ci : limit write permission to only the release step + fixes (#13392)

* ci : limit write permission to only the release step

* fix win cuda file name

* fix license file copy on multi-config generators

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

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

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

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

.github/workflows/build.yml

@@ -2,30 +2,19 @@ name: CI
 
 on:
   workflow_dispatch: # allows manual triggering
-    inputs:
-      create_release:
-        description: 'Create new release'
-        required: true
-        type: boolean
   push:
     branches:
       - master
-    paths: ['.github/workflows/build.yml', '.github/workflows/build-linux-cross.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal', '**/*.comp']
+    paths: ['.github/workflows/build.yml', '.github/workflows/build-linux-cross.yml', '**/CMakeLists.txt', '**/.cmake', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal', '**/*.comp']
   pull_request:
     types: [opened, synchronize, reopened]
-    paths: ['.github/workflows/build.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal', '**/*.comp']
+    paths: ['.github/workflows/build.yml', '.github/workflows/build-linux-cross.yml', '**/CMakeLists.txt', '**/.cmake', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal', '**/*.comp']
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
   cancel-in-progress: true
 
-# Fine-grant permission
-# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
-permissions:
-  contents: write # for creating release
-
 env:
-  BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
   GGML_NLOOP: 3
   GGML_N_THREADS: 1
   LLAMA_LOG_COLORS: 1
@@ -40,8 +29,6 @@ jobs:
       - name: Clone
         id: checkout
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
 
       - name: ccache
         uses: hendrikmuhs/ccache-action@v1.2.16
@@ -74,33 +61,6 @@ jobs:
           cd build
           ctest -L 'main|curl' --verbose --timeout 900
 
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Pack artifacts
-        id: pack_artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        run: |
-          cp LICENSE ./build/bin/
-          zip -r llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip ./build/bin/*
-
-      - name: Upload artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip
-          name: llama-bin-macos-arm64.zip
-
   macOS-latest-cmake-x64:
     runs-on: macos-13
 
@@ -108,8 +68,6 @@ jobs:
       - name: Clone
         id: checkout
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
 
       - name: ccache
         uses: hendrikmuhs/ccache-action@v1.2.16
@@ -143,33 +101,6 @@ jobs:
           cd build
           ctest -L main --verbose --timeout 900
 
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Pack artifacts
-        id: pack_artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        run: |
-          cp LICENSE ./build/bin/
-          zip -r llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip ./build/bin/*
-
-      - name: Upload artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip
-          name: llama-bin-macos-x64.zip
-
   ubuntu-cpu-cmake:
     strategy:
       matrix:
@@ -185,8 +116,6 @@ jobs:
       - name: Clone
         id: checkout
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
 
       - name: ccache
         uses: hendrikmuhs/ccache-action@v1.2.16
@@ -225,33 +154,6 @@ jobs:
           ./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
 
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Pack artifacts
-        id: pack_artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        run: |
-          cp LICENSE ./build/bin/
-          zip -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip ./build/bin/*
-
-      - name: Upload artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip
-          name: llama-bin-ubuntu-${{ matrix.build }}.zip
-
   ubuntu-latest-cmake-sanitizer:
     runs-on: ubuntu-latest
 
@@ -378,8 +280,6 @@ jobs:
       - name: Clone
         id: checkout
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
 
       - name: ccache
         uses: hendrikmuhs/ccache-action@v1.2.16
@@ -409,33 +309,6 @@ jobs:
           # This is using llvmpipe and runs slower than other backends
           ctest -L main --verbose --timeout 2700
 
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Pack artifacts
-        id: pack_artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        run: |
-          cp LICENSE ./build/bin/
-          zip -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip ./build/bin/*
-
-      - name: Upload artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip
-          name: llama-bin-ubuntu-vulkan-x64.zip
-
   ubuntu-22-cmake-hip:
     runs-on: ubuntu-22.04
     container: rocm/dev-ubuntu-22.04:6.0.2
@@ -831,8 +704,6 @@ jobs:
       - name: Clone
         id: checkout
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
 
       - name: ccache
         uses: hendrikmuhs/ccache-action@v1.2.16
@@ -935,35 +806,6 @@ jobs:
       #     $env:LLAMA_SKIP_TESTS_SLOW_ON_EMULATOR = 1
       #     & $sde -future -- ctest -L main -C Release --verbose --timeout 900
 
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Pack artifacts
-        id: pack_artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        env:
-          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
-        run: |
-          Copy-Item $env:CURL_PATH\bin\libcurl-x64.dll .\build\bin\Release\libcurl-x64.dll
-          7z a llama-${{ steps.tag.outputs.name }}-bin-win-${{ matrix.build }}.zip .\build\bin\Release\*
-
-      - name: Upload artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-win-${{ matrix.build }}.zip
-          name: llama-bin-win-${{ matrix.build }}.zip
-
   ubuntu-latest-cmake-cuda:
     runs-on: ubuntu-latest
     container: nvidia/cuda:12.6.2-devel-ubuntu24.04
@@ -972,8 +814,6 @@ jobs:
         - name: Clone
           id: checkout
           uses: actions/checkout@v4
-          with:
-            fetch-depth: 0
 
         - name: Install dependencies
           env:
@@ -1005,77 +845,23 @@ jobs:
     strategy:
       matrix:
         cuda: ['12.4', '11.7']
-        build: ['cuda']
 
     steps:
       - name: Clone
         id: checkout
         uses: actions/checkout@v4
-        with:
-            fetch-depth: 0
 
       - name: Install ccache
         uses: hendrikmuhs/ccache-action@v1.2.16
         with:
-          key: ${{ github.job }}-${{ matrix.cuda }}-${{ matrix.build }}
+          key: windows-cuda-${{ matrix.cuda }}
           variant: ccache
           evict-old-files: 1d
 
-      - name: Install Cuda Toolkit 11.7
-        if: ${{ matrix.cuda == '11.7' }}
-        run: |
-          mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7"
-          choco install unzip -y
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-11.7.99-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-11.7.99-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-11.7.99-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-11.7.4.6-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-11.7.91-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-11.7.91-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvprof/windows-x86_64/cuda_nvprof-windows-x86_64-11.7.101-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-11.7.91-archive.zip"
-          unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7"
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_cudart-windows-x86_64-11.7.99-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvcc-windows-x86_64-11.7.99-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvrtc-windows-x86_64-11.7.99-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\libcublas-windows-x86_64-11.7.4.6-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvtx-windows-x86_64-11.7.91-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\visual_studio_integration-windows-x86_64-11.7.91-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvprof-windows-x86_64-11.7.101-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_cccl-windows-x86_64-11.7.91-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
-          echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-          echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\libnvvp" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-          echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
-          echo "CUDA_PATH_V11_7=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
-
-      - name: Install Cuda Toolkit 12.4
-        if: ${{ matrix.cuda == '12.4' }}
-        run: |
-          mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4"
-          choco install unzip -y
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-12.4.127-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-12.4.131-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-12.4.127-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-12.4.5.8-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-12.4.127-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_profiler_api/windows-x86_64/cuda_profiler_api-windows-x86_64-12.4.127-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-12.4.127-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvprof/windows-x86_64/cuda_nvprof-windows-x86_64-12.4.127-archive.zip"
-          curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-12.4.127-archive.zip"
-          unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4"
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_cudart-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvcc-windows-x86_64-12.4.131-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvrtc-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\libcublas-windows-x86_64-12.4.5.8-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvtx-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_profiler_api-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\visual_studio_integration-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvprof-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
-          xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_cccl-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
-          echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-          echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\libnvvp" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-          echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
-          echo "CUDA_PATH_V12_4=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
+      - name: Install Cuda Toolkit
+        uses: ./.github/actions/windows-setup-cuda
+        with:
+          cuda_version: ${{ matrix.cuda }}
 
       - name: Install Ninja
         id: install_ninja
@@ -1105,51 +891,6 @@ jobs:
           cmake --build build --config Release -j %NINJA_JOBS% -t ggml
           cmake --build build --config Release
 
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Pack artifacts
-        id: pack_artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        env:
-          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
-        run: |
-          cp $env:CURL_PATH\bin\libcurl-x64.dll .\build\bin\Release\libcurl-x64.dll
-          7z a llama-${{ steps.tag.outputs.name }}-bin-win-${{ matrix.build }}-cu${{ matrix.cuda }}-x64.zip .\build\bin\Release\*
-
-      - name: Upload artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-win-${{ matrix.build }}-cu${{ matrix.cuda }}-x64.zip
-          name: llama-bin-win-cu${{ matrix.cuda }}-x64.zip
-
-      - name: Copy and pack Cuda runtime
-        if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
-        run: |
-          echo "Cuda install location: ${{ env.CUDA_PATH }}"
-          $dst='.\build\bin\cudart\'
-          robocopy "${{env.CUDA_PATH}}\bin" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll
-          robocopy "${{env.CUDA_PATH}}\lib" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll
-          7z a cudart-llama-bin-win-cu${{ matrix.cuda }}-x64.zip $dst\*
-
-      - name: Upload Cuda runtime
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        uses: actions/upload-artifact@v4
-        with:
-          path: cudart-llama-bin-win-cu${{ matrix.cuda }}-x64.zip
-          name: cudart-llama-bin-win-cu${{ matrix.cuda }}-x64.zip
-
   windows-latest-cmake-sycl:
     runs-on: windows-latest
 
@@ -1165,8 +906,6 @@ jobs:
       - name: Clone
         id: checkout
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
 
       - name: ccache
         uses: hendrikmuhs/ccache-action@v1.2.16
@@ -1185,52 +924,6 @@ jobs:
         id: cmake_build
         run:  examples/sycl/win-build-sycl.bat
 
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Build the release package
-        id: pack_artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        run: |
-          echo "cp oneAPI running time dll files in ${{ env.ONEAPI_ROOT }} to ./build/bin"
-
-          cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_sycl_blas.5.dll" ./build/bin
-          cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_core.2.dll" ./build/bin
-          cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_tbb_thread.2.dll" ./build/bin
-
-          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_level_zero.dll" ./build/bin
-          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_opencl.dll" ./build/bin
-          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_loader.dll" ./build/bin
-          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_win_proxy_loader.dll" ./build/bin
-
-          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/sycl8.dll" ./build/bin
-          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/svml_dispmd.dll" ./build/bin
-          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libmmd.dll" ./build/bin
-          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libiomp5md.dll" ./build/bin
-
-          cp "${{ env.ONEAPI_ROOT }}/dnnl/latest/bin/dnnl.dll" ./build/bin
-          cp "${{ env.ONEAPI_ROOT }}/tbb/latest/bin/tbb12.dll" ./build/bin
-
-          echo "cp oneAPI running time dll files to ./build/bin done"
-          7z a llama-${{ steps.tag.outputs.name }}-bin-win-sycl-x64.zip ./build/bin/*
-
-      - name: Upload the release package
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-win-sycl-x64.zip
-          name: llama-bin-win-sycl-x64.zip
-
   windows-latest-cmake-hip:
     if: ${{ github.event.inputs.create_release != 'true' }}
     runs-on: windows-latest
@@ -1288,110 +981,12 @@ jobs:
             -DCURL_LIBRARY="$env:CURL_PATH/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:CURL_PATH/include"
           cmake --build build -j ${env:NUMBER_OF_PROCESSORS}
 
-  # TODO: reuse windows-latest-cmake-hip instead of duplicating this job
-  windows-latest-cmake-hip-release:
-    if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-    runs-on: windows-latest
-
-    strategy:
-      matrix:
-        gpu_target: [gfx1100, gfx1101, gfx1030]
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v4
-        with:
-            fetch-depth: 0
-
-      - name: Clone rocWMMA repository
-        id: clone_rocwmma
-        run: |
-          git clone https://github.com/rocm/rocwmma --branch rocm-6.2.4 --depth 1
-
-      - name: ccache
-        uses: hendrikmuhs/ccache-action@v1.2.16
-        with:
-          key: windows-latest-cmake-hip-release
-          evict-old-files: 1d
-
-      - name: Install
-        id: depends
-        run: |
-          $ErrorActionPreference = "Stop"
-          write-host "Downloading AMD HIP SDK Installer"
-          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
-          write-host "Installing AMD HIP SDK"
-          Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
-          write-host "Completed AMD HIP SDK installation"
-
-      - name: Verify ROCm
-        id: verify
-        run: |
-          & 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
-
-      - name: libCURL
-        id: get_libcurl
-        uses: ./.github/actions/windows-setup-curl
-
-      - name: Build
-        id: cmake_build
-        env:
-          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
-        run: |
-          $env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
-          $env:CMAKE_PREFIX_PATH="${env:HIP_PATH}"
-          cmake -G "Unix Makefiles" -B build -S . `
-            -DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
-            -DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
-            -DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/rocwmma/library/include/" `
-            -DCMAKE_BUILD_TYPE=Release `
-            -DAMDGPU_TARGETS=${{ matrix.gpu_target }} `
-            -DGGML_HIP_ROCWMMA_FATTN=ON `
-            -DGGML_HIP=ON `
-            -DGGML_RPC=ON `
-            -DCURL_LIBRARY="$env:CURL_PATH/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:CURL_PATH/include"
-          cmake --build build -j ${env:NUMBER_OF_PROCESSORS}
-          md "build\bin\rocblas\library\"
-          cp "${env:HIP_PATH}\bin\hipblas.dll" "build\bin\"
-          cp "${env:HIP_PATH}\bin\rocblas.dll" "build\bin\"
-          cp "${env:HIP_PATH}\bin\rocblas\library\*" "build\bin\rocblas\library\"
-
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Pack artifacts
-        id: pack_artifacts
-        env:
-          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
-        run: |
-          cp $env:CURL_PATH\bin\libcurl-x64.dll .\build\bin\libcurl-x64.dll
-          7z a llama-${{ steps.tag.outputs.name }}-bin-win-hip-x64-${{ matrix.gpu_target }}.zip .\build\bin\*
-
-      - name: Upload artifacts
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-bin-win-hip-x64-${{ matrix.gpu_target }}.zip
-          name: llama-bin-win-hip-x64-${{ matrix.gpu_target }}.zip
-
   ios-xcode-build:
     runs-on: macos-latest
 
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
 
       - name: Build
         id: cmake_build
@@ -1418,32 +1013,6 @@ jobs:
       - name: Build Xcode project
         run: xcodebuild -project examples/llama.swiftui/llama.swiftui.xcodeproj -scheme llama.swiftui -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' FRAMEWORK_FOLDER_PATH=./build-ios build
 
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Pack artifacts
-        id: pack_artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        run: |
-          zip --symlinks -r llama-${{ steps.tag.outputs.name }}-xcframework.zip build-apple/llama.xcframework
-
-      - name: Upload artifacts
-        if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-        uses: actions/upload-artifact@v4
-        with:
-          path: llama-${{ steps.tag.outputs.name }}-xcframework.zip
-          name: llama-${{ steps.tag.outputs.name }}-xcframework
-
   android-build:
     runs-on: ubuntu-latest
 
@@ -1471,283 +1040,8 @@ jobs:
       - name: Build
         run: |
           cd examples/llama.android
-
           ./gradlew build --no-daemon
 
-  release:
-    if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
-
-    runs-on: ubuntu-latest
-
-    needs:
-      - ubuntu-cpu-cmake
-      - ubuntu-22-cmake-vulkan
-      - windows-latest-cmake
-      - windows-2019-cmake-cuda
-      - windows-latest-cmake-sycl
-      - windows-latest-cmake-hip-release
-      - macOS-latest-cmake-arm64
-      - macOS-latest-cmake-x64
-
-    steps:
-      - name: Clone
-        id: checkout
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-
-      - name: ccache
-        uses: hendrikmuhs/ccache-action@v1.2.16
-        with:
-          key: release
-          evict-old-files: 1d
-
-      - name: Determine tag name
-        id: tag
-        shell: bash
-        run: |
-          BUILD_NUMBER="$(git rev-list --count HEAD)"
-          SHORT_HASH="$(git rev-parse --short=7 HEAD)"
-          if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
-            echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
-          else
-            SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
-            echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Download artifacts
-        id: download-artifact
-        uses: actions/download-artifact@v4
-        with:
-          path: ./artifact
-
-      - name: Move artifacts
-        id: move_artifacts
-        run: mkdir -p ./artifact/release && mv ./artifact/*/*.zip ./artifact/release
-
-      - name: Create release
-        id: create_release
-        uses: ggml-org/action-create-release@v1
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        with:
-          tag_name: ${{ steps.tag.outputs.name }}
-
-      - name: Upload release
-        id: upload_release
-        uses: actions/github-script@v3
-        with:
-          github-token: ${{secrets.GITHUB_TOKEN}}
-          script: |
-            const path = require('path');
-            const fs = require('fs');
-            const release_id = '${{ steps.create_release.outputs.id }}';
-            for (let file of await fs.readdirSync('./artifact/release')) {
-              if (path.extname(file) === '.zip') {
-                console.log('uploadReleaseAsset', file);
-                await github.repos.uploadReleaseAsset({
-                  owner: context.repo.owner,
-                  repo: context.repo.repo,
-                  release_id: release_id,
-                  name: file,
-                  data: await fs.readFileSync(`./artifact/release/${file}`)
-                });
-              }
-            }
-
-#  ubuntu-latest-gcc:
-#    runs-on: ubuntu-latest
-#
-#    strategy:
-#      matrix:
-#        build: [Debug, Release]
-#
-#    steps:
-#      - name: Clone
-#        uses: actions/checkout@v4
-#
-#      - name: Dependencies
-#        run: |
-#          sudo apt-get update
-#          sudo apt-get install build-essential
-#          sudo apt-get install cmake
-#
-#      - name: Configure
-#        run: cmake . -DCMAKE_BUILD_TYPE=${{ matrix.build }}
-#
-#      - name: Build
-#        run: |
-#          make
-#
-#  ubuntu-latest-clang:
-#    runs-on: ubuntu-latest
-#
-#    strategy:
-#      matrix:
-#        build: [Debug, Release]
-#
-#    steps:
-#      - name: Clone
-#        uses: actions/checkout@v4
-#
-#      - name: Dependencies
-#        run: |
-#          sudo apt-get update
-#          sudo apt-get install build-essential
-#          sudo apt-get install cmake
-#
-#      - name: Configure
-#        run: cmake . -DCMAKE_BUILD_TYPE=${{ matrix.build }} -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang
-#
-#      - name: Build
-#        run: |
-#          make
-#
-#  ubuntu-latest-gcc-sanitized:
-#    runs-on: ubuntu-latest
-#
-#    strategy:
-#      matrix:
-#        sanitizer: [ADDRESS, THREAD, UNDEFINED]
-#
-#    steps:
-#      - name: Clone
-#        uses: actions/checkout@v4
-#
-#      - name: Dependencies
-#        run: |
-#          sudo apt-get update
-#          sudo apt-get install build-essential
-#          sudo apt-get install cmake
-#
-#      - name: Configure
-#        run: cmake . -DCMAKE_BUILD_TYPE=Debug -DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON
-#
-#      - name: Build
-#        run: |
-#          make
-#
-#  windows:
-#    runs-on: windows-latest
-#
-#    strategy:
-#      matrix:
-#        build: [Release]
-#        arch: [Win32, x64]
-#        include:
-#          - arch: Win32
-#            s2arc: x86
-#          - arch: x64
-#            s2arc: x64
-#
-#    steps:
-#      - name: Clone
-#        uses: actions/checkout@v4
-#
-#      - name: Add msbuild to PATH
-#        uses: microsoft/setup-msbuild@v1
-#
-#      - name: Configure
-#        run: >
-#          cmake -S . -B ./build -A ${{ matrix.arch }}
-#          -DCMAKE_BUILD_TYPE=${{ matrix.build }}
-#
-#      - name: Build
-#        run: |
-#          cd ./build
-#          msbuild ALL_BUILD.vcxproj -t:build -p:configuration=${{ matrix.build }} -p:platform=${{ matrix.arch }}
-#
-#      - name: Upload binaries
-#        uses: actions/upload-artifact@v4
-#        with:
-#          name: llama-bin-${{ matrix.arch }}
-#          path: build/bin/${{ matrix.build }}
-#
-#  windows-blas:
-#    runs-on: windows-latest
-#
-#    strategy:
-#      matrix:
-#        build: [Release]
-#        arch: [Win32, x64]
-#        blas: [ON]
-#        include:
-#          - arch: Win32
-#            obzip: https://github.com/xianyi/OpenBLAS/releases/download/v0.3.21/OpenBLAS-0.3.21-x86.zip
-#            s2arc: x86
-#          - arch: x64
-#            obzip: https://github.com/xianyi/OpenBLAS/releases/download/v0.3.21/OpenBLAS-0.3.21-x64.zip
-#            s2arc: x64
-#
-#    steps:
-#      - name: Clone
-#        uses: actions/checkout@v4
-#
-#      - name: Add msbuild to PATH
-#        uses: microsoft/setup-msbuild@v1
-#
-#      - name: Fetch OpenBLAS
-#        if: matrix.blas == 'ON'
-#        run: |
-#          C:/msys64/usr/bin/wget.exe -qO blas.zip ${{ matrix.obzip }}
-#          7z x blas.zip -oblas -y
-#          copy blas/include/cblas.h .
-#          copy blas/include/openblas_config.h .
-#          echo "blasdir=$env:GITHUB_WORKSPACE/blas" >> $env:GITHUB_ENV
-#
-#      - name: Configure
-#        run: >
-#          cmake -S . -B ./build -A ${{ matrix.arch }}
-#          -DCMAKE_BUILD_TYPE=${{ matrix.build }}
-#          -DLLAMA_SUPPORT_OPENBLAS=${{ matrix.blas }}
-#          -DCMAKE_LIBRARY_PATH="$env:blasdir/lib"
-#
-#      - name: Build
-#        run: |
-#          cd ./build
-#          msbuild ALL_BUILD.vcxproj -t:build -p:configuration=${{ matrix.build }} -p:platform=${{ matrix.arch }}
-#
-#      - name: Copy libopenblas.dll
-#        if: matrix.blas == 'ON'
-#        run: copy "$env:blasdir/bin/libopenblas.dll" build/bin/${{ matrix.build }}
-#
-#      - name: Upload binaries
-#        if: matrix.blas == 'ON'
-#        uses: actions/upload-artifact@v4
-#        with:
-#          name: llama-blas-bin-${{ matrix.arch }}
-#          path: build/bin/${{ matrix.build }}
-#
-#  emscripten:
-#    runs-on: ubuntu-latest
-#
-#    strategy:
-#      matrix:
-#        build: [Release]
-#
-#    steps:
-#      - name: Clone
-#        uses: actions/checkout@v4
-#
-#      - name: Dependencies
-#        run: |
-#          wget -q https://github.com/emscripten-core/emsdk/archive/master.tar.gz
-#          tar -xvf master.tar.gz
-#          emsdk-master/emsdk update
-#          emsdk-master/emsdk install latest
-#          emsdk-master/emsdk activate latest
-#
-#      - name: Configure
-#        run: echo "tmp"
-#
-#      - name: Build
-#        run: |
-#          pushd emsdk-master
-#          source ./emsdk_env.sh
-#          popd
-#          emcmake cmake . -DCMAKE_BUILD_TYPE=${{ matrix.build }}
-#          make
-
   openEuler-latest-cmake-cann:
     if: ${{ github.event_name != 'pull_request' || contains(github.event.pull_request.labels.*.name, 'Ascend NPU') }}
     defaults:

.github/workflows/docker.yml

@@ -36,10 +36,14 @@ jobs:
       matrix:
         config:
           # Multi-stage build
-          - { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64,linux/arm64", full: true, light: true, server: true, free_disk_space: false }
+          # Note: the arm64 images are failing, which prevents the amd64 images from being built
+          # https://github.com/ggml-org/llama.cpp/issues/11888
+          #- { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64,linux/arm64", full: true, light: true, server: true, free_disk_space: false }
+          - { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
           - { tag: "cuda", dockerfile: ".devops/cuda.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
           - { tag: "musa", dockerfile: ".devops/musa.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true }
-          - { tag: "intel", dockerfile: ".devops/intel.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
+          # Note: the intel images are failing due to an out of disk space error
+          # - { tag: "intel", dockerfile: ".devops/intel.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
           - { tag: "vulkan", dockerfile: ".devops/vulkan.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
           # Note: the rocm images are failing due to a compiler error and are disabled until this is fixed to allow the workflow to complete
           #- {tag: "rocm", dockerfile: ".devops/rocm.Dockerfile", platforms: "linux/amd64,linux/arm64", full: true, light: true, server: true, free_disk_space: true }

