arch-btw@users.noreply.github.com>
 arcrank <arcrank@gmail.com>
 ardfork <134447697+ardfork@users.noreply.github.com>
 Arik Poznanski <arikpoz@users.noreply.github.com>
-Aritro Bandyopadhyay <71339004+AriBandyo@users.noreply.github.com>
 arlo-phoenix <140345165+arlo-phoenix@users.noreply.github.com>
 Armen Kaleshian <kriation@users.noreply.github.com>
 Arsen Arutunan <58118221+limloop@users.noreply.github.com>
@@ -236,7 +230,6 @@ bandoti <141645996+bandoti@users.noreply.github.com>
 Bar Haim <barvhaim@gmail.com>
 BarfingLemurs <128182951+BarfingLemurs@users.noreply.github.com>
 Bart Louwers <bart.louwers@gmail.com>
-Bartosz Taudul <wolf@nereid.pl>
 Bartowski <3266127+bartowski1182@users.noreply.github.com>
 Bartowski <ckealty1182@gmail.com>
 Bas Nijholt <basnijholt@gmail.com>
@@ -284,7 +277,6 @@ Bono Lv <lvscar@users.noreply.github.com>
 Borislav Stanimirov <b.stanimirov@abv.bg>
 Borislav Stanimirov <b@ibob.bg>
 Bowen Han <fancycode@gmail.com>
-Brad Smith <1472326+infinitewarp@users.noreply.github.com>
 Branden Butler <bwtbutler@hotmail.com>
 Brandon Squizzato <35474886+bsquizz@users.noreply.github.com>
 Brian <mofosyne@gmail.com>
@@ -295,7 +287,6 @@ Bryan Honof <bryanhonof@gmail.com>
 bryanSwk <93190252+bryanSwk@users.noreply.github.com>
 bsilvereagle <bsilvereagle@users.noreply.github.com>
 bssrdf <merlintiger@hotmail.com>
-Buğra Özgürsoy <13810383+ozgursoy@users.noreply.github.com>
 byte-6174 <88070277+byte-6174@users.noreply.github.com>
 Caleb DeLeeuw <143902425+SolshineCode@users.noreply.github.com>
 Calvin Laurenson <calvin@laurenson.dev>
@@ -335,7 +326,6 @@ Chenguang Li <757486878@qq.com>
 Chenguang Li <87689256+noemotiovon@users.noreply.github.com>
 Chipmunk <101038159+CHIPMUNK-T0T@users.noreply.github.com>
 chiranko <96988916+chiranko@users.noreply.github.com>
-Chris Danis <cdanis@gmail.com>
 Chris Elrod <elrodc@gmail.com>
 Chris Kuehl <ckuehl@ckuehl.me>
 Chris Lee <clee@mg8.org>
@@ -366,7 +356,6 @@ clyang <clyang@clyang.net>
 cmdr2 <secondary.cmdr2@gmail.com>
 cmdr2 <shashank.shekhar.global@gmail.com>
 cocktailpeanut <121128867+cocktailpeanut@users.noreply.github.com>
-codemonkey <441345965@qq.com>
 codezjx <code.zjx@gmail.com>
 coezbek <c.oezbek@gmail.com>
 comex <comexk@gmail.com>
@@ -378,8 +367,6 @@ Copilot <198982749+Copilot@users.noreply.github.com>
 Corentin REGAL <corentin.regal@gmail.com>
 cphlipot <9103367+cphlipot@users.noreply.github.com>
 cpumaxx <163466046+cpumaxx@users.noreply.github.com>
-cqderek <cqderek@gmail.com>
-cqderek <cqiang@qti.qualcomm.com>
 crasm <crasm@git.vczf.net>
 crasm <crasm@git.vczf.us>
 crat0z <11581854+crat0z@users.noreply.github.com>
@@ -440,7 +427,6 @@ DavidKorczynski <david@adalogics.com>
 davidrhodus <david@vacovideo.com>
 Dawid Potocki <github@dawidpotocki.com>
 Dawid Wysocki <62249621+TortillaZHawaii@users.noreply.github.com>
-Daya Adianto <addianto@users.noreply.github.com>
 ddh0 <chemist-mulches-39@icloud.com>
 ddh0 <dylanhalladay02@icloud.com>
 ddpasa <112642920+ddpasa@users.noreply.github.com>
@@ -477,7 +463,6 @@ Dmytro Romanov <casteldazur@gmail.com>
 Dobri Danchev <12420863+danchev@users.noreply.github.com>
 DocShotgun <126566557+DocShotgun@users.noreply.github.com>
 Doctor Shotgun <126566557+DocShotgun@users.noreply.github.com>
-Dominik Pantaleoni <95251853+dpantaleoni@users.noreply.github.com>
 Don Mahurin <dmahurin@users.noreply.github.com>
 Dong Won Kim <63934649+ddwkim@users.noreply.github.com>
 Donghyeon Jeong <54725479+djeong20@users.noreply.github.com>
@@ -519,7 +504,6 @@ Emmanuel Ferdman <emmanuelferdman@gmail.com>
 Emreerdog <34742675+Emreerdog@users.noreply.github.com>
 Engininja2 <139037756+Engininja2@users.noreply.github.com>
 Equim <sayaka@ekyu.moe>
-Eric A Stalee <87948564+Eric-A-Stalee@users.noreply.github.com>
 Eric Curtin <ecurtin@redhat.com>
 Eric Curtin <eric.curtin@docker.com>
 Eric Curtin <ericcurtin17@gmail.com>
@@ -535,7 +519,6 @@ Esko Toivonen <eskot98@gmail.com>
 Ethan Turner <eturner64@gmail.com>
 Ettore Di Giacinto <mudler@users.noreply.github.com>
 EugeoSynthesisThirtyTwo <gabriel.dhimoila@gmail.com>
-Eurekatic <eurekatic@eurekatic.eu>
 Evan Huus <eapache@gmail.com>
 Evan Jones <evan.q.jones@gmail.com>
 Evan Miller <emmiller@gmail.com>
@@ -694,7 +677,6 @@ HimariO <dsfhe49854@gmail.com>
 hipudding <huafengchun@gmail.com>
 Hitesh Chopra <34310832+hiteshchopra11@users.noreply.github.com>
 hksdpc255 <43977088+hksdpc255@users.noreply.github.com>
-hmirin <hmirin@users.noreply.github.com>
 hmscider <201289679+hmscider@users.noreply.github.com>
 Hoang Nguyen <hugo53@users.noreply.github.com>
 hoangmit <hoangmit@users.noreply.github.com>
@@ -719,7 +701,6 @@ Huawei Lin <huaweilin.cs@gmail.com>
 Hugo <hugo@whynothugo.nl>
 Hugo Roussel <hugo.rous@gmail.com>
 Huifeng Ou <79071290+ho2103@users.noreply.github.com>
-HumerousGorgon <31957201+HumerousGorgon@users.noreply.github.com>
 hutli <6594598+hutli@users.noreply.github.com>
 hutli <hutli@hutli.hu>
 hutli <jensstaermose@hotmail.com>
@@ -757,15 +738,12 @@ intelmatt <61025942+intelmatt@users.noreply.github.com>
 iohub <rickyang.pro@gmail.com>
 Ionoclast Laboratories <brigham@ionoclast.com>
 iron <lizhenneng@gmail.com>
-Isaac <34376531+init-22@users.noreply.github.com>
 Isaac McFadyen <isaac@imcf.me>
 IsaacDynamo <61521674+IsaacDynamo@users.noreply.github.com>
 Ishaan Gandhi <Ishaangandhi@gmail.com>
 iSma <ismail.senhaji@gmail.com>
 Ismail <115064057+AlrIsmail@users.noreply.github.com>
 issixx <46835150+issixx@users.noreply.github.com>
-itsnotoger <19309683+itsnotoger@users.noreply.github.com>
-itterative <190138728+itterative@users.noreply.github.com>
 Ivan <nekotekina@gmail.com>
 Ivan Chikish <nekotekina@gmail.com>
 Ivan Filipov <159561759+vanaka11@users.noreply.github.com>
@@ -790,7 +768,6 @@ Jakkala Mahesh <155058658+MaheshJakkala@users.noreply.github.com>
 Jakub N <jakubniemczyk97@gmail.com>
 JamePeng <jame_peng@sina.com>
 James A Capozzoli <157492257+jac-jim@users.noreply.github.com>
-James Francis <6763899+JamesFranc@users.noreply.github.com>
 James O'Leary <65884233+jpohhhh@users.noreply.github.com>
 James Reynolds <magnusviri@users.noreply.github.com>
 jameswu2014 <545426914@qq.com>
@@ -821,7 +798,6 @@ Jed Fox <git@jedfox.com>
 Jeff Bolz <jbolz@nvidia.com>
 Jeffrey Morgan <jmorganca@gmail.com>
 Jeffrey Quesnelle <emozilla@nousresearch.com>
-Jeremie Miller <jeremie.miller@gmail.com>
 Jeremy Demeule <jdemeule@users.noreply.github.com>
 Jeremy Rand <244188+JeremyRand@users.noreply.github.com>
 Jeroen Mostert <jeroen.mostert@cm.com>
@@ -833,7 +809,6 @@ Jesse Jojo Johnson <williamsaintgeorge@gmail.com>
 Jesse LaRose <jesse@taey.ai>
 Jesse Posner <jesse.posner@gmail.com>
 Jesus Talavera <145992175+jesus-talavera-ibm@users.noreply.github.com>
-Jetson Tan <tanzongyouyi@outlook.com>
 Jett Janiak <jettjaniak@gmail.com>
 Jeximo <jeximo@gmail.com>
 JFLFY2255 <JFLFY2255@163.com>
@@ -850,7 +825,6 @@ Jie Fu (傅杰) <jiefu@tencent.com>
 jiez <373447296@qq.com>
 Jillis ter Hove <j.terhove@gmail.com>
 Jim Wu <jimw567@users.noreply.github.com>
-Jingxin (Philip) Li <philipaslee@gmail.com>
 Jinwoo Jeong <33892306+williamjeong2@users.noreply.github.com>
 Jinyang He <hejinyang@loongson.cn>
 jinzihao <jinzihao1996@gmail.com>
@@ -876,13 +850,11 @@ John Balis <phobossystems@gmail.com>
 John Bean <113509988+johnbean393@users.noreply.github.com>
 John Eismeier <42679190+jeis4wpi@users.noreply.github.com>
 John Smith <67539080+kingsidelee@users.noreply.github.com>
-John-Henry Lim <42513874+Interpause@users.noreply.github.com>
 Johnathan Craig Maudlin <13183098+jcmdln@users.noreply.github.com>
 JohnnyB <jboero@users.noreply.github.com>
 johnson442 <56517414+johnson442@users.noreply.github.com>
 jojorne <jojorne@users.noreply.github.com>
 jon-chuang <9093549+jon-chuang@users.noreply.github.com>
-Jonas J <111707981+John-194@users.noreply.github.com>
 Jonas Jankaitis <111707981+John-194@users.noreply.github.com>
 Jonas Wunderlich <32615971+jonas-w@users.noreply.github.com>
 Jonathan <47618606+jbuchananr@users.noreply.github.com>
@@ -952,7 +924,6 @@ Karsten Weiss <knweiss@gmail.com>
 Karthick <j.karthic2004@gmail.com>
 Karthik Kumar Viswanathan <195178+guilt@users.noreply.github.com>
 Karthik Sethuraman <k.seth1993@gmail.com>
-Kartik Gulia <kgulia@nvidia.com>
 Kartik Sirohi <99896785+sirohikartik@users.noreply.github.com>
 Kashif Rasul <kashif.rasul@gmail.com>
 KASR <karim.asrih@gmail.com>
@@ -960,7 +931,6 @@ Kasumi <90275229+kasumi-1@users.noreply.github.com>
 Katostrofik <georgiopapairo@gmail.com>
 katsu560 <118887472+katsu560@users.noreply.github.com>
 Kawrakow <48489457+ikawrakow@users.noreply.github.com>
-kbenkhaled <khalilbenkhaled01@gmail.com>
 kchro3 <62481661+kchro3@users.noreply.github.com>
 kdkd <2569413+kdkd@users.noreply.github.com>
 Keiichi Tabata <keiichi.tabata@outlook.com>
@@ -969,7 +939,6 @@ Kenvix ⭐ <kenvixzure@live.com>
 Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
 Kevin Gibbons <bakkot@gmail.com>
 Kevin Hannon <kehannon@redhat.com>
-Kevin Hopper <93635715+kh0pper@users.noreply.github.com>
 Kevin Ji <1146876+kevinji@users.noreply.github.com>
 Kevin Kwok <antimatter15@gmail.com>
 Kevin Liu <4396kevinliu@gmail.com>
@@ -995,14 +964,12 @@ Konstantin Herud <konstantin.herud@denkbares.com>
 Konstantin Zhuravlyov <konstantin.zhuravlyov@amd.com>
 Krishna Sridhar <99914379+srikris-sridhar@users.noreply.github.com>
 krystiancha <krystian@krystianch.com>
-krzsztf <krzysztof@witkowscy.org>
 kubawoo <k-wach@o2.pl>
 kumaal <44551860+kumaal@users.noreply.github.com>
 kunal-vaishnavi <115581922+kunal-vaishnavi@users.noreply.github.com>
 kunnis <kunnis@users.noreply.github.com>
 Kunshang Ji <kunshang.ji@intel.com>
 kuronekosaiko <EvanChanJ@163.com>
-kurquhar <kurquhar@qti.qualcomm.com>
 Kusha Gharahi <3326002+kushagharahi@users.noreply.github.com>
 kustaaya <58045274+kustaaya@users.noreply.github.com>
 kuvaus <22169537+kuvaus@users.noreply.github.com>
@@ -1014,7 +981,6 @@ Kyle Liang <liangmanlai@gmail.com>
 Kyle Mistele <kyle@mistele.com>
 KyleHagy <59183061+KyleHagy@users.noreply.github.com>
 Kylin <56434533+KyL0N@users.noreply.github.com>
-Kyozzz <1147385157@qq.com>
 l-austenfeld <53152202+l-austenfeld@users.noreply.github.com>
 l3utterfly <gc.pthzfoldr@gmail.com>
 l8bloom <l8bloomapi@gmail.com>
@@ -1026,7 +992,6 @@ Lars Sonchocky-Helldorf <lars.sonchocky-helldorf@hamburg.de>
 las7 <98077186+las7@users.noreply.github.com>
 Lasse Lauwerys <65569591+Iemand005@users.noreply.github.com>
 Laura <Tijntje_7@msn.com>
-Laurent Zuijdwijk <laurent.zuijdwijk@gmail.com>
 Law Po Ying <30721578+yingying0906@users.noreply.github.com>
 lcy <lcy0321@users.noreply.github.com>
 ldwang <ftgreat@163.com>
@@ -1074,8 +1039,6 @@ Ludovic Henry <git@ludovic.dev>
 Ludovic Henry <ludovic@rivosinc.com>
 Lukas Straub <lukasstraub2@web.de>
 Łukasz Ślusarczyk <112692748+lslusarczyk@users.noreply.github.com>
-Lukasz Stolcman <4583553+lstolcman@users.noreply.github.com>
-LunalFresh <165352784+LunalFresh@users.noreply.github.com>
 Luo Tian <lt@basecity.com>
 luoyu-intel <yu.luo@intel.com>
 luyhcsu <110711054+luyhcsu@users.noreply.github.com>
@@ -1091,7 +1054,6 @@ Maarten ter Huurne <maarten@treewalker.org>
 Maciej Lisowski <39798354+MaciejDromin@users.noreply.github.com>
 Mack Straight <eiz@users.noreply.github.com>
 maddes8cht <55592906+maddes8cht@users.noreply.github.com>
-Mads Marquart <mads@marquart.dk>
 Maël Kerbiriou <m431.kerbiriou@gmail.com>
 MaggotHATE <clay1326@gmail.com>
 MagicExists <106458387+gugugiyu@users.noreply.github.com>
@@ -1253,8 +1215,6 @@ Naco Siren <naco-siren@users.noreply.github.com>
 Nam D. Tran <42194884+namtranase@users.noreply.github.com>
 nanahi <130121847+na-na-hi@users.noreply.github.com>
 Nathan Epstein <nate2@umbc.edu>
-Nathan Wilson <67372905+Nathanw1014@users.noreply.github.com>
-Nathanw1014 <67372905+Nathanw1014@users.noreply.github.com>
 Natsu <chino@hotococoa.moe>
 Nauful Shaikh <nauful@gmail.com>
 NawafAlansari <72708095+NawafAlansari@users.noreply.github.com>
@@ -1277,7 +1237,6 @@ niansa/tuxifan <tuxifan@posteo.de>
 Nicholai Tukanov <nicholaitukanov@gmail.com>
 Nicholas Sparks <157740354+nisparks@users.noreply.github.com>
 Nick <0x0b4ac@gmail.com>
-Nick Farrell <nick.farrell@aiven.io>
 nick huang <nickhuang99@hotmail.com>
 Nick Lafleur <55208706+nicklafleur@users.noreply.github.com>
 Nick Towle <ntowle@gmail.com>
@@ -1300,7 +1259,6 @@ NikolaiLyssogor <59844691+NikolaiLyssogor@users.noreply.github.com>
 Nikolaos Pothitos <pothitos@di.uoa.gr>
 Nikolas <127742645+nneubacher@users.noreply.github.com>
 Nikolay Popov <131475237+npopov-vst@users.noreply.github.com>
-Nils Gladitz <nilsgladitz@gmail.com>
 Nindaleth <Nindaleth@users.noreply.github.com>
 ningshanwutuobang <ningshanwutuobang@gmail.com>
 Noah <99681487+NoahOksuz@users.noreply.github.com>
@@ -1397,7 +1355,6 @@ Pop Flamingo <trevor.annedenise@icloud.com>
 postmasters <namnguyen@google.com>
 Pouya <PooyaGhahramanian@Gmail.com>
 pqnet <119850+pqnet@users.noreply.github.com>
-Prabhsimran Singh <pskrunner14@gmail.com>
 Prabod <prabod@maincode.com>
 Prajwal B Mehendarkar <prajwal.b.mehendarkar@ibm.com>
 Pranav Dhinakar <pdhinaka@qti.qualcomm.com>
@@ -1421,7 +1378,6 @@ qouoq <qouoq@fastmail.com>
 Qu Zongfu <43257352+yancaoweidaode@users.noreply.github.com>
 quei <56998528+quei4r@users.noreply.github.com>
 Quentin Bramas <quentin.bramas@gmail.com>
-QuintinShaw <github@xyt.email>
 QuintinShaw <yx6f20@soton.ac.uk>
 qunash <anzoria@gmail.com>
 quyentonndbs <raynaedgar8677@outlook.com>
@@ -1506,7 +1462,6 @@ robertomeroni <150194833+robertomeroni@users.noreply.github.com>
 Robey Holderith <robey@flaminglunchbox.net>
 Robin Davidsson <40024429+R-Dson@users.noreply.github.com>
 Robyn <robyngraf@users.noreply.github.com>
-Rock Chen <rockchen.tw@gmail.com>
 Rőczey Barnabás <31726601+An0nie@users.noreply.github.com>
 RodriMora <bullerwins@gmail.com>
 Roger Chen <chenrui@gmail.com>
@@ -1544,21 +1499,17 @@ runfuture <runfuture@users.noreply.github.com>
 RunningLeon <maningsheng@sensetime.com>
 RunningLeon <mnsheng@yeah.net>
 Russyyds <161207317+Russyyds@users.noreply.github.com>
-Ryan C <ryan5rdx@users.noreply.github.com>
 Ryan Goulden <percontation@gmail.com>
 Ryan Landay <rlanday@gmail.com>
 Ryan Mangeno <160974989+ryan-mangeno@users.noreply.github.com>
 Ryder Wishart <ryderwishart@gmail.com>
 Ryuei <louixs@users.noreply.github.com>
 s-goto-11 <206795233+s-goto-11@users.noreply.github.com>
-s0mecode <213953308+s0mecode@users.noreply.github.com>
 s8322 <s0527684199@gmail.com>
-Saad Ali <NIXKnight@users.noreply.github.com>
 Saba Fallah <10401143+sfallah@users.noreply.github.com>
 Saba Fallah <sabafallah@gmail.com>
 Sachin Desai <smdesai@gmail.com>
 Sachin Sharma <sachin@zettabolt.com>
-Safi Ullah <safiullah.3915@gmail.com>
 safranowith <bsh155762@gmail.com>
 SakuraUmi <yukinon244@gmail.com>
 Salvador E. Tropea <stropea@inti.gob.ar>
@@ -1601,7 +1552,6 @@ Sergey Alirzaev <l29ah@riseup.net>
 Sergey Alirzaev <zl29ah@gmail.com>
 Sergey Fedorov <vital.had@gmail.com>
 Sergey Malinin <sergmalinin@gmail.com>
-Sergey Sklyarov <sergey.sklyarov@gmail.com>
 Sergio López <slp@redhat.com>
 Sergio López <slp@sinrega.org>
 Sergiu <8598216+mzsergiu@users.noreply.github.com>
@@ -1632,13 +1582,11 @@ Shawn Gu <shawngu@qti.qualcomm.com>
 Shawn yang <137684499+Yangxiaoz@users.noreply.github.com>
 Shelby Jenkins <47464908+ShelbyJenkins@users.noreply.github.com>
 Sheldon Robinson <sheldon.robinson@live.com>
-Shenghan Yang <ysharke@sjtu.edu.cn>
 shibe2 <shibe@tuta.io>
 Shijie <821898965@qq.com>
 Shin-myoung-serp <relent95@naver.com>
 Shintarou Okada <kokuzen@gmail.com>
 shivamkumard-ctrl <shivamkumard@nvidia.com>
-Shobhit <sobhit.me@gmail.com>
 Shouyu <65317431+joeldushouyu@users.noreply.github.com>
 Shouzheng Liu <61452103+lshzh-ww@users.noreply.github.com>
 Shouzheng Liu <lshzh.hi@gmail.com>
@@ -1659,7 +1607,6 @@ Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
 Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
 simevo <github@simevo.com>
 Simon Redman <simon@ergotech.com>
-Simon Teixidor <simon@flaskpost.me>
 Simon Willison <swillison@gmail.com>
 simon886212 <37953122+simon886212@users.noreply.github.com>
 Simranjeet Singh <105192966+simrnsingh@users.noreply.github.com>
@@ -1716,7 +1663,6 @@ stevenkuang <stevenkuang@tencent.com>
 Steward Garcia <57494570+FSSRepo@users.noreply.github.com>
 StrangeBytesDev <141275258+StrangeBytesDev@users.noreply.github.com>
 strawberrymelonpanda <152940198+strawberrymelonpanda@users.noreply.github.com>
-Strongtut <Strongtut@users.noreply.github.com>
 Suaj Carrot <72162667+SuajCarrot@users.noreply.github.com>
 sudhiarm <sudhi.sathyavathy@arm.com>
 Sukriti Sharma <Ssukriti@users.noreply.github.com>
@@ -1741,7 +1687,6 @@ Tamar <Tamar0812@outlook.co.il>
 tamarPal <tamarp3385@gmail.com>
 Tameem <113388789+AhmadTameem@users.noreply.github.com>
 Tamotsu Takahashi <ttakah+github@gmail.com>
-Tanner Bruhn <66120666+tannerbruhn@users.noreply.github.com>
 tarcey <cey.tarik@gmail.com>
 Tarek Dakhran <t.dakhran@gmail.com>
 Tarek Dakhran <tarek@liquid.ai>
@@ -1751,7 +1696,6 @@ Taylor <quantumtraveling@gmail.com>
 tc-mb <157115220+tc-mb@users.noreply.github.com>
 TecJesh <qdvm5gl@163.com>
 Tei Home <taiteitonghome@proton.me>
-Tekin Ertekin <tekin.ertekin@gmail.com>
 Tekin Ertekin <tekinertekin@gmail.com>
 tempstudio <49735574+tempstudio@users.noreply.github.com>
 teo <TeoZosa@users.noreply.github.com>
@@ -1793,7 +1737,6 @@ Ting Lou <louting@189.cn>
 Ting Lou <ting.lou@gmail.com>
 Ting Sun <suntcrick@gmail.com>
 Titaniumtown <titaniumtown@proton.me>
-Tiwei Bie <tiwei.btw@antgroup.com>
 tjohnman <tjohnman@users.noreply.github.com>
 Tobias Lütke <tobi@shopify.com>
 Toby <25832191+aetherbird@users.noreply.github.com>
@@ -1870,7 +1813,6 @@ Vishal Agarwal <vishalagarwal.jss@gmail.com>
 Vishal Singh <vishal@zettabolt.com>
 Vitali Lovich <vlovich+github@gmail.com>
 Vivian <vynride@gmail.com>
-vk <89937361+itsvedantkumar@users.noreply.github.com>
 Vlad <spitfireage@gmail.com>
 Vladimir <bogdad@gmail.com>
 Vladimir Malyutin <first-leon@yandex.ru>
@@ -1955,7 +1897,6 @@ Yaiko <elyaiko@hotmail.com>
 Yakine Tahtah <96926916+ReinforcedKnowledge@users.noreply.github.com>
 YangLe <smilingpoplar@gmail.com>
 yangli2 <yangli2@gmail.com>
-Yaniss Amazouz <yaniss91600@gmail.com>
 Yann Follet <131855179+YannFollet@users.noreply.github.com>
 Yanzhao Wang <yanzhaow@qti.qualcomm.com>
 Yarden Tal <yardent@qti.qualcomm.com>

CMakeLists.txt

@@ -4,8 +4,8 @@ include(CheckIncludeFileCXX)
 
 ### llama.cpp version
 set(LLAMA_VERSION_MAJOR 0)
-set(LLAMA_VERSION_MINOR 4)
-set(LLAMA_VERSION_PATCH 1)
+set(LLAMA_VERSION_MINOR 2)
+set(LLAMA_VERSION_PATCH 0)
 set(LLAMA_VERSION_BASE "${LLAMA_VERSION_MAJOR}.${LLAMA_VERSION_MINOR}.${LLAMA_VERSION_PATCH}")
 
 # whether this is a development/nightly build
@@ -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)
@@ -197,16 +197,6 @@ llama_option_depr(WARNING     LLAMA_CURL)
 include("cmake/license.cmake")
 license_add_file("llama.cpp" "LICENSE")
 
-#
-# compile options
-#
-
-# clang stores the modification time of the precompiled header sources inside the
-# header and rejects it when they differ, so the timestamp is left out of it
-add_compile_options(
-    "$<$<COMPILE_LANG_AND_ID:C,Clang,IntelLLVM>:SHELL:-Xclang -fno-pch-timestamp>"
-    "$<$<COMPILE_LANG_AND_ID:CXX,Clang,IntelLLVM>:SHELL:-Xclang -fno-pch-timestamp>")
-
 #
 # 3rd-party
 #

CODEOWNERS

@@ -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

CONTRIBUTING.md

@@ -20,8 +20,8 @@ If AI is used to generate any portion of the code, contributors must adhere to t
 
 1. Explicitly disclose the manner in which AI was employed.
 2. Check for an existing PR addressing the same change; if one exists, comment there to work with its author instead of opening a duplicate.
-3. Perform a comprehensive manual review prior to submitting the pull request. A proper code review usually takes something like one hour per 200-400 LOC and you should be spending **at least that much time on code review alone**.
-4. Be prepared to explain every line of code you submit when asked about it by a maintainer.
+3. Perform a comprehensive manual review prior to submitting the pull request.
+4. Be prepared to explain every line of code they submitted when asked about it by a maintainer.
 5. It is strictly prohibited to use AI to write your posts for you (bug reports, feature requests, pull request descriptions, Github discussions, responding to humans, ...).
 
