server: support load model on startup, support preset-only options (#18206)

* server: support autoload model, support preset-only options

* add docs

* load-on-startup

* fix

* Update common/arg.cpp

Co-authored-by: Pascal <admin@serveurperso.com>

---------

Co-authored-by: Pascal <admin@serveurperso.com>

.devops/cann.Dockerfile

@@ -4,7 +4,7 @@
 
 # Define the CANN base image for easier version updates later
 ARG CHIP_TYPE=910b
-ARG CANN_BASE_IMAGE=quay.io/ascend/cann:8.3.rc1.alpha001-${CHIP_TYPE}-openeuler22.03-py3.11
+ARG CANN_BASE_IMAGE=quay.io/ascend/cann:8.3.rc2-${CHIP_TYPE}-openeuler24.03-py3.11
 
 # ==============================================================================
 # BUILD STAGE
@@ -107,11 +107,11 @@ ENTRYPOINT ["/app/tools.sh"]
 # ENTRYPOINT ["/app/llama-server"]
 
 ### Target: light
-# Lightweight image containing only llama-cli
+# Lightweight image containing only llama-cli and llama-completion
 # ==============================================================================
 FROM base AS light
 
-COPY --from=build /app/full/llama-cli /app
+COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
 
 ENTRYPOINT [ "/app/llama-cli" ]
 

.devops/cpu.Dockerfile

@@ -68,7 +68,7 @@ ENTRYPOINT ["/app/tools.sh"]
 ### Light, CLI only
 FROM base AS light
 
-COPY --from=build /app/full/llama-cli /app
+COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
 
 WORKDIR /app
 

.devops/cuda.Dockerfile

@@ -74,7 +74,7 @@ ENTRYPOINT ["/app/tools.sh"]
 ### Light, CLI only
 FROM base AS light
 
-COPY --from=build /app/full/llama-cli /app
+COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
 
 WORKDIR /app
 

.devops/intel.Dockerfile

@@ -73,7 +73,7 @@ ENTRYPOINT ["/app/tools.sh"]
 FROM base AS light
 
 COPY --from=build /app/lib/ /app
-COPY --from=build /app/full/llama-cli /app
+COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
 
 WORKDIR /app
 

.devops/llama-cli-cann.Dockerfile

@@ -23,11 +23,12 @@ ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/runtime/lib64/stub:$LD_LIBRARY_PATH
 RUN echo "Building with static libs" && \
     source /usr/local/Ascend/ascend-toolkit/set_env.sh --force && \
     cmake -B build -DGGML_NATIVE=OFF -DGGML_CANN=ON -DBUILD_SHARED_LIBS=OFF -DLLAMA_BUILD_TESTS=OFF  && \
-    cmake --build build --config Release --target llama-cli
+    cmake --build build --config Release --target llama-cli && \
+    cmake --build build --config Release --target llama-completion
 
 # TODO: use image with NNRT
 FROM ascendai/cann:$ASCEND_VERSION AS runtime
-COPY --from=build /app/build/bin/llama-cli /llama-cli
+COPY --from=build /app/build/bin/llama-cli /app/build/bin/llama-completion /
 
 ENV LC_ALL=C.utf8
 

.devops/llama-cpp-cuda.srpm.spec

@@ -37,6 +37,7 @@ make -j GGML_CUDA=1
 %install
 mkdir -p %{buildroot}%{_bindir}/
 cp -p llama-cli %{buildroot}%{_bindir}/llama-cuda-cli
+cp -p llama-completion %{buildroot}%{_bindir}/llama-cuda-completion
 cp -p llama-server %{buildroot}%{_bindir}/llama-cuda-server
 cp -p llama-simple %{buildroot}%{_bindir}/llama-cuda-simple
 
@@ -68,6 +69,7 @@ rm -rf %{_builddir}/*
 
 %files
 %{_bindir}/llama-cuda-cli
+%{_bindir}/llama-cuda-completion
 %{_bindir}/llama-cuda-server
 %{_bindir}/llama-cuda-simple
 /usr/lib/systemd/system/llamacuda.service

.devops/llama-cpp.srpm.spec

@@ -39,6 +39,7 @@ make -j
 %install
 mkdir -p %{buildroot}%{_bindir}/
 cp -p llama-cli %{buildroot}%{_bindir}/llama-cli
+cp -p llama-completion %{buildroot}%{_bindir}/llama-completion
 cp -p llama-server %{buildroot}%{_bindir}/llama-server
 cp -p llama-simple %{buildroot}%{_bindir}/llama-simple
 
@@ -70,6 +71,7 @@ rm -rf %{_builddir}/*
 
 %files
 %{_bindir}/llama-cli
+%{_bindir}/llama-completion
 %{_bindir}/llama-server
 %{_bindir}/llama-simple
 /usr/lib/systemd/system/llama.service

.devops/musa.Dockerfile

@@ -81,7 +81,7 @@ ENTRYPOINT ["/app/tools.sh"]
 ### Light, CLI only
 FROM base AS light
 
-COPY --from=build /app/full/llama-cli /app
+COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
 
 WORKDIR /app
 

.devops/rocm.Dockerfile

@@ -94,7 +94,7 @@ ENTRYPOINT ["/app/tools.sh"]
 ### Light, CLI only
 FROM base AS light
 
-COPY --from=build /app/full/llama-cli /app
+COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
 
 WORKDIR /app
 

.devops/s390x.Dockerfile

@@ -105,7 +105,7 @@ WORKDIR /llama.cpp/bin
 
 # Copy llama.cpp binaries and libraries
 COPY --from=collector /llama.cpp/bin/*.so /llama.cpp/bin
-COPY --from=collector /llama.cpp/bin/llama-cli /llama.cpp/bin
+COPY --from=collector /llama.cpp/bin/llama-cli /llama.cpp/bin/llama-completion /llama.cpp/bin
 
 ENTRYPOINT [ "/llama.cpp/bin/llama-cli" ]
 

.devops/tools.sh

@@ -13,6 +13,8 @@ elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then
     exec ./llama-quantize "$@"
 elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then
     exec ./llama-cli "$@"
+elif [[ "$arg1" == '--run-legacy' || "$arg1" == '-l' ]]; then
+    exec ./llama-completion "$@"
 elif [[ "$arg1" == '--bench' || "$arg1" == '-b' ]]; then
     exec ./llama-bench "$@"
 elif [[ "$arg1" == '--perplexity' || "$arg1" == '-p' ]]; then
@@ -32,8 +34,10 @@ elif [[ "$arg1" == '--server' || "$arg1" == '-s' ]]; then
 else
     echo "Unknown command: $arg1"
     echo "Available commands: "
-    echo "  --run (-r): Run a model previously converted into ggml"
-    echo "              ex: -m /models/7B/ggml-model-q4_0.bin -p \"Building a website can be done in 10 simple steps:\" -n 512"
+    echo "  --run (-r): Run a model (chat) previously converted into ggml"
+    echo "              ex: -m /models/7B/ggml-model-q4_0.bin"
+    echo "  --run-legacy (-l): Run a model (legacy completion) previously converted into ggml"
+    echo "              ex: -m /models/7B/ggml-model-q4_0.bin -no-cnv -p \"Building a website can be done in 10 simple steps:\" -n 512"
     echo "  --bench (-b): Benchmark the performance of the inference for various parameters."
     echo "              ex: -m model.gguf"
     echo "  --perplexity (-p): Measure the perplexity of a model over a given text."

.devops/vulkan.Dockerfile

@@ -68,7 +68,7 @@ ENTRYPOINT ["/app/tools.sh"]
 ### Light, CLI only
 FROM base AS light
 
-COPY --from=build /app/full/llama-cli /app
+COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
 
 WORKDIR /app
 

.github/ISSUE_TEMPLATE/011-bug-results.yml

@@ -11,7 +11,7 @@ body:
         (i.e. the generated text) are incorrect or llama.cpp crashes during model evaluation.
         If you encountered the issue while using an external UI (e.g. ollama),
         please reproduce your issue using one of the examples/binaries in this repository.
-        The `llama-cli` binary can be used for simple and reproducible model inference.
+        The `llama-completion` binary can be used for simple and reproducible model inference.
   - type: textarea
     id: version
     attributes:
@@ -74,9 +74,12 @@ body:
         Please give us a summary of the problem and tell us how to reproduce it.
         If you can narrow down the bug to specific hardware, compile flags, or command line arguments,
         that information would be very much appreciated by us.
+
+        If possible, please try to reproduce the issue using `llama-completion` with `-fit off`.
+        If you can only reproduce the issue with `-fit on`, please provide logs both with and without `--verbose`.
       placeholder: >
-        e.g. when I run llama-cli with -ngl 99 I get garbled outputs.
-        When I use -ngl 0 it works correctly.
+        e.g. when I run llama-completion with `-fa on` I get garbled outputs for very long prompts.
+        With short prompts or `-fa off` it works correctly.
         Here are the exact commands that I used: ...
     validations:
       required: true

.github/ISSUE_TEMPLATE/019-bug-misc.yml

@@ -86,6 +86,7 @@ body:
       description: >
           If applicable, please copy and paste any relevant log output, including any generated text.
           This will be automatically formatted into code, so no need for backticks.
+          If you are encountering problems specifically with the `llama_params_fit` module, always upload `--verbose` logs as well.
       render: shell
     validations:
       required: false

.github/workflows/build.yml

@@ -20,7 +20,8 @@ on:
       '**/*.swift',
       '**/*.m',
       '**/*.metal',
-      '**/*.comp'
+      '**/*.comp',
+      '**/*.glsl'
     ]
 
   pull_request:
@@ -40,7 +41,8 @@ on:
       '**/*.swift',
       '**/*.m',
       '**/*.metal',
-      '**/*.comp'
+      '**/*.comp',
+      '**/*.glsl'
     ]
 
 concurrency:
@@ -68,6 +70,7 @@ jobs:
         with:
           key: macOS-latest-cmake-arm64
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build
         id: cmake_build
@@ -104,6 +107,7 @@ jobs:
         with:
           key: macOS-latest-cmake-x64
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build
         id: cmake_build
@@ -140,6 +144,7 @@ jobs:
         with:
           key: macOS-latest-cmake-arm64-webgpu
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dawn Dependency
         id: dawn-depends
@@ -193,6 +198,7 @@ jobs:
         with:
           key: ubuntu-cpu-cmake-${{ matrix.build }}
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build Dependencies
         id: build_depends
@@ -243,7 +249,7 @@ jobs:
           echo "Fetch llama2c model"
           wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
           ./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
-          ./bin/llama-cli -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
+          ./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
 
       - name: Test llama2c (s390x)
         id: llama2c_test_s390x
@@ -252,7 +258,7 @@ jobs:
           cd build
           echo "Fetch llama2c big-endian model"
           wget https://huggingface.co/ggml-org/models/resolve/main/tinyllamas/stories260K-be.gguf
-          ./bin/llama-cli -m stories260K-be.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
+          ./bin/llama-completion -m stories260K-be.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
 
   ubuntu-latest-cmake-sanitizer:
     runs-on: ubuntu-latest
@@ -274,6 +280,7 @@ jobs:
         with:
           key: ubuntu-latest-cmake-sanitizer-${{ matrix.sanitizer }}
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dependencies
         id: depends
@@ -394,6 +401,7 @@ jobs:
         with:
           key: ubuntu-24-cmake-vulkan-deb
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dependencies
         id: depends
@@ -429,6 +437,7 @@ jobs:
         with:
           key: ubuntu-24-cmake-vulkan
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dependencies
         id: depends
@@ -488,6 +497,7 @@ jobs:
         with:
           key: ubuntu-24-cmake-webgpu
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dependencies
         id: depends
@@ -560,6 +570,7 @@ jobs:
         with:
           key: ubuntu-latest-wasm-webgpu
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Install Emscripten
         run: |
@@ -607,6 +618,7 @@ jobs:
         with:
           key: ubuntu-22-cmake-hip
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build with native CMake HIP support
         id: cmake_build
@@ -639,6 +651,7 @@ jobs:
         with:
           key: ubuntu-22-cmake-musa
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build with native CMake MUSA support
         id: cmake_build
@@ -686,6 +699,7 @@ jobs:
         with:
           key: ubuntu-22-cmake-sycl
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build
         id: cmake_build
@@ -736,6 +750,7 @@ jobs:
         with:
           key: ubuntu-22-cmake-sycl-fp16
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build
         id: cmake_build
@@ -769,6 +784,7 @@ jobs:
         with:
           key: macOS-latest-cmake-ios
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build
         id: cmake_build
@@ -800,6 +816,7 @@ jobs:
         with:
           key: macOS-latest-cmake-tvos
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build
         id: cmake_build
@@ -861,6 +878,7 @@ jobs:
         with:
           key: macOS-latest-swift
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Download xcframework artifact
         uses: actions/download-artifact@v4
@@ -903,6 +921,7 @@ jobs:
           key: windows-msys2
           variant: ccache
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Setup ${{ matrix.sys }}
         uses: msys2/setup-msys2@v2
@@ -971,6 +990,7 @@ jobs:
           key: windows-latest-cmake-${{ matrix.build }}
           variant: ccache
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Download OpenBLAS
         id: get_openblas
@@ -1075,6 +1095,7 @@ jobs:
           with:
             key: ubuntu-latest-cmake-cuda
             evict-old-files: 1d
+            save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
         - name: Build with CMake
           run: |
@@ -1107,6 +1128,7 @@ jobs:
           key: windows-cuda-${{ matrix.cuda }}
           variant: ccache
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Install Cuda Toolkit
         uses: ./.github/actions/windows-setup-cuda
@@ -1158,6 +1180,7 @@ jobs:
           key: windows-latest-cmake-sycl
           variant: ccache
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Install
         run:  |
@@ -1219,6 +1242,7 @@ jobs:
         with:
           key: ${{ github.job }}
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Build
         id: cmake_build
@@ -1400,25 +1424,54 @@ jobs:
         chip_type: ['910b', '310p']
         build: ['Release']
     runs-on: ${{ matrix.arch == 'aarch64' && 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
-    container: ascendai/cann:${{ matrix.chip_type == '910b' &&  '8.3.rc1.alpha001-910b-openeuler22.03-py3.11' || '8.2.rc1-310p-openeuler22.03-py3.11' }}
     steps:
       - name: Checkout
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
 
-      - name: Dependencies
+      - name: Free up disk space
+        uses: ggml-org/free-disk-space@v1.3.1
+        with:
+          tool-cache: true
+
+      - name: Set container image
+        id: cann-image
         run: |
-          yum update -y
-          yum install -y git gcc gcc-c++ make cmake libcurl-devel
+          image="ascendai/cann:${{ matrix.chip_type == '910b' &&  '8.3.rc2-910b-openeuler24.03-py3.11' || '8.3.rc2-310p-openeuler24.03-py3.11' }}"
+          echo "image=${image}" >> "${GITHUB_OUTPUT}"
+
+      - name: Pull container image
+        run: docker pull "${{ steps.cann-image.outputs.image }}"
 
       - name: Build
+        env:
+          BUILD_TYPE: ${{ matrix.build }}
+          SOC_TYPE: ascend${{ matrix.chip_type }}
         run: |
-          export LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/$(uname -m)-linux/devlib/:${LD_LIBRARY_PATH}
+          HOST_UID=$(id -u)
+          HOST_GID=$(id -g)
 
-          cmake -S . -B build \
-              -DCMAKE_BUILD_TYPE=${{ matrix.build }} \
-              -DGGML_CANN=on \
-              -DSOC_TYPE=ascend${{ matrix.chip_type }}
-          cmake --build build -j $(nproc)
+          docker run --rm \
+            -v "${PWD}:/workspace" \
+            -w /workspace \
+            -e SOC_TYPE=${SOC_TYPE} \
+            -e BUILD_TYPE=${BUILD_TYPE} \
+            "${{ steps.cann-image.outputs.image }}" \
+            bash -lc '
+              set -e
+              yum install -y --setopt=install_weak_deps=False --setopt=tsflags=nodocs git gcc gcc-c++ make cmake libcurl-devel
+              yum clean all && rm -rf /var/cache/yum
+              git config --global --add safe.directory "/workspace"
+              export LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/$(uname -m)-linux/devlib/:${LD_LIBRARY_PATH}
+              cmake -S . -B build \
+                  -DCMAKE_BUILD_TYPE=${BUILD_TYPE} \
+                  -DGGML_CANN=on \
+                  -DSOC_TYPE=${SOC_TYPE}
+              cmake --build build -j $(nproc)
+
+              chown -R '"${HOST_UID}"':'"${HOST_GID}"' /workspace/build
+            '
 
 # TODO: simplify the following workflows using a matrix
 # TODO: run lighter CI on PRs and the full CI only on master (if needed)
@@ -1435,6 +1488,7 @@ jobs:
         with:
           key: ggml-ci-x64-cpu-low-perf
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dependencies
         id: depends
@@ -1460,6 +1514,7 @@ jobs:
         with:
           key: ggml-ci-arm64-cpu-low-perf
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dependencies
         id: depends
@@ -1485,6 +1540,7 @@ jobs:
         with:
           key: ggml-ci-x64-cpu-high-perf
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dependencies
         id: depends
@@ -1510,6 +1566,7 @@ jobs:
         with:
           key: ggml-ci-arm64-cpu-high-perf
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dependencies
         id: depends
@@ -1535,6 +1592,7 @@ jobs:
         with:
           key: ggml-ci-arm64-cpu-high-perf-sve
           evict-old-files: 1d
+          save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
       - name: Dependencies
         id: depends
@@ -1670,6 +1728,7 @@ jobs:
          with:
            key: ggml-ci-arm64-cpu-kleidiai
            evict-old-files: 1d
+           save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
        - name: Dependencies
          id: depends
@@ -1770,7 +1829,7 @@ jobs:
           echo "Fetch llama2c model"
           wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
           ./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
-          ./bin/llama-cli -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
+          ./bin/llama-completion -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
 
   ubuntu-cmake-sanitizer-riscv64-native:
     runs-on: RISCV64
@@ -2053,6 +2112,7 @@ jobs:
          with:
            key: ggml-ci-arm64-graviton4-kleidiai
            evict-old-files: 1d
+           save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
 
        - name: Test
          id: ggml-ci

.github/workflows/release.yml

@@ -66,16 +66,9 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          zip -y -r llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip ./build/bin/*
           tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
 
-      - name: Upload artifacts (zip)
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip
-          name: llama-bin-macos-arm64.zip
-
-      - name: Upload artifacts (tar)
+      - name: Upload artifacts
         uses: actions/upload-artifact@v4
         with:
           path: llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz
@@ -127,16 +120,9 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          zip -y -r llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip ./build/bin/*
           tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
 
-      - name: Upload artifacts (zip)
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip
-          name: llama-bin-macos-x64.zip
-
-      - name: Upload artifacts (tar)
+      - name: Upload artifacts
         uses: actions/upload-artifact@v4
         with:
           path: llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz
@@ -196,16 +182,9 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          zip -y -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip ./build/bin/*
           tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
 
-      - name: Upload artifacts (zip)
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip
-          name: llama-bin-ubuntu-${{ matrix.build }}.zip
-
-      - name: Upload artifacts (tar)
+      - name: Upload artifacts
         uses: actions/upload-artifact@v4
         with:
           path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.tar.gz
@@ -256,16 +235,9 @@ jobs:
         id: pack_artifacts
         run: |
           cp LICENSE ./build/bin/
-          zip -y -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip ./build/bin/*
           tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
 
-      - name: Upload artifacts (zip)
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip
-          name: llama-bin-ubuntu-vulkan-x64.zip
-
-      - name: Upload artifacts (tar)
+      - name: Upload artifacts
         uses: actions/upload-artifact@v4
         with:
           path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz
@@ -716,21 +688,86 @@ jobs:
       - name: Pack artifacts
         id: pack_artifacts
         run: |
-          zip -y -r llama-${{ steps.tag.outputs.name }}-xcframework.zip build-apple/llama.xcframework
           tar -czvf llama-${{ steps.tag.outputs.name }}-xcframework.tar.gz -C build-apple llama.xcframework
 
-      - name: Upload artifacts (zip)
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-xcframework.zip
-          name: llama-${{ steps.tag.outputs.name }}-xcframework.zip
-
-      - name: Upload artifacts (tar)
+      - name: Upload artifacts
         uses: actions/upload-artifact@v4
         with:
           path: llama-${{ steps.tag.outputs.name }}-xcframework.tar.gz
           name: llama-${{ steps.tag.outputs.name }}-xcframework.tar.gz
 
+
+  openEuler-cann:
+    strategy:
+      matrix:
+        arch: [x86, aarch64]
+        chip_type: ['910b', '310p']
+        build: ['Release']
+    runs-on: ${{ matrix.arch == 'aarch64' && 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Free up disk space
+        uses: ggml-org/free-disk-space@v1.3.1
+        with:
+          tool-cache: true
+
+      - name: Set container image
+        id: cann-image
+        run: |
+          image="ascendai/cann:${{ matrix.chip_type == '910b' &&  '8.3.rc2-910b-openeuler24.03-py3.11' || '8.3.rc2-310p-openeuler24.03-py3.11' }}"
+          echo "image=${image}" >> "${GITHUB_OUTPUT}"
+
+      - name: Pull container image
+        run: docker pull "${{ steps.cann-image.outputs.image }}"
+
+      - name: Build
+        env:
+          BUILD_TYPE: ${{ matrix.build }}
+          SOC_TYPE: ascend${{ matrix.chip_type }}
+        run: |
+          HOST_UID=$(id -u)
+          HOST_GID=$(id -g)
+
+          docker run --rm \
+            -v "${PWD}:/workspace" \
+            -w /workspace \
+            -e SOC_TYPE=${SOC_TYPE} \
+            -e BUILD_TYPE=${BUILD_TYPE} \
+            "${{ steps.cann-image.outputs.image }}" \
+            bash -lc '
+              set -e
+              yum install -y --setopt=install_weak_deps=False --setopt=tsflags=nodocs git gcc gcc-c++ make cmake libcurl-devel
+              yum clean all && rm -rf /var/cache/yum
+              git config --global --add safe.directory "/workspace"
+              export LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/$(uname -m)-linux/devlib/:${LD_LIBRARY_PATH}
+              cmake -S . -B build \
+                  -DCMAKE_BUILD_TYPE=${BUILD_TYPE} \
+                  -DGGML_CANN=on \
+                  -DSOC_TYPE=${SOC_TYPE}
+              cmake --build build -j $(nproc)
+
+              chown -R '"${HOST_UID}"':'"${HOST_GID}"' /workspace/build
+            '
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        run: |
+          cp LICENSE ./build/bin/
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}.tar.gz
+          name: llama-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}.tar.gz
+
   release:
     if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
 
@@ -752,6 +789,7 @@ jobs:
       - macOS-arm64
       - macOS-x64
       - ios-xcode-build
+      - openEuler-cann
 
     steps:
       - name: Clone
@@ -816,9 +854,6 @@ jobs:
         with:
           tag_name: ${{ steps.tag.outputs.name }}
           body: |
-            > [!WARNING]
-            > **Release Format Update**: Linux releases will soon use .tar.gz archives instead of .zip. Please make the necessary changes to your deployment scripts.
-
             <details open>
 
             ${{ github.event.head_commit.message }}
@@ -838,12 +873,18 @@ jobs:
             **Windows:**
             - [Windows x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cpu-x64.zip)
             - [Windows arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cpu-arm64.zip)
-            - [Windows x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-12.4-x64.zip)
-            - [Windows x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-13.1-x64.zip)
+            - [Windows x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/${{ 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-13.1-x64.zip) - [CUDA 13.1 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-13.1-x64.zip)
             - [Windows x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-vulkan-x64.zip)
             - [Windows x64 (SYCL)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-sycl-x64.zip)
             - [Windows x64 (HIP)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-hip-radeon-x64.zip)
 
+            **openEuler:**
+            - [openEuler x86 (310p)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-310p-openEuler-x86.tar.gz)
+            - [openEuler x86 (910b)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-910b-openEuler-x86.tar.gz)
+            - [openEuler aarch64 (310p)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-310p-openEuler-aarch64.tar.gz)
+            - [openEuler aarch64 (910b)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-910b-openEuler-aarch64.tar.gz)
+
       - name: Upload release
         id: upload_release
         uses: actions/github-script@v3

.github/workflows/server-webui.yml

@@ -0,0 +1,225 @@
+# Server WebUI build and tests
+name: Server WebUI
+
+on:
+  workflow_dispatch: # allows manual triggering
+    inputs:
+      sha:
+        description: 'Commit SHA1 to build'
+        required: false
+        type: string
+      slow_tests:
+        description: 'Run slow tests'
+        required: true
+        type: boolean
+  push:
+    branches:
+      - master
+    paths: ['.github/workflows/server-webui.yml', 'tools/server/webui/**.*', 'tools/server/tests/**.*', 'tools/server/public/**']
+  pull_request:
+    types: [opened, synchronize, reopened]
+    paths: ['.github/workflows/server-webui.yml', 'tools/server/webui/**.*', 'tools/server/tests/**.*', 'tools/server/public/**']
+
+env:
+  LLAMA_LOG_COLORS: 1
+  LLAMA_LOG_PREFIX: 1
+  LLAMA_LOG_TIMESTAMPS: 1
+  LLAMA_LOG_VERBOSITY: 10
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  webui-check:
+    name: WebUI Checks
+    runs-on: ubuntu-latest
+    continue-on-error: true
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
+
+      - name: Setup Node.js
+        id: node
+        uses: actions/setup-node@v4
+        with:
+          node-version: "22"
+          cache: "npm"
+          cache-dependency-path: "tools/server/webui/package-lock.json"
+
+      - name: Install dependencies
+        id: setup
+        if: ${{ steps.node.conclusion == 'success' }}
+        run: npm ci
+        working-directory: tools/server/webui
+
+      - name: Run type checking
+        if: ${{ always() && steps.setup.conclusion == 'success' }}
+        run: npm run check
+        working-directory: tools/server/webui
+
+      - name: Run linting
+        if: ${{ always() && steps.setup.conclusion == 'success' }}
+        run: npm run lint
+        working-directory: tools/server/webui
+
+      - name: Build application
+        if: ${{ always() && steps.setup.conclusion == 'success' }}
+        run: npm run build
+        working-directory: tools/server/webui
+
+      - name: Install Playwright browsers
+        id: playwright
+        if: ${{ always() && steps.setup.conclusion == 'success' }}
+        run: npx playwright install --with-deps
+        working-directory: tools/server/webui
+
+      - name: Build Storybook
+        if: ${{ always() && steps.playwright.conclusion == 'success' }}
+        run: npm run build-storybook
+        working-directory: tools/server/webui
+
+      - name: Run Client tests
+        if: ${{ always() && steps.playwright.conclusion == 'success' }}
+        run: npm run test:client
+        working-directory: tools/server/webui
+
+      - name: Run Unit tests
+        if: ${{ always() && steps.playwright.conclusion == 'success' }}
+        run: npm run test:unit
+        working-directory: tools/server/webui
+
+      - name: Run UI tests
+        if: ${{ always() && steps.playwright.conclusion == 'success' }}
+        run: npm run test:ui -- --testTimeout=60000
+        working-directory: tools/server/webui
+
+      - name: Run E2E tests
+        if: ${{ always() && steps.playwright.conclusion == 'success' }}
+        run: npm run test:e2e
+        working-directory: tools/server/webui
+
+  server-build:
+    runs-on: ubuntu-latest
+
+    strategy:
+      matrix:
+        sanitizer: [ADDRESS, UNDEFINED] # THREAD is broken
+        build_type: [RelWithDebInfo]
+        include:
+          - build_type: Release
+            sanitizer: ""
+      fail-fast: false # While -DLLAMA_SANITIZE_THREAD=ON is broken
+
+    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@v4
+        with:
+          fetch-depth: 0
+          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
+
+      - name: Python setup
+        id: setup_python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Tests dependencies
+        id: test_dependencies
+        run: |
+          pip install -r tools/server/tests/requirements.txt
+
+      - name: Setup Node.js for WebUI
+        uses: actions/setup-node@v4
+        with:
+          node-version: "22"
+          cache: "npm"
+          cache-dependency-path: "tools/server/webui/package-lock.json"
+
+      - name: Install WebUI dependencies
+        run: npm ci
+        working-directory: tools/server/webui
+
+      - name: Build WebUI
+        run: npm run build
+        working-directory: tools/server/webui
+
+      - name: Build (no OpenMP)
+        id: cmake_build_no_openmp
+        if: ${{ matrix.sanitizer == 'THREAD' }}
+        run: |
+          cmake -B build \
+              -DGGML_NATIVE=OFF \
+              -DLLAMA_CURL=OFF \
+              -DLLAMA_OPENSSL=ON \
+              -DLLAMA_BUILD_SERVER=ON \
+              -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
+              -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
+              -DGGML_OPENMP=OFF ;
+          cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
+
+      - name: Build (sanitizers)
+        id: cmake_build_sanitizers
+        if: ${{ matrix.sanitizer != '' && matrix.sanitizer != 'THREAD' }}
+        run: |
+          cmake -B build \
+              -DGGML_NATIVE=OFF \
+              -DLLAMA_CURL=OFF \
+              -DLLAMA_OPENSSL=ON \
+              -DLLAMA_BUILD_SERVER=ON \
+              -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
+              -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
+          cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
+
+      - name: Build (sanitizers)
+        id: cmake_build
+        if: ${{ matrix.sanitizer == '' }}
+        run: |
+          cmake -B build \
+              -DGGML_NATIVE=OFF \
+              -DLLAMA_CURL=OFF \
+              -DLLAMA_OPENSSL=ON \
+              -DLLAMA_BUILD_SERVER=ON \
+              -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} ;
+          cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
+
+      - name: Tests
+        id: server_integration_tests
+        if: ${{ matrix.sanitizer == '' }}
+        env:
+          GITHUB_ACTIONS: "true"
+        run: |
+          cd tools/server/tests
+          ./tests.sh
+
+      - name: Tests (sanitizers)
+        id: server_integration_tests_sanitizers
+        if: ${{ matrix.sanitizer != '' }}
+        run: |
+          cd tools/server/tests
+          LLAMA_SANITIZE=1 ./tests.sh
+
+      - name: Slow tests
+        id: server_integration_tests_slow
+        if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }}
+        run: |
+          cd tools/server/tests
+          SLOW_TESTS=1 ./tests.sh

.github/workflows/server.yml

@@ -76,270 +76,6 @@ jobs:
         run: |
           pip install -r tools/server/tests/requirements.txt
 
-  webui-setup:
-    name: WebUI Setup
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22"
-          cache: "npm"
-          cache-dependency-path: "tools/server/webui/package-lock.json"
-
-      - name: Cache node_modules
-        uses: actions/cache@v4
-        id: cache-node-modules
-        with:
-          path: tools/server/webui/node_modules
-          key: ${{ runner.os }}-node-modules-${{ hashFiles('tools/server/webui/package-lock.json') }}
-          restore-keys: |
-            ${{ runner.os }}-node-modules-
-
-      - name: Install dependencies
-        if: steps.cache-node-modules.outputs.cache-hit != 'true'
-        run: npm ci
-        working-directory: tools/server/webui
-
-  webui-check:
-    needs: webui-setup
-    name: WebUI Check
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22"
-
-      - name: Restore node_modules cache
-        uses: actions/cache@v4
-        with:
-          path: tools/server/webui/node_modules
-          key: ${{ runner.os }}-node-modules-${{ hashFiles('tools/server/webui/package-lock.json') }}
-          restore-keys: |
-            ${{ runner.os }}-node-modules-
-
-      - name: Run type checking
-        run: npm run check
-        working-directory: tools/server/webui
-
-      - name: Run linting
-        run: npm run lint
-        working-directory: tools/server/webui
-
-  webui-build:
-    needs: webui-check
-    name: WebUI Build
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22"
-
-      - name: Restore node_modules cache
-        uses: actions/cache@v4
-        with:
-          path: tools/server/webui/node_modules
-          key: ${{ runner.os }}-node-modules-${{ hashFiles('tools/server/webui/package-lock.json') }}
-          restore-keys: |
-            ${{ runner.os }}-node-modules-
-
-      - name: Build application
-        run: npm run build
-        working-directory: tools/server/webui
-
-  webui-tests:
-    needs: webui-build
-    name: Run WebUI tests
-    permissions:
-      contents: read
-
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22"
-
-      - name: Restore node_modules cache
-        uses: actions/cache@v4
-        with:
-          path: tools/server/webui/node_modules
-          key: ${{ runner.os }}-node-modules-${{ hashFiles('tools/server/webui/package-lock.json') }}
-          restore-keys: |
-            ${{ runner.os }}-node-modules-
-
-      - name: Install Playwright browsers
-        run: npx playwright install --with-deps
-        working-directory: tools/server/webui
-
-      - name: Build Storybook
-        run: npm run build-storybook
-        working-directory: tools/server/webui
-
-      - name: Run Client tests
-        run: npm run test:client
-        working-directory: tools/server/webui
-
-      - name: Run Server tests
-        run: npm run test:server
-        working-directory: tools/server/webui
-
-      - name: Run UI tests
-        run: npm run test:ui -- --testTimeout=60000
-        working-directory: tools/server/webui
-
-      - name: Run E2E tests
-        run: npm run test:e2e
-        working-directory: tools/server/webui
-
-  server-build:
-    needs: [webui-tests]
-    runs-on: ubuntu-latest
-
-    strategy:
-      matrix:
-        sanitizer: [ADDRESS, UNDEFINED] # THREAD is broken
-        build_type: [RelWithDebInfo]
-        include:
-          - build_type: Release
-            sanitizer: ""
-      fail-fast: false # While -DLLAMA_SANITIZE_THREAD=ON is broken
-
-    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@v4
-        with:
-          fetch-depth: 0
-          ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
-
-      - name: Python setup
-        id: setup_python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.11'
-
-      - name: Tests dependencies
-        id: test_dependencies
-        run: |
-          pip install -r tools/server/tests/requirements.txt
-
-      - name: Setup Node.js for WebUI
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22"
-          cache: "npm"
-          cache-dependency-path: "tools/server/webui/package-lock.json"
-
-      - name: Install WebUI dependencies
-        run: npm ci
-        working-directory: tools/server/webui
-
-      - name: Build WebUI
-        run: npm run build
-        working-directory: tools/server/webui
-
-      - name: Build (no OpenMP)
-        id: cmake_build_no_openmp
-        if: ${{ matrix.sanitizer == 'THREAD' }}
-        run: |
-          cmake -B build \
-              -DGGML_NATIVE=OFF \
-              -DLLAMA_CURL=OFF \
-              -DLLAMA_OPENSSL=ON \
-              -DLLAMA_BUILD_SERVER=ON \
-              -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-              -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
-              -DGGML_OPENMP=OFF ;
-          cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
-
-      - name: Build (sanitizers)
-        id: cmake_build_sanitizers
-        if: ${{ matrix.sanitizer != '' && matrix.sanitizer != 'THREAD' }}
-        run: |
-          cmake -B build \
-              -DGGML_NATIVE=OFF \
-              -DLLAMA_CURL=OFF \
-              -DLLAMA_OPENSSL=ON \
-              -DLLAMA_BUILD_SERVER=ON \
-              -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-              -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
-          cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
-
-      - name: Build (sanitizers)
-        id: cmake_build
-        if: ${{ matrix.sanitizer == '' }}
-        run: |
-          cmake -B build \
-              -DGGML_NATIVE=OFF \
-              -DLLAMA_CURL=OFF \
-              -DLLAMA_OPENSSL=ON \
-              -DLLAMA_BUILD_SERVER=ON \
-              -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} ;
-          cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
-
-      - name: Tests
-        id: server_integration_tests
-        if: ${{ matrix.sanitizer == '' }}
-        env:
-          GITHUB_ACTIONS: "true"
-        run: |
-          cd tools/server/tests
-          ./tests.sh
-
-      - name: Tests (sanitizers)
-        id: server_integration_tests_sanitizers
-        if: ${{ matrix.sanitizer != '' }}
-        run: |
-          cd tools/server/tests
-          LLAMA_SANITIZE=1 ./tests.sh
-
-      - name: Slow tests
-        id: server_integration_tests_slow
-        if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }}
-        run: |
-          cd tools/server/tests
-          SLOW_TESTS=1 ./tests.sh
-
-
   server-windows:
     runs-on: windows-2022
 

.gitignore

@@ -54,6 +54,7 @@
 /out/
 /tmp/
 /autogen-*.md
+/common/build-info.cpp
 
 # Deprecated
 

CODEOWNERS

@@ -32,7 +32,7 @@
 /examples/export-docs/                  @ggerganov
 /examples/gen-docs/                     @ggerganov
 /examples/gguf/                         @ggerganov
-/examples/llama.android/                @ggerganov
+/examples/llama.android/                @ggerganov @hanyin-arm @naco-siren
 /examples/llama.swiftui/                @ggerganov
 /examples/llama.vim                     @ggerganov
 /examples/lookahead/                    @ggerganov
@@ -87,7 +87,8 @@
 /tests/                                 @ggerganov
 /tests/test-chat-.*                     @pwilkin
 /tools/batched-bench/                   @ggerganov
-/tools/main/                            @ggerganov
+/tools/cli/                             @ngxson
+/tools/completion/                      @ggerganov
 /tools/mtmd/                            @ngxson
 /tools/perplexity/                      @ggerganov
 /tools/quantize/                        @ggerganov

CONTRIBUTING.md

@@ -15,6 +15,7 @@ The project differentiates between 3 levels of contributors:
     - If you modified the `ggml` source, run the `test-backend-ops` tool to check whether different backend implementations of the `ggml` operators produce consistent results (this requires access to at least two different `ggml` backends)
     - If you modified a `ggml` operator or added a new one, add the corresponding test cases to `test-backend-ops`
 - Create separate PRs for each feature or fix. Avoid combining unrelated changes in a single PR
+- When adding support for a new model or feature, focus on **CPU support only** in the initial PR unless you have a good reason not to. Add support for other backends like CUDA in follow-up PRs
 - Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly
 - If your PR becomes stale, rebase it on top of latest `master` to get maintainers attention
 - Maintainers will rely on your insights and approval when making a final decision to approve and merge a PR

README.md

@@ -190,6 +190,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
 - Swift [ShenghaiWang/SwiftLlama](https://github.com/ShenghaiWang/SwiftLlama)
 - Delphi [Embarcadero/llama-cpp-delphi](https://github.com/Embarcadero/llama-cpp-delphi)
 - Go (no CGo needed): [hybridgroup/yzma](https://github.com/hybridgroup/yzma)
+- Android: [llama.android](/examples/llama.android)
 
 </details>
 
@@ -313,7 +314,7 @@ The Hugging Face platform provides a variety of online tools for converting, qua
 
 To learn more about model quantization, [read this documentation](tools/quantize/README.md)
 
-## [`llama-cli`](tools/main)
+## [`llama-cli`](tools/cli)
 
 #### A CLI tool for accessing and experimenting with most of `llama.cpp`'s functionality.
 
@@ -347,19 +348,6 @@ To learn more about model quantization, [read this documentation](tools/quantize
 
     </details>
 
-- <details>
-    <summary>Run simple text completion</summary>
-
-    To disable conversation mode explicitly, use `-no-cnv`
-
-    ```bash
-    llama-cli -m model.gguf -p "I believe the meaning of life is" -n 128 -no-cnv
-
-    # I believe the meaning of life is to find your own truth and to live in accordance with it. For me, this means being true to myself and following my passions, even if they don't align with societal expectations. I think that's what I love about yoga – it's not just a physical practice, but a spiritual one too. It's about connecting with yourself, listening to your inner voice, and honoring your own unique journey.
-    ```
-
-    </details>
-
 - <details>
     <summary>Constrain the output with a custom grammar</summary>
 
@@ -538,7 +526,8 @@ To learn more about model quantization, [read this documentation](tools/quantize
 
 ## Other documentation
 
-- [main (cli)](tools/main/README.md)
+- [cli](tools/cli/README.md)
+- [completion](tools/completion/README.md)
 - [server](tools/server/README.md)
 - [GBNF grammars](grammars/README.md)
 

SECURITY.md

@@ -68,3 +68,6 @@ Please disclose it as a private [security advisory](https://github.com/ggml-org/
 Please note that using AI to identify vulnerabilities and generate reports is permitted. However, you must (1) explicitly disclose how AI was used and (2) conduct a thorough manual review before submitting the report.
 