.github/workflows/release.yml

@@ -0,0 +1,709 @@
+name: Create Release
+
+on:
+  workflow_dispatch: # allows manual triggering
+    inputs:
+      create_release:
+        description: 'Create new release'
+        required: true
+        type: boolean
+  push:
+    branches:
+      - master
+    paths: ['.github/workflows/release.yml', '**/CMakeLists.txt', '**/.cmake', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal', '**/*.comp']
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+env:
+  BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
+  CMAKE_ARGS: "-DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_TOOLS=ON -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON"
+
+jobs:
+  macOS-arm64:
+    runs-on: macos-14
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: macOS-latest-cmake-arm64
+          evict-old-files: 1d
+
+      - name: Dependencies
+        id: depends
+        continue-on-error: true
+        run: |
+          brew update
+          brew install curl
+
+      - name: Build
+        id: cmake_build
+        run: |
+          sysctl -a
+          cmake -B build \
+            -DCMAKE_BUILD_RPATH="@loader_path" \
+            -DLLAMA_FATAL_WARNINGS=ON \
+            -DGGML_METAL_USE_BF16=ON \
+            -DGGML_METAL_EMBED_LIBRARY=ON \
+            -DGGML_RPC=ON \
+            ${{ env.CMAKE_ARGS }}
+          cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        run: |
+          cp LICENSE ./build/bin/
+          zip -r llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip ./build/bin/*
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.zip
+          name: llama-bin-macos-arm64.zip
+
+  macOS-x64:
+    runs-on: macos-13
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: macOS-latest-cmake-x64
+          evict-old-files: 1d
+
+      - name: Dependencies
+        id: depends
+        continue-on-error: true
+        run: |
+          brew update
+          brew install curl
+
+      - name: Build
+        id: cmake_build
+        run: |
+          sysctl -a
+          # Metal is disabled due to intermittent failures with Github runners not having a GPU:
+          # https://github.com/ggml-org/llama.cpp/actions/runs/8635935781/job/23674807267#step:5:2313
+          cmake -B build \
+            -DCMAKE_BUILD_RPATH="@loader_path" \
+            -DLLAMA_FATAL_WARNINGS=ON \
+            -DGGML_METAL=OFF \
+            -DGGML_RPC=ON
+          cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        run: |
+          cp LICENSE ./build/bin/
+          zip -r llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip ./build/bin/*
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-macos-x64.zip
+          name: llama-bin-macos-x64.zip
+
+  ubuntu-22-cpu:
+    strategy:
+      matrix:
+        include:
+          - build: 'x64'
+            os: ubuntu-22.04
+          - build: 'arm64'
+            os: ubuntu-22.04-arm
+
+    runs-on: ${{ matrix.os }}
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: ubuntu-cpu-cmake
+          evict-old-files: 1d
+
+      - name: Dependencies
+        id: depends
+        run: |
+          sudo apt-get update
+          sudo apt-get install build-essential libcurl4-openssl-dev
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build \
+            -DLLAMA_FATAL_WARNINGS=ON \
+            ${{ env.CMAKE_ARGS }}
+          cmake --build build --config Release -j $(nproc)
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        run: |
+          cp LICENSE ./build/bin/
+          zip -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip ./build/bin/*
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.zip
+          name: llama-bin-ubuntu-${{ matrix.build }}.zip
+
+  ubuntu-22-vulkan:
+    runs-on: ubuntu-22.04
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: ubuntu-22-cmake-vulkan
+          evict-old-files: 1d
+
+      - name: Dependencies
+        id: depends
+        run: |
+          wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | sudo apt-key add -
+          sudo wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
+          sudo apt-get update -y
+          sudo apt-get install -y build-essential mesa-vulkan-drivers vulkan-sdk libcurl4-openssl-dev
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build \
+            -DGGML_VULKAN=ON \
+            ${{ env.CMAKE_ARGS }}
+          cmake --build build --config Release -j $(nproc)
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        run: |
+          cp LICENSE ./build/bin/
+          zip -r llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip ./build/bin/*
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.zip
+          name: llama-bin-ubuntu-vulkan-x64.zip
+
+  windows:
+    runs-on: windows-latest
+
+    env:
+      OPENBLAS_VERSION: 0.3.23
+      VULKAN_VERSION: 1.4.309.0
+
+    strategy:
+      matrix:
+        include:
+          - build: 'cpu-x64'
+            defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_OPENMP=OFF'
+          #- build: 'openblas-x64'
+          #  defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/x64-windows-llvm.cmake -DGGML_NATIVE=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_OPENMP=OFF -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS -DBLAS_INCLUDE_DIRS="$env:RUNNER_TEMP/openblas/include" -DBLAS_LIBRARIES="$env:RUNNER_TEMP/openblas/lib/openblas.lib"'
+          - build: 'vulkan-x64'
+            defines: '-DGGML_NATIVE=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DGGML_VULKAN=ON'
+          - build: 'cpu-arm64'
+            defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DGGML_NATIVE=OFF'
+          - build: 'opencl-adreno-arm64'
+            defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" -DGGML_OPENCL=ON -DGGML_OPENCL_USE_ADRENO_KERNELS=ON'
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: windows-latest-cmake-${{ matrix.build }}
+          variant: ccache
+          evict-old-files: 1d
+
+      - name: Download OpenBLAS
+        id: get_openblas
+        if: ${{ matrix.build == 'openblas-x64' }}
+        run: |
+          curl.exe -o $env:RUNNER_TEMP/openblas.zip -L "https://github.com/xianyi/OpenBLAS/releases/download/v${env:OPENBLAS_VERSION}/OpenBLAS-${env:OPENBLAS_VERSION}-x64.zip"
+          curl.exe -o $env:RUNNER_TEMP/OpenBLAS.LICENSE.txt -L "https://github.com/xianyi/OpenBLAS/raw/v${env:OPENBLAS_VERSION}/LICENSE"
+          mkdir $env:RUNNER_TEMP/openblas
+          tar.exe -xvf $env:RUNNER_TEMP/openblas.zip -C $env:RUNNER_TEMP/openblas
+          $vcdir = $(vswhere -latest -products * -requires Microsoft.VisualStudio.Component.VC.Tools.x86.x64 -property installationPath)
+          $msvc = $(join-path $vcdir $('VC\Tools\MSVC\'+$(gc -raw $(join-path $vcdir 'VC\Auxiliary\Build\Microsoft.VCToolsVersion.default.txt')).Trim()))
+          $lib =  $(join-path $msvc 'bin\Hostx64\x64\lib.exe')
+          & $lib /machine:x64 "/def:${env:RUNNER_TEMP}/openblas/lib/libopenblas.def" "/out:${env:RUNNER_TEMP}/openblas/lib/openblas.lib" /name:openblas.dll
+
+      - name: Install Vulkan SDK
+        id: get_vulkan
+        if: ${{ matrix.build == 'vulkan-x64' }}
+        run: |
+          curl.exe -o $env:RUNNER_TEMP/VulkanSDK-Installer.exe -L "https://sdk.lunarg.com/sdk/download/${env:VULKAN_VERSION}/windows/VulkanSDK-${env:VULKAN_VERSION}-Installer.exe"
+          & "$env:RUNNER_TEMP\VulkanSDK-Installer.exe" --accept-licenses --default-answer --confirm-command install
+          Add-Content $env:GITHUB_ENV "VULKAN_SDK=C:\VulkanSDK\${env:VULKAN_VERSION}"
+          Add-Content $env:GITHUB_PATH "C:\VulkanSDK\${env:VULKAN_VERSION}\bin"
+
+      - name: Install Ninja
+        id: install_ninja
+        run: |
+          choco install ninja
+
+      - name: Install OpenCL Headers and Libs
+        id: install_opencl
+        if: ${{ matrix.build == 'opencl-adreno-arm64' }}
+        run: |
+          git clone https://github.com/KhronosGroup/OpenCL-Headers
+          cd OpenCL-Headers
+          cmake -B build `
+            -DBUILD_TESTING=OFF `
+            -DOPENCL_HEADERS_BUILD_TESTING=OFF `
+            -DOPENCL_HEADERS_BUILD_CXX_TESTS=OFF `
+            -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
+          cmake --build build --target install
+          git clone https://github.com/KhronosGroup/OpenCL-ICD-Loader
+          cd OpenCL-ICD-Loader
+          cmake -B build-arm64-release `
+            -A arm64 `
+            -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" `
+            -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
+          cmake --build build-arm64-release --target install --config release
+
+      - name: libCURL
+        id: get_libcurl
+        uses: ./.github/actions/windows-setup-curl
+
+      - name: Build
+        id: cmake_build
+        env:
+          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
+        run: |
+          cmake -S . -B build ${{ matrix.defines }} `
+            -DCURL_LIBRARY="$env:CURL_PATH/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:CURL_PATH/include" `
+            ${{ env.CMAKE_ARGS }}
+          cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS}
+
+      - name: Add libopenblas.dll
+        id: add_libopenblas_dll
+        if: ${{ matrix.build == 'openblas-x64' }}
+        run: |
+          cp $env:RUNNER_TEMP/openblas/bin/libopenblas.dll ./build/bin/Release/openblas.dll
+          cp $env:RUNNER_TEMP/OpenBLAS.LICENSE.txt ./build/bin/Release/OpenBLAS-${env:OPENBLAS_VERSION}.txt
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        env:
+          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
+        run: |
+          Copy-Item $env:CURL_PATH\bin\libcurl-x64.dll .\build\bin\Release\libcurl-x64.dll
+          7z a llama-${{ steps.tag.outputs.name }}-bin-win-${{ matrix.build }}.zip .\build\bin\Release\*
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-win-${{ matrix.build }}.zip
+          name: llama-bin-win-${{ matrix.build }}.zip
+
+  windows-cuda:
+    runs-on: windows-2019
+
+    strategy:
+      matrix:
+        cuda: ['12.4', '11.7']
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+            fetch-depth: 0
+
+      - name: Install ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: windows-cuda-${{ matrix.cuda }}
+          variant: ccache
+          evict-old-files: 1d
+
+      - name: Install Cuda Toolkit
+        uses: ./.github/actions/windows-setup-cuda
+        with:
+          cuda_version: ${{ matrix.cuda }}
+
+      - name: Install Ninja
+        id: install_ninja
+        run: |
+          choco install ninja
+
+      - name: libCURL
+        id: get_libcurl
+        uses: ./.github/actions/windows-setup-curl
+
+      - name: Build
+        id: cmake_build
+        shell: cmd
+        env:
+          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
+        run: |
+          call "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Auxiliary\Build\vcvars64.bat"
+          cmake -S . -B build -G "Ninja Multi-Config" ^
+            -DGGML_NATIVE=OFF ^
+            -DGGML_BACKEND_DL=ON ^
+            -DGGML_CPU_ALL_VARIANTS=ON ^
+            -DGGML_CUDA=ON ^
+            -DCURL_LIBRARY="%CURL_PATH%/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="%CURL_PATH%/include" ^
+            ${{ env.CMAKE_ARGS }}
+          set /A NINJA_JOBS=%NUMBER_OF_PROCESSORS%-1
+          cmake --build build --config Release -j %NINJA_JOBS% -t ggml
+          cmake --build build --config Release
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        env:
+          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
+        run: |
+          cp $env:CURL_PATH\bin\libcurl-x64.dll .\build\bin\Release\libcurl-x64.dll
+          7z a llama-${{ steps.tag.outputs.name }}-bin-win-cuda${{ matrix.cuda }}-x64.zip .\build\bin\Release\*
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-win-cuda${{ matrix.cuda }}-x64.zip
+          name: llama-bin-win-cuda${{ matrix.cuda }}-x64.zip
+
+      - name: Copy and pack Cuda runtime
+        run: |
+          echo "Cuda install location: ${{ env.CUDA_PATH }}"
+          $dst='.\build\bin\cudart\'
+          robocopy "${{env.CUDA_PATH}}\bin" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll
+          robocopy "${{env.CUDA_PATH}}\lib" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll
+          7z a cudart-llama-bin-win-cuda${{ matrix.cuda }}-x64.zip $dst\*
+
+      - name: Upload Cuda runtime
+        uses: actions/upload-artifact@v4
+        with:
+          path: cudart-llama-bin-win-cuda${{ matrix.cuda }}-x64.zip
+          name: cudart-llama-bin-win-cuda${{ matrix.cuda }}-x64.zip
+
+  windows-sycl:
+    runs-on: windows-latest
+
+    defaults:
+      run:
+        shell: bash
+
+    env:
+      WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/b380d914-366b-4b77-a74a-05e3c38b3514/intel-oneapi-base-toolkit-2025.0.0.882_offline.exe
+      WINDOWS_DPCPP_MKL: intel.oneapi.win.cpp-dpcpp-common:intel.oneapi.win.mkl.devel:intel.oneapi.win.dnnl:intel.oneapi.win.tbb.devel
+      ONEAPI_ROOT: "C:/Program Files (x86)/Intel/oneAPI"
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: windows-latest-cmake-sycl
+          variant: ccache
+          evict-old-files: 1d
+
+      - name: Install
+        run:  |
+          scripts/install-oneapi.bat $WINDOWS_BASEKIT_URL $WINDOWS_DPCPP_MKL
+
+      # TODO: add libcurl support ; we will also need to modify win-build-sycl.bat to accept user-specified args
+
+      - name: Build
+        id: cmake_build
+        run:  examples/sycl/win-build-sycl.bat
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Build the release package
+        id: pack_artifacts
+        run: |
+          echo "cp oneAPI running time dll files in ${{ env.ONEAPI_ROOT }} to ./build/bin"
+
+          cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_sycl_blas.5.dll" ./build/bin
+          cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_core.2.dll" ./build/bin
+          cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_tbb_thread.2.dll" ./build/bin
+
+          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_level_zero.dll" ./build/bin
+          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_opencl.dll" ./build/bin
+          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_loader.dll" ./build/bin
+          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_win_proxy_loader.dll" ./build/bin
+
+          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/sycl8.dll" ./build/bin
+          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/svml_dispmd.dll" ./build/bin
+          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libmmd.dll" ./build/bin
+          cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libiomp5md.dll" ./build/bin
+
+          cp "${{ env.ONEAPI_ROOT }}/dnnl/latest/bin/dnnl.dll" ./build/bin
+          cp "${{ env.ONEAPI_ROOT }}/tbb/latest/bin/tbb12.dll" ./build/bin
+
+          echo "cp oneAPI running time dll files to ./build/bin done"
+          7z a llama-${{ steps.tag.outputs.name }}-bin-win-sycl-x64.zip ./build/bin/*
+
+      - name: Upload the release package
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-win-sycl-x64.zip
+          name: llama-bin-win-sycl-x64.zip
+
+  windows-hip:
+    runs-on: windows-latest
+
+    strategy:
+      matrix:
+        gpu_target: [gfx1100, gfx1101, gfx1030]
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+            fetch-depth: 0
+
+      - name: Clone rocWMMA repository
+        id: clone_rocwmma
+        run: |
+          git clone https://github.com/rocm/rocwmma --branch rocm-6.2.4 --depth 1
+
+      - name: ccache
+        uses: hendrikmuhs/ccache-action@v1.2.16
+        with:
+          key: windows-latest-cmake-hip-release
+          evict-old-files: 1d
+
+      - name: Install
+        id: depends
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "Downloading AMD HIP SDK Installer"
+          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
+          write-host "Installing AMD HIP SDK"
+          Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
+          write-host "Completed AMD HIP SDK installation"
+
+      - name: Verify ROCm
+        id: verify
+        run: |
+          & 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
+
+      - name: libCURL
+        id: get_libcurl
+        uses: ./.github/actions/windows-setup-curl
+
+      - name: Build
+        id: cmake_build
+        env:
+          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
+        run: |
+          $env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
+          $env:CMAKE_PREFIX_PATH="${env:HIP_PATH}"
+          cmake -G "Unix Makefiles" -B build -S . `
+            -DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
+            -DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
+            -DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/rocwmma/library/include/" `
+            -DCMAKE_BUILD_TYPE=Release `
+            -DAMDGPU_TARGETS=${{ matrix.gpu_target }} `
+            -DGGML_HIP_ROCWMMA_FATTN=ON `
+            -DGGML_HIP=ON `
+            -DCURL_LIBRARY="$env:CURL_PATH/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:CURL_PATH/include" `
+            ${{ env.CMAKE_ARGS }}
+          cmake --build build -j ${env:NUMBER_OF_PROCESSORS}
+          md "build\bin\rocblas\library\"
+          cp "${env:HIP_PATH}\bin\hipblas.dll" "build\bin\"
+          cp "${env:HIP_PATH}\bin\rocblas.dll" "build\bin\"
+          cp "${env:HIP_PATH}\bin\rocblas\library\*" "build\bin\rocblas\library\"
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        env:
+          CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
+        run: |
+          cp $env:CURL_PATH\bin\libcurl-x64.dll .\build\bin\libcurl-x64.dll
+          7z a llama-${{ steps.tag.outputs.name }}-bin-win-hip-x64-${{ matrix.gpu_target }}.zip .\build\bin\*
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-win-hip-x64-${{ matrix.gpu_target }}.zip
+          name: llama-bin-win-hip-x64-${{ matrix.gpu_target }}.zip
+
+  ios-xcode-build:
+    runs-on: macos-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Build
+        id: cmake_build
+        run: |
+          sysctl -a
+          cmake -B build -G Xcode \
+            -DGGML_METAL_USE_BF16=ON \
+            -DGGML_METAL_EMBED_LIBRARY=ON \
+            -DLLAMA_CURL=OFF \
+            -DLLAMA_BUILD_EXAMPLES=OFF \
+            -DLLAMA_BUILD_TOOLS=OFF \
+            -DLLAMA_BUILD_TESTS=OFF \
+            -DLLAMA_BUILD_SERVER=OFF \
+            -DCMAKE_SYSTEM_NAME=iOS \
+            -DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 \
+            -DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
+          cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO
+
+      - name: xcodebuild for swift package
+        id: xcodebuild
+        run: |
+          ./build-xcframework.sh
+
+      - name: Build Xcode project
+        run: xcodebuild -project examples/llama.swiftui/llama.swiftui.xcodeproj -scheme llama.swiftui -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' FRAMEWORK_FOLDER_PATH=./build-ios build
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        run: |
+          zip --symlinks -r llama-${{ steps.tag.outputs.name }}-xcframework.zip build-apple/llama.xcframework
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-xcframework.zip
+          name: llama-${{ steps.tag.outputs.name }}-xcframework
+
+  release:
+    if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
+
+    # Fine-grant permission
+    # https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
+    permissions:
+        contents: write # for creating release
+
+    runs-on: ubuntu-latest
+
+    needs:
+      - ubuntu-22-cpu
+      - ubuntu-22-vulkan
+      - windows
+      - windows-cuda
+      - windows-sycl
+      - windows-hip
+      - macOS-arm64
+      - macOS-x64
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Download artifacts
+        id: download-artifact
+        uses: actions/download-artifact@v4
+        with:
+          path: ./artifact
+
+      - name: Move artifacts
+        id: move_artifacts
+        run: mkdir -p ./artifact/release && mv ./artifact/*/*.zip ./artifact/release
+
+      - name: Create release
+        id: create_release
+        uses: ggml-org/action-create-release@v1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:
+          tag_name: ${{ steps.tag.outputs.name }}
+
+      - name: Upload release
+        id: upload_release
+        uses: actions/github-script@v3
+        with:
+          github-token: ${{secrets.GITHUB_TOKEN}}
+          script: |
+            const path = require('path');
+            const fs = require('fs');
+            const release_id = '${{ steps.create_release.outputs.id }}';
+            for (let file of await fs.readdirSync('./artifact/release')) {
+              if (path.extname(file) === '.zip') {
+                console.log('uploadReleaseAsset', file);
+                await github.repos.uploadReleaseAsset({
+                  owner: context.repo.owner,
+                  repo: context.repo.repo,
+                  release_id: release_id,
+                  name: file,
+                  data: await fs.readFileSync(`./artifact/release/${file}`)
+                });
+              }
+            }

CMakeLists.txt

@@ -252,20 +252,3 @@ configure_file(cmake/llama.pc.in
 
 install(FILES "${CMAKE_CURRENT_BINARY_DIR}/llama.pc"
         DESTINATION ${CMAKE_INSTALL_LIBDIR}/pkgconfig)
-
-#
-# copy the license files
-#
-
-# Check if running in GitHub Actions
-if(DEFINED ENV{GITHUB_ACTIONS} AND "$ENV{GITHUB_ACTIONS}" STREQUAL "true")
-    message(STATUS "Running inside GitHub Actions - copying license files")
-
-    # Copy all files from licenses/ to build/bin/
-    file(GLOB LICENSE_FILES "${CMAKE_SOURCE_DIR}/licenses/*")
-    foreach(LICENSE_FILE ${LICENSE_FILES})
-        get_filename_component(FILENAME ${LICENSE_FILE} NAME)
-        configure_file(${LICENSE_FILE} "${CMAKE_BINARY_DIR}/bin/${FILENAME}" COPYONLY)
-    endforeach()
-endif()
-

CMakePresets.json

@@ -38,15 +38,6 @@
         }
     },
 
-    {
-        "name": "arm64-windows-msvc", "hidden": true,
-        "architecture": { "value": "arm64",    "strategy": "external" },
-        "toolset":      { "value": "host=x64", "strategy": "external" },
-        "cacheVariables": {
-            "CMAKE_TOOLCHAIN_FILE": "${sourceDir}/cmake/arm64-windows-msvc.cmake"
-        }
-    },
-
     {
         "name": "arm64-windows-llvm", "hidden": true,
         "architecture": { "value": "arm64",    "strategy": "external" },
@@ -73,10 +64,6 @@
     { "name": "arm64-apple-clang-release", "inherits": [ "base", "arm64-apple-clang", "reldbg" ] },
     { "name": "arm64-apple-clang+static-release", "inherits": [ "base", "arm64-apple-clang",  "reldbg", "static" ] },
 
-    { "name": "arm64-windows-msvc-debug", "inherits": [ "base", "arm64-windows-msvc",  "debug"   ] },
-    { "name": "arm64-windows-msvc-release", "inherits": [ "base", "arm64-windows-msvc",  "reldbg" ] },
-    { "name": "arm64-windows-msvc+static-release", "inherits": [ "base", "arm64-windows-msvc",  "reldbg", "static" ] },
-
     { "name": "x64-windows-llvm-debug", "inherits": [ "base", "x64-windows-llvm", "debug" ] },
     { "name": "x64-windows-llvm-release", "inherits": [ "base", "x64-windows-llvm", "release" ] },
     { "name": "x64-windows-llvm-reldbg", "inherits": [ "base", "x64-windows-llvm", "reldbg" ] },

Makefile

@@ -1187,11 +1187,6 @@ llama-cli: tools/main/main.cpp \
 	@echo '====  Run ./llama-cli -h for help.  ===='
 	@echo
 
-llama-infill: examples/infill/infill.cpp \
-	$(OBJ_ALL)
-	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
-	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
-
 llama-run: tools/run/run.cpp \
 	$(OBJ_ALL)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)

common/CMakeLists.txt

@@ -144,3 +144,27 @@ endif ()
 target_include_directories(${TARGET} PUBLIC .)
 target_compile_features   (${TARGET} PUBLIC cxx_std_17)
 target_link_libraries     (${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads)
+
+
+#
+# copy the license files
+#
+
+# Check if running in GitHub Actions
+if (DEFINED ENV{GITHUB_ACTIONS} AND "$ENV{GITHUB_ACTIONS}" STREQUAL "true")
+    message(STATUS "Running inside GitHub Actions - copying license files")
+
+    # Copy all files from licenses/ to build/bin/
+    file(GLOB LICENSE_FILES "${CMAKE_SOURCE_DIR}/licenses/*")
+    foreach(LICENSE_FILE ${LICENSE_FILES})
+        get_filename_component(FILENAME ${LICENSE_FILE} NAME)
+        add_custom_command(
+            POST_BUILD
+            TARGET ${TARGET}
+            COMMAND ${CMAKE_COMMAND} -E copy_if_different
+                "${LICENSE_FILE}"
+                "$<TARGET_FILE_DIR:llama>/${FILENAME}"
+            COMMENT "Copying ${FILENAME} to ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}")
+        message(STATUS "Copying ${LICENSE_FILE} to ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/${FILENAME}")
+    endforeach()
+endif()

common/arg.cpp

@@ -1283,7 +1283,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         [](common_params & params) {
             params.use_color = true;
         }
-    ).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_INFILL, LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP}));
+    ).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP}));
     add_opt(common_arg(
         {"-t", "--threads"}, "N",
         string_format("number of threads to use during generation (default: %d)", params.cpuparams.n_threads),
@@ -1416,7 +1416,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     add_opt(common_arg(
         {"-n", "--predict", "--n-predict"}, "N",
         string_format(
-            ex == LLAMA_EXAMPLE_MAIN || ex == LLAMA_EXAMPLE_INFILL
+            ex == LLAMA_EXAMPLE_MAIN
                 ? "number of tokens to predict (default: %d, -1 = infinity, -2 = until context filled)"
                 : "number of tokens to predict (default: %d, -1 = infinity)",
             params.n_predict),
@@ -1655,7 +1655,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.input_prefix = value;
             params.enable_chat_template = false;
         }
-    ).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_INFILL}));
+    ).set_examples({LLAMA_EXAMPLE_MAIN}));
     add_opt(common_arg(
         {"--in-suffix"}, "STRING",
         "string to suffix after user inputs with (default: empty)",
@@ -1663,7 +1663,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.input_suffix = value;
             params.enable_chat_template = false;
         }
-    ).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_INFILL}));
+    ).set_examples({LLAMA_EXAMPLE_MAIN}));
     add_opt(common_arg(
         {"--no-warmup"},
         "skip warming up the model with an empty run",
@@ -1680,7 +1680,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         [](common_params & params) {
             params.spm_infill = true;
         }
-    ).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_INFILL}));
+    ).set_examples({LLAMA_EXAMPLE_SERVER}));
     add_opt(common_arg(
         {"--samplers"}, "SAMPLERS",
         string_format("samplers that will be used for generation in the order, separated by \';\'\n(default: %s)", sampler_type_names.c_str()),
@@ -2097,13 +2097,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.cache_type_v = kv_cache_type_from_str(value);
         }
     ).set_env("LLAMA_ARG_CACHE_TYPE_V"));
-    add_opt(common_arg(
-        {"--perplexity", "--all-logits"},
-        string_format("return logits for all tokens in the batch (default: %s)", params.logits_all ? "true" : "false"),
-        [](common_params & params) {
-            params.logits_all = true;
-        }
-    ).set_examples({LLAMA_EXAMPLE_PERPLEXITY}));
     add_opt(common_arg(
         {"--hellaswag"},
         "compute HellaSwag score over random tasks from datafile supplied with -f",
@@ -2892,7 +2885,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         [](common_params & params) {
             params.simple_io = true;
         }
-    ).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_INFILL}));
+    ).set_examples({LLAMA_EXAMPLE_MAIN}));
     add_opt(common_arg(
         {"--positive-file"}, "FNAME",
         string_format("positive prompts file, one prompt per line (default: '%s')", params.cvector_positive_file.c_str()),

common/chat.cpp

@@ -125,7 +125,9 @@ std::vector<common_chat_msg> common_chat_msgs_parse_oaicompat(const json & messa
             msgs.push_back(msg);
         }
     } catch (const std::exception & e) {
-        throw std::runtime_error("Failed to parse messages: " + std::string(e.what()) + "; messages = " + messages.dump(2));
+        // @ngxson : disable otherwise it's bloating the API response
+        // printf("%s\n", std::string("; messages = ") + messages.dump(2));
+        throw std::runtime_error("Failed to parse messages: " + std::string(e.what()));
     }
 
     return msgs;

common/common.cpp

@@ -1096,7 +1096,6 @@ struct llama_context_params common_context_params_to_llama(const common_params &
     cparams.n_threads         = params.cpuparams.n_threads;
     cparams.n_threads_batch   = params.cpuparams_batch.n_threads == -1 ?
                                 params.cpuparams.n_threads : params.cpuparams_batch.n_threads;
-    cparams.logits_all        = params.logits_all;
     cparams.embeddings        = params.embedding;
     cparams.rope_scaling_type = params.rope_scaling_type;
     cparams.rope_freq_base    = params.rope_freq_base;

common/common.h

@@ -66,7 +66,6 @@ enum llama_example {
     LLAMA_EXAMPLE_COMMON,
     LLAMA_EXAMPLE_SPECULATIVE,
     LLAMA_EXAMPLE_MAIN,
-    LLAMA_EXAMPLE_INFILL,
     LLAMA_EXAMPLE_EMBEDDING,
     LLAMA_EXAMPLE_PERPLEXITY,
     LLAMA_EXAMPLE_RETRIEVAL,
@@ -325,7 +324,6 @@ struct common_params {
     bool ctx_shift         = true;  // context shift on inifinite text generation
 
     bool input_prefix_bos  = false; // prefix BOS to user inputs, preceding input_prefix
-    bool logits_all        = false; // return logits for all tokens in the batch
     bool use_mmap          = true;  // use mmap for faster loads
     bool use_mlock         = false; // use mlock to keep model in memory
     bool verbose_prompt    = false; // print prompt tokens before generation

common/sampling.cpp

@@ -1,6 +1,7 @@
 #include "sampling.h"
 
 #include "common.h"
+#include "log.h"
 
 #include <cmath>
 #include <unordered_map>
@@ -534,14 +535,16 @@ std::vector<common_sampler_type> common_sampler_types_from_names(const std::vect
         auto sampler = sampler_canonical_name_map.find(name);
         if (sampler != sampler_canonical_name_map.end()) {
             samplers.push_back(sampler->second);
-        } else {
-            if (allow_alt_names) {
-                sampler = sampler_alt_name_map.find(name);
-                if (sampler != sampler_alt_name_map.end()) {
-                    samplers.push_back(sampler->second);
-                }
+            continue;
+        }
+        if (allow_alt_names) {
+            sampler = sampler_alt_name_map.find(name);
+            if (sampler != sampler_alt_name_map.end()) {
+                samplers.push_back(sampler->second);
+                continue;
             }
         }
+        LOG_WRN("%s: unable to match sampler by name '%s'\n", __func__, name.c_str());
     }
 
     return samplers;
@@ -568,6 +571,8 @@ std::vector<common_sampler_type> common_sampler_types_from_chars(const std::stri
         const auto sampler = sampler_name_map.find(c);
         if (sampler != sampler_name_map.end()) {
             samplers.push_back(sampler->second);
+        } else {
+            LOG_WRN("%s: unable to match sampler by char '%c'\n", __func__, c);
         }
     }
 

convert_hf_to_gguf.py

@@ -1388,10 +1388,10 @@ class BaichuanModel(TextModel):
         self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"])
         self.gguf_writer.add_file_type(self.ftype)
 
-        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
-            if self.hparams["rope_scaling"].get("type") == "linear":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
-                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "linear" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         head_count = self.hparams["num_attention_heads"]
@@ -1512,10 +1512,10 @@ class XverseModel(TextModel):
         self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"])
         self.gguf_writer.add_file_type(self.ftype)
 
-        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
-            if self.hparams["rope_scaling"].get("type") == "linear":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
-                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "linear" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         del bid  # unused
@@ -1828,10 +1828,10 @@ class LlamaModel(TextModel):
             rope_dim = hparams["hidden_size"] // hparams["num_attention_heads"]
         self.gguf_writer.add_rope_dimension_count(rope_dim)
 
-        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
-            if self.hparams["rope_scaling"].get("type") == "linear":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
-                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "linear" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
 
     @staticmethod
     def permute(weights: Tensor, n_head: int, n_head_kv: int | None):
@@ -2206,10 +2206,10 @@ class DeciModel(TextModel):
             rope_dim = hparams["hidden_size"] // hparams["num_attention_heads"]
         self.gguf_writer.add_rope_dimension_count(rope_dim)
 
-        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
-            if self.hparams["rope_scaling"].get("type") == "linear":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
-                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "linear" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
 