 For more info, please refer to the [AGENTS.md](AGENTS.md) 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.

README.md

@@ -13,7 +13,7 @@
 [![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)
 
-[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 +74,7 @@ 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 |

app/CMakeLists.txt

@@ -16,7 +16,7 @@ target_link_libraries(${TARGET} PRIVATE
 target_compile_features(${TARGET} PRIVATE cxx_std_17)
 
 # Automatically add all files from the 'licenses' directory
-file(GLOB EXTRA_LICENSES "${PROJECT_SOURCE_DIR}/licenses/LICENSE-*")
+file(GLOB EXTRA_LICENSES "${CMAKE_SOURCE_DIR}/licenses/LICENSE-*")
 
 foreach(FILE_PATH ${EXTRA_LICENSES})
     get_filename_component(FILE_NAME "${FILE_PATH}" NAME)

app/llama.cpp

@@ -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;
 }
 

build-xcframework.sh

@@ -18,7 +18,7 @@ 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
 
@@ -169,14 +169,6 @@ 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 > ${module_path}module.modulemap << EOF
 framework module llama {
@@ -458,7 +450,6 @@ build_ios_sim() {
         -DIOS=ON \
         -DCMAKE_SYSTEM_NAME=iOS \
         -DCMAKE_OSX_SYSROOT=iphonesimulator \
-        -DGGML_METAL_TARGET_OS=ios \
         -DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
         -DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=iphonesimulator \
         -DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
@@ -476,7 +467,6 @@ build_ios_device() {
         -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}" \
@@ -508,7 +498,6 @@ build_visionos() {
         -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}" \
@@ -527,7 +516,6 @@ build_visionos_sim() {
         -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}" \
@@ -546,7 +534,6 @@ build_tvos_sim() {
         -DCMAKE_OSX_DEPLOYMENT_TARGET=${TVOS_MIN_OS_VERSION} \
         -DCMAKE_SYSTEM_NAME=tvOS \
         -DCMAKE_OSX_SYSROOT=appletvsimulator \
-        -DGGML_METAL_TARGET_OS=tvos \
         -DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
         -DGGML_METAL=ON \
         -DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=appletvsimulator \
@@ -565,7 +552,6 @@ build_tvos_device() {
         -DCMAKE_OSX_DEPLOYMENT_TARGET=${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 \

ci/run.sh

@@ -58,6 +58,8 @@ if [ -n "${GG_BUILD_ROCM}" ] && [ -n "${GITHUB_RUN_ID}" ]; then
 fi
 
 rm -f $OUT/*.log
+rm -f $OUT/*.exit
+rm -f $OUT/*.md
 
 sd=`dirname $0`
 cd $sd/../
@@ -187,8 +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-save-load-state"
+    # TODO: fix and re-enable the `test-llama-archs` test below
+    CTEST_EXTRA="-E test-llama-archs|test-recurrent-state-rollback-nemotron-h"
 fi
 
 ## helpers
@@ -209,6 +211,10 @@ function gg_wget {
     cd $cwd
 }
 
+function gg_printf {
+    printf -- "$@" >> $OUT/README.md
+}
+
 function gg_run {
     ci=$1
 
@@ -217,10 +223,13 @@ function gg_run {
 
     gg_run_$ci | tee $OUT/$ci.log
     cur=$?
+    echo "$cur" > $OUT/$ci.exit
 
     set +x
     set +o pipefail
 
+    gg_sum_$ci
+
     ret=$((ret | cur))
 }
 
@@ -241,11 +250,22 @@ function gg_run_ctest_debug {
     (cmake -G "${CMAKE_GENERATOR}" -DCMAKE_BUILD_TYPE=Debug ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
     (time cmake --build . --config Debug -j$(nproc)) 2>&1 | tee -a $OUT/${ci}-make.log
 
-    (time ctest -C Debug --output-on-failure -L main -E "test-opt|test-llama-archs" ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
+    (time ctest -C Debug --output-on-failure -L main -E "test-opt|test-backend-ops|test-llama-archs" ${CTEST_EXTRA}) 2>&1 | tee -a $OUT/${ci}-ctest.log
 
     set +e
 }
 
+function gg_sum_ctest_debug {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Runs ctest in debug mode\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '```\n'
+    gg_printf '%s\n' "$(cat $OUT/${ci}-ctest.log)"
+    gg_printf '```\n'
+    gg_printf '\n'
+}
+
 # ctest_release
 
 function gg_run_ctest_release {
@@ -270,47 +290,14 @@ function gg_run_ctest_release {
     set +e
 }
 
-# test_llama_archs_tensor_split
+function gg_sum_ctest_release {
+    gg_printf '### %s\n\n' "${ci}"
 
-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
-}
-
-# test_llama_archs_models
-
-function gg_run_test_llama_archs_models {
-    cd ${SRC}
-
-    set -e
-
-    # TODO: fix and re-enable `test-llama-archs` on OpenVINO
-    # TODO: the `test-llama-archs` currently does not build on Windows, so we check if the binary exists
-    if [ -z ${GG_BUILD_OPENVINO} ] && [ -f ./build-ci-release/bin/test-llama-archs ]; then
-        rm -rf build-ci-models && mkdir -p build-ci-models
-
-        # generate the dummy models used by the model-dependent tests
-        ./build-ci-release/bin/test-llama-archs -o build-ci-models 2>&1
-    fi
-
-    set +e
+    gg_printf 'Runs ctest in release mode\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '```\n'
+    gg_printf '%s\n' "$(cat $OUT/${ci}-ctest.log)"
+    gg_printf '```\n'
 }
 
 # test_scripts
@@ -326,6 +313,17 @@ function gg_run_test_scripts {
     set +e
 }
 
+function gg_sum_test_scripts {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Runs test scripts\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '```\n'
+    gg_printf '%s\n' "$(cat $OUT/${ci}-scripts.log)"
+    gg_printf '```\n'
+    gg_printf '\n'
+}
+
 function gg_get_model {
     #local gguf_0="$MNT/models/qwen3/0.6B/ggml-model-f16.gguf"
     local gguf_0="$MNT/models/qwen3/0.6B/ggml-model-q4_0.gguf"
@@ -369,6 +367,26 @@ function gg_run_ctest_with_model_release {
     cd ..
 }
 
+function gg_sum_ctest_with_model_debug {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Runs ctest with model files in debug mode\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '```\n'
+    gg_printf '%s\n' "$(cat $OUT/${ci}-ctest.log)"
+    gg_printf '```\n'
+}
+
+function gg_sum_ctest_with_model_release {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Runs ctest with model files in release mode\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '```\n'
+    gg_printf '%s\n' "$(cat $OUT/${ci}-ctest.log)"
+    gg_printf '```\n'
+}
+
 # qwen3_0_6b
 
 function gg_run_qwen3_0_6b {
@@ -473,24 +491,50 @@ function gg_run_qwen3_0_6b {
         return 0
     }
 
-    check_ppl "f16"  "$(cat $OUT/${ci}-tg-f16.log  | grep "^\[1\]")"
+    check_ppl "f16"  "$(cat $OUT/${ci}-tg-f16.log  | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
     if [ -z ${GG_BUILD_NO_BF16} ]; then
-        check_ppl "bf16" "$(cat $OUT/${ci}-tg-bf16.log | grep "^\[1\]")"
+        check_ppl "bf16" "$(cat $OUT/${ci}-tg-bf16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
     fi
-    check_ppl "q8_0" "$(cat $OUT/${ci}-tg-q8_0.log | grep "^\[1\]")"
-    check_ppl "q4_0" "$(cat $OUT/${ci}-tg-q4_0.log | grep "^\[1\]")"
-    check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")"
-    check_ppl "q5_0" "$(cat $OUT/${ci}-tg-q5_0.log | grep "^\[1\]")"
-    check_ppl "q5_1" "$(cat $OUT/${ci}-tg-q5_1.log | grep "^\[1\]")"
-   #check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" # note: ppl > 20.0 for this quant and model
-    check_ppl "q3_k" "$(cat $OUT/${ci}-tg-q3_k.log | grep "^\[1\]")"
-    check_ppl "q4_k" "$(cat $OUT/${ci}-tg-q4_k.log | grep "^\[1\]")"
-    check_ppl "q5_k" "$(cat $OUT/${ci}-tg-q5_k.log | grep "^\[1\]")"
-    check_ppl "q6_k" "$(cat $OUT/${ci}-tg-q6_k.log | grep "^\[1\]")"
+    check_ppl "q8_0" "$(cat $OUT/${ci}-tg-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q4_0" "$(cat $OUT/${ci}-tg-q4_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q5_0" "$(cat $OUT/${ci}-tg-q5_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q5_1" "$(cat $OUT/${ci}-tg-q5_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+   #check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log # note: ppl > 20.0 for this quant and model
+    check_ppl "q3_k" "$(cat $OUT/${ci}-tg-q3_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q4_k" "$(cat $OUT/${ci}-tg-q4_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q5_k" "$(cat $OUT/${ci}-tg-q5_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+    check_ppl "q6_k" "$(cat $OUT/${ci}-tg-q6_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
+
+    cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log
 
     set +e
 }
 
+function gg_sum_qwen3_0_6b {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Qwen3 0.6B:\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
+    gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
+    gg_printf '- f16:\n```\n%s\n```\n'  "$(cat $OUT/${ci}-tg-f16.log)"
+    if [ -z ${GG_BUILD_NO_BF16} ]; then
+        gg_printf '- bf16:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-bf16.log)"
+    fi
+    gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
+    gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
+    gg_printf '- q4_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_1.log)"
+    gg_printf '- q5_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_0.log)"
+    gg_printf '- q5_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_1.log)"
+    gg_printf '- q2_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q2_k.log)"
+    gg_printf '- q3_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q3_k.log)"
+    gg_printf '- q4_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_k.log)"
+    gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)"
+    gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)"
+    gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
+}
+
 # bge-small
 
 function gg_run_embd_bge_small {
@@ -532,6 +576,15 @@ function gg_run_embd_bge_small {
     set +e
 }
 
+function gg_sum_embd_bge_small {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'BGE Small (BERT):\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
+    gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
+}
+
 # rerank_tiny
 
 function gg_run_rerank_tiny {
@@ -588,102 +641,88 @@ function gg_run_rerank_tiny {
     set +e
 }
 
+function gg_sum_rerank_tiny {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Rerank Tiny (Jina):\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-rk-f16.log)"
+}
+
 function gg_check_build_requirements {
     if ! command -v git &> /dev/null; then
-        echo 'git not found, please install'
+        gg_printf 'git not found, please install\n'
         exit 1
     fi
 
     if ! command -v git-lfs &> /dev/null; then
-        echo 'git-lfs not found, please install'
+        gg_printf 'git-lfs not found, please install\n'
         exit 1
     fi
 
     if ! git config --get filter.lfs.clean &> /dev/null; then
-        echo 'git-lfs not initialized, please run `git lfs install`'
+        gg_printf 'git-lfs not initialized, please run `git lfs install`\n'
         exit 1
     fi
 
     if ! command -v wget &> /dev/null; then
-        echo 'wget not found, please install'
+        gg_printf 'wget not found, please install\n'
         exit 1
     fi
 
     if ! command -v python3 &> /dev/null; then
-        echo 'python3 not found, please install'
+        gg_printf 'python3 not found, please install\n'
         exit 1
     fi
 
     if ! command -v pip3 &> /dev/null; then
-        echo 'pip3 not found, please install'
+        gg_printf 'pip3 not found, please install\n'
         exit 1
     fi
 
     if ! python3 -m ensurepip --help &> /dev/null; then
-        echo 'ensurepip not found, please install python3-venv package'
+        gg_printf 'ensurepip not found, please install python3-venv package\n'
         exit 1
     fi
 
     if ! command -v cmake &> /dev/null; then
-        echo 'cmake not found, please install'
+        gg_printf 'cmake not found, please install\n'
         exit 1
     fi
 
     if ! command -v ccache &> /dev/null; then
-        echo 'ccache not found, please consider installing for faster builds'
+        gg_printf 'ccache not found, please consider installing for faster builds\n'
     fi
 
     if ! command -v ctest &> /dev/null; then
-        echo 'ctest not found, please install'
-        exit 1
-    fi
-
-    if ! command -v unzip &> /dev/null; then
-        echo 'unzip not found, please install'
+        gg_printf 'ctest not found, please install\n'
         exit 1
     fi
 }
 
-function gg_run_test_backend_ops {
+function gg_run_test_backend_ops_cpu {
     cd ${SRC}
 
     cd build-ci-release
 
     set -e
 
-    local n_jobs=$(nproc)
-    if [ "${n_jobs}" -gt 2 ]; then
-        n_jobs=2
-    fi
-    local args_extra="-j ${n_jobs}"
-
-    # TODO: fix multi-threaded for ROCm
-    #       https://github.com/ggml-org/llama.cpp/actions/runs/34576278519/job/103297889044?pr=28740#step:3:4865
-    if [ ! -z ${GG_BUILD_ROCM} ]; then
-        args_extra=""
-    fi
-
-    # TODO: MoltenVK bug?
-    #       https://github.com/ggml-org/llama.cpp/actions/runs/34611260059/job/103302413736?pr=28740#step:3:5897
-    if [ ! -z "${GG_BUILD_VULKAN}" ] && [ "$(uname -s)" = "Darwin" ]; then
-        args_extra=""
-    fi
-
-    # TODO: OpenVINO GPU plugin crashes (CL_OUT_OF_RESOURCES) with 2 concurrent workers on GPU.
-    if [ ! -z "${GG_BUILD_OPENVINO}" ] && [ "${GGML_OPENVINO_DEVICE:-}" = "GPU" ]; then
-        args_extra=""
-    fi
-
-    # TODO: reduce the test-backend-ops timeout to 1800s
-    if [ ! -z ${GG_BUILD_HIGH_PERF} ]; then
-        (time timeout 3600 ./bin/test-backend-ops ${args_extra} -b CPU) 2>&1 | tee -a $OUT/${ci}-test-backend-ops.log
-    else
-        (time timeout 3600 ./bin/test-backend-ops ${args_extra}       ) 2>&1 | tee -a $OUT/${ci}-test-backend-ops.log
-    fi
+    (time ./bin/test-backend-ops -b CPU ) 2>&1 | tee -a $OUT/${ci}-test-backend-ops-cpu.log
 
     set +e
 }
 
+function gg_sum_test_backend_ops_cpu {
+    gg_printf '### %s\n\n' "${ci}"
+
+    gg_printf 'Runs test-backend-ops for CPU backend\n'
+    gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
+    gg_printf '```\n'
+    gg_printf '%s\n' "$(cat $OUT/${ci}-test-backend-ops-cpu.log)"
+    gg_printf '```\n'
+    gg_printf '\n'
+}
+
 ## main
 
 export LLAMA_ARG_LOG_PREFIX=1
@@ -712,10 +751,9 @@ 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_backend_ops
-
-test $ret -eq 0 && gg_run test_llama_archs_models
-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
 
 if [ -z ${GG_BUILD_LOW_PERF} ]; then
     test $ret -eq 0 && gg_run embd_bge_small
@@ -731,4 +769,6 @@ if [ -z ${GG_BUILD_LOW_PERF} ]; then
     test $ret -eq 0 && gg_run ctest_with_model_release
 fi
 
+cat $OUT/README.md
+
 exit $ret

common/CMakeLists.txt

@@ -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-schema.cpp
-    json-schema.h
     json.cpp
     json.h
     llguidance.cpp

common/arg.cpp

@@ -872,6 +872,17 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
                     arg.c_str(), e.what(), opt.to_string().c_str()));
             }
         }
+
+        // TODO: remove this check after deprecating --mmap|mlock|dio
+        auto has_arg = [&](std::initializer_list<const char *> names) {
+            return std::any_of(names.begin(), names.end(), [&](const char * name) {
+                return seen_args.count(name);
+            });
+        };
+        if (has_arg({"-lm", "--load-mode"}) &&
+            has_arg({"--mlock", "--mmap", "--no-mmap", "-dio", "--direct-io", "-ndio", "--no-direct-io"})) {
+            LOG_WRN("DEPRECATED: `--load-mode` and `--mlock`/`--mmap`/`--direct-io` should not be combined; only the last flag on the command line will take effect\n");
+        }
     };
 
     // parse all CLI args now, so that -hf is available below for remote preset resolution
@@ -883,12 +894,6 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
     postprocess_cpu_params(params.speculative.draft.cpuparams,       &params.cpuparams);
     postprocess_cpu_params(params.speculative.draft.cpuparams_batch, &params.cpuparams_batch);
 
-    // default the mmproj device to the global device selection if not set explicitly with -mmdev
-    if (params.mmproj_use_gpu && params.mmproj_device == nullptr && !params.devices.empty()) {
-        params.mmproj_device = params.devices.front();
-        params.mmproj_use_gpu = params.mmproj_device != nullptr;
-    }
-
     if (params.prompt_cache_all && (params.interactive || params.interactive_first)) {
         throw std::invalid_argument("error: --prompt-cache-all not supported in interactive mode yet\n");
     }
@@ -955,11 +960,6 @@ 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;
 }
 
@@ -1643,14 +1643,6 @@ 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(
@@ -2277,14 +2269,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     ).set_sampling());
     add_opt(common_arg(
         {"-j", "--json-schema"}, "SCHEMA",
-        "JSON schema to constrain generations (https://json-schema.org/), e.g. `{\"type\": \"object\"}` for any JSON object",
+        "JSON schema to constrain generations (https://json-schema.org/), e.g. `{}` for any JSON object\nFor schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead",
         [](common_params & params, const std::string & value) {
             params.sampling.grammar = {COMMON_GRAMMAR_TYPE_OUTPUT_FORMAT, json_schema_to_grammar(json::parse(value))};
         }
     ).set_sampling());
     add_opt(common_arg(
         {"-jf", "--json-schema-file"}, "FILE",
-        "File containing a JSON schema to constrain generations (https://json-schema.org/), e.g. `{\"type\": \"object\"}` for any JSON object",
+        "File containing a JSON schema to constrain generations (https://json-schema.org/), e.g. `{}` for any JSON object\nFor schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead",
         [](common_params & params, const std::string & value) {
             std::ifstream file(value);
             if (!file) {
@@ -2605,7 +2597,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     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: follows --device)\n"
+        "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") {
@@ -2652,27 +2644,6 @@ 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",
@@ -2683,6 +2654,32 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             }
         ).set_env("LLAMA_ARG_RPC"));
     }
+    add_opt(common_arg(
+        {"--mlock"},
+        "DEPRECATED in favor of `--load-mode`: force system to keep model in RAM rather than swapping or compressing",
+        [](common_params & params) {
+            LOG_WRN("DEPRECATED: --mlock is deprecated. use --load-mode mlock instead\n");
+            params.load_mode = LLAMA_LOAD_MODE_MLOCK;
+        }
+    ).set_env("LLAMA_ARG_MLOCK"));
+    add_opt(common_arg(
+        {"--mmap"},
+        {"--no-mmap"},
+        "DEPRECATED in favor of `--load-mode`: whether to memory-map model. (if mmap disabled, slower load but may reduce pageouts if not using mlock)",
+        [](common_params & params, bool value) {
+            LOG_WRN("DEPRECATED: --mmap and --no-mmap are deprecated. use --load-mode mmap instead\n");
+            params.load_mode = value ? LLAMA_LOAD_MODE_MMAP : LLAMA_LOAD_MODE_NONE;
+        }
+    ).set_env("LLAMA_ARG_MMAP"));
+    add_opt(common_arg(
+        {"-dio", "--direct-io"},
+        {"-ndio", "--no-direct-io"},
+        "DEPRECATED in favor of `--load-mode`: use DirectIO if available",
+        [](common_params & params, bool value) {
+            LOG_WRN("DEPRECATED: --direct-io and --no-direct-io are deprecated. use --load-mode dio instead\n");
+            params.load_mode = value ? LLAMA_LOAD_MODE_DIRECT_IO : LLAMA_LOAD_MODE_NONE;
+        }
+    ).set_env("LLAMA_ARG_DIO"));
     add_opt(common_arg(
         {"-lm", "--load-mode"}, "MODE",
         "model loading mode (default: auto)\n"
@@ -2702,19 +2699,6 @@ 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"
@@ -2766,20 +2750,14 @@ 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",
@@ -3527,10 +3505,6 @@ 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();
             }
         }
@@ -3721,7 +3695,7 @@ 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) {
@@ -3730,7 +3704,6 @@ 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(
@@ -3870,14 +3843,6 @@ 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(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)",
@@ -4119,7 +4084,11 @@ 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"));
 