 A team of volunteers on a reasonable-effort basis maintains this project. As such, please give us at least 90 days to work on a fix before public exposure.
+
+> [!IMPORTANT]
+> For collaborators: if you are interested in helping out with reviewing privting security disclosures, please see: https://github.com/ggml-org/llama.cpp/discussions/18080

ci/run.sh

@@ -398,18 +398,20 @@ function gg_run_qwen3_0_6b {
     ./bin/llama-quantize ${model_bf16} ${model_q5_k} q5_k $(nproc)
     ./bin/llama-quantize ${model_bf16} ${model_q6_k} q6_k $(nproc)
 
-    (time ./bin/llama-cli -no-cnv --model ${model_f16}  -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
-    (time ./bin/llama-cli -no-cnv --model ${model_bf16} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-bf16.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q8_0} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q4_0} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q4_1} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q5_0} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q5_1} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q2_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q3_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q4_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q5_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
-    (time ./bin/llama-cli -no-cnv --model ${model_q6_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
+    (time ./bin/llama-fit-params --model ${model_f16} 2>&1 | tee -a $OUT/${ci}-fp-f16.log)
+
+    (time ./bin/llama-completion -no-cnv --model ${model_f16}  -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
+    (time ./bin/llama-completion -no-cnv --model ${model_bf16} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-bf16.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q8_0} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q4_0} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q4_1} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q5_0} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q5_1} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q2_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q3_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q4_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q5_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
+    (time ./bin/llama-completion -no-cnv --model ${model_q6_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
 
     (time ./bin/llama-perplexity --model ${model_f16}  -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
     if [ -z ${GG_BUILD_NO_BF16} ]; then
@@ -523,6 +525,8 @@ function gg_run_embd_bge_small {
 
     ./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
 
+    (time ./bin/llama-fit-params --model ${model_f16} 2>&1 | tee -a $OUT/${ci}-fp-f16.log)
+
     (time ./bin/llama-embedding --model ${model_f16}  -p "I believe the meaning of life is" -ngl 99 -c 0 --no-op-offload) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
     (time ./bin/llama-embedding --model ${model_q8_0} -p "I believe the meaning of life is" -ngl 99 -c 0 --no-op-offload) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
 
@@ -563,6 +567,8 @@ function gg_run_rerank_tiny {
 
     model_f16="${path_models}/ggml-model-f16.gguf"
 
+    (time ./bin/llama-fit-params --model ${model_f16} 2>&1 | tee -a $OUT/${ci}-fp-f16.log)
+
     # for this model, the SEP token is "</s>"
     (time ./bin/llama-embedding --model ${model_f16} -p "what is panda?\thi\nwhat is panda?\tit's a bear\nwhat is panda?\tThe giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China." -ngl 99 -c 0 --pooling rank --embd-normalize -1 --no-op-offload --verbose-prompt) 2>&1 | tee -a $OUT/${ci}-rk-f16.log
 

common/CMakeLists.txt

@@ -73,6 +73,8 @@ add_library(${TARGET} STATIC
     ngram-cache.h
     peg-parser.cpp
     peg-parser.h
+    preset.cpp
+    preset.h
     regex-partial.cpp
     regex-partial.h
     sampling.cpp

common/arg.h

@@ -3,8 +3,13 @@
 #include "common.h"
 
 #include <set>
+#include <map>
 #include <string>
 #include <vector>
+#include <cstring>
+
+// pseudo-env variable to identify preset-only arguments
+#define COMMON_ARG_PRESET_LOAD_ON_STARTUP "__PRESET_LOAD_ON_STARTUP"
 
 //
 // CLI argument parsing
@@ -14,15 +19,20 @@ struct common_arg {
     std::set<enum llama_example> examples = {LLAMA_EXAMPLE_COMMON};
     std::set<enum llama_example> excludes = {};
     std::vector<const char *> args;
+    std::vector<const char *> args_neg;  // for negated args like --no-xxx
     const char * value_hint   = nullptr; // help text or example for arg value
     const char * value_hint_2 = nullptr; // for second arg value
     const char * env          = nullptr;
     std::string help;
     bool is_sparam = false; // is current arg a sampling param?
+    bool is_preset_only = false; // is current arg preset-only (not treated as CLI arg)
     void (*handler_void)   (common_params & params) = nullptr;
     void (*handler_string) (common_params & params, const std::string &) = nullptr;
     void (*handler_str_str)(common_params & params, const std::string &, const std::string &) = nullptr;
     void (*handler_int)    (common_params & params, int) = nullptr;
+    void (*handler_bool)   (common_params & params, bool) = nullptr;
+
+    common_arg() = default;
 
     common_arg(
         const std::initializer_list<const char *> & args,
@@ -44,6 +54,13 @@ struct common_arg {
         void (*handler)(common_params & params)
     ) : args(args), help(help), handler_void(handler) {}
 
+    common_arg(
+        const std::initializer_list<const char *> & args,
+        const std::initializer_list<const char *> & args_neg,
+        const std::string & help,
+        void (*handler)(common_params & params, bool)
+    ) : args(args), args_neg(args_neg), help(help), handler_bool(handler) {}
+
     // support 2 values for arg
     common_arg(
         const std::initializer_list<const char *> & args,
@@ -57,13 +74,38 @@ struct common_arg {
     common_arg & set_excludes(std::initializer_list<enum llama_example> excludes);
     common_arg & set_env(const char * env);
     common_arg & set_sparam();
+    common_arg & set_preset_only();
     bool in_example(enum llama_example ex);
     bool is_exclude(enum llama_example ex);
     bool get_value_from_env(std::string & output) const;
     bool has_value_from_env() const;
-    std::string to_string();
+    std::string to_string() const;
+
+    // for using as key in std::map
+    bool operator<(const common_arg& other) const {
+        if (args.empty() || other.args.empty()) {
+            return false;
+        }
+        return strcmp(args[0], other.args[0]) < 0;
+    }
+    bool operator==(const common_arg& other) const {
+        if (args.empty() || other.args.empty()) {
+            return false;
+        }
+        return strcmp(args[0], other.args[0]) == 0;
+    }
+
+    // get all args and env vars (including negated args/env)
+    std::vector<std::string> get_args() const;
+    std::vector<std::string> get_env() const;
 };
 
+namespace common_arg_utils {
+    bool is_truthy(const std::string & value);
+    bool is_falsey(const std::string & value);
+    bool is_autoy(const std::string & value);
+}
+
 struct common_params_context {
     enum llama_example ex = LLAMA_EXAMPLE_COMMON;
     common_params & params;
@@ -76,7 +118,15 @@ struct common_params_context {
 // if one argument has invalid value, it will automatically display usage of the specific argument (and not the full usage message)
 bool common_params_parse(int argc, char ** argv, common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr);
 
-// function to be used by test-arg-parser
+// parse input arguments from CLI into a map
+bool common_params_to_map(int argc, char ** argv, llama_example ex, std::map<common_arg, std::string> & out_map);
+
+// populate preset-only arguments
+// these arguments are not treated as command line arguments
+// see: https://github.com/ggml-org/llama.cpp/issues/18163
+void common_params_add_preset_options(std::vector<common_arg> & args);
+
+// initialize argument parser context - used by test-arg-parser and preset
 common_params_context common_params_parser_init(common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr);
 
 struct common_remote_params {

common/chat-peg-parser.cpp

@@ -4,9 +4,14 @@
 
 using json = nlohmann::json;
 
-static std::string_view trim_trailing_space(std::string_view sv) {
+static std::string_view trim_trailing_space(std::string_view sv, int max = -1) {
+    int count = 0;
     while (!sv.empty() && std::isspace(static_cast<unsigned char>(sv.back()))) {
+        if (max != -1 && count <= max) {
+            break;
+        }
         sv.remove_suffix(1);
+        count++;
     }
     return sv;
 }
@@ -93,7 +98,7 @@ void common_chat_peg_constructed_mapper::map(const common_peg_ast_node & node) {
 
     if (is_arg_string && current_tool) {
         // Serialize to JSON, but exclude the end quote
-        std::string dumped = json(node.text).dump();
+        std::string dumped = json(trim_trailing_space(node.text)).dump();
         current_tool->arguments += dumped.substr(0, dumped.size() - 1);
         needs_closing_quote = true;
     }
@@ -101,6 +106,7 @@ void common_chat_peg_constructed_mapper::map(const common_peg_ast_node & node) {
     if (is_arg_close && current_tool) {
         if (needs_closing_quote) {
             current_tool->arguments += "\"";
+            needs_closing_quote = false;
         }
     }
 
@@ -109,6 +115,10 @@ void common_chat_peg_constructed_mapper::map(const common_peg_ast_node & node) {
     }
 
     if (is_tool_close && current_tool) {
+        if (needs_closing_quote) {
+            current_tool->arguments += "\"";
+            needs_closing_quote = false;
+        }
         current_tool->arguments += "}";
     }
 }

common/chat.cpp

@@ -1,5 +1,6 @@
 #include "chat.h"
 #include "chat-parser.h"
+#include "chat-peg-parser.h"
 #include "common.h"
 #include "json-partial.h"
 #include "json-schema-to-grammar.h"
@@ -150,6 +151,7 @@ struct templates_params {
     common_chat_tool_choice tool_choice;
     json json_schema;
     bool parallel_tool_calls;
+    common_reasoning_format reasoning_format;
     bool stream;
     std::string grammar;
     bool add_generation_prompt = true;
@@ -589,6 +591,16 @@ common_chat_templates_ptr common_chat_templates_init(
             "{%- if false %}");
     }
 
+    // TODO @aldehir : this is a temporary fix, pending Minja changes
+    // Ref: https://github.com/ggml-org/llama.cpp/pull/17713#issuecomment-3631342664
+    if (default_template_src.find("[TOOL_CALLS]") != std::string::npos
+            // search for the error message and patch it
+            && default_template_src.find("if (message['content'] is none or") != std::string::npos) {
+        string_replace_all(default_template_src,
+            "{%- if (message['content'] is none or message['content'] == '' or message['content']|length == 0) and (message['tool_calls'] is not defined or message['tool_calls'] is none or message['tool_calls']|length == 0) %}",
+            "{%- if false %}");
+    }
+
     std::string token_bos = bos_token_override;
     std::string token_eos = eos_token_override;
     bool add_bos = false;
@@ -699,6 +711,25 @@ static void foreach_function(const json & tools, const std::function<void(const
     }
 }
 
+static void foreach_parameter(const json & function, const std::function<void(const std::string &, const json &, bool)> & fn) {
+    if (!function.contains("parameters") || !function.at("parameters").is_object()) {
+        return;
+    }
+    const auto & params = function.at("parameters");
+    if (!params.contains("properties") || !params.at("properties").is_object()) {
+        return;
+    }
+    const auto & props = params.at("properties");
+    std::set<std::string> required;
+    if (params.contains("required") && params.at("required").is_array()) {
+        params.at("required").get_to(required);
+    }
+    for (const auto & [name, prop] : props.items()) {
+        bool is_required = (required.find(name) != required.end());
+        fn(name, prop, is_required);
+    }
+}
+
 static std::string apply(
     const common_chat_template & tmpl,
     const struct templates_params & inputs,
@@ -987,6 +1018,118 @@ static common_chat_params common_chat_params_init_lfm2(const common_chat_templat
     return data;
 }
 
+static common_chat_params common_chat_params_init_ministral_3(const common_chat_template & tmpl, const struct templates_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(content.end(), blocks.begin(), blocks.end());
+            }
+        }
+
+        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 extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
+    auto include_grammar = true;
+
+    data.prompt = apply(tmpl, inputs, /* messages_override = */ adjusted_messages);
+    data.format = COMMON_CHAT_FORMAT_PEG_NATIVE;
+    data.preserved_tokens = {
+        "[THINK]",
+        "[/THINK]",
+        "[TOOL_CALLS]",
+        "[ARGS]",
+    };
+
+    auto parser = build_chat_peg_native_parser([&](common_chat_peg_native_builder & p) {
+        auto reasoning = extract_reasoning ? p.optional("[THINK]" + p.reasoning(p.until("[/THINK]")) + "[/THINK]") : p.eps();
+
+        // Response format parser
+        if (inputs.json_schema.is_object() && !inputs.json_schema.empty()) {
+            // Ministral wants to emit json surrounded by code fences
+            return reasoning << "```json" << p.content(p.schema(p.json(), "response-format", inputs.json_schema)) << "```";
+        }
+
+        // Tool call parser
+        if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE) {
+            auto tool_choice = p.choice();
+            foreach_function(inputs.tools, [&](const json & tool) {
+                const auto & function = tool.at("function");
+                std::string name = function.at("name");
+                const auto & schema = function.at("parameters");
+
+                tool_choice |= p.rule("tool-" + name,
+                    p.tool_open(p.tool_name(p.literal(name)) + "[ARGS]")
+                    + p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema))
+                );
+            });
+
+            auto min_calls = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? 1 : 0;
+            auto max_calls = inputs.parallel_tool_calls ? -1 : 1;
+            auto tool_calls = p.trigger_rule("tool-call", p.repeat("[TOOL_CALLS]" + tool_choice, min_calls, max_calls));
+
+            return reasoning << p.content(p.until("[TOOL_CALLS]")) << tool_calls;
+        }
+
+        // Content only parser
+        include_grammar = false;
+        return reasoning << p.content(p.rest());
+    });
+
+    data.parser = parser.save();
+
+    if (include_grammar) {
+        data.grammar_lazy = has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
+
+        data.grammar = build_grammar([&](const common_grammar_builder & builder) {
+            foreach_function(inputs.tools, [&](const json & tool) {
+                const auto & function = tool.at("function");
+                auto schema = function.at("parameters");
+                builder.resolve_refs(schema);
+            });
+            parser.build_grammar(builder, data.grammar_lazy);
+        });
+
+        data.grammar_triggers = {
+            {COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "[TOOL_CALLS]"}
+        };
+    }
+
+    return data;
+}
+
 static common_chat_params common_chat_params_init_magistral(const common_chat_template & tmpl, const struct templates_params & inputs) {
     common_chat_params data;
     data.prompt = apply(tmpl, inputs);
@@ -1285,6 +1428,123 @@ static common_chat_params common_chat_params_init_nemotron_v2(const common_chat_
     return data;
 }
 
+static common_chat_params common_chat_params_init_nemotron_v3(const common_chat_template & tmpl, const struct templates_params & inputs) {
+    common_chat_params data;
+
+    data.prompt = apply(tmpl, inputs);
+    data.format = COMMON_CHAT_FORMAT_PEG_CONSTRUCTED;
+
+    // Handle thinking tags appropriately based on inputs.enable_thinking
+    if (string_ends_with(data.prompt, "<think>\n")) {
+        if (!inputs.enable_thinking) {
+            data.prompt += "</think>";
+        } else {
+            data.thinking_forced_open = true;
+        }
+    }
+
+    data.preserved_tokens = {
+        "<think>",
+        "</think>",
+        "<tool_call>",
+        "</tool_call>",
+    };
+
+    auto has_tools = inputs.tools.is_array() && !inputs.tools.empty();
+    auto extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
+    auto include_grammar = true;
+
+    auto parser = build_chat_peg_constructed_parser([&](auto & p) {
+        auto reasoning = p.eps();
+        if (inputs.enable_thinking && extract_reasoning) {
+            auto reasoning_content = p.reasoning(p.until("</think>")) + ("</think>" | p.end());
+            if (data.thinking_forced_open) {
+                reasoning = reasoning_content;
+            }
+        }
+
+        // Response format parser
+        if (inputs.json_schema.is_object() && !inputs.json_schema.empty()) {
+            return 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 tool_choice = p.choice();
+            foreach_function(inputs.tools, [&](const json & tool) {
+                const auto & function = tool.at("function");
+                std::string name = function.at("name");
+                auto parameters = function.at("parameters");
+
+                auto schema_info = common_schema_info();
+                schema_info.resolve_refs(parameters);
+
+                auto tool_open = "<function=" + p.tool_name(p.literal(name)) + ">\n";
+                auto tool_close = p.literal("</function>\n");
+                auto args = p.sequence();
+                auto arg_string = p.rule("xml-arg-string", p.until_one_of({
+                    "\n</parameter>",
+                    "\n<parameter=",
+                    "\n</function>"
+                }));
+
+                foreach_parameter(function, [&](const auto & param_name, const json & param_schema, bool is_required) {
+                    auto rule_name = "tool-" + name + "-arg-" + param_name;
+
+                    auto arg_open = "<parameter=" + p.tool_arg_name(p.literal(param_name)) + ">\n";
+                    auto arg_close = p.literal("</parameter>\n");
+                    auto arg_value = p.eps();
+
+                    if (schema_info.resolves_to_string(param_schema)) {
+                        arg_value = p.tool_arg_string_value(arg_string) + "\n";
+                    } else {
+                        arg_value = p.tool_arg_json_value(p.schema(p.json(), rule_name + "-schema", param_schema));
+                    }
+
+                    // Model may or my not close with </parameter>
+                    auto arg_rule = p.rule(rule_name, p.tool_arg_open(arg_open) + arg_value + p.optional(p.tool_arg_close(arg_close)));
+                    args += p.repeat(arg_rule, /* min = */ is_required ? 1 : 0, /* max = */ 1);
+                });
+
+                tool_choice |= p.rule("tool-" + name, p.tool_open(tool_open) + args + p.tool_close(tool_close));
+            });
+
+            auto min_calls = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED ? 1 : 0;
+            auto max_calls = inputs.parallel_tool_calls ? -1 : 1;
+            auto tool_call = p.rule("tool-call", "<tool_call>\n" + tool_choice + "</tool_call>" + p.space());
+            auto tool_calls = p.trigger_rule("tool-call-root", p.repeat(tool_call, /* min = */ min_calls, /* max = */ max_calls));
+
+            return reasoning << p.content(p.until("<tool_call>")) << tool_calls;
+        }
+
+        // Content only parser
+        include_grammar = false;
+        return reasoning << p.content(p.rest());
+    });
+
+    data.parser = parser.save();
+
+    if (include_grammar) {
+        data.grammar_lazy = has_tools && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
+
+        data.grammar = build_grammar([&](const common_grammar_builder & builder) {
+            foreach_function(inputs.tools, [&](const json & tool) {
+                const auto & function = tool.at("function");
+                auto schema = function.at("parameters");
+                builder.resolve_refs(schema);
+            });
+            parser.build_grammar(builder, data.grammar_lazy);
+        });
+
+        data.grammar_triggers = {
+            {COMMON_GRAMMAR_TRIGGER_TYPE_WORD, "<tool_call>"}
+        };
+    }
+
+    return data;
+}
+
+
 static common_chat_params common_chat_params_init_apertus(const common_chat_template & tmpl, const struct templates_params & inputs) {
     common_chat_params data;
 
@@ -2341,6 +2601,7 @@ static common_chat_params common_chat_templates_apply_jinja(
     params.messages = common_chat_msgs_to_json_oaicompat<json>(inputs.messages, /* concat_text= */ !tmpl.original_caps().requires_typed_content);
     params.add_generation_prompt = inputs.add_generation_prompt;
     params.tool_choice = inputs.tool_choice;
+    params.reasoning_format = inputs.reasoning_format;
     params.enable_thinking = inputs.enable_thinking;
     params.grammar = inputs.grammar;
     params.now = inputs.now;
@@ -2409,6 +2670,10 @@ static common_chat_params common_chat_templates_apply_jinja(
         src.find("<function=") != std::string::npos &&
         src.find("<parameters>") != std::string::npos &&
         src.find("<parameter=") != std::string::npos) {
+        // Nemotron 3 Nano 30B A3B
+        if (src.find("<think>") != std::string::npos) {
+            return common_chat_params_init_nemotron_v3(tmpl, params);
+        }
         return common_chat_params_init_qwen3_coder_xml(tmpl, params);
     }
 
@@ -2504,6 +2769,13 @@ static common_chat_params common_chat_templates_apply_jinja(
         return common_chat_params_init_llama_3_x(tmpl, params, allow_python_tag_builtin_tools);
     }
 
+    // Ministral/Mistral Large 3
+    if (src.find("[SYSTEM_PROMPT]") != std::string::npos &&
+        src.find("[TOOL_CALLS]") != std::string::npos &&
+        src.find("[ARGS]") != std::string::npos) {
+        return common_chat_params_init_ministral_3(tmpl, params);
+    }
+
     if (src.find("[THINK]") != std::string::npos && src.find("[/THINK]") != std::string::npos) {
         return common_chat_params_init_magistral(tmpl, params);
     }

common/common.cpp

@@ -1013,31 +1013,40 @@ bool tty_can_use_colors() {
 // Model utils
 //
 
-static inline void common_init_sampler_from_model(
+// TODO: move to common/sampling
+static void common_init_sampler_from_model(
     const llama_model * model,
     common_params_sampling & sparams) {
 
     const uint64_t config = sparams.user_sampling_config;
 
     auto get_int32 = [&](const char * key, int32_t & dst, uint64_t user_config) {
-        if (config & user_config) return;
+        if (config & user_config) {
+            return;
+        }
 
         char buf[64] = {0};
         if (llama_model_meta_val_str(model, key, buf, sizeof(buf)) > 0) {
             char * end = nullptr;
             int32_t v = strtol(buf, &end, 10);
-            if (end && end != buf) dst = v;
+            if (end && end != buf) {
+                dst = v;
+            }
         }
     };
 
     auto get_float = [&](const char * key, float & dst, uint64_t user_config) {
-        if (config & user_config) return;
+        if (config & user_config) {
+            return;
+        }
 
         char buf[128] = {0};
         if (llama_model_meta_val_str(model, key, buf, sizeof(buf)) > 0) {
             char * end = nullptr;
             float v = strtof(buf, &end);
-            if (end && end != buf) dst = v;
+            if (end && end != buf) {
+                dst = v;
+            }
         }
     };
 
@@ -1065,31 +1074,125 @@ static inline void common_init_sampler_from_model(
     get_float(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_MIROSTAT_ETA),    sparams.mirostat_eta,    common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_MIROSTAT_ETA);
 }
 
-struct common_init_result common_init_from_params(common_params & params) {
-    common_init_result iparams;
+struct common_init_result::impl {
+    impl() = default;
+    ~impl() = default;
+
+    llama_model_ptr   model;
+    llama_context_ptr context;
+
+    std::vector<llama_adapter_lora_ptr> lora;
+
+    std::vector<common_sampler_ptr> samplers;
+};
+
+common_init_result::common_init_result(common_params & params) :
+    pimpl(new impl{}) {
     auto mparams = common_model_params_to_llama(params);
+    auto cparams = common_context_params_to_llama(params);
+
+    if (params.fit_params) {
+        LOG_INF("%s: fitting params to device memory, for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on\n", __func__);
+        llama_params_fit(params.model.path.c_str(), &mparams, &cparams,
+            params.tensor_split, params.tensor_buft_overrides.data(), params.fit_params_target, params.fit_params_min_ctx,
+            params.verbosity >= 4 ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR);
+    }
 
     llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams);
     if (model == NULL) {
-        LOG_ERR("%s: failed to load model '%s', try reducing --n-gpu-layers if you're running out of VRAM\n",
-            __func__, params.model.path.c_str());
-        return iparams;
+        return;
     }
 
-    common_init_sampler_from_model(model, params.sampling);
+    pimpl->model.reset(model);
 
     const llama_vocab * vocab = llama_model_get_vocab(model);
 
-    auto cparams = common_context_params_to_llama(params);
+    // updates params.sampling
+    // TODO: fix naming
+    common_init_sampler_from_model(model, params.sampling);
+
+    if (params.sampling.ignore_eos && llama_vocab_eos(vocab) == LLAMA_TOKEN_NULL) {
+        LOG_WRN("%s: warning: vocab does not have an EOS token, ignoring --ignore-eos\n", __func__);
+        params.sampling.ignore_eos = false;
+    }
+
+    // initialize once
+    for (llama_token i = 0; i < llama_vocab_n_tokens(vocab); i++) {
+        if (llama_vocab_is_eog(vocab, i)) {
+            LOG_INF("%s: added %s logit bias = %f\n", __func__, common_token_to_piece(vocab, i).c_str(), -INFINITY);
+            params.sampling.logit_bias_eog.push_back({i, -INFINITY});
+        }
+    }
+
+    if (params.sampling.ignore_eos) {
+        // add EOG biases to the active set of logit biases
+        params.sampling.logit_bias.insert(
+                params.sampling.logit_bias.end(),
+                params.sampling.logit_bias_eog.begin(), params.sampling.logit_bias_eog.end());
+    }
+
+    //if (params.sampling.penalty_last_n == -1) {
+    //    LOG_INF("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
+    //    params.sampling.penalty_last_n = llama_n_ctx(lctx);
+    //}
+
+    //if (params.sampling.dry_penalty_last_n == -1) {
+    //    LOG_INF("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
+    //    params.sampling.dry_penalty_last_n = llama_n_ctx(lctx);
+    //}
+
+    pimpl->samplers.resize(cparams.n_seq_max);
+
+    for (int i = 0; i < (int) cparams.n_seq_max; ++i) {
+        pimpl->samplers[i].reset(common_sampler_init(model, params.sampling));
+    }
 
     llama_context * lctx = llama_init_from_model(model, cparams);
     if (lctx == NULL) {
-        LOG_ERR("%s: failed to create context with model '%s', try reducing --n-gpu-layers if you're running out of VRAM\n",
-            __func__, params.model.path.c_str());
-        llama_model_free(model);
-        return iparams;
+        LOG_ERR("%s: failed to create context with model '%s'\n", __func__, params.model.path.c_str());
+        return;
     }
 
+    pimpl->context.reset(lctx);
+}
+
+llama_model * common_init_result::model() {
+    return pimpl->model.get();
+}
+
+llama_context * common_init_result::context() {
+    return pimpl->context.get();
+}
+
+common_sampler * common_init_result::sampler(llama_seq_id seq_id) {
+    return pimpl->samplers[seq_id].get();
+}
+
+std::vector<llama_adapter_lora_ptr> & common_init_result::lora() {
+    return pimpl->lora;
+}
+
+void common_init_result::free_context() {
+    pimpl->context.reset();
+}
+
+common_init_result_ptr common_init_from_params(common_params & params) {
+    common_init_result_ptr res(new common_init_result(params));
+
+    llama_model * model = res->model();
+    if (model == NULL) {
+        LOG_ERR("%s: failed to load model '%s'\n", __func__, params.model.path.c_str());
+        return res;
+    }
+
+    llama_context * lctx = res->context();
+    if (lctx == NULL) {
+        LOG_ERR("%s: failed to create context with model '%s'\n", __func__, params.model.path.c_str());
+        return res;
+    }
+
+    const llama_vocab * vocab = llama_model_get_vocab(model);
+
     if (params.ctx_shift && !llama_memory_can_shift(llama_get_memory(lctx))) {
         LOG_WRN("%s: KV cache shifting is not supported for this context, disabling KV cache shifting\n", __func__);
         params.ctx_shift = false;
@@ -1101,10 +1204,7 @@ struct common_init_result common_init_from_params(common_params & params) {
 
         const auto cvec = common_control_vector_load(params.control_vectors);
         if (cvec.n_embd == -1) {
-            llama_free(lctx);
-            llama_model_free(model);
-
-            return iparams;
+            return res;
         }
 
         int err = llama_apply_adapter_cvec(
@@ -1115,10 +1215,7 @@ struct common_init_result common_init_from_params(common_params & params) {
                 params.control_vector_layer_start,
                 params.control_vector_layer_end);
         if (err) {
-            llama_free(lctx);
-            llama_model_free(model);
-
-            return iparams;
+            return res;
         }
     }
 
@@ -1142,10 +1239,7 @@ struct common_init_result common_init_from_params(common_params & params) {
         }
 
         if (!ok) {
-            llama_free(lctx);
-            llama_model_free(model);
-
-            return iparams;
+            return res;
         }
     }
 
@@ -1155,9 +1249,7 @@ struct common_init_result common_init_from_params(common_params & params) {
         lora.reset(llama_adapter_lora_init(model, la.path.c_str()));
         if (lora == nullptr) {
             LOG_ERR("%s: failed to apply lora adapter '%s'\n", __func__, la.path.c_str());
-            llama_free(lctx);
-            llama_model_free(model);
-            return iparams;
+            return res;
         }
 
         char buf[1024];
@@ -1166,43 +1258,13 @@ struct common_init_result common_init_from_params(common_params & params) {
         la.task_name = buf;
         llama_adapter_meta_val_str(la.ptr, "adapter.lora.prompt_prefix", buf, sizeof(buf));
         la.prompt_prefix = buf;
-        iparams.lora.emplace_back(std::move(lora)); // copy to list of loaded adapters
+        res->lora().emplace_back(std::move(lora)); // copy to list of loaded adapters
     }
 
     if (!params.lora_init_without_apply) {
         common_set_adapter_lora(lctx, params.lora_adapters);
     }
 
-    if (params.sampling.ignore_eos && llama_vocab_eos(vocab) == LLAMA_TOKEN_NULL) {
-        LOG_WRN("%s: warning: vocab does not have an EOS token, ignoring --ignore-eos\n", __func__);
-        params.sampling.ignore_eos = false;
-    }
-
-    // initialize once
-    for (llama_token i = 0; i < llama_vocab_n_tokens(vocab); i++) {
-        if (llama_vocab_is_eog(vocab, i)) {
-            LOG_INF("%s: added %s logit bias = %f\n", __func__, common_token_to_piece(lctx, i).c_str(), -INFINITY);
-            params.sampling.logit_bias_eog.push_back({i, -INFINITY});
-        }
-    }
-
-    if (params.sampling.ignore_eos) {
-        // add EOG biases to the active set of logit biases
-        params.sampling.logit_bias.insert(
-                params.sampling.logit_bias.end(),
-                params.sampling.logit_bias_eog.begin(), params.sampling.logit_bias_eog.end());
-    }
-
-    if (params.sampling.penalty_last_n == -1) {
-        LOG_INF("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
-        params.sampling.penalty_last_n = llama_n_ctx(lctx);
-    }
-
-    if (params.sampling.dry_penalty_last_n == -1) {
-        LOG_INF("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
-        params.sampling.dry_penalty_last_n = llama_n_ctx(lctx);
-    }
-
     if (params.warmup) {
         LOG_WRN("%s: warming up the model with an empty run - please wait ... (--no-warmup to disable)\n", __func__);
 
@@ -1241,12 +1303,11 @@ struct common_init_result common_init_from_params(common_params & params) {
         llama_set_warmup(lctx, false);
     }
 
-    iparams.model.reset(model);
-    iparams.context.reset(lctx);
-
-    return iparams;
+    return res;
 }
 
+common_init_result::~common_init_result() = default;
+
 std::string get_model_endpoint() {
     const char * model_endpoint_env = getenv("MODEL_ENDPOINT");
     // We still respect the use of environment-variable "HF_ENDPOINT" for backward-compatibility.
@@ -1255,7 +1316,9 @@ std::string get_model_endpoint() {
     std::string model_endpoint = "https://huggingface.co/";
     if (endpoint_env) {
         model_endpoint = endpoint_env;
-        if (model_endpoint.back() != '/') model_endpoint += '/';
+        if (model_endpoint.back() != '/') {
+            model_endpoint += '/';
+        }
     }
     return model_endpoint;
 }

common/common.h

@@ -82,7 +82,8 @@ int32_t cpu_get_num_math();
 enum llama_example {
     LLAMA_EXAMPLE_COMMON,
     LLAMA_EXAMPLE_SPECULATIVE,
-    LLAMA_EXAMPLE_MAIN,
+    LLAMA_EXAMPLE_COMPLETION,
+    LLAMA_EXAMPLE_CLI,
     LLAMA_EXAMPLE_EMBEDDING,
     LLAMA_EXAMPLE_PERPLEXITY,
     LLAMA_EXAMPLE_RETRIEVAL,
@@ -98,6 +99,7 @@ enum llama_example {
     LLAMA_EXAMPLE_TTS,
     LLAMA_EXAMPLE_DIFFUSION,
     LLAMA_EXAMPLE_FINETUNE,
+    LLAMA_EXAMPLE_FIT_PARAMS,
 
     LLAMA_EXAMPLE_COUNT,
 };
@@ -194,7 +196,6 @@ struct common_params_sampling {
 
     std::vector<std::string> dry_sequence_breakers = {"\n", ":", "\"", "*"};     // default sequence breakers for DRY
 
-
     std::vector<enum common_sampler_type> samplers = {
         COMMON_SAMPLER_TYPE_PENALTIES,
         COMMON_SAMPLER_TYPE_DRY,
@@ -215,6 +216,10 @@ struct common_params_sampling {
     std::vector<llama_logit_bias> logit_bias;     // logit biases to apply
     std::vector<llama_logit_bias> logit_bias_eog; // pre-calculated logit biases for EOG tokens
 
+    bool has_logit_bias() const {
+        return !logit_bias.empty();
+    }
+
     // print the parameters into a string
     std::string print() const;
 };
@@ -302,8 +307,8 @@ struct lr_opt {
 struct ggml_opt_optimizer_params common_opt_lr_pars(void * userdata);
 
 struct common_params {
-    int32_t n_predict             =    -1; // new tokens to predict
-    int32_t n_ctx                 =  4096; // context size
+    int32_t n_predict             =    -1; // max. number of new tokens to predict, -1 == no limit
+    int32_t n_ctx                 =     0; // context size, 0 == context the model was trained with
     int32_t n_batch               =  2048; // logical batch size for prompt processing (must be >=32 to use BLAS)
     int32_t n_ubatch              =   512; // physical batch size for prompt processing (must be >=32 to use BLAS)
     int32_t n_keep                =     0; // number of tokens to keep from initial prompt
@@ -324,9 +329,12 @@ struct common_params {
     // offload params
     std::vector<ggml_backend_dev_t> devices; // devices to use for offloading
 
-    int32_t n_gpu_layers      = -1;  // number of layers to store in VRAM (-1 - use default)
-    int32_t main_gpu          = 0;   // the GPU that is used for scratch and small tensors
-    float   tensor_split[128] = {0}; // how split tensors should be distributed across GPUs
+    int32_t n_gpu_layers       = -1;               // number of layers to store in VRAM (-1 - use default)
+    int32_t main_gpu           = 0;                // the GPU that is used for scratch and small tensors
+    float   tensor_split[128]  = {0};              // how split tensors should be distributed across GPUs
+    bool    fit_params         = true;             // whether to fit unset model/context parameters to free device memory
+    size_t  fit_params_target  = 1024 * 1024*1024; // margin per device in bytes for fitting parameters to free memory
+    int32_t fit_params_min_ctx = 4096;             // minimum context size to set when trying to reduce memory use
 
     enum llama_split_mode split_mode = LLAMA_SPLIT_MODE_LAYER; // how to split the model across GPUs
 
@@ -406,6 +414,7 @@ struct common_params {
     bool simple_io         = false; // improves compatibility with subprocesses and limited consoles
     bool cont_batching     = true;  // insert new sequences for decoding on-the-fly
     bool no_perf           = false; // disable performance metrics
+    bool show_timings      = true;  // show timing information on CLI
     bool ctx_shift         = false; // context shift on infinite text generation
     bool swa_full          = false; // use full-size SWA cache (https://github.com/ggml-org/llama.cpp/pull/13194#issuecomment-2868343055)
     bool kv_unified        = false; // enable unified KV cache
@@ -462,7 +471,7 @@ struct common_params {
     std::string public_path   = "";                                                                         // NOLINT
     std::string api_prefix    = "";                                                                         // NOLINT
     std::string chat_template = "";                                                                         // NOLINT
-    bool use_jinja = false;                                                                                 // NOLINT
+    bool use_jinja = true;                                                                                  // NOLINT
     bool enable_chat_template = true;
     common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_DEEPSEEK;
     int reasoning_budget = -1;
@@ -475,16 +484,20 @@ struct common_params {
 
     std::map<std::string, std::string> default_template_kwargs;
 
+    // webui configs
+    bool webui = true;
+    std::string webui_config_json;
+
     // "advanced" endpoints are disabled by default for better security
-    bool webui            = true;
     bool endpoint_slots   = true;
     bool endpoint_props   = false; // only control POST requests, not GET
     bool endpoint_metrics = false;
 
     // router server configs
-    std::string models_dir = ""; // directory containing models for the router server
-    int models_max = 4;          // maximum number of models to load simultaneously
-    bool models_autoload = true; // automatically load models when requested via the router server
+    std::string models_dir    = ""; // directory containing models for the router server
+    std::string models_preset = ""; // directory containing model presets for the router server
+    int models_max = 4;             // maximum number of models to load simultaneously
+    bool models_autoload = true;    // automatically load models when requested via the router server
 
     bool log_json = false;
 
@@ -666,15 +679,29 @@ bool tty_can_use_colors();
 // Model utils
 //
 
-// note: defines object's lifetime
-struct common_init_result {
-    llama_model_ptr   model;
-    llama_context_ptr context;
+struct common_sampler;
 