     @staticmethod
     def permute(weights: Tensor, n_head: int, n_head_kv: int | None):
@@ -2449,10 +2449,10 @@ class MiniCPMModel(TextModel):
         logit_scale = self.hparams["hidden_size"] / self.hparams["dim_model_base"]
         self.gguf_writer.add_logit_scale(logit_scale)
         logger.info(f"gguf: (minicpm) logit_scale = {logit_scale}")
-        if self.hparams.get("rope_scaling") is not None:
-            if self.hparams["rope_scaling"].get("type") == "longrope":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LONGROPE)
-                logger.info(f"gguf: (minicpm) rope_scaling_type = {gguf.RopeScalingType.LONGROPE}")
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "longrope":
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LONGROPE)
+            logger.info(f"gguf: (minicpm) rope_scaling_type = {gguf.RopeScalingType.LONGROPE}")
 
     def generate_extra_tensors(self) -> Iterable[tuple[str, Tensor]]:
         rope_dims = self.hparams["hidden_size"] // self.hparams["num_attention_heads"]
@@ -2597,11 +2597,11 @@ class Qwen2Model(TextModel):
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
         self._try_set_pooling_type()
-        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
-            if self.hparams["rope_scaling"].get("type") == "yarn":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
-                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
-                self.gguf_writer.add_rope_scaling_orig_ctx_len(self.hparams["rope_scaling"]["original_max_position_embeddings"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "yarn" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
+            self.gguf_writer.add_rope_scaling_orig_ctx_len(rope_scaling["original_max_position_embeddings"])
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         if self.hf_arch == "Qwen2Model":
@@ -2761,6 +2761,13 @@ class Qwen2MoeModel(TextModel):
         if (shared_expert_intermediate_size := self.hparams.get('shared_expert_intermediate_size')) is not None:
             self.gguf_writer.add_expert_shared_feed_forward_length(shared_expert_intermediate_size)
             logger.info(f"gguf: expert shared feed forward length = {shared_expert_intermediate_size}")
+        # YaRN is not enabled by default
+        # To enable it, please refer to this guide: https://huggingface.co/Qwen/Qwen3-30B-A3B#processing-long-texts
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "yarn" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
+            self.gguf_writer.add_rope_scaling_orig_ctx_len(rope_scaling["original_max_position_embeddings"])
 
     _experts: list[dict[str, Tensor]] | None = None
 
@@ -3028,7 +3035,7 @@ class Phi3MiniModel(TextModel):
 
         scale = max_pos_embds / orig_max_pos_embds
 
-        rope_scaling_type = rope_scaling.get('type', '').lower()
+        rope_scaling_type = rope_scaling.get('rope_type', rope_scaling.get('type', '')).lower()
         if len(rope_scaling_type) == 0:
             raise KeyError('Missing the required key rope_scaling.type')
 
@@ -3340,10 +3347,10 @@ class InternLM2Model(TextModel):
         self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"])
         self.gguf_writer.add_head_count_kv(self.hparams["num_key_value_heads"])
         self.gguf_writer.add_file_type(self.ftype)
-        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
-            if self.hparams["rope_scaling"].get("type") == "linear":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
-                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "linear" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         num_heads = self.hparams["num_attention_heads"]
@@ -3418,10 +3425,10 @@ class InternLM3Model(TextModel):
             rope_dim = hparams["hidden_size"] // hparams["num_attention_heads"]
         self.gguf_writer.add_rope_dimension_count(rope_dim)
 
-        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
-            if self.hparams["rope_scaling"].get("type") == "linear" or self.hparams["rope_scaling"].get("rope_type") == "linear":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
-                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "linear" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         n_head = self.hparams["num_attention_heads"]
@@ -3908,6 +3915,16 @@ class Gemma3VisionModel(VisionModel):
         # default values below are taken from HF tranformers code
         self.gguf_writer.add_vision_attention_layernorm_eps(hparams.get("layer_norm_eps", 1e-6))
         self.gguf_writer.add_vision_use_gelu(True)
+        # calculate proj_scale_factor (used by tinygemma3 test model)
+        image_seq_length = self.preprocessor_config.get("image_seq_length", 256)
+        n_per_side = int(image_seq_length ** 0.5)
+        image_size = self.hparams["image_size"]
+        patch_size = self.hparams["patch_size"]
+        proj_scale_factor = (image_size // patch_size) // n_per_side
+        if proj_scale_factor > 0 and proj_scale_factor != 4:
+            # we only need to write this if it's not the default value
+            # in this case, we are converting a test model
+            self.gguf_writer.add_vision_projector_scale_factor(proj_scale_factor)
 
     def tensor_force_quant(self, name, new_name, bid, n_dims):
         del bid, new_name, n_dims  # unused
@@ -3921,6 +3938,9 @@ class Gemma3VisionModel(VisionModel):
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         del bid  # unused
 
+        if "vision_model.head." in name:
+            return [] # skip redundant tensors for tinygemma3
+
         if name.startswith("multi_modal_projector.") or name.startswith("vision_tower.") \
                 or name.startswith("multimodal_projector.") or name.startswith("vision_model."):
             # process vision tensors
@@ -4846,12 +4866,12 @@ class DeepseekV2Model(TextModel):
 
         self.gguf_writer.add_rope_dimension_count(hparams["qk_rope_head_dim"])
 
-        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
-            if self.hparams["rope_scaling"].get("type") == "yarn":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
-                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
-                self.gguf_writer.add_rope_scaling_orig_ctx_len(self.hparams["rope_scaling"]["original_max_position_embeddings"])
-                self.gguf_writer.add_rope_scaling_yarn_log_mul(0.1 * hparams["rope_scaling"]["mscale_all_dim"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "yarn" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
+            self.gguf_writer.add_rope_scaling_orig_ctx_len(rope_scaling["original_max_position_embeddings"])
+            self.gguf_writer.add_rope_scaling_yarn_log_mul(0.1 * rope_scaling["mscale_all_dim"])
 
     _experts: list[dict[str, Tensor]] | None = None
 
@@ -5343,11 +5363,11 @@ class Glm4Model(TextModel):
         super().set_gguf_parameters()
         rope_dim = self.hparams["head_dim"]
         self.gguf_writer.add_rope_dimension_count(int(rope_dim * self.hparams.get("partial_rotary_factor", 0.5)))
-        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
-            if self.hparams["rope_scaling"].get("type") == "yarn":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
-                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
-                self.gguf_writer.add_rope_scaling_orig_ctx_len(self.hparams["rope_scaling"]["original_max_position_embeddings"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "yarn" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
+            self.gguf_writer.add_rope_scaling_orig_ctx_len(rope_scaling["original_max_position_embeddings"])
 
 
 @ModelBase.register("GlmForCausalLM", "ChatGLMModel", "ChatGLMForConditionalGeneration")
@@ -5580,10 +5600,10 @@ class ExaoneModel(TextModel):
         rotary_factor = self.find_hparam(["partial_rotary_factor", "rope_pct"], optional=True)
         rotary_factor = rotary_factor if rotary_factor is not None else 1.0
         self.gguf_writer.add_rope_dimension_count(int(rotary_factor * (hparams["hidden_size"] // hparams["num_attention_heads"])))
-        if hparams.get("rope_scaling") is not None and "factor" in hparams["rope_scaling"]:
-            if hparams["rope_scaling"].get("type") == "linear":
-                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
-                self.gguf_writer.add_rope_scaling_factor(hparams["rope_scaling"]["factor"])
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "linear" and "factor" in rope_scaling:
+            self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
 
     def generate_extra_tensors(self) -> Iterable[tuple[str, Tensor]]:
         if rope_scaling := self.find_hparam(["rope_scaling"], optional=True):
@@ -5686,10 +5706,11 @@ class BailingMoeModel(TextModel):
         rope_dim = hparams.get("head_dim") or hparams["hidden_size"] // hparams["num_attention_heads"]
 
         self.gguf_writer.add_rope_dimension_count(rope_dim)
-        if (self.hparams.get("rope_scaling") or {}).get("type") == "yarn" and "factor" in self.hparams["rope_scaling"]:
+        rope_scaling = self.hparams.get("rope_scaling") or {}
+        if rope_scaling.get("rope_type", rope_scaling.get("type")) == "yarn" and "factor" in rope_scaling:
             self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
-            self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
-            self.gguf_writer.add_rope_scaling_orig_ctx_len(self.hparams["rope_scaling"]["original_max_position_embeddings"])
+            self.gguf_writer.add_rope_scaling_factor(rope_scaling["factor"])
+            self.gguf_writer.add_rope_scaling_orig_ctx_len(rope_scaling["original_max_position_embeddings"])
         else:
             self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.NONE)
         self.gguf_writer.add_leading_dense_block_count(hparams["first_k_dense_replace"])

examples/CMakeLists.txt

@@ -21,7 +21,6 @@ else()
     add_subdirectory(gguf-hash)
     add_subdirectory(gguf)
     add_subdirectory(gritlm)
-    add_subdirectory(infill)
     add_subdirectory(lookahead)
     add_subdirectory(lookup)
     add_subdirectory(parallel)

examples/embedding/embedding.cpp

@@ -35,23 +35,14 @@ static void batch_add_seq(llama_batch & batch, const std::vector<int32_t> & toke
 
 static void batch_decode(llama_context * ctx, llama_batch & batch, float * output, int n_seq, int n_embd, int embd_norm) {
     const enum llama_pooling_type pooling_type = llama_pooling_type(ctx);
-    const struct llama_model * model = llama_get_model(ctx);
 
     // clear previous kv_cache values (irrelevant for embeddings)
     llama_kv_self_clear(ctx);
 
     // run model
     LOG_INF("%s: n_tokens = %d, n_seq = %d\n", __func__, batch.n_tokens, n_seq);
-    if (llama_model_has_encoder(model) && !llama_model_has_decoder(model)) {
-        // encoder-only model
-        if (llama_encode(ctx, batch) < 0) {
-            LOG_ERR("%s : failed to encode\n", __func__);
-        }
-    } else if (!llama_model_has_encoder(model) && llama_model_has_decoder(model)) {
-        // decoder-only model
-        if (llama_decode(ctx, batch) < 0) {
-            LOG_ERR("%s : failed to decode\n", __func__);
-        }
+    if (llama_encode(ctx, batch) < 0) {
+        LOG_ERR("%s : failed to encode\n", __func__);
     }
 
     for (int i = 0; i < batch.n_tokens; i++) {

examples/infill/CMakeLists.txt

@@ -1,5 +0,0 @@
-set(TARGET llama-infill)
-add_executable(${TARGET} infill.cpp)
-install(TARGETS ${TARGET} RUNTIME)
-target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
-target_compile_features(${TARGET} PRIVATE cxx_std_17)

examples/infill/README.md

@@ -1,47 +0,0 @@
-# llama.cpp/example/infill
-
-This example shows how to use the infill mode with Code Llama models supporting infill mode.
-Currently the 7B and 13B models support infill mode.
-
-Infill supports most of the options available in the main example.
-
-For further information have a look at the main README.md in llama.cpp/example/main/README.md
-
-## Common Options
-
-In this section, we cover the most commonly used options for running the `infill` program with the LLaMA models:
-
--   `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.bin`).
--   `-i, --interactive`: Run the program in interactive mode, allowing you to provide input directly and receive real-time responses.
--   `-n N, --n-predict N`: Set the number of tokens to predict when generating text. Adjusting this value can influence the length of the generated text.
--   `-c N, --ctx-size N`: Set the size of the prompt context. The default is 4096, but if a LLaMA model was built with a longer context, increasing this value will provide better results for longer input/inference.
--   `--spm-infill`: Use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this.
-
-## Input Prompts
-
-The `infill` program provides several ways to interact with the LLaMA models using input prompts:
-
--   `--in-prefix PROMPT_BEFORE_CURSOR`: Provide the prefix directly as a command-line option.
--   `--in-suffix PROMPT_AFTER_CURSOR`: Provide the suffix directly as a command-line option.
--   `--interactive-first`: Run the program in interactive mode and wait for input right away. (More on this below.)
-
-## Interaction
-
-The `infill` program offers a seamless way to interact with LLaMA models, allowing users to receive real-time infill suggestions. The interactive mode can be triggered using `--interactive`, and `--interactive-first`
-
-### Interaction Options
-
--   `-i, --interactive`: Run the program in interactive mode, allowing users to get real time code suggestions from model.
--   `--interactive-first`: Run the program in interactive mode and immediately wait for user input before starting the text generation.
--   `--color`: Enable colorized output to differentiate visually distinguishing between prompts, user input, and generated text.
-
-### Example
-
-Download a model that supports infill, for example CodeLlama:
-```console
-scripts/hf.sh --repo TheBloke/CodeLlama-13B-GGUF --file codellama-13b.Q5_K_S.gguf --outdir models
-```
-
-```bash
-./llama-infill -t 10 -ngl 0 -m models/codellama-13b.Q5_K_S.gguf -c 4096 --temp 0.7 --repeat_penalty 1.1 -n 20 --in-prefix "def helloworld():\n    print(\"hell" --in-suffix "\n   print(\"goodbye world\")\n    "
-```

examples/infill/infill.cpp

@@ -1,590 +0,0 @@
-#include "arg.h"
-#include "common.h"
-#include "console.h"
-#include "sampling.h"
-#include "log.h"
-#include "llama.h"
-
-#include <cassert>
-#include <cinttypes>
-#include <cmath>
-#include <cstdio>
-#include <cstring>
-#include <ctime>
-#include <fstream>
-#include <iostream>
-#include <sstream>
-#include <string>
-#include <vector>
-
-#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
-#include <signal.h>
-#include <unistd.h>
-#elif defined (_WIN32)
-#define WIN32_LEAN_AND_MEAN
-#ifndef NOMINMAX
-#define NOMINMAX
-#endif
-#include <windows.h>
-#include <signal.h>
-#endif
-
-#if defined(_MSC_VER)
-#pragma warning(disable: 4244 4267) // possible loss of data
-#endif
-
-static llama_context           ** g_ctx;
-static llama_model             ** g_model;
-static common_sampler          ** g_smpl;
-static common_params            * g_params;
-static std::vector<llama_token> * g_input_tokens;
-static std::ostringstream       * g_output_ss;
-static std::vector<llama_token> * g_output_tokens;
-
-static bool is_interacting = false;
-
-#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32)
-static void sigint_handler(int signo) {
-    if (signo == SIGINT) {
-        if (!is_interacting) {
-            is_interacting = true;
-        } else {
-            console::cleanup();
-            LOG("\n");
-            common_perf_print(*g_ctx, *g_smpl);
-
-            // make sure all logs are flushed
-            LOG("Interrupted by user\n");
-            common_log_pause(common_log_main());
-
-            _exit(130);
-        }
-    }
-}
-#endif
-
-int main(int argc, char ** argv) {
-    common_params params;
-    g_params = &params;
-
-    if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_INFILL)) {
-        return 1;
-    }
-
-    common_init();
-
-    auto & sparams = params.sampling;
-
-    console::init(params.simple_io, params.use_color);
-    atexit([]() { console::cleanup(); });
-
-    if (params.logits_all) {
-        LOG_ERR("\n************\n");
-        LOG_ERR("%s: please use the 'perplexity' tool for perplexity calculations\n", __func__);
-        LOG_ERR("************\n\n");
-
-        return 0;
-    }
-
-    if (params.embedding) {
-        LOG_ERR("\n************\n");
-        LOG_ERR("%s: please use the 'embedding' tool for embedding calculations\n", __func__);
-        LOG_ERR("************\n\n");
-
-        return 0;
-    }
-
-    if (params.n_ctx != 0 && params.n_ctx < 8) {
-        LOG_WRN("%s: minimum context size is 8, using minimum size.\n", __func__);
-        params.n_ctx = 8;
-    }
-
-    if (!params.interactive_first && (params.input_prefix.empty() && params.input_suffix.empty())) {
-        LOG_ERR("\n************\n");
-        LOG_ERR("%s: please use '--interactive_first' or specify '--in_prefix' and/or '--in_suffix'\n", __func__);
-        LOG_ERR("************\n\n");
-
-        return 0;
-    }
-
-    if (params.rope_freq_base != 0.0) {
-        LOG_WRN("%s: changing RoPE frequency base to %g.\n", __func__, params.rope_freq_base);
-    }
-
-    if (params.rope_freq_scale != 0.0) {
-        LOG_WRN("%s: scaling RoPE frequency by %g.\n", __func__, params.rope_freq_scale);
-    }
-
-    LOG_INF("%s: llama backend init\n", __func__);
-    llama_backend_init();
-    llama_numa_init(params.numa);
-
-    llama_model * model = nullptr;
-    llama_context * ctx = nullptr;
-    common_sampler * smpl = nullptr;
-
-    g_model = &model;
-    g_ctx = &ctx;
-    g_smpl = &smpl;
-
-    // load the model and apply lora adapter, if any
-    LOG_INF("%s: load the model and apply lora adapter, if any\n", __func__);
-    common_init_result llama_init = common_init_from_params(params);
-
-    model = llama_init.model.get();
-    ctx = llama_init.context.get();
-
-    if (model == NULL) {
-        LOG_ERR("%s: unable to load model\n", __func__);
-        return 1;
-    }
-
-    const llama_vocab * vocab = llama_model_get_vocab(model);
-
-    const int n_ctx_train = llama_model_n_ctx_train(model);
-    const int n_ctx = llama_n_ctx(ctx);
-    LOG_DBG("n_ctx: %d\n", n_ctx);
-
-    if (n_ctx > n_ctx_train) {
-        LOG_WRN("%s: model was trained on only %d context tokens (%d specified)\n", __func__, n_ctx_train, n_ctx);
-    }
-
-    // print system information
-    {
-        LOG_INF("\n");
-        LOG_INF("%s\n", common_params_get_system_info(params).c_str());
-    }
-    const bool add_bos = llama_vocab_get_add_bos(vocab);
-    GGML_ASSERT(!llama_vocab_get_add_eos(vocab));
-
-    std::vector<llama_token> embd_inp;
-    std::vector<llama_token> embd_end;
-    std::vector<llama_token> inp_pfx = common_tokenize(ctx, params.input_prefix, false);
-    std::vector<llama_token> inp_sfx = common_tokenize(ctx, params.input_suffix, false);
-
-    GGML_ASSERT(llama_vocab_fim_pre(vocab) >= 0);
-    GGML_ASSERT(llama_vocab_fim_suf(vocab) >= 0);
-
-    inp_pfx.insert(inp_pfx.begin(), llama_vocab_fim_pre(vocab));
-    inp_sfx.insert(inp_sfx.begin(), llama_vocab_fim_suf(vocab));
-
-    embd_inp = params.spm_infill ? inp_sfx : inp_pfx;
-    embd_end = params.spm_infill ? inp_pfx : inp_sfx;
-    if (add_bos) {
-        embd_inp.insert(embd_inp.begin(), llama_vocab_bos(vocab));
-    }
-    embd_inp.insert(embd_inp.end(), embd_end.begin(), embd_end.end());
-
-    const llama_token middle_token = llama_vocab_fim_mid(vocab);
-    if (middle_token >= 0) {
-        embd_inp.push_back(middle_token);
-    }
-
-    LOG_DBG("add_bos: %d\n", add_bos);
-    LOG_DBG("prefix: \"%s\"\n", params.input_prefix.c_str());
-    LOG_DBG("suffix: \"%s\"\n", params.input_suffix.c_str());
-    LOG_DBG("tokens: %s\n", string_from(ctx, embd_inp).c_str());
-
-    // Should not run without any tokens
-    if (embd_inp.empty()) {
-        embd_inp.push_back(llama_vocab_bos(vocab));
-        LOG_WRN("embd_inp was considered empty and bos was added: %s\n", string_from(ctx, embd_inp).c_str());
-    }
-
-    if ((int) embd_inp.size() > n_ctx - 4) {
-        LOG_ERR("%s: prompt is too long (%d tokens, max %d)\n", __func__, (int) embd_inp.size(), n_ctx - 4);
-        return 1;
-    }
-
-    // number of tokens to keep when resetting context
-    if (params.n_keep < 0 || params.n_keep > (int) embd_inp.size()) {
-        params.n_keep = (int)embd_inp.size();
-    }
-
-    LOG_INF("inp_pfx: %s\n", string_from(ctx, inp_pfx).c_str());
-    LOG_INF("inp_sfx: %s\n", string_from(ctx, inp_sfx).c_str());
-
-    // enable interactive mode if interactive start is specified
-    if (params.interactive_first) {
-        params.interactive = true;
-    }
-
-    if (params.verbose_prompt) {
-        LOG_INF("\n");
-        LOG_INF("%s: prompt: '%s'\n", __func__, params.prompt.c_str());
-        LOG_INF("%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size());
-        for (int i = 0; i < (int) embd_inp.size(); i++) {
-            LOG_INF("%6d -> '%s'\n", embd_inp[i], common_token_to_piece(ctx, embd_inp[i]).c_str());
-        }
-
-        if (params.n_keep > 0) {
-        LOG_INF("%s: static prompt based on n_keep: '", __func__);
-            for (int i = 0; i < params.n_keep; i++) {
-                LOG_CNT("%s", common_token_to_piece(ctx, embd_inp[i]).c_str());
-            }
-            LOG_CNT("'\n");
-        }
-        LOG_INF("\n");
-    }
-
-    if (params.interactive) {
-#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
-        struct sigaction sigint_action;
-        sigint_action.sa_handler = sigint_handler;
-        sigemptyset (&sigint_action.sa_mask);
-        sigint_action.sa_flags = 0;
-        sigaction(SIGINT, &sigint_action, NULL);
-#elif defined (_WIN32)
-        auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
-            return (ctrl_type == CTRL_C_EVENT) ? (sigint_handler(SIGINT), true) : false;
-        };
-        SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
-#endif
-
-        LOG_INF("%s: interactive mode on.\n", __func__);
-
-        if (params.input_prefix_bos) {
-            LOG_INF("Input prefix with BOS\n");
-        }
-
-        if (!params.input_prefix.empty()) {
-            LOG_INF("Input prefix: '%s'\n", params.input_prefix.c_str());
-        }
-
-        if (!params.input_suffix.empty()) {
-            LOG_INF("Input suffix: '%s'\n", params.input_suffix.c_str());
-        }
-    }
-    smpl = common_sampler_init(model, sparams);
-
-    LOG_INF("sampler seed: %u\n",     common_sampler_get_seed(smpl));
-    LOG_INF("sampler params: \n%s\n", sparams.print().c_str());
-    LOG_INF("sampler chain: %s\n",    common_sampler_print(smpl).c_str());
-
-    LOG_INF("generate: n_ctx = %d, n_batch = %d, n_predict = %d, n_keep = %d\n", n_ctx, params.n_batch, params.n_predict, params.n_keep);
-
-    LOG_INF("\n");
-    LOG_INF("\n#####  Infill mode  #####\n\n");
-    if (params.interactive) {
-        const char *control_message;
-        if (params.multiline_input) {
-            control_message = " - To return control to LLaMA, end your input with '\\'.\n"
-                              " - To return control without starting a new line, end your input with '/'.\n";
-        } else {
-            control_message = " - Press Return to return control to LLaMA.\n"
-                              " - To return control without starting a new line, end your input with '/'.\n"
-                              " - If you want to submit another line, end your input with '\\'.\n";
-        }
-        LOG_INF("== Running in interactive mode. ==\n");
-#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__)) || defined (_WIN32)
-        LOG_INF(       " - Press Ctrl+C to interject at any time.\n");
-#endif
-        LOG_INF(       "%s\n", control_message);
-
-        is_interacting = params.interactive_first;
-    }
-
-    bool input_echo = true;
-
-    int n_past     = 0;
-    int n_remain   = params.n_predict;
-    int n_consumed = 0;
-
-    std::vector<int>   input_tokens;  g_input_tokens  = &input_tokens;
-    std::vector<int>   output_tokens; g_output_tokens = &output_tokens;
-    std::ostringstream output_ss;     g_output_ss     = &output_ss;
-
-    // the first thing we will do is to output the prompt, so set color accordingly
-    console::set_display(console::prompt);
-
-    std::vector<llama_token> embd;
-
-    while (n_remain != 0 || params.interactive) {
-        // predict
-        if (!embd.empty()) {
-            // Note: n_ctx - 4 here is to match the logic for commandline prompt handling via
-            // --prompt or --file which uses the same value.
-            int max_embd_size = n_ctx - 4;
-
-            // Ensure the input doesn't exceed the context size by truncating embd if necessary.
-            if ((int) embd.size() > max_embd_size) {
-                const int skipped_tokens = (int) embd.size() - max_embd_size;
-                embd.resize(max_embd_size);
-
-                console::set_display(console::error);
-                LOG_WRN("<<input too long: skipped %d token%s>>", skipped_tokens, skipped_tokens != 1 ? "s" : "");
-                console::set_display(console::reset);
-            }
-
-            // infinite text generation via context swapping
-            // if we run out of context:
-            // - take the n_keep first tokens from the original prompt (via n_past)
-            // - take half of the last (n_ctx - n_keep) tokens and recompute the logits in batches
-            if (n_past + (int) embd.size() > n_ctx) {
-                if (params.n_predict == -2) {
-                    LOG_DBG("\n\n%s: context full and n_predict == -%d => stopping\n", __func__, params.n_predict);
-                    break;
-                }
-
-                const int n_left    = n_past - params.n_keep - 1;
-                const int n_discard = n_left/2;
-
-                LOG_DBG("context full, swapping: n_past = %d, n_left = %d, n_ctx = %d, n_keep = %d, n_discard = %d\n",
-                    n_past, n_left, n_ctx, params.n_keep, n_discard);
-
-                llama_kv_self_seq_rm (ctx, 0, params.n_keep + 1            , params.n_keep + n_discard + 1);
-                llama_kv_self_seq_add(ctx, 0, params.n_keep + 1 + n_discard, n_past, -n_discard);
-
-                n_past -= n_discard;
-
-                LOG_DBG("after swap: n_past = %d\n", n_past);
-
-                LOG_DBG("embd: %s\n", string_from(ctx, embd).c_str());
-
-            }
-
-            // evaluate tokens in batches
-            // embd is typically prepared beforehand to fit within a batch, but not always
-            for (int i = 0; i < (int) embd.size(); i += params.n_batch) {
-                int n_eval = (int) embd.size() - i;
-                if (n_eval > params.n_batch) {
-                    n_eval = params.n_batch;
-                }
-
-                LOG_DBG("eval: %s\n", string_from(ctx, embd).c_str());
-
-                if (llama_decode(ctx, llama_batch_get_one(&embd[i], n_eval))) {
-                    LOG_ERR("%s : failed to eval\n", __func__);
-                    return 1;
-                }
-
-                n_past += n_eval;
-
-                LOG_DBG("n_past = %d\n", n_past);
-            }
-
-        }
-
-        embd.clear();
-
-        if ((int) embd_inp.size() <= n_consumed && !is_interacting) {
-            const llama_token id = common_sampler_sample(smpl, ctx, -1);
-
-            common_sampler_accept(smpl, id, true);
-
-            // LOG_DBG("last: %s\n", string_from(ctx, smpl->prev.to_vector()).c_str());
-
-            embd.push_back(id);
-
-            // echo this to console
-            input_echo = true;
-
-            // decrement remaining sampling budget
-            --n_remain;
-
-            LOG_DBG("n_remain: %d\n", n_remain);
-        } else {
-            // some user input remains from prompt or interaction, forward it to processing
-            LOG_DBG("embd_inp.size(): %d, n_consumed: %d\n", (int) embd_inp.size(), n_consumed);
-            while ((int) embd_inp.size() > n_consumed) {
-                embd.push_back(embd_inp[n_consumed]);
-
-                // push the prompt in the sampling context in order to apply repetition penalties later
-                // for the prompt, we don't apply grammar rules
-                common_sampler_accept(smpl, embd_inp[n_consumed], false);
-
-                ++n_consumed;
-                if ((int) embd.size() >= params.n_batch) {
-                    break;
-                }
-            }
-        }
-
-        // display text
-        if (input_echo) {
-            for (auto id : embd) {
-                const std::string token_str = common_token_to_piece(ctx, id);
-                LOG("%s", token_str.c_str());
-
-                if (embd.size() > 1) {
-                    input_tokens.push_back(id);
-                } else {
-                    output_tokens.push_back(id);
-                    output_ss << token_str;
-                }
-            }
-        }
-        // reset color to default if we there is no pending user input
-        if (input_echo && (int) embd_inp.size() == n_consumed) {
-            console::set_display(console::reset);
-        }
-
-        // if not currently processing queued inputs;
-        if ((int) embd_inp.size() <= n_consumed) {
-            // deal with eot token in infill mode
-            if ((common_sampler_last(smpl) == llama_vocab_eot(vocab) || is_interacting) && params.interactive){
-                if (is_interacting && !params.interactive_first) {
-                    // print an eot token
-                    LOG("%s", common_token_to_piece(ctx, llama_vocab_eot(vocab)).c_str());
-                }
-                LOG("\n");
-                console::set_display(console::user_input);
-                std::string buffer;
-                std::string line;
-                bool another_line=true;
-                // set a new prefix via stdin
-                do {
-                    another_line = console::readline(line, params.multiline_input);
-                    buffer += line;
-                } while (another_line);
-                // check if we got an empty line, if so we use the old input
-                if (!buffer.empty() && !(buffer.length() == 1 && buffer[0] == '\n')) {
-                    params.input_prefix = buffer;
-                }
-                buffer.clear();
-                // set a new suffix via stdin
-                do {
-                    another_line = console::readline(line, params.multiline_input);
-                    buffer += line;
-                } while (another_line);
-                // check if we got an empty line
-                if (!buffer.empty() && !(buffer.length() == 1 && buffer[0] == '\n')) {
-                    params.input_suffix = buffer;
-                }
-                buffer.clear();
-                // done taking input, reset color
-                console::set_display(console::reset);
-
-                if (params.escape) {
-                    //process escape sequences, for the initial prompt this is done in common.cpp when we load the params, but for the interactive mode we need to do it here
-                    string_process_escapes(params.input_prefix);
-                    string_process_escapes(params.input_suffix);
-                }
-
-                // tokenize new prefix and suffix
-                std::vector<llama_token> inp_pfx = common_tokenize(ctx, params.input_prefix, false);
-                std::vector<llama_token> inp_sfx = common_tokenize(ctx, params.input_suffix, false);
-
-                inp_pfx.insert(inp_pfx.begin(), llama_vocab_fim_pre(vocab));
-                inp_sfx.insert(inp_sfx.begin(), llama_vocab_fim_suf(vocab));
-
-                embd_inp = params.spm_infill ? inp_sfx : inp_pfx;
-                embd_end = params.spm_infill ? inp_pfx : inp_sfx;
-                if (add_bos) {
-                    embd_inp.insert(embd_inp.begin(), llama_vocab_bos(vocab));
-                }
-                embd_inp.insert(embd_inp.end(), embd_end.begin(), embd_end.end());
-
-                if (middle_token >= 0) {
-                    embd_inp.push_back(middle_token);
-                }
-
-                embd.clear();
-                n_remain = params.n_predict;
-                n_past = 0;
-                n_consumed = 0;
-                is_interacting = false;
-            }
-            // deal with end of generation tokens in interactive mode
-            else if (llama_vocab_is_eog(vocab, common_sampler_last(smpl))) {
-                LOG_DBG("found EOS token\n");
-
-                if (params.interactive) {
-
-                    is_interacting = true;
-                    LOG("\n");
-                    console::set_display(console::user_input);
-               }
-            }
-
-            if (n_past > 0 && is_interacting && !params.interactive) {
-                LOG_DBG("waiting for user input\n");
-
-                if (params.input_prefix_bos) {
-                    LOG_DBG("adding input prefix BOS token\n");
-                    embd_inp.push_back(llama_vocab_bos(vocab));
-                }
-
-                std::string buffer;
-                if (!params.input_prefix.empty()) {
-                    LOG_DBG("appending input prefix: '%s'\n", params.input_prefix.c_str());
-                    buffer += params.input_prefix;
-                    LOG("%s", buffer.c_str());
-                }
-
-                std::string line;
-                bool another_line = true;
-                do {
-                    another_line = console::readline(line, params.multiline_input);
-                    buffer += line;
-                } while (another_line);
-
-                // done taking input, reset color
-                console::set_display(console::reset);
-
-                // Add tokens to embd only if the input buffer is non-empty
-                // Entering a empty line lets the user pass control back
-                if (buffer.length() > 1) {
-                    // append input suffix if any
-                    if (!params.input_suffix.empty()) {
-                        LOG_DBG("appending input suffix: '%s'\n", params.input_suffix.c_str());
-                        buffer += params.input_suffix;
-                        LOG("%s", params.input_suffix.c_str());
-                    }
-
-                    LOG_DBG("buffer: '%s'\n", buffer.c_str());
-
-                    const size_t original_size = embd_inp.size();
-
-                    const auto line_inp = common_tokenize(ctx, buffer, false);
-                    LOG_DBG("input tokens: %s\n", string_from(ctx, line_inp).c_str());
-
-                    embd_inp.insert(embd_inp.end(), line_inp.begin(), line_inp.end());
-
-                    for (size_t i = original_size; i < embd_inp.size(); ++i) {
-                        const llama_token token = embd_inp[i];
-                        output_tokens.push_back(token);
-                        output_ss << common_token_to_piece(ctx, token);
-                    }
-
-                    n_remain -= line_inp.size();
-                    LOG_DBG("n_remain: %d\n", n_remain);
-                } else {
-                    LOG_DBG("empty line, passing control back\n");
-                }
-
-                input_echo = false; // do not echo this again
-            }
-
-            if (n_past > 0) {
-                if (is_interacting) {
-                    common_sampler_reset(smpl);
-                }
-                is_interacting = false;
-            }
-        }
-
-        // end of generation
-        if (!embd.empty() && llama_vocab_is_eog(vocab, embd.back()) && !params.interactive) {
-            break;
-        }
-
-        // In interactive mode, respect the maximum number of tokens and drop back to user input when reached.
-        // We skip this logic when n_predict == -1 (infinite) or -2 (stop at context size).
-        if (params.interactive && n_remain <= 0 && params.n_predict >= 0) {
-            n_remain = params.n_predict;
-            is_interacting = true;
-        }
-    }
-    if (!params.interactive && n_remain <= 0) {
-        LOG("%s", common_token_to_piece(ctx, llama_vocab_eot(vocab)).c_str());
-    }
-
-    LOG("\n");
-    common_perf_print(ctx, smpl);
-
-    common_sampler_free(smpl);
-    llama_backend_free();
-
-    return 0;
-}