@@ -4140,38 +4109,6 @@ 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",
@@ -4198,7 +4135,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_BACKEND_SAMPLING"));
     add_opt(common_arg(
         {"--spec-draft-device", "-devd", "--device-draft"}, "<dev1,dev2,..>",
-        "comma-separated list of devices to use for offloading the draft model (none = don't offload, default: follows --device)\n"
+        "comma-separated list of devices to use for offloading the draft model (none = don't offload)\n"
         "use --list-devices to see a list of available devices",
         [](common_params & params, const std::string & value) {
             params.speculative.draft.devices = parse_device_list(value);

common/build-info.cpp.in

@@ -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());
 }

common/build-info.h

@@ -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 *);

common/chat-auto-parser-generator.cpp

@@ -5,7 +5,6 @@
 #include "common.h"
 #include "json-schema-to-grammar.h"
 #include "log.h"
-#include "parsers/parsers.h"
 #include "peg-parser.h"
 
 #include <stdexcept>
@@ -13,6 +12,16 @@
 
 using json = common_json;
 
+// Helper to iterate over tools/functions
+static 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")) {
+            continue;
+        }
+        fn(tool);
+    }
+}
+
 namespace autoparser {
 
 parser_build_context::parser_build_context(common_chat_peg_builder & p, const generation_params & inputs) :
@@ -78,6 +87,15 @@ common_chat_params peg_generator::generate_parser(const common_chat_template &
     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.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);
         });
 
@@ -294,7 +312,7 @@ common_peg_parser analyze_tools::build_tool_parser_tag_json(parser_build_context
     foreach_function(inputs.tools, [&](const json & tool) {
         const auto & func   = tool.at("function");
         std::string  name   = func.at("name");
-        const auto   schema = common_chat_tool_parameters(func);
+        const auto & schema = func.contains("parameters") ? func.at("parameters") : json::object();
 
         // Build call_id parser based on position (if supported)
         bool have_call_id = false;
@@ -365,31 +383,43 @@ common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_conte
     common_peg_parser tool_choice = p.choice();
 
     foreach_function(inputs.tools, [&](const json & tool) {
-        const auto & func = tool.at("function");
-        std::string  name = func.at("name");
+        const auto &          func       = tool.at("function");
+        std::string           name       = func.at("name");
+        auto                  params     = func.contains("parameters") ? func.at("parameters") : json::object();
+        const auto &          properties = params.contains("properties") ? params.at("properties") : json::object();
+
+        std::set<std::string> required;
+        if (params.contains("required")) {
+            required = params.at("required").get<std::set<std::string>>();
+        }
+
+        auto schema_info = common_schema_info();
+        schema_info.resolve_refs(params);
 
         // Build parser for each argument, separating required and optional
         std::vector<common_peg_parser> required_parsers;
         std::vector<common_peg_parser> optional_parsers;
-        foreach_parameter(func, [&](const common_chat_schema_property & param, const common_chat_schema_document_ptr & doc) {
+        for (const auto & [param_name, param_schema] : properties.items()) {
+            bool is_required = required.find(param_name) != required.end();
+
             auto arg =
-                p.tool_arg(p.tool_arg_open(arguments.name_prefix + p.tool_arg_name(p.literal(param.name)) +
+                p.tool_arg(p.tool_arg_open(arguments.name_prefix + p.tool_arg_name(p.literal(param_name)) +
                                            arguments.name_suffix) +
                            arguments.value_prefix +
-                           (param.schema->may_be_string() ?
+                           (schema_info.resolves_to_string(param_schema) ?
                                 p.ac(p.tool_arg_string_value(until_suffix) +
                                     p.tool_arg_close(p.literal(arguments.value_suffix)), arguments.value_suffix) :
                                 (p.tool_arg_json_value(p.schema(
-                                    p.json(), "tool-" + name + "-arg-" + param.name + "-schema", doc, *param.schema)) +
+                                    p.json(), "tool-" + name + "-arg-" + param_name + "-schema", param_schema, false)) +
                                     p.tool_arg_close(p.literal(arguments.value_suffix)))));
 
-            auto named_arg = p.rule("tool-" + name + "-arg-" + param.name, arg);
-            if (param.required) {
+            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);
             }
-        });
+        }
 
         // Build required arg sequence in definition order
         common_peg_parser args_seq = p.eps();

common/chat-peg-parser.cpp

@@ -488,7 +488,7 @@ common_peg_parser common_chat_peg_builder::standard_constructed_tools(
         }
         const auto &   function = tool_def.at("function");
         std::string    name     = function.at("name");
-        ordered_json   params   = common_chat_tool_parameters(function);
+        ordered_json   params   = function.contains("parameters") ? function.at("parameters") : ordered_json::object();
 
         // Build argument parsers
         auto args = eps();
@@ -565,7 +565,7 @@ common_peg_parser common_chat_peg_builder::python_style_tool_calls(
         }
         const auto &   function = tool_def.at("function");
         std::string    name     = function.at("name");
-        ordered_json   params   = common_chat_tool_parameters(function);
+        ordered_json   params   = function.contains("parameters") ? function.at("parameters") : ordered_json::object();
 
         auto args = eps();
         if (params.contains("properties") && !params["properties"].empty()) {
@@ -640,7 +640,7 @@ common_peg_parser common_chat_peg_builder::build_json_tools_function_is_key(
         }
         const auto &   function = tool_def.at("function");
         std::string    name     = function.at("name");
-        ordered_json   params   = common_chat_tool_parameters(function);
+        ordered_json   params   = function.contains("parameters") ? function.at("parameters") : ordered_json::object();
 
         // Build inner object fields
         std::vector<common_peg_parser> inner_fields;
@@ -726,7 +726,7 @@ common_peg_parser common_chat_peg_builder::build_json_tools_nested_keys(
         }
         const auto &   function = tool_def.at("function");
         std::string    name     = function.at("name");
-        ordered_json   params   = common_chat_tool_parameters(function);
+        ordered_json   params   = function.contains("parameters") ? function.at("parameters") : ordered_json::object();
 
         auto nested_name = literal("\"" + nested_name_field + "\"") + space() + literal(":") + space() +
                           atomic(literal("\"") + tool_name(literal(name)) + literal("\""));
@@ -795,7 +795,7 @@ common_peg_parser common_chat_peg_builder::build_json_tools_flat_keys(
         }
         const auto &   function = tool_def.at("function");
         std::string    name     = function.at("name");
-        ordered_json   params   = common_chat_tool_parameters(function);
+        ordered_json   params   = function.contains("parameters") ? function.at("parameters") : ordered_json::object();
 
         auto tool_name_ = name_key_parser + space() + literal(":") + space() +
                          atomic(literal("\"") + tool_name(literal(name)) + literal("\""));

common/chat.h

@@ -360,9 +360,6 @@ common_json common_chat_msgs_to_json_oaicompat(const std::vector<common_chat_msg
 
 common_json common_chat_tools_to_json_oaicompat(const std::vector<common_chat_tool> & tools);
 
-// The parameters schema of a function tool. A tool without parameters, or with an empty {}, takes zero arguments.
-common_json common_chat_tool_parameters(const common_json & function);
-
 // 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);
 

common/common.cpp

@@ -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);
     }
 
@@ -1586,11 +1562,6 @@ common_context_seq_rm_type common_context_can_seq_rm(llama_context * ctx) {
         return COMMON_CONTEXT_SEQ_RM_TYPE_NO;
     }
 
-    if (llama_n_rs_seq(ctx) > 0) {
-        COM_TRC("%s", "the context supports bounded partial sequence removal\n");
-        return COMMON_CONTEXT_SEQ_RM_TYPE_RS;
-    }
-
     common_context_seq_rm_type res = COMMON_CONTEXT_SEQ_RM_TYPE_PART;
 
     llama_memory_clear(mem, true);
@@ -1607,6 +1578,12 @@ common_context_seq_rm_type common_context_can_seq_rm(llama_context * ctx) {
         goto done;
     }
 
+    if (llama_n_rs_seq(ctx) > 0) {
+        COM_TRC("%s", "the context supports bounded partial sequence removal\n");
+        res = COMMON_CONTEXT_SEQ_RM_TYPE_RS;
+        goto done;
+    }
+
     // try to remove the last tokens
     if (!llama_memory_seq_rm(mem, 0, 1, -1)) {
         COM_TRC("%s", "the context does not support partial sequence removal\n");
@@ -1687,7 +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;

common/common.h

@@ -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;
 
@@ -599,11 +589,6 @@ struct common_params {
     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 +612,6 @@ 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 +641,6 @@ 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 +1108,19 @@ 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
 //

common/fit.cpp

@@ -1,6 +1,5 @@
 #include "fit.h"
 
-#include "json.h"
 #include "log.h"
 
 #include "../src/llama-ext.h"
@@ -179,7 +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");
     }
@@ -192,92 +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
@@ -390,8 +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];
@@ -411,9 +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 {
@@ -423,16 +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;
@@ -441,14 +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 {
@@ -593,9 +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++) {
@@ -622,9 +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;
@@ -884,12 +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());
@@ -916,9 +827,6 @@ void common_memory_breakdown_print(const struct llama_context * ctx) {
 
     std::vector<std::array<std::string, 9>> table_data;
     table_data.reserve(devices.size());
-
-    // same data as the table below, for --log-jsonl consumers
-    common_json rows = common_json::array();
     const std::string template_header = "%s: | %s | %s   %s    %s   %s   %s   %s    %s |\n";
     const std::string template_gpu    = "%s: | %s | %s = %s + (%s = %s + %s + %s) + %s |\n";
     const std::string template_other  = "%s: | %s | %s   %s    %s = %s + %s + %s    %s |\n";
@@ -993,19 +901,6 @@ void common_memory_breakdown_print(const struct llama_context * ctx) {
             std::to_string(mb.context / MiB),
             std::to_string(mb.compute / MiB),
             std::to_string(unaccounted / static_cast<int64_t>(MiB))});
-
-        rows.push_back({
-            {"kind",        "device"},
-            {"name",        name},
-            {"description", desc},
-            {"total",       total / MiB},
-            {"free",        free / MiB},
-            {"self",        self / MiB},
-            {"model",       mb.model / MiB},
-            {"context",     mb.context / MiB},
-            {"compute",     mb.compute / MiB},
-            {"unaccounted", unaccounted / static_cast<int64_t>(MiB)},
-        });
     }
 
     // print memory breakdown for host:
@@ -1021,15 +916,6 @@ void common_memory_breakdown_print(const struct llama_context * ctx) {
             std::to_string(mb_host.context / MiB),
             std::to_string(mb_host.compute / MiB),
             ""}); // unaccounted
-
-        rows.push_back({
-            {"kind",    "host"},
-            {"name",    "Host"},
-            {"self",    self / MiB},
-            {"model",   mb_host.model / MiB},
-            {"context", mb_host.context / MiB},
-            {"compute", mb_host.compute / MiB},
-        });
     }
 
     // print memory breakdown for all remaining buffer types:
@@ -1051,16 +937,6 @@ void common_memory_breakdown_print(const struct llama_context * ctx) {
             std::to_string(mb.context / MiB),
             std::to_string(mb.compute / MiB),
             ""}); // unaccounted
-
-        rows.push_back({
-            {"kind",    "buffer_type"},
-            {"name",    name},
-            {"self",    self / MiB},
-            {"model",   mb.model / MiB},
-            {"context", mb.context / MiB},
-            {"compute", mb.compute / MiB},
-        });
-
         seen_buffer_types.insert(buft);
     }
 
@@ -1078,11 +954,6 @@ void common_memory_breakdown_print(const struct llama_context * ctx) {
             __func__, td[1].c_str(), td[2].c_str(), td[3].c_str(), td[4].c_str(), td[5].c_str(),
             td[6].c_str(), td[7].c_str(), td[8].c_str());
     }
-
-    LOG_JSON("fit_memory_breakdown", common_json({
-        {"unit", "MiB"},
-        {"rows", rows},
-    }));
 }
 
 void common_fit_print(

common/fit.h

@@ -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

common/jinja/caps.cpp

@@ -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

common/jinja/runtime.cpp

@@ -167,12 +167,6 @@ value binary_expression::execute_impl(context & ctx) {
         }
         throw std::runtime_error("Cannot perform operation " + op.value + " on undefined values");
     } else if (is_val<value_none>(left_val) || is_val<value_none>(right_val)) {
-        if (!is_val<value_none>(right_val) && (op.value == "in" || op.value == "not in")) {
-            // case: none in {'low': 1}
-            // A null left operand is looked up like any other value.
-            bool member = test_is_in();
-            return mk_val<value_bool>(op.value == "in" ? member : !member);
-        }
         if (op.value == "+" || op.value == "~") {
             value res = mk_val<value_undefined>();
             if (workaround_concat_null_with_str(res)) {
@@ -418,18 +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) {
@@ -842,12 +830,6 @@ value member_expression::execute_impl(context & ctx) {
         } else {
             property = this->property->execute(ctx);
         }
-    } else if (is_stmt<integer_literal>(this->property)) {
-        // syntax: obj.index
-        property = mk_val<value_int>(cast_stmt<integer_literal>(this->property)->val);
-        if (property->as_int() < 0) {
-            throw std::runtime_error("Static member property cannot be negative");
-        }
     } else {
         // syntax: obj.prop
         if (!is_stmt<identifier>(this->property)) {

common/json-schema-to-grammar.cpp

@@ -1,7 +1,5 @@
 #include "json-schema-to-grammar.h"
 #include "common.h"
-#include "trie.h"
-#include "unicode.h"
 
 #include <algorithm>
 #include <limits>
@@ -338,20 +336,18 @@ static size_t gbnf_escape_length(const std::string & pattern, size_t pos) {
     return 2 + n_hex;
 }
 
-class common_chat_schema_converter {
+class common_schema_converter {
 private:
+    friend class common_schema_info;
     friend std::string build_grammar(const std::function<void(const common_grammar_builder &)> & cb, const common_grammar_options & options);
+    std::function<json(const std::string &)> _fetch_json;
     bool _dotall;
     std::map<std::string, std::string> _rules;
+    std::unordered_map<std::string, json> _refs;
     std::unordered_set<std::string> _refs_being_resolved;
     std::vector<std::string> _errors;
     std::vector<std::string> _warnings;
 
-    template <typename T>
-    static const T & as(const common_chat_schema & node) {
-        return static_cast<const T &>(node);
-    }
-
     std::string _add_rule(const std::string & name, const std::string & rule) {
         std::string esc_name = regex_replace(name, INVALID_RULE_CHARS_RE, "-");
         if (_rules.find(esc_name) == _rules.end() || _rules[esc_name] == rule) {
@@ -367,11 +363,11 @@ private:
         return key;
     }
 
-    std::string _generate_union_rule(const std::string & name, const std::vector<common_chat_schema_ptr> & alt_schemas) {
+    std::string _generate_union_rule(const std::string & name, const std::vector<json> & alt_schemas) {
         std::vector<std::string> rules;
         rules.reserve(alt_schemas.size());
         for (size_t i = 0; i < alt_schemas.size(); i++) {
-            rules.push_back(visit(*alt_schemas[i], name + (name.empty() ? "alternative-" : "-") + std::to_string(i)));
+            rules.push_back(visit(alt_schemas[i], name + (name.empty() ? "alternative-" : "-") + std::to_string(i)));
         }
         return string_join(rules, " | ");
     }
@@ -638,68 +634,85 @@ private:
             -> ["] ( [a] ([l] ([s] ([o] char+ | [^"o] char*) | [^"s] char*) | [n] ([d] char+ | [^"d] char*) | [^"ln] char*) | [^"a] char* )? ["]
     */
     std::string _not_strings(const std::vector<std::string> & strings) {
-        common_trie trie(strings);
+
+        struct TrieNode {
+            std::map<char, TrieNode> children;
+            bool is_end_of_string;
+
+            TrieNode() : is_end_of_string(false) {}
+
+            void insert(const std::string & string) {
+                auto *node = this;
+                for (char c : string) {
+                    node = &node->children[c];
+                }
+                node->is_end_of_string = true;
+            }
+        };
+
+        TrieNode trie;
+        for (const auto & s : strings) {
+            trie.insert(s);
+        }
 
         std::string char_rule = _add_primitive("char", PRIMITIVE_RULES.at("char"));
         std::ostringstream out;
         out << "[\"] ( ";
-        std::function<void(size_t)> visit = [&](size_t idx) {
-            const auto & node = trie.nodes[idx];
-            std::string rejects;
+        std::function<void(const TrieNode &)> visit = [&](const TrieNode & node) {
+            std::ostringstream rejects;
             auto first = true;
-            for (const auto & [cpt, child] : node.children) {
-                std::string c = common_unicode_cpt_to_utf8(cpt);
-                rejects += c;
+            for (const auto & kv : node.children) {
+                rejects << kv.first;
                 if (first) {
                     first = false;
                 } else {
                     out << " | ";
                 }
-                out << "[" << c << "]";
-                if (!trie.nodes[child].children.empty()) {
+                out << "[" << kv.first << "]";
+                if (!kv.second.children.empty()) {
                     out << " (";
-                    visit(child);
+                    visit(kv.second);
                     out << ")";
-                } else {
+                } else if (kv.second.is_end_of_string) {
                     out << " " << char_rule << "+";
                 }
             }
             if (!node.children.empty()) {
-                out << " | [^\"" << rejects << "] " << char_rule << "*";
+                if (!first) {
+                    out << " | ";
+                }
+                out << "[^\"" << rejects.str() << "] " << char_rule << "*";
             }
         };
-        visit(0);
+        visit(trie);
 
         out << " )";
-        if (trie.nodes[0].pattern < 0) {
+        if (!trie.is_end_of_string) {
             out << "?";
         }
         out << " [\"]";
         return out.str();
     }
 
-    std::string _resolve_ref(const common_chat_schema_ref & schema) {
-        auto it = schema.ref.find('#');
-        std::string ref_fragment = it != std::string::npos ? schema.ref.substr(it + 1) : schema.ref;
+    std::string _resolve_ref(const std::string & ref) {
+        auto it = ref.find('#');
+        std::string ref_fragment = it != std::string::npos ? ref.substr(it + 1) : ref;
         static const std::regex nonalphanumeric_regex(R"([^a-zA-Z0-9-]+)");
         std::string ref_name = "ref" + std::regex_replace(ref_fragment, nonalphanumeric_regex, "-");
-        if (_rules.find(ref_name) == _rules.end() && _refs_being_resolved.find(schema.ref) == _refs_being_resolved.end()) {
-            if (!schema.target) {
-                _errors.push_back("Unresolved $ref " + schema.ref);
-                return "";
-            }
-            _refs_being_resolved.insert(schema.ref);
-            ref_name = visit(*schema.target, ref_name);
-            _refs_being_resolved.erase(schema.ref);
+        if (_rules.find(ref_name) == _rules.end() && _refs_being_resolved.find(ref) == _refs_being_resolved.end()) {
+            _refs_being_resolved.insert(ref);
+            json resolved = _refs[ref];
+            ref_name = visit(resolved, ref_name);
+            _refs_being_resolved.erase(ref);
         }
         return ref_name;
     }
 
     std::string _build_object_rule(
-        const std::vector<std::pair<std::string, const common_chat_schema *>> & properties,
+        const std::vector<std::pair<std::string, json>> & properties,
         const std::unordered_set<std::string> & required,
         const std::string & name,
-        const common_chat_schema * additional_properties)
+        const json & additional_properties)
     {
         std::vector<std::string> required_props;
         std::vector<std::string> optional_props;
@@ -709,7 +722,7 @@ private:
             const auto &prop_name = kv.first;
             const auto &prop_schema = kv.second;
 
-            std::string prop_rule_name = visit(*prop_schema, name + (name.empty() ? "" : "-") + prop_name);
+            std::string prop_rule_name = visit(prop_schema, name + (name.empty() ? "" : "-") + prop_name);
             prop_kv_rule_names[prop_name] = _add_rule(
                 name + (name.empty() ? "" : "-") + prop_name + "-kv",
                 format_literal(json(prop_name).dump()) + " space \":\" space " + prop_rule_name
@@ -721,10 +734,10 @@ private:
             }
             prop_names.push_back(prop_name);
         }
-        if (additional_properties) {
+        if ((additional_properties.is_boolean() && additional_properties.get<bool>()) || additional_properties.is_object()) {
             std::string sub_name = name + (name.empty() ? "" : "-") + "additional";
             std::string value_rule =
-                additional_properties->kind() != common_chat_schema::KIND_ANY ? visit(*additional_properties, sub_name + "-value")
+                additional_properties.is_object() ? visit(additional_properties, sub_name + "-value")
                 : _add_primitive("value", PRIMITIVE_RULES.at("value"));
 
             auto key_rule =
@@ -735,10 +748,6 @@ 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) {
@@ -812,163 +821,267 @@ private:
     }
 
 public:
-    explicit common_chat_schema_converter(bool dotall) : _dotall(dotall) {
+    common_schema_converter(
+        const std::function<json(const std::string &)> & fetch_json,
+        bool dotall)
+          : _fetch_json(fetch_json), _dotall(dotall)
+    {
         _rules["space"] = SPACE_RULE;
     }
 
-    std::string add_schema(const std::string & name, const common_chat_schema & schema) {
-        return visit(schema, name);
+    void resolve_refs(json & schema, const std::string & url) {
+        /*
+        * Resolves all $ref fields in the given schema, fetching any remote schemas,
+        * replacing each $ref with absolute reference URL and populates _refs with the
+        * respective referenced (sub)schema dictionaries.
+        */
+        std::function<void(json &)> visit_refs = [&](json & n) {
+            if (n.is_array()) {
+                for (auto & x : n) {
+                    visit_refs(x);
+                }
+            } else if (n.is_object()) {
+                if (n.contains("$ref")) {
+                    std::string ref = n["$ref"];
+                    if (_refs.find(ref) == _refs.end()) {
+                        json target;
+                        if (ref.find("https://") == 0) {
+                            std::string base_url = ref.substr(0, ref.find('#'));
+                            auto it = _refs.find(base_url);
+                            if (it != _refs.end()) {
+                                target = it->second;
+                            } else {
+                                // Fetch the referenced schema and resolve its refs
+                                auto referenced = _fetch_json(ref);
+                                resolve_refs(referenced, base_url);
+                                _refs[base_url] = referenced;
+                            }
+                            if (ref.find('#') == std::string::npos || ref.substr(ref.find('#') + 1).empty()) {
+                                return;
+                            }
+                        } else if (ref.find("#/") == 0) {
+                            target = schema;
+                            n["$ref"] = url + ref;
+                            ref = url + ref;
+                        } else {
+                            _errors.push_back("Unsupported ref: " + ref);
+                            return;
+                        }
+                        std::string pointer = ref.substr(ref.find('#') + 1);
+                        std::vector<std::string> tokens = string_split(pointer, "/");
+                        for (size_t i = 1; i < tokens.size(); ++i) {
+                            const std::string& sel = tokens[i];
+                            if (target.is_object() && target.contains(sel)) {
+                                target = target[sel];
+                            } else if (target.is_array()) {
+                                size_t sel_index;
+                                try {
+                                    sel_index = std::stoull(sel);
+                                } catch (const std::invalid_argument & e) {
+                                    sel_index = target.size();
+                                }
+                                if (sel_index >= target.size()) {
+                                    _errors.push_back("Error resolving ref " + ref + ": " + sel + " not in " + target.dump());
+                                    return;
+                                }
+                                target = target[sel_index];
+                            } else {
+                                _errors.push_back("Error resolving ref " + ref + ": " + sel + " not in " + target.dump());
+                                return;
+                            }
+                        }
+                        _refs[ref] = target;
+                    }
+                } else {
+                    for (const auto & kv : n.items()) {
+                        visit_refs(kv.value());
+                    }
+                }
+            }
+        };
+
+        visit_refs(schema);
     }
 
     static std::string _generate_constant_rule(const json & value) {
         return format_literal(value.dump());
     }
 
