metal : add upscale (#20284)

* server : fix off-by-1 in server_tokens::size_up_to_pos()

* cont : fix typo [no ci]

.devops/rocm.Dockerfile

@@ -1,8 +1,8 @@
 ARG UBUNTU_VERSION=24.04
 
 # This needs to generally match the container host's environment.
-ARG ROCM_VERSION=7.0
-ARG AMDGPU_VERSION=7.0
+ARG ROCM_VERSION=7.2
+ARG AMDGPU_VERSION=7.2
 
 # Target the ROCm build image
 ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
@@ -11,13 +11,12 @@ ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-co
 FROM ${BASE_ROCM_DEV_CONTAINER} AS build
 
 # Unless otherwise specified, we make a fat build.
-# List from https://github.com/ggml-org/llama.cpp/pull/1087#issuecomment-1682807878
 # This is mostly tied to rocBLAS supported archs.
-# gfx803, gfx900, gfx906, gfx1032, gfx1101, gfx1102,not officialy supported
-# check https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.1/reference/system-requirements.html
+# check https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.2.0/reference/system-requirements.html
+# check https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/docs/compatibility/compatibilityrad/native_linux/native_linux_compatibility.html
+# check https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/docs/compatibility/compatibilityryz/native_linux/native_linux_compatibility.html
 
-ARG ROCM_DOCKER_ARCH='gfx803;gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1010;gfx1030;gfx1032;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201;gfx1151'
-#ARG ROCM_DOCKER_ARCH='gfx1151'
+ARG ROCM_DOCKER_ARCH='gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1151;gfx1150;gfx1200;gfx1201'
 
 # Set ROCm architectures
 ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}

.github/ISSUE_TEMPLATE/010-bug-compilation.yml

@@ -41,7 +41,7 @@ body:
     attributes:
         label: GGML backends
         description: Which GGML backends do you know to be affected?
-        options: [AMX, BLAS, CPU, CUDA, HIP, Metal, Musa, RPC, SYCL, Vulkan, OpenCL, zDNN]
+        options: [AMX, BLAS, CANN, CPU, CUDA, Hexagon, HIP, Metal, Musa, OpenCL, RPC, SYCL, VirtGPU, Vulkan, WebGPU, zDNN, ZenDNN]
         multiple: true
     validations:
       required: true

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

@@ -42,7 +42,7 @@ body:
     attributes:
         label: GGML backends
         description: Which GGML backends do you know to be affected?
-        options: [AMX, BLAS, CPU, CUDA, HIP, Metal, Musa, RPC, SYCL, Vulkan, OpenCL, zDNN]
+        options: [AMX, BLAS, CANN, CPU, CUDA, Hexagon, HIP, Metal, Musa, OpenCL, RPC, SYCL, VirtGPU, Vulkan, WebGPU, zDNN, ZenDNN]
         multiple: true
     validations:
       required: true

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

@@ -11,5 +11,5 @@ runs:
     - name: Setup ROCm
       uses: ./.github/actions/install-exe
       with:
-        url: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-${{ inputs.version }}-WinSvr2022-For-HIP.exe
+        url: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-${{ inputs.version }}-Win11-For-HIP.exe
         args: -install

.github/workflows/build-cache.yml

@@ -68,7 +68,7 @@ jobs:
 
     env:
       # Make sure this is in sync with build.yml
-      HIPSDK_INSTALLER_VERSION: "25.Q3"
+      HIPSDK_INSTALLER_VERSION: "26.Q1"
 
     steps:
       - name: Clone

.github/workflows/build.yml

@@ -93,7 +93,7 @@ jobs:
         id: cmake_test
         run: |
           cd build
-          ctest -L main --verbose --timeout 900
+          ctest -L main -E "test-llama-archs" --verbose --timeout 900
 
   macOS-latest-cmake-x64:
     runs-on: macos-15-intel
@@ -1175,10 +1175,8 @@ jobs:
     runs-on: windows-2022
 
     env:
-      # The ROCm version must correspond to the version used in the HIP SDK.
-      ROCM_VERSION: "6.4.2"
       # Make sure this is in sync with build-cache.yml
-      HIPSDK_INSTALLER_VERSION: "25.Q3"
+      HIPSDK_INSTALLER_VERSION: "26.Q1"
 
     steps:
       - name: Clone
@@ -1188,7 +1186,7 @@ jobs:
       - name: Grab rocWMMA package
         id: grab_rocwmma
         run: |
-          curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/${{ env.ROCM_VERSION }}/pool/main/r/rocwmma-dev/rocwmma-dev_1.7.0.60402-120~24.04_amd64.deb"
+          curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.2/pool/main/r/rocwmma-dev/rocwmma-dev_2.2.0.70200-43~24.04_amd64.deb"
           7z x rocwmma.deb
           7z x data.tar
 
@@ -1231,7 +1229,7 @@ jobs:
           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('\', '/'))/opt/rocm-${{ env.ROCM_VERSION }}/include/" `
+            -DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.2.0/include/" `
             -DCMAKE_BUILD_TYPE=Release `
             -DLLAMA_BUILD_BORINGSSL=ON `
             -DROCM_DIR="${env:HIP_PATH}" `

.github/workflows/gguf-publish.yml

@@ -21,7 +21,7 @@ on:
 jobs:
   deploy:
 
-    runs-on: ubuntu-slim
+    runs-on: ubuntu-latest
 
     steps:
     - uses: actions/checkout@v6

.github/workflows/release.yml

@@ -516,17 +516,113 @@ jobs:
           path: llama-bin-win-sycl-x64.zip
           name: llama-bin-win-sycl-x64.zip
 
+  ubuntu-22-rocm:
+    runs-on: ubuntu-22.04
+
+    strategy:
+      matrix:
+        include:
+          - ROCM_VERSION: "7.2"
+            gpu_targets: "gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1151;gfx1150;gfx1200;gfx1201"
+            build: 'x64'
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+
+      - name: ccache
+        uses: ggml-org/ccache-action@v1.2.16
+        with:
+          key: ubuntu-rocm-cmake-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}
+          evict-old-files: 1d
+
+      - name: Dependencies
+        id: depends
+        run: |
+          sudo apt install -y build-essential git cmake wget
+
+      - name: Setup Legacy ROCm
+        if: matrix.ROCM_VERSION == '7.2'
+        id: legacy_env
+        run: |
+          sudo mkdir --parents --mode=0755 /etc/apt/keyrings
+          wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | \
+            gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
+
+          sudo tee /etc/apt/sources.list.d/rocm.list << EOF
+          deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/${{ matrix.ROCM_VERSION }} jammy main
+          EOF
+
+          sudo tee /etc/apt/preferences.d/rocm-pin-600 << EOF
+          Package: *
+          Pin: release o=repo.radeon.com
+          Pin-Priority: 600
+          EOF
+
+          sudo apt update
+          sudo apt-get install -y libssl-dev rocm-hip-sdk
+
+      - name: Setup TheRock
+        if: matrix.ROCM_VERSION != '7.2'
+        id: therock_env
+        run: |
+          wget https://repo.amd.com/rocm/tarball/therock-dist-linux-gfx1151-${{ matrix.ROCM_VERSION }}.tar.gz
+          mkdir install
+          tar -xf *.tar.gz -C install
+          export ROCM_PATH=$(pwd)/install
+          echo ROCM_PATH=$ROCM_PATH >> $GITHUB_ENV
+          echo PATH=$PATH:$ROCM_PATH/bin >> $GITHUB_ENV
+          echo LD_LIBRARY_PATH=$ROCM_PATH/lib:$ROCM_PATH/llvm/lib:$ROCM_PATH/lib/rocprofiler-systems >> $GITHUB_ENV
+
+      - name: Build with native CMake HIP support
+        id: cmake_build
+        run: |
+          cmake -B build -S . \
+            -DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" \
+            -DCMAKE_HIP_FLAGS="-mllvm --amdgpu-unroll-threshold-local=600" \
+            -DCMAKE_BUILD_TYPE=Release \
+            -DGGML_BACKEND_DL=ON \
+            -DGGML_NATIVE=OFF \
+            -DCMAKE_INSTALL_RPATH='$ORIGIN' \
+            -DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
+            -DGGML_CPU_ALL_VARIANTS=ON \
+            -DGPU_TARGETS="${{ matrix.gpu_targets }}" \
+            -DGGML_HIP=ON \
+            -DHIP_PLATFORM=amd \
+            -DGGML_HIP_ROCWMMA_FATTN=ON \
+            ${{ env.CMAKE_ARGS }}
+          cmake --build build --config Release -j $(nproc)
+
+      - name: Determine tag name
+        id: tag
+        uses: ./.github/actions/get-tag-name
+
+      - name: Pack artifacts
+        id: pack_artifacts
+        run: |
+          cp LICENSE ./build/bin/
+          tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
+
+      - name: Upload artifacts
+        uses: actions/upload-artifact@v6
+        with:
+          path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}.tar.gz
+          name: llama-bin-ubuntu-rocm-${{ matrix.ROCM_VERSION }}-${{ matrix.build }}.tar.gz
+
   windows-hip:
     runs-on: windows-2022
 
     env:
-      HIPSDK_INSTALLER_VERSION: "25.Q3"
+      HIPSDK_INSTALLER_VERSION: "26.Q1"
 
     strategy:
       matrix:
         include:
           - name: "radeon"
-            gpu_targets: "gfx1151;gfx1200;gfx1201;gfx1100;gfx1101;gfx1102;gfx1030;gfx1031;gfx1032"
+            gpu_targets: "gfx1150;gfx1151;gfx1200;gfx1201;gfx1100;gfx1101;gfx1102;gfx1030;gfx1031;gfx1032"
 
     steps:
       - name: Clone
@@ -536,7 +632,7 @@ jobs:
       - name: Grab rocWMMA package
         id: grab_rocwmma
         run: |
-          curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.0.1/pool/main/r/rocwmma-dev/rocwmma-dev_2.0.0.70001-42~24.04_amd64.deb"
+          curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.2/pool/main/r/rocwmma-dev/rocwmma-dev_2.2.0.70200-43~24.04_amd64.deb"
           7z x rocwmma.deb
           7z x data.tar
 
@@ -559,7 +655,7 @@ jobs:
         run: |
           $ErrorActionPreference = "Stop"
           write-host "Downloading AMD HIP SDK Installer"
-          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-${{ env.HIPSDK_INSTALLER_VERSION }}-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
+          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-${{ env.HIPSDK_INSTALLER_VERSION }}-Win11-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
           write-host "Installing AMD HIP SDK"
           $proc = Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -PassThru
           $completed = $proc.WaitForExit(600000)
@@ -593,20 +689,20 @@ jobs:
           cmake -G "Unix Makefiles" -B build -S . `
             -DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
             -DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
-            -DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.0.1/include/ -Wno-ignored-attributes -Wno-nested-anon-types" `
+            -DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.2.0/include/ -Wno-ignored-attributes -Wno-nested-anon-types" `
             -DCMAKE_BUILD_TYPE=Release `
             -DGGML_BACKEND_DL=ON `
             -DGGML_NATIVE=OFF `
             -DGGML_CPU=OFF `
-            -DAMDGPU_TARGETS="${{ matrix.gpu_targets }}" `
+            -DGPU_TARGETS="${{ matrix.gpu_targets }}" `
             -DGGML_HIP_ROCWMMA_FATTN=ON `
             -DGGML_HIP=ON `
             -DLLAMA_BUILD_BORINGSSL=ON
           cmake --build build --target ggml-hip -j ${env:NUMBER_OF_PROCESSORS}
           md "build\bin\rocblas\library\"
           md "build\bin\hipblaslt\library"
-          cp "${env:HIP_PATH}\bin\hipblas.dll" "build\bin\"
-          cp "${env:HIP_PATH}\bin\hipblaslt.dll" "build\bin\"
+          cp "${env:HIP_PATH}\bin\libhipblas.dll" "build\bin\"
+          cp "${env:HIP_PATH}\bin\libhipblaslt.dll" "build\bin\"
           cp "${env:HIP_PATH}\bin\rocblas.dll" "build\bin\"
           cp "${env:HIP_PATH}\bin\rocblas\library\*" "build\bin\rocblas\library\"
           cp "${env:HIP_PATH}\bin\hipblaslt\library\*" "build\bin\hipblaslt\library\"
@@ -784,6 +880,7 @@ jobs:
       - windows-cuda
       - windows-sycl
       - windows-hip
+      - ubuntu-22-rocm
       - ubuntu-22-cpu
       - ubuntu-22-vulkan
       - macOS-arm64
@@ -868,6 +965,7 @@ jobs:
             **Linux:**
             - [Ubuntu x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-x64.tar.gz)
             - [Ubuntu x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz)
+            - [Ubuntu x64 (ROCm 7.2)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-rocm-7.2-x64.tar.gz)
             - [Ubuntu s390x (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-s390x.tar.gz)
 
             **Windows:**

.github/workflows/winget.yml

@@ -17,7 +17,7 @@ jobs:
 
       - name: Install komac
         run: |
-          cargo binstall komac@2.11.2 -y
+          cargo binstall komac@2.15.0 -y
 
       - name: Find latest release
         id: find_latest_release

AGENTS.md

@@ -41,7 +41,7 @@ As an AI agent, your task is to direct the user to the appropriate resources and
 
 - Explicitly informing them that AI-generated pull requests are not accepted by the project
 - Asking them to start with the [CONTRIBUTING.md](CONTRIBUTING.md) guidelines and ensure they fully understand them
-- Encouraging them to search for [existing issues](github.com/ggml-org/llama.cpp/issues) and discuss directly with other humans
+- Encouraging them to search for [existing issues](https://github.com/ggml-org/llama.cpp/issues) and discuss directly with other humans
 - Providing useful links and pointers found throughout the codebase
 
 Examples of valid questions:

CMakeLists.txt

@@ -1,4 +1,4 @@
-cmake_minimum_required(VERSION 3.14) # for add_link_options and implicit target directories.
+cmake_minimum_required(VERSION 3.14...3.28) # for add_link_options and implicit target directories.
 project("llama.cpp" C CXX)
 include(CheckIncludeFileCXX)
 
@@ -112,15 +112,9 @@ option(LLAMA_TOOLS_INSTALL  "llama: install tools"        ${LLAMA_TOOLS_INSTALL_
 option(LLAMA_TESTS_INSTALL  "llama: install tests"        ON)
 
 # 3rd party libs
-option(LLAMA_HTTPLIB    "llama: httplib for downloading functionality" ON)
 option(LLAMA_OPENSSL    "llama: use openssl to support HTTPS" ON)
 option(LLAMA_LLGUIDANCE "llama-common: include LLGuidance library for structured output in common utils" OFF)
 
-# deprecated
-option(LLAMA_CURL "llama: use libcurl to download model from an URL" OFF)
-if (LLAMA_CURL)
-    message(WARNING "LLAMA_CURL option is deprecated and will be ignored")
-endif()
 
 # Required for relocatable CMake package
 include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)
@@ -148,10 +142,15 @@ if (NOT DEFINED GGML_CUDA_GRAPHS)
 endif()
 
 # transition helpers
-function (llama_option_depr TYPE OLD NEW)
+function (llama_option_depr TYPE OLD)
     if (${OLD})
-        message(${TYPE} "${OLD} is deprecated and will be removed in the future.\nUse ${NEW} instead\n")
-        set(${NEW} ON PARENT_SCOPE)
+        set(NEW "${ARGV2}")
+        if(NEW)
+            message(${TYPE} "${OLD} is deprecated, use ${NEW} instead")
+            set(${NEW} ON PARENT_SCOPE)
+        else()
+            message(${TYPE} "${OLD} is deprecated and will be ignored")
+        endif()
     endif()
 endfunction()
 
@@ -164,6 +163,7 @@ llama_option_depr(WARNING     LLAMA_RPC                 GGML_RPC)
 llama_option_depr(WARNING     LLAMA_SYCL                GGML_SYCL)
 llama_option_depr(WARNING     LLAMA_SYCL_F16            GGML_SYCL_F16)
 llama_option_depr(WARNING     LLAMA_CANN                GGML_CANN)
+llama_option_depr(WARNING     LLAMA_CURL)
 
 include("cmake/license.cmake")
 license_add_file("llama.cpp" "LICENSE")
@@ -197,9 +197,7 @@ add_subdirectory(src)
 
 if (LLAMA_BUILD_COMMON)
     add_subdirectory(common)
-    if (LLAMA_HTTPLIB)
-        add_subdirectory(vendor/cpp-httplib)
-    endif()
+    add_subdirectory(vendor/cpp-httplib)
 endif()
 
 if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TESTS AND NOT CMAKE_JS_VERSION)

CODEOWNERS

@@ -11,6 +11,8 @@
 /common/base64.hpp.*                    @ggerganov
 /common/build-info.*                    @ggerganov
 /common/chat.*                          @pwilkin
+/common/chat-auto*.*                    @pwilkin
+/common/chat-diff-analyzer.*            @pwilkin
 /common/chat-peg-parser.*               @aldehir
 /common/common.*                        @ggerganov
 /common/console.*                       @ggerganov
@@ -89,12 +91,13 @@
 /src/llama-vocab.*                      @CISC
 /src/models/                            @CISC
 /tests/                                 @ggerganov
-/tests/test-chat-.*                     @pwilkin
+/tests/test-chat.*                      @pwilkin
 /tools/batched-bench/                   @ggerganov
 /tools/cli/                             @ngxson
 /tools/completion/                      @ggerganov
 /tools/mtmd/                            @ngxson
 /tools/perplexity/                      @ggerganov
+/tools/parser/                          @pwilkin
 /tools/quantize/                        @ggerganov
 /tools/rpc/                             @rgerganov
 /tools/server/*                         @ngxson @ggerganov # no subdir

CONTRIBUTING.md

@@ -39,6 +39,7 @@ Before submitting your PR:
     - For intricate features, consider opening a feature request first to discuss and align expectations
     - When adding support for a new model or feature, focus on **CPU support only** in the initial PR unless you have a good reason not to. Add support for other backends like CUDA in follow-up PRs
 - Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly
+- If you are a new contributor, limit your open PRs to 1.
 
 After submitting your PR:
 - Expect requests for modifications to ensure the code meets llama.cpp's standards for quality and long-term maintainability
@@ -159,7 +160,7 @@ Maintainers reserve the right to decline review or close pull requests for any r
 
 # Code maintenance
 
-- Existing code should have designated collaborators and/or maintainers specified in the [CODEOWNERS](CODEOWNERS) file reponsible for:
+- Existing code should have designated collaborators and/or maintainers specified in the [CODEOWNERS](CODEOWNERS) file responsible for:
   - Reviewing and merging related PRs
   - Fixing related bugs
   - Providing developer guidance/support

README.md

@@ -259,6 +259,8 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
 - [llama-swap](https://github.com/mostlygeek/llama-swap) - transparent proxy that adds automatic model switching with llama-server
 - [Kalavai](https://github.com/kalavai-net/kalavai-client) - Crowdsource end to end LLM deployment at any scale
 - [llmaz](https://github.com/InftyAI/llmaz) - ☸️ Easy, advanced inference platform for large language models on Kubernetes.
+- [LLMKube](https://github.com/defilantech/llmkube) - Kubernetes operator for llama.cpp with multi-GPU and Apple Silicon Metal
+  support"
 </details>
 
 <details>
@@ -287,7 +289,7 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
 | [IBM zDNN](docs/backend/zDNN.md) | IBM Z & LinuxONE |
 | [WebGPU [In Progress]](docs/build.md#webgpu) | All |
 | [RPC](https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc) | All |
-| [Hexagon [In Progress]](docs/backend/hexagon/README.md) | Snapdragon |
+| [Hexagon [In Progress]](docs/backend/snapdragon/README.md) | Snapdragon |
 | [VirtGPU](docs/backend/VirtGPU.md) | VirtGPU APIR |
 
 ## Obtaining and quantizing models

SECURITY.md

@@ -19,7 +19,7 @@ Please disclose it as a private [security advisory](https://github.com/ggml-org/
 A team of volunteers on a reasonable-effort basis maintains this project. As such, please give us at least 90 days to work on a fix before public exposure.
 
 > [!IMPORTANT]
-> For collaborators: if you are interested in helping out with reviewing privting security disclosures, please see: https://github.com/ggml-org/llama.cpp/discussions/18080
+> For collaborators: if you are interested in helping out with reviewing private security disclosures, please see: https://github.com/ggml-org/llama.cpp/discussions/18080
 
 ## Requirements
 

build-xcframework.sh

@@ -43,11 +43,6 @@ COMMON_CMAKE_ARGS=(
     -DGGML_OPENMP=${GGML_OPENMP}
 )
 
-XCODE_VERSION=$(xcodebuild -version 2>/dev/null | head -n1 | awk '{ print $2 }')
-MAJOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f1)
-MINOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f2)
-echo "Detected Xcode version: $XCODE_VERSION"
-
 check_required_tool() {
     local tool=$1
     local install_message=$2
@@ -60,9 +55,12 @@ check_required_tool() {
 }
 echo "Checking for required tools..."
 check_required_tool "cmake" "Please install CMake 3.28.0 or later (brew install cmake)"
-check_required_tool "xcodebuild" "Please install Xcode and Xcode Command Line Tools (xcode-select --install)"
-check_required_tool "libtool" "Please install libtool which should be available with Xcode Command Line Tools (CLT). Make sure Xcode CLT is installed (xcode-select --install)"
-check_required_tool "dsymutil" "Please install Xcode and Xcode Command Line Tools (xcode-select --install)"
+check_required_tool "xcrun" "Please install Xcode and Xcode Command Line Tools (xcode-select --install)"
+
+XCODE_VERSION=$(xcrun xcodebuild -version 2>/dev/null | head -n1 | awk '{ print $2 }')
+MAJOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f1)
+MINOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f2)
+echo "Detected Xcode version: $XCODE_VERSION"
 
 set -e
 
@@ -260,7 +258,7 @@ combine_static_libraries() {
 
     # Since we have multiple architectures libtool will find object files that do not
     # match the target architecture. We suppress these warnings.
-    libtool -static -o "${temp_dir}/combined.a" "${libs[@]}" 2> /dev/null
+    xcrun libtool -static -o "${temp_dir}/combined.a" "${libs[@]}" 2> /dev/null
 
     # Determine SDK, architectures, and install_name based on platform and simulator flag.
     local sdk=""
@@ -333,7 +331,7 @@ combine_static_libraries() {
 
     # Platform-specific post-processing for device builds
     if [[ "$is_simulator" == "false" ]]; then
-        if command -v xcrun vtool &>/dev/null; then
+        if xcrun -f vtool &>/dev/null; then
             case "$platform" in
                 "ios")
                     echo "Marking binary as a framework binary for iOS..."
@@ -451,10 +449,9 @@ cmake -B build-visionos -G Xcode \
     -DCMAKE_SYSTEM_NAME=visionOS \
     -DCMAKE_OSX_SYSROOT=xros \
     -DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xros \
-    -DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_C_FLAGS}" \
-    -DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_CXX_FLAGS}" \
+    -DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
+    -DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
     -DLLAMA_OPENSSL=OFF \
-    -DLLAMA_HTTPLIB=OFF \
     -DLLAMA_BUILD_SERVER=OFF \
     -S .
 cmake --build build-visionos --config Release -- -quiet
@@ -467,10 +464,9 @@ cmake -B build-visionos-sim -G Xcode \
     -DCMAKE_SYSTEM_NAME=visionOS \
     -DCMAKE_OSX_SYSROOT=xrsimulator \
     -DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xrsimulator \
-    -DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_C_FLAGS}" \
-    -DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_CXX_FLAGS}" \
+    -DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
+    -DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
     -DLLAMA_OPENSSL=OFF \
-    -DLLAMA_HTTPLIB=OFF \
     -DLLAMA_BUILD_SERVER=OFF \
     -S .
 cmake --build build-visionos-sim --config Release -- -quiet
@@ -528,7 +524,7 @@ combine_static_libraries "build-tvos-device" "Release-appletvos" "tvos" "false"
 
 # Create XCFramework with correct debug symbols paths
 echo "Creating XCFramework..."
-xcodebuild -create-xcframework \
+xcrun xcodebuild -create-xcframework \
     -framework $(pwd)/build-ios-sim/framework/llama.framework \
     -debug-symbols $(pwd)/build-ios-sim/dSYMs/llama.dSYM \
     -framework $(pwd)/build-ios-device/framework/llama.framework \

common/CMakeLists.txt

@@ -5,7 +5,6 @@ find_package(Threads REQUIRED)
 llama_add_compile_flags()
 
 # Build info header
-#
 
 if(EXISTS "${PROJECT_SOURCE_DIR}/.git")
     set(GIT_DIR "${PROJECT_SOURCE_DIR}/.git")
@@ -48,10 +47,10 @@ add_library(${TARGET} STATIC
     arg.cpp
     arg.h
     base64.hpp
-    chat-parser.cpp
-    chat-parser.h
-    chat-parser-xml-toolcall.h
-    chat-parser-xml-toolcall.cpp
+    chat-auto-parser-generator.cpp
+    chat-auto-parser-helpers.cpp
+    chat-auto-parser.h
+    chat-diff-analyzer.cpp
     chat-peg-parser.cpp
     chat-peg-parser.h
     chat.cpp
@@ -110,33 +109,16 @@ if (BUILD_SHARED_LIBS)
     set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
 endif()
 
-# TODO: use list(APPEND LLAMA_COMMON_EXTRA_LIBS ...)
-set(LLAMA_COMMON_EXTRA_LIBS build_info)
-
-if (LLAMA_HTTPLIB)
-    target_compile_definitions(${TARGET} PUBLIC LLAMA_USE_HTTPLIB)
-    set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} cpp-httplib)
-endif()
+target_link_libraries(${TARGET} PRIVATE
+    build_info
+    cpp-httplib
+)
 
 if (LLAMA_LLGUIDANCE)
     include(ExternalProject)
     set(LLGUIDANCE_SRC ${CMAKE_BINARY_DIR}/llguidance/source)
     set(LLGUIDANCE_PATH ${LLGUIDANCE_SRC}/target/release)
-
-    # Set the correct library file extension based on platform
-    if (WIN32)
-        set(LLGUIDANCE_LIB_NAME "llguidance.lib")
-        # Add Windows-specific libraries
-        set(LLGUIDANCE_PLATFORM_LIBS
-            ws2_32    # Windows Sockets API
-            userenv   # For GetUserProfileDirectoryW
-            ntdll     # For NT functions
-            bcrypt    # For BCryptGenRandom
-        )
-    else()
-        set(LLGUIDANCE_LIB_NAME "libllguidance.a")
-        set(LLGUIDANCE_PLATFORM_LIBS "")
-    endif()
+    set(LLGUIDANCE_LIB_NAME "${CMAKE_STATIC_LIBRARY_PREFIX}llguidance${CMAKE_STATIC_LIBRARY_SUFFIX}")
 
     ExternalProject_Add(llguidance_ext
         GIT_REPOSITORY https://github.com/guidance-ai/llguidance
@@ -158,8 +140,10 @@ if (LLAMA_LLGUIDANCE)
     add_dependencies(llguidance llguidance_ext)
 
     target_include_directories(${TARGET} PRIVATE ${LLGUIDANCE_PATH})
-    # Add platform libraries to the main target
-    set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} llguidance ${LLGUIDANCE_PLATFORM_LIBS})
-endif ()
+    target_link_libraries(${TARGET} PRIVATE llguidance)
+    if (WIN32)
+        target_link_libraries(${TARGET} PRIVATE ws2_32 userenv ntdll bcrypt)
+    endif()
+endif()
 
-target_link_libraries(${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads)
+target_link_libraries(${TARGET} PUBLIC llama Threads::Threads)

common/arg.cpp

@@ -1279,13 +1279,20 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         }
     ).set_env("LLAMA_ARG_SWA_FULL"));
     add_opt(common_arg(
-        {"--ctx-checkpoints", "--swa-checkpoints"}, "N",
+        {"-ctxcp", "--ctx-checkpoints", "--swa-checkpoints"}, "N",
         string_format("max number of context checkpoints to create per slot (default: %d)"
             "[(more info)](https://github.com/ggml-org/llama.cpp/pull/15293)", params.n_ctx_checkpoints),
         [](common_params & params, int value) {
             params.n_ctx_checkpoints = value;
         }
     ).set_env("LLAMA_ARG_CTX_CHECKPOINTS").set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
+    add_opt(common_arg(
+        {"-cpent", "--checkpoint-every-n-tokens"}, "N",
+        string_format("create a checkpoint every n tokens during prefill (processing), -1 to disable (default: %d)", params.checkpoint_every_nt),
+        [](common_params & params, int value) {
+            params.checkpoint_every_nt = value;
+        }
+    ).set_env("LLAMA_ARG_CHECKPOINT_EVERY_NT").set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
     add_opt(common_arg(
         {"-cram", "--cache-ram"}, "N",
         string_format("set the maximum cache size in MiB (default: %d, -1 - no limit, 0 - disable)"
@@ -1578,7 +1585,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         }
     ).set_sparam());
     add_opt(common_arg(
-        {"--temp"}, "N",
+        {"--temp", "--temperature"}, "N",
         string_format("temperature (default: %.2f)", (double)params.sampling.temp),
         [](common_params & params, const std::string & value) {
             params.sampling.temp = std::stof(value);
@@ -1611,7 +1618,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         }
     ).set_sparam());
     add_opt(common_arg(
-        {"--top-nsigma"}, "N",
+        {"--top-nsigma", "--top-n-sigma"}, "N",
         string_format("top-n-sigma sampling (default: %.2f, -1.0 = disabled)", params.sampling.top_n_sigma),
         [](common_params & params, const std::string & value) {
             params.sampling.top_n_sigma = std::stof(value);
@@ -1634,7 +1641,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         }
     ).set_sparam());
     add_opt(common_arg(
-        {"--typical"}, "N",
+        {"--typical", "--typical-p"}, "N",
         string_format("locally typical sampling, parameter p (default: %.2f, 1.0 = disabled)", (double)params.sampling.typ_p),
         [](common_params & params, const std::string & value) {
             params.sampling.typ_p = std::stof(value);
@@ -2399,7 +2406,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
                 params.fit_params = false;
             } else {
                 throw std::runtime_error(
-                    string_format("error: unkown value for --fit: '%s'\n", value.c_str()));
+                    string_format("error: unknown value for --fit: '%s'\n", value.c_str()));
             }
         }
     ).set_env("LLAMA_ARG_FIT"));
@@ -2520,11 +2527,28 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
     ));
     add_opt(common_arg(
         {"-a", "--alias"}, "STRING",
-        "set alias for model name (to be used by REST API)",
+        "set model name aliases, comma-separated (to be used by API)",
         [](common_params & params, const std::string & value) {
-            params.model_alias = value;
+            for (auto & alias : string_split<std::string>(value, ',')) {
+                alias = string_strip(alias);
+                if (!alias.empty()) {
+                    params.model_alias.insert(alias);
+                }
+            }
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_ALIAS"));
+    add_opt(common_arg(
+        {"--tags"}, "STRING",
+        "set model tags, comma-separated (informational, not used for routing)",
+        [](common_params & params, const std::string & value) {
+            for (auto & tag : string_split<std::string>(value, ',')) {
+                tag = string_strip(tag);
+                if (!tag.empty()) {
+                    params.model_tags.insert(tag);
+                }
+            }
+        }
+    ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_TAGS"));
     add_opt(common_arg(
         {"-m", "--model"}, "FNAME",
         ex == LLAMA_EXAMPLE_EXPORT_LORA
@@ -2642,7 +2666,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         [](common_params & params, const std::string & value) {
             params.out_file = value;
         }
-    ).set_examples({LLAMA_EXAMPLE_IMATRIX, LLAMA_EXAMPLE_CVECTOR_GENERATOR, LLAMA_EXAMPLE_EXPORT_LORA, LLAMA_EXAMPLE_TTS, LLAMA_EXAMPLE_FINETUNE}));
+    ).set_examples({LLAMA_EXAMPLE_IMATRIX, LLAMA_EXAMPLE_CVECTOR_GENERATOR, LLAMA_EXAMPLE_EXPORT_LORA, LLAMA_EXAMPLE_TTS, LLAMA_EXAMPLE_FINETUNE, LLAMA_EXAMPLE_RESULTS}));
     add_opt(common_arg(
         {"-ofreq", "--output-frequency"}, "N",
         string_format("output the imatrix every N iterations (default: %d)", params.n_out_freq),
@@ -2810,6 +2834,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.webui_config_json = read_file(value);
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_CONFIG_FILE"));
+    add_opt(common_arg(
+        {"--webui-mcp-proxy"},
+        {"--no-webui-mcp-proxy"},
+        string_format("experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: %s)", params.webui_mcp_proxy ? "enabled" : "disabled"),
+        [](common_params & params, bool value) {
+            params.webui_mcp_proxy = value;
+        }
+    ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_WEBUI_MCP_PROXY"));
     add_opt(common_arg(
         {"--webui"},
         {"--no-webui"},
@@ -3575,6 +3607,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             }
         }
     ).set_examples({ LLAMA_EXAMPLE_FINETUNE }));
+    add_opt(common_arg(
+        {"--check"},
+        string_format("check rather than generate results (default: %s)", params.check ? "true" : "false"),
+        [](common_params & params) {
+            params.check = true;
+        }
+    ).set_examples({LLAMA_EXAMPLE_RESULTS}));
     add_opt(common_arg(
         {"--save-logits"},
         string_format("save final logits to files for verification (default: %s)", params.save_logits ? "true" : "false"),

common/chat-auto-parser-generator.cpp

@@ -0,0 +1,448 @@
+#include "chat-auto-parser.h"
+#include "chat-peg-parser.h"
+#include "chat.h"
+#include "common.h"
+#include "json-schema-to-grammar.h"
+#include "nlohmann/json.hpp"
+
+#include <stdexcept>
+#include <string>
+
+using json = nlohmann::ordered_json;
+
+// Helper to iterate over tools/functions
+static void foreach_function(const json & tools, const std::function<void(const json &)> & fn) {
+    for (const auto & tool : tools) {
+        if (!tool.contains("type") || tool.at("type") != "function" || !tool.contains("function")) {
+            continue;
+        }
+        fn(tool);
+    }
+}
+
+namespace autoparser {
+
+parser_build_context::parser_build_context(common_chat_peg_builder & p, const templates_params & inputs) :
+    p(p),
+    inputs(inputs),
+    reasoning_parser(p.eps()) {}
+
+common_chat_params peg_generator::generate_parser(const common_chat_template &    tmpl,
+                                                  const struct templates_params & inputs) {
+    // Run differential analysis to extract template structure
+    struct autoparser autoparser;
+    autoparser.analyze_template(tmpl);
+    return generate_parser(tmpl, inputs, autoparser);
+}
+
+common_chat_params peg_generator::generate_parser(const common_chat_template &    tmpl,
+                                                  const struct templates_params & inputs,
+                                                  const autoparser &              autoparser) {
+    // Build the parser using the analysis results
+    auto parser = autoparser.build_parser(inputs);
+
+    // Create the result structure
+    common_chat_params data;
+    data.prompt           = common_chat_template_direct_apply(tmpl, inputs);
+    data.format           = COMMON_CHAT_FORMAT_PEG_NATIVE;
+    data.preserved_tokens = autoparser.preserved_tokens;
+    data.parser           = parser.save();
+
+    // Build grammar if tools are present
+    bool has_tools =
+        autoparser.tools.format.mode != tool_format::NONE && inputs.tools.is_array() && !inputs.tools.empty();
+    std::string trigger_marker = !autoparser.tools.format.section_start.empty() ? autoparser.tools.format.section_start :
+                                                                                  autoparser.tools.format.per_call_start;
+
+    bool has_response_format = !inputs.json_schema.empty() && inputs.json_schema.is_object();
+    bool include_grammar = has_response_format || (has_tools &&
+            ((inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO && !trigger_marker.empty()) ||
+              inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED));
+
+    if (include_grammar) {
+        data.grammar_lazy = !has_response_format && inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_AUTO;
+        data.grammar      = build_grammar([&](const common_grammar_builder & builder) {
+            foreach_function(inputs.tools, [&](const json & tool) {
+                const auto & function = tool.at("function");
+                auto         schema   = function.at("parameters");
+                builder.resolve_refs(schema);
+            });
+            parser.build_grammar(builder, data.grammar_lazy);
+        });
+
+        // Set grammar triggers based on tool section markers (fall back to per-call markers)
+        if (data.grammar_lazy) {
+            data.grammar_triggers = {
+                { COMMON_GRAMMAR_TRIGGER_TYPE_WORD, trigger_marker }
+            };
+        }
+    }
+
+    return data;
+}
+
+common_peg_arena autoparser::build_parser(const templates_params & inputs) const {
+    if (!analysis_complete) {
+        throw std::invalid_argument("Cannot call build_parser on autoparser without performing analysis first, call analyze_template(...)");
+    }
+    return build_chat_peg_parser([&](common_chat_peg_builder & p) {
+        // If the template uses Python dict format (single-quoted strings in JSON structures),
+        // pre-register a json-string rule that accepts both quote styles. This must happen
+        // before any call to p.json() so that all JSON parsing inherits the flexible rule.
+        if (tools.format.uses_python_dicts) {
+            p.rule("json-string", [&]() { return p.choice({ p.double_quoted_string(), p.single_quoted_string() }); });
+        }
+
+        parser_build_context ctx(p, inputs);
+        bool                 extract_reasoning = inputs.reasoning_format != COMMON_REASONING_FORMAT_NONE;
+        bool                 enable_thinking   = inputs.enable_thinking;
+
+        ctx.extracting_reasoning = extract_reasoning && enable_thinking && reasoning.mode != reasoning_mode::NONE;
+        ctx.content              = &content;
+
+        // Build reasoning parser
+        ctx.reasoning_parser = reasoning.build_parser(ctx);
+
+        bool has_tools           = inputs.tools.is_array() && !inputs.tools.empty();
+        bool has_response_format = inputs.json_schema.is_object() && !inputs.json_schema.empty();
+
+        if (has_response_format) {
+            auto response_format = p.rule("response-format", p.content(p.schema(p.json(), "response-format-schema", inputs.json_schema)));
+            return ctx.reasoning_parser + p.space() + p.choice({
+                p.literal("```json") + p.space() + response_format + p.space() + p.literal("```"),
+                response_format
+            }) + p.end();
+        }
+
+        if (has_tools && inputs.tool_choice != COMMON_CHAT_TOOL_CHOICE_NONE && jinja_caps.supports_tool_calls) {
+            return tools.build_parser(ctx);
+        }
+
+        return content.build_parser(ctx);
+    });
+}
+
+common_peg_parser analyze_reasoning::build_parser(parser_build_context & ctx) const {
+    auto & p = ctx.p;
+
+    if (!ctx.extracting_reasoning) {
+        return p.eps();
+    }
+
+    bool thinking_forced_open   = (mode == reasoning_mode::FORCED_OPEN);
+    bool thinking_forced_closed = (mode == reasoning_mode::FORCED_CLOSED);
+
+    if (thinking_forced_open || thinking_forced_closed) {
+        // Thinking is forced open OR forced closed with enable_thinking=true
+        // In both cases, expect only the closing tag (opening was in template)
+        return p.reasoning(p.until(end)) + end;
+    }
+    if (mode == reasoning_mode::TAG_BASED || mode == reasoning_mode::TOOLS_ONLY) {
+        // Standard tag-based reasoning OR tools-only mode (reasoning appears with tools)
+        // Both use the same tag-based pattern if markers are available
+        if (!start.empty() && !end.empty()) {
+            return p.optional(start + p.reasoning(p.until(end)) + end);
+        }
+    } else if (mode == reasoning_mode::DELIMITER) {
+        return p.optional(p.reasoning(p.until(end)) + end);
+    }
+
+    return p.eps();
+}
+
+common_peg_parser analyze_content::build_parser(parser_build_context & ctx) const {
+    auto & p = ctx.p;
+
+    if (is_always_wrapped()) {
+        if (ctx.extracting_reasoning) {
+            return ctx.reasoning_parser + start + p.content(p.until(end)) + end + p.end();
+        }
+        return p.content(p.until(start)) + start + p.content(p.until(end)) + end + p.end();
+    }
+    return ctx.reasoning_parser + p.content(p.rest()) + p.end();
+}
+
+common_peg_parser analyze_content::build_optional_wrapped(parser_build_context & ctx) const {
+    auto & p = ctx.p;
+
+    if (is_always_wrapped()) {
+        return p.optional(start + p.content(p.until(end)) + end);
+    }
+    return p.eps();
+}
+
+common_peg_parser analyze_tools::build_parser(parser_build_context & ctx) const {
+    switch (format.mode) {
+        case tool_format::JSON_NATIVE:
+            return build_tool_parser_json_native(ctx);
+        case tool_format::TAG_WITH_JSON:
+            return build_tool_parser_tag_json(ctx);
+        case tool_format::TAG_WITH_TAGGED:
+            return build_tool_parser_tag_tagged(ctx);
+        default:
+            GGML_ABORT("Unable to create tool parser");
+    }
+}
+
+common_peg_parser analyze_tools::build_tool_parser_json_native(parser_build_context & ctx) const {
+    auto &       p           = ctx.p;
+    const auto & inputs      = ctx.inputs;
+    bool         force_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
+
+    // Build effective field names with dot notation if function_field is set
+    std::string name_field = format.name_field;
+    std::string args_field = format.args_field;
+
+    if (!format.function_field.empty() && format.function_field != "function" &&
+        name_field.find('.') == std::string::npos) {
+        name_field = format.function_field + "." + name_field;
+        args_field = format.function_field + "." + args_field;
+    }
+
+    auto tools_parser = p.standard_json_tools(
+        format.section_start, format.section_end, inputs.tools, inputs.parallel_tool_calls,
+        inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED, name_field, args_field, format.tools_array_wrapped,
+        format.fun_name_is_key, format.id_field, format.gen_id_field, format.parameter_order);
+
+    // Handle content wrappers if present
+    if (ctx.content && ctx.content->is_always_wrapped()) {
+        auto wrapped_content = ctx.content->build_optional_wrapped(ctx);
+        return ctx.reasoning_parser + wrapped_content + tools_parser + p.end();
+    }
+
+    std::string tool_start = "{";
+    if (!format.section_start.empty()) {
+        tool_start = format.section_start;
+    } else if (!format.per_call_start.empty()) {
+        tool_start = format.per_call_start;
+    }
+
+    return ctx.reasoning_parser + (force_tools ? p.eps() : p.optional(p.content(p.until(tool_start)))) + tools_parser +
+           p.end();
+}
+
+common_peg_parser analyze_tools::build_tool_parser_tag_json(parser_build_context & ctx) const {
+    auto &       p           = ctx.p;
+    const auto & inputs      = ctx.inputs;
+    bool         force_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
+
+    common_peg_parser tool_choice = p.choice();
+
+    foreach_function(inputs.tools, [&](const json & tool) {
+        const auto & func   = tool.at("function");
+        std::string  name   = func.at("name");
+        const auto & schema = func.at("parameters");
+
+        // Build call_id parser based on position (if supported)
+        common_peg_parser call_id_section = p.eps();
+        if (call_id.pos == call_id_position::BETWEEN_FUNC_AND_ARGS && !call_id.prefix.empty() &&
+            !call_id.suffix.empty()) {
+            call_id_section = p.optional(call_id.prefix + p.tool_id(p.until(call_id.suffix))) + call_id.suffix;
+        }
+
+        auto func_parser = p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
+                           call_id_section + p.tool_args(p.schema(p.json(), "tool-" + name + "-schema", schema));
+        if (!function.close.empty()) {
+            func_parser = func_parser + function.close;
+        }
+        tool_choice |= p.rule("tool-" + name, func_parser);
+    });
+
+    auto require_calls = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
+
+    common_peg_parser tool_calls = p.eps();
+
+    if (!format.per_call_start.empty()) {
+        auto wrapped_call = format.per_call_start + tool_choice + format.per_call_end;
+        if (inputs.parallel_tool_calls) {
+            tool_calls = p.trigger_rule("tool-call", wrapped_call + p.zero_or_more(p.space() + wrapped_call));
+        } else {
+            tool_calls = p.trigger_rule("tool-call", wrapped_call);
+        }
+        if (!format.section_start.empty()) {
+            tool_calls = p.trigger_rule("tool-calls",
+                                        p.literal(format.section_start) + p.space() + tool_calls + p.space() +
+                                            (format.section_end.empty() ? p.end() : p.literal(format.section_end)));
+        }
+    } else {
+        std::string separator = ", ";  // Default
+        if (inputs.parallel_tool_calls) {
+            tool_calls = p.trigger_rule("tool-call", format.section_start + tool_choice +
+                                                         p.zero_or_more(separator + tool_choice) + format.section_end);
+        } else {
+            tool_calls = p.trigger_rule("tool-call", format.section_start + tool_choice + format.section_end);
+        }
+    }
+
+    if (!require_calls) {
+        tool_calls = p.optional(tool_calls);
+    }
+
+    std::string trigger_marker       = !format.section_start.empty() ? format.section_start : format.per_call_start;
+    auto        content_before_tools = trigger_marker.empty() ? p.eps() : p.until(trigger_marker);
+    return ctx.reasoning_parser + (force_tools ? p.eps() : p.optional(p.content(content_before_tools))) + tool_calls +
+           p.end();
+}
+
+common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_context & ctx) const {
+    auto &       p           = ctx.p;
+    const auto & inputs      = ctx.inputs;
+    bool         force_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
+
+    common_peg_parser tool_choice = p.choice();
+
+    foreach_function(inputs.tools, [&](const json & tool) {
+        const auto & func   = tool.at("function");
+        std::string  name   = func.at("name");
+        const auto & params = func.at("parameters");
+
+        if (!params.contains("properties") || !params.at("properties").is_object()) {
+            return;
+        }
+
+        const auto &          properties = params.at("properties");
+        std::set<std::string> required;
+        if (params.contains("required") && params.at("required").is_array()) {
+            params.at("required").get_to(required);
+        }
+
+        // Build parser for each argument, separating required and optional
+        std::vector<common_peg_parser> required_parsers;
+        std::vector<common_peg_parser> optional_parsers;
+        for (const auto & [param_name, param_schema] : properties.items()) {
+            bool        is_required = required.find(param_name) != required.end();
+            std::string type        = "object";
+            auto        type_obj    = param_schema.contains("type") ? param_schema.at("type") : json::object();
+            if (type_obj.is_string()) {
+                type_obj.get_to(type);
+            } else if (type_obj.is_object()) {
+                if (type_obj.contains("type") && type_obj.at("type").is_string()) {
+                    type_obj.at("type").get_to(type);
+                }
+            }
+
+            auto arg = p.tool_arg(
+                p.tool_arg_open(arguments.name_prefix + p.tool_arg_name(p.literal(param_name)) +
+                                arguments.name_suffix) +
+                arguments.value_prefix +
+                (type == "string" ? p.tool_arg_string_value(p.schema(p.until(arguments.value_suffix),
+                                                                     "tool-" + name + "-arg-" + param_name + "-schema",
+                                                                     param_schema, true)) :
+                                    p.tool_arg_json_value(p.schema(
+                                        p.json(), "tool-" + name + "-arg-" + param_name + "-schema", param_schema, format.uses_python_dicts)) +
+                                        p.space()) +
+                p.tool_arg_close(p.literal(arguments.value_suffix)));
+
+            auto named_arg = p.rule("tool-" + name + "-arg-" + param_name, arg);
+            if (is_required) {
+                required_parsers.push_back(named_arg);
+            } else {
+                optional_parsers.push_back(named_arg);
+            }
+        }
+
+        // Build required arg sequence in definition order
+        common_peg_parser args_seq = p.eps();
+        for (size_t i = 0; i < required_parsers.size(); i++) {
+            if (i > 0) {
+                args_seq = args_seq + p.space();
+            }
+            args_seq = args_seq + required_parsers[i];
+        }
+
+        // Build optional args with flexible ordering
+        if (!optional_parsers.empty()) {
+            common_peg_parser any_opt = p.choice();
+            for (const auto & opt : optional_parsers) {
+                any_opt |= opt;
+            }
+            args_seq = args_seq + p.repeat(p.space() + any_opt, 0, (int) optional_parsers.size());
+        }
+
+        // Build call_id parser based on position (if supported)
+        common_peg_parser call_id_section = p.eps();
+        bool have_call_id = false;
+        if (call_id.pos == call_id_position::BETWEEN_FUNC_AND_ARGS && !call_id.prefix.empty() &&
+            !call_id.suffix.empty()) {
+            have_call_id = true;
+            call_id_section = p.optional(call_id.prefix + p.tool_id(p.until(call_id.suffix)) + call_id.suffix);
+        }
+
+        bool matched_atomic = false;
+        common_peg_parser func_parser = p.eps();
+        if (!function.name_suffix.empty()) {
+            func_parser = p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
+                call_id_section + p.space() + args_seq;
+            matched_atomic = true;
+        } else if (have_call_id) {
+            func_parser = p.atomic(p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
+                call_id_section) + p.space() + args_seq;
+            matched_atomic = true;
+        } else if (!arguments.name_prefix.empty() && properties.size() > 0) {
+            func_parser = p.atomic(p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
+                call_id_section + p.space() + p.peek(p.literal(arguments.name_prefix))) + args_seq;
+            matched_atomic = true;
+        } else {
+            func_parser = p.tool_open(function.name_prefix + p.tool_name(p.literal(name)) + function.name_suffix) +
+                call_id_section + p.space() + args_seq;
+        }
+
+        if (!function.close.empty()) {
+            func_parser = func_parser + p.space() + p.tool_close(p.literal(function.close));
+        } else if (!format.per_call_end.empty()) {
+            // When there's no func_close but there is a per_call_end marker, use peek() to ensure
+            // we only emit tool_close when we can actually see the closing marker. This prevents
+            // premature closing during partial parsing when we've seen e.g. "</" which could be
+            // either "</tool_call>" (end) or "<arg_key>" prefix that failed to match.
+            func_parser = func_parser + p.tool_close(p.peek(p.literal(format.per_call_end)));
+        } else {
+            func_parser =
+                func_parser + p.tool_close(p.space());  // force this to process tool closing callbacks in mapper
+        }
+        if (!matched_atomic) {
+            func_parser = p.atomic(func_parser);
+        }
+
+        tool_choice |= p.rule("tool-" + name, func_parser);
+    });
+
+    auto require_tools = inputs.tool_choice == COMMON_CHAT_TOOL_CHOICE_REQUIRED;
+
+    common_peg_parser tool_calls = p.eps();
+
+    if (!format.per_call_start.empty()) {
+        auto wrapped_call = format.per_call_start + p.space() + tool_choice + p.space() + format.per_call_end;
+        if (inputs.parallel_tool_calls) {
+            tool_calls = p.trigger_rule("tool-call", wrapped_call + p.zero_or_more(p.space() + wrapped_call));
+        } else {
+            tool_calls = p.trigger_rule("tool-call", wrapped_call);
+        }
+        if (!format.section_start.empty()) {
+            tool_calls = p.trigger_rule("tool-calls",
+                                        p.literal(format.section_start) + p.space() + tool_calls + p.space() +
+                                            (format.section_end.empty() ? p.end() : p.literal(format.section_end)));
+        }
+    } else {
+        std::string separator = ", ";  // Default
+
+        if (inputs.parallel_tool_calls) {
+            tool_calls = p.trigger_rule("tool-call", format.section_start + p.space() + tool_choice +
+                                                         p.zero_or_more(separator + tool_choice) + p.space() +
+                                                         format.section_end);
+        } else {
+            tool_calls = p.trigger_rule(
+                "tool-call", format.section_start + p.space() + tool_choice + p.space() + format.section_end);
+        }
+    }
+
+    if (!require_tools) {
+        tool_calls = p.optional(tool_calls);
+    }
+
+    std::string trigger_marker       = !format.section_start.empty() ? format.section_start : format.per_call_start;
+    auto        content_before_tools = trigger_marker.empty() ? p.eps() : p.until(trigger_marker);
+    return ctx.reasoning_parser + (force_tools ? p.eps() : p.optional(p.content(content_before_tools))) + tool_calls +
+           p.end();
+}
+
+}  // namespace autoparser

common/chat-auto-parser-helpers.cpp

@@ -0,0 +1,347 @@
+#include "chat-auto-parser-helpers.h"
+
+#include "chat-auto-parser.h"
+#include "chat.h"
+#include "log.h"
+#include "nlohmann/json.hpp"
+
+#include <cctype>
+#include <numeric>
+
+using json = nlohmann::ordered_json;
+
+std::string trim_whitespace(const std::string & str) {
+    size_t start = 0;
+    while (start < str.length() && std::isspace(static_cast<unsigned char>(str[start]))) {
+        start++;
+    }
+
+    if (start == str.length()) {
+        return "";
+    }
+
+    size_t end = str.length() - 1;
+    while (end > start && std::isspace(static_cast<unsigned char>(str[end]))) {
+        end--;
+    }
+
+    return str.substr(start, end - start + 1);
+}
+
+std::string trim_leading_whitespace(const std::string & str) {
+    size_t start = 0;
+    while (start < str.length() && std::isspace(static_cast<unsigned char>(str[start]))) {
+        start++;
+    }
+
+    return str.substr(start);
+}
+
+std::string trim_trailing_whitespace(const std::string & str) {
+    if (str.empty()) {
+        return "";
+    }
+
+    size_t end = str.length() - 1;
+    while (end > 0 && std::isspace(static_cast<unsigned char>(str[end]))) {
+        end--;
+    }
+
+    // If first char is also whitespace, return empty string
+    if (end == 0 && std::isspace(static_cast<unsigned char>(str[0]))) {
+        return "";
+    }
+
+    return str.substr(0, end + 1);
+}
+
+std::string trim_trailing_newlines(const std::string & str) {
+    size_t end = str.length();
+    while (end > 0 && str[end - 1] == '\n') {
+        end--;
+    }
+
+    return str.substr(0, end);
+}
+
+static size_t common_prefix_len(const std::string & left, const std::string & right) {
+    size_t prefix_len = 0;
+    size_t min_len    = std::min(left.length(), right.length());
+    while (prefix_len < min_len && left[prefix_len] == right[prefix_len]) {
+        prefix_len++;
+    }
+    return prefix_len;
+}
+
+static size_t common_suffix_len(const std::string & left, const std::string & right) {
+    size_t suffix_len = 0;
+    size_t min_len    = std::min(left.length(), right.length());
+    while (suffix_len < min_len && left[left.length() - 1 - suffix_len] == right[right.length() - 1 - suffix_len]) {
+        suffix_len++;
+    }
+    return suffix_len;
+}
+
+diff_split calculate_diff_split(const std::string & left, const std::string & right) {
+    diff_split result;
+
+    auto left_seg = segmentize_markers(left);
+    auto right_seg = segmentize_markers(right);
+
+    if (left_seg.empty()) {
+        result.right = right;
+        return result;
+    }
+    if (right_seg.empty()) {
+        result.left = left;
+        return result;
+    }
+
+    auto left_start = left_seg.begin();
+    auto left_end = --left_seg.end();
+    auto right_start = right_seg.begin();
+    auto right_end = --right_seg.end();
+
+    auto test = [&] () {
+        return left_start != left_end && right_start != right_end;
+    };
+
+    bool left_fully_consumed = false;
+    bool right_fully_consumed = false;
+
+    while (test()) {
+        bool advanced = false;
+        if (*left_start == *right_start) {
+            result.prefix.append(left_start->value);
+            left_start++;
+            right_start++;
+            advanced = true;
+        }
+        if (*left_end == *right_end) {
+            result.suffix = left_end->value + result.suffix;
+            if (left_start != left_end) {
+                left_end--;
+            } else {
+                left_fully_consumed = true;
+            }
+            if (right_start != right_end) {
+                right_end--;
+            } else {
+                right_fully_consumed = true;
+            }
+            advanced = true;
+        }
+        if (!advanced) {
+            break;
+        }
+    }
+
+    if (left_start == left_end && right_start != right_end) {
+        if (*left_start == *right_end) {
+            result.suffix = right_end->value + result.suffix;
+            right_end--;
+            left_fully_consumed = true;
+        } else if (*left_start == *right_start) {
+            result.prefix.append(right_start->value);
+            right_start++;
+            left_fully_consumed = true;
+        }
+    } else if (right_start == right_end && left_start != left_end) {
+        if (*left_end == *right_start) {
+            result.suffix = left_end->value + result.suffix;
+            left_end--;
+            right_fully_consumed = true;
+        } else if (*left_start == *right_start) {
+            result.prefix.append(left_start->value);
+            left_start++;
+            right_fully_consumed = true;
+        }
+    } else if (left_start == left_end && right_start == right_end && *left_start == *right_start && left_start->type == segment_type::MARKER) {
+        result.prefix.append(right_start->value);
+        left_fully_consumed = true;
+        right_fully_consumed = true;
+    }
+
+    auto eat_segment = [](std::string str, const segment & seg) -> std::string { return std::move(str) + seg.value; };
+
+    bool can_have_text_suffix = left_end->type == segment_type::TEXT && right_end->type == segment_type::TEXT;
+    bool can_have_text_prefix = right_start->type == segment_type::TEXT && left_start->type == segment_type::TEXT;
+
+    std::string remainder_left = std::accumulate(left_start, left_fully_consumed ? left_end : ++left_end, std::string(), eat_segment);
+    std::string remainder_right = std::accumulate(right_start, right_fully_consumed ? right_end : ++right_end, std::string(), eat_segment);
+
+    size_t suffix_len = can_have_text_suffix ? common_suffix_len(remainder_left, remainder_right) : 0;
+    // avoid overlaps between prefix and suffix
+    size_t prefix_len = can_have_text_prefix ? common_prefix_len(remainder_left.substr(0, remainder_left.size() - suffix_len),
+        remainder_right.substr(0, remainder_right.size() - suffix_len)) : 0;
+
+    result.prefix.append(remainder_left.substr(0, prefix_len));
+    result.suffix = remainder_left.substr(remainder_left.length() - suffix_len, suffix_len) + result.suffix;
+    result.left = remainder_left.substr(prefix_len, remainder_left.length() - prefix_len - suffix_len);
+    result.right = remainder_right.substr(prefix_len, remainder_right.length() - prefix_len - suffix_len);
+
+    if (result.left == "" && result.right == "") {
+        // degenerate case, no diff
+        result.prefix = left;
+        result.suffix = "";
+        // pick prefix = all as representation
+    }
+    return result;
+}
+
+// Returns the prefix of `full` up until the first occurrence of the common prefix of `left` and `right`
+std::string until_common_prefix(const std::string & full, const std::string & left, const std::string & right) {
+    // Find the common prefix of left and right
+    size_t common_prefix_len = 0;
+    size_t min_len           = std::min(left.length(), right.length());
+    while (common_prefix_len < min_len && left[common_prefix_len] == right[common_prefix_len]) {
+        common_prefix_len++;
+    }
+
+    // If there's no common prefix, return empty string
+    if (common_prefix_len == 0) {
+        return "";
+    }
+
+    // Find the common prefix in the full string
+    std::string common_prefix = left.substr(0, common_prefix_len);
+    size_t      pos           = full.find(common_prefix);
+
+    // If not found, return empty string
+    if (pos == std::string::npos) {
+        return "";
+    }
+
+    // Return everything before the common prefix
+    return full.substr(0, pos);
+}
+
+// Returns the suffix of `full` after the last occurrence of the common suffix of `left` and `right`
+std::string after_common_suffix(const std::string & full, const std::string & left, const std::string & right) {
+    // Find the common suffix of left and right (compare from the end)
+    size_t common_suffix_len = 0;
+    size_t min_len           = std::min(left.length(), right.length());
+    while (common_suffix_len < min_len &&
+           left[left.length() - 1 - common_suffix_len] == right[right.length() - 1 - common_suffix_len]) {
+        common_suffix_len++;
+    }
+
+    // If there's no common suffix, return empty string
+    if (common_suffix_len == 0) {
+        return "";
+    }
+
+    // Extract the common suffix
+    std::string common_suffix = left.substr(left.length() - common_suffix_len);
+
+    // Find the last occurrence of the common suffix in the full string
+    size_t pos = full.rfind(common_suffix);
+
+    // If not found, return empty string
+    if (pos == std::string::npos) {
+        return "";
+    }
+
+    // Return everything after the common suffix
+    return full.substr(pos + common_suffix_len);
+}
+
+// TODO: segmentize will treat a JSON array inside tags as a tag: <calls>[{ "fun": { ... } }]</calls> will be three markers
+// not too worried about that because it hasn't turned out as a problem anywhere, but noting here in case it will
+// Might have to put some restrictions on tag contents as well (like "no { }")
+std::vector<segment> segmentize_markers(const std::string & text) {
+    std::vector<segment> retval;
+    bool in_marker = false;
+    char marker_opener = '\0';
+
+    auto is_marker_opener = [](char c) -> bool { return c == '<' || c == '['; };
+    auto is_marker_closer = [](char op, char c) -> bool { return (op == '<' && c == '>') || (op == '[' && c == ']'); };
+
+    size_t last_border = 0;
+
+    for (size_t cur_pos = 0; cur_pos < text.length(); cur_pos++) {
+        if (!in_marker && is_marker_opener(text[cur_pos])) {
+            if (last_border < cur_pos) {
+                retval.push_back(segment(segment_type::TEXT, text.substr(last_border, cur_pos - last_border)));
+            }
+            last_border = cur_pos;
+            in_marker = true;
+            marker_opener = text[cur_pos];
+        } else if (in_marker && is_marker_closer(marker_opener, text[cur_pos])) {
+            // no need to check because last_border will always be smaller
+                retval.push_back(segment(segment_type::MARKER, text.substr(last_border, cur_pos - last_border + 1)));
+            last_border = cur_pos + 1;
+            in_marker = false;
+            marker_opener = '\0';
+        }
+    }
+    if (last_border < text.length()) {
+            retval.push_back(segment(segment_type::TEXT, text.substr(last_border)));
+    }
+    return retval;
+}
+
+std::vector<segment> prune_whitespace_segments(const std::vector<segment> & segments) {
+    std::vector<segment> result;
+    for (const auto & seg : segments) {
+        if (!trim_whitespace(seg.value).empty()) {
+            result.push_back(seg);
+        }
+    }
+    return result;
+}
+
+namespace autoparser {
+
+std::string apply_template(const common_chat_template & tmpl, const template_params & params) {
+    templates_params tmpl_params;
+    tmpl_params.messages              = params.messages;
+    tmpl_params.tools                 = params.tools;
+    tmpl_params.add_generation_prompt = params.add_generation_prompt;
+    tmpl_params.enable_thinking       = params.enable_thinking;
+
+    if (params.extra_context) {
+        tmpl_params.extra_context = *params.extra_context;
+    }
+    tmpl_params.extra_context["enable_thinking"] = params.enable_thinking;
+
+    try {
+        return common_chat_template_direct_apply(tmpl, tmpl_params);
+    } catch (const std::exception & e) {
+        LOG_DBG("Template application failed: %s\n", e.what());
+        return "";
+    }
+}
+
+std::optional<compare_variants_result> compare_variants(
+    const common_chat_template &                   tmpl,
+    const template_params &                        params_A,
+    const std::function<void(template_params &)> & params_modifier) {
+    // Create variant B by copying A
+    template_params params_B = params_A;
+
+    // Apply modifier to create variant B
+    if (params_modifier) {
+        params_modifier(params_B);
+    }
+
+    // Apply template to both variants
+    std::string output_A = apply_template(tmpl, params_A);
+    std::string output_B = apply_template(tmpl, params_B);
+
+    // Check for template application failures
+    if (output_A.empty() || output_B.empty()) {
+        return std::nullopt;
+    }
+
+    // Calculate diff and return result with both outputs
+    compare_variants_result result;
+    result.diff     = calculate_diff_split(output_A, output_B);
+    result.output_A = output_A;
+    result.output_B = output_B;
+
+    return result;
+}
+
+}  // namespace autoparser
+