ggml/CMakeLists.txt

@@ -366,6 +366,8 @@ if (MSVC)
         /wd4005  # Macro redefinition
         /wd4244  # Conversion from one type to another type, possible loss of data
         /wd4267  # Conversion from 'size_t' to a smaller type, possible loss of data
+        /wd4996  # Disable POSIX deprecation warnings
+        /wd4702  # Unreachable code warnings
     )
     function(disable_msvc_warnings target_name)
         if(TARGET ${target_name})

ggml/include/ggml.h

@@ -673,11 +673,15 @@ extern "C" {
     GGML_API bool ggml_is_3d        (const struct ggml_tensor * tensor);
     GGML_API int  ggml_n_dims       (const struct ggml_tensor * tensor); // returns 1 for scalars
 
+    // returns whether the tensor elements can be iterated over with a flattened index (no gaps, no permutation)
     GGML_API bool ggml_is_contiguous  (const struct ggml_tensor * tensor);
     GGML_API bool ggml_is_contiguous_0(const struct ggml_tensor * tensor); // same as ggml_is_contiguous()
     GGML_API bool ggml_is_contiguous_1(const struct ggml_tensor * tensor); // contiguous for dims >= 1
     GGML_API bool ggml_is_contiguous_2(const struct ggml_tensor * tensor); // contiguous for dims >= 2
 
+    // returns whether the tensor elements are allocated as one contiguous block of memory (no gaps, but permutation ok)
+    GGML_API bool ggml_is_contiguously_allocated(const struct ggml_tensor * tensor);
+
     // true for tensor that is stored in memory as CxWxHxN and has been permuted to WxHxCxN
     GGML_API bool ggml_is_contiguous_channels(const struct ggml_tensor * tensor);
 

ggml/src/CMakeLists.txt

@@ -214,7 +214,7 @@ add_library(ggml
 target_link_libraries(ggml PUBLIC ggml-base)
 
 if (CMAKE_SYSTEM_NAME MATCHES "Linux")
-    target_link_libraries(ggml PRIVATE dl stdc++fs)
+    target_link_libraries(ggml PRIVATE dl)
 endif()
 
 function(ggml_add_backend_library backend)

ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp

@@ -72,8 +72,6 @@ static_assert(sizeof(block_iq4_nlx4) == 4 * sizeof(ggml_half) + QK4_NL * 2, "wro
 
 #if defined(__GNUC__)
 #pragma GCC diagnostic ignored "-Woverlength-strings"
-#elif defined(_MSC_VER)
-#pragma warning(disable: 4244 4267) // possible loss of data
 #endif
 
 #define UNUSED GGML_UNUSED

ggml/src/ggml-cpu/ggml-cpu-quants.c

@@ -20,12 +20,6 @@
 #define GROUP_MAX_EPS_IQ1_M 1e-7f
 #define GROUP_MAX_EPS_IQ1_S 1e-12f
 
-#if defined(_MSC_VER)
-// disable "possible loss of data" to avoid warnings for hundreds of casts
-// we should just be careful :)
-#pragma warning(disable: 4244 4267)
-#endif
-
 #define UNUSED GGML_UNUSED
 
 // some compilers don't provide _mm256_set_m128i, e.g. gcc 7

ggml/src/ggml-cpu/ggml-cpu.c

@@ -50,19 +50,6 @@
 #include "llamafile/sgemm.h"
 #endif
 
-#if defined(_MSC_VER)
-// disable "possible loss of data" to avoid hundreds of casts
-// we should just be careful :)
-#pragma warning(disable: 4244 4267)
-
-// disable POSIX deprecation warnings
-// these functions are never going away, anyway
-#pragma warning(disable: 4996)
-
-// unreachable code because of multiple instances of code after GGML_ABORT
-#pragma warning(disable: 4702)
-#endif
-
 // Note: once we move threading into a separate C++ file
 // will use std::hardware_destructive_interference_size instead of hardcoding it here
 // and we'll use C++ attribute syntax.

ggml/src/ggml-cpu/ops.cpp

@@ -8,19 +8,6 @@
 
 #include <float.h>
 
-#if defined(_MSC_VER)
-// disable "possible loss of data" to avoid hundreds of casts
-// we should just be careful :)
-#pragma warning(disable: 4244 4267)
-
-// disable POSIX deprecation warnings
-// these functions are never going away, anyway
-#pragma warning(disable: 4996)
-
-// unreachable code because of multiple instances of code after GGML_ABORT
-#pragma warning(disable: 4702)
-#endif
-
 // ggml_compute_forward_dup
 
 static void ggml_compute_forward_dup_same_cont(

ggml/src/ggml-cpu/vec.cpp

@@ -2,12 +2,6 @@
 
 #include <cassert>
 
-#if defined(_MSC_VER)
-// disable "possible loss of data" to avoid hundreds of casts
-// we should just be careful :)
-#pragma warning(disable: 4244 4267)
-#endif
-
 // precomputed gelu table for f16 (128 KB)
 ggml_fp16_t ggml_table_gelu_f16[1 << 16];
 

ggml/src/ggml-cuda/CMakeLists.txt

@@ -12,12 +12,30 @@ if (CUDAToolkit_FOUND)
         # 61     == Pascal, __dp4a instruction (per-byte integer dot product)
         # 70     == V100, FP16 tensor cores
         # 75     == Turing, int8 tensor cores
+        # 80     == Ampere, asynchronous data loading, faster tensor core instructions
+        # 86     == RTX 3000, needs CUDA v11.1
+        # 89     == RTX 4000, needs CUDA v11.8
+        #
+        # XX-virtual == compile CUDA code as PTX, do JIT compilation to binary code on first run
+        # XX-real    == compile CUDA code as device code for this specific architecture
+        # no suffix  == compile as both PTX and device code
+        #
+        # The default behavior for a non-native is to build virtual architectures as needed to cover all features needed
+        #     for best performance and to also build real architectures for the most commonly used GPUs.
         if (GGML_NATIVE AND CUDAToolkit_VERSION VERSION_GREATER_EQUAL "11.6" AND CMAKE_VERSION VERSION_GREATER_EQUAL "3.24")
             set(CMAKE_CUDA_ARCHITECTURES "native")
         elseif(GGML_CUDA_F16 OR GGML_CUDA_DMMV_F16)
-            set(CMAKE_CUDA_ARCHITECTURES "60;61;70;75;80")
+            if (CUDAToolkit_VERSION VERSION_GREATER_EQUAL "11.8")
+                set(CMAKE_CUDA_ARCHITECTURES "60-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-real;89-real")
+            else()
+                set(CMAKE_CUDA_ARCHITECTURES "60-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-real")
+            endif()
         else()
-            set(CMAKE_CUDA_ARCHITECTURES "50;61;70;75;80")
+            if (CUDAToolkit_VERSION VERSION_GREATER_EQUAL "11.8")
+                set(CMAKE_CUDA_ARCHITECTURES "50-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-real;89-real")
+            else()
+                set(CMAKE_CUDA_ARCHITECTURES "50-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-real")
+            endif()
         endif()
     endif()
     message(STATUS "Using CUDA architectures: ${CMAKE_CUDA_ARCHITECTURES}")

ggml/src/ggml-cuda/common.cuh

@@ -130,10 +130,6 @@ static int ggml_cuda_highest_compiled_arch(const int arch) {
 
 #define MATRIX_ROW_PADDING 512 // last row of quant. matrices is a multiple of this to avoid out-of-bounds memory accesses
 
-#if defined(_MSC_VER)
-#pragma warning(disable: 4244 4267) // possible loss of data
-#endif
-
 #define GGML_CUDA_MAX_STREAMS 8
 
 [[noreturn]]

ggml/src/ggml-cuda/fattn-common.cuh

@@ -719,6 +719,7 @@ void launch_fattn(
     size_t nb23 = V->nb[3];
 
     if (need_f16_K && K->type != GGML_TYPE_F16) {
+        GGML_ASSERT(ggml_is_contiguously_allocated(K));
         K_f16.alloc(ggml_nelements(K));
         to_fp16_cuda_t to_fp16 = ggml_get_to_fp16_cuda(K->type);
         to_fp16(K_data, K_f16.ptr, ggml_nelements(K), main_stream);
@@ -733,6 +734,7 @@ void launch_fattn(
     }
 
     if (need_f16_V && V->type != GGML_TYPE_F16) {
+        GGML_ASSERT(ggml_is_contiguously_allocated(V));
         V_f16.alloc(ggml_nelements(V));
         to_fp16_cuda_t to_fp16 = ggml_get_to_fp16_cuda(V->type);
         to_fp16(V_data, V_f16.ptr, ggml_nelements(V), main_stream);

ggml/src/ggml-cuda/ggml-cuda.cu

@@ -1536,6 +1536,8 @@ static void ggml_cuda_op_mul_mat(
 
         // If src0 is on a temporary compute buffer (partial offloading) there may be some padding that needs to be cleared:
         if (ne00 % MATRIX_ROW_PADDING != 0 && ggml_is_quantized(src0->type) && ggml_backend_buffer_get_usage(src0->buffer) == GGML_BACKEND_BUFFER_USAGE_COMPUTE && src0->view_src == nullptr) {
+            GGML_ASSERT(ggml_is_contiguously_allocated(src0));
+            GGML_ASSERT(!src0->view_src);
             const size_t nbytes_data    = ggml_row_size(src0->type, (dev[id].row_high - dev[id].row_low)*ne00);
             const size_t nbytes_padding = ggml_row_size(src0->type, MATRIX_ROW_PADDING - ne00 % MATRIX_ROW_PADDING);
             CUDA_CHECK(cudaMemsetAsync(dev[id].src0_dd + nbytes_data, 0, nbytes_padding, stream));
@@ -2067,10 +2069,11 @@ static void ggml_cuda_mul_mat_id(ggml_backend_cuda_context & ctx, ggml_tensor *
         }
 
         ggml_tensor src0_slice = *src0;
-        src0_slice.ne[2] = 1;
-        src0_slice.nb[3] = src0_slice.nb[2];
-        src0_slice.data  = (char *) src0->data + i02*nb02;
-        GGML_ASSERT(!ggml_cuda_should_use_mmq(src0->type, cc, ne11) || ne00 % MATRIX_ROW_PADDING == 0);
+        src0_slice.ne[2]    = 1;
+        src0_slice.nb[3]    = src0_slice.nb[2];
+        src0_slice.op       = GGML_OP_VIEW;
+        src0_slice.view_src = dst->src[0]; // non-const pointer to src0
+        src0_slice.data     = (char *) src0->data + i02*nb02;
 
         ggml_tensor src1_slice;
         memset(&src1_slice, 0, sizeof(src1_slice));

ggml/src/ggml-cuda/mmq.cu

@@ -91,7 +91,8 @@ void ggml_cuda_mul_mat_q(
 
     // If src0 is a temporary compute buffer, clear any potential padding.
     if (ggml_backend_buffer_get_usage(src0->buffer) == GGML_BACKEND_BUFFER_USAGE_COMPUTE) {
-        GGML_ASSERT(ggml_is_contiguous(src0));
+        GGML_ASSERT(ggml_is_contiguously_allocated(src0));
+        GGML_ASSERT(!src0->view_src);
         const size_t size_data  = ggml_nbytes(src0);
         const size_t size_alloc = ggml_backend_buffer_get_alloc_size(src0->buffer, src0);
         if (size_alloc > size_data) {

ggml/src/ggml-cuda/mmq.cuh

@@ -2522,7 +2522,7 @@ template <ggml_type type, int mmq_x, int nwarps, bool need_check, bool fixup>
 static __device__ __forceinline__ void mul_mat_q_process_tile(
         const char * __restrict__ x, const int offset_x, const int * __restrict__ y,
         const int * __restrict__ ids_dst, float * __restrict__ dst, float * __restrict__ tmp_fixup,
-        const int nrows_x, const int stride_row_x, const int ncols_y, const int stride_col_dst,
+        const int stride_row_x, const int ncols_y, const int stride_col_dst,
         const int tile_x_max_i, const int tile_y_max_j, const int kb0_start, const int kb0_stop) {
 
     constexpr int              qk         = ggml_cuda_type_traits<type>::qk;
@@ -2689,7 +2689,7 @@ static __global__ void mul_mat_q(
 
         constexpr bool fixup = false;
         mul_mat_q_process_tile<type, mmq_x, nwarps, need_check, fixup>
-            (x, offset_x, y + offset_y, ids_dst_shared, dst + offset_dst, tmp_fixup, nrows_x, stride_row_x, ncols_y, stride_col_dst,
+            (x, offset_x, y + offset_y, ids_dst_shared, dst + offset_dst, tmp_fixup, stride_row_x, ncols_y, stride_col_dst,
              tile_x_max_i, tile_y_max_j, 0, ncols_x/qk);
         return;
     }
@@ -2767,7 +2767,7 @@ static __global__ void mul_mat_q(
 
         constexpr bool fixup = false; // All but (potentially) the last iterations write their data to dst rather than the fixup buffer.
         mul_mat_q_process_tile<type, mmq_x, nwarps, need_check, fixup>
-            (x, offset_x, y + offset_y, ids_dst_shared, dst + offset_dst, tmp_fixup, nrows_x, stride_row_x, ncols_y, stride_col_dst,
+            (x, offset_x, y + offset_y, ids_dst_shared, dst + offset_dst, tmp_fixup, stride_row_x, ncols_y, stride_col_dst,
              tile_x_max_i, tile_y_max_j, kb0_start, kb0_stop);
 
         kbc += blocks_per_ne00;
@@ -2834,7 +2834,7 @@ static __global__ void mul_mat_q(
 
     constexpr bool fixup = true; // Last index writes its data to fixup buffer to avoid data races with other blocks.
     mul_mat_q_process_tile<type, mmq_x, nwarps, need_check, fixup>
-        (x, offset_x, y + offset_y, ids_dst_shared, dst + offset_dst, tmp_fixup, nrows_x, stride_row_x, ncols_y, stride_col_dst,
+        (x, offset_x, y + offset_y, ids_dst_shared, dst + offset_dst, tmp_fixup, stride_row_x, ncols_y, stride_col_dst,
          tile_x_max_i, tile_y_max_j, kb0_start, kb0_stop);
 }
 

ggml/src/ggml-cuda/mmvq.cu

@@ -515,7 +515,8 @@ void ggml_cuda_mul_mat_vec_q(
 
     // If src0 is a temporary compute buffer, clear any potential padding.
     if (ggml_backend_buffer_get_usage(src0->buffer) == GGML_BACKEND_BUFFER_USAGE_COMPUTE) {
-        GGML_ASSERT(ggml_is_contiguous(src0));
+        GGML_ASSERT(ggml_is_contiguously_allocated(src0));
+        GGML_ASSERT(!src0->view_src);
         const size_t size_data  = ggml_nbytes(src0);
         const size_t size_alloc = ggml_backend_buffer_get_alloc_size(src0->buffer, src0);
         if (size_alloc > size_data) {

ggml/src/ggml-quants.c

@@ -19,12 +19,6 @@
 #define GROUP_MAX_EPS_IQ1_M 1e-7f
 #define GROUP_MAX_EPS_IQ1_S 1e-12f
 
-#if defined(_MSC_VER)
-// disable "possible loss of data" to avoid warnings for hundreds of casts
-// we should just be careful :)
-#pragma warning(disable: 4244 4267)
-#endif
-
 #define UNUSED GGML_UNUSED
 
 // reference implementation for deterministic creation of model files

ggml/src/ggml-sycl/common.hpp

@@ -80,10 +80,6 @@ extern int g_ggml_sycl_disable_optimize;
 // max batch size to use MMQ kernels when tensor cores are available
 #define MMQ_MAX_BATCH_SIZE 32
 
-#if defined(_MSC_VER)
-#pragma warning(disable : 4244 4267) // possible loss of data
-#endif
-
 // dmmv = dequantize_mul_mat_vec
 #ifndef GGML_SYCL_DMMV_X
 #define GGML_SYCL_DMMV_X 32
@@ -118,17 +114,12 @@ static void crash() {
   GGML_ABORT("SYCL error");
 }
 
-#define SYCL_CHECK(err)                     \
-  do {                                      \
-    auto err_ = (err);                      \
-    if (err_ != 0)                          \
-      ggml_sycl_error(                      \
-          #err,                             \
-          __func__,                         \
-          __FILE__,                         \
-          __LINE__,                         \
-          "Meet error in this line code!"); \
-  } while (0)
+#define SYCL_CHECK(err)                                                                                    \
+    do {                                                                                                   \
+        auto err_ = (err);                                                                                 \
+        if (err_ != 0)                                                                                     \
+            ggml_sycl_error(#err, __func__, __FILE__, __LINE__, "Exception caught in this line of code."); \
+    } while (0)
 
 #if DPCT_COMPAT_RT_VERSION >= 11100
 #define GGML_SYCL_ASSUME(x) __builtin_assume(x)

ggml/src/ggml-sycl/convert.cpp

@@ -437,41 +437,52 @@ static void dequantize_row_iq4_nl_sycl(const void *vx, dst_t *y, const int64_t k
 }
 
 template <typename src_t, typename dst_t>
-static void convert_unary(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t k,
-                          const sycl::nd_item<3> &item_ct1) {
+static void convert_unary_nc(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t ne00, const int64_t ne01,
+                          const int64_t ne02, const int64_t s01, const int64_t s02, const int64_t s03,
+                          const sycl::nd_item<3> & item_ct1) {
+
     const int64_t work_group_size = item_ct1.get_local_range(2);
-    const int64_t global_id = item_ct1.get_local_id(2) + work_group_size * item_ct1.get_group(2);
+    const int64_t global_id       = item_ct1.get_local_id(2) + work_group_size * item_ct1.get_group(2);
+
+    const int64_t i01 = item_ct1.get_group(1);
+    const int64_t i02 = item_ct1.get_group(0) % ne02;
+    const int64_t i03 = item_ct1.get_group(0) / ne02;
 
     // make each work-item deal with more elements since sycl global range can not exceed max int
-    const src_t * x = (const src_t *) vx;
-    for (int64_t i = global_id; i < k; i += work_group_size * item_ct1.get_group_range(2)) {
-        y[i] = x[i];
+    const src_t * x = static_cast<const src_t *>(vx);
+    const int64_t ix = i03 * s03 + i02 * s02 + i01 * s01;
+    const int64_t iy = ((i03 * ne02 + i02) * ne01 + i01) * ne00;
+
+#pragma unroll
+    for (int64_t i00 = global_id; i00 < ne00; i00 += work_group_size * item_ct1.get_group_range(2)) {
+        y[iy + i00] = static_cast<dst_t>(x[ix + i00]);
     }
 }
 
 template <typename src_t, typename dst_t>
-static void convert_unary_sycl(const void *__restrict__ vx,
-                               dst_t *__restrict__ y, const int64_t k,
-                               dpct::queue_ptr stream) {
-    const int64_t num_blocks = (k + SYCL_DEQUANTIZE_BLOCK_SIZE - 1) / SYCL_DEQUANTIZE_BLOCK_SIZE;
+static void convert_unary_nc_sycl(const void * __restrict__ vx, dst_t * __restrict__ y,
+                                  const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03,
+                                  const int64_t s01, const int64_t s02, const int64_t s03, dpct::queue_ptr queue) {
+    dpct::has_capability_or_fail(queue->get_device(), { sycl::aspect::fp16 });
+
+    sycl::range<3> global_size(ne02 * ne03, ne01, ceil_div(ne00, SYCL_DEQUANTIZE_BLOCK_SIZE));
 
     // decrease global range when it exceeds the max int
-    int64_t local_size = downsample_sycl_global_range(num_blocks, SYCL_DEQUANTIZE_BLOCK_SIZE);
-    sycl::range<3> block_nums(1, 1, num_blocks);
-    sycl::range<3> local_range(1, 1, local_size);
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
+    // TODO: Downsample logic is separated from the kernel, a rewrite is desirable
+    int64_t        downsized_workgroup = downsample_sycl_global_range(global_size[0], SYCL_DEQUANTIZE_BLOCK_SIZE);
+    sycl::range<3> workgroup_size(1, 1, downsized_workgroup);
 
-        stream->parallel_for(
-            sycl::nd_range<3>(block_nums * local_range, local_range),
-            [=](sycl::nd_item<3> item_ct1) {
-                convert_unary<src_t>(vx, y, k, item_ct1);
-            });
-    }
+    queue->parallel_for(sycl::nd_range<3>(global_size * workgroup_size, workgroup_size), [=](sycl::nd_item<3> item_ct1) {
+        convert_unary_nc<src_t>(vx, y, ne00, ne01, ne02, s01, s02, s03, item_ct1);
+    });
 }
 
-to_fp16_sycl_t ggml_get_to_fp16_sycl(ggml_type type, ggml_tensor *dst) {
+template <typename src_t, typename dst_t>
+static void convert_unary_sycl(const void * vx, dst_t * y, const int64_t k, dpct::queue_ptr queue) {
+    convert_unary_nc_sycl<src_t>(vx, y, k, 1, 1, 1, k, k, k, queue);
+}
+
+to_fp16_sycl_t ggml_get_to_fp16_sycl(ggml_type type, ggml_tensor * dst) {
     switch (type) {
         case GGML_TYPE_Q4_0:
             if (dst->src[0]->extra &&
@@ -574,3 +585,12 @@ to_fp32_sycl_t ggml_get_to_fp32_sycl(ggml_type type, ggml_tensor *dst) {
             return nullptr;
     }
 }
+
+to_fp16_nc_sycl_t get_to_fp16_nc_sycl(ggml_type type) {
+    switch (type) {
+        case GGML_TYPE_F32:
+            return convert_unary_nc_sycl<float>;
+        default:
+            return nullptr;
+    }
+}

ggml/src/ggml-sycl/convert.hpp

@@ -1,6 +1,6 @@
 //
 // MIT license
-// Copyright (C) 2024 Intel Corporation
+// Copyright (C) 2025 Intel Corporation
 // SPDX-License-Identifier: MIT
 //
 
@@ -16,12 +16,19 @@
 #include "common.hpp"
 
 template <typename T>
-using to_t_sycl_t = void (*)(const void *__restrict__ x, T *__restrict__ y,
-                             int64_t k, dpct::queue_ptr stream);
-typedef to_t_sycl_t<float> to_fp32_sycl_t;
+using to_t_sycl_t = void (*)(const void * __restrict__ x, T * __restrict__ y, int64_t k, dpct::queue_ptr stream);
+typedef to_t_sycl_t<float>      to_fp32_sycl_t;
 typedef to_t_sycl_t<sycl::half> to_fp16_sycl_t;
 