-    std::string _visit_primitive(const std::string & rule_name, const std::string & type) {
-        return _add_primitive(rule_name == "root" ? "root" : type, PRIMITIVE_RULES.at(type));
-    }
-
-    std::string _visit_all_of(const common_chat_schema_all_of & schema, const std::string & name, const std::string & rule_name) {
-        std::unordered_set<std::string> required;
-        std::vector<std::pair<std::string, const common_chat_schema *>> properties;
-        std::map<std::string, size_t> enum_values;
-        std::function<void(const common_chat_schema &, bool)> add_component = [&](const common_chat_schema & comp, bool is_required) {
-            if (comp.kind() == common_chat_schema::KIND_REF) {
-                if (const auto * target = as<common_chat_schema_ref>(comp).target) {
-                    add_component(*target, is_required);
-                }
-            } else if (comp.kind() == common_chat_schema::KIND_OBJECT) {
-                for (const auto & prop : as<common_chat_schema_object>(comp).properties) {
-                    properties.emplace_back(prop.name, prop.schema.get());
-                    if (is_required) {
-                        required.insert(prop.name);
-                    }
-                }
-            } else if (comp.kind() == common_chat_schema::KIND_ENUM) {
-                for (const auto & v : as<common_chat_schema_enum>(comp).values) {
-                    enum_values[_generate_constant_rule(v)] += 1;
-                }
-            }
-        };
-        for (const auto & child : schema.children) {
-            if (child->kind() == common_chat_schema::KIND_ANY_OF) {
-                for (const auto & alt : as<common_chat_schema_any_of>(*child).children) {
-                    add_component(*alt, false);
-                }
-            } else {
-                add_component(*child, true);
-            }
-        }
-        if (!enum_values.empty()) {
-            std::vector<std::string> enum_intersection;
-            for (const auto & p : enum_values) {
-                if (p.second == schema.children.size()) {
-                    enum_intersection.push_back(p.first);
-                }
-            }
-            if (!enum_intersection.empty()) {
-                return _add_rule(rule_name, "(" + string_join(enum_intersection, " | ") + ")");
-            }
-        }
-        return _add_rule(rule_name, _build_object_rule(properties, required, name, nullptr));
-    }
-
-    std::string visit(const common_chat_schema & schema, const std::string & name) {
+    std::string visit(const json & schema, const std::string & name) {
+        json schema_type = schema.contains("type") ? schema["type"] : json();
+        std::string schema_format = schema.contains("format") ? schema["format"].get<std::string>() : "";
         std::string rule_name = is_reserved_name(name) ? name + "-" : name.empty() ? "root" : name;
-        std::string sub_name  = name + (name.empty() ? "" : "-");
 
-        switch (schema.kind()) {
-            case common_chat_schema::KIND_REF:
-                return _add_rule(rule_name, _resolve_ref(as<common_chat_schema_ref>(schema)));
-            case common_chat_schema::KIND_ANY_OF:
-                return _add_rule(rule_name, _generate_union_rule(name, as<common_chat_schema_any_of>(schema).children));
-            case common_chat_schema::KIND_ALL_OF:
-                return _visit_all_of(as<common_chat_schema_all_of>(schema), name, rule_name);
-            case common_chat_schema::KIND_CONST:
-                return _add_rule(rule_name, _generate_constant_rule(as<common_chat_schema_const>(schema).value));
-            case common_chat_schema::KIND_ENUM: {
-                std::vector<std::string> enum_values;
-                for (const auto & v : as<common_chat_schema_enum>(schema).values) {
-                    enum_values.push_back(_generate_constant_rule(v));
-                }
-                return _add_rule(rule_name, "(" + string_join(enum_values, " | ") + ")");
+        if (schema.contains("$ref")) {
+            return _add_rule(rule_name, _resolve_ref(schema["$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);
             }
-            case common_chat_schema::KIND_OBJECT: {
-                const auto & obj = as<common_chat_schema_object>(schema);
-                if (obj.properties.empty() && obj.additional_properties && obj.additional_properties->kind() == common_chat_schema::KIND_ANY) {
-                    return _add_rule(rule_name, _add_primitive("object", PRIMITIVE_RULES.at("object")));
-                }
-                std::vector<std::pair<std::string, const common_chat_schema *>> properties;
-                std::unordered_set<std::string> required;
-                for (const auto & prop : obj.properties) {
-                    properties.emplace_back(prop.name, prop.schema.get());
-                    if (prop.required) {
-                        required.insert(prop.name);
+            return _add_rule(rule_name, _generate_union_rule(name, alt_schemas));
+        }
+        if (schema_type.is_array()) {
+            std::vector<json> schema_types;
+            for (const auto & t : schema_type) {
+                json schema_copy(schema);
+                schema_copy["type"] = t;
+                schema_types.push_back(schema_copy);
+            }
+            return _add_rule(rule_name, _generate_union_rule(name, schema_types));
+        }
+        if (schema.contains("const")) {
+            return _add_rule(rule_name, _generate_constant_rule(schema["const"]));
+        }
+        if (schema.contains("enum")) {
+            std::vector<std::string> enum_values;
+            for (const auto & v : schema["enum"]) {
+                enum_values.push_back(_generate_constant_rule(v));
+            }
+            return _add_rule(rule_name, "(" + string_join(enum_values, " | ") + ")");
+        }
+        if ((schema_type.is_null() || schema_type == "object")
+                && (schema.contains("properties") ||
+                    (schema.contains("additionalProperties") && schema["additionalProperties"] != true))) {
+            std::unordered_set<std::string> required;
+            if (schema.contains("required") && schema["required"].is_array()) {
+                for (const auto & item : schema["required"]) {
+                    if (item.is_string()) {
+                        required.insert(item.get<std::string>());
                     }
                 }
-                return _add_rule(rule_name, _build_object_rule(properties, required, name, obj.additional_properties.get()));
             }
-            case common_chat_schema::KIND_TUPLE: {
-                const auto & items = as<common_chat_schema_tuple>(schema).items;
+            std::vector<std::pair<std::string, json>> properties;
+            if (schema.contains("properties")) {
+                for (const auto & prop : schema["properties"].items()) {
+                    properties.emplace_back(prop.key(), prop.value());
+                }
+            }
+            return _add_rule(rule_name,
+                _build_object_rule(
+                    properties, required, name,
+                    schema.contains("additionalProperties") ? schema["additionalProperties"] : json()));
+        }
+        if ((schema_type.is_null() || schema_type == "object" || schema_type == "string") && schema.contains("allOf")) {
+            std::unordered_set<std::string> required;
+            std::vector<std::pair<std::string, json>> properties;
+            std::map<std::string, size_t> enum_values;
+            const std::string& hybrid_name = name;
+            std::function<void(const json &, bool)> add_component = [&](const json & comp_schema, bool is_required) {
+                if (comp_schema.contains("$ref")) {
+                    add_component(_refs[comp_schema["$ref"]], is_required);
+                } else if (comp_schema.contains("properties")) {
+                    for (const auto & prop : comp_schema["properties"].items()) {
+                        properties.emplace_back(prop.key(), prop.value());
+                        if (is_required) {
+                            required.insert(prop.key());
+                        }
+                    }
+                } else if (comp_schema.contains("enum")) {
+                    for (const auto & v : comp_schema["enum"]) {
+                        const auto rule = _generate_constant_rule(v);
+                        if (enum_values.find(rule) == enum_values.end()) {
+                            enum_values[rule] = 0;
+                        }
+                        enum_values[rule] += 1;
+                    }
+                } else {
+                  // todo warning
+                }
+            };
+            for (const auto & t : schema["allOf"]) {
+                if (t.contains("anyOf")) {
+                    for (const auto & tt : t["anyOf"]) {
+                        add_component(tt, false);
+                    }
+                } else {
+                    add_component(t, true);
+                }
+            }
+            if (!enum_values.empty()) {
+                std::vector<std::string> enum_intersection;
+                for (const auto & p : enum_values) {
+                    if (p.second == schema["allOf"].size()) {
+                        enum_intersection.push_back(p.first);
+                    }
+                }
+                if (!enum_intersection.empty()) {
+                    return _add_rule(rule_name, "(" + string_join(enum_intersection, " | ") + ")");
+                }
+            }
+            return _add_rule(rule_name, _build_object_rule(properties, required, hybrid_name, json()));
+        }
+        if ((schema_type.is_null() || schema_type == "array") && (schema.contains("items") || schema.contains("prefixItems"))) {
+            json items = schema.contains("items") ? schema["items"] : schema["prefixItems"];
+            if (items.is_array()) {
                 std::string rule = "\"[\" space ";
                 for (size_t i = 0; i < items.size(); i++) {
                     if (i > 0) {
                         rule += " \",\" space ";
                     }
-                    rule += visit(*items[i], sub_name + "tuple-" + std::to_string(i));
+                    rule += visit(items[i], name + (name.empty() ? "" : "-") + "tuple-" + std::to_string(i));
                 }
                 rule += " space \"]\"";
                 return _add_rule(rule_name, rule);
             }
-            case common_chat_schema::KIND_ARRAY: {
-                const auto & arr = as<common_chat_schema_array>(schema);
-                if (arr.items->kind() == common_chat_schema::KIND_ANY && arr.min_items == 0 && arr.max_items < 0) {
-                    return _visit_primitive(rule_name, "array");
-                }
-                std::string item_rule_name = visit(*arr.items, sub_name + "item");
-                int max_items = arr.max_items < 0 ? std::numeric_limits<int>::max() : arr.max_items;
-                return _add_rule(rule_name, "\"[\" space " + build_repetition(item_rule_name, arr.min_items, max_items, "\",\" space") + " space \"]\"");
-            }
-            case common_chat_schema::KIND_STRING: {
-                const auto & str = as<common_chat_schema_string>(schema);
-                if (!str.pattern.empty()) {
-                    return _visit_pattern(str.pattern, rule_name);
-                }
-                if (str.format == common_chat_schema::FORMAT_UUID) {
-                    return _visit_primitive(rule_name, "uuid");
-                }
-                if (str.format != common_chat_schema::FORMAT_NONE) {
-                    std::string prim_name = std::string(str.format == common_chat_schema::FORMAT_DATE ? "date" : str.format == common_chat_schema::FORMAT_TIME ? "time" : "date-time") + "-string";
-                    return _add_rule(rule_name, _add_primitive(prim_name, STRING_FORMAT_RULES.at(prim_name)));
-                }
-                if (str.min_length > 0 || str.max_length >= 0) {
-                    std::string char_rule = _add_primitive("char", PRIMITIVE_RULES.at("char"));
-                    int max_len = str.max_length < 0 ? std::numeric_limits<int>::max() : str.max_length;
-                    return _add_rule(rule_name, "\"\\\"\" " + build_repetition(char_rule, str.min_length, max_len) + " \"\\\"\"");
-                }
-                return _visit_primitive(rule_name, "string");
-            }
-            case common_chat_schema::KIND_INTEGER: {
-                const auto & i = as<common_chat_schema_integer>(schema);
-                if (i.minimum == std::numeric_limits<int64_t>::min() && i.maximum == std::numeric_limits<int64_t>::max()) {
-                    return _visit_primitive(rule_name, "integer");
-                }
-                std::stringstream out;
-                out << "(";
-                build_min_max_int(i.minimum, i.maximum, out);
-                out << ")";
-                return _add_rule(rule_name, out.str());
-            }
-            case common_chat_schema::KIND_NUMBER:
-                return _visit_primitive(rule_name, "number");
-            case common_chat_schema::KIND_BOOLEAN:
-                return _visit_primitive(rule_name, "boolean");
-            case common_chat_schema::KIND_NULL:
-                return _visit_primitive(rule_name, "null");
-            case common_chat_schema::KIND_ANY:
-                return _add_rule(rule_name, _add_primitive("value", PRIMITIVE_RULES.at("value")));
+            std::string item_rule_name = visit(items, name + (name.empty() ? "" : "-") + "item");
+            int min_items = schema.contains("minItems") ? schema["minItems"].get<int>() : 0;
+            json max_items_json = schema.contains("maxItems") ? schema["maxItems"] : json();
+            int max_items = max_items_json.is_number_integer() ? max_items_json.get<int>() : std::numeric_limits<int>::max();
+
+            return _add_rule(rule_name, "\"[\" space " + build_repetition(item_rule_name, min_items, max_items, "\",\" space") + " space \"]\"");
         }
-        return "";
+        if ((schema_type.is_null() || schema_type == "string") && schema.contains("pattern")) {
+            return _visit_pattern(schema["pattern"], rule_name);
+        }
+        if ((schema_type.is_null() || schema_type == "string") && std::regex_match(schema_format, std::regex("^uuid[1-5]?$"))) {
+            return _add_primitive(rule_name == "root" ? "root" : schema_format, PRIMITIVE_RULES.at("uuid"));
+        }
+        if ((schema_type.is_null() || schema_type == "string") && STRING_FORMAT_RULES.find(schema_format + "-string") != STRING_FORMAT_RULES.end()) {
+            auto prim_name = schema_format + "-string";
+            return _add_rule(rule_name, _add_primitive(prim_name, STRING_FORMAT_RULES.at(prim_name)));
+        }
+        if (schema_type == "string" && (schema.contains("minLength") || schema.contains("maxLength"))) {
+            std::string char_rule = _add_primitive("char", PRIMITIVE_RULES.at("char"));
+            int min_len = schema.contains("minLength") ? schema["minLength"].get<int>() : 0;
+            int max_len = schema.contains("maxLength") ? schema["maxLength"].get<int>() : std::numeric_limits<int>::max();
+            return _add_rule(rule_name, "\"\\\"\" " + build_repetition(char_rule, min_len, max_len) + " \"\\\"\"");
+        }
+        if (schema_type == "integer" && (schema.contains("minimum") || schema.contains("exclusiveMinimum") || schema.contains("maximum") || schema.contains("exclusiveMaximum"))) {
+            int64_t min_value = std::numeric_limits<int64_t>::min();
+            int64_t max_value = std::numeric_limits<int64_t>::max();
+            if (schema.contains("minimum")) {
+                min_value = schema["minimum"].get<int64_t>();
+            } else if (schema.contains("exclusiveMinimum")) {
+                min_value = schema["exclusiveMinimum"].get<int64_t>() + 1;
+            }
+            if (schema.contains("maximum")) {
+                max_value = schema["maximum"].get<int64_t>();
+            } else if (schema.contains("exclusiveMaximum")) {
+                max_value = schema["exclusiveMaximum"].get<int64_t>() - 1;
+            }
+            std::stringstream out;
+            out << "(";
+            build_min_max_int(min_value, max_value, out);
+            out << ")";
+            return _add_rule(rule_name, out.str());
+        }
+        if (schema.empty() || schema_type == "object") {
+            return _add_rule(rule_name, _add_primitive("object", PRIMITIVE_RULES.at("object")));
+        }
+        if (schema_type.is_null() && schema.is_object()) {
+            // No type constraint and no recognized structural keywords (e.g. {"description": "..."}).
+            // Per JSON Schema semantics this is equivalent to {} and accepts any value.
+            return _add_rule(rule_name, _add_primitive("value", PRIMITIVE_RULES.at("value")));
+        }
+        if (!schema_type.is_string() || PRIMITIVE_RULES.find(schema_type.get<std::string>()) == PRIMITIVE_RULES.end()) {
+            _errors.push_back("Unrecognized schema: " + schema.dump());
+            return "";
+        }
+        // TODO: support minimum, maximum, exclusiveMinimum, exclusiveMaximum at least for zero
+        return _add_primitive(rule_name == "root" ? "root" : schema_type.get<std::string>(), PRIMITIVE_RULES.at(schema_type.get<std::string>()));
     }
 
     void check_errors() {
@@ -989,6 +1102,134 @@ public:
     }
 };
 
+// common_schema_info implementation (pimpl)
+
+common_schema_info::common_schema_info()
+    : impl_(std::make_unique<common_schema_converter>(
+        [](const std::string &) { return json(); },
+        false)) {}
+
+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) {
+    impl_->resolve_refs(schema, "");
+}
+
+// Determines if a JSON schema can resolve to a string type through any path.
+// 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) {
+    std::unordered_set<std::string> visited_refs;
+
+    std::function<bool(const json &)> check = [&](const json & s) -> bool {
+        if (!s.is_object()) {
+            return false;
+        }
+
+        // Handle $ref
+        if (s.contains("$ref")) {
+            const std::string & ref = s["$ref"];
+            if (visited_refs.find(ref) != visited_refs.end()) {
+                // Circular reference, assume not a string to be safe
+                return false;
+            }
+            visited_refs.insert(ref);
+            auto it = impl_->_refs.find(ref);
+            if (it != impl_->_refs.end()) {
+                return check(it->second);
+            }
+            return false;
+        }
+
+        // Check type field
+        if (s.contains("type")) {
+            const json & schema_type = s["type"];
+            if (schema_type.is_string()) {
+                if (schema_type == "string") {
+                    return true;
+                }
+            } else if (schema_type.is_array()) {
+                // Type can be an array like ["string", "null"]
+                for (const auto & t : schema_type) {
+                    if (t == "string") {
+                        return true;
+                    }
+                }
+            }
+        }
+
+        // Check oneOf/anyOf - if any alternative can be a string
+        if (s.contains("oneOf")) {
+            for (const auto & alt : s["oneOf"]) {
+                if (check(alt)) {
+                    return true;
+                }
+            }
+        }
+        if (s.contains("anyOf")) {
+            for (const auto & alt : s["anyOf"]) {
+                if (check(alt)) {
+                    return true;
+                }
+            }
+        }
+
+        // Check allOf - all components must be compatible with string type
+        if (s.contains("allOf")) {
+            bool all_string = true;
+            for (const auto & component : s["allOf"]) {
+                if (!check(component)) {
+                    all_string = false;
+                    break;
+                }
+            }
+            if (all_string) {
+                return true;
+            }
+        }
+
+        // Check const - if the constant value is a string
+        if (s.contains("const")) {
+            if (s["const"].is_string()) {
+                return true;
+            }
+        }
+
+        // Check enum - if any enum value is a string
+        if (s.contains("enum")) {
+            for (const auto & val : s["enum"]) {
+                if (val.is_string()) {
+                    return true;
+                }
+            }
+        }
+
+        // String-specific keywords imply string type
+        if (s.contains("pattern") || s.contains("minLength") || s.contains("maxLength")) {
+            return true;
+        }
+
+        // Check format - many formats imply string
+        if (s.contains("format")) {
+            const std::string & fmt = s["format"];
+            if (fmt == "date" || fmt == "time" || fmt == "date-time" ||
+                fmt == "uri" || fmt == "email" || fmt == "hostname" ||
+                fmt == "ipv4" || fmt == "ipv6" || fmt == "uuid" ||
+                fmt.find("uuid") == 0) {
+                return true;
+            }
+        }
+
+        return false;
+    };
+
+    return check(schema);
+}
+
 std::string json_schema_to_grammar(const common_json & schema, bool force_gbnf) {
 #ifdef LLAMA_USE_LLGUIDANCE
     if (!force_gbnf) {
@@ -997,29 +1238,25 @@ std::string json_schema_to_grammar(const common_json & schema, bool force_gbnf)
 #else
     (void)force_gbnf;
 #endif // LLAMA_USE_LLGUIDANCE
-    try {
-        return json_schema_to_grammar(common_chat_schema_from_json(schema));
-    } catch (const std::runtime_error & e) {
-        throw std::invalid_argument(std::string("JSON schema conversion failed:\n") + e.what());
-    }
-}
-
-std::string json_schema_to_grammar(const common_chat_schema_document & schema) {
-    common_chat_schema_converter converter(false);
-    converter.visit(*schema.root, "");
-    converter.check_errors();
-    return converter.format_grammar();
+    return build_grammar([&](const common_grammar_builder & callbacks) {
+        auto copy = schema;
+        callbacks.resolve_refs(copy);
+        callbacks.add_schema("", copy);
+    });
 }
 
 std::string build_grammar(const std::function<void(const common_grammar_builder &)> & cb, const common_grammar_options & options) {
-    common_chat_schema_converter converter(options.dotall);
+    common_schema_converter converter([&](const std::string &) { return json(); }, options.dotall);
     common_grammar_builder builder {
         /* .add_rule = */ [&](const std::string & name, const std::string & rule) {
             return converter._add_rule(name, rule);
         },
-        /* .add_schema = */ [&](const std::string & name, const common_chat_schema & schema) {
-            return converter.add_schema(name == "root" ? "" : name, schema);
+        /* .add_schema = */ [&](const std::string & name, const common_json & schema) {
+            return converter.visit(schema, name == "root" ? "" : name);
         },
+        /* .resolve_refs = */ [&](common_json & schema) {
+            converter.resolve_refs(schema, "");
+        }
     };
     cb(builder);
     converter.check_errors();

common/json-schema-to-grammar.h

@@ -1,17 +1,37 @@
 #pragma once
 
-#include "json-schema.h"
 #include "json.h"
 
 #include <functional>
+#include <memory>
 #include <string>
 
-std::string json_schema_to_grammar(const common_json & schema, bool force_gbnf = false);
-std::string json_schema_to_grammar(const common_chat_schema_document & schema);
+std::string json_schema_to_grammar(const common_json & schema,
+                                   bool force_gbnf = false);
+
+class common_schema_converter;
+
+// Probes a JSON schema to extract information about its structure and type constraints.
+class common_schema_info {
+    std::unique_ptr<common_schema_converter> impl_;
+
+  public:
+    common_schema_info();
+    ~common_schema_info();
+
+    common_schema_info(const common_schema_info &) = delete;
+    common_schema_info & operator=(const common_schema_info &) = delete;
+    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);
+};
 