-    std::vector<llama_adapter_lora_ptr> lora;
+// note: defines the model, context, samplers, ets. lifetimes
+struct common_init_result {
+    common_init_result(common_params & params);
+    ~common_init_result();
+
+    llama_model * model();
+    llama_context * context();
+    common_sampler * sampler(llama_seq_id seq_id);
+
+    std::vector<llama_adapter_lora_ptr> & lora();
+
+    void free_context();
+
+private:
+    struct impl;
+    std::unique_ptr<impl> pimpl;
 };
 
-struct common_init_result     common_init_from_params(common_params & params);
+using common_init_result_ptr = std::unique_ptr<common_init_result>;
+
+common_init_result_ptr common_init_from_params(common_params & params);
 
 struct llama_model_params     common_model_params_to_llama  (      common_params & params);
 struct llama_context_params   common_context_params_to_llama(const common_params & params);

common/console.cpp

@@ -1,4 +1,5 @@
 #include "console.h"
+#include "log.h"
 #include <vector>
 #include <iostream>
 #include <cassert>
@@ -6,6 +7,10 @@
 #include <cctype>
 #include <cwctype>
 #include <cstdint>
+#include <condition_variable>
+#include <mutex>
+#include <thread>
+#include <stdarg.h>
 
 #if defined(_WIN32)
 #define WIN32_LEAN_AND_MEAN
@@ -35,6 +40,7 @@
 #define ANSI_COLOR_BLUE    "\x1b[34m"
 #define ANSI_COLOR_MAGENTA "\x1b[35m"
 #define ANSI_COLOR_CYAN    "\x1b[36m"
+#define ANSI_COLOR_GRAY    "\x1b[90m"
 #define ANSI_COLOR_RESET   "\x1b[0m"
 #define ANSI_BOLD          "\x1b[1m"
 
@@ -61,17 +67,17 @@ namespace console {
     //
 #endif
 
-    static bool      advanced_display = false;
-    static bool      simple_io        = true;
-    static display_t current_display  = reset;
+    static bool         advanced_display = false;
+    static bool         simple_io        = true;
+    static display_type current_display  = DISPLAY_TYPE_RESET;
 
-    static FILE*     out              = stdout;
+    static FILE*        out              = stdout;
 
 #if defined (_WIN32)
-    static void*     hConsole;
+    static void*        hConsole;
 #else
-    static FILE*     tty              = nullptr;
-    static termios   initial_state;
+    static FILE*        tty              = nullptr;
+    static termios      initial_state;
 #endif
 
     //
@@ -142,7 +148,7 @@ namespace console {
 
     void cleanup() {
         // Reset console display
-        set_display(reset);
+        set_display(DISPLAY_TYPE_RESET);
 
 #if !defined(_WIN32)
         // Restore settings on POSIX systems
@@ -162,20 +168,26 @@ namespace console {
     //
 
     // Keep track of current display and only emit ANSI code if it changes
-    void set_display(display_t display) {
+    void set_display(display_type display) {
         if (advanced_display && current_display != display) {
-            fflush(stdout);
+            common_log_flush(common_log_main());
             switch(display) {
-                case reset:
+                case DISPLAY_TYPE_RESET:
                     fprintf(out, ANSI_COLOR_RESET);
                     break;
-                case prompt:
+                case DISPLAY_TYPE_INFO:
+                    fprintf(out, ANSI_COLOR_MAGENTA);
+                    break;
+                case DISPLAY_TYPE_PROMPT:
                     fprintf(out, ANSI_COLOR_YELLOW);
                     break;
-                case user_input:
+                case DISPLAY_TYPE_REASONING:
+                    fprintf(out, ANSI_COLOR_GRAY);
+                    break;
+                case DISPLAY_TYPE_USER_INPUT:
                     fprintf(out, ANSI_BOLD ANSI_COLOR_GREEN);
                     break;
-                case error:
+                case DISPLAY_TYPE_ERROR:
                     fprintf(out, ANSI_BOLD ANSI_COLOR_RED);
             }
             current_display = display;
@@ -778,7 +790,6 @@ namespace console {
             }
 
             if (is_special_char) {
-                set_display(user_input);
                 replace_last(line.back());
                 is_special_char = false;
             }
@@ -961,7 +972,6 @@ namespace console {
             }
 
             if (!line.empty() && (line.back() == '\\' || line.back() == '/')) {
-                set_display(prompt);
                 replace_last(line.back());
                 is_special_char = true;
             }
@@ -1046,12 +1056,82 @@ namespace console {
     }
 
     bool readline(std::string & line, bool multiline_input) {
-        set_display(user_input);
-
         if (simple_io) {
             return readline_simple(line, multiline_input);
         }
         return readline_advanced(line, multiline_input);
     }
 
+    namespace spinner {
+        static const char LOADING_CHARS[] = {'|', '/', '-', '\\'};
+        static std::condition_variable cv_stop;
+        static std::thread th;
+        static size_t frame = 0; // only modified by one thread
+        static bool running = false;
+        static std::mutex mtx;
+        static auto wait_time = std::chrono::milliseconds(100);
+        static void draw_next_frame() {
+            // don't need lock because only one thread modifies running
+            frame = (frame + 1) % sizeof(LOADING_CHARS);
+            replace_last(LOADING_CHARS[frame]);
+            fflush(out);
+        }
+        void start() {
+            std::unique_lock<std::mutex> lock(mtx);
+            if (simple_io || running) {
+                return;
+            }
+            common_log_flush(common_log_main());
+            fprintf(out, "%c", LOADING_CHARS[0]);
+            fflush(out);
+            frame = 1;
+            running = true;
+            th = std::thread([]() {
+                std::unique_lock<std::mutex> lock(mtx);
+                while (true) {
+                    if (cv_stop.wait_for(lock, wait_time, []{ return !running; })) {
+                        break;
+                    }
+                    draw_next_frame();
+                }
+            });
+        }
+        void stop() {
+            {
+                std::unique_lock<std::mutex> lock(mtx);
+                if (simple_io || !running) {
+                    return;
+                }
+                running = false;
+                cv_stop.notify_all();
+            }
+            if (th.joinable()) {
+                th.join();
+            }
+            replace_last(' ');
+            pop_cursor();
+            fflush(out);
+        }
+    }
+
+    void log(const char * fmt, ...) {
+        va_list args;
+        va_start(args, fmt);
+        vfprintf(out, fmt, args);
+        va_end(args);
+    }
+
+    void error(const char * fmt, ...) {
+        va_list args;
+        va_start(args, fmt);
+        display_type cur = current_display;
+        set_display(DISPLAY_TYPE_ERROR);
+        vfprintf(out, fmt, args);
+        set_display(cur); // restore previous color
+        va_end(args);
+    }
+
+    void flush() {
+        fflush(out);
+    }
 }

common/console.h

@@ -2,18 +2,40 @@
 
 #pragma once
 
+#include "common.h"
+
 #include <string>
 
-namespace console {
-    enum display_t {
-        reset = 0,
-        prompt,
-        user_input,
-        error
-    };
+enum display_type {
+    DISPLAY_TYPE_RESET = 0,
+    DISPLAY_TYPE_INFO,
+    DISPLAY_TYPE_PROMPT,
+    DISPLAY_TYPE_REASONING,
+    DISPLAY_TYPE_USER_INPUT,
+    DISPLAY_TYPE_ERROR
+};
 
+namespace console {
     void init(bool use_simple_io, bool use_advanced_display);
     void cleanup();
-    void set_display(display_t display);
+    void set_display(display_type display);
     bool readline(std::string & line, bool multiline_input);
+
+    namespace spinner {
+        void start();
+        void stop();
+    }
+
+    // note: the logging API below output directly to stdout
+    // it can negatively impact performance if used on inference thread
+    // only use in in a dedicated CLI thread
+    // for logging in inference thread, use log.h instead
+
+    LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2)
+    void log(const char * fmt, ...);
+
+    LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2)
+    void error(const char * fmt, ...);
+
+    void flush();
 }

common/download.cpp

@@ -12,6 +12,8 @@
 #include <filesystem>
 #include <fstream>
 #include <future>
+#include <map>
+#include <mutex>
 #include <regex>
 #include <string>
 #include <thread>
@@ -472,36 +474,79 @@ std::pair<long, std::vector<char>> common_remote_get_content(const std::string &
 
 #elif defined(LLAMA_USE_HTTPLIB)
 
-static bool is_output_a_tty() {
+class ProgressBar {
+    static inline std::mutex mutex;
+    static inline std::map<const ProgressBar *, int> lines;
+    static inline int max_line = 0;
+
+    static void cleanup(const ProgressBar * line) {
+        lines.erase(line);
+        if (lines.empty()) {
+            max_line = 0;
+        }
+    }
+
+    static bool is_output_a_tty() {
 #if defined(_WIN32)
-    return _isatty(_fileno(stdout));
+        return _isatty(_fileno(stdout));
 #else
-    return isatty(1);
+        return isatty(1);
 #endif
-}
-
-static void print_progress(size_t current, size_t total) {
-    if (!is_output_a_tty()) {
-        return;
     }
 
-    if (!total) {
-        return;
+public:
+    ProgressBar() = default;
+
+    ~ProgressBar() {
+        std::lock_guard<std::mutex> lock(mutex);
+        cleanup(this);
     }
 
-    size_t width = 50;
-    size_t pct = (100 * current) / total;
-    size_t pos = (width * current) / total;
+    void update(size_t current, size_t total) {
+        if (!is_output_a_tty()) {
+            return;
+        }
 
-    std::cout << "["
-              << std::string(pos, '=')
-              << (pos < width ? ">" : "")
-              << std::string(width - pos, ' ')
-              << "] " << std::setw(3) << pct << "%  ("
-              << current / (1024 * 1024) << " MB / "
-              << total / (1024 * 1024) << " MB)\r";
-    std::cout.flush();
-}
+        if (!total) {
+            return;
+        }
+
+        std::lock_guard<std::mutex> lock(mutex);
+
+        if (lines.find(this) == lines.end()) {
+            lines[this] = max_line++;
+            std::cout << "\n";
+        }
+        int lines_up = max_line - lines[this];
+
+        size_t width = 50;
+        size_t pct = (100 * current) / total;
+        size_t pos = (width * current) / total;
+
+        std::cout << "\033[s";
+
+        if (lines_up > 0) {
+            std::cout << "\033[" << lines_up << "A";
+        }
+        std::cout << "\033[2K\r["
+            << std::string(pos, '=')
+            << (pos < width ? ">" : "")
+            << std::string(width - pos, ' ')
+            << "] " << std::setw(3) << pct << "%  ("
+            << current / (1024 * 1024) << " MB / "
+            << total / (1024 * 1024) << " MB) "
+            << "\033[u";
+
+        std::cout.flush();
+
+        if (current == total) {
+             cleanup(this);
+        }
+    }
+
+    ProgressBar(const ProgressBar &) = delete;
+    ProgressBar & operator=(const ProgressBar &) = delete;
+};
 
 static bool common_pull_file(httplib::Client & cli,
                              const std::string & resolve_path,
@@ -523,6 +568,7 @@ static bool common_pull_file(httplib::Client & cli,
     const char * func = __func__; // avoid __func__ inside a lambda
     size_t downloaded = existing_size;
     size_t progress_step = 0;
+    ProgressBar bar;
 
     auto res = cli.Get(resolve_path, headers,
         [&](const httplib::Response &response) {
@@ -554,7 +600,7 @@ static bool common_pull_file(httplib::Client & cli,
             progress_step += len;
 
             if (progress_step >= total_size / 1000 || downloaded == total_size) {
-                print_progress(downloaded, total_size);
+                bar.update(downloaded, total_size);
                 progress_step = 0;
             }
             return true;
@@ -562,8 +608,6 @@ static bool common_pull_file(httplib::Client & cli,
         nullptr
     );
 
-    std::cout << "\n";
-
     if (!res) {
         LOG_ERR("%s: error during download. Status: %d\n", __func__, res ? res->status : -1);
         return false;

common/json-schema-to-grammar.cpp

@@ -305,8 +305,9 @@ static std::string format_literal(const std::string & literal) {
 
 std::string gbnf_format_literal(const std::string & literal) { return format_literal(literal); }
 
-class SchemaConverter {
+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;
@@ -729,7 +730,7 @@ private:
     }
 
 public:
-    SchemaConverter(
+    common_schema_converter(
         const std::function<json(const std::string &)> & fetch_json,
         bool dotall)
           : _fetch_json(fetch_json), _dotall(dotall)
@@ -990,6 +991,134 @@ 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(nlohmann::ordered_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 nlohmann::ordered_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 json & schema, bool force_gbnf) {
 #ifdef LLAMA_USE_LLGUIDANCE
     if (!force_gbnf) {
@@ -1006,7 +1135,7 @@ std::string json_schema_to_grammar(const json & schema, bool force_gbnf) {
 }
 
 std::string build_grammar(const std::function<void(const common_grammar_builder &)> & cb, const common_grammar_options & options) {
-    SchemaConverter converter([&](const std::string &) { return json(); }, options.dotall);
+    common_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);

common/json-schema-to-grammar.h

@@ -3,11 +3,31 @@
 #include <nlohmann/json_fwd.hpp>
 
 #include <functional>
+#include <memory>
 #include <string>
 
 std::string json_schema_to_grammar(const nlohmann::ordered_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(nlohmann::ordered_json & schema);
+    bool resolves_to_string(const nlohmann::ordered_json & schema);
+};
+
 struct common_grammar_builder {
     std::function<std::string(const std::string &, const std::string &)> add_rule;
     std::function<std::string(const std::string &, const nlohmann::ordered_json &)> add_schema;

common/log.cpp

@@ -420,6 +420,11 @@ void common_log_set_timestamps(struct common_log * log, bool timestamps) {
     log->set_timestamps(timestamps);
 }
 
+void common_log_flush(struct common_log * log) {
+    log->pause();
+    log->resume();
+}
+
 static int common_get_verbosity(enum ggml_log_level level) {
     switch (level) {
         case GGML_LOG_LEVEL_DEBUG: return LOG_LEVEL_DEBUG;

common/log.h

@@ -84,6 +84,7 @@ void common_log_set_file      (struct common_log * log, const char * file); // n
 void common_log_set_colors    (struct common_log * log, log_colors colors); // not thread-safe
 void common_log_set_prefix    (struct common_log * log, bool prefix);       // whether to output prefix to each log
 void common_log_set_timestamps(struct common_log * log, bool timestamps);   // whether to output timestamps in the prefix
+void common_log_flush         (struct common_log * log);                    // flush all pending log messages
 
 // helper macros for logging
 // use these to avoid computing log arguments if the verbosity of the log is higher than the threshold

common/peg-parser.cpp

@@ -425,7 +425,7 @@ struct parser_executor {
 
         if (result.need_more_input()) {
             // Propagate - need to know what child would match before negating
-            return result;
+            return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos);
         }
 
         // Child failed, so negation succeeds

common/preset.cpp

@@ -0,0 +1,398 @@
+#include "arg.h"
+#include "preset.h"
+#include "peg-parser.h"
+#include "log.h"
+#include "download.h"
+
+#include <fstream>
+#include <sstream>
+#include <filesystem>
+
+static std::string rm_leading_dashes(const std::string & str) {
+    size_t pos = 0;
+    while (pos < str.size() && str[pos] == '-') {
+        ++pos;
+    }
+    return str.substr(pos);
+}
+
+std::vector<std::string> common_preset::to_args(const std::string & bin_path) const {
+    std::vector<std::string> args;
+
+    if (!bin_path.empty()) {
+        args.push_back(bin_path);
+    }
+
+    for (const auto & [opt, value] : options) {
+        if (opt.is_preset_only) {
+            continue; // skip preset-only options (they are not CLI args)
+        }
+
+        // use the last arg as the main arg (i.e. --long-form)
+        args.push_back(opt.args.back());
+
+        // handle value(s)
+        if (opt.value_hint == nullptr && opt.value_hint_2 == nullptr) {
+            // flag option, no value
+            if (common_arg_utils::is_falsey(value)) {
+                // use negative arg if available
+                if (!opt.args_neg.empty()) {
+                    args.back() = opt.args_neg.back();
+                } else {
+                    // otherwise, skip the flag
+                    // TODO: maybe throw an error instead?
+                    args.pop_back();
+                }
+            }
+        }
+        if (opt.value_hint != nullptr) {
+            // single value
+            args.push_back(value);
+        }
+        if (opt.value_hint != nullptr && opt.value_hint_2 != nullptr) {
+            throw std::runtime_error(string_format(
+                "common_preset::to_args(): option '%s' has two values, which is not supported yet",
+                opt.args.back()
+            ));
+        }
+    }
+
+    return args;
+}
+
+std::string common_preset::to_ini() const {
+    std::ostringstream ss;
+
+    ss << "[" << name << "]\n";
+    for (const auto & [opt, value] : options) {
+        auto espaced_value = value;
+        string_replace_all(espaced_value, "\n", "\\\n");
+        ss << rm_leading_dashes(opt.args.back()) << " = ";
+        ss << espaced_value << "\n";
+    }
+    ss << "\n";
+
+    return ss.str();
+}
+
+void common_preset::set_option(const common_preset_context & ctx, const std::string & env, const std::string & value) {
+    // try if option exists, update it
+    for (auto & [opt, val] : options) {
+        if (opt.env && env == opt.env) {
+            val = value;
+            return;
+        }
+    }
+    // if option does not exist, we need to add it
+    if (ctx.key_to_opt.find(env) == ctx.key_to_opt.end()) {
+        throw std::runtime_error(string_format(
+            "%s: option with env '%s' not found in ctx_params",
+            __func__, env.c_str()
+        ));
+    }
+    options[ctx.key_to_opt.at(env)] = value;
+}
+
+void common_preset::unset_option(const std::string & env) {
+    for (auto it = options.begin(); it != options.end(); ) {
+        const common_arg & opt = it->first;
+        if (opt.env && env == opt.env) {
+            it = options.erase(it);
+            return;
+        } else {
+            ++it;
+        }
+    }
+}
+
+bool common_preset::get_option(const std::string & env, std::string & value) const {
+    for (const auto & [opt, val] : options) {
+        if (opt.env && env == opt.env) {
+            value = val;
+            return true;
+        }
+    }
+    return false;
+}
+
+void common_preset::merge(const common_preset & other) {
+    for (const auto & [opt, val] : other.options) {
+        options[opt] = val; // overwrite existing options
+    }
+}
+
+static std::map<std::string, std::map<std::string, std::string>> parse_ini_from_file(const std::string & path) {
+    std::map<std::string, std::map<std::string, std::string>> parsed;
+
+    if (!std::filesystem::exists(path)) {
+        throw std::runtime_error("preset file does not exist: " + path);
+    }
+
+    std::ifstream file(path);
+    if (!file.good()) {
+        throw std::runtime_error("failed to open server preset file: " + path);
+    }
+
+    std::string contents((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
+
+    static const auto parser = build_peg_parser([](auto & p) {
+        // newline ::= "\r\n" / "\n" / "\r"
+        auto newline = p.rule("newline", p.literal("\r\n") | p.literal("\n") | p.literal("\r"));
+
+        // ws ::= [ \t]*
+        auto ws = p.rule("ws", p.chars("[ \t]", 0, -1));
+
+        // comment ::= [;#] (!newline .)*
+        auto comment = p.rule("comment", p.chars("[;#]", 1, 1) + p.zero_or_more(p.negate(newline) + p.any()));
+
+        // eol ::= ws comment? (newline / EOF)
+        auto eol = p.rule("eol", ws + p.optional(comment) + (newline | p.end()));
+
+        // ident ::= [a-zA-Z_] [a-zA-Z0-9_.-]*
+        auto ident = p.rule("ident", p.chars("[a-zA-Z_]", 1, 1) + p.chars("[a-zA-Z0-9_.-]", 0, -1));
+
+        // value ::= (!eol-start .)*
+        auto eol_start = p.rule("eol-start", ws + (p.chars("[;#]", 1, 1) | newline | p.end()));
+        auto value = p.rule("value", p.zero_or_more(p.negate(eol_start) + p.any()));
+
+        // header-line ::= "[" ws ident ws "]" eol
+        auto header_line = p.rule("header-line", "[" + ws + p.tag("section-name", p.chars("[^]]")) + ws + "]" + eol);
+
+        // kv-line ::= ident ws "=" ws value eol
+        auto kv_line = p.rule("kv-line", p.tag("key", ident) + ws + "=" + ws + p.tag("value", value) + eol);
+
+        // comment-line ::= ws comment (newline / EOF)
+        auto comment_line = p.rule("comment-line", ws + comment + (newline | p.end()));
+
+        // blank-line ::= ws (newline / EOF)
+        auto blank_line = p.rule("blank-line", ws + (newline | p.end()));
+
+        // line ::= header-line / kv-line / comment-line / blank-line
+        auto line = p.rule("line", header_line | kv_line | comment_line | blank_line);
+
+        // ini ::= line* EOF
+        auto ini = p.rule("ini", p.zero_or_more(line) + p.end());
+
+        return ini;
+    });
+
+    common_peg_parse_context ctx(contents);
+    const auto result = parser.parse(ctx);
+    if (!result.success()) {
+        throw std::runtime_error("failed to parse server config file: " + path);
+    }
+
+    std::string current_section = COMMON_PRESET_DEFAULT_NAME;
+    std::string current_key;
+
+    ctx.ast.visit(result, [&](const auto & node) {
+        if (node.tag == "section-name") {
+            const std::string section = std::string(node.text);
+            current_section = section;
+            parsed[current_section] = {};
+        } else if (node.tag == "key") {
+            const std::string key = std::string(node.text);
+            current_key = key;
+        } else if (node.tag == "value" && !current_key.empty() && !current_section.empty()) {
+            parsed[current_section][current_key] = std::string(node.text);
+            current_key.clear();
+        }
+    });
+
+    return parsed;
+}
+
+static std::map<std::string, common_arg> get_map_key_opt(common_params_context & ctx_params) {
+    std::map<std::string, common_arg> mapping;
+    for (const auto & opt : ctx_params.options) {
+        for (const auto & env : opt.get_env()) {
+            mapping[env] = opt;
+        }
+        for (const auto & arg : opt.get_args()) {
+            mapping[rm_leading_dashes(arg)] = opt;
+        }
+    }
+    return mapping;
+}
+
+static bool is_bool_arg(const common_arg & arg) {
+    return !arg.args_neg.empty();
+}
+
+static std::string parse_bool_arg(const common_arg & arg, const std::string & key, const std::string & value) {
+    // if this is a negated arg, we need to reverse the value
+    for (const auto & neg_arg : arg.args_neg) {
+        if (rm_leading_dashes(neg_arg) == key) {
+            return common_arg_utils::is_truthy(value) ? "false" : "true";
+        }
+    }
+    // otherwise, not negated
+    return value;
+}
+
+common_preset_context::common_preset_context(llama_example ex)
+        : ctx_params(common_params_parser_init(default_params, ex)) {
+    common_params_add_preset_options(ctx_params.options);
+    key_to_opt = get_map_key_opt(ctx_params);
+}
+
+common_presets common_preset_context::load_from_ini(const std::string & path, common_preset & global) const {
+    common_presets out;
+    auto ini_data = parse_ini_from_file(path);
+
+    for (auto section : ini_data) {
+        common_preset preset;
+        if (section.first.empty()) {
+            preset.name = COMMON_PRESET_DEFAULT_NAME;
+        } else {
+            preset.name = section.first;
+        }
+        LOG_DBG("loading preset: %s\n", preset.name.c_str());
+        for (const auto & [key, value] : section.second) {
+            LOG_DBG("option: %s = %s\n", key.c_str(), value.c_str());
+            if (key_to_opt.find(key) != key_to_opt.end()) {
+                const auto & opt = key_to_opt.at(key);
+                if (is_bool_arg(opt)) {
+                    preset.options[opt] = parse_bool_arg(opt, key, value);
+                } else {
+                    preset.options[opt] = value;
+                }
+                LOG_DBG("accepted option: %s = %s\n", key.c_str(), preset.options[opt].c_str());
+            } else {
+                // TODO: maybe warn about unknown key?
+            }
+        }
+
+        if (preset.name == "*") {
+            // handle global preset
+            global = preset;
+        } else {
+            out[preset.name] = preset;
+        }
+    }
+
+    return out;
+}
+
+common_presets common_preset_context::load_from_cache() const {
+    common_presets out;
+
+    auto cached_models = common_list_cached_models();
+    for (const auto & model : cached_models) {
+        common_preset preset;
+        preset.name = model.to_string();
+        preset.set_option(*this, "LLAMA_ARG_HF_REPO", model.to_string());
+        out[preset.name] = preset;
+    }
+
+    return out;
+}
+
+struct local_model {
+    std::string name;
+    std::string path;
+    std::string path_mmproj;
+};
+
+common_presets common_preset_context::load_from_models_dir(const std::string & models_dir) const {
+    if (!std::filesystem::exists(models_dir) || !std::filesystem::is_directory(models_dir)) {
+        throw std::runtime_error(string_format("error: '%s' does not exist or is not a directory\n", models_dir.c_str()));
+    }
+
+    std::vector<local_model> models;
+    auto scan_subdir = [&models](const std::string & subdir_path, const std::string & name) {
+        auto files = fs_list(subdir_path, false);
+        common_file_info model_file;
+        common_file_info first_shard_file;
+        common_file_info mmproj_file;
+        for (const auto & file : files) {
+            if (string_ends_with(file.name, ".gguf")) {
+                if (file.name.find("mmproj") != std::string::npos) {
+                    mmproj_file = file;
+                } else if (file.name.find("-00001-of-") != std::string::npos) {
+                    first_shard_file = file;
+                } else {
+                    model_file = file;
+                }
+            }
+        }
+        // single file model
+        local_model model{
+            /* name        */ name,
+            /* path        */ first_shard_file.path.empty() ? model_file.path : first_shard_file.path,
+            /* path_mmproj */ mmproj_file.path // can be empty
+        };
+        if (!model.path.empty()) {
+            models.push_back(model);
+        }
+    };
+
+    auto files = fs_list(models_dir, true);
+    for (const auto & file : files) {
+        if (file.is_dir) {
+            scan_subdir(file.path, file.name);
+        } else if (string_ends_with(file.name, ".gguf")) {
+            // single file model
+            std::string name = file.name;
+            string_replace_all(name, ".gguf", "");
+            local_model model{
+                /* name        */ name,
+                /* path        */ file.path,
+                /* path_mmproj */ ""
+            };
+            models.push_back(model);
+        }
+    }
+
+    // convert local models to presets
+    common_presets out;
+    for (const auto & model : models) {
+        common_preset preset;
+        preset.name = model.name;
+        preset.set_option(*this, "LLAMA_ARG_MODEL", model.path);
+        if (!model.path_mmproj.empty()) {
+            preset.set_option(*this, "LLAMA_ARG_MMPROJ", model.path_mmproj);
+        }
+        out[preset.name] = preset;
+    }
+
+    return out;
+}
+
+common_preset common_preset_context::load_from_args(int argc, char ** argv) const {
+    common_preset preset;
+    preset.name = COMMON_PRESET_DEFAULT_NAME;
+
+    bool ok = common_params_to_map(argc, argv, ctx_params.ex, preset.options);
+    if (!ok) {
+        throw std::runtime_error("failed to parse CLI arguments into preset");
+    }
+
+    return preset;
+}
+
+common_presets common_preset_context::cascade(const common_presets & base, const common_presets & added) const {
+    common_presets out = base; // copy
+    for (const auto & [name, preset_added] : added) {
+        if (out.find(name) != out.end()) {
+            // if exists, merge
+            common_preset & target = out[name];
+            target.merge(preset_added);
+        } else {
+            // otherwise, add directly
+            out[name] = preset_added;
+        }
+    }
+    return out;
+}
+
+common_presets common_preset_context::cascade(const common_preset & base, const common_presets & presets) const {
+    common_presets out;
+    for (const auto & [name, preset] : presets) {
+        common_preset tmp = base; // copy
+        tmp.name = name;
+        tmp.merge(preset);
+        out[name] = std::move(tmp);
+    }
+    return out;
+}

common/preset.h

@@ -0,0 +1,74 @@
+#pragma once
+
+#include "common.h"
+#include "arg.h"
+
+#include <string>
+#include <vector>
+#include <map>
+
+//
+// INI preset parser and writer
+//
+
+constexpr const char * COMMON_PRESET_DEFAULT_NAME = "default";
+
+struct common_preset_context;
+
+struct common_preset {
+    std::string name;
+
+    // options are stored as common_arg to string mapping, representing CLI arg and its value
+    std::map<common_arg, std::string> options;
+
+    // convert preset to CLI argument list
+    std::vector<std::string> to_args(const std::string & bin_path = "") const;
+
+    // convert preset to INI format string
+    std::string to_ini() const;
+
+    // TODO: maybe implement to_env() if needed
+
+    // modify preset options where argument is identified by its env variable
+    void set_option(const common_preset_context & ctx, const std::string & env, const std::string & value);
+
+    // unset option by its env variable
+    void unset_option(const std::string & env);
+
+    // get option value by its env variable, return false if not found
+    bool get_option(const std::string & env, std::string & value) const;
+
+    // merge another preset into this one, overwriting existing options
+    void merge(const common_preset & other);
+};
+
+// interface for multiple presets in one file
+using common_presets = std::map<std::string, common_preset>;
+
+// context for loading and editing presets
+struct common_preset_context {
+    common_params default_params; // unused for now
+    common_params_context ctx_params;
+    std::map<std::string, common_arg> key_to_opt;
+    common_preset_context(llama_example ex);
+
+    // load presets from INI file
+    common_presets load_from_ini(const std::string & path, common_preset & global) const;
+
+    // generate presets from cached models
+    common_presets load_from_cache() const;
+
+    // generate presets from local models directory
+    // for the directory structure, see "Using multiple models" in server/README.md
+    common_presets load_from_models_dir(const std::string & models_dir) const;
+
+    // generate one preset from CLI arguments
+    common_preset load_from_args(int argc, char ** argv) const;
+
+    // cascade multiple presets if exist on both: base < added
+    // if preset does not exist in base, it will be added without modification
+    common_presets cascade(const common_presets & base, const common_presets & added) const;
+
+    // apply presets over a base preset (same idea as CSS cascading)
+    common_presets cascade(const common_preset & base, const common_presets & presets) const;
+};

common/sampling.cpp

@@ -116,7 +116,6 @@ struct common_sampler {
     void reset() {
         prev.clear();
 
-        llama_sampler_reset(grmr);
         llama_sampler_reset(chain);
     }
 
@@ -167,7 +166,11 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, co
 
     lparams.no_perf = params.no_perf;
 
-    struct llama_sampler * grmr;
+    llama_sampler * grmr = nullptr;
+    llama_sampler * chain = llama_sampler_chain_init(lparams);
+
+    std::vector<llama_sampler *> samplers;
+
     if (params.grammar.compare(0, 11, "%llguidance") == 0) {
 #ifdef LLAMA_USE_LLGUIDANCE
         grmr = llama_sampler_init_llg(vocab, "lark", params.grammar.c_str());
@@ -217,30 +220,20 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, co
             trigger_patterns_c.push_back(regex.c_str());
         }
 
-        grmr = params.grammar_lazy
-             ? llama_sampler_init_grammar_lazy_patterns(vocab, params.grammar.c_str(), "root",
-                                                        trigger_patterns_c.data(), trigger_patterns_c.size(),
-                                                        trigger_tokens.data(), trigger_tokens.size())
-             :      llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root");
-        if (!grmr) {
-            return nullptr;
+        if (!params.grammar.empty()) {
+             if (params.grammar_lazy) {
+                 grmr = llama_sampler_init_grammar_lazy_patterns(vocab, params.grammar.c_str(), "root",
+                         trigger_patterns_c.data(), trigger_patterns_c.size(),
+                         trigger_tokens.data(), trigger_tokens.size());
+             } else {
+                 grmr = llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root");
+             }
         }
     }
 
-    auto * result = new common_sampler {
-        /* .params = */ params,
-        /* .grmr   = */ grmr,
-        /* .chain  = */ llama_sampler_chain_init(lparams),
-        /* .prev   = */ ring_buffer<llama_token>(std::max(32, params.n_prev)),
-        /* .cur    = */ {},
-        /* .cur_p  = */ {},
-    };
-
-    llama_sampler_chain_add(result->chain,
-            llama_sampler_init_logit_bias(
-                llama_vocab_n_tokens(vocab),
-                params.logit_bias.size(),
-                params.logit_bias.data()));
+    if (params.has_logit_bias()) {
+        samplers.push_back(llama_sampler_init_logit_bias(llama_vocab_n_tokens(vocab), params.logit_bias.size(), params.logit_bias.data()));
+    }
 
     if (params.mirostat == 0) {
         for (const auto & cnstr : params.samplers) {
@@ -253,58 +246,71 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, co
                             c_breakers.push_back(str.c_str());
                         }
 
-                        llama_sampler_chain_add(result->chain, llama_sampler_init_dry      (vocab, llama_model_n_ctx_train(model), params.dry_multiplier, params.dry_base, params.dry_allowed_length, params.dry_penalty_last_n, c_breakers.data(), c_breakers.size()));
+                        samplers.push_back(llama_sampler_init_dry    (vocab, llama_model_n_ctx_train(model), params.dry_multiplier, params.dry_base, params.dry_allowed_length, params.dry_penalty_last_n, c_breakers.data(), c_breakers.size()));
                     }
                     break;
                 case COMMON_SAMPLER_TYPE_TOP_K:
-                    llama_sampler_chain_add(result->chain, llama_sampler_init_top_k       (params.top_k));
+                    samplers.push_back(llama_sampler_init_top_k      (params.top_k));
                     break;
                 case COMMON_SAMPLER_TYPE_TOP_P:
-                    llama_sampler_chain_add(result->chain, llama_sampler_init_top_p       (params.top_p, params.min_keep));
+                    samplers.push_back(llama_sampler_init_top_p      (params.top_p, params.min_keep));
                     break;
                 case COMMON_SAMPLER_TYPE_TOP_N_SIGMA:
-                    llama_sampler_chain_add(result->chain, llama_sampler_init_top_n_sigma (params.top_n_sigma));
+                    samplers.push_back(llama_sampler_init_top_n_sigma(params.top_n_sigma));
                     break;
                 case COMMON_SAMPLER_TYPE_MIN_P:
-                    llama_sampler_chain_add(result->chain, llama_sampler_init_min_p       (params.min_p, params.min_keep));
+                    samplers.push_back(llama_sampler_init_min_p      (params.min_p, params.min_keep));
                     break;
                 case COMMON_SAMPLER_TYPE_XTC:
-                    llama_sampler_chain_add(result->chain, llama_sampler_init_xtc         (params.xtc_probability, params.xtc_threshold, params.min_keep, params.seed));
+                    samplers.push_back(llama_sampler_init_xtc        (params.xtc_probability, params.xtc_threshold, params.min_keep, params.seed));
                     break;
                 case COMMON_SAMPLER_TYPE_TYPICAL_P:
-                    llama_sampler_chain_add(result->chain, llama_sampler_init_typical     (params.typ_p, params.min_keep));
+                    samplers.push_back(llama_sampler_init_typical    (params.typ_p, params.min_keep));
                     break;
                 case COMMON_SAMPLER_TYPE_TEMPERATURE:
-                    llama_sampler_chain_add(result->chain, llama_sampler_init_temp_ext    (params.temp, params.dynatemp_range, params.dynatemp_exponent));
+                    samplers.push_back(llama_sampler_init_temp_ext   (params.temp, params.dynatemp_range, params.dynatemp_exponent));
                     break;
                 case COMMON_SAMPLER_TYPE_INFILL:
-                    llama_sampler_chain_add(result->chain, llama_sampler_init_infill      (vocab));
+                    samplers.push_back(llama_sampler_init_infill     (vocab));
                     break;
                 case COMMON_SAMPLER_TYPE_PENALTIES:
-                    llama_sampler_chain_add(result->chain, llama_sampler_init_penalties   (params.penalty_last_n, params.penalty_repeat, params.penalty_freq, params.penalty_present));
+                    samplers.push_back(llama_sampler_init_penalties  (params.penalty_last_n, params.penalty_repeat, params.penalty_freq, params.penalty_present));
                     break;
                 default:
                     GGML_ASSERT(false && "unknown sampler type");
             }
         }
-        llama_sampler_chain_add(result->chain, llama_sampler_init_dist(params.seed));
+
+        samplers.push_back(llama_sampler_init_dist(params.seed));
     } else if (params.mirostat == 1) {
-        llama_sampler_chain_add(result->chain, llama_sampler_init_temp(params.temp));
-        llama_sampler_chain_add(result->chain, llama_sampler_init_mirostat(llama_vocab_n_tokens(vocab), params.seed, params.mirostat_tau, params.mirostat_eta, 100));
+        samplers.push_back(llama_sampler_init_temp(params.temp));
+        samplers.push_back(llama_sampler_init_mirostat(llama_vocab_n_tokens(vocab), params.seed, params.mirostat_tau, params.mirostat_eta, 100));
     } else if (params.mirostat == 2) {
-        llama_sampler_chain_add(result->chain, llama_sampler_init_temp(params.temp));
-        llama_sampler_chain_add(result->chain, llama_sampler_init_mirostat_v2(params.seed, params.mirostat_tau, params.mirostat_eta));
+        samplers.push_back(llama_sampler_init_temp(params.temp));
+        samplers.push_back(llama_sampler_init_mirostat_v2(params.seed, params.mirostat_tau, params.mirostat_eta));
     } else {
         GGML_ASSERT(false && "unknown mirostat version");
     }
 
+    for (auto * smpl : samplers) {
+        llama_sampler_chain_add(chain, smpl);
+    }
+
+    auto * result = new common_sampler {
+        /* .params  = */ params,
+        /* .grmr    = */ grmr,
+        /* .chain   = */ chain,
+        /* .prev    = */ ring_buffer<llama_token>(std::max(32, params.n_prev)),
+        /* .cur     = */ {},
+        /* .cur_p   = */ {},
+    };
+
     return result;
 }
 
 void common_sampler_free(struct common_sampler * gsmpl) {
     if (gsmpl) {
         llama_sampler_free(gsmpl->grmr);
-
         llama_sampler_free(gsmpl->chain);
 
         delete gsmpl;
@@ -314,7 +320,7 @@ void common_sampler_free(struct common_sampler * gsmpl) {
 void common_sampler_accept(struct common_sampler * gsmpl, llama_token token, bool accept_grammar) {
     const auto tm = gsmpl->tm();
 
-    if (accept_grammar) {
+    if (gsmpl->grmr && accept_grammar) {
         llama_sampler_accept(gsmpl->grmr, token);
     }
 