-to_fp16_sycl_t ggml_get_to_fp16_sycl(ggml_type type, ggml_tensor *dst);
-to_fp32_sycl_t ggml_get_to_fp32_sycl(ggml_type type, ggml_tensor *dst);
+to_fp16_sycl_t ggml_get_to_fp16_sycl(ggml_type type, ggml_tensor * dst);
+to_fp32_sycl_t ggml_get_to_fp32_sycl(ggml_type type, ggml_tensor * dst);
 
-#endif // GGML_SYCL_CONVERT_HPP
+// Nc = Non-contiguous
+template <typename T>
+using to_t_nc_sycl_t = void (*)(const void * x, T * y, int64_t ne00, int64_t ne01, int64_t ne02, int64_t ne03,
+                                   int64_t s01, int64_t s02, int64_t s03, dpct::queue_ptr queue);
+
+typedef to_t_nc_sycl_t<sycl::half> to_fp16_nc_sycl_t;
+to_fp16_nc_sycl_t get_to_fp16_nc_sycl(ggml_type type);
+
+#endif  // GGML_SYCL_CONVERT_HPP

ggml/src/ggml-sycl/ggml-sycl.cpp

@@ -193,7 +193,7 @@ static void ggml_check_sycl() try {
 
     if (!initialized) {
         g_ggml_sycl_debug = get_sycl_env("GGML_SYCL_DEBUG", 0);
-        g_ggml_sycl_disable_optimize= get_sycl_env("GGML_SYCL_DISABLE_OPT", 0);
+        g_ggml_sycl_disable_optimize= get_sycl_env("GGML_SYCL_DISABLE_OPT", 1);
         g_ggml_sycl_disable_graph = get_sycl_env("GGML_SYCL_DISABLE_GRAPH", 1);
         GGML_SYCL_DEBUG("[SYCL] call ggml_check_sycl\n");
         GGML_LOG_INFO("Running with Environment Variables:\n");
@@ -338,7 +338,7 @@ ggml_backend_sycl_buffer_init_tensor(ggml_backend_buffer_t buffer,
         assert(tensor->view_src->buffer->buft == buffer->buft);
         return GGML_STATUS_SUCCESS;
     }
-    if (tensor->type == GGML_TYPE_Q4_0) {
+    if (tensor->type == GGML_TYPE_Q4_0 && !g_ggml_sycl_disable_optimize) {
         ggml_tensor_extra_gpu * extra = new ggml_tensor_extra_gpu{};
         tensor->extra                 = extra;
         ctx->tensor_extras.push_back(extra);  //used to release it when destroy ctx.
@@ -2694,35 +2694,31 @@ catch (sycl::exception const &exc) {
   std::exit(1);
 }
 
-static void k_compute_batched_ptrs(const sycl::half *src0_as_f16,
-                                   const sycl::half *src1_as_f16, char *dst,
-                                   const void **ptrs_src, void **ptrs_dst,
-                                   int64_t ne12, int64_t ne13, int64_t ne23,
-                                   size_t nb02, size_t nb03, size_t nb12,
-                                   size_t nb13, size_t nbd2, size_t nbd3,
-                                   int64_t r2, int64_t r3,
-                                   const sycl::nd_item<3> &item_ct1) {
-    int64_t i13 = item_ct1.get_group(2) * item_ct1.get_local_range(2) +
-                  item_ct1.get_local_id(2);
-    int64_t i12 = item_ct1.get_group(1) * item_ct1.get_local_range(1) +
-                  item_ct1.get_local_id(1);
+static void k_compute_batched_ptrs(const sycl::half * src0_as_f16, const sycl::half * src1_as_f16, char * dst,
+                                   const void ** ptrs_src, void ** ptrs_dst, int64_t ne12, int64_t ne13, int64_t ne23,
+                                   size_t nb02, size_t nb03, size_t nb12, size_t nb13, size_t nbd2, size_t nbd3,
+                                   int64_t r2, int64_t r3, const sycl::nd_item<3> & item_ct1) {
+    const int64_t i13 = item_ct1.get_group(2) * item_ct1.get_local_range(2) + item_ct1.get_local_id(2);
+    const int64_t i12 = item_ct1.get_group(1) * item_ct1.get_local_range(1) + item_ct1.get_local_id(1);
 
     if (i13 >= ne13 || i12 >= ne12) {
         return;
     }
 
-    int64_t i03 = i13 / r3;
-    int64_t i02 = i12 / r2;
+    const int64_t i03 = i13 / r3;
+    const int64_t i02 = i12 / r2;
 
-    ptrs_src[0*ne23 + i12 + i13*ne12] = (const char *) src0_as_f16 + i02*nb02 + i03*nb03;
-    ptrs_src[1*ne23 + i12 + i13*ne12] = (const char *) src1_as_f16 + i12*nb12 + i13*nb13;
-    ptrs_dst[0*ne23 + i12 + i13*ne12] = (      char *)         dst + i12*nbd2 + i13*nbd3;
+    const uint8_t * src0_bytes = reinterpret_cast<const uint8_t *>(src0_as_f16);
+    const uint8_t * src1_bytes = reinterpret_cast<const uint8_t *>(src1_as_f16);
+    uint8_t *       dst_bytes  = reinterpret_cast<uint8_t *>(dst);
+
+    ptrs_src[0 * ne23 + i12 + i13 * ne12] = src0_bytes + i02 * nb02 + i03 * nb03;
+    ptrs_src[1 * ne23 + i12 + i13 * ne12] = src1_bytes + i12 * nb12 + i13 * nb13;
+    ptrs_dst[0 * ne23 + i12 + i13 * ne12] = dst_bytes + i12 * nbd2 + i13 * nbd3;
 }
 
-static void ggml_sycl_mul_mat_batched_sycl(ggml_backend_sycl_context & ctx,
-                                             const ggml_tensor *src0,
-                                             const ggml_tensor *src1,
-                                             ggml_tensor *dst) try {
+static void ggml_sycl_mul_mat_batched_sycl(ggml_backend_sycl_context & ctx, const ggml_tensor * src0,
+                                           const ggml_tensor * src1, ggml_tensor * dst) try {
     GGML_ASSERT(!ggml_is_transposed(src0));
     GGML_ASSERT(!ggml_is_transposed(src1));
     GGML_ASSERT(!ggml_backend_buffer_is_sycl_split(src0->buffer));
@@ -2730,102 +2726,100 @@ static void ggml_sycl_mul_mat_batched_sycl(ggml_backend_sycl_context & ctx,
 
     GGML_TENSOR_BINARY_OP_LOCALS
 
+    // TODO: see https://github.com/ggml-org/llama.cpp/pull/13155
+    // Batched mul_mat requires a rewrite to support both oneDNN and non-contiguous dst
+    GGML_ASSERT(ggml_is_contiguous(dst));
 
     SYCL_CHECK(ggml_sycl_set_device(ctx.device));
-    queue_ptr main_stream = ctx.stream();;
+    queue_ptr queue = ctx.stream();
 
-    void * src0_ddq = src0->data;
-    sycl::half *src0_as_f16 = (sycl::half *)src0_ddq;
-    float * src1_ddf = (float *) src1->data;
-    float * dst_ddf = (float *) dst->data;
+    dpct::has_capability_or_fail(queue->get_device(), { sycl::aspect::fp16 });
+
+    const sycl::half * src0_f16 = static_cast<const sycl::half *>(src0->data);
+    float *            dst_ddf  = static_cast<float *>(dst->data);
+
+    const sycl::half * src1_f16       = static_cast<const sycl::half *>(src1->data);
+    const size_t       type_size_src1 = ggml_type_size(src1->type);
+    GGML_ASSERT(nb10 == type_size_src1);
+
+    // SRC1 strides
+    int64_t                          s11 = nb11 / type_size_src1;
+    int64_t                          s12 = nb12 / type_size_src1;
+    int64_t                          s13 = nb13 / type_size_src1;
+    ggml_sycl_pool_alloc<sycl::half> src1_f16_alloc(ctx.pool());
 
     // convert src1 to fp16
-    ggml_sycl_pool_alloc<sycl::half> src1_f16_alloc(ctx.pool());
     if (src1->type != GGML_TYPE_F16) {
-        const to_fp16_sycl_t to_fp16_sycl = ggml_get_to_fp16_sycl(src1->type, dst);
+        const to_fp16_nc_sycl_t to_fp16_nc_sycl = get_to_fp16_nc_sycl(src1->type);
+        GGML_ASSERT(to_fp16_nc_sycl != nullptr);
         const int64_t ne_src1 = ggml_nelements(src1);
         src1_f16_alloc.alloc(ne_src1);
-        GGML_ASSERT(to_fp16_sycl != nullptr);
-        to_fp16_sycl(src1_ddf, src1_f16_alloc.get(), ne_src1, main_stream);
+        to_fp16_nc_sycl(src1_f16, src1_f16_alloc.get(), ne10, ne11, ne12, ne13, s11, s12, s13, queue);
+
+        src1_f16 = src1_f16_alloc.get();
+        s11      = ne10;
+        s12      = ne11 * s11;
+        s13      = ne12 * s12;
     }
-    sycl::half *src1_f16 = src1->type == GGML_TYPE_F16 ? (sycl::half *)src1_ddf
-                                                       : src1_f16_alloc.get();
 
-    char * dst_t;
+    ggml_sycl_pool_alloc<sycl::half> dst_f16(ctx.pool());
+    char *                           dst_t = reinterpret_cast<char *>(dst_ddf);
 
-    dpct::library_data_t cu_compute_type = dpct::library_data_t::real_float;
-    dpct::library_data_t cu_data_type = dpct::library_data_t::real_float;
+    dpct::library_data_t mkl_compute_type = dpct::library_data_t::real_float;
+    dpct::library_data_t mkl_data_type    = dpct::library_data_t::real_float;
 
     // dst strides
     size_t nbd2 = dst->nb[2];
     size_t nbd3 = dst->nb[3];
 
     const float alpha_f32 = 1.0f;
-    const float beta_f32 = 0.0f;
+    const float beta_f32  = 0.0f;
 
     const void * alpha = &alpha_f32;
     const void * beta  = &beta_f32;
 
-    dst_t = (char *) dst_ddf;
-
     GGML_ASSERT(ne12 % ne02 == 0);
     GGML_ASSERT(ne13 % ne03 == 0);
 
     // broadcast factors
-    const int64_t r2 = ne12/ne02;
-    const int64_t r3 = ne13/ne03;
+    const int64_t r2 = ne12 / ne02;
+    const int64_t r3 = ne13 / ne03;
 
     if (r2 == 1 && r3 == 1 && ggml_is_contiguous_2(src0) && ggml_is_contiguous_2(src1)) {
         // there is no broadcast and src0, src1 are contiguous across dims 2, 3
-        SYCL_CHECK(CHECK_TRY_ERROR(dpct::gemm_batch(
-            *main_stream, oneapi::math::transpose::trans, oneapi::math::transpose::nontrans, ne01, ne11, ne10, alpha,
-            (const char *) src0_as_f16, dpct::library_data_t::real_half, nb01 / nb00, nb02 / nb00,
-            (const char *) src1_f16, dpct::library_data_t::real_half, nb11 / nb10, nb12 / nb10, beta, (char *) dst_t,
-            cu_data_type, ne01, nb2 / nb0, ne12 * ne13, cu_compute_type)));
+        SYCL_CHECK(CHECK_TRY_ERROR(dpct::gemm_batch(*queue, oneapi::math::transpose::trans,
+                                                    oneapi::math::transpose::nontrans, ne01, ne11, ne10, alpha,
+                                                    src0_f16, dpct::library_data_t::real_half, nb01 / nb00, nb02 / nb00,
+                                                    src1_f16, dpct::library_data_t::real_half, s11, s12, beta, dst_t,
+                                                    mkl_data_type, ne0, ne1 * ne0, ne12 * ne13, mkl_compute_type)));
     } else {
-        const int ne23 = ne12*ne13;
+        const int ne23 = ne12 * ne13;
 
-        ggml_sycl_pool_alloc<const void *> ptrs_src(ctx.pool(), 2*ne23);
-        ggml_sycl_pool_alloc<      void *> ptrs_dst(ctx.pool(), 1*ne23);
+        ggml_sycl_pool_alloc<const void *>         ptrs_src(ctx.pool(), 2 * ne23);
+        ggml_sycl_pool_alloc<void *>               ptrs_dst(ctx.pool(), 1 * ne23);
         ggml_sycl_pool_alloc<matrix_info_t<float>> matrix_info(ctx.host_pool(), 1);
 
         sycl::range<3> block_dims(1, ne12, ne13);
-        /*
-        DPCT1049:47: The work-group size passed to the SYCL kernel may exceed
-        the limit. To get the device limit, query
-        info::device::max_work_group_size. Adjust the work-group size if needed.
-        */
-        {
-            dpct::has_capability_or_fail(main_stream->get_device(),
-                                         {sycl::aspect::fp16});
-
-            main_stream->submit([&](sycl::handler &cgh) {
-                const void **ptrs_src_get = ptrs_src.get();
-                void **ptrs_dst_get = ptrs_dst.get();
-                size_t nb12_scaled = src1->type == GGML_TYPE_F16 ? nb12 : nb12 / 2;
-                size_t nb13_scaled = src1->type == GGML_TYPE_F16 ? nb13 : nb13 / 2;
-                cgh.parallel_for(sycl::nd_range<3>(block_dims, block_dims),
-                                 [=](sycl::nd_item<3> item_ct1) {
-                                     k_compute_batched_ptrs(
-                                         src0_as_f16, src1_f16,
-                                         dst_t, ptrs_src_get,
-                                         ptrs_dst_get, ne12, ne13, ne23,
-                                         nb02, nb03, nb12_scaled, nb13_scaled,
-                                         nbd2, nbd3, r2, r3, item_ct1);
-                                 });
+        queue->submit([&](sycl::handler & cgh) {
+            const void ** ptrs_src_get = ptrs_src.get();
+            void **       ptrs_dst_get = ptrs_dst.get();
+            size_t        nb12_scaled  = src1->type == GGML_TYPE_F16 ? nb12 : s12 * sizeof(sycl::half);
+            size_t        nb13_scaled  = src1->type == GGML_TYPE_F16 ? nb13 : s13 * sizeof(sycl::half);
+            cgh.parallel_for(sycl::nd_range<3>(block_dims, block_dims), [=](sycl::nd_item<3> item_ct1) {
+                k_compute_batched_ptrs(src0_f16, src1_f16, dst_t, ptrs_src_get, ptrs_dst_get, ne12, ne13, ne23, nb02,
+                                       nb03, nb12_scaled, nb13_scaled, nbd2, nbd3, r2, r3, item_ct1);
             });
-        }
+        });
+
         SYCL_CHECK(CHECK_TRY_ERROR(dpct::gemm_batch(
-            *main_stream, oneapi::math::transpose::trans, oneapi::math::transpose::nontrans, ne01, ne11, ne10, alpha,
+            *queue, oneapi::math::transpose::trans, oneapi::math::transpose::nontrans, ne01, ne11, ne10, alpha,
             (const void **) (ptrs_src.get() + 0 * ne23), dpct::library_data_t::real_half, nb01 / nb00,
-            (const void **) (ptrs_src.get() + 1 * ne23), dpct::library_data_t::real_half, nb11 / nb10, beta,
-            (void **) (ptrs_dst.get() + 0 * ne23), cu_data_type, ne01, ne23, cu_compute_type, matrix_info.get())));
+            (const void **) (ptrs_src.get() + 1 * ne23), dpct::library_data_t::real_half, s11, beta,
+            (void **) (ptrs_dst.get() + 0 * ne23), mkl_data_type, ne0, ne23, mkl_compute_type, matrix_info.get())));
     }
-}
-catch (sycl::exception const &exc) {
-  std::cerr << exc.what() << "Exception caught at file:" << __FILE__
-            << ", line:" << __LINE__ << std::endl;
-  std::exit(1);
+} catch (const sycl::exception & exc) {
+    std::cerr << exc.what() << "Exception caught at file:" << __FILE__ << ", line:" << __LINE__ << std::endl;
+    std::exit(1);
 }
 
 inline bool ggml_sycl_supports_mmq(enum ggml_type type) {
@@ -2966,7 +2960,7 @@ static void ggml_sycl_mul_mat(ggml_backend_sycl_context & ctx, const ggml_tensor
             // The kernel from the if path is faster for that specific case, but does not support all mul mats.
             ggml_sycl_mul_mat_batched_sycl(ctx, src0, src1, dst);
         }
-    } else if (!split && src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && !ggml_is_transposed(src1) && src1->ne[1] == 1) {
+    } else if (!split && src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && ggml_is_contiguous(src1) && !ggml_is_transposed(src1) && src1->ne[1] == 1) {
         // KQV single-batch
         ggml_sycl_mul_mat_vec_nc(ctx, src0, src1, dst);
     } else if (!split && src0->type == GGML_TYPE_F16 && !ggml_is_transposed(src0) && !ggml_is_transposed(src1) && src1->ne[2]*src1->ne[3] > 1) {
@@ -3873,9 +3867,6 @@ static bool ggml_backend_sycl_device_supports_op(ggml_backend_dev_t dev, const g
                 if (a->ne[3] != b->ne[3]) {
                     return false;
                 }
-                if (!ggml_is_contiguous(b)) {
-                    return false;
-                }
                 ggml_type a_type = a->type;
                 if (a_type == GGML_TYPE_IQ4_NL  || a_type == GGML_TYPE_IQ4_XS ||
                     a_type == GGML_TYPE_IQ3_XXS || a_type == GGML_TYPE_IQ3_S  ||

ggml/src/ggml.c

@@ -1299,6 +1299,10 @@ bool ggml_is_contiguous_2(const struct ggml_tensor * tensor) {
     return ggml_is_contiguous_n(tensor, 2);
 }
 
+bool ggml_is_contiguously_allocated(const struct ggml_tensor * tensor) {
+    return ggml_nbytes(tensor) == ggml_nelements(tensor) * ggml_type_size(tensor->type)/ggml_blck_size(tensor->type);
+}
+
 bool ggml_is_permuted(const struct ggml_tensor * tensor) {
     static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
 

include/llama.h

@@ -351,19 +351,17 @@ extern "C" {
         enum ggml_type type_k; // data type for K cache [EXPERIMENTAL]
         enum ggml_type type_v; // data type for V cache [EXPERIMENTAL]
 
-        // Keep the booleans together and at the end of the struct to avoid misalignment during copy-by-value.
-        // TODO: move at the end of the struct
-        bool logits_all;  // the llama_decode() call computes all logits, not just the last one (DEPRECATED - set llama_batch.logits instead)
-        bool embeddings;  // if true, extract embeddings (together with logits)
-        bool offload_kqv; // whether to offload the KQV ops (including the KV cache) to GPU
-        bool flash_attn;  // whether to use flash attention [EXPERIMENTAL]
-        bool no_perf;     // whether to measure performance timings
-
         // Abort callback
         // if it returns true, execution of llama_decode() will be aborted
         // currently works only with CPU execution
         ggml_abort_callback abort_callback;
         void *              abort_callback_data;
+
+        // Keep the booleans together and at the end of the struct to avoid misalignment during copy-by-value.
+        bool embeddings;  // if true, extract embeddings (together with logits)
+        bool offload_kqv; // whether to offload the KQV ops (including the KV cache) to GPU
+        bool flash_attn;  // whether to use flash attention [EXPERIMENTAL]
+        bool no_perf;     // whether to measure performance timings
     };
 
     // model quantization parameters
@@ -924,14 +922,19 @@ extern "C" {
     // Frees a batch of tokens allocated with llama_batch_init()
     LLAMA_API void llama_batch_free(struct llama_batch batch);
 
-    // Processes a batch of tokens with the ecoder part of the encoder-decoder model.
-    // Stores the encoder output internally for later use by the decoder cross-attention layers.
+    // Process a batch of tokens.
+    // In contrast to llama_decode() - this call does not use KV cache.
+    // For encode-decoder contexts, processes the batch using the encoder.
+    // Can store the encoder output internally for later use by the decoder's cross-attention layers.
     //   0 - success
     // < 0 - error. the KV cache state is restored to the state before this call
     LLAMA_API int32_t llama_encode(
             struct llama_context * ctx,
               struct llama_batch   batch);
 
+    // Process a batch of tokens.
+    // Requires KV cache.
+    // For encode-decoder contexts, processes the batch using the decoder.
     // Positive return values does not mean a fatal error, but rather a warning.
     //   0 - success
     //   1 - could not find a KV slot for the batch (try reducing the size of the batch or increase the context)

scripts/sync-ggml.last

@@ -1 +1 @@
-0482de9c63b9134eb462c7732888c0ee0dbc2755
+b59bddafe278877dfa22a80e53a637513862babb

src/llama-context.cpp

@@ -116,8 +116,6 @@ llama_context::llama_context(
                 __func__, n_ctx_per_seq, hparams.n_ctx_train);
     }
 
-    logits_all = params.logits_all;
-
     if (!hparams.vocab_only) {
         // GPU backends
         for (auto * dev : model.devices) {
@@ -253,7 +251,7 @@ llama_context::llama_context(
     }
 
     // reserve worst-case graph
-    if (!hparams.vocab_only) {
+    if (!hparams.vocab_only && memory) {
         const uint32_t n_seqs = 1; // TODO: worst-case number of sequences
         const uint32_t n_tokens = std::min(cparams.n_ctx, cparams.n_ubatch);
 
@@ -702,6 +700,8 @@ int llama_context::encode(llama_batch & inp_batch) {
         t_compute_start_us = ggml_time_us();
     }
 
+    embd_seq.clear();
+
     n_queued_tokens += n_tokens;
 
     const int64_t n_embd = hparams.n_embd;
@@ -763,12 +763,12 @@ int llama_context::encode(llama_batch & inp_batch) {
         ggml_backend_t backend_embd = ggml_backend_sched_get_tensor_backend(sched.get(), t_embd);
         GGML_ASSERT(backend_embd != nullptr);
 
-        GGML_ASSERT(embd != nullptr);
-
         switch (cparams.pooling_type) {
             case LLAMA_POOLING_TYPE_NONE:
                 {
                     // extract token embeddings
+                    GGML_ASSERT(embd != nullptr);
+
                     GGML_ASSERT(n_tokens*n_embd <= (int64_t) embd_size);
                     ggml_backend_tensor_get_async(backend_embd, t_embd, embd, 0, n_tokens*n_embd*sizeof(float));
                 } break;
@@ -793,11 +793,18 @@ int llama_context::encode(llama_batch & inp_batch) {
                 } break;
             case LLAMA_POOLING_TYPE_RANK:
                 {
-                    // TODO: this likely should be the same logic as in llama_decoder_internal, but better to
-                    //       wait for an encoder model that requires this pooling type in order to test it
-                    //       https://github.com/ggerganov/llama.cpp/pull/9510
-                    GGML_ABORT("RANK pooling not implemented yet");
-                }
+                    // extract the rerank score - a single float per sequence
+                    auto & embd_seq_out = embd_seq;
+
+                    for (uint32_t s = 0; s < ubatch.n_seqs; ++s) {
+                        const llama_seq_id seq_id = ubatch.seq_id[s][0];
+                        if (embd_seq_out.find(seq_id) != embd_seq_out.end()) {
+                            continue;
+                        }
+                        embd_seq_out[seq_id].resize(1);
+                        ggml_backend_tensor_get_async(backend_embd, t_embd, embd_seq_out[seq_id].data(), (seq_id)*sizeof(float), sizeof(float));
+                    }
+                } break;
             case LLAMA_POOLING_TYPE_UNSPECIFIED:
                 {
                     GGML_ABORT("unknown pooling type");
@@ -835,6 +842,11 @@ int llama_context::encode(llama_batch & inp_batch) {
 }
 
 int llama_context::decode(llama_batch & inp_batch) {
+    if (!memory) {
+        LLAMA_LOG_WARN("%s: cannot decode batches with this context (use llama_encode() instead)\n", __func__);
+        return encode(inp_batch);
+    }
+
     if (inp_batch.n_tokens == 0) {
         LLAMA_LOG_ERROR("%s: n_tokens == 0\n", __func__);
         return -1;
@@ -890,7 +902,7 @@ int llama_context::decode(llama_batch & inp_batch) {
         for (uint32_t i = 0; i < n_tokens_all; ++i) {
             n_outputs_all += batch.logits[i] != 0;
         }
-    } else if (logits_all || embd_pooled) {
+    } else if (embd_pooled) {
         n_outputs_all = n_tokens_all;
     } else {
         // keep last output only
@@ -1853,13 +1865,12 @@ llama_context_params llama_context_default_params() {
         /*.cb_eval_user_data           =*/ nullptr,
         /*.type_k                      =*/ GGML_TYPE_F16,
         /*.type_v                      =*/ GGML_TYPE_F16,
-        /*.logits_all                  =*/ false,
+        /*.abort_callback              =*/ nullptr,
+        /*.abort_callback_data         =*/ nullptr,
         /*.embeddings                  =*/ false,
         /*.offload_kqv                 =*/ true,
         /*.flash_attn                  =*/ false,
         /*.no_perf                     =*/ true,
-        /*.abort_callback              =*/ nullptr,
-        /*.abort_callback_data         =*/ nullptr,
     };
 
     return result;

src/llama-context.h

@@ -187,9 +187,6 @@ private:
 
     std::unique_ptr<llama_memory_i> memory;
 
-    // TODO: remove
-    bool logits_all = false;
-
     // decode output (2-dimensional array: [n_outputs][n_vocab])
     size_t  logits_size = 0; // capacity (of floats) for logits
     float * logits      = nullptr;

src/llama-graph.cpp

@@ -782,7 +782,7 @@ ggml_tensor * llm_graph_context::build_ffn(
             } break;
     }
 
-    if (type_gate == LLM_FFN_PAR) {
+    if (gate && type_gate == LLM_FFN_PAR) {
         cur = ggml_mul(ctx0, cur, tmp);
         cb(cur, "ffn_gate_par", il);
     }

src/llama-model.cpp

@@ -1651,8 +1651,11 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
                 for (const auto * overrides = ml.tensor_buft_overrides; overrides->pattern != nullptr; ++overrides) {
                     std::regex pattern(overrides->pattern);
                     if (std::regex_search(tensor_name, pattern)) {
-                        LLAMA_LOG_DEBUG("tensor %s buffer type overriden to %s\n", tensor_name.c_str(), ggml_backend_buft_name(overrides->buft));
                         buft = overrides->buft;
+                        LLAMA_LOG_DEBUG("tensor %s (%zu MiB %s) buffer type overridden to %s\n",
+                                tensor_name.c_str(),
+                                ggml_nbytes(t_meta) / 1024 / 1024, ggml_type_name(t_meta->type),
+                                ggml_backend_buft_name(buft));
                         break;
                     }
                 }
@@ -3510,7 +3513,11 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
 
                     // output
                     output_norm   = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);
-                    output        = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, 0);
+                    output        = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);
+                    // if output is NULL, init from the input tok embed
+                    if (output == NULL) {
+                        output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);
+                    }
 
                     for (int i = 0; i < n_layer; ++i) {
                         auto & layer = layers[i];
@@ -4788,7 +4795,7 @@ struct llm_build_deci : public llm_graph_context {
             }
 
             // FFN-free layer of Llama-3_1-Nemotron-Ultra-253B
-            if (n_head == 0 && n_ff == 0) {
+            if (n_ff == 0) {
                 continue;
             }
 
@@ -12845,6 +12852,13 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
     llama_memory_i * res;
 
     switch (arch) {
+        case LLM_ARCH_BERT:
+        case LLM_ARCH_JINA_BERT_V2:
+        case LLM_ARCH_NOMIC_BERT:
+        case LLM_ARCH_NOMIC_BERT_MOE:
+            {
+                res = nullptr;
+            } break;
         case LLM_ARCH_MAMBA:
         case LLM_ARCH_RWKV6:
         case LLM_ARCH_RWKV6QWEN2:

src/llama-sampling.cpp

@@ -1750,27 +1750,35 @@ static const char * llama_sampler_top_n_sigma_name(const struct llama_sampler *
 static void llama_sampler_top_n_sigma_apply(struct llama_sampler * smpl, llama_token_data_array * cur_p) {
     const auto * ctx = (llama_sampler_top_n_sigma *) smpl->ctx;
 
-    if (ctx->n < 0.0f) {
+    if (ctx->n <= 0.0f || cur_p->size <= 1) {
         return;
     }
 