 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_chat_schema &)> add_schema;
+    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;
 };
 
 struct common_grammar_options {

common/json-schema.cpp

@@ -1,514 +0,0 @@
-#include "json-schema.h"
-#include "common.h"
-
-#include <cmath>
-#include <map>
-#include <stdexcept>
-#include <string>
-#include <unordered_set>
-#include <utility>
-#include <vector>
-
-class common_chat_schema_builder {
-    const common_json &      root_;
-    common_chat_schema_document & doc_;
-
-    // the targets built here, moved into doc_ once the whole schema is built
-    std::map<std::string, common_chat_schema_ptr> refs_;
-
-    // ref nodes get their target once every $ref is built, a cycle would otherwise need it too early
-    std::vector<common_chat_schema_ref *> pending_;
-
-    [[noreturn]] static void fail(const std::string & path, const std::string & msg) {
-        throw std::runtime_error("JSON schema error at " + path + ": " + msg);
-    }
-
-    static int get_count(const common_json & schema, const std::string & key, const std::string & path, int def) {
-        if (!schema.contains(key)) {
-            return def;
-        }
-        const common_json & value = schema.at(key);
-        if (!value.is_number_integer() || value.get<int>() < 0) {
-            fail(path, key + " must be a non-negative integer");
-        }
-        return value.get<int>();
-    }
-
-    // a fractional bound is rounded inwards, towards the integers it still admits
-    static int64_t get_bound(const common_json & schema, const std::string & key, const std::string & path, bool round_up) {
-        const common_json & value = schema.at(key);
-        if (value.is_number_integer()) {
-            return value.get<int64_t>();
-        }
-        if (!value.is_number()) {
-            fail(path, key + " must be a number");
-        }
-        double d = value.get<double>();
-        return (int64_t) (round_up ? std::ceil(d) : std::floor(d));
-    }
-
-    static common_chat_schema::string_format get_format(const common_json & schema, const std::string & path) {
-        if (!schema.contains("format")) {
-            return common_chat_schema::FORMAT_NONE;
-        }
-        const common_json & value = schema.at("format");
-        if (!value.is_string()) {
-            fail(path, "format must be a string");
-        }
-        std::string format = value.get<std::string>();
-        if (format == "date") {
-            return common_chat_schema::FORMAT_DATE;
-        }
-        if (format == "time") {
-            return common_chat_schema::FORMAT_TIME;
-        }
-        if (format == "date-time") {
-            return common_chat_schema::FORMAT_DATE_TIME;
-        }
-        if (format == "uuid" || (format.size() == 5 && format.compare(0, 4, "uuid") == 0 && format[4] >= '1' && format[4] <= '5')) {
-            return common_chat_schema::FORMAT_UUID;
-        }
-        return common_chat_schema::FORMAT_NONE;
-    }
-
-    const common_json & resolve_ref(const std::string & ref, const std::string & path) {
-        const common_json * target = &root_;
-        auto tokens = string_split(ref.substr(1), "/");
-        for (size_t i = 1; i < tokens.size(); i++) {
-            const std::string & sel = tokens[i];
-            if (target->is_object() && target->contains(sel)) {
-                target = &target->at(sel);
-            } else if (target->is_array()) {
-                size_t idx;
-                try {
-                    idx = std::stoull(sel);
-                } catch (const std::logic_error &) {
-                    idx = target->size();
-                }
-                if (idx >= target->size()) {
-                    fail(path, "cannot resolve $ref " + ref + ", " + sel + " is out of range");
-                }
-                target = &target->at(idx);
-            } else {
-                fail(path, "cannot resolve $ref " + ref + ", " + sel + " not found");
-            }
-        }
-        return *target;
-    }
-
-    common_chat_schema_ptr build_ref(const common_json & value, const std::string & path) {
-        if (!value.is_string()) {
-            fail(path, "$ref must be a string");
-        }
-        std::string ref = value.get<std::string>();
-        if (ref.compare(0, 2, "#/") != 0) {
-            fail(path, "unsupported $ref " + ref + ", only references into the same document are supported");
-        }
-        if (refs_.find(ref) == refs_.end()) {
-            // reserve the key first, so that a cycle back to this $ref stops here
-            refs_[ref] = nullptr;
-            refs_[ref] = build_node(resolve_ref(ref, path), ref);
-        }
-        auto node = std::make_unique<common_chat_schema_ref>(ref);
-        pending_.push_back(node.get());
-        return node;
-    }
-
-    template <typename T>
-    common_chat_schema_ptr build_alternatives(const common_json & alts, const std::string & path) {
-        if (!alts.is_array()) {
-            fail(path, "must be an array of schemas");
-        }
-        if (alts.empty()) {
-            fail(path, "must not be empty");
-        }
-        auto node = std::make_unique<T>();
-        size_t i = 0;
-        for (const auto & alt : alts) {
-            node->children.push_back(build_node(alt, path + "/" + std::to_string(i++)));
-        }
-        return node;
-    }
-
-    common_chat_schema_ptr build_object(const common_json & schema, const std::string & path) {
-        auto node = std::make_unique<common_chat_schema_object>();
-
-        std::unordered_set<std::string> required;
-        if (schema.contains("required") && schema.at("required").is_array()) {
-            for (const auto & name : schema.at("required")) {
-                if (name.is_string()) {
-                    required.insert(name.get<std::string>());
-                }
-            }
-        }
-
-        if (schema.contains("properties")) {
-            const common_json & properties = schema.at("properties");
-            if (!properties.is_object()) {
-                fail(path, "properties must be an object");
-            }
-            for (const auto & [name, prop] : properties.items()) {
-                node->properties.push_back({name, build_node(prop, path + "/properties/" + name), required.count(name) > 0});
-            }
-        }
-
-        if (schema.contains("additionalProperties")) {
-            const common_json & additional = schema.at("additionalProperties");
-            if (additional.is_boolean()) {
-                if (additional.get<bool>()) {
-                    node->additional_properties = std::make_unique<common_chat_schema_any>();
-                }
-            } else if (additional.is_object()) {
-                node->additional_properties = build_node(additional, path + "/additionalProperties");
-            } else {
-                fail(path, "additionalProperties must be a boolean or a schema");
-            }
-        } else if (!schema.contains("properties")) {
-            // {"type": "object"} on its own accepts any object
-            node->additional_properties = std::make_unique<common_chat_schema_any>();
-        }
-
-        return node;
-    }
-
-    common_chat_schema_ptr build_array(const common_json & schema, const std::string & path) {
-        auto node = std::make_unique<common_chat_schema_array>();
-        if (schema.contains("items") || schema.contains("prefixItems")) {
-            // "items" wins when both are present; as in the converter, a schema instead of an array is the item schema
-            const std::string key = schema.contains("items") ? "items" : "prefixItems";
-            const common_json & items = schema.at(key);
-            if (items.is_array()) {
-                auto tuple = std::make_unique<common_chat_schema_tuple>();
-                size_t i = 0;
-                for (const auto & item : items) {
-                    tuple->items.push_back(build_node(item, path + "/" + key + "/" + std::to_string(i++)));
-                }
-                return tuple;
-            }
-            node->items = build_node(items, path + "/" + key);
-        } else {
-            node->items = std::make_unique<common_chat_schema_any>();
-        }
-        node->min_items = get_count(schema, "minItems", path, 0);
-        node->max_items = get_count(schema, "maxItems", path, -1);
-        return node;
-    }
-
-    common_chat_schema_ptr build_string(const common_json & schema, const std::string & path) {
-        auto node = std::make_unique<common_chat_schema_string>();
-        if (schema.contains("pattern")) {
-            const common_json & pattern = schema.at("pattern");
-            if (!pattern.is_string()) {
-                fail(path, "pattern must be a string");
-            }
-            node->pattern = pattern.get<std::string>();
-        }
-        node->format     = get_format(schema, path);
-        node->min_length = get_count(schema, "minLength", path, 0);
-        node->max_length = get_count(schema, "maxLength", path, -1);
-        return node;
-    }
-
-    common_chat_schema_ptr build_integer(const common_json & schema, const std::string & path) {
-        auto node = std::make_unique<common_chat_schema_integer>();
-        if (schema.contains("minimum")) {
-            node->minimum = get_bound(schema, "minimum", path, /* round_up */ true);
-        } else if (schema.contains("exclusiveMinimum")) {
-            node->minimum = get_bound(schema, "exclusiveMinimum", path, /* round_up */ false) + 1;
-        }
-        if (schema.contains("maximum")) {
-            node->maximum = get_bound(schema, "maximum", path, /* round_up */ false);
-        } else if (schema.contains("exclusiveMaximum")) {
-            node->maximum = get_bound(schema, "exclusiveMaximum", path, /* round_up */ true) - 1;
-        }
-        return node;
-    }
-
-    common_chat_schema_ptr build_node(const common_json & schema, const std::string & path) {
-        if (!schema.is_object()) {
-            fail(path, "schema must be an object");
-        }
-        if (schema.contains("$ref")) {
-            return build_ref(schema.at("$ref"), path);
-        }
-        if (schema.contains("oneOf") || schema.contains("anyOf")) {
-            const std::string key = schema.contains("oneOf") ? "oneOf" : "anyOf";
-            return build_alternatives<common_chat_schema_any_of>(schema.at(key), path + "/" + key);
-        }
-
-        common_json type;
-        if (schema.contains("type")) {
-            type = schema.at("type");
-        }
-        if (type.is_array()) {
-            // {"type": ["a", "b"], ...} is {"anyOf": [{"type": "a", ...}, {"type": "b", ...}]}
-            if (type.empty()) {
-                fail(path, "type must not be empty");
-            }
-            auto node = std::make_unique<common_chat_schema_any_of>();
-            size_t i = 0;
-            for (const auto & t : type) {
-                common_json alt = schema;
-                alt["type"] = t;
-                node->children.push_back(build_node(alt, path + "/type/" + std::to_string(i++)));
-            }
-            return node;
-        }
-        if (schema.contains("const")) {
-            return std::make_unique<common_chat_schema_const>(schema.at("const"));
-        }
-        if (schema.contains("enum")) {
-            const common_json & values = schema.at("enum");
-            if (!values.is_array() || values.empty()) {
-                fail(path, "enum must be a non-empty array");
-            }
-            auto node = std::make_unique<common_chat_schema_enum>();
-            for (const auto & value : values) {
-                node->values.push_back(value);
-            }
-            return node;
-        }
-        if (!type.is_null() && !type.is_string()) {
-            fail(path, "type must be a string or an array of strings");
-        }
-
-        const std::string type_name = type.is_string() ? type.get<std::string>() : "";
-        const bool has_properties = schema.contains("properties") ||
-            (schema.contains("additionalProperties") && schema.at("additionalProperties") != true);
-
-        if (type_name.empty()) {
-            // without a type the structural keywords decide, in the same order as the converter
-            if (has_properties) {
-                return build_object(schema, path);
-            }
-            if (schema.contains("allOf")) {
-                return build_alternatives<common_chat_schema_all_of>(schema.at("allOf"), path + "/allOf");
-            }
-            if (schema.contains("items") || schema.contains("prefixItems")) {
-                return build_array(schema, path);
-            }
-            if (schema.contains("pattern") || schema.contains("minLength") || schema.contains("maxLength") || get_format(schema, path) != common_chat_schema::FORMAT_NONE) {
-                return build_string(schema, path);
-            }
-            return std::make_unique<common_chat_schema_any>();
-        }
-        if (type_name == "object") {
-            if (!has_properties && schema.contains("allOf")) {
-                return build_alternatives<common_chat_schema_all_of>(schema.at("allOf"), path + "/allOf");
-            }
-            return build_object(schema, path);
-        }
-        if (type_name == "string") {
-            if (schema.contains("allOf")) {
-                return build_alternatives<common_chat_schema_all_of>(schema.at("allOf"), path + "/allOf");
-            }
-            return build_string(schema, path);
-        }
-        if (type_name == "array") {
-            return build_array(schema, path);
-        }
-        if (type_name == "integer") {
-            return build_integer(schema, path);
-        }
-        if (type_name == "number") {
-            return std::make_unique<common_chat_schema_number>();
-        }
-        if (type_name == "boolean") {
-            return std::make_unique<common_chat_schema_boolean>();
-        }
-        if (type_name == "null") {
-            return std::make_unique<common_chat_schema_null>();
-        }
-        fail(path, "unrecognized type " + type_name);
-    }
-
-  public:
-    common_chat_schema_builder(const common_json & root, common_chat_schema_document & doc) : root_(root), doc_(doc) {}
-
-    common_chat_schema_ptr build() {
-        auto node = build_node(root_, "#");
-        for (auto & entry : refs_) {
-            doc_.refs[entry.first] = std::move(entry.second);
-        }
-        for (auto * ref : pending_) {
-            ref->target = doc_.refs.at(ref->ref).get();
-        }
-        return node;
-    }
-};
-
-common_chat_schema_document common_chat_schema_from_json(const common_json & schema) {
-    common_chat_schema_document doc;
-    doc.root = common_chat_schema_builder(schema, doc).build();
-    return doc;
-}
-
-static common_chat_schema::value_type json_type(const common_json & value) {
-    if (value.is_null()) {
-        return common_chat_schema::TYPE_NULL;
-    }
-    if (value.is_boolean()) {
-        return common_chat_schema::TYPE_BOOLEAN;
-    }
-    if (value.is_number_integer()) {
-        return common_chat_schema::TYPE_INTEGER;
-    }
-    if (value.is_number()) {
-        return common_chat_schema::TYPE_NUMBER;
-    }
-    if (value.is_string()) {
-        return common_chat_schema::TYPE_STRING;
-    }
-    if (value.is_array()) {
-        return common_chat_schema::TYPE_ARRAY;
-    }
-    return common_chat_schema::TYPE_OBJECT;
-}
-
-static common_chat_schema::type_set value_types_impl(const common_chat_schema & s, std::unordered_set<const common_chat_schema *> & visited) {
-    switch (s.kind()) {
-        case common_chat_schema::KIND_ANY:
-            return common_chat_schema::type_set::all();
-        case common_chat_schema::KIND_NULL:
-            return { common_chat_schema::TYPE_NULL };
-        case common_chat_schema::KIND_BOOLEAN:
-            return { common_chat_schema::TYPE_BOOLEAN };
-        case common_chat_schema::KIND_NUMBER:
-            return { common_chat_schema::TYPE_NUMBER, common_chat_schema::TYPE_INTEGER };
-        case common_chat_schema::KIND_INTEGER:
-            return { common_chat_schema::TYPE_INTEGER };
-        case common_chat_schema::KIND_STRING:
-            return { common_chat_schema::TYPE_STRING };
-        case common_chat_schema::KIND_ARRAY:
-        case common_chat_schema::KIND_TUPLE:
-            return { common_chat_schema::TYPE_ARRAY };
-        case common_chat_schema::KIND_OBJECT:
-            return { common_chat_schema::TYPE_OBJECT };
-        case common_chat_schema::KIND_CONST:
-            return { json_type(static_cast<const common_chat_schema_const &>(s).value) };
-        case common_chat_schema::KIND_ENUM: {
-            common_chat_schema::type_set types;
-            for (const auto & value : static_cast<const common_chat_schema_enum &>(s).values) {
-                types.add(json_type(value));
-            }
-            return types;
-        }
-        case common_chat_schema::KIND_REF: {
-            const auto * target = static_cast<const common_chat_schema_ref &>(s).target;
-            if (!target || !visited.insert(target).second) {
-                // a cycle contributes no type, to be safe
-                return {};
-            }
-            auto types = value_types_impl(*target, visited);
-            visited.erase(target);
-            return types;
-        }
-        case common_chat_schema::KIND_ANY_OF: {
-            common_chat_schema::type_set types;
-            for (const auto & child : static_cast<const common_chat_schema_any_of &>(s).children) {
-                types |= value_types_impl(*child, visited);
-            }
-            return types;
-        }
-        case common_chat_schema::KIND_ALL_OF: {
-            auto types = common_chat_schema::type_set::all();
-            for (const auto & child : static_cast<const common_chat_schema_all_of &>(s).children) {
-                types &= value_types_impl(*child, visited);
-            }
-            return types;
-        }
-    }
-    return {};
-}
-
-common_chat_schema::type_set common_chat_schema::value_types() const {
-    std::unordered_set<const common_chat_schema *> visited;
-    return value_types_impl(*this, visited);
-}
-
-static bool may_be_string_impl(const common_chat_schema & s, std::unordered_set<const common_chat_schema *> & visited) {
-    switch (s.kind()) {
-        case common_chat_schema::KIND_STRING:
-            return true;
-        case common_chat_schema::KIND_CONST:
-            return static_cast<const common_chat_schema_const &>(s).value.is_string();
-        case common_chat_schema::KIND_ENUM:
-            for (const auto & v : static_cast<const common_chat_schema_enum &>(s).values) {
-                if (v.is_string()) {
-                    return true;
-                }
-            }
-            return false;
-        case common_chat_schema::KIND_REF: {
-            // a cycle is taken as not a string, to be safe
-            const auto * target = static_cast<const common_chat_schema_ref &>(s).target;
-            if (!target || !visited.insert(target).second) {
-                return false;
-            }
-            bool result = may_be_string_impl(*target, visited);
-            visited.erase(target);
-            return result;
-        }
-        case common_chat_schema::KIND_ANY_OF:
-            for (const auto & child : static_cast<const common_chat_schema_any_of &>(s).children) {
-                if (may_be_string_impl(*child, visited)) {
-                    return true;
-                }
-            }
-            return false;
-        case common_chat_schema::KIND_ALL_OF: {
-            // every child must allow a string, an any child constrains nothing
-            bool any_string = false;
-            for (const auto & child : static_cast<const common_chat_schema_all_of &>(s).children) {
-                if (child->kind() == common_chat_schema::KIND_ANY) {
-                    continue;
-                }
-                if (!may_be_string_impl(*child, visited)) {
-                    return false;
-                }
-                any_string = true;
-            }
-            return any_string;
-        }
-        default:
-            return false;
-    }
-}
-
-bool common_chat_schema::may_be_string() const {
-    std::unordered_set<const common_chat_schema *> visited;
-    return may_be_string_impl(*this, visited);
-}
-
-const char * common_chat_schema::kind_name(node_kind kind) {
-    switch (kind) {
-        case KIND_ANY:     return "any";
-        case KIND_REF:     return "ref";
-        case KIND_ANY_OF:  return "anyOf";
-        case KIND_ALL_OF:  return "allOf";
-        case KIND_CONST:   return "const";
-        case KIND_ENUM:    return "enum";
-        case KIND_NULL:    return "null";
-        case KIND_BOOLEAN: return "boolean";
-        case KIND_NUMBER:  return "number";
-        case KIND_INTEGER: return "integer";
-        case KIND_STRING:  return "string";
-        case KIND_ARRAY:   return "array";
-        case KIND_TUPLE:   return "tuple";
-        case KIND_OBJECT:  return "object";
-    }
-    return "?";
-}
-
-const char * common_chat_schema::type_name(value_type type) {
-    switch (type) {
-        case TYPE_NULL:    return "null";
-        case TYPE_BOOLEAN: return "boolean";
-        case TYPE_NUMBER:  return "number";
-        case TYPE_INTEGER: return "integer";
-        case TYPE_STRING:  return "string";
-        case TYPE_ARRAY:   return "array";
-        case TYPE_OBJECT:  return "object";
-    }
-    return "?";
-}

common/json-schema.h

@@ -1,198 +0,0 @@
-#pragma once
-
-#include "json.h"
-
-#include <cstdint>
-#include <initializer_list>
-#include <map>
-#include <memory>
-#include <string>
-#include <vector>
-
-// JSON schema, covering the subset that json_schema_to_grammar() can convert.
-
-struct common_chat_schema {
-    enum node_kind {
-        KIND_ANY,
-        KIND_REF,
-        KIND_ANY_OF,
-        KIND_ALL_OF,
-        KIND_CONST,
-        KIND_ENUM,
-        KIND_NULL,
-        KIND_BOOLEAN,
-        KIND_NUMBER,
-        KIND_INTEGER,
-        KIND_STRING,
-        KIND_ARRAY,
-        KIND_TUPLE,
-        KIND_OBJECT,
-    };
-
-    enum value_type {
-        TYPE_NULL,
-        TYPE_BOOLEAN,
-        TYPE_NUMBER,
-        TYPE_INTEGER,
-        TYPE_STRING,
-        TYPE_ARRAY,
-        TYPE_OBJECT,
-    };
-
-    enum string_format {
-        FORMAT_NONE,
-        FORMAT_UUID,  // uuid, uuid1 .. uuid5
-        FORMAT_DATE,
-        FORMAT_TIME,
-        FORMAT_DATE_TIME,
-    };
-
-    class type_set {
-        uint32_t mask_ = 0;
-
-      public:
-        type_set() = default;
-        type_set(std::initializer_list<value_type> types) {
-            for (auto type : types) {
-                add(type);
-            }
-        }
-
-        static type_set all() {
-            return { TYPE_NULL, TYPE_BOOLEAN, TYPE_NUMBER, TYPE_INTEGER, TYPE_STRING, TYPE_ARRAY, TYPE_OBJECT };
-        }
-
-        void add(value_type type) { mask_ |= 1u << type; }
-
-        bool has(value_type type) const { return (mask_ & (1u << type)) != 0; }
-        bool is_only(value_type type) const { return mask_ == (1u << type); }
-        bool empty() const { return mask_ == 0; }
-
-        type_set & operator|=(const type_set & other) { mask_ |= other.mask_; return *this; }
-        type_set & operator&=(const type_set & other) { mask_ &= other.mask_; return *this; }
-
-        bool operator==(const type_set & other) const { return mask_ == other.mask_; }
-        bool operator!=(const type_set & other) const { return mask_ != other.mask_; }
-    };
-
-    virtual ~common_chat_schema() = default;
-    virtual node_kind kind() const = 0;
-
-    type_set value_types() const;
-
-    // Whether a value matching the schema may be a string, through any branch of it.
-    bool may_be_string() const;
-
-    static const char * kind_name(node_kind kind);
-    static const char * type_name(value_type type);
-};
-
-using common_chat_schema_ptr = std::unique_ptr<common_chat_schema>;
-
-struct common_chat_schema_any : common_chat_schema {
-    node_kind kind() const override { return KIND_ANY; }
-};
-
-// {"$ref": "#/..."}, only references into the same document are supported
-struct common_chat_schema_ref : common_chat_schema {
-    std::string                ref;
-    const common_chat_schema * target = nullptr;  // owned by common_chat_schema_document::refs
-
-    explicit common_chat_schema_ref(std::string ref) : ref(std::move(ref)) {}
-
-    node_kind kind() const override { return KIND_REF; }
-};
-
-// oneOf / anyOf, or a "type" array expanded to one alternative per type
-struct common_chat_schema_any_of : common_chat_schema {
-    std::vector<common_chat_schema_ptr> children;
-
-    node_kind kind() const override { return KIND_ANY_OF; }
-};
-
-struct common_chat_schema_all_of : common_chat_schema {
-    std::vector<common_chat_schema_ptr> children;
-
-    node_kind kind() const override { return KIND_ALL_OF; }
-};
-
-struct common_chat_schema_const : common_chat_schema {
-    common_json value;
-
-    explicit common_chat_schema_const(common_json value) : value(std::move(value)) {}
-
-    node_kind kind() const override { return KIND_CONST; }
-};
-
-struct common_chat_schema_enum : common_chat_schema {
-    std::vector<common_json> values;
-
-    node_kind kind() const override { return KIND_ENUM; }
-};
-
-struct common_chat_schema_null : common_chat_schema {
-    node_kind kind() const override { return KIND_NULL; }
-};
-
-struct common_chat_schema_boolean : common_chat_schema {
-    node_kind kind() const override { return KIND_BOOLEAN; }
-};
-
-struct common_chat_schema_number : common_chat_schema {
-    node_kind kind() const override { return KIND_NUMBER; }
-};
-
-// bounds are inclusive, exclusiveMinimum / exclusiveMaximum are folded in
-struct common_chat_schema_integer : common_chat_schema {
-    int64_t minimum = INT64_MIN;  // INT64_MIN for unbounded
-    int64_t maximum = INT64_MAX;  // INT64_MAX for unbounded
-
-    node_kind kind() const override { return KIND_INTEGER; }
-};
-
-struct common_chat_schema_string : common_chat_schema {
-    std::string   pattern;  // empty when absent
-    string_format format     = FORMAT_NONE;
-    int           min_length = 0;
-    int           max_length = -1;  // -1 for unbounded
-
-    node_kind kind() const override { return KIND_STRING; }
-};
-
-struct common_chat_schema_array : common_chat_schema {
-    common_chat_schema_ptr items;  // a common_chat_schema_any when "items" is absent
-    int                    min_items = 0;
-    int                    max_items = -1;  // -1 for unbounded
-
-    node_kind kind() const override { return KIND_ARRAY; }
-};
-
-struct common_chat_schema_tuple : common_chat_schema {
-    std::vector<common_chat_schema_ptr> items;
-
-    node_kind kind() const override { return KIND_TUPLE; }
-};
-
-struct common_chat_schema_property {
-    std::string            name;
-    common_chat_schema_ptr schema;
-    bool                   required = false;
-};
-
-struct common_chat_schema_object : common_chat_schema {
-    std::vector<common_chat_schema_property> properties;             // in schema order
-    common_chat_schema_ptr                   additional_properties;  // null when not allowed
-
-    node_kind kind() const override { return KIND_OBJECT; }
-};
-
-struct common_chat_schema_document {
-    common_chat_schema_ptr                        root;
-    std::map<std::string, common_chat_schema_ptr> refs;
-};
-
-// A document shared by the PEG parsers built from its nodes, which it keeps alive
-using common_chat_schema_document_ptr = std::shared_ptr<const common_chat_schema_document>;
-
-// Throws std::runtime_error when the schema falls outside the supported subset.
-common_chat_schema_document common_chat_schema_from_json(const common_json & schema);

common/json.cpp

@@ -78,21 +78,19 @@ common_json_value::common_json_value(const 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_value::common_json_value(const std::set<T> & vals) : type(VAL_JSON) {
     common_json out = common_json::array();
 
     for (const auto & val : vals) {
         out.push_back(val);
     }
 
-    return std::make_shared<common_json>(std::move(out));
+    val_json = 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)) {}
+#define COMMON_JSON_SET(...) template common_json_value::common_json_value(const std::set<__VA_ARGS__> &);
 
 COMMON_JSON_SET(int)
 COMMON_JSON_SET(std::string)
@@ -100,45 +98,56 @@ 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_value::common_json_value(const std::map<std::string, T> & vals) : type(VAL_JSON) {
     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));
+    val_json = 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)) {}
+#define COMMON_JSON_MAP(...) template common_json_value::common_json_value(const std::map<std::string, __VA_ARGS__> &);
 
 COMMON_JSON_MAP(bool)
 COMMON_JSON_MAP(std::string)
 
 #undef COMMON_JSON_MAP
 
+template <typename T>
+common_json_value::common_json_value(const std::unordered_map<std::string, T> & vals) : type(VAL_JSON) {
+    common_json out = common_json::object();
+
+    for (const auto & val : vals) {
+        out.set({ val.first, val.second });
+    }
+
+    val_json = std::make_shared<common_json>(std::move(out));
+}
+
 // 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)) {}
+#define COMMON_JSON_UMAP(...) template common_json_value::common_json_value(const std::unordered_map<std::string, __VA_ARGS__> &);
 
 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_value::common_json_value(const std::vector<T> & vals) : type(VAL_JSON) {
     common_json out = common_json::array();
 
     for (const auto & val : vals) {
         out.push_back(val);
     }
 
-    return std::make_shared<common_json>(std::move(out));
+    val_json = 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)) {}
+#define COMMON_JSON_VEC(...) template common_json_value::common_json_value(const std::vector<__VA_ARGS__> &);
 