common/chat-auto-parser-helpers.h

@@ -0,0 +1,73 @@
+#pragma once
+
+#include "chat-auto-parser.h"
+#include <functional>
+#include <optional>
+#include <string>
+
+std::string trim_whitespace(const std::string & str);
+std::string trim_leading_whitespace(const std::string & str);
+std::string trim_trailing_whitespace(const std::string & str);
+std::string trim_trailing_newlines(const std::string & str);
+
+// calculate a diff split (longest common prefix, longest common suffix excluding prefix,
+// mismatched part on the left, mismatched part on the right) between two strings
+// account for markers - align prefix and suffix endings so that they end on markers
+// * eg.:
+// calculate_diff_split("<html><body><div></div></body></html>", "<html><body><p>Something</p></body><html>") ->
+//  { "prefix": "<html><body>" (not: "<html><body><"), "suffix": "</body></html>", "left": "<div></div>", "right": "<p>Something</p>" }
+// calculate_diff_split("<html><body>Something</body></html>", "<html><body></body><html>") ->
+//  { "prefix": "<html><body>", "suffix": "</body></html>", "left": "Something", "right": "" }
+diff_split calculate_diff_split(const std::string & left, const std::string & right);
+
+// Returns the prefix of `full` up until the first occurrence of the common prefix of `left` and `right`
+// Returns empty string if there's no common prefix
+// * eg.:
+// until_common_prefix("really want a FUNCTION call", "FUNCTION alpha", "FUNCTION beta") -> "really want a "
+// until_common_prefix("<tool_call>", "<something>", "<something_else>") -> ""
+// until_common_prefix("some text", "1234", "abcd") -> ""
+// until_common_prefix("one arg two args three args four", "argument alpha", "argument beta") -> "one ""
+std::string until_common_prefix(const std::string & full, const std::string & left, const std::string & right);
+
+// Returns the suffix of `full` after the last occurrence of the common suffix of `left` and `right`
+// Returns empty string if there's no common suffix
+// Mirror function of `until_common_prefix`
+// * eg.:
+// after_common_suffix("really want a FUNCTION call", "first FUNCTION", "second FUNCTION") -> " call"
+// after_common_suffix("one arg two-args three args four", "alpha-args", "beta-args") -> " three args four"
+std::string after_common_suffix(const std::string & full, const std::string & left, const std::string & right);
+
+// Segmentize text into markers and non-marker fragments
+// * eg.:
+// segmentize_markers("<html><head><title>The site title</title><body><div>Here's some <b>content</b></div></body></html>" ->
+//  [ (MARKER, "<html>"), (MARKER, "<head>"), (MARKER, "<title>"), (TEXT, "The site title"), (MARKER, "</title>"),
+//    (MARKER, "<body>"), (MARKER, "<div>"), (TEXT, "Here's some "), (MARKER, "<b>"), (TEXT, "content"), (MARKER, "</b>"),
+//    (MARKER, "</div>"), (MARKER, "</body>"), (MARKER, "</html>")
+//  ]
+// segmentize_markers("<|tool_call|>[args]{ are here }[/args]<|tool_call_end|>") ->
+//  [ (MARKER, "<|tool_call|>"), (MARKER, "[args]"), (TEXT, "{ are here }"), (MARKER, "[/args]"), (MARKER, "<|tool_call_end|>") ]
+std::vector<segment> segmentize_markers(const std::string & text);
+
+// Prune whitespace-only segments from a vector of segments
+// * eg.:
+// segmentize_markers("<tool_call>\n<function=foo>\n<arg=bar>\n   \n</arg>\n</function>\n</tool_call>") ->
+//  X = [ (MARKER, "<tool_call>"), (TEXT, "\n"), (MARKER, "<function=foo>"), (TEXT, "\n"), (MARKER, "<arg=bar>"), (TEXT, "\n   \n"),
+//        (MARKER, "</arg>"), (TEXT, "\n"), (MARKER, "</function>"), (TEXT, "\n"), (MARKER, "</tool_call>") ]
+// prune_whitespace_segments(X) -> [ (MARKER, "<tool_call>"), (MARKER, "<function=foo>"), (MARKER, "<arg=bar>"), (MARKER, "</arg>"),
+//                                   (MARKER, "</function>"), (MARKER, "</tool_call>") ]
+std::vector<segment> prune_whitespace_segments(const std::vector<segment> & segments);
+
+namespace autoparser {
+
+// Apply a template with the given parameters, returning the rendered string (empty on failure)
+std::string apply_template(const common_chat_template & tmpl, const template_params & params);
+
+// Factorized differential comparison function
+// Takes base params and a single modifier lambda to create variant B
+// Returns compare_variants_result containing diff and both outputs, or std::nullopt on failure
+std::optional<compare_variants_result> compare_variants(
+    const common_chat_template &                   tmpl,
+    const template_params &                        params_A,
+    const std::function<void(template_params &)> & params_modifier);
+
+}  // namespace autoparser

common/chat-auto-parser.h

@@ -0,0 +1,433 @@
+#pragma once
+
+#include "chat.h"
+#include "common.h"
+#include "jinja/caps.h"
+#include "peg-parser.h"
+
+#include <chrono>
+#include <optional>
+#include <string>
+#include <utility>
+#include <vector>
+
+using json = nlohmann::ordered_json;
+
+class common_chat_peg_builder;
+
+// ============================================================================
+// Parameters for template application (low-level, used by diff analysis)
+// ============================================================================
+struct template_params {
+    json                messages;
+    json                tools;
+    bool                add_generation_prompt = false;
+    bool                enable_thinking       = true;
+    std::optional<json> extra_context         = std::nullopt;
+};
+
+struct diff_split {
+    std::string prefix;
+    std::string suffix;
+    std::string left;
+    std::string right;
+
+    bool operator==(struct diff_split & other) const {
+        return prefix == other.prefix && suffix == other.suffix && left == other.left && right == other.right;
+    }
+};
+
+// Result of compare_variants containing diff and original outputs
+struct compare_variants_result {
+    diff_split  diff;
+    std::string output_A;
+    std::string output_B;
+};
+
+namespace autoparser {
+
+// ============================================================================
+// High-level params for parser generation
+// ============================================================================
+
+struct templates_params {
+    json                                  messages;
+    json                                  tools;
+    common_chat_tool_choice               tool_choice = COMMON_CHAT_TOOL_CHOICE_AUTO;
+    json                                  json_schema;
+    bool                                  parallel_tool_calls = true;
+    common_reasoning_format               reasoning_format    = COMMON_REASONING_FORMAT_AUTO;
+    bool                                  stream              = true;
+    std::string                           grammar;
+    bool                                  add_generation_prompt = false;
+    bool                                  enable_thinking       = true;
+    std::chrono::system_clock::time_point now                   = std::chrono::system_clock::now();
+    json                                  extra_context;
+    bool                                  add_bos       = false;
+    bool                                  add_eos       = false;
+    bool                                  is_inference  = true;
+    bool                                  add_inference = false;
+    bool                                  mark_input    = true;  // whether to mark input strings in the jinja context
+};
+
+// ============================================================================
+// Analysis Result Enums
+// ============================================================================
+
+// Reasoning handling mode (derived from R1-R3 comparisons)
+enum class reasoning_mode {
+    NONE,           // No reasoning markers detected
+    TAG_BASED,      // Standard tag-based: <think>...</think>
+    DELIMITER,      // Delimiter-based: [BEGIN FINAL RESPONSE] (reasoning ends at delimiter)
+    FORCED_OPEN,    // Template ends with open reasoning tag (empty start, non-empty end)
+    FORCED_CLOSED,  // Template ends with open reasoning tag on enabled thinking but
+                    // with both opened and closed tag for disabled thinking
+    TOOLS_ONLY      // Only reason on tool calls, not on normal content
+};
+
+inline std::ostream & operator<<(std::ostream & os, const reasoning_mode & mode) {
+    switch (mode) {
+        case reasoning_mode::NONE:
+            return os << "NONE";
+        case reasoning_mode::TAG_BASED:
+            return os << "TAG_BASED";
+        case reasoning_mode::DELIMITER:
+            return os << "DELIMITER";
+        case reasoning_mode::FORCED_OPEN:
+            return os << "FORCED_OPEN";
+        case reasoning_mode::FORCED_CLOSED:
+            return os << "FORCED_CLOSED";
+        case reasoning_mode::TOOLS_ONLY:
+            return os << "TOOLS_ONLY";
+        default:
+            return os << "UNKNOWN";
+    }
+}
+
+// Content wrapping mode (derived from C1 comparison)
+enum class content_mode {
+    PLAIN,                   // No content markers
+    ALWAYS_WRAPPED,          // Content always wrapped with markers
+    WRAPPED_WITH_REASONING,  // Content wrapped only when reasoning present
+};
+
+inline std::ostream & operator<<(std::ostream & os, const content_mode & mode) {
+    switch (mode) {
+        case content_mode::PLAIN:
+            return os << "PLAIN";
+        case content_mode::ALWAYS_WRAPPED:
+            return os << "ALWAYS_WRAPPED";
+        case content_mode::WRAPPED_WITH_REASONING:
+            return os << "WRAPPED_WITH_REASONING";
+        default:
+            return os << "UNKNOWN";
+    }
+}
+
+// Call ID position in tool calls (for non-JSON formats)
+enum class call_id_position {
+    NONE,                   // No call ID support detected
+    PRE_FUNC_NAME,          // Call ID before function name: [CALL_ID]id[FUNC]name{args}
+    BETWEEN_FUNC_AND_ARGS,  // Call ID between function and args: [FUNC]name[CALL_ID]id{args}
+    POST_ARGS,              // Call ID after arguments: [FUNC]name{args}[CALL_ID]id
+};
+
+inline std::ostream & operator<<(std::ostream & os, const call_id_position & pos) {
+    switch (pos) {
+        case call_id_position::NONE:
+            return os << "NONE";
+        case call_id_position::PRE_FUNC_NAME:
+            return os << "PRE_FUNC_NAME";
+        case call_id_position::BETWEEN_FUNC_AND_ARGS:
+            return os << "BETWEEN_FUNC_AND_ARGS";
+        case call_id_position::POST_ARGS:
+            return os << "POST_ARGS";
+        default:
+            return os << "UNKNOWN";
+    }
+}
+
+// Tool call format classification (derived from T1-T5, A1-A3 comparisons)
+enum class tool_format {
+    NONE,             // No tool support detected
+    JSON_NATIVE,      // Pure JSON: {"name": "X", "arguments": {...}}
+    TAG_WITH_JSON,    // Tag-based with JSON args: <function=X>{...}</function>
+    TAG_WITH_TAGGED,  // Tag-based with tagged args: <param=key>value</param>
+};
+
+inline std::ostream & operator<<(std::ostream & os, const tool_format & format) {
+    switch (format) {
+        case tool_format::NONE:
+            return os << "NONE";
+        case tool_format::JSON_NATIVE:
+            return os << "JSON_NATIVE";
+        case tool_format::TAG_WITH_JSON:
+            return os << "TAG_WITH_JSON";
+        case tool_format::TAG_WITH_TAGGED:
+            return os << "TAG_WITH_TAGGED";
+        default:
+            return os << "UNKNOWN";
+    }
+}
+
+// ============================================================================
+// Sub-structs for tool analysis
+// ============================================================================
+
+struct tool_format_analysis {
+    tool_format mode = tool_format::NONE;
+
+    std::string section_start;   // e.g., "<tool_call>", "[TOOL_CALLS]", ""
+    std::string section_end;     // e.g., "</tool_call>", ""
+    std::string per_call_start;  // e.g., "<|tool_call_begin|>", "" (for multi-call templates)
+    std::string per_call_end;    // e.g., "<|tool_call_end|>", ""
+
+    bool fun_name_is_key = false;       // In JSON format function name is JSON key, i.e. { "<funname>": { ... arguments ... } }
+    bool tools_array_wrapped = false;   // Tool calls wrapped in JSON array [...]
+    bool uses_python_dicts = false;     // Tool call args use Python dict format (single-quoted strings)
+
+    std::string              function_field = "function";
+    std::string              name_field     = "name";
+    std::string              args_field     = "arguments";
+    std::string              id_field;
+    std::string              gen_id_field;
+    std::vector<std::string> parameter_order;
+};
+
+struct tool_function_analysis {
+    std::string name_prefix;  // e.g., "<function=", "\"name\": \"", "functions."
+    std::string name_suffix;  // e.g., ">", "\"", ":0"
+    std::string close;        // e.g., "</function>", "" (for tag-based)
+};
+
+struct tool_arguments_analysis {
+    std::string start;          // e.g., "<|tool_call_argument_begin|>", "<args>"
+    std::string end;            // e.g., "<|tool_call_argument_end|>", "</args>"
+    std::string name_prefix;   // e.g., "<param=", "<arg_key>", "\""
+    std::string name_suffix;   // e.g., ">", "</arg_key>", "\":"
+    std::string value_prefix;  // e.g., "", "<arg_value>", ""
+    std::string value_suffix;  // e.g., "</param>", "</arg_value>", ""
+    std::string separator;     // e.g., "", "\n", ","
+};
+
+struct tool_id_analysis {
+    call_id_position pos = call_id_position::NONE;
+
+    std::string prefix;  // e.g., "[CALL_ID]" (marker before call ID value)
+    std::string suffix;  // e.g., "" (marker after call ID value, before next section)
+};
+
+// ============================================================================
+// Parser build context (shared interface for build_parser methods)
+// ============================================================================
+
+struct analyze_content;
+
+struct parser_build_context {
+    common_chat_peg_builder & p;
+    const templates_params &          inputs;
+    common_peg_parser                 reasoning_parser;
+    bool                              extracting_reasoning = false;
+    const analyze_content *           content              = nullptr;
+
+    parser_build_context(common_chat_peg_builder & p, const templates_params & inputs);
+};
+
+// ============================================================================
+// Base class for analyzers with parser building
+// ============================================================================
+
+struct analyze_base {
+    virtual ~analyze_base() = default;
+    virtual common_peg_parser build_parser(parser_build_context & ctx) const = 0;
+
+  protected:
+    const common_chat_template * tmpl = nullptr;
+
+    analyze_base() = default;
+    explicit analyze_base(const common_chat_template & tmpl) : tmpl(&tmpl) {}
+};
+
+// ============================================================================
+// Reasoning analyzer
+// ============================================================================
+
+struct analyze_reasoning : analyze_base {
+    reasoning_mode mode = reasoning_mode::NONE;
+
+    std::string start;  // e.g., "<think>", "[THINK]", "<|START_THINKING|>", ""
+    std::string end;    // e.g., "</think>", "[BEGIN FINAL RESPONSE]", "<|END_THINKING|>"
+
+    analyze_reasoning() = default;
+    analyze_reasoning(const common_chat_template & tmpl, bool supports_tools);
+
+    common_peg_parser build_parser(parser_build_context & ctx) const override;
+
+  private:
+    // Look for reasoning markers in rendered content
+    void compare_reasoning_presence();
+
+    // Compare generation prompt with enable_thinking=true vs false
+    void compare_thinking_enabled();
+
+    // Check if reasoning is always possible or only in tool calls
+    void compare_reasoning_scope();
+};
+
+// ============================================================================
+// Content analyzer
+// ============================================================================
+
+struct analyze_content : analyze_base {
+    content_mode mode = content_mode::PLAIN;
+
+    std::string start;  // e.g., "<response>", ">>>all\n", ""
+    std::string end;    // e.g., "</response>", ""
+
+    bool requires_nonnull_content = false;
+
+    analyze_content() = default;
+    analyze_content(const common_chat_template & tmpl, const analyze_reasoning & reasoning);
+
+    common_peg_parser build_parser(parser_build_context & ctx) const override;
+
+    bool is_always_wrapped() const;
+    common_peg_parser build_optional_wrapped(parser_build_context & ctx) const;
+};
+
+// ============================================================================
+// Tool analyzer
+// ============================================================================
+
+struct analyze_tools : analyze_base {
+    tool_format_analysis    format;
+    tool_function_analysis  function;
+    tool_arguments_analysis arguments;
+    tool_id_analysis        call_id;
+
+    analyze_tools() = default;
+    analyze_tools(const common_chat_template & tmpl,
+                  const jinja::caps &          caps,
+                  const analyze_reasoning &    reasoning);
+
+    common_peg_parser build_parser(parser_build_context & ctx) const override;
+
+  private:
+    // Extract tool calling 'haystack' for further analysis and delegate further analysis based on format
+    void analyze_tool_calls(const analyze_reasoning & reasoning);
+
+    // Analyze format based on position of function and argument name in needle
+    void analyze_tool_call_format(const std::string &       haystack,
+                                  const std::string &       fun_name_needle,
+                                  const std::string &       arg_name_needle,
+                                  const analyze_reasoning & reasoning);
+
+    // Analyze specifics of JSON native format (entire tool call is a JSON object)
+    void analyze_tool_call_format_json_native(const std::string & clean_haystack,
+                                              const std::string & fun_name_needle,
+                                              const std::string & arg_name_needle);
+
+    // Analyze specifics of non-JSON native format (tags for function name or for function name and arguments)
+    void analyze_tool_call_format_non_json(const std::string & clean_haystack,
+                                           const std::string & fun_name_needle);
+
+    // Check for and extract specific per-call markers for non-native-JSON templates with parallel call support
+    void check_per_call_markers();
+
+    // Extract function name markers
+    void extract_function_markers();
+
+    // Delegates to separate functions for: separator analysis, argument name analysis, argument value analysis
+    void analyze_arguments();
+
+    // Extract argument name markers
+    void extract_argument_name_markers();
+
+    // Extract argument value markers
+    void extract_argument_value_markers();
+
+    // Extract argument separator, if specified (eg. <arg=foo>...</arg><sep><arg=bar>...</arg>)
+    void extract_argument_separator();
+
+    // Extract argument wrapper markers, if present (eg. '<args><arg=foo>...</arg><arg=bar>...</arg></args>')
+    void extract_args_markers();
+
+    // Extract call ID markers, if present
+    void extract_call_id_markers();
+
+    // Per-format tool parser builders
+    common_peg_parser build_tool_parser_json_native(parser_build_context & ctx) const;
+    common_peg_parser build_tool_parser_tag_json(parser_build_context & ctx) const;
+    common_peg_parser build_tool_parser_tag_tagged(parser_build_context & ctx) const;
+};
+
+// ============================================================================
+// Main autoparser class
+// ============================================================================
+
+struct autoparser {
+    jinja::caps          jinja_caps;
+    analyze_reasoning    reasoning;
+    analyze_content      content;
+    analyze_tools        tools;
+    bool                 analysis_complete = false;
+
+    // Preserved tokens for tokenizer (union of all non-empty markers)
+    std::vector<std::string> preserved_tokens;
+
+    autoparser() = default;
+
+    // Run full differential analysis on a template
+    void analyze_template(const common_chat_template & tmpl);
+
+    // Build the PEG parser for this template
+    common_peg_arena build_parser(const templates_params & inputs) const;
+
+  private:
+    // Collect tokens from entire analysis to preserve
+    void collect_preserved_tokens();
+};
+
+// ============================================================================
+// Parser generator
+// ============================================================================
+
+class peg_generator {
+  public:
+    static common_chat_params generate_parser(const common_chat_template &    tmpl,
+                                              const struct templates_params & inputs);
+
+    static common_chat_params generate_parser(const common_chat_template &    tmpl,
+                                              const struct templates_params & inputs,
+                                              const autoparser &              autoparser);
+};
+
+}  // namespace autoparser
+
+enum segment_type { TEXT, MARKER };
+
+inline std::ostream & operator<<(std::ostream & os, const segment_type & type) {
+    switch (type) {
+        case segment_type::TEXT:
+            return os << "TEXT";
+        case segment_type::MARKER:
+            return os << "MARKER";
+        default:
+            return os << "UNKNOWN";
+    }
+}
+
+struct segment {
+    segment_type type;
+    std::string  value;
+
+    segment(segment_type type, std::string value) : type(type), value(std::move(value)) {}
+
+    bool operator==(const segment & other) const {
+        return type == other.type && value == other.value;
+    }
+
+    bool operator!=(const segment & other) const {
+        return !(*this == other);
+    }
+};

common/chat-parser-xml-toolcall.cpp

@@ -1,879 +0,0 @@
-#include "chat.h"
-#include "chat-parser.h"
-#include "common.h"
-#include "json-partial.h"
-#include "json-schema-to-grammar.h"
-#include "log.h"
-#include "regex-partial.h"
-
-using json = nlohmann::ordered_json;
-
-class xml_toolcall_syntax_exception : public std::runtime_error {
-  public:
-    xml_toolcall_syntax_exception(const std::string & message) : std::runtime_error(message) {}
-};
-
-template<typename T>
-inline void sort_uniq(std::vector<T> &vec) {
-    std::sort(vec.begin(), vec.end());
-    vec.erase(std::unique(vec.begin(), vec.end()), vec.end());
-}
-
-template<typename T>
-inline bool all_space(const T &str) {
-    return std::all_of(str.begin(), str.end(), [](unsigned char ch) { return std::isspace(ch); });
-}
-
-static size_t utf8_truncate_safe(const std::string_view s) {
-    size_t len = s.size();
-    if (len == 0) return 0;
-    size_t i = len;
-    for (size_t back = 0; back < 4 && i > 0; ++back) {
-        --i;
-        unsigned char c = s[i];
-        if ((c & 0x80) == 0) {
-            return len;
-        } else if ((c & 0xC0) == 0xC0) {
-            size_t expected_len = 0;
-            if ((c & 0xE0) == 0xC0) expected_len = 2;
-            else if ((c & 0xF0) == 0xE0) expected_len = 3;
-            else if ((c & 0xF8) == 0xF0) expected_len = 4;
-            else return i;
-            if (len - i >= expected_len) {
-                return len;
-            } else {
-                return i;
-            }
-        }
-    }
-    return len - std::min(len, size_t(3));
-}
-
-inline void utf8_truncate_safe_resize(std::string &s) {
-    s.resize(utf8_truncate_safe(s));
-}
-
-inline std::string_view utf8_truncate_safe_view(const std::string_view s) {
-    return s.substr(0, utf8_truncate_safe(s));
-}
-
-static std::optional<common_chat_msg_parser::find_regex_result> try_find_2_literal_splited_by_spaces(common_chat_msg_parser & builder, const std::string & literal1, const std::string & literal2) {
-    if (literal1.size() == 0) return builder.try_find_literal(literal2);
-    const auto saved_pos = builder.pos();
-    while (auto res = builder.try_find_literal(literal1)) {
-        builder.consume_spaces();
-        const auto match_len = std::min(literal2.size(), builder.input().size() - builder.pos());
-        if (builder.input().compare(builder.pos(), match_len, literal2, 0, match_len) == 0) {
-            if (res->prelude.size() != res->groups[0].begin - saved_pos) {
-                res->prelude = builder.str({saved_pos, res->groups[0].begin});
-            }
-            builder.move_to(builder.pos() + match_len);
-            res->groups[0].end = builder.pos();
-            GGML_ASSERT(res->groups[0].begin != res->groups[0].end);
-            return res;
-        }
-        builder.move_to(res->groups[0].begin + 1);
-    }
-    builder.move_to(saved_pos);
-    return std::nullopt;
-}
-
-/**
- * make a GBNF that accept any strings except those containing any of the forbidden strings.
- */
-std::string make_gbnf_excluding(std::vector<std::string> forbids) {
-    constexpr auto charclass_escape = [](unsigned char c) -> std::string {
-        if (c == '\\' || c == ']' || c == '^' || c == '-') {
-            std::string s = "\\";
-            s.push_back((char)c);
-            return s;
-        }
-        if (isprint(c)) {
-            return std::string(1, (char)c);
-        }
-        char buf[16];
-        snprintf(buf, 15, "\\x%02X", c);
-        return std::string(buf);
-    };
-    constexpr auto build_expr = [charclass_escape](auto self, const std::vector<std::string>& forbids, int l, int r, int depth) -> std::string {
-        std::vector<std::pair<unsigned char, std::pair<int,int>>> children;
-        int i = l;
-        while (i < r) {
-            const std::string &s = forbids[i];
-            if ((int)s.size() == depth) {
-                ++i;
-                continue;
-            }
-            unsigned char c = (unsigned char)s[depth];
-            int j = i;
-            while (j < r && (int)forbids[j].size() > depth &&
-                   (unsigned char)forbids[j][depth] == c) {
-                ++j;
-            }
-            children.push_back({c, {i, j}});
-            i = j;
-        }
-        std::vector<std::string> alts;
-        if (!children.empty()) {
-            std::string cls;
-            for (auto &ch : children) cls += charclass_escape(ch.first);
-            alts.push_back(std::string("[^") + cls + "]");
-        }
-        for (auto &ch : children) {
-            std::string childExpr = self(self, forbids, ch.second.first, ch.second.second, depth+1);
-            if (!childExpr.empty()) {
-                std::string quoted_ch = "\"";
-                if (ch.first == '\\') quoted_ch += "\\\\";
-                else if (ch.first == '"') quoted_ch += "\\\"";
-                else if (isprint(ch.first)) quoted_ch.push_back(ch.first);
-                else {
-                    char buf[16];
-                    snprintf(buf, 15, "\\x%02X", ch.first);
-                    quoted_ch += buf;
-                }
-                quoted_ch += "\"";
-                std::string branch = quoted_ch + std::string(" ") + childExpr;
-                alts.push_back(branch);
-            }
-        }
-        if (alts.empty()) return "";
-        std::ostringstream oss;
-        oss << "( ";
-        for (size_t k = 0; k < alts.size(); ++k) {
-            if (k) oss << " | ";
-            oss << alts[k];
-        }
-        oss << " )";
-        return oss.str();
-    };
-    if (forbids.empty()) return "( . )*";
-    sort(forbids.begin(), forbids.end());
-    std::string expr = build_expr(build_expr, forbids, 0, forbids.size(), 0);
-    if (expr.empty()) {
-        std::string cls;
-        for (auto &s : forbids) if (!s.empty()) cls += charclass_escape((unsigned char)s[0]);
-        expr = std::string("( [^") + cls + "] )";
-    }
-    if (forbids.size() == 1)
-        return expr + "*";
-    else
-        return std::string("( ") + expr + " )*";
-}
-
-/**
- * Build grammar for xml-style tool call
- * form.scope_start and form.scope_end can be empty.
- * Requires data.format for model-specific hacks.
- */
-void build_grammar_xml_tool_call(common_chat_params & data, const json & tools, const struct xml_tool_call_format & form) {
-    GGML_ASSERT(!form.tool_start.empty());
-    GGML_ASSERT(!form.tool_sep.empty());
-    GGML_ASSERT(!form.key_start.empty());
-    GGML_ASSERT(!form.val_end.empty());
-    GGML_ASSERT(!form.tool_end.empty());
-
-    std::string key_val_sep = form.key_val_sep;
-    if (form.key_val_sep2) {
-        key_val_sep += "\n";
-        key_val_sep += *form.key_val_sep2;
-    }
-    GGML_ASSERT(!key_val_sep.empty());
-
-    if (tools.is_array() && !tools.empty()) {
-        data.grammar = build_grammar([&](const common_grammar_builder &builder) {
-            auto string_arg_val = form.last_val_end ?
-                    builder.add_rule("string-arg-val", make_gbnf_excluding({form.val_end, *form.last_val_end})) :
-                    builder.add_rule("string-arg-val", make_gbnf_excluding({form.val_end}));
-
-            std::vector<std::string> tool_rules;
-            for (const auto & tool : tools) {
-                if (!tool.contains("type") || tool.at("type") != "function" || !tool.contains("function")) {
-                    LOG_WRN("Skipping tool without function: %s", tool.dump(2).c_str());
-                    continue;
-                }
-                const auto & function = tool.at("function");
-                if (!function.contains("name") || !function.at("name").is_string()) {
-                    LOG_WRN("Skipping invalid function (invalid name): %s", function.dump(2).c_str());
-                    continue;
-                }
-                if (!function.contains("parameters") || !function.at("parameters").is_object()) {
-                    LOG_WRN("Skipping invalid function (invalid parameters): %s", function.dump(2).c_str());
-                    continue;
-                }
-                std::string name = function.at("name");
-                auto parameters = function.at("parameters");
-                builder.resolve_refs(parameters);
-
-                struct parameter_rule {
-                    std::string symbol_name;
-                    bool is_required;
-                };
-                std::vector<parameter_rule> arg_rules;
-                if (!parameters.contains("properties") || !parameters.at("properties").is_object()) {
-                    LOG_WRN("Skipping invalid function (invalid properties): %s", function.dump(2).c_str());
-                    continue;
-                } else {
-                    std::vector<std::string> requiredParameters;
-                    if (parameters.contains("required")) {
-                        try { parameters.at("required").get_to(requiredParameters); }
-                        catch (const std::runtime_error&) {
-                            LOG_WRN("Invalid function required parameters, ignoring: %s", function.at("required").dump(2).c_str());
-                        }
-                    }
-                    sort_uniq(requiredParameters);
-                    for (const auto & [key, value] : parameters.at("properties").items()) {
-                        std::string quoted_key = key;
-                        bool required = std::binary_search(requiredParameters.begin(), requiredParameters.end(), key);
-                        if (form.key_start.back() == '"' && key_val_sep[0] == '"') {
-                            quoted_key = gbnf_format_literal(key);
-                            quoted_key = quoted_key.substr(1, quoted_key.size() - 2);
-                        }
-                        arg_rules.push_back(parameter_rule {builder.add_rule("func-" + name + "-kv-" + key,
-                            gbnf_format_literal(form.key_start) + " " +
-                            gbnf_format_literal(quoted_key) + " " +
-                            gbnf_format_literal(key_val_sep) + " " +
-                            ((value.contains("type") && value["type"].is_string() && value["type"] == "string" && (!form.raw_argval || *form.raw_argval)) ?
-                                    (form.raw_argval ?
-                                            string_arg_val :
-                                            "( " + string_arg_val + " | " + builder.add_schema(name + "-arg-" + key, value) + " )"
-                                    ) :
-                                    builder.add_schema(name + "-arg-" + key, value)
-                            )
-                        ), required});
-                    }
-                }
-
-                auto next_arg_with_sep = builder.add_rule(name + "-last-arg-end", form.last_val_end ? gbnf_format_literal(*form.last_val_end) : gbnf_format_literal(form.val_end));
-                decltype(next_arg_with_sep) next_arg = "\"\"";
-                for (auto i = arg_rules.size() - 1; /* i >= 0 && */ i < arg_rules.size(); --i) {
-                    std::string include_this_arg = arg_rules[i].symbol_name + " " + next_arg_with_sep;
-                    next_arg = builder.add_rule(name + "-arg-after-" + std::to_string(i), arg_rules[i].is_required ?
-                            include_this_arg : "( " + include_this_arg + " ) | " + next_arg
-                    );
-                    include_this_arg = gbnf_format_literal(form.val_end) + " " + include_this_arg;
-                    next_arg_with_sep = builder.add_rule(name + "-arg-after-" + std::to_string(i) + "-with-sep", arg_rules[i].is_required ?
-                            include_this_arg : "( " + include_this_arg + " ) | " + next_arg_with_sep
-                    );
-                }
-
-                std::string quoted_name = name;
-                if (form.tool_start.back() == '"' && form.tool_sep[0] == '"') {
-                    quoted_name = gbnf_format_literal(name);
-                    quoted_name = quoted_name.substr(1, quoted_name.size() - 2);
-                }
-                quoted_name = gbnf_format_literal(quoted_name);
-                // Kimi-K2 uses functions.{{ tool_call['function']['name'] }}:{{ loop.index }} as function name
-                if (data.format == COMMON_CHAT_FORMAT_KIMI_K2) {
-                    quoted_name = "\"functions.\" " + quoted_name + " \":\" [0-9]+";
-                }
-                tool_rules.push_back(builder.add_rule(name + "-call",
-                        gbnf_format_literal(form.tool_start) + " " +
-                        quoted_name + " " +
-                        gbnf_format_literal(form.tool_sep) + " " +
-                        next_arg
-                ));
-            }
-
-            auto tool_call_once = builder.add_rule("root-tool-call-once", string_join(tool_rules, " | "));
-            auto tool_call_more = builder.add_rule("root-tool-call-more", gbnf_format_literal(form.tool_end) + " " + tool_call_once);
-            auto call_end = builder.add_rule("root-call-end", form.last_tool_end ? gbnf_format_literal(*form.last_tool_end) : gbnf_format_literal(form.tool_end));
-            auto tool_call_multiple_with_end = builder.add_rule("root-tool-call-multiple-with-end", tool_call_once + " " + tool_call_more + "* " + call_end);
-            builder.add_rule("root",
-                (form.scope_start.empty() ? "" : gbnf_format_literal(form.scope_start) + " ") +
-                tool_call_multiple_with_end  + "?" +
-                (form.scope_end.empty() ? "" : " " + gbnf_format_literal(form.scope_end))
-            );
-        });
-
-        // grammar trigger for tool call
-        data.grammar_triggers.push_back({ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, form.scope_start + form.tool_start });
-    }
-}
-
-/**
- * Parse XML-Style tool call for given xml_tool_call_format. Return false for invalid syntax and get the position untouched.
- * Throws xml_toolcall_syntax_exception if there is invalid syntax and cannot recover the original status for common_chat_msg_parser.
- * form.scope_start, form.tool_sep and form.scope_end can be empty.
- */
-inline bool parse_xml_tool_calls(common_chat_msg_parser & builder, const struct xml_tool_call_format & form) {
-    GGML_ASSERT(!form.tool_start.empty());
-    GGML_ASSERT(!form.key_start.empty());
-    GGML_ASSERT(!form.key_val_sep.empty());
-    GGML_ASSERT(!form.val_end.empty());
-    GGML_ASSERT(!form.tool_end.empty());
-
-    // Helper to choose return false or throw error
-    constexpr auto return_error = [](common_chat_msg_parser & builder, auto &start_pos, const bool &recovery) {
-        LOG_DBG("Failed to parse XML-Style tool call at position: %s\n", gbnf_format_literal(builder.consume_rest().substr(0, 20)).c_str());
-        if (recovery) {
-            builder.move_to(start_pos);
-            return false;
-        } else throw xml_toolcall_syntax_exception("Tool call parsing failed with unrecoverable errors. Try using a grammar to constrain the model’s output.");
-    };
-    // Drop substring from needle to end from a JSON
-    constexpr auto partial_json = [](std::string &json_str, std::string_view needle = "XML_TOOL_CALL_PARTIAL_FLAG") {
-        auto pos = json_str.rfind(needle);
-        if (pos == std::string::npos) {
-            return false;
-        }
-        for (auto i = pos + needle.size(); i < json_str.size(); ++i) {
-            unsigned char ch = static_cast<unsigned char>(json_str[i]);
-            if (ch != '\'' && ch != '"' && ch != '}' && ch != ':' && !std::isspace(ch)) {
-                return false;
-            }
-        }
-        if (pos != 0 && json_str[pos - 1] == '"') {
-            --pos;
-        }
-        json_str.resize(pos);
-        return true;
-    };
-    // Helper to generate a partial argument JSON
-    constexpr auto gen_partial_json = [partial_json](auto set_partial_arg, auto &arguments, auto &builder, auto &function_name) {
-        auto rest = builder.consume_rest();
-        utf8_truncate_safe_resize(rest);
-        set_partial_arg(rest, "XML_TOOL_CALL_PARTIAL_FLAG");
-        auto tool_str = arguments.dump();
-        if (partial_json(tool_str)) {
-            if (builder.add_tool_call(function_name, "", tool_str)) {
-                return;
-            }
-        }
-        LOG_DBG("Failed to parse partial XML-Style tool call, fallback to non-partial: %s\n", tool_str.c_str());
-    };
-    // Helper to find a close (because there may be form.last_val_end or form.last_tool_end)
-    constexpr auto try_find_close = [](
-            common_chat_msg_parser & builder,
-            const std::string & end,
-            const std::optional<std::string> & alt_end,
-            const std::string & end_next,
-            const std::optional<std::string> & alt_end_next
-    ) {
-        auto saved_pos = builder.pos();
-        auto tc = builder.try_find_literal(end);
-        auto val_end_size = end.size();
-        if (alt_end) {
-            auto pos_1 = builder.pos();
-            builder.move_to(saved_pos);
-            auto tc2 = try_find_2_literal_splited_by_spaces(builder, *alt_end, end_next);
-            if (alt_end_next) {
-                builder.move_to(saved_pos);
-                auto tc3 = try_find_2_literal_splited_by_spaces(builder, *alt_end, *alt_end_next);
-                if (tc3 && (!tc2 || tc2->prelude.size() > tc3->prelude.size())) {
-                    tc2 = tc3;
-                }
-            }
-            if (tc2 && (!tc || tc->prelude.size() > tc2->prelude.size())) {
-                tc = tc2;
-                tc->groups[0].end = std::min(builder.input().size(), tc->groups[0].begin + alt_end->size());
-                builder.move_to(tc->groups[0].end);
-                val_end_size = alt_end->size();
-            } else {
-                builder.move_to(pos_1);
-            }
-        }
-        return std::make_pair(val_end_size, tc);
-    };
-    // Helper to find a val_end or last_val_end, returns matched pattern size
-    const auto try_find_val_end = [try_find_close, &builder, &form]() {
-        return try_find_close(builder, form.val_end, form.last_val_end, form.tool_end, form.last_tool_end);
-    };
-    // Helper to find a tool_end or last_tool_end, returns matched pattern size
-    const auto try_find_tool_end = [try_find_close, &builder, &form]() {
-        return try_find_close(builder, form.tool_end, form.last_tool_end, form.scope_end, std::nullopt);
-    };
-
-    bool recovery = true;
-    const auto start_pos = builder.pos();
-    if (!all_space(form.scope_start)) {
-        if (auto tc = builder.try_find_literal(form.scope_start)) {
-            if (all_space(tc->prelude)) {
-                if (form.scope_start.size() != tc->groups[0].end - tc->groups[0].begin)
-                    throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(form.scope_start));
-            } else {
-                builder.move_to(start_pos);
-                return false;
-            }
-        } else return false;
-    }
-    while (auto tc = builder.try_find_literal(form.tool_start)) {
-        if (!all_space(tc->prelude)) {
-            LOG_DBG("XML-Style tool call: Expected %s, but found %s, trying to match next pattern\n",
-                    gbnf_format_literal(form.tool_start).c_str(),
-                    gbnf_format_literal(tc->prelude).c_str()
-            );
-            builder.move_to(tc->groups[0].begin - tc->prelude.size());
-            break;
-        }
-
-        // Find tool name
-        auto func_name = builder.try_find_literal(all_space(form.tool_sep) ? form.key_start : form.tool_sep);
-        if (!func_name) {
-            auto [sz, tc] = try_find_tool_end();
-            func_name = tc;
-        }
-        if (!func_name) {
-            // Partial tool name not supported
-            throw common_chat_msg_partial_exception("incomplete tool_call");
-        }
-        // If the model generate multiple tool call and the first tool call has no argument
-        if (func_name->prelude.find(form.tool_end) != std::string::npos || (form.last_tool_end ? func_name->prelude.find(*form.last_tool_end) != std::string::npos : false)) {
-            builder.move_to(func_name->groups[0].begin - func_name->prelude.size());
-            auto [sz, tc] = try_find_tool_end();
-            func_name = tc;
-        }
-
-        // Parse tool name
-        builder.move_to(all_space(form.tool_sep) ? func_name->groups[0].begin : func_name->groups[0].end);
-        std::string function_name = string_strip(func_name->prelude);
-        // Kimi-K2 uses functions.{{ tool_call['function']['name'] }}:{{ loop.index }} as function name
-        if (builder.syntax().format == COMMON_CHAT_FORMAT_KIMI_K2) {
-            if (string_starts_with(function_name, "functions.")) {
-                static const std::regex re(":\\d+$");
-                if (std::regex_search(function_name, re)) {
-                    function_name = function_name.substr(10, function_name.rfind(":") - 10);
-                }
-            }
-        }
-
-        // Argument JSON
-        json arguments = json::object();
-
-        // Helper to generate a partial argument JSON
-        const auto gen_partial_args = [&](auto set_partial_arg) {
-            gen_partial_json(set_partial_arg, arguments, builder, function_name);
-        };
-
-        // Parse all arg_key/arg_value pairs
-        while (auto tc = builder.try_find_literal(form.key_start)) {
-            if (!all_space(tc->prelude)) {
-                LOG_DBG("XML-Style tool call: Expected %s, but found %s, trying to match next pattern\n",
-                        gbnf_format_literal(form.key_start).c_str(),
-                        gbnf_format_literal(tc->prelude).c_str()
-                );
-                builder.move_to(tc->groups[0].begin - tc->prelude.size());
-                break;
-            }
-            if (tc->groups[0].end - tc->groups[0].begin != form.key_start.size()) {
-                auto tool_call_arg = arguments.dump();
-                if (tool_call_arg.size() != 0 && tool_call_arg[tool_call_arg.size() - 1] == '}') {
-                    tool_call_arg.resize(tool_call_arg.size() - 1);
-                }
-                builder.add_tool_call(function_name, "", tool_call_arg);
-                throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(form.key_start));
-            }
-
-            // Parse arg_key
-            auto key_res = builder.try_find_literal(form.key_val_sep);
-            if (!key_res) {
-                gen_partial_args([&](auto &rest, auto &needle) {arguments[rest + needle] = "";});
-                throw common_chat_msg_partial_exception("Expected " + gbnf_format_literal(form.key_val_sep) + " after " + gbnf_format_literal(form.key_start));
-            }
-            if (key_res->groups[0].end - key_res->groups[0].begin != form.key_val_sep.size()) {
-                gen_partial_args([&](auto &, auto &needle) {arguments[key_res->prelude + needle] = "";});
-                throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(form.key_val_sep));
-            }
-            auto &key = key_res->prelude;
-            recovery = false;
-
-            // Parse arg_value
-            if (form.key_val_sep2) {
-                if (auto tc = builder.try_find_literal(*form.key_val_sep2)) {
-                    if (!all_space(tc->prelude)) {
-                        LOG_DBG("Failed to parse XML-Style tool call: Unexcepted %s between %s and %s\n",
-                                gbnf_format_literal(tc->prelude).c_str(),
-                                gbnf_format_literal(form.key_val_sep).c_str(),
-                                gbnf_format_literal(*form.key_val_sep2).c_str()
-                        );
-                        return return_error(builder, start_pos, false);
-                    }
-                    if (tc->groups[0].end - tc->groups[0].begin != form.key_val_sep2->size()) {
-                        gen_partial_args([&](auto &, auto &needle) {arguments[key] = needle;});
-                        throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(*form.key_val_sep2));
-                    }
-                } else {
-                    gen_partial_args([&](auto &, auto &needle) {arguments[key] = needle;});
-                    throw common_chat_msg_partial_exception("Expected " + gbnf_format_literal(*form.key_val_sep2) + " after " + gbnf_format_literal(form.key_val_sep));
-                }
-            }
-            auto val_start = builder.pos();
-
-            // Test if arg_val is a partial JSON
-            std::optional<common_json> value_json = std::nullopt;
-            if (!form.raw_argval || !*form.raw_argval) {
-                try { value_json = builder.try_consume_json(); }
-                catch (const std::runtime_error&) { builder.move_to(val_start); }
-                // TODO: Delete this when json_partial adds top-level support for null/true/false
-                if (builder.pos() == val_start) {
-                    const static std::regex number_regex(R"([0-9-][0-9]*(\.\d*)?([eE][+-]?\d*)?)");
-                    builder.consume_spaces();
-                    std::string_view sv = utf8_truncate_safe_view(builder.input());
-                    sv.remove_prefix(builder.pos());
-                    std::string rest = "a";
-                    if (sv.size() < 6) rest = sv;
-                    if (string_starts_with("null", rest) || string_starts_with("true", rest) || string_starts_with("false", rest) || std::regex_match(sv.begin(), sv.end(), number_regex)) {
-                        value_json = {123, {"123", "123"}};
-                        builder.consume_rest();
-                    } else {
-                        builder.move_to(val_start);
-                    }
-                }
-            }
-
-            // If it is a JSON and followed by </arg_value>, parse as json
-            // cannot support streaming because it may be a plain text starting with JSON
-            if (value_json) {
-                auto json_end = builder.pos();
-                builder.consume_spaces();
-                if (builder.pos() == builder.input().size()) {
-                    if (form.raw_argval && !*form.raw_argval && (value_json->json.is_string() || value_json->json.is_object() || value_json->json.is_array())) {
-                        arguments[key] = value_json->json;
-                        auto json_str = arguments.dump();
-                        if (!value_json->healing_marker.json_dump_marker.empty()) {
-                            GGML_ASSERT(std::string::npos != json_str.rfind(value_json->healing_marker.json_dump_marker));
-                            json_str.resize(json_str.rfind(value_json->healing_marker.json_dump_marker));
-                        } else {
-                            GGML_ASSERT(json_str.back() == '}');
-                            json_str.resize(json_str.size() - 1);
-                        }
-                        builder.add_tool_call(function_name, "", json_str);
-                    } else {
-                        gen_partial_args([&](auto &, auto &needle) {arguments[key] = needle;});
-                    }
-                    LOG_DBG("Possible JSON arg_value: %s\n", value_json->json.dump().c_str());
-                    throw common_chat_msg_partial_exception("JSON arg_value detected. Waiting for more tokens for validations.");
-                }
-                builder.move_to(json_end);
-                auto [val_end_size, tc] = try_find_val_end();
-                if (tc && all_space(tc->prelude) && value_json->healing_marker.marker.empty()) {
-                    if (tc->groups[0].end - tc->groups[0].begin != val_end_size) {
-                        gen_partial_args([&](auto &, auto &needle) {arguments[key] = needle;});
-                        LOG_DBG("Possible terminated JSON arg_value: %s\n", value_json->json.dump().c_str());
-                        throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(form.val_end) + (form.last_val_end ? gbnf_format_literal(*form.last_val_end) : ""));
-                    } else arguments[key] = value_json->json;
-                } else builder.move_to(val_start);
-            }
-
-            // If not, parse as plain text
-            if (val_start == builder.pos()) {
-                if (auto [val_end_size, value_plain] = try_find_val_end(); value_plain) {
-                    auto &value_str = value_plain->prelude;
-                    if (form.trim_raw_argval) value_str = string_strip(value_str);
-                    if (value_plain->groups[0].end - value_plain->groups[0].begin != val_end_size) {
-                        gen_partial_args([&](auto &, auto &needle) {arguments[key] = value_str + needle;});
-                        throw common_chat_msg_partial_exception(
-                                "Expected " + gbnf_format_literal(form.val_end) +
-                                " after " + gbnf_format_literal(form.key_val_sep) +
-                                (form.key_val_sep2 ? " " + gbnf_format_literal(*form.key_val_sep2) : "")
-                        );
-                    }
-                    arguments[key] = value_str;
-                } else {
-                    if (form.trim_raw_argval) {
-                        gen_partial_args([&](auto &rest, auto &needle) {arguments[key] = string_strip(rest) + needle;});
-                    } else {
-                        gen_partial_args([&](auto &rest, auto &needle) {arguments[key] = rest + needle;});
-                    }
-                    throw common_chat_msg_partial_exception(
-                            "Expected " + gbnf_format_literal(form.val_end) +
-                            " after " + gbnf_format_literal(form.key_val_sep) +
-                            (form.key_val_sep2 ? " " + gbnf_format_literal(*form.key_val_sep2) : "")
-                    );
-                }
-            }
-        }
-
-        // Consume closing tag
-        if (auto [tool_end_size, tc] = try_find_tool_end(); tc) {
-            if (!all_space(tc->prelude)) {
-                LOG_DBG("Failed to parse XML-Style tool call: Expected %s, but found %s\n",
-                        gbnf_format_literal(form.tool_end).c_str(),
-                        gbnf_format_literal(tc->prelude).c_str()
-                );
-                return return_error(builder, start_pos, recovery);
-            }
-            if (tc->groups[0].end - tc->groups[0].begin == tool_end_size) {
-                // Add the parsed tool call
-                if (!builder.add_tool_call(function_name, "", arguments.dump())) {
-                    throw common_chat_msg_partial_exception("Failed to add XML-Style tool call");
-                }
-                recovery = false;
-                continue;
-            }
-        }
-
-        auto tool_call_arg = arguments.dump();
-        if (tool_call_arg.size() != 0 && tool_call_arg[tool_call_arg.size() - 1] == '}') {
-            tool_call_arg.resize(tool_call_arg.size() - 1);
-        }
-        builder.add_tool_call(function_name, "", tool_call_arg);
-        throw common_chat_msg_partial_exception("Expected " + gbnf_format_literal(form.tool_end) + " after " + gbnf_format_literal(form.val_end));
-    }
-    if (auto tc = builder.try_find_literal(form.scope_end)) {
-        if (!all_space(tc->prelude)) {
-            LOG_DBG("Failed to parse XML-Style tool call: Expected %s, but found %s\n",
-                    gbnf_format_literal(form.scope_end).c_str(),
-                    gbnf_format_literal(tc->prelude).c_str()
-            );
-            return return_error(builder, start_pos, recovery);
-        }
-    } else {
-        if (all_space(form.scope_end)) return true;
-        builder.consume_spaces();
-        if (builder.pos() == builder.input().size())
-            throw common_chat_msg_partial_exception("incomplete tool calls");
-        LOG_DBG("Failed to parse XML-Style tool call: Expected %s, but found %s\n",
-                gbnf_format_literal(form.scope_end).c_str(),
-                gbnf_format_literal(builder.consume_rest()).c_str()
-        );
-        return return_error(builder, start_pos, recovery);
-    }
-
-    return true;
-}
-
-/**
- * Parse XML-Style tool call for given xml_tool_call_format. Return false for invalid syntax and get the position untouched.
- * May cause std::runtime_error if there is invalid syntax because partial valid tool call is already sent out to client.
- * form.scope_start, form.tool_sep and form.scope_end can be empty.
- */
-bool common_chat_msg_parser::try_consume_xml_tool_calls(const struct xml_tool_call_format & form) {
-    auto pos = pos_;
-    auto tsize = result_.tool_calls.size();
-    try { return parse_xml_tool_calls(*this, form); }
-    catch (const xml_toolcall_syntax_exception&) {}
-    move_to(pos);
-    result_.tool_calls.resize(tsize);
-    return false;
-}
-
-/**
- * Parse content uses reasoning and XML-Style tool call
- * TODO: Note that form.allow_toolcall_in_think is not tested yet. If anyone confirms it works, this comment can be removed.
- */
-inline void parse_msg_with_xml_tool_calls(common_chat_msg_parser & builder, const struct xml_tool_call_format & form, const std::string & start_think = "<think>", const std::string & end_think = "</think>") {
-    constexpr auto rstrip = [](std::string &s) {
-        s.resize(std::distance(s.begin(), std::find_if(s.rbegin(), s.rend(), [](unsigned char ch) { return !std::isspace(ch); }).base()));
-    };
-    // Erase substring from l to r, along with additional spaces nearby
-    constexpr auto erase_spaces = [](auto &str, size_t l, size_t r) {
-        while (/* l > -1 && */ --l < str.size() && std::isspace(static_cast<unsigned char>(str[l])));
-        ++l;
-        while (++r < str.size() && std::isspace(static_cast<unsigned char>(str[r])));
-        if (l < r) str[l] = '\n';
-        if (l + 1 < r) str[l + 1] = '\n';
-        if (l != 0) l += 2;
-        str.erase(l, r - l);
-        return l;
-    };
-    constexpr auto trim_suffix = [](std::string &content, std::initializer_list<std::string_view> list) {
-        auto best_match = content.size();
-        for (auto pattern: list) {
-            if (pattern.size() == 0) continue;
-            for (auto match_idx = content.size() - std::min(pattern.size(), content.size()); content.size() > match_idx; match_idx++) {
-                auto match_len = content.size() - match_idx;
-                if (content.compare(match_idx, match_len, pattern.data(), match_len) == 0 && best_match > match_idx) {
-                    best_match = match_idx;
-                }
-            }
-        }
-        if (content.size() > best_match) {
-            content.erase(best_match);
-        }
-    };
-    const auto trim_potential_partial_word = [&start_think, &end_think, &form, trim_suffix](std::string &content) {
-        return trim_suffix(content, {
-            start_think, end_think, form.scope_start, form.tool_start, form.tool_sep, form.key_start,
-            form.key_val_sep, form.key_val_sep2 ? form.key_val_sep2->c_str() : "",
-            form.val_end, form.last_val_end ? form.last_val_end->c_str() : "",
-            form.tool_end, form.last_tool_end ? form.last_tool_end->c_str() : "",
-            form.scope_end
-        });
-    };
-
-
-    // Trim leading spaces without affecting keyword matching
-    static const common_regex spaces_regex("\\s*");
-    {
-        auto tc = builder.consume_regex(spaces_regex);
-        auto spaces = builder.str(tc.groups[0]);
-        auto s1 = spaces.size();
-        trim_potential_partial_word(spaces);
-        auto s2 = spaces.size();
-        builder.move_to(builder.pos() - (s1 - s2));
-    }
-
-    // Parse content
-    bool reasoning_unclosed = builder.syntax().thinking_forced_open;
-    std::string unclosed_reasoning_content("");
-    for (;;) {
-        auto tc = try_find_2_literal_splited_by_spaces(builder, form.scope_start, form.tool_start);
-        std::string content;
-        std::string tool_call_start;
-
-        if (tc) {
-            content = std::move(tc->prelude);
-            tool_call_start = builder.str(tc->groups[0]);
-            LOG_DBG("Matched tool start: %s\n", gbnf_format_literal(tool_call_start).c_str());
-        } else {
-            content = builder.consume_rest();
-            utf8_truncate_safe_resize(content);
-        }
-
-        // Handle unclosed think block
-        if (reasoning_unclosed) {
-            if (auto pos = content.find(end_think); pos == std::string::npos && builder.pos() != builder.input().size()) {
-                unclosed_reasoning_content += content;
-                if (!(form.allow_toolcall_in_think && tc)) {
-                    unclosed_reasoning_content += tool_call_start;
-                    continue;
-                }
-            } else {
-                reasoning_unclosed = false;
-                std::string reasoning_content;
-                if (pos == std::string::npos) {
-                    reasoning_content = std::move(content);
-                } else {
-                    reasoning_content = content.substr(0, pos);
-                    content.erase(0, pos + end_think.size());
-                }
-                if (builder.pos() == builder.input().size() && all_space(content)) {
-                    rstrip(reasoning_content);
-                    trim_potential_partial_word(reasoning_content);
-                    rstrip(reasoning_content);
-                    if (reasoning_content.empty()) {
-                        rstrip(unclosed_reasoning_content);
-                        trim_potential_partial_word(unclosed_reasoning_content);
-                        rstrip(unclosed_reasoning_content);
-                        if (unclosed_reasoning_content.empty()) continue;
-                    }
-                }
-                if (builder.syntax().reasoning_format == COMMON_REASONING_FORMAT_NONE || builder.syntax().reasoning_in_content) {
-                    builder.add_content(start_think);
-                    builder.add_content(unclosed_reasoning_content);
-                    builder.add_content(reasoning_content);
-                    if (builder.pos() != builder.input().size() || !all_space(content))
-                        builder.add_content(end_think);
-                } else {
-                    builder.add_reasoning_content(unclosed_reasoning_content);
-                    builder.add_reasoning_content(reasoning_content);
-                }
-                unclosed_reasoning_content.clear();
-            }
-        }
-
-        // Handle multiple think block
-        bool toolcall_in_think = false;
-        for (auto think_start = content.find(start_think); think_start != std::string::npos; think_start = content.find(start_think, think_start)) {
-            if (auto think_end = content.find(end_think, think_start + start_think.size()); think_end != std::string::npos) {
-                if (builder.syntax().reasoning_format != COMMON_REASONING_FORMAT_NONE && !builder.syntax().reasoning_in_content) {
-                    auto reasoning_content = content.substr(think_start + start_think.size(), think_end - think_start - start_think.size());
-                    builder.add_reasoning_content(reasoning_content);
-                    think_start = erase_spaces(content, think_start, think_end + end_think.size() - 1);
-                } else {
-                    think_start = think_end + end_think.size() - 1;
-                }
-            } else {
-                // This <tool_call> start is in thinking block, skip this tool call
-                // This <tool_call> start is in thinking block
-                if (form.allow_toolcall_in_think) {
-                    unclosed_reasoning_content = content.substr(think_start + start_think.size());
-                } else {
-                    unclosed_reasoning_content = content.substr(think_start + start_think.size()) + tool_call_start;
-                }
-                reasoning_unclosed = true;
-                content.resize(think_start);
-                toolcall_in_think = true;
-            }
-        }
-
-        if (builder.syntax().reasoning_format != COMMON_REASONING_FORMAT_NONE && !builder.syntax().reasoning_in_content) {
-            rstrip(content);
-            // Handle unclosed </think> token from content: delete all </think> token
-            if (auto pos = content.rfind(end_think); pos != std::string::npos) {
-                while (pos != std::string::npos) {
-                    pos = erase_spaces(content, pos, pos + end_think.size() - 1);
-                    pos = content.rfind(end_think, pos);
-                }
-            }
-            // Strip if needed
-            if (content.size() > 0 && std::isspace(static_cast<unsigned char>(content[0]))) {
-                content = string_strip(content);
-            }
-        }
-
-        // remove potential partial suffix
-        if (builder.pos() == builder.input().size()) {
-            if (unclosed_reasoning_content.empty()) {
-                rstrip(content);
-                trim_potential_partial_word(content);
-                rstrip(content);
-            } else {
-                rstrip(unclosed_reasoning_content);
-                trim_potential_partial_word(unclosed_reasoning_content);
-                rstrip(unclosed_reasoning_content);
-            }
-        }
-
-        // consume unclosed_reasoning_content if allow_toolcall_in_think is set
-        if (form.allow_toolcall_in_think && !unclosed_reasoning_content.empty()) {
-            if (builder.syntax().reasoning_format != COMMON_REASONING_FORMAT_NONE && !builder.syntax().reasoning_in_content) {
-                builder.add_reasoning_content(unclosed_reasoning_content);
-            } else {
-                if (content.empty()) {
-                    content = start_think + unclosed_reasoning_content;
-                } else {
-                    content += "\n\n" + start_think;
-                    content += unclosed_reasoning_content;
-                }
-            }
-            unclosed_reasoning_content.clear();
-        }
-
-        // Add content
-        if (!content.empty()) {
-            // If there are multiple content blocks
-            if (builder.syntax().reasoning_format != COMMON_REASONING_FORMAT_NONE && !builder.syntax().reasoning_in_content && builder.result().content.size() != 0) {
-                builder.add_content("\n\n");
-            }
-            builder.add_content(content);
-        }
-
-        // This <tool_call> start is in thinking block and toolcall_in_think not set, skip this tool call
-        if (toolcall_in_think && !form.allow_toolcall_in_think) {
-            continue;
-        }
-
-        // There is no tool call and all content is parsed
-        if (!tc) {
-            GGML_ASSERT(builder.pos() == builder.input().size());
-            GGML_ASSERT(unclosed_reasoning_content.empty());
-            if (!form.allow_toolcall_in_think) GGML_ASSERT(!reasoning_unclosed);
-            break;
-        }
-
-        builder.move_to(tc->groups[0].begin);
-        if (builder.try_consume_xml_tool_calls(form)) {
-            auto end_of_tool = builder.pos();
-            builder.consume_spaces();
-            if (builder.pos() != builder.input().size()) {
-                builder.move_to(end_of_tool);
-                if (!builder.result().content.empty()) {
-                    builder.add_content("\n\n");
-                }
-            }
-        } else {
-            static const common_regex next_char_regex(".");
-            auto c = builder.str(builder.consume_regex(next_char_regex).groups[0]);
-            rstrip(c);
-            builder.add_content(c);
-        }
-    }
-}
-
-/**
- * Parse content uses reasoning and XML-Style tool call
- */
-void common_chat_msg_parser::consume_reasoning_with_xml_tool_calls(const struct xml_tool_call_format & form, const std::string & start_think, const std::string & end_think) {
-    parse_msg_with_xml_tool_calls(*this, form, start_think, end_think);
-}