     // find max logit and calculate mean
     float max = cur_p->data[0].logit;
     float logits_sum = 0;
+    size_t valid_count = 0;
     for (size_t i = 0; i < cur_p->size; ++i) {
-        if (cur_p->data[i].logit > max) {
-            max = cur_p->data[i].logit;
+        // Only count non-negative infinity values
+        if (cur_p->data[i].logit != -INFINITY) {
+            if (cur_p->data[i].logit > max) {
+                max = cur_p->data[i].logit;
+            }
+            logits_sum += cur_p->data[i].logit;
+            valid_count++;
         }
-        logits_sum += cur_p->data[i].logit;
     }
-    float mean = logits_sum/cur_p->size;
+    float mean = valid_count > 0 ? logits_sum/valid_count : 0;
 
     // calculate standard deviation
     float acc = 0;
     for (size_t i = 0; i < cur_p->size; ++i) {
-        acc += pow(cur_p->data[i].logit - mean, 2);
+        // Skip -infinity in std calculation
+        if (cur_p->data[i].logit != -INFINITY) {
+            acc += pow(cur_p->data[i].logit - mean, 2);
+        }
     }
-    float std = sqrt(acc/cur_p->size);
+    float std = valid_count > 0 ? sqrt(acc/valid_count) : 0;
 
     //apply mask
     for (size_t i = 0; i < cur_p->size; ++i) {

tests/test-sampling.cpp

@@ -360,7 +360,7 @@ int main(void) {
     test_dry({0.2f, 0.2f, 0.2f, 0.2f, 0.2f}, {0, 1, 2, 3, 4, 0, 1}, {0.2f, 0.2f, 0.2f, 0.2f, 0.2f}, 1.0f, 1.1f, 4, 7, {});
 
     test_top_n_sigma({0.1f, 0.2f, 0.3f, 0.4f}, {0.571429f, 0.428571f, 0.0f, 0.0f}, 1.00f);
-    test_top_n_sigma({0.1f, 0.2f, 0.3f, 0.4f}, {1.0f, 0.0f, 0.0f, 0.0f}, 0.00f);
+    test_top_n_sigma({0.1f, 0.2f, 0.3f, 0.4f}, {0.4f, 0.3f, 0.2f, 0.1f}, 0.00f); // top_n_sigma == 0 now represents a no-op rather than greedy decoding as of PR#13345
     test_top_n_sigma({0.1f, 0.2f, 0.3f, 0.4f}, {0.4f, 0.3f, 0.2f, 0.1f}, 3.00f);
 
     test_sampler_queue(10000, "k", 10000, 1.0f, 1.0f);

tools/imatrix/imatrix.cpp

@@ -585,7 +585,6 @@ int main(int argc, char ** argv) {
     params.out_file = "imatrix.dat" ;
 
     params.n_ctx = 512;
-    params.logits_all = true;
     params.escape = false;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_IMATRIX, print_usage)) {

tools/main/main.cpp

@@ -99,14 +99,6 @@ int main(int argc, char ** argv) {
     console::init(params.simple_io, params.use_color);
     atexit([]() { console::cleanup(); });
 
-    if (params.logits_all) {
-        LOG_ERR("************\n");
-        LOG_ERR("%s: please use the 'perplexity' tool for perplexity calculations\n", __func__);
-        LOG_ERR("************\n\n");
-
-        return 0;
-    }
-
     if (params.embedding) {
         LOG_ERR("************\n");
         LOG_ERR("%s: please use the 'embedding' tool for embedding calculations\n", __func__);

tools/mtmd/mtmd.cpp

@@ -580,6 +580,79 @@ struct decode_embd_batch {
     }
 };
 
+// Helper function for decoding an image whose embeddings have already been calculated
+int32_t mtmd_helper_decode_image_chunk(
+        mtmd_context * ctx,
+        struct llama_context * lctx,
+        const mtmd_input_chunk * chunk,
+        float * encoded_embd,
+        llama_pos n_past,
+        llama_seq_id seq_id,
+        int32_t n_batch,
+        llama_pos * new_n_past) {
+    if (mtmd_input_chunk_get_type(chunk) != MTMD_INPUT_CHUNK_TYPE_IMAGE) {
+        LOG_ERR("failed to decode image chunk: input chunk not of image type\n");
+        return -1;
+    }
+    const auto image_tokens = mtmd_input_chunk_get_tokens_image(chunk);
+    if (!image_tokens) {
+        LOG_ERR("failed to decode image chunk: image tokens are null\n");
+        return -1;
+    }
+
+    int n_mmproj_embd = clip_n_mmproj_embd(ctx->ctx_clip);
+    int n_pos_per_embd = mtmd_decode_use_mrope(ctx) ? 4 : 1;
+
+    int32_t n_tokens = mtmd_image_tokens_get_n_tokens(image_tokens);
+    int32_t i_batch = 0;
+    int32_t n_img_batches = GGML_PAD(n_tokens, n_batch) / n_batch;
+    decode_embd_batch batch_embd(encoded_embd, n_tokens, n_pos_per_embd, n_mmproj_embd);
+
+    const int nx = mtmd_image_tokens_get_nx(image_tokens);
+    const int ny = mtmd_image_tokens_get_ny(image_tokens);
+
+    if (mtmd_decode_use_mrope(ctx)) {
+        batch_embd.set_position_mrope(n_past, nx, ny, seq_id);
+    } else {
+        batch_embd.set_position_normal(n_past, seq_id);
+    }
+
+    if (mtmd_decode_use_non_causal(ctx)) {
+        llama_set_causal_attn(lctx, false);
+        // TODO @ngxson : need to make sure only one image is processed at a time, and n_ubatch must be enough to hold the image
+    }
+
+    while (i_batch < n_img_batches) { // split into batches
+        int pos_offset = i_batch*n_batch;
+        int n_tokens_batch = std::min(n_batch, n_tokens - pos_offset);
+        llama_batch batch_embd_view = batch_embd.get_view(pos_offset, n_tokens_batch);
+
+        LOG_INF("decoding image batch %d/%d, n_tokens_batch = %d\n", i_batch+1, n_img_batches, n_tokens_batch);
+
+        int64_t t1 = ggml_time_ms();
+        int32_t ret = llama_decode(lctx, batch_embd_view);
+        if (ret != 0) {
+            LOG_ERR("failed to decode image\n");
+            llama_set_causal_attn(lctx, true); // restore causal attn
+            return ret;
+        }
+
+        if (ctx->print_timings) {
+            LOG_INF("image decoded (batch %d/%d) in %" PRId64 " ms\n", i_batch+1, n_img_batches, ggml_time_ms() - t1);
+        }
+
+        i_batch++;
+    }
+
+    n_past += mtmd_image_tokens_get_n_pos(image_tokens);
+    *new_n_past = n_past;
+
+    if (mtmd_decode_use_non_causal(ctx)) {
+        llama_set_causal_attn(lctx, true);
+    }
+    return 0;
+}
+
 int32_t mtmd_helper_eval_chunk_single(mtmd_context * ctx,
         struct llama_context * lctx,
         const mtmd_input_chunk * chunk,
@@ -591,8 +664,6 @@ int32_t mtmd_helper_eval_chunk_single(mtmd_context * ctx,
     int32_t ret;
     llama_batch text_batch = llama_batch_init(n_batch, 0, 1);
     auto chunk_type = mtmd_input_chunk_get_type(chunk);
-    int n_mmproj_embd = clip_n_mmproj_embd(ctx->ctx_clip);
-    int n_pos_per_embd = mtmd_decode_use_mrope(ctx) ? 4 : 1;
 
     if (chunk_type == MTMD_INPUT_CHUNK_TYPE_TEXT) {
         size_t n_tokens;
@@ -637,57 +708,13 @@ int32_t mtmd_helper_eval_chunk_single(mtmd_context * ctx,
         if (ctx->print_timings) {
             LOG_INF("image/slice encoded in %" PRId64 " ms\n", ggml_time_ms() - t0);
         }
-
-        int32_t n_tokens = mtmd_image_tokens_get_n_tokens(image_tokens);
-        int32_t i_batch = 0;
-        int32_t n_img_batches = GGML_PAD(n_tokens, n_batch) / n_batch;
         float * embd = mtmd_get_output_embd(ctx);
-        decode_embd_batch batch_embd(embd, n_tokens, n_pos_per_embd, n_mmproj_embd);
-
-        const int nx = mtmd_image_tokens_get_nx(image_tokens);
-        const int ny = mtmd_image_tokens_get_ny(image_tokens);
-
-        if (mtmd_decode_use_mrope(ctx)) {
-            batch_embd.set_position_mrope(n_past, nx, ny, seq_id);
-        } else {
-            batch_embd.set_position_normal(n_past, seq_id);
+        ret = mtmd_helper_decode_image_chunk(ctx, lctx, chunk, embd, n_past, seq_id, n_batch, new_n_past);
+        if (ret != 0) {
+            LOG_ERR("failed to decode image\n");
+            llama_batch_free(text_batch);
+            return ret;
         }
-
-        if (mtmd_decode_use_non_causal(ctx)) {
-            llama_set_causal_attn(lctx, false);
-            // TODO @ngxson : need to make sure only one image is processed at a time, and n_ubatch must be enough to hold the image
-        }
-
-        while (i_batch < n_img_batches) { // split into batches
-            int pos_offset = i_batch*n_batch;
-            int n_tokens_batch = std::min(n_batch, n_tokens - pos_offset);
-            llama_batch batch_embd_view = batch_embd.get_view(pos_offset, n_tokens_batch);
-
-            LOG_INF("decoding image batch %d/%d, n_tokens_batch = %d\n", i_batch+1, n_img_batches, n_tokens_batch);
-
-            int64_t t1 = ggml_time_ms();
-            ret = llama_decode(lctx, batch_embd_view);
-            if (ret != 0) {
-                LOG_ERR("failed to decode image\n");
-                llama_set_causal_attn(lctx, true); // restore causal attn
-                llama_batch_free(text_batch);
-                return ret;
-            }
-
-            if (ctx->print_timings) {
-                LOG_INF("image decoded (batch %d/%d) in %" PRId64 " ms\n", i_batch+1, n_img_batches, ggml_time_ms() - t1);
-            }
-
-            i_batch++;
-        }
-
-        n_past += mtmd_image_tokens_get_n_pos(image_tokens);
-        *new_n_past = n_past;
-
-        if (mtmd_decode_use_non_causal(ctx)) {
-            llama_set_causal_attn(lctx, true);
-        }
-
     } else {
         GGML_ABORT("chunk type not supported");
     }

tools/mtmd/mtmd.h

@@ -231,6 +231,18 @@ MTMD_API int32_t mtmd_helper_eval_chunk_single(mtmd_context * ctx,
                                                bool logits_last,
                                                llama_pos * new_n_past);
 
+// helper function to decode an image whose embeddings have already been calculated
+// this helper will handle batching and pre/post decoding setup (for ex. gemma 3 requires non-causal attention)
+// ret 0 on success, -1 on chunk not being a valid image chunk, 1 on decode failure
+MTMD_API int32_t mtmd_helper_decode_image_chunk(mtmd_context * ctx,
+                                                struct llama_context * lctx,
+                                                const mtmd_input_chunk * chunk,
+                                                float * encoded_embd,
+                                                llama_pos n_past,
+                                                llama_seq_id seq_id,
+                                                int32_t n_batch,
+                                                llama_pos * new_n_past);
+
 /////////////////////////////////////////
 
 // test function, to be used in test-mtmd-c-api.c

tools/perplexity/perplexity.cpp

@@ -1554,7 +1554,10 @@ static void multiple_choice_score(llama_context * ctx, const common_params & par
             if (int(batch_indeces.size()) != num_answers) {
                 batch_indeces.resize(num_answers);
             }
-            for (int s = 0; s < num_answers; ++s) batch_indeces[s] = s0 + s;
+
+            for (int s = 0; s < num_answers; ++s) {
+                batch_indeces[s] = s0 + s;
+            }
 
             for (size_t i = 0; i < cur_task.common_prefix; ++i) {
                 //llama_batch_add(batch, cur_task.seq_tokens[0][i], i, { s0 + 0, s0 + 1, s0 + 2, s0 + 3}, false);
@@ -1970,7 +1973,6 @@ int main(int argc, char ** argv) {
     common_params params;
 
     params.n_ctx = 512;
-    params.logits_all = true;
     params.escape = false;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_PERPLEXITY)) {

tools/server/server.cpp

@@ -3214,7 +3214,14 @@ struct server_context {
                 batch.logits   + i,
             };
 
-            const int ret = llama_decode(ctx, batch_view);
+            int ret = 0;
+
+            if (params_base.embedding || params_base.reranking) {
+                ret = llama_encode(ctx, batch_view);
+            } else {
+                ret = llama_decode(ctx, batch_view);
+            }
+
             metrics.on_decoded(slots);
 
             if (ret != 0) {
@@ -3943,7 +3950,7 @@ int main(int argc, char ** argv) {
     const auto handle_completions_impl = [&ctx_server, &res_error, &res_ok](
             server_task_type type,
             json & data,
-            std::function<bool()> is_connection_closed,
+            const std::function<bool()> & is_connection_closed,
             httplib::Response & res,
             oaicompat_type oaicompat) {
         GGML_ASSERT(type == SERVER_TASK_TYPE_COMPLETION || type == SERVER_TASK_TYPE_INFILL);

tools/server/webui/package-lock.json

@@ -21,6 +21,8 @@
         "postcss": "^8.4.49",
         "react": "^18.3.1",
         "react-dom": "^18.3.1",
+        "react-dropzone": "^14.3.8",
+        "react-hot-toast": "^2.5.2",
         "react-markdown": "^9.0.3",
         "react-router": "^7.1.5",
         "rehype-highlight": "^7.0.2",
@@ -2058,6 +2060,15 @@
       "dev": true,
       "license": "Python-2.0"
     },
+    "node_modules/attr-accept": {
+      "version": "2.2.5",
+      "resolved": "https://registry.npmjs.org/attr-accept/-/attr-accept-2.2.5.tgz",
+      "integrity": "sha512-0bDNnY/u6pPwHDMoF0FieU354oBi0a8rD9FcsLwzcGWbc8KS8KPIi7y+s13OlVY+gMWc/9xEMUgNE6Qm8ZllYQ==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=4"
+      }
+    },
     "node_modules/autoprefixer": {
       "version": "10.4.20",
       "resolved": "https://registry.npmjs.org/autoprefixer/-/autoprefixer-10.4.20.tgz",
@@ -2804,6 +2815,18 @@
         "node": ">=16.0.0"
       }
     },
+    "node_modules/file-selector": {
+      "version": "2.1.2",
+      "resolved": "https://registry.npmjs.org/file-selector/-/file-selector-2.1.2.tgz",
+      "integrity": "sha512-QgXo+mXTe8ljeqUFaX3QVHc5osSItJ/Km+xpocx0aSqWGMSCf6qYs/VnzZgS864Pjn5iceMRFigeAV7AfTlaig==",
+      "license": "MIT",
+      "dependencies": {
+        "tslib": "^2.7.0"
+      },
+      "engines": {
+        "node": ">= 12"
+      }
+    },
     "node_modules/fill-range": {
       "version": "7.1.1",
       "resolved": "https://registry.npmjs.org/fill-range/-/fill-range-7.1.1.tgz",
@@ -2917,6 +2940,15 @@
         "url": "https://github.com/sponsors/sindresorhus"
       }
     },
+    "node_modules/goober": {
+      "version": "2.1.16",
+      "resolved": "https://registry.npmjs.org/goober/-/goober-2.1.16.tgz",
+      "integrity": "sha512-erjk19y1U33+XAMe1VTvIONHYoSqE4iS7BYUZfHaqeohLmnC0FdxEh7rQU+6MZ4OajItzjZFSRtVANrQwNq6/g==",
+      "license": "MIT",
+      "peerDependencies": {
+        "csstype": "^3.0.10"
+      }
+    },
     "node_modules/graceful-fs": {
       "version": "4.2.11",
       "resolved": "https://registry.npmjs.org/graceful-fs/-/graceful-fs-4.2.11.tgz",
@@ -4674,6 +4706,15 @@
         "node": ">=0.10.0"
       }
     },
+    "node_modules/object-assign": {
+      "version": "4.1.1",
+      "resolved": "https://registry.npmjs.org/object-assign/-/object-assign-4.1.1.tgz",
+      "integrity": "sha512-rJgTQnkUnH1sFw8yT6VSU3zD3sWmu6sZhIseY8VX+GRu3P6F7Fu+JNDoXfklElbLJSnc3FUQHVe4cU5hj+BcUg==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=0.10.0"
+      }
+    },
     "node_modules/optionator": {
       "version": "0.9.4",
       "resolved": "https://registry.npmjs.org/optionator/-/optionator-0.9.4.tgz",
@@ -4872,6 +4913,17 @@
         "url": "https://github.com/prettier/prettier?sponsor=1"
       }
     },
+    "node_modules/prop-types": {
+      "version": "15.8.1",
+      "resolved": "https://registry.npmjs.org/prop-types/-/prop-types-15.8.1.tgz",
+      "integrity": "sha512-oj87CgZICdulUohogVAR7AjlC0327U4el4L6eAvOqCeudMDVU0NThNaV+b9Df4dXgSP1gXMTnPdhfe/2qDH5cg==",
+      "license": "MIT",
+      "dependencies": {
+        "loose-envify": "^1.4.0",
+        "object-assign": "^4.1.1",
+        "react-is": "^16.13.1"
+      }
+    },
     "node_modules/property-information": {
       "version": "6.5.0",
       "resolved": "https://registry.npmjs.org/property-information/-/property-information-6.5.0.tgz",
@@ -4938,6 +4990,46 @@
         "react": "^18.3.1"
       }
     },
+    "node_modules/react-dropzone": {
+      "version": "14.3.8",
+      "resolved": "https://registry.npmjs.org/react-dropzone/-/react-dropzone-14.3.8.tgz",
+      "integrity": "sha512-sBgODnq+lcA4P296DY4wacOZz3JFpD99fp+hb//iBO2HHnyeZU3FwWyXJ6salNpqQdsZrgMrotuko/BdJMV8Ug==",
+      "license": "MIT",
+      "dependencies": {
+        "attr-accept": "^2.2.4",
+        "file-selector": "^2.1.0",
+        "prop-types": "^15.8.1"
+      },
+      "engines": {
+        "node": ">= 10.13"
+      },
+      "peerDependencies": {
+        "react": ">= 16.8 || 18.0.0"
+      }
+    },
+    "node_modules/react-hot-toast": {
+      "version": "2.5.2",
+      "resolved": "https://registry.npmjs.org/react-hot-toast/-/react-hot-toast-2.5.2.tgz",
+      "integrity": "sha512-Tun3BbCxzmXXM7C+NI4qiv6lT0uwGh4oAfeJyNOjYUejTsm35mK9iCaYLGv8cBz9L5YxZLx/2ii7zsIwPtPUdw==",
+      "license": "MIT",
+      "dependencies": {
+        "csstype": "^3.1.3",
+        "goober": "^2.1.16"
+      },
+      "engines": {
+        "node": ">=10"
+      },
+      "peerDependencies": {
+        "react": ">=16",
+        "react-dom": ">=16"
+      }
+    },
+    "node_modules/react-is": {
+      "version": "16.13.1",
+      "resolved": "https://registry.npmjs.org/react-is/-/react-is-16.13.1.tgz",
+      "integrity": "sha512-24e6ynE2H+OKt4kqsOvNd8kBpV65zoxbA4BVsEOB3ARVWQki/DHzaUoC5KuON/BiccDaCCTZBuOcfZs70kR8bQ==",
+      "license": "MIT"
+    },
     "node_modules/react-markdown": {
       "version": "9.0.3",
       "resolved": "https://registry.npmjs.org/react-markdown/-/react-markdown-9.0.3.tgz",
@@ -5814,7 +5906,6 @@
       "version": "2.8.1",
       "resolved": "https://registry.npmjs.org/tslib/-/tslib-2.8.1.tgz",
       "integrity": "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w==",
-      "devOptional": true,
       "license": "0BSD"
     },
     "node_modules/turbo-stream": {

tools/server/webui/package.json

@@ -24,6 +24,8 @@
     "postcss": "^8.4.49",
     "react": "^18.3.1",
     "react-dom": "^18.3.1",
+    "react-dropzone": "^14.3.8",
+    "react-hot-toast": "^2.5.2",
     "react-markdown": "^9.0.3",
     "react-router": "^7.1.5",
     "rehype-highlight": "^7.0.2",

tools/server/webui/src/App.tsx

@@ -4,6 +4,7 @@ import Sidebar from './components/Sidebar';
 import { AppContextProvider, useAppContext } from './utils/app.context';
 import ChatScreen from './components/ChatScreen';
 import SettingDialog from './components/SettingDialog';
+import { Toaster } from 'react-hot-toast';
 
 function App() {
   return (
@@ -40,6 +41,7 @@ function AppLayout() {
           onClose={() => setShowSettings(false)}
         />
       }
+      <Toaster />
     </>
   );
 }

tools/server/webui/src/Config.ts

@@ -12,7 +12,7 @@ export const CONFIG_DEFAULT = {
   // Note: in order not to introduce breaking changes, please keep the same data type (number, string, etc) if you want to change the default value. Do not use null or undefined for default value.
   // Do not use nested objects, keep it single level. Prefix the key if you need to group them.
   apiKey: '',
-  systemMessage: 'You are a helpful assistant.',
+  systemMessage: '',
   showTokensPerSecond: false,
   showThoughtInProgress: false,
   excludeThoughtOnReq: true,

tools/server/webui/src/components/ChatInputExtraContextItem.tsx

@@ -0,0 +1,92 @@
+import { DocumentTextIcon, XMarkIcon } from '@heroicons/react/24/outline';
+import { MessageExtra } from '../utils/types';
+import { useState } from 'react';
+import { classNames } from '../utils/misc';
+
+export default function ChatInputExtraContextItem({
+  items,
+  removeItem,
+  clickToShow,
+}: {
+  items?: MessageExtra[];
+  removeItem?: (index: number) => void;
+  clickToShow?: boolean;
+}) {
+  const [show, setShow] = useState(-1);
+  const showingItem = show >= 0 ? items?.[show] : undefined;
+
+  if (!items) return null;
+
+  return (
+    <div className="flex flex-row gap-4 overflow-x-auto py-2 px-1 mb-1">
+      {items.map((item, i) => (
+        <div
+          className="indicator"
+          key={i}
+          onClick={() => clickToShow && setShow(i)}
+        >
+          {removeItem && (
+            <div className="indicator-item indicator-top">
+              <button
+                className="btn btn-neutral btn-sm w-4 h-4 p-0 rounded-full"
+                onClick={() => removeItem(i)}
+              >
+                <XMarkIcon className="h-3 w-3" />
+              </button>
+            </div>
+          )}
+
+          <div
+            className={classNames({
+              'flex flex-row rounded-md shadow-sm items-center m-0 p-0': true,
+              'cursor-pointer hover:shadow-md': !!clickToShow,
+            })}
+          >
+            {item.type === 'imageFile' ? (
+              <>
+                <img
+                  src={item.base64Url}
+                  alt={item.name}
+                  className="w-14 h-14 object-cover rounded-md"
+                />
+              </>
+            ) : (
+              <>
+                <div className="w-14 h-14 flex items-center justify-center">
+                  <DocumentTextIcon className="h-8 w-14 text-base-content/50" />
+                </div>
+
+                <div className="text-xs pr-4">
+                  <b>{item.name ?? 'Extra content'}</b>
+                </div>
+              </>
+            )}
+          </div>
+        </div>
+      ))}
+
+      {showingItem && (
+        <dialog className="modal modal-open">
+          <div className="modal-box">
+            <div className="flex justify-between items-center mb-4">
+              <b>{showingItem.name ?? 'Extra content'}</b>
+              <button className="btn btn-ghost btn-sm">
+                <XMarkIcon className="h-5 w-5" onClick={() => setShow(-1)} />
+              </button>
+            </div>
+            {showingItem.type === 'imageFile' ? (
+              <img src={showingItem.base64Url} alt={showingItem.name} />
+            ) : (
+              <div className="overflow-x-auto">
+                <pre className="whitespace-pre-wrap break-words text-sm">
+                  {showingItem.content}
+                </pre>
+              </div>
+            )}
+          </div>
+          <div className="modal-backdrop" onClick={() => setShow(-1)}></div>
+        </dialog>
+      )}
+    </div>
+  );
+}

tools/server/webui/src/components/ChatMessage.tsx

@@ -3,7 +3,14 @@ import { useAppContext } from '../utils/app.context';
 import { Message, PendingMessage } from '../utils/types';
 import { classNames } from '../utils/misc';
 import MarkdownDisplay, { CopyButton } from './MarkdownDisplay';
-import { ChevronLeftIcon, ChevronRightIcon } from '@heroicons/react/24/outline';
+import {
+  ArrowPathIcon,
+  ChevronLeftIcon,
+  ChevronRightIcon,
+  PencilSquareIcon,
+} from '@heroicons/react/24/outline';
+import ChatInputExtraContextItem from './ChatInputExtraContextItem';
+import { BtnWithTooltips } from '../utils/common';
 
 interface SplitMessage {
   content: PendingMessage['content'];
@@ -85,10 +92,14 @@ export default function ChatMessage({
           'chat-end': msg.role === 'user',
         })}
       >
+        {msg.extra && msg.extra.length > 0 && (
+          <ChatInputExtraContextItem items={msg.extra} clickToShow />
+        )}
+
         <div
           className={classNames({
             'chat-bubble markdown': true,
-            'chat-bubble-base-300': msg.role !== 'user',
+            'chat-bubble bg-transparent': msg.role !== 'user',
           })}
         >
           {/* textarea for editing message */}
@@ -133,59 +144,11 @@ export default function ChatMessage({
                   {/* render message as markdown */}
                   <div dir="auto">
                     {thought && (
-                      <details
-                        className="collapse bg-base-200 collapse-arrow mb-4"
-                        open={isThinking && config.showThoughtInProgress}
-                      >
-                        <summary className="collapse-title">
-                          {isPending && isThinking ? (
-                            <span>
-                              <span
-                                v-if="isGenerating"
-                                className="loading loading-spinner loading-md mr-2"
-                                style={{ verticalAlign: 'middle' }}
-                              ></span>
-                              <b>Thinking</b>
-                            </span>
-                          ) : (
-                            <b>Thought Process</b>
-                          )}
-                        </summary>
-                        <div className="collapse-content">
-                          <MarkdownDisplay
-                            content={thought}
-                            isGenerating={isPending}
-                          />
-                        </div>
-                      </details>
-                    )}
-
-                    {msg.extra && msg.extra.length > 0 && (
-                      <details
-                        className={classNames({
-                          'collapse collapse-arrow mb-4 bg-base-200': true,
-                          'bg-opacity-10': msg.role !== 'assistant',
-                        })}
-                      >
-                        <summary className="collapse-title">
-                          Extra content
-                        </summary>
-                        <div className="collapse-content">
-                          {msg.extra.map(
-                            (extra, i) =>
-                              extra.type === 'textFile' ? (
-                                <div key={extra.name}>
-                                  <b>{extra.name}</b>
-                                  <pre>{extra.content}</pre>
-                                </div>
-                              ) : extra.type === 'context' ? (
-                                <div key={i}>
-                                  <pre>{extra.content}</pre>
-                                </div>
-                              ) : null // TODO: support other extra types
-                          )}
-                        </div>
-                      </details>
+                      <ThoughtProcess
+                        isThinking={!!isThinking && !!isPending}
+                        content={thought}
+                        open={config.showThoughtInProgress}
+                      />
                     )}
 