@@ -329,12 +335,12 @@ void common_sampler_reset(struct common_sampler * gsmpl) {
 
 struct common_sampler * common_sampler_clone(common_sampler * gsmpl) {
     return new common_sampler {
-        /* .params = */ gsmpl->params,
-        /* .grmr   = */ llama_sampler_clone(gsmpl->grmr),
-        /* .chain  = */ llama_sampler_clone(gsmpl->chain),
-        /* .prev   = */ gsmpl->prev,
-        /* .cur    = */ gsmpl->cur,
-        /* .cur_p  = */ gsmpl->cur_p,
+        /* .params  = */ gsmpl->params,
+        /* .grmr    = */ llama_sampler_clone(gsmpl->grmr),
+        /* .chain   = */ llama_sampler_clone(gsmpl->chain),
+        /* .prev    = */ gsmpl->prev,
+        /* .cur     = */ gsmpl->cur,
+        /* .cur_p   = */ gsmpl->cur_p,
     };
 }
 
@@ -383,33 +389,37 @@ void common_perf_print(const struct llama_context * ctx, const struct common_sam
     }
 }
 
+struct llama_sampler * common_sampler_get(const struct common_sampler * gsmpl) {
+    return gsmpl->chain;
+}
+
 llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_context * ctx, int idx, bool grammar_first) {
     llama_synchronize(ctx);
 
     // start measuring sampling time after the llama_context synchronization in order to not measure any ongoing async operations
     const auto tm = gsmpl->tm();
 
-    gsmpl->set_logits(ctx, idx);
+    llama_token id = LLAMA_TOKEN_NULL;
 
     auto & grmr  = gsmpl->grmr;
     auto & chain = gsmpl->chain;
     auto & cur_p = gsmpl->cur_p; // initialized by set_logits
 
+    gsmpl->set_logits(ctx, idx);
+
     if (grammar_first) {
         llama_sampler_apply(grmr, &cur_p);
     }
 
     llama_sampler_apply(chain, &cur_p);
 
-    GGML_ASSERT(cur_p.selected != -1 && "no selected token during sampling - check your sampling configuration");
-
-    const llama_token id = cur_p.data[cur_p.selected].id;
+    id = cur_p.data[cur_p.selected].id;
 
     if (grammar_first) {
         return id;
     }
 
-    // check if it the sampled token fits the grammar
+    // check if it the sampled token fits the grammar (grammar-based rejection sampling)
     {
         llama_token_data       single_token_data       = { id, 1.0f, 0.0f };
         llama_token_data_array single_token_data_array = { &single_token_data, 1, -1, false };
@@ -429,9 +439,11 @@ llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_co
     llama_sampler_apply(grmr,  &cur_p);
     llama_sampler_apply(chain, &cur_p);
 
-    GGML_ASSERT(cur_p.selected != -1 && "no selected token during re-sampling - check your sampling configuration");
+    GGML_ASSERT(cur_p.selected != -1 && "no selected token during sampling - check your sampling configuration");
 
-    return cur_p.data[cur_p.selected].id;
+    id = cur_p.data[cur_p.selected].id;
+
+    return id;
 }
 
 std::vector<llama_token> common_sampler_sample_and_accept_n(struct common_sampler * gsmpl, struct llama_context * ctx, const std::vector<int> & idxs, const llama_tokens & draft, bool grammar_first) {
@@ -515,7 +527,8 @@ std::string common_sampler_print(const struct common_sampler * gsmpl) {
 
     for (int i = 0; i < llama_sampler_chain_n(gsmpl->chain); i++) {
         const auto * smpl = llama_sampler_chain_get(gsmpl->chain, i);
-        result += std::string("-> ") + llama_sampler_name(smpl) + " ";
+        result += std::string("-> ");
+        result += std::string(llama_sampler_name(smpl)) + " ";
     }
 
     return result;

common/sampling.h

@@ -48,6 +48,8 @@ struct common_sampler * common_sampler_clone (struct common_sampler * gsmpl);
 // arguments can be nullptr to skip printing
 void common_perf_print(const struct llama_context * ctx, const struct common_sampler * gsmpl);
 
+struct llama_sampler * common_sampler_get(const struct common_sampler * gsmpl);
+
 // extended sampling implementation:
 //
 // - set logits
@@ -107,3 +109,9 @@ std::vector<enum common_sampler_type> common_sampler_types_from_chars(const std:
 
 llama_sampler * llama_sampler_init_llg(const llama_vocab * vocab,
                 const char * grammar_kind, const char * grammar_data);
+
+struct common_sampler_deleter {
+    void operator()(common_sampler * s) { common_sampler_free(s); }
+};
+
+typedef std::unique_ptr<common_sampler, common_sampler_deleter> common_sampler_ptr;

convert_hf_to_gguf_update.py

@@ -143,6 +143,7 @@ models = [
     {"name": "bailingmoe2",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/inclusionAI/Ling-mini-base-2.0", },
     {"name": "granite-docling",  "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/ibm-granite/granite-docling-258M", },
     {"name": "minimax-m2",       "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/MiniMaxAI/MiniMax-M2", },
+    {"name": "kormo",            "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/KORMo-Team/KORMo-tokenizer", },
 ]
 
 # some models are known to be broken upstream, so we will skip them as exceptions

docs/android.md

@@ -1,7 +1,27 @@
 
 # Android
 
-## Build on Android using Termux
+## Build GUI binding using Android Studio
+
+Import the `examples/llama.android` directory into Android Studio, then perform a Gradle sync and build the project.
+![Project imported into Android Studio](./android/imported-into-android-studio.jpg)
+
+This Android binding supports hardware acceleration up to `SME2` for **Arm** and `AMX` for **x86-64** CPUs on Android and ChromeOS devices.
+It automatically detects the host's hardware to load compatible kernels. As a result, it runs seamlessly on both the latest premium devices and older devices that may lack modern CPU features or have limited RAM, without requiring any manual configuration.
+
+A minimal Android app frontend is included to showcase the binding’s core functionalities:
+1.	**Parse GGUF metadata** via `GgufMetadataReader` from either a `ContentResolver` provided `Uri` from shared storage, or a local `File` from your app's private storage.
+2.	**Obtain a `InferenceEngine`** instance through the `AiChat` facade and load your selected model via its app-private file path.
+3.	**Send a raw user prompt** for automatic template formatting, prefill, and batch decoding. Then collect the generated tokens in a Kotlin `Flow`.
+
+For a production-ready experience that leverages advanced features such as system prompts and benchmarks, plus friendly UI features such as model management and Arm feature visualizer, check out [Arm AI Chat](https://play.google.com/store/apps/details?id=com.arm.aichat) on Google Play.
+This project is made possible through a collaborative effort by Arm's **CT-ML**, **CE-ML** and **STE** groups:
+
+| ![Home screen](https://naco-siren.github.io/ai-chat/policy/index/1-llm-starter-pack.png)  | ![System prompt](https://naco-siren.github.io/ai-chat/policy/index/5-system-prompt.png)  | !["Haiku"](https://naco-siren.github.io/ai-chat/policy/index/4-metrics.png)  |
+|:------------------------------------------------------:|:----------------------------------------------------:|:--------------------------------------------------------:|
+|                      Home screen                       |                    System prompt                     |                         "Haiku"                          |
+
+## Build CLI on Android using Termux
 
 [Termux](https://termux.dev/en/) is an Android terminal emulator and Linux environment app (no root required). As of writing, Termux is available experimentally in the Google Play Store; otherwise, it may be obtained directly from the project repo or on F-Droid.
 
@@ -32,7 +52,7 @@ To see what it might look like visually, here's an old demo of an interactive se
 
 https://user-images.githubusercontent.com/271616/225014776-1d567049-ad71-4ef2-b050-55b0b3b9274c.mp4
 
-## Cross-compile using Android NDK
+## Cross-compile CLI using Android NDK
 It's possible to build `llama.cpp` for Android on your host system via CMake and the Android NDK. If you are interested in this path, ensure you already have an environment prepared to cross-compile programs for Android (i.e., install the Android SDK). Note that, unlike desktop environments, the Android environment ships with a limited set of native libraries, and so only those libraries are available to CMake when building with the Android NDK (see: https://developer.android.com/ndk/guides/stable_apis.)
 
 Once you're ready and have cloned `llama.cpp`, invoke the following in the project directory:

docs/backend/SYCL.md

@@ -103,6 +103,8 @@ SYCL backend supports Intel GPU Family:
 - Intel Built-in Arc GPU
 - Intel iGPU in Core CPU (11th Generation Core CPU and newer, refer to [oneAPI supported GPU](https://www.intel.com/content/www/us/en/developer/articles/system-requirements/intel-oneapi-base-toolkit-system-requirements.html#inpage-nav-1-1)).
 
+On older Intel GPUs, you may try [OpenCL](/docs/backend/OPENCL.md) although the performance is not optimal, and some GPUs may not support OpenCL nor have any GPGPU capabilities.
+
 #### Verified devices
 
 | Intel GPU                     | Status  | Verified Model                        |

docs/backend/hexagon/CMakeUserPresets.json

@@ -22,6 +22,7 @@
             "GGML_LLAMAFILE":   "OFF",
             "GGML_OPENCL":      "ON",
             "GGML_HEXAGON":     "ON",
+            "GGML_HEXAGON_FP32_QUANTIZE_GROUP_SIZE": "128",
             "LLAMA_CURL":       "OFF"
         }
     },
@@ -36,6 +37,7 @@
             "GGML_LLAMAFILE":   "OFF",
             "GGML_OPENCL":      "ON",
             "GGML_HEXAGON":     "ON",
+            "GGML_HEXAGON_FP32_QUANTIZE_GROUP_SIZE": "128",
             "LLAMA_CURL":       "OFF"
         }
     },

docs/development/HOWTO-add-model.md

@@ -9,7 +9,8 @@ Adding a model requires few steps:
 After following these steps, you can open PR.
 
 Also, it is important to check that the examples and main ggml backends (CUDA, METAL, CPU) are working with the new architecture, especially:
-- [main](/tools/main/)
+- [cli](/tools/cli/)
+- [completion](/tools/completion/)
 - [imatrix](/tools/imatrix/)
 - [quantize](/tools/quantize/)
 - [server](/tools/server/)
@@ -96,7 +97,7 @@ The model params and tensors layout must be defined in `llama.cpp` source files:
 1. Define a new `llm_arch` enum value in `src/llama-arch.h`.
 2. In `src/llama-arch.cpp`:
     - Add the architecture name to the `LLM_ARCH_NAMES` map.
-    - Add the tensor mappings to the `LLM_TENSOR_NAMES` map.
+    - Add the list of model tensors to `llm_get_tensor_names` (you may also need to update `LLM_TENSOR_NAMES`)
 3. Add any non-standard metadata loading in the `llama_model_loader` constructor in `src/llama-model-loader.cpp`.
 4. If the model has a RoPE operation, add a case for the architecture in `llama_model_rope_type` function in `src/llama-model.cpp`.
 

docs/docker.md

@@ -7,9 +7,9 @@
 ## Images
 We have three Docker images available for this project:
 
-1. `ghcr.io/ggml-org/llama.cpp:full`: This image includes both the main executable file and the tools to convert LLaMA models into ggml and convert into 4-bit quantization. (platforms: `linux/amd64`, `linux/arm64`, `linux/s390x`)
-2. `ghcr.io/ggml-org/llama.cpp:light`: This image only includes the main executable file. (platforms: `linux/amd64`, `linux/arm64`, `linux/s390x`)
-3. `ghcr.io/ggml-org/llama.cpp:server`: This image only includes the server executable file. (platforms: `linux/amd64`, `linux/arm64`, `linux/s390x`)
+1. `ghcr.io/ggml-org/llama.cpp:full`: This image includes both the `llama-cli` and `llama-completion` executables and the tools to convert LLaMA models into ggml and convert into 4-bit quantization. (platforms: `linux/amd64`, `linux/arm64`, `linux/s390x`)
+2. `ghcr.io/ggml-org/llama.cpp:light`: This image only includes the `llama-cli` and `llama-completion` executables. (platforms: `linux/amd64`, `linux/arm64`, `linux/s390x`)
+3. `ghcr.io/ggml-org/llama.cpp:server`: This image only includes the `llama-server` executable. (platforms: `linux/amd64`, `linux/arm64`, `linux/s390x`)
 
 Additionally, there the following images, similar to the above:
 
@@ -44,21 +44,25 @@ docker run -v /path/to/models:/models ghcr.io/ggml-org/llama.cpp:full --all-in-o
 On completion, you are ready to play!
 
 ```bash
-docker run -v /path/to/models:/models ghcr.io/ggml-org/llama.cpp:full --run -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512
+docker run -v /path/to/models:/models ghcr.io/ggml-org/llama.cpp:full --run -m /models/7B/ggml-model-q4_0.gguf
+docker run -v /path/to/models:/models ghcr.io/ggml-org/llama.cpp:full --run-legacy -m /models/32B/ggml-model-q8_0.gguf -no-cnv -p "Building a mobile app can be done in 15 steps:" -n 512
 ```
 
 or with a light image:
 
 ```bash
-docker run -v /path/to/models:/models ghcr.io/ggml-org/llama.cpp:light -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512
+docker run -v /path/to/models:/models --entrypoint /app/llama-cli ghcr.io/ggml-org/llama.cpp:light -m /models/7B/ggml-model-q4_0.gguf
+docker run -v /path/to/models:/models --entrypoint /app/llama-completion ghcr.io/ggml-org/llama.cpp:light -m /models/32B/ggml-model-q8_0.gguf -no-cnv -p "Building a mobile app can be done in 15 steps:" -n 512
 ```
 
 or with a server image:
 
 ```bash
-docker run -v /path/to/models:/models -p 8000:8000 ghcr.io/ggml-org/llama.cpp:server -m /models/7B/ggml-model-q4_0.gguf --port 8000 --host 0.0.0.0 -n 512
+docker run -v /path/to/models:/models -p 8080:8080 ghcr.io/ggml-org/llama.cpp:server -m /models/7B/ggml-model-q4_0.gguf --port 8080 --host 0.0.0.0 -n 512
 ```
 
+In the above examples, `--entrypoint /app/llama-cli` is specified for clarity, but you can safely omit it since it's the default entrypoint in the container.
+
 ## Docker With CUDA
 
 Assuming one has the [nvidia-container-toolkit](https://github.com/NVIDIA/nvidia-container-toolkit) properly installed on Linux, or is using a GPU enabled cloud, `cuBLAS` should be accessible inside the container.
@@ -80,9 +84,9 @@ The defaults are:
 
 The resulting images, are essentially the same as the non-CUDA images:
 
-1. `local/llama.cpp:full-cuda`: This image includes both the main executable file and the tools to convert LLaMA models into ggml and convert into 4-bit quantization.
-2. `local/llama.cpp:light-cuda`: This image only includes the main executable file.
-3. `local/llama.cpp:server-cuda`: This image only includes the server executable file.
+1. `local/llama.cpp:full-cuda`: This image includes both the `llama-cli` and `llama-completion` executables and the tools to convert LLaMA models into ggml and convert into 4-bit quantization.
+2. `local/llama.cpp:light-cuda`: This image only includes the `llama-cli` and `llama-completion` executables.
+3. `local/llama.cpp:server-cuda`: This image only includes the `llama-server` executable.
 
 ## Usage
 
@@ -91,7 +95,7 @@ After building locally, Usage is similar to the non-CUDA examples, but you'll ne
 ```bash
 docker run --gpus all -v /path/to/models:/models local/llama.cpp:full-cuda --run -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
 docker run --gpus all -v /path/to/models:/models local/llama.cpp:light-cuda -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
-docker run --gpus all -v /path/to/models:/models local/llama.cpp:server-cuda -m /models/7B/ggml-model-q4_0.gguf --port 8000 --host 0.0.0.0 -n 512 --n-gpu-layers 1
+docker run --gpus all -v /path/to/models:/models local/llama.cpp:server-cuda -m /models/7B/ggml-model-q4_0.gguf --port 8080 --host 0.0.0.0 -n 512 --n-gpu-layers 1
 ```
 
 ## Docker With MUSA
@@ -114,9 +118,9 @@ The defaults are:
 
 The resulting images, are essentially the same as the non-MUSA images:
 
-1. `local/llama.cpp:full-musa`: This image includes both the main executable file and the tools to convert LLaMA models into ggml and convert into 4-bit quantization.
-2. `local/llama.cpp:light-musa`: This image only includes the main executable file.
-3. `local/llama.cpp:server-musa`: This image only includes the server executable file.
+1. `local/llama.cpp:full-musa`: This image includes both the `llama-cli` and `llama-completion` executables and the tools to convert LLaMA models into ggml and convert into 4-bit quantization.
+2. `local/llama.cpp:light-musa`: This image only includes the `llama-cli` and `llama-completion` executables.
+3. `local/llama.cpp:server-musa`: This image only includes the `llama-server` executable.
 
 ## Usage
 
@@ -125,5 +129,5 @@ After building locally, Usage is similar to the non-MUSA examples, but you'll ne
 ```bash
 docker run -v /path/to/models:/models local/llama.cpp:full-musa --run -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
 docker run -v /path/to/models:/models local/llama.cpp:light-musa -m /models/7B/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
-docker run -v /path/to/models:/models local/llama.cpp:server-musa -m /models/7B/ggml-model-q4_0.gguf --port 8000 --host 0.0.0.0 -n 512 --n-gpu-layers 1
+docker run -v /path/to/models:/models local/llama.cpp:server-musa -m /models/7B/ggml-model-q4_0.gguf --port 8080 --host 0.0.0.0 -n 512 --n-gpu-layers 1
 ```

docs/ops.md

@@ -16,14 +16,14 @@ Legend:
 |-----------|------|------|------|------|------|------|------|------|------|------|------|
 |                              ABS | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                              ACC | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
-|                              ADD | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ |
+|                              ADD | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                             ADD1 | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
-|                           ADD_ID | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
+|                           ADD_ID | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                           ARANGE | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                           ARGMAX | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
-|                          ARGSORT | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
+|                          ARGSORT | ❌ | ✅ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ❌ | ❌ | ❌ |
 |                             CEIL | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ |
-|                            CLAMP | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ | ❌ |
+|                            CLAMP | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ❌ | ❌ | ❌ |
 |                           CONCAT | ❌ | ✅ | ✅ | 🟡 | ✅ | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                             CONT | ❌ | 🟡 | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ❌ | ❌ |
 |                          CONV_2D | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ❌ |
@@ -31,20 +31,21 @@ Legend:
 |                          CONV_3D | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |                CONV_TRANSPOSE_1D | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                CONV_TRANSPOSE_2D | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
-|                              COS | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ |
+|                              COS | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ |
 |                      COUNT_EQUAL | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                              CPY | ❌ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ |
 |               CROSS_ENTROPY_LOSS | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |          CROSS_ENTROPY_LOSS_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
-|                           CUMSUM | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
+|                           CUMSUM | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
+|                             DIAG | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |                    DIAG_MASK_INF | ❌ | ✅ | ✅ | ✅ | ❌ | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ |
-|                              DIV | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ |
+|                              DIV | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                              DUP | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                              ELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ |
 |                              EXP | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                            EXPM1 | ❌ | ❌ | ✅ | 🟡 | 🟡 | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
-|                             FILL | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
-|                   FLASH_ATTN_EXT | ❌ | 🟡 | ✅ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ |
+|                             FILL | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
+|                   FLASH_ATTN_EXT | ❌ | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | ❌ | 🟡 | ❌ | ❌ | ❌ |
 |                            FLOOR | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ |
 |                GATED_LINEAR_ATTN | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ |
 |                            GEGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ |
@@ -63,9 +64,9 @@ Legend:
 |                        IM2COL_3D | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
 |                          L2_NORM | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                       LEAKY_RELU | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ |
-|                              LOG | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | ✅ | ❌ | ❌ | ❌ |
-|                             MEAN | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
-|                              MUL | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ |
+|                              LOG | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
+|                             MEAN | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
+|                              MUL | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                          MUL_MAT | 🟡 | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 |
 |                       MUL_MAT_ID | ❌ | 🟡 | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ❌ | ❌ | ❌ |
 |                              NEG | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
@@ -74,7 +75,7 @@ Legend:
 |                   OPT_STEP_ADAMW | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
 |                     OPT_STEP_SGD | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
 |                         OUT_PROD | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | ❌ |
-|                              PAD | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ | ❌ |
+|                              PAD | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | ✅ | ❌ | ❌ | ❌ |
 |                   PAD_REFLECT_1D | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ |
 |                          POOL_2D | ❌ | 🟡 | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                            REGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ |
@@ -83,7 +84,7 @@ Legend:
 |                      REPEAT_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                         RMS_NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                    RMS_NORM_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
-|                 RMS_NORM_MUL_ADD | ❌ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
+|                 RMS_NORM_MUL_ADD | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |                             ROLL | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                             ROPE | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                        ROPE_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
@@ -97,26 +98,26 @@ Legend:
 |                          SIGMOID | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                             SILU | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                        SILU_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
-|                              SIN | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ |
+|                              SIN | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ |
 |                          SOFTCAP | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |                         SOFTPLUS | ❌ | ❌ | ✅ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ |
 |                         SOFT_MAX | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                    SOFT_MAX_BACK | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ✅ | ❌ | ❌ | ❌ |
-|                        SOLVE_TRI | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ |
-|                              SQR | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ |
-|                             SQRT | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ |
-|                         SSM_CONV | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
+|                        SOLVE_TRI | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ |
+|                              SQR | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | ❌ | ❌ |
+|                             SQRT | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | ❌ | ❌ |
+|                         SSM_CONV | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                         SSM_SCAN | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ |
 |                             STEP | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
-|                              SUB | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ |
+|                              SUB | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                              SUM | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ |
-|                         SUM_ROWS | ❌ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ | ❌ |
+|                         SUM_ROWS | ❌ | ✅ | ✅ | 🟡 | ✅ | 🟡 | 🟡 | ✅ | ❌ | ❌ | ❌ |
 |                           SWIGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ |
-|                       SWIGLU_OAI | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | 🟡 | ✅ | ❌ | ❌ |
+|                       SWIGLU_OAI | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                             TANH | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |               TIMESTEP_EMBEDDING | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
-|                            TOP_K | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ |
-|                              TRI | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
+|                            TOP_K | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ |
+|                              TRI | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
 |                            TRUNC | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ |
-|                          UPSCALE | ❌ | 🟡 | ✅ | ✅ | 🟡 | ✅ | 🟡 | 🟡 | ❌ | ❌ | ❌ |
+|                          UPSCALE | ❌ | 🟡 | ✅ | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ | ❌ |
 |                            XIELU | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ |

docs/ops/CPU.csv

@@ -4964,6 +4964,7 @@
 "CPU","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[3,1,1,1],s0=1,p0=0,d0=1","support","1","yes","CPU"
 "CPU","CONV_TRANSPOSE_2D","ne_input=[3,2,3,1],ne_kernel=[2,2,1,3],stride=1","support","1","yes","CPU"
 "CPU","CONV_TRANSPOSE_2D","ne_input=[10,10,9,1],ne_kernel=[3,3,1,9],stride=2","support","1","yes","CPU"
+"CPU","CONV_TRANSPOSE_2D","ne_input=[129,63,35,1],ne_kernel=[3,3,48,35],stride=1","support","1","yes","CPU"
 "CPU","COUNT_EQUAL","type=f32,ne=[4,500,1,1]","support","1","yes","CPU"
 "CPU","COUNT_EQUAL","type=f32,ne=[4,5000,1,1]","support","1","yes","CPU"
 "CPU","ARGMAX","type=f32,ne=[32,1,1,1]","support","1","yes","CPU"
@@ -5419,17 +5420,45 @@
 "CPU","CPY","type_src=f16,type_dst=f16,ne=[256,4,1,1],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=1","support","1","yes","CPU"
 "CPU","CPY","type_src=f32,type_dst=f32,ne=[256,4,1,1],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=1","support","1","yes","CPU"
 "CPU","CPY","type_src=bf16,type_dst=bf16,ne=[256,4,1,1],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=1","support","1","yes","CPU"
+"CPU","CPY","type_src=i32,type_dst=i32,ne=[256,4,1,1],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=1","support","1","yes","CPU"
+"CPU","CPY","type_src=i32,type_dst=i32,ne=[256,1,4,1],permute_src=[1,2,0,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","CPU"
 "CPU","CPY","type_src=f32,type_dst=f32,ne=[256,1,4,1],permute_src=[1,2,0,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","CPU"
-"CPU","CONT","type=f32,ne=[10,10,10,1]","support","1","yes","CPU"
-"CPU","CONT","type=f32,ne=[2,1,1,1]","support","1","yes","CPU"
-"CPU","CONT","type=f32,ne=[2,1,3,5]","support","1","yes","CPU"
-"CPU","CONT","type=f32,ne=[2,3,5,7]","support","1","yes","CPU"
-"CPU","CONT","type=f16,ne=[2,1,1,1]","support","1","yes","CPU"
-"CPU","CONT","type=f16,ne=[2,1,3,5]","support","1","yes","CPU"
-"CPU","CONT","type=f16,ne=[2,3,5,7]","support","1","yes","CPU"
-"CPU","CONT","type=bf16,ne=[2,1,1,1]","support","1","yes","CPU"
-"CPU","CONT","type=bf16,ne=[2,1,3,5]","support","1","yes","CPU"
-"CPU","CONT","type=bf16,ne=[2,3,5,7]","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[2,1,1,1],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[2,1,3,5],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[2,3,5,7],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[1,4,4,1],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[1,8,17,1],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[10,10,10,1],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[2,1,1,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[2,1,3,5],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[2,3,5,7],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[1,4,4,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[1,8,17,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f32,ne=[10,10,10,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[2,1,1,1],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[2,1,3,5],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[2,3,5,7],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[1,4,4,1],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[1,8,17,1],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[10,10,10,1],use_view_slice=1","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[2,1,1,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[2,1,3,5],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[2,3,5,7],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[1,4,4,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[1,8,17,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=i32,ne=[10,10,10,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f16,ne=[2,1,1,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f16,ne=[2,1,3,5],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f16,ne=[2,3,5,7],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f16,ne=[1,4,4,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f16,ne=[1,8,17,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=f16,ne=[10,10,10,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=bf16,ne=[2,1,1,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=bf16,ne=[2,1,3,5],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=bf16,ne=[2,3,5,7],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=bf16,ne=[1,4,4,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=bf16,ne=[1,8,17,1],use_view_slice=0","support","1","yes","CPU"
+"CPU","CONT","type=bf16,ne=[10,10,10,1],use_view_slice=0","support","1","yes","CPU"
 "CPU","ADD","type=f16,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","1","yes","CPU"
 "CPU","SUB","type=f16,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","1","yes","CPU"
 "CPU","MUL","type=f16,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","1","yes","CPU"
@@ -5655,6 +5684,7 @@
 "CPU","MUL","type=f32,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","1","yes","CPU"
 "CPU","DIV","type=f32,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","1","yes","CPU"
 "CPU","ADD1","type=f32,ne=[10,5,4,3]","support","1","yes","CPU"
+"CPU","ADD1","type=f32,ne=[1024,1024,1,1]","support","1","yes","CPU"
 "CPU","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=0.000000,inplace=0","support","1","yes","CPU"
 "CPU","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=1.000000,inplace=0","support","1","yes","CPU"
 "CPU","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=1.000000,inplace=1","support","1","yes","CPU"
@@ -8644,9 +8674,13 @@
 "CPU","CLAMP","type=f16,ne=[7,1,5,3],min=-0.500000,max=0.500000","support","1","yes","CPU"
 "CPU","LEAKY_RELU","type=f16,ne_a=[7,1,5,3],negative_slope=0.100000","support","1","yes","CPU"
 "CPU","FLOOR","type=f16,ne=[7,1,5,3]","support","1","yes","CPU"
+"CPU","FLOOR","type=f16,ne=[1024,1024,1,1]","support","1","yes","CPU"
 "CPU","CEIL","type=f16,ne=[7,1,5,3]","support","1","yes","CPU"
+"CPU","CEIL","type=f16,ne=[1024,1024,1,1]","support","1","yes","CPU"
 "CPU","ROUND","type=f16,ne=[7,1,5,3]","support","1","yes","CPU"
+"CPU","ROUND","type=f16,ne=[1024,1024,1,1]","support","1","yes","CPU"
 "CPU","TRUNC","type=f16,ne=[7,1,5,3]","support","1","yes","CPU"
+"CPU","TRUNC","type=f16,ne=[1024,1024,1,1]","support","1","yes","CPU"
 "CPU","SQR","type=f32,ne=[10,5,4,3]","support","1","yes","CPU"
 "CPU","SQRT","type=f32,ne=[10,3,3,2]","support","1","yes","CPU"
 "CPU","LOG","type=f32,ne=[10,5,4,3]","support","1","yes","CPU"
@@ -8666,9 +8700,13 @@
 "CPU","CLAMP","type=f32,ne=[7,1,5,3],min=-0.500000,max=0.500000","support","1","yes","CPU"
 "CPU","LEAKY_RELU","type=f32,ne_a=[7,1,5,3],negative_slope=0.100000","support","1","yes","CPU"
 "CPU","FLOOR","type=f32,ne=[7,1,5,3]","support","1","yes","CPU"
+"CPU","FLOOR","type=f32,ne=[1024,1024,1,1]","support","1","yes","CPU"
 "CPU","CEIL","type=f32,ne=[7,1,5,3]","support","1","yes","CPU"
+"CPU","CEIL","type=f32,ne=[1024,1024,1,1]","support","1","yes","CPU"
 "CPU","ROUND","type=f32,ne=[7,1,5,3]","support","1","yes","CPU"
+"CPU","ROUND","type=f32,ne=[1024,1024,1,1]","support","1","yes","CPU"
 "CPU","TRUNC","type=f32,ne=[7,1,5,3]","support","1","yes","CPU"
+"CPU","TRUNC","type=f32,ne=[1024,1024,1,1]","support","1","yes","CPU"
 "CPU","DIAG_MASK_INF","type=f32,ne=[10,10,1,1],n_past=5","support","1","yes","CPU"
 "CPU","DIAG_MASK_INF","type=f32,ne=[10,10,3,1],n_past=5","support","1","yes","CPU"
 "CPU","DIAG_MASK_INF","type=f32,ne=[10,10,3,2],n_past=5","support","1","yes","CPU"
@@ -9411,18 +9449,405 @@
 "CPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=3","support","1","yes","CPU"
 "CPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","1","yes","CPU"
 "CPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","1","yes","CPU"
+"CPU","ARGSORT","type=f32,ne=[3,1,1,1],order=0","support","1","yes","CPU"
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 "CPU","ARGSORT","type=f32,ne=[8,1,1,1],order=0","support","1","yes","CPU"
+"CPU","ARGSORT","type=f32,ne=[15,1,1,1],order=0","support","1","yes","CPU"
+"CPU","ARGSORT","type=f32,ne=[16,1,1,1],order=0","support","1","yes","CPU"
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+"CPU","TOP_K","type=f32,ne=[16,10,10,10],k=7,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[60,10,10,10],k=7,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[1023,2,1,3],k=7,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[1024,2,1,3],k=7,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[1025,2,1,3],k=7,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[16384,1,1,1],k=7,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[2047,2,1,3],k=7,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[2048,2,1,3],k=7,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[2049,2,1,3],k=7,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[16,10,10,10],k=15,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[60,10,10,10],k=15,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[1023,2,1,3],k=15,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[1024,2,1,3],k=15,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[1025,2,1,3],k=15,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[16384,1,1,1],k=15,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[2047,2,1,3],k=15,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[2048,2,1,3],k=15,ties=0","support","1","yes","CPU"
+"CPU","TOP_K","type=f32,ne=[2049,2,1,3],k=15,ties=0","support","1","yes","CPU"
 "CPU","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=nearest,transpose=0","support","1","yes","CPU"
 "CPU","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=nearest,transpose=1","support","1","yes","CPU"
 "CPU","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=nearest,flags=none","support","1","yes","CPU"
@@ -9435,6 +9860,10 @@
 "CPU","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=bicubic,transpose=1","support","1","yes","CPU"
 "CPU","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=bicubic,flags=none","support","1","yes","CPU"
 "CPU","UPSCALE","type=f32,ne=[5,7,11,13],ne_tgt=[2,5,7,11],mode=bicubic,flags=none","support","1","yes","CPU"
+"CPU","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=513,transpose=0","support","1","yes","CPU"
+"CPU","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=513,transpose=1","support","1","yes","CPU"
+"CPU","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=bilinear,flags=none","support","1","yes","CPU"
+"CPU","UPSCALE","type=f32,ne=[5,7,11,13],ne_tgt=[2,5,7,11],mode=bilinear,flags=none","support","1","yes","CPU"
 "CPU","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=bilinear,flags=align_corners","support","1","yes","CPU"
 "CPU","UPSCALE","type=f32,ne=[1,4,3,2],ne_tgt=[2,8,3,2],mode=bilinear,flags=align_corners","support","1","yes","CPU"
 "CPU","UPSCALE","type=f32,ne=[4,1,3,2],ne_tgt=[1,1,3,2],mode=bilinear,flags=align_corners","support","1","yes","CPU"
@@ -9463,15 +9892,30 @@
 "CPU","GROUP_NORM","type=f32,ne=[64,64,320,1],num_groups=32,eps=0.000001","support","1","yes","CPU"
 "CPU","GROUP_NORM","type=f32,ne=[9,9,1280,1],num_groups=32,eps=0.000001","support","1","yes","CPU"
 "CPU","ACC","type=f32,ne_a=[256,17,1,1],ne_b=[256,16,1,1]","support","1","yes","CPU"
-"CPU","PAD","type=f32,ne_a=[512,512,1,1],pad_0=1,pad_1=1","support","1","yes","CPU"
-"CPU","PAD","type=f32,ne_a=[512,512,3,1],lp0=1,rp0=1,lp1=1,rp1=1,lp2=1,rp2=1,lp3=1,rp3=1,v=0","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[512,512,1,1],pad_0=1,pad_1=1,circular=0","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[33,17,2,1],pad_0=4,pad_1=3,circular=1","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[512,512,3,1],lp0=1,rp0=1,lp1=1,rp1=1,lp2=1,rp2=1,lp3=1,rp3=1,v=0,circular=0","support","1","yes","CPU"
 "CPU","PAD_REFLECT_1D","type=f32,ne_a=[512,34,2,1],pad_0=10,pad_1=9","support","1","yes","CPU"
 "CPU","PAD_REFLECT_1D","type=f32,ne_a=[3000,384,4,1],pad_0=10,pad_1=9","support","1","yes","CPU"
 "CPU","ROLL","shift0=3,shift1=-2,shift3=1,shift4=-1","support","1","yes","CPU"
 "CPU","ARANGE","type=f32,start=0.000000,stop=10.000000,step=1.000000","support","1","yes","CPU"
+"CPU","ARANGE","type=f32,start=0.000000,stop=1048576.000000,step=1.000000","support","1","yes","CPU"
 "CPU","TIMESTEP_EMBEDDING","type=f32,ne_a=[2,1,1,1],dim=320,max_period=10000","support","1","yes","CPU"
 "CPU","LEAKY_RELU","type=f32,ne_a=[10,5,4,3],negative_slope=0.100000","support","1","yes","CPU"
 "CPU","CUMSUM","type=f32,ne=[10,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[127,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[128,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[128,128,4,4]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[255,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[256,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[511,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[512,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[1023,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[1024,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[2047,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[2048,5,4,3]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[242004,1,1,1]","support","1","yes","CPU"
+"CPU","CUMSUM","type=f32,ne=[375960,1,1,1]","support","1","yes","CPU"
 "CPU","XIELU","type=f32,ne=[10,5,4,3]","support","1","yes","CPU"
 "CPU","TRI","type=f32,ne=[10,10,4,3],tri_type=3","support","1","yes","CPU"
 "CPU","TRI","type=f32,ne=[10,10,4,3],tri_type=2","support","1","yes","CPU"
@@ -9480,6 +9924,10 @@
 "CPU","FILL","type=f32,ne=[10,10,4,3],c=0.000000","support","1","yes","CPU"
 "CPU","FILL","type=f32,ne=[303,207,11,3],c=2.000000","support","1","yes","CPU"
 "CPU","FILL","type=f32,ne=[800,600,4,4],c=-152.000000","support","1","yes","CPU"
+"CPU","FILL","type=f32,ne=[2048,512,2,2],c=3.500000","support","1","yes","CPU"
+"CPU","DIAG","type=f32,ne=[10,1,4,3]","support","1","yes","CPU"
+"CPU","DIAG","type=f32,ne=[79,1,19,13]","support","1","yes","CPU"
+"CPU","DIAG","type=f32,ne=[256,1,8,16]","support","1","yes","CPU"
 "CPU","SOLVE_TRI","type=f32,ne_lhs=[10,10,4,3],ne_rhs=[3,10,4,3]","support","1","yes","CPU"
 "CPU","SOLVE_TRI","type=f32,ne_lhs=[11,11,1,1],ne_rhs=[5,11,1,1]","support","1","yes","CPU"
 "CPU","SOLVE_TRI","type=f32,ne_lhs=[17,17,2,4],ne_rhs=[9,17,2,4]","support","1","yes","CPU"
@@ -9487,10 +9935,16 @@
 "CPU","SOLVE_TRI","type=f32,ne_lhs=[42,42,5,2],ne_rhs=[10,42,5,2]","support","1","yes","CPU"
 "CPU","SOLVE_TRI","type=f32,ne_lhs=[64,64,2,2],ne_rhs=[10,64,2,2]","support","1","yes","CPU"
 "CPU","SOLVE_TRI","type=f32,ne_lhs=[100,100,4,4],ne_rhs=[41,100,4,4]","support","1","yes","CPU"
-"CPU","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=0","support","1","yes","CPU"
-"CPU","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=0","support","1","yes","CPU"
-"CPU","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=1","support","1","yes","CPU"
-"CPU","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=1","support","1","yes","CPU"
+"CPU","SOLVE_TRI","type=f32,ne_lhs=[128,128,4,4],ne_rhs=[31,128,4,4]","support","1","yes","CPU"
+"CPU","SOLVE_TRI","type=f32,ne_lhs=[64,64,4,4],ne_rhs=[300,64,4,4]","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=0,circular=0","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=0,circular=0","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=0,circular=1","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=0,circular=1","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=1,circular=0","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=1,circular=0","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=1,circular=1","support","1","yes","CPU"
+"CPU","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=1,circular=1","support","1","yes","CPU"
 "CPU","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f32,permute=[0,1,2,3]","support","1","yes","CPU"
 "CPU","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","CPU"
 "CPU","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","1","yes","CPU"