 COMMON_JSON_VEC(int)
 COMMON_JSON_VEC(unsigned char)
@@ -395,6 +404,10 @@ common_json::items_view common_json::items() const {
     return items_view(const_cast<common_json *>(this), size());
 }
 
+template <typename T> T common_json::get() const {
+    return guard([&] { return as_json(this).get<T>(); });
+}
+
 // 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;
@@ -402,7 +415,7 @@ template <> common_json common_json::get<common_json>() const {
 
 // 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__>(); }); }
+#define COMMON_JSON_GET(...) template __VA_ARGS__ common_json::get<__VA_ARGS__>() const;
 
 COMMON_JSON_GET(bool)
 COMMON_JSON_GET(int)
@@ -422,12 +435,3 @@ 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);
-}

common/json.h

@@ -221,14 +221,16 @@ class common_json {
     // 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;
+    operator std::string() const { return get<std::string>(); }
 
     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;
+    std::string value(const std::string & key, const char * def) const {
+        return contains(key) ? at(key).get<std::string>() : std::string(def);
+    }
 
     // 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 {

common/log.cpp

@@ -1,6 +1,5 @@
 #include "common.h"
 #include "log.h"
-#include "json.h"
 
 #include <chrono>
 #include <condition_variable>
@@ -37,16 +36,6 @@ void common_log_set_verbosity_thold(int verbosity) {
     common_log_verbosity_thold = verbosity;
 }
 
-static bool common_log_jsonl = false;
-
-bool common_log_get_jsonl(void) {
-    return common_log_jsonl;
-}
-
-void common_log_set_jsonl(bool jsonl) {
-    common_log_jsonl = jsonl;
-}
-
 static int64_t t_us() {
     return std::chrono::duration_cast<std::chrono::microseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
 }
@@ -77,17 +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};
 
@@ -96,8 +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 };
-    bool is_json      { false }; // msg already holds a serialized JSON object
 
     common_log_entry(size_t size = 256) : msg(size) { }
 
@@ -112,29 +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) {
-            if (is_json) {
-                fprintf(fcur, "%s\n", msg.data());
-                fflush(fcur);
-                return;
-            }
-
-            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]
@@ -288,8 +246,6 @@ public:
         entry.is_end    = false;
         entry.level     = level;
         entry.prefix    = prefix;
-        entry.jsonl     = common_log_jsonl;
-        entry.is_json   = false;
         entry.timestamp = 0;
         if (timestamps) {
             entry.timestamp = t_us() - t_start;
@@ -299,42 +255,6 @@ public:
         cv_new.notify_one();
     }
 
-    void add_json(const char * type, const common_json & obj) {
-        const common_json full = {
-            {"type", type},
-            {"data", obj},
-        };
-
-        const std::string text = full.dump_safe();
-
-        std::unique_lock<std::mutex> lock(mtx);
-
-        // block if the queue is full
-        cv_full.wait(lock, [this]() { return !running || !is_full(); });
-
-        if (!running) {
-            // discard messages while the worker thread is paused
-            return;
-        }
-
-        auto & entry = queue[tail];
-
-        if (entry.msg.size() < text.size() + 1) {
-            entry.msg.resize(text.size() + 1);
-        }
-        memcpy(entry.msg.data(), text.c_str(), text.size() + 1);
-
-        entry.is_end    = false;
-        entry.level     = GGML_LOG_LEVEL_NONE;
-        entry.prefix    = false;
-        entry.jsonl     = true;
-        entry.is_json   = true;
-        entry.timestamp = 0;
-
-        tail = (tail + 1) % queue.size();
-        cv_new.notify_one();
-    }
-
     void resume() {
         std::lock_guard<std::mutex> lock(mtx);
 
@@ -486,14 +406,6 @@ void common_log_add(struct common_log * log, enum ggml_log_level level, const ch
     va_end(args);
 }
 
-void common_log_add_json(struct common_log * log, const char * type, const common_json & obj) {
-    if (!common_log_jsonl) {
-        return;
-    }
-
-    log->add_json(type, obj);
-}
-
 void common_log_set_file(struct common_log * log, const char * file) {
     log->set_file(file);
 }
@@ -526,7 +438,7 @@ void common_log_flush(struct common_log * log) {
     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;
@@ -540,7 +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);
     }

common/log.h

@@ -43,12 +43,6 @@ int  common_log_get_verbosity_thold(void);
 
 void common_log_set_verbosity_thold(int verbosity); // not thread-safe
 
-bool common_log_get_jsonl(void);
-
-void common_log_set_jsonl(bool jsonl); // 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
@@ -130,17 +124,3 @@ void common_log_flush         (struct common_log * log);                    // f
 #define LOG_WRNV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_WARN,  verbosity, __VA_ARGS__)
 #define LOG_ERRV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_ERROR, verbosity, __VA_ARGS__)
 #define LOG_CNTV(verbosity, ...) LOG_TMPL(GGML_LOG_LEVEL_CONT,  verbosity, __VA_ARGS__)
-
-class common_json; // defined in common/json.h
-
-// helper allows different types of json output
-// no-op if --log-jsonl is not set
-void common_log_add_json(struct common_log * log, const char * type, const common_json & data);
-
-// will only print if --log-jsonl is set
-#define LOG_JSON(type, data) \
-    do { \
-        if (common_log_get_jsonl()) { \
-            common_log_add_json(common_log_main(), type, data); \
-        } \
-    } while (0)

common/parsers/cohere2moe.cpp

@@ -1,141 +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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, ACTION_START }
-        };
-    }
-
-    return data;
-}

common/parsers/deepseek.cpp

@@ -1,267 +0,0 @@
-#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");
-
-                std::vector<common_peg_parser> required_parsers;
-                std::vector<common_peg_parser> optional_parsers;
-                foreach_parameter(function, [&](const common_chat_schema_property & param, const common_chat_schema_document_ptr & doc) {
-                    bool is_string = param.schema->may_be_string();
-
-                    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",
-                                                            doc, *param.schema))) +
-                        p.tool_arg_close(p.literal(PARAM_END)));
-
-                    auto named_arg = p.rule("tool-" + name + "-arg-" + param.name, arg);
-                    if (param.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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, FC_START },
-        };
-    }
-
-    return data;
-}

common/parsers/functionary-v3-2.cpp

@@ -1,96 +0,0 @@
-#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   = common_chat_tool_parameters(function);
-
-            // 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) {
-            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;
-}

common/parsers/gemma4.cpp

@@ -1,303 +0,0 @@
-#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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "<|tool_call>" },
-        };
-    }
-
-    return data;
-}

common/parsers/gigachat-v3.cpp

@@ -1,76 +0,0 @@
-#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 = common_chat_tool_parameters(function);
-
-                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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            {COMMON_GRAMMAR_TRIGGER_TYPE_WORD, tool_call_start_prefix}
-        };
-    }
-    return data;
-}

common/parsers/gpt-oss.cpp

@@ -1,158 +0,0 @@
-#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   = common_chat_tool_parameters(function);
-
-                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) {
-            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;
-}

common/parsers/kimi-k2.cpp

@@ -1,128 +0,0 @@
-#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   = common_chat_tool_parameters(function);
-
-            // 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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "<|tool_call_begin|>" }
-        };
-    }
-
-    return data;
-}

common/parsers/kimi-k3.cpp

@@ -1,167 +0,0 @@
-#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   = common_chat_tool_parameters(function);
-
-            // 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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, TOOLS_START },
-        };
-    }
-
-    return data;
-}

common/parsers/lfm2.cpp

@@ -1,110 +0,0 @@
-#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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, TOOL_CALL_START }
-        };
-    }
-
-    return data;
-}

common/parsers/minicpm5.cpp

@@ -1,130 +0,0 @@
-#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");
-
-                std::vector<common_peg_parser> arg_rules;
-                foreach_parameter(function, [&](const common_chat_schema_property & prop, const common_chat_schema_document_ptr & doc) {
-                    auto value_parser = p.eps();
-                    if (prop.schema->may_be_string()) {
-                        value_parser = string_value;
-                    } else {
-                        value_parser = p.tool_arg_json_value(
-                                p.schema(p.json(), "tool-" + name + "-arg-" + prop.name + "-schema", doc, *prop.schema)
-                            ) + p.tool_arg_close(p.literal("</param>"));
-                    }
-
-                    arg_rules.push_back(p.tool_arg(
-                        p.tool_arg_open(p.literal("<param name=\"") + p.tool_arg_name(p.literal(prop.name)) + p.literal("\">")) +
-                        value_parser
-                    ));
-                });
-
-                auto args = p.eps();
-                if (!arg_rules.empty()) {
-                    args = p.zero_or_more(p.choice(arg_rules) + 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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "<function" },
-        };
-    }
-
-    return data;
-}

common/parsers/minimax-m3.cpp

@@ -1,229 +0,0 @@
-#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 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   = common_chat_tool_parameters(function);
-            auto         doc      = std::make_shared<const common_chat_schema_document>(common_chat_schema_from_json(params));
-
-            // The template expands argument values recursively in XML (see the to_xml() macro)
-            std::function<common_peg_parser(const common_chat_schema &, const std::string &, const std::string &)> value_of;
-            std::function<common_peg_parser(const common_chat_schema_object &, const std::string &)>              members_of;
-
-            auto element_of = [&](const std::string & tag, const common_chat_schema & 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 common_chat_schema & 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.may_be_string()) {
-                    return p.ac(p.tool_arg_string_value(p.until(close)) + close_tag, close);
-                }
-
-                if (schema.kind() == common_chat_schema::KIND_ANY_OF) {
-                    std::vector<common_peg_parser> choices;
-
-                    size_t index = 0;
-                    for (const auto & alternative : static_cast<const common_chat_schema_any_of &>(schema).children) {
-                        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);
-                }
-
-                if (schema.kind() == common_chat_schema::KIND_OBJECT) {
-                    const auto & object = static_cast<const common_chat_schema_object &>(schema);
-                    if (!object.properties.empty()) {
-                        return p.tag(mm3::TOOL_ARG_OBJECT, members_of(object, rule_name)) + p.space() + close_tag;
-                    }
-                }
-
-                if (schema.kind() == common_chat_schema::KIND_ARRAY) {
-                    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(*static_cast<const common_chat_schema_array &>(schema).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", doc, schema)) + close_tag;
-            };
-
-            // Required properties in schema order, then any number of optional ones in any order.
-            members_of = [&](const common_chat_schema_object & object, const std::string & rule_prefix) -> common_peg_parser {
-                std::vector<common_peg_parser> required_elements;
-                std::vector<common_peg_parser> optional_elements;
-                for (const auto & prop : object.properties) {
-                    auto element = element_of(prop.name, *prop.schema, rule_prefix + "-" + prop.name);
-                    (prop.required ? required_elements : 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 = p.eps();
-            if (doc->root->kind() == common_chat_schema::KIND_OBJECT) {
-                invoke_body = members_of(static_cast<const common_chat_schema_object &>(*doc->root), "tool-" + name + "-arg");
-            }
-
-            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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, FC_START },
-        };
-    }
-
-    return data;
-}

common/parsers/ministral3.cpp

@@ -1,126 +0,0 @@
-#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   = common_chat_tool_parameters(function);
-
-                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) {
-            parser.build_grammar(builder, data.grammar_lazy);
-        });
-
-        data.grammar_triggers = {
-            { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "[TOOL_CALLS]" }
-        };
-    }
-
-    return data;
-}

common/parsers/muse-glimmer.cpp

@@ -1,138 +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");
-
-                std::vector<common_peg_parser> arg_rules;
-                foreach_parameter(function, [&](const common_chat_schema_property & prop, const common_chat_schema_document_ptr & doc) {
-                    auto value_parser = p.eps();
-                    if (prop.schema->may_be_string()) {
-                        value_parser = string_value;
-                    } else {
-                        value_parser = p.tool_arg_json_value(
-                                p.schema(p.json(), "tool-" + name + "-arg-" + prop.name + "-schema", doc, *prop.schema))
-                            + p.tool_arg_close(p.literal("</atem:parameter>"));
-                    }
-
-                    arg_rules.push_back(p.tool_arg(
-                        p.tool_arg_open(p.literal("<atem:parameter name=\"") + p.tool_arg_name(p.literal(prop.name)) + p.literal("\">")) +
-                        value_parser));
-                });
-
-                auto args = p.eps();
-                if (!arg_rules.empty()) {
-                    args = p.zero_or_more(p.choice(arg_rules) + 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) {
-            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;
-}

common/parsers/parsers.cpp

@@ -1,25 +0,0 @@
-#include "parsers.h"
-
-#include "log.h"
-
-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 common_chat_schema_property &, const common_chat_schema_document_ptr &)> & fn) {
-    auto         params = common_chat_tool_parameters(function);
-    auto         doc    = std::make_shared<const common_chat_schema_document>(common_chat_schema_from_json(params));
-    const auto * object = dynamic_cast<const common_chat_schema_object *>(doc->root.get());
-    if (!object) {
-        return;
-    }
-    for (const auto & prop : object->properties) {
-        fn(prop, doc);
-    }
-}

common/parsers/parsers.h

@@ -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, with the document that owns them
-void foreach_parameter(const json & function, const std::function<void(const common_chat_schema_property &, const common_chat_schema_document_ptr &)> & 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);

common/parsers/qwen3-coder.cpp

@@ -1,193 +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");
-
-                std::vector<common_peg_parser> required_args;
-                std::vector<common_peg_parser> optional_args;
-
-                foreach_parameter(function, [&](const common_chat_schema_property & param, const common_chat_schema_document_ptr & doc) {
-                    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 types = param.schema->value_types();
-
-                    auto arg_value = p.eps();
-                    if (!types.has(common_chat_schema::TYPE_STRING)) {
-                        arg_value = p.tool_arg_json_value(p.schema(p.json(), rule_name + "-schema", doc, *param.schema)) + arg_close;
-                    } else if (types.is_only(common_chat_schema::TYPE_STRING)) {
-                        arg_value = arg_string;
-                    } else {
-                        // The string alternative accepts any text, so the grammar only keeps the raw string
-                        // rule. The parser still tries the JSON alternatives first to type the value.
-                        auto json_value = p.choice();
-                        if (types.has(common_chat_schema::TYPE_OBJECT)) {
-                            json_value |= p.json_object();
-                        }
-                        if (types.has(common_chat_schema::TYPE_ARRAY)) {
-                            json_value |= p.json_array();
-                        }
-                        if (types.has(common_chat_schema::TYPE_NUMBER) || types.has(common_chat_schema::TYPE_INTEGER)) {
-                            json_value |= p.json_number();
-                        }
-                        if (types.has(common_chat_schema::TYPE_BOOLEAN)) {
-                            json_value |= p.json_bool();
-                        }
-                        if (types.has(common_chat_schema::TYPE_NULL)) {
-                            json_value |= p.json_null();
-                        }
-                        arg_value = p.gbnf(p.atomic(p.tool_arg_json_value(json_value) + arg_close) | arg_string, "xml-arg-string");
-                    }
-
-                    auto arg_rule = p.rule(rule_name, p.tool_arg(arg_open + arg_value));
-
-                    (param.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) {
-            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;
-}

common/parsers/sources.cmake

@@ -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
-)

common/peg-parser.cpp

@@ -953,7 +953,7 @@ std::string common_peg_arena::dump_impl(common_peg_parser_id
         } else if constexpr (std::is_same_v<T, common_peg_until_parser>) {
             return "Until(" + string_join(p.delimiters, " | ") + ")";
         } else if constexpr (std::is_same_v<T, common_peg_schema_parser>) {
-            return "Schema(" + dump_impl(p.child, visited) + ", " + (p.node ? common_chat_schema::kind_name(p.node->kind()) : "null") + ")";
+            return "Schema(" + dump_impl(p.child, visited) + ", " + (p.schema ? p.schema->dump() : "null") + ")";
         } else if constexpr (std::is_same_v<T, common_peg_rule_parser>) {
             return "Rule(" + p.name + ", " + dump_impl(p.child, visited) + ")";
         } else if constexpr (std::is_same_v<T, common_peg_ref_parser>) {
@@ -1119,13 +1119,8 @@ 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, common_chat_schema_document_ptr doc, const common_chat_schema & node, bool raw) {
-    return wrap(arena_.add_parser(common_peg_schema_parser{p.id(), name, std::move(doc), &node, raw}));
-}
-
 common_peg_parser common_peg_parser_builder::schema(const common_peg_parser & p, const std::string & name, const common_json & schema, bool raw) {
-    auto doc = std::make_shared<const common_chat_schema_document>(common_chat_schema_from_json(schema));
-    return this->schema(p, name, doc, *doc->root, 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::rule(const std::string & name, const common_peg_parser & p, bool trigger) {
@@ -1578,9 +1573,30 @@ static std::set<std::string> collect_reachable_rules(
 
 // GBNF generation implementation
 void common_peg_arena::build_grammar(const common_grammar_builder & builder, bool lazy) const {
-    // A raw string value is parsed by the child rather than constrained by the schema
     auto schema_delegates = [](const common_peg_schema_parser & s) -> bool {
-        return !s.node || (s.raw && s.node->may_be_string());
+        if (!s.schema) {
+            return true;
+        }
+        if (s.raw && s.schema->contains("type")) {
+            const auto & type_val = s.schema->at("type");
+            if (type_val.is_string() && type_val == "string") {
+                return true;
+            }
+            // Handle nullable types like ["string", "null"] - delegate when the
+            // non-null type is string, since the tagged format uses raw text
+            if (type_val.is_array()) {
+                for (const auto & t : type_val) {
+                    if (t.is_string() && t.get<std::string>() != "null") {
+                        return t.get<std::string>() == "string";
+                    }
+                }
+            }
+        }
+        // Delegate for enum schemas in raw mode - enum values are literal strings
+        if (s.raw && !s.schema->contains("type") && s.schema->contains("enum")) {
+            return true;
+        }
+        return false;
     };
 
     // Unwrap the parser so we can properly check if it's a sequence or choice
@@ -1715,7 +1731,7 @@ void common_peg_arena::build_grammar(const common_grammar_builder & builder, boo
                 if (schema_delegates(p)) {
                     return to_gbnf(p.child);
                 }
-                return builder.add_schema(p.name, *p.node);
+                return builder.add_schema(p.name, *p.schema);
             } else if constexpr (std::is_same_v<T, common_peg_rule_parser>) {
                 return p.name;
             } else if constexpr (std::is_same_v<T, common_peg_ref_parser>) {
@@ -1843,6 +1859,7 @@ 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)},
                 {"raw", p.raw}
             };
         } else if constexpr (std::is_same_v<T, common_peg_rule_parser>) {
@@ -1982,12 +1999,15 @@ static common_peg_parser_variant deserialize_parser_variant(const common_json &
         return common_peg_until_parser{j["delimiters"].get<std::vector<std::string>>()};
     }
     if (type == "schema") {
-        if (!j.contains("child") || !j.contains("name") || !j.contains("raw")) {
+        if (!j.contains("child") || !j.contains("name") || !j.contains("schema") || !j.contains("raw")) {
             throw std::runtime_error("schema parser missing required fields");
         }
         common_peg_schema_parser parser;
         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.raw = j["raw"].get<bool>();
         return parser;
     }

common/peg-parser.h

@@ -1,6 +1,5 @@
 #pragma once
 
-#include "json-schema.h"
 #include "json.h"
 
 #include <memory>
@@ -246,8 +245,7 @@ struct common_peg_until_parser {
 struct common_peg_schema_parser {
     common_peg_parser_id child;
     std::string name;
-    common_chat_schema_document_ptr doc;  // owns node
-    const common_chat_schema * node = nullptr;
+    std::shared_ptr<common_json> schema;
 
     // Indicates if the GBNF should accept a raw string that matches the schema.
     bool raw;
@@ -490,10 +488,8 @@ class common_peg_parser_builder {
     // A marker, i.e. text delimited by a pair of <> or []
     common_peg_parser marker();
 
-    // Wraps a parser with the schema its GBNF is generated from, a node of the document that owns it
-    common_peg_parser schema(const common_peg_parser & p, const std::string & name, common_chat_schema_document_ptr doc, const common_chat_schema & node, bool raw = false);
-
-    // Parses the JSON schema into a document of its own
+    // Wraps a parser with JSON schema metadata for grammar generation.
+    // Used internally to convert JSON schemas to GBNF grammar rules.
     common_peg_parser schema(const common_peg_parser & p, const std::string & name, const common_json & schema, bool raw = false);
 
     // Creates a named rule, stores it in the grammar, and returns a ref.

common/speculative.cpp

@@ -14,7 +14,6 @@
 
 #include <algorithm>
 #include <cassert>
-#include <cmath>
 #include <cstring>
 #include <iomanip>
 #include <map>
@@ -139,7 +138,6 @@ struct common_speculative_impl {
     const common_speculative_type type;
 
     uint32_t n_seq;
-    int32_t n_max; // maximum draft length after implementation-specific limits
 
     size_t n_call_begin  = 0; // number of times this implementation was called for refresh.
     size_t n_call_draft  = 0; // number of times this implementation was called for generation.
@@ -159,7 +157,7 @@ struct common_speculative_impl {
     int64_t t_draft_us  = 0; // total time spent in generating drafts in this implementation in microseconds.
     int64_t t_accept_us = 0; // total time spent in accumulation of this implementation in microseconds.
 