                     <MarkdownDisplay
@@ -259,34 +222,36 @@ export default function ChatMessage({
           )}
           {/* user message */}
           {msg.role === 'user' && (
-            <button
-              className="badge btn-mini show-on-hover"
+            <BtnWithTooltips
+              className="btn-mini show-on-hover w-8 h-8"
               onClick={() => setEditingContent(msg.content)}
               disabled={msg.content === null}
+              tooltipsContent="Edit message"
             >
-              ✍️ Edit
-            </button>
+              <PencilSquareIcon className="h-4 w-4" />
+            </BtnWithTooltips>
           )}
           {/* assistant message */}
           {msg.role === 'assistant' && (
             <>
               {!isPending && (
-                <button
-                  className="badge btn-mini show-on-hover mr-2"
+                <BtnWithTooltips
+                  className="btn-mini show-on-hover w-8 h-8"
                   onClick={() => {
                     if (msg.content !== null) {
                       onRegenerateMessage(msg as Message);
                     }
                   }}
                   disabled={msg.content === null}
+                  tooltipsContent="Regenerate response"
                 >
-                  🔄 Regenerate
-                </button>
+                  <ArrowPathIcon className="h-4 w-4" />
+                </BtnWithTooltips>
               )}
             </>
           )}
           <CopyButton
-            className="badge btn-mini show-on-hover mr-2"
+            className="btn-mini show-on-hover w-8 h-8"
             content={msg.content}
           />
         </div>
@@ -294,3 +259,44 @@ export default function ChatMessage({
     </div>
   );
 }
+
+function ThoughtProcess({
+  isThinking,
+  content,
+  open,
+}: {
+  isThinking: boolean;
+  content: string;
+  open: boolean;
+}) {
+  return (
+    <div
+      tabIndex={0}
+      className={classNames({
+        'collapse bg-none': true,
+      })}
+    >
+      <input type="checkbox" defaultChecked={open} />
+      <div className="collapse-title px-0">
+        <div className="btn rounded-xl">
+          {isThinking ? (
+            <span>
+              <span
+                className="loading loading-spinner loading-md mr-2"
+                style={{ verticalAlign: 'middle' }}
+              ></span>
+              Thinking
+            </span>
+          ) : (
+            <>Thought Process</>
+          )}
+        </div>
+      </div>
+      <div className="collapse-content text-base-content/70 text-sm p-1">
+        <div className="border-l-2 border-base-content/20 pl-4 mb-4">
+          <MarkdownDisplay content={content} />
+        </div>
+      </div>
+    </div>
+  );
+}

tools/server/webui/src/components/ChatScreen.tsx

@@ -1,12 +1,25 @@
-import { useEffect, useMemo, useState } from 'react';
+import { useEffect, useMemo, useRef, useState } from 'react';
 import { CallbackGeneratedChunk, useAppContext } from '../utils/app.context';
 import ChatMessage from './ChatMessage';
 import { CanvasType, Message, PendingMessage } from '../utils/types';
-import { classNames, cleanCurrentUrl, throttle } from '../utils/misc';
+import { classNames, cleanCurrentUrl } from '../utils/misc';
 import CanvasPyInterpreter from './CanvasPyInterpreter';
 import StorageUtils from '../utils/storage';
 import { useVSCodeContext } from '../utils/llama-vscode';
 import { useChatTextarea, ChatTextareaApi } from './useChatTextarea.ts';
+import {
+  ArrowUpIcon,
+  StopIcon,
+  PaperClipIcon,
+} from '@heroicons/react/24/solid';
+import {
+  ChatExtraContextApi,
+  useChatExtraContext,
+} from './useChatExtraContext.tsx';
+import Dropzone from 'react-dropzone';
+import toast from 'react-hot-toast';
+import ChatInputExtraContextItem from './ChatInputExtraContextItem.tsx';
+import { scrollToBottom, useChatScroll } from './useChatScroll.tsx';
 
 /**
  * A message display is a message node with additional information for rendering.
@@ -72,24 +85,6 @@ function getListMessageDisplay(
   return res;
 }
 
-const scrollToBottom = throttle(
-  (requiresNearBottom: boolean, delay: number = 80) => {
-    const mainScrollElem = document.getElementById('main-scroll');
-    if (!mainScrollElem) return;
-    const spaceToBottom =
-      mainScrollElem.scrollHeight -
-      mainScrollElem.scrollTop -
-      mainScrollElem.clientHeight;
-    if (!requiresNearBottom || spaceToBottom < 50) {
-      setTimeout(
-        () => mainScrollElem.scrollTo({ top: mainScrollElem.scrollHeight }),
-        delay
-      );
-    }
-  },
-  80
-);
-
 export default function ChatScreen() {
   const {
     viewingChat,
@@ -102,10 +97,11 @@ export default function ChatScreen() {
   } = useAppContext();
 
   const textarea: ChatTextareaApi = useChatTextarea(prefilledMsg.content());
+  const extraContext = useChatExtraContext();
+  useVSCodeContext(textarea, extraContext);
 
-  const { extraContext, clearExtraContext } = useVSCodeContext(textarea);
-  // TODO: improve this when we have "upload file" feature
-  const currExtra: Message['extra'] = extraContext ? [extraContext] : undefined;
+  const msgListRef = useRef<HTMLDivElement>(null);
+  useChatScroll(msgListRef);
 
   // keep track of leaf node for rendering
   const [currNodeId, setCurrNodeId] = useState<number>(-1);
@@ -129,13 +125,15 @@ export default function ChatScreen() {
     if (currLeafNodeId) {
       setCurrNodeId(currLeafNodeId);
     }
-    scrollToBottom(true);
+    // useChatScroll will handle the auto scroll
   };
 
   const sendNewMessage = async () => {
     const lastInpMsg = textarea.value();
-    if (lastInpMsg.trim().length === 0 || isGenerating(currConvId ?? ''))
+    if (lastInpMsg.trim().length === 0 || isGenerating(currConvId ?? '')) {
+      toast.error('Please enter a message');
       return;
+    }
     textarea.setValue('');
     scrollToBottom(false);
     setCurrNodeId(-1);
@@ -146,7 +144,7 @@ export default function ChatScreen() {
         currConvId,
         lastMsgNodeId,
         lastInpMsg,
-        currExtra,
+        extraContext.items,
         onChunk
       ))
     ) {
@@ -154,7 +152,7 @@ export default function ChatScreen() {
       textarea.setValue(lastInpMsg);
     }
     // OK
-    clearExtraContext();
+    extraContext.clearItems();
   };
 
   // for vscode context
@@ -234,10 +232,17 @@ export default function ChatScreen() {
         })}
       >
         {/* chat messages */}
-        <div id="messages-list" className="grow">
-          <div className="mt-auto flex justify-center">
+        <div id="messages-list" className="grow" ref={msgListRef}>
+          <div className="mt-auto flex flex-col items-center">
             {/* placeholder to shift the message to the bottom */}
-            {viewingChat ? '' : 'Send a message to start'}
+            {viewingChat ? (
+              ''
+            ) : (
+              <>
+                <div className="mb-4">Send a message to start</div>
+                <ServerInfo />
+              </>
+            )}
           </div>
           {[...messages, ...pendingMsgDisplay].map((msg) => (
             <ChatMessage
@@ -248,46 +253,19 @@ export default function ChatScreen() {
               onRegenerateMessage={handleRegenerateMessage}
               onEditMessage={handleEditMessage}
               onChangeSibling={setCurrNodeId}
+              isPending={msg.isPending}
             />
           ))}
         </div>
 
         {/* chat input */}
-        <div className="flex flex-row items-end pt-8 pb-6 sticky bottom-0 bg-base-100">
-          <textarea
-            // Default (mobile): Enable vertical resize, overflow auto for scrolling if needed
-            // Large screens (lg:): Disable manual resize, apply max-height for autosize limit
-            className="textarea textarea-bordered w-full resize-vertical lg:resize-none lg:max-h-48 lg:overflow-y-auto" // Adjust lg:max-h-48 as needed (e.g., lg:max-h-60)
-            placeholder="Type a message (Shift+Enter to add a new line)"
-            ref={textarea.ref}
-            onInput={textarea.onInput} // Hook's input handler (will only resize height on lg+ screens)
-            onKeyDown={(e) => {
-              if (e.nativeEvent.isComposing || e.keyCode === 229) return;
-              if (e.key === 'Enter' && !e.shiftKey) {
-                e.preventDefault();
-                sendNewMessage();
-              }
-            }}
-            id="msg-input"
-            dir="auto"
-            // Set a base height of 2 rows for mobile views
-            // On lg+ screens, the hook will calculate and set the initial height anyway
-            rows={2}
-          ></textarea>
-
-          {isGenerating(currConvId ?? '') ? (
-            <button
-              className="btn btn-neutral ml-2"
-              onClick={() => stopGenerating(currConvId ?? '')}
-            >
-              Stop
-            </button>
-          ) : (
-            <button className="btn btn-primary ml-2" onClick={sendNewMessage}>
-              Send
-            </button>
-          )}
-        </div>
+        <ChatInput
+          textarea={textarea}
+          extraContext={extraContext}
+          onSend={sendNewMessage}
+          onStop={() => stopGenerating(currConvId ?? '')}
+          isGenerating={isGenerating(currConvId ?? '')}
+        />
       </div>
       <div className="w-full sticky top-[7em] h-[calc(100vh-9em)]">
         {canvasData?.type === CanvasType.PY_INTERPRETER && (
@@ -297,3 +275,129 @@ export default function ChatScreen() {
     </div>
   );
 }
+
+function ServerInfo() {
+  const { serverProps } = useAppContext();
+  return (
+    <div className="card card-sm shadow-sm border-1 border-base-content/20 text-base-content/70 mb-6">
+      <div className="card-body">
+        <b>Server Info</b>
+        <p>
+          <b>Model</b>: {serverProps?.model_path?.split(/(\\|\/)/).pop()}
+          <br />
+          <b>Build</b>: {serverProps?.build_info}
+          <br />
+        </p>
+      </div>
+    </div>
+  );
+}
+
+function ChatInput({
+  textarea,
+  extraContext,
+  onSend,
+  onStop,
+  isGenerating,
+}: {
+  textarea: ChatTextareaApi;
+  extraContext: ChatExtraContextApi;
+  onSend: () => void;
+  onStop: () => void;
+  isGenerating: boolean;
+}) {
+  const [isDrag, setIsDrag] = useState(false);
+
+  return (
+    <div
+      className={classNames({
+        'flex items-end pt-8 pb-6 sticky bottom-0 bg-base-100': true,
+        'opacity-50': isDrag, // simply visual feedback to inform user that the file will be accepted
+      })}
+    >
+      <Dropzone
+        noClick
+        onDrop={(files: File[]) => {
+          setIsDrag(false);
+          extraContext.onFileAdded(files);
+        }}
+        onDragEnter={() => setIsDrag(true)}
+        onDragLeave={() => setIsDrag(false)}
+        multiple={true}
+      >
+        {({ getRootProps, getInputProps }) => (
+          <div
+            className="flex flex-col rounded-xl border-1 border-base-content/30 p-3 w-full"
+            {...getRootProps()}
+          >
+            {!isGenerating && (
+              <ChatInputExtraContextItem
+                items={extraContext.items}
+                removeItem={extraContext.removeItem}
+              />
+            )}
+
+            <div className="flex flex-row w-full">
+              <textarea
+                // Default (mobile): Enable vertical resize, overflow auto for scrolling if needed
+                // Large screens (lg:): Disable manual resize, apply max-height for autosize limit
+                className="text-md outline-none border-none w-full resize-vertical lg:resize-none lg:max-h-48 lg:overflow-y-auto" // Adjust lg:max-h-48 as needed (e.g., lg:max-h-60)
+                placeholder="Type a message (Shift+Enter to add a new line)"
+                ref={textarea.ref}
+                onInput={textarea.onInput} // Hook's input handler (will only resize height on lg+ screens)
+                onKeyDown={(e) => {
+                  if (e.nativeEvent.isComposing || e.keyCode === 229) return;
+                  if (e.key === 'Enter' && !e.shiftKey) {
+                    e.preventDefault();
+                    onSend();
+                  }
+                }}
+                id="msg-input"
+                dir="auto"
+                // Set a base height of 2 rows for mobile views
+                // On lg+ screens, the hook will calculate and set the initial height anyway
+                rows={2}
+              ></textarea>
+
+              {/* buttons area */}
+              <div className="flex flex-row gap-2 ml-2">
+                <label
+                  htmlFor="file-upload"
+                  className={classNames({
+                    'btn w-8 h-8 p-0 rounded-full': true,
+                    'btn-disabled': isGenerating,
+                  })}
+                >
+                  <PaperClipIcon className="h-5 w-5" />
+                </label>
+                <input
+                  id="file-upload"
+                  type="file"
+                  className="hidden"
+                  disabled={isGenerating}
+                  {...getInputProps()}
+                  hidden
+                />
+                {isGenerating ? (
+                  <button
+                    className="btn btn-neutral w-8 h-8 p-0 rounded-full"
+                    onClick={onStop}
+                  >
+                    <StopIcon className="h-5 w-5" />
+                  </button>
+                ) : (
+                  <button
+                    className="btn btn-primary w-8 h-8 p-0 rounded-full"
+                    onClick={onSend}
+                  >
+                    <ArrowUpIcon className="h-5 w-5" />
+                  </button>
+                )}
+              </div>
+            </div>
+          </div>
+        )}
+      </Dropzone>
+    </div>
+  );
+}

tools/server/webui/src/components/Header.tsx

@@ -4,10 +4,13 @@ import { useAppContext } from '../utils/app.context';
 import { classNames } from '../utils/misc';
 import daisyuiThemes from 'daisyui/theme/object';
 import { THEMES } from '../Config';
-import { useNavigate } from 'react-router';
+import {
+  Cog8ToothIcon,
+  MoonIcon,
+  Bars3Icon,
+} from '@heroicons/react/24/outline';
 
 export default function Header() {
-  const navigate = useNavigate();
   const [selectedTheme, setSelectedTheme] = useState(StorageUtils.getTheme());
   const { setShowSettings } = useAppContext();
 
@@ -24,105 +27,21 @@ export default function Header() {
     );
   }, [selectedTheme]);
 
-  const { isGenerating, viewingChat } = useAppContext();
-  const isCurrConvGenerating = isGenerating(viewingChat?.conv.id ?? '');
-
-  const removeConversation = () => {
-    if (isCurrConvGenerating || !viewingChat) return;
-    const convId = viewingChat?.conv.id;
-    if (window.confirm('Are you sure to delete this conversation?')) {
-      StorageUtils.remove(convId);
-      navigate('/');
-    }
-  };
-
-  const downloadConversation = () => {
-    if (isCurrConvGenerating || !viewingChat) return;
-    const convId = viewingChat?.conv.id;
-    const conversationJson = JSON.stringify(viewingChat, null, 2);
-    const blob = new Blob([conversationJson], { type: 'application/json' });
-    const url = URL.createObjectURL(blob);
-    const a = document.createElement('a');
-    a.href = url;
-    a.download = `conversation_${convId}.json`;
-    document.body.appendChild(a);
-    a.click();
-    document.body.removeChild(a);
-    URL.revokeObjectURL(url);
-  };
-
   return (
     <div className="flex flex-row items-center pt-6 pb-6 sticky top-0 z-10 bg-base-100">
       {/* open sidebar button */}
       <label htmlFor="toggle-drawer" className="btn btn-ghost lg:hidden">
-        <svg
-          xmlns="http://www.w3.org/2000/svg"
-          width="16"
-          height="16"
-          fill="currentColor"
-          className="bi bi-list"
-          viewBox="0 0 16 16"
-        >
-          <path
-            fillRule="evenodd"
-            d="M2.5 12a.5.5 0 0 1 .5-.5h10a.5.5 0 0 1 0 1H3a.5.5 0 0 1-.5-.5m0-4a.5.5 0 0 1 .5-.5h10a.5.5 0 0 1 0 1H3a.5.5 0 0 1-.5-.5m0-4a.5.5 0 0 1 .5-.5h10a.5.5 0 0 1 0 1H3a.5.5 0 0 1-.5-.5"
-          />
-        </svg>
+        <Bars3Icon className="h-5 w-5" />
       </label>
 
       <div className="grow text-2xl font-bold ml-2">llama.cpp</div>
 
       {/* action buttons (top right) */}
       <div className="flex items-center">
-        {viewingChat && (
-          <div className="dropdown dropdown-end">
-            {/* "..." button */}
-            <button
-              tabIndex={0}
-              role="button"
-              className="btn m-1"
-              disabled={isCurrConvGenerating}
-            >
-              <svg
-                xmlns="http://www.w3.org/2000/svg"
-                width="16"
-                height="16"
-                fill="currentColor"
-                className="bi bi-three-dots-vertical"
-                viewBox="0 0 16 16"
-              >
-                <path d="M9.5 13a1.5 1.5 0 1 1-3 0 1.5 1.5 0 0 1 3 0m0-5a1.5 1.5 0 1 1-3 0 1.5 1.5 0 0 1 3 0m0-5a1.5 1.5 0 1 1-3 0 1.5 1.5 0 0 1 3 0" />
-              </svg>
-            </button>
-            {/* dropdown menu */}
-            <ul
-              tabIndex={0}
-              className="dropdown-content menu bg-base-100 rounded-box z-[1] w-52 p-2 shadow"
-            >
-              <li onClick={downloadConversation}>
-                <a>Download</a>
-              </li>
-              <li className="text-error" onClick={removeConversation}>
-                <a>Delete</a>
-              </li>
-            </ul>
-          </div>
-        )}
-
         <div className="tooltip tooltip-bottom" data-tip="Settings">
           <button className="btn" onClick={() => setShowSettings(true)}>
             {/* settings button */}
-            <svg
-              xmlns="http://www.w3.org/2000/svg"
-              width="16"
-              height="16"
-              fill="currentColor"
-              className="bi bi-gear"
-              viewBox="0 0 16 16"
-            >
-              <path d="M8 4.754a3.246 3.246 0 1 0 0 6.492 3.246 3.246 0 0 0 0-6.492M5.754 8a2.246 2.246 0 1 1 4.492 0 2.246 2.246 0 0 1-4.492 0" />
-              <path d="M9.796 1.343c-.527-1.79-3.065-1.79-3.592 0l-.094.319a.873.873 0 0 1-1.255.52l-.292-.16c-1.64-.892-3.433.902-2.54 2.541l.159.292a.873.873 0 0 1-.52 1.255l-.319.094c-1.79.527-1.79 3.065 0 3.592l.319.094a.873.873 0 0 1 .52 1.255l-.16.292c-.892 1.64.901 3.434 2.541 2.54l.292-.159a.873.873 0 0 1 1.255.52l.094.319c.527 1.79 3.065 1.79 3.592 0l.094-.319a.873.873 0 0 1 1.255-.52l.292.16c1.64.893 3.434-.902 2.54-2.541l-.159-.292a.873.873 0 0 1 .52-1.255l.319-.094c1.79-.527 1.79-3.065 0-3.592l-.319-.094a.873.873 0 0 1-.52-1.255l.16-.292c.893-1.64-.902-3.433-2.541-2.54l-.292.159a.873.873 0 0 1-1.255-.52zm-2.633.283c.246-.835 1.428-.835 1.674 0l.094.319a1.873 1.873 0 0 0 2.693 1.115l.291-.16c.764-.415 1.6.42 1.184 1.185l-.159.292a1.873 1.873 0 0 0 1.116 2.692l.318.094c.835.246.835 1.428 0 1.674l-.319.094a1.873 1.873 0 0 0-1.115 2.693l.16.291c.415.764-.42 1.6-1.185 1.184l-.291-.159a1.873 1.873 0 0 0-2.693 1.116l-.094.318c-.246.835-1.428.835-1.674 0l-.094-.319a1.873 1.873 0 0 0-2.692-1.115l-.292.16c-.764.415-1.6-.42-1.184-1.185l.159-.291A1.873 1.873 0 0 0 1.945 8.93l-.319-.094c-.835-.246-.835-1.428 0-1.674l.319-.094A1.873 1.873 0 0 0 3.06 4.377l-.16-.292c-.415-.764.42-1.6 1.185-1.184l.292.159a1.873 1.873 0 0 0 2.692-1.115z" />
-            </svg>
+            <Cog8ToothIcon className="w-5 h-5" />
           </button>
         </div>
 
@@ -130,16 +49,7 @@ export default function Header() {
         <div className="tooltip tooltip-bottom" data-tip="Themes">
           <div className="dropdown dropdown-end dropdown-bottom">
             <div tabIndex={0} role="button" className="btn m-1">
-              <svg
-                xmlns="http://www.w3.org/2000/svg"
-                width="16"
-                height="16"
-                fill="currentColor"
-                className="bi bi-palette2"
-                viewBox="0 0 16 16"
-              >
-                <path d="M0 .5A.5.5 0 0 1 .5 0h5a.5.5 0 0 1 .5.5v5.277l4.147-4.131a.5.5 0 0 1 .707 0l3.535 3.536a.5.5 0 0 1 0 .708L10.261 10H15.5a.5.5 0 0 1 .5.5v5a.5.5 0 0 1-.5.5H3a3 3 0 0 1-2.121-.879A3 3 0 0 1 0 13.044m6-.21 7.328-7.3-2.829-2.828L6 7.188zM4.5 13a1.5 1.5 0 1 0-3 0 1.5 1.5 0 0 0 3 0M15 15v-4H9.258l-4.015 4zM0 .5v12.495zm0 12.495V13z" />
-              </svg>
+              <MoonIcon className="w-5 h-5" />
             </div>
             <ul
               tabIndex={0}

tools/server/webui/src/components/MarkdownDisplay.tsx

@@ -11,6 +11,8 @@ import { ElementContent, Root } from 'hast';
 import { visit } from 'unist-util-visit';
 import { useAppContext } from '../utils/app.context';
 import { CanvasType } from '../utils/types';
+import { BtnWithTooltips } from '../utils/common';
+import { DocumentDuplicateIcon, PlayIcon } from '@heroicons/react/24/outline';
 
 export default function MarkdownDisplay({
   content,
@@ -81,10 +83,13 @@ const CodeBlockButtons: React.ElementType<
         'display-none': !node?.position,
       })}
     >
-      <CopyButton className="badge btn-mini" content={copiedContent} />
+      <CopyButton
+        className="badge btn-mini btn-soft shadow-sm"
+        content={copiedContent}
+      />
       {canRunCode && (
         <RunPyCodeButton
-          className="badge btn-mini ml-2"
+          className="badge btn-mini shadow-sm ml-2"
           content={copiedContent}
         />
       )}
@@ -101,16 +106,17 @@ export const CopyButton = ({
 }) => {
   const [copied, setCopied] = useState(false);
   return (
-    <button
+    <BtnWithTooltips
       className={className}
       onClick={() => {
         copyStr(content);
         setCopied(true);
       }}
       onMouseLeave={() => setCopied(false)}
+      tooltipsContent={copied ? 'Copied!' : 'Copy'}
     >
-      {copied ? 'Copied!' : '📋 Copy'}
-    </button>
+      <DocumentDuplicateIcon className="h-4 w-4" />
+    </BtnWithTooltips>
   );
 };
 
@@ -124,7 +130,7 @@ export const RunPyCodeButton = ({
   const { setCanvasData } = useAppContext();
   return (
     <>
-      <button
+      <BtnWithTooltips
         className={className}
         onClick={() =>
           setCanvasData({
@@ -132,9 +138,10 @@ export const RunPyCodeButton = ({
             content,
           })
         }
+        tooltipsContent="Run code"
       >
-        ▶️ Run
-      </button>
+        <PlayIcon className="h-4 w-4" />
+      </BtnWithTooltips>
     </>
   );
 };

tools/server/webui/src/components/Sidebar.tsx

@@ -1,13 +1,26 @@
-import { useEffect, useState } from 'react';
+import { useEffect, useMemo, useState } from 'react';
 import { classNames } from '../utils/misc';
 import { Conversation } from '../utils/types';
 import StorageUtils from '../utils/storage';
 import { useNavigate, useParams } from 'react-router';
+import {
+  ArrowDownTrayIcon,
+  EllipsisVerticalIcon,
+  PencilIcon,
+  PencilSquareIcon,
+  TrashIcon,
+  XMarkIcon,
+} from '@heroicons/react/24/outline';
+import { BtnWithTooltips } from '../utils/common';
+import { useAppContext } from '../utils/app.context';
+import toast from 'react-hot-toast';
 
 export default function Sidebar() {
   const params = useParams();
   const navigate = useNavigate();
 
+  const { isGenerating } = useAppContext();
+
   const [conversations, setConversations] = useState<Conversation[]>([]);
   const [currConv, setCurrConv] = useState<Conversation | null>(null);
 
@@ -26,6 +39,11 @@ export default function Sidebar() {
     };
   }, []);
 
+  const groupedConv = useMemo(
+    () => groupConversationsByDate(conversations),
+    [conversations]
+  );
+
   return (
     <>
       <input
@@ -47,46 +65,100 @@ export default function Sidebar() {
 
             {/* close sidebar button */}
             <label htmlFor="toggle-drawer" className="btn btn-ghost lg:hidden">
-              <svg
-                xmlns="http://www.w3.org/2000/svg"
-                width="16"
-                height="16"
-                fill="currentColor"
-                className="bi bi-arrow-bar-left"
-                viewBox="0 0 16 16"
-              >
-                <path
-                  fillRule="evenodd"
-                  d="M12.5 15a.5.5 0 0 1-.5-.5v-13a.5.5 0 0 1 1 0v13a.5.5 0 0 1-.5.5M10 8a.5.5 0 0 1-.5.5H3.707l2.147 2.146a.5.5 0 0 1-.708.708l-3-3a.5.5 0 0 1 0-.708l3-3a.5.5 0 1 1 .708.708L3.707 7.5H9.5a.5.5 0 0 1 .5.5"
-                />
-              </svg>
+              <XMarkIcon className="w-5 h-5" />
             </label>
           </div>
 