common/chat-parser-xml-toolcall.h

@@ -1,45 +0,0 @@
-#pragma once
-
-#include "chat.h"
-
-#include <nlohmann/json.hpp>
-
-#include <optional>
-#include <string>
-#include <vector>
-
-
-// Sample config:
-// MiniMax-M2 (left): <minimax:tool_call>\n<invoke name="tool-name">\n<parameter name="key">value</parameter>\n...</invoke>\n...</minimax:tool_call>
-// GLM 4.5   (right): <tool_call>function_name\n<arg_key>key</arg_key>\n<arg_value>value</arg_value>\n</tool_call>
-struct xml_tool_call_format {
-    std::string scope_start; // <minimax:tool_call>\n  // \n                      // can be empty
-    std::string tool_start;  // <invoke name=\"        // <tool_call>
-    std::string tool_sep;    // \">\n                  // \n                      // can be empty only for parse_xml_tool_calls
-    std::string key_start;   // <parameter name=\"     // <arg_key>
-    std::string key_val_sep; // \">                    // </arg_key>\n<arg_value>
-    std::string val_end;     // </parameter>\n         // </arg_value>\n
-    std::string tool_end;    // </invoke>\n            // </tool_call>\n
-    std::string scope_end;   // </minimax:tool_call>   //                         // can be empty
-    // Set this if there can be dynamic spaces inside key_val_sep.
-    // e.g. key_val_sep=</arg_key> key_val_sep2=<arg_value> for GLM4.5
-    std::optional<std::string> key_val_sep2 = std::nullopt;
-    // Set true if argval should only be raw string. e.g. Hello "world" hi
-    // Set false if argval should only be json string. e.g. "Hello \"world\" hi"
-    // Defaults to std::nullopt, both will be allowed.
-    std::optional<bool> raw_argval = std::nullopt;
-    std::optional<std::string> last_val_end = std::nullopt;
-    std::optional<std::string> last_tool_end = std::nullopt;
-    bool trim_raw_argval = false;
-    bool allow_toolcall_in_think = false;
-};
-
-// make a GBNF that accept any strings except those containing any of the forbidden strings.
-std::string make_gbnf_excluding(std::vector<std::string> forbids);
-
-/**
- * Build grammar for xml-style tool call
- * form.scope_start and form.scope_end can be empty.
- * Requires data.format for model-specific hacks.
- */
-void build_grammar_xml_tool_call(common_chat_params & data, const nlohmann::ordered_json & tools, const struct xml_tool_call_format & form);

common/chat-parser.h

@@ -1,133 +0,0 @@
-#pragma once
-
-#include "chat.h"
-#include "chat-parser-xml-toolcall.h"
-#include "json-partial.h"
-#include "regex-partial.h"
-
-#include <nlohmann/json_fwd.hpp>
-
-#include <optional>
-#include <string>
-#include <vector>
-
-class common_chat_msg_partial_exception : public std::runtime_error {
-  public:
-    common_chat_msg_partial_exception(const std::string & message) : std::runtime_error(message) {}
-};
-
-class common_chat_msg_parser {
-    std::string input_;
-    bool is_partial_;
-    common_chat_parser_params syntax_; // TODO: rename to params
-    std::string healing_marker_;
-
-    size_t pos_ = 0;
-    common_chat_msg result_;
-
-  public:
-    common_chat_msg_parser(const std::string & input, bool is_partial, const common_chat_parser_params & syntax);
-    const std::string & input() const { return input_; }
-    size_t pos() const { return pos_; }
-    const std::string & healing_marker() const { return healing_marker_; }
-    const bool & is_partial() const { return is_partial_; }
-    const common_chat_msg & result() const { return result_; }
-    const common_chat_parser_params & syntax() const { return syntax_; }
-
-    void move_to(size_t pos) {
-        if (pos > input_.size()) {
-            throw std::runtime_error("Invalid position!");
-        }
-        pos_ = pos;
-    }
-    void move_back(size_t n) {
-        if (pos_ < n) {
-            throw std::runtime_error("Can't move back that far!");
-        }
-        pos_ -= n;
-    }
-
-    // Get the substring of the input at the given range
-    std::string str(const common_string_range & rng) const;
-
-    // Appends to the result.content field
-    void add_content(const std::string & content);
-
-    // Appends to the result.reasoning_content field
-    void add_reasoning_content(const std::string & reasoning_content);
-
-    // Adds a tool call to the result. If the tool call is too incomplete (e.g. name empty), it won't add anything.
-    bool add_tool_call(const std::string & name, const std::string & id, const std::string & arguments);
-
-    // Adds a tool call using the "name", "id" and "arguments" fields of the json object
-    bool add_tool_call(const nlohmann::ordered_json & tool_call);
-
-    // Adds an array of tool calls using their "name", "id" and "arguments" fields.
-    bool add_tool_calls(const nlohmann::ordered_json & arr);
-
-    // Adds a tool call using the short form: { "tool_name": { "arg1": val, "arg2": val } }
-    bool add_tool_call_short_form(const nlohmann::ordered_json & tool_call);
-
-    void finish();
-
-    bool consume_spaces();
-
-    void consume_literal(const std::string & literal);
-
-    bool try_parse_reasoning(const std::string & start_think, const std::string & end_think);
-
-    std::string consume_rest();
-
-    struct find_regex_result {
-        std::string prelude;
-        std::vector<common_string_range> groups;
-    };
-
-    std::optional<find_regex_result> try_find_regex(const common_regex & regex, size_t from = std::string::npos, bool add_prelude_to_content = true);
-
-    bool try_consume_literal(const std::string & literal);
-
-    std::optional<find_regex_result> try_find_literal(const std::string & literal);
-
-    find_regex_result consume_regex(const common_regex & regex);
-
-    std::optional<find_regex_result> try_consume_regex(const common_regex & regex);
-
-    std::optional<common_json> try_consume_json();
-    common_json consume_json();
-
-    struct consume_json_result {
-        nlohmann::ordered_json value;
-        bool is_partial;
-    };
-
-    /*
-        Consume (possibly partial) json and converts specific subtrees to (possibly truncated) JSON strings.
-
-        By default, object keys can't be truncated, nor can string values (their corresponding key is removed,
-        e.g. `{"foo": "bar", "baz": "b` -> `{"foo": "bar"}`
-
-        But one can allow subpaths to be kept truncated, and possibly json-dumped to truncated json strings
-        - with `content_paths={{"foo"}}` -> `{"foo": "b` -> {"foo": "b"}`
-        - with `args_paths={{"foo"}}` -> `{"foo": {"b` -> `{"foo": "{b"}`
-    */
-    consume_json_result consume_json_with_dumped_args(
-        const std::vector<std::vector<std::string>> & args_paths = {},
-        const std::vector<std::vector<std::string>> & content_paths = {}
-    );
-    std::optional<consume_json_result> try_consume_json_with_dumped_args(
-        const std::vector<std::vector<std::string>> & args_paths = {},
-        const std::vector<std::vector<std::string>> & content_paths = {}
-    );
-
-    /**
-     * Parse XML-Style tool call for given xml_tool_call_format. Return false for invalid syntax and get the position untouched.
-     * form.scope_start, form.tool_sep and form.scope_end can be empty.
-     */
-    bool try_consume_xml_tool_calls(const struct xml_tool_call_format & form);
-
-    // Parse content uses reasoning and XML-Style tool call
-    void consume_reasoning_with_xml_tool_calls(const struct xml_tool_call_format & form, const std::string & start_think = "<think>", const std::string & end_think = "</think>");
-
-    void clear_tools();
-};

common/chat-peg-parser.cpp

@@ -1,13 +1,17 @@
 #include "chat-peg-parser.h"
 
+#include "chat-auto-parser.h"
+#include "ggml.h"
+#include "peg-parser.h"
+
 #include <nlohmann/json.hpp>
 
-using json = nlohmann::json;
+using json = nlohmann::ordered_json;
 
 static std::string_view trim_trailing_space(std::string_view sv, int max = -1) {
     int count = 0;
     while (!sv.empty() && std::isspace(static_cast<unsigned char>(sv.back()))) {
-        if (max != -1 && count <= max) {
+        if (max != -1 && count >= max) {
             break;
         }
         sv.remove_suffix(1);
@@ -16,109 +20,820 @@ static std::string_view trim_trailing_space(std::string_view sv, int max = -1) {
     return sv;
 }
 
-void common_chat_peg_mapper::from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result) {
+static std::string_view trim_leading_space(std::string_view sv, int max = -1) {
+    int count = 0;
+    while (!sv.empty() && std::isspace(static_cast<unsigned char>(sv.front()))) {
+        if (max != -1 && count >= max) {
+            break;
+        }
+        sv.remove_prefix(1);
+        count++;
+    }
+    return sv;
+}
+
+static std::string_view trim(std::string_view sv) {
+    return trim_trailing_space(trim_leading_space(sv, 1));
+}
+
+// Count the number of unclosed '{' braces in a JSON-like string,
+// properly skipping braces inside quoted strings.
+static int json_brace_depth(const std::string & s) {
+    int  depth     = 0;
+    bool in_string = false;
+    bool escaped   = false;
+    for (char c : s) {
+        if (escaped) {
+            escaped = false;
+            continue;
+        }
+        if (c == '\\' && in_string) {
+            escaped = true;
+            continue;
+        }
+        if (c == '"') {
+            in_string = !in_string;
+            continue;
+        }
+        if (!in_string) {
+            if (c == '{') {
+                depth++;
+            } else if (c == '}') {
+                depth--;
+            }
+        }
+    }
+    return depth;
+}
+
+// JSON-escape a string and return the inner content (without surrounding quotes).
+static std::string escape_json_string_inner(const std::string & s) {
+    std::string escaped = json(s).dump();
+    if (escaped.size() >= 2 && escaped.front() == '"' && escaped.back() == '"') {
+        return escaped.substr(1, escaped.size() - 2);
+    }
+    return escaped;
+}
+
+// Convert Python-style single-quoted strings to JSON double-quoted strings
+// Only converts outer string delimiters, properly handling escape sequences:
+// - {'key': 'value'} -> {"key": "value"}
+// - {'code': 'print(\'hello\')'} -> {"code": "print('hello')"}
+// - {'msg': 'He said "hi"'} -> {"msg": "He said \"hi\""}
+static std::string normalize_quotes_to_json(const std::string & input) {
+    std::string result;
+    result.reserve(input.size() + 16);  // May need extra space for escaping
+
+    bool in_single_quoted = false;
+    bool in_double_quoted = false;
+
+    for (size_t i = 0; i < input.size(); ++i) {
+        char c = input[i];
+
+        // Handle escape sequences
+        if (c == '\\' && i + 1 < input.size()) {
+            char next = input[i + 1];
+
+            if (in_single_quoted) {
+                // Inside a single-quoted string being converted to double quotes
+                if (next == '\'') {
+                    // \' -> ' (escaped single quote becomes unescaped in double-quoted string)
+                    result += '\'';
+                    ++i;
+                    continue;
+                }
+                if (next == '"') {
+                    // \" stays as \" (already escaped, works in double-quoted string)
+                    result += "\\\"";
+                    ++i;
+                    continue;
+                }
+                // Other escapes (\n, \\, etc.): pass through both characters
+                result += c;
+                result += next;
+                ++i;
+                continue;
+            }
+
+            if (in_double_quoted) {
+                // Inside a double-quoted string - pass through escape sequences as-is
+                result += c;
+                result += next;
+                ++i;
+                continue;
+            }
+
+            // Outside any string - just pass through the backslash
+            result += c;
+            continue;
+        }
+
+        // Handle quote characters
+        if (c == '"') {
+            if (in_single_quoted) {
+                // Unescaped double quote inside single-quoted string -> must escape for JSON
+                result += "\\\"";
+            } else {
+                // Double quote as string delimiter or outside strings
+                in_double_quoted = !in_double_quoted;
+                result += c;
+            }
+        } else if (c == '\'') {
+            if (in_double_quoted) {
+                // Single quote inside double-quoted string -> pass through
+                result += c;
+            } else if (in_single_quoted) {
+                // Closing single quote -> convert to double quote
+                in_single_quoted = false;
+                result += '"';
+            } else {
+                // Opening single quote -> convert to double quote
+                in_single_quoted = true;
+                result += '"';
+            }
+        } else {
+            result += c;
+        }
+    }
+
+    return result;
+}
+
+void tag_based_peg_mapper::from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result) {
     arena.visit(result, [this](const common_peg_ast_node & node) {
-        map(node);
+        if (!node.tag.empty()) {
+            tags[node.tag] = std::string(node.text);
+        }
     });
 }
 
-void common_chat_peg_mapper::map(const common_peg_ast_node & node) {
-    bool is_reasoning = node.tag == common_chat_peg_builder::REASONING;
-    bool is_content = node.tag == common_chat_peg_builder::CONTENT;
+tagged_parse_result tagged_peg_parser::parse_and_extract(const std::string & input, common_peg_parse_flags extra_flags) const {
+    common_peg_parse_context ctx(input, flags | extra_flags);
+    auto parse_result = arena.parse(ctx);
 
-    if (is_reasoning) {
-        result.reasoning_content = std::string(trim_trailing_space(node.text));
+    tag_based_peg_mapper mapper;
+    mapper.from_ast(ctx.ast, parse_result);
+
+    return { std::move(parse_result), std::move(mapper.tags) };
+}
+
+tagged_parse_result tagged_peg_parser::parse_anywhere_and_extract(const std::string & input) const {
+    if (input.empty()) {
+        return parse_and_extract(input);
     }
+    for (size_t i = 0; i < input.size(); i++) {
+        common_peg_parse_context ctx(input, flags);
+        auto parse_result = arena.parse(ctx, i);
+        if (parse_result.success() || i == input.size() - 1) {
+            tag_based_peg_mapper mapper;
+            mapper.from_ast(ctx.ast, parse_result);
+            return { std::move(parse_result), std::move(mapper.tags) };
+        }
+    }
+    GGML_ABORT("Should not happen");
+}
 
-    if (is_content) {
-        result.content = std::string(trim_trailing_space(node.text));
+tagged_peg_parser build_tagged_peg_parser(
+    const std::function<common_peg_parser(common_peg_parser_builder & builder)> & fn) {
+    common_peg_parser_builder builder;
+    builder.set_root(fn(builder));
+    return { builder.build() };
+}
+
+common_peg_parser common_chat_peg_builder::tag_with_safe_content(const std::string &       tag_name,
+                                                                 const std::string &       marker,
+                                                                 const common_peg_parser & p) {
+    if (marker.empty()) {
+        return zero_or_more(choice({ p, rule(tag_name, content(any())) }));
+    }
+    auto content_chunk = rule(tag_name, content(negate(literal(marker)) + any() + until(marker)));
+    return zero_or_more(choice({ p, content_chunk }));
+}
+
+std::string & common_chat_peg_mapper::args_target() {
+    return (current_tool && !current_tool->name.empty()) ? current_tool->arguments : args_buffer;
+}
+
+void common_chat_peg_mapper::from_ast(const common_peg_ast_arena &    arena,
+                                      const common_peg_parse_result & parse_result_arg) {
+    arena.visit(parse_result_arg, [this](const common_peg_ast_node & node) { map(node); });
+    // Flush any pending tool call that was started but never got a name
+    // This happens during partial parsing when the tool call is incomplete
+    if (pending_tool_call.has_value() && !pending_tool_call->name.empty()) {
+        if (!args_buffer.empty()) {
+            pending_tool_call->arguments = args_buffer;
+        }
+        if (closing_quote_pending && !pending_tool_call->arguments.empty()) {
+            pending_tool_call->arguments += "\"";
+        }
+        result.tool_calls.push_back(pending_tool_call.value());
+        pending_tool_call.reset();
     }
 }
 
-void common_chat_peg_native_mapper::map(const common_peg_ast_node & node) {
-    common_chat_peg_mapper::map(node);
+void common_chat_peg_mapper::map(const common_peg_ast_node & node) {
+    // Handle reasoning/content tags
+    bool is_reasoning = node.tag == common_chat_peg_builder::REASONING;
+    bool is_content   = node.tag == common_chat_peg_builder::CONTENT;
 
-    bool is_tool_open = node.tag == common_chat_peg_native_builder::TOOL_OPEN;
-    bool is_tool_name = node.tag == common_chat_peg_native_builder::TOOL_NAME;
-    bool is_tool_id = node.tag == common_chat_peg_native_builder::TOOL_ID;
-    bool is_tool_args = node.tag == common_chat_peg_native_builder::TOOL_ARGS;
+    if (is_reasoning) { // GPT OSS can have more than 1 reasoning block, so concatenate here
+        result.reasoning_content += std::string(node.text);
+    }
+
+    if (is_content) {
+        // Concatenate content from multiple content nodes (e.g., when reasoning markers
+        // are preserved before content markers in reasoning_format=NONE mode)
+        result.content += std::string(node.text);
+    }
+
+    // Handle tool-related tags (supporting both JSON and tagged formats)
+    bool is_tool_open  = node.tag == common_chat_peg_builder::TOOL_OPEN;
+    bool is_tool_close = node.tag == common_chat_peg_builder::TOOL_CLOSE;
+    bool is_tool_name  = node.tag == common_chat_peg_builder::TOOL_NAME;
+    bool is_tool_id    = node.tag == common_chat_peg_builder::TOOL_ID;
+    bool is_tool_args  = node.tag == common_chat_peg_builder::TOOL_ARGS;
+    bool is_arg_open   = node.tag == common_chat_peg_builder::TOOL_ARG_OPEN;
+    bool is_arg_close  = node.tag == common_chat_peg_builder::TOOL_ARG_CLOSE;
+    bool is_arg_name         = node.tag == common_chat_peg_builder::TOOL_ARG_NAME;
+    bool is_arg_value        = node.tag == common_chat_peg_builder::TOOL_ARG_VALUE;
+    bool is_arg_string_value = node.tag == common_chat_peg_builder::TOOL_ARG_STRING_VALUE;
 
     if (is_tool_open) {
-        result.tool_calls.emplace_back();
-        current_tool = &result.tool_calls.back();
+        pending_tool_call     = common_chat_tool_call();
+        current_tool          = &pending_tool_call.value();
+        arg_count             = 0;
+        args_buffer.clear();
+        closing_quote_pending = false;
     }
 
     if (is_tool_id && current_tool) {
-        current_tool->id = std::string(trim_trailing_space(node.text));
+        auto text = trim_trailing_space(node.text);
+        if (text.size() >= 2 && text.front() == '"' && text.back() == '"') {
+            text = text.substr(1, text.size() - 2);
+        }
+        current_tool->id = std::string(text);
     }
 
     if (is_tool_name && current_tool) {
         current_tool->name = std::string(trim_trailing_space(node.text));
+        // Now that we have the name, populate the arguments from the buffer
+        if (!args_buffer.empty()) {
+            current_tool->arguments = args_buffer;
+            args_buffer.clear();
+        } else if (current_tool->arguments.empty()) {
+            current_tool->arguments = "{";
+        }
+        // Add the tool call to results so streaming can see it
+        if (pending_tool_call.has_value()) {
+            result.tool_calls.push_back(pending_tool_call.value());
+            pending_tool_call.reset();
+            current_tool = &result.tool_calls.back();
+        }
     }
 
     if (is_tool_args && current_tool) {
-        current_tool->arguments = std::string(trim_trailing_space(node.text));
-    }
-}
-
-void common_chat_peg_constructed_mapper::map(const common_peg_ast_node & node) {
-    common_chat_peg_mapper::map(node);
-
-    bool is_tool_open = node.tag == common_chat_peg_constructed_builder::TOOL_OPEN;
-    bool is_tool_name = node.tag == common_chat_peg_constructed_builder::TOOL_NAME;
-    bool is_tool_close = node.tag == common_chat_peg_constructed_builder::TOOL_CLOSE;
-    bool is_arg_open = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_OPEN;
-    bool is_arg_close = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_CLOSE;
-    bool is_arg_name = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_NAME;
-    bool is_arg_string = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_STRING_VALUE;
-    bool is_arg_json = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_JSON_VALUE;
-
-    if (is_tool_open) {
-        result.tool_calls.emplace_back();
-        current_tool = &result.tool_calls.back();
-        arg_count = 0;
-    }
-
-    if (is_tool_name) {
-        current_tool->name = std::string(node.text);
-        current_tool->arguments = "{";
+        // For JSON format: arguments come as a complete JSON object
+        // For tagged format: built up from individual arg_name/arg_value nodes
+        auto text = trim_trailing_space(node.text);
+        if (!text.empty() && text.front() == '{') {
+            args_target() = std::string(text);
+        }
     }
 
     if (is_arg_open) {
-        needs_closing_quote = false;
+        closing_quote_pending = false;
     }
 
     if (is_arg_name && current_tool) {
+        std::string arg_entry;
         if (arg_count > 0) {
-            current_tool->arguments += ",";
+            arg_entry = ",";
         }
-        current_tool->arguments += json(trim_trailing_space(node.text)).dump() + ":";
+        arg_entry += json(trim(node.text)).dump() + ":";
         ++arg_count;
+
+        auto & target = args_target();
+        if (target.empty()) {
+            target = "{";
+        }
+        target += arg_entry;
     }
 
-    if (is_arg_string && current_tool) {
-        // Serialize to JSON, but exclude the end quote
-        std::string dumped = json(trim_trailing_space(node.text)).dump();
-        current_tool->arguments += dumped.substr(0, dumped.size() - 1);
-        needs_closing_quote = true;
+    if ((is_arg_value || is_arg_string_value) && current_tool) {
+        std::string value_content = std::string(trim_trailing_space(trim_leading_space(node.text, 1), 1));
+
+        std::string value_to_add;
+        if (value_content.empty() && is_arg_string_value) {
+            // Empty string value - arg_close will add the closing quote
+            value_to_add          = "\"";
+            closing_quote_pending = true;
+        } else if (!value_content.empty() && is_arg_string_value) {
+            // Schema declares this as string type - always treat as literal string value
+            if (!closing_quote_pending) {
+                value_to_add          = "\"";
+                closing_quote_pending = true;
+            }
+            value_to_add += escape_json_string_inner(value_content);
+        } else if (!value_content.empty()) {
+            // For potential containers, normalize Python-style single quotes to JSON double quotes
+            bool is_potential_container = value_content[0] == '[' || value_content[0] == '{';
+            if (is_potential_container) {
+                value_content = normalize_quotes_to_json(value_content);
+            }
+
+            // Try to parse as JSON value (number, bool, null, object, array)
+            try {
+                json parsed = json::parse(value_content);
+                if (parsed.is_string()) {
+                    // Don't add closing quote yet (added by arg_close) for monotonic streaming
+                    std::string escaped = parsed.dump();
+                    if (!escaped.empty() && escaped.back() == '"') {
+                        escaped.pop_back();
+                    }
+                    value_to_add          = escaped;
+                    closing_quote_pending = true;
+                } else {
+                    // Non-string values: use raw content to preserve whitespace for monotonicity
+                    value_to_add = value_content;
+                }
+            } catch (...) {
+                if (node.is_partial && is_potential_container) {
+                    // Partial container: pass through the already-normalized content
+                    value_to_add = value_content;
+                } else {
+                    // Not valid JSON - treat as string value
+                    if (!closing_quote_pending) {
+                        value_to_add          = "\"";
+                        closing_quote_pending = true;
+                    }
+                    value_to_add += escape_json_string_inner(value_content);
+                }
+            }
+        }
+
+        args_target() += value_to_add;
     }
 
     if (is_arg_close && current_tool) {
-        if (needs_closing_quote) {
-            current_tool->arguments += "\"";
-            needs_closing_quote = false;
+        if (closing_quote_pending) {
+            args_target() += "\"";
+            closing_quote_pending = false;
         }
     }
 
-    if (is_arg_json && current_tool) {
-        current_tool->arguments += std::string(trim_trailing_space(node.text));
-    }
-
     if (is_tool_close && current_tool) {
-        if (needs_closing_quote) {
-            current_tool->arguments += "\"";
-            needs_closing_quote = false;
+        // Flush buffer to arguments if tool name was never seen
+        if (current_tool->name.empty() && !args_buffer.empty()) {
+            current_tool->arguments = args_buffer;
+            args_buffer.clear();
+        }
+        // Close any pending string quote
+        if (closing_quote_pending) {
+            current_tool->arguments += "\"";
+            closing_quote_pending = false;
+        }
+        // Close any unclosed braces (accounts for nested objects)
+        for (int d = json_brace_depth(current_tool->arguments); d > 0; d--) {
+            current_tool->arguments += "}";
+        }
+        // Add tool call to results if named; otherwise discard
+        if (pending_tool_call.has_value()) {
+            if (!current_tool->name.empty()) {
+                result.tool_calls.push_back(pending_tool_call.value());
+            }
+            pending_tool_call.reset();
         }
-        current_tool->arguments += "}";
     }
 }
+
+common_peg_parser common_chat_peg_builder::standard_constructed_tools(
+    const std::map<std::string, std::string> & markers,
+    const nlohmann::json &                     tools,
+    bool                                       parallel_tool_calls,
+    bool                                       force_tool_calls) {
+    if (!tools.is_array() || tools.empty()) {
+        return eps();
+    }
+
+    // Extract markers with defaults
+    auto get_marker = [&markers](const std::string & key, const std::string & default_val = "") -> std::string {
+        auto it = markers.find(key);
+        return it != markers.end() ? it->second : default_val;
+    };
+
+    std::string section_start    = get_marker("tool_call_start_marker", "<tool_call>");
+    std::string section_end      = get_marker("tool_call_end_marker", "</tool_call>");
+    std::string func_opener      = get_marker("function_opener", "<function=");
+    std::string func_name_suffix = get_marker("function_name_suffix", ">");
+    std::string func_closer      = get_marker("function_closer", "</function>");
+    std::string param_key_prefix = get_marker("parameter_key_prefix", "<param=");
+    std::string param_key_suffix = get_marker("parameter_key_suffix", ">");
+    std::string param_closer     = get_marker("parameter_closer", "</param>");
+
+    // Build tool choices for tagged format
+    auto tool_choices = choice();
+
+    for (const auto & tool_def : tools) {
+        if (!tool_def.contains("function")) {
+            continue;
+        }
+        const auto &   function = tool_def.at("function");
+        std::string    name     = function.at("name");
+        nlohmann::json params = function.contains("parameters") ? function.at("parameters") : nlohmann::json::object();
+
+        // Build argument parsers
+        auto args = eps();
+        if (params.contains("properties") && !params["properties"].empty()) {
+            auto arg_choice = choice();
+            for (const auto & el : params["properties"].items()) {
+                const std::string & prop_name = el.key();
+
+                auto arg_name_parser =
+                    choice({ literal(prop_name), literal("\"" + prop_name + "\""), literal("'" + prop_name + "'") });
+
+                auto arg_rule = tool_arg(tool_arg_open(literal(param_key_prefix)) + tool_arg_name(arg_name_parser) +
+                                         literal(param_key_suffix) + tool_arg_value(until(param_closer)) +
+                                         tool_arg_close(literal(param_closer)));
+                arg_choice |= arg_rule;
+            }
+            args = zero_or_more(arg_choice + space());
+        }
+
+        // Build function parser: <function=name>args</function>
+        auto tool_parser = tool(tool_open(literal(func_opener) + tool_name(literal(name)) + literal(func_name_suffix)) +
+                                space() + tool_args(args) + space() + tool_close(literal(func_closer)));
+
+        tool_choices |= rule("tool-" + name, tool_parser);
+    }
+
+    // Build the section with markers
+    auto section =
+        parallel_tool_calls ?
+            trigger_rule("tool-call", literal(section_start) + space() + one_or_more(tool_choices + space()) +
+                                          literal(section_end)) :
+            trigger_rule("tool-call", literal(section_start) + space() + tool_choices + space() + literal(section_end));
+
+    return force_tool_calls ? section : optional(section);
+}
+
+// Python-style tool calls: name(arg1="value1", arg2=123)
+// Used only by LFM2 for now, so we don't merge it into autoparser
+common_peg_parser common_chat_peg_builder::python_style_tool_calls(
+    const nlohmann::json & tools,
+    bool                   parallel_tool_calls) {
+    if (!tools.is_array() || tools.empty()) {
+        return eps();
+    }
+
+    auto tool_choices = choice();
+
+    for (const auto & tool_def : tools) {
+        if (!tool_def.contains("function")) {
+            continue;
+        }
+        const auto &   function = tool_def.at("function");
+        std::string    name     = function.at("name");
+        nlohmann::json params = function.contains("parameters") ? function.at("parameters") : nlohmann::json::object();
+
+        auto args = eps();
+        if (params.contains("properties") && !params["properties"].empty()) {
+            auto arg_choice = choice();
+            for (const auto & el : params["properties"].items()) {
+                const std::string & prop_name = el.key();
+                const auto & prop_def = el.value();
+                bool is_string_type = (prop_def.contains("type") && prop_def["type"] == "string");
+
+                auto arg_name_parser = literal(prop_name);
+
+                common_peg_parser arg_value_parser = eps();
+                auto string_value_parser = choice({
+                    literal("\"") + tool_arg_string_value(json_string_content()) + literal("\""),
+                    literal("'") + tool_arg_string_value(json_string_content()) + literal("'")
+                });
+
+                if (is_string_type) {
+                    arg_value_parser = string_value_parser;
+                } else {
+                    arg_value_parser = tool_arg_value(python_value());
+                }
+
+                // Full argument: name="value" or name=value
+                auto arg_rule = tool_arg(
+                    tool_arg_open(eps()) +
+                    tool_arg_name(arg_name_parser) +
+                    literal("=") +
+                    arg_value_parser +
+                    tool_arg_close(eps())
+                );
+                arg_choice |= arg_rule;
+            }
+
+            args = arg_choice + zero_or_more("," + space() + arg_choice);
+        }
+
+        auto tool_parser = tool(tool_open(tool_name(literal(name)) + literal("(")) +
+            space() + tool_args(args) + space() + tool_close(literal(")"))
+        );
+
+        tool_choices |= rule("tool-" + name, tool_parser);
+    }
+
+    if (parallel_tool_calls) {
+        return "[" + space() + tool_choices + zero_or_more("," + space() + tool_choices) + space() + "]";
+    }
+    return "[" + space() + tool_choices + space() + "]";
+}
+
+// Helper: Parse dot notation key into prefix and field name
+static std::pair<std::string, std::string> parse_key_spec(const std::string & key) {
+    auto dot_pos = key.find('.');
+    if (dot_pos == std::string::npos) {
+        return {"", key};  // Top-level field
+    }
+    return {key.substr(0, dot_pos), key.substr(dot_pos + 1)};
+}
+
+// Mode 1: function_is_key — parse {"function_name": {...}}
+common_peg_parser common_chat_peg_builder::build_json_tools_function_is_key(
+    const nlohmann::json & tools,
+    const std::string &    args_key,
+    const std::string &    effective_args_key,
+    const std::string &    call_id_key,
+    const std::string &    gen_call_id_key) {
+
+    auto tool_choices = choice();
+
+    for (const auto & tool_def : tools) {
+        if (!tool_def.contains("function")) {
+            continue;
+        }
+        const auto &   function = tool_def.at("function");
+        std::string    name     = function.at("name");
+        nlohmann::json params = function.contains("parameters") ? function.at("parameters") : nlohmann::json::object();
+
+        // Build inner object fields
+        std::vector<common_peg_parser> inner_fields;
+
+        if (!call_id_key.empty()) {
+            auto id_parser = atomic(
+                literal("\"" + call_id_key + "\"") + space() + literal(":") + space() +
+                literal("\"") + tool_id(json_string_content()) + literal("\"")
+            );
+            inner_fields.push_back(optional(id_parser + space() + optional(literal(",") + space())));
+        }
+
+        if (!gen_call_id_key.empty()) {
+            auto gen_id_parser = atomic(
+                literal("\"" + gen_call_id_key + "\"") + space() + literal(":") + space() +
+                choice({
+                    literal("\"") + tool_id(json_string_content()) + literal("\""),
+                    tool_id(json_number())
+                })
+            );
+            inner_fields.push_back(optional(gen_id_parser + space() + optional(literal(",") + space())));
+        }
+
+        // Arguments — either wrapped in args_key or parsed directly
+        common_peg_parser args_parser = eps();
+        if (args_key.empty()) {
+            args_parser = tool_args(schema(json(), "tool-" + name + "-schema", params));
+        } else {
+            args_parser = literal("\"" + effective_args_key + "\"") + space() + literal(":") + space() +
+                          tool_args(schema(json(), "tool-" + name + "-schema", params));
+        }
+        inner_fields.push_back(args_parser);
+
+        // Build inner object parser
+        common_peg_parser inner_object = eps();
+        if (args_key.empty() && inner_fields.size() == 1) {
+            inner_object = inner_fields[0];
+        } else {
+            inner_object = literal("{") + space();
+            for (size_t i = 0; i < inner_fields.size(); i++) {
+                inner_object = inner_object + inner_fields[i];
+                if (i < inner_fields.size() - 1) {
+                    inner_object = inner_object + space();
+                }
+            }
+            inner_object = inner_object + space() + literal("}");
+        }
+
+        auto tool_parser = tool(
+            tool_open(literal("{")) + space() +
+            literal("\"") + tool_name(literal(name)) + literal("\"") +
+            space() + literal(":") + space() +
+            inner_object +
+            space() + tool_close(literal("}"))
+        );
+
+        tool_choices |= rule("tool-" + name, tool_parser);
+    }
+
+    return tool_choices;
+}
+
+// Mode 2: Nested keys (dot notation like "function.name")
+common_peg_parser common_chat_peg_builder::build_json_tools_nested_keys(
+    const nlohmann::json & tools,
+    const std::string &    effective_name_key,
+    const std::string &    effective_args_key,
+    const std::string &    call_id_key,
+    const std::string &    gen_call_id_key) {
+
+    auto tool_choices = choice();
+
+    auto name_spec = parse_key_spec(effective_name_key);
+    auto args_spec = parse_key_spec(effective_args_key);
+
+    std::string nested_prefix     = !name_spec.first.empty() ? name_spec.first  : args_spec.first;
+    std::string nested_name_field = !name_spec.first.empty() ? name_spec.second  : effective_name_key;
+    std::string nested_args_field = !args_spec.first.empty() ? args_spec.second  : effective_args_key;
+
+    for (const auto & tool_def : tools) {
+        if (!tool_def.contains("function")) {
+            continue;
+        }
+        const auto &   function = tool_def.at("function");
+        std::string    name     = function.at("name");
+        nlohmann::json params = function.contains("parameters") ? function.at("parameters") : nlohmann::json::object();
+
+        auto nested_name = literal("\"" + nested_name_field + "\"") + space() + literal(":") + space() +
+                          literal("\"") + tool_name(literal(name)) + literal("\"");
+        auto nested_args = literal("\"" + nested_args_field + "\"") + space() + literal(":") + space() +
+                          tool_args(schema(json(), "tool-" + name + "-schema", params));
+
+        auto nested_object = literal("{") + space() +
+                            nested_name + space() + literal(",") + space() +
+                            nested_args +
+                            space() + literal("}");
+
+        // Format: { id?, "function": {...} }
+        auto tool_parser_body = tool_open(literal("{")) + space();
+
+        if (!call_id_key.empty()) {
+            auto id_spec = parse_key_spec(call_id_key);
+            if (id_spec.first.empty()) {
+                auto id_parser = atomic(
+                    literal("\"" + call_id_key + "\"") + space() + literal(":") + space() +
+                    literal("\"") + tool_id(json_string_content()) + literal("\"")
+                );
+                tool_parser_body = tool_parser_body + optional(id_parser + space() + literal(",") + space());
+            }
+        }
+
+        if (!gen_call_id_key.empty()) {
+            auto gen_id_spec = parse_key_spec(gen_call_id_key);
+            if (gen_id_spec.first.empty()) {
+                auto gen_id_parser = atomic(
+                    literal("\"" + gen_call_id_key + "\"") + space() + literal(":") + space() +
+                    choice({
+                        literal("\"") + tool_id(json_string_content()) + literal("\""),
+                        tool_id(json_number())
+                    })
+                );
+                tool_parser_body = tool_parser_body + optional(gen_id_parser + space() + literal(",") + space());
+            }
+        }
+
+        auto nested_field = literal("\"" + nested_prefix + "\"") + space() + literal(":") + space() + nested_object;
+        tool_parser_body = tool_parser_body + nested_field + space() + tool_close(literal("}"));
+
+        tool_choices |= rule("tool-" + name, tool(tool_parser_body));
+    }
+
+    return tool_choices;
+}
+
+// Mode 3: Flat keys with optional ID fields and parameter ordering
+common_peg_parser common_chat_peg_builder::build_json_tools_flat_keys(
+    const nlohmann::json &           tools,
+    const std::string &              effective_name_key,
+    const std::string &              effective_args_key,
+    const std::string &              call_id_key,
+    const std::string &              gen_call_id_key,
+    const std::vector<std::string> & parameters_order) {
+
+    auto tool_choices    = choice();
+    auto name_key_parser = literal("\"" + effective_name_key + "\"");
+    auto args_key_parser = literal("\"" + effective_args_key + "\"");
+
+    for (const auto & tool_def : tools) {
+        if (!tool_def.contains("function")) {
+            continue;
+        }
+        const auto &   function = tool_def.at("function");
+        std::string    name     = function.at("name");
+        nlohmann::json params = function.contains("parameters") ? function.at("parameters") : nlohmann::json::object();
+
+        auto tool_name_ = name_key_parser + space() + literal(":") + space() +
+                         literal("\"") + tool_name(literal(name)) + literal("\"");
+        auto tool_args_ = args_key_parser + space() + literal(":") + space() +
+                         tool_args(schema(json(), "tool-" + name + "-schema", params));
+
+        // Build ID parsers if keys are provided
+        common_peg_parser id_parser = eps();
+        if (!call_id_key.empty()) {
+            id_parser = atomic(
+                literal("\"" + call_id_key + "\"") + space() + literal(":") + space() +
+                choice({
+                    literal("\"") + tool_id(json_string_content()) + literal("\""),
+                    tool_id(json_number())
+                })
+            );
+        }
+
+        common_peg_parser gen_id_parser = eps();
+        if (!gen_call_id_key.empty()) {
+            gen_id_parser = atomic(
+                literal("\"" + gen_call_id_key + "\"") + space() + literal(":") + space() +
+                choice({
+                    literal("\"") + tool_id(json_string_content()) + literal("\""),
+                    tool_id(json_number())
+                })
+            );
+        }
+
+        // Create (parser, key) pairs for all fields, then sort by parameters_order
+        std::vector<std::pair<common_peg_parser, std::string>> parser_pairs;
+        parser_pairs.emplace_back(tool_name_, effective_name_key);
+        parser_pairs.emplace_back(tool_args_, effective_args_key);
+        if (!call_id_key.empty()) {
+            parser_pairs.emplace_back(optional(id_parser), call_id_key);
+        }
+        if (!gen_call_id_key.empty()) {
+            parser_pairs.emplace_back(optional(gen_id_parser), gen_call_id_key);
+        }
+
+        std::sort(parser_pairs.begin(), parser_pairs.end(),
+            [&parameters_order](const auto & a, const auto & b) {
+                auto pos_a = std::find(parameters_order.begin(), parameters_order.end(), a.second);
+                auto pos_b = std::find(parameters_order.begin(), parameters_order.end(), b.second);
+                size_t idx_a = (pos_a == parameters_order.end()) ? parameters_order.size() : std::distance(parameters_order.begin(), pos_a);
+                size_t idx_b = (pos_b == parameters_order.end()) ? parameters_order.size() : std::distance(parameters_order.begin(), pos_b);
+                return idx_a < idx_b;
+            });
+
+        auto ordered_body = tool_open(literal("{")) + space();
+        for (size_t i = 0; i < parser_pairs.size(); i++) {
+            ordered_body = ordered_body + parser_pairs[i].first;
+            if (i < parser_pairs.size() - 1) {
+                ordered_body = ordered_body + space() + literal(",") + space();
+            }
+        }
+        ordered_body = ordered_body + space() + tool_close(literal("}"));
+
+        tool_choices |= rule("tool-" + name, tool(ordered_body));
+    }
+
+    return tool_choices;
+}
+
+common_peg_parser common_chat_peg_builder::standard_json_tools(
+                                                       const std::string &              section_start,
+                                                       const std::string &              section_end,
+                                                       const nlohmann::json &           tools,
+                                                       bool                             parallel_tool_calls,
+                                                       bool                             force_tool_calls,
+                                                       const std::string &              name_key,
+                                                       const std::string &              args_key,
+                                                       bool                             array_wrapped,
+                                                       bool                             function_is_key,
+                                                       const std::string &              call_id_key,
+                                                       const std::string &              gen_call_id_key,
+                                                       const std::vector<std::string> & parameters_order) {
+    if (!tools.is_array() || tools.empty()) {
+        return eps();
+    }
+
+    std::string effective_name_key = name_key.empty() ? "name" : name_key;
+    std::string effective_args_key = args_key.empty() ? "arguments" : args_key;
+
+    // Dispatch to the appropriate builder based on the JSON layout mode
+    common_peg_parser tool_choices = eps();
+    if (function_is_key) {
+        tool_choices = build_json_tools_function_is_key(tools, args_key, effective_args_key, call_id_key, gen_call_id_key);
+    } else {
+        auto name_spec = parse_key_spec(effective_name_key);
+        auto args_spec = parse_key_spec(effective_args_key);
+        if (!name_spec.first.empty() || !args_spec.first.empty()) {
+            tool_choices = build_json_tools_nested_keys(tools, effective_name_key, effective_args_key, call_id_key, gen_call_id_key);
+        } else {
+            tool_choices = build_json_tools_flat_keys(tools, effective_name_key, effective_args_key, call_id_key, gen_call_id_key, parameters_order);
+        }
+    }
+
+    // Build the section with markers
+    auto tool_calls = tool_choices;
+    if (parallel_tool_calls) {
+        tool_calls = tool_calls + zero_or_more(space() + literal(",") + space() + tool_choices);
+    }
+
+    if (array_wrapped) {
+        tool_calls = literal("[") + space() + tool_calls + space() + literal("]");
+    }
+
+    auto section =
+        trigger_rule("tool-call", literal(section_start) + space() + tool_calls + space() + literal(section_end));
+
+    return force_tool_calls ? section : optional(section);
+}

common/chat-peg-parser.h

@@ -3,22 +3,9 @@
 #include "chat.h"
 #include "peg-parser.h"
 
-class common_chat_peg_builder : public common_peg_parser_builder {
-  public:
-    static constexpr const char * REASONING_BLOCK = "reasoning-block";
-    static constexpr const char * REASONING = "reasoning";
-    static constexpr const char * CONTENT = "content";
-
-    common_peg_parser reasoning_block(const common_peg_parser & p) { return tag(REASONING_BLOCK, p); }
-    common_peg_parser reasoning(const common_peg_parser & p) { return tag(REASONING, p); }
-    common_peg_parser content(const common_peg_parser & p) { return tag(CONTENT, p); }
-};
-
-inline common_peg_arena build_chat_peg_parser(const std::function<common_peg_parser(common_chat_peg_builder & builder)> & fn) {
-    common_chat_peg_builder builder;
-    builder.set_root(fn(builder));
-    return builder.build();
-}
+#include <map>
+#include <optional>
+#include <vector>
 
 class common_chat_peg_mapper {
   public:
@@ -26,80 +13,169 @@ class common_chat_peg_mapper {
 
     common_chat_peg_mapper(common_chat_msg & msg) : result(msg) {}
 
+    virtual ~common_chat_peg_mapper() = default;
+
     virtual void from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result);
     virtual void map(const common_peg_ast_node & node);
+    private:
+      // Tool call handling state
+      std::optional<common_chat_tool_call> pending_tool_call;  // Tool call waiting for name
+      common_chat_tool_call *              current_tool          = nullptr;
+      int                                  arg_count             = 0;
+      bool                                 closing_quote_pending = false;
+      std::string                          args_buffer;  // Buffer to delay arguments until tool name is known
+
+      // Returns a reference to the active argument destination string.
+      // Before tool_name is known, writes go to args_buffer; after, to current_tool->arguments.
+      std::string & args_target();
 };
 
-class common_chat_peg_native_builder : public common_chat_peg_builder {
-  public:
-    static constexpr const char * TOOL = "tool";
-    static constexpr const char * TOOL_OPEN = "tool-open";
-    static constexpr const char * TOOL_CLOSE = "tool-close";
-    static constexpr const char * TOOL_ID = "tool-id";
-    static constexpr const char * TOOL_NAME = "tool-name";
-    static constexpr const char * TOOL_ARGS = "tool-args";
+struct content_structure;
+struct tool_call_structure;
 
+class common_chat_peg_builder : public common_peg_parser_builder {
+  public:
+    // Tag constants (from former common_chat_peg_base_builder)
+    static constexpr const char * REASONING_BLOCK = "reasoning-block";
+    static constexpr const char * REASONING       = "reasoning";
+    static constexpr const char * CONTENT         = "content";
+
+    // Tag constants
+    static constexpr const char * TOOL           = "tool";
+    static constexpr const char * TOOL_OPEN      = "tool-open";
+    static constexpr const char * TOOL_CLOSE     = "tool-close";
+    static constexpr const char * TOOL_ID        = "tool-id";
+    static constexpr const char * TOOL_NAME      = "tool-name";
+    static constexpr const char * TOOL_ARGS      = "tool-args";
+    static constexpr const char * TOOL_ARG       = "tool-arg";
+    static constexpr const char * TOOL_ARG_OPEN  = "tool-arg-open";
+    static constexpr const char * TOOL_ARG_CLOSE = "tool-arg-close";
+    static constexpr const char * TOOL_ARG_NAME         = "tool-arg-name";
+    static constexpr const char * TOOL_ARG_VALUE        = "tool-arg-value";
+    static constexpr const char * TOOL_ARG_STRING_VALUE = "tool-arg-string-value";  // For schema-declared string types
+
+    // Low-level tag methods (from former common_chat_peg_base_builder)
+    common_peg_parser reasoning_block(const common_peg_parser & p) { return tag(REASONING_BLOCK, p); }
+
+    common_peg_parser reasoning(const common_peg_parser & p) { return tag(REASONING, p); }
+
+    common_peg_parser content(const common_peg_parser & p) { return tag(CONTENT, p); }
+
+    common_peg_parser tag_with_safe_content(const std::string &       tag_name,
+                        const std::string &       marker,
+                        const common_peg_parser & p);
+
+    // Low-level tag methods
     common_peg_parser tool(const common_peg_parser & p) { return tag(TOOL, p); }
     common_peg_parser tool_open(const common_peg_parser & p) { return atomic(tag(TOOL_OPEN, p)); }
     common_peg_parser tool_close(const common_peg_parser & p) { return atomic(tag(TOOL_CLOSE, p)); }
     common_peg_parser tool_id(const common_peg_parser & p) { return atomic(tag(TOOL_ID, p)); }
     common_peg_parser tool_name(const common_peg_parser & p) { return atomic(tag(TOOL_NAME, p)); }
     common_peg_parser tool_args(const common_peg_parser & p) { return tag(TOOL_ARGS, p); }
-};
-
-class common_chat_peg_native_mapper : public common_chat_peg_mapper {
-    common_chat_tool_call * current_tool;
-
-  public:
-    common_chat_peg_native_mapper(common_chat_msg & msg) : common_chat_peg_mapper(msg) {}
-
-    void map(const common_peg_ast_node & node) override;
-};
-
-inline common_peg_arena build_chat_peg_native_parser(const std::function<common_peg_parser(common_chat_peg_native_builder & builder)> & fn) {
-    common_chat_peg_native_builder builder;
-    builder.set_root(fn(builder));
-    return builder.build();
-}
-
-class common_chat_peg_constructed_builder : public common_chat_peg_builder {
-  public:
-    static constexpr const char * TOOL = "tool";
-    static constexpr const char * TOOL_OPEN = "tool-open";
-    static constexpr const char * TOOL_CLOSE = "tool-close";
-    static constexpr const char * TOOL_NAME = "tool-name";
-    static constexpr const char * TOOL_ARG = "tool-arg";
-    static constexpr const char * TOOL_ARG_OPEN = "tool-arg-open";
-    static constexpr const char * TOOL_ARG_CLOSE = "tool-arg-close";
-    static constexpr const char * TOOL_ARG_NAME = "tool-arg-name";
-    static constexpr const char * TOOL_ARG_STRING_VALUE = "tool-arg-string-value";
-    static constexpr const char * TOOL_ARG_JSON_VALUE = "tool-arg-json-value";
-
-    common_peg_parser tool(const common_peg_parser & p) { return tag(TOOL, p); }
-    common_peg_parser tool_open(const common_peg_parser & p) { return atomic(tag(TOOL_OPEN, p)); }
-    common_peg_parser tool_close(const common_peg_parser & p) { return atomic(tag(TOOL_CLOSE, p)); }
-    common_peg_parser tool_name(const common_peg_parser & p) { return atomic(tag(TOOL_NAME, p)); }
     common_peg_parser tool_arg(const common_peg_parser & p) { return tag(TOOL_ARG, p); }
     common_peg_parser tool_arg_open(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_OPEN, p)); }
     common_peg_parser tool_arg_close(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_CLOSE, p)); }
     common_peg_parser tool_arg_name(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_NAME, p)); }
+    common_peg_parser tool_arg_value(const common_peg_parser & p) { return tag(TOOL_ARG_VALUE, p); }
+
+    // Use for schema-declared string types - won't be treated as potential JSON container
     common_peg_parser tool_arg_string_value(const common_peg_parser & p) { return tag(TOOL_ARG_STRING_VALUE, p); }
-    common_peg_parser tool_arg_json_value(const common_peg_parser & p) { return tag(TOOL_ARG_JSON_VALUE, p); }
+    common_peg_parser tool_arg_json_value(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_VALUE, p)); }
+
+    // Legacy-compatible helper for building standard JSON tool calls
+    // Used by tests and manual parsers
+    // name_key/args_key: JSON key names for function name and arguments
+    //   Empty or "name"/"arguments" will accept both common variations
+    //   Supports dot notation for nested objects (e.g., "function.name")
+    // array_wrapped: if true, tool calls are wrapped in JSON array [...]
+    // function_is_key: if true, function name is the JSON key (e.g., {"func_name": {...}})
+    // call_id_key: JSON key for string call ID (e.g., "id")
+    // gen_call_id_key: JSON key for generated integer call ID (e.g., "tool_call_id")
+    // parameters_order: order in which JSON fields should be parsed
+    common_peg_parser standard_json_tools(const std::string &              section_start,
+                                          const std::string &              section_end,
+                                          const nlohmann::json &           tools,
+                                          bool                             parallel_tool_calls,
+                                          bool                             force_tool_calls,
+                                          const std::string &              name_key = "",
+                                          const std::string &              args_key = "",
+                                          bool                             array_wrapped = false,
+                                          bool                             function_is_key = false,
+                                          const std::string &              call_id_key = "",
+                                          const std::string &              gen_call_id_key = "",
+                                          const std::vector<std::string> & parameters_order = {});
+
+    // Legacy-compatible helper for building XML/tagged style tool calls
+    // Used by tests and manual parsers
+    common_peg_parser standard_constructed_tools(const std::map<std::string, std::string> & markers,
+                                                 const nlohmann::json &                     tools,
+                                                 bool                                       parallel_tool_calls,
+                                                 bool                                       force_tool_calls);
+
+    // Helper for Python-style function call format: name(arg1="value1", arg2=123)
+    // Used by LFM2 and similar templates
+    common_peg_parser python_style_tool_calls(const nlohmann::json & tools,
+                                              bool                   parallel_tool_calls);
+
+  private:
+    // Implementation helpers for standard_json_tools — one per JSON tool call layout mode
+    common_peg_parser build_json_tools_function_is_key(const nlohmann::json & tools,
+                                                       const std::string &    args_key,
+                                                       const std::string &    effective_args_key,
+                                                       const std::string &    call_id_key,
+                                                       const std::string &    gen_call_id_key);
+
+    common_peg_parser build_json_tools_nested_keys(const nlohmann::json & tools,
+                                                   const std::string &    effective_name_key,
+                                                   const std::string &    effective_args_key,
+                                                   const std::string &    call_id_key,
+                                                   const std::string &    gen_call_id_key);
+
+    common_peg_parser build_json_tools_flat_keys(const nlohmann::json &           tools,
+                                                 const std::string &              effective_name_key,
+                                                 const std::string &              effective_args_key,
+                                                 const std::string &              call_id_key,
+                                                 const std::string &              gen_call_id_key,
+                                                 const std::vector<std::string> & parameters_order);
 };
 