-    common_speculative_impl(common_speculative_type type, uint32_t n_seq, int32_t n_max) : type(type), n_seq(n_seq), n_max(n_max) {}
+    common_speculative_impl(common_speculative_type type, uint32_t n_seq) : type(type), n_seq(n_seq) {}
 
     virtual ~common_speculative_impl() = default;
 
@@ -184,7 +182,7 @@ struct common_speculative_impl_draft_simple : public common_speculative_impl {
     std::vector<common_sampler_ptr> smpls;
 
     common_speculative_impl_draft_simple(const common_params_speculative & params, uint32_t n_seq)
-        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_DRAFT_SIMPLE, n_seq, params.draft.n_max)
+        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_DRAFT_SIMPLE, n_seq)
         , params(params.draft)
     {
         auto * ctx_dft = this->params.ctx_dft;
@@ -296,7 +294,7 @@ struct common_speculative_impl_draft_simple : public common_speculative_impl {
             drafting[seq_id] = true;
             common_sampler_reset(smpls[seq_id].get());
 
-            common_batch_add(batch, dp.id_last, dp.pos0, { seq_id }, true);
+            common_batch_add(batch, dp.id_last, dp.n_past, { seq_id }, true);
         }
 
         int ret = llama_decode(ctx_dft, batch);
@@ -355,7 +353,7 @@ struct common_speculative_impl_draft_simple : public common_speculative_impl {
                     continue;
                 }
 
-                common_batch_add(batch, id, dp.pos0 + i + 1, { seq_id }, true);
+                common_batch_add(batch, id, dp.n_past + i + 1, { seq_id }, true);
             }
 
             if (batch.n_tokens == 0) {
@@ -454,7 +452,7 @@ struct common_speculative_impl_draft_eagle3 : public common_speculative_impl {
     std::vector<float> g_embd_buf;
 
     common_speculative_impl_draft_eagle3(const common_params_speculative & params, uint32_t n_seq)
-        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_DRAFT_EAGLE3, n_seq, params.draft.n_max)
+        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_DRAFT_EAGLE3, n_seq)
         , params(params.draft)
     {
         SPC_TRC("%s", "adding speculative implementation 'draft-eagle3'\n");
@@ -925,25 +923,21 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
     int32_t     block_size    = 0;
     llama_token mask_token_id = 0;
 
-    bool    is_dflash2     = false;
-    bool    is_mrope       = false;
-    int32_t selector_top_k = 0;
-
     // draft-dspark: the draft carries a Markov head and uses an anchor-first block layout
     const bool is_dspark;
 
     // dspark speculators
     bool sample_from_anchor = true;
 
-    // block-internal attention
-    bool causal_attn = false;
-
     const int32_t * target_layer_ids   = nullptr; // model_dft's extract layer indices
     uint32_t        target_layer_ids_n = 0;
 
+    // scratch buffer for concatenated target features [n_tokens, n_embd_enc]
+    std::vector<float> features_buf;
+
     common_speculative_impl_draft_dflash(const common_params_speculative & params, uint32_t n_seq,
             common_speculative_type type = COMMON_SPECULATIVE_TYPE_DRAFT_DFLASH)
-        : common_speculative_impl(type, n_seq, params.draft.n_max)
+        : common_speculative_impl(type, n_seq)
         , params(params.draft)
         , is_dspark(type == COMMON_SPECULATIVE_TYPE_DRAFT_DSPARK)
     {
@@ -972,25 +966,9 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
             if (llama_model_meta_val_str(model_dft, "dflash.sample_from_anchor", buf, sizeof(buf)) >= 0) {
                 sample_from_anchor = std::strcmp(buf, "true") == 0;
             }
-            if (llama_model_meta_val_str(model_dft, "dflash.attention.causal", buf, sizeof(buf)) >= 0) {
-                causal_attn = std::strcmp(buf, "true") == 0;
-            }
         }
-
-        selector_top_k = llama_model_dflash_selector_top_k(model_dft);
-        is_dflash2     = selector_top_k > 0;
         mask_token_id = llama_vocab_mask(llama_model_get_vocab(model_dft));
 
-        if (is_dspark && this->params.p_min > 0.0f) {
-            char buf[16] = {};
-            const bool has_conf =
-                llama_model_meta_val_str(model_dft, "dflash.has_confidence_head", buf, sizeof(buf)) < 0 ||
-                std::strcmp(buf, "true") == 0;
-            if (!has_conf) {
-                throw std::runtime_error("DSpark draft has no confidence head: please set --spec-draft-p-min 0");
-            }
-        }
-
         LOG_INF("%s: adding speculative implementation '%s'\n", __func__, common_speculative_type_to_str(type).c_str());
         LOG_INF("%s: - n_max=%d, n_min=%d, p_min=%.2f\n", __func__, this->params.n_max, this->params.n_min, this->params.p_min);
         LOG_INF("%s: - block_size=%d, mask_token_id=%d, n_extract=%u, sample_from_anchor=%s\n", __func__,
@@ -1005,17 +983,9 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
             this->params.n_max = std::min(this->params.n_max, n_draft_max);
             this->params.n_min = std::min(this->params.n_min, n_draft_max);
         }
-        this->n_max = this->params.n_max;
 
         batch        = llama_batch_init(llama_n_batch(ctx_dft), 0,          n_seq);
-        batch_inject = llama_batch_init(llama_n_ubatch(ctx_dft), n_embd_enc, n_seq);
-
-        // embd batches on an M-RoPE draft need 4 position rows per token
-        is_mrope = llama_model_rope_type(model_dft) == LLAMA_ROPE_TYPE_MROPE;
-        if (is_mrope) {
-            free(batch_inject.pos);
-            batch_inject.pos = (llama_pos *) malloc(sizeof(llama_pos) * 4 * llama_n_batch(ctx_dft));
-        }
+        batch_inject = llama_batch_init(llama_n_batch(ctx_dft), n_embd_dec, n_seq);
 
         smpls.resize(n_seq);
         for (auto & s : smpls) {
@@ -1028,7 +998,7 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
 
         // offload draft sampling to the backend
         backend_chains.assign(n_seq, nullptr);
-        if (this->params.backend_sampling && !is_dflash2) {
+        if (this->params.backend_sampling) {
             for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) n_seq; ++seq_id) {
                 llama_sampler * chain = llama_sampler_chain_init(llama_sampler_chain_default_params());
                 llama_sampler_chain_add(chain, llama_sampler_init_top_k(10));
@@ -1047,9 +1017,8 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
             llama_set_embeddings_layer_inp(ctx_tgt, (uint32_t) target_layer_ids[k], true);
         }
 
-        // DFlash2 reads its selector lattice from h_nextn and never consumes raw logits.
-        llama_set_embeddings_nextn(ctx_dft, true, /*masked*/ !is_dflash2);
-        llama_set_causal_attn(ctx_dft, causal_attn); // DFlash needs non-causal attention unless the model says otherwise
+        llama_set_embeddings_nextn(ctx_dft, true, /*masked*/ true);
+        llama_set_causal_attn(ctx_dft, false); // DFlash needs non-causal attention
     }
 
     ~common_speculative_impl_draft_dflash() override {
@@ -1094,7 +1063,8 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
 
         // Target prefill may contain token IDs or multimodal embeddings. Both
         // produce the target-layer features used to seed the draft KV cache, so
-        // embeddings are injected too, except the pinned ones skipped below.
+        // skipping the embedding batches leaves a hole in the draft's cache and
+        // the next injection fails to initialize.
         // TODO: revisit after https://github.com/ggml-org/llama.cpp/pull/24669 is merged
         const bool has_tokens     = batch_in.token != nullptr;
         const bool has_embeddings = batch_in.embd  != nullptr;
@@ -1130,44 +1100,55 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
             }
             const int32_t n_rows = i_batch_end[seq_id] - i_batch_beg[seq_id] + 1;
 
-            // an M-RoPE image pins all its rows to one position, so a windowed draft
-            // cache cannot free cells for it - skip it, the draft can jump over the gap
-            const bool pos_pinned = batch_in.pos[i_batch_beg[seq_id]] == batch_in.pos[i_batch_end[seq_id]];
-            if (has_embeddings && n_rows > 1 && pos_pinned) {
-                continue;
-            }
-
             for (int32_t offset = 0; offset < n_rows; offset += n_ubatch) {
                 const int32_t n_chunk = std::min(n_ubatch, n_rows - offset);
 
-                // gather target features per extract layer; the fused decode encodes and
-                // injects them into the K/V cache at the target positions
-                batch_inject.n_tokens = n_chunk;
+                // gather this chunk's target features, interleaved by extract layer
+                features_buf.resize((size_t) n_chunk * n_embd_enc);
                 for (uint32_t k = 0; k < target_layer_ids_n; ++k) {
                     const float * layer = llama_get_embeddings_layer_inp(ctx_tgt, (uint32_t) target_layer_ids[k]);
                     if (!layer) {
                         GGML_ABORT("DFlash: target layer %d input not extracted.", target_layer_ids[k]);
                     }
                     for (int32_t i = 0; i < n_chunk; ++i) {
-                        float       * dst = batch_inject.embd + (size_t) i * n_embd_enc + k * (size_t) n_embd_tgt;
+                        float       * dst = features_buf.data() + (size_t) i * n_embd_enc + k * (size_t) n_embd_tgt;
                         const float * src = layer + (size_t) (i_batch_beg[seq_id] + offset + i) * n_embd_tgt;
                         std::memcpy(dst, src, (size_t) n_embd_tgt * sizeof(float));
                     }
                 }
 
+                // fuse extracted features through DFlash encoder
+                llama_batch enc_batch = {
+                    /*.n_tokens =*/ n_chunk,
+                    /*.token    =*/ nullptr,
+                    /*.embd     =*/ features_buf.data(),
+                    /*.pos      =*/ nullptr,
+                    /*.n_seq_id =*/ nullptr,
+                    /*.seq_id   =*/ nullptr,
+                    /*.logits   =*/ nullptr,
+                };
+
+                int32_t rc = llama_encode(ctx_dft, enc_batch);
+                if (rc != 0) {
+                    LOG_ERR("%s: llama_encode(ctx_dft) failed rc=%d (n_tokens=%d, offset=%d)\n",
+                            __func__, rc, (int) n_chunk, (int) offset);
+                    return false;
+                }
+
+                const float * inp_g = llama_get_embeddings_nextn(ctx_dft);
+                GGML_ASSERT(inp_g && "DFlash encoder produced no output.");
+
+                // inject the DFlash decoder K/V cache at the tokens' target positions
+                batch_inject.n_tokens = n_chunk;
+                std::memcpy(batch_inject.embd, inp_g, (size_t) n_chunk * n_embd_dec * sizeof(float));
+
                 for (int32_t i = 0; i < n_chunk; ++i) {
-                    const llama_pos p = batch_in.pos[i_batch_beg[seq_id] + offset + i];
-                    batch_inject.pos[i] = p;
-                    if (is_mrope) {
-                        batch_inject.pos[1 * n_chunk + i] = p;
-                        batch_inject.pos[2 * n_chunk + i] = p;
-                        batch_inject.pos[3 * n_chunk + i] = 0;
-                    }
+                    batch_inject.pos[i]       = batch_in.pos[i_batch_beg[seq_id] + offset + i];
                     batch_inject.n_seq_id[i]  = 1;
                     batch_inject.seq_id[i][0] = seq_id;
                     batch_inject.logits[i]    = false;
                 }
-                const int32_t rc = llama_decode(ctx_dft, batch_inject);
+                rc = llama_decode(ctx_dft, batch_inject);
                 if (rc != 0) {
                     LOG_ERR("%s: llama_decode(ctx_dft) failed rc=%d (n_tokens=%d, offset=%d)\n",
                             __func__, rc, (int) n_chunk, (int) offset);
@@ -1197,7 +1178,7 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
 
             common_sampler_reset(smpls[seq_id].get());
 
-            const int32_t n = (int32_t) dp.pos0;
+            const int32_t n = (int32_t) dp.n_past;
 
             const int32_t n_draft = params.n_max;
 
@@ -1205,7 +1186,7 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
             i_block_beg[seq_id] = batch.n_tokens;
             n_block    [seq_id] = n_block_tokens;
             for (int32_t i = 0; i < n_block_tokens; ++i) {
-                common_batch_add(batch, i == 0 ? dp.id_last : mask_token_id, n + i, { seq_id }, !is_dflash2);
+                common_batch_add(batch, i == 0 ? dp.id_last : mask_token_id, n + i, { seq_id }, true);
             }
         }
 
@@ -1233,36 +1214,6 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
 
             auto & result = *dp.result;
 
-            if (is_dflash2) {
-                const float * lattice = llama_get_embeddings_nextn(ctx_dft);
-                GGML_ASSERT(lattice && "DFlash2 selector produced no lattice");
-
-                int32_t predecessor = 0;
-                for (int32_t i = 1; i < n_block_tokens; ++i) {
-                    const float * row = lattice + (size_t) (beg + i) * n_embd_dec;
-                    const float * scores = row + selector_top_k + (size_t) predecessor * selector_top_k;
-
-                    predecessor = (int32_t) std::distance(scores,
-                            std::max_element(scores, scores + selector_top_k));
-                    if (params.p_min > 0.0f) {
-                        // softmax(scores) at the argmax, i.e. 1 / sum(exp(s_k - s_max))
-                        float sum = 0.0f;
-                        for (int32_t k = 0; k < selector_top_k; ++k) {
-                            sum += std::exp(scores[k] - scores[predecessor]);
-                        }
-                        if (1.0f / sum < params.p_min) {
-                            break;
-                        }
-                    }
-                    result.push_back((llama_token) row[predecessor]);
-                }
-
-                if (result.size() < (size_t) params.n_min) {
-                    result.clear();
-                }
-                continue;
-            }
-
             if (is_dspark) {
                 // DSpark: read from the first draft slot, truncate below the confidence threshold
                 const float * conf = params.p_min > 0.0f ? llama_get_embeddings_nextn(ctx_dft) : nullptr;
@@ -1364,7 +1315,7 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
     std::vector<std::vector<float>> chain_h;
 
     common_speculative_impl_draft_mtp(const common_params_speculative & params, uint32_t n_seq)
-        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_DRAFT_MTP, n_seq, params.draft.n_max)
+        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_DRAFT_MTP, n_seq)
         , params(params.draft)
     {
         auto * ctx_tgt = this->params.ctx_tgt;
@@ -1431,7 +1382,6 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
                 c.reserve((size_t) (this->params.n_max + 1) * n_embd);
             }
         }
-        this->n_max = this->params.n_max;
 
         pending_h.assign(n_seq, std::vector<float>(n_embd, 0.0f));
 
@@ -1493,7 +1443,7 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
 
         const int32_t n_tokens = batch_in.n_tokens;
 
-        // remember the first and last batch index for each sequence
+        // remember the frist and last batch index for each sequence
         std::fill(i_batch_beg.begin(), i_batch_beg.end(), -1);
         std::fill(i_batch_end.begin(), i_batch_end.end(), -1);
 
@@ -1621,7 +1571,7 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
             drafting[seq_id] = true;
             common_sampler_reset(smpls[seq_id].get());
 
-            common_batch_add(batch, dp.id_last, dp.pos0, { seq_id }, true);
+            common_batch_add(batch, dp.id_last, dp.n_past, { seq_id }, true);
             std::memcpy(batch.embd + (size_t) (batch.n_tokens - 1) * n_embd, pending_h[seq_id].data(), row_bytes);
 
             i_last[seq_id] = batch.n_tokens - 1;
@@ -1635,16 +1585,16 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
 
         while (n_drafting > 0) {
             // each step decodes under a different head, i.e. a different decoder layer, and
-            // KV is per layer. process() filled this layer's KV only for positions < pos0
+            // KV is per layer. process() filled this layer's KV only for positions < n_past
             // (prompt + accepted prefix) — nothing in the draft region yet. so reset the
-            // draft region (the seq_rm lower bound is pos0, leaving the prompt KV intact)
+            // draft region (the seq_rm lower bound is n_past, leaving the prompt KV intact)
             // and select head i so it rebuilds its own layer's KV there; decoding just the
             // latest token would leave its attention reading cells only another head wrote.
             if (chain_heads) {
                 auto * mem_dft = llama_get_memory(ctx_dft);
                 for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) n_seq; ++seq_id) {
                     if (drafting[seq_id]) {
-                        llama_memory_seq_rm(mem_dft, seq_id, dparams[seq_id].pos0, -1);
+                        llama_memory_seq_rm(mem_dft, seq_id, dparams[seq_id].n_past, -1);
                     }
                 }
                 llama_set_nextn_layer_offset(ctx_dft, i);
@@ -1710,17 +1660,17 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
                     const int n_rows = (int) result.size() + 1; // id_last + tokens drafted so far
                     for (int t = 0; t < n_rows; ++t) {
                         const llama_token tok = (t == 0) ? dp.id_last : result[t - 1];
-                        common_batch_add(batch, tok, dp.pos0 + t, { seq_id }, t == n_rows - 1);
+                        common_batch_add(batch, tok, dp.n_past + t, { seq_id }, t == n_rows - 1);
                         std::memcpy(batch.embd + (size_t) (batch.n_tokens - 1) * n_embd,
                                     chain_h[seq_id].data() + (size_t) t * n_embd, row_bytes);
                     }
                 } else if (is_mem_shared) {
                     // note: with shared memory (e.g. Gemma4 assistants) we use the same position for all draft tokens
                     // ref: https://github.com/huggingface/transformers/blob/effde20942e3f82a1b97449f60b3a48c5ff96145/docs/source/en/model_doc/gemma4_assistant.md?plain=1#L36-L37
-                    common_batch_add(batch, id, dp.pos0, { seq_id }, true);
+                    common_batch_add(batch, id, dp.n_past, { seq_id }, true);
                     std::memcpy(batch.embd + (size_t) (batch.n_tokens - 1) * n_embd, h_row, row_bytes);
                 } else {
-                    common_batch_add(batch, id, dp.pos0 + i + 1, { seq_id }, true);
+                    common_batch_add(batch, id, dp.n_past + i + 1, { seq_id }, true);
                     std::memcpy(batch.embd + (size_t) (batch.n_tokens - 1) * n_embd, h_row, row_bytes);
                 }
 
@@ -1776,7 +1726,7 @@ struct common_speculative_impl_ngram_simple : public common_speculative_impl {
     common_speculative_impl_ngram_simple(
             const common_params_speculative & params, uint32_t n_seq,
             common_ngram_simple_config config)
-        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_NGRAM_SIMPLE, n_seq, params.ngram_simple.size_m)
+        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_NGRAM_SIMPLE, n_seq)
         , params(params.ngram_simple)
         , config(config)
     {
@@ -1820,7 +1770,7 @@ struct common_speculative_impl_ngram_map_k : public common_speculative_impl {
             const common_ngram_map & config,
             uint32_t n_seq)
         : common_speculative_impl(config.key_only ? COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K
-            : COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K4V, n_seq, config.size_value)
+            : COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K4V, n_seq)
     {
         for (uint32_t i = 0; i < n_seq; i++) {
             this->config.push_back(config);
@@ -1891,7 +1841,7 @@ struct common_speculative_impl_ngram_mod : public common_speculative_impl {
     common_speculative_impl_ngram_mod(
             const common_params_speculative & params,
             uint32_t n_seq)
-        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_NGRAM_MOD, n_seq, params.ngram_mod.n_max)
+        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_NGRAM_MOD, n_seq)
         , params(params.ngram_mod)
         , mod(params.ngram_mod.n_match, 4*1024*1024)
         , verbose(std::getenv("LLAMA_TRACE") != nullptr) {
@@ -2067,7 +2017,7 @@ struct common_speculative_impl_ngram_cache : public common_speculative_impl {
             const std::string & path_dynamic,
             bool save_dynamic,
             bool save_static)
-        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_NGRAM_CACHE, n_seq, n_draft)
+        : common_speculative_impl(COMMON_SPECULATIVE_TYPE_NGRAM_CACHE, n_seq)
         , params(params.ngram_cache)
         , n_draft(n_draft)
         , save_dynamic(save_dynamic)
@@ -2188,8 +2138,6 @@ struct common_speculative {
 
     // which implementaion was used for a given seq_id
     std::vector<common_speculative_impl *> impl_last;
-
-    std::vector<double> synth_probs;
 };
 
 static common_ngram_map get_common_ngram_map(
@@ -2368,101 +2316,6 @@ int32_t common_speculative_n_max(const common_params_speculative * spec) {
     return n_max;
 }
 
-int32_t common_speculative_n_max(const common_speculative * spec) {
-    int32_t n_max = 0;
-
-    if (spec == nullptr) {
-        return n_max;
-    }
-
-    for (const auto & impl : spec->impls) {
-        n_max = std::max(n_max, std::max(0, impl->n_max));
-    }
-
-    return n_max;
-}
-
-std::vector<double> common_speculative_synth_rates_resolve(const common_params_speculative * spec, int32_t n_max) {
-    const bool has_length = spec->synth_len != -1.0;
-    const bool has_rates  = !spec->synth_rates.empty();
-
-    if (!has_length && !has_rates) {
-        return {};
-    }
-    if (has_length && has_rates) {
-        throw std::invalid_argument("synthetic acceptance length and rates are mutually exclusive");
-    }
-
-    if (n_max <= 0) {
-        throw std::invalid_argument("synthetic acceptance requires at least one speculative token");
-    }
-
-    if (has_rates) {
-        const auto & rates = spec->synth_rates;
-        if (rates.size() != (size_t) n_max) {
-            throw std::invalid_argument(string_format(
-                    "synthetic acceptance rates must contain %d values, got %zu", n_max, rates.size()));
-        }
-
-        for (size_t i = 0; i < rates.size(); ++i) {
-            if (!std::isfinite(rates[i]) || rates[i] < 0.0 || rates[i] > 1.0) {
-                throw std::invalid_argument("synthetic acceptance rates must be finite and within [0, 1]");
-            }
-            if (i > 0 && rates[i] > rates[i - 1]) {
-                throw std::invalid_argument("synthetic acceptance rates must be monotonically non-increasing");
-            }
-        }
-
-        return rates;
-    }
-
-    const double length = spec->synth_len;
-    const double length_max = (double) n_max + 1.0;
-    if (!std::isfinite(length) || length < 1.0 || length > length_max) {
-        throw std::invalid_argument(string_format(
-                "synthetic acceptance length must be finite and within [1, %.0f]", length_max));
-    }
-
-    double p = 0.0;
-    if (length == length_max) {
-        p = 1.0;
-    } else if (length > 1.0) {
-        double p_min = 0.0;
-        double p_max = 1.0;
-        for (int i = 0; i < 32; ++i) {
-            const double p_mid = 0.5 * (p_min + p_max);
-            double sum = 0.0;
-            double term = p_mid;
-            for (int32_t j = 0; j < n_max; ++j) {
-                sum += term;
-                term *= p_mid;
-            }
-
-            if (sum < length - 1.0) {
-                p_min = p_mid;
-            } else {
-                p_max = p_mid;
-            }
-        }
-        p = 0.5 * (p_min + p_max);
-    }
-
-    std::vector<double> rates;
-    rates.reserve(n_max);
-    double rate = p;
-    for (int32_t i = 0; i < n_max; ++i) {
-        rates.push_back(rate);
-        rate *= p;
-    }
-
-    return rates;
-}
-
-const std::vector<double> & common_speculative_get_synth_probs(const common_speculative * spec) {
-    GGML_ASSERT(spec);
-    return spec->synth_probs;
-}
-
 common_params common_base_params_to_speculative(const common_params & params) {
     const bool has_draft = params.speculative.has_dft();
 
@@ -2473,22 +2326,11 @@ common_params common_base_params_to_speculative(const common_params & params) {
     result.pooling_type = LLAMA_POOLING_TYPE_UNSPECIFIED;
 
     if (has_draft) {
-        // default to global devices value
-        if (!params_spec.devices.empty()) {
-            result.devices           = params_spec.devices;
-        }
+        result.devices               = params_spec.devices;
         result.model                 = params_spec.mparams;
         result.n_gpu_layers          = params_spec.n_gpu_layers;
         result.tensor_buft_overrides = params_spec.tensor_buft_overrides;
 
-        // a draft pinned to a single device doesn't need the meta wrapper an inherited -sm tensor would give it
-        // (the device list is null-terminated, so a single device means size 2)
-        const size_t n_devs = std::count_if(params_spec.devices.begin(), params_spec.devices.end(),
-                [](ggml_backend_dev_t d) { return d != nullptr; });
-        if (n_devs == 1) {
-            result.split_mode = LLAMA_SPLIT_MODE_LAYER;
-        }
-
         if (params_spec.cpuparams.n_threads > 0) {
             result.cpuparams.n_threads       = params_spec.cpuparams.n_threads;
             result.cpuparams_batch.n_threads = params_spec.cpuparams_batch.n_threads;
@@ -2546,9 +2388,6 @@ common_speculative_init_result::common_speculative_init_result(
         cparams.ctx_type = LLAMA_CONTEXT_TYPE_MTP;
     }
 
-    // the draft context holds as many tokens per sequence as the target context
-    cparams.n_ctx = llama_n_ctx(ctx_tgt);
-
     // note: for small models maybe we can set this to the maximum possible draft from all speculative types
     //       the extra memory for small models is likely negligible?
     cparams.n_rs_seq  = 0;
@@ -2726,39 +2565,13 @@ common_speculative * common_speculative_init(common_params_speculative & params,
         return nullptr;
     }
 
-    common_speculative_ptr result(new common_speculative {
-        /* .dparams     = */ common_speculative_draft_params_vec(n_seq),
-        /* .impls       = */ std::move(impls),
-        /* .impl_last   = */ std::vector<common_speculative_impl *>(n_seq, nullptr),
-        /* .synth_probs = */ {},
-    });
+    auto * result = new common_speculative {
+        /* .dparams   = */ common_speculative_draft_params_vec(n_seq),
+        /* .impls     = */ std::move(impls),
+        /* .impl_last = */ std::vector<common_speculative_impl *>(n_seq, nullptr)
+    };
 
-    const int32_t n_max_configured = common_speculative_n_max(&params);
-    const int32_t n_max_effective  = common_speculative_n_max(result.get());
-    const auto rates = common_speculative_synth_rates_resolve(&params, n_max_effective);
-
-    std::vector<std::string> rates_str;
-    rates_str.reserve(rates.size());
-    result->synth_probs.reserve(rates.size());
-    double rate_prev = 1.0;
-    double acceptance_length = 1.0;
-    for (const double rate : rates) {
-        result->synth_probs.push_back(rate_prev > 0.0 ? rate / rate_prev : 0.0);
-        rates_str.push_back(string_format("%.6g", rate));
-        rate_prev = rate;
-        acceptance_length += rate;
-    }
-    if (!result->synth_probs.empty()) {
-        SPC_WRN("%s", "synthetic speculative acceptance is enabled for benchmarking; generated output is not valid\n");
-        if (n_max_effective != n_max_configured) {
-            SPC_WRN("synthetic acceptance draft limit was reduced from %d to %d by the initialized speculative implementations\n",
-                    n_max_configured, n_max_effective);
-        }
-        SPC_INF("synthetic acceptance: n_max = %zu, mean length = %.6f, rates = [%s]\n",
-                rates.size(), acceptance_length, string_join(rates_str, ", ").c_str());
-    }
-
-    return result.release();
+    return result;
 }
 
 void common_speculative_free(common_speculative * spec) {

common/speculative.h

@@ -26,15 +26,6 @@ std::string common_speculative_type_to_str(enum common_speculative_type type);
 // return the max number of draft tokens based on the speculative parameters
 int32_t common_speculative_n_max(const common_params_speculative * spec);
 