-          {/* list of conversations */}
+          {/* new conversation button */}
           <div
             className={classNames({
-              'btn btn-ghost justify-start': true,
-              'btn-active': !currConv,
+              'btn btn-ghost justify-start px-2': true,
+              'btn-soft': !currConv,
             })}
             onClick={() => navigate('/')}
           >
-            + New conversation
+            <PencilSquareIcon className="w-5 h-5" />
+            New conversation
           </div>
-          {conversations.map((conv) => (
-            <div
-              key={conv.id}
-              className={classNames({
-                'btn btn-ghost justify-start font-normal': true,
-                'btn-active': conv.id === currConv?.id,
-              })}
-              onClick={() => navigate(`/chat/${conv.id}`)}
-              dir="auto"
-            >
-              <span className="truncate">{conv.name}</span>
+
+          {/* list of conversations */}
+          {groupedConv.map((group, i) => (
+            <div key={i}>
+              {/* group name (by date) */}
+              {group.title ? (
+                // we use btn class here to make sure that the padding/margin are aligned with the other items
+                <b className="btn btn-ghost btn-xs bg-none btn-disabled block text-xs text-base-content text-start px-2 mb-0 mt-6 font-bold">
+                  {group.title}
+                </b>
+              ) : (
+                <div className="h-2" />
+              )}
+
+              {group.conversations.map((conv) => (
+                <ConversationItem
+                  key={conv.id}
+                  conv={conv}
+                  isCurrConv={currConv?.id === conv.id}
+                  onSelect={() => {
+                    navigate(`/chat/${conv.id}`);
+                  }}
+                  onDelete={() => {
+                    if (isGenerating(conv.id)) {
+                      toast.error(
+                        'Cannot delete conversation while generating'
+                      );
+                      return;
+                    }
+                    if (
+                      window.confirm(
+                        'Are you sure to delete this conversation?'
+                      )
+                    ) {
+                      toast.success('Conversation deleted');
+                      StorageUtils.remove(conv.id);
+                      navigate('/');
+                    }
+                  }}
+                  onDownload={() => {
+                    if (isGenerating(conv.id)) {
+                      toast.error(
+                        'Cannot download conversation while generating'
+                      );
+                      return;
+                    }
+                    const conversationJson = JSON.stringify(conv, null, 2);
+                    const blob = new Blob([conversationJson], {
+                      type: 'application/json',
+                    });
+                    const url = URL.createObjectURL(blob);
+                    const a = document.createElement('a');
+                    a.href = url;
+                    a.download = `conversation_${conv.id}.json`;
+                    document.body.appendChild(a);
+                    a.click();
+                    document.body.removeChild(a);
+                    URL.revokeObjectURL(url);
+                  }}
+                  onRename={() => {
+                    if (isGenerating(conv.id)) {
+                      toast.error(
+                        'Cannot rename conversation while generating'
+                      );
+                      return;
+                    }
+                    const newName = window.prompt(
+                      'Enter new name for the conversation',
+                      conv.name
+                    );
+                    if (newName && newName.trim().length > 0) {
+                      StorageUtils.updateConversationName(conv.id, newName);
+                    }
+                  }}
+                />
+              ))}
             </div>
           ))}
-          <div className="text-center text-xs opacity-40 mt-auto mx-4">
+          <div className="text-center text-xs opacity-40 mt-auto mx-4 pt-8">
             Conversations are saved to browser's IndexedDB
           </div>
         </div>
@@ -94,3 +166,170 @@ export default function Sidebar() {
     </>
   );
 }
+
+function ConversationItem({
+  conv,
+  isCurrConv,
+  onSelect,
+  onDelete,
+  onDownload,
+  onRename,
+}: {
+  conv: Conversation;
+  isCurrConv: boolean;
+  onSelect: () => void;
+  onDelete: () => void;
+  onDownload: () => void;
+  onRename: () => void;
+}) {
+  return (
+    <div
+      className={classNames({
+        'group flex flex-row btn btn-ghost justify-start items-center font-normal px-2 h-9':
+          true,
+        'btn-soft': isCurrConv,
+      })}
+    >
+      <div
+        key={conv.id}
+        className="w-full overflow-hidden truncate text-start"
+        onClick={onSelect}
+        dir="auto"
+      >
+        {conv.name}
+      </div>
+      <div className="dropdown dropdown-end h-5">
+        <BtnWithTooltips
+          // on mobile, we always show the ellipsis icon
+          // on desktop, we only show it when the user hovers over the conversation item
+          // we use opacity instead of hidden to avoid layout shift
+          className="cursor-pointer opacity-100 md:opacity-0 group-hover:opacity-100"
+          onClick={() => {}}
+          tooltipsContent="More"
+        >
+          <EllipsisVerticalIcon className="w-5 h-5" />
+        </BtnWithTooltips>
+        {/* dropdown menu */}
+        <ul
+          tabIndex={0}
+          className="dropdown-content menu bg-base-100 rounded-box z-[1] p-2 shadow"
+        >
+          <li onClick={onRename}>
+            <a>
+              <PencilIcon className="w-4 h-4" />
+              Rename
+            </a>
+          </li>
+          <li onClick={onDownload}>
+            <a>
+              <ArrowDownTrayIcon className="w-4 h-4" />
+              Download
+            </a>
+          </li>
+          <li className="text-error" onClick={onDelete}>
+            <a>
+              <TrashIcon className="w-4 h-4" />
+              Delete
+            </a>
+          </li>
+        </ul>
+      </div>
+    </div>
+  );
+}
+
+// WARN: vibe code below
+
+export interface GroupedConversations {
+  title?: string;
+  conversations: Conversation[];
+}
+
+// TODO @ngxson : add test for this function
+// Group conversations by date
+// - "Previous 7 Days"
+// - "Previous 30 Days"
+// - "Month Year" (e.g., "April 2023")
+export function groupConversationsByDate(
+  conversations: Conversation[]
+): GroupedConversations[] {
+  const now = new Date();
+  const today = new Date(now.getFullYear(), now.getMonth(), now.getDate()); // Start of today
+
+  const sevenDaysAgo = new Date(today);
+  sevenDaysAgo.setDate(today.getDate() - 7);
+
+  const thirtyDaysAgo = new Date(today);
+  thirtyDaysAgo.setDate(today.getDate() - 30);
+
+  const groups: { [key: string]: Conversation[] } = {
+    Today: [],
+    'Previous 7 Days': [],
+    'Previous 30 Days': [],
+  };
+  const monthlyGroups: { [key: string]: Conversation[] } = {}; // Key format: "Month Year" e.g., "April 2023"
+
+  // Sort conversations by lastModified date in descending order (newest first)
+  // This helps when adding to groups, but the final output order of groups is fixed.
+  const sortedConversations = [...conversations].sort(
+    (a, b) => b.lastModified - a.lastModified
+  );
+
+  for (const conv of sortedConversations) {
+    const convDate = new Date(conv.lastModified);
+
+    if (convDate >= today) {
+      groups['Today'].push(conv);
+    } else if (convDate >= sevenDaysAgo) {
+      groups['Previous 7 Days'].push(conv);
+    } else if (convDate >= thirtyDaysAgo) {
+      groups['Previous 30 Days'].push(conv);
+    } else {
+      const monthName = convDate.toLocaleString('default', { month: 'long' });
+      const year = convDate.getFullYear();
+      const monthYearKey = `${monthName} ${year}`;
+      if (!monthlyGroups[monthYearKey]) {
+        monthlyGroups[monthYearKey] = [];
+      }
+      monthlyGroups[monthYearKey].push(conv);
+    }
+  }
+
+  const result: GroupedConversations[] = [];
+
+  if (groups['Today'].length > 0) {
+    result.push({
+      title: undefined, // no title for Today
+      conversations: groups['Today'],
+    });
+  }
+
+  if (groups['Previous 7 Days'].length > 0) {
+    result.push({
+      title: 'Previous 7 Days',
+      conversations: groups['Previous 7 Days'],
+    });
+  }
+
+  if (groups['Previous 30 Days'].length > 0) {
+    result.push({
+      title: 'Previous 30 Days',
+      conversations: groups['Previous 30 Days'],
+    });
+  }
+
+  // Sort monthly groups by date (most recent month first)
+  const sortedMonthKeys = Object.keys(monthlyGroups).sort((a, b) => {
+    const dateA = new Date(a); // "Month Year" can be parsed by Date constructor
+    const dateB = new Date(b);
+    return dateB.getTime() - dateA.getTime();
+  });
+
+  for (const monthKey of sortedMonthKeys) {
+    if (monthlyGroups[monthKey].length > 0) {
+      result.push({ title: monthKey, conversations: monthlyGroups[monthKey] });
+    }
+  }
+
+  return result;
+}

tools/server/webui/src/components/useChatExtraContext.tsx

@@ -0,0 +1,174 @@
+import { useState } from 'react';
+import { MessageExtra } from '../utils/types';
+import toast from 'react-hot-toast';
+import { useAppContext } from '../utils/app.context';
+
+// Interface describing the API returned by the hook
+export interface ChatExtraContextApi {
+  items?: MessageExtra[]; // undefined if empty, similar to Message['extra']
+  addItems: (items: MessageExtra[]) => void;
+  removeItem: (idx: number) => void;
+  clearItems: () => void;
+  onFileAdded: (files: File[]) => void; // used by "upload" button
+}
+
+export function useChatExtraContext(): ChatExtraContextApi {
+  const { serverProps } = useAppContext();
+  const [items, setItems] = useState<MessageExtra[]>([]);
+
+  const addItems = (newItems: MessageExtra[]) => {
+    setItems((prev) => [...prev, ...newItems]);
+  };
+
+  const removeItem = (idx: number) => {
+    setItems((prev) => prev.filter((_, i) => i !== idx));
+  };
+
+  const clearItems = () => {
+    setItems([]);
+  };
+
+  const onFileAdded = (files: File[]) => {
+    for (const file of files) {
+      const mimeType = file.type;
+      console.debug({ mimeType, file });
+      if (file.size > 10 * 1024 * 1024) {
+        toast.error('File is too large. Maximum size is 10MB.');
+        break;
+      }
+
+      if (mimeType.startsWith('image/') && mimeType !== 'image/svg+xml') {
+        if (!serverProps?.has_multimodal) {
+          toast.error('Multimodal is not supported by this server or model.');
+          break;
+        }
+        const reader = new FileReader();
+        reader.onload = (event) => {
+          if (event.target?.result) {
+            addItems([
+              {
+                type: 'imageFile',
+                name: file.name,
+                base64Url: event.target.result as string,
+              },
+            ]);
+          }
+        };
+        reader.readAsDataURL(file);
+      } else if (
+        mimeType.startsWith('video/') ||
+        mimeType.startsWith('audio/')
+      ) {
+        toast.error('Video and audio files are not supported yet.');
+        break;
+      } else if (mimeType.startsWith('application/pdf')) {
+        toast.error('PDF files are not supported yet.');
+        break;
+      } else {
+        // Because there can be many text file types (like code file), we will not check the mime type
+        // and will just check if the file is not binary.
+        const reader = new FileReader();
+        reader.onload = (event) => {
+          if (event.target?.result) {
+            const content = event.target.result as string;
+            if (!isLikelyNotBinary(content)) {
+              toast.error('File is binary. Please upload a text file.');
+              return;
+            }
+            addItems([
+              {
+                type: 'textFile',
+                name: file.name,
+                content,
+              },
+            ]);
+          }
+        };
+        reader.readAsText(file);
+      }
+    }
+  };
+
+  return {
+    items: items.length > 0 ? items : undefined,
+    addItems,
+    removeItem,
+    clearItems,
+    onFileAdded,
+  };
+}
+
+// WARN: vibe code below
+// This code is a heuristic to determine if a string is likely not binary.
+// It is necessary because input file can have various mime types which we don't have time to investigate.
+// For example, a python file can be text/plain, application/x-python, etc.
+export function isLikelyNotBinary(str: string): boolean {
+  const options = {
+    prefixLength: 1024 * 10, // Check the first 10KB of the string
+    suspiciousCharThresholdRatio: 0.15, // Allow up to 15% suspicious chars
+    maxAbsoluteNullBytes: 2,
+  };
+
+  if (!str) {
+    return true; // Empty string is considered "not binary" or trivially text.
+  }
+
+  const sampleLength = Math.min(str.length, options.prefixLength);
+  if (sampleLength === 0) {
+    return true; // Effectively an empty string after considering prefixLength.
+  }
+
+  let suspiciousCharCount = 0;
+  let nullByteCount = 0;
+
+  for (let i = 0; i < sampleLength; i++) {
+    const charCode = str.charCodeAt(i);
+
+    // 1. Check for Unicode Replacement Character (U+FFFD)
+    // This is a strong indicator if the string was created from decoding bytes as UTF-8.
+    if (charCode === 0xfffd) {
+      suspiciousCharCount++;
+      continue;
+    }
+
+    // 2. Check for Null Bytes (U+0000)
+    if (charCode === 0x0000) {
+      nullByteCount++;
+      // We also count nulls towards the general suspicious character count,
+      // as they are less common in typical text files.
+      suspiciousCharCount++;
+      continue;
+    }
+
+    // 3. Check for C0 Control Characters (U+0001 to U+001F)
+    // Exclude common text control characters: TAB (9), LF (10), CR (13).
+    // We can also be a bit lenient with BEL (7) and BS (8) which sometimes appear in logs.
+    if (charCode < 32) {
+      if (
+        charCode !== 9 && // TAB
+        charCode !== 10 && // LF
+        charCode !== 13 && // CR
+        charCode !== 7 && // BEL (Bell) - sometimes in logs
+        charCode !== 8 // BS (Backspace) - less common, but possible
+      ) {
+        suspiciousCharCount++;
+      }
+    }
+    // Characters from 32 (space) up to 126 (~) are printable ASCII.
+    // Characters 127 (DEL) is a control character.
+    // Characters >= 128 are extended ASCII / multi-byte Unicode.
+    // If they resulted in U+FFFD, we caught it. Otherwise, they are valid
+    // (though perhaps unusual) Unicode characters from JS's perspective.
+    // The main concern is if those higher characters came from misinterpreting
+    // a single-byte encoding as UTF-8, which again, U+FFFD would usually flag.
+  }
+
+  // Check absolute null byte count
+  if (nullByteCount > options.maxAbsoluteNullBytes) {
+    return false; // Too many null bytes is a strong binary indicator
+  }
+
+  // Check ratio of suspicious characters
+  const ratio = suspiciousCharCount / sampleLength;
+  return ratio <= options.suspiciousCharThresholdRatio;
+}

tools/server/webui/src/components/useChatScroll.tsx

@@ -0,0 +1,34 @@
+import React, { useEffect } from 'react';
+import { throttle } from '../utils/misc';
+
+export const scrollToBottom = (requiresNearBottom: boolean, delay?: number) => {
+  const mainScrollElem = document.getElementById('main-scroll');
+  if (!mainScrollElem) return;
+  const spaceToBottom =
+    mainScrollElem.scrollHeight -
+    mainScrollElem.scrollTop -
+    mainScrollElem.clientHeight;
+  if (!requiresNearBottom || spaceToBottom < 100) {
+    setTimeout(
+      () => mainScrollElem.scrollTo({ top: mainScrollElem.scrollHeight }),
+      delay ?? 80
+    );
+  }
+};
+
+const scrollToBottomThrottled = throttle(scrollToBottom, 80);
+
+export function useChatScroll(msgListRef: React.RefObject<HTMLDivElement>) {
+  useEffect(() => {
+    if (!msgListRef.current) return;
+
+    const resizeObserver = new ResizeObserver((_) => {
+      scrollToBottomThrottled(true, 10);
+    });
+
+    resizeObserver.observe(msgListRef.current);
+    return () => {
+      resizeObserver.disconnect();
+    };
+  }, [msgListRef]);
+}

tools/server/webui/src/components/useChatTextarea.ts

@@ -1,35 +1,39 @@
 import { useEffect, useRef, useState, useCallback } from 'react';
+import { throttle } from '../utils/misc';
 
 // Media Query for detecting "large" screens (matching Tailwind's lg: breakpoint)
 const LARGE_SCREEN_MQ = '(min-width: 1024px)';
 
 // Calculates and sets the textarea height based on its scrollHeight
-const adjustTextareaHeight = (textarea: HTMLTextAreaElement | null) => {
-  if (!textarea) return;
+const adjustTextareaHeight = throttle(
+  (textarea: HTMLTextAreaElement | null) => {
+    if (!textarea) return;
 
-  // Only perform auto-sizing on large screens
-  if (!window.matchMedia(LARGE_SCREEN_MQ).matches) {
-    // On small screens, reset inline height and max-height styles.
-    // This allows CSS (e.g., `rows` attribute or classes) to control the height,
-    // and enables manual resizing if `resize-vertical` is set.
-    textarea.style.height = ''; // Use 'auto' or '' to reset
-    textarea.style.maxHeight = '';
-    return; // Do not adjust height programmatically on small screens
-  }
+    // Only perform auto-sizing on large screens
+    if (!window.matchMedia(LARGE_SCREEN_MQ).matches) {
+      // On small screens, reset inline height and max-height styles.
+      // This allows CSS (e.g., `rows` attribute or classes) to control the height,
+      // and enables manual resizing if `resize-vertical` is set.
+      textarea.style.height = ''; // Use 'auto' or '' to reset
+      textarea.style.maxHeight = '';
+      return; // Do not adjust height programmatically on small screens
+    }
 
-  const computedStyle = window.getComputedStyle(textarea);
-  // Get the max-height specified by CSS (e.g., from `lg:max-h-48`)
-  const currentMaxHeight = computedStyle.maxHeight;
+    const computedStyle = window.getComputedStyle(textarea);
+    // Get the max-height specified by CSS (e.g., from `lg:max-h-48`)
+    const currentMaxHeight = computedStyle.maxHeight;
 
-  // Temporarily remove max-height to allow scrollHeight to be calculated correctly
-  textarea.style.maxHeight = 'none';
-  // Reset height to 'auto' to measure the actual scrollHeight needed
-  textarea.style.height = 'auto';
-  // Set the height to the calculated scrollHeight
-  textarea.style.height = `${textarea.scrollHeight}px`;
-  // Re-apply the original max-height from CSS to enforce the limit
-  textarea.style.maxHeight = currentMaxHeight;
-};
+    // Temporarily remove max-height to allow scrollHeight to be calculated correctly
+    textarea.style.maxHeight = 'none';
+    // Reset height to 'auto' to measure the actual scrollHeight needed
+    textarea.style.height = 'auto';
+    // Set the height to the calculated scrollHeight
+    textarea.style.height = `${textarea.scrollHeight}px`;
+    // Re-apply the original max-height from CSS to enforce the limit
+    textarea.style.maxHeight = currentMaxHeight;
+  },
+  100
+); // Throttle to prevent excessive calls
 
 // Interface describing the API returned by the hook
 export interface ChatTextareaApi {
@@ -65,6 +69,7 @@ export function useChatTextarea(initValue: string): ChatTextareaApi {
     }
   }, [textareaRef, savedInitValue]); // Depend on ref and savedInitValue
 
+  // On input change, we adjust the height of the textarea
   const handleInput = useCallback(
     (event: React.FormEvent<HTMLTextAreaElement>) => {
       // Call adjustTextareaHeight on every input - it will decide whether to act
@@ -94,6 +99,6 @@ export function useChatTextarea(initValue: string): ChatTextareaApi {
     },
     ref: textareaRef,
     refOnSubmit: onSubmitRef,
-    onInput: handleInput,
+    onInput: handleInput, // for adjusting height on input
   };
 }

tools/server/webui/src/index.scss

@@ -22,12 +22,15 @@ html {
     all: revert;
   }
   pre {
-    @apply whitespace-pre-wrap rounded-lg p-2;
+    @apply whitespace-pre-wrap rounded-lg p-2 mb-3;
     border: 1px solid currentColor;
   }
   p {
     @apply mb-2;
   }
+  hr {
+    @apply my-4 border-base-content/20 border-1;
+  }
   /* TODO: fix markdown table */
 }
 
@@ -35,7 +38,7 @@ html {
   @apply md:opacity-0 md:group-hover:opacity-100;
 }
 .btn-mini {
-  @apply cursor-pointer hover:shadow-md;
+  @apply cursor-pointer;
 }
 .chat-screen {
   max-width: 900px;

tools/server/webui/src/utils/app.context.tsx

@@ -3,6 +3,7 @@ import {
   APIMessage,
   CanvasData,
   Conversation,
+  LlamaCppServerProps,
   Message,
   PendingMessage,
   ViewingChat,
@@ -12,9 +13,11 @@ import {
   filterThoughtFromMsgs,
   normalizeMsgsForAPI,
   getSSEStreamAsync,
+  getServerProps,
 } from './misc';
 import { BASE_URL, CONFIG_DEFAULT, isDev } from '../Config';
 import { matchPath, useLocation, useNavigate } from 'react-router';
+import toast from 'react-hot-toast';
 
 interface AppContextValue {
   // conversations and messages
@@ -46,6 +49,9 @@ interface AppContextValue {
   saveConfig: (config: typeof CONFIG_DEFAULT) => void;
   showSettings: boolean;
   setShowSettings: (show: boolean) => void;
+
+  // props
+  serverProps: LlamaCppServerProps | null;
 }
 
 // this callback is used for scrolling to the bottom of the chat and switching to the last node
@@ -74,6 +80,9 @@ export const AppContextProvider = ({
   const params = matchPath('/chat/:convId', pathname);
   const convId = params?.params?.convId;
 
+  const [serverProps, setServerProps] = useState<LlamaCppServerProps | null>(
+    null
+  );
   const [viewingChat, setViewingChat] = useState<ViewingChat | null>(null);
   const [pendingMessages, setPendingMessages] = useState<
     Record<Conversation['id'], PendingMessage>
@@ -85,6 +94,20 @@ export const AppContextProvider = ({
   const [canvasData, setCanvasData] = useState<CanvasData | null>(null);
   const [showSettings, setShowSettings] = useState(false);
 
+  // get server props
+  useEffect(() => {
+    getServerProps(BASE_URL, config.apiKey)
+      .then((props) => {
+        console.debug('Server props:', props);
+        setServerProps(props);
+      })
+      .catch((err) => {
+        console.error(err);
+        toast.error('Failed to fetch server props');
+      });
+    // eslint-disable-next-line
+  }, []);
+
   // handle change when the convId from URL is changed
   useEffect(() => {
     // also reset the canvas data
@@ -260,7 +283,7 @@ export const AppContextProvider = ({
       } else {
         console.error(err);
         // eslint-disable-next-line @typescript-eslint/no-explicit-any
-        alert((err as any)?.message ?? 'Unknown error');
+        toast.error((err as any)?.message ?? 'Unknown error');
         throw err; // rethrow
       }
     }
@@ -377,6 +400,7 @@ export const AppContextProvider = ({
         saveConfig,
         showSettings,
         setShowSettings,
+        serverProps,
       }}
     >
       {children}

tools/server/webui/src/utils/common.tsx

@@ -36,3 +36,32 @@ export const OpenInNewTab = ({
     {children}
   </a>
 );
+
+export function BtnWithTooltips({
+  className,
+  onClick,
+  onMouseLeave,
+  children,
+  tooltipsContent,
+  disabled,
+}: {
+  className?: string;
+  onClick: () => void;
+  onMouseLeave?: () => void;
+  children: React.ReactNode;
+  tooltipsContent: string;
+  disabled?: boolean;
+}) {
+  return (
+    <div className="tooltip tooltip-bottom" data-tip={tooltipsContent}>
+      <button
+        className={`${className ?? ''} flex items-center justify-center`}
+        onClick={onClick}
+        disabled={disabled}
+        onMouseLeave={onMouseLeave}
+      >
+        {children}
+      </button>
+    </div>
+  );
+}

tools/server/webui/src/utils/llama-vscode.ts

@@ -1,6 +1,6 @@
-import { useEffect, useState } from 'react';
-import { MessageExtraContext } from './types';
+import { useEffect } from 'react';
 import { ChatTextareaApi } from '../components/useChatTextarea.ts';
+import { ChatExtraContextApi } from '../components/useChatExtraContext.tsx';
 
 // Extra context when using llama.cpp WebUI from llama-vscode, inside an iframe
 // Ref: https://github.com/ggml-org/llama.cpp/pull/11940
@@ -15,11 +15,10 @@ interface SetTextEvData {
  * window.postMessage({ command: 'setText', text: 'Spot the syntax error', context: 'def test()\n  return 123' }, '*');
  */
 
-export const useVSCodeContext = (textarea: ChatTextareaApi) => {
-  const [extraContext, setExtraContext] = useState<MessageExtraContext | null>(
-    null
-  );
-
+export const useVSCodeContext = (
+  textarea: ChatTextareaApi,
+  extraContext: ChatExtraContextApi
+) => {
   // Accept setText message from a parent window and set inputMsg and extraContext
   useEffect(() => {
     const handleMessage = (event: MessageEvent) => {
@@ -27,10 +26,14 @@ export const useVSCodeContext = (textarea: ChatTextareaApi) => {
         const data: SetTextEvData = event.data;
         textarea.setValue(data?.text);
         if (data?.context && data.context.length > 0) {
-          setExtraContext({
-            type: 'context',
-            content: data.context,
-          });
+          extraContext.clearItems();
+          extraContext.addItems([
+            {
+              type: 'context',
+              name: 'Extra context',
+              content: data.context,
+            },
+          ]);
         }
         textarea.focus();
         setTimeout(() => {
@@ -41,7 +44,7 @@ export const useVSCodeContext = (textarea: ChatTextareaApi) => {
 
     window.addEventListener('message', handleMessage);
     return () => window.removeEventListener('message', handleMessage);
-  }, [textarea]);
+  }, [textarea, extraContext]);
 
   // Add a keydown listener that sends the "escapePressed" message to the parent window
   useEffect(() => {
@@ -55,9 +58,5 @@ export const useVSCodeContext = (textarea: ChatTextareaApi) => {
     return () => window.removeEventListener('keydown', handleKeyDown);
   }, []);
 
-  return {
-    extraContext,
-    // call once the user message is sent, to clear the extra context
-    clearExtraContext: () => setExtraContext(null),
-  };
+  return {};
 };

tools/server/webui/src/utils/misc.ts

@@ -1,6 +1,11 @@
 // @ts-expect-error this package does not have typing
 import TextLineStream from 'textlinestream';
-import { APIMessage, Message } from './types';
+import {
+  APIMessage,
+  APIMessageContentPart,
+  LlamaCppServerProps,
+  Message,
+} from './types';
 
 // ponyfill for missing ReadableStream asyncIterator on Safari
 import { asyncIterator } from '@sec-ant/readable-stream/ponyfill/asyncIterator';
@@ -57,19 +62,47 @@ export const copyStr = (textToCopy: string) => {
  */
 export function normalizeMsgsForAPI(messages: Readonly<Message[]>) {
   return messages.map((msg) => {
-    let newContent = '';
+    if (msg.role !== 'user' || !msg.extra) {
+      return {
+        role: msg.role,
+        content: msg.content,
+      } as APIMessage;
+    }
+
+    // extra content first, then user text message in the end
+    // this allow re-using the same cache prefix for long context
+    const contentArr: APIMessageContentPart[] = [];
 
     for (const extra of msg.extra ?? []) {
       if (extra.type === 'context') {
-        newContent += `${extra.content}\n\n`;
+        contentArr.push({
+          type: 'text',
+          text: extra.content,
+        });
+      } else if (extra.type === 'textFile') {
+        contentArr.push({
+          type: 'text',
+          text: `File: ${extra.name}\nContent:\n\n${extra.content}`,
+        });
+      } else if (extra.type === 'imageFile') {
+        contentArr.push({
+          type: 'image_url',
+          image_url: { url: extra.base64Url },
+        });
+      } else {
+        throw new Error('Unknown extra type');
       }
     }
 
-    newContent += msg.content;
+    // add user message to the end
+    contentArr.push({
+      type: 'text',
+      text: msg.content,
+    });
 
     return {
       role: msg.role,
-      content: newContent,
+      content: contentArr,
     };
   }) as APIMessage[];
 }
@@ -78,13 +111,19 @@ export function normalizeMsgsForAPI(messages: Readonly<Message[]>) {
  * recommended for DeepsSeek-R1, filter out content between <think> and </think> tags
  */
 export function filterThoughtFromMsgs(messages: APIMessage[]) {
+  console.debug({ messages });
   return messages.map((msg) => {
+    if (msg.role !== 'assistant') {
+      return msg;
+    }
+    // assistant message is always a string
+    const contentStr = msg.content as string;
     return {
       role: msg.role,
       content:
         msg.role === 'assistant'
-          ? msg.content.split('</think>').at(-1)!.trim()
-          : msg.content,
+          ? contentStr.split('</think>').at(-1)!.trim()
+          : contentStr,
     } as APIMessage;
   });
 }
@@ -126,3 +165,25 @@ export const cleanCurrentUrl = (removeQueryParams: string[]) => {
   });
   window.history.replaceState({}, '', url.toString());
 };
+
+export const getServerProps = async (
+  baseUrl: string,
+  apiKey?: string
+): Promise<LlamaCppServerProps> => {
+  try {
+    const response = await fetch(`${baseUrl}/props`, {
+      headers: {
+        'Content-Type': 'application/json',
+        ...(apiKey ? { Authorization: `Bearer ${apiKey}` } : {}),
+      },
+    });
+    if (!response.ok) {
+      throw new Error('Failed to fetch server props');
+    }
+    const data = await response.json();
+    return data as LlamaCppServerProps;
+  } catch (error) {
+    console.error('Error fetching server props:', error);
+    throw error;
+  }
+};

tools/server/webui/src/utils/storage.ts

@@ -116,6 +116,16 @@ const StorageUtils = {
     });
     return conv;
   },
+  /**
+   * update the name of a conversation
+   */
+  async updateConversationName(convId: string, name: string): Promise<void> {
+    await db.conversations.update(convId, {
+      name,
+      lastModified: Date.now(),
+    });
+    dispatchConversationChange(convId);
+  },
   /**
    * if convId does not exist, throw an error
    */

tools/server/webui/src/utils/types.ts

@@ -48,7 +48,10 @@ export interface Message {
   children: Message['id'][];
 }
 
-type MessageExtra = MessageExtraTextFile | MessageExtraContext; // TODO: will add more in the future
+export type MessageExtra =
+  | MessageExtraTextFile
+  | MessageExtraImageFile
+  | MessageExtraContext;
 
 export interface MessageExtraTextFile {
   type: 'textFile';
@@ -56,12 +59,32 @@ export interface MessageExtraTextFile {
   content: string;
 }
 
+export interface MessageExtraImageFile {
+  type: 'imageFile';
+  name: string;
+  base64Url: string;
+}
+
 export interface MessageExtraContext {
   type: 'context';
+  name: string;
   content: string;
 }
 
-export type APIMessage = Pick<Message, 'role' | 'content'>;
+export type APIMessageContentPart =
+  | {
+      type: 'text';
+      text: string;
+    }
+  | {
+      type: 'image_url';
+      image_url: { url: string };
+    };
+
+export type APIMessage = {
+  role: Message['role'];
+  content: string | APIMessageContentPart[];
+};
 
 export interface Conversation {
   id: string; // format: `conv-{timestamp}`
@@ -89,3 +112,12 @@ export interface CanvasPyInterpreter {
 }
 
 export type CanvasData = CanvasPyInterpreter;
+
+// a non-complete list of props, only contains the ones we need
+export interface LlamaCppServerProps {
+  build_info: string;
+  model_path: string;
+  n_ctx: number;
+  has_multimodal: boolean;
+  // TODO: support params
+}

tools/server/webui/vite.config.ts

@@ -71,6 +71,7 @@ export default defineConfig({
   server: {
     proxy: {
       '/v1': 'http://localhost:8080',
+      '/props': 'http://localhost:8080',
     },
     headers: {
       'Cross-Origin-Embedder-Policy': 'require-corp',