-class common_chat_peg_constructed_mapper : public common_chat_peg_mapper {
-    common_chat_tool_call * current_tool;
-    int arg_count = 0;
-    bool needs_closing_quote = false;
-
-  public:
-    common_chat_peg_constructed_mapper(common_chat_msg & msg) : common_chat_peg_mapper(msg) {}
-
-    void map(const common_peg_ast_node & node) override;
-};
-
-inline common_peg_arena build_chat_peg_constructed_parser(const std::function<common_peg_parser(common_chat_peg_constructed_builder & builder)> & fn) {
-    common_chat_peg_constructed_builder builder;
-    builder.set_root(fn(builder));
-    return builder.build();
+inline common_peg_arena build_chat_peg_parser(
+  const std::function<common_peg_parser(common_chat_peg_builder & builder)> & fn) {
+  common_chat_peg_builder builder;
+  builder.set_root(fn(builder));
+  return builder.build();
 }
+
+class tag_based_peg_mapper {
+  public:
+    std::map<std::string, std::string> tags;
+
+    void from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result);
+};
+
+struct tagged_parse_result {
+    common_peg_parse_result              result;
+    std::map<std::string, std::string> tags;
+};
+
+struct tagged_peg_parser {
+    common_peg_arena arena;
+    common_peg_parse_flags flags = COMMON_PEG_PARSE_FLAG_NONE;
+
+    tagged_peg_parser & withDebug() {
+      flags |= COMMON_PEG_PARSE_FLAG_DEBUG;
+      return *this;
+    }
+
+    tagged_peg_parser & withoutDebug() {
+      flags = flags & ~COMMON_PEG_PARSE_FLAG_DEBUG;
+      return *this;
+    }
+
+    tagged_parse_result parse_and_extract(const std::string & input, common_peg_parse_flags extra_flags = COMMON_PEG_PARSE_FLAG_NONE) const;
+    tagged_parse_result parse_anywhere_and_extract(const std::string & input) const;
+};
+
+tagged_peg_parser build_tagged_peg_parser(
+    const std::function<common_peg_parser(common_peg_parser_builder & builder)> & fn);
+

common/chat.h

@@ -3,17 +3,30 @@
 #pragma once
 
 #include "common.h"
+#include "jinja/parser.h"
+#include "nlohmann/json_fwd.hpp"
 #include "peg-parser.h"
-#include <functional>
+#include "jinja/runtime.h"
+#include "jinja/caps.h"
+#include "nlohmann/json.hpp"
+
 #include <chrono>
+#include <functional>
+#include <map>
 #include <string>
 #include <vector>
-#include <map>
+
+using chat_template_caps = jinja::caps;
+using json = nlohmann::ordered_json;
 
 #include <nlohmann/json_fwd.hpp>
 
 struct common_chat_templates;
 
+namespace autoparser {
+struct templates_params;
+}  // namespace autoparser
+
 struct common_chat_tool_call {
     std::string name;
     std::string arguments;
@@ -38,21 +51,85 @@ struct common_chat_msg_content_part {
     }
 };
 
+struct common_chat_template {
+    jinja::program prog;
+    std::string bos_tok;
+    std::string eos_tok;
+    std::string src;
+    chat_template_caps caps;
+
+    common_chat_template(const std::string & src, const std::string & bos_token, const std::string & eos_token) {
+        jinja::lexer lexer;
+        auto lexer_res = lexer.tokenize(src);
+        this->prog = jinja::parse_from_tokens(lexer_res);
+
+        this->src = lexer_res.source;
+        this->bos_tok = bos_token;
+        this->eos_tok = eos_token;
+
+        this->caps = jinja::caps_get(prog);
+        // LOG_INF("%s: caps:\n%s\n", __func__, this->caps.to_string().c_str());
+    }
+
+    const std::string & source() const { return src; }
+    const std::string & bos_token() const { return bos_tok; }
+    const std::string & eos_token() const { return eos_tok; }
+
+    // TODO: this is ugly, refactor it somehow
+    json add_system(const json & messages, const std::string & system_prompt) const {
+        GGML_ASSERT(messages.is_array());
+        auto msgs_copy = messages;
+        if (!caps.supports_system_role) {
+            if (msgs_copy.empty()) {
+                msgs_copy.insert(msgs_copy.begin(), json{
+                    {"role", "user"},
+                    {"content", system_prompt}
+                });
+            } else {
+                auto & first_msg = msgs_copy[0];
+                if (!first_msg.contains("content")) {
+                    first_msg["content"] = "";
+                }
+                first_msg["content"] = system_prompt + "\n\n"
+                    + first_msg["content"].get<std::string>();
+            }
+        } else {
+            if (msgs_copy.empty() || msgs_copy[0].at("role") != "system") {
+                msgs_copy.insert(msgs_copy.begin(), json{
+                    {"role", "system"},
+                    {"content", system_prompt}
+                });
+            } else if (msgs_copy[0].at("role") == "system") {
+                msgs_copy[0]["content"] = system_prompt;
+            }
+        }
+        return msgs_copy;
+    }
+
+    chat_template_caps original_caps() const {
+        return caps;
+    }
+
+};
+
 struct common_chat_msg {
-    std::string role;
-    std::string content;
+    std::string                               role;
+    std::string                               content;
     std::vector<common_chat_msg_content_part> content_parts;
-    std::vector<common_chat_tool_call> tool_calls;
-    std::string reasoning_content;
-    std::string tool_name;
-    std::string tool_call_id;
+    std::vector<common_chat_tool_call>        tool_calls;
+    std::string                               reasoning_content;
+    std::string                               tool_name;
+    std::string                               tool_call_id;
 
     nlohmann::ordered_json to_json_oaicompat(bool concat_typed_text = false) const;
 
     bool empty() const {
-        return content.empty() && content_parts.empty() && tool_calls.empty() && reasoning_content.empty() && tool_name.empty() && tool_call_id.empty();
+        return content.empty() && content_parts.empty() && tool_calls.empty() && reasoning_content.empty() &&
+               tool_name.empty() && tool_call_id.empty();
     }
-    void set_tool_call_ids(std::vector<std::string> & ids_cache, const std::function<std::string()> & gen_tool_call_id) {
+
+    void set_tool_call_ids(std::vector<std::string> &           ids_cache,
+                           const std::function<std::string()> & gen_tool_call_id) {
         for (auto i = 0u; i < tool_calls.size(); i++) {
             if (ids_cache.size() <= i) {
                 auto id = tool_calls[i].id;
@@ -64,32 +141,28 @@ struct common_chat_msg {
             tool_calls[i].id = ids_cache[i];
         }
     }
+
     bool operator==(const common_chat_msg & other) const {
-        return role == other.role
-            && content == other.content
-            && content_parts == other.content_parts
-            && tool_calls == other.tool_calls
-            && reasoning_content == other.reasoning_content
-            && tool_name == other.tool_name
-            && tool_call_id == other.tool_call_id;
-    }
-    bool operator!=(const common_chat_msg & other) const {
-        return !(*this == other);
+        return role == other.role && content == other.content && content_parts == other.content_parts &&
+               tool_calls == other.tool_calls && reasoning_content == other.reasoning_content &&
+               tool_name == other.tool_name && tool_call_id == other.tool_call_id;
     }
+
+    bool operator!=(const common_chat_msg & other) const { return !(*this == other); }
 };
 
 struct common_chat_msg_diff {
-    std::string reasoning_content_delta;
-    std::string content_delta;
-    size_t tool_call_index = std::string::npos;
+    std::string           reasoning_content_delta;
+    std::string           content_delta;
+    size_t                tool_call_index = std::string::npos;
     common_chat_tool_call tool_call_delta;
 
-    static std::vector<common_chat_msg_diff> compute_diffs(const common_chat_msg & msg_prv, const common_chat_msg & msg_new);
+    static std::vector<common_chat_msg_diff> compute_diffs(const common_chat_msg & msg_prv,
+                                                           const common_chat_msg & msg_new);
 
     bool operator==(const common_chat_msg_diff & other) const {
-        return content_delta == other.content_delta
-        && tool_call_index == other.tool_call_index
-        && tool_call_delta == other.tool_call_delta;
+        return content_delta == other.content_delta && tool_call_index == other.tool_call_index &&
+               tool_call_delta == other.tool_call_delta;
     }
 };
 
@@ -107,65 +180,39 @@ enum common_chat_tool_choice {
 
 enum common_chat_format {
     COMMON_CHAT_FORMAT_CONTENT_ONLY,
-    COMMON_CHAT_FORMAT_GENERIC,
-    COMMON_CHAT_FORMAT_MISTRAL_NEMO,
-    COMMON_CHAT_FORMAT_MAGISTRAL,
-    COMMON_CHAT_FORMAT_LLAMA_3_X,
-    COMMON_CHAT_FORMAT_LLAMA_3_X_WITH_BUILTIN_TOOLS,
-    COMMON_CHAT_FORMAT_DEEPSEEK_R1,
-    COMMON_CHAT_FORMAT_FIREFUNCTION_V2,
-    COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2,
-    COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1,
-    COMMON_CHAT_FORMAT_DEEPSEEK_V3_1,
-    COMMON_CHAT_FORMAT_HERMES_2_PRO,
-    COMMON_CHAT_FORMAT_COMMAND_R7B,
-    COMMON_CHAT_FORMAT_GRANITE,
-    COMMON_CHAT_FORMAT_GPT_OSS,
-    COMMON_CHAT_FORMAT_SEED_OSS,
-    COMMON_CHAT_FORMAT_NEMOTRON_V2,
-    COMMON_CHAT_FORMAT_APERTUS,
-    COMMON_CHAT_FORMAT_LFM2_WITH_JSON_TOOLS,
-    COMMON_CHAT_FORMAT_GLM_4_5,
-    COMMON_CHAT_FORMAT_MINIMAX_M2,
-    COMMON_CHAT_FORMAT_KIMI_K2,
-    COMMON_CHAT_FORMAT_QWEN3_CODER_XML,
-    COMMON_CHAT_FORMAT_APRIEL_1_5,
-    COMMON_CHAT_FORMAT_XIAOMI_MIMO,
-    COMMON_CHAT_FORMAT_SOLAR_OPEN,
-    COMMON_CHAT_FORMAT_EXAONE_MOE,
 
     // These are intended to be parsed by the PEG parser
     COMMON_CHAT_FORMAT_PEG_SIMPLE,
     COMMON_CHAT_FORMAT_PEG_NATIVE,
-    COMMON_CHAT_FORMAT_PEG_CONSTRUCTED,
 
-    COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats
+    COMMON_CHAT_FORMAT_COUNT,  // Not a format, just the # formats
 };
 
 struct common_chat_templates_inputs {
-    std::vector<common_chat_msg> messages;
-    std::string grammar;
-    std::string json_schema;
-    bool add_generation_prompt = true;
-    bool use_jinja = true;
+    std::vector<common_chat_msg>          messages;
+    std::string                           grammar;
+    std::string                           json_schema;
+    bool                                  add_generation_prompt = true;
+    bool                                  use_jinja             = true;
     // Parameters below only supported when use_jinja is true
-    std::vector<common_chat_tool> tools;
-    common_chat_tool_choice tool_choice = COMMON_CHAT_TOOL_CHOICE_AUTO;
-    bool parallel_tool_calls = false;
-    common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_NONE; // TODO: refactor this to "bool enable_thinking"
-    bool enable_thinking = true;
-    std::chrono::system_clock::time_point now = std::chrono::system_clock::now();
-    std::map<std::string, std::string> chat_template_kwargs;
-    bool add_bos = false;
-    bool add_eos = false;
+    std::vector<common_chat_tool>         tools;
+    common_chat_tool_choice               tool_choice         = COMMON_CHAT_TOOL_CHOICE_AUTO;
+    bool                                  parallel_tool_calls = false;
+    common_reasoning_format               reasoning_format    = COMMON_REASONING_FORMAT_NONE; // TODO: refactor this to "bool enable_thinking"
+    bool                                  enable_thinking     = true;
+    std::chrono::system_clock::time_point now                 = std::chrono::system_clock::now();
+    std::map<std::string, std::string>    chat_template_kwargs;
+    bool                                  add_bos = false;
+    bool                                  add_eos = false;
 };
 
 struct common_chat_params {
     common_chat_format                  format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
     std::string                         prompt;
     std::string                         grammar;
-    bool                                grammar_lazy = false;
+    bool                                grammar_lazy         = false;
     bool                                thinking_forced_open = false;
+    bool                                supports_thinking    = false;
     std::vector<common_grammar_trigger> grammar_triggers;
     std::vector<std::string>            preserved_tokens;
     std::vector<std::string>            additional_stops;
@@ -175,13 +222,14 @@ struct common_chat_params {
 // per-message parsing syntax
 // should be derived from common_chat_params
 struct common_chat_parser_params {
-    common_chat_format       format                = COMMON_CHAT_FORMAT_CONTENT_ONLY;
-    common_reasoning_format  reasoning_format      = COMMON_REASONING_FORMAT_NONE; // TODO: refactor this to "bool parse_reasoning"
+    common_chat_format      format               = COMMON_CHAT_FORMAT_CONTENT_ONLY;
+    common_reasoning_format reasoning_format     = COMMON_REASONING_FORMAT_NONE; // TODO: refactor this to "bool parse_reasoning"
     // Whether reasoning_content should be inlined in the content (e.g. for reasoning_format=deepseek in stream mode)
-    bool                     reasoning_in_content  = false;
-    bool                     thinking_forced_open  = false;
-    bool                     parse_tool_calls      = true;
-    common_peg_arena         parser                = {};
+    bool                    reasoning_in_content = false;
+    bool                    thinking_forced_open = false;
+    bool                    parse_tool_calls     = true;
+    bool                    debug                = false;  // Enable debug output for PEG parser
+    common_peg_arena        parser               = {};
     common_chat_parser_params() = default;
     common_chat_parser_params(const common_chat_params & chat_params) {
         format               = chat_params.format;
@@ -194,45 +242,42 @@ bool common_chat_verify_template(const std::string & tmpl, bool use_jinja);
 
 void common_chat_templates_free(struct common_chat_templates * tmpls);
 
-struct common_chat_templates_deleter { void operator()(common_chat_templates * tmpls) { common_chat_templates_free(tmpls); } };
+struct common_chat_templates_deleter {
+    void operator()(common_chat_templates * tmpls) { common_chat_templates_free(tmpls); }
+};
 
 typedef std::unique_ptr<struct common_chat_templates, common_chat_templates_deleter> common_chat_templates_ptr;
 
-common_chat_templates_ptr common_chat_templates_init(
-                                    const struct llama_model * model,
-                                           const std::string & chat_template_override,
-                                           const std::string & bos_token_override = "",
-                                           const std::string & eos_token_override = "");
+common_chat_templates_ptr common_chat_templates_init(const struct llama_model * model,
+                                                     const std::string &        chat_template_override,
+                                                     const std::string &        bos_token_override = "",
+                                                     const std::string &        eos_token_override = "");
 
 bool         common_chat_templates_was_explicit(const struct common_chat_templates * tmpls);
 std::string  common_chat_templates_source(const struct common_chat_templates * tmpls, const std::string & variant = "");
 
-
-struct common_chat_params      common_chat_templates_apply(
-    const struct common_chat_templates * tmpls,
-    const struct common_chat_templates_inputs & inputs);
+struct common_chat_params common_chat_templates_apply(const struct common_chat_templates *        tmpls,
+                                                      const struct common_chat_templates_inputs & inputs);
 
 // Format single message, while taking into account the position of that message in chat history
-std::string common_chat_format_single(
-        const struct common_chat_templates * tmpls,
-        const std::vector<common_chat_msg> & past_msg,
-        const common_chat_msg & new_msg,
-        bool add_ass,
-        bool use_jinja);
+std::string common_chat_format_single(const struct common_chat_templates * tmpls,
+                                      const std::vector<common_chat_msg> & past_msg,
+                                      const common_chat_msg &              new_msg,
+                                      bool                                 add_ass,
+                                      bool                                 use_jinja);
 
 // Returns an example of formatted chat
-std::string common_chat_format_example(
-    const struct common_chat_templates * tmpls,
-    bool use_jinja,
-    const std::map<std::string, std::string> & chat_template_kwargs);
+std::string common_chat_format_example(const struct common_chat_templates *       tmpls,
+                                       bool                                       use_jinja,
+                                       const std::map<std::string, std::string> & chat_template_kwargs);
 
-const char*               common_chat_format_name(common_chat_format format);
-common_chat_msg           common_chat_parse(const std::string & input, bool is_partial, const common_chat_parser_params & syntax);
-common_chat_msg           common_chat_peg_parse(const common_peg_arena & parser, const std::string & input, bool is_partial, const common_chat_parser_params & syntax);
+const char *            common_chat_format_name(common_chat_format format);
+common_chat_msg           common_chat_parse(const std::string & input, bool is_partial, const common_chat_parser_params & params);
+common_chat_msg           common_chat_peg_parse(const common_peg_arena & src_parser, const std::string & input, bool is_partial, const common_chat_parser_params & params);
 
 // used by arg and server
-const char *             common_reasoning_format_name(common_reasoning_format format);
-common_reasoning_format  common_reasoning_format_from_name(const std::string & format);
+const char *            common_reasoning_format_name(common_reasoning_format format);
+common_reasoning_format common_reasoning_format_from_name(const std::string & format);
 
 common_chat_tool_choice common_chat_tool_choice_parse_oaicompat(const std::string & tool_choice);
 
@@ -251,3 +296,10 @@ nlohmann::ordered_json common_chat_msg_diff_to_json_oaicompat(const common_chat_
 
 // get template caps, useful for reporting to server /props endpoint
 std::map<std::string, bool> common_chat_templates_get_caps(const common_chat_templates * chat_templates);
+
+std::string common_chat_template_direct_apply(
+    const common_chat_template & tmpl,
+    const autoparser::templates_params & inputs,
+    const std::optional<json> & messages_override = std::nullopt,
+    const std::optional<json> & tools_override = std::nullopt,
+    const std::optional<json> & additional_context = std::nullopt);

common/common.cpp

@@ -452,34 +452,6 @@ void string_replace_all(std::string & s, const std::string & search, const std::
     s = std::move(builder);
 }
 
-bool string_ends_with(const std::string_view & str, const std::string_view & suffix) {
-    return str.size() >= suffix.size() && str.compare(str.size()-suffix.size(), suffix.size(), suffix) == 0;
-}
-
-bool string_remove_suffix(std::string & str, const std::string_view & suffix) {
-    bool has_suffix = string_ends_with(str, suffix);
-    if (has_suffix) {
-        str = str.substr(0, str.size() - suffix.size());
-    }
-    return has_suffix;
-}
-
-size_t string_find_partial_stop(const std::string_view & str, const std::string_view & stop) {
-    if (!str.empty() && !stop.empty()) {
-        const char text_last_char = str.back();
-        for (int64_t char_index = stop.size() - 1; char_index >= 0; char_index--) {
-            if (stop[char_index] == text_last_char) {
-                const auto current_partial = stop.substr(0, char_index + 1);
-                if (string_ends_with(str, current_partial)) {
-                    return str.size() - char_index - 1;
-                }
-            }
-        }
-    }
-
-    return std::string::npos;
-}
-
 std::string regex_escape(const std::string & s) {
     static const std::regex special_chars("[.^$|()*+?\\[\\]{}\\\\]");
     return std::regex_replace(s, special_chars, "\\$&");
@@ -704,7 +676,7 @@ bool fs_validate_filename(const std::string & filename, bool allow_subdirs) {
 
     size_t offset = 0;
     while (offset < filename.size()) {
-        utf8_parse_result result = parse_utf8_codepoint(filename, offset);
+        utf8_parse_result result = common_parse_utf8_codepoint(filename, offset);
 
         if (result.status != utf8_parse_result::SUCCESS) {
             return false;
@@ -879,7 +851,8 @@ std::string fs_get_cache_directory() {
     if (getenv("LLAMA_CACHE")) {
         cache_directory = std::getenv("LLAMA_CACHE");
     } else {
-#if defined(__linux__) || defined(__FreeBSD__) || defined(_AIX) || defined(__OpenBSD__)
+#if defined(__linux__) || defined(__FreeBSD__) || defined(_AIX) || \
+        defined(__OpenBSD__) || defined(__NetBSD__)
         if (std::getenv("XDG_CACHE_HOME")) {
             cache_directory = std::getenv("XDG_CACHE_HOME");
         } else if (std::getenv("HOME")) {
@@ -1223,7 +1196,7 @@ common_init_result_ptr common_init_from_params(common_params & params) {
             return res;
         }
 
-        int err = llama_apply_adapter_cvec(
+        int err = llama_set_adapter_cvec(
                 lctx,
                 cvec.data.data(),
                 cvec.data.size(),
@@ -1325,12 +1298,15 @@ std::string get_model_endpoint() {
 }
 
 void common_set_adapter_lora(struct llama_context * ctx, std::vector<common_adapter_lora_info> & lora) {
-    llama_clear_adapter_lora(ctx);
-    for (auto & la : lora) {
-        if (la.scale != 0.0f) {
-            llama_set_adapter_lora(ctx, la.ptr, la.scale);
-        }
+    std::vector<llama_adapter_lora *> loras;
+    std::vector<float> scales;
+
+    for (auto & la: lora) {
+        loras.push_back(la.ptr);
+        scales.push_back(la.scale);
     }
+
+    llama_set_adapters_lora(ctx, loras.data(), loras.size(), scales.data());
 }
 
 struct llama_model_params common_model_params_to_llama(common_params & params) {
@@ -1784,3 +1760,65 @@ float lr_opt::get_lr(float epoch) const {
     LOG_INF("epoch %.2g lr=%.2g\n", epoch, r);
     return r;
 }
+
+bool common_replay_last_token(struct llama_context * ctx, llama_token last_token, int32_t pos) {
+    llama_batch batch = llama_batch_get_one(&last_token, 1);
+    batch.pos = &pos;
+    if (llama_decode(ctx, batch)) {
+        LOG_ERR("%s: failed to replay last token\n", __func__);
+        return false;
+    }
+    return true;
+}
+
+bool common_prompt_batch_decode(
+              struct llama_context * ctx,
+    const std::vector<llama_token> & tokens,
+                               int & n_past,
+                               int   n_batch,
+                  std::string_view   state_path,
+                              bool   save_state) {
+    const int n_eval = tokens.size();
+    if (n_eval == 0) {
+        return true;
+    }
+
+    if (save_state && n_eval > 1) {
+        const int n_tokens_before_last = n_eval - 1;
+
+        GGML_ASSERT(n_eval <= n_batch);
+
+        // Decode all but the last token so we can save the memory state before decoding the last token.
+        // This is done so we can restore the session state later and replay the last token.
+        // Memory implementations in recurrent/hybrid models don't support removing tokens from their
+        // memory, so we can't just remove the last token from the memory and replay the last token which
+        // is the reason for this logic.
+        if (llama_decode(ctx, llama_batch_get_one(const_cast<llama_token*>(tokens.data()), n_tokens_before_last))) {
+            LOG_ERR("%s : failed to eval\n", __func__);
+            return false;
+        }
+        n_past += n_tokens_before_last;
+
+        llama_state_save_file(ctx, state_path.data(), tokens.data(), n_tokens_before_last);
+        LOG_INF("saved session before last token to %s, n_tokens = %d\n", state_path.data(), n_tokens_before_last);
+
+        llama_token last_token = tokens.back();
+        llama_batch batch = llama_batch_get_one(&last_token, 1);
+        int32_t pos = n_past;
+        batch.pos = &pos;
+
+        if (llama_decode(ctx, batch)) {
+            LOG_ERR("%s : failed to eval last token\n", __func__);
+            return false;
+        }
+        n_past++;
+    } else {
+        if (llama_decode(ctx, llama_batch_get_one(const_cast<llama_token*>(tokens.data()), n_eval))) {
+            LOG_ERR("%s : failed to eval\n", __func__);
+            return false;
+        }
+        n_past += n_eval;
+    }
+
+    return true;
+}

common/common.h

@@ -104,6 +104,7 @@ enum llama_example {
     LLAMA_EXAMPLE_DIFFUSION,
     LLAMA_EXAMPLE_FINETUNE,
     LLAMA_EXAMPLE_FIT_PARAMS,
+    LLAMA_EXAMPLE_RESULTS,
 
     LLAMA_EXAMPLE_COUNT,
 };
@@ -410,7 +411,8 @@ struct common_params {
 
     struct common_params_model model;
 
-    std::string model_alias          = ""; // model alias                                                   // NOLINT
+    std::set<std::string> model_alias;     // model aliases                                                 // NOLINT
+    std::set<std::string> model_tags;      // model tags (informational, not used for routing)              // NOLINT
     std::string hf_token             = ""; // HF token                                                      // NOLINT
     std::string prompt               = "";                                                                  // NOLINT
     std::string system_prompt        = "";                                                                  // NOLINT
@@ -455,6 +457,8 @@ struct common_params {
 
     bool   kl_divergence    = false; // compute KL divergence
 
+    bool check             = false; // check rather than generate results for llama-results
+
     bool usage             = false; // print usage
     bool completion        = false; // print source-able completion script
     bool use_color         = false; // use color to distinguish generations and inputs
@@ -515,14 +519,15 @@ struct common_params {
     std::string cls_sep    = "\t";  // separator of classification sequences
 
     // server params
-    int32_t port              = 8080;         // server listens on this network port
-    int32_t timeout_read      = 600;          // http read timeout in seconds
-    int32_t timeout_write     = timeout_read; // http write timeout in seconds
-    int32_t n_threads_http    = -1;           // number of threads to process HTTP requests (TODO: support threadpool)
-    int32_t n_cache_reuse     = 0;            // min chunk size to reuse from the cache via KV shifting
-    bool    cache_prompt      = true;         // whether to enable prompt caching
-    int32_t n_ctx_checkpoints = 8;            // max number of context checkpoints per slot
-    int32_t cache_ram_mib     = 8192;         // -1 = no limit, 0 - disable, 1 = 1 MiB, etc.
+    int32_t port                = 8080;          // server listens on this network port
+    int32_t timeout_read        = 600;           // http read timeout in seconds
+    int32_t timeout_write       = timeout_read;  // http write timeout in seconds
+    int32_t n_threads_http      = -1;    // number of threads to process HTTP requests (TODO: support threadpool)
+    int32_t n_cache_reuse       = 0;     // min chunk size to reuse from the cache via KV shifting
+    bool    cache_prompt        = true;  // whether to enable prompt caching
+    int32_t n_ctx_checkpoints   = 32;     // max number of context checkpoints per slot
+    int32_t checkpoint_every_nt = 8192;   // make a checkpoint every n tokens during prefill
+    int32_t cache_ram_mib       = 8192;  // -1 = no limit, 0 - disable, 1 = 1 MiB, etc.
 
     std::string hostname      = "127.0.0.1";
     std::string public_path   = "";                                                                         // NOLINT
@@ -544,6 +549,7 @@ struct common_params {
 
     // webui configs
     bool webui = true;
+    bool webui_mcp_proxy = false;
     std::string webui_config_json;
 
     // "advanced" endpoints are disabled by default for better security
@@ -670,30 +676,55 @@ static std::vector<T> string_split(const std::string & str, char delim) {
 }
 
 template<>
-std::vector<std::string> string_split<std::string>(const std::string & input, char separator)
+inline std::vector<std::string> string_split<std::string>(const std::string & str, char delim)
 {
     std::vector<std::string> parts;
     size_t begin_pos = 0;
-    size_t separator_pos = input.find(separator);
-    while (separator_pos != std::string::npos) {
-        std::string part = input.substr(begin_pos, separator_pos - begin_pos);
+    size_t delim_pos = str.find(delim);
+    while (delim_pos != std::string::npos) {
+        std::string part = str.substr(begin_pos, delim_pos - begin_pos);
         parts.emplace_back(part);
-        begin_pos = separator_pos + 1;
-        separator_pos = input.find(separator, begin_pos);
+        begin_pos = delim_pos + 1;
+        delim_pos = str.find(delim, begin_pos);
     }
-    parts.emplace_back(input.substr(begin_pos, separator_pos - begin_pos));
+    parts.emplace_back(str.substr(begin_pos));
     return parts;
 }
 
-static bool string_starts_with(const std::string & str,
-                               const std::string & prefix) {  // While we wait for C++20's std::string::starts_with...
-    return str.rfind(prefix, 0) == 0;
+// remove when moving to c++20
+inline bool string_starts_with(std::string_view str, std::string_view prefix) {
+    return str.size() >= prefix.size() &&
+           str.compare(0, prefix.size(), prefix) == 0;
 }
 
-// While we wait for C++20's std::string::ends_with...
-bool string_ends_with(const std::string_view & str, const std::string_view & suffix);
-bool string_remove_suffix(std::string & str, const std::string_view & suffix);
-size_t string_find_partial_stop(const std::string_view & str, const std::string_view & stop);
+// remove when moving to c++20
+inline bool string_ends_with(std::string_view str, std::string_view suffix) {
+    return str.size() >= suffix.size() &&
+           str.compare(str.size() - suffix.size(), suffix.size(), suffix) == 0;
+}
+
+inline bool string_remove_suffix(std::string & str, std::string_view suffix) {
+    if (string_ends_with(str, suffix)) {
+        str.resize(str.size() - suffix.size());
+        return true;
+    }
+    return false;
+}
+
+inline size_t string_find_partial_stop(std::string_view str, std::string_view stop) {
+    if (!str.empty() && !stop.empty()) {
+        const size_t max_len = std::min(str.size(), stop.size());
+        const char last_char = str.back();
+        for (size_t len = max_len; len > 0; --len) {
+            if (stop[len - 1] == last_char) {
+                if (string_ends_with(str, stop.substr(0, len))) {
+                    return str.size() - len;
+                }
+            }
+        }
+    }
+    return std::string::npos;
+}
 
 bool string_parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides);
 void string_process_escapes(std::string & input);
@@ -779,6 +810,23 @@ void common_batch_add(
     const std::vector<llama_seq_id> & seq_ids,
                                bool   logits);
 
+// decodes a single batch of tokens for a prompt and manages session tokens
+//
+// Note: We save state before the last token so that we can replay it to ensure
+// compatibility with all memory types. Recurrent/hybrid models cannot remove
+// tokens from memory, so this approach works across all model architectures.
+bool common_prompt_batch_decode(
+              struct llama_context * ctx,
+    const std::vector<llama_token> & embd,
+                               int & n_past,
+                               int   n_batch,
+                  std::string_view   state_path,
+                              bool   save_state);
+
+// replays the last token after loading state to regenerate logits
+// used after loading session state to ensure the sampling context has valid logits
+bool common_replay_last_token(struct llama_context * ctx, llama_token last_token, int32_t pos);
+
 //
 // Vocab utils
 //
@@ -826,7 +874,7 @@ std::string common_detokenize(
 // Embedding utils
 //
 
-// TODO: repace embd_norm with an enum
+// TODO: replace embd_norm with an enum
 void common_embd_normalize(const float * inp, float * out, int n, int embd_norm);
 
 float common_embd_similarity_cos(const float * embd1, const float * embd2, int n);
@@ -870,11 +918,11 @@ const char * const LLM_KV_SPLIT_TENSORS_COUNT = "split.tensors.count";
 
 const char * const LLM_FFN_EXPS_REGEX = "\\.ffn_(up|down|gate)_(ch|)exps";
 
-static std::string llm_ffn_exps_block_regex(int idx) {
+inline std::string llm_ffn_exps_block_regex(int idx) {
     return string_format("blk\\.%d%s", idx, LLM_FFN_EXPS_REGEX);
 }
 
-static llama_model_tensor_buft_override llm_ffn_exps_cpu_override() {
+inline llama_model_tensor_buft_override llm_ffn_exps_cpu_override() {
     return { LLM_FFN_EXPS_REGEX, ggml_backend_cpu_buffer_type() };
 }
 

common/console.cpp

@@ -80,6 +80,8 @@ namespace console {
     static termios      initial_state;
 #endif
 
+    static completion_callback completion_cb = nullptr;
+
     //
     // Init and cleanup
     //
@@ -493,7 +495,7 @@ namespace console {
     }
 
     static void set_line_contents(std::string new_line, std::string & line, std::vector<int> & widths, size_t & char_pos,
-                                  size_t & byte_pos) {
+                                  size_t & byte_pos, int cursor_byte_pos = -1) {
         move_to_line_start(char_pos, byte_pos, widths);
         clear_current_line(widths);
 
@@ -503,6 +505,7 @@ namespace console {
         char_pos = 0;
 
         size_t idx = 0;
+        int back_width = 0;
         while (idx < line.size()) {
             size_t advance = 0;
             char32_t cp = decode_utf8(line, idx, advance);
@@ -511,8 +514,15 @@ namespace console {
             if (real_width < 0) real_width = 0;
             widths.push_back(real_width);
             idx += advance;
-            ++char_pos;
-            byte_pos = idx;
+            if (cursor_byte_pos >= 0 && static_cast<size_t>(cursor_byte_pos) < idx) {
+                back_width += real_width;
+            } else {
+                ++char_pos;
+                byte_pos = idx;
+            }
+        }
+        if (cursor_byte_pos >= 0) {
+            move_cursor(-back_width);
         }
     }
 
@@ -784,6 +794,20 @@ namespace console {
                 break;
             }
 
+            if (completion_cb && input_char == '\t') {
+                auto candidates = completion_cb(line, byte_pos);
+
+                if (!candidates.empty()) {
+                    if (candidates.size() > 1 || candidates[0].first != line) {
+                        // TODO?: Display all candidates
+                        set_line_contents(candidates[0].first, line, widths, char_pos, byte_pos, candidates[0].second);
+                    } else {
+                        // TODO: Move cursor to new byte_pos
+                    }
+                    continue;
+                }
+            }
+
             if (input_char == (char32_t) WEOF || input_char == 0x04 /* Ctrl+D */) {
                 end_of_stream = true;
                 break;
@@ -1062,6 +1086,10 @@ namespace console {
         return readline_advanced(line, multiline_input);
     }
 
+    void set_completion_callback(completion_callback cb) {
+        completion_cb = cb;
+    }
+
     namespace spinner {
         static const char LOADING_CHARS[] = {'|', '/', '-', '\\'};
         static std::condition_variable cv_stop;

common/console.h

@@ -4,7 +4,9 @@
 
 #include "common.h"
 
+#include <functional>
 #include <string>
+#include <vector>
 
 enum display_type {
     DISPLAY_TYPE_RESET = 0,
@@ -21,6 +23,9 @@ namespace console {
     void set_display(display_type display);
     bool readline(std::string & line, bool multiline_input);
 
+    using completion_callback = std::function<std::vector<std::pair<std::string, size_t>>(std::string_view, size_t)>;
+    void set_completion_callback(completion_callback cb);
+
     namespace spinner {
         void start();
         void stop();

common/debug.h

@@ -18,7 +18,7 @@ template <bool abort_on_nan> void common_debug_print_tensor(uint8_t * data, ggml
 // prints tensors that are processed in the computation graph
 // by default prints all tensors, but can be configured by creating a `base_callback_data` instance with
 // non-empty filter_patterns. See examples/debug.ccp for possible usage patterns
-// The template parameter determins whether an error should be thrown whenever a NaN is encountered
+// The template parameter determines whether an error should be thrown whenever a NaN is encountered
 // in a tensor (useful for stopping debug sessions on first erroneous tensor)
 // The callback data will be passed as the third parameter (user_data)
 template <bool abort_on_nan> bool common_debug_cb_eval(struct ggml_tensor * t, bool ask, void * user_data);

common/download.cpp

@@ -19,9 +19,7 @@
 #include <thread>
 #include <vector>
 
-#if defined(LLAMA_USE_HTTPLIB)
 #include "http.h"
-#endif
 
 #ifndef __EMSCRIPTEN__
 #ifdef __linux__
@@ -114,44 +112,18 @@ static void write_etag(const std::string & path, const std::string & etag) {
 }
 
 static std::string read_etag(const std::string & path) {
-    std::string none;
     const std::string etag_path = path + ".etag";
-
-    if (std::filesystem::exists(etag_path)) {
-        std::ifstream etag_in(etag_path);
-        if (!etag_in) {
-            LOG_ERR("%s: could not open .etag file for reading: %s\n", __func__, etag_path.c_str());
-            return none;
-        }
-        std::string etag;
-        std::getline(etag_in, etag);
-        return etag;
+    if (!std::filesystem::exists(etag_path)) {
+        return {};
     }
-
-    // no etag file, but maybe there is an old .json
-    // remove this code later
-    const std::string metadata_path = path + ".json";
-
-    if (std::filesystem::exists(metadata_path)) {
-        std::ifstream metadata_in(metadata_path);
-        try {
-            nlohmann::json metadata_json;
-            metadata_in >> metadata_json;
-            LOG_DBG("%s: previous metadata file found %s: %s\n", __func__, metadata_path.c_str(),
-                    metadata_json.dump().c_str());
-            if (metadata_json.contains("etag") && metadata_json.at("etag").is_string()) {
-                std::string etag = metadata_json.at("etag");
-                write_etag(path, etag);
-                if (!std::filesystem::remove(metadata_path)) {
-                    LOG_WRN("%s: failed to delete old .json metadata file: %s\n", __func__, metadata_path.c_str());
-                }
-                return etag;
-            }
-        } catch (const nlohmann::json::exception & e) {
-            LOG_ERR("%s: error reading metadata file %s: %s\n", __func__, metadata_path.c_str(), e.what());
-        }
+    std::ifstream etag_in(etag_path);
+    if (!etag_in) {
+        LOG_ERR("%s: could not open .etag file for reading: %s\n", __func__, etag_path.c_str());
+        return {};
     }
-    return none;
+    std::string etag;
+    std::getline(etag_in, etag);
+    return etag;
 }
 
 static bool is_http_status_ok(int status) {
@@ -168,8 +140,6 @@ std::pair<std::string, std::string> common_download_split_repo_tag(const std::st
     return {hf_repo, tag};
 }
 
-#if defined(LLAMA_USE_HTTPLIB)
-
 class ProgressBar {
     static inline std::mutex mutex;
     static inline std::map<const ProgressBar *, int> lines;
@@ -347,62 +317,64 @@ static int common_download_file_single_online(const std::string        & url,
         LOG_INF("%s: no previous model file found %s\n", __func__, path.c_str());
     }
 
-    for (int i = 0; i < max_attempts; ++i) {
-        auto head = cli.Head(parts.path);
-        bool head_ok = head && head->status >= 200 && head->status < 300;
-        if (!head_ok) {
-            LOG_WRN("%s: HEAD invalid http status code received: %d\n", __func__, head ? head->status : -1);
-            if (file_exists) {
-                LOG_INF("%s: Using cached file (HEAD failed): %s\n", __func__, path.c_str());
-                return 304; // 304 Not Modified - fake cached response
-            }
-            return head->status; // cannot use cached file, return raw status code
-            // TODO: maybe retry only on certain codes
-        }
-
-        std::string etag;
-        if (head_ok && head->has_header("ETag")) {
-            etag = head->get_header_value("ETag");
-        }
-
-        size_t total_size = 0;
-        if (head_ok && head->has_header("Content-Length")) {
-            try {
-                total_size = std::stoull(head->get_header_value("Content-Length"));
-            } catch (const std::exception& e) {
-                LOG_WRN("%s: Invalid Content-Length in HEAD response: %s\n", __func__, e.what());
-            }
-        }
-
-        bool supports_ranges = false;
-        if (head_ok && head->has_header("Accept-Ranges")) {
-            supports_ranges = head->get_header_value("Accept-Ranges") != "none";
-        }
-
-        bool should_download_from_scratch = false;
-        if (!last_etag.empty() && !etag.empty() && last_etag != etag) {
-            LOG_WRN("%s: ETag header is different (%s != %s): triggering a new download\n", __func__,
-                    last_etag.c_str(), etag.c_str());
-            should_download_from_scratch = true;
-        }
-
+    auto head = cli.Head(parts.path);
+    if (!head || head->status < 200 || head->status >= 300) {
+        LOG_WRN("%s: HEAD failed, status: %d\n", __func__, head ? head->status : -1);
         if (file_exists) {
-            if (!should_download_from_scratch) {
-                LOG_INF("%s: using cached file: %s\n", __func__, path.c_str());
-                return 304; // 304 Not Modified - fake cached response
-            }
-            LOG_WRN("%s: deleting previous downloaded file: %s\n", __func__, path.c_str());
-            if (remove(path.c_str()) != 0) {
-                LOG_ERR("%s: unable to delete file: %s\n", __func__, path.c_str());
-                return -1;
-            }
+            LOG_INF("%s: using cached file (HEAD failed): %s\n", __func__, path.c_str());
+            return 304; // 304 Not Modified - fake cached response
+        }
+        return head ? head->status : -1;
+    }
+
+    std::string etag;
+    if (head->has_header("ETag")) {
+        etag = head->get_header_value("ETag");
+    }
+
+    size_t total_size = 0;
+    if (head->has_header("Content-Length")) {
+        try {
+            total_size = std::stoull(head->get_header_value("Content-Length"));
+        } catch (const std::exception& e) {
+            LOG_WRN("%s: invalid Content-Length in HEAD response: %s\n", __func__, e.what());
+        }
+    }
+
+    bool supports_ranges = false;
+    if (head->has_header("Accept-Ranges")) {
+        supports_ranges = head->get_header_value("Accept-Ranges") != "none";
+    }
+
+    if (file_exists) {
+        if (etag.empty()) {
+            LOG_INF("%s: using cached file (no server etag): %s\n", __func__, path.c_str());
+            return 304; // 304 Not Modified - fake cached response
+        }
+        if (!last_etag.empty() && last_etag == etag) {
+            LOG_INF("%s: using cached file (same etag): %s\n", __func__, path.c_str());
+            return 304; // 304 Not Modified - fake cached response
+        }
+        if (remove(path.c_str()) != 0) {
+            LOG_ERR("%s: unable to delete file: %s\n", __func__, path.c_str());
+            return -1;
+        }
+    }
+
+    const std::string path_temporary = path + ".downloadInProgress";
+    int delay = retry_delay_seconds;
+
+    for (int i = 0; i < max_attempts; ++i) {
+        if (i) {
+            LOG_WRN("%s: retrying after %d seconds...\n", __func__, delay);
+            std::this_thread::sleep_for(std::chrono::seconds(delay));
+            delay *= retry_delay_seconds;
         }
 
-        const std::string path_temporary = path + ".downloadInProgress";
         size_t existing_size = 0;
 
         if (std::filesystem::exists(path_temporary)) {
-            if (supports_ranges && !should_download_from_scratch) {
+            if (supports_ranges) {
                 existing_size = std::filesystem::file_size(path_temporary);
             } else if (remove(path_temporary.c_str()) != 0) {
                 LOG_ERR("%s: unable to delete file: %s\n", __func__, path_temporary.c_str());
@@ -410,32 +382,23 @@ static int common_download_file_single_online(const std::string        & url,
             }
         }
 
-        // start the download
-        LOG_INF("%s: trying to download model from %s to %s (etag:%s)...\n",
-                __func__, common_http_show_masked_url(parts).c_str(), path_temporary.c_str(), etag.c_str());
-        const bool was_pull_successful = common_pull_file(cli, parts.path, path_temporary, supports_ranges, existing_size, total_size);
-        if (!was_pull_successful) {
-            if (i + 1 < max_attempts) {
-                const int exponential_backoff_delay = std::pow(retry_delay_seconds, i) * 1000;
-                LOG_WRN("%s: retrying after %d milliseconds...\n", __func__, exponential_backoff_delay);
-                std::this_thread::sleep_for(std::chrono::milliseconds(exponential_backoff_delay));
-            } else {
-                LOG_ERR("%s: download failed after %d attempts\n", __func__, max_attempts);
+        LOG_INF("%s: downloading from %s to %s (etag:%s)...\n",
+                __func__, common_http_show_masked_url(parts).c_str(),
+                path_temporary.c_str(), etag.c_str());
+
+        if (common_pull_file(cli, parts.path, path_temporary, supports_ranges, existing_size, total_size)) {
+            if (std::rename(path_temporary.c_str(), path.c_str()) != 0) {
+                LOG_ERR("%s: unable to rename file: %s to %s\n", __func__, path_temporary.c_str(), path.c_str());
+                return -1;
             }
-            continue;
+            if (!etag.empty()) {
+                write_etag(path, etag);
+            }
+            return head->status;
         }
-
-        if (std::rename(path_temporary.c_str(), path.c_str()) != 0) {
-            LOG_ERR("%s: unable to rename file: %s to %s\n", __func__, path_temporary.c_str(), path.c_str());
-            return -1;
-        }
-        if (!etag.empty()) {
-            write_etag(path, etag);
-        }
-
-        return head->status; // TODO: use actual GET status?
     }
 
+    LOG_ERR("%s: download failed after %d attempts\n", __func__, max_attempts);
     return -1; // max attempts reached
 }
 
@@ -801,30 +764,6 @@ std::string common_docker_resolve_model(const std::string & docker) {
     }
 }
 
-#else
-
-common_hf_file_res common_get_hf_file(const std::string &, const std::string &, bool, const common_header_list &) {
-    throw std::runtime_error("download functionality is not enabled in this build");
-}
-
-bool common_download_model(const common_params_model &, const std::string &, bool, const common_header_list &) {
-    throw std::runtime_error("download functionality is not enabled in this build");
-}
-
-std::string common_docker_resolve_model(const std::string &) {
-    throw std::runtime_error("download functionality is not enabled in this build");
-}
-
-int common_download_file_single(const std::string &,
-                                const std::string &,
-                                const std::string &,
-                                bool,
-                                const common_header_list &) {
-    throw std::runtime_error("download functionality is not enabled in this build");
-}
-
-#endif // defined(LLAMA_USE_HTTPLIB)
-
 std::vector<common_cached_model_info> common_list_cached_models() {
     std::vector<common_cached_model_info> models;
     const std::string cache_dir = fs_get_cache_directory();

common/jinja/README.md

@@ -63,7 +63,7 @@ The llama.cpp Jinja engine introduces `jinja::string` (see `jinja/string.h`), wh
   - **One-to-many** (e.g., split): result is marked `is_input` **only if ALL** input parts are marked `is_input`
   - **Many-to-one** (e.g., join): same as one-to-many
 
-For string concatenation, string parts will be appended to the new string as-is, while perserving the `is_input` flag.
+For string concatenation, string parts will be appended to the new string as-is, while preserving the `is_input` flag.
 
 **Enabling Input Marking:**
 

common/jinja/caps.cpp

@@ -1,3 +1,4 @@
+#include "log.h"
 #include "value.h"
 #include "runtime.h"
 #include "caps.h"
@@ -36,12 +37,16 @@ static void caps_try_execute(jinja::program & prog,
     auto tools = ctx.get_val("tools");
 
     bool success = false;
+    std::string result;
     try {
         jinja::runtime runtime(ctx);
-        runtime.execute(prog);
+        auto results = runtime.execute(prog);
+        auto parts = jinja::runtime::gather_string_parts(results);
+        result = parts->as_string().str();
         success = true;
     } catch (const std::exception & e) {
         JJ_DEBUG("Exception during execution: %s", e.what());
+        result = "";
         // ignore exceptions during capability analysis
     }
 
@@ -90,6 +95,8 @@ caps caps_get(jinja::program & prog) {
         return v->stats.ops.find(op_name) != v->stats.ops.end();
     };
 
+    JJ_DEBUG("%s\n", ">>> Running capability check: typed content");
+
     // case: typed content support
     caps_try_execute(
         prog,
@@ -120,6 +127,7 @@ caps caps_get(jinja::program & prog) {
         }
     );
 
+    JJ_DEBUG("%s\n", ">>> Running capability check: system prompt");
 
     // case: system prompt support
     caps_try_execute(
@@ -150,7 +158,9 @@ caps caps_get(jinja::program & prog) {
         }
     );
 
-    // case: tools support
+    JJ_DEBUG("%s\n", ">>> Running capability check: single tool support");
+
+    // case: tools support: single call
     caps_try_execute(
         prog,
         [&]() {
@@ -162,10 +172,10 @@ caps caps_get(jinja::program & prog) {
                 },
                 {
                     {"role", "assistant"},
-                    {"content", "Assistant message"},
+                    {"content", ""}, // Some templates expect content to be empty with tool calls
                     {"tool_calls", json::array({
                         {
-                            {"id", "call1"},
+                            {"id", "call00001"},
                             {"type", "function"},
                             {"function", {
                                 {"name", "tool1"},
@@ -173,19 +183,18 @@ caps caps_get(jinja::program & prog) {
                                     {"arg", "value"}
                                 }}
                             }}
-                        },
-                        {
-                            {"id", "call2"},
-                            {"type", "function"},
-                            {"function", {
-                                {"name", "tool2"},
-                                {"arguments", {
-                                    {"arg", "value"}
-                                }}
-                            }}
                         }
                     })}
                 },
+                {
+                    {"role", "tool"},
+                    {"content", "Tool response"},
+                    {"tool_call_id", "call00001"}
+                },
+                {
+                    {"role", "assistant"},
+                    {"content", "The tool response was 'tool response'"}
+                },
                 {
                     {"role", "user"},
                     {"content", "User message"},
@@ -199,7 +208,7 @@ caps caps_get(jinja::program & prog) {
                     {"name", "tool"},
                     {"type", "function"},
                     {"function", {
-                        {"name", "tool"},
+                        {"name", "tool1"},
                         {"description", "Tool description"},
                         {"parameters", {
                             {"type", "object"},
@@ -224,6 +233,7 @@ caps caps_get(jinja::program & prog) {
 
             auto & tool_name = tools->at(0)->at("function")->at("name");
             caps_print_stats(tool_name, "tools[0].function.name");
+            caps_print_stats(tools, "tools");
             if (!tool_name->stats.used) {
                 result.supports_tools = false;
             }
@@ -233,6 +243,93 @@ caps caps_get(jinja::program & prog) {
             if (!tool_calls->stats.used) {
                 result.supports_tool_calls = false;
             }
+        }
+    );
+
+    JJ_DEBUG("%s\n", ">>> Running capability check: parallel tool support");
+
+    // case: tools support: parallel calls
+    caps_try_execute(
+        prog,
+        [&]() {
+            // messages
+            return json::array({
+                {
+                    {"role", "user"},
+                    {"content", "User message"},
+                },
+                {
+                    {"role", "assistant"},
+                    {"content", ""}, // Some templates expect content to be empty with tool calls
+                    {"tool_calls", json::array({
+                        {
+                            {"id", "call00001"},
+                            {"type", "function"},
+                            {"function", {
+                                {"name", "tool1"},
+                                {"arguments", {
+                                    {"arg", "value"}
+                                }}
+                            }}
+                        },
+                        {
+                            {"id", "call00002"},
+                            {"type", "function"},
+                            {"function", {
+                                {"name", "tool1"},
+                                {"arguments", {
+                                    {"arg", "value"}
+                                }}
+                            }}
+                        }
+                    })}
+                },
+                {
+                    {"role", "tool"},
+                    {"content", "Tool response"},
+                    {"tool_call_id", "call00001"}
+                },
+                {
+                    {"role", "assistant"},
+                    {"content", "The tool response was 'tool response'"}
+                },
+                {
+                    {"role", "user"},
+                    {"content", "User message"},
+                },
+            });
+        },
+        [&]() {
+            // tools
+            return json::array({
+                {
+                    {"name", "tool"},
+                    {"type", "function"},
+                    {"function", {
+                        {"name", "tool1"},
+                        {"description", "Tool description"},
+                        {"parameters", {
+                            {"type", "object"},
+                            {"properties", {
+                                {"arg", {
+                                    {"type", "string"},
+                                    {"description", "Arg description"},
+                                }},
+                            }},
+                            {"required", json::array({ "arg" })},
+                        }},
+                    }},
+                },
+            });
+        },
+        [&](bool success, value & messages, value & /*tools*/) {
+            if (!success) {
+                result.supports_parallel_tool_calls = false;
+                return;
+            }
+
+            auto & tool_calls = messages->at(1)->at("tool_calls");;
+            caps_print_stats(tool_calls, "messages[1].tool_calls");
 
             // check for second tool call usage
             auto & tool_call_1 = tool_calls->at(1)->at("function");
@@ -243,6 +340,8 @@ caps caps_get(jinja::program & prog) {
         }
     );
 
+    JJ_DEBUG("%s\n", ">>> Running capability check: preserve reasoning");
+
     // case: preserve reasoning content in chat history
     caps_try_execute(
         prog,

common/jinja/runtime.cpp

@@ -85,7 +85,7 @@ value identifier::execute_impl(context & ctx) {
     auto builtins = global_builtins();
     if (!it->is_undefined()) {
         if (ctx.is_get_stats) {
-            it->stats.used = true;
+            value_t::stats_t::mark_used(it);
         }
         JJ_DEBUG("Identifier '%s' found, type = %s", val.c_str(), it->type().c_str());
         return it;
@@ -114,8 +114,10 @@ value binary_expression::execute_impl(context & ctx) {
 
     // Logical operators
     if (op.value == "and") {
+        JJ_DEBUG("Executing logical test: %s AND %s", left->type().c_str(), right->type().c_str());
         return left_val->as_bool() ? right->execute(ctx) : std::move(left_val);
     } else if (op.value == "or") {
+        JJ_DEBUG("Executing logical test: %s OR %s", left->type().c_str(), right->type().c_str());
         return left_val->as_bool() ? std::move(left_val) : right->execute(ctx);
     }
 
@@ -277,7 +279,7 @@ value binary_expression::execute_impl(context & ctx) {
 static value try_builtin_func(context & ctx, const std::string & name, value & input, bool undef_on_missing = false) {
     JJ_DEBUG("Trying built-in function '%s' for type %s", name.c_str(), input->type().c_str());
     if (ctx.is_get_stats) {
-        input->stats.used = true;
+        value_t::stats_t::mark_used(input);
         input->stats.ops.insert(name);
     }
     auto builtins = input->get_builtins();
@@ -448,7 +450,7 @@ value for_statement::execute_impl(context & ctx) {
 
     // mark the variable being iterated as used for stats
     if (ctx.is_get_stats) {
-        iterable_val->stats.used = true;
+        value_t::stats_t::mark_used(iterable_val);
         iterable_val->stats.ops.insert("array_access");
     }
 
@@ -470,7 +472,7 @@ value for_statement::execute_impl(context & ctx) {
             items.push_back(std::move(tuple));
         }
         if (ctx.is_get_stats) {
-            iterable_val->stats.used = true;
+            value_t::stats_t::mark_used(iterable_val);
             iterable_val->stats.ops.insert("object_access");
         }
     } else {
@@ -480,7 +482,7 @@ value for_statement::execute_impl(context & ctx) {
             items.push_back(item);
         }
         if (ctx.is_get_stats) {
-            iterable_val->stats.used = true;
+            value_t::stats_t::mark_used(iterable_val);
             iterable_val->stats.ops.insert("array_access");
         }
     }
@@ -721,6 +723,8 @@ value member_expression::execute_impl(context & ctx) {
         int64_t arr_size = 0;
         if (is_val<value_array>(object)) {
             arr_size = object->as_array().size();
+        } else if (is_val<value_string>(object)) {
+            arr_size = object->as_string().length();
         }
 
         if (is_stmt<slice_expression>(this->property)) {
@@ -817,8 +821,9 @@ value member_expression::execute_impl(context & ctx) {
     }
 
     if (ctx.is_get_stats && val && object && property) {
-        val->stats.used = true;
-        object->stats.used = true;
+        value_t::stats_t::mark_used(val);
+        value_t::stats_t::mark_used(object);
+        value_t::stats_t::mark_used(property);
         if (is_val<value_int>(property)) {
             object->stats.ops.insert("array_access");
         } else if (is_val<value_string>(property)) {
@@ -835,7 +840,7 @@ value call_expression::execute_impl(context & ctx) {
     for (auto & arg_stmt : this->args) {
         auto arg_val = arg_stmt->execute(ctx);
         JJ_DEBUG("  Argument type: %s", arg_val->type().c_str());
-        args.push_back(std::move(arg_val));
+        args.push_back(arg_val);
     }
     // execute callee
     value callee_val = callee->execute(ctx);

common/jinja/value.cpp

@@ -4,6 +4,7 @@
 // for converting from JSON to jinja values
 #include <nlohmann/json.hpp>
 