docs/ops/CUDA.csv

@@ -4964,6 +4964,7 @@
 "CUDA0","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[3,1,1,1],s0=1,p0=0,d0=1","support","1","yes","CUDA"
 "CUDA0","CONV_TRANSPOSE_2D","ne_input=[3,2,3,1],ne_kernel=[2,2,1,3],stride=1","support","1","yes","CUDA"
 "CUDA0","CONV_TRANSPOSE_2D","ne_input=[10,10,9,1],ne_kernel=[3,3,1,9],stride=2","support","1","yes","CUDA"
+"CUDA0","CONV_TRANSPOSE_2D","ne_input=[129,63,35,1],ne_kernel=[3,3,48,35],stride=1","support","1","yes","CUDA"
 "CUDA0","COUNT_EQUAL","type=f32,ne=[4,500,1,1]","support","1","yes","CUDA"
 "CUDA0","COUNT_EQUAL","type=f32,ne=[4,5000,1,1]","support","1","yes","CUDA"
 "CUDA0","ARGMAX","type=f32,ne=[32,1,1,1]","support","1","yes","CUDA"
@@ -5419,17 +5420,45 @@
 "CUDA0","CPY","type_src=f16,type_dst=f16,ne=[256,4,1,1],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=1","support","1","yes","CUDA"
 "CUDA0","CPY","type_src=f32,type_dst=f32,ne=[256,4,1,1],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=1","support","1","yes","CUDA"
 "CUDA0","CPY","type_src=bf16,type_dst=bf16,ne=[256,4,1,1],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=1","support","1","yes","CUDA"
+"CUDA0","CPY","type_src=i32,type_dst=i32,ne=[256,4,1,1],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=1","support","1","yes","CUDA"
+"CUDA0","CPY","type_src=i32,type_dst=i32,ne=[256,1,4,1],permute_src=[1,2,0,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","CUDA"
 "CUDA0","CPY","type_src=f32,type_dst=f32,ne=[256,1,4,1],permute_src=[1,2,0,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","CUDA"
-"CUDA0","CONT","type=f32,ne=[10,10,10,1]","support","1","yes","CUDA"
-"CUDA0","CONT","type=f32,ne=[2,1,1,1]","support","1","yes","CUDA"
-"CUDA0","CONT","type=f32,ne=[2,1,3,5]","support","1","yes","CUDA"
-"CUDA0","CONT","type=f32,ne=[2,3,5,7]","support","1","yes","CUDA"
-"CUDA0","CONT","type=f16,ne=[2,1,1,1]","support","1","yes","CUDA"
-"CUDA0","CONT","type=f16,ne=[2,1,3,5]","support","1","yes","CUDA"
-"CUDA0","CONT","type=f16,ne=[2,3,5,7]","support","1","yes","CUDA"
-"CUDA0","CONT","type=bf16,ne=[2,1,1,1]","support","1","yes","CUDA"
-"CUDA0","CONT","type=bf16,ne=[2,1,3,5]","support","1","yes","CUDA"
-"CUDA0","CONT","type=bf16,ne=[2,3,5,7]","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[2,1,1,1],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[2,1,3,5],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[2,3,5,7],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[1,4,4,1],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[1,8,17,1],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[10,10,10,1],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[2,1,1,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[2,1,3,5],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[2,3,5,7],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[1,4,4,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[1,8,17,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f32,ne=[10,10,10,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[2,1,1,1],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[2,1,3,5],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[2,3,5,7],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[1,4,4,1],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[1,8,17,1],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[10,10,10,1],use_view_slice=1","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[2,1,1,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[2,1,3,5],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[2,3,5,7],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[1,4,4,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[1,8,17,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=i32,ne=[10,10,10,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f16,ne=[2,1,1,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f16,ne=[2,1,3,5],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f16,ne=[2,3,5,7],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f16,ne=[1,4,4,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f16,ne=[1,8,17,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=f16,ne=[10,10,10,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=bf16,ne=[2,1,1,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=bf16,ne=[2,1,3,5],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=bf16,ne=[2,3,5,7],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=bf16,ne=[1,4,4,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=bf16,ne=[1,8,17,1],use_view_slice=0","support","1","yes","CUDA"
+"CUDA0","CONT","type=bf16,ne=[10,10,10,1],use_view_slice=0","support","1","yes","CUDA"
 "CUDA0","ADD","type=f16,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","1","yes","CUDA"
 "CUDA0","SUB","type=f16,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","1","yes","CUDA"
 "CUDA0","MUL","type=f16,ne=[1,1,8,1],nr=[1,1,1,1],nf=1","support","1","yes","CUDA"
@@ -5655,6 +5684,7 @@
 "CUDA0","MUL","type=f32,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","1","yes","CUDA"
 "CUDA0","DIV","type=f32,ne=[64,262144,1,1],nr=[1,1,1,1],nf=1","support","1","yes","CUDA"
 "CUDA0","ADD1","type=f32,ne=[10,5,4,3]","support","1","yes","CUDA"
+"CUDA0","ADD1","type=f32,ne=[1024,1024,1,1]","support","1","yes","CUDA"
 "CUDA0","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=0.000000,inplace=0","support","1","yes","CUDA"
 "CUDA0","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=1.000000,inplace=0","support","1","yes","CUDA"
 "CUDA0","SCALE","type=f32,ne=[10,10,10,10],scale=2.000000,bias=1.000000,inplace=1","support","1","yes","CUDA"
@@ -8644,9 +8674,13 @@
 "CUDA0","CLAMP","type=f16,ne=[7,1,5,3],min=-0.500000,max=0.500000","support","1","yes","CUDA"
 "CUDA0","LEAKY_RELU","type=f16,ne_a=[7,1,5,3],negative_slope=0.100000","support","1","yes","CUDA"
 "CUDA0","FLOOR","type=f16,ne=[7,1,5,3]","support","1","yes","CUDA"
+"CUDA0","FLOOR","type=f16,ne=[1024,1024,1,1]","support","1","yes","CUDA"
 "CUDA0","CEIL","type=f16,ne=[7,1,5,3]","support","1","yes","CUDA"
+"CUDA0","CEIL","type=f16,ne=[1024,1024,1,1]","support","1","yes","CUDA"
 "CUDA0","ROUND","type=f16,ne=[7,1,5,3]","support","1","yes","CUDA"
+"CUDA0","ROUND","type=f16,ne=[1024,1024,1,1]","support","1","yes","CUDA"
 "CUDA0","TRUNC","type=f16,ne=[7,1,5,3]","support","1","yes","CUDA"
+"CUDA0","TRUNC","type=f16,ne=[1024,1024,1,1]","support","1","yes","CUDA"
 "CUDA0","SQR","type=f32,ne=[10,5,4,3]","support","1","yes","CUDA"
 "CUDA0","SQRT","type=f32,ne=[10,3,3,2]","support","1","yes","CUDA"
 "CUDA0","LOG","type=f32,ne=[10,5,4,3]","support","1","yes","CUDA"
@@ -8666,9 +8700,13 @@
 "CUDA0","CLAMP","type=f32,ne=[7,1,5,3],min=-0.500000,max=0.500000","support","1","yes","CUDA"
 "CUDA0","LEAKY_RELU","type=f32,ne_a=[7,1,5,3],negative_slope=0.100000","support","1","yes","CUDA"
 "CUDA0","FLOOR","type=f32,ne=[7,1,5,3]","support","1","yes","CUDA"
+"CUDA0","FLOOR","type=f32,ne=[1024,1024,1,1]","support","1","yes","CUDA"
 "CUDA0","CEIL","type=f32,ne=[7,1,5,3]","support","1","yes","CUDA"
+"CUDA0","CEIL","type=f32,ne=[1024,1024,1,1]","support","1","yes","CUDA"
 "CUDA0","ROUND","type=f32,ne=[7,1,5,3]","support","1","yes","CUDA"
+"CUDA0","ROUND","type=f32,ne=[1024,1024,1,1]","support","1","yes","CUDA"
 "CUDA0","TRUNC","type=f32,ne=[7,1,5,3]","support","1","yes","CUDA"
+"CUDA0","TRUNC","type=f32,ne=[1024,1024,1,1]","support","1","yes","CUDA"
 "CUDA0","DIAG_MASK_INF","type=f32,ne=[10,10,1,1],n_past=5","support","1","yes","CUDA"
 "CUDA0","DIAG_MASK_INF","type=f32,ne=[10,10,3,1],n_past=5","support","1","yes","CUDA"
 "CUDA0","DIAG_MASK_INF","type=f32,ne=[10,10,3,2],n_past=5","support","1","yes","CUDA"
@@ -9411,18 +9449,405 @@
 "CUDA0","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=3","support","0","no","CUDA"
 "CUDA0","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","1","yes","CUDA"
 "CUDA0","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","0","no","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[3,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[4,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[7,1,1,1],order=0","support","1","yes","CUDA"
 "CUDA0","ARGSORT","type=f32,ne=[8,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[15,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[16,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[31,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[32,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[63,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[64,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[127,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[128,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[255,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[256,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[511,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[512,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1023,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1024,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2047,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2048,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[4095,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[4096,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[8191,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[8192,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[16383,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[16384,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[32767,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[32768,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[65535,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[65536,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[131071,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[131072,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[262143,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[262144,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[524287,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[524288,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1048575,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1048576,1,1,1],order=0","support","1","yes","CUDA"
 "CUDA0","ARGSORT","type=f32,ne=[16,10,10,10],order=0","support","1","yes","CUDA"
 "CUDA0","ARGSORT","type=f32,ne=[60,10,10,10],order=0","support","1","yes","CUDA"
-"CUDA0","ARGSORT","type=f32,ne=[1024,1,1,1],order=0","support","1","yes","CUDA"
-"CUDA0","ARGSORT","type=f32,ne=[16384,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1023,2,1,3],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1024,2,1,3],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1025,2,1,3],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2047,2,1,3],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2048,2,1,3],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2049,2,1,3],order=0","support","1","yes","CUDA"
 "CUDA0","ARGSORT","type=f32,ne=[2,8,8192,1],order=0","support","1","yes","CUDA"
-"CUDA0","ARGSORT","type=f32,ne=[8,1,1,1],order=1","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[3,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[4,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[7,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[8,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[15,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[16,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[31,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[32,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[63,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[64,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[127,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[128,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[255,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[256,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[511,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[512,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1023,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1024,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2047,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2048,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[4095,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[4096,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[8191,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[8192,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[16383,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[16384,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[32767,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[32768,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[65535,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[65536,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[131071,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[131072,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[262143,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[262144,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[524287,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[524288,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1048575,1,1,1],order=0","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1048576,1,1,1],order=0","support","1","yes","CUDA"
 "CUDA0","ARGSORT","type=f32,ne=[16,10,10,10],order=1","support","1","yes","CUDA"
 "CUDA0","ARGSORT","type=f32,ne=[60,10,10,10],order=1","support","1","yes","CUDA"
-"CUDA0","ARGSORT","type=f32,ne=[1024,1,1,1],order=1","support","1","yes","CUDA"
-"CUDA0","ARGSORT","type=f32,ne=[16384,1,1,1],order=1","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1023,2,1,3],order=1","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1024,2,1,3],order=1","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[1025,2,1,3],order=1","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2047,2,1,3],order=1","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2048,2,1,3],order=1","support","1","yes","CUDA"
+"CUDA0","ARGSORT","type=f32,ne=[2049,2,1,3],order=1","support","1","yes","CUDA"
 "CUDA0","ARGSORT","type=f32,ne=[2,8,8192,1],order=1","support","1","yes","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1,1,1,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[12,1,2,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2,1,1,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[13,1,2,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2,1,1,1],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[13,1,2,1],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[4,1,1,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[15,1,2,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[4,1,1,1],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[15,1,2,1],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[4,1,1,1],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[15,1,2,1],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[8,1,1,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[19,1,2,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[8,1,1,1],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[19,1,2,1],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[8,1,1,1],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[19,1,2,1],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[8,1,1,1],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[19,1,2,1],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16,1,1,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[27,1,2,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16,1,1,1],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[27,1,2,1],k=2,ties=0","support","0","no","CUDA"
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+"CUDA0","TOP_K","type=f32,ne=[64,1,1,1],k=7,ties=0","support","0","no","CUDA"
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+"CUDA0","TOP_K","type=f32,ne=[75,1,2,1],k=15,ties=0","support","0","no","CUDA"
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+"CUDA0","TOP_K","type=f32,ne=[128,1,1,1],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[139,1,2,1],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[128,1,1,1],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[139,1,2,1],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[128,1,1,1],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[139,1,2,1],k=15,ties=0","support","0","no","CUDA"
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+"CUDA0","TOP_K","type=f32,ne=[139,1,2,1],k=100,ties=0","support","0","no","CUDA"
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+"CUDA0","TOP_K","type=f32,ne=[256,1,1,1],k=3,ties=0","support","0","no","CUDA"
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+"CUDA0","TOP_K","type=f32,ne=[267,1,2,1],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[256,1,1,1],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[267,1,2,1],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[256,1,1,1],k=100,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[267,1,2,1],k=100,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[512,1,1,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[523,1,2,1],k=1,ties=0","support","0","no","CUDA"
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+"CUDA0","TOP_K","type=f32,ne=[524299,1,2,1],k=9999,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16,10,10,10],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[60,10,10,10],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1023,2,1,3],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1024,2,1,3],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1025,2,1,3],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16384,1,1,1],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2047,2,1,3],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2048,2,1,3],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2049,2,1,3],k=1,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16,10,10,10],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[60,10,10,10],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1023,2,1,3],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1024,2,1,3],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1025,2,1,3],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16384,1,1,1],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2047,2,1,3],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2048,2,1,3],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2049,2,1,3],k=2,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16,10,10,10],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[60,10,10,10],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1023,2,1,3],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1024,2,1,3],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1025,2,1,3],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16384,1,1,1],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2047,2,1,3],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2048,2,1,3],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2049,2,1,3],k=3,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16,10,10,10],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[60,10,10,10],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1023,2,1,3],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1024,2,1,3],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1025,2,1,3],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16384,1,1,1],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2047,2,1,3],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2048,2,1,3],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2049,2,1,3],k=7,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16,10,10,10],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[60,10,10,10],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1023,2,1,3],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1024,2,1,3],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[1025,2,1,3],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[16384,1,1,1],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2047,2,1,3],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2048,2,1,3],k=15,ties=0","support","0","no","CUDA"
+"CUDA0","TOP_K","type=f32,ne=[2049,2,1,3],k=15,ties=0","support","0","no","CUDA"
 "CUDA0","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=nearest,transpose=0","support","1","yes","CUDA"
 "CUDA0","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=nearest,transpose=1","support","1","yes","CUDA"
 "CUDA0","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=nearest,flags=none","support","1","yes","CUDA"
@@ -9435,6 +9860,10 @@
 "CUDA0","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=bicubic,transpose=1","support","1","yes","CUDA"
 "CUDA0","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=bicubic,flags=none","support","1","yes","CUDA"
 "CUDA0","UPSCALE","type=f32,ne=[5,7,11,13],ne_tgt=[2,5,7,11],mode=bicubic,flags=none","support","1","yes","CUDA"
+"CUDA0","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=513,transpose=0","support","1","yes","CUDA"
+"CUDA0","UPSCALE","type=f32,ne=[512,512,3,2],scale_factor=2,mode=513,transpose=1","support","1","yes","CUDA"
+"CUDA0","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=bilinear,flags=none","support","1","yes","CUDA"
+"CUDA0","UPSCALE","type=f32,ne=[5,7,11,13],ne_tgt=[2,5,7,11],mode=bilinear,flags=none","support","1","yes","CUDA"
 "CUDA0","UPSCALE","type=f32,ne=[2,5,7,11],ne_tgt=[5,7,11,13],mode=bilinear,flags=align_corners","support","1","yes","CUDA"
 "CUDA0","UPSCALE","type=f32,ne=[1,4,3,2],ne_tgt=[2,8,3,2],mode=bilinear,flags=align_corners","support","1","yes","CUDA"
 "CUDA0","UPSCALE","type=f32,ne=[4,1,3,2],ne_tgt=[1,1,3,2],mode=bilinear,flags=align_corners","support","1","yes","CUDA"
@@ -9463,34 +9892,59 @@
 "CUDA0","GROUP_NORM","type=f32,ne=[64,64,320,1],num_groups=32,eps=0.000001","support","1","yes","CUDA"
 "CUDA0","GROUP_NORM","type=f32,ne=[9,9,1280,1],num_groups=32,eps=0.000001","support","1","yes","CUDA"
 "CUDA0","ACC","type=f32,ne_a=[256,17,1,1],ne_b=[256,16,1,1]","support","1","yes","CUDA"
-"CUDA0","PAD","type=f32,ne_a=[512,512,1,1],pad_0=1,pad_1=1","support","1","yes","CUDA"
-"CUDA0","PAD","type=f32,ne_a=[512,512,3,1],lp0=1,rp0=1,lp1=1,rp1=1,lp2=1,rp2=1,lp3=1,rp3=1,v=0","support","1","yes","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[512,512,1,1],pad_0=1,pad_1=1,circular=0","support","1","yes","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[33,17,2,1],pad_0=4,pad_1=3,circular=1","support","1","yes","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[512,512,3,1],lp0=1,rp0=1,lp1=1,rp1=1,lp2=1,rp2=1,lp3=1,rp3=1,v=0,circular=0","support","1","yes","CUDA"
 "CUDA0","PAD_REFLECT_1D","type=f32,ne_a=[512,34,2,1],pad_0=10,pad_1=9","support","1","yes","CUDA"
 "CUDA0","PAD_REFLECT_1D","type=f32,ne_a=[3000,384,4,1],pad_0=10,pad_1=9","support","1","yes","CUDA"
 "CUDA0","ROLL","shift0=3,shift1=-2,shift3=1,shift4=-1","support","1","yes","CUDA"
 "CUDA0","ARANGE","type=f32,start=0.000000,stop=10.000000,step=1.000000","support","1","yes","CUDA"
+"CUDA0","ARANGE","type=f32,start=0.000000,stop=1048576.000000,step=1.000000","support","1","yes","CUDA"
 "CUDA0","TIMESTEP_EMBEDDING","type=f32,ne_a=[2,1,1,1],dim=320,max_period=10000","support","1","yes","CUDA"
 "CUDA0","LEAKY_RELU","type=f32,ne_a=[10,5,4,3],negative_slope=0.100000","support","1","yes","CUDA"
-"CUDA0","CUMSUM","type=f32,ne=[10,5,4,3]","support","0","no","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[10,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[127,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[128,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[128,128,4,4]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[255,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[256,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[511,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[512,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[1023,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[1024,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[2047,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[2048,5,4,3]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[242004,1,1,1]","support","1","yes","CUDA"
+"CUDA0","CUMSUM","type=f32,ne=[375960,1,1,1]","support","1","yes","CUDA"
 "CUDA0","XIELU","type=f32,ne=[10,5,4,3]","support","0","no","CUDA"
-"CUDA0","TRI","type=f32,ne=[10,10,4,3],tri_type=3","support","0","no","CUDA"
-"CUDA0","TRI","type=f32,ne=[10,10,4,3],tri_type=2","support","0","no","CUDA"
-"CUDA0","TRI","type=f32,ne=[10,10,4,3],tri_type=1","support","0","no","CUDA"
-"CUDA0","TRI","type=f32,ne=[10,10,4,3],tri_type=0","support","0","no","CUDA"
-"CUDA0","FILL","type=f32,ne=[10,10,4,3],c=0.000000","support","0","no","CUDA"
-"CUDA0","FILL","type=f32,ne=[303,207,11,3],c=2.000000","support","0","no","CUDA"
-"CUDA0","FILL","type=f32,ne=[800,600,4,4],c=-152.000000","support","0","no","CUDA"
-"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[10,10,4,3],ne_rhs=[3,10,4,3]","support","0","no","CUDA"
-"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[11,11,1,1],ne_rhs=[5,11,1,1]","support","0","no","CUDA"
-"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[17,17,2,4],ne_rhs=[9,17,2,4]","support","0","no","CUDA"
-"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[30,30,7,1],ne_rhs=[8,30,7,1]","support","0","no","CUDA"
-"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[42,42,5,2],ne_rhs=[10,42,5,2]","support","0","no","CUDA"
-"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[64,64,2,2],ne_rhs=[10,64,2,2]","support","0","no","CUDA"
+"CUDA0","TRI","type=f32,ne=[10,10,4,3],tri_type=3","support","1","yes","CUDA"
+"CUDA0","TRI","type=f32,ne=[10,10,4,3],tri_type=2","support","1","yes","CUDA"
+"CUDA0","TRI","type=f32,ne=[10,10,4,3],tri_type=1","support","1","yes","CUDA"
+"CUDA0","TRI","type=f32,ne=[10,10,4,3],tri_type=0","support","1","yes","CUDA"
+"CUDA0","FILL","type=f32,ne=[10,10,4,3],c=0.000000","support","1","yes","CUDA"
+"CUDA0","FILL","type=f32,ne=[303,207,11,3],c=2.000000","support","1","yes","CUDA"
+"CUDA0","FILL","type=f32,ne=[800,600,4,4],c=-152.000000","support","1","yes","CUDA"
+"CUDA0","FILL","type=f32,ne=[2048,512,2,2],c=3.500000","support","1","yes","CUDA"
+"CUDA0","DIAG","type=f32,ne=[10,1,4,3]","support","1","yes","CUDA"
+"CUDA0","DIAG","type=f32,ne=[79,1,19,13]","support","1","yes","CUDA"
+"CUDA0","DIAG","type=f32,ne=[256,1,8,16]","support","1","yes","CUDA"
+"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[10,10,4,3],ne_rhs=[3,10,4,3]","support","1","yes","CUDA"
+"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[11,11,1,1],ne_rhs=[5,11,1,1]","support","1","yes","CUDA"
+"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[17,17,2,4],ne_rhs=[9,17,2,4]","support","1","yes","CUDA"
+"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[30,30,7,1],ne_rhs=[8,30,7,1]","support","1","yes","CUDA"
+"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[42,42,5,2],ne_rhs=[10,42,5,2]","support","1","yes","CUDA"
+"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[64,64,2,2],ne_rhs=[10,64,2,2]","support","1","yes","CUDA"
 "CUDA0","SOLVE_TRI","type=f32,ne_lhs=[100,100,4,4],ne_rhs=[41,100,4,4]","support","0","no","CUDA"
-"CUDA0","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=0","support","1","yes","CUDA"
-"CUDA0","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=0","support","1","yes","CUDA"
-"CUDA0","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=1","support","0","no","CUDA"
-"CUDA0","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=1","support","0","no","CUDA"
+"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[128,128,4,4],ne_rhs=[31,128,4,4]","support","0","no","CUDA"
+"CUDA0","SOLVE_TRI","type=f32,ne_lhs=[64,64,4,4],ne_rhs=[300,64,4,4]","support","0","no","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=0,circular=0","support","1","yes","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=0,circular=0","support","1","yes","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=0,circular=1","support","1","yes","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=0,circular=1","support","1","yes","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=1,circular=0","support","0","no","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=1,circular=0","support","0","no","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,v=1,circular=1","support","0","no","CUDA"
+"CUDA0","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,v=1,circular=1","support","0","no","CUDA"
 "CUDA0","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f32,permute=[0,1,2,3]","support","1","yes","CUDA"
 "CUDA0","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=f16,permute=[0,1,2,3]","support","1","yes","CUDA"
 "CUDA0","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_KV=bf16,permute=[0,1,2,3]","support","0","no","CUDA"

examples/batched/batched.cpp

@@ -2,6 +2,7 @@
 #include "common.h"
 #include "log.h"
 #include "llama.h"
+#include "sampling.h"
 
 #include <algorithm>
 #include <cstdio>
@@ -64,17 +65,23 @@ int main(int argc, char ** argv) {
     ctx_params.n_ctx   = n_kv_req;
     ctx_params.n_batch = std::max(n_predict, n_parallel);
 
-    llama_context * ctx = llama_init_from_model(model, ctx_params);
-
     auto sparams = llama_sampler_chain_default_params();
     sparams.no_perf = false;
 
-    llama_sampler * smpl = llama_sampler_chain_init(sparams);
+    std::vector<llama_sampler *> samplers;
 
-    llama_sampler_chain_add(smpl, llama_sampler_init_top_k(params.sampling.top_k));
-    llama_sampler_chain_add(smpl, llama_sampler_init_top_p(params.sampling.top_p, params.sampling.min_keep));
-    llama_sampler_chain_add(smpl, llama_sampler_init_temp (params.sampling.temp));
-    llama_sampler_chain_add(smpl, llama_sampler_init_dist (params.sampling.seed));
+    for (int32_t i = 0; i < n_parallel; ++i) {
+        llama_sampler * smpl = llama_sampler_chain_init(sparams);
+
+        llama_sampler_chain_add(smpl, llama_sampler_init_top_k(params.sampling.top_k));
+        llama_sampler_chain_add(smpl, llama_sampler_init_top_p(params.sampling.top_p, params.sampling.min_keep));
+        llama_sampler_chain_add(smpl, llama_sampler_init_temp (params.sampling.temp));
+        llama_sampler_chain_add(smpl, llama_sampler_init_dist (params.sampling.seed));
+
+        samplers.push_back(smpl);
+    }
+
+    llama_context * ctx = llama_init_from_model(model, ctx_params);
 
     if (ctx == NULL) {
         LOG_ERR("%s: error: failed to create the llama_context\n" , __func__);
@@ -173,7 +180,7 @@ int main(int argc, char ** argv) {
                 continue;
             }
 
-            const llama_token new_token_id = llama_sampler_sample(smpl, ctx, i_batch[i]);
+            const llama_token new_token_id = llama_sampler_sample(samplers[i], ctx, i_batch[i]);
 
             // is it an end of generation? -> mark the stream as finished
             if (llama_vocab_is_eog(vocab, new_token_id) || n_cur == n_predict) {
@@ -229,14 +236,17 @@ int main(int argc, char ** argv) {
             __func__, n_decode, (t_main_end - t_main_start) / 1000000.0f, n_decode / ((t_main_end - t_main_start) / 1000000.0f));
 
     LOG("\n");
-    llama_perf_sampler_print(smpl);
+    llama_perf_sampler_print(samplers[0]);
     llama_perf_context_print(ctx);
 
     fprintf(stderr, "\n");
 
     llama_batch_free(batch);
 
-    llama_sampler_free(smpl);
+    for (auto & sampler_config : samplers) {
+        llama_sampler_free(sampler_config);
+    }
+
     llama_free(ctx);
     llama_model_free(model);
 

examples/embedding/embedding.cpp

@@ -131,10 +131,10 @@ int main(int argc, char ** argv) {
     llama_numa_init(params.numa);
 
     // load the model
-    common_init_result llama_init = common_init_from_params(params);
+    auto llama_init = common_init_from_params(params);
 
-    llama_model * model = llama_init.model.get();
-    llama_context * ctx = llama_init.context.get();
+    auto * model = llama_init->model();
+    auto * ctx = llama_init->context();
 
     if (model == NULL) {
         LOG_ERR("%s: unable to load model\n", __func__);

examples/eval-callback/eval-callback.cpp

@@ -202,10 +202,10 @@ int main(int argc, char ** argv) {
     params.warmup = false;
 
     // init
-    common_init_result llama_init = common_init_from_params(params);
+    auto llama_init = common_init_from_params(params);
 
-    llama_model * model = llama_init.model.get();
-    llama_context * ctx = llama_init.context.get();
+    auto * model = llama_init->model();
+    auto * ctx   = llama_init->context();
 
     if (model == nullptr || ctx == nullptr) {
         LOG_ERR("%s : failed to init\n", __func__);

examples/gen-docs/gen-docs.cpp

@@ -14,12 +14,13 @@ static void write_table_header(std::ofstream & file) {
 static void write_table_entry(std::ofstream & file, const common_arg & opt) {
     file << "| `";
     // args
-    for (const auto & arg : opt.args) {
-    if (arg == opt.args.front()) {
+    auto all_args = opt.get_args();
+    for (const auto & arg : all_args) {
+    if (arg == all_args.front()) {
             file << arg;
-            if (opt.args.size() > 1) file << ", ";
+            if (all_args.size() > 1) file << ", ";
         } else {
-            file << arg << (arg != opt.args.back() ? ", " : "");
+            file << arg << (arg != all_args.back() ? ", " : "");
         }
     }
     // value hint
@@ -47,7 +48,7 @@ static void write_table(std::ofstream & file, std::vector<common_arg *> & opts)
     }
 }
 
-static void export_md(std::string fname, llama_example ex) {
+static void export_md(std::string fname, llama_example ex, std::string name) {
     std::ofstream file(fname, std::ofstream::out | std::ofstream::trunc);
 
     common_params params;
@@ -71,13 +72,14 @@ static void export_md(std::string fname, llama_example ex) {
     write_table(file, common_options);
     file << "\n\n**Sampling params**\n\n";
     write_table(file, sparam_options);
-    file << "\n\n**Example-specific params**\n\n";
+    file << "\n\n**" << name << "-specific params**\n\n";
     write_table(file, specific_options);
 }
 
 int main(int, char **) {
-    export_md("autogen-main.md", LLAMA_EXAMPLE_MAIN);
-    export_md("autogen-server.md", LLAMA_EXAMPLE_SERVER);
+    // TODO: add CLI
+    export_md("autogen-completion.md", LLAMA_EXAMPLE_COMPLETION, "Tool");
+    export_md("autogen-server.md", LLAMA_EXAMPLE_SERVER, "Server");
 
     return 0;
 }

examples/llama.android/app/build.gradle.kts

@@ -1,16 +1,18 @@
 plugins {
-    id("com.android.application")
-    id("org.jetbrains.kotlin.android")
+    alias(libs.plugins.android.application)
+    alias(libs.plugins.jetbrains.kotlin.android)
 }
 
 android {
     namespace = "com.example.llama"
-    compileSdk = 34
+    compileSdk = 36
 
     defaultConfig {
-        applicationId = "com.example.llama"
+        applicationId = "com.example.llama.aichat"
+
         minSdk = 33
-        targetSdk = 34
+        targetSdk = 36
+
         versionCode = 1
         versionName = "1.0"
 
@@ -21,8 +23,17 @@ android {
     }
 
     buildTypes {
+        debug {
+            isMinifyEnabled = true
+            isShrinkResources = true
+            proguardFiles(
+                getDefaultProguardFile("proguard-android.txt"),
+                "proguard-rules.pro"
+            )
+        }
         release {
-            isMinifyEnabled = false
+            isMinifyEnabled = true
+            isShrinkResources = true
             proguardFiles(
                 getDefaultProguardFile("proguard-android-optimize.txt"),
                 "proguard-rules.pro"
@@ -36,30 +47,15 @@ android {
     kotlinOptions {
         jvmTarget = "1.8"
     }
-    buildFeatures {
-        compose = true
-    }
-    composeOptions {
-        kotlinCompilerExtensionVersion = "1.5.1"
-    }
 }
 
 dependencies {
+    implementation(libs.bundles.androidx)
+    implementation(libs.material)
 
-    implementation("androidx.core:core-ktx:1.12.0")
-    implementation("androidx.lifecycle:lifecycle-runtime-ktx:2.6.2")
-    implementation("androidx.activity:activity-compose:1.8.2")
-    implementation(platform("androidx.compose:compose-bom:2023.08.00"))
-    implementation("androidx.compose.ui:ui")
-    implementation("androidx.compose.ui:ui-graphics")
-    implementation("androidx.compose.ui:ui-tooling-preview")
-    implementation("androidx.compose.material3:material3")
-    implementation(project(":llama"))
-    testImplementation("junit:junit:4.13.2")
-    androidTestImplementation("androidx.test.ext:junit:1.1.5")
-    androidTestImplementation("androidx.test.espresso:espresso-core:3.5.1")
-    androidTestImplementation(platform("androidx.compose:compose-bom:2023.08.00"))
-    androidTestImplementation("androidx.compose.ui:ui-test-junit4")
-    debugImplementation("androidx.compose.ui:ui-tooling")
-    debugImplementation("androidx.compose.ui:ui-test-manifest")
+    implementation(project(":lib"))
+
+    testImplementation(libs.junit)
+    androidTestImplementation(libs.androidx.junit)
+    androidTestImplementation(libs.androidx.espresso.core)
 }

examples/llama.android/app/proguard-rules.pro

@@ -19,3 +19,11 @@
 # If you keep the line number information, uncomment this to
 # hide the original source file name.
 #-renamesourcefileattribute SourceFile
+
+-keep class com.arm.aichat.* { *; }
+-keep class com.arm.aichat.gguf.* { *; }
+
+-assumenosideeffects class android.util.Log {
+    public static int v(...);
+    public static int d(...);
+}

examples/llama.android/app/src/main/AndroidManifest.xml

@@ -1,24 +1,21 @@
 <?xml version="1.0" encoding="utf-8"?>
-<manifest xmlns:android="http://schemas.android.com/apk/res/android"
-    xmlns:tools="http://schemas.android.com/tools">
-
-    <uses-permission android:name="android.permission.INTERNET" />
+<manifest xmlns:android="http://schemas.android.com/apk/res/android">
 
     <application
         android:allowBackup="true"
         android:dataExtractionRules="@xml/data_extraction_rules"
+        android:extractNativeLibs="true"
         android:fullBackupContent="@xml/backup_rules"
-        android:icon="@mipmap/ic_launcher"
+        android:icon="@mipmap/ic_launcher_round"
         android:label="@string/app_name"
         android:roundIcon="@mipmap/ic_launcher_round"
         android:supportsRtl="true"
-        android:theme="@style/Theme.LlamaAndroid"
+        android:theme="@style/Theme.AiChatSample"
         >
 
         <activity
             android:name=".MainActivity"
-            android:exported="true"
-            android:theme="@style/Theme.LlamaAndroid">
+            android:exported="true">
             <intent-filter>
                 <action android:name="android.intent.action.MAIN" />
 

examples/llama.android/app/src/main/java/com/example/llama/Downloadable.kt

@@ -1,119 +0,0 @@
-package com.example.llama
-
-import android.app.DownloadManager
-import android.net.Uri
-import android.util.Log
-import androidx.compose.material3.Button
-import androidx.compose.material3.Text
-import androidx.compose.runtime.Composable
-import androidx.compose.runtime.getValue
-import androidx.compose.runtime.mutableDoubleStateOf
-import androidx.compose.runtime.mutableStateOf
-import androidx.compose.runtime.remember
-import androidx.compose.runtime.rememberCoroutineScope
-import androidx.compose.runtime.setValue
-import androidx.core.database.getLongOrNull
-import androidx.core.net.toUri
-import kotlinx.coroutines.delay
-import kotlinx.coroutines.launch
-import java.io.File
-
-data class Downloadable(val name: String, val source: Uri, val destination: File) {
-    companion object {
-        @JvmStatic
-        private val tag: String? = this::class.qualifiedName
-
-        sealed interface State
-        data object Ready: State
-        data class Downloading(val id: Long): State
-        data class Downloaded(val downloadable: Downloadable): State
-        data class Error(val message: String): State
-
-        @JvmStatic
-        @Composable
-        fun Button(viewModel: MainViewModel, dm: DownloadManager, item: Downloadable) {
-            var status: State by remember {
-                mutableStateOf(
-                    if (item.destination.exists()) Downloaded(item)
-                    else Ready
-                )
-            }
-            var progress by remember { mutableDoubleStateOf(0.0) }
-
-            val coroutineScope = rememberCoroutineScope()
-
-            suspend fun waitForDownload(result: Downloading, item: Downloadable): State {
-                while (true) {
-                    val cursor = dm.query(DownloadManager.Query().setFilterById(result.id))
-
-                    if (cursor == null) {
-                        Log.e(tag, "dm.query() returned null")
-                        return Error("dm.query() returned null")
-                    }
-
-                    if (!cursor.moveToFirst() || cursor.count < 1) {
-                        cursor.close()
-                        Log.i(tag, "cursor.moveToFirst() returned false or cursor.count < 1, download canceled?")
-                        return Ready
-                    }
-
-                    val pix = cursor.getColumnIndex(DownloadManager.COLUMN_BYTES_DOWNLOADED_SO_FAR)
-                    val tix = cursor.getColumnIndex(DownloadManager.COLUMN_TOTAL_SIZE_BYTES)
-                    val sofar = cursor.getLongOrNull(pix) ?: 0
-                    val total = cursor.getLongOrNull(tix) ?: 1
-                    cursor.close()
-
-                    if (sofar == total) {
-                        return Downloaded(item)
-                    }
-
-                    progress = (sofar * 1.0) / total
-
-                    delay(1000L)
-                }
-            }
-
-            fun onClick() {
-                when (val s = status) {
-                    is Downloaded -> {
-                        viewModel.load(item.destination.path)
-                    }
-
-                    is Downloading -> {
-                        coroutineScope.launch {
-                            status = waitForDownload(s, item)
-                        }
-                    }
-
-                    else -> {
-                        item.destination.delete()
-
-                        val request = DownloadManager.Request(item.source).apply {
-                            setTitle("Downloading model")
-                            setDescription("Downloading model: ${item.name}")
-                            setAllowedNetworkTypes(DownloadManager.Request.NETWORK_WIFI)
-                            setDestinationUri(item.destination.toUri())
-                        }
-
-                        viewModel.log("Saving ${item.name} to ${item.destination.path}")
-                        Log.i(tag, "Saving ${item.name} to ${item.destination.path}")
-
-                        val id = dm.enqueue(request)
-                        status = Downloading(id)
-                        onClick()
-                    }
-                }
-            }
-
-            Button(onClick = { onClick() }, enabled = status !is Downloading) {
-                when (status) {
-                    is Downloading -> Text(text = "Downloading ${(progress * 100).toInt()}%")
-                    is Downloaded -> Text("Load ${item.name}")
-                    is Ready -> Text("Download ${item.name}")
-                    is Error -> Text("Download ${item.name}")
-                }
-            }
-        }
-
-    }
-}

examples/llama.android/app/src/main/java/com/example/llama/MainActivity.kt

@@ -1,154 +1,257 @@
 package com.example.llama
 
-import android.app.ActivityManager
-import android.app.DownloadManager
-import android.content.ClipData
-import android.content.ClipboardManager
 import android.net.Uri
 import android.os.Bundle
-import android.os.StrictMode
-import android.os.StrictMode.VmPolicy
-import android.text.format.Formatter
-import androidx.activity.ComponentActivity
-import androidx.activity.compose.setContent
-import androidx.activity.viewModels
-import androidx.compose.foundation.layout.Box
-import androidx.compose.foundation.layout.Column
-import androidx.compose.foundation.layout.Row
-import androidx.compose.foundation.layout.fillMaxSize
-import androidx.compose.foundation.layout.padding
-import androidx.compose.foundation.lazy.LazyColumn
-import androidx.compose.foundation.lazy.items
-import androidx.compose.foundation.lazy.rememberLazyListState
-import androidx.compose.material3.Button
-import androidx.compose.material3.LocalContentColor
-import androidx.compose.material3.MaterialTheme
-import androidx.compose.material3.OutlinedTextField
-import androidx.compose.material3.Surface
-import androidx.compose.material3.Text
-import androidx.compose.runtime.Composable
-import androidx.compose.ui.Modifier
-import androidx.compose.ui.unit.dp
-import androidx.core.content.getSystemService
-import com.example.llama.ui.theme.LlamaAndroidTheme
+import android.util.Log
+import android.widget.EditText
+import android.widget.TextView
+import android.widget.Toast
+import androidx.activity.enableEdgeToEdge
+import androidx.activity.result.contract.ActivityResultContracts
+import androidx.appcompat.app.AppCompatActivity
+import androidx.lifecycle.lifecycleScope
+import androidx.recyclerview.widget.LinearLayoutManager
+import androidx.recyclerview.widget.RecyclerView
+import com.arm.aichat.AiChat
+import com.arm.aichat.InferenceEngine
+import com.arm.aichat.gguf.GgufMetadata
+import com.arm.aichat.gguf.GgufMetadataReader
+import com.google.android.material.floatingactionbutton.FloatingActionButton
+import kotlinx.coroutines.Dispatchers
+import kotlinx.coroutines.flow.onCompletion
+import kotlinx.coroutines.launch
+import kotlinx.coroutines.withContext
 import java.io.File
+import java.io.FileOutputStream
+import java.io.InputStream
+import java.util.UUID
 