-// return the max number of draft tokens from the initialized implementations
-int32_t common_speculative_n_max(const common_speculative * spec);
-
-// validate and resolve the unconditional synthetic acceptance rates
-std::vector<double> common_speculative_synth_rates_resolve(const common_params_speculative * spec, int32_t n_max);
-
-// return the conditional synthetic acceptance probabilities
-const std::vector<double> & common_speculative_get_synth_probs(const common_speculative * spec);
-
 common_params common_base_params_to_speculative(const common_params & params);
 
 struct common_speculative_output_limits {
@@ -61,7 +52,7 @@ struct common_speculative_draft_params {
     // can be used to constraint the max draft based on the remaining context size
     int32_t n_max = -1;
 
-    llama_pos   pos0;
+    llama_pos   n_past;
     llama_token id_last;
 
     // TODO: remove in the future by keeping track of the prompt from the _begin() call and the consecutive accept calls

conversion/__init__.py

@@ -54,7 +54,6 @@ TEXT_MODEL_MAP: dict[str, str] = {
     "DeepseekV3ForCausalLM": "deepseek",
     "DeepseekV32ForCausalLM": "deepseek",
     "DFlashDraftModel": "qwen",
-    "DFlash2DraftModel": "qwen",
     "Qwen3DSparkModel": "qwen",
     "DSparkDraftModel": "qwen",
     "DSparkSpeculator": "qwen",
@@ -124,7 +123,6 @@ TEXT_MODEL_MAP: dict[str, str] = {
     "HunYuanMoEV1ForCausalLM": "hunyuan",
     "HunYuanVLForConditionalGeneration": "hunyuan",
     "HYV3ForCausalLM": "hunyuan",
-    "HYV4ForCausalLM": "hy_v4",
     "IQuestCoderForCausalLM": "llama",
     "InternLM2ForCausalLM": "internlm",
     "InternLM3ForCausalLM": "internlm",
@@ -168,7 +166,6 @@ TEXT_MODEL_MAP: dict[str, str] = {
     "Mamba2ForCausalLM": "mamba",
     "MambaForCausalLM": "mamba",
     "MambaLMHeadModel": "mamba",
-    "MapleForCausalLM": "maple",
     "MellumForCausalLM": "mellum",
     "MiMoV2FlashForCausalLM": "mimo",
     "MiMoV2ForCausalLM": "mimo",
@@ -190,7 +187,6 @@ TEXT_MODEL_MAP: dict[str, str] = {
     "NanbeigeForCausalLM": "nanbeige",
     "NemotronForCausalLM": "nemotron",
     "NemotronHForCausalLM": "nemotron",
-    "NemotronHPuzzleForCausalLM": "nemotron",
     "NeoBERT": "bert",
     "NeoBERTForSequenceClassification": "bert",
     "NeoBERTLMHead": "bert",
@@ -239,8 +235,6 @@ TEXT_MODEL_MAP: dict[str, str] = {
     "Qwen3_5ForConditionalGeneration": "qwen",
     "Qwen3_5MoeForCausalLM": "qwen",
     "Qwen3_5MoeForConditionalGeneration": "qwen",
-    "Qwen4ExpForCausalLM": "qwen4exp",
-    "Qwen4ExpForConditionalGeneration": "qwen4exp",
     "RND1": "qwen",
     "RWForCausalLM": "falcon",
     "RWKV6Qwen2ForCausalLM": "rwkv",
@@ -256,7 +250,6 @@ TEXT_MODEL_MAP: dict[str, str] = {
     "SeedOssForCausalLM": "olmo",
     "SmallThinkerForCausalLM": "smallthinker",
     "SmolLM3ForCausalLM": "llama",
-    "Spark2_5ForCausalLM": "spark2_5",
     "SolarOpenForCausalLM": "glm",
     "StableLMEpochForCausalLM": "stablelm",
     "StableLmForCausalLM": "stablelm",
@@ -290,7 +283,6 @@ MMPROJ_MODEL_MAP: dict[str, str] = {
     "CogVLMForCausalLM": "cogvlm",
     "DeepseekOCR2ForCausalLM": "deepseek",
     "DeepseekOCRForCausalLM": "deepseek",
-    "DeepseekV4ForCausalLM": "deepseek",
     "Dots3NoteForCausalLM": "dots3",
     "Dots3NoteForConditionalGeneration": "dots3",
     "DotsOCRForCausalLM": "dotsocr",
@@ -340,7 +332,6 @@ MMPROJ_MODEL_MAP: dict[str, str] = {
     "Qwen3VLMoeForConditionalGeneration": "qwen3vl",
     "Qwen3_5ForConditionalGeneration": "qwen3vl",
     "Qwen3_5MoeForConditionalGeneration": "qwen3vl",
-    "Qwen4ExpForConditionalGeneration": "qwen4exp",
     "RADIOModel": "nemotron",
     "Sarashina2VisionForCausalLM": "sarashina2",
     "SmolVLMForConditionalGeneration": "smolvlm",

conversion/base.py

@@ -130,8 +130,7 @@ class ModelBase:
                  sentence_transformers_dense_modules: bool = False,
                  target_model_dir: Path | None = None,
                  fuse_gate_up_exps: bool = False,
-                 fp8_as_q8: bool = False,
-                 fuse_qkv: bool = False):
+                 fp8_as_q8: bool = False):
         if type(self) is ModelBase or \
                 type(self) is TextModel or \
                 type(self) is MmprojModel:
@@ -154,15 +153,6 @@ class ModelBase:
         self.fuse_gate_up_exps = fuse_gate_up_exps
         self._gate_exp_buffer: dict[int, Tensor] = {}
         self._up_exp_buffer: dict[int, Tensor] = {}
-        self.fuse_qkv = fuse_qkv
-        self._q_buffer: dict[int, Tensor] = {}
-        self._k_buffer: dict[int, Tensor] = {}
-        self._v_buffer: dict[int, Tensor] = {}
-        self._q_bias_buffer: dict[int, Tensor] = {}
-        self._k_bias_buffer: dict[int, Tensor] = {}
-        self._v_bias_buffer: dict[int, Tensor] = {}
-        self._fusable_qkv_weight_layers: set[int] = set()
-        self._fusable_qkv_bias_layers: set[int] = set()
         self.hparams = ModelBase.load_hparams(self.dir_model, self.is_mistral_format) if hparams is None else hparams
         self.model_tensors = self.index_tensors(remote_hf_model_id=remote_hf_model_id)
         self.metadata_override = metadata_override
@@ -627,43 +617,6 @@ class ModelBase:
             raise ValueError(f"Can not map tensor {name!r}")
         return new_name
 
-    def prepare_qkv_fusion(self) -> None:
-        self._fusable_qkv_weight_layers.clear()
-        self._fusable_qkv_bias_layers.clear()
-        if not self.fuse_qkv or gguf.MODEL_TENSOR.ATTN_QKV not in gguf.MODEL_TENSORS[self.model_arch]:
-            return
-
-        qkv_types = {
-            gguf.MODEL_TENSOR.ATTN_Q,
-            gguf.MODEL_TENSOR.ATTN_K,
-            gguf.MODEL_TENSOR.ATTN_V,
-        }
-        weights: dict[int, set[gguf.MODEL_TENSOR]] = {}
-        biases: dict[int, set[gguf.MODEL_TENSOR]] = {}
-
-        for name in self.model_tensors:
-            mapped = self.tensor_map.get_type_and_name(name, try_suffixes=(".weight", ".bias"))
-            if mapped is None:
-                continue
-            tensor_type, new_name = mapped
-            if tensor_type not in qkv_types:
-                continue
-
-            bid = next((int(part) for part in new_name.split(".") if part.isdecimal()), None)
-            if bid is None:
-                continue
-            if new_name.endswith(".weight"):
-                weights.setdefault(bid, set()).add(tensor_type)
-            elif new_name.endswith(".bias"):
-                biases.setdefault(bid, set()).add(tensor_type)
-
-        for bid, weight_types in weights.items():
-            bias_types = biases.get(bid, set())
-            if weight_types == qkv_types and (not bias_types or bias_types == qkv_types):
-                self._fusable_qkv_weight_layers.add(bid)
-                if bias_types:
-                    self._fusable_qkv_bias_layers.add(bid)
-
     def set_gguf_parameters(self):
         raise NotImplementedError("set_gguf_parameters() must be implemented in subclasses")
 
@@ -692,40 +645,6 @@ class ModelBase:
                self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.FFN_UP_EXP, bid):
                 return []
 
-        # Handle Q/K/V tensor fusion if enabled
-        qkv_bid = next((int(part) for part in new_name.split(".") if part.isdecimal()), None) if self.fuse_qkv else None
-        if qkv_bid is not None:
-            is_bias = new_name.endswith('.bias')
-            suffix = '.bias' if is_bias else '.weight'
-            fusable_layers = self._fusable_qkv_bias_layers if is_bias else self._fusable_qkv_weight_layers
-            if qkv_bid not in fusable_layers:
-                return [(new_name, data_torch)]
-
-            buf_q = self._q_bias_buffer if is_bias else self._q_buffer
-            buf_k = self._k_bias_buffer if is_bias else self._k_buffer
-            buf_v = self._v_bias_buffer if is_bias else self._v_buffer
-
-            if self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.ATTN_Q, qkv_bid, suffix):
-                buf_q[qkv_bid] = data_torch
-            elif self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.ATTN_K, qkv_bid, suffix):
-                buf_k[qkv_bid] = data_torch
-            elif self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.ATTN_V, qkv_bid, suffix):
-                buf_v[qkv_bid] = data_torch
-
-            if qkv_bid in buf_q and qkv_bid in buf_k and qkv_bid in buf_v:
-                q_data = buf_q.pop(qkv_bid)
-                k_data = buf_k.pop(qkv_bid)
-                v_data = buf_v.pop(qkv_bid)
-                fused_data = torch.cat([q_data, k_data, v_data], dim=0)
-                fused_name = self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_QKV, qkv_bid, suffix=suffix)
-                logger.info(f"Fused Q, K, V {suffix[1:]} into QKV for layer {qkv_bid}")
-                return [(fused_name, fused_data)]
-
-            if self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.ATTN_Q, qkv_bid, suffix) or \
-               self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.ATTN_K, qkv_bid, suffix) or \
-               self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.ATTN_V, qkv_bid, suffix):
-                return []
-
         return [(new_name, data_torch)]
 
     def tensor_force_quant(self, name: str, new_name: str, bid: int | None, n_dims: int) -> gguf.GGMLQuantizationType | bool:
@@ -980,8 +899,6 @@ class ModelBase:
 
         self.dequant_model()
 
-        self.prepare_qkv_fusion()
-
         # Handle empty tensor_map for models with block_count=0 (like MobileNetV5)
         if self.tensor_map.mapping:
             max_name_len = max(len(s) for _, s in self.tensor_map.mapping.values()) + len(".weight,")
@@ -1089,16 +1006,12 @@ class ModelBase:
                     else:
                         raise ValueError(f"Unknown file type: {self.ftype.name}")
 
-                # a chunked tensor quantizes as one chunk at a time, while it is written
-                quantize = data.quantize if isinstance(data, gguf.LazyChunkedTensor) else (
-                    lambda qtype, d=data: gguf.quants.quantize(d, qtype))
-
                 try:
-                    data = quantize(data_qtype)
+                    data = gguf.quants.quantize(data, data_qtype)
                 except gguf.QuantError as e:
                     logger.warning("%s, %s", e, "falling back to F16")
                     data_qtype = gguf.GGMLQuantizationType.F16
-                    data = quantize(data_qtype)
+                    data = gguf.quants.quantize(data, data_qtype)
 
                 shape = gguf.quant_shape_from_byte_shape(data.shape, data_qtype) if data.dtype == np.uint8 else data.shape
 
@@ -1110,13 +1023,6 @@ class ModelBase:
 
                 self.gguf_writer.add_tensor(new_name, data, raw_dtype=data_qtype)
 
-        qkv_buffers = (
-            self._q_buffer, self._k_buffer, self._v_buffer,
-            self._q_bias_buffer, self._k_bias_buffer, self._v_bias_buffer,
-        )
-        if any(qkv_buffers):
-            raise ValueError("QKV fusion did not consume all buffered tensors")
-
     def set_type(self):
         self.gguf_writer.add_type(gguf.GGUFType.MODEL)
 
@@ -1597,9 +1503,6 @@ class TextModel(ModelBase):
         if chkhsh == "bba3b3366b646dbdded5dbc42d59598b849371afc42f7beafa914afaa5b70aa6":
             # ref: https://huggingface.co/tencent/Hunyuan-4B-Instruct
             res = "hunyuan-dense"
-        if chkhsh == "e6ddf9c6686791c12d698d34c31ab9be1fea9af5a3d9a6909783ab382198ae1c":
-            # ref: https://huggingface.co/tencent/Hy4-preview
-            res = "hy_v4"
         if chkhsh == "a6b57017d60e6edb4d88ecc2845188e0eb333a70357e45dcc9b53964a73bbae6":
             # ref: https://huggingface.co/tiiuae/Falcon-H1-0.5B-Base
             res = "falcon-h1"
@@ -1633,9 +1536,6 @@ class TextModel(ModelBase):
         if chkhsh == "9e454714343b69b99b71795c1d27a68c2a1d15dab111f4d353109f966af29da7":
             # ref: https://huggingface.co/LiquidAI/LFM2.5-8B-A1B
             res = "lfm2"
-        if chkhsh == "0a766d034107bc736a3f2dc4968fd62e54a3570f1454443e0c5a4cc6bd7941ed":
-            # ref: https://huggingface.co/XHToken/Spark-X2.5-1.7B
-            res = "spark2_5"
         if chkhsh == "0ef9807a4087ebef797fc749390439009c3b9eda9ad1a097abbe738f486c01e5":
             # ref: https://huggingface.co/meta-llama/Meta-Llama-3-8B
             res = "llama-bpe"

conversion/deepseek.py

@@ -578,8 +578,6 @@ class DeepseekV4Model(TextModel):
     @classmethod
     def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
         name, gen = item
-        if name.startswith(("aligner.", "image_")):
-            return None
         if name.startswith("mtp."):
             if not cls.mtp_only:
                 cls._skipped_mtp_tensors += 1
@@ -855,7 +853,6 @@ class DeepseekV4Model(TextModel):
             "ffn_norm.weight": (gguf.MODEL_TENSOR.FFN_NORM, ".weight"),
             "ffn.gate.weight": (gguf.MODEL_TENSOR.FFN_GATE_INP, ".weight"),
             "ffn.gate.bias": (gguf.MODEL_TENSOR.FFN_EXP_PROBS_B, ".bias"),
-            "ffn.gate.bias_vl": (gguf.MODEL_TENSOR.FFN_EXP_PROBS_B_VL, ".bias"),
             "ffn.gate.tid2eid": (gguf.MODEL_TENSOR.FFN_GATE_TID2EID, ".weight"),
             "ffn.shared_experts.w1.weight": (gguf.MODEL_TENSOR.FFN_GATE_SHEXP, ".weight"),
             "ffn.shared_experts.w2.weight": (gguf.MODEL_TENSOR.FFN_DOWN_SHEXP, ".weight"),
@@ -881,10 +878,6 @@ class DeepseekV4Model(TextModel):
         if re.match(r"layers\.\d+\.ffn\.experts\.\d+\.w[123]\.(weight|scale)$", name):
             return []
 
-        # hash layers route text tokens via tid2eid and image tokens via bias_vl; gate.bias is unused
-        if name.endswith(".ffn.gate.bias") and bid is not None and bid < self.hparams["num_hash_layers"]:
-            return []
-
         tensor_key, suffix = self._map_dsv4_tensor_name(name, bid)
         if tensor_key == gguf.MODEL_TENSOR.FFN_GATE_TID2EID:
             return []
@@ -1007,13 +1000,6 @@ class DeepseekV4DSparkModel(DeepseekV4Model):
             return self._DSPARK_ROOT_MAP[name]
         return super()._map_dsv4_tensor_name(name, bid)
 
-    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
-        # the DFlash draft uses the plain exp-probs bias (ffn.gate.bias -> FFN_EXP_PROBS_B);
-        # the mtmd-only hash routing tensors (bias_vl, tid2eid) are not part of the DFLASH arch
-        if name.endswith(".ffn.gate.bias_vl"):
-            return
-        yield from super().modify_tensors(data_torch, name, bid)
-
     def set_vocab(self):
         if self.target_model_dir is None:
             raise ValueError("DeepSeek-V4 DSpark requires --target-model-dir with the target tokenizer")
@@ -1032,73 +1018,3 @@ class DeepseekV4DSparkModel(DeepseekV4Model):
 
         self.gguf_writer.add_block_size(self.hparams["dspark_block_size"])
         self.gguf_writer.add_target_layers([layer + 1 for layer in self.hparams["dspark_target_layer_ids"]])
-
-
-@ModelBase.register("DeepseekV4ForCausalLM")
-@ModelBase.example("deepseek-ai/DeepSeek-V4-Flash-Vision-Exp")
-class DeepseekV4FlashVisionModel(MmprojModel):
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        assert self.hparams_vision is not None
-        # no preprocessor_config.json in the repo; normalization is (x/255 - 0.5) / 0.5
-        # ref: inference/image_processor.py (load_image)
-        self.preprocessor_config = {
-            "image_mean": [0.5, 0.5, 0.5],
-            "image_std":  [0.5, 0.5, 0.5],
-            **self.preprocessor_config,
-        }
-
-    def get_vision_config(self) -> dict[str, Any] | None:
-        cfg = self.global_config
-        if cfg.get("vision_n_layers", 0) == 0:
-            raise ValueError("DeepseekV4FlashVisionModel requires vision_n_layers > 0 in the model config")
-        return {
-            "num_hidden_layers":   cfg["vision_n_layers"],
-            "hidden_size":         cfg["vision_dim"],
-            "num_attention_heads": cfg["vision_n_heads"],
-            "intermediate_size":   cfg["vision_inter_dim"],
-            "patch_size":          cfg["vision_patch_size"],
-            # dynamic resolution; only used for compat / warmup
-            "image_size":          cfg["vision_patch_size"] * cfg["vision_downsample_ratio"] * 16,
-            "rope_theta":          cfg.get("vision_rope_theta", 10000.0),
-            "downsample_ratio":    cfg["vision_downsample_ratio"],
-            "min_pixels":          cfg["vision_min_pixels"],
-        }
-
-    def set_gguf_parameters(self):
-        super().set_gguf_parameters()
-        assert self.hparams_vision is not None
-        self.gguf_writer.add_clip_projector_type(gguf.VisionProjectorType.DEEPSEEK4V)
-        # vision RMSNorm eps is the pytorch default, NOT the LLM's rms_norm_eps (1e-20)
-        # ref: inference/vision.py (RMSNorm)
-        self.gguf_writer.add_vision_attention_layernorm_eps(1e-6)
-        self.gguf_writer.add_vision_use_silu(True) # SwiGLU MLP
-        self.gguf_writer.add_vision_projector_scale_factor(self.hparams_vision["downsample_ratio"])
-        self.gguf_writer.add_vision_min_pixels(self.hparams_vision["min_pixels"])
-        # hardcoded on the C++ side (see PROJECTOR_TYPE_DEEPSEEK4V in clip.cpp)
-        # if future models use different values, add GGUF keys for those
-        assert self.global_config["vision_max_n_token"] == 384
-        assert self.global_config["vision_max_wh_ratio"] == 8
-
-    @classmethod
-    def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
-        name, _ = item
-        if not (name.startswith(("vision.", "aligner.", "image_"))):
-            return None
-        return super().filter_tensors(item)
-
-    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
-        assert self.hparams_vision is not None
-        if name == "vision.patch_embed.proj.weight":
-            # nn.Linear over flattened (3, p, p) patches == conv2d weight
-            p = self.hparams_vision["patch_size"]
-            data_torch = data_torch.reshape(data_torch.shape[0], 3, p, p)
-
-        if ".mlp.w1." in name:
-            # fused SwiGLU gate+up
-            gate, up = data_torch.chunk(2, dim=0)
-            yield from super().modify_tensors(gate, name.replace("w1", "w1_gate"), bid)
-            yield from super().modify_tensors(up, name.replace("w1", "w1_up"), bid)
-            return
-
-        yield from super().modify_tensors(data_torch, name, bid)

conversion/glm.py

@@ -112,38 +112,12 @@ class GlmOCRModel(Glm4Model):
 @ModelBase.example("zai-org/GLM-4.5-Air")
 class Glm4MoeModel(TextModel):
     model_arch = gguf.MODEL_ARCH.GLM4_MOE
-    supports_mtp_export = True
-    _n_main_layers: int | None = None
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        if not self.no_mtp:
-            self.block_count += self.hparams.get("num_nextn_predict_layers", 0)
-            self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)
-
-    def index_tensors(self, remote_hf_model_id: str | None = None):
-        hparams = {**self.hparams, **self.hparams.get("text_config", {})}
-        key = next((k for k in ["n_layers", "num_hidden_layers", "n_layer", "num_layers"] if k in hparams), None)
-        type(self)._n_main_layers = hparams.get(key)
-        return super().index_tensors(remote_hf_model_id=remote_hf_model_id)
-
-    @classmethod
-    def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
-        if (titem := super().filter_tensors(item)) is None:
-            return None
-        name, gen = titem
-
-        assert cls._n_main_layers is not None
-        is_mtp = (m := re.match(r"model\.layers\.(\d+)\.", name)) is not None and int(m.group(1)) >= cls._n_main_layers
-
-        if is_mtp and cls.no_mtp:
-            return None
-        if cls.mtp_only and not is_mtp and name not in (
-            "model.embed_tokens.weight", "model.norm.weight", "lm_head.weight",
-        ):
-            return None
-
-        return name, gen
+        # GLM4_MOE has num_hidden_layers + 1 actual layers (including NextN layer)
+        self.block_count = self.hparams["num_hidden_layers"] + self.hparams.get("num_nextn_predict_layers", 0)
+        self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)
 
     def set_vocab(self):
         return self._set_vocab_glm()
@@ -179,22 +153,10 @@ class Glm4MoeModel(TextModel):
         if (norm_topk_prob := self.hparams.get("norm_topk_prob")) is not None:
             self.gguf_writer.add_expert_weights_norm(norm_topk_prob)
 
-        if not self.no_mtp and (num_nextn_predict_layers := self.hparams.get("num_nextn_predict_layers")) is not None:
+        # NextN/MTP prediction layers
+        if (num_nextn_predict_layers := self.hparams.get("num_nextn_predict_layers")) is not None:
             self.gguf_writer.add_nextn_predict_layers(num_nextn_predict_layers)
 
-    def prepare_metadata(self, vocab_only: bool):
-        from_dir = self.fname_out.is_dir()
-        super().prepare_metadata(vocab_only=vocab_only)
-
-        if not self.mtp_only or not from_dir:
-            return
-
-        output_type: str = self.ftype.name.partition("_")[2]
-        fname_default: str = gguf.naming_convention(
-            self.metadata.name, self.metadata.basename, self.metadata.finetune,
-            self.metadata.version, size_label=None, output_type=output_type, model_type=None)
-        self.fname_out = self.fname_out.parent / f"mtp-{fname_default}.gguf"
-
     _experts: list[dict[str, Tensor]] | None = None
 
     # note: unlike GLM4V non-MoE, we don't need to permute Q/K here since GLM4V_MOE uses Neox ordering already
@@ -386,7 +348,6 @@ class GlmMoeDsaModel(DeepseekV2Model):
 @ModelBase.example("upstage/Solar-Open-100B")
 class SolarOpenModel(Glm4MoeModel):
     model_arch = gguf.MODEL_ARCH.GLM4_MOE
-    supports_mtp_export = False
 
     def set_vocab(self):
         from transformers import AutoTokenizer