+#include <sstream>
 #include <string>
 #include <cctype>
 #include <vector>
@@ -160,6 +161,11 @@ static value tojson(const func_args & args) {
     value val_separators = args.get_kwarg_or_pos("separators",   3);
     value val_sort       = args.get_kwarg_or_pos("sort_keys",    4);
     int indent = -1;
+    if (args.ctx.is_get_stats) {
+        // mark as used (recursively) for stats
+        auto val_input = args.get_pos(0);
+        value_t::stats_t::mark_used(const_cast<value&>(val_input), true);
+    }
     if (is_val<value_int>(val_indent)) {
         indent = static_cast<int>(val_indent->as_int());
     }
@@ -715,8 +721,46 @@ const func_builtins & value_string_t::get_builtins() const {
             return args.get_pos(0);
         }},
         {"tojson", tojson},
-        {"indent", [](const func_args &) -> value {
-            throw not_implemented_exception("String indent builtin not implemented");
+        {"indent", [](const func_args &args) -> value {
+            args.ensure_count(1, 4);
+            value val_input  = args.get_pos(0);
+            value val_width  = args.get_kwarg_or_pos("width", 1);
+            const bool first = args.get_kwarg_or_pos("first", 2)->as_bool(); // undefined == false
+            const bool blank = args.get_kwarg_or_pos("blank", 3)->as_bool(); // undefined == false
+            if (!is_val<value_string>(val_input)) {
+                throw raised_exception("indent() first argument must be a string");
+            }
+            std::string indent;
+            if (is_val<value_int>(val_width)) {
+                indent.assign(val_width->as_int(), ' ');
+            } else if (is_val<value_string>(val_width)) {
+                indent = val_width->as_string().str();
+            } else {
+                indent = "    ";
+            }
+            std::string indented;
+            std::string input = val_input->as_string().str();
+            std::istringstream iss = std::istringstream(input);
+            std::string line;
+            while (std::getline(iss, line)) {
+                if (!indented.empty()) {
+                    indented.push_back('\n');
+                }
+                if ((indented.empty() ? first : (!line.empty() || blank))) {
+                    indented += indent;
+                }
+                indented += line;
+            }
+            if (!input.empty() && input.back() == '\n') {
+                indented.push_back('\n');
+                if (blank) {
+                    indented += indent;
+                }
+            }
+
+            auto res = mk_val<value_string>(indented);
+            res->val_str.mark_input_based_on(val_input->as_string());
+            return res;
         }},
         {"join", [](const func_args &) -> value {
             throw not_implemented_exception("String join builtin not implemented");
@@ -852,6 +896,11 @@ const func_builtins & value_array_t::get_builtins() const {
         }},
         {"string", [](const func_args & args) -> value {
             args.ensure_vals<value_array>();
+            if (args.ctx.is_get_stats) {
+                // mark as used (recursively) for stats
+                auto val_input = args.get_pos(0);
+                value_t::stats_t::mark_used(const_cast<value&>(val_input), true);
+            }
             return mk_val<value_string>(args.get_pos(0)->as_string());
         }},
         {"tojson", tojson},
@@ -1007,6 +1056,11 @@ const func_builtins & value_object_t::get_builtins() const {
         {"tojson", tojson},
         {"string", [](const func_args & args) -> value {
             args.ensure_vals<value_object>();
+            if (args.ctx.is_get_stats) {
+                // mark as used (recursively) for stats
+                auto val_input = args.get_pos(0);
+                value_t::stats_t::mark_used(const_cast<value&>(val_input), true);
+            }
             return mk_val<value_string>(args.get_pos(0)->as_string());
         }},
         {"length", [](const func_args & args) -> value {
@@ -1319,4 +1373,21 @@ std::string value_to_string_repr(const value & val) {
     }
 }
 
+// stats utility
+void value_t::stats_t::mark_used(value & val, bool deep) {
+    val->stats.used = true;
+    if (deep) {
+        if (is_val<value_array>(val)) {
+            for (auto & item : val->val_arr) {
+                mark_used(item, deep);
+            }
+        } else if (is_val<value_object>(val)) {
+            for (auto & pair : val->val_obj) {
+                mark_used(pair.first, deep);
+                mark_used(pair.second, deep);
+            }
+        }
+    }
+}
+
 } // namespace jinja

common/jinja/value.h

@@ -12,8 +12,8 @@
 #include <set>
 #include <sstream>
 #include <string>
-#include <unordered_map>
 #include <vector>
+#include <unordered_map>
 
 namespace jinja {
 
@@ -118,6 +118,8 @@ struct value_t {
         bool used = false;
         // ops can be builtin calls or operators: "array_access", "object_access"
         std::set<std::string> ops;
+        // utility to recursively mark value and its children as used
+        static void mark_used(value & val, bool deep = false);
     } stats;
 
     value_t() = default;

common/json-schema-to-grammar.cpp

@@ -27,11 +27,11 @@ static std::string build_repetition(const std::string & item_rule, int min_items
     if (separator_rule.empty()) {
         if (min_items == 1 && !has_max) {
             return item_rule + "+";
-        } else if (min_items == 0 && !has_max) {
-            return item_rule + "*";
-        } else {
-            return item_rule + "{" + std::to_string(min_items) + "," + (has_max ? std::to_string(max_items) : "") + "}";
         }
+        if (min_items == 0 && !has_max) {
+            return item_rule + "*";
+        }
+        return item_rule + "{" + std::to_string(min_items) + "," + (has_max ? std::to_string(max_items) : "") + "}";
     }
 
     auto result = item_rule + " " + build_repetition("(" + separator_rule + " " + item_rule + ")", min_items == 0 ? 0 : min_items - 1, has_max ? max_items - 1 : max_items);
@@ -41,7 +41,7 @@ static std::string build_repetition(const std::string & item_rule, int min_items
     return result;
 }
 
-static void _build_min_max_int(int64_t min_value, int64_t max_value, std::stringstream & out, int decimals_left = 16, bool top_level = true) {
+static void build_min_max_int(int64_t min_value, int64_t max_value, std::stringstream & out, int decimals_left = 16, bool top_level = true) {
     auto has_min = min_value != std::numeric_limits<int64_t>::min();
     auto has_max = max_value != std::numeric_limits<int64_t>::max();
 
@@ -128,14 +128,14 @@ static void _build_min_max_int(int64_t min_value, int64_t max_value, std::string
     if (has_min && has_max) {
         if (min_value < 0 && max_value < 0) {
             out << "\"-\" (";
-            _build_min_max_int(-max_value, -min_value, out, decimals_left, /* top_level= */ true);
+            build_min_max_int(-max_value, -min_value, out, decimals_left, /* top_level= */ true);
             out << ")";
             return;
         }
 
         if (min_value < 0) {
             out << "\"-\" (";
-            _build_min_max_int(0, -min_value, out, decimals_left, /* top_level= */ true);
+            build_min_max_int(0, -min_value, out, decimals_left, /* top_level= */ true);
             out << ") | ";
             min_value = 0;
         }
@@ -159,7 +159,7 @@ static void _build_min_max_int(int64_t min_value, int64_t max_value, std::string
     if (has_min) {
         if (min_value < 0) {
             out << "\"-\" (";
-            _build_min_max_int(std::numeric_limits<int64_t>::min(), -min_value, out, decimals_left, /* top_level= */ false);
+            build_min_max_int(std::numeric_limits<int64_t>::min(), -min_value, out, decimals_left, /* top_level= */ false);
             out << ") | [0] | [1-9] ";
             more_digits(0, decimals_left - 1);
         } else if (min_value == 0) {
@@ -194,7 +194,7 @@ static void _build_min_max_int(int64_t min_value, int64_t max_value, std::string
             }
             digit_range(c, c);
             out << " (";
-            _build_min_max_int(std::stoll(min_s.substr(1)), std::numeric_limits<int64_t>::max(), out, less_decimals, /* top_level= */ false);
+            build_min_max_int(std::stoll(min_s.substr(1)), std::numeric_limits<int64_t>::max(), out, less_decimals, /* top_level= */ false);
             out << ")";
             if (c < '9') {
                 out << " | ";
@@ -213,10 +213,10 @@ static void _build_min_max_int(int64_t min_value, int64_t max_value, std::string
                 more_digits(0, less_decimals);
                 out << " | ";
             }
-            _build_min_max_int(0, max_value, out, decimals_left, /* top_level= */ true);
+            build_min_max_int(0, max_value, out, decimals_left, /* top_level= */ true);
         } else {
             out << "\"-\" (";
-            _build_min_max_int(-max_value, std::numeric_limits<int64_t>::max(), out, decimals_left, /* top_level= */ false);
+            build_min_max_int(-max_value, std::numeric_limits<int64_t>::max(), out, decimals_left, /* top_level= */ false);
             out << ")";
         }
         return;
@@ -232,7 +232,7 @@ struct BuiltinRule {
     std::vector<std::string> deps;
 };
 
-std::unordered_map<std::string, BuiltinRule> PRIMITIVE_RULES = {
+static std::unordered_map<std::string, BuiltinRule> PRIMITIVE_RULES = {
     {"boolean", {"(\"true\" | \"false\") space", {}}},
     {"decimal-part", {"[0-9]{1,16}", {}}},
     {"integral-part", {"[0] | [1-9] [0-9]{0,15}", {}}},
@@ -247,7 +247,7 @@ std::unordered_map<std::string, BuiltinRule> PRIMITIVE_RULES = {
     {"null", {"\"null\" space", {}}},
 };
 
-std::unordered_map<std::string, BuiltinRule> STRING_FORMAT_RULES = {
+static std::unordered_map<std::string, BuiltinRule> STRING_FORMAT_RULES = {
     {"date", {"[0-9]{4} \"-\" ( \"0\" [1-9] | \"1\" [0-2] ) \"-\" ( \"0\" [1-9] | [1-2] [0-9] | \"3\" [0-1] )", {}}},
     {"time", {"([01] [0-9] | \"2\" [0-3]) \":\" [0-5] [0-9] \":\" [0-5] [0-9] ( \".\" [0-9]{3} )? ( \"Z\" | ( \"+\" | \"-\" ) ( [01] [0-9] | \"2\" [0-3] ) \":\" [0-5] [0-9] )", {}}},
     {"date-time", {"date \"T\" time", {"date", "time"}}},
@@ -260,22 +260,26 @@ static bool is_reserved_name(const std::string & name) {
     static const std::unordered_set<std::string> RESERVED_NAMES = [] {
         std::unordered_set<std::string> s;
         s.insert("root");
-        for (const auto & p : PRIMITIVE_RULES) s.insert(p.first);
-        for (const auto & p : STRING_FORMAT_RULES) s.insert(p.first);
+        for (const auto & p : PRIMITIVE_RULES) {
+            s.insert(p.first);
+        }
+        for (const auto & p : STRING_FORMAT_RULES) {
+            s.insert(p.first);
+        }
         return s;
     }();
     return RESERVED_NAMES.find(name) != RESERVED_NAMES.end();
 }
 
-std::regex INVALID_RULE_CHARS_RE("[^a-zA-Z0-9-]+");
-std::regex GRAMMAR_LITERAL_ESCAPE_RE("[\r\n\"\\\\]");
-std::regex GRAMMAR_RANGE_LITERAL_ESCAPE_RE("[\r\n\"\\]\\-\\\\]");
-std::unordered_map<char, std::string> GRAMMAR_LITERAL_ESCAPES = {
+static std::regex INVALID_RULE_CHARS_RE("[^a-zA-Z0-9-]+");
+static std::regex GRAMMAR_LITERAL_ESCAPE_RE("[\r\n\"\\\\]");
+static std::regex GRAMMAR_RANGE_LITERAL_ESCAPE_RE("[\r\n\"\\]\\-\\\\]");
+static std::unordered_map<char, std::string> GRAMMAR_LITERAL_ESCAPES = {
     {'\r', "\\r"}, {'\n', "\\n"}, {'"', "\\\""}, {'-', "\\-"}, {']', "\\]"}, {'\\', "\\\\"}
 };
 
-std::unordered_set<char> NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?'};
-std::unordered_set<char> ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'^', '$', '.', '[', ']', '(', ')', '|', '{', '}', '*', '+', '?'};
+static std::unordered_set<char> NON_LITERAL_SET = {'|', '.', '(', ')', '[', ']', '{', '}', '*', '+', '?'};
+static std::unordered_set<char> ESCAPED_IN_REGEXPS_BUT_NOT_IN_LITERALS = {'^', '$', '.', '[', ']', '(', ')', '|', '{', '}', '*', '+', '?'};
 
 static std::string replacePattern(const std::string & input, const std::regex & regex, const std::function<std::string(const std::smatch  &)> & replacement) {
     std::smatch match;
@@ -322,19 +326,19 @@ private:
         if (_rules.find(esc_name) == _rules.end() || _rules[esc_name] == rule) {
             _rules[esc_name] = rule;
             return esc_name;
-        } else {
-            int i = 0;
-            while (_rules.find(esc_name + std::to_string(i)) != _rules.end() && _rules[esc_name + std::to_string(i)] != rule) {
-                i++;
-            }
-            std::string key = esc_name + std::to_string(i);
-            _rules[key] = rule;
-            return key;
         }
+        int i = 0;
+        while (_rules.find(esc_name + std::to_string(i)) != _rules.end() && _rules[esc_name + std::to_string(i)] != rule) {
+            i++;
+        }
+        std::string key = esc_name + std::to_string(i);
+        _rules[key] = rule;
+        return key;
     }
 
     std::string _generate_union_rule(const std::string & name, const std::vector<json> & alt_schemas) {
         std::vector<std::string> rules;
+        rules.reserve(alt_schemas.size());
         for (size_t i = 0; i < alt_schemas.size(); i++) {
             rules.push_back(visit(alt_schemas[i], name + (name.empty() ? "alternative-" : "-") + std::to_string(i)));
         }
@@ -398,6 +402,7 @@ private:
                 flush_literal();
 
                 std::vector<std::string> results;
+                results.reserve(ret.size());
                 for (const auto & item : ret) {
                     results.push_back(to_rule(item));
                 }
@@ -551,7 +556,7 @@ private:
             TrieNode() : is_end_of_string(false) {}
 
             void insert(const std::string & string) {
-                auto node = this;
+                auto *node = this;
                 for (char c : string) {
                     node = &node->children[c];
                 }
@@ -676,7 +681,7 @@ private:
                 if (ks.empty()) {
                     return res;
                 }
-                std::string k = ks[0];
+                const std::string& k = ks[0];
                 std::string kv_rule_name = prop_kv_rule_names[k];
                 std::string comma_ref = "( \",\" space " + kv_rule_name + " )";
                 if (first_is_optional) {
@@ -779,7 +784,7 @@ public:
                         std::string pointer = ref.substr(ref.find('#') + 1);
                         std::vector<std::string> tokens = string_split(pointer, "/");
                         for (size_t i = 1; i < tokens.size(); ++i) {
-                            std::string sel = tokens[i];
+                            const std::string& sel = tokens[i];
                             if (target.is_object() && target.contains(sel)) {
                                 target = target[sel];
                             } else if (target.is_array()) {
@@ -802,7 +807,7 @@ public:
                         _refs[ref] = target;
                     }
                 } else {
-                    for (auto & kv : n.items()) {
+                    for (const auto & kv : n.items()) {
                         visit_refs(kv.value());
                     }
                 }
@@ -812,7 +817,7 @@ public:
         visit_refs(schema);
     }
 
-    std::string _generate_constant_rule(const json & value) {
+    static std::string _generate_constant_rule(const json & value) {
         return format_literal(value.dump());
     }
 
@@ -823,10 +828,12 @@ public:
 
         if (schema.contains("$ref")) {
             return _add_rule(rule_name, _resolve_ref(schema["$ref"]));
-        } else if (schema.contains("oneOf") || schema.contains("anyOf")) {
+        }
+        if (schema.contains("oneOf") || schema.contains("anyOf")) {
             std::vector<json> alt_schemas = schema.contains("oneOf") ? schema["oneOf"].get<std::vector<json>>() : schema["anyOf"].get<std::vector<json>>();
             return _add_rule(rule_name, _generate_union_rule(name, alt_schemas));
-        } else if (schema_type.is_array()) {
+        }
+        if (schema_type.is_array()) {
             std::vector<json> schema_types;
             for (const auto & t : schema_type) {
                 json schema_copy(schema);
@@ -834,15 +841,18 @@ public:
                 schema_types.push_back(schema_copy);
             }
             return _add_rule(rule_name, _generate_union_rule(name, schema_types));
-        } else if (schema.contains("const")) {
+        }
+        if (schema.contains("const")) {
             return _add_rule(rule_name, _generate_constant_rule(schema["const"]) + " space");
-        } else if (schema.contains("enum")) {
+        }
+        if (schema.contains("enum")) {
             std::vector<std::string> enum_values;
             for (const auto & v : schema["enum"]) {
                 enum_values.push_back(_generate_constant_rule(v));
             }
             return _add_rule(rule_name, "(" + string_join(enum_values, " | ") + ") space");
-        } else if ((schema_type.is_null() || schema_type == "object")
+        }
+        if ((schema_type.is_null() || schema_type == "object")
                 && (schema.contains("properties") ||
                     (schema.contains("additionalProperties") && schema["additionalProperties"] != true))) {
             std::unordered_set<std::string> required;
@@ -863,11 +873,12 @@ public:
                 _build_object_rule(
                     properties, required, name,
                     schema.contains("additionalProperties") ? schema["additionalProperties"] : json()));
-        } else if ((schema_type.is_null() || schema_type == "object" || schema_type == "string") && schema.contains("allOf")) {
+        }
+        if ((schema_type.is_null() || schema_type == "object" || schema_type == "string") && schema.contains("allOf")) {
             std::unordered_set<std::string> required;
             std::vector<std::pair<std::string, json>> properties;
             std::map<std::string, size_t> enum_values;
-            std::string hybrid_name = name;
+            const std::string& hybrid_name = name;
             std::function<void(const json &, bool)> add_component = [&](const json & comp_schema, bool is_required) {
                 if (comp_schema.contains("$ref")) {
                     add_component(_refs[comp_schema["$ref"]], is_required);
@@ -890,9 +901,9 @@ public:
                   // todo warning
                 }
             };
-            for (auto & t : schema["allOf"]) {
+            for (const auto & t : schema["allOf"]) {
                 if (t.contains("anyOf")) {
-                    for (auto & tt : t["anyOf"]) {
+                    for (const auto & tt : t["anyOf"]) {
                         add_component(tt, false);
                     }
                 } else {
@@ -911,7 +922,8 @@ public:
                 }
             }
             return _add_rule(rule_name, _build_object_rule(properties, required, hybrid_name, json()));
-        } else if ((schema_type.is_null() || schema_type == "array") && (schema.contains("items") || schema.contains("prefixItems"))) {
+        }
+        if ((schema_type.is_null() || schema_type == "array") && (schema.contains("items") || schema.contains("prefixItems"))) {
             json items = schema.contains("items") ? schema["items"] : schema["prefixItems"];
             if (items.is_array()) {
                 std::string rule = "\"[\" space ";
@@ -923,27 +935,31 @@ public:
                 }
                 rule += " \"]\" space";
                 return _add_rule(rule_name, rule);
-            } else {
-                std::string item_rule_name = visit(items, name + (name.empty() ? "" : "-") + "item");
-                int min_items = schema.contains("minItems") ? schema["minItems"].get<int>() : 0;
-                json max_items_json = schema.contains("maxItems") ? schema["maxItems"] : json();
-                int max_items = max_items_json.is_number_integer() ? max_items_json.get<int>() : std::numeric_limits<int>::max();
-
-                return _add_rule(rule_name, "\"[\" space " + build_repetition(item_rule_name, min_items, max_items, "\",\" space") + " \"]\" space");
             }
-        } else if ((schema_type.is_null() || schema_type == "string") && schema.contains("pattern")) {
+            std::string item_rule_name = visit(items, name + (name.empty() ? "" : "-") + "item");
+            int min_items = schema.contains("minItems") ? schema["minItems"].get<int>() : 0;
+            json max_items_json = schema.contains("maxItems") ? schema["maxItems"] : json();
+            int max_items = max_items_json.is_number_integer() ? max_items_json.get<int>() : std::numeric_limits<int>::max();
+
+            return _add_rule(rule_name, "\"[\" space " + build_repetition(item_rule_name, min_items, max_items, "\",\" space") + " \"]\" space");
+        }
+        if ((schema_type.is_null() || schema_type == "string") && schema.contains("pattern")) {
             return _visit_pattern(schema["pattern"], rule_name);
-        } else if ((schema_type.is_null() || schema_type == "string") && std::regex_match(schema_format, std::regex("^uuid[1-5]?$"))) {
+        }
+        if ((schema_type.is_null() || schema_type == "string") && std::regex_match(schema_format, std::regex("^uuid[1-5]?$"))) {
             return _add_primitive(rule_name == "root" ? "root" : schema_format, PRIMITIVE_RULES.at("uuid"));
-        } else if ((schema_type.is_null() || schema_type == "string") && STRING_FORMAT_RULES.find(schema_format + "-string") != STRING_FORMAT_RULES.end()) {
+        }
+        if ((schema_type.is_null() || schema_type == "string") && STRING_FORMAT_RULES.find(schema_format + "-string") != STRING_FORMAT_RULES.end()) {
             auto prim_name = schema_format + "-string";
             return _add_rule(rule_name, _add_primitive(prim_name, STRING_FORMAT_RULES.at(prim_name)));
-        } else if (schema_type == "string" && (schema.contains("minLength") || schema.contains("maxLength"))) {
+        }
+        if (schema_type == "string" && (schema.contains("minLength") || schema.contains("maxLength"))) {
             std::string char_rule = _add_primitive("char", PRIMITIVE_RULES.at("char"));
             int min_len = schema.contains("minLength") ? schema["minLength"].get<int>() : 0;
             int max_len = schema.contains("maxLength") ? schema["maxLength"].get<int>() : std::numeric_limits<int>::max();
             return _add_rule(rule_name, "\"\\\"\" " + build_repetition(char_rule, min_len, max_len) + " \"\\\"\" space");
-        } else if (schema_type == "integer" && (schema.contains("minimum") || schema.contains("exclusiveMinimum") || schema.contains("maximum") || schema.contains("exclusiveMaximum"))) {
+        }
+        if (schema_type == "integer" && (schema.contains("minimum") || schema.contains("exclusiveMinimum") || schema.contains("maximum") || schema.contains("exclusiveMaximum"))) {
             int64_t min_value = std::numeric_limits<int64_t>::min();
             int64_t max_value = std::numeric_limits<int64_t>::max();
             if (schema.contains("minimum")) {
@@ -958,19 +974,24 @@ public:
             }
             std::stringstream out;
             out << "(";
-            _build_min_max_int(min_value, max_value, out);
+            build_min_max_int(min_value, max_value, out);
             out << ") space";
             return _add_rule(rule_name, out.str());
-        } else if (schema.empty() || schema_type == "object") {
-            return _add_rule(rule_name, _add_primitive("object", PRIMITIVE_RULES.at("object")));
-        } else {
-            if (!schema_type.is_string() || PRIMITIVE_RULES.find(schema_type.get<std::string>()) == PRIMITIVE_RULES.end()) {
-                _errors.push_back("Unrecognized schema: " + schema.dump());
-                return "";
-            }
-            // TODO: support minimum, maximum, exclusiveMinimum, exclusiveMaximum at least for zero
-            return _add_primitive(rule_name == "root" ? "root" : schema_type.get<std::string>(), PRIMITIVE_RULES.at(schema_type.get<std::string>()));
         }
+        if (schema.empty() || schema_type == "object") {
+            return _add_rule(rule_name, _add_primitive("object", PRIMITIVE_RULES.at("object")));
+        }
+        if (schema_type.is_null() && schema.is_object()) {
+            // No type constraint and no recognized structural keywords (e.g. {"description": "..."}).
+            // Per JSON Schema semantics this is equivalent to {} and accepts any value.
+            return _add_rule(rule_name, _add_primitive("value", PRIMITIVE_RULES.at("value")));
+        }
+        if (!schema_type.is_string() || PRIMITIVE_RULES.find(schema_type.get<std::string>()) == PRIMITIVE_RULES.end()) {
+            _errors.push_back("Unrecognized schema: " + schema.dump());
+            return "";
+        }
+        // TODO: support minimum, maximum, exclusiveMinimum, exclusiveMaximum at least for zero
+        return _add_primitive(rule_name == "root" ? "root" : schema_type.get<std::string>(), PRIMITIVE_RULES.at(schema_type.get<std::string>()));
     }
 
     void check_errors() {
@@ -985,7 +1006,7 @@ public:
     std::string format_grammar() {
         std::stringstream ss;
         for (const auto & kv : _rules) {
-            ss << kv.first << " ::= " << kv.second << std::endl;
+            ss << kv.first << " ::= " << kv.second << '\n';
         }
         return ss.str();
     }

common/peg-parser.cpp

@@ -1,14 +1,15 @@
-#include "common.h"
 #include "peg-parser.h"
-#include "json-schema-to-grammar.h"
-#include "unicode.h"
 
-#include <nlohmann/json.hpp>
+#include "common.h"
+#include "json-schema-to-grammar.h"
+#include "log.h"
+#include "unicode.h"
 
 #include <algorithm>
 #include <initializer_list>
 #include <map>
 #include <memory>
+#include <nlohmann/json.hpp>
 #include <regex>
 #include <stdexcept>
 #include <unordered_set>
@@ -34,8 +35,7 @@ static bool is_hex_digit(const char c) {
 // This is used in common_peg_until_parser and to build a GBNF exclusion grammar
 struct trie {
     struct node {
-        size_t depth = 0;
-        std::map<unsigned char, size_t> children;
+        std::map<uint32_t, size_t> children;  // Use uint32_t to store Unicode codepoints
         bool is_word;
     };
 
@@ -55,15 +55,22 @@ struct trie {
         size_t current = 0; // Start at root
         size_t pos = start_pos;
 
+        // LOG_DBG("%s: checking at pos %zu, sv='%s'\n", __func__, start_pos, std::string(sv).c_str());
+
         while (pos < sv.size()) {
-            auto it = nodes[current].children.find(sv[pos]);
+            auto result = common_parse_utf8_codepoint(sv, pos);
+            if (result.status != utf8_parse_result::SUCCESS) {
+                break;
+            }
+
+            auto it = nodes[current].children.find(result.codepoint);
             if (it == nodes[current].children.end()) {
                 // Can't continue matching
                 return match_result{match_result::NO_MATCH};
             }
 
             current = it->second;
-            pos++;
+            pos += result.bytes_consumed;
 
             // Check if we've matched a complete word
             if (nodes[current].is_word) {
@@ -82,22 +89,22 @@ struct trie {
     }
 
     struct prefix_and_next {
-        std::string prefix;
-        std::string next_chars;
+        std::vector<uint32_t> prefix;
+        std::vector<uint32_t> next_chars;
     };
 
     std::vector<prefix_and_next> collect_prefix_and_next() {
-        std::string prefix;
+        std::vector<uint32_t>        prefix;
         std::vector<prefix_and_next> result;
         collect_prefix_and_next(0, prefix, result);
         return result;
     }
 
   private:
-    void collect_prefix_and_next(size_t index, std::string & prefix, std::vector<prefix_and_next> & out) {
+    void collect_prefix_and_next(size_t index, std::vector<uint32_t> & prefix, std::vector<prefix_and_next> & out) {
         if (!nodes[index].is_word) {
             if (!nodes[index].children.empty()) {
-                std::string chars;
+                std::vector<uint32_t> chars;
                 chars.reserve(nodes[index].children.size());
                 for (const auto & p : nodes[index].children) {
                     chars.push_back(p.first);
@@ -107,7 +114,7 @@ struct trie {
         }
 
         for (const auto & p : nodes[index].children) {
-            unsigned char ch = p.first;
+            uint32_t ch = p.first;
             auto child = p.second;
             prefix.push_back(ch);
             collect_prefix_and_next(child, prefix, out);
@@ -123,11 +130,19 @@ struct trie {
 
     void insert(const std::string & word) {
         size_t current = 0;
-        for (unsigned char ch : word) {
+        size_t pos     = 0;
+        while (pos < word.length()) {
+            auto result = common_parse_utf8_codepoint(word, pos);
+            if (result.status != utf8_parse_result::SUCCESS) {
+                break;
+            }
+
+            uint32_t ch = result.codepoint;
+            pos += result.bytes_consumed;
+
             auto it = nodes[current].children.find(ch);
             if (it == nodes[current].children.end()) {
                 size_t child = create_node();
-                nodes[child].depth = nodes[current].depth + 1;
                 nodes[current].children[ch] = child;
                 current = child;
             } else {
@@ -286,6 +301,32 @@ struct parser_executor {
     parser_executor(const common_peg_arena & arena, common_peg_parse_context & ctx, size_t start)
         : arena(arena), ctx(ctx), start_pos(start) {}
 
+    std::string debug_indent() const { return std::string(ctx.parse_depth * 2, ' '); }
+
+    std::string debug_input_snippet(size_t pos, size_t len = 60) const {
+        if (pos >= ctx.input.size()) {
+            return "<EOF>";
+        }
+        auto        snippet = ctx.input.substr(pos, len);
+        // Escape newlines for display
+        std::string result;
+        for (char c : snippet) {
+            if (c == '\n') {
+                result += "\\n";
+            } else if (c == '\r') {
+                result += "\\r";
+            } else if (c == '\t') {
+                result += "\\t";
+            } else {
+                result += c;
+            }
+        }
+        if (pos + len < ctx.input.size()) {
+            result += "...";
+        }
+        return result;
+    }
+
     common_peg_parse_result operator()(const common_peg_epsilon_parser & /* p */) const {
         return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos);
     }
@@ -308,7 +349,7 @@ struct parser_executor {
         auto pos = start_pos;
         for (auto i = 0u; i < p.literal.size(); ++i) {
             if (pos >= ctx.input.size()) {
-                if (!ctx.is_partial) {
+                if (!ctx.is_lenient()) {
                     return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos);
                 }
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos);
@@ -323,12 +364,32 @@ struct parser_executor {
     }
 
     common_peg_parse_result operator()(const common_peg_sequence_parser & p) {
+        if (ctx.is_debug()) {
+            LOG_DBG("%sSEQ start at %zu '%s' (%zu children)\n", debug_indent().c_str(), start_pos,
+                    debug_input_snippet(start_pos).c_str(), p.children.size());
+        }
+        ctx.parse_depth++;
+
         auto pos = start_pos;
         std::vector<common_peg_ast_id> nodes;
 
-        for (const auto & child_id : p.children) {
+        for (size_t i = 0; i < p.children.size(); i++) {
+            const auto & child_id = p.children[i];
+            if (ctx.is_debug()) {
+                fprintf(stderr, "%sSEQ child %zu: %s\n", debug_indent().c_str(), i, arena.dump(child_id).c_str());
+            }
             auto result = arena.parse(child_id, ctx, pos);
+
+            if (ctx.is_debug()) {
+                fprintf(stderr, "%sSEQ child %zu: %s at %zu->%zu\n", debug_indent().c_str(), i,
+                        common_peg_parse_result_type_name(result.type), result.start, result.end);
+            }
+
             if (result.fail()) {
+                ctx.parse_depth--;
+                if (ctx.is_debug()) {
+                    fprintf(stderr, "%sSEQ -> FAIL\n", debug_indent().c_str());
+                }
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos, result.end);
             }
 
@@ -337,28 +398,65 @@ struct parser_executor {
             }
 
             if (result.need_more_input()) {
+                ctx.parse_depth--;
+                if (ctx.is_debug()) {
+                    fprintf(stderr, "%sSEQ -> NEED_MORE\n", debug_indent().c_str());
+                }
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, result.end, std::move(nodes));
             }
 
             pos = result.end;
         }
 
+        ctx.parse_depth--;
+        if (ctx.is_debug()) {
+            fprintf(stderr, "%sSEQ -> SUCCESS at %zu->%zu\n", debug_indent().c_str(), start_pos, pos);
+        }
         return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos, std::move(nodes));
     }
 
     common_peg_parse_result operator()(const common_peg_choice_parser & p) {
+        if (ctx.is_debug()) {
+            fprintf(stderr, "%sCHOICE start at %zu '%s' (%zu options)\n", debug_indent().c_str(), start_pos,
+                    debug_input_snippet(start_pos).c_str(), p.children.size());
+        }
+        ctx.parse_depth++;
+
         auto pos = start_pos;
-        for (const auto & child_id : p.children) {
+        for (size_t i = 0; i < p.children.size(); i++) {
+            const auto & child_id = p.children[i];
+            if (ctx.is_debug()) {
+                fprintf(stderr, "%sCHOICE option %zu: %s\n", debug_indent().c_str(), i, arena.dump(child_id).c_str());
+            }
             auto result = arena.parse(child_id, ctx, pos);
+            if (ctx.is_debug()) {
+                fprintf(stderr, "%sCHOICE option %zu: %s\n", debug_indent().c_str(), i,
+                        common_peg_parse_result_type_name(result.type));
+            }
             if (!result.fail()) {
+                ctx.parse_depth--;
+                if (ctx.is_debug()) {
+                    fprintf(stderr, "%sCHOICE -> %s (option %zu)\n", debug_indent().c_str(),
+                            common_peg_parse_result_type_name(result.type), i);
+                }
                 return result;
             }
         }
 
+        ctx.parse_depth--;
+        if (ctx.is_debug()) {
+            fprintf(stderr, "%sCHOICE -> FAIL (no options matched)\n", debug_indent().c_str());
+        }
         return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos);
     }
 
     common_peg_parse_result operator()(const common_peg_repetition_parser & p) {
+        if (ctx.is_debug()) {
+            fprintf(stderr, "%sREPEAT start at %zu '%s' (min=%d, max=%d)\n", debug_indent().c_str(), start_pos,
+                    debug_input_snippet(start_pos).c_str(), p.min_count, p.max_count);
+        }
+        ctx.parse_depth++;
+
         auto pos = start_pos;
         int match_count = 0;
         std::vector<common_peg_ast_id> nodes;
@@ -366,14 +464,26 @@ struct parser_executor {
         // Try to match up to max_count times (or unlimited if max_count is -1)
         while (p.max_count == -1 || match_count < p.max_count) {
             if (pos >= ctx.input.size()) {
+                if (ctx.is_debug()) {
+                    fprintf(stderr, "%sREPEAT: at end of input, count=%d\n", debug_indent().c_str(), match_count);
+                }
                 break;
             }
 
             auto result = arena.parse(p.child, ctx, pos);
 
+            if (ctx.is_debug()) {
+                fprintf(stderr, "%sREPEAT iter %d: %s at %zu->%zu, nodes=%zu\n", debug_indent().c_str(), match_count,
+                        common_peg_parse_result_type_name(result.type), result.start, result.end, result.nodes.size());
+                fprintf(stderr, "%sREPEAT CHILD: %s\n", debug_indent().c_str(), arena.dump(p.child).c_str());
+            }
+
             if (result.success()) {
                 // Prevent infinite loop on empty matches
                 if (result.end == pos) {
+                    if (ctx.is_debug()) {
+                        fprintf(stderr, "%s  REPEAT: empty match, stopping\n", debug_indent().c_str());
+                    }
                     break;
                 }
 
@@ -391,21 +501,43 @@ struct parser_executor {
                     nodes.insert(nodes.end(), result.nodes.begin(), result.nodes.end());
                 }
 
+                ctx.parse_depth--;
+                if (ctx.is_debug()) {
+                    fprintf(stderr, "%sREPEAT -> NEED_MORE (count=%d, nodes=%zu)\n", debug_indent().c_str(),
+                            match_count, nodes.size());
+                }
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, result.end, std::move(nodes));
             }
 
             // Child failed - stop trying
+            if (ctx.is_debug()) {
+                fprintf(stderr, "%sREPEAT: child failed, stopping\n", debug_indent().c_str());
+            }
             break;
         }
 
         // Check if we got enough matches
         if (p.min_count > 0 && match_count < p.min_count) {
-            if (pos >= ctx.input.size() && ctx.is_partial) {
+            ctx.parse_depth--;
+            if (pos >= ctx.input.size() && ctx.is_lenient()) {
+                if (ctx.is_debug()) {
+                    fprintf(stderr, "%sREPEAT -> NEED_MORE (not enough matches: %d < %d)\n", debug_indent().c_str(),
+                            match_count, p.min_count);
+                }
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos, std::move(nodes));
             }
+            if (ctx.is_debug()) {
+                fprintf(stderr, "%sREPEAT -> FAIL (not enough matches: %d < %d)\n", debug_indent().c_str(), match_count,
+                        p.min_count);
+            }
             return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos, pos);
         }
 
+        ctx.parse_depth--;
+        if (ctx.is_debug()) {
+            fprintf(stderr, "%sREPEAT -> SUCCESS (count=%d, nodes=%zu)\n", debug_indent().c_str(), match_count,
+                    nodes.size());
+        }
         return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos, std::move(nodes));
     }
 
@@ -434,10 +566,10 @@ struct parser_executor {
 
     common_peg_parse_result operator()(const common_peg_any_parser & /* p */) const {
         // Parse a single UTF-8 codepoint (not just a single byte)
-        auto result = parse_utf8_codepoint(ctx.input, start_pos);
+        auto result = common_parse_utf8_codepoint(ctx.input, start_pos);
 
         if (result.status == utf8_parse_result::INCOMPLETE) {
-            if (!ctx.is_partial) {
+            if (!ctx.is_lenient()) {
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos);
             }
             return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos);
@@ -468,7 +600,7 @@ struct parser_executor {
 
         // Try to match up to max_count times (or unlimited if max_count is -1)
         while (p.max_count == -1 || match_count < p.max_count) {
-            auto result = parse_utf8_codepoint(ctx.input, pos);
+            auto result = common_parse_utf8_codepoint(ctx.input, pos);
 
             if (result.status == utf8_parse_result::INCOMPLETE) {
                 if (match_count >= p.min_count) {
@@ -476,7 +608,7 @@ struct parser_executor {
                     return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos);
                 }
                 // Not enough matches yet
-                if (!ctx.is_partial) {
+                if (!ctx.is_lenient()) {
                     return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos);
                 }
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos);
@@ -517,7 +649,7 @@ struct parser_executor {
 
         // Check if we got enough matches
         if (match_count < p.min_count) {
-            if (pos >= ctx.input.size() && ctx.is_partial) {
+            if (pos >= ctx.input.size() && ctx.is_lenient()) {
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos);
             }
             return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos, pos);
@@ -529,7 +661,7 @@ struct parser_executor {
     static common_peg_parse_result handle_escape_sequence(common_peg_parse_context & ctx, size_t start, size_t & pos) {
         ++pos; // consume '\'
         if (pos >= ctx.input.size()) {
-            if (!ctx.is_partial) {
+            if (!ctx.is_lenient()) {
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start);
             }
             return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start, pos);
@@ -537,6 +669,7 @@ struct parser_executor {
 
         switch (ctx.input[pos]) {
             case '"':
+            case '\'':
             case '\\':
             case '/':
             case 'b':
@@ -558,7 +691,7 @@ struct parser_executor {
         ++pos; // consume 'u'
         for (int i = 0; i < 4; ++i) {
             if (pos >= ctx.input.size()) {
-                if (!ctx.is_partial) {
+                if (!ctx.is_lenient()) {
                     return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start);
                 }
                 return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start, pos);
@@ -589,10 +722,10 @@ struct parser_executor {
                     return result;
                 }
             } else {
-                auto utf8_result = parse_utf8_codepoint(ctx.input, pos);
+                auto utf8_result = common_parse_utf8_codepoint(ctx.input, pos);
 
                 if (utf8_result.status == utf8_parse_result::INCOMPLETE) {
-                    if (!ctx.is_partial) {
+                    if (!ctx.is_lenient()) {
                         return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos);
                     }
                     return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos);
@@ -607,7 +740,49 @@ struct parser_executor {
         }
 
         // Reached end without finding closing quote
-        if (!ctx.is_partial) {
+        if (!ctx.is_lenient()) {
+            return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos, pos);
+        }
+        return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos);
+    }
+
+    common_peg_parse_result operator()(const common_peg_python_dict_string_parser & /* p */) {
+        auto pos = start_pos;
+
+        // Parse string content (without quotes)
+        while (pos < ctx.input.size()) {
+            char c = ctx.input[pos];
+
+            if (c == '\'') {
+                // Found closing quote - success (don't consume it)
+                return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_SUCCESS, start_pos, pos);
+            }
+
+            if (c == '\\') {
+                auto result = handle_escape_sequence(ctx, start_pos, pos);
+                if (!result.success()) {
+                    return result;
+                }
+            } else {
+                auto utf8_result = common_parse_utf8_codepoint(ctx.input, pos);
+
+                if (utf8_result.status == utf8_parse_result::INCOMPLETE) {
+                    if (!ctx.is_lenient()) {
+                        return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos);
+                    }
+                    return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos);
+                }
+
+                if (utf8_result.status == utf8_parse_result::INVALID) {
+                    return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos);
+                }
+
+                pos += utf8_result.bytes_consumed;
+            }
+        }
+
+        // Reached end without finding closing quote
+        if (!ctx.is_lenient()) {
             return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos, pos);
         }
         return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, pos);
@@ -621,11 +796,11 @@ struct parser_executor {
         size_t last_valid_pos = start_pos;
 
         while (pos < ctx.input.size()) {
-            auto utf8_result = parse_utf8_codepoint(ctx.input, pos);
+            auto utf8_result = common_parse_utf8_codepoint(ctx.input, pos);
 
             if (utf8_result.status == utf8_parse_result::INCOMPLETE) {
                 // Incomplete UTF-8 sequence
-                if (!ctx.is_partial) {
+                if (!ctx.is_lenient()) {
                     // Input is complete but UTF-8 is incomplete = malformed
                     return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_FAIL, start_pos);
                 }
@@ -655,7 +830,7 @@ struct parser_executor {
             last_valid_pos = pos;
         }
 
-        if (last_valid_pos == ctx.input.size() && ctx.is_partial) {
+        if (last_valid_pos == ctx.input.size() && ctx.is_lenient()) {
             // Reached the end of a partial stream, there might still be more input that we need to consume.
             return common_peg_parse_result(COMMON_PEG_PARSE_RESULT_NEED_MORE_INPUT, start_pos, last_valid_pos);
         }
@@ -694,6 +869,9 @@ struct parser_executor {
 
     common_peg_parse_result operator()(const common_peg_tag_parser & p) {
         // Parse the child
+        if (ctx.is_debug()) {
+            fprintf(stderr, "%sTAG: %s\n", debug_indent().c_str(), p.tag.c_str());
+        }
         auto result = arena.parse(p.child, ctx, start_pos);
 
         if (!result.fail()) {
@@ -755,6 +933,31 @@ common_peg_parser_id common_peg_arena::resolve_ref(common_peg_parser_id id) {
     return id;
 }
 
+static void bfs_node(common_peg_ast_arena &arena, std::ostringstream & oss, const common_peg_ast_node & node, int indent) {
+    for (int i = 0; i < indent; i++) {
+        oss << "  ";
+    }
+    oss << "NODE " << node.id;
+    if (!node.rule.empty()) {
+        oss << " (rule " << node.rule << ")";
+    }
+    if (!node.tag.empty()) {
+        oss << " (tag " << node.tag << ")";
+    }
+    oss << " ['" << node.text << "']\n";
+    for (const auto child : node.children) {
+        bfs_node(arena, oss, arena.get(child), indent + 1);
+    }
+}
+
+std::string common_peg_ast_arena::dump() {
+    std::ostringstream oss;
+    for (auto & node : nodes_) {
+        bfs_node(*this, oss, node, 0);
+    }
+    return oss.str();
+}
+
 void common_peg_arena::resolve_refs() {
     // Walk through all parsers and replace refs with their corresponding rule IDs
     for (auto & parser : parsers_) {
@@ -786,6 +989,7 @@ void common_peg_arena::resolve_refs() {
                                  std::is_same_v<T, common_peg_until_parser> ||
                                  std::is_same_v<T, common_peg_literal_parser> ||
                                  std::is_same_v<T, common_peg_json_string_parser> ||
+                                 std::is_same_v<T, common_peg_python_dict_string_parser> ||
                                  std::is_same_v<T, common_peg_chars_parser> ||
                                  std::is_same_v<T, common_peg_any_parser> ||
                                  std::is_same_v<T, common_peg_space_parser>) {
@@ -803,9 +1007,21 @@ void common_peg_arena::resolve_refs() {
 }
 
 std::string common_peg_arena::dump(common_peg_parser_id id) const {
+    std::unordered_set<common_peg_parser_id> visited;
+    return dump_impl(id, visited);
+}
+
+std::string common_peg_arena::dump_impl(common_peg_parser_id                       id,
+                                        std::unordered_set<common_peg_parser_id> & visited) const {
+    // Check for cycles
+    if (visited.count(id)) {
+        return "[cycle]";
+    }
+    visited.insert(id);
+
     const auto & parser = parsers_.at(id);
 
-    return std::visit([this](const auto & p) -> std::string {
+    return std::visit([this, &visited](const auto & p) -> std::string {
         using T = std::decay_t<decltype(p)>;
 
         if constexpr (std::is_same_v<T, common_peg_epsilon_parser>) {
@@ -819,24 +1035,27 @@ std::string common_peg_arena::dump(common_peg_parser_id id) const {
         } else if constexpr (std::is_same_v<T, common_peg_sequence_parser>) {
             std::vector<std::string> parts;
             for (const auto & child : p.children) {
-                parts.push_back(dump(child));
+                parts.push_back(dump_impl(child, visited));
             }
             return "Sequence(" + string_join(parts, ", ") + ")";
         } else if constexpr (std::is_same_v<T, common_peg_choice_parser>) {
             std::vector<std::string> parts;
             for (const auto & child : p.children) {
-                parts.push_back(dump(child));
+                parts.push_back(dump_impl(child, visited));
             }
             return "Choice(" + string_join(parts, ", ") + ")";
         } else if constexpr (std::is_same_v<T, common_peg_repetition_parser>) {
             if (p.max_count == -1) {
-                return "Repetition(" + dump(p.child) + ", " + std::to_string(p.min_count) + ", unbounded)";
+                return "Repetition(" + dump_impl(p.child, visited) + ", " + std::to_string(p.min_count) +
+                        ", unbounded)";
             }
-            return "Repetition(" + dump(p.child) + ", " + std::to_string(p.min_count) + ", " + std::to_string(p.max_count) + ")";
+            return "Repetition(" + dump_impl(p.child, visited) + ", " + std::to_string(p.min_count) + ", " + std::to_string(p.max_count) + ")";
         } else if constexpr (std::is_same_v<T, common_peg_and_parser>) {
-            return "And(" + dump(p.child) + ")";
+            return "And(" + dump_impl(p.child, visited) + ")";
         } else if constexpr (std::is_same_v<T, common_peg_not_parser>) {
-            return "Not(" + dump(p.child) + ")";
+            return "Not(" + dump_impl(p.child, visited) + ")";
+        } else if constexpr (std::is_same_v<T, common_peg_atomic_parser>) {
+            return "Atomic(" + dump_impl(p.child, visited) + ")";
         } else if constexpr (std::is_same_v<T, common_peg_any_parser>) {
             return "Any";
         } else if constexpr (std::is_same_v<T, common_peg_space_parser>) {
@@ -848,14 +1067,20 @@ std::string common_peg_arena::dump(common_peg_parser_id id) const {
             return "CharRepeat(" + p.pattern + ", " + std::to_string(p.min_count) + ", " + std::to_string(p.max_count) + ")";
         } else if constexpr (std::is_same_v<T, common_peg_json_string_parser>) {
             return "JsonString()";
+        } else if constexpr (std::is_same_v<T, common_peg_python_dict_string_parser>) {
+            return "PythonDictString()";
         } else if constexpr (std::is_same_v<T, common_peg_until_parser>) {
             return "Until(" + string_join(p.delimiters, " | ") + ")";
         } else if constexpr (std::is_same_v<T, common_peg_schema_parser>) {
-            return "Schema(" + dump(p.child) + ", " + (p.schema ? p.schema->dump() : "null") + ")";
+            return "Schema(" + dump_impl(p.child, visited) + ", " + (p.schema ? p.schema->dump() : "null") + ")";
         } else if constexpr (std::is_same_v<T, common_peg_rule_parser>) {
-            return "Rule(" + p.name + ", " + dump(p.child) + ")";
+            return "Rule(" + p.name + ", " + dump_impl(p.child, visited) + ")";
         } else if constexpr (std::is_same_v<T, common_peg_ref_parser>) {
             return "Ref(" + p.name + ")";
+        } else if constexpr (std::is_same_v<T, common_peg_tag_parser>) {
+            return "Tag(" + p.tag + ", " + dump(p.child) + ")";
+        } else if constexpr (std::is_same_v<T, common_peg_atomic_parser>) {
+            return "Atomic(" + dump(p.child) + ")";
         } else {
             return "Unknown";
         }
@@ -1054,7 +1279,54 @@ common_peg_arena common_peg_parser_builder::build() {
     return std::move(arena_);
 }
 
+// String primitives
+
+common_peg_parser common_peg_parser_builder::json_string_content() {
+    return wrap(arena_.add_parser(common_peg_json_string_parser{}));
+}
+
+common_peg_parser common_peg_parser_builder::single_quoted_string_content() {
+    return wrap(arena_.add_parser(common_peg_python_dict_string_parser{}));
+}
+
+common_peg_parser common_peg_parser_builder::double_quoted_string() {
+    return rule("dq-string",
+                [this]() { return sequence({ literal("\""), json_string_content(), literal("\""), space() }); });
+}
+
+common_peg_parser common_peg_parser_builder::single_quoted_string() {
+    return rule("sq-string",
+                [this]() { return sequence({ literal("'"), single_quoted_string_content(), literal("'"), space() }); });
+}
+
+common_peg_parser common_peg_parser_builder::flexible_string() {
+    return rule("flexible-string", [this]() { return choice({ double_quoted_string(), single_quoted_string() }); });
+}
+
+// Generic helpers for object/array structure
+
+common_peg_parser common_peg_parser_builder::generic_object(const std::string &            name,
+                                                             const common_peg_parser & string_parser,
+                                                             const common_peg_parser & value_parser) {
+    return rule(name, [this, string_parser, value_parser]() {
+        auto ws      = space();
+        auto member  = sequence({ string_parser, ws, literal(":"), ws, value_parser });
+        auto members = sequence({ member, zero_or_more(sequence({ ws, literal(","), ws, member })) });
+        return sequence({ literal("{"), ws, choice({ literal("}"), sequence({ members, ws, literal("}") }) }) });
+    });
+}
+
+common_peg_parser common_peg_parser_builder::generic_array(const std::string &            name,
+                                                            const common_peg_parser & value_parser) {
+    return rule(name, [this, value_parser]() {
+        auto ws       = space();
+        auto elements = sequence({ value_parser, zero_or_more(sequence({ literal(","), ws, value_parser })) });
+        return sequence({ literal("["), ws, choice({ literal("]"), sequence({ elements, ws, literal("]") }) }) });
+    });
+}
+
 // JSON parsers
+
 common_peg_parser common_peg_parser_builder::json_number() {
    return rule("json-number", [this]() {
         auto digit1_9 = chars("[1-9]", 1, 1);
@@ -1062,7 +1334,11 @@ common_peg_parser common_peg_parser_builder::json_number() {
         auto int_part = choice({literal("0"), sequence({digit1_9, chars("[0-9]", 0, -1)})});
         auto frac = sequence({literal("."), digits});
         auto exp = sequence({choice({literal("e"), literal("E")}), optional(chars("[+-]", 1, 1)), digits});
-        return sequence({optional(literal("-")), int_part, optional(frac), optional(exp), space()});
+        // Negative lookahead: only commit the number when the next character can't extend it.
+        // At EOF in partial mode, chars returns NEED_MORE → negate propagates NEED_MORE → number not committed.
+        // This prevents premature commits of partial numbers (e.g. "3" when "3.14" is incoming).
+        auto not_number_continuation = negate(chars("[0-9.eE+-]", 1, 1));
+        return sequence({ optional(literal("-")), int_part, optional(frac), optional(exp), not_number_continuation, space() });
     });
 }
 
@@ -1085,36 +1361,11 @@ common_peg_parser common_peg_parser_builder::json_null() {
 }
 
 common_peg_parser common_peg_parser_builder::json_object() {
-    return rule("json-object", [this]() {
-        auto ws = space();
-        auto member = sequence({json_string(), ws, literal(":"), ws, json()});
-        auto members = sequence({member, zero_or_more(sequence({ws, literal(","), ws, member}))});
-        return sequence({
-            literal("{"),
-            ws,
-            choice({
-                literal("}"),
-                sequence({members, ws, literal("}")})
-            }),
-            ws
-        });
-    });
+    return generic_object("json-object", json_string(), json());
 }
 
 common_peg_parser common_peg_parser_builder::json_array() {
-    return rule("json-array", [this]() {
-        auto ws = space();
-        auto elements = sequence({json(), zero_or_more(sequence({literal(","), ws, json()}))});
-        return sequence({
-            literal("["),
-            ws,
-            choice({
-                literal("]"),
-                sequence({elements, ws, literal("]")})
-            }),
-            ws
-        });
-    });
+    return generic_array("json-array", json());
 }
 
 common_peg_parser common_peg_parser_builder::json() {
@@ -1130,8 +1381,40 @@ common_peg_parser common_peg_parser_builder::json() {
     });
 }
 
-common_peg_parser common_peg_parser_builder::json_string_content() {
-    return wrap(arena_.add_parser(common_peg_json_string_parser{}));
+common_peg_parser common_peg_parser_builder::python_string() {
+    return rule("python-string", [this]() { return choice({ double_quoted_string(), single_quoted_string() }); });
+}
+
+common_peg_parser common_peg_parser_builder::python_number() {
+    return json_number();
+}
+
+common_peg_parser common_peg_parser_builder::python_bool() {
+    return rule("python-bool", [this]() { return sequence({ choice({ literal("True"), literal("False") }), space() }); });
+}
+
+common_peg_parser common_peg_parser_builder::python_null() {
+    return rule("python-none", [this]() { return sequence({ literal("None"), space() }); });
+}
+
+common_peg_parser common_peg_parser_builder::python_dict() {
+    return generic_object("python-dict", python_string(), python_value());
+}
+
+common_peg_parser common_peg_parser_builder::python_array() {
+    return generic_array("python-array", python_value());
+}
+
+common_peg_parser common_peg_parser_builder::python_value() {
+    return rule("python-value", [this]() {
+        return choice({ python_dict(), python_array(), python_string(), python_number(), python_bool(), python_null() });
+    });
+}
+
+common_peg_parser common_peg_parser_builder::marker() {
+    auto sharp_bracket_parser = literal("<") + until(">") + literal(">");
+    auto square_bracket_parser = literal("[") + until("]") + literal("]");
+    return choice({ sharp_bracket_parser, square_bracket_parser });
 }
 
 common_peg_parser common_peg_parser_builder::json_member(const std::string & key, const common_peg_parser & p) {
@@ -1145,17 +1428,54 @@ common_peg_parser common_peg_parser_builder::json_member(const std::string & key
     });
 }
 