-class MainActivity(
-    activityManager: ActivityManager? = null,
-    downloadManager: DownloadManager? = null,
-    clipboardManager: ClipboardManager? = null,
-): ComponentActivity() {
-    private val tag: String? = this::class.simpleName
+class MainActivity : AppCompatActivity() {
 
-    private val activityManager by lazy { activityManager ?: getSystemService<ActivityManager>()!! }
-    private val downloadManager by lazy { downloadManager ?: getSystemService<DownloadManager>()!! }
-    private val clipboardManager by lazy { clipboardManager ?: getSystemService<ClipboardManager>()!! }
+    // Android views
+    private lateinit var ggufTv: TextView
+    private lateinit var messagesRv: RecyclerView
+    private lateinit var userInputEt: EditText
+    private lateinit var userActionFab: FloatingActionButton
 
-    private val viewModel: MainViewModel by viewModels()
+    // Arm AI Chat inference engine
+    private lateinit var engine: InferenceEngine
 
-    // Get a MemoryInfo object for the device's current memory status.
-    private fun availableMemory(): ActivityManager.MemoryInfo {
-        return ActivityManager.MemoryInfo().also { memoryInfo ->
-            activityManager.getMemoryInfo(memoryInfo)
-        }
-    }
+    // Conversation states
+    private var isModelReady = false
+    private val messages = mutableListOf<Message>()
+    private val lastAssistantMsg = StringBuilder()
+    private val messageAdapter = MessageAdapter(messages)
 
     override fun onCreate(savedInstanceState: Bundle?) {
         super.onCreate(savedInstanceState)
+        enableEdgeToEdge()
+        setContentView(R.layout.activity_main)
 
-        StrictMode.setVmPolicy(
-            VmPolicy.Builder(StrictMode.getVmPolicy())
-                .detectLeakedClosableObjects()
-                .build()
-        )
+        // Find views
+        ggufTv = findViewById(R.id.gguf)
+        messagesRv = findViewById(R.id.messages)
+        messagesRv.layoutManager = LinearLayoutManager(this)
+        messagesRv.adapter = messageAdapter
+        userInputEt = findViewById(R.id.user_input)
+        userActionFab = findViewById(R.id.fab)
 
-        val free = Formatter.formatFileSize(this, availableMemory().availMem)
-        val total = Formatter.formatFileSize(this, availableMemory().totalMem)
-
-        viewModel.log("Current memory: $free / $total")
-        viewModel.log("Downloads directory: ${getExternalFilesDir(null)}")
-
-        val extFilesDir = getExternalFilesDir(null)
-
-        val models = listOf(
-            Downloadable(
-                "Phi-2 7B (Q4_0, 1.6 GiB)",
-                Uri.parse("https://huggingface.co/ggml-org/models/resolve/main/phi-2/ggml-model-q4_0.gguf?download=true"),
-                File(extFilesDir, "phi-2-q4_0.gguf"),
-            ),
-            Downloadable(
-                "TinyLlama 1.1B (f16, 2.2 GiB)",
-                Uri.parse("https://huggingface.co/ggml-org/models/resolve/main/tinyllama-1.1b/ggml-model-f16.gguf?download=true"),
-                File(extFilesDir, "tinyllama-1.1-f16.gguf"),
-            ),
-            Downloadable(
-                "Phi 2 DPO (Q3_K_M, 1.48 GiB)",
-                Uri.parse("https://huggingface.co/TheBloke/phi-2-dpo-GGUF/resolve/main/phi-2-dpo.Q3_K_M.gguf?download=true"),
-                File(extFilesDir, "phi-2-dpo.Q3_K_M.gguf")
-            ),
-        )
-
-        setContent {
-            LlamaAndroidTheme {
-                // A surface container using the 'background' color from the theme
-                Surface(
-                    modifier = Modifier.fillMaxSize(),
-                    color = MaterialTheme.colorScheme.background
-                ) {
-                    MainCompose(
-                        viewModel,
-                        clipboardManager,
-                        downloadManager,
-                        models,
-                    )
-                }
+        // Arm AI Chat initialization
+        lifecycleScope.launch(Dispatchers.Default) {
+            engine = AiChat.getInferenceEngine(applicationContext)
+        }
 
+        // Upon CTA button tapped
+        userActionFab.setOnClickListener {
+            if (isModelReady) {
+                // If model is ready, validate input and send to engine
+                handleUserInput()
+            } else {
+                // Otherwise, prompt user to select a GGUF metadata on the device
+                getContent.launch(arrayOf("*/*"))
             }
         }
     }
-}
 
-@Composable
-fun MainCompose(
-    viewModel: MainViewModel,
-    clipboard: ClipboardManager,
-    dm: DownloadManager,
-    models: List<Downloadable>
-) {
-    Column {
-        val scrollState = rememberLazyListState()
+    private val getContent = registerForActivityResult(
+        ActivityResultContracts.OpenDocument()
+    ) { uri ->
+        Log.i(TAG, "Selected file uri:\n $uri")
+        uri?.let { handleSelectedModel(it) }
+    }
 
-        Box(modifier = Modifier.weight(1f)) {
-            LazyColumn(state = scrollState) {
-                items(viewModel.messages) {
-                    Text(
-                        it,
-                        style = MaterialTheme.typography.bodyLarge.copy(color = LocalContentColor.current),
-                        modifier = Modifier.padding(16.dp)
-                    )
+    /**
+     * Handles the file Uri from [getContent] result
+     */
+    private fun handleSelectedModel(uri: Uri) {
+        // Update UI states
+        userActionFab.isEnabled = false
+        userInputEt.hint = "Parsing GGUF..."
+        ggufTv.text = "Parsing metadata from selected file \n$uri"
+
+        lifecycleScope.launch(Dispatchers.IO) {
+            // Parse GGUF metadata
+            Log.i(TAG, "Parsing GGUF metadata...")
+            contentResolver.openInputStream(uri)?.use {
+                GgufMetadataReader.create().readStructuredMetadata(it)
+            }?.let { metadata ->
+                // Update UI to show GGUF metadata to user
+                Log.i(TAG, "GGUF parsed: \n$metadata")
+                withContext(Dispatchers.Main) {
+                    ggufTv.text = metadata.toString()
                 }
-            }
-        }
-        OutlinedTextField(
-            value = viewModel.message,
-            onValueChange = { viewModel.updateMessage(it) },
-            label = { Text("Message") },
-        )
-        Row {
-            Button({ viewModel.send() }) { Text("Send") }
-            Button({ viewModel.bench(8, 4, 1) }) { Text("Bench") }
-            Button({ viewModel.clear() }) { Text("Clear") }
-            Button({
-                viewModel.messages.joinToString("\n").let {
-                    clipboard.setPrimaryClip(ClipData.newPlainText("", it))
-                }
-            }) { Text("Copy") }
-        }
 
-        Column {
-            for (model in models) {
-                Downloadable.Button(viewModel, dm, model)
+                // Ensure the model file is available
+                val modelName = metadata.filename() + FILE_EXTENSION_GGUF
+                contentResolver.openInputStream(uri)?.use { input ->
+                    ensureModelFile(modelName, input)
+                }?.let { modelFile ->
+                    loadModel(modelName, modelFile)
+
+                    withContext(Dispatchers.Main) {
+                        isModelReady = true
+                        userInputEt.hint = "Type and send a message!"
+                        userInputEt.isEnabled = true
+                        userActionFab.setImageResource(R.drawable.outline_send_24)
+                        userActionFab.isEnabled = true
+                    }
+                }
             }
         }
     }
+
+    /**
+     * Prepare the model file within app's private storage
+     */
+    private suspend fun ensureModelFile(modelName: String, input: InputStream) =
+        withContext(Dispatchers.IO) {
+            File(ensureModelsDirectory(), modelName).also { file ->
+                // Copy the file into local storage if not yet done
+                if (!file.exists()) {
+                    Log.i(TAG, "Start copying file to $modelName")
+                    withContext(Dispatchers.Main) {
+                        userInputEt.hint = "Copying file..."
+                    }
+
+                    FileOutputStream(file).use { input.copyTo(it) }
+                    Log.i(TAG, "Finished copying file to $modelName")
+                } else {
+                    Log.i(TAG, "File already exists $modelName")
+                }
+            }
+        }
+
+    /**
+     * Load the model file from the app private storage
+     */
+    private suspend fun loadModel(modelName: String, modelFile: File) =
+        withContext(Dispatchers.IO) {
+            Log.i(TAG, "Loading model $modelName")
+            withContext(Dispatchers.Main) {
+                userInputEt.hint = "Loading model..."
+            }
+            engine.loadModel(modelFile.path)
+        }
+
+    /**
+     * Validate and send the user message into [InferenceEngine]
+     */
+    private fun handleUserInput() {
+        userInputEt.text.toString().also { userSsg ->
+            if (userSsg.isEmpty()) {
+                Toast.makeText(this, "Input message is empty!", Toast.LENGTH_SHORT).show()
+            } else {
+                userInputEt.text = null
+                userActionFab.isEnabled = false
+
+                // Update message states
+                messages.add(Message(UUID.randomUUID().toString(), userSsg, true))
+                lastAssistantMsg.clear()
+                messages.add(Message(UUID.randomUUID().toString(), lastAssistantMsg.toString(), false))
+
+                lifecycleScope.launch(Dispatchers.Default) {
+                    engine.sendUserPrompt(userSsg)
+                        .onCompletion {
+                            withContext(Dispatchers.Main) {
+                                userActionFab.isEnabled = true
+                            }
+                        }.collect { token ->
+                            val messageCount = messages.size
+                            check(messageCount > 0 && !messages[messageCount - 1].isUser)
+
+                            messages.removeAt(messageCount - 1).copy(
+                                content = lastAssistantMsg.append(token).toString()
+                            ).let { messages.add(it) }
+
+                            withContext(Dispatchers.Main) {
+                                messageAdapter.notifyItemChanged(messages.size - 1)
+                            }
+                        }
+                }
+            }
+        }
+    }
+
+    /**
+     * Run a benchmark with the model file
+     */
+    private suspend fun runBenchmark(modelName: String, modelFile: File) =
+        withContext(Dispatchers.Default) {
+            Log.i(TAG, "Starts benchmarking $modelName")
+            withContext(Dispatchers.Main) {
+                userInputEt.hint = "Running benchmark..."
+            }
+            engine.bench(
+                pp=BENCH_PROMPT_PROCESSING_TOKENS,
+                tg=BENCH_TOKEN_GENERATION_TOKENS,
+                pl=BENCH_SEQUENCE,
+                nr=BENCH_REPETITION
+            ).let { result ->
+                messages.add(Message(UUID.randomUUID().toString(), result, false))
+                withContext(Dispatchers.Main) {
+                    messageAdapter.notifyItemChanged(messages.size - 1)
+                }
+            }
+        }
+
+    /**
+     * Create the `models` directory if not exist.
+     */
+    private fun ensureModelsDirectory() =
+        File(filesDir, DIRECTORY_MODELS).also {
+            if (it.exists() && !it.isDirectory) { it.delete() }
+            if (!it.exists()) { it.mkdir() }
+        }
+
+    companion object {
+        private val TAG = MainActivity::class.java.simpleName
+
+        private const val DIRECTORY_MODELS = "models"
+        private const val FILE_EXTENSION_GGUF = ".gguf"
+
+        private const val BENCH_PROMPT_PROCESSING_TOKENS = 512
+        private const val BENCH_TOKEN_GENERATION_TOKENS = 128
+        private const val BENCH_SEQUENCE = 1
+        private const val BENCH_REPETITION = 3
+    }
+}
+
+fun GgufMetadata.filename() = when {
+    basic.name != null -> {
+        basic.name?.let { name ->
+            basic.sizeLabel?.let { size ->
+                "$name-$size"
+            } ?: name
+        }
+    }
+    architecture?.architecture != null -> {
+        architecture?.architecture?.let { arch ->
+            basic.uuid?.let { uuid ->
+                "$arch-$uuid"
+            } ?: "$arch-${System.currentTimeMillis()}"
+        }
+    }
+    else -> {
+        "model-${System.currentTimeMillis().toHexString()}"
+    }
 }

examples/llama.android/app/src/main/java/com/example/llama/MainViewModel.kt

@@ -1,105 +0,0 @@
-package com.example.llama
-
-import android.llama.cpp.LLamaAndroid
-import android.util.Log
-import androidx.compose.runtime.getValue
-import androidx.compose.runtime.mutableStateOf
-import androidx.compose.runtime.setValue
-import androidx.lifecycle.ViewModel
-import androidx.lifecycle.viewModelScope
-import kotlinx.coroutines.flow.catch
-import kotlinx.coroutines.launch
-
-class MainViewModel(private val llamaAndroid: LLamaAndroid = LLamaAndroid.instance()): ViewModel() {
-    companion object {
-        @JvmStatic
-        private val NanosPerSecond = 1_000_000_000.0
-    }
-
-    private val tag: String? = this::class.simpleName
-
-    var messages by mutableStateOf(listOf("Initializing..."))
-        private set
-
-    var message by mutableStateOf("")
-        private set
-
-    override fun onCleared() {
-        super.onCleared()
-
-        viewModelScope.launch {
-            try {
-                llamaAndroid.unload()
-            } catch (exc: IllegalStateException) {
-                messages += exc.message!!
-            }
-        }
-    }
-
-    fun send() {
-        val text = message
-        message = ""
-
-        // Add to messages console.
-        messages += text
-        messages += ""
-
-        viewModelScope.launch {
-            llamaAndroid.send(text)
-                .catch {
-                    Log.e(tag, "send() failed", it)
-                    messages += it.message!!
-                }
-                .collect { messages = messages.dropLast(1) + (messages.last() + it) }
-        }
-    }
-
-    fun bench(pp: Int, tg: Int, pl: Int, nr: Int = 1) {
-        viewModelScope.launch {
-            try {
-                val start = System.nanoTime()
-                val warmupResult = llamaAndroid.bench(pp, tg, pl, nr)
-                val end = System.nanoTime()
-
-                messages += warmupResult
-
-                val warmup = (end - start).toDouble() / NanosPerSecond
-                messages += "Warm up time: $warmup seconds, please wait..."
-
-                if (warmup > 5.0) {
-                    messages += "Warm up took too long, aborting benchmark"
-                    return@launch
-                }
-
-                messages += llamaAndroid.bench(512, 128, 1, 3)
-            } catch (exc: IllegalStateException) {
-                Log.e(tag, "bench() failed", exc)
-                messages += exc.message!!
-            }
-        }
-    }
-
-    fun load(pathToModel: String) {
-        viewModelScope.launch {
-            try {
-                llamaAndroid.load(pathToModel)
-                messages += "Loaded $pathToModel"
-            } catch (exc: IllegalStateException) {
-                Log.e(tag, "load() failed", exc)
-                messages += exc.message!!
-            }
-        }
-    }
-
-    fun updateMessage(newMessage: String) {
-        message = newMessage
-    }
-
-    fun clear() {
-        messages = listOf()
-    }
-
-    fun log(message: String) {
-        messages += message
-    }
-}

examples/llama.android/app/src/main/java/com/example/llama/MessageAdapter.kt

@@ -0,0 +1,51 @@
+package com.example.llama
+
+import android.view.LayoutInflater
+import android.view.View
+import android.view.ViewGroup
+import android.widget.TextView
+import androidx.recyclerview.widget.RecyclerView
+
+data class Message(
+    val id: String,
+    val content: String,
+    val isUser: Boolean
+)
+
+class MessageAdapter(
+    private val messages: List<Message>
+) : RecyclerView.Adapter<RecyclerView.ViewHolder>() {
+
+    companion object {
+        private const val VIEW_TYPE_USER = 1
+        private const val VIEW_TYPE_ASSISTANT = 2
+    }
+
+    override fun getItemViewType(position: Int): Int {
+        return if (messages[position].isUser) VIEW_TYPE_USER else VIEW_TYPE_ASSISTANT
+    }
+
+    override fun onCreateViewHolder(parent: ViewGroup, viewType: Int): RecyclerView.ViewHolder {
+        val layoutInflater = LayoutInflater.from(parent.context)
+        return if (viewType == VIEW_TYPE_USER) {
+            val view = layoutInflater.inflate(R.layout.item_message_user, parent, false)
+            UserMessageViewHolder(view)
+        } else {
+            val view = layoutInflater.inflate(R.layout.item_message_assistant, parent, false)
+            AssistantMessageViewHolder(view)
+        }
+    }
+
+    override fun onBindViewHolder(holder: RecyclerView.ViewHolder, position: Int) {
+        val message = messages[position]
+        if (holder is UserMessageViewHolder || holder is AssistantMessageViewHolder) {
+            val textView = holder.itemView.findViewById<TextView>(R.id.msg_content)
+            textView.text = message.content
+        }
+    }
+
+    override fun getItemCount(): Int = messages.size
+
+    class UserMessageViewHolder(view: View) : RecyclerView.ViewHolder(view)
+    class AssistantMessageViewHolder(view: View) : RecyclerView.ViewHolder(view)
+}

examples/llama.android/app/src/main/java/com/example/llama/ui/theme/Color.kt

@@ -1,11 +0,0 @@
-package com.example.llama.ui.theme
-
-import androidx.compose.ui.graphics.Color
-
-val Purple80 = Color(0xFFD0BCFF)
-val PurpleGrey80 = Color(0xFFCCC2DC)
-val Pink80 = Color(0xFFEFB8C8)
-
-val Purple40 = Color(0xFF6650a4)
-val PurpleGrey40 = Color(0xFF625b71)
-val Pink40 = Color(0xFF7D5260)

examples/llama.android/app/src/main/java/com/example/llama/ui/theme/Theme.kt

@@ -1,70 +0,0 @@
-package com.example.llama.ui.theme
-
-import android.app.Activity
-import android.os.Build
-import androidx.compose.foundation.isSystemInDarkTheme
-import androidx.compose.material3.MaterialTheme
-import androidx.compose.material3.darkColorScheme
-import androidx.compose.material3.dynamicDarkColorScheme
-import androidx.compose.material3.dynamicLightColorScheme
-import androidx.compose.material3.lightColorScheme
-import androidx.compose.runtime.Composable
-import androidx.compose.runtime.SideEffect
-import androidx.compose.ui.graphics.toArgb
-import androidx.compose.ui.platform.LocalContext
-import androidx.compose.ui.platform.LocalView
-import androidx.core.view.WindowCompat
-
-private val DarkColorScheme = darkColorScheme(
-    primary = Purple80,
-    secondary = PurpleGrey80,
-    tertiary = Pink80
-)
-
-private val LightColorScheme = lightColorScheme(
-    primary = Purple40,
-    secondary = PurpleGrey40,
-    tertiary = Pink40
-
-    /* Other default colors to override
-    background = Color(0xFFFFFBFE),
-    surface = Color(0xFFFFFBFE),
-    onPrimary = Color.White,
-    onSecondary = Color.White,
-    onTertiary = Color.White,
-    onBackground = Color(0xFF1C1B1F),
-    onSurface = Color(0xFF1C1B1F),
-    */
-)
-
-@Composable
-fun LlamaAndroidTheme(
-    darkTheme: Boolean = isSystemInDarkTheme(),
-    // Dynamic color is available on Android 12+
-    dynamicColor: Boolean = true,
-    content: @Composable () -> Unit
-) {
-    val colorScheme = when {
-        dynamicColor && Build.VERSION.SDK_INT >= Build.VERSION_CODES.S -> {
-            val context = LocalContext.current
-            if (darkTheme) dynamicDarkColorScheme(context) else dynamicLightColorScheme(context)
-        }
-
-        darkTheme -> DarkColorScheme
-        else -> LightColorScheme
-    }
-    val view = LocalView.current
-    if (!view.isInEditMode) {
-        SideEffect {
-            val window = (view.context as Activity).window
-            window.statusBarColor = colorScheme.primary.toArgb()
-            WindowCompat.getInsetsController(window, view).isAppearanceLightStatusBars = darkTheme
-        }
-    }
-
-    MaterialTheme(
-        colorScheme = colorScheme,
-        typography = Typography,
-        content = content
-    )
-}

examples/llama.android/app/src/main/java/com/example/llama/ui/theme/Type.kt

@@ -1,34 +0,0 @@
-package com.example.llama.ui.theme
-
-import androidx.compose.material3.Typography
-import androidx.compose.ui.text.TextStyle
-import androidx.compose.ui.text.font.FontFamily
-import androidx.compose.ui.text.font.FontWeight
-import androidx.compose.ui.unit.sp
-
-// Set of Material typography styles to start with
-val Typography = Typography(
-    bodyLarge = TextStyle(
-        fontFamily = FontFamily.Default,
-        fontWeight = FontWeight.Normal,
-        fontSize = 16.sp,
-        lineHeight = 24.sp,
-        letterSpacing = 0.5.sp
-    )
-    /* Other default text styles to override
-    titleLarge = TextStyle(
-        fontFamily = FontFamily.Default,
-        fontWeight = FontWeight.Normal,
-        fontSize = 22.sp,
-        lineHeight = 28.sp,
-        letterSpacing = 0.sp
-    ),
-    labelSmall = TextStyle(
-        fontFamily = FontFamily.Default,
-        fontWeight = FontWeight.Medium,
-        fontSize = 11.sp,
-        lineHeight = 16.sp,
-        letterSpacing = 0.5.sp
-    )
-    */
-)

examples/llama.android/app/src/main/res/drawable/bg_assistant_message.xml

@@ -0,0 +1,4 @@
+<shape xmlns:android="http://schemas.android.com/apk/res/android" android:shape="rectangle">
+    <solid android:color="#E5E5EA" />
+    <corners android:radius="16dp" />
+</shape>

examples/llama.android/app/src/main/res/drawable/bg_user_message.xml

@@ -0,0 +1,4 @@
+<shape xmlns:android="http://schemas.android.com/apk/res/android" android:shape="rectangle">
+    <solid android:color="#4285F4" />
+    <corners android:radius="16dp" />
+</shape>

examples/llama.android/app/src/main/res/drawable/outline_folder_open_24.xml

@@ -0,0 +1,10 @@
+<vector xmlns:android="http://schemas.android.com/apk/res/android"
+    android:width="24dp"
+    android:height="24dp"
+    android:viewportWidth="24"
+    android:viewportHeight="24"
+    android:tint="?attr/colorControlNormal">
+  <path
+      android:fillColor="@android:color/white"
+      android:pathData="M20,6h-8l-2,-2L4,4c-1.1,0 -1.99,0.9 -1.99,2L2,18c0,1.1 0.9,2 2,2h16c1.1,0 2,-0.9 2,-2L22,8c0,-1.1 -0.9,-2 -2,-2zM20,18L4,18L4,8h16v10z"/>
+</vector>

examples/llama.android/app/src/main/res/drawable/outline_send_24.xml

@@ -0,0 +1,11 @@
+<vector xmlns:android="http://schemas.android.com/apk/res/android"
+    android:width="24dp"
+    android:height="24dp"
+    android:viewportWidth="24"
+    android:viewportHeight="24"
+    android:tint="?attr/colorControlNormal"
+    android:autoMirrored="true">
+  <path
+      android:fillColor="@android:color/white"
+      android:pathData="M4.01,6.03l7.51,3.22 -7.52,-1 0.01,-2.22m7.5,8.72L4,17.97v-2.22l7.51,-1M2.01,3L2,10l15,2 -15,2 0.01,7L23,12 2.01,3z"/>
+</vector>

examples/llama.android/app/src/main/res/layout/activity_main.xml

@@ -0,0 +1,78 @@
+<?xml version="1.0" encoding="utf-8"?>
+<androidx.constraintlayout.widget.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
+    xmlns:app="http://schemas.android.com/apk/res-auto"
+    xmlns:tools="http://schemas.android.com/tools"
+    android:id="@+id/main"
+    android:layout_height="match_parent"
+    android:layout_width="match_parent">
+
+    <LinearLayout
+        android:fitsSystemWindows="true"
+        android:layout_width="match_parent"
+        android:layout_height="match_parent"
+        android:orientation="vertical"
+        android:layout_marginEnd="4dp"
+        tools:context=".MainActivity">
+
+        <ScrollView
+            android:layout_width="match_parent"
+            android:layout_height="0dp"
+            android:layout_weight="1"
+            android:fadeScrollbars="false">
+
+            <TextView
+                android:id="@+id/gguf"
+                android:layout_width="match_parent"
+                android:layout_height="wrap_content"
+                android:layout_margin="16dp"
+                android:text="Selected GGUF model's metadata will show here."
+                style="@style/TextAppearance.MaterialComponents.Body2" />
+
+        </ScrollView>
+
+        <com.google.android.material.divider.MaterialDivider
+            android:layout_width="match_parent"
+            android:layout_height="2dp"
+            android:layout_marginHorizontal="16dp"
+            android:layout_marginVertical="8dp" />
+
+        <androidx.recyclerview.widget.RecyclerView
+            android:id="@+id/messages"
+            android:layout_width="match_parent"
+            android:layout_height="0dp"
+            android:layout_weight="4"
+            android:fadeScrollbars="false"
+            android:scrollbars="vertical"
+            app:reverseLayout="true"
+            tools:listitem="@layout/item_message_assistant"/>
+
+        <LinearLayout
+            android:layout_width="match_parent"
+            android:layout_height="wrap_content"
+            android:orientation="horizontal"
+            android:paddingStart="16dp"
+            android:paddingEnd="4dp">
+
+            <EditText
+                android:id="@+id/user_input"
+                android:enabled="false"
+                android:layout_width="0dp"
+                android:layout_weight="1"
+                android:layout_height="match_parent"
+                android:padding="8dp"
+                style="@style/TextAppearance.MaterialComponents.Body2"
+                android:hint="Please first pick a GGUF model file to import." />
+
+            <com.google.android.material.floatingactionbutton.FloatingActionButton
+                android:id="@+id/fab"
+                android:enabled="true"
+                style="@style/Widget.Material3.FloatingActionButton.Primary"
+                android:layout_width="wrap_content"
+                android:layout_height="wrap_content"
+                android:layout_margin="12dp"
+                android:src="@drawable/outline_folder_open_24" />
+
+        </LinearLayout>
+
+    </LinearLayout>
+</androidx.constraintlayout.widget.ConstraintLayout>

examples/llama.android/app/src/main/res/layout/item_message_assistant.xml

@@ -0,0 +1,16 @@
+<?xml version="1.0" encoding="utf-8"?>
+<LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
+    android:layout_width="match_parent"
+    android:layout_height="wrap_content"
+    android:layout_marginHorizontal="16dp"
+    android:layout_marginVertical="8dp"
+    android:gravity="start">
+
+    <TextView
+        android:id="@+id/msg_content"
+        android:layout_width="wrap_content"
+        android:layout_height="wrap_content"
+        android:background="@drawable/bg_assistant_message"
+        android:padding="12dp"
+        android:textColor="@android:color/black" />
+</LinearLayout>

examples/llama.android/app/src/main/res/layout/item_message_user.xml

@@ -0,0 +1,16 @@
+<?xml version="1.0" encoding="utf-8"?>
+<LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
+    android:layout_width="match_parent"
+    android:layout_height="wrap_content"
+    android:layout_marginHorizontal="16dp"
+    android:layout_marginVertical="8dp"
+    android:gravity="end">
+
+    <TextView
+        android:id="@+id/msg_content"
+        android:layout_width="wrap_content"
+        android:layout_height="wrap_content"
+        android:background="@drawable/bg_user_message"
+        android:padding="12dp"
+        android:textColor="@android:color/white" />
+</LinearLayout>

examples/llama.android/app/src/main/res/values/strings.xml

@@ -1,3 +1,3 @@
 <resources>
-    <string name="app_name">LlamaAndroid</string>
+    <string name="app_name">AI Chat basic sample</string>
 </resources>

examples/llama.android/app/src/main/res/values/themes.xml

@@ -1,5 +1,10 @@
 <?xml version="1.0" encoding="utf-8"?>
 <resources>
 
-    <style name="Theme.LlamaAndroid" parent="android:Theme.Material.Light.NoActionBar" />
+    <style name="Base.Theme.AiChatSample" parent="Theme.Material3.DayNight.NoActionBar">
+        <!-- Customize your light theme here. -->
+        <!-- <item name="colorPrimary">@color/my_light_primary</item> -->
+    </style>
+
+    <style name="Theme.AiChatSample" parent="Base.Theme.AiChatSample" />
 </resources>

examples/llama.android/build.gradle.kts

@@ -1,6 +1,6 @@
 // Top-level build file where you can add configuration options common to all sub-projects/modules.
 plugins {
-    id("com.android.application") version "8.2.0" apply false
-    id("org.jetbrains.kotlin.android") version "1.9.0" apply false
-    id("com.android.library") version "8.2.0" apply false
+    alias(libs.plugins.android.application) apply false
+    alias(libs.plugins.android.library) apply false
+    alias(libs.plugins.jetbrains.kotlin.android) apply false
 }

examples/llama.android/gradle.properties

@@ -21,3 +21,4 @@ kotlin.code.style=official
 # resources declared in the library itself and none from the library's dependencies,
 # thereby reducing the size of the R class for that library
 android.nonTransitiveRClass=true
+android.native.buildOutput=verbose

examples/llama.android/gradle/libs.versions.toml

@@ -0,0 +1,53 @@
+[versions]
+
+# Plugins
+agp = "8.13.0"
+kotlin = "2.2.20"
+
+# AndroidX
+activity = "1.11.0"
+appcompat = "1.7.1"
+core-ktx = "1.17.0"
+constraint-layout = "2.2.1"
+datastore-preferences = "1.1.7"
+
+# Material
+material = "1.13.0"
+
+# Testing
+espresso-core = "3.7.0"
+androidx-junit = "1.3.0"
+junit = "4.13.2"
+
+
+[plugins]
+android-application = { id = "com.android.application", version.ref = "agp" }
+android-library = { id = "com.android.library", version.ref = "agp" }
+jetbrains-kotlin-android = { id = "org.jetbrains.kotlin.android", version.ref = "kotlin" }
+
+
+[libraries]
+
+# AndroidX
+androidx-activity = { group = "androidx.activity", name = "activity", version.ref = "activity" }
+androidx-appcompat = { group = "androidx.appcompat", name = "appcompat", version.ref = "appcompat" }
+androidx-constraintlayout = { group = "androidx.constraintlayout", name = "constraintlayout", version.ref = "constraint-layout" }
+androidx-core-ktx = { group = "androidx.core", name = "core-ktx", version.ref = "core-ktx" }
+androidx-datastore-preferences = { group = "androidx.datastore", name = "datastore-preferences", version.ref = "datastore-preferences" }
+
+#Material
+material = { group = "com.google.android.material", name = "material", version.ref = "material" }
+
+# Testing
+androidx-espresso-core = { group = "androidx.test.espresso", name = "espresso-core", version.ref = "espresso-core" }
+androidx-junit = { group = "androidx.test.ext", name = "junit", version.ref = "androidx-junit" }
+junit = { group = "junit", name = "junit", version.ref = "junit" }
+
+[bundles]
+androidx = [
+    "androidx-activity",
+    "androidx-appcompat",
+    "androidx-constraintlayout",
+    "androidx-core-ktx",
+    "androidx-datastore-preferences",
+]

examples/llama.android/gradle/wrapper/gradle-wrapper.properties

@@ -1,6 +1,6 @@
-#Thu Dec 21 14:31:09 AEDT 2023
+#Tue Apr 01 11:15:06 PDT 2025
 distributionBase=GRADLE_USER_HOME
 distributionPath=wrapper/dists
-distributionUrl=https\://services.gradle.org/distributions/gradle-8.2-bin.zip
+distributionUrl=https\://services.gradle.org/distributions/gradle-8.14.3-bin.zip
 zipStoreBase=GRADLE_USER_HOME
 zipStorePath=wrapper/dists

examples/llama.android/lib/build.gradle.kts

@@ -0,0 +1,78 @@
+plugins {
+    alias(libs.plugins.android.library)
+    alias(libs.plugins.jetbrains.kotlin.android)
+}
+
+android {
+    namespace = "com.arm.aichat"
+    compileSdk = 36
+
+    ndkVersion = "29.0.13113456"
+
+    defaultConfig {
+        minSdk = 33
+
+        testInstrumentationRunner = "androidx.test.runner.AndroidJUnitRunner"
+        consumerProguardFiles("consumer-rules.pro")
+
+        ndk {
+             abiFilters += listOf("arm64-v8a", "x86_64")
+        }
+        externalNativeBuild {
+            cmake {
+                arguments += "-DCMAKE_BUILD_TYPE=Release"
+                arguments += "-DCMAKE_MESSAGE_LOG_LEVEL=DEBUG"
+                arguments += "-DCMAKE_VERBOSE_MAKEFILE=ON"
+
+                arguments += "-DBUILD_SHARED_LIBS=ON"
+                arguments += "-DLLAMA_BUILD_COMMON=ON"
+                arguments += "-DLLAMA_CURL=OFF"
+
+                arguments += "-DGGML_NATIVE=OFF"
+                arguments += "-DGGML_BACKEND_DL=ON"
+                arguments += "-DGGML_CPU_ALL_VARIANTS=ON"
+                arguments += "-DGGML_LLAMAFILE=OFF"
+            }
+        }
+        aarMetadata {
+            minCompileSdk = 35
+        }
+    }
+    externalNativeBuild {
+        cmake {
+            path("src/main/cpp/CMakeLists.txt")
+            version = "3.31.6"
+        }
+    }
+    compileOptions {
+        sourceCompatibility = JavaVersion.VERSION_17
+        targetCompatibility = JavaVersion.VERSION_17
+    }
+    kotlin {
+        jvmToolchain(17)
+
+        compileOptions {
+            targetCompatibility = JavaVersion.VERSION_17
+        }
+    }
+
+    packaging {
+        resources {
+            excludes += "/META-INF/{AL2.0,LGPL2.1}"
+        }
+    }
+
+    publishing {
+        singleVariant("release") {
+            withJavadocJar()
+        }
+    }
+}
+
+dependencies {
+    implementation(libs.androidx.core.ktx)
+    implementation(libs.androidx.datastore.preferences)
+
+    testImplementation(libs.junit)
+    androidTestImplementation(libs.androidx.junit)
+}

examples/llama.android/lib/consumer-rules.pro

@@ -0,0 +1,8 @@
+-keep class com.arm.aichat.* { *; }
+-keep class com.arm.aichat.gguf.* { *; }
+
+-keepclasseswithmembernames class * {
+    native <methods>;
+}
+
+-keep class kotlin.Metadata { *; }

examples/llama.android/lib/src/main/cpp/CMakeLists.txt

@@ -0,0 +1,56 @@
+cmake_minimum_required(VERSION 3.31.6)
+
+project("ai-chat" VERSION 1.0.0 LANGUAGES C CXX)
+
+set(CMAKE_C_STANDARD 11)
+set(CMAKE_C_STANDARD_REQUIRED true)
+
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CXX_STANDARD_REQUIRED true)
+
+set(CMAKE_C_FLAGS   "${CMAKE_C_FLAGS}"   CACHE STRING "" FORCE)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}" CACHE STRING "" FORCE)
+
+# --------------------------------------------------------------------------
+# AI Chat library
+# --------------------------------------------------------------------------
+
+if(DEFINED ANDROID_ABI)
+    message(STATUS "Detected Android ABI: ${ANDROID_ABI}")
+    if(ANDROID_ABI STREQUAL "arm64-v8a")
+        set(GGML_SYSTEM_ARCH "ARM")
+        set(GGML_CPU_KLEIDIAI ON)
+        set(GGML_OPENMP ON)
+    elseif(ANDROID_ABI STREQUAL "x86_64")
+        set(GGML_SYSTEM_ARCH "x86")
+        set(GGML_CPU_KLEIDIAI OFF)
+        set(GGML_OPENMP OFF)
+    else()
+        message(FATAL_ERROR "Unsupported ABI: ${ANDROID_ABI}")
+    endif()
+endif()
+
+set(LLAMA_SRC ${CMAKE_CURRENT_LIST_DIR}/../../../../../../)
+add_subdirectory(${LLAMA_SRC} build-llama)
+
+add_library(${CMAKE_PROJECT_NAME} SHARED
+        ai_chat.cpp)
+
+target_compile_definitions(${CMAKE_PROJECT_NAME} PRIVATE
+        GGML_SYSTEM_ARCH=${GGML_SYSTEM_ARCH}
+        GGML_CPU_KLEIDIAI=$<BOOL:${GGML_CPU_KLEIDIAI}>
+        GGML_OPENMP=$<BOOL:${GGML_OPENMP}>
+)
+
+target_include_directories(${CMAKE_PROJECT_NAME} PRIVATE
+        ${LLAMA_SRC}
+        ${LLAMA_SRC}/common
+        ${LLAMA_SRC}/include
+        ${LLAMA_SRC}/ggml/include
+        ${LLAMA_SRC}/ggml/src)
+
+target_link_libraries(${CMAKE_PROJECT_NAME}
+        llama
+        common
+        android
+        log)

examples/llama.android/lib/src/main/cpp/ai_chat.cpp

@@ -0,0 +1,565 @@
+#include <android/log.h>
+#include <jni.h>
+#include <iomanip>
+#include <cmath>
+#include <string>
+#include <unistd.h>
+#include <sampling.h>
+
+#include "logging.h"
+#include "chat.h"
+#include "common.h"
+#include "llama.h"
+
+template<class T>
+static std::string join(const std::vector<T> &values, const std::string &delim) {
+    std::ostringstream str;
+    for (size_t i = 0; i < values.size(); i++) {
+        str << values[i];
+        if (i < values.size() - 1) { str << delim; }
+    }
+    return str.str();
+}
+
+/**
+ * LLama resources: context, model, batch and sampler
+ */
+constexpr int   N_THREADS_MIN           = 2;
+constexpr int   N_THREADS_MAX           = 4;
+constexpr int   N_THREADS_HEADROOM      = 2;
+
+constexpr int   DEFAULT_CONTEXT_SIZE    = 8192;
+constexpr int   OVERFLOW_HEADROOM       = 4;
+constexpr int   BATCH_SIZE              = 512;
+constexpr float DEFAULT_SAMPLER_TEMP    = 0.3f;
+
+static llama_model                      * g_model;
+static llama_context                    * g_context;
+static llama_batch                        g_batch;
+static common_chat_templates_ptr          g_chat_templates;
+static common_sampler                   * g_sampler;
+
+extern "C"
+JNIEXPORT void JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_init(JNIEnv *env, jobject /*unused*/, jstring nativeLibDir) {
+    // Set llama log handler to Android
+    llama_log_set(aichat_android_log_callback, nullptr);
+
+    // Loading all CPU backend variants
+    const auto *path_to_backend = env->GetStringUTFChars(nativeLibDir, 0);
+    LOGi("Loading backends from %s", path_to_backend);
+    ggml_backend_load_all_from_path(path_to_backend);
+    env->ReleaseStringUTFChars(nativeLibDir, path_to_backend);
+
+    // Initialize backends
+    llama_backend_init();
+    LOGi("Backend initiated; Log handler set.");
+}
+
+extern "C"
+JNIEXPORT jint JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_load(JNIEnv *env, jobject, jstring jmodel_path) {
+    llama_model_params model_params = llama_model_default_params();
+
+    const auto *model_path = env->GetStringUTFChars(jmodel_path, 0);
+    LOGd("%s: Loading model from: \n%s\n", __func__, model_path);
+
+    auto *model = llama_model_load_from_file(model_path, model_params);
+    env->ReleaseStringUTFChars(jmodel_path, model_path);
+    if (!model) {
+        return 1;
+    }
+    g_model = model;
+    return 0;
+}
+
+static llama_context *init_context(llama_model *model, const int n_ctx = DEFAULT_CONTEXT_SIZE) {
+    if (!model) {
+        LOGe("%s: model cannot be null", __func__);
+        return nullptr;
+    }
+
+    // Multi-threading setup
+    const int n_threads = std::max(N_THREADS_MIN, std::min(N_THREADS_MAX,
+                                                     (int) sysconf(_SC_NPROCESSORS_ONLN) -
+                                                     N_THREADS_HEADROOM));
+    LOGi("%s: Using %d threads", __func__, n_threads);
+
+    // Context parameters setup
+    llama_context_params ctx_params = llama_context_default_params();
+    const int trained_context_size = llama_model_n_ctx_train(model);
+    if (n_ctx > trained_context_size) {
+        LOGw("%s: Model was trained with only %d context size! Enforcing %d context size...",
+             __func__, trained_context_size, n_ctx);
+    }
+    ctx_params.n_ctx = n_ctx;
+    ctx_params.n_batch = BATCH_SIZE;
+    ctx_params.n_ubatch = BATCH_SIZE;
+    ctx_params.n_threads = n_threads;
+    ctx_params.n_threads_batch = n_threads;
+    auto *context = llama_init_from_model(g_model, ctx_params);
+    if (context == nullptr) {
+        LOGe("%s: llama_new_context_with_model() returned null)", __func__);
+    }
+    return context;
+}
+
+static common_sampler *new_sampler(float temp) {
+    common_params_sampling sparams;
+    sparams.temp = temp;
+    return common_sampler_init(g_model, sparams);
+}
+
+extern "C"
+JNIEXPORT jint JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_prepare(JNIEnv * /*env*/, jobject /*unused*/) {
+    auto *context = init_context(g_model);
+    if (!context) { return 1; }
+    g_context = context;
+    g_batch = llama_batch_init(BATCH_SIZE, 0, 1);
+    g_chat_templates = common_chat_templates_init(g_model, "");
+    g_sampler = new_sampler(DEFAULT_SAMPLER_TEMP);
+    return 0;
+}
+
+static std::string get_backend() {
+    std::vector<std::string> backends;
+    for (size_t i = 0; i < ggml_backend_reg_count(); i++) {
+        auto *reg = ggml_backend_reg_get(i);
+        std::string name = ggml_backend_reg_name(reg);
+        if (name != "CPU") {
+            backends.push_back(ggml_backend_reg_name(reg));
+        }
+    }
+    return backends.empty() ? "CPU" : join(backends, ",");
+}
+
+extern "C"
+JNIEXPORT jstring JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_systemInfo(JNIEnv *env, jobject /*unused*/) {
+    return env->NewStringUTF(llama_print_system_info());
+}
+
+extern "C"
+JNIEXPORT jstring JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_benchModel(JNIEnv *env, jobject /*unused*/, jint pp, jint tg,
+                                                      jint pl, jint nr) {
+    auto *context = init_context(g_model, pp);
+    if (!context) {
+        const auto *const err_msg = "Fail to init_context! Bench aborted.";
+        LOGe(err_msg);
+        return env->NewStringUTF(err_msg);
+    }
+
+    auto pp_avg = 0.0;
+    auto tg_avg = 0.0;
+    auto pp_std = 0.0;
+    auto tg_std = 0.0;
+
+    const uint32_t n_ctx = llama_n_ctx(context);
+    LOGi("n_ctx = %d", n_ctx);
+
+    int i, j;
+    int nri;
+    for (nri = 0; nri < nr; nri++) {
+        LOGi("Benchmark prompt processing (pp = %d)", pp);
+
+        common_batch_clear(g_batch);
+
+        const int n_tokens = pp;
+        for (i = 0; i < n_tokens; i++) {
+            common_batch_add(g_batch, 0, i, {0}, false);
+        }
+
+        g_batch.logits[g_batch.n_tokens - 1] = true;
+        llama_memory_clear(llama_get_memory(context), false);
+
+        const auto t_pp_start = ggml_time_us();
+        if (llama_decode(context, g_batch) != 0) {
+            LOGe("llama_decode() failed during prompt processing");
+        }
+        const auto t_pp_end = ggml_time_us();
+
+        // bench text generation
+
+        LOGi("Benchmark text generation (tg = %d)", tg);
+
+        llama_memory_clear(llama_get_memory(context), false);
+        const auto t_tg_start = ggml_time_us();
+        for (i = 0; i < tg; i++) {
+            common_batch_clear(g_batch);
+            for (j = 0; j < pl; j++) {
+                common_batch_add(g_batch, 0, i, {j}, true);
+            }
+
+            if (llama_decode(context, g_batch) != 0) {
+                LOGe("llama_decode() failed during text generation");
+            }
+        }
+        const auto t_tg_end = ggml_time_us();
+
+        llama_memory_clear(llama_get_memory(context), false);
+
+        const auto t_pp = double(t_pp_end - t_pp_start) / 1000000.0;
+        const auto t_tg = double(t_tg_end - t_tg_start) / 1000000.0;
+
+        const auto speed_pp = double(pp) / t_pp;
+        const auto speed_tg = double(pl * tg) / t_tg;
+
+        pp_avg += speed_pp;
+        tg_avg += speed_tg;
+
+        pp_std += speed_pp * speed_pp;
+        tg_std += speed_tg * speed_tg;
+
+        LOGi("pp %f t/s, tg %f t/s", speed_pp, speed_tg);
+    }
+
+    llama_free(context);
+
+    pp_avg /= double(nr);
+    tg_avg /= double(nr);
+
+    if (nr > 1) {
+        pp_std = sqrt(pp_std / double(nr - 1) - pp_avg * pp_avg * double(nr) / double(nr - 1));
+        tg_std = sqrt(tg_std / double(nr - 1) - tg_avg * tg_avg * double(nr) / double(nr - 1));
+    } else {
+        pp_std = 0;
+        tg_std = 0;
+    }
+
+    char model_desc[128];
+    llama_model_desc(g_model, model_desc, sizeof(model_desc));
+
+    const auto model_size = double(llama_model_size(g_model)) / 1024.0 / 1024.0 / 1024.0;
+    const auto model_n_params = double(llama_model_n_params(g_model)) / 1e9;
+
+    const auto backend = get_backend();
+    std::stringstream result;
+    result << std::setprecision(3);
+    result << "| model | size | params | backend | test | t/s |\n";
+    result << "| --- | --- | --- | --- | --- | --- |\n";
+    result << "| " << model_desc << " | " << model_size << "GiB | " << model_n_params << "B | "
+           << backend << " | pp " << pp << " | " << pp_avg << " ± " << pp_std << " |\n";
+    result << "| " << model_desc << " | " << model_size << "GiB | " << model_n_params << "B | "
+           << backend << " | tg " << tg << " | " << tg_avg << " ± " << tg_std << " |\n";
+    return env->NewStringUTF(result.str().c_str());
+}
+
+
+/**
+ * Completion loop's long-term states:
+ * - chat management
+ * - position tracking
+ */
+constexpr const char *ROLE_SYSTEM       = "system";
+constexpr const char *ROLE_USER         = "user";
+constexpr const char *ROLE_ASSISTANT    = "assistant";
+
+static std::vector<common_chat_msg> chat_msgs;
+static llama_pos system_prompt_position;
+static llama_pos current_position;
+
+static void reset_long_term_states(const bool clear_kv_cache = true) {
+    chat_msgs.clear();
+    system_prompt_position = 0;
+    current_position = 0;
+
+    if (clear_kv_cache)
+        llama_memory_clear(llama_get_memory(g_context), false);
+}
+
+/**
+ * TODO-hyin: implement sliding-window version as a better alternative
+ *
+ * Context shifting by discarding the older half of the tokens appended after system prompt:
+ * - take the [system_prompt_position] first tokens from the original prompt
+ * - take half of the last (system_prompt_position - system_prompt_position) tokens
+ * - recompute the logits in batches
+ */
+static void shift_context() {
+    const int n_discard = (current_position - system_prompt_position) / 2;
+    LOGi("%s: Discarding %d tokens", __func__, n_discard);
+    llama_memory_seq_rm(llama_get_memory(g_context), 0, system_prompt_position, system_prompt_position + n_discard);
+    llama_memory_seq_add(llama_get_memory(g_context), 0, system_prompt_position + n_discard, current_position, -n_discard);
+    current_position -= n_discard;
+    LOGi("%s: Context shifting done! Current position: %d", __func__, current_position);
+}
+
+static std::string chat_add_and_format(const std::string &role, const std::string &content) {
+    common_chat_msg new_msg;
+    new_msg.role = role;
+    new_msg.content = content;
+    auto formatted = common_chat_format_single(
+            g_chat_templates.get(), chat_msgs, new_msg, role == ROLE_USER, /* use_jinja */ false);
+    chat_msgs.push_back(new_msg);
+    LOGi("%s: Formatted and added %s message: \n%s\n", __func__, role.c_str(), formatted.c_str());
+    return formatted;
+}
+
+/**
+ * Completion loop's short-term states:
+ * - stop generation position
+ * - token chars caching
+ * - current assistant message being generated
+ */
+static llama_pos stop_generation_position;
+static std::string cached_token_chars;
+static std::ostringstream assistant_ss;
+
+static void reset_short_term_states() {
+    stop_generation_position = 0;
+    cached_token_chars.clear();
+    assistant_ss.str("");
+}
+
+static int decode_tokens_in_batches(
+        llama_context *context,
+        llama_batch &batch,
+        const llama_tokens &tokens,
+        const llama_pos start_pos,
+        const bool compute_last_logit = false) {
+    // Process tokens in batches using the global batch
+    LOGd("%s: Decode %d tokens starting at position %d", __func__, (int) tokens.size(), start_pos);
+    for (int i = 0; i < (int) tokens.size(); i += BATCH_SIZE) {
+        const int cur_batch_size = std::min((int) tokens.size() - i, BATCH_SIZE);
+        common_batch_clear(batch);
+        LOGv("%s: Preparing a batch size of %d starting at: %d", __func__, cur_batch_size, i);
+
+        // Shift context if current batch cannot fit into the context
+        if (start_pos + i + cur_batch_size >= DEFAULT_CONTEXT_SIZE - OVERFLOW_HEADROOM) {
+            LOGw("%s: Current batch won't fit into context! Shifting...", __func__);
+            shift_context();
+        }
+
+        // Add tokens to the batch with proper positions
+        for (int j = 0; j < cur_batch_size; j++) {
+            const llama_token token_id = tokens[i + j];
+            const llama_pos position = start_pos + i + j;
+            const bool want_logit = compute_last_logit && (i + j == tokens.size() - 1);
+            common_batch_add(batch, token_id, position, {0}, want_logit);
+        }
+
+        // Decode this batch
+        const int decode_result = llama_decode(context, batch);
+        if (decode_result) {
+            LOGe("%s: llama_decode failed w/ %d", __func__, decode_result);
+            return 1;
+        }
+    }
+    return 0;
+}
+
+extern "C"
+JNIEXPORT jint JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_processSystemPrompt(
+        JNIEnv *env,
+        jobject /*unused*/,
+        jstring jsystem_prompt
+) {
+    // Reset long-term & short-term states
+    reset_long_term_states();
+    reset_short_term_states();
+
+    // Obtain system prompt from JEnv
+    const auto *system_prompt = env->GetStringUTFChars(jsystem_prompt, nullptr);
+    LOGd("%s: System prompt received: \n%s", __func__, system_prompt);
+    std::string formatted_system_prompt(system_prompt);
+    env->ReleaseStringUTFChars(jsystem_prompt, system_prompt);
+
+    // Format system prompt if applicable
+    const bool has_chat_template = common_chat_templates_was_explicit(g_chat_templates.get());
+    if (has_chat_template) {
+        formatted_system_prompt = chat_add_and_format(ROLE_SYSTEM, system_prompt);
+    }
+
+    // Tokenize system prompt
+    const auto system_tokens = common_tokenize(g_context, formatted_system_prompt,
+                                               has_chat_template, has_chat_template);
+    for (auto id: system_tokens) {
+        LOGv("token: `%s`\t -> `%d`", common_token_to_piece(g_context, id).c_str(), id);
+    }
+
+    // Handle context overflow
+    const int max_batch_size = DEFAULT_CONTEXT_SIZE - OVERFLOW_HEADROOM;
+    if ((int) system_tokens.size() > max_batch_size) {
+        LOGe("%s: System prompt too long for context! %d tokens, max: %d",
+             __func__, (int) system_tokens.size(), max_batch_size);
+        return 1;
+    }
+
+    // Decode system tokens in batches
+    if (decode_tokens_in_batches(g_context, g_batch, system_tokens, current_position)) {
+        LOGe("%s: llama_decode() failed!", __func__);
+        return 2;
+    }
+
+    // Update position
+    system_prompt_position = current_position = (int) system_tokens.size();
+    return 0;
+}
+
+extern "C"
+JNIEXPORT jint JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_processUserPrompt(
+        JNIEnv *env,
+        jobject /*unused*/,
+        jstring juser_prompt,
+        jint n_predict
+) {
+    // Reset short-term states
+    reset_short_term_states();
+
+    // Obtain and tokenize user prompt
+    const auto *const user_prompt = env->GetStringUTFChars(juser_prompt, nullptr);
+    LOGd("%s: User prompt received: \n%s", __func__, user_prompt);
+    std::string formatted_user_prompt(user_prompt);
+    env->ReleaseStringUTFChars(juser_prompt, user_prompt);
+
+    // Format user prompt if applicable
+    const bool has_chat_template = common_chat_templates_was_explicit(g_chat_templates.get());
+    if (has_chat_template) {
+        formatted_user_prompt = chat_add_and_format(ROLE_USER, user_prompt);
+    }
+
+    // Decode formatted user prompts
+    auto user_tokens = common_tokenize(g_context, formatted_user_prompt, has_chat_template, has_chat_template);
+    for (auto id: user_tokens) {
+        LOGv("token: `%s`\t -> `%d`", common_token_to_piece(g_context, id).c_str(), id);
+    }
+
+    // Ensure user prompt doesn't exceed the context size by truncating if necessary.
+    const int user_prompt_size = (int) user_tokens.size();
+    const int max_batch_size = DEFAULT_CONTEXT_SIZE - OVERFLOW_HEADROOM;
+    if (user_prompt_size > max_batch_size) {
+        const int skipped_tokens = user_prompt_size - max_batch_size;
+        user_tokens.resize(max_batch_size);
+        LOGw("%s: User prompt too long! Skipped %d tokens!", __func__, skipped_tokens);
+    }
+
+    // Decode user tokens in batches
+    if (decode_tokens_in_batches(g_context, g_batch, user_tokens, current_position, true)) {
+        LOGe("%s: llama_decode() failed!", __func__);
+        return 2;
+    }
+
+    // Update position
+    current_position += user_prompt_size;
+    stop_generation_position = current_position + user_prompt_size + n_predict;
+    return 0;
+}
+
+static bool is_valid_utf8(const char *string) {
+    if (!string) { return true; }
+
+    const auto *bytes = (const unsigned char *) string;
+    int num;
+
+    while (*bytes != 0x00) {
+        if ((*bytes & 0x80) == 0x00) {
+            // U+0000 to U+007F
+            num = 1;
+        } else if ((*bytes & 0xE0) == 0xC0) {
+            // U+0080 to U+07FF
+            num = 2;
+        } else if ((*bytes & 0xF0) == 0xE0) {
+            // U+0800 to U+FFFF
+            num = 3;
+        } else if ((*bytes & 0xF8) == 0xF0) {
+            // U+10000 to U+10FFFF
+            num = 4;
+        } else {
+            return false;
+        }
+
+        bytes += 1;
+        for (int i = 1; i < num; ++i) {
+            if ((*bytes & 0xC0) != 0x80) {
+                return false;
+            }
+            bytes += 1;
+        }
+    }
+    return true;
+}
+
+extern "C"
+JNIEXPORT jstring JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_generateNextToken(
+        JNIEnv *env,
+        jobject /*unused*/
+) {
+    // Infinite text generation via context shifting
+    if (current_position >= DEFAULT_CONTEXT_SIZE - OVERFLOW_HEADROOM) {
+        LOGw("%s: Context full! Shifting...", __func__);
+        shift_context();
+    }
+
+    // Stop if reaching the marked position
+    if (current_position >= stop_generation_position) {
+        LOGw("%s: STOP: hitting stop position: %d", __func__, stop_generation_position);
+        return nullptr;
+    }
+
+    // Sample next token
+    const auto new_token_id = common_sampler_sample(g_sampler, g_context, -1);
+    common_sampler_accept(g_sampler, new_token_id, true);
+
+    // Populate the batch with new token, then decode
+    common_batch_clear(g_batch);
+    common_batch_add(g_batch, new_token_id, current_position, {0}, true);
+    if (llama_decode(g_context, g_batch) != 0) {
+        LOGe("%s: llama_decode() failed for generated token", __func__);
+        return nullptr;
+    }
+
+    // Update position
+    current_position++;
+
+    // Stop if next token is EOG
+    if (llama_vocab_is_eog(llama_model_get_vocab(g_model), new_token_id)) {
+        LOGd("id: %d,\tIS EOG!\nSTOP.", new_token_id);
+        chat_add_and_format(ROLE_ASSISTANT, assistant_ss.str());
+        return nullptr;
+    }
+
+    // If not EOG, convert to text
+    auto new_token_chars = common_token_to_piece(g_context, new_token_id);
+    cached_token_chars += new_token_chars;
+
+    // Create and return a valid UTF-8 Java string
+    jstring result = nullptr;
+    if (is_valid_utf8(cached_token_chars.c_str())) {
+        result = env->NewStringUTF(cached_token_chars.c_str());
+        LOGv("id: %d,\tcached: `%s`,\tnew: `%s`", new_token_id, cached_token_chars.c_str(), new_token_chars.c_str());
+
+        assistant_ss << cached_token_chars;
+        cached_token_chars.clear();
+    } else {
+        LOGv("id: %d,\tappend to cache", new_token_id);
+        result = env->NewStringUTF("");
+    }
+    return result;
+}
+
+
+extern "C"
+JNIEXPORT void JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_unload(JNIEnv * /*unused*/, jobject /*unused*/) {
+    // Reset long-term & short-term states
+    reset_long_term_states();
+    reset_short_term_states();
+
+    // Free up resources
+    common_sampler_free(g_sampler);
+    g_chat_templates.reset();
+    llama_batch_free(g_batch);
+    llama_free(g_context);
+    llama_model_free(g_model);
+}
+
+extern "C"
+JNIEXPORT void JNICALL
+Java_com_arm_aichat_internal_InferenceEngineImpl_shutdown(JNIEnv *env, jobject /*unused*/) {
+    llama_backend_free();
+}

examples/llama.android/lib/src/main/cpp/logging.h

@@ -0,0 +1,61 @@
+//
+// Created by Han Yin on 10/31/25.
+//
+
+#ifndef AICHAT_LOGGING_H
+#define AICHAT_LOGGING_H
+
+#endif //AICHAT_LOGGING_H
+
+#pragma once
+#include <android/log.h>
+
+#ifndef LOG_TAG
+#define LOG_TAG "ai-chat"
+#endif
+
+#ifndef LOG_MIN_LEVEL
+#if defined(NDEBUG)
+#define LOG_MIN_LEVEL ANDROID_LOG_INFO
+#else
+#define LOG_MIN_LEVEL ANDROID_LOG_VERBOSE
+#endif
+#endif
+
+static inline int ai_should_log(int prio) {
+    return __android_log_is_loggable(prio, LOG_TAG, LOG_MIN_LEVEL);
+}
+
+#if LOG_MIN_LEVEL <= ANDROID_LOG_VERBOSE
+#define LOGv(...) do { if (ai_should_log(ANDROID_LOG_VERBOSE)) __android_log_print(ANDROID_LOG_VERBOSE, LOG_TAG, __VA_ARGS__); } while (0)
+#else
+#define LOGv(...) ((void)0)
+#endif
+
+#if LOG_MIN_LEVEL <= ANDROID_LOG_DEBUG
+#define LOGd(...) do { if (ai_should_log(ANDROID_LOG_DEBUG)) __android_log_print(ANDROID_LOG_DEBUG, LOG_TAG, __VA_ARGS__); } while (0)
+#else
+#define LOGd(...) ((void)0)
+#endif
+
+#define LOGi(...)   do { if (ai_should_log(ANDROID_LOG_INFO )) __android_log_print(ANDROID_LOG_INFO , LOG_TAG, __VA_ARGS__); } while (0)
+#define LOGw(...)   do { if (ai_should_log(ANDROID_LOG_WARN )) __android_log_print(ANDROID_LOG_WARN , LOG_TAG, __VA_ARGS__); } while (0)
+#define LOGe(...)   do { if (ai_should_log(ANDROID_LOG_ERROR)) __android_log_print(ANDROID_LOG_ERROR, LOG_TAG, __VA_ARGS__); } while (0)
+
+static inline int android_log_prio_from_ggml(enum ggml_log_level level) {
+    switch (level) {
+        case GGML_LOG_LEVEL_ERROR: return ANDROID_LOG_ERROR;
+        case GGML_LOG_LEVEL_WARN:  return ANDROID_LOG_WARN;
+        case GGML_LOG_LEVEL_INFO:  return ANDROID_LOG_INFO;
+        case GGML_LOG_LEVEL_DEBUG: return ANDROID_LOG_DEBUG;
+        default:                   return ANDROID_LOG_DEFAULT;
+    }
+}
+
+static inline void aichat_android_log_callback(enum ggml_log_level level,
+                                              const char* text,
+                                              void* /*user*/) {
+    const int prio = android_log_prio_from_ggml(level);
+    if (!ai_should_log(prio)) return;
+    __android_log_write(prio, LOG_TAG, text);
+}

examples/llama.android/lib/src/main/java/com/arm/aichat/AiChat.kt

@@ -0,0 +1,14 @@
+package com.arm.aichat
+
+import android.content.Context
+import com.arm.aichat.internal.InferenceEngineImpl
+
+/**
+ * Main entry point for Arm's AI Chat library.
+ */
+object AiChat {
+    /**
+     * Get the inference engine single instance.
+     */
+    fun getInferenceEngine(context: Context) = InferenceEngineImpl.getInstance(context)
+}

examples/llama.android/lib/src/main/java/com/arm/aichat/InferenceEngine.kt

@@ -0,0 +1,89 @@
+package com.arm.aichat
+
+import com.arm.aichat.InferenceEngine.State
+import kotlinx.coroutines.flow.Flow
+import kotlinx.coroutines.flow.StateFlow
+
+/**
+ * Interface defining the core LLM inference operations.
+ */
+interface InferenceEngine {
+    /**
+     * Current state of the inference engine
+     */
+    val state: StateFlow<State>
+
+    /**
+     * Load a model from the given path.
+     *
+     * @throws UnsupportedArchitectureException if model architecture not supported
+     */
+    suspend fun loadModel(pathToModel: String)
+
+    /**
+     * Sends a system prompt to the loaded model
+     */
+    suspend fun setSystemPrompt(systemPrompt: String)
+
+    /**
+     * Sends a user prompt to the loaded model and returns a Flow of generated tokens.
+     */
+    fun sendUserPrompt(message: String, predictLength: Int = DEFAULT_PREDICT_LENGTH): Flow<String>
+
+    /**
+     * Runs a benchmark with the specified parameters.
+     */
+    suspend fun bench(pp: Int, tg: Int, pl: Int, nr: Int = 1): String
+
+    /**
+     * Unloads the currently loaded model.
+     */
+    suspend fun cleanUp()
+
+    /**
+     * Cleans up resources when the engine is no longer needed.
+     */
+    fun destroy()
+
+    /**
+     * States of the inference engine
+     */
+    sealed class State {
+        object Uninitialized : State()
+        object Initializing : State()
+        object Initialized : State()
+
+        object LoadingModel : State()
+        object UnloadingModel : State()
+        object ModelReady : State()
+
+        object Benchmarking : State()
+        object ProcessingSystemPrompt : State()
+        object ProcessingUserPrompt : State()
+
+        object Generating : State()
+
+        data class Error(val exception: Exception) : State()
+    }
+
+    companion object {
+        const val DEFAULT_PREDICT_LENGTH = 1024
+    }
+}
+
+val State.isUninterruptible
+    get() = this is State.Initializing ||
+        this is State.LoadingModel ||
+        this is State.UnloadingModel ||
+        this is State.Benchmarking ||
+        this is State.ProcessingSystemPrompt ||
+        this is State.ProcessingUserPrompt
+
+val State.isModelLoaded: Boolean
+    get() = this is State.ModelReady ||
+        this is State.Benchmarking ||
+        this is State.ProcessingSystemPrompt ||
+        this is State.ProcessingUserPrompt ||
+        this is State.Generating
+
+class UnsupportedArchitectureException : Exception()

examples/llama.android/lib/src/main/java/com/arm/aichat/gguf/FileType.kt

@@ -0,0 +1,61 @@
+package com.arm.aichat.gguf
+
+import kotlin.collections.get
+
+
+/**
+ * Numerical codes used by `general.file_type` (see llama.cpp repo's `constants.py`).
+ * The `label` matches what llama‑cli prints.
+ */
+enum class FileType(val code: Int, val label: String) {
+    ALL_F32(0, "all F32"),
+    MOSTLY_F16(1, "F16"),
+    MOSTLY_Q4_0(2, "Q4_0"),
+    MOSTLY_Q4_1(3, "Q4_1"),
+    // 4 removed
+    MOSTLY_Q8_0(7, "Q8_0"),
+    MOSTLY_Q5_0(8, "Q5_0"),
+    MOSTLY_Q5_1(9, "Q5_1"),
+
+    /* K‑quants ------------------------------------------------------------ */
+    MOSTLY_Q2_K      (10, "Q2_K - Medium"),
+    MOSTLY_Q3_K_S    (11, "Q3_K - Small"),
+    MOSTLY_Q3_K_M    (12, "Q3_K - Medium"),
+    MOSTLY_Q3_K_L    (13, "Q3_K - Large"),
+    MOSTLY_Q4_K_S    (14, "Q4_K - Small"),
+    MOSTLY_Q4_K_M    (15, "Q4_K - Medium"),
+    MOSTLY_Q5_K_S    (16, "Q5_K - Small"),
+    MOSTLY_Q5_K_M    (17, "Q5_K - Medium"),
+    MOSTLY_Q6_K      (18, "Q6_K"),
+
+    /* IQ quants ----------------------------------------------------------- */
+    MOSTLY_IQ2_XXS   (19, "IQ2_XXS - 2.06 bpw"),
+    MOSTLY_IQ2_XS    (20, "IQ2_XS - 2.31 bpw"),
+    MOSTLY_Q2_K_S    (21, "Q2_K - Small"),
+    MOSTLY_IQ3_XS    (22, "IQ3_XS - 3.30 bpw"),
+    MOSTLY_IQ3_XXS   (23, "IQ3_XXS - 3.06 bpw"),
+    MOSTLY_IQ1_S     (24, "IQ1_S - 1.56 bpw"),
+    MOSTLY_IQ4_NL    (25, "IQ4_NL - 4.5 bpw"),
+    MOSTLY_IQ3_S     (26, "IQ3_S - 3.44 bpw"),
+    MOSTLY_IQ3_M     (27, "IQ3_M - 3.66 bpw"),
+    MOSTLY_IQ2_S     (28, "IQ2_S - 2.50 bpw"),
+    MOSTLY_IQ2_M     (29, "IQ2_M - 2.70 bpw"),
+    MOSTLY_IQ4_XS    (30, "IQ4_XS - 4.25 bpw"),
+    MOSTLY_IQ1_M     (31, "IQ1_M - 1.75 bpw"),
+
+    /* BF16 & Ternary ------------------------------------------------------ */
+    MOSTLY_BF16      (32, "BF16"),
+    MOSTLY_TQ1_0     (36, "TQ1_0 - 1.69 bpw ternary"),
+    MOSTLY_TQ2_0     (37, "TQ2_0 - 2.06 bpw ternary"),
+
+    /* Special flag -------------------------------------------------------- */
+    GUESSED(1024, "(guessed)"),
+
+    UNKNOWN(-1, "unknown");
+
+    companion object {
+        private val map = entries.associateBy(FileType::code)
+
+        fun fromCode(code: Int?): FileType = map[code] ?: UNKNOWN
+    }
+}

examples/llama.android/lib/src/main/java/com/arm/aichat/gguf/GgufMetadata.kt

@@ -0,0 +1,132 @@
+package com.arm.aichat.gguf
+
+import java.io.IOException
+
+
+/**
+ * Structured metadata of GGUF
+ */
+data class GgufMetadata(
+    // Basic file info
+    val version: GgufVersion,
+    val tensorCount: Long,
+    val kvCount: Long,
+
+    // General info
+    val basic: BasicInfo,
+    val author: AuthorInfo? = null,
+    val additional: AdditionalInfo? = null,
+    val architecture: ArchitectureInfo? = null,
+    val baseModels: List<BaseModelInfo>? = null,
+    val tokenizer: TokenizerInfo? = null,
+
+    // Derivative info
+    val dimensions: DimensionsInfo? = null,
+    val attention: AttentionInfo? = null,
+    val rope: RopeInfo? = null,
+    val experts: ExpertsInfo? = null
+) {
+    enum class GgufVersion(val code: Int, val label: String) {
+        /** First public draft; little‑endian only, no alignment key. */
+        LEGACY_V1(1, "Legacy v1"),
+
+        /** Added split‑file support and some extra metadata keys. */
+        EXTENDED_V2(2, "Extended v2"),
+
+        /** Current spec: endian‑aware, mandatory alignment, fully validated. */
+        VALIDATED_V3(3, "Validated v3");
+
+        companion object {
+            fun fromCode(code: Int): GgufVersion =
+                entries.firstOrNull { it.code == code }
+                    ?: throw IOException("Unknown GGUF version code $code")
+        }
+
+        override fun toString(): String = "$label (code=$code)"
+    }
+
+    data class BasicInfo(
+        val uuid: String? = null,
+        val name: String? = null,
+        val nameLabel: String? = null,
+        val sizeLabel: String? = null,  // Size label like "7B"
+    )
+
+    data class AuthorInfo(
+        val organization: String? = null,
+        val author: String? = null,
+        val doi: String? = null,
+        val url: String? = null,
+        val repoUrl: String? = null,
+        val license: String? = null,
+        val licenseLink: String? = null,
+    )
+
+    data class AdditionalInfo(
+        val type: String? = null,
+        val description: String? = null,
+        val tags: List<String>? = null,
+        val languages: List<String>? = null,
+    )
+
+    data class ArchitectureInfo(
+        val architecture: String? = null,
+        val fileType: Int? = null,
+        val vocabSize: Int? = null,
+        val finetune: String? = null,
+        val quantizationVersion: Int? = null,
+    )
+
+    data class BaseModelInfo(
+        val name: String? = null,
+        val author: String? = null,
+        val version: String? = null,
+        val organization: String? = null,
+        val url: String? = null,
+        val doi: String? = null,
+        val uuid: String? = null,
+        val repoUrl: String? = null,
+    )
+
+    data class TokenizerInfo(
+        val model: String? = null,
+        val bosTokenId: Int? = null,
+        val eosTokenId: Int? = null,
+        val unknownTokenId: Int? = null,
+        val paddingTokenId: Int? = null,
+        val addBosToken: Boolean? = null,
+        val addEosToken: Boolean? = null,
+        val chatTemplate: String? = null,
+    )
+
+    data class DimensionsInfo(
+        val contextLength: Int? = null,
+        val embeddingSize: Int? = null,
+        val blockCount: Int? = null,
+        val feedForwardSize: Int? = null,
+    )
+
+    data class AttentionInfo(
+        val headCount: Int? = null,
+        val headCountKv: Int? = null,
+        val keyLength: Int? = null,
+        val valueLength: Int? = null,
+        val layerNormEpsilon: Float? = null,
+        val layerNormRmsEpsilon: Float? = null,
+    )
+
+    data class RopeInfo(
+        val frequencyBase: Float? = null,
+        val dimensionCount: Int? = null,
+        val scalingType: String? = null,
+        val scalingFactor: Float? = null,
+        val attnFactor: Float? = null,
+        val originalContextLength: Int? = null,
+        val finetuned: Boolean? = null,
+    )
+
+    data class ExpertsInfo(
+        val count: Int? = null,
+        val usedCount: Int? = null,
+    )
+}

examples/llama.android/lib/src/main/java/com/arm/aichat/gguf/GgufMetadataReader.kt

@@ -0,0 +1,77 @@
+package com.arm.aichat.gguf
+
+import android.content.Context
+import android.net.Uri
+import com.arm.aichat.internal.gguf.GgufMetadataReaderImpl
+import java.io.File
+import java.io.IOException
+import java.io.InputStream
+
+/**
+ * Interface for reading GGUF metadata from model files.
+ * Use `GgufMetadataReader.create()` to get an instance.
+ */
+interface GgufMetadataReader {
+    /**
+     * Reads the magic number from the specified file path.
+     *
+     * @param file Java File to the GGUF file with absolute path
+     * @return true if file is valid GGUF, otherwise false
+     * @throws InvalidFileFormatException if file format is invalid
+     */
+    suspend fun ensureSourceFileFormat(file: File): Boolean
+
+    /**
+     * Reads the magic number from the specified file path.
+     *
+     * @param context Context for obtaining [android.content.ContentProvider]
+     * @param uri Uri to the GGUF file provided by [android.content.ContentProvider]
+     * @return true if file is valid GGUF, otherwise false
+     * @throws InvalidFileFormatException if file format is invalid
+     */
+    suspend fun ensureSourceFileFormat(context: Context, uri: Uri): Boolean
+
+    /**
+     * Reads and parses GGUF metadata from the specified file path.
+     *
+     * @param input the [InputStream] obtained from a readable file or content
+     * @return Structured metadata extracted from the file
+     * @throws IOException if file is damaged or cannot be read
+     * @throws InvalidFileFormatException if file format is invalid
+     */
+    suspend fun readStructuredMetadata(input: InputStream): GgufMetadata
+
+    companion object {
+        private val DEFAULT_SKIP_KEYS = setOf(
+            "tokenizer.chat_template",
+            "tokenizer.ggml.scores",
+            "tokenizer.ggml.tokens",
+            "tokenizer.ggml.token_type"
+        )
+
+        /**
+         * Creates a default GgufMetadataReader instance
+         */
+        fun create(): GgufMetadataReader = GgufMetadataReaderImpl(
+            skipKeys = DEFAULT_SKIP_KEYS,
+            arraySummariseThreshold = 1_000
+        )
+
+        /**
+         * Creates a GgufMetadataReader with custom configuration
+         *
+         * @param skipKeys Keys whose value should be skipped entirely (not kept in the result map)
+         * @param arraySummariseThreshold If ≥0, arrays longer get summarised, not materialised;
+         *                                If -1, never summarise.
+         */
+        fun create(
+            skipKeys: Set<String> = DEFAULT_SKIP_KEYS,
+            arraySummariseThreshold: Int = 1_000
+        ): GgufMetadataReader = GgufMetadataReaderImpl(
+            skipKeys = skipKeys,
+            arraySummariseThreshold = arraySummariseThreshold
+        )
+    }
+}
+
+class InvalidFileFormatException : IOException()

examples/llama.android/lib/src/main/java/com/arm/aichat/internal/InferenceEngineImpl.kt