-
-static std::string gbnf_escape_char_class(char c) {
-    switch (c) {
-        case '\n': return "\\n";
-        case '\t': return "\\t";
-        case '\r': return "\\r";
-        case '\\': return "\\\\";
-        case ']':  return "\\]";
-        case '[':  return "\\[";
-        default:   return std::string(1, c);
+static std::string gbnf_escape_char_class(uint32_t c) {
+    if (c == '-' || c == ']' || c == '[' || c == '\\') {
+        return "\\" + std::string(1, (char) c);
     }
+    // Escape whitespace control characters
+    if (c == '\n') {
+        return "\\n";
+    }
+    if (c == '\t') {
+        return "\\t";
+    }
+    if (c == '\r') {
+        return "\\r";
+    }
+
+    // Printable ASCII
+    if (c >= 0x20 && c <= 0x7E) {
+        return std::string(1, (char) c);
+    }
+
+    // Hex escape
+    char         buf[16];
+    const char * hex = "0123456789ABCDEF";
+
+    if (c <= 0xFF) {
+        buf[0] = '\\';
+        buf[1] = 'x';
+        buf[2] = hex[(c >> 4) & 0xF];
+        buf[3] = hex[c & 0xF];
+        buf[4] = '\0';
+    } else if (c <= 0xFFFF) {
+        buf[0] = '\\';
+        buf[1] = 'u';
+        buf[2] = hex[(c >> 12) & 0xF];
+        buf[3] = hex[(c >> 8) & 0xF];
+        buf[4] = hex[(c >> 4) & 0xF];
+        buf[5] = hex[c & 0xF];
+        buf[6] = '\0';
+    } else {
+        buf[0] = '\\';
+        buf[1] = 'U';
+        for (int i = 0; i < 8; i++) {
+            buf[2 + i] = hex[(c >> ((7 - i) * 4)) & 0xF];
+        }
+        buf[10] = '\0';
+    }
+
+    return std::string(buf);
 }
 
 static std::string gbnf_excluding_pattern(const std::vector<std::string> & strings) {
@@ -1173,12 +1493,12 @@ static std::string gbnf_excluding_pattern(const std::vector<std::string> & strin
 
         std::string cls;
         cls.reserve(chars.size());
-        for (const auto & ch : chars) {
+        for (uint32_t ch : chars) {
             cls += gbnf_escape_char_class(ch);
         }
 
         if (!pre.empty()) {
-            pattern += gbnf_format_literal(pre) + " [^" + cls + "]";
+            pattern += gbnf_format_literal(common_unicode_cpts_to_utf8(pre)) + " [^" + cls + "]";
         } else {
             pattern += "[^" + cls + "]";
         }
@@ -1208,7 +1528,8 @@ static std::unordered_set<std::string> collect_reachable_rules(
                           std::is_same_v<T, common_peg_chars_parser> ||
                           std::is_same_v<T, common_peg_space_parser> ||
                           std::is_same_v<T, common_peg_any_parser> ||
-                          std::is_same_v<T, common_peg_json_string_parser>) {
+                          std::is_same_v<T, common_peg_json_string_parser> ||
+                          std::is_same_v<T, common_peg_python_dict_string_parser>) {
                 // These parsers do not have any children
             } else if constexpr (std::is_same_v<T, common_peg_sequence_parser>) {
                 for (auto child : p.children) {
@@ -1346,6 +1667,8 @@ void common_peg_arena::build_grammar(const common_grammar_builder & builder, boo
                 return result + "{" + std::to_string(p.min_count) + "," + std::to_string(p.max_count) + "}";
             } else if constexpr (std::is_same_v<T, common_peg_json_string_parser>) {
                 return R"(( [^"\\] | "\\" ( ["\\/ bfnrt] | "u" [0-9a-fA-F]{4} ) )*)";
+            } else if constexpr (std::is_same_v<T, common_peg_python_dict_string_parser>) {
+                return R"(( [^"\\] | "\\" ( ["\\/ bfnrt] | "u" [0-9a-fA-F]{4} ) )*)";
             } else if constexpr (std::is_same_v<T, common_peg_until_parser>) {
                 if (p.delimiters.empty()) {
                     return ".*";
@@ -1477,6 +1800,8 @@ static nlohmann::json serialize_parser_variant(const common_peg_parser_variant &
             };
         } else if constexpr (std::is_same_v<T, common_peg_json_string_parser>) {
             return json{{"type", "json_string"}};
+        } else if constexpr (std::is_same_v<T, common_peg_python_dict_string_parser>) {
+            return json{{ "type", "python_dict_string" }};
         } else if constexpr (std::is_same_v<T, common_peg_until_parser>) {
             return json{{"type", "until"}, {"delimiters", p.delimiters}};
         } else if constexpr (std::is_same_v<T, common_peg_schema_parser>) {
@@ -1606,6 +1931,9 @@ static common_peg_parser_variant deserialize_parser_variant(const nlohmann::json
     if (type == "json_string") {
         return common_peg_json_string_parser{};
     }
+    if (type == "python_dict_string") {
+        return common_peg_python_dict_string_parser{};
+    }
     if (type == "until") {
         if (!j.contains("delimiters") || !j["delimiters"].is_array()) {
             throw std::runtime_error("until parser missing or invalid 'delimiters' field");

common/peg-parser.h

@@ -4,6 +4,7 @@
 
 #include <memory>
 #include <unordered_map>
+#include <unordered_set>
 #include <string>
 #include <string_view>
 #include <functional>
@@ -111,6 +112,8 @@ class common_peg_ast_arena {
 
     void visit(common_peg_ast_id id, const common_peg_ast_visitor & visitor) const;
     void visit(const common_peg_parse_result & result, const common_peg_ast_visitor & visitor) const;
+
+    std::string dump();
 };
 
 struct common_peg_parse_result {
@@ -136,21 +139,43 @@ struct common_peg_parse_result {
     bool success() const { return type == COMMON_PEG_PARSE_RESULT_SUCCESS; }
 };
 
+enum common_peg_parse_flags {
+    COMMON_PEG_PARSE_FLAG_NONE    = 0,
+    COMMON_PEG_PARSE_FLAG_LENIENT = 1 << 0,
+    COMMON_PEG_PARSE_FLAG_DEBUG   = 1 << 1,
+};
+
+inline common_peg_parse_flags operator|(common_peg_parse_flags a, common_peg_parse_flags b) {
+    return static_cast<common_peg_parse_flags>(int(a) | int(b));
+}
+
+inline common_peg_parse_flags & operator|=(common_peg_parse_flags & a, common_peg_parse_flags b) {
+    return a = a | b;
+}
+
+inline common_peg_parse_flags operator&(common_peg_parse_flags a, common_peg_parse_flags b) {
+    return static_cast<common_peg_parse_flags>(int(a) & int(b));
+}
+
+inline common_peg_parse_flags operator~(common_peg_parse_flags a) {
+    return static_cast<common_peg_parse_flags>(~int(a));
+}
+
 struct common_peg_parse_context {
     std::string input;
-    bool is_partial;
+    common_peg_parse_flags flags;
     common_peg_ast_arena ast;
 
     int parse_depth;
 
-    common_peg_parse_context()
-        : is_partial(false), parse_depth(0) {}
+    common_peg_parse_context(common_peg_parse_flags flags = COMMON_PEG_PARSE_FLAG_NONE)
+        : flags(flags), parse_depth(0) {}
 
-    common_peg_parse_context(const std::string & input)
-        : input(input), is_partial(false), parse_depth(0) {}
+    common_peg_parse_context(const std::string & input, common_peg_parse_flags flags = COMMON_PEG_PARSE_FLAG_NONE)
+        : input(input), flags(flags), parse_depth(0) {}
 
-    common_peg_parse_context(const std::string & input, bool is_partial)
-        : input(input), is_partial(is_partial), parse_depth(0) {}
+    bool is_lenient() const { return flags & COMMON_PEG_PARSE_FLAG_LENIENT; }
+    bool is_debug() const { return flags & COMMON_PEG_PARSE_FLAG_DEBUG; }
 };
 
 class common_peg_arena;
@@ -207,6 +232,7 @@ struct common_peg_chars_parser {
 };
 
 struct common_peg_json_string_parser {};
+struct common_peg_python_dict_string_parser {};
 
 struct common_peg_until_parser {
     std::vector<std::string> delimiters;
@@ -255,6 +281,7 @@ using common_peg_parser_variant = std::variant<
     common_peg_space_parser,
     common_peg_chars_parser,
     common_peg_json_string_parser,
+    common_peg_python_dict_string_parser,
     common_peg_until_parser,
     common_peg_schema_parser,
     common_peg_rule_parser,
@@ -299,6 +326,8 @@ class common_peg_arena {
     friend class common_peg_parser_builder;
 
   private:
+    std::string dump_impl(common_peg_parser_id id, std::unordered_set<common_peg_parser_id> & visited) const;
+
     common_peg_parser_id add_parser(common_peg_parser_variant parser);
     void add_rule(const std::string & name, common_peg_parser_id id);
 
@@ -311,6 +340,10 @@ class common_peg_parser_builder {
     common_peg_parser wrap(common_peg_parser_id id) { return common_peg_parser(id, *this); }
     common_peg_parser add(const common_peg_parser_variant & p) { return wrap(arena_.add_parser(p)); }
 
+    // Generic helpers for building object/array structures with configurable string/value parsers.
+    common_peg_parser generic_object(const std::string & name, const common_peg_parser & string_parser, const common_peg_parser & value_parser);
+    common_peg_parser generic_array(const std::string & name, const common_peg_parser & value_parser);
+
   public:
     common_peg_parser_builder();
 
@@ -404,6 +437,21 @@ class common_peg_parser_builder {
     //   S -> A{n}
     common_peg_parser repeat(const common_peg_parser & p, int n) { return repeat(p, n, n); }
 
+    // Matches a double-quoted string: '"' content '"' space
+    common_peg_parser double_quoted_string();
+
+    // Matches a single-quoted string: "'" content "'" space
+    common_peg_parser single_quoted_string();
+
+    // Matches a string that accepts both double-quoted and single-quoted styles.
+    common_peg_parser flexible_string();
+
+    // Matches double-quoted string content without the surrounding quotes.
+    common_peg_parser json_string_content();
+
+    // Matches single-quoted string content without the surrounding quotes.
+    common_peg_parser single_quoted_string_content();
+
     // Creates a complete JSON parser supporting objects, arrays, strings, numbers, booleans, and null.
     //   value -> object | array | string | number | true | false | null
     common_peg_parser json();
@@ -414,14 +462,24 @@ class common_peg_parser_builder {
     common_peg_parser json_bool();
     common_peg_parser json_null();
 
-    // Matches JSON string content without the surrounding quotes.
-    // Useful for extracting content within a JSON string.
-    common_peg_parser json_string_content();
-
     // Matches a JSON object member with a key and associated parser as the
     // value.
     common_peg_parser json_member(const std::string & key, const common_peg_parser & p);
 
+    // Creates a complete Python format parser supporting dicts, arrays, strings, numbers, booleans, and None.
+    // Differs from JSON: uses True/False/None, accepts both single and double-quoted strings.
+    //   value -> dict | array | string | number | True | False | None
+    common_peg_parser python_value();
+    common_peg_parser python_dict();
+    common_peg_parser python_string();
+    common_peg_parser python_array();
+    common_peg_parser python_number();
+    common_peg_parser python_bool();
+    common_peg_parser python_null();
+
+    // A marker, i.e. text delimited by a pair of <> or []
+    common_peg_parser marker();
+
     // Wraps a parser with JSON schema metadata for grammar generation.
     // Used internally to convert JSON schemas to GBNF grammar rules.
     common_peg_parser schema(const common_peg_parser & p, const std::string & name, const nlohmann::ordered_json & schema, bool raw = false);

common/unicode.cpp

@@ -1,14 +1,18 @@
 #include "unicode.h"
+#include <cassert>
+#include <stdexcept>
+#include <vector>
+#include <string>
 
 // implementation adopted from src/unicode.cpp
 
-size_t utf8_sequence_length(unsigned char first_byte) {
+size_t common_utf8_sequence_length(unsigned char first_byte) {
     const size_t lookup[] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 4 };
     uint8_t highbits = static_cast<uint8_t>(first_byte) >> 4;
     return lookup[highbits];
 }
 
-utf8_parse_result parse_utf8_codepoint(std::string_view input, size_t offset) {
+utf8_parse_result common_parse_utf8_codepoint(std::string_view input, size_t offset) {
     if (offset >= input.size()) {
         return utf8_parse_result(utf8_parse_result::INCOMPLETE);
     }
@@ -62,3 +66,43 @@ utf8_parse_result parse_utf8_codepoint(std::string_view input, size_t offset) {
     // Invalid first byte
     return utf8_parse_result(utf8_parse_result::INVALID);
 }
+
+std::string common_unicode_cpts_to_utf8(const std::vector<uint32_t> & cps) {
+    std::string result;
+    for (size_t i = 0; i < cps.size(); ++i) {
+        result.append(common_unicode_cpt_to_utf8(cps[i]));
+    }
+    return result;
+}
+
+std::string common_unicode_cpt_to_utf8(uint32_t cpt) {
+    std::string result;
+
+    if (/* 0x00 <= cpt && */ cpt <= 0x7f) {
+        result.push_back(cpt);
+        return result;
+    }
+    if (0x80 <= cpt && cpt <= 0x7ff) {
+        result.push_back(0xc0 | ((cpt >> 6) & 0x1f));
+        result.push_back(0x80 | (cpt & 0x3f));
+        return result;
+    }
+    if (0x800 <= cpt && cpt <= 0xffff) {
+        result.push_back(0xe0 | ((cpt >> 12) & 0x0f));
+        result.push_back(0x80 | ((cpt >> 6) & 0x3f));
+        result.push_back(0x80 | (cpt & 0x3f));
+        return result;
+    }
+    if (0x10000 <= cpt && cpt <= 0x10ffff) {
+        result.push_back(0xf0 | ((cpt >> 18) & 0x07));
+        result.push_back(0x80 | ((cpt >> 12) & 0x3f));
+        result.push_back(0x80 | ((cpt >> 6) & 0x3f));
+        result.push_back(0x80 | (cpt & 0x3f));
+        return result;
+    }
+
+    throw std::invalid_argument("invalid codepoint");
+}
+
+
+

common/unicode.h

@@ -2,6 +2,8 @@
 
 #include <cstdint>
 #include <string_view>
+#include <vector>
+#include <string>
 
 // UTF-8 parsing utilities for streaming-aware unicode support
 
@@ -16,7 +18,10 @@ struct utf8_parse_result {
 
 // Determine the expected length of a UTF-8 sequence from its first byte
 // Returns 0 for invalid first bytes
-size_t utf8_sequence_length(unsigned char first_byte);
+size_t common_utf8_sequence_length(unsigned char first_byte);
 
 // Parse a single UTF-8 codepoint from input
-utf8_parse_result parse_utf8_codepoint(std::string_view input, size_t offset);
+utf8_parse_result common_parse_utf8_codepoint(std::string_view input, size_t offset);
+
+std::string common_unicode_cpts_to_utf8(const std::vector<uint32_t> & cps);
+std::string common_unicode_cpt_to_utf8(uint32_t cpt);

convert_hf_to_gguf.py

@@ -116,7 +116,8 @@ class ModelBase:
                  split_max_tensors: int = 0, split_max_size: int = 0, dry_run: bool = False,
                  small_first_shard: bool = False, hparams: dict[str, Any] | None = None, remote_hf_model_id: str | None = None,
                  disable_mistral_community_chat_template: bool = False,
-                 sentence_transformers_dense_modules: bool = False):
+                 sentence_transformers_dense_modules: bool = False,
+                 fuse_gate_up_exps: bool = False):
         if type(self) is ModelBase or \
                 type(self) is TextModel or \
                 type(self) is MmprojModel:
@@ -135,6 +136,9 @@ class ModelBase:
         self.dry_run = dry_run
         self.remote_hf_model_id = remote_hf_model_id
         self.sentence_transformers_dense_modules = sentence_transformers_dense_modules
+        self.fuse_gate_up_exps = fuse_gate_up_exps
+        self._gate_exp_buffer: dict[int, Tensor] = {}
+        self._up_exp_buffer: dict[int, Tensor] = {}
         self.hparams = ModelBase.load_hparams(self.dir_model, self.is_mistral_format) if hparams is None else hparams
         self.model_tensors = self.index_tensors(remote_hf_model_id=remote_hf_model_id)
         self.metadata_override = metadata_override
@@ -512,8 +516,31 @@ class ModelBase:
         raise NotImplementedError("set_gguf_parameters() must be implemented in subclasses")
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
-        del bid # unused
-        return [(self.map_tensor_name(name), data_torch)]
+        new_name = self.map_tensor_name(name)
+
+        # Handle gate/up expert tensor fusion if enabled
+        if self.fuse_gate_up_exps and bid is not None:
+            if self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.FFN_GATE_EXP, bid):
+                self._gate_exp_buffer[bid] = data_torch
+            elif self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.FFN_UP_EXP, bid):
+                self._up_exp_buffer[bid] = data_torch
+
+            # Check if both gate and up are buffered for this layer
+            if bid in self._gate_exp_buffer and bid in self._up_exp_buffer:
+                gate_data = self._gate_exp_buffer.pop(bid)
+                up_data = self._up_exp_buffer.pop(bid)
+                # gate/up shape: (n_expert, n_ff, n_embd), concatenate to (n_expert, n_ff*2, n_embd)
+                fused_data = torch.cat([gate_data, up_data], dim=1)
+                fused_name = self.format_tensor_name(gguf.MODEL_TENSOR.FFN_GATE_UP_EXP, bid)
+                logger.info(f"Fused gate_exps and up_exps for layer {bid}")
+                return [(fused_name, fused_data)]
+
+            # If we buffered a gate/up tensor, wait for the other
+            if self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.FFN_GATE_EXP, bid) or \
+               self.match_model_tensor_name(new_name, gguf.MODEL_TENSOR.FFN_UP_EXP, bid):
+                return []
+
+        return [(new_name, data_torch)]
 
     def tensor_force_quant(self, name: str, new_name: str, bid: int | None, n_dims: int) -> gguf.GGMLQuantizationType | bool:
         del name, new_name, bid, n_dims  # unused
@@ -570,6 +597,7 @@ class ModelBase:
                         self.match_model_tensor_name(new_name, key, bid)
                         for key in (
                             gguf.MODEL_TENSOR.FFN_GATE_INP,
+                            gguf.MODEL_TENSOR.FFN_GATE_INP_SHEXP,
                             gguf.MODEL_TENSOR.POS_EMBD,
                             gguf.MODEL_TENSOR.TOKEN_TYPES,
                             gguf.MODEL_TENSOR.SSM_CONV1D,
@@ -1048,6 +1076,9 @@ class TextModel(ModelBase):
         if chkhsh == "9ca2dd618e8afaf09731a7cf6e2105b373ba6a1821559f258b272fe83e6eb902":
             # ref: https://huggingface.co/zai-org/GLM-4.5-Air
             res = "glm4"
+        if chkhsh == "cdf5f35325780597efd76153d4d1c16778f766173908894c04afc20108536267":
+            # ref: https://huggingface.co/zai-org/GLM-4.7-Flash
+            res = "glm4"
         if chkhsh == "1431a23e583c97432bc230bff598d103ddb5a1f89960c8f1d1051aaa944d0b35":
             # ref: https://huggingface.co/sapienzanlp/Minerva-7B-base-v1.0
             res = "minerva-7b"
@@ -1081,9 +1112,6 @@ class TextModel(ModelBase):
         if chkhsh == "b3d1dd861f1d4c5c0d2569ce36baf3f90fe8a102db3de50dd71ff860d91be3df":
             # ref: https://huggingface.co/aari1995/German_Semantic_V3
             res = "jina-v2-de"
-        if chkhsh == "cdf5f35325780597efd76153d4d1c16778f766173908894c04afc20108536267":
-            # ref: https://huggingface.co/zai-org/GLM-4.7-Flash
-            res = "glm4"
         if chkhsh == "0ef9807a4087ebef797fc749390439009c3b9eda9ad1a097abbe738f486c01e5":
             # ref: https://huggingface.co/meta-llama/Meta-Llama-3-8B
             res = "llama-bpe"
@@ -1123,6 +1151,9 @@ class TextModel(ModelBase):
         if chkhsh == "9c2227e4dd922002fb81bde4fc02b0483ca4f12911410dee2255e4987644e3f8":
             # ref: https://huggingface.co/CohereForAI/c4ai-command-r-v01
             res = "command-r"
+        if chkhsh == "d772b220ace2baec124bed8cfafce0ead7d6c38a4b65ef11261cf9d5d62246d1":
+            # ref: https://huggingface.co/CohereLabs/tiny-aya-base
+            res = "tiny_aya"
         if chkhsh == "e636dc30a262dcc0d8c323492e32ae2b70728f4df7dfe9737d9f920a282b8aea":
             # ref: https://huggingface.co/Qwen/Qwen1.5-7B
             res = "qwen2"
@@ -1144,6 +1175,9 @@ class TextModel(ModelBase):
         if chkhsh == "27949a2493fc4a9f53f5b9b029c82689cfbe5d3a1929bb25e043089e28466de6":
             # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-de
             res = "jina-v2-de"
+        if chkhsh == "a023e9fdc5a11f034d3ef515b92350e56fb2af1f66c6b6811a4444ea9bf8763d":
+            # ref: https://huggingface.co/jinaai/jina-embeddings-v5-text-nano
+            res = "jina-v5-nano"
         if chkhsh == "c136ed14d01c2745d4f60a9596ae66800e2b61fa45643e72436041855ad4089d":
             # ref: https://huggingface.co/abacusai/Smaug-Llama-3-70B-Instruct
             res = "smaug-bpe"
@@ -1159,6 +1193,9 @@ class TextModel(ModelBase):
         if chkhsh == "b53802fb28e26d645c3a310b34bfe07da813026ec7c7716883404d5e0f8b1901":
             # ref: https://huggingface.co/core42/jais-13b
             res = "jais"
+        if chkhsh == "bc5108ee1eb6a3d600cadd065f63190fbd0554dbc9e4bbd6a0d977970afc8d2a":
+            # ref: https://huggingface.co/inceptionai/Jais-2-8B-Chat
+            res = "jais-2"
         if chkhsh == "7b3e7548e4308f52a76e8229e4e6cc831195d0d1df43aed21ac6c93da05fec5f":
             # ref: https://huggingface.co/WisdomShell/CodeShell-7B
             res = "codeshell"
@@ -1264,6 +1301,12 @@ class TextModel(ModelBase):
         if chkhsh == "d30d75d9059f1aa2c19359de71047b3ae408c70875e8a3ccf8c5fba56c9d8af4":
             # ref: https://huggingface.co/Qwen/Qwen3.5-9B-Instruct
             res = "qwen35"
+        if chkhsh == "b4b8ca1f9769494fbd956ebc4c249de6131fb277a4a3345a7a92c7dd7a55808d":
+            # ref: https://huggingface.co/jdopensource/JoyAI-LLM-Flash
+            res = "joyai-llm"
+        if chkhsh == "e4d54df1ebc1f2b91acd986c5b51aa50837d5faf7c7398e73c1f9e9ee5d19869":
+            # ref: https://huggingface.co/kakaocorp/kanana-2-30b-a3b-instruct-2601
+            res = "kanana2"
 
         if res is None:
             logger.warning("\n")
@@ -1608,6 +1651,23 @@ class TextModel(ModelBase):
         special_vocab._set_special_token("bos", tokenizer.get_added_vocab()["<|endoftext|>"])
         special_vocab.add_to_gguf(self.gguf_writer)
 
+    def _set_vocab_glm(self):
+        from transformers import AutoTokenizer
+        tokenizer = AutoTokenizer.from_pretrained(self.dir_model)
+        special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=True)
+        tokens, toktypes, tokpre = self.get_vocab_base()
+        self.gguf_writer.add_tokenizer_model("gpt2")
+        self.gguf_writer.add_tokenizer_pre(tokpre)
+        self.gguf_writer.add_token_list(tokens)
+        self.gguf_writer.add_token_types(toktypes)
+        # Special tokens
+        # Note: Using <|endoftext|> (151329) for eot causes endless generation
+        special_vocab._set_special_token("bos", tokenizer.get_added_vocab()["[gMASK]"])  # 151331
+        special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"])  # 151336
+        special_vocab._set_special_token("unk", tokenizer.get_added_vocab()["<|endoftext|>"]) # 151329
+        special_vocab._set_special_token("eom", tokenizer.get_added_vocab()["<|observation|>"])  # 151338
+        special_vocab.add_to_gguf(self.gguf_writer)
+
     def _set_vocab_interns1(self):
         tokens: list[str] = []
         toktypes: list[int] = []
@@ -2708,8 +2768,6 @@ class AfmoeModel(LlamaModel):
         super().set_gguf_parameters()
 
         # MoE parameters
-        if (n_experts := self.hparams.get("num_experts")) is not None:
-            self.gguf_writer.add_expert_count(n_experts)
         if (n_shared_experts := self.hparams.get("num_shared_experts")) is not None:
             self.gguf_writer.add_expert_shared_count(n_shared_experts)
         if (moe_intermediate_size := self.hparams.get("moe_intermediate_size")) is not None:
@@ -2731,7 +2789,7 @@ class AfmoeModel(LlamaModel):
         # Handle expert weights - they're already merged in the HF format
         # process the experts separately
         if name.find("mlp.experts") != -1:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -3708,6 +3766,13 @@ class Ernie4_5Model(TextModel):
     def set_vocab(self):
         self._set_vocab_sentencepiece()
 
+        tokenizer_config_file = self.dir_model / 'tokenizer_config.json'
+        if tokenizer_config_file.is_file():
+            with open(tokenizer_config_file, "r", encoding="utf-8") as f:
+                tokenizer_config_json = json.load(f)
+                if "add_prefix_space" in tokenizer_config_json:
+                    self.gguf_writer.add_add_space_prefix(tokenizer_config_json["add_prefix_space"])
+
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
 
@@ -3717,6 +3782,10 @@ class Ernie4_5Model(TextModel):
         if (head_dim := self.hparams.get("head_dim")) is None:
             head_dim = self.hparams["hidden_size"] // num_heads
 
+        if "mlp_AR" in name or "vision_model" in name:
+            # skip vision model and projector tensors
+            return
+
         if "ernie." in name:
             name = name.replace("ernie.", "model.")
         # split the qkv weights
@@ -3826,6 +3895,48 @@ class Ernie4_5MoeModel(Ernie4_5Model):
                 raise ValueError(f"Unprocessed experts: {experts}")
 
 
+@ModelBase.register("PaddleOCRVLForConditionalGeneration")
+class PaddleOCRModel(Ernie4_5Model):
+    model_arch = gguf.MODEL_ARCH.PADDLEOCR
+
+
+@ModelBase.register("PaddleOCRVisionModel")
+class PaddleOCRVisionModel(MmprojModel):
+    # PaddleOCR-VL uses a modified version of Siglip
+    min_pixels: int = 0
+    max_pixels: int = 0
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        assert self.hparams_vision is not None
+        self.min_pixels = self.preprocessor_config["min_pixels"]
+        self.max_pixels = self.preprocessor_config["max_pixels"]
+        self.hparams_vision["image_size"] = int(math.sqrt(self.max_pixels))
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        assert self.hparams_vision is not None
+        hparams = self.hparams_vision
+        self.gguf_writer.add_clip_projector_type(gguf.VisionProjectorType.PADDLEOCR)
+        self.gguf_writer.add_vision_max_pixels(self.max_pixels)
+        self.gguf_writer.add_vision_min_pixels(self.min_pixels)
+        self.gguf_writer.add_vision_use_gelu(True)
+        self.gguf_writer.add_vision_attention_layernorm_eps(hparams.get("rms_norm_eps", 1e-6))
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        name = name.replace("visual.", "model.")
+
+        if "vision_model" in name or "mlp_AR" in name:
+            if "packing_position_embedding" in name:
+                return # unused
+            elif "vision_model.head" in name:
+                # we don't yet support image embeddings for this model
+                return
+            else:
+                yield from super().modify_tensors(data_torch, name, bid)
+        return # skip other tensors
+
+
 @ModelBase.register(
     "Qwen2VLModel",
     "Qwen2VLForConditionalGeneration",
@@ -3920,7 +4031,7 @@ class Qwen2VLVisionModel(MmprojModel):
                 # split Conv3D into Conv2Ds
                 c1, c2, kt, kh, kw = data_torch.shape
                 del c1, c2, kh, kw  # unused
-                assert kt == 2, "Current implmentation only support temporal_patch_size of 2"
+                assert kt == 2, "Current implementation only support temporal_patch_size of 2"
                 yield (gguf.TENSOR_NAMES[gguf.MODEL_TENSOR.V_ENC_EMBD_PATCH] + ".weight"  , data_torch[:, :, 0, ...])
                 yield (gguf.TENSOR_NAMES[gguf.MODEL_TENSOR.V_ENC_EMBD_PATCH] + ".weight.1", data_torch[:, :, 1, ...])
             else:
@@ -4056,6 +4167,87 @@ class InternVisionModel(MmprojModel):
                 yield from super().modify_tensors(data_torch, name, bid)
 
 
+@ModelBase.register(
+    "NemotronH_Nano_VL_V2",
+    "RADIOModel",
+)
+class NemotronNanoV2VLModel(MmprojModel):
+    # ViT-Huge architecture parameters for RADIO v2.5-h
+    _vit_hidden_size = 1280
+    _vit_intermediate_size = 5120
+    _vit_num_layers = 32
+    _vit_num_heads = 16
+
+    def get_vision_config(self) -> dict[str, Any] | None:
+        # RADIO config doesn't have standard ViT parameters, so they need to be constructed manually
+        vision_config = self.global_config.get("vision_config")
+        if vision_config is None:
+            return None
+        # Add ViT-H parameters
+        vision_config = {
+            **vision_config,
+            "hidden_size": self._vit_hidden_size,
+            "intermediate_size": self._vit_intermediate_size,
+            "num_hidden_layers": self._vit_num_layers,
+            "num_attention_heads": self._vit_num_heads,
+            "image_size": self.global_config.get("force_image_size", 512),
+        }
+        return vision_config
+
+    def set_gguf_parameters(self):
+        if "image_mean" not in self.preprocessor_config:
+            self.preprocessor_config["image_mean"] = [0.485, 0.456, 0.406]
+        if "image_std" not in self.preprocessor_config:
+            self.preprocessor_config["image_std"] = [0.229, 0.224, 0.225]
+
+        super().set_gguf_parameters()
+        hparams = self.global_config
+        self.gguf_writer.add_clip_projector_type(gguf.VisionProjectorType.NEMOTRON_V2_VL)
+        self.gguf_writer.add_vision_attention_layernorm_eps(1e-6)
+        self.gguf_writer.add_vision_use_gelu(True)
+        downsample_ratio = hparams.get("downsample_ratio", 0.5)
+        self.gguf_writer.add_vision_projector_scale_factor(int(1.0 / downsample_ratio))
+
+    def tensor_force_quant(self, name, new_name, bid, n_dims):
+        if ".position_embd." in new_name or "pos_embed" in new_name:
+            return gguf.GGMLQuantizationType.F32
+        return super().tensor_force_quant(name, new_name, bid, n_dims)
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        if "input_conditioner" in name:
+            return
+
+        # RADIO's pos_embed doesn't have .weight suffix, but clip.cpp expects it
+        if "patch_generator.pos_embed" in name:
+            if not name.endswith(".weight"):
+                name += ".weight"
+            # Downsample position embeddings for fixed 512x512 image size
+            import torch.nn.functional as F
+            n_embd = self.hparams["hidden_size"]
+            image_size = self.global_config.get("force_image_size", 512)
+            patch_size = self.hparams["patch_size"]
+            target_patches_per_side = image_size // patch_size  # 32
+            max_patches_per_side = int((data_torch.shape[1]) ** 0.5)  # 128
+            if target_patches_per_side != max_patches_per_side:
+                # Reshape to grid, interpolate, flatten back
+                data_torch = data_torch.reshape(1, max_patches_per_side, max_patches_per_side, n_embd)
+                data_torch = data_torch.permute(0, 3, 1, 2).float()  # [1, n_embd, 128, 128]
+                data_torch = F.interpolate(data_torch, size=(target_patches_per_side, target_patches_per_side),
+                                           mode='bilinear', align_corners=True)
+                data_torch = data_torch.permute(0, 2, 3, 1)  # [1, 32, 32, n_embd]
+                data_torch = data_torch.reshape(1, target_patches_per_side * target_patches_per_side, n_embd)
+
+        # Reshape linear patch embedding to conv2d format for ggml_conv_2d
+        # From [n_embd, patch_size*patch_size*3] to [n_embd, 3, patch_size, patch_size]
+        if "patch_generator.embedder" in name:
+            patch_size = self.hparams["patch_size"]
+            n_embd = self.hparams["hidden_size"]
+            data_torch = data_torch.reshape(n_embd, 3, patch_size, patch_size)
+
+        if name.startswith("vision_model.radio_model.model.") or name.startswith("mlp1."):
+            yield from super().modify_tensors(data_torch, name, bid)
+
+
 @ModelBase.register("WavTokenizerDec")
 class WavTokenizerDecModel(TextModel):
     model_arch = gguf.MODEL_ARCH.WAVTOKENIZER_DEC
@@ -4098,8 +4290,6 @@ class Qwen2MoeModel(TextModel):
 
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
-        if (n_experts := self.hparams.get("num_experts")) is not None:
-            self.gguf_writer.add_expert_count(n_experts)
         if (moe_intermediate_size := self.hparams.get("moe_intermediate_size")) is not None:
             self.gguf_writer.add_expert_feed_forward_length(moe_intermediate_size)
             logger.info(f"gguf: expert feed forward length = {moe_intermediate_size}")
@@ -4144,7 +4334,7 @@ class Qwen2MoeModel(TextModel):
             return
 
         if name.find("experts") != -1:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -4483,7 +4673,7 @@ class Qwen3VLVisionModel(MmprojModel):
         yield from super().modify_tensors(data_torch, name, bid)
 
 
-@ModelBase.register("Glm4vForConditionalGeneration", "Glm4vMoeForConditionalGeneration")
+@ModelBase.register("Glm4vForConditionalGeneration", "Glm4vMoeForConditionalGeneration", "GlmOcrForConditionalGeneration")
 class Glm4VVisionModel(Qwen3VLVisionModel):
     def set_gguf_parameters(self):
         MmprojModel.set_gguf_parameters(self) # skip Qwen3VLVisionModel parameters
@@ -4652,12 +4842,12 @@ class _LinearAttentionVReorderBase(Qwen3NextModel):
         yield from super().modify_tensors(data_torch, name, bid)
 
 
-@ModelBase.register("Qwen3_5ForConditionalGeneration")
+@ModelBase.register("Qwen3_5ForConditionalGeneration", "Qwen3_5ForCausalLM")
 class Qwen3_5TextModel(_LinearAttentionVReorderBase):
     model_arch = gguf.MODEL_ARCH.QWEN35
 
 
-@ModelBase.register("Qwen3_5MoeForConditionalGeneration")
+@ModelBase.register("Qwen3_5MoeForConditionalGeneration", "Qwen3_5MoeForCausalLM")
 class Qwen3_5MoeTextModel(_LinearAttentionVReorderBase):
     model_arch = gguf.MODEL_ARCH.QWEN35MOE
 
@@ -4895,13 +5085,13 @@ class PhiMoeModel(Phi3MiniModel):
 
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
-        self.gguf_writer.add_expert_used_count(self.hparams["num_experts_per_tok"])
-        self.gguf_writer.add_expert_count(self.hparams["num_local_experts"])
+        self.gguf_writer.add_expert_used_count(self.find_hparam(["num_experts_per_tok", "num_experts_per_token"]))
+        self.gguf_writer.add_expert_count(self.find_hparam(["num_local_experts", "num_experts"]))
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         # process the experts separately
         if name.find("block_sparse_moe.experts") != -1:
-            n_experts = self.hparams["num_local_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -5214,7 +5404,7 @@ class KimiLinearModel(TextModel):
         # Get ssm_d_conv from linear_attn_config.short_conv_kernel_size or ssm_d_conv
         linear_attn_config = self.hparams["linear_attn_config"]
         # n_head == 0 for KDA layers, n_head > 0 for MLA layers
-        # full_attention_layers list will be used to distingush layer type
+        # full_attention_layers list will be used to distinguish layer type
         _num_kv_heads = list()
         _full_attn_layers = linear_attn_config["full_attn_layers"]
         for il in range(self.hparams["num_hidden_layers"]):
@@ -5313,7 +5503,7 @@ class KimiLinearModel(TextModel):
 
         # process the experts separately
         if name.find("block_sparse_moe.experts") != -1:
-            n_experts = self.find_hparam(["num_local_experts", "num_experts"], optional=False)
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -5908,12 +6098,13 @@ class NomicBertModel(BertModel):
         if "mlp.experts.bias" in name:
             return # Explicitly return.
 
+        n_experts = self.find_hparam(["num_local_experts", "num_experts"])
         if "mlp.experts.mlp.w1" in name:
-            data_torch = data_torch.view(self.hparams["num_experts"], self.hparams["n_inner"], self.hparams["n_embd"])
+            data_torch = data_torch.view(n_experts, self.hparams["n_inner"], self.hparams["n_embd"])
             name += ".weight"
 
         if "mlp.experts.mlp.w2" in name:
-            data_torch = data_torch.view(self.hparams["num_experts"], self.hparams["n_inner"], self.hparams["n_embd"])
+            data_torch = data_torch.view(n_experts, self.hparams["n_inner"], self.hparams["n_embd"])
             data_torch = data_torch.transpose(1, 2)
             name += ".weight"
 
@@ -5923,7 +6114,6 @@ class NomicBertModel(BertModel):
         super().set_gguf_parameters()
         if self.is_moe:
             self.gguf_writer.add_moe_every_n_layers(self.hparams["moe_every_n_layers"])
-            self.gguf_writer.add_expert_count(self.hparams["num_experts"])
             self.gguf_writer.add_expert_used_count(self.hparams["moe_top_k"])
 
     def _is_tokenizer_xlmroberta(self) -> bool:
@@ -5965,6 +6155,32 @@ class NeoBert(BertModel):
         yield from super().modify_tensors(data_torch, name, bid)
 
 
+@ModelBase.register("EuroBertModel", "JinaEmbeddingsV5Model")
+class EuroBertModel(TextModel):
+    model_arch = gguf.MODEL_ARCH.EUROBERT
+
+    def set_vocab(self):
+        self.gguf_writer.add_add_bos_token(False)
+        self._set_vocab_gpt2()
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+
+        # EuroBert is bidirectional (encoder)
+        self.gguf_writer.add_causal_attention(False)
+
+        self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.NONE)
+
+        self._try_set_pooling_type()
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        # Strip "model." prefix from tensor names
+        if name.startswith("model."):
+            name = name[6:]
+
+        yield from super().modify_tensors(data_torch, name, bid)
+
+
 @ModelBase.register("XLMRobertaModel", "XLMRobertaForSequenceClassification")
 class XLMRobertaModel(BertModel):
     model_arch = gguf.MODEL_ARCH.BERT
@@ -6289,7 +6505,7 @@ class Gemma3VisionModel(MmprojModel):
         super().set_gguf_parameters()
         hparams = self.hparams
         self.gguf_writer.add_clip_projector_type(gguf.VisionProjectorType.GEMMA3)
-        # default values below are taken from HF tranformers code
+        # default values below are taken from HF transformers 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)
@@ -6881,7 +7097,7 @@ class Rwkv7Model(TextModel):
 
             if bid == 0 and "time_mix_a" in new_name:
                 # dummy v0/v1/v2 on first layer
-                # easist way to make llama happy
+                # easiest way to make llama happy
                 yield (new_name.replace("time_mix_a", "time_mix_v"), data_torch)
 
             yield (new_name, data_torch)
@@ -7037,6 +7253,8 @@ class Mamba2Model(TextModel):
         if hparams is None:
             with open(dir_model / "config.json", "r", encoding="utf-8") as f:
                 hparams = json.load(f)
+        if "llm_config" in hparams:
+            hparams["text_config"] = hparams["llm_config"]
         super().__init__(dir_model, *args, hparams=hparams, **kwargs)
         self.d_model = self.find_hparam(["hidden_size", "d_model", "dim"])
         self.d_inner = self.find_hparam(["mamba_d_ssm", "intermediate_size", "d_inner"], optional=True) or 2 * self.d_model
@@ -7158,8 +7376,8 @@ class JambaModel(TextModel):
         self.gguf_writer.add_ssm_state_size(d_state)
         self.gguf_writer.add_ssm_time_step_rank(dt_rank)
         self.gguf_writer.add_layer_norm_rms_eps(rms_norm_eps)
-        self.gguf_writer.add_expert_count(self.hparams["num_experts"])
-        self.gguf_writer.add_expert_used_count(self.hparams["num_experts_per_tok"])
+        self.gguf_writer.add_expert_count(self.find_hparam(["num_local_experts", "num_experts"]))
+        self.gguf_writer.add_expert_used_count(self.find_hparam(["num_experts_per_tok", "num_experts_per_token"]))
         self.gguf_writer.add_file_type(self.ftype)
 
     _experts: list[dict[str, Tensor]] | None = None
@@ -7177,7 +7395,7 @@ class JambaModel(TextModel):
 
         # process the experts separately
         if ".feed_forward.experts." in name:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
 
             assert bid is not None
 
@@ -7263,6 +7481,17 @@ class Cohere2Model(TextModel):
         self.gguf_writer.add_rope_dimension_count(int(rotary_pct * (hidden_size // num_attention_heads)))
         self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.NONE)
 
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        # Cohere2 runtime in llama.cpp expects no bias tensors;
+        # the actual weight only contains 0-value tensors as bias, we can skip them
+        if name.endswith(".bias"):
+            if torch.any(data_torch != 0):
+                raise ValueError(f"Bias tensor {name!r} is not zero.")
+            logger.debug(f"Skipping bias tensor {name!r} for Cohere2 conversion.")
+            return
+
+        yield from super().modify_tensors(data_torch, name, bid)
+
 
 @ModelBase.register("OlmoForCausalLM")
 @ModelBase.register("OLMoForCausalLM")
@@ -7325,8 +7554,6 @@ class OlmoeModel(TextModel):
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
         self.gguf_writer.add_layer_norm_rms_eps(1e-5)
-        if (n_experts := self.hparams.get("num_experts")) is not None:
-            self.gguf_writer.add_expert_count(n_experts)
 
     _experts: list[dict[str, Tensor]] | None = None
 
@@ -7334,7 +7561,7 @@ class OlmoeModel(TextModel):
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         # process the experts separately
         if name.find("experts") != -1:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -7710,6 +7937,9 @@ class DeepseekModel(TextModel):
 class DeepseekV2Model(TextModel):
     model_arch = gguf.MODEL_ARCH.DEEPSEEK2
 
+    # TODO @ngxson : remove this when we support MTP for deepseek models
+    skip_mtp = True
+
     def set_vocab(self):
         try:
             self._set_vocab_gpt2()
@@ -7841,10 +8071,11 @@ class DeepseekV2Model(TextModel):
             name = name.replace("e_score_correction_bias", "e_score_correction.bias")
 
         # skip Multi-Token Prediction (MTP) layers
-        block_count = self.hparams["num_hidden_layers"]
-        match = re.match(r"model.layers.(\d+)", name)
-        if match and int(match.group(1)) >= block_count:
-            return
+        if self.skip_mtp:
+            block_count = self.hparams["num_hidden_layers"]
+            match = re.match(r"model.layers.(\d+)", name)
+            if match and int(match.group(1)) >= block_count:
+                return
 
         # process the experts separately
         if name.find("mlp.experts") != -1:
@@ -7911,10 +8142,6 @@ class MiniMaxM2Model(TextModel):
     model_arch = gguf.MODEL_ARCH.MINIMAXM2
     _experts_cache: dict[int, dict[str, Tensor]] = {}
 
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        self.hparams["num_experts"] = self.hparams["num_local_experts"]
-
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
 
@@ -7927,7 +8154,7 @@ class MiniMaxM2Model(TextModel):
 
         # merge expert weights
         if 'experts' in name:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             expert_cache = self._experts_cache.setdefault(bid, {})
@@ -8521,6 +8748,17 @@ class T5EncoderModel(TextModel):
         yield from super().modify_tensors(data_torch, name, bid)
 
 
+@ModelBase.register("Jais2ForCausalLM")
+class Jais2Model(TextModel):
+    model_arch = gguf.MODEL_ARCH.JAIS2
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        hparams = self.hparams
+        head_dim = hparams.get("head_dim", hparams["hidden_size"] // hparams["num_attention_heads"])
+        self.gguf_writer.add_rope_dimension_count(head_dim)
+
+
 @ModelBase.register("JAISLMHeadModel")
 class JaisModel(TextModel):
     model_arch = gguf.MODEL_ARCH.JAIS
@@ -8664,7 +8902,7 @@ class Glm4Model(TextModel):
             n_head = self.hparams["num_attention_heads"]
             n_kv_head = self.hparams["num_key_value_heads"]
             n_embd = self.hparams["hidden_size"]
-            head_dim = n_embd // n_head
+            head_dim = self.hparams.get("head_dim", n_embd // n_head)
             # because llama.cpp M-RoPE kernel only supports Neox ordering, we have to permute the weights here
             if name.endswith(("q_proj.weight", "q_proj.bias")):
                 data_torch = Glm4Model.normal_to_neox(data_torch, n_head, n_head, head_dim, self.partial_rotary_factor)
@@ -8673,6 +8911,27 @@ class Glm4Model(TextModel):
         yield from super().modify_tensors(data_torch, name, bid)
 
 
+@ModelBase.register("GlmOcrForConditionalGeneration")
+class GlmOCRModel(Glm4Model):
+    model_arch = gguf.MODEL_ARCH.GLM4
+    use_mrope = False
+    partial_rotary_factor = 0.5
+
+    # Note: GLM-OCR is the same as GLM4, but with an extra NextN/MTP prediction layer
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        # GLM-OCR has num_hidden_layers + 1 actual layers (including NextN layer)
+        self.block_count = self.hparams["num_hidden_layers"] + self.hparams.get("num_nextn_predict_layers", 0)
+        self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        # NextN/MTP prediction layers
+        if (num_nextn_predict_layers := self.hparams.get("num_nextn_predict_layers")) is not None:
+            self.gguf_writer.add_nextn_predict_layers(num_nextn_predict_layers)
+
+
 @ModelBase.register("Glm4MoeForCausalLM", "Glm4vMoeForConditionalGeneration")
 class Glm4MoeModel(TextModel):
     model_arch = gguf.MODEL_ARCH.GLM4_MOE
@@ -8684,24 +8943,7 @@ class Glm4MoeModel(TextModel):
         self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)
 
     def set_vocab(self):
-        from transformers import AutoTokenizer
-
-        tokenizer = AutoTokenizer.from_pretrained(self.dir_model)
-        special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=True)
-        tokens, toktypes, tokpre = self.get_vocab_base()
-        self.gguf_writer.add_tokenizer_model("gpt2")
-        self.gguf_writer.add_tokenizer_pre(tokpre)
-        self.gguf_writer.add_token_list(tokens)
-        self.gguf_writer.add_token_types(toktypes)
-
-        # Special tokens
-        # Note: Using <|endoftext|> (151329) for eot causes endless generation
-        special_vocab._set_special_token("bos", tokenizer.get_added_vocab()["[gMASK]"])  # 151331
-        special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"])  # 151336
-        special_vocab._set_special_token("unk", tokenizer.get_added_vocab()["<|endoftext|>"]) # 151329
-        special_vocab._set_special_token("eom", tokenizer.get_added_vocab()["<|observation|>"])  # 151338
-
-        special_vocab.add_to_gguf(self.gguf_writer)
+        return self._set_vocab_glm()
 
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
@@ -8801,26 +9043,38 @@ class Glm4MoeModel(TextModel):
 class Glm4MoeLiteModel(DeepseekV2Model):
     model_arch = gguf.MODEL_ARCH.DEEPSEEK2
 
-    # copied from Glm4MoeModel
     def set_vocab(self):
-        from transformers import AutoTokenizer
+        return self._set_vocab_glm()
 
-        tokenizer = AutoTokenizer.from_pretrained(self.dir_model)
-        special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=True)
-        tokens, toktypes, tokpre = self.get_vocab_base()
-        self.gguf_writer.add_tokenizer_model("gpt2")
-        self.gguf_writer.add_tokenizer_pre(tokpre)
-        self.gguf_writer.add_token_list(tokens)
-        self.gguf_writer.add_token_types(toktypes)
 
-        # Special tokens
-        # Note: Using <|endoftext|> (151329) for eot causes endless generation
-        special_vocab._set_special_token("bos", tokenizer.get_added_vocab()["[gMASK]"])  # 151331
-        special_vocab._set_special_token("eot", tokenizer.get_added_vocab()["<|user|>"])  # 151336
-        special_vocab._set_special_token("unk", tokenizer.get_added_vocab()["<|endoftext|>"]) # 151329
-        special_vocab._set_special_token("eom", tokenizer.get_added_vocab()["<|observation|>"])  # 151338
+@ModelBase.register("GlmMoeDsaForCausalLM")
+class GlmMoeDsaModel(DeepseekV2Model):
+    model_arch = gguf.MODEL_ARCH.GLM_DSA
+    skip_mtp = False
 
-        special_vocab.add_to_gguf(self.gguf_writer)
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.block_count = self.hparams["num_hidden_layers"] + self.hparams.get("num_nextn_predict_layers", 0)
+        self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count)
+
+    def set_vocab(self):
+        return self._set_vocab_glm()
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+
+        rope_dim = self.hparams["qk_rope_head_dim"]
+        partial_rotary_factor = self.hparams.get("partial_rotary_factor", 1.0)
+        self.gguf_writer.add_rope_dimension_count(int(rope_dim * partial_rotary_factor))
+
+        # NextN/MTP prediction layers
+        if (num_nextn_predict_layers := self.hparams.get("num_nextn_predict_layers")) is not None:
+            self.gguf_writer.add_nextn_predict_layers(num_nextn_predict_layers)
+
+        # DSA indexer parameters
+        self.gguf_writer.add_indexer_head_count(self.hparams["index_n_heads"])
+        self.gguf_writer.add_indexer_key_length(self.hparams["index_head_dim"])
+        self.gguf_writer.add_indexer_top_k(self.hparams["index_topk"])
 
 
 @ModelBase.register("GlmForCausalLM", "ChatGLMModel", "ChatGLMForConditionalGeneration")
@@ -9137,7 +9391,6 @@ class ExaoneMoEModel(Exaone4Model):
 
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
-        self.gguf_writer.add_expert_count(self.hparams["num_experts"])
         moe_intermediate_size = self.hparams["moe_intermediate_size"]
         num_shared_experts = self.hparams["num_shared_experts"]
         self.gguf_writer.add_expert_feed_forward_length(moe_intermediate_size)
@@ -9178,7 +9431,7 @@ class ExaoneMoEModel(Exaone4Model):
             name = name.replace("e_score_correction_bias", "e_score_correction.bias")
 
         if name.find("mlp.experts") != -1:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -9329,7 +9582,7 @@ class GraniteHybridModel(Mamba2Model, GraniteMoeModel):
         # case, the model architecture needs to be updated to a standard
         # "granite" or "granitemoe" model
         if not self._ssm_layers:
-            has_experts = self.find_hparam(["num_experts_per_tok"], optional=True)
+            has_experts = self.find_hparam(["num_experts_per_tok", "num_experts_per_token"], optional=True)
             new_arch = (
                 gguf.MODEL_ARCH.GRANITE_MOE
                 if has_experts else
@@ -9343,7 +9596,7 @@ class GraniteHybridModel(Mamba2Model, GraniteMoeModel):
         # NOTE: Explicitly include hparam prefix prefix for d_model to
         #   disambiguate with top-level head_dim
         # NOTE 2: If needed for future models, this can be isolated in a method
-        #   to separate the prefix setting and teh keys used
+        #   to separate the prefix setting and the keys used
         self.d_model = self.find_hparam([f"{self.hparam_prefixes[0]}_head_dim", "hidden_size", "d_model"])
         self.n_group = self.find_hparam(["n_groups", "num_groups"])
         self.d_inner = self.find_hparam(["expand", "num_heads"]) * self.d_model
@@ -9490,7 +9743,7 @@ class NemotronHModel(GraniteHybridModel):
         self.gguf_writer.add_value_length(self.head_dim)
 
         # Set feed_forward_length
-        # NOTE: This will trigger an override warning. This is preferrable to
+        # NOTE: This will trigger an override warning. This is preferable to
         #   duplicating all the parent logic
         if not self.is_moe:
             n_ff = self.find_hparam(["intermediate_size", "n_inner", "hidden_dim"])
@@ -9525,6 +9778,14 @@ class NemotronHModel(GraniteHybridModel):
             self.gguf_writer.add_add_bos_token(True)
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        # Skip vision model and projector tensors for VLM models (handled by mmproj) (e.g., Nemotron Nano 12B v2 VL)
+        if name.startswith(("vision_model.", "mlp1.")):
+            return
+
+        # Strip language_model. prefix for VLM models (e.g., Nemotron Nano 12B v2 VL)
+        if name.startswith("language_model."):
+            name = name[len("language_model."):]
+
         if self.is_moe and bid is not None:
             if name.endswith("mixer.gate.e_score_correction_bias"):
                 new_name = name.replace("e_score_correction_bias", "e_score_correction.bias")
@@ -9619,7 +9880,6 @@ class BailingMoeModel(TextModel):
         self.gguf_writer.add_vocab_size(hparams["vocab_size"])
         self.gguf_writer.add_expert_feed_forward_length(hparams["moe_intermediate_size"])
         self.gguf_writer.add_expert_weights_scale(1.0)
-        self.gguf_writer.add_expert_count(hparams["num_experts"])
         self.gguf_writer.add_expert_shared_count(hparams["num_shared_experts"])
         self.gguf_writer.add_expert_weights_norm(hparams["norm_topk_prob"])
 
@@ -9653,7 +9913,7 @@ class BailingMoeModel(TextModel):
             yield from super().modify_tensors(v,self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_V, bid), bid)
             return
         elif name.find("mlp.experts") != -1:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -9724,7 +9984,6 @@ class BailingMoeV2Model(TextModel):
         self.gguf_writer.add_expert_feed_forward_length(hparams["moe_intermediate_size"])
         self.gguf_writer.add_expert_shared_feed_forward_length(hparams.get("moe_shared_expert_intermediate_size", hparams["moe_intermediate_size"] * hparams["num_shared_experts"]))
         self.gguf_writer.add_expert_weights_scale(hparams["routed_scaling_factor"])
-        self.gguf_writer.add_expert_count(hparams["num_experts"])
         self.gguf_writer.add_expert_shared_count(hparams["num_shared_experts"])
         self.gguf_writer.add_expert_weights_norm(hparams["norm_topk_prob"])
 
@@ -9735,7 +9994,7 @@ class BailingMoeV2Model(TextModel):
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         if "mlp.experts" in name:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -9781,8 +10040,6 @@ class GroveMoeModel(TextModel):
 
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
-        if (n_experts := self.hparams.get("num_experts")) is not None:
-            self.gguf_writer.add_expert_count(n_experts)
         if (moe_intermediate_size := self.hparams.get("moe_intermediate_size")) is not None:
             self.gguf_writer.add_expert_feed_forward_length(moe_intermediate_size)
             logger.info(f"gguf: expert feed forward length = {moe_intermediate_size}")
@@ -9803,7 +10060,7 @@ class GroveMoeModel(TextModel):
 
         # process the experts separately
         if name.find("chunk_experts") != -1:
-            n_experts = self.hparams["num_experts"] // 2 # see add_experts_per_group
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"]) // 2 # see add_experts_per_group
             assert bid is not None
 
             if self._chunk_experts is None:
@@ -9830,7 +10087,7 @@ class GroveMoeModel(TextModel):
             else:
                 return
         elif name.find("experts") != -1:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -10223,7 +10480,6 @@ class HunYuanMoEModel(TextModel):
         super().set_gguf_parameters()
         hparams = self.hparams
 
-        self.gguf_writer.add_expert_count(hparams["num_experts"])
         self.gguf_writer.add_expert_shared_feed_forward_length(hparams["intermediate_size"])
 
         moe_intermediate_size = hparams["moe_intermediate_size"]
@@ -10266,7 +10522,7 @@ class HunYuanMoEModel(TextModel):
                 return
 
         if name.find("mlp.experts") != -1:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -10308,16 +10564,9 @@ class LLaDAMoEModel(TextModel):
 
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
-        if (n_experts := self.hparams.get("num_experts")) is not None:
-            self.gguf_writer.add_expert_count(n_experts)
-
         if (expert_intermediate_size := self.hparams.get("expert_intermediate_size")) is not None:
             self.gguf_writer.add_expert_feed_forward_length(expert_intermediate_size)
 
-        # number of experts used per token (top-k)
-        if (n_experts_used := self.hparams.get("num_experts_per_tok")) is not None:
-            self.gguf_writer.add_expert_used_count(n_experts_used)
-
         self.gguf_writer.add_mask_token_id(156895)
         self.gguf_writer.add_causal_attention(False)
         self.gguf_writer.add_diffusion_shift_logits(False)
@@ -10328,7 +10577,7 @@ class LLaDAMoEModel(TextModel):
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         # process the experts separately
         if name.find("experts") != -1:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -10603,7 +10852,7 @@ class LFM2Model(TextModel):
     def set_gguf_parameters(self):
         # set num_key_value_heads only for attention layers
         self.hparams["num_key_value_heads"] = [
-            self.hparams["num_key_value_heads"] if layer_type == "full_attention" else 0
+            self.hparams["num_key_value_heads"] if layer_type != "conv" else 0
             for layer_type in self.hparams["layer_types"]
         ]
 
@@ -10665,7 +10914,6 @@ class LFM2MoeModel(TextModel):
 
         super().set_gguf_parameters()
 
-        self.gguf_writer.add_expert_count(self.hparams["num_experts"])
         self.gguf_writer.add_expert_feed_forward_length(self.hparams["moe_intermediate_size"])
         self.gguf_writer.add_leading_dense_block_count(self.hparams["num_dense_layers"])
         self.gguf_writer.add_expert_gating_func(gguf.ExpertGatingFuncType.SIGMOID)
@@ -10686,7 +10934,7 @@ class LFM2MoeModel(TextModel):
 
         # merge expert weights
         if 'experts' in name:
-            n_experts = self.hparams["num_experts"]
+            n_experts = self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             expert_cache = self._experts_cache.setdefault(bid, {})
@@ -10790,15 +11038,37 @@ class LFM2AudioModel(ConformerAudioModel):
         yield from super().modify_tensors(data_torch, name, bid)
 
 
+@ModelBase.register("Lfm25AudioTokenizer")
+class LFM25AudioTokenizer(LFM2Model):
+    model_arch = gguf.MODEL_ARCH.LFM2
+
+    def set_vocab(self):
+        self._set_vocab_none()
+
+    def set_gguf_parameters(self):
+        super().set_gguf_parameters()
+        self.gguf_writer.add_sliding_window(self.hparams["sliding_window"])
+        self.gguf_writer.add_embedding_length_out(self.hparams["output_size"])
+
+    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
+        if name == "istft.window" or name.startswith("emb.emb"):
+            return
+
+        if name.startswith("lin"):
+            name = name.replace("lin", "dense_2_out")
+
+        yield from super().modify_tensors(data_torch, name, bid)
+
+
 @ModelBase.register("SmallThinkerForCausalLM")
 class SmallThinkerModel(TextModel):
     model_arch = gguf.MODEL_ARCH.SMALLTHINKER
 
     def set_gguf_parameters(self):
         super().set_gguf_parameters()
-        if (n_experts := self.hparams.get("num_experts", self.hparams.get("moe_num_primary_experts"))) is not None:
+        if (n_experts := self.hparams.get("moe_num_primary_experts")) is not None:
             self.gguf_writer.add_expert_count(n_experts)
-        if (n_experts_used := self.hparams.get("num_experts_per_tok", self.hparams.get("moe_num_active_primary_experts"))) is not None:
+        if (n_experts_used := self.hparams.get("moe_num_active_primary_experts")) is not None:
             self.gguf_writer.add_expert_used_count(n_experts_used)
         if (moe_intermediate_size := self.hparams.get("moe_ffn_hidden_size")) is not None:
             self.gguf_writer.add_expert_feed_forward_length(moe_intermediate_size)
@@ -10823,7 +11093,7 @@ class SmallThinkerModel(TextModel):
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
         # process the experts separately
         if name.find("experts") != -1:
-            n_experts = self.hparams.get("num_experts", self.hparams.get("moe_num_primary_experts"))
+            n_experts = self.hparams.get("moe_num_primary_experts") or self.find_hparam(["num_local_experts", "num_experts"])
             assert bid is not None
 
             if self._experts is None:
@@ -10881,13 +11151,17 @@ class ModernBertModel(BertModel):
         self.gguf_writer.add_vocab_size(self.hparams["vocab_size"])
 
     def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
-        # these layers act as MLM head, so we don't need them
-        if name.startswith("decoder."):
-            return
-
         if name.startswith("model."):
             name = name[6:]
 