@@ -0,0 +1,309 @@
+package com.arm.aichat.internal
+
+import android.content.Context
+import android.util.Log
+import com.arm.aichat.InferenceEngine
+import com.arm.aichat.UnsupportedArchitectureException
+import com.arm.aichat.internal.InferenceEngineImpl.Companion.getInstance
+import dalvik.annotation.optimization.FastNative
+import kotlinx.coroutines.CancellationException
+import kotlinx.coroutines.CoroutineScope
+import kotlinx.coroutines.Dispatchers
+import kotlinx.coroutines.ExperimentalCoroutinesApi
+import kotlinx.coroutines.SupervisorJob
+import kotlinx.coroutines.cancel
+import kotlinx.coroutines.flow.Flow
+import kotlinx.coroutines.flow.MutableStateFlow
+import kotlinx.coroutines.flow.StateFlow
+import kotlinx.coroutines.flow.flow
+import kotlinx.coroutines.flow.flowOn
+import kotlinx.coroutines.launch
+import kotlinx.coroutines.withContext
+import java.io.File
+import java.io.IOException
+
+/**
+ * JNI wrapper for the llama.cpp library providing Android-friendly access to large language models.
+ *
+ * This class implements a singleton pattern for managing the lifecycle of a single LLM instance.
+ * All operations are executed on a dedicated single-threaded dispatcher to ensure thread safety
+ * with the underlying C++ native code.
+ *
+ * The typical usage flow is:
+ * 1. Get instance via [getInstance]
+ * 2. Load a model with [loadModel]
+ * 3. Send prompts with [sendUserPrompt]
+ * 4. Generate responses as token streams
+ * 5. Perform [cleanUp] when done with a model
+ * 6. Properly [destroy] when completely done
+ *
+ * State transitions are managed automatically and validated at each operation.
+ *
+ * @see ai_chat.cpp for the native implementation details
+ */
+internal class InferenceEngineImpl private constructor(
+    private val nativeLibDir: String
+) : InferenceEngine {
+
+    companion object {
+        private val TAG = InferenceEngineImpl::class.java.simpleName
+
+        @Volatile
+        private var instance: InferenceEngine? = null
+
+        /**
+         * Create or obtain [InferenceEngineImpl]'s single instance.
+         *
+         * @param Context for obtaining native library directory
+         * @throws IllegalArgumentException if native library path is invalid
+         * @throws UnsatisfiedLinkError if library failed to load
+         */
+        internal fun getInstance(context: Context) =
+            instance ?: synchronized(this) {
+                val nativeLibDir = context.applicationInfo.nativeLibraryDir
+                require(nativeLibDir.isNotBlank()) { "Expected a valid native library path!" }
+
+                try {
+                    Log.i(TAG, "Instantiating InferenceEngineImpl,,,")
+                    InferenceEngineImpl(nativeLibDir).also { instance = it }
+                } catch (e: UnsatisfiedLinkError) {
+                    Log.e(TAG, "Failed to load native library from $nativeLibDir", e)
+                    throw e
+                }
+            }
+    }
+
+    /**
+     * JNI methods
+     * @see ai_chat.cpp
+     */
+    @FastNative
+    private external fun init(nativeLibDir: String)
+
+    @FastNative
+    private external fun load(modelPath: String): Int
+
+    @FastNative
+    private external fun prepare(): Int
+
+    @FastNative
+    private external fun systemInfo(): String
+
+    @FastNative
+    private external fun benchModel(pp: Int, tg: Int, pl: Int, nr: Int): String
+
+    @FastNative
+    private external fun processSystemPrompt(systemPrompt: String): Int
+
+    @FastNative
+    private external fun processUserPrompt(userPrompt: String, predictLength: Int): Int
+
+    @FastNative
+    private external fun generateNextToken(): String?
+
+    @FastNative
+    private external fun unload()
+
+    @FastNative
+    private external fun shutdown()
+
+    private val _state =
+        MutableStateFlow<InferenceEngine.State>(InferenceEngine.State.Uninitialized)
+    override val state: StateFlow<InferenceEngine.State> = _state
+
+    private var _readyForSystemPrompt = false
+
+    /**
+     * Single-threaded coroutine dispatcher & scope for LLama asynchronous operations
+     */
+    @OptIn(ExperimentalCoroutinesApi::class)
+    private val llamaDispatcher = Dispatchers.IO.limitedParallelism(1)
+    private val llamaScope = CoroutineScope(llamaDispatcher + SupervisorJob())
+
+    init {
+        llamaScope.launch {
+            try {
+                check(_state.value is InferenceEngine.State.Uninitialized) {
+                    "Cannot load native library in ${_state.value.javaClass.simpleName}!"
+                }
+                _state.value = InferenceEngine.State.Initializing
+                Log.i(TAG, "Loading native library...")
+                System.loadLibrary("ai-chat")
+                init(nativeLibDir)
+                _state.value = InferenceEngine.State.Initialized
+                Log.i(TAG, "Native library loaded! System info: \n${systemInfo()}")
+
+            } catch (e: Exception) {
+                Log.e(TAG, "Failed to load native library", e)
+                throw e
+            }
+        }
+    }
+
+    /**
+     * Load the LLM
+     */
+    override suspend fun loadModel(pathToModel: String) =
+        withContext(llamaDispatcher) {
+            check(_state.value is InferenceEngine.State.Initialized) {
+                "Cannot load model in ${_state.value.javaClass.simpleName}!"
+            }
+
+            try {
+                Log.i(TAG, "Checking access to model file... \n$pathToModel")
+                File(pathToModel).let {
+                    require(it.exists()) { "File not found" }
+                    require(it.isFile) { "Not a valid file" }
+                    require(it.canRead()) { "Cannot read file" }
+                }
+
+                Log.i(TAG, "Loading model... \n$pathToModel")
+                _readyForSystemPrompt = false
+                _state.value = InferenceEngine.State.LoadingModel
+                load(pathToModel).let {
+                    // TODO-han.yin: find a better way to pass other error codes
+                    if (it != 0) throw UnsupportedArchitectureException()
+                }
+                prepare().let {
+                    if (it != 0) throw IOException("Failed to prepare resources")
+                }
+                Log.i(TAG, "Model loaded!")
+                _readyForSystemPrompt = true
+                _state.value = InferenceEngine.State.ModelReady
+            } catch (e: Exception) {
+                Log.e(TAG, (e.message ?: "Error loading model") + "\n" + pathToModel, e)
+                _state.value = InferenceEngine.State.Error(e)
+                throw e
+            }
+        }
+
+    /**
+     * Process the plain text system prompt
+     *
+     * TODO-han.yin: return error code if system prompt not correct processed?
+     */
+    override suspend fun setSystemPrompt(prompt: String) =
+        withContext(llamaDispatcher) {
+            require(prompt.isNotBlank()) { "Cannot process empty system prompt!" }
+            check(_readyForSystemPrompt) { "System prompt must be set ** RIGHT AFTER ** model loaded!" }
+            check(_state.value is InferenceEngine.State.ModelReady) {
+                "Cannot process system prompt in ${_state.value.javaClass.simpleName}!"
+            }
+
+            Log.i(TAG, "Sending system prompt...")
+            _readyForSystemPrompt = false
+            _state.value = InferenceEngine.State.ProcessingSystemPrompt
+            processSystemPrompt(prompt).let { result ->
+                if (result != 0) {
+                    RuntimeException("Failed to process system prompt: $result").also {
+                        _state.value = InferenceEngine.State.Error(it)
+                        throw it
+                    }
+                }
+            }
+            Log.i(TAG, "System prompt processed! Awaiting user prompt...")
+            _state.value = InferenceEngine.State.ModelReady
+        }
+
+    /**
+     * Send plain text user prompt to LLM, which starts generating tokens in a [Flow]
+     */
+    override fun sendUserPrompt(
+        message: String,
+        predictLength: Int,
+    ): Flow<String> = flow {
+        require(message.isNotEmpty()) { "User prompt discarded due to being empty!" }
+        check(_state.value is InferenceEngine.State.ModelReady) {
+            "User prompt discarded due to: ${_state.value.javaClass.simpleName}"
+        }
+
+        try {
+            Log.i(TAG, "Sending user prompt...")
+            _readyForSystemPrompt = false
+            _state.value = InferenceEngine.State.ProcessingUserPrompt
+
+            processUserPrompt(message, predictLength).let { result ->
+                if (result != 0) {
+                    Log.e(TAG, "Failed to process user prompt: $result")
+                    return@flow
+                }
+            }
+
+            Log.i(TAG, "User prompt processed. Generating assistant prompt...")
+            _state.value = InferenceEngine.State.Generating
+            while (true) {
+                generateNextToken()?.let { utf8token ->
+                    if (utf8token.isNotEmpty()) emit(utf8token)
+                } ?: break
+            }
+            Log.i(TAG, "Assistant generation complete. Awaiting user prompt...")
+            _state.value = InferenceEngine.State.ModelReady
+        } catch (e: CancellationException) {
+            Log.i(TAG, "Generation cancelled by user.")
+            _state.value = InferenceEngine.State.ModelReady
+            throw e
+        } catch (e: Exception) {
+            Log.e(TAG, "Error during generation!", e)
+            _state.value = InferenceEngine.State.Error(e)
+            throw e
+        }
+    }.flowOn(llamaDispatcher)
+
+    /**
+     * Benchmark the model
+     */
+    override suspend fun bench(pp: Int, tg: Int, pl: Int, nr: Int): String =
+        withContext(llamaDispatcher) {
+            check(_state.value is InferenceEngine.State.ModelReady) {
+                "Benchmark request discarded due to: $state"
+            }
+            Log.i(TAG, "Start benchmark (pp: $pp, tg: $tg, pl: $pl, nr: $nr)")
+            _readyForSystemPrompt = false   // Just to be safe
+            _state.value = InferenceEngine.State.Benchmarking
+            benchModel(pp, tg, pl, nr).also {
+                _state.value = InferenceEngine.State.ModelReady
+            }
+        }
+
+    /**
+     * Unloads the model and frees resources, or reset error states
+     */
+    override suspend fun cleanUp() =
+        withContext(llamaDispatcher) {
+            when (val state = _state.value) {
+                is InferenceEngine.State.ModelReady -> {
+                    Log.i(TAG, "Unloading model and free resources...")
+                    _readyForSystemPrompt = false
+                    _state.value = InferenceEngine.State.UnloadingModel
+
+                    unload()
+
+                    _state.value = InferenceEngine.State.Initialized
+                    Log.i(TAG, "Model unloaded!")
+                    Unit
+                }
+
+                is InferenceEngine.State.Error -> {
+                    Log.i(TAG, "Resetting error states...")
+                    _state.value = InferenceEngine.State.Initialized
+                    Log.i(TAG, "States reset!")
+                    Unit
+                }
+
+                else -> throw IllegalStateException("Cannot unload model in ${state.javaClass.simpleName}")
+            }
+        }
+
+    /**
+     * Cancel all ongoing coroutines and free GGML backends
+     */
+    override fun destroy() {
+        _readyForSystemPrompt = false
+        llamaScope.cancel()
+        when(_state.value) {
+            is InferenceEngine.State.Uninitialized -> {}
+            is InferenceEngine.State.Initialized -> shutdown()
+            else -> { unload(); shutdown() }
+        }
+    }
+}

examples/llama.android/lib/src/main/java/com/arm/aichat/internal/gguf/GgufMetadataReaderImpl.kt

@@ -0,0 +1,590 @@
+package com.arm.aichat.internal.gguf
+
+import android.content.Context
+import android.net.Uri
+import com.arm.aichat.gguf.GgufMetadata
+import com.arm.aichat.gguf.GgufMetadataReader
+import com.arm.aichat.gguf.InvalidFileFormatException
+import java.io.File
+import java.io.IOException
+import java.io.InputStream
+
+
+/**
+ * Utility class to read GGUF model files and extract metadata key-value pairs.
+ * This parser reads the header and metadata of a GGUF v3 file (little-endian) and skips tensor data.
+ */
+internal class GgufMetadataReaderImpl(
+    private val skipKeys: Set<String>,
+    private val arraySummariseThreshold: Int,
+) : GgufMetadataReader {
+    companion object {
+        private const val ARCH_LLAMA = "llama"
+    }
+
+    /** Enum corresponding to GGUF metadata value types (for convenience and array element typing). */
+    enum class MetadataType(val code: Int) {
+        UINT8(0), INT8(1), UINT16(2), INT16(3),
+        UINT32(4), INT32(5), FLOAT32(6), BOOL(7),
+        STRING(8), ARRAY(9), UINT64(10), INT64(11), FLOAT64(12);
+        companion object {
+            private val codeMap = entries.associateBy(MetadataType::code)
+            fun fromCode(code: Int): MetadataType = codeMap[code]
+                ?: throw IOException("Unknown metadata value type code: $code")
+        }
+    }
+
+    /** Sealed class hierarchy for metadata values, providing type-safe representations for each GGUF metadata type. */
+    sealed class MetadataValue {
+        data class UInt8(val value: UByte) : MetadataValue()       // 0:  8-bit unsigned int
+        data class Int8(val value: Byte) : MetadataValue()         // 1:  8-bit signed int
+        data class UInt16(val value: UShort) : MetadataValue()     // 2:  16-bit unsigned int (little-endian)
+        data class Int16(val value: Short) : MetadataValue()       // 3:  16-bit signed int (little-endian)
+        data class UInt32(val value: UInt) : MetadataValue()       // 4:  32-bit unsigned int (little-endian)
+        data class Int32(val value: Int) : MetadataValue()         // 5:  32-bit signed int (little-endian)
+        data class Float32(val value: Float) : MetadataValue()     // 6:  32-bit IEEE754 float
+        data class Bool(val value: Boolean) : MetadataValue()      // 7:  Boolean (1-byte, 0=false, 1=true)
+        data class StringVal(val value: String) : MetadataValue()  // 8:  UTF-8 string (length-prefixed)
+        data class ArrayVal(val elementType: MetadataType, val elements: List<MetadataValue>) : MetadataValue()
+        data class UInt64(val value: ULong) : MetadataValue()      // 10: 64-bit unsigned int (little-endian)
+        data class Int64(val value: Long) : MetadataValue()        // 11: 64-bit signed int (little-endian)
+        data class Float64(val value: Double) : MetadataValue()    // 12: 64-bit IEEE754 double
+    }
+
+    /* Convert MetadataValue to plain Kotlin primitives for allMetadata map */
+    private fun MetadataValue.toPrimitive(): Any = when (this) {
+        is MetadataValue.UInt8     -> value
+        is MetadataValue.Int8      -> value
+        is MetadataValue.UInt16    -> value
+        is MetadataValue.Int16     -> value
+        is MetadataValue.UInt32    -> value
+        is MetadataValue.Int32     -> value
+        is MetadataValue.Float32   -> value
+        is MetadataValue.Bool      -> value
+        is MetadataValue.StringVal -> value
+        is MetadataValue.UInt64    -> value
+        is MetadataValue.Int64     -> value
+        is MetadataValue.Float64   -> value
+        is MetadataValue.ArrayVal  -> elements.map { it.toPrimitive() }
+    }
+
+    /**
+     * Reads the magic number from the specified file path.
+     *
+     * @param context Context for obtaining ContentResolver
+     * @param uri Uri to the GGUF file provided by ContentProvider
+     * @return true if file is valid GGUF, otherwise false
+     */
+    override suspend fun ensureSourceFileFormat(file: File): Boolean =
+        file.inputStream().buffered().use { ensureMagic(it) }
+
+    /**
+     * Reads the magic number from the specified file path.
+     *
+     * @param context Context for obtaining ContentResolver
+     * @param uri Uri to the GGUF file provided by ContentProvider
+     * @return true if file is valid GGUF, otherwise false
+     */
+    override suspend fun ensureSourceFileFormat(context: Context, uri: Uri): Boolean =
+        context.contentResolver.openInputStream(uri)?.buffered()?.use { ensureMagic(it) } == true
+
+    /** Reads the 4‑byte magic; throws if magic ≠ "GGUF". */
+    private fun ensureMagic(input: InputStream): Boolean =
+        ByteArray(4).let {
+            if (input.read(it) != 4) throw IOException("Not a valid file!")
+            it.contentEquals(byteArrayOf(0x47, 0x47, 0x55, 0x46)) // "GGUF"
+        }
+
+    /**
+     * High‑level entry point: parses a `.gguf` file on disk and returns the fully
+     * populated [GgufMetadata] tree.
+     *
+     * Steps performed internally:
+     * 1.  Reads and validates the 8‑byte header (`"GGUF"` magic + version).
+     * 2.  Streams through the key‑value section, skipping large blobs if the key
+     *     appears in [skipKeys] or if an array exceeds [arraySummariseThreshold].
+     * 3.  Converts the resulting raw map into strongly‑typed sub‑structures
+     *     (basic info, tokenizer, rope, etc.).
+     *
+     * The method is STREAMING‑ONLY: tensors are never mapped or loaded into
+     * memory, so even multi‑GB model files can be processed in < 50 ms.
+     *
+     * @param path Absolute or relative filesystem path to a `.gguf` file.
+     * @return A [GgufMetadata] instance containing all recognised metadata plus
+     *         an `allMetadata` map with any keys that were not given a dedicated
+     *         field.
+     * @throws IOException if the file is not GGUF, the version is unsupported,
+     *         or the metadata block is truncated / corrupt.
+     */
+    override suspend fun readStructuredMetadata(input: InputStream): GgufMetadata {
+        // ── 1. header ──────────────────────────────────────────────────────────
+        // throws on mismatch
+        val version       = ensureMagicAndVersion(input)
+        val tensorCount   = readLittleLong(input)
+        val kvCount       = readLittleLong(input)
+
+        // ── 2. metadata map (reuse our raw parser, but we need access to the stream) ──
+        val meta = readMetaMap(input, kvCount)    // <String, MetadataValue>
+
+        // ── 3. build structured object ────────────────────────────────────────
+        return buildStructured(meta, version, tensorCount, kvCount)
+    }
+
+    /** Reads the 4‑byte magic + 4‑byte version; throws if magic ≠ "GGUF". */
+    private fun ensureMagicAndVersion(input: InputStream): GgufMetadata.GgufVersion {
+        if (!ensureMagic(input)) throw InvalidFileFormatException()
+        return GgufMetadata.GgufVersion.fromCode(readLEUInt32(input))
+    }
+
+    /**
+     * Read an unsigned 32‑bit little‑endian integer.
+     *
+     * @throws IOException if fewer than four bytes are available.
+     */
+    private fun readLEUInt32(input: InputStream): Int {
+        val b0 = input.read(); val b1 = input.read(); val b2 = input.read(); val b3 = input.read()
+        if (b3 == -1) throw IOException("Unexpected EOF while reading UInt32")
+        return (b3 and 0xFF shl 24) or
+            (b2 and 0xFF shl 16) or
+            (b1 and 0xFF shl  8) or
+            (b0 and 0xFF)
+    }
+
+    /**
+     * Low‑level helper that reads the entire “key-value” section from the current
+     * stream position.
+     *
+     * @param input  Open stream positioned JUST AFTER the header.
+     * @param kvCnt  Number of key‑value pairs (taken from the header).
+     * @return       Mutable map with one [MetadataValue] for every key that is NOT skipped.
+     *
+     * The function honours [skipKeys] and [arraySummariseThreshold] by invoking
+     * [skipValue] or [parseValue] accordingly.
+     */
+    private fun readMetaMap(input: InputStream, kvCnt: Long): Map<String, MetadataValue> =
+        mutableMapOf<String, MetadataValue>().apply {
+             repeat(kvCnt.toInt()) {
+                 val key = readString(input)
+                 val valueT = MetadataType.fromCode(littleEndianBytesToInt(input.readNBytesExact(4)))
+                 if (key in skipKeys) {
+                     skipValue(input, valueT)
+                 } else {
+                     this[key] = parseValue(input, valueT)
+                 }
+             }
+         }
+
+    /**
+     * Converts a flat [Map]<[String], [MetadataValue]> into the strongly‑typed
+     * [GgufMetadata] tree used by the rest of the app.
+     *
+     * Only the keys listed in the spec are copied into dedicated data classes;
+     * everything else is preserved in `GgufMetadata.allMetadata`.
+     *
+     * @param m            Raw key/value map.
+     * @param version      GGUF file‑format version (enum).
+     * @param tensorCnt    Number of tensors (from the header).
+     * @param kvCnt        Total metadata pair count (from the header).
+     */
+    private fun buildStructured(
+        m: Map<String, MetadataValue>,
+        version: GgufMetadata.GgufVersion,
+        tensorCnt: Long,
+        kvCnt: Long
+    ): GgufMetadata {
+        // ---------- helpers ----------
+        fun String.str()  = (m[this] as? MetadataValue.StringVal)?.value
+        fun String.bool() = (m[this] as? MetadataValue.Bool)?.value
+        fun String.i32()  = (m[this] as? MetadataValue.Int32)?.value
+        fun String.u32()  = (m[this] as? MetadataValue.UInt32)?.value?.toInt()
+        fun String.f32()  = (m[this] as? MetadataValue.Float32)?.value
+        fun String.f64()  = (m[this] as? MetadataValue.Float64)?.value?.toFloat()
+        fun String.strList(): List<String>? =
+            (m[this] as? MetadataValue.ArrayVal)
+                ?.elements
+                ?.mapNotNull { (it as? MetadataValue.StringVal)?.value }
+
+        val arch = "general.architecture".str() ?: ARCH_LLAMA
+
+        // -------------- populate sections ----------------
+        val basic = GgufMetadata.BasicInfo(
+            uuid      = "general.uuid".str(),
+            name      = "general.basename".str(),
+            nameLabel = "general.name".str(),
+            sizeLabel = "general.size_label".str()
+        )
+
+        val author = GgufMetadata.AuthorInfo(
+            organization = "general.organization".str(),
+            author       = "general.author".str(),
+            doi          = "general.doi".str(),
+            url          = "general.url".str(),
+            repoUrl      = "general.repo_url".str(),
+            license      = "general.license".str(),
+            licenseLink  = "general.license.link".str()
+        ).takeUnless {
+            organization == null && author == null && doi == null &&
+                url == null && repoUrl == null && license == null && licenseLink == null
+        }
+
+        val additional = GgufMetadata.AdditionalInfo(
+            type        = "general.type".str(),
+            description = "general.description".str(),
+            tags        = "general.tags".strList(),
+            languages   = "general.languages".strList()
+        ).takeUnless {
+            type == null && description == null && tags == null && languages == null
+        }
+
+        val architectureInfo = GgufMetadata.ArchitectureInfo(
+            architecture        = arch,
+            fileType            = "general.file_type".u32(),
+            vocabSize           = "$arch.vocab_size".u32(),
+            finetune            = "general.finetune".str(),
+            quantizationVersion = "general.quantization_version".u32()
+        ).takeUnless { fileType == null && vocabSize == null && finetune == null && quantizationVersion == null }
+
+        val baseModels = buildList {
+            val n = "general.base_model.count".u32() ?: 0
+            for (i in 0 until n) {
+                fun k(s: String) = "general.base_model.$i.$s"
+                add(
+                    GgufMetadata.BaseModelInfo(
+                        name         = k("name").str(),
+                        author       = k("author").str(),
+                        version      = k("version").str(),
+                        organization = k("organization").str(),
+                        url          = k("url").str(),
+                        doi          = k("doi").str(),
+                        uuid         = k("uuid").str(),
+                        repoUrl      = k("repo_url").str(),
+                    )
+                )
+            }
+        }.takeIf { it.isNotEmpty() }
+
+        val tokenizer = GgufMetadata.TokenizerInfo(
+            model            = "tokenizer.ggml.model".str(),
+            bosTokenId       = "tokenizer.ggml.bos_token_id".u32(),
+            eosTokenId       = "tokenizer.ggml.eos_token_id".u32(),
+            unknownTokenId   = "tokenizer.ggml.unknown_token_id".u32(),
+            paddingTokenId   = "tokenizer.ggml.padding_token_id".u32(),
+            addBosToken      = "tokenizer.ggml.add_bos_token".bool(),
+            addEosToken      = "tokenizer.ggml.add_eos_token".bool(),
+            chatTemplate     = "tokenizer.chat_template".str()
+        ).takeUnless { model == null && bosTokenId == null && eosTokenId == null &&
+            unknownTokenId == null && paddingTokenId == null &&
+            addBosToken == null && addEosToken == null && chatTemplate == null
+        }
+
+        val dimensions = GgufMetadata.DimensionsInfo(
+            contextLength    = "$arch.context_length".u32(),
+            embeddingSize    = "$arch.embedding_length".u32(),
+            blockCount       = "$arch.block_count".u32(),
+            feedForwardSize  = "$arch.feed_forward_length".u32()
+        ).takeUnless { contextLength == null && embeddingSize == null && blockCount == null && feedForwardSize == null }
+
+        val attention = GgufMetadata.AttentionInfo(
+            headCount             = "$arch.attention.head_count".u32(),
+            headCountKv           = "$arch.attention.head_count_kv".u32(),
+            keyLength             = "$arch.attention.key_length".u32(),
+            valueLength           = "$arch.attention.value_length".u32(),
+            layerNormEpsilon      = "$arch.attention.layer_norm_epsilon".f32(),
+            layerNormRmsEpsilon   = "$arch.attention.layer_norm_rms_epsilon".f32(),
+        ).takeUnless { headCount == null && headCountKv == null && keyLength == null && valueLength == null &&
+            layerNormEpsilon == null && layerNormRmsEpsilon == null
+        }
+
+        val rope = GgufMetadata.RopeInfo(
+            frequencyBase          = "$arch.rope.freq_base".f32(),
+            dimensionCount         = "$arch.rope.dimension_count".u32(),
+            scalingType            = "$arch.rope.scaling.type".str(),
+            scalingFactor          = "$arch.rope.scaling.factor".f32(),
+            attnFactor             = "$arch.rope.scaling.attn_factor".f32(),
+            originalContextLength  = "$arch.rope.scaling.original_context_length".u32(),
+            finetuned              = "$arch.rope.scaling.finetuned".bool()
+        ).takeUnless { frequencyBase == null && dimensionCount == null &&
+            scalingType == null && scalingFactor == null && attnFactor == null &&
+            originalContextLength == null && finetuned == null
+        }
+
+        val experts = GgufMetadata.ExpertsInfo(
+            count      = "$arch.expert_count".u32(),
+            usedCount  = "$arch.expert_used_count".u32()
+        ).takeUnless { count == null && usedCount == null }
+
+        return GgufMetadata(
+            version = version,
+            tensorCount = tensorCnt,
+            kvCount = kvCnt,
+            basic = basic,
+            author = author,
+            additional = additional,
+            architecture = architectureInfo,
+            baseModels = baseModels,
+            tokenizer = tokenizer,
+            dimensions = dimensions,
+            attention = attention,
+            rope = rope,
+            experts = experts
+        )
+    }
+
+    /**
+     * Recursively parses a metadata value of the given type from the input stream.
+     * @param input The input stream positioned at the start of the value.
+     * @param type The metadata value type to parse.
+     */
+    private fun parseValue(input: InputStream, type: MetadataType): MetadataValue = when (type) {
+        MetadataType.UINT8 -> {
+            // 1-byte unsigned integer
+            val byteVal = input.read()
+            if (byteVal == -1) throw IOException("Unexpected EOF while reading uint8 value.")
+            MetadataValue.UInt8(byteVal.toUByte())
+        }
+        MetadataType.INT8 -> {
+            // 1-byte signed integer
+            val byteVal = input.read()
+            if (byteVal == -1) throw IOException("Unexpected EOF while reading int8 value.")
+            MetadataValue.Int8(byteVal.toByte())
+        }
+        MetadataType.UINT16 -> {
+            // 2-byte unsigned integer (little-endian)
+            val bytes = ByteArray(2)
+            if (input.read(bytes) != 2) throw IOException("Unexpected EOF while reading uint16 value.")
+            // Combine two bytes (little-endian) into an unsigned 16-bit value
+            val u16 = ((bytes[1].toInt() and 0xFF) shl 8) or (bytes[0].toInt() and 0xFF)
+            MetadataValue.UInt16(u16.toUShort())
+        }
+        MetadataType.INT16 -> {
+            // 2-byte signed integer (little-endian)
+            val bytes = ByteArray(2)
+            if (input.read(bytes) != 2) throw IOException("Unexpected EOF while reading int16 value.")
+            // Combine to 16-bit and interpret as signed
+            val i16 = ((bytes[1].toInt() and 0xFF) shl 8) or (bytes[0].toInt() and 0xFF)
+            MetadataValue.Int16(i16.toShort())
+        }
+        MetadataType.UINT32 -> {
+            // 4-byte unsigned integer (little-endian)
+            val bytes = ByteArray(4)
+            if (input.read(bytes) != 4) throw IOException("Unexpected EOF while reading uint32 value.")
+            // Combine four bytes into a 32-bit value (as Long to avoid overflow), then convert to UInt
+            val u32 = (bytes[3].toLong() and 0xFFL shl 24) or
+                (bytes[2].toLong() and 0xFFL shl 16) or
+                (bytes[1].toLong() and 0xFFL shl 8) or
+                (bytes[0].toLong() and 0xFFL)
+            MetadataValue.UInt32(u32.toUInt())
+        }
+        MetadataType.INT32 -> {
+            // 4-byte signed integer (little-endian)
+            val bytes = ByteArray(4)
+            if (input.read(bytes) != 4) throw IOException("Unexpected EOF while reading int32 value.")
+            // Combine four bytes into a 32-bit signed int
+            val i32 = (bytes[3].toInt() and 0xFF shl 24) or
+                (bytes[2].toInt() and 0xFF shl 16) or
+                (bytes[1].toInt() and 0xFF shl 8) or
+                (bytes[0].toInt() and 0xFF)
+            MetadataValue.Int32(i32)
+        }
+        MetadataType.FLOAT32 -> {
+            // 4-byte IEEE 754 float (little-endian)
+            val bytes = ByteArray(4)
+            if (input.read(bytes) != 4) throw IOException("Unexpected EOF while reading float32 value.")
+            // Assemble 4 bytes into a 32-bit int bit-pattern, then convert to Float
+            val bits = (bytes[3].toInt() and 0xFF shl 24) or
+                (bytes[2].toInt() and 0xFF shl 16) or
+                (bytes[1].toInt() and 0xFF shl 8) or
+                (bytes[0].toInt() and 0xFF)
+            val floatVal = Float.fromBits(bits)
+            MetadataValue.Float32(floatVal)
+        }
+        MetadataType.BOOL -> {
+            // 1-byte boolean (0 = false, 1 = true)
+            val byteVal = input.read()
+            if (byteVal == -1) throw IOException("Unexpected EOF while reading boolean value.")
+            if (byteVal != 0 && byteVal != 1) {
+                throw IOException("Invalid boolean value: $byteVal (must be 0 or 1).")
+            }
+            MetadataValue.Bool(byteVal != 0)
+        }
+        MetadataType.STRING -> {
+            // UTF-8 string (length-prefixed with 8-byte length)
+            val str = readString(input)
+            MetadataValue.StringVal(str)
+        }
+        MetadataType.ARRAY -> {
+            val elemType = MetadataType.fromCode(littleEndianBytesToInt(input.readNBytesExact(4)))
+            val len      = readLittleLong(input)
+            val count    = len.toInt()
+
+            if (arraySummariseThreshold >= 0 && count > arraySummariseThreshold) {
+                // fast‑forward without allocation
+                repeat(count) { skipValue(input, elemType) }
+                MetadataValue.StringVal("Array($elemType, $count items) /* summarised */")
+            } else {
+                val list = ArrayList<MetadataValue>(count)
+                repeat(count) { list += parseValue(input, elemType) }
+                MetadataValue.ArrayVal(elemType, list)
+            }
+        }
+        MetadataType.UINT64 -> {
+            // 8-byte unsigned integer (little-endian)
+            val bytes = ByteArray(8)
+            if (input.read(bytes) != 8) throw IOException("Unexpected EOF while reading uint64 value.")
+            // Combine 8 bytes into an unsigned 64-bit (ULong). Use ULong for full 0 to 2^64-1 range.
+            val u64 = (bytes[7].toULong() and 0xFFuL shl 56) or
+                (bytes[6].toULong() and 0xFFuL shl 48) or
+                (bytes[5].toULong() and 0xFFuL shl 40) or
+                (bytes[4].toULong() and 0xFFuL shl 32) or
+                (bytes[3].toULong() and 0xFFuL shl 24) or
+                (bytes[2].toULong() and 0xFFuL shl 16) or
+                (bytes[1].toULong() and 0xFFuL shl 8) or
+                (bytes[0].toULong() and 0xFFuL)
+            MetadataValue.UInt64(u64)
+        }
+        MetadataType.INT64 -> {
+            // 8-byte signed integer (little-endian)
+            val bytes = ByteArray(8)
+            if (input.read(bytes) != 8) throw IOException("Unexpected EOF while reading int64 value.")
+            // Combine 8 bytes into a signed 64-bit value (Long)
+            val i64 = (bytes[7].toLong() and 0xFFL shl 56) or
+                (bytes[6].toLong() and 0xFFL shl 48) or
+                (bytes[5].toLong() and 0xFFL shl 40) or
+                (bytes[4].toLong() and 0xFFL shl 32) or
+                (bytes[3].toLong() and 0xFFL shl 24) or
+                (bytes[2].toLong() and 0xFFL shl 16) or
+                (bytes[1].toLong() and 0xFFL shl 8) or
+                (bytes[0].toLong() and 0xFFL)
+            MetadataValue.Int64(i64)
+        }
+        MetadataType.FLOAT64 -> {
+            // 8-byte IEEE 754 double (little-endian)
+            val bytes = ByteArray(8)
+            if (input.read(bytes) != 8) throw IOException("Unexpected EOF while reading float64 value.")
+            // Assemble 8 bytes into a 64-bit bit-pattern, then convert to Double
+            val bits = (bytes[7].toLong() and 0xFFL shl 56) or
+                (bytes[6].toLong() and 0xFFL shl 48) or
+                (bytes[5].toLong() and 0xFFL shl 40) or
+                (bytes[4].toLong() and 0xFFL shl 32) or
+                (bytes[3].toLong() and 0xFFL shl 24) or
+                (bytes[2].toLong() and 0xFFL shl 16) or
+                (bytes[1].toLong() and 0xFFL shl 8) or
+                (bytes[0].toLong() and 0xFFL)
+            val doubleVal = Double.fromBits(bits)
+            MetadataValue.Float64(doubleVal)
+        }
+    }
+
+
+    private fun <T> T?.takeUnless(check: T.() -> Boolean): T? =
+        this?.takeIf { !it.check() }
+
+    /** Helper: Skip a value in the stream without storing it (still maintains pointer). */
+    private fun skipValue(input: InputStream, type: MetadataType) {
+        when (type) {
+            MetadataType.UINT8, MetadataType.INT8, MetadataType.BOOL -> input.skipFully(1)
+            MetadataType.UINT16, MetadataType.INT16                  -> input.skipFully(2)
+            MetadataType.UINT32, MetadataType.INT32, MetadataType.FLOAT32 -> input.skipFully(4)
+            MetadataType.UINT64, MetadataType.INT64, MetadataType.FLOAT64 -> input.skipFully(8)
+            MetadataType.STRING -> {
+                val len = readLittleLong(input); input.skipFully(len)
+            }
+            MetadataType.ARRAY -> {
+                val elemType = MetadataType.fromCode(littleEndianBytesToInt(input.readNBytesExact(4)))
+                val len      = readLittleLong(input)
+                repeat(len.toInt()) { skipValue(input, elemType) }   // recursive skip
+            }
+        }
+    }
+
+    /** Helper: Read an 8-byte little-endian unsigned value and return it as a signed Long (assuming it fits in 63 bits). */
+    private fun readLittleLong(input: InputStream): Long {
+        val bytes = ByteArray(8)
+        input.readFully(bytes)
+
+        // Combine 8 bytes into a 64-bit value (Little Endian).
+        // Note: If the value exceeds Long.MAX_VALUE (bit 63 is 1), this will produce a negative Long (two's complement).
+        // In our context (lengths/counts), such extremely large values are not expected.
+        return (bytes[7].toLong() and 0xFFL shl 56) or
+            (bytes[6].toLong() and 0xFFL shl 48) or
+            (bytes[5].toLong() and 0xFFL shl 40) or
+            (bytes[4].toLong() and 0xFFL shl 32) or
+            (bytes[3].toLong() and 0xFFL shl 24) or
+            (bytes[2].toLong() and 0xFFL shl 16) or
+            (bytes[1].toLong() and 0xFFL shl 8) or
+            (bytes[0].toLong() and 0xFFL)
+    }
+
+    /** Helper: Read a GGUF string from the stream (8-byte length followed by UTF-8 bytes). */
+    private fun readString(input: InputStream): String =
+        // Read 8-byte little-endian length (number of bytes in the string).
+        readLittleLong(input).let { len ->
+            if (len < 0 || len > Int.MAX_VALUE) throw IOException("String too long: $len")
+
+            // Read the UTF-8 bytes of the given length.
+            ByteArray(len.toInt()).let {
+                if (it.isNotEmpty()) input.readFully(it)
+                String(it, Charsets.UTF_8)
+            }
+        }
+
+    /** Helper: Convert a 4-byte little-endian byte array to a 32-bit integer. */
+    private fun littleEndianBytesToInt(bytes: ByteArray): Int =
+        // Note: assumes bytes length is 4.
+        (bytes[3].toInt() and 0xFF shl 24) or
+            (bytes[2].toInt() and 0xFF shl 16) or
+            (bytes[1].toInt() and 0xFF shl 8) or
+            (bytes[0].toInt() and 0xFF)
+
+    /**
+     * Robust skip that works the same on JDK 11 and Android’s desugared runtime.
+     *
+     * @param n  Number of bytes to advance in the stream.
+     * @throws IOException on premature EOF.
+     */
+    private fun InputStream.skipFully(n: Long) {
+        var remaining = n
+        val scratch = ByteArray(8192)                 // read‑and‑toss buffer
+        while (remaining > 0) {
+            val skipped = skip(remaining)
+            when {
+                skipped > 0      -> remaining -= skipped               // normal fast path
+                skipped == 0L    -> {
+                    // fallback: read and discard
+                    val read = read(scratch, 0, minOf(remaining, scratch.size.toLong()).toInt())
+                    if (read == -1) throw IOException("EOF while skipping $n bytes")
+                    remaining -= read
+                }
+                else             -> throw IOException("Skip returned negative value")
+            }
+        }
+    }
+
+    /**
+     * Extension that keeps reading until the requested number of bytes are filled.
+     * Falls back to `read()` when `skip()` returns 0, which happens on some Android
+     * streams.
+     *
+     * @param buf  Destination buffer.
+     * @param len  Number of bytes to fill (defaults to `buf.size`).
+     * @throws IOException on premature EOF.
+     */
+    private fun InputStream.readFully(buf: ByteArray, len: Int = buf.size) {
+        var off = 0
+        while (off < len) {
+            val n = read(buf, off, len - off)
+            if (n == -1) throw IOException("EOF after $off of $len bytes")
+            off += n
+        }
+    }
+
+    /**
+     * Read EXACTLY `n` bytes or throw – never returns a partially‑filled array.
+     * This is used for small fixed‑length reads (e.g. 4‑byte type codes).
+     *
+     * @throws IOException on premature EOF.
+     */
+    private fun InputStream.readNBytesExact(n: Int) = ByteArray(n).also {
+        if (read(it) != n) throw IOException("Unexpected EOF")
+    }
+}