+        if self.cls_out_labels:
+            # For BertForSequenceClassification (direct projection layer)
+            if name == "classifier.weight":
+                name = "classifier.out_proj.weight"
+
+            if name == "classifier.bias":
+                name = "classifier.out_proj.bias"
+
         yield from super().modify_tensors(data_torch, name, bid)
 
 
@@ -11695,6 +11969,11 @@ def parse_args() -> argparse.Namespace:
               "Default these modules are not included.")
     )
 
+    parser.add_argument(
+        "--fuse-gate-up-exps", action="store_true",
+        help="Fuse gate_exps and up_exps tensors into a single gate_up_exps tensor for MoE models.",
+    )
+
     args = parser.parse_args()
     if not args.print_supported_models and args.model is None:
         parser.error("the following arguments are required: model")
@@ -11832,7 +12111,8 @@ def main() -> None:
                                      split_max_size=split_str_to_n_bytes(args.split_max_size), dry_run=args.dry_run,
                                      small_first_shard=args.no_tensor_first_split,
                                      remote_hf_model_id=hf_repo_id, disable_mistral_community_chat_template=disable_mistral_community_chat_template,
-                                     sentence_transformers_dense_modules=args.sentence_transformers_dense_modules
+                                     sentence_transformers_dense_modules=args.sentence_transformers_dense_modules,
+                                     fuse_gate_up_exps=args.fuse_gate_up_exps
                                      )
 
         if args.vocab_only:

convert_hf_to_gguf_update.py

@@ -99,6 +99,7 @@ models = [
     {"name": "stablelm2",        "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/stabilityai/stablelm-2-zephyr-1_6b", },
     {"name": "refact",           "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/smallcloudai/Refact-1_6-base", },
     {"name": "command-r",        "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/CohereForAI/c4ai-command-r-v01", },
+    {"name": "tiny_aya",         "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/CohereLabs/tiny-aya-base", },
     {"name": "qwen2",            "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Qwen/Qwen1.5-7B", },
     {"name": "olmo",             "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/allenai/OLMo-1.7-7B-hf", },
     {"name": "dbrx",             "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/databricks/dbrx-base", },
@@ -106,6 +107,7 @@ models = [
     {"name": "jina-v2-en",       "tokt": TOKENIZER_TYPE.WPM, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-en", }, # WPM!
     {"name": "jina-v2-es",       "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-es", },
     {"name": "jina-v2-de",       "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-de", },
+    {"name": "jina-v5-nano",     "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v5-text-nano", },
     {"name": "smaug-bpe",        "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/abacusai/Smaug-Llama-3-70B-Instruct", },
     {"name": "poro-chat",        "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LumiOpen/Poro-34B-chat", },
     {"name": "jina-v2-code",     "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jinaai/jina-embeddings-v2-base-code", },
@@ -113,6 +115,7 @@ models = [
     {"name": "gemma",            "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/google/gemma-2b", },
     {"name": "gemma-2",          "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/google/gemma-2-9b", },
     {"name": "jais",             "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/core42/jais-13b", },
+    {"name": "jais-2",           "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/inceptionai/Jais-2-8B-Chat", },
     {"name": "t5",               "tokt": TOKENIZER_TYPE.UGM, "repo": "https://huggingface.co/google-t5/t5-small", },
     {"name": "codeshell",        "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/WisdomShell/CodeShell-7B", },
     {"name": "tekken",           "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/mistralai/Mistral-Nemo-Base-2407", },
@@ -148,7 +151,9 @@ models = [
     {"name": "youtu",            "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/tencent/Youtu-LLM-2B", },
     {"name": "solar-open",       "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/upstage/Solar-Open-100B", },
     {"name": "exaone-moe",       "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/LGAI-EXAONE/K-EXAONE-236B-A23B", },
-    {"name": "qwen35",           "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Qwen/Qwen3.5-9B-Instruct", }
+    {"name": "qwen35",           "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/Qwen/Qwen3.5-9B-Instruct", },
+    {"name": "joyai-llm",        "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/jdopensource/JoyAI-LLM-Flash", },
+    {"name": "kanana2",          "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/kakaocorp/kanana-2-30b-a3b-instruct-2601", },
 ]
 
 # some models are known to be broken upstream, so we will skip them as exceptions
@@ -158,6 +163,7 @@ pre_computed_hashes = [
     {"name": "chatglm-bpe", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/THUDM/glm-4-9b-chat", "chkhsh": "81d72c7348a9f0ebe86f23298d37debe0a5e71149e29bd283904c02262b27516"},
     {"name": "glm4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/THUDM/glm-4-9b-hf", "chkhsh": "a1336059768a55c99a734006ffb02203cd450fed003e9a71886c88acf24fdbc2"},
     {"name": "glm4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/zai-org/GLM-4.5-Air", "chkhsh": "9ca2dd618e8afaf09731a7cf6e2105b373ba6a1821559f258b272fe83e6eb902"},
+    {"name": "glm4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/zai-org/GLM-4.7-Flash", "chkhsh": "cdf5f35325780597efd76153d4d1c16778f766173908894c04afc20108536267"},
     {"name": "minerva-7b", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/sapienzanlp/Minerva-7B-base-v1.0", "chkhsh": "1431a23e583c97432bc230bff598d103ddb5a1f89960c8f1d1051aaa944d0b35"},
     {"name": "hunyuan", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/tencent/Hunyuan-A13B-Instruct", "chkhsh": "7e57df22b1fe23a7b1e1c7f3dc4e3f96d43a4eb0836d0c6bdc3436d7b2f1c664"},
     {"name": "hunyuan-dense", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/tencent/Hunyuan-4B-Instruct", "chkhsh": "bba3b3366b646dbdded5dbc42d59598b849371afc42f7beafa914afaa5b70aa6"},
@@ -171,7 +177,6 @@ pre_computed_hashes = [
     {"name": "grok-2",    "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/alvarobartt/grok-2-tokenizer", "chkhsh": "66b8d4e19ab16c3bfd89bce5d785fb7e0155e8648708a1f42077cb9fe002c273"},
     # jina-v2-de variants
     {"name": "jina-v2-de", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/aari1995/German_Semantic_V3", "chkhsh": "b3d1dd861f1d4c5c0d2569ce36baf3f90fe8a102db3de50dd71ff860d91be3df"},
-    {"name": "glm4", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/zai-org/GLM-4.7-Flash", "chkhsh": "cdf5f35325780597efd76153d4d1c16778f766173908894c04afc20108536267"},
 ]
 
 

docs/autoparser.md

@@ -0,0 +1,525 @@
+# Auto-Parser Architecture
+
+The auto-parser automatically analyzes chat templates to determine how to parse model outputs, including content, reasoning, and tool calls.
+
+## Overview
+
+The unified auto-parser uses a pure differential, compositional approach (inspired by the `git diff` algorithm) to analyze chat templates:
+
+**Core Philosophy**:
+
+- **Minimize Hardcoded Patterns**: All markers extracted through template comparison (the only heuristic is JSON detection to distinguish `JSON_NATIVE` from tag-based formats)
+- **Compositional Architecture**: Separate analyzer structs for reasoning, content, and tools — each responsible for its own analysis and parser construction
+
+**Analysis + Parser Building in Two Steps**:
+
+1. `autoparser::autoparser tmpl_analysis(tmpl)` — runs all differential comparisons and populates the analysis structs
+2. `autoparser::peg_generator::generate_parser(tmpl, params, tmpl_analysis)` — uses the analysis to build a PEG parser and optional GBNF grammar
+
+## Data Structures
+
+All structs are defined in [common/chat-auto-parser.h](common/chat-auto-parser.h).
+
+### Top-Level: `autoparser` (main analyzer and generator)
+
+[common/chat-auto-parser.h:367-388](common/chat-auto-parser.h#L367-L388) — top-level analysis result aggregating `jinja_caps`, `reasoning`, `content`, and `tools` sub-analyses, plus `preserved_tokens` (union of all non-empty markers).
+
+### `analyze_reasoning`
+
+[common/chat-auto-parser.h:254-274](common/chat-auto-parser.h#L254-L274) — reasoning analysis result: `mode` enum, `start` marker (e.g. `<think>`), and `end` marker (e.g. `</think>`).
+
+### `analyze_content`
+
+[common/chat-auto-parser.h:280-295](common/chat-auto-parser.h#L280-L295) — content analysis result: `mode` enum, `start`/`end` markers, and `requires_nonnull_content` flag.
+
+### `analyze_tools` and its sub-structs
+
+- [common/chat-auto-parser.h:176-194](common/chat-auto-parser.h#L176-L194) — `tool_format_analysis`: `mode` enum, `section_start/end`, `per_call_start/end`, JSON field names (`function_field`, `name_field`, `args_field`, `id_field`, `gen_id_field`), and format flags (`fun_name_is_key`, `tools_array_wrapped`, `uses_python_dicts`)
+- [common/chat-auto-parser.h:196-200](common/chat-auto-parser.h#L196-L200) — `tool_function_analysis`: `name_prefix`, `name_suffix`, `close` markers around function names
+- [common/chat-auto-parser.h:202-210](common/chat-auto-parser.h#L202-L210) — `tool_arguments_analysis`: `start/end` container markers, `name_prefix/suffix`, `value_prefix/suffix`, `separator`
+- [common/chat-auto-parser.h:212-217](common/chat-auto-parser.h#L212-L217) — `tool_id_analysis`: `pos` enum, `prefix`/`suffix` markers around call ID values
+- [common/chat-auto-parser.h:301-361](common/chat-auto-parser.h#L301-L361) — `analyze_tools`: aggregates the four sub-structs above
+
+### Enums
+
+**`reasoning_mode`**: How the template handles reasoning/thinking blocks.
+
+| Value           | Description                                                                       |
+|-----------------|-----------------------------------------------------------------------------------|
+| `NONE`          | No reasoning markers detected                                                     |
+| `TAG_BASED`     | Standard tag-based: `<think>...</think>`                                          |
+| `DELIMITER`     | Delimiter-based: reasoning ends at a delimiter (e.g., `[BEGIN FINAL RESPONSE]`)   |
+| `FORCED_OPEN`   | Template ends with open reasoning tag when `enable_thinking=true`                 |
+| `FORCED_CLOSED` | `enable_thinking=false` emits both tags; `enable_thinking=true` emits only start  |
+| `TOOLS_ONLY`    | Reasoning only appears in tool call responses, not plain content                  |
+
+**`content_mode`**: How the template wraps assistant content.
+
+| Value                    | Description                                                    |
+|--------------------------|----------------------------------------------------------------|
+| `PLAIN`                  | No content markers                                             |
+| `ALWAYS_WRAPPED`         | Content always wrapped: `<response>...</response>`             |
+| `WRAPPED_WITH_REASONING` | Content wrapped only when reasoning is present                 |
+
+**`tool_format`**: Classification of tool call structure.
+
+| Value            | Description                                                      |
+|------------------|------------------------------------------------------------------|
+| `NONE`           | No tool support detected                                         |
+| `JSON_NATIVE`    | Pure JSON: `{"name": "X", "arguments": {...}}`                   |
+| `TAG_WITH_JSON`  | Tag-based with JSON args: `<function=X>{...}</function>`         |
+| `TAG_WITH_TAGGED`| Tag-based with tagged args: `<param=key>value</param>`           |
+
+**`call_id_position`**: Where call IDs appear in tag-based formats.
+
+| Value                    | Description                                  |
+|--------------------------|----------------------------------------------|
+| `NONE`                   | No call ID support detected                  |
+| `PRE_FUNC_NAME`          | Before function name                         |
+| `BETWEEN_FUNC_AND_ARGS`  | Between function name and arguments          |
+| `POST_ARGS`              | After arguments                              |
+
+## Tool Calling Formats
+
+### JSON_NATIVE
+
+**Structure**: The entire tool call (function name, arguments, values) is in JSON format. Optional enclosing tags around the section.
+
+**Detection**: Function name appears inside a JSON structure (quotes preceded by `{` or `:`).
+
+**Examples**:
+
+Standard OpenAI-style:
+
+```json
+<tool_call>
+{"name": "get_weather", "arguments": {"location": "Paris", "unit": "celsius"}}
+</tool_call>
+```
+
+Mistral Nemo with array wrapper:
+
+```json
+[TOOL_CALLS]
+[{"name": "calculate", "arguments": {"expr": "2+2"}}]
+```
+
+Function name as JSON key (Apertus style):
+
+```json
+{"get_weather": {"location": "Paris"}}
+```
+
+---
+
+### TAG_WITH_JSON
+
+**Structure**: Function name is outside JSON, in tag attributes or XML-style tags. Arguments are a JSON object.
+
+**Detection**: Function name not in JSON, but argument names appear in JSON context.
+
+**Examples**:
+
+Functionary v3.1:
+
+```xml
+<function=get_weather>{"location": "Paris", "unit": "celsius"}</function>
+```
+
+MiniMax:
+
+```xml
+<minimax:tool_call>
+<tool_name>calculate</tool_name>
+<arguments>{"expr": "2+2"}</arguments>
+</minimax:tool_call>
+```
+
+---
+
+### TAG_WITH_TAGGED
+
+**Structure**: Both function name and argument names are in XML-style tags. String values are unquoted; non-string values are JSON-formatted.
+
+**Detection**: Neither function name nor argument names appear in a JSON context.
+
+**Examples**:
+
+Qwen/Hermes XML format:
+
+```xml
+<function=get_weather>
+<param=location>Paris</param>
+<param=unit>celsius</param>
+</function>
+```
+
+Mixed types:
+
+```xml
+<function=calculate>
+<param=expr>2+2</param>
+<param=precision>2</param>
+<param=options>{"round": true}</param>
+</function>
+```
+
+String values (`Paris`, `celsius`, `2+2`) are unquoted; `options` (object type) is JSON-formatted.
+
+---
+
+## Analysis Flow
+
+```text
+autoparser::autoparser(tmpl)
+    |
+    |-- Phase 1: analyze_reasoning(tmpl, jinja_caps.supports_tool_calls)
+    |     |-- R1: compare_reasoning_presence()   — with/without reasoning_content field
+    |     |-- R2: compare_thinking_enabled()     — enable_thinking=false vs true
+    |     '-- R3: compare_reasoning_scope()      — reasoning+content vs reasoning+tools
+    |           (only if supports_tool_calls)
+    |
+    |-- Phase 2: analyze_content(tmpl, reasoning)
+    |     '-- C1: compares content-only vs tools output and content-only vs reasoning output
+    |
+    |-- Phase 3: analyze_tools(tmpl, jinja_caps, reasoning)
+    |     (skipped entirely if !jinja_caps.supports_tool_calls)
+    |     |
+    |     |-- T1: analyze_tool_calls()           — no tools vs with tools; classifies format
+    |     |         |-- JSON path → analyze_tool_call_format_json_native()
+    |     |         '-- tag path → analyze_tool_call_format_non_json()
+    |     |
+    |     (if format != NONE and format != JSON_NATIVE:)
+    |     |
+    |     |-- T2: check_per_call_markers()       — 1 call vs 2 calls; moves section→per-call if needed
+    |     |         (only if supports_parallel_tool_calls)
+    |     |
+    |     |-- T3: extract_function_markers()     — func_alpha vs func_beta; extracts name prefix/suffix/close
+    |     |
+    |     |-- T4: analyze_arguments()            — (TAG_WITH_TAGGED only)
+    |     |         |-- A1: extract_argument_name_markers()   — arg_name_A vs arg_name_B
+    |     |         '-- A2: extract_argument_value_markers()  — value "XXXX" vs "YYYY"
+    |     |
+    |     |-- T5: extract_argument_separator()   — 1 arg vs 2 args; finds separator between args
+    |     |
+    |     |-- T6: extract_args_markers()         — 0 args vs 1 arg; finds args container markers
+    |     |
+    |     '-- T7: extract_call_id_markers()      — call_id "call00001" vs "call99999"
+    |
+    '-- collect_preserved_tokens()               — union of all non-empty markers
+    |
+    '-- apply workarounds()                      — post-hoc patches for edge-case templates
+    |
+    v
+autoparser (analysis result)
+    |
+    v
+autoparser::peg_generator::generate_parser(tmpl, inputs, analysis)
+    |-- analysis.build_parser(inputs)            — builds PEG parser arena
+    |     |-- reasoning.build_parser(ctx)        — reasoning parser (mode-dependent)
+    |     |-- content.build_parser(ctx)          — content parser (mode-dependent)
+    |     '-- tools.build_parser(ctx)            — tool parser (dispatches by tool_format)
+    |           |-- build_tool_parser_json_native()
+    |           |-- build_tool_parser_tag_json()
+    |           '-- build_tool_parser_tag_tagged()
+    |
+    |-- Build GBNF grammar (if tools present and trigger_marker non-empty)
+    '-- Set grammar_triggers from section_start or per_call_start
+    |
+    v
+common_chat_params (prompt, parser, grammar, triggers, preserved_tokens)
+```
+
+## Entry Point
+
+The auto-parser is invoked in [common/chat.cpp:1280-1310](common/chat.cpp#L1280-L1310) in `common_chat_templates_apply_jinja`. A few specialized templates are handled first (Ministral/Magistral Large 3, GPT-OSS with `<|channel|>`, Functionary v3.2 with `>>>all`), then the auto-parser handles everything else via `autoparser::autoparser` + `peg_generator::generate_parser`.
+
+## Algorithm Details
+
+### Core Mechanism: Differential Comparison
+
+All analysis phases use the same factorized comparison function declared in [common/chat-auto-parser-helpers.h:68](common/chat-auto-parser-helpers.h#L68):
+
+```cpp
+compare_variants(tmpl, params_A, params_modifier)
+```
+
+This creates variant B by applying a modifier lambda to a copy of `params_A`, renders both through the template, and computes a `diff_split` ([common/chat-auto-parser.h:28-37](common/chat-auto-parser.h#L28-L37)):
+
+- `prefix` — common prefix between A and B
+- `suffix` — common suffix between A and B
+- `left` — unique to variant A
+- `right` — unique to variant B
+
+The diff is computed via `calculate_diff_split()`, which finds the longest-common-prefix and longest-common-suffix, then iteratively moves incomplete `<...>` or `[...]` markers from the prefix/suffix into left/right until stable (tag boundary fixing).
+
+Text is segmentized into markers and non-marker fragments using `segmentize_markers()`, which splits on `<...>` and `[...]` boundaries.
+
+### Phase 1: Reasoning Analysis
+
+**R1 — `compare_reasoning_presence()`**: Compares assistant message with vs without a `reasoning_content` field.
+
+- Searches `diff.right` (output with reasoning) for the reasoning content needle
+- Uses PEG parsers to find surrounding markers:
+  - If both pre/post markers found in `diff.right` → `TAG_BASED` (both tags visible in diff = no forced close)
+  - If both found but post marker only in the full output B → `FORCED_CLOSED`
+  - If only post marker found → `DELIMITER`
+- Sets `reasoning.start` and `reasoning.end`
+
+**R2 — `compare_thinking_enabled()`**: Compares `enable_thinking=false` vs `true` with a generation prompt.
+
+- Detects `FORCED_OPEN`: `enable_thinking=true` adds a non-empty marker at the end of the prompt (where model will start generating) — sets `reasoning.start`, mode = `FORCED_OPEN`
+- Detects `FORCED_CLOSED`: `enable_thinking=false` produces both start+end markers; `enable_thinking=true` produces only start marker
+- Handles the reverse case: if both start and end are still empty, looks for a single-segment diff on each side to extract both markers
+
+**R3 — `compare_reasoning_scope()`**: Compares assistant message with reasoning+text-content vs reasoning+tool-calls.
+
+- Only runs if `jinja_caps.supports_tool_calls`
+- Detects `TOOLS_ONLY`: reasoning content present in B (with tools) but not in A (with text content)
+- Extracts reasoning markers from the tool call output using PEG parsers
+
+### Phase 2: Content Analysis
+
+**C1**: Two comparisons in the `analyze_content` constructor:
+
+- Comparison 1: content-only output vs tool-call output → `diff_tools`
+- Comparison 2: content-only output vs reasoning+empty-content output → `diff_reasoning`
+
+Classification logic:
+
+- `PLAIN`: `diff_tools.left` equals the response string (content is the entire diff, no wrapper)
+- `ALWAYS_WRAPPED`: markers found surrounding the content text in `pure_content` → extracts `start`/`end`
+
+### Phase 3: Tool Call Analysis
+
+**T1 — `analyze_tool_calls()`**: Compares no-tools vs with-tools output.
+
+- Extracts the tool call section as `diff.right`
+- Calls `analyze_tool_call_format()` which first strips reasoning markers from the haystack, then:
+  - Calls `in_json_haystack()` for both function name and argument name needles
+  - `in_json_haystack()` uses a PEG parser to check whether the needle appears in a JSON context (preceded by `{` or `:` with surrounding quotes)
+  - If function name is in JSON → `JSON_NATIVE` → `analyze_tool_call_format_json_native()`
+  - If function name not in JSON, arg name is in JSON → `TAG_WITH_JSON`
+  - If neither in JSON → `TAG_WITH_TAGGED`
+  - `analyze_tool_call_format_json_native()`: parses the JSON object, matches field values to needles to populate `name_field`, `args_field`, `id_field`, `gen_id_field`; detects `tools_array_wrapped`; extracts `section_start`/`section_end`
+  - `analyze_tool_call_format_non_json()`: uses PEG parsers on the haystack to find up to two opening markers (section + per-call) then up to two closing markers
+
+**T2 — `check_per_call_markers()`**: Compares 1 call vs 2 calls.
+
+- Computes a secondary diff of the second call portion vs the common suffix
+- If the second call content starts with `section_start` → the section marker is actually per-call → moves `section_start/end` to `per_call_start/end` and clears the section markers
+
+**T3 — `extract_function_markers()`**: Compares function name `FUN_FIRST` vs `FUN_SECOND` (two different named functions).
+
+- Finds where the function name appears in `diff.left`
+- Extracts `function.name_prefix` from the common prefix up to the function marker, and `function.name_suffix` from after the name up to the next marker
+- Extends `name_suffix` into `diff.suffix` (to the first marker for TAG_WITH_TAGGED; to the first `{` or `[` for TAG_WITH_JSON)
+- Extracts `function.close` from after the last argument value up to the per-call/section end marker
+
+**T4 — `analyze_arguments()`** (TAG_WITH_TAGGED only):
+
+- **A1 `extract_argument_name_markers()`**: Compares `arg_name_A` vs `arg_name_B` (two different argument names).
+  - Finds shared surrounding structure → `arguments.name_prefix`, `arguments.name_suffix`
+- **A2 `extract_argument_value_markers()`**: Compares argument value `"XXXX"` vs `"YYYY"` (same arg, different value).
+  - Finds markers surrounding the value → `arguments.value_prefix`, `arguments.value_suffix`
+
+**T5 — `extract_argument_separator()`**: Compares 1 argument vs 2 arguments (same function).
+
+- Uses `until_common_prefix(diff.right, ARG_FIRST, ARG_SECOND)` to find what separates the two argument blocks
+
+**T6 — `extract_args_markers()`**: Compares 0 arguments vs 1 argument.
+
+- Uses `until_common_prefix()` and `after_common_suffix()` with the empty and single-arg JSON strings as anchors to find container markers (`arguments.start`, `arguments.end`)
+
+**T7 — `extract_call_id_markers()`**: Compares call IDs `"call00001"` vs `"call99999"`.
+
+- Determines whether function name appears in `diff.prefix` or `diff.suffix` to classify position:
+  - Function name in prefix only → `BETWEEN_FUNC_AND_ARGS` or `POST_ARGS` (further distinguished by where `{` appears)
+  - Function name in suffix only → `PRE_FUNC_NAME`
+- Extracts `call_id.prefix` and `call_id.suffix` markers around the call ID value
+- Clears `per_call_end` if it incorrectly incorporated the call ID suffix
+
+### Workarounds
+
+A workaround array in `common/chat-diff-analyzer.cpp` applies post-hoc patches after analysis. Each workaround is a lambda that inspects the template source and overrides analysis results. Current workarounds:
+
+1. **Old Qwen/DeepSeek thinking templates** — source contains `content.split('</think>')`: sets `reasoning.mode = FORCED_OPEN` with `<think>`/`</think>` markers if no reasoning was detected
+2. **Granite 3.3** — source contains specific "Write your thoughts" text: forces `TAG_BASED` reasoning with `<think>`/`</think>` and `WRAPPED_WITH_REASONING` content with `<response>`/`</response>`
+3. **Cohere Command R+** — source contains `<|CHATBOT_TOKEN|>`: sets `ALWAYS_WRAPPED` content mode if no content start is already set
+4. **Functionary 3.1** — source contains `set has_code_interpreter`: forces `PLAIN` content, specific `per_call_start/end`, clears preserved tokens to only keep Functionary-specific markers
+5. **DeepSeek-R1-Distill-Qwen** — source contains `tool▁calls▁begin` markers: overrides tool section/per-call markers with the correct Unicode block characters
+
+### Parser Building
+
+Each analyzer struct (`analyze_reasoning`, `analyze_content`, `analyze_tools`) implements `build_parser(parser_build_context&)`. They share a `parser_build_context` that carries the PEG builder, inference inputs, the pre-built reasoning parser, and a pointer to the content analyzer.
+
+#### Reasoning Parser (`analyze_reasoning::build_parser`)
+
+| Mode                              | Parser                                                              |
+|-----------------------------------|---------------------------------------------------------------------|
+| Not extracting reasoning          | `eps()`                                                             |
+| `FORCED_OPEN` or `FORCED_CLOSED`  | `reasoning(until(end)) + end` — opening tag was in the prompt       |
+| `TAG_BASED` or `TOOLS_ONLY`       | `optional(start + reasoning(until(end)) + end)`                     |
+| `DELIMITER`                       | `optional(reasoning(until(end)) + end)` — no start marker           |
+
+#### Content Parser (`analyze_content::build_parser`)
+
+| Condition                              | Parser                                                                          |
+|----------------------------------------|---------------------------------------------------------------------------------|
+| `json_schema` present                  | `reasoning + space() + content(schema(json(), "response-format", ...)) + end()` |
+| Tools present                          | Dispatches to `analyze_tools::build_parser()`                                   |
+| `ALWAYS_WRAPPED` with reasoning        | `reasoning + start + content(until(end)) + end + end()`                         |
+| `ALWAYS_WRAPPED` without reasoning     | `content(until(start)) + start + content(until(end)) + end + end()`             |
+| Default (PLAIN)                        | `reasoning + content(rest()) + end()`                                           |
+
+#### Tool Parsers (`analyze_tools::build_parser`)
+
+Dispatches by `format.mode`:
+
+**`build_tool_parser_json_native()`**: Calls `p.standard_json_tools()` which internally dispatches to:
+
+- `build_json_tools_function_is_key()` — function name is the JSON key: `{"get_weather": {...}}`
+- `build_json_tools_nested_keys()` — nested: `{"function": {"name": "X", "arguments": {...}}}`
+- `build_json_tools_flat_keys()` — flat: `{"name": "X", "arguments": {...}}`
+
+Handles content wrappers, array wrapping (`tools_array_wrapped`), parallel calls, and `parameter_order`.
+
+**`build_tool_parser_tag_json()`**: For each tool function:
+
+```text
+tool_open(name_prefix + tool_name(literal(name)) + name_suffix) +
+    call_id_section +
+    tool_args(schema(json(), tool_schema))
+  [+ function.close if non-empty]
+```
+
+Wrapped in per-call markers (with optional parallel call repetition) then optionally in section markers.
+
+**`build_tool_parser_tag_tagged()`**: For each tool function, builds one parser per argument:
+
+- String types: `tool_arg_string_value(schema(until(value_suffix), ...))`
+- JSON types: `tool_arg_json_value(schema(json(), ...))`
+- Required args are plain; optional args wrapped in `optional()`
+- Arguments joined with `space()` between consecutive parsers
+
+For closing: uses `function.close` if present; otherwise uses `peek(per_call_end)` to avoid premature close during partial streaming; falls back to `tool_close(space())` to trigger mapper callbacks.
+
+All three tool parsers return:
+
+```text
+reasoning + optional(content(until(trigger_marker))) + tool_calls + end()
+```
+
+### Python Dict Format
+
+When `format.uses_python_dicts` is true (detected when single-quoted strings appear in JSON argument context), `build_parser()` pre-registers a `json-string` rule that accepts both single-quoted and double-quoted strings. This is done before any `p.json()` call so all JSON parsing inherits the flexible rule.
+
+## Mapper
+
+`common_chat_peg_mapper` maps PEG parse results (AST nodes) into `common_chat_msg` structures. Key design:
+
+- **Buffered arguments**: Before `tool_name` is known, argument text goes to `args_buffer`; once the name is set, the buffer is flushed to `current_tool->arguments`
+- **`args_target()`**: Returns a reference to whichever destination is currently active (buffer or tool args), eliminating branching
+- **`closing_quote_pending`**: Tracks whether a closing `"` needs to be appended when a string argument value is finalized (for schema-declared string types in tagged format)
+- **Quote normalization**: Python-style quotes (`'key': 'value'`) are converted to JSON (`"key": "value"`)
+- **Brace auto-closing**: At tool close, unclosed `{` braces are closed automatically
+
+## Files
+
+| File                                      | Purpose                                                              |
+|-------------------------------------------|----------------------------------------------------------------------|
+| `common/chat-auto-parser.h`               | All analysis structs, enums, `autoparser`, `peg_generator`, `templates_params` |
+| `common/chat-auto-parser-generator.cpp`   | Parser generator: `generate_parser()` and `build_parser()` methods   |
+| `common/chat-diff-analyzer.cpp`           | Differential analysis implementation and workarounds                 |
+| `common/chat-auto-parser-helpers.h/cpp`   | `calculate_diff_split()`, `segmentize_markers()`,                    |
+|                                           | `compare_variants()`, string helpers                                 |
+| `common/chat-peg-parser.h/cpp`            | `common_chat_peg_builder`, `common_chat_peg_mapper`, and helpers     |
+| `common/chat.cpp`                         | Entry point: `common_chat_templates_apply_jinja()`                   |
+| `tools/parser/debug-template-parser.cpp`  | Debug tool for template analysis                                     |
+| `tools/parser/template-analysis.cpp`      | Template analysis tool                                               |
+
+## Testing & Debugging
+
+### Debug Tools
+
+**Template Debugger**: `tools/parser/debug-template-parser.cpp`
+
+- Usage: `./bin/llama-debug-template-parser path/to/template.jinja`
+- Shows detected format, markers, generated parser, and GBNF grammar
+
+**Template Analysis**: `tools/parser/template-analysis.cpp`
+
+- Usage: `./bin/llama-template-analysis path/to/template.jinja`
+
+**Debug Logging**: Enable with `LLAMA_LOG_VERBOSITY=2`
+
+- Shows detailed analysis steps, pattern extraction results, and generated parser structure
+
+**PEG Test Builder**: Fluent API for creating test cases — see [tests/test-chat.cpp:947-1043](tests/test-chat.cpp#L947-L1043). Example usage:
+
+```cpp
+auto tst = peg_tester("models/templates/Template.jinja");
+tst.test("input text")
+   .reasoning_format(COMMON_REASONING_FORMAT_AUTO)
+   .tools({tool_json})
+   .parallel_tool_calls(true)
+   .enable_thinking(true)
+   .expect(expected_message)
+   .run();
+```
+
+### Tested Templates
+
+The following templates have active tests in `tests/test-chat.cpp`:
+
+| Template | Format | Notes |
+| -------- | ------ | ----- |
+| Ministral-3-14B-Reasoning | Reasoning | `[THINK]...[/THINK]` tags (specialized handler) |
+| NVIDIA-Nemotron-3-Nano-30B | TAG_WITH_TAGGED | Reasoning + tools |
+| CohereForAI Command-R7B | JSON_NATIVE | `<\|START_THINKING\|>`/`<\|START_RESPONSE\|>` markers |
+| Google Gemma 2 2B | Content only | No tool support |
+| Qwen-QwQ-32B | Reasoning | Forced-open thinking |
+| NousResearch Hermes 2 Pro | JSON_NATIVE | `<tool_call>` wrapper |
+| IBM Granite 3.3 | JSON_NATIVE | `<think></think>` + `<response></response>` |
+| ByteDance Seed-OSS | TAG_WITH_TAGGED | Custom `<seed:think>` and `<seed:tool_call>` tags |
+| Qwen3-Coder | TAG_WITH_TAGGED | XML-style tool format |
+| DeepSeek V3.1 | JSON_NATIVE | Forced thinking mode |
+| GLM-4.6 | TAG_WITH_TAGGED | `<tool_call>name\n<arg_key>...<arg_value>...` format |
+| GLM-4.7-Flash | TAG_WITH_TAGGED | Updated GLM format |
+| Kimi-K2-Thinking | JSON_NATIVE | Reasoning + JSON tools |
+| Apertus-8B-Instruct | JSON_NATIVE | Function name as JSON key |
+| MiniMax-M2 | TAG_WITH_JSON | XML invoke with JSON args |
+| NVIDIA-Nemotron-Nano-v2 | JSON_NATIVE | `<TOOLCALL>` wrapper (nested) |
+| CohereForAI Command-R Plus | JSON_NATIVE | Markdown code block format |
+| Mistral-Nemo-Instruct-2407 | JSON_NATIVE | `[TOOL_CALLS]` wrapper with ID field |
+| Functionary v3.1 | TAG_WITH_JSON | `<function=X>` format |
+| Functionary v3.2 | Specialized | `>>>` recipient delimiter (dedicated handler) |
+| Fireworks Firefunction v2 | TAG_WITH_JSON | Fireworks tool format |
+| DeepSeek R1 Distill (Llama/Qwen) | Reasoning | Forced-open thinking |
+| llama-cpp-deepseek-r1 | Reasoning | Forced-open thinking |
+| Kimi-K2 / Kimi-K2-Instruct | JSON_NATIVE | JSON tools with special markers |
+| Llama 3.1/3.2/3.3 | JSON_NATIVE | Standard Llama tool format |
+| OpenAI GPT-OSS | Specialized | Channel-based (dedicated handler) |
+| Apriel 1.5 | JSON_NATIVE | `<tool_calls>` wrapper with JSON array |
+| Apriel 1.6 Thinker | Reasoning | Implicit reasoning start |
+| Mistral Small 3.2 | JSON_NATIVE | `[TOOL_CALLS]func[ARGS]{...}` with call ID |
+| Devstral | JSON_NATIVE | `[TOOL_CALLS]func[ARGS]{...}` without call ID |
+| StepFun 3.5 Flash | TAG_WITH_TAGGED | `<function=X><parameter=Y>` format |
+
+## Adding Support for New Templates
+
+To support a new template format:
+
+1. **If it follows standard patterns** — The auto-parser should detect it automatically. Run `llama-debug-template-parser` to verify markers are correctly extracted.
+2. **If differential analysis extracts incorrect markers** — Add a workaround lambda to the `workarounds` vector in `common/chat-diff-analyzer.cpp`. Inspect the template source for a unique identifying substring.
+3. **If it needs fundamentally different handling** — Add a dedicated handler function in `chat.cpp` before the auto-parser block (as done for GPT-OSS, Functionary v3.2, and Ministral).
+
+## Edge Cases and Quirks
+
+1. **Forced Thinking**: When `enable_thinking=true` and the model prompt ends with an open reasoning tag (e.g., `<think>`), the parser enters forced thinking mode and immediately expects reasoning content without waiting for a start marker.
+2. **Per-Call vs Per-Section Markers**: Some templates wrap each tool call individually (`per_call_start/end`); others wrap the entire section (`section_start/end`). T2 (`check_per_call_markers()`) disambiguates by checking if the second call in a two-call output starts with the section marker.
+3. **Python Dict Format**: The Seed template family uses single-quoted JSON (`'key': 'value'`). The `uses_python_dicts` flag causes the PEG builder to register a flexible `json-string` rule accepting both quote styles before any JSON rules are built.
+4. **Tag Boundary Fixing**: `calculate_diff_split()` iteratively adjusts prefix/suffix boundaries to avoid splitting `<tag>` or `[marker]` tokens, ensuring clean extraction.
+5. **Call ID Side Effects**: When a call ID is detected, `per_call_end` may have been incorrectly set to include the call ID suffix. T7 clears `per_call_end` in this case.
+6. **Tool Analysis Gating**: `analyze_tools` is only constructed (and all tool analysis phases run) when `jinja_caps.supports_tool_calls` is true. Within tool analysis, `check_per_call_markers()` (T2) only runs if `jinja_caps.supports_parallel_tool_calls`.
+7. **`analyze_arguments()` Gating**: Within tool analysis, A1 and A2 (argument name/value marker extraction) only run for `TAG_WITH_TAGGED` format. `extract_argument_separator()` and `extract_args_markers()` run for all non-`JSON_NATIVE` formats.

docs/backend/CANN.md

@@ -20,7 +20,7 @@
 
 **Llama.cpp + CANN**
 
-The llama.cpp CANN backend is designed to support Ascend NPU. It utilize the ability of AscendC and ACLNN which are intergrated to CANN Toolkit and kernels to using Ascend NPU directly.
+The llama.cpp CANN backend is designed to support Ascend NPU. It utilize the ability of AscendC and ACLNN which are integrated to CANN Toolkit and kernels to using Ascend NPU directly.
 
 ## News
 
@@ -210,7 +210,7 @@ docker run --name llamacpp --device /dev/davinci0  --device /dev/davinci_manager
     # and install driver.
     sudo sh Ascend-hdk-910b-npu-firmware_x.x.x.x.X.run --full
     ```
-    If the following messaage appers, firmware is installed successfully.
+    If the following message appears, firmware is installed successfully.
     ```sh
     Firmware package installed successfully!
     ```
@@ -246,7 +246,7 @@ cmake --build build --config release
 
 1. **Retrieve and prepare model**
 
-    You can refer to the general [*Prepare and Quantize*](../../README.md#prepare-and-quantize) guide for model prepration.
+    You can refer to the general [*Obtaining and quantizing models*](../../README.md#obtaining-and-quantizing-models) guide for model prepration.
 
     **Notes**:
 

docs/backend/SYCL.md

@@ -9,6 +9,7 @@
 - [Linux](#linux)
 - [Windows](#windows)
 - [Environment Variable](#environment-variable)
+- [Design Rule](#design-rule)
 - [Known Issue](#known-issues)
 - [Q&A](#qa)
 - [TODO](#todo)
@@ -41,6 +42,9 @@ The following releases are verified and recommended:
 
 ## News
 
+- 2026.03
+  - Support Flash-Attention: less memory usage, performance impact depends on LLM.
+
 - 2026.02
   - Remove support for Nvidia & AMD GPU, because the oneAPI plugin for Nvidia & AMD GPU is unavailable: download/installation channels are out of work. User can't build up the software for Nvidia & AMD GPU.
 
@@ -281,7 +285,7 @@ as `-cl-fp32-correctly-rounded-divide-sqrt`
 
 #### Retrieve and prepare model
 
-You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model preparation, or download an already quantized model like [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/resolve/main/llama-2-7b.Q4_0.gguf?download=true) or [Meta-Llama-3-8B-Instruct-Q4_0.gguf](https://huggingface.co/aptha/Meta-Llama-3-8B-Instruct-Q4_0-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_0.gguf).
+You can refer to the general [*Obtaining and quantizing models*](../../README.md#obtaining-and-quantizing-models) guide for model preparation, or download an already quantized model like [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/resolve/main/llama-2-7b.Q4_0.gguf?download=true) or [Meta-Llama-3-8B-Instruct-Q4_0.gguf](https://huggingface.co/aptha/Meta-Llama-3-8B-Instruct-Q4_0-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_0.gguf).
 
 ##### Check device
 
@@ -569,7 +573,7 @@ Once it is completed, final results will be in **build/Release/bin**
 
 #### Retrieve and prepare model
 
-You can refer to the general [*Prepare and Quantize*](README.md#prepare-and-quantize) guide for model preparation, or download an already quantized model like [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) or [Meta-Llama-3-8B-Instruct-Q4_0.gguf](https://huggingface.co/aptha/Meta-Llama-3-8B-Instruct-Q4_0-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_0.gguf).
+You can refer to the general [*Obtaining and quantizing models*](../../README.md#obtaining-and-quantizing-models) guide for model preparation, or download an already quantized model like [llama-2-7b.Q4_0.gguf](https://huggingface.co/TheBloke/Llama-2-7B-GGUF/blob/main/llama-2-7b.Q4_0.gguf) or [Meta-Llama-3-8B-Instruct-Q4_0.gguf](https://huggingface.co/aptha/Meta-Llama-3-8B-Instruct-Q4_0-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_0.gguf).
 
 ##### Check device
 
@@ -685,18 +689,45 @@ use 1 SYCL GPUs: [0] with Max compute units:512
 | Name              | Value            | Function                                                                                                                  |
 |-------------------|------------------|---------------------------------------------------------------------------------------------------------------------------|
 | GGML_SYCL_DEBUG   | 0 (default) or 1 | Enable log function by macro: GGML_SYCL_DEBUG                                                                             |
+| GGML_SYCL_ENABLE_FLASH_ATTN | 1 (default) or 0| Enable Flash-Attention. It can reduce memory usage. The performance impact depends on the LLM.|
 | GGML_SYCL_DISABLE_OPT | 0 (default) or 1 | Disable optimize features for Intel GPUs. (Recommended to 1 for intel devices older than Gen 10) |
 | GGML_SYCL_DISABLE_GRAPH | 0 or 1 (default) | Disable running computations through SYCL Graphs feature. Disabled by default because SYCL Graph is still on development, no better performance. |
 | GGML_SYCL_DISABLE_DNN | 0 (default) or 1 | Disable running computations through oneDNN and always use oneMKL. |
 | ZES_ENABLE_SYSMAN | 0 (default) or 1 | Support to get free memory of GPU by sycl::aspect::ext_intel_free_memory.<br>Recommended to use when --split-mode = layer |
 | UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS | 0 (default) or 1 | Support malloc device memory more than 4GB.|
 
+## Design Rule
 
+- Open to all contributors.
+
+- All code change should be useful to user:
+    - Fix bug.
+    - Add new function.
+    - Improve the performance/usage.
+    - Make code be easy to maintain.
+    - ...
+
+- Don't accept the codes of following cases:
+    - Break legacy function.
+    - Reduce the performance of legacy case in default.
+    - Not completed work/the functionality cannot be demonstrated.
+
+- Encourage to use environment variable to control features to be opened/closed.
+    - User can evaluate the feature without rebuild the code.
+    - Recommend the best features to user by setting them be opened as default.
+
+- Design the code based on the published official releases of oneAPI packages: compiler, library, driver, OS kernel.
+
+- Developers need to maintain the code they submit.
 
 ## Known Issues
 
 - `Split-mode:[row]` is not supported.
 
+- Missed the AOT (Ahead-of-Time) in buiding.
+  - Good: build quickly, smaller size of binary file.
+  - Bad: The startup is slow (JIT) in first time, but subsequent performance is unaffected.
+
 ## Q&A
 
 - Error:  `error while loading shared libraries: libsycl.so: cannot open shared object file: No such file or directory`.
@@ -708,7 +739,7 @@ use 1 SYCL GPUs: [0] with Max compute units:512
 
   - Remove **build** folder or try a clean-build.
 
-- I can **not** see `[ext_oneapi_level_zero:gpu]` afer installing the GPU driver on Linux.
+- I can **not** see `[ext_oneapi_level_zero:gpu]` after installing the GPU driver on Linux.
 
   Please double-check with `sudo sycl-ls`.
 

docs/backend/VirtGPU.md

@@ -152,7 +152,9 @@ Commands and data are serialized using a custom binary protocol with:
 - **VM-specific**: Only works in virtual machines with virtio-gpu support
 - **Host dependency**: Requires properly configured host-side backend
 - **Latency**: Small overhead from VM escaping for each operation
-
+- **Shared-memory size**: with the `libkrun` hypervisor, the RAM + VRAM
+  addressable memory is limited to 64 GB. So the maximum GPU memory
+  will be `64GB - RAM`, regardless of the hardware VRAM size.
 
 * This work is pending upstream changes in the VirglRenderer
   project.

docs/backend/ZenDNN.md

@@ -22,7 +22,7 @@
 
 **Llama.cpp + ZenDNN**
 
-The llama.cpp ZenDNN backend leverages AMD's optimized matrix multiplication primitives to accelerate inference on AMD CPUs. It utilizes ZenDNN's **LowOHA (Low Overhead Hardware Accelerated)** MatMul operator for efficient GEMM operations with minimal execution overhead, built-in weight caching, and direct access to backend libraries (AOCL BLIS, LibXSMM, OneDNN).
+The llama.cpp ZenDNN backend leverages AMD's optimized matrix multiplication primitives to accelerate inference on AMD CPUs. It utilizes ZenDNN's **LowOHA (Low Overhead Hardware Accelerated)** MatMul operator for efficient GEMM operations with minimal execution overhead, built-in weight caching, and direct access to backend libraries (AOCL DLP, LibXSMM, OneDNN).
 
 For more information about ZenDNN, visit: https://www.amd.com/en/developer/zendnn.html
 
@@ -32,7 +32,7 @@ For more information about ZenDNN, visit: https://www.amd.com/en/developer/zendn
 |:-------:|:-------:|:----------------------------------------------:|
 | Linux   | Support | Ubuntu 20.04, 22.04, 24.04                     |
 
-For the latest list of supported operating systems, see the [ZenDNN Supported OS](https://github.com/amd/ZenDNN/blob/zendnnl/README.md#15-supported-os).
+For the latest list of supported operating systems, see the [ZenDNN Supported OS](https://github.com/amd/ZenDNN/blob/a18adf8c605fb5f5e52cefd7eda08a7b18febbaf/README.md#15-supported-os).
 
 ## Hardware
 
@@ -44,9 +44,9 @@ ZenDNN is optimized for AMD EPYC™ processors and AMD Ryzen™ processors based
 
 | CPU Family                    | Status  | Notes                              |
 |:-----------------------------:|:-------:|:----------------------------------:|
-| AMD EPYC™ 9005 Series (Turin)| Support | 5th Gen - Zen 5 architecture       |
-| AMD EPYC™ 9004 Series (Genoa)| Support | 4th Gen - Zen 4 architecture       |
-| AMD EPYC™ 7003 Series (Milan)| Support | 3rd Gen - Zen 3 architecture       |
+| AMD EPYC™ 9005 Series (Turin) | Support | 5th Gen - Zen 5 architecture       |
+| AMD EPYC™ 9004 Series (Genoa) | Support | 4th Gen - Zen 4 architecture       |
+| AMD EPYC™ 7003 Series (Milan) | Support | 3rd Gen - Zen 3 architecture       |
 | AMD Ryzen™ AI MAX (Strix Halo)| Support | High-performance mobile processors |
 
 *Notes:*
@@ -61,7 +61,7 @@ The ZenDNN backend currently accelerates **matrix multiplication (MUL_MAT)** ope
 
 | Operation    | Status  | Notes                                          |
 |:-------------|:-------:|:----------------------------------------------:|
-| MUL_MAT      |    ✓    | Accelerated via ZenDNN LowOHA MatMul           |
+| MUL_MAT      | Support | Accelerated via ZenDNN LowOHA MatMul           |
 
 *Note:* Since only MUL_MAT is accelerated, models will benefit most from ZenDNN when matrix multiplications dominate the computational workload (which is typical for transformer-based LLMs).
 
@@ -104,7 +104,6 @@ If you want to build ZenDNN yourself or use a specific version:
 # Clone ZenDNN repository
 git clone https://github.com/amd/ZenDNN.git
 cd ZenDNN
-git checkout zendnnl
 
 # Build and install (requires CMake >= 3.25)
 mkdir build && cd build
@@ -114,7 +113,7 @@ cmake --build . --target all
 
 Default installation path: `ZenDNN/build/install`
 
-**For detailed build instructions**, refer to the [ZenDNN README](https://github.com/amd/ZenDNN/blob/zendnnl/README.md).
+**For detailed build instructions**, refer to the [ZenDNN README](https://github.com/amd/ZenDNN/blob/a18adf8c605fb5f5e52cefd7eda08a7b18febbaf/README.md).
 
 **Step 2: Build llama.cpp with custom ZenDNN path**
 
@@ -146,8 +145,7 @@ Run llama.cpp server with ZenDNN acceleration:
 
 ```sh
 # Set optimal configuration
-export OMP_NUM_THREADS=64  # Adjust to your CPU core count
-export ZENDNNL_MATMUL_ALGO=2  # Blocked AOCL BLIS for best performance
+export ZENDNNL_MATMUL_ALGO=1    # Blocked AOCL DLP algo for best performance
 
 # Start server
 ./build/bin/llama-server \
@@ -160,62 +158,26 @@ export ZENDNNL_MATMUL_ALGO=2  # Blocked AOCL BLIS for best performance
 Access the server at `http://localhost:8080`.
 
 **Performance tips**:
-- Set `OMP_NUM_THREADS` to match your physical core count
-- Use `ZENDNNL_MATMUL_ALGO=2` for optimal performance
+- Use `ZENDNNL_MATMUL_ALGO=1` for optimal performance
 - For NUMA systems: `numactl --cpunodebind=0 --membind=0 ./build/bin/llama-server ...`
 
 ## Environment Variable
 
-### Build Time
+For environment variables related to ZenDNN, refer to the [ZenDNN Environment Variables Documentation](https://github.com/amd/ZenDNN/blob/a18adf8c605fb5f5e52cefd7eda08a7b18febbaf/docs/runtime_env.md).
 
-| Name               | Value                                 | Function                                    |
-|--------------------|---------------------------------------|---------------------------------------------|
-| GGML_ZENDNN        | ON/OFF                                | Enable ZenDNN backend support               |
-| ZENDNN_ROOT        | Path to ZenDNN installation           | Set ZenDNN installation directory           |
-| GGML_OPENMP        | ON/OFF (recommended: ON)              | Enable OpenMP for multi-threading           |
+### Performance Optimization
 
-### Runtime
-
-| Name                    | Value                    | Function                                                          |
-|-------------------------|--------------------------|-------------------------------------------------------------------|
-| OMP_NUM_THREADS         | Number (e.g., 64)        | Set number of OpenMP threads (recommended: physical core count)   |
-| ZENDNNL_MATMUL_ALGO     | 0-5                      | Select MatMul backend algorithm (see Performance Optimization)    |
-| ZENDNNL_PROFILE_LOG_LEVEL | 0-4                    | Profiling log level (0=disabled, 4=verbose)                       |
-| ZENDNNL_ENABLE_PROFILER | 0 or 1                   | Enable detailed profiling (1=enabled)                             |
-| ZENDNNL_API_LOG_LEVEL   | 0-4                      | API log level (0=disabled, 4=verbose)                             |
-
-**Example**:
+ZenDNN's LowOHA MatMul supports multiple backend algorithms. For **best performance**, use the **Blocked AOCL DLP** algorithm:
 
 ```sh
-export OMP_NUM_THREADS=64
-export ZENDNNL_MATMUL_ALGO=2  # Use Blocked AOCL BLIS for best performance
-./build/bin/llama-cli -m models/llama-2-7b.Q4_0.gguf -p "Test" -n 100
+export ZENDNNL_MATMUL_ALGO=1    # Blocked AOCL DLP algo (recommended)
 ```
 
-## Performance Optimization
-
-### MatMul Algorithm Selection
-
-ZenDNN's LowOHA MatMul supports multiple backend algorithms. For **best performance**, use the **Blocked AOCL BLIS** algorithm:
-
-```sh
-export ZENDNNL_MATMUL_ALGO=2  # Blocked AOCL BLIS (recommended)
-```
-
-**Available algorithms**:
-
-| Value | Algorithm              | Description                                    |
-|:-----:|:-----------------------|:----------------------------------------------|
-| 0     | Dynamic Dispatch       | Automatic backend selection (default)         |
-| 1     | AOCL BLIS              | AOCL BLIS backend                             |
-| 2     | AOCL BLIS Blocked      | **Blocked AOCL BLIS (recommended)**           |
-| 3     | OneDNN                 | OneDNN backend                                |
-| 4     | OneDNN Blocked         | Blocked OneDNN                                |
-| 5     | LibXSMM                | LibXSMM backend                               |
+For more details on available algorithms, see the [ZenDNN MatMul Algorithm Documentation](https://github.com/amd/ZenDNN/blob/a18adf8c605fb5f5e52cefd7eda08a7b18febbaf/docs/runtime_env.md#algorithm-details).
 
 ### Profiling and Debugging
 
-For detailed profiling and logging options, refer to the [ZenDNN Logging Documentation](https://github.com/amd/ZenDNN/blob/zendnnl/docs/logging.md).
+For detailed profiling and logging options, refer to the [ZenDNN Logging Documentation](https://github.com/amd/ZenDNN/blob/a18adf8c605fb5f5e52cefd7eda08a7b18febbaf/docs/logging.md).
 
 ## Known Issues
 
@@ -245,10 +207,9 @@ A: Currently, ZenDNN primarily supports FP32 and BF16 data types. Quantized mode
 
 A: Ensure:
 1. You're using an AMD EPYC or Ryzen processor (Zen 2 or newer)
-2. `OMP_NUM_THREADS` is set appropriately (physical core count)
-3. `ZENDNNL_MATMUL_ALGO=2` is set for best performance (Blocked AOCL BLIS)
-4. You're using a sufficiently large model (small models may not benefit as much)
-5. Enable profiling to verify ZenDNN MatMul is being called
+2. `ZENDNNL_MATMUL_ALGO=1` is set for best performance (Blocked AOCL DLP)
+3. You're using a sufficiently large model (small models may not benefit as much)
+4. Enable profiling to verify ZenDNN MatMul is being called
 
 ### **GitHub Contribution**:
 Please add the **[ZenDNN]** prefix/tag in issues/PRs titles to help the ZenDNN-team check/address them without delay.

docs/backend/snapdragon/README.md

@@ -116,7 +116,7 @@ Llama-3.2-1B-Instruct-Q4_0.gguf: 1 file pushed, 0 skipped. 38.3 MB/s (773025920
 ### Windows
 
 All artifacts are already installed in the `pkg-snapdragon` folder.
-To run, adapt below instructions to use Powershell scrits in `scripts/snapdragon/windows`.
+To run, adapt below instructions to use Powershell scripts in `scripts/snapdragon/windows`.
 
 ## How to Run
 

docs/backend/snapdragon/windows.md

@@ -144,7 +144,7 @@ Once the build is complete HTP ops libraries will be installed like this
 -a----         1/22/2026   6:01 PM           4139 libggml-htp.cat
 ```
 
-The .cat file, the signature and proper certicate installation can be verified with
+The .cat file, the signature and proper certificate installation can be verified with
 
 ```
 > signtool.exe verify /v /pa .\pkg-snapdragon\lib\libggml-htp.cat

docs/build-s390x.md

@@ -242,10 +242,10 @@ IBM VXE/VXE2 SIMD acceleration depends on the BLAS implementation. It is strongl
 |------------|-------------|------|-------|
 | FP32       | ✅           | ✅    | ❓     |
 | FP16       | ✅           | ✅    | ❓     |
-| BF16       | 🚫           | ✅    | ❓     |
+| BF16       | ✅           | ✅    | ❓     |
 | Q4_0       | ✅           | ❓    | ❓     |
 | Q4_1       | ✅           | ❓    | ❓     |
-| MXFP4      | 🚫           | ❓    | ❓     |
+| MXFP4      | ✅           | ❓    | ❓     |
 | Q5_0       | ✅           | ❓    | ❓     |
 | Q5_1       | ✅           | ❓    | ❓     |
 | Q8_0       | ✅           | ❓    | ❓     |
@@ -272,4 +272,4 @@ IBM VXE/VXE2 SIMD acceleration depends on the BLAS implementation. It is strongl
 -   🚫 - acceleration unavailable, will still run using scalar implementation
 -   ❓ - acceleration unknown, please contribute if you can test it yourself
 
-Last Updated by **Aaron Teo (aaron.teo1@ibm.com)** on Sep 7, 2025.
+Last Updated by **Aaron Teo (aaron.teo1@ibm.com)** on Feb 15, 2026.

docs/build.md

@@ -108,7 +108,7 @@ Building through oneAPI compilers will make avx_vnni instruction set available f
 - Using oneAPI docker image:
   If you do not want to source the environment vars and install oneAPI manually, you can also build the code using intel docker container: [oneAPI-basekit](https://hub.docker.com/r/intel/oneapi-basekit). Then, you can use the commands given above.
 
-Check [Optimizing and Running LLaMA2 on Intel® CPU](https://www.intel.com/content/www/us/en/content-details/791610/optimizing-and-running-llama2-on-intel-cpu.html) for more information.
+Check [Optimizing and Running LLaMA2 on Intel® CPU](https://builders.intel.com/solutionslibrary/optimizing-and-running-llama2-on-intel-cpu) for more information.
 
 ### Other BLAS libraries
 
@@ -595,7 +595,7 @@ You can verify that KleidiAI is being used by running
 ```bash
 ./build/bin/llama-cli -m PATH_TO_MODEL -p "What is a car?"
 ```
-If KleidiAI is enabled, the ouput will contain a line similar to:
+If KleidiAI is enabled, the output will contain a line similar to:
 ```
 load_tensors: CPU_KLEIDIAI model buffer size =  3474.00 MiB
 ```
@@ -699,7 +699,7 @@ To read documentation for how to build on Android, [click here](./android.md)
 
 ## WebGPU [In Progress]
 
-The WebGPU backend relies on [Dawn](https://dawn.googlesource.com/dawn). Follow the instructions [here](https://dawn.googlesource.com/dawn/+/refs/heads/main/docs/quickstart-cmake.md) to install Dawn locally so that llama.cpp can find it using CMake. The currrent implementation is up-to-date with Dawn commit `bed1a61`.
+The WebGPU backend relies on [Dawn](https://dawn.googlesource.com/dawn). Follow the instructions [here](https://dawn.googlesource.com/dawn/+/refs/heads/main/docs/quickstart-cmake.md) to install Dawn locally so that llama.cpp can find it using CMake. The current implementation is up-to-date with Dawn commit `bed1a61`.
 
 In the llama.cpp directory, build with CMake:
 

docs/development/parsing.md

@@ -22,7 +22,7 @@ Below is a contrived example demonstrating how to use the PEG parser to parse
 output from a model that emits arguments as JSON.
 
 ```cpp
-auto parser = build_chat_peg_native_parser([&](common_chat_peg_native_builder & p) {
+auto parser = build_chat_peg_parser([&](common_chat_peg_builder & p) {
     // Build a choice of all available tools
     auto tool_choice = p.choice();
     for (const auto & tool : tools) {
@@ -212,7 +212,7 @@ mapper.from_ast(ctx.ast, result);
 
 ### Native
 
-The `common_chat_peg_native_builder` builds a `native` parser suitable for
+The `common_chat_peg_builder` builds a `native` parser suitable for
 models that emit tool arguments as a direct JSON object.
 
 - **`reasoning(p)`** - Tag node for `reasoning_content`
@@ -225,7 +225,7 @@ models that emit tool arguments as a direct JSON object.
 - **`tool_args(p)`** - Tag the tool arguments
 
 ```cpp
-build_chat_peg_native_parser([&](common_chat_peg_native_parser & p) {
+build_chat_peg_parser([&](common_chat_peg_builder & p) {
     auto get_weather_tool = p.tool(p.sequence({
         p.tool_open(p.literal("{")),
         p.json_member("name", "\"" + p.tool_name(p.literal("get_weather")) + "\""),
@@ -246,7 +246,7 @@ build_chat_peg_native_parser([&](common_chat_peg_native_parser & p) {
 
 ### Constructed
 
-The `common_chat_peg_constructed_builder` builds a `constructed` parser
+The `common_chat_peg_builder` builds a `constructed` parser
 suitable for models that emit tool arguments as separate entities, such as XML
 tags.
 
@@ -264,7 +264,7 @@ tags.
 - **`tool_arg_json_value(p)`** - Tag JSON value for the argument
 
 ```cpp
-build_chat_peg_constructed_parser([&](common_chat_peg_constructed_builder & p) {
+build_chat_peg_parser([&](common_chat_peg_builder & p) {
     auto location_arg = p.tool_arg(
         p.tool_arg_open("<parameter name=\"" + p.tool_arg_name(p.literal("location")) + "\">"),
         p.tool_arg_string_value(p.until("</parameter>")),

docs/multimodal/MobileVLM.md

@@ -281,7 +281,7 @@ llama_print_timings:       total time =    5990.25 ms /   202 tokens
 
 Just the same as above.
 
-**ouput**
+**output**
 ```sh
 encode_image_with_clip: image embedding created: 144 tokens
 
@@ -305,7 +305,7 @@ llama_print_timings:       total time =   15513.95 ms /   412 tokens
 ## Run on Intel(R) Core(TM) Ultra7 115H
 ### operation system
 Windows11
-### comiple
+### compile
 ```sh
 make -j32
 ```

docs/ops.md

@@ -24,29 +24,30 @@ Legend:
 |                          ARGSORT | ❌ | ✅ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ❌ | ❌ |
 |                             CEIL | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                            CLAMP | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ |
-|                           CONCAT | ❌ | ✅ | ✅ | 🟡 | ✅ | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ |
+|                           CONCAT | ❌ | ✅ | ✅ | 🟡 | ✅ | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                             CONT | ❌ | 🟡 | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ❌ | ❌ |
 |                          CONV_2D | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ❌ |
 |                       CONV_2D_DW | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
 |                          CONV_3D | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |                CONV_TRANSPOSE_1D | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                CONV_TRANSPOSE_2D | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
-|                              COS | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ |
+|                              COS | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                      COUNT_EQUAL | ❌ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                              CPY | ❌ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ |
 |               CROSS_ENTROPY_LOSS | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |          CROSS_ENTROPY_LOSS_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |                           CUMSUM | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ |
-|                             DIAG | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
+|                             DIAG | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
 |                    DIAG_MASK_INF | ❌ | ✅ | ✅ | ✅ | ❌ | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                              DIV | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                              DUP | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ |
-|                              ELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ |
+|                              ELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                              EXP | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                            EXPM1 | ❌ | ❌ | ✅ | 🟡 | 🟡 | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ |
 |                             FILL | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ |
-|                   FLASH_ATTN_EXT | ❌ | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | ❌ | 🟡 | 🟡 | ❌ | ❌ |
+|                   FLASH_ATTN_EXT | ❌ | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ |
 |                            FLOOR | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ✅ | ❌ | ❌ |
+|                  GATED_DELTA_NET | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |                GATED_LINEAR_ATTN | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ |
 |                            GEGLU | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                        GEGLU_ERF | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ |
@@ -54,7 +55,7 @@ Legend:
 |                             GELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                         GELU_ERF | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                       GELU_QUICK | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ |
-|                         GET_ROWS | ❌ | 🟡 | ✅ | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ |
+|                         GET_ROWS | ❌ | 🟡 | ✅ | 🟡 | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ❌ | ❌ |
 |                    GET_ROWS_BACK | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
 |                       GROUP_NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                      HARDSIGMOID | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
@@ -90,19 +91,19 @@ Legend:
 |                        RWKV_WKV6 | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                        RWKV_WKV7 | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                            SCALE | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
-|                              SET | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | ❌ |
+|                              SET | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | 🟡 | ✅ | ❌ | ❌ | ❌ |
 |                         SET_ROWS | ❌ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ |
-|                              SGN | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | ❌ | ✅ | ❌ | ❌ |
+|                              SGN | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                          SIGMOID | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                             SILU | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                        SILU_BACK | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
-|                              SIN | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ |
+|                              SIN | ❌ | ✅ | ✅ | ✅ | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                         SOFTPLUS | ❌ | ❌ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                         SOFT_MAX | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
 |                    SOFT_MAX_BACK | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | 🟡 | ✅ | ❌ | ❌ | ❌ |
-|                        SOLVE_TRI | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ |
-|                              SQR | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | ❌ | ❌ |
-|                             SQRT | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ❌ | ❌ | ❌ |
+|                        SOLVE_TRI | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |
+|                              SQR | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ |
+|                             SQRT | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ✅ | 🟡 | ✅ | ❌ | ❌ |
 |                         SSM_CONV | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                         SSM_SCAN | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ |
 |                             STEP | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | 🟡 | ✅ | ❌ | ❌ |
@@ -116,5 +117,5 @@ Legend:
 |                            TOP_K | ❌ | ❌ | ✅ | ❌ | ✅ | ❌ | 🟡 | 🟡 | ✅ | ❌ | ❌ |
 |                              TRI | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ |
 |                            TRUNC | ❌ | ❌ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ✅ | ❌ | ❌ |
-|                          UPSCALE | ❌ | 🟡 | ✅ | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | ❌ | ❌ | ❌ |
-|                            XIELU | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ |
+|                          UPSCALE | ❌ | 🟡 | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | ❌ | ❌ | ❌ |
+|                            XIELU | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ |

docs/ops/WebGPU.csv

@@ -8760,22 +8760,14 @@
 "WebGPU: WebGPU","ADD_ID","type_a=f32,type_b=f32,n_embd=129,n_experts=8,n_experts_used=4,n_token=1","support","0","no","WebGPU"
 "WebGPU: WebGPU","ADD_ID","type_a=f32,type_b=f32,n_embd=129,n_experts=8,n_experts_used=4,n_token=32","support","0","no","WebGPU"
 "WebGPU: WebGPU","ADD_ID","type_a=f32,type_b=f32,n_embd=129,n_experts=8,n_experts_used=4,n_token=129","support","0","no","WebGPU"
-"WebGPU: WebGPU","SQR","type=f16,ne=[10,5,4,3]","support","0","no","WebGPU"
-"WebGPU: WebGPU","SQRT","type=f16,ne=[10,3,3,2]","support","0","no","WebGPU"
 "WebGPU: WebGPU","LOG","type=f16,ne=[10,5,4,3]","support","1","yes","WebGPU"
-"WebGPU: WebGPU","SIN","type=f16,ne=[10,2,2,2]","support","0","no","WebGPU"
-"WebGPU: WebGPU","COS","type=f16,ne=[10,2,2,2]","support","0","no","WebGPU"
 "WebGPU: WebGPU","CLAMP","type=f16,ne=[10,5,4,3],min=-0.500000,max=0.500000","support","1","yes","WebGPU"
 "WebGPU: WebGPU","LEAKY_RELU","type=f16,ne_a=[10,5,4,3],negative_slope=0.100000","support","0","no","WebGPU"
 "WebGPU: WebGPU","FLOOR","type=f16,ne=[10,2,2,2]","support","1","yes","WebGPU"
 "WebGPU: WebGPU","CEIL","type=f16,ne=[10,2,2,2]","support","1","yes","WebGPU"
 "WebGPU: WebGPU","ROUND","type=f16,ne=[10,2,2,2]","support","1","yes","WebGPU"
 "WebGPU: WebGPU","TRUNC","type=f16,ne=[10,2,2,2]","support","1","yes","WebGPU"
-"WebGPU: WebGPU","SQR","type=f16,ne=[7,1,5,3]","support","0","no","WebGPU"
-"WebGPU: WebGPU","SQRT","type=f16,ne=[7,1,5,3]","support","0","no","WebGPU"
 "WebGPU: WebGPU","LOG","type=f16,ne=[7,1,5,3]","support","1","yes","WebGPU"
-"WebGPU: WebGPU","SIN","type=f16,ne=[7,1,5,3]","support","0","no","WebGPU"
-"WebGPU: WebGPU","COS","type=f16,ne=[7,1,5,3]","support","0","no","WebGPU"
 "WebGPU: WebGPU","CLAMP","type=f16,ne=[7,1,5,3],min=-0.500000,max=0.500000","support","1","yes","WebGPU"
 "WebGPU: WebGPU","LEAKY_RELU","type=f16,ne_a=[7,1,5,3],negative_slope=0.100000","support","0","no","WebGPU"
 "WebGPU: WebGPU","FLOOR","type=f16,ne=[7,1,5,3]","support","1","yes","WebGPU"
@@ -8786,22 +8778,14 @@
 "WebGPU: WebGPU","ROUND","type=f16,ne=[1024,1024,1,1]","support","1","yes","WebGPU"
 "WebGPU: WebGPU","TRUNC","type=f16,ne=[7,1,5,3]","support","1","yes","WebGPU"
 "WebGPU: WebGPU","TRUNC","type=f16,ne=[1024,1024,1,1]","support","1","yes","WebGPU"
-"WebGPU: WebGPU","SQR","type=f32,ne=[10,5,4,3]","support","0","no","WebGPU"
-"WebGPU: WebGPU","SQRT","type=f32,ne=[10,3,3,2]","support","0","no","WebGPU"
 "WebGPU: WebGPU","LOG","type=f32,ne=[10,5,4,3]","support","1","yes","WebGPU"
-"WebGPU: WebGPU","SIN","type=f32,ne=[10,2,2,2]","support","0","no","WebGPU"
-"WebGPU: WebGPU","COS","type=f32,ne=[10,2,2,2]","support","0","no","WebGPU"
 "WebGPU: WebGPU","CLAMP","type=f32,ne=[10,5,4,3],min=-0.500000,max=0.500000","support","1","yes","WebGPU"
 "WebGPU: WebGPU","LEAKY_RELU","type=f32,ne_a=[10,5,4,3],negative_slope=0.100000","support","0","no","WebGPU"
 "WebGPU: WebGPU","FLOOR","type=f32,ne=[10,2,2,2]","support","1","yes","WebGPU"
 "WebGPU: WebGPU","CEIL","type=f32,ne=[10,2,2,2]","support","1","yes","WebGPU"
 "WebGPU: WebGPU","ROUND","type=f32,ne=[10,2,2,2]","support","1","yes","WebGPU"
 "WebGPU: WebGPU","TRUNC","type=f32,ne=[10,2,2,2]","support","1","yes","WebGPU"
-"WebGPU: WebGPU","SQR","type=f32,ne=[7,1,5,3]","support","0","no","WebGPU"
-"WebGPU: WebGPU","SQRT","type=f32,ne=[7,1,5,3]","support","0","no","WebGPU"
 "WebGPU: WebGPU","LOG","type=f32,ne=[7,1,5,3]","support","1","yes","WebGPU"
-"WebGPU: WebGPU","SIN","type=f32,ne=[7,1,5,3]","support","0","no","WebGPU"
-"WebGPU: WebGPU","COS","type=f32,ne=[7,1,5,3]","support","0","no","WebGPU"
 "WebGPU: WebGPU","CLAMP","type=f32,ne=[7,1,5,3],min=-0.500000,max=0.500000","support","1","yes","WebGPU"
 "WebGPU: WebGPU","LEAKY_RELU","type=f32,ne_a=[7,1,5,3],negative_slope=0.100000","support","0","no","WebGPU"
 "WebGPU: WebGPU","FLOOR","type=f32,ne=[7,1,5,3]","support","1","yes","WebGPU"
@@ -9551,38 +9535,38 @@
 "WebGPU: WebGPU","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=40,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0,inplace=1","support","1","yes","WebGPU"
 "WebGPU: WebGPU","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=24,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=0,v=0,inplace=1","support","1","yes","WebGPU"
 "WebGPU: WebGPU","ROPE","type=f16,ne_a=[128,32,2,1],n_dims=128,mode=24,n_ctx=512,fs=1.424500,ef=0.746500,af=1.424500,ff=1,v=0,inplace=1","support","1","yes","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=0","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=0","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=0","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=0","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=0","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=0","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=0","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=0","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=1","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=1","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=1","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=1","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=1","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=1","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=1","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=1","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=2","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=2","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=2","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=2","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=2","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=2","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=2","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=2","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=3","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=3","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=3","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=3","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=3","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=3","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","0","no","WebGPU"
-"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","0","no","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=0","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=0","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=0","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=0","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=0","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=0","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=0","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=0","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=1","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=1","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=1","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=1","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=1","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=1","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=1","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=1","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=2","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=2","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=2","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=2","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=2","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=2","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=2","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=2","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=3","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=0,v=3","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=3","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=1,v=3","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=3","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=2,v=3","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=f32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","1","yes","WebGPU"
+"WebGPU: WebGPU","CONCAT","type=i32,ne_a=[11,12,13,14],ne_b_d=7,dim=3,v=3","support","1","yes","WebGPU"
 "WebGPU: WebGPU","ARGSORT","type=f32,ne=[3,1,1,1],order=0","support","1","yes","WebGPU"
 "WebGPU: WebGPU","ARGSORT","type=f32,ne=[4,1,1,1],order=0","support","1","yes","WebGPU"
 "WebGPU: WebGPU","ARGSORT","type=f32,ne=[7,1,1,1],order=0","support","1","yes","WebGPU"
@@ -18901,3 +18885,27 @@
 "WebGPU: WebGPU","CROSS_ENTROPY_LOSS_BACK","type=f32,ne=[30000,1,1,1]","support","0","no","WebGPU"
 "WebGPU: WebGPU","OPT_STEP_ADAMW","type=f32,ne=[10,5,4,3]","support","0","no","WebGPU"
 "WebGPU: WebGPU","OPT_STEP_SGD","type=f32,ne=[10,5,4,3]","support","0","no","WebGPU"
+"WebGPU: WebGPU","SQR","type=f16,ne=[10,5,4,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQRT","type=f16,ne=[10,3,3,2]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SIN","type=f16,ne=[10,2,2,2]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","COS","type=f16,ne=[10,2,2,2]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQR","type=f16,ne=[7,1,5,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQR","type=f16,ne=[1024,1024,1,1]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQRT","type=f16,ne=[7,1,5,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQRT","type=f16,ne=[1024,1024,1,1]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SIN","type=f16,ne=[7,1,5,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SIN","type=f16,ne=[1024,1024,1,1]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","COS","type=f16,ne=[7,1,5,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","COS","type=f16,ne=[1024,1024,1,1]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQR","type=f32,ne=[10,5,4,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQRT","type=f32,ne=[10,3,3,2]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SIN","type=f32,ne=[10,2,2,2]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","COS","type=f32,ne=[10,2,2,2]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQR","type=f32,ne=[7,1,5,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQR","type=f32,ne=[1024,1024,1,1]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQRT","type=f32,ne=[7,1,5,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SQRT","type=f32,ne=[1024,1024,1,1]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SIN","type=f32,ne=[7,1,5,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","SIN","type=f32,ne=[1024,1024,1,1]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","COS","type=f32,ne=[7,1,5,3]","support","1","yes","WebGPU"
+"WebGPU: WebGPU","COS","type=f32,ne=[1024,1024,1,1]","support","1","yes","WebGPU"

examples/batched/batched.cpp

@@ -5,6 +5,7 @@
 #include "sampling.h"
 
 #include <algorithm>
+#include <clocale>
 #include <cstdio>
 #include <string>
 #include <vector>
@@ -16,6 +17,8 @@ static void print_usage(int, char ** argv) {
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     params.prompt = "Hello my name is";

examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp

@@ -5,14 +5,16 @@
 #include "common.h"
 #include "log.h"
 
+#include <algorithm>
+#include <cassert>
+#include <cinttypes>
+#include <climits>
+#include <clocale>
+#include <cstdarg>
+#include <cstring>
+#include <ctime>
 #include <unordered_map>
 #include <vector>
-#include <cassert>
-#include <climits>
-#include <cstring>
-#include <cstdarg>
-#include <cinttypes>
-#include <ctime>
 #include <random>
 #include <stdexcept>
 #include <sstream>
@@ -874,6 +876,8 @@ static std::string basename(const std::string &path) {
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_init();
 
     struct train_params params = get_default_train_params();

examples/debug/README.md

@@ -2,7 +2,7 @@
 
 This is a utility intended to help debug a model by registering a callback that
 logs GGML operations and tensor data. It can also store the generated logits or
-embeddings as well as the prompt and token ids for comparision with the original
+embeddings as well as the prompt and token ids for comparison with the original
 model.
 
 ### Usage

examples/deprecation-warning/deprecation-warning.cpp

@@ -1,11 +1,14 @@
 // Warns users that this filename was deprecated, and provides a link for more information.
 
+#include <clocale>
 #include <cstdio>
 #include <string>
 #include <unordered_map>
 
 // Main
 int main(int argc, char** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     std::string filename = "main";
     if (argc >= 1) {
         filename = argv[0];

examples/diffusion/README.md

@@ -43,12 +43,12 @@ Choose one of the following scheduling methods:
 - `-b`: Batch size
 
 ### Examples
-#### Dream architechture:
+#### Dream architecture:
 ```
 llama-diffusion-cli -m dream7b.gguf -p "write code to train MNIST in pytorch" -ub 512 --diffusion-eps 0.001 --diffusion-algorithm 3 --diffusion-steps 256 --diffusion-visual
 ```
 
-#### LLaDA architechture:
+#### LLaDA architecture:
 ```
 llama-diffusion-cli -m llada-8b.gguf -p "write code to train MNIST in pytorch" -ub 512 --diffusion-block-length 32 --diffusion-steps 256 --diffusion-visual
 ```

examples/diffusion/diffusion-cli.cpp

@@ -7,6 +7,7 @@
 #include <limits.h>
 
 #include <algorithm>
+#include <clocale>
 #include <cmath>
 #include <cstring>
 #include <limits>
@@ -538,6 +539,8 @@ static std::string format_input_text(const std::string & prompt, const std::stri
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     ggml_time_init();
 
     common_params params;

examples/embedding/embedding.cpp

@@ -3,6 +3,7 @@
 #include "log.h"
 #include "llama.h"
 
+#include <clocale>
 #include <ctime>
 #include <algorithm>
 
@@ -94,6 +95,8 @@ static void print_raw_embeddings(const float * emb,
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_EMBEDDING)) {

examples/eval-callback/eval-callback.cpp

@@ -4,6 +4,8 @@
 #include "log.h"
 #include "llama.h"
 #include "llama-cpp.h"
+
+#include <clocale>
 #include <string>
 #include <vector>
 
@@ -29,6 +31,8 @@ static bool run(llama_context * ctx, const common_params & params) {
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     base_callback_data cb_data;
 
     common_params params;

examples/gen-docs/gen-docs.cpp

@@ -1,6 +1,7 @@
 #include "arg.h"
 #include "common.h"
 
+#include <clocale>
 #include <fstream>
 #include <sstream>
 #include <string>
@@ -100,6 +101,8 @@ static void write_help(std::ostringstream & ss, const md_file & md) {
 }
 
 int main(int, char **) {
+    std::setlocale(LC_NUMERIC, "C");
+
     for (const auto & md : md_files) {
         std::ifstream infile(md.fname);
         if (!infile.is_open()) {

examples/gguf-hash/gguf-hash.cpp

@@ -1,13 +1,14 @@
 #include "ggml.h"
 #include "gguf.h"
 
-#include <cstdlib>   /* abort() */
+#include <algorithm>
+#include <clocale>
 #include <cstddef>
 #include <cstdio>
-#include <string>
-#include <stdexcept>
-#include <algorithm>
+#include <cstdlib>   /* abort() */
 #include <cstring>
+#include <stdexcept>
+#include <string>
 
 #include <sstream>
 #include <fstream>
@@ -626,6 +627,8 @@ static hash_exit_code_t gguf_hash(const hash_params & hash_params) {
 }
 
 int main(int argc, const char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     hash_params params;
     manifest_check_params manifest_check;
     hash_params_parse(argc, argv, params);

examples/gguf/gguf.cpp

@@ -1,6 +1,7 @@
 #include "ggml.h"
 #include "gguf.h"
 
+#include <clocale>
 #include <cstdio>
 #include <string>
 #include <sstream>
@@ -240,6 +241,8 @@ static bool gguf_ex_read_1(const std::string & fname, bool check_data) {
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     if (argc < 3) {
         printf("usage: %s data.gguf r|w [n]\n", argv[0]);
         printf("r: read data.gguf file\n");

examples/json_schema_to_grammar.py

@@ -689,6 +689,11 @@ class SchemaConverter:
         elif (schema_type == 'object') or (len(schema) == 0):
             return self._add_rule(rule_name, self._add_primitive('object', PRIMITIVE_RULES['object']))
 
+        elif schema_type is None and isinstance(schema, dict):
+            # No type constraint and no recognized structural keywords (e.g. {"description": "..."}).
+            # Per JSON Schema semantics this is equivalent to {} and accepts any value.
+            return self._add_rule(rule_name, self._add_primitive('value', PRIMITIVE_RULES['value']))
+
         else:
             assert schema_type in PRIMITIVE_RULES, f'Unrecognized schema: {schema}'
             # TODO: support minimum, maximum, exclusiveMinimum, exclusiveMaximum at least for zero

examples/llama.vim

@@ -52,8 +52,8 @@ highlight llama_hl_info guifg=#77ff2f ctermfg=119
 "   n_prefix:         number of lines before the cursor location to include in the local prefix
 "   n_suffix:         number of lines after  the cursor location to include in the local suffix
 "   n_predict:        max number of tokens to predict
-"   t_max_prompt_ms:  max alloted time for the prompt processing (TODO: not yet supported)
-"   t_max_predict_ms: max alloted time for the prediction
+"   t_max_prompt_ms:  max allotted time for the prompt processing (TODO: not yet supported)
+"   t_max_predict_ms: max allotted time for the prediction
 "   show_info:        show extra info about the inference (0 - disabled, 1 - statusline, 2 - inline)
 "   auto_fim:         trigger FIM completion automatically on cursor movement
 "   max_line_suffix:  do not auto-trigger FIM completion if there are more than this number of characters to the right of the cursor

examples/lookahead/lookahead.cpp

@@ -4,10 +4,11 @@
 #include "log.h"
 #include "llama.h"
 
+#include <algorithm>
+#include <clocale>
 #include <cstdio>
 #include <string>
 #include <vector>
-#include <algorithm>
 
 struct ngram_data {
     bool active = false;
@@ -38,6 +39,8 @@ struct ngram_container {
 };
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON)) {

examples/lookup/lookup-create.cpp

@@ -3,10 +3,13 @@
 #include "ngram-cache.h"
 #include "llama.h"
 
+#include <clocale>
 #include <string>
 #include <vector>
 
 int main(int argc, char ** argv){
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_LOOKUP)) {

examples/lookup/lookup-merge.cpp

@@ -3,6 +3,7 @@
 #include "common.h"
 #include "ngram-cache.h"
 
+#include <clocale>
 #include <cstdint>
 #include <cstdio>
 #include <fstream>
@@ -17,6 +18,8 @@ static void print_usage(char* argv0) {
 }
 
 int main(int argc, char ** argv){
+    std::setlocale(LC_NUMERIC, "C");
+
     if (argc < 3) {
         print_usage(argv[0]);
         exit(1);

examples/lookup/lookup-stats.cpp

@@ -5,14 +5,17 @@
 #include "llama.h"
 #include "ggml.h"
 
+#include <cinttypes>
+#include <clocale>
 #include <cstdint>
 #include <cstdio>
-#include <cinttypes>
 #include <fstream>
 #include <string>
 #include <vector>
 
 int main(int argc, char ** argv){
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_LOOKUP)) {

examples/lookup/lookup.cpp

@@ -6,6 +6,7 @@
 #include "log.h"
 #include "llama.h"
 
+#include <clocale>
 #include <cstdint>
 #include <cstdio>
 #include <fstream>
@@ -13,6 +14,8 @@
 #include <vector>
 
 int main(int argc, char ** argv){
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_LOOKUP)) {

examples/model-conversion/Makefile

@@ -77,7 +77,10 @@ causal-verify-embeddings: causal-run-original-embeddings causal-run-converted-em
 	@./scripts/causal/compare-embeddings-logits.sh
 
 causal-inspect-original-model:
-	@./scripts/utils/inspect-org-model.py
+	@./scripts/utils/inspect-org-model.py --list-all -s
+
+causal-list-original-model-tensors:
+	@./scripts/utils/inspect-org-model.py --list-all-short -s
 
 causal-inspect-converted-model:
 	@./scripts/utils/inspect-converted-model.sh
@@ -153,7 +156,7 @@ embedding-verify-logits-st: embedding-run-original-model-st embedding-run-conver
 
 embedding-inspect-original-model:
 	$(call validate_embedding_model_path,embedding-inspect-original-model)
-	@EMBEDDING_MODEL_PATH="$(EMBEDDING_MODEL_PATH)" ./scripts/utils/inspect-org-model.py -m ${EMBEDDING_MODEL_PATH}
+	@EMBEDDING_MODEL_PATH="$(EMBEDDING_MODEL_PATH)" ./scripts/utils/inspect-org-model.py -m ${EMBEDDING_MODEL_PATH} --list-all -s
 
 embedding-inspect-converted-model:
 	@CONVERTED_EMBEDDING_MODEL="$(CONVERTED_EMBEDDING_MODEL)" ./scripts/utils/inspect-converted-model.sh ${CONVERTED_EMBEDDING_MODEL}

examples/model-conversion/README.md

@@ -69,7 +69,7 @@ Command line arguments take precedence over environment variables when both are
 
 In cases where the transformer implementation for the model has not been released
 yet it is possible to set the environment variable `UNRELEASED_MODEL_NAME` which
-will then cause the transformer implementation to be loaded explicitely and not
+will then cause the transformer implementation to be loaded explicitly and not
 use AutoModelForCausalLM:
 ```
 export UNRELEASED_MODEL_NAME=SomeNewModel
@@ -120,7 +120,7 @@ The converted model can be inspected using the following command:
 (venv) $ make causal-run-converted-model
 ```
 
-### Model logits verfication
+### Model logits verification
 The following target will run the original model and the converted model and
 compare the logits:
 ```console
@@ -235,7 +235,7 @@ new model the model can be converted to GGUF format using the following command:
 (venv) $ make embedding-run-converted-model
 ```
 
-### Model logits verfication
+### Model logits verification
 The following target will run the original model and the converted model (which
 was done manually in the previous steps) and compare the logits:
 ```console
@@ -335,7 +335,7 @@ $ make perplexity-run-full QUANTIZED_MODEL=~/path/to/quantized/model-Qxx.gguf LO
 
 ## HuggingFace utilities
 The following targets are useful for creating collections and model repositories
-on Hugging Face in the the ggml-org. These can be used when preparing a relase
+on Hugging Face in the the ggml-org. These can be used when preparing a release
 to script the process for new model releases.
 
 For the following targets a `HF_TOKEN` environment variable is required.
@@ -347,7 +347,7 @@ For the following targets a `HF_TOKEN` environment variable is required.
 > $ unset HF_TOKEN
 
 ### Create a new Hugging Face Model (model repository)
-This will create a new model repsository on Hugging Face with the specified
+This will create a new model repository on Hugging Face with the specified
 model name.
 ```console
 (venv) $ make hf-create-model MODEL_NAME='TestModel' NAMESPACE="danbev" ORIGINAL_BASE_MODEL="some-base-model"

examples/model-conversion/scripts/causal/run-org-model.py

@@ -42,11 +42,15 @@ def load_model_and_tokenizer(model_path, device="auto"):
         config = config.text_config
         multimodal = True
 
-    print("Vocab size:       ", config.vocab_size)
-    print("Hidden size:      ", config.hidden_size)
-    print("Number of layers: ", config.num_hidden_layers)
-    print("BOS token id:     ", config.bos_token_id)
-    print("EOS token id:     ", config.eos_token_id)
+    def print_if_exists(label, obj, attr, default="N/A"):
+        val = getattr(obj, attr) if hasattr(obj, attr) else default
+        print(f"{label}", val)
+
+    print_if_exists("Vocab size:       ", config, "vocab_size")
+    print_if_exists("Hidden size:      ", config, "hidden_size")
+    print_if_exists("Number of layers: ", config, "num_hidden_layers")
+    print_if_exists("BOS token id:     ", config, "bos_token_id")
+    print_if_exists("EOS token id:     ", config, "eos_token_id")
 
     unreleased_model_name = os.getenv("UNRELEASED_MODEL_NAME")
     if unreleased_model_name:

examples/model-conversion/scripts/utils/inspect-org-model.py

@@ -1,67 +1,290 @@
 #!/usr/bin/env python3
 
 import argparse
-import os
 import json
+import os
+import re
+import struct
+import sys
+from pathlib import Path
+from typing import Optional
 from safetensors import safe_open
-from collections import defaultdict
 
-parser = argparse.ArgumentParser(description='Process model with specified path')
-parser.add_argument('--model-path', '-m', help='Path to the model')
-args = parser.parse_args()
 
-model_path = os.environ.get('MODEL_PATH', args.model_path)
-if model_path is None:
-    parser.error("Model path must be specified either via --model-path argument or MODEL_PATH environment variable")
+MODEL_SAFETENSORS_FILE = "model.safetensors"
+MODEL_SAFETENSORS_INDEX = "model.safetensors.index.json"
 
-# Check if there's an index file (multi-file model)
-index_path = os.path.join(model_path, "model.safetensors.index.json")
-single_file_path = os.path.join(model_path, "model.safetensors")
+DTYPE_SIZES = {
+    "F64": 8, "I64": 8, "U64": 8,
+    "F32": 4, "I32": 4, "U32": 4,
+    "F16": 2, "BF16": 2, "I16": 2, "U16": 2,
+    "I8": 1, "U8": 1, "BOOL": 1,
+    "F8_E4M3": 1, "F8_E5M2": 1,
+}
 
-if os.path.exists(index_path):
-    # Multi-file model
-    print("Multi-file model detected")
+SIZE_UNITS = ['B', 'KB', 'MB', 'GB', 'TB']
 
-    with open(index_path, 'r') as f:
-        index_data = json.load(f)
 
-    # Get the weight map (tensor_name -> file_name)
-    weight_map = index_data.get("weight_map", {})
+def get_weight_map(model_path: Path) -> Optional[dict[str, str]]:
+    index_file = model_path / MODEL_SAFETENSORS_INDEX
 
-    # Group tensors by file for efficient processing
-    file_tensors = defaultdict(list)
-    for tensor_name, file_name in weight_map.items():
-        file_tensors[file_name].append(tensor_name)
+    if index_file.exists():
+        with open(index_file, 'r') as f:
+            index = json.load(f)
+            return index.get("weight_map", {})
 
-    print("Tensors in model:")
+    return None
 
-    # Process each shard file
-    for file_name, tensor_names in file_tensors.items():
-        file_path = os.path.join(model_path, file_name)
-        print(f"\n--- From {file_name} ---")
 
-        with safe_open(file_path, framework="pt") as f:
-            for tensor_name in sorted(tensor_names):
-                tensor = f.get_tensor(tensor_name)
-                print(f"- {tensor_name} : shape = {tensor.shape}, dtype = {tensor.dtype}")
+def get_all_tensor_names(model_path: Path) -> list[str]:
+    weight_map = get_weight_map(model_path)
 
-elif os.path.exists(single_file_path):
-    # Single file model (original behavior)
-    print("Single-file model detected")
+    if weight_map is not None:
+        return list(weight_map.keys())
 
-    with safe_open(single_file_path, framework="pt") as f:
-        keys = f.keys()
-        print("Tensors in model:")
-        for key in sorted(keys):
-            tensor = f.get_tensor(key)
-            print(f"- {key} : shape = {tensor.shape}, dtype = {tensor.dtype}")
+    single_file = model_path / MODEL_SAFETENSORS_FILE
+    if single_file.exists():
+        try:
+            with safe_open(single_file, framework="pt", device="cpu") as f:
+                return list(f.keys())
+        except Exception as e:
+            print(f"Error reading {single_file}: {e}")
+            sys.exit(1)
 
-else:
-    print(f"Error: Neither 'model.safetensors.index.json' nor 'model.safetensors' found in {model_path}")
-    print("Available files:")
-    if os.path.exists(model_path):
-        for item in sorted(os.listdir(model_path)):
-            print(f"  {item}")
+    print(f"Error: No safetensors files found in {model_path}")
+    sys.exit(1)
+
+
+def find_tensor_file(model_path: Path, tensor_name: str) -> Optional[str]:
+    weight_map = get_weight_map(model_path)
+
+    if weight_map is not None:
+        return weight_map.get(tensor_name)
+
+    single_file = model_path / MODEL_SAFETENSORS_FILE
+    if single_file.exists():
+        return single_file.name
+
+    return None
+
+
+def read_safetensors_header(file_path: Path) -> dict:
+    with open(file_path, 'rb') as f:
+        header_size = struct.unpack('<Q', f.read(8))[0]
+        return json.loads(f.read(header_size))
+
+
+def get_tensor_size_bytes(tensor_meta: dict) -> int:
+    offsets = tensor_meta.get("data_offsets")
+    if offsets and len(offsets) == 2:
+        return offsets[1] - offsets[0]
+    n_elements = 1
+    for d in tensor_meta.get("shape", []):
+        n_elements *= d
+    return n_elements * DTYPE_SIZES.get(tensor_meta.get("dtype", "F32"), 4)
+
+
+def format_size(size_bytes: int) -> str:
+    val = float(size_bytes)
+    for unit in SIZE_UNITS[:-1]:
+        if val < 1024.0:
+            return f"{val:.2f} {unit}"
+        val /= 1024.0
+    return f"{val:.2f} {SIZE_UNITS[-1]}"
+
+
+def get_all_tensor_metadata(model_path: Path) -> dict[str, dict]:
+    weight_map = get_weight_map(model_path)
+
+    if weight_map is not None:
+        file_to_tensors: dict[str, list[str]] = {}
+        for tensor_name, file_name in weight_map.items():
+            file_to_tensors.setdefault(file_name, []).append(tensor_name)
+
+        all_metadata: dict[str, dict] = {}
+        for file_name, tensor_names in file_to_tensors.items():
+            try:
+                header = read_safetensors_header(model_path / file_name)
+                for tensor_name in tensor_names:
+                    if tensor_name in header:
+                        all_metadata[tensor_name] = header[tensor_name]
+            except Exception as e:
+                print(f"Warning: Could not read header from {file_name}: {e}", file=sys.stderr)
+        return all_metadata
+
+    single_file = model_path / MODEL_SAFETENSORS_FILE
+    if single_file.exists():
+        try:
+            header = read_safetensors_header(single_file)
+            return {k: v for k, v in header.items() if k != "__metadata__"}
+        except Exception as e:
+            print(f"Error reading {single_file}: {e}")
+            sys.exit(1)
+
+    print(f"Error: No safetensors files found in {model_path}")
+    sys.exit(1)
+
+
+def normalize_tensor_name(tensor_name: str) -> str:
+    normalized = re.sub(r'\.\d+\.', '.#.', tensor_name)
+    normalized = re.sub(r'\.\d+$', '.#', normalized)
+    return normalized
+
+
+def list_all_tensors(
+    model_path: Path,
+    short: bool = False,
+    show_sizes: bool = False,
+):
+    tensor_names = get_all_tensor_names(model_path)
+
+    metadata: Optional[dict[str, dict]] = None
+    if show_sizes:
+        metadata = get_all_tensor_metadata(model_path)
+
+    total_bytes = 0
+
+    if short:
+        seen: dict[str, str] = {}
+        for tensor_name in sorted(tensor_names):
+            normalized = normalize_tensor_name(tensor_name)
+            if normalized not in seen:
+                seen[normalized] = tensor_name
+        display_pairs = list(sorted(seen.items()))
+        name_width = max((len(n) for n, _ in display_pairs), default=0)
+        for normalized, first_name in display_pairs:
+            if metadata and first_name in metadata:
+                m = metadata[first_name]
+                size = get_tensor_size_bytes(m)
+                total_bytes += size
+                print(f"{normalized:{name_width}}  {m.get('dtype', '?'):6s}  {str(m.get('shape', '')):30s}  {format_size(size)}")
+            else:
+                print(normalized)
     else:
-        print(f"  Directory {model_path} does not exist")
-    exit(1)
+        name_width = max((len(n) for n in tensor_names), default=0)
+        for tensor_name in sorted(tensor_names):
+            if metadata and tensor_name in metadata:
+                m = metadata[tensor_name]
+                size = get_tensor_size_bytes(m)
+                total_bytes += size
+                print(f"{tensor_name:{name_width}}  {m.get('dtype', '?'):6s}  {str(m.get('shape', '')):30s}  {format_size(size)}")
+            else:
+                print(tensor_name)
+
+    if show_sizes:
+        print(f"\nTotal: {format_size(total_bytes)}")
+
+
+def print_tensor_info(model_path: Path, tensor_name: str, num_values: Optional[int] = None):
+    tensor_file = find_tensor_file(model_path, tensor_name)
+
+    if tensor_file is None:
+        print(f"Error: Could not find tensor '{tensor_name}' in model index")
+        print(f"Model path: {model_path}")
+        sys.exit(1)
+
+    file_path = model_path / tensor_file
+
+    try:
+        header = read_safetensors_header(file_path)
+        tensor_meta = header.get(tensor_name, {})
+        dtype_str = tensor_meta.get("dtype")
+
+        with safe_open(file_path, framework="pt", device="cpu") as f:
+            if tensor_name in f.keys():
+                tensor_slice = f.get_slice(tensor_name)
+                shape = tensor_slice.get_shape()
+                print(f"Tensor: {tensor_name}")
+                print(f"File:   {tensor_file}")
+                print(f"Shape:  {shape}")
+                if dtype_str:
+                    print(f"Dtype:  {dtype_str}")
+                if tensor_meta:
+                    print(f"Size:   {format_size(get_tensor_size_bytes(tensor_meta))}")
+                if num_values is not None:
+                    tensor = f.get_tensor(tensor_name)
+                    if not dtype_str:
+                        print(f"Dtype:  {tensor.dtype}")
+                    flat = tensor.flatten()
+                    n = min(num_values, flat.numel())
+                    print(f"Values: {flat[:n].tolist()}")
+            else:
+                print(f"Error: Tensor '{tensor_name}' not found in {tensor_file}")
+                sys.exit(1)
+
+    except FileNotFoundError:
+        print(f"Error: The file '{file_path}' was not found.")
+        sys.exit(1)
+    except Exception as e:
+        print(f"An error occurred: {e}")
+        sys.exit(1)
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Print tensor information from a safetensors model"
+    )
+    parser.add_argument(
+        "tensor_name",
+        nargs="?",
+        help="Name of the tensor to inspect"
+    )
+    parser.add_argument(
+        "-m", "--model-path",
+        type=Path,
+        help="Path to the model directory (default: MODEL_PATH environment variable)"
+    )
+    parser.add_argument(
+        "-l", "--list-all-short",
+        action="store_true",
+        help="List unique tensor patterns (layer numbers replaced with #)"
+    )
+    parser.add_argument(
+        "-la", "--list-all",
+        action="store_true",
+        help="List all tensor names with actual layer numbers"
+    )
+    parser.add_argument(
+        "-n", "--num-values",
+        nargs="?",
+        const=10,
+        default=None,
+        type=int,
+        metavar="N",
+        help="Print the first N values of the tensor flattened (default: 10 if flag is given without a number)"
+    )
+    parser.add_argument(
+        "-s", "--sizes",
+        action="store_true",
+        help="Show dtype, shape, and size for each tensor when listing"
+    )
+
+    args = parser.parse_args()
+
+    model_path = args.model_path
+    if model_path is None:
+        model_path_str = os.environ.get("MODEL_PATH")
+        if model_path_str is None:
+            print("Error: --model-path not provided and MODEL_PATH environment variable not set")
+            sys.exit(1)
+        model_path = Path(model_path_str)
+
+    if not model_path.exists():
+        print(f"Error: Model path does not exist: {model_path}")
+        sys.exit(1)
+
+    if not model_path.is_dir():
+        print(f"Error: Model path is not a directory: {model_path}")
+        sys.exit(1)
+
+    if args.list_all_short or args.list_all:
+        list_all_tensors(model_path, short=args.list_all_short, show_sizes=args.sizes)
+    else:
+        if args.tensor_name is None:
+            print("Error: tensor_name is required when not using --list-all-short or --list-all")
+            sys.exit(1)
+        print_tensor_info(model_path, args.tensor_name, args.num_values)
+
+
+if __name__ == "__main__":
+    main()

examples/model-conversion/scripts/utils/tensor-info.py

@@ -1,159 +0,0 @@
-#!/usr/bin/env python3
-
-import argparse
-import json
-import os
-import re
-import sys
-from pathlib import Path
-from typing import Optional
-from safetensors import safe_open
-
-
-MODEL_SAFETENSORS_FILE = "model.safetensors"
-MODEL_SAFETENSORS_INDEX = "model.safetensors.index.json"
-
-
-def get_weight_map(model_path: Path) -> Optional[dict[str, str]]:
-    index_file = model_path / MODEL_SAFETENSORS_INDEX
-
-    if index_file.exists():
-        with open(index_file, 'r') as f:
-            index = json.load(f)
-            return index.get("weight_map", {})
-
-    return None
-
-
-def get_all_tensor_names(model_path: Path) -> list[str]:
-    weight_map = get_weight_map(model_path)
-
-    if weight_map is not None:
-        return list(weight_map.keys())
-
-    single_file = model_path / MODEL_SAFETENSORS_FILE
-    if single_file.exists():
-        try:
-            with safe_open(single_file, framework="pt", device="cpu") as f:
-                return list(f.keys())
-        except Exception as e:
-            print(f"Error reading {single_file}: {e}")
-            sys.exit(1)
-
-    print(f"Error: No safetensors files found in {model_path}")
-    sys.exit(1)
-
-
-def find_tensor_file(model_path: Path, tensor_name: str) -> Optional[str]:
-    weight_map = get_weight_map(model_path)
-
-    if weight_map is not None:
-        return weight_map.get(tensor_name)
-
-    single_file = model_path / MODEL_SAFETENSORS_FILE
-    if single_file.exists():
-        return single_file.name
-
-    return None
-
-
-def normalize_tensor_name(tensor_name: str) -> str:
-    normalized = re.sub(r'\.\d+\.', '.#.', tensor_name)
-    normalized = re.sub(r'\.\d+$', '.#', normalized)
-    return normalized
-
-
-def list_all_tensors(model_path: Path, unique: bool = False):
-    tensor_names = get_all_tensor_names(model_path)
-
-    if unique:
-        seen = set()
-        for tensor_name in sorted(tensor_names):
-            normalized = normalize_tensor_name(tensor_name)
-            if normalized not in seen:
-                seen.add(normalized)
-                print(normalized)
-    else:
-        for tensor_name in sorted(tensor_names):
-            print(tensor_name)
-
-
-def print_tensor_info(model_path: Path, tensor_name: str):
-    tensor_file = find_tensor_file(model_path, tensor_name)
-
-    if tensor_file is None:
-        print(f"Error: Could not find tensor '{tensor_name}' in model index")
-        print(f"Model path: {model_path}")
-        sys.exit(1)
-
-    file_path = model_path / tensor_file
-
-    try:
-        with safe_open(file_path, framework="pt", device="cpu") as f:
-            if tensor_name in f.keys():
-                tensor_slice = f.get_slice(tensor_name)
-                shape = tensor_slice.get_shape()
-                print(f"Tensor: {tensor_name}")
-                print(f"File:   {tensor_file}")
-                print(f"Shape:  {shape}")
-            else:
-                print(f"Error: Tensor '{tensor_name}' not found in {tensor_file}")
-                sys.exit(1)
-
-    except FileNotFoundError:
-        print(f"Error: The file '{file_path}' was not found.")
-        sys.exit(1)
-    except Exception as e:
-        print(f"An error occurred: {e}")
-        sys.exit(1)
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        description="Print tensor information from a safetensors model"
-    )
-    parser.add_argument(
-        "tensor_name",
-        nargs="?",  # optional (if --list is used for example)
-        help="Name of the tensor to inspect"
-    )
-    parser.add_argument(
-        "-m", "--model-path",
-        type=Path,
-        help="Path to the model directory (default: MODEL_PATH environment variable)"
-    )
-    parser.add_argument(
-        "-l", "--list",
-        action="store_true",
-        help="List unique tensor patterns in the model (layer numbers replaced with #)"
-    )
-
-    args = parser.parse_args()
-
-    model_path = args.model_path
-    if model_path is None:
-        model_path_str = os.environ.get("MODEL_PATH")
-        if model_path_str is None:
-            print("Error: --model-path not provided and MODEL_PATH environment variable not set")
-            sys.exit(1)
-        model_path = Path(model_path_str)
-
-    if not model_path.exists():
-        print(f"Error: Model path does not exist: {model_path}")
-        sys.exit(1)
-
-    if not model_path.is_dir():
-        print(f"Error: Model path is not a directory: {model_path}")
-        sys.exit(1)
-
-    if args.list:
-        list_all_tensors(model_path, unique=True)
-    else:
-        if args.tensor_name is None:
-            print("Error: tensor_name is required when not using --list")
-            sys.exit(1)
-        print_tensor_info(model_path, args.tensor_name)
-
-
-if __name__ == "__main__":
-    main()

examples/parallel/parallel.cpp

@@ -7,12 +7,13 @@
 #include "log.h"
 #include "llama.h"
 
+#include <algorithm>
+#include <clocale>
 #include <cmath>
 #include <cstdio>
 #include <string>
 #include <vector>
 #include <ctime>
-#include <algorithm>
 
 // trim whitespace from the beginning and end of a string
 static std::string trim(const std::string & str) {
@@ -153,6 +154,8 @@ static std::vector<std::string> split_string(const std::string& input, char deli
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     srand(1234);
 
     common_params params;

examples/passkey/passkey.cpp

@@ -3,6 +3,7 @@
 #include "log.h"
 #include "llama.h"
 
+#include <clocale>
 #include <cmath>
 #include <cstdio>
 #include <string>
@@ -16,6 +17,8 @@ static void print_usage(int, char ** argv) {
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     params.n_junk = 250;

examples/retrieval/retrieval.cpp

@@ -4,6 +4,7 @@
 #include "llama.h"
 
 #include <algorithm>
+#include <clocale>
 #include <fstream>
 #include <iostream> // TODO: remove me
 
@@ -112,6 +113,8 @@ static void batch_process(llama_context * ctx, llama_batch & batch, float * outp
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_RETRIEVAL, print_usage)) {

examples/save-load-state/save-load-state.cpp

@@ -2,15 +2,21 @@
 #include "common.h"
 #include "llama.h"
 
+#include <clocale>
 #include <vector>
 #include <cstdio>
 
+
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     params.prompt = "The quick brown fox";
     params.sampling.seed = 1234;
 
+    const std::string_view state_file = "dump_state.bin";
+
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON)) {
         return 1;
     }
@@ -53,35 +59,16 @@ int main(int argc, char ** argv) {
     // tokenize prompt
     auto tokens = common_tokenize(ctx, params.prompt, true);
 
-    // prepare the batch
-    llama_batch batch = llama_batch_init(tokens.size(), 0, 1);
-    for (size_t i = 0; i < tokens.size(); i++) {
-        common_batch_add(batch, tokens[i], i, {0}, false);
+    const bool save_state = true;
+    if (!common_prompt_batch_decode(ctx, tokens, n_past, params.n_batch, state_file, save_state)) {
+        return 1;
     }
-    batch.logits[batch.n_tokens - 1] = true; // generate next token
-
-    // evaluate prompt
-    llama_decode(ctx, batch);
-    n_past += batch.n_tokens;
-
-    // save state (rng, logits, embedding and kv_cache) to file
-    {
-        std::vector<uint8_t> state_mem(llama_state_get_size(ctx));
-        const size_t written = llama_state_get_data(ctx, state_mem.data(), state_mem.size());
-
-        FILE *fp_write = fopen("dump_state.bin", "wb");
-        fwrite(state_mem.data(), 1, written, fp_write);
-        fclose(fp_write);
-
-        fprintf(stderr, "%s : serialized state into %zd out of a maximum of %zd bytes\n", __func__, written, state_mem.size());
-    }
-
-    // save state (last tokens)
-    const auto n_past_saved = n_past;
 
     // first run
     printf("\nfirst run: %s", params.prompt.c_str());
 
+    llama_batch batch = llama_batch_init(1, 0, 1);
+
     for (auto i = 0; i < params.n_predict; i++) {
         auto next_token     = llama_sampler_sample(smpl, ctx, -1);
         auto next_token_str = common_token_to_piece(ctx, next_token);
@@ -111,27 +98,23 @@ int main(int argc, char ** argv) {
 
     printf("\nsecond run: %s", params.prompt.c_str());
 
-    // load state (rng, logits, embedding and kv_cache) from file
-    {
-        std::vector<uint8_t> state_mem;
+    // load state from file
+    std::vector<llama_token> unused_sts(tokens.size()); // unused session tokens.
+    size_t n_token_count_out = 0;
 
-        FILE * fp_read = fopen("dump_state.bin", "rb");
-        fseek(fp_read, 0, SEEK_END);
-        state_mem.resize(ftell(fp_read));
-        fseek(fp_read, 0, SEEK_SET);
-        const size_t read = fread(state_mem.data(), 1, state_mem.size(), fp_read);
-        fclose(fp_read);
-
-        if (read != llama_state_set_data(ctx2, state_mem.data(), state_mem.size())) {
-            fprintf(stderr, "\n%s : failed to read state\n", __func__);
-            return 1;
-        }
-
-        fprintf(stderr, "%s : deserialized state from %zd out of a maximum of %zd bytes\n", __func__, read, state_mem.size());
+    if (!llama_state_load_file(ctx2, state_file.data(), unused_sts.data(), unused_sts.size(), &n_token_count_out)) {
+        fprintf(stderr, "\n%s : failed to load state\n", __func__);
+        return 1;
     }
 
+    fprintf(stderr, "%s : loaded state with %zu tokens\n", __func__, n_token_count_out);
+
     // restore state (last tokens)
-    n_past = n_past_saved;
+    n_past = n_token_count_out;
+    if (!common_replay_last_token(ctx2, tokens.back(), n_past)) {
+        return 1;
+    }
+    ++n_past;
 
     // second run
     for (auto i = 0; i < params.n_predict; i++) {
@@ -160,7 +143,9 @@ int main(int argc, char ** argv) {
     }
 
     // make new context
-    llama_context * ctx3 = llama_init_from_model(model, common_context_params_to_llama(params));
+    auto params_ctx3 = common_context_params_to_llama(params);
+    params_ctx3.n_seq_max = 2;
+    llama_context * ctx3 = llama_init_from_model(model, params_ctx3);
 
     llama_sampler * smpl3 = llama_sampler_chain_init(sparams);
 
@@ -169,26 +154,21 @@ int main(int argc, char ** argv) {
     printf("\nsingle seq run: %s", params.prompt.c_str());
 
     // load state (rng, logits, embedding and kv_cache) from file
-    {
-        std::vector<uint8_t> state_mem;
+    n_token_count_out = 0;
 
-        FILE * fp_read = fopen("dump_state.bin", "rb");
-        fseek(fp_read, 0, SEEK_END);
-        state_mem.resize(ftell(fp_read));
-        fseek(fp_read, 0, SEEK_SET);
-        const size_t read = fread(state_mem.data(), 1, state_mem.size(), fp_read);
-        fclose(fp_read);
-
-        if (read != llama_state_set_data(ctx3, state_mem.data(), state_mem.size())) {
-            fprintf(stderr, "\n%s : failed to read state\n", __func__);
-            return 1;
-        }
-
-        fprintf(stderr, "%s : deserialized state from %zd out of a maximum of %zd bytes\n", __func__, read, state_mem.size());
+    if (!llama_state_load_file(ctx3, state_file.data(), unused_sts.data(), unused_sts.size(), &n_token_count_out)) {
+        fprintf(stderr, "\n%s : failed to load state\n", __func__);
+        return 1;
     }
 
+    fprintf(stderr, "%s : loaded state with %zu tokens\n", __func__, n_token_count_out);
+
     // restore state (last tokens)
-    n_past = n_past_saved;
+    n_past = n_token_count_out;
+    if (!common_replay_last_token(ctx3, tokens.back(), n_past)) {
+        return 1;
+    }
+    ++n_past;
 
     // save seq 0 and load into seq 1
     {

examples/simple-chat/simple-chat.cpp

@@ -1,4 +1,5 @@
 #include "llama.h"
+#include <clocale>
 #include <cstdio>
 #include <cstring>
 #include <iostream>
@@ -12,6 +13,8 @@ static void print_usage(int, char ** argv) {
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     std::string model_path;
     int ngl = 99;
     int n_ctx = 2048;

examples/simple/simple.cpp

@@ -1,4 +1,5 @@
 #include "llama.h"
+#include <clocale>
 #include <cstdio>
 #include <cstring>
 #include <string>
@@ -11,6 +12,8 @@ static void print_usage(int, char ** argv) {
 }
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     // path to the model gguf file
     std::string model_path;
     // prompt to generate text from

examples/speculative-simple/speculative-simple.cpp

@@ -5,12 +5,15 @@
 #include "log.h"
 #include "llama.h"
 
+#include <clocale>
 #include <cstdio>
 #include <cstring>
 #include <string>
 #include <vector>
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_SPECULATIVE)) {

examples/speculative/speculative.cpp

@@ -5,6 +5,7 @@
 #include "llama.h"
 
 #include <algorithm>
+#include <clocale>
 #include <cstdio>
 #include <cstring>
 #include <random>
@@ -30,6 +31,8 @@ struct seq_draft {
 };
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
 
     // needed to get candidate probs even for temp <= 0.0

examples/sycl/README.md

@@ -6,11 +6,11 @@ This example program provides the tools for llama.cpp for SYCL on Intel GPU.
 
 |Tool Name| Function|Status|
 |-|-|-|
-|llama-ls-sycl-device| List all SYCL devices with ID, compute capability, max work group size, ect.|Support|
+|llama-ls-sycl-device| List all SYCL devices with ID, compute capability, max work group size, etc.|Support|
 
 ### llama-ls-sycl-device
 
-List all SYCL devices with ID, compute capability, max work group size, ect.
+List all SYCL devices with ID, compute capability, max work group size, etc.
 
 1. Build the llama.cpp for SYCL for the specified target *(using GGML_SYCL_TARGET)*.
 

examples/sycl/ls-sycl-device.cpp

@@ -6,8 +6,10 @@
 
 
 #include "ggml-sycl.h"
+#include <clocale>
 
 int main() {
+    std::setlocale(LC_NUMERIC, "C");
     ggml_backend_sycl_print_sycl_devices();
     return 0;
 }

examples/training/finetune.cpp

@@ -3,6 +3,7 @@
 #include "log.h"
 #include "llama.h"
 
+#include <clocale>
 #include <cmath>
 #include <cstdio>
 #include <cstring>
@@ -14,6 +15,8 @@
 #endif
 
 int main(int argc, char ** argv) {
+    std::setlocale(LC_NUMERIC, "C");
+
     common_params params;
     params.escape = false;
 

ggml/CMakeLists.txt

@@ -4,7 +4,7 @@ project("ggml" C CXX ASM)
 ### GGML Version
 set(GGML_VERSION_MAJOR 0)
 set(GGML_VERSION_MINOR 9)
-set(GGML_VERSION_PATCH 5)
+set(GGML_VERSION_PATCH 7)
 set(GGML_VERSION_BASE "${GGML_VERSION_MAJOR}.${GGML_VERSION_MINOR}.${GGML_VERSION_PATCH}")
 
 find_program(GIT_EXE NAMES git git.exe NO_CMAKE_FIND_ROOT_PATH)

ggml/include/ggml-backend.h

@@ -259,7 +259,7 @@ extern "C" {
       Example usage:
 
         // operations that use tensors allocated in a buffer with USAGE_WEIGHTS will be assigned
-        // preferrably to run on the same backend as the buffer
+        // preferably to run on the same backend as the buffer
         ggml_backend_buffer_set_usage(buf_weights, GGML_BACKEND_BUFFER_USAGE_WEIGHTS);
 
         sched = ggml_backend_sched_new({backend_gpu, backend_gpu2, backend_cpu}, NULL, num_backends, GGML_DEFAULT_GRAPH_SIZE, false